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- Title
Alternative stable states, nonlinear behavior, and predictability of microbiome dynamics.
- Authors
Fujita, Hiroaki; Ushio, Masayuki; Suzuki, Kenta; Abe, Masato S.; Yamamichi, Masato; Iwayama, Koji; Canarini, Alberto; Hayashi, Ibuki; Fukushima, Keitaro; Fukuda, Shinji; Kiers, E. Toby; Toju, Hirokazu
- Abstract
Background: Microbiome dynamics are both crucial indicators and potential drivers of human health, agricultural output, and industrial bio-applications. However, predicting microbiome dynamics is notoriously difficult because communities often show abrupt structural changes, such as "dysbiosis" in human microbiomes. Methods: We integrated theoretical frameworks and empirical analyses with the aim of anticipating drastic shifts of microbial communities. We monitored 48 experimental microbiomes for 110 days and observed that various community-level events, including collapse and gradual compositional changes, occurred according to a defined set of environmental conditions. We analyzed the time-series data based on statistical physics and non-linear mechanics to describe the characteristics of the microbiome dynamics and to examine the predictability of major shifts in microbial community structure. Results: We confirmed that the abrupt community changes observed through the time-series could be described as shifts between "alternative stable states" or dynamics around complex attractors. Furthermore, collapses of microbiome structure were successfully anticipated by means of the diagnostic threshold defined with the "energy landscape" analysis of statistical physics or that of a stability index of nonlinear mechanics. Conclusions: The results indicate that abrupt microbiome events in complex microbial communities can be forecasted by extending classic ecological concepts to the scale of species-rich microbial systems. BZtjfqfgm5MWSae9EkdSwR Video Abstract
- Subjects
STATISTICAL physics; ECOLOGICAL regime shifts; NONLINEAR mechanics; COMMUNITIES; HUMAN microbiota; MICROBIAL communities
- Publication
Microbiome, 2023, Vol 11, Issue 1, p1
- ISSN
2049-2618
- Publication type
Article
- DOI
10.1186/s40168-023-01474-5