Emergent Ecological Patterns and Modelling of Gut Microbiomes in Health and in Disease

Abstract

Recent advancements in next-generation sequencing have revolutionized our understanding of the human microbiome. Despite this progress, challenges persist in comprehending the microbiomes influence on disease, hindered by technical complexities in species classification, abundance estimation, and data compositionality. At the same time, recently the existence of macroecological laws describing the variation and diversity in microbial communities irrespective of their environment has been proposed using 16s data and explained by a simple phenomenological model of population dynamics. We here investigate the relationship between dysbiosis, i.e. in unhealthy individuals there are deviations from the "regular" composition of the gut microbial community, and the existence of macro-ecological emergent law in microbial communities. We first quantitatively reconstruct these patterns at the species level using shotgun data, offering a more biologically interpretable approach, and addressing the consequences of sampling effects and false positives on ecological patterns. We then ask if such patterns can discriminate between healthy and unhealthy cohorts. Concomitantly, we evaluate the efficacy of different population models, which incorporate sampling and different ecological and statistical principles (e.g., the Taylors law and environmental noise) to describe such patterns. A critical aspect of our analysis is understanding the relationship between model parameters, which have clear ecological interpretations, and the state of the gut microbiome, thereby enabling the generation of synthetic compositional data that distinctively represent healthy and unhealthy individuals. Our approach, grounded in theoretical ecology and statistical physics, allows for a robust comparison of these models with empirical data, enhancing our understanding of the strengths and limitations of simple microbial models of population dynamics. Author summaryIn this study, we explore emerging ecological properties in gut microbiomes. Our aim here is to determine whether these patterns can be informative of the gut microbiome (healthy or diseased) and unveil essential ingredients driving its population dynamics. Leveraging on phenomenological models of species abundance fluctuations and metagenomics data, we highlight the pivotal role of Taylors law, a straightforward mathematical relation, in constructing theoretical models for the human gut microbiome. We thus explore such a general theoretical framework for investigating microbiome composition and show that not all ecological patterns are informative to characterize its states, while few are (e.g., species diversity). Eventually, thanks to the ecological interpretability of the inferred models parameters, our analysis provides insights into the role of environmental fluctuations and carrying capacities of the gut microbiomes in both health and disease. This study offers valuable knowledge, bridging theoretical concepts with practical implications for human health.