{"doi":"10.1101/2023.07.22.550177","title":"Metabolomic rearrangement controls the intrinsic microbial response to temperature changes","abstract":"Temperature is one of the key determinants of microbial behavior and survival, whose impact is typically studied under heat- or cold-shock conditions that elicit specific regulation to combat lethal stress. At intermediate temperatures, cellular growth rate varies according to the Arrhenius law of thermodynamics without stress responses, a behavior whose origins have not yet been elucidated. Using single-cell microscopy during temperature perturbations, we show that bacteria exhibit a highly conserved, gradual response to temperature upshifts with a time scale of ~1.5 doublings at the higher temperature, regardless of initial/final temperature or nutrient source. We find that this behavior is coupled to a temperature memory, which we rule out as being neither transcriptional, translational, nor membrane dependent. Instead, we demonstrate that an autocatalytic enzyme network incorporating temperature-sensitive Michaelis-Menten kinetics recapitulates all temperature-shift dynamics through metabolome rearrangement, which encodes a temperature memory and successfully predicts alterations in the upshift response observed under simple-sugar, low-nutrient conditions, and in fungi. This model also provides a mechanistic framework for both Arrhenius-dependent growth and the classical Monod Equation through temperature-dependent metabolite flux.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2023,"id":393483,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9554,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":310233,"name":"Lisa Willis","orcid":"0000-0003-0568-1442","position":1,"is_corresponding":false},{"id":392588,"name":"Carlos G. Gonzalez","orcid":"0000-0002-4673-4048","position":2,"is_corresponding":false},{"id":1167550,"name":"Harsh Vashistha","orcid":"0000-0002-9411-5137","position":3,"is_corresponding":false},{"id":1168026,"name":"Joanna Jammal Touma","orcid":null,"position":4,"is_corresponding":false},{"id":850664,"name":"Mikhail Tikhonov","orcid":"0000-0002-9558-1121","position":5,"is_corresponding":false},{"id":416265,"name":"Jeffrey L. Ram","orcid":"0000-0002-1063-546X","position":6,"is_corresponding":false},{"id":1167551,"name":"Hanna Salman","orcid":"0000-0002-5847-524X","position":7,"is_corresponding":false},{"id":1168027,"name":"Josh E. Elias","orcid":null,"position":8,"is_corresponding":false},{"id":74113,"name":"Kerwyn Casey Huang","orcid":"0000-0002-8043-8138","position":9,"is_corresponding":false},{"id":316862,"name":"Benjamin D. Knapp","orcid":"0000-0002-9522-6218","position":0,"is_corresponding":true}],"reference_count":75,"raw_metadata":null,"created_at":"2026-07-19T01:19:05.913428Z","pmid":"37546722","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":[]}