A small periplasmic protein governs broad physiological adaptations in Vibrio cholerae via regulation of the DbfRS two-component system

A small periplasmic protein governs broad physiological adaptations in Vibrio cholerae via regulation of the DbfRS two-component system | 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 A small periplasmic protein governs broad physiological adaptations in Vibrio cholerae via regulation of the DbfRS two-component system View ORCID Profile Emmy Nguyen , View ORCID Profile Charles Agbavor , Anjali Steenhaut , M R Pratyush , View ORCID Profile N. Luisa Hiller , View ORCID Profile Laty A. Cahoon , View ORCID Profile Irina V. Mikheyeva , View ORCID Profile Wai-Leung Ng , View ORCID Profile Andrew A. Bridges doi: https://doi.org/10.1101/2025.03.24.645060 Emmy Nguyen 1 Department of Biological Sciences, Carnegie Mellon University , Pittsburgh, PA 15213, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Emmy Nguyen Charles Agbavor 2 Department of Biological Sciences, University of Pittsburgh , Pittsburgh, PA 15260, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Charles Agbavor Anjali Steenhaut 3 Department of Molecular Biology and Microbiology, Tufts University School of Medicine , Boston, MA 02111, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site M R Pratyush 1 Department of Biological Sciences, Carnegie Mellon University , Pittsburgh, PA 15213, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site N. Luisa Hiller 1 Department of Biological Sciences, Carnegie Mellon University , Pittsburgh, PA 15213, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for N. Luisa Hiller Laty A. Cahoon 2 Department of Biological Sciences, University of Pittsburgh , Pittsburgh, PA 15260, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Laty A. Cahoon Irina V. Mikheyeva 1 Department of Biological Sciences, Carnegie Mellon University , Pittsburgh, PA 15213, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Irina V. Mikheyeva Wai-Leung Ng 3 Department of Molecular Biology and Microbiology, Tufts University School of Medicine , Boston, MA 02111, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Wai-Leung Ng Andrew A. Bridges 1 Department of Biological Sciences, Carnegie Mellon University , Pittsburgh, PA 15213, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Andrew A. Bridges For correspondence: bridges{at}cmu.edu Abstract Full Text Info/History Metrics Preview PDF Abstract Two-component signaling pathways allow bacteria to sense and respond to environmental changes, yet the sensory mechanisms of many remain poorly understood. In the pathogen Vibrio cholerae , the DbfRS two-component system controls the biofilm lifecycle, a critical process for environmental persistence and host colonization. Here, we identified DbfQ, a small periplasmic protein encoded adjacent to dbfRS , as a direct modulator of pathway activity. DbfQ directly binds the sensory domain of the histidine kinase DbfS, shifting it toward phosphatase activity and promoting biofilm dispersal. In contrast, outer membrane perturbations, caused by mutations in lipopolysaccharide biosynthesis genes or membrane-damaging antimicrobials, activate phosphorylation of the response regulator DbfR. Transcriptomic analyses reveal that DbfR phosphorylation leads to broad transcriptional changes spanning genes involved in biofilm formation, central metabolism, peptidoglycan synthesis, and cellular stress responses. Constitutive DbfR phosphorylation imposes severe fitness costs in an infection model, highlighting this pathway as a potential target for anti-infective therapeutics. We find that dbfQRS -like genetic modules are widely present across bacterial phyla, underscoring their broad relevance in bacterial physiology. Collectively, these findings establish DbfQ as a new class of periplasmic regulator that influences two-component signaling and bacterial adaptation. Introduction Microorganisms must adapt to environmental fluctuations to ensure their persistence. As a result, over evolution, bacteria have developed sophisticated sensory mechanisms that translate environmental signals into adaptive responses. Among these mechanisms, two-component systems (TCSs), which consist of a membrane-associated sensor histidine kinase and a cognate response regulator, are ubiquitous across the bacterial domain ( 1 , 2 ). Upon the detection of specific stimuli, histidine kinases modify the phosphorylation state of the response regulator which, in turn, orchestrates physiological changes, often through regulation of gene expression ( 3 – 5 ). The prevalence and diversity of TCSs in bacterial genomes is immense, with some individual species encoding as many as 200 distinct TCSs ( 6 ). Despite their pervasiveness, research into TCS molecular mechanisms has primarily concentrated on a handful of major TCS families ( 7 – 9 ). As a result, for most TCSs, the identities of their stimuli, mechanisms of signal transduction, and consequences to bacterial physiology remain underexplored. TCSs frequently control bacterial social behaviors, including regulation of the biofilm lifecycle, whereby bacteria form surface-associated, multicellular communities ( 10 – 13 ). In the biofilm state, bacterial cells are encased in a self-produced extracellular matrix that confers environmental protection against antimicrobials, immune responses, fluid flow, and bacteriophage predation ( 14 – 17 ). For these reasons, biofilms are notoriously difficult to eradicate in both clinical and industrial settings. Despite the adaptive benefits of the biofilm lifestyle, prolonged biofilm formation can be associated with bacterial fitness costs. Dense multicellular communities face competition for resources, their surface-associated characteristic limits spread to new territories, and extracellular matrix production diverts resources from metabolic processes ( 18 – 20 ). Consequently, bacteria have evolved intricate sensory mechanisms, often involving TCSs, to control the balance of biofilm formation and biofilm dispersal, whereby cells transition to the free-swimming state ( 21 – 23 ). For Vibrio cholerae , the causative agent of cholera disease, the biofilm lifecycle is thought to underlie its ability to transition between the aquatic niche and the human host ( 24 – 26 ). Moreover, transitions between bacterial niches are often mediated by TCSs, enabling host adaptation in facultative pathogens such as V. cholerae ( 27 – 29 ). In prior work, we identified a TCS, named DbfRS (encoded by vc_1638 and vc_1639 ), as a regulator of V. cholerae biofilm lifecycle transitions ( 30 ). Within this cascade, DbfS serves as the sensor histidine kinase that controls the phosphorylation state of the transcription factor DbfR ( Fig. 1A ). The balance between kinase and phosphatase activities of DbfS determines the phosphorylation state of DbfR, which in turn dictates whether cells commit to the biofilm state or disperse. Specifically, dephosphorylation of DbfR enables biofilm dispersal, whereas DbfR phosphorylation activates biofilm formation and represses dispersal via positive regulation of biofilm matrix gene expression ( Fig. 1A ). Beyond these basic findings, the DbfRS pathway remains uncharacterized - the environmental signal(s) controlling pathway activity remain unknown, the DbfR regulon is undefined, and its role during infection is unclear. Download figure Open in new tab Figure 1. DbfQ regulates the biofilm lifecycle via modulation of the DbfRS signaling cascade. (A) Initial model for DbfRS regulation of the biofilm lifecycle. OM = outer membrane, IM = inner membrane. Grey objects remain uncharacterized. (B) Top panel: Operon structure of the genes encoding the DbfRS pathway. The vc_1637 gene encoding a small hypothetical protein DbfQ is located directly upstream of dbfR and dbfS . Bottom panel: Domain architecture of DbfQ. (C) Quantification of biofilm biomass over time for WT V. cholerae, Δ dbfQ, and Δ dbfS mutants using time-lapse brightfield microscopy. Points represent averages of N = 2 biological replicates and 3 technical replicates, ± standard deviations (SD, shaded regions). (D) As in C for the Δ dbfS dbfR D51V and Δ dbfQ dbfR D51V strains. (E) Gene neighborhood analysis reveals a module of PepSY domain-containing protein(s) (green), histidine kinase (blue), and response regulator (magenta) genes encoded nearby in the genome. A selected set of species associated with human infections or agriculture is shown. F) Phos-tag analysis of DbfR-SNAP in-gel fluorescence in the presence (+) and absence (Δ) of dbfS and dbfQ . (G) Quantification of P dbfQRS -lux reporter activity for the indicated strains. Data are presented as mean ± SD of peak relative light units (RLU, defined as lux /OD 600 ) normalized to the average peak value of WT. Points represent individual replicates of N = 2 biological replicates and 3 technical replicates. In this study, we comprehensively investigated the DbfRS regulatory network, defining its sensory inputs, physiological outputs, and fitness consequences. We identified a previously uncharacterized small protein, DbfQ, that directly interacts with and modulates the sensory domain of DbfS, driving the receptor toward phosphatase activity. We find that outer membrane stresses activate the DbfQRS pathway and that DbfR phosphorylation leads to global transcriptional changes, coordinating biofilm commitment and peptidoglycan maintenance with reduced metabolic activity. Activation of the DbfQRS pathway is detrimental to bacterial colonization in an animal model of infection, highlighting the potential of this pathway as a therapeutic target for limiting the spread of V. cholerae . Finally, the widespread occurrence of dbfQRS -like genetic modules, including in other important pathogens, underscores the broader relevance of this novel regulatory mechanism. Results A small protein controls the biofilm lifecycle via regulation of the DbfRS signaling cascade For many bacterial TCSs, the genes encoding response regulator and histidine kinase pairs commonly exist within the same operon. Examination of the dbfRS operon revealed a third gene, herein referred to as dbfQ , encoded immediately upstream and predicted to be co-transcribed with dbfRS ( Fig. 1B ) ( 31 ). Given its presumed co-regulation, we wondered whether DbfQ could participate in regulating the biofilm lifecycle via the DbfRS signaling pathway. dbfQ encodes a 135-amino-acid protein with a predicted N-terminal secretion signal (Sec/SPI) ( 32 ). The predicted mature ∼12kDa protein harbors a single Pfam domain, annotated as PepSY (residues 74 to 122) ( 33 ). Several studies have implicated PepSY domains in metal binding and/or protease inhibition ( 34 , 35 ), though the exact role of this motif is unclear. To determine whether DbfQ modulates the biofilm lifecycle, we constructed an in-frame deletion of dbfQ . Similar to the Δ dbfS mutant, the Δ dbfQ strain exhibited enhanced biofilm formation and a defect in biofilm dispersal, with substantial biofilm biomass remaining at the final timepoint ( Fig. 1C ). Both mutants also exhibited a growth defect compared to wild-type (WT) ( Fig. S1A ). Complementation of the Δ dbfQ mutant by introducing P tac - dbfQ at a neutral locus restored the biofilm lifecycle and growth rate to that of WT ( Fig. S1B-E ). To determine whether DbfQ controls the biofilm lifecycle via the DbfRS cascade, we introduced the Δ dbfQ deletion into a strain harboring a non-phosphorylatable allele of dbfR ( dbfR D51V ), rendering it unresponsive to DbfS activity. We found that the Δ dbfQ dbfR D51V double mutant did not exhibit the altered biofilm phenotype measured for the Δ dbfQ mutant ( Fig. 1D ), supporting a model in which DbfQ regulates biofilm dynamics through the DbfRS signaling pathway, presumably by modulating DbfS activity. Download figure Open in new tab Figure S1: Δ dbfQ and Δ dbfS growth curves and complementation. (A) Growth curves of WT V. cholerae compared to the Δ dbfQ and Δ dbfS mutant strains as measured by OD 600 . (B) Quantification of biofilm biomass over time using time-lapse brightfield microscopy for WT, Δ dbfQ , and Δ dbfQ P tac - dbfQ expressed from an ectopic locus ( vc_1807 ). (C) As in B for WT, Δ dbfS , and the Δ dbfS P tac - dbfS complemented strain. (D) As in A for WT, Δ dbfQ , and Δ dbfQ P tac - dbfQ complemented strain. (E) For all panels, points represent averages of N = 2 biological replicates and 3 technical replicates, ± SD (shaded regions). Bacterial TCSs show a broad range of conservation, with some TCSs exhibiting a high degree of similarity across diverse taxa, whereas others are present only in specific lineages ( 36 ). Given this understanding, we wondered whether DbfQ-like proteins encoded adjacent to TCSs are widespread. To investigate the pervasiveness of the DbfQRS module, we conducted a bioinformatic search for gene neighborhoods in which a small PepSY domain-containing protein was encoded in the vicinity of a histidine kinase or response regulator (vicinity was defined as within four genes). We found that such gene neighborhoods were present across multiple bacterial phyla, with a large representation of Proteobacteria as well as instances in Terrabacteria and Fusobacteria ( Fig. 1E , Fig. S2 ). Indeed, the observed frequency of a PepSY-domain protein encoded in proximity to a TCS was >60-fold higher than expected by chance (see Methods). Notably, DbfQRS-like modules are present in numerous bacteria associated with human infections and agriculture ( Fig. 1E ). The organization of these genetic modules varied with, in some cases, two DbfQ-like proteins encoded upstream of the TCS (e.g. Pseudomonas aeruginosa ) ( Fig. 1E ). In other cases, PepSY-protein and TCS genes were adjacent but encoded on opposite strands (e.g. Burkholderia pseudomallei ) ( Fig. 1E ). Collectively, these findings show that DbfQRS-like genetic modules are widespread, suggestive of a potentially conserved regulatory principle at play across diverse bacteria. Download figure Open in new tab Figure S2: Representative taxa encoding a PepSY domain-containing protein and a response regulator or histidine kinase within a 4-gene vicinity. All taxa (phyla, classes and orders) that have a representation of 0.8% or higher are shown. Phyla are arranged from top to bottom by order of representation. A wide range of bacterial taxa encodes this module, with a large representation of γ-, α- and β-proteobacteria, actinobacteria, firmicutes, and a smaller representation of fusobacteria. Given the dramatic effect of DbfQ on the biofilm lifecycle of V. cholerae , combined with the widespread presence of DbfQRS modules, we sought to determine the molecular mechanisms by which DbfQ impinges upon the TCS. Prior work demonstrated that DbfS functions as a phosphatase under laboratory growth conditions, permitting biofilm dispersal ( 30 ). In the Δ dbfS mutant, DbfR is phosphorylated by an unidentified kinase or small molecule phosphate donor, leading to increased biofilm formation and inhibited dispersal. We set out to confirm this relationship using Phos-tag gel analysis, where more negatively charged, phosphorylated species migrate slower than the dephosphorylated form. Consistent with earlier findings, in the absence of dbfS , a distinct second, slower-migrating band corresponding to phosphorylated DbfR was detected ( Fig. 1F ). As histidine kinases typically switch between kinase and phosphatase modes depending on the ligand occupancy of their sensory domains, we reasoned that DbfQ could influence the balance between these catalytic activities of DbfS. To test this possibility, we examined DbfR phosphorylation in the Δ dbfQ mutant strain and observed complete phosphorylation of the DbfR response regulator ( Fig. 1F ). In contrast, the Δ dbfQ Δ dbfS double mutant phenocopied the Δ dbfS single mutant, demonstrating that DbfQ controls DbfR phosphorylation, and in turn the biofilm lifecycle, by modulating the kinase-phosphatase equilibrium of DbfS. Because DbfR is phosphorylated in the absence of DbfQ, our results suggest that DbfQ biases DbfS towards phosphatase activity. Together, these results demonstrate that DbfQ acts as a key regulator of the DbfRS signaling cascade, impinging on the biofilm lifecycle by controlling the activity of the DbfS receptor. To establish a quantitative readout of DbfQRS signal transduction, we set out to generate a luminescent reporter for pathway activity. During Phos-tag analysis ( Fig. 1F ), we noticed that increased DbfR phosphorylation appeared to correlate with elevated DbfR levels, suggestive of positive autoregulation of the dbfQRS operon, a common feature of bacterial TCSs ( 3 ). Thus, to generate a luminescent reporter for DbfR phosphorylation, we fused the dbfQRS promoter to luciferase (P dbfQRS -lux ). To validate the reporter, we first measured luminescence in the Δ dbfS and Δ dbfQ mutants which, as shown above, exhibit elevated DbfR phosphorylation ( Fig. 1F ). Both mutants displayed a ∼40-fold increase in luminescence compared to the WT strain ( Fig. 1G ). Moreover, introduction of the phospho-dead dbfR D51V allele into the Δ dbfS and Δ dbfQ mutant backgrounds reduced light production to below that of WT, demonstrating that P dbfQRS -lux reports on DbfR phosphorylation state. DbfQ directly interacts with the sensory domain of DbfS The genetic results presented above indicate that DbfQ promotes DbfS phosphatase activity. We reasoned that DbfQ could directly interact with the DbfS receptor to modulate its activity. To investigate this possibility, we first examined DbfQ localization. As noted above, DbfQ contains a predicted N-terminal secretion signal and predicted Sec/SPI cleavage site, suggestive of secretion into the periplasm, where it could modulate the periplasmic sensory domain of DbfS. To determine DbfQ localization, we fused DbfQ to mNeonGreen (mNG) and performed confocal microscopy. While endogenously tagged DbfQ was undetectable due to low expression levels, overexpression of DbfQ-mNG revealed localization at the cell periphery, consistent with potential periplasmic localization ( Fig. 2A ). In contrast, an in-frame deletion of the predicted secretion signal of DbfQ ( dbfQ Δsec -mNG ) resulted in DbfQ retention in the cytoplasm ( Fig. 2A ), suggesting that the secretion signal is essential for DbfQ localization. To assess whether DbfQ secretion is required for pathway function, we examined P dbfQRS -lux output in the dbfQ Δ sec background and observed a >15-fold activation of light production ( Fig. 2B ), indicating that mislocalization of DbfQ results in increased DbfR phosphorylation. We next interrogated the role of DbfQ secretion signal cleavage by introducing bulky aromatic sidechain substitutions at the predicted cleavage residue A31 (A31Y and A31W), a strategy that, for other proteins, has been shown to inhibit processing by Signal Peptidase I ( 37 – 39 ). Western blot of the WT DbfQ-3xFLAG yielded a ∼17kDa band corresponding to the expected size of cleaved DbfQ-3xFLAG ( Fig. 2C ). In contrast, the DbfQ A31W -3xFLAG and DbfQ A31Y -3xFLAG exhibited higher molecular weight products consistent with the uncleaved, full-length DbfQ ( Fig. 2C ). The dbfQ A31W and dbfQ A31Y cleavage mutants exhibited 12- and 8-fold increases in P dbfQRS -lux reporter activity, respectively, compared to WT ( Fig. 2B ). Therefore, periplasmic localization and processing of DbfQ is required for its regulatory effect on DbfS activity, and consequently, on DbfR phosphorylation state. Download figure Open in new tab Figure 2. DbfQ directly interacts with the sensory domain of DbfS. (A) Left: Representative confocal microscopy images of DbfQ-mNG in V. cholerae expressed from an ectopic locus. Right: As in left panel, except the secretion signal of DbfQ has been removed ( dbfQ Δsec -mNG). (B) Quantification of P dbfQRS - lux reporter activity for secretion and cleavage mutants. Data are presented as mean ± SD of peak RLU normalized to the average peak value of WT. Points represent individual replicates of N = 2 biological replicates and 3 technical replicates. (C) Western blot analysis of the FLAG-tagged WT DbfQ (cleaved) and the cleavage site mutants DbfQ A31W and DbfQ A31Y . Data are representative of N = 3 biological replicates. (D) Structure of AlphaFold3 predicted interaction between cleaved DbfQ (green) and full-length DbfS (blue), with an ipTM = 0.69. Critical domains of DbfS including sensory, transmembrane (TM), and kinase/phosphatase domains are labeled. (E) SDS-PAGE results of a Ni-NTA pull-down assay between purified DbfQ and the DbfS SD -6xHis. Data are representative of N = 3 independent experiments. (F) MST dose-response curve used to measure the DbfQ and DbfS SD interaction. DbfQ was covalently labeled with an amine-reactive Red-NHS dye and subsequently titrated against increasing concentrations of unlabeled DbfS while changes in thermophoretic behavior were monitored. Normalized fluorescence (F n ) results were fit with a one-site binding model (95% confidence interval), yielding a dissociation constant of 30 nM [10, 70] [Lower Limit, Upper Limit]. Data are presented as mean ± SD of N = 4 independent replicates. (G) Proposed model for the DbfQRS signaling pathway. OM = outer membrane, IM = inner membrane. The periplasmic co-localization of DbfQ and the sensory domain of DbfS suggests that DbfQ could directly bind to DbfS to control its output activity. To explore this possibility, we first utilized AlphaFold3, which predicted an interaction between DbfQ and the DbfS sensory domain, with an interface predicted template modeling (ipTM) score of 0.69, a relatively high-confidence value ( Fig. 2D ). To validate this prediction, we recombinantly expressed and purified DbfQ and the DbfS sensory domain (DbfS SD -6xHis) for pull-down assays ( Fig. S3A ). When supplied alone, DbfQ, which lacked the affinity tag, displayed no binding to Ni-NTA resin, whereas DbfS SD -6xHis was bound and subsequently eluted. However, when the two proteins were pre-mixed, DbfQ co-eluted as a complex with DbfS SD -6xHis, confirming a direct interaction ( Fig. 2E ). To measure binding affinity and stoichiometry, we performed microscale thermophoresis (MST). This approach revealed a high-affinity interaction between DbfQ and DbfS, with a dissociation constant (K d ) of 30 nM ( Fig. 2F ). To determine the stoichiometry of the DbfQ-DbfS interaction, the thermophoretic behavior of labeled DbfQ and unlabeled DbfS was probed using a titration to saturation experiment ( 40 ), which indicates a 1:1 stoichiometry between DbfQ and DbfS ( Fig. S3B ). Collectively, these computational and experimental results establish that DbfQ controls the activity of DbfS via a direct, high-affinity interaction in the periplasm. Combined with our genetic results, we infer that DbfQ binding to DbfS biases the receptor towards phosphatase activity, driving dephosphorylation of DbfR and enabling biofilm dispersal ( Fig. 2G ). Download figure Open in new tab Figure S3: DbfQ and DbfS SD purification and binding stoichiometry (A) Representative SDS-PAGE gel analyses of DbfQ-6xHis and DbfS SD -6xHis protein purifications. The 6xHis tag of DbfQ was removed by thrombin cleavage for pull-down assays. (B) Microscale thermophoresis signals of labeled DbfQ titrated against narrow increasing concentrations of DbfS SD . Dashed lines show the saturation point (“kink”) of the data representing the occupancy of the DbfQ on its receptor, DbfS SD , with an apparent binding ratio of 1:1. Data are presented as relative thermophoresis values ± SD of N = 4 independent measurements. DbfQRS activity is sensitive to changes in membrane integrity A longstanding challenge involving studies of novel bacterial TCSs is identifying the signal(s) that modulate pathway activities. Some TCSs are known to respond to exogenous stimuli, such as nutrients, metals, or host-derived factors ( 41 – 43 ), while others integrate self-produced or intrinsic cues including quorum sensing autoinducers or cell envelope stress ( 44 – 47 ). The P. aeruginosa DbfS ortholog, BqsS, was previously shown to be iron-responsive ( 48 ), however, we found that supplementation of Fe(II) or Fe(III) did not alter P dbfQRS -lux reporter output in V. cholerae ( Fig. S4A ). Given the tremendous number of potential exogenous inputs, we decided to focus on identifying any intrinsic factors that modulate DbfQRS activity. We reasoned that such factors could be identified using a transposon mutagenesis approach while monitoring P dbfQRS -lux reporter activity. Since DbfS exhibits basal phosphatase activity under our laboratory conditions, we sought to identify mutations that increased P dbfQRS -lux output, reflective of elevated DbfR phosphorylation. Screening of ∼20,000 Tn5 mutagenized colonies yielded 54 isolates exhibiting elevated luminescence, which, after sequencing, mapped to 23 loci spanning eight functional categories ( Table 1 , Table S1 , and Fig. S4B ). Among the hits, the identification of dbfQ ::Tn 5 and dbfS ::Tn 5 validated our screening strategy, as these mutants display increased DbfR phosphorylation ( Fig. 1F, G ). Strikingly, the largest category of hits (∼35%) mapped to genes predicted to be involved in lipopolysaccharide (LPS) biosynthesis. Defects in LPS biosynthesis can profoundly affect the cell envelope by increasing membrane permeability, altering membrane protein expression, and affecting susceptibility to antibiotics ( 49 – 51 ). Consistent with our findings, previous work implicated vc_1639 ( dbfS ) in resistance to polymyxin B ( 52 ), a cationic antimicrobial peptide that disrupts the LPS network and destabilizes the outer membrane. These results suggest a relationship between membrane integrity and DbfQRS pathway activity. To validate this relationship, we first constructed an in-frame deletion of wavA ( vc_0223 ), the first gene in the LPS core-polysaccharide biosynthesis cluster, which was previously reported to result in truncated LPS lacking O-antigen attachment ( 53 , 54 ). The Δ wavA mutant exhibited a nearly 5-fold increase in luminescence compared to WT strain, consistent with elevated DbfR phosphorylation ( Fig. 3A ). Introducing the phospho-dead dbfR D51V allele into Δ wavA background suppressed light production to below that of WT, confirming that modifications in LPS enhance pathway activation specifically via DbfR phosphorylation, and not via parallel transcriptional control of the dbfQRS promoter. To further substantiate the link between membrane stress and DbfQRS activation, we treated WT cells with sub-lethal concentrations of the membrane-targeting antibiotic polymyxin B and measured P dbfQRS -lux reporter output. This treatment led to a dose-dependent increase in luminescence, reaching a maximum of 6-fold induction at the highest concentration tested ( Fig. 3B ). Similarly, exposure to thymol, an antimicrobial compound known to disrupt membrane integrity ( 55 ), produced up to an 8-fold increase in luminescence ( Fig. 3C ). In contrast, the dbfR D51V strain failed to induce light production under either treatment, demonstrating that DbfR phosphorylation is a direct readout of outer membrane stress. Possible mechanisms through which the DbfQRS pathway senses outer membrane damage are numerous, including that DbfQ or DbfS senses some characteristic of envelope stress that modulates their interaction. Defining the precise mechanism underlying this response will be the topic of future work. Download figure Open in new tab Figure S4: Identification of activators of the DbfQRS pathway. (A) P dbfQRS -lux reporter activity in WT and dbfR D51V strains measured in the presence of 100 μM Fe(II) or Fe(III). Data are presented as mean ± SD of peak RLU normalized to the average peak value of WT. Points represent individual replicates of 3 biological replicates. (B) Transposon mutagenesis screen for P dbfQRS -lux reporter activation. Visual screening of ∼20,000 colonies yielded 232 colonies with elevated luminescence compared to the parent strain. Luminescence outputs (relative light units, RLU) for these strains were subsequently quantified using a Biotek Cytation1 plate reader and normalized to the WT parental strain (normalized RLU = 1). The scatter plot shows the normalized RLU values for all 232 colonies, with a red solid line indicating a three-fold increase in RLUs. A total of 54 colonies exceeding this threshold were selected for transposon insertion site sequencing. View this table: View inline View popup Download powerpoint Table S1. List of transposon mutagenized genes resulting in elevated P dbfQRS -lux activity. View this table: View inline View popup Download powerpoint Table S2: Gene disruptions identified as suppressing Δ dbfS colony rugosity. View this table: View inline View popup Table S3: Strains used in this study View this table: View inline View popup Table S4: DNA oligonucleotides and gene fragments used in this study. Download figure Open in new tab Figure 3. DbfQRS activity is sensitive to membrane disruption. (A) Quantification of P dbfQRS -lux reporter activity for the indicated strains. Data are presented as mean ± SD of peak RLU normalized to the average peak value of WT. Points represent individual replicates of N = 2 biological replicates and 3 technical replicates. (B) As in A for the indicated strains under polymyxin B treatment. (C) As in A for the indicated strains under thymol treatment. View this table: View inline View popup Download powerpoint Table 1: Functional distribution of transposon mutagenized genes with increased DbfQRS activity The DbfQRS pathway activates biofilm formation while downregulating metabolic processes Our next goal was to characterize the effects of DbfQRS signaling on downstream gene expression. To define the DbfR regulon, we performed RNA sequencing under conditions where DbfR was either constitutively dephosphorylated or phosphorylated. We began by comparing the transcriptome of WT V. cholerae to the phospho-dead dbfR D51V strain. This strain displayed modest transcriptional changes, with 54 genes exhibiting differential expression (Log 2 FC > ± 1.0 and P -value < 0.05) ( Fig. S5A , Dataset S1). In contrast, when DbfR was phosphorylated (using the Δ dbfS mutant strain), we observed a dramatic shift in gene expression, with 12% of genomic loci ( N = 540 genes) exhibiting differential expression ( Fig. 4A , Dataset S2). These results confirm that DbfR phosphorylation drives large-scale transcriptional reprogramming. As expected, the Δ dbfQ mutant, which also exhibits elevated DbfR phosphorylation ( Fig. 1F, G ), displayed a similar transcriptional profile to the Δ dbfS strain (R = 0.93) ( Fig. 4B , Fig. S5B and Dataset S3). Download figure Open in new tab Figure S5: RNA sequencing results for dbfR D51V and Δ dbfQ strains. (A) Volcano plot comparing fold changes and P-values for gene expression in the dbfR D51V V. cholerae strain compared to WT. vps and motility genes are colored in orange and blue, respectively. The horizontal dotted line represents a -Log 10 P-value of 0.05 and left and right vertical dashed lines represent Log 2 fold changes of −1 and 1, respectively. Samples were collected at OD 600 = 0.1 and N = 3 biological replicates for each strain. Complete datasets are available in Dataset S1. (B) As in A, for the Δ dbfQ strain compared to WT. Complete datasets are available in Dataset S3. Download figure Open in new tab Figure 4. The DbfQRS pathway regulates the expression of metabolic and lifestyle genes. (A) Volcano plot comparing fold changes and P -values for gene expression in the Δ dbfS V. cholerae strain compared to WT. vps and motility genes are highlighted in orange and cyan, respectively. The horizontal dotted line represents a -Log 10 P -value of 0.05, and left and right vertical dashed lines represent Log 2 fold changes of −1 and 1, respectively. Samples were collected at OD 600 = 0.1 and N = 3 biological replicates for each strain. Complete datasets are available in Dataset S2. (B) Comparison of Log 2 fold changes in gene expression for the Δ dbfS and Δ dbfQ mutants. r = Pearson’s correlation coefficient. Complete datasets are available in Dataset S2 and S3. (C) Significantly enriched KEGG pathways ( P < 0.05) in the Δ dbfS mutant strain. Differentially regulated genes (false discovery rate < 0.05) were assigned to pathways using the “kegga” functionality in limma R package ( 56 ). Red bars represent upregulated pathways, and blue bars represent downregulated pathways. (D) Motility zone measurement for the indicated strains after 10 hours of incubation. Points represent individual replicates of N = 6 biological replicates. Statistical analyses were performed using unpaired, two-sample t-tests with a 95% confidence interval (****, P < 0.0001; ns, not significant). To gain functional insights into the genes regulated by phospho-DbfR, we performed a KEGG pathway enrichment analysis. This analysis revealed significant downregulation of genes involved in central metabolic pathways, including the tricarboxylic acid (TCA) cycle and oxidative phosphorylation, as well as genes implicated in purine/pyrimidine metabolism, amino acid metabolism, and the biosynthesis of secondary metabolites ( Fig. 4C , Dataset S4). These results are consistent with our finding that the Δ dbfS and Δ dbfQ mutants exhibited a reduced growth rate compared to WT ( Fig. S1A ). Beyond metabolic changes, genes involved in flagellar assembly were also downregulated under phospho-DbfR conditions, suggesting that the pathway controls motility in addition to biofilm formation ( Fig. 4A, D ). Soft-agar motility assays confirmed that both Δ dbfS and Δ dbfQ strains exhibited significantly decreased motility compared to WT, though not to the extent of the Δ flaA mutant lacking the major flagellin subunit ( Fig. 4D and Fig. S6 ). On the other hand, significantly upregulated pathways in the Δ dbfS and Δ dbfQ transcriptomes included genes encoding vibrio exopolysaccharide ( vps ) biofilm matrix components, peptidoglycan biosynthesis, and mismatch repair proteins ( Fig. 4A, C ). Collectively, these results suggest that DbfR activation biases V. cholerae towards a sessile biofilm state, while simultaneously slowing growth by reducing metabolic processes. We propose that entering this state could prepare cells for environmental challenges. Download figure Open in new tab Figure S6: Motility assay for V. cholerae strains on soft agar plate (LB media, 0.3% agar) . Representative image was captured after 10 hours of growth at 37° C. Results are representative of those from N = 6 biological replicates. DbfR phosphorylation drives biofilm formation by increasing c-di-GMP levels The simultaneous upregulation of vps gene expression and downregulation of motility factors observed in our transcriptomic analysis could be manifested by changes in cyclic dimeric GMP (c-di-GMP) levels. C-di-GMP is a widespread bacterial second messenger molecule which controls motile-to-sessile transitions by repressing motility and promoting biofilm matrix production in V. cholerae and other organisms ( 57 ). To assess intracellular c-di-GMP levels under phospho-DbfR conditions, we introduced an established riboswitch-based c-di-GMP fluorescence reporter into the Δ dbfS mutant ( 58 , 59 ). Reporter output in this strain was ∼40% higher than in WT, confirming that DbfR phosphorylation is associated with elevated intracellular c-di-GMP levels ( Fig. 5A ). Intracellular c-di-GMP levels are regulated by opposing enzymatic activities: diguanylate cyclases synthesize c-di-GMP via GGDEF domains, while phosphodiesterases degrade c-di-GMP through EAL or HD-GYP domains ( 60 , 61 ). Of note, V. cholerae encodes 62 such c-di-GMP metabolic enzymes ( 62 ), raising the question of which specific enzyme(s) drive the observed c-di-GMP increase upon DbfR phosphorylation. Examination of RNA-sequencing results was not particularly revealing, as widespread changes in the expression of c-di-GMP-metabolizing enzymes were observed in the Δ dbfS mutant ( Fig. 5B , Dataset S2). Download figure Open in new tab Figure 5. DbfR phosphorylation drives increased c-di-GMP levels via upregulation of cdgL . (A) Relative c-di-GMP reporter output for the WT and Δ dbfS strains, expressed as the mean ± SD of percentage difference relative to the WT control. Points represent individual replicates of N = 2 biological replicates and 3 technical replicates. Statistical analyses were performed using unpaired, two-sample t-tests with a 95% confidence interval (****, P < 0.0001). (B) Heatmap of RNAseq results for c-di-GMP metabolizing enzymes in the indicated strains. Genes are grouped by the presence of GGDEF domain (diguanylate cyclase), EAL or HD-GYP domains (phosphodiesterase), or multiple catalytic domains, potentially representing bifunctionality. Color bar represents Log 2 fold changes. VC_2285 ( cdgL ) is bolded for ease of identification. (C) Stereomicroscope images of WT and Δ dbfS colony morphologies. (D) Left: Schematic of mutagenesis screen. Middle: Hit frequency for genes in the vps-I and vps-II operons. Right panel: Hit frequency for selected regulators of biofilm formation. All screen hits are reported in Table S2. (E) Quantification of biofilm biomass for WT, Δ dbfS , and Δ dbfS Δ cdgL strains using time-lapse brightfield microscopy. Points represent averages of N = 2 biological replicates and 3 technical replicates, ± SD (shaded regions). (F) As in A for the Δ cdgL and Δ dbfS Δ cdgL double mutant. Reporter output is normalized to the Δ cdgL strain. To pinpoint the critical enzyme(s) responsible for elevated c-di-GMP in the Δ dbfS background, we pursued an unbiased mutagenesis screen that exploits the distinctive colony morphology of the Δ dbfS mutant. This strain exhibits a wrinkled, “rugose” phenotype consistent with elevated biofilm matrix production, thereby providing a clear phenotypic readout for its hyper-biofilm formation ( Fig. 5C ). We mutagenized the Δ dbfS strain with the Tn 5 transposase, screened ∼20,000 colonies and identified 183 suppressor mutants exhibiting a smooth colony morphology. Sequencing these mutants revealed that 81% harbored disruptions in vps genes (Table S2) within the biofilm matrix operons, confirming that the rugose to smooth phenotypic transition reflects loss of biofilm matrix production ( Fig. 5D , Left). Each vps gene was disrupted ∼8 times on average, validating the comprehensiveness of our screen ( Fig. 5D , Middle). We also identified other established biofilm regulators, including the master biofilm transcription factors vpsR and vpsT , the quorum-sensing regulator luxO , and the alternative sigma factor rpoN ( Fig. 5D , Right). Most notably, a single c-di-GMP metabolizing enzyme, cdgL ( vc_2285 ), emerged from the screen. This diguanylate cyclase also appeared as the most highly upregulated c-di-GMP metabolizing enzyme in our Δ dbfS transcriptomic dataset ( Fig. 5B ), suggesting it could mediate elevated c-di-GMP upon DbfR phosphorylation. To test this possibility, we deleted cdgL in the Δ dbfS background, which reduced peak biofilm formation to below that of WT, and restored biofilm dispersal, demonstrating that CdgL is essential for the hyper-biofilm phenotype of the Δ dbfS strain ( Fig. 5E ). To determine if CdgL links DbfR phosphorylation to elevated c-di-GMP levels, we introduced the c-di-GMP reporter into the Δ dbfS Δ cdgL double mutant. As expected, the ∼40% increase in c-di-GMP levels observed in the Δ dbfS strain ( Fig. 5A ) was nearly abolished in the Δ dbfS Δ cdgL double mutant, which exhibited only a modest (∼12%) increase relative to the Δ cdgL single mutant ( Fig. 5F ). Of note, we found that the Δ cdgL single mutant exhibited a >20% reduction in basal c-di-GMP reporter output and reduced peak biofilm biomass relative to the WT ( Fig. S7A, B ), demonstrating that CdgL also contributes to baseline c-di-GMP synthesis even when DbfR is dephosphorylated. Taken together, our results suggest that phosphorylated DbfR activates c-di-GMP synthesis in large part through cdgL upregulation, driving a transcriptional program favoring a sessile biofilm state. Download figure Open in new tab Figure S7: Deletion of cdgL decreases intracellular c-di-GMP levels and peak biofilm biomass compared to the WT V. cholerae strain. (A) Relative c-di-GMP reporter output for the WT and Δ cdgL strains, expressed as mean ± SD of the percentage difference relative to the WT control. Points represent individual replicates of N = 2 biological replicates and 3 technical replicates. Statistical analysis was performed using an unpaired, two-sample t-test (****, P < 0.0001). (B) Quantification of biofilm biomass for WT and Δ cdgL strains using time-lapse brightfield microscopy. Points represent averages of N = 2 biological replicates and 3 technical replicates, ± SD (shaded regions). Constitutive DbfR phosphorylation compromises V. cholerae fitness in an animal model of infection Given the dramatic transcriptomic changes, reduced growth rate, and commitment to the biofilm state observed upon DbfR phosphorylation, we wondered how activation of this pathway relates to V. cholerae fitness, particularly during infection. To assess fitness, we conducted competition assays in LB media and in the infant mouse model of V. cholerae infection. We competed WT V. cholerae against the dephosphorylated dbfR D51V strain, as well as the Δ dbfS and Δ dbfQ strains that exhibit elevated DbfR phosphorylation. For both in vitro and in vivo assays, the competitive index (CI) for dbfR D51V was around 1, indicating that inactivation of DbfR phosphorylation does not impair V. cholerae fitness in media or in the animal ( Fig. 6A, B ). In contrast, the Δ dbfS and Δ dbfQ mutants were significantly outcompeted by the WT strain under both conditions, with CI values at least 10-fold lower than the dbfR D51V strain ( Fig. 6A, B ). Complementation of the Δ dbfS and Δ dbfQ mutants restored fitness in both conditions. We wondered whether the disadvantage of the phospho-DbfR strains was due to their commitment to the biofilm state. To test this possibility, we performed competition experiments with the Δ dbfS Δ cdgL mutant, which, as shown above, disconnects biofilm regulation from DbfR-phosphorylation. We note that the Δ dbfS Δ cdgL strain exhibits slower growth than the WT, though its growth defect is less severe than the Δ dbfS single mutant ( Fig. S7C ). Consistent with this observation, we found that the Δ dbfS Δ cdgL strain was also significantly outcompeted in culture and in mice ( Fig. 6A, B ). Given that 540 genes are differentially expressed in the Δ dbfS mutant ( Fig. 4A ), our results suggest that other components of the regulon, unrelated to the biofilm lifecycle, are responsible for the competitive disadvantage in vitro and in vivo . Overall, our results demonstrate that activation of the DbfQRS pathway negatively impacts the fitness of V. cholerae both in culture and in mice. Importantly, our findings highlight that the DbfQRS pathway could serve as a suitable target for the development of novel anti-infectives that function by reducing V. cholerae fitness. Download figure Open in new tab Figure 6. Activation of the DbfQRS pathway results in a competitive disadvantage in vitro and in vivo . (A) In vitro competition assay. WT ( lacZ ⁻) V. cholerae were competed against the indicated strains at a 1:1 ratio in LB medium for 24 hours. Data are displayed as the median with interquartile ranges. Points represent individual replicates of N = 3 biological replicates. Statistical analyses were performed using unpaired, two-sample t-tests with a 95% confidence interval. (B) In vivo competitive colonization assay. WT ( lacZ ⁻) was competed against the indicated strains at a 1:1 ratio in the infant mouse small intestine for 24 hours. Data are presented as a single data point per mouse, along with median and interquartile range for each condition. Statistical analyses were performed using the Mann-Whitney U test. In both assays, competitive indices (CI) were calculated as the ratio of output to input of the mutant strain relative to the WT. (*, P < 0.05; **, P < 0.01; ***, P < 0.001, ****, P < 0.0001; ns, not significant). Discussion The current work represents an initial characterization of a novel class of bacterial TCSs involving a small, secreted protein which directly modulates receptor activity. We provide a comprehensive investigation of the DbfRS TCS in V. cholerae – encompassing its input signals, the role of DbfQ as pathway regulator, and downstream effects of DbfR phosphorylation. Using multidisciplinary approaches, we demonstrate that DbfQ controls the activity of DbfS via a direct, high-affinity interaction that is central to pathway regulation. Indeed, the dynamic balance in the opposing kinase and phosphatase activities of DbfS calibrates the phosphorylation state of DbfR, which in turn determines V. cholerae ’s decision to disperse or commit to a biofilm state. We reveal that defects in LPS biosynthesis or the presence of membrane-targeting agents elevate DbfR phosphorylation, implicating the pathway in responding to outer membrane perturbations. We propose that membrane damage could lead to the loss of periplasmic components (e.g. leakage of DbfQ), or the release of other mechanical and biochemical cues that might be directly detected by DbfQ or DbfS. These signals could function to disrupt the DbfQ-DbfS interaction, biasing the system towards DbfR phosphorylation. Cells could then commit to the biofilm-associated state, potentially as a stress-driven protective response. Future investigations will be required to resolve whether DbfQRS directly senses perturbations in membrane integrity or responds to secondary stress signals. The DbfQRS pathway exerts pleiotropic control over the biofilm lifecycle, metabolic activities, motility, and peptidoglycan biosynthesis, underscoring its wide-ranging influences on V. cholerae physiology. Strikingly, constitutive activation of the pathway imposes a fitness cost, compromising V. cholerae growth and colonization. Consistent with this finding, we note that a previous attempt to generate an in-frame deletion of dbfS in a different V. cholerae isolate was unsuccessful, suggesting that constitutive DbfR activation may even be lethal in some strain backgrounds ( 63 ). In the current study, we find that the growth defect observed upon pathway activation is not due to the costs associated with elevated biofilm production. Thus, we propose that the fitness cost of DbfQRS hyperactivity is likely to arise from transcriptional downregulation of metabolic processes. Pinpointing the pathways controlled by DbfR that impact growth will be the subject of future studies. Despite the costs of DbfQRS hyperactivation, the widespread conservation of this pathway suggests it confers a selective advantage under specific conditions. Given that DbfQRS responds to outer membrane stresses, its activation may serve as a regulatory mechanism that prioritizes stress adaptation over cellular activity. By reprogramming cellular processes (i.e. enhancing biofilm formation while downregulating metabolism, motility, and growth), DbfQRS activation likely benefits V. cholerae in hostile environments where survival takes precedence over rapid proliferation. For example, downregulation of metabolic processes may conserve energy during nutrient deprivation while biofilm formation could provide protection against environmental stressors such as predation or antimicrobials. The DbfQRS pathway is distinct in that, unlike many TCSs that regulate specific aspects of bacterial adaptation, it orchestrates a broad, pleiotropic shift in cellular physiology — encompassing biofilm regulation, metabolism, motility, and cell envelope integrity. Such expansive regulatory control underscores its unique role as a master switch for multiple adaptation strategies in adverse environments. In summary, our work reveals that the DbfQRS pathway integrates membrane stress signals with global regulatory responses, thereby linking environmental challenges to adaptive lifestyle transitions in V. cholerae . More broadly, understanding how stress-responsive TCSs like DbfQRS orchestrate bacterial adaptation may reveal novel antimicrobial strategies that exploit the inherent trade-offs in bacterial stress adaptation. Because DbfQRS influences a global profile of gene expression, interventions targeting this pathway might be effective against multiple facets of bacterial physiology. By hyperactivating the pathway to force V. cholerae into a low-fitness state, we could exploit its pleiotropic trade-offs to curb bacterial resilience. Given the widespread conservation of dbfQRS -like modules across bacterial phyla, it is likely that similar regulatory principles extend beyond V. cholerae . Future studies should explore whether this pathway plays a comparable role in other clinically and environmentally relevant bacteria. Examining the function of DbfQRS homologs in diverse species could reveal conserved and species-specific regulatory strategies, offering insight into how different bacteria fine-tune stress responses. Additionally, structural and biochemical characterization of DbfQ orthologs could determine whether their mode of receptor modulation is universally conserved or has evolved to accommodate distinct signaling contexts. A deeper understanding of the DbfQRS family may not only refine our current models of bacterial signaling networks but also uncover new targets for antimicrobial interventions by disrupting stress adaptation mechanisms in pathogenic bacteria. Materials and Methods Bacterial strains, reagents, and cloning The V. cholerae parent strain used in this study was O1 El Tor biotype C6706str2. E. coli S17 and Top10 were used to transfer plasmids into V. cholerae by conjugation. A complete list of strains used in this study is provided in Table S3. For passaging and cloning, V. cholerae and E. coli strains were cultivated in lysogeny broth (LB) supplemented with 1.5% agar or in liquid LB with shaking at 30°C and 37°C, respectively. Unless otherwise specified, antibiotics were used at the following concentrations: polymyxin B, 50 μg/mL; kanamycin, 50 μg/mL; spectinomycin, 200 μg/mL; streptomycin, 400 μg/mL, chloramphenicol, 2 μg/mL; and gentamicin, 15 μg/mL; ampicillin, 100 μg/mL. For microscopy, luminescence quantifications, and c-di-GMP reporter measurements, V. cholerae strains were grown in M9 minimal medium supplemented with dextrose and casamino acids (1x M9 salts, 100 µM CaCl 2 , 2 mM MgSO 4 , 0.5% dextrose, 0.5% casamino acids). When required, L -arabinose (Thermo Fisher Scientific) was added at a concentration of 0.2% from the start of assays. All genetic modifications were generated by replacing genomic DNA with linear DNA introduced via natural transformation, as described previously ( 64 – 66 ). PCR amplification was performed with iProof (Bio-rad) or Q5 DNA polymerase (New England Biolabs). Sanger sequencing (Azenta) was used to verify genetic alterations. Genomic DNA from recombinant strains was used as templates for generating DNA fragments as needed. Gene deletions were generated in-frame to remove the entire coding sequences, except for dbfS and dbfR , which overlap in their operon. For these genes, an internal portion of each gene was deleted to avoid perturbing the adjacent gene. To construct dbfQ-3xFLAG at its native locus, a C-terminal 3xFLAG epitope tag was inserted immediately upstream of the dbfQ stop codon. Oligonucleotides and synthetic linear DNA g-blocks were ordered from IDT and are reported in Table S4. Microscopy and image analysis The V. cholerae biofilm lifecycle was monitored by time-lapse brightfield microscopy as described previously ( 67 ). Briefly, single colonies of V. cholerae were inoculated into 200 μl of LB medium in 96-well plates covered with a breathe-easier membrane (USA Scientific Inc) and grown overnight at 30°C with constant shaking. The following morning, overnight cultures were diluted ∼1:200,000 in M9 minimal medium to achieve a final OD 600 of ∼1 x 10 -5 . Diluted cultures were statically grown at 30°C in 96-well polystyrene microtiter plates (Corning) in an Agilent Biospa robotic incubator which transferred microtiter plates for brightfield imaging at 30-min intervals over a 24-h period. Image acquisition was performed using the Agilent Biotek Cytation 1 imaging plate reader equipped with a 10x air objective (Olympus Plan Fluorite, NA 0.3) or a 4x air objective (Olympus Plan Fluorite, NA 0.13), controlled by the Biotek Gen5 (Version 3.12) software. Quantifications of biofilm biomass were performed based on the principle that biofilms scatter light to a greater degree than planktonic cells in low-magnification brightfield images. To segment biofilms within brightfield images, first pixel intensities were inverted, local contrast was normalized, images were blurred with a Gaussian filter, and a fixed threshold was applied allowing for the differentiation of biofilms from background. The resulting binarized image masks were then applied to the raw images to determine the total light attenuated by biofilms with the field of view, yielding our biofilm biomass metric. Peak biofilm biomass corresponding to the maximum value recorded in each time-lapse replicate. In all cases, biomass values were normalized to the peak biomass of the control strain to account for day-to-day variability and for ease of comparison between strains/conditions. Image analyses were performed using the Julia programming language (version 1.11.1). Plotting was performed in RStudio (version 4.4.1) ( 68 ) using the ggplot2 package ( 69 ). Fluorescence microscopy used to investigate DbfQ localization was performed on a DMI8 Leica SP-8 point scanning confocal microscope driven by LasX software. For imaging, strains harboring DbfQ fusions to mNG were first grown in M9 medium to OD 600 = 0.6, at which point cultures were diluted 1000x and inoculated into glass-bottomed 96-well plates (Mattek). Cells were then allowed to attach for 1 h before imaging. Microscopy was performed with a 63x objective (Leica, NA = 1.20), along with a digital zoom of 5x. A tunable white-light laser (Leica; model #WLL2; excitation window = 470–670 nm) set to 503 nm was used to excite mNG fluorescence. Light was detected using GaAsP spectral detectors (Leica, HyD SP), and timed gate detection and frame averaging were employed to minimize background signal. Gene neighborhood analysis To assess if PepSY domain-containing proteins (PDPs) are frequently found in the genomic proximity of histidine kinases (HKs) and/or response regulators (RRs) in bacterial genomes, we performed a non-comprehensive screen using a large database of proteins from InterPro ( 70 ). First, we downloaded gene IDs and organism IDs for three sets of proteins: ( 1 ) ∼1.2M proteins containing the HK domain (IPR005467), ( 2 ) ∼1.6M proteins containing the RR domain (IPR001789), and ( 3 ) ∼17K proteins containing only the PepSY domain (IPR025711). Gene IDs for each protein were of the form “_”. Second, using a custom Python script, we parsed the above gene IDs and identified all pairs of PDP and HK/RR genes that lie within 4-gene numbers in the same genome. This stringent cutoff was not selected to be comprehensive, but instead to reveal genomes where three gene classes are closely positioned on the genome. Third, to allow an assessment of our result, we estimated the null probability of a PDP lying near an HK/RR by assuming an average circular bacterial genome of 4000 genes, and one copy each of a PDP and an HK/RR distributed randomly in this genome. The observed frequency of a PDP and an HK/RR in proximity was found to be >60-fold higher than null. To identify which taxa had a PDP and an HK/RR within a 4-gene vicinity, we used organism IDs from the shortlisted set above and determined their taxonomic order, class and phylum using the tree of life found in the STRING database ( string-db.org/cgi/download ) ( 71 ). The order Vibrionales (containing genus Vibrio ) made up 0.8% of the dataset. Therefore, all taxa with a representation of ≥ 0.8% were shown in the table ( Fig. S2 ). Finally, for a handpicked set of species relevant to human health and agriculture, gene neighborhood data was displayed ( Fig. 1E ) using the FlaGs pipeline ( 72 ) with the following RefSeq IDs of PDPs as input and default parameters: WP_001165432.1, WP_011080671.1, WP_003090497.1, WP_000780501.1, WP_004201003.1, and WP_003592804.1. Phos-tag gel analysis To monitor DbfR and phospho-DbfR via SDS-PAGE, phos-tag gel experiment was carried out as described previously ( 30 ), with some minor adjustments. Briefly, the endogenous dbfR gene was replaced with dbfR-SNAP in Δ dbfS and Δ dbfQ Δ dbfS strains, and an arabinose-inducible P BAD -dbfS was introduced at an ectopic locus ( vc_1807 ). Overnight cultures of each strain were diluted 1:1,000 in 3 mL of LB and grown at 30°C with shaking to an OD 600 of ∼0.6, after which 1 µM SNAP-Cell TMR Star (New England Biolabs) was added to label the SNAP tag. Cultures were subsequently divided into two tubes: 0.2% L -arabinose was added to one tube to induce DbfS production, while the other tube was left uninduced. The cultures were returned to 30°C with shaking and after 1-h incubation, 1 mL of the cultures were harvested by centrifugation (13,000 rpm, 1min). Pelleted cells were subsequently lysed in 40 μL of Bug Buster (EMD Millipore, #70584–4) for 5 min at 25°C with intermittent vortexing. Lysates were solubilized in 1.5x SDS/PAGE buffer for 5 min and samples were immediately loaded onto a cold 7.5% SuperSep Phos-tag gel (50 μM) (FUJIFILM Wako Pure Chemical; 198-17981). Electrophoresis was carried out at 80V at 4°C for ∼1 h. Gel images were captured on the FluorChem E Imaging System (ProteinSimple) Quantification of P dbfQRS - lux To quantify the transcriptional activity of the dbfQRS promoter as a proxy for DbfR phosphorylation, we constructed a P dbfQRS - lux reporter by fusing the dbfQRS promoter to the luxCDABE luciferase operon from Photorhabdus ( 73 ). All strains used in this assay harbored a vpsL deletion to eliminate biofilm-related interference with luminescence and optical density measurements. Unless indicated otherwise, overnight cultures of strains harboring the P dbfQRS - lux reporter were diluted to OD 600 of ∼1 x 10 -5 in fresh M9 medium in 96-well plates. Optical density at 600 nm (OD 600 ) and luminescence intensity ( lux ) from P dbfQRS - lux were measured simultaneously at 30-min or 1-h time intervals over a 24-h period using the Agilent Biotek Cytation 1 Plate Reader, driven by the Biotek Gen5 software. For quantification of P dbfQRS - lux reporter output in the presence of antimicrobials or iron, cultures were adjusted to a starting OD 600 ∼ 0.1 at the onset of assay. For antimicrobials assay, overnight cultures were diluted in M9 medium supplemented with increasing concentrations of polymyxin B or thymol. For iron supplementation assay, overnight cultures were diluted in M9 medium supplemented with 100 µM FeCl 2 or FeCl 3 , followed by a shortened 2-h assay to minimize Fe(II) oxidation. Transposon mutagenesis screens Two independent Tn5 transposon mutagenesis screens were performed: ( 1 ) to identify mutations activating P dbfQRS -lux , and ( 2 ) to identify suppressors of colony rugosity in the Δ dbfS background. In both cases, transposon mutagenesis was carried out identically: E coli strain S17 harboring the Tn5:: kan transposase plasmid was conjugated with the specified parent V. cholerae strains. Conjugation was allowed to proceed for two hours at 37° C on LB agar plates without selection. The short incubation ensured limited appearance of “sister” mutants derived from cell divisions following transposon insertion. Conjugations were collected with a sterile loop, resuspended in liquid LB media, and plated on selective media. Transposon insertion mutants were selected on LB agar plates supplemented with streptomycin (to kill E. coli ) and kanamycin (to select for transposon integration). For the P dbfQRS -lux screen, mutant colonies with visibly increased luminescence, as observed on a FluorChem E imager, were isolated, grown overnight, and arrayed into 96-well plates for quantification of P dbfQRS - lux reporter activity as described above. Mutants exhibiting significantly elevated luminescence compared to WT control were selected for further analysis. In the Δ dbfS colony rugosity suppressor screen, mutants displaying a smooth colony morphology (rugose-to-smooth transition) were identified by visual inspection and selected for sequencing. The locations of transposon insertions in both screens were determined using arbitrary PCR (Table S4) followed by Sanger sequencing (Azenta) ( 74 ). Western blotting of DbfQ-3xFLAG For western blotting to assess DbfQ cleavage, cultures of strains expressing DbfQ- 3xFLAG and its cleavage variants were grown to OD 600 = 1.0, then harvested by centrifugation for 1 min at 13,000 rpm. The resulting pellets were flash frozen, thawed, and lysed for 10 min at 25°C by resuspension to OD 600 = 1.0 in Bug Buster (EMD Millipore) supplemented with 0.5% Triton-X, 50 μg/mL lysozyme, 25 U/mL benzonase nuclease, and 1 mM phenylmethylsulfonyl fluoride (PMSF). 1x SDS-PAGE buffer (final) was then added and allowed to incubate for 1 h at 37°C before loading into 4–20% Mini-Protein TGX gels (Bio-Rad). Electrophoresis was performed at 200 V for 30 min. Protein transfer onto PVDF membranes (Bio-Rad) was then performed for 1 h at 4°C at 100 V in transfer buffer (25 mM Tris, 190 mM glycine, 20% methanol). Membranes were blocked for 1 h in 5% milk in PBST (137 mM NaCl, 2.7 mM KCl, 8 mM Na 2 HPO 4 , 2 mM KH 2 PO 4 , and 0.1% Tween). Membranes were subsequently probed for 1 h using a monoclonal Anti-FLAG- Peroxidase antibody (Millipore Sigma, #A8592) at a 1:5000 dilution in PBS-T containing 5% milk. After six 5-min washes in PBST, membranes were developed using the Amersham ECL western blotting detection reagent (GE Healthcare). AlphaFold prediction The AlphaFold Server ( https://alphafoldserver.com/ ), powered by AlphaFold 3 ( 75 ), was used to predict the interaction between DbfQ and DbfS. The interaction interface was predicted between the secreted form of DbfQ (beginning at residue 32) and full-length DbfS, with an interface predicted template modeling (ipTM) score of 0.69. The highest- ranked prediction based on reported confidence scores was selected for further visualization and analysis. Structural figures illustrating the predicted protein complexes were prepared using PyMOL (Schrödinger, LLC). Purification and pull-down assays for DbfQ and DbfS SD DNA encoding processed DbfQ-6xHis (residues 32 to 135, excluding the secretion signal), and DbfS SD -6xHis (residues 43 to 171) were cloned into the pET-15b vector via Gibson assembly (NEB), followed by transformation into chemically competent E. coli BL21 (DE3) cells. For protein purification, cultures were grown in Terrific broth (Fisher BioReagents) supplemented with 100 μg/mL ampicillin at 37°C for 4 h with shaking until OD 600 ∼ 0.6 - 0.8 was achieved. Protein expression was induced with 1 mM IPTG, followed by incubation at 18°C for 16 hours with continuous shaking. The following morning, cells were harvested by centrifugation (5,000 x g, 20 min, 4°C) and resuspended in lysis buffer (25 mM Tris–HCl pH 7.5, 300 mM NaCl, 10 mM imidazole, 10% glycerol, 0.5 mg/mL lysozyme, 25 U/mL benzonase nuclease, and 1x EDTA-free protease inhibitor tablet (Thermo Scientific). To stimulate lysis, resuspended cells were subjected to sonication (4 minutes total; 30 seconds on, 1:30 off; 8x cycles). Lysates were then subjected to centrifugation (15,000 rpm, 20 min, 4°C). Supernatants were filtered through 0.45-µm filters (Cytiva, #4654) and loaded onto Ni-NTA resin (EMD Millipore, #70666-4) pre-equilibrated with lysis buffer. After lysate flow-through was completed, columns were washed 3 times with 10x column volumes of wash buffer (25 mM Tris–HCl pH 7.5, 300 mM NaCl, 10 mM imidazole, 10% glycerol), after which bound proteins were eluted with elution buffer (25 mM Tris–HCl pH 7.5, 100 mM NaCl, 300 mM imidazole, 10% glycerol). The 6xHis tag on DbfQ was removed by thrombin cleavage (Cytiva Thrombin Protease, #45001320), and cleaved DbfQ was separated from the His-tag and uncleaved protein by repeated Ni-NTA affinity chromatography. Proteins were then dialyzed into storage buffer (25 mM Tris–HCl pH 7.5, 100 mM NaCl) using 3,500 molecular weight cut-off dialysis cassettes (Thermo Scientific, #66330) overnight at 4°C. Protein purity and concentration were assessed by SDS-PAGE and Pierce BCA Protein Assay (Thermo Scientific, #23225), respectively. Aliquots of proteins were flash-frozen in liquid nitrogen and stored at −80°C for subsequent use. For pull-down assays, 50 µM of DbfQ (6xHis tag-cleaved) and 50 µM of DbfS SD - 6xHis were mixed in binding buffer (25 mM Tris–HCl pH 7.5, 100 mM NaCl, 1x EDTA-free protease inhibitor tablet). The protein mixture was incubated for 1 h at 25°C, then applied to Ni-NTA resin. After three washes with wash buffer, bound proteins were eluted with elution buffer and analyzed by SDS-PAGE. As controls, individual DbfQ (6xHis tag- cleaved) and DbfS SD -6xHis were incubated with Ni-NTA resin under identical conditions. Microscale thermophoresis (MST) analysis Experiments were performed as described previously with minor modifications ( 76 ). Before labeling with fluorescent probes, DbfQ was diluted, and buffer exchanged into buffer M (20 mM MES, 100 mM NaCl, 10% glycerol) to remove incompatible buffer components. For protein labeling, 10 µM DbfQ was mixed with 3x excess Red NHS dye (Nanotemper Technologies) dissolved in DMSO and incubated at room temperature in the dark for 30 min. After incubation, excess and unreacted dye was removed by passing the protein-dye mixture through a gel-filtration column (Column B, Nanotemper Technologies). Optimal protein labeling was determined using the formula: A 650 /195,000/M/cm x concentration of labeled protein; A 650 = absorbance at 650 nm, and 195,000/M/cm is the molar absorbance of the Red NHS dye. An optimal labeling was considered as a value between 0.6 and 1. For MST experiments, unlabeled DbfS protein was serially diluted in low binding tubes in buffer M supplemented with 0.05% Tween 20 at pH 7.5. The labeled DbfQ protein was added and incubated for 5 min at room temperature. The concentration of unlabeled DbfS ranged from 0.49 nM to 16,105 nM while the concentration of the labeled DbfQ was kept constant (20 nM). After incubation, samples were loaded into standard Monolith NT.115 capillary tubes and thermophoresis was determined using the Monolith MST device (Nanotemper Technologies) with the following parameters: 20%–60% excitation power and medium MST Power at 25°C. Thermophoresis results were analyzed using the PALMIST ( 77 ) and GUSSI ( 78 ) analysis pipeline. Briefly, data from Monolith Software were imported into the PALMIST software and a preset T-jump (TJ) was applied to the data using a 1:1 binding model with 95% confidence interval. After data analysis, figures were rendered using GUSSI. For stoichiometry determination, DbfQ-NHS (100 nM) was titrated against narrow increasing concentrations of unlabeled DbfS (0 nM to 40,000 nM) using 20%–60% excitation power and medium MST Power at 25°C. Fluorescence values were converted into relative thermophoresis by dividing the normalized fluorescence by the resulting amplitude at each data point. RNA-sequencing Cultures of the indicated V. cholerae strains, grown in triplicate, were diluted to OD 600 ∼0.001 in 5 mL of M9 medium. Subcultures were incubated at 30°C with shaking until OD 600 0.1 was reached. At this point, cells were collected by centrifugation for 10 min at 3,200x g and resuspended in RNAprotect (Qiagen). RNeasy mini kit (Qiagen) was used for RNA isolation and a TURBO DNA-free kit (Invitrogen) was used to remove remaining DNA. The concentration and purity of RNA were measured using a NanoDrop instrument (Thermo). Samples were frozen in liquid nitrogen and stored at −80°C until they were shipped on dry ice to the Microbial Genome Sequencing Center (now SeqCoast). Upon sample submission, the 12 million paired-end reads option and the intermediate analysis package were selected for each sample. As per the MIGS project report, quality control and adapter trimming were performed with bcl2fastq (Illumina), while read mapping was performed with HISAT2 ( 79 ). Read quantitation was performed using Subread’s featureCounts ( 80 ) functionality, and subsequently, counts were loaded into R (R Core Team) and normalized using edgeR’s ( 81 ) Trimmed Mean of M values (TMM) algorithm. Values were converted to counts per million (cpm), and differential expression analyses were performed using edgeR’s QuasiLinear F-Test (qlfTest) functionality against treatment groups, as indicated. Kegg pathway analysis was performed using limma’s ( 56 ) “kegga” functionality with default parameters. Genes considered Up/Down in this analysis had a false discovery rate < 0.05. Plots, including heatmaps, pathway regulation, and volcano plots were produced in RStudio using the ggplot2 package. Motility assay Motility assays were performed on 6-well plates containing 1% tryptone, 0.5% NaCl, and 0.3% agar. V. cholerae strains were first grown overnight on LB agar plates at 30°C. A single colony from each strain was picked by a sterile pipette tip and inoculated into the center of each well of the motility plates. Plates were incubated at 37°C for 16 h, during which images were taken every hour using an Epson V750 Pro flatbed scanner. Motility was quantified by measuring the diameter of the motility zone for each strain in ImageJ. All statistical analyses in this study were performed using GraphPad Prism version 10.4.1 (GraphPad Software, San Diego, CA, USA). c-di-GMP reporter assay The c-di-GMP reporter assays were performed as previously described ( 58 ) Strains were constructed by conjugation with E.coli Top10 and S17 cells. Briefly, overnight V. cholerae cultures were diluted 1:5000 into M9 medium supplemented with 15 μg/mL gentamicin and transferred into 96-well plates sealed with a breathe-easier membrane. Plates were incubated overnight at 37°C with shaking. The following day, membrane was removed, and reporter measurements were obtained using a Tecan Spark plate reader using AmCyan (ex: 430 ± 20 nm, em: 490± 20 nm) and Turbo RFP (ex: 520 ± 20 nm, em: 580 ± 20 nm) channels. Relative fluorescence intensity (RFI) was calculated as the c-di- GMP regulated TurboRFP signal divided by constitutive AmCyan signal, and RFI values of mutants were normalized to WT signal. In vitro and in vivo competition assays Competition assays were conducted to assess fitness of mutant V. cholerae strains relative to a WT reference strain ( lacZ −) both in LB medium ( in vitro ) and in an infant mouse model ( in vivo ). For both assays, bacterial cultures were grown aerobically for ∼18 h in LB medium at 30°C. For in vitro assays, ∼10⁵ CFU of each competing strain were mixed 1:1 in LB medium containing glass beads (to disrupt biofilms, as has been done previously) and incubated for 24 h at 30 °C. At the onset of the experiment and after 24 h of competition, samples were collected, serially diluted, and plated on LB/X-gal plates to enumerate CFUs for each strain. For in vivo competition assays, competing strains were mixed equally at a 1:1 ratio, and approximately 10 6 CFU were administered orogastrically to 4- to 7-day-old CD-1 mice (Charles River Laboratories). Prior to infection, infant mice were housed with their dam with ample access to food and water for at least 24 h and monitored. Serial dilutions of the intestinal homogenates were plated on LB/X-gal agar plates, allowing for CFU enumeration. In both assays, competitive index (CI) was calculated as the ratio of output to input of the mutant strain relative to the WT. For in vitro assays, three biological replicates were performed, while a minimum of five mice were used for each in vivo experiment. Each biological replicate ( in vitro ) or individual mouse ( in vivo ) was treated as a single data point, and results are presented as the median with interquartile range. All animal experiments were approved by the Institutional Animal Care and Use Committee at Tufts University School of Medicine (Protocol B2024-26). Data Availability Statement The source data used to generate all main and supporting figures in this work are available on Figshare, or as Supplemental Datasets. Biological materials used in this study are available upon request from Carnegie Mellon University. Ethics Statement All animal experiments were done in accordance with NIH guidelines, the Animal Welfare Act, and US federal law. The infant mouse colonization experimental protocol B2024-26 was approved by Tufts University School of Medicine’s Institutional Animal Care and Use Committee. All animals were housed in a centralized and AAALAC-accredited research animal facility that is fully staffed with trained husbandry, technical, and veterinary personnel in accordance with the regulations of the Comparative Medicine Services at Tufts University School of Medicine Acknowledgements We thank members of the Bridges lab for their insightful discussions and detailed feedback on the manuscript. We especially thank Dr. Bonnie Basler for guidance and for sharing strains. This work was supported by NIH grant R00AI158939, a Shurl and Kay Curci Foundation grant ( https://curcifoundation.org/ ), a Kaufman Foundation New Investigator Research Grant KA2023-136488 ( https://kaufman.pittsburghfoundation.org/ ), a Damon Runyon Cancer Research Foundation Dale F. Frey Award for Breakthrough Scientists 2302-17 ( https://www.damonrunyon.org/ ), and startup funds from Carnegie Mellon University to AAB. WLN and AS were supported by NIH grant R01AI121337. 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Bridges bioRxiv 2025.03.24.645060; doi: https://doi.org/10.1101/2025.03.24.645060 Share This Article: Copy Citation Tools A small periplasmic protein governs broad physiological adaptations in Vibrio cholerae via regulation of the DbfRS two-component system Emmy Nguyen , Charles Agbavor , Anjali Steenhaut , M R Pratyush , N. Luisa Hiller , Laty A. Cahoon , Irina V. Mikheyeva , Wai-Leung Ng , Andrew A. 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