Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters

Yu Shang; Johannes Sikorski; Michael Bonkowski; Anna-Maria Fiore-Donno; Ellen Kandeler; Sven Marhan; Runa S Boeddinghaus; Emily F Solly; Marion Schrumpf; Ingo Schöning; Tesfaye Wubet; Francois Buscot; Jörg Overmann

doi:10.1371/journal.pone.0173765

Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters

PLoS One. 2017 Mar 13;12(3):e0173765. doi: 10.1371/journal.pone.0173765. eCollection 2017.

Authors

Yu Shang¹, Johannes Sikorski^{1

2}, Michael Bonkowski³, Anna-Maria Fiore-Donno³, Ellen Kandeler⁴, Sven Marhan⁴, Runa S Boeddinghaus⁴, Emily F Solly⁵, Marion Schrumpf⁵, Ingo Schöning⁵, Tesfaye Wubet^{6

2}, Francois Buscot^{6

2}, Jörg Overmann^{1

2}

Affiliations

¹ Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Inhoffenstraße 7B, D-38124, Braunschweig, Deutschland.
² German Center for Integrative Biodiversity Research (iDiv) Jena Halle Leipzig, Deutscher Platz 5e, 04103 Leipzig, Deutschland.
³ Department of Terrestrial Ecology, Institute of Zoology, University of Cologne, Zülpicher Straße 47b, D-50674 Köln, Deutschland.
⁴ Institute of Soil Science and Land Evaluation, Soil Biology Section (310b), University of Hohenheim, Emil-Wolff-Straße. 27, D-70593 Stuttgart, Deutschland.
⁵ Max-Planck-Institut für Biogeochemie, Hans-Knöll-Straße 10, D-07745 Jena, Deutschland.
⁶ Department of Soil Ecology, Helmholtz Centre for Environmental Research - UFZ, Theodor-Lieser-Straße 4, D-06120, Halle/Saale, Deutschland.

Abstract

Interactions occur between two or more organisms affecting each other. Interactions are decisive for the ecology of the organisms. Without direct experimental evidence the analysis of interactions is difficult. Correlation analyses that are based on co-occurrences are often used to approximate interaction. Here, we present a new mathematical model to estimate the interaction strengths between taxa, based on changes in their relative abundances across environmental gradients.

MeSH terms

Base Sequence
Ecosystem
Germany
Hydrogen-Ion Concentration
Microbial Consortia / genetics*
Microbial Consortia / physiology
Models, Statistical
Models, Theoretical*
Random Allocation
Soil / chemistry
Soil Microbiology*

Substances

Soil

Grants and funding

The work has been (partly) funded by the Deutsche Forschungsgemeinschaft (DFG) Priority Program 1374 “Infrastructure-Biodiversity-Exploratories” (Grants No. OV 20/21-1, 22-1 http://gepris.dfg.de/gepris/projekt/252263987). J.O. received the funding. Field work permits were issued by the responsible state environmental offices of Baden-Württemberg, Thüringen, and Brandenburg (according to §72 BbgNatSchG).