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1 Swiss Federal Institute for Environmental Science and Technology, PO Box 611, Überlandstrasse 133, CH-8600 Dübendorf, Switzerland
2 Empa, Swiss Federal Institute for Materials Testing and Technology, Lerchenfeldstrasse 5, CH-9014 St Gallen, Switzerland
3 Istituto Cantonale di Microbiologia, Via Mirasole 22A, CH-6500 Bellinzona, Switzerland
4 Department of Biology, University of Genova, Corso Europa 26 V piano, 16132 Genova, Italy
5 Genomic Research Laboratory, University Hospitals of Geneva, rue Micheli-du-Crest 24, CH-1211 Geneva 14, Switzerland
6 VIDO – Vaccine & Infectious Diseases Organization, University of Saskatchewan, 120 Veterinary Road, Saskatoon, SK S7N 5E3, Canada
Correspondence
Thomas Egli
egli{at}eawag.ch
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Microarray data, design and oligonucleotide sequences GEO DataSets accession nos are GSE6407, GSE6486 and GPL4618.
The raw DNA microarray data of this and other studies and the genomic DNA labelling protocol are available with the online version of this paper.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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; Lan & Reeves, 2000; Ochman et al., 2000). In fact, natural isolates of Escherichia coli vary in their chromosome length between 4500 and 5500 kb (Bergthorsson & Ochman, 1998), which is thought to mainly result from incorporation of foreign DNA and gene deletion events (Dobrindt et al., 2003). The standard laboratory E. coli K-12 strain MG1655 is estimated to contain up to 18 % of horizontally acquired DNA (Lawrence & Ochman, 1998) and only 70 % of all predicted MG1655 proteins are shared with both of the fully sequenced pathogenic E. coli strains, CFT073 and EDL933 (Welch et al., 2002). Phenotypic variations in LPS structure, fimbriae, capsular antigens, utilization of certain sugars, antibiotic resistance and more are common to natural isolates of E. coli (Selander et al., 1996) and are suggested to reflect adaptations to specific hosts or even to different ecological niches (Reeves, 1992; Dobrindt et al., 2004). In the case of various E. coli pathotypes, horizontally acquired genomic regions (pathogenicity islands) carry the crucial traits for leading a parasitic life-style (Hacker & Kaper, 2000; Perna et al., 2001; Welch et al., 2002).
This contrasts with numerous physiological characteristics not involved in pathogenicity, which are highly conserved in all or at least in an overwhelming majority of E. coli strains, e.g. lactose, maltose and galactose utilization, β-glucuronidase activity, resistance to bile salts, ability to grow at 44 °C, mixed acid fermentation, etc. (Bettelheim, 1992). Indeed, these common characteristics allow a reliable identification of E. coli by classical means (Holt, 1994). The large number of shared phenotypic traits is consistent with a large amount of shared DNA sequences constituting the so-called core (or backbone) genome of E. coli (Welch et al., 2002; Anjum et al., 2003; Dobrindt et al., 2003).
The question of how conserved or how variable physiological properties and other characteristics of E. coli are is further complicated by the rapid emergence of sequence polymorphisms in laboratory evolution experiments. These genetic changes can lead to drastically enhanced fitness (Ks) under glucose-limited growth conditions (Senn et al., 1994; Notley-McRobb & Ferenci, 1999a, b; Wick et al., 2001), but also to a decrease in stress resistance (Chen et al., 2004; Notley-McRobb et al., 2002; Zinser & Kolter, 1999) or to an inactivation of catabolic functions (Cooper & Lenski, 2000).
The normal life cycle of E. coli consists of two phases: (i) growth in the primary habitat, the mammalian large intestine, and (ii) survival in the secondary habitat, water and soil, until a new host can be colonized (Savageau, 1983). Both habitats are predominantly carbon- and energy-limited and specific growth rates fluctuate between a small fraction of µmax to negative (die-off) for most of the time (Freter et al., 1983a; Savageau, 1983; Macfarlane & Macfarlane, 1997). E. coli MG1655 adapts to carbon and energy limitation by complex physiological changes that confer a high degree of catabolic flexibility, the capacity for mixed substrate growth and efficient carbon substrate uptake abilities to the cells (Wick et al., 2001; Ihssen & Egli, 2005; Liu et al., 2005). At the same time, slow-growing or growth-arrested E. coli protect themselves against oxidative cellular deterioration and environmental stresses by expressing various protective proteins, many of which are regulated by the alternative sigma factor RpoS (reviewed by Hengge-Aronis, 1996; Matin, 2004; Nyström, 2004).
If mixed-substrate growth, high-affinity transport and stress defence functions are crucial fitness determinants for the species E. coli in its primary and secondary habitats, they should not be subject to variation among strains, i.e. they should be part of the core genome. Therefore, we analysed four sets of comparative genomic hybridization (CGH) data for the presence and absence of known MG1655: (i) catabolic operons, (ii) operons encoding binding protein-dependent ATP-driven transporters or phosphotransferase systems for carbon substrates, and (iii) stress defence operons. In addition, intraspecies variability of the physiological adaptation to carbon- and energy-limited growth and starvation was determined by comparing growth kinetic parameters, RpoS phenotype, derepression of catabolic pathways and expression of high-affinity binding proteins of six environmental E. coli isolates with MG1655. Both CGH and physiological results indicate that numerous ecologically relevant properties of E. coli are highly conserved and may result from a long-term adaptation of this species to its current niche.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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. Six strains originated from raw source water (RSW) of drinking water catchments in northern Switzerland (WK1–WK8). Based on phenotypic differences (Table 2), they were selected from a total of 45 strains isolated during routine screening. Standard E. coli diagnostic agar plates were used for screening and isolation. The 19 faecal strains (Table 1) were isolated from stool samples of healthy adult humans and domestic animals in southern and south-western Switzerland.
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). Antibiotic resistance was tested on LB agar plates amended with antibiotics and confirmed for WK1–WK8 in liquid culture. Faecal strains were isolated from healthy human and animal hosts from Geneva and Ticino (south western and south eastern Switzerland), respectively. Antibiotic resistance determination for these strains was performed by the disk diffusion method. Transfers of isolates on laboratory growth media were generally kept as low as possible (maximally three transfers on complex medium agar before storage at –80 °C). Siderophore excretion of the RSW strains was evaluated according to the size and intensity of orange haloes formed around the bacterial colonies grown on blue agar plates containing chrome azurol S (CAS plates) after incubation for 12 h at 37 °C (Schwyn & Neilands, 1987). For analysis of colicin production, the strains were streaked onto LB plates. After incubation for 12 h at 37 °C, the cells were killed by treatment with chloroform vapour for 30 min and then exposed to air for 1 h. The plates were then overlaid with LB soft agar (0.5 % agar; Difco) containing a sensitive E. coli K-12 strain at 106 c.f.u. ml–1 (Ölschläger et al., 1984). After incubation for 12 h at 37 °C, growth inhibition zones in the lawn of the indicator strain were analysed. For investigation of haemolysin production, strains were streaked onto sheep blood agar plates and grown for 24–48 h at 37 °C as described in Beutin et al. (1989). Clearing zones around colonies were indicative of haemolysin production.
DNA microarrays.
The genome composition of the RSW isolates was analysed by CGH using commercially available E. coli K-12 V2 microarrays (MWG Biotech). The arrays contained all ORFs of E. coli MG1655 (Blattner et al., 1997). Microarrays were hybridized according to the manufacturer's instructions with fluorescently labelled genomic DNA of the reference strain MG1655 and of environmental strains. Total genomic DNA was extracted from stationary phase LB cultures with a genomic DNA purification kit (Fermentas), followed by random hexamer-primed labelling with Cy3-dCTP or Cy5-dCTP (Amersham Biosciences). In each reaction, 2 µg unsheared genomic DNA was labelled with the BioPrime labelling kit (Invitrogen) according to the protocol of DeRisi (Anjum et al., 2003). After labelling, Cy3- and Cy5-cDNA were combined and co-purified on MinElute PCR purification columns (Qiagen). For each strain two arrays were hybridized with individually labelled DNA derived from two separate overnight LB cultures. The processed slides were scanned with an Affimetrix 428 array scanner. Fluorescent spots and local background intensities were quantified with Affimetrix Jaguar software version 2 and analysed further in Microsoft Excel. Very few spots had a Cy3 signal for the reference strain which was lower than the background signal intensity plus two standard deviations of background intensity. They were excluded from further analysis as suggested by Anjum et al. (2003). For each array, Cy5 intensities of all spots were normalized to the median of Cy3 intensities. This procedure resulted in Cy3 : Cy5 ratios of approximately one for the majority of spots, which means that labelled target DNA from both the reference and the environmental strain hybridized. Similarly to what has been reported for signal intensity ratios of known gene deletions in laboratory strains (Anjum et al., 2003), certain spots were clear positive outliers. Negative outliers (which would indicate missing genes in our MG1655 strain) were not detected. A cut-off value of 1.6 for logarithmic Cy5 : Cy3 ratios (fivefold difference in signal intensity) was chosen as threshold for missing genes, because this value was more than two times the positive range of background variation (Anjum et al., 2003, used a cut-off value of 2.0). Two arrays hybridized with genomic DNA of the same strain yielded similar patterns of missing ORFs, with only a few contradictory results; those were excluded from further analysis. Microarray data for the RSW isolates are available in the GEO online database (www.ncbi.nlm.nih.gov/projects/geo/index.cgi) with series accession no. GSE6407.
The 19 faecal strains were analysed using an in-house-designed oligoarray (Charbonnier et al., 2005). A set of 2700 oligonucleotide probes covering 63 % of the ORFs of the E. coli K-12 chromosome was synthesized using the SurePrint technology (Agilent Technologies). Further details of array design and oligonucleotide sequences can be found in the GEO DataSets under the accession no. GPL4618. In CGH experiments, Cy3-dCTP-labelled K-12 genomic DNA and Cy5-dCTP-labelled DNA of a test strain were heated to 95 °C for 2 min, and then hybridized for 17 h at 60 °C with rotation in a dedicated hybridization oven (Robbins Scientific). Stringent washes were then performed according to the manufacturer's instructions. Slides were dried under nitrogen flow and scanned using 100 % photon multiplier tube power for both wavelengths with the Agilent scanner. Fluorescence intensities were extracted using the Feature extraction software (version 6.1.1; Agilent). Local background-subtracted signals were corrected for unequal dye incorporation or unequal load of the labelled product. The algorithm consisted of a rank consistency filter and a curve fit using the default LOWESS (locally weighted linear regression) method. The background noise of each experiment was evaluated by computing the standard deviation of negative-control intensities. Features whose intensities were smaller than the standard deviation value of the negative controls were considered as inefficient hybridization and discarded from further analysis. For each spot, the logarithm of the ratio between the test channel and the control channel (log ratio) was computed. Computed log ratio values were further sorted into 150 bin categories and fitted with a Gaussian distribution curve, using the Levenberg–Marquardt algorithm. The presence probability of each oligonucleotide probe (EPP) was determined, as described by Kim's algorithm (Kim et al., 2002). Thus, the probability of presence was estimated for each ORF, allowing assessment of the presence or the divergence of genes in relation to K-12 genes. Genes that were either absent or sufficiently different to be hindered from hybridizing to the related oligonucleotide probes were defined as divergent. The most divergent genes (458), which failed to be detected in 25 % of the tested strains, were considered here as missing. Microarray data for the faecal strains are available in the GEO DataSets with series accession no. GSE6486.
Analysis of CGH datasets.
Four sets of CGH datasets where total genomic DNA of E. coli strains was hybridized to E. coli MG1655 arrays were analysed in this study: (i) 5 isolates from raw source water (RSW, Tables 1
and 2), (ii) 19 faecal isolates from human and animal hosts (Faecal, Table 1), (iii) 6 commensal strains plus the laboratory strain E. coli B (Dobrindt et al., 2003) and (iv) 26 pathogenic strains (Anjum et al., 2003). The lists of missing and present MG1655 ORFs were analysed for genes known to encode catabolic, transport, stress protection and global regulatory functions. Substrate-specific catabolic and transport genes and stress defence genes were compiled from Lin (1996), McFall & Newman (1996), Berlyn (1998), Wick & Egli (2004) and the online databases KEGG (Kanehisa & Goto, 2000) and EcoCyc (Keseler et al., 2005). The presence/absence CGH datasets are available as supplementary material with the online version of this paper.
Determination of growth kinetic parameters, growth substrate range and catabolic flexibility in glucose-limited chemostat cultures.
Glucose-limited mineral media and cultivation conditions were described previously (Ihssen & Egli, 2004). Maximum specific growth rates in glucose mineral medium (µmax,Glc) were determined in triplicate in magnetically stirred flasks at 37 °C. Transfers on LB and mineral medium were kept as few as possible. Glucose affinities (Ks,Glc) and growth yields for glucose were determined in carbon-limited chemostat cultures after 20 h of cultivation (for details see Ihssen & Egli, 2004). The growth substrate spectrum of environmental E. coli strains and K-12 MG1655 was analysed with Biolog AN MicroPlates, which contain 95 different carbon and energy sources. Plates were inoculated in triplicate with cells grown overnight on TSA agar plates and resuspended in carbon-source-free mineral medium to an OD546 of 0.1. Microplates were incubated for 30 h at 37 °C before A460 was measured with a microplate reader. Wells with an A460 above 0.4 were counted as growth-positive (background A460 of control wells was between 0.13 and 0.17). Expression of alternative catabolic pathways in glucose batch and glucose-limited chemostat cultures was determined with a previously described Biolog respiration assay using chloramphenicol-inhibited cells (Ihssen & Egli, 2005). Wild-type E. coli K-12 MG 1655 used as reference laboratory strain was the same as described previously (Wick et al., 2001).
Hydroperoxidase assay, analysis of periplasmic proteins and RpoS-immunoblot.
RpoS-dependent hydroperoxidase II specific activities were determined spectrophotometrically with crude cell extracts (Ihssen & Egli, 2004; Visick & Clarke, 1997). Periplasmic proteins were extracted by chloroform shock treatment (Ames et al., 1984) and analysed by SDS-PAGE. For details of sample preparation, electrophoresis and protein identification see Ihssen & Egli (2005). RpoS protein levels were determined by immunoblot analysis (Ihssen & Egli, 2004) after extraction of total cellular proteins by TCA precipitation (Lange & Hengge-Aronis, 1994). Immunoblot loading volumes were normalized to the respective average band intensity of total proteins on Coomassie-stained control SDS-PAGE gels. Relative band intensities on SDS-PAGE gels and immunoblots were quantified with the publicly available software ImageJ (http://rsb.info.nih.gov/ij/download.html).
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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), i.e. they can hypothetically be subject to deletions or truncations by genome rearrangements and horizontal gene transfer (HGT). However, the incidence of missing MG1655 catabolic genes was very low both in commensal and pathogenic strains (Tables 3 and 4). Only the atoCDAEB operon, required for the degradation of C4 fatty acids, and the glutamate-catabolism-related hypothetical regulatory protein gltF were missing consistently in a high percentage of strains. There were no systematic differences in the genome content of MG1655 catabolic and stress defence genes between environmental, faecal and pathogenic strains, and we also found no systematic differences between strains of different ECOR groups. In general, commensal strains predominantly belong to ECOR groups A and B1, while pathogenic strains are found mostly in ECOR groups B2 and D (Clermont et al., 2000; Dobrindt et al., 2003). The strains isolated from RSW were all classified as ECOR group A (Table 1) and therefore are most likely commensals. The majority of faecal isolates from humans also belonged to group A (Table 1). In contrast, 67 % of isolates from cats, dogs, cattle and swine fell into the pathogenic groups B2 and D (Table 1).
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). The corresponding substrate-specific genes were present in all RSW strains. In the other datasets included in the CGH analysis, a limited number of these genes were recorded as absent in a low proportion of strains (Table 3).
Table 4 lists catabolic operons for substrates that do not, or only in a subset of E. coli strains, support growth in mineral medium. Surprisingly, our CGH data analysis indicated that the respective catabolic operons are nevertheless highly conserved in the E. coli population (Table 4). For example, in spite of the fact that dulcitol supported growth of only 50 % of the RSW isolates, the gatRDCBAZY operon was present in all of these strains (Table 4). Similarly, although E. coli generally lacks the ability to utilize cellobiose (Lin, 1996; compare also second column of Table 4), the celFDCBA operon, which is also present on the MG1655 genome, was detected in more than 95 % of the strains (Table 4).
Efficient substrate uptake most likely is a key fitness determinant in bacteria. Phosphotransferase systems are the most efficient uptake systems of E. coli under anoxic conditions (Manché et al., 1999), whereas binding-protein-dependent, ATP-driven (ABC) transporters allow E. coli to scavenge trace amounts of carbon substrates during aerobic growth (Ferenci, 2001). Operons encoding either type of transport system were only in rare cases (mostly partially) missing from the strains analysed (Tables 3 and 4).
Complex global gene regulation mechanisms have evolved in bacteria which respond rapidly to environmental stimuli. In E. coli, most catabolic operons are part of the cAMP-CRP global regulatory network (e.g. the operons for maltose, ribose and arabinose utilization). The genes encoding the key regulatory proteins of the cAMP-CRP network, the cya (adenylate cyclase) and crp (cAMP receptor protein) genes were present in all RSW, Faecal, Commensal and PEC strains (data not shown). In accordance with known physiological characteristics of E. coli, operons needed for mixed acid fermentation and fumarate respiration (adhE, adhP, hycIHGFEDCBA, fdhF, frdDCBA, pta, ackA, poxB, ldhA, mdh, fumCA, fumB, tdcEDCBAR) and the respective global regulators (fur, arcA, arcB) exhibited a very low frequency of gene deletions (data not shown).
CGH analysis of stress defence functions
Protection against desiccation, acid stress, oxidative stress, starvation and other adverse conditions is a prerequisite for the cycling of E. coli between hosts. Therefore, we screened the four CGH datasets for missing or variable stress defence functions. The frequency of missing genes known to encode protective functions was very low in the 57 strains analysed (Table 5). The majority of genes shown in Table 5 are positively regulated by the general stress response sigma factor RpoS (Ishihama, 2000; Loewen et al., 1998). The rpoS gene itself, as well as the genes for the heat shock and envelope stress sigma factors (rpoH, rpoE), showed no variability at all on MG1655 microarrays. One gene for the synthesis of the reserve material glycogen (glgS) was variably absent and present; however, the other glycogen synthetase (glgA) was detected in all strains (Table 5).
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). On average, 5.7 % of all MG1655 translatable ORFs spotted on the MWG arrays were absent in the RSW strains (range 4.5–6.9 %). In the 19 faecal isolates, 1.3–17.5 % of MG1655 ORFs were missing (average 7.8 %, median 6.5 %). This corresponds well with an average of 5.8 % MG1655 ORFs missing in 23 pathogenic and commensal E. coli strains (Dobrindt et al., 2003).
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) (Anjum et al., 2003). Most of the missing MG1655 ORFs encoded genes of hypothetical or unknown function. Only three operons with catabolic or transport functions were part of the deletion hot spots, a hypothetical D-allose phosphotransferase system (yjcVWX), the catabolic operon for C4-fatty acids (atoCDAEB) and an Fe(III)-dicitrate uptake system including a TonB-dependent outer membrane receptor and an ABC transporter (fecIRABCDE). Also found on frequently missing DNA stretches were the mcr and hsr operons involved in DNA restriction, the LPS synthesis operons wbb and rfb, the hof operon encoding a type II secretion system and the idn operon involved in sugar acid metabolism. LPS composition is known to vary strongly between E. coli strains and has been associated with HGT.
Physiological characteristics of environmental isolates in comparison to E. coli MG1655
Intraspecies genomic variation and a proposed trade-off between self-protection and nutritional competence (King et al., 2004) can theoretically result in a substantial variation in nutritional versatility, in the RpoS phenotype and in growth kinetic parameters of environmental E. coli. However, the RSW isolates varied little from one another and from MG1655 in these physiological characteristics, in spite of clear phenotypic differences in antibiotic resistance, siderophore excretion and haemolysin or colicin production (Tables 1 and 2). The latter functions are predominantly encoded on mobile genetic elements such as plasmids, transposons and integrons.
The substrate spectrum of source water isolates analysed with Biolog AN MicroPlates exhibited some variation, but did not differ significantly from that of E. coli MG1655 (data not shown). The total number of growth-supporting substrates was rather similar and showed no obvious negative correlation with the expression of stress defence functions (Table 6). Variation in the raffinose, dulcitol and sucrose phenotypes (Table 3) is consistent with published data for E. coli isolates (Durso et al., 2004; Holt, 1994; Miller & Hartl, 1986). Raffinose and sucrose are two of the few catabolic genes that are easily transferred between E. coli strains (Smith & Parsell, 1975). For other substrates, mutational silencing may have led to variation between strains. However, some of the phenotype variability, especially with regard to amino acids, may be an artefact, because these substrates supported in general only weak growth; also with the ‘negative’ strains, there was usually some colour formation observed, although it did not pass the (arbitrary) threshold of 0.4 A460 for recording growth as positive. MG1655 cells grown in complex medium dissimilate ‘growth negative’ substrates such as L-serine at high rates (Ihssen & Egli, 2005). In the natural habitats of E. coli, amino acids are always a part of substrate mixtures.
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). At a fixed specific growth rate of 0.3 h–1, intracellular RpoS concentrations varied by a factor of approximately six (Table 6) and the RpoS level of MG1655 was in the upper third of the observed range (Table 6). For unknown reasons, hydroperoxidase II (HPII) specific activity in the different strains did not correlate well with relative RpoS levels (Table 6), although HPII is a good indicator for RpoS levels in MG1655 when growing at different specific growth rates (Ihssen & Egli, 2004). Similarly to RpoS levels, HPII specific activity of MG1655 was present at a level comparable to that of environmental strains (Table 6). All RSW isolates exhibited both heat-stable HPII (KatE) and heat-labile HPI (KatG) catalase activity (data not shown), which is consistent with CGH data for the corresponding genes (Table 5).
Glucose affinities of the RSW isolates differed by a factor of four at the most. Surprisingly, some of the environmental strains exhibited a considerably lower affinity for glucose (Ks,Glc) than wild-type E. coli MG1655 (Table 5). Judged from the capacity of MG1655 to dramatically improve its Ks,Glc more than tenfold down to 50 µg l–1 within 200 generations in glucose-limited chemostat cultures (Wick et al., 2002), neither laboratory nor natural growth environments seem to select for genotypes with high glucose affinity.
RpoS is known to have a negative effect on the expression of high-affinity glucose uptake proteins and thus on Ks,Glc (Notley-McRobb et al., 2002; Wick et al., 2002). Whereas some strains confirmed this correlation, others (WK4 and K12) did not (Table 6). A negative effect of positive antibiotic resistance, siderophore, colicin or haemolysin phenotypes on glucose affinity was not detected (Tables 1, 2 and 6). Thus, carriage of the corresponding genetic elements seems not to decrease competitiveness for carbon substrates.
Glucose growth yields of the RSW strains and MG1655 were rather similar (Table 6), which is in agreement with a narrow range of growth yields [0.42–0.47 g dry wt (g glucose)–1, mean 0.45 g dry wt (g glucose)–1] observed in seven natural isolates and one laboratory strain by Mikkola & Kurland (1992). Maximum specific growth rates in glucose mineral medium also showed remarkably little variation, but were in general approximately 20 % higher than the µmax,Glc of MG1655 (Table 6). The reduced µmax,Glc of MG1655 is caused by the rph1 mutation that impairs pyrimidine biosynthesis (Soupene et al., 2003). Other wild-type laboratory strains exhibit µmax,Glc values close to the RSW strains, e.g. 0.78 h–1 and 0.87 h–1 for strains ML 30G and 017, respectively (Mikkola & Kurland, 1992; Shehata & Marr, 1971). In contrast to our findings, Mikkola & Kurland (1992) reported a broad range of (initial) µmax,Glc values from 0.34 to 0.99 h–1 (mean 0.64 h–1) for seven natural E. coli isolates. Except for differences in experimental procedures, we have no explanation for this contradiction. Durso et al. (2004) also reported a low µmax,Glc variability for 41 commensal and 81 pathogenic E. coli strains, but the mean µmax,Glc was significantly lower (0.42 h–1). However, the lower values may have resulted from oxygen limitation in the Biolog microplate wells the strains were cultivated in.
Physiological response of environmental E. coli to glucose limitation
E. coli MG1655 adapts to low concentrations of carbon and energy sources in chemostat cultures by the derepression of diverse catabolic functions and high-affinity binding proteins (Ihssen & Egli, 2005). A very similar physiological response to glucose limitation was observed in environmental isolates. The pattern of derepressed catabolic functions resembled that of MG1655 (Fig. 2). Close similarity was also observed for the pattern of high-affinity binding proteins upregulated in response to glucose limitation (Fig. 3). The upregulation included, as judged from the position of the bands on the gel, DppA (A), MalE (B), MglB (C), RbsB (D) and GlnH (E) in most strains (bands were identified in a previous study with MG1655; Ihssen & Egli, 2005).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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). However, still very little is known about the nutritional preferences of gut bacteria (Peekhaus & Conway, 1998). Experimental evidence suggests that E. coli successfully competes for a variety of carbon and energy sources in the colon because it can establish itself in multi-species anaerobic bioreactors simulating the digestive tract (Freter et al., 1983a, b; Macfarlane et al., 1998).
It has been suggested that the ecologically relevant traits, i.e. the traits crucial for successful competition against other bacterial species, are those found in all strains and not those that are variable (Mason & Richardson, 1981). In this study, a very low level of intraspecies genomic variation in phosphotransferase systems and dissimilatory enzymes for sugars and sugar alcohols was found (Tables 3 and 4). Therefore, we hypothesize that E. coli is specialized on a particular set of fermentable substrates in the gut, mainly monomeric and dimeric sugars, sugar acids and sugar alcohols. The monomeric substrates can be derived either from secreted mucus, e.g. N-acetylglucosamine, galactose, glucuronate (Peekhaus & Conway, 1998), or from polymers degraded by extracellular enzymes of other gut bacteria, e.g. arabinose from pectin, gluconate from muscle tissue and glucose from cellulose. The large arsenal of sugar, sugar acid and sugar alcohol catabolic operons presumably allows E. coli to engage in kinetically favourable mixed-substrate growth (Egli, 1995) and to flexibly react to transient availability of these substrates. In our view, the genomic variation observed in few catabolic functions can hardly reflect the specialization of different E. coli lineages to specific nutritional niches in the colon. Thus, the ‘catabolome’ of the species E. coli seems to be highly conserved.
Conserved adaptation of E. coli to the secondary habitat
When leaving the alimentary tract of the host, E. coli is faced with (i) very low concentrations of carbon and energy substrates, (ii) oxic conditions, (iii) low temperatures, (iv) UV AB and oxidative stress, and (v) osmotic and desiccation stress. In addition, cells must survive severe acid stress in the stomach before being able to colonize a new host. Both CGH and physiological data suggest that the evolutionary adaptation to these challenges is highly conserved in E. coli.
Due to the poor ATP yield per utilized sugar molecule in anaerobically growing E. coli, ATP-consuming binding-protein-dependent ABC transporters presumably are of limited use in the anoxic gut. However, in the predominantly oxic secondary habitat (water and soil), the ability to scavenge trace amounts of carbon substrates with ABC transporters may be one of the most important fitness factors. The presence of all known ABC-transport systems for amino acids and sugars in practically all strains and the very low variability in catabolic operons for organic acids and nucleotides (Tables 3 and 4) suggest that E. coli takes up and metabolizes variable mixtures of minute concentrations of these substrates for maintenance purposes in the secondary habitat.
A drawback of the microarray approach is the neglect of differences caused by more subtle genetic changes (e.g. single nucleotide exchanges, frame shift mutations) in the catabolic gene itself or in regulatory proteins. Thus, strains might differ significantly in catabolic abilities and stress resistance in spite of a ‘similar’ genome composition. At least regarding the six RSW strains and E. coli K-12 MG1655, physiological analysis indicates that expression of the non-variable catabolic and stress defence genes does not vary to a great extent (Table 6, Figs 2 and 3). Particularly, the remarkably consistent pattern of derepressed catabolic pathways and high-affinity binding proteins under glucose-limited growth conditions (Figs 2 and 3) suggests that a carbon source foraging strategy (Liu et al., 2005; Ihssen & Egli, 2005) is a highly conserved (eco-)physiological adaptation of E. coli. Analysis of the proteome under well-defined conditions might give a more detailed picture of differences in gene expression among E. coli isolates, but this is far beyond the scope of this study.
The CGH analysis also suggests that E. coli cannot tolerate much genomic variation in stress defence functions. Especially the highly conserved RpoS-dependent genes (Table 5), which play a key role in the survival of starvation and other stressful conditions (Matin, 1991; Munro et al., 1995; Eisenstark et al., 1996; Booth et al., 2002), might be indispensable for the passage of E. coli through non-host environments to a new intestinal habitat.
Our data do not support the proposed trade-off between catabolic versatility and RpoS-dependent self-protection (King et al., 2004) in natural E. coli populations (Table 6). The trade-off hypothesis is based on observations for one pathogenic and one laboratory strain, which showed very high RpoS/RpoD ratios. The catabolic spectrum of the four other strains used in the latter study (including K-12 MG1655 and two EcoR reference strains) was not improved by an RpoS knockout mutation and these strains had quite similar RpoS/RpoD ratios (King et al., 2004). Presumably, only strains with an extremely strong RpoS phenotype are negatively affected in their catabolic versatility, but such strains are not likely to be widespread in the total E. coli population because they would have a competitive disadvantage in many growth situations. One may speculate that the frequency of strong RpoS phenotypes might be higher among pathogenic E. coli because they may require a more frequent transfer between hosts and do not compete with the intestinal flora for carbon and energy sources. However, the fact that 17.2 % of 58 shiga-like-toxin-producing E. coli were RpoS-attenuated (Waterman & Small, 1996) speaks against a generally strong RpoS phenotype in pathogenic strains. To decide how variable the RpoS phenotype and how broad the range of stress resistance truly is in the natural E. coli population, and how it affects nutritional abilities, more data for commensal and pathogenic isolates are needed.
How important are variable (HGT-related) traits relative to the core genome?
The relative contribution of horizontal gene transfer (HGT) and vertical inheritance to the evolution of bacteria remains fiercely debated (for recent reviews with opposing views see Dagan & William, 2006, Kurland, 2005 and Philippe & Douady, 2003). The numerous prophages found in E. coli genomes (Perna et al., 2001) indicate the widespread occurrence of HGT also in this species. On the one hand, HGT-driven evolution of pathogenic strains (Blum et al., 1994; Hacker & Kaper, 2000) speaks in favour of an adaptation of E. coli to novel niches by horizontal acquisition of foreign genes. On the other hand, evidence for HGT-driven niche specialization of commensal E. coli, which by far outnumber pathotypes in terms of total populations size, is scarce. If one assumes that ecology is metabolism for (non-pathogenic) bacteria (Lawrence, 2001), the high degree of similarity in the genome content of catabolic pathways found in our study indicates that the adaptation of E. coli to its current niche has been dominated by vertical inheritance. Whether the lac operon, which once was proposed as a paradigmatic example of niche adaptation by HGT (Ochman et al., 2000), counts as counter evidence is questionable, because strong doubts have been raised whether the lac operon ever was transferred laterally into E. coli (Stoebel, 2004).
Horizontally transferred properties like the ability to produce colicins, O-antigen composition, fimbriae and capsules may nevertheless contribute to strain substitutions and differential persistence in the colon (Gordon et al., 1998; Nowrouzian et al., 2006). In an in vivo experimental study though, no positive effect of fimbriae or adhesin plasmids on the persistence of particular strains in the human digestive tract was found (Smith & Huggins, 1978). Further ecological studies are needed to clarify the role of HGT-acquired genes in the competition between different commensal E. coli strains.
It is striking that the strain-specific genomic regions of E. coli MG1655 (K-islands; Perna et al., 2001) are dominated so much by phage-related genes (Anjum et al., 2003; Dobrindt et al., 2003). A high proportion of phage-related genes among variably absent or present ORFs in E. coli has also been found in a detailed CGH study on O55 : H7 and O157 : H7 strains (Wick et al., 2005). These genes are most likely parasitic in nature rather than contributing to the fitness of the host strain (Kurland, 2005). The fact that the majority of horizontally acquired DNA is maintained in the E. coli genome only for – in evolutionary timescales – short periods of time (Lawrence & Ochman, 1998) also speaks against routine fitness gains by HGT.
A last point we would like to make is that the term ‘housekeeping genes’, commonly used for the content of the conserved E. coli core genome (e.g. Anjum et al., 2003; Dobrindt et al., 2003), is misleading, because it has the connotation ‘non-niche-specific traits’, i.e. genes needed for basic energy generation, biosynthesis and cell division. With the core genome of E. coli apparently including so many genes needed for growth and survival in its primary and secondary habitats, the terms ‘life cycle’- or ‘habitat’-specific genes might be more appropriate.
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ACKNOWLEDGEMENTS |
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Edited by: W. Margolin
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Received 31 August 2006;
revised 26 March 2007;
accepted 3 April 2007.
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