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

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Zoller,  Hannah
5.4 Data Science Centre, 5.0 Geoinformation, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;
Submitting Corresponding Author, Deutsches GeoForschungsZentrum;

Garcia Perez,  Carlos
External Organizations;

Betel Geijo Fernández,  Javier
External Organizations;

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Graf zu Castell-Rüdenhausen,  Wolfgang
5.0 Geoinformation, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Lewis,  Nathan E.
External Organizations;

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5028070.pdf
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Zitation

Zoller, H., Garcia Perez, C., Betel Geijo Fernández, J., Graf zu Castell-Rüdenhausen, W. (2024): Measuring and understanding information storage and transfer in a simulated human gut microbiome. - PLOS Computational Biology, 20, 9, e1012359.
https://doi.org/10.1371/journal.pcbi.1012359


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5028070
Zusammenfassung
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.