{"language":[{"iso":"eng"}],"intvolume":"        13","publist_id":"5815","oa_version":"Preprint","issue":"3","quality_controlled":"1","scopus_import":1,"title":"Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1601.03243"}],"date_published":"2016-05-27T00:00:00Z","day":"27","year":"2016","publisher":"IOP Publishing Ltd.","ec_funded":1,"type":"journal_article","date_updated":"2021-01-12T06:50:23Z","volume":13,"abstract":[{"text":"The solution space of genome-scale models of cellular metabolism provides a map between physically\r\nviable flux configurations and cellular metabolic phenotypes described, at the most basic level, by the\r\ncorresponding growth rates. By sampling the solution space of E. coliʼs metabolic network, we show\r\nthat empirical growth rate distributions recently obtained in experiments at single-cell resolution can\r\nbe explained in terms of a trade-off between the higher fitness of fast-growing phenotypes and the\r\nhigher entropy of slow-growing ones. Based on this, we propose a minimal model for the evolution of\r\na large bacterial population that captures this trade-off. The scaling relationships observed in\r\nexperiments encode, in such frameworks, for the same distance from the maximum achievable growth\r\nrate, the same degree of growth rate maximization, and/or the same rate of phenotypic change. Being\r\ngrounded on genome-scale metabolic network reconstructions, these results allow for multiple\r\nimplications and extensions in spite of the underlying conceptual simplicity.","lang":"eng"}],"article_number":"036005","publication_status":"published","publication":"Physical Biology","_id":"1394","author":[{"full_name":"De Martino, Daniele","first_name":"Daniele","orcid":"0000-0002-5214-4706","last_name":"De Martino","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Capuani","first_name":"Fabrizio","full_name":"Capuani, Fabrizio"},{"full_name":"De Martino, Andrea","first_name":"Andrea","last_name":"De Martino"}],"doi":"10.1088/1478-3975/13/3/036005","month":"05","date_created":"2018-12-11T11:51:46Z","citation":{"ieee":"D. De Martino, F. Capuani, and A. De Martino, “Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli,” <i>Physical Biology</i>, vol. 13, no. 3. IOP Publishing Ltd., 2016.","mla":"De Martino, Daniele, et al. “Growth against Entropy in Bacterial Metabolism: The Phenotypic Trade-off behind Empirical Growth Rate Distributions in E. Coli.” <i>Physical Biology</i>, vol. 13, no. 3, 036005, IOP Publishing Ltd., 2016, doi:<a href=\"https://doi.org/10.1088/1478-3975/13/3/036005\">10.1088/1478-3975/13/3/036005</a>.","ama":"De Martino D, Capuani F, De Martino A. Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. <i>Physical Biology</i>. 2016;13(3). doi:<a href=\"https://doi.org/10.1088/1478-3975/13/3/036005\">10.1088/1478-3975/13/3/036005</a>","short":"D. De Martino, F. Capuani, A. De Martino, Physical Biology 13 (2016).","apa":"De Martino, D., Capuani, F., &#38; De Martino, A. (2016). Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. <i>Physical Biology</i>. IOP Publishing Ltd. <a href=\"https://doi.org/10.1088/1478-3975/13/3/036005\">https://doi.org/10.1088/1478-3975/13/3/036005</a>","ista":"De Martino D, Capuani F, De Martino A. 2016. Growth against entropy in bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions in E. coli. Physical Biology. 13(3), 036005.","chicago":"De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Growth against Entropy in Bacterial Metabolism: The Phenotypic Trade-off behind Empirical Growth Rate Distributions in E. Coli.” <i>Physical Biology</i>. IOP Publishing Ltd., 2016. <a href=\"https://doi.org/10.1088/1478-3975/13/3/036005\">https://doi.org/10.1088/1478-3975/13/3/036005</a>."},"acknowledgement":"The research leading to these results has received funding from the from the Marie\r\nCurie Action ITN NETADIS, grant agreement no. 290038.","department":[{"_id":"GaTk"}],"oa":1,"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","status":"public","project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425"}]}