{"title":"Genome replication in asynchronously growing microbial populations","authors":"Florian Pflug, Deepak Bhat, Simone Pigolotti","doi":"arxiv-2308.12664","DOIUrl":null,"url":null,"abstract":"Biological cells adopt specific programs to replicate their genomes.\nInformation about the replication program of an organism can be obtained by\nsequencing an exponentially growing cell culture and studying the frequency of\nDNA fragments as a function of genomic position. However, a quantitative\ninterpretation of this data has been challenging for asynchronously growing\ncultures. In this paper, we introduce a general theory to predict the abundance\nof DNA fragments in asynchronously growing cultures from any given stochastic\nmodel of the DNA replication program. As key examples, we present stochastic\nmodels of DNA replication in Escherichia coli and in budding yeast. In both\ncases, our approach leads to analytical predictions that are in excellent\nagreement with experimental data and permit to infer biophysically relevant\nparameters. In particular, our method is able to infer the locations of known\nreplication origins in budding yeast with high accuracy. These examples\ndemonstrate that our method can provide insight into a broad range of\norganisms, from bacteria to eukaryotes.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"58 48","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-24","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-2308.12664","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
Biological cells adopt specific programs to replicate their genomes.
Information about the replication program of an organism can be obtained by
sequencing an exponentially growing cell culture and studying the frequency of
DNA fragments as a function of genomic position. However, a quantitative
interpretation of this data has been challenging for asynchronously growing
cultures. In this paper, we introduce a general theory to predict the abundance
of DNA fragments in asynchronously growing cultures from any given stochastic
model of the DNA replication program. As key examples, we present stochastic
models of DNA replication in Escherichia coli and in budding yeast. In both
cases, our approach leads to analytical predictions that are in excellent
agreement with experimental data and permit to infer biophysically relevant
parameters. In particular, our method is able to infer the locations of known
replication origins in budding yeast with high accuracy. These examples
demonstrate that our method can provide insight into a broad range of
organisms, from bacteria to eukaryotes.