@article {70230, title = {Evidence for a multi-level trophic organization of the human gut microbiome.}, journal = {PLoS Comput Biol}, volume = {15}, year = {2019}, month = {2019 Dec}, pages = {e1007524}, abstract = {

The human gut microbiome is a complex ecosystem, in which hundreds of microbial species and metabolites coexist, in part due to an extensive network of cross-feeding interactions. However, both the large-scale trophic organization of this ecosystem, and its effects on the underlying metabolic flow, remain unexplored. Here, using a simplified model, we provide quantitative support for a multi-level trophic organization of the human gut microbiome, where microbes consume and secrete metabolites in multiple iterative steps. Using a manually-curated set of metabolic interactions between microbes, our model suggests about four trophic levels, each characterized by a high level-to-level metabolic transfer of byproducts. It also quantitatively predicts the typical metabolic environment of the gut (fecal metabolome) in approximate agreement with the real data. To understand the consequences of this trophic organization, we quantify the metabolic flow and biomass distribution, and explore patterns of microbial and metabolic diversity in different levels. The hierarchical trophic organization suggested by our model can help mechanistically establish causal links between the abundances of microbes and metabolites in the human gut.

}, issn = {1553-7358}, doi = {10.1371/journal.pcbi.1007524}, author = {Wang, Tong and Goyal, Akshit and Dubinkina, Veronika and Maslov, Sergei} } @article {36260, title = {Diversity, Stability, and Reproducibility in Stochastically Assembled Microbial Ecosystems.}, journal = {Phys Rev Lett}, volume = {120}, year = {2018}, month = {2018 Apr 13}, pages = {158102}, abstract = {

Microbial ecosystems are remarkably diverse, stable, and usually consist of a mixture of core and peripheral species. Here we propose a conceptual model exhibiting all these emergent properties in quantitative agreement with real ecosystem data, specifically species abundance and prevalence distributions. Resource competition and metabolic commensalism drive the stochastic ecosystem assembly in our model. We demonstrate that even when supplied with just one resource, ecosystems can exhibit high diversity, increasing stability, and partial reproducibility between samples.

}, keywords = {Ecosystem, Microbiota, Models, Biological, Stochastic Processes}, issn = {1079-7114}, doi = {10.1103/PhysRevLett.120.158102}, author = {Goyal, Akshit and Maslov, Sergei} } @article {39422, title = {Multiple stable states in microbial communities explained by the stable marriage problem.}, journal = {ISME J}, year = {2018}, month = {2018 Jul 19}, abstract = {

Experimental studies of microbial communities routinely reveal that they have multiple stable states. While each of these states is generally resilient, certain perturbations such as antibiotics, probiotics, and diet shifts, result in transitions to other states. Can we reliably both predict such stable states as well as direct and control transitions between them? Here we present a new conceptual model-inspired by the stable marriage problem in game theory and economics-in which microbial communities naturally exhibit multiple stable states, each state with a different species{\textquoteright} abundance profile. Our model{\textquoteright}s core ingredient is that microbes utilize nutrients one at a time while competing with each other. Using only two ranked tables, one with microbes{\textquoteright} nutrient preferences and one with their competitive abilities, we can determine all possible stable states as well as predict inter-state transitions, triggered by the removal or addition of a specific nutrient or microbe. Further, using an example of seven Bacteroides species common to the human gut utilizing nine polysaccharides, we predict that mutual complementarity in nutrient preferences enables these species to coexist at high abundances.

}, issn = {1751-7370}, doi = {10.1038/s41396-018-0222-x}, author = {Goyal, Akshit and Dubinkina, Veronika and Maslov, Sergei} }