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Biol."],"published-print":{"date-parts":[[2015,1]]},"abstract":"<jats:p>Fluctuating environments pose tremendous challenges to bacterial populations. It is observed in numerous bacterial species that individual cells can stochastically switch among multiple phenotypes for the population to survive in rapidly changing environments. This kind of phenotypic heterogeneity with stochastic phenotype switching is generally understood to be an adaptive bet\u2010hedging strategy. Mathematical models are essential to gain a deeper insight into the principle behind bet\u2010hedging and the pattern behind experimental data. Traditional deterministic models cannot provide a correct description of stochastic phenotype switching and bet\u2010hedging, and traditional Markov chain models at the cellular level fail to explain their underlying molecular mechanisms. In this paper, we propose a nonlinear stochastic model of multistable bacterial systems at the molecular level. It turns out that our model not only provides a clear description of stochastic phenotype switching and bet\u2010hedging within isogenic bacterial populations, but also provides a deeper insight into the analysis of multidimensional experimental data. Moreover, we use some deep mathematical theories to show that our stochastic model and traditional Markov chain models are essentially consistent and reflect the dynamic behavior of the bacterial system at two different time scales. In addition, we provide a quantitative characterization of the critical state of multistable bacterial systems and develop an effective data\u2010driven method to identify the critical state without resorting to specific mathematical models.<\/jats:p>","DOI":"10.1007\/s40484-014-0035-5","type":"journal-article","created":{"date-parts":[[2015,1,12]],"date-time":"2015-01-12T10:08:26Z","timestamp":1421057306000},"page":"110-125","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Modeling stochastic phenotype switching and bet\u2010hedging in bacteria: stochastic nonlinear dynamics and critical state identification"],"prefix":"10.1002","volume":"2","author":[{"given":"Chen","family":"Jia","sequence":"first","affiliation":[{"name":"<!--1--> LMAM School of Mathematical Sciences Peking University Beijing 100871 China"},{"name":"<!--2--> Beijing International Center for Mathematical Research Beijing 100871 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minping","family":"Qian","sequence":"additional","affiliation":[{"name":"<!--1--> LMAM School of Mathematical Sciences Peking University Beijing 100871 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Kang","sequence":"additional","affiliation":[{"name":"<!--3--> CAS Key Laboratory of Genome Sciences and Information Beijing Institute of Genomics Chinese Academy of Sciences Beijing 100101 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daquan","family":"Jiang","sequence":"additional","affiliation":[{"name":"<!--1--> LMAM School of Mathematical Sciences Peking University Beijing 100871 China"},{"name":"<!--4--> Center for Statistical Science Peking University Beijing 100871 China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2015,1]]},"reference":[{"key":"e_1_2_8_2_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.1114383"},{"key":"e_1_2_8_3_2","doi-asserted-by":"publisher","DOI":"10.1038\/nrmicro1381"},{"key":"e_1_2_8_4_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365\u20102958.2006.05249.x"},{"key":"e_1_2_8_5_2","doi-asserted-by":"publisher","DOI":"10.1038\/nrmicro1460"},{"key":"e_1_2_8_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.mib.2006.12.007"},{"key":"e_1_2_8_7_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0706115104"},{"key":"e_1_2_8_8_2","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.micro.62.081307.163002"},{"key":"e_1_2_8_9_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365\u20102958.2009.06605.x"},{"key":"e_1_2_8_10_2","doi-asserted-by":"publisher","DOI":"10.1086\/598822"},{"key":"e_1_2_8_11_2","doi-asserted-by":"publisher","DOI":"10.1038\/nrm3044"},{"key":"e_1_2_8_12_2","doi-asserted-by":"publisher","DOI":"10.1021\/sb4002008"},{"key":"e_1_2_8_13_2","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.113.108102"},{"key":"e_1_2_8_14_2","doi-asserted-by":"publisher","DOI":"10.1038\/ng.110"},{"key":"e_1_2_8_15_2","doi-asserted-by":"publisher","DOI":"10.1534\/genetics.109.103333"},{"key":"e_1_2_8_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.mib.2008.09.020"},{"key":"e_1_2_8_17_2","doi-asserted-by":"publisher","DOI":"10.1534\/genetics.109.113431"},{"key":"e_1_2_8_18_2","doi-asserted-by":"publisher","DOI":"10.1098\/rspb.2011.0146"},{"key":"e_1_2_8_19_2","doi-asserted-by":"publisher","DOI":"10.1186\/1475\u20102859\u201010\u2010S1\u2010S14"},{"key":"e_1_2_8_20_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature02298"},{"key":"e_1_2_8_21_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature04588"},{"key":"e_1_2_8_22_2","doi-asserted-by":"publisher","DOI":"10.1038\/msb4100064"},{"key":"e_1_2_8_23_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0707965104"},{"key":"e_1_2_8_24_2","doi-asserted-by":"crossref","unstructured":"Sonenshein A.L. 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