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Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Results and discussion
  5. Experimental procedures
  6. Acknowledgements
  7. References

Deoxyadenosine methyltransferase (Dam) methylates the deoxyadenine residues in 5-GATC-3 sequences and is important in many cellular processes in Escherichia coli. We performed a computational analysis of the entire E. coli genome and confirmed that GATC sequences are distributed unevenly in regulatory regions, which suggests that Dam might regulate gene transcription. To test this, a high-density DNA microarray of 4097 E. coli genes was constructed and used to assess the gene expression profiles of the wild type and the dam-16::kam mutant strain grown under four different conditions. We also used two-dimensional electrophoretic analysis of the proteome to assess the protein profiles. The expression of a large number of genes was affected by the dam deficiency. Genes involved in aerobic respiration, stress and SOS responses, amino acid meta-bolism and nucleotide metabolism were expressed at higher levels in the mutant cells, especially in aerobic conditions. In contrast, transcription of genes partici-pating in anaerobic respiration, flagella biosynthesis, chemotaxis and motility was decreased in the dam mutant strain under both aerobic and low aerobic conditions. Thus, Dam-controlled genes are involved in adjusting the metabolic and respiratory pathways and bacterial motility to suit particular environmental conditions. The promoters of most of these Dam-controlled genes were also found to contain GATC sequences that overlap with recognition sites for two global regulators, fumarate nitrate reduction (Fnr) and catabolite activator protein (CRP). We propose that Dam-mediated methylation plays an important role in the global regulation of genes, particularly those with Fnr and CRP binding sites.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Results and discussion
  5. Experimental procedures
  6. Acknowledgements
  7. References

The 4.6 Mbp Escherichia coli genome encodes about 4300 open reading frames (ORFs) (Blattner et al., 1997), the functions of about 50% of which remain unknown. To understand the global gene regulation of the E. coli genome, its gene expression under various conditions has been comprehensively investigated using transcriptome and proteome analytical methods. This includes the transcriptome analyses using DNA microarrays that were performed to study the gene expression that takes place in response to changing environment conditions, during the heat shock response and as a result of gene disruption (Richmond et al., 1999; Tao et al., 1999; Arfin et al., 2000). In addition, the proteome approach using two-dimensional gel electrophoresis has been performed with strains with mutations in nucleoid proteins such as IHF, H-NS or Fis (Nyström, 1995; Laurent-Winter et al., 1997; Choe et al., 1999), as well as to study the response to environmental stimuli (cold shock, heat shock and exogenous pyrophosphate) (Van Bogelen and Neidhardt, 1990; Biville et al., 1996) and to assess the alterations that occur during the change in growth phase (Nyström et al., 1996).

Dam (deoxyadenosine methyltransferase) methylates the adenine residue within 5′-GATC-3′ sequences in double-stranded DNA. This methylation is known to play important physiological roles in E. coli. This is particularly demonstrated by Dam-defective mutants, which have highly pleiotropic changes including increased mutability, hyper-recombination and transcriptional alterations (Marinus, 1996; 2000). Dam also contributes to the timing at which chromosome replication is initiated (Marinus, 1996). These processes are all regulated by the hemimethylation of the DNA that occurs following the synthesis of a new DNA strand after the passage of the replication fork.

The protection analysis of the whole E. coli genome has revealed that global regulators, including CRP, Fnr and IHF, can block Dam-mediated methylation of many GATC sequences (Wang and Church, 1992; Tavazoie and Church, 1998). This suggests that the recognition sites of these global regulators may coincide with GATC sequences, and that Dam methylation may serve to limit the access of global regulators to upstream regions of a gene, thereby regulating transcription. Observations with individual genes support this notion. For example, the DNA methylation pattern of the two GATC sites within the regulatory regions of the pyelonephritis-associated pilus (pap) operon controls pap transcription because it affects the ability of two regulatory proteins [leucine-responsive regulatory protein (Lrp) and pap-encoded co-regulatory protein (PapI)] to bind upstream (Blyn et al., 1990; Braaten et al., 1994; Nou et al., 1995; van der Woude et al., 1998). Furthermore, computational analysis of part of the E. coli genome has revealed that GATC sequences have an unusual distribution in that they often cluster within Fnr and CRP recognition sequences located upstream of respiratory or DNA replication genes (Henaut et al., 1996). Thus, Dam-mediated GATC methylation may affect protein–DNA interaction by modifying the recognition sequence of transcriptional regulators or RNA polymerases (Marinus, 1996). This suggests that many genes with GATC sequences in or near recognition sites for transcriptional regulators may be regulated by Dam-mediated GATC methylation. However, the exact mechanism by which Dam regulates transcription and the extent of its biological importance remains unclear.

It has been reported recently that Dam participates in the virulence of Salmonella typhimurium (Heithoff et al., 1999), as Dam-deficient S. typhimurium mutants can colonize mucosal sites but are unable to penetrate deeper into the tissue. The Dam-deficient mutants also cannot invade non-phagocytic cells, a function that is required for the virulence of S. typhimurium, although normal intracellular proliferation was observed. It was found that Dam controls the expression of a large number of genes that may participate in the invasion of host cells. However, how Dam does this and which genes are particularly crucial for the invasion of host cells by S. typhimurium is still not clear.

In this study, we performed a computational analysis of the 500 bp upstream of the ORFs of all E. coli genes. We found that, as described previously by Henaut et al. (1996), GATC sequences/sites are not randomly distributed, and often overlap with sequences recognized by global regulators. This supports the notion that Dam is important in global gene regulation. We then assessed E. coli gene expression of a dam mutant under various environmental conditions using transcriptome and proteome techniques. This showed that Dam up- and downregulates many genes, including genes involved in energy and nucleotide metabolism and cellular processes, as well as SOS and stress response genes and translation-related genes. In addition, as genes involved in E. coli motility also appear to be controlled by Dam, we speculate that the poor virulence of the Dam mutant S. typhimurium may result from defects in bacterial motility.

Results and discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Results and discussion
  5. Experimental procedures
  6. Acknowledgements
  7. References

GATC sites occur frequently in the transcriptional regulatory region of genes in the entire E. coli genome

It has been suggested that GATC sites are part of the sequences recognized by the global regulators CRP, Fnr and IHF (Wang and Church, 1992; Hale et al., 1994; Henaut et al., 1996; Tavazoie and Church, 1998). To assess the GATC distribution in the E. coli genome comprehensively, we performed computational analysis on the whole E. coli genome. This was done by examining the 500 bp upstream of all the ORF start points in the entire E. coli genome for GATC sites. If the A, T, G and C residues in E. coli genomic sequences were be purely randomly distributed, the average distance between separate GATC sequences would be about 256 bp (i.e. less than two GATC sequences should be present in each 500 bp upstream sequence; Henaut et al., 1996). However, we found that about 50% of all E. coli genes contained more than two GATCs in the 500 bp upstream of the ORF start, with 630 genes and 222 genes containing three and more than five GATCs respectively. The genes with the highest number of GATC sites were yahG and gidA, which contain 10 and 18 GATCs respectively. There were also regions of low GATC density, the rhs gene family being located in such a region. The rhs family is large and consists of imperfectly repeated DNA sequences. This family is responsible for duplication within the E. coli chromosome (Lin et al., 1984). The results of our computational sequence analysis of the entire E. coli genome are shown on our web site (http://ecoli.aist-nara.ac.jp/xp_analysis/dam/all.html). This non-random and frequent localization of GATC in the promoter regions of the E. coli genome suggests that this sequence may participate in gene expression and/or genome structure.

We also confirmed that GATC sites overlap with the consensus sequences for the global regulators Fnr and/or CRP that are found in the regulatory region of several genes/operons (data not shown; Henaut et al., 1996). This supports the hypothesis that GATC may be part of the cis-acting elements that are bound by these global transcriptional regulators, and that its methylation affects the DNA recognition by these regulators. To explore further the biological role of Dam-mediated GATC methylation, we used DNA microarray and two-dimensional PAGE techniques to compare the expression of the whole genome of wild-type E. coli and an isogenic Dam-deficient mutant that were grown under various grown conditions.

Microarray analysis of gene expression in the dam-16::kam mutant

The dam mutant, which is defective in Dam methylase activity, is dam-16::kam, the result of inserting the kanamycin cassette in the opposite direction to dam gene transcription (Parker and Marinus, 1988). The wild-type and mutant cells were grown in L broth under aerobic or low aerobic conditions and sampled in both logarithmic (log) and stationary phases. Total RNA was prepared twice from independently grown cultures, and each preparation was used twice for the hybridization analysis. Thus, for each gene in each strain, transcription levels are represented by four independent measurements (see Experimental procedures). The transcription levels of the genes in the dam mutant are expressed relative to those of the wild type, yielding a relative ratio (see Experi-mental procedures). The genes with significantly altered transcriptional levels in the dam mutant cells are summarized in Table 1. Supplemental data are available on our web site (http://ecoli.aist-nara.ac.jp/xp_analysis/dam/all.html).

Table 1. Genes differentially expressed between KK46( dam +) and KK335( dam- 16:: kam ).
 Relative log ratio (KK335(dam-16::kam)/KK46)a  
 AerobicLow aerobic  
 LogStationaryLogStationaryDescriptionbNo. of GATCc
  • a.   The expression level was described by relative log ratio (logE value) of KK335( dam -16:: kam )/KK46 ( dam + ). G2 represents drastic alteration of expression of a gene whose expression was detected only in KK46 (down) or KK335 (up). When some data in four hybridizations were classified as group 2 and others were classified as group 1, the expression level was described by more than (>) or less than (<) the mean of the relative ratio determined by only part of the hybridization data classified in group 1. The details of group 1 and group 2 were described in Experimental procedures .

  • b.

    The column for description was described according to SWISSPROT, Genobase database and GenBank.

  • c.

    The number of GATC sequences within the upstream 500 bp of each gene is described in column c.

  • The results obtained are representative of four independent hybridizations from two independent total RNAs extracted from independent culture. Only genes with a P-value <1E-2 in a Wilcoxon statistical test and factor >0.69 (= twofold alteration corresponding to logE value) differential expression between KK46 (dam+) and KK335 (dam-16::kam) (bold), or consistent up/down regulation more than twofold of all four independent hybridizations were classified according to their function.

Amino acid metabolism
 ansB0.88   Asparaginase (EC 3.5.1.1) II precursor2
 argM   −1.19Succinylornithine aminotransferase, N-(alpha)- acetylorinithine-(delta)-aminotransferase (EC 2.6.1.-) (Carbon starvation protein C)2
 astA   −1.37Arginine succinyltransferase3
 avtA 0.88    0.71 Valine−pyruvate aminotransferase (EC 2.6.1.66) (Transaminase C) (alanine-valine transaminase)1
 dadA 1.79   0.85 D -Amino acid dehydrogenase small subunit (EC 1.4.99.1) 1
 dadX 1.55    Alanine racemase, catabolic precursor (EC 5.1.1.1)4
 dapB 1.36 0.74  Dihydrodipicolinate reductase (EC 1.3.1.26)2
 dpaL 1.53  Putative diaminopropionate ammonia lyase[EC4.3.1.15] [diaminopropio-natase) (Alpha, beta-diaminopropionate ammonia-lyase)3
 gltD  0.830.72Glutamate synthase (NADPH) small chain (EC 1.4.1.13) (glutamate synthase beta subunit) (nadph-gogat) (GltS beta chain)1
 (gltD) 1.26  Hypothetical protein1
 gph1.010.451.59 Phosphoglycolate phosphatase (EC 3.1.3.18) (PGP)2
 hisC1.07   Histidinol-phosphate aminotransferase3
 hisD 0.74    Histidinol dehydrogenase (EC 1.1.1.23) (hdh)4
 hisG 0.73    ATP phosphoribosyltransferase3
 ltaA 2.53 1.062.16  L -Allo-threonine aldolase (EC 4.1.2.-) 2
 putA 0.72    Proline dehydrogenase (EC 1.5.99.8) (proline oxidase)/ delta-1-pyrroline-5-carboxylate dehydrogenase (EC 1.5.1.12) (p5c dehydrogenase)0
 sdaB0.76    L -Serine deaminase 1
 sol 0.99    Sarcosine oxidase (EC 1.5.3.1)0
 speA 0.74   0.69  Arginine decarboxylase (EC 4.1.1.19)0
 tdcB  −1.8 Threonine dehydratase catabolic (EC 4.2.1.16) (threonine deaminase)0
 thrA 1.09    ThrA bifunctional enzyme, aspartokinase I bifunctional enzyme N-terminal is aspartokinase I and C-terminal is homoserine dehydrogenase I (EC 2.7.2.4) (EC 1.1.1.3)0
 thrC 0.97  1.58 Threonine synthase (EC 4.2.99.2)1
Biosynthesis of cofactors, prosthetic groups, carriers
 bioA>1.91 >3.33 Adenosylmethionine-8-amino-7-oxononanoate transaminase (EC 2.6.1.62)3
 (bioD)1.37   Dethiobiotin synthase (EC 6.3.3.3)1
 entE1.86 >1.75 Enterochelin synthetase (EC 6.-.-.-) component E2
 ispA 1.28    Geranyl transtransferase (EC 2.5.1.10) (farnesyl- diphosphate synthase)(FPP synthase)0
 nadD   −0.97Nicotinic acid mononucleotide adenylyltransferase, NAMN adenylyltransferase0
 panC0.94   Pantoate-beta-alanine ligase (EC 6.3.2.1) (pantothenate synthetase) (pantoate activating enzyme)3
 panD1.08   Aspartate 1-decarboxylase (EC 4.1.1.11)0
 ribD 1.17 0.860.890.94Riboflavin-specific deaminase1
 ribH 0.74    6,7-Dimethyl-8-ribityllumazine synthase2
 yncB   −1.63Putative NADP-dependent oxidoreductase (EC 1.-.-.-)1
Cell envelope
 crl 0.83   0.86Crl protein3
 cheA  −0.93 Chemotaxis protein CheA (EC 2.7.3.-), CheY kinase3
 cheR  −1.16 Chemotaxis protein methyltransferase (EC 2.1.1.80)4
 cheY  −1.26 Chemotaxis protein CheY, chemotaxis response regulator protein4
 cheZ  −1.16 CheY phosphatase1
 fimB1.05   0.97 Type 1 fimbriae regulatory protein FimB0
 flgD  0.78   Basal-body rod modification protein0
 fliC  1.4 Flagellin1
 fliK 0.84    Flagellar hook-length control protein3
 motB  −1.05 Chemotaxis MotB protein (motility protein b)1
 ompA   0.99Outer membrane protein a precursor (outer membrane protein II)1
 ompX0.69  0.89Outer membrane protease0
 ompW−1.66   Outer membrane protein W3
 rfbX0.85   O-antigen transporter0
 rfc1.480.890.93 Probable O-antigen polymerase1
 slp   1.2Slp protein0
 tap −1.11−1.63 Methyl-accepting chemotaxis protein II (Mcp-II) (aspartate chemoreceptor protein)4
 tar  −1.45 Methyl-accepting chemotaxis protein II (Mcp-II) (aspartate chemoreceptor protein)2
 trg   −0.99Methyl-accepting chemotaxis protein III (Mcp-III) (ribose and galactose chemoreceptor protein)1
Central intermediary metabolism
 gabD   −1.26Succinate-semi-aldehyde dehydrogenase (NADP+) (EC 1.2.1.16) (ssdh)2
 gabT   −0.884-Aminobutyrate transaminase (EC 2.6.1.19)1
 glpK 0.76    Glycerol kinase (EC 2.7.1.30)2
 hdhA0.78  0.757-Alpha-hydroxysteroid dehydrogenase (EC 1.1.1.159) (7-alpha-hsdH)2
 nagA  −1.19 N-acetylglucosamine-6-phosphate deacetylase (EC 3.5.1.25) (NagA)1
 nagB  −1.37 Glucosamine-6-phosphate isomerase (EC 5.3.1.10) (glucosamine-6-phosphate deaminase)1
 nagC  −0.86 N-acetylglucosamine repressor1
 nanA1.92 2.7 N-acetylneuraminate lyase subunit (EC 4.1.3.3) (N-acetylneuraminic acid aldolase) (N-acetylneuraminate pyruvate lyase) (nalase)9
 nanE  −2.04 ManNAc epimerase5
 nanK1.08 1.21 ManNAc kinase2
 rfbC 0.76  dTDP-6-deoxy-D-glucose-3,5 epimerase1
 yojH1.2   Malate:quinone oxidoreductase3
Energy metabolism
 aceA 0.78    Isocitrate lyase (EC 4.1.3.1) (isocitrase) (isocitratase) (icl)5
 aceB 0.85    Malate synthase a (EC 4.1.3.2) (msa)6
 ackA   0.79  Acetate kinase (EC 2.7.2.1)2
 acnA   −1.2Aconitate hydratase (EC 4.2.1.3)4
 adhE  −0.99 Alcohol dehydrogenase (EC 1.1.1.1)1
 araC1.39   Arabinose operon regulatory protein2
 astB   −1.11Succinylarginine dihydrolase2
 astD   −1.17Succinylglutamic semi-aldehyde dehydrogenase2
 citE1.32 1.44 Citrate lyase beta chain (acyl lyase subunit) (citE) homologue1
 cydB   0.99Cytochrome d ubiquinol oxidase subunit II (EC 1.10.3.-)1
 cyoA   −1.09Cytochrome O ubiquinol oxidase (EC 1.10.-.-) chain II1
 cyoD  0.79   CyoD protein2
 dmsA1.43   Dimethyl sulphoxide reductase chain A1
 fadB 1.24    Fatty oxidation complex alpha subunit (contain: enoyl-CoA hydratase (EC 4.2.1.17), delta(3)-cis-delta(2)-trans-enoyl- CoA isomerase (EC 5.3.3.8), 3-hydroxyacyl-CoA dehydrogenase (EC 1.1.1.35), and 3-hydroxybutyryl-CoA epimerase (EC 5.1.2.3))4
 frdB0.77   Fumarate reductase (EC 1.3.99.1) iron−sulphur protein2
 fucR  −1.43 Fuc operon regulatory protein3
 fumA 1.13    Fumarate hydratase (EC 4.2.1.2) FumC, iron dependent1
 gatA  −1.17 PTS system, galactitol-specific IIA component1
 gatB  2.18 Phosphotransferase system enzyme II, galactitol specific, protein B1
 gatC  −2.16 PTS system, galactitol-specific IIC component (EIIC-GAT) (galacticol-permease IIC component) (phosphotransferase enzyme II, C component)1
 gatD−1.43 <−3.51 Galactitol-1-phosphate 5-dehydrogenase (EC 1.1.1.251)3
 (gatR)  −1.24 Galactitol utilization operon repressor2
 gatY0.94 1.520.81Tagatose-bisphosphate aldolase (EC 4.1.2.-)1
 gatZ  −1.56 Putative tagatose 6-phosphate kinase (EC 2.7.1.143)1
 glf0.960.66  UDP-galactopyranose mutase (EC 5.4.99.9)0
 glgS   −1.22RpoS-dependent glycogen synthesis protein2
 glk  −1.11 Glucokinase (EC 2.7.1.2)3
 gltA  −0.92 Citrate synthase (EC 4.1.3.7)2
 gutD1.03   Sorbitol-6-phosphate 2-dehydrogenase (EC 1.1.1.140) (glucitol-6-phosphate dehydrogenase) (ketosephosphate reductase)2
 gutM1.35   Glucitol operon activator protein7
 kdsA1.16   3-deoxy-D-manno-octulosonic acid 8-phosphate synthetase5
 hoxK−1.11   Hydrogenase (EC 1.18.99.1) small-chain precursor3
 lldD  −1.04  L -Lactate dehydrogenase (cytochrome) (EC 1.1.2.3) 2
 mhpE1.94 1.84 4-Hydroxy-2-oxovalerate aldolase (EC 4.1.3.-)0
 mhpR2.86   Mhp operon transcriptional activator2
 napA−1.66   Probable periplasmic nitrate reductase 3 (EC 1.7.99.4)2
 napD−1.24   NapD protein1
 napF−1.54   Ferredoxin-type protein NapF2
 narG−2.25−0.88  Respiratory nitrate reductase 1 alpha chain (EC 1.7.99.4)1
 narH −0.99  Respiratory nitrate reductase 1 beta chain (EC 1.7.99.4)2
 narJ  <−1.02 NarJ protein1
 narK1.31   Nitrate transport protein NarK2
 narZ−1.77−0.94  Respiratory nitrate reductase 2 alpha chain (EC 1.7.99.4)3
 nirB2.19 1.51 Nitrite reductase (NAD(P)H) large subunit (EC 1.6.6.4)1
 nirD  −1.56 Nitrite reductase (NAD(P)H) small subunit (EC 1.6.6.4)4
 nuoH  −0.8 NADH dehydrogenase I chain H (EC 1.6.5.3) (NADH- ubiquinone oxidoreductase chain 8) (nuo8)2
 ppsA 1.52  1.32 Pyruvate, water dikinase (EC 2.7.9.2)3
 rpe−1.12 −1.22 Ribulose-phosphate 3-epimerase (EC 5.1.3.1) (pentose-5- phosphate 3-epimerase) (ppe)3
 sfsA   −1.04Sugar fermentation stimulation protein0
 sucA  −1.06 Oxoglutarate dehydrogenase (lipoamide) (EC 1.2.4.2)1
 sucC  −1.12 Succinate-CoA ligase (ADP-forming) (EC 6.2.1.5) beta chain7
 sucD  −0.81 Succinate-CoA ligase (ADP-forming) (EC 6.2.1.5) alpha chain3
 tpiA 0.72    Triosephosphate isomerase (EC 5.3.1.1) (tim)1
 treC0.74 1.68 Trehalose-6-phosphate hydrolase (EC 3.2.1.93) (alpha, alpha-phosphotrehalase)1
 udhA  −1.37 Soluble pyridine nucleotide transhydrogenase1
 yahKG2(up) >1.32 Hypothetical zinc-type alcohol dehydrogenase-like protein2
 (yagR) 1.62  Hypothetical oxidoreductase protein2
 ydbC   −0.94Hypothetical oxidoreductase1
 ydeV   −0.83Hypothetical sugar kinase1
 yfcX 1.84 1.13  Putative fatty oxidation complex alpha subunit (enoyl-CoA: hydratase (EC 4.2.1.17))3
 yibO0.81 0.84 Putative 2,3-bisphosphoglycerate-independent phosphoglycerate mutase (EC 5.4.2.1) (phosphoglyceromutase)3
 yjiY−1.01 −1.54 Carbon starvation protein A homologue0
Environmental, metabolic response
 bolA   −1.29BolA protein4
 cspD   −0.92Cold shock-like protein CspD1
 cspE1.3   CspE protein0
 dnaJ1.01   DnaJ protein, heat shock protein0
 dnaK 0.76   0.87DnaK protein, chaperone Hsp701
 dppA 1.44    Dipeptide-binding protein DppA precursor1
 hslU 1.17    Heat shock protein HslU3
 hslV 1.49    Heat shock protein HslV1
 htpG   0.78Heat shock protein C62.53
 ibpA 1.66    16 kDa heat shock protein A2
 lytB 0.73    Penicillin tolerance protein (lytB), probable metalloproteinase2
 groES 0.94    10 kDa chaperonin (protein CPN10) (protein GroES)1
 osmB   −1.2Lipoprotein OsmB precursor, osmotically inducible1
 rnb1.21   Exoribonuclease II (EC 3.1.13.1) (Ribonuclease II) (RNase II)1
 sfmC 2.54 0.772.420.77Chaperone protein SmfC precursor1
 sulA 1.57 2.071.281.21Cell division inhibitor5
 surA 0.97    Survival protein SurA precursor (peptidyl-prolyl cis-trans isomerase SurA) (EC 5.2.1.8) (PPiase) (rotamase C)1
 yhbU<−1.20   Putative protease (o331)1
 uspB   −1.06Universal stress protein B2
 ybeW  −0.77 Putative chaperone protein HscC4
Fatty acid and phospholipid metabolism
 accC 1.04    Acetyl-CoA carboxylase (EC 6.4.1.2), biotin carboxylase2
 acs   −1.43Acetyl-coenzyme A synthetase (EC 6.2.1.1) (acetate-CoA ligase) (acyl-activating enzyme)1
 envM1.44   Enoyl-[acyl-carrier-protein] reductase (NADH) (EC 1.3.1.9) (NADH-dependent enoyl-acp reductase)0
 fabB 1.04    3-oxoacyl-[acyl-carrier-protein] synthase I (EC 2.3.1.41) (beta-ketoacyl-acp synthase I) (KasI)3
 fabI 1.42    Enoyl-[acyl-carrier-protein] reductase (NADH) (EC 1.3.1.9) (NADH-dependent enoyl-acp reductase)0
 flxA  −1.17 Gene whose expression is dependent on the flagellum-specific sigma factor, FliA, but dispensable for motility development1
 gpsA 0.73     L -Glycerol 3-phosphate dehydrogenase 2
 ybbO 0.79    Hypothetical oxidoreductase (EC 1.-.-.-)0
 ybhO 3.48 0.98  Hypothetical protein2
 yebF 0.93 1.482.23 Hypothetical lipoprotein (ORF122)1
 yefI 0.76  Hypothetical protein2
 yfcY 1 1.01  Probable 3-ketoacyl-CoA thiolase (EC 2.3.1.16)0
Nucleotide metabolism
 add−1.41   Adenosine deaminase (EC 3.5.4.4)2
 adk 1.38    Adenylate kinase (EC 2.7.4.3) (ATP-amp transphosphorylase)4
 apt 1.1   1.15  Adenine phosphoribosyltransferase (EC 2.4.2.7) (AprT)0
 codA 1.24   0.83  Cytosine deaminase (EC 3.5.4.1)2
 gpt 0.92   0.08Xanthine-guanine phosphoribosyltransferase (EC 2.4.2.22) (XgpRT)3
 gsk1.19   Inosine-guanosine kinase (EC 2.7.1.73)2
 guaC 1.68    GMP reductase (EC 1.6.6.8)3
 ndk 1.65    Nucleoside-diphosphate kinase (EC 2.7.4.6)0
 nrdD−1.71   Oxygen-sensitive ribonucleoside-triphosphate reductase (EC 1.17.4.-)1
 prsA1.21 1.13 Ribose-phosphate pyrophosphokinase (EC 2.7.6.1) (phosphoribosyl pyrophosphate synthetase)2
 purB 1.08   0.96  Adenylosuccinate lyase (EC 4.3.2.2)2
 purD  1.5 Phosphoribosylamine-glycine ligase (EC 6.3.4.13)1
 purE2.09 2.04 Phosphoribosylaminoimidazole carboxylase (EC 4.1.1.21) catalytic chain2
 purF  1.81 Amidophosphoribosyltransferase (EC 2.4.2.14) (glutamine phosphoribosylpyrophosphate amidotransferase) (atase)4
 purH  1.4 PurH bifunctional enzyme.1
 purK  1.58 Phosphoribosylaminoimidazole carboxylase ATPase subunit (EC 4.1.1.21) (air carboxylase) (AirC)0
 purT  1.51 Glycinamide ribonucleotide transformylase1
 pyrC1.15   Dihydroorotase (EC 3.5.2.3)1
 upp0.8   Uracil phosphoribosyltransferase (EC 2.4.2.9) (UMP pyrophosphorylase) (uprtase)0
Regulatory functions
 304#1   −0.9Hypothetical transcriptional regulator1
 cpxP0.91  0.78Periplasmic protein precursor1
 fnr 0.93    Fumarate and nitrate reduction regulatory protein.1
 himA   −1.22Integration host factor alpha-subunit (IHF-alpha)/bending2
 hns   −1.27DNA-binding protein H-NS/bending0
 lacI 1.49  0.84 Lac repressor3
 lexA  1.09 LexA repressor (EC 3.4.21.88)2
 relB   −1.41RelB protein1
 relE   −1.24Hypothetical protein1
 ybaO>2.03 2.65 Hypothetical transcriptional regulator6
 ybiH>3.032.162.81 Hypothetical transcriptional regulator2
 yhiW −0.83  Hypothetical transcriptional regulator2
 yjbK  0.94 Regulator protein of zinc uptake system znuABC0
Replication
 dinF  1.51 DNA damage-inducible protein F1
 dinI 1.38 1.481.60.77DNA damage-inducible protein I0
 dskA   −1.01Dosage-dependent DnaK suppressor protein1
 gyrI 0.96  DNA gyrase inhibitory protein0
 holA1.2   DNA-directed DNA polymerase (EC 2.7.7.7) III delta chain5
 mfd 1.19    Transcription-repair coupling protein Mfd2
 prlC 1.21    Primosomal protein ‘n’ precursor0
 recA 1.451.151.04ATP-dependent recombinase1
 recN 1.8 2.011.971.43DNA repair protein RecN (recombination protein n)3
 recR  1.03   Recombination protein RecR3
 ruvA 0.77  0.88 RuvA protein1
 uvrA1.07   Excinuclease ABC subunit A1
Transcription
 deaD0.73  0.96  ATP-dependent RNA helicase1
 nusA0.98   N utilization substance protein A (NusA protein) (l factor)3
 nusB 0.91   0.94N utilization substance protein B (NusB protein)1
 rhlE1.85 1.74 Putative ATP-dependent RNA helicase RhlE0
 yfiA0.96 1.151.2Hypothetical protein (URF1) (ORFS54)2
Translation
 asnS1.03   Asparaginyl-tRNA synthetase (EC 6.1.1.22) (asparagine- tRNA ligase) (asnRS)1
 glnS 0.780.81 Glutaminyl-tRNA synthetase (EC 6.1.1.18) (glutamine- tRNA ligase) (GlnRS)5
 hha   −1.56Osmolarlity effect protein2
 infA   0.78Translation initiation factor IF-11
 infC   0.73Initiation factor IF-31
 rbfA−1.09   Ribosome-binding factor a (p15b protein)3
 rplA1.06   Ribosomal protein L10
 rplE0.74   50S ribosomal protein L50
 rplK0.73   Ribosomal protein L112
 rplM  0.98 Ribosomal protein L132
 rplS0.73   Ribosomal protein l191
 rplW0.71   50S ribosomal protein L235
 rpsO0.94   Ribosomal protein S15.3
 rpsS0.82   Ribosomal protein S191
 rrmA  1.18rRNA(guanine-N1-)-)-methyltransferase2
Transport and binding protein
 agaZ1.02 1.7 Putative tagatose 6-phosphate kinase AgaZ (EC 2.7.1.-)7
 argT   −1.17Lysine-arginine-ornithine-binding periplasmic protein precursor (lao-binding protein)2
 dctA   0.95  DctA protein1
 dppB 0.82    Transmembrane protein DppB3
 dppF 0.95 0.7  Dipeptide transport ATP-binding protein DppF1
 focA2.36  0.72Probable formate transporter3
 ftn0.71   Ferritin4
 glnH 0.83    Glutamine-binding protein precursor1
 gsr   −1.01Phosphotransferase system enzyme II (EC 2.7.1.69), glucose-specific, factor III1
 kgtP   −1.05Alpha-ketoglutarate permease0
 lamB  −2.73 Maltoporin precursor (lambda receptor protein)2
 malE  −2.9 Maltose-binding protein precursor1
 malF  −2.9 Inner membrane protein MalF2
 malG  −1.83 Maltose transport protein MalG5
 malM  −2.12 Maltose operon periplasmic protein precursor0
 malK  −2.59 Maltose/maltodextrin transport ATP-binding protein MalK1
 malP  −1.74 Maltodextrin phosphorylase (EC 2.4.1.1)3
 malS  <−2.53 Alpha-amylase (EC 3.2.1.1) precursor1
 mglB  −2.12  D -galactose-binding protein precursor 2
 malQ  −1.56 4-Alpha-glucanotransferase (EC 2.4.1.25) (amylomaltase) (disproportionating enzyme) (d-enzyme)3
 manX0.830.81.461.04Phosphotransferase system enzyme II (EC 2.7.1.69), mannose-specific, factor III2
 manY  −1.39 Phosphotransferase system enzyme II (EC 2.7.1.69), mannose-specific, factor II-P3
 manZ  −1.56−0.99PTS system, mannose-specific IID component (EIID-Man) (mannose-permease IID component) (phosphotransferase enzyme II, D component) (EII-M-Man)3
 modA0.77 0.85 Molybdate-binding periplasmic protein precursor0
 nagE  −0.98 PTS system, N-acetylglucosamine-specific IIABC component (EIIABC-Nag) (N-acetylglucosamine-permease IIABC component) (phosphotransferase enzyme II, ABC component) (EC 2.7.1.69) (EII-Nag)3
 nanT1.77 2.42 Putative sialic acid transporter5
 nikA−1.63   NikA protein.5
 nupC 0.83    0.74 Nucleoside permease (nucleoside-transport system protein)3
 (potC)   −1.11Spermidine/putrescine transmembrane protein C2
 proX 0.93  Glycine betaine-binding periplasmic protein precursor.4
 ptsH0.81 0.990.76Phosphocarrier protein Hpr (histidine-containing protein).1
 putP 0.94 0.78  Proline carrier protein0
 sapC1.1   Peptide transport system permease protein SapC4
 sapF1.27   Peptide transport system ATP-binding protein1
 sprE   −0.92Putative two-component response regulator1
 srlA 1 0.75  PTS system, glucitol/sorbitol-specific IIBC component (EIIBC-Gut) (glucitol/sorbitol-permease IIBC component) (phosphotransferase enzyme II, BC component) (EC 2.7.1.69) (EII-Gut)2
 treB1.040.871.83 Phosphotransferase system trehalose permease5
 xylF −0.93   D -Xylose-binding periplasmic protein (precursor) 2
 yaaA  −0.83 Putative inner membrane transport protein4
 ybhL 1.41   1.43  Probable transport permease2
 ycjV  −0.9 Hypothetical ABC transporter ATP-binding protein3
 ydeA 1.12   L -Arabinose and IPTG exporter protein 3
 ygfO 1.35  Hypothetical purine permease3
Other categories
 ampG1.22   AmpG protein, regulates beta-lactamase synthesis3
 cinA−1.43   Putative competence-damage protein1
 emrA 1.16  Multidrug-resistant protein EmrA5
 fms   −1.04Polypeptide deformylase (EC 3.5.1.31)0
 intD−1.17   Prophage dLp12 integrase (prophage qsr′ integrase)0
 intE 2.54 >1.62Prophage lambda integrase1
 pqiA1.73 1.76 Paraquat-inducible protein A2
 yjiY1.01 1.57 Carbon starvation protein A homologue0
 yjjW0.76 0.88 Hypothetical protein4
 VXISBPP21  >1.48 Excisionase1
Y genes
 129#5  1.7 Hypothetical protein (o198)2
 334#5.1   −1.35Hypothetical protein0
 356#8 0.94  Hypothetical protein1
 358#3   −0.93Hypothetical protein1
 411#1−1.02   Hypothetical protein3
 421#40.91   Hypothetical protein7
 443#3   −1.74Hypothetical protein1
 467#1 1.29  Hypothetical protein1
 502#6  −1.12 Hypothetical protein1
 576#14   −1.33Hypothetical protein2
 yabP<−0.97   Hypothetical protein1
 yadF 1.15   0.62  Hypothetical protein2
 yadR   −1.22Hypothetical protein (ORF118)1
 yaeH   −0.94Hypothetical protein3
 yahO −1.04 −1.86Hypothetical protein2
 ybaJ   −1.58Hypothetical protein1
 ybaX1.46   Hypothetical protein1
 ybbN 1.29    Hypothetical protein1
 ybcI4.54G2(up)3.11 Hypothetical protein2
 ybdQ−1.27  −1.16Unknown protein from 2-D PAGE (spots pr25/lm16/2d_000lr3)2
 ybeY 0.67   0.81Hypothetical protein2
 ybhN2.58 >1.66 Hypothetical protein7
 ybhO>3.43 >3.45 Hypothetical protein2
 ybiJG2(up)   Hypothetical protein1
 ycdQ 1.74 1.292.63 Hypothetical protein0
 yceD0.85   Hypothetical protein1
 yceP   −1.14Hypothetical protein0
 ycgB   −1.04Hypothetical protein1
 ychF 0.8   0.7  Probable GTP-binding protein (ORF-3)1
 ychH−1.54  −1.51Hypothetical protein (ORF-2)1
 ychM   0.71  Hypothetical protein3
 yciM0.95   Hypothetical protein2
 ycjX1.85   Hypothetical protein1
 ydaA   −0.93Hypothetical protein3
 ydgA   0.92Hypothetical protein (o490)0
 ydhV  −1.77 Hypothetical protein2
 ydiJ 0.9    Hypothetical protein0
 yeaA   1.06Hypothetical protein2
 yeaG   −1.09Hypothetical protein kinase0
 yeaH   −1.02Hypothetical protein2
 yeaR   −1.11Hypothetical protein0
 yebG0.921.31.381.29Hypothetical protein (ORF96)3
 yebK  −0.88 Hypothetical protein1
 (yefJ)   −0.9Hypothetical protein3
 yefM   −0.92Hypothetical protein3
 yfhP0.97   Hypothetical protein0
 yfhT1.1   Hypothetical protein2
 yfjF 0.96    Hypothetical protein (f102)1
 yfiD1.8  0.60Hypothetical protein1
 ygaF   −1.41Hypothetical protein2
 ygfM 1.62  Hypothetical protein0
 ygfP 1.38  Hypothetical protein1
 ygjJ 2.31 1.430.81 Hypothetical protein2
 yhaD  −1.26 Hypothetical protein (ORF3)3
 yhaG  −1.29 Hypothetical protein2
 yhaU  −1.58 Hypothetical protein1
 yhbC0.83   Hypothetical protein2
 yhbE−1.11   Hypothetical protein (f321)0
 yhcH−1.86 −2.41 Hypothetical protein (f154)2
 yhcN   −1.17Hypothetical protein0
 yhgN1.14   0.75 Hypothetical protein1
 yhhA   −1.2Hypothetical protein0
 yhiE −1.45  Hypothetical protein2
 yhjK0.92   Hypothetical protein2
 yhjX<−3.00   Hypothetical protein1
 yidK2.79 >3.34 Hypothetical protein3
 yigB 0.89    Hypothetical protein1
 yihK   1.1  Hypothetical protein2
 yiiD 0.82    Hypothetical protein (o329)1
 yjhA  <−2.81 Hypothetical protein3
 yjhC  −2 Hypothetical protein0
 yjhTG2(down) −2.21 Hypothetical protein1
 yjjI−1.8   Hypothetical protein4
 ykfF  1.72 Hypothetical protein1
 ykgE0.96 0.79 Hypothetical protein2
 yliH   −1.26Hypothetical protein5
 ymfI 1.33 1.25Hypothetical protein1
 ymfJ 1.74 1.71Hypothetical protein2
 ygeW 1.21  Hypothetical protein2
 ygeY 1.42  Hypothetical protein0
 ygeZ 1.39  Hypothetical protein2
 yqaA0.81   Hypothetical protein2
 yqeB 1.52  Hypothetical protein1
 yqfB1.26   0.78 Hypothetical protein1
 yrbL   −1.54Hypothetical protein (o210)1

The dam mutation affects the transcriptional expression of energy metabolism and respiratory enzymes

The genes with altered transcriptional levels included most genes involved in the TCA cycle. Under low aerobic conditions, acnA (aconitate hydratase; underlined genes in the text are listed in Table 1), gltA (citrate synthase) and the sucACD (2-ketoglutarate dehydrogenase, succinyl-CoA synthetase(α,β)) operon were transcribed at lower levels in the dam mutant than in the wild type (Table 1). Furthermore, under aerobic conditions, the expression levels of the aceBA operon (whose operon is controlled by global regulators IHF, IclR and FadR; Resnik et al., 1996) and fumA were increased in the dam mutant. In addition, several TCA-related genes (e.g. sdhCDB, sucAB and lpdA) were also moderately upregulated in the dam mutant under aerobic conditions (data not shown, see our web site http://ecoli.aist-nara.ac.jp/xp_analysis/ dam/all.html). Thus, in normal E. coli grown in aerobic conditions, the cellular levels of TCA cycle enzymes are directly or indirectly negatively controlled at the transcriptional level by GATC methylation, whereas in low aerobic conditions, the expression is positively regulated.

Also affected by the dam mutation was the regulation of genes involved in sugar metabolism and degradation (araC and the srlEABDgutM–srlRQ operon, whose transcription is controlled by CRP and ppsA), the degradation of phospholipid (fadB and yfcX, whose transcription is controlled by CRP, see Fig. 4) and the metabolism of carbohydrates (mhpE and mhpR) as, under aerobic conditions, the transcription of these genes was increased in the dam mutant. In contrast, in dam mutant cells grown to log phase under aerobic conditions, the transcription of several respiratory enzyme genes, especially related to anaerobic respiration, was decreased. These genes included dmsA and frdB (whose synthesis is controlled by Fnr), the nirBDC operon (encoding anaerobic reductase), the nap operon napFDAGHBC (encoding periplasmic nitrate reductase), the narGHJI operon (encoding the major membrane-bound nitrate reductase) and the narK and Z genes, which encode the nitrate transport protein and the alpha-chain of respiratory nitrate reductase 2 respectively. The nar operon is controlled by Fnr or NarL (Li et al., 1994). Furthermore, several genes of anaerobic respiration-related genes were also moderately down-regulated in a dam mutant under low aerobic conditions (e.g. narG, narJ and narZ; data not shown). It suggested that the expression of anaerobic respiration-related genes were decreased in the dam mutant.

image

Figure 4. Genes found to be differentially regulated in KK46 and KK335 and that have a documented or putative CRP or Fnr binding site that overlaps with GATC sequences. ORFs of genes (operons) are represented as boxed arrows. The 400 bp upstream of each ORF are represented by a straight line. Intervals of 50 bp are indicated by vertical lines. Black arrows identify the documented transcriptional start sites. Open arrows identify the putative transcriptional start sites (data obtained from NCBI). Open boxes indicate documented or putative CRP binding sites (GTGANNNNNNTCAC, allowing for a 1 bp mismatch). Filled boxes indicate documented or putative Fnr binding sites (TTGANNNNNNTCAA; allowing for a 1 bp mismatch). Open/filled boxes indicate putative CRP and/or Fnr binding sites. Arrowheads on the open or closed boxes indicate GATC sites within the CRP or Fnr binding sites respectively. CRP or Fnr binding sites of genes written in bold letters have been documented to be CRP or Fnr binding sites ( Li et al., 1994 ; Basby and Kolb, 1996 ). If recognition sequences were predicted to be present in the 400–500 bp upstream, the 3′ position of these recognition sequences is shown at the relevant bp number.

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Several of the genes were upregulated by transcription in the dam mutant grown in both aerobic and low aerobic conditions. These genes include yahK (hypothetical zinc-type alcohol dehydrogenase), citE (citrate lyase alpha chain), mhpE (4-hydroxy-2-oxovalerate aldolase) and ppsA (phosphoenolpyruvate synthase, whose expression is positively regulated by FruR). In contrast, transcription of the gatABCDRYZ operon, whose products convert galactitol to dihydroxyacetone-P and glyceraldehyde-3-P (PTS system), was downregulated in the mutant strain in aerobic and low aerobic conditions.

These observations together suggest that Dam-dependent transcriptional control may participate in energy metabolism and respiration by regulating the control of global regulators.

The dam mutation affects the transcription of genes involved in cofactor biosynthesis and metabolism of amino acids, fatty acids phospholipids and nucleotides

In log phase dam mutant bacteria grown in aerobic conditions, the transcription of several genes involved in amino acid metabolism was elevated. These genes include avtA, the dadA,X cluster, the hisGDC operon, ltaA, putA and the thrABC operon. The transcription of several other genes was also elevated in these conditions. These included entE involved in enterobactin synthesis, the genes encoding pantothenate synthase (panD and C cluster) and genes participating in riboflavin synthesis (ribD and H cluster). Transcription of genes involved in lipid (accC, fabB and I) and phosphatidic acid (gpsA) biosynthesis was also increased, as was transcription of genes concerned with purine salvage and interconversion (apt, gpt, gst and guaC) and pyrimidine or purine biosynthesis (adk, codA, ndk, prsA and pyrC). Thus, Dam appears to be involved in the transcriptional regulation of many metabolic pathways.

Notably, in log phase mutant bacteria grown under aerobic and/or low aerobic conditions, transcription of several genes involved in purine nucleotide synthesis was increased. These changes included purEK, purHD, purB, purF and purT. All these pur genes contain common operator sequences (ACGCAAACGTTTGCGT) and are included in the pur regulon that is regulated by PurR. However, although the transcription of these individual pur genes was increased in the mutant bacteria, the transcriptional levels of purR did not differ between the dam mutant and the wild-type cells grown in equivalent conditions (data not shown). Thus, how Dam regulates the genes contained in the pur regulon is unclear.

The dam mutation constitutively affects the transcription of genes involved in environmental stress response

The transcriptional activity of genes encoding the heat shock proteins and carrying an rpoH (which encodes a heat shock-specific sigma factor in E. coli)-dependent promoter (dnaK, dnaJ, hslU, hslV, htpG, ibpA, groES and groEL, Table 1 and our web site) were all upregulated in the dam mutant grown in aerobic conditions. However, the transcriptome analysis revealed no significant differences in rpoH expression levels between the two strains (data not shown). This suggests that some significant stress suffered by the dam mutant has led to the accumulation of a heat shock sigma factor, sigma 32, by transcriptional activation or stabilization. The transcript levels of several other environmental response genes (cspE, dppA, lytB, rnb, sfmC and surA) were also increased in the dam mutant. It is known that the dam mutant has an elevated expression of SOS-related genes such as recA, lexA, uvrAB, uvrD, sulA, dinF and dinD (Peterson et al., 1985), and we also observed an increase in the transcription levels of many of these genes (dinI, dinF, dinD, lexA, recA, recN, ruvA, sulA, uvrA and yebG; Oh and Kim, 1999) in the dam mutant under both aerobic and low aerobic conditions (Table 1 and our web site). Why the dam mutant appears to be responding to some constitutively present stress, regardless of environmental conditions, is not clear. One possibility is that GATC sequences are targets for restriction and that, in the Dam mutant, lack of methylation of these sequences might expose GATC-bearing sequences to abnormal restriction (Marinus, 2000). This may in turn lead to a constitutive induction of the SOS response in the dam mutant that bears no relation to the environmental conditions. Our data are consistent with this model.

Recently, the transcriptional profile of E. coli cells treated with hydrogen peroxide was examined by DNA microarray analysis (Zheng et al., 2001). Hydrogen peroxide was found to induce the transcription, in an OxyR-independent manner, of a number of genes, including heat shock genes (groEL, groES, dnaK and htpG), SOS response genes (recA, recN, lexA and dinD), a TCA cycle-related gene (fumA), a cysteine metabolism gene (cysK) and the nrd operon (nrdF). In contrast, the expression of many ribosomal protein genes was repressed. With regard to the dam mutant, when the cells were grown under aerobic conditions and harvested during the log phase, the transcription of the genes identified by Zheng et al. (2001) followed a similar pattern to that for the hydrogen peroxide-treated E. coli (Table 1 and our web site). This also suggests that the dam mutant suffers some kind of constitutive stress, even when it is grown under favourable aerobic conditions.

The dam mutation affects the transcriptional expression of genes involved in periplasmic binding protein-dependent transporters

The transcript level of the dppBCEF operon, whose products form the periplasmic-binding protein-dependent (BPD) transport system, is increased in the dam mutant under aerobic conditions. Under low aerobic conditions, the expression levels of genes involved in the maltose BPD transport system (the malEFG and the malKlamBmalM operons) and involved in change to glucose and glucose 1-phosphate from maltose and maltodextrin (the malPQ operon and malS) were decreased in the dam mutant (Table 1). The transport system is essential to the utilization of maltose and maltodextrins in E. coli. We found that the intergenic region between the divergently transcribed malK and malE, F and G genes contains multiple binding sites for CRP and MalT overlapping with Dam methylation sites (Fig. 4).

The expression level of genes involved in carbohydrate phosphotransferase systems [manXYZ and nagE, which are negatively regulated by CRP and NagC (Plumbridge and Kolb, 1991) and gsr, treB and ptsH, which are positively controlled by CRP (De Reuse and Danchin, 1991)] were also decreased in the dam mutant under low aerobic conditions (Table 1). In addition, under aerobic and/or low aerobic conditions, genes concerned with the uptake and metabolism of iron, molybdenum and nickel (fnt, modA and nikA) were downregulated in the dam mutant. Intracellular transport genes (argT, focA, nanT, narK and yaaA) were also downregulated in the dam mutant. The transcription of both focA and nikA is positively regulated by Fnr. Our observations suggest that these genes are regulated by global regulators (CRP, Fnr, MalT and NagC) and Dam via the methylation state of the regulatory region.

Dam regulates the respiratory- and motility-associated gene expression that allows E. coli to adapt to low aerobic conditions

As described above, the expression of respiratory genes, especially nitrate reductase, was markedly reduced in the dam mutant. Thus, these enzymes may be positively controlled directly or indirectly at the transcriptional level by Dam methylase. Our observations also suggest the intriguing possibility that the methylation of GATC sequences is an integral part of the system used by E. coli to adapt to environmental changes, in particular to changes in the levels of oxygen and nitrate, which are the final acceptors in the respiratory chain.

One normal response made by E. coli to low oxygen levels is taxis. Taxis is the movement of E. coli cells growing in a limited supply of oxygen and various ligands to an environment that has more optimal oxygen and ligand concentrations. The low oxygen concentrations elicit the expression of motility and chemotaxis genes (Jones et al., 1992) when methyl-accepting chemotaxis proteins (Aer, Tar, Tsr, Tap and Trg) sense signals that consist of oxygen levels, redox potential, light and external ligands. These signals are then transmitted to cytoplasmic signal transduction proteins (CheA, CheB, CheR, CheW, CheY and CheZ) and affect the motility of E. coli by inducing taxis (Taylor and Zhulin, 1998; Taylor et al., 1999). Alternative acceptors in the respiratory chain, such as nitrate, can also elicit an aerotaxis-like behaviour by substituting for oxygen as an electron acceptor (Taylor et al., 1979; Taylor and Zhulin, 1998). Flagellar, motility and chemotaxis genes are known to form clusters in four distinct regions on the chromosome, namely in regions I (24 min), II (41 min), IIIa and IIIb (43 min) (Macnab, 1996). When the dam strain was grown under low aerobic conditions, its expression of most genes located specifically in region II (tartapcheRBYZ operon, motABcheAW operon) and region IIIa (fliC) was significantly lower than in the wild-type cells (Table 1). It suggests that Dam is involved in regulating taxis under low aerobic conditions and that the dam mutant might be defective in taxis under these conditions.

These changes in the dam mutant cell suggest that its motility may differ from that of the wild-type strain, and thus we tested the motility of both strains. The wild-type strain (FB8) shows normal motility, but the isogenic dam mutant (FB8 dam-16::kam) strain did not move normally (Fig. 1). Confirming that dam is involved, the dam mutant complemented by plasmid pCAdam+ showed normal motility (Fig. 1), whereas the dam mutant carrying the pCA24N plasmid, which is the vector system used for archiving all the E. coli ORFs (Mori et al., 2000), did not move normally. These results were also observed in the MG1655, KK46 (W3110 derivative strain) and their isogenic dam mutant strains (data not shown), although the native motility of KK46 was less than that of the FB8 and MG1655 strains. Thus, loss of dam activity generated a defective motility phenotype.

image

Figure 1. Motility of the wild-type strain FB8, the FB8 dam -16:: kam mutant, FB8 dam -16:: kam containing plasmid pCA24N and FB8 dam -16:: kam containing plasmid pCAdam + . Fresh overnight cultures of each strain (1 μl) were spotted onto a semi-solid agar plate, incubated at 30°C for 6 h and photographed. The segregation frequency, whereby the plasmid-bearing cells lost the plasmid during growth, was very low, as the frequency of plasmid-loss cells among the total population was only <0.5% after 50 generations.

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Poor motility may be responsible for the lack of invasiveness by the S. typhimurium dam mutant

The dam mutant of S. typhimurium was recently reported to be defective in cell invasion and virulence (Garcia Del Portillo et al., 1999; Heithoff et al., 1999), indicating the importance of Dam in regulating these activities. However, the crucial virulence/invasion genes being modulated by Dam in S. typhimurium were not identified. As motility-negative mutant strains of S. typhimurium are also non-invasive (Liu et al., 1988; Jones et al., 1992), it may be that Dam-regulated motility genes are important in virulence/invasion. This notion is supported by our parallel observations made with E. coli. We showed that, in the dam mutant of E. coli grown under low aerobic conditions, the expression of certain chemotaxis-related genes (tar, tap, cheA, cheY, motA and motB) is significantly lower than in the wild type (Table 1). The motility of the dam mutant was also less than that of wild type (Fig. 1). Given the close sequence similarities between S. typhimurium and E. coli, it is quite possible that the dam-specific expression profile of the E. coli dam mutant may also occur in the dam mutant of S. typhimurium, supporting the notion that poor motility may be responsible for the poor invasiveness of the dam mutant of S. typhimurium.

Results obtained with Northern hybridization and DNA microarray methods are comparable

We assessed whether the results obtained with the DNA microarray method could be reproduced using another method for detecting mRNA, i.e. Northern hybridization. Thus, the wild-type and the dam mutant strains were cultured under aerobic and low aerobic conditions and harvested at log phase. Total RNA was prepared from the cell extract of each strain and separated by gel electro-phoresis. The blotted membrane was then hybridized with several labelled probes. For examining gene expression in aerobic conditions, DNAs of the sdhC (the sdh–suc operon), aceB (the aceAB operon), gutM (the srl–gut operon) and npl were amplified by polymerase chain reaction (PCR) and labelled with [32P]-dCTP. For examining gene expression in low aerobic conditions, motA (the motAB operon) probes were made and labelled. The hybridized membranes are shown in Fig. 2 and indicate that the transcription levels of these genes as measured by the DNA microarray method are consistent with those measured by Northern hybridization.

image

Figure 2. Comparison of the mRNA levels of five genes in the KK46 and KK335 strains measured by Northern blot and microarray analyses.

A. Northern blot analysis of the motAB operon was performed using RNA prepared twice from KK46 and KK335 (dam-16::kam) grown in low aerobic conditions. The KK335/KK46 mRNA ratios for both genes were calculated from data obtained by the Northern blot and microarray analyses and are shown to the left of the data. The same RNA preparations were used for both methods.

B. Northern blot analysis of the sdh–suc operon, the aceBA operon, the srl–gut operon and npl was performed using RNA prepared from KK46 and KK335 (dam-16::kam) grown in aerobic conditions. The KK335/KK46 mRNA ratios were calculated as in (A) and are shown to the left of the data. The relative ratios of microarray data for each gene were taken from http://ecoli.aist-nara.ac.jp/xp_analysis/dam/all.html. Each relative ratio represents the mean of four independent microarray data.

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Two-dimensional gel electrophoresis of proteins from the Δdam mutant supports the microarray analysis

To examine the expression levels of the proteins encoded by the genes whose transcription was significantly altered in the dam mutant, we carried out proteome analysis by radical-free and highly reducing two-dimensional polyacrylamide gel electrophoresis (RFHR 2-D PAGE) (Wada, 1986). We examined the proteins fractionated from wild-type and dam mutant cells growing at log and stationary phases under aerobic and low aerobic conditions. As expected from the microarray assays, products of genes involved in a number of cellular functions were present at higher levels in the dam strain grown under aerobic conditions compared with similarly grown wild-type cells (Table 2A and B, Fig. 3). These categories included energy metabolism (atpG, frdA, gapA, lpdA, mdh), translation (fusA, glnS, infC, ppiB, tufA), cell envelope (ompF, yeaF, uncD), amino acid metabolism (ansB, glyA), nucleotide metabolism (adk, deoC, guaA, guaB) and stress response (dnaK, fkpA, groEL, tig). In addition, the accumulation of the oxidative stress-responsive gene product SodA, the nucleoid protein H-NS and HlpA and the OppA, RbsB, IpyR and YrbC proteins were clearly observed in the dam mutant at the stationary phase. These data strongly suggest that the expression of TCA cycle-related enzymes, as well as GuaA, ImdH and DeoC, which participate in the purine and pyrimidine salvage pathway, is modulated by Dam (see microarray results described above). This analysis also revealed that gene products involved in the translational machinery and the chaperone system for protein folding and transport are more highly expressed in the dam mutant than in the wild type grown under aerobic conditions (Table 2A and B, Fig. 3). On the other hand, EF-G, GatY and ModA in the log phase and OmpW in the stationary phase were decreased in the dam mutant, although we could find no biological meaning for this downregulation at present (Table 2A and B).

Table 2. Summary of proteome analyses of the dam mutant strain under aerobic and low aerobic conditions.
ProteinGeneDescriptionFunctional classificationaProteinb KK335/KK46cDNAc KK335/KK46No. ofd GATC sites
  • a.

    The proteins are classified into biological functional categories modified from Riley and Labedan, 1996 ).

  • b.   Ratios of amounts of protein, KK335( dam -16:: kam )/KK46( dam + ), were analysed by RFHR 2-D PAGE.

  • c.   Ratios of amounts of cDNA, KK335( dam -16:: kam )/KK46( dam + ), were analysed by DNA microarrays (see Experimental procedures for microarray).

  • d.

    Number of GATC sequences on 500 bp upstream region from the first base of ORF start site.

  • Proteins whose expression was significantly enhanced or decreased in the dam mutant are listed: ratios of amounts of protein, KK335 (dam-16::kam)/KK46(dam+). >1.3 or <0.7 at log and stationary phase are listed. The ratios obtained by DNA microarray analysis under the same conditions are shown for comparison.

A. Log phase (aerobic condition)
Asg2 ansB Asparaginase II precursorAmino acid metabolism1.40.42
OmpF ompF Outer membrane protein F precursorCell envelope1.50.81
YeaF YeaF Scaffolding protein for murein-synthesising holoenzymeCell envelope1.31.91
GatY gatY Tagatose-bisphosphate aldolaseEnergy metabolism0.70.41
SodA sodA Superoxide dismutaseEnvironmental response1.311
GuaA guaA GMP synthaseNucleotide metabolism1.41.31
ImdH imdH IMP dehydrogenaseNucleotide metabolism1.51.13
OppA oppA Periplasmic oligopeptide-binding proteinProtein/peptide secretion1.41.31
EF-G fusA Elongation factor GTranslation0.40.81
Syq glnS Glutaminyl-tRNA synthetaseTranslation1.41.85
ModA modA Molybdate-binding periplasmic protein precursorTransport/binding protein0.70.50
RbsB rbsB D -ribose-binding periplasmic protein precursor Transport/binding protein1.31.64
B. Stationary phase (aerobic condition)
Asg2 ansB Asparaginase II precursorAmino acid metabolism1.41.32
GlyA glyA Serine hydroxymethyltransferaseAmino acid metabolism1.411
AtpB uncD H+ transporting ATP synthase beta chainCell envelope1.81.34
OmpW ompW Outer membrane protein WCell envelope0.70.63
YeaF yeaF Scaffolding protein for murein-synthesizing holoenzymeCell envelope5.80.91
IpyR ppa Inorganic pyrophosphataseCentral intermediary metabolism1.40.81
AptG aptG ATP synthase gamma chainEnergy metabolism2.51.63
DldH IpdA Dihydrolipoamide dehydrogenaseEnergy metabolism2.81.91
FrdA frdA Fumarate reductase flavoprotein subunitEnergy metabolism1.31.44
G3P1 gapA Glyceraldehyde-3-phosphate dehydrogenase AEnergy metabolism3.50.92
Mdh Mdh Malate dehydrogenaseEnergy metabolism1.31.20
DnaK dnaK DnaK proteinEnvironmental response1.90.91
FkpA fkpA Fkbp-type peptidyl-prodyl cis-trans isomeraseEnvironmental response1.71.32
GroEL groEL GroEL proteinEnvironmental response3.91.25
SodA sodA Superoxide dismutaseEnvironmental response1.30.81
Tig tig Trigger factorEnvironmental response1.71.20
DeoC deoC Deoxyribose-phosphate aldolaseNucleotide metabolism1.31.62
GuaA guaA GMP synthaseNucleotide metabolism1.70.91
ImdH guaB Imp dehydrogenaseNucleotide metabolism1.90.83
Kad adK Adenylate kinaseNucleotide metabolism1.41.94
OppA oppA Periplasmic oligopeptide-binding proteinProtein/peptide secretion1.51.21
HlpA hlpA Histone-like protein Hlp-1 precursorRegulatory function1.51.53
H-NS hns DNA binding proteinRegulatory function1.80.70
CypB ppiB Peptidylprolyl isomeraseTranslation1.71.25
EF-G fusA Elongation factor GTranslation2.40.91
EF-TU tufA Translation elongation factor EF-TU.ATranslation2.41.52
If3 infC Initiation factor IF-3Translation1.40.61
Syq glnS Glutaminyl-tRNA synthetaseTranslation1.71.35
RbsB rbsB D -ribose-binding periplasmic protein precursor Protein/peptide secretion1.91.54
YrbC yrbC Hypothetical proteinUnknown1.50.91
C. Log phase (low aerobic condition)
Otc2 argF Ornithine carnoyltransferase (EC 2.1.3.3) chain FAmino acid metabolism2.41.21
GlyA glyA Serine hydroxymethyltransferaseAmino acid metabolism1.71.21
IpyR ppa Inorganic pyrophosphataseCentral intermediary metabolism3.811
AtpB atpD H+ transporting ATP synthase beta chainCell envelope1.41.34
OmpW ompW Outer membrane protein WCell envelope1.30.73
Alf fba Fructose-bisphosphate aldolaseEnergy metabolism3.10.70
FrdA frdA Fumalate reductaseEnergy metabolism0.414
G3pI gapA Glyceraldehyde-3-phosphate dehydrogenaseEnergy metabolism1.60.72
GatY gatY Tagatose-bisphosphate aldolaseEnergy metabolism0.60.21
GlpD glpD Glycerol-3-phosphate dehydrogenaseEnergy metabolism2.91.12
Pgk pgk Phosphoglycerate kinaseEnergy metabolism3.00.74
TpiS tpiA Triosephosphate isomeraseEnergy metabolism2.20.91
DegP htrA Heat shock protein protease Do precursorEnvironmental response0.40.60
DnaK dnaK DnaK protein, chaperone Hsp70Environmental response2.90.71
DppA dppA Dipeptide-binding proteinEnvironmental response2.90.71
GroEL groEL Chaperonin Hsp60Environmental response3.80.65
HlpA hlpA Histone-like proteinRegulatory function1.60.93
DeaD deaD ATP-dependent RNA helicaseTranscription3.92.71
RhlE rhlE Putative ATP-dependent RNA helicase RhlETranscription1.95.80
Rho rho Transcription termination factor GTranscription1.70.62
EF-G fusA Elongation factor GTranslation4.11.41
RL10 rplJ Ribosomal protein L10Translation1.81.50
Rrf rrf Ribosomal recycling factorTranslation1.61.22
RS1 rpsA 30S ribosomal protein S1Translation2.91.92
RS3 rpsC 30S ribosomal protein S3Translation2.31.63
OppA oppA Periplasmic oligopeptide-binding proteinTransport/binding protein1.61.01
ProP proP Proline/betaine transport proteinTransport/binding protein1.91.41
RbsB rbsB D -ribose-binding periplasmic protein precursor Transport/binding protein1.81.41
YajQ yajQ Hypothetical proteinUnknown1.31.44
YbeJ ybeJ Amino-acid ABC transporter binding proteinUnknown2.50.92
YdgH 313 # 2 Hypothetical proteinUnknown1.81.11
D. Stationary phase (low aerobic condition)
MotA motA Chemotaxis protein MotACell envelope0.41.71
OmpC ompC Outer membrane c precursorCell envelope3.20.60
Alf fba Fructose-bisphosphate aldolaseEnergy metabolism0.30.70
Eno eno EnolaseEnergy metabolism0.50.63
G3P1 gapA Glyceraldehyde-3-phosphate dehydrogenase AEnergy metabolism0.30.62
GatY gatY Tagatose-bisphosphate aldolaseEnergy metabolism0.20.51
ODP1 ace Pyruvate dehydrogenase el componentEnergy metabolism0.40.90
PflB pflB Formate c-acetyltransferaseEnergy metabolism0.40.52
Pgk pgk Phosphoglycerate kinaseEnergy metabolism0.10.94
TpiS tpiA Triosephosphate isomeraseEnergy metabolism0.71.01
DnaK dnaK DnaK protein, chaperone Hsp70Environmental response0.50.41
DnaJ dnaJ DnaJ protein, chaperone Hsp40Environmental response0.50.70
GroEL groEL Chaperonin Hsp60Environmental response0.70.85
SodA sodA Superoxide dismutaseEnvironmental response0.20.61
Dps dps DNA binding proteinRegulatory function0.50.50
RS1 rpsA 30S ribosomal protein S1Translation1.50.52
OppA oppA Periplasmic oligopeptide-binding proteinTransport/binding protein1.60.81
PthP ptsH Phosphocarrier protein HprTransport/binding protein0.60.51
SR54 ffh Signal recognition particle proteinTransport/binding protein0.20.71
YajQ yajQ HypotheticalUnknown1.70.64
image

Figure 3. RFHR 2-D PAGE (proteome) analysis of proteins in KK46 and KK335 ( dam -16:: kam ) grown to the log or stationary phase. The bacterial samples from KK46 and KK335 ( dam -16:: kam ) grown in L broth under aerobic conditions were fractionated and analysed by two-dimensional electrophoresis. The two-dimensional patterns with PRS (post-ribosomal supernatant), CD (crude debris) and CR (crude ribosome) fractions are presented in (A), (B) and (C) respectively. Arrows indicate proteins that were detected in increased quantities (ratio >1.3) in KK335 ( dam -16:: kam ) compared with the wild type. A summary of this analysis is presented in Table 2A and B . There was no significant difference between KK335 ( dam -16:: kam ) and the wild-type strains in the two-dimensional pattern of CR at log phase (data not shown). The two-dimensional experiments were repeated at least three times, and these patterns were confirmed to be reproducible. The data from one such representative experiment are shown.

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When the dam mutant was grown under low aerobic conditions and harvested at log phase, the levels of proteins encoded by genes involved in energy metabolism (fba, gapA, glpD, tpiA), stress response (dnaK, dppA, groEL), transcription (deaD, rhlE, rho), translation (fusA, rplJ, rrf, rpsA, rpsC) and transport/binding protein (proP, rbsB, oppA, ybeJ) were increased (Table 2C). On the other hand, when dam cells were grown in low aerobic conditions and harvested in the stationary phase, the protein products of genes involved in energy metabolism (tpiA, gapA, pgk, eno, fba, gatY, ace, pflB) were decreased. Similarly, proteins involved in stress response (dnaK, dnaJ, groEL, sodA), the transport/binding protein (ptsH, ffh) and the DNA-binding protein (dps) were also present in lower amounts in the dam mutant (Table 2D). The levels of many ribosomal proteins were also decreased (data not shown).

In general, the observations made with the two-dimensional analysis were consistent with those arising from the microarray analysis.

GATC sites and the cis-elements of global regulators overlap in the promoters of genes affected by Dam deficiency

The previously published computational analysis of the GATC sequences in part of the E. coli genome revealed that many GATC sequences overlap with consensus Fnr and/or CRP binding sites (Henaut et al., 1996). We thus examined the genes affected by the dam mutation that we identified in our microarray analysis for the presence of GATC sites that overlap with documented or predicted Fnr and/or CRP binding sites. In many cases, an overlap was observed, indicating that the transcription of these genes may be directly regulated by Dam-mediated DNA methylation that modulates the activity of transcriptional regulators (Fig. 4). However, GATCs were not found within the recognition sequences for transcriptional regulators in some cases, suggesting that dam-mediated regulation of some genes in E. coli may also occur through indirect mechanisms.

Conclusions

Dam methylase is found in a limited number of Proteobacteria species, namely the gamma subdivision, which includes E. coli and S. typhimurium. Dam-mediated methylation is known to be responsible for regulating metabolism, invasion, replication and mismatch repair in E. coli (Marinus, 1996; 2000; Garcia Del Portillo et al., 1999; Heithoff et al., 1999). In addition, DNA methylation of the oriC region by Dam is indispensable for the regulation of DNA replication and the organization of daughter chromosome separation. Interestingly, two other proteins that, like Dam, exist only in E. coli and related bacteria, also play an important role in the positioning of daughter chromosomes, namely SeqA, which binds to hemimethylated GATC sequences, and MukB (Hiraga et al., 2000). The methylation of GATC by Dam may thus constitute a unique and important system that regulates biological function in some bacteria.

Our DNA microarray and two-dimensional electro-phoretic analyses suggest that energy metabolism and the stress response are activated inappropriately in the dam-deficient mutant grown in aerobic conditions. These findings strongly suggest that at least one of the functions of Dam is the negative regulation of energy metabolism under aerobic conditions. In contrast, the expression of taxis-related and nitrate reductase genes was decreased in the dam mutant grown in low aerobic conditions. It thus appears that energy synthesis in the dam mutant is insufficient, especially in low aerobic conditions. These observations together suggest that Dam might properly regulate the balance of energy synthesis according to the aerobic/anaerobic conditions.

We also observed that transcription of motility genes was poor in the dam mutant, and functional studies confirmed that this mutant indeed had poor motility. Given that motility-deficient and dam-deficient S. typhimurium mutants are both poorly invasive, our observations with the closely related E. coli support the notion that the low invasiveness of the S. typhimurium dam mutant may result from its poor motility.

One mechanism by which Dam regulates the transcription of the genes affected in the dam mutant is by methylating sites within transcriptional regulators, thus modulating their activity (Fig. 4). However, as GATC sequences were not found to coincide with transcriptional regulator recognition sequences in the promoter regions of some genes, it appears that dam-mediated regulation may also occur through indirect mechanisms.

That the regulation of fundamental cellular activities such as energy metabolism and the oxidative stress response is Dam dependent suggests that further analysis of the mechanism by which Dam regulates transcription will provide important clues about how E. coli and related bacteria respond to environmental change.

Experimental procedures

  1. Top of page
  2. Summary
  3. Introduction
  4. Results and discussion
  5. Experimental procedures
  6. Acknowledgements
  7. References

Bacterial strains, plasmids, media and growth conditions

Isogenic bacterial strains derived from the E. coli K-12 strain were used. The wild-type strain is denoted as KK46 (YK1100: trpC9941) (Yamanaka et al., 1996), and the dam-defective mutant is KK335 (KK46: dam-16::kam). The amount of Dam methyltransferase (MTase) in the mutant dam-16::kam is below the level of detection both in vitro and in vivo (Parker and Marinus, 1988). KK335 is a deletion–insertion mutant that was derived by P1 transduction from KK46 (S. Hiraga, unpublished data). Two other E. coli strains denoted as FB8 and MG1655 were used for motility assays (see below). Their dam-16::kam-deficient isogenic mutant strains were also constructed by P1 transduction. Several plasmids, namely pCA24N and pCAdam+, were used for complementation analysis of the low motility phenotype of the dam mutant FB8 and MG1655 strains. pCAdam+ was constructed by NotI digestion and self-ligation from the dam+ archive clones (Mori et al., 2000), and its sequence was confirmed by DNA sequencing analysis. All cultures were grown in Luria–Bertani (LB) medium. Overnight cultures were diluted 500-fold with fresh LB medium and cultured further. Cells were grown to the log (OD600 = 0.4) or stationary phase (time 5–9 h) in either aerobic (5 h) or low aerobic conditions (9 h). Four independent cultures for each growth phase–aerobicity combination were harvested. Aerobic cultures were grown at 37°C in 1 l flasks containing 200 ml of medium that was reciprocally shaken at 170 r.p.m. Low aerobic cultures were grown in the same conditions except that they were in a 300 ml flask containing 200 ml of LB broth and under rotary shaking. The concentration of dissolved oxygen (DO) in the culture medium was monitored during cell culture using an OM-12 DO meter (Horiba). The DO (3.2 mg l−1) of cultures grown to log phase under aerobic conditions was about five times higher than that in the log phase under low aerobic conditions (DO 0.63 mg l−1). However, the DO (0.23 mg l−1) of the aerobic culture grown to stationary phase was very similar to the DO (0.29 mg l−1) of cultures grown to stationary phase in low aerobic conditions.

RNA isolation

Preparation of total RNA from crude cell lysate was performed using a modified hot phenol method (Aiba, 1985). Briefly, cells were harvested by centrifugation at 12 000 g for 2 min at room temperature, resuspended in 0.5 ml of solution A (0.5% SDS, 20 mM sodium acetate, 10 mM EDTA) and then mixed by pipetting with 0.5 ml of acidic phenol (pH 5.5) preheated at 60°C. The mixture was incubated at 60°C for 5 min. After centrifugation at 12 000 r.p.m. for 3 min at room temperature, the supernatant was recovered. This extraction process was repeated. A phenol–chloroform (1:1, pH 5.5) extraction was then performed, and the RNA was precipitated by the addition of three volumes of ethanol. The RNA pellet was dried and dissolved in a DNase solution (100 mM sodium acetate, 50 mM MgSO4) containing 5 units of RNase-free DNase (Takara), and incubated at room temperature for 1 h. A second phenol–chloroform extraction and RNA precipitation were then performed. Purified total RNA was subjected to 1% agarose gel electrophoresis to check for degradation and whether the 23S and 16S ribosomal RNA were recovered without contamination of genomic DNA. The prepared RNAs were used for both microarray and Northern blot analyses.

Preparation of DNA microarrays

We used custom-made high-density microarrays of DNA molecules on glass slides that had been prepared by the Takara Shuzo Company. The array contains the 4097 independent genes of the E. coli genome that have been cloned previously from the E. coli K-12 W3110 strain, the so-called archive clone (Mori et al., 2000). Each gene on the slide was completely amplified by PCR using vector-specific primers targeting both sites of the integrated gene fragment: primer 1, 5′-ATCACCAT CACCATACGGATCCGGCCCTGA-3′; primer 2, 5′-TTCTTCT CCTTTACTGCGGCCGCATAGGCC-3′.

The PCR-amplified fragments contained the DNA region spanning from the second to the last codon of all genes in E. coli. The DNA concentration was more than 0.1 mg ml−1. Furthermore, all PCR fragments were confirmed by DNA sequencing. In addition to the genes mentioned above, there were 24 spots of human β-actin gene as a negative control on the slide. Human transferrin receptor gene, E. coli genomic DNA and a fluorescent position marker were spotted as a negative control, a positive control and a positional marker, respectively, to estimate the spotting error. We also checked the accuracy of our microarray using well-characterized mutants. Using four two-component deletion mutants, namely, ΔarcA, ΔarcB, ΔompR–envZ and ΔrssB, the DNA microarray analyses indicated, as expected, upregulation of the TCA cycle genes in the ΔarcA and ΔarcB mutants, downregulation of the ompFC transcript in the ΔompR–envZ mutant and increased transcription of rpoS-dependent genes in the ΔrssB mutant (T. Oshima, H. Aiba, Y. Masuda, S. Kanaya, B. L. Wanner, H. Mori and T. Mizuno, submitted). The accuracy of our microarray was also verified by the fact that our observations regarding SOS gene induction in the dam mutant coincided with those reported previously (Peterson et al., 1985). The microarray of the E. coli genome is now available from Takara Shuzo.

Fluorescent-labelled cDNA preparation, array hybridization and the capture of data

The preparation of fluorescent-labelled cDNA using Cy3 and Cy5, and microarray hybridization were performed essentially according to the M guide (http://cmgm.stanford.edu/ pbrown/mguide/index.html; DeRisi et al., 1997). Fluorescent-labelled cDNA probes were prepared by random priming methods. Reverse transcriptase reactions were performed by AMVXL (XL Life Science) and 4 nmol of either Cy3-dUTP or Cy5-dUTP (Amersham Pharmacia) using the total RNA from KK46 or KK335 (dam-16::kam) grown in the four conditions as templates respectively. Labelled cDNA probes were purified by Centri-sep (Princeton Separations), phenol– chloroform extraction and ethanol precipitation. After drying, the cDNA probe was dissolved in 9 μl of water. Both Cy3- and Cy5-labelled cDNA probes were then added to a final volume of 23 μl of hybridization buffer (4× SSC, 0.2% SDS, 5× Denhardt's solution, 100 ng ml−1 salmon sperm DNA) and denatured by heating at 98°C for 2 min. The denatured cDNA probe was applied to the microarray prehybridized by 100 ng ml−1 salmon sperm DNA under a coverslip. Hybridization was carried out at 65°C for 16 h. Slides were washed at 60°C with 2× SSC for 5 min, then at 60°C with 0.2× SSC containing 0.1% SDS and, finally, at room temperature with 0.2× SSC. The slides were scanned for fluorescent intensity using a GMS 418 array scanner (Genetic Microsystems) and recorded to 16 bit image files. The signal density of each spot in the microarray was quantified using IMAGENE software (BioDiscovery). Two independently obtained mRNA preparations of cells at each growth phase–aerobicity combination were tested. Each preparation was then tested twice by microarray analysis. Thus, the values shown in Table 1 are the mean of the four independently obtained data per gene (spot).

Data analysis of microarrays

To distinguish reliable data from the background, we corrected each spot for the local background by subtracting the local background from the intensity of each spot. In addition, a mean value of the intensity of the 24 negative control spots (human β-actin gene) was determined, together with a standard deviation (SD). Each spot or gene, now represented by a corrected signal intensity, was then classified into three groups according to the relative expression of the gene in the wild type and the dam mutant. Group 1 consisted of genes in which both the Cy3 (wild type) and Cy5 (mutant) signal intensities were greater than the mean +1 SD of the negative controls. Group 2 consisted of spots in which either, but not both, the Cy3 and Cy5 signal intensities were greater than the mean +1 SD of the negative controls. Group 3 consisted of spots in which both Cy3 and Cy5 signal intensities were lower than the mean +1 SD of the negative controls. We then normalized the intensity of all spots in group 1. This was done by calculating, for each spot in group 1, the following ratio: mRNA level from KK335 (dam-16::kam) labelled by Cy5/mRNA level from KK46 labelled by Cy3. Initially, all group 1 spots were normalized by defining the mean of ratios (Cy5/Cy3) of all spots as 1.0. The ratio of the group 2 spots could not be determined because of the lack of either a Cy3 or a Cy5 fluorescent signal. Spots in this group with high Cy3 or Cy5 intensity (over 1000, i.e. of a sufficiently high intensity value to be detected precisely by the GMS 418 array scanner) were considered to represent altered expression levels in the dam mutant relative to the wild-type strain. Spots in group 3 were considered to be undetectable spots. The expression profiles of KK335 (dam-16::kam) were compared with those of the KK46 strain in two ways. (i) To ensure that the observed transcript alterations were really caused by the dam mutant, we first assessed the degree of random fluctuation and systematic biases inherent in our system. Cy5- and Cy3-labelled probes were simultaneously synthesized from the same template RNA purified from the wild-type strain, and their intensities were compared with each other. Reproducible twofold increases and decreases were observed in a few genes. We judged these alterations to be artificial errors and, as such, systematic biases. However, when KK46 and KK335 (dam-16::kam) were compared, reproducible twofold increases and decreases were observed in more than 90 genes. These changes are considerably more frequent than those resulting from systematic biases. On the basis of these observations, we recognized spots to represent a significant alteration in transcription in the mutant compared with the wild type when the following conditions were fulfilled for the four independent data obtained for each gene: for group 1 spots, if the KK335 Cy5/KK46 Cy3 ratio was reproducibly less than 0.5, indicating a negative fold difference, or reproducibly more than 2.0, indicating a positive fold difference; for group 2 spots (a) if the Cy3 signal exceeded the high-intensity cut-off (>1000), whereas the Cy5 signal showed no significant intensity, indicating a higher transcript level in the wild type, or (b) if the Cy5 signal exceeded the high-intensity cut-off, whereas the Cy3 signal showed no significant intensity, indicating a higher transcript level in the mutant. This method was used to judge the expression alteration of all genes included in groups 1 and 2. (ii) The second method used to locate significant differences in the transcript levels of each gene in the mutant was by more statistical methods. This could be done only with the group 1 genes. We calculated the consistency of the differential expression in the four data obtained per gene (two separate RNA preparations obtained from each strain were tested twice, thus yielding four independent spots per gene) using Wilcoxon signed rank test on the PYTHON program. Thus, spots with a significantly (P < 0.01) lower (<0.5, i.e. a negative fold difference) or higher (>2, i.e. a positive fold difference) KK335 Cy5/KK46 Cy3 ratio were considered to be real differences.

To estimate the reproducibility of the independently performed experiments, we calculated Pearson's correlation coefficient for the two experiments performed with each of the two mRNA preparations by assessing the total gene expression profiles obtained with the same growth phase– aerobicity combination (i.e. aerobic log, aerobic stationary, low aerobic log and low aerobic stationary) (these data can be found at http://ecoli.aist-nara.ac.jp/xp_analysis/dam/ overlaps.html). If the expression profiles between two independent experiments per experimental condition are similar, one would expect a high correlation coefficient. Indeed, a high value was obtained for three of the four growth con-ditions (aerobic log, 0.45; aerobic stationary, 0.55; low aerobic log, 0.70). In addition, the value was moderate but still significant for low aerobic stationary conditions (0.24). Thus, the microarray data in this analysis appear to be reproducible.

For each growth condition, the number of genes that could be included in groups 1 and 2 after one hybridization exceeded 2400 (> about 60% of the total spotted genes on the slide). When the four individual hybridizations were examined, transcript profiles of more than 90 genes (that is at least 2% of total genes) were found to be reproducibly and significantly altered in the mutant strain. These data are available on our web site at http://ecoli. aist-nara.ac.jp/xp_analysis/dam/.

Northern blot analysis

The analysis was performed using specific probes essentially as described previously (Ito et al., 1993). Total RNA was prepared as described above and separated using 1.0% agarose gel electrophoresis with formamide and transferred to a Hybond-N+ membrane (Amersham Pharmacia). All DNA fragments used for this analysis were amplified by PCR using ORF-specific primers (see http://ecoli.aist-nara.ac.jp/ PRIMER/index.html). The DNA probes were labelled with [32P]-dCTP (Amersham Pharmacia) by a random priming kit (Takara). The blotted membrane was hybridized with each labelled probe, washed, dried and visualized with a Fuji bioimaging analyser (BAS2000, Fuji).

Motility analysis

Overnight cultures of cells were spotted onto semi-solid agar plates containing 0.8% nutrient broth (Difco), 8% gelatin (Wako, Japan) and 0.4% agarose (Difco). The plates were incubated at 30°C for 6 h and photographed.

Proteome analysis by RFHR 2-D PAGE

Escherichia coli were grown under the same aerobic conditions used for the microarray analysis. An aliquot of 400 ml of cells was collected in the cold at log phase and at stationary phase grown under aerobic and low aerobic conditions. Cell growth was stopped by ice and azide (final 0.01 M). About 1.0–1.2 g of wet cells was suspended in 1.5 ml of buffer 1 [100 mM CH 3COONH4, 15 mM (CH3COO)2Mg, 20 mM Tris-HCl, pH 7.6, 6 mM β-mercaptoethanol, and 0.5 mM phenylmethylsulphonyl fluoride (PMSF)], sonicated for 15 min at 20 kHz with 50% duty cycle (on for 7.5 s then off for 7.5 s) (Bioruptor UCD-200TM, Cosmo Bio) in the cold and then centrifuged for 10 min at 900 g. The supernatant (sup) was centrifuged for a further 20 min at 10 000 g. The pellet (ppt) arising from this latter centrifugation was resuspended in 2 ml of buffer 1, centrifuged for 20 min at 10 000 g and then homogenized in 0.5–0.7 ml of buffer 1. This fraction was defined as ‘CD’. The sup after centrifugation for 20 min at 10 000 g was centrifuged further for 180 min at 100 000 g. The sup was defined as ‘PRS’, and the ppt was resuspended in 0.5 ml of buffer 1 and centrifuged for 10 min at 17 000 g. The sup was defined as ‘CR’.

The PRS, CD and CR fractions were resuspended in a solution of 67% acetic acid and 33 mM MgCl2 and centrifuged for 10 min at 10 000 g. The ppts were resuspended in the same buffer, and the elution procedure was repeated. The two sups obtained after this were combined and desalted by Sephadex G-25 (Medium). The samples were then lyophilized. Lyophilized protein (≈ 1–2 mg per gel) was analysed by RFHR 2-D PAGE essentially as described previously (Wada, 1986; see http://www.osaka-med.ac.jp/ ~yhide/index.htm), except that the volume of glacial acetic acid used in the sample charging buffer (50×) was 7.4 ml, not 74 ml, and a gel thickness of 2 mm was used to improve the resolution.

After RFHR 2-D PAGE, the gels were stained with CBB (Coomassie brilliant blue R250) to visualize the proteins. The protein spots were measured by Personal Densitometer S1 (Molecular Dynamic Japan), quantified using IMAGEQUANT (Molecular Dynamic Japan), and the density of the protein spots in the wild-type strain was compared with that of the dam strain. Protein spots that were increased in the dam strain compared with the wild-type strain were identified by the gene–protein index for RFHR 2-D PAGE (http://ecoli.aist-nara.ac.jp/docs/GB4/search/proteome/index.html). The spots not included in the gene–protein index were identified by peptide sequencing or matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Briefly, this meant that, after the RFHR 2-D PAGE, either proteins were blotted to a polyvinylidene difluoride (PVDF) membrane for determination of N-terminus amino acid sequences using a Shimazu PPSQ-23 peptide sequencer or the protein spots were digested in proteinase (Endoproteinase LysC) for MALDI-TOF MS analyses (Voyager DETMPRO, Applied Biosystems).

The density of each protein was normalized by the control proteins, molecular weight markers (molecular weight 2512–16949, Amersham Pharmacia Biotech) and the internal proteins, which showed very little difference in density between the wild-type strain and the dam strain. We used two or three proteins as control proteins in each gel but obtained equivalent results. We isolated two to four independent protein preparations and tested the protein preparations from each growing condition three to six times on 2-D PAGE. Reproducibly and significantly altered spots were selected. The density of each protein in the mutant was related to the wild-type protein density by expressing the two values as a ratio (KK335/KK46). Table 2 indicates selected proteins whose ratio of the relative density of protein from KK335 (dam-16::kam) relative to that of the wild-type strain exceeds 1.3.

Software analysis

The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database (Kanehisa and Goto, 2000) was used to analyse the Dam-regulated biological cascade. GENESPRING version 3.0 (Silicon Genetics) was used to locate CRP and Fnr recognition sequences, to discover where GATC sequences overlap with these recognition sequences and to perform statistical analysis. Statistical analyses were also performed by EXCEL 2000 and the PYTHON program.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Results and discussion
  5. Experimental procedures
  6. Acknowledgements
  7. References

We thank M. Kitagawa, T. Nakamichi-Ioka, E. Inamoto, H. Toyonaga and S. Kanata for the E. coli clone bank essential for the construction of DNA microarray, E. Boye for the dam mutant strain, G. Kobayashi and A. Wada for proteome analysis, M. Ueta for laboratory supplies, M. Kitagawa and T. Horiuchi for helpful discussions, and T. Yura for warm support and critical reading of the manuscript. This work was supported by the CREST programme of Japan Science and Technology and Grants-in-Aid for Scientific Research on Priority Areas, ‘Genome Science’ from the Ministry of Education, Science, Sports and Culture of Japan.

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