Facilitative interaction networks in experimental microbial community dynamics

Hiroaki Fujita; Masayuki Ushio; Kenta Suzuki; Masato S Abe; Masato Yamamichi; Yusuke Okazaki; Alberto Canarini; Ibuki Hayashi; Keitaro Fukushima; Shinji Fukuda; E Toby Kiers; Hirokazu Toju

doi:10.3389/fmicb.2023.1153952

Facilitative interaction networks in experimental microbial community dynamics

Front Microbiol. 2023 Apr 11:14:1153952. doi: 10.3389/fmicb.2023.1153952. eCollection 2023.

Authors

Hiroaki Fujita¹, Masayuki Ushio², Kenta Suzuki³, Masato S Abe⁴, Masato Yamamichi^{5

6}, Yusuke Okazaki⁷, Alberto Canarini¹, Ibuki Hayashi¹, Keitaro Fukushima⁸, Shinji Fukuda^{9

10

11

12}, E Toby Kiers¹³, Hirokazu Toju¹

Affiliations

¹ Center for Ecological Research, Kyoto University, Kyoto, Japan.
² Department of Ocean Science (OCES), The Hong Kong University of Science and Technology (HKUST), Kowloon, Hong Kong SAR, China.
³ Integrated Bioresource Information Division, BioResource Research Center, RIKEN, Tsukuba, Japan.
⁴ Faculty of Culture and Information Science, Doshisha University, Kyoto, Japan.
⁵ School of Biological Sciences, The University of Queensland, Brisbane, QLD, Australia.
⁶ Department of International Health and Medical Anthropology, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan.
⁷ Institute for Chemical Research, Kyoto University, Kyoto, Japan.
⁸ Faculty of Food and Agricultural Sciences, Fukushima University, Fukushima, Japan.
⁹ Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan.
¹⁰ Gut Environmental Design Group, Kanagawa Institute of Industrial Science and Technology, Kawasaki, Japan.
¹¹ Transborder Medical Research Center, University of Tsukuba, Tsukuba, Japan.
¹² Laboratory for Regenerative Microbiology, Juntendo University Graduate School of Medicine, Tokyo, Japan.
¹³ Amsterdam Institute for Life and Environment, Vrije Universiteit, Amsterdam, Netherlands.

Abstract

Facilitative interactions between microbial species are ubiquitous in various types of ecosystems on the Earth. Therefore, inferring how entangled webs of interspecific interactions shift through time in microbial ecosystems is an essential step for understanding ecological processes driving microbiome dynamics. By compiling shotgun metagenomic sequencing data of an experimental microbial community, we examined how the architectural features of facilitative interaction networks could change through time. A metabolic modeling approach for estimating dependence between microbial genomes (species) allowed us to infer the network structure of potential facilitative interactions at 13 time points through the 110-day monitoring of experimental microbiomes. We then found that positive feedback loops, which were theoretically predicted to promote cascade breakdown of ecological communities, existed within the inferred networks of metabolic interactions prior to the drastic community-compositional shift observed in the microbiome time-series. We further applied "directed-graph" analyses to pinpoint potential keystone species located at the "upper stream" positions of such feedback loops. These analyses on facilitative interactions will help us understand key mechanisms causing catastrophic shifts in microbial community structure.

Keywords: community stability; dysbiosis; ecosystem functions; metabolic modeling; microbe-microbe interactions; microbial functions; mutualism; species interactions.