Global analysis of the cold-shock response in the model antibiotic producing actinomycete, Streptomyces coelicolor A3(2)

Global analysis of the cold-shock response in the model antibiotic producing actinomycete, Streptomyces coelicolor A3(2) | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Global analysis of the cold-shock response in the model antibiotic producing actinomycete, Streptomyces coelicolor A3(2) View ORCID Profile R. Tony Evans , View ORCID Profile Giselda Bucca , View ORCID Profile Andrew Hesketh , View ORCID Profile Colin P. Smith doi: https://doi.org/10.1101/2025.04.11.648403 R. Tony Evans 1 School of Applied Sciences, University of Brighton , Lewes Road, Brighton, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for R. Tony Evans Giselda Bucca 2 School of Immunology & Microbial Sciences, Faculty of Life Sciences & Medicine, Guy’s Hospital, Borough Wing, Great Maze Pond, King’s College London , London, SE1 9RT, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Giselda Bucca For correspondence: giselda.bucca{at}kcl.ac.uk buccagiselda9{at}gmail.com Andrew Hesketh 1 School of Applied Sciences, University of Brighton , Lewes Road, Brighton, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Andrew Hesketh Colin P. Smith 2 School of Immunology & Microbial Sciences, Faculty of Life Sciences & Medicine, Guy’s Hospital, Borough Wing, Great Maze Pond, King’s College London , London, SE1 9RT, UK 3 School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey , Surrey, GU2 7XH, UK . E-mail: Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Colin P. Smith For correspondence: c.p.smith{at}surrey.ac.uk Abstract Full Text Info/History Metrics Supplementary material Preview PDF ABSTRACT The cold shock (CS) response of the model actinomycete bacterium, Streptomyces coelicolor A3(2) has been characterized for the first time at the transcriptome and translatome level. Key players of the CS response reside in three operons encoding a CspA homologue, a DEAD box helicase and either a cystathionine-beta-synthase domain protein, or a protein of unknown function, or both ( SCO5921–SCO5918; SCO46984-SCO4686; SCO3731-SCO3733 ). Genes in the SCO5921-SCO5918 and SCO4684-SCO4686 operons are subjected to massive transcriptional induction, up to 2,000-fold, upon cold acclimation. Moreover, SCO5920 , SCO5919 and SCO5918 are the most highly upregulated at the transcriptional and translational level (potentiated). Cold adaptation resulted in transcriptional changes in 811 genes, with enrichment for four functional groups: helicases, transcription factors, phenylalanine metabolism and extracellular functions. Major CS-induced gene products are involved in assisting transcription and translation at low temperature including RNA helicases and RNA chaperone proteins (CS proteins). The considerable induction of these gene products is presumed to reflect their critical importance to removing excessive nucleic acid secondary structure in the high %G+C Streptomyces genome (>73% G+C). Three novel CS-induced transcriptional regulators were identified: SCO1568, SCO4640 and SCO7014. Several putative cis-acting regulatory elements have been identified in the CspA-encoding cold-shock operons and other members of the CS regulon. Furthermore, two small non-coding RNAs are substantially induced by cold-shock, sRNA126 and sRNA208, and their expression correlates with that of the novel transcription factors. Other upregulated genes were identified with functions in modification of cell membrane (e.g. delta fatty acid desaturase, des ( SCO3682 )) and cell wall structure (e.g. D-alanyl-D-alanine carboxypeptidase ( SCO7050 ) and SCO617 9)). Several membrane efflux transporter pumps conferring resistance to translation targeting antibiotics were induced, including pqrB which encodes a multidrug resistance efflux pump of the major facilitator superfamily and SCO4120, conferring ciprofloxacin and chloramphenicol resistance. The phenylacetate degradation (PAA) regulon is co-ordinately CS-induced. Exclusively translationally enhanced genes are enriched in the protein phosphorylation functional category. The highly conserved gene pair, SCO0818 and SCO0819 , encoding an ABC transporter ATP-binding protein and a transmembrane protein, is in this group. The CS-induced transcriptional and translational cis-acting control regions identified in this study, within the massively induced SCO5921 and SCO4684 operons, could be exploited as novel synthetic biology tools for manipulating antibiotic biosynthetic gene clusters in this industrially important bacterial group. INTRODUCTION Streptomycetes are Gram-positive non-motile bacteria notable for their production of a wide range of secondary metabolites, most notably antibiotics, their unusual developmental biology and the high proportion of guanine and cytosine bases in their DNA (‘High G+C content’). They are found in numerous ecosystems and are ubiquitous in soil. In order to survive in the dynamic and competitive environments in which they live, they must be able to respond quickly to changes in their environment, such as changes in pH, temperature, nutrient availability which is scarce in an oligotrophic soil environment or exposure to antibiotics excreted by competing organisms. We previously demonstrated ( Bucca et al., 2018 ) that the streptomycete response to heat shock is largely controlled post-transcriptionally, enabling a fast response to this stress. In the heat shock response, of the seventy-four more efficiently translated genes identified in the above study, the most enriched cluster was nucleic acid binding proteins including six putative cold-shock proteins (CSPs), SCO0527, SCO3731, SCO3748, SCO4505, SCO4684 and SCO5921. The cold-shock response in Escherichia coli and Bacillus subtilis has been much studied ( Zhang et al., 2018 , Gualerzi et al., 2003 , Weber and Marahiel, 2002 ), and the central role of the cold-shock protein A (CspA) revealed, but no comparable studies have yet been reported on the genomic response to cold-shock in the model actinomycete, Streptomyces coelicolor A3(2). Post transcriptional and translational regulation of cspA and other cold shock mRNAs is well documented in E. coli ( Giuliodori et al., 2010 ); the cspA mRNA has a 5’ untranslated region which functions as a thermosensor to stabilize the mRNA at low temperature aiding its binding to the 30S ribosomal subunit via the ‘downstream box’ sequence 12 bases downstream of the initiation triplet ( Giuliodori et al., 2010 , 2019 , Xia et al., 2002 ). Trans acting factors (IF3 and CspA itself) also contribute to the translational bias of cold shock transcripts during cold acclimation in concert with cis acting elements in the 5’-untranslated regions. The ribosome could also play a role as temperature sensor and ribosomal protein composition can be modified upon cold-shock, resulting in a translation apparatus more efficient at translating cold shock mRNAs ( Gualerzi et al., 2003 ). Zhang et al (2018) have demonstrated a drastic increase in global mRNA secondary structure 30 min after cold-shock from 37°C to 10°C in E. coli ; this is accompanied by a global arrest in bulk protein translation (measured by ribosome profiling) due to a sharp decline in protein elongation rate and inhibition in protein translation initiation. As E. coli cells start to acclimatize in the 6 hours following exposure to cold-shock, the amount of structured RNA decreases and translation resumes although at a much reduced rate. Two classes of ‘cold shock’ proteins are principally responsible for the acclimation phase following a sudden drop in growth temperature: the ribonuclease, RNaseR, and CspA. RNaseR is presumed to degrade highly structured mRNAs which can still bind ribosomes but cannot be translated, while CspA is an abundant RNA binding protein whose synthesis massively increases following exposure to cold temperatures. CspA functions as a chaperone of nascent mRNAs; by binding to mRNAs CspA avoids the formation of unwanted secondary structures and favours translation initiation. Given its ability to bind and melt double stranded RNAs, CspA also resolves secondary structures that are already formed ( Gottesmann, 2018 ; Zhang et al., 2018 ; Rennella et al., 2017 ). A recent transcriptomic study of the cold shock response in Mycobacterium smegmatis , a close relative of the Streptomyces bacteria, belonging to the same Actinomycete group, revealed different dynamics of the cold stress induced genes during acclimation and adaptation phases; in addition to CspA and DEAD box helicases, different sets of genes were induced during the acclimation phase, including genes associated with cell wall remodelling, starvation response, osmotic pressure stress and DNA topology enzymes. Global changes in the expression of transcription factors and the downregulation of ribosomal genes were observed during the acclimation phase; those changes were reversed in the adaptation phase to allow cells to grow again even if at a lower rate ( Grigorov et al, 2023 ). In the present study we have analysed global changes in transcription and translation of S. coelicolor A3(2) MT1110 in response to a sudden decrease in temperature from 30°C to 10°C in supplemented minimal liquid medium (SMM). Transcriptome changes were followed in parallel by global quantification of mRNAs association with monosome and polysome fractions through polysome profiling as a proxy for monitoring translation. Translational efficiencies (TE) were calculated to distinguish transcripts that were regulated either at the level of transcription, or of translation, or both, following exposure to cold temperatures. MATERIALS AND METHODS Establishment of cold-shock induction conditions and RNA extraction Spores from S. coelicolor prototrophic strain MT1110 ( Hindle and Smith, 1994 ) were pre-germinated in 100 ml of 2 x YT medium ( Kieser et al., 2000 ) for 7 h at 30°C in an orbital shaker at 250 rpm and the germ tubes used to inoculate 165 ml of SMM medium ( Kieser et al., 2000 ) in 500 ml conical flasks containing springs approximately equal in length to the bottom circumference of the flask, at an inoculum concentration of approx. 500,000 cfu / ml. The cultures were incubated for 17 h 13 min (samples CT0A, CT0B, CS120A, CS120B, CT120A) or 15 h 45 min (samples CT0C, CT120B, CS120C, CT120C) at 30°C and 250 rpm, corresponding to late exponential growth phase. Ten ml of each culture was taken immediately prior to the cold-shock as a ‘time=0’ reference, treated with RNAProtect (Qiagen Cat. No. 76506) by incubation at room temperature for 10 min. Bacterial pellets were stored at -80°C for later total RNA extraction. For Polysome profiling 20 ml of culture was taken at the same point for use as a ‘time=0’ reference for the monosome and polysome associated fractions. The experimental design is summarised in Figure 1 . Download figure Open in new tab Figure 1 Schematic representation of the experimental design of the cold-shock experiments. Cold-shock eliciting conditions: 30 ml of cultures were exposed to cold-shock by the addition of 3 volumes of fresh medium pre-equilibrated at 4°C to rapidly reduce the temperature to 10°C, whilst control cultures had 3 volumes of fresh medium pre-equilibrated at 30°C added. After 2 h incubation at 10°C, 40 ml of culture was sampled for total RNA analysis (cultures were treated with RNAPprotect as described above) and 50 ml was treated with chloramphenicol and the cell lysates were fractionated through sucrose gradients as described below. Two biological replicates were analysed. Polysome profiling The polysome profiling fractionation method was as described in Bucca et al (2018) ; 20 ml of culture was taken at the same point for use as a ‘time=0’ reference for the monosome and polysome associated fractions, chloramphenicol was added to a final concentration of 80 µg / ml in order to stop translation, then mycelia were chilled on ice and mycelial pellets were collected by centrifugation at 6,000 r.p.pm. for 4 min at 4°C. The mycelium was resuspended in 3 ml ice-cold lysis buffer (20 mM Tris-HCl, pH 8.0, 140 mM KCl, 1.5 mM MgCl 2 , 0.5 mM DTT, 1% Triton X-100, 80 μg/ml chloramphenicol, protease inhibitor cocktail (Roche) and 100 u/ml RNase out (Thermo Fisher Scientific)) disrupted mechanically by mixing on a vortex mixer in the presence of 5 mm glass beads for 20 sec, four times, with 1 minute intervals on ice. The mycelial debris was discarded after centrifugation at 12,000 rpm/5 min/4°C and the supernatant retained for fractionation by ultracentrifugation at 166,880 RCF / 4°C in a 10%-50% sucrose gradient prepared from 75% sucrose solution in RNase-free water diluted to five solutions at final concentrations of 10-50% sucrose in 20 mM Tris-HCl, pH 8.0, 140 mM KCl, 5 mM MgCl 2 , 0.5 mM DTT, 80 μg/ml chloramphenicol. After ultracentrifugation, the monosome and polysome fractions were obtained by loading the gradients into a Teledyne ISCO gradient fractionator (Teledyne Foxy R1 Brandel). The collected fractions were rapidly frozen in liquid nitrogen and stored at -80°C. Polysome and monosome associated RNAs were extracted by mixing 3 volumes of Trizol-LS (Invitrogen 10296028) to 500 μl sucrose gradients fractions corresponding to the monosome/polysome peaks. The mixture was thoroughly mixed by vortex mixer for 15 sec and incubated 5 min at room temperature. 200 µl chloroform was added and samples were mixed by vortex mixer for 15 sec, incubated at room temperature for 5 min and centrifuged to separate the phases. The upper phase was retained and the RNA was precipitated at - 80°C for 1 hour by adding 0.1 vol of 3M sodium acetate, 1µl of glycoblue (Invitrogen AM9516) and 1 vol of isopropanol. RNA was pelleted at 9,838 RCF / 4°C for 1 h and the supernatant discarded, the RNA pellet washed twice in 1 ml ice-cold 75% ethanol and then dissolved in nuclease-free water. For total RNA extraction (transcriptome analysis), pellets from 10 ml (time=0 reference) or 40 ml (cold-shock or control samples) of bacterial cultures were resuspended in 200 µl of lysozyme dissolved in TE buffer at a concentration of 0.015 g per ml and incubated at room temperature for 15 min. 600 µl of RNeasy Lysis Buffer (RLT buffer, Qiagen 79216) containing 10 µl/ml β-mercaptoethanol was added and the mixture mixed by vortex mixer then transferred to a 2 ml microfuge tube containing one 5 mm stainless steel bead (Qiagen 69989) and placed in a Tissuelyser LT (Qiagen 85600) for efficient mechanical cell disruption / homogenisation for 2 min at 30 rpm. The suspension was then centrifuged at 16,627 RCF for 2 min, the supernatant was recovered, and its volume estimated. One volume of acid pH 4.5 phenol:chloroform:isoamyl alcohol (25:24:1, Fisher AM9720) was added, and the mixture mixed by vortex mixer for 30 seconds, then centrifuged at 4°C for 5 min at 16,627 RCF. The upper phase containing the nucleic acids was removed and the phenol/chloroform extraction repeated twice more. Then one volume of chloroform was added, the mixture mixed by vortex mixer then centrifuged at 4°C for 2 min at 16,627 RCF, and the upper phase was again transferred to a fresh RNase-free microfuge tube. From this point onward the standard manufacturer’s instructions were followed for the miRNAeasy RNA extraction kit (Qiagen 217004). The total RNA was then eluted in 30 µl of nuclease free water and stored at -80°C. Genomic DNA was removed using the Turbo DNA free kit (Invitrogen AM1907). The RNA extracted from monosome and polysome fractions and the corresponding paired total RNA samples were quantified using a Nanodrop 1C spectrophotometer (Labtech International) and quality checked on an Agilent TapeStation 4200 instrument (Agilent Technologies). The RIN e of the RNA samples taken forward for analysis were between 6.5-9.2 (average value for RNAseq experiments = 7.94 and Polysome profiling experiments = 7.56). The NEBNext RNA Depletion Core Reagent Set (NEB cat. E7865) with custom probes to specifically deplete the most abundant rRNAs and the three abundant RNAs, rnpB, ssrA and srp from the S. coelicolor transcriptome (Supplementary Data File S1. These were identified in the course of previously unsuccessful attempts to deplete rRNAs from S. coelicolor using other commercially available kits (Illumina Ribozero Bacteria rRNA depletion kit, Cat No. MRZMB12424, Qiagen QIAseq FastSelect 5S/16S/23S kit, Cat. No. 335927. Sequencing libraries were prepared using the NEBNext Ultra II Directional RNA Library Prep Kit (NEB cat. 7760), and sequenced on a NextSeq 500 sequencer using a mid-output V2.5 paired end 2 x 75 cycles (Illumina Cat. No. 20024904). Data analysis The Illumina BaseSpace web portal ( http://basespace.illumina.com ) was used to submit RNA-seq files to the NextSeq 500, verify the quality of the run, and download the resulting files in FASTQ format. The S. coelicolor genome assembly ASM20383v1 (RefSeq accession No. GCF_00020385.1) was downloaded to serve as a reference. Start and stop positions of all open reading frames were extracted from the reference genome and combined with known transcription start and stop positions of all RNAs identified by the B. K. Cho laboratory ( Jeong et al., 2016 ) Initial sequencing read quality control was performed using fastqc (( https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ version 0.11.9) and multiqc (version 1.8) ( Ewels et al., 2016 ). Quality controlled reads were quantified using kallisto quant 0.46.2 ( Bray et al., 2016 ) and a transcriptome mapping index derived from S. coelicolor genome version GCF_000203835.1_ASM20383v1. Kallisto transcript quantifications were converted to gene level by tximport 1.20.0 (Sonenson et al., 2016). The data was normalized and analysed in R using the DESeq2 pipeline ( Love et al., 2014 ). Unsupervised clustering of the sample data was performed using the R packages pheatmap ( Kolde, 2019 ) and pcaMethods ( Stacklies et al., 2007 ). Significant changes in gene transcript abundance between conditions within each RNA fraction (total RNA, polysome or monosome) were identified by applying a 5% false discovery significance threshold (padj<=0.05). Significant changes in translational efficiency (padj<=0.05) were determined using data from both the polysome and total RNA fractions employing a generalised null hypothesis of (Condition 1 polysome – Condition 1 total RNA) -(Condition 2 polysome – Condition 2 total RNA) = 0, where conditions 1 and 2 are the two experimental conditions being compared. This is based on a definition of translational efficiency (TE) for a given gene being equal to the quantity of a gene transcript present in the polysome divided by the quantity of the same gene transcript present in the total RNA. In comparisons between transcript abundance changes taking place in the polysome and total RNA (transcriptome) fractions, genes were assigned to the following groups based on the stated criteria: forwarded , significantly changed in both the polysome and the transcriptome, but no significant change in TE; exclusive , significantly changed in the polysome but not the transcriptome; intensified (also known as potentiated) , significantly changed in the transcriptome and a significant change in TE in the same direction (i.e., both increased or both decreased); buffered , significantly changed in the transcriptome and a significant change in TE in the opposite direction (ie. one increased and one decreased); none, not significantly changed in either the polysome or the transcriptome. Supplementary Data File S2: p.GSE229820.combined.rna_v_ps.xlsx presents the expression data for all genes at both the transcriptional and translational level. Functional analysis of the groups of DE genes was performed using clusterProfiler (Yu et al., 2012). Annotations for the gene ontology (GO) categories was downloaded from the EBI database (84.S_coelicolor.goa) in July 2024. Functional enrichment analysis was also performed using the STRING protein-protein interaction networks database ( Szklarczyk et al., 2023 ). Common DNA sequence motifs in the DNA sequences encompassing the translation initiation regions (−200 bp to +200 bp relative to the start codon) of selected members of the cold-shock regulon were identified using the MEME Suite ( Bailey et al., 2015 ). RESULTS AND DISCUSSION Transcriptional response to cold-shock in Streptomyces coelicolor In order to determine the optimal conditions for cold-shock, a time course experiment was conducted, sampling at 15, 30, 60 and 120 min after administering a cold-shock at 10°C (from 30°C to 10°C). A parallel set of control cultures were similarly handled but returned to growth at 30°C ( Figure 1 ). This controls for the effects of the addition of fresh medium during the cold shock which are likely to include changes in nutrient availability and pH, and the dilution of any inhibitory metabolic products. The strongest response was observed after 120 minutes at 10°C, and genes were deemed to be transcriptionally significantly differentially expressed (DE) in response to cold-shock if their expression was significantly altered two hours after cold treatment (adj P<0.05) compared to the matched 30°C control (10°C 120 min v 30°C 120 min), and was also significantly changed in the same direction of up- or down-regulation relative to the pre-treatment sample (10°C 120 min v 30°C 0 min)( Figure 2a ). This identified 811 genes that are transcriptionally significantly differentially expressed following cold shock, comprising 532 that are progressively up-regulated in response to the cold treatment, and 279 that are down-regulated ( Figure 2b , clusters 1 and 2 respectively). Notably, several hundred genes that are significantly differently expressed in the 10°C 120 min v 30°C 120 min comparison are excluded from consideration as being cold responsive since they are not also significantly changed at 10°C relative to the pre-treatment sample (10°C 120 min v 30°C 0 min) ( Figure 2a ). Cold-shock treatment is growth-inhibitory and these are likely to be growth-related genes that more quickly change in expression in the 30°C control conditions than during culturing at 10°C. The experimental design evaluates expression in terms of transcript abundance and will be a mixture of changes in the level of induction or repression of each gene and in the half-life of its mRNA transcript. Download figure Open in new tab Figure 2a. Identification of cold-shock induced genes. Time course data from liquid SMM transcriptome experiment, Accession No. GSE225850. The graph represents the overlap between sets of significant genes. Sets of genes that are significantly changed in the ‘120 difference’ group AND also significantly changed in any of the other groups that are relative to time 0 were taken forward in the analysis. These are considered ‘cold-shock’ responsive genes which are largely captured by the intersection of the differences identified in ‘120min 10 degrees v 120min 30 degrees’ and ‘120min 10 degrees’ v ‘0min 30 degrees’. These sets of genes are indicated by asterisks above the plots and represent the three conditions used in analysing translational control (Accession No. GSE229820). Download figure Open in new tab Figure 2b. Hierarchical clustering of cold-shock responsive genes. The 811 genes in the groups indicated by asterisks in Figure 2a . The genes are detailed in Supplementary Data File S3.p.Heatmap.GSE225850_clusters.xlsx Three cold-shock protein-encoding operons are massively induced following cold-shock. The S. coelicolor genome encodes a total of nine CSP homologues; only three CSPs were significantly DE following cold shock, and are contained in three operons ( Figure 3a ). Each operon encodes a highly conserved cold-shock protein (CspA homologue) and a ‘DEAD box’ helicase which is also massively cold-shock induced. A gene of unknown function and/or encoding a cystathionine ý-synthase domain containing protein are transcribed in the same operons. The expression time course of the respective helicases adjacent to cold shock domain proteins is shown in Fig 3b . Genes comprising the three cold-shock induced CSP operons were all induced substantially: up to 1,973-fold ( SCO5920 ) and 1,218-fold ( SCO4685 ). (Supplementary Data File S3: p.Heatmap.GSE225850_clusters.xlsx; Supplementary Data File S4: DESeq2_SMM_GSE225850_GSE229820.xlsx). The analysis presented in Figure 2 refers to RNA-seq experiment Accession No. GSE225850. Note: a second RNA-seq experiment, with Accession No. GSE229820, was performed in parallel with polysome profiling. Download figure Open in new tab Figure 3a. Genetic organisation of the three major cold shock induced operons of Streptomyces coelicolor . TSS indicates positions of known transcription start site(s), and in the two operons, SCO5921-SCO5918 and SCO4684-SCO4686 , the ‘cold-shock protein’ gene is immediately followed by a large, conserved, stem-loop structure (CS_IR_sco; Figure 7 ). Scale above each diagram shows position on the chromosome (in kb). Adapted from images from NCBI Reference Sequence NC_003888.3 at https://www.ncbi.nlm.nih.gov . Download figure Open in new tab Figure 3b. Time course of cold-shock induced expression of genes encoding cold-shock domain proteins and helicases in the two major cold-shock operons. Functional enrichment analysis of the DE genes The hierarchical clustering identified two main clusters of significantly DE genes, respectively up and down regulated by cold-shock. Functional enrichment analysis performed by clusterProfiler on the 811 DE genes revealed no significant functional enrichment for genes whose expression profiles were downregulated (Cluster 2 in Figure 2b ). Four functionally-enriched categories were identified in the genes that were upregulated following cold shock (cluster 1 in Fig 2b ): (1) helicase activity (GO:0004386, GOMF); (2) transcription cis-regulatory region binding (GO:0000976, GOMF); (3) Phenylalanine metabolism (sco00360, KEGG pathway); (4) extracellular region (GO:0005576, GOCC) ( Figure 4 ). Helicase activity The expression profiles of the nine helicase-encoding genes significantly upregulated in this study are presented in Figure 5 . The three DEAD box helicases encoded by SCO4685 , SCO5920 and SCO3732 in the three cold shock operons ( Figure 3a ) are in this category. DEAD box helicases are well conserved cold shock proteins across all bacteria and could be considered global post transcriptional regulators. They are able to destabilize secondary structures in mRNA at low temperature and therefore are of crucial importance in allowing the reestablishment of fundamental cellular processes that are affected by the sudden exposures to low temperatures, such as transcription and translation ( Phadtare, 2004 ). The Streptomyces genome is characterized by a high 73 % of G+C, often reaching >80% G+C in translated sequences and therefore the secondary structures formed would represent more of an obstacle to transcription and translation compared to other bacteria, such as E. coli and B. subtilis . The DEAD box helicases encoded by SCO4685 , SCO5920 and SCO3732 are similar to the RNA helicase RhlE from E. coli which is involved in ribosome assembly, facilitating the interconversion of ribosomal RNA intermediaries that are further processed during ribosome maturation ( Jain, 2008 ) The functionally enriched category ‘helicase’ also comprises two Rho transcription termination factors, encoded by SCO0537 and SCO7051 . These are RNA-DNA helicases that actively release nascent mRNA from paused transcription complexes in addition to facilitate transcription termination by a mechanism that involves Rho binding to the nascent RNA and release of mRNA from the DNA template. Their increased synthesis is probably necessitated by the extensive secondary structures formed in the high %G+C Streptomyces genome. The expression profiles of the five most highly induced helicases are illustrated in Figure 6 . A DNase encoding gene ( SCO2737 ) and another DEAD box helicase ( SCO5166 ) are also in the helicase category although their cold-shock induction levels are not so striking. Transcription cis -regulatory binding regulators Twenty six transcriptional regulators are induced by cold-shock in S. coelicolor ( Fig 5 ) where the expression of three regulators, encoded by SCO1568 , SCO4640 and SCO7014 are particularly striking ( Figures 5 and 6). Of these, only SCO1568 has been reported in the literature previously; it encodes the ‘paraquat resistance’ negative transcriptional regulator PqrA ( Cho et al., 2003 ) which regulates itself and the other components of the operon. SCO7014 , encodes a probable LacI family transcriptional regulatory protein while SCO4640 encodes a probable TetR family transcriptional regulator. Extracellular functions. The cold-shock expression profiles of the ten genes belonging to this category are presented in Figure 5 and are listed in Supplementary Data File S5 (p.ORA.genes.GSE225850.xlsx). The most highly induced gene, SCO3471 , encodes the DagA agarase precursor protein. Phenylalanine metabolism. Ten cold-shock induced genes are associated with the phenylacetic acid degradation pathway (PAA), an intermediate in the catabolism of the amino acid L-phenylalanine. PAA catabolism leads to the production of succinyl-Co-A and acetyl Co-A which feeds into the TCA cycle. The PAA pathway is highly regulated under many diverse conditions associated with stress signalling in Acinetobacter ( Hooppaw et al., 2022 ). Download figure Open in new tab Figure 4. Functional enrichment analysis of the genes in Cluster 1 ( Figure 2b : heatmap). Key: GOCC; Gene Ontology Cellular Component; GOMF, Gene Ontology Molecular Function; KEGG, KEGG metabolic pathway. Download figure Open in new tab Figure 5. Expression time course of the cold-shock induction of genes comprising the four significant functionally enriched groups ( Figure 4 ). The normalised expression values are given in Supplementary Data File S5 p.ORA.genes.GSE225850.xlsx. Download figure Open in new tab Figure 6. Heatmap representing the time course of expression of the most highly expressed cold-shock induced genes encoding helicases and transcriptional regulators shown in Figure 5 . The normalised expression values are given in Supplementary Data File S5 p.ORA.genes.GSE225850.xlsx. Other highly induced cold-shock genes Modification of cell membrane and cell wall and ABC transporters. Following cold-shock, the cell membrane becomes less fluid, affecting permeability and the functions of membrane-associated proteins ( Zhang et al., 2021 ). The gene des ( SCO3682 ) is homologous to the Bacillus subtilis delta fatty acid desaturase encoding gene which acts to increase membrane fluidity by adding double bonds to fatty acids attached to the membrane. SCO3682 together with the first gene of the operon SCO3681 and SCO3684 and SCO3685 are strongly cold shock induced. SCO3681 , SCO3684 and SCO3685 encode proteins of unknown function. The synthesis of two cell wall and cell wall glycan biosynthetic enzymes are cold shock induced: SCO7050 and SCO6179 . SCO7050 encodes a D-alanyl-D-alanine carboxypeptidase, a member of the penicillin binding proteins (PBPs), a family of proteins inhibited by ß-lactam antibiotics that are involved in peptidoglycan synthesis and remodelling. SCO6179 encodes a nucleotide sugar dehydratase, the first gene of the cwg operon encoding the enzymes involved in the biosynthesis of a c ell w all g lycan ( Hong et al., 2002 ) In our data set we also observe cold-shock induction of efflux pump encoding genes. For example: SCO4120, encoding an integral membrane protein, is similar to multidrug resistance proteins conferring resistance to ciproflaxin, chloramphenicol and increasing oxidative stress tolerance ( Nag et al., 2021 ); sco3366 encoding a rifampicin efflux pump ( Nag and Mehra, 2022 ), prqB ( SCO1567 ) encoding a Major Facilitator Superfamily (MFS) efflux pump known to confer resistance against the redox cycling agent paraquat ( Cho et al., 2003 ), and cmlR2 ( SCO7662 ) which confers resistance to chloramphenicol ( Vecchione et al., 2009 ); SCO4641 , encoding a transmembrane efflux pump, belonging to the MFS superfamily (Bateman et al., 2023) and the first two genes the gene cluster areABCD ( SCO3956 – SCO3959 ) encoding two ABC transporter systems (Jetsin et al., 2013). SCO3956 is universally conserved across all domains of life while SCO3959 is conserved across bacteria. Identification of conserved motifs in the 5’-regions of cold shock genes The observation that three transcriptional regulators (TFs) are strongly induced by cold shock ( Fig 6 ) prompted a search for genes with correlated expression profiles to identify potential targets of the respective TFs (Supplementary Data File S6: Genes correlating with the three CS TFs). We observed high Spearman correlations with several genes including the CspA-encoding homologues, SCO4684 and SCO5921 . Two small RNAs, sRNA126 and sRNA208 also ranked in the list of top scoring correlated genes. Searches for conserved DNA sequence motifs were then conducted using MEME ( Bailey et al., 2015 ). Two gene sets were selected for the motif searching: (Set 1) The top scoring 39 genes most highly correlated (Spearman) with the expression profile of the three cold-shock inducible transcriptional regulators (TFs) identified in our study: SCO1568, SCO4640 and SCO7014. Eleven cold-shock induced genes associated with membrane remodelling and efflux pumps plus the cold-shock inducible TF, SCO7014, were added to the list forming a total of 50 genes (Supplementary Data File S6 Genes correlating with the three CS TFs) ; (Set 2) Genes that were reported in the four functional enrichment categories identified in this study as putative members of the cold shock regulon (55 genes; Fig 4 and 5; Supplementary Data File S5). Four conserved motifs and one conserved large inverted repeat which have potential regulatory roles in the cold shock response were identified ( Figure 7 ). The three major cold-shock operons contain one or more motifs in the upstream region of genes encoding the CspA homologue and the DEAD box helicases ( Figure 8a , Table 1 ). SCO4685 and SCO5920 have several conserved motifs in their upstream regions: CS_IR_sco, a large stem loop IR sequence; additionally, CS_Motif_1_sco and CS_Motif_2_sco motifs are present in the translation initiation regions of SCO3732 , SCO4685 and SCO5920 . Moreover CS_Motif_4_sco is present in the translation initiation region of SCO4685 and SCO5921 . Interestingly, CS_Motif_1_sco overlaps the start codons of the respective genes ( Figure 8a ). The relative positions of the identified motifs 1-4 suggests a role in translational regulation. The motif alignments of the four conserved motifs are presented in Table 1 ; the motif logos are presented in Figure 7 . Download figure Open in new tab Figure 7. Conserved DNA sequence motifs identified in this study. Consensus logos of the cold-shock motifs 1 – 4 and the inverted repeat sequences upstream from the genes encoding the two major cold-shock induced helicases. Blue font indicated nucleotide differences between the 2 CS_IR_sco sequences and red font indicates non-palindromic nucleotides. Download figure Open in new tab Download figure Open in new tab Figure 8a. Conserved DNA sequence motifs identified upstream from cold-shock induced helicase-encoding genes. The different motifs listed in Table 1 are colour coded in the DNA sequence: CS_Motif_1_sco (3 sites, specific to the 3 helicase-encoding genes); CS_Motif_2_sco : this is a truncated version of CS_Motif_1_sco and is underlined and italicised in the sequence; CS_Motif_4_sco ; CS_IR_sco shows the stem-loop sequence in SCO4685 and SCO5920 . Translation start codons, ATG , are indicated in red. View this table: View inline View popup Table 1. Conserved sequence motifs in cold shock induced genes. The consensus sequences of each motif identified in this study are presented together with the coordinates of each hit and their respective statistical significance. Download figure Open in new tab Figure 8b. Location of CS_Motif_3_sco DNA sequence motifs in the divergently transcribed SCO7470 - SCO7471 intergenic region of the phenylacetic acid degradation (PAA) regulon. Protein coding sequences are presented in boldface, TSSs (>) and start codons are boldface and underlined. A fifth motif, CS_Motif_3_sco, has been mapped in the intergenic region of the phenylacetic acid degradation-encoding (PAA) operon between the two divergently transcribed genes, SCO7470 and SCO7471 ( Figure 8b ). The PAA operon is co-ordinately induced by cold-shock. This suggests an important role in stress resistance and cold adaptation, for example through the provision of TCA cycle intermediates. Post-transcriptional regulation of the cold-shock response The rate limiting step in protein synthesis is translation initiation, and ribosome attachment to the transcript can therefore be used as a proxy for translation ( Duval et al., 2015 ). To explore changes in translation in response to cold-shock, we exposed a second set of cultures to the optimal cold-shock conditions established above, 120 min treatment at 10°C, and subjected the samples to RNA-seq and polysome-profiling (Experiment with Accession number GSE229820). Translational Efficiency (TE) is the ratio between the number of transcripts for a particular gene being translated in a cell versus the number of transcripts present, and any significant changes in TE is considered to demonstrate the existence of post-transcriptional regulation. The deltaTE protocol developed by Chothani et al. (2019) was used to analyse post-transcriptional regulation in both the cold-shock and control cultures. Genes which showed a significant difference in their TE were classified into four groups, defined as follows. Forwarded – genes that are transcriptionally regulated. Their TE doesn’t change significantly compared with the reference, they are translated in proportion to their transcription level. Exclusive – genes that are exclusively regulated at the translational level. They show no significant change in transcriptional expression but show up or downregulation in the ribosome associated fractions, and hence increased or decreased translation rates. Intensified (also known as Potentiated )– genes that are regulated both transcriptionally and translationally, and the translational regulation is in the same direction as transcription. That is, if their transcripts are significantly more abundant, their translation is even more abundant (‘potentiated up’) and vice versa (‘potentiated down’). Buffered - genes that are regulated both transcriptionally and translationally, and the translational regulation is in the opposite direction to transcription. That is, if their transcripts are significantly more abundant, this effect is buffered by them being translated at a significantly lower rate and vice versa. The scatter plots representing the relative changes in the transcriptome and polysome-associated transcripts in cold-shocked and control cultures are presented in Figure 9 and the associated data are in Supplementary Data File S2. Overall, there is a good correlation between changes in the total RNA and changes in the polysome-associated fractions (10°C 120 min v 30°C 0 min, R=0.839 (p-value < 2.2e-16); 10°C 120 min v 30°C 120 min, R=0.835 (p-value < 2.2e-16); 30° 120 min v 30°C 0 min, R=0.799 (p-value < 2.2e-16)). Download figure Open in new tab Figure 9. Scatter plots of the transcriptome data relative to the polysome profiling data. There are good correlations between changes in relative abundance of transcripts in the polysome fraction compared to their respective changes in abundance in the transcriptome: ‘10°C 120 min v 30°C 0 min’, R=0.839 (p-value < 2.2e-16); ‘10°C 120 min v 30°C 120 min’, R=0.835 (p-value < 2.2e-16); ‘30° 120 min v 30°C 0 min’, R=0.799 (p-value < 2.2e-16)). The different classifications of expression, forwarded, exclusive, potentiated and buffered are colour-coded below the figure. The key potentiated cold-shock operon SCO5921-SCO5918, is indicated on the plots. The data used to generate these plots is given in Supplementary Data File S2. Post-transcriptional regulation following cold-shock Potentiated genes Sixty four genes were identified as potentiated 37 potentiated up and 27 potentiated down). There is an over-representation of ABC transporters and other integral membrane proteins in the genes ‘potentiated up’ and respiratory chain and cytochrome-c oxidase activity and nitrate metabolic process in the genes ‘potentiated down’ (Supplementary Data File S2). With the exception of promoter proximal SCO5921, the other three genes of the major cold-shock operon are potentiated reflecting their crucial role in the cold-shock response. Buffered genes In the 61 genes following this pattern of transcriptional and translational regulation going in opposite trends, STRING analysis identified one GO term (GO:0008270) as significantly enriched: zinc ion binding (false discovery rate: 0.0219) Some of these genes are involved in translation such as SCO7600 encoding a possible alanyl tRNA synthetase and SCO6149 encoding a putative ATP GTP-binding protein which assists together with other proteins the late maturation steps of the ribosomal 30S subunit. SCO1321 encodes the translation elongation factor TU-3. SC07600, encoding a putative alanyl-tRNA synthetase (AlaS2), is transcriptionally enhanced but translationally repressed. SCO7600 is part of the WblC regulon which controls many genes involved in translation, promoting translation during antibiotic stress ( Lee et al., 2020 ). SCO6720 , encoding a probable ABC transporter and SCO7600 are well conserved and cooccurrence has been observed across all Bacteria, Eukaryota and Archaea. The cmlR2 chloramphenicol resistance encoding gene, SCO7662, is transcriptionally induced but translationally repressed Forwarded genes A total of 2,299 genes displayed an upward trend in transcription and translation, with no change in TE (Supplementary Data File S2). Exclusive genes Exclusively translationally enhanced genes (polysome associated transcripts with no change in transcription) were identified as significantly changed at the translation level following cold shock (952 genes). One biological process was found to be significantly enriched in the STRING Functional analysis, Protein phosphorylation (GO:0006468; false discovery rate, 0.0338). This finding is consistent with the requirement for a rapid post-transcriptional response following a sudden down-shift in temperature. In contrast exclusively translationally repressed genes were identified as significantly reduced at the translation level but not transcriptional level following cold shock (1,119 genes). These include the glutamine synthetase-encoding gene SCO2198 and the glycine cleavage system (Supplementary Data File S2). The glycine cleavage system (including SCO1378 ( gcvP )) is conserved across all three domains of life. Whilst it forms part of many proteins, glycine can be cytotoxic as it can replace alanine in glycoproteins that form the cell wall and its concentration in the cell must therefore be closely controlled, and the glycine cleavage system plays a role in its regulation ( Tezuka et al., 2014 ). The gene pair SCO0630-SCO0631 is conserved across Actinobacteria and SCO0630 is predicted to encode an acetyl transferase. Several key biological processes were enriched in the STRING Functional analysis: KEGG Pathways Oxidative phosphorylation (sco00190 FDR 1.68 e-05, Metabolic pathways (sco01100 FDR 3.17 e-10, Biosynthesis of secondary metabolites (sco01110 FDR 6.19 e-06), Carbon metabolism (sco01200 FDR 0.00029), Biosynthesis of amino acids (sco01230 FDR 0.00067) (Supplementary Figure S1a). Selected translationally enhanced genes In the group of potentiated genes, the gene pair SCO0818 and SCO0819 , encoding an ABC transporter ATP-binding protein and a transmembrane protein, respectively, are transcribed as an operon. SCO0818 is highly conserved across all domains of life, while SCO0819 is restricted to Actinobacteria and three other bacterial groups. The physiological role of this gene pair is unclear but is predicted to be important to cold-shock adaptation. SCO4640 , encoding the highly cold-shock induced transcription factor ( Fig 6 ), is also potentiated, reflecting its importance in the cold-shock response. SCO4124 (‘exclusive up’) encodes a probable two component system sensor kinase (DesK homologue of B. subtilis ) and SCO2216 (‘exclusive up’) the associated response regulator (DesR homologue). These two genes are highly conserved and co-expressed in the genomes of most bacterial groups and the putative homologues of the DesR/K system are probably responsible for cold-induction of the des gene (encoding Delta 5 acyl-lipid desaturase). The system acts as a sensor of membrane fluidity ( Cybulski et al., 2004 ), and is probably activated by DesR via phosphorylation. It is expected that this potentiated gene pair fulfils an equivalent role in Streptomyces under cold-shock conditions. The three operonic genes, SCO4584-SCO4586 are all potentiated and encode an ABC transporter complex. SCO7748 , SCO7749 and SCO7750 (‘potentiated up’) encode hypothetical proteins, with SCO7750 specifying a putative anti-anti sigma factor and SCO7748 encoding an RsbU homologue, encoding a serine phosphatase; SCO7748 and SCO7750 represent a highly conserved gene pair among the prokaryotic domains. Importantly B. subtilis RsbU forms part of the ‘stressosome’ where RsbR acts as a positive and negative regulator of sigma-B activity ( Reeves & Haldenwang, 2007 ). SCO7050 (‘potentiated up’) encodes D-Ala-D-Ala carboxypeptidase and SCO3830 (BkdB2) (‘potentiated up’) encodes a probable branched chain alpha keto acid dehydrogenase subunit. The potentiated gene, SCO2927 encodes a putative 4-hydroxyphenyl pyruvate dioxygenase (HppD) that is central to catabolism of tyrosine, providing key components of the TCA cycle, fumarate and acetoacetate ( Yang et al (2007) . Tyrosine catabolism provides nitrogen, carbon and energy substrates crucial for growth. The gene, SCO4928 (‘exclusive up’), encodes adenylate cyclase and is likely to play an important role in the signal transduction response to cold-shock. SCO3956 and SCO3959 , the first and last genes of a four-gene operon are ‘potentiated up’. They encode components of an ABC transporter complex that mediates S-adenosylmethionine (SAM) signal transduction ( Lee at., 2012 ). The first two genes of the operon are also transcriptionally induced following cold shock. Conclusions In this study we have determined the experimental conditions to elicit the cold-shock response in Streptomyces . In contrast to the streptomycete heat-shock response, the cold shock response is principally regulated at the transcriptional level. Functional enrichment of four main categories were identified: transcription regulation, helicase activity, phenylalanine metabolism and extracellular functions. Approximately 10% of transcripts were significantly DE following cold-shock. Three cold-shock operons encoding CspA homologues and DEAD box helicases were massively induced at the transcriptional level. Three previously undescribed cold-shock induced transcription factors were identified ( SCO1568 , SCO4540 and SCO7014 ). Highly conserved motifs were identified upstream from the three cold shock-induced operons and a highly conserved large stem-loop was identified downstream from the CspA-encoding homologues, SCO4684 and SCO5921 ; further experiments are required to determine the roles of these respective sequences in transcriptional and translational control of the cold-shock response. The most strikingly potentiated genes are contained within the SCO5921-SCO5918 operon underlining its crucial role in acclimation following cold-shock. Since the helicase encoding genes are transcriptionally induced up to 2,000-fold, the control systems governing this scale of response could potentially be harnessed in synthetic biology applications. This study underlines the critical importance of RNA helicase activity in maintaining RNA structure to enable fundamental cellular processes to continue under low temperatures. This is particularly relevant in organisms like streptomycetes, with such extreme G+C content (>80% G+C) in their protein coding sequences This study has identified novel genes in the Streptomyces response to cold-shock. For example the gene pair, SCO0818 and SCO0819 , encoding an ABC transporter ATP-binding protein and a transmembrane protein, are predicted to have an important physiological role in cold-shock adaptation. DATA AVAILABILITY The gene expression data underpinning this article are available from NCBI’s Gene Expression Omnibus at https://www.ncbi.nlm.nih.gov/geo and can be accessed with the following accession numbers: GSE225850 and GSE229820. FUNDING This work was generously supported by Michael and Maureen Chowen and the University of Brighton. RTE also contributed financially to research costs and provided funding for open access charges. CONFLICT OF INTEREST STATEMENT None declared. A Supplementary files Supplementary Data File S1: Oligonucleotides designed for depleting rRNAs and selected non-coding RNAs. Filename: Supplementary Data File S1 (Word format) Note : for each Excel spreadsheet a README sheet is included with an explanatory key for each column. Supplementary Data File S2: p.GSE229820.combined.rna_v_ps.xlsx Supplementary Data File S3: p.Heatmap.GSE225850_clusters.xlsx Supplementary Data File S4: DESeq2_SMM_GSE225850_GSE229820.xlsx Supplementary Data File S5: p.ORA.genes.GSE225850.xlsx Supplementary Data File S6: Genes correlating with the three CS TFs GSE225850_reg_correlations.xlsx Supplementary Figure S1: Pathways downregulated following cold-shock. (a) KEGG pathways; (b) Biological Process (Gene Ontology) enrichment. Supplementary Figure S2: CS_Motif_4_sco motif in cold-shock induced genes (8 sites). ACKNOWLEDGEMENTS We are very grateful for the generous technical advice and support from Prof Byung-Kwan Cho and his group at KAIST (Republic of Korea), Dr Kenji Nakahigashi and Prof Hirotada Mori at NAIST (Japan) and Dr Rocio Martinez-Nunez from KCL (UK). Footnotes ↵ † This paper is dedicated to the memory of Professor David A. Hodgson REFERENCES ↵ Bailey , T. L. , Johnson , J. , Grant , C. E. , & Noble , W. S . ( 2015 ). The MEME Suite . Nucleic Acids Res , 43 ( W1 ), W39 – 49 . doi: 10.1093/nar/gkv416 OpenUrl CrossRef PubMed ↵ Bray , N. L. , Pimentel , H. , Melsted , P. , & Pachter , L . ( 2016 ). Near-optimal probabilistic RNA-seq quantification . Nat Biotechnol , 34 , 525 – 527 . doi: 10.1038/nbt.3519 OpenUrl CrossRef PubMed ↵ Bucca , G. , Pothi , R. , Hesketh , A. , Moller-Levet , C. , Hodgson , D. A. , Laing , E. E. , … Smith , C. P. ( 2018 ). Translational control plays an important role in the adaptive heat-shock response of Streptomyces coelicolor . 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