Gene expression metaModules identifies key functional subnet- works in microbiome-related disease

A. May, B.W. Brandt, M. El-Kebir, G.W. Klau, E. Zaura, W. Crielaard, J. Heringa, S. Abeln

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Motivation: The human microbiome plays a key role in health and disease. Thanks to comparative metatranscriptomics, the cellular functions that are deregulated by the microbiome in disease can now be computationally explored. Unlike gene-centric approaches, pathway-based methods provide a systemic view of such functions; however, they typically consider each pathway in isolation and in its entirety. They can therefore overlook the key differences that (i) span multiple pathways, (ii) contain bidirectionally deregulated components, (iii) are confined to a pathway region. To capture these properties, computational methods that reach beyond the scope of predefined pathways are needed. Results: By integrating an existing module discovery algorithm into comparative metatranscriptomic analysis, we developed metaModules, a novel computational framework for automated identification of the key functional differences between health- and disease-associated communities. Using this framework, we recovered significantly deregulated subnetworks that were indeed recognized to be involved in two well-studied, microbiome-mediated oral diseases, such as butanoate production in periodontal disease and metabolism of sugar alcohols in dental caries. More importantly, our results indicate that our method can be used for hypothesis generation based on automated discovery of novel, disease-related functional subnetworks, which would otherwise require extensive and laborious manual assessment. Availability and implementation: metaModules is available at https://bitbucket.org/alimay/metamodules/ Supplementary information: Supplementary data are available at Bioinformatics online.
Original languageEnglish
Pages (from-to)1678-1685
JournalBioinformatics
Volume32
Issue number11
DOIs
Publication statusPublished - 2016

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Microbiota
Gene expression
Gene Expression
Pathway
Mouth Diseases
Sugar Alcohols
Health
Dental Caries
Periodontal Diseases
Computational Biology
Alcohol
Bioinformatics
Sugars
Computational methods
Comparative Analysis
Metabolism
Computational Methods
Isolation
Availability
Genes

Cite this

May, A. ; Brandt, B.W. ; El-Kebir, M. ; Klau, G.W. ; Zaura, E. ; Crielaard, W. ; Heringa, J. ; Abeln, S. / Gene expression metaModules identifies key functional subnet- works in microbiome-related disease. In: Bioinformatics. 2016 ; Vol. 32, No. 11. pp. 1678-1685.
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Gene expression metaModules identifies key functional subnet- works in microbiome-related disease. / May, A.; Brandt, B.W.; El-Kebir, M.; Klau, G.W.; Zaura, E.; Crielaard, W.; Heringa, J.; Abeln, S.

In: Bioinformatics, Vol. 32, No. 11, 2016, p. 1678-1685.

Research output: Contribution to JournalArticleAcademicpeer-review

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