Multispecies Emergence of Collective Behavior: Microbiome Connectome, Diversity and Services

M. Convertino
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Abstract

Ecosystems’ microbiome organization is the epitomic feature of ecosystem function and an incredibly fascinating system considering its complexity, ecology and evolution, and practical applications for individual and population health. Due to its ‘’unknowns’’ the microbiome also provides the opportunity to test and develop information theoretic models that mimic and predict its dynamics. A novel information and network theoretic model that predicts microbiome network organization, diversity, dynamics and stability for the human gut microbiome is presented. The model is able to classify health states based on microbiome entropic patterns, that, in the optimal biological function are related to neutral scale-free information organization of species interactions. The healthy state is characterized by an optimal metabolic function that is predicted by macroecological quintessential indicators whose variability is meaningful of state transitions. Information propagation analyses detect total species importance, proportional to outgoing information flow, which can be use for microbial engineering or disease diagnosis and etiognosis. Finally a link with ocean microbial ecosystems is highlighted as well as the collectivity-diversity-dynamics triality.
集体行为的多物种出现:微生物组连接组、多样性和服务
生态系统的微生物组组织是生态系统功能的缩影,考虑到它的复杂性、生态学和进化,以及对个体和群体健康的实际应用,它是一个令人难以置信的迷人系统。由于其“未知”,微生物组也提供了测试和开发模拟和预测其动态的信息理论模型的机会。提出了一种新的信息和网络理论模型,用于预测人类肠道微生物群的网络组织、多样性、动态和稳定性。该模型能够根据微生物组的熵模式对健康状态进行分类,在最优的生物功能中,这些熵模式与物种相互作用的中性无标度信息组织有关。健康状态的特征是由宏观生态基本指标预测的最佳代谢功能,其变异性对状态转变有意义。信息传播分析可以检测出与流出信息流成正比的总物种重要性,可用于微生物工程或疾病诊断和病因诊断。最后,强调了与海洋微生物生态系统的联系以及集体性-多样性-动态性。
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