erratum Genome sequence of enterohaemorrhagic Escherichia coli 0157:H7

A high-throughput and machine learning resistance monitoring system to determine the point of resistance for Escherichia coli with tetracycline: Combining UV-visible spectrophotometry with principal component analysis

UV-visible spectroscopy (UV-Vis) is routinely used in microbiology as a tool to check the optical density (OD) pertaining to the growth stages of microbial cultures at the single wavelength of 600 nm, better known as the OD₆₀₀ . Typically, modern UV-Vis spectrophotometers can scan in the region of approximately 200-1000 nm in the electromagnetic spectrum, where users do not extend the use of the instrument's full capability in a laboratory. In this study, the full potential of UV-Vis spectrophotometry (multiwavelength collection) was used to examine bacterial growth phases when treated with antibiotics showcasing the ability to understand the point of resistance when an antibiotic is introduced into the media and therefore understand the biochemical changes of the infectious pathogens. A multiplate reader demonstrated a high throughput experiment (96 samples) to understand the growth of Escherichia coli when varied concentrations of the antibiotic tetracycline was added into the well plates. Principal component analysis (PCA) and partial least squares discriminant analysis were then used as the data mining techniques to interpret the UV-Vis spectral data and generate machine learning "proof of principle" for the UV-Vis spectrophotometer plate reader. Results from this study showed that the PCA analysis provides an accurate yet simple visual classification and the recognition of E. coli samples belonging to each treatment. These data show significant advantages when compared to the traditional OD₆₀₀ method where we can now understand biochemical changes in the system rather than a mere optical density measurement. Due to the unique experimental setup and procedure that involves indirect use of antibiotics, the same test could be used for obtaining practical information on the type, resistance, and dose of antibiotic necessary to establish the optimum diagnosis, treatment, and decontamination strategies for pathogenic and antibiotic resistant species.

Comparative Genomic Analysis of Escherichia coli O157:H7 Isolated from Super-Shedder and Low-Shedder Cattle

Cattle are the primary reservoir of the foodborne pathogen Escherichia coli O157:H7, with the concentration and frequency of E. coli O157:H7 shedding varying substantially among individual hosts. The term ''super-shedder" has been applied to cattle that shed ≥10(4) cfu E. coli O157:H7/g of feces. Super-shedders have been reported to be responsible for the majority of E. coli O157:H7 shed into the environment. The objective of this study was to determine if there are phenotypic and/or genotypic differences between E. coli O157:H7 isolates obtained from super-shedder compared to low-shedder cattle. From a total of 784 isolates, four were selected from low-shedder steers and six isolates from super-shedder steers (4.01-8.45 log cfu/g feces) for whole genome sequencing. Isolates were phage and clade typed, screened for substrate utilization, pH sensitivity, virulence gene profiles and Stx bacteriophage insertion (SBI) sites. A range of 89-2473 total single nucleotide polymorphisms (SNPs) were identified when sequenced strains were compared to E. coli O157:H7 strain Sakai. More non-synonymous SNP mutations were observed in low-shedder isolates. Pan-genomic and SNPs comparisons did not identify genetic segregation between super-shedder or low-shedder isolates. All super-shedder isolates and 3 of 4 of low-shedder isolates were typed as phage type 14a, SBI cluster 3 and SNP clade 2. Super-shedder isolates displayed increased utilization of galactitol, thymidine and 3-O-β-D-galactopyranosyl-D-arabinose when compared to low-shedder isolates, but no differences in SNPs were observed in genes encoding for proteins involved in the metabolism of these substrates. While genetic traits specific to super-shedder isolates were not identified in this study, differences in the level of gene expression or genes of unknown function may still contribute to some strains of E. coli O157:H7 reaching high densities within bovine feces.

A qPCR assay to detect and quantify Shiga toxin-producing E. coli (STEC) in cattle and on farms: a potential predictive tool for STEC culture-positive farms

Shiga toxin-producing E. coli (STEC), of various serogroups harboring the intimin gene, form a serious threat to human health. They are asymptomatically carried by cattle. In this study, a quantitative real-time PCR (qPCR) method was developed as a molecular method to detect and quantify Shiga toxin genes stx1 and stx2 and the intimin gene eae. Subsequently, 59 fecal samples from six farms were tested using qPCR and a culture method as a reference. Three farms had contaminated animals as demonstrated by the culture method. Culture-positive farms showed moderate significantly higher stx prevalences than culture-negative farms (p = 0.05). This is the first study which showed preliminary results that qPCR can predict STEC farm contamination, with a specificity of 77% and a sensitivity of 83%, as compared with the culture method. Furthermore, the presence or quantity of stx genes in feces was not correlated to the isolation of STEC from the individual animal. Quantitative data thus did not add value to the results. Finally, the detection of both stx and eae genes within the same fecal sample or farm using qPCR was not correlated with the isolation of an eae-harboring STEC strain from the respective sample or farm using the culture method.

Effects of OTU clustering and PCR artifacts on microbial diversity estimates

Next-generation sequencing has increased the coverage of microbial diversity surveys by orders of magnitude, but differentiating artifacts from rare environmental sequences remains a challenge. Clustering 16S rRNA sequences into operational taxonomic units (OTUs) organizes sequence data into groups of 97 % identity, helping to reduce data volumes and avoid analyzing sequencing artifacts by grouping them with real sequences. Here, we analyze sequence abundance distributions across environmental samples and show that 16S rRNA sequences of >99 % identity can represent functionally distinct microorganisms, rendering OTU clustering problematic when the goal is an accurate analysis of organism distribution. Strict postsequencing quality control (QC) filters eliminated the most prevalent artifacts without clustering. Further experiments proved that DNA polymerase errors in polymerase chain reaction (PCR) generate a significant number of substitution errors, most of which pass QC filters. Based on our findings, we recommend minimizing the number of PCR cycles in DNA library preparation and applying strict postsequencing QC filters to reduce the most prevalent artifacts while maintaining a high level of accuracy in diversity estimates. We further recommend correlating rare and abundant sequences across environmental samples, rather than clustering into OTUs, to identify remaining sequence artifacts without losing the resolution afforded by high-throughput sequencing.

H-NS controls metabolism and stress tolerance in Escherichia coli O157:H7 that influence mouse passage

BACKGROUND

H-NS is a DNA-binding protein with central roles in gene regulation and nucleoid structuring in Escherichia coli. There are over 60 genes that are influenced by H-NS many of which are involved in metabolism. To determine the significance of H-NS-regulated genes in metabolism and stress tolerance, an hns mutant of E. coli O157:H7 was generated (hns::nptI, FRIK47001P) and its growth, metabolism, and gastrointestinal passage compared to the parent strain (43895) and strain FRIK47001P harboring pSC0061 which contains a functional hns and 90-bp upstream of the open-reading frame.

RESULTS

The hns mutant grew slower and was non-motile in comparison to the parent strain. Carbon and nitrogen metabolism was significantly altered in the hns mutant, which was incapable of utilizing 42 carbon, and 19 nitrogen sources that the parent strain metabolized. Among the non-metabolized substrates were several amino acids, organic acids, and key metabolic intermediates (i.e., pyruvate) that limit carbon acquisition and energy generation. Growth studies determined that the parent strain grew in LB containing 14 to 15% bile or bile salts, while the hns mutant grew in 6.5 and 9% of these compounds, respectively. Conversely, log-phase cells of the hns mutant were significantly (p < 0.05) more acid tolerant than the parent strain and hns mutant complemented with pSC0061. In mouse passage studies, the parent strain was recovered at a higher frequency (p < 0.01) than the hns mutant regardless of whether log- or stationary-phase phase cells were orally administered.

CONCLUSION

These results demonstrate that H-NS is a powerful regulator of carbon and nitrogen metabolism as well as tolerance to bile salts. It is likely that the metabolic impairments and/or the reduced bile tolerance of the E. coli O157:H7 hns mutant decreased its ability to survive passage through mice. Collectively, these results expand the influence of H-NS on carbon and nitrogen metabolism and highlight its role in the ability of O157:H7 strains to respond to changing nutrients and conditions encountered in the environment and its hosts.