Genome-wide expression analysis in Corynebacteriumglutamicum using DNA microarrays
Volker F. Wendisch *
Institute of Biotechnology, 1 Research Center Julich, D-52428 Julich, Germany
Received 20 November 2002; received in revised form 20 January 2003; accepted 11 March 2003
Abstract
DNA microarray technology has become an important research tool for microbiology and biotechnology as it allows
for comprehensive DNA and RNA analyses to characterize genetic diversity and gene expression in a genome-wide
manner. DNA microarrays have been applied extensively to study the biology of many bacteria including
Mycobacterium tuberculosis , but only recently have they been used for the related high-GC Gram-positive
Corynebacterium glutamicum , which is widely used for biotechnological amino acid production. Besides the design
and generation of microarrays as well as their use in hybridization experiments and subsequent data analysis, recent
applications of DNA microarray technology in C. glutamicum including the characterization of ribose-specific gene
expression and the valine stress response will be described. Emerging perspectives of functional genomics to enlarge our
insight into fundamental biology of C. glutamicum and their impact on applied biotechnology will be discussed.
# 2003 Elsevier B.V. All rights reserved.
Keywords: Genome-wide gene expression analysis; DNA chips; DNA microarrays; Cluster analysis; Genome map image; Global
regulatory mechanisms; Corynebacterium ; Mycobacterium
1. Introduction
C. glutamicum was isolated as a natural L-
glutamate producer and high-producing strains
for the production of L-glutamate, but also of L-
lysine and other amino acids, have been generated
through classical mutation and selection (Sahm et
al., 1996). With the advent of molecular biology
methods for this organism, targeted metabolic
pathway engineering became possible. Besides the
molecular elucidation of amino acid biosynthesis
and central metabolic pathways on the genetic and
biochemical level, carbon flux analyses have al-
lowed to gain a quantitative understanding of the
corynebacterial central metabolism. Furthermore,
these studies have led to the rational improvement
of C. glutamicum strains by ‘metabolic design’ for
the production of D-pantothenate, L-isoleucine, L-
valine, L-threonine and L-lysine (Sahm et al.,
2000). After the determination of the C. glutami-
cum genome sequence (Tauch et al., 2002), genetic
methods can now be performed on the basis of the
whole genome information. Genome-wide gene
expression analyses with DNA microarrays allow* Tel.: �/49-2461-615169; fax: �/49-2461-612710.
E-mail address: [email protected] (V.F. Wendisch).
Journal of Biotechnology 104 (2003) 273�/285
www.elsevier.com/locate/jbiotec
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doi:10.1016/S0168-1656(03)00147-0
to unravel global regulatory mechanisms and holdthe promise for targeted biotechnological strain
improvement off the known pathways of central
metabolism and amino acid biosynthesis.
This review focuses on the applications of
whole-genome DNA microarrays for genome-
wide expression analysis (transcriptomics) and
comparative genomics of C. glutamicum and,
when useful, refers to similar analyses of anothermember of the Corynebacterianeae , M. tuberculo-
sis . On a gene by gene basis, gene expression
analyses in C. glutamicum have been performed
previously on the transcriptional and RNA level
using Northern blotting (e.g. Follettie et al., 1988;
Schwinde et al., 1993; Mateos et al., 1994), primer
extension (e.g. Schwinde et al., 1993; Mateos et al.,
1994; Patek et al., 1996) and plasmid-borne orchromosomal transcriptional reporter gene fusions
(e.g. Eikmanns et al., 1991; Vasicova et al., 1998).
The analysis of 33 promoters from C. glutamicum
revealed conserved sequences centred about 10 bp
(TA.aaT) and 35 bp (ttGcca) upstream of the
transcriptional start site with the consensus hex-
amer of the �/35 region being much less conserved
than in Escherichia coli , Bacillus subtilis , Lactoba-
cilli and Streptococci (Patek et al., 1996). The
availability of the genome-based methods for C.
glutamicum will allow to refine this analysis,
taking into account several identified RNA poly-
merase sigma factors. Similarly, a combination of
a bioinformatic approach to predict all putative
operons based on a detailed analysis of the genome
sequence with an experimental approach based ongene expression analysis using DNA microarrays
for their verification, as recently performed for E.
coli (Sabatti et al., 2002), will amend our under-
standing of the basic mechanisms of gene expres-
sion in C. glutamicum .
2. Construction and use of whole-genome C.glutamicum DNA microarrays
For the analysis of genome-wide expression
patterns, several techniques are currently in use:
DNA microarrays (Schena et al., 1995; Lockhart
et al., 1996), proteome analyses, which also allow
to detect post-translational modifications of pro-
teins and which are established for C. glutamicum
(Hermann et al., 2001; Schaffer et al., 2001),
differential display (Liang and Pardee, 1992),
SAGE (Velculescu et al., 1995) and MPSS (Bren-
ner et al., 2000). The latter two methods involve
cloning and sequencing of expressed RNAs
whereas DNA microarray experiments rely on
rapid nucleic acid hybridization. It should be
noted that different RNA levels indicate differen-tial gene expression, but it remains to be deter-
mined whether they are due to transcriptional
control or regulated RNA degradation. DNA
microarrays are based either on single-stranded
DNA oligonucleotides (Lockhart et al., 1996) or
on double-stranded DNA fragments (Schena et
al., 1995) generated by PCR amplification of each
gene of an organism (reviewed in Ye et al., 2001;van Hal et al., 2000; Rhodius et al., 2002) or in
rare cases of inserts from a random DNA library
(Hayward et al., 2000). Whereas for M. tubercu-
losis , both DNA microarray types are in use (e.g.
Wilson et al., 1999; Salamon et al., 2000), so far
genome-wide expression analysis in C. glutamicum
was performed only using DNA microarrays with
double-stranded DNA (Muffler et al., 2002; Langeet al., 2003; Gerstmeir et al., 2003; Wendisch,
unpublished results).
2.1. PCR-product-based whole-genome
microarrays of C. glutamicum
The generation of PCR-product-based whole-
genome microarrays and their use for gene expres-
sion analysis was pioneered for Saccharomyces
cerevisiae by the labs of Pat Brown and David
Botstein (Schena et al., 1995; DeRisi et al., 1997;
Ye et al., 2001). Subsequently, genome-wide ex-
pression analysis was established for the model
bacteria E. coli (e.g. Richmond et al., 1999;
Khodursky et al., 2000; Zimmer et al., 2000; Wei
et al., 2001) and B. subtilis (e.g. Fawcett et al.,
2000), for a member of the Corynebacterianeae ,M. tuberculosis (Wilson et al., 1999; Behr et al.,
1999) and several other bacteria (reviewed in Ye et
al., 2001). For many organisms including C.
glutamicum , preliminary tests of parallel transcript
profiling of few genes have been performed
(Schena et al., 1995; de Saizieu et al., 1998;
V.F. Wendisch / Journal of Biotechnology 104 (2003) 273�/285274
Hayashi et al., 2002; Loos et al., 2001). Now,whole-genome DNA microarrays allow to perform
genome-wide gene expression analysis as well as
comparative genomics experiments in C. glutami-
cum (Muffler et al., 2002; Lange et al., 2003; Ishige
et al., 2003; Gerstmeir et al., 2003). The C.
glutamicum whole-genome DNA microarrays
used in the author’s laboratory comprise 3673
PCR products covering 2860 of the 2994 genes(506 in duplicate) described for the genome
according to NCBI NC003450 and 284 further
putative coding sequences (23 in duplicate). Ad-
ditionally, 100 spots of C. glutamicum genomic
DNA are present as normalization controls and 16
spots of l-DNA, 16 spots of E. coli and 1 spot of
the E. coli aceK gene as negative controls.
2.2. RNA isolation and fluorescent labelling, whole-
genome DNA microarray hybridization and
fluorescence scanning
In general, only minor modifications of methods
that had been developed for DNA microarray
analysis of other microorganisms were needed to
transfer this technique to C. glutamicum . Typi-
cally, total RNA of sufficient quality and quantitycan be purified after mechanical disruption of C.
glutamicum cells (Lange et al., 2003). Quenching
to minimize RNA degradation, a problem much
more pronounced in bacteria than in eucarya, can
be achieved by rapid cooling or by chemical
treatment, e.g. with azide (Lange et al., 2003;
Ishige et al., 2003; Gerstmeir et al., 2003). A
protocol for the selective isolation and purificationof bacterial mRNA is also available (Wendisch et
al., 2001). RNA can be labelled green- or red-
fluorescently in a reverse transcription reaction
primed with random dNTP hexamers, either
directly using e.g. Cy3-dUTP or Cy5-dUTP or
indirectly using aminoallyl-dUTP followed by
reacting the modified cDNA with monoreactive
Cy3- or Cy5-dyes. After labelled cDNAs arepurified from dNTPs not incorporated, hybridiza-
tion to the whole-genome DNA microarrays is
performed in humid chambers. Hybridization
periods may vary between 5 and 18 h and stringent
washing is performed under low salt conditions.
Several commercial fluorescence scanners can be
used for determining fluorescence at 635 and 532nm with a resolution between 5 and 20 mm. The
recorded fluorograms can be exported to a number
of file formats containing the fluorescence infor-
mation of both fluorophores for each pixel.
2.3. Storage and analysis of raw data from C.
glutamicum whole-genome DNA microarray
hybridizations
Whole-genome DNA microarray experiments
generate many data and hence the need to store
primary data rather than derived values in a
searchable format. Several commercial (e.g. Axon
Acuity, Lion arraySCOUT, Silicon Genetics
GeneSpring) and academic solutions (e.g. Stanford
Microarray Database, EcoReg) are available. Fig.
1 summarizes some features of such a database (T.Polen, unpublished). All relevant experimental
information (e.g. strain, media, pre-culture condi-
tions, growth curve, number of generations for
which a balanced condition has been maintained
or time point of harvest after a particular stimulus,
etc.) for each experiment are stored in an accom-
panying data table. Raw primary data including
position on the array, number of pixels represent-ing the spot or the local background, etc., and
derived data such as fluorescence ratios are stored
in a relational database. The fluorogram of the
DNA microarray hybridization (Fig. 1A) is stored
and hybridization spots on all visual representa-
tions are linked to the raw data and further
available information about that gene in a web-
based manner (Fig. 1B). Genome map images(Zimmer et al., 2000) representing hybridization
signals of each gene arranged according to the
position on the genome (Fig. 1C) can also be
generated. To compare expression of a particular
gene throughout the experimental conditions re-
presented in the database, expression changes are
summarized, grouped (B/0.5; B/0.66 and �/0.5;
between 0.66 and 1.5; �/1.5 and B/2; �/2) andgraphically represented (Fig. 1D).
Relative RNA levels of a gene are calculated
from the net fluorescence intensities obtained in a
DNA microarray hybridization experiment. It is
important that relative RNA levels are calculated
only from fluorescence signals clearly exceeding
V.F. Wendisch / Journal of Biotechnology 104 (2003) 273�/285 275
background noise and when neither fluorescence
signal shows a signal-to-noise-ratio greater than a
defined threshold, e.g. threefold, the signals should
be considered too low to derive a relative RNA
level for that gene. In fluorescence images scanned
at high resolution (5 or 10 mm), hybridization spots
are represented typically by at least 100 pixels.
Calculations taking the variance of pixel informa-
Fig. 1. Example of a relational database for storage and analysis of whole-genome DNA microarray data based on the freely available
database management system mySQL. Fluorogram of a genome-wide expression analysis using a whole genome C. glutamicum DNA
microarray (A) linked to information on raw data as well as background information (B). Relative RNA levels of operons can be
visualized as a genome map image (C). Expression data of individual genes can be searched in all experiments, grouped (ratios B/0.5 or
between 0.5 and 0.66 or between 0.66 and 1.5 or between 1.5 and 2 or �/2) and summarized graphically (D).
V.F. Wendisch / Journal of Biotechnology 104 (2003) 273�/285276
tion for hybridization spots into account, such asthe ratio of medians, offer robust means to
calculate relative RNA levels from hybridization
images.
2.4. Bioinformatic tools
Genome-wide expression analyses pose the
challenge to carefully control all experimental
parameters starting from the pre-cultivation tothe final data analysis. The problem of noise in
such analyses is obvious and needs to be addressed
for interpretation of the DNA microarray results.
Several statistical approaches have been estab-
lished to identify statistically significant gene
expression changes (reviewed, e.g. in Pan, 2002).
Among those, the two-sample t-test has been used
to identify significant gene expression changes ingenome-wide expression analysis (e.g. Arfin et al.,
2000; Lehnen et al., 2002; Polen et al., 2003). It is
clearly a prerequisite to include more than two
independent replicates in a genome-wide expres-
sion analysis and these replicates have to be
obtained from independent cultivations to take
biological as well as experimental noise into
account.A versatile tool to identify and visualize gen-
ome-wide expression patterns of many different
experimental conditions was introduced by Eisen
et al. (1998). By hierarchical clustering of gene
expression data, genes as well as experimental
conditions are sorted according to similarities in
gene expression patterns. This and similar analyses
(reviewed in Tamames et al., 2002; Rhodius et al.,2002) are well suited to identify operons based on
experimentally determined expression (for E. coli ,
Sabatti et al., 2002) as can be demonstrated by
hierarchical clustering of a set of 220 C. glutami-
cum whole-genome DNA microarray experiments
from our lab (Fig. 2). Whereas none of the
experimental conditions aimed at the analysis of
the regulation of arginine biosynthesis (specifi-cally, neither experiments using arginine auxo-
trophic mutants nor experiments using arginine as
nitrogen or carbon source or other medium
component were included), the subtle gene expres-
sion changes of the putative argCJBDFRGH
operon revealed that expression of each gene
within this group is more similar to each otherthan to any other gene (Fig. 2A). It becomes
evident as well that some operons physically
distant on the genome are exhibiting very similar
expression patterns and form syn-expression
groups (Niehrs and Pollet, 1999). It remains to
be shown whether syn-expression groups, such as
that comprising the ctaE-qcrCAB (Niebisch and
Bott, 2001) and sdhCAB operons (Fig. 2B) areregulated by one common regulator and thus form
a regulon or whether they respond to one stimulus
and thus form a stimulon. With the help of pattern
recognition as realized by clustering global gene
expression data, one can efficiently deduce hy-
potheses on global gene regulation in bacteria such
as C. glutamicum and help to plan experiments
aimed at their verification (or falsification).
3. Applications and perspectives
3.1. Comparative genomics or genomotyping of C.
glutamicum strains
Comparative genomic studies aim at the identi-
fication of differences between genomes and canbe carried out by hybridization of labelled genomic
DNA to DNA microarrays. Oligonucleotide DNA
microarrays can be used to detect genomic differ-
ences down to the single nucleotide level, i.e. the
identification of SNPs (Hacia et al., 1996). One of
the first examples of DNA microarray analysis in
the Corynebacterianeae was the comparative geno-
mics study of Behr et al. (1999) in M. tuberculosis
which led to the identification of genome differ-
ences of the different Bacille Calmette-Guerin
(BCG) strains used for vaccination throughout
the world. This study demonstrated that DNA
microarrays based on PCR products are efficient
tools for the detection of gene deletions or
amplifications although they offer only a resolu-
tion of about 1 kb. Similarly, C. glutamicum
whole-genome DNA microarrays which are based
on PCR products are efficient for genomotyping.
As shown in Fig. 3, using C. glutamicum whole-
genome DNA microarrays, it is possible to detect
chromosomal rearrangements such as deletions at
the gene level. In a comparison of genomic DNA
V.F. Wendisch / Journal of Biotechnology 104 (2003) 273�/285 277
from leuA deletion strains and their respective
isogenic parent strains (WT, WTDleuA , MH20-
22B and MH20-22BDleuA ), the absence or pre-
sence of the leuA gene was detected with two leuA
PCR products whereas no false-positive signal was
detected (Fig. 3). Due to unspecific hybridization,
the ratios of hybridization signals are smaller than
theoretically expected (Behr et al., 1999). In future
applications, it will be important to identify
genomic differences between amino acid-produ-
cing strains obtained by repeated mutageneses and
selections and the respective wild-type strain. The
deletions or amplifications identified in such a
manner will be tested individually regarding their
relevance for amino acid production. Introduction
of these mutations into the wild-type strain, alone
and in combination, should give rise to well-
defined, high-level amino acid-producing strains.
This approach, also named ‘genome breeding’ or
‘inverse metabolic engineering’, recently led to a
first success (Ohnishi et al., 2002) when the
combinatory introduction of a limited number of
previously known, beneficial mutations present
only in L-lysine production strains into the
Fig. 2. Hierarchical cluster analysis of 220 global gene expression experiments using whole-genome C. glutamicum DNA microarrays.
Two details show co-expression of the putative argCJBDFRGH operon or cluster (A) and of a syn-expression group comprising two
operons separated by about 1.4 Mbp: the succinate dehydrogenase operon sdhCAB with an adjacent ORF and the ctaE-qcrCAB
operon encoding subunit III of cytochrome aa3 and the three subunits of the cytochrome bc1 complex (B). The cluster analysis was
performed on 736 genes that were reliably detected in more than 180 of the 220 experiments and that in one or more of them showed an
at least twofold RNA level change. Genes referred to by gene name or Ncgl number of NC003450 are in lines and experiments in
columns. The scale depicts the color coding for relative RNA levels whereas grey color represents signals too low to deduce a relative
RNA level.
V.F. Wendisch / Journal of Biotechnology 104 (2003) 273�/285278
C. glutamicum wild-type strain endowed the re-
sulting defined strain with the capability to pro-
duce about 100 g l�1L-lysine.
Whole-genome DNA microarrays can also be
used to determine which genes confer beneficial or
detrimental traits, e.g. growth (dis)advantages or
improved/decreased product yields. This form of
parallel gene-trait mapping consists of a genome-
altering step to generate a pool of mutants, e.g. by
deletion mutagenesis or by transforming a strain
with a genomic library, followed by an enrichment
of a subpopulation containing the trait conferring
gene(s) by selection and using DNA microarrays
to identify the enriched or counterselected genes
(Cho et al., 1998). This method can readily be
applied, e.g. for the identification of conditionally
Fig. 3. Comparative genomics of C. glutamicum strains. The ratios of hybridization signals in DNA microarray experiments
comparing genomic DNA from C. glutamicum ATCC 13032 (WT) to WTDleuA (A) and from MH20-22B to MH20-22BDleuA (B) are
shown according to the respective gene numbers in NCBI NC003450. The dotted lines indicate ratios of hybridization signals of 2 and
1/2, respectively. The absence or presence of the leuA gene was detected for both isogenic strain pairs with both the two leuA PCR
products that cover different parts of the leuA gene.
V.F. Wendisch / Journal of Biotechnology 104 (2003) 273�/285 279
essential genes (Sassetti et al., 2001) or genesconferring antibiotic resistance (Gill et al., 2002).
However, whereas the diagnostic readout of such
experiments by DNA microarray analysis is
straightforward, the challenge for the biotechnol-
ogist will be to work out schemes that allow to
select subpopulations with improved product
yields.
3.2. Global regulation and the carbon, energy,
nitrogen or phosphorous sources
In the model bacteria E. coli and B. subtilis , the
global regulatory mechanisms that control the
utilization of carbon, energy, nitrogen and phos-
phorous sources are well known. With the excep-
tion of the regulation of the acetate metabolism(reviewed in Gerstmeir et al., 2003) and nitrogen
control (reviewed by Burkovski, 2003), little is
known about global regulatory mechanisms in C.
glutamicum . Genome-wide expression analyses
with DNA microarrays efficiently allow to identify
regulons or stimulons, i.e. the groups of genes
controlled by one regulator or responding to one
stimulus, respectively. The specificity of this typeof analysis may be demonstrated by the analysis of
ribose-specific gene expression in C. glutamicum .
In a comparison of gene expression from C.
glutamicum ATCC 13032 cultures grown exponen-
tially by repeated dilution for at least 10 genera-
tions on either glucose or ribose as sole carbon and
energy source, only eight genes in two clusters/
putative operons exhibited significantly changedRNA levels. The putative rbsACBD operon en-
codes the subunits of an ABC transport system
and its binding protein shows sequence similarities
to ribose-specific binding proteins from other
bacteria. The second gene cluster comprises rbsK
encoding ribokinase which phosphorylates ribose
to ribose-5-phosphate, an intermediate of the
pentose phosphate shunt, and two adjacent genes.Expression of the pentose phosphate pathway
genes did not change. Thus, only those genes
encoding proteins required for the uptake of ribose
and its entry into the central carbon metabolism
exhibit higher RNA levels with ribose as a carbon
source.
As opposed to the constricted regulation ofribose-specific gene expression, a complex gene
expression response results when C. glutamicum is
starved for phosphate, its preferred source of
phosphorous (Ishige et al., 2003). The phosphate
starvation stimulon of C. glutamicum apparently
comprises more than 100 genes and time-resolved
analysis of the gene expression changes after
eliciting phosphate starvation demonstrated gra-dual and timed gene expression changes indicating
a multi-level regulatory control (Ishige et al.,
2003). A central cornerstone of this regulation
became evident with the demonstration that the
regulon of one two-component regulatory system
largely overlaps with the phosphate starvation
stimulon (Mickova, unpublished results). The
definition of the phosphate starvation stimulonalso allowed to deduce a common theme in
phosphorous metabolism of C. glutamicum . This
bacterium primarily relies on phosphate as a
source of phosphorous and, when starved for it,
increases expression of the genes encoding a high-
affinity phosphate uptake system. Only when by
this means phosphate starvation is not overcome,
C. glutamicum starts to scavenge other sources ofphosphorous and genes for uptake and utilization
of organophosphates exhibit increased RNA le-
vels.
3.3. Amino acid production, metabolic pathway
engineering and the impact of genomics
The interest in C. glutamicum arises primarily
from its application as a highly efficient aminoacid producer. Classical strain optimization by
mutation and selection was successful from an
industrial point of view, but not very rewarding for
the microbiologist attempting to understand ami-
no acid production. Then, based on the knowledge
of the most important pathways in the conversion
of the carbon source to the wanted product,
targeted metabolic engineering allowed to improveamino acid production on a rational basis. This
rational approach came with a price as it was
reductionistic and did not take into account any
influence of more than 2500 genes, gene products
or their activities. With the diagnostic power of C.
glutamicum whole-genome DNA microarrays, it
V.F. Wendisch / Journal of Biotechnology 104 (2003) 273�/285280
appears possible to widen the rational
metabolic engineering approach from its
traditionally constricted focus to the full genome
level.Metabolic pathway engineering of the wild-type
strain ATCC 13032 which does not overproduce
valine led to a valine production strain (Radma-
cher et al., 2002). Growth of this valine-producing
strain as well as of the L-lysine-producing strain
MH20-22B was inhibited by valine added to the
growth medium whereas growth of the wild type
was unaffected (Eggeling et al., 1997; Lange et al.,
2003). DNA microarray analysis of the valine
stress response of the valine-producing strain
identified gene expression changes indicating an
intracellular isoleucine limitation: increased ex-
pression of the branched-chain amino acid bio-
synthesis genes ilvBNC , which was confirmed by
proteome analysis and determination of enzyme
activities, and of an isoleucine tRNA synthetase
gene. Subsequently, it was shown that isoleucine
limitation as a consequence of valine addition was
linked to the ilvA deletion in the isoleucine
auxotrophic valine-producing strain and could be
overcome by addition of high isoleucine concen-
trations. Finally, the fact that supplementation of
the valine-producing strain with the dipeptide
isoleucyl-isoleucine relieved the inhibitory effect
of valine identified competition for uptake of
isoleucine by the carrier BrnQ, which transports
all branched-chain amino acids, as the cause of
valine inhibition (Lange et al., 2003). Based on the
surprising finding that valine increased ilvBN
expression, it was shown that addition of
external valine stimulated valine production
by the valine-producing strain indicating that
activity of the ilvBN encoded acetohydroxy
acid synthase may still be a limiting factor
for valine production in this valine-producing
strain.
Clearly, the impact of genome-wide expression
analyses on our understanding of amino acid
production by C. glutamicum from a whole-cell
point of view is just emerging, but pointing
to DNA microarray analysis as enabling technol-
ogy for the optimization of amino acid produc-
tion.
3.4. Common regulatory themes in M. tuberculosis
and C. glutamicum
Global gene expression patterns of the pathogen
M. tuberculosis , which as the non-pathogenic C.
glutamicum belongs to the Corynebacterianeae ,
have been studied with a particular focus on the
tuberculosis pathology. The comparative func-
tional genomic analysis of several members ofthe Corynebacterianeae will help to unravel glob-
ally genus-specific gene expression differences as
well as those relevant for pathogenicity. As M.
tuberculosis and C. glutamicum are close relatives,
global regulatory circuits controlling general func-
tions such as the heat- or acid-shock response are
likely to be conserved and progress made for either
of the different members of the Corynebacteria-
neae should be easily transferred to the other. In
line of this view, it was already shown that
molecular biology methods and vectors developed
for C. glutamicum function in C. diphtheriae and
that nitrogen control in these Corynebacterianeae
is similar (Nolden et al., 2002).
In C. glutamicum , DNA microarray analysis of
the heat-shock response revealed increased RNAlevels of various chaperone genes (dnaJ , dnaK ,
groEL ), Clp protease subunit genes, genes for
thioredoxin recycling and for the extracytoplasmic
function sigma factor E (sE) of RNA polymerase
(Muffler et al., 2002). In M. tuberculosis , the heat-
shock response comprises more genes (Stewart et
al., 2002) and its complex regulation begins to
emerge as the regulons of the sigma factors sE andsH and of the regulators HcaR and HspR were
determined by DNA microarray analysis (Manga-
nelli et al., 2001, 2002; Stewart et al., 2002;
Kaushal et al., 2002). Interestingly, the heat shock
response and the oxidative stress response in M.
tuberculosis seem to be interrelated as a sH mutant
not only shows a reduced immunopathology and
increased heat-shock sensitivity but also increasedsensitivity to oxidative stresses (Manganelli et al.,
2002; Kaushal et al., 2002). For C. glutamicum
biotechnology, these results may guide experi-
ments aimed at understanding induction of L-
glutamate production by a temperature-shift and
maintaining it over long production periods.
Similarly, L-lysine production at temperatures
V.F. Wendisch / Journal of Biotechnology 104 (2003) 273�/285 281
higher than the optimal growth temperature of
30 8C for wild-type C. glutamicum is desirable to
minimize cooling during amino acid production.
The response to hypoxic conditions, which as
heat-shock and nutrient starvation (Betts et al.,
2002) pertains to M. tuberculosis pathogenicity or
latency, has been determined by DNA microarray
analysis (Sherman et al., 2001). In biotechnologi-
cal processes involving C. glutamicum , sufficient
oxygen supply is a minor problem for smaller
scales but still remains a problem for certain zones
of the large bioreactors used in industrial amino
acid production. Genes responsive to hypoxia
identified in M. tuberculosis might serve useful in
monitoring oxygen availability of C. glutamicum
cells during large-scale amino acid production on
the gene expression level.
Iron-complexing compounds as protocatechuic
acid are required for the cultivation of C. gluta-
micum (Liebl et al., 1989) while M. tuberculosis
faces iron-limiting conditions within the human
host (Rodriguez et al., 2002). The transcriptional
regulator of iron metabolism genes, IdeR, is a
homologue of DtxR of C. diphtheriae and is
essential in M. tuberculosis . DNA microarray
analyses have shown that the regulon of IdeR in
M. tuberculosis comprises many putative trans-
porters, proteins involved in siderophore synthesis
and iron storage, transcriptional regulators and
enzymes involved in lipid metabolism. The binding
sites of IdeR upstream of iron-responsive genes
have been identified (Rodriguez et al., 2002) and
will allow for an in silico analysis of C. glutamicum
promoters to predict putative iron-responsive
genes which in turn might serve as diagnostic
markers for iron limitation in amino acid produc-
tion processes.
The genome of C. glutamicum is more than 1
Mbp smaller and contains about 1000 genes less
than that of M. tuberculosis . It is conceivable that
many global regulatory mechanisms turn out to be
less complex in C. glutamicum than in M. tubercu-
losis . Therefore, as can already be seen with
respect to the central carbon, nitrogen and phos-
phate metabolism, amino acid and lipid biosynth-
esis as well as cell wall biogenesis (Eggeling and
Sahm, 2001) and the maintenance of homeostasis,
C. glutamicum might become a model organism ofthe Corynebacterianeae.
4. Conclusion
We can now use C. glutamicum whole-genome
DNA microarrays to characterize global gene
regulatory mechanisms on the RNA level and
subsequently we can determine whether changed
RNA levels are due to transcriptional regulation
and/or differential RNA stability. However, to
gain a complete view of global regulation we haveto follow a more comprehensive approach by
complementing transcriptomics with proteomics
and biochemistry to study regulation of transla-
tion, protein folding, degradation or modification
and with metabolic flux analysis and metabolo-
mics to study in vivo activities and allosteric
control of enzymes.
Although the application of whole-genomeDNA microarrays to study C. glutamicum is in
its infancy, DNA microarrays will be a corner-
stone in a comprehensive experimental approach
to increase our knowledge about fundamental and
applied aspects of corynebacterial physiology.
They hold the promise to enable strain and process
optimization for amino acid production with C.
glutamicum .
Acknowledgements
I would like to thank Hermann Sahm for
continuous support, Michael Bott for critically
reading the manuscript as well as stimulating
discussions and Degussa AG for making available
the C. glutamicum genome sequence. In particular,
I would like to thank Doris Rittmann, Tino Polen,
Georg Sindelar, Christian Lange, Takeru Ishige,
Andrea Veit, Malgorzata Krause, Andreas Krug,Sandra Knebel and Corinna Stansen for their
work in various projects as well as Tino Polen,
Georg Sindelar, Silke Rosnowsky and Thorsten
Kloesges for sharing results prior to publication.
The support of the EU (QLK3-2000-00497),
BMBF (Netzwerk Genomforschung an Mikroor-
V.F. Wendisch / Journal of Biotechnology 104 (2003) 273�/285282
ganismen) and Degussa AG is gratefully acknowl-edged.
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