Skip to main content
International Journal of Microbiology logoLink to International Journal of Microbiology
. 2010 Sep 29;2011:340506. doi: 10.1155/2011/340506

Gene Expression during Survival of Escherichia coli O157:H7 in Soil and Water

Ashley D Duffitt 1, 2,2, Robert T Reber 1, Andrew Whipple 1, 3,3, Christian Chauret 2,*
PMCID: PMC2948877  PMID: 20936140

Abstract

The in vitro survival of Escherichia coli O157:H7 at 15°C under two experimental conditions (sterile soil and sterile natural water) was examined. DNA microarrays of the entire set of E. coli O157:H7 genes were used to measure the genomic expression patterns after 14 days. Although the populations declined, some E. coli O157:H7 cells survived in sterile stream water up to 234 days and in sterile soil for up to 179 days. Cells incubated in soil microcosms for 14 days expressed genes for antibiotic resistance, biosynthesis, DNA replication and modification, metabolism, phages, transposons, plasmids, pathogenesis and virulence, antibiotic resistance, ribosomal proteins, the stress response, transcription, translation, and transport and binding proteins at significantly higher levels than cells grown in Luria broth. These results suggest that E. coli O157:H7 may develop a different phenotype during transport through the environment. Furthermore, this pathogen may become more resistant to antibiotics making subsequent infections more difficult to treat.

1. Introduction

Escherichia coli O157:H7 is an enterohemorrhagic strain of E. coli that produces a powerful shiga-like toxin. It is capable of causing bloody stools, hemorrhagic colitis, and hemolytic uremic syndrome [1]. Nearly 75,000 cases of O157:H7 infection occur every year in the US [2]. Most outbreaks have been associated with the consumption of contaminated, undercooked, bovine food products [1]. There also have been reports of E. coli O157:H7 outbreaks associated with both drinking and recreational water [37].

E. coli O157:H7 is ubiquitous on farms where healthy cattle and sheep harbor the pathogen in their gastrointestinal tracts [8]. As a consequence, farm animal manure is a source for spreading E. coli O157:H7 into the environment and potentially to the human food chain. One of the most common modes by which E. coli O157:H7 is introduced onto food crops is through contaminated irrigation water [9]. In addition, the propagation of this pathogen through the environment has been linked to runoff contaminated with bovine manure or by use as soil amendment [10]. The contamination of surface and ground water in rural areas of the United States is becoming increasingly more common as a result of concentrated animal feeding operations [9].

Escherichia coli O157:H7 can survive in varying habitats under a wide range of conditions. In the environment, cells are exposed to rapidly changing conditions such as changes in pH, nutrient availability, temperature, oxidative stress, and osmotic challenge [11]. E. coli O157:H7 pollution of water and soil is dependent on the ability of this pathogen to adapt to these changes. However, there is limited information concerning the survival of E. coli O157:H7 in soil and water as growth of bacteria, if any, in these environments is not well understood or documented. E. coli O157:H7 may respond to adverse conditions in the environment by expressing various stress response genes that enable survival [12]. The master regulator of the general stress response is an alternative sigma factor σ 38 (RpoS). This sigma factor may be induced in response to stresses such as weak acids, starvation, high osmolarity, and high or low temperature [13]. There is evidence that stress responses may enable survival under more severe conditions, increase pathogenicity, and enhance resistance to secondary stresses [14]. In other words, when E. coli cells are stressed, they become harder to kill and are more resistant to starvation and toxic chemicals typically used in distribution systems such as chlorine. This has significant public health implications because E. coli O157:H7 could develop a disinfectant-resistant phenotype during transport to water treatment plants [14]. Therefore, understanding the effects of stress on gene expression in response to altered environmental conditions may be crucial in understanding the survival of this organism as it moves from one environment to another.

Limited work has been conducted to investigate E. coli O157:H7 survival and functional genomics in the environment. Further research is needed to understand the mechanisms that enable E. coli O157:H7 to survive in such a wide variety of environments. This study compared genetic expression profiles of Escherichia coli O157:H7 under two environmental conditions (soil and natural water) to expression in growth media using DNA microarrays. In addition, we investigated the long-term survival of E. coli O157:H7 in microcosms simulating these environments.

2. Materials and Methods

2.1. Soil and Water Collection and Site Description

Soil and water were collected from Newby Ditch in June of 2006 within 24 hours of a rainfall event (1.93 cm or 0.76 inches). Newby Ditch is located within the Mississinewa watershed on the Tipton Till Plain of East Central Indiana (USA). This watershed is characterized as a highly disturbed landscape predominated by row crop agriculture. Environmental samples were placed in sterile bottles and stored in a cooler with ice packs for transport to the lab. The samples were processed within 24 hours for use as soil and water microcosms according to the methods described below.

2.2. Inoculum and Incubation Conditions

E. coli O157:H7 strain ATCC 35150 was used to investigate survival and differences in gene expression under two different environmental conditions compared to Luria broth (LB) (BD, Rockville, MD). For long-term storage, the culture was maintained in 10% glycerol at −50°C. In the short term, cells were cultured on nutrient agar (BD) slants at 4°C. The E. coli O157:H7 experiment cultures were prepared by transferring a loopful of a slant culture into a 100 mL flask containing 30 mL of LB. The flask was incubated for 24 hours at 37°C without shaking. This culture was used to inoculate the three treatment conditions: 30 mL LB control, 90 mL sterile stream water microcosms, and 100-g sterile soil microcosms. The 30 mL LB control (100 mL flask) was inoculated with 1 mL of the culture and incubated at 15°C for 48 hours with shaking at 60 rpm. The remaining cells were harvested by centrifugation at 10,000 × g for 10 minutes at 4°C (Sorvall RC-5B), washed twice with sterile deionized water, and resuspended in 10 mL of sterile stream water or 10 mL of sterile deionized water. This suspension was used to inoculate the stream water and soil microcosms, respectively. The control and water experiments were performed using ten replicates each, four for microarray analysis and six to monitor survival with replacement. The soil treatment was prepared with 34 replicates, four for microarray analysis and 30 to monitor survival without replacement. The water microcosms were incubated at 15°C with shaking at 60 rpm, and the soil microcosms were incubated at 15°C without shaking. Four microcosms, each of soil and water, were removed after 14 days for DNA microarray analysis. Four flasks of the 15°C LB control were removed after 48 hours for DNA microarray analysis. Survival was assessed periodically using the spread plate method described below.

2.3. Water Microcosms

The stream water used in this experiment had a pH of 7.26. Aliquots of water (90 mL) were placed into 250 mL sterile bottles and autoclaved at 121°C at 15 psi for 15 minutes. Following sterilization, the water microcosms were stored at 4°C until inoculation. Following inoculation with 8.8 ×108 CFU/mL of E. coli O157:H7 ATCC 35150, the water microcosms were incubated at 15°C with shaking at 60 rpm.

2.4. Soil Microcosms

The soil used in this study was a Fox silt loam with a pH of 6.95 [15]. Fox silt loam is a typical agricultural soil in East Central Indiana. It is a well-drained soil with a moderate available water capacity, medium runoff, and poor filtering capacity [15]. Soil pH was determined by placing 20 g of soil into a 50 mL beaker, adding 20 mL of deionized water, and stirring for 30 minutes [16]. This suspension was allowed to settle for an hour, and pH was measured with a pH meter. Soil moisture content was determined using the gravimetric method; soil was weighed, oven dried at 105°C, and then reweighed until the sample weight was constant [16]. The soil moisture content was determined to be 0.323 (32.3%), which is a slightly moist soil [15]. Large rocks and debris were removed from the dried soil, and 100-g aliquots were placed in 250 mL glass bottles. The soil microcosms were autoclaved at 121°C at 15 psi for 15 minutes Following sterilization, the soil was returned to the drying oven for 24 hours at 105°C to remove any residual moisture. Sterile soil, as checked by plate counting, was stored at room temperature prior to inoculation. Soil moisture content was adjusted to field conditions by adding 32.3 mL of sterile deionized water [16]. Following inoculation with 8.8 × 108 CFU/ml of E. coli O157:H7 ATCC 35150, the microcosms were sealed and incubated statically at 15°C.

2.5. Colony Counting

The initial (zero-time postinoculation) concentration E. coli O157:H7 was determined for each condition prior to incubation. E. coli O157:H7 concentrations were determined for each condition by using the spread plate method. Samples for counting were removed directly from the water microcosms and LB broth. For extraction of bacteria from soil, 100 mL 0.1% polyethylene glycol (PEG) was added to 100 g of soil. This suspension was shaken (150 rpm) for 15 minutes at 15°C and then allowed to settle for five minutes. The supernatant from this suspension was centrifuged for ten minutes (10,000 × g, 4°C), and the resulting supernatant was used to enumerate the cells. Viable cell counts were performed in duplicate by serial dilution in 0.9% sterile saline and spread plate culturing 0.1 mL onto R2A agar (BD) plates. The plates were incubated at 37°C for 48 hours. Following incubation, plates with colony counts between 25 and 250 were considered, and duplicate counts were averaged. The average number of colonies was divided by the volume or mass of the original solution to estimate the number of CFU/ml and CFU/g, respectively.

2.6. Isolation of Total RNA

Total RNA was isolated using the FastRNA Pro Soil-Direct Kit (Qbiogene, Inc., CA) with minor modifications (described below) to improve quality and yield. The kit-supplied Lysing Matrix E tubes were placed at −10°C for 2 days prior to RNA extraction to minimize heating and RNA degradation. One gram of the sample was placed into the kit-supplied Lysing Matrix E tubes for lysis. Sample lysis was performed using a Mini-BeadBeater-1 instrument (Biospec Products, Inc., Bartlesville, OK) for 80 seconds at a speed setting of 48 (maximum speed). RNA was centrifuged through the kit-supplied Quick-Clean Spin Filters to remove residual inhibitors following extraction and stored in 100 μL of DEPC-H20 at −50°C. RNA quality was determined by 1.0% (w/v) agarose gel electrophoresis and by spectrophotometric analysis (OD260/OD280) using a Thermo Scientific Spectronic GENESYS 5 Spectrophotometer. An OD measurement at 260 nm was used to quantify the RNA yield. Approximately 100 μg of total RNA was obtained per sample. The purified RNA samples were delivered on ice to Dr. Howard Edenberg's laboratory at the Indiana University School of Medicine Center for Medical Genomics where the microarray analysis was performed.

2.7. DNA Microarrays, cDNA Preparation, and Hybridization

DNA microarrays were used to evaluate the genetic expression profiles of E. coli O157:H7 ATCC 35150 maintained under three environmental conditions. The microarray system used for E. coli was the GeneChip E. coli Genome 2.0 Array (Affymetrix, Inc., Santa Clara, CA). The microarray analysis was performed with four biologically-independent replicates (with respect to E. coli growth, RNA isolation, sample preparation, and array hybridization) for each treatment condition.

The standard protocol for prokaryotic sample and array processing recommended by Affymetrix in their GeneChip Expression Analysis Technical Manual (Affymetrix, Santa Clara, CA) was used. cDNA was synthesized using a T7 promoter-dT24 oligonucleotide as a primer with the Invitrogen Life Technologies SuperScrip Choice system. Following second-strand cDNA synthesis and incubation with T4 DNA polymerase, the products were purified using the Affymetrix Cleanup Module. Biotinylated cRNA was made using the Affymetrix IVT kit. The cRNA was purified using the Qiagen RNeasy column, quantitated, and then fragmented by incubation at high temperature with magnesium. Biotinylated cRNA was then added to a hybridization solution and hybridized to the GeneChip after adding control oligonucleotides at 45°C for 17 hours with constant rotation. The hybridization mixture was removed, and the GeneChip was washed and stained with phycoerythrin-labeled Streptavidin using the Affymetrix Fluidics Station. The GeneChip was washed again, incubated with biotinylated antistreptavidin, and then restained with phycoerythrin-labeled Streptavidin to amplify the signals. Balanced groups of samples were handled in parallel to reduce nonrandom error. The arrays were scanned using the dedicated scanner controlled by Affymetrix GCOS software.

2.8. Data Analysis

The microarray expression data were generated using Affymetrix GCOS software. The Affymetrix Microarray Suite Algorithm was used to analyze the hybridization intensity data from GeneChip expression probe arrays and to calculate a set of metrics to describe probe set performance. The average intensity of each array was normalized by global scaling to a target intensity of 1000. An average expression value for each treatment group was calculated via geometric mean because it is better applied to data with large fluctuations. Only probe sets that received a “present” call of 75% or greater were considered. The expression values were normalized by log 2 transformation [17]. Two treatments were compared by determining the log 2 ratio of gene expression for the corresponding averaged intensities for each treatment. Fold change was calculated from log 2 data such that values for induction range from 1 to 100 while values for repression are restricted to the space between 0 and 1 [18]. For example, a value of 2 indicates a 2-fold upregulation while a value of 0.5 indicates a 2-fold downregulation for a gene comparing the environmental condition to the Luria broth. A t-test on the log 2 transformed data was performed using Microsoft Excel. Significant gene selection was performed using the Microsoft Excel filter function to select for genes with greater than or equal to a 2-fold up- or downregulation and a P-value less than .05.

2.9. Functional Groups

Functions of significantly expressed genes were determined using the Affymetrixs NetAffx Analysis Center (http://www.affymetrix.com/analysis/netaffx/index.affx) and EcoCyc (http://ecocyc.org/) database. Functional group analysis was performed by assigning genes to one of 13 functional groups.

3. Results

3.1. Survival of E. coli O157:H7 in Sterile Soil Microcosms

Soil microcosms were inoculated with 10 mL of 8.8 × 108 CFU/g of E. coli O157:H7 strain ATCC 35150. Immediately after inoculation, the average preincubation concentration of E. coli O157:H7 was 1.8 × 107 CFU/g. Following incubation at 15°C, survival was monitored on a regular basis for 179 days. No significant decrease in the E. coli O157:H7 concentration was observed during the first 30 days of incubation (Figure 1). The last measurement was taken on day 179, and the average concentration of cells was 7.7 × 107 CFU/g (data not shown).

Figure 1.

Figure 1

Survival of E. coli O157:H7 in sterile soil microcosms at 15°C. The average concentrations of E. coli O157:H7 were determined by the spread plate method and are shown as CFU per gram. Error bars represent standard deviations about the means (n = 4).

3.2. Survival of E. coli O157:H7 in Water Microcosms

Sterile water was inoculated with 10 mL of 8.8 × 108 CFU/mL of E. coli O157:H7 strain ATCC 35150. On day 0, the mean concentration of E. coli O157:H7 was 1.1 × 108 CFU/mL. The microcosms were incubated at 15°C with gentle shaking at 60 rpm, and survival was monitored for 234 days. A decrease in the E. coli O157:H7 concentration below the postinoculation concentration was not observed until day 3 (Figure 2). The population decreased by less than 0.3 log by day 28. The final measurement was taken on day 234 (nearly 8 months following inoculation), and the mean concentration of cells was 2.98 × 104 CFU/mL (data not shown).

Figure 2.

Figure 2

Survival of E. coli O157:H7 in sterile stream water microcosms at 15°C at 60 rpm. The average concentrations of E. coli O157:H7 were determined by the spread plate method and are shown as CFU per milliliter. Error bars represent standard deviations about the means (n = 4).

3.3. Microarray Analysis

The genomic expression profiles of E. coli O157:H7 ATCC 35150 incubated in sterile soil, water, and LB were evaluated. The log expression ratios of the E. coli O157:H7 genome for cells grown in LB at 15°C for 48 hours with shaking at 60 rpm versus fourteen-day incubation in sterile stream water at 15°C are illustrated in Figure 3. The whole genome analysis indicated that 705 genes were more highly expressed in LB (plotted with a negative value) while 751 genes were more highly expressed in sterile stream water (plotted with a positive value) (Figure 3). Figure 4 shows the log expression ratios of the E. coli O157:H7 genome for cells grown in LB at 15°C for 48 hours versus fourteen-day incubation in sterile soil at 15°C. The analysis of the whole genome indicated that 2,664 genes were more highly expressed in LB (plotted with a negative value) while 1,823 genes were more highly expressed in sterile soil (plotted with a positive value).

Figure 3.

Figure 3

The log expression ratio of the E. coli O157:H7 genome was plotted for Luria broth versus sterile stream water. Genes more highly expressed in LB have a negative value, whereas genes more highly expressed in water have a positive value.

Figure 4.

Figure 4

The log expression ratio of the E. coli O157:H7 genome was plotted for Luria broth versus sterile soil. Genes more highly expressed in LB have a negative value, whereas genes more highly expressed in soil have a positive value.

An analysis of gene ratios with significant expression levels (≥ 2 folds and P-value < .05) revealed that the majority of genes did not differ significantly between conditions. This was especially true of the cells grown in LB compared with the cells incubated in sterile stream water; 26 genes were more significantly expressed in LB compared to 12 genes in cells incubated in sterile stream water (Table 1). The comparison of cells incubated in sterile soil compared to cells grown in LB yielded more differences in expression; 89 genes were expressed at significantly higher levels in LB while 308 genes were more highly expressed in sterile soil (Table 2).

Table 1.

Functional groups differentially expressed between growth in LB and growth in sterile stream water.

Functional group Total Higher in LB Higher in water
Whole genome 38 26 12
Antibiotic resistance 0 0 0
Biosynthesis 0 0 0
DNA replication/repair, restriction/modification 2 1 1
Metabolism 0 0 0
Pathogenesis and virulence 0 0 0
Phage, transposon, or plasmid 0 0 0
Ribosomal proteins 1 1 0
Signaling and motility 1 1 0
Stress response 3 3 0
Transcription, RNA processing, and degradation 4 4 0
Translation and posttranslational modification 1 1 0
Transport and binding proteins 7 6 1
Uncategorized 19 9 10

Table 2.

Functional groups differentially expressed between growth in LB and growth in sterile soil.

Functional group Total Higher in LB Higher in soil
Whole genome 397 89 308
Antibiotic resistance 3 0 3
Biosynthesis 21 1 20
DNA replication/repair, restriction/modification 10 2 8
Metabolism 33 15 18
Pathogenesis and virulence 7 0 7
Phage, transposon, or plasmid 8 3 5
Ribosomal proteins 45 0 45
Signaling and motility 2 2 0
Stress response 18 0 18
Transcription, RNA processing, and degradation 39 5 34
Translation and posttranslational modification 27 2 25
Transport and binding proteins 48 21 27
Uncategorized 136 38 98

A functional group analysis was performed for significantly expressed genes in LB versus sterile soil (Table 2) and LB versus sterile stream water (Table 1). Functional group analysis of LB versus sterile soil revealed that cells incubated in sterile soil expressed more genes for antibiotic resistance, biosynthesis, DNA replication/repair and restriction/modification, metabolism, pathogenesis and virulence, phages, transposons, and plasmids, ribosomal proteins, stress response, transcription, RNA processing, and degradation, translation and posttranslational modification, and transport and binding proteins (Table 2). Functional group analysis of LB versus sterile stream water revealed that cells incubated in sterile stream water expressed more genes of unknown function while cells grown in LB expressed more genes for ribosomal proteins, signaling and motility, stress response, transcription, RNA processing, and degradation, translation and posttranslational modification, and transport and binding proteins (Table 1). The nature of these differences in genomic expression is described in detail in Tables 3 and 4. For example, seven of the genes for amino acid biosynthesis were expressed at significantly higher levels in soil than in LB (Table 3). There were no differences in expression of these amino acid biosynthesis genes between cells grown in LB and cells incubated in sterile natural water (Table 4). Of the 55 genes that are known to encode ribosomal proteins, 45 were expressed at significantly higher levels in soil compared to Luria broth (Table 2). Only one ribosomal protein gene (rpmC) was significantly expressed in cells grown in LB compared to water (Table 1).

Table 3.

Selected genes differentially expressed between growth in LB and sterile soil microcosms.

Function and gene Description Logarithmic ratio (S/C) P-value
Amino acid biosynthesis
 hisG Histidine biosynthesis 2.05 1.04E-03
 argB Arginine biosynthesis 3.05 1.60E-04
 argC Arginine biosynthesis 3.52 4.13E-04
 argG Arginine biosynthesis 3.07 2.56E-06
 asnB Asparagine synthetase B 3.41 1.66E-02
 thrL Thr operon leader peptide 3.43 1.23E-03
 cysK Cysteine biosynthesis 3.53 2.00E-06

Antibiotic resistance
 marA Multiple antibiotic resistance protein 4.20 2.31E-09
 marB Multiple antibiotic resistance protein 4.41 3.25E-05
 marR Multiple antibiotic resistance protein 5.16 2.51E-07

DNA replication/repair, restriction/modification
 priB Primosomal replication protein 2.19 1.23E-03
 topA DNA topoisomerase I 2.33 6.56E-08
 fis DNA binding protein Fis 2.37 3.72E-05
 priA Primosome assembly protein 2.60 4.67E-02

Metabolism
 aceE Pyruvate dehydrogenase E1 subunit 2.03 5.14E-06
 asmA Protein asmA precursor; electron transport 2.21 3.40E-02
 lpdA Dihydrolipoamide dehydrogenase; energy metabolism 2.24 1.16E-04
 nemA N-ethylmaleimide reductase; central intermediary metabolism 2.71 1.56E-05
 glpC Anaerobic glycerol-3-phosphate dehydrogenase subunit C 2.81 7.83E-03
 yfhO Cysteine metabolism; amino acid metabolism 3.25 3.64E-05
 icdA Isocitrate dehydrogenase; TCA cycle metabolism 3.48 9.13E-05
 adhC Alcohol dehydrogenase class III; energy metabolism 4.19 9.70E-05
 yibO Phosphoglyceromutase; carbohydrate metabolism 6.21 8.10E-03
 ttdB L(+)-tartrate dehydrase; energy metabolism 0.44 2.22E-06
 hycG Formate hydrogenlyase subunit 7; mitochondrial electron transport 0.44 3.00E-06
 phnH Carbon-phosphorus lyase complex subunit; central intermediary metabolism 0.45 2.51E-04
 mhpF Acetaldehyde dehydrogenase; amino acid metabolism 0.46 1.45E-06
 phnJ Carbon-phosphorus lyase complex subunit; central intermediary metabolism 0.46 5.55E-05
 hycF Hydrogenase 4 Fe-S subunit formate hydrogenlyase, complex iron-sulfur protein 0.47 2.96E-05
 eutI Phosphate acetyltransferase 0.47 8.02E-04
 ygjL 2,4-dienoyl-CoA reductase (NADPH), NADH and FMN-linked 0.49 4.90E-01

Pathogenesis and virulence
 vacB Ribonuclease R, exoribonuclease R, RNase R 2.26 1.44E-05
 tolA Colicin production 2.26 2.51E-05
 wcaL Colanic acid biosynthesis; resistance to acid stress, desiccation, and thermal stress 2.51 1.32E-02
 ygeO Hypothetical protein 2.66 1.04E-02

Phage, transposon, or plasmid
 sieB Rac prophage; phage superinfection exclusion protein 0.43 5.93E-03
 Lar Rac prophage; restriction alleviation protein 0.43 9.19E-03
 ydaE Rac prophage; conserved protein 0.44 2.28E-03
 ydaQ Rac prophase; conserved protein 0.45 2.22E-03
 ydaC Rac prophage predicted protein 0.50 8.85E-03
 ymfP E14 prophage; conserved protein 4.46 1.87E-02
 mprA Translational repressor mprA; plasmid related function 3.53 1.78E-05

Ribosomal proteins
 rpsU 30S ribosomal protein S21 2.25 1.12E-04
 rpsT 30S ribosomal protein S20 2.35 4.46E-04
 rplY 50S ribosomal protein L25 2.35 2.21E-03
 rpmF 50S ribosomal protein L32 2.43 1.16E-03
 rpmH 50S ribosomal protein L34 2.52 3.30E-05
 rplK 50S ribosomal protein L11 2.67 9.18E-04
 rpsR 30S ribosomal protein S18 2.87 7.21E-05
 rplA 50S ribosomal protein L1 2.87 9.28E-05
 rpmD 50S ribosomal protein L30 3.17 3.14E-05
 rpsJ 30S ribosomal protein S10 3.24 6.19E-04
 rpmE 50S ribosomal protein L31 3.32 4.52E-05
 rplW 50S ribosomal protein L23 3.53 1.57E-04
 rpsH 30S ribosomal protein S8 4.34 3.27E-04
 rplF 50S ribosomal protein L6 4.57 1.39E-04
 rplX 50S ribosomal protein L24 4.66 2.51E-05
 rpsN 30S ribosomal protein S14 5.68 6.06E-05

Stress response
 cspE Cold shock protein E 2.02 5.08E-03
 yfiA Cold shock protein, associated with 30S ribosomal subunit 2.10 1.23E-03
 htpX Heat shock protein 2.10 2.02E-04
 sulA SOS cell division inhibitor 2.17 1.69E-05
 ymcE Cold shock gene 2.33 1.49E-04
 dnaK Heat shock protein; molecular chaperone 2.48 3.21E-04
 recA Recombinase A; SOS response 2.59 8.09E-04
 rpoS Response to organic acid stress and acetate induced acid tolerance; regulatory function 2.68 6.83E-04
 ahpC Alkyl hydroperoxide reductase C22 protein; oxidative stress 2.91 9.08E-06
 dead Cold shock DEAD box protein A 3.04 1.18E-05
 rpoH RNA polymerase sigma factor; heat response 3.19 5.63E-06
 Spy Envelope stress induced periplasmic protein 3.54 6.83E-08
 osmB Osmotic adaptation; Osmotically inducible lipoprotein B precursor 4.77 1.81E-04
 cspG Cold shock protein 5.04 2.93E-05
 cpxP Envelope stress response 7.08 1.17E-05
 cspA Cold shock protein cspA, major cold shock protein 8.59 6.77E-05

Transcription, RNA processing, and degradation
 rpoB DNA directed RNA polymerase beta subunit; transcription 2.12 1.54E-04
 rpoD Hypothetical protein, RNA polymerase sigma factor 2.20 1.79E-03
 Pnp Polyribonucleotide, nucleotidyltransferase; RNA processing 2.21 1.58E-03
 rpnA Ribonuclease P 2.31 4.01E-05
 Rne Ribonuclease E, fused ribonuclease E: endoribonuclease 2.72 1.33E-03
 rpoA DNA-directed RNA polymerase alpha subunit; transcription 2.92 1.72E-04
 nusA Transcription elongation factor NusA 3.16 1.15E-04
 Rho Transcription termination factor Rho 3.34 5.92E-05

Translation and posttranslational modification
 soxS Regulatory protein, DNA binding dual transcriptional regulator 2.44 2.47E-04
 tufA Elongation factor Tu, protein chain elongation factor (EF-Tu) 2.61 8.28E-05
 infA Translation initiation factor IF-1 3.09 4.37E-05
 infC Translation initiation factor IF-3 3.31 3.27E-05
 fusA Elongation factor EF-2 3.36 7.54E-05
 infB Translation initiation factor IF-2 4.13 5.84E-04

Transport and binding proteins
 phnO Phosphonate transport, N-acetyltransferase activity 0.46 1.40E-06
 treB PTS system, trehalose-specific IIBC component; transport of small molecules 0.47 3.04E-04
 malK Maltose/maltodextrin transport 0.48 1.49E-05
 thiQ Thiamine transport 0.49 1.48E-04
 fepB Iron-enterobactin transporter subunit 0.49 7.73E-05
 cusB Copper efflux system protein 2.02 4.55E-06
 yjbB Phosphate transport, sodium dependent phosphate transporter 2.07 5.77E-03
 livJ Leucine/isoleucine/valine transporter subunit 2.22 3.16E-04
 oppA Oligopeptide transporter subunit 2.32 2.98E-04
 lolE Lipoprotein releasing system, transmembrane protein lolE 2.32 1.54E-02
 prlA Preprotein translocase; protein transport 2.46 3.03E-05
 glnH Glutamine ABC transporter, periplasmic-binding protein 2.50 5.52E-05
 artP Arginine transport 2.52 1.33E-05
 fepD Ferric enterobactin transport system 3.25 3.01E-02
 fepE Ferric enterobactin transport protein 3.85 5.61E-03

Table 4.

Selected genes differentially expressed between growth in LB and sterile water microcosms.

Function and gene Description Logarithmic ratio (W/C) P-value
DNA replication/repair, restriction/modification
 ycbY DNA restriction-modification system; DNA methylation 2.38 4.13E-02
Membrane
 ompA Outer membrane protein 0.42 4.62E-04
 ompX Outer membrane protein X; integral to outer membrane 0.43 1.09E-04
Metabolism
 yfiD Protein yfiD, pyruvate formate lyase subunit 0.48 3.74E-03

Ribosomal proteins
 rpmC Protein biosynthesis, structural constituent of ribosome, intracellular ribosome, ribonucleoprotein complex 0.48 3.25E-04

Regulatory RNA
 gcvB Regulatory sRNA 0.23 1.00E-03
 csrC Regulatory RNA 0.39 4.40E-03
 vmicF Regulatory sRNA 0.41 1.99E-03
 ryhA Unknown RNA 0.46 8.79E-03
Stress response
 cspC Cold-shock stress protein 0.48 1.41E-04
 dps DNA protection during starvation conditions 0.49 3.75E-04

Transcription, RNA processing, and degradation
 himA Integration host factor alpha subunit; DNA recombination and transcription regulation 0.49 9.13E-03

Transport and binding proteins
 ompF Outer membrane protein F precursor; ion transport, porin activity 0.46 1.21E-03
 potF Putrescine-binding, periplasmic protein precursor 2.71 3.22E-02

The genes responsible for the stress response include those that function in temperature shock, acid tolerance, the SOS response, and osmotic challenge. Eighteen stress response genes were significantly expressed in cells incubated in sterile soil compared to LB (Table 2). On the other hand, three stress response genes were more significantly expressed in LB compared to cells incubated in sterile natural water (Table 1). The rpoS gene is induced in response to entry into stationary phase and also by stresses such as weak acids, starvation, osmotic challenge, and temperature changes. The expression of rpoS was significantly elevated in soil (2.68-fold induction) (Table 3). The rpoH heat shock sigma factor 32 (σ 32), which regulates the heat shock response, was more highly expressed in soil compared to LB (3.19-fold induction) (Table 3). Cells grown in soil expressed heat shock genes dnaK and htpX at significantly greater levels (Table 3). In addition, table 3 shows that rseA, an antisigma regulator of the rpoE envelope heat stress system, was induced in cells incubated in soil (3.29-fold induction). Numerous cold shock genes were significantly expressed in cells incubated in soil compared to cells grown in LB: cspA, cspE, cspG, ymcE, deaD, yfiA (Table 3). Only one cold shock gene (cspC) was expressed at significantly lower levels in cells incubated in sterile water compared to cells grown in LB (0.48-fold repression) (Table 4). Two genes involved in the SOS response were significantly expressed in cells grown in soil compared to LB: recA and sulA. This regulatory network is induced by DNA damage or interference with DNA replication. The osmotically inducible gene osmB was expressed at significantly higher levels in cells incubated in soil (4.77-fold induction). osmB encodes an outer membrane protein of unknown function. Seven genes that aid in pathogenesis and virulence were significantly expressed in cells incubated in soil compared to those grown in LB (Table 2). In particular, the vacB gene was expressed (2.26-fold induction) (Table 3). tolA, a gene involved in colicin production, was significantly expressed in cells incubated in soil compared to cells grown in LB (2.26-fold induction) (Table 3). Also, the soxS gene was more highly expressed in cells incubated in sterile soil microcosms (2.44-fold induction) (Table 3). Finally, three antibiotic resistance genes (marR, marA, and marB) were expressed at significantly higher levels in cells incubated in sterile soil microcosms compared to LB (Table 2).

4. Discussion

E. coli O157:H7 may encounter conditions that are less than optimal for growth in soil and water and must adapt to these conditions in order to survive. Various stress response mechanisms allow this pathogen to adapt to sublethal environmental conditions. Extended exposure to these stresses enables E. coli O157:H7 to survive under more severe conditions, increases its pathogenesis, and enhances its resistance to chemicals typically used in water distribution systems [14]. This has significant public health implications because E. coli O157:H7 could develop a disinfectant-resistant phenotype during transport to water treatment plants [14]. Therefore, this study investigated the survival and genetic expression profiles of E. coli O157:H7 in sterile soil and sterile natural water. Our results indicate that E. coli O157:H7 can persist for long periods of time in sterile soil and sterile stream water. In addition, we found that E. coli O157:H7 exhibits differential gene expression profiles in sterile soil and sterile stream water compared to cells freshly grown in LB. This survival does not account for the possible effects of competition with other bacteria or interactions with predatory protozoa. Under natural conditions, where predators and other bacteria are present, a net die off of E. coli O157:H7 would likely occur. It is also possible that the environmental persistence of E. coli O157:H7 cells initially grown in fecal extracts could be different.

Microarray analysis revealed that cells incubated in sterile soil for 14 days remain very active. In fact, 308 genes were found to be more highly expressed in these cells compared to cells grown in LB. A functional group analysis revealed that the majority of these genes were involved in amino acid biosynthesis, DNA replication and repair, pathogenesis and virulence, the stress response, ribosomal proteins, antibiotic resistance, transcription, and translation. On the other hand, microarray analysis of cells placed in sterile stream water for 14 days revealed that only 12 genes were more highly expressed in this condition. The majority of these genes are uncategorized and of unknown function. There was a marked difference in the expression of ribosomal protein and translation genes. Typically, faster-growing cells synthesize proteins more rapidly and contain more ribosomes [19, 20]. Tao et al. [18] studied the gene expression of E. coli K12 in response to nutrient limitation. These researchers found that 42 ribosomal protein genes were expressed at significantly higher levels in cells grown under high nutrient conditions. The present study, on the other hand, revealed that 45 ribosomal protein genes were more highly expressed in cells incubated in sterile soil compared to cells grown in LB. The exception to growth-rate-dependent regulation of ribosome number occurs at very low growth rates [21]. When E. coli cells adjust to a slow growth rate from a fast one, RNA accumulation is attenuated for a short time until the RNA content is reduced to that characteristic of cells grown at the slower rate [22].

It is thought that the same mechanism that functions during amino acid starvation also functions during growth rate transitions. In fact, the continued accumulation of RNA in cells under partial amino acid starvation has been shown to be accompanied by a continued synthesis in ribosomal proteins [23]. This could account for the higher expression of genes for ribosomal proteins observed in the present study as genes encoding the enzymes needed for amino acid biosynthesis were more highly expressed in cells incubated in sterile soil microcosms. In E. coli, there are 97 known genes responsible for encoding the enzymes needed for amino acid biosynthesis [18]. Previous results [18] indicate that these genes are induced for growth in low nutrient environments as appears to be the case in the present study. Growth conditions that lead to a decreased rate of ribosome synthesis typically result in an excess of ribosomal proteins, and their transcript levels are higher in faster growing cells.

The regulatory mechanism that controls the general stress response is the RpoS sigma factor (σ 38) and is encoded by the rpoS gene [24]. An early adaptation in cells exposed to environmental stresses involves the expression of rpoS. This gene, which controls the expression of more than 50 proteins, is induced in response to entry into stationary phase and also by stresses such as weak acids, starvation, osmotic challenge, and temperature changes [13]. The expression of rpoS in cells in sterile soil microcosms was 2.68-fold higher when compared to cells cultured in Luria broth. In addition, the expression of 18 genes involved in the stress response was more highly expressed in cells from soil. These genes regulate cellular response to cold shock, heat shock, acid tolerance, osmotic challenge, and the SOS response [24]. This indicates that the soil environment stressed these cells, and they turned on genes to cope with sublethal environmental conditions.

The heat shock response is a protective mechanism to cope with heat-induced damage to proteins; however, there is evidence suggesting that these genes are also induced in response to acidic conditions [17], SOS-inducing treatments [25], and sublethal exposure to chlorine [26]. Most heat shock proteins act as molecular chaperones that bind to and stabilize unfolded proteins and promote protein refolding and proper assembly [27]. This is the case with the product of the dnaK gene. The dnaK gene product has been shown to regulate other heat shock proteins, such as htpX, and play a major role in digesting irreversibly heat damaged polypeptides [28]. In addition to heath shock proteins, numerous cold shock genes were significantly expressed in cells incubated in soil compared to cells grown in LB: cspA, cspE, cspG, ymcE, deaD, yfiA. These genes protect the cell during sublethal environmental temperatures. CspA is the major cold shock protein of pathogenic E. coli. It functions as an RNA chaperone and facilitates translation at low temperatures [29]. A specific sigma factor has not yet been identified in the case of the cold shock response [27].

Two genes involved in the SOS response were significantly expressed in cells grown in soil compared to LB: recA and sulA. This regulatory network is induced by DNA damage or interference with DNA replication. The RecA protein functions as a positive control for SOS regulation, is required for all homologous recombination in E. coli, and catalyzes synapsis and strand exchange between homologous molecules [30]. The sulA gene product functions as an inducible inhibitor of septation [31]. When cells are exposed to SOS-inducing environments, they will continue to elongate but fail to septate and thus form filaments.

Several genes responsible for the pathogenesis and virulence of E. coli O157:H7 were significantly expressed in cells from sterile soil microcosms. The vacB gene, which is required for the full expression of the virulence phenotype in E. coli [32], was highly expressed in cells incubated in soil. Moreover, a gene involved in colonic acid biosynthesis, wcaL, was more highly expressed in soil compared to LB. wcaL is the last gene of the colanic acid gene cluster [33]. Colanic acid forms a protective capsule around the bacterial cell surface and plays a role in pathogenesis [34]. Danese et al. [35] demonstrated that colonic acid synthesis is upregulated in biofilms and is not synthesized in planktonic cells under normal laboratory conditions. This may account for the differences in colonic acid gene expression observed between the cells incubated in sterile soil microcosms (in which biofilms are likely) compared to the LB control. A gene involved in colicin production, tolA, was significantly expressed at a higher level in cells incubated in soil compared to cells grown in luria broth. Colicins are antibacterial proteins produced by some strains of E. coli that kill competing strains of bacteria by inhibiting energy metabolism, protein synthesis, or DNA synthesis [36]. Colicins are also known to increase bacterial resistance to host defense. In addition, three genes (marR, marA, and marB) responsible for multiple antibiotic resistance were more highly expressed in sterile soil. The multiple antibiotic resistance (mar) locus in E. coli is composed of two operons (marC and marRAB). Expression of the marRAB operon protects E. coli against numerous antibiotics [37]. Moreover, the elevated expression of the soxS gene product has been associated with the multiple antibiotic resistance (mar) phenotype [37]. The collective expression of these genes and the genes involved in the general stress response may contribute to bacterial survival and virulence during infection. In fact, there is evidence that antibiotic treatment increases the development of hemolytic uremic syndrome (HUS) in children with E. coli O157:H7 infection [38].

In conclusion, Affymetrix GeneChip E. coli Genome Arrays were used to demonstrate that E. coli O157:H7 cells placed in sterile soil and water microcosms at 15°C for 14 days exhibit differential gene expression compared to cells grown in LB at 15°C for 48 hours. The cells incubated in sterile soil microcosms were undoubtedly stressed and therefore in a different physiological state than cells grown in LB at 15°C for 48 hours. These cells exhibit a phenotype that may lead to stress-associated disinfection resistance, increased pathogenesis, and virulence. This has important implications in water treatment and public health because surface and ground waters are the source for municipal drinking water. Further research on the mechanisms and regulation of the stress response of E. coli O157:H7 is needed to prevent potential risk of disease. It is also possible that the genetics expression could be different in nonsterile environments, and this needs to be investigated.

Acknowledgments

The microarray studies were carried out using the facilities of the Center for Medical Genomics at Indiana University School of Medicine. The Center for Medical Genomics is supported in part by the Indiana Genomics Initiative at Indiana University (INGENE, which is supported in part by the Lilly Endowment, Inc.). In addition, the authors thank Dr. Michael Guebert at Taylor University for assistance in selecting the sample site.

References

  • 1.Boyce TG, Swerdlow DL, Griffin PM. Escherichia coli O157:H7 and the hemolytic-uremic syndrome. The New England Journal of Medicine. 1995;333(6):364–368. doi: 10.1056/NEJM199508103330608. [DOI] [PubMed] [Google Scholar]
  • 2.Perna NT, Plunkett G, Burland V, et al. Genome sequence of enterohaemorrhagic Escherichia coli O157:H7. Nature. 2001;409(6819):529–533. doi: 10.1038/35054089. [DOI] [PubMed] [Google Scholar]
  • 3.Swerdlow DL, Woodruff BA, Brady RC, et al. A waterborne outbreak in Missouri of Escherichia coli O157:H7 associated with bloody diarrhea and death. Annals of Internal Medicine. 1992;117(10):812–819. doi: 10.7326/0003-4819-117-10-812. [DOI] [PubMed] [Google Scholar]
  • 4.Ackman D, Marks S, Mack P, Caldwell M, Root T, Birkhead G. Swimming-associated haemorrhagic colitis due to Escherichia coli O157:H7 infection: evidence of prolonged contamination of a fresh water lake. Epidemiology and Infection. 1997;119(1):1–8. doi: 10.1017/s095026889700770x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Olsen SJ, Miller G, Breuer T, et al. A waterborne outbreak of Escherichia coli O157:H7 infections and hemolytic uremic syndrome: implications for rural water systems. Emerging Infectious Diseases. 2002;8(4):370–375. doi: 10.3201/eid0804.000218. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Samadpour M, Stewart J, Steingart K, et al. Laboratory investigation of an E. coli O157:H7 outbreak associated with swimming in Battle Ground Lake, Vancouver, Washington. Journal of Environmental Health. 2002;64(10):16–25. [PubMed] [Google Scholar]
  • 7.Bopp DJ, Sauders BD, Waring AL, et al. Detection, isolation, and molecular subtyping of Escherichia coli O157:H7 and Campylobacter jejuni associated with a large waterborne outbreak. Journal of Clinical Microbiology. 2003;41(1):174–180. doi: 10.1128/JCM.41.1.174-180.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Chapman PA, Siddons CA, Wright DJ, Norman P, Fox J, Crick E. Cattle as a possible source of verocytotoxin-producing Escherichia coli O157 infections in man. Epidemiology and Infection. 1993;111(3):439–447. doi: 10.1017/s0950268800057162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Ibekwe AM, Watt PM, Shouse PJ, Grieve CM. Fate of Escherichia coli O157:H7 in irrigation water on soils and plants as validated by culture method and real-time PCR. Canadian Journal of Microbiology. 2004;50(12):1007–1014. doi: 10.1139/w04-097. [DOI] [PubMed] [Google Scholar]
  • 10.Kudva IT, Blanch K, Hovde CJ. Analysis of Escherichia coli O157:H7 survival in ovine or bovine manure and manure slurry. Applied and Environmental Microbiology. 1998;64(9):3166–3174. doi: 10.1128/aem.64.9.3166-3174.1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Farrell MJ, Finkel SE. The growth advantage in stationary-phase phenotype conferred by rpoS mutations is dependent on the pH and nutrient environment. Journal of Bacteriology. 2003;185(24):7044–7052. doi: 10.1128/JB.185.24.7044-7052.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Arnold KW, Kaspar CW. Starvation- and stationary-phase-induced acid tolerance in Escherichia coli O157:H7. Applied and Environmental Microbiology. 1995;61(5):2037–2039. doi: 10.1128/aem.61.5.2037-2039.1995. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Lange R, Hengge-Aronis R. The cellular concentration of the σ(S) subunit of RNA polymerase in Escherichia coli is controlled at the levels of transcription, translation, and protein stability. Genes and Development. 1994;8(13):1600–1612. doi: 10.1101/gad.8.13.1600. [DOI] [PubMed] [Google Scholar]
  • 14.Lisle JT, Broadaway SC, Prescott AM, Pyle BH, Fricker C, Mcfeters GA. Effects of starvation on physiological activity and chlorine disinfection resistance in Escherichia coli O157:H7. Applied and Environmental Microbiology. 1998;64(12):4658–4662. doi: 10.1128/aem.64.12.4658-4662.1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Jensen EL, Braun RJ, Rich KS, Tardy SW, Walker CF. Soil Survey of Grant County, Indiana. West Lafayette, Ind, USA: Department of Agriculture, Soil Conservation Service, Purdue University Agricultural Experiment Station; 1988. [Google Scholar]
  • 16.Marshal CE, Shaw BT, Jacob KD. Methods of Soil Analysis Part 2: Chemical and Microbiological Properties. Madison, Wis, USA: American Society of Agronomy; 1965. [Google Scholar]
  • 17.Maurer LM, Yohannes E, Bondurant SS, Radmacher M, Slonczewski JL. pH regulates genes for flagellar motility, catabolism, and oxidative stress in Escherichia coli K-12. Journal of Bacteriology. 2005;187(1):304–319. doi: 10.1128/JB.187.1.304-319.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Tao H, Bausch C, Richmond C, Blattner FR, Conway T. Functional genomics: expression analysis of Escherichia coli growing on minimal and rich media. Journal of Bacteriology. 1999;181(20):6425–6440. doi: 10.1128/jb.181.20.6425-6440.1999. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Tabor PS, Ohwada K, Colwell RR. Filterable marine bacteria found in the deep sea: distribution, taxonomy, and response to starvation. Microbial Ecology. 1981;7(1):67–83. doi: 10.1007/BF02010479. [DOI] [PubMed] [Google Scholar]
  • 20.Keener J, Nomura M. Regulation of ribosome synthesis. In: Neidharde FC, Curtiss R III, Ingraham JL, et al., editors. Escherichia coli and Salmonella: Cellular and Molecular Biology. 2nd edition. Washington, DC, USA: ASM Press; 1996. pp. 1417–1431. [Google Scholar]
  • 21.Dennis PP, Bremer H. Differential rate of ribosomal protein synthesis in Escherichia coli . Journal of Molecular Biology. 1974;84(3):407–422. doi: 10.1016/0022-2836(74)90449-5. [DOI] [PubMed] [Google Scholar]
  • 22.Winslow RM. A consequence of the rel gene during a glucose to lactate downshift in Escherichia coli. The rates of ribonucleic acid synthesis. The Journal of Biological Chemistry. 1971;246(15):4872–4877. [PubMed] [Google Scholar]
  • 23.Dennis PP, Nomura M. Regulation of the expression of ribosomal protein genes in Escherichia coli . Journal of Molecular Biology. 1975;97(1):61–76. doi: 10.1016/s0022-2836(75)80022-2. [DOI] [PubMed] [Google Scholar]
  • 24.Hengge-Aronis R. Survival of hunger and stress: the role of rpoS in early stationary phase gene regulation in E. coli . Cell. 1993;72(2):165–168. doi: 10.1016/0092-8674(93)90655-a. [DOI] [PubMed] [Google Scholar]
  • 25.Krueger JH, Walker GC. groEL and dnaK genes of Escherichia coli are induced by UV irradiation and nalidixic acid in an htpR-dependent manner. Proceedings of the National Academy of Sciences of the United States of America. 1984;81(5):1499–1503. doi: 10.1073/pnas.81.5.1499. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Dukan S, Dadon S, Smulski DR, Belkin S. Hypochlorous acid activates the heat shock and soxRS systems of Escherichia coli . Applied and Environmental Microbiology. 1996;62(11):4003–4008. doi: 10.1128/aem.62.11.4003-4008.1996. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Chung HJ, Bang W, Drake MA. Stress response of Escherichia coli . Comprehensive Reviews in Food Science and Food Safety. 2006;5(3):52–64. [Google Scholar]
  • 28.Morris JG. Bacterial shock responses. Endeavour. 1993;17(1):2–6. doi: 10.1016/0160-9327(93)90003-l. [DOI] [PubMed] [Google Scholar]
  • 29.Jiang W, Hou Y, Inouye M. CspA, the major cold-shock protein of Escherichia coli, is an RNA chaperone. The Journal of Biological Chemistry. 1997;272(1):196–202. doi: 10.1074/jbc.272.1.196. [DOI] [PubMed] [Google Scholar]
  • 30.Kowalczykowski SC. Biochemistry of genetic recombination: energetics and mechanism of DNA strand exchange. Annual Review of Biophysics and Biophysical Chemistry. 1991;20:539–575. doi: 10.1146/annurev.bb.20.060191.002543. [DOI] [PubMed] [Google Scholar]
  • 31.Schoemaker JM, Gayda RC, Markovitz A. Regulation of cell division in Escherichia coli: SOS induction and cellular location of the SulA protein, a key to lon-associated filamentation and death. Journal of Bacteriology. 1984;158(2):551–561. doi: 10.1128/jb.158.2.551-561.1984. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Cheng Z-F, Zuo Y, Li Z, Rudd KE, Deutscher MP. The vacB gene required for virulence in Shigella flexneri and Escherichia coli encodes the exoribonuclease RNase R. The Journal of Biological Chemistry. 1998;273(23):14077–14080. doi: 10.1074/jbc.273.23.14077. [DOI] [PubMed] [Google Scholar]
  • 33.Wang L, Huskic S, Cisterne A, Rothemund D, Reeves PR. The O-antigen gene cluster of Escherichia coli O55:H7 and identification of a new UDP-GlcNAc C4 epimerase gene. Journal of Bacteriology. 2002;184(10):2620–2625. doi: 10.1128/JB.184.10.2620-2625.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Christensen GD, Simpson WA, Bisno AL, Beachey EH. Adherence of slime-producing strains of Staphylococcus epidermidis to smooth surfaces. Infection and Immunity. 1982;37(1):318–326. doi: 10.1128/iai.37.1.318-326.1982. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Danese PN, Pratt LA, Kolter R. Exopolysaccharide production is required for development of Escherichia coli K-12 biofilm architecture. Journal of Bacteriology. 2000;182(12):3593–3596. doi: 10.1128/jb.182.12.3593-3596.2000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Davies DL, Falkiner FR, Hardy KG. Colicin V production by clinical isolates of Escherichia coli . Infection and Immunity. 1981;31(2):574–579. doi: 10.1128/iai.31.2.574-579.1981. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Gambino L, Gracheck SJ, Miller PF. Overexpression of the marA positive regulator is sufficient to confer multiple antibiotic resistance in Escherichia coli . Journal of Bacteriology. 1993;175(10):2888–2894. doi: 10.1128/jb.175.10.2888-2894.1993. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Wong CS, Jelacic S, Habeeb RL, Watkins SL, Tarr PI. The risk of the hemolytic-uremic syndrome after antibiotic treatment of Escherichia coli O157:H7 infections. The New England Journal of Medicine. 2000;342(26):1930–1936. doi: 10.1056/NEJM200006293422601. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from International Journal of Microbiology are provided here courtesy of Wiley

RESOURCES