Dataset Information

Strand-specific transcriptomes of Enterohemorrhagic Escherichia coli in response to interactions with ground beef microbiota: interactions between microorganisms in raw meat.

ABSTRACT: Enterohemorrhagic Escherichia coli (EHEC) are zoonotic agents associated with outbreaks worldwide. Growth of EHEC strains in ground beef could be inhibited by background microbiota that is present initially at levels greater than that of the pathogen E. coli. However, how the microbiota outcompetes the pathogenic bacteria is unknown. Our objective was to identify metabolic pathways of EHEC that were altered by natural microbiota in order to improve our understanding of the mechanisms controlling the growth and survival of EHECs in ground beef.Based on 16S metagenomics analysis, we identified the microbial community structure in our beef samples which was an essential preliminary for subtractively analyzing the gene expression of the EHEC strains. Then, we applied strand-specific RNA-seq to investigate the effects of this microbiota on the global gene expression of EHEC O2621765 and O157EDL933 strains by comparison with their behavior in beef meat without microbiota. In strain O2621765, the expression of genes connected with nitrate metabolism and nitrite detoxification, DNA repair, iron and nickel acquisition and carbohydrate metabolism, and numerous genes involved in amino acid metabolism were down-regulated. Further, the observed repression of ftsL and murF, involved respectively in building the cytokinetic ring apparatus and in synthesizing the cytoplasmic precursor of cell wall peptidoglycan, might help to explain the microbiota's inhibitory effect on EHECs. For strain O157EDL933, the induced expression of the genes implicated in detoxification and the general stress response and the repressed expression of the peR gene, a gene negatively associated with the virulence phenotype, might be linked to the survival and virulence of O157:H7 in ground beef with microbiota.In the present study, we show how RNA-Seq coupled with a 16S metagenomics analysis can be used to identify the effects of a complex microbial community on relevant functions of an individual microbe within it. These findings add to our understanding of the behavior of EHECs in ground beef. By measuring transcriptional responses of EHEC, we could identify putative targets which may be useful to develop new strategies to limit their shedding in ground meat thus reducing the risk of human illnesses.

SUBMITTER: Galia W

PROVIDER: S-EPMC5543532 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Strand-specific transcriptomes of Enterohemorrhagic Escherichia coli in response to interactions with ground beef microbiota: interactions between microorganisms in raw meat.

Galia Wessam W Leriche Francoise F Cruveiller Stéphane S Garnier Cindy C Navratil Vincent V Dubost Audrey A Blanquet-Diot Stéphanie S Thevenot-Sergentet Delphine D

BMC genomics 20170803 1

<h4>Background</h4>Enterohemorrhagic Escherichia coli (EHEC) are zoonotic agents associated with outbreaks worldwide. Growth of EHEC strains in ground beef could be inhibited by background microbiota that is present initially at levels greater than that of the pathogen E. coli. However, how the microbiota outcompetes the pathogenic bacteria is unknown. Our objective was to identify metabolic pathways of EHEC that were altered by natural microbiota in order to improve our understanding of the mec ...[more]

PMID: 28774270

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Project description:BackgroundMultiple infection sources for enterohemorrhagic Escherichia coli O157:H7 (EHEC) are known, including animal products, fruit and vegetables. The ecology of this pathogen outside its human host is largely unknown and one third of its annotated genes are still hypothetical. To identify genetic determinants expressed under a variety of environmental factors, we applied strand-specific RNA-sequencing, comparing the SOLiD and Illumina systems.ResultsTranscriptomes of EHEC were sequenced under 11 different biotic and abiotic conditions: LB medium at pH4, pH7, pH9, or at 15°C; LB with nitrite or trimethoprim-sulfamethoxazole; LB-agar surface, M9 minimal medium, spinach leaf juice, surface of living radish sprouts, and cattle feces. Of 5379 annotated genes in strain EDL933 (genome and plasmid), a surprising minority of only 144 had null sequencing reads under all conditions. We therefore developed a statistical method to distinguish weakly transcribed genes from background transcription. We find that 96% of all genes and 91.5% of the hypothetical genes exhibit a significant transcriptional signal under at least one condition. Comparing SOLiD and Illumina systems, we find a high correlation between both approaches for fold-changes of the induced or repressed genes. The pathogenicity island LEE showed highest transcriptional activity in LB medium, minimal medium, and after treatment with antibiotics. Unique sets of genes, including many hypothetical genes, are highly up-regulated on radish sprouts, cattle feces, or in the presence of antibiotics. Furthermore, we observed induction of the shiga-toxin carrying phages by antibiotics and confirmed active biofilm related genes on radish sprouts, in cattle feces, and on agar plates.ConclusionsSince only a minority of genes (2.7%) were not active under any condition tested (null reads), we suggest that the assumption of significant genome over-annotations is wrong. Environmental transcriptomics uncovered hitherto unknown gene functions and unique regulatory patterns in EHEC. For instance, the environmental function of azoR had been elusive, but this gene is highly active on radish sprouts. Thus, NGS-transcriptomics is an appropriate technique to propose new roles of hypothetical genes and to guide future research.

Dataset Information

Strand-specific transcriptomes of Enterohemorrhagic Escherichia coli in response to interactions with ground beef microbiota: interactions between microorganisms in raw meat.

Publications

Strand-specific transcriptomes of Enterohemorrhagic Escherichia coli in response to interactions with ground beef microbiota: interactions between microorganisms in raw meat.

Similar Datasets

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