BacArena: Individual-based metabolic modeling of heterogeneous microbes in complex communities
Authored by Eugen Bauer, Johannes Zimmermann, Federico Baldini, Ines Thiele, Christoph Kaleta
Date Published: 2017
DOI: 10.1371/journal.pcbi.1005544
Sponsors:
German Research Foundation (Deutsche Forschungsgemeinschaft, DFG)
French National Research Agency (ANR)
Platforms:
R
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
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.
Tags
growth
Escherichia-coli
In-silico
Chain fatty-acids
Spatial-organization
Biofilms
Gut microbiota
Carbon-dioxide
Pathogen pseudomonas-aeruginosa
Mucin
dynamics