Collective colony growth is optimized by branching pattern formation in Pseudomonas aeruginosa
| Autor: | Jia Lu, Xiaoyi Ouyang, Lingchong You, Nan Luo, Shangying Wang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Medicine (General)
QH301-705.5 Colony Count Microbial Pattern formation Biology medicine.disease_cause Models Biological General Biochemistry Genetics and Molecular Biology Article Branching (linguistics) 03 medical and health sciences 0302 clinical medicine R5-920 branching pattern pattern formation medicine coarse‐grained modeling bacterial colony Computer Simulation Biomass Biology (General) Coarse-grained modeling 030304 developmental biology 0303 health sciences General Immunology and Microbiology Pseudomonas aeruginosa Applied Mathematics optimization model Articles Microbiology Virology & Host Pathogen Interaction Computational Theory and Mathematics Evolutionary biology Spatial ecology General Agricultural and Biological Sciences Synthetic Biology & Biotechnology 030217 neurology & neurosurgery Information Systems Bacterial colony |
| Zdroj: | Molecular Systems Biology Molecular Systems Biology, Vol 17, Iss 4, Pp n/a-n/a (2021) |
| ISSN: | 1744-4292 |
| Popis: | Branching pattern formation is common in many microbes. Extensive studies have focused on addressing how such patterns emerge from local cell–cell and cell–environment interactions. However, little is known about whether and to what extent these patterns play a physiological role. Here, we consider the colonization of bacteria as an optimization problem to find the colony patterns that maximize colony growth efficiency under different environmental conditions. We demonstrate that Pseudomonas aeruginosa colonies develop branching patterns with characteristics comparable to the prediction of modeling; for example, colonies form thin branches in a nutrient‐poor environment. Hence, the formation of branching patterns represents an optimal strategy for the growth of Pseudomonas aeruginosa colonies. The quantitative relationship between colony patterns and growth conditions enables us to develop a coarse‐grained model to predict diverse colony patterns under more complex conditions, which we validated experimentally. Our results offer new insights into branching pattern formation as a problem‐solving social behavior in microbes and enable fast and accurate predictions of complex spatial patterns in branching colonies. Optimization modeling demonstrates that branching patterns maximize the growth efficiency of Pseudomonas colonies in adverse environments. An optimization rule of pattern formation provides a new way of predicting complex colony patterns. |
| Databáze: | OpenAIRE |
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