AI Article Synopsis
- Microbiome dynamics are important for health and agriculture but are hard to predict due to sudden changes, like "dysbiosis" in humans.
- Through a study of 48 experimental microbiomes over 110 days, researchers observed community changes linked to specific environmental conditions, using statistical physics and non-linear mechanics for analysis.
- They found that these abrupt changes could be anticipated by analyzing the community's dynamics, indicating that classic ecological theories can be applied to complex microbial ecosystems.
Article 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. Video Abstract.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10052866 | PMC |
| http://dx.doi.org/10.1186/s40168-023-01474-5 | DOI Listing |
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