Reference : BacArena: Individual-Based Metabolic Modeling of Heterogeneous Microbes in Complex Co...
Scientific journals : Article
Life sciences : Microbiology
Life sciences : Multidisciplinary, general & others
Systems Biomedicine; Computational Sciences
http://hdl.handle.net/10993/30995
BacArena: Individual-Based Metabolic Modeling of Heterogeneous Microbes in Complex Communities
English
Bauer, Eugen* mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Zimmermann, Johannes* mailto [Christian-Albrechts-Universität zu Kiel - CAU Kiel]
Baldini, Federico mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Thiele, Ines mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Kaleta, Christoph mailto [Christian-Albrechts-Universität zu Kiel - CAU Kiel]
* These authors have contributed equally to this work.
22-May-2017
PLoS Computational Biology
Public Library of Science
Yes (verified by ORBilu)
1553-734X
1553-7358
San Francisco
CA
[en] simulation of microbial communities ; microbial physiology ; biofilm ; cross-feeding ; gut microbiota ; agent-based modeling ; flux balance analysis
[en] Recent advances focusing on the metabolic interactions within and between cellular populations, have emphasized the importance of microbial communities for human health. Constraint-based modeling, with flux balance analysis in particular, has been established as a key approach for studying microbial metabolism, whereas individual-based modeling has been commonly used to study complex dynamics between interacting organisms. In this study, we combine both techniques into the R package BacArena (https://cran.r-project.org/package=BacArena), to generate novel biological insights into Pseudomonas aeruginosa biofilm formation as well as a seven species model community of the human gut. For our P. aeruginosa model, we found that cross-feeding of fermentation products cause a spatial differentiation of emerging metabolic phenotypes in the biofilm over time. In the human gut model community, we found that spatial gradients of mucus glycans are important for niche formations, which shape the overall community structure. Additionally, we could provide novel hypothesis concerning the metabolic interactions between the microbes. These results demonstrate the importance of spatial and temporal multi-scale modeling approaches such as BacArena.
http://hdl.handle.net/10993/30995

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