FUNCTIONAL DIVERSIFICATION OF THE UNFOLDED PROTEIN RESPONSE IN
ARABIDOPSIS
By
Evan Russell Angelos
A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Biochemistry and Molecular Biology- Doctor of Philosophy
2021
ABSTRACT
FUNCTIONAL DIVERSIFICATION OF THE UNFOLDED PROTEIN RESPONSE IN
ARABIDOPSIS
By
Evan Russell Angelos
Much like a factory, the endoplasmic reticulum (ER) assembles simple cellular building
blocks into complex molecular machines known as proteins. In order to protect the delicate
protein folding process and ensure the proper cellular delivery of protein products under
environmental stresses, eukaryotes have evolved a set of signaling mechanisms known as the
unfolded protein response (UPR) to increase the folding capacity and resiliency of the ER. While
the UPR is a conserved aspect of nearly all eukaryotic cells, this process is particularly important
in plants, because their sessile nature commands adaptation for survival rather than escape from
stress. As such, plants make special use of the UPR, and evidence indicates that the master
regulators and downstream effectors of the UPR have distinct roles in mediating cellular
processes that affect plant growth, development and stress responses. In my research I sought to
contribute to the general knowledge of how the plant UPR is integrated with, and connected to
other critical signal transduction mechanisms in stress and development. My work has helped to
connect plant UPR activities with reactive oxygen species (ROS) signaling under canonical ER
stress situations, by demonstrating that this ROS is required for ER stress survival. In
collaboration with the National Aeronautics and Space Administration (NASA) I was able to
explore the relevance of the UPR to spaceflight associated stress, and uncovered novel
connections between the UPR and plant-specific abiotic stress responses. Finally, I establish a
role for the UPR in the regulation of widely conserved metabolic signaling pathways, which are
critical to maintain plant organ growth.
To Sandy and Tim, to Lauren, and to Ben.
None of this would have been possible without your unwavering love and support.
iii
ACKNOWLEDGEMENTS
I will be forever grateful to Dr. Binney Girdler, who recognized my potential, and put up
with me while I explored the scientific process for the first time. Those early experiments may
have made a mess, and stunk up the biology labs, but they set me on the path I walk today. I am
also grateful to Dr. Jonathan Walton, who gave me a chance as an undergraduate, and then
offered support and mentorship long afterward. Without Dr. Walton and Binney’s advice in
those formative years, I do not know where I would be.
I would like to thank Dr. Federica Brandizzi, my Ph.D supervisor. Over the years she has
guided me and help me turn raw enthusiasm for science and an unending curiosity into a
productive research career. She has supported me through the good times and the bad, in any
way that she could, and I will always be grateful for that. To the past and current members of the
Brandizzi lab, I would not have gotten through this time without you. In particular, Melissa,
Starla, Anne, Gianni, Luciana, Sang-Jin, Cristina, you all offered friendship, support, and took
the time to answer my thousands of questions with patience and respect. To Noelia, you kept me
going when things were at their worst, I can’t thank you enough.
I would also like to thank the members of my Ph.D Committee and Comprehensive Exam
committee: Dr. Sharkey, Dr. Hamberger, Dr. Hu, Dr. Hsu, and Dr. Kuhn. Their feedback,
guidance, discussions, and validation have been invaluable to my progress, which would not
have been possible without their support. In addition, I would like to thank Dr. David Arnosti,
the BMB graduate programs director, who has been a sympathetic and understanding advisor
throughout my time here and provided many opportunities for growth and development as a
researcher and as a member of the BMB community. I would also like to thank Dr. Robert Last,
iv
and the other members of the Plant Biotechnology for Health and Sustainability program who
provided financial support and invaluable leadership experience during my time at MSU. I have
been walking among giants here at the PRL for the last ten years, I couldn’t have imagined a
better place to launch my career.
v
TABLE OF CONTENTS
LIST OF FIGURES ....................................................................................................................... ix
KEY TO ABBREVIATIONS ........................................................................................................ xi
CHAPTER I INTRODUCTION ......................................................................................................1
THE UNFOLDED PROTEIN RESPONSE MONITORS ENDOPLASMIC RETICULUM
HOMEOSTASIS..................................................................................................................2
Entrance to the Secretory Pathway..................................................................................2
A Varied Toolbox: The Primary Regulators of the Unfolded Protein Response .............4
FUNCTIONAL DIVERSIFICATION OF THE UPR IN ADAPTATION TO
ENVIRONMENTAL STRESS .........................................................................................10
From Humans to Arabidopsis: A Myriad of Cell Stresses Elicit UPR Activation .........10
Functional Diversification of IRE1 Activation and Effects ...........................................16
Functional Diversification of UPR Transcription Factors ............................................21
FUNCTIONAL DIVERSIFICATION OF THE UPR IN DEVELOPMENT ...................26
The UPR is Essential to Multicellular Metazoan Development ....................................26
Physiological Roles of the Plant UPR in Development .................................................29
RATIONAL FOR STUDY ................................................................................................35
REFERENCES ..............................................................................................................................37
CHAPTER II NADPH OXIDASE ACTIVITY IS REQUIRED FOR ER STRESS SURVIVAL
IN PLANTS ...................................................................................................................................52
ABSTRACT .......................................................................................................................53
INTRODUCTION .............................................................................................................53
MATERIALS AND METHODS .......................................................................................58
Plant Materials and Growth Conditions .......................................................................58
Superoxide Histochemical Staining and Quantification ................................................58
Extraction and Quantification of H2O2 in Seedling Tissues Using Amplex
Ultra Red ....................................................................................................................59
RNA Extraction and Quantitative RT-PCR Analyses ....................................................62
Recovery from ER Stress and Chronic ER Stress Phenotypic Analyses ........................63
Electrolyte Leakage Measurements ...............................................................................64
RESULTS ..........................................................................................................................65
ER Stress Induces Accumulation of Superoxide by NADPH Oxidases..........................65
ER Stress Induces Accumulation of Hydrogen Peroxide Dependent upon RBOHD
and RBOHF Activity and Intact UPR Signaling ........................................................67
UPR Regulators Influence RBOHD and RBOHF Expression During Adaptive UPR ..70
RBOHD and RBOHF are Necessary for Recovery from Short-Term and Chronic
ER Stress ....................................................................................................................74
RBOHD and RBOHF Contribute to Preventing ER Stress Induced Cell Death ...........75
DISCUSSION ....................................................................................................................80
NADPH Oxidases Contribute to ROS Production in Conditions of ER Stress .............80
vi
Unlike in Metazoans, NADPH Oxidase-Produced ROS are Beneficial to
Overcome ER Stress in Plants ...................................................................................82
Homeostasis of NADPH oxidase activity is required to maintain an effective UPR .....83
In ER Stress Conditions, the Production of ROS is Antagonized by IRE1 and the
bZIP60/bZIP28 Transcription Factors ......................................................................84
ACKNOWLEDGEMENTS ...............................................................................................87
REFERENCES ..............................................................................................................................88
CHAPTER III RELEVANCE OF THE UNFOLDED PROTEIN RESPONSE TO
SPACEFLIGHT INDUCED TRANSCRIPTIONAL REPROGRAMMING IN
ARABIDOPSIS .............................................................................................................................95
ABSTRACT .......................................................................................................................96
INTRODUCTION .............................................................................................................97
MATERIALS AND METHODS .....................................................................................100
Launch Hardware and Experimental Timeline............................................................100
Germplasm and Culture Conditions ............................................................................101
Sample Processing and Experimental Material Assessment .......................................102
Library Preparation, Sequencing, and Bioinformatics Analysis .................................102
RESULTS ........................................................................................................................104
Spaceflight Alters the Growth of Seedlings Independent of an Intact UPR Signaling 104
Spaceflight Results in an Increase of Total RNA .........................................................104
Global Transcriptomic Analyses Indicate that Gene Expression Reprogramming
in Response to Spaceflight Depends Partially on Intact UPR Signaling ................108
Biological Pathways Connected to DEGs Between Flight and Ground .....................110
The UPR Regulators Exert a Minor but Significant Role on Gene Expression
in Spaceflight ...........................................................................................................113
DISCUSSION ..................................................................................................................118
DATA AVAILABILITY .................................................................................................125
ACKNOWLEDGEMENTS .............................................................................................125
AUTHOR CONTRIBUTIONS ........................................................................................126
APPENDIX ..................................................................................................................................127
REFERENCES ............................................................................................................................130
CHAPTER IV THE UPR REGULATOR IRE1 PROMOTES BALANCED ORGAN
DEVELOPMENT BY RESTRICTING TOR DEPENDANT CONTROL OF CELLULAR
DIFFERENTIATION IN ARABIDOPSIS ..................................................................................136
ABSTRACT .....................................................................................................................137
INTRODUCTION ...........................................................................................................138
MATERIALS AND METHODS .....................................................................................142
Plant Material and High-Quality Seed Production .....................................................142
Plant Phenotyping ........................................................................................................143
mPS-PI Staining and Meristem Cellular Organization Analysis ................................144
TOR Activity Assays .....................................................................................................145
EdU Pulse-Chase Experiments ....................................................................................147
Data Reporting and Statistical Analysis ......................................................................148
RESULTS ........................................................................................................................150
vii
IRE1 Promotes Root Growth in an Age-Dependent Manner.......................................150
IRE1 is Required for Proper Cell Elongation in the Root Meristem ...........................154
The Emergence of the ire1a ire1b Root Growth Phenotype Depends on High
Rates of Root Growth ...............................................................................................157
TOR Inhibition Rescues the ire1a ire1b Primary Root Growth Phenotypes ...............161
TOR is Hyperactive at the Growing Primary Root Tips of the ire1a ire1b Mutant ....165
TOR Inhibition Rescues the ire1a ire1b Cellular Elongation Phenotypes
at the Root Meristem ................................................................................................167
TOR Hyper-activity in the ire1a ire1b Mutant Promotes Differentiation
Rather than Cellular Proliferation ..........................................................................170
DISCUSSION ..................................................................................................................175
IRE1 can Regulate TOR Activity in a Multicellular Eukaryote ...................................176
IRE1 is Necessary to Control TOR Activity at Tissue- and Development-
Specific Levels ..........................................................................................................176
IRE1-Dependent Repression of TOR is Independent from the Unconventional
Splicing of bZIP60 ..................................................................................................178
TOR Activity Regulates Cellular Differentiation and Cell Elongation in Actively
Growing Arabidopsis Root Tips ..............................................................................179
ACKNOWLEDGEMENTS .............................................................................................182
APPENDIX ..................................................................................................................................183
REFERENCES ............................................................................................................................193
CHAPTER V FUTURE PERSPECTIVES ..................................................................................200
Chapter 2: Integrating ER Stress Response with NADPH Oxidase Signaling ................202
Chapter 3: UPR Transcriptome in Spaceflight Experiment Reveals Possible
Novel Roles for UPR TFs .............................................................................................204
Chapter 4: Old Friends with a New Relationship, IRE1 and TOR..................................206
REFERENCES ............................................................................................................................208
viii
LIST OF FIGURES
Figure 1.1. The IRE1 and ATF6 dependent arms of the UPR are conserved in Arabidopsis .........8
Figure 1.2. Simplified models comparing RNase activation mechanism of mammalian and S.
cerevisiae IRE1s.............................................................................................................................18
Figure 1.3. The UPR TFs interact with a variety of conserved and plant specific partners to
regulate transcription. ....................................................................................................................24
Figure 2.1. NADPH oxidase-dependent O2- is generated during ER stress partially through
RBOHD and RBOHF. ..................................................................................................................66
Figure 2.2. ER Stress-induced H2O2 is controlled by RBOHD and RBOHF as well as intact UPR
signaling. ........................................................................................................................................69
Figure 2.3. Intact UPR signaling is required to maintain homeostasis of RBOH transcript levels
and ROS signaling, while RBOH activity affects UPR homeostasis. ...........................................72
Figure 2.4. RBOHD and RBOHF are required in the recovery from temporary ER stress...........76
Figure 2.5. RBOHD and RBOHF are required for adaptation to chronic ER stress. ....................77
Figure 2.6. RBOHD and RBOHF act to prevent ER stress-induced cell death. ............................79
Figure 3.1. Growth of etiolated hypocotyls was altered by spaceflight.......................................105
Figure 3.2. RNA quality assessment of flight and ground control samples. ...............................107
Figure 3.3. Overall quality assessment of RNA-sequencing dataset. ..........................................109
Figure 3.4. Summary of differential gene expression analysis. ...................................................110
Figure 3.5. Representative biological processes gene ontologies over- or under-represented by
upregulated or downregulated DEGs in the WT background. .....................................................112
Figure 3.6. K-means clustering analysis of all 3465 DEGs in at least 1 background. .................114
Figure 3.7. Simplified model of regulatory framework controlling stress responsive DEGs......122
Figure 3.S1. Representative Bioanalyzer traces of ground and flight samples ...........................128
Figure 3.S2. Number of total mapped reads and mapping rate per sample .................................128
ix
Figure 3.S3. Number of DEGs which had WT FPKM values which were significantly different
from WT in at least one mutant genotype ....................................................................................129
Figure 3.S4. Percentage of DEGs with statistically different ground FPKM values in the
indicated UPR mutant genotype compared to the WT ground FPKM values .............................129
Figure 4.1. The ire1a ire1b double mutant shows age dependent primary root growth defects .151
Figure 4.2. Meristem organization defects in ire1a ire1b are first manifested in cell elongation in
the elongation zone ......................................................................................................................155
Figure 4.3. The emergence of the ire1a ire1b root phenotype depends on a high rate of root
growth ..........................................................................................................................................159
Figure 4.4. TOR inhibition rescues the ire1a ire1b root growth phenotype................................163
Figure 4.5. TOR is hyperactive in the ire1a ire1b mutant root tips but not in the mature root. ..166
Figure 4.6. Meristem organization defects in ire1a ire1b are rescued by TOR inhibition ..........168
Figure 4.7. TOR hyperactivity in the ire1a ire1b mutant promotes differentiation rather than
cellular proliferation.....................................................................................................................172
Figure 4.S1. Rate of shoot fresh weight accumulation and primary root growth for data displayed
in Figure 4.1 .................................................................................................................................184
Figure 4.S2. At D5 there are no significant defects in the ire1a ire1b meristem organization ...185
Figure 4.S3. Average root tip cellular organization metrics displayed over time in WT and ire1a
ire1b ............................................................................................................................................186
Figure 4.S4. TOR inhibitor AZD-8055 concentration response analysis ....................................187
Figure 4.S5. TOR inhibitor TORIN2 rescues the ire1a ire1b root growth phenotypes ..............188
Figure 4.S6. Other chemical inhibitors of root growth do not rescue the ire1a ire1b root length
phenotype .....................................................................................................................................189
Figure 4.S7. Auxin inhibition of root growth and TOR inhibition of root growth are additive
effects in WT and ire1a ire1b plants ...........................................................................................190
Figure 4.S8. Full blot images from Figure 4.5 and images of blots after Ponceau’s stain to
demonstrate equal protein loading ...............................................................................................191
Figure 4.S9. Simplified model showing that TOR activity must be carefully balanced to maintain
optimal cell elongation .................................................................................................................192
Figure 5.1. Summary Graphic of Dissertation Investigations......................................................201
x
KEY TO ABBREVIATIONS
1
O2‐ - singlet oxygen
ADP- adenosine diphosphate
AGB1- Arabidopsis Gβ subunit 1
ANOVA- analysis of variance
ATF6- Activating Transcription Factor 6
AUR- Amplex Ultra Red
BAK1- BRI1-associated receptor kinase 1
BAX- Bcl-2 associated X
BI1- BAX inhibitor 1
BiPs- luminal binding proteins
BR- brassinosteroid
BRI1- brassinosteroid insensitive 1 receptor
BRIC- Biological Research In a Canister
BSA- bovine serum albumin
bZIP- basic leucine zipper
ch1- chlorophyll A oxygenase mutant
CL- continuous light
clv- CLAVATA mutant
COPII- coat protein complex II
CoV- coefficients of variation
CPR5- constitutive expressor of pathogenesis-related genes-5
ddH2O- double distilled water
DEGs- differentially expressed genes
DMSO-dimethyl sulfoxide
DPI-diphenyleneiodonium chloride
EB- extraction buffer
EdU- ethynyl‐2′‐deoxyuridine
xi
EF-Tu- elongation factor Tu receptor
eIF- eukaryotic translation initiation factors
ER- endoplasmic reticulum
ERAD- ER-associated protein degradation
ERdj3- ER resident J domain 3
ERO1- ER oxidoreductin 1
ERQC endoplasmic reticulum quality control
ERSE- ER Stress Response Elements
EZ- elongation zone
FPKM- fragments per kilobase exon model per million mapped reads
FRET- Förster resonance energy transfer
GLS- Golgi localization sequence
GO- Gene Ontology
H2O2- hydrogen peroxide
HRP- horseradish peroxidase
HSP- heat shock protein
HY5- Elongated Hypocotyl 5
IP3R- inositol triphosphate receptor
IRE1- Inositol Requiring Enzyme 1
ISS- International Space Station
ISSES- ISS Environmental Simulator
JA- jasmonic acid
KSC- Kennedy Space Center
LS- Linsmaier and Skoog
LSD1- Lesion Stimulating Disease 1
MEcPP- 2-C-methyl-D-erythritol-2,4-cyclopyrophosphate
MEP- methylerythritol phosphate
mPS-PI- modified pseudo-Schiff propidium iodide
MS- Murashige and Skoog
mTORC1- mammalian TOR complex 1
xii
MTTFs- membrane tethered bZIP transcription factors
MZ- meristematic zone
NAA-1-naphthaleneacetic acid
NBT- Nitro Tetrazolium Blue
NF-Y- Nuclear Y Factor
NOX- NADPH Oxidases
NPR1- Nonexpressor of Pathogenesis Related 1
NTCA- neutralized trichloroacetic acid
O2- - superoxide
OST- oligosaccharyltransferase
PA- periodic acid
PAMP- pathogen-associated molecular pattern
PBS- phosphate buffered saline
PCA- principal component analysis
PCD- programmed cell death
PDFU- Petri Dish Fixation Unit
PDI- protein disulfide isomerase
PERK- Protein kinase R-like Endoplasmic Reticulum Kinase
PM- plasma membrane
R/FR- red/ far red light
RBOH- respiratory burst oxidase homolog
RHI- root hair initial
RIDD- Regulated IRE1 Dependent Decay
RIN- RNA Integrity Number
RIP- regulated intramembrane proteolysis
RNAi- RNA interference
RNase- endoribonuclease
RNA-seq- RNA-sequencing
ROS- reactive oxygen species
rRNA- ribosomal RNA
xiii
RT-PCR- reverse transcriptase PCR
S1P- Site-1 Proteases
S2P- Site-2 Proteases
S6K- Serine Kinase 6
SA- salicylic acid
SAR- systemic acquired resistance
SAS- shade avoidance syndrome
SD- standard deviation
SE- standard error
SERCA- sarcoplasmic/endoplasmic reticulum calcium ATPase
SERK4- somatic embryo receptor kinase 4
SFW- shoot fresh weight
shd- heat shock protein 90.7 mutant
SOD- superoxide dismutase
STT3a- staurosporin and temperature sensitive 3
TBST- tris buffered saline plus Tween20
TCA- trichloroacetic acid
TF- transcription factor
Tm- tunicamycin
tms1- Thermosensitive Male Sterile 1
TOR- Target of Rapamycin kinase
TRAF2- TNFR-associated factor 2
TZ- transition zone
UGGT- UDP-glucose glycoprotein-glucosyltransferase
UPR- Unfolded Protein Response
UPRE- Unfolded Protein Response Element
wANOVA- weighted least squares analysis of variance
WT- wild type
XBP1- X-box binding protein 1
xiv
CHAPTER I
INTRODUCTION
Parts of the work presented in this chapter has been published in The Plant Journal and Trends
in Biochemical Sciences:
Angelos E., Ruberti C., Kim S.J., and Brandizzi F. (2017) Maintaining the factory: the roles
of the unfolded protein response in cellular homeostasis in plants. Plant Journal. 90(4):671-682.
Pastor-Cantizano N., Ko D.K., Angelos E., Pu Y., and Brandizzi F. (2020) Functional
Diversification of ER Stress Responses in Arabidopsis. Trends in Biochemical Sciences.
45(2):123-136.
1
THE UNFOLDED PROTEIN RESPONSE MONITORS ENDOPLASMIC RETICULUM
HOMEOSTASIS
Entrance to the Secretory Pathway
If the plant cell was reimagined as a city, it would be easy to see how the endoplasmic
reticulum (ER) could be described as the town’s central factory. At the ER, shipments of raw
materials in the form of amino acids and carbohydrates are reshaped and assembled into fully-
functional molecular machines in the form of proteins. Properly folded proteins are then shipped
out and utilized for a variety of different purposes in different places throughout or outside the
cell. In order to prevent the production of faulty goods, the ER has specific machinery,
collectively called ER quality control (ERQC), to survey the protein folding status, facilitate
folding and ensure quality of the produced protein (Ron and Walter 2007). The production of
most secretory proteins begins with the co-translational introduction of the protein into the ER.
In this process, specific peptide sequences target nascent polypeptide chains to the ER and are
translocated across the membrane as they are synthesized via the Sec translocon (Denecke et al.
1993, Akopian et al. 2013, Schweiger and Schwenkert 2013).
Then, a dedicated battery of ER-resident proteins work to prevent misfolding of nascent
polypeptide chains and facilitate the proper folding of the client proteins via post-translational
modification (Dobson 2003, Gupta and Tuteja 2011). As the polypeptide enters the ER lumen,
molecular chaperones such as the luminal binding proteins (BiPs), bind to the chain of the nascent
polypeptides and prevent premature folding (Foresti et al. 2003, Carvalho et al. 2014). The
oligosaccharyltransferase (OST) complex (Lerouxel et al. 2005) recognizes specific amino acid
sequences and transfers N-linked glycans to the peptides. In some cases, this post translational
modification adds to the intrinsic stability or solubility of a protein, and importantly, it functions
2
as a recognition beacon for major ER luminal foldase complexes (Sinclair and Elliott 2005).
Nascent polypeptides undergo iterative folding cycles where they are passed between the
calnexin/calreticulin complex, and UDP-glucose glycoprotein-glucosyltransferase (UGGT),
which monitor protein folding and retains unfolded proteins in the ER (Totani et al. 2009) as a part
of the ERQC. Other proteins participate in folding cycles under the purview of these central ER
foldase complexes, such as thioredoxins (i.e. protein disulfide isomerases; PDIs), which catalyze
the reduction and reformation of disulfide bonds (Bottomley et al. 2001, Wilkinson and Gilbert
2004). Properly folded proteins are then transported to the Golgi apparatus, while the unfolded or
irremediably misfolded proteins are picked up by proteins like OS9 of the ER-associated protein
degradation (ERAD) system, dislocated out of the ER, ubiquitinated, and finally degraded by the
26S proteasome (Hüttner et al. 2012).
Due to intrinsic nature of the ER as the entry point to secretory pathway (Vitale and
Denecke 1999), a site of phospholipid synthesis (Ohlrogge and Browse 1995), a hub for critical
stress and growth signaling molecules (Ron and Walter 2007, Shore et al. 2011, Light et al. 2016),
a calcium storage site (Kaufman and Malhotra 2014), and an assembly plant for a third of a cell’s
total proteome (Wallin and Heijne 1998), interruptions in ER function can have vast consequences
in cellular health. For example, the ERQC mediates the proper folding of critical client plasma
membrane receptor proteins in plants, including the Arabidopsis elongation factor Tu (EF-Tu)
receptor which mediates pathogen associated molecular pattern-based immunity (Li et al. 2009)
and brassinosteroid insensitive 1 (BRI1) receptor (Li and Chory 1997). Beyond enabling proper
function of cellular signaling pathways with receptors at the plasma membrane (like EF-Tu and
BRI1), the specificity of N-linked glycosylation-bearing proteins has recently been shown to play
important roles in regulating cell death. The Arabidopsis BAK1 (BRI1-associated receptor kinase
3
1) and SERK4 (somatic embryo receptor kinase 4) both interact with immune receptors and BRI1
and negatively regulate hypersensitive response-like programmed cell death (PCD) through yet-
unknown mechanisms (Li et al. 2002, Nam and Li 2002, Roux et al. 2011, Gou et al. 2012).
Intriguingly, loss of STT3a (staurosporin and temperature sensitive 3), one of the two catalytic
subunits of the OST complex involved in N-glycosylation of ER proteins, is linked to the cell death
phenotype observed in BAK1/SERK4 silenced plants (de Oliveira et al. 2016). Together these
examples underscore the importance of maintaining the ER as a fully-functional protein folding
factory.
A Varied Toolbox: The Primary Regulators of the Unfolded Protein Response
In eukaryotic organisms, exogenous environmental stresses and increased demands for
protein folding can perturb the delicate folding machinery inside the ER leading, to the
accumulation of unfolded or misfolded proteins (Hetz and Papa 2018, Mitra and Ryoo 2019). This
accumulation leads to a potentially lethal condition known as ER stress (Dobson 2003, Hartl and
Hayer-Hartl 2009, Buchberger et al. 2010). Indeed, under prolonged or severe levels of stress, the
accumulation and aggregation of unfolded proteins can become cytotoxic and lead to death of
eukaryotic cells (Ron and Walter 2007). The unfolded protein response (UPR) is a set of signaling
mechanisms which are meant to prevent accumulation of misfolded proteins in the ER (Walter and
Ron 2011). Specialized ER-localized membrane proteins are able to detect the buildup of unfolded
proteins and activate intracellular signaling cascades in response (Ron and Walter 2007). The
activated UPR sensors upregulate the synthesis of ER protein chaperones, expand the size of the
ER by increasing the rate of membrane synthesis, while also limiting the overall rate of protein
translation in the cell (Ron and Walter 2007, Ruberti and Brandizzi 2014, Han and Kaufman 2017).
4
In metazoans there are three “arms” to the UPR, each controlled by one of the three primary ER-
localized stress sensors. These sensors are the Inositol Requiring Enzyme 1 (IRE1), Activating
Transcription Factor 6 (ATF6) and Protein kinase R-like Endoplasmic Reticulum Kinase (PERK)
(Wang et al. 1998, Harding et al. 1999, Shen et al. 2002). In unicellular organisms such as yeast
and algae (i.e. S. cerevisiae and Chlamydomonas reinhardtii) only IRE1 homologs have been
identified (Nikawa and Yamashita 1992, Yamaoka et al. 2018). In multicellular plants, homologs
of the of the IRE1 and ATF6 sensors have been identified (Ruberti and Brandizzi 2014). To date,
no direct homolog or functional analog of the metazoan PERK enzyme has been identified in either
yeast or plants (Ruberti and Brandizzi 2014). However, accumulating evidence suggests that there
are remarkable similarities between the core complement of UPR sensors in mammals and
Arabidopsis.
In mammals, two IRE1 paralogs are encoded in the genome, identified as IREα and IRE1β.
Both of these sensors contain an ER luminal domain (which mediates protein-protein interactions)
connected by a type I transmembrane domain to cytosolic serine/threonine kinase and
endoribonuclease (RNase) subdomains (Cox et al. 1993, Morl et al. 1993). Of these two isoforms,
IREα is the predominate protein and is widely expressed in most tissue types, whereas IRE1β
expression is limited primarily to the gut epithelium and mucosal airways (Riaz et al. 2020). Of
the IRE1 paralogs in the Arabidopsis genome, two of them (IRE1a and IRE1b) closely resemble
the IRE1 found in metazoans and yeast (Figure 1.1A; Koizumi et al. 2001). IRE1b is the
predominate form in Arabidopsis and is expressed in nearly all tissue types (Pu et al. 2019). IRE1a
is primarily expressed in root tissues, but is also expressed in seed and embryos (Koizumi et al.
2001, Noh et al. 2002, Pu et al. 2019). Arabidopsis and other Brassicaceae also have a third IRE1
isoform named IRE1c which lacks an ER luminal domain and has considerable sequence
5
divergence compared to other IRE1s (Mishiba et al. 2019, Pu et al. 2019). However, the relevance
of the IRE1c to ER stress responses is yet unknown (Mishiba et al. 2019, Pu et al. 2019).
The accumulation of unfolded and irremediably misfolded proteins leads to the activation
of IRE1 (Riaz et al. 2020). Although the activation mechanism of IRE1 has yet to be established
in plants, there is a large body of work describing these mechanisms in both yeast and metazoan
models (Korennykh et al. 2009, Ali et al. 2011). Under non-stressed conditions BiP protein
chaperones bind the IRE1 luminal domain, which forces the IRE1 proteins to retain a monomeric
organization (Figure 1.1A; Zhou et al. 2006). However, during ER stress conditions BiP
chaperones preferentially bind to increased numbers of unfolded proteins, thereby freeing the ER
luminal domains of IRE1 (Pincus et al. 2010). These newly freed luminal domains lead to homo-
oligomerization of IRE1, and subsequently to trans-autophosphorylation of the IRE1 kinase
subdomains (Shamu and Walter 1996, Welihinda and Kaufman 1996, Korennykh et al. 2009, Ali
et al. 2011). Sensor residues near the IRE1 transmembrane domain can also detect aberrant ER
membrane composition, leading to IRE1 oligomerization and autophosphorylation even in the
absence of proteotoxic stress (Volmer et al. 2013, Halbleib et al. 2017). In both methods of IRE1
activation, autophosphorylation of the kinase subdomain causes secondary structural changes
which greatly increases the activity of the RNase domain (Zhou et al. 2006). Previous research has
shown that the Arabidopsis IRE1a and IRE1b genes can dimerize and auto-phosphorylate
(Koizumi et al. 2001, Noh et al. 2002, Zhang et al. 2015) suggesting similar overall functions the
in Arabidopsis, however more study is needed to uncover the structural mechanisms by which
IRE1 is activated in plants.
The overall effects of metazoan and plant IRE1s on downstream UPR gene regulation is
also relatively similar. In each kingdom the activated IRE1 RNase subdomain catalyzes the
6
unconventional splicing of a mRNA encoding a conserved basic leucine zipper (bZIP) type
transcription factor (TF; Figure 1.1A (Pathway 1) ; Ruberti et al. 2015). This splicing of the
mammalian XBP1 and the plant bZIP60 leads to a translational frameshift of the mRNA
eliminating an ER transmembrane anchor domain. (Cox and Walter 1996, Mori et al. 1996,
Yoshida et al. 2001, Deng et al. 2011, Nagashima et al. 2011). This process is initiated when the
IRE1 RNase domains binds to and cleaves two consensus hairpin motifs in these mRNAs (Ron
and Walter 2011, Ruberti et al. 2015). Then a specific tRNA ligase ligates the 5` and 3` ends of
the transcript without the excised section (Sawaya et al. 2003, Steiger et al. 2005, Jurkin et al.
2014, Nagashima et al. 2016). The spliced XBP1 and bZIP60 transcripts are then translated without
their ER anchors, allowing for translocation of the active TF to the nucleus where they modulate
downstream target genes (Zhang et al. 2016). Intriguingly, the RNase activity of IRE1 is not
limited to unconventional splicing of these transcription factors. In metazoans, plants, and some
yeasts Regulated IRE1 Dependent Decay (RIDD) affects the abundance of many cytosolic and ER
associated mRNAs other than XBP1/bZIP60 in the response to ER stress (Figure 1.1A; Pathway
2; Hollien et al. 2009, Tam et al. 2014). IRE1 is also known to perform a number of RNase-
independent functions (Riaz et al. 2020). In metazoans, the active IRE1 is known to act as a protein
scaffold, which enables interactions between the UPR and other cellular signaling pathways
(Urano et al. 2000, Adams et al. 2019). For example, binding of the active IRE1 by TNFR-
associated factor 2 (TRAF2) leads to activation of a MAP kinase signal cascade known as the JNK
pathway, which regulates cell death in mammalian cells under ER stress conditions (Figure 1.1A;
Pathway 3; Urano et al. 2000). Whether or not a pathway analogous to the IRE1-TRAF2-JNK
signaling axis is conserved in plants remains an exciting topic for future study.
7
Figure 1.1. The IRE1 and ATF6 dependent arms of the UPR are conserved in Arabidopsis.
A) Monomeric IRE1a/b are kept inactive by binding of BiP proteins to the IRE1 luminal domain.
Buildup of unfolded proteins allows dimerization and trans-autophosphorylation of IRE1
monomers leading to their activation. B) Release of BiP proteins allows for trafficking of the
Arabidopsis ATF6 homolog, bZIP28, to the Golgi. Subsequent regulated intramembrane
proteolysis (RIP) releases the active transcription factor for nuclear translocation. This figure was
previously published in Pastor-Cantizano et al. (2020).
8
There are also strong similarities between the mammalian and plant ATF6-dependent arms of
the UPR. In mammals there are two ATF6 paralogs (ATF6a and ATF6b; Figure 1.1B; Haze et al.
1999). Both of these sensors consist of an ER luminal domain which mediates protein-protein
interactions and ER retention, a type II transmembrane domain, and a cytosolic bZIP TF domain
(Haze et al. 1999). In Arabidopsis two ATF6 homologs exist, bZIP17 and bZIP28 (Liu et al. 2007,
Liu et al. 2007, Kim et al. 2018). Under normal conditions BiP proteins bind to and cover the
Golgi localization signals (GLSs) found in the ER luminal domain of ATF6a and ATF6b trapping
them in an inactive state in the ER (Ye et al. 2000). Under ER stress conditions, the BiP chaperones
dissociate from ATF6, and translocate to the Golgi where they undergo regulated intramembrane
proteolysis (RIP) by the Site-1 and Site-2 Proteases (S1P; S2P) (Ye et al. 2000). The freed TFs
are then translocated to the nucleus to regulate UPR gene expression similar to XBP1/bZIP60 (Ye
et al. 2000). In Arabidopsis, bZIP28 has been shown to undergo similar regulation and processing
(Liu et al. 2007), however an interaction between bZIP17 and BiP has yet to be verified. The
mammalian ATF6a, and the Arabidopsis bZIP28 TFs are the primary contributors to the ER stress
response from this arm of the UPR (Thuerauf et al. 2004, Thuerauf et al. 2007, Kim et al. 2018).
Together, this information supports the supposition that the core elements of the plant UPR,
namely IRE1 and bZIP17/28, have retained remarkable similarities to the mammalian UPR despite
millions of years of evolutionary divergence. In the following section I will discuss how these
conserved elements are applied in organism specific contexts, and discuss the ways in which plants
have co-opted this machinery to adapt to their unique environmental circumstances.
9
FUNCTIONAL DIVERSIFICATION OF THE UPR IN ADAPTATION TO
ENVIRONMENTAL STRESS
From Humans to Arabidopsis: A Myriad of Cell Stresses Elicit UPR Activation
The study of the UPR in human and animal models is largely focused on how altered ER
proteostasis and aberrant UPR signaling is related to the development of a number of human
diseases, including metabolic diseases, chronic inflammation, neurodegeneration, and cancer
(Hetz et al. 2020). Some of these studies examine how genetic defects allow the buildup of
misfolded proteins, and seek to mitigate the cytotoxic effects of the resulting aggregates (Stefani
and Dobson 2003, Rao and Bredesen 2004). However, most studies look to utilize the selective
manipulation of UPR components in disease intervention by targeting the UPR signaling network
with small molecule and gene therapy approaches (Hetz et al. 2020).
The mammalian UPR is a key modulator of the body’s response to overnutrition stress.
High fat diets or diets high in saturated fatty acids promote lipid accumulation in the liver, which
is sensed by IRE1 as ER membrane disequilibrium in those tissues (Halbleib et al. 2017, Hetz et
al. 2020). Subsequent activation of IRE1 controls the expression of a number of downstream
effectors boosting lipolysis, fatty acid oxidation, and promoting anti-inflammatory responses in
the affected cells (Zhang et al. 2011, Wang et al. 2018). However, sustained IRE1 activation in
the liver was found to be linked with hepatic insulin resistance and the development of type 2
diabetes through inhibition of insulin receptor signaling (Özcan et al. 2004). The IRE1 dependent
arm of the UPR also plays a critical role in the development of diabetes by controlling the survival
of insulin producing pancreatic β-cells (Hetz et al. 2020). Previous reports have demonstrated that
IRE1 activity needs to be carefully balanced in these cells as both hyperactivation of IRE1 and
10
loss-of-function mutations in IRE1 lead to low β-cell survival (Lipson et al. 2006, Hassler et al.
2015).
The role of the UPR in the progression of cancer and tumor growth is also an increasingly
studied topic. Cancer cells rapidly proliferate and metabolize large quantities of glucose (Urra et
al. 2016). In addition, tumor masses can be poorly vascularized which may lead to a number of
cellular stresses such as nutrient and oxygen deprivation conditions which are known to stimulate
UPR activation in mammalian models (Urra et al. 2016). Furthermore, the overexpression of
oncogenes in tumors also leads to higher rates of protein synthesis and increased overall demands
on the secretory pathway (Urra et al. 2016). As such, all arms of the UPR are known to promote
oncogenic transformation by contributing to tumor growth, angiogenesis, and immune system
evasion (Urra et al. 2016). High expression of the spliced XBP1 isoform in lymphoma, multiple
myeloma, brain cancer and breast cancer biopsies correlates with low patient survival rates (Urra
et al. 2016). Together, these examples of UPR involvement in overnutrition stress and cancer
growth demonstrate a large potential to treat prevalent human diseases by targeting UPR activities.
However, these therapies must be carefully designed, as misregulation of the UPR in off target
tissues could be more detrimental that the primary disease.
In contrast with mammals and humans, which can alter their environment, or move to avoid
environmental stressors, the sessile nature of plants demands physiological adaptation to
environmental change. As such, study of the plant UPR has largely focused on improving plant
growth and crop yield under adverse environmental conditions. There is a large potential for
biotechnological applications for UPR-related mechanisms in ensuring plant productivity.
However, considerable work must be done to understand how the conserved elements of the UPR
are integrated into intra- and inter-cellular signaling mechanisms that are plant specific. Even
11
though there is considerable evidence to suggest that the UPR components are required for many
different aspects of plant physiology (Chen and Brandizzi 2012, Chen and Brandizzi 2012, Barba-
Espín et al. 2014, Ruberti and Brandizzi 2014, Verchot and Pajerowska-Mukhtar 2021), we are
only beginning to connect the molecular activities of IRE1 and bZIP17/bZIP28 to the modulation
of plant-specific stress resistance.
Enhancing the UPR appears potentially critical to efforts to maintain crop productivity by
priming plants to survive under a diverse array of adverse environmental conditions (Tateda et al.
2008, Carvalho et al. 2014, Xiang et al. 2016, Verchot and Pajerowska-Mukhtar 2021). In
particular, a number of studies have demonstrated a significant contribution of the UPR to plant
responses to pathogen attack. Of these, viral pathogens predictably activate UPR signaling
(Verchot and Pajerowska-Mukhtar 2021). The translation of ER-targeted viral proteins has been
demonstrated to activate the UPR (Verchot and Pajerowska-Mukhtar 2021). However, the overall
effects of UPR activation are dependent upon the specific viral pathogen (Bao and Howell 2017).
During infection by most viral pathogens, the UPR actively prevents infection spread to
surrounding and systemic tissues (Caplan et al. 2009). However, some viruses have been shown
hijack the UPR to promote viral pathogenesis, as ablation of UPR components in these contexts
prevents viral replication and disease progression (Bao and Howell 2017). Although these are
promising first steps, further research is required to better understand the mechanisms by which
the UPR affects these outcomes in order to utilize UPR to promote viral resistance.
Pathogen attack by fungi or bacteria can also elicit a UPR response, however the
mechanisms behind the activation of the UPR sensors in these contexts is less clear. During
bacterial infection by pathogens such as Pseudomonas syringae, it has been hypothesized that
increased transcription and translation of secretory pathway components required for the cell’s
12
immune system response leads to activation of UPR (Verchot and Pajerowska-Mukhtar 2021).
However, treatment of Arabidopsis plants with the biotic stress-hormone salicylic acid (SA) was
also shown to activate both arms of the UPR controlled by IRE1 and bZIP28 (Moreno et al. 2012,
Nagashima et al. 2014). Although, the mechanism by which the UPR is activated by SA and
microbial pathogens is not well understood, further findings have demonstrated that IRE1a and
IRE1b are required to fully establish systemic acquired resistance (SAR) to these microbial
pathogens (Nagashima et al. 2014). Recent research has also demonstrated that the IRE1-bZIP60
dependent arm of the UPR positively affects infection outcomes of the necrotic fungal
pathogen, Alternaria alternata in the Nicotiana attenuata model (Xu et al. 2019). That work
demonstrates that the N. attenuata homologs of IRE1 and bZIP60 are activated by the defense
hormone jasmonic acid (JA) and upregulate UPR chaperones during fungal infection (Xu et al.
2019). Whether or not JA upregulation of the UPR is a broadly conserved trait in different plant
species has yet to be determined. Overall, the UPR has a clearly demonstrated role in mediating
plant-pathogen interactions. However further work is needed to understand what the effects of
UPR activation are at the molecular level before this information can be utilized in
biotechnological applications.
In addition to the verified activation of the UPR in biotic stress contexts, the UPR is also
known to be activated by a wide range of abiotic stresses which can affect plant health. One of the
most thoroughly described environmental UPR inducer is heat stress (Duke and Doehlert 1996,
Gao et al. 2008, Yang et al. 2009, Deng et al. 2011, Schmollinger et al. 2013) which affects the
rate at which proteins fold, and negatively affects the productivity of ER protein folding machinery
(Dobson 2003). UPR activation in these contexts promotes cell and plant survival (Gao et al. 2008,
Yang et al. 2009, Zhang et al. 2017). Extreme osmotic stress, salt stress, and exposure to heavy
13
metals such as selenium have also been shown to induce some of the downstream effects of the
UPR such as increased transcription of the BiP chaperone (Liu et al. 2007, Van Hoewyk 2016).
Among these heavy metals, cadmium stress was shown to activate both arms of the UPR (Xi et al.
2016). In these contexts, growth inhibition of Arabidopsis seedlings by cadmium treatment was
shown to be a UPR dependent process, as this growth inhibition was rescued in a bzip60 bzip28
double mutant (Xi et al. 2016). Furthermore, cadmium toxicity in Arabidopsis was also alleviated
by co-treatment with small molecule chemical chaperones which are known to reduce ER stress
and prevent protein misfolding (Xi et al. 2016). How heavy metal, salt, and osmotic stresses can
cause ER stress has yet to be determined, however, these examples suggest that manipulation of
the UPR could help to improve plant growth under abiotic stress.
A possible route to activation of the UPR by these biotic and abiotic stresses may lie in
novel associations between ER and plastid stress signaling cascades. A forward genetics screen
for genes involved in retrograde signaling from chloroplast to nucleus identified the ceh1 mutation
in the 4-hydroxy-3methylbut-2-enyl diphosphate synthase enzyme (Xiao et al. 2012). This
enzyme is a part of the plastidial methylerythritol phosphate (MEP) pathway, and further study of
this mutant demonstrated that the isoprenoid precursor 2-C-methyl-D-erythritol-2,4-
cyclopyrophosphate (MEcPP) acts as a retrograde signal during diverse stress responses, including
wounding and high light responses (Xiao et al. 2012). In these conditions, cellular accumulation
of MEcPP activates transcription of JA and SA biosynthesis enzymes in the nucleus (Xiao et al.
2012). In later studies, it was demonstrated that the UPR is strongly activated in the ceh1 mutant
in both SA-dependent and SA- independent manners (Benn et al. 2016).
This chloroplast-stress related UPR activation was also given further context by the
interesting effect of plastid sourced reactive oxygen species (ROS) on the induction of the UPR
14
(Ozgur et al. 2015). It was demonstrated that plastid-originated ROS production induced UPR
activation, further suggesting that plastidial stress may be intimately linked with UPR signaling
mechanisms (Ozgur et al. 2015). Indeed, recent reports have also demonstrated the plant UPR
plays a critical role in the response to high light induced singlet oxygen (1O2‐), a particularly
damaging ROS generated as a by-product of photosynthesis in the chloroplast (Triantaphylidès et
al. 2008, Xu et al. 2017, Beaugelin et al. 2020). In a study of the downstream effectors of 1O2‐,
Beaugelin et al. (2020) utilized the ch1 Arabidopsis mutant, which carries a mutation in the
Chlorophyll A Oxygenase gene and leads to 1O2‐ production in plants treated with high levels of
light. Acute treatment of this mutant with high light leads to induction of 1O2‐ dependent cell death
(Beaugelin et al. 2020). The authors found that when this mutant is treated with acute high light
the UPR is activated, as denoted by strong induction of transcriptional markers of both the IRE1
and bZIP28 dependent arms of the UPR, in an SA-dependent manner (Beaugelin et al. 2020).
Additionally, they found that the bzip60 bzip28 double mutant was resistant to high light induced
cell death suggesting the plant UPR promotes programmed cell death in this context. Accordingly,
pretreatment of plants with chemical chaperones known to alleviate ER stress and reduce UPR
responses also lead to lower level of damage in high light treated Arabidopsis leaves (Beaugelin
et al. 2020). However, the authors of this study also noted that mild ER stress and UPR activation
had a protective effect in high light conditions. The cell death phenotype of the ch1 mutant can be
avoided by gradual acclimation (hereafter referred to as light acclimation) of the ch1 mutant to
these conditions prior to acute high light treatment. They found that light acclimation followed by
high light treatment led to the selective induction of BiP3 transcription and a lower level of
transcription in all other UPR markers compared to the high light treatment alone. Accordingly,
they also found that genetic ablation of BiP3 in the bip3 mutant led to an increase in high light
15
induced cell death (Beaugelin et al. 2020). As increased BiP chaperone levels are an inherent
negative regulator of UPR sensor activation, the authors hypothesized that the UPR fulfills a dual
role in high light stress, wherein a mild UPR activation is part of the acclimatory response to 1O2‐
, and intense UPR activation leads to cell death. This example suggests that, similar to UPR
targeting in human disease therapy, UPR based biotechnology meant to improve plant growth and
stress responses must be carefully designed to limit off target effects.
While researching the UPR in the context of these biotic and abiotic stresses is important
to fully understand the endogenous functions of the UPR in plant life, the highly variable nature
of secondary stress responses complicates the study of the direct effects of UPR sensors. Therefore,
in the lab, chemical UPR inducers such as tunicamycin, which inhibits N-linked glycosylation in
the ER lumen, are often used to investigate the UPR by mimicking the conditions associated with
environmental stresses that cause the buildup of unfolded proteins in the ER (Welihinda and
Kaufman 1996). Furthermore, the biochemical effect of these chemical ER stress inducers is
conserved in most eukaryotic model organisms, which allows for comparison of in vivo UPR
mechanisms between kingdoms.
Functional Diversification of IRE1 Activation and Effects
Although IRE1 is the only UPR sensor found in metazoans, plants, and fungi, in-depth
investigations of IRE1 structure have revealed remarkable differences between kingdoms. This is
particularly true in the study of biochemical and structural modifications required to activate IRE1
RNase activity. Although very little is known about the plant IRE1 activation mechanism, the
mammalian and yeast IRE1s exhibit striking differences in their activation prerequisites and
signaling outputs (Figure 1.2; Bashir et al. 2021). After being released from BiP chaperones,
16
mammalian and yeast IRE1 luminal domains interact, bringing the IRE1 cytosolic domains into
close proximity (Figure 1.2A, B Step 1; Kimata et al. 2007, Amin-Wetzel et al. 2017). The
cytosolic domains of the mammalian IRE1 then interact and form what is known as a face-to-face
dimer. In this formation, the kinase active sites are sufficiently close to the target phosphorylation
site on the opposing IRE1 monomer to catalyze the reaction (Figure 1.2A, Step 2; Zhou et al. 2006,
Oikawa et al. 2009). In the next step, trans-autophosphorylation of the mammalian IRE1 leads to
a structural conformation shift that forces monomer reorientation into an RNase active back-to-
back formation (Figure 1.2A, Step 3; Bashir et al. 2021). In contrast, the S. cerevisiae IRE1
monomers initially form back-to-back dimers with protein-protein contacts on the RNase
subdomains, which do not allow for trans-autophosphorylation. Then these dimers further
aggregate into inactive higher-order IRE1 oligomers (Figure 1.2B, Step 2; Kimata et al. 2007,
Gardner and Walter 2011). Finally, the inactive S. cerevisiae IRE1 oligomers require binding of
unfolded proteins to their luminal domains, which induces a structural conformation shift allowing
for trans-autophosphorylation of nearby IRE1 monomers within the oligomer, leading to RNase
activation (Figure 1.2B, Step 3; Kimata et al. 2007, Gardner and Walter 2011). In mammalian
models activated IRE1 can also aggregate into higher-order oligomers depending upon the severity
and duration of ER stress. This oligomerization has also been attributed to unfolded protein binding
to the IRE1 luminal domains (Karagöz et al. 2017). While the endpoint effect (i.e. RNase
activation) is similar between these two models, there are dramatic differences in the RNase
signaling outputs between mammalian and S. cerevisiae IRE1 (Bashir et al. 2021). This is
exemplified by the differences between the in vitro RNase activity of mammalian and S. cerevisiae
IRE1. When the cytosolic domain of each IRE1 is heterologously expressed in E.coli and
incubated with a Förster resonance energy transfer (FRET) RNA substrate, only the mammalian
17
Mammalian IRE1
S. cerevisiae IRE1
Figure 1.2. Simplified models comparing RNase activation mechanism of mammalian and S.
cerevisiae IRE1s.
A) After being released from BiP (orange) in Step 1, mammalian IRE1 form a face-to-face dimer
allowing trans-autophosphorylation of the kinase domain (cyan) in Step 2. Phosphorylation causes
a shift in secondary structure leading to monomer rotation and forming the RNase-active back-to-
back dimer in Step 3. B) After being released from BiP (orange) in Step 1, S. cerevisiae forms
back-to-back dimers that cannot autophosphorylate, which then aggregate into higher order
oligomers in Step 2. Unfolded proteins then bind the luminal domain, leading to a shift in
secondary structure that allows autophosphorylation and subsequent RNase activation.
IRE1 displays constitutive RNase activity at low nanomolar concentrations of enzyme (Cross et
al. 2012). The S. cerevisiae IRE1 requires micromolar concentrations of enzyme and millimolar
concentrations of ADP (adenosine diphosphate) and salt to elicit appreciable in vitro RNase
activity (Wiseman et al. 2010). In vivo experiments have provided further context to these
18
observations, by demonstrating that mutations in the S. cerevisiae IRE1 that promote a lower
activation threshold lead to inhibition of yeast growth under physiological conditions (Bashir et
al. 2021). This suggest that IRE1 activity may only be required under severe stress in S. cerevisiae.
Additionally, whereas mammalian IRE1 exhibits XBP1 splicing activity and RIDD activity in
vivo, the only known function of S. cerevisiae IRE1 is splicing of the XBP1 homolog HAC1, as
no other mRNA targets have been identified (Bashir et al. 2021). However, these differences may
be attributable to functional diversification of IRE1 activity within yeasts, as a close relative of S.
cerevisiae, S. pombe, does not have a HAC1 homolog in its genome and exclusively performs
RIDD activities under ER stress (Kimmig et al. 2012, Maurel et al. 2014, Guydosh et al. 2017).
Whether Arabidopsis and other plant IRE1s exhibit activity closer to mammalian or S. cerevisiae
IRE1 has yet to be established. Previous results have demonstrated the Arabidopsis IRE1a and
IRE1b have RIDD activity similar to the mammalian IRE1, however fluorescent protein labeled
IRE1b formed aggregate foci under ER stress when expressed in S. cerevisiae similar to the native
protein (Mishiba et al. 2013, Zhang et al. 2016). Characterization of IRE1a and IRE1b in vitro
activity may help to clarify this point. In Arabidopsis and other Brassicaceae even further work is
required to elucidate the function of the divergent IRE1c gene. Although it lacks an ER luminal
domain and has several mutations in residues conserved between mammals, yeasts, and plants,
this isoform was still found to have essential and overlapping functions with IRE1A and IRE1B
(discussed in a later section; Mishiba et al. 2019, Pu et al. 2019). On the whole, this establishes
Arabidopsis as a new frontier in the study of IRE1 functional diversification.
This is further illustrated by a number of studies on the regulatory factors which are
upstream of IRE1 activation. In addition to the presence of unfolded client proteins inside the ER,
accumulating evidence suggests that other ER resident proteins and chaperones can affect IRE1
19
activity (Hetz et al. 2020). One of those regulators that has been well studied in mammalian models
is the ER transmembrane protein Bcl-2 associated X (BAX) inhibitor 1 (BI1), which has a well
conserved homolog in Arabidopsis (Kawai-Yamada et al. 2001, Chae et al. 2003, Kawai-Yamada
et al. 2004). In mammals, BI1 was found to physically interact with the mammalian IRE1,
inhibiting it’s RNase activity and the pro-survival role of IRE1 under ER stress (Lisbona et al.
2009). However, under chronic ER stress the mammalian BI1 also inhibits its namesake factor,
the pro-apoptotic BAX, leading to a dual role of BI1 in stress situations. Initial studies of BI1 in
Arabidopsis treated with osmotic stress suggested that this role may have been conserved in plants
(Kawai-Yamada et al. 2001, Chae et al. 2003). Upon closer inspection, it was demonstrated that
this was not the case, as a loss-of-function mutation in BI1 had no effect on IRE1 mediated splicing
of bZIP60 under ER stress conditions (Ruberti et al. 2018). In surprising contrast, BI1 was actually
found to be a negative regulator of the Arabidopsis ATF6 homolog, bZIP28, as genetic ablation of
BI1 in the bzip28 mutant background partially rescued the ER stress sensitivity of the bzip28
mutant (Ruberti et al. 2018). This suggests that plants have acquired new ways to regulate and fine
tune the responses of UPR sensors under ER stress.
Evidence of IRE1 functional diversification is also demonstrated by the different effects of
IRE1 RIDD activity in mammals and Arabidopsis. Overall, RIDD is suggested to be a pro-survival
process which functions by reducing the abundance of ER client mRNAs under ER stress (Walter
and Ron 2011, Maurel et al. 2014). However, in mammals RIDD activity has a dual role which
can promote cell survival under mild ER stress, but transitions to pro-apoptotic functions in
prolonged or severe ER stress situations. In these conditions, mammalian RIDD activity targets a
series of micro-RNA (miRNA) transcripts which ordinarily prevent the translation of the pro-
apoptotic caspase 2 protease (CASP2; Han et al. 2009, Maurel et al. 2014). In plants, neither the
20
miRNAs nor CASP2 are directly conserved. Thus far, what we know about the Arabidopsis IRE1s
suggests that their RIDD functionality has strong pro-survival roles (Ruberti et al. 2015). This is
particularly evident when comparing the differences between the stress responsive phenotypes of
the IRE1 and bZIP60 loss-of-function mutants. Germination of the ire1a ire1b double mutant
seeds on media containing a mere 25 ng/ml of tunicamycin is seedling lethal, while wild type (WT)
seedlings are relatively unaffected (Chen and Brandizzi 2012). In these conditions, commonly
referred to as chronic ER stress treatment, the bzip60 mutant has a WT-like phenotype (Chen and
Brandizzi 2012). Furthermore, complementation of the ire1a ire1b mutant with an RNase dead
IRE1b variant did not complement the ire1a ire1b ER stress lethality (Deng et al. 2013). This
therefore suggests that RNase activity other than bZIP60 splicing is critical to the pro-survival ER
stress response in Arabidopsis. Recent investigations have found that a number of Arabidopsis
RIDD targets are suppressors of autophagy, leading to the hypothesis that Arabidopsis RIDD
activities coordinate upregulation of autophagy during ER stress (Bao et al. 2018). On the whole,
this demonstrates that the bZIP60-independent functions of IRE1 have a substantial pro-survival
impact in Arabidopsis during ER stress situations, and contrasts with mammalian models where
XBP1-independent effects have mixed outcomes (Maurel et al. 2014), or the S. cerevisiae model
where IRE1 has no HAC1-independent effects (Bashir et al. 2021).
Functional Diversification of UPR Transcription Factors
Similar to IRE1, the core functionality of the ATF6 homologs in mammals and plants is
conserved (Liu et al. 2007, Ruberti and Brandizzi 2014). However, there are a number of important
distinctions between the activation mechanisms of the mammalian ATF6, and Arabidopsis bZIP28
(Pastor-Cantizano et al. 2020). In mammals, the accumulation of unfolded proteins leads to the
21
release of ATF6 by the BiP chaperones, subsequently revealing two Golgi Localization Signals
(GLSs) in the ER luminal domain (Shen et al. 2002, Schindler and Schekman 2009). A yet
unknown cargo receptor then links these signals with the cytosolic coat protein complex II (COPII)
forming an association which leads to translocation of ATF6 from the ER to the Golgi via COPII
vesicular transport (Nadanaka et al. 2004, Schindler and Schekman 2009, Srivastava et al. 2012).
In contrast, bZIP28 does not have luminal GLS sequences (Srivastava et al. 2012). Instead, two
dibasic motifs on the cytosolic face of the protein near the transmembrane domain are required for
translocation to the Golgi via COPII vesicles (Srivastava et al. 2012). Once translocated to the
Golgi it was widely assumed that bZIP28 was processed by S1P and S2P proteases, similar to
ATF6, due to the conserved S1P and S2P consensus cites (Srivastava et al. 2014). However, it was
recently demonstrated that the S1P protease does not participate in bZIP28 processing, instead a
yet unknown protease was found to remove the ER/Golgi luminal domain from the bZIP28
transmembrane domain (Iwata et al. 2017). Due to the conservation of the dibasic trafficking
motifs between bZIP28 and bZIP17, it is assumed that the trafficking and proteolytic processing
is the same for these two regulators. However, further study is needed to confirm this hypothesis,
as recent findings have shown that bZIP17 and bZIP28 do not respond identically to different
forms of ER stress (Liu et al. 2007, Kim et al. 2018). Whereas bZIP28 primarily mediates
tunicamycin induced ER chaperone transcription, bZIP17 is the primary contributor to ER
chaperone transcription under salt stress conditions (Liu et al. 2007, Kim et al. 2018). Interestingly,
differences in the response to varied cell stresses by these UPR TFs is not regulated exclusively
by the factors controlling their release at the ER.
In addition to the primary activation of bZIP17, bZIP28 and bZIP60 at the Golgi and ER,
the downstream effects of these UPR TFs are also controlled by their interactions with other
22
proteins in the nucleus (Figure 1.3). After being translocated, bZIP28 and bZIP60 bind promoter
sequences known as the ER Stress Response Elements (ERSE-I 5ʹ-CCAAT-N10-CACG-3ʹ) and
the Unfolded Protein Response Element-1 (UPRE-I 5ʹ-TGACGTGR-3ʹ ; Liu and Howell 2010).
In the nucleus the UPR TFs are assisted by the CCAAT-box-binding TF complex which is
conserved between mammals and plants (Liu and Howell 2010). This complex consists of three
Nuclear Y Factor (NF-Y) subunits, NF-YA, NF-YB, and NF-YC. In Arabidopsis there are 36
genes encoding NF-Y subfactors, four of which were demonstrated to interact with bZIP28 at the
ERSE-I promoter motif (Liu and Howell 2010). Although there is a large potential for differential
regulation of bZIP28 target binding based on the number of possible interactions with NF-Y
subunits, the overall effect of this interaction in ER stress resistance is yet unknown (Liu and
Howell 2010). In order to facilitate the formation of the transcription preinitiation complex at their
target binding sites, bZIP28 and bZIP60 must also interact with Ash2 and WDR5 proteins, which
are the core components of the COMPASS-like complex (Song et al. 2015). This interaction with
the COMPASS-like complex directs H3K4me3 deposition onto the promoters of UPR target
genes, a crucial step in gene specific transcription (Song et al. 2015). While a number of
downstream target genes are specific to either bZIP28 or bZIP60, they can also interact with each
other in a mechanism conserved between mammals and plants that coordinates UPR transcription
for a subset of downstream targets (Liu and Howell 2010, Ruberti and Brandizzi 2014).
Recent research has also revealed a number of interactions between bZIP28 and bZIP60
with plant-specific TFs. These interactions allow for the integration of UPR transcriptional
responses with other stress related pathways. Prior to the discovery of UPR involvement with
high-light induced PCD (Beaugelin et al. 2020), it was found that Arabidopsis seedlings grown
under high-light conditions exhibited a marked increase in ER stress sensitivity (Nawkar et al.
23
Figure 1.3. The UPR TFs interact with a variety of conserved and plant specific partners to
regulate transcription.
This figure was previously published in Pastor-Cantizano et al. (2020).
2017). This investigation determined that the causative mechanism was competitive interaction
between the UPR and a photoreceptor signaling cascade (Nawkar et al. 2017). Another bZIP TF
downstream of these photoreceptors, Elongated Hypocotyl 5 (HY5; Osterlund et al. 2000), was
found to compete with bZIP28 in the binding of ERSE-I promoter motifs, which have overlapping
sequence with HY5’s target G-box element (CACGTG; Nawkar et al. 2017). The physiological
relevance of this interaction was demonstrated by a HY5 loss-of-function mutant which exhibited
higher expression of UPR marker genes and increased ER stress resistance compared to wild-type
Arabidopsis plants (Nawkar et al. 2017).
Interactions between UPR TFs and nuclear SA signaling have also been described
(Nagashima et al. 2014). In addition to the previously discussed role of SA in the situational
24
activation of the UPR response, a number of SA signaling components have also been shown to
interact with UPR TFs to fine tune their activities (Nagashima et al. 2014, Meng et al. 2016, Lai
et al. 2018). Among these is the constitutive expressor of pathogenesis-related genes-5 (CPR5) a
nuclear envelope localized protein which represses SA accumulation under non-stressed
conditions to promote growth (Bowling et al. 1997). The cpr5 mutant had constitutively higher
UPR transcription, which surprisingly was found to be SA independent (Meng et al. 2016). It was
found that CPR5 physically interacted with bZIP60 and bZIP28 and repressed their transcriptional
activities (Meng et al. 2016). As such, the cpr5 mutant was found to be strongly resistant to chronic
ER stress. In addition, bZIP60 and bZIP28 were found to interact with the Nonexpressor of
Pathogenesis Related 1 (NPR1) protein (Lai et al. 2018). NPR1 is an SA receptor that forms homo-
oligomers in the cytosol through interprotein disulfide bonds in an inactive state (Mou et al. 2003).
Upon SA accumulation or SA treatment, cells first undergo a cytosolic reduction, reducing the
NPR1 disulfide bonds and freeing the monomers which are then translocated to the nucleus (Mou
et al. 2003). Upon SA binding, conformational changes in NPR1 activate the protein, which forms
a transcriptional enhancer complex with the TGA2 clade of bZIP transcription factors (Mou et al.
2003, Wu et al. 2012). ER stress conditions also lead to cytosolic reduction and nuclear
translocation of NPR1 in a SA-independent manner (Lai et al. 2018). In contrast with its SA
receptor function, NPR1 under ER stress interacted with bZIP60 and bZIP28 in the nucleus
repressing their activities (Lai et al. 2018). As such, the npr1 loss of function mutant was also
strongly resistant to ER stress treatment and exhibited increased transcription of UPR chaperones
(Lai et al. 2018). On the whole, these collective results demonstrate that the UPR TFs have a strong
role in mediating growth and defense trade-offs by integrating UPR functionality with other plant
cell signaling mechanisms activated by a diverse set of cell stressors.
25
FUNCTIONAL DIVERSIFICATION OF THE UPR IN DEVELOPMENT
The UPR is Essential to Multicellular Metazoan Development
In addition to the clear roles of the UPR in adaptation to environmental stress, accumulating
evidence suggests that the UPR also makes significant contributions to the normal growth and
development of multicellular eukaryotes. Basic models of UPR activation often suggest that UPR
regulators are completely inactive under physiological conditions (i.e., in the absence of
exogenously applied stress). However, the evidence that complete loss-of-function mutations of
UPR sensors in multicellular eukaryotes are lethal under physiological conditions suggests that
this may be inaccurate (Mitra and Ryoo 2019). In heterotrophic and autotrophic unicellular model
organisms (i.e., S. cerevisiae and Chlamydomonas reinhardtii) complete loss-of-function
mutations in their sole UPR regulator, IRE1, are viable (Nikawa and Yamashita 1992, Yamaoka
et al. 2018). Given standard culture conditions, both organisms proliferate at WT levels. Only
when challenged with nutrient starvation or induced ER stress do these mutants display appreciable
growth phenotypes.
In marked contrast, complete loss-of-function mutations of mammalian, Xenopus (frog),
Drosophila (fruit fly), and Oryzias (medaka fish) IRE1s are all embryo lethal (Mitra and Ryoo
2019). In each of the models, IRE1 activities were found to be critical to developmental
programming of certain tissue types (Mitra and Ryoo 2019). In each case, the tissue specificity
and IRE1 mechanism (i.e., XBP1 splicing or RIDD) required for proper development are highly
dependent on the organism in question. In mammalian models, IRE1 is required for B cell
differentiation (Reimold et al. 2000, Reimold et al. 2001). In response to antigen detection, pre-B
26
cells differentiate into antibody secreting plasma cells, which involves secretion of a large quantity
of immunoglubulins and a dramatic expansion of ER size (Iwakoshi et al. 2003, Van Anken et al.
2003). IRE1 dependent activation of XBP1 is necessary to actuate these changes (Iwakoshi et al.
2003, Van Anken et al. 2003). However, the embryo lethality of both IRE1 and XBP1 knockout
mice was commonly traced to liver dysfunction during embryogenesis (Lee et al. 2005).
Furthermore, liver specific expression of XBP1 in XBP1 knockout lines, also demonstrated a
requirement for XBP1 in the development of the pancreatic and salivary glands (Lee et al. 2005).
While the majority of tissue specific defects in an IRE1 knockout are shared by XBP1 knockouts
in mammals, there are also XBP1-independent requirements for IRE1. For example, defects in
extraembryonic tissue development (i.e., the placenta) could not be rescued by complementation
with a spliced XBP1 isoform (Iwawaki et al. 2009). In medaka fish and frogs IRE1 and XBP1
were required for notochord and hatching glad development (Bennett et al. 2007, Tanegashima et
al. 2009). In contrast with mammalian models, which have XBP1-independent roles for IRE1 in
development, developmental defects of the IRE1 knockout in medaka fish are entirely rescued by
transgene expression of the spliced XBP1 isoform, indicating that in that organism there are no
XBP1-independent rolls for IRE1 in development (Ishikawa et al. 2017). In Drosophila there are
both XBP1-dependent and XBP1-independent roles of IRE1 in development, although there has
been a particular emphasis on the study of RIDD function in photoreceptor cells of pupal eyes
(Coelho et al. 2013, Huang et al. 2017). In this tissue XBP1 expression is not detectable, instead
loss of IRE1 leads to RIDD target accumulation, promoting fatty acid transport and impairment of
Rhodopsin-1 trafficking during photoreceptor cell differentiation (Coelho et al. 2013). On the
whole, these examples demonstrate a strict requirement for at least one facet of IRE1 activity in
most metazoan model organisms.
27
Similar to IRE1, complete loss-of-function mutations in the ATF6 arm of the UPR also
exhibit considerable differences in their effect on development of metazoan models. In invertebrate
species, there is a single copy of the ATF6 gene which is largely dispensable for UPR gene
transcription (Mitra and Ryoo 2019). Although ATF6 in these organisms has not been studied
extensively, ATF6 knockouts in Caenorhabditis elegans, and Drosophila are viable (Mitra and
Ryoo 2019). In vertebrates (i.e., mice and medaka fish), single knockouts of either ATF6α or
ATF6β are viable and fertile, however the double knockout has an early embryo lethal phenotype
which is noted for being more severe than other UPR knockouts such as IRE1 or XBP1 (Yamamoto
et al. 2007, Ishikawa et al. 2011, Ishikawa et al. 2013). It has been suggested that this is due to the
vertebrate ATF6 having an outsized role in the upregulation of ER chaperones and UPR signaling
mediators under physiological conditions (Yoshida et al. 2001, Yamamoto et al. 2008, Ishikawa
et al. 2013). Overall, this supports the hypothesis that conserved UPR components have been
adapted in novel ways by different organisms to perform critical cell functions.
In most of these examples, the cell and tissue types affected by genetic ablation of UPR
regulators correspond to tissues with high secretory requirements (Mitra and Ryoo 2019).
Experiments in Drosophila have provided evidence that endogenous developmental processes
were negatively impacting ER proteostasis by increasing levels of unfolded proteins in the ER
(Mitra and Ryoo 2019). In these studies, it was shown that an IRE1 which lack unfolded protein
sensing abilities was unable to complement the development defects of an IRE1 knockout line
suggesting that increased secretory demand was a causative factor. Together, this information
demonstrates the essential nature of UPR function to multicellular development, and further
suggests that while core UPR mechanisms have been conserved, the relevance of these
mechanisms is strongly dependent on the individual organism and tissue contexts.
28
Physiological Roles of the Plant UPR in Development
Similar to multicellular metazoans, mutations in UPR components also have severe
impacts on the growth, development and reproduction of plants. In rice (Oryza sativa), there is a
single IRE1 homolog, OsIRE1 (Wakasa et al. 2012). To understand OsIRE1’s role in development,
a recent study introduced specific missense mutations in conserved residues in the native OsIRE1
by homologous recombination-based gene targeting (Wakasa et al. 2012). This was done in order
to overcome the potential lethality of complete loss-of-function mutations. In the first set of
transformations, they mutated a conserved lysine residue in the OsIRE1 kinase active site, and in
a second set of transformations they mutated a lysine in the RNase active site. From multiple
independent transformants, the authors were unable to obtain transformants which were
homozygous for the kinase domain mutation, however they were able to obtain transformants for
the RNase domain transformation. Furthermore, the RNase domain mutation did not produce any
discernable effects on transformant development, despite the verified inability of the mutant
OsIRE1 to splice the bZIP60 homolog OsbZIP50 (Wakasa et al. 2012). Further investigations have
shown that an RNAi knockdown of OsIRE1 leads to defective shoot, root and reproductive organ
growth, while RNAi knockdown of OsbZIP50 had no effect on development (Hayashi et al. 2012).
Together this suggests that the kinase, and not the RNase activity of OsIRE1 is critical to rice
development and reproduction. Although the metazoan IRE1 has downstream mechanisms which
are independent of the RNase activity, i.e., the IRE1-TRAF2-JNK signaling axis, whether or not
these activities affect metazoan development has yet to be elucidated. As such, determining the
RNase-independent role of OsIRE1 in development may help to inform the study of IRE1 in other
organisms.
29
In Arabidopsis there are three copies of the IRE1 gene: IRE1a, IRE1b, and IRE1c which
perform partially redundant functions (Mishiba et al. 2019, Pu et al. 2019). Single mutant
phenotypes of each IRE1 gene are identical to WT plants under normal Arabidopsis culture
conditions, however high-order mutations cause increasingly severe developmental defects. The
ire1b ire1c double mutant has a gamete lethal phenotype (Pu et al. 2019). Defects in male and
female gamete viability were observed (Mishiba et al. 2019, Pu et al. 2019). The ire1a ire1b double
mutant reproduces normally, but has a short root phenotype (Chen and Brandizzi 2012). The
differences between the double mutant phenotypes are likely to be caused by selective tissue
expression of the IRE1 homologs rather than divergent functions of the IRE1 proteins. IRE1c is
expressed heavily in reproductive tissues during gametogenesis, whereas IRE1a is more heavily
expressed in root tissues; the IRE1b homolog is expressed at a similar level in nearly all tissue
types (Koizumi et al. 2001, Noh et al. 2002, Mishiba et al. 2019, Pu et al. 2019). Like the ire1b
ire1c double mutant the ire1a ire1b ire1c triple mutant is also gamete lethal (Mishiba et al. 2019).
However, plants which are heterozygous for ire1c and homozygous for ire1a and ire1b have severe
developmental defects in all tissue types (Mishiba et al. 2019). How the Arabidopsis IRE1 genes
affect growth and development is still unknown. Although functional complementation of the
ire1a ire1b mutant with kinase-dead and RNase dead mutations have been performed, the growth
phenotypes of these complemented lines in the absence of stress has yet to be published (Deng et
al. 2013). However, loss of function mutations in the Arabidopsis XBP1 homolog bZIP60 do not
have any growth or reproductive phenotypes under standard Arabidopsis growth conditions
(Nagashima et al. 2011, Chen and Brandizzi 2012, Moreno et al. 2012). This would indicate that
like OsIRE1, the Arabidopsis IRE1s promotes plant growth through an alternative mechanism
which is independent of bZIP60. On the whole, these phenotypes suggest that IRE1 performs
30
critical functions which promote the growth and development of monocot and dicot model plants,
although more research is needed to understand whether IRE1 promotes plant growth through
alternative RNase activities or kinase dependent activities. Furthermore, how these effects of IRE1
are integrated with other growth and development regulating pathways is also not well understood.
It will be interesting to understand how this IRE1- dependent mechanism might be connected with
other conserved pathways that regulate eukaryotic growth and development, such as the Target of
Rapamycin kinase (Shi et al.2018).
Loss-of-function mutations in the UPR TFs bZIP17 and bZIP28 also have severe effects
on Arabidopsis growth and development. The bzip17 bzip28 double mutant was originally thought
to be an unobtainable, lethal mutation. However, after screening thousands of seedlings Kim et al.
(2018) was able to isolate a viable mutant with extreme growth defects. This bzip17 bzip28 double
mutant was found to have rosettes a third of the size of WT rosettes (Kim et al. 2018). When grown
in standard sterile culture conditions for 12 days bzip17 bzip28 roots were a mere 0.5 cm long,
compared to almost 7 cm long in the WT background. Although transcriptome analysis of this
mutant under normal conditions demonstrated significant dysregulation of genes involved with
root growth, it is still unknown which genes are relevant to the growth promoting effects of bZIP17
and bZIP28 (Kim et al. 2018). However, in a previous study of the growth defects induced by
mutation of the S2P protease which activates these UPR TFs, it was demonstrated that bZIP17 and
bZIP28 promote brassinosteroid (BR) hormone signaling (Che et al. 2010). The authors found that
the bzip17, bzip28, and the S2P single mutants were less sensitive to exogenous BR. Furthermore,
the authors demonstrated that expression of a constitutively active bZIP17 and bZIP28 can
partially rescue the growth of a BR insensitive 1(BRI1) mutant allele (Che et al. 2010). BRI1 is a
plasma membrane (PM) BR receptor (Li and Chory 1997). The specific mutant used in the Che
31
et al. (2010) study, bri1-5, has full BR binding and signaling capabilities, however it is not
effectively trafficked to the PM and accumulates in the ER (Hong et al. 2008). In contrast with the
rescue of bri1-5 by expression of activated bZIP17/28, expression of a constitutively active bZIP17
and bZIP28 had no effect on the growth of the bri1-6 allele. In this mutant BRI1 is effectively
trafficked to the PM but is defective in BR signaling (Li and Jin 2007). Therefore, Che et al. (2010)
suggest that the increased level of ER chaperones induced by BZIP17, bZIP28 and S2P, promotes
the proper delivery of BRI1 to the PM to affect BR signaling. Whether or not defective BR
signaling underlies the severe defects of the bzip17 bzip28 double mutant remains an exciting topic
for future study.
Genetic interactions between the IRE1 and bZIP17/BZIP28 dependent arms of the UPR
have also been studied in Arabidopsis by crossing viable UPR mutants (Deng et al. 2013, Kim et
al. 2018, Bao et al. 2019). When the bzip17 bzip28 mutant was crossed with the bzip60 single
mutant, no triple mutants could be obtained (Kim et al. 2018). However, plants which were
homozygous for bzip17 and bzip28, and heterozygous for bzip60 had more severe developmental
defects than the bzip17 bzip28 double mutant and were completely sterile (Kim et al. 2018). This
suggests that the downstream transcriptional regulation performed by bZIP60 and bZIP17/28 have
overlapping or compensatory functions in developmental contexts (Kim et al. 2018). This is
supported by qRT-PCR data which showed a 3-fold increase in the basal levels of bZIP60 splicing
in the bzip17 bzip28 double mutant in unstressed conditions (Kim et al. 2018). bZIP17 and bZIP28
mutants have also been crossed into IRE1 mutant lines. The ire1a ire1b bzip28 triple mutant was
not obtainable in previous studies (Deng et al. 2013), however, more recent work has obtained an
ire1a ire1b bzip17 triple mutant, which was found to have a more severe root growth defect than
the ire1a ire1b double mutant (Bao et al. 2019). Although it was not determined if bZIP17 or
32
bZIP28 were activated as a compensatory mechanism in the ire1a ire1b mutant, these studies
demonstrate that there may be considerable interactions between the two arms of the UPR in
Arabidopsis (Bao et al. 2019). Further research is needed to understand whether these interactions
are due to convergent regulation of the same genes through alternative mechanisms, or whether
separate defects in gene regulation downstream of these UPR sensors has synergistic, negative
effects on plant growth.
In addition to the important roles of the core UPR sensors have in promoting plant growth,
accumulating evidence suggests that the downstream genes targeted by the UPR also have
significant roles in development. One of these targets Arabidopsis Heat Shock Protein 90.7
(HSP90.7), which is highly upregulated under ER stress conditions, was also found to have specific
functions in proliferating tissues (Ishiguro et al. 2002, Klein et al. 2006). The shd (hsp90.7)
knockout mutant is phenotypically identical to clv, a mutant defective in CLAVATA signaling (a
critical negative modulator of shoot apical meristem activity) indicating that HSP90.7 may be
required for plant-specific production of the CLAVATA peptide (Miwa et al. 2009, Aichinger et
al. 2012). Further examples of UPR effectors with plant-specific roles in growth and development
can also be found with respect to ERdj3 (ER resident J domain 3) protein function during
gametophyte development (Yamamoto et al. 2008). J domain proteins (Hsp40) found in the ER
lumen bind BiP proteins and stabilize their interactions with unfolded client proteins (Misselwitz
et al. 1998, Yamamoto et al. 2008). ERdj3A, which is induced under ER stress, contains a C-
terminal protein disulfide isomerase domain that has reductive capabilities on substrates in vitro
(Yang et al. 2009), in addition to the canonical HSP40 ATPase activity that these proteins usually
possess (Ma et al. 2015). This suggests that ERdj3A may act on a plant-specific subset of client
proteins and may also have novel protein folding properties. Further in vivo analyses of ERdj3A
33
and its homologs ERdj3B and P58IPK support this possibility by demonstrating their importance
in development (Maruyama et al. 2014). Indeed, genetic analysis of the mutant Thermosensitive
Male Sterile 1 (tms1) revealed a nonfunctional allele of ERdj3A, that under elevated temperatures
was defective in pollen tube growth (Yang et al. 2009). Under normal conditions, in conjunction
with P58IPK and ERdj3b, ERdj3A was also shown to mediate polar haploid nuclei fusion in
female gametophytes (Maruyama et al. 2014) prior to double fertilization. During this nuclear
fusion process, the perinuclear ER fuses with the outer nuclear envelope and creates a continuous
outer membrane around the two haploid nuclei, which is followed by a second fusion of the inner
nuclear membranes (Jensen 1964). Recently it was demonstrated that ERdj3A and P58IPK are
required for the fusion of the ER membrane with the outer nuclear membranes. A double knockout
(erdj3a p58ipk) resulted in seed abortion after fertilization due to aberrant endosperm proliferation,
similar to that found in bip1 bip2 double mutants (Maruyama et al. 2010, Maruyama et al. 2014).
The inner membrane fusion requires the ERdj3B/P58IPK pair, and although the erdj3b p58ipk
double mutants had unfused haploid nuclei in close proximity, unlike erdj3a p58ipk, no aborted
seeds were found (Maruyama et al. 2014). The developmental defects found in plants with mutant
alleles of UPR induced ER-resident proteins (e.g., ERdj, BiP, SHD) are consistent with the
evidence that high-order mutations in Arabidopsis IRE1 lead to both male and female gametophyte
lethality (Mishiba et al. 2019, Pu et al. 2019) and with the evidence that the bzip17 bzip28 bzip60
is sterile (Kim et al. 2018). This underscores the need to fully understand the detailed functional
mechanisms of downstream UPR components in addition to the core UPR sensors. Although
studies exploring the similarities between yeast, mammalian and plant UPR have led to significant
advances in plant ER stress research, in order to fully understand the mechanisms connecting the
UPR to plant specific physiology it will also be important to look at the contrasting characteristics.
34
RATIONAL FOR STUDY
The molecular products assembled inside the ER have an ever-expanding relevance to
plants under environmental stress and in developmental contexts. Although many open questions
still plague the study of the UPR in plants, including the identity of the molecular mechanisms for
the activation and de-activation of the master regulator IRE1, the general relevance of the UPR in
maintaining ER homeostasis is clear. The ERQC and UPR maintain the folding properties of the
ER, and in doing so, enable a wide range of downstream processes from proper heat stress
adaptation and defense against pathogens, to root growth. Specifically, the downstream effectors
of the UPR have been implicated in transcriptional and post transcriptional regulation of both ER
homeostatic genes, and developmental processes. However, new oddities arising in research
focusing upstream and downstream of the UPR offer ever expanding possibilities where the UPR
may play a defining role in plant physiology. UPR activation in response to plastid metabolic
dysfunction and oxidative stress implicates the potential for the UPR to respond in many different
signal transduction cascades that utilize ROS as a secondary messenger. Further inquiry exploring
the canonical UPR, in non-canonical and tissue-specific contexts, may help elucidate hidden
functions and better integrate our understanding of UPR functionality in plant life.
As such, in my dissertation research I examined the roles of the UPR in both stress and
developmental contexts. In these studies, I investigate the nature of the relationship between the
conserved core UPR sensors and signaling pathways which are specific to plants, or are conserved
in eukaryotes but have taken on new functions in Arabidopsis. First, I elucidated the cellular and
physiological consequences of ROS generation by conserved NADPH oxidases under ER stress
conditions in Chapter II. Second, I explored the functional significance of the UPR in regulation
of transcription during spaceflight associated stresses in Chapter III. Third, I demonstrate an
35
important functional connection between IRE1 and Target of Rapamycin (TOR) signaling in the
context of seedling growth and development in Chapter IV. On the whole, these works provide
important new information on how the plant UPR is integrated into broader plant signaling
pathways and deepen our understanding of how the conserved UPR mechanisms have been
adapted by plants to meet the requirements of their unique ecological niche.
36
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37
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51
CHAPTER II
NADPH OXIDASE ACTIVITY IS REQUIRED FOR ER STRESS
SURVIVAL IN PLANTS
The work presented in this chapter has been published in The Plant Journal:
Angelos E, Brandizzi F. (2018) NADPH oxidase activity is required for ER stress survival in
plants. Plant Journal. 96(6):1106-1120.
52
ABSTRACT
In all eukaryotes, the unfolded protein response (UPR) relieves endoplasmic reticulum
(ER) stress, which is a potentially lethal condition caused by the accumulation of misfolded
proteins in the ER. In mammalian and yeast cells, reactive oxygen species (ROS) generated during
ER stress attenuate the UPR, negatively impacting cell survival. In plants, the relationship between
the UPR and ROS is less clear. Although ROS develop during ER stress, the sources of ROS linked
to ER stress responses and the physiological impact of ROS generation on the survival from
proteotoxic stress are yet unknown. Here we show that in Arabidopsis thaliana the respiratory
burst oxidase homologs, RBOHD and RBOHF, contribute to the production of ROS during ER
stress. We also demonstrate that during ER stress RBOHD and RBOHF are necessary to properly
mount the adaptive UPR and overcome temporary and chronic ER stress situations. These results
ascribe a cytoprotective role to RBOH‐generated ROS in the defense from proteotoxic stress in an
essential organelle, and support a plant‐specific feature of the UPR management among
eukaryotes.
53
INTRODUCTION
Physiological and stress situations causing insufficiency of the endoplasmic reticulum (ER)
to meet cellular demands for secretory protein folding lead to a potentially lethal condition, known
as ER stress (Gething et al. 1992). To overcome ER stress and restore homeostasis, protective
signaling cascades, collectively called the unfolded protein response (UPR), originate at the ER
and lead to the synthesis of ER chaperones and foldases to attenuate ER stress. If this adaptive
UPR fails, such as in conditions of unresolved or chronic ER stress, cells commit to programmed
cell death (Ron et al. 2007, Ruberti et al. 2015, Angelos et al. 2017). In all eukaryotes, the adaptive
phase of the UPR is initiated with the activation of IRE1, an ER-associated membrane kinase and
ribonuclease, which catalyzes the unconventional splicing of transcripts of bZIP-transcription
factors: yeast Hac1, mammalian Xbp1, or plant bZIP60. This step is necessary for the production
of an active transcription factor that controls the expression of UPR target genes (Deng et al. 2011,
Nagashima et al. 2011, Moreno et al. 2012). In multicellular eukaryotes, the UPR has expanded
to include additional UPR effectors, such as membrane tethered bZIP transcription factors
(MTTFs), namely mammalian ATF6 and plant bZIP28. Upon sensing ER stress, these MTTFs
translocate to the Golgi, where the cytosol-exposed transcription factor domain is proteolytically
removed from the transmembrane anchor and translocated to the nucleus for the transcriptional
regulation of UPR target genes (Liu et al. 2007b, Gao et al. 2008, Srivastava et al. 2013, Sun et
al. 2013).
In metazoan cells, a third arm of the UPR is activated by the ER associated PKR-like ER kinase
(PERK) protein, which oligomerizes and autophosphorylates in conditions of ER stress. PERK
activity results in the phosphorylation and inactivation of the eukaryotic translation initiation
54
factors eIF2A thereby promoting a global repression of the rate of the protein translation (Harding
et al. 1999, Shen et al. 2002). The transcription factors ATF4 and Nrf2 downstream of PERK are
able to escape this translational repression and upregulate an oxidative stress response through the
production of antioxidant proteins (Harding et al. 2000, Cullinan et al. 2003). Indeed, mutations
in PERK signaling markedly increase the generation of reactive oxygen species (ROS), which
negatively affect UPR efficiency and the ability of cells to survive ER stress (Marciniak et al.
2004, Back et al. 2009, Han et al. 2013, Maity et al. 2016). In yeast, which similarly to plants lack
PERK, a dysregulated production of H2O2 under ER stress results in a translational attenuation of
ER stress genes (Maity et al. 2016). Therefore, in metazoans and yeast, ROS cause attenuation of
the cytoprotective functions of the UPR and acceleration of responses leading to cell death. In
humans, this process potentiates the development of multiple diseases including diabetes,
neurodegenerative diseases, and atherosclerosis (Malhotra et al. 2007).
In plants, a functional connection between ROS and the UPR management has not yet been
clearly defined. During growth and in conditions of stress, several organelles including the
mitochondria, chloroplasts, and peroxisomes generate ROS (Tripathy et al. 2012). ROS are also
produced in the apoplast mainly by the activity of the membrane-bound NADPH Oxidase (NOX)
enzymes, known in plants as respiratory burst oxidase homologues (RBOH) (Torres et al. 2002).
The NOX/RBOH enzymes generate O2- through electron transfer from NADPH to oxygen (Gapper
et al. 2006). O2- is highly reactive and is dismutated to H2O2 either via the superoxide dismutase
(SOD) enzymes or spontaneously (Mori et al. 2004). H2O2 is more stable than O2- and moves
through membranes via aquaporins (Bienert et al. 2007), and it is therefore considered as a potent
signaling ROS in plants (Sadhukhan et al. 2017). Thus far in plants, an increase of soluble H2O2
and lipid peroxidation during ER stress have been reported (Ozgur et al. 2014, Ozgur et al. 2015,
55
Ozgur et al. 2018) but the source of ROS during ER stress and the influence of ER-stress generated
ROS on UPR signaling are not yet established. The oxidative function of ERO1 (ER oxidoreductin
1) in the ER lumen is a significant source of ER peroxides both in homeostatic conditions of growth
and during ER stress; however, an increase in NADPH Oxidase activity has also been observed
via biochemical assays during the early UPR (Tu et al. 2004, Sevier et al. 2008, Zito 2015, Ozgur
et al. 2018). Under similar conditions, small inductions in transcript levels of RBOHD and
RBOHF, two plasma membrane-localized NADPH Oxidases (Torres et al. 2002, Torres et al.
2005), were also noted in tissues subjected to ER stress treatment, leading to the suggestion that
increases in ROS levels were due to the respiratory burst oxidase homologs D and F (RBOHD and
RBOHF) (Ozgur et al. 2014). Nonetheless, it is yet to be experimentally tested to what extent
RBOH activity contributes to the ROS levels during ER stress, and whether these enzymes are
necessary for the actuation of effective ER stress responses. More generally, the downstream
effects of increased ROS levels during plant ER stress responses are also largely unmapped.
Previous reports have shown a variable regulation of the antioxidant defense systems under
conditions of ER stress. For example, in conditions of ER stress the O2- scavenging activity of
superoxide dismutase is induced in roots, but down-regulated in shoots. Conversely, H2O2
scavenging activities of catalase and ascorbate peroxidase are upregulated in shoots but have no
change in roots (Ozgur et al. 2014). However, in both roots and shoots a significantly increased
glutathione content and glutathione reductase activity during ER stress lends weight to the
conclusion that antioxidant defenses are upregulated to manage the increased ROS production in
ER stress (Ozgur et al. 2014). Nonetheless, critical questions remain unanswered. For example, it
is yet unknown what effects an increase in ROS levels may have on the adaptive UPR, nor is it
understood whether ROS may contribute to life or death decisions in temporary and chronic ER
56
stress. To address these fundamental questions, in this work we explored the functional connection
between ROS and the UPR in plants. We demonstrate that O2- and H2O2 are significantly
contributed by RBOHD and RBOHF during ER stress. We also show that RBOHD and RBOHF
elicit a transcriptional response to ROS during ER stress in the adaptive UPR. Furthermore, we
provide evidence for a stringent requirement of RBOHD and RBOHF to prevent the progression
of cell death in recovery from temporary ER stress and under chronic ER stress. Together, these
findings support a positive role of superoxide signaling in potentiating the cell’s ability to survive
temporary and chronic ER stress and ascribe a significant role to two RBOH proteins in this
process.
57
MATERIALS AND METHODS
Plant Materials and Growth Conditions
Arabidopsis thaliana ecotype Columbia (Col-0), rbohd rbohf, (Torres et al. 2002) ire1a
ire1b, and bzip60 bzip28 (Chen et al. 2012, Deng et al. 2013) plants were used in this study. For
all experiments, surface-sterilized seeds were plated directly onto petri dishes containing half-
strength Linsmaier and Skoog (½ LS) medium, 1.0% w/v sucrose, and 1.0% agar and then cold
treated (4°C) in the dark for 2 days to synchronize germination. Plates were then transferred to a
Percival growth chamber and incubated for the indicated time at 21°C under continuous light (130
μE).
Superoxide Histochemical Staining and Quantification
WT or rbohd rbohf seedlings were grown vertically on for 7 days, and then transferred to
½ LS media containing 1.0 μg/ml Tm, 1.0 μg/ml TM + 2.5 µM DPI, or DMSO and allowed to
grow for a further 24 or 48 hours (hr) in the growth chamber. Whole seedlings were used for the
subsequent Nitro Tetrazolium Blue (NBT) staining which took place at the same time on each day.
NBT was dissolved to a concentration of 1 mg/ml in 20 mM HEPES pH 6.1, and protected from
light until used. To reduce the inherent variability created by staggered staining of the seedlings
for very short incubation periods, all experimental groups were treated with NBT solution at the
same time. To do so, six 60 mm Petri dishes containing 2 ml of ddH2O were prepared. Fifteen
individuals from each genotype/treatment were then transferred to separate dishes with forceps.
Once all seedlings were transferred, 15 ml of NBT solution was added to each dish and covered
58
for 15 minutes (min). For each plate, the NBT solution was quickly removed with a seriological
pipette and replaced with ~20 ml of ddH2O to remove excess NBT. Restarting at the first dish, the
ddH2O was then removed, and seedlings were submerged in 95-100% ethanol for 10 min to fix
the root tissues. Seedlings were then mounted on slides in a 1:1 ethanol:glycerol solution with a
coverslip covering just the roots. Images were obtained using the microscope function of an
Olympus Tough F2.0 camera outfitted with ring LED light guide. Over a white surface, slides
were placed on a 60 mm Petri dish marked with a reference distance. The slide and 60 mm dish
were then placed in the center of a 100 mm square Petri dish and covered with the lid. The camera
was placed directly on the square lid for imaging to ensure consistent distance from the subject.
Three independent experiments were performed with similar results.
To quantify the stain intensity along the root, unedited images were converted to 32 bit
black and white in ImageJ. Beginning at the root apex, pixel intensities were recorded along a
traced line segment (1000 individual measurements). The same line traces were then moved
immediately left or right of the root and background pixel intensities were recorded. For each root,
relative pixel stain intensity was calculated by subtracting the background value from the original
trace value. For each experimental group the relative stain intensity from 8 roots was averaged and
standard error calculated. Three independent experiments were performed with similar results.
Extraction and Quantification of H2O2 in Seedling Tissues using Amplex Ultra Red
Two H2O2 extraction methods described previously (Chakraborty et al. 2016, Le et al.
2016) were tested: 1) phosphate buffer (K2HPO4, 20 mM pH 6.5) and 2) neutralized
Trichloroacetic Acid (TCA). For phosphate buffer extractions, 200 μl was added to frozen tissue
59
then briefly vortexed. Samples were then centrifuged at 21000 xg and 4°C for 20 min to ensure
plant debris was pelleted then used immediately for H2O2 quantification. NTCA extractions were
performed as follows: ten percent trichloroacetic acid (TCA), and 1 M sodium bicarbonate
solutions were prepared and kept on ice. Two hundred microliters of 10% TCA was added to still
frozen samples on ice and briefly vortexed until mixture was homogenous and centrifuged at
21000 xg and 4°C for 20 min. In separate microcentrifuge tubes 86.6 μl of sodium bicarbonate
solution was aliquoted and 150 μl of the centrifuged 10% TCA supernatant extract was added to
bicarbonate containing tubes on ice. Any pink coloration due anthocyanin content in extracts
should change to a dark blue hue after neutralization. One hundred microliters of the neutralized
supernatants were arranged in 96 well plates on ice, to allow for sample transfer to assay with a
multichannel pipette.
A working solution of catalase was prepared by centrifuging 10 μl of ammonium sulfate
catalase suspension (Sigma, C3515-10MG). The clear ammonium sulfate supernatant was then
removed before catalase pellet was dissolved in 600 μl of ddH2O. Five microliters of catalase
working solution was then added to the remaining neutralized sample extracts in microcentrifuge
tubes. These samples were incubated at room temperature for a minimum of 10 min. One hundred
microliters of the catalase treated supernatants were then stored in the same 96 well plate on ice.
An H2O2 standard curve was prepared by serial dilution of 30% H2O2 to concentrations of
100 µM, 50 µM 25 µM 10 µM and 5 µM which were then diluted 10x (from 50 microliter aliquots)
by sequential addition of 200 μl of 10% TCA, 122 μl of 1M sodium bicarbonate and 128 μl of
ddH2O to mimic extraction procedure. Final concentrations of H2O2 standards therefore ranged
from 10 µM to 0.5 μM. NTCA extraction resulted in no net loss of H2O2. H2O2 standards were
prepared fresh daily.
60
Amplex Ultra Red (AUR) working solution was prepared by dissolving one vial of AUR
in 340 μl of DMSO per manufacturer’s instructions to make a 10 mM AUR stock. AUR assay
solutions were prepared immediately before use. Fifty microliters of AUR stock was added to 10
ml of ddH2O containing 5 μg/ml commercial horseradish peroxidase (AUR-HRP) and to another
10 ml of ddH2O without HRP (AUR-NoHRP). Solutions were kept on ice and protected from light.
All assays were performed in clear 96 well microplates and prepared on a cold block. Twenty five
microliters of neutralized samples and catalase treated samples were always pipetted prior to
addition of 75 μl of the appropriate AUR assay solution by multichannel pipette. The plate was
then briefly incubated (5 min) at room temperature in the dark. Longer incubation periods did not
lead to greater differences between catalase treated samples and untreated samples, only increases
in AUR chemical auto-oxidation. The microplates were read using a SpectramaxM2 (Molecular
Devices) equipped with fluorescence detection capabilities. The excitation wavelength was set to
544 nm, and emission was recorded at 590 nm.
Experiments were performed to test the effectiveness of extraction procedures, dose
response, and catalase treatment (Figure 1.2A,B,C). WT seedlings (~2g) were ground in a mortar
with liquid nitrogen, to a fine powder and separated into triplicate 40, 30, 20, or 10 mg aliquots.
Extraction procedures were performed as described above and assayed with AUR-HRP or AUR-
NoHRP as indicated.
To assay H2O2 accumulation under ER stress conditions WT, rbohd rbohf, ire1a ire1b, and
bzip60 bzip28 were grown for 7 days and transferred to plates containing 1.0 μg/ml Tm or DMSO
for 6, 24, or 48 hr as indicated, and harvested at the same time on consecutive days. Three
biological replicates consisting of approximately 30-60 mg of seedling tissue each were briefly
dried on a Kimwipe and exact fresh weight recorded before samples were placed in 1.7 ml
61
microcentrifuge tubes with two glass beads, and frozen in liquid nitrogen. Samples were ground
to a fine powder in a Retch MM301 (Retch; Haan, Germany) by agitation at a frequency of
30/second (sec) for two sets of 30 sec which were separated by refreezing in liquid nitrogen and
stored in liquid nitrogen. Samples were extracted with NTCA, and then treated with catalase as
indicated. For each biological replicate the neutralized samples and catalase samples were assayed
in two technical replicates in the same plate with a standard curve. Each genotype was assayed in
a separate plate. The catalase labile signal was calculated by subtracting average fluorescence
intensity of catalase treated replicates from the average fluorescence intensity of the neutralized
sample replicates. The samples were compared to the individual H2O2 standard curves to derive
an [H2O2] of the samples, and total micromoles of H2O2 in the extract. This was normalized to
recorded sample fresh weights.
RNA Extraction and Quantitative RT-PCR Analyses
The RNA measurement experiments were performed in parallel with the H2O2
quantification experiments. Seedlings germinated under normal growth conditions and grown for
7 days were transferred to plates containing ½ LS media with 1.0% sucrose and 1.0 μg/ml Tm or
DMSO for 6, 24, or 48 hr as indicated, and harvested at the same time on 2 consecutive days.
Groups of 5-10 seedlings were pooled placed in 1.7 ml microcentrifuge tubes with two glass beads,
and frozen in liquid nitrogen. Total RNA was extracted from whole seedlings using a NucleoSpin
Plant RNA kit (Machery-Nagel) according to the manufacturer’s instructions, including on column
DNase Digestion. All samples within the experiment were reverse-transcribed using iScript
Reverse Transcriptase. RT-PCR with SYBR Green detection using a ΔΔct method was performed
in technical triplicates using the Applied Biosystem 7500 Fast Real-Time 7500 PCR system, and
62
data normalized to the expression of UBQ10 (AT4G05320). The values presented are the mean of
three independent biological replicates ±SE.
Recovery from ER Stress, and Chronic ER Stress Phenotypic Analyses
For the recovery from ER stress experiments WT, rbohd rbohf, and ire1a ire1b were
germinated on ½ LS plates grown vertically for 5 days, transferred to liquid ½ LS media containing
1.0 μg ml-1 Tm for 6 hr, then replated on ½ LS plates and grown vertically for a further 3 days.
The plates were then photographed and the root lengths of at least 30 individuals from 4 separate
plates were determined using ImageJ; the mean ±SE was then calculated. In groups of two shoots
were excised, fresh weight recorded, placed in 1.7 ml microcentrifuge tubes with two glass beads,
and frozen in liquid nitrogen.
For the chronic ER stress experiments WT, rbohd rbohf, ire1a ire1b, and bzip60 bzip28
were germinated on ½ LS plates containing DMSO, 5 ng/ml, 10 ng/ml, or 25 ng/ml Tm and grown
for two weeks then photographed. In groups of five, shoots were excised, fresh weight recorded,
placed in 1.7 ml microcentrifuge tubes with two glass beads, and then frozen in liquid nitrogen.
For both ER stress recovery and chronic stress experiments, total chlorophyll content (chlorophyll
a+ chlorophyll b) per mg fresh weight was determined as described previously (Tait et al. 2003).
Samples were ground to a fine powder in a Retch MM301 (Retch; Haan, Germany) by agitation
at a frequency of 30/sec for two sets of 30 sec which were separated by refreezing in liquid
nitrogen. From the liquid nitrogen 1 ml of DMSO was added to the sample tubes, inverted until
mixed then incubated at room temperature for 20 min in the dark. Samples were then centrifuged
at 21000xg and 200 μl aliquots added to a clear 96 well plate for spectrophotometric quantification
63
of chlorophyll content using a SpectramaxM2 (Molecular Devices). For all experiments at least 10
biological replicates for each experimental group were recorded, presented data represents the
mean ±SE.
Electrolyte Leakage Measurements
WT, rbohd rbohf, ire1a ire1b, and bzip60 bzip28 seedlings were grown for 7 days then
transferred to plates containing 1.0 µg/ml Tm, or DMSO. Seedlings were imaged after six days on
treatment plates. After 48 and 144 hr the extent of cell death was determined by quantification of
percent electrolyte leakage as described previously with minor modifications (Dong et al. 2006,
Lee et al. 2010). Groups of five seedlings were briefly washed in ddH2O, and then incubated in 4
ml of ddH2O for 3 hr in glass culture tubes with gentle agitation. Liquid conductivity was measured
(Measurement 1). The tubes were autoclaved with caps and allowed to cool under gentle agitation
for 3 hr. Total conductivity was measured (measurement 2) and percentage of the total was
calculated as (%=measurement1/measurement2*100).
64
RESULTS
ER Stress Induces Accumulation of Superoxide by NADPH Oxidases
We first aimed to test whether ER stress activates NADPH oxidases by establishing the
levels of O2-, the product of NADPH oxidases, in seedlings subjected to induced ER stress
conditions. To do so, we followed O2- accumulation in situ using nitrotetrazolium blue (NBT), a
chromogenic substrate for oxidases commonly applied to the study of NADPH Oxidase activity in
vivo (Dunand et al. 2007). We analyzed roots of wild type (WT) and a double RBOHD and
RBOHF knockout seedlings (herein dubbed rbohd rbohf (Torres et al. 2002)). RBOHD and
RBOHF belong to a ten-member family of proteins and are mainly expressed in the shoot and
vascular tissue (Morales et al. 2016) After 7 days of growth on solid ½ LS media, the seedlings
were transferred to solid ½ LS media containing the well-established ER stress inducer
tunicamycin (Tm) for 24 or 48 hr to induce the adaptive UPR in a plate system (Iwata et al. 2005,
Liu et al. 2007a, Chen et al. 2013).. We found that at 24 hr, the levels of NBT staining were only
slightly increased, mainly at the root tip, both in Tm-treated WT and rbohd rbohf compared to the
respective DMSO controls (Tm solvent) (Figure 2.1A; root tip indicated with ∆). However, at 48
hr of TM treatment, in WT and in the rbohd rbohf line the levels of NBT staining had dissipated
at the root tip and increased along the maturation zone and mature root tissues (Figure 2.1A; mature
zone and maturation zone indicated with † and ‡, respectively). The NBT staining was higher in
the mature zone of WT roots compared to rbohd rbohf. These observations were validated by
measurements of the relative levels of NBT staining along the root length using ImageJ (Figure
2.1B). These verified differences in NBT staining at the tissue level are consistent with the notion
that RBOHD and RBOHF are expressed largely in shoot tissues and
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Figure 2.1. NADPH oxidase-dependent O2- is generated during ER Stress partially through
RBOHD and RBOHF activity.
In situ detection and semi-quantification of superoxide in root tissues by staining with nitro-
tetrazolium blue (NBT) A) WT or rbohd rbohf seedlings treated with 1.0 μg/ml Tm, 1.0 μg/ml TM
+ 2.5 µM DPI, or DMSO were stained with NBT after 24 or 48 hr. †: mature zone; ‡: maturation
zone; ∆: root tip. B) Tissue-specific differences in superoxide are shown by relative pixel
intensities of NBT stain from the root tip ± SE.
66
mature root tissues but not at the root tip in Arabidopsis (Morales et al. 2016). We next tested
whether the observed NBT staining in rbohd rbohf could be due to other RBOH activity.
Therefore, we supplemented the Tm-treated samples with diphenyleneiodonium (DPI), a broad
spectrum flavoprotein inhibitor that is commonly applied in the study of RBOH proteins
(Ogasawara et al. 2008). We found that DPI-treatment largely ablated the Tm-induced NBT-
staining in WT and rbohd rbohf (Figure 2.1A, B). These results indicate that the remaining Tm-
induced NBT staining found at the root tips may be sourced from the activity of RBOH other
enzymes functioning redundantly to RBOHD and RBOHF (Huang et al. 2016). Together, these
results indicate that RBOHD, RBOHF, and potentially other RBOH enzymes are involved in ER
stress-induced O2- production, which at least for RBOHD and RBOHF is consistent with the
previously described expression pattern at the tissue level.
ER Stress Induces Accumulation of Hydrogen Peroxide Dependent upon RBOHD and RBOHF
Activity and Intact UPR Signaling
Because O2- is converted to H2O2, we next aimed to establish the levels of accumulation of
H2O2 in seedlings undergoing ER stress. To do so, we first set up an assay to measure reliably
H2O2 levels in untreated tissues. We utilized a sensitive enzymatic fluorimetric assay based on the
stoichiometric oxidization of non-fluorescent Amplex Ultra Red (AUR) by H2O2 by exogenous
horseradish peroxidase (HRP) to brightly fluorescent resorufin (Queval et al. 2008, Zhu et al.
2010, Chakraborty et al. 2016). We expected that this assay would lead to the detection of resorufin
fluorescence in the presence of HRP and to reduced levels of resorufin fluorescence in the absence
of this enzyme. We first conducted tissue extraction using potassium phosphate buffer
(Chakraborty et al. 2016, Le et al. 2016), and found no significant differences in oxidization of
67
non-fluorescent AUR by added HRP compared to the control (Figure 2.2A). These results indicate
either that the assay was not sensitive enough or that the AUR oxidation was saturated in the
absence of HRP. To test this, we implemented a 10% trichloroacetic acid extraction (neutralized:
NTCA) to precipitate possibly interfering enzymatic reactions, and then assayed the levels of
H2O2. Consistent with our original hypothesis, we found that, in the presence of HRP, the levels
of resorufin fluorescence were significantly higher than in the absence of the enzyme compared to
the control (Figure 2.2A). As a further control for the validity of our assay, we treated the samples
with catalase, which specifically dismutates H2O2 in the extract and should therefore further lower
the levels of resorufin fluorescence in HRP-treated samples. Conversely, we expected no
differences in catalase treatment of samples extracted in potassium phosphate buffer compared the
untreated control. In samples extracted with NTCA, we found that the levels of resorufin
fluorescence were significantly lower in catalase-treated samples compared untreated samples
(Figure 2.2C). As expected also, the addition of catalase did not alter the levels of fluorescence of
potassium phosphate buffer-extracted samples compared to untreated samples (Figure 2.2B).
These results support that the resorufin fluorescence levels detected in the potassium phosphate
buffer-extracted samples are due to H2O2-independent oxidation of AUR. Importantly, these
results also indicate that we have established a quantitative approach to track specifically H2O2
levels in tissues.
We then used this assay to measure the levels of H2O2 in seedlings experiencing ER stress
during the adaptive phase of the UPR. Using the same plate system detailed earlier (Figure 2.1),
we compared the effects of Tm treatment for 6, 24, and 48 hr against seedlings growing on plates
containing DMSO as control. We tested WT, rbohd rbohf, a mutant lacking the two IRE1 isoforms
(ire1a ire1b; (Chen et al. 2012)) and a double mutant lacking functional bZIP60 and
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Figure 2.2. ER Stress induced H2O2 are controlled by RBOHD and RBOHF as well as intact
UPR signalling.
Development and application of an Amplex Ultra Red protocol for H2O2 quantification from
seedling tissues subjected to ER stress. A) Comparison of H2O2 extraction methods using
potassium phosphate buffer (PHOS) or 10% TCA neutralized with NaHCO3 (NTCA) incubated in
the presence or absence of horseradish peroxidase (HRP). B) Evaluation of tissue loading during
PHOS extraction and catalase treatment. C) Evaluation of tissue loading during NTCA extraction
and catalase treatment. D) WT, rbohd rbohf, ire1a ire1b, and bzip60 bzip28 seedlings were treated
in a plate system with Tm or DMSO for the indicated time and H2O2 quantified; see materials and
methods. Data represent the mean concentration ± SE. E) From the values in (D) average fold
change ± SE (Tm/DMSO) was determined from biological replicates in the order that they were
measured. Statistical significance compared to equivalent WT value, unless a bracket is used to
indicate comparison. Statistical significance determined using Student’s unpaired t-test and
indicated by: *=p<0.05, **=p<0.005 ***=p<0.0005, NS=not significant.
69
bZIP28 transcription factors (bzip60 bzip28; (Deng et al. 2013)). We found differences in H2O2
concentrations among the various backgrounds and their controls (Figure 2.2D), in support of a
significant bearing of RBOHD and RBOHF activity as well as intact UPR on H2O2 production. To
better illustrate such differences we estimated the fold change in concentration between
Tm/DMSO (Figure 2.2E). Specifically, we found that in all backgrounds at 6-hr of treatment there
were no differences in fold change of H2O2 concentrations (TM/DMSO; Figure 2.2E). At 24 hr,
we established that Tm-treatment led to a small but significant increase in H2O2 levels in the ire1a
ire1b mutant background only. However, at 48 hr, coincident with significant increases in O2- in
mature WT tissues (Figure 2.1B), we found a significant increase in H2O2 levels in WT that were
not observed in the rbohd rbohf mutant (Figure 2.2E), indicating that RBOHD and RBOHF are
required for the accumulation of H2O2 under ER stress conditions. Noticeably, the increase of H2O2
verified in WT but not rbohd rbohf was significantly greater in ire1a ire1b and bzip60 bzip28
mutants (Figure 2.2E), supporting a requirement of an intact UPR signaling for the management
of H2O2 levels in conditions of ER stress. Together, these results indicate that H2O2 accumulates
in response to ER stress in the adaptive phase of the UPR dependent on RBOHD and RBOHF
activity and also influenced by the integrity of UPR signaling.
UPR Regulators Influence RBOHD and RBOHF Expression During Adaptive UPR
Having established that RBOHD and RBOHF activity is required for ER stress-induced
O2- and H2O2 production (Figures 2.1, 2.2), we next aimed to determine if the canonical UPR arms
affected RBOHD or RBOHF expression at the transcriptional level. Therefore, we tested whether
ER stress modulated RBOHF or RBOHD transcript levels as it occurs for other ER stress
responsive genes, such as bZIP60, BiP3, ERdj3A and ERdj3B (Chen et al. 2012, Ruberti et al.
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2018). To do so, a subset of seedlings from the H2O2 quantification experiments (Figure 2.2) were
used to follow the changes in gene transcript levels by quantitative RT-PCR (qRT-PCR) during
Tm treatment in the plate system (Iwata et al. 2005, Liu et al. 2007a, Chen et al. 2013). We found
no changes in the RBOHF transcript levels in the WT, ire1a ire1b, or bzip60 bzip28 lines at 6 hr
of treatment. However, at 24 and 48 hr of TM treatment, the bzip60 bzip28 line had slightly lower
levels of the RBOHF transcripts compared to WT (Figure 2.3A). Conversely, in the WT and ire1a
ire1b, the RBOHD transcripts were transiently induced at 24 hr and then restored to basal levels at
48 hr. We also observed that the RBOHD induction was significantly higher in ire1a ire1b
compared to WT (Figure 2.3B). The RBOHD transcript levels in the bzip60 bzip28 line we found
to be slightly repressed at 6 hr of treatment (with a TM/DMSO ratio of ~0.8; Figure 2.3B).
Noticeably, however, at 24 hr in the bzip60 bzip28 line the RBOHD transcript levels were
significantly lower compared to WT and ire1a ire1b. Together these results demonstrate that
although the integrity of UPR signaling is required for maintaining homeostatic levels of RBOH
expression during ER stress, the timing of the observed changes does not directly correlate with
RBOHD and RBOHF dependent O2- (Figure 2.1) or H2O2 production (Figure 2.2) in WT plants.
This indicates that other factors, such as post translational modifications, protein-protein
interactions, or altered endomembrane trafficking of the protein product may contribute to these
outcomes.
To provide further evidence that the observed increases in O2- (Figure 2.1) are dependent
upon RBOHD and RBOHF activity during ER stress, we quantified the expression of ZAT12, an
O2- responsive marker gene (Miller et al. 2009, Xu et al. 2017). Consistent with transiently
increased levels of NBT staining at 24 hr in the root tip, which was largely independent of
RBOHD and RBOHF activity (Figure 1A), we found a 6-fold upregulation in ZAT12 levels in the
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Figure 2.3. Intact UPR signaling is required to maintain homeostasis of RBOH transcript
levels and ROS signaling, while RBOH activity affects UPR homeostasis.
Time course gene expression analysis of WT, rbohd rbohf, ire1a ire1b, and bzip60 bzip28
seedlings subjected to ER stress. qRT-PCR analyses were performed using primers specific for
either A) RBOHF , B) RBOHD , C) ZAT12 , D) spliced bZIP60 (sbZIP60), E) BIP3, or F) ERdj3B
. Data represent the mean ratio ± SE (biological replicates=3); Statistical significance compared to
equivalent WT value, unless a bracket is used to indicate comparison. Statistical significance
determined using Student’s unpaired t-test and indicated by: *=p<0.05, **=p<0.005 ***=p<0.005,
NS=not significant.
72
WT and WT and rbohd rbohf lines (Figure 2.3C). Significantly at 48 hr, where we observed an
increase in NBT staining of mature root tissues and upregulated H2O2 levels in WT but not rbohd
rbohf seedlings (Figures 2.1, 2.2), we also found that rbohd rbohf seedlings had significantly lower
levels of ZAT12 transcript (Figure 2.3C). These results demonstrate that 48 hr of ER stress induces
O2- accumulation via RBOHD and RBOHF (Figure 2.1) to a level that elicits a transcriptional
response.
We next aimed to test whether UPR regulation of RBOHD and RBOHF transcripts or H2O2
levels (Figures 2.2, 2.3A, 2.3B) was correlated with changes in superoxide-dependent signaling.
We found that at 6 hr of Tm treatment in ire1a ire1b the levels of ZAT12 were significantly higher
compared to WT. At 24 hr of treatment, ZAT12 levels in bzip60 bzip28 and ire1a ire1b mutants
were slightly lower and higher than WT levels, respectively. Conversely, at 48 hr of treatment
ZAT12 levels in bzip60 bzip28 and ire1a ire1b mutants were higher and lower than WT levels,
respectively (Figure 2.3C). Although the increased ZAT12 levels in the ire1a ire1b mutant are
consistent with the verified increase in transcription of RBOHD and H2O2 accumulation at 24 hr,
the regulation of ZAT12 in both UPR mutant lines does not correlate with the RBOH transcription,
or H2O2 accumulation at 48 hr. We therefore propose that an impaired UPR response likely has
pleiotropic effects in the regulation of superoxide production, superoxide signaling, and H2O2
accumulation during adaptation to ER stress.
We next tested whether impaired RBOHD and RBOHF activity affected the canonical UPR
at a transcriptional level. We tested the levels of ER stress-responsive genes such as spliced bZIP60
transcripts (sbZIP60) and BIP3, whose abundance is primarily regulated by IRE1-bZIP60, as well
as ERDJ3B, whose expression is primarily regulated by bZIP28 (Ruberti et al., 2018). In WT, we
found that the Tm treatment led to increased levels of sbZIP60 transcripts at 6 hr, which were
73
attenuated at 24 and 48 hr (Figure 2.3D). Compared to WT, in the rbohd robhf line, we observed
no significant changes in the induction of sbZIP60 levels at 6 hr but a significant ~2 fold reduction
of sbZIP60 levels at 48 hr (Figure 2.3D). An altered UPR signaling in rbohd rbohf was reflected
in our analyses of BIP3 transcript levels, which were ~2-fold higher at 6 hr of treatment and ~4
fold lower at 48 hr in the rbohd rbohf line compared to WT (Figure 2.3E). Conversely, ERdj3B
was found to be ~1.2-fold lower at 6 hr in the rbohd rbohf line compared to WT, but was otherwise
insignificantly different. Taken together, these results indicate that RBOHD and RBOHF
contribute to maintain UPR signaling homeostasis during ER stress.
RBOHD and RBOHF are Necessary for Recovery from Short-Term and Chronic ER Stress
We next aimed to test whether RBOHD and RBOHF could contribute to ER stress
resolution in situations subsequent to the adaptive phase. In this context, progression of the plant
UPR has been studied in conditions of relief from ER stress (temporary ER stress; (Ruberti et al.
2018)) and in conditions of unresolved ER stress (chronic ER stress; (Chen et al. 2013)). Therefore,
we first tested the role of RBOHD and RBOHF in recovery from temporary ER stress. In this
assay, 7-day old-seedlings are transferred to liquid media containing Tm for 6 hr, and then re-
plated on growth medium without Tm. After 3 further days of growth, shoot fresh weight, root
length and chlorophyll content are assayed to assess the ability of the various genetic backgrounds
to overcome ER stress upon relief from an ER stress inducer. For the assay, we used WT, rbohd
rbohf and ire1a ire1b. Consistent with previous findings (Ruberti et al. 2018), at the completion
of the recovery phase, we found that the shoots of the ire1a ire1b mutant weighed significantly
less than DMSO-treated controls and lost most of their chlorophyll; the root also ceased further
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growth (Figure 2.4A-D). We also found that although the shoots of the Tm-treated rbohd rbohf
plants weighed similarly to the Tm-treated WT (Figure 2.4B), a significant reduction of
chlorophyll content was evident (Figure 2.4C). The roots of Tm-treated rbohd rbohf also showed
an overall reduction in length compared to WT (Figure 2.4D). These results indicate that RBOHD
and RBOHF are necessary to successfully overcome temporary ER stress.
We then tested the requirement of RBOHD and RBOHF for overcoming chronic ER stress.
To do so, we followed the customary approach to germinate seeds on growth medium containing
Tm for comparison with seedlings germinated on control plates (Chen et al. 2012). As positive
controls, we again used ire1a ire1b as well as bzip60 bzip28, which are hypersensitive to chronic
ER stress (Liu et al. 2007a, Chen et al. 2012). After 14 days of growth, we examined shoot fresh
weight and chlorophyll content (Figure 2.5A-C). Consistent with previous findings (Chen et al.
2012, Ruberti et al. 2018), the ire1a ire1b and bzip60 bzip28 mutants showed a strong phenotype
with marked reduction in shoot fresh weight and loss of chlorophyll content. When we analyzed
rbohd rbohf, we found a significant reduction in the average shoot fresh weight and chlorophyll
content compared to WT. These results indicate that, similar to temporary ER stress recovery,
RBOHD and RBOHF are required to successfully overcome chronic ER stress.
RBOHD and RBOHF Contribute to Preventing ER Stress Induced Cell Death
Previous reports have detailed the protective role that RBOHD and RBOHF play in
preventing the spread of cell death during plant immune system response through yet undetermined
mechanisms (Torres et al. 2005). Having established that RBOHD and RBOHF are required for
successful recovery from temporary ER stress and survival from chronic ER stress, we postulated
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Figure 2.4. RBOHD and RBOHF are required in the recovery from temporary ER stress.
Phenotypic analyses of the various genetic backgrounds subjected to temporary ER stress. A).
WT, rbohd rbohf, and ire1a ire1b seedlings were subjected to ER stress and were imaged after a
3 day recovery. From the seedlings grown in (A) shoot fresh weight (B), average total
chlorophyll (C), and root length (D), were recorded as described in the materials and methods.
Data represent the mean ± SE. (at least 10 biological replicates). Letters above each data point
indicate statistically significant groups using Student’s unpaired t-test (p<0.05).
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Figure 2.5. RBOHD and RBOHF are required for adaptation to chronic ER stress.
Phenotypic analysis of different seedling genetic backgrounds subjected to chronic ER stress. A)
WT, rbohd rbohf, ire1a ire1b, and bzip60 bzip28 were germinated on media containing the
indicated concentration of Tm or DMSO grown for two weeks. B) Shoots fresh weight, and C)
total chlorophyll content were measured. Data represent the mean ± SE (at least 10 biological
replicates). Letters above each data point indicate statistically significant groups using Student’s
unpaired t-test (p<0.05).
77
that these enzymes could be involved in mechanisms preventing cell death caused by ER stress.
To test this hypothesis, we followed cell death by quantification of electrolyte leakage (Lee
et al. 2010) in WT, rbohd rbohf, ire1a ire1b, and bzip60 bzip28 seedlings exposed to Tm for 2 and
6 days (Figure 2.6A, B). We found that although the shoot and root of Tm-treated WT seedlings
grew considerably less compared to DMSO control, no significant differences were detected in
electrolyte leakage levels (Figure 2.6B). As expected, the bzip60 bzip28 and ire1a ire1b mutants
showed considerable chlorophyll loss with electrolyte leakage reaching almost 50% at 6 days of
Tm treatment. We found that rbohd rbohf plants also showed a significant chlorophyll loss and
electrolyte leakage by 6 days of Tm-treatment (Figure 2.6B) compared to WT plants. These results
indicate that RBOHD and RBOHF contribute in preventing cell death in ER stress conditions.
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Figure 2.6. RBOHD and RBOHF act to prevent ER stress induced cell death.
Determining the extent of cell death in seedlings of different genetic background subjected to
prolonged ER stress. A) WT, rbohd rbohf, ire1a ire1b, and bzip60 bzip28 seedlings treated with
Tm in a plate system for 48 and 144 hr, and then photographed at 144 hr. B) The extent of cell
death was determined by quantification of percent electrolyte leakage. Data represent the mean ±
SE (4 biological replicates). Letters above each data point indicate statistically significant groups
using Student’s unpaired t-test (p<0.05).
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DISCUSSION
In plants, the identity of several critical sensors and transducers of ER stress has been
unraveled (Angelos et al. 2017), and the challenge ahead is to discover additional factors that
participate in the UPR management. In this work, we have established that two NADPH oxidases
are necessary to overcome specific situations of ER stress, such as recovery from ER stress
conditions and unresolved ER stress. These results enrich the general knowledge of the identity of
the proteins and signaling pathways that contribute to ER stress survival in plants. The ability of
mammalian cells to overcome ER stress is negatively influenced by NADPH Oxidases-produced
ROS (Li et al. 2010). In plants, the relationship between ROS and the UPR was unknown. In this
work, we showed that, in conditions of an intact UPR signaling, NADPH Oxidases-produced ROS
exert a positive role on the ability of the plant to overcome ER stress. These findings support the
conclusion that, despite the functional conservation of canonical ER stress sensors and transducers
such as IRE1 and bZIP-transcription factors, plants have evolved unique strategies for ER stress
survival.
NADPH Oxidases Contribute to ROS Production in Conditions of ER Stress
Several metabolic and signaling processes affect cellular concentrations of H2O2 in plants,
including biotic and abiotic stress responses (Miller et al. 2009), nutrient availability (Contento et
al. 2010), circadian rhythms (Zhong et al. 1994), and gravity (Hausmann et al. 2014). In
Arabidopsis there are also studies indicating that ER stress affects cellular concentrations of H2O2,
through both direct measurements (Ozgur et al. 2014, Ozgur et al. 2018) and analyses of redox-
related biochemical activities that are intimately linked with cellular H2O2 levels (Ozgur et al.
80
2014). However, prior to our work the nature of the enzymes contributing to H2O2 levels in
conditions of ER stress had yet to be clearly established in plants. In this work, we have set up a
sensitive assay to measure H2O2 levels (Figure 2.2). Using this assay, superoxide staining and a
genetic background lacking RBOHD and RBOHF, we showed that ER stress causes activation of
NADPH Oxidase-coupled superoxide production, leading to the accumulation of H2O2 (Figures
2.1, 2.2). We further show that a superoxide-responsive signaling pathway (Xu et al. 2017) is also
activated, as demonstrated by transcriptional induction of the marker gene ZAT12 (Figure 2.3C).
The concomitant reduction of three different ROS reporters in the rbohd rbohf line compared to
WT under conditions of ER stress (Figures 2.1, 2.2, 2.3; 48 hr) supports that the elevation of H2O2
in conditions of stress is contributed partially by RBOHD and RBOHF. Therefore, these findings
identify two of the enzymes that operate in ROS management during ER stress potentially sharing
redundant functions with other RBOH-enzymes.
Although, the exact molecular mechanisms leading to activation of these enzymes in
response to ER stress have yet to be elucidated, a regulation of RBOH enzymes by altered cytosolic
calcium levels and association with G-protein signaling components may be postulated as
contributing factors. In metazoans cellular calcium ion homeostasis is intimately linked with ER
stress, as calcium is required for the proper functioning of ER luminal foldase activities (Krebs et
al. 2015). Inhibition of sarcoplasmic/endoplasmic reticulum calcium ATPase (SERCA)
transporters leads to the induction of ER stress and the UPR (Krebs et al. 2015). Upon prolonged
UPR activation, a number of factors, including ER lumen hyper-oxidation by ER oxidase 1a
(ERO1a), leads to calcium release from the ER through activation of inositol triphosphate
receptors (IP3R) and apoptotic events (Sovolyova et al. 2014). Although IP3R-like ER calcium
channels have yet to be identified in plants, SERCA-like transporters have been identified (Liang
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et al. 1997). Therefore it is possible that ER stress/UPR induction could alter ER and cytosolic
calcium levels, which can promote RBOHD activation (Ogasawara et al. 2008). Furthermore, in
plant responses to bacterial pathogen attack, it has also been demonstrated that a null mutation in
the Arabidopsis Gβ subunit (agb1) of the heterotrimeric G-protein plasma membrane signaling
complex was epistatic to the rbohd rbohf null mutation(Torres et al. 2013). The AGB1 gene acts
in concert with receptor-like kinases to mediate oxidative burst response to pathogen-associated
molecular pattern (PAMP) triggered immunity(Liu et al. 2013, Liu et al. 2016b). Although it is
yet to be tested whether AGB1 interacts genetically with RBOHD and RBOHF in ER stress,
similar to rbohd rbohf, agb1 is sensitive to chronic ER stress (Chen et al. 2012). It is therefore
possible that AGB1 may contribute to RBOH signaling in conditions of ER stress.
Unlike in Metazoans, NADPH Oxidase-Produced ROS are Beneficial to Overcome ER Stress in
Plants
Many aspects of the UPR regulators are conserved between plants and metazoans at a
functional level even when compared to yeast wherein only IRE1 arm of the UPR is genetically
encoded (Ron et al. 2007, Ruberti et al. 2015, Liu et al. 2016a). However, it is increasingly obvious
that the different evolutionary contexts between plants and animals have forced the development
of different survival strategies in overcoming ER stress. The lack of a plant homolog of the
mammalian PERK UPR pathway is evidence to that effect. NADPH Oxidases are largely
conserved between mammals and plants (Suzuki et al. 2011). However, the activities of
mammalian NADPH Oxidase 2 (Nox2) and NADPH Oxidase 4 (Nox4), two homologs of RBOHD
and RBOHF, promote apoptosis during ER stress (Pedruzzi et al. 2004, Li et al. 2010).
Specifically, an intravenous tunicamycin challenge in Nox2-/- mice resulted in a dramatic
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reduction of renal cell apoptosis and increased protection against renal dysfunction when
compared to WT mice (Li et al. 2010). In this work, we show that rbohd rbohf plants display a
significant sensitivity to ER stress conditions (Figures 2.4, 2.5, 2.6). Specifically, in the recovery
from acute Tm treatment, in rbohd rbohf, the resumption of plant growth is markedly delayed, and
under chronic stress conditions (Figures 2.5, 2.6), rbohd rbohf plants exhibit enhanced progression
of cell death (Figure 2.6). Therefore, differently from the mammalian system, during ER stress
NADPH Oxidases RBOHD and RBOHF exert a pro-survival role in the ER stress response. As
such, the results presented in this study identify RBOHD and RBOHF as important positive
contributors to UPR adaptation in plants in a manner that runs differently from the mammalian
cell system.
Homeostasis of NADPH Oxidase Activity is Required to Maintain an Effective UPR
Several studies, including studies of RBOH activity during heat stress response in plants,
support a non-specific “transcriptional priming” by which fast acting ROS production by RBOHD
amplifies initial stress-specific transcriptional responses in local and systemic tissues (Mittler et
al. 2015). In our analyses, we established that the RBOHD and RBOHF are involved in the
adaptive phase of the UPR (Figure 2.3D-F) as well as in recovery from temporary ER stress and
in situations of chronic ER stress (Figures 2.4, 2.5). Consistent with a priming role of RBOH
activity in stress responses, the verified misregulation of the adaptive phase of the UPR due to a
compromised RBOH activity may lead to a defective actuation of proper cytoprotective responses
necessary for surviving temporary and chronic ER stress. Interestingly, when compared to ERdj3B
levels, we verified a stronger impact on the induction levels of sbZIP60 and BIP3 in rbohd rbohf
compared to WT (Figure 2.3D-E). Based on the findings that BIP3 expression is principally
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controlled by the IRE1-bZIP60 arm and that the ERdj3B is principally controlled by bZIP28 arm,
we propose that the activity of RBOHD and RBOHF positively influences the transcriptional role
of bZIP60. This hypothesis does not exclude that other RBOH enzymes may affect the
transcriptional role of bZIP60 as well as bZIP28. Indeed, in our work, while we demonstrate that
RBOHD and RBOHF activity is required for successfully overcoming these specific conditions of
ER stress, the activity of these enzymes is not strictly essential. This is supported by the relative
survival of rbohd rbohf compared to ire1a ire1b and bzip60 bzip28 in temporary and chronic ER
stress conditions (Figures 2.4, 2.5, 2.6). Given the relatively large size of RBOH family and the
residual NADPH Oxidase marker activity observed in the rbohd rbohf line (Figure 2.1), it is
possible that RBOHD and RBOHF share redundant activity with other RBOH enzymes in
temporary and chronic ER stress conditions.
In ER Stress Conditions, the Production of ROS is Antagonized by IRE1 and the bZIP60/bZIP28
Transcription Factors
The plant IRE1 as well as the availability of bZIP28 and bZIP60 together are strictly
necessary to overcome temporary and prolonged stress, as demonstrated by the evidence that death
is accelerated in the ire1a ire1b and bzip60 bzip28 mutants compared to WT in situations of
recovery from temporary ER stress or in conditions of chronic ER stress ((Nagashima et al. 2011,
Chen et al. 2012, Deng et al. 2013, Liu et al. 2016a); Figures 2.4, 2.5). An analysis of ER stress
response in Chlamydomonas reinhardtii reported a significant transcriptional induction of ROS-
dependent marker genes in IRE1 knockouts (Yamaoka et al. 2018). These findings led to the
hypothesis that an increase in ROS may contribute to the ER stress sensitivity of ire1 knockout
lines in this model system (Yamaoka et al. 2018). Our results that in the Arabidopsis ire1a ire1b
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line, which is hypersensitive to ER stress (Figures 2.4-2.6; Chen et al. 2012), the H2O2 levels are
higher at 24 and 48 hr of Tm treatment compared to WT (Figure 2.2E) corroborate this hypothesis.
Our results also provide direct evidence in support of the hypothesis that UPR regulators are
required to manage cellular H2O2 concentrations under ER stress conditions in plants like they do
in metazoans (Hourihan et al. 2016). However, the verified increases in H2O2 content in the ire1a
ire1b and bzip60 bzip28 mutants were not directly correlated with the observed misregulation of
ZAT12/RBOHD transcript levels in these lines compared to WT, which may indicate that an intact
UPR signaling potentially coordinates ROS production/signaling through multiple mechanisms to
promote proper ER stress management. Conversely, the verified differences in transcript induction
of UPR marker genes (i.e., sbZIP60, BIP3 and ERdj3B) in rbohd rbohf compared to WT (Figure
2.3D-E) indicate that RBOH activity is required to maintain proper UPR signaling. How the
observed increase in H2O2 levels may affect the UPR is yet undetermined at a mechanistic level.
Recent findings have shown that ER stress alters the cytosolic redox potential, which in turn
modulates the activity of the transcriptional coregulatory NPR1 (nonexpressor of PR genes), which
binds and represses the transcriptional function of bZIP28 and bZIP60 (Lai et al. 2018). It is
similarly possible that an excessive elevation of H2O2 in conditions of ER stress changes the
activity of UPR and programmed cell death modulators. The ROS species produced by RBOHD
and RBOHF suppress the spread of runaway cell death in a pathway parallel to the Lesion
Stimulating Disease 1 (LSD1) zinc-finger protein under normal growth conditions, in response to
salicylic acid, extracellular superoxide, and pathogen induced hypersensitive response (Torres et
al. 2005). The results of our study indicate that RBOHD and RBOHF may also prevent the
propagation of cell death in response to chronic ER stress (Figure 2.6). Under this light, the noted
misregulation of RBOH activity and accumulation of H2O2 in ire1a ire1b and bzip60 bzip28
85
mutants during ER stress (Figures 2.2E, 2.3C) may represent convergent signals that initiate
processes leading toward programmed cell death, and could at least partially explain the
hypersensitivity of these lines to ER stress conditions (Figure 2.4-2.6) (Chen et al. 2012, Deng et
al. 2013). Therefore, together our results support the hypothesis for a dual role of H2O2 in ER
stress-induced programmed cell death, which is differently manifested in WT and mutants of the
UPR signaling pathway. Specifically, in cells with an intact UPR, RBOH activity and H2O2 levels
are maintained to levels that promote survival; however, a defective UPR likely causes
misregulation of RBOH activity and excess H2O2 accumulation that may lead to cell death. The
latter scenario may be beneficial for plants to favor the survival only of cells with an intact ability
to overcome proteotoxic stress.
86
ACKNOWLEDGEMENTS
We acknowledge support by the Chemical Sciences, Geosciences and Biosciences
Division, Office of Basic Energy Sciences, Office of Science, U.S. Department of Energy (award
number DE-FG02-91ER20021) for infrastructure, NASA (award NNX12AN71G), NIH R01-
GM101038, and a fellowship from Michigan State University under the Training Program in Plant
Biotechnology for Health and Sustainability (T32-GM110523).
87
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94
CHAPTER III
RELEVANCE OF THE UNFOLDED PROTEIN RESPONSE TO SPACEFLIGHT-
INDUCED TRANSCRIPTIONAL REPROGRAMMING IN ARABIDOPSIS
The work presented in this chapter has been published in Astrobiology:
Angelos E., Ko D.K, Zemelis-Durfee S and Brandizzi F. (2021) Relevance of the Unfolded
Protein Response to Spaceflight-Induced Transcriptional Reprogramming in Arabidopsis.
Astrobiology. 21(3):367-380.
95
ABSTRACT
Plants are primary producers of food and oxygen on Earth and will likewise be
indispensable to the establishment of large-scale sustainable ecosystems and human survival in
space. To contribute to the understanding of how plants respond to spaceflight stress, we
examined the significance of the unfolded protein response (UPR), a conserved signaling
cascade that responds to a number of unfavorable environmental stresses, in the model plant
Arabidopsis thaliana. To do so, we performed a large-scale comparative transcriptome profiling
in wild type (WT) and various UPR-defective mutants during the SpaceX-CRS12 mission to the
International Space Station. We established that orbital culture substantially alters the expression
of hundreds of stress-related genes compared to ground control conditions. Although expression
of those genes varied in the UPR mutants on the ground, it was largely similar across the
genotypes in the spaceflight condition. Our results have yielded new information on how plants
respond to growth in orbit and support the hypothesis that spaceflight induces the activation of
signaling pathways that compensate for the loss of UPR regulators in the control of downstream
transcriptional regulatory networks.
96
INTRODUCTION
Extraterrestrial habitation and prolonged space travel require successful plant growth to
recreate livable environments for humans (Ferl et al. 2002; Massa et al. 2016; Zhou et al. 2019).
Studies over the past 70 years have sought to develop a better understanding of how plants are
affected by and adapt to the significant stresses imposed by spaceflight (e.g., microgravity,
radiation, vibration, limited exchange of gases), which can affect plant development and yield
(Paul et al. 2013). Recent iterations of the sophisticated chamber hardware for plant growth housed
on the International Space Station (ISS) have allowed for multigenerational plant growth in space
and analyses of plant responses to this environment (Massa et al. 2016). However, these facilities
are insufficient for large-scale plant growth on extraterrestrial environments due to their size and
resource cost. Therefore, generation of germplasm adapted to stresses experienced during growth
in extraterrestrial environments is a critical contribution to the realization of sustainable plant
cultivation in space.
The UPR is a signaling cascade that responds to a number of unfavorable environmental
and cellular stresses. The UPR is generally activated by a buildup of unfolded proteins in the
endoplasmic reticulum (ER), a condition known as ER stress (Ron and Walter 2007). The ER
stress sensors conserved across metazoans and plants include the ER-associated protein kinase and
ribonuclease inositol requiring enzyme 1 (IRE1) and ER membrane-tethered transcription factors
(TFs) (metazoan Activating Transcription Factor 6 (ATF6) and plant basic Leucine Zipper 17
(bZIP17) and bZIP28). Activation of IRE1 leads to unconventional splicing of an intron from the
mRNA of an IRE1-downstream bZIP-TF (metazoan X-box binding protein 1 (XBP1) and plant
bZIP60). The UPR TFs are translocated to the nucleus to control expression of UPR target genes
97
and restore ER homeostasis (Chen and Brandizzi 2012; Halbleib et al. 2017; Kim et al. 2018;
Koizumi et al. 2001; Mishiba et al. 2019; Pastor-Cantizano et al. 2019; Pu et al. 2019; Ruberti et
al. 2018; Tam et al. 2018). Insufficient UPR leads to the actuation of cell death (Ron and Walter
2007; Walter and Ron 2011).
In terrestrially grown plants, the UPR is a key mediator of responses to a variety of stresses
including heat, pathogen, and high light / singlet oxygen (Beaugelin et al. 2020; Deng et al. 2011;
Guillemette et al. 2014; Moreno et al. 2012; Pastor-Cantizano et al. 2019; Zhang et al. 2015;
Zhang et al. 2017). Additionally, analyses of higher order UPR mutants have demonstrated that
the UPR regulators are necessary for post embryonic growth and reproductive development in
Arabidopsis under unstressed conditions as well (Chen and Brandizzi 2012; Kim et al. 2018;
Mishiba et al. 2019; Pu et al. 2019). Therefore, a better understanding of the UPR can enable
efforts to potentiate plant stress responses and improve plant yield.
Given the broad responsiveness of the UPR to environmental stresses, we hypothesized
that the UPR effectors could coordinate gene expression reprogramming in spaceflight stress
conditions. To test this hypothesis, we analyzed global gene expression changes in WT
Arabidopsis as well as loss-of-function mutants of IRE1 (ire1a ire1b, herein dubbed ire1), bZIP28
and bZIP60 (single and double mutants: bzip28, bzip60, bzip28 bzip60), cultivated in orbit during
the SpaceX-CRS12 mission to the ISS. We used these genetic backgrounds to identify genes
controlled jointly or specifically by the UPR sensors and UPR TFs and define the extent to which
the known signaling pathways of the UPR functionally interact in a whole organism under
microgravity-associated conditions. We established that, in space and on ground, gene expression
undergoes a substantial reprogramming on a genome-scale. Growth in orbit substantially altered
the expression of thousands of genes associated with significant biological traits compared to
98
ground controls. However, while many of these spaceflight-responsive genes were regulated
uniquely in certain UPR mutants compared to WT in the ground control, such a genotype-specific
regulation was not observed in the spaceflight condition. These observations not only provide new
insight into how plants respond to spaceflight, they also establish that spaceflight induced-
transcriptional responses mitigate the need for the gene-regulatory networks controlled by the UPR
sensors.
99
MATERIALS AND METHODS
Launch Hardware and Experimental Timeline
This flight experiment utilized 4 Biological Research In a Canister (BRIC) containing a
total of 22 Petri Dish Fixation Unit (PDFU) hardware (Wells et al. 2001) to cultivate sterile dark
grown seedlings germinated aboard the International Space Station (ISS) for a 14 day period.
PDFU actuation chambers were loaded with a tissue fixative (RNAlater; Invitrogen) to preserve
samples at the conclusion of the flight experiment. An identical set of samples was prepared and
grown on earth with a two-day offset at Kennedy Space Center (KSC) ISS Environmental
Simulator (ISSES) to allow for data transmission and reproduction of incubation conditions
experienced by flight samples in orbit. HOBO data loggers equipped with temperature sensors
were integrated into two of the four BRICs to record temperatures experienced by samples during
the experiment for post-hoc analysis. Launch samples (i.e., Arabidopsis seeds) were integrated
into BRIC flight hardware in a sterile hood approximately 48 hr before the August 14th, 2017
launch of SpaceX-CRS12 spacecraft. Integrated science/hardware was kept at 4 °C to maintain
seed dormancy prior to packing in cold storage bags while being loaded onto Dragon capsule and
during launch. After docking, samples were removed from cold storage bags by ISS astronauts,
warmed to ambient ISS temperature, allowing seed germination and experiment initiation in the
BRIC. After 14 days, ISS astronauts actuated PDFUs, which were then incubated at room
temperature for a further 3 hr before being transferred to the ISS -80 MELFI freezer. Samples were
kept at approximately -80 °C until BRICs were conditioned to -32 °C in double cold bag storage
(Hutchison and Campana 2009), and stowed in the Dragon capsule before undocking and
100
atmospheric reentry on September 16th. After returning to KSC, samples were stored at -80 °C
until de-integration of the flight and ground samples. De-integration occurred on November 1st,
2017.
Germplasm and Culture Conditions
Arabidopsis thaliana seeds of the following genotypes were used for flight and grounds
controls: WT (Col-0 ecotype), atire1 (Chen and Brandizzi 2012; Nagashima et al. 2011), bzip60
(Moreno et al. 2012), bzip28 (Gao et al. 2008), and bzip28 bzip60 (Deng et al. 2013). Petri dishes
(60 mm) were prepared with 6.7 ml of sterile ½ Murashige and Skoog (MS) media supplemented
with Gamborg’s B5 Vitamins (PhytoTechnology Laboratories), 0.5% sucrose (Sigma-Aldrich),
0.4% Phytagel (Sigma-Aldrich), pH adjusted to 5.7. In a sterile hood, seeds of WT and UPR
mutant genotypes were surface sterilized with one wash of 70% ethanol, one wash of 50% bleach
containing 0.5% Tween 20, and then nine additional washes with sterile H2O distilled twice. After
the final wash was removed, seeds were resuspended in 1.5 ml sterile water for wet plating using
a 1 mL pipette equipped with sterile filter-tip. For each experimental unit (flight and ground
control), five plate replicates of WT and bzip28/bzip60 genotypes and four plate replicates of
atire1, bzip28, bzip60 genotypes were prepared. Each plate replicate contained 70-80 seeds evenly
spaced in a grid pattern on the plate surface. The Petri dishes were sealed with Parafilm (Heathrow
Scientific) and individual plates were then wrapped twice with sterile aluminum foil. Individually
wrapped plates were grouped by BRIC configuration and wrapped together with two more layers
of sterile aluminum foil prior to sample removal from the sterile hood. Plates were placed at 4 °C
until the integration of samples into science hardware the following morning.
101
Sample Processing and Experimental Material Assessment
Flight and ground control experiments samples were preserved in RNAlater in situ, and
kept at -80 °C (see results section for experimental timeline). The Petri dishes were removed from
packaging and thawed in groups of three to prevent excess exposure to room temperature during
sample collection. After removing most of the RNAlater from the plates, sterile forceps were used
to transfer seedlings from the plates to microcentrifuge tubes containing two glass beads. Seedlings
were then frozen in liquid nitrogen. This procedure was done quickly to maximize RNA recovery.
Accordingly, only some pictures were taken of plates before extraction for example purposes. Most
pictures were taken after the bulk of the sample was removed, with the remaining seedlings also
imaged for post-hoc inspection. All plates were free from any visible evidence of bacterial or
fungal contamination. Frozen samples were ground to a powder using a Retch Mixer Mill (Retch;
Haan, Germany). RNA was extracted from tissues using a NucleoSpin RNA Plant Kit (Machery-
Nagel) according to the manufacturer’s instructions including DNase Digestion. The overall
quality and RNA Integrity Number (RIN) of RNA samples were assessed using Agilent
Bioanalyzer 2100 (Agilent, Santa Clara, CA USA).
Library Preparation, Sequencing and Bioinformatics Analysis
RNA-seq libraries were constructed using the Illumina TruSeq Stranded mRNA Library
(Illumina, San Diego, CA, USA) and sequenced in single-end mode on the Illumina HiSeq 4000
platform (50-nt) at Research Technology Support Facility Genomics Core at Michigan State
University (RTSF-MSU). For each library, read quality was assessed using the FastQC (version
0.11.3) software (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Reads were
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cleaned for quality and adapter sequences with Cutadapt (version1.8.1) using a minimum base
quality 20 retaining reads with a minimum length of 30 nucleotides after trimming (Martin 2011).
Quality-filtered reads were aligned to the Col-0 reference genome (TAIR10) using Bowtie (version
2.3.1) and TopHat (version 2.1.1) with a 10 bp minimum intron length and 15,000 bp maximum
intron length (Kim et al. 2013; Langmead and Salzberg 2012). Fragments per kilobase exon model
per million mapped reads (FPKM) were measured using TAIR10 gene model annotation with
Cufflinks (version 1.3.0) (Trapnell et al. 2010). The log2 transformed and normalized gene
expression levels [FPKM + 1] were used for correlation analysis (Spearman’s rank correlation
coefficient) between biological replicates and principal component analysis (PCA). Per-gene read
counts were identified using HTSeq (version 0.6.1p1) in the union mode with a minimum mapping
quality of 20 with stranded reverse counting (Anders et al. 2015). Differential gene expression
analysis was performed in four biological replicates (for WT and bzip28 bzip60, selected based on
the correlation with other biological replicates) using DESeq2 (version 1.16.1) within R (version
3.4.0) based on a comparison of spaceflight to ground with adjusted P-value < 0.01 and absolute
log2-transformed fold change > 1.5 (Love et al. 2014). Genes of which the total count across all
samples is < 100 were not included in the analysis. Gene Ontology (GO) Overrepresentation was
performed using PANTHER (Fisher’s Exact type with False Discovery Rate correction)
(http://www.pantherdb.org) (Mi et al. 2019a; Mi et al. 2019b). K-means clustering analysis on
average FPKM values from biological replicates was performed using the Morpheus tool
(Morpheus, https://software.broadinstitute.org/morpheus). The optimal number of K-means
clusters was determined using factoextra package in R.
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RESULTS
Spaceflight Alters the Growth of Seedlings Independently from an Intact UPR Signaling
When we inspected the WT and UPR mutant seedlings (atire1, bzip60, bzip28 and bzip28
bzip60) of the ground control and flight samples at the completion of the mission, we found that
in the ground control samples, etiolated hypocotyls (i.e., pale and elongated due to the lack of
light) were above the surface of the solidified media while roots had penetrated the growth medium
perpendicular to the surface (Figure 3.1A). However, in flight samples, we found that etiolated
hypocotyls as well as roots had generally penetrated the growth medium regardless of genotype
tested (Figure 3.1A). Interestingly, we also observed that cotyledon petioles of flight sample
seedlings were elongated (Figure 3.1B) compared to ground control seedlings (Figure 3.1A).
Overall, these observations are consistent with plant growth in the darkness and space, conditions
leading to elongated hypocotyls and petioles, and a lack of directional growth, respectively (Paul
et al. 2017). These observations also suggest that the UPR unlikely exerts a noticeable role in
growth direction in response to altered gravity levels.
Spaceflight Results in an Increase of Total RNA
RNA degradation has previously been observed in independent Arabidopsis spaceflight
experiments performed in BRIC-PDFUs (Johnson et al. 2017; Paul et al. 2012). To test the RNA
quality of our samples, we measured RNA integrity number (RIN) as an indicator of overall RNA
quality (RIN, 1 = low quality; 10 = high quality) of each sample and compared size peaks of 25S
and 18S ribosomal RNA (rRNA) among samples (Mueller et al. 2004). Note that these
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Figure 3.1. Growth of etiolated hypocotyls was altered by spaceflight.
A) Representative ground and flight sample plates (left) were imaged after the bulk of etiolated
hypocotyls and RNAlater was removed to ensure maximal RNA integrity. Remaining seedlings
were used for post-hoc analysis of morphological/growth differences. B) Example plate of a WT
flight sample which was imaged after thawing, but prior to seedling removal. Individual seedlings
which could be distinguished from the bulk were marked with a blue arrow to mark the shoot
meristem. The cotyledons of elongated petioles were marked with a red arrow and a red line used
to connect the cotyledon to the meristem of the same seedling. Petioles were elongated compared
to ground sample petioles (representative morphology of ground control presented in FIG 1A, right
side).
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measurements include smaller plastid rRNA peaks, which lower the maximum RIN value to
around 8, independent of RNA quality (Babu and Gassmann 2016). We found that all flight
samples had RIN values between 7.5 and 8.0, indicating that RNA was of high quality. For ground
samples, RIN values were found to be between 4.0 and 7.7, which would ordinarily indicate mild
degradation of some samples. However, closer analyses revealed that, in nearly all ground samples
(77%), the RIN algorithm failed to identify the correct peaks. In these samples, the algorithm
identified the 18S rRNA peak as the 25S rRNA peak, and a putative organelle rRNA peak (Babu
and Gassmann 2016) as the 18S rRNA (Figure 3.S1; Supplemental figures found in Chapter
Appendix). Therefore, to compare RNA quality between treatments and genotypes from the
Bioanalyzer data outputs, we used the ratio of 25S/18S peak heights as a substitute measure.
Because the 25S peak height is reduced more quickly than the 18S peak in RNA degrading
conditions (e.g., elevated temperature, exogenous RNases, endogenous apoptotic RNase activity)
(Babu and Gassmann 2016; Mueller et al. 2004), a decreased 25S/18S ratio would indicate RNA
degradation. We observed no significant differences of the 25S/18S ratio across all genotypes
(Figure 3.2A), therefore, both flight and ground samples had no significant RNA degradation.
Interestingly, by comparing the 25S peak height to one of the two other peaks near the 18S peak
(i.e., a putative organellular rRNA peak, designated 18S (-3); Figure 3.S1) in each sample, it was
clear that the relative ratio of 25S to 18S (-3) was significantly lower in the ground samples
compared to flight samples (Figure 3.2B, Figure 3.S1). This low ratio indicates that the ground
samples were depleted of nuclear-encoded rRNAs (i.e. 25S and 18S rRNAs) compared to other
RNA species. This observation is also consistent with our findings that our ground samples
contained significantly less total RNA (of which rRNA is a significant fraction (Lodish 2000))
than flight samples (Figure 3.2C). Because we extracted RNA from a similar number of seedlings
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Figure 3.2. RNA quality assessment of flight and ground control samples.
A) Average ratio of 25S/18S peak heights as determined from Bioanalyzer traces from each sample
was used as a secondary measure of RNA quality due to the RIN algorithms incorrect identification
of the appropriate peaks. B) The relative content of rRNA found in each genotype in both
conditions was determined by comparing the height of the 25S peak to an organellular rRNA peak
(18S (-3)) which was found in each sample. C) Average RNA yields from each genotype from
flight and ground samples. Statistical significance determined by Welch’s T-test, p value represent
by NS= >0.05; *= <0.05; **=<0.005; ***=<0.0005.
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from flight samples and ground samples, our results indicate that flight samples contained larger
amount of total RNA compared to ground samples, which is likely to be caused by elevated levels
of nuclear encoded rRNA in flight samples, and unlikely to be due to RNA degradation of the
ground samples.
Global Transcriptomics Analyses Indicate that Gene Expression Reprogramming in Response to
Spaceflight Depends partially on Intact UPR Signaling
Having established that the total RNA from ground and flight samples was of acceptable
quality, we next proceeded to RNA-sequencing (RNA-seq) to investigate the impact of spaceflight
on global gene expression changes in the UPR mutants. In RNA-seq library preparation, mRNA
was enriched by purification to efficiently remove rRNA (Zhao et al. 2018) and mitigate potential
sequencing bias due to higher rRNA levels in flight samples. We obtained an average of
approximately 32 million reads per sample, of which 95-99% were successfully mapped to the
Arabidopsis reference genome (Figure 3.S2). Spearman’s rank correlation coefficients calculated
between biological replicates showed a high reproducibility of our RNA-seq dataset (Figure 3.3A).
Furthermore, principal component analysis (PCA) exhibited a strong separation of ground samples
from flight samples (Figure 3.3B) and indicated that ground samples located more closely to each
other than the flight samples. Overall, these analyses further supported a statistical robustness of
the RNA-Seq and justified further investigation.
To investigate gene expression changes in response to spaceflight, we identified
differentially expressed genes (DEGs) in each genotype by comparing gene expression values in
ground and flight samples (Supplemental Data File 1.1). A total of 3,465 genes were classified as
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Figure 3.3. Overall quality assessment of RNA-sequencing dataset
A) Spearman’s correlation coefficients demonstrate a close relationship between biological
replicates. B) Principal component analysis demonstrates a clear separation between flight and
ground samples.
DEGs in at least one genotypes. WT had the largest number of DEGs (upregulated DEGs in flight
compared to ground, n = 1675; downregulated DEGs, n = 831) among the genotypes tested. The
bzip28 bzip60 mutant had the smallest number of DEGs (upregulated DEGs, n = 1293;
downregulated DEGs, n = 562) (Figure 3.4A, B). In all genotypes, the number of upregulated
DEGs were higher than that of downregulated DEGs (WT, 2.02-fold; atire1, 1.98-fold; bzip28,
2.28-fold; bzip60, 1.80-fold; bzip28 bzip60, 2.30-fold), indicating a higher impact of space flight
on inducing gene expression rather than suppressing it. While the identity of 34.8% (783/2249) of
upregulated DEGs and 27.5% (335/1217) of downregulated DEGs overlapped across all
genotypes, relatively smaller numbers of DEGs were found to be genotype-specific, ranging from
30 (downregulated exclusively in bzip28 bzip60) to 207 (upregulated in WT).
In summary, based on the verified number of upregulated and downregulated DEGs in
flight samples compared to ground samples across genotypes, the UPR mutants had consistently
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Figure 3.4. Summary of differential gene expression analyses.
Differential expression analysis using the 4 biological replicates with the highest correlation was
performed via HTseq v0.6.1pl and DESeq v2. For each genotype and for genes differentially
expressed genes in flight samples relative to ground samples were determined using a strict
criterion: adjusted P value <0.01; |log2FC|> 1.5. Total number of upregulated A) and
downregulated B) DEGs in each background were analyzed to determine what proportion were
shared between the different genotypes.
fewer overall DEGs than WT, indicating that the UPR could play at least a partial a role in
regulating the transcriptional reprogramming in space compared to ground control.
Biological Pathways Connected to the DEGs between Flight and Ground
To gain insights in the biological pathways altered in spaceflight in our experimental set
up, we performed separate Gene Ontology (GO) analyses on upregulated and downregulated
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DEGs in WT (Supplemental Data File 1.2), generating a list of parental-GO terms (more general,
represented by a larger number of genes in the reference gene set), and cognate child-GO terms
(more specific, smaller numbers of genes in the reference gene set) (Figure 3.5). Intriguingly, we
found that stress responsive-genes (e.g., “response to abscisic acid”, “response to hypoxia”,
“response to water deprivation” and “response to oxidative stress”) as well as genes involved in
physiological responses often associated with stress response adaptation were enriched in
downregulated DEGs in WT. This result is consistent with previous studies that reported
downregulation of water-stress related genes using Arabidopsis BRIC-PDFU microarray
transcriptomes (Johnson et al. 2017) and that found abscisic acid response and water stress
response overrepresentation in misregulated DEGs in Col-0 WT using RNA-seq (Choi et al. 2019).
In addition, we observed that metabolic processes associated with stress adaptation (Batista-Silva
et al. 2019; Hildebrandt et al. 2015), including amino acid catabolism and sucrose starvation
response, were overrepresented in flight- downregulated DEGs. Ribosome biogenesis, translation
and gene expression processes were highly underrepresented in this category, i.e. they were more
likely to be upregulated by flight, or remain unchanged. By further analyzing the normalized gene
expression values (FPKM), we also found that ribosome biogenesis and rRNA processing GO
terms appeared significantly overrepresented in genes upregulated by > 2 fold changes
(flight/ground). These, however, were not considered as DEGs based upon the strict statistical
criteria applied in our analyses (see methods). The lower FPKMs of ribosome biogenesis-related
genes in ground control samples are consistent with our observations that the ground control
samples were partially depleted of 25S and 18S rRNA compared to flight samples (Figure 3.2C).
We also found that GO terms enriched in upregulated DEGs included biological processes
that have been noted in previous Arabidopsis spaceflight transcriptome analyses, such as
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Figure 3.5. Representative biological processes gene ontologies over- or under- represented
by upregulated or downregulated DEGs in the WT background.
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secondary metabolite biosynthesis associated with defense responses (Choi et al. 2019; Johnson
et al. 2017). Furthermore, we verified the dichotomous occurrence of the “absence of light”,
“response to red or far red light (R/FR) response” GO terms in the down- and upregulated gene
sets, respectively. The overrepresentation of photosynthetic components in upregulated DEGs is
partially consistent with the results of a previous BRIC-PDFU experiment showing light/high light
response and some photosynthesis-related genes to be differentially regulated in a subset of the
tested genotypes (Choi et al. 2019). In addition to the findings consistent with previous spaceflight
reports, we also observed a significant enrichment of DNA repair, DNA replication, and cell cycle
pathways in the upregulated DEGs, which could be possibly associated with exposure of flight
samples, but not ground samples, to ionizing radiation during spaceflight.
Together these results indicate that in our experimental conditions, spaceflight globally
affects gene expression changes associated with a broad array of significant biological processes,
largely identified also in previous spaceflight transcriptome studies (Choi et al. 2019; Johnson et
al. 2017).
The UPR Regulators Exert a Minor but Significant Role on Gene Expression in Spaceflight
Next, we aimed to gain insights into the transcriptome changes caused by the absence of
intact UPR signaling in both ground and spaceflight conditions. To address it, we performed K-
means clustering analysis on FPKM values for all DEGs (n = 3,465) obtained in at least one
genotype (Figure 3.6; Data File 1.3) and then performed GO analysis to correlate the expression
signature of each cluster to biological functions (Data File 1.4). Our clustering analysis suggested
that variations in the identified DEGs between different genotypes (Figure 3.4) were primarily the
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Figure 3.6. K-means clustering analysis of all 3,465 DEGs in at least 1 background.
Each row represents FPKM values of an individual gene averaged between biological replicates.
For each row blue represents the minimum relative expression value and red the maximum
expression value, white is the middle value. For each cluster GO biological process analysis of
DEGs demonstrates a role for UPR regulation of ground control stress responses, which are largely
repressed by flight.
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result of variable FPKM values in the ground control samples (Figure 3.6). In flight, the FPKM
values were roughly equalized to insignificantly different levels of expression across all genotypes.
Of the 3,465 DEGs, in the ground samples 517 DEGs had FPKM values that were significantly
different (p-value ≤ 0.01) in at least one UPR mutant compared to WT; however, in flight samples
only 144 genes had FPKM values that were significantly different in at least one UPR mutant
genotype compared to WT (Figure 3.6; Figure 3.S3).
The largest cluster (Cluster 1 DEGs; n = 2299) consisted of DEGs upregulated to varying
degrees in most of the genotypes tested. As such, a nearly identical set of GO terms that were
enriched in upregulated DEGs in WT (Figure 3.5) were also enriched in Cluster 1. We then
compared the FPKM values of DEGs in ground samples across genotypes, and found that 39.1%
and 19.8% of DEGs in Cluster 1 were significantly different in the bzip60 and bzip28 bzip60,
respectively, compared to WT, while only 4.6% and 2.9% of DEGs were significantly different in
bzip28 and atire1 compared to WT (Figure 3.S4). Overall, these results indicate that bZIP60 has
functions that are independent of IRE1 and bZIP28, which in turn are required to downregulate
Cluster 1 DEGs in ground control conditions. These observations are in accordance with the
findings in ground conditions that bZIP28 and bZIP60 control some UPR target genes in an
independent manner (Ruberti et al. 2018). In Cluster 2 (DEGs; n = 546), expression of DEGs was
induced exclusively in ground bzip60 compared to other ground genotypes while highly
suppressed to similar levels of expression in flight samples of all genotypes. As such, the
proportion of DEGs in bzip60, whose expression was significantly different from WT, was much
higher (17%) than other genotypes (bzip28 bzip60, 0.9%; bzip28, 1.0%; atire1, 1.2%) (Figure
3.S4). We reasoned that bZIP28 and bZIP60 could have a negative feedback relationship in which
the absence of bZIP28 suppressed the effect of bzip60 mutation exclusively in the ground
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condition. The overrepresented GO terms in Cluster 2 were largely similar to the GO terms
enriched in the downregulated DEGs genes in the WT genotype: “response to abscisic acid”,
“response to water deprivation”, and “response to hypoxia” (Figure 3.5). In addition, Cluster 2
DEGs showed significant enrichment of GO terms associated with biotic stress responses that were
not found in analyses of the WT genotype (Figure 3.5) or found to be strongly enriched in the any
of the other clusters (Figure 3.6; Data File 1.4). These results indicate that bZIP60 may have
repressive roles in regulating genes involved in both abiotic and biotic stress responses.
The gene expression pattern of Cluster 3 (DEGs; n = 274) was also characterized largely
by genes with lower expression values in spaceflight compared to ground control across genotypes,
except for bzip28. However, contrasting with Cluster 2, the FPKM values in the bzip60 genotype
was not different from WT FPKM values; only 3.2% of DEGs showed significantly different
FPKM compared to WT (Figure 3.S4). Instead, the absence of bZIP28 (i.e., in the bzip28 mutant)
had a higher impact on gene expression in the ground condition compared to other mutants (Figure
3.S4). Interestingly, these Cluster 3 DEGs had intermediate FPKM values in the bzip28 bzip60
genotype in ground control compared to the extremes of the bzip60 and bzip28 single mutants,
indicating an antagonistic regulation of bZIP28 and bZIP60 on these genes in the ground condition,
which was largely compensated for in the bzip28 bzip60 genotype.
Similar to Clusters 2 and 3, Cluster 4 (DEGs; n =55) contained genes, whose expression
exhibited overall lower FPKMs in spaceflight compared to ground across genotypes. However,
Cluster 4 showed a unique pattern: the expression of the DEGs in this cluster was significantly
lower in bzip60 compared to WT and the other genotypes in the ground condition (Figure 3.S4)
and showed no prominent differences across genotypes in the spaceflight condition. Although
Cluster 4 was not significantly represented by any biological process GO terms, a closer analysis
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revealed that 22% of all DEGs in this cluster were encoded on the mitochondrial genome;
mitochondria-encoded genes comprise only 0.5% of all protein-coding genes in the Arabidopsis
genome annotation (https://www.arabidopsis.org) and 0.3% of DEGs called in this study.
Cluster 5 (DEGs; n= 291) showed a gene expression pattern similar to Cluster 2 with
significantly higher levels in the bzip60 genotype compared to the other genotypes in the ground
control samples. (Figure 3.S4). In this Cluster, the DEGs were more affected by the absence of
bZIP28 (bzip28 bzip60 and bzip28) in the ground condition compared to Cluster 2. The GO term
“response to water deprivation”, which was found to be enriched in Cluster 2, was significantly
enriched in Cluster 5. In addition, relatively narrow child GO terms “toxin catabolic process” and
“glutathione metabolic process”, which were not enriched in other clusters, were enriched in
Cluster 5.
Overall, by comparing the bzip60 and bzip28 single mutants with the bzip28 bzip60 double
mutant, our transcriptomic profiling provides evidence for a highly complex, unconventional,
regulatory relationship between bZIP60 and bZIP28 under the conditions experienced by ground
control seedlings. Furthermore, a small number of significant differences between WT and the
UPR mutants in spaceflight were found, supporting a small but significant role of the UPR in gene
expression in spaceflight.
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DISCUSSION
In this study, we examined the transcriptional responses of WT and seedlings with a
compromised UPR to spaceflight to set the foundations to manipulate a critical growth and stress
signaling pathway for improving plant adaptation to extraterrestrial environments. We utilized the
BRIC-PDFU sterile plant culture hardware during the SpaceX-CRS12 mission to compare the
transcriptional responses to the spaceflight between Arabidopsis thaliana WT and mutants
defective in one or more components of the UPR, namely the TFs bZIP60, bZIP28, and the ER
resident kinase/ribonuclease IRE1.
The BRIC-PDFU hardware has been employed in a number of dark-grown Arabidopsis
transcriptome experiments towards different aims (Choi et al. 2019; Johnson et al. 2017; Kwon et
al. 2015; Paul et al. 2012). Variability in technical experimental details and limited overlap
between spaceflight/ground DEGs have been verified even between the same WT control genotype
in simultaneous experiments (Johnson et al. 2017). However, some broad biological pathways
have been found to be induced or repressed in response to spaceflight, including cell wall
modification, response to light / high light, and oxidative stress, osmotic stress response, heat
shock, and biotic defense / secondary metabolite synthesis (Choi et al. 2019; Johnson et al. 2017;
Paul et al. 2012). Many of these responses were also noted in our study, including the
downregulation of water stress response in space, which has been identified in four separate
experiments (Choi et al. 2019; Johnson et al. 2017). However, we also observed correlative
differences in seedling growth and an overall gene expression landscape not noted in previous
studies. Our ground control seedlings had grown in a predictable manner, consistent with the
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expected morphology of terrestrially grown Arabidopsis etiolated hypocotyls (Figure 3.1). Flight
sample growth was also largely in line with expectations for seedlings grown in microgravity,
including the observed petiole elongation which was shared in all flight samples. Indeed a petiole
elongation of flight samples was also present in the images published of dark grown Arabidopsis
experiments in the Col-0 background in previous experiments (Johnson et al. 2015; Paul et al.
2017). This growth phenotype is consistent with low R/FR ratio and shade avoidance syndrome
(SAS) mediated by phytochrome signaling (Franklin 2008). The correlative responses observed in
the transcriptome analysis (Figure 3.4) support that differentially regulated growth phenotypes and
the large transcriptional rearrangements in flight during our experiment might have been mediated
by phytochrome-related signaling, which is also known to constitutively repress abscisic acid
signaling (Yang et al. 2016), and were found to be repressed in our flight samples. However, these
differences in the response to light and the increased expression of photosynthetic components
between ground and flight samples are anomalous when considering the spaceflight culture
methods used in this study. BRIC-PDFUs are autoclavable, black polymer containers, which are
sealed with metal lids during science integration, and allow injection of the chemical preservative
without opening the unit. After being sealed on August 12th, the seeds and seedlings germinated
from these seeds in the BRICs were not exposed to light during the launch and the 14-day growth
period on the ISS. Therefore, the dichotomous occurrence of the “absence of light”
overrepresentation in downregulated and of “response to red or far red light response” in
upregulated DEGs is unlikely to be the result of actual differential exposure to light. One likely
explanation is related to the hypocotyl-tissue media contact that occurred in our flight samples,
which lacked a clear growth vector in microgravity, but had not occurred in our ground samples
where roots grew perpendicular into the media. In previous experiments by Johnson et al. (2015)
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and Paul et al. (2017), the dark grown ground control plates were oriented vertically and both
sample sets displayed petiole elongation, although the precise differences in length or extent of
petiole elongation between flight and ground were not quantified. How media contact could induce
Red / Far Red (R/FR) light signaling in the dark is not immediately obvious; however, earlier
studies showed that media containing sucrose modulated the R/FR signaling mediated by
phytochrome A, promoting a red light response (Dijkwel et al. 1997). Coincidentally, the higher
rRNA and total RNA content observed in flight samples compared to ground control samples in
our study (Figure 3.2) is also consistent with an increased exposure of cells to sucrose or glucose,
which is known to induce RNA accumulation, rRNA transcription, and ribosome biogenesis in
plants (Ishida et al. 2016; Kojima et al. 2007), yeast (Kunkel et al. 2019), and mammals (Hannan
et al. 2003). Nonetheless, we cannot rule out the remote possibility that our observations may be
influenced by possible interactions between ionizing radiation and phytochrome R/FR signaling.
For example, low dose gamma (γ) irradiation of lettuce seeds was found to mimic the effects of
FR deactivation of red light activated phytochromes (Hsiao and Vidaver 1974). Additionally, a
structural study of the bacterial phytochrome from the radiation resistant bacterial Deinococcus
radiodurans established that X-ray radiation induced deprotonation of chromophore in the inactive
phytochrome, a biochemical step thought to be involved in light induced activation of this protein
(Li et al. 2015). Although the dose required to deprotonate 50% of the phytochrome (Li et al.
2015) was orders of magnitude larger than that expected to be experienced during our experimental
period on the ISS, differences between prokaryotic and eukaryotic phytochromes could affect
relevant properties of a hypothetical phytochrome-radiation interaction.
Interpreting a role for the UPR in the transcriptional response to spaceflight is complicated.
We observed clear differences in the number of spaceflight DEGs in the UPR mutant backgrounds
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compared to WT (Figure 3.4); and only 1,118 of the 3,465 DEGs were common to all genotypes.
This would normally suggest that the transcriptional readjustments that occurred in response to
spaceflight were at least partially the result of UPR-dependent processes. However, upon closer
analysis of the underlying FPKM values it became clear that the differences in fold change values
(flight/ground) across genotypes were more heavily influenced by the differential regulation of
expression in the ground samples by the UPR regulators (Figure 3.6). The number of DEGs with
FPKM values significantly different from WT FPKM values in at least one UPR mutant genotype
was four times greater in the ground samples compared to flight samples (Figure 3.S3). The heat
map visualization of these values (Figure 3.6) further suggests that the variations in ground
samples expression levels were largely muted by spaceflight, as the endpoint transcript levels in
flight samples were nearly uniform in the different genotypes. Overall, this would suggest that the
UPR does not have a broad involvement in the response to spaceflight. One explanation for this
observation may be related to the concerted downregulation of many stress-responsive processes
in the flight samples compared to the ground samples (Figure 3.6). In spaceflight conditions, it
seems likely that alternative signaling pathways are actuated, which repress the observed stress
responses regulated by the UPR. Given the prevalence of starvation responses in ground samples,
it is possible that microgravity induced-changes in growth habit provide better nutrient availability
(Figure 3.7). As such, plants in flight may be able to better handle the stresses imposed by culture
conditions, without requiring UPR regulator involvement.
Nonetheless, the observations related to an interaction between the UPR regulators bZIP60
and bZIP28 and the stresses imposed on ground control seedlings have yielded important
information, which should be explored in the future. In the canonical ER stress response induced
chemically or via environmental stress, bZIP60 and bZIP28 transcription factors interact in the
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Figure 3.7. Simplified model of regulatory framework controlling stress responsive DEGs.
(A) Hypothesized regulatory framework for stress responsive DEGs found to be regulated by the
UPR on the ground but not in flight conditions. Possible interactions between bZIP60 and
bZIP28 in the regulation of DEGs found in (B) clusters 2 and 5 (C) cluster 3, and (D) cluster 4.
nucleus and direct the actions of the COMPASS DNA methylation complex to increase
transcription of target genes (Song et al. 2015). Furthermore, these transcription factors can also
bind independently to gene promoters to activate downstream UPR genes, as evidenced by the
weaker activation of ER chaperones in the bzip28 bzip60 double mutant compared to either of the
bzip28 or bzip60 single mutants (Ruberti et al. 2018; this work). Although it has been suggested
that bZIP60 and bZIP28 may also have unique target genes (Pastor-Cantizano et al. 2019), in our
ground control samples the transcriptomic data suggest that bZIP60 and bZIP28 may have a more
complex antagonistic relationship in the control of genes related to the response to abscisic acid,
hypoxia, water deprivation, and to oxidative stress (Figures 3.6). In Clusters 2 and 5, and Cluster
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4, we observed that the expression levels of the DEGs were higher or lower than WT in the bzip60
genotype, respectively (Figure 3.6, Figure 3.S3). However, these differences were not observed in
the bzip28 bzip60 double mutant as would be expected. Conversely, in Cluster 3 we observed in
ground samples that the expression levels of the DEGs were sharply lower in the bzip28 genotype
compared to WT. In the bzip28 bzip60 genotype, the genes in Cluster 3 had expression levels that
were higher than the bzip28 genotype but were also lower than those of these genes in the WT or
bzip60 genotypes. In response to chemically induced UPR conditions, bZIP60 and bZIP28
cooperatively upregulate several UPR genes (Ruberti et al. 2018; Song et al. 2015). In our ground
controls, the stress responsive genes, largely represented by “response to abscisic acid”, “response
to water deprivation”, and “response to hypoxia” abiotic stress responses were regulated by
bZIP28 and bZIP60 in a way that suggests that these TFs have antagonistic regulatory effects on
these processes (Figure 3.7B-D).
The exact nature of the stress experienced by the ground control seedlings would need to
be elucidated to better understand the impact of this information on agronomic and/or spaceflight-
applications. Studies on the effect of plant growth in BRIC-PDFUs have already established that
significant stress may be imposed on the seedlings grown in these conditions (Basu et al. 2017;
Johnson et al. 2015). Consistent with our results, other BRIC-PDFU transcriptomes have found a
downregulation of genes related to water stress responses (Johnson et al. 2017). However, as
evaporative water loss from the BRIC-PDFUs is unlikely because they are sealed containers, the
strongly represented GO terms related to “response to water deprivation” and “response to abscisic
acid” are unlikely to be a direct response to actual water loss from the plates. Instead, it may be
possible that the ground seedlings with etiolated hypocotyls that are not in contact with the media
or have less overall contact with the media are water stressed compared to flight seedlings that are
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in direct contact or have penetrated the media. Independently from the underlying stimulus for the
observed differences, the possibility that bZIP60 and bZIP28 may have antagonistic interactions
related to control of abscisic acid signaling or water deprivation responses should be investigated
at the molecular level in the future to improve plant growth and stress responses in space and on
the ground.
124
DATA AVAILABILITY
Raw sequencing data has been deposited at the NCBI Gene Expression Omnibus under the
accession number GSE148914. Raw sequencing data has also been deposited at the NASA
GeneLab data repository (Ray et al. 2018) for spaceflight experiments under the accession number
GLDS-321.
ACKNOLWEDGEMENTS
We would like to thank the NASA, KSC, and NASA contractor support staff whose
diligent work made these experiments possible. This work was supported primarily by NASA
NNX12AN71G with contributing support from Training Program in Plant Biotechnology for
Health and Sustainability (T32‐GM110523), the DOE Great Lakes Bioenergy Research Center
(DOE BER Office of Science DE‐FC02‐07ER64494 and DE‐SC0018409), the Chemical Sciences,
Geosciences and Biosciences Division, Office of Basic Energy Sciences, Office of Science, US
Department of Energy (award number DE‐FG02‐91ER20021), National Institutes of Health
(GM101038) and AgBioResearch (MICL02598) to FB.
125
AUTHOR CONTRIBUTIONS
F.B. designed the experiments. S.Z.-D. and E.A. performed preliminary launch
preparations. E.A. executed the experiments. D.K.K. performed bioinformatics analysis. E.A.,
D.K.K., S.Z.-D, and F.B. analyzed data and wrote the article.
126
APPENDIX
127
Figure 3.S1. Representative Bioanalyzer traces of ground and flight samples.
Representative Bioanalyzer traces of A) ground, and B) flight samples illustrating
misidentification of peaks by the RIN algorithm in the ground sample, and identification of the
correct 25S and 18S peaks in the flight samples. The peak labeled 18S(-3) is an likely organellular
rRNA peak which had similar sizes in flight and ground samples which was used to quantify the
relative content of 25S rRNA in Figure 3.2.
Figure 3.S2. Number of total mapped reads and mapping rate per sample.
128
Figure 3.S3. Number of DEGs which had WT FPKM values which were significantly
different from WT in at least one mutant genotype.
For all 3,465 DEGs identified, significant differences in FPKMs were identified between WT
and each individual mutant genotype using a Welch’s t-test. The number of genes which had p-
values between 0.05 and 0.01 and p-values less than 0.01 are indicated by the different colors.
Figure 3.S4. Percentage of DEGs with statistically different ground FPKM values in the
indicated UPR mutant genotype compared to WT ground FPKM values.
For each cluster in Figure 3.6, significant differences in FPKMs were identified between WT and
each individual mutant genotype using a Welch’s t-test. The number of genes in that cluster
which had p-values < 0.05 in the indicated genotype were counted and displayed as a percentage
of the total number of genes in that cluster.
129
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CHAPTER IV
THE UPR REGULATOR IRE1 PROMOTES BALANCED ORGAN DEVELOPMENT
BY RESTRICTING TOR-DEPENDENT CONTROL OF CELLULAR
DIFFERENTIATION IN ARABIDOPSIS
The work presented in this chapter has been submitted for publication.
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ABSTRACT
Proteostasis of the endoplasmic reticulum (ER) is controlled by sophisticated signaling
pathways that are collectively called the unfolded protein response (UPR) and are initiated by
specialized ER membrane-associated sensors. The evidence that complete loss-of-function
mutations of the most conserved of the UPR sensors, inositol requiring enzyme 1 (IRE1),
dysregulates tissue growth and development in metazoans and plants raises the fundamental
question as to how IRE1 is connected to organismal growth. To address this question, we
interrogated the Arabidopsis primary root, an established model for organ development, using the
tractable Arabidopsis IRE1 mutant, ire1a ire1b, which has marked root development defects in the
absence of exogenous stress. We demonstrate that IRE1 is required to reach maximum rates of cell
elongation and root growth. We also established that in the actively growing ire1a ire1b mutant
root tips the Target of Rapamycin (TOR) kinase, a widely conserved pro-growth regulator, is
hyperactive, and that, unlike cell proliferation, the rate of cell differentiation is enhanced in ire1a
ire1b in a TOR-dependent manner. By functionally connecting two essential growth regulators,
these results underpin a novel and critical role of IRE1 in organ development and indicate that, as
cells exit an undifferentiated state, IRE1 is required to monitor TOR activity to balance cell
expansion and maturation during organ biogenesis.
137
INTRODUCTION
The endoplasmic reticulum (ER) is responsible for the synthesis of one third of the cellular
proteome. Therefore, its biosynthetic capacity is constantly monitored by a set of ER membrane-
associated sensors that can upregulate the synthesis of ER protein chaperones and ER membrane
while also limiting the rate of protein translation (Ron and Walter 2007, Han and Kaufman 2017).
The UPR sensors conserved between metazoans and plants include the ER membrane protein
kinase and ribonuclease IRE1 and ER membrane tethered transcription factors (TFs) (metazoan
ATF6 and plant bZIP17 and bZIP28) (Angelos et al. 2017, Pastor-Cantizano et al. 2020). Through
its ribonuclease domain, IRE1 catalyzes the unconventional cytosolic splicing of mRNA encoding
of a transcription factor, XBP1 in mammalian cells, bZIP60 in Arabidopsis, and Hac1 in yeast
(Kawahara et al. 1997, Calfon et al. 2002, Nagashima et al. 2011). In addition to the
unconventional splicing of the mRNA of target TFs, IRE1 degrades cytosolic mRNAs through a
process known as regulated IRE1-dependent decay (RIDD) to preserve cell proteostasis (Hollien
et al. 2009, Mishiba et al. 2013).
Exogenous stress factors, such as hypoxia and metabolic stress in metazoans (Hetz and
Papa 2018) as well as heat stress (Gao et al. 2008), pathogen attack (Guillemette et al. 2014, Zhang
et al. 2015), and singlet oxygen generation (Beaugelin et al. 2020) in plants, are known to activate
the UPR sensors. Interestingly, these sensors are also activated by endogenous cellular cues during
physiological development (Mitra and Ryoo 2019). For example, the mammalian IRE1 has critical
functions in placental and liver development during embryogenesis and during the differentiation
of antibody-secreting B-lymphocytes (Reimold et al. 2000, Reimold et al. 2001). In Drosophila,
IRE1 activity is required for the development of the digestive tract (Huang et al. 2017). In Xenopus
138
and medaka fish, IRE1 is required for proper notochord formation and hatching gland
development, respectively (Tanegashima et al. 2009, Ishikawa et al. 2017). In these metazoan
models, complete IRE1 loss-of-function mutations are embryo or larval lethal (Mitra and Ryoo
2019).
In Arabidopsis there are three homologs of the IRE1 gene, IRE1a, IRE1b, and IRE1c,
which perform only partially overlapping functions (Mishiba et al. 2019, Pu et al. 2019). IRE1c is
expressed primarily in reproductive tissues during gametogenesis, whereas IRE1a is primarily
expressed in root tissues, and IRE1b is expressed at a similar level in nearly all tissue types (Pu et
al. 2019). Single mutants of the Arabidopsis IRE1 homologs are phenotypically identical to wild
type (WT) plants under physiological conditions of growth; however high-order mutations cause
severe developmental defects. For example, the ire1b ire1c double mutant has a gamete lethal
phenotype (Pu et al. 2019), and the ire1a ire1b double mutant, a functional IRE1 knock-down,
reproduces normally but has a short root phenotype (Deng et al. 2011, Chen and Brandizzi 2012,
Chen et al. 2014, Bao et al. 2019). Similar to ire1b ire1c, the ire1a ire1b ire1c triple mutant is also
gamete lethal (Mishiba et al. 2019), and plants that are heterozygous for ire1c and homozygous
for ire1a and ire1b have severe developmental defects in all tissue types (Mishiba et al. 2019). On
the whole, these phenotypes support that IRE1 performs critical functions to promote the growth
and development of several Arabidopsis tissue types with some degree of specificity likely linked
to the expression of the IRE1 isoforms in their respective tissues.
How the Arabidopsis IRE1 controls tissue growth and development is completely
unknown. In most metazoan model species, IRE1 primarily contributes to development through
activation of XBP1 (Reimold et al. 2000, Reimold et al. 2001, Ishikawa et al. 2017). Indeed, XBP1
null mutations are also embryo lethal and affect the development of the same tissue types as IRE1
139
mutations (Mitra and Ryoo 2019). Surprisingly, loss-of-function mutations in the Arabidopsis
bZIP60 do not have any growth or reproductive phenotypes (Nagashima et al. 2011, Chen and
Brandizzi 2012, Moreno et al. 2012). Therefore, unlike the metazoan IRE1, the Arabidopsis IRE1
promotes organ growth through mechanisms that are independent from its canonical splicing
target.
Similar to IRE1, the Target of Rapamycin (TOR) kinase is highly conserved across
eukaryotes (Shi et al. 2018). TOR and its associated protein complexes act as cell regulatory hubs
that integrate nutrient availability, energy status, hormone, and stress input signals to coordinate a
wide variety of cellular activities ranging from cell proliferation and growth, to metabolism and
autophagy (Shi et al. 2018, Burkart and Brandizzi 2020). While several of the key proteins in the
TOR complex are conserved between plants and animals (such as LST8 and RAPTOR), the
specific inputs and outputs have been evolutionarily adapted to meet organism-specific needs
(Burkart and Brandizzi 2020). Indeed, plant TOR receives activating signals from light availability
via photosynthetic production of carbohydrates (photosynthates) and light-dependent synthesis of
the plant hormone auxin (Li et al. 2017, Chen et al. 2018). Photosynthate-dependent activation of
TOR via glucose is necessary and sufficient to activate root tips and promote cell division in root
meristematic zones via activation of E2F transcription factors (Xiong et al. 2013). TOR activity is
also required for the polar growth of root hairs (Montané and Menand 2013), which necessitates
substantial synthesis of new cytosolic, membrane, and cell wall components (Ovečka et al. 2005,
Retzer and Weckwerth 2021). Nonetheless, how TOR activities are integrated into other aspects
of development in actively growing roots is not well understood.
Despite the evidence that both IRE1 and TOR control growth, a functional connection
between these essential regulators in the context of development has yet to be made. Earlier studies
140
of chemically induced ER stress and other stress situations in metazoan cells have demonstrated
that TOR activity can lead to an induction of the IRE1-JNK pro-apoptotic kinase signal cascade,
(Kato et al. 2012, Kato et al. 2013, Shanware et al. 2014), as well as IRE1 inactivation (Sanchez-
Alvarez et al. 2017). Nonetheless to date, it is yet unknown whether IRE1 controls TOR activity
under induced ER stress conditions or physiological conditions of growth in any model organism.
To address these fundamental knowledge gaps, we used the tractable Arabidopsis ire1a ire1b
model because it avoids the gamete lethality and extreme pleotropic phenotypes of other high-
order UPR mutants (Kim et al. 2018, Mishiba et al. 2019). Furthermore in physiological conditions
of growth, the plant phenotype of this mutant is restricted to the root (Chen and Brandizzi 2012,
Ruberti et al. 2018). Due to their invariant cell ontogeny and cell organization the Arabidopsis root
is an exquisite development model system (Scheres and Wolkenfelt 1998), and is therefore suitable
to investigate the role of IRE1 in tissue development. Through an in-depth characterization of ire1a
ire1b root development in normal conditions of growth, we demonstrate that IRE1 is required to
reach maximum rates of root growth afforded by prolonged photoperiods and high carbohydrate
availability during the transition from early seedling stage to adult vegetative stage. A detailed
analysis of this developmental transition carried out in this work indicates that in the root meristem
IRE1 is required for the correct timing of cell elongation in a manner that is dependent upon a
strict regulation of TOR activity, and TOR-dependent cell differentiation. Hence this work brings
to light a physiological role of IRE1 in tissue growth by connecting two essential and highly
conserved growth-regulating pathways.
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MATERIALS AND METHODS
Plant Material and High-Quality Seed Production
Seeds of the Arabidopsis thaliana ire1a (WISCDSLOX420D09) and ire1b
(SAIL_238_F07) were obtained from the Arabidopsis Biological Resource Center (Columbus,
OH, USA), and the ire1a ire1b double mutant was published previously (Chen and Brandizzi
2012). Special care was taken to produce high quality seeds to enable vigorous and reproducible
growth of seedlings on sterile culture plates without any exogenously supplied carbohydrates. WT
and ire1a ire1b seeds used for the same experiments were always produced simultaneously. Plate
grown seedlings were transplanted to potting soil and grown in standard Arabidopsis growth
chamber conditions (16 hr 150 μE light/ 8 hr dark; 50% humidity, 23°C). Plants were watered
exclusively with Hoagland’s nutrient solution every ~7 days prior to bolting and then as needed
after bolting (usually every 4 days). Prior to any silique senescence, inflorescences were staked
and tied after they could not support their own weight to prevent seed loss. Two to four weeks
after bolting, prior to any significant rosette senescence, ¼ to ½ of all formed siliques will had
senesced. Seeds were harvested by tapping or gentle gripping of the tied inflorescence, and seeds
that fell off with minimal physical disturbance were harvested and the remaining plant was
discarded. Large number of plants were grown simultaneously to compensate for smaller seed
yield per plant. Plants were not dried prior to seed harvest. In our experience seeds produced under
these conditions had initial germination rates near 100% on 0% sucrose containing plates and had
germination rates >98% on 0% sucrose after a year of storage in ideal conditions (seed envelope
in humidity controlled, dark environment).
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Plant Phenotyping
Unless otherwise stated, all sterile culture plates were made with half-strength Linsmaier
and Skoog (½ LS) basal salts containing buffer (LSP03, Caisson Labs) with 1.0% w/v agar
(NCM0236A, Neogen) added and without exogenous sucrose (or other carbohydrates). Media was
adjusted to pH 5.7 and autoclaved for 20 min under standard conditions. Media was cooled on a
stir plate until the external temperature of the bottle was 40°C, then dispensed into plates and
allowed to cool in a single layer (as opposed to stacked plates) to allow for even cooling rates.
Plates were always made the on the same day the seeds were sterilized and plated. Seeds were
sterilized with 1x wash of 100% ethanol for 30 sec, 1x wash of 50% bleach with 0.1% Tween20
for 1 min, and 6x washes with sterile double distilled water (ddH2O). Seeds were sterilized and
wet plated using a 1 ml pipette immediately after plates had cooled. We suspect that extended
incubation in ddH2O in the microcetrifuge tube after sterilization may affect germination and initial
growth rates on 0% sucrose media. After seed plating, plates were left open in the sterile hood for
3-5 min or until water from plating method evaporated. Plates were wrapped with 1-inch surgical
tape (70200534694, 3M, MN, USA) with overlapping sections on the bottom of the plate and then
wrapped in aluminum foil. Seeds were stratified at 4°C for 48 hr. Plates were incubated vertically
in Percival growth chambers in continuous 150 μE light (verified with an external PAR light meter)
for the indicated growth periods. A minimum of 5 plate replicates per experimental group were
used for each phenotyping experiment.
TORIN2 (MedChemExpress), AZD-8055(MedChemExpress), oryzalin (Sigma-Aldrich)
latrunculin b (Sigma-Aldrich) 1-naphthaleneacetic acid (NAA, Sigma-Aldrich), and oligomycin B
were dissolved in DMSO and antimycin A in 100% ethanol to 10 mM and stored at -80°C. These
chemicals were removed from the -80°C after the external temperature of the media bottle reached
143
40°C and added simultaneously to all bottles in that experiment at the required concentrations.
This was done to increase reproducibility, as the AZD-8055 was found to lose ~50% of its effect
on WT root growth inhibition (at 150 nM) when left at room temperature for 10 min in DMSO.
After the indicated incubation period plates were removed from the Percival as needed,
imaged, used for downstream analysis and then discarded. No repeated measures were performed
on individual plates (i.e. different timepoints within the same experiment were recorded from two
separate populations of seedlings). This was done to prevent possible confounding effects of
altered gravity vectors from plate movement on the ire1a ire1b root phenotype during critical
growth stages. Average shoot fresh weight was determined by excising shoots from all plants on
one plate (usually 8-10 shoots) weighing the total and dividing by number of seedlings. Root length
was measured using Image J. Root tip angles were also measured using ImageJ by placing an
approximately 3 mm line over the root tip (beginning at the apex) and using the Feret’s diameter
measurement function which was then converted into a 360° scale.
mPS-PI Staining and Meristem Cellular Organization Analysis
Modified pseudo-Schiff propidium iodide (mPS-PI) staining protocol was adapted from
Truernit et al. (2008). After the indicated growth period, whole seedlings (for 5- or 7-day old
seedling) or 2 cm excised roots sections (for 10 day old seedlings) were fixed in a 5:4:1 methanol:
ddH2O:acetic acid solution and stored at 4°C for a minimum of 12 hr and for as long as two weeks
in capped 2 dram vials. For the staining procedure seedlings/roots were treated in six well plates
to avoid mechanical damage. After removal of fixative, tissue was washed with 10 ml of ddH2O
and then treated with 5 ml of a 1% periodic acid (PA) solution for 40 min. After removing the PA
solution, tissue was washed with 10 ml of ddH2O and then treated with 5 ml of freshly made mPS-
PI working reagent (100 mM sodium metabisuphite, 0.15 M HCl, 100 μg/ml propidium iodide)
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for 40 min in the dark. After removing the mPS-PI solution samples were was washed with another
10 ml of ddH2O then submerged in 3 ml of the chloral hydrate alternative Visikol to clear the
tissue. Samples were sealed with parafilm and incubated for 2-3 days prior to confocal microscopy
analysis.
Samples were imaged using a Nikon A1 confocal microscope with 488 nm laser excitation,
and 520-720 nm emission collected. Transmitted light detection images were also collected in
parallel to assist in root tip zone identification. For each root one 20x image was collected for
accurate identification and quantification of meristem and transition zone metrics, and a 10x image
was collected for identification of transition zone and elongation zone metrics. The beginning of
the transition zone was defined as the first cell in the cortical cell layer which was >2 times as long
as the previous one (Casamitjana-Martinez et al. 2003, Di Mambro et al. 2017) . The first cortical
cell which was twice as long as it was wide was identified as the beginning of the elongation zone.
The end of the elongation zone was defined as the last cortical cell before the first visible root hair
initiation, which was identified using the transmitted light image if no root hair initiations were
visible in the same focal plane as the cortex cells. In some instances, (particularly for WT D10
samples) two images were required to fully measure the length of the elongation zone.
TOR Activity Assays
Tissue for TOR activity assays was collected from 7 day old seedlings. One biological
replicate consisted of 60 seedlings grown on two plates. The plates were removed from the Percival
and approximately 3 mm of the root tip from all 60 seedlings were quickly but carefully cut in situ
using surgical scissors. A 3 mm reference object was used to ensure accuracy. After cutting,
forceps were used to gently collect root tips into a prepared microcentrifuge tube with two glass
beads and placed in liquid nitrogen. Then a second cut was used to excise the mature root tissues
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which were collected into a second microcentrifuge tube with two glass beads. The excisions and
collection of both tissue types took less than 5 min total for each biological replicate. This process
was repeated, alternating experimental groups until all biological replicates were collected.
Continuous light was used to eliminate potential sample variation caused by circadian dependent
processes over the multiple hr required to harvest these samples by an individual researcher.
Biological replicates in Figure 4.5 were collected over 4 separate experiments.
Frozen samples were ground to a powder using a Retch Mixer Mill (Retch; Haan,
Germany) in 2x 10 sec bursts then 4x 20 sec bursts with refreezing in liquid nitrogen between
bursts and after the final grinding. To the frozen root tip tissue, 100 μls of extraction buffer (EB)
containing phosphate buffered saline (PBS) pH 7.4, plant protease inhibitor cocktail (P9599,
Sigma-Aldrich), and PhosSTOP phosphatase inhibitor (4906845001, Roche) was added to the root
tip samples and 200uls of EB to the mature root samples. Tubes were shaken and vortexed until
the sample/buffer was melted and homogenized then kept on ice (30 sec). The entire
sample/supernatant was transferred into a new tube without the beads and sequentially spun down
at 21,000x g for 5, 10, 15 min in a 4°C cooled centrifuge transferring the supernatant to a new tube
between each spin. Protein content of the root tip extracts were sufficient to load 2.5 μg of total
protein on two 12% SDS-PAGE gels. Gels were transferred to PVDF membranes (1620177, Bio-
Rad) and then blocked with 3% bovine serum albumin (BSA) in tris buffered saline plus Tween20
(TBST) for 1 hour at room temperature then, incubated with primary antibodies in TBST to detect
total S6K (αS6K1/2, AS12 1855; Agrisera) or phosphorylated-S6K (ab207399, Abcam) overnight
at 4°C. Blots were washed three times with TBST for 20 min each then incubated with secondary
HRP conjugated goat anti-rabbit antibody (A0545, Sigma-Aldrich,) for 1 hour at room
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temperature. Blots were developed using SuperSignal West Femto Kit (34096, ThermoFisher
Scientific).
EdU Pulse-Chase Experiments
The 5‐ethynyl‐2′‐deoxyuridine (EdU) pulse-chase was performed on 7-day old seedlings
grown on plates containing DMSO or 150 nm AZD-8055 using the Click-iT EdU Alexa Fluor 488
Imaging Kit (C10337, ThermoFisher Scientific). Seedlings were transferred from Petri dishes to 6
well plates containing 10 μM EdU in ½ LS media (no sucrose) and then placed back in the Percival
for 20 min. At the end of the incubation period, the ½ LS media with EdU was removed and the
seedlings were gently washed 3x with 5 ml of ½ LS media (without EdU). Half of the seedlings
were then transferred to fixation buffer (4% paraformaldehyde, 0.1% Triton X-100, 1x PBS pH
7.4) while the other half were returned to their growth plates. Plates were re-wrapped in surgical
tape and placed back in the Percival for 6 hr. Chase samples were transferred to fixation buffer
after the 6-hr chase period. Samples were then stored for between 12 hr and 1 week at 4°C. Samples
were stained and imaged in small batches (with some samples from each experimental group) on
each day over that week and no degradation of sample was found.
Click-iT reaction procedure was performed according to the manufacturer protocol with
some modifications. Seedlings were removed from the fixation buffer and washed 3 times with
3% BSA in PBS. Click-iT reaction cocktail was prepared without modification and samples were
incubated with the cocktail for 1 hr in the dark. Shorter incubation periods lead to incomplete tissue
penetration of the reaction cocktail into the meristematic zone. After incubation, samples were
washed 1x with 3% BSA in PBS, then washed 3x with PBS. Samples were then incubated with
Hoechst 33342 provided with Click-iT kit (working solution created by diluting 1 μl Hoechst
33342/ 1 ml of PBS) for 40 min in the dark. Samples were then washed with 2x washes of PBS.
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Shoot tissue was removed and roots were mounted in PBS on slides using polypropylene packing
tape to create a watertight imaging chamber of uniform depth (~70 μm). Z-series images were
collected over the entire depth of the root tips using a Nikon A1 confocal microscope equipped
with a 10x objective. Sum EdU intensity and EdU signal area were quantified in each root tip using
the Nikon NIS-Elements Advanced Research software after transformation of Z-series images into
max intensity projects and background subtraction (which was equally applied to all images).
Length to the first root hair initial (RHI) and the number of EdU+ nuclei found after the first RHI
were manually quantified using the Z-series images.
Data Reporting and Statistical Analysis
Sample sizes were the determined by maximum number of replicates which could be grown
simultaneously in a unform incubation environment (i.e. on the same shelf of a Percival) or by
maximum number of samples that could be collected by a single researcher in a reasonable time
frame.
All statistical analysis was performed using R. Two-way or three-way, between-subjects
analysis of variance (ANOVA) was conducted as needed on each data set to determine the effect
of experimental variables on test outcomes. Type III ANOVAs were used for unbalanced data sets.
For each dataset, residual analysis was performed in order to test the for the assumptions of the
ANOVAs. The Shapiro-Wilk test was used to check normality assumption and homogeneity of
variance was assessed via studentized Breusch-Pagan test and Levene’s test. In most of the data
sets the homogeneity of variances assumption was violated due to the increased variance in the
ire1a ire1b short root phenotype (see changes in standard deviation of the ire1a ire1b root length
over time in Figure 4.1C and Figure 4.S3D, E). If the assumption tests were violated (p-value
<0.05), Box-Cox or log transformations were applied to the dataset and the ANOVA re-run using
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transformed data. If the assumption checks were still violated after Box-Cox or log transformations
then weighted least squares regression was applied to the ANOVA model (referred to in the text
as: wANOVA). All datasets which were subjected to weighted least squares regression passed the
residual analysis. From the appropriate ANOVA model for each data set (standard, transformed,
or weighted least squares) pairwise comparisons (CRAN R package: emmeans) were then run with
Bonferroni adjustment applied. Significance markers in figure graphs were based on the results of
these pairwise comparison tests. Code and list of used R packages for the analysis pipeline is found
in Supplemental Data File 2.12.
To determine if there were significant differences in the coefficient of variation between
root tip angles of two different experimental groups, we utilized the asymptotic Feltz and Miller
test (Feltz and Miller 1996) as applied by Rodriguez et al. (2020) using the CRAN R package:
cvequality.
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RESULTS
IRE1 Promotes Root Growth in an Age-Dependent Manner
The reduced length of the ire1a ire1b root has been documented earlier (Chen and
Brandizzi 2012, Deng et al. 2013, Chen et al. 2014, Bao et al. 2019), but has not been studied in
detail during the transition from early seedling development to an adult vegetative state, which
corresponds to a highly active growth period. To fill this gap and establish a robust platform for
defining the role of IRE1 in organ growth, we set up a time-course analysis of ire1a ire1b growth
with measurements of phenotypic traits at 5, 7, 10, and 12 days after germination (D5, D7, D10,
D12; Figure 4.1A).
We first analyzed shoot development by quantifying the shoot fresh weight (SFW) in WT
and ire1a ire1b seedlings at these time points (Figure 4.1B). To test the effect of our experimental
variables, i.e. seedling age and genotype, on the SFW, we carried out a two-way between-subjects
analysis of variance (hereafter referred to as a ANOVA; see materials and methods for the
statistical analysis pipeline). The analysis indicated that there was not a significant interaction
between the effects of seedling age and genotype on SFW (F(3,76)= 0.344, p= 0.793). We also
found that there was not a significant effect of the individual variable (hereafter referred to as a
simple main effect) of genotype alone on SFW (F(1,76)= 0.684, p= 0.0411). However, in both WT
and ire1a ire1b genotypes, rapid and similar increases in SFW were found from D0 to D12 (Figure
4.S1A); accordingly, there was a highly significant effect of seedling age on SFW (F(3,76)= 130,
p= <2 x10-16). Together these results demonstrate that the level of IRE1 functional impairment in
the ire1a ire1b mutant does not have an effect on shoot development.
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Figure 4.1. The ire1a ire1b double mutant shows age dependent primary root growth defects.
A) Representative images of WT and ire1a ire1b mutants grown for 5, 7, 10 or 12 days. B) Shoot
fresh weight was determined by averaging WT or ire1a ire1b shoots grown in an individual plate
for each plate replicate (n=10; error bars show SD). C) Root length of individual roots was
measured using ImageJ. For Figure 4.1B and 4.1C: error bars show SD; p-values significance
markers displayed above an ire1a ire1b experimental group are pairwise comparisons to the
corresponding WT group for that specific treatment. Brackets denote other specific pairwise
comparisons. Significance markers: NS = adj. p >0.01; *= adj. p < 0.01 and >0.001;**= adj. p
<0.001 and >0.0001; ***= adj. p < 0.0001 D) Angle of the root tip away from vertical (0º) was
measured using ImageJ. Significant differences between coefficient of variation was tested using
the asymptotic Feltz and Miller test as described in materials and methods. Error bars show SD;
p-values: NS = >0.0001, **= p-value < 0.0001 and >1.0e -10, ***= p-value < 1.0 x10 -10
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We next analyzed primary root development by recording the root length of WT and ire1a
ire1b at each time point (Figure 4.1C). We attempted to utilize an ANOVA to test the effect of,
and interaction between, seedling age and genotype on root length. However, when we tested the
normality and homogeneity of variance assumptions of the ANOVA by Shapiro-Wilk test and
Levene’s test, respectively, we found that these assumptions were violated. Box-Cox and log
transformation of the data set were also attempted; however, the assumptions were still violated.
We therefore carried out a two-way between-subjects ANOVA utilizing weighted least squares
regression (hereafter referred to as a wANOVA; see materials and methods and Supplemental Data
File 2.12) to analyze primary root length. The wANOVA showed a highly significant interaction
between seedling age and genotype on root length (F(3,753)= 133, p= <2 x10-16), although the
simple main effect of genotype alone was not significant (F(1,753)= 2.08, p= 0.149). To determine
the nature of these interactions, we performed pairwise comparisons between different
experimental groups, the results of which are displayed as significance markers in the referenced
figures. At D5, we found no significant differences in average root length between WT and ire1a
ire1b (Figure 4.1C), indicating that the ire1a ire1b mutation does not affect root growth during
early seedling development. Past D5, we found dramatic increases in the rate of root growth in
WT from approximately 0.2 cm/day between D0-D5, to approximately 0.9 cm/day between D5-
D10 (Figure 4.S1B); accordingly, there was also a highly significant simple main effect of seedling
age on root length (F(3,753)= 3001, p= <2 x10-16). Noticeably, during the D5-D10 phase of
growth, the root growth phenotype of ire1a ire1b became increasingly more severe compared to
the earlier phase of growth (i.e., D0-D5). Specifically, the average ire1a ire1b root length was
significantly shorter than WT at D7, D10, and D12 (Figure 4.1C). Furthermore, while the rate of
root growth in the ire1a ire1b mutant accelerated from approximately 0.2 cm/day to approximately
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0.7 cm/day between D5-D7, it then declined to approximately 0.5 cm/day between D7-D10 (Figure
4.S1B). These results are consistent with the findings that IRE1 is required for root growth (Deng
et al. 2011, Chen and Brandizzi 2012, Chen et al. 2014, Bao et al. 2019), but also expand on these
results by demonstrating that IRE1 is required to maintain accelerated rates of primary root growth
as seedlings mature.
Concurrent with altered growth rates in maturing ire1a ire1b primary roots, we observed
that directional root growth was increasingly impaired as the seedlings matured. To analyze this,
we determined the growth vector of the primary root tip by measuring the root tip angle away from
a vertical axis (0°) in a counterclockwise orientation, such that roots growing directly downward
would have a recorded angle of 180° (Figure 4.1D). We next tested the effect of genotype and
seedling age on the average root growth vector and found that there was no significant effect of
either variable (Data File 2.1). However, we observed increasingly large differences in standard
deviation between WT and ire1a ire1b as seedlings matured (Figure 4.1D). In order to compare
the relative distribution of the collected data points, we performed asymptotic Feltz and Miller
tests to determine if there were significant differences between coefficients of variation (CoV) of
the different experimental groups (Feltz and Miller 1996). We found that the CoV was not
significantly different between WT root tip angles at D5, D7, and D10, but found a significant
difference in WT CoV between D5 and D12 (Figure 4.1D). At all the tested time points, the CoV
of ire1a ire1b root tip angles were significantly different from the corresponding WT CoV (Figure
4.1D). Furthermore, the ire1a ire1b root tip angles CoV significantly increased with seedling age
at every time point compared to the baseline measurements at D5 (Figure 4.1D). Several different
types of cell division and organization defects in the root tip can cause a short root phenotype
(Lucas et al. 2011, Petricka et al. 2012). However, defective control of the primary root growth
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vector is more likely due to aberrant cell elongation because tropic growth responses regulate
asymmetric cell elongation on one side of the root to direct organ growth in a specific direction
(Ishikawa and Evans 1993, Mullen et al. 1998, Sato et al. 2015). Therefore, the increasingly
random root growth vectors displayed by maturing ire1a ire1b support the hypothesis that IRE1
may be required for proper cell elongation.
IRE1 is Required for Proper Cell Elongation in the Root Meristem
Next, we aimed to test the hypothesis that IRE1 is required to control cell elongation and
map the role of IRE1 in the different root zones. To do so we performed modified pseudo-Schiff
propidium iodide (mPS-PI) staining (Truernit et al. 2008) of fixed WT and ire1a ire1b roots at
D5, D7, and D10 followed by confocal microscope imaging and quantitative image analysis
(Figure 4.2; Figure 4.S2, 4.S3). For each root, we identified the meristematic zone (MZ), transition
zone (TZ) and elongation zone (EZ) of the root tips according to previously published criteria
(Casamitjana-Martinez et al. 2003, Di Mambro et al. 2017). Canonically, cells divide in the MZ,
then undergo a transitional stage consisting of genomic endoreduplication and cytoarchitectural
changes in the TZ followed by cell elongation in the EZ (Scheres and Wolkenfelt 1998, Hayashi
et al. 2013). For each root tip zone, we recorded the length, the number of cells, and the average
cell length. We then performed a series of two-way wANOVAs (or ANOVAs as indicated) to test
the effects of seedling age and genotype on each these zone metrics in the MZ, TZ, and EZ. This
was done to test if there were potential interactions between genotype and seedling age other than
cell elongation in the EZ. We found significant interactions between seedling age and genotype on
the zone length, cell number and average cell length of the EZ (wANOVA; F(2,119)=37.0, p=
3.24 x10-13, F(2,119)=15.8, p= 8.48 x10-7, F(2,119)=13.2, p= 6.54 x10-6, respectively).
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Figure 4.2. Meristem organization defects in ire1a ire1b are first manifested in cell elongation
in the elongation zone.
At D7 and D10, root tips were subjected to mPS-PI staining and confocal microscopy to analyze
root tip cellular organization. A) Representative 10x images of mPS-PI stained WT and ire1a ire1b
roots at D7. The yellow line demarks the end of the meristem zone (MZ) and the beginning of the
transition zone (TZ), the red lines marks all of the cells in the elongation zone (EZ), and the white
arrow marks the first root hair initiation. For all measurements of the MZ secondary 20x images
were used to collect data. B-D) Zone length, # of cells, and cell length at D7. E) Representative
10x images of mPS-PI stained WT and ire1a ire1b roots at D10 F-G) Zone length, # of cells, and
cell length at D10. For all graphs error bars show SD; p-values significance markers displayed
above an ire1a ire1b experimental group are pairwise comparisons to the corresponding WT group
for that specific treatment. Brackets denote other specific pairwise comparisons. Significance
markers: NS = adj. p >0.01; *= adj. p < 0.01 and >0.001;**= adj. p <0.001 and >0.0001; ***= adj.
p < 0.0001.
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In addition, we also found significant interactions between the effects of seedling age and genotype
on the zone length and cell number of the MZ (wANOVA; F(2,119)=9.71, p= 1.23 x10-04,
F(2,119)=11.4, p= 2.83 x10-05, respectively) but not MZ cell size (wANOVA; F(2,119)=1.08, p=
0.342). We did not find any significant interactions between seedling age and genotype on any of
the zone metrics in the TZ (zone length: wANOVA F(2,119)=1.87, p= 0.157; cell number:
ANOVA F(2,119)=0.674, p= 0.512; cell length wANOVA F(2,119)=1.03, p= 0.361). We found
that the simple main effect of genotype alone did not have a significant effect on any zone metrics
measured in the MZ, EZ or TZ (Data File 2.2). Together, these results support that the differences
in root tip cell organization between WT and ire1a ire1b map to the MZ and the EZ in a manner
that is dependent upon the age of the seedlings. This is further supported by the evidence that at
D5, where no significant differences in primary root length were found between WT and ire1a
ire1b roots (Figure 4.1C), there were no significant differences between WT and ire1a ire1b for
any of the root tip organization metrics recorded (i.e., zone length, number of cells, cell length;
Supplemental Figure 4.2A-D). Therefore, the ire1a ire1b mutation does not affect root growth
during early seedling development (Figure 4.1).
We then focused on defining the variables underpinning the dramatic increase in WT
primary root growth rates from ~0.2 cm/ day at D5 to ~0.9 cm/day at D10; (Figure 4.S1B). We
found that the length of both the MZ and EZ roughly doubled in WT root tips during this period,
while the length of the TZ remained unchanged (Figure 4.S3A). Interestingly, we observed a
significant 1.7-fold increase in the number of cells in the MZ, while the length of MZ cells
remained unchanged, indicating that the increased size of the MZ was due to an increase in the
cell number in this zone (Figure 4.S3B, C). We also found a 1.25-fold increase in cell size and a
2-fold increase in the number of cells in the EZ at D10 compared to D5, supporting that the
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observed increased size of the EZ was due to an increase of both cell length and number in the EZ
(Figure 4.S3B). Next, we compared the root tip organization of WT and ire1a ire1b when the
mutant root phenotype is visible (i.e., D7 and D10; Figure 4.2A-H). At D7, we found that the ire1a
ire1b MZ was not significantly different from WT MZ in terms of zone length, number of cells,
and cell length (Figure 4.2B-D). However, when we examined the EZ, we found that the ire1a
ire1b EZ was significantly shorter than WT EZ, due to significantly shorter cell length (Figure
4.2B, D). Therefore, at D7, the short root phenotype of ire1a ire1b coincides with the development
of a defective EZ. At D10, we found that the ire1a ire1b MZ was significantly shorter than WT
and contained a smaller number of cells (Figure 4.2F, H). Contrary to the WT MZ, we did not
detect increase in ire1a ire1b MZ size at D10 compared to D7 (Figure 4.S2B, E), supporting that
the expected increases in MZ size do not take place in the ire1a ire1b mutant. At D10, we also
observed EZ length reduction in ire1a ire1b compared to WT (Figure 4.2F) with a significantly
reduced cell size and number (Figure 4.2G, H). In summary, while the EZ length more than
doubled between D5-D10 in WT, it did not significantly change in ire1a ire1b over this growth
period (Figure 4.S2A, D). Together these data indicate that the ire1a ire1b roots fail to obtain the
rapid rates of root growth achieved by WT plants as they mature, primarily due to defective cell
elongation in the EZ. Furthermore, we have successfully established a solid working platform to
study the mechanisms underpinning IRE1-dependent control of root growth.
The Emergence of the ire1a ire1b Root Growth Phenotype Depends on High Rates of Root Growth
We then sought to test whether the ire1a ire1b root growth phenotype exclusively depends
upon seedling age or whether it could be responsive to increased rates of root growth. To do this,
we grew seedlings under increasing photoperiod lengths and in the presence of exogenous sucrose
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supply in the media. Extending the photoperiod results in an accumulation of photosynthates (i.e.,
sucrose) (Sulpice et al. 2014) and an increase in the overall rate of rate of root growth
(Yazdanbakhsh et al. 2011). Adding sucrose to the growth medium also increases rates of root
growth (Yazdanbakhsh et al. 2011). Therefore, we grew WT and ire1a ire1b seedlings for 10 days
in three different light conditions with increasing photoperiods: 8 hr 150 μE light/ 16 hr dark, 16
hr 150 μE light/ 8 hr dark, and continuous 150 μE light (hereafter abbreviated 8/16, 16/8, and CL
respectively). In each photoperiod condition, we grew seedlings on plates containing no sucrose
or 1% sucrose (Figure 4.3).
We first measured SFW and found no significant interaction between the effects of
exogenous sucrose supply, photoperiod, and genotype via a three-way ANOVA (Figure 4.3B;
F(2,88)=0.626, p= 0.537). However, we did find that there was a significant interaction between
exogenous sucrose supply and photoperiod (Figure 4.3B; F(2,88)=10.5, p= 7.81 x10-5; complete
statistics results in Data File 2.3). We found that increased photoperiod had a dramatic effect on
the development of WT shoots, with a ~2 fold SFW increase in 16/8 light compared to 8/16, and
a further ~2 fold SFW increase in CL compared to 16/8 (Figure 4.3B). Exogenous sucrose had an
additional significant growth-promoting effect in both 8/16 and 16/8 light conditions. In both light
conditions, WT SFW was ~1.4 fold larger when grown on sucrose containing media compared to
no sucrose controls (Figure 4.3B). In CL, there was no significant effect of sucrose on SFW
accumulation (Figure 4.3B). In all conditions tested, the ire1a ire1b SFW was not significantly
different from the respective WT controls (Figure 4.3B). Therefore, IRE1 is not required for shoot
biomass accumulation regardless of the tested growth conditions.
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Figure 4.3. The emergence of the ire1a ire1b root phenotype depends on a high rate of root
growth.
A) Representative images of WT and ire1a ire1b mutants grown in the indicated conditions. B)
Shoot fresh weight was determined by averaging WT or ire1a ire1b shoots grown in an individual
plate for each plate replicate (n=10; error bars show SD). C) Root length of individual roots was
measured using ImageJ. For Figure 4.3B and 4.3C: error bars show SD; p-values significance
markers displayed above an ire1a ire1b experimental group are pairwise comparisons to the
corresponding WT group for that specific treatment. Brackets denote other specific pairwise
comparisons. Significance markers: NS = adj. p >0.01; *= adj. p < 0.01 and >0.001;**= adj. p
<0.001 and >0.0001; ***= adj. p-value < 0.0001. D) Angle of the root tip away from vertical (0º)
was measured using ImageJ. Significant differences between coefficient of variation was tested
using the asymptotic Feltz and Miller test as described in materials and methods. p-values: NS =
>0.05, **= p-value < 0.01 and >0.001, ***= p-value < 0.001
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We then measured root length and found a significant interaction between the effects of
exogenous sucrose supply, photoperiod, and genotype on primary root length (Figure 4.3C; three-
way wANOVA: F(2,397)=9.13, p= 1.32 x10-4; Data File 2.3). In WT seedlings, the root length
increased significantly in 16/8 light conditions compared to 8/16 light conditions, but no
significant differences were noted between 16/8 and CL (Figure 4.3C). We also found that
exogenously supplied sucrose significantly increased root length of WT plants grown in 8/16 or
16/8 light photoperiod conditions but not CL, similar to the effect of exogenous sucrose on SFW
(Figure 4.3B). In an analysis of root growth vector distribution under these conditions, we also
found that the WT CoV was not significantly different from any WT samples across all tested
conditions (Figure 4.3D). We then analyzed the ire1a ire1b mutant. In 8/16 light conditions, with
and without sucrose in the media, the ire1a ire1b root length and growth vector distribution were
identical to WT (Figure 4.3C, D). These results indicate that the ire1a ire1b root growth phenotype
is not strictly dependent upon age alone. In 16/8 light, the ire1a ire1b roots were slightly but
significantly smaller than WT on plates without sucrose (Figure 4.3C). Differently from WT root
length, there were no significant differences in overall length between sucrose and no sucrose-
treated ire1a ire1b roots in 16/8 light (Figure 4.3C). We also observed that 16/8 light led to
significant differences in CoV in root growth vector between WT and ire1a ire1b (Figure 4.3D).
Importantly, we also found that the addition of sucrose to the media significantly increased the
root growth vector CoV compared to the ire1a ire1b no sucrose control, indicating that exogenous
sucrose supply causes aberrant directional root growth in the ire1a ire1b mutant (Figure 4.3D). In
CL conditions, we found that ire1a ire1b roots were significantly shorter than both WT roots
grown in CL and ire1a ire1b roots grown in 16/8 light conditions. Furthermore, similar to the 16/8
light conditions, the roots of ire1a ire1b grown either on sucrose-containing plates or no sucrose
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controls in CL were similar in length (Figure 4.3C). The ire1a ire1b root growth vector CoV was
significantly increased by exposure to CL compared to the 16/8 conditions, confirming that
prolonged photoperiod leads to aberrant directional root growth in the ire1a ire1b mutant. On the
whole, these data indicate that, while prolonged photoperiod and sucrose availability equally
promote shoot growth of WT and the ire1a ire1b mutant, IRE1 is absolutely required to reach the
maximum rates of root growth afforded by extended photoperiod and increased carbohydrate
availability.
TOR Inhibition Rescues the ire1a ire1b Primary Root Growth Phenotype
It has been documented that plant TOR integrates light and carbohydrate availability
signals to control growth (Li et al. 2017), and that hyper-activation of TOR can lead to a short root
phenotype (Cao et al. 2019). Based on the negative effect of pro-growth signals (i.e., prolonged
photoperiod and exogenous sucrose supply) on ire1a ire1b root growth, we hypothesized that TOR
could be hyperactive in ire1a ire1b and, therefore, that the IRE1 root growth phenotype might be
alleviated by TOR inhibition. As a first step to test this hypothesis, we performed our growth
phenotyping assays (Figures 4.1, 4.2), but also supplemented growth media with the TOR inhibitor
AZD-8055 (hereafter referred to as AZD; Cao et al. 2019) or DMSO control vehicle. We first
conducted a test using concentrations of AZD ranging from 50 to 200 nM in the culture media
(Figure 4.S3). At a 150 nM concentration, AZD had a slight inhibitory effect on WT root length
in line with previous results (Montané and Menand 2013, Cao et al. 2019), and significantly altered
ire1a ire1b root length phenotype compared to DMSO control. (Figure 4.S3). Therefore, for our
analyses we proceeded to use 150 nM AZD in the growth medium to induce a low-level inhibition
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of TOR compared to the more commonly applied applications of 1 μM or more AZD (Montané
and Menand 2013, Schepetilnikov et al. 2017, Barrada et al. 2019, Zhuo et al. 2020).
We then performed a time-course analysis of ire1a ire1b root growth from D7-D12 on
growth media containing either DMSO vehicle or 150 nM AZD (Figure 4.4A). We found a small
effect of AZD on WT root growth. We then conducted ANOVAs to test for an interaction between
seedling age, AZD effect, and genotype on seedling growth phenotypes (i.e. SFW and root length).
While we found no significant interactions between these variables on average SFW (three-way
ANOVA: F(2,84)=0.150, p=0.861; Figure 4.4B), we did find a highly significant interaction
between seedling age, AZD treatment, and genotype on primary root length (three-way wANOVA:
F(2,887)=67.253, p= <2.2 x10-16; Figure 4.4C). Similar to our earlier results (Figure 4.1), we
observed strong, age-dependent, root growth defects in the ire1a ire1b mutant in the DMSO
conditions (Figure 4.4C, D). However, when ire1a ire1b was grown in the presence of AZD, at
D7 and at D10 we found that the average primary root length was not significantly different from
WT (Figure 4.4A, C). At D12, the average primary root length of AZD-treated ire1a ire1b was
slightly but significantly smaller compared to WT; however, the AZD-treated ire1a ire1b roots
were nearly 1.5 cm longer than their respective DMSO controls at this time point (Figure 4.4C).
In an analysis of directional root growth, we found that, when ire1a ire1b was grown in the
presence of AZD, there were no significant differences in the ire1a ire1b root CoV compared to
AZD-treated WT at D7 and D10 (Figure 4.4D). At D12, while the CoV of AZD-treated ire1a ire1b
root tip angles were significantly different from AZD-treated WT, we found that the AZD-treated
ire1a ire1b root tip angles were significantly less variable than DMSO-treated ire1a ire1b root tip
angles at D12 (Figure 4.4D). These results support the hypothesis that inhibition of TOR activity
in ire1a ire1b rescues the short root and directional growth phenotypes of this mutant. To confirm
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Figure 4.4. TOR inhibition rescues ire1a ire1b root growth phenotype.
A) Representative images of WT and ire1a ire1b mutants grown for 7,10 or 12 days on plates
containing 150 nM AZD-8055 or DMSO control. B) Shoot fresh weight was determined by
averaging WT or ire1a ire1b shoots grown in an individual plate for each plate replicate (n=10;
error bars show SD). C) Root length of individual roots was measured using ImageJ. For Figure
4.4B and 4.4C: error bars show SD; p-values significance markers displayed above an ire1a ire1b
experimental group are pairwise comparisons to the corresponding WT group for that specific
treatment. Brackets denote other specific pairwise comparisons. Significance markers: NS = adj.
p >0.01; *= adj. p < 0.01 and >0.001; **= adj. p <0.001 and >0.0001; ***= adj. p-value < 0.0001
. D) Angle of the root tip away from vertical (0º) was measured using ImageJ. Significance
differences between coefficient of variation was tested using the asymptotic Feltz and Miller test
as described in materials and methods. p-values: NS = >0.0001, **= p-value < 0.0001 and >1.0e -
10
, ***= p-value < 1.0 x10 -10.
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these results, we tested an additional chemical inhibitor of TOR activity, TORIN2 (Montané and
Menand 2013, Cao et al. 2019), on WT and ire1a ire1b. Similar to AZD treatment, 200 nM
TORIN2 rescued both the short root and root tip angle phenotypes of the ire1a ire1b mutant
(Figure 4.S5).
We then tested whether the rescue of the ire1a ire1b root phenotype was specific to TOR
inhibition or a general effect of slower root growth rates, which could be brought about by other
chemical inhibitors or hormones. To do so, we first grew WT and ire1a ire1b on media containing
low concentrations mitochondrial respiration inhibitors and cytoskeletal inhibitors, which are
known to affect negatively the growth of WT roots (Van Aken et al. 2016, Renna et al. 2018, Cao
et al. 2019). In all cases, we found that the treatments led to significant root growth inhibition in
the ire1a ire1b mutant and not a rescue effect, indicating that general inhibitors of root growth are
uninfluential to the rescue of the ire1a ire1b phenotype (Figure 4.S6, 4.S7). Next, because of the
similarities between the ire1a ire1b root phenotype and root morphology phenotype induced by
treatment with exogenous auxin (Evans et al. 1994, Fendrych et al. 2018), the connection between
induced ER stress and auxin signaling (Chen et al. 2014), and the previous findings that auxin
activates TOR (Schepetilnikov et al. 2017, Retzer and Weckwerth 2021), we tested whether the
ire1a ire1b phenotype may be related to a possible auxin-dependent TOR hyper-activation. In the
absence of a commercially available auxin synthesis or signaling inhibitor, we sought to test
whether the auxin-dependent root growth inhibition of WT could be rescued by TOR inhibition.
We found that TOR inhibition did not rescue growth inhibition induced by the synthetic auxin 1-
naphthaleneacetic acid (NAA), but rather that the effects of AZD and NAA were additive (Figure
4.S8). We also found that ire1a ire1b seedlings treated with AZD responded to NAA identically
to WT plants, supporting that, in the context of root growth inhibition, TOR and auxin most likely
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act independently (Figure 4.S8). Together, these results that TOR inhibition rescues the short root
and misdirected primary root growth vector phenotypes of the ire1a ire1b mutant indicate that
TOR activity strongly and specifically contributes to the root growth phenotypes of the ire1a ire1b
mutant.
TOR is Hyperactive at the Growing Primary Root Tips of the ire1a ire1b Mutant
Next, we sought to map the endogenous alterations to TOR activity in actively growing
ire1a ire1b roots. To do this we utilized a common immunoblot based assay of phosphorylated
Serine-Kinase 6 (phospho-S6K), a conserved target of TOR kinase activity (Xiong et al. 2013).
We excised approximately 3 mm from 60 root tips and pooled these tips to create an individual
biological replicate, and we executed 11 independent biological replicates. The remaining mature
root tissue from each root was also excised and pooled. We performed this analysis using 7-day-
old seedlings to avoid the possibly confounding effects of the more severe morphological
differences between WT and ire1a ire1b observed at D10. We compared the relative phospho-
S6K signal ratio, which was derived from detection of phospho-S6K over total S6K signal
(αS6K1/2), and subsequent normalization to the average WT-DMSO ratio for each individual blot
(Figures 4.5, 4.S8). We used WT and ire1a ire1b seedlings grown in DMSO or AZD-containing
media. We then tested the effects of genotype and AZD treatment on the phospho-S6K signal ratio
in root tips using a two-way wANOVA. While we found that there was no significant interaction
between these variables on phospho-S6K signal ratio (F(1,40)= 1.65, p= 0.206), the simple main
effects of genotype and AZD treatment on the phospho-S6K signal ratio were individually
significant (F(1,40)=9.58, p= 3.59 x10-3; F(1,40)= 16.7, p= 2.02 x10-4, respectively). We found
that the ire1a ire1b root tips had a ~2-fold higher S6K-ratio compared to WT in DMSO
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Figure 4.5. TOR is hyperactive in the ire1a ire1b mutant root tips but not in the mature root.
A) Representative immunoblot assay to determine relative S6K phosphorylation levels. Antibodies
against total S6K (αS6K1/2) or Phosphorylated-S6K (Phos-S6K) were used against total soluble
protein extracted from excised WT or ire1a ire1b root tips grown for 7 days on media containing
AZD-8055 or DMSO control (see materials and methods). Relative signals (Phos-S6K/ αS6K1/2)
in each experimental group was normalized to WT DMSO control (n=11). B) Same immunoblot
method used in A) but used against total soluble protein extracted from excised mature WT or
ire1a ire1b root tissues grown for 7 days on media containing AZD-8055 or DMSO control (n=9).
For all graphs error bars show SD; p-values significance markers displayed above an ire1a ire1b
experimental group are pairwise comparisons to the corresponding WT group for that specific
treatment. Brackets denote other specific pairwise comparisons. Significance markers: NS = adj.
p >0.05; *= adj. p < 0.05 and >0.005;**= adj. p <0.005 and >0.0005; ***= adj. p < 0.0005 See
Figure 4.S8 for full blot images and Ponceau’s stain loading controls.
conditions (Figure 4.5A). As expected, AZD treatment led to significantly lower S6K-ratio in WT
root tips (0.7-fold change) compared to DMSO. The AZD treatment also significantly reduced the
S6K-ratio of ire1a ire1b root tips compared to DMSO control (Figure 4.5A). The S6K-ratio of
AZD-treated ire1a ire1b root tips was not significantly different from AZD-treated WT (Figure
4.5A). When we analyzed the mature root tissues (Figure 4.5B), we found a significant effect of
AZD treatment on the relative phospho-S6K signal ratio (two-way ANOVA: F(1,32)= 24.9, p=
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2.03 x10-5). However, the genotype did not have a significant effect on the relative phospho-S6K
signal ratio in mature root tissues (F(1,32)= 1.26, p= 0.269), and there were no significant
differences between WT and ire1a ire1b S6K-ratios in mature root tissues in either DMSO or AZD
treatments (Figure 4.5B). Together these results indicate that the loss of IRE1 leads to increased
TOR activity in the root tips but not in mature tissues. Therefore, IRE1 is necessary to maintain
proper TOR activity levels specifically in rapidly developing root tips.
TOR Inhibition Rescues the ire1a ire1b Cell Elongation Phenotype at the Root Meristem
The spatial specificity of TOR hyper-activation verified in growing root tips but not in
mature tissues of the ire1a ire1b roots (Figure 4.5) prompted us to establish the cellular
consequences of the TOR hyper-activity in the ire1a ire1b mutant. To do so, we performed mPS-
PI analysis of root tips from WT and ire1a ire1b plants grown on DMSO or AZD-containing media
(Figure 4.6A). We performed our analysis at D10 in order to test the effects of TOR inhibition on
the strong defects in cell elongation in the EZ as well as the moderate defects in the MZ, which
only were found at D10 (Figures 4.2E-H). In WT plants grown on AZD-containing media, we
observed a small but significant decrease in the number of cells in the MZ, and a small but
significant increase in the number of cells in the TZ (Figure 4.6C), consistent with previously
published results of TOR inhibition on root tip meristem organization (Montané and Menand
2013). We then performed a series of two-way wANOVAs (or ANOVAs as indicated) to test the
effects of AZD treatment and genotype on each these zone metrics in the MZ, TZ and EZ. We
found significant interactions between AZD treatment and genotype on zone length, cell number
and average cell length of the EZ (wANOVA; F(1,76)= 62.8, p= 1.51 x10-11, F(1,76)= 21.4, p=
1.51 x10-5, F(1,76)= 34.1, p= 1.21 x10-7, respectively). We also found significant interactions
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Figure 4.6. Meristem organization defects in ire1a ire1b are rescued by TOR inhibition.
At D10, root tips grown on DMSO or AZD media were subjected to mPS-PI staining and confocal
microscopy to analyze root tip cellular organization. A) Representative 10x images of mPS-PI
stained WT and ire1a ire1b roots The yellow line demarks the end of the meristem zone (MZ) and
the beginning of the transition zone (TZ), the red lines marks all of the cells in the elongation zone
(EZ), and the white arrow marks the first root hair initiation. For all measurements of the MZ
secondary 20x images were used to collect data. B-D) Zone length, # of cells, and cell length at
D10 in roots gown on DMSO or AZD containing media. For all graphs error bars show SD; p-
values significance markers displayed above an ire1a ire1b experimental group are pairwise
comparisons to the corresponding WT group for that specific treatment. Brackets denote other
specific pairwise comparisons. Significance markers: NS = adj. p >0.01; *= adj. p < 0.01 and
>0.001;**= adj. p <0.001 and >0.0001; ***= adj. p-value < 0.0001
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between the effects of AZD treatment and genotype on the zone length and cell number of the MZ
(wANOVA; F(1,76)= 24.2, p= 4.80 x10-6, F(1,76)= 43.9, p= 4.39 x10-9, respectively), and a
marginally significant interaction on MZ cell length (F(1,76)= 6.44, p= 0.0131). We did not find
any significant interactions between seedling age and genotype on any of the zone metrics in the
TZ (wANOVA; zone length: F(1,76)=1.87, p= 0.157; cell number: F(1,76)=0.674, p= 0.512; cell
length F(1,76)=1.03, p= 0.361). On the whole, these results demonstrate that the zone metrics
exhibiting significant interactions between seedling age and genotype (Figure 4.2) also showed
significant interactions between AZD treatment and genotype.
We then narrowed our analysis to determine the nature of the interaction between AZD
treatment and genotype in the MZ and EZ by performing pairwise comparisons. In addition to the
small but significant decrease in MZ cell number and increase in TZ cell number of the WT root
tips treated with AZD, we also found that the EZ length was significant shorter in AZD-treated
WT, compared to DMSO controls (Figure 4.6B). Interestingly, we observed that while the number
of EZ cells remained unchanged, the average cell length in the EZ of the AZD-treated WT root
tips was significantly smaller than DMSO controls, indicating that the decreased size of the EZ
was specifically due to a decrease in cell length in this zone (Figures 4.6C, D). This suggests that
TOR activity is required to increase rates of cell elongation, consistent with previous reports (Yuan
et al. 2020). However, in net contrast, we found that AZD inhibition of TOR in the ire1a ire1b
mutant led to an increase in the zone length and number of cells in the both the MZ and EZ
compared to DMSO-treated ire1a ire1b controls (Figures 4.6B, C). Additionally, we also verified
an increase in cell size in the EZ of AZD-treated ire1a ire1b (Figure 4.6D). In every measured
zone metric of the root tip organization, we found no significant differences between AZD-treated
WT and AZD-treated ire1a ire1b root tips (Figure 4.6), consistent with an AZD-mediated rescue
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of the ire1a ire1b root growth phenotype verified at D10 (Figure 4.4). These results support that,
while basal TOR activity is needed to increase rates of cell elongation, TOR hyper-activity in the
ire1a ire1b mutant is detrimental to elongation processes.
TOR Hyper-activity in the ire1a ire1b Mutant Promotes Cell Differentiation Rather than Cell
Proliferation.
Based on the results that TOR hyper-activity in the ire1a ire1b mutant has a detrimental
effect on cellular elongation (Figure 4.6), and on previous published reports that after cell
elongation TOR activity in necessary to actuate root hair growth in the differentiation zone (also
referred to as the maturation zone; Retzer and Weckwerth 2021), we hypothesized that a
hyperactive TOR may lead to increased rates of differentiation, which would halt cell elongation.
Therefore, we sought to test whether TOR hyper-activity in the ire1a ire1b mutant affected rates
of cell proliferation, which have already been associated with TOR activity (Xiong et al. 2013), or
led to increased rates of cell differentiation. We utilized 5‐ethynyl‐2′‐deoxyuridine (EdU; a
thymidine analog that marks cell cycle entry into S-phase; Hayashi et al. 2013) to perform a pulse-
chase experiment of labelled nuclei in intact roots. This would allow us to determine the rate of
DNA synthesis at the root tip as a measure of cell proliferation and would also allow us to track
labeled meristematic cells over time to determine relative rates of cell differentiation, which is
marked by root hair initiation (Dolan and Davies 2004). At D7, whole seedlings grown on DMSO
or AZD-containing media were treated in liquid ½ LS media containing EdU for 20 min. Subsets
of seedlings were then immediately fixed (0 hr; Figure 4.7) while the rest of the seedlings were
returned to their original ½ LS plates for an additional 6 hr allowing for further root growth before
fixation (6 hr; Figure 4.7). Z-series of consecutive images for each root tip were then collected by
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confocal microscopy, and assembled into max intensity projections (Figure 4.7A). For each root
dataset, the sum EdU intensity (Figure 4.7B) and area covered by EdU signal (hereafter EdU signal
area; Figure 4.7C) were quantified after background subtraction, which was identical for each
image. With this experimental set up, we then sought to determine if there were differences in cell
proliferation between WT and ire1a ire1b under conditions of TOR inhibition. We therefore tested
the effect of EdU-chase time, genotype, and AZD treatment individually on sum EdU intensity,
and EdU signal area via three-way wANOVAs We did not establish a significant interaction
between chase time, genotype and AZD treatment on the sum of EdU intensity (three-way
wANOVA: F(1,196)= 0.160, p= 0.690), and found only a marginally significant simple main
effect of genotype or AZD treatment alone on sum EdU intensity (F(1,196)= 5.93, p= 0.0157,
F(1,40)= 2.83, p= 0.0937, respectively). In contrast, we did find a highly significant effect of chase
time on sum EdU intensity (F(1,196)= 122, p= <2.2 x10-16). Pairwise comparisons of these values
did not indicate any significant differences between WT and ire1a ire1 in DMSO or AZD
treatment, indicating that the IRE1 mutation and low-level TOR inhibition do not have a significant
effect on the rates of EdU incorporation and, therefore, cell proliferation (Figure 4.7B). However,
the AZD treatment altered the size of the root region marked by the EdU signal. This region
appeared more confined in both WT and ire1a ire1b mutants in AZD conditions compared to
DMSO (Figure 4.7A). While there was only a marginally significant interaction between chase
time and AZD treatment on EdU signal area (F(1,196)= 5.33, p= 0.0219), pairwise comparisons
demonstrated that EdU signal area was significantly lower in AZD-treated WT and ire1a ire1b at
6 hr chase compared to their respective DMSO controls (Figure 4.7C). Together these results
indicate that the loss of IRE1 does not significantly compromise the rate of cell proliferation;
however, AZD treatment may have a marginal negative effect
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Figure 4.7. TOR hyper-activity in the ire1a ire1b mutant promotes differentiation rather
than cellular proliferation.
Seedlings grown for 7 days on media containing DMSO or AZD-8055 were treated briefly with
EdU and immediately fixed (0 hours) or returned to plates and allowed to grow for a further 6 hr
(6 hours). See materials and methods for full analysis methods. A) Composite image compiled
from representative 10x max projection images of root tips from all treatments. B) Sum EdU
intensity and C) EdU signal area determined from max projection images of individual roots. D)
Diagrams of vertical and horizontal cross sections of an Arabidopsis root tip highlighting the
epidermal and cortex cell layers above the first RHI where EdU positive nuclei were counted. E)
Length to the first RHI and F) number of differentiated EdU+ nuclei were determined for each
root by manual assessment of z-series images. For all graphs error bars show SD; p-values
significance markers displayed above an ire1a ire1b experimental group are pairwise comparisons
to the corresponding WT group for that specific treatment. Brackets denote other specific pairwise
comparisons. Significance markers: NS = adj. p >0.01; *= adj. p < 0.01 and >0.001; **= adj. p
<0.001 and >0.0001; ***= adj. p-value < 0.0001.
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on differentiation of newly generated cells away from the MZ over time.
We next aimed to test the effect of IRE1 on the rates of cell differentiation. To do this, we
manually analyzed the Z-series images for each root in the 6-hr chase sample pool to identify along
the root tip axis the first cells bearing root hairs (i.e., first root hair initials ; RHI), as markers for
tissue differentiation (Figures 4.7D, E; Dolan and Davies 2004). We then counted the number of
EdU positive (+) nuclei in the cortex or epidermal cells past the first RHI (hereafter referred to as
differentiated EdU+ cells; Figures 4.7D, F). Nuclei that were uniformly labeled (corresponding to
labeling during early S-phase) and nuclei that displayed a speckled pattern (corresponding to
labeling during late S-phase) were both counted as EdU+ (Hayashi et al. 2013). We specifically
counted EdU+ nuclei in the cortex and epidermal cell layers because they are unambiguously
identifiable based on their size and because they only undergo cell division in the MZ (Dolan and
Costa 2001). We found that there was a significant interaction between AZD treatment and
genotype on the length to the first RHI (two-way ANOVA: F(1,113)= 7.92, p= 5.76 x10-3 ; Figure
4.7E) as well as significant simple main effects of AZD treatment and genotype alone (F(1,113)=
12.3, p= 6.38 x10-4; F(1,113)= 12.6, p= 5.48 x10-4, respectively). We also established that the root
tip length to first RHI was significantly shorter in ire1a ire1b than WT in DMSO conditions. AZD
treatment significantly shortened the length to first RHI in WT but not in ire1a ire1b, which
remained unchanged (Figures 4.7A, F). This pattern matches the D7 root growth phenotype where
AZD-treated WT and ire1a ire1b roots have primary root lengths that are identical to the ire1a
ire1b roots grown in DMSO (Figures 4.4A, C).
While we found that the outward morphological characteristics and rates of cell
proliferation were similar between DMSO and AZD-treated ire1a ire1b roots, the number of
differentiated EdU+ cells were markedly different (Figure 4.7E). Specifically, we found a
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significant interaction between AZD treatment and genotype on the number of differentiated EdU+
cells (two-way wANOVA: F(1,113)= 13.4, p= 3.81 x10-4), as well as significant simple main
effects of AZD treatment and genotype alone (F(1,113)= 22.0, p= 7.84 x10-6; F(1,113)= 20.5, p=
1.51 x10-5, respectively). In the ire1a ire1b root tips, which had higher levels of TOR activity in
DMSO conditions (Figure 4.5), we found that the number of differentiated EdU+ cells was nearly
2-fold higher than WT. We also established that AZD treatment led to a significant reduction in
the number of differentiated EdU+ cells in both WT (~2 fold) and ire1a ire1b (~4 fold), such that
there was not a significant difference between WT and ire1a ire1b in AZD conditions. Together
these results support that an IRE1-dependent limitation of TOR activity is required to prevent
uncontrolled increases in the rate of cell differentiation from the meristem in the shootward
direction.
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DISCUSSION
Loss-of-function mutations of IRE1, the most conserved master regulator of the UPR
across eukaryotes, cause a wide variety of defects in growth and development in plants and
metazoans (Chen et al. 2014, Kim et al. 2018, Bao et al. 2019, Mishiba et al. 2019, Mitra and
Ryoo 2019). In metazoans, some of the causative relationships between the loss of IRE1 activity
and developmental defects have been defined (Mitra and Ryoo 2019). In marked contrast in plants,
prior to this work, a functional connection between the loss of IRE1 and developmental defects
had yet to be made. To address this significant gap, we performed a detailed analysis of the
tractable ire1a ire1b model, which exhibits a distinctive defect in primary root growth. We found
that the development of ire1a ire1b root growth defects are specifically brought on by age-related
increases in rates of organ growth, which are most likely tied to increased availability of
carbohydrates as the plants mature. We established that such defects primarily manifest through
ineffective actuation of cellular elongation at the root tip, leading to shorter roots that do not
maintain gravity-driven growth vectors. We found that in actively growing root tips of the ire1a
ire1b mutant, TOR activity is significantly elevated compared to WT, and that low-level inhibition
of TOR restores the ire1a ire1b root growth phenotype to WT levels. We further demonstrated
that such TOR hyper-activation drives increased rates of cell differentiation at the root tips.
Therefore, our work demonstrates that IRE1 controls TOR activity in specific developmental
stages in physiological conditions of growth. In addition to supporting the canonical role for TOR
as a driver of cell proliferation in the root tip, our results also reveal a new role of TOR in cell
differentiation whose functional homeostasis depends on IRE1 availability.
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IRE1 Regulates TOR Activity in a Multicellular Eukaryote
In mammalian models, some connections between mammalian TOR (mTOR) activity and
IRE1 regulation have been found previously (Pfaffenbach et al. 2010, Kato et al. 2012, Kato et al.
2013, Young et al. 2013, Li et al. 2014, Shanware et al. 2014, Sanchez-Alvarez et al. 2017). In
cases of light-induced retinal injury, hepatic lipotoxicity, chemically induced ER stress, cadmium
toxicity, and lipid-starved solid tumor microenvironments, mTOR activity induces cell apoptosis
either through aggravation of general ER stress (Pfaffenbach et al. 2010, Li et al. 2014), or through
specific activation of the IRE1-induced apoptosis via the IRE1-JNK kinase signal cascade (Kato
et al. 2012, Kato et al. 2013, Young et al. 2013). Significantly, in all of these studies modulation
of IRE1 activity is a downstream effect of mTOR activation. In this work, we show that in actively
growing root tips of the ire1a ire1b mutant TOR is hyperactive (Figure 4.5). These results, in
conjunction with the observations that low-level TOR inhibition completely rescues all aspects of
the ire1a ire1b root growth phenotype (Figures 4.4, 4.6, 4.7), lead us to conclude that not only
does IRE1 control TOR activity, but this is the primary pathway by which IRE1 promotes proper
organ biogenesis. To our knowledge, the results presented in this work are the first to demonstrate
that IRE1 regulates TOR activity in any model organism, and that such activity occurs in the
absence of induced ER stress.
IRE1 is Necessary to Control TOR Activity at Tissue- and Development-Specific Levels
Previous reports indicated that IRE1 contributes to Arabidopsis growth and development on a
broad level and have repeatedly demonstrated that the ire1a ire1b mutant has a short root
phenotype (Chen and Brandizzi 2012, Deng et al. 2013, Mishiba et al. 2019, Pu et al. 2019).
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However, a detailed dissection of events leading to this phenotype at the cell- and tissue-level and
an accounting of how variation in standard growth conditions could alter it were lacking. In our
work, we have demonstrated that the increased rates of root growth maintained in WT plants as
they mature cannot be actuated in the ire1a ire1b mutant (Figure 4.1). We established that this
primary defect is restricted to the EZ and secondarily to the MZ as a function of seedling age
(Figure 4.2), and is concurrent with hyper-activation of TOR in the ire1a ire1b mutant specifically
at the root tips (Figure 4.5). At the initial phase of rapid root growth (day 7), we found that the
ire1a ire1b EZ exhibits less and smaller cells compared to WT (Figure 4.2), but we did not observe
any significant differences in cell size and proliferation rate in the ire1a ire1b MZ compared to
WT (Figures 4.2, 4.7). Therefore, our results argue that, in early developmental stages in WT,
IRE1 is necessary to maintain homeostatic levels of TOR activity in the EZ but not in the MZ. At
the later stages of the ire1a ire1b phenotype development (i.e. day 10), we found that the ire1a
ire1b MZ is shorter, and has not increased in size like the WT MZ (Figure 4.2). Fascinatingly, we
also found that the reduction in the number of cells in the ire1a ire1b MZ is reverted to WT levels
by chemical inhibition of TOR (Figure 4.6). Based on these results, we conclude that TOR activity
levels may have opposite effects in the MZ during the rapid growth of the root tip: basal TOR
activity promotes cell proliferation in MZ, as reported earlier (Xiong et al. 2013, Li et al. 2017),
but TOR hyper-activity may also dampen it, as demonstrated in this work. In connection with our
ire1a ire1b root phenotypic results, we infer that IRE1 activity is required to control TOR activity
especially at stages of development requiring increased cell proliferation and elongation. Although
the underlying mechanisms on the MZ size control exerted by IRE1 through TOR are yet unknown,
our data support that IRE1 is absolutely required to antagonizes TOR hyper-activation to maintain
proper organ development.
177
IRE1-Dependent Repression of TOR is Independent from the Unconventional Splicing of bZIP60
In conditions of induced ER stress, IRE1 splices the mRNA of its effector TF, bZIP60
(Nagashima et al. 2011). It is well established that in physiological conditions of growth, a bzip60
complete loss-of function mutant does not exhibit a short root phenotype (Nagashima et al. 2011,
Chen and Brandizzi 2012, Moreno et al. 2012). Based on our results that ire1a ire1b has a marked
root length phenotype (Figure 4.1) and the notion that an ire1a ire1b bzip60 triple mutant is
phenotypically indistinguishable from ire1a ire1b under normal growth conditions (Ruberti et al.
2018), we deduce that the molecular mechanisms by which IRE1 controls root development and
TOR activity are independent from a functional interaction with bZIP60. The loss of the
mammalian homolog of bZIP60, XBP1, compromises tissue development in a similar way to IRE1
loss-of-function mutations; for example, both mutations lead to defective embryonic liver
development (Mitra and Ryoo 2019). Hence, the results that in physiological conditions of growth
a bzip60 mutant does not exhibit visible phenotype highlight a functional divergence between the
IRE1-dependent TFs XBP1 and bZIP60 in organ development across kingdoms.
Metazoan and plant IRE1 proteins are known to cleave transcripts other than XBP1 or
bZIP60 through RIDD (Hollien et al. 2009, Mishiba et al. 2013). Therefore, we hypothesize that
under high growth pressure due to prolonged photoperiod and abundant carbohydrate supply,
conditions that we selectively applied in our work (Figure 4.3), IRE1-mediated RIDD of a single
or multiple RNA targets could lead to a strong limitation or cap on TOR activity in certain tissue
types. Due to the fact that known Arabidopsis IRE1-RIDD targets have thus far been identified
exclusively in ER stress conditions using RNA derived from whole seedlings (Mishiba et al. 2013),
the identification of the intermediate targets between IRE1 and TOR under physiological
conditions in actively growing root tissues remains an exciting topic for future study.
178
In Arabidopsis, TOR activity depends on a variety of cues (e.g., mitochondrial respiration,
auxin, amino acids (Li et al. 2017, Schepetilnikov et al. 2017, Shi et al. 2018, Burkart and
Brandizzi 2020). Hence potential RIDD targets may affect one or several of these pathways.
Nonetheless, based on our observations that link the ire1a ire1b phenotype to photoperiod and
carbohydrate-related increases in rates of root growth (Figure 4.3), we speculate that the most
probable target may be associated with IRE1 and regulation of mitochondrial respiration. This is
predicated by the evidence that the assembly of the mammalian TOR complex 1 (mTORC1)
depends on the TTT-RUVBL1/2 complex, which leads to activation of TOR through formation of
TOR obligate dimers (Kim et al. 2013). The activity of the TTT-RUVBL1/2 complex is in turn
strongly dependent on mitochondrial ATP generation through respiration. ER functions and
mitochondrial metabolism are closely linked in metazoan models primarily through calcium
delivery to mitochondria via the ER (Szabadkai et al. 2006, Kaufman and Malhotra 2014,
Hirabayashi et al. 2017, Rieusset 2018, Gutiérrez et al. 2020). In Arabidopsis, IRE1 activity has
been tied to a regulation of mitochondrial stress responses, albeit under induced ER stress
situations (Ng et al. 2013). Therefore, it is possible that in Arabidopsis, IRE1 may regulate
mitochondrial respiration in rapidly growing tissues under physiological conditions.
TOR Activity Regulates Cellular Differentiation and Elongation in Actively Growing Arabidopsis
Root Tips
Previous work supports that TOR activity can promote cell elongation. Specifically, TOR
was shown to promote accumulation of the auxin efflux transporter PIN2 at the root meristem
through a direct protein-protein interaction, leading to increased size of cells in the EZ without
affecting cell proliferation (Yuan et al. 2020). In our work, we have demonstrated that low-level
179
TOR inhibition of rapidly growing WT roots leads to a small reduction root length (Figure 4.4,
Day 7) and was sufficient to significantly impact TOR activity at the root tip (Figure 4.5).
However, this minimal TOR inhibition does not strongly affect overall rates of cell proliferation
and instead leads to smaller cells in the EZ and a reduced rate of cell differentiation (Figures 4.6,
4.7). In the ire1a ire1b root tips, we found that TOR hyper-activity coincided with increased rates
of cell differentiation compared to WT, which were reduced to WT levels with low-level TOR
inhibition (Figure 4.7).
A plausible model to illustrate the effect of ire1a ire1b mutation and TOR inhibition on
cell differentiation is presented in Figure 4.S9. In this model, TOR activity is needed in the later
stages of cell maturation to actuate cell differentiation programs in addition to the known roles of
TOR in promoting cell proliferation. In contrast with the effect on cell differentiation, which
responds in a linear manner to TOR activity, it seems that cell elongation has a biphasic response
to TOR activation (Figure 4.S9). Similar to cell differentiation, our data support that a basal level
of TOR activity is also required to promote cell elongation. However, at high levels of TOR
activity cell elongation is negatively impacted and is rescued by TOR inhibition. We speculate that
under TOR hyper-activity the increased rate of cellular differentiation negatively impacts the time
that cells have to undergo cell elongation processes prior to root hair initiation, leading to a smaller
maximum cell size in the EZ cells. Together these results provide further evidence that TOR has
significant effects in determining cell fate outside of cell proliferation in the MZ and demonstrate
that IRE1 is an upstream regulatory factor of TOR in these contexts. Therefore, this study provides
an important foundation for future work by uncovering a novel link between two ancient
eukaryotic signaling pathways. With this tractable ire1a ire1b model further investigation could
180
yield important information related to UPR and TOR dependent control over multicellular
organism development.
181
ACKNOWLEDGEMENTS
We acknowledge support by the Chemical Sciences, Geosciences and Biosciences
Division, Office of Basic Energy Sciences, Office of Science, U.S. Department of Energy (award
number DE-FG02-91ER20021) for infrastructure, NASA (award 80NSSC19K0707), NIH
GM136637, and a fellowship from Michigan State University under the Training Program in Plant
Biotechnology for Health and Sustainability (T32-GM110523). We would also like to thank the
Center for Statistical Training and Consulting at Michigan State University for their kind
assistance and for providing the necessary code to perform the ANOVA tests utilizing weighted
least squares regression.
182
APPENDIX
183
Figure 4.S1. Rate of shoot fresh weight accumulation, and rate of primary root growth for
data displayed in Figure 4.1.
A) Average shoot fresh weight values from Figure 4.1B were reprocessed to show the rate of shoot
fresh weight accumulation for a specific growth period (value= average shoot fresh weight
accumulated during a growth period/ days in that growth period). B) Average root length values
from Figure 4.1C were reprocessed to show the rate of primary root length increases for a specific
growth period (value= average root length increases accumulated during a growth period/ days in
that growth period).
184
Figure 4.S2. At D5 there are no significant defects in ire1a ire1b meristem organization.
At D5, root tips were subjected to mPS-PI staining and confocal microscopy to analyze root tip
cellular organization. A) Representative 10x images of mPS-PI stained WT and ire1a ire1b roots.
The yellow line demarks the end of the meristem zone (MZ) and the beginning of the transition
zone (TZ), the red lines marks all of the cells in the elongation zone (EZ), and the white arrow
marks the first root hair initiation. For all measurements of the MZ secondary 20x images were
used to collect data. B) The average length of each zone. C) The # of cells in each zone. D) Average
cell length in each zone. For all graphs error bars show SD; p-values significance markers
displayed above an ire1a ire1b experimental group are pairwise comparisons to the corresponding
WT group for that specific treatment. Brackets denote other specific pairwise comparisons.
Significance markers: NS = adj. p >0.01; *= adj. p < 0.01 and >0.001;**= adj. p <0.001 and
>0.0001; ***= adj. p-value < 0.0001
185
Figure 4.S3. Average root tip cellular organization metrics displayed over time in WT and
ire1a ire1b.
Average values from the data presented in Figure 4.S2, and Figure 4.2 are plotted over time to
compare differences over time in each genotype separately. A-C) Zone length, # of cells, and cell
length in the WT root tips. D-F) Zone length, # of cells, and cell length in the ire1a ire1b root tips.
For all graphs: Error bars are SD, p-values significance markers displayed over an experimental
group at D7 or D10 are comparisons to the corresponding D5 value for that group. Brackets denote
other specific pairwise comparisons. Significance markers: NS = adj. p >0.01; *= adj. p < 0.01 and
>0.001;**= adj. p <0.001 and >0.0001; ***= adj. p-value < 0.0001 . p-value indicator color matches the
color of the corresponding root tip zone.
186
Figure 4.S4. TOR inhibitor AZD-8055 concentration response analysis.
A) Representative images from DMSO, 100 nm and 200 nm AZD-8055 conditions. B) Root length
of individual roots was measured using ImageJ. For all graphs error bars show SD; p-values
significance markers displayed above an ire1a ire1b experimental group are pairwise comparisons
to the corresponding WT group for that specific treatment. Brackets denote other specific pairwise
comparisons. Significance markers: NS = adj. p >0.01; *= adj. p < 0.01 and >0.001;**= adj. p
<0.001 and >0.0001; ***= adj. p-value < 0.0001. For this experiment the growth chamber used
had 200 μE continuous light which caused proportionally shorter roots in both WT and ire1a ire1b
compared to 150 μE light, however the general conclusions from the DMSO vs AZD treatments
are the same in both conditions.
187
Figure 4.S5. TOR inhibitor TORIN2 rescues the ire1a ire1b root growth phenotypes.
A) Representative images from DMSO, and TORIN2 conditions. B) Root length of individual
roots was measured using ImageJ. Error bars show SD; p-values significance markers displayed
above an ire1a ire1b experimental group are pairwise comparisons to the corresponding WT group
for that specific treatment. Brackets denote other specific pairwise comparisons. Significance
markers: NS = adj. p >0.01; *= adj. p < 0.01 and >0.001;**= adj. p <0.001 and >0.0001; ***= adj.
p-value < 0.0001 C) Angle of the root tip away from vertical (0º) was measured using ImageJ.
Significant differences between coefficient of variation was tested using the asymptotic Feltz and
Miller test as described in materials and methods. p-values: NS = >0.05, **= p-value < 0.01 and
>0.001, ***= p-value < 0.001
188
Figure 4.S6. Other chemical inhibitors of root growth do not rescue the ire1a ire1b root
length phenotype.
A) Representative images from DMSO, Oryzalin, Latrunculin B and Oligomycin growth
conditions. This experiment and TORIN2 experiments (Figure 4.S5.) were performed
simultaneously and share the DMSO control data. B) Root length of individual roots was measured
using ImageJ. C) Representative images from Antimycin A and ethanol control growth conditions.
C) Root lengths of individual roots for ethanol and Antimycin A growth conditions. For all graphs
error bars show SD; p-values significance markers displayed above an ire1a ire1b experimental
group are pairwise comparisons to the corresponding WT group for that specific treatment.
Brackets denote other specific pairwise comparisons. Significance markers: NS = adj. p >0.01; *=
adj. p < 0.01 and >0.001;**= adj. p <0.001 and >0.0001; ***= adj. p-value < 0.0001
189
Figure 4.S7. Auxin inhibition of root growth and TOR inhibition of root growth are
additive effects in WT plants.
A) Representative images of seedlings grown on plates containing various concentrations of NAA,
with or without addition of AZD-8055. B) Primary root length after 10 days of growth. For graphs
error bars show SD; p-values significance markers displayed above an ire1a ire1b experimental
group are pairwise comparisons to the corresponding WT group for that specific treatment.
Brackets denote other specific pairwise comparisons. Significance markers: NS = adj. p >0.01; *=
adj. p < 0.01 and >0.001;**= adj. p <0.001 and >0.0001; ***= adj. p < 0.0001
190
Figure 4.S8. Full blot images (from Fig 4.5) and the Ponceau’s stain images to demonstrate
equal protein loading.
191
Figure 4.S9. Simplified model of the effect of TOR activity on cell elongation in the ire1a
ire1b mutant.
Simplified model based on our results showing that TOR activity must be balanced by IRE1 to
maintain optimal cell elongation. Basal TOR activity is needed for cell elongation, illustrated by
the difference between WT-DMSO and WT- AZD-8055. However, TOR hyper-activity promotes
faster and unbalanced rates of differentiation, which favors premature root hair initiation and
cessation of cell elongation. This in turn leads to shorter length of mature cells and an overall
shorter root length in the ire1a ire1b mutant.
192
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CHAPTER V
Future Perspectives
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In my dissertation research I examined how conserved elements of the UPR interact with
plant-specific physiological mechanisms in the context of development and stress response. By
exploring how the canonical UPR responds in non-canonical and tissue-specific ways my research
has helped to broaden our knowledge of the plant UPR and better integrate our understanding of
the UPR functionality in plant life. In the Chapter 1 literature review, I examine how broadly
conserved elements of the UPR, such as IRE1, have evolved novel biochemical mechanisms in
different eukaryotic organisms (Figure 5.1). I further outline our current understanding of how the
functional diversification of the UPR in plants affects a variety of stress responses and
developmental processes. In Chapter 2, I add to this knowledge by studying the functional
interaction between the Arabidopsis UPR regulators and the conserved NADPH Oxidase proteins
(also known as RBOH enzymes) in the contexts of the ER stress response. In Chapter 3, I explore
Figure 5.1. Summary Graphic of Dissertation Investigations.
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how the UPR may be connected with other plant signaling mechanisms through an analysis of
UPR-dependent transcriptional reprogramming in spaceflight conditions. In Chapter 4, I sought to
better understand how to the UPR functions specifically contribute to plant development, by
looking at the relationship between IRE1 and the TOR kinase in the context of root growth. In this
chapter, I further expand upon the context of these findings and discuss how they might be
explored in the future.
Chapter 2: Integrating ER Stress Response with NADPH Oxidase Signaling
In Arabidopsis, NADPH oxidase-dependent ROS signaling is already known to mediate a
wide variety of stress responses including abiotic stress (i.e. light, mechanical, heat), and biotic
stress (i.e. bacterial, fungal, and viral infection) (Miller et al. 2009). In particular, the RBOH
proteins expressed in plant vasculature mediate systemic signaling to prime unstressed portions of
the plant with pre-emptive stress signals (Suzuki et al. 2011). Interlinked signal transduction
mediated by RBOH-dependent H2O2 and Ca2+ propagate from cell to cell over long distances in
plants (Mittler 2017). This signal transduction, which is analogous to nerve impulses in metazoans,
has been called ROS wave signaling.
In chapter 2, I built on previous work that demonstrated ROS accumulation during ER
stress in Arabidopsis, and examined the specific role of RBOHD and RBOHF in the UPR response
at the organism level. I was able to demonstrate that H2O2 accumulation which occurs with
prolonged ER stress is almost entirely dependent on the functional activities of RBOHD and
RBOHF. Furthermore, I demonstrate that the functions of these proteins are a strongly pro-
survival influence under these conditions. This may be explained by my observations which
demonstrate RBOHD and RBOHF dependent functions promote IRE1 activation under prolonged
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stress treatments. With this established, it will now be important to understand whether these
observations are due to localized RBOH activity at the primary sites of stress, or whether RBOHs
participate in long distance signaling to prime the plant UPR in unstressed tissues.
Recent work from our lab has demonstrated that ER stress does transmit a systemic signal
in the root to shoot direction (Lai et al. 2018). Roots that are stressed by tunicamycin application
promote a local UPR response as expected, however shoot tissues in these plants also show a
significant UPR response dependent upon UPR activation in root tissues (Lai et al. 2018). It was
demonstrated that the tunicamycin itself is not taken up in the vascular streams and transported to
the shoot, instead a secondary signal leads to UPR activation in connected tissues. One explanation
supplied by the authors is the potential for cell-to-cell transport of the bZIP60 mRNA or protein,
which was shown to be transported from a specific cell type at the root tip to the surrounding
tissues (Lai et al. 2018). This transport was ablated in plasmodesmata deficient mutants suggesting
that short-distance transportation of bZIP60 is likely (Lai et al. 2018). However, given the
prominent role of RBOH activity in long-distance systemic signaling, it may be possible that
RBOH dependent ROS waves may be involved in transmitting the ER stress signal from root to
shoot. In my study I demonstrate that superoxide production initially begins at the root tip after 24
hr, but is transferred to the mature root tissues, including the vascular column, after 48 hr of ER
stress. This superoxide production in mature tissues was dependent on RBOHD and RBOHF.
Therefore, it may be possible that RBOH activity in these mature tissues leads to systemic
signaling. Future work in this area could explore whether ER stress in the root tissues requires
RBOHD or RBOHF to transmit the systemic UPR signals observed by Lai et al. (2018), and could
utilize selective tissue applications of ER stress agents and ROS scavengers to explore this
possibility.
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The connection between ER stress signaling and RBOH-dependent ROS signaling may
also play an important role in other types of abiotic and biotic stresses. As discussed in Chapter I,
the UPR and IRE1 play an important role in establishing systemic acquired resistance (SAR) to
different types of pathogens through an unknown mechanism (Verchot and Pajerowska-Mukhtar
2021). ROS wave signaling also has a demonstrated role in promoting SAR and plant survival in
these contexts as well (Torres et al. 2005). Given the results discussed in Chapter II, it may be
possible that ER stress at the site of the infection may lead to ROS wave propagation, promoting
ER stress and pathogen resistance in systemic tissues. A similar ER-stress dependent activation of
ROS wave signaling may exist in the response to high light as well, given the verified roles that
RBOHD and the UPR have in regulating high-light stress resistance (Miller et al. 2009, Beaugelin
et al. 2020). Taken together, my work has demonstrated an important link between ER stress
response and the RBOH-dependent ROS signaling network. In doing so, this work has helped to
connect the conserved component of the plant UPR with the wider network of plant signaling
pathways and provide possible contexts for UPR functions in a variety of biotic and abiotic stress
responses.
Chapter 3: UPR Transcriptome in Spaceflight Experiment Reveals Possible Novel Roles for UPR
TFs
Spaceflight conditions impose a novel set of environmental stressors on plants, including
microgravity, radiation, vibration, and limited exchange of gases, which can affect plant
development and yield (Paul et al. 2012, Paul et al. 2013). Given the broad versatility of the UPR
in responding to a number of environmental stressors, I explored the possibility that the UPR
contributes to transcriptional regulation during spaceflight associated stress conditions. I did this
by sterile culturing Arabidopsis etiolated hypocotyls in orbit at the International Space Station
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(ISS), utilizing the available BRIC-PDFU hardware. This hardware has been used previously in
the study of Arabidopsis transcriptomes in spaceflight conditions, and a number of the
transcriptional responses observed in previous studies were also found in our WT transcriptome.
However, a study published after the execution of my spaceflight experiment demonstrated that
seedlings grown in this hardware experience extensive stresses which are independent of
spaceflight associated stress (Basu et al. 2017). In these contexts, I observed a surprising
downregulation of multiple stress responsive processes at the transcript level in spaceflight
compared to ground controls, including water deprivation and starvation responses. Although the
limitations of this experiment and the inability to perform additional experimental replicates
prevented further investigation, observations of plant growth patterns in culture plates led me to
hypothesize that in spaceflight conditions the lack of directional growth in microgravity improved
seedling access to water and nutrients by increased contact with the media. The improved access
to these nutrients may have suppressed the BRIC-PDFU induced stress responses. While there
were very few differences between WT and UPR mutant transcriptomes in the spaceflight samples,
in the ground controls samples I found a large requirement for intact bZIP60 and bZIP28 signaling
in the regulation of a number of stress responses, including water deprivation and abscisic acid
signaling. These results demonstrate for the first time, the possible connection between UPR TFs
and abscisic acid/ water deprivation stress. However, further investigation is needed to dissect the
causative nature of the stress experienced by seedlings cultured inside BRIC-PDFUs and
determine whether the outcomes of this stress are applicable to other biological contexts. In the
future, spaceflight associated research of plants would be better performed in hardware which can
better replicate normal growth conditions of plants on Earth. In that respect, the open-air growth
of plants in the VEGGIE growth chamber on the ISS may be better suited to future research of
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plant spaceflight stress responses, and may help to re-evaluate the role of the UPR in these
conditions.
Chapter 4: Old Friends with a New Relationship, IRE1 and TOR
Given the near universal occurrence of IRE1 and TOR in the genomes of most eukaryotic
organisms, including animals, fungi and plants (Ruberti and Brandizzi 2014, Shi et al. 2018), it is
plausible to assume that these two cell status regulators have coexisted on a broad evolutionary
timescale. However, few interactions between their regulatory networks have been elucidated.
This is peculiar given the strong influence that both regulators have on protein synthesis at the cell
level (Walter and Ron 2011, Xiong et al. 2013, Shi et al. 2018, Bashir et al. 2021). Although a
small number of studies have demonstrated that TOR activity can affect UPR or IRE1 signaling in
stressed mammalian cells (Pfaffenbach et al. 2010, Kato et al. 2012, Kato et al. 2013, Young et
al. 2013, Li et al. 2014, Shanware et al. 2014, Sanchez-Alvarez et al. 2017), to my best knowledge,
no previous studies have demonstrated that IRE1 can affect TOR activity under cell stress or
developmental contexts.
In the work presented in Chapter IV, I demonstrate the requirement of IRE1 specifically in
the rapid development of Arabidopsis primary root tips. I show that IRE1 is required to reach
maximum rates of growth afforded by prolonged photoperiod and increased carbohydrate
availability. I further show that the ire1a ire1b root growth phenotype is dependent upon
hyperactivation of TOR, which leads to increased rates of cell differentiation. Prior to this work,
the signaling and physiological pathways by which IRE1 activities controls development in plants
were completely unknown. These findings help to establish that IRE1 controls growth via a
negative regulation of TOR activity.
206
The molecular mechanism which connects IRE1 to TOR activity is yet unknown, but of
considerable interest. Although it is highly unlikely that TOR is regulated via bZIP60 splicing, it
will take considerable work to elucidate whether IRE1 affects these outcomes via it’s kinase
activity, alternative RNase activity, or another novel signaling pathway. Furthermore, the tissue
specific contexts of this interaction will complicate future studies. Tissue-specific or single cell
RNA-sequencing of WT and IRE1 mutant root tips may be required to elucidate potential RNA-
targets of IRE1 in these transient developmental contexts. These putative targets could then be
examined by standard reverse genetics approaches. Elucidation of this mechanism may allow for
broader control over plant growth, development, and metabolism via the IRE1 pathway and help
to establish new routes for biotechnological utilization of UPR mechanisms in crop species to
improve productivity.
207
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