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Comparison of strand-specific transcriptomes of enterohemorrhagic Escherichia coli O157:H7 EDL933 (EHEC) under eleven different environmental conditions including radish sprouts and cattle feces.

Landstorfer R, Simon S, Schober S, Keim D, Scherer S, Neuhaus K - BMC Genomics (2014)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Lehrstuhl für Mikrobielle Ökologie, Wissenschaftszentrum Weihenstephan, Technische Universität München, Weihenstephaner Berg 3, D-85350 Freising, Germany. neuhaus@wzw.tum.de.

ABSTRACT

Background: Multiple 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.

Results: Transcriptomes 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 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.

Conclusions: Since only a minority of genes (2.7%) were not active under any condition tested ( 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.

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Correlation of sequencing depth and number of active genes. Active genes are defined as genes with a probability ≤ 0.05 to originate from background transcription. Additionally, the number of active genes is shown with an RPKM of 5 (about 40 × average random RPKM). An averaged correlation for each data set is shown using a logarithmic trend line.
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Fig3: Correlation of sequencing depth and number of active genes. Active genes are defined as genes with a probability ≤ 0.05 to originate from background transcription. Additionally, the number of active genes is shown with an RPKM of 5 (about 40 × average random RPKM). An averaged correlation for each data set is shown using a logarithmic trend line.

Mentions: It was observed that the number of active genes differs for different conditions (Table 1). In feces, the number of active genes is more than 1,000 genes lower compared to sprouts, although both conditions have about the same sequencing depth. This is important since differences in numbers of active genes could have originated from different sequencing depths as this influences the chance of finding a transcript. We show that such an effect of the sequencing depth does indeed influence the number of genes which will be defined as active (Figure 3): the number of active genes asymptotically reaches saturation with an increase in sequencing depth. The same pattern was observed by Haas et al.[28], also for EHEC EDL933. Vivancos et al.[33] show a similar effect for RNA-seq in Mycoplasma pneumonia and Mus musculus. However, the sequencing depth for EHEC grown on radish sprouts and feces is about the same. Therefore, the major difference observed must be of biological significance. We assume that survival of EHEC on radish sprouts requires a larger number of active genes than persistence in cattle feces since the cells have to deal with many environmental factors such as differing water activities, osmotic stress, radiation, temperature changes and low nutrient contents which are not present in cattle feces.Figure 3


Comparison of strand-specific transcriptomes of enterohemorrhagic Escherichia coli O157:H7 EDL933 (EHEC) under eleven different environmental conditions including radish sprouts and cattle feces.

Landstorfer R, Simon S, Schober S, Keim D, Scherer S, Neuhaus K - BMC Genomics (2014)

Correlation of sequencing depth and number of active genes. Active genes are defined as genes with a probability ≤ 0.05 to originate from background transcription. Additionally, the number of active genes is shown with an RPKM of 5 (about 40 × average random RPKM). An averaged correlation for each data set is shown using a logarithmic trend line.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4048457&req=5

Fig3: Correlation of sequencing depth and number of active genes. Active genes are defined as genes with a probability ≤ 0.05 to originate from background transcription. Additionally, the number of active genes is shown with an RPKM of 5 (about 40 × average random RPKM). An averaged correlation for each data set is shown using a logarithmic trend line.
Mentions: It was observed that the number of active genes differs for different conditions (Table 1). In feces, the number of active genes is more than 1,000 genes lower compared to sprouts, although both conditions have about the same sequencing depth. This is important since differences in numbers of active genes could have originated from different sequencing depths as this influences the chance of finding a transcript. We show that such an effect of the sequencing depth does indeed influence the number of genes which will be defined as active (Figure 3): the number of active genes asymptotically reaches saturation with an increase in sequencing depth. The same pattern was observed by Haas et al.[28], also for EHEC EDL933. Vivancos et al.[33] show a similar effect for RNA-seq in Mycoplasma pneumonia and Mus musculus. However, the sequencing depth for EHEC grown on radish sprouts and feces is about the same. Therefore, the major difference observed must be of biological significance. We assume that survival of EHEC on radish sprouts requires a larger number of active genes than persistence in cattle feces since the cells have to deal with many environmental factors such as differing water activities, osmotic stress, radiation, temperature changes and low nutrient contents which are not present in cattle feces.Figure 3

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Lehrstuhl für Mikrobielle Ökologie, Wissenschaftszentrum Weihenstephan, Technische Universität München, Weihenstephaner Berg 3, D-85350 Freising, Germany. neuhaus@wzw.tum.de.

ABSTRACT

Background: Multiple 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.

Results: Transcriptomes 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 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.

Conclusions: Since only a minority of genes (2.7%) were not active under any condition tested ( 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.

Show MeSH
Related in: MedlinePlus