Dataset Information

Using gene expression data and network topology to detect substantial pathways, clusters and switches during oxygen deprivation of Escherichia coli.

ABSTRACT:

Background

Biochemical investigations over the last decades have elucidated an increasingly complete image of the cellular metabolism. To derive a systems view for the regulation of the metabolism when cells adapt to environmental changes, whole genome gene expression profiles can be analysed. Moreover, utilising a network topology based on gene relationships may facilitate interpreting this vast amount of information, and extracting significant patterns within the networks.

Results

Interpreting expression levels as pixels with grey value intensities and network topology as relationships between pixels, allows for an image-like representation of cellular metabolism. While the topology of a regular image is a lattice grid, biological networks demonstrate scale-free architecture and thus advanced image processing methods such as wavelet transforms cannot directly be applied. In the study reported here, one-dimensional enzyme-enzyme pairs were tracked to reveal sub-graphs of a biological interaction network which showed significant adaptations to a changing environment. As a case study, the response of the hetero-fermentative bacterium E. coli to oxygen deprivation was investigated. With our novel method, we detected, as expected, an up-regulation in the pathways of hexose nutrients up-take and metabolism and formate fermentation. Furthermore, our approach revealed a down-regulation in iron processing as well as the up-regulation of the histidine biosynthesis pathway. The latter may reflect an adaptive response of E. coli against an increasingly acidic environment due to the excretion of acidic products during anaerobic growth in a batch culture.

Conclusion

Based on microarray expression profiling data of prokaryotic cells exposed to fundamental treatment changes, our novel technique proved to extract system changes for a rather broad spectrum of the biochemical network.

SUBMITTER: Schramm G

PROVIDER: S-EPMC1884177 | biostudies-literature | 2007 May

REPOSITORIES: biostudies-literature

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Publications

Using gene expression data and network topology to detect substantial pathways, clusters and switches during oxygen deprivation of Escherichia coli.

Schramm Gunnar G Zapatka Marc M Eils Roland R König Rainer R

BMC bioinformatics 20070508

<h4>Background</h4>Biochemical investigations over the last decades have elucidated an increasingly complete image of the cellular metabolism. To derive a systems view for the regulation of the metabolism when cells adapt to environmental changes, whole genome gene expression profiles can be analysed. Moreover, utilising a network topology based on gene relationships may facilitate interpreting this vast amount of information, and extracting significant patterns within the networks.<h4>Results</ ...[more]

PMID: 17488495

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Project description:The biogeography of the gut is diverse in its longitudinal axis, as well as within specific microenvironments. Differential oxygenation and nutrient composition drive the membership of microbial communities in these habitats. Moreover, enteric pathogens can orchestrate further modifications to gain a competitive advantage toward host colonization. These pathogens are versatile and adept when exploiting the human colon. They expertly navigate complex environmental cues and interkingdom signaling to colonize and infect their hosts. Here we demonstrate how enterohemorrhagic Escherichia coli (EHEC) uses three sugar-sensing transcription factors, Cra, KdpE, and FusR, to exquisitely regulate the expression of virulence factors associated with its type III secretion system (T3SS) when exposed to various oxygen concentrations. We also explored the effect of mucin-derived nonpreferred carbon sources on EHEC growth and expression of virulence genes. Taken together, the results show that EHEC represses the expression of its T3SS when oxygen is absent, mimicking the largely anaerobic lumen, and activates its T3SS when oxygen is available through Cra. In addition, when EHEC senses mucin-derived sugars heavily present in the O-linked and N-linked glycans of the large intestine, virulence gene expression is initiated. Sugars derived from pectin, a complex plant polysaccharide digested in the large intestine, also increased virulence gene expression. Not only does EHEC sense host- and microbiota-derived interkingdom signals, it also uses oxygen availability and mucin-derived sugars liberated by the microbiota to stimulate expression of the T3SS. This precision in gene regulation allows EHEC to be an efficient pathogen with an extremely low infectious dose.ImportanceEnteric pathogens have to be crafty when interpreting multiple environmental cues to successfully establish themselves within complex and diverse gut microenvironments. Differences in oxygen tension and nutrient composition determine the biogeography of the gut microbiota and provide unique niches that can be exploited by enteric pathogens. EHEC is an enteric pathogen that colonizes the colon and causes outbreaks of bloody diarrhea and hemolytic-uremic syndrome worldwide. It has a very low infectious dose, which requires it to be an extremely effective pathogen. Hence, here we show that EHEC senses multiple sugar sources and oxygen levels to optimally control the expression of its virulence repertoire. This exquisite regulatory control equips EHEC to sense different intestinal compartments to colonize the host.

Dataset Information

Using gene expression data and network topology to detect substantial pathways, clusters and switches during oxygen deprivation of Escherichia coli.

Background

Results

Conclusion

Publications

Using gene expression data and network topology to detect substantial pathways, clusters and switches during oxygen deprivation of Escherichia coli.

Similar Datasets

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