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

Jens Christian Claussen*, Jurgita Skiecevičienė, Jun Wang, Philipp Rausch, Tom H. Karlsen, Wolfgang Lieb, John F. Baines, Andre Franke, Marc Thorsten Hütt

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Article numbere1005361
JournalPLoS computational biology
Issue number6
Publication statusPublished - 22 Jun 2017

Bibliographical note

© 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.


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