Percolation and lifestyle transition in microbial metabolism
Supo-Escalante, R.; Plata, G.; Usmanova, D. R.; Vitkup, D.
Show abstract
Microbial species exhibit a remarkable diversity in their metabolic properties, genome composition, and ecological distribution. A central challenge of systems biology is to understand the relationships between genomic, metabolic, and phenotypic properties of bacteria. However, it is currently not well understood how the structure of metabolic network defines and reflects the lifestyle of diverse bacterial species across the tree of life. By analyzing thousands of genome-scale metabolic models of bacteria, we found a percolation-like transition in their ability to grow on independent carbon sources at around 800 metabolic reactions or about 2000 protein-coding genes. The observed transition is characterized by significant changes in metabolic network functional connectivity primarily associated with the completion of central carbon metabolism and the TCA cycle. Strikingly, experimentally observed phenotypic properties of bacteria also exhibit two markedly different regimes below and above the transition. Species with metabolic network sizes below the transition are typically obligate symbionts and require complex minimal media for their growth. In contrast, species with networks above the transition are primarily free- living generalists. The observed percolation transition is also reflected in multiple other genomic properties, such as a substantial decrease in the fraction of regulatory genes below the transition and higher evolvability for new metabolic phenotypes above the transition. Furthermore, we find that the distribution of bacterial genome sizes from unbiased environmental metagenomic sequencing also reflects genomic clusters corresponding to the observed transition. Overall, our work identifies two qualitatively different regimes in microbial metabolism and lifestyles characterized by distinct structural and functional properties of their metabolic networks.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Coarse-Grained Model of Serial Dilution Dynamics in Synthetic Human Gut Microbiome 95%
- Pathway-based and phylogenetically adjusted quantification of metabolic interaction between microbial species 95%
- BEEM-Static: Accurate inference of ecological interactions from cross-sectional metagenomic data 94%
Similar papers in this journal
- Metabolic rules of microbial community assembly 96%
- Guiding the Refinement of Biochemical Knowledgebases with Ensembles of Metabolic Networks and Machine Learning 96%
- APOLLO: A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.