{"title":"Impact of micro-habitat fragmentation on microbial population growth dynamics","authors":"Dina Mant, Tomer Orevi, Nadav Kashtan","doi":"10.1093/ismejo/wrae256","DOIUrl":null,"url":null,"abstract":"Microbial communities thrive in virtually every habitat on Earth and are essential to the function of diverse ecosystems. Most microbial habitats are not spatially continuous and well-mixed, but rather composed, at the microscale, of many isolated or semi-isolated local patches of different sizes, resulting in partitioning of microbial populations into discrete local populations. The impact of this spatial fragmentation on population dynamics is not well-understood. Here, we study how such variably sized micro-habitat patches affect the growth dynamics of clonal microbial populations and how dynamics in individual patches dictate those of the metapopulation. To investigate this, we developed the μ-SPLASH, an ecology-on-a-chip platform, enabling the culture of microbes in microscopic landscapes comprised of thousands of microdroplets, with a wide range of sizes. Using the μ-SPLASH, we cultured the model bacteria E. coli and based on time-lapse microscopy, analyzed the population dynamics within thousands of individual droplets. Our results reveal that growth curves substantially vary with droplet size. Although growth rates generally increase with drop size, reproductive success and the time to approach carrying capacity, display non-monotonic patterns. Combining μ-SPLASH experiments with computational modeling, we show that these patterns result from both stochastic and deterministic processes, and demonstrate the roles of initial population density, patchiness, and patch size distribution in dictating the local and metapopulation dynamics. This study reveals basic principles that elucidate the effects of habitat fragmentation and population partitioning on microbial population dynamics. These insights deepen our understanding of natural microbial communities and have significant implications for microbiome engineering.","PeriodicalId":516554,"journal":{"name":"The ISME Journal","volume":"32 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The ISME Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/ismejo/wrae256","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Microbial communities thrive in virtually every habitat on Earth and are essential to the function of diverse ecosystems. Most microbial habitats are not spatially continuous and well-mixed, but rather composed, at the microscale, of many isolated or semi-isolated local patches of different sizes, resulting in partitioning of microbial populations into discrete local populations. The impact of this spatial fragmentation on population dynamics is not well-understood. Here, we study how such variably sized micro-habitat patches affect the growth dynamics of clonal microbial populations and how dynamics in individual patches dictate those of the metapopulation. To investigate this, we developed the μ-SPLASH, an ecology-on-a-chip platform, enabling the culture of microbes in microscopic landscapes comprised of thousands of microdroplets, with a wide range of sizes. Using the μ-SPLASH, we cultured the model bacteria E. coli and based on time-lapse microscopy, analyzed the population dynamics within thousands of individual droplets. Our results reveal that growth curves substantially vary with droplet size. Although growth rates generally increase with drop size, reproductive success and the time to approach carrying capacity, display non-monotonic patterns. Combining μ-SPLASH experiments with computational modeling, we show that these patterns result from both stochastic and deterministic processes, and demonstrate the roles of initial population density, patchiness, and patch size distribution in dictating the local and metapopulation dynamics. This study reveals basic principles that elucidate the effects of habitat fragmentation and population partitioning on microbial population dynamics. These insights deepen our understanding of natural microbial communities and have significant implications for microbiome engineering.