Charles S. Wright, Kunaal Joshi, Rudro R. Biswas, Srividya Iyer-Biswas
{"title":"Emergent Simplicities in the Living Histories of Individual Cells","authors":"Charles S. Wright, Kunaal Joshi, Rudro R. Biswas, Srividya Iyer-Biswas","doi":"arxiv-2404.01682","DOIUrl":null,"url":null,"abstract":"Organisms maintain the status quo, holding key physiological variables\nconstant to within an acceptable tolerance, and yet adapt with precision and\nplasticity to dynamic changes in externalities. What organizational principles\nensure such exquisite yet robust control of systems-level \"state variables\" in\ncomplex systems with an extraordinary number of moving parts and fluctuating\nvariables? Here we focus on these issues in the specific context of intra- and\nintergenerational life histories of individual bacterial cells, whose\nbiographies are precisely charted via high-precision dynamic experiments using\nthe SChemostat technology. We highlight intra- and intergenerational scaling\nlaws and other \"emergent simplicities\" revealed by these high-precision data.\nIn turn, these facilitate a principled route to dimensional reduction of the\nproblem, and serve as essential building blocks for phenomenological and\nmechanistic theory. Parameter-free data-theory matches for multiple organisms\nvalidate theory frameworks, and explicate the systems physics of stochastic\nhomeostasis and adaptation.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"38 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Cell Behavior","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2404.01682","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
Organisms maintain the status quo, holding key physiological variables
constant to within an acceptable tolerance, and yet adapt with precision and
plasticity to dynamic changes in externalities. What organizational principles
ensure such exquisite yet robust control of systems-level "state variables" in
complex systems with an extraordinary number of moving parts and fluctuating
variables? Here we focus on these issues in the specific context of intra- and
intergenerational life histories of individual bacterial cells, whose
biographies are precisely charted via high-precision dynamic experiments using
the SChemostat technology. We highlight intra- and intergenerational scaling
laws and other "emergent simplicities" revealed by these high-precision data.
In turn, these facilitate a principled route to dimensional reduction of the
problem, and serve as essential building blocks for phenomenological and
mechanistic theory. Parameter-free data-theory matches for multiple organisms
validate theory frameworks, and explicate the systems physics of stochastic
homeostasis and adaptation.