Measuring and understanding information storage and transfer in a simulated human gut microbiome

IF 3.8 2区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

PLoS Computational Biology Pub Date : 2024-09-17 DOI:10.1371/journal.pcbi.1012359

Hannah Zoller, Carlos Garcia Perez, Javier Betel Geijo Fernández, Wolfgang zu Castell

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Abstract

Considering biological systems as information processing entities and analyzing their organizational structure via information-theoretic measures has become an established approach in life sciences. We transfer this framework to a field of broad general interest, the human gut microbiome. We use BacArena, a software combining agent-based modelling and flux-balance analysis, to simulate a simplified human intestinal microbiome (SIHUMI). In a first step, we derive information theoretic measures from the simulated abundance data, and, in a second step, relate them to the metabolic processes underlying the abundance data. Our study provides further evidence on the role of active information storage as an indicator of unexpected structural change in the observed system. Besides, we show that information transfer reflects coherent behavior in the microbial community, both as a reaction to environmental changes and as a result of direct effective interaction. In this sense, purely abundance-based information theoretic measures can provide meaningful insight on metabolic interactions within bacterial communities. Furthermore, we shed light on the important however little noticed technical aspect of distinguishing immediate and delayed effects in the interpretation of local information theoretical measures.

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测量和了解模拟人类肠道微生物群中的信息存储和传输

将生物系统视为信息处理实体，并通过信息论措施分析其组织结构，已成为生命科学领域的一种既定方法。我们将这一框架应用到一个具有广泛普遍意义的领域--人类肠道微生物组。我们使用 BacArena（一种结合了代理建模和通量平衡分析的软件）来模拟简化的人类肠道微生物组（SIHUMI）。第一步，我们从模拟的丰度数据中推导出信息理论测量值；第二步，将这些测量值与丰度数据背后的代谢过程联系起来。我们的研究进一步证明了主动信息存储作为观测系统中意外结构变化指标的作用。此外，我们还表明，信息传递反映了微生物群落的一致行为，既是对环境变化的反应，也是直接有效互动的结果。从这个意义上说，纯粹基于丰度的信息理论测量可以为细菌群落内部的代谢互动提供有意义的见解。此外，我们还阐明了在解释局部信息理论测量时区分即时效应和延迟效应这一重要但却鲜为人知的技术问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY

CiteScore

7.10

自引率

4.70%

发文量

820

审稿时长

2.5 months

期刊介绍： PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.