The interplay between temperature and growth phase shapes the transcriptional landscape of Pseudomonas aeruginosa.

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Learn more: PMC Disclaimer | PMC Copyright Notice J Bacteriol . 2026 Mar 11;208(4):e00385-25. doi: 10.1128/jb.00385-25 Search in PMC Search in PubMed View in NLM Catalog Add to search The interplay between temperature and growth phase shapes the transcriptional landscape of Pseudomonas aeruginosa Rachel E Robinson Rachel E Robinson 1 Microbiology and Molecular Genetics Program, Graduate Division of Biological and Biomedical Sciences, Laney Graduate School, Emory University, Atlanta, Georgia, USA 2 Department of Pediatrics, Division of Pulmonary, Asthma, Cystic Fibrosis, and Sleep, Emory University School of Medicine, Atlanta, Georgia, USA Find articles by Rachel E Robinson 1, 2 , Michael J Gebhardt Michael J Gebhardt 3 Department of Microbiology & Immunology, Carver College of Medicine, University of Iowa, Iowa City, Iowa, USA Find articles by Michael J Gebhardt 3 , Joanna B Goldberg Joanna B Goldberg 2 Department of Pediatrics, Division of Pulmonary, Asthma, Cystic Fibrosis, and Sleep, Emory University School of Medicine, Atlanta, Georgia, USA 4 Emory+Children’s Center for Cystic Fibrosis and Airway Disease Research, Emory University School of Medicine, Atlanta, Georgia, USA Find articles by Joanna B Goldberg 2, 4, ✉ Editor: George O'Toole 5 Author information Article notes Copyright and License information 1 Microbiology and Molecular Genetics Program, Graduate Division of Biological and Biomedical Sciences, Laney Graduate School, Emory University, Atlanta, Georgia, USA 2 Department of Pediatrics, Division of Pulmonary, Asthma, Cystic Fibrosis, and Sleep, Emory University School of Medicine, Atlanta, Georgia, USA 3 Department of Microbiology & Immunology, Carver College of Medicine, University of Iowa, Iowa City, Iowa, USA 4 Emory+Children’s Center for Cystic Fibrosis and Airway Disease Research, Emory University School of Medicine, Atlanta, Georgia, USA 5 Dartmouth College Geisel School of Medicine, Hanover, New Hampshire, USA ✉ Address correspondence to Joanna B. Goldberg, [email protected] The authors declare no conflict of interest. Roles George O'Toole : Editor Received 2025 Aug 28; Accepted 2026 Jan 24; Collection date 2026 Apr. Copyright © 2026 Robinson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license . PMC Copyright notice PMCID: PMC13086522  NIHMSID: NIHMS2162065 PMID: 41810973 Previous version available: This article is based on a previously available preprint posted on bioRxiv on August 29, 2025: " The interplay between temperature and growth phase shapes the transcriptional landscape of Pseudomonas aeruginosa ". Previous version available: This article is based on a previously available preprint posted on bioRxiv on September 17, 2025: " The interplay between temperature and growth phase shapes the transcriptional landscape of Pseudomonas aeruginosa ". ABSTRACT Pseudomonas aeruginosa is a highly versatile bacterium capable of surviving and often thriving in stressful environmental conditions. Here, we report the effect of two environmental conditions, temperature and growth phase, on the P. aeruginosa PAO1 transcriptome. As P. aeruginosa is well-known for its growth phase dependent phenotypes and gene regulation, our goal was to determine how temperature altered global gene expression at exponential versus stationary phase and to characterize how growth phase affects thermoregulation. To do this, we grew PAO1 in parallel at 25°C and 37°C and sampled the same populations first at exponential phase and then again at stationary phase and assessed gene expression by RNA-sequencing. We found that temperature regulated hundreds of genes at, and unique to, exponential and stationary phases. We also grew PAO1 and an isogenic Δ lasR mutant at 25°C and 37°C and sampled populations at stationary phase to define LasR-regulated genes at each temperature by RNA-sequencing. LasR regulated most of its target genes similarly at 25°C and 37°C, although we identified a subset of genes whose regulation by LasR was affected by temperature. This work provides a comprehensive assessment of thermoregulation for PAO1 at two distinct growth phases, as well as growth phase transcriptomics at two temperatures, and expands our understanding of quorum sensing regulation under different environmental conditions that P. aeruginosa encounters. IMPORTANCE Pseudomonas aeruginosa is a highly adaptable opportunistic pathogen with a repertoire of mechanisms for surviving in diverse and often challenging environments, yet it is most studied at 37°C as the optimum temperature for growth. To better understand how this bacterium survives in the environment versus the human body, we performed transcriptomics on P. aeruginosa grown at 25°C and 37°C. At each temperature, we examined both exponential and stationary phases and determined the LasRI quorum sensing regulon at 37°C compared to 25°C using a Δ lasR mutant, which uncovered a suite of previously unrecognized LasR-regulated genes. Our work provides a comprehensive transcriptomic resource for the thermoregulation of P. aeruginosa at two growth phases, as well as growth phase and LasR regulation at two temperatures. KEYWORDS: quorum sensing, temperature regulation, Pseudomonas aeruginosa INTRODUCTION Pseudomonas aeruginosa is a versatile opportunistic bacterial pathogen that causes infections of burns, wounds, and the cornea, and respiratory infections in immunocompromised patients ( 1 ). It is a particular health burden for people with the genetic disorder cystic fibrosis (CF), in whom P. aeruginosa can cause chronic and often life-long lung infections that result in significant morbidity and mortality ( 2 ). Antibiotic resistance further underscores P. aeruginosa as a major public health concern, with the emergence of untreatable strains resistant to last-line antibiotics ( 3 ). Although its optimum temperature for growth is 37°C, P. aeruginosa can survive temperatures from 4°C to as high as 42°C—a wide range that distinguishes it from other Pseudomonads ( 4 , 5 ). Accordingly, it can be found in a wide range of environments, although it is more often isolated from anthropogenic locations, such as sinks, hospital surfaces, and medical devices like ventilators and catheters ( 6 ). The transition from a contaminated surface to the human host inherently involves a change from ambient temperature to human body temperature, 37°C (or higher in cases of fever). However, most laboratory studies of P. aeruginosa physiology and pathogenesis have historically been conducted with bacterial cells grown at 37°C; this is despite the intrinsic relevance of temperature changes to nosocomial infections in which P. aeruginosa transitions from ambient or room temperature to human body temperature. It is commonly appreciated that many bacterial pathogens sense and respond to human body temperature by regulating the expression of virulence factors ( 7 , 8 ). As many P. aeruginosa infections are acquired from healthcare settings, investigating how this bacterium adapts to different temperatures associated with nosocomial infections may provide insights into mechanisms that are important for its pathogenesis. Recently, our lab characterized a mechanism for the thermoregulation of protease IV ( piv ) gene expression ( 9 ). During this work, we were intrigued to find that piv thermoregulation depends strongly on growth phase due to temperature-dependent upregulation by the quorum sensing regulator LasR ( 9 ). In the P. aeruginosa strain PAO1, LasRI is the master quorum sensing system. In brief, LasI synthesizes the diffusible homoserine lactone (HSL) autoinducer molecule 3-oxo-C12, which complexes with and activates the transcriptional activator LasR at higher cell densities, such as those experienced during stationary phase. Quorum sensing enables detection of kin cell density and the subsequent regulation of many genes, including virulence factors and secreted products ( 10 , 11 ). Extensive and complex transcriptional rewiring occurs in P. aeruginosa populations at stationary phase, largely due to the multiple quorum sensing systems active at this growth phase ( 12 – 15 ). Given the effect of growth phase on the P. aeruginosa transcriptome, we wondered if the thermoregulation of other genes depended strongly on growth phase, akin to piv . However, studies of both growth phase and LasRI quorum sensing regulation in P. aeruginosa laboratory strains have only been conducted at 37°C ( 13 , 14 , 16 ). Additionally, while some transcriptomic studies have shown how P. aeruginosa responds to growing at ambient (22°C or 28°C) versus human body (37°C) temperature ( 17 – 19 ), as well as at normal human body versus febrile (39°C–46°C) temperatures ( 20 , 21 ), these studies were limited to examining global gene expression at a single point in the growth curve (i.e., exponential or stationary phase but not both). Thus, we wanted to investigate global transcriptional thermoregulation at both exponential and stationary phases, as well as to compare how growth at different temperatures impacts the global transcriptome at different growth phases. We hypothesized that the thermoregulation of other genes would be affected by growth phase. Here, we used RNA sequencing to determine how P. aeruginosa PAO1 adapts to growth at an ambient temperature of 25°C versus human body temperature of 37°C, at both exponential and stationary phases. This also allowed us to compare how growth phase affects gene expression in cells grown at 25°C versus 37°C. We further examined how temperature affects regulation by the quorum sensing regulator LasR. These experiments reveal that the thermoregulon in P. aeruginosa depends highly on growth phase and that growth phase regulates the majority of the transcriptome similarly at both temperatures tested. We also show that while LasR regulates most target genes to the same degree at both 25°C and 37°C, a few genes were regulated by LasR uniquely in response to different temperatures. This work has expanded our knowledge of how P. aeruginosa adapts to growing at two common temperatures in unique ways depending on the growth phase. RESULTS Temperature globally regulates the expression of distinct genes at exponential and stationary phase To identify genes regulated by temperature at exponential versus stationary phase, PAO1 was grown overnight at 37°C and each of three biological replicates was used to inoculate two “paired” cultures, one of which was incubated at 37°C and the other at 25°C. RNA was extracted from an equal number of cells from each of the cultures first at exponential phase (OD 600 of 0.5) and then again at stationary phase (OD 600 of 2.0), as depicted in Fig. 1A , and followed by RNA-sequencing. We first examined gene expression at 37°C versus 25°C, hereafter called thermoregulation, at each growth phase by differential expression analysis. Fig 1. Open in a new tab Temperature regulates the expression of hundreds of distinct genes in P. aeruginosa at both exponential and stationary phases. ( A ) Diagram of the experimental setup for RNA-seq of P. aeruginosa PAO1 grown at two temperatures and sampled at two growth phases. PAO1 was grown overnight at 37°C and then subcultured in parallel at 37°C and 25°C. At exponential phase, RNA was extracted from ~10 9 cells and the populations were allowed to continue growing until stationary phase, when RNA was extracted again from the same number of cells. RNA was then sequenced on an Illumina NextSeq 2000. Created with BioRender.com. ( B, C ) Volcano plots showing the thermoregulation of PAO1 transcripts at exponential phase ( B ) and stationary phase ( C ). Differential gene expression analysis (DESeq2) was used to compare gene expression at 37°C to 25°C. Transcripts with an absolute value of fold change greater than 2 (vertical dashed lines) and an adjusted P value <0.05 (horizontal dashed line) were considered thermoregulated, with transcripts upregulated at 37°C represented by red points and transcripts upregulated at 25°C represented by blue points. Transcripts that did not change by an absolute value of fold change greater than 2 or were not statistically significant (adjusted P value > 0.05) are depicted in gray. Genes of interest are annotated. ( D, E ) Metabolic pathways were significantly enriched (adjusted P value < 0.05) at exponential phase ( D ) and stationary phase ( E ) at 25°C (left panel for each D and E) and 37°C (right panel for each D and E). Enrichment was determined by gene set enrichment analysis using KEGG metabolic pathways for P. aeruginosa . ( F ) The fold thermoregulation (expression at 37°C/25°C) of statistically significant transcripts was plotted at exponential phase (x-axis) versus stationary phase (y-axis). Transcripts are colored according to how growth phase affected thermoregulation, with genes of interest annotated. Linear regression with 95% confidence intervals is shown. ( G ) Venn diagram showing at which growth phase (exponential, stationary, or both) statistically significant transcripts were thermoregulated. Thermoregulation at exponential phase At exponential phase, temperature affected the expression of 791 genes by twofold or more (adjusted P value < 0.05), indicating that 13.84% of the annotated genome was regulated by temperature ( Fig. 1B , with select genes of interest labeled, and Data set S1 ). Of these differentially regulated genes, 386 were upregulated at 37°C compared to 25°C, and 405 were upregulated at 25°C compared to 37°C. Perhaps unsurprisingly, many thermoregulated genes are involved in metabolism and/or respiration. Many of the biological pathways significantly enriched ( Fig. 1D , right panel, adjusted P value < 0.05) at exponential phase in cells grown at 37°C contain genes involved in anaerobic respiration, including nitrogen metabolism, porphyrin metabolism, and arginine metabolism ( Fig. 2 ). With those pathway enrichment results in mind, we noticed a striking trend that the genes most highly upregulated at 37°C compared to 25°C (i.e., genes with the highest log 2 fold change value in Data set S1 ) are those genes involved in anaerobic respiration ( 22 ). We cross-referenced genes in Data set S1 with anaerobic regulation studies ( 23 – 37 ) and found that the majority of known anaerobic genes are upregulated at 37°C compared to 25°C. For convenience, these genes and their corresponding fold changes in thermoregulation are also presented in Table 1 , along with whether each gene is regulated by Anr, the low oxygen transcriptional regulator. In the absence of sufficient oxygen for fully aerobic respiration, P. aeruginosa can utilize various nitrogen oxides as terminal electron receptors for anaerobic respiration in a process known as denitrification ( 38 , 39 ). The nar , nor , nir , and nos operons each encode genes whose products are involved in the reduction of a specific nitrogen oxide and were among the genes most upregulated at 37°C, along with other genes involved in the regulation of denitrification, such as narXL and dnr ( Table 1 ). Also upregulated at 37°C are moeA1 and moaB1 , two genes in the biosynthetic pathway for production of molybdopterin guanine dinucleotide (MGD) cofactor, which is essential for the activity of nitrate reductase and thus anaerobic respiration via denitrification. P. aeruginosa contains two operons for cytochrome c cbb 3 -type oxidases that accept electrons and reduce oxygen to water. One of the operons, ccoNOQP -2, is greatly induced under low oxygen conditions, while the ccoNOQP -1 operon is dominant under high oxygen conditions ( 33 ). We found all genes of the ccoNOQP -2 operon were significantly upregulated at 37°C, while the immediately downstream ccoNOQP -1 operon was not thermoregulated ( Table 1 ; Data set S1 ). Under low oxygen and low nitrogen conditions, and thus in the absence of oxygen or nitrogen species as terminal electron receptors, P. aeruginosa can survive by converting ADP to ATP via the arginine deaminase pathway encoded by the arcDABC operon, which is induced by low oxygen ( 36 , 40 – 43 ) and was upregulated at 37°C in our data set. Both the anaerobic ribonucleoside reductase genes nrdD and nrdG , as well as the constitutive ribonucleoside reductase genes nrdJ a and nrdJ b, were upregulated at 37°C. Other metabolic processes were upregulated at 37°C and are shown in Fig. 2 , with pathways related to survival in low oxygen environments marked as such. We note that the activity of these metabolic processes may depend on other factors in addition to gene expression, such as the availability of substrates. Fig 2. Open in a new tab Metabolic pathways upregulated in P. aeruginosa growing at 37°C at exponential phase. A selection of notable metabolic and enzymatic pathways that were characteristic of PAO1 growing at 37°C at exponential phase are shown. Genes labeled in red were significantly upregulated at 37°C (fold change > 2, adjusted P value < 0.05) with the approximate log 2 fold change (37°C/25°C) indicated next to the gene; for operons, the average log 2 fold change for all genes in the operon is shown. Pathways are simplified to highlight the function of thermoregulated genes. Pathways or genes related to anaerobic growth and survival and/or induced by low oxygen conditions are marked with Low O 2 . MGD, molybdopterin guanine dinucleotide; HCN, hydrogen cyanide. TABLE 1. Low oxygen response genes that are thermoregulated PA locus Gene name Gene description Log 2 fold change (37°C/25°C) Anr regulated? Reference(s) PA0141 Conserved hypothetical protein 3.861931392 Yes ( 23 ) PA0200 Hypothetical protein 1.860850141 Yes ( 23 ) PA0459 Probable ClpA/B protease ATP binding subunit 3.003597721 Yes ( 23 ) PA0509 nirN NirN 3.367641568 Yes ( 24 , 31 , 32 ) PA0510 nirE NirE 4.093841973 Yes ( 24 , 31 , 32 ) PA0511 nirJ Heme d1 biosynthesis protein NirJ 5.016441673 Yes ( 24 , 31 , 32 ) PA0512 nirH NirH 4.082194492 Yes ( 24 , 31 , 32 ) PA0513 nirG NirG 4.816402884 Yes ( 24 , 31 , 32 ) PA0514 nirL Heme d1 biosynthesis protein NirL 4.448124526 Yes ( 24 , 31 , 32 ) PA0515 nirD Probable transcriptional regulator 4.97281466 Yes ( 24 , 31 , 32 ) PA0516 nirF Heme d1 biosynthesis protein NirF 5.365993218 Yes ( 24 , 31 , 32 ) PA0517 nirC Probable c-type cytochrome precursor 5.346628779 Yes ( 23 , 24 , 31 , 32 ) PA0518 nirM Cytochrome c-551 precursor 5.465658373 Yes ( 23 , 24 , 31 , 32 ) PA0519 nirS Nitrite reductase precursor 4.640740455 Yes ( 23 , 24 , 31 , 32 ) PA0520 nirQ Regulatory protein NirQ 2.098179684 Yes ( 23 , 24 , 31 ) PA0521 nirO Probable cytochrome c oxidase subunit 2.431460609 Yes ( 24 , 31 ) PA0522 nirP Hypothetical protein 2.601836238 Yes ( 24 , 31 ) PA0523 norC Nitric-oxide reductase subunit C 5.565058671 Yes ( 23 , 24 , 31 , 32 ) PA0524 norB Nitric-oxide reductase subunit B 4.847517393 Yes ( 23 , 24 , 31 , 32 ) PA0525 norD Probable dinitrification protein NorD 3.743445873 Yes ( 23 , 24 , 31 , 32 ) PA0527 dnr Transcriptional regulator Dnr 1.706108937 Yes ( 24 , 32 ) PA0835 pta Phosphate acetyltransferase 1.92046193 Yes ( 23 , 26 ) PA0836 ackA Acetate kinase 2.515250961 Yes ( 23 , 26 ) PA1076 Hypothetical protein 1.72119139 Yes ( 23 ) PA1183 dctA C4-dicarboxylate transport protein 1.443397316 Yes ( 23 ) PA1333 Hypothetical protein 1.550989673 No ( 23 ) PA1414 Hypothetical protein 1.02457116 Yes ( 23 ) PA1546 hemN Oxygen-independent coproporphyrinogen III oxidase 2.031704743 Yes ( 23 , 27 ) PA1555 ccoP2 Cytochrome c oxidase, cbb3-type, CcoP subunit 4.608050716 Yes ( 23 , 33 ) PA1555.1 ccoQ2 Cytochrome c oxidase, cbb3-type, CcoQ subunit 4.655966801 Yes ( 33 ) PA1556 ccoO2 Cytochrome c oxidase, cbb3-type, CcoO subunit 4.466914246 Yes ( 23 , 33 ) PA1557 ccoN2 Cytochrome c oxidase, cbb3-type, CcoN subunit 3.693993192 Yes ( 23 , 33 ) PA1561 aer Aerotaxis receptor Aer 1.407974962 Yes ( 23 ) PA1673 mhr Microoxic hemerythrin, Mhr 1.648674194 Yes ( 23 , 28 ) PA1742 pauD2 Glutamine amidotransferase class I 1.205871771 No ( 23 ) PA1746 Hypothetical protein 3.310750245 Yes ( 23 ) PA1789 Hypothetical protein 2.140513884 Yes ( 23 ) PA1919 nrdG Class III (anaerobic) ribonucleoside-triphosphate reductase activating protein, “activase,” NrdG 3.124377908 No ( 37 ) PA1920 nrdD Class III (anaerobic) ribonucleoside-triphosphate reductase subunit, NrdD 3.446583869 No ( 37 ) PA2119 Alcohol dehydrogenase (Zn-dependent) 1.681907197 Yes ( 23 ) PA2126 cgrC cupA gene regulator C, CgrC 3.273837671 Yes ( 23 ) PA2127 cgrA cupA gene regulator A, CgrA 2.574823088 Yes ( 23 ) PA2193 hcnA Hydrogen cyanide synthase HcnA 1.068630222 Yes ( 25 , 34 ) PA2194 hcnB Hydrogen cyanide synthase HcnB 2.43019007 Yes ( 25 , 34 ) PA2195 hcnC Hydrogen cyanide synthase HcnC 2.513248472 Yes ( 25 , 34 ) PA2501 Hypothetical protein 1.956608358 No ( 23 ) PA2567 Hypothetical protein 1.210810652 No ( 23 ) PA2662 Conserved hypothetical protein 3.679243955 Yes ( 23 ) PA2663 ppyR psl and pyoverdine operon regulator, PpyR 3.316445689 Yes ( 23 ) PA2664 fhp Flavohemoprotein 2.771634841 Yes ( 23 ) PA2753 Hypothetical protein 2.084672861 Yes ( 23 ) PA2754 Conserved hypothetical protein 2.185701963 Yes ( 23 ) PA2937 Hypothetical protein 1.029493262 No ( 23 ) PA3278 Hypothetical protein 1.633837058 Yes ( 23 ) PA3309 Conserved hypothetical protein 2.602443724 Yes ( 23 ) PA3337 rfaD ADP-L-glycero-D-mannoheptose 6-epimerase 2.570948547 Yes ( 23 ) PA3391 nosR Regulatory protein NosR 5.048970297 Yes ( 32 , 35 ) PA3392 nosZ Nitrous-oxide reductase precursor 4.408020398 Yes ( 32 , 35 ) PA3393 nosD NosD protein 2.147346339 Yes ( 32 , 35 ) PA3432 Hypothetical protein 2.240172802 No ( 23 ) PA3458 Probable transcriptional regulator 2.530708298 No ( 23 ) PA3572 Hypothetical protein 2.008605328 Yes ( 23 ) PA3614 Hypothetical protein 2.21971923 No ( 23 ) PA3662 Hypothetical protein 1.219686929 No ( 23 ) PA3872 narI Respiratory nitrate reductase gamma chain 2.521795139 Yes ( 24 ) PA3873 narJ Respiratory nitrate reductase delta chain 2.653713928 Yes ( 24 ) PA3874 narH Respiratory nitrate reductase beta chain 2.538853508 Yes ( 24 ) PA3875 narG Respiratory nitrate reductase alpha chain 4.820343687 Yes ( 24 ) PA3876 narK2 Nitrite extrusion protein 2 5.35518565 Yes ( 24 ) PA3877 narK1 Nitrite extrusion protein 1 4.646502638 Yes ( 24 ) PA3878 narX Two-component sensor NarX 2.417819085 Yes ( 24 ) PA3879 narL Two-component response regulator NarL 2.699787211 Yes ( 23 , 24 ) PA3880 Conserved hypothetical protein 2.254943056 Yes ( 23 ) PA3914 moeA1 Molybdenum cofactor biosynthetic protein A1 3.16662168 No ( 29 ) PA3915 moaB1 Molybdopterin biosynthetic protein B1 3.172528337 No ( 29 ) PA3919 Conserved hypothetical protein 1.478477733 No ( 23 ) PA3971 Hypothetical protein 1.803475732 No ( 23 ) PA3972 Probable acyl-CoA dehydrogenase 1.719007994 No ( 23 ) PA3973 Probable transcriptional regulator 1.411019935 No ( 23 ) PA4067 oprG Outer membrane protein OprG precursor 2.754767099 Yes ( 23 ) PA4205 mexG Hypothetical protein 1.10548162 Yes ( 23 ) PA4206 mexH Probable resistance-nodulation-cell division (RND) efflux membrane fusion protein precursor 1.248864198 No ( 23 ) PA4236 katA Catalase 2.693295008 Yes ( 23 ) PA4328 Hypothetical protein 1.796007739 Yes ( 23 ) PA4348 Conserved hypothetical protein 1.055038374 Yes ( 23 ) PA4352 Conserved hypothetical protein 2.210265213 Yes ( 23 ) PA4577 Hypothetical protein 1.899164823 Yes ( 23 ) PA4587 ccpR Cytochrome c551 peroxidase precursor 3.770015293 Yes ( 23 ) PA4610 Hypothetical protein 2.476738855 Yes ( 23 ) PA4611 Hypothetical protein 2.439104222 Yes ( 23 ) PA4880 Probable bacterioferritin 1.043718176 No ( 23 ) PA5027 Hypothetical protein 2.646373417 Yes ( 23 ) PA5170 arcD Arginine/ornithine antiporter 2.642994913 Yes ( 23 , 36 ) PA5171 arcA Arginine deiminase 4.334215635 Yes ( 23 , 36 ) PA5172 arcB Ornithine carbamoyltransferase, catabolic 4.492376991 Yes ( 23 , 36 ) PA5173 arcC Carbamate kinase 3.888778879 Yes ( 23 , 36 ) PA5208 Conserved hypothetical protein 1.838077286 No ( 23 ) PA5231 Probable ATP-binding/permease fusion ABC transporter 2.045986169 Yes ( 23 ) PA5232 Conserved hypothetical protein 1.477745597 Yes ( 23 ) PA5312 pauC Aldehyde dehydrogenase 1.225743499 No ( 23 ) PA5427 adhA Alcohol dehydrogenase 3.240422776 Yes ( 23 ) PA5475 Hypothetical protein 2.338124562 Yes ( 23 ) PA5494 Hypothetical protein 1.290103294 Yes ( 23 ) PA5495 thrB Homoserine kinase 1.108758708 No ( 23 ) PA5546 Conserved hypothetical protein 1.224459723 No ( 23 ) Open in a new tab At 25°C, aminoacyl-tRNA biosynthesis was significantly enriched ( Fig. 1D , left panel, adjusted P value < 0.05), which suggests that cells adapt to growing at lower temperatures by increasing tRNA pools for translation. Also upregulated at 25°C were 30S ribosomal subunit genes rpsU and rpsT ( Data set S1 ). We initially predicted that cold adaptation protein gene(s) would be upregulated at 25°C due to the decrease in temperature from overnight growth at 37°C. We examined the normalized gene expression of all the annotated putative cold shock proteins in PAO1 (PA0456, PA0961, PA1159, PA2622, PA3266) and found varying thermoregulation and growth phase regulation phenotypes ( Fig. 3 ). PA0456 was expressed equally at 25°C versus 37°C at both growth phases and expression was generally higher at exponential phase than stationary phase. PA0961 was lowly or not expressed in any of the conditions tested. PA1159 was also not thermoregulated at either growth phase, although transcript levels appeared slightly higher at stationary phase. PA2622 was lowly expressed at exponential phase and highly expressed at stationary phase, independent of temperature. Only PA3266, also called capB , was more highly expressed at 25°C than 37°C at exponential phase (approximately sixfold higher, Data set S1 ); at stationary phase, expression was low at both 25°C and 37°C and not thermoregulated. CapB was originally identified in the related pseudomonad Pseudomonas fragi as one of four low molecular weight proteins induced by cold shock ( 44 ). The authors found that at the amino acid level, CapB was similar to the well-studied Escherichia coli cold shock RNA chaperone CspA ( 44 ). Under the conditions we tested, capB was the only putative cold shock protein gene whose expression was induced at 25°C. Its expression greatly decreased by stationary phase, suggesting that capB is likely involved in the initial adaptation to colder growth conditions. We also note that eftM , a thermolabile methyltransferase that modifies EF-Tu at 25°C but not 37°C in PAO1, which we have previously studied ( 45 ), is expressed ~5.85-fold more at 25°C than 37°C, which is consistent with an enzyme known to be functional only at ambient temperatures ( Data set S1 ). Fig 3. Open in a new tab capB is the only putative cold shock response gene induced at 25°C. Normalized reads from the RNA-seq experiment diagrammed in Fig. 1A are visualized in Integrative Genomics Viewer (IGV) for the annotated putative cold shock response genes PA0456 ( A ), PA0961 ( B ), PA1159 ( C ), PA2622 ( cspD ) ( D ), and PA3266 ( capB ) ( E ). Reads for either the plus or minus strand are shown as relevant to the transcriptional direction of each gene, indicated by arrows within the gray boxes marking the protein coding region of each gene. Reads from the same representative biological replicate sampled first at exponential phase and again at stationary phase are shown for all genes. The genomic position (in kilobase pairs) is indicated at the top of each panel. Thermoregulation at stationary phase At stationary phase, expression of 715 genes was affected twofold or greater by temperature (adjusted P value < 0.05), with 392 genes upregulated at 37°C compared to 25°C and 323 genes upregulated at 25°C compared to 37°C ( Fig. 1C ; Data set S2 ). At this growth phase, 12.48% of the annotated genome was thermoregulated. This is comparable to our findings for thermoregulation at exponential phase, and a higher percentage than what had been previously found to be thermoregulated at stationary phase in either PAO1 or PA14 laboratory strains ( 18 , 19 ). We found that phenazine biosynthesis and quorum sensing pathways, including the genes rhlAB , lasA , and lecB , were significantly enriched at 37°C ( Fig. 1E , right panel, adjusted P value < 0.05), whereas at 25°C the metabolism of various amino acids, as well as glyoxylate metabolism (related to the glyoxylate shunt), was enriched ( Fig. 1E , left panel, adjusted P value < 0.05). To examine how each annotated gene in the genome was thermoregulated at exponential phase versus stationary phase, we compared the fold thermoregulation of each statistically significant gene (adjusted P value < 0.05, a total of 5,018 genes) at exponential phase to its fold thermoregulation at stationary phase ( Fig. 1F ). Thermoregulation at exponential and stationary phases was weakly correlated (r = 0.1688), and most genes that were thermoregulated were only thermoregulated at one growth phase ( Fig. 1G ). This underscores that temperature induces transcriptional changes that are distinct to the growth phase of the bacterial population. To further investigate how temperature and growth phase affect global transcriptional changes, we examined the variation in gene expression from all four conditions studied (exponential at 37°C, exponential at 25°C, stationary at 37°C, stationary at 25°C) using a principal component analysis ( Fig. 4A ). Despite the different growth temperatures, samples from exponential phase at 25°C and 37°C generally clustered together, as did samples from stationary phase at 25°C and 37°C. Additionally, samples from exponential phase (circles in Fig. 4A ) clustered rather distinctly from samples from stationary phase (triangles in Fig. 4A ) regardless of temperature, indicating that growth phase contributes more to overall variation than temperature does. Given the distinct clustering based on growth phase, we next used differential expression analysis to compare gene expression at stationary phase versus exponential phase at each 37°C and 25°C. At 37°C, the expression of 2,457 genes (43.00% of the annotated genome) was affected twofold or greater by growth phase (adjusted P value < 0.05), with 1,371 genes upregulated at stationary phase and 1,086 genes upregulated at exponential phase ( Fig. 4B ; Data set S3 ). At 25°C, the expression of 2,760 genes (48.31% of the annotated genome) was affected twofold or greater (adjusted P value < 0.05) by growth phase, with 1,493 genes upregulated at stationary phase and 1,267 genes upregulated at exponential phase ( Fig. 4C ; Data set S4 ). We then compared the growth phase regulation of each statistically significant gene (adjusted P value < 0.05, a total of 5,018 genes) at 37°C to its growth phase regulation at 25°C ( Fig. 4D ) and found a positive correlation between growth phase regulation at 37°C and 25°C (r = 0.8637). While most genes were regulated by growth phase similarly at both 37°C and 25°C, there were some exceptions. The glc operon genes were only upregulated at stationary phase when cells were grown at 25°C but not when grown at 37°C ( Fig. 4D ; Data sets S3 and S4 ). In conclusion, growth phase regulates gene expression similarly whether PAO1 is grown at 37°C or 25°C and is a stronger environmental cue driving global transcriptional changes than temperature. Fig 4. Open in a new tab Growth phase regulates gene expression similarly at 25°C and 37°C. ( A ) Principal component analysis of reads from RNA-seq of three biological replicates of PAO1 grown at two temperatures and sampled at two growth phases is shown. Each data point represents a transcriptome of PAO1 grown at 25°C (cool colors) or 37°C (warm colors) from exponential phase (circles) or stationary phase (triangles). Each color indicates a specific bacterial population that was sampled first at exponential phase and again at stationary phase to allow longitudinal comparison. ( B, C ) Volcano plots showing the growth phase regulation of PAO1 transcripts at 37°C ( B ) and 25°C ( C ). Differential gene expression analysis (DESeq2) was used to compare gene expression at stationary phase to exponential phase. Transcripts with an absolute value of fold change greater than 2 (vertical dashed lines) and an adjusted P value <0.05 (horizontal dashed line) were considered growth phase regulated, with transcripts upregulated at stationary phase represented by teal points and transcripts upregulated at exponential phase represented by yellow points. Transcripts that did not change by an absolute value of fold change greater than 2 or were not statistically significant (adjusted P value > 0.05) are depicted in gray. Genes of interest are annotated. ( D ) The fold growth phase regulation (expression at stationary/exponential phase) of statistically significant transcripts was plotted at 37°C (x-axis) versus 25°C (y-axis). Transcripts are colored according to how temperature affected growth phase regulation and genes of interest are annotated. Linear regression with 95% confidence intervals is shown. LasR regulation is generally robust against temperature changes We noticed that many genes known to be regulated by LasR were upregulated at 37°C compared to 25°C at stationary phase ( Data set S2 ). As with many transcriptional regulators, LasRI quorum sensing regulation has been historically studied at 37°C ( 12 – 16 ). With our recent finding that the secreted protease piv , which is upregulated at 25°C compared to 37°C at stationary phase, is regulated by LasR in a temperature-dependent manner ( 9 ), we wondered if LasR could regulate other genes in a temperature-dependent manner. To address this, we grew PAO1 and an isogenic Δ lasR mutant overnight at 37°C and then subcultured in biological triplicate at 37°C or 25°C ( Fig. 5A ). At stationary phase (OD 600 of 2.0), when LasR regulation is active, RNA was extracted and RNA-sequencing was performed. We first determined genes regulated by LasR at 37°C and found that the expression of 778 genes was changed twofold or greater (adjusted P value < 0.05) in the Δ lasR mutant ( Fig. 5B ; Data set S5 ). Of those genes, the expression of 503 genes decreased in Δ lasR while the expression of 275 genes increased. At 25°C, the expression of 667 genes was changed twofold or greater (adjusted P value < 0.05) in the Δ lasR mutant compared to PAO1 ( Fig. 5C ; Data set S6 ). Of those, the expression of 424 genes decreased in Δ lasR while the expression of 243 genes increased. These data reveal that LasR regulates similar numbers of genes at 37°C as at 25°C, both positively and negatively. Fig 5. Open in a new tab LasR regulates most target genes similarly at 37°C as 25°C, with notable exceptions. ( A ) Diagram of the experimental setup for RNA-seq of PAO1 and Δ lasR grown at two temperatures and sampled at stationary phase is shown. PAO1 and Δ lasR were grown overnight at 37°C and then subcultured in parallel at 37°C and 25°C. At stationary phase, RNA was extracted from ~10 9 cells and sequenced on an Illumina NovaSeq X Plus. Created using BioRender.com. ( B, C ) Volcano plots showing the LasR regulation of PAO1 transcripts at 37°C ( B ) and 25°C ( C ). Differential gene expression analysis (DESeq2) was used to compare gene expression in Δ lasR to PAO1. Transcripts with an absolute value of fold change greater than 2 (vertical dashed lines) and an adjusted P value <0.05 (horizontal dashed line) were considered LasR regulated, with transcripts negatively regulated by LasR represented by light pink points and transcripts positively regulated by LasR represented by purple points. Transcripts that did not change by an absolute value of fold change greater than 2 or were not statistically significant (adjusted P value > 0.05) are depicted in gray. Genes of interest are annotated. ( D ) The fold LasR regulation (expression in Δ lasR /PAO1) of statistically significant transcripts was plotted at 37°C (x-axis) versus 25°C (y-axis). Transcripts are colored according to how temperature affected LasR regulation and genes of interest are annotated. Linear regression with 95% confidence intervals is shown. To investigate how temperature affects LasR regulation, we compared the LasR regulation of each statistically significant gene (adjusted P value < 0.05, a total of 3,402 genes), including those not differentially expressed, at 37°C with its LasR regulation at 25°C ( Fig. 5D ). We found a positive correlation between LasR regulation at 37°C and 25°C (r = 0.776), indicating that LasR generally regulates target genes similarly at both 37°C and 25°C, including the well-studied LasR targets lasA , lecB , and rsaL . We also found that LasR regulated piv more at 25°C than at 37°C, an observation consistent with our previous findings ( 9 ). To identify genes that were not regulated by LasR similarly at both temperatures ( Table S1 ), we then further filtered these genes based on their LasR regulation at 37°C and 25°C according to the following criteria: a gene was regulated by LasR at one temperature but not the other (i.e., a gene was differentially expressed in Δ lasR at only one temperature) or a gene was regulated by LasR positively (or negatively) at one temperature and vice versa at the other temperature. Interestingly, the LasR regulation of over 500 genes was sensitive to temperature, and the majority met the first criteria of being regulated by LasR at only one temperature and hence are present in Data set S5 or S6 , but not both. Notably, the nirNEJHGHLDFCMS , nirQOP , norBC , and nosRZDF operons were strongly upregulated in Δ lasR compared to PAO1 at 25°C only ( Table S1 ). This indicates that normally in PAO1 cultures at 25°C, LasR negatively regulates the nir , nor , and nos operons, while at 37°C, LasR does not regulate these operons. Of the nitrate reductase nar operon, only two genes ( narK1 and narH ) had their LasR regulation affected by temperature, which suggests that the temperature-dependent LasR regulation of denitrification at 25°C may be limited to the nir , nor , and nos operons. We also found that the siaABCD operon, which promotes biofilm formation in response to SDS exposure and/or carbon availability ( 46 , 47 ), was negatively regulated by LasR at 37°C (i.e., siaABCD expression was increased in Δ lasR compared to PAO1) but not at 25°C. DISCUSSION Using RNA-seq, we identified the global thermoregulon for PAO1 at exponential phase ( Data set S1 ) and stationary phase ( Data set S2 ), as well as the growth phase regulon at 37°C ( Data set S3 ) and at 25°C ( Data set S4 ). We also determined the LasR regulon at stationary phase using a clean Δ lasR mutant, at both the commonly studied temperature of 37°C ( Data set S5 ), as well as the more environmentally relevant temperature of 25°C ( Data set S6 ). Our experimental design for paired growth at two temperatures with longitudinal sampling at two growth phases allowed us to compare temperature and growth phase as two environmental factors driving the transcriptomic landscape. We found that ~13% of the PAO1 transcriptome was thermoregulated at each exponential and stationary phase, which is higher than prior studies that found ~6% thermoregulated at only stationary phase in P. aeruginosa strains PAO1 ( 18 ) and PA14 ( 19 ). This could be due to differences in strains used (PAO1 vs PA14), differences in sequencing technologies used (microarray vs RNA-sequencing), better annotation of the PAO1 genome, or other technical aspects, such as the improvement of RNA-sequencing technology and methods of downstream analysis. We were curious if there are DNA motifs common to the promoters of genes that were thermoregulated similarly at each growth phase, which could suggest the existence of a temperature-responsive transcription factor underlying a mechanism for global transcriptional thermoregulation. Interestingly, we did not find any temperature-associated motifs or evidence for a centralized mechanism for global transcriptional thermoregulation based on our data (data not shown). This suggests that temperature may be transduced via a gene’s own regulatory network to regulate expression rather than through a unified global temperature regulation response like a temperature-responsive transcription factor. Distinct genes were thermoregulated at each growth phase, largely due to genes being expressed at one growth phase but not the other. With exceptions (such as the glc operon, which is only growth phase regulated at 25°C), growth phase affected gene expression similarly at 25°C and 37°C ( Fig. 4D ). Growth phase also affected more of the transcriptome than temperature, with upward of 50% of the transcriptome regulated by growth phase at each 25°C and 37°C, and transcriptomes from the same growth phases were more similar to each other regardless of the temperature conditions ( Fig. 4A ). This underscores the role of growth phase and kin cell density in P. aeruginosa physiology and the inherent robustness of P. aeruginosa to grow at different temperatures. Accordingly, we found that expression of many of its oft-studied virulence factors and behaviors, such as the genes for rhamnolipid, lectin, and pyocyanin production, is more sensitive to growth phase than temperature changes. This indicates that although P. aeruginosa clearly adapts to growing at different temperatures, upregulation of its key virulence factors following the transition from exponential to stationary phase occurs to a similar degree at the temperatures we tested and the genes are expressed even at non-human body temperature. This supports the hypothesis that these virulence factors are general mechanisms for this bacterium to acquire nutrients and compete with other microbes, and also happen to be beneficial for survival in humans by facilitating pathogenesis. A major question of this work is how P. aeruginosa responds to growing at different temperatures at exponential phase and stationary phase. At exponential phase, we found that increased expression of many genes related to anaerobic growth and survival ( 22 ) is a strong signature of growth at 37°C versus 25°C ( Fig. 1D ; Table 1 ). This included both genes for anaerobic respiration via denitrification ( nar , nir , nor , and nos operons), as well as non-nitrogen-based mechanisms of survival in a low oxygen environment (the high oxygen affinity type II cytochrome c oxidase ccoNOQP -2, the arginine deaminase pathway arcDABC , pyruvate fermentation, and others, see Fig. 2 and Table 1 ). Of note is that many of these thermoregulated genes related to anaerobic survival are regulated by Anr ( Table 1 ), a major low oxygen transcriptional regulator in P. aeruginosa ( 25 ), and thus we suspect that regulation by Anr could be affected by temperature. However, expression of the anr gene is not thermoregulated in our data sets and thus transcriptomics does not explain how virtually all of the known Anr regulon is thermoregulated. Anr regulation is complex ( 22 , 39 ) and strongly impacted by oxygen availability. For instance, in the absence of oxygen, Anr interacts with a [4Fe–4S] 2+ cluster which is essential for its ability to bind DNA; upon exposure to oxygen, aerobic Anr can no longer bind DNA and regulate target genes, possibly due to an inability to dimerize without [4Fe–4S] 2+ , such as with the E. coli low oxygen regulator Fnr ( 48 , 49 ). A lower intracellular oxygen availability at 37°C than at 25°C is consistent with higher regulatory activity by Anr at 37°C and could be caused by myriad factors. Cells growing at 37°C grow faster than those at 25°C, and the increased metabolic activity and respiratory rate at 37°C could result in more rapid consumption of oxygen, leading to upregulation of anaerobic response genes to sustain growth. Temperature could also directly affect the availability of oxygen to cells in the environment, as oxygen solubility generally decreases as temperature increases ( 50 ). It is likely that both biological factors like metabolic rate and environmental factors like oxygen availability influence the cellular demand for oxygen and resulting upregulation of anaerobic genes at 37°C. In addition to its direct targets, Anr also upregulates the regulator Dnr, which specifically activates the nar , nir , nor , and nos denitrification operons and is important for fitness in microoxic, as well as anaerobic environments ( 51 ). Expression of dnr was slightly thermoregulated in our data set ( Table 1 ; Data set S1 ), which could contribute in part to the thermoregulation of its specific targets. However, since much of the Anr regulon is not co-regulated by Dnr, thermoregulation of dnr cannot fully account for how so many anaerobic genes are also regulated by temperature, and future studies are needed to explore this further. Although we studied gene expression in in vitro lab conditions, we also note that many of the oxygen starvation genes upregulated at 37°C during exponential growth are upregulated in respiratory infections in CF patients ( 52 , 53 ). Mucus within the lungs of CF patients has been characterized as both oxygen-poor and sufficiently nitrogen-rich for P. aeruginosa to respire via denitrification ( 54 – 58 ). That temperature alone can lead to upregulation of oxygen starvation genes associated with chronic infection and long-term adaptation to the CF lung environment ( 22 , 52 , 53 ), suggests that thermoregulation may help prime P. aeruginosa for adaptation to the human body as a new environment. This work thus provides new insights into how thermoregulation participates in P. aeruginosa ’s successful transition from an ambient environment to the human body. For genes upregulated at exponential phase at 25°C, we expected to identify cold adaptation genes, as transitioning an overnight culture grown at 37°C to subculturing at 25°C slows the growth of PAO1, particularly during the initial lag and early exponential phases of growth ( 9 ). However, we found that expression of only one of the five annotated putative cold shock proteins (Csps), PA3266 ( capB ), was upregulated at 25°C, and the remaining four were either not expressed under the tested growth conditions or were expressed during at least one growth phase but were not thermoregulated ( Fig. 3 ). Cold shock proteins are commonly identified by a characteristic and highly conserved nucleotide-binding domain of an anti-parallel, five-strand β-barrel first identified in eukaryotic Y-box proteins ( 59 ). CapB appears similar to the well-studied cold-shock RNA-binding protein CspA in E. coli ; in E. coli , CspA serves as a “master” Csp regulator and negatively regulates other Csps such that they are only expressed if CspA becomes non-functional ( 60 – 62 ). Thus, the other annotated putative Csps may be similarly repressed by CapB in P. aeruginosa , or they may respond to other environmental stressors than temperature, as is the case for CspD in E. coli being induced by nutritional deprivation at stationary phase ( 63 ); we also found that expression of PA2622, annotated as CspD in the PAO1 genome, was induced at stationary phase at both 25°C and 37°C. At stationary phase, we noted that many thermoregulated genes are also LasR-regulated, which has been previously observed ( 18 , 19 ) and was not unexpected as LasR is an active regulator at stationary phase and drives many (although not all) transcriptional changes during this growth phase. The LasRI quorum sensing regulon has previously been characterized by adding the autoinducer 3O-C12-HSL to a P. aeruginosa strain deficient in producing any quorum sensing signal ( 12 , 14 , 15 ) or by ectopically overexpressing the LasR receptor during early growth in addition to supplementation with 3O-C12-HSL ( 13 ). The effects of temperature on LasR regulation had not been previously explored, and we thus determined the LasRI quorum sensing regulon using a clean Δ lasR mutant at both 37°C and 25°C at stationary phase, when LasR would be active in wild-type cells. Overall, LasR regulates many of its target genes to a similar degree when grown at either 37°C or 25°C ( Fig. 5D ). However, we found over 500 genes whose LasR regulation is sensitive to temperature ( Table S1 ), including genes that have not previously been well recognized as LasR-regulated when cells are grown in standard conditions in lysogeny broth (LB) media, possibly due to all prior transcriptomic studies of the LasR regulon being conducted at 37°C ( 13 – 16 ). One example of this is the nir , nor , and nos operons, which we found are very negatively regulated by LasR at 25°C but not regulated by LasR at 37°C (see Data sets S5 and S6 , respectively). One study conducted at 37°C with cells grown anaerobically in media supplemented with potassium nitrate found that LasR indirectly repressed denitrification operons via RhlR through a not fully elucidated mechanism ( 64 ). Interestingly, we found that the nir , nor , and nos operons were also negatively regulated by LasR (and thus likely indirectly) but only at 25°C and not 37°C. Our results combined with the results of Toyofuku et al. ( 64 ) could suggest that LasR’s indirect regulation of denitrification depends on both temperature and media composition: LasR indirectly regulates denitrification at 37°C only under strictly anaerobic conditions, possibly with a nitrogen source, while during standard aerobic growth LasR indirectly regulates denitrification only at 25°C. This model would be consistent with the many transcriptomic studies of LasR and RhlR at 37°C in standard aerobic growth conditions that did not find LasR regulating denitrification ( 13 , 14 ). Growing P. aeruginosa at the non-standard temperature of 25°C was critical for these findings and underscores the importance of diverse environmental and nutritional conditions in better understanding bacterial physiology. In conclusion, as an opportunistic human pathogen, P. aeruginosa is capable of surviving in both an ambient environment and the human body and must sense the transition between these environments in order to adapt accordingly. Studying the transcriptome at an ambient temperature, 25°C, as well as human body temperature, 37°C, at both exponential and stationary phase has led to new insights into the role of thermoregulation in P. aeruginosa adapting to the human body. Our RNA-seq analyses have also identified many thermoregulated genes for future research on the mechanism(s) by which temperature regulates their expression. MATERIALS AND METHODS Culture conditions and RNA-sequencing Biological triplicates of the indicated strain ( Table 2 ) were grown in 3 mL LB overnight in a rolling drum at 37°C, subcultured to an initial OD 600 of 0.05 in 25 mL LB, and incubated at either 25°C or 37°C with shaking at 200 rpm. RNA was extracted from ~10 9 cells of the triplicate cultures first at exponential phase (OD 600 = 0.5) and then from the same cultures again at early stationary phase (OD 600 = 2.0) using TRI-Reagent (Millipore Sigma) according to the manufacturer’s recommendations. For the RNA-seq comparing PAO1 and Δ lasR at 25°C and 37°C, RNA was extracted from biological triplicate cultures at early stationary phase. All samples were treated with TURBO DNase (ThermoFisher) and RNA-seq was subsequently performed by SeqCenter (Pittsburgh, PA) on an Illumina NextSeq 2000 or NovaSeq X Plus as indicated. Libraries were prepared by SeqCenter using Illumina Stranded Total RNA Prep Ligation with Ribo-Zero Plus kit for rRNA depletion. TABLE 2. Bacterial strains used in this study Strain Source Pseudomonas aeruginosa PAO1 Simon Dove (Boston Children’s Hospital) PAO1 Δ lasR ( 9 ) Open in a new tab Analysis of RNA-sequencing Demultiplexing, quality control, and adapter trimming were performed by SeqCenter using bcl-convert. Reads were mapped to the Pseudomonas aeruginosa PAO1 reference genome (NCBI Reference Sequence NC_002516.2 ) using bowtie2 version 2.4.5 on the following settings: very-sensitive, non-deterministic, dovetail, no-mixed, no-discordant, no-unaligned ( 65 ). Mapped reads were counted with htseq-count version 2.0.2, differential gene expression analysis conducted using DESeq2 version 1.38.3 ( 66 ), and visualized with volcano plots made using ggplot2. For Data sets S1 to S6 , genes with a twofold or more change and an adjusted P value <0.05 were considered significant. For principal component analyses (PCA), mapped reads were variance stabilizing transformation (VST) normalized using the vst function of DESeq2 and subsequently used by the plotPCA function of DESeq2 to produce the PCA, which was further visualized using ggplot2. Gene set enrichment analysis of KEGG pathways (in Fig. 1D and E ) was conducted using the gseKEGG function of the clusterProfiler version 4.10.1 and visualized using the dotplot function of enrichplot version 1.22.0. Mapped reads were normalized and visualized (in Fig. 3 ) in Integrative Genomics Viewer (IGV) ( 67 ). Additional information on gene names, descriptions, and locus numbers was sourced from the Pseudomonas Genome Database ( 68 ). ACKNOWLEDGMENTS We thank the Goldberg lab for discussion and feedback on the manuscript. R.E.R. was supported by NIH NRSA F31 Pre-Doctoral Fellowship AI172335. M.J.G. was supported by NIH grant GM156848. This study was supported in part by the Emory Integrated Genomics Core (EIGC), which is subsidized by the Emory University School of Medicine and is one of the Emory Integrated Core Facilities. RNA-seq libraries were constructed and sequenced at SeqCenter. Contributor Information Joanna B. Goldberg, Email: [email protected]. George O'Toole, Dartmouth College Geisel School of Medicine, Hanover, New Hampshire, USA. DATA AVAILABILITY Sequencing data have been deposited to the Gene Expression Omnibus (GEO) at NCBI under accession number GSE304330 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE304330 ). SUPPLEMENTAL MATERIAL The following material is available online at https://doi.org/10.1128/jb.00385-25 . Data set S1. jb.00385-25-s0001.xlsx. Thermoregulated (37°C/25°C) genes at exponential phase. jb.00385-25-s0001.xlsx (53.9KB, xlsx) DOI: 10.1128/jb.00385-25.SuF1 Data set S2. jb.00385-25-s0002.xlsx. Thermoregulated (37°C/25°C) genes at stationary phase. jb.00385-25-s0002.xlsx (51.8KB, xlsx) DOI: 10.1128/jb.00385-25.SuF2 Data set S3. jb.00385-25-s0003.xlsx. Growth phase regulated (stationary/exponential) genes at 37°C. jb.00385-25-s0003.xlsx (156KB, xlsx) DOI: 10.1128/jb.00385-25.SuF3 Data set S4. jb.00385-25-s0004.xlsx. Growth phase regulated (stationary/exponential) genes at 25°C. jb.00385-25-s0004.xlsx (174KB, xlsx) DOI: 10.1128/jb.00385-25.SuF4 Data set S5. jb.00385-25-s0005.xlsx. LasR regulated (Δ lasR /PAO1) genes at 37°C. jb.00385-25-s0005.xlsx (55.4KB, xlsx) DOI: 10.1128/jb.00385-25.SuF5 Data set S6. jb.00385-25-s0006.xlsx. LasR regulated (Δ lasR /PAO1) genes at 25°C. jb.00385-25-s0006.xlsx (49.4KB, xlsx) DOI: 10.1128/jb.00385-25.SuF6 Table S1. jb.00385-25-s0007.pdf. Genes whose LasR regulation depends on temperature. jb.00385-25-s0007.pdf (151.4KB, pdf) DOI: 10.1128/jb.00385-25.SuF7 ASM does not own the copyrights to Supplemental Material that may be linked to, or accessed through, an article. The authors have granted ASM a non-exclusive, world-wide license to publish the Supplemental Material files. Please contact the corresponding author directly for reuse. REFERENCES 1. Letizia M, Diggle SP, Whiteley M. 2025. 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Growth phase regulated (stationary/exponential) genes at 37°C. jb.00385-25-s0003.xlsx (156KB, xlsx) DOI: 10.1128/jb.00385-25.SuF3 Data set S4. jb.00385-25-s0004.xlsx. Growth phase regulated (stationary/exponential) genes at 25°C. jb.00385-25-s0004.xlsx (174KB, xlsx) DOI: 10.1128/jb.00385-25.SuF4 Data set S5. jb.00385-25-s0005.xlsx. LasR regulated (Δ lasR /PAO1) genes at 37°C. jb.00385-25-s0005.xlsx (55.4KB, xlsx) DOI: 10.1128/jb.00385-25.SuF5 Data set S6. jb.00385-25-s0006.xlsx. LasR regulated (Δ lasR /PAO1) genes at 25°C. jb.00385-25-s0006.xlsx (49.4KB, xlsx) DOI: 10.1128/jb.00385-25.SuF6 Table S1. jb.00385-25-s0007.pdf. Genes whose LasR regulation depends on temperature. jb.00385-25-s0007.pdf (151.4KB, pdf) DOI: 10.1128/jb.00385-25.SuF7 Data Availability Statement Sequencing data have been deposited to the Gene Expression Omnibus (GEO) at NCBI under accession number GSE304330 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE304330 ). 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