Boolean analysis reveals systematic interactions among low-abundance species in the human gut microbiome

Claussen, Jens Christian, Skiecevičienė, Jurgita, Wang, Jun, Rausch, Philipp, Karlsen, Tom H., Lieb, Wolfgang, Baines, John F., Franke, Andre and Hütt, Marc Thorsten (2017). Boolean analysis reveals systematic interactions among low-abundance species in the human gut microbiome. PLoS computational biology, 13 (6),

Abstract

The analysis of microbiome compositions in the human gut has gained increasing interest due to the broader availability of data and functional databases and substantial progress in data analysis methods, but also due to the high relevance of the microbiome in human health and disease. While most analyses infer interactions among highly abundant species, the large number of low-abundance species has received less attention. Here we present a novel analysis method based on Boolean operations applied to microbial co-occurrence patterns. We calibrate our approach with simulated data based on a dynamical Boolean network model from which we interpret the statistics of attractor states as a theoretical proxy for microbiome composition. We show that for given fractions of synergistic and competitive interactions in the model our Boolean abundance analysis can reliably detect these interactions. Analyzing a novel data set of 822 microbiome compositions of the human gut, we find a large number of highly significant synergistic interactions among these low-abundance species, forming a connected network, and a few isolated competitive interactions.

Publication DOI: https://doi.org/10.1371/journal.pcbi.1005361
Divisions: Engineering & Applied Sciences
Aston Business School > Marketing & strategy
Additional Information: © 2017 Claussen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Uncontrolled Keywords: Ecology, Evolution, Behavior and Systematics,Modelling and Simulation,Ecology,Molecular Biology,Genetics,Cellular and Molecular Neuroscience,Computational Theory and Mathematics
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
http://journals ... al.pcbi.1005361 (Publisher URL)
Published Date: 2017-06-22
Authors: Claussen, Jens Christian ( 0000-0002-9870-4924)
Skiecevičienė, Jurgita
Wang, Jun
Rausch, Philipp
Karlsen, Tom H.
Lieb, Wolfgang
Baines, John F.
Franke, Andre
Hütt, Marc Thorsten

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