{"title":"Principles of bursty mRNA expression and irreversibility in single cells and extrinsically varying populations","authors":"James Holehouse","doi":"arxiv-2405.12897","DOIUrl":null,"url":null,"abstract":"The canonical model of mRNA expression is the telegraph model, describing a\ngene that switches on and off, subject to transcription and decay. It describes\nsteady-state mRNA distributions that subscribe to transcription in bursts with\nfirst-order decay, referred to as super-Poissonian expression. Using a\ntelegraph-like model, I propose an answer to the question of why gene\nexpression is bursty in the first place, and what benefits it confers. Using\nanalytics for the entropy production rate, I find that entropy production is\nmaximal when the on and off switching rates between the gene states are\napproximately equal. This is related to a lower bound on the free energy\nnecessary to keep the system out of equilibrium, meaning that bursty gene\nexpression may have evolved in part due to free energy efficiency. It is shown\nthat there are trade-offs between having slow nuclear export, which can reduce\ncytoplasmic mRNA noise, and the energy required to keep the system out of\nequilibrium -- nuclear compartmentalization comes with an associated free\nenergy cost. At the population level, I find that extrinsic variation,\nmanifested in cell-to-cell differences in kinetic parameters, can make the\nsystem more or less reversible -- and potentially energy efficient -- depending\non where the noise is located. This highlights that there evolutionary\nconstraints on the suppression of extrinsic noise, whose origin is in cellular\nheterogeneity, in addition to intrinsic randomness arising from molecular\ncollisions. Finally, I investigate the partially observed nature of most mRNA\nexpression data which seems to obey detailed balance, yet remains unavoidably\nout-of-equilibrium.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"27 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Subcellular Processes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2405.12897","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
The canonical model of mRNA expression is the telegraph model, describing a
gene that switches on and off, subject to transcription and decay. It describes
steady-state mRNA distributions that subscribe to transcription in bursts with
first-order decay, referred to as super-Poissonian expression. Using a
telegraph-like model, I propose an answer to the question of why gene
expression is bursty in the first place, and what benefits it confers. Using
analytics for the entropy production rate, I find that entropy production is
maximal when the on and off switching rates between the gene states are
approximately equal. This is related to a lower bound on the free energy
necessary to keep the system out of equilibrium, meaning that bursty gene
expression may have evolved in part due to free energy efficiency. It is shown
that there are trade-offs between having slow nuclear export, which can reduce
cytoplasmic mRNA noise, and the energy required to keep the system out of
equilibrium -- nuclear compartmentalization comes with an associated free
energy cost. At the population level, I find that extrinsic variation,
manifested in cell-to-cell differences in kinetic parameters, can make the
system more or less reversible -- and potentially energy efficient -- depending
on where the noise is located. This highlights that there evolutionary
constraints on the suppression of extrinsic noise, whose origin is in cellular
heterogeneity, in addition to intrinsic randomness arising from molecular
collisions. Finally, I investigate the partially observed nature of most mRNA
expression data which seems to obey detailed balance, yet remains unavoidably
out-of-equilibrium.