GadXW
Regulon and Glutamate-DependentAcid Resistance
December, 2002
Tucker,
et al., 2002, J Bacteriol 183: 6551-6558 (PDF)
Ma, et al., 2002, J
Bacteriol 184: 7001-7012 (PDF)
Tucker, et al.,
2003, J Bacteriol 185: 3190-3201 (PDF)
Ma, et al.,
et al., 2003, Mol Microbiol 49: 1309-1320 (PDF)
GadXW
Experimental Design and Data
Project
Summary. E. coli
MG1655 acid-inducible genes were identified by whole-genome expression
profiling. Cultures were grown to mid-logarithmic phase on acidified
glucose minimal medium, conditions that induce glutamate-dependent acid
resistance (AR) while the other AR systems are either repressed or not
induced. A total of 28 genes were induced in at least 2 of 3 experiments
in which the gene expression profiles of cells grown in acid (pH 5.5 or
4.5) were compared to cells grown at pH 7.4. Several of these genes are
clustered in the gadA region, including
hdeA, which encodes a putative periplasmic
acid chaperone, and 4 putative regulatory genes. One of these putative
regulators, yhiE, was shown to significantly
increase acid resistance when overexpressed
in cells that had not been pre-induced by growth at pH 5.5 and mutation
of yhiE decreased acid resistance; yhiE
could therefore encode an activator of AR genes. Thus the acid-inducible
genes clustered in the gadA region appear
to be involved in glutatmate-dependent acid resistance, although their specific
roles remain to be elucidated.
GadX
regulates two genes that encode isoforms of
glutamate decarboxylase critical to this system,
but additional genes associated with the glutamate-dependent acid resistance
system remained to be identified. The gadX gene and a second downstream araC-like transcription factor, gadW,
were mutated separately and in combination, and the gene expression profiles
of the mutants were compared to the wild type strain grown in neutral
and acidified medium under conditions favoring induction of glutamate-dependent
acid resistance. Cluster and principal component analysis identified
15 GadX-regulated, acid-inducible genes. Reverse
transcriptase mapping demonstrated that these genes are organized in 10
operons. Analysis of the strain
lacking GadX but possessing GadW confirmed
that GadX is a transcriptional activator under
acidic growth conditions. Analysis of the strain lacking GadW
but possessing GadX indicated that GadW exerts
negative control over three GadX target genes.
The strain lacking both GadX and GadW
was defective in acid-induction of most but not all GadX
target genes, consistent with the roles of GadW
as an inhibitor of GadX-dependent activation
of some genes and an activator of other genes. Resistance to acid was
decreased under certain conditions in a gadX
mutant and even more so by combined mutation of gadX
and gadW. However, there was no defect in colonization
of the streptomycin-treated mouse model by the gadX
mutant in competition with the wildtype, and
the gadX gadW
mutant was a better colonizer than the wildtype. Thus, E. coli colonization of the mouse
does not appear to require glutamate-dependent acid resistance.
We favor a model of AR gene
control in which GadX and GadW
are intermediates in a regulatory cascade and serve to integrate signal(s)
received by the cells to indicate they are present in an acid environment,
have entered into stationary phase (RpoS), reflect
medium composition (CRP), and additional unknown signals (HN-S and EvgA).
This would leave the role of direct activation of target genes to one
of the other transcription factors. In support of this hypothesis, we
tested whether overproduction of YhiE could
rescue AR in the gadX gadW
mutant – it did (data not shown). Thus, we propose a complex regulatory
cascade in which global regulators (RpoS, CRP, HN-S, EvgA, etc.) influence
the expression levels and/or activities of GadX
and GadW, which in turn activates the expression
and/or activities of transcription activators (eg.
YdeO and YhiE) that directly activate
subsets of target genes involved in AR. One prediction of this model
is that YhiE directly activates the glutamate-dependent AR genes.
This cascade would allow the cell to integrate various physiological processes
that are collectively important in AR.
GadXW
and Acid Resistance Experimental Design
Growth of E. coli MG1655 (CGSC# 7740) growing at pH 7.2, pH 5.5,
and pH 4.5. Increasing acidity placed increasing burden on growth. There
was no difference in the growth curves of E. coli DT162 (delta
gadX::KanR), DT169 (delta gadXkan-), DT203 (delta gadW::KanR),
and DT232 (delta gadXgadW::KanR). Arrows indicate the time of
RNA isolation.
Culture Conditions.
All cultures used for genomic expression profiling of acid resistance
and GadXW regulon genes were grown in the minimal medium developed for
E. coli proteome studies (Neidhardt et al., 1974). Glucose (0.2%)
was the sole carbon and energy source. Morpholinepropanesulfonic acid
(MOPS) was used as the buffer for pH 7.4 media and morpholinethanesulfonic
acid (MES) was used to buffer the pH 4.5 and 5.5 media. Cultures were
grown aerobically with 300 rpm agitation at 37 degrees C in 50 ml of medium
in 250 ml fleakers. Growth was monitored by measuring the optical density
(OD) at 600nm. RNA
samples were isolated in mid-logarithmic phase by pipeting into ice-cold
RNAlater™ (Ambion, Austin, TX) followed by purification using an
RNeasy™ Mini Kit (Qiagen, Valencia, CA). The RNA
samples were labeled by first strand cDNA synthesis. Labeled targets
were hybridized to DNA arrays (Panorama E. coli Gene Arrays, Sigma
Genosys Biotechnologies, Inc., The Woodlands, TX). The hybridized arrays
were scanned
by phosphorimaging at a pixel density of 100 microns (10,000 dots/cm2)
with a STORM 820 PhosphoImager (Molecular Dynamics, Sunnyvale, CA) following
exposure to a Kodak Storage Phosphor Screen GP (Eastman Kodak Co., Rochester,
NY) for 24 hrs. The array membranes were consecutively hybridized, stripped,
and rehybridized.
Spot-finding and quantitation.
Image analysis software (ArrayVision, Imaging Research, Inc.) was used
for spot-finding
and quantitation of the E. coli Panorama arrays. The raw spot intensities
were represented in a row-column format and exported into Microsoft Excel
spreadsheets for further analysis, or as comma-delimited files (.csv)
for upload to the database. Raw data from each experimental replicate
were analyzed
in Excel workbooks containing manually executed macros written in
Visual Basic, or the data were processed in the database. The first step
in the analysis associates the array coordinate for each spot with a unique
spot number, the gene name, and related gene annotation. On the membrane
arrays there are two spots for each gene, and these were treated as separate
determinations. The raw data were normalized by expressing spot intensities
as a percentage of the sum of all of the gene-specific spot intensities.
The second step in the analysis applies the student t-test to determine
the probability that the average of the experimental replicates is significantly
different from the average of the control replicates . The P values (derived
from the student t-test) for the normalized and natural log transformed
data were calculated. The third step calculates relative gene expression
between conditions by introducing a threshold value, chosen to be representative
of the limit of detection of expressed genes (usually the 500th lowest
expressed gene), and then calculating the ratio of the experimental/control
expression levels such that genes that are more highly expressed in the
experimental condition are given a positive value, and genes that are
more highly expressed in the control condition are given a negative value.
Experiments.
The goal of the gene expression profiling experiments was to identify
acid-inducible target genes under GadX and or GadW control. The following
gene expression profiles were obtained:
|
|
|
Replicates |
Expt # |
Strain |
Condition |
Biological |
Technical |
1 |
Wt |
pH 7.4 |
2 |
5 |
2 |
Wt |
pH 7.4 |
1 |
2 |
3 |
Wt |
pH 5.5 |
2 |
5 |
4 |
Wt |
pH 5.5 |
1 |
2 |
5 |
Wt |
pH 4.5 |
1 |
2 |
6 |
gadX |
pH 7.4 |
2 |
5 |
7 |
gadX |
pH 7.4 |
1 |
2 |
8 |
gadX |
pH 5.5 |
2 |
5 |
9 |
gadX |
pH 5.5 |
1 |
2 |
10 |
gadX |
pH 4.5 |
1 |
2 |
11 |
gadX(Km-) |
pH 7.4 |
1 |
2 |
12 |
gadX(Km-) |
pH 5.5 |
1 |
2 |
13 |
gadW |
pH 7.4 |
1 |
2 |
14 |
gadW |
pH 5.5 |
1 |
2 |
15 |
gadX gadW |
pH 7.4 |
1 |
2 |
16 |
gadX gadW |
pH 5.5 |
1 |
2 |
Pair-wise Comparisons
Acid vs. Neutral Conditions
Exp 3 vs. 1; wildtype; pH 5.5 vs. pH 7.4
Exp 5 vs. 1; wildtype; pH 4.5 vs. pH 7.4
Exp 4 vs. 2; wildtype; pH 5.5 vs. pH 7.4
Exp 8 vs. 6; gadX; pH 5.5 vs. pH 7.4
Exp 10 vs. 6; gadX; pH 4.5 vs. pH 7.4
Exp 9 vs. 7; gadX; pH 5.5 vs. pH 7.4
Exp 12 vs. 11; gadX(kan-); pH 5.5 vs. pH 7.4
Exp 14 vs. 13; gadW; pH 5.5 vs. pH 7.4
Exp 16 vs. 15; gadXW; pH 5.5 vs. pH 7.4
Mutants vs. Wildtype under Neutral Conditions
Exp 6 vs. 1; pH 7.4; gadX vs. wildtype
Exp 7 vs. 2; pH 7.4; gadX vs. wildtype
Exp 11 vs. 2; pH 7.4; gadX(kan-) vs. wildtype
Exp 13 vs. 2; pH 7.4; gadW vs. wildtype
Exp 15 vs. 2; pH 7.4; gadXW vs. wildtype
Mutants vs. Wildtype under Acid Conditions
Exp 8 vs. 3; pH 5.5; gadX vs. wildtype
Exp 10 vs. 5; pH 4.5; gadX vs. wildtype
Exp 9 vs. 4; pH 5.5; gadX vs. wildtype
Exp 12 vs. 4; pH 5.5; gadX(kan-) vs. wildtype
Exp 14 vs. 4; pH 5.5; gadW vs. wildtype
Exp 16 vs. 4; pH 5.5; gadXW vs. wildtype
Data Legend
GadXW
Data Set; Excel: 5.7 Mb)
1)WtpH7-4pct: average normalized spot intensity for experiment
1; values expressed as a percentage of the sum of all of the gene-specific
spot intensities
3vs1)WtpH5-5vs7-4: log10 ratio of experiment 3 vs. experiment
1
3vs1)WtpH5-5vs7-4.p-ln: P value for the corresponding
log ratio calculated from the normalized, natural log transformed data
E. coli Gene Expression Database (Oracle) Interface
|