DNA Research Advance Access published November 25, 2013
DNA RESEARCH pp. 1–12, (2013)

doi:10.1093/dnares/dst050

Global Transcriptional Response to Heat Shock of the Legume Symbiont
Mesorhizobium loti MAFF303099 Comprises Extensive Gene
Downregulation
ANA Alexandre1,2, MARTA Laranjo1,2, and SOLANGE Oliveira1,*
ICAAM – Instituto de Ciencias Agrarias e Ambientais Mediterranicas (Laboratorio de Microbiologia do Solo),
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Universidade de Evora, Nucleo da Mitra, Ap. 94, 7002-554 Evora, Portugal1 and IIFA – Instituto de Investigac ao e
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Formacao Avanc ada, Universidade de Evora, Ap. 94, 7002-554 Evora, Portugal2
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*To whom correspondence should be addressed. Tel. þ351-266760878. Email: ismo@uevora.pt

(Received 19 August 2013; accepted 24 October 2013)

Abstract
Rhizobia, the bacterial legume symbionts able to fix atmospheric nitrogen inside root nodules, have to
survive in varied environmental conditions. The aim of this study was to analyse the transcriptional response
to heat shock of Mesorhizobium loti MAFF303099, a rhizobium with a large multipartite genome of 7.6 Mb
that nodulates the model legume Lotus japonicus. Using microarray analysis, extensive transcriptomic
changes were detected in response to heat shock: 30% of the protein-coding genes were differentially
expressed (2067 genes in the chromosome, 62 in pMLa and 57 in pMLb). The highest-induced genes are
in the same operon and code for two sHSP. Only one of the five groEL genes in MAFF303099 genome was
induced by heat shock. Unlike other prokaryotes, the transcriptional response of this Mesorhizobium
included the underexpression of an unusually large number of genes (72% of the differentially expressed
genes). This extensive downregulation of gene expression may be an important part of the heat shock response, as a way of reducing energetic costs under stress. To our knowledge, this study reports the heat
shock response of the largest prokaryote genome analysed so far, representing an important contribution
to understand the response of plant-interacting bacteria to challenging environmental conditions.
Key words: stress; rhizobia; microarrays; chaperone; sHSP

1.

Introduction

Rhizobia are soil bacteria able to colonize legume
roots and form nodules, where atmospheric nitrogen
is metabolized into compounds that can be used by
the plant. The impact of the biological nitrogen fixation
carried out by rhizobia in agriculture is both economic
and environmental. Rhizobia may reduce the use of
chemical N-fertilizers, which represent a production
cost reduction and at the same time a decrease in the
pollution resulting from N-fertilizers synthesis and
from soil nitrate lixiviation.1
Rhizobia typically have large genomes, which are
often composed by several replicons. These seem to

be common features of bacterial species that interact
with a host.2 This rhizobial trend to harbour a large accessory genome is probably related, not only to the
symbiosis itself (interacting with a host), but also to
the plasticity required to survive in complex and distinct
environments. As free-living bacteria, rhizobia have to
cope with changes in soil conditions and as plantsymbionts, rhizobia must overcome plant defence
mechanisms and adapt to the intracellular nodule environment. For all the above reasons, these bacteria
are particularly interesting to study stress response.
The most important consequences of heat stress at
the cellular level are protein denaturation and aggregation.3 These effects are common to other adverse

# The Author 2013. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/),
which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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Edited by Dr Naotake Ogasawara

Page 2 of 12

Heat Shock Response of Mesorhizobium loti MAFF303099
of a large number of sHSP is a common feature in rhizobia genomes.25 Some sHSP have a specific regulation
designated by repression of heat shock gene expression
(ROSE). ROSE element is a posttranscriptional regulation mechanism that consists in a conserved sequence
downstream to the promoter.26
The heat shock response has been extensively studied
in bacteria, however to our knowledge, only one rhizobia
strain was studied in terms of heat shock transcriptome,
namely S. meliloti 1021, a symbiont of Medicago spp.5,27
The strain analysed in the present report, Mesorhizobium
loti MAFF303099, is a rhizobium able to establish nitrogen-fixing symbiosis with Lotus species.28,29 M. loti
MAFF303099 genome comprises a large chromosome
(7 Mb) and two plasmids designated as pMLa (352 kb)
and pMLb (208 kb). A chromosomal symbiosis island
(610 kb) contains most genes involved in nodulation
and nitrogen fixation. A previous study showed that this
strain is tolerant to heat shock and cold conditions, and
grows well at pH 5.30
The aim of the present study is to characterize the
transcriptional response to heat shock in a resourceful
rhizobium with a large and complex genome. The analysis of the global transcriptional alterations following a
sudden exposure to high-temperature conditions in M.
loti MAFF303099 will contribute to a better understanding of the general stress response, in particular in
symbiotic bacteria with multiple replicons and large accessory genome.
2.

Materials and methods

2.1. RNA purification
Overnight cultures of M. loti MAFF303099 were
grown in YMB31 at 288C, to a final optical density of
0.3 (540 nm). A volume of 10 ml of bacterial culture
was used in each treatment: 30 min at control (288C)
and heat shock (488C) conditions. Cells were harvested
and total RNA was purified using RNeasy Mini Kit
(Qiagen). Contamination with DNA was removed by
DNase digestion (Roche), followed by RNA cleanup
using RNeasy Mini kit (Qiagen). Total RNA integrity
was checked using the RNA Nano kit and an Agilent
2100 Bioanalyser (Agilent Technologies), while RNA
quantification was performed using NanoDrop ND1000 (NanoDrop Technologies). RNA was prepared
from three independent cell cultures.
2.2. Microarray experiments
RNA processing as well as microarrays hybridization
and raw data extraction were a service provided by
Biocant Park—Genomics Unit (Portugal). In order to
enrich the RNA samples in mRNA, the MICROB
ExpressTM Kit (Ambion) was used to remove most of
the rRNA. mRNA was then amplified with the

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conditions, as for example oxidative stress, so the study
of the heat stress response is also relevant in understanding tolerance to other stresses.
The plasticity to respond to stressful conditions
involves rapid changes in gene expression. Alternative
sigma factors allow bacteria to rapidly redirect the
RNA polymerases pool to the set of genes that are
required to respond to a certain condition.4 Rhizobia
genomes typically harbour a large number of alternative sigma factors, including multiple copies of rpoH,
which encodes s32, the major sigma factor involved in
the heat shock response.5 s32 might be involved in response to other stresses as seen in Rhizobium etli,
where rpoH2 seems to be more related to oxidative
stress response.6 Furthermore, rhizobia with rpoH deletions may also be affected in their symbiotic pheno21% of the genes
type.6,7 The transcription of
induced in response to a temperature upshift are
rpoH1 dependent in Sinorhizobium meliloti and these
include chaperones, proteases and small heat shock
proteins (sHSP).5
Important chaperone systems, such as GroES-GroEL
and DnaK-DnaJ-GrpE, are s32-regulated in most alphaproteobacteria. Chaperones play a key role in the heat
shock response, as they are involved in promoting the
acquisition of the native conformation by proteins
that suffered denaturation and present the wrong
folding.8 The importance of chaperonins in defining
tolerance to temperature has been highlighted by
several studies in E. coli.9,10 A more recent study
showed that a high level of the GroESL system has a fundamental role in the evolution of heat tolerance.11
Some important reports on the functional analysis of
the multiple groESL operons in rhizobia have been published.12 – 14 Mutational studies showed that groESL
operons within the same genome are induced by different stimuli and that these genes are involved not only in
stress tolerance, but also in the nodulation and nitrogen
fixation processes.15 In Mesorhizobium spp., both dnaK
and groESL genes were reported to be transcriptionally
induced by a temperature upshift, especially in heat
tolerant isolates.16 In rhizobia, groESL operons are
often CIRCE (controlling inverted repeat of chaperone
expression) regulated, as already reported in
Bradyrhizobium japonicum, S. meliloti and Rhizobium
leguminosarum.13,17,18 CIRCE is a highly conserved
DNA sequence that serves as binding site of the repressor protein HrcA.19,20
Similar to the GroESL chaperonins, also the DnaKJ
system seems to be involved in both heat tolerance
and symbiosis phenotype.21 – 23 Regarding the cochaperone dnaJ, rhizobia mutants showed that both
stress tolerance and symbiotic performance are
affected.21,22,24
sHSP are mostly involved in preventing the irreversible aggregation of misfolded proteins. The presence

A. Alexandre et al.
MessageAmpTM II-Bacteria Kit (Ambion), with the incorporation of 5-(3-aminoallyl)-UTP (Ambion) for indirect labelling, which was carried out by the coupling of
fluorescent Cy3 to the amplified RNA (aRNA), following
the instructions of the Amino Allyl MessageAmpTM II
aRNA Amplification Kit (Ambion).
The 40K array for M. loti MAFF303099 (MYcroarray)
includes probes for 7231 genes ( 99% of the total
number of protein-coding genes) with five replicates
for each probe. Slide hybridization was carried out as
described by the microarray’s supplier, using the Gene
Expression Hybridization Kit (Agilent Technologies).
Data were acquired using a DNA Microarray B Scanner
(Agilent Technologies), with an intensity of 100% PTM
in the green channel.

2.4. Microarray data validation
Validation of microarray data was performed by realtime quantitative RT–PCR (qRT–PCR). cDNA was
obtained by reverse transcription using Maxima First
Strand cDNA Synthesis kit (Thermo Scientific) according to the manufacturer’s instructions. Primers
(Supplementary Table S1) were designed using Primer
Express 3.0 software (Applied Biosystems). Real-time
qRT– PCR reactions were prepared using 0.1 ng/ml of
template cDNA, SYBR Green PCR Master Mix and
0.3 mM of each primer. Amplifications were carried

out in a 7500 Real-time PCR System (Applied
Biosystems). Ct values for the target genes were normalized using the reference genes hisC, rpoA and sigA, which
showed no variation in the corresponding transcript
levels for the experimental conditions used (data not
shown).
3.

Results and discussion

3.1. Global transcriptional response
Analysis of the M. loti MAFF303099 transcriptome
allowed the identification of 2186 protein-coding
genes that were differentially expressed after heat
shock (out of 7231 genes analysed), with an average
false discovery rate of 1.5% (accession number
GSE43529). This indicates that the transcript levels of
30% of the protein-coding genes were altered by
this stress. The transcriptional response included a
much higher number of downregulated (1584) compared with the upregulated (602) genes (Fig. 1). The
unexpected larger proportion of downregulated genes
does not seem to be a feature of rhizobia, taking into
account the similar numbers of induced and repressed
genes reported for S. meliloti.5,27
To our knowledge, the present study reports the
largest prokaryote genome studied so far in terms of response to heat shock. To investigate the influence of
genome size in the global heat response, a comparison
of the transcriptional response to heat of prokaryotes
with different genome sizes was performed (Fig. 2).
Strain MAFF303099 shows an unusual proportion
of downregulated genes in response to heat shock
compared with several other bacteria and archaea
that, in general, show a similar number of genes
under- and overexpressed following a temperature
upshift (though different heat shock conditions are
compared). Despite the fact that diverse species with
distinct lifestyles and subjected to different heat shock
conditions are compared in Fig. 2, analysis of the transcriptomic data suggests a general trend of pronounced
increase in the number of downregulated genes with
genome size. One might speculate that many expendable genes are shutdown, so that the cellular machinery
can be more effective in the synthesis of the specific
functional response. Nevertheless, the extensive gene
downregulation is not particularly detected in the accessory genome that is presumably more dispensable.
Indeed, the symbiosis island shows dispersed underand overexpressed genes similar to the rest of the
chromosome (Fig. 3). Furthermore, some highly
induced genes are plasmid encoded, mainly in pMLb
(Fig. 4). This is somewhat unexpected since symbiosis
islands and plasmids are mobile elements in the
genome, known to be laterally transferred within soil
populations and thus less expected to carry genes

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2.3. Data analysis
The microarrays data were analysed using BRB
ArrayTools (version 4.2).32 The arrays were normalized
using the array median and genes that were differentially expressed following heat shock were identified using
MeV software.33 Genes were considered differentially
expressed for P  0.01 in the t-test.
Despite the recent update on the annotation of the
MAFF303099 genome released by NCBI (October
2012), all genes differentially expressed that were
annotated as ‘hypothetical protein’ were further analysed using Blast2GO software.34 This analysis included
Blast, Mapping and Annotation, and allowed further annotation of many genes. In order to assign the highest
number possible of genes to a clusters of orthologous
genes (COG) category, STRING 9.0 database (search
tool for the retrieval of interacting genes)35 was used.
MicrobesOnline Operon Predictions (www.microbesonline.org/operons/) was used for operon prediction.36 The identification of putative promoter
sequences was performed using BPROM-Prediction of
bacterial promoters software (www.softberry.com).
DNAPlotter37 was used to generate circular DNA maps
showing transcriptomics data.
Spearman’s coefficient was used to test for correlation between genome size and number of over- or
underexpressed genes (IBM SPSS Statistics, version 21).

Page 3 of 12

Page 4 of 12

Heat Shock Response of Mesorhizobium loti MAFF303099

Figure 2. Number of overexpressed (þ) and underexpressed (O)
genes resulting from the transcriptome studies of the response to
heat shock of 18 species of Bacteria and Archaea plotted against
their genome size. Trendlines are shown in grey for the number
of overexpressed genes (R 2 ¼ 0.35; Spearman’s r ¼ 0.583, P 
0.05) and in black for the number of underexpressed genes (R 2 ¼
0.69; Spearman’s r ¼ 0.608, P  0.01). From the smallest to the
largest genome size: Mycoplasma hyopneumoniae38; Tropheryma
whip-plei39; Rickettsia prowazekii40; Campylobacter jejuni 41; Streptococcus thermophilus42; Achaeoglobus fulgidus 43; Bifidobacterium
longum44; Xylella fastidiosa 45; Listeria monocytogenes46; Acidithiobacillus ferrooxidans 47; Corynebacterium glutamicum 48; Desulfovibrio vulgaris 49; Clostridium difficile 50; Escherichia coli 51;
Methanosarcina barkeri 52; Shewanella oneidensis 53; S. meliloti5; M.
loti (this study). The two rhizobia species are denoted in the
graphic. Note: in case of multiple heat shock transcriptome
datasets for the same species, the dataset with the largest number
of differentially expressed genes was chosen.

essential for stress survival. In addition, the set of 100
genes with highest M-values comprises 14 plasmid
encoded genes, while the 100 highly underexpressed
genes are all chromosomal (Supplementary Table S2).
The high number of underexpressed genes may
suggest that the heat shock response relies on a lowenergy transcriptional response. Accordingly, 40%
of the induced genes show a low increase in the transcriptional levels (M , 1). This low level of gene induction, commonly disregarded, may be important part of
cells response, as pointed before by Wren and
Conway.54
Analysis of the location of the differentially expressed
genes in each replicon shows an apparently random distribution of over- and underexpressed genes, with the
exception of an 200 kb-long region located in
1 000 000 – 1 200 000 (462 genes) where all the differentially expressed genes are downregulated (Fig. 3).
Both in the chromosome and plasmids, distribution of
the differentially expressed genes seems to be unrelated
to the DNA strand or GC content.
Real-time qRT– PCR was used to validate the microarray data. Genes were chosen based on M-values
from the microarrays results, in order to include
overexpressed, underexpressed and not differentially
expressed genes, as well as genes encoded in both
DNA strands and scattered in the chromosome. In
general, the results from the real-time qRT– PCR experiments are in agreement with the microarrays analysis
results (Table 1), with exception of the dnaK gene (discussed in the section ‘The DnaKJ chaperone system’).

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Figure 1. Microarrays analysis of M. loti MAFF303099 subjected to heat shock. M-values for the differentially expressed genes (P , 0.01)
obtained from the comparison between heat shock (488C) and control (288C) conditions. Genes with increased amount of mRNA
following the heat shock have positive M-values (overexpressed), while genes with decreased mRNA levels after heat shock show negative
M-values (underexpressed).

A. Alexandre et al.

Page 5 of 12

Figure 3. Circular plots of the chromosome and two plasmids
included in M. loti MAFF303099 genome showing, from outer
to inner rings: COG group for each gene; the %GC plot; and the
heat shock transcriptome data (M-values). The plasmids plots
include two additional outer rings displaying the genes encoded
in the plus strand (outermost ring) and minus strand. COG

colours: information storage and processing—blue; cellular
processes and signalling—green; metabolism—magenta; poorly
characterized—yellow; more than one COG category—brown; no
COG—light grey. Transcriptome data: overexpressed—black;
underexpressed—grey. %GC data: above average—dark red; below
average—orange. The symbiosis island (coordinates 4 644 792–
5 255 766)28 is marked in blue in the chromosome plot. This
figure appears in colour in the online version of DNA Research.

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Protein-coding genes can be grouped into COG,
according to their similarity in terms of domain architecture and function.55 The present study showed that temperature stress-induced changes in the expression of
genes belonging to all COG categories from the
MAFF303099 genome (Fig. 5). For all COG categories,
the percentage of underexpressed genes is higher than
that of overexpressed genes (Fig. 5 and Supplementary
Fig. S1). In addition to the fact that a high number of differentially expressed genes are not in a COG (1580
genes), there are also many poorly characterized genes
(‘S—function unknown’ and ‘R—general function prediction only’ categories) (Supplementary Fig. S1).
The COG category with the highest percentage of
overexpressed genes is ‘L—replication, recombination
and repair’ (9%). This COG category also shows the
lowest percentage of underexpressed genes (12%).
Nevertheless, the percentage of overexpressed genes is
between 7 and 8% in nine other categories, including
the COG category where chaperones and other heat
shock proteins are included (‘O—posttranslational
modification, protein turnover and chaperones’). This
suggests a balanced response in terms of gene induction
throughout the COG categories; yet, 13% of the overexpressed genes are not in a COG. Three categories include
a high percentage of underexpressed genes following a
heat shock, namely ‘D—cell cycle control, cell division,
chromosome partitioning’, ‘F—nucleotide transport
and metabolism’ and ‘N—cell motility’ (53, 48 and
44%, respectively). COG categories with a high number
of overexpressed genes are ‘K—transcription’, ‘G—carbohydrate transport and metabolism’ and ‘E—amino acid
transport and metabolism’ (Supplementary Fig. S1A).
On the other hand, COG categories E and G also show a
high number of underexpressed genes (Supplementary
Fig. S1B). This is consistent with other bacterial species
for which these two COG categories also showed a high
number of over- and underexpressed genes in response
to heat shock.46,48 According to Konstantinidis and
Tiedje,56 large genomes tend to have a disproportional
increase of genes belonging to COG ‘K—transcription’,
‘T—signal transduction mechanisms’ and ‘Q—secondary
metabolites biosynthesis, transport and catabolism’,
which could be expected to be the most underexpressed
categories in large genome bacteria, nevertheless that is
not observed in MAFF303099 (Fig. 5 and Supplementary Fig. S1B).

Page 6 of 12

Heat Shock Response of Mesorhizobium loti MAFF303099

Figure 4. Number and location of differentially expressed genes in
M. loti MAFF303099, following the heat shock.

Table 1. Microarrays data validation using real-time qRT– PCR
Gene

mll2386

–

14.6

6.6

mlr2394

groEL

11.9

5.8

mll1528

–

4.6

4.7

mll3429

clpB

7.0

2.9

mll3842

citZ

6.1

2.2

mlr5932

acdS

1.5

1.1

M-value
Real-time qRT– PCR

Microarrays

mll3873

–

20.6

21.9

mlr0883

gcvT

20.9

22.2

mlr6118

–

22.4

22.7

mll1546

ftsZ

23.4

23.7

mll6630

–

23.8

24.0

mlr2911

flgB

23.7

24.3

mll6578

fixK

24.0

25.1

mll6432

–

mll4757
mll4755
mlr7618

0.3

nde

dnaK

5.5

nde

dnaJ

20.2

nde

greA

0.9

nde

nde, not differentially expressed.

3.2. Small heat shock proteins
The two most heat shock-induced genes (mll2387
and mll2386 with M-values of 6.61 and 6.32, respectively) code for sHSP (Table 2). These genes are probably
co-transcribed, since a single putative promoter was
identified upstream mll2387 (predicted promoter:
-35 TTGACG and -10 ACTCATTCT). This particular
sHSP operon is likely to play an important role in the
heat shock response, since homologous genes were
also detected as the most overexpressed in S. meliloti following a less severe heat shock.5 Following a longer heat
exposure, these genes seem to be less overexpressed, yet
showing an induction of approximately 4-fold.27 The
homologous ibpAB are also the most-induced genes in
the heat shock response of E. coli.51 Western analysis of
protein extracts of several rhizobia species confirmed
an increase of the amount of sHPS with temperature

3.3. GroESL chaperone system
Similar to other heat shock related genes, rhizobia
genomes harbour several copies of the groESL operon,
usually with different regulation mechanisms and expression kinetics.15 M. loti MAFF303099 has four
groESL operons in the chromosome and one in pMLa.
From these five operons, only one appears to be
involved in heat shock response, namely the groEL
gene mlr2394, which was strongly overexpressed after
heat shock exposure (M ¼ 5.79). This groEL gene is
highly similar to groEL5 and groEL1 from S. meliloti
(87 and 83% amino acid identity, respectively), which
are the most heat shock-inducible copies in that
species.5,27
From what is known from other rhizobia genera, only
some groESL operons encoded in the same genome are
heat inducible and those can be regulated either by the
s32 or by CIRCE element.12,13,59 In the case of
MAFF303099, a CIRCE element was found upstream
all groESL operons (Supplementary Fig. S2B). The
same exact consensus sequence of this inverted repeat
is found in three operons and the remaining two
operons differ in only two positions. The overexpressed

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Locus tag

upshifts.25 As in many other bacteria species, in M. loti,
S. meliloti and E. coli, a ROSE element was identified upstream of these operons26 (Supplementary Fig. S2A).
Nevertheless, these sHSP genes were reported as rpoHdependent in S. meliloti,5 suggesting multiple regulation
mechanisms that may allow a dynamic stress response.
Rhizobia genomes carry a large number of sHSP.25
Strain MAFF303099 has eight genes identified as
sHSP, from which four were highly induced by heat
shock (mll2387, mll2386, mll9627 and mll3033),
two remained unaltered (mll2257 and mlr3192) and
two were underexpressed (mlr4720 and mlr4721).
sHSP can be divided into two classes in terms of sequence: class A includes sHSP similar to E. coli IbpAB,
while sHSP grouped in class B are more divergent in
terms of sequence.25 Gene mll2387 belongs to class
A, while mll2386 is more divergent and considered a
class B sHSP.57 According to Studer & Narberhaus58 it
is improbable that mll2386 and mll2387 could form
hetero-oligomers even if co-expressed, since in B. japonicum hetero-oligomers only occurred between sHSP
from the same class. All class A sHSP from M. loti
MAFF303099 (mll2387, mll3033, mlr3192 and
mll9627-plasmid encoded) showed a ROSE element
downstream to the promoter, which would confer
high-temperature sensitivity to the transcription of
these genes26 (Supplementary Fig. S2A). However,
one of these sHSP was not overexpressed following the
heat shock tested (mll3192-hspH), despite the fact
that its B. japonicum homolog, also regulated by a
ROSE element, is heat inducible.25

A. Alexandre et al.

Page 7 of 12

groEL gene belongs to one of the operons regulated by a
slightly divergent CIRCE element. Our results suggest
that the presence of a CIRCE consensus sequence does
not ensure a highly efficient induction under heat
stress conditions. A similar situation was detected in R.
leguminosarum, where a putative CIRCE element was
found upstream of all three groESL operons, and
further analysis of this regulation mechanism showed
that the most heat-inducible operon was indeed
CIRCE regulated, but a second operon, less induced by
heat, was not affected by CIRCE deletion or hrcA knockout.17 This second operon was rpoH regulated, suggesting an overlapping of regulation mechanisms.17
Despite the high M-value detected for the groEL
mlr2394, the expression of the groES gene in the same
operon (mlr2393) following the heat shock remained
unaltered. Similarly, in S. meliloti, the gene SMb22023
(groES5) was not induced by heat shock, despite the
high induction of the corresponding groEL5 gene
(SMb21566).5,27 No promoter could be identified in
the 59 bp groES –groEL intergenic space using BProm,
so a bicistronic mRNA should be synthesized. A posttranscriptional cleavage could explain why only the transcript of the second gene in the operon is highly
abundant. A cleavage event occurs in the groESL transcript of Agrobacterium tumefaciens, explaining why the
transcript corresponding to groEL alone is the abundant

mRNA detected after heat shock.60 Analysing the intergenic space in the MAFF303099 groES –groEL operon,
using the ‘KineFold Web Server’,61 a stem-loop structure
was found, though weaker than the one described to
undergo cleavage in A. tumefaciens (data not shown).
GroES – GroEL complexes comprising proteins encoded
by different operons tend to be less efficient than
the chaperonins complexes encoded by the same
operon.62 However, the predominant GroES – GroEL
complex consists of a single 10 kDa-heptameric ring
(GroES) plus two rings of seven 60 kDa-monomers
(GroEL), so the ratio between the two is 1:2, which is consistent with a lower groES transcription.

3.4. DnaKJ chaperone system
The role of the DnaKJ chaperone system in stress response is well known in other bacteria; however, few
studies address these heat shock proteins in rhizobia. In
the present study, dnaK (mll4757) and the co-chaperone dnaJ (mll4755) were not found to be significantly
heat shock induced. Nevertheless, the real-time qRT–
PCR results (Table 1) show that dnaK was induced
by heat shock, agreeing with previous studies in
Mesorhizobium.16 Approximately, 2-fold induction of
the dnaK gene was detected in S. meliloti cells exposed
to 408C for 30 min,5 while no induction was reported

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Figure 5. Percentage of genes from each COG category overexpressed and underexpressed after the heat shock. Genes not in a COG are also
shown. The number of genes included in each category is shown at the right end of the graphic.

Page 8 of 12

Heat Shock Response of Mesorhizobium loti MAFF303099
Table 2. Overexpressed genes following the heat shock, identified by microarray analysis.
COG categorya

Gene description

M-value

Chr

O

sHSP

6.61

mll2387

Chr

O

sHSP

6.32

mll3685

Chr

–

PRC-barrel domain-containing protein

6.08

msl2054

Chr

–

Hypothetical protein

5.84

mll1959

Chr

–

BA14k family protein

5.82

Locus tag

Replicon

mll2386

mlr2394

Chr

O

Molecular chaperone-GroEL

5.79

mll7465

Chr

G

ABC transporter permease

5.79

msr9689

pMLb

–

Hypothetical protein

5.62

msr8048

Chr

–

Hypothetical protein

5.61

msl2390

Chr

E

Usg family protein

5.54

Chr

–

Hypothetical protein

5.49

mlr4836

Chr

HC

Monooxygenase FAD-binding protein

5.27

mlr2158

Chr

SR

Metallo-beta-lactamase superfamily protein

5.25

mlr2234

Chr

–

Hypothetical protein

5.25

mll9627

pMLb

O

sHSP

5.23

mlr2160

Chr

R

Transporter component

5.17

mlr5153

Chr

–

Transmembrane protein

5.09

mll9357

pMLa

S

Domain-containing protein

5.03

mll3694

Chr

T

Transcriptional regulator

4.98

mll1952

Chr

C

Norsolorinic acid reductase

4.98

mll4827

Chr

J

Endoribonuclease L-PSP

4.89

mlr2159

Chr

K

Transcriptional regulator

4.86

msr8615

Chr

R

Transporter component

4.82

msl3831

Chr

–

Conserved hypothetical transmembrane protein

4.79

mlr9581

pMLb

–

PRC-barrel protein

4.78

mll4607

Chr

S

Ku protein

4.66

mll1528

Chr

S

Small integral membrane protein

4.65

mlr8230

Chr

K

Transcriptional regulator

4.56

mlr0408

Chr

K

Transmembrane anti-sigma factor

4.56

msr2497

Chr

S

Hypothetical protein

4.47

mll8293

Chr

–

Hypothetical protein

4.38

msl2212

Chr

K

Family transcriptional regulator

4.36

msl7604

Chr

–

Hypothetical protein

4.31

msl7943

Chr

–

Hypothetical protein

4.28

msl9358

pMLa

S

Transcription factor

4.27

mlr2125

Chr

–

Hypothetical protein

4.27

mlr3707

Chr

–

Hypothetical protein

4.25

mlr0407

Chr

K

RNA polymerase sigma factor

4.16

mll3692

Chr

–

Hypothetical protein

4.14

msr8675

Chr

S

Hypothetical protein

4.11

mlr3233

Chr

N

Host attachment protein

4.07

msr4317

Chr

–

Hypothetical protein

4.04

mll2066

Chr

D

Mobile mystery protein b

4.02

mll6953

Chr

R

Domain-containing protein

4.02

mll6858

Chr

RIQ

Short chain dehydrogenase

3.98

mlr1797

Chr

S

Conserved domain protein

3.91
Continued

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msl1808

A. Alexandre et al.

Page 9 of 12

Table 2. Continued
COG categorya

Gene description

M-value

Chr

C

Luciferase-like protein

3.91

mll2211

Chr

C

Morphinone reductase

3.89

msl6857

Chr

R

Hypothetical protein

3.88

mll8179

Chr

S

Family protein

3.83

Locus tag

Replicon

mll3445

The 50 genes with the highest M-values are shown. Gene descriptions shown in bold resulted from sequence analysis using
Blast2GO software.
a
COG category letters according to NCBI functional categories (http://www.ncbi.nlm.nih.gov/COG/grace/fiew.cgi).

3.5. Sigma factors
Rhizobia usually have multiple copies of genes encoding the same sigma factors, for example rpoH and rpoE.
The M. loti MAFF303099 genome includes 25 putative
sigma factors, from which four were induced by heat
shock (mlr0407, mll3697, mll8140 and mlr3807).
None of these sigma factor-encoding genes is completely annotated; nevertheless, BLAST analysis
showed that loci mlr0407 (highly induced) and
mll8140 are similar to both s70 and s24, and
mlr3807 is more similar to s24, while mll3697 shows
high similarity to the S. meliloti rpoE2 gene (76%).
Sauviac and collaborators27 suggested RpoE2 as the
major global regulator of stress response in S. meliloti,
despite the fact that no phenotype change was detected
in the rpoE2 mutant. Our results are consistent with

that suggestion, since mll3697 is overexpressed in
heat shock conditions with an M-value of 2.4. The
gene mll2869 encoding s70 was found to be underexpressed following heat shock conditions, which may
contribute to the extensive downregulation detected
in MAFF303099 transcriptional response.
Sigma factors typically related to the heat shock response, as s32 (rpoH) and s24 (rpoE) that probably are
encoded by mlr3741 and mlr8088 in MAFF303099,
were not affected at the transcriptional level by the
heat shock conditions applied. The gene rpoH2
(mlr3862) was also not induced in the conditions
´nez-Salazar and cowused in this study. Similarly, Martı
orkers6 reported that none of the rpoH genes were
induced by heat shock in R. etli. Nevertheless, rpoH
mutants are usually impaired in their stress tolerance
phenotype, as is the case for S. meliloti and R. etli.6,66
rpoH1 controls the expression of 21% of the heat
shock-induced genes in S. meliloti and is also related
to oxidative stress response, while rpoH2 seems to
play a minor role in the heat shock response and is
more involved in osmotic tolerance.5,6
In E. coli, the rpoH regulation seems to be more at the
protein level than at the transcriptional level. This
control hypothesis is known as the ‘unfolded protein titration model’ and involves the most important chaperone systems: under normal growth conditions, s32
binds to DnaKJ and GroESL so it becomes unavailable
for RNA polymerase binding; under heat stress, misfolded proteins have higher affinity for chaperone
systems and s32 would be released.67 This posttranslational regulation has not been investigated in rhizobia,
nevertheless the fact that no rpoH induction was
detected under heat stress conditions is consistent
with the proposed model.
3.6. Nodulation and nitrogen fixation genes
Some of the genes involved in nodulation and nitrogen
fixation were detected to be differentially expressed
after heat shock. Several fix genes showed severe underexpression, especially fixK, which encodes a transcriptional regulator and was the most underexpressed gene
following the heat stress (Supplementary Table S2).

Downloaded from http://dnaresearch.oxfordjournals.org/ by guest on January 24, 2014

for a shorter heat shock (428C for 15 min).27 In the
microarray analysis, the changes in expression levels of
the dnaK gene were considered not statistically significant due to discrepancies among replicates.
It was reported for several rhizobia species that dnaJ
deletions cause reduced growth at high temperatures;21,24 however, no transcriptional activation following a heat shock was detected in the present study
or in other studies with S. meliloti.5,27 Similar to our
results, no induction of grpE was reported for S. meliloti
by Sauviac and coworkers,27 while a different study
showed induction of grpE by heat shock.5
Another heat shock protein that has a close interaction with the DnaKJ system is ClpB. The clpB gene
(mll3429) was found to be overexpressed in the
present study, with an M-value of 2.93. The clpB gene
was already seen to be upregulated following a heat
shock in S. meliloti 5,27 and the importance of ClpB in
rhizobia stress response, especially to heat shock, was
also previously reported.63 Similar to E. coli, the knockout of the clpB gene in Mesorhizobium ciceri led to an inability to endure high temperatures. Furthermore, in M.
ciceri the symbiotic performance was also negatively
affected.63,64 These results are consistent with the
ClpB role in denatured protein disaggregation, namely
by its cooperation with the DnaKJ system.65

Page 10 of 12

Heat Shock Response of Mesorhizobium loti MAFF303099

3.7. Other heat shock-inducible genes
Among the 50 genes with the highest M-values
(Table 2), there are five transcriptional regulators, one
sigma factor and one anti-sigma factor, which indicates
that heat shock response is a complex system with relevant control at the transcriptional level.
Additional analysis of all hypothetical proteins differentially expressed performed in this study, allowed
further characterization of many genes, for example
mll4607, which is now annotated as Ku protein
(Table 2). Together with LigD this protein is involved
in DNA repair, namely in the repair of non-homologous
end-joining of double-strand DNA.70 Unlike other bacteria, rhizobial genomes encode multiple copies of this
Ku/LigD system, which has been further studied in S.
meliloti.71 Although none of the ku homologues is
required for the symbiosis establishment, this DNA
repair system is active in both free-living cells and bacteroids.71 From the four ku homologs in the
MAFF303099 genome, three are induced by heat
shock (mll4607, mlr9624 and mlr9623), as well as
one of the three ligD homologues (mll9625). Until recently, double-stranded DNA breaks (DSB) were not
thought to be a consequence of heat shock; however,
a recent study, using eukaryotic cells, showed that
heat shock may in fact induce DSB on certain phases
of the cell cycle.72 It is tempting to agree with the

suggestion from Kobayashi and coworkers71 that
these systems do have some role under stress conditions, such as heat shock.
Altogether our results suggest that in a large bacterial
genome, the extensive gene downregulation may be an
important part of the heat shock response. Although
the present study has contributed to further knowledge
on rhizobia stress response, future studies are required
to understand the role of individual genes and the
mechanisms regulating these molecular responses.
Acknowledgements: We thank Ana Catarina Gomes
from Biocant Park (Portugal) for her assistance with
microarray data analysis and Owen Woody from the
University of Waterloo (Canada) for his help with the
DNAplotter software.
Supplementary data: Supplementary Data are
available at www.dnaresearch.oxfordjournals.org.
Funding
ˆ
This work was funded by Fundacao para a Ciencia e a
¸˜
Tecnologia (FCT), including the research projects
FCOMP-01-0124-FEDER-007091,PTDC/BIA-EVF/4158/
2012 and the strategic project PEst-C/AGR/UI0115/
2011, that include FEDER funds through the Operational
Programme for Com-petitiveness Factors—COMPETE
and National funds. A. A. and M. L. acknowledge postdoctoral fellowships from FCT (SFRH/BPD/73243/2010
and SFRH/BPD/27008/2006).
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Heat Shock Response of Mesorhizobium loti MAFF303099