Multi-species community of a minimal human intestinal microbiota (SIHUMI) in rich medium.

<p><b>A</b> Spatial population structure in the exponential phase after simulating 8 hours under a uniformly distributed rich medium (all possible metabolites that can be taken up are added to the environment), with <b>B</b> the growth curves of each species. <b>C</b> Spatial population structure in the exponential phase after 8 hours simulation time under a uniformly distributed rich medium with a spatial gradient of mucus glycans, with <b>D</b> the growth curves of each species. The curve range shows the standard deviation of 10 replicate simulations.</p

Multi-species community of a minimal human intestinal microbiota (SIHUMI) in rich medium.

<p><b>A</b> Spatial population structure in the exponential phase after simulating 8 hours under a uniformly distributed rich medium (all possible metabolites that can be taken up are added to the environment), with <b>B</b> the growth curves of each species. <b>C</b> Spatial population structure in the exponential phase after 8 hours simulation time under a uniformly distributed rich medium with a spatial gradient of mucus glycans, with <b>D</b> the growth curves of each species. The curve range shows the standard deviation of 10 replicate simulations.</p

Factor loadings of short version.

Optimized model using ant colony optimization to develop a short version to identify personality disorders in adolescence. The configuration corresponds to model 7b in Fig 1.</p

Influence of mucus glycan gradients on community dynamics.

<p><b>A</b> Comparison of simulated metabolite concentrations with experimental values based on <i>in vitro</i> SIHUMI co-cultures [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005544#pcbi.1005544.ref047" target="_blank">47</a>]. <b>B</b> Metabolite secretion rates of different microbes in our SIHUMI model, determined by the overall metabolic secretion flux of the populations comprising all individuals. <b>C</b> Emerging metabolic interaction network of different fermentation products that can be exchanged between the microbe population in our SIHUMI model. Nodes represent species and edges represent exchanged metabolites, which are directed from the secreting species to the consuming species. The secretion and uptake was determined by the overall metabolic flux of the populations comprising all individuals.</p

Different configural assumptions tested for the long version.

Different configural assumptions tested for the long version.</p

LoPF-Q 12–18 model.

(PDF)</p

Confirmatory factor analyses (CFA) testing different factorial assumptions (long version).

Confirmatory factor analyses (CFA) testing different factorial assumptions (long version).</p

Schematic overview of BacArena.

<p>Microbial species are shown in different colors. Fluxes of exchange reactions are indicated as uni-directional arrows, movement and replication as bi-directional arrows.</p

Runtime of BacArena in relation to the number of added individuals and species.

<p><b>A</b> Runtime based on an example draft metabolic model (<i>Clostridium</i> sp. SY8519 model taken from [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005544#pcbi.1005544.ref030" target="_blank">30</a>]) with an increasing number of individuals added to an environment with a dimension of 50 times 50 grid cells. <b>B</b> Runtime based on an increasing number of species (301 draft metabolic models taken from [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005544#pcbi.1005544.ref030" target="_blank">30</a>]) added to an environment with a dimension of 50 times 50 grid cells and one simulation step. All simulations were run on a windows machine with 32GB of RAM and a 3.5GHz processor with four physical cores.</p

List of rules implemented in BacArena and their corresponding references obtained from experimental studies.

<p>List of rules implemented in BacArena and their corresponding references obtained from experimental studies.</p