{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T06:19:25Z","timestamp":1772173165708,"version":"3.50.1"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1010565","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2022,10,18]],"date-time":"2022-10-18T00:00:00Z","timestamp":1666051200000}}],"reference-count":39,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2022,10,3]],"date-time":"2022-10-03T00:00:00Z","timestamp":1664755200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Rappaport Family Institute for Research in the Medical Sciences"},{"DOI":"10.13039\/501100007426","name":"Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100007426","id-type":"DOI","asserted-by":"publisher"}]},{"name":"UOM-Israel collaboration"},{"DOI":"10.13039\/501100001320","name":"The Wolfson Foundation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100001320","id-type":"DOI","asserted-by":"crossref"}]},{"name":"ISF","award":["1860\/21"],"award-info":[{"award-number":["1860\/21"]}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>\n                    Although closely related, bacterial strains from the same species show significant diversity in their growth and death dynamics. Yet, our understanding of the relationship between the kinetic parameters that dictate these dynamics is still lacking. Here, we measured the growth and death dynamics of 11 strains of\n                    <jats:italic>Escherichia coli<\/jats:italic>\n                    originating from different hosts and show that the growth patterns are clustered into three major classes with typical growth rates, maximal fold change, and death rates. To infer the underlying phenotypic parameters that govern the dynamics, we developed a phenomenological mathematical model that accounts not only for growth rate and its dependence on resource availability, but also for death rates and density-dependent growth inhibition. We show that density-dependent growth is essential for capturing the variability in growth dynamics between the strains. Indeed, the main parameter determining the dynamics is the typical density at which they slow down their growth, rather than the maximal growth rate or death rate. Moreover, we show that the phenotypic landscape resides within a two-dimensional plane spanned by resource utilization efficiency, death rate, and density-dependent growth inhibition. In this phenotypic plane, we identify three clusters that correspond to the growth pattern classes. Overall, our results reveal the tradeoffs between growth parameters that constrain bacterial adaptation.\n                  <\/jats:p>","DOI":"10.1371\/journal.pcbi.1010565","type":"journal-article","created":{"date-parts":[[2022,10,3]],"date-time":"2022-10-03T13:55:31Z","timestamp":1664805331000},"page":"e1010565","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":8,"title":["Density-dependent effects are the main determinants of variation in growth dynamics between closely related bacterial strains"],"prefix":"10.1371","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8573-7703","authenticated-orcid":true,"given":"Sabrin","family":"Hilau","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9114-2466","authenticated-orcid":true,"given":"Sophia","family":"Katz","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0221-1891","authenticated-orcid":true,"given":"Tanya","family":"Wasserman","sequence":"additional","affiliation":[]},{"given":"Ruth","family":"Hershberg","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5345-8491","authenticated-orcid":true,"given":"Yonatan","family":"Savir","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2022,10,3]]},"reference":[{"key":"pcbi.1010565.ref001","first-page":"1157","article-title":"Evolutionary trade-offs, pareto optimality, and the geometry of phenotype space","volume":"336","author":"O Shoval","year":"2012","journal-title":"Science (1979)"},{"key":"pcbi.1010565.ref002","doi-asserted-by":"crossref","first-page":"3475","DOI":"10.1073\/pnas.0911663107","article-title":"Cross-species analysis traces adaptation of Rubisco toward optimality in a low-dimensional landscape","volume":"107","author":"Y Savir","year":"2010","journal-title":"Proc Natl Acad Sci U S A"},{"key":"pcbi.1010565.ref003","first-page":"1","article-title":"Experimental evolution reveals hidden diversity in evolutionary pathways","volume":"2015","author":"PA Lind","year":"2015","journal-title":"Elife"},{"key":"pcbi.1010565.ref004","doi-asserted-by":"crossref","first-page":"14302","DOI":"10.1073\/pnas.1308523110","article-title":"Availability of public goods shapes the evolution of competing metabolic strategies","volume":"110","author":"H Bachmann","year":"2013","journal-title":"Proc Natl Acad Sci U S A"},{"key":"pcbi.1010565.ref005","doi-asserted-by":"crossref","first-page":"1","DOI":"10.7554\/eLife.24669","article-title":"Environment determines evolutionary trajectory in a constrained phenotypic space","volume":"6","author":"DT Fraebel","year":"2017","journal-title":"Elife"},{"key":"pcbi.1010565.ref006","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fmicb.2015.00254","article-title":"Microbial resource utilization traits and trade-offs: Implications for community structure, functioning, and biogeochemical impacts at present and in the future","volume":"6","author":"E Litchman","year":"2015","journal-title":"Front Microbiol."},{"key":"pcbi.1010565.ref007","first-page":"1","article-title":"Laboratory evolution reveals a two-dimensional rate-yield tradeoff in microbial metabolism","volume":"15","author":"O Cheng C","year":"2019","journal-title":"PLoS Comput Biol"},{"key":"pcbi.1010565.ref008","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fmicb.2015.00615","article-title":"The complex relationship between microbial growth rate and yield and its implications for ecosystem processes","volume":"6","author":"DA Lipson","year":"2015","journal-title":"Front Microbiol"},{"key":"pcbi.1010565.ref009","doi-asserted-by":"crossref","first-page":"1758","DOI":"10.1093\/molbev\/msx118","article-title":"Rapid Genetic Adaptation during the First Four Months of Survival under Resource Exhaustion","volume":"34","author":"S Avrani","year":"2017","journal-title":"Mol Biol Evol"},{"key":"pcbi.1010565.ref010","first-page":"1","article-title":"Bacterial growth: A statistical physicist\u2019s guide","author":"RJ Allen","year":"2019","journal-title":"Reports on Progress in Physics"},{"key":"pcbi.1010565.ref011","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1038\/nrendo.2016.150","article-title":"Role of the gut microbiota in host appetite control: Bacterial growth to animal feeding behaviour","volume":"13","author":"SO Fetissov","year":"2017","journal-title":"Nat Rev Endocrinol"},{"key":"pcbi.1010565.ref012","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1038\/131061a0","article-title":"Ford HD. 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