CHARACTERIZATION OF NANNOCHLOROPSIS OCEANICA CCMP1779 GROWN IN
LIGHT:DARK CYCLES INFORMS GENETIC ENGINEERING TOOL DEVELOPMENT
By
Eric Poliner

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Cell and Molecular Biology – Doctor of Philosophy
2017

ABSTRACT
CHARACTERIZATION OF NANNOCHLOROPSIS OCEANICA CCMP1779 GROWN IN
LIGHT:DARK CYCLES INFORMS GENETIC ENGINEERING TOOL DEVELOPMENT
By
Eric Poliner
Nannochloropsis is a genus of fast-growing microalgae that have a high lipid content.
Nannochloropsis species have a high triacylglycerol (TAG) content and contain a large amount
of the omega-3 long-chain polyunsaturated fatty acid, eicosapentaenoic acid (EPA). There is a
growing interest in Nannochloropsis species as models for the study of microalga lipid
metabolism and as a platform for synthetic biology. Genome sequences are available for several
species, and genetic engineering techniques are being introduced. In this study, I developed a
new generation of transgenic vectors for gene stacking and marker-free gene disruption in
Nannochloropsis oceanica CCMP1779. These tools enable gene specific studies and were
applied to investigate a lipid biosynthetic pathway that is co-expressed under different light
conditions.
As for all photosynthetic organisms, light plays an important role in driving metabolism
and regulation by photosensing in Nannochloropsis species. Each day photosynthetic organisms
must maximize their energy capture during the day and be able to sustain themselves during the
night. Nannochloropsis cultures synchronize cell division during a light:dark cycle, with cell
division occurring at night, along with the usage of stored metabolites that are accumulated
during the day. RNA-sequencing measures global transcript abundance, that ultimately might
lead to changes in enzymatic activity, metabolism and physiology. I investigated the role of
transcriptional regulation on metabolite levels and cell physiology using RNA-sequencing. In
the study I found coordination between cell growth, triacylglycerol and hexose content, and

transcript abundance of the genes in relevant pathways. Briefly anabolic processes were phased
to the light period and catabolic processes phased to the dark period. Furthermore, promoters for
transgenic expression were chosen based on transcriptomic measurements gathered in this study.
Eicosapentaenoic acid is a high-value fatty acid that is a necessary nutrient for humans,
with a biosynthetic pathway consisting of 5 fatty acids desaturases (FADs) and a fatty acid
elongase (FAE). Interestingly, the genes of this biosynthetic pathway were strongly co-expressed
during light:dark cycles, and I set out to characterize the pathway. Expression of isolated cDNAs
in S. cerevisiae resulted in the production of the expected long-chain polyunsaturated fatty acids
(LC-PUFAs), and ultimately EPA when all 4 LC-PUFA FADs and an FAE were co-expressed.
Selected FADs were overexpressed in N. oceanica and resulted in increased LC-PUFA and EPA
content.
CRISPR/Cas9 is a potent tool for gene editing. The RNA-guided nuclease, Cas9, was
tested as a fusion with green fluorescent protein (GFP) and NanoLuciferase (Nlux) reporters, and
the Cas9-Nlux fusion was readily detectable for efficient screening of transformants for
recombinant protein production. Single-guide RNAs (sgRNAs) when fused to 5’ and 3’ selfcleaving ribozymes efficiently targeted genes. The two components of the system were
expressed from a bidirectional promoter. N. oceanica is capable of expressing transgenes from
circular episomal DNA, and an episomal CRISPR construct was generated. The nitrate reductase
gene was targeted and the mutants generated with frame-shifts in the coding sequence were
unable to grow on nitrate. When antibiotic selection was removed, the episome was lost, and a
mutant line that was “cured” of the episome was isolated. These tools are being utilized for gene
specific studies in N. oceanica.

TABLE OF CONTENTS

LIST OF TABLES ........................................................................................................................ vii
LIST OF FIGURES ..................................................................................................................... viii
KEY TO ABBREVIATIONS ........................................................................................................ xi
Chapter 1. Introduction ................................................................................................................... 1
Taxomony and Evolution of the Nannochloropsis genus ....................................................... 3
Genomes and transcriptomes across the Nannochloropsis genus........................................... 5
Light regulation and photosynthesis ....................................................................................... 6
Lipid and carbon metabolism.................................................................................................. 8
Transcriptional Regulation.................................................................................................... 10
Transformation and gene expression platforms .................................................................... 12
Antibiotic resistance marker genes ....................................................................................... 13
Transgenic expression in Nannochloropsis species .............................................................. 14
Generation of targeted gene disruption and transcriptional repression ................................ 16
Altering metabolism in Nannochloropsis species by protein engineering ........................... 18
Altering metabolism in Nannochloropsis species by regulatory engineering ...................... 19
Additional challenges for the development of improved Nannochloropsis strains .............. 20
Call for an open alga ............................................................................................................. 21
APPENDIX ............................................................................................................................... 23
Chapter 2. Transcriptional coordination of physiological responses in Nannochloropsis oceanica
CCMP1779 under light:dark cycles .............................................................................................. 33
ABSTRACT.............................................................................................................................. 33
INTRODUCTION .................................................................................................................... 33
RESULTS ................................................................................................................................. 35
N. oceanica CCMP1779 growth and metabolite content under diel conditions ................... 35
Oscillations in global gene expression in N. oceanica under day:night cycles .................... 36
Genes involved in cell division display strong diurnal oscillations in N. oceanica
CCMP1779 ........................................................................................................................... 38
The RNA content of genes involved in carbon assimilation peaks at dawn ......................... 39
Carbohydrate metabolism under light:dark cycles ............................................................... 41
Acetyl-CoA metabolism is temporally and spatially segregated in N. oceanica CCMP1779
............................................................................................................................................... 42
The expression of fatty acid synthesis genes precede lipid accumulation during the day .... 44
Regulation of gene expression related to lipid biosynthesis over the diel cycle. ................. 45
Lipid degradation and the TCA cycle. .................................................................................. 47
Cyclic expression of transcriptional regulators..................................................................... 48
DISCUSSION ........................................................................................................................... 50
EXPERIMENTAL PROCEDURES ......................................................................................... 51
Culture conditions ................................................................................................................. 51
Lipid analyses ....................................................................................................................... 51
Carbohydrate analysis ........................................................................................................... 52
iv

Analysis of gene expression by RNA-Seq ............................................................................ 52
Accession Numbers .............................................................................................................. 53
Analysis of cyclic gene expression ....................................................................................... 54
Analysis of gene expression by RT-qPCR............................................................................ 54
Flow cytometry analysis ....................................................................................................... 55
Microscopic analysis ............................................................................................................. 55
Gene functional annotation ................................................................................................... 56
Protein analysis ..................................................................................................................... 56
APPENDICES .......................................................................................................................... 58
Appendix 2.1. Chapter 2 figures and tables. ......................................................................... 59
Appendix 2.2. Chapter 2 datasets. ........................................................................................ 83
Chapter 3. A toolkit for Nannochloropsis oceanica CCMP1779 enables gene stacking and
genetic engineering of the eicosapentaenoic acid pathway for enhanced long-chain
polyunsaturated fatty acid production........................................................................................... 84
ABSTRACT.............................................................................................................................. 84
INTRODUCTION .................................................................................................................... 84
RESULTS ................................................................................................................................. 87
Genes encoding enzymes of the eicosapentaenoic acid biosynthesis pathway are coexpressed ............................................................................................................................... 87
N. oceanica CCMP1779 FADs catalyze the production of LC-PUFAs in yeast.................. 89
A vector toolkit for multigene expression in Nannochloropsis species. .............................. 90
Overexpression of EPA biosynthesis genes in N. oceanica CCMP1779 ............................. 92
Increase in LC-PUFA content in FAD overexpressing lines ................................................ 94
DISCUSSION ........................................................................................................................... 94
Expanding transgenic techniques in N. oceanica ................................................................. 94
Characterization of the EPA biosynthetic pathway .............................................................. 96
Metabolic engineering for increased EPA content in N. oceanica ....................................... 97
EXPERIMENTAL PROCEDURES ....................................................................................... 100
Growth conditions ............................................................................................................... 100
Cloning of N. oceanica CCMP1779 EPA pathway genes .................................................. 100
Yeast transformation and expression .................................................................................. 100
Protein sequence analysis ................................................................................................... 101
Identification of bidirectional promoters in N. oceanica CCMP1779 ................................ 102
Construction of Nannochloropsis expression vectors......................................................... 102
Nannochloropsis transformation......................................................................................... 104
Nannochloropsis luminescence assays ............................................................................... 104
Expression analysis in N. oceanica CCMP1779................................................................. 105
Fatty acid methyl ester extractions in N. oceanica ............................................................. 105
Confocal microscopy .......................................................................................................... 106
APPENDICES ........................................................................................................................ 107
Appendix 3.1. Chapter 3 figures and tables. ....................................................................... 108
Appendix 3.2. Chapter 3 datasets. ...................................................................................... 136
Chapter 4. Non-transgenic marker-free gene disruption by an episomal CRISPR system in the
oleaginous microalga, Nannochloropsis oceanica CCMP1779 ................................................. 137
ABSTRACT............................................................................................................................ 137
v

INTRODUCTION .................................................................................................................. 137
RESULTS ............................................................................................................................... 139
Development of a CRISPR system for N. oceanica ........................................................... 139
Use of an episomal CRISPR system to disrupt the nitrate reductase gene ......................... 140
Removal of the CRISPR episomes from N. oceanica mutants ........................................... 142
DISCUSSION ......................................................................................................................... 143
EXPERIMENTAL PROCEDURES ....................................................................................... 145
Strains and growth conditions............................................................................................. 145
CRISPR plasmid construction ............................................................................................ 146
N. oceanica transformation ................................................................................................. 148
NanoLuciferase luminescence assays ................................................................................. 149
N. oceanica colony PCR ..................................................................................................... 149
Episomal DNA isolation from N. oceanica ........................................................................ 149
Episome rescue ................................................................................................................... 150
Episome curing ................................................................................................................... 150
Immunoblotting................................................................................................................... 151
Confocal microscopy .......................................................................................................... 151
Southern-blot analysis ......................................................................................................... 152
APPENDIX ............................................................................................................................. 153
Chapter 5. Concluding Remarks ................................................................................................. 168
Characterization of growth in light:dark cycles .................................................................. 168
Development of transgenic tools ........................................................................................ 169
APPENDIX ............................................................................................................................. 173
REFERENCES ........................................................................................................................... 176

vi

LIST OF TABLES
Table 1.1. Publicly available whole-genome datasets produced in Nannochloropsis species. .... 27
Table 1.2. Genetic tools developed for the Nannochloropsis genus............................................. 28
Table 1.3. Effective antibiotic selection agents and resistance genes for N. oceanica ................. 32
Table 2.1. Prediction of cyclic gene expression. .......................................................................... 82
Table 2.2. Primers used for RT-qPCR in Chapter 2. .................................................................... 82
Table 3.1. Fatty acid mole percentage of S. cerevisiae strains. .................................................. 121
Table 3.2. Codon usage of N. oceanica CCMP1779. ................................................................. 124
Table 3.3. Bidirectional gene pairs. ............................................................................................ 126
Table 3.4. Fatty acid mole percent of N. oceanica CCMP1779 strains. ..................................... 127
Table 3.5. Cellular fatty acid content of N. oceanica CCMP1779 strains. ................................. 128
Table 3.6. Primers used in Chapter 3. ......................................................................................... 129
Table 3.7. Constructs generated in Chapter 3. ............................................................................ 134
Table 4.1. Materials generated in Chapter 4. .............................................................................. 164
Table 4.2. Primers used in Chapter 4. ......................................................................................... 165

vii

LIST OF FIGURES
Figure 1.1 The Nannochloropsis genus as a chassis organism. .................................................... 24
Figure 1.2 Multi-gene overexpression (gene stacking) strategies in N. oceanica. ....................... 25
Figure 1.3 Gene repression and inactivation techniques in the Nannochloropsis genus. ............. 26
Figure 2.1. N. oceanica CCMP1779 cell growth under diel cycles. ............................................. 59
Figure 2.2. Metabolite content under diel cycles. ......................................................................... 60
Figure 2.3. Confirmation of RNA-Seq measurements by reverse transcription quantitative PCR.
....................................................................................................................................................... 61
Figure 2.4. Gene expression phase and GO terms enriched in cyclically expressed genes. ......... 62
Figure 2.5. Phylogenetic analysis of N. oceanica CCMP1779 CDK-related proteins. ................ 63
Figure 2.6. Phylogenetic analysis of N. oceanica CCMP1779 cyclin related proteins. ............... 64
Figure 2.7. Cell cycle progression in light:dark cycles................................................................. 65
Figure 2.8. Time lapse images of a N. oceanica CCMP1779 cell undergoing division into four
daughter cells. ............................................................................................................................... 66
Figure 2.9. Transcription regulation of genes involved in central carbon metabolism in N.
oceanica CCMP1779 under diel conditions. ................................................................................ 67
Figure 2.10. Phylogenetic analysis of N. oceanica CCMP1779 SLC4 related proteins. .............. 69
Figure 2.11. Phylogenetic analysis of N. oceanica CCMP1779 malic enzyme related proteins. . 70
Figure 2.12. Heatmap displaying relative expression levels of putative glycosyl transferases and
glycosyl hydrolases encoding genes. ............................................................................................ 71
Figure 2.13. Phylogenetic analysis of the N. oceanica CCMP1779 β-1,3-glucan synthase related
protein. .......................................................................................................................................... 72
Figure 2.14. Expression of genes potentially involved in the mannitol cycle. ............................. 73
Figure 2.15. Gene expression of genes involved in lipid biosynthesis under light:dark cycles. .. 74
Figure 2.16. Phylogenetic analysis of the N. oceanica CCMP1779 type I FAS-like genes. ........ 75
Figure 2.17. LDSP expression under light:dark cycles................................................................. 76
Figure 2.18. Gene expression of genes involved in fatty acid degradation under light:dark cycles.
....................................................................................................................................................... 77
viii

Figure 2.19. Heatmap displaying relative expression levels of genes involved in the lipid
degradation. ................................................................................................................................... 78
Figure 2.20. Cyclic expression of transcription regulators. .......................................................... 79
Figure 2.21. Heatmap displaying relative expression levels of genes involved in chromatin
modification. ................................................................................................................................. 80
Figure 2.22. The relationship between the cyclic score derived from the DFT and negative log
transformed p-value from COSPOT. ............................................................................................ 81
Figure 3.1. EPA biosynthetic pathway identification in N. oceanica CCMP1779. .................... 108
Figure 3.2. Computational annotation of protein sequences of isolated EPA biosynthetic genes.
..................................................................................................................................................... 109
Figure 3.3. Galactose inducible expression of the EPA pathway genes in S. cerevisiae............ 110
Figure 3.4. Functional characterization of EPA biosynthesis enzymes in S. cerevisae.............. 111
Figure 3.5. Assembly of native promoters, terminators, and a range of reporters to generate a
transgenic expression toolkit for N. oceanica CCMP1779......................................................... 112
Figure 3.6. Modification of the Ribi promoter to remove restriction sites. ................................ 113
Figure 3.7. Assessment N. oceanica promoters’ strength using NanoLuciferase. ..................... 114
Figure 3.8. Optimization of 2A peptides ribosomal skipping efficiency in N. oceanica
CCMP1779. ................................................................................................................................ 115
Figure 3.9. N-terminal extended 2A peptide screening for increased ribosomal skipping
efficiency..................................................................................................................................... 116
Figure 3.10. Vectors for FAD overproduction in N. oceanica CCMP1779. .............................. 117
Figure 3.11. CLSM analysis of N. oceanica CCMP1779 wild type, and empty vector and CFPdesaturase overexpressing (DOX) transformants. ...................................................................... 118
Figure 3.12. Desaturase overproduction alters the fatty acid profile of N. oceanica CCMP1779.
..................................................................................................................................................... 119
Figure 3.13. Growth rates of N. oceanica CCMP1779 DOX lines during exponential growth. 120
Figure 4.1. A one-vector CRISPR system for gene disruption in N. oceanica........................... 154
Figure 4.2. Confocal microscopy of Cas9-GFP expressing N. oceanica with the nucleus stained
by DAPI. ..................................................................................................................................... 155
Figure 4.3. Cloning strategies for the generation of a ribozyme-sgRNA. .................................. 156
ix

Figure 4.4. Development of an episomal CRISPR system. ........................................................ 157
Figure 4.5. Identification of NR knockout mutants by CRISPR/Cas9. ...................................... 158
Figure 4.6. Verification of rescued episomes. ............................................................................ 159
Figure 4.7. Southern blot analysis of the episomal and integrated empty-vector CRISPR mutants.
..................................................................................................................................................... 160
Figure 4.8. Curing episomes from NR-KO lines. ....................................................................... 161
Figure 4.9. Generation of marker-free non-transgenic mutants by episomal removal (curing). 162
Figure 4.10. A one-vector CRISPR system for scarless cloning of guide sequences. ................ 163

x

KEY TO ABBREVIATIONS
TAG - triacylglycerol
LC-PUFA - long-chain polyunsaturated fatty acids
EPA - eicosapentaenoic acid
RNA-seq - RNA-sequencing
CHIP-Seq - chromatin immunoprecipitation DNA sequencing
GC - guanine cytosine nucleotides
N - nitrogen
bZIP - basic leucine zipper
VCP - violaxanthin chlorophyll binding protein
Ribi - ribosomal subunit bidirectional promoter
UEP - ubiquitin extension protein
β-tub - β-tubulin
EF - elongation factor
lux - luciferase
bHLH - basic helix loop helix
WRI1 - WRINKLED1 transcription factor
UTR - untranslated region
DGDG - digalactosyldiacylglycerol
DGTS - diacylglyceryl-NN-trimethylhomoserine
DAG - diacylglycerol phosphate
MGDG - monogalactosyldiacylglycerol
SQDG - sulfoquinovsyldiacylglycerol

xi

PC - phosphatidylcholine
PE - phosphatylethanolamine
ACP - acyl-carrier protein
ENR - enoyl-ACP reductase
KAS - ketoacyl-ACP synthase
KAR - ketoacyl-ACP reductase
TE - acyl-ACP thioesterase
LC-FACs - long-chain fatty acyl-CoA synthetase
PAP - phosphatidic acid phosphatase
LPAT - lysophosphatidyl acyltransferase
PDC - pyruvate dehydrogenase complex
PDCK - pyruvate dehydrogenase complex kinase
PDAT - phospholipidiacylglycerol acyltransferases
DGAT - diacylglycerol acyltransferase type I
DGTT - diacylglycerol acyltransferase type II
FAS - fatty acid synthase
DGDS - digalactosyl-1,2-sn-diacyl-glycerol synthase
ELO - elongase
ENO - enolase
GPAT - glycerol-3-phosphate acyltransferase
LPAAT - lysophosphatidic acid acyltransferase
GT - glycosyl transferases
GH - glycosyl hydrolases

xii

M2HD - mannitol 2-dehydrogenase
MDH - malate dehydrogenase
ME - malic enzyme
MGDGS - monogalactosyl-1,2-sn-diacylglycerol synthase
MPDH - mannitol-1-phosphate dehydrogenase
MPP - manitol-1-phosphatase
PC - phosphoenolpyruvate carboxylase
PCK - pyruvate carboxykinase
PDH - pyruvate dehydrogenase
PFK - phosphofructokinase
PGI - phosphoglucoisomerase
PGK - phosphoglycerate kinase
PGLM - phosphoglycerase mutase
PGM - phosphoglucomutase
PK - pyruvate kinase
PP - phosphatidate phosphatase
PPDK - pyruvate phosphate dikinase
PYC - pyruvate carboxylase
SLS - sulfolipid synthase
TPI - triose-phosphase isomerase
TPT - triosephosphate transporter
UGPase - UDP-glucose pyrophosphylase
TFA - total fatty acids

xiii

NR - nitrate reductase
HR - homologous recombination
FP - Fluorescent Protein
Nlux - NanoLuciferase
NLS - nuclear localization signal
sgRNA - single-guide RNA
CRISPR - Clustered Regularly Interspaced Short Palindromic Repeats
KO - knockout
HDV - hepatitis delta virus ribozyme
HH - hammerhead ribozyme
CEN/ARS – Saccharomyces cerevisiae centromere and autonomous replication sequence fusion
FP - fluorescent protein
CP - chromoprotein
BRET - bioluminescence resonance energy transfer
X-Gluc - 5-bromo-4-chloro-3-indolyl-beta-D-glucuronic acid
kb - kilobase
TF - transcription factor
TR - transcription regulator
TFBS - transcription factor binding site
PWM - position weighted matrix
TPR - third party-repository
PS - photosystem
LHC - light harvesting complex

xiv

ACC - acetyl-coA carboxylase
ACL - ATP citrate lyase
ACS - acetyl-coA synthetase
ADH - aldehyde dehydrogenase
ALD - aldolase
CA - carbonic anhydrase
CS - cellulose synthase
HS - heat shock protein
DES - desaturase
FbP - fructose 1,6-bisphosphase
FK - fructokinase GAPDH - glyceraldehyde 3-phosphase dehydrogenase
GBS - β-1,3-glucan synthase
16:0 - 16:0 fatty acid
2PGA - 2-phosphoglycerate
3PGA - 3-phosphoglycerate
6PG - 6-phosphogluconate
Ac-CoA - acetyl-CoA
Ace - acetate
Citr - citrate
DHAP - dihydroxyacetone phosphate
F1-6P - fructose 1,6-bisphosphate
F6P - fructose 6-phosphate

xv

FA - fatty acid
Fru - fructose
G1-3-P - glycerate 1,3-bisphosphate
G1P - glucose 1-phosphate
G3P - glycerate 3-phosphate
G6P - glucose 6-phosphate
Glu - glucose
M1P - mannitol 1-phosphate
Mal - malate
Mnl - mannitol
OAA - oxaloacetate
PEP - phosphoenolpyruvate
Pyr - pyruvate
UDPG - UDP-glucose
Mito - mitochondria
FAD - fatty acid desaturase
FAE - fatty acid elongase
aa - amino acid
DOX - desaturase overexpression line
NR-KO - nitrate redctase knockout line
iEV - integrate empty-vector CRISPR line
WT - wild-type
construct - constructed DNA

xvi

PBS - phosphate buffered saline solution
Δ - delta
ω - omega
PCR - polymerase chain reaction
DAPI - 4’-6-Diamidino-2-Phenylindole
CLSM - confocal laser scanning microscopy
LDSP - lipid droplet surface protein

xvii

Chapter 1. Introduction
Algae are highly efficient at turning solar energy into biomass, and are sources of unique
bioproducts, such as omega-3 fatty acids (1, 2), carotenoids (3), and interesting polysaccharides,
such as agarose, alginate, and β-1,3-glucans (3-5). Several groups have screened algae for
productivity and production of valuable compounds (4, 6, 7). Nannochloropsis was identified as
a genus with rapid growth, and high lipid content, including triacylglycerol (TAG) (6) and the
omega-3 (ω3) long-chain polyunsaturated fatty acid, eicosapentaenoic acid (EPA) (1). Under
nutrient-replete conditions Nannochloropsis species have a lipid content of ~25-30% of dryweight (6, 8-10). Stresses, such as high-light or nutrient deprivation, in particular nitrogen (N)
deprivation, causes microalgae to pause growth and accumulate triacylglycerol or other storage
compounds, and drives Nannochloropsis species to accumulate high quantities of TAG, up to
60% of biomass (6, 8-11). In recent years genomes for several Nannochloropsis species have
become available (Table 1.1) (11-13) and molecular tools have been developed (Table 1.2) (1417), making this genus excellent microalgal models for comparative genomics (18, 19).
Synthetic biology is an emerging field based on rationally designing biological systems
(20). To develop systems that behave as desired, an approach described as design, build, test, is
used to iteratively test refinements and determine how elements of the system influence the
outcome (21). The design phase is often based on information drawn from genome-wide data
and databases of related systems. Organisms with high-quality genome-wide data and advanced
genetic engineering tools that can be redesigned are known as chassis organisms (Figure 1.1).
Metabolic maps are built using genome assemblies, functional annotation, and databases of
known enzymatic pathways. Regulatory networks are coming into focus through integrating
RNA-seq, chromatin immunoprecipitation DNA sequencing (CHIP-Seq), and databases of

1

transcription factors and their target DNA motifs. In order to build or refine biosynthetic
pathways or develop chassis organisms, several molecular tools are needed to modify the
genome of an organism. While molecular tools, such as mutant libraries, transgenic
overexpression, and reporter protein fusions, are instrumental in gaining a molecular
understanding of biological processes, they are by themselves insufficient to create optimized
biological systems. Redesigned algae will require a new generation of tools that enable precise
and marker-free gene disruption mutants, and high-capacity gene stacking systems that can
robustly and predictably express multiple genes. Finally, in order to test the synthesized system,
highly facile methods to select or screen for the desired modifications as quickly as possible post
transformation are needed.
The Nannochloropsis genus is also an emerging algal model for genetic engineering of
lipid accumulation (17, 19, 22). Several Nannochloropsis species seem particularly amenable to
transgenic expression, with a moderate GC (guanine cytosine) content and simple gene structure
facilitating genetic manipulation (11, 18, 23). Several endogenous promoters and terminators are
in use, including bidirectional promoters that are helpful in stacking transgenes, i.e. expressing
multiple genes (14, 15, 23-25). Methods exist for targeted DNA insertion by homologous
recombination into the genome (14, 25, 26). We and others developed CRISPR (Clustered
Regularly Interspaced Short Palindromic Repeats) based methods, making targeted gene
disruption and editing possible (17, 27). Genetic engineering toolkits are becoming publicly
available and should accelerate development of Nannochloropsis species as chassis organisms
(Figure 1.1).
In order to develop the knowledge and tools to make Nannochloropsis oceanica
CCMP1779 into a chassis organism I investigated the coordination between cell physiology,

2

metabolites, and the transcriptome during growth under light:dark cycles in Chapter 2. Based on
this study I identified the EPA biosynthetic pathway as being co-expressed during light:dark
cycles. In Chapter 3, I describe the isolation and characterization of the constituent genes of this
pathway, the development of molecular tools for gene overexpression and gene stacking, and
subsequent manipulation of the EPA pathway in N. oceanica. My development of a gene
disruption technique based on an episomal CRISPR/Cas9 system, that can make non-transgenic
gene disruption (knockout) mutants, is detailed in Chapter 4. The transcriptomic data gathered
and genetic tools developed make N. oceanica gene-specific studies feasible and form the basis
to develop N. oceanica as a chassis strain.

Taxomony and Evolution of the Nannochloropsis genus
Nannochloropsis is a genus in the heterokont phylum. Photosynthetic heterokonts are secondary
endosymbionts originating from an unicellular heterotrophic eukaryotic cell that engulfed a red
alga, which, over time, became a plastid. The evolutionary relationships of organisms in this
clade are complex and still not well defined. The red-algal type plastid shows several signatures
of its origin distinct from green lineage plastids (28-30). Brown algae and diatoms are also algae
of the heterokont lineage that share 57% and 51% of genes with N. gaditana CCMP526 genome,
respectively (13).
The Nannochloropsis genus seems to possess a number of genes derived from
endosymbiotic gene transfer, particularly in lipid biosynthetic and carbohydrate degradation
pathways, e.g. glycosyl hydrolases (18). The diverse genetic background of the Nannochloropsis
genus may have contributed to its oleaginousness, with a particularly large set of lipid
biosynthetic genes. For example, Nannochloropsis oceanica possess 11 type-2 diacylglycerol

3

acyltransferases (DGATs) referred to also as DGTTs (11, 18, 31, 32), and a high copy number of
other predicted lipid biosynthetic genes such as: enoyl-ACP reductase (ENR), ketoacyl-ACP
synthase (KAS), ketoacyl-ACP reductase (KAR), acyl-ACP thioesterase (TE), long-chain fatty
acyl-CoA synthetase (LC-FACS), phosphatidic acid phosphatase (PAP), and lysophosphatidyl
acyltransferase (LPAT) (18). The evolutionary origins of these genes are still being investigated
and it is hypothesized that the ancestral heterotroph, red alga, and horizontal gene transfer
contributed to the present genome (18).
The secondary endosymbiosis event also led to interesting cellular structure
characteristics, such as four membranes surrounding the plastid, complicating intracellular
trafficking (30, 33, 34). Trafficking of nuclear encoded proteins into the plastid has been
extensively studied in diatoms (35), and has led to the protein location prediction program
HECTAR (36). While in several Nannochloropsis species there are some examples of protein
localization by fluorescent protein (FP) fusions, including to the plastid (24), endoplasmic
reticulum (ER) (15), mitochondria (37) and lipid droplets (25, 31), there have not been
investigations into the signals and mechanisms of protein localization. The transport of
metabolites across subcellular compartments also has not been studied in the Nannochloropsis
genus, although it represents a plausible target for optimizing metabolite production (38).
Genetic diversity has also arisen frequently by horizontal gene transfer during algae
evolution (39, 40), and enables adaption to unique environments or metabolic niches (41).
Several lipid biosynthetic genes appear to be related to bacterial orthologs and likely were
acquired by horizontal gene transfer, including KAR, PAP, ENR, KAS, TE, and LC-FACS genes
(18). An operon encoding proteins specialized in hydrogen generation possibly derived from
bacteria has also been identified in N. oceanica (11). Transkingdom gene transfer by bacterial

4

conjugation to diatoms and the capacity for heterokonts to maintain episomal DNA indicates a
possible route of gene acquisition (40, 42). This evolutionary diversity of the Nannochloropsis
genus and the genetic plasticity of the heterokonts may lead to an interesting model for symbiotic
evolution and a chassis organism that can be robustly adapted for genetic engineering.

Genomes and transcriptomes across the Nannochloropsis genus
A complete genome sequence forms the foundation for gene-specific studies, and is a
prerequisite for the drafting of metabolic and regulatory maps. Several genome assemblies have
been generated for different species of Nannochloropsis, including multiple strains within a
species, such as, N. oceanica CCMP1779 (11) and IMET1 (18), N. gaditana CCMP526 (13, 27)
and B-31 (12), N. salina CCMP537, N. oculata CCMP525 (18), and N. granulata CCMP529
(Table 1.1) (18). The genomes of the examined Nannochloropsis species are approximately 30
megabases, and contain 7-11,000 genes each (11, 13, 18). The N. gaditana B-31 genome is
estimated to be distributed over 30 chromosomes (12), and the presumed N. oceanica IMET1
chromosomes separated by pulse-field gel electrophoresis as 22 individual genome fragments
(18).
The plastid and mitochondrial genomes of representatives from five Nannochloropsis
species were used to produce a pangenome of each organelle (28). The N. oceanica IMET1
plastid genome is 117,548 bp and contains 160 genes consisting of 126 protein-coding genes,
and 34 RNA genes, and the mitochondrial genome is 38,057 bp and contains 63 genes consisting
of 35 protein-coding genes and 28 RNA genes (28). The Nannochloropsis genus plastid
pangenome contains signatures of a red algal origin, including red algal-type Rubisco and
Rubisco activase genes (43).

5

Extensive transcriptome data based on RNA-sequencing of cultures grown under
different conditions reveal characteristic transcriptional changes, providing a whole-genome
view of possible adjustments to maintain homeostasis. Different examined conditions included
phosphorus (44) and N deprivation (11, 12, 22), alternating light:dark cycles (45)(Chapter 2),
varying light intensities (46), and different growth phases of batch cultures (13), in various
Nannochloropsis species (Table 1.1). These datasets suggest that different aspects of metabolism
and other cellular processes, such as the cell cycle are coordinated on a transcriptional level in
response to environmental conditions. For example, N deprivation, which generally leads to a
transition from the normal cell division cycle to quiescence, also causes transcriptional
downregulation of photosynthesis and protein production, while lipid biosynthesis is upregulated
as observed in Chlamydomonas (47, 48), and Nannochloropsis species (12, 13, 22) . In Chapter
2, I show that when N. oceanica is grown in a light:dark cycle, there is phased expression of
genes at different times of day, including those involved in cell division at night, and anabolic
processes during the day (45). A majority (64%) of the DNA-binding transcription factors and
56% of other transcriptional regulators, have phased expression during light:dark cycles. This
genome-wide dataset was an asset for further studies such as the identification of conditionspecific promoters. Links to currently published genome-wide datasets are listed in Table 1.1.

Light regulation and photosynthesis
In heterokont algae, light, either by capture and conversion of solar energy during photosynthesis
or by perception through photosensory regulatory proteins, affects metabolite levels (pigments,
lipids, and carbohydrates) (45, 49), coordinates the cell cycle (45, 49-52), and may entrain a
circadian clock (53). In Nannochloropsis species, high-intensity light results in accumulation of

6

TAG and a decrease in plastid size, thus maximizing energy conversion while avoiding
photodamage (10, 46, 54). The day:night cycle influences most organisms to coordinate behavior
and/or metabolism with either phase (45, 49, 52). The transitory storage compounds used by N.
oceanica during a light:dark cycle are unknown, therefore I measured TAG and carbohydrates
(in the form of hexoses) content throughout a light:dark cycle (Chapter 2). Nannochloropsis
species accumulate TAG (55) and carbohydrates during the day, which are both metabolized
during the night, in accordance with transcriptional changes in genes encoding enzymes of the
respective biosynthesis and utilization pathways (45).
Nannochloropsis species are studied as a model for photosynthesis in secondary
endosymbionts. The Nannochloropsis genus is notable for only possessing chlorophyll a, the
unusual carotenoids violaxanthin and vaucheriaxanthin ester, and an alternative xanthophyll
cycle utilizing violaxanthin, antheraxanthin, and zeaxanthin (56-58). Red algae and their derived
endosymbionts contain LHCr type antenna proteins that link core complex pigment and protein
components, and participate in energy transfer and photoprotection (56, 58, 59). Characterization
of the photosystem II (PSII) of N. gaditana identified the light harvesting complex proteins of
the classes LHCx, LHCf, Red-CLH-like LHC, and LHCr, that are characteristic of the red algaetype plastid (59). Characterization of the N. gaditana photosystem I (PSI) discovered the
absence of several subunits (PsaH, PsaK, PsaG) that are typically present in plants, and identified
the light harvesting complex proteins of the classes LHCr, LHCf, and LHCx associated with PSI
(58).

7

Lipid and carbon metabolism
Lipid biosynthesis is the best characterized metabolic pathway in Nannochloropsis species, in
particular the production of TAG and EPA. The Nannochloropsis genus is hypothesized to
possess a cytosolic type-I fatty acid synthase (FAS) in addition to the plastid type-II FAS
complex, but further studies to corroborate this hypothesis are needed (11, 45, 46). The TAG
biosynthetic pathway involves the transfer of acyl chains to a glycerol backbone by the
sequential action of glycerolphosphate acyltransferase (GPAT), LPAT, and DGAT, in addition
phospholipidiacylglycerol acyltransferases (PDATs) have also been identified in
Nannochloropsis species (11). The four LPATs of N. oceanica have been investigated for their
roles in membrane lipids and TAG biosynthesis with LPAT1 and LPAT4 having primary roles in
each process respectively, and LPAT2 and LPAT3 possibly playing roles in both processes (25).
Of the 13 DGATs encoding genes, 6 are upregulated during N deprivation, a condition that also
favors TAG accumulation (31). We identified a N. oceanica DGAT (DGTT5) that is able to
increase TAG production in many different hosts (31).
The Nannochloropsis genus contains the omega-3 fatty acid EPA in its membrane lipids
(15-30% total fatty acids - TFA) (1, 11, 60, 61). I reconstructed the N. oceanica EPA
biosynthetic pathway in S. cerevisiae by introducing four LC-PUFA fatty acid desaturases
(FADs) and a fatty acid elongase (FAE), resulting in the production of EPA (0.1% TFA) (15)
(Chapter 3). FADs are named for the double bond introduced, a specific number of carbons from
either the carboxyl (Δ, delta-) or methyl (ω, omega-) end of a fatty acid chain. Thus, omega-3
and delta-6 FADS act on the third carbon from the methyl end and the sixth carbon from the
carboxyl end, respectively. The FADs of N. oceanica resemble those of other heterokont algae
with their histidine box motifs for coordinating a diiron center, and in two cases (delta-5 and

8

delta-6) contain a cytochrome b domain (15). Eleven fatty acid elongases have been identified in
N. oceanica (11) and delta-6 and palmitic fatty acid specific elongases from N. oceanica and N.
gaditana, respectvely, have been characterized in some detail. The palmitic acid elongase
controls flux into the EPA pathway by conversion of 16:0 to 18:0 (26), while the delta-6
elongase converts 18:3 to 20:3, two intermediates with low in vivo abundance (15). EPA is likely
produced in the ER but ultimately accumulates on diacylglyceryl-trimethylhomoserine (DGTS)
and monogactosyl diacylglycerol (MGDG), the latter of which is assembled in the plastid (Figure
1.1). Thus it has been proposed that EPA is imported into the plastid by a DGTS mediated
transport mechanism (61).
Carbohydrates play structural, storage, and osmoprotectant roles in Nannochloropsis
species. In N. oceanica glucose is the predominant hexose in the total complex carbohydrate
fraction, which contains smaller amounts of mannose, and trace amounts of rhamnose, fucose,
arabinose, xylose, and galactose (11). Marine Nannochloropsis species reduce their level of the
sugar alcohol mannitol and the disaccharide trehalose content in response to low-salt stress
consistent with a role of these carbohydrates in osmoprotection (62). Heterokont algae lack
starch but produce β-1,3 linked polysaccharides (chrysolamarinin), by the activity of a β-1,3glucan synthase which ispredicted to be encoded in the genome of Nannochloropsis species (11,
12). Approximately 20% of alcohol insoluble polysaccharides are in this form in N. oceanica
(11). Chrysolamarinin is also a storage compound in diatoms (49, 63), and has been suggested to
have a similar role in Nannochloropsis species (10, 22, 64), but further studies are needed to
confirm this hypothesis. Cellulose is a major polysaccharide in Nannochloropsis species, with
approximately 80% of the of alcohol insoluble polysaccharides in this form in N. oceanica (11).
Cellulose serves as a major component of the cell wall (11, 65, 66), but the cell wall is quite

9

complex in Nannochloropsis species (65). Four putative cellulose synthase-encoding genes have
been identified (65, 66). A large number of carbohydrate-degrading enzymes, 48-49 glycosyl
hydrolases, with very diverse taxonomic relations, are found encoded across the pangenome
(18). The complete repertoire of carbohydrate metabolism in the Nannochloropsis genus has yet
to be fully established.
In order to understand the metabolic networks of Nannochloropsis species, a summary of
possible chemical reactions in the form of a metabolic map has been generated. A mass-balanced
metabolic map for N. salina CCMP537 has been produced by Loira and colleagues taking into
account 9 organelles (as well as the plastid lumen) of the cell (38). The model was validated by
modeling different growth conditions and comparing it to in vivo data. The conditions of N and
phosphate deprivation, were used to maximize lipid production and determine essential nutrients,
respectively. The iNS934 map-based model predicted several genes whose disruption may result
in increased TAG.

Transcriptional Regulation
The dynamic control of metabolism in response to environmental changes and intracellular cues
is multilayered but inevitably involves transcription factors (TF, which possess DNA binding
activity) and transcriptional regulators (TR, regulators of TF activity) that modulate gene
expression. Databases of known TFs and corresponding position-weighted matrices (PWM) (67)
can be used to systematically determine potential interacting TF-DNA sequences. Having a large
number of closely related organisms is a valuable resource for in silico predictions of conserved
regulatory DNA motifs (19). Genome sequencing and cataloging of TFs as a first step has been
undertaken for the Nannochloropsis genus (11, 19). Comparative genomic studies of the

10

heterokont lineage have identified TF signatures based upon organismal lifestyle (autotrophic,
parasitic), multicellularity, or lifecycle stages (68-70). TF prediction of N. oceanica implied the
presence of 115 putative TFs and 109 putative TRs, which combined represent about 2% of the
genome (11). The Nannochloropsis genus has a reduced number of TF and TR families (20-26)
compared to land plants and green algae, possibly due to a simple lifecycle and its unicellularity
(11, 19). Putative TFs of the Myb family (29-35 members), a TF family known to regulate
growth and metabolism in other organisms, are enriched in the Nannochloropsis genus (11, 19).
Several TFs in Nannochloropsis species have been investigated but studies into their targets are
only beginning. Despite the large amounts of predicted TFs and TRs their roles need to be
experimentally corroborated.
Several approaches have been used to identify regulators of lipid biosynthesis in
Nannochloropsis species. Hu and colleagues (19) took advantage of the extensive genome
sequences available to predict conserved transcription factor binding sites (TFBS). They
determined the enrichment of gene ontology (GO) terms associated with each motif, and
enrichment of motifs associated with lipid biosynthetic genes. Using a TF catalogue and RNAseq during N deprivation Hu et al. identified TFs that showed positive or negative co-expression
with lipid biosynthetic genes. Finally, they predicted putative connections between TFs and
motifs in lipid biosynthetic gene promoters based on a TF-PWM database (71). One of these
predicted lipid biosynthesis regulating TFs (bZIP1) was recently investigated (72). In addition,
Ajjawi and colleagues (17) identified 20 TFs possibly involved in TAG accumulation based on
changes in expression under N deprivation, and used CRISPR/Cas9 disruption to assess the
predictions.

11

As a photosynthetic organism, light sensing is likely important for tuning metabolism in
Nannochloropsis species. Aureochromes are heterokont specific photosensitive transcription
activators, with a bZIP DNA binding domain and a photosensing dimerization LOV domain
(11). In diatoms the aureochromes are implicated in regulating several processes, including cell
cycle and light acclimation (50, 73, 74). Cryptochromes are blue light photoreceptors derived
from DNA repair enzymes, which have been characterized in diatoms (75) and found to oscillate
during light:dark cycles in diatoms (52) and N. oceanica (45). Recently, the Chlamydomonas
reinhardtii animal-like cryptochrome was reported to be involved in regulating the cell cycle and
the circadian clock (76, 77). Finally, although phytochromes were thought to be absent in most
heterokonts, they have recently been identified in diatoms (78). N. oceanica possesses three
aureochromes, an animal-like cryptochrome, and lack phytochromes, but these proteins have not
been functionally characterized (11).

Transformation and gene expression platforms
The most widely adapted method for transformation of Nannochloropsis species is by
electroporation (11, 13, 14), but other protocols based on biolistics (79, 80) or agrobacterium
have been developed (81, 82). For insertion of a transgene into the genome by electroporation a
linear piece of DNA is required; a constructed DNA (construct) is therefore digested with
restriction enzymes or PCR-amplified (11, 14, 15, 83). Each transformant is likely to have a
distinct insertion site, and therefore may display different phenotypes due to genome contextspecific regulation of the transgene’s expression or disruption of endogenous genes by transgene
insertion (82).

12

Introduction of circular DNA has so far had mixed success in producing transformants
(11, 14, 83). Synthetic Genomics Inc. has described plasmid/episome maintenance in algae by
use of autonomous replication sequences from a Nannochloropsis (84), and the utilization of an
S. cerevisiae centromere – autonomous replication sequence (CEN/ARS) in pennate and centric
diatoms (40, 42, 85). I developed an episomal expression system for N. oceanica based on the
CEN/ARS region (Chapter 4). In diatoms, episomes are maintained under antibiotic selection but
are gradually lost without selection pressure (40, 42, 85). The transgene expression levels from
episomes are more uniform compared to genome integrated constructs between independent
transformants, likely due to the absence of insertion site-specific effects using this approach (42,
85). The capacity of episomes for maintenance of foreign DNA have been reported to be up to 94
kilobases (kb) in diatoms (42).

Antibiotic resistance marker genes
Several antibiotics are effective depending on the Nannochloropsis strain, including hygromycin,
zeocin, and blastidicin, and genes conferring resistance are used to isolate Nannochloropsis
transformants (11, 13, 14, 17, 25). Zeocin in combination with its respective marker gene is the
most widely used selection in Nannochloropsis species due to its stringency at low
concentrations (Table 1.2). However, it is mutagenic and can lead to secondary mutations (86).
In diatoms, the selection agents nourseothricin and G418 are frequently utilized with their
respective antibiotic resistance genes (42, 63, 87). Mutated endogenous proteins in conjunction
with competitive inhibitors, such as phytoene desaturase and the inhibitor norflurazon can also
be used as a selection marker in some algae (88). I have made a number of vectors containing N.
oceanica-adapted antibiotic selection marker genesthat will be available on Addgene

13

(www.addgene.com)(Table 1.3). When several selection agents and resistance genes are
available,multiple transgenic tools can be used in conjunction in one transgenicline (Figure 1.2a).
However, techniques for generation of transgenic algae without antibiotic resistance markers are
necessary for deployment into open ponds. The removal of an antibiotic resistance marker gene
could be achieved by the use of a recombinase or endogenous homologous recombination (89).
The cotransformation of an episome carrying an antibiotic resistance gene with an insertion
construct without a selection marker may also enable generation of marker-free mutants after
episome loss in the absence of selection pressure.

Transgenic expression in Nannochloropsis species
A fundamental technique for genetic engineering and synthetic biology is the overexpression of
target genes by increasing transcriptional and/or translational efficiency. Most often, strong
promoters that mediate high transcription rates are utilized to express heterologous or
endogenous genes at elevated levels. Several endogenous promoters from a variety of
Nannochloropsis species have been isolated and applied to transgenic expression (Table 1.2),
including those driving the genes encoding ubiquitin extension protein (UEP)(13, 26, 79, 90), βtubulin (β-tub)(13, 27, 37, 79, 83), lipid droplet surface protein (LDSP)(11, 15, 25, 91), and
elongation factor (EF)(15, 31). Several bidirectional promoters have also been utilized for
transgenic expression, including those driving the expression of the genes encoding violaxanthin
chlorophyll binding proteins (VCP)(14, 24, 37) or ribosomal subunits (Ribi) (Figure 1.2b) (15).
To enhance translational efficiency of transgenes, a 5’ UTR can include a consensus Kozak
sequence (92) or leader enhancing sequence (93-95). Chapter 3 details the identification of the
EF and Ribi promoters (15).

14

Reporter genes are useful for evaluating transgenic strategies and understanding
gene/promoter function. In several Nannochloropsis species, members of the classes of the
fluorescent- (FP), luminescent- (lux), and chromoproteins (CP) have been used (Table 1.2).
Green fluorescent protein (GFP) is the most widely reported fluorescent protein and has been
utilized for subcellular localization of fusion proteins throughout Nannochloropsis cells (24, 25,
37). Other fluorescent proteins such as a red fluorescent protein (RFP, sfCherry) (79), yellow FP
(YFP, Venus variant) (25, 31, 96), and cyan FP (CFP, Cerulean variant)(15) have been employed
in different Nannochloropsis species (Chapter 3 and Chapter 4). Luciferases have the advantage
of a high signal to noise ratio, and specific substrates allow their use in combination. I developed
codon-optimized firefly luciferase (Flux) and the ultra-bright NanoLuciferase (Nlux) for in-vivo
assays in N. oceanica (Chapter 3 and Chapter 4)(15). The ultra-bright Nlux allows detection of
very low protein quantities and is an effective photon donor for bioluminescence resonance
energy transfer (BRET) (97, 98). Chromoproteins are colored and do not need a substrate, while
the β-Glucuronidase (GUS) reporter is an enzyme that produces a blue stain after conversion of
5-bromo-4-chloro-3-indolyl-beta-D-glucuronic acid (X-Gluc). A purple chromoprotein (shPCP)
from the sea anemone Stichodacyla haddoni was successfully produced in N. oculata and used
for screening of transformants (99), while GUS has been utilized in N. salina (83).
Virus-derived 2A peptides allow production of two discrete proteins from a single
transcript by preventing the formation of a peptide bond (peptide bond "skipping") (Figure 1.2c).
The nascent protein interacts with the ribosome causing it to stall, then during the release of the
ribosome a peptide bond is “skipped” between the final two amino acids (100). 2A peptides have
been widely applied to different hosts and the efficiency of skipping depends on the peptide
variant and host. After screening several variants and lengths in N. oceanica, I found the P2A

15

peptide of 60 amino acids to be most efficient (Chapter 3)(15). The F2A peptide has also been
used in N. salina (7) and Chlamydomonas (101). In order to facilitate multigene expression,
bidirectional promoters with P2A peptide sequences were assembled in the pNOC-stacked vector
series and will be made available through Addgene (Chapter 3)(15). Toolkits for assembly of
multiple transgenic expression cassettes into a single vector have been developed for some algae
(102, 103), and would facilitate gene stacking in Nannochloropsis species (Figure 1.2d).

Generation of targeted gene disruption and transcriptional repression
RNA interference (RNAi) is a powerful technique that can suppress gene expression to varying
degrees. RNAi by antisense or double-stranded RNA has been developed in a number of algae
including Chlamydomonas (104, 105), diatoms (63, 73, 106), and different Nannochloropsis
species (16, 17, 37, 90). RNAi using an inverted repeat of regions of a target gene has been
found to be effective throughout the Nannochloropsis genus (Figure 1.3a) (Table 1.2) (16, 17,
37, 90). In order to generate a strong and stable repression effect several strategies are available
including, fusing the interfering RNA to an antibiotic resistance gene (16, 17, 106), co-silencing
a gene that can be counter selected (105), or expression of the interfering RNA from a
bidirectional promoter that also drives expression of an antibiotic resistance gene. In case of
essential genes, disruption of the target gene can result in slow growth or lethality while
transcriptional repression targeting the same gene may result in a moderate phenotype (17).
Homologous recombination has been demonstrated in several Nannochloropsis species
for insertion of an antibiotic resistance marker with flanking regions of 1 kb identical to the
insertion site (Figure 1.3b). Targeting efficiency has been reported to be high when transforming
low-density cultures (14). Several groups have used this technique for gene disruption (Table

16

1.2)(14, 25, 26, 96). Homologous recombination is adaptable to several purposes, such as,
insertion of protein tags, insertion into neutral sites, or replacement of genes with altered
functionality.
CRISPR/Cas9 is an RNA-guided nuclease based approach that is dramatically expanding
the capabilities of biologists to modify genomes, particularly through the ability to disrupt
specific genes or perform precise gene editing (107, 108). In this system two components have to
be targeted to the nucleus , a single-guide RNA (sgRNA) and the Cas9 nuclease, which together
form a ribonucleoprotein complex (Figure 1.3c). The sgRNA requires production without
extraneous sequences or modifications on the termini; strategies for sgRNA production include
the use of RNA polymerase III-driven promoters (most often the U6 promoter) (109), direct
introduction into the cell (17), expression of modified tRNAs containing the sgRNA in a spliced
region (110), co-expression of a ribonuclease and sgRNA with cleavage sites, and use of selfcleaving ribozymes (110). The U6 promoter from diatoms appear to be active and suitable for
sgRNA production (109). However, there have been no reports of successful U6 promoter use in
the Nannochloropsis genus, and two publications utilized alternative strategies (Table 1.2).
Wang and colleagues (27) expressed the sgRNA from an V-ATPase promoter and had a low
mutational efficiency. In a strategy developed by Ajjawi and coworkers (17), the sgRNA is
synthesized and introduced by transformation into a Nannochloropsis strain expressing Cas9. In
Chapter 4, I detail the development of a CRISPR/Cas9 system for N. oceanica based on a Cas9Nlux fusion protein and a self-cleaving ribozyme flanked sgRNA, co-expressed by a
bidirectional promoter. The generation of off-target mutations is an unresolved issue for CRISPR
based gene editing, which has not been examined in the Nannochloropsis genus. Several
strategies exist to reduce the number of potential off-targets, including transient expression of

17

one or both components (17, 111, 112), paired nickase Cas9 (108), or high-fidelity Cas9
enzymes (113, 114). The CRISPR/Cas9 system developed in Chapter 4 is based on an episome,
which can be removed after a mutation is produced. This method thus generates a marker-free
mutant without the continued presence of Cas9 and reduces the chances of potential off-target
mutations.
Insertional mutatagenesis, whereby an antibiotic resistance gene is randomly integrated
into a genome, results in gene disruptions and gene deletions (Figure 1.3d) (47, 115). Insertional
mutagenesis conducted in N. gaditana produced mutants with a variety of growth and
photosynthetic phenotypes, screening of which identified lines with enhanced light-use
efficiency(116). While insertional mutagenesis is an efficient method for forward-genetic
screens, ready-to-use lines with a disruption of a desired gene requires a mutant library that takes
a significant investment to establish (115).

Altering metabolism in Nannochloropsis species by protein engineering
The usefulness of the aforementioned genetic engineering tools has been demonstrated by
modifying different aspects of metabolism. The majority of studies have targeted lipid
biosynthesis, either to enhance TAG or EPA production (Table 1.2). In several cases endogenous
or heterologous (from S. cerevisiae or C. reinhardtii) DGATs have been overproduced in
different Nannochloropsis species (31, 32, 81, 90, 95, 117). Overexpression of the endogenous
DGAT1a-encoding gene in N. oceanica resulted in a 39% increase in TAG content per cell and
RNAi repression resulted in a 20% decrease in TAG content per cell following N deprivation
(90). We found that the overexpression of the endogenous DGGT5-encoding cDNA in N.
oceanica resulted in a 3.5 fold increase in TAG (as %TFA)(31). Furthermore, the DGTT7-

18

encoding cDNA has also been overexpressed in N. oceanica IMET1 resulting in 69% and 129%
increase in neutral lipid (% dry weight) content under N-replete and N-deprivation conditions
(95). The malonyl-CoA transacylase of N. oceanica IMET1, which loads the malonyl group onto
the acyl-carrier protein for fatty acid synthesis, has been characterized (118) and its
overproduction results in a 36% (% dry weight) increase in lipids without compromised growth
(119). In N. salina RNAi conducted against the pyruvate dehydrogenase complex (PDC) kinase
(PDCK), in order to increase acetyl-CoA levels for fatty acid production (21), resulted in
enhanced TAG content at the expense of protein (37). I increased expression of the desaturase
genes in the EPA pathway using gene stacking techniques achieving up to a 25% increase in
EPA (Chapter 3)(15). Engineering efforts are only beginning and the enhanced productivity of
engineered Nannochloropsis strains will require further identification of targets to affect
metabolite partitioning into the desired pathways, and/or the reduction of final product turnover.

Altering metabolism in Nannochloropsis species by regulatory engineering
Manipulation of entire metabolic pathways on a greater scale could be accomplished by TF
engineering. Recently, TF overproduction, or inactivation (CRISPR) and repression (RNAi) of a
TF encoding gene have been used in various Nannochloropsis species with the goal of increasing
biomass and/or lipid production (Table 1.2)(17, 72, 80, 120). Overproduction of the bHLH2 TF,
in N. salina resulted in an increased growth rate and a greater biomass productivity, although the
transcriptional reprogramming was not described (80). Overproduction of the bZIP1 TF, a
predicted lipid biosynthetic TF (19), in N. salina resulted in enhanced growth, and under stress
conditions enhanced lipid content (72). In the bZIP1 overexpressor lines, the expression of
putative target genes involved in lipid biosynthesis (19) was increased under normal conditions

19

and more dramatically under stress conditions (72). Remarkably, the introduction of the
Arabidopsis thaliana WRINKLED1 TF (WRI1), a regulator of seed oil production, into N. salina
enhanced lipid accumulation, possibly by upregulating lipid biosynthetic genes containing the
WRI1 motifs in the promoter (120). CRISPR inactivation of the ZnCys TF, likely involved in N
assimilation, resulted in a large increase in TAG content in N. gaditana but a strong reduction of
growth. An optimization of the balance between growth versus lipid accumulation was achieved
by decreased expression of ZnCys by RNAi or by the CRISPR/Cas9 mediated insertion of an
antibiotic resistance cassette into the 3' UTR of this gene (17).

Additional challenges for the development of improved Nannochloropsis strains
To develop improved strains optimized for biosynthetic yield, either by increasing flux into the
target pathway or by disruption of competing pathways multiple specific modifications are likely
to be required. For example, stacking gene modifications will be necessary to introduce new
pathways or for the optimization of existing pathways. Furthermore, the development of markerfree strategies or the utilization of auxotrophic markers for selection of genetically modified
strains are necessary for deployment of engineered strains into open ponds exposed to the
environment.
Disrupting competing metabolic pathways may yield enhanced productivity of certain
bioproducts. Carbohydrates are a competing sink for lipid production and polysaccharide
biosynthetic genes have been targeted for repression in green algae and diatoms to increase lipid
accumulation (63, 121, 122). The tough cell wall of the Nannochloropsis genus takes
considerable cellular resources to construct and is an impediment to efficient processing of cells
to obtain bioproducts. Therefore, Nannochloropsis strains with weakened walls may be superior

20

for bioproduction. Reducing the turnover of desired products may enhance their accumulation,
and identification of the genes involved in product degradation will be an avenue towards
enhancing the productivity of algae (123, 124).
The successful adoption of gene disruption technology will facilitate disruption of
biosynthetic genes for essential metabolites, generating strains that require supplementation or
gene complementation (auxotrophy). Nitrate reductase (NR)-deficient strains of Chlamydomonas
strains can be complemented with a wild-type NR gene and selected (125). The NR gene has
been targeted in several studies in various Nannochloropsis species (14, 17, 27) and diatoms
(126, 127). In Chapter 4, I describe the generation of a NR knockout line that is non-transgenic
using the episome CRISPR/Cas9 system. This line is an ideal chassis organism for development
of an auxotrophic marker. Auxotrophic selection may be particularly useful when paired with
episomal artificial chromosomes, enabling a nutrient selection pressure on episome maintenance.

Call for an open alga
Establishing a model organism (or bioproduct chassis) requires dissemination of the skills and
tools developed to a wide network of scientists. A niche is developing for third-party repositories
(TPR) that facilitate the maintenance of accumulated biological materials and are making these
materials more accessible than ever before. However, for a TPR to be sustainable innovators
must be willing to transfer their materials and utilize the TPR as part of their own workflow. A
notable nonprofit TPR for plasmid and strain dissemination is Addgene that we are collaborating
with by depositing the collection of Nannochloropsis engineering vectors developed in my
studies. Some of the model Nannochoropsis species such as CCMP1779 (N. oceanica),
CCMP526 (N. gaditana), and CCMP537 (N. salina) are publicly available from algae culture

21

collections (NCMA, https://ncma.bigelow.org/). We are making our engineered NR knockout
strain publicly available through NCMA, as well (Chapter 4). As transgenic tools and knockout
and chassis strains are produced, deposition with TPRs will accelerate innovation, allow
researchers to do more with less, build genome-wide overexpression and gene disruption strain
libraries, and establish quality controls and standardization in the field.

22

APPENDIX

23

Figure 1.1 The Nannochloropsis genus as a chassis organism.
Advantageous growth characteristics and genome-wide datasets of the Nannochloropsis genus
are listed on the left. Genetic engineering capabilities in the Nannochloropsis genus are listed on
the right. A schematic of a Nanochloropsis cell is shown in the center, highlighting the EPA
pathway and cell organization. Organelles and cell structures are identified by color and text,
metabolites are in capital letters, and enzymes bolded.

24

Figure 1.2 Multi-gene overexpression (gene stacking) strategies in N. oceanica.
Diagrams represent configuration for two protein coding transgenes. Gene1 represented by GFP
is shown in green. Gene2 represented by NanoLuciferase is shown in blue. Promoters are
indicated by arrows and terminators by a T (Synthetic Biology Open Language standard) (128).
Resistance markers are indicated as R’ (red). Nannochloropsis expression cassettes without a
plasmid backbone are shown. a. Constructs with unique selection markers (indicated as R’1 and
R’2, red) can be introduced into one line. b. Bidirectional promoters regulate transcription on
both DNA strands, and express two transcripts. c. Sequences encoding 2A peptides are placed
between two protein-encoding genes. A peptide bond is not formed between the two final amino
acids (*) during translation. Two discrete proteins are produced, the N’ terminal protein (green)
contains the majority of the 2A peptide (yellow) and the C terminal protein (blue) contains the
last amino acid of the 2A peptide (not shown). d. Assembly of multiple expression cassettes into
a single construct to produce multiple transcripts from different promoters. The image of the
GFP protein was obtained from the NIH Image Gallery (https://www.flickr.com/photos/nihgov/)
and is adapted under the terms of CC BY-NC 2.0. The NanoLuciferase image is adapted from
Hall et al. with permission (97).

25

Figure 1.3 Gene repression and inactivation techniques in the Nannochloropsis genus.
Promoters are indicated by arrows and terminators by a T (Synthetic Biology Open Language
standard) (128). Resistance markers are indicated as R’ (red). Extended DNA is indicated by an
overhanging backbone, and free ends of DNA are indicated by blunt ends. a. RNA interference
by expression of sense (blue) and antisense (green) sequences of a target gene at the 3’ end of a
resistance gene. The sense and antisense sequences form an inverted repeat on the resistance
marker transcript. b. Homology arms are the sequences flanking a desired insertion site (green).
A resistance cassette with flanking homology arms to a target region is introduced by
transformation. Homologous recombination between the homology arms of the resistance
cassette and the target region results in a disrupted gene. c. CRISPR/Cas9 techniques utilize the
Cas9 nuclease and an sgRNA, forming ribonucleoprotein complex (yellow). The PAM site (blue)
and the final 3' nucleotide of the guide sequence (green) are indicated. Double stranded cuts are
produced in the 3' end of the target region. Incorrect repair of the strand break prevents further
Cas9 action. Insertion or deletion mutations are most likely to occur. d. Insertional mutagenesis
by transformation with a resistance cassette. The resistance cassette is randomly inserted
throughout the genome, resulting in mutant lines with unique insertion sites. Desired mutants
(green) are identified by a phenotype screen, target gene screen, or from a mutant library.

26

Table 1.1. Publicly available whole-genome datasets produced in Nannochloropsis species.
The first column contains the lead author and citation. Strains refers to the Nannochloropsis subspecies. The data and presentation are
listed in the third column. A link to the complete data is listed in the fourth column (public access).
Citation
Strain(s)
Datasets
Public access
Radakovits
http://nannochloropsis.genomeprojectsolutionsN. gaditana CCMP526
Genome assembly
(13)
databases.com/
Corteggiani
Genome browser and
- Carpinelli N. gaditana B-31
www.nannochloropsis.org
BLAST
(12)
N. oceanica IMET1 and
CCMP531, N. granulata
CCMP529, N. oculata
Genome browser and
http://www.bioenergychina.org:8989/
Wang (18)
CCMP525, N. salina
BLAST
CCMP537, N. gaditana
CCMP526
Genome browser and
https://genome.jgi.doe.gov/Nanoce1779/Nanoce1779.home.
Vieler (11) N. oceanica CCMP1779
BLAST
html
Poliner
RNA-Seq during
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE6
N. oceanica CCMP1779
(45)
light:dark cycles
9460
Mühlroth
RNA-seq under
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE9
N. oceanica CCMP1779
(44)
phosphate deprivation 5774
N. oceanica IMET1 and
CCMP531, N. granulata
Predicted regulatory
CCMP529, N. oculata
http://www.singlecellcenter.org
Hu (19)
connections of lipid
CCMP525, N. salina
/en/NannoRegulationDatabase/Download.htm
biosynthetic genes
CCMP537, N. gaditana
CCMP526

27

Table 1.2. Genetic tools developed for the Nannochloropsis genus.
The first column contains the lead author and citation. Strains refers to the Nannochloropsis subspecies. Methods describe the genetic
techniques used in the study. The target gene refers to the function of the primary gene manipulated. Reporter or epitope indicates if a
protein tag was included, reporter abbreviations are FP - fluorescent protein, CP - chromoprotein, and GUS - β-glucuronidase.
Promoters used to drive transcription of transgenes in vivo are listed; the species of origin for non-Nannochloropsis promoters are
indicated in italics. Endogenous promoter abbreviations are LDSP - lipid droplet surface protein, β-tub - β-tubulin, UEP - ubiquitin
extension protein, HSP - heat shock protein, EF- elongation factor, VCP - violaxanthin–chlorophyll a binding protein, and Ribi ribosomal subunit bidirectional promoter. Selection agent refers to antibiotic selection used to isolate Nannochloropsis transformants.
Reporter(s) or
Selection
Citation
Method(s)
Strain(s)
Target gene(s)
Promoter(s)
epitope(s)
agent(s)
Transformation
Vieler (11)
N. oceanica CCMP1779
LDSP promoter Hygromycin
protocol
Radakovits Transformation
N. gaditana CCMP526
β-tub, UEP, HSP
Zeocin
(13)
protocol
N. oceanica PP983 and
MBIC10090, N. granulata
Transformation
MBIC10054, N. salina
Li (83)
GUS
β-tub
Zeocin
protocol
MBIC10063, N. gaditana
CCAP849/5, N. oculata CCAP
849/1, N. limnetica KR1998/3
Transformation
Cha (82)
N. sp. UMT-M3
CMV 35S
Hygromycin
protocol
Transformation
C. reinhardtii
Ma (129)
N. oculata CS-179
Zeocin
protocol
HSP70A::RBCS2
Subcellular
Moog (24)
N. oceanica CCMP1779
Green FP
VCP
Zeocin
localization
Chromoprotein
C. reinhardtii
Shih (99)
N. oculata NIES-2146
shCP
screening
HSP70A::RBCS2
Kang (79)

Reporter protein

N. salina CCMP1776

Chen (130)

Transformation

N. oculata

sfCherry
Fish growth
28

β-tub and UEP
C. reinhardtii

Zeocin

Table 1.2 (cont'd)
protocol

hormone

HSP70A::RBCS2

Overexpression

Poliner (15)

Multi-gene
overexpression

N. oceanica CCMP1779

Zienkiewicz
(31)

N. oceanica CCMP1779

Kaye (91)

N. oceanica CCMP1779

Li (95)

N. oceanica CCMP1779

Kang (80)

N. salina CCMP1776

Beacham
(81)

N. salina CCAP 849/3

Chen (119)

N. oceanica IMET1

Wei (131)

N. oceanica IMET1

Firefly
luciferase,
delta-9, delta-12,
NanoLuciferase
delta-5 fatty acid
, Cyan FP
desaturases
(Cerulean
variant)
diacylglycerol
Yellow FP
acyltransferase
(Venus variant)
type 2-5
delta-12 fatty
acid desaturase
diacylglycerol
acyltransferase
Flag tag
type 2-7
basic helix loop
Flag tag
helix 2
S. cerevisiae
DGA1
malonyl CoAacyl carrier
Flag tag
protein
transacylase
RuBisCO
activase

29

EF, LDSP, Ribi

Hygromycin,
Zeocin

EF

Hygromycin

LDSP

Hygromycin

Hsp20

Zeocin

β-tub, UEP

Zeocin

CMV Tef, 35S

Hygromycin

Hsp20

Zeocin

β-tub, HSP70

Zeocin

Table 1.2 (cont'd)
Iwai (117)

N. oceanica NIES-2145

Kang (120)

N. salina CCMP1776

Kwon (72)

N. salina CCMP1776

C. reinhardtii
diacylglycerol
acyltransferase
type 2-4
A. thaliana
WRINKLED1
basic leucine
zipper domain 1

VCP, C.
reinhardtii SQD

Zeocin

Flag tag

β-tub, UEP

Zeocin

Flag tag

β-tub, UEP

Zeocin

Gene disruption/
Transcriptional
repression
Kilian (14)

Gene disruption
by HR

Gene disruption
by CRISPR/Cas9
Gene disruption
by CRISPR/Cas9,
repression by
Ajjawi (17)
CRISPR/Cas9,
repression by
RNAi
Repression by
Wei (16)
RNAi
Gene disruption
Dolch (26)
by HR
Wang (27)

N. oceanica W2J3B

nitrate reductase

VCP

Zeocin,
Hygromycin,
Blasticidin

N. oceanica IMET1

nitrate reductase

VCP, β-tub, VATPase

Hygromycin

N. gaditana CCMP1894

ZnCys

N. oceanica IMET1 and
CCMP1779

carbonic
anhydrase
palmitate
elongase

N. gaditana CCMP526

30

initiation factor
4AIII, 60S
Green FP, Flag
Hygromycin,
ribosomal protein
tag
Blasticidin
L24, initiation
factor 3, TCT
β-tub

Zeocin

UEP

Zeocin

Table 1.2 (cont'd)
Gene disruption
or transcriptional
repression, and
overexpression
Wei (90)

Overexpression
and repression by
RNAi

N. oceanica IMET1

diacylglycerol
acyltransferase
type 1-1A

Green FP

VCP, UEP, β-tub

Zeocin

Gee (96)

Gene disruption
by HR,
complementation

N. oceanica CCMP1779

carbonic
anhydrase

Flag tag,
Yellow FP
(Venus variant)

UEP

Zeocin

Nobusawa
(25)

Overexpression
and gene
disruption by HR

N. oceanica NIES-2145

LDSP

Zeocin,
Hygromycin

Ma (37)

Overexpression
and repression by
RNAI

N. salina CCMP537

β-tub, VCP

Zeocin

lysophosphatidic
Green FP,
acid
Yellow FP
acyltransferase
(Venus variant)
1-4
pyruvate
dehydrogenase
Green FP
kinase

31

Table 1.3. Effective antibiotic selection agents and resistance genes for N. oceanica
The first, second, and third columns contain the antibiotic common name, its molecular class, and the lethal concentration for N.
oceanica CCMP1779, respectively. The fourth, fifth, and six column contain the resistance gene name, organism from which it was
isolated, and the number of amino acids of the resulting protein, respectively.
Effective concentration
Amino
Antibiotic
Molecular class
(μg/ml)
Resistance gene
Originating organism
acids
Hygromycin-B
Hygromycin
aminoglycoside
100-500
phosphotransferase
Escherichia coli
441
Zeocin

glycopeptide

5

Bleomycin
resistance protein

Streptoalloteichus
hindustanus

124

Blasticidin

peptidyl nucleoside

50

Blasticidin-S
deaminase

Aspergillus terreus

129

G418

aminoglycoside

250

Klebsiella pneumoniae

266

Nourseothricin

aminoglycoside

100

Streptomyces noursei

189

Aminoglycoside 3'phosphotransferase
Nourseothricin
acetyltransferase

32

Chapter 2. Transcriptional coordination of physiological responses in Nannochloropsis
oceanica CCMP1779 under light:dark cycles
ABSTRACT
Nannochloropsis oceanica CCMP1779 is a marine unicellular heterokont and an emerging
reference species for basic research on oleogenic microalgae with biotechnological relevance.
We investigated its physiology and transcriptome under light:dark cycles. We observed
oscillations in lipid content and a predominance of cell division in the first half of the dark phase.
Globally, more than 60% of the genes cycled in N. oceanica CCMP1779, with gene expression
peaking at different times of the day. Interestingly, the phase of expression of genes involved in
certain biological processes was conserved across photosynthetic lineages. Furthermore, in
agreement with our physiological studies we found the processes of lipid metabolism and cell
division enriched in cycling genes. For example, there was tight coordination of genes involved
in the lower part of glycolysis, fatty acid synthesis and lipid production at dawn preceding lipid
accumulation during the day. Our results suggest that diel lipid storage plays a key role for N.
oceanica CCMP1779 growth under natural conditions making this alga a promising model to
gain a basic mechanistic understanding of triacylglycerol production in photosynthetic cells. Our
data will help the formulation of new hypotheses on the transcriptional control of cell growth and
metabolism in Nannochloropsis.

INTRODUCTION
The daily light:dark cycle is a major environmental change affecting photosynthetic organisms.
During the light period photoautotrophs rely on solar energy to drive anabolic processes
including the transient storage of a fraction of the fixed carbon for later use in cellular processes

33

during the dark period. Other processes controlled by light:dark cycles in photosynthetic
organisms include cell division, stress sensitivity, chemotaxis, nutrient uptake, and phototaxis
(132-135). Studies of circadian clock mutants that display disruptions in the timing of daily
events indicate that this coordination is necessary for optimal growth and survival (136, 137).
Moreover, these rhythms not only affect the physiology of single organisms but could also
influence the structure of phytoplankton communities (138).
Nannochloropsis species are small unicellular algae belonging to the heterokont lineage.
They live in marine, and fresh and brackish water environments. Marine Nannochloropsis
species are used as a source of fish food and omega-3 fatty acids (139) and, due to their high
lipid content, have been considered as a potential source of biofuels (6, 140-142). The genomes
of several Nannochloropsis species collected at different locations around the globe have been
recently sequenced (18). Their small genomes range from ~25 to ~32 Mb and contain ~9,00012,000 genes. Nannochloropsis species all display an expansion of gene families involved in
lipid biosynthesis (11, 18) and accumulate triacylglycerols, particularly under nutrient limiting
conditions (11-13, 22, 143). In accordance, transcriptomic analysis of different Nannochloropsis
species have been focused on identifying changes occurring under nitrogen deprivation (11-13,
22, 143).
In different Nannochloropsis species cell division is synchronized and carbohydrate, lipid
and protein contents per cell oscillate under daily light:dark cycles. However, little is known
about changes in gene expression occurring under diel conditions. In contrast to plants and green
algae (144-146), information on global gene expression changes under diel cycles in heterkonts
is limited. Only one study on the diatom Phaeodactylum tricornutum analyzed global gene
expression changes over the course of a light:dark cycle (49). In this report, we characterize gene

34

expression, cell growth and metabolite content of Nannochloropsis oceanica CCMP1779 every
three hours under day-night cycles of 12 h light and 12 h dark. We also extend the annotation of
cell cycle and central metabolism genes and use changes in expression under diel cycle together
with predictions of subcellular localization of central carbon metabolism genes to propose a
model of primary metabolism under light:dark cycles in N. oceanica CCMP1779.

RESULTS
N. oceanica CCMP1779 growth and metabolite content under diel conditions
Many algae grown under light:dark cycles display synchronized cell division (147). We
investigated cell division rates in N. oceanica CCMP1779 under diel conditions of 12 h light and
12 dark (LD) and observed that cell division was confined to the first 6 h of the dark period. Cell
growth occurred only during the light period with cell mass increasing from a minimum at ZT0
(Zeitgeber time, h after last lights on) to a maximum at ZT12 (Figure 2.1). This pattern of growth
is similar to what has been observed in other phytoplankton species under both laboratory
conditions (148-150) as well as in situ (151). In contrast, in some diatom species cell division
occurs continuously during exponential growth (50-52).
Nannochloropsis species are able to produce large amounts of lipids and when grown
under light:dark cycles accumulate lipids only during the light phase (55, 152). We therefore
quantified the content of neutral, storage and polar membrane lipids over a 24 h diel cycle in N.
oceanica CCMP1779. The content of the different lipids followed the same pattern during the
LD cycle increasing during the day and decreasing during the night including triacylglycerol
(TAG),

digalactosyldiacylglycerol

sulfoquinovosuldiacylglycerol

(DGDG),

(SQDG),

monogalactosyldiacylglycerol

phosphatidylcholine,

35

(MGDG),

phosphatylethanolamine,

phosphatidylglycerol and phosphatylinositol (Figure 2.2). By the end of the light period TAG
was the most abundant lipid followed by the membrane lipids MGDG and phosphatidylcholine
(Figure 2.2). The total fatty acid content was similar to previous reports cellular fatty acid
content during a light:dark cycle in other Nannochloropsis species (55, 152) and glycerolipids
content as percent dry-weight was similar to previously reported values under similar light
intensities (22). The oscillations of lipid content per cell might be just a reflection of cell growth
during the day and division during the night. However, we observed that TAG was the only lipid
that showed oscillations as a percentage of dry-weight indicating that in this case the change in
content was independent of cell size changes (Figure 2.2). This result suggests a role of TAG in
transitory carbon storage under LD cycles in N. oceanica CCMP1779. Glucose is the most
abundant hexose in N. oceanica strains (9, 11). Total glucose content per cell and its level on a
percent dry weight oscillated under diel conditions (Figure 2.2). The decrease in glucose content
during the night could be due to shedding of the cell wall during cell division, which is
composed mainly of cellulose (11, 65), and the use of glucose-containing storage compounds,
such as intracellular laminarin (9).

Oscillations in global gene expression in N. oceanica under day:night cycles
To understand the mechanisms driving the oscillations in growth and metabolism we analyzed
global changes in gene expression in LD in N. oceanica CCMP1779 using transcriptome
sequencing (RNA-Seq). We analyzed gene expression in two independent biological replicates
every three hours over the course of one day. We confirmed similar expression patterns by
reverse transcription quantitative PCR for genes expressed at different times of day in
independent experiments (Figure 2.3). For data analysis and graphic representation using heat

36

maps we used the two biological replicates as representing two consecutive days as has been
done for analyses of diel datasets in other species (153). COSPOT (154) and an application of
the discrete Fourier transform (DFT) were used for the identification of cycling genes (see
Experimental Procedures). We found that 7433 genes (61.8% of the genome) in N. oceanica
CCMP1779 were predicted to be cyclic. Of these predictions, the majority (59%) were common
to both COSPOT and the DFT analysis methods. The overlap between the two methods was high
since the intersection between COPSOT and DFT covered ~70% of DFT predictions and ~80%
of COSPOT predictions (Table 2.1). We also observed many genes displaying oscillatory
expression patterns with narrow peaks of RNA levels that were not identified as cycling in our
initial analysis. We therefore used EdgeR to identify an additional 199 cycling genes. In
summary, a total of 7632 genes or 63.7% of the genome cycled under LD conditions in N.
oceanica CCMP1779 with phases of expression at different times of the day (Figure 2.4a, Data
2.1). This percentage is higher than what has been observed for land plants, where 30-40% of
genes cycle under day:night conditions (145, 153, 155). It is also higher than a recent estimate of
~45% cycling genes for the diatom Phaedodactylum tricornutum (49) but lower than those for
some cyanobacteria (156). The distribution of expression phase was approximately bimodal with
most genes peaking close to dawn (ZT21-ZT0) and in anticipation of dusk (ZT9) (Figure 2.4a).
This pattern is similar to the one observed in many photosynthetic species (145, 146, 153, 155158).
Using an existing genome annotation (11), the enrichment GO terms were assessed
within each phase group and 195 terms contained a significantly over-represented number of
cycling genes in at least one phase group (multiple testing adjusted p<0.05; Figure 2.4b). A
summary of the top enriched GO terms for each phase can be found in Figure 2.4c. The phase

37

groups at ZT9 and ZT21 hours account for 60% of enriched GO terms with 67 and 50 terms
respectively. These results indicate that changes in gene expression can be associated with
different physiological processes occurring at specific times of day. For example, we found
enriched GO terms relevant to terpenoid and chlorophyll biosynthesis in the early morning, DNA
replication in the middle of the light period and terms associated with translation at the end of the
night period (Figure 2.4c). Several of these phase-specific enrichments are similar to those
observed in other photosynthetic organisms grown in both the laboratory as well as under natural
conditions (145, 146, 153, 155-159).

Genes involved in cell division display strong diurnal oscillations in N. oceanica CCMP1779
Synchronization of the cell cycle in unicellular alga could affect the synchronization of global
gene expression under diel conditions and play a role in the regulation of metabolism (160-162).
We identified several cell cycle genes in N. oceanica CCMP1779 including 10 cyclin dependent
kinases (CDK) and 10 cyclin related genes (CYC) (Figure 2.5, 2.6; Data 2.2). All these genes
displayed oscillations in mRNA levels during the LD cycle (Figure 2.7). However, some of these
genes were not identified as cycling using our initial analysis pipeline, probably due to their
narrow peaks of expression. We had observed an enrichment of GO-terms associated with DNA
synthesis at ZT6 (Figure 2.4c). The interaction between a retinoblastoma protein and E2F/DP
transcription factors regulate the G1-S transition in most eukaryotes (163). The expression of a
putative retinoblastoma-like gene (NannoCCMP1779|10679, for brevity 10679) preceded the
expression of one putative DP-1 transcription regulator (3316) one E2F gene (4416), which
peaked at ZT6 (Figure 2.7). In the diatom Phaedodactylum tricornutum the G1-S transition is
light regulated and the expression of several cell cycle genes oscillates under light:dark cycles

38

(51). Interestingly, in N. oceanica CCMP1779 putative CDKA1s (4688), CDKD1 (2601) and
CDKA2 (1586) genes display a similar phase of expression as their homologs in P. tricornutum
indicating that cell cycle progression might occur in similar fashion as in diatoms under LD
conditions (Figure 2.7). In order to further characterize the cell cycle in N. oceanica CCMP1779
we performed DNA content analyses by flow cytometry under diel conditions (Figure 2.7b, c).
These results confirmed that under our growth conditions not all cells divided each day. Most of
the cells were in G1 in the morning and DNA synthesis (S-phase) started about ZT6. At ZT15,
three hours into the dark period some cells had two and four times the G1 DNA content (Figure
2.7b). Accordingly, cells with two and four nuclei were present during the dark period (Figure
2.7d) and some cells divided into four daughter cells at that time (Figure 2.8). These results
correspond well with RNA levels of cell cycle genes.
We also observed that the RNA levels of genes potentially involved in organelle division,
such as genes encoding FtsZ-like proteins (10028, 11167, 10560), an ARC5/DRP5B-like protein
(7886) and one MinD-like protein (5101) cycled. Their expression peaked between the middle
and end of the day (Figure 2.7). These results suggest a coordination of organelle and cell
division during the diel cycle as has been observed in diatoms (161). As is the case for other
heterokonts, Nannochloropsis plastids are surrounded by four membranes. The outer most
membrane continues directly to the outer nuclear envelope and tight coordination of the nuclear
and plastid division has been observed in Nannochloropsis oculata (33).

The RNA content of genes involved in carbon assimilation peaks at dawn
The N. oceanica CCMP1779 genome encodes all the enzymes necessary for the Calvin-Benson
cycle (11). Several reactions of the Calvin-Benson cycle are shared with other metabolic

39

pathways, and we therefore focused our analysis on reactions specific to carbon assimilation. We
observed that the strongest expressed genes encoding phosphoribulokinase (11364) and both
putative sedoheptulose bisphosphatases (2947, 4791) were coregulated peaking within the first 3
h of the light period (Data 2.2, Figure 2.9). Interestingly, the highest expressed genes potentially
involved in carbon concentrating mechanisms were on at dawn (Data 2.2). For example, the
highest expressed putative α-carbonic anhydrase gene (6698) displayed strong oscillations with
changes in amplitude of almost 60-fold with a maximum in RNA content at 3 h into the light
period. We have also identified two genes that peak at dawn encoding putative carbonate
transporters. Our phylogenetic analysis showed that these genes belong to the SLC4 family of
proteins present in other marine heterokonts and marine green algae but are likely to be different
than the recently characterized Phaeodactylum bicarbonate pumps (164) (Figure 2.10, Data 2.2).
These observations are consistent with the hypothesis that these genes are involved in processes
occurring during the light period (Figure 2.9). Finally, most genes involved in the light reactions
of photosynthesis also peaked close to dawn or during the first half of the light period (Data 2.2),
suggesting a tight transcriptional control of the photosynthetic process in N. oceanica
CCMP1779.
The presence of genes encoding a phosphoenolpyruvate (PEP) carboxylase (3970,
PEPC), malic enzymes (9004, 4675, ME), a PEP carboxykinase (6821, PCK), pyruvate
phosphate dikinase genes (2768) in Nannochloropsis species has led to the speculation of the
presence of a C4-type carbon fixation mechanism (11-13). The expression of these genes peaked
at the end of the night period (Data 2.2). The highest expressed of these genes, PEPC (3970),
encodes an enzyme with a putative mitochondrial localization signal and might be similar to the
T. pseudonana mitochondria-localized PEPC (165). One of the two ME contains a signal

40

peptide, is similar to other NADP-ME, and could localize in the plastid (Figure 2.11, Data 2.2).
In addition to a potential role in a CO2 concentrating mechanism it has been suggested that these
proteins could function in the generation of reducing equivalents for lipid biosynthesis (166,
167), the dissipation of excess light energy, and/or pH regulation (168).

Carbohydrate metabolism under light:dark cycles
Glucose and mannitol in monomeric and polymeric forms are the major intracellular
carbohydrates in N. oceanica IMET1 (9) and cellulose is the main carbohydrate component of
the cell walls of different Nannochloropsis species (11, 65). Nannochloropsis genomes encode
for large families of glycosyl transferases (GT) and glycosyl hydrolases (GH)(11, 18, 65).
However, the details of polysaccharide biosynthesis in Nannochloropsis species are still
unknown. Clustering analysis revealed several large sets of highly coregulated GT and GH genes
(Figure 2.12). For example, we found three large groups of GT and GH encoding genes peaking
at distinct times between ZT9 and ZT15 that could be involved in specific steps necessary for
cell wall restructuring and biosynthesis during cell division.
Laminarin digestibility assays indicate that 20% of N. oceanica CCMP1779 insoluble
polysaccharides are made up of β-1,3-glucans (11). The gene encoding the only β-1,3-glucan
synthase (9088)(GBS) in N. oceanica CCMP1779, which is closely related to GT48 family
proteins in other heterokonts (Figure 2.13), peaked at ZT15 (Data 2.2). These results suggest that
it might be involved in the synthesis of polymers similar to the ones found in other heterokonts.
It

is

expressed

earlier

phospholucoisomerase

than

(11835,

genes
2243),

involved

in

UDP-glucose

phosphoglucomutase

(4161)

synthesis
and

such

as

UDP-glucose

pyrophosphorylase encoding genes (6938, 11841; Data 2.2), which peak at dawn indicating a

41

potential role in polysaccharide biosynthesis during the light period. In contrast, we observed
that genes involved in the metabolization of hexoses, such as a hexokinase (11432), two of the
three putative phosphofructokinases (6373, 10476) and the two glucose-6-phosphate
dehydrogenases (640, 2822) peaked at ZT9 (Data 2.2) indicating that they might be involved in
storage carbohydrate metabolization during the night period (Figure 2.2, Figure 2.9).
Genes potentially involved in mannitol biosynthesis also display diel oscillations in N.
oceanica CCMP1779. For example genes encoding a mannitol 1-phosphate dehydrogenase
(10023) and a partial mannitol 1-phosphate phosphatase gene (10755) with similarity to E.
siliculosus EsM1Pase1 and EsM1Pase2, peaked in the middle of the light period (Data 2.2,
Figure 2.14). In contrast, the expression of a gene encoding a putative mannitol 2-dehydrogenase
(5782, M2DH) with 43% identity to E. siliculosus M2DH (NCBI: CBJ29121.1), which catalyzes
the conversion of mannitol to fructose, peaked at ZT21 (Figure 2.14). Moreover, M2DH was
tightly co-expressed with a putative fructokinase-encoding gene (6825) that could close the
mannitol cycle generating fructose-6-phosphate (Figure 2.14, Figure 2.9). In brown algae
mannitol content as well as the expression of mannitol metabolic genes also oscillate under
light:dark cycles (169-171) and our results suggest this might also occur in N. oceanica
CCMP1779.

Acetyl-CoA metabolism is temporally and spatially segregated in N. oceanica CCMP1779
N. oceanica CCMP1779 plastids appear to contain all the enzymes necessary for the conversion
of hexose-phosphates to acetyl-CoA (Data 2.2). Our current predictions indicate that N. oceanica
CCMP1779 mitochondria are also able to metabolize triose-phosphates to acetyl-CoA, however
this species seems to lack a cytosolic enolase (Figure 2.9, Data 2.2). This compartmentalization

42

is similar to what has been proposed in diatoms, where a complete cytosolic glycolytic pathway
is lacking in several species (172). Based on the observed increase in lipid content during the
light period in N. oceanica CCMP1779 (Figure 2.2) we expected a higher expression of genes
involved in acetyl-CoA biosynthesis in the first part of the day. In accordance, the genes
encoding enzymes of both the plastid and mitochondrial bottom parts of glycolysis displayed
high degree of co-expression with maxima close to dawn (Figure 2.9, Data 2.2). In particular, all
four pyruvate kinase genes (PK) (497, 5759, 10510, 8741) displayed strong oscillations with
peaks within 3 h of dawn (Figure 2.9, Data 2.2). This observation contrasts with the case of P.
tricornutum in which the genes encoding the highest expressed PK isoenzymes are strongly
expressed at the end of the day (49). Moreover genes encoding putative plastid pyruvate
dehydrogenase complex (PDC) subunits displayed very similar expression profiles during the
LD cycle peaking close to dawn (Figure 2.15). In contrast, several putative mitochondrial PDC
subunits displayed only weak RNA oscillations with higher levels during night period (Figure
2.15). Even though gene expression does not directly indicate metabolic flux, based on our
results one might hypothesize that there is not a large flux from carbohydrates into acetyl-CoA at
night in N. oceanica CCMP1779. This hypothesis implies that at night most acetyl-CoA is
generated by β-oxidation of lipids.
We also identified other enzymes that could be involved in acetyl-CoA production in the
cytosol in N. oceanica CCMP1779, including a putative cytosolic ATP-citrate lyase (10051) and
two acetyl-CoA synthetases (956, 1243). The RNA levels of the ATP-citrate lysase gene peaked
at dusk and the highest expressed putative acetyl-CoA synthetases encoding gene (956) peaked
at ZT15 (Data 2.2, Figure 2.9). Based on their lack of co-expression with other fatty acid
biosynthesis genes, these genes are not likely to be involved in lipid biosynthesis and might

43

generate acetyl-CoA for other processes such as histone acetylation in the nucleus (173).
However, radiolabeling studies in Nannochloropsis sp. suggest that long chain polyunsaturated
fatty acids (LC-PUFA) can be produced by an extraplastidic pathway, which could use a
cytosolic acetyl-CoA source (61).

The expression of fatty acid synthesis genes precede lipid accumulation during the day
We found that most genes likely to be involved in fatty acid synthesis cycled under LD
conditions in N. oceanica CCMP1779. Acetyl-coA carboxylase (ACC) catalyzes the
carboxylation of acetyl-coA to form malonyl-coA, which is then used for fatty acid biosynthesis.
Several heterokonts, including diatoms, contain two forms of monomeric ACC, one of which
contains a signaling peptide and could localize to the plastid (174). However, as in other
Nannochloropsis species (12, 22), we did not find genes encoding full length monomeric ACCs
in N. oceanica CCMP1779. We identified eight genes containing ACC specific domains that
might encode subunits of heteromeric ACCs, as found in seed plants, or form part of a yet
unidentified monomeric ACC (175)(Data 2.2). Visual inspection indicated that the expression of
five of these genes peaked at dawn in a similar manner as a plastid malonyltransferase (6562)
and putative components of the plastidtype II fatty acid synthase (FAS) (Figure 2.15). The peak
of expression of genes encoding putative components of the mitochondria type II FAS peaked
slightly earlier during the mid-late night (Figure 2.15). Taken together our observations suggest
the coordination between the glycolysis and fatty acid synthesis for lipid production in N.
oceanica CCMP1779 (Figure 2.9).
Three putative type I FAS-like genes had been previously identified in N. oceanica
CCMP1779 (3502, 6720, 1983) (11). Phylogenetic analysis showed that these proteins are more

44

similar to fungal polyketide synthases (Figure 2.16). Moreover, the expression of these three
genes cycle at different phases of the LD cycle (Data 2.2) indicating that each of them might
have slightly different functions and act independently of fatty acid biosynthesis in this alga.

Regulation of gene expression related to lipid biosynthesis over the diel cycle.
In order to identify the mechanism responsible for the observed diel oscillations in lipid content
in N. oceanica CCMP1779 (Figure 2.2) we also analyzed the expression of genes putatively
involved in lipid biosynthesis in our dataset. By visual inspection the expression of 88% (62/70)
of genes involved in lipid biosynthesis cycled under diel conditions. Genome analyses indicate
the presence of a plastid as well as an endoplasmatic reticulum (ER) localized glycerolipid
biosynthetic pathways in N. oceanica CCMP1779 (176). We observed that all three genes
involved in the plastid diacylglycerol (DAG) synthesis (4533, 2512, 4742) displayed coordinated
expression with a peak at the dark to light transition (Figure 2.15). The putative plastid
galactolipid synthases MGD1 (10634) and DGD1 (4384) (11) cycled with expression peaking
also at dawn (Figure 2.15). The SQDG biosynthetic genes (6637, 4348) also showed cyclic
expression with a maximum during the light period (Figure 2.15). In summary, the expression of
the plastid glycerolipid genes in N. oceanica CCMP1779 displayed high coordination with fatty
acid synthesis genes at the transcriptional level so their expression preceded the observed lipid
accumulation during the light period (Figure 2.9). In contrast, lipid biosynthesis in the ER did not
appear to be as tightly coordinated over the diel cycle (Figure 2.15). Although most of the genes
involved in DAG production in the ER cycled with a peak close to dawn, the genes involved in
phosphatidylcholine, phosphatylethanolamine and phosphatylinositol biosynthesis peaked at
different times of day (Data 2.2).

45

Nannochloropsis species produce high amounts of LC-PUFA (11, 22, 141, 177). We
observed that in N. oceanica CCMP1779 all genes encoding fatty acid desaturases (11542, 6416,
2179, 5130, 5794, 126) were strongly co-expressed throughout the LD cycle with maxima at
ZT3 (Figure 2.15). In contrast, the expression of most elongase encoding genes peaked at
different times between dusk and dawn (Figure 2.15). Most of the EPA in N. oceanica
CCMP1779 is found in MGDG and the betain lipid DGTS (11). The expression of the
bifunctional monomeric DGTS synthase (10012) rapidly increased during the first hours of the
light period and was co-expressed with the fatty acid desaturase genes (Figure 2.15).
We observed oscillations in TAG content on a per dry weight basis in N. oceanica
CCMP1779 (Figure 2.2). TAG can be generated from DAG via diacylglycerol acyltransferase
(DGAT) and the Nannochloropsis genus displays a large expansion of the DGAT/MGAT gene
family (18). The N. oceanica CCMP1779 genome encodes for one DGAT-1 and 10 DGAT-2
genes (11). The expression of most DGAT-2 genes cycled with peaks of expression at different
times during the light period (Figure 2.15). In contrast, DGAT-1 (3520) RNA levels peaked at
dusk (Figure 2.15). TAG can also be synthesized by the transfer of a glycerolipid-bound fatty
acid to DAG. The two phospholipid:DAG tranferases identified in N. oceanica CCMP1779
(2212, 8602) were expressed during the light period (Figure 2.15). TAG is stored in lipid
droplets formed by a membrane lipid monolayer and a neutral lipid core. Lipid droplet proteins
have been characterized in a number of algal species, including the major lipid droplet (MLDP)
in Chlamydomonas and lipid droplet surface protein (LDSP) in N. oceanica CCMP1779 (104,
176). MLDP and LDSP protein levels were found to correlate with TAG content during nitrogen
stress (104, 176). We observed that LDSP RNA levels strongly increase during the first half of

46

the day and that LDSP protein levels correlate with TAG content over the diel cycle (Figure
2.17).

Lipid degradation and the TCA cycle.
Genome analyses indicate that β-oxidation occurs in both the peroxisome and mitochondria in N.
oceanica CCMP1779 (11). The expression of most genes involved in the early steps of βoxidation peaked between dusk and dawn during diel cycles and might be involved in the
degradation of lipids in the dark (Figure 2.18). For example, the expression of the strongest
expressed mitochondrial acyl-CoA dehydrogenase encoding gene (6983), the mitochondrial
multifunctional enzyme α-subunit (4030) and three putative β-subunits/thiolases (2420, 11662,
3591) peaked at dusk (Figure 2.18). We also identified an acyl-CoA synthetase (LACS) with a
putative mitochondrial localization signal expressed at dusk (11454), suggesting a role in
mitochondrial β-oxidation (Figure 2.18). In contrast, the expression of genes involved in
peroxisomal β-oxidation, such as a peroxisomal acyl-CoA oxidase (10648), the peroxisomal
multifunctional enzyme (6411) and a putative peroxisomal LACS (4001) peaked later during the
night period (Figure 2.18). We had previously identified several genes that could be involved in
lipid degradation (11). Although most of these genes were expressed either close to dusk or
during the night period in a similar manner as β-oxidation genes, a group was expressed
preferentially during the early light phase indicating that they might be involved in acyl editing
during lipid biosynthesis (178) (Figure 2.19).
We found that most genes involved in the mitochondrial TCA cycle were also coexpressed with peaks in RNA levels around dusk (Figure 2.18). Interestingly, all four genes
encoding pyruvate carboxylases (PYC) in N. oceanica CCMP1779 (6175, 7693, 4504, 7838)
47

displayed similar patterns of expression with maximum RNA levels at the end of the day (Data
2.2). In contrast, in the diatom Phaeodactylum triconutum genes encoding a plastid PYC and a
mitochondrial PYC are expressed at dawn and early during the night period respectively (49).
Our results indicate that PYCs could play an anapleurotic role in the TCA cycle at night, further
suggesting that in the dark most of the acetyl-CoA derives from fatty acid degradation in N.
oceanica CCMP1779.

Cyclic expression of transcriptional regulators
We observed that the mRNA levels of about 60% of the N. oceanica CCMP1779 genes cycle
under diel conditions (Figure 2.4a). These changes could be a result of diurnal oscillations of
light and/or metabolite levels or directly caused by a circadian oscillator. In order to identify
potential regulatory proteins we analyzed the expression of genes encoding transcription factors.
About 64% of the DNA binding transcription factors and 56% of other transcriptional regulators
identified in N. oceanica CCMP1779 (11) displayed cycling mRNA levels under diel conditions
(Figure 2.20a). We did not observe a particular enrichment in either phase of expression or
number of cycling members in the different gene families, but we found that AP2, CCAAT, TIG,
BSD and HMG families contain less than 50% of cycling members based on computational
analysis (Data 2.2). We had identified four genes encoding putative blue light receptors in N.
oceanica

CCMP1779,

three

Aureochrome-like

proteins

(AUREO2/3/4)

and

a

cryptochrome/photolyase family protein (CPF1) (11). In other organisms these proteins are able
to directly affect gene expression. For example, AUREO1a in Phaeodactylum tricornutum
regulates the expression of the diatom specific cyclin 2 gene by binding to its promoter (47, and
PtCPF1 is able to act as transcriptional repressor (75). The expression of AUREO3 (10447) and 4

48

(5385) as well as CPF1 (4809) displayed oscillations in gene expression with peaks close to
dawn (Figure 2.20b) indicating that they might be involved in light dependent regulation of gene
expression at dawn. Interestingly, PtCPF1 and PtAUREO1c also have higher expression levels at
dawn than at dusk (52).
Nucleosome modifications lead to changes in chromatin state and can influence gene
expression (179). Using HMMER analysis (180) we identified genes encoding proteins
potentially involved in the regulation of histone modifications, these included putative histone
deacetylases, histone methylases, histone acetyltransferases, Chromosome Condensation 1-like
proteins and SNF2 related proteins. We found that the expression of large number of these genes
peaked at ZT21, with a second group peaking during the first half of the day (Figure 2.21). These
results show that N. oceanica CCMP1779 tightly controls the diurnal expression of chromatin
modification factors, which could be involved in the global cyclic gene expression as has been
shown to occur in mammals (181).
Some plastid encoded genes displayed cycling RNA levels (Data 2.2). Although the N.
oceanica CCMP1779 chloroplast genome has not been assembled, we identified a few genes
likely to be chloroplast encoded based on the localization in the N. oceanica IMET1 chloroplast
genome (28). It has been recently shown that in Arabidopsis the nuclear encoded sigma 70-like
factors affect the diel and circadian oscillations of chloroplast encoded genes (182). All five
sigma 70-like transcriptional regulator encoding genes in N. oceanica CCMP1779 displayed diel
oscillations in gene expression at different times of the day (Figure 2.20c). Thus, they could be
involved in regulating cyclic plastid expression in N. oceanica CCMP1779. Moreover, the
expression of three of the four putative mitochondrial transcription termination factor-related

49

gene (mTERF) also displayed diel oscillations in N. oceanica (Figure 2.20d) indicating that
mitochondrial gene expression might also be diurnally controlled (183).

DISCUSSION
The large number of genes displaying cyclic expression indicates the existence of significant
transcriptional control of growth and metabolic rhythms in N. oceanica CCMP1779. We found
that the timing of expression of genes related to some metabolic pathways was conserved among
taxa of photosynthetic organisms. These include the expression close to dawn of carbon fixation
and protein synthesis related genes, the expression of photosynthesis and pigment biosynthesis
genes during the first half of the light period and the expression of genes related to the TCA
cycle and β-oxidation close to dusk (49, 145, 158, 160). Our results indicate that lipids play a
major role as photosynthetic carbon sinks in N. oceanica. We found strong co-expression of
genes involved in the lower part of glycolysis in both plastid and mitochondria with fatty acid
biosynthesis genes at dawn suggesting cooperation for lipid production. Our results also suggest
that N. oceanica CCMP1779 use TAG partly as transitory carbon storage under diel conditions.
In addition, we observed that the RNA level of genes involved in TAG synthesis and storage as
well as the expression of a lipid droplet protein displayed oscillations under diel conditions that
correlated with TAG content. We expect that the data presented here will provide not only a
resource to the community interested in the evolution of cyclic gene expression, but will also
aide the future exploration of TAG biosynthesis and degradation during natural day-night cycles.
Understanding this process will be crucial for optimizing TAG yield in biotechnologically
relevant algae.

50

EXPERIMENTAL PROCEDURES
Culture conditions
For all experiments N. oceanica CCMP1779 cells were grown in flasks containing f/2 media
under 12 h light:12 h dark cycles at 22°C under agitation (100 rpm). Light intensity during light
periods was 40 µmol s-1 m-2. ZT0-9 and ZT12-21 sets of samples were grown in two identical
incubators set to reversed light:dark cycles. The ZT0 samples were collected in the dark and
ZT12 samples in the light. Cell numbers were determined using a Beckman Coulter Z/2.

Lipid analyses
For each biological replicate, we used one 100 ml culture grown in a 500 ml flask. Cell numbers
were ~ 30 106 ml-1 at time of harvest. For dry weight determination 40 ml of culture were
filtrated through pre-dried and pre-weighed Whatman GF/F or C filters and dried for 48 hours in
a vacuum desiccator. For metabolite analysis, 40 ml of each culture were collected by
centrifugation at 4000 g for 10 minutes. Cells were transferred to 1.5 ml tubes and frozen in
liquid nitrogen after a final centrifugation step. For polar lipid separation shown in Figure 2.2,
lipids were extracted from the frozen pellet using the Bligh Dyer protocol followed by a 0.9 %
KCl wash (184). Lipids were separated by thin layer chromatography using either (80:32:16:3:3)
chloroform: acetone: methanol: acetic acid: water (55), or (25:25:25:10:4) methyl acetate:
isopropanol: chloroform: methanol: KCl (0.25%) (185) based on the separation resolution of
known standards and the use of headgroup specific dyes. For data shown in Figure 2.4, frozen
pellets were ground using a TissueLyser II (Qiagen) and resuspended in 400 µl methanol. For the
lipid extraction, 200 µl of the methanol suspension were used for the Bligh Dyer protocol
followed by a 0.9 % KCl wash (184). The organic phase was separated and dried to completion

51

under nitrogen and the pellet was resuspended in 400 µl chloroform. TAG was separated over 8
cm with 80:20:1 petroleum ether: diethyl ether: acetic acid, and total polar lipids were collected
by scraping the origin. An internal standard of 5 µg of pentadecanoic acid was added to each
tube containing scraped bands and fatty acid methyl esters (FAMEs) were prepared with 1M
methanolic HCl at 80°C for 30 minutes. FAMES were phase separated with hexane and 0.9%
NaCl, dried to completion under nitrogen and resuspended in 50-75 µl of hexane. Gas
chromatography and flame ionization detection (Agilent) were used to separate and quantify the
fatty acid profile (11).

Carbohydrate analysis
Cells were grown and harvested as described for the lipid analysis. Frozen ground pellets were
resuspended in 400 µl methanol. 20 µl of this methanol suspension, which was the same one
used for lipid analysis, and 10 µg of myo-inositol internal standard were dried under vacuum
before the addition of 150 µl 3.3N trifluoroacetic acid (TFA). TFA hydrolysis and the
preparation of alditol acetates were performed as described previously (186). Sugar alditol
acetates were quantified gas chromatography-mass spectrometry (Agilent) against the myoinositol internal standard and a 0.625-20 µg standard curve using target ion counts (186).

Analysis of gene expression by RNA-Seq
For each biological replicate we used a 50 ml culture grown in a 250 ml flask (~20-30 106 cells
ml-1). Cells were collected every 3 h and two biological replicates were harvested for each time
point. Cells were collected at 4,000 g for 10 min at 4°C, the cell pellet was resuspended in 1.5 ml
f/2 media and transferred to 2 ml tubes. The cells were centrifuged again at 18,000 g for 10 min
52

at 4°C and flash frozen in liquid nitrogen. Samples that were in the dark at the time of collection
were placed in black or amber tubes to prevent light exposure. RNA was extracted from ground
frozen pellets using the Omega eZNA Plant RNA kit (Omega Biotek). RNA quality was checked
with the Bioanalyzer (Agilent). All samples had a RIN of 6.9-7.9. Samples were sequenced at the
MSU-Research Technology Support Facility using an Illumina HiSeq 2500 and a single-end 50
nucleotide run. Eight samples were sequenced in each lane using a custom bar-coding, but the
two biological replicates from the same time point were run in separate lanes. The average
number of RNA-seq reads per sample was 23,434,157 and they ranged between 16,783,501 and
30,197,823. The reads of each of the 16 samples (8 time points, 2 samples each time point) were
mapped to the N. oceanica CCMP1779 V1 (11) genome using Tophat (187) with default
parameters except for intron length (min 13, max 8712) and max-multi-hits (1). Expression level
estimates in Fragments Per Kilobase of exon per Million fragments mapped (FPKM) was
calculated using Cufflinks (188) with parameter –I 8712.

Accession Numbers
Nannochloropsis oceanica CCMP1779 genome data and gene IDs are from the Nannochloropsis
oceanica CCMP1779_V1 (11) (https://bmb.natsci.msu.edu/about/directory/faculty/christophbenning/nannochloropsis-oceanica-ccmp1779/). For clarity, in the main text and figures, gene
IDs in the format NannoCCMP1779|xxxxx, have been abbreviated to the digits xxxxx. Raw read
data have been deposited in NCBI's Gene Expression Omnibus (189) and are accessible through
GEO

Series

accession

number

(http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE69460)

53

GSE69460

Analysis of cyclic gene expression
The determination of cycling genes was performed using COSPOT (154) and the discrete
Fourier transform (DFT) as described previously (144). In this parallel study of Chlamydomonas
reinhardtii, we had compared the performance of these methods, both separately and in
conjunction, using a gold standard set of cyclic genes (144). Since no such set was available for
N. oceanica CCMP1779 and the relationship between the COSPOT p-value and “cyclic score”
derived from the DFT appears to be the same (Figure 2.22), we applied the same cutoff
thresholds that we used in C. reinhardtii. A gene in N. oceanica CCMP1779 was called “cyclic”
if its expression vector had a COPSOT p-value < 0.02 or a cyclic score > 0.800, which is
equivalent to the p-value of 0.02 in a population of randomized expression vectors derived from
the N. oceanica FPKM data set.

Neither COSPOT nor DFT have high coverage of oscillatory expression profiles that peak only
at a single time point (i.e. narrow peak of expression). To detect these patterns, we used EdgeR
(190) to identify cases where read counts were non-uniformly distributed across time samples. A
gene was called sharply expressed if the read counts were significantly over-expressed (p-value
< 0.05) at one time point in the light-dark cycle relative to every other time point.

Analysis of gene expression by RT-qPCR
RNA was collected as described above and used to produce cDNA using the iScript cDNA
Synthesis Kit (Bio-Rad). Primers with annealing temperatures of 55ºC were designed for RTqPCR and checked for efficiency using serial dilutions of cDNA template and for specificity by
melting curve analysis (Table 2.2). We used an elongation factor encoding gene 10181 as

54

reference, since its expression was constitutive in our experiment (Data 2.1) and had been
previously suggested to be a constitutively expressed gene in Nannochloropsis species (Cao et
al., 2012). Quantitative PCR was performed using Sybr Green Master Mix (Life Technologiess)
and a Mastercyler ep realplex (Eppendorf). Relative gene expression was obtained by the ΔCT
method.

Flow cytometry analysis
Cells grown under diel conditions were fixed over night in 70% ethanol at 4ºC, washed twice in
phosphate-buffered saline pH 7.2 (PBS) and stained in PBS/0.1% Triton/1µg ml-1 4', 6'diamidino-2-phenylindole (DAPI). Flow cytometry analysis was conducted on an Influx sorter
(BD Biosciences, USA) using a 355nm UV laser and a 460/50 band pass filter, and 10,000 cells
were analyzed per sample. The percentage of cells in 1C (unreplicated haploid genome), S1 (first
round of DNA synthesis), 2C (replicated haploid genome), S2 (second round of DNA synthesis)
and 4C (cells with four haploid genomes) where estimated using WinList (Verity Software
House).

Microscopic analysis
Cells grown under diel conditions were harvested at ZT 18 in the dark. Cells were fixed in a
mixture of 4% (w/v) paraformaldehyde and 0.25% (v/v) glutaraldehyde prepared in PBS
overnight at 4 °C. DNA was stained with DAPI. The samples were analyzed with a Olympus
FluoView 1000 confocal laser scanning microscope with excitation at 405 nm and emission 440
nm. The three-dimensional optical sections were acquired at 0.45 μm step intervals. The final

55

images represent projection of an image stack. For image processing and analysis we used the
Olympus FluoView 1000 software.

Gene functional annotation
Candidate genes were first identified by BLASTp searches using functionally annotated
Phaeodactylum tricornutum (39), Ectocarpus siliculosus (191), N. gaditana (12) or N. oceanica
IMET1 (18) sequences and by PFAM domain analysis using HMMER3 (180), and checked by
reciprocal BLAST against NCBI. For the phylogenetic analyses sequences were aligned using
MUSCLE (192) and trees constructed using the maximum likelihood method implemented in
MEGA 5 (193), with bootstrap replicates and gap removal. For each phylogenetic analysis the
best combination of evolutionary model and rates was found using MEGA 5. Subcellular
localization was predicted using HECTAR (36). In addition, subcellular analysis for a few genes
was also performed using PredPlantPTS1 (194) and MitoProtII (195) and ASAFind (196). For
ASAFind, we used SignalP 4.1 with default settings.

Protein analysis
N. oceanica CCMP1779 liquid cultures were grown in f/2 medium to mid-log phase under light
dark cycles. 5.0x107 cells were transferred to a 1.7 ml tube and centrifuged at 13,000 g for 1
minute. Ground cell pellets were resuspended in 1 ml of Laemmli buffer, mixed by vortexing
and left at 22°C for 10 min. 20 µl (1 million cells) were loaded on a BioRad Mini-PROTEAN
TGX 10 well pre-cast 4%-20% gel (#456-1094). The LDSP protein was detected using an antiLDSP antibody (176) used in a 1:10,000 dilution. Detection occurred using a BioRad goat antiRabbit IgG HRP (170-6515, 1:20,000) and Thermo Fisher SuperSignal West Femto (#34095).

56

Blots were imaged on a BioRad ChemiDoc MP system. Direct-Blue 71 (197) staining was used
as indication of total protein content on the blots.

57

APPENDICES

58

Appendix 2.1. Chapter 2 figures and tables.

Figure 2.1. N. oceanica CCMP1779 cell growth under diel cycles.
Cells were grown in 12 h light:12 h dark diel cycle. Shaded areas indicate dark periods. (a) Cell
number (filled squares) and cell dry weight (DW, open circles) were quantified at different times
of the day. Values are the average of 3-6 independent cultures from three experiments. (b) Cell
growth during four days under diel conditions. Values are the average of three independent
cultures. Error bars represent SEM (some are smaller than the symbol).

59

Figure 2.2. Metabolite content under diel cycles.
Cells were grown in 12 h light:12 h dark cycles. Lipids were quantified as esterified fatty acids
associated with each lipid class. Shaded areas indicate dark periods. Values are the average of 36 different cultures from three independent experiments. Error bars represent SEM.

60

Figure 2.3. Confirmation of RNA-Seq measurements by reverse transcription quantitative
PCR.
Cells were grown in light:dark cycles and collected at the indicated times. RNA levels determined by
RT-qPCR were normalized against the elongation factor (10181) reference gene. RNA-seq and RTqPCR expression values were then normalized between 0 and 1 and represent the mean of 2 (RNASeq) or 2-3 (RT-qPCR) biological replicates plotted with SEM or range. LHC1, LIGHT
HARVESTING COMPLEX I (8367); α-TUBULIN (4716); CS, CELLULOSE SYNTHASE (5780);
KAS3, β-KETOACYL-ACP SYNTHASE (2094); DGAT5, DIACYLGLYCEROL
ACYLTRANSFERASE 5 (3915); ω3, ω3 DESATURASE (6416). Shaded areas represent dark periods.

61

Figure 2.4. Gene expression phase and GO terms enriched in cyclically expressed genes.
(a) The relative expression of each cycling gene (each row) across a 24-hour period (columns).
The two biological replicates were plotted as consecutive days. Genes were assigned to phase
clusters based on the predicted peak expression. Genes in each phase cluster were ordered using
hierarchical clustering. The white and black bars below indicate samples from the light and the
dark periods, respectively. FPKM values were normalized between 0 and 1. (b) The Fisher Exact
Test p-value (Benjamini-Hochberg adjusted) of GO term (row) enrichment for genes cycling in
each phase cluster (column). GO terms were ordered along the y-axis according to their first
enriched phase and clustered within each enriched phase. (c) The most enriched GO terms in
each phase with a p-value <0.005.

62

Figure 2.5. Phylogenetic analysis of N. oceanica CCMP1779 CDK-related proteins.
The phylogeny was inferred using the Maximum Likelihood method based on the General
Reverse Transcriptase + Freq. model (198). Branch bootstrap values (500 replicates) are
indicated. Initial tree(s) for the heuristic search were obtained by applying the Neighbor-Joining
method to a matrix of pairwise distances estimated using a JTT model (199). The branch lengths
are proportional to the number of substitutions per site. All positions with less than 95 % site
coverage were eliminated. Evolutionary analyses were conducted in MEGA5 (193). The ID
numbers for the diatom P. tricornutum (Pt) proteins are according to the annotated genomes at
JGI-release 2 as described in Huysman et al., (2010) (51). The names and ID numbers for the E.
siliculosus (Es) proteins are from Bothwell et al. (2010) (200). Arabidopsis thaliana (At), Oryza
sativa (Os) and Homo sapiens (Hs) sequences were retrieved from UniProt.

63

Figure 2.6. Phylogenetic analysis of N. oceanica CCMP1779 cyclin related proteins.
The phylogeny was inferred by using the Maximum Likelihood method based on the Whelan
And Goldman model (201). Initial tree(s) were generated and alignment positions filtered as in
Figure 2.5. Branches with bootstrap support (500 replicates) values higher than 50% are
indicated by (*). The branch lengths are proportional to the number of substitutions per site. All
positions with less than 95% site coverage were eliminated. Evolutionary analyses were
conducted in MEGA5(193). The names and ID numbers were obtained from the same sources as
detailed in Figure 2.5.

64

Figure 2.7. Cell cycle progression in light:dark cycles.
(a) Heatmap displaying relative gene expression levels of genes involved in cell division in N.
oceanica CCMP1779. Early, middle and late, relate to phases in the cell cycle. (b) DNA content
per cell measured as DAPI fluorescence using flow cytometry at different times of day (ZT,
hours after lights on). (c) Estimation of the percentage of cells in 1C (unreplicated haploid
genome), S1 (first round of DNA synthesis) and 2C (replicated haploid genome)- S2 (second
round of DNA synthesis)- 4C (cells with four haploid genomes). (d) Images of DAPI stained N.
oceanica CCMP1779 cells harvested at ZT18, containing two or four nuclei. Three-dimensional
optical sections were acquired at 0.45 μm step intervals. The final images represent projection of
an image stack. The inserts are the corresponding bright field images. Bars=1.5 µm. (e)
Organelle division genes. For (a) and (e) FPKM values were normalized between 0 and 1 and
used for hierarchical cluster analysis implemented in R. The two biological replicates were
plotted as consecutive days to visualize variability. Numbers indicate the digits of the gene IDs.
Descriptions and expression values can be found in Data 2.2. (*) Proteins discussed in the text.

65

Figure 2.8. Time lapse images of a N. oceanica CCMP1779 cell undergoing division into
four daughter cells.
Bright field microscopy using a Leica DMRA2 microscope and a 100x objective. Scale bar = 3
µm. * Non-dividing cell.

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Figure 2.9. Transcription regulation of genes involved in central carbon metabolism in N.
oceanica CCMP1779 under diel conditions.
Arrow and enzyme name colors indicate phase of expression as determined visually. Parallel
arrows with different colors indicate multiple genes expressed at different times of day encoding
for one enzyme. Expression data can be found in Data 2.2. Subcellular localization was based on
HECTAR analysis. In addition, subcellular analysis for a few proteins was also performed using
PredPlantPTS1 and MitoProtII. Enzyme abbreviations: ACC, acetyl co-A carboxylase; ACL,
ATP citrate lyase; ACS, acetyl-coA synthetase; ADH, aldehyde dehydrogenase; ALD, aldolase;
CA, carbonic anhydrase; CS, cellulose synthase; DES, desaturase; DGDS, digalactosyl-1,2,sndiacyl-glycerol synthase; ELO, elongase; ENO, enolase; FAS, fatty acid synthase; FbP, fructose
1,6-bisphosphase; FK, fructokinase; GAPDH, glyceraldehyde 3-phosphase dehydrogenase; GBS,
β-1,3-glucan synthase ; GPAT, glycerol-3-phosphate acyltransferase; LPAAT, lysophosphatidic
acid acyltransferase; M2HD, mannitol 2-dehydrogenase; MDH, malate dehydrogenase; ME,
malic enzyme; MGDGS, monogalactosyl-1,2sn-diacylglycerol synthase; MPDH, mannitol-1phosphate dehydrogenase; MPP, manitol-1-phosphatase; PC, phosphoenolpyruvate carboxylase;
PCK, pyruvate carboxykinase; PDC, pyruvate decarboxylase; PDH, pyruvate dehydrogenase;
PFK, phosphofructokinase; PGI, phosphoglucoisomerase; PGK, phosphoglycerate kinase;
67

Figure 2.9 (cont'd)
PGLM,
phosphoglycerase
mutase;
PGLM,
phosphoglycerate
mutase;
PGM,
phosphoglucomutase; PK, pyruvate kinase; PP, phosphatidate phosphatase; PPDK, pyruvate
phosphate dikinase; PYC, pyruvate carboxylase; SLS, sulfolipid synthase; TPI, triose-phosphase
isomerase; TPT, triosephosphate transporter; UGPase, UDP-glucose pyrophosphylase.
Metabolite abbreviations: 16:0-ACP; 16:0 fatty acid; 2PGA, 2-phosphoglycerate; 3PGA, 3phosphoglycerate; 6PG, 6-phosphogluconate; Ac-CoA, acetyl Co-A; Ace, acetate; Citr, citrate;
DAG,
diacylglycerol
phosphate;
DGDG,
digalactosyldiacylglycerol;
DGTS,
diacylglyceryltrimethylhomoserine; DHAP, dihydroxyacetone phosphate; F1,6P, fructose 1,6bisphosphate; F6P, fructose 6-phosphate; FA, fatty acid; Fru, fructose; G1,3-P, glycerase 1,3bisphosphate; G1P, glucose 1-phosphate; G3P, glycerate 3-phosphate; G6P, glucose 6phosphate; Glu, glucose; LC-PUFA, long chain polyunsaturated fatty acids; M1P, mannitol 1phosphate; Mal, malate; MGDG, monogalactosyldiacylglycerol; Mnl, mannitol; OAA,
oxaloacetate; PEP, phosphoenolpyruvate; Pyr, pyruvate; SQDG, sulfoquinovsyldiacylglycerol;
TAG, triacylglycerol; UDPG, UDP-glucose.

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Figure 2.10. Phylogenetic analysis of N. oceanica CCMP1779 SLC4 related proteins.
The phylogeny was inferred as in Figure 2.5. Branch bootstrap values (500 replicates) are
indicated. Initial tree(s) for the heuristic search were obtained automatically by applying
Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using a JTT
model, and then selecting the topology with superior log likelihood value. A discrete Gamma
distribution was used to model evolutionary rate differences among sites. The rate variation
model allowed for some sites to be evolutionarily invariable. The branch lengths are proportional
to the number of substitutions per site. All positions with less than 95% site coverage were
eliminated. Evolutionary analyses were conducted in MEGA5 (193). Identifiers are from
Genbank with the exception of N. oceanica CCMP1779 sequences.

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Figure 2.11. Phylogenetic analysis of N. oceanica CCMP1779 malic enzyme related
proteins.
The phylogeny was inferred as in Figure 2.5. Branch bootstrap values (500 replicates) are
indicated. The search for the initial trees and the modeling of evolutionary rate differences were
performed as described in Figure 2.5. The branch lengths are proportional to the number of
substitutions per site. All positions with less than 95% site coverage were eliminated.
Evolutionary analyses were conducted in MEGA5. Protein identifiers are from UniProt or NCBI
gi sequence identifiers with the exception of N. oceanica CCMP1779 sequences.

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Figure 2.12. Heatmap displaying relative expression levels of putative glycosyl transferases
and glycosyl hydrolases encoding genes.
Expression values were analyzed as described in Figure 2.7. Row descriptions indicate gene IDs.
CS, cellulose synthase; GT48, glycosyl transferase 48 family gene.

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Figure 2.13. Phylogenetic analysis of the N. oceanica CCMP1779 β-1,3-glucan synthase
related protein.
The phylogeny was inferred as described for Figure 2.6. Branch bootstrap values (500 replicates)
are indicated. The search for the initial trees and the modeling of evolutionary rate differences
were performed as described in Figure 2.6. The branch lengths are proportional to the number of
substitutions per site. All positions with less than 95% site coverage were eliminated.
Evolutionary analyses were conducted in MEGA5 (193). Protein identifiers are NCBI gi
sequence identifiers or UniProt accession numbers for the Ectocarpus sequences with the
exception of N. oceanica CCMP1779 sequences.

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Figure 2.14. Expression of genes potentially involved in the mannitol cycle.
FPKM values were normalized between 0 and 1. MPDH, mannitol 1-phosphate dehydrogenase;
MPP, mannitol 1-phosphate phosphatase; M2DH, mannitol 2-dehydrogenase; FK, fructokinase.
Numbers indicate the digits of the gene IDs.

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Figure 2.15. Gene expression of genes involved in lipid biosynthesis under light:dark cycles.
Expression values were analyzed as described in Figure 2.7. Descriptions and expression values
can be found in Data 2.2. Chl, chloroplast; PDC, pyruvate decarboxylase comples; FAS, fatty
acid synthase; Mito, mitochondria; ACC, acetyl-CoA carboxylase components; ER,
endoplasmatic reticulum; TAG, triacylglycerol. Numbers indicate digits in the gene IDs.

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Figure 2.16. Phylogenetic analysis of the N. oceanica CCMP1779 type I FAS-like genes.
The phylogeny was inferred as in Figure 2.6. Branch bootstrap values (500 replicates) are
indicated. The search for the initial trees and the modeling of evolutionary rate differences were
performed as described in Figure 2.6. The tree is drawn to scale, with branch lengths measured in
the number of substitutions per site. All positions with less than 95% site coverage were
eliminated. Evolutionary analyses were conducted in MEGA5 (193). Identifiers are from
Genbank with the exception of N. oceanica CCMP1779 sequences, and the Coccomyxa
sequence (JGI Phytozome Coccomyxa subellipsoidea C-169 v2.0). PKS, polyketide synthases;
FAS, type I fatty acid synthases; Euk, eukaryotes; Prok, prokaryotes.

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Figure 2.17. LDSP expression under light:dark cycles.
(a) LDSP RNA levels. RNA levels determined by RT-qPCR were normalized against the elongation
factor (10181) reference gene. RNA-seq and RT-qPCR expression values were then normalized
between 0 and 1 and represent the mean of 2 (RNA-Seq) or 2-3 (RT-qPCR) biological replicates
plotted with SEM or range. (b) Quantification of LDSP protein content. Values are the average ±
range of two biological replicates. (c) Immunodetection of LDSP protein levels under diel
conditions using an anti-LDSP (αLDSP) antibody. Proteins extracted from one million cells were
loaded on each well. Direct-Blue 71 (DB71) staining was used as a total protein stain. Shaded
areas indicate dark periods.

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Figure 2.18. Gene expression of genes involved in fatty acid degradation under light:dark
cycles.
Expression values were analyzed as described in Figure 2.7. Descriptions and expression values
can be found in Data 2.2. Perox., peroxisome; TCA, tricarboxylic acid cycle. Numbers indicate
digits of gene IDs.

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Figure 2.19. Heatmap displaying relative expression levels of genes involved in the lipid
degradation.
Expression values were analyzed as described in Figure 2.7. Labels indicate gene IDs. * Indicate
genes potentially involved in β-oxidation. Expression values can be found in Data 2.2.

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Figure 2.20. Cyclic expression of transcription regulators.
(a) Percent of cycling transcription regulators under light:dark cycles as determined by COSPOT
and DFT. Relative expression level of blue light receptors (b), Sigma70-like factors (c) and
mTERFs (d). FPKM values were normalized between 0 and 1. The values represent the average
of two biological replicates. Shaded region represent dark periods. In (c) and (d) labels indicate
the digits of the gene IDs.

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Figure 2.21. Heatmap displaying relative expression levels of genes involved in chromatin
modification.
Expression values were analyzed as described in Figure 2.7. Labels indicate gene IDs,
descriptions indicate conserved domains identified using HMMER (180).

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Figure 2.22. The relationship between the cyclic score derived from the DFT and negative
log transformed p-value from COSPOT.
A power-law trendline is plotted against the data (equation in upper left hand corner). The results
of the parallel analysis in C. reinhardtii show a similar power law relation (y = 2.4871x2.1549)
between COSPOT and the DFT with R2 > 0.70.

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Table 2.1. Prediction of cyclic gene expression.
The number of cyclic genes predicted by COSPOT, the DFT, and the combination of both
methods, as well as the period mean and phase peaks for each set of predictions. A gene was
called “cyclic” if its expression vector had a COPSOT p-value < 0.02 or a cyclic score > 0.800,
which is equivalent to the p-value of 0.02 in a population of randomized expression vectors
derived from the N. oceanica CCMP1779 FPKM data set.

Table 2.2. Primers used for RT-qPCR in Chapter 2.
The target gene is listed in the first column, primer name in the second column, and the primer
sequence in the third column.

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Appendix 2.2. Chapter 2 datasets.
Supplemental datasets are available online from:
http://onlinelibrary.wiley.com/doi/10.1111/tpj.12944/full

Data 2.1. Expression of N. oceanica CCMP1779 under light:dark cycles and prediction of cyclic
gene expression.

Data 2.2. Expression patterns and estimation of subcellular localization of manually annotated
genes.

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Chapter 3. A toolkit for Nannochloropsis oceanica CCMP1779 enables gene stacking and
genetic engineering of the eicosapentaenoic acid pathway for enhanced long-chain
polyunsaturated fatty acid production

ABSTRACT
Nannochloropsis oceanica is an oleaginous microalga rich in ω3 long-chain polyunsaturated
fatty acids (LC-PUFAs) content, in the form of eicosapentaenoic acid (EPA). We identified the
enzymes involved in LC-PUFA biosynthesis in N. oceanica CCMP1779 and generated
multigene expression vectors aiming at increasing LC-PUFA content in vivo. We isolated the
cDNAs encoding four fatty acid desaturases (FAD) and determined their function by
heterologous expression in S. cerevisiae. To increase the expression of multiple fatty acid
desaturases in N. oceanica CCMP1779 we developed a genetic engineering toolkit that includes
an endogenous bidirectional promoter and optimized peptide bond skipping 2A peptides. The
toolkit also includes multiple epitopes for tagged fusion protein production and two antibiotic
resistance genes. We applied this toolkit, towards building a gene stacking system for N.
oceanica that consists of two vector series, pNOC-OX and pNOC-stacked. These tools for
genetic engineering were employed to test the effects of the overproduction of one, two or three
desaturase encoding cDNAs in N. oceanica CCMP1779 and prove the feasibility of gene
stacking in this genetically tractable oleaginous microalga. All FAD overexpressing lines had
considerable increases in the proportion of LC-PUFAs, with the overexpression of Δ12 and Δ5
FAD encoding sequences leading to an increase in the final ω3 product, EPA.

INTRODUCTION
Long-chain polyunsaturated fatty acids (LC-PUFAs) are hydrocarbon acyl chains (18-22
carbons) containing multiple cis double bonds. The double bond closest to the methyl (ω,
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omega-) end of a fatty acid, usually 3 or 6 carbons, differentiates LC-PUFAs into ω3 or ω6
classes, respectively. Evidence suggests consuming LC-PUFAs in adequate amounts with a
balanced ratio among LC-PUFAs is essential for human physical and mental health (202), while
current diets are often low in ω3 LC-PUFAs.
Currently seafood is the major source of ω3 LC-PUFAs, particularly EPA (20:5; number
of carbons:number of double bonds) and docosahexaenoic acid (DHA, 22:6). However
overfishing, habitat destruction, and pollution have reduced wild fish stocks, while increasing
human populations drive a record demand for LC-PUFA nutrients (203, 204). Though fish are
rich in ω3 fatty acids, the majority of LC-PUFAs acyl chains originate at the base of the food
chain in marine microalgae (205) (205, 206). Aquaculture of microalgae is an emerging source
of LC-PUFAs for fish farming or direct human consumption, and understanding the biosynthetic
pathways and factors that influence LC-PUFA metabolism in algae will enable increased
production from these organisms (2).
One promising source of LC-PUFAs are oleaginous microalgae of the Nannochloropsis
genus, which have a high EPA content (177, 207, 208). In Nannochloropsis species, EPA is
associated with membrane lipids, particularly monogalactosyl diacylglycerol (MDGD) and the
betaine lipid,diacylglyceryl-N,N,N-trimethylhomoserine (DGTS) (11, 54, 209, 210). Despite the
research interest and economic implications, the EPA biosynthetic pathway in Nannochloropsis
species is only partially characterized. Gene annotation and 14C-acetate pulse-chase labeling
suggest that EPA biosynthesis occurs via the ω6 desaturation and elongation pathway and is
localizedin the endoplasmic reticulum, with the phospholipids, phosphatidylcholine (PC) and
phosphatidylethanolamine (PE), as substrates for fatty acid desaturases (FADs) (11, 91, 209).

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Genome annotation identified putative components of the EPA biosynthetic pathway including
Δ9, Δ12, Δ6, Δ5 and ω3 FADs, and a Δ6 fatty acid elongase (FAE) in N. oceanica CCMP1779
(11). Only the N. oceanica Δ6 and Δ12 FADs have been isolated and expressed in S. cerevisiae
to corroborate their predicted functions (14, 91).
Genetic engineering can increase the production of LC-PUFAs in plants (211-213), fungi
(124, 214, 215), and microalgae (102, 216-219). For example, the overexpression of the Δ12
FAD encoding cDNA using a stress inducible promoter in N. oceanica caused an increase of the
18:2 fatty acid content of PC during normal growth and diversion of 18:2 into triacylglycerol
(TAG) following nitrogen deprivation (91). Furthermore, ω3 LC-PUFA production has been
introduced into oleaginous yeast and plants by multiple gene expression systems (124, 220, 221).
The effective diversion of metabolism into LC-PUFA production is likely to require coexpression of multiple genes encoding enzymes that catalyze different desaturation and
elongation steps (2, 222, 223).
Metabolic engineering of multigene pathways has been developed using a variety of
strategies (224, 225). Commonly, each transgene is placed under the regulation of separate
promoters and terminators, and single gene expression plasmids are independently introduced
into the host or assembled into a larger multigene expression plasmid (224). However, other
strategies exist to express multiple genes. For example, bidirectional promoters allow compact
assembly of coregulated gene pairs and have been utilized in a number of transgenic strategies,
including in Nannochloropsis species (14, 24).
An obstacle to compact multigene expression systems in eukaryotes is the requirement of
each transgene to be encoded in individual mRNAs. However, introducing short viral 2A peptide
coding sequences (226, 227), prevents the formation of a peptide bond during translation,

86

allowing multiple proteins to be encoded by a single mRNA molecule, which has increased the
efficiency of multiple coding sequence expression in eukaryotic cells.Advantages of using 2A
peptides include: their compact size of 20-60 amino acids (aa), high efficiency in most
eukaryotes tested to date, low toxicity, and stoichiometric co-expression of linked proteins (100,
226-229). However, the efficiency of peptide bond skipping varies depending on the 2A peptide
and the host combination, therefore, optimization for the respective host is needed for the
approach to become practical.
Using state-of-the-art technology, we developed vectors that combinea highly active
unidirectional promoter (EF) or a bidirectional promoter (Ribi) with a variety of reporter proteins
and epitope tags for optimized transgene expression in N. oceanica CCMP1779. Moreover, we
optimized a viral 2A peptide for polycistronic expression to generate a multigene expression
system for this oleaginous microalga. This vector toolkit was successfully used to manipulate the
EPA biosynthesis pathwayin N. oceanica CCMP1779.

RESULTS
Genes encoding enzymes of the eicosapentaenoic acid biosynthesis pathway are coexpressed
The identification of ω6 intermediates (20:4Δ5,Δ8,Δ11,Δ14) (Figure 3.1a) points to the presence of an
ω6 pathway for EPA biosynthesis in N. oceanica CCMP1779 (Figure 3.1b). We isolated the
cDNAs for the 5 FADs and a putative Δ6 fatty acid elongase (FAE) proposed to be involved in
LC-PUFA biosynthesis in N. oceanica CCMP1779 (Figure 3.1b). These cDNA sequences served
to update the gene models of the Δ9, Δ12, Δ6, Δ5, ω3 FADs, and Δ6 FAE. Their updated cDNA
sequences were deposited at NCBI with the accession numbers KY214449, KY214450,

87

KY214451, KY214453, KY214454, and KY214452 respectively. Using the corrected gene
models, we observed that the FAD genes are highly co-expressed under light:dark conditions
with a maximum expression 6 hours after dawn (Figure 3.1c).
Computational tools and manual examination were used to predict functional domains,
subcellular localization, and transmembrane sequences in these proteins in support of their initial
functional annotations (Figure 3.2). The FADs contain typical fatty acid desaturase domains, in
particular the crucial three histidine boxes for coordinating a diiron center in the active site (230,
231). Moreover, the Δ6 and Δ5FADs contain a cytochrome b5 domain that donates electrons for
desaturation as observed for front end desaturases of eukaryotic origin, as well as glutamine
substitutions in the third histidine box characteristic of front end desaturases (232-234).
The Δ6 FAE contains an ELO family elongase domain, which is involved in very long
chain fatty acid elongation and sphingolipid formation (235, 236). Further evidence of a possible
elongase function is provided by the presence of FLHXYHH and MYSYY motifs characteristic
of Δ6 and Δ5 fatty acid elongases; the first is positioned with an upstream glutamine
characteristic of PUFA elongases, and the latter is typically found in microalga Δ6 and Δ5 fatty
acid elongases (234, 237, 238) (Figure 3.2).
All the N. oceanica CCMP1779 EPA biosynthesis proteins are predicted to contain
membrane spanning domains by TMHMM2 (239). The heterokont specific subcellular
localization algorithm HECTAR (36) predicted endoplasmic reticulum localization signals for
the Δ12 and Δ6 FADs, and Δ6 FAE (Figure 3.2).

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N. oceanica CCMP1779 FADs catalyze the production of LC-PUFAs in yeast
In order to test the biological activity of the putative FADs and FAE from N. oceanica
CCMP1779, the pathway was reconstituted in the heterologous host Saccharomyces cerevisiae
using a gene stacking strategy (Figure 3.3a). S. cerevisiae contains a single Δ9 FAD which
produces 16:1Δ9 and 18:1Δ9(240). Therefore, to generate EPA from the endogenous 18:1Δ9 it is
necessary to introduce four additional desaturases and an elongase. Towards this end we coexpressed cDNAs encoding the Δ12, Δ6 and Δ5, ω3 FADs and the Δ6 FAE under the control of
galactose inducible promoters in the S. cerevisiae strain InvSc1 (Figure 3.3a).
The presence of these constructs in the absence of galactose induction or the introduction
of a LacZ expression control vector (Sc-LacZ strain) did not alter the cellular fatty acid
composition of S. cerevisiae (Figure 3.3b, Figure 3.4a, Table 3.1). Induction of the Δ12 and Δ6
FADs led to the production of 18:2Δ9,Δ12(1.8% of total fatty acids) and 18:3Δ6,Δ9,Δ12 (4.1%) in the
Sc-Δ12+Δ6 strain (Figure 3.2b). The putative Δ6 FAE was introduced in combination with Δ12
and Δ6 FADs resulting in elongation of 18:3Δ6,Δ9,Δ12 to 20:3Δ8,Δ11,Δ14 (di-homo gamma
linolenicacid, DGLA) in the Sc-Δ12+Δ6+E6 strain (Figure 3.3b). Finally, co-expression of the
Δ12, Δ6, Δ5, ω3 FADs and the Δ6 FAE in the Sc-Δ12+Δ6+E6+Δ5+ω3 strain resulted in the
formation of EPA (20:5Δ5,Δ8,Δ11,Δ14,Δ17) (0.1%) (Figure 3.3b, Table 3.1). Reconstruction of this
LC-PUFA pathway in S. cerevisiae documented the combined functionality of the proteins as
predicted from their respective sequences.
Interestingly, the 20:4 fatty acid produced by Sc-Δ12+Δ6+E6+Δ5+ω3, 20:4Δ8,Δ11,Δ14,Δ17
differed from the major 20:4Δ5,Δ8,Δ11,Δ14 found in Nannochloropsis (11)(Figure 3.1a, Figure 3.3b).
This difference could be due to the ω3 FAD acting on 20:3, preceding the Δ5 reaction when
present in S. cerevisiae. To test this hypothesis, we expressed the Δ5 and ω3 FADs individually

89

and in combination in yeast to generate the strains Sc-Δ5+ω3, Sc-Δ5, and Sc-ω3. When ScΔ5+ω3 was grown in the presence of exogenous 20:3Δ8,Δ11,Δ14, this strain was able to produce
20:4Δ8,Δ11,Δ14,Δ17 and EPA (20:5Δ5,Δ8,Δ11,Δ14,Δ17) establishing the activity of the final two desaturases
(Figure 3.4a, Table 3.1). To further examine the substrate specificity of the Δ5 and ω3 FADs,
yeast expressing the individual FADs were supplied 20:3Δ8,Δ11,Δ14 and either 20:4Δ8,Δ11,Δ14,Δ17 or
20:4Δ5,Δ8,Δ11,Δ14, individually or in combination (Figure 3.4b-d, Table 3.1). When supplied with
20:3Δ8,Δ11,Δ14, Sc-Δ5 produced 20:4Δ5,Δ8,Δ11,Δ14 and Sc-ω3 produced 20:4Δ8,Δ11,Δ14,Δ17 (Figure 3.4b,
Table 3.1). Supplying Sc-Δ5 and Sc-ω3 with 20:4Δ8,Δ11,Δ14,Δ17and 20:4Δ5,Δ8,Δ11,Δ14 respectively,
resulted in the production of EPA (20:5Δ5,Δ8,Δ11,Δ14,Δ17) (Figure 3.4c, Table 3.1). Sc-Δ5 supplied
with 20:3Δ8,Δ11,Δ14 and 20:4Δ8,Δ11,Δ14,Δ17 resulted in the respective products 20:4Δ5,Δ8,Δ11,Δ14 and EPA
(20:5Δ5,Δ8,Δ11,Δ14,Δ17) (Figure 3.4d, Table 3.1). Supplying Sc-ω3 with 20:3Δ8,Δ11,Δ14 and
20:4Δ5,Δ8,Δ11,Δ14 resulted in production of 20:4Δ8,Δ11,Δ14,Δ17 and EPA (20:5Δ5,Δ8,Δ11,Δ14,Δ17) (Figure
3.4d, Table 3.1). These experiments revealed that the Δ5 FAD can accept either ω3
(20:4Δ8,Δ11,Δ14,Δ17) or ω6 (20:3Δ8,Δ11,Δ14) substrates, and the ω3 FAD can accept either 20:3Δ8,Δ11,Δ14
or 20:4Δ5,Δ8,Δ11,Δ14 substrates when produced in yeast.

A vector toolkit for multigene expression in Nannochloropsis species.
To facilitate the co-expression of multiple coding sequences and characterization of the
respective enzymes, we generated a set of vectors to overexpress multiple FADs in N. oceanica
(Figure 3.5a). For single transcript expression vectors we chose the elongation factor promoter
(EFpro) (NannoCCMP1779_10181) due to its high constitutive activity during light:dark cycles
(Figure 3.5b). We generated a vector series (pNOC-OX) encoding a variety of reporter proteins
and epitope tags, including hemagglutinin (HA), Green Fluorescent Protein (eGFP), Cyan

90

Fluorescent Protein (Cerulean variant), Yellow Fluorescent Protein (Venus variant), and the
ultra-bright codon optimized (Table 3.2) NanoLuciferase (Nlux) (97), flanked by glycine-serineglycine encoded linkers and a set of compatible restriction sites (AscI/HpaI, and MluI/NruI)
which enable translational fusion of the epitope tags to either the C or N terminus of the targeted
protein (Figure 3.5a).
To identify candidate bidirectional promoters in N. oceanica, a custom python script
(Data 3.1) was used to find diverging gene pairs that co-expressed (Table 3.3). We selected the
intergenic region between two ribosomal subunits as a promising candidate bidirectional
promoter (Ribi) due to a high degree of co-expression and moderate expression levels throughout
the light:dark cycle of the respective gene pair (NannoCCMP1779_9669,
NannoCCMP1779_9668) (Figure 3.5b). The Ribi promoter (after modification to remove MluI
and NruI recognition sites, Figure 3.6) was assembled with the best performing selection marker
P2A cassette coding sequences (BleR-P2A(60) and HygR-P2A(60)) and the toolkit epitope tag
coding sequences to generate the pNOC-stacked vector series (Figure 3.5a).
To test the newly developed vectors we transformed N. oceanica CCMP1779 with
pNOC-OX-CFP, pNOC-OX-Nlux, and pNOC-stacked-Nlux. Production of CFP and Nlux was
confirmed in selected strains by immunoblotting with α-GFP and α-HA antibodies respectively
(Figure 3.5c, Figure 3.7a). In order to assess the activity of the selected promoters, transformants
of N. oceanica with pNOC-OX-Nlux and pNOC-stacked-Nlux were screened for their
luminescence signals. To quantitatively compare Nlux reporter signal from each promoter,
luminescence from an equal number of cells of pNOC-OX-Nlux and pNOC-stacked-Nlux
transformants was measured. Reflecting the higher activity level of EFpro than Ribi, the

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luminescence of Nlux in pNOC-OX-NLux was greater than in pNOC-stacked-Nlux lines (Figure
3.7b).
Viral derived 2A peptides are used for polycistronic expression of multiple transgenes in
eukaryotes and are widely used to tie resistance markers to the production of target proteins. We
first determined the ribosomal skipping efficiency of the three mostly commonly used 2A
peptides of ~20 aa, designated 2A peptide(amino acid length). The F2A(24), T2A(18), and
P2A(19) coding sequences were appended to the zeocin/bleomycin (BleR) and/or hygromycin
(HygR) resistance marker genes followed by insertion of the HA-tagged firefly luciferase (Flux)
coding sequence (Figure 3.8a). Introduction of these constructs into N. oceanica CCMP1779
resulted in zeocin or hygromycin resistant colonies, of which those with high luciferase activity
were selected for further study. Immunoblotting detected full-length BleR-2A-Flux protein, and
only small amounts of released Flux in the first round of screening (Figure 3.8b, Figure 3.9).
Ribosomal skipping efficiency was less than 10% for F2A, and T2A sequences, while P2A had
an efficiency of 10-30% (Figure 3.9c). In order to increase ribosomal skipping efficiency the Nterminal F2A peptide encoding sequence was extended to 58 aa, and the P2A sequence to 30 aa,
45 aa, and 60 aa. These changes enhanced the ribosomal skipping efficiency for F2A(58) to
~20%, for P2A(30) to ~40%, for P2A(45) to ~50%, and for P2A(60) to >50% (Figure 3.8b,
Figure 3.9). Based on these results, the extended P2A sequence was selected as the most
promising 2A peptide for use in N. oceanica CCMP1779.

Overexpression of EPA biosynthesis genes in N. oceanica CCMP1779
We first generated lines expressing the Δ9, Δ12, and Δ5 FADs under the control of the EF
promoter in N. oceanica CCMP1779 (designated DOX9, DOX12, and DOX5 lines, respectively)

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(Figure 3.10a). Δ9 FAD coding sequence was cloned into pNOC-P2A(30) (Figure 3.8) to
generate the pNOC-DOX9 vector. The Δ12 and Δ5 FAD coding sequences were placed in
overexpression vectors with C-terminal epitope tags (pNOC-DOX12-HA, pNOC-DOX12-CFP,
pNOC-DOX5). Lines with changes in their fatty acid profiles were selected for further studies.
The DOX12 and DOX5 lines produced appropriately sized proteins (Figure 3.10b). However, we
did not detect full-length HA-Δ9 FAD in DOX9 lines but only several small molecular weight
polypeptide products (Figure 3.10b), which could be due to degradation of the tagged protein.
Confocal microscopy of DOX5 and DOX12 lines revealed that the desaturase CFP fusion
proteins have an ER subcellular location, as indicated by overlap with an ER specific marker
dye, supporting the protein annotation and predicted location (Figure 3.11).
In order to test whether overproduction of more than one FAD would improve LC-PUFA
accumulation in N. oceanica CCMP1779, we transformed wild-type and the DOX5 strain B3
with a desaturase stacking vector, containing the HA-Δ9 FAD and Δ12 FAD-HA coding regions
under the control of the Ribi bidirectional promoter (pNOC-stacked-DOX9+12) (Figure 3.10a,c).
DOX9+12 and DOX5+9+12 lines with changes in their fatty acid profile were selected for
further analyses. Immunoblotting of selected lines detected full-length Δ12 FAD-HA and HAΔ9 FAD peptides in all lines, and Δ5 FAD-CFP in the triple FAD overexpression lines (Figure
3.10d).
To determine the level of overexpression, mRNA levels were quantified by qPCR (Figure
3.12a). Lines transformed with the pNOC-OX vectors (Figure 3.5a), resulted in expression up to
3.5 fold higher than the wild-type, while DOX9 overexpression using pNOC-P2A(30) led
to~8fold increase in mRNA. In the DOX9+12 lines, the Δ12 FAD mRNA content was 10-30

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times that of the wild-type and displayed large differences between the lines, while the Δ9 FAD
expression was increased 2-4 fold.

Increase in LC-PUFA content in FAD overexpressing lines
Fatty acid profiling of wild-type, empty vector controls (EV), and DOX lines showed that an
increase in FAD production altered fatty acid proportions (Table 3.4). While EV controls did not
cause alterations to the fatty acid profile compared to the wild-type, the overexpression of Δ9
FAD led to a small increase in the mol percent of its product 18:1Δ9 and the overexpression of the
Δ12 or Δ5 FADs resulted in a higher LC-PUFA fraction. We did not observe a further increase in
LC-PUFAs in the stacking lines, DOX9+12 and DOX5+9+12, and these lines had a similar ~
25% increase in EPA (20:5Δ5,Δ8,Δ11,Δ14,Δ17)and 35% increase in LC-PUFAs mol ratio as the single
FAD overexpressing lines (Table 3.4).
To further assess the impact of FAD overproduction, we measured cell growth over
several days (Figure 3.12b). The growth rate of EV, DOX5, DOX12, DOX9+12, and
DOX5+9+12 lines, but not DOX9, was increased with respect to the wild-type (Figure 3.13).
This effect could be related to the decreased average cell sizes of these lines (Figure 3.12c). Total
cellular fatty acid content per cell was likewise decreased in DOX5, DOX12, DOX9+12, and
DOX5+9+12 lines, while EV and DOX9 lines were unaffected (Table 3.5).

DISCUSSION
Expanding transgenic techniques in N. oceanica
A strong biotechnological interest has driven development of transgenic tools for
Nannochloropsis species in recent years (11, 13, 14, 19, 79). However, a comprehensive and

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modular protein production toolkit vector set allowing the engineering of convenient epitope
tagged fusion proteins was lacking. Such a toolkit with multiple genetic reporters, selection
markers, two additional promoters, and several strategies for multi-gene expression is now
available.
We tested two new promoters for protein overproduction in N. oceanica CCMP1779. To
enhance expression of single transgenes in Nannochloropsis species, engineers have used several
endogenous promoters including the lipid droplet surface protein (LDSP) (11, 91) β-tubulin, heat
shock protein 70, and ubiquitin extension promoters (UEP) (13, 79). We tested an elongation
factor promoter that displays high and stable expression throughout light:dark cycles (15, 45),
and has been utilized in diverse organisms (241, 242), including diatoms (243) . A variety of
promoters allow gene expression at different levels and in response to different environmental
conditions. Furthermore, repeated use of transgenic elements can lead to genetic instability and
as gene stacking techniques mature in Nannochloropsis species multiple promoters are desirable
to modulate the expression of many genes.
Bidirectional promoters are extremely useful for multi-gene expression. The endogenous
bidirectional promoter (VCP) between a pair of violaxanthin/chlorophyll a-binding proteins
(NannoCCMP1779|4698 and NannoCCMP1779|4699) has been used to drive resistance genes
(14) and has been paired with coding sequences for fluorescent proteins with subcellular location
tags (24). We have tested the ribosomal component S15 and S12 bidirectional promoter (Ribi)
and identified several additional bidirectional promoters that may also be suitable for transgenic
expression including histones, other VCPs, and nitrate reductase (Table 3.3). These bidirectional
promoters can be used for selection of high target transgene expression or for reducing potential
silencing effects of transgenes by linking transgene production to a resistance marker.

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Transgenic techniques in a number of eukaryotes have exploited 2A peptides, which
enable a single transcript to encode multiple discrete protein products. A variety of 2A peptides
have been identified and exploited with differing levels of efficiency in a number of eukaryotes,
including yeast (244), animals (226, 228), plants (245), insects (246), and algae (101, 247).
Applying this approach to a heterokont, we have successfully developed an extended P2A
sequence that is efficient for peptide bond skipping in N. oceanica CCMP1779. When placed
between a resistance gene and firefly luciferase reporter, we obtained skipping efficiency of
greater than >60%. Moreover, the overproduction of the Δ9 FAD coding sequence downstream
of BleR-P2A(30) resulted in non-significant increase in 18:1Δ9, indicating enzymes produced as a
P2A mediated fusion with a resistance gene are functional in N. oceanica CCMP1779. Our
extensions of the P2A sequence showed diminishing increases in cleavage efficiency suggesting
an optimal length has been found (Figure 3.9). Therefore, the P2A peptide is a promising tool for
producing discrete proteins from a single reading frame in N. oceanica CCMP1779, and further
mutational studies of the P2A sequences could potentially yield higher performing variants.
We anticipate that the development of the pNOC-OX and pNOC-stacked expression vectors will
facilitate research in Nannochloropsis species and lay the foundation for combinatorial genetic
engineering in an oleaginous microalga chassis for synthetic biology.

Characterization of the EPA biosynthetic pathway
As an example for multi-gene metabolic engineering in N. oceanica CCMP1779, we identified
and characterized the four fatty acid desaturases and one elongase involved in the production of
the LC-PUFA, EPA (20:5). Heterologous expression in S. cerevisiae confirmed the predicted
biochemical function of each gene in the pathway, leading to EPA production without the supply

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of external fatty acids (Figure 3.3 , Table 3.1). We also showed that the Δ5 and ω3 FADs can
both use ω3 or ω6 fatty acids when reconstituted in yeast (Figure 3.4). Similarly, N. oceanica Δ6
FAD expressed in S. cerevisiae was able to process ω3 or ω6 fatty acids when exogenously
supplied (248), suggesting substrate preference may be determined by glycerolipid acyl carriers.
We used our gene stacking vector toolset (Figure 3.5) to increase expression levels of single
or multiple endogenous genes involved in EPA synthesis. Strains overexpressing one, two, or
three FAD encoding genes displayed elevated fractions of LC-PUFAs, notably EPA (Table 3.4).
However, we did not observe a further increase in LC-PUFAs in the lines overproducing more
than one enzyme. The isolation of the EPA biosynthetic genes enables further studies into
regulation of the pathway and provides tools useful for manipulation of LC-PUFA production in
N. oceanica and heterologous hosts.

Metabolic engineering for increased EPA content in N. oceanica
The overexpression of single Δ5, or Δ12 FADs led to an approximate 25% increase in EPA mol
ratio (Table 3.4), in line with observations in other heterokonts. The overproduction of an
endogenous Δ5 FAD in P. tricornutum under the control of a fucoxanthin chlorophyll a/c binding
protein gene promoter led to a 58% increase in EPA (217). Overproduction of an elongase
involved in LC-PUFA production in T. pseudonana led to a 40% increase in EPA (219). It has
been previously shown that in N. oceanica CCMP1779 the inducible overproduction of the Δ12
FAD using the LDSP promoter produced a 50-75% increase in the 20:4Δ5,Δ8,Δ11,Δ14 mol ratio
during nitrogen deprivation and stationary phase (91).
The FAD genes in N. oceanica CCMP1779 are co-expressed under diurnal light:dark
cycles during exponential growth (Figure 3.1) (45). Therefore, we had initially hypothesized that

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high expression of multiple enzymes is necessary to maintain flux through the pathway and
further increase end product concentration. However, the overproduction of the multiple
desaturase proteins in the DOX9+12 and DOX5+9+12 lines did not have an additive effect.
These results suggest that there might be a limit to PUFA content in N. oceanica CCMP1779
before cell physiology is affected under the growth conditions tested.
The cell division rate of DOX lines was not reduced when compared to wild-type cells.
However, decreases in total cellular fatty acids of DOX lines expressing the Δ12 or Δ5 FAD
coding sequences indicates that the physiology of N. oceanica is compromised by desaturase
overproduction (Table 3.5). In N. oceanica EPA is an endogenous major LC-PUFA that is
associated with polar lipids of plastidic membranes and likely has a functional role in the
photosynthetic membrane (249). Typically, in response to environmental conditions, membrane
saturation is altered to maintain membrane fluidity, and LC-PUFAs are increased in membranes
during lower temperatures and high-light. Interference with native membrane composition may
have deleterious effects that limit the accumulation of EPA beyond certain levels.
A higher relative increase in some LC-PUFAs has been achieved when the strategy has
been to introduce novel LC-PUFAs (124, 220) or to elevate the level of minor LC-PUFAs,
initially present in small amounts (102). For example, the heterologous expression of both a Δ6
FAD and a Δ5 FAE coding sequence in P. tricornutum led to a stronger DHA accumulation than
in the single overexpressing lines (102). However, wild-type P. tricornutum contains only trace
amounts of DHA and in these transgenic lines the accumulation of DHA correlated with a strong
decrease in EPA levels, indicating that these transgenics increased partitioning towards DHA but
not an overall increase in flux through the LC-PUFA pathway. These observations support the
hypothesis of a limit of LC-PUFA imposed on the cell under specific growth conditions.

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In addition to possible negative effects on algal physiology, it is likely that other steps in
LC-PUFA biosynthesis, such as fatty acid elongation or Δ6 or ω3 desaturation, are rate limiting
and need further enhancement to increase LC-PUFA content. Moreover, it is possible that
increased LC-PUFA turnover by β-oxidation is involved in maintaining a balanced LC-PUFAs
content (124, 250). Downregulation of the native EPA biosynthetic pathway at a transcriptional
or post-transcriptional level may also compensate for the overproduction of FADs described
here.
Strategies for sequestration of LC-PUFAs in TAG could be an option to overproduce LCPUFAs without compromising cell physiology (91). Although N. oceanica contains little LCPUFAs in TAG under normal conditions, the content of LC-PUFAs in TAG increases following
cellular stresses (176, 210). We observed a decrease 16:0 and 16:1 per cell in the DOX lines
(Table 3.5), however, the overexpression of a Δ12 FAD using a stress inducible promoter (91)
did not cause such a decrease, indicating that the timing of gene expression is likely to be
important for minimizing negative effects of enhanced LC-PUFA content by maybe sequestering
LC-PUFAs in TAG. Diacylglycerol acyltransferases (DGATs) and phosphatidylglycerol
acyltransferase (PDATs) that have preferences for 20C fatty acids also offer potential tools for
channeling EPA to the TAG stores (251, 252). N. oceanica contains 12 DGATS and two PDATs
that are likely to have different substrate preferences, including for LC-PUFAs (31). Studies into
the functional effects of altering the fatty acid profile as well as identifying compensating
internal forms of regulation are needed to identify strategies for further accumulation of LCPUFAs.

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EXPERIMENTAL PROCEDURES
Growth conditions
Axenic cultures were grown in shaking flasks of f/2 medium under 100 µm s-1 m-2 white light, at
22° C and 120 rpm. For protein, metabolite and gene expression analyses, cells were grown
under constant light and samples were collected from mid log cultures (30 106 cells ml-1).

Cloning of N. oceanica CCMP1779 EPA pathway genes
Axenic cultures were under 12:12 light:dark cycle at 22° C (45). Cell counts and cell size
measurements were obtained using a Coulter Counter Z2 (Beckman Coulter) using a profile with
a range of 1.8-3.6 μm. N. oceanica CCMP1779 at midlog phase was used for RNA isolation as
described previously (45). First strand DNA synthesis was accomplished using SuperScript III
with oligo dT (NEB). cDNAs were amplified using primers shown in Table 3.6 and Q5
polymerase (NEB), blunt cloned into pCR-Blunt (Thermo Scientific) and sequenced.

Yeast transformation and expression
EPA pathway genes were cloned into yeast expression vectors containing galactose inducible
promoters. The elongase PCR product was integrated into pYES2.1-topo (Invitrogen).
Desaturases were amplified with the addition of C-terminal 6X histidine tails and restriction sites
for integration into pESC-his and pESC-leu (Agilent). The PCR product was digested with the
noted restriction enzymes (Table 3.6) and ligated into the yeast expression vectors. InvSc1 yeast
cells (253) were transformed with the expression vectors using the Frozen-EZ Yeast
Transformation II Kit (Zymo Research) and selected on SC (ClonTech) medium with proper
drop-out auxotrophy selection. Several colonies from each transformation were selected for

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further experimentation and were grown in 5 ml of SC overnight at 30° C. The overnight cultures
were collected by centrifugation at 1000 x G for 5 minutes, thoroughly decanted, resuspended in
5 ml of SC without sugar, histidine, leucine, and uracil and OD600 was measured in duplicate.
For the zero-hour time point fatty acid analysis 0.5 ml culture was collected by centrifugation at
13,000 x G, decanted and frozen in liquid nitrogen. Flasks of 5 ml SC 2% galactose were
inoculated at 0.4 OD600 and grown at 20° C and 24 hour and 48-hour time points were
collected. For substrate feeding 0.1% NP-40 (Sigma-Aldrich), as a detergent, and 0.5 mM free
fatty acids (Santa Cruz Biotechnology) in glucose and galactose SC medium were included.
Fatty acid analysis with washed cell pellets and 5 μg of pentadecanoic acid internal standard
were conducted. LC-PUFA authentic standards were prepared in a separate reaction for
confirmation of LC-PUFA running times. Fatty acid methyl ester preparation and extraction was
performed as described previously (Liu et al., 2013).

Protein sequence analysis
Protein sequences were generated by translation of the obtained cDNA using canonical codon
usage. To identify functional domains, the protein sequences were submitted to CDD BLAST
(http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi). To identify localization signals, protein
sequences were submitted to HECTAR (http://webtools.sb-roscoff.fr/) (36). To identify
transmembrane domains, protein sequences were submitted to TMHMM2
(http://www.cbs.dtu.dk/services/TMHMM/).

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Identification of bidirectional promoters in N. oceanica CCMP1779
A custom python script was used to assemble the coding regions of each gene as determined in
the genome assembly and annotation of N. oceanica CCMP1779 (11), and only genes with start
and stop codons were added to the final list. These coding regions were assessed with the CUSP
function of the EMBOSS program (Table 3.2). A custom python script was used to identify
diverging gene pairs with intergenic regions of <1500 base pairs, with suitable gene expression
during light:dark cycles (45). Putative gene pairs were manually examined to determine
functional annotation (Table 3.3).

Construction of Nannochloropsis expression vectors
The elongation factor promoter was amplified with the primers EFpro GW F+ and EFpro GW Rlisted in Table 3.6 and inserted into the pENTR gateway entry vector (Invitrogen), sequenced,
and transferred to pNoc-Dlux by a LR clonase (Invitrogen) reaction. The EF promoter was
placed 5’ of the codon optimized firefly luciferase reporter coding sequence (DNA 2.0) in a
Nannochloropsis transformation vector (pNOC-Dlux), and transformants with luciferase activity
were confirmed by immunoblotting detected the presence of the HA tagged protein (Figure 3.9).
Subsequent modifications included removal of the luciferase reporter coding sequence by
digestion with AscI and SacI and replacement with an HA tag coding sequence and a
multicloning site. Primers for insertion of the reporter genes with glycine-serine-glycine linkers
as listed in table 3.6 were used to amplify, fluorescent protein cerulean, venus, GFP, and
NanoLuciferase coding sequences, which were then blunt cloned, sequenced and inserted into
the HpaI and MluI sites. A codon optimized NanoLuciferase sequence was synthesized (IDT).

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The 2A peptide coding sequences were appended to the 3' end of the zeocin (BleR) and
hygromycin (HygR) resistance genes by site directed mutagenesis PCR of resistance vectors,
pNOC-401 and pNOC-411, using Q5 polymerase and the primers listed in Table 3.6. For
elongation of the 2A peptide coding sequences, plasmids containing shorter variants were used
as a template for site directed mutagenesis PCR. To insert a firefly luciferase (with c-terminal
HA tag) coding sequence 3’ of the BleR-2A coding sequences, the 2A vector was digested with
MluI/SacI and the firefly luciferase released from pNOC-Dlux by digestion with AscI/SacI.
Ligations yielded pNOC-411-2A-Flux constructs that were introduced into N. oceanica to assess
2A peptide skipping efficiency. A new multicloning site containing PspomI/XbaI/AfeI/stop
codon/KpnI recognition sequences followed by the heat shock terminator was inserted after the
2A peptide coding sequence. The 2A resistance cassette was inserted into the pNOC-OX-NLux
vector in the opposite orientation using the restriction sites XhoI/PsiI. The Ribi promoter was
amplified from the N. oceanica genome, subcloned, subjected to two round of site directed
mutagenesis to remove the MluI and NruI sites (Figure 3.6). The modified promoter was inserted
between the GFP and 2A coding sequences to generate the vectors pNOC-Stacked-HygR-NLux
and pNOC-Stacked-BleR-NLux.
The coding and terminator regions of the Δ9 FAD gene were PCR amplified from N.
oceanica genomic DNA with the addition of an N-terminal HA tag and the restriction sites MluI
and EcorV, NsiI using the primers D9 mlui HA start F+ and D9 ecorv nsi R- listed in table 3.6.
The PCR product and the vector pNOC-411-P2A(30) was digested with MluI and NsiI and
ligated together. To overexpress the desaturases coding sequences in the pNOC-OX vector
series, desaturase coding regions were PCR amplified with MluI/HpaI sites and ligated to the
AscI and HpaI sites of pNOC-OX. To assemble a desaturase stacking vector the Δ12-HA-LDSP

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terminator sequence was PCR amplified to add the restriction sites EcoRI and PsiI, for digestion
and ligation into the corresponding sites of pNOC-DOX9. The bidirectional ribosomal
component promoter was PCR amplified from the N. oceanica genome with the restriction sites
EcoRI and XhoI and ligated between the two desaturase expression cassettes. All of the vectors
for expression in S. cerevisiae and N. oceanica are listed in Table 3.7 and the complete annotated
sequences are included below. Complete vector seqences are available in Data 3.2.

Nannochloropsis transformation
Vectors were linearized by restriction digestion, and purified and concentrated by ethanol
precipitation. N. oceanica CCMP1779 transformation was performed according to the method of
Vieler et al., (11) with 3 µg of vector DNA, with 30 µg carrier DNA (Invitrogen UltraPure™
Salmon Sperm DNA Solution). Transformed cells were allowed to recover for 48 hours then
plated in top agar with the respective selection. After 3-4 weeks, individual colonies were
resuspended in 100 μl f/2. From each transformation ~20 colonies were screened for increased
LC-PUFA content, and 2-3 colonies identified as positive.

Nannochloropsis luminescence assays
N. oceanica CCMP1779 culture was mixed with f/2 supplemented with either firefly luciferin
(Gold Biotech) or NanoLuciferase substrate (Promega), at a final volume of 200 μl, with 500 μM
firefly luciferin or 10,000X dilutions of NanoLuciferase substrate. For normalized
measurements, 1 million N. oceanica cells were used. Luminescence was measured with a
Centro XS3 LB960 luminometer (Berthold Technologies) over a 0.3 sec exposure.

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Expression analysis in N. oceanica CCMP1779
For protein expression, frozen pellets from 5 ml culture were ball milled in 2 ml tubes (30Hz, 2
minutes) with a TissueLyser II (Qiagen). After addition of protein extraction buffer (100mM Tris
pH 8.0, 2mM PMSF, 2% B-mercaptoethanol, 4% SDS) the sample was heated to for 3 min (60°
C for FADs, 80° C for other proteins), centrifuged at 13,000 x G for 3 minutes, and the
supernatant was transferred to new tube. Protein content was determined using the RCDC assay
(Bio-Rad) and equal quantities of protein were loaded for SDS-PAGE. Proteins were transferred
to PVDF membranes (Bio-Rad) overnight at 4° C. Blots were blocked in TBST with 5% milk for
1 hour at room temperature and washed 6 times with TBST. For GFP detection we used α-GFP
antibody (Abcam ab5450) 1:1000 in TBST with 5% BSA for 1 hour, and a secondary donkey αgoat HRP antibody (Santa Cruz sc-2020) 1:10000 in TBST with 5% milk. For HA detection, we
used α-HA-HRP antibody solution (Roche 3F10) at 1:1000 in TBST with 5% milk for 1 hour.
Signals were detected using clarity chemiluminescence reagent (Bio-Rad). Band quantification
was conducted using Image Lab software (Bio-Rad).
RNA isolation, cDNA synthesis and real time PCR were performed as described previously (45).
Real time PCR primers were checked for efficiency and specificity. The delta-delta Ct method
was used to determine gene expression relative to the gene encoding the actin related protein
(ACTR) NannoCCMP1779_1845.

Fatty acid methyl ester extractions in N. oceanica
Cells (2 ml) were collected by filtration through GF/C filters, and filters stored in screw top tubes
at -80° C. Fatty acid methyl esters (FAMEs) extraction and analysis was carried out as described
previously (210).

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Confocal microscopy
Cerulean detection in transformed N. oceanica CCMP1779 was carried out with Olympus
Spectral FV1000 microscope (Olympus, Japan) at the excitation wavelength of 435 nm (a diode
laser). For endoplasmic reticulum labeling 50 nM DiOC6 (Sigma-Aldrich) in f/2 medium was
used. Cells were labeled directly before microscopic analysis. An argon (488 nm) laser was used
for DiOC6 excitation. Chloroplast autofluorescence was excited by using a solid state (515 nm)
laser. CLSM figures represent Z-series images composed using the Olympus FluoView FV1000
confocal microscope software (Olympus).

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APPENDICES

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Appendix 3.1. Chapter 3 figures and tables.

Figure 3.1. EPA biosynthetic pathway identification in N. oceanica CCMP1779.
(a) Identification of the fatty acid species by comparison with canola oil and 20 carbon LCPUFAs standards (20:3Δ8,Δ11,Δ14, di-homo gamma linolenic acid; 20:4Δ5,Δ8,Δ11,Δ14, ω6
eicosatetranoic acid; 20:4Δ8,Δ11,Δ14,Δ17, ω3 eicosatetraenoic acid; and 20:5Δ5,Δ8,Δ11,Δ14,Δ17,
eicosapentaenoic acid). (b) The EPA biosynthetic pathway includes five desaturases (red ovals,
FADs) and an elongase (blue oval, FAE). Gene IDs are shortened from the NannoCCMP1779_#
format. (c) Expression of the EPA biosynthetic pathway encoding genes during a light:dark
cycle. The arrow indicates the time of cell harvest for cDNA isolation of EPA biosynthetic
pathway genes. Gene expression was calculated using a previous experiment (45) and the
corrected gene annotation. Values are average ± range of two independent cultures.
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Figure 3.2. Computational annotation of protein sequences of isolated EPA biosynthetic
genes.
Protein sequences were generated based upon isolated cDNA sequences. Active site amino acids
and conserved domains identified using conserved domain BLAST. ER localization signals
identified with HECTAR. Transmembrane domains predicted using TMHMM2.

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Figure 3.3. Galactose inducible expression of the EPA pathway genes in S. cerevisiae.
(a) The stacking strategy for EPA production in S. cerevisiae used three plasmids, containing
different auxotrophic markers. Dual expression of FADs (pESC-D12+D6, and pESC-D5+W3)
was achieved by a bidirectional Gal10 promoter, and expression of the FAE was under control of
the Gal1 promoter (pYES-E6). (Co)transformation of vectors yielded S. cerevisiae strains ScΔ12+Δ6, Sc-Δ12+Δ6+E6, and Sc-Δ12+Δ6+E6+Δ5+ω3. (b) Representative GC-FID fatty acid
profiles of Sc-LacZ negative control and FAD expressing yeast strains 48 hours post galactose
induction.

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Figure 3.4. Functional characterization of EPA biosynthesis enzymes in S. cerevisae.
Representative GC-FID fatty acid profiles. In the chromatograms, fatty acids supplied in the
media are indicated with a (+), and fatty acids produced by yeast are indicated with a (*)
underneath the respective peaks. 20C std mix, indicates standards of 20 carbon LC-PUFAs. (a)
Yeast exogenously supplied with 20:3Δ8,Δ11,Δ14 and expressing either the Δ5 and ω3 FAD (ScΔ5+ω3), or the LacZ control gene (Sc-LacZ) before (pre) or after (post) 48 h gene expression
induction by galactose. (b) Yeast exogenously supplied with 20:3Δ8,Δ11,Δ14 and expressing either
ω3 FAD (Sc-ω3), Δ5 FAD (Sc-Δ5), or the negative control (Sc-Leu) after 48 h gene expression
induction by galactose. (c) Yeast exogenously supplied with either 20:4ω3 (20:4Δ8,Δ11,Δ14,Δ17) or
20:4ω6 (20:4Δ5,Δ8,Δ11,Δ14), and expressing either ω3 FAD (Sc-ω3), Δ5 FAD (Sc-Δ5), or the
negative control (Sc-Leu) after 48 h gene expression induction by galactose. (d) Yeast expressing
either ω3 FAD (Sc-ω3) or Δ5 FAD (Sc-Δ5) and exogenously supplied with 20:4ω3
(20:4Δ8,Δ11,Δ14,Δ17) and 20:4ω6 (20:4Δ5,Δ8,Δ11,Δ14) respectively after 48 h gene expression induction
by galactose.

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Figure 3.5. Assembly of native promoters, terminators, and a range of reporters to
generate a transgenic expression toolkit for N. oceanica CCMP1779.
(a) The pNOC-OX vector series contains a series of reporters under the control the EF promoter
with the LDSP terminator, and a hygromycin resistance gene under the control of the LDSP
promoter and 35S terminator. Epitopes include the cyan fluorescent protein (CFP), yellow
fluorescent protein (YFP), green fluorescent protein (GFP) and NanoLuciferase (Nlux), and
hemagglutinin peptide (HA) encoding sequences. P2A(60) is an extended 2A peptide coding
sequence placed 3’ of the zeocin resistance gene (BleR) or hygromycin resistance gene (HygR)
for bicistronic expression by ribosomal skipping. The pNOC-stacked vectors utilize a
bidirectional promoter (Ribi) for co-expression of a reporter and resistance gene with 2A peptide
coding sequence and multicloning site followed by a heat shock terminator (HS). (b) RNA
expression of endogenous genes corresponding to the promoters, NannoCCMP1779_10181
(EFpro), and the gene pair NannoCCMP1779_9669 and NannoCCMP1779_9669 (Ribi
promoter) under light:dark cycles (data from (45)). (c) Transgenic protein confirmation by
immunoblot of pNOC-OX-CFP transformants detected with α-GFP. Total protein was stained
using the dye DB71.

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Figure 3.6. Modification of the Ribi promoter to remove restriction sites.
(a) The genomic sequence of the intergenic region between the bidirectional gene pair,
NannoCCMP1779_9669 and NannoCCMP1779_9669, is shown and the restriction sites MluI
and NruI are bolded and underlined. (b) The Ribi promoter after site directed mutagenesis. The
modified restriction sites are bolded and underlined, with nucleotide deletions represented by
periods and alterations shown in upper case.

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Figure 3.7. Assessment N. oceanica promoters’ strength using NanoLuciferase.
(a) Immunoblotting with α-HA of N. oceanica lines transformed with pNOC-OX-Nlux and
pNOC-Stacked-Nlux detects the Nlux-HA protein. Total protein stained using the dye DB71. (b)
Normalized luminescence signal of N. oceanica lines transformed with pNOC-OX-Nlux and
pNOC-Stacked-Nlux (average ± range, 2 technical replicates).

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Figure 3.8. Optimization of 2A peptides ribosomal skipping efficiency in N. oceanica
CCMP1779.
(a) Schematic of pNOC-2A vector series containing a zeocin resistance coding sequence (BleR)
followed by a 2A peptide coding sequence and a multicloning site. Numbers in parentheses
correspond to numbers of amino acids of the 2A peptide incorporated, and the encoded amino
acid sequence is above (arrow indicates skipping site). For assessing function in N. oceanica
CCMP1779 a coding sequence for firefly luciferase (Flux) with a C-terminal HA tag was
inserted downstream of the 2A peptide. (b-c) Immunoblotting with α-HA antibody of lines
transformed with the pNOC-2A vector series expressing full-length BleR-2A-Flux (FL) and Flux
(Flux*). Total protein stained using DB71.

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Figure 3.9. N-terminal extended 2A peptide screening for increased ribosomal skipping
efficiency.
(a) Numbers in parentheses correspond to numbers of amino acids of the 2A peptide.
Immunoblotting with α-HA detects full-length (FL) and released firefly luciferase (*Flux).
Assesment of transformants producing BleR linked to Flux by a variety of 2A peptides: BleRF2A(24)-Flux, BleR-P2A(19)-Flux, BleR-T2A(18)-Flux, BleR-P2A(30)-Flux, BleR-F2A(58)Flux, BleR-P2A(45)-Flux, and BleR-P2A(60)-Flux. (b) Assesment of transformants producing
HygR linked to Flux by different length P2A peptides: HygR-P2A(19)-Flux, HygR-P2A(45)Flux, and HygR-P2A(60)-Flux. (c) Peptide bond skipping quantified using densitometric
measurements of FL and Flux quantities and efficiency determined with the equation
(*Flux/(FL+*Flux))×100; (average ± SEM, n=2-8).

116

Figure 3.10. Vectors for FAD overproduction in N. oceanica CCMP1779.
(a) Schematics of pNOC-DOX vectors for overexpression of N. oceanica FADs. The Δ9 FAD
coding sequence was expressed 3’ of the BleR-P2A(30) coding cassette in the vector pNOCDOX9. Expression of Δ5 or Δ12 FAD coding sequences by a pNOC-OX vector with a CFP or
HA epitope tag. The stacking vector (pNOC-stacked-DOX) uses the Ribi promoter to co-express
the coding sequences for BleR-P2A(30)-Δ9 FAD, and Δ12 FAD. (b) Immunoblotting N.
oceanica single desaturase DOX lines using α-HA or α-GFP antibodies. Total protein was
stained using DB71. (c) Gene stacking strategy for N. oceanica by use of bicistronic pNOCstacked-DOX and sequential introduction of vectors with different selection markers. (d)
Immunoblotting of stacked DOX9+12 and DOX5+9+12 lines using α-HA or α-GFP antibodies.
Total protein was stained using the dye DB71.

117

Figure 3.11. CLSM analysis of N. oceanica CCMP1779 wild type, and empty vector and
CFP-desaturase overexpressing (DOX) transformants.
Cells were examined for the presence of cerulean fluorescence. Staining with an ER specific
fluorescent dye and chlorophyll autofluorescence were compared to the cerulean signal.
Arrowheads indicate co-localization of ER and cerulean fluorescence. Bars = 1.5 μm.

118

Figure 3.12. Desaturase overproduction alters the fatty acid profile of N. oceanica
CCMP1779.
(a) Gene expression of FADs measured by qPCR using the ACTR gene as control (average ±
SEM of 3 independent cultures). (b) Cell growth of DOX lines during five days under constant
light (average ± SEM of 4 independent cultures). (c) Cell diameter of DOX lines (average ±
SEM of 4 independent cultures). WT, wild-type; EV, empty vector control.

119

Figure 3.13. Growth rates of N. oceanica CCMP1779 DOX lines during exponential
growth.
Growth rates were estimated using the first four days of the growth curves shown in Figure 3.12b
(average +/- SEM, 8-12 independent cultures from 2-3 lines). Cell counts were natural log
transformed and growth rates calculated using linear regression. Values statistically different are
labeled with different letters (p<0.05; ANOVA followed by Bonferroni’s post hoc test).

120

Table 3.1. Fatty acid mole percentage of S. cerevisiae strains.
Yeast strains and timepoints with replicates are listed in the first column. Exogenous fatty acid when supplied is listed in the second
column. Fatty acid mole percentage is determined by converting mass of each fatty acid class to moles, and normalizing the mole
content of each fatty acid class against the total moles of all fatty acids (average ± standard error). Fatty acids not detected are
represented by n.d..
Strain and
timepoint

Substrate
supplied

18:2

18:3ω6

20:3

20:4ω6

20:4ω3

20:5

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

21.54 +/1.1312
19.86 +/0.1178
22.17 +/0.1482

n.d.
1.4 +/0.0517
1.82 +/0.1425

n.d.
4.41 +/0.092
4.1 +/0.1791

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

5.13 +/0.5659
5.1 +/0.1362
6.42 +/0.2541

17.56 +/0.696
21.17 +/0.4623
23.35 +/0.064

n.d.
0.88 +/0.021
1.41 +/0.0504

n.d.
1.35 +/0.0309
1.31 +/0.0475

n.d.
1.23 +/0.0026
1.55 +/0.0292

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

50.54 +/1.1552

4.8 +/0.2115

19.66 +/0.9521

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

18.55 +/0.1181

51.37 +/0.1766

4.99 +/0.0922

23.97 +/0.4621

0.39 +/0.2547

0.48 +/0.0572

0.25 +/0.0586

n.d.

n.d.

n.d.

18.59 +/0.1782

45.77 +/0.5259

6.21 +/0.2244

26.33 +/0.2078

1.4 +/0.1521

0.74 +/0.0047

0.55 +/0.0371

n.d.

0.3 +/0.0013

0.11 +/0.0039

Sc-LacZ 0hr (n=2)
Sc-LacZ 24hr
(n=2)
Sc-LacZ 48hr
(n=2)

16:0
28.71 +/0.0437
18.51 +/0.6455
19.66 +/0.0805

16:1
47.72 +/0.3081
52.74 +/0.7295
49.44 +/0.4685

18:0
5.64 +/0.0826
4.12 +/0.1101
4.77 +/0.0951

18:1
17.93 +/0.2692
24.62 +/0.1942
26.13 +/0.2928

Sc-Δ12+Δ6 0hr
(n=3)
Sc-Δ12+Δ6 24hr
(n=3)
Sc-Δ12+Δ6 48hr
(n=3)

25.56 +/1.2474
21.83 +/0.0178
25.04 +/0.4096

47.21 +/0.1305
47.36 +/0.0785
40.62 +/0.3604

5.7 +/0.083
5.15 +/0.0314
6.24 +/0.0899

Sc-Δ12+Δ6+E6
0hr (n=2)
Sc-Δ12+Δ6+E6
24hr (n=2)
Sc-Δ12+Δ6+E6
48hr (n=2)

28.75 +/0.5478
19.48 +/0.1286
22.7 +/0.5734

48.56 +/1.8096
50.8 +/0.4153
43.27 +/0.7372

25.0 +/1.2938

ScΔ12+Δ6+E6+Δ5+
ω3 0hr (n=3)
ScΔ12+Δ6+E6+Δ5+
ω3 24hr (n=3)
ScΔ12+Δ6+E6+Δ5+
ω3 48hr (n=3)

121

Table 3.1 (cont'd)
Sc-LacZ 0hr (n=2)
Sc-LacZ 24hr
(n=2)
Sc-LacZ 48hr
(n=2)
Sc-Δ5+ω3 0hr
(n=4)
Sc-Δ5+ω3 24hr
(n=4)
Sc-Δ5+ω3 48hr
(n=4)

20:3
20:3
20:3

20:3
20:3
20:3

27.98 +/0.1938
18.12 +/0.1678
22.14 +/0.0269

30.08 +/2.9067
47.28 +/0.29
43.77 +/0.0804

4.52 +/0.0903
3.88 +/0.0302
4.57 +/0.0472

9.85 +/1.3444
21.79 +/0.5658
24.63 +/0.0782

26.84 +/0.6474
19.58 +/0.133
20.68 +/0.1245

45.58 +/0.1301
47.27 +/0.2142
42.18 +/0.4403

5.24 +/0.0125
4.66 +/0.1392
5.51 +/0.1087

17.89 +/0.1804
22.95 +/0.6476
26.85 +/0.2623

21.62 +/0.3112
18.76 +/0.0367
18.47 +/0.0384

37.6 +/0.1856
42.33 +/0.8341
41.69 +/0.2594

5.58 +/0.0529
4.89 +/0.0294
5.25 +/0.2512

21.91 +/0.4474
22.53 +/0.1811
23.85 +/0.8267

35.01 +/0.4783
40.15 +/0.8664
40.87 +/0.4416

6.01 +/0.0155
5.28 +/0.1969
5.23 +/0.2064

22.29 +/0.9076
25.04 +/0.1745
26.08 +/0.038

Sc-Leu 0hr (n=2)

20:3

Sc-Leu 24hr (n=2)

20:3

Sc-Leu 48hr (n=2)

20:3

Sc-Leu 0hr (n=2)

20:4ω6

Sc-Leu 24hr (n=2)

20:4ω6

Sc-Leu 48hr (n=2)

20:4ω6

23.41 +/0.8118
19.51 +/0.3211
18.28 +/0.5734

Sc-Leu 0hr (n=1)
Sc-Leu 24hr (n=1)
Sc-Leu 48hr (n=1)

20:4ω3
20:4ω3
20:4ω3

21.75
19.15
17.22

27.02
32.72
32.96

6.66
5.31
5.94

19.34
22
23.66

Sc-Δ5 0hr (n=3)

20:3

Sc-Δ5 24hr (n=3)
Sc-Δ5 48hr (n=3)

20:3
20:3

20.8 +/0.2822
17.98 +/0.0081
17.99 +/-

35.4 +/0.161
41.34 +/0.9836
39.71 +/-

5.76 +/0.0353
5.12 +/0.0799
5.72 +/-

22.75 +/0.5027
23.84 +/0.6283
24.89 +/-

122

27.58 +/4.1476
8.93 +/0.7182
4.89 +/0.0226

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.
0.92 +/0.0854
0.4 +/0.0171

n.d.
0.62 +/0.1026
0.26 +/0.0137

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

13.09 +/0.3574
11.49 +/0.6604
10.73 +/0.78

n.d.

0.19 +/0.0173

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

0.18 +/0.0297
0.07 +/0.0072

n.d.

13.09 +/0.5289
9.95 +/0.5157
9.54 +/0.3003

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.
n.d.
n.d.

n.d.
n.d.
n.d.

n.d.
n.d.
n.d.

n.d.
n.d.
n.d.

25.24
20.83
20.21

n.d.
n.d.
n.d.

n.d.

n.d.

15.04 +/0.2402
10.36 +/1.5669
10.39 +/-

n.d.
1.36 +/0.0818
1.3 +/-

0.24 +/0.1283

n.d.

n.d.
n.d.

n.d.
n.d.

n.d.
n.d.

n.d.
n.d.

4.44 +/0.3245
4.01 +/0.2516
4.11 +/0.0245

n.d.

n.d.
n.d.

Table 3.1 (cont'd)
0.1227

0.9696

0.1621

0.8541

26.12 +/0.1373
29.52 +/0.2052
32.74 +/0.3841

6.68 +/0.0833
6.32 +/0.0839
6.04 +/0.1991

19.78 +/0.7863
21.22 +/0.1081
25.39 +/0.4848

Sc-Δ5 0hr (n=3)

20:4ω3

Sc-Δ5 24hr (n=3)

20:4ω3

Sc-Δ5 48hr (n=3)

20:4ω3

20.78 +/0.7178
20.51 +/0.1
16.87 +/0.124

Sc-Δ5 48hr (n=2)

20:3 +
20:4ω3
20:3 +
20:4ω3
20:3 +
20:4ω3

21.23 +/1.0009
20.53 +/0.1962
16.88 +/0.2146

24.82 +/0.0068
28.73 +/0.9679
32.37 +/0.1615

6.63 +/0.0876
7.26 +/0.9888
5.85 +/0.051

18.63 +/1.1196
21.4 +/0.1983
24.73 +/0.1856

Sc-ω3 0hr (n=3)

20:3

Sc-ω3 24hr (n=3)

20:3

Sc-ω3 48hr (n=3)

20:3

20.85 +/0.1576
18.9 +/0.7494
17.99 +/0.029

36.85 +/0.2822
43.99 +/0.3518
41.93 +/0.3393

5.78 +/0.0231
5.4 +/0.0276
6.14 +/0.1451

22.84 +/0.2797
22.54 +/1.13
25.22 +/0.2175

Sc-ω3 0hr (n=3)

20:4ω6

Sc-ω3 24hr (n=3)

20:4ω6

Sc-ω3 48hr (n=3)

20:4ω6

22.99 +/0.1278
20.6 +/1.1558
18.36 +/0.2632

34.62 +/0.163
39.72 +/0.6478
39.42 +/0.4584

6.24 +/0.0229
5.55 +/0.1178
5.93 +/0.1357

22.63 +/0.1817
22.02 +/1.479
25.09 +/0.3808

20:3 +
20:4ω6
20:3 +
20:4ω6
20:3 +
20:4ω6

22.45 +/0.1346
21.83 +/0.5563
18.12 +/0.2614

32.8 +/0.075
37.86 +/0.5847
38.12 +/0.2251

6.09 +/0.004
5.85 +/0.0551
5.94 +/0.0163

21.55 +/0.1546
20.74 +/0.5772
25.48 +/0.1351

Sc-Δ5 0hr (n=2)
Sc-Δ5 24hr (n=2)

Sc-ω3 0hr (n=3)
Sc-ω3 24hr (n=3)
Sc-ω3 48hr (n=3)

123

1.9407

0.0892

n.d.

n.d.

0.26 +/0.0348

n.d.

n.d.

26.38 +/0.2179
19.59 +/0.1188
16.85 +/0.2848

n.d.
2.83 +/0.0265
2.11 +/0.024

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

8.32 +/0.3738
2.42 +/0.1677
2.49 +/0.1484

n.d.
0.36 +/0.0236
0.25 +/0.0145

20.38 +/0.1606
17.03 +/0.1943
15.64 +/0.3764

n.d.
2.28 +/0.02
1.78 +/0.0281

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

13.52 +/0.4101
6.79 +/0.4948
6.78 +/0.1037

n.d.

n.d.

0.23 +/0.0145

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.

n.d.
n.d.
n.d.

0.15 +/0.1527
2.38 +/0.2214
1.94 +/0.022

n.d.
n.d.
n.d.

0.14 +/0.003

n.d.

13.14 +/0.1967
9.48 +/0.732
9.11 +/0.1571

n.d.

n.d.
2.64 +/0.2762
2.09 +/0.1326

7.98 +/0.2614
3.55 +/0.4969
3.54 +/0.6561

8.97 +/0.2458
7.25 +/0.8004
6.88 +/0.2697

0.15 +/0.0043
1.12 +/0.0685
0.69 +/0.0909

n.d.
1.81 +/0.2391
1.24 +/0.0962

n.d.

Table 3.2. Codon usage of N. oceanica CCMP1779.
DNA codons (and the corresponding amino acid) from the coding regions of N. oceanica were
computated using the CUSP function of EMBOSS. Total usage of each codon is displayed in
column 3. Frequency refers to the expected occurrence of each codon for a random 1000 amino
acid protein. Fraction is the relative usage between synonymous codons for each amino acid.
# in
Codon
AA
CDS Frquency Fraction
GCA
A
37448
18.577
0.195
GCC
A
63080
31.292
0.329
GCG
A
57333
28.441
0.299
GCT
A
33942
16.837
0.177
TGT
C
12131
6.018
0.432
TGC
C
15928
7.901
0.568
GAT
D
43756
21.706
0.441
GAC
D
55406
27.485
0.559
GAG
E
103188
51.188
0.694
GAA
E
45410
22.526
0.306
TTT
F
35522
17.621
0.5
TTC
F
35467
17.594
0.5
GGT
G
26541
13.166
0.15
GGG
G
62294
30.902
0.351
GGA
G
41466
20.57
0.234
GGC
G
47132
23.381
0.266
CAT
H
20110
9.976
0.448
CAC
H
24792
12.298
0.552
ATC
I
37199
18.453
0.478
ATA
I
10216
5.068
0.131
ATT
I
30401
15.081
0.391
AAG
K
75091
37.25
0.714
AAA
K
30136
14.949
0.286
CTT
L
22678
11.25
0.117
CTG
L
47550
23.588
0.245
CTA
L
11493
5.701
0.059
CTC
L
39175
19.433
0.202
TTA
L
12010
5.958
0.062
TTG
L
60902
30.211
0.314
ATG
M
51143
25.37
1
AAC
N
29344
14.557
0.52
AAT
N
27071
13.429
0.48
CCT
P
25477
12.638
0.258
124

Table 3.2 (cont'd)
CCG
P
CCA
P
CCC
P
CAA
Q
CAG
Q
AGG
R
AGA
R
CGA
R
CGC
R
CGG
R
CGT
R
AGC
S
AGT
S
TCG
S
TCA
S
TCC
S
TCT
S
TAG
Stop
TGA
Stop
TAA
Stop
ACT
T
ACA
T
ACG
T
ACC
T
GTA
V
GTC
V
GTG
V
GTT
V
TGG
W
TAT
Y
TAC
Y

25713
15181
32469
28943
47211
26519
11067
17006
26259
29741
16435
33287
19055
27308
12477
32748
17960
1602
1535
1473
16188
19127
37173
32493
16373
37871
70785
18173
24709
19599
28550

12.755
7.531
16.107
14.358
23.42
13.155
5.49
8.436
13.026
14.753
8.153
16.513
9.453
13.547
6.189
16.245
8.909
0.795
0.761
0.731
8.03
9.488
18.44
16.119
8.122
18.787
35.114
9.015
12.257
9.722
14.163

0.26
0.154
0.329
0.38
0.62
0.209
0.087
0.134
0.207
0.234
0.129
0.233
0.133
0.191
0.087
0.229
0.126
0.348
0.333
0.32
0.154
0.182
0.354
0.31
0.114
0.264
0.494
0.127
1
0.407
0.593

125

Table 3.3. Bidirectional gene pairs.
Diverging genes with suitable expression (column 2) based upon light:dark RNA-Seq are listed with their contig (column 1).
Maximum, minimum, fold change, and Pearson's correlation based on the light:dark RNA-seq is displayed in columns 3-6. Functional
annotation of genes are listed in column 7.
Light:Dark
Light:Dark
minimum
maximum
Gene number
expression
expression
CoContig
(NannoCCMP1779_#)
(FPKM)
(FPKM)
Fold change
expression
Annotation
nanno_913
210
65
268
4.15
0.8
Histone
nanno_913
197
180
293
1.63
Histone
nanno_989
9669
162
362
2.24
0.94
Ribosmal 40S S15
nanno_989
9668
145
366
2.53
Ribosomal 60S l21
Ribosomal 60S
nanno_84
7418
10
476
45.88
-0.7
component
nanno_84
7414
83
315
3.81
Transaldose
nanno_750
7642
421
1736
4.12
0.47
Ribosomal component
Mitochondrial NADH
nanno_750
7640
306
548
1.79
oxireductase
nanno_1064
10564
448
2453
5.47
0.99
VCP4
nanno_1064
10562
829
4471
5.39
VCP5
nanno_4100
4699
173
6760
39.16
0.99
VCP1
nanno_4100
4698
507
9277
18.3
VCP2
Nanno_476
6455
160
232
1.44
0.13
Histone
Nanno_476
6451
281
568
2.02
Histone
Nanno_913
194
457
801
1.75
-0.25
Histone
Nanno_913
212
16
41
2.5
Histone
Nanno_1361
443
4
111
25.67
1
Nitrate transporter
Nanno_1361
438
8
858
107.93
Nitrate reductase

126

Table 3.4. Fatty acid mole percent of N. oceanica CCMP1779 strains.
Fatty acid mole percentage was determined by normalizing the mole content of each fatty acid class against the total moles of all fatty
acids. Average ± SEM of 4 independent cultures. Bold indicates a significant difference with both empty vector (EV) controls
(ANOVA and Bonferroni’s post hoc test, p<0.05). 16:1Δ9; 18:1Δ9; 18:2Δ9,Δ12; 20:4Δ5,Δ8,Δ11,Δ14; 20:5Δ5,Δ8,Δ11,Δ14,Δ17.
Line
WT1
WT2
DOX5 B3
DOX5 C1
DOX12 A11
DOX12 G11
DOX9 A3
DOX9 B6
DOX9+12 9D
DOX9+12
10E
DOX5+9+12
1H
DOX5+9+12
2C
EV F1
EV G2

14:00
4.13 +/0.35
3.84 +/0.32
6.17 +/0.39
6.45 +/0.22
6.02 +/0.21
6.30 +/0.11
3.49 +/0.04
3.42 +/0.09
6.25 +/0.30
6.55 +/0.22
6.25 +/0.31
6.66 +/0.32
3.94 +/0.13
3.62 +/0.06

16:00
37.83 +/1.55
38.28 +/1.66
34.35 +/1.49
34.33 +/1.36
35.79 +/1.51
35.93 +/1.55
34.85 +/0.91
33.65 +/1.02
34.88 +/0.69
35.72 +/0.96
34.91 +/1.46
33.43 +/1.40
38.09 +/1.21
38.24 +/1.58

16:01
32.34 +/0.72
33.40 +/0.55
27.87 +/0.14
26.43 +/0.51
26.43 +/0.21
27.03 +/0.44
33.49 +/0.35
35.25 +/0.09
26.76 +/0.34
26.39 +/0.18
27.61 +/0.49
27.04 +/0.13
35.69 +/0.21
35.81 +/0.26

18:00
1.77 +/0.33
1.49 +/0.14
1.41 +/0.20
1.33 +/0.24
1.19 +/0.18
1.23 +/0.09
1.22 +/0.13
1.21 +/0.13
1.13 +/0.18
0.98 +/0.34
1.19 +/0.23
1.21 +/0.25
1.46 +/0.12
1.59 +/0.15

18:01
1.94 +/0.10
1.98 +/0.07
1.43 +/0.32
1.27 +/0.15
0.82 +/0.22
1.02 +/0.12
3.08 +/0.18
3.77 +/0.32
1.70 +/0.17
0.89 +/0.32
1.35 +/0.13
1.51 +/0.16
2.06 +/0.05
1.98 +/0.05

127

18:02
0.90 +/0.16
0.80 +/0.11
1.62 +/0.18
1.24 +/0.12
1.27 +/0.25
1.38 +/0.18
1.30 +/0.12
1.30 +/0.06
1.93 +/0.15
2.05 +/0.23
1.64 +/0.24
2.18 +/0.27
0.59 +/0.06
0.41 +/0.10

20:04
3.66 +/0.42
3.41 +/0.32
5.83 +/0.22
5.21 +/0.11
5.27 +/0.24
5.53 +/0.21
4.61 +/0.18
4.97 +/0.20
5.82 +/0.13
5.93 +/0.20
5.83 +/0.29
6.37 +/0.31
2.93 +/0.19
2.79 +/0.22

20:05
17.36 +/1.08
16.80 +/1.23
21.27 +/1.27
23.52 +/1.60
23.04 +/1.11
21.27 +/1.28
17.85 +/0.92
16.43 +/1.11
21.53 +/0.62
21.51 +/0.96
21.11 +/1.03
21.47 +/0.92
15.24 +/0.90
15.57 +/1.15

LCPUFA
22.01 +/1.61
21.01 +/1.59
28.79 +/1.69
30.21 +/1.86
29.76 +/1.62
28.50 +/1.73
23.87 +/1.21
22.70 +/1.30
29.29 +/0.76
29.48 +/1.33
28.71 +/1.63
30.15 +/1.46
18.76 +/1.15
18.76 +/1.45

Table 3.5. Cellular fatty acid content of N. oceanica CCMP1779 strains.
Average ± SEM of 4 independent cultures. Bold indicates a significant difference with both empty vector (EV) controls (ANOVA and
Bonferroni’s post hoc test, p<0.05). Fatty acids descriptions as in Table 3.4.
Line
WT1
WT2
DOX5 B3
DOX5 C1
DOX12 A11
DOX12 G11
DOX9 A3
DOX9 B6
DOX9+12 9D
DOX9+12
10E
DOX5+9+12
1h
DOX5+9+12
2C
EV F1
EV G2

14:0
14.9 +/0.8
15.8 +/0.7
17.7 +/2.3
18.8 +/1.3
18.5 +/0.8
16.0 +/0.9
18.0 +/1.6
16.0 +/2.2
16.6 +/1.3
17.1 +/1.9
16.8 +/01.0
18.7 +/1.3
17.3 +/0.7
17.2 +/1.0

16:0
157.2 +/18.4
180.4 +/20.0
110.3 +/10.7
112.7 +/8.1
123.9 +/7.1
103.6 +/10.6
202.0 +/20.7
176.1 +/24.6
104.1 +/7.0
105.6 +/12.6
107.1 +/12.5
97.9 +/11.6
188.2 +/6.6
204.4 +/18.5

16:1
133.1 +/13.2
155.4 +/13.0
88.5 +/- 7.4
86.0 +/- 4.8
90.7 +/- 2.6
76.8 +/- 5.4
191.6 +/15.3
182.2 +/23.0
79.2 +/- 4.7
77.0 +/- 7.9
83.2 +/- 6.5
81.8 +/- 8.3
174.8 +/1.7
188.7 +/10.0

18:0
8.4 +/2.3
7.9 +/1.3
5.0 +/0.8
4.8 +/0.9
4.5 +/0.7
4.0 +/0.5
8.0 +/1.4
7.3 +/1.8
3.7 +/0.7
3.4 +/1.2
4.2 +/1.2
4.5 +/1.1
8.0 +/0.6
9.3 +/01.0

18:1
8.8 +/1.0
10.3 +/1.1
5.1 +/1.4
4.5 +/0.5
3.2 +/0.9
3.3 +/0.6
19.8 +/2.7
21.8 +/3.5
5.7 +/0.8
3.1 +/1.2
4.6 +/0.8
6.0 +/1.1
11.2 +/0.3
11.6 +/0.8

128

18:2
3.9 +/0.4
4.0 +/0.4
5.6 +/0.7
4.4 +/0.5
4.8 +/0.9
4.2 +/0.4
8.1 +/0.9
7.3 +/0.8
6.3 +/0.6
6.4 +/0.3
5.4 +/0.7
8.4 +/1.0
3.2 +/0.3
2.3 +/0.5

20:4
17.4 +/0.8
18.6 +/1.0
22.1 +/1.7
20.3 +/1.0
21.6 +/0.9
18.7 +/0.7
31.5 +/2.5
30.3 +/2.5
20.6 +/1.2
20.5 +/1.4
20.9 +/1.5
24.5 +/2.9
17.2 +/1.1
17.4 +/0.8

20:5
83.7 +/- 5.0
91.9 +/- 6.0
79.6 +/- 5.7
91.4 +/- 9.5
93.7 +/- 3.3
71.1 +/- 2.8
121.2 +/9.6
100.2 +/11.9
75.5 +/- 3.7
73.7 +/- 4.8
74.9 +/- 3.4
75.6 +/- 6.3
88.7 +/- 5.0
96.6 +/- 3.3

Total
427.8 +/35.4
484.3 +/36.4
334.0 +/26.1
344.0 +/20.8
361.6 +/8.6
298.7 +/19.7
601.0 +/52.0
541.2 +/68.2
311.7 +/17.7
306.9 +/29.8
317.4 +/25.6
317.3 +/32.0
508.6 +/4.5
547.6 +/29.4

Table 3.6. Primers used in Chapter 3.
Primer sequences are provided 5' to 3'. Restriction sites used in cloning are underlined, while restriction sites in the primer are listed in
column 3. Small features that were introduced into constructs by the primer are listed in column 4.
Restriction
Features
Primer name
Primer sequence
sites
incorporated
cDNA isolation
D12 10636 F+
Atgggacgcggcggtgag
D12 10636 Rcggccctctagaggtggtgatggtgatgatgtgcccgctgcttgtagaatac
XbaI
His tag
S. cerevisiae
D6 2179 F+
Acactggcggccgcaaaaaaatgtctggacgcggtggcgagcgg
NotI
kozak sequence
D6 2179 Rcggccctctagaggtggtgatggtgatgatgcatggcggggaaatcggcc
XbaI
His tag
D5 5794 F+
Gcctccccagaacgac
D5 5794 RCtaacccatgtgcacctcc
W3 6416 F+
Atggttgagcaaacgttaccg
W3 126 RCggaggggatgatgaacg
E6 9141 F+
Gccgccgcccttcttg
E6 9141 RGccggtttccaagaaggct
Yeast expression
S. cerevisiae
D12 Sc F+
Aaccccggatccaaaaaatgtctggacgcggcggtgag
BamHI
kozak sequence
D12 Sc Rcggccctctagaggtggtgatggtgatgatgtgcccgctgcttgtagaatac
XbaI
His tag
E6 9141 ScTopo F+
Atgtctgccgccgcccttcttg
E6 9141 ScTopo RGccggtttccaagaaggct
S. cerevisiae
D5 Sc F+
Gcggccgcaaaaaaatgtctcctccccagaacgac
NotI
kozak sequence
D5 Sc RGagctcctagtggtgatggtgatgatgacccatgtgcacctcc
SacI
His tag
S. cerevisiae
W3 Sc F+
Gggcccaaaaaaatgtctgttgagcaaacgttaccgac
ApaI
kozak sequence
W3 Sc Rcggccctctagaggtggtgatggtgatgatgcggaggggatgatgaacg
XbaI
His tag
129

Table 3.6 (cont'd)
Toolkit epitopes
OX Hafillin+
OX HA fillin -

cgcgccctcgttaacatgtacccctatgacgtgccggactacgccacgcgtgagtcgcgatgagc
t
catcgcgactcacgcgtggcgtagtccggcacgtcataggggtacatgttaacgaggg

HpaI
MluI, NruI

venus HM GSG OX F+ Gttaaccaattggggagcggcatggtgagcaagggcgag

HpaI, MfeI

venus GSG SM OX RCerulean HM GSG OX
F+
Cerulean GSG SM OX
Rnocox EGFP mfe gsg
F+
nocox EGFP gsg stui
Rnocox Nlux mfe gsg
F+

Acgcgtaggcctgccgcttcctttgtacaactcatccatcccaagc

StuI, MluI

Gttaaccaattggggagcggcatggtgtccaagggcgag

HpaI, MfeI

Acgcgtaggcctgccgcttcccttgtacagctcgtccatgcc

StuI, MluI

Caattggggagcggcatggtgagcaagggcgag

MfeI

Aggcctgccgcttcccttgtacagctcgtccatgc

StuI

Caattggggagcggcatggtgtttactctcgaggacttc

MfeI

nocox Nlux gsg stui R-

Aggcctgccgcttcccgcgtagtcgggcacgtc

StuI

Ccatccacagaatcgattggcgcgccctcgtt
Atggatctcgagggttgcgtgtgtatc

AscI, ClaI
XhoI

Gaattcatcgattctgtggatggagggagg
Ctcgagggttgcgtgtgtatctgtg
cacctatagctacatggtagctag,
Tgttacgaagtgagggttgag

EcorI, ClaI
XhoI

Nannochloropsis
promoters
EFbidi asci T clai F+
EFbidi xho REF bidi pro ecori clai
F+
EF bidi pro xhoi REfpro GW F+
Efpro GW R-

130

HA epitope
HA epitope
Glycine-serineglycine
Glycine-serineglycine
Glycine-serineglycine
Glycine-serineglycine
Glycine-serineglycine
Glycine-serineglycine
Glycine-serineglycine
Glycine-serineglycine

Table 3.6 (cont'd)
NoEF1a
NoEF1a
Ribi sdm nru F+
Ribi sdm nru RRibi sdm mlui F+
Ribi sdm mlui R-

Cttggccatggtcagctgctcgagtgttacgaagtgagggttg
Cctttttacggttcctggcctctagagtatagctacatggtagc
Gaggagaggtcgtgagaacaggatg
Ttcctggccaccatcgcttc
Tccccatcaggcagcagac
Gtctagctgtgacactgaggac

XhoI
XbaI

Desaturase
overexpression
cloning
D9 mlui HA start :
D9 ecorv nsi RD12 claI xhoi F+
D12 nrui R+
D5 OX mluI F+
D5 OX nrui RD6 OX mluI F+
D6 OX nrui RD12 OX mluI F+
D12 OX nrui Rw3 OX mluI F+
w3 OX nrui R-

acgcgttatccgtacgatgtccctgactatgcgatggtcttccagctcgc
Atgcatgatatccagatttccagtccttggtc
Ctcgagatcgatgggacgcggcggtgag
Tcgcgaggcgtagtccggcacgtc
Acgcgtatgcctccccagaacgacgctg
Tcgcgaacccatgtgcacctccgc
Acgcgtatgggacgcggtggcgagc
Tcgcgacatggcggggaaatcggc
Acgcgtatgggacgcggcggtgagaag
Tcgcgatgcccgctgcttgtagaatacc
Acgcgtatggttgagcaaacgttaccg
Tcgcgacggaggggatgatgaacg

MluI
EcorV, NsiI
XhoI, ClaI
NruI
MluI
NruI
MluI
NruI
MluI
NruI
MluI
NruI

2A site directed
mutagenesis
F2A 58 F+

Ccggcgcgcccgtgaccgagttgctttaccg

F2A 58 R-

Gcgttctagagggccccgggttggactc

AscI
PspomI,
XbaI
131

HA epitope

Table 3.6 (cont'd)
T2A F+
T2A R401 p2A F+

Ccttgctgacgtgcggggacgtggaggagaac
Aaccccgcccctctccactagtgccgcatgc
gtccgagggcaaaggaagcatgcggcactagtggagcgacgaacttctccttgctga

4-1 p2A R4-1 p2A R+
401 F2A F+:
401 p2A F-

gagctcacgtacgcgttctagagggccccgggttctcctccacgtccccggcctgct
agcaggccggggacgtggaggagaacccggggccctctagaacgcgtacgtgagctc
gtccgagggcaaaggaaggctccggcgcgcccgtgaagcagacgctgaacttcgacctgc
tcagcaaggagaagttcgtcgctccactagtgccgcatgcttcctttgccctcggac

4-1 p2A R+
401 F2A F-:
P2a 30 aa F+
P2a 30 aa R+
p2a 45aa sdm F+
p2a 45aa sdm Rp2a 60aa sdm F+
p2a 60aa sdm R-

agcaggccggggacgtggaggagaacccggggccctctagaacgcgtacgtgagctc
gcaggtcgaagttcagcgtctgcttcacgggcgcgccggagccttcctttgccctcggac
Ttccaggggccgggggcgacgaacttctccttg
Gcatgcggcactagtggaatgacgaccctgtcc
cgcagcgaacgcctgagcaccgcg atgacgaccctgtccttcca
Gccatcgctgttttccggatggcttccactagtgccgcatgc
tgatccggcggcgtttagcaaa agccatccggaaaacagcg
Tgaatgccggggcgcgggcaaaatccactagtgccgcatgc

N. oceanica qPCR
ActRP4 1845 qPCR
F2+
ActRP4 1845 qPCR
R2D9 qpcr F2+
D9 qpcr R2D12 qpcr F2+
D12 qpcr R2D6 qpcr F2+
D6 qpcr R2-

Gatgtggaggataacgaccc
Aactctttccgcacgtccac
Agcagttcaacccgaccaag
Tcatgctcttcccattcgcc
Caagatgccgttctaccacg
Gcccgctgcttgtagaatac
Gttggtgcagtggttctgtg
Ccctcccacatattcgtctc
132

SphI
SphI, SpeI
SacI, MluI,
XbaI
NheI
AscI
SphI, SpeI
SacI, MluI,
XbaI
AscI
SphI
SphI, SpeI
SphI, SpeI
SphI, SpeI
SphI, SpeI

Table 3.6 (cont'd)
D5 qpcr F2+
D5 qpcr R2w3 qpcr F2+
w3 qpcr R2-

Ggactacgcccacaataacg
Gtcacaaaatcgggcaggac
Gctctcctatgtggattggg
Gttggtcttccttctcggac

133

Table 3.7. Constructs generated in Chapter 3.
Plasmids generated for yeast and Nannochloropsis expression. Restriction sites within the same
multiple MCS are separated by slashes and different multiple cloning sites (MCS) separated by
commas. Addgene IDs when applicable are listed in column 4.
Addgene ID
Construct
Host selection MCS
Yeast expression
vectors
98121
pESC-leu-D5+w3
leucine
98120
pESC-his-D12+D6
histidine
98117
pYES-E6
uracil
Nannochloropsis
toolkit
Selection casettes
pNOC-411
pNOC-401
2A peptides
pNOC-411-F2A(24)
pNOC-411-T2A(18)
pNOC-411-P2A(19)
pNOC-411-P2A(30)
pNOC-411-P2A(45)
pNOC-411-P2A(60)
pNOC-411-F2A(58)
pNOC-401-P2A(19)
pNOC-401-P2A(29)
pNOC-401-P2A(45)
pNOC-401-P2A(60)
pNOC-401-P2A(60)Hsterm
pNOC-411-P2A(60)Hsterm
pNOC-411-F2A(24)Flux
pNOC-411-T2A(18)Flux
pNOC-411-P2A(19)Flux
pNOC-411-P2A(29)Flux

zeocin
hygromycin

NheI/MluI/SacI
NheI/MluI/SacI

98853
98852

zeocin
zeocin
zeocin
zeocin
zeocin
zeocin
zeocin
hygromycin
hygromycin
hygromycin
hygromycin

XbaI/MluI/SacI/MfeI
XbaI/MluI/SacI/MfeI
XbaI/MluI/SacI/MfeI
XbaI/MluI/SacI/MfeI
XbaI/MluI/SacI/MfeI
XbaI/MluI/SacI/MfeI
XbaI/MluI/SacI/MfeI
XbaI/MluI/SacI/MfeI
XbaI/MluI/SacI/MfeI
XbaI/MluI/SacI/MfeI
XbaI/MluI/SacI/MfeI

98843

hygromycin

PspomI/XbaI/AfeI/KpnI

zeocin

PspomI/XbaI/AfeI/KpnI

zeocin

XbaI/MluI/SacI/MfeI

zeocin

XbaI/MluI/SacI/MfeI

zeocin

XbaI/MluI/SacI/MfeI

zeocin

XbaI/MluI/SacI/MfeI
134

98850
98859
98860

Table 3.7 (cont'd)
pNOC-411-P2A(45)Flux
pNOC-411-P2A(60)Flux
pNOC-411-F2A(58)Flux
pNOC-401-P2A(19)Flux
pNOC-401-P2A(29)Flux
pNOC-401-P2A(45)Flux
pNOC-401-P2A(60)Flux

zeocin

XbaI/MluI/SacI/MfeI

zeocin

XbaI/MluI/SacI/MfeI

zeocin

XbaI/MluI/SacI/MfeI

hygromycin

XbaI/MluI/SacI/MfeI

hygromycin

XbaI/MluI/SacI/MfeI

hygromycin

XbaI/MluI/SacI/MfeI

hygromycin

XbaI/MluI/SacI/MfeI

Epitopes
pNOC-Dlux
pNOC-Efpro-Dlux
pNOC-OX-HA

hygromycin
hygromycin
hygromycin

pNOC-OX-CFP

hygromycin

pNOC-OX-YFP

hygromycin

pNOC-OX-GFP

hygromycin

pNOC-OX-Nlux

hygromycin

pNOC-stackedHygR-Nlux

hygromycin

AscI/HpaI,MluI/NruI/SacI
AscI/HpaI/MfeI,
StuI/MluI/NruI/SacI
AscI/HpaI/MfeI,
StuI/MluI/NruI/SacI
AscI/HpaI/MfeI,
StuI/MluI/NruI/SacI
AscI/HpaI/MfeI,
StuI/MluI/NruI/SacI
AscI/HpaI/MfeI,
StuI/MluI/NruI/SacI,
PspomI/XbaI/AfeI/KpnI
AscI/HpaI/MfeI,
StuI/MluI/NruI/SacI,
PspomI/XbaI/AfeI/KpnI

pNOC-stacked-BleRGFP
zeocin
Desaturase
overexpression
pNOC-DOX5-CFP
pNOC-DOX12-CFP
pNOC-DOX12-HA
pNOC-DOX9
pNOC-stackedDOX9+12

hygromycin
hygromycin
hygromycin
zeocin

-

zeocin

-

135

98844

98851

98114
98111
98112
98110
98113

98842

98116

98869
98870
98871
98873
98872

Appendix 3.2. Chapter 3 datasets.
Supplemental datasets are available online from:
http://onlinelibrary.wiley.com/doi/10.1111/pbi.12772/full

Data 3.1 Script used for the identification of bidirectional promoters.

Data 3.2 Description of vector construction and sequences of vectors generated in this study.

136

Chapter 4. Non-transgenic marker-free gene disruption by an episomal CRISPR system in
the oleaginous microalga, Nannochloropsis oceanica CCMP1779
ABSTRACT
Utilization of microalgae has been hampered by limited tools for creating loss-of-function
mutants. Furthermore, modified strains for deployment into the field must be free of antibiotic
resistance genes and face significantly less regulatory hurdles if they are transgene free. The
oleaginous microalga, Nannochloropsis oceanica CCMP1779, is an emerging model for
microalga lipid metabolism. We present a one-vector episomal CRISPR/Cas9 system for N.
oceanica that enables the generation of marker-free mutant lines. The CEN/ARS6 region from
Saccharomyces cerevisiae was included in the vector to facilitate its maintenance as circular
extrachromosal DNA. The vector utilizes a bidirectional promoter to produce both Cas9 and a
ribozyme flanked sgRNA. This system efficiently generates targeted mutations, and allows the
loss of episomal DNA after the removal of selection pressure, resulting in marker-free nontransgenic engineered lines. To test this system, we disrupted the nitrate reductase gene (NR) and
subsequently removed the CRISPR episome to generate non-transgenic marker-free nitrate
reductase knockout lines (NR-KO).

INTRODUCTION
Microalgae are some of the most productive biomass sources on Earth and can generate many
high-value bioproducts such as omega-3 fatty acids, carotenoids, and unusual polysaccharides
(5). One genus of microalgae that has distinguished itself for productivity and genetic
engineering potential is Nannochloropsis (11, 15, 254). Genetic engineering of microalgae has
been hampered by a limited ability to disrupt genes and by the challenges of generating
transformed algae that meet biocontainment requirements for open pond production (255).
137

Recently, the use of cisgenic elements, marker-free strategies, and DNA free genome editing
have allowed the generation of modified organisms that lack antibiotic selection markers (89,
125, 256) or even any heterologous DNA (112, 257). Such organisms satisfy the criteria for nontransgenic organisms, making deployment of modified strains into open systems feasible.
Gene targeting in microalgae has been performed by homologous recombination (14),
TALENs (121, 126, 258), and CRISPR/Cas9 (17, 27, 109, 112, 259-261). So far, gene disruption
by these methods in microalgae has required the integration of a transgenic selection marker into
the genome. A recently described CRISPR/Cas9 system for N. oceanica IMET had low
efficiency (~1-4%), possibly due to low targeting efficiency of the single guide RNA (sgRNA)
produced from a protein coding gene promoter (27). Another CRISPR/Cas9 system for N.
gaditana utilized exogenously synthesized sgRNAs and required two selection markers for
targeted disruption (17). Efficient CRISPR/Cas9 based mutagenesis requires a sgRNA without
modified ends or extraneous sequences for efficient interaction with the Cas9 nuclease and DNA
target. Therefore,sgRNAs flanked by the hammerhead (HH) and hepatitis delta virus (HDV) selfcleaving ribozymes are used to generate precise 5’ and 3’ ends (257, 262), and enable the
production of sgRNAs under the control of protein-coding gene promoters (transcribed by RNA
polymerase II).
Episomes (extrachromosomal nuclear DNA that is usually circular) occur naturally in
some red algae (263), and diatoms are capable of maintaining synthetic circular episomes
containing a low GC (guanine cytosine) centromere-like region (40, 42, 85). In diatoms, an
extrachromosomal episomewith a centromere and autonomous replication sequence fusion
developed from Saccharomyces cerevisiae (CEN/ARS) is replicated and segregated into
daughter cells (40, 42). Furthermore, this episomal system is able to produce proteins that can be

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localized throughout the cell and results in more uniform transgene expression levels between
independent transformantscompared to integrated vectors, possibly by avoiding integration sitespecific effects (42). While circular episomes are an effective expression platform in diatoms,
without selection pressure, they are lost over several generations providing a way to “cure” cells
of them (85).
We developed a CRISPR/Cas9 system that can be expressed from an episome in the
heterokont microalgae Nannochloropsis oceanica CCMP1779. The subsequent removal of the
episome after the mutation was produced generates marker-free non-transgenic gene disruption
mutants that can be modified repeatedly.

RESULTS
Development of a CRISPR system for N. oceanica
The linearized pNOC-CRISPR-GFP vector, containing a Cas9-GFP expression cassette and a
hygromycin resistance cassette (11), generated Hygromycin B resistant transformants when
introduced into N. oceanica (Figure 4.1A). To establish a highly efficient CRISPR/Cas9 gene
editing system in N. oceanica we confirmed the nuclear localization of a Cas9-GFP nuclease
with C’ and N’ terminal SV40 nuclear localization signals (NLS) by confocal microscopy. Cas9GFP proteins co-localized with a DNA stain (4’, 6-Diamidino-2-Phenylindole, DAPI),
demonstrating their nuclear localization in N. oceanica (Figure 4.1B, Figure 4.2). To facilitate
Cas9 detection in vivo, we then generated a Cas9 nuclease fused to the ultra-bright
NanoLuciferase reporter protein with an HA tag (Nlux-HA) in the vector pNOC-CRISPR. Nlux
has high luminescence activity (97), and accordingly N. oceanica transformants can be screened
for the presence of Cas9-Nlux-HA fusion in a 96-well plate using a small number of cells (15).

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Immunoblotting confirmed the production of Cas9-Nlux-HA (186.2 kDa) and Cas9-GFP
proteins (191.8 kDa) (Figure 4.1C-D) in transgenic integrated empty-vector CRISPR N. oceanica
lines (iEV).
The pNOC-CRISPR vector contains the Cas9-Nlux-HA and a gRNA scaffold with a 3’
fusion to the HDV ribozyme under the control of the Ribi bidirectional promoter (257, 262). To
facilitate cleavage precisely at the 5’ end of a sgRNA sequence, a hammerhead ribozyme (HH)
specific to the guide sequence is introduced during sgRNA generation (Figure 4.3). Strategies for
cloning sgRNAs are described in the Methods section.

Use of an episomal CRISPR system to disrupt the nitrate reductase gene
We next designed an episome-based CRISPR/Cas9 system, by incorporating the CEN/ARS
region from S. cerevisiae into the pNOC-CRISPR-Nlux vector, generating the vector pNOCARS-CRISPR (Figure 4.4A). To test this system, we targeted the nitrate reductase gene (NR) for
the known phenotype of NR disruption lines (NR-KO) (Figure 4.4A) (125, 127, 264).
Nannochloropsis NR-KO lines can grow on ammonium (NH4) but are not able to sustain growth
when provided with only nitrate (NO3) as a nitrogen source (14, 27). Two sgRNAs flanked by
self-cleaving ribozymes (sgNR1 and sgNR2) were used to independently target two sites at the
5’ end of the NR gene. We transformed the pNOC-ARS-CRISPR-sgNR1 and pNOC-ARSCRISPR-sgNR2 episomes into N. oceanica and generated the NR1-KO and NR2-KO lines
respectively. Introduction of the circular episomal CRISPR plasmids into N. oceanica resulted in
Hygromycin B resistant lines, which were screened for Cas9-Nlux-HA signal (Figure 4.5A-B).
Lines displaying luminescence were examined for mutations in the NR gene by PCR
amplification of the genomic locus and Sanger sequencing (Figure 4.5). We found that 47% of

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lines with Nlux signal had frame-shift mutations and 13% had in-frame mutations, while 10%
had no mutation and 30% resulted in low-quality sequencing outcomes (Figure 4.5). The lowquality sequencing reactions often had good quality chromatographs up to the target site and then
became unreadable. This observation suggests that a heterogenous population of mutants was
recovered from single colonies, possibly due to mutagenesis occurring after plating. We selected
N. oceanica mutants with small deletions (1D, 1H), a larger (47 bp) deletion (4G), and a small
insertion (B12) as frame-shifted null mutants (NR-KO lines), and the B7 line with a 3 bp
deletion as an in-frame mutant (NR-IF) for further analyses (Figure 4.4B, Figure 4.5D-E).
Immunoblotting detected the Cas9-Nlux-HA protein in all the lines indicating that proteins can
be produced from an episomal DNA in N. oceanica (Figure 4.4C). To test for the loss of NR
activity, cell growth was analyzed in liquid cultures after transfer from NH4 to NO3 containing
medium. The frame-shifted NR-KO mutants could not grow, while the wild type (WT), the iEV
lines, and the in-frame mutant B7 grew in NO3 containing liquid medium (Figure 4.4D). This
indicates frame-shifts introduced into the coding sequence of targeted genes ablates the function
of the resulting protein, while in-frame mutations may still produce functional proteins.
To determine if the episomes were maintained as circular DNA, we conducted an
episome rescue experiment by transforming Escherichia coli with DNA isolated from N.
oceanica episome carrying lines (NR-KOs). WT and iEV lines were used as negative controls. E.
coli transformants were only obtained from untreated DNA isolated from NR-KO lines, but not
from untreated DNA of iEV lines, or the WT strain (Figure 4.4E). To further confirm that the
plasmids rescued from N. oceanica NR-KO lines were circular, an equal amount of DNA from
the NR-KO lines was subjected to endonuclease ClaI restriction digest and/or treated with
Exonuclease V, which acts on free DNA ends 41). Due to the ClaI site in the pNOC-ARS-

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CRISPR plasmid, ClaI treatment of DNA isolated from NR-KO lines strongly decreased the
number of E. coli transformants (Figure 4.4E). Although treatment with Exonuclease V resulted
in a reduction of E. coli transfomants compared to mock treatments, a combined endonuclease
and exonuclease treatment resulted in no colonies being recovered (Figure 4.4E). Restriction
fragment analysis of plasmids recovered from the episome rescue indicated that the episomes
were faithfully maintained in N. oceanica (Figure 4.6). Restriction enzyme recognition sites by
the CEN/ARS region (AgeI), in the Cas9 and HygR genes (EcoRI), and backbone (NotI),
indicated that the episome had no apparent insertions or deletions (Figure 4.6A-B). Sanger
sequencing of the recovered episomes further confirmed their authenticity (Figure 4.6C-D).
We performed southern blots to further characterize the CRISPR episomal lines (Figure
4.7). As a control, we used iEV lines containing the genomic integrated pNOC-CRISPR vector.
DNA was isolated from NR-KO, iEV and WT cells and was then digested with SacI and
hybridized with either a HygR or an AmpR gene probe (Figure 4.7A). In all the NR-KO lines
tested, both probes generated one fragment of ~13,000 bp that matched the episome CRISPR
vector size (Figure 4.7B). However, the iEV lines generated different size fragments when using
the HygR probe and only one line had a detectable fragment when the AmpR probe was used
(Figure 4.7B). The AmpR probe hybridizes close to the AseI cut site used for linearizing the
pNOC-CRISPR vector before transformation to generate the iEV lines. Therefore, the absence of
a band in AmpR probed iEV DNA indicates that the AmpR was partially lost during integration
or that the fragment is too small to be detected in the current experiment. None of the WT lines
had a detectable signal in these assays. This experiment further confirmed the presence of a
circular DNA molecule in the CRISPR episomal lines.
Removal of the CRISPR episomes from N. oceanica mutants

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After generating the NR-KO lines we sought to remove the episome to form marker-less nontransgenic mutants. Nlux signal is a convenient measure for Cas9 presence in the transformed
lines and to monitor for the loss of the episomes. Four NR-KO lines were grown for 10 days
without selection in liquid medium and plated on solid medium to generate independent colonies.
The colonies were screened for Nlux luminescence, followed by a PCR test for the presence of
the episome and a control genomic locus (Figure 4.8A). After growth in non-selective medium,
the NR-KO lines had various levels of Nlux signal and 25-75% of the lines had low
luminescence signal (Figure 4.8B). To confirm that these cured low Nlux luminescent lines had
lost the episome, we conducted PCR for the Cas9 gene contained in the episome, and the NR
gene as a genomic positive control (Figure 4.9A-B). PCR detected the NR gene in all lines, while
the Cas9 coding sequence was only present in the episomal lines but not in the cured lines
(Figure 4.9B). Furthermore, growth tests were used to demonstrate the different phenotypes of
the generated lines. First, the cured lines that had lost the episome were unable to grow on
Hygromycin B containing medium, while the episome carrying parental lines were Hygromycin
B resistant (Figure 4.9C). Second, growth on solid medium containing either NO3 or NH4
revealed a chlorotic phenotype of the episome carrying and cured NR-KO lines only when grown
on NO3 (Figure 4.9C) (14).

DISCUSSION
We have developed a system to produce marker-less non-transgenic gene knockout strains that
not only allows for the generation of lines with multiple modifications but also facilitates the
transfer of strains developed in the lab to the field. Our CRISPR/Cas9 components have been
optimized for efficient detection, with a Cas9-Nlux-HA reporter fusion that has high signal to

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noise ratio and can be screened in a 96-well plate format soon after transformant isolation.
Furthermore, the Cas9-Nlux-HA and sgRNAare coregulated by a bidirectional promoter, thus
linking Cas9 production to sgRNA expression (Figure 4.1A) (15). The pNOC-CRISPR vector
series contains unique restriction sites between the elements making it an ideal platform for
further development of CRISPR/Cas9 as a system for transcriptional reprogramming and other
DNA targeting techniques.
The use of self-cleaving ribozymes facilitates the flexible expression sgRNAs. The
ribozyme flanked sgRNAs can be expressed from different types of promoters, in our case a
bidirectional promoter, but also possibly from conditional promoters. Our final episomal vector,
pNOC-ARS-CRISPR-v2, contains a multi-cloning site with a pair of BspQI type IIS restriction
sites for scarless insertion of a guide sequence, for one-step cloning (Figure 4.10A-B).Selfcleaving sequences for expression of the sgRNA could be used for the production of multiple
sgRNAs from a single transcript (22). Production of multiple sgRNAs can be used to target
multiple genes for simultaneous disruption, used in pairs for deletion of a region between two
targeted sites on a chromosome, or in pairs along with a nickase Cas9 variant for enhanced
specificity.
Transgenic expression in algae is most often performed by integrating a constructed DNA
(construct) into the genome. However, this can result in site-specific effects, or the disruption of
genes at the insertion site. Therefore, episomes are an emerging expression platform in
microalgae that avoids these issues. In diatoms, effective centromere sequences have the simple
requirements of a GC content <30%, a length of over >500 bp, with long stretches of A-T
sequences (40, 42, 85) . These centromere-like regions interact with the centromeric histone
protein (CENH3) likely facilitating segregation during cell division (40). However, the

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molecular processes for replication of synthetic episomes in algae are yet to be determined.
While these first-generation synthetic episomes can robustly express transgenes, they are
unstable and lost from the population when selection pressure is not applied. These
characteristics are ideal for transient CRISPR/Cas9 gene disruption, making it easy to screen
transformants for mutations in the target site, followed by curing of the episome (256, 257). The
cured mutants, thus contain a scar in the target site but lack an antibiotic resistance gene or any
other transgenic elements, and can be used for subsequent modifications and do not need further
biocontainment strategies. This technique will aid in the development of chassis strains for
biotechnology, and makes marker-free genomic integration or endogenous locus tagging of
expression constructs foreseeable.
To make the generated non-transgenic NR-KO mutant available for wide use, the NR1KO 4G-5A strain is deposited with NCMA. To make the high-efficiency, CRISPR/Cas9 dual
component pNOC-CRISPR vectors widely available, the plasmids developed in this study are
deposited with Addgene (Table 4.1).

EXPERIMENTAL PROCEDURES
Strains and growth conditions
N. oceanica CCMP1779 was used in all experiments. Cells were grown in f/2 medium under
constant 100 µmol m-2 s-1 light at 22º C, on a shaker set at 120 rpm. F/2 medium with 2.5 mM
KNO3 or 2.5 mM NaNH4 was used. Hygromycin B (Sigma-Aldrich) was utilized at a
concentration of 100 µg/ml. Cell concentrations were measured with a Z2 Coulter Counter
(Beckman Coulter) with a range of 1.8-3.6 µM. To determine cell growth rates, N. oceanica
strains were inoculated to 5 106 cells/ml and cell density measured every 24 hours. For

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assessment of antibiotic resistance, growth after plating 30,000 cells on solid medium was
monitored for 1 month.

CRISPR plasmid construction
All enzymes were obtained from NEB, unless otherwise noted. Vector maps were produced
using SnapGene (www.Snapgene.com), and sequence views generated with Benchling
(www.Benchling.com). Primers used in this study are listed in Table 4.2.
Generation of pNOC-CRISPR-GFP: The Cas9 gene was PCR amplified from hCas9
(AddGene 41815) with the primers Cas9 NLS F+ and Cas9 linker R-, and GFP was amplified
from pOCS-Ole-LDSP (3) with the primers GFP linker F+ and GFP NLS R- (Table 4.2). The
vector backbone of pNOC 411 (containing the EF promoter (NannoCCMP1779_10181) and
LDSP terminator (NannoCCMP1779_4188)) (11) was amplified with the primers 411 Cas9 Fand 411 GFP R+, and fused by Gibson Assembly (265) with Cas9 and GFP fragments to form
pNOC-Cas9-GFP. A Hygromycin B resistance cassette, composed of the LDSP promoter, the
HygR gene, and the 35S terminator was PCR amplified from pSEL100 with the primers LDSP
NsiI F+ and LDSP BspQI R-. This PCR product and the vector pNOC-Cas9-GFP were digested
with BspQI and NsiI and ligated to form pNOC-Cas9-GFP-HygC. The Ribi promoter (between
NannoCCMP1779_9669 and NannoCCMP1779_9668) and the terminator of the N. oceanica
cellulose synthase gene (CS, NannoCCMP1779_5780) were PCR amplified from genomic DNA
with the primer pair Ribi CRISPR F+ and Ribi CRISPR R-, and CSterm sgRNA F+ and CSterm
sgRNA R- respectively, and were combined with the XhoI/AgeI digested pNOC-Cas9-GFP
backbone by Gibson Assembly, to form pNOC-stacked-Cas9-GFP. A smaller section of the CS
terminator that did not contain BspQI sites was PCR amplified CSterm sgRNA F+ and CSterm

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sgRNA R2-, and used to replace the CS terminator. The gRNA scaffold with a HDV 3’ ribozyme
sequence was synthesized (Integrated DNA Technologies) and placed into the ClaI and KpnI
sites in pNOC-stacked-Cas9-GFP to form pNOC-CRISPR-GFP.
Generation of pNOC-CRISPR: A C-terminal section of Cas9 was amplified with the
addition of an HA tag-SV40 NLS by overlap extension PCR using the primers Cas9 3’ AscI F+,
Cas9 3’ RE R1-, and Cas9 3’ RE R2-, and after digestion with AscI/MfeI ligated with AscI/MfeI
digested pNOC-CRISPR-GFP to form pNOC-CRISPR-HA. N. oceanica codon optimized NluxHA was PCR amplified from pNOC-OX-Nlux (15) with primers Nlux HpaI F+ and Nlux NheI
R-. This PCR product and the vector pNOC-CRISPR-HA were digested with HpaI/NheI and
ligated to form pNOC-CRISPR.
Generation of pNOC-ARS-CRISPR: The CEN/ARS region was PCR amplified from
pDEST22 (Thermofisher) with the primers CEN/ARS F+ and CEN/ARS R-, and digested with
AgeI. The vector pNOC-CRISPR was digested with AgeI, phosphatase (CIP) treated, and ligated
with the ARS region to form the vector pNOC-ARS-CRISPR.
Design and cloning of NR sgRNAs: Target sequences were chosen by identifying NGG
motifs at the 5’ end of the NR coding sequence. The potential target sequences were submitted to
the N. oceanica CCMP1779 BLAST (https://genome.jgi.doe.gov/pages/blastquery.jsf?db=Nanoce1779) to identify mismatches and nonspecific targets sharing PAM
sequences were rejected. Corresponding guide sequences with a HH ribozyme sequence were
appended to the 5’ end of gRNA scaffold by PCR site directed mutagenesis (257, 262). For this
process a fragment of the pNOC-CRISPR including the gRNA scaffold, the CSterminator, the
AmpR resistance gene and the origin of replication was amplified with the primers sgHH NR-1
ClaI F+ and sgHH NR-1 R-, and sgHH NR-2 ClaI F+ and sgHH NR-2 R-, for sgNR1 and sgNR2

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respectively (Figures 4.3). These primers contain the HH ribozyme sequence that includes a
section complementary to the guide sequence (Figure 4.3A). After PCR amplification, the
product was ligated and cloned into E. coli to generate the sgHH-target plasmid (Figure 4.3B).
The ClaI/KpnI fragment of sgHH-target was transferred to pNOC-ARS-CRISPR digested with
ClaI/KpnI.
Generation of pNOC-ARS-CRISPR-v2: This smaller vector was generated to allow HHguide insertion on the gRNA scaffold using BspQI restriction sites. To remove the BspQI site
originally present in the CEN/ARS region, the backbone of pDEST22 (Thermofisher) was
amplified with the primers Crispr compact F+ and Crispr compact R-, religated, and amplified
with CEN/ARS -bspq sdm F+ and CEN/ARS -bspq sdm R. This vector backbone and the
CRISPR cassette (the Cas9 and sgRNA expression cassette under the control of the Ribi
promoter, and CS and LDSP terminators) from pNOC-ARS-CRISPR were digested with
NotI/AgeI and ligated together to form pNOC-ARS-CRISPR-compact. A 35S terminator was
amplified from pSELECT100 (3) with the primers 35S terminator F+ and 35S terminator R- and
digested with NotI/PmeI and ligated into pNOC-ARS-CRISPR-compact NotI/PmeI sites to form
pNOC-ARS-CRISPR-35S. The Hygromycin B resistance cassette from pNOC-ARS-CRISPR,
that includes the LDSP promoter and HygR gene, was amplified with the primers LDSPpro F+
and HygR R-, digested with NotI/NheI and ligated into the NotI/SpeI sites of pNOC-ARSCRISPR-35S to form pNOC-ARS-CRISPR-v2.

N. oceanica transformation
Integrating vectors were digested with AseI and concentrated by ethanol precipitation.
Transformations were conducted as previously described (15), with 3 µg of DNA and 30 µg of

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blocking DNA (Ultrapure salmon sperm DNA - Invitrogen). Transformants were plated using
the top agar method on 100 µg/ml Hygromycin B and grown under 100 µmol m-2 s-1 for 3 weeks.
Individual lines were transferred to 500 µl of f/2 with 100 µg/ml Hygromycin B (GoldBio) in a
96 deep well plate (Evergreen Biotech). Cultures were then maintained on solid plates.

NanoLuciferase luminescence assays
For Nlux activity screening, 100 µl of cell culture was transferred to a luminescence plate, and
100 µl of f/2 containing Nanoglo substrate (Promega) at a 10,000X dilution. For normalized
luminescence measurements, 1.5 million cells per well were transferred to the 96-well
luminometer plate, the volume was adjusted to 100 µl with f/2 medium, and 100 µl of f/2
containing Nanoglo substrate (Promega) at a 10,000X dilution was added. Luminescence was
measured after 180 sec delay with a 0.3 sec exposure using a Centro XS3 LB960 (Berthold).

N. oceanica colony PCR
A 1X Q5 buffered solution (NEB) with 1 µl of N. oceanica culture per 10 µl of required sample
was boiled (100º C) for 10 min. A 10 µl PCR master mix was added to the 10 µl of sample and
PCR conducted according to the manufacturer’s suggestions (NEB). The primers NR F+ and NR
R- were used to amplify the NR gene (Table 4.2).

Episomal DNA isolation from N. oceanica
For DNA isolation 10 ml of culture at mid-log phase (~ 3 107 cells ml-1) was collected and
frozen. The protocol of Karas et al. (41) was utilized with some modifications. Briefly, for each
reaction 235 µl Qiagen P1 solution was combined with 5 µl lysozyme (25 mg/ml) (Sigma-

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Aldrich), 2.5 µl macerozyme (100 mg/ml)(Yakult Pharmaceuticals), 2.5 µl zymolyase (10
mg/ml) (Zymo Research), and 5 µl cellulase (100mg/ml)(Yakult Pharmaceuticals) and used to
resuspend the cell pellets. The resuspended cell culture was incubated at 37º C for 30 min. After
addition of the P2 solution, and S3 solution (Qiagen), the cell debris was pelleted at 14000 x G
for 10 min. Supernatant was aspirated and combined with an equal volume of isopropanol, mixed
and centrifuged at 14,000 x G at 4º C for 10 min. After decanting the pellet was washed with 750
µl 70% ethanol, centrifuged, decanted, and dried. The DNA was resuspended in 40 µl TE, and
the concentration determined using a NanoDrop Lite (Thermo Scientific).

Episome rescue
Equal amounts of DNA isolated from NR-KO, iEV, and WT lines were used for E. coli
transformations. For enzyme treatment of the DNA extracted from NR-KO lines, 2 µg of DNA
was treated with 10 units of Exonuclease V (NEB) and/or 10 units of ClaI (NEB) in a 20 µl
reaction for 1 hour at 37º C. Reactions were heat inactivated at 75º C for 30 min. An equal
amount of DNA (500 ng) from enzyme treated samples, mock treated, and untreated samples
were used to transform E. coli (DH5α subcloning efficiency, NEB). Resulting colonies were
counted and random colonies selected for plasmid isolation. Resulting plasmids and control
pNOC-ARS-CRISPR-sgNR2 DNA, were digested with AgeI, NotI, and EcorI (NEB) according
to manufacturer’s instructions (NEB), and separated on a 0.9% agarose gel.

Episome curing
Episome containing NR-KO lines were grown in liquid 2.5 mM NaNH4 f/2 without Hygromycin
B for 10 days. Cultures were diluted to 3,000 cells per ml, and 3,000 cells were plated on 2.5

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mM NaNH4 f/2. Single colonies developed over 3 weeks, and 48 colonies were isolated and
grown in 2.5 mM NaNH4 f/2. After 1 week, the Nlux luminescence was measured and low Nlux
signal lines were further screened by colony PCR. Primers used were NR F+, NR R-, and epi
Cas9 F+and epi Cas9 R- (Table 4.2).

Immunoblotting
Immunoblotting was conducted as described previously (2). Protein extract (50 µg) was
separated on 8-10% SDS-polyacrylamide gels. After transfer to PVDF membranes Cas9-GFP
was detected with α-GFP (Abcam ab5450) 1:1,000 in TBST with 5% BSA followed by donkey
α-goat-HRP (Santa Cruz sc-2020) 1:10,000 in TBST with 5% milk, and Cas9-Nlux-HA with αHA-HRP (Roche 3F10) 1:1,000 in TBST with 5% milk. Detection was conducted by
chemilumiscence with Femto substrate (ThermoFisher). After detection, total protein was stained
with Direct Blue 71 (197).

Confocal microscopy
Confocal microscopy was performed using an inverted Olympus FluoView1000 confocal laser
scanning microscope (Olympus Corporation, USA). Cells grown in f/2 medium were stained
with 4’,6-Diamidino-2-Phenylindole (DAPI, 358/461 - Life Technologies) with a final
concentration of 0.2 µg/µl and observed using a 100x UPlanSApo oil objective (N.A. 1.4). DAPI
fluorochromes were excited using a 405 nm blue diode laser, and the emission signals were
filtered using the BA430-470 band pass filter. Cas9-GFP was excited using an argon 488 nm
laser, and the emission signals from GFP were filtered using a BA500-530 band pass filter. Postimaging analyses were performed using Olympus FluoView1000 software.

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Southern-blot analysis
We used a procedure described previously (3). Briefly, N. oceanica DNA was isolated by CTAB
and 20 µg was digested with SacI and was separated on an agarose gel (0.9%, 70 Volts
overnight), followed by blotting to a Hybond Nylon membrane overnight (GE Health Care).
Subsequent hybridization and detection was performed with a digoxigenin (DIG) labeling and
detection kit according to the manufacturer’s instructions (Roche Applied Sciences). Two probes
were amplified by PCR, one for the HygR gene (with the primers HygR probe F+ and HygR
probe R-) and one for the AmpR gene (AmpR probe F+ and AmpR probe R-), and were used for
hybridization in PefectHyb Plus hybridization buffer (Sigma-Aldrich).

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APPENDIX

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Figure 4.1. A one-vector CRISPR system for gene disruption in N. oceanica.
(A) The pNOC-CRISPR vector series includes a Hygromycin B resistance cassette (HygC,
green). A bidirectional promoter (Ribi) drives the transcription of the Cas9-reporter fusion and
gRNA scaffold (scaffold, blue), along with the LDSP and CS terminators (LDSP-T, CS-T)
respectively. Cas9 is fused to either the GFP or Nlux (with HA tag) reporters by a 3x glycineserine linker (GSGSGS) and contains SV40 nuclear localization signals on the N’ and C’ termini
(NLS). The gRNA scaffold and the 3’ self-cleaving HDV ribozyme is integrated into the vector.
The 5’ hammerhead ribozyme (HH) specific for each guide sequence (GS, orange) is fused to the
gRNA scaffold (scaffold) to form a sgRNA. Ribozymes are highlighted in yellow. Unique
restriction sites are shown with an upwards line and the name in italics. (B) Confocal analysis of
DAPI nuclear staining, Cas9-GFP signal, and merged brightfield, DAPI and GFP signal in N.
oceanica cells. Scale bar of 5 μM. (C) Immunoblotting with an α-GFP antibody detected the
Cas9-GFP produced in N. oceanica transformed with pNOC-CRISPR-GFP. (D) Immunoblotting
with an α-HA antibody detected the appropriately sized Cas9-Nlux-HA in N. oceanica
transformed with pNOC-CRISPR. For (C) and (D) numbers on the left of immunoblots indicate
size markers (KDa).

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Figure 4.2. Confocal microscopy of Cas9-GFP expressing N. oceanica with the nucleus
stained by DAPI.
Scale bars of 5 µm. (A) Wild-type (WT) cultures with DAPI nuclear stain, GFP signal, and
merged view of DAPI, GFP and brightfield signals. (B) Tranformants producing Cas9-GFP with
DAPI nuclear stain, GFP signal, and merged view of DAPI, GFP and brightfield signal.

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Figure 4.3. Cloning strategies for the generation of a ribozyme-sgRNA.
(A) Example of a ribozyme (highlighted in yellow) flanked sgRNA (highlighted in purple) with
unique ClaI and KpnI restriction sites indicated. The hammerhead ribozyme is customized to
each guide sequence (highlighted in orange) with a reverse complement of the first six basepairs
(highlighted in red). The 80 bp gRNA scaffold (highlighted in blue) has a HDV ribozyme at the
3’ end. Primers used to clone the hammerhead-guide sequence, HH sgTarget F+ and HH
sgTarget R-, are indicated as grey and orange arrows respectively. (B) Subcloning strategy to
generate ribozyme flanked sgRNA in pNOC-CRISPR series. The HH sgTarget F+ primer,
anneals at the 5’ end of the gRNA scaffold (blue) on pNOC-CRISPR vectors and includes a 5’
extension containing the 20 bp guide sequence and 3’ end of the HH sequence. The HH sgTarget
R- primer anneals to a region in the vector backbone downstream of the hygromycin resistance
gene (HygR, green) and includes a 5’ extension containing the 5’ end of the HH ribozyme
sequence, 6 bp specific to the guide sequence for loop formation and a ClaI site. The vector map
indicates the location of primer annealing. After amplification, ligation, and transformation into
E. coli, a subcloning vector (sgHH-target) containing the HH-guide-sgRNA-HDV sequence is
recovered. The ClaI/KpnI digested fragment of the sgHH-target vector is then ligated with
ClaI/KpnI digested pNOC-CRISPR vector to form the final pNOC-CRISPR-sgTarget vector. (C)
Sequences of generic sgTarget F+ and HH sgTarget R- primers. The 20 bp guide sequence is
placed in the guide region (shown in uppercase) of a HH sgTarget F+ primer, and the first 6 bp
of the guide sequence (uppercase, highlighted in red) placed in the asterisk region (*) of the HH
sgTarget R- primer.
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Figure 4.4. Development of an episomal CRISPR system.
(A) The S. cerevisiae CEN/ARS6 region (ARS, red) was included in the pNOC-ARS-CRISPR
construct for episomal maintenance. Guide sequences (orange) for nitrate reductase targets, with
a 5' hammerhead ribozyme (HH), were fused to the gRNA scaffold to form the NR sgRNAs
(sgNR). Ribozymes are highlighted in yellow. The sgNR1 and sgNR2 were added to pNOCARS-CRISPR to form pNOC-ARS-CRISPR-sgNR1 and pNOC-ARS-CRISPR-sgNR2,
respectively. N. oceanica is transformed with circular episomal CRISPR constructs. (B)
Mutations in the two target sites in the NR genomic locus (Target 1 and Target 2) of N. oceanica
transformed with the respective pNOC-ARS-CRISPR-sgNR construct. Mutant lines are
identified by 96-well plate location (Figure 4.5). Deleted nucleotides are represented with dashes
and inserted nucleotides are shown in bold. Protospacer adjacent motifs (PAM sites) are
underlined. (C) Immunoblot using an α-HA antibody of N. oceanica NR1-KO and NR2-KO lines
producing Cas9-Nlux-HA from the CRISPR episome. Numbers on the left indicate size markers
(KDa). (D) Growth curves after transfer from NH4 to NO3 containing medium of NR-KO frameshifted lines (1D, 1H, 4G, B12) and NR2-IF B7 in-frame line, empty vector integrated CRISPR
control lines (iEV), and wild-type (WT). (E) Episome rescue by E. coli transformation using
equal quantities of DNA isolated from NR-KO lines, iEV, and WT N. oceanica lines. Values are
the average colonies generated ± SE (NR-KOs n = 4 independent lines, WT n = 2 biological
replicates, and iEV n = 2 independent lines). Equal quantities of DNA from NR-KO lines after
treatment were used for E. coli transformation, and the resulting colonies counted (n = 4
independent lines). Exonuclease V (ExoV), ClaI endonuclease (ClaI), and ClaI endonuclease
with Exonuclease V (ClaI+ExoV).

157

Figure 4.5. Identification of NR knockout mutants by CRISPR/Cas9.
(A) Representative 96-well Nlux luminescence screen of NR1-KO lines. The PCR products of
the NR genomic locus from bolded wells were submitted for Sanger sequencing. Frame-shift
mutations are red, in-frame mutations italicized, colonies returning poor quality sequences are
indicated by strikethroughs, wild-type sequences are unmodified (bolded), and lines selected are
marked with an asterisks (*). (B) Representative 96-well Nlux luminescence screen of NR2-KO
lines. Lines are highlighted as described in panel A. (C) Rates of sequencing results of NR1-KO
and NR2-KO lines. (D) Chromatographs of target1 region from wild-type and NR1-KO lines
(identified by plate location). (E) Chromatographs of target2 region from wild-type, NR2-KO,
and NR2-IF line (identified by plate location).

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Figure 4.6. Verification of rescued episomes.
(A) Plasmid map indicating restriction sites used for restriction fragment analysis. (B) Triplicate
recovered plasmids from each NR-KO episomal line were digested with AgeI, NotI, and EcorI
endonucleases. The positive control plasmid (+), pNOC-ARS-CRISPR-sgNR2, was used.
Restriction fragments were visualized after separation by agarose (0.9%) gel electrophoresis
using a 1 kb+ size ladder (Invitrogen). (C) Sanger sequencing of the sgRNA region of the
recovered episomes from NR1-KO lines aligned to pNOC-ARS-CRISPR-sgNR1. (D) Sanger
sequencing of the sgRNA region of the recovered episomes from the NR2-KO line aligned to
pNOC-ARS-CRISPR-sgNR2.

159

Figure 4.7. Southern blot analysis of the episomal and integrated empty-vector CRISPR
mutants.
(A) Plasmid map showing the pNOC-ARS-CRISPR-sgNR vectors used for transformation. DNA
was digested SacI site prior to analysis. HygR and AmpR regions were used as probes. The AseI
site was used to linearize the plasmid for integrated empty-vector controls. (B) and (C) Genomic
DNA digested with SacI was separated with a 0.9% agarose gel. Left panels show the stained
agarose gels and right panels show the hybridization signals. The ladder location of 12 kb and 3
kb bands are noted. The blot contains the plasmid pNOC-ARS-CRISPR-sgNR2 as a positive
control (+), a 1 kb+ DNA ladder (L), three wild-type DNA (WT) samples as negative controls,
DNA from episomal mutant lines (NR-KO), and DNA from integrated empty-vector lines (iEV).
HygR and AmpR probes were used in (B) and (C), respectively.

160

Figure 4.8. Curing episomes from NR-KO lines.
(A) Strategy for the generation of episome-less NR-KO lines. NR-KO mutants carrying the
episome were grown without selection for 10 days, and then plated on medium without selection.
Single colonies were isolated in 96-well plates and screened for luminescence signal, followed
by PCR to detect the Cas9 gene. A PCR against the genomic sequence of the NR gene was used
as genomic locus control. (B) Nlux luminescence screen of independent colonies after curing
procedure of NR-KO lines. A cutoff of 300 counts/0.3 seconds was used to define low
luminescent lines. The percentage of lines falling below the threshold are displayed beneath the
raw measurements. Bolded wells were screened by PCR and lines in red were selected as
putative “cured” lines (C) Colony PCR for Cas9 (episomal marker) and NR (genomic marker)
genes separated on 0.9% agarose gels. 1 Kb+ ladder (L), wild-type (WT), episome carrying
parental lines were used as positive control (+), 4 low-Nlux signal, and 2 high-Nlux recovered
colonies (identified by location in the 96-well growth plate) were tested. Final cured lines are
highlighted in red. The ladder location for 1.65, 1.0, 0.85, and 0.65 kb bands are noted on the left
side of each gel.

161

Figure 4.9. Generation of marker-free non-transgenic mutants by episomal removal
(curing).
(A) Luminescence from equal number of cells of WT, and NR-KO lines either containing the
episome or cured of the episome. (B) PCR for detection of a positive control NR genomic locus
and the Cas9 regions on the episome conducted on the same DNA extract obtained from WT
and, NR-KO episomal and cured lines. (C) Plating of an equal number of cells of WT, NR-KO
and NR-KO cured lines on NH4, NO3, and NH4 with Hygromycin B on f/2 solid medium after 1
month of growth.

162

Figure 4.10. A one-vector CRISPR system for scarless cloning of guide sequences.
(A) The multicloning site for guide sequence insertion contains a pair of BspQI sites for removal
of the MCS and generation of sticky ends on the Ribi promoter and gRNA scaffold. (B) Map of
pNOC-ARS-CRISPR-v2.

163

Table 4.1. Materials generated in Chapter 4.
Vectors and Nannochloropsis strains generated for the study are listed in the first column and if
deposited with third-party repository their identification number is listed in the second column
Vectors
Addgene
pNOC-Cas9-GFP
pNOC-Cas9-GFP-HygC
pNOC-stacked-Cas9-GFP
pNOC-CRISPR-GFP
100009
pNOC-CRISPR-HA
99370
pNOC-CRISPR
100008
pNOC-ARS-CRISPR
100011
pNOC-ARS-CRISPR-sgNR-1
100010
pNOC-ARS-CRISPR-sgNR-2
102915
pNOC-ARS-CRISPR-compact
99369
pNOC-CRISPR-35S
99861
pNOC-ARS-CRISPR-v2
99863
Nannochloropsis strains
NR1-KO 1D
NR1-KO 1H
NR1-KO 4G
NR1-KO B12
NR1-KO 1D-6H
NR1-KO 1H-12A
NR1-KO 4G-5A
NR1-KO B12-12G

NCMA

.

164

Table 4.2. Primers used in Chapter 4.
The primer name is listed on the left followed by the oligo sequence. Restriction enzymes used for cloning are noted in the third
column and is underlines in the sequence. Features created or altered by the oligo are listed in the fourth column and bolded in the
sequence.
Restriction
site

Feature

ACTCGAGCATGCCCAAGAAAAAGCGGAAGGTGGACAAGAAGTACTCCATTG
GGACCCGCTGCCGGACCCGTCAGCCCTGCTGTCTC
GACGGGTCCGGCAGCGGGTCCATGGTGAGCAAGGGCG

PspXI

SV40
NLS

GFP NLS R411 Cas9 F-

CAATTGTCAGACCTTCCTCTTCTTTTTCGGCTTGTACAGCTCGTCCATG
CCGCTTTTTCTTGGGCATGCTCGAGTGTTACGAAGTG

MfeI

411 GFP R+
LDSP HygR NsiI
F+
LDSP BspQI
R+CSterm sgRNA
F+
CSterm sgRNA
RCSterm sgRNA
R2Ribi CRISPR F+
Ribi CRISPR RCas9 3' RE AscI
F+
Cas9 3' RE R1-

CCGAAAAAGAAGAGGAAGGTCTGACAATTGGAAAGATCCAAGAGAG

Primer name
CRISPR
constructs

Primer sequence

Cas9 NLS F+
Cas9 linker RGFP linker F+

NcoI

PspXI
SV40
NLS

ATGCATACTTGGAAGATGGAGTGGATGGAGG

NsiI

GCTCTTCCAGCTGGTCACTGGATTTTGGTTTTAG

BspQI

AATCGATAGGCCTTGGTACCATGGGAAAGAAAGGATGAGAA

ClaI

GGTGCATGGGTTGACCGGTCGAGGAGGCATTGTATTTAC

AgeI

GGGTTGACCGGTGCAAAGCTGACGCCCTTTTC
CCATGGTACCAAGGCCTATCGATTCTGTGGATGGAGGG
GCTTTTTCTTGGGCATGCTCGAGGGTTGCGTGTGTATCTGTGTG

AgeI

CTCTGACCAACTTGGGCG
GGGCTAGCGTAGTCCGGCACGTCATAGGGGTAGTTAACGGACCCGCTGCCG
165

SV40
NLS

ClaI
PspXI

NheI

HA tag

Table 4.2 (cont'd)
GACC
Cas9 3' RE R2Nlux HpaI F+

CATCACAATTGTCAGACCTTCCTCTTCTTTTTCGGGCTAGCGTAGTCCGG
GTTAACATGGTGTTTACTCTCGAGGAC

MfeI

Nlux NheI RCEN/ARS RCEN/ARS F+
Crispr compact
F+
Crispr compact
RCEN/ARS -bspq
sdm F+
CEN/ARS -bspq
sdm R35S terminator
F+
35S terminator
RLDSPpro F+
HygR R-

GCTAGCCACCATGGACGCGTAGTCGGGCACGTC
GAGTTGACCGGTGGCCGGCCGGTTTCTTAGACGGATCGCTTG
CTTTGCACCGGTGTTTAAACACCTGGGTCCTTTTCATCACGTG

NheI

CTTTGCACCGGTGGCACTTTTCGGGGAAATGTG

AgeI

GCCATGGCGGCCGCACTAGTAGTAGATGCCGACCGGAGTC

NotI

Target cloning
sgHH NR-1 ClaI
F+
sgHH NR-1 RsgHH NR-2 ClaI
F+
sgHH NR-2 R-

HpaI

AgeI
AgeI

ACAAGATAAAAGGTAGTATTTGTTGGC

343 G to
A

ACTTCCTGCTCTCAGGTATTAATG

A to T

GCTTGAACTAGTAGTAGATG

SpeI

ACATGTTTAAACCAGGTCACTGGATTTTGG
ACGTAGGCGGCCGCGATGGAGTGGATGGAGGAGGAGG
TCGGCAGCTAGCCTATTCCTTTGCCCTCGGAC

PmeI

GTTTCGTCCTCACGGACTCATCAGGTGTGCATCGATGGTAATACGGTTATCCAC
AG
GAGTAAGCTCGTCGTGTGCGGCTCGGCGTTAAAGTTTTAGAGCTAGAAATAGC
AAG
GTTTCGTCCTCACGGACTCATCAGGTCTCGATCGATGGTAATACGGTTATCCAC
AG
GAGTAAGCTCGTCGTCTCGCGCGTCTGTACTGGGTTTTAGAGCTAGAAATAGC
AAG
166

NotI
NheI

ClaI

ClaI

Table 4.2 (cont'd)
Detection
primers
NR F+
NR RCas9 epi F+
Cas epi R-

CCCCCACTCAAGAGTAACTG
AATGGAGGTGCTCACTGCAC
ACCATGCGCATGATGCCTAC
CGTCCAGGACCTCCTTTGTAG

Southern blot
probes
HygR probe F+
HygR probe RAmpR probe F+
AmpR probe R-

AGCCAGACGAGCGGGTTC
CTTCTGCGGGCGATTTGT
TTTCCGTGTCGCCCTTAT
GCTCGTCGTTTGGTATGG

167

Chapter 5. Concluding Remarks
Characterization of growth in light:dark cycles
I found that N. oceanica growth is coordinated under cycling light conditions, with cyclic
changes in cell physiology, metabolite levels, and transcript abundance (Chapter 2)(45). During
the day N. oceanica cells grow in size and divide early in the night (Chapter 2)(45). Cellular
lipids in the form of polar lipids and TAG are accumulated during the day, as well as cellular
sugars (Chapter 2)(45). On a dry-weight basis TAG and sugars oscillate, with accumulation
during the day and decreases during the dark period, indicating these act as storage compounds
during the dark period (Chapter 2)(45).
Measurements of global transcript abundance indicated coordination between
transcription and metabolism during the light:dark cycle (Chapter 2)(45). A majority of genes
(63.7%) were found to have phased expression with different processes active at different times
of the day (Chapter 2)(45). Cluster analysis followed by analysis for GO term enrichment
identified processes phased to different times during the day including DNA synthesis,
photosynthesis, and translation (Chapter 2)(45). In the case of LDSP the transcript and protein
abundance were correlated (Chapter 2)(45). The RNA-seq data is a useful resource for
generating new hypotheses and informed the subsequent studies (Chapter 2)(45). Work to
characterize whether the observed oscillations are regulated by a circadian clock under freerunning conditions is continuing. Circadian bioluminescent reporter lines have been established
and I have identified putative clock component genes for disruption by CRISPR/Cas9.
The genes of the EPA biosynthetic pathway are strongly co-expressed during the
light:dark cycle, with an increase in transcript abundance starting at dawn and peaking midday
(Chapter 2 and Chapter 3)(15, 45). This suggests the genes of the pathway may be coregulated

168

by light. The four LC-PUFA FADs and delta-6 FAE cDNAs were isolated, and the sequences
analyzed and deposited with NCBI (Chapter 3)(15). Heterologous expression of these cDNAs in
S. cerevisiae led to production of LC-PUFAs and ultimately EPA at 0.1% TFA (Chapter 3)(15).
The successful reconstitution of the pathway in yeast provided proof of concept for further
biotechnological studies focusing on these genes to realize their potential. Therefore,
overexpression in the native host, N. oceanica, was tested for promoting alterations in the fatty
acid profile. Overproduction of a single (delta-9, delta-12, delta-6) FAD increased LC-PUFA and
EPA proportions by ~35% and ~25% of TFA, respectively (Chapter 3)(15). Stacking of dual and
triple FAD overexpression cassettes resulted in lines with two or three overproduced FADs,
however the fatty acid profile was not altered further compared to single FAD overexpression
lines (Chapter 3)(15).
Thus the EPA pathway of N. oceanica could potentially be useful for the production of
LC-PUFAs for human consumption. In order to make the pathway widely available for
experimentation, the yeast expression vectors were deposited with Addgene. The limitation of
EPA accumulation in N. oceanica could be due to the physiological effect of changing the fatty
acid composition, and future work to channel EPA to TAG may lead to further enhancements.
Investigations into the role of light regulation on the EPA pathway are ongoing.

Development of transgenic tools
In order to investigate the roles of specific genes, genome modification techniques to achieve the
expression of transgenes and the inactivation of endogenous genes are necessary. To build a
flexible high-capability toolkit, many elements are needed. The essential components for
transgene expression include promoters, terminators, resistance markers, and reporter genes. The

169

addition of 2A peptides and self-cleaving ribozymes enable targeted breaks in polypeptides and
oligoribonuleotides, respectively. Several endogenous promoters have been utilized for
transgenic expression; with bidirectional promoters proving particularly useful due to their
capacity to express two genes. Based on the RNA-Seq data generated in Chapter 2, the
unidirectional EF promoter and the Ribi bidirectional promoter were identified, and tested for
transgenic expression (Chapter 3)(15). Several reporters were implemented in N. oceanica with
both fluorescent proteins (including green, yellow, and cyan variants), and luciferases (including
firefly and NanoLuciferase) used (Chapter 3)(15). These reporters were employed to localize
proteins and quantify transgene expression, respectively (Chapter 3)(15). Endogenous
terminators for the CS, LDSP, and HS genes were utilized in the toolkit (Chapter 3)(15). For use
of multiple constructs in one strain both HygR and BleR antibiotic resistance markers are
available (Chapter 3). After screening several variants of 2A peptides, the P2A of 60 amino acids
was found to be most effective at causing ribosomal skipping (Chapter 3)(15). These elements
were integrated into several vectors for gene overexpression and stacking (Chapter 3)(15).
The aforementioned vector toolkit was deposited with Addgene for wide access by the
scientific community and I am continuing to develop more advanced genetic engineering
techniques. The luciferases reporter proteins are proving particularly useful for monitoring
transgene expression, and I am testing additional reporters and biosensors. In ongoing work, I
found several additional antibiotic selection agents and implemented resistance markers. I
constructed destination and entry vectors to combine multiple stacking cassettes with the
capability to produce up to six transgenes, and used the system to produce four transgenes from a
single transformation. Ongoing work to characterize additional bidirectional promoters identified

170

in Chapter 3 is underway. For example, I found the bidirectional promoter regulating the nitrate
reductase and transporter genes is conditionally expressed depending on the nitrogen source.
A system to disrupt a target gene is needed for robust model organisms and
biotechnological chassis organisms. The CRISPR/Cas9 RNA-guided nuclease is a potent tool for
genome modification and the dual components were optimized for N. oceanica as described in
Chapter 4. A series of Cas9-reporter fusions were tested for expression and nuclear location, and
single-guide RNAs were produced with flanking self-cleaving ribozymes for efficient gene
targeting (Chapter 4). N. oceanica has the ability to utilize episomes for transgene expression,
which was used as a platform for the CRISPR system (Chapter 4). After a mutation is produced
and antibiotic selection pressure is removed, the construct will be lost, producing a strain that is
marker and transgene free (Chapter 4). This will be important for future implementation of
engineered but non-transgenic production strains in outdoor ponds. A nitrate reductase knockout
(NR-KO) line was developed in this way, which has lost the ability to grow on nitrate (Chapter
4). This strain and the vectors utilized provide a facile new selection system and are deposited
with public access repositories, to allow broad access to scientists. Due to the NR gene being
required for growth on nitrate, work is ongoing to develop the NR-KO strain and the NR gene
into an auxotrophic selection system by complementation. The developed vectors can potentially
be used in marker-free genetic engineering and episomes as an artificial chromosome.
Additional RNA-seq and genome-wide datasets will enable charting of regulatory maps
and identification of crucial enzymatic steps necessary for survival under dynamic environmental
conditions or which control metabolic flux into bioproducts. The key regulators and enzymes
will be targets for genetic engineering, in part using tools established in this study. A genetic
engineering toolkit requires the ability go express genes at different levels and robust reporters

171

for characterization. The NR, VCP, and Ribi bidirectional promoters identified in this study
express at different levels and under different conditions, so regulation of transgenes can be finetuned. Putative rate-limiting enzymes can now be overexpressed rapidly and in a combinatorial
manner by gene stacking. It is possible transcriptional reprogramming may be superior to
promoter swapping for altering gene expression, and this may be feasible by CRISPR
transcriptional activators and repressors. Either way, transgene promoter design and
transcriptional reprogramming techniques will be aided by a greater understanding of the TF:
DNA motif interactions that underly transcriptional regulation. The FP and lux reporters
integrated in our toolkit will enable high-throughput and high-resolution characterization of
gene expression and function. For example, Nlux protein fusions can track protein production, be
easily screened for, used as a BRET donor, or fused to a FP for localization. Epitope tagging of
TFs enable several methods for studying DNA and protein interactions, such as chromatin
immunoprecipitation DNA sequencing (CHIP-Seq) and, co-immunoprecipitation massspectrometry (CoIP-MS). Additionally, CRISPR chromatin affinity mass-spectrometry
(CRISPR-ChAP-MS) is a newly developed technique using non-cutting Cas9 to isolate a genome
sequence and the associated proteins, which are identified by MS (266). Thus the tools
developed in this study make possible state-of-the-art techniques to unravel the molecular
regulators of metabolism in N. oceanica.

172

APPENDIX

173

Chapter 1. is prepared as a review article for Plant Cell Reports titled "Nannochloropsis oceanica
an open-access oleaginous microalga".
Chapter 2. Transcriptional coordination of physiological responses in Nannochloropsis oceanica
CCMP1779 under light:dark cycles is reproduced from "Transcriptional coordination of
physiological responses in Nannochloropsis oceanica CCMP1779 under light:dark cycles"
published by The Plant Journal on Aug 20, 2015 (DOI: 10.1111/tpj.12944) with permission.

174

Chapter 3. A toolkit for Nannochloropsis oceanica CCMP1779 enables gene stacking and
genetic engineering of the eicosapentaenoic acid pathway for enhanced long-chain
polyunsaturated fatty acid production is reproduced from "A toolkit for Nannochloropsis
oceanica CCMP1779 enables gene stacking and genetic engineering of the eicosapentaenoic acid
pathway for enhanced long-chain polyunsaturated fatty acid production" published by Plant
Biotechnology Journal on Jul 13, 2017 (DOI: 10.1111/pbi.12772) under a Creative Commons
Attribution License (CC-BY).

Chapter 4. Non-transgenic marker-free gene disruption by an episomal CRISPR system in the
oleaginous microalga, Nannochloropsis oceanica CCMP1779 has been submitted to ACS
Synthetic Biology and is reproduced under the terms of the AMERICAN CHEMICAL
SOCIETY JOURNAL PUBLISHING AGREEMENT.

175

REFERENCES

176

REFERENCES

1.

Zou, N., Zhang, C., Cohen, Z., and Richmond, A. (2000) Production of cell mass and
eicosapentaenoic acid (EPA) in ultrahigh cell density cultures of Nannochloropsis sp.
(Eustigmatophyceae), European Journal of Phycology 35, 127-133.

2.

Mühlroth, A., Li, K., Røkke, G., Winge, P., Olsen, Y., Hohmann-Marriott, M., Vadstein,
O., and Bones, A. (2013) Pathways of Lipid Metabolism in Marine Algae, Co-Expression
Network, Bottlenecks and Candidate Genes for Enhanced Production of EPA and DHA
in Species of Chromista, Marine Drugs 11, 4662-4697.

3.

Yaakob, Z., Ali, E., Zainal, A., Mohamad, M., and Takriff, M. (2014) An overview:
biomolecules from microalgae for animal feed and aquaculture, Journal of Biological
Research-Thessaloniki 21, 6.

4.

Sheehan, J., Dunahay, T., Benemann, J., and Roessler, P. (1998) Look Back at the U.S.
Department of Energy's Aquatic Species Program: Biodiesel from Algae; Close-Out
Report.

5.

Chew, K. W., Yap, J. Y., Show, P. L., Suan, N. H., Juan, J. C., Ling, T. C., Lee, D.-J.,
and Chang, J.-S. (2017) Microalgae biorefinery: High value products perspectives,
Bioresource Technology 229, 53-62.

6.

Rodolfi, L., Chini Zittelli, G., Bassi, N., Padovani, G., Biondi, N., Bonini, G., and
Tredici, M. R. (2009) Microalgae for oil: Strain selection, induction of lipid synthesis and
outdoor mass cultivation in a low-cost photobioreactor, Biotechnology and
Bioengineering 102, 100-112.

7.

Unkefer, C. J., Sayre, R. T., Magnuson, J. K., Anderson, D. B., Baxter, I., Blaby, I. K.,
Brown, J. K., Carleton, M., Cattolico, R. A., Dale, T., Devarenne, T. P., Downes, C. M.,
Dutcher, S. K., Fox, D. T., Goodenough, U., Jaworski, J., Holladay, J. E., Kramer, D. M.,
Koppisch, A. T., Lipton, M. S., Marrone, B. L., McCormick, M., Molnár, I., Mott, J. B.,
Ogden, K. L., Panisko, E. A., Pellegrini, M., Polle, J., Richardson, J. W., Sabarsky, M.,
Starkenburg, S. R., Stormo, G. D., Teshima, M., Twary, S. N., Unkefer, P. J., Yuan, J. S.,
and Olivares, J. A. (2017) Review of the algal biology program within the National
Alliance for Advanced Biofuels and Bioproducts, Algal Research 22, 187-215.

8.

Meng, Y., Jiang, J., Wang, H., Cao, X., Xue, S., Yang, Q., and Wang, W. (2015) The
characteristics of TAG and EPA accumulation in Nannochloropsis oceanica IMET1
under different nitrogen supply regimes, Bioresource Technology 179, 483-489.

9.

Jia, J., Han, D., Gerken, H. G., Li, Y., Sommerfeld, M., Hu, Q., and Xu, J. (2015)
Molecular mechanisms for photosynthetic carbon partitioning into storage neutral lipids
in Nannochloropsis oceanica under nitrogen-depletion conditions, Algal Research 7, 6677.

177

10.

Xiao, Y., Zhang, J., Cui, J., Yao, X., Sun, Z., Feng, Y., and Cui, Q. (2015) Simultaneous
accumulation of neutral lipids and biomass in Nannochloropsis oceanica IMET1 under
high light intensity and nitrogen replete conditions, Algal Research 11, 55-62.

11.

Vieler, A., Wu, G., Tsai, C.-H., Bullard, B., Cornish, A. J., Harvey, C., Reca, I.-B.,
Thornburg, C., Achawanantakun, R., Buehl, C. J., Campbell, M. S., Cavalier, D., Childs,
K. L., Clark, T. J., Deshpande, R., Erickson, E., Armenia Ferguson, A., Handee, W.,
Kong, Q., Li, X., Liu, B., Lundback, S., Peng, C., Roston, R. L., Sanjaya, Simpson, J. P.,
TerBush, A., Warakanont, J., Zäuner, S., Farre, E. M., Hegg, E. L., Jiang, N., Kuo, M.H., Lu, Y., Niyogi, K. K., Ohlrogge, J., Osteryoung, K. W., Shachar-Hill, Y., Sears, B.
B., Sun, Y., Takahashi, H., Yandell, M., Shiu, S.-H., and Benning, C. (2012) Genome,
Functional Gene Annotation, and Nuclear Transformation of the Heterokont Oleaginous
Alga Nannochloropsis oceanica CCMP1779, PLoS Genet 8, e1003064.

12.

Corteggiani Carpinelli, E., Telatin, A., Vitulo, N., Forcato, C., D’Angelo, M., Schiavon,
R., Vezzi, A., Giacometti, G. M., Morosinotto, T., and Valle, G. (2013) Chromosome
Scale Genome Assembly and Transcriptome Profiling of Nannochloropsis gaditana in
Nitrogen Depletion, Molecular Plant.

13.

Radakovits, R., Jinkerson, R. E., Fuerstenberg, S. I., Tae, H., Settlage, R. E., Boore, J. L.,
and Posewitz, M. C. (2012) Draft genome sequence and genetic transformation of the
oleaginous alga Nannochloropsis gaditana, Nat Commun 3, 686.

14.

Kilian, O., Benemann, C. S. E., Niyogi, K. K., and Vick, B. (2011) High-efficiency
homologous recombination in the oil-producing alga Nannochloropsis sp., Proceedings
of the National Academy of Sciences of the United States of America 108, 21265-21269.

15.

Poliner, E., Pulman, J. A., Zienkiewicz, K., Childs, K., Benning, C., and Farre, E. M.
(2017) A toolkit for Nannochloropsis oceanica CCMP1779 enables gene stacking and
genetic engineering of the eicosapentaenoic acid pathway for enhanced long-chain
polyunsaturated fatty acid production, Plant biotechnology journal.

16.

Wei, L., Xin, Y., Wang, Q., Yang, J., Hu, H., and Xu, J. (2017) RNAi-based targeted
gene knockdown in the model oleaginous microalgae Nannochloropsis oceanica, The
Plant Journal 89, 1236-1250.

17.

Ajjawi, I., Verruto, J., Aqui, M., Soriaga, L. B., Coppersmith, J., Kwok, K., Peach, L.,
Orchard, E., Kalb, R., Xu, W., Carlson, T. J., Francis, K., Konigsfeld, K., Bartalis, J.,
Schultz, A., Lambert, W., Schwartz, A. S., Brown, R., and Moellering, E. R. (2017) Lipid
production in Nannochloropsis gaditana is doubled by decreasing expression of a single
transcriptional regulator, Nature Biotechnology 35, 647-652.

18.

Wang, D., Ning, K., Li, J., Hu, J., Han, D., Wang, H., Zeng, X., Jing, X., Zhou, Q., Su,
X., Chang, X., Wang, A., Wang, W., Jia, J., Wei, L., Xin, Y., Qiao, Y., Huang, R., Chen,
J., Han, B., Yoon, K., Hill, R. T., Zohar, Y., Chen, F., Hu, Q., and Xu, J. (2014)
Nannochloropsis Genomes Reveal Evolution of Microalgal Oleaginous Traits, PLoS
Genetics 10, e1004094.
178

19.

Hu, J., Wang, D., Li, J., Jing, G., Ning, K., and Xu, J. (2014) Genome-wide identification
of transcription factors and transcription-factor binding sites in oleaginous microalgae
Nannochloropsis, Scientific Reports 4.

20.

Andrianantoandro, E., Basu, S., Karig, D. K., and Weiss, R. (2006) Synthetic biology:
new engineering rules for an emerging discipline, Molecular Systems Biology 2.

21.

Agapakis, C. M. (2014) Designing Synthetic Biology, ACS Synthetic Biology 3, 121-128.

22.

Li, J., Han, D., Wang, D., Ning, K., Jia, J., Wei, L., Jing, X., Huang, S., Chen, J., Li, Y.,
Hu, Q., and Xu, J. (2014) Choreography of Transcriptomes and Lipidomes of
Nannochloropsis Reveals the Mechanisms of Oil Synthesis in Microalgae, Plant Cell 26,
1645-1665.

23.

Jinkerson, R. E., Radakovits, R., and Posewitz, M. C. (2013) Genomic insights from the
oleaginous model alga Nannochloropsis gaditana, Bioengineered 4, 37-43.

24.

Moog, D., Stork, S., Reislöhner, S., Grosche, C., and Maier, U.-G. (2015) In vivo
Localization Studies in the Stramenopile Alga Nannochloropsis oceanica, Protist 166,
161-171.

25.

Nobusawa, T., Hori, K., Mori, H., Kurokawa, K., and Ohta, H. (2017) Differently
localized lysophosphatidic acid acyltransferases crucial for triacylglycerol biosynthesis in
the oleaginous alga Nannochloropsis, The Plant Journal 90, 547-559.

26.

Dolch, L.-J., Rak, C., Perin, G., Tourcier, G., Broughton, R., Leterrier, M., Morosinotto,
T., Tellier, F., Faure, J.-D., Falconet, D., Jouhet, J., Sayanova, O., Beaudoin, F., and
Maréchal, E. (2017) A Palmitic Acid Elongase Affects Eicosapentaenoic Acid and
Plastidial Monogalactosyldiacylglycerol Levels in Nannochloropsis, Plant Physiology
173, 742-759.

27.

Wang, Q., Lu, Y., Xin, Y., Wei, L., Huang, S., and Xu, J. (2016) Genome editing of
model oleaginous microalgae Nannochloropsis spp. by CRISPR/Cas9, The Plant Journal
88, 1071-1081.

28.

Wei, L., Xin, Y., Wang, D., Jing, X., Zhou, Q., Su, X., Jia, J., Ning, K., Chen, F., Hu, Q.,
and Xu, J. (2013) Nannochloropsis plastid and mitochondrial phylogenomes reveal
organelle diversification mechanism and intragenus phylotyping strategy in microalgae,
BMC Genomics 14, 534.

29.

Janouskovec, J., Horak, A., Obornik, M., Lukes, J., and Keeling, P. J. (2010) A common
red algal origin of the apicomplexan, dinoflagellate, and heterokont plastids, Proceedings
of the National Academy of Sciences 107, 10949-10954.

30.

Keeling, P. J. (2009) Chromalveolates and the Evolution of Plastids by Secondary
Endosymbiosis, Journal of Eukaryotic Microbiology 56, 1-8.

179

31.

Zienkiewicz, K., Zienkiewicz, A., Poliner, E., Du, Z.-Y., Vollheyde, K., Herrfurth, C.,
Marmon, S., Farré, E. M., Feussner, I., and Benning, C. (2017) Nannochloropsis, a rich
source of diacylglycerol acyltransferases for engineering of triacylglycerol content in
different hosts, Biotechnology for Biofuels 10.

32.

Xin, Y., Lu, Y., Lee, Y.-Y., Wei, L., Jia, J., Wang, Q., Wang, D., Bai, F., Hu, H., Hu, Q.,
Liu, J., Li, Y., and Xu, J. (2017) Producing Designer Oils in Industrial Microalgae by
Rational Modulation of Co-evolving Type-2 Diacylglycerol Acyltransferases, Molecular
Plant.

33.

Murakami, R., and Hashimoto, H. (2009) Unusual Nuclear Division in Nannochloropsis
oculata (Eustigmatophyceae, Heterokonta) which May Ensure Faithful Transmission of
Secondary Plastids, Protist 160, 41-49.

34.

Kroth, P., and Strotmann, H. (1999) Diatom plastids: Secondary endocytobiosis, plastid
genome and protein import, Physiologia Plantarum 107, 136-141.

35.

Bolte, K., Bullmann, L., Hempel, F., Bozarth, A., Zauner, S., and Maier, U.-G. (2009)
Protein Targeting into Secondary Plastids, Journal of Eukaryotic Microbiology 56, 9-15.

36.

Gschloessl, B., Guermeur, Y., and Cock, J. M. (2008) HECTAR: a method to predict
subcellular targeting in heterokonts, BMC Bioinformatics 9, 393.

37.

Ma, X., Yao, L., Yang, B., Lee, Y. K., Chen, F., and Liu, J. (2017) RNAi-mediated
silencing of a pyruvate dehydrogenase kinase enhances triacylglycerol biosynthesis in the
oleaginous marine alga Nannochloropsis salina, Scientific Reports 7.

38.

Loira, N., Mendoza, S., Paz Cortés, M., Rojas, N., Travisany, D., Genova, A. D.,
Gajardo, N., Ehrenfeld, N., and Maass, A. (2017) Reconstruction of the microalga
Nannochloropsis salina genome-scale metabolic model with applications to lipid
production, BMC Systems Biology 11.

39.

Bowler, C., Allen, A. E., Badger, J. H., Grimwood, J., Jabbari, K., Kuo, A., Maheswari,
U., Martens, C., Maumus, F., Otillar, R. P., Rayko, E., Salamov, A., Vandepoele, K.,
Beszteri, B., Gruber, A., Heijde, M., Katinka, M., Mock, T., Valentin, K., Verret, F.,
Berges, J. A., Brownlee, C., Cadoret, J. P., Chiovitti, A., Choi, C. J., Coesel, S., De
Martino, A., Detter, J. C., Durkin, C., Falciatore, A., Fournet, J., Haruta, M., Huysman,
M. J. J., Jenkins, B. D., Jiroutova, K., Jorgensen, R. E., Joubert, Y., Kaplan, A., Kroger,
N., Kroth, P. G., La Roche, J., Lindquist, E., Lommer, M., Martin-Jezequel, V., Lopez, P.
J., Lucas, S., Mangogna, M., McGinnis, K., Medlin, L. K., Montsant, A., Oudot-Le Secq,
M. P., Napoli, C., Obornik, M., Parker, M. S., Petit, J. L., Porcel, B. M., Poulsen, N.,
Robison, M., Rychlewski, L., Rynearson, T. A., Schmutz, J., Shapiro, H., Siaut, M.,
Stanley, M., Sussman, M. R., Taylor, A. R., Vardi, A., von Dassow, P., Vyverman, W.,
Willis, A., Wyrwicz, L. S., Rokhsar, D. S., Weissenbach, J., Armbrust, E. V., Green, B.
R., Van De Peer, Y., and Grigoriev, I. V. (2008) The Phaeodactylum genome reveals the
evolutionary history of diatom genomes, Nature 456, 239-244.

180

40.

Diner, R. E., Noddings, C. M., Lian, N. C., Kang, A. K., McQuaid, J. B., Jablanovic, J.,
Espinoza, J. L., Nguyen, N. A., Anzelmatti, M. A., Jansson, J., Bielinski, V. A., Karas, B.
J., Dupont, C. L., Allen, A. E., and Weyman, P. D. (2017) Diatom centromeres suggest a
mechanism for nuclear DNA acquisition, Proceedings of the National Academy of
Sciences 114, E6015-E6024.

41.

Schonknecht, G., Chen, W. H., Ternes, C. M., Barbier, G. G., Shrestha, R. P., Stanke, M.,
Brautigam, A., Baker, B. J., Banfield, J. F., Garavito, R. M., Carr, K., Wilkerson, C.,
Rensing, S. A., Gagneul, D., Dickenson, N. E., Oesterhelt, C., Lercher, M. J., and Weber,
A. P. M. (2013) Gene Transfer from Bacteria and Archaea Facilitated Evolution of an
Extremophilic Eukaryote, Science 339, 1207-1210.

42.

Karas, B. J., Diner, R. E., Lefebvre, S. C., McQuaid, J., Phillips, A. P., Noddings, C. M.,
Brunson, J. K., Valas, R. E., Deerinck, T. J., Jablanovic, J., Gillard, J. T., Beeri, K.,
Ellisman, M. H., Glass, J. I., Hutchison, C. A., 3rd, Smith, H. O., Venter, J. C., Allen, A.
E., Dupont, C. L., and Weyman, P. D. (2015) Designer diatom episomes delivered by
bacterial conjugation, Nat Commun 6, 6925.

43.

Starkenburg, S. R., Kwon, K. J., Jha, R. K., McKay, C., Jacobs, M., Chertkov, O., Twary,
S., Rocap, G., and Cattolico, R. (2014) A pangenomic analysis of the Nannochloropsis
organellar genomes reveals novel genetic variations in key metabolic genes, BMC
Genomics 15, 212.

44.

Mühlroth, A., Winge, P., Assimi, A. E., Jouhet, J., Marechal, E., Hohmann-Marriott, M.
F., Vadstein, O., and Bones, A. M. (2017) Mechanisms of phosphorus acquisition and
lipid class remodelling under P limitation in a marine microalga, Plant Physiology.

45.

Poliner, E., Panchy, N., Newton, L., Wu, G., Lapinsky, A., Bullard, B., Zienkiewicz, A.,
Benning, C., Shiu, S. H., and Farre, E. M. (2015) Transcriptional coordination of
physiological responses in Nannochloropsis oceanica CCMP1779 under light/dark
cycles, The Plant journal : for cell and molecular biology 83, 1097-1113.

46.

Alboresi, A., Perin, G., Vitulo, N., Diretto, G., Block, M. A., Jouhet, J., Meneghesso, A.,
Valle, G., Giuliano, G., Maréchal, E., and Morosinotto, T. (2016) Light Remodels Lipid
Biosynthesis in Nannochloropsis gaditana by Modulating Carbon Partitioning Between
Organelles, Plant Physiology, pp.00599.02016.

47.

Tsai, C. H., Warakanont, J., Takeuchi, T., Sears, B. B., Moellering, E. R., and Benning,
C. (2014) The protein Compromised Hydrolysis of Triacylglycerols 7 (CHT7) acts as a
repressor of cellular quiescence in Chlamydomonas, Proceedings of the National
Academy of Sciences of the United States of America 111, 15833-15838.

48.

Miller, R., Wu, G., Deshpande, R. R., Vieler, A., Gartner, K., Li, X., Moellering, E. R.,
Zauner, S., Cornish, A. J., Liu, B., Bullard, B., Sears, B. B., Kuo, M. H., Hegg, E. L.,
Shachar-Hill, Y., Shiu, S. H., and Benning, C. (2010) Changes in transcript abundance in
Chlamydomonas reinhardtii following nitrogen deprivation predict diversion of
metabolism, Plant Physiology 154, 1737-1752.
181

49.

Chauton, M. S., Winge, P., Brembu, T., Vadstein, O., and Bones, A. M. (2013) Gene
Regulation of Carbon Fixation, Storage, and Utilization in the Diatom Phaeodactylum
tricornutum Acclimated to Light/Dark Cycles, Plant Physiology 161, 1034-1048.

50.

Huysman, M. J., Fortunato, A. E., Matthijs, M., Costa, B. S., Vanderhaeghen, R., Van
den Daele, H., Sachse, M., Inze, D., Bowler, C., Kroth, P. G., Wilhelm, C., Falciatore, A.,
Vyverman, W., and De Veylder, L. (2013) AUREOCHROME1a-mediated induction of
the diatom-specific cyclin dsCYC2 controls the onset of cell division in diatoms
(Phaeodactylum tricornutum), Plant Cell 25, 215-228.

51.

Huysman, M. J., Martens, C., Vandepoele, K., Gillard, J., Rayko, E., Heijde, M., Bowler,
C., Inze, D., Van de Peer, Y., De Veylder, L., and Vyverman, W. (2010) Genome-wide
analysis of the diatom cell cycle unveils a novel type of cyclins involved in
environmental signaling, Genome biology 11, R17.

52.

Ashworth, J., Coesel, S., Lee, A., Armbrust, E. V., Orellana, M. V., and Baliga, N. S.
(2013) Genome-wide diel growth state transitions in the diatom Thalassiosira
pseudonana, Proceedings of the National Academy of Sciences 110, 7518-7523.

53.

Braun, R., Farre, E. M., Schurr, U., and Matsubara, S. (2014) Effects of light and
circadian clock on growth and chlorophyll accumulation of Nannochloropsis gaditana,
Journal of phycology 50, 515-525.

54.

Sukenik, A., Carmeli, Y., and Berner, T. (1989) Regulation of Fatty Acid Composition
by Irradiance Level in the Eustigmatophyte Nannochloropsis Sp., Journal of phycology
25, 686-692.

55.

Sukenik, A., and Carmeli, Y. (1990) Lipid Synthesis and Fatty Acid Composition in
Nannochloropsis Sp. (Eustigmatophyceae) Grown in a Light-Dark Cycle, Journal of
phycology 26, 463-469.

56.

Cao, S., Zhang, X., Xu, D., Fan, X., Mou, S., Wang, Y., Ye, N., and Wang, W. (2013) A
transthylakoid proton gradient and inhibitors induce a non-photochemical fluorescence
quenching in unicellular algae Nannochloropsis sp, FEBS Letters 587, 1310-1315.

57.

Chukhutsina, V. U., Fristedt, R., Morosinotto, T., and Croce, R. (2017) Photoprotection
strategies of the alga Nannochloropsis gaditana, Biochimica et Biophysica Acta (BBA) Bioenergetics 1858, 544-552.

58.

Alboresi, A., Le Quiniou, C., Yadav, S. K. N., Scholz, M., Meneghesso, A., Gerotto, C.,
Simionato, D., Hippler, M., Boekema, E. J., Croce, R., and Morosinotto, T. (2017)
Conservation of core complex subunits shaped the structure and function of photosystem
I in the secondary endosymbiont alga Nannochloropsis gaditana, New Phytologist 213,
714-726.

59.

Umetani, I., Kunugi, M., Yokono, M., Takabayashi, A., and Tanaka, A. (2017) Evidence
of the supercomplex organization of photosystem II and light-harvesting complexes in
Nannochloropsis granulata, Photosynthesis Research.
182

60.

Schneider, J. C., Livne, A., Sukenik, A., and Roessler, P. G. (1995) A mutant of
Nannochloropsis deficient in eicosapentaenoic acid production, Phytochemistry 40, 807814.

61.

Schneider, J. C., and Roessler, P. (1994) Radiolabeling Studies Of Lipids And Fatty
Acids In Nannochloropsis (Eustigmatophyceae), An Oleaginous Marine Alga1, Journal
of phycology 30, 594-598.

62.

Pal, D., Khozin-Goldberg, I., Didi-Cohen, S., Solovchenko, A., Batushansky, A., Kaye,
Y., Sikron, N., Samani, T., Fait, A., and Boussiba, S. (2013) Growth, lipid production and
metabolic adjustments in the euryhaline eustigmatophyte Nannochloropsis oceanica
CCALA 804 in response to osmotic downshift, Applied Microbiology and Biotechnology
97, 8291-8306.

63.

Hildebrand, M., Manandhar-Shrestha, K., and Abbriano, R. (2017) Effects of
chrysolaminarin synthase knockdown in the diatom Thalassiosira pseudonana:
Implications of reduced carbohydrate storage relative to green algae, Algal Research 23,
66-77.

64.

Arnold, A. A., Genard, B., Zito, F., Tremblay, R., Warschawski, D. E., and Marcotte, I.
(2015) Identification of lipid and saccharide constituents of whole microalgal cells by
13C solid-state NMR, Biochimica et Biophysica Acta (BBA) - Biomembranes 1848, 369377.

65.

Scholz, M. J., Weiss, T. L., Jinkerson, R. E., Jing, J., Roth, R., Goodenough, U.,
Posewitz, M. C., and Gerken, H. G. (2014) Ultrastructure and Composition of the
Nannochloropsis gaditana Cell Wall, Eukaryotic Cell 13, 1450-1464.

66.

Jeong, S. W., Nam, S. W., HwangBo, K., Jeong, W. J., Jeong, B.-r., Chang, Y. K., and
Park, Y.-I. (2017) Transcriptional Regulation of Cellulose Biosynthesis during the Early
Phase of Nitrogen Deprivation in Nannochloropsis salina, Scientific Reports 7.

67.

Stormo, G. D. (2000) DNA binding sites: representation and discovery, Bioinformatics
16, 16-23.

68.

Buitrago-Flórez, F. J., Restrepo, S., and Riaño-Pachón, D. M. (2014) Identification of
Transcription Factor Genes and Their Correlation with the High Diversity of
Stramenopiles, PLoS ONE 9, e111841.

69.

Rayko, E., Maumus, F., Maheswari, U., Jabbari, K., and Bowler, C. (2010) Transcription
factor families inferred from genome sequences of photosynthetic stramenopiles, New
Phytologist 188, 52-66.

70.

Thiriet-Rupert, S., Carrier, G., Chénais, B., Trottier, C., Bougaran, G., Cadoret, J.-P.,
Schoefs, B., and Saint-Jean, B. (2016) Transcription factors in microalgae: genome-wide
prediction and comparative analysis, BMC Genomics 17.

183

71.

Wingender, E. (2008) The TRANSFAC project as an example of framework technology
that supports the analysis of genomic regulation, Brief. Bioinformatics 9, 326-332.

72.

Kwon, S., Kang, N. K., Koh, H. G., Shin, S.-E., Lee, B., Jeong, B.-r., and Chang, Y. K.
(2017) Enhancement of biomass and lipid productivity by overexpression of a bZIP
transcription factor in Nannochloropsis salina: Engineering of Nannochloropsis with
bZIP TF, Biotechnology and Bioengineering.

73.

Schellenberger Costa, B., Sachse, M., Jungandreas, A., Bartulos, C. R., Gruber, A.,
Jakob, T., Kroth, P. G., and Wilhelm, C. (2013) Aureochrome 1a Is Involved in the
Photoacclimation of the Diatom Phaeodactylum tricornutum, PLoS ONE 8, e74451.

74.

Mann, M., Serif, M., Jakob, T., Kroth, P. G., and Wilhelm, C. (2017) PtAUREO1a and
PtAUREO1b knockout mutants of the diatom Phaeodactylum tricornutum are blocked in
photoacclimation to blue light, Journal of Plant Physiology 217, 44-48.

75.

Coesel, S., Mangogna, M., Ishikawa, T., Heijde, M., Rogato, A., Finazzi, G., Todo, T.,
Bowler, C., and Falciatore, A. (2009) Diatom PtCPF1 is a new cryptochrome/photolyase
family member with DNA repair and transcription regulation activity, EMBO reports 10,
655-661.

76.

Zou, Y., Wenzel, S., Müller, N., Prager, K., Jung, E.-M., Kothe, E., Kottke, T., and
Mittag, M. (2017) An Animal-Like Cryptochrome Controls the Chlamydomonas Sexual
Cycle, Plant Physiology 174, 1334-1347.

77.

Müller, N., Wenzel, S., Zou, Y., Künzel, S., Sasso, S., Weiß, D., Prager, K., Grossman,
A., Kottke, T., and Mittag, M. (2017) A Plant Cryptochrome Controls Key Features of
the Chlamydomonas Circadian Clock and Its Life Cycle, Plant Physiology 174, 185-201.

78.

Fortunato, A. E., Jaubert, M., Enomoto, G., Bouly, J.-P., Raniello, R., Thaler, M.,
Malviya, S., Bernardes, J. S., Rappaport, F., Gentili, B., Huysman, M. J. J., Carbone, A.,
Bowler, C., d’Alcalà, M. R., Ikeuchi, M., and Falciatore, A. (2016) Diatom
Phytochromes Reveal the Existence of Far-Red-Light-Based Sensing in the Ocean, Plant
Cell 28, 616-628.

79.

Kang, N. K., Choi, G.-G., Kim, E. K., Shin, S.-E., Jeon, S., Park, M. S., Jeong, K. J.,
Jeong, B.-r., Chang, Y. K., Yang, J.-W., and Lee, B. (2015) Heterologous overexpression
of sfCherry fluorescent protein in Nannochloropsis salina, Biotechnology Reports 8, 1015.

80.

Kang, N. K., Jeon, S., Kwon, S., Koh, H. G., Shin, S.-E., Lee, B., Choi, G.-G., Yang, J.W., Jeong, B.-r., and Chang, Y. K. (2015) Effects of overexpression of a bHLH
transcription factor on biomass and lipid production in Nannochloropsis salina,
Biotechnology for Biofuels 8.

81.

Beacham, T. A., and Ali, S. T. (2016) Growth dependent silencing and resetting of
DGA1 transgene in Nannochloropsis salina, Algal Research 14, 65-71.
184

82.

Cha, T.-S., Chen, C.-F., Yee, W., Aziz, A., and Loh, S.-H. (2011) Cinnamic acid,
coumarin and vanillin: Alternative phenolic compounds for efficient Agrobacteriummediated transformation of the unicellular green alga, Nannochloropsis sp, Journal of
Microbiological Methods 84, 430-434.

83.

Li, F., Gao, D., and Hu, H. (2014) High-efficiency nuclear transformation of the
oleaginous marine Nannochloropsis species using PCR product, Bioscience,
Biotechnology, and Biochemistry 78, 812-817.

84.

Peter Dehoff, S. A., Leah Soriaga. (2014) Autonomous replication sequences and
episomal DNA molecules, Synthetic Genomics, Inc., US9447422 B2.

85.

Diner, R. E., Bielinski, V. A., Dupont, C. L., Allen, A. E., and Weyman, P. D. (2016)
Refinement of the Diatom Episome Maintenance Sequence and Improvement of
Conjugation-Based DNA Delivery Methods, Frontiers in bioengineering and
biotechnology 4, 65.

86.

Lin, G., Wang, Y., Guo, L., Ding, H., Hu, Y., Liang, S., Zhang, Z., and Yang, G. (2017)
Verification of mutagen function of Zeocin in Nannochloropsis oceanica through
transcriptome analysis, Journal of Ocean University of China 16, 501-508.

87.

Zaslavskaia, L. A., Lippmeier, J. C., Kroth, P. G., Grossman, A. R., and Apt, K. E.
(2001) Transformation of the diatom Phaeodactylum tricornutum (Bacillariophyceae)
with a variety of selectable marker and reporter genes, Journal of phycology 36, 379-386.

88.

Huang, J., Liu, J., Li, Y., and Chen, F. (2008) Isolation and Characterization of the
Phytoene Desaturase Gene as a Potential Selective Marker for Genetic Engineering of the
Astaxanthin-Producing Green Alga Chlorella Zofingiensis (Chlorophyta), Journal of
phycology 44, 684-690.

89.

Cheah, Y. E., Albers, S. C., and Peebles, C. A. M. (2013) A novel counter-selection
method for markerless genetic modification in Synechocystis sp. PCC 6803,
Biotechnology Progress 29, 23-30.

90.

Wei, H., Shi, Y., Ma, X., Pan, Y., Hu, H., Li, Y., Luo, M., Gerken, H., and Liu, J. (2017)
A type-I diacylglycerol acyltransferase modulates triacylglycerol biosynthesis and fatty
acid composition in the oleaginous microalga, Nannochloropsis oceanica, Biotechnology
for Biofuels 10.

91.

Kaye, Y., Grundman, O., Leu, S., Zarka, A., Zorin, B., Didi-Cohen, S., Khozin-Goldberg,
I., and Boussiba, S. (2015) Metabolic engineering toward enhanced LC-PUFA
biosynthesis in Nannochloropsis oceanica: Overexpression of endogenous Δ12
desaturase driven by stress-inducible promoter leads to enhanced deposition of
polyunsaturated fatty acids in TAG, Algal Research 11, 387-398.

92.

Peter Dehoff, L. S. (2014) Nannochloropsis kozak consensus sequence, Exxonmobil
Research And Engineering Company, US9447422 B2.
185

93.

Gallie, D. R., Sleat, D. E., Watts, J. W., Turner, P. C., and Wilson, T. M. A. (1987) The
5'-leader sequence of tobacco mosaic virus RNA enhances the expression of foreign gene
transcripts in vitro and in vivo, Nucleic Acids Research 15, 3257-3273.

94.

Xue, J., Niu, Y.-F., Huang, T., Yang, W.-D., Liu, J.-S., and Li, H.-Y. (2015) Genetic
improvement of the microalga Phaeodactylum tricornutum for boosting neutral lipid
accumulation, Metabolic Engineering 27, 1-9.

95.

Li, D.-W., Cen, S.-Y., Liu, Y.-H., Balamurugan, S., Zheng, X.-Y., Alimujiang, A., Yang,
W.-D., Liu, J.-S., and Li, H.-Y. (2016) A type 2 diacylglycerol acyltransferase accelerates
the triacylglycerol biosynthesis in heterokont oleaginous microalga Nannochloropsis
oceanica, Journal of Biotechnology 229, 65-71.

96.

Gee, C. W., and Niyogi, K. K. (2017) The carbonic anhydrase CAH1 is an essential
component of the carbon-concentrating mechanism in Nannochloropsis oceanica,
Proceedings of the National Academy of Sciences 114, 4537-4542.

97.

Hall, M. P., Unch, J., Binkowski, B. F., Valley, M. P., Butler, B. L., Wood, M. G., Otto,
P., Zimmerman, K., Vidugiris, G., Machleidt, T., Robers, M. B., Benink, H. A., Eggers,
C. T., Slater, M. R., Meisenheimer, P. L., Klaubert, D. H., Fan, F., Encell, L. P., and
Wood, K. V. (2012) Engineered luciferase reporter from a deep sea shrimp utilizing a
novel imidazopyrazinone substrate, ACS chemical biology 7, 1848-1857.

98.

Suzuki, K., Kimura, T., Shinoda, H., Bai, G., Daniels, M. J., Arai, Y., Nakano, M., and
Nagai, T. (2016) Five colour variants of bright luminescent protein for real-time
multicolour bioimaging, Nat Commun 7, 13718.

99.

Shih, C.-H., Chen, H.-Y., Lee, H.-C., and Tsai, H.-J. (2015) Purple Chromoprotein Gene
Serves as a New Selection Marker for Transgenesis of the Microalga Nannochloropsis
oculata, PLOS ONE 10, e0120780.

100.

Sharma, P., Yan, F., Doronina, V. A., Escuin-Ordinas, H., Ryan, M. D., and Brown, J. D.
(2012) 2A peptides provide distinct solutions to driving stop-carry on translational
recoding, Nucleic Acids Research 40, 3143-3151.

101.

Plucinak, T. M., Horken, K. M., Jiang, W., Fostvedt, J., Nguyen, S. T., and Weeks, D. P.
(2015) Improved and versatile viral 2A platforms for dependable and inducible high-level
expression of dicistronic nuclear genes in Chlamydomonas reinhardtii, The Plant Journal
82, 717-729.

102.

Hamilton, M. L., Haslam, R. P., Napier, J. A., and Sayanova, O. (2014) Metabolic
engineering of Phaeodactylum tricornutum for the enhanced accumulation of omega-3
long chain polyunsaturated fatty acids, Metabolic Engineering 22, 3-9.

103.

Jia, B., Zheng, Y., Xiao, K., Wu, M., Lei, Y., Huang, Y., and Hu, Z. (2016) A vector for
multiple gene co-expression in Chlamydomonas reinhardtii, Algal Research 20, 53-56.

186

104.

Moellering, E. R., and Benning, C. (2010) RNA Interference Silencing of a Major Lipid
Droplet Protein Affects Lipid Droplet Size in Chlamydomonas reinhardtii, Eukaryotic
Cell 9, 97-106.

105.

Rohr, J., Sarkar, N., Balenger, S., Jeong, B.-r., and Cerutti, H. (2004) Tandem inverted
repeat system for selection of effective transgenic RNAi strains in Chlamydomonas:
Tandem inverted repeat system for efficient RNAi, The Plant Journal 40, 611-621.

106.

De Riso, V., Raniello, R., Maumus, F., Rogato, A., Bowler, C., and Falciatore, A. (2009)
Gene silencing in the marine diatom Phaeodactylum tricornutum, Nucleic Acids
Research 37, e96-e96.

107.

Cong, L., Ran, F. A., Cox, D., Lin, S., Barretto, R., Habib, N., Hsu, P. D., Wu, X., Jiang,
W., Marraffini, L. A., and Zhang, F. (2013) Multiplex Genome Engineering Using
CRISPR/Cas Systems, Science 339, 819-823.

108.

Ran, F. A., Hsu, Patrick D., Lin, C.-Y., Gootenberg, Jonathan S., Konermann, S.,
Trevino, A. E., Scott, David A., Inoue, A., Matoba, S., Zhang, Y., and Zhang, F. (2013)
Double Nicking by RNA-Guided CRISPR Cas9 for Enhanced Genome Editing
Specificity, Cell 154, 1380-1389.

109.

Nymark, M., Sharma, A. K., Sparstad, T., Bones, A. M., and Winge, P. (2016) A
CRISPR/Cas9 system adapted for gene editing in marine algae, Scientific Reports 6,
24951.

110.

Cermak, T., Curtin, S. J., Gil-Humanes, J., Čegan, R., Kono, T. J. Y., Konečná, E.,
Belanto, J. J., Starker, C. G., Mathre, J. W., Greenstein, R. L., and Voytas, D. F. (2017) A
multi-purpose toolkit to enable advanced genome engineering in plants, Plant Cell,
tpc.00922.02016.

111.

Xie, Y., Wang, D., Lan, F., Wei, G., Ni, T., Chai, R., Liu, D., Hu, S., Li, M., Li, D.,
Wang, H., and Wang, Y. (2017) An episomal vector-based CRISPR/Cas9 system for
highly efficient gene knockout in human pluripotent stem cells, Scientific Reports 7.

112.

Baek, K., Kim, D. H., Jeong, J., Sim, S. J., Melis, A., Kim, J.-S., Jin, E., and Bae, S.
(2016) DNA-free two-gene knockout in Chlamydomonas reinhardtii via CRISPR-Cas9
ribonucleoproteins, Scientific Reports 6, 30620.

113.

Kleinstiver, B. P., Pattanayak, V., Prew, M. S., Tsai, S. Q., Nguyen, N. T., Zheng, Z., and
Joung, J. K. (2016) High-fidelity CRISPR–Cas9 nucleases with no detectable genomewide off-target effects, Nature 529, 490-495.

114.

Slaymaker, I. M., Gao, L., Zetsche, B., Scott, D. A., Yan, W. X., and Zhang, F. (2016)
Rationally engineered Cas9 nucleases with improved specificity, Science 351, 84-88.

115.

Li, X., Zhang, R., Patena, W., Gang, S. S., Blum, S. R., Ivanova, N., Yue, R., Robertson,
J. M., Lefebvre, P. A., Fitz-Gibbon, S. T., Grossman, A. R., and Jonikas, M. C. (2016)

187

An Indexed, Mapped Mutant Library Enables Reverse Genetics Studies of Biological
Processes in Chlamydomonas reinhardtii, Plant Cell 28, 367-387.
116.

Perin, G., Bellan, A., Segalla, A., Meneghesso, A., Alboresi, A., and Morosinotto, T.
(2015) Generation of random mutants to improve light-use efficiency of Nannochloropsis
gaditana cultures for biofuel production, Biotechnology for Biofuels 8, 161.

117.

Iwai, M., Hori, K., Sasaki-Sekimoto, Y., Shimojima, M., and Ohta, H. (2015)
Manipulation of oil synthesis in Nannochloropsis strain NIES-2145 with a phosphorus
starvation–inducible promoter from Chlamydomonas reinhardtii, Frontiers in
Microbiology 6.

118.

Tian, J., Zheng, M., Yang, G., Zheng, L., Chen, J., and Yang, B. (2013) Cloning and
stress-responding expression analysis of malonyl CoA-acyl carrier protein transacylase
gene of Nannochloropsis gaditana, Gene 530, 33-38.

119.

Chen, J.-W., Liu, W.-J., Hu, D.-X., Wang, X., Balamurugan, S., Alimujiang, A., Yang,
W.-D., Liu, J.-S., and Li, H.-Y. (2017) Identification of a malonyl CoA-acyl carrier
protein transacylase and its regulatory role in fatty acid biosynthesis in oleaginous
microalga Nannochloropsis oceanica: Nannochloropsis MCAT, Biotechnology and
Applied Biochemistry.

120.

Kang, N. K., Kim, E. K., Kim, Y. U., Lee, B., Jeong, W.-J., Jeong, B.-r., and Chang, Y.
K. (2017) Increased lipid production by heterologous expression of AtWRI1 transcription
factor in Nannochloropsis salina, Biotechnology for Biofuels 10.

121.

Daboussi, F., Leduc, S., Maréchal, A., Dubois, G., Guyot, V., Perez-Michaut, C., Amato,
A., Falciatore, A., Juillerat, A., Beurdeley, M., Voytas, D. F., Cavarec, L., and
Duchateau, P. (2014) Genome engineering empowers the diatom Phaeodactylum
tricornutum for biotechnology, Nature Communications 5.

122.

Work, V. H., Radakovits, R., Jinkerson, R. E., Meuser, J. E., Elliott, L. G., Vinyard, D. J.,
Laurens, L. M. L., Dismukes, G. C., and Posewitz, M. C. (2010) Increased Lipid
Accumulation in the Chlamydomonas reinhardtii sta7-10 Starchless Isoamylase Mutant
and Increased Carbohydrate Synthesis in Complemented Strains, Eukaryotic Cell 9,
1251-1261.

123.

Trentacoste, E. M., Shrestha, R. P., Smith, S. R., Gle, C., Hartmann, A. C., Hildebrand,
M., and Gerwick, W. H. (2013) Metabolic engineering of lipid catabolism increases
microalgal lipid accumulation without compromising growth, Proceedings of the
National Academy of Sciences 110, 19748-19753.

124.

Xue, Z., Sharpe, P. L., Hong, S.-P., Yadav, N. S., Xie, D., Short, D. R., Damude, H. G.,
Rupert, R. A., Seip, J. E., Wang, J., Pollak, D. W., Bostick, M. W., Bosak, M. D.,
Macool, D. J., Hollerbach, D. H., Zhang, H., Arcilla, D. M., Bledsoe, S. A., Croker, K.,
McCord, E. F., Tyreus, B. D., Jackson, E. N., and Zhu, Q. (2013) Production of omega-3
eicosapentaenoic acid by metabolic engineering of Yarrowia lipolytica, Nature
Biotechnology 31, 734-740.
188

125.

Kindle, K. L., Schnell, R. A., Fernández, E., and Lefebvre, P. A. (1989) Stable nuclear
transformation of Chlamydomonas using the Chlamydomonas gene for nitrate reductase,
J. Cell Biol. 109, 2589-2601.

126.

Diner, R. E., Schwenck, S. M., McCrow, J. P., Zheng, H., and Allen, A. E. (2016)
Genetic Manipulation of Competition for Nitrate between Heterotrophic Bacteria and
Diatoms, Frontiers in Microbiology 7.

127.

McCarthy, J. K., Smith, S. R., McCrow, J. P., Tan, M., Zheng, H., Beeri, K., Roth, R.,
Lichtle, C., Goodenough, U., Bowler, C. P., Dupont, C. L., and Allen, A. E. (2017)
Nitrate Reductase Knockout Uncouples Nitrate Transport from Nitrate Assimilation and
Drives Repartitioning of Carbon Flux in a Model Pennate Diatom, Plant Cell 29, 20472070.

128.

Galdzicki, M., Clancy, K. P., Oberortner, E., Pocock, M., Quinn, J. Y., Rodriguez, C. A.,
Roehner, N., Wilson, M. L., Adam, L., Anderson, J. C., Bartley, B. A., Beal, J.,
Chandran, D., Chen, J., Densmore, D., Endy, D., Grunberg, R., Hallinan, J., Hillson, N.
J., Johnson, J. D., Kuchinsky, A., Lux, M., Misirli, G., Peccoud, J., Plahar, H. A., Sirin,
E., Stan, G. B., Villalobos, A., Wipat, A., Gennari, J. H., Myers, C. J., and Sauro, H. M.
(2014) The Synthetic Biology Open Language (SBOL) provides a community standard
for communicating designs in synthetic biology, Nat. Biotechnol. 32, 545-550.

129.

Ma, X., Pan, K., Zhang, L., Zhu, B., Yang, G., and Zhang, X. (2016) Genetic
transformation of Nannochloropsis oculata with a bacterial phleomycin resistance gene
as dominant selective marker, Journal of Ocean University of China 15, 351-356.

130.

Chen, H. L., Li, S. S., Huang, R., and Tsai, H. J. (2008) Conditional Production of a
Functional Fish Growth Hormone in the Transgenic Line of Nannochloropsis Oculata
(Eustigmatophyceae), Journal of phycology 44, 768-776.

131.

Wei, L., Wang, Q., Xin, Y., Lu, Y., and Xu, J. (2017) Enhancing photosynthetic biomass
productivity of industrial oleaginous microalgae by overexpression of RuBisCO activase,
Algal Research 27, 366-375.

132.

Matsuo, T., and Ishiura, M. (2011) Chlamydomonas reinhardtii as a new model system
for studying the molecular basis of the circadian clock, FEBS Letters 585, 1495-1502.

133.

Nikaido, S. S., and Johnson, C. H. (2000) Daily and circadian variation in survival from
ultraviolet radiation in Chlamydomonas reinhardtii, Photochemistry and photobiology
71, 758-765.

134.

Lemaire, S. D., Hours, M., Gerard-Hirne, C., Trouabal, A., Roche, O., and Jacquot, J.-P.
(1999) Analysis of light/dark synchronization of cell-wall-less Chlamydomonas
reinhardtii (Chlorophyta) cells by flow cytometry, European Journal of Phycology 34,
279-286.

135.

McClung, C. R. (2011) The Genetics of Plant Clocks, Adv Genet 74, 105-139.
189

136.

Dodd, A. N., Salathia, N., Hall, A., Kevei, E., Toth, R., Nagy, F., Hibberd, J. M., Millar,
A. J., and Webb, A. A. (2005) Plant circadian clocks increase photosynthesis, growth,
survival, and competitive advantage, Science 309, 630-633.

137.

Ouyang, Y., Andersson, C. R., Kondo, T., Golden, S. S., and Johnson, C. H. (1998)
Resonating circadian clocks enhance fitness in cyanobacteria, Proc Natl Acad Sci U S A
95, 8660-8664.

138.

Litchman, E., Klausmeier, C. A., and Bossard, P. (2004) Phytoplankton nutrient
competition under dynamic light regimes, Limnol Oceanogr 49, 1457-1462.

139.

Adarme-Vega, T. C., Lim, D. K., Timmins, M., Vernen, F., Li, Y., and Schenk, P. M.
(2012) Microalgal biofactories: a promising approach towards sustainable omega-3 fatty
acid production, Microbial cell factories 11, 96.

140.

Hu, H., and Gao, K. (2003) Optimization of growth and fatty acid composition of a
unicellular marine picoplankton, Nannochloropsis sp., with enriched carbon sources,
Biotechnology letters 25, 421-425.

141.

Xu, F., Cai, Z. L., Cong, W., and Ouyang, F. (2004) Growth and fatty acid composition
of Nannochloropsis sp. grown mixotrophically in fed-batch culture, Biotechnology letters
26, 1319-1322.

142.

Van Vooren, G., Le Grand, F., Legrand, J., Cuine, S., Peltier, G., and Pruvost, J. (2012)
Investigation of fatty acids accumulation in Nannochloropsis oculata for biodiesel
application, Bioresource Technology 124, 421-432.

143.

Zheng, M., Tian, J., Yang, G., Zheng, L., Chen, G., Chen, J., and Wang, B. (2013)
Transcriptome sequencing, annotation and expression analysis of Nannochloropsis sp. at
different growth phases, Gene 523, 117-121.

144.

Panchy, N., Wu, G., Newton, L., Tsai, C. H., Chen, J., Benning, C., Farre, E. M., and
Shiu, S. H. (2014) Prevalence, evolution, and cis-regulation of diel transcription in
Chlamydomonas reinhardtii, G3 4, 2461-2471.

145.

Filichkin, S. A., Breton, G., Priest, H. D., Dharmawardhana, P., Jaiswal, P., Fox, S. E.,
Michael, T. P., Chory, J., Kay, S. A., and Mockler, T. C. (2011) Global profiling of rice
and poplar transcriptomes highlights key conserved circadian-controlled pathways and
cis-regulatory modules, PLoS One 6, e16907.

146.

Monnier, A., Liverani, S., Bouvet, R., Jesson, B., Smith, J., Mosser, J., Corellou, F., and
Bouget, F.-Y. (2010) Orchestrated transcription of biological processes in the marine
picoeukaryote Ostreococcus exposed to light/dark cycles, BMC Genomics 11, 192.

147.

Farre, E. M. (2012) The regulation of plant growth by the circadian clock, Plant Biology
14, 401-410.

190

148.

Putt, M., and Prézelin, B. B. (1988) Diel Periodicity Of Photosynthesis And Cell Division
Compared In Thalassiosira Weissflogii (Bacillariophyceae), Journal of phycology 24,
315-324.

149.

Moulager, M., Monnier, A., Jesson, B., Bouvet, R., Mosser, J., Schwartz, C., Garnier, L.,
Corellou, F., and Bouget, F. Y. (2007) Light-dependent regulation of cell division in
Ostreococcus: evidence for a major transcriptional input, Plant Physiology 144, 13601369.

150.

Asato, Y. (2003) Toward an understanding of cell growth and the cell division cycle of
unicellular photoautotrophic cyanobacteria, Cellular and molecular life sciences : CMLS
60, 663-687.

151.

Higashi, Y., and Seki, H. (2000) Ecological adaptation and acclimatization of natural
freshwater phytoplankters with a nutrient gradient, Environmental pollution 109, 311320.

152.

Fábregas, J., Maseda, A., Domínguez, A., Ferreira, M., and Otero, A. (2002) Changes in
the cell composition of the marine microalga, Nannochloropsis gaditana, during a
light:dark cycle, Biotechnology letters 24, 1699-1703.

153.

Michael, T. P., Mockler, T. C., Breton, G., McEntee, C., Byer, A., Trout, J. D., Hazen, S.
P., Shen, R., Priest, H. D., Sullivan, C. M., Givan, S. A., Yanovsky, M., Hong, F., Kay,
S. A., and Chory, J. (2008) Network discovery pipeline elucidates conserved time-of-dayspecific cis-regulatory modules, PLoS Genet 4, e14.

154.

Panda, S., Antoch, M. P., Miller, B. H., Su, A. I., Schook, A. B., Straume, M., Schultz, P.
G., Kay, S. A., Takahashi, J. S., and Hogenesch, J. B. (2002) Coordinated transcription of
key pathways in the mouse by the circadian clock, Cell 109, 307-320.

155.

Blasing, O. E. (2005) Sugars and Circadian Regulation Make Major Contributions to the
Global Regulation of Diurnal Gene Expression in Arabidopsis, Plant Cell 17, 3257-3281.

156.

Zinser, E. R., Lindell, D., Johnson, Z. I., Futschik, M. E., Steglich, C., Coleman, M. L.,
Wright, M. A., Rector, T., Steen, R., McNulty, N., Thompson, L. R., and Chisholm, S.
W. (2009) Choreography of the transcriptome, photophysiology, and cell cycle of a
minimal photoautotroph, prochlorococcus, PLoS One 4, e5135.

157.

Shi, T., Ilikchyan, I., Rabouille, S., and Zehr, J. P. (2010) Genome-wide analysis of diel
gene expression in the unicellular N(2)-fixing cyanobacterium Crocosphaera watsonii
WH 8501, The ISME journal 4, 621-632.

158.

Ottesen, E. A., Young, C. R., Gifford, S. M., Eppley, J. M., Marin, R., 3rd, Schuster, S.
C., Scholin, C. A., and DeLong, E. F. (2014) Ocean microbes. Multispecies diel
transcriptional oscillations in open ocean heterotrophic bacterial assemblages, Science
345, 207-212.

191

159.

Izawa, T., Mihara, M., Suzuki, Y., Gupta, M., Itoh, H., Nagano, A. J., Motoyama, R.,
Sawada, Y., Yano, M., Hirai, M. Y., Makino, A., and Nagamura, Y. (2011) OsGIGANTEA confers robust diurnal rhythms on the global transcriptome of rice in the
field, Plant Cell 23, 1741-1755.

160.

Waldbauer, J. R., Rodrigue, S., Coleman, M. L., and Chisholm, S. W. (2012)
Transcriptome and proteome dynamics of a light-dark synchronized bacterial cell cycle,
PLoS One 7, e43432.

161.

Gillard, J., Devos, V., Huysman, M. J., De Veylder, L., D'Hondt, S., Martens, C.,
Vanormelingen, P., Vannerum, K., Sabbe, K., Chepurnov, V. A., Inze, D., Vuylsteke, M.,
and Vyverman, W. (2008) Physiological and transcriptomic evidence for a close coupling
between chloroplast ontogeny and cell cycle progression in the pennate diatom Seminavis
robusta, Plant Physiol 148, 1394-1411.

162.

Setlikova, E., Setlik, I., Kupper, H., Kasalicky, V., and Prasil, O. (2005) The
photosynthesis of individual algal cells during the cell cycle of Scenedesmus quadricauda
studied by chlorophyll fluorescence kinetic microscopy, Photosynthesis Research 84,
113-120.

163.

Claudio, P. P., Tonini, T., and Giordano, A. (2002) The retinoblastoma family: twins or
distant cousins?, Genome biology 3, reviews3012.

164.

Nakajima, K., Tanaka, A., and Matsuda, Y. (2013) SLC4 family transporters in a marine
diatom directly pump bicarbonate from seawater, Proceedings of the National Academy
of Sciences of the United States of America 110, 1767-1772.

165.

Tanaka, R., Kikutani, S., Mahardika, A., and Matsuda, Y. (2014) Localization of
enzymes relating to C4 organic acid metabolisms in the marine diatom, Thalassiosira
pseudonana, Photosynthesis Research 121, 251-263.

166.

Ratledge, C. (2014) The role of malic enzyme as the provider of NADPH in oleaginous
microorganisms: a reappraisal and unsolved problems, Biotechnology letters 36, 15571568.

167.

Johnson, X., and Alric, J. (2013) Central carbon metabolism and electron transport in
Chlamydomonas reinhardtii: metabolic constraints for carbon partitioning between oil
and starch, Eukaryotic Cell 12, 776-793.

168.

Haimovich-Dayan, M., Garfinkel, N., Ewe, D., Marcus, Y., Gruber, A., Wagner, H.,
Kroth, P. G., and Kaplan, A. (2013) The role of C4 metabolism in the marine diatom
Phaeodactylum tricornutum, The New phytologist 197, 177-185.

169.

Rousvoal, S., Groisillier, A., Dittami, S. M., Michel, G., Boyen, C., and Tonon, T. (2011)
Mannitol-1-phosphate dehydrogenase activity in Ectocarpus siliculosus, a key role for
mannitol synthesis in brown algae, Planta 233, 261-273.

192

170.

Groisillier, A., Shao, Z., Michel, G., Goulitquer, S., Bonin, P., Krahulec, S., Nidetzky, B.,
Duan, D., Boyen, C., and Tonon, T. (2014) Mannitol metabolism in brown algae involves
a new phosphatase family, Journal of experimental botany 65, 559-570.

171.

Gravot, A., Dittami, S. M., Rousvoal, S., Lugan, R., Eggert, A., Collen, J., Boyen, C.,
Bouchereau, A., and Tonon, T. (2010) Diurnal oscillations of metabolite abundances and
gene analysis provide new insights into central metabolic processes of the brown alga
Ectocarpus siliculosus, The New phytologist 188, 98-110.

172.

Smith, S. R., Abbriano, R. M., and Hildebrand, M. (2012) Comparative analysis of
diatom genomes reveals substantial differences in the organization of carbon partitioning
pathways, Algal Research 1, 2-16.

173.

Takahashi, H., McCaffery, J. M., Irizarry, R. A., and Boeke, J. D. (2006) Nucleocytosolic
acetyl-coenzyme a synthetase is required for histone acetylation and global transcription,
Molecular cell 23, 207-217.

174.

Roessler, P. G., and Ohlrogge, J. B. (1993) Cloning and characterization of the gene that
encodes acetyl-coenzyme A carboxylase in the alga Cyclotella cryptica, The Journal of
biological chemistry 268, 19254-19259.

175.

Li-Beisson, Y., Shorrosh, B., Beisson, F., Andersson, M. X., Arondel, V., Bates, P. D.,
Baud, S., Bird, D., Debono, A., Durrett, T. P., Franke, R. B., Graham, I. A., Katayama,
K., Kelly, A. A., Larson, T., Markham, J. E., Miquel, M., Molina, I., Nishida, I.,
Rowland, O., Samuels, L., Schmid, K. M., Wada, H., Welti, R., Xu, C., Zallot, R., and
Ohlrogge, J. (2013) Acyl-lipid metabolism, The Arabidopsis book / American Society of
Plant Biologists 11, e0161.

176.

Vieler, A., Brubaker, S. B., Vick, B., and Benning, C. (2012) A Lipid Droplet Protein of
Nannochloropsis with Functions Partially Analogous to Plant Oleosins, Plant Physiology
158, 1562-1569.

177.

Krienitz, L., and Wirth, M. (2006) The high content of polyunsaturated fatty acids in
Nannochloropsis limnetica (Eustigmatophyceae) and its implication for food web
interactions, freshwater aquaculture and biotechnology, Limnologica - Ecology and
Management of Inland Waters 36, 204-210.

178.

Li, X., Moellering, E. R., Liu, B., Johnny, C., Fedewa, M., Sears, B. B., Kuo, M. H., and
Benning, C. (2012) A galactoglycerolipid lipase is required for triacylglycerol
accumulation and survival following nitrogen deprivation in Chlamydomonas reinhardtii,
Plant Cell 24, 4670-4686.

179.

Zentner, G. E., and Henikoff, S. (2013) Regulation of nucleosome dynamics by histone
modifications, Nature structural & molecular biology 20, 259-266.

180.

Eddy, S. R. (2011) Accelerated Profile HMM Searches, Plos Comput Biol 7.

193

181.

Koike, N., Yoo, S. H., Huang, H. C., Kumar, V., Lee, C., Kim, T. K., and Takahashi, J. S.
(2012) Transcriptional architecture and chromatin landscape of the core circadian clock
in mammals, Science 338, 349-354.

182.

Noordally, Z. B., Ishii, K., Atkins, K. A., Wetherill, S. J., Kusakina, J., Walton, E. J.,
Kato, M., Azuma, M., Tanaka, K., Hanaoka, M., and Dodd, A. N. (2013) Circadian
control of chloroplast transcription by a nuclear-encoded timing signal, Science 339,
1316-1319.

183.

Roberti, M., Polosa, P. L., Bruni, F., Manzari, C., Deceglie, S., Gadaleta, M. N., and
Cantatore, P. (2009) The MTERF family proteins: mitochondrial transcription regulators
and beyond, Biochimica et biophysica acta 1787, 303-311.

184.

Bligh, E. G., and Dyer, W. J. (1959) A rapid method of total lipid extraction and
purification, Canadian journal of biochemistry and physiology 37, 911-917.

185.

Vieler, A., Wilhelm, C., Goss, R., Süß, R., and Schiller, J. (2007) The lipid composition
of the unicellular green alga Chlamydomonas reinhardtii and the diatom Cyclotella
meneghiniana investigated by MALDI-TOF MS and TLC, Chemistry and Physics of
Lipids 150, 143-155.

186.

Cavalier, D. M., Lerouxel, O., Neumetzler, L., Yamauchi, K., Reinecke, A., Freshour, G.,
Zabotina, O. A., Hahn, M. G., Burgert, I., Pauly, M., Raikhel, N. V., and Keegstra, K.
(2008) Disrupting two Arabidopsis thaliana xylosyltransferase genes results in plants
deficient in xyloglucan, a major primary cell wall component, Plant Cell 20, 1519-1537.

187.

Trapnell, C., Pachter, L., and Salzberg, S. L. (2009) TopHat: discovering splice junctions
with RNA-Seq, Bioinformatics 25, 1105-1111.

188.

Trapnell, C., Williams, B. A., Pertea, G., Mortazavi, A., Kwan, G., van Baren, M. J.,
Salzberg, S. L., Wold, B. J., and Pachter, L. (2010) Transcript assembly and
quantification by RNA-Seq reveals unannotated transcripts and isoform switching during
cell differentiation, Nat Biotechnol 28, 511-515.

189.

Edgar, R., Domrachev, M., and Lash, A. E. (2002) Gene Expression Omnibus: NCBI
gene expression and hybridization array data repository, Nucleic Acids Res 30, 207-210.

190.

Robinson, M. D., McCarthy, D. J., and Smyth, G. K. (2010) edgeR: a Bioconductor
package for differential expression analysis of digital gene expression data,
Bioinformatics 26, 139-140.

191.

Cock, J. M., Sterck, L., Rouze, P., Scornet, D., Allen, A. E., Amoutzias, G., Anthouard,
V., Artiguenave, F., Aury, J. M., Badger, J. H., Beszteri, B., Billiau, K., Bonnet, E.,
Bothwell, J. H., Bowler, C., Boyen, C., Brownlee, C., Carrano, C. J., Charrier, B., Cho,
G. Y., Coelho, S. M., Collen, J., Corre, E., Da Silva, C., Delage, L., Delaroque, N.,
Dittami, S. M., Doulbeau, S., Elias, M., Farnham, G., Gachon, C. M. M., Gschloessl, B.,
Heesch, S., Jabbari, K., Jubin, C., Kawai, H., Kimura, K., Kloareg, B., Kupper, F. C.,
Lang, D., Le Bail, A., Leblanc, C., Lerouge, P., Lohr, M., Lopez, P. J., Martens, C.,
194

Maumus, F., Michel, G., Miranda-Saavedra, D., Morales, J., Moreau, H., Motomura, T.,
Nagasato, C., Napoli, C. A., Nelson, D. R., Nyvall-Collen, P., Peters, A. F., Pommier, C.,
Potin, P., Poulain, J., Quesneville, H., Read, B., Rensing, S. A., Ritter, A., Rousvoal, S.,
Samanta, M., Samson, G., Schroeder, D. C., Segurens, B., Strittmatter, M., Tonon, T.,
Tregear, J. W., Valentin, K., von Dassow, P., Yamagishi, T., Van de Peer, Y., and
Wincker, P. (2010) The Ectocarpus genome and the independent evolution of
multicellularity in brown algae, Nature 465, 617-621.
192.

Edgar, R. C. (2004) MUSCLE: multiple sequence alignment with high accuracy and high
throughput, Nucleic Acids Res 32, 1792-1797.

193.

Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M., and Kumar, S. (2011)
MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood,
Evolutionary Distance, and Maximum Parsimony Methods, Mol Biol Evol 28, 27312739.

194.

Reumann, S., Buchwald, D., and Lingner, T. (2012) PredPlantPTS1: A Web Server for
the Prediction of Plant Peroxisomal Proteins, Frontiers in plant science 3, 194.

195.

Claros, M. G., and Vincens, P. (1996) Computational method to predict mitochondrially
imported proteins and their targeting sequences, European journal of biochemistry /
FEBS 241, 779-786.

196.

Gruber, A., Rocap, G., Kroth, P. G., Armbrust, E. V., and Mock, T. (2015) Plastid
proteome prediction for diatoms and other algae with secondary plastids of the red
lineage, The Plant journal : for cell and molecular biology 81, 519-528.

197.

Hee-Youn Hong, G.-S. Y. J.-K. C. (2000) Direct Blue 71 staining of proteins bound to
blotting membranes, Electrophoresis 21, 841-845.

198.

Dimmic, M. W., Rest, J. S., Mindell, D. P., and Goldstein, R. A. (2002) rtREV: an amino
acid substitution matrix for inference of retrovirus and reverse transcriptase phylogeny,
Journal of molecular evolution 55, 65-73.

199.

Jones, D. T., Taylor Wr Fau - Thornton, J. M., and Thornton, J. M. The rapid generation
of mutation data matrices from protein sequences.

200.

Bothwell, J. H. F., Marie, D., Peters, A. F., Cock, J. M., and Coelho, S. M. (2014) Cell
cycles and endocycles in the model brown seaweed, Ectocarpus siliculosus, Plant
Signaling & Behavior 5, 1473-1475.

201.

Whelan, S., and Goldman, N. A general empirical model of protein evolution derived
from multiple protein families using a maximum-likelihood approach.

202.

Chen, G.-C., Yang, J., Eggersdorfer, M., Zhang, W., and Qin, L.-Q. (2016) N-3 longchain polyunsaturated fatty acids and risk of all-cause mortality among general
populations: a meta-analysis, Scientific Reports 6, 28165.

195

203.

Betancor, M. B., Sprague, M., Usher, S., Sayanova, O., Campbell, P. J., Napier, J. A., and
Tocher, D. R. (2015) A nutritionally-enhanced oil from transgenic Camelina sativa
effectively replaces fish oil as a source of eicosapentaenoic acid for fish, Sci Rep 5, 8104.

204.

Petrie, J. R., and Singh, S. P. (2011) Expanding the docosahexaenoic acid food web for
sustainable production: engineering lower plant pathways into higher plants, AoB
PLANTS 2011, plr011.

205.

Doughman, S. D., Krupanidhi, S., and Sanjeevi, C. B. (2007) Omega-3 fatty acids for
nutrition and medicine: considering microalgae oil as a vegetarian source of EPA and
DHA, Curr Diabetes Rev 3, 198-203.

206.

Martins, D., Custódio, L., Barreira, L., Pereira, H., Ben-Hamadou, R., Varela, J., and
Abu-Salah, K. (2013) Alternative Sources of n-3 Long-Chain Polyunsaturated Fatty
Acids in Marine Microalgae, Marine Drugs 11, 2259-2281.

207.

Chini Zittelli, G., Lavista, F., Bastianini, A., Rodolfi, L., Vincenzini, M., and Tredici, M.
R. (1999) Production of eicosapentaenoic acid by Nannochloropsis sp. cultures in
outdoor tubular photobioreactors, Journal of Biotechnology 70, 299-312.

208.

Spolaore, P., Joannis-Cassan, C., Duran, E., and Isambert, A. (2006) Commercial
applications of microalgae, Journal of Bioscience and Bioengineering 101, 87-96.

209.

Sukenik, A., Schneider, J. C., Roessler, P. G., Livne, A., Berner, T., Kolber, Z., Wyman,
K., Prasil, O., and Falkowski, P. G. (1998) Photosynthetic Characterization of a Mutant
of Nannochloropsis Deficient in the Synthesis of Eicosapentaenoic Acid, Israel Journal
of Plant Sciences 46, 101-108.

210.

Liu, B., Vieler, A., Li, C., Daniel Jones, A., and Benning, C. (2013) Triacylglycerol
profiling of microalgae Chlamydomonas reinhardtii and Nannochloropsis oceanica,
Bioresource Technology 146, 310-316.

211.

Qi, B., Fraser, T., Mugford, S., Dobson, G., Sayanova, O., Butler, J., Napier, J. A.,
Stobart, A. K., and Lazarus, C. M. (2004) Production of very long chain polyunsaturated
omega-3 and omega-6 fatty acids in plants, Nature Biotechnology 22, 739-745.

212.

Hong, H. (2002) High-Level Production of gamma -Linolenic Acid in Brassica juncea
Using a Delta 6 Desaturase from Pythium irregulare, PLANT PHYSIOLOGY 129, 354362.

213.

Wu, G., Truksa, M., Datla, N., Vrinten, P., Bauer, J., Zank, T., Cirpus, P., Heinz, E., and
Qiu, X. (2005) Stepwise engineering to produce high yields of very long-chain
polyunsaturated fatty acids in plants, Nat Biotechnol 23, 1013-1017.

214.

Okuda, T., Ando, A., Negoro, H., Muratsubaki, T., Kikukawa, H., Sakamoto, T.,
Sakuradani, E., Shimizu, S., and Ogawa, J. (2015) Eicosapentaenoic acid (EPA)
production by an oleaginous fungus Mortierella alpina expressing heterologous the Δ17196

desaturase gene under ordinary temperature, European Journal of Lipid Science and
Technology 117, 1919-1927.
215.

Tavares, S., Grotkjaer, T., Obsen, T., Haslam, R. P., Napier, J. A., and Gunnarsson, N.
(2011) Metabolic Engineering of Saccharomyces cerevisiae for Production of
Eicosapentaenoic Acid, Using a Novel 5-Desaturase from Paramecium tetraurelia,
Applied and Environmental Microbiology 77, 1854-1861.

216.

Hwangbo, K., Ahn, J.-W., Lim, J.-M., Park, Y.-I., Liu, J. R., and Jeong, W.-J. (2014)
Overexpression of stearoyl-ACP desaturase enhances accumulations of oleic acid in the
green alga Chlamydomonas reinhardtii, Plant Biotechnology Reports 8, 135-142.

217.

Peng, K.-T., Zheng, C.-N., Xue, J., Chen, X.-Y., Yang, W.-D., Liu, J.-S., Bai, W., and Li,
H.-Y. (2014) Delta 5 Fatty Acid Desaturase Upregulates the Synthesis of Polyunsaturated
Fatty Acids in the Marine Diatom Phaeodactylum tricornutum, Journal of Agricultural
and Food Chemistry 62, 8773-8776.

218.

Hildebrand, M., Abbriano, R. M., Polle, J. E. W., Traller, J. C., Trentacoste, E. M.,
Smith, S. R., and Davis, A. K. (2013) Metabolic and cellular organization in
evolutionarily diverse microalgae as related to biofuels production, Current Opinion in
Chemical Biology 17, 506-514.

219.

Cook, O., and Hildebrand, M. (2015) Enhancing LC-PUFA production in Thalassiosira
pseudonana by overexpressing the endogenous fatty acid elongase genes, Journal of
Applied Phycology 28, 897-905.

220.

Ruiz-Lopez, N., Haslam, R. P., Napier, J. A., and Sayanova, O. (2014) Successful highlevel accumulation of fish oil omega-3 long-chain polyunsaturated fatty acids in a
transgenic oilseed crop, The Plant journal : for cell and molecular biology 77, 198-208.

221.

Ruiz-Lopez, N., Sayanova, O., Napier, J. A., and Haslam, R. P. (2012) Metabolic
engineering of the omega-3 long chain polyunsaturated fatty acid biosynthetic pathway
into transgenic plants, Journal of experimental botany 63, 2397-2410.

222.

Metz, J. G. (2001) Production of Polyunsaturated Fatty Acids by Polyketide Synthases in
Both Prokaryotes and Eukaryotes, Science 293, 290-293.

223.

Cahoon, E. B., Shockey, J. M., Dietrich, C. R., Gidda, S. K., Mullen, R. T., and Dyer, J.
M. (2007) Engineering oilseeds for sustainable production of industrial and nutritional
feedstocks: solving bottlenecks in fatty acid flux, Current Opinion in Plant Biology 10,
236-244.

224.

Halpin, C. (2005) Gene stacking in transgenic plants - the challenge for 21st century plant
biotechnology: The challenge of transgene and trait stacking, Plant biotechnology journal
3, 141-155.

225.

Naqvi, S., Farré, G., Sanahuja, G., Capell, T., Zhu, C., and Christou, P. (2010) When
more is better: multigene engineering in plants, Trends in Plant Science 15, 48-56.
197

226.

Szymczak, A. L., Workman, C. J., Wang, Y., Vignali, K. M., Dilioglou, S., Vanin, E. F.,
and Vignali, D. A. A. (2004) Correction of multi-gene deficiency in vivo using a single
'self-cleaving' 2A peptide–based retroviral vector, Nature Biotechnology 22, 589-594.

227.

Szymczak-Workman, A. L., Vignali, K. M., and Vignali, D. A. A. (2012) Design and
Construction of 2A Peptide-Linked Multicistronic Vectors, Cold Spring Harbor
Protocols 2012, pdb.ip067876-pdb.ip067876.

228.

Kim, J. H., Lee, S.-R., Li, L.-H., Park, H.-J., Park, J.-H., Lee, K. Y., Kim, M.-K., Shin, B.
A., and Choi, S.-Y. (2011) High Cleavage Efficiency of a 2A Peptide Derived from
Porcine Teschovirus-1 in Human Cell Lines, Zebrafish and Mice, PLoS ONE 6, e18556.

229.

de Felipe, P., Hughes, L. E., Ryan, M. D., and Brown, J. D. (2003) Co-translational,
Intraribosomal Cleavage of Polypeptides by the Foot-and-mouth Disease Virus 2A
Peptide, Journal of Biological Chemistry 278, 11441-11448.

230.

López Alonso, D., García-Maroto, F., Rodríguez-Ruiz, J., Garrido, J. A., and Vilches, M.
A. (2003) Evolution of the membrane-bound fatty acid desaturases, Biochemical
Systematics and Ecology 31, 1111-1124.

231.

Broun, P. (1998) Catalytic Plasticity of Fatty Acid Modification Enzymes Underlying
Chemical Diversity of Plant Lipids, Science 282, 1315-1317.

232.

Domergue, F., Lerchl, J., Zähringer, U., and Heinz, E. (2002) Cloning and functional
characterization of Phaeodactylum tricornutum front-end desaturases involved in
eicosapentaenoic acid biosynthesis: Δ5- and Δ6-fatty acid desaturases from diatom,
European Journal of Biochemistry 269, 4105-4113.

233.

Meesapyodsuk, D., and Qiu, X. (2012) The Front-end Desaturase: Structure, Function,
Evolution and Biotechnological Use, Lipids 47, 227-237.

234.

Hashimoto, K., Yoshizawa, A. C., Okuda, S., Kuma, K., Goto, S., and Kanehisa, M.
(2008) The repertoire of desaturases and elongases reveals fatty acid variations in 56
eukaryotic genomes, The Journal of Lipid Research 49, 183-191.

235.

Tvrdik, P., Westerberg, R., Silve, S., Asadi, A., Jakobsson, A., Cannon, B., Loison, G.,
and Jacobsson, A. (2000) Role of a new mammalian gene family in the biosynthesis of
very long chain fatty acids and sphingolipids, J. Cell Biol. 149, 707-718.

236.

Oh, C. S., Toke, D. A., Mandala, S., and Martin, C. E. (1997) ELO2 and ELO3,
homologues of the Saccharomyces cerevisiae ELO1 gene, function in fatty acid
elongation and are required for sphingolipid formation, The Journal of biological
chemistry 272, 17376-17384.

237.

Jiang, M., Guo, B., Wan, X., Gong, Y., Zhang, Y., and Hu, C. (2014) Isolation and
Characterization of the Diatom Phaeodactylum Δ5-Elongase Gene for Transgenic LCPUFA Production in Pichia pastoris, Marine Drugs 12, 1317-1334.

198

238.

Yu, S. Y., Li, H., Tong, M., Ouyang, L. L., and Zhou, Z. G. (2012) Identification of a Δ6
fatty acid elongase gene for arachidonic acid biosynthesis localized to the endoplasmic
reticulum in the green microalga Myrmecia incisa Reisigl, Gene 493, 219-227.

239.

Moller, S., Croning, M. D. R., and Apweiler, R. (2001) Evaluation of methods for the
prediction of membrane spanning regions, Bioinformatics 17, 646-653.

240.

Stukey, J. E., McDonough, V. M., and Martin, C. E. (1990) The OLE1 gene of
Saccharomyces cerevisiae encodes the delta 9 fatty acid desaturase and can be
functionally replaced by the rat stearoyl-CoA desaturase gene, The Journal of biological
chemistry 265, 20144-20149.

241.

Gill, D. R., Smyth, S. E., Goddard, C. A., Pringle, I. A., Higgins, C. F., Colledge, W. H.,
and Hyde, S. C. (2001) Increased persistence of lung gene expression using plasmids
containing the ubiquitin C or elongation factor 1alpha promoter, Gene Ther. 8, 15391546.

242.

Kim, D. W., Uetsuki, T., Kaziro, Y., Yamaguchi, N., and Sugano, S. (1990) Use of the
human elongation factor 1α promoter as a versatile and efficient expression system, Gene
91, 217-223.

243.

Seo, S., Jeon, H., Hwang, S., Jin, E., and Chang, K. S. (2015) Development of a new
constitutive expression system for the transformation of the diatom Phaeodactylum
tricornutum, Algal Research 11, 50-54.

244.

Doronina, V. A., Wu, C., de Felipe, P., Sachs, M. S., Ryan, M. D., and Brown, J. D.
(2008) Site-specific release of nascent chains from ribosomes at a sense codon,
Molecular and cellular biology 28, 4227-4239.

245.

Burén, S., Ortega-Villasante, C., Ötvös, K., Samuelsson, G., Bakó, L., and Villarejo, A.
(2012) Use of the Foot-and-Mouth Disease Virus 2A Peptide Co-Expression System to
Study Intracellular Protein Trafficking in Arabidopsis, PLoS ONE 7, e51973.

246.

Wang, Y., Wang, F., Wang, R., Zhao, P., and Xia, Q. (2015) 2A self-cleaving peptidebased multi-gene expression system in the silkworm Bombyx mori, Scientific Reports 5,
16273.

247.

Rasala, B. A., Lee, P. A., Shen, Z., Briggs, S. P., Mendez, M., and Mayfield, S. P. (2012)
Robust Expression and Secretion of Xylanase1 in Chlamydomonas reinhardtii by Fusion
to a Selection Gene and Processing with the FMDV 2A Peptide, PLoS ONE 7, e43349.

248.

Ma, X., Yu, J., Zhu, B., Pan, K., Pan, J., and Yang, G. (2011) Cloning and
characterization of a delta-6 desaturase encoding gene from Nannochloropsis oculata,
Chinese Journal of Oceanology and Limnology 29, 290-296.

249.

Valentine, R. C., and Valentine, D. L. (2004) Omega-3 fatty acids in cellular membranes:
a unified concept, Progress in Lipid Research 43, 383-402.

199

250.

Moire, L. (2004) Impact of Unusual Fatty Acid Synthesis on Futile Cycling through Oxidation and on Gene Expression in Transgenic Plants, Plant Physiology 134, 432-442.

251.

Manandhar-Shrestha, K., and Hildebrand, M. (2015) Characterization and manipulation
of a DGAT2 from the diatom Thalassiosira pseudonana: Improved TAG accumulation
without detriment to growth, and implications for chloroplast TAG accumulation, Algal
Research 12, 239-248.

252.

Xu, J., Kazachkov, M., Jia, Y., Zheng, Z., and Zou, J. (2013) Expression of a type 2
diacylglycerol acyltransferase from Thalassiosira pseudonana in yeast leads to
incorporation of docosahexaenoic acid β-oxidation intermediates into triacylglycerol,
FEBS Journal 280, 6162-6172.

253.

Kajiwara, S., Shirai, A., Fujii, T., Toguri, T., Nakamura, K., and Ohtaguchi, K. (1996)
Polyunsaturated fatty acid biosynthesis in Saccharomyces cerevisiae: expression of
ethanol tolerance and the FAD2 gene from Arabidopsis thaliana, Applied and
Environmental Microbiology 62, 4309-4313.

254.

Rodolfi, L., Chini Zittelli, G., Bassi, N., Padovani, G., Biondi, N., Bonini, G., and
Tredici, M. R. (2009) Microalgae for oil: strain selection, induction of lipid synthesis and
outdoor mass cultivation in a low-cost photobioreactor, Biotechnology and
bioengineering 102, 100-112.

255.

Kumar, S. (2015) GM Algae for Biofuel Production: Biosafety and Risk Assessment, Vol.
9.

256.

Lu, J., Tong, Y., Pan, J., Yang, Y., Liu, Q., Tan, X., Zhao, S., Qin, L., and Chen, X.
(2016) A redesigned CRISPR/Cas9 system for marker-free genome editing in
Plasmodium falciparum, Parasites & Vectors 9.

257.

Weninger, A., Hatzl, A.-M., Schmid, C., Vogl, T., and Glieder, A. (2016) Combinatorial
optimization of CRISPR/Cas9 expression enables precision genome engineering in the
methylotrophic yeast Pichia pastoris, Journal of Biotechnology 235, 139-149.

258.

Weyman, P. D., Beeri, K., Lefebvre, S. C., Rivera, J., McCarthy, J. K., Heuberger, A. L.,
Peers, G., Allen, A. E., and Dupont, C. L. (2015) Inactivation of Phaeodactylum
tricornutum urease gene using transcription activator-like effector nuclease-based
targeted mutagenesis, Plant biotechnology journal 13, 460-470.

259.

Jiang, W., Brueggeman, A. J., Horken, K. M., Plucinak, T. M., and Weeks, D. P. (2014)
Successful Transient Expression of Cas9 and Single Guide RNA Genes in
Chlamydomonas reinhardtii, Eukaryotic Cell 13, 1465-1469.

260.

Shin, S.-E., Lim, J.-M., Koh, H. G., Kim, E. K., Kang, N. K., Jeon, S., Kwon, S., Shin,
W.-S., Lee, B., Hwangbo, K., Kim, J., Ye, S. H., Yun, J.-Y., Seo, H., Oh, H.-M., Kim,
K.-J., Kim, J.-S., Jeong, W.-J., Chang, Y. K., and Jeong, B.-r. (2016) CRISPR/Cas9induced knockout and knock-in mutations in Chlamydomonas reinhardtii, Scientific
Reports 6, 27810.
200

261.

Hopes, A., Nekrasov, V., Kamoun, S., and Mock, T. (2016) Editing of the urease gene by
CRISPR-Cas in the diatom Thalassiosira pseudonana, Plant Methods 12.

262.

Zhang, W.-W., and Matlashewski, G. (2015) CRISPR-Cas9-Mediated Genome Editing in
Leishmania donovani, mBio 6, e00861-00815.

263.

Moon, D. A., and Goff, L. J. (1997) Molecular characterization of two large DNA
plasmids in the red alga Porphyra pulchra, Curr. Genet. 32, 132-138.

264.

Fernández, E., Schnell, R., Ranum, L. P., Hussey, S. C., Silflow, C. D., and Lefebvre, P.
A. (1989) Isolation and characterization of the nitrate reductase structural gene of
Chlamydomonas reinhardtii, Proceedings of the National Academy of Sciences of the
United States of America 86, 6449-6453.

265.

Gibson, D. G., Young, L., Chuang, R. Y., Venter, J. C., Hutchison, C. A., 3rd, and Smith,
H. O. (2009) Enzymatic assembly of DNA molecules up to several hundred kilobases,
Nature methods 6, 343-345.

266.

Waldrip, Z. J., Byrum, S. D., Storey, A. J., Gao, J., Byrd, A. K., Mackintosh, S. G.,
Wahls, W. P., Taverna, S. D., Raney, K. D., and Tackett, A. J. (2014) A CRISPR-based
approach for proteomic analysis of a single genomic locus, Epigenetics 9, 1207-1211.

201