{"doi":"10.1073/pnas.0804953105","title":"Growth-rate-dependent partitioning of RNA polymerases in bacteria","abstract":"<jats:p>\n                    Physiological changes that result in changes in bacterial gene expression are often accompanied by changes in the growth rate for fast adapting enteric bacteria. Because the availability of RNA polymerase (RNAP) in cells depends on the growth rate, transcriptional control involves not only the regulation of promoters, but also depends on the available (or free) RNAP concentration, which is difficult to quantify directly. Here, we develop a simple physical model describing the partitioning of cellular RNAP into different classes: RNAPs transcribing mRNA and ribosomal RNA (rRNA), RNAPs nonspecifically bound to DNA, free RNAP, and immature RNAP. Available experimental data for\n                    <jats:italic>Escherichia coli</jats:italic>\n                    allow us to determine the 2 unknown parameters of the model and hence deduce the free RNAP concentration at different growth rates. The results allow us to predict the growth-rate dependence of the activities of constitutive (unregulated) promoters, and to disentangle the growth-rate-dependent regulation of promoters (e.g., the promoters of rRNA operons) from changes in transcription due to changes in the free RNAP concentration at different growth rates. Our model can quantitatively account for the observed changes in gene expression patterns in mutant\n                    <jats:italic>E. coli</jats:italic>\n                    strains with altered levels of RNAP expression without invoking additional parameters. Applying our model to the case of the stringent response after amino acid starvation, we can evaluate the plausibility of various scenarios of passive transcriptional control proposed to account for the observed changes in the expression of rRNA and biosynthetic operons.\n                  </jats:p>","journal":"Proceedings of the National Academy of Sciences","year":2008,"id":595055,"datarank":0.8182981673036553,"base_score":5.455321115357702,"endowment":5.455321115357702,"self_citation_contribution":0.8182981673036553,"citation_network_contribution":0.0,"self_endowment_contribution":0.8182981673036553,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":233,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":268940,"name":"Terence Hwa","orcid":"0000-0003-1837-6842","position":1,"is_corresponding":false},{"id":1523564,"name":"Stefan Klumpp","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Growth-rate-dependent partitioning of RNA polymerases in bacteria","abstract":"<jats:p>\n                    Physiological changes that result in changes in bacterial gene expression are often accompanied by changes in the growth rate for fast adapting enteric bacteria. Because the availability of RNA polymerase (RNAP) in cells depends on the growth rate, transcriptional control involves not only the regulation of promoters, but also depends on the available (or free) RNAP concentration, which is difficult to quantify directly. Here, we develop a simple physical model describing the partitioning of cellular RNAP into different classes: RNAPs transcribing mRNA and ribosomal RNA (rRNA), RNAPs nonspecifically bound to DNA, free RNAP, and immature RNAP. Available experimental data for\n                    <jats:italic>Escherichia coli</jats:italic>\n                    allow us to determine the 2 unknown parameters of the model and hence deduce the free RNAP concentration at different growth rates. The results allow us to predict the growth-rate dependence of the activities of constitutive (unregulated) promoters, and to disentangle the growth-rate-dependent regulation of promoters (e.g., the promoters of rRNA operons) from changes in transcription due to changes in the free RNAP concentration at different growth rates. Our model can quantitatively account for the observed changes in gene expression patterns in mutant\n                    <jats:italic>E. coli</jats:italic>\n                    strains with altered levels of RNAP expression without invoking additional parameters. Applying our model to the case of the stringent response after amino acid starvation, we can evaluate the plausibility of various scenarios of passive transcriptional control proposed to account for the observed changes in the expression of rRNA and biosynthetic operons.\n                  </jats:p>","is_dataset_classified":null,"base_score":5.455321115357702,"endowment":5.455321115357702,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19073937","pmcid":"PMC2629260","openalex_id":"https://openalex.org/W2010420771","authors":[],"funders":[{"funder_name":"NIGMS NIH HHS","grant_id":"R01 GM077298","title":null},{"funder_name":"National Science Foundation","grant_id":"0216576","title":"Center for Theoretical Biological Physics"},{"funder_name":"National Science Foundation","grant_id":"0225630","title":"ITR: Center for Computational Biophysics"},{"funder_name":"National Science Foundation","grant_id":"0746581","title":"Quantitative Studies of Nitrogen Assimilation & Its Control in Enteric Bacteria: From Molecules to Physiology"}],"total_grants":4,"fwci":4.5743,"citation_percentile":0.94908142,"influential_citations":0,"citation_trend":[{"year":2012,"count":10},{"year":2013,"count":16},{"year":2014,"count":22},{"year":2015,"count":17},{"year":2016,"count":6},{"year":2017,"count":13},{"year":2018,"count":12},{"year":2019,"count":19},{"year":2020,"count":23},{"year":2021,"count":16},{"year":2022,"count":13},{"year":2023,"count":12},{"year":2024,"count":10},{"year":2025,"count":7},{"year":2026,"count":12}],"oa_status":"green","license":"arXiv Non-Exclusive Distribution","oa_locations":[{"url":"https://arxiv.org/pdf/0812.2057","host_type":"repository"},{"url":"https://arxiv.org/pdf/0812.2057","host_type":"repository"},{"url":"https://pnas.org/doi/pdf/10.1073/pnas.0804953105","host_type":"publisher"},{"url":"http://arxiv.org/abs/0812.2057","host_type":"repository"},{"url":"https://doi.org/10.1073/pnas.0804953105","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/19073937","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/2629260","host_type":"repository"},{"url":"http://www.pnas.org/content/105/51/20245.full.pdf","host_type":""},{"url":"https://dx.doi.org/10.48550/arxiv.0812.2057","host_type":""},{"url":"https://dx.doi.org/10.1073/pnas.0804953105","host_type":""}],"fields_of_study":["Bacterial Genetics and Biotechnology","Diffusion and Search Dynamics","RNA and protein synthesis mechanisms","0301 basic medicine","0303 health sciences","03 medical and health sciences"],"mesh_terms":["Bacteria","Gene Expression Regulation","Operon","Promoter Regions, Genetic","DNA-Directed RNA Polymerases","RNA, Ribosomal","Escherichia coli Proteins"],"keywords":["Stringent response","RNA polymerase","Promoter","Operon","Biology","RNA","Transcription (linguistics)","Gene expression","Polymerase","Gene","DNA","Bacterial transcription","Mutant","Escherichia coli","Cell biology","Genetics","Quantitative Biology - Subcellular Processes","Bacteria","Gene Expression Regulation","RNA, Ribosomal","Escherichia coli Proteins","FOS: Biological sciences","DNA-Directed RNA Polymerases","Promoter Regions, Genetic","Subcellular Processes (q-bio.SC)"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-27T16:26:36.286847Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}