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• W4323348560 abstract "Crowding effects critically impact the self-organization of densely packed cellular assemblies, such as biofilms, solid tumors, and developing tissues. When cells grow and divide, they push each other apart, remodeling the structure and extent of the population's range. Recent work has shown that crowding has a strong impact on the strength of natural selection. However, the impact of crowding on neutral processes, which controls the fate of new variants as long as they are rare, remains unclear. Here, we quantify the genetic diversity of expanding microbial colonies and uncover signatures of crowding in the site frequency spectrum. By combining Luria-Delbrück fluctuation tests, lineage tracing in a novel microfluidic incubator, cell-based simulations, and theoretical modeling, we find that the majority of mutations arise behind the expanding frontier, giving rise to clones that are mechanically pushed out of the growing region by the proliferating cells in front. These excluded-volume interactions result in a clone-size distribution that solely depends on where the mutation first arose relative to the front and is characterized by a simple power law for low-frequency clones. Our model predicts that the distribution depends on a single parameter-the characteristic growth layer thickness-and hence allows estimation of the mutation rate in a variety of crowded cellular populations. Combined with previous studies on high-frequency mutations, our finding provides a unified picture of the genetic diversity in expanding populations over the whole frequency range and suggests a practical method to assess growth dynamics by sequencing populations across spatial scales." @default.
• W4323348560 created "2023-03-08" @default.
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• W4323348560 date "2023-03-07" @default.
• W4323348560 modified "2023-10-03" @default.
• W4323348560 title "Impact of crowding on the diversity of expanding populations" @default.
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• W4323348560 doi "https://doi.org/10.1073/pnas.2208361120" @default.
• W4323348560 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36881622" @default.
• W4323348560 hasPublicationYear "2023" @default.
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