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This is to certify that the
dissertation entitled

ECOLOGY, PHYSIOLOGY AND METABOLISM OF COLD-
ADAPTED MICROORGANISMS FROM THE SIBERIAN
PERMAFROST

 

presented by

DEBORA FRIGI RODRIGUES

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Mlchislan State
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has been accepted towards fulfillment
of the requirements for the

Ph.D. degree in Microbiology and Molecular
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ECOLOGY, PHYSIOLOGY AND METABOLISM OF
COLD-ADAPTED MICROORGANISMS FROM THE
SIBERIAN PERMAFROST

by

Debora Frigi Rodrigues

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Microbiology and Molecular Genetics

2007

ABSTRACT
ECOLOGY, PHYSIOLOGY AND METABOLISM OF COLD-ADAPTED

MICROORGANISMS FROM THE SIBERIAN PERMAFROST
By
Debora Frigi Rodrigues

In our solar system, seven out of nine planets, including Earth, are considered to be
cold. Even though cold temperatures are lethal to many microorganisms, some
successfully colonize cold habitats. I studied the distribution, abundance and diversity of
two cold-adapted genera, Exiguobacterium and Psychrobacter. Total microbial
community DNA extracted from 54 sediment and soil samples from Siberia, Antarctica,
Michigan, Iowa, Brazil, Puerto Rico and Hawaii was analyzed with specific primer sets
for each genus by quantitative real-time PCR and by 16S rRNA gene clone libraries.
Both genera were more commonly found and have higher densities in polar regions, but
they were also detected in some temperate and tropical sites. The later was more likely
the case when physicochemical conditions such as salinity, K+ and pH were similar to
their polar habitat conditions.

Exiguobacterium isolates obtained from the Siberian permafrost were analyzed using
a polyphasic approach, and yielded a new species, Exiguobacterium sibiricum. The
genome of the type strain of the new E. sibiricum species was sequenced by the DOE
Joint Genome Institute. The genome is approximately 3 Mb in size, has a GC content of
47.7% and includes 2,978 putative protein—encoding genes (CDS). I used the genome and

transcriptome analysis along with the organism’s known physiology to better understand

its thermal adaptation. A total of about 27%, 3.2% and 5.2% of E. sibiricum strain 255-15

CDS spotted on the DNA microarray yielded differentially expressed genes in cells
grown at -2.5°C, 10°C and 39°C, respectively, when compared to cells grown at 28°C.
The hypothetical and unknown genes represented 10.6%, 0.89% and 2.3% of the CDS
differentially expressed when grown at -2.5°C, 10°C and 39°C versus 28°C. The
transcriptome analyses showed that E. sibiricum is constitutively adapted to cold
temperatures since little differential gene expression was observed at growth

temperatures of 10°C and 28°C, but at the extremities of its Arrhenius growth profile,

namely -2.5°C and 39°C, much more differential gene expression occurred. The genes

that responded were more typically associated with stress response.
I showed that Exiguobacterium and Psychrobacter are more prevalent in but not
restricted to cold, polar environments, and that this ecology is consistent with the

Exiguobacterium’s transcriptional response, i.e., little differential gene expression

between 10°C and 28°C.

This work is dedicated to my husband
and my family who have continuously
loved and supported me.

 

ACKNOWLEDGEMENTS

I cannot thank enough Dr. James Tiedje, my advisor, for giving me the opportunity
to fulfill my dream of doing my Ph.D. in US. I have learned a lot from his wisdom and
professional experience. His friendship and professionalism truly inspired me to follow a
path of excellence not only in my career, but also in every aspect of my life. Thank you
so much for supporting me in my professional plans, and for all the encouragement and
guidance.

1 would like to thank Dr. Michael Bagdasarian who had his door always open for all
my questions. I am really grateful for his valuable suggestions and comments.

I would like to thank Dr. Robert Britton, for giving me the opportunity to be
his Teaching Assistant. It was a great experience and I learned a lot from him. He was a
great teaching mentor for me. I am also truly thankful for his pertinent and very valuable
advices about my career and experiments.

I would like to thank Dr. Sophia Kathariou for being so kind and helpful in
everything I needed related to presentations, experiments and Exiguobacterium strains.
Thank you for giving me all the support in my career plans and for all the kind words that
gave me so much confidence in my research.

1 would like to thank Dr. Michael Thomashow for the great help in the edits of my
first manuscript, and for all the intriguing and pertinent questions that stimulated my
research in all our NASA and committee meetings.

I am grateful to all my Astrobiology colleagues, Dr. Tatiana Vishnivetskaya, Dr.

Shannon Hinsa—Leasure, Dr. Hector L. Ayala-del-Rio, Dr. Peter Bergholz and Dr. Corien

Bakerrnans, for their advice, encouragement and friendship.

I also would like to say special thanks to my co-workers and friends Dr. Vivian
Helena Pellizari, Dr. Johan Goris, Dr. Alban Ramette, Dr. Vincent Denef, Erick
Cardemas, Ederson Conceicao Jesus and Dr. Stephan Gantner, not only for teaching me
techniques and programs essential for my thesis and research development, but also for
enriching my life here at MSU with their priceless friendship.

Thanks to the administrative and technical staff, Lisa Pline, Pat Englehart, Nikki
Mulvaney, Suzanne Peacock, Angela Zell, Maryam Thompson and Joyce Wildenthal for
their great assistance and support. I also would like to say a special thanks to the lab
assistants Chia-Ju Lin and Christopher Bradley who contributed to my research.

Most of all, I wish to express my deepest gratitude to my parents, my sister and
my beloved husband for giving me support, financially and spiritually. I could not make

it without their love.

vi

PREFACE

The life processes of all organisms are adapted for ecological success in their
respective “normal” physiological environments. Any change in environmental
conditions is experienced as a stress that threatens the normal metabolic balance and
produces a response designed to counter the effects of the disturbing influence.
Among all the natural stress conditions on our planet and solar system, cold is by far
the most widespread from the perspective of Earth’s most visable, albeit, mesophilic
organisms. In our solar system, seven (including Earth) out of nine planets are cold.
For instance, 90% of the Earth’s oceans have a temperature of 5°C or less. When
terrestrial habitats are included, over 80% of the Earth’s biosphere is permanently
cold. Since we inhabit a cold planet and numerous microorganisms found on Earth
have the ability to cope with low temperatures, this makes them appear to be the
Earth’s most successful colonizers.

Among the cold habitats on our planet, the permafrost environments are strong
candidates for astrobiological studies because they have characteristics similar to
other cold planets in our solar system. The permafrost habitat underlies an estimated
20 to 25% of the Earth’s terrestrial surface. The mean annual temperature is between
-10 and -12°C in the Arctic and between -18 and -27°C in the Antarctic. Permafrost
microorganisms have been living in the frozen sediments for as long as 2 to 3 million
years in our primary study aerea, northeastern Siberia, without gene flow and

microbial dispersal from any outside source.

vii

“‘3!!an

 

In previous studies, four of the six major taxa isolated from the Siberian
permafrost had strains from the Antarctic or other cold habitats as their closest known
phylogenetic relatives. This pattern suggests the selection for more than a few traits
for cold adaptation. One derivative of this hypothesis is that such strains may be
restricted to cold environments. In this study, I studied two taxa, Exiguobacterium
and Psychrobacter, to establish their distribution, abundance and biodiversity in
polar, temperate and tropical locations on our planet. The results demonstrated that
both genera had a patchy distribution in warmer environments, but were ubiquitous in
polar regions.

Exiguobaclerium isolates from the Siberian permafrost were further studied to
better understand their physiology and the basis of their adaptation to permafrost. I
found that permafrost harbors Exiguobacterium species with several metabolic and
physiological features that seem to be necessary for survival and growth under
subzero temperatures. Hence, the present study provides new data on the ecology,

physiology and metabolism of psychrotroph microorganisms from permafrost.

viii

firm-HP“

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

TABLE OF CONTENTS

LIST OF TABLES XI

LIST OF FIGURES XII

CHAPTER 1

COPING WITH OUR COLD PLAN ET 1
ABSTRACT ...................................................................................................................................................... 2
INTRODUCTION ............................................................................................................................................ 2
ACKNOWLEGDEMENTS ........................................................................................................................... 12
REFERENCES ............................................................................................................................................... 13

CHAPTER 2

3100 EOGRAPHY, DIVERSITY AND ABUN DANCE OF EXIGUOBACTERIUM SPP. AND

PSYCHROBACTER SPP. 22
ABSTRACT .................................................................................................................................................... 23
INTRODUCTION ........................................................................... . ........................ 23
MATERIAL AND METHODS ................................................................. .................... 24
RESULTS AND DISCUSSION .............................................................. . 32
ACKNOWLEGEMENTS ...................................................................................................... 42
REFERENCES ....................................................................................... .43

CHAPTER 3

IDENTIFICATION AND CHARACTERIZATION OF EXIGUOBACTERIUM ISOLATES FROM

THE PERMA FROST 47
ABSTRACT ........................................................................................... 48
INTRODUCTION ......................................................................... .................... 48
MATERIAL AND METHODS .......................................................................................... 50
RESULTS AND DISCUSSION ................................................................ .................... 53
ACKNOWLEDGEMENTS .................................................................................................... 70
REFERENCES ............................................................................... - .................... 71

CHAPTER 4

EXIGUOBACTERIUM GENUS: AN EXAMPLE OF PERMAFROST SURVIVOR 75
ABSTRACT ........................................................................... 76
INTRODUCTION ....................................................................................... .. ...................... 76
MATERIAL AND METHODS ..................................................................................... 78
RESULTS ..................................................................................................... . . .. 85
DISCUSSION ................................................................................ 97
ACKNOWLEDGEMENTS .................................................................................................... 99
REFERENCES ................................................................................. 100

ix

 

were—emu

 

CHAPTER 5
ARCHITECTURE OF THERMAL ADAPTATION IN EXIGUOBACTERIUM SIBIRICUM

 

 

 

 

 

 

 

 

 

 

 

STRAIN 255-15: A GENOME AND TRANSCRIPTOME APPROACH 104
ABSTRACT ....................................................................... 105
INTRODUCTION ........................................................................................................................................ 105
MATERIAL AND METHODS .................................................................................. 107
RESULTS AND DISCUSSION ................................................................................ Ill
ACKNOWLEGMENTS .............................................................................................. 146
REFERENCES ................................................................................................. I47

EPILOGUF 152

RESEARCH SUMMARY AND FUTURE DIRECTIONS 152
SUMMARY ........................................................ . ...... 153
FUTURE DIRECTIONS ............................................................ . ......................... 154

 

 

LIST OF TABLES
Table 1.1. Summary of genes important for adapting to cold-shock stress ................... 7
Table 2.1. Location and information of sampling sites ......................................... 25

Table 2.2. Physicochemical results from the sites used for the principal component
analysis ............................................................................................... 30

Table 2.3. Diversity comparisons of 16S rRNA environmental clone libraries ............ 36

Table 3.1. Primers used for PCR amplification for MLST analysis. All the primers,
except for the major cold-shock protein, where designed based on the Exiguobacterium
sequences as well as other strains from the Bacillus genus .................................... 52

Table 3.2. DNA-DNA similarity of Exiguobacterium strains using the microplate DNA-
DNA hybridization technique. Data greater than 70% in bold ................................ 59

Table 3.3. Phenotypic characteristics of new isolates and type strains of Exiguobacterium
strains: 1= 7-3; 2= 255-15; 3= 190-11; 4= E. undae DSM 14481T (data obtained from this
work and Frflhling et al. 2002); 5= E. antarcticum DSM 14480T (data obtained from this
work and Frfihling et a1. 2002); 6= E. aurantiacum DSM 6203T (data obtained from this
work and Frfihling et al. 2002); 7= E. acetylicum DSM 20416T (data obtained from this
work, Frtihling et al. 2002, Collins et al., 1983); 8= E. oxidotorerans (Yumoto et al.,

2004); 9= E. aestuarii (Kim et al, 2005); 10= E. marinum (Kim et a1, 2005) ............. 60

Table 3.4. Fatty acid composition of the Siberian permafrost isolates and the type strains
of Exiguobacterium. Values 2 5% are in bold ................................................... 62
Table 3.5. Phenotype properties that differentiate the novel isolates from
Exiguobacterium type strains using Biolog and API 50 CH .................................. 67
Table 4.1. Location and additional information of the sample
sites ................................................................................................... 78
Table 4.2. Specificity of real-time PCR for Exiguobacterium spp ........................... 81
Table 5.1. COGS (Cluster of orthologous groups) classification of the genes in the
genome of Exiguobacterium sibiricum strain 255-15 ......................................... 115
Table 5.2. Fold-change (log odds score) at different temperatures ......................... 124

xi

“‘1': s. '

 

LIST OF FIGURES

Figure 2.1. Exiguobacterium spp. and Psychrobater spp. gene abundance in various

habitats as measured by Q-PCR. The sample number corresponds to the sample numbers
in Table 2.1 .......................................................................................... 33

Figure 2.2. Correlation biplot from physicochemical characteristics of principal
component analysis ................................................................................... 34

Figure 2.3. Distribution of OTUs abundance in different soils. The colors are ranking the
most abundant OTU to the least abundant. The labels correspond to the clones
represented in the phylogenetic trees for each genus ........................................... 37

Figure 2.4. Results of selected I-LIBSHUFF comparisons. Homologous (Cx) and
heterologous (ny) coverage curves for 16S rRNA gene sequence libraries from
Psychrobacter spp. in Michigan and Puerto Rico. Solid lines indicate the value of (Q,—

ny)2 for the original samples at each value of Evolutionary Distance (D). D is equal the
Jukes-Cantor evolutionary distance determined by RDP-II pipeline. Broken lines indicate

the 950th value (or P=0.05) of (Cx-ny)2 for the randomized samples. (A) Comparison of
Psychrobacter clones from Michigan soil (x=Ml) and from Puerto Rico soil (y=PR). (B)

Comparison of Psychrobacter clones from Puerto Rico soil (x=PR) and from Michigan
soil (y=PR) ........................................................................................... 38

Figure 2.5. Phylogenetic tree based on 168 rRNA gene sequences of Psychrobacter
strains and the top seven dominant OTUs in the clone libraries from Michigan (A),
Puerto Rico (0) and Antarctica sediment (CI). The trees were produced by the neighbor-
joining method and rooted using the 16 S rRNA gene from B. subtilis. The nodes with
less than 45% bootstrap values were not added to the tree. The scale bar represents
changes per nucleotide ............................................................................. 39

Figure 2.6. Phylogenetic tree based on 16S rRNA gene sequences of Exiguobacterium
strains and clone libraries from Michigan (A), Puerto Rico (0) and Antarctica sediment
(CI). The trees were produced by the neighbor-joining method and rooted using the 16S
rRNA gene from B. subtilis. The nodes with less than 45% bootstrap values were not
added to the tree. The scale bar represents changes per nucleotide ........................... 40

Figure 3.1. Phylogenetic trees based on 16S rRNA gene (a), rpoB (b), recA (c), hsp70
(d), gyrB (e), citC (f), major cold-shock proteins (g) sequences of the following genes of
indicated Exiguobacterium strains. The trees were produced by a maximum-likelihood
method using fastDNAml_loop and were rooted using those genes from B. subtilis. The
nodes without bootstrap values represent either branching orders that were inconsistent
between the phylogenetic tree generated by the maximum-likelihood method and the
consensus tree generated from 1000 bootstraps or had bootstrap values of 40% or less.
The scale bar represents 0.1 changes per nucleotide position ................................. 55

xii

Figure 3.2. Phenogram obtained from the carbon source utilization of the seven
Exiguobacterium strains based on the UPGMA method (unweighted pair-group method
using arithmetic averages) after measuring similarity/dissimilarity among the strains
using the coefficient of simple matching, which considers the same weight positive and
negative similarities ................................................................................. 63

Figure 3.3. Cell morphology of new isolates and reference strains of E. antarcticum

DSM1448O and E. undae DSM 14481 grown at 0°C by phase contrast microscopy. Bar
scale corresponds to 10 pm ........................................................................ 66

Figure 3.4. Negatively stained electron micrograph of 7-3 and 255-15 grown at 0°C.
Strain 7-3 presents elongated cells and 255-15 presents intracellular granules ............. 66

Figure 4.1 (A). Phylogenetic tree based on hypothetical (A) and rpoB (B) sequences of
indicated Exiguobacterium strains and clone libraries from Michigan (A),Puerto Rico soil
(Cl) and three Siberia permafrost soils dated of 2 to 3 million years (0), 100-200 thousand
years (I) and 12 to 40 thousand years (A). The trees were produced by the neighbor-
joining method. The rpoB tree was rooted using the rpoB gene from B. subtilis. The
nodes with less than 40% bootstrap values were not added to the tree. The scale bar
represents changes per nucleotide ................................................................. 87

Figure 4.1 (B). Phylogenetic tree based on hypothetical (A) and rpoB (B) sequences of
indicated Exiguobacterium strains and clone libraries from Michigan (A),Puerto Rico soil
(C1) and three Siberia permafrost soils dated of 2 to 3 million years (°), 100—200 thousand
years (I) and 12 to 40 thousand years (A). The trees were produced by the neighbor-
joining method. The rpoB tree was rooted using the rpoB gene from B. subtilis. The
nodes with less than 40% bootstrap values were not added to the tree. The scale bar
represents changes per nucleotide ................................................................. 88

Figure 4.2. Phylogenetic tree based on gyrB sequences of indicated Exiguobacterium
strains and clone libraries from Puerto Rico soil (Cl) and three Siberia permafrost soils
dated of 2 to 3 million years ('), 100-200 thousand years (I) and 12 to 40 thousand years
(A). The tree was produced by neighbor-joining method and was rooted using the gyrB
gene from B. subtilis. The nodes with less than 40% bootstrap values were not added to
the tree. The scale bar represents 0.05 changes per nucleotide ............................... 89

Figure 4.3. Calibration Curves for each primer set ............................................. 92
Figure 4.4. Detection limit of the Exiguobacterium spp. using real-time PCR. The
denoted volumes of serially diluted gene clone were added to different reaction mixtures.
(A) Detection limit of hypothetical gene. (B) Detection limit of gyrB gene ................ 93
Figure 4.5. Relationship between gene copy number and error illustrated for gyrB. The

horizontal line represents the MAE to discriminate between samples containing a twofold
difference in Exiguobacterium sibiricum 255-15, E. undae 190-11 and E. antarcticum

xiii

DSM 14480T copy number. Values shown represent the mean from 16 independent
standard curves. The 95% confidence intervals are shown as a dashed line ................. 94

Figure 4.6. Percentage recovery of 104 hypothetical gene copies of Exiguobacterium spp.
added to the soil DNA extracted from the different environments ........................... 95

Figure 4.7. Exiguobacterium gene abundance in various habitats as measured by qPCR.
The sample number corresponds to the permafrost sample number in Table 4.1 .......... 96

Figure 5.1. Metabolic pathway reconstruction of Exiguobacterium sibiricum 255-15
based on genome content (Figure provided by Natalia Ivannova) .......................... 113

Figure 5.2. Distribution of top hits with other microorganisms of Exiguobacterium
sibiricum 255-15 CDS by using BLASTP ...................................................... 114

Figure 5.3. Negatively stained electron micrograph of E. sibiricum strain 255-15.
Exopolysaccharide and no flagella are observed after growth at -2.5°C .................. 116

Figure 5.4. Known cold and heat stress response genes with homologs to
Exiguobacterium sibiricum 255-15. The genes in red correspond to the heat expressed
genes. The genes in blue are the cold expressed genes and the ones in pink are the ones
that are expressed in both conditions. Images in this dissertation are presented in
color .................................................................................... . ............................................. 121

Figure 5.5. Arrhenius plot of E. sibiricum 255-15 growth rates in 1/2 TSB. The first phase
of the biphasic response is in gray and the second phase is in black, each with its

respective trend lines and R2 values ............................................................ 122

Figure 5.6. Venn diagram of all differentially expressed genes at the indicated
temperature ......................................................................................... 123

Figure. 5.7. Venn diagram of unknown or hypothetical genes differentially expressed at
the indicated temperatures ........................................................................ 123

Figure 5.8. Heat maps of E. sibiricum strain 255-15 showing gradient of gene expression
with increase or decrease of temperature growth. Image in this thesis is presented in
color ................................................................................................. 134

Figure 5.9. Summary of Exiguobacterium sibiricum 255-15 architecture of thermal
adaptation at -2.5°C and 39°C .................................................................... 135

Figure 5.10. Negatively stained electron micrograph of E. sibiricum strain 255-15. Cell
with flagella at 10°C ............................................................................... 145

xiv

 

CHAPTER 1

COPIN G WITH OUR COLD PLANET

 

ABSTRACT

In our solar system, seven out of nine planets, including Earth, are considered to be
cryogenic. Since water is the medium for all biochemical reactions in biological systems,
changes in water properties due to cold temperatures directly affect biochemical reactions
and hence, the physiology of microorganisms. Even though cold temperatures can affect
survival of many microorganisms, this has not impeded cold-adapted microorganisms to
successfully colonize and grow in polar, deep-sea waters and alpine regions that are at, or
close to, sub-zero temperatures. In this brief review I will summarize how physical
properties of water can affect the physiology of microorganisms at cold temperatures. I

will also summarize the adaptations microorganisms use to live at low temperatures.

INTRODUCTION

Several factors can generate physiological stress conditions. Of all the natural
stress conditions on this planet and in our solar system, cold is by far the most
widespread, from the perspective of mesophilic and thermophilic organisms. In our solar

system, seven out of nine planets, including Earth, are cold. For instance, 90% of the
Earth’s oceans have a temperature of 5°C or less. When terrestrial habitats are included,

over 80% of the Earth’s biosphere is permanently cold (78).

The fact that water is the major constituent of life, it is expected that the manner
in which its physical properties depend on temperature must be understood to better
understand the mechanisms that govern cold tolerance and acclimation. Since we inhabit
a cold planet and several microorganisms found on Earth have the ability to cope with
low temperatures, this makes them appear to be the Earth’s most successful colonizers

(28, 29). In this brief review I summarize how physical properties of water at cold

temperatures affects the physiology of microorganisms. I also summarize the
mechanisms microorganisms have used to adapt to cold temperatures and hence
successfully live in cold habitats.

Effects of cold on physical properties of water and on biochemical reactions. In a
subzero environment, water can be supercooled or frozen (21). The first condition does
not involve separation of water as a pure phase (ice). Thus supercooling conditions are
not accompanied by changes in the concentrations of water-soluble components, except
in rare cases where such substances might be near saturation at normal temperatures and

precipitate under supercooling conditions. Supercooling conditions in aqueous systems
can persist down to - 40°C and even below (21). Under cold and subzero temperatures the
physical properties of liquid water exhibit substantial changes. These changes are not
linear but become more pronounced at lower temperatures. Some of the changes at lower
temperatures involve increase in viscosity, dielectric permittivity and pKw; and reduction
of diffusion (1). However, the most dramatic effect, at least from the biochemistry
viewpoint, is the degree of ionization (35). As H+ and OH- ions are involved in most life
reactions (condensation, hydrolysis, oxidation and reduction) it is likely that the decrease
of Kw will affect equilibrium and kinetic process (21).

Besides the supercooled water condition, some cells can also endure freezing. The
cooling velocity is one of the major factors that determines whether or not a cell will be
viable after freezing. Cooling either too slowly or too rapidly can be damaging (59). If
cooling is sufficiently slow and ice forms extracellularly, the cell is able to lose water
rapidly enough by exosmosis resulting in increased concentration of intracellular solutes

to maintain the chemical potential of intracellular water in equilibrium with that of

 

extracellular water. The result is that the cell dehydrates and does not freeze
intracellulary. But if the cell is cooled too rapidly, it is not able to lose water fast enough
to maintain equilibrium and can eventually freeze intracellulary. Ideally, for better cell
survival at subzero temperatures, it is necessary to cool the cells slowly enough to avoid
intracellular ice formation by increasing the solutes concentration intracellularly and to
permit the cell to physiologically adapt to the new temperature condition (59).

Besides the fact that the change in water properties can affect cell integrity, water
is also essential for most biochemical reactions. In virtually all natural environments,
energy or sometimes other substrates necessary for growth (phosphates, sulfates,
nitrogenous compounds, among others) is present in rate-limiting concentrations (65).
Growth and survival depend, therefore, upon the ability of sequestering these sparse
resources more successfully than the competing species. The reduction of the substrate
diffusion rates and the increase in the viscosity of the water in the cells’ environment at
cold temperatures make it more difficult for the cell to acquire resources. The efficiency
of active uptake at low concentration depends on substrate affinity of uptake mechanisms
(65). Affinity for substrate uptake is frequently described by Monod type of saturation
curves relating growth rate to the concentration of the rate-limiting substrate (32). The
general paradigm is that when environmental temperatures decrease below the optimum
for growth there is concomitant decreased affinity for substrates as measured by umax/Ks.
The trend of decreased affinity with lowered temperatures applies to the uptake of both
organic and inorganic substrates (36, 66, 70).

A common strategy used to sustain cell activity at a permanently low temperature

is to produce cold-adapted enzymes with enhanced catalytic efficiency (14). In general,

mt!

extracellular enzymes for substrate uptake at low temperatures requires mainly increased
specific activity (kcat) (14, 20, 68). Alternatively, for secreted enzymes in marine
environments or intracellular enzymes that could face low substrate concentrations, a
decrease in Km (Michaelis-Menten constant) provides a higher substrate affinity (25, 37).

Enzymes are stabilized largely by noncovalent bonds, which have low energies of
stabilization (80). Decreases in temperature will change intramolecular bonds,
interactions with water and its associated ions, both leading to a possible compaction of
the protein core and hence, a reduction of enzyme flexibility (80). Hydrogen bonds and
electrostatic interactions are formed exotherrnically, so they are stronger at low
temperatures. In contrast, hydrophobic bonds are formed endothermically and are weaker
at low temperatures. These general considerations are reflected in more specific terms by
changes in frequency of particular molecular bonds and hence, amino acids, in cold-
active proteins, i.e., more polar and less hydrophobic residues, additional glycine
residues, a lower arginine/lysine ratio, additional surface loops with increased polar
residues and/or decreased proline content, lack of salt bridges, modified alpha-helix
dipole interactions, reduced hydrophobic interactions between subunits, and fewer
hydrogen bonds, aromatic interactions and ion pairs. All these features are not present in
the same cold-active enzymes, but are some of the characteristic changes found in cold-
active enzymes relative to their mesophilic/thermophilic counterparts (80). These cold-
adaptive features are illustrated in several reviews comparing cold-adapted enzymes with
mesophilic/thermophilic counterparts, such as lactate dehydrogenase, citrate synthase,

alpha-amylase and malate dehydrogenase among others (l3, 14, 37, 80).

wen-J“!

 

Microbial responses to temperature stress. Cold is a physical stress that drastically
modifies all physical-chemical parameters of a living cell, and thereby influences solute
diffusion rates, enzyme kinetics, membrane fluidity and conformation, flexibility,
topology and interactions of macromolecules such as DNA, RNA and proteins. In order
to overcome these physical effects caused by cold stress, cellular modifications may
occur (Table 1.1). The DNA becomes more negatively supercoiled and nucleoid -
associated proteins such as, Gyrase A (gyrA) and DNA-binding proteins HU-B (hupB)
and H-NS (hns) are suggested to be necessary for its relaxation (34, 81, 93). However,
studies in Escherichia coli, demonstrated that hns is essential for extended growth in the
cold, but not for cell survival immediately after cold shock. Additionally, null mutants for
hns display severe morphological alterations and eventually lyse in the cold (18).

The transcription system is also affected by the cold, for instance, the
transcription factor NusA is known to be involved in both termination and
antiterrnination of transcripts in E. coli and it is highly expressed at lower temperatures
(22, 73). Besides the transcription and translation of mRNA, the cells need to cope with
all the transcripts produced. The system responsible for mRNA degradation during cold
stress depends on the activity of 3’-5’Exonuclease PNPase (pnp) and possibly of the
DeaD RNA helicase (csdA) (4, 96, 97). Defects in mRNA degradation produce a cold-
lethal phenotype displayed by pnp mutants in Yersinia enterocolica (67) and E. coli (96).
A DeaD RNA helicase deletion mutant of E. coli has reduced growth rate and

filamentous growth at low temperature (34, 44).

Table 1.1. Summary of genes important for adapting to cold-shock stress

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Protein Functions References
AceE Decarboxylation of pyruvate (41, 45)
(Pyruvate dehydrogenase)
AceF Dihydrolipoyltransacetylase (41)
(Pyruvate dehydrogenase)
CspA RNA chaperone (30, 69, 95)
CspB RN A/DNA chaperone (1’) (54, 69)
C spE Regulation of CspA (3)
CspG RNA/DNA chaperone (7) (64, 69)
CspI Unknown (92)
CsdA RNA unwinding activity (44, 88)
DNA binding and replication (2)
DnaA (initiation); transcriptional
regulator
RbfA 30S ribosomal binding factor (42)
@fA Initiation factors: Binding of (45)
InfB charged tRNA-fmet to the 30 S (45)
ribosomal subunit
PNP Degradation of DNA (4, 45, 57,
~ 96)
Hsc66 Molecular chaperone (5 5)
HscB DnaJ homologue (55)
HUB Nucleoid protein; DNA (26, 62)
_ supercoiling
Trigger Factor ProlyI-isomerase activity and (50)
_ other functions
3ecA Recombination factor (45)
_GyrA DNA topoisomerase (33, 43, 56)
H-NS Nucleoid-associated DNA binding (18, 53, 69)
_ protein
NusA Involved in termination and (45)
_ antitermination
QtsA Trehalose phosphate synthase (49)
QtsB Trehalose phosphatase (49)
Qesaturases Unsaturation of membrane lipids (33, 53, 63)
gihydrolipomide acetyltransferase Decarboxylation of pyruvate (45)
LAlpha-glutamyltranspeptidase Glutathione metabolism (73)

 

For translation, ribosome assembly may be affected by cold stress, as suggested

by the cold-sensitive phenotype displayed by many ribosome assembly mutants in E. coli

and in yeast (16). In light of these considerations, it seems likely that the resumption of

 

this process, when interrupted by a sudden cold stress or when starting de novo ribosome
assembly at a suboptimal temperature, requires the presence of new types and /or
additional copies of proteins, RNA chaperones and helicases. Among the genes that
encode ribosome-associated proteins translated during cold stress there are cold-shock
protein A (cspA), DeaD-box RNA helicase (csdA), ribosome binding factor A (rbfA) and
initiation factor 2 (IF-2). The cspA product was proposed to act as a chaperone to make
translation more efficient during cold shock because it can bind to RNA and destabilize
its secondary structure (40, 71). The gene product of csdA exhibits RNA helicase
activity, which may help in unwinding RNA secondary structure for efficient translation

at low temperature (19, 73). Initiation factor 2 (IF2) mediates the binding of charged
tRNAfmet to the 308 subunit for initiation of translation (41). After translation of the

proteins, correct protein folding in the cold could be problematic and require the presence
of chaperones such as the DnaK homologue H5066 (55) and perhaps IF2 (10) while a
direct or indirect participation of Trigger factor (TF) in this process has also been
suggested (34).

Besides the production of cold induced proteins, several other known cold stress
cellular responses occur to maintain cell viability, such as the cell membrane
composition. To avoid membranes from becoming less fluid under cold temperatures (77,
79), cells synthesize unsaturated and branched fatty acids. This phenomenon has been
studied in detail in two cyanobacteria, Anabaena variabilis and Synechocystis PCC 6803,
in which mutants defective in the desaturation of fatty acids (desA) have a lower rate of
growth at low temperature (91). Grau and collaborators (33) proposed that DNA

supercoiling may regulate unsaturated fatty acid synthesis in Bacillus subtilis since the

desaturation of fatty acids induced after transfer to low temperature is inhibited by
addition of novobiocin, an antibiotic that affects DNA gyrase activity.

Although increased unsaturation and decreased chain length of fatty acids
constitute the major modifications of cell membrane, other membrane associated
molecules may. also play important roles in low temperature adaptation of Antarctic
psychrotrophic bacteria (12, 38, 73). One such molecule is a carotenoid pigment, which
remains associated with the cell membrane. Studies in vitro have indicated that the
pigments interact with cell membrane and increase its rigidity (38). Since a large number
of Antarctic bacteria have been found to contain carotenoid pigments in their membrane,
it has been speculated that these pigments may have a role in buffering membrane fluidity
when there is an up shift in environmental temperature (38). In such an up-shift, the
caroteinoid pigments may maintain the homeoviscosity of membrane prior to the de novo
synthesis of saturated fatty acids. However, experimental evidence is still lacking for this
hypothesis.

Cells undergo many cellular modifications in order to survive and grow at
extreme temperatures. A network of genes that are activated simultaneously or in cascade
fashion generates these modifications. However, how the cascade of genes is activated
and the effect of some of these genes in different microorganisms is unexplored,
especially in psychrotrophs and psychrophilic microoganisms.

Biodiversity in cold habitats. The lowest temperature reported for microbial activity is -
20°C in permafrost soil and sea ice (15). Cold-adapted microorganisms have been found
in Antarctic sub-glacial soil and permanently ice-covered lakes, cloud droplets, ice cap

cores from considerable depth, snow, glaciers and cold deep-sea environments (17, 85).

Both Bacteria and Archaea have been surveyed in polar and several other cold
environments (9, ll, 24, 51, 90). The Bacteria are usually present in greater number and
diversity than the Archaea. The exceptions are the cold interior and deep waters of the
ocean, well below the upper mixed layer. There, the Archaea appear in numbers elevated
above their counterparts in surface waters (17, 72) and above the Bacteria at the same
depths (51). In the deep Pacific Ocean, the populations of Crenarchaeota largely account
for the Archaeal with population densities matching or exceeding the Bacterial densities
(51).

Even though most of the biodiversity studies in cold habitats focus on the domain

Bacteria, this domain still holds surprises, since conventional cultivation produces
isolates from cold environments that grow at -1°C, containing many novel 16S rRNA

sequences (46, 52). Most isolates from Arctic and Antarctic permafrost were
psychrotrophic rather than psychrophilic, although mesophiles and even a limited number
of therrnophiles were detected (85). A wide diversity of bacteria including aerobic and
anaerobic heterotrophs, methanogens, iron reducers, sulfate reducers, nitrifying and
nitrogen-fixing bacteria representing over 30 bacterial genera, including Arthrobacter,
Aeromonas, Bacillus, Cellulomonas, Exiguobacterium, Flavobacterium, Micrococcus,
Myxococcus, Nitrobacter, Pseudomonas, Psychrobacter, Rhodococcus, Streptomyces,
and others have been isolated from Arctic permafrost (29, 70, 76, 82, 90). In Antarctic
permafrost the genera Arthrobacter, Bacillus, Streptomyces were predominant (85), even
though Exiguobacterium (23) and Psychrobacter (8, 83, 84), among others, were also

found.

10

The interface between the solid and liquid phase has the coldest ice forms so far
examined (sea ice at -20°C) and it is called eutectic interface. Microscopic studies in situ
have shown that living bacteria can be found in this eutectic interface (47), these
microorganisms are called eutectophiles (l7). Kanavarioti and collaborators (48) by
exploring ice eutectic phase, found that the ice matrix with its concentrated solutes in the
spaces between ice crystals can propitiate oligonucleotide polymerization reactions.
These findings suggest that microorganisms may be able to survive and have metabolic
activity in these eutectic interfaces.

Besides, Archaea and Bacteria, viruses are also found in cold environments,
however this domain is the least explored in cold habitats. A marine virus-host system,
unique in its cold adaptation, was obtained from Arctic sea ice (5, 6, 89, 94). This
knowledge gives us insight into the dynamics of polar microbial ecosystems and explores
lateral gene transfer at cold temperatures.

Conclusions. Understanding how cold adapted microorganisms survive cold
temperatures is of ecological importance, as well as biotechnological and evolutionary
significance. Ecologically, these microorganisms are vital to nutrient recycling and for
production and consumption of greenhouse gases (86). The fact that these organisms can
survive in permanently frozen environments may indicate that they possess unique
mechanisms that allow them to maintain viability for very long periods of time. Also,
some enzymes may have value in biotechnology. Low temperature enzymes may be used
in industry, agriculture, bioremediation, and in food microbiology for preservation or
avoidance of food spoilage (31). Additionally, recent evidence of massive amounts of

shallow ground ice near the surface of Mars (7, 85) and the realization that the majority

11

of cosmic bodies beyond Earth are cold have made cold terrestrial environments
significant extraterrestrial analog sites (27, 39, 74, 75). Studies in frigid environments on
Earth will aid in the testing and refinement of instruments and procedures for looking for
life on other planets, in the development of overall concepts for cold-adapted biology,
and will allow the collection of baseline data for comparison to results from Mars (60).
Microorganisms that are able to survive in frozen soil on our planet and on other
planets may have ancient traits since they have very low metabolic activity at such
temperatures and consequently have evolved more slowly than mesophilic counterparts.
Therefore, analysis of their features may be a window into microbial life as it was several
million years ago. Even though studies in cold environments are advancing rapidly, the
complete understanding of the microbial community and its functions is still in its

infancy.

ACKNOWLEGDEMENTS
This work was supported by a cooperative agreement with NASA Astrobiology

Institute, number NCC2-1274.

12

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21

CHAPTER 2

BIOGEOGRAPHY, DIVERSITY AND ABUNDANCE OF
EXIGUOBAC TERI UM SPP. AND PS YCHROBAC T ER SPP.

22

ABSTRACT

The biogeography and phylogenetic diversity of Psychrobacter and Exiguobacterium was
studied in 54 soil and sediment samples from polar, temperate and tropical environments
to determine their habitat preferences. Quantitative PCR revealed that both genera were
more prevalent in but not restricted to the polar environments. Three sites from each
climatic region and with high abundance of both genera were selected to build 16S rRNA
gene libraries. The clone libraries were analyzed using FastGroupII, DOTUR and f-
libshuff to determine their diversity, structure and similarity. Exiguobacterium spp. and
Psychrobacter spp. both had patchy distributions, which showed correlation to salinity,

pH, potassium and Cu.

INTRODUCTION

Ecologists describing microbial biogeography typically invoke Baas-Becking’s
statement: “Everything is everywhere, but, the environment selects” (7). Few studies
have, however, attempted to verify this statement (14, 20, 35), as well as, to determine
which environmental factors exert the strongest influences on a population’s distribution
in nature (12, 21). It recently has been argued that the ubiquitous distribution of some
extremophile species is implausible due to barriers to their surviving dispersal (19, 35).
Studies on biogeography of microbes from hot springs or geothermal sources have shown
endemism (21, 35). Studies with sea ice bacteria indicate that members of some genera
occur at both poles but the species found in the poles are not in warmer environments,
hence at the species level they are not cosmopolitan (30).

Considering that 80% of Earth’s biosphere is permanently cold, it is surprising

that few biogeography studies have been done with microorganisms from cold

23

environments (30). Among the cold habitats of our planet, microorganisms inhabiting
permafrost are strong candidates for biogeography and biodiversity studies. Permafrost
microorganisms have been living in frozen Siberian sediments for as long as 2 to 3
million years, conditions that have prevented gene flow from any outside biota (34) and
prevented dispersal to other environments.

Previous studies in Siberian permafrost soils yielded isolates of Exiguobacterium
and Psychrobacter from geological strata frozen for 20 thousand to 3 million years (I, 23,
33). Another study demonstrated ubiquity of the Exiguobacterium genus in the Siberian
permafrost (24). In addition to Siberian permafrost, species of Exiguobacterium and
Psychrobacter have also been isolated from several other cold environments, such as
Antarctica, sea ice and the Himalayan mountains (2, 3, 28, 29) . The fact that they seem
to be successful in cold environments and that one is a Grarn-positive (Exiguobacterium)
and the other is a Gram-negative (Psychrobacter), make them good models to test Baas-
Becking’s statement. The results show that these genera are not resctricted to the poles,

but are favoured in cold and polar environments.

MATERIAL AND METHODS
Sample collection. A total of six sediments and forty-eight soil samples were collected

from a wide range of ecosystems with diverse climates and site characteristics (Table

2.1). All samples were stored frozen at -20°C until processed.

24

Table 2.1. Location and information of sampling sites.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sample Description Sample Sites (ytffs) 1:61:31] 35:55:53:
P1 Puerto Rico: Ballena beach Recent 0 to 17° 57.243'N,
0.1m 66° 50.858'W
P2 Puerto Rico: Carmelitas Recent 0 to 18° 26’30”N
underground cave system - 0.1m 66° 21 ’15”W
Ortencia cave
P3 Puerto Rico: Carmelitas Recent 0 to 18° 26’30”N
underground cave system - Reina 0.1m 66° 21 ’15”W
cave
P4 Puerto Rico: Ceiba mangrove Recent 0 to l8°13’40.40”N
0.1m 65°35’21.31”W
P5 Puerto Rico: San Juan mangrove Recent 0 to 18°21 ’06.85”N
0.1m 65°36’53.22”W
P6 Puerto Rico: Carmelitas Recent O to 180 26’30”N,
underground cave system - 0.1m 66° 21’ 15”W
Murciélago cave
P7 Puerto Rico: Guanica dry forest Recent 0 to 17°58’N, 66°51’W
0.1m
HW Hawaii: Kohala forest Recent O to 20°03’N, 155°41’E
0.1m
Bl Brazil: Forest, Guanabara 11, 1-5 Recent 0 to 0.2 4° 24’ 20.0” S, 69°
m 54’ 27.7”W
82 Brazil: Forest, Guanabara II, 1- Recent 0 to 0.2 4° 24’ 20.0”S, 690
10 m 54’ 27.7”W
B3 Brazil: Forest, Guanabara II, 1- Recent 0 to 0.2 4° 24’ 20.0”S, 69°
16 m 54’ 27.7”W
B4 Brazil: Pasture, Benjamin Recent 0 to 0.2 4° 22’ 24.2”S, 70°
Constant, 6-84 m 01’ 39.4”W
BS Brazil: Pasture, Benjamin Recent 0 to 0.2 4° 22’ 24.2”S, 70°
Constant, 6-91 m 01’ 39.4”W
B6 Brazil: Pasture, Benjamin Recent 0 to 0.2 4° 22’ 24.2”S, 70°
Constant, 6-92 m 01’ 39.4”W
MI Michigan: KBS deciduous Recent O to 42° 24' N,
Forest - DF-l 0.1m 85° 24' W
M2 Michigan: KBS deciduous Recent 0 to 42° 24' N,
Forest - DF-2 0.1m 85° 24' W
M3 Michigan: wheat plantation KBS Recent 0 to 42° 24' N,
-T1Rl 0.1m 85° 24' W
M4 Michigan: wheat plantation KBS Recent 0 to 42° 24' N,
-T1R2 0.1m 85° 24' W
M5 Michigan: mid-successional Recent 0 to 42° 24' N,
communifl KBS -T8R1 0.1m 85° 24' W

 

 

 

 

 

25

 

Table 2.1 (cont’d).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

M6 Michigan: mid-successional Recent 0 to 42° 24’ N,
community KBS -—T8R2 0.1m 85° 24’ W

M7 Michigan: Baker Woodlot, Recent 0.1m 42°44’N, 08°42’W
Rachana Raj endra Bird
Sanctuary -— MSU

IA Iowa: Prairie wetland, Jasper Recent 0 to 41°48’N, 09°30W
county 0.1m

A1 Antarctica: Bratina Island — fresh Recent 0 to 0.1 78° 01’S,
pond m 165° 32’E

A2 Antarctica: Bratina Island - Recent 0 to 0.1 78° 01 ’S,
brack pond m 165° 32’E

A3 Antarctica marine sediment: Recent 20m 62° 05,1255’S,
Commandante Ferraz station 58° 23,390’W

A4 Antarctica marine sediment: Recent 20m 62° 04,91 ’ S
Punta Ulmann 58° 20,15’ W

A5 Antarctica marine sediment: Recent 20m 62° 05,845’S,
Botany Point 58° 20,144’W

A6 Antarctica marine sediment: Recent 30m 62° 05,4317’ S
Macchu Picchu 58° 28,5578’ W

A7 Antarctica marine sediment: Recent 20m 62° 10,3337’ S
Arctowski 58° 31,3476’ W

A8 Antarctica marine sediment: Recent 30m 62° 10,3337’ S
Arctowski 58° 31,3476’ W

S] Siberian Permafrost: Kolyma 5-10 tds 2.55m 70°05’N, 159°55’E
Lowland, Cape Chukochii, East
Siberian Sea coast, tundra zone

82 Siberian Permafrost: Kolyma 5-10 td 8.55m 70°05’N, 159°55’E
Lowland, Cape Chukochii, East
Siberian Sea coast, tundra zone

S3 Siberian Permafrost: Kolyma 5-10 td 14.95m 70°05’N, 159°55’E
Lowland, Cape Chukochii, East
Siberian Sea coast, tundra zone

S4 Siberian Permafrost: Cape 5-10 td 6.3m 129° 30’E, 71°40’N
Bykovskii Laptev Sea coast,
tundra zone

S5 Siberian Permafrost: Cape 5-10 tds 6.8m 130° OO’E, 72° OO’N
Bykovskii Laptev Sea coast,
tundra zone

S6 Siberian Permafrost: Cape 5-10 td 3m 130O OO'E, 72° OO'N
Bykovskii Laptev Sea coast,

 

tundra zone

 

 

 

 

26

 

Table 2.1 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

S7 Siberian Permafrost: Cape 5-10 td 7.5m 130° 00'E, 72° OO'N
Bykovskii Laptev Sea coast,
tundra zone

S8 Siberian Permafrost: Kolyma 20-30 td 20m 70°05'N, 159°55'E
Lowland, Cape Chukochii, East
Siberian Sea coast, tundra zone

S9 Siberian Permafrost: Cape 12-40 td 2.8m 129° 30'E, 71°40'N
Bykovskii Laptev Sea coast,
tundra zone

SIO Siberian Permafrost: Cape 12-40 td 8m 129° 30'E, 71°40'N
Bykovskii Laptev Sea coast,
tundra zone

31] Siberian Permafrost: Cape 12-40 td 13m 129° 30'E, 71°40'N
Bykovskii Laptev Sea coast,
tundra zone

812 Siberian Permafrost: Cape 12-40 td 23.3m 129° 30'E, 71°40'N
Bykovskii Laptev Sea coast,
tundra zone

Sl3 Siberian Permafrost: Cape 12-40 td 33m 129° 30'E, 71°40'N
Bykovskii Laptev Sea coast,
tundra zone

S14 Siberian Permafrost: Cape 12-40 td ’ 37.5m 129° 30'E, 71°40'N
Bykovskii Laptev Sea coast,
tundra zone

S15 Siberian Permafrost: Cape 15-20 td 4.8m 1300 00'E, 72° OO'N
Bykovskii Laptev Sea coast,
tundra zone

Sl6 Siberian Permafrost: Cape 15-20 td 8.15m 130° 00'E, 72° OO'N
Bykovskii Laptev Sea coast,
tundra zone

Sl7 Siberian Permafrost: Kolyma 20 td 11m 68°50'N, 161°02'E
Lowland, forest-tundra zone, left
bank of Kolyma river,
Khalarchinskaya tundra sandy
plain

S18 Siberian Permafrost: Cape 300-400 22.5m 140°10'E, 72°55'N
Svyatoi Nos, Laptev Sea coast, td
tundra zone

Sl9 Siberian Permafrost: Cape 3 18.1m 130° 00'E, 72° OO'N
Bykovskii Laptev Sea coast, million
tundra zone

S20 Siberian Permafrost: Cape 3 24m 130° 00'E, 72° 00'N
Bykovskii Laptev Sea coast, million
tundra zone

 

 

 

 

 

27

 

Table 2.1 (cont’d)

 

 

821 Siberian Permafrost: Cape 3 24.4m 130o 00'E, 72° 00'N
Bykovskii Laptev Sea coast, million
. tundra zone
S22 Siberian Permafrost: Kolyma 2-3 16.5m 66°50'N, 62°30'E

Lowland, Krestovka River, right million
inflow of Kolyma River (north
taiga)

S23 Siberian Permafrost: Kolyma 2-3 18.7m 66°50'N, 62°30'E
Lowland, tundra zone, Mouth of million
Malaya Kon'kovaya River, right
bank

S24 Siberian Permafrost: Kolyma 2-3 19.9m 66°50'N, 62°30'E
Lowland, tundra zone, Mouth of million
Malaya Kon'kovaya River, right
bank

KBS: Kellog biological station, MSU: Michigan State University

 

 

 

 

 

 

 

 

 

DNA extraction. Total community genomic DNA was extracted using the Fast DNA
SPIN kit for soil (Bio 101, Q BIOgene) with some modifications, namely the first step of

the extraction was a grinding step using liquid nitrogen followed by treatment with 100
pl of lysozyme (50 pg ul '1) at room temperature before using the kit. The quality of the

extracted DNA was analyzed by electrophoresis on a 1% agarose gel. DNA
concentrations were measured by absorbance at 260 nm.

Quantitative real-time PCR assays (Q-PCR). The primer sets for rpoB, gyrB and
hypothetical genes and conditions for Exiguobacterium spp. quantitative real-time PCR
were described previously (24). Detection was only considered positive when at least
two genes were amplified by these primer sets. Data are represented as copy number
averages and standard deviations. The primers used for Psychrobacter spp. quantification
were 432-F (5’-GCA CTT TAA GCA GTG AAG AAG A- 3’) and 476-R (5’-TAT TCT

GCA GCT AAT GTC ATC G- 3’). These primers were designed by Dr. Hector Ayala-

del-Rio. The reaction mixture contained 1X SYBR green PCR buffer, 1.75 mM MgC12,

28

0.2 mM dNTPs, 0.05 U 111'1 Amplitaq Gold, 0.15 pM and 0.4 mg ml'1 of bovine serum
albumine (BSA) and the amplification settings were the standard for real-time PCR with
annealing and extension at 59°C for l min. The real-time PCR reactions and primer

optimizations for both genera were done as described previously (24). The increase in

fluorescence emission was monitored during PCR amplification using the 7700 Sequence
Detector (PE Applied Biosystems). The CT values obtained from each sample were

compared with the standard curve to determine the initial copy number of the target gene.
Principal component analysis was performed with 22 samples described in Table
2.2. The variables for the principal component analysis consisted of Q-PCR results for
each genus as well as nine environmental variables selected among 14 variables
measured (phosphorus, potassium, magnesium, calcium, cation exchange capacity,
copper, manganese, zinc, iron, pH, organic matter, moisture, soluble salts and average
annual temperature) that had statistically significant Pearson correlation with at least
another variable. The variables were transformed by Box-Cox transformation to improve
normality of the sample, the principal component analysis was performed with a
correlation matrix and the results were displayed by a correlation biplot. The program
XLSTAT was used for data transformation and principal component analysis.
Genus specific clone library construction and sequencing. Primers for conserved
regions of the 168 rRNA genes for the genera Exiguobacterium spp. and Psychrobacter
spp. were designed using ARB based on alignments of reference strains for each genus

and 50 other Gram-positive and Gram-negative microorganisms (16).

29

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30

The annealing temperatures for Exiguobacterium spp. and Psychrobacter spp.

primer sets were 59°C and 57°C, respectively. Amplification, for all primers, was by

standard procedures, except MgC12 concentrations that were optimized to 1.75 mM for

Psychrobacter spp. and 1.5 mM for Exiguobacterium spp. (8). Primer sequences used for
the 16S rRNA gene were 432-F and 823-R (5’-TCA AGG GAC CCA ACG ACT AGT
A- 3’) for Psychrobacter spp. and Exi16S-F (5’- GAT GAA AGG CGC TYC GGC G-
3’) and Exil6S-R (5’- CGG TCA RGG GGA TGT CAA GAG TT- 3’) for
Exiguobacterium spp. Amplicon sizes were approximately 400 bp and 800 bp,
respectively.

The specific 16S rRNA gene amplicons for each genus were cloned using the
TOPO TA Cloning kit for sequencing (Invitrogen Life Technologies) and sent to
Macrogen Inc. (Seoul, Korea; www.Macrogen.com) for sequencing with primers for the
cloning vector (M13F). Sequences generated in the present study were deposited in
GenBank.

Clone library analysis. The 168 rRNA gene sequences from the clone libraries were
processed by using the pipeline quality filter tools on the Ribosomal Database Project

(RDP-II) website (5) ( httpzx‘”rtlp.cntc.msu.edu). The Classifier tool provided by RDP-II

 

was used to assign the 168 rRNA gene sequences to the taxonomical hierarchy. Aligned
sequences assigned to Exiguobacterium or Psychrobacter were downloaded from RDP-II
for further analyses. The aligned sequences were uploaded to FastGroupII program (37)
to cluster sequences with 99% similarity including gaps. One representative of each

dominant cluster was used to construct the phylogenetic tree within MEGA 3.1

31

 

environment (15) by the neighbor-joining method. The robustness of the inferred tree was
evaluated by applying 1000 bootstrap re-samplings.

Distance matrix files for each clone library were downloaded from the RDP-II
pipeline to determine alpha diversity through Distance-Based Operational Taxonomic
Unit and Richness (DOTUR) program (26), and to compare clone library similarity via

statistical tests provided by f-libshuf program (27).

RESULTS AND DISCUSSION

Distribution and abundance data of Exiguobacterium spp. and Psychrobacter spp.
show that both genera are more commonly found in both Antarctic and Arctic samples
than in the non-polar samples (Figure 2.1). Psychrobacter spp., however, seems to be
more successful in Antarctica than Exiguobacterium spp., as the quantity of
Psychrobacter spp. is higher in Antarctica than in the Siberian permafrost. The Antarctic
samples, however, are both from non-frozen sediments: ponds A1 and A2, and coastal
marine sediments A3 to A8, which had the highest population densities. In temperate
(Michigan and Iowa) and in tropical (Brazil, Puerto Rico and Hawaii) environments, the
distribution and abundance of Psychrobacter spp. was patchy and when present, in very
low density. For Exiguobacterium spp. the distribution was also patchy but when present
its abundance was similar to that found in the colder habitats. The fact that both genera
were not found in most of the non-polar soil samples suggests that they are not
cosmopolitan, in the strict sense; however they are not restricted to the poles as

previously suggested for some polar bacteria (30).

32

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The patchy distribution of these microorganisms correlates with some physico-
chemical factors of their environment (Figure 2.2). Exiguobacterium spp. and
Psychrobacter spp. populations have a high correlation with pH and salinity, as well as
potassium (K+), cation exchange capacity (CBC) and the micronutrient copper (Cu).

Copper is an essential micronutrient for respiring bacteria, e. g. cytochrome c
oxidase and some peroxidase dismutases (17); both genera are aerobes. The fact that pH
showed a strong correlation with the presence of these genera is not surprising, since this
is a well known population determinant. Soils with near-neutral pH have from 26% to
60% higher richness than more acidic soils (9). Exiguobacterium spp. and Psychrobacter

spp. abundance seem to follow the same pattern in regard to pH, preferring neutrality.

 

Variables (axes F1 and F2: 76.60 %) I

 

 

1 I . l
0.75
Psychrobacter
0.5 pH
l-inguobacterium
Salinity
A 0.25
at .-/ K u
8 ‘EC
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3.3
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-0.75 l

 

-1 .-
-1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1

F1 (60.81 %) ,

 

Figure 2.2. Correlation biplot from physicochemical characteristics of principal
component analysis

34

Potassium is the principal cation in bacteria, and it not only plays a role as a
cofactor for many enzymes and ribosomes, but is also responsible for pH and osmotic
homeostasis (36). Environments with pH 6 to 8, which seems to be the optimum
environmental pH range for these genera, triggers K+ influx to raise the intracellular pH
(36). This physiological need for K+ to maintain the cell pH homeostasis, could explain
their preference for higher environmental concentrations of K+.

The effect of salinity on the abundance of these genera can be explained by their
physiology. Studies with Psychrobacter spp. and Exiguobacterium spp. isolated from the
Siberian permafrost have shown that these genera can tolerate increased osmolarity and
showed associated changes in membrane composition, cell morphology and size (22).
Besides, all isolates from Exiguobacterium spp. and Psychrobacter spp. can grow with
the addition of NaCl at various concentrations in their medium (6, 23, 25, 28). This
evidence suggests that these genera are adapted to salinity, which would explain the
strong correlation of the presence and high abundance of these genera to moderate to high
salinity habitats, i.e. Antarctic marine sediments, the Puerto Rican mangroves and the
Siberian permafrost, which due to its frozen water status has low water activity (22).

While these genera are not restricted to the poles, it may be that species or
subspecies may be specially adapted to particular temperature regions. We examined
OTU (Operational Taxonomic Unit) diversity patterns from very different geographic
locations for each genus in which they were abundant. The number of clones for each site
was determined by rank abundance curves, which reached a plateau (data not shown) and
ensured that most phylotypes were sampled (Table 2.3). To quantitatively measure

diversity in the samples (Table 2.3), we used the Shannon and Simpson indices and

35

 

Chaol estimator (11, 13, 18). The data from all the indices (Table 2.3), as well as the
abundance of OTUs in each site (Figure 2.3) depicted similar results, showing that the
diversity within each genus and sampling site was different. Even though in some sites
the quantity of Exiguobacterium spp. was higher than of Psychrobacter spp. (Figure 2.1),
the diversity within Exiguobacterium was never higher than for Psychrobacter (Figure
2.3). Furthermore, the results indicate an apparent latitudinal gradient in diversity at the
species level for both genera: Psychrobacter spp. and Exiguobacterium spp. were more
diverse in the Antarctica samples with less diversity in Michigan and even less diversity
in Puerto Rican samples (Figure 2.3 and Table 2.3). Similar distance decay relationships
are seen with macroorganisms (31) and with Pseudomonas genotype, in which genetic
similarity of Pseudomonas isolates was negatively correlated with geographic distance at
regional distances, but not at continental scales (4, 10). The higher abundance and
diversity of these genera at the poles than in the other regions suggest that the preferred
habitats for these genera are the cold, polar environments.

Table 2.3. Diversity comparisons of 16S rRNA environmental clone libraries

 

 

 

 

 

 

 

 

Samplesa Genus studied Total No No. of Shannon Simpson Chao l
of OTUs Index Index estimator

sequences (D)

A3 Psychrobacter 129 21 2.60 0.09 21.43

M5 Psychrobacter 150 14 2.22 0.13 17.00

P5 Psychrobacter 137 1 1 1.84 0.21 1 1.50

A5 Exiguobacterium 149 7 1.53 0.26 7

M7 Exiguobacterium 109 4 0.34 0.84

P3 Exiguobacteri um I 3 5 1 0 l 1

 

 

 

 

 

 

 

 

a See table 2.1 for sample code

The result obtained by f-libshuff verifies whether two samples are drawn from the
same populations or whether one is a subset of the other. The Puerto Rican and Michigan

clone libraries for Psychrobacter displayed significantly different populations from these

36

rm— — '7

 

from Antarctica (Figure 2.4). However, the f-libshuff analysis for Puerto Rico and
Michigan clone libraries for Psychrobacter spp. revealed that the Puerto Rican population
is a subset of the Michigan population, i.e., they have many OTUs in common; however,
Michigan has more diverse OTUs. All the Exiguobacterium from the different sites had

significantly different populations, i.e. all samples had different OTUs.

 

100% - .-g_ _.__
. a d. - —
90% - m1" Stu; U
80% I ‘95.",
70% « m

60% - ,w

'3‘"?
_‘Lteo W

50% ‘ £12
I A12

40% i
30% . H11

 

Distribution of OT Us abundance
(percentage)

 

   

 

 

20% -
10% -
0% -
Antarctica Michigan Puerto Ricxmarctica Michigan Puerto Rico
Y W
Psychrobacter Exiguobacterium

Figure 2.3. Distribution of OTUs abundance in different soils. The colors are ranking the
most abundant OTU to the least abundant. The labels correspond to the clones
represented in the phylogenetic trees for each genus.

37

1.2 7 z _ _
I
l
1 .x_,_x_..x_--x—ozx—tiffjgxfissx—--x
Ix" .- o' ' '
A 0.8
8 /- —"' 'Cwu)
o ',
E 0.6 1x ' ' ' Own-Pm
9 _ 2
‘3 (CMI’CMIPRI
O
0.4
P-value = 0.0028

 

 

 

 

0 0000
0 0025
0 0050 I
0 0075
0 0100
0.0125
0 0150
0 0202
0 0225
0 0226

Evolutionary Distance (D)

0.0252

0.0304

 

 

 

 

 

 

0.007

0.006

0.005

0.004

2

0.003

(Ox-Cw)

0.002

0.001

B
1.2 T - 0.005
“r 0.0045
1 , :— 4.»...- -;:- 5"; -..'- H'- UT—T‘ W _ 0 004
P 0.0035
0.8 ‘r
g »o.003
8) -’"" C(PR)
g 0.6 - _ _ Clem) -- 0.0025
>
8 (CPR'CPRMllz -» 0.002
0.4 1-
* 0.0015
P- value = 0.0028
* 0.001
0.2 I»
r 0.0005
0 1 1L 1 i 0

 

 

 

 

0 0.0025 0.005 0.0075 0.01 0.0125
Evolutionary Distance (D)

Figure 2.4. Results of selected I-LIBSHUFF comparisons. Homologous (Cx) and
heterologous (ny) coverage curves for 16S rRNA gene sequence libraries from
Psychrobacter spp. in Michigan and Puerto Rico. Solid lines indicate the value of (Q,-

ny)2 for the original samples at each value of Evolutionary Distance (D). D is equal the
Jukes-Cantor evolutionary distance determined by RDP-II pipeline. Broken lines indicate

38

0.015

(CX’lez

 

 

the 950th value (or P=0.05) of (Cx-ny)2 for the randomized samples. (A) Comparison of
Psychrobacter clones from Michigan soil (x=MI) and from Puerto Rico soil (y=PR). (B)

Comparison of Psychrobacter clones from Puerto Rico soil (x=PR) and from Michigan
soil (y=PR).

P. fozll
44- A Mlchlgan H1 1
P. okh otskcnsls
P. luti LMG 21276
0 Puerto Rico 603
8 A Michigan H02
5 0 Puerto Rico H02
P. arctlcus 273-4
0 Puerto Rico 503
0 Puerto Rico A07
P. glacialis 0043
P. cryohalolcn :15 K5
D Antarctica GI o
A Michigan 507
D An tanctica co7
D Antarctica H02
1:! Antarctica £07
7 P. clbarius JG—220
A Michigan coz
P. lmmobilis DSM 7229T
Antarctica H1 0
6 A Michigan A12
6 0 Puerto Rico £12
[-A Mldilgan F07
— D Antarctica H031!
5 2 D Antarctica H03
P. faecalls 05-38
9 P. pulmonls CECT 59891’
a P ch robacter sp. lkaltc

   
   
 
 
 
  
   
  
 

 

 

 

 

 

Puerto Rico 003
A Michigan cos
0 Puerto Rico 304
Moraxella atlan tau
l-—-1
0. 01

Figure 2.5. Phylogenetic tree based on 16S rRNA gene sequences of Psychrobacter
strains and the top seven dominant OTUs in the clone libraries from Michigan (A),
Puerto Rico (0) and Antarctica sediment (E1). The trees were produced by the neighbor-
joining method and rooted using the 16 S rRNA gene from B. subtilis. The nodes with
less than 45% bootstrap values were not added to the tree. The scale bar represents
changes per nucleotide.

39

 

 

 

Eaurantiacum
E. indicum K22-26

A Michigan A04

Exiguobacterium sp. 8N

Enomiense

Eaestuarii strain TF-16

EJactigcncs

Exiguobactcrium sp. A 1

— E.taiwanensa

Exiguobacterium sp. indla orange

Exiguobacterium sp. M 37

Exiguobacterium sp. AT4

Exi uobacterium sp.AT1b
Antarctica 004

6 6 E.mari'num strain TF-80

D Antarctica 512
D Antarctica 010
i; D Antarctica 808
5 1 DAntarctica C05a

D Antarctica D02
99 DAntarctica B12

64

\l

5

 

54

 

 

 

 

 

7 D Antarctica D 1 1
D Antarctica 605

Eacetyiicum
6 5 l Eslbiricum strain 255-15

Exiguobacterium sp. strain 5138
9 1 4 Exiguobacterium sp. india Stream
Esibiricum strain 7-3
6 D Antarctica 005
s a- 0 Puerto Rico 507
F- 0 Puerto Rico B12
E.oxidotoicrans
0 Puerto Rico H06
- 0 Puerto Rico 606
81 E.undac
Sundae strain 190-11
9 6 D Antarctica 604
A Michigan car
9 O Eantarcticum
3 0 AM ichigan 803

 

 

 

 

 

7O
98

 

 

 

 

 

 

B.subtilis

0.005

Figure 2.6. Phylogenetic tree based on 16S rRNA gene sequences of Exiguobacierium
strains and clone libraries from Michigan (A), Puerto Rico (0) and Antarctica sediment
(C1). The trees were produced by the neighbor-joining method and rooted using the 168

rRNA gene from B. subtilis. The nodes with less than 45% bootstrap values were not
added to the tree. The scale bar represents changes per nucleotide.

The phylogenetic trees from Psychrobacter spp. and Exiguobacterium spp. show

that new species are yet to be identified, especially in Antarctica. There are many clusters

40

 

of clones that do not contain any known described species (Figure 2.5, 2.6). The
Psychrobacter spp. tree, confirms the results from f-libshuff that Michigan and Puerto
Rico share similar OTUs, since several clusters contain clones from both habitats.
Additionally, some Puerto Rican clones also contained OTUs with high similarity to
isolates from the Siberian permafrost, such as P. cryohalolentis K5 (1) but also to isolates
found in warmer habitats, such as P. pulmom’s (32) that was isolated from lamb lungs.

In the case of Exiguobacierium spp. all the Puerto Rican clones clustered with E.
oxidoiolerans isolated from a fish processing plant, a strain that tolerates 12% of NaCl,
pH values from 7 to 10 and is a mesophilic (38). One group of clones from Antarctica
had identical sequence to several isolates from the Siberian Permafrost, such as E.
sibiricum strains 7-3 and 255-15, Exiguobacierium sp. strain 5138 (23), confirming that
both poles share similar species. The Exiguobacierium phylogenetic tree also confirmed
the results from f-libshuff, since the clones from the diverse geographic locations never
clustered with one another.

This study shows that Exiguobacterium spp. and Psychrobacter spp. are more
commonly found and have higher densities in polar regions, but they can be detected in
temperate and tropical sites. The later is more likely the case when physicochemical
conditions such as salinity, K+ and pH are similar to these in their polar sites. In the
context of the Baas-Becking statement, the data suggest that Exiguobacterium and
Psychrobacter have been widely distributed in diverse sites but polar and other low water

activity environments favor their growth.

41

 

ACKNOWLEGEMENTS

This work was supported by a cooperative agreement with NASA Astrobiology
Institute, number NCC2-1274.

We also acknowledge Andrew Corbin and the NSF Long-Term Ecological
Research Program at the Kellogg Biological Station for the Michigan samples, and Peter
Bergholz for the samples from Bratina Island during the 2005-2006 NSF Antarctic

Biology Course (OPP Project B-301-M).

42

 

 

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46

 

CHAPTER 3

IDENTIFICATION AND CHARACTERIZATION OF
EXIGUOBAC TERI UM ISOLATES FROM THE PERMAFROST

Rodrigues, D. F., J. Goris, T. Vishnivetskaya, D. Gilichinsky, M. F. Thomashow,
and J. M. Tiedje. 2006. Characterization of Exiguobacierium isolates from the Siberian
permafrost. Description of Exiguobacterium sibiricum sp. nov. Extremophiles 10:285-94.

47

 

ABSTRACT
Three Gram-positive bacterial strains, 7-3, 255-15 and 190-11, previously isolated from
Siberian permafrost, were characterized and taxonomically classified. These

microorganisms are rod-shaped, facultative aerobic, motile with peritrichous flagella and
their growth ranges are from -2.5°C to 40°C. The chemotaxonomic markers indicated that

the three strains belong to the genus Exiguobacierium. Their peptidoglycan type was A30.
L-Lys-Gly. The predominant menaquinone detected in all three strains was MK-7. The
polar lipids present were phosphatidyl-glycerol, diphosphatidyl-glycerol and
phosphatidyl-ethanolamine. The major fatty acids were iso-C13:0, anteiso-Cl320, iso-
C 15:0, C 16:0 and iso-C1720. Phylogenetic analysis based on 16S rRNA and six diverse
genes, gyrB (gyrase subunit B), rpoB (DNA-directed RNA polymerase beta subunit),
recA (homologous recombination), csp (cold shock protein), hsp70 (ClassI-heat shock
protein — Chaperonin) and ciiC (isocitrate dehydrogenase), indicated that the strains were
closely related to E. undae (DSM 14481T) and E. antarcticum (DSM 14480T). On the
basis of the phenotypic characteristics, phylogenetic data and DNA-DNA reassociation
data, strain 190-11 was classified as E. undae, while the other two isolates, 7-3 and 255-

15, comprise a novel species, for which the name Exiguobacteri'um sibiricum sp. nov. is

proposed.

INTRODUCTION
Temperature is a major environmental condition that affects microbial physiology and
growth. Viable microorganisms in permafrost survive and perhaps metabolize in their

continuously frozen habitat. Earth’s permafrost is characterized by low carbon

48

 

availability, low water availability and continuous exposure to gamma radiation (0.03
rad/year) originating from the soil minerals. Despite these challenging conditions,
microorganisms in several microbial groups remain viable for 20,000 to 3 million years.
Many of the studies demonstrating this point were performed by Russian scientists in the

Kolyma Lowland, region of northeast Siberia. This area has tundra vegetation and an
Arctic climate with a mean annual air temperature of -13.4°C and an annual precipitation

of 229 mm (31). The ice content of the permafrost is 20-50 % with 2-5 % of liquid water
in films adsorbed to soil particles (20, 39). The permafrost in this region is formed from
deposits of sediment that came from shallow lake bottoms, alluvial deposits and marine
sediments during the late Pliocene and Pleistocene periods (31), and can reach a thickness
of 600 to 800 m. While the upper tundra layer, 0.5 to 1 m deep, freezes and thaws every
year, the strata below have remained permanently frozen since they were buried by

geological events. The temperature at a depth of 14 m below the surface is stable at -10
0C (1 I). This region is considered to be among the oldest continuously frozen localities

on Earth (21) and make this environment ideal for studies of microorganisms that are
adapted to survive at subzero temperatures.

Three Exiguobacierium strains were previously isolated from Kolyma Lowland
permafrost cores of three different ages. Exiguobacierium strain 255-15 was isolated
from a depth of 43.6 m from a geological layer estimated to be 2 to 3 million years old.
Strains 7-3 and 190-11 were isolated from layers estimated to be 20 - 30 thousand years
and 200 — 600 thousand years old, respectively. Because of their unique physiology and
habitat, we characterized these strains and established their taxonomy. Two of the strains

comprise a new species.

49

 

MATERIAL AND METHODS

Bacterial strains. Exiguobacierium strains 255-15 and 190-11 were isolated by
Vishnivetskaya et al. (33) and strain 7-3 was isolated by Vera Soina (Moscow State
University). They were compared to four reference strains obtained from the DSMZ

(Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH), E. acetyli'cum

(DSM 20416), E. auraniiacum (DSM 6208T), E. antarcticum (DSM 14480) and E.
undae (DSM 14481T). The strains were grown and maintained on 1/2 Tryptic Soy Broth
(TSB) and V2 Tryptic Soy Agar (TSA; Difco Laboratories, Detroit, Michigan, USA) at 30

0C. The strains were stored at -80 0C in 1/2 TSB supplemented with 25% glycerol.
Genotypic characterization. Chromosomal DNA isolation and purification was

performed as described by (19) from cells grown overnight at 30 °C in 1/2 TSB. DNA

concentrations were quantified by UV spectrophotometry at 260 nm (Cary 50 Bio from
Varian).

The genomic diversity of the strains was determined by repetitive element-PCR (14,
30) with BOXAIR primer as described previously (32). The patterns were analyzed using
GelCompar II (Applied Maths Version 3.0) using the pairwise Pearson’s product-moment
correlation coefficient (25).

DNA-DNA reassociation was determined fluorometrically by the method of Ezaki et

al. (7) using photobiotin-labelled DNA probes and black MaxiSorp microplates (Nunc).
Hybridizations were performed at 37°C in eight replicates for each sample. The reported

DNA-DNA reassociation values are the averages following exclusion of the outliers

according to the criteria established for this method (12).

50

The phylogeny of the new isolates was determined from sequences of 16S rRNA
gene and six other genes previously used for phylogenetic classification (1, 10, 15, 34,
35, 38): gyrB (gyrase subunit B), rpoB (DNA-directed RNA polymerase beta subunit),
recA (homologous recombination), csp (cold shock protein), hsp70 (ClassI-heat shock
protein — Chaperonin) and citC (isocitrate dehydrogenase). The primers (Table 3.1) were
designed based on alignments of these genes found in Exiguobacierium 255-15 genome
(http://genome.jgi-psf.org/draft_microbes/exigu/exigu.draft.html) with the same genes of
other Gram-positive microorganisms using ARB (17), with the exception of the standard

16S rRNA (Lane 1991) and csp primers (8). Amplification, for all primers, was by

standard procedures (6). The annealing temperatures for each primer sets were 56 °C for

csp, 53 °C for rpoB, 49 °C for gyrB and citC, 47 °C for recA and hsp70. The 16S rRNA

amplified product was purified using the Qiaquick PCR purification kit (Qiagen,
Valencia, CA, USA) and sequenced. For the other genes, the amplicons were cloned
using the TOPO TA Cloning kit for sequencing (Invitrogen Life Technologies) and the
clones were extracted using the Qiagen Plasmid Mini kit (Qiagen, Valencia, CA, USA).
Cycle sequencing was performed on a Perkin Elmer 9600 thermal cycler using ABI dye
terminator chemistry (PE Applied Biosystems) and products were analyzed on an ABI
373a DNA sequencer. Five primers described in Table 3.1 were used for the 16S rRNA
gene sequencing, and primers for the cloning vector (M13F and M13R) were used for
sequencing the other genes. Assembled sequences were generated using the Sequencher
program versions 3.1.1 (Gene Codes Corporation). Sequences were deposited in
GenBank (accession numbers D9019127 to DQ019169). Sequences from strain 255-15

were obtained from the sequenced genome.

51

Table 3.1. Primers used for PCR amplification for MLST analysis. All the primers,
except for the major cold-shock protein, where designed based on the Exiguobacterium
sequences as well as other strains from the Bacillus genus.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Gene amplified Sequence (5’- to -3’) Fragment
size (bp)
DNA Gyrase - beta subunit
gyrB —F AAA CGT CCG GGT ATG TAT ATC GGA TCG AC 1539 bp
gyrB- R CGG CGG CTG SGC AAT RTA SAC GTA
Universal mafir cold-shock protein (Francis & Stewart 1997)
cspu 5 CCC GAA TTC GGT AHA GTA AAA TGG TTY AAC 200 bp
KC
cspu 3 CCC GGA TCC GGT TAC GTT ASC WGC sz HGG
DCC
DNA-directed RNA polymerase beta subunit
rpoB -1: CGA ACA TGC AAC GTC AGG C 1073 bp
rpoB-R ACA TCY TCY TCA CGN GCA CC
ClassI-heat shock protein - Chaperonin
13,70 -1: GGT ATT GAY TTA GGA ACA ACA AAC T 1455 bp
hsp70-R CTT CTG CWT CTT TKA CCA T
Homologous recombination protein
rec/1-}? GAR AAR CAA TTY 008 AAA GGT TC 869 bp
recA-R TGT TTY GMA TTT TCA CGK CCT TG
Isocitrate dehydrogenase '
citC-F GGD GAY GGM ACW GGw CCW GAY ATT TGG 1165 bp
citC-R AAT TCW GAA CAT TTM ACT TCT GT

 

l6S rRNA gene universal primers (Lane 1991)

 

 

 

 

 

 

8F AGA GTT TGA TCC TGG CTC AG
787R TAC CAG GGT ATC TAA T
802F ATT AGA TAC CCT GGT A
l 100R AGG GTT GCG CTC GTT G
1525R AAG GAG GTG WTC CAR CC

 

 

N=A:T:C:G; H=A:T:C; D= TszA; K= TzG; Y= C:T; M=C:A; W=A:T; R= AzG; S=C:G ; all 1:1
The consensus sequences were aligned against the most similar sequences using ARB

(17). Phylogenetic analyses were performed by the neighbor-joining (27) and distance (5)

methods from within the ARB environment and by a maximum-likelihood method using

fastDNAml (24). The robustness of the inferred tree was evaluated by applying 1000

bootstrap re-samplings.

Phenotypic characterization. Temperature requirements were determined by growing

all the Exiguobacterium strains on V2 TSA. Inoculated agar plates were incubated for 24

52

 

h to 48 h at 30 0C, 4 to 6 days at 12 0C, 20 days at 0 0C, 32 days at -2.5 0C in order to

reach a colony size of 1 to 2 mm of diameter. Cell morphology at different temperatures
was examined by phase contrast microscopy and transmission electron microscopy
(TEM) using colonies grown on the same plate. Flagellum type was observed by TEM at
all temperatures. Cultural and physiological characteristics were determined by using API
50 CHE (bioMérieux) and Biolog GP2 microplate (26). Production of constitutive
enzymes was assessed with API ZYM strips (bioMérieux) as recommended by the

manufacturer. Cells for the fatty acid methyl ester analysis (FAME) (22) and
chemotaxonomic markers were grown at 28°C on TSA and analyzed by DSMZ. The

chemotaxonomic markers studied were cell wall amino acids using the methodology of
Schleifer and Kandler (29), polar lipids by Minnikin et al. (23), peptidoglycan structure
by (18), (28) and (18, 28, 29) and isoprenoid quinones by (3) and (13).

Cytochrome oxidase was tested using the Bactident Oxidase kit from Merck
(1.13300) and catalase activity was tested using H202 as described by (16). Nitrate
reduction was analyzed as described by Cowan and Steel (4). The ability of the new
isolates and the four reference strains to grow in 1/2 TSB supplemented with 5%, 10 %, 12

%, 15 % and 17 % of NaCl was also determined. Results were only considered positive if

an increased medium turbidity was observed for both duplicates.

RESULTS AND DISCUSSION
Genotypic analysis. Genotypic studies were performed on Exiguobacierium permafrost
strains 7-3, 190-11 and 25 5-15 to determine their phylogenetic relationship with the most

relevant set of reference strains. The rep-PCR profiles confirmed that the new isolates

53

 

and reference strains were all distinct genotypes (data not shown). Sequence analysis of
the 16S rRNA genes of the strains placed them in the genus Exiguobacterium (Figure
3.1a). Strains 7-3, 190-11, 255-15, E. undae, E. antarcticum, E. acetylicum and E.
oxidoioierans form a closely related group with a bootstrap value of 1000, while E.
auranti‘acum, E. marinum, and the two E. aestuarii' strains form another closely related
group. For a more robust analysis of the phylogenetic relationships of strains within
Exiguobacierium, we analyzed the phylogeny of six protein-encoded genes (Figure
3.1b,c,d,e,f,g).

Since protein-encoding genes evolve much faster than ribosomal RNAs, they provide
higher resolution than 16S rRNA gene sequences (37). Furthermore, such results were
shown with Acinetobacter to fill the resolution gap between 16S rRNA gene sequence

analysis and DNA-DNA reassociation values (36).

54

 

 

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55

The basic tree t0pologies of rpoB (Figure 3.1b), recA (Figure 3.10), hsp 70 (Figure
3.1d), gyrB (Figure 3.1e) and citC (Figure 3.10 were very similar. E. undae DSM 14481T
and strain 190-11 showed very similar sequences and always clustered together with very

high bootstrap values. Strains 7-3 and 255-15, also clustered together, albeit at a slightly

lower sequence similarity. As found for the 16S rRNA gene sequence analysis, E.

acetylicum DSM 20416T and E. aurantiacum DSM 6208T were always clearly separated
from the other Exiguobacterium strains by long branches. E. antarcticum DSM 14480T

was the only strain for which the clustering was inconsistent over the different genes,
either clustering with strain 190-11 and E. undae DSM 14481T (rpoB, citC) or with strain
7-3 and 255-15 (recA). In other cases (hsp70, gyrB), E. antarcticum DSM 14480T was

separated from these four related Exiguobacterium strains. Notably, the branch nodes
were often not well supported by the bootstrap values, which makes the affiliation of E.
antarcticum DSM 14480T uncertain.

In order to unequivocally determine the species status of the new isolates, DNA-DNA
hybridization experiments were performed (Table 3.2). All reassociation values with

strains E. acetylicum DSM 20416T and E. aurantiacum DSM 6208T were well below the

threshold for species identity (14 - 44 %). Strain 190-11 and E. undae DSM 14481T

showed a DNA relatedness of 91 %, which indicates that these two strains belong to the
same species. This is in agreement with the multi-locus sequence typing analysis

(MLST), and many of the phenotypic analyses (see below). Furthermore, strain 190-11

showed a relatively high reassociation (65 %) with E. antarcticum DSM 1448GT.

S6

 

A DNA reassociation value of 71 % was found between the strains 7-3 and 255-
15, suggesting that these strains maybe members of the same species. However, both 7-3

and 255-15 had a relatively high similarity (65-68 %) with the type strains E. undae DSM

14431T and E. antarcticum DSM 14480T (Table 3.2). The DNA-DNA reassociation

values are borderline for species delineation, making it difficult to classify the new strains
as belonging to one or to the other species. Those two type strains are clearly distinct
based on their phenotypic differences and DNA-DNA reassociation values of 51 % by
(9), and confirmed by our results (59 %). Since the two isolates, 7-3 and 255-15, cannot
be clearly classified as belong to either one of these type strains and have consistent
MLST data supporting that they are related and distinct from the other species previously
described, we suggest that they are a new species.
Phenotypic properties. Phenotypic studies were also performed to determine whether
the new isolates are phenotypically distinguishable from each other and from the
reference strains of Exiguobacterium. Allocation of the strains 7-3, 190-11 and 255-15 to
the genus Exiguobacterium was confirmed by the presence of the peptidoglycan type
A30 L-Lys-Gly, which is typically the genus (2).

The major isoprenoid quinone (Table 2.3) in all strains was an unsaturated

menaquinone with seven isoprene units (abbreviated as MK7). Strains 7-3, 190-11, E.
undae DSM 14481T and E. antarcticum DSM 14480T contained minor but significant

amounts of MK6 and MKS quinones, while for 255-15 the major quinone was MK7 with

trace amounts of MK6 and MK8, which provides a good distinction from the other
closely related strains like E. undae DSM 14481T and E. antarcticum DSM 14480T. 1n

the analysis of polar lipids, none of the Siberian isolates (7-3, 190-11 and 255-15)

57

 

contained phosphatidyl-serine or phosphatidyl-inositol as was observed in E. undae DSM

14481T and E. antarcticum DSM 14480T (Table 3.3). All strains were catalase positive.
E. antarcticum DSM 14480T and E. aurantiacum DSM 6208T were the only oxidase

negative strains (Table 3.3). E. aurantl'acum DSM 6208T was also the only strain positive

for nitrate reduction. The major fatty acids in the new isolates (Table 3.4) were iso-

C13:O, anteiso-C13zO, iso—C1520, C1620 and iso-C 17:0, which were similar to these in E.
antarcticum DSM 14480T and E. undae DSM 14481T, further supporting the assignment
of the new isolates as Exiguobacterium.

E. aurantiacum DSM 6208T was the only strain that did not express any of the 19

enzymes tested (API ZYM), and 7-3 and 190-11 were the only strains that expressed
esterase lipase (C8) and B-glucosidase respectively. All Exiguobacterium strains

expressed a-glucosidase and B-galactosidase with the exception of E. aurantiacum DSM

6208T, as mentioned above, and E. acetylicum DSM 20416, which only expressed or-
glucosidase. Interestingly, even though 190-11 and E. undae DSM 14481T were highly

similar in all genotypic tests, only 190-11 and E. antarcticum DSM 14480T did not

express alkaline phosphatase, while 7-3, 255-15 and E. undae DSM 14481T did express

this enzyme.

58

 

 

 

 

 

 

 

 

 

 

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62

The BIOLOG and API 50 CH systems (Table 3.5) were used to assess the metabolic
profile of Exiguobact'erium strains. A dendrogram obtained with this data shows that 25 5-
15 shares a slightly more similar carbon utilization pattern with E. antarcticum DSM

14480T (76 % similarity) than with the other strains (Figure 3.2). In addition, 7—3, 190-11

and E. undae DSM 14481T were clustered together and had more similar carbon

utilization patterns, respectively with 73 % and 82 % similarity to E. undae DSM 14481T.

 

 

 

 

0.25 0.50 0.75 1.00
n . . 73
190-11
—: E. undae DSM 14481
255-15
"‘ E. antarcticum DSM 14480

 

 

 

 

E. acetylicum DSM 20416
E. aurantiacum DSM 6208

 

 

Figure 3.2. Phenogram obtained from the carbon source utilization of the seven
Exiguobacterium strains based on the UPGMA method (unweighted pair-group method
using arithmetic averages) after measuring similarity/dissimilarity among the strains
using the coefficient of simple matching, which considers the same weight positive and
negative similarities.

However, the higher similarity observed was between 190-11 and E. undae DSM
14481T, which had 82 % similarity in the carbon source utilization, confirming the

genotypic data that suggests that they are the same species. In the case of 7-3 and 255-15,
even though they were clustered with two different reference strains in the phenogram,

when we look at the matrix (data not shown) the pair-wise comparison of those two

strains with the other reference strains (except for E. acetylicum DSM 20416T and E.
aurantiacum DSM 6208T) showed a similarity of 71 % and 73 % for 7-3 with E.

antarcticum DSM 14480T and E. undae DSM 14481T, respectively, and a similarity of 73

63

% and 76 % for 255—15 with E. antarcticum DSM 14480T and E. undae DSM 14481T,

respectively. Hence, this data is not conclusive with regard to a species assignment for
these two new strains.

The strains were also tested for their ability to grow at different temperatures, from -

2.5 to 30 0C. The reference strains E. acetylicum DSM 20416T and E. aurantiacum DSM
6208T were unable to grow at 4 0C or below, but were able to grow at 30 0C and 12 0C.

Strains 73, 190-11, E. undae DSM 14481T and E. antarcticum DSM 14430T grew at all
temperatures tested. The cell pigmentation remained unaltered at low growth
temperatures, except for E. acelylicum DSM 20416, which at 12 °C, became much more

orange and therefore more similar to the other Exiguobacterium strains. These data

confirm results obtained with the csp gene (Figure 3.1g), i.e. that these two strains unable
to grow below 12°C cluster together, while the others that are able to grow at lower

temperatures formed a separate cluster. This observation suggests that CSP primers may
be able to discriminate strains that grow at lower temperatures from the ones that cannot.

In regard to growth at different salt concentrations, 7-3 and 255—15 were able to grow

in up to 10 % NaCl, as was the case for E. acetylicum DSM 20416T. Strain 190-11 was
able to grow at salinities of up to 12 % NaCl, like E. undae DSM 14481T, E.
oxidot‘olerans and E. aurantiacum DSM 6208T (Table 3.3). These data show that E.

undae DSM 14481T and 190-11 have another phenotype in common. The same is
observed for the strains 7-3 and 255-15 that also exhibit the same tolerance to salt.
Colonies of all the new isolates and the reference strains (except for DSM 20416T,

which was yellow colored) were orange-colored, smooth, circular, convex and shiny. The

64

 

orange pigment did not diffuse into the medium. The isolates also showed genus-specific

characters such as rod-shape morphology, motility, peritrichous flagella and absence of
spore formation at all temperatures tested (Table 3.3). Strains were inoculated on 1/2 TSA

plates and cell morphology was observed in different temperatures with phase contrast
microscopy and transmission electron microscope after negative staining. The cell shape

and slime secretion of 190-11 and 255-15 strains did not change with temperature and

were very similar to E. antarcticum DSM 14480T and E. undae DSM 14481T. However,

inclusions were observed inside the cells of strain 255-15 at 0 0C, which could be carbon
storage polymer (Figure 3.4). Strain 7-3 was the only strain that showed temperature-
dependent cell morphology. For temperatures from 0 to 12 °C, the cells became much
more elongated in comparison to all the other strains and in comparison to its growth at

30 CC (Figure 3.3 and 3.4). This elongation state was not permanent, as cell size returned

to normal when incubated at 30 0C. Interestingly, at -2.5 0C the cell size of 7-3 was
similar to the other strains.

The phenotypic analyses confirmed that the new isolates are Exiguobacterium, that
190-11 and E. undae DSM 14481T share similar properties and hence are the same

species, consistent with the genotypic analyses; and that 255-15 and 7-3 have some
phenotypic properties that are not consistent with any current species. The genotypic
results were clearer cut for 7-3 and 255-15 classification, in that they had high DNA-

DNA reassociation and were clustered together in all but one of the MLST analyses.

65

 

 

Figure 3.3. Cell morphology of new isolates and reference strains of E. antarcticum

DSM14480 and E. undae DSM 14481 grown at 0°C by phase contrast microscopy. Bar

scale corresponds to 10 um.
1.3

k

 

1: .
Figure 3.4. Iflegatively stained. electron micrograph of 7-3 and 255-15 grown at 0°C.
Strain 7-3 presents elongated cells and 255-15 presents intracellular granules.
Hence, we conclude that, 255-15 and 7-3 are members of the same species and that
they belong to a different species from the reference strains described so far. The
phenotypic results for all Exiguobacterium new and old members are not strikingly

distinctive among the species, except for the most distantly related strains. Hence, the

genotypic analyses are more conclusive for the species of this genus.

66

 

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a-Positive results for the following substrates: 2'-deoxy adenosine, Adenosine, a-D-
Glucose, a-Ketovaleric acid, Amygdalin, arbutin, b-Methyl-D-glucoside, D- Mannose, D-
cellobiose, Dextrin, D-Fructose, D-glucose, D-maltose, D-psicose, D-saccaharose,
Gentiobiose, glycerol, Glycogen, Inosine, D-trehalose, Maltose, Maltotriose, Thymidine,
uridine, Palatinose

Negative results for the following substrates: a-D-Lactose, a-hydroxybutyric acid, a-
ketoglutaric acid, a-Methyl-D-Galactoside, a-methyl-D-mannoside, b-methyl-D-
Galactoside, D-Arabitol, D-fucose, D-galacturonic acid, D-Gluconic acid, D-Lactic acid
Methyl ester, D-lyxose, D-malic acid, D-sorbitol, D-tagatose, D-turanose, Dulcitol, g-
hydroxybutyric acid, inositol, Inulin, Lactamide, Lactulose, L-alaninamide, L-arabinose,
L-arabitol, L-Fucose, L-rhamnose, L-sorbose, Mannan, Methyl-alpha-D-
mannopyranoside, p-Hydroxyphenylacetic acid, potassium 2-ketogluconate, potassium 5-
ketogluconate, potassium gluconate, Putrescine, Succinamic Acid, Succinic acid, Tween
40, Tween 80, xylitol.

69

Description of Exiguobacterium sibiricum sp. nov.
Exiguobacterium sibiricum (si.bi.ri.cum M. L. — Sibir’ from Siberia, a Russian region)
Cells are Gram-positive and facultatively anaerobic, non-spore-forming rods, motile

with peritrichous flagella. The cells can vary in shape and size depending on growth

temperature. At 30 oC, they can have 0.8 mm long and 0.6 pm in diameter, but can reach
up to 15 mm long at temperatures between 12 0C and O 0C. Surface colonies on 1/2 TSA
are 3.5 to 4 mm in diameter after 50 h at 30 0C, bright orange, convex, entire and shiny.
The orange pigment does not diffuse in the medium. Growth occurs at -2.5 0C to 40 0C,

with optimum temperature growth rate at 36 0C. Growth does occur in 1/2 TSB with 10 %

NaCl, but does not occur at 12 %. The peptidoglycan type is L-Lys—Gly and the
predominant menaquinone is MK-7; MK-6 and MK-8 might or might not occur. The only
polar lipids are phosphatidyl-glycerol, diphosphatidyl-glycerol and phosphatidyl-
ethanolamine, and the major fatty acids are iso-C13:0, anteiso-C13:0, iso-C1510, C16:O
and iso-C17:O. The G+C content of DNA of the type strain is 47.7 mol% and its genome

size is 3 Mb. The type strain is strain 255-15 (= DSM 17290)

ACKNOWLEDGEMENTS
This work was supported by a cooperative agreement with NASA Astrobiology

Institute, number NCC2-1274.

70

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35. Whitaker, R. J., D. W. Grogan, and J. W. Taylor. 2003. Geographic barriers
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36. Yamamoto, S., P. J. Bouvet, and S. Harayama. 1999. Phylogenetic structures
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37. Yamamoto, S., and S. Harayama. 1998. Phylogenetic relationships of
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39. Zvyagintsev, D. G., D. A. Gilichinsky, S. A. Blagodatskii, E. A. Vorobyeva, G.
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74

CHAPTER 4

EXIGUOBAC TERI UM GENUS: AN EXAMPLE OF PERMAFROST
SURVIVOR

Rodrigues, D. F., and J. M. Tiedje. 2007. Multi-locus real-time PCR for quantitation of

bacteria in the environment reveals Exiguobacterium to be prevalent in permafrost.
FEMS Microbiol Ecol 59:489-99.

75

ABSTRACT

We developed a multi-locus quantitative PCR approach to minimize problems of
precision, sensitivity and primer specificity for quantifying a targeted microbial group in
nature. This approach also avoids a systematic error in population quantitation when 16S
rRNA genes are used because of copy number heterogeneity. Specific primers were
designed to assess the abundance of psychrotrophic and mesophilic Exiguobacterium spp.
that excluded the thermophilic members of the genus. The chosen primers targeted genes
for DNA gyrase B (gyrB), the beta subunit of the RNA polymerase gene (rpoB) and a
hypothetical gene so far found only in this group. The results demonstrate that the
multiple primer approach provides a more reliable estimate of population density; that the
targeted Exiguobacterium group is found at a median density of 50,000 gene copies ug"
of total community DNA in 27 of 29 permafrost soils but was found in only one of the

four temperate and tropical soils tested.

INTRODUCTION

Quantification of microbial abundances is central to understand microbial
community structure and population dynamics. Real-time PCR (qPCR) provides high
sensitivity, is quantitative (29) and less laborious than whole-cell fluorescence in situ
hybridization techniques (6, 16). Real-time PCR techniques have more commonly been
developed for bacteria and viruses of clinical importance, c.f. for bacteria (11, 18, 21, 31)
and viruses (9, 19). More recently this technique has been used for detection of

microorganisms such as Pseudomonas stutzeri (10), Rhodococcus sp. (23) and Geobacter

spp. (25) in terrestrial environments.

 

All studies using real-time PCR to quantify microorganisms in the environment
use only one gene, typically the 16S rRNA gene or functional genes of interest, such as
nitrate reductases (10), (bi) sulfite reductases (20) and aromatic dioxygenases (2). The
conserved nature of the 16S rRNA gene can make it difficult if not impossible to design
primers of sufficient specificity to track populations of interest, plus the variation in copy
number of this gene leads to uncertainty in quantitation. If less conserved genes are used,
the lack of sequence data, especially for the targeted species, makes specificity and the
detection range of primers uncertain. Additionally, some primers yield less than desired
sensitivity (10, 24). The above problems can lead to over or under estimation of the
number of microorganisms in the environment, especially when dealing with complex
communities.

Previous studies in Siberian permafrost soils yielded isolates of Exiguobacterium
from four geological strata ranging from 20 thousand to 3 million years since they were
frozen (22). This genus belongs to the family Bacillaceae. These microorganisms are
Gram positive, rod-shaped, facultative aerobic, motile with peritrichous flagella. Colonies
on '/2 Tryptic soy agar medium are orange-yellow. The pigment does not diffuse in the
medium. Since this genus was found in several layers of the Siberian permafrost,
including the oldest, we sought to determine whether it is more prevalent in these soils
than temperate or tropical soils. To do this we developed a multi—locus quantitative real-
time PCR (ML-qPCR) method to achieve more specific and accurate quantification of
psychrotrophic and mesophilic members of Exiguobacterium. The results demonstrate the
importance of using multiple genes for more accurate quantification of the targeted

group, and that Exiguobacterium preferentially resides in permafrost.

77

MATERIAL AND METHODS

Soils. Twenty-nine Siberian permafrost soil samples from sixteen sites were collected by
David Gilichinsky’s team, Russian Academy of Sciences, Pushchino, from depths
varying from 2.55 m to 37.5 m. These soils had been frozen between 5 thousand to 3
million years depending on the location and depth (Table 4.1). Non-permafrost soils from
Michigan, Iowa, Hawaii and Puerto Rico were sampled from 5 to 10 cm depth. All soils

were stored frozen at -20°C.

Table 4.1. Location and additional information of sample sites 3.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sample Depth (111) Collection Age (years) Location
Date
(Year)
1- Siberia 2.55 2000 5-10 thousand Kolyma Lowland, Cape
2- Siberia 8.55 Chukochii, East Siberian
3- Siberia 14.95 Sea coast, ttmdra zone,
4- Siberia 20.0 20-30 thousand 70°05'N, 159°55'E
5- Siberia 2.8 2001 12-40 thousand
6- Siberia 8.0 Cape 129°
7- Siberia 13.0 30'E,
8- Siberia 23.3-23.4 Bykovskii
9- Siberia 28.0 71°
10- Siberia 33.0 Laptev 40'N
11- Siberia 37.5
12- Siberia 6.3 2001 5-10 thousand Sea
l3- Siberia 6.8
14- Siberia 18.1-18.2 2003 3 million coast, 130°
15- Siberia 24.0 00'E,
16- Siberia 24.4 tundra
17- Siberia 3.0 2003 5-10 thousand 72°
18- Siberia 7.5 1°“ 00'N
19- Siberia 4.8-4.9 2003 15-20 thousand
20- Siberia 8.15-8.25
21- Siberia 22.5-22.6 2001 300-400 Cape Svyatoi Nos, Laptev
22- Siberia 9.0 thousand Sea coast, tundra
zone,140°10'E, 72°55'N

 

 

 

 

 

78

 

Table 4.1 (cont’d)

 

23- Siberia

11.0

1 990

20 thousand

Kolyma Lowland, forest-
tundra zone, left bank of
Kolyma river,
Khalarchinskaya tundra
sandy plain, 68°50'N,
161°02'E

 

24- Siberia

16.5

1990

2-3 million

Kolyma Lowland,
Krestovka River, right
inflow of Kolyma River
(north taiga), 66°50'N,
62°30'E

 

25- Siberia

18.7

 

26- Siberia

19.9

1992

2-3 million

Kolyma Lowland, tundra
zone, Mouth of Malaya
Kon'kovaya River, right
bank, 69°23'N, 58°28'E

 

27- Siberia

20.1-20.2

 

28- Siberia

23.3-23.45

 

29- Siberia

16.8-16.9

1999

100-120
thousand

Kolyma Lowland, tundra
zone, Lake Yakutskoe,
East Siberian Sea coast,
69°51'N, 159°29'E

 

Puerto Rico

0.]

2002

Recent

Guanica dry forest, vereda
cerca de casa guardia,
17°58’N, 66°51’W

 

Hawaii

0.1

1992

Recent

Kohala forest, 20°03’N,
155 °41 ’E

 

Iowa

0.1

2005

Recent

Prairie wetland, Jasper
county
41°48’N, 09°3OW

 

 

Michigan

 

0.1

 

2005

Recent

 

 

Baker Woodlot, Rachana
Rajendra Bird Sanctuary —
Michigan State
University, 42°44’N,
08°42W

 

a The permafrost sample information was provided by David Gilichinsky.

Bacterial strains and culture conditions. The following microorganisms were used as

negative controls: Achromobacter cyclocastes ATCC 21321T, Streptococcus pyogenes

JCM 5674, Rhodococcus opacus ATCC 51881T, Arthrobacter sp. 348-9 (Siberian

permafrost isolate), Pseudomonas fluorescens ATCC 17575T, Bacillus azotoformans

79

 

ATCC 29788T, Corynebacterium nephridii ATCC 11425T, Psychrobacter arcticus VKM

B-23 77 (Siberian permafrost isolate), Escherichia coli B and Pseudomonas stutzeri strain
JM3OO DSM 10701. Positive controls: Exiguobacterium spp. isolates (strains Ale,

M37, A1, A19, TC38-2b, 5138, India orange and India stream) Exiguobacterium

aurantiacum DSM 6208T, Exiguobacterium oxidotolerans JMC 12280T,
Exiguobacterium acetylicum DSM 20416T, Exiguobacterium antarcticum DSM 14480T,

Exiguobacterium undae DSM14481T, Exiguobacterium undae strain 190-11,

Exiguobacterium sibiricum strain 255-15 DSM 17290 (Table 4.2). All culture collection
strains and permafrost isolates used in this study were grown in 1/2 tryptic soy broth (TSB)

at 28°C (Difco, Detroit, Mich), except for Psychrobacter arcticus which was grown at

20°C. E. coli transformants carrying TOPO TA clones (Invitrogen, Life Technologies)

were grown in LB amended with kanamycin (50 ug mL'l) as recommended by the
manufacturer.

DNA extraction and quantification Genomic DNA from the isolates was extracted
from late-exponential phase cultures using the QiAamp DNA mini kit (Qiagen Inc.).
Plasmid DNA from E. coli transformants was extracted using the Qiagen Plasmid mini kit
(Qiagen Inc.). Soil DNA was extracted using the Fast DNA SPIN kit for soil (Bio 101, Q

BIOgene) with some modifications, namely the first step of the extraction was a grinding
step using liquid nitrogen followed by treatment with 100 pl of lysozyme (50 ug ul 4)

before using the kit. The quality of the extracted DNA was analyzed by electrophoresis

on a 0.8% agarose gel. DNA concentrations were measured by absorbance at 260 nm.

80

Table 4.2. Specificity of real-time PCR for Exiguobacterium spp.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

orange

 

 

 

 

 

Strains Local of Temperature Real- time PCR
isolation Ranges " Hypothetical RpoB gyrB

E. sibiricum strain Siberia Psychrotroph + + +
25 5- 1 5 permafrost
E. undae strain Siberia Psychrotroph + + +
1 90-1 1 permafrost
E. undae DSM Garden pond, Psychrotroph + + +
14481 Germany
E. antarcticum Antarctica Psychrotroph + + +
DSM 14480
Exiguobacterium Siberia Psychrotroph + + +
sp. strain 5138 permafrost
Exiguobacterium Stem of potato Psychrotroph - - +
sp. strain A19 plants infected

with Erwinia

carotova,

Austria
Exiguobacterium Carpathian Psychrotroph - + +
sp. strain TC38- Mountains,
2b Ukraine
Exiguobacterium Alkaline Mesophilic + + +
aurantiacum effluent of
DSM 6208 potato wash,

UK
Exiguobacterium Creamery Mesophilic + + +
acetylicum DSM waste, UK
20416
E. oxidotolerans Fish processing Mesophilic - + -
JMC 12280 plant, Japan
Exiguobacterium Hot spring, Mesophilic - - +
sp. strain India India
stream
Exiguobacterium Yellowstone Moderate - - -
sp. strain A1 park, US Thermophilic
Exiguobacterium Yellowstone Moderate - - -
sp. strain Ale park, US Thermophilic
Exiguobacterium Yellowstone Moderate - - -
sp. strain M37 park, US Thermophilic
Exiguobacterium Kunds, India Moderate - - -
sp. strain India Therm0phi1ic

 

a- Information obtained from Vishnivetskaya and coworkers (28).
All strains used as negative controls did not amplify in the q-PCR with any of the primers

81

 

Primers. Specific primers were designed for gyrase subunit B (gyrBZ7-F 5’ACT GCA
TCG AAG GGG CTT CA 3’; gyrBl98-R 5’ACT GCC GGA CGT CCC ATC TT 3’),
DNA-directed RNA polymerase beta subunit (rpoB2-F 5’TGG CAA CAT CGT TCA
AGG TG; rpoBl48-R 5’ ATC GAT GGA CCA TCT GCA AGG 3’) and a hypothetical
gene from Exiguobacterium sibiricum strain 255-15 (hy926-F 5’ TGA CCA TTA CCG
ACG ACA TCG 3’; hy1070-R 5’CCG CGG ATC AGT AAA TTA CCG 3’). Alignments
of gene sequences from Exiguobacterium spp. and unrelated strains were obtained from
Rodrigues and coworkers (22) and the Joint Genome Institute’s (JGI) website
(hilly/genon1e.jgi-psf.org’dra l"t_microbcs/exigu/exiguliomehtml) and compared using
the ARB program (17) to select conserved regions that encompassed the cold adapted
Exiguobacterium species. The primers were designed within the conserved regions using
the program PrimerExpress (PE Applied Biosystems) and checked against GenBank for
specificity. Integrated DNA Technologies (Coralville, Iowa) synthesized the primers.

Real-Time PCR assays. The Real-time PCR reactions and primer optimizations were
done as described in Applied Biosystems protocol for SYBR Green PCR master mix and

RT-PCR (3). The reagents used for the reaction were the 2X PCR master mix (Applied
Biosystems) with addition of 0.4 mg ml'I final concentration of Bovine Serum Albunine
(Roche). The optimum primer concentrations for hypothetical and gyrB were 50 nM and
300 nM for rpoB. The annealing and extension temperatures for all primers were 60°C,

as described by the Applied Biosystems protocol. The size of the amplicons for gyrB,
rpoB and hypothetical were 141 bp, 148 bp, 147 bp, respectively.

The increase in fluorescence emission was monitored during PCR amplification using the

7700 Sequence Detector (PE Applied Biosystems). The CT values obtained for each

82

sample were compared with the standard curve to determine the initial copy number of
the target gene.

Primer specificity. The DNA extracted from the Exiguobacterium spp. and the other
species described above were used as positive and negative controls to test the specificity
of the primer sets. Template DNA (10 ng) was added to each reaction tube. Total soil
DNA extracts from Puerto Rico, Michigan and three permafrost soils from different ages
and locations were amplified with each primer set to construct clone libraries with the
TOPO TA cloning kit (Invitrogen) to verify the specificity of the primers in detecting
Exiguobacterium spp.

Primers for the cloning vector (M13F and M13R) were used for sequencing. Cycle
sequencing was performed on a Perkin Elmer 9600 thermal cycler using ABI dye
terminator chemistry (PE Applied Biosystems) and products were analyzed on an ABI
373a DNA sequencer. Sequences generated in the present study were deposited in
GenBank (accession numbers are DQ490772-DQ490823, DQ490824-DQ490868 and
Dg2499826-DQ499885 for rpoB, gyrB and hypothetical, respectively) and sequences
from strain 255-15 were obtained from the genome sequenced by JGI
(http://genome.ornl.gov/microbial/exigO.

To construct the phylogenetic trees, the sequences were aligned in the ClustaIW
program (26). Analyses were performed by the neighbor-joining method from within the
MEGA 3.1 environment (15).

Sensitivity and detection limit. Exiguobacterium undae strain 190-11, Exiguobacterium
sibiricum strain 255-15 and Exiguobacterium antarcticum DSM 14480T were chosen for

determining the detection limit of the hypothetical, gyrB and rpoB primer sets. Clones of

83

 

each gene of Exiguobacterium undae strain 190-11 were used to measure sensitivity and
to generate standard curves in subsequent determinations. Serial dilutions (IO-fold) of
each DNA were prepared with lug pl" E. coli B DNA as a carrier in water (Sigma —
molecular biology reagent). Different volumes (2, 4, 10 and 20 ul) of template DNA plus
E. coli B DNA were added to individual reaction tubes and the differences were made up
with water. Calibration curves were constructed to determine the lower detection limit of
each assay and our ability to discriminate two-fold difference in template concentration.
All determinations were performed in triplicate and standard deviations were determined

(shown as error bars). The maximum allowable error (MAE) in order to distinguish a
twofold difference in copy number among CT obtained from three different strains (E.
sibiricum 255-15, E. undae 190—11 and E. antarcticum DSM 14480T) was calculated as
follow: ACT = m - log(2), where ACT is the difference between CT obtained from
samples with a twofold difference in target copy number, and “m” is the slope of the
standard curve. The MAE, calculated as: MAE = /_\.CT /2, was computed for each

standard curve, and the mean MAE and the 95% confidence interval were determined.
Quantification and accuracy of Exiguobacterium spp. in environmental samples.
Reactions were performed using 10 ng of template DNA. The template copy number was

determined from CT values from triplicates by using standard curves.
In order to test for the presence of PCR inhibitors, 104 clone copies were added to 10 ng

of DNA extracted from the environmental samples from each site. Samples, with and
without the addition of positive control DNA, were compared and the percent recovery of

the added DNA was calculated.

84

RESULTS
Primer selection and specificity. We previously used five housekeeping genes for
phylogenetic studies (22) and from this set we could design specific primers for the genus
Exiguobacterium from the gyrB and rpoB sequences. These genes are essential for
bacterial growth and are present in low copy number. For the rpoB, we found that only
1.3% of 234 genomes on the JGI website have two copies in their genome, and for gyrB
only 11.3% and 0.5% of 194 genomes have two and three copies, respectively
(http://img.iui.tloe.gov.«"cgi-bilamb/main.cgi). The hypothetical gene was selected since
this category of gene is often specific for a genus or species. We tested several primers
designed for five diverse hypothetical genes from the Exiguobacterium sibiricum 255-15
genome, and found one primer set that was able to amplify this gene from only the
targeted group.

DNA extracted from a range of Exiguobacterium spp. isolated from different
environments and with different growth temperature ranges were used to test the
Specificity of the three primer sets (Table 4.2). A logarithmic increase in fluorescence

intensity was observed by qPCR for five psychrotroph isolates for all three primer sets

tested. Even though two mesophilic isolates, E. aurantiacum DSM 6208T and E.

acetylicum DSM 20416T, could also be detected with all primers, the logarithmic

increase in fluorescence intensity was much lower when compared to the psychrotrophs
(data not shown). Although the primers for the hypothetical gene (Table 4.2) did not
detect two psychrotrophic strains from non-polar regions, it seems to be more specific for
the psychrotrophs, and detected all the strains from the two Polar Regions. The primers

for gyrB and rpoB detected additional mesophilic strains and a broader set of

85

 

Exiguobacterium overall. None of the primers could amplify the moderately thermophilic
isolates.

The sequences of the cloned genes confirmed that only the targeted gene was
detected. In the rpoB gene tree (Figure 4.1), the cluster with all the thermophilic strains,
with 90% bootstrap value, did not contain any clone from the permafrost, temperate
(Michigan and Iowa) or tropical environments (Hawaii and Puerto Rico). This tree also
shows that mesophilic and psychrotrophic Exiguobacterium spp. cluster together with a
99% bootstrap value and separated from the thermophilic strains. Additionally, the
majority of the clones obtained from the Siberian permafrost soils from geologic strata of
100-200 thousand years Since being frozen were similar to Exiguobacterium sp. TC38-2b
isolated from the Carpathian Mountain in Ukraine. Most of the other clones were similar
to the strains found previously in the Siberia permafrost, such as E. undae strain 190-11
isolated in soils from geological strata of 200-600 thousand years and E. sibiricum strain
255-15 from soil dated 2 to 3 million years before present.

The phylogenetic tree for the hypothetical gene does not contain any clones
related to mesophilic or thermophilic strains (Figure 4.1), consistent with its higher
Specificity for psychrotrophic strains. In addition, all clones obtained from temperate
(Michigan) or tropical (Puerto Rico) soils clustered together, while the others obtained
from the Siberian permafrost formed an independent cluster with 65% bootstrap. The
phylogenetic tree for gyrB gene (Figure 4.2) had clones mostly similar to the strains from
the Species Exiguobacterium undae with a few clones similar to the other strains from

cold environments (Siberia or Antarctica). No clones were similar to the mesophilic E.

acetylicum DSM 20416T and E. aurantiacum DSM 6208T.

86

‘Michigan - clone 810
. Michigan - clone 804
13 Puerto Rico - clone CO1
D Puerto Rico - clone 004
0 Puerto Rico - clone 006
U Puerto Rico - clone 007
‘Michigan - clone 811
U Puerto Rico - clone 002
D Puerto Rico - clone CO4
U Puerto Rico - clone CO6
D Puerto Rico - clone COB
' U Puerto Rico - clone C05
——-‘ Michigan - clone A02
Puerto Rico - clone C10
Michigan - clone 808
1:] Puerto Rico - clone C03
‘Michigan - clone A01
U Puerto Rico - clone 002
U Puerto Rico - clone 012
60 [:1 Puerto Rico - clone C07
._ E. undae strain 190-11
1:] Puerto Rico - clone 008
. U Puerto Rico - clone 001
U Puerto Rico - clone 009
D Puerto Rico - clone C09
U Puerto Rico - clone 003
13 Puerto Rico - clone 005
‘Michi an - clone 802
Siberia permafrost - clone E7
66 L— . Siberia permafrost - clone 67
E.undae DSM 14481
g Siberia permafrost - clone G3

 

 

 

 

 

 

 

 

 

Siberia permafrost - clone E2

Siberia permafrost - clone E12

Siberia permafrost - clone E11

Siberia permafrost - clone C4

85 Siberia permafrost - clone E10

Siberia permafrost - clone H2

Siberia permafrost - clone E5

Siberia permafrost - clone E9

I Siberia permafrost - clone H11

. Siberia permafrost - clone 62

I Siberia permafrost - clone F2

I Siberia permafrost - clone C9

I Siberia permafrost - clone H6

. Siberia permafrost - clone G9

I E. sibiricum strain 255-15

. Siberia permafrost - clone 612
Siberia permafrost - clone G11

94 E. sibiricum strain 7-3

I Siberia permafrost - clone F7

I Siberia permafrost - clone F1

I Siberia permafrost - clone C8
Siberia permafrost - clone H4
Siberia permafrost - clone E1

I Siberia permafrost - clone F12

I Siberia permafrost - clone F5

I Siberia permafrost - clone F6

I Siberia permafrost - clone H5

. Siberia permafrost - clone G1
. Siberia permafrost - clone G10

 

66

 

 

 

 

 

 

1W0?

Figure 4.1 (A). Phylogenetic tree based on hypothetical (A) and rpoB (B) sequences of
indicated Exiguobacterium strains and clone libraries from Michigan (A),Puerto Rico soil
([3) and three Siberia permafrost soils dated of 2 to 3 million years ('), 100-200 thousand
years (l) and 12 to 40 thousand years ( A). The trees were produced by the neighbor-
joining method. The rpoB tree was rooted using the rpoB gene from B. subtilis. The
nodes with less than 40% bootstrap values were not added to the tree. The scale bar
represents changes per nucleotide.

87

r I Siberia permafrost - clone 801
- Siberia permafrost - clone C02
r- Siberia permafrost -c|one CO6
h . Siberia permafrost - clone C07
_.I Siberia permafrost - clone 809
I Siberia permafrost - clone C08
0 E. sibiricum strain 255-15
l Siberia permafrost - clone 804
Siberia permafrost - clone C12
Siberia permafrost - clone A06
I Siberia permafrost - clone 811
I Siberia permafrost - clone 805
a: Siberia permafrost - clone C10

4

d

 

I Siberia permafrost - clone 810
. Siberia permafrost - clone CO5
I Siberia permafrost - clone 611
I Siberia permafrost - clone 807
7 I Siberia permafrost - clone 808
Eacetylicum DSM 20416
I Siberia permafrost - clone 806
I Siberia permafrost - clone 812
E.antarctlcum DSM14460
. Siberia permafrost - clone C04
I Siberia permafrost - clone 802
I Siberia permafrost - clone 803
I E. undae strain 190-11
44 E.undae DSM 14481
-. Siberia permafrost - clone (306
Siberia permafrost - clone G10
Siberia permafrost - clone G11
- Siberia permafrost clone 604
E. sibiricum strain 7-3
E. oxidotolerans JC M12280
Siberia permafrost - clone 609i
Siberia permafrost - clone A08
Siberia permafrost - clone 603
Siberia permafrost - clone G12
Siberia permafrost - clone A04
Siberia permafrost - clone A01
Siberia permafrost - clone A05
Siberia permafrost - clone 001
Siberia permafrost - clone (308
Siberia permafrost - clone 605
Siberia permafrost - clone 602
Sibeira permafrost - clone A11
Siberia permafrost - clone 607
Siberia permafrost - clone A02
Exiguobacterium sp. TC38-2b
Exiguobacterium sp. India stream
Exiguobacterium sp. A1
93 ‘ Exiguobacterium sp. 5136
Exiguobacterium sp. A19
56 E.aurantiacum DSM 6208
Exiguobacterium sp. GICS1or
Exiguobacterium sp. AT4
Exiguobacterium sp. M37
Exiguobacterium sp. India orange
Exiguobacterium sp. AT1b
Exiguobacterium sp. Colorado Road
B.subrllis

 
   
     
   
 
  
 

  

96

 

18

   
  
 
 
 
 
 
 
 
  
  
 

 

99

 

53

 

  
 
  
    

 

90

 

 

0.05

Figure 4.1 (B). Phylogenetic tree based on hypothetical (A) and rpoB (B) sequences of
indicated Exiguobacterium strains and clone libraries from Michigan (A),Puerto Rico soil
(Cl) and three Siberia permafrost soils dated of 2 to 3 million years (°), 100-200 thousand
years (I) and 12 to 40 thousand years ( A). The trees were produced by the neighbor-
joining method. The rpoB tree was rooted using the rpoB gene from B. subtilis. The
nodes with less than 40% bootstrap values were not added to the tree. The scale bar
represents changes per nucleotide.

88

- I Siberia permafrost - clone804
I Siberia permafrost - clone 804a
I Siberia permafrost - clone H04
I Siberia permafrost - clone H06
I Siberia permafrost - clone CO7
Siberia permafrost - clone A02
Siberia permafrost - clone H01
I Siberia permafrost - clone 801
I Siberia permafrost - clone C09
- I Siberia permafrost - clone 804 1
Siberia permafrost - clone C05
I Siberia permafrost - clone 808
I Siberia permafrost - clone F06
I Siberia permafrost - clone 803
I Siberia permafrost - clone 811
I Siberia permafrost - clone 810
I Siberia permafros - clone 809
I Siberia permafrost - clone 807
I Siberia permafrost - clone 805a
E.undae DSM 14481
I Siberia permafrost - clone C02
E. undae strain 190-11
Siberia permafrost - cioneA01
73 El Puerto Rico - clone 809
I Siberia permafrost - clone CO3
I Siberia permafrost - clone C06
I Siberia permafrost - clone C08
I Siberia permafrost - clone H05
I Siberia permafrost- clone H03
I Siberia permafrost - clone A05
Siberia permafrost - clone 606
Siberia permafrost - clone 806
El Puerto Rico - clone 806
13 Puerto Rico - clone F08
El Puerto Rico - clone F11

 

 
    
  
   
 
 
 
   
 
  
 
 
  
 
 

la

 

E.aurantiacum DSM 6208
I E. sibiricum strain 255-15
E. sibiricum strain 7-3
Siberian permafrost - clone E04
Exiguobacterium sp. TC38-2b
58 Exiguobacterium sp. India stream
72 Exiguobacterium sp. A19
41 Exiguobacterium sp. 5138
Exiguobacterium sp. A1
83 I Siberia permafrost - clone F05
57 E.antarcticum DSM 14480
99 I Siberia permafrost - clone 805
I Siberia permafrost - clone 805
56 I Siberia permafrost - clone 006
_r——‘ Siberia permafrost - clone A04
E. oxidotoierans JMC12880
E.ucetyllcum DSM 20416

 

 

 

 

 

 

 

B.subtms

 

005

Figure 4.2. Phylogenetic tree based on gyrB sequences of indicated Exiguobacterium
strains and clone libraries from Puerto Rico soil (E1) and three Siberia permafrost soils
dated of 2 to 3 million years (0), 100-200 thousand years (I) and 12 to 40 thousand years
(A ). The tree was produced by neighbor-joining method and was rooted using the gyrB

89

gene from B. subtilis. The nodes with less than 40% bootstrap values were not added to
the tree. The scale bar represents 0.05 changes per nucleotide.

Sensitivity, detection limit and accuracy. We tested the sensitivity of the real-time

detection system using a dilution series of clone for each gene from Exiguobacterium
undae strain 190-11 for each gene. To each dilution we added lug ul'1 of E. coli DNA to
simulate the soil DNA in samples. The data obtained were used to construct a standard
curve relating the CT values to the added mass of Exiguobacterium undae gene clones. A
regression line between the mean threshold cycle (CT) values and the template DNAS
from 1 to 106 dilution range gave an r2 value superior to 0.98 for all genes tested (Figure
4.3). Detection of fluorescence could be observed in DNA concentrations as low as 100

gene copies per ul for the hypothetical gene and as low as 10I gene copies per pl for the
gyrB and rpoB genes (Fig 4).
We also tested the detection limit and our ability to differentiate similar DNA

concentrations of E. undae strain 190-11, E. sibiricum strain 255-15 and E. antarcticum

DSM 14480T for each gene. Different volumes (ranging from 2 to 20 ul) of a dilution
series of template DNA (ranging from 1 to 106 gene copies ul '1) were added to the PCR

reactions. The variability associated with the CT values was evaluated (Figure 4.5) for
low and high copy numbers. Although the curves remained linear for all strains, the
variability associated with CT values at low copy numbers precluded our ability to

distinguish concentrations for different strains in samples with similar amounts. Only
when copy number was greater than 100 were we able to reliably differentiate a twofold

difference in all the samples.

90

The increase in variability with cycle number is apparent when the upper 95%

confidence interval for all determinations is plotted against the gene copy number. Based
on the slope of each individual standard curve, we calculated the maximal error in the CT

value that would still allow detection of a twofold difference in gene copy number
(MAE). This analysis was done for all three genes as illustrated in figure 4.5 for gyrB,
since the other genes gave Similar results. The average MAE value varied little for each
gene tested, 0.51, 0.50 and 0.48 for hypothetical gene, gyrB (Figure 4.5) and rpoB,
respectively. The corresponding 95% confidence interval was in all cases very small for

all genes tested.
To test the accuracy of the system, 104 gene copies of E. undae strain 190-11 was

added to 10 ng of different soil samples (Figure 4.6). Data for all genes showed that in
most cases soil inhibitors for qPCR amplification did not inhibit the reaction by more
than a factor of 10 (data not shown for rpoB and gyrB Since results were similar to those

for the hypothetical gene).

91

45-

 
 
 
 
   

 

 

40 ' RpoB gene
y = -3.0923x + 36,475
35 ' R2 = 0.99
7: . Hypothetical
9. 3° y = -2.956x + 36.412
% 25 1 R2 = 0.99
>5
0 20 -
32
SC: 15 J ' Hypothetical :3
‘ ‘ RpoB G r8 one
0 1O " ‘ o G y 9
" yrB = .
5 l _ _ Linear (RpoB) y 3.6463x + 39.023
5 1 - - - Linear (Hypothetical) R2 = 0.99
, —-Linear (GyrB)
0 T I I I
0 2 4 6 8

Number of copies (log quantity)

Figure 4.3. Calibration curves for each primer set.
Analyses of environmental samples. DNA extracted from the soil samples showed that

Exiguobacterium spp. is widely distributed in the Siberian permafrost (Figure 4.7) and at
a median density of 105 gene copies ug'I of total community DNA. In none of the four

temperate or tropical soils was Exiguobacterium detected by all three primers, which was
the case in only two Siberian samples, numbers 19 and 20. Furthermore, gyrB had the
lowest detection capability in the permafrost environment, but it gave the highest and
only positive detection for these Exiguobacteria in the tropical environments. On the
other hand, the rpoB primer was the only primer to detect Exiguobacterium spp. uniquely
in the permafrost, even though it has the potential to detect both mesophilic and

psychrotrophic ecotypes (Table 4.2).

92

40- - 747-77“-

   
   

       
 

 

 

 

         

. 20L template 1
35 -
8 D4pL template ‘
v 30 - E100L template 3:: l
o IZOthem late
2 25 .
g .‘r
.2 20 1 j: l
O ,
(I) I:
2 10 - ‘ ‘
.r: ., i
.— 5 _
0 j '3 1355
IO N 1- O
9 9 9 9’ 9 9 9
u.l ul |.l.l |.U u.l u.l tn
0 o o q o o o
B Gene copies per uL
45 - - 7 ~- v~~‘—7
I ZpL template
A 40 4 0L template
u
e 35 .éSiim‘i‘i‘i -
2 30 p empae ! a
O i ’-,- -:—'- was
>. 25 - i += :
u - E .3
a a .3:
.f: E w :-
10 .. ii". a:
=1 as
=2 - a
E a t-
s a a a a s
+ + + + +
uJ u.l UJ LU u.l g
0. o 0. o 0. .

Gene copies per pL

Figure 4.4. Detection limit of the Exiguobacterium spp. using real-time PCR. The
denoted volumes of serially diluted gene clone were added to different reaction mixtures.
(A) Detection limit of hypothetical gene. (B) Detection limit of gyrB gene.

93

 

 

 

0 ° 95% CI of CT values

4'5 0 ‘——mean MAE

4 ------ 95% Cl value
a:
g .
a, 3.5 ‘
ID 1-
:: U .
g: u- 3 - 0
o 0 » °
‘3 w 2.5
o\ 2
ID 3 2
8 s . . .
3. 15
s ' » . .

1 o o 00 °

0 O
o o o 000 o o °° o o o o o o
0.5.4.4....,”H.t..Q..o..o..c.........;.,,=-,°,,_,._.,-o..n,“flung-".0,I.”an“; 0
‘ 0° 00° 0 o ° °

0°; o _ "f o____° °°°° o n_:_ o _0_ 0° .

1.005-01 1.00900 1.00901 1.00902 1.00903 1.00904 1.00905 1.00906 1.00907
Gene Copy Number

Figure 4.5. Relationship between gene copy number and error illustrated for gyrB. The
horizontal line represents the MAE to discriminate between samples containing a twofold
difference in Exiguobacterium sibiricum 255-15, E. undae 190-11 and E. antarcticum
DSM 14480T copy number. Values shown represent the mean from 16 independent
standard curves. The 95% confidence intervals are shown as a dashed line.

94

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96

DISCUSSION

Real-time PCR can provide Specificity, sensitivity and precision for quantifying
microbial populations (10, 19), provided that appropriate primers are identified. Using
more than one gene to quantify a taxon will reduce the error in both the quantitation and
specificity. The former is achieved if the genes are single locus, which is not the case for
the 16S rRNA gene, and the later can be achieved by using multiple and less conserved
genes as primer targets.

The copy number of rRN A operons per bacterial genome may vary from 1 to as many
as 15 (1, 7, 13). Even within a genus the rrn copy number can vary, e.g. Bifidobacterium
species have 1 to 5 copies of the rm operon (5). Labrenz and coworkers (16) suggested
using a standard DNA representing the bacteria most likely to predominate in a given
habitat to reduce the copy number error, but this information is often unknown. The
sequenced genome of Exiguobacterium sibiricum 255-15 has nine rrn copies, making the
quantitation issue, if based on this gene, significant.

In the present study, we designed primers for three protein-coding genes (gyrB, rpoB
and a hypothetical gene) to quantify the targeted Exiguobacterium group. The sequenced
genome shows two copies of gyrB gene and one copy of rpoB and the hypothetical gene,
which make them good candidates for study. The data show that the numbers of the
hypothetical and rpoB genes are more consistent in the permafrost samples and in the
Puerto Rican sample for the hypothetical and gyrB genes. This consistency, and similar
and sensitive standard curves suggest that the use of both genes provides a more reliable

quantitation of the targeted Exiguobacteria.

97

Certain protein-coding genes may have other advantages over use of rRNA-targeted
primers. Usually, protein-coding genes have higher levels of sequence variation, which
allow the differentiation of closely related strains (30), which is necessary for studies of
different species from the same genus. Several publications have suggested that gyrB and
rpoB are suitable genes for bacterial phylogeny, possessing essential attributes such as
limited horizontal gene transfer and presence in all bacterial groups (12, 14, 30, 32). The
hypothetical gene with unknown function was also used in this study because it was not
found in any other genus when blasted against the NCBI database, which suggested that
this gene is unique to our genus and not laterally transferred to other genera. The
phylogenetic trees derived from the sequences of these three genes confirmed the ability
of these primers to discriminate subgroups of the Exiguobacteria in clone libraries. The
phylogenetic trees also show considerable diversity within the Exiguobacterium
populations in different environments.

This study indicates that reliance on one primer set will not always give reliable
quantitative results for the target group. Hence, multiple primers are advantageous. When
multiple primers do not give the same results, criteria are needed to determine which
primer sets best reflect the population density of the targeted group. Useful criteria are
specificity with control strains, standard curve sensitivity, phylogeny of amplified clones
and primer performance on a variety of habitat samples. While qPCR provides a fast and
sensitive method for gene quantitation, the multi-locus addition provides greater
Specificity and in some cases sensitivity for more reliable quantitation of a targeted
population. This approach is especially important where specific rRNA primers cannot be

found, or where population resolution is important at the species or ecotype levels.

98

The fact that in some samples only one primer showed positive results suggests
that if Exiguobacterium is present, that it is a substantially different genotype and
probably species. The consistent and significant populations of Exiguobacterium detected
in permafrost by the two primer pairs, and not generally in other soils, suggest that
Exiguobacterium is selected in the Siberian permafrost. Furthermore, this genus may be
ubiquitous in cold environments since a number of strains have been isolated from other
cold environments such as Antarctica (8), Carpathian mountains (Ukraine) (4), Himalaya
(India) (Mayilraj, S. personal communication and sequence DQ450895) and Siberian
permafrost (27). Exiguobacterium ubiquity in cold versus other environments can now be

tested with the qPCR method described herein.

ACKNOWLEDGEMENTS

The outstanding technical assistance of Dr. Annette Thelen from the RSTF
facility at Michigan State University and Chia-Ju Lin is greatly appreciated.
We thank Dr. Sophia Kathariou and Dr. Tatiana Vishnivetskya for providing most of the
Exiguobacterium spp. strains for this study; Dr. David Gilichinsky and Dr. Lycely
Sepulveda for providing the permafrost and the Puerto Rico soil, respectively.

This work was supported by a cooperative agreement with NASA Astrobiology Institute

number NCC2-1274.

99

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CHAPTER 5

ARCHITECTURE OF THERMAL ADAPTATION IN
EXIGUOBAC TERI UM SIBIRIC UM STRAIN 255-15: A GENOME
AND TRANSCRIPTOME APPROACH

104

ABSTRACT

Several microorganisms have wide temperature growth range and versatility to tolerate
large thermal fluctuations in diverse environments. To better understand thermal

adaptation of psychrotrophs, I used Exiguobacterium sibiricum strain 255-15, a
psychrotrophic bacterium that grows from -5°C to 39°C. Its genome is approximately 3

Mb in size, has a GC content of 47.7% and includes 2,978 putative protein-encoding
genes (CDS). I used the genome and transcriptome analysis along with the organism’s
known physiology to better understand its thermal adaptation. A total of about 27%, 3.2%

and 5.2% of E. sibiricum strain 255-15 CDS spotted on the DNA microarray yielded

differentially expressed genes in cells grown at -2.5°C, 10°C and 39°C, respectively,
when compared to cells grown at 28°C. The hypothetical and unknown genes represented
10.6%, 0.89% and 2.3% of the CDS differentially expressed when grown at -2.5°C, 10°C

and 39°C versus 28°C. The transcriptome analyses showed that E. sibiricum is
constitutively adapted to cold temperatures since little differential gene expression was
observed at growth temperatures of 10°C and 28°C, but at the extremities of its Arrhenius
growth profile, namely -2.5°C and 39°C, much more differential gene expression

occurred. The genes that responded were more typically associated with stress response.

INTRODUCTION
About 80% of Earth’s surface is 15°C or colder (18). Psychrophilic together with

psychrotolerant bacteria comprise the cold-adapted microorganisms. These microbes

have been isolated and characterized from various environments such as polar sediments

105

and soils, as well as open oceans (37, 46). Psychrotolerant microorganisms are of special
interest since they grow at a wide range of temperatures, between -5 and +40°C (26, 46),

to tolerate large thermal fluctuations in diverse environments (12, 37).

A number of factors have been identified that provide physiological advantages
for cold-adapted microorganisms (11, 37). A range of mechanisms that contribute to
survival for mesophilic bacteria has been identified by examining the cold-shock
response (28, 44). In contrast, to the best of my knowledge, no research has been devoted
to exploring thermal adaptation of psychrotrophic bacteria over their entire growth
temperature range.

The variation in specific growth rate as a function of temperature is commonly

portrayed by Arrhenius equations (14). The Arrhenius profiles of most bacteria are
characterized by a linear portion in a 20°C suboptimal growth range, which is called the

normal or Arrhenius range (14). Below and above the normal range, deviations of the
thermodependence of growth from the Arrhenius law reveals the inability of cells to
maximize their growth rate (17), but little is known about the reasons why microbes are
unable to maximize their growth rate at these extreme temperatures.

In the psychrotrophic bacterium Exiguobacterium sibiricum strain 255-15, grth

occurs from -5°C to 40°C . This member of the Bacillaceae is Gram positive, rod-shaped,

facultative aerobic, motile with peritrichous flagella (35). The relevance of studying this
microorganism is that this genus has been shown to be prevalent in Siberian permafrost
(36) and can be found in geological layers frozen for 20 thousands to up to 3 million
years. Besides, this microorganism grows over an unusually broad temperature range and

hence provides a good model for exploring molecular mechanisms of thermal adaptation.

106

The genome of E. sibiricum 255-15 has been sequenced to draft status by DOE’s
Joint Genome Institute. The genome has been assembled into 51 contigs of 20 reads or

larger with an estimated genome size of 3 Mb. This study shows that few transcriptional

changes were observed when the microbes were grown at 10°C and 28°C, but a number

of changes were observed after growth at -2.5°C and 39°C, indicating that E. sibiricum

strain 255-15 is constitutively adapted for growth at moderate range of temperatures.

MATERIAL AND METHODS

Bacterial strain and genome sequence. E. sibiricum 255-15 was isolated from a depth
of 43.6 m in the permafrost sediment of the Kolyma Indigirka Lowland by
Vishnivetskaya et al. [105]. At this depth, sediments are estimated to have been
continuously frozen for 2 to 3 million years. A draft genome of 8X sequence coverage
was produced by the Department of Energy’s Joint Genome Institute and annotated by
the automated pipeline operated by Oak Ridge National Laboratory’s Computational
Genomics Group. The annotation used in this work is available at JGI/ORNL dated April
15‘, 2005 (him/genome.ornl.gov/microbialr’exigO. The genome sequence is available on

line at NCBI under the accession numbers: AADW02000001 to AADW02000051.
Arrhenius profile. E. sibiricum strain 255-15 was grown in flasks of V2 tryptic soy broth

(TSB) (Difco, Detroit, MI) shaken at 200 rpm, at temperatures from 39°C to -2.5°C.

Growth rates were calculated from the SIOpe of optical densities for four or more time

points for each temperature and summarized as an Arrhenius relationship.

107

Transmission electron microscopy. Inoculated agar plates were incubated for at 30°C,

12°C and -2.5°C, until they reached a colony size of l to 2 mm of diameter. Cell

morphology and flagella were examined by transmission electron microscopy (TEM).

Probe design and array construction. The genome of Exiguobacterium strain 255-15
has a GC content of 47.7% and 2978 putative protein-encoding sequences (CDS). All
2978 CDS were used to select gene-specific or group-Specific oligonucleotide (70 mer)
probes using CommOligo (20) with group-specific probe design features. The design
criteria were as follows: (i) 85% sequence similarity, 18-base stretch, and -35 kcal/mol
free energy for gene-specific probes; and (ii) 96% sequence similarity, 55-base stretch,
and -90 kcal/mol free energy for group-specific probes. Based on those criteria, 2931
CDS had gene-specific probes; 25 CDS were covered by Six group-specific probes; no
qualified probes were selected for 22 CDS. In addition, - 10 human and 10 Arabidopsis
probes were designed as controls. Those probes are expected to be very specific since the
criteria used are even stricter than those previously suggested (15). All designed
oligonucleotides were commercially synthesized without modification by MWG Biotech

Inc. (High Point, NC). The concentration of oligonucleotides was adjusted to 100 pmol
ul'l. Oligonucleotide probes prepared in 50% DMSO (Sigma Chemical Co., M0) were

Spotted onto UltraGAPS glass slides (Corning Life Science, NY) using a Microgrid II

robotic arrayer (Genomic Solutions Inc., MI). Each oligonucleotide probe had two spots
on a single slide. Additionally, six different concentrations (5~300 ng 1.114) of genomic

DNA were also spotted (four duplicates on a single slide) as positive controls. After
printing, the oligonucleotide probes were fixed onto the slide by UV cross-linking (600

mJ of energy) according to the protocol of the manufacturer (Corning Life Science, NY).

108

 

Growth conditions. All the cells for the DNA microarray experiments came from the

same E. sibiricum 255-15 frozen stock that was used for the genome sequencing. All

experiments were performed by first plating the cells in 1/2 Tryptic Soy Agar (TSA) and
then transferred to V2 Tryptic Soy Broth (TSB) twice. In total, I had six samples grown
independently at 39°C, 28°C, 10°C and -2.5°C. The cells were acclimated by growth at
39°C, 28°C, 10°C and -2.5°C. For the growth at 39°C and 28°C the plates were incubated

overnight. At 10°C, the plates were incubated for 3 to 4 days. At -2.5°C the plates were
transferred three times to new plates to acclimate the cells to lower temperature as

follows: the first plates were incubated overnight at 22°C followed by incubation at 4°C
for 3 days and then for 2-3 weeks at -2.5°C. After growing the cells in agar at the four
temperatures, a loop from each plate was transferred to tubes containing 5 ml 1/2 TSB and
grown in its respective temperatures until an optical density at 600 nm (OD600) of 1.0
was attained. Then 1 ml of this culture was used to inoculate 100 ml of 1/2 TSB in a
Nephlo Flask (Belco), except for the -2.5°C cultures that were inoculated in tissue flasks
for better aeration. The samples were incubated until reaching mid-log growth (0.1 <

OD600 < 0.3) when 100 ml of RNAlater (Ambion, Austin, Texas) was added at the same
temperature as the grown cells. Cells were pelleted by centrifugation at 5,000 X g for 20

min at 4°C and resuspended in 1 ml of RNAlater, transferred to a 1.5 ml microcentrifuge
tube, and re-pelleted at 5,000 X g at 4°C for 10 min.

RNA isolation. The cells were re-suspended in 100 pl of RNase-free 3 mg ml'1

Lysozyme in TE buffer pH 8 (50 mM Tris-Cl and 1 mM EDTA) by vortexing and then

109

incubated at room temperature for at least 20 min or until the pellet cleared. Lysozyme
incubation at 37°C for 1 h was needed to lyze cells grown at -2.5°C. The RNA was then
isolated using the RNeasy mini Prep kit (Qiagen) according to the manufacturer’s
instructions; the step of DNase digestion was included. The resulting RNA was checked
by denaturing agarose gel electrophoresis for DNA contamination and for the presence
and integrity of the rRNA bands. The amount of RNA was quantified using a UV-
spectrophotometer at OD260.

cDNA labeling and slide hybridization. Amino-allyl labeling was performed as adapted
from a protocol of The Institute for Genomic Research (TIGR)

(http://www.tigl'oggjldb/niicroatry/protocolsTlGRshtml). Briefly, 10 pg of total RNA

 

was used to synthesize cDNA overnight at 42°C using 0.5 mM of Random Hexamer

Primers (Invitrogen, Carlsbad, CA), 3:2 ratio of 5-(3-amino—allyl)-dUTP and dTTP
(Ambion), and Superscript II reverse transcriptase (Invitrogen), and subsequently labeled
by coupling reactive Cy5 or Cy3 fluorophores (Amersham, Piscataway, NJ) to the amino-
allyl groups. Purification after cDNA synthesis and chemical coupling were performed
using QiaQuick PCR purification columns (Qiagen) as described in TIGR protocol. The
quantity of labeled cDNA and the fluorophore incorporation efficiency were determined
by using UV-visible spectrophotometry.

Microarray slides were incubated for 60 min at 46°C with prehybridization

solution (50% Ultrapure formarnide (Invitrogen), 5x SSC, 0.1% SDS and 0.1 mg ml'l),

washed three times in double-distilled water and one time in isopropanol, and dried by
centrifugation at 50 X g for 3 min. Two cDNA’s from different temperatures were mixed

for direct comparisons for all temperature combinations. Each microarray received about

110

30 pl of hybridization solution (50% Ultrapure Forrnamide, 5x SSC, 0.1% SDS, 0.1
pg/pl Salmon sperm DNA) containing the two cDNAS. The solution was applied by
capillary action under a coverslip (LifterSlip; Erie Scientific Company, Portsmouth, NH)
placed over the microarray. The whole assembly was sealed in a hybridization chamber
(CMT Hybridization Chamber; Corning Incorporated, Corning, NY) and submerged for
16 h in a 46°C water bath. Microarray slides were washed twice for 5 min at 46°C with
1X SSC-0.1%SDS; twice for 10 min at room temperature with 0.1X SSC-0.1%SDS and
five times for 1 min at room temperature with 0.1 X SSC. Slides were dried by
centrifugation at 50 X g for 3 min and were immediately scanned and analyzed.

Data analysis. Slides were scanned with an Axon 4000B scanner and GenePix 5.0 used
for spot finding. Only spots with more than 80% of pixels greater than background plus 2
standard deviations in either Cy5 or Cy3 channel were used for analysis. Analysis was
performed with Limma (Linear models for microarrays data) library in the CARMAweb
environment (32). The background correction was done by background subtraction of the
median value, followed by within and between arrays data normalization using the print
tip Lowess method, and quantile method, respectively. A moderated t-test based on
empirical Bayes approach (from the Bioconductors Limma package) with an adjustment
of the calculated raw P-values was used with the following methods: Benjamini and
Hochberg (1), Westfall and Young (49) as well as Bonferroni. Only P-values smaller that

0.01 for all these methods were considered statistically Significant for further analysis.

RESULTS AND DISCUSSION

Genome analysis

111

E. sibiricum’s genome sequence was compared by BLASTP with sequences from
other microorganisms. The pathways and types of carbohydrate, amino acid, coenzyme,
cofactor, nucleotide and energy metabolism of this microorganism were inferred from the
genome to give a wholistic view of its metabolic potential (Figure 5.1). The genome
showed that 27% of its CDS have top hits with Bacillus halodurans, while 25% and 24%
have top hits with B. anthracis and B. subtilis, respectively (Figure 5.2). About 75% of
the Exiguobacterium 255-15 CDS encode proteins that are putative homologs to
Psychrobacter arcticus 273-4 proteins, which is a Gram negative microorganism also
prevalent in Siberian permafrost.

The analysis of cluster of orthologous groups (COGS) distribution of E. sibiricum
genome (Table 5.1) shows that it has a distribution similar to most microorganisms.
Approximately 23% of the genes are poorly characterized. Since cold and heat stress
related genes are not yet completely elucidated, it is possible that among these large
numbers of poorly characterized genes there are those important for the cell acclimation
to stress temperatures. The genome encodes apparent homologs of stress-related proteins
as well as many novel proteins that may have unique roles in adaptation to the permafrost

environment (Table 5.1).

112

.‘q‘i

 

 

Trehalose D-galactose Starch and
degradation degradation glycogen
degradation

 

  
 

Requirements:
branched chain
amino acids
methionine or
methylthrioribose
-pheni|alanine?
—biotine

 

Sucrose
degradation

 
 
 

D-gluconate
degradation

     

 

 

Mannitol
deg adation

   
 

 

Rlbitol recherc-1
lacid biosynthesis l
Glycerol and dihydroxyacetone ' ' ‘ 7 ’ .._.

degradation ‘

   
   
 
  

degradation '
r‘Glycerol tel'cfiok l
'BC'ld bigimheiis.
branched-chain amino

f’fa’tt'yicid acid degradation
biosynthesis ‘ /

L-serine and L-alanine , , Amino acid, nucleotide and
. . , - .. coengmebiosmthesis

L-threonine
degradation

Figure 5.1. Metabolic pathway reconstruction of Exiguobacterium sibiricum 255-15
based on genome content (Figure provided by Natalia Ivannova).

1 divided the genome analysis of E. sibiricum 255-15 into the following seven
categories to more specifically analyze this psychroactive microorganism’s metabolism
(Figure 5.1): carbohydrate metabolism, amino acid biosynthesis, amino acid catabolisrn,
coenzyme and cofactor biosynthesis, nucleotide biosynthesis, energy metabolism and
miscellaneous observations, which includes the description of genes involved in

temperature adaptation.

113

rt _—
g m SPECIES %
o B. halodurans 27
:40 _ B. anthracis 25
g B. subtilis 24
I”, B. cereus 21
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Figure 5.2. Distribution of top hits with other microorganisms of Exiguobacterim
sibiricum 255-15 CDS by using BLASTP.

Carbohydrate metabolism. The genome analysis and physiological studies previously
done showed that E. sibiricum 255-15 prefers sugar and carbohydrate polymers as carbon
sources (29, 35). All the genes for Embden-Meyerhoff version of glycolysis such as
glucose-specific PTS, glucose-6-phosphate isomerase, 6-phosphofructokinase, fructose-
bisphosphate aldolase, among others, are present. In addition to glycolysis, E. sibiricum
should be capable of gluconeogenic growth on glycerol due to the presence of glycerol
utilization operons and fructose-1,6-bisphosphatase and also due to its ability to grow on
glycerol as sole carbon source (35). The presence of methylglyoxal synthase is another
indicator that E. sibiricum prefers glycolytic substrates, since it allows bacteria to bypass
the lower part of glycolysis in carbon-rich but phosphorus-limited conditions. E.

sibiricum also has all enzymes from the non-oxidative pentose phosphate pathway, but

114

not from its oxidative branch (no glucose-6-phosphate dehydrogenase and
phosphogluconolactonase). Among the sugars that E. sibiricum can utilize for growth are
(35): D-glucose, D-gluconate, D-galactose (with two operons), maltose, D-fructose,
sucrose, trehalose, beta-glucosides such as salicin and arbutin, mannitol (the last five
sugars have the glucose-specific PTS), N-acetylglucosamine, D-ribose, glycerol and
dihydroxyacetone. E. sibiricum might be able to utilize some other compounds, such as
ethanol and methylthioribose, but it has not been tested experimentally.

Table 5.1. COGS (cluster of orthologous groups) classification of the genes in the genome
of Exiguobacterium sibiricum strain 255-15.

 

CLUSTER OF ORTHOLOGOUS GROUPS “/0 in the total
CATEGORIES COGS

Information storage and processing: 19%
J Translation, ribosomal structure and biogenesis 6

 

 

 

K Transcription 7

 

L DNA replication, recombination and repair 6

 

Cellular processes: 21%

 

D Cell division and chromosome partitioning

 

V Defense mechanisms

 

T Signal transduction mechanisms

 

M Cell envelope biogenesis, outer membrane
N Cell motility and secretion

 

 

U Intracellular trafficking, secretion, and vesicular transport

 

WNWMQNH

O Posttranslational modification, protein turnover, chaperones

 

 

Metabolism: 36%

C Energy production and conversion

G Carbohydrate transport and metabolism
E Amino acid transport and metabolism

F Nucleotide transport and metabolism

H Coenzyme metabolism *

I Lipid metabolism

P Inorganic ion transport and metabolism
Q Secondary metabolites biosynthesis, transport and
catabolism

Poorly characterized: 23%
R General function prediction only 13
S Function unknown 10

 

 

 

 

 

 

 

 

wahwooxlm

 

 

 

 

 

 

115

E. sibiricum 255-15 has a number of enzymes for degradation of carbohydrate
polymers, mostly starch and starch-derived oligosaccharides, which were observed in the
genome and experimentally (data not shown). These include several alpha-amylases,
oligo-1,6-glucosidases, non-glucogenic alpha-amylase, exo-alpha—1,4-glucosidase, alpha-
glucosidase, pullulanases, maltose phosphorylase. E. sibiricum may also store carbon as a
non-branch glucose polymer, similar to glycogen, but without 1->6 branches, due to the
absence of the branching enzyme. E. sibiricum might be capable of storing extracellular
carbohydrate polymers such as glucans due to the presence of a putative glucansucrase,
which catalyzes synthesis of insoluble alpha-D-glucans from sucrose. Most likely, the
linkage pattern of the glucan product is 1->4/ 1->6 alpha-D-glucan based on the
specificity of hydrolases found in the genome. Previous work has shown the presence of
granules inside the cell (35), as well as the presence of exopolysaccarides (Figure 5.3),

which could be result of these gene products.

 

Figure 5.3. Negatively stained electron micrograph of E. sibiricum strain 255-15.
Exopolysaccharide and no flagella are observed after growth at -2.5°C.

116

 

 

Amino acid biosynthesis. E. sibiricum should be auxotrophic for branched-chain amino
acids (leucine, isoleucine and valine) and threonine due to the absence of any enzymes
for their biosynthetic pathways. E. sibiricum might also be auxotrophic for phenylalanine,
since there are no orthologs of the genes for phenylalanine and tyrosine biosynthesis.
However, it is also possible that it might have an unusual pathway for phenylalanine
biosynthesis, Since it has the gene for the first enzyme (after chorismate) chorismate
mutase, which is fused to 3-deoxy-D-arabino-heptulosonate-7-phosphate (DAHP)
synthase. In addition, there is a weak homolog of the periplasmic cyclohexadienyl
dehydratase from P. aeruginosa. However, since Gram-positive bacteria do not have
periplasmic space, it is unlikely that this protein is part of phenylalanine biosynthesis
pathway. Besides, no ortholog of a periplasmic aromatic amino acid aminotransferase of
P. aeruginosa is present. No genes from the sulfate activation pathway (ATP sulfurylase,
APS reductase or APS kinase and PAPS reductase, any of sulfite reductases) were found,
which indicates that E. sibiricum requires an organic sulfur source, such as methionine,
cysteine or methylthioribose. Orthologs of a putative cysteine (cystine) ABC transporter
and a methionine ABC transporter, such as in Lactococcus lactis, were found. E.
sibiricum has a probable serine O-acetyltransferase and cysteine synthase for biosynthesis
of cysteine from serine and sulfide. In addition, it seems to have a transsulfurylation
pathway from methionine to cysteine represented by cystathionine beta-synthase and
cystathionine gamma-lyase. No orthologs of homoserine O-succinyl(O-acetyl)transferase
(metA) or O-acetylhomoserine sulfliydrylase (cysD) were found in the genome. E.
sibiricum has cobalamin-independent homocysteine S-methyltransferase and a pathway

for methylthioribose recycling to methionine. Thus, it appears that E. sibiricum requires

117

 

 

 

methionine or methylthioribose for growth and can produce cysteine by transsulfurylation
from methionine. Tyrosine might be produced from phenylalanine by phenylalanine 4-
hydroxylase and a complete pathway for tryptophan biosynthesis is present. Lysine
biosynthesis appears to be proceeding via acetylated intermediates and employing a
dapX-type diarninopimelate epimerase.

Conventional amino acid biosynthesis pathways are present for the remaining

amino acids: arginine, histidine, glutamate, glutamine, aparagine, serine and even
polyamines.
Amino acid catabolism. E. sibiricum has several amino acid degradation pathways and
some of them can be used as energy sources. It has an operon, which includes NAD-
dependent valine dehydrogenase, which catalyzes oxidative deamination of valine,
isoleucine and leucine, branched-chain alpha-keto acid dehydrogenase,
phosphotransbutyrylase and butyrate kinase. This pathway would allow use of branched-
chain amino acids as nitrogen sources and convert branched-chain amino acids into
corresponding free acids: isovalerate, isobutyrate, and methylbutyrate. The organism also
has the genes to produce ATP through substrate-level phosphorylation under anaerobic
conditions and provides branched-chain acyl-CoAs for fatty acid biosynthesis.

E. sibiricum also has pathways for degradation of the aromatic amino acids
phenylalanine and tryptophan. Phenylalanine dehydrogenase is present, which catalyzes
the oxidative deamination of phenylalanine to phenylpyruvate, a product which can be
further converted to phenylacetate (e.g., by pyruvate dehydrogenase found next to
phenylalanine dehydrogenase). Phenylacetate can be further degraded via a ring-

hydroxylation/beta-oxidation pathway encoded by an operon next to phenylacetate-CoA

118

 

 

ligase. Tryptophan degradation genes encoding tryptophan dioxygenase, kynurenine
forrnamidase and kynureninase are present and could produce enzymes to degrade L-
tryptophan to anthranilate. There is no pathway for further degradation of anthranilate, so
most likely tryptophan can be used as nitrogen, but not carbon source.

E. sibiricum has a pathway for anaerobic degradation of threonine, which includes
threonine 3-dehydrogenase and 2-amino-3-ketobutyrate-COA ligase, which converts
threonine into glycine and acetyl-CoA and would allow using threonine as a nitrogen and
probably carbon source. Glycine can be further degraded via a glycine cleavage system.
L-Serine dehydratase and alanine dehydrogenase are also present; they produce pyruvate
out of L-serine and L-alanine, respectively.

Coenzyme and cofactor biosynthesis. E. sibiricum is auxotrophic for biotin (no KAPA
synthase, KAPA aminotransferase, dethiobiotin synthase and biotin synthase genes). The
rest of coenzyme biosynthesis pathways seem to be complete, with the exception of
several genes missed either by annotation or sequencing. The missing genes include
uroporphyrinogen-III synthase (the gene is present in the sequence, but it was missed by
the gene prediction algorithm), riboflavin kinase/FAD synthase, GTP cyclohydrolase I,
and pantothenate kinase.

Nucleotide biosynthesis. Both purine and pyrimidine biosynthesis pathways are
complete. E. sibiricum has both aerobic and anaerobic ribonucleoside
diphosphate/triphosphate reductases.

Energy metabolism. E. sibiricum has been shown to grow both aerobically and
anaerobically (data not Shown). For aerobic growth, one can observe in the genome a

complete TCA cycle and an aerobic respiratory chain, which consists of monomeric

119

 

 

NADH-quinone oxidoreductase, and two quinol oxidases, one cytochrome caa3-
dependent, another cytochrome ba3-dependent. Although there is no anaerobic
respiratory chain observed in the genome, anaerobic growth has been shown to occur via
fermentation of sugars (data not shown) and maybe via fermentation of branched-chain
amino acids and threonine. Fermentation pathways found in the genome include
pyruvate-forrnate lyase and acetoin (or butanediol).
Miscellaneous observations. E. sibiricum has genes that encode the production of both
glycerol teichoic and ribitol teichoic acids. It has only one fatty acid desaturase, no fatty
acid hydroxylases and no cyclopropane-fatty acid synthase, but it seems to produce
mostly branched-chain fatty acids (29). It might be also capable of producing one or more
different carotenoids (two squalene/phytoene synthases, one of them is clustered with
likely diapophytoene desaturase and another phytoene dehydrogenase). The orange
pigmentation observed in Exiguobacterium colonies suggests that it does caroteinoid
(Monica Ponder personal communication).

This microorganism has several genes that may be involved in thermal adaptation,
i.e. heat and cold-shock. The genes listed in Figure 5.4 are candidates that are present in
E. sibiricum strain 255-15 genome and hence may be expressed under temperature
stresses. These include several ribosomal binding proteins for the translational
machinery, genes responsible to maintain the membrane homeoviscous adaptation, sigma
factors, genes involved in DNA replication and metabolism genes that may have special

temperature adaptations.

120

 

 

 

Ribosomal binding ‘ Metabolism
- CspA,C,R,L — isocitrate dehydrogenase
- GroEL, GroES, GrpE - Cysteine synthase
— rpsF - Glyceraldehyde phosphate
_ rbfA dehydrogenase
_ Ef_Tu — Triose phosphate isomerase
_ Trigger factor-chaperone - Pyruvate dehydrogenase
_ DnaK, DnaJ -chaperone - y-glutamyltranspeptidase
Membrane alteration — D'hydmhpoam'de
acetyltransferase
- Desaturase
— B-ketoacyl carrier protein ' Sigma factors _
_ - rpoE
Miscellaneous _ rpoH
— NusB - rpoD
_ recA - rseB (anti-sigma factor)
- IFZB Lon protease
— General stress proteins 0 DNA replication
- htrA _ Gyr A
— hrcA

Figure 5.4. Known cold and heat stress response genes with homologs to
Exiguobacterium sibiricum 255-15. The genes in red correspond to the heat expressed
genes. The genes in blue are the cold expressed genes and the ones in pink are the ones
that are expressed in both conditions. The Image in this dissertation is presented in color.

 

Transcrigtome analysis

To gain further insight into which of the organism’s genes may be involved in
temperature adaptations, I performed a transcriptome analysis with cells at -2.5°C, 10°C,
28°C and 39°C (Figure 5.5). The 28°C and 10°C temperatures were chosen as the mean
of the maximum and the minimum temperature where the biphasic shift in the growth

rate occurs (Figure 5.6). The temperature of 39°C was selected because it is close to the

upper limit of E. sibiricum 255-15 growth (40°) and -2.5°C was selected as a subzero

temperature where the medium does not freeze.

121

 

 

 

 

 

 

 

I.

.C

\

C

a -

z ’2

-‘ -3
-4
-5 R2 = 0.98 '
-6 r

3.10 3.20 3.30 3.40 3.50 3.60 3.70 3.80
Temperature 1000/T(°K)

Figure 5.5. Arrhenius plot of E. sibiricum 255-15 growth rates in 1/2 TSB. The first phase
of the biphasic response is in gray and the second phase is in black, each with its
respective trend lines and R2 values.

The transcriptome studies overall results are represented by Venn diagrams in

Figures 5.6 and 5.7. A total of about 27%, 3.2% and 5.2% of E. sibiricum strain 255-15

CDS Spotted on the DNA microarray yielded differentially expressed genes in cells
grown at -2.5°C, 10°C and 39°C, respectively, when compared to cells grown at 28°C.
The hypothetical and unknown genes represented 10.6%, 0.89% and 2.3% of the CDS

differentially expressed when grown at -2.5°C, 10°C and 39°C versus 28°C. This data

shows that many unknown genes are differentially expressed, especially at -2.5°C,

suggesting that new genes important to thermal adaptation may be in this group. The

results from the transcriptome comparisons are represented in Table 5.2.

 

122

 

28 vs -2.5°c 28 vs 10°C

 

28 vs 40°C

Figure 5.6. Venn diagram of all differentially expressed genes at the indicated
temperatures

28 vs -2.5°C 28 vs 10‘C

 

28 vs 40°C

Figure 5.7. Venn diagram of unknown or hypothetical genes differentially expressed at
the indicated temperatures

123

 

Table 5.2. F old-change (log odds score) at different temperatures.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ID Gene Product Gene 23°C vs
10°C -2.5°C 40°C

General metabolism

278_1189 Orotate phosphoribosyl PyrE -3.9 -5.6 -O.9
transferase

278_1190 Orotidine 5’-phosphate PyrF -3.8 -5.3 -0.8
decarboxylase

278_1191 Dihydroorotate dehydrogenase 1 PyrD -2.8 -4.1 -1.0

278_1192 dihydroorotate dehydrogenase UbiB -4.3 -6.0 -O.7
electron transfer subunit

278_l 193 Carbamoyl-phosphate synthase, CarB -4.6 -5.8 -O.9
large subunit, glutamine-
dependent

278_1194 Carbamoyl-phosphate synthase, CarA -4.1 ~7.0 -l .2
small subunit

278__1195 Dihydroorotase multifunctional Per -3.8 -5.1 -1.5
complex type

278_1196 Aspartate carbamoyltransferase PyrB -3.9 -5.4 -1.3

278_1 197 Xanthine/uracil permease UraA -2.6 -4.7 -0.5

278_l 198 pyrimidine operon attenuation PyrR -2.2 -3.9 -O.3
protein

283_2148 AICARFT/IMPCHase bienzyme PurD -1.1 -0.4 0.0

283_2149 Phosphoribosylglycinamide PurH -1.2 -1.6 0.1
forrnyltransferase

283_2] 50 Phosphoribosylformylglycinamidi PurN -1 .2 -2.5 0.4
ne cyclo-ligase

283_2] 5 1 Amidophosphoribosyl transferase PurM -l .0 -2.8 0.1

283_2152 Phosphoribosylformylglycinamidi PurF -O.7 -2.8 -0.2
ne synthase II _

283_2153 Phosphoribosylformylglycinamidi PurL -1 .3 -2.3 -0.5
ne synthase I

283_21 54 Phosphoribosylformylglycinamidi PurL -0.8 -1 .6 -0.3
ne synthetase PurS

283_2155 SAICAR synthetase PurS -0.8 -3.4 -0.4

283_2156 Adenylosuccinate lyase PurC -1.0 -2.5 -0.8

283_21 57 Phosphoribosylaminoimidazole PurB -0.6 -2.6 -O.4
carboxylase, ATPase subunit

283_215 8 1-(5-Phosphoribosyl)-5-amino-4- PurK -1.0 -2.4 -1.1
imidazole-carboxylate (AIR)
carboxylase

277_1054 Adenylosuccinate synthetase PurA -O.9 -0.8 0.3

 

 

 

 

 

 

124

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 5.2 (cont’d)

Energy metabolism

245_40 NADH dehydrogenase Ndh -0.1 -2.0 -0.5

245_47 NADH dehydrogenase Ndh -0.6 —1.3 0.5

249_98 Ubiquinone/menaquinone UbiE -0.8 -2.2 -0.9
biosynthesis methyltransferase

250_1 14 Nicotinate PncB 0.2 1.0 0.4
phosphoribosyltransferase related

272_751 oxidoreductase, putative 0.3 3.2 0.9

272_787 2-polyprenyl-3-methyl-5- UbiQ -0.1 -1.6 -0.1
hydroxy-6-metoxy-1 4-
benzoquinol methylase

279_1294 electron transfer flavoprotein FixA -0.2 1.8 -O.3
beta-subunit

279_1295 electron transfer flavoprotein, FixB 0.3 2.4 0.3
alpha subunit

281_1741 NADH-dependent flavin NemA 0.2 1.2 -0.1
oxidoreductase

284_2268 Rieske 2F e-ZS iron-sulfur protein -0.2 3.6 0.0

285_2440 Carbonic anhydrase CynT 0.0 1.9 3.2

284_2338 H+-transporting two-sector AtpD 0.1 -0.9 -O.9
ATPase, gamma subunit

284_2339 ATP synthase F 1, alpha subunit Ath 0.1 -1.6 -l.8

284_2340 H+-transporting two-sector AtpA -O.5 -1 .2 -1 .7
ATPase, delta (OSCP) subunit

284_2341 ATP synthase F0, subunit B AtpH -0.2 -1.1 -1.0

284_2342 ATP synthase F0, C subunit Ath 0.2 —1.3 -1.2

284_23 74 6,7-dimethyl-8-ribityllumazine Rin -0.9 2.0 0.4
synthase

284_2375 3,4-Dihydroxy-2-butanone 4- RibB 0.3 2.5 0.5
phosphate synthasezGTP
cyclohydrolase II

284_23 76 Lumazine-binding protein RibC 0.3 2.2 0.3

284_23 77 Riboflavin biosynthesis protein RibD -0.9 2.3 1.1
RibD

278__1235 cytochrome caa3 oxidase subunit cyoC -1.7 -2.2 —1.2
III

278__1236 cytochrome c oxidase subunit I cyoB -l .2 -2.0 -1.2

278_1237 cytochrome c oxidase subunit II cyoA -0.5 -4.1 -1.7

278_1238 Protoheme IX farnesyltransferase cyoE -1.3 -2.0 -O.5

283_201 5 Heme/copper-type cyoA -0.7 2.3 0. 1

 

cytochrome/quinol oxidases
subunit 2

 

 

 

 

 

125

 

Table 5.2 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

274_901 Dihydropteroate synthase FolP -0.3 1.1 -O.6

274_902 Dihydroneopterin aldolase F olB 0.5 2.2 0.5
familyzDihydroneopterin aldolase

257_279 Dihydrofolate reductase F olA 0.2 3.0 -0.6

Carbohydrate metabolism

260_327 glycerol-3-phosphate GlpA 0.5 2.6 1.1
dehydrogenase

247_71 Glycerol kinase GlpK 0.6 2.4 -0.3

247_72 Aquaporin GlpF l .7 3 .8 0.1

28l_1712 glycerol-3—phosphate GlpA -0.2 -0.6 2.0
dehydrogenase, aerobic

248_85 simple sugar transport system -1.1 -2.3 -l .5
permease protein

248_86 sugar ABC transporter (permease) 0.1 -1.6 -O.4

256_250 Phosphoenolpyruvate-protein PtsA 1 .l -O.1 -1 .5
phosphotransferase

256_252 PTS system, glucose-specific PtsG -0.4 -l.0 0.2
IIBC component

260_320 glucose uptake protein GlcU -0.7 1.3 1.9

260_321 glucose l-dehydrogenase gdh 0.0 2.5 2.3

262_369 fructokinase RbsK -0.3 -0.9 0.3

262_371 PTS system, sucrose-specific PtsG -0.6 -2.6 -1.1
IIBC component

264_451 butyryl-CoA dehydrogenase CaiA 0.4 2.7 -O.4

265_462 Phosphoenolpyruvate PckA 0.2 l .9 0.1
carboxykinase (ATP)

265_481 maltose permease -1.1 -1.1 -l.4

281_1564 L-lactate dehydrogenase Mdh 0.8 3.1 1.6

281_1578 Alpha amylase, catalytic AmyA 1.6 3.9 1.4
subdomain

28l_1678 maltosaccharide ABC transporter, MalG 0.0 2.9 1.2
permease

281__1679 maltosaccharide ABC transporter, ngA -0.3 1.6 1.5
permease protein

281_1681 Alpha amylase, catalytic AmyA 0.1 1.4 0.3
subdomain

281_1713 Glycerol kinase GlpK -3 .0 -0.4 -0.5

281_l715 Aquaporin GlpF -1.0 1.3 -0.9

282_1773 Alpha amylase, catalytic AmyA -0.1 0.3 1.7
subdomain

 

 

 

 

 

 

126

 

Table 5.2 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

282_1868 transcriptional repressor of the 0.0 2.3 -0.3
xylose operon

282_1876 UDP-glucose 4-epimerase GalK -0.3 0.9 0.2

282_1878 aldose l-epimerase GalT -0.6 1.1 0.2

282_1912 glycerol dehydrogenase ARAl -0.6 -2.0 0.5

283_2100 PTS system, N- 1.0 1.4 -0.6
acetylglucosamine-specific IIBC
component

283_2101 Phosphotransferase system IIC 0.7 3.8 0.2
components glucose/maltose/N-
acetylglucosamine-specific

284_2172 Sugar-specific permease, EIIA 1 3.0 —0.9 0.2
domain

284_2210 Alpha amylase, catalytic AmyA 0.6 -1.6 0.3
subdomain

285_2848 Alpha amylase, catalytic AmyA 1.5 2.6 1.0
subdomain

285_2893 Alpha amylase, catalytic AmyA 0.0 3.0 -0.3
subdomain

283_2005 Pyruvate-formate lyase PflD 0.9 l .9 1.7

266_510 pyruvate ferredoxin PorA -1.2 -2.4 0.1
oxidoreductase, alpha subunit

Amino acid metabolism

249_105 3-dehydroquinate synthase AroB -1.3 —1.9 -0.3

250_112 phosphoglycerate mutase GmpB -0.3 0.9 0.2

250_1 14 Nicotinate PncB 0.9 1.0 0.4
phosphoribosyltransferase related

250_121 Alanine racemase region Alr -0.5 -1.0 0.2

257_273 cystathionine gamma-synthase MetC -2.6 1.1 -0.4

257_274 cysteine synthase CystK -3.1 0.3 -0.7

260_328 probable amino-acid transporter 0.5 -1.6 0.8
transmembrane protein

262_366 Amino acid/peptide transporter -1.1 -1.4 -0.3

264_434 Histidinol phosphate phosphatase HisJ 0.4 1.5 -0.3

264_435 ATP phosphoribosy[transferase HisZ -0.5 1.3 0.0
involved in histidine biosynthesis

264_436 ATP phosphoribosyltransferase HisG -0.7 1.4 0.5

264_43 7 Histidinol dehydrogenase HisD -0.9 1.1 0.1

264_438 histidinol-phosphate HisC -0.6 1.2 0.3

 

aminotransferase

 

 

 

 

 

127

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 5.2 (cont’d)
264_439 imidazoleglycerol-phosphate HisB -0.6 1 .5 0.3
dehydratase
264_440 Imidazole glycerol phosphate HisH -O.5 0.9 0.3
synthase, glutamine
amidotransferase subunit
264_441 Phosphoribosylformimino-S- HisA -0.6 1 .4 0.2
aminoimidazole carboxamide
ribotide isomerase
264_442 Histidine biosynthesis protein HisF -0.6 1.8 0.4
264_443 phosphoribosyl-ATP HisI -0.6 1 .6 0.3
pyrophosphatase/phosphoribosy1-
AMP cyclohydrolase
264_444 phosphoribosyl-ATP -0.7 1 .0 -0.2
pyrophosphatase
264_447 prolyne dehydrogenase 0.7 1.1 -0.8
266__508 L-threonine 3-dehydrogenase Tdh -1.1 -l .8 0.0
272_784 Amino acid ABC transporter, HisM 2.0 1.7 -0.4
permease protein, 3-TM region,
His/Glu/Gln/Arg/opine
272_785 ABC-type amino acid transport His] 1.0 2.6 0.1
270_612 Choline-glycine betaine BetT 1.3 -1.2 -0.7
transporter
279_1267 Threonyl-tRNA synthetase, class ThrS 0.1 -1.8 -0.8
Ila
279_1276 RNA methyltransferase, TrmH PheS -0.2 -1 .6 -O.8
family
279_1277 Phenylalanyl-tRNA synthetase, PheT -0.3 -1.5 -0.2
alpha subunit
281_1604 Glycyl-tRNA synthetase, alpha GlyQ 0.0 -2.1 -O.6
subunfi
283_1956 Gutamate-l-semialdehyde HemL 0.5 2.8 -0.8
aminotransfer
283_2041 Arginine biosynthesis ArgJ -0.1 3.2 1.7
283_2089 D-alanyl-D-alanine VanY 0.1 5.2 0.8
carboxypeptidase
283_2102 Ornithine aminotransferase PtsG 0.7 2.7 -0.7
283_2104 arginine omithine antiporter 1.3 1.4 -0.7
283_2111 Glycine betaine/L-proline OpuB 1.4 2.9 0.0
transport ATP-binding subunit C
283_2] 12 Peptidoglycan-binding LysM OpuB 1.8 2.5 -0.6
A

 

 

 

 

 

 

 

128

”TI

1
V

 

Table 5.2 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

283_2117 Dihydrodipicolinate reductase DapD 0.3 1.0 ~0.3

283_2118 Dihydrodipicolinate synthase DapB 1.4 1.6 -0.1
subfamily

283_21 19 Aspartate-semialdehyde DapA 1 .9 1 .7 0.1
dehydroggnase, USG-l related

285_2845 Phosphoserine aminotransferase SerC 1.7 2.2 -1.0

285_2846 D-3-phosphoglycerate SerA 0.9 2.4 -0.3
dehydrogenase

285_2878 Glutamate synthase, GltD 0.6 4.9 1.1
NADH/NADPH, small subunit 1

285_2879 glutamate synthase (NADPH) 1.5 4.5 1.0
large chain

259_295 Lysine/omithine N- IucD 0.2 2.0 0.8
monooxygenase

DNA replication, transcription and translation

251_136 Alanyl-tRNA synthetase, class IIc AlaS -0.2 -1.5 -0.4

268_568 Tyrosyl-tRNA synthetase, class Ib TyrS -0.9 —2.5 -0.4

262_353 Helicase, C— SrmB 1.5 0.9 -0.7
terrninalzDEAD/DEAH box
helicase, N-terminal

27l_642 Ribosome-binding factor A RbfA 0.4 0.9 -0.6

27l_643 Initiation factor 2:Small GTP- InfB 0.5 1.1 -0.8
binding protein domain

27 l_644 ribosomal protein, L7Ae family Rpl8A 0.9 1.5 -O.4
(50S ribosomal protein)

27 l_645 Predicted nucleic-acid-binding 0.6 1.0 -0.6
protein implicated in transcription
termination

27l_646 Transcription termination factor NusaA 0.7 1.2 -0.6
NusA

27l_656 Elongation factor Ts Tsf -O.9 -1.9 -0.5

27l_694 Bacterial DNA topoisomerase I TopA -0.1 -1.7 -0.9

272_724 Inosine guanosine and xanthosine DeoA 1.6 2.7 1.4
phosphorylase

272__723 pyrimidine-nucleoside Pnp 0.7 2.3 1.0
phosphorylase

272_765 Bacterial DNA topoisomerase III TopA 0.6 1.6 0.2

277_1053 DnaB helicase DnaB 0.0 2.3 1.4

278_1201 Isoleucyl-tRNA synthetase, class IleS 1.0 -1.9 -1.0
Ia

278_1221 Ribosomal protein S32, bacterial Rme 0.2 -1.7 -0.1

 

and organelle form

 

 

 

 

 

129

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 5.2 (cont’d)
279_1285 Ribonuclease HIII RnhC -0.3 2.1 0.2
279_1325 Glutamate-1-semialdehyde-2,1- HemL 0.5 1 .7 0.6
aminomutase
279_1326 Valyl-tRNA synthetase, class Ia ValS 0.6 -l.3 -0.4
279_1322 Glutamyl-tRNA reductase HemA 0.1 -1.0 -0.3
280_1438 similar to Oligoendopeptidase F -1.8 2.2 0.1
280_1496 DNA topoisomerase VI subunit A -0.8 3.7 1.4
281_1533 NusB antitermination factor NusB -0.6 -1.9 -O.4
281_1593 Helicase, C- SrmB 0.9 1.6 -0.6
terminalzDEAD/DEAH box
helicase, N-terminal
284_2171 Oligoendopeptidase F 1.9 4.4 0.0
284_23 86 Transcription termination factor Rho 0.1 1.4 -0.1
Rho
285_2751 Ribosomal protein L25 RplY 0.4 6.2 2.5
285_2752 Helicase, C- HepA 1.1 0.7 2.0
terminalzDEAD/DEAH box
helicase, N-terminal
285_2754 Gram positive topoisomerase IV, GyrB -0.1 4.4 2.6
subunit B
285_2756 Gram positive topoisomerase IV, GyrA 0.0 1.1 0.5
subunit A
248_82 ATP-dependent DNA helicase RecQ -l .0 -1.9 0.2
RecQ
261_350 RecF protein RecF 0.1 1.4 -0.8
266_514 RecA bacterial DNA RecA 0.3 1.3 0.4
recombination protein
273_836 Exonuclease DnaQ -0.5 -1.2 -0.6
278_1 162 RecG-like helicase RecG 0.4 1.5 -0.3
281_1531 Exonuclease VII, small subunit XseB -0.5 -1.9 -O.1
281_1532 Exonuclease VII, large subunit XseA -0.5 -1.4 -0.1
242_17 Bacterial regulatory protein, MarR 8.9 2.2 0.7
MarR
248_81 Bacterial regulatory protein, MerR -0.4 -0.6 0.8
MerR
248_89 Bacterial regulatory protein GntR, GntR -0.4 -1.8 -1.1
HTH '
255_236 RNA polymerase sigma-54 factor RpoN 0.4 2.2 1.4
27l_659 Sigma-70 factor 0.0 -2.2 0.1

 

 

 

 

 

 

130

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 5.2 (cont’d)
285_2541 Bacterial regulatory protein, MarR 0.0 1.5 -O.2
MarR
285_2542 Transcriptional regulator MarR -0.1 -2.8 -0.8
285_2572 Transcriptional regulator GntR 0.4 -3.1 1 .3
285_2919 Helicase, C- 0.3 1.5 0.5
terminalzDEAD/DEAH box
helicase, N-terminal
Miscellaneous observations
27l_660 methylation of methyl-accepting CheD 0.0 -2.1 0.3
chemotaxis protein KO: K03411
chemotaxis protein CheD
27l_661 chemotactic methyltransferase CheC -1.0 -3.1 -0.1
inhibitor KO: K03410
chemotaxis protein CheC
27l_662 CheW-like protein CheW -0.5 -3.2 0.1
27l_663 CheW-like proteinzATP-binding CheA -0.5 -2.9 0.2
region, ATPase-likeszt
27l_664 putative flagellar biosynthesis Fth -O.3 -3.0 0.3
protein Fth KO: K04562
flagellar biosynthesis protein
Fth
27l_665 ATPas Fth -0.8 -3.7 0.0
27l_666 Flagellar biosynthesis protein F lhA -O.8 -3.2 0.3
FlhA
271__667 Flagellar biosynthetic protein F lhB -1.0 -3.7 0.3
FlhB
27l_668 Flagellar biosynthesis protein FliR FliR -0.8 -3.5 0.1
27l_669 F lagellar biosynthesis protein FliQ -O.l -3.8 0.7
F linType III secretion protein
HrpO
27l_670 Flagellar transport protein FliP FliP -1.0 -3.3 0.3
27l_671 Flagellar biogenesis protein F liO -0.8 -4.4 0.1
27l_672 Response regulator receiver CheY -0.6 -3.3 0.4
27 l_673 Surface presentation of antigens CheC -0.4 -3.8 0.4
(SPOA) protein
27l_674 Flagellar motor switch protein F liM -1.2 -3.7 0.0
FliM
27l_675 flagellar FliL protein KO FliL —0.5 -3.1 0.5
27l_679 Flagellar hook-length control FliK -0.6 -2.9 0.5
protein
27l_682 ATPase F liI/Y scN PM -0.8 -2.9 0.4

 

 

 

 

 

 

131

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 5.2 (cont’d)
27l_683 Flagellar biosynthesis/type III FliH -0.5 -2.2 0.5
secretog pathway protein
27l_684 Flagellar motor switch protein FliG -0.3 -3.0 1.1
FliG
27l_685 F lagellar F liF M-ring protein FliF -0.9 -3.6 0.3
27l_686 F lagellar hook-basal body FliE -0.4 -1.4 0.0
complex protein FliE
27 l_688 Flagellar basal-body rod protein -0.1 -3.1 1.0
FlgB
275_944 F lagellar protein FliS FliS -0.2 0.7 -0.1
275_945 flagellar hook-associated protein 2 FliD 0.4 1.4 0.1
275_946 flagellar protein FlaG 0.4 1.4 0.5
284_2328 flagellar hook-basal body protein FlaG 0.6 -2.2 -l.1
284_2329 flagellar basal-body rod protein FlaG -0.1 -2.0 -1.1
KO
273_798 Response regulator receiver OmpR 0.5 1.2 0.4
279_1330 Type II secretory pathway PulJ -0.2 -1.4 -0.8
component PulJ
279_1331 Tfp pilus assembly protein PilW -0.3 -0.4 -0.3
279_1335 Type II secretory pathway PulE -0.4 -1.6 -1.2
ATPase
279_1336 Pilus retraction protein PilT PilT —0.5 -2.0 -1 .5
279_1337 type IV pilus assembly protein PilC -0.8 -1.9 -1.1
PilC
279_1338 Tfp pilus assembly protein PilE -0.1 -2.5 -1.3
279_1339 signal peptidase PulO -0.1 -1.5 -1.3
[D Gene Product Gene 40°C
Phosphate starvation 28°C 10 °C -2.5°C
262_3 82 low-affinity inorganic phosphate PiT
transporter -O.5 -1 -1.9
281_1571 PhoU PhoU 2,3 2,9 1.8
281_1572 Phosphate transport system PstB
permease protein 1 2.0 2.4 1.8
281_1573 Phosphate transport system PstA
permease protein 2 2.6 2.8 1.6
281_1574 Phosphate ABC transporter, PstC
permease protein PstC 1.5 1.8 1.7
281_1575 Phosphate binding protein PstS 2,9 3_1 1,7
heat shock proteins
281_1649 Heat shock protein DnaJ, N- DnaJ
terminal -0.3 0.6 0.9

 

 

 

 

 

 

 

132

m
\

 

 

Table 5.2 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

281_1650 molecular chaperone DnaK DnaK

(Hsp70) 0.4 2.0 0.5
281_1651 molecular chaperone GrpE GrpE 0,8 19 1, 5
281_1652 Negative regulator of class I heat HrcA

shock protein 1.4 2.0 1.1
283_2134 ATPases with chaperone activity ClpA

ATP-binding subunit 1.3 1.9 0.9
284_2427 Chaperonin Cpn60/TCP-l GroL 1,7 33 2,4
284_2428 Chaperonin GroES (HsplO) GroS 2,0 3,8 3,5

 

The results from the transcriptome analysis confirmed the projections from the
genome analysis and from previous physiological studies done with this microorganism
(29, 35). The general trend of E. sibiricum metabolism seen as temperature decreases is
that changes in expression of functions that are associated with the reduction of growth
rate (Figure 5.5 and Figure 5.8). This reduction in metabolic rate is certainly in part
conferred by the gradual reduction in expressed levels of pyrimidine, purine and several
other metabolic processes. A similar observation was reported by Budde and
collaborators with B. subtilis growing at low temperature (2).

Changes in gene expression commonly observed in cells enduring heat and cold
shock were also observed during growth at the upper temperature limit of E. sibiricum
255-15 and at subzero temperature, respectively. These changes were in transcripts
associated with carbohydrate metabolism, energy metabolism, amino acid biosynthesis
and catabolism, membrane and cell wall adaptation as well as DNA replication,

transcription and translation (Figure 5.9).

133

 

Pyrimidine pathway

Phosphate uptake

Heat shock genes

 

Figure 5.8. Heat maps of E. sibiricum strain 255-15 showing gradient of gene expression
with increase or decrease of temperature growth. Image in this thesis is presented in
color.

134

 

 

 

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135

Carbohydrate metabolism. There seemed to be some differences in preference for

carbon source utilization due to temperature (Table 5.2). For instance, glycerol can be
used as a carbon source at 24°C but not at 4°C in the physiology study (29) and in the
transcriptome the genes from the glycerol metabolism such as one of the genes for

glycerol 3-phosphate dehydrogenase (glpA) was up regulated at 39°C, but down
regulated at 10°C. At -2.5°C, however, the pathway for glycerol degradation is again up

regulated and its differential expression is higher than at all the previous temperatures
(glp K, F, A) as well as D-galactose genes. Temperature also seems to affect the carbon

source take up, since we observed up-regulation of all the genes involved in the PTS

transport system of glucose at 25°C, 10°C and 28°C when compared to 39°C. The PTS

system is down regulated at 39°C but glucose is still being taken up by up-regulated

glucose permeases, as well as other sugars such as maltose, melobiose and polymers,

since maltose-binding proteins and Na+/ melobiose and alpha-amylases are up regulated
at 39°C. The fact that enzyme structure and function can be affected by, either low or

higher temperatures, suggests that cells will increase the synthesis of proteins to
compensate for a decrease in activity and stability (22), but in this case the cell is coping
with the different temperatures by changing its carbon source utilization or uptake
mechanism. Another interesting observation is that at -2.5°C several glucosidases (alpha-
amylases) have different gene expressions at different temperatures; some are highly
expressed at -2.5°C and others are down regulated when compared to the other
temperatures. In a few cases, we observed the gene expression for this type of enzyme to

gradually change expression with the temperature. Several others have described

136

different physiological efficiencies of mesophilic and psychrophilic alpha-amylases (5,
39). Maybe, E. sibiricum has alleles for both mesophilic and psychrophilic alpha-
amylases, which would explain the preferential gene expression at certain temperatures.
E. sibiricum can certainly produce intra and extracellular polymers that are probably
carbohydrate, since storage granules were observed previously in transmission electron
microscopy (35), as well as external slime capsule (Figure 5.3), additionally several
genes related to capsular polysaccharide biosynthesis were also expressed. The diverse
genes for exopolysaccaride synthesis were downregulated at 25°C when compared to
10°C. In microscopic observations, the exopolysaccharide was present at all temperatures
(Figure 5.3), but probably since the metabolism of E. sibiricum is reduced at -2.5°C, this
is also reflected in the gene expression level, suggesting that it is still producing the
exopolysaccharide but in smaller quantities.
Energy metabolism. E. sibiricum is certainly able to grow aerobically as well as
anaerobically. This was observed not only experimentally by growing the cells under

anaerobic conditions (data not shown) but also by the results obtained in the
transcriptome analysis at 39°C (Table 5.2). At this temperature several genes from
different pyruvate fermentation pathways were expressed, such as pyruvatezferrodoxin

oxidoreductase, pyruvate-formate lyase and L-lactate dehydrogenase. This transcriptome

result is not surprising since oxygen solubility is significantly reduced at 39°C in water,
about 6.1 mg l" (3, 51). This amount of oxygen is considered to be close to the limit for

survival of most vertebrates (51). Additionally, other factors such as higher culture
medium viscosity than water and the microorganism’s high metabolic rate at this

temperature would contribute to the decrease of oxygen availability to E. sibiricum,

137

 

 

generating a microaerophilic or even anaerobic environment that would trigger the
expression of fermentation pathways. Like oxygen, C02 availability also seems to be an
issue at 39°C, since the gene for carbonic anhydrase synthesis is induced in E. sibiricum
as it is for E. coli under heat stress (25). This enzyme interconverts C02 and bicarbonate.
Various essential metabolic processes require either C02 or bicarbonate. Although carbon
dioxide and bicarbonate spontaneously equilibrate in solution, the low concentration of
C02 in air and its rapid diffusion from the cell mean that insufficient bicarbonate is
spontaneously made in vivo to meet metabolic and biosynthetic needs, so the cell needs
to express this gene to overcome this problem (25). The gene for this enzyme is also up
regulated at -2.5°C when compared to 28°C, but down regulated when compared to 39°C;
this probably indicates that C02 is also limiting for the cell at -2.5°C. Even though at -
25°C the solubility of gases increases considerably in the medium, the amount of
C02/bicarbonate produced by the cell is probably not sufficient due to the low
metabolism of the cell, leading to the expression of this gene.

Another indication that E. sibiricum is changing its cell bionergetics at the
temperature extremes is the fact that ATPase sythase and cytochrome synthesis (cyo C,
B, A, E) operons are down regulated at -2.5°C and 39°C. These two operons are used for
ATP synthesis and generation of proton motive force during aerobic respiration,
respectively. However, the reasons for down regulating these genes are certainly different
for these extreme temperatures. In the case of -2.5°C, the cell is still respiring 02 due to
the high solubility of this gas at this temperature but also, since several electron carrier
genes are up regulated when compared to all the other temperatures, namely, the genes

for FAD biosynthesis (Rib H, B, D) and Rieske Fe/S. The better explanation for reducing

138

the expression of these genes at -2.5°C is the low metabolic rate of the microorganism.
On the other hand, the low expression of ATP synthase and cytochrome c genes at 39°C
is probably due to decreasing respiration, i.e. proton motor force (PMF), caused by low
02 concentration in the medium. This is consistent into a switch from oxidative
phosphorylation to substrate-level phosphorylation indicated by the expression change of
two genes, known to be expressed in microorganisms under anaerobic conditions (50),
pyruvate-formate lyase (PfyD) and pyruvate-ferrodoxin oxidorectase (PorA).

Energy metabolism also requires phosphate for the synthesis of ATP. At 25°C,
10°C and 28°C, E. sibiricum seems to have enough phosphate available in the medium;
however at 39°C the cell seems to undergo phosphate starvation, since all the genes for
inorganic phosphate starvation response are up regulated (PstABC and PhoU). This
response suggests that somehow this high temperature affects the availability of
phosphate to the cell.

Amino acid biosynthesis and catabolism. Amino acids in the cells are not only
important as building blocks and energy sources but also as osmoprotectants (44). At
25°C and 10°C the transport of osmoprotectants for glycine betaine, camitine, choline
system permease is up regulated and completely down regulated at 39°C (Table 5.2).
Additionally, proline dehydrogenase, which is responsible for the first step in the
conversion of proline to glutamate, is progressively up regulated with the decrease of
temperature, reaching a high gene expression at -2.5°C. In E. coli the shift to higher
osmolarity triggers the accumulation of glutamate as an osmoprotectant (8). In E.
sibiricum at -2.5°C the media becomes supercooled (24), the supercooled water generates

a water flow out of the cell as if it was under salt stress. So the decrease of temperature is

139

sensed by the cell due to the differential chemical potential that probably triggers the
production of glutamate, from proline degradation, as an osmoprotectant as well as the
uptake of other osmoprotectants. In addition, genes for carnitine degradation that
generate several osmoprotectans are also upregulated at -2.5°C. Therefore, besides the
cold stress per se, cold temperatures also seem to affect the osmotic homeostasis of the
cell.

E. sibiricum also seems to be changing its amino acids metabolism, especially at

25°C. Histidine, serine, arginine and lysine biosynthesis genes are up regulated at -2.5°C
when compared to the other temperatures. Hence, cold stress seems to lead to flux and
pool size redistribution throughout the entire network of amino acid metabolism. A
similar effect was observed in cowpea cells under heat shock, which modified the
metabolism and concentration of diverse amino acids in the cells (23). The reason for a
change in cell metabolism is uncertain, but it maybe to synthesize more stable proteins at
lower temperatures.
Cell membrane and cell wall adaptation. Cell membrane is important for the
transmembrane transfer of molecules and other functions of the membrane-bound
protein. After cold shock, bacterial cells experience membrane modifications, such as to
increase unsaturation in the membrane phospholipids and decrease in chain length of
fatty acids (11, 27, 34, 38) to help maintain the homeoviscosity and hence function (11,
38).

This phenomenon has been extensively studied in cyanobacteria, Anabaena
variabilis and Synechocystis PCC 6803. Mutants defective in the desaturation of fatty

acids (gene desA) that have a lower growth rate at low temperature (47). It has also been

140

 

 

found that some bacteria such as Vibrio sp. and Micrococcus cryophilus adapted to low
temperature by decreasing the chain length of the fatty acids (34, 38). Further studies of
cold-shock showed an increased degree of unsaturation in the cold-adapted lipid A of E.
coli (4) and changes in the branched fatty acid profile of B. subtilis (19).

E. sibiricum also seems to change its saturation and chain length under different
temperature conditions. Ponder and collaborators (29) demonstrated that E. sibiricum

255-15 shifted the fatty acids from saturated to unsaturated at 4°C, consistent with my
finding of an increase in fatty acid desaturase gene expression at 10°C and -2.5°C. The

fatty acid C16:0 was the predominant fatty acid in E. sibiricum 255-15 at mesophilic but
at 4°C a shift occurred to iso C17:0 (29). Therefore, E. sibiricum seems to be keeping its
homeoviscous adaptation by increasing the membrane fatty acid saturation.

Another important change in E. sibiricum 255-15 with cold temperature is the
increase of gene expression of peptidoglycan biosynthesis genes (MurA, D, E, I) as well
as the lysine biosynthesis (DapA, B, D), which is one of the main amino acids in the E.
sibiricum peptidoglycan structure (35) only observed at -2.5°C (Table 5.2). The
thickening of the cell wall at -2.5°C was noticed as well by the increased difficulty to lyse
the cell with lyzozyme during the RNA extraction (data not shown). This thickening of
the cell wall at subzero temperature is probably for protection against cell disruption by
ice formation and/or osmotic pressure that can be generated at subzero temperatures.
DNA replication, transcription and translation dynamics. The DNA becomes more
negatively supercoiled (11), while under heat stress, the DNA becomes less negative
supercoiled (21). In both cases the DNA must be stabilized in a more functional

conformation. In the case of cold stress, nucleoid-associated proteins such as Gyrase A,

141

IHF and H-NS are suggested to be necessary for its relaxation (13, 40, 48); while for heat
stress only gyrase A has been described as being important. In E. sibiricum only at -2.5°C
and 39°C DNA topoisomerases are up-regulated (gyrase B for both temperatures and
gyrase A only at 25°C DNA), suggesting that E. sibiricum DNA topology at -2.5°C and
39°C has to constantly adapt its supercoiling by expressing the DNA topoisomerase genes
(Table 5.2).

At the transcriptional level, we observed several genes enconding transcriptional
regulators in E. sibiricum, including ARO8, MarR and GntR family proteins, which
showed significant expression changes at 39°C. The MarR family transcriptional
regulators were also induced in B. subtilis and Termothoga maritima during heat stress
response (16, 30). In the case of T. maritima (30), the expression change of MarR family
protein was dramatically higher during a long-term heat adaptation experiment, which
was similar to the response observed in E. sibiricum at 39°C (Table 5.2). This suggests
that this gene is playing a role in the cell adaptation under high temperatures.

The transcription system can also be affected by cold temperatures, for instance,
the transcription factor NusA is known to be involved in both termination and
antitermination of transcripts in E. coli, and it is highly expressed under lower
temperatures (10, 34). This gene is also up regulated at -2.5°C and 10°C in E. sibiricum.
Additionally, the RNA polymerase sigma 54 (rpoN) is up regulated and the RNA
polymerase sigma 70 (housekeeping sigma) is down regulated only at 25°C, suggesting
that sigma 54 may be responsible for the transcription of genes under cold or subzero

conditions.

142

Besides the transcription, the cells need to cope with the translation of all
transcripts produced, and for that the cells need to assure that all ribosome-associated
proteins required for the formation of the translation initiation complex are produced.
During cold-shock, several studies demonstrated that different genes are needed for this
initiation complex to be fully functional, such as DeaD-box RNA helicase, ribosome
binding factor A (RbfA), initiation factor 2 (IF-2) (33, 34) among several other ribosomal
proteins. E. sibiricum does up regulated RNA helicases at -2.5°C and 10°C that may
help unwind the RNA secondary structure for efficient translation at low temperature (9,
34). However, it is only at 25°C that IF-2, IF-3 and RbfA are significantly up regulated
in E. sibiricum (Table 5.2). Different temperatures, especially at 25°C and 39°C, also

affect the transcription of ribosomal proteins. The transcripts of ribosomal proteins L25

(RplY) are up regulated at 39°C and 25°C; while Rp18A (L7Ae family) is up regulated

only at 25°C. On the other hand, the ribosomal protein transcript of Rpm F is down

regulated at -2.5°C (Table 5.2). This change in ribosomal protein expression has been
observed as well in several other microorganisms, such as Lactobacillus plantarum (6),
Halobacterium sp. NRC-1 (43) and B. subtilis (42), among others. These proteins are
supposed to be the binding site for several of the factors involved in protein synthesis and
appeared to be essential for accurate translation (45).

After the mRNA is transcribed and translated it needs to be degraded. It has been
shown that during cold-shock, the RNA produced is degraded by a ‘cold-adapted’ RNA
degradosome that contains PNPase (13). E. sibiricum also increases its Pnp gene

expression with the decrease of temperature with a higher expression at -2.5°C, which

143

 

 

suggests that E. sibiricum may need the expression of this gene for growth in cold
temperature.

The proteins that come out of the translational machinery also needs to be folded
properly in order to be fully functional, and this can be an issue, especially under high
temperatures that can cause protein denaturation. E. sibiricum seems to overcome this
problem by inducing genes, at 39°C, from diverse heat shock proteins. These proteins are
homologous to B. subtilis and T. maritima class I heat-shock genes hrcA-gprE-dnaJ-dnaK
and GroEL-groES. In E. sibiricum 255-15, two operons are observed, the first contains
the genes Dnak, GrpE and HrcA, respectively, that have identical expression levels and
are in the reverse strand. The other contains Adk (Cpn60) and GroL also in the reverse
strand and presents a similar expression level to the first operon at 39°C. The gene for
DnaJ is also highly expressed at 39°C, but it is not part of the same operon that contains
DnaK, as seen in B. subtilis (41). Additionally, some genes encoding ATP-dependent
proteases ClpA and ClpP are also up regulated in E. coli and B. subtilis, under heat stress
(7, 30, 52), as well as in E. sibiricum at 39°C. Futherrnore, the genes Dna K, GroEs,
Cpn60 are downregulated at -2.5°C and start to gradually increase expression with the
increase in temperature and become highly expressed at 39°C.

Miscellaneous observations. Even thought at 10°C, E. sibiricum is fully motile (Figure
5.10), at -2.5°C, E. sibiricum appears to not be able to move by flagellar movement, since
all the Che genes in the Operon, as well as all the genes involved in flagella synthesis (all
the genes from F Lh, Fli and Flg operons) are down regulated (Table 5.2). The absence of
flagella was also observed by TEM (Figure 5.3). The subzero temperature makes the

media more viscous and it becomes close to freezing temperature, so the cell at this

144

 

temperature seems to be preparing for a frozen environment where flagella is no longer
necessary. Additionally, several genes for pilus assembly proteins (Pil genes) and type II

secretory pathway (Pul genes) are also down regulated at -2.5°C.

IQ

  

09‘
"‘ a

Figure 5.10. Negatively stained electron micrograph of E. sibiricum strain 255-15. Cell
with flagella at 10°C.

a?!

 

In conclusion, not too many differences in gene expression related to cold
adaptation are observed in E. sibiricum at the temperatures 10°C, 28°C and even at 4°C,
previously analyzed by proteomics (31). This work demonstrates that this microorganism
is constitutively adapted to cold temperatures since at stressful temperatures for
mesophiles, such as 4°C and 10°C, no genes related to temperature stress are significantly
expressed. Even though the growth rates change between 10°C and 28°C, it was
surprising to see very little difference in gene expression and no expression of genes
related to stress, especially because these two temperatures belong to two different phases
of the biphasic Arrhenius plot (Figure 5.5). It seems that the growth rate shift in the
Arrhenius plot does not have a strong significance on the microorganism physiology, at
least observable at the transcriptome level. On the other hand, at the extremities of the

Arrhenius profile, E. sibiricum undergoes several physiological adaptations very similar

145

to cold and heat shock responses previously studied in other organisms. Previous studies
suggested that these physiological or gene/protein expression changes were only
temporary during the initial shock (11, 44), while this study demonstrates that some of
the changes in gene expression are not transient but necessary in the longer term for the

cell survival and growth at these more extreme grth temperatures.

ACKNOWLEGMENTS

This research was supported by a cooperative agreement with NASA
Astrobiology Institute number NCC2-1274. The authors thank Dr. Robert Britton and
Peter Bergholz for the DNA microarray protocols and research discussions; and Dr.
Jizhong Zhou and Dr. Zhili He for designing and spotting the oligonucleotides onto

slides.

146

 

 

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systmes. Florida department of agriculture and consumer services.

Yura, T., and K. Nakahigashi. 1999. Regulation of the heat-shock response.
Current Opinion in Microbiology 2: 153-158.

151

EPILOGUE
RESEARCH SUMMARY AND FUTURE DIRECTIONS

152

SUMMARY

The aim of the present work was to explore the ecology, physiology and metabolism
of representative cold-adapted genera from Siberian Permafrost, to try to understand
the important traits that make microorganisms successful in a cold environment and
hence to disperse to other habitats than the Siberian permafrost. The results of this
work showed that Exiguobacterium spp. and Psychrobacter spp. had a patchy
distribution in temperate and tropical environments, but were ubiquitous in polar
regions. The diversity of these microorganisms seems to have a latitudinal diversity
gradient at the species level and their distribution in the environment seems to be
influenced by environmental physico-chemical factors, such as pH, salinity,
potassium (K+), cation exchange capacity (CBC) and the micronutrient copper (Cu).
The metabolism of these microorganisms correlates very well with physico-chemical
factors of the environment, which shows the value of understanding the physiology to
interpret the ecology of the microorganism.

The genome of E. sibiricum 255-15 was sequenced to better understand its
general metabolism and thermal adaptation to a wide range of growth temperatures.
At temperatures between 28°C to 4°C the cells do not show any significant
physiological change, but at the extremities of its grth range, i.e., 39°C and -2.5°C,
the microorganism undergoes several physiological changes to grow. Several
physiological changes previously believed to occur under shock (cold or heat) appear
necessary for sustained growth at subzero and high temperatures. Hence this present
study provided insights about ecology, physiology and metabolism of psychrotrophic

microorganisms.

153

FUTURE DIRECTIONS

Exiguobacterium sibiricum has been shown to be a very useful model for thermal-
adaption, however no genetic system is available for this microorganism to be able to test
the importance of several genes expressed under the differenttemperatures on the growth
of this microbe. Hence, developing a genetic system for Exiguobacterium would be of
great value for directly determining the role of some of the genes identified by
differential expression in temperature adaptation.

Secondly, recently we obtained approval for the genome sequencing of a
moderate thermophilic Exiguobacterium from a Yellowstone National Park thermal pool,
that will provide an excellent resource for comparative genomics and proteomics under
different temperatures.The genome sequence of both microorganisms will answer
questions, at the molecular level, about how the enzymes of these microorganisms differ
from one another.

A third question is whether Exiguobacterium spp. are present in older soils from
tropical and temperate regions. If present, how do they diverge from the ones fiom the
poles, as well as how diverse are the different species compared to the ones found in the
poles?

Finally, defining the best carbon sources and growth conditions for these
microorganisms will help understand of the role of these species in the microbial

community.

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