Quorum sensing antiactivators constrain Pseudomonas aeruginosa RhlR activity

Quorum sensing antiactivators constrain Pseudomonas aeruginosa RhlR activity | 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 Quorum sensing antiactivators constrain Pseudomonas aeruginosa RhlR activity View ORCID Profile Varun Sridhar , Nicole. E. Smalley , View ORCID Profile Ajai A. Dandekar , View ORCID Profile Kyle L. Asfahl doi: https://doi.org/10.1101/2025.10.31.685934 Varun Sridhar 1 Department of Plant and Microbial Biology, University of California - Berkeley , Berkeley, CA 94720 Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Varun Sridhar Nicole. E. Smalley 2 Department of Microbiology, University of Washington , Seattle, WA 98195 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ajai A. Dandekar 2 Department of Microbiology, University of Washington , Seattle, WA 98195 3 Department of Medicine, University of Washington , Seattle, WA 98195 Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ajai A. Dandekar Kyle L. Asfahl 3 Department of Medicine, University of Washington , Seattle, WA 98195 4 Microbial Interactions and Microbiome Center, University of Washington , Seattle, WA 98195 Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Kyle L. Asfahl For correspondence: asfahl{at}uw.edu Abstract Full Text Info/History Metrics Preview PDF Abstract Pseudomonas aeruginosa , an opportunistic pathogen, uses a cell-cell communication system called quorum sensing (QS) to regulate gene expression in response to population density. P. aeruginosa QS involves, in part, two transcription factors, LasR and RhlR, that respond to N -acyl homoserine lactone (AHL) signals. Two proteins known as “antiactivators,” QteE and QslA, attenuate QS by inhibiting LasR, RhlR, or both. While initial characterization of antiactivation has revealed the considerable influence these factors may have on dampening QS, details regarding the individual impacts of these antiactivators on P. aeruginosa QS activity remain scant. Additionally, the effects of antiactivators on RhlR QS activity and in QS systems in isolates or strain lacking LasR have yet to be explored. To investigate how QteE and QslA each modulate LasR or RhlR independently, we combined gene deletion and over-expression analysis of each antiactivator in wild-type P. aeruginosa (PAO1) and two strains with rhl -dominated QS: clinical isolate E90 and PAO Δ lasR Δ mexT . As measured with a transcriptional reporter, over-expression of qteE or qslA notably reduced RhlR activity in PAO1 and PAO Δ lasR Δ mexT , but only expression of qteE had a marked effect on RhlR activity in E90. Expression analysis indicates LasR and RhlR repress QteE transcription, but not QslA. By over-expressing qslA in the absence of QteE and vice versa, we demonstrate that QslA activity and corresponding effects on QS phenotypes can be QteE-dependent in some scenarios. Our results reveal a nuanced role for individual antiactivator proteins in affecting the layered P. aeruginosa QS circuitry. Importance Quorum sensing (QS) is a cell signaling mechanism that enables populations of Pseudomonas aeruginosa to coordinate group behaviors such as biofilm formation, virulence factor production, and antibiotic tolerance once a critical cell-density threshold is reached. P. aeruginosa employs two “antiactivator” proteins that attenuate QS at low cell densities, dampening QS activation. The specific effects of individual antiactivators on the complex and hierarchically-arranged P. aeruginosa QS systems remain undefined. Here, we use two strains with rewired QS circuits to independently assess the effects of QS antiactivators on each QS circuit. We find that while one antiactivator selectively targets one QS circuit, the other can broadly target both with strong effects on QS activity. This work reveals an additional layer of complexity to counter-regulation of QS signalling and further defines antiactivation as a mechanism P. aeruginosa uses to finely tune QS responses. Introduction Many bacteria use quorum sensing (QS), a signaling system that couples cell-cell communication and gene regulation in response to population density, to concert population-wide behavior ( 1 ). A common type of QS in Gram-negative bacteria is mediated by acyl-homoserine (AHL) signal molecules. These diffusible AHL signals are produced by LuxI-type synthases (I-proteins) and received and bound by LuxR-type regulators (R-proteins). In most cases, the signal-bound R-protein serves as a transcriptional activator that binds conserved promoter sequences to control expression of target genes ( 1 , 2 ). Pseudomonas aeruginosa , an opportunistic pathogen and a model for QS in Gram-negative bacteria, employs two complete LuxI/R-type gene circuits: LasI/R and RhlI/R. The LasI synthase produces an N -3-oxo-dodecanoyl-homoserine lactone (3OC12-HSL) signal which binds to the transcription activator LasR, and the RhlI synthase produces N -butanoyl-homoserine lactone (C4-HSL) which binds to RhlR ( 3 ). At low cell density, basal transcription of I-proteins yields low concentrations of signal that minimally bind and activate R-proteins, yielding an overall QS-off state. At high cell density and signal concentrations, both R-proteins form homodimers upon binding of their cognate signal to produce transcriptionally active complexes and a QS-on state ( 4 , 5 ). Activation of each QS system is amplified via auto-induction and further transcription of their respective synthases under conditions of high cell density and signal concentration. LasR controls the activation of rhlR in lab strains, positioning the two QS systems in a hierarchy with LasR as the master regulator ( 6 ). Together, the las and rhl QS circuits control the transcription of overlapping regulons that include genes encoding a battery of secreted products and virulence factors such as extracellular proteases, rhamnolipids, phenazines, and hydrogen cyanide ( 7 ). A remarkable trait of QS is that a population can trigger the induction of QS circuits in a majority of cells once the group reaches a target cell density, yet avoid early activation in individual cells ( 1 , 2 ). A natural question therefore arises: how do bacteria prevent early QS activation below a target density threshold? One such mechanism described in several AHL QS systems, including the LasI/R system of P. aeruginosa , is inhibition of R-protein activation through binding by so-called “antiactivator” proteins. QS antiactivation was first defined in the AHL QS system of Agrobacterium tumefaciens , in which the antiactivator TraM directly binds the receptor-regulator TraR to sequester it and prevent further dimerization and activation of the QS network ( 8 – 10 ). Mutants of TraM display higher QS activity and earlier activation of QS-controlled genes, indicating an important role for antiactivation in delaying QS induction in this system ( 9 ). P. aeruginosa employs proteins that serve to similarly dampen QS activity, two of which fall under the description of R-protein antiactivation: QteE and QslA ( 11 – 13 ). QteE is known to destabilize LasR dimers independently of transcription or translation, suggesting a direct interaction and sequestration of heterodimers or other post-translational mechanism ( 11 ). Some evidence has suggested QteE also targets and serves to destabilize RhlR ( 11 ). QslA works in a similar fashion as TraM (despite low sequence similarity), directly binding LasR monomers in a 2:1 ratio to prevent dimerization ( 12 , 13 ). qslA is expressed 55.8 times lower in a P. aeruginosa model for hypervirulence compared to the WT laboratory strain; this decreased expression drives higher production of many virulence factors and expression of lasR and rhlR , indicating repression of antiactivation may promote higher virulence in P. aeruginosa infections ( 14 ). Deleting both antiactivators has a greater effect on both the timing of QS induction and the magnitude of QS-controlled phenotypes than individual deletions of either gene ( 15 ). Measuring lasI expression in AHL signal-proficient and -deficient cells grown in coculture, Smith and Schuster demonstrated that signal-proficient cells exhibited much stronger lasI induction at low cell densities in an antiactivator mutant background compared to the wild-type, suggesting a clear role for QteE and QslA in prevention of early las circuit activation ( 16 ). Although previous work has uncovered some aspects of how these two P. aeruginosa antiactivators function to affect QS induction, several questions remain. Most work on the mechanisms underlying QteE and QslA activity has focused on LasR and not RhlR, a consequence of LasR regulating the rhl QS circuit in many lab strains. Many strains of P. aeruginosa isolated from infections or the environment do not have a functional LasR and instead use RhlR to control QS, underscoring both a need for further study of these divergent QS circuits while also presenting a potential resource ( 17 , 18 ). How antiactivation affects RhlR activity in QS circuits divorced from LasR remains unknown. The repressive effects of QteE and QslA appear distinct for LasR, but further investigation is warranted to better understand their individual roles in signal reception or LasR activity and stability, in addition to exploration of their effects on RhlR. Here, we leverage both a lab-adapted strain and a clinical isolate that showcase rhl -dominated QS to demonstrate a clear antiactivation effect of QteE, and to a lesser extent QslA, on RhlR. Using a combination of deletion mutants and over-expression constructs coupled with measurements of transcriptional activity, signal response, protein expression, and QS phenotypes, we uncover considerable nuance in the role of QteE and QslA in dampening QS in P. aeruginosa . Results Bacterial strains for studying LasR-independent QS circuits While Las-independent Rhl-QS systems are common in natural isolates of P. aeruginosa, laboratory strain genetics have made study of this type of QS challenging. The effects of deleting qteE, qslA , or both antiactivator-encoding genes in conjunction have been examined in wild-type P. aeruginosa , strain PAO1, but such deletions have not been examined in QS circuits free of the LasR-dominated regulatory hierarchy common in this widely-used laboratory strain ( 11 , 13 , 15 , 16 ). Analytical strategies used to address this issue with respect to QteE activity include inducible expression of rhlR in a Δ lasR Δ rhlR mutant, or ectopic expression of the pertinent QS and antiactivator proteins in E. coli ( 11 ). While both approaches have yielded some insight into QteE’s role in dampening P. aeruginosa QS, neither have been employed to better understand QslA, and importantly, these previous efforts have not addressed antiactivation of RhlR in a native P. aeruginosa regulatory context. One solution is to use clinical isolates from P. aeruginosa infections in people with cystic fibrosis ( 19 – 21 ). Many of these clinical isolates carry nonfunctional alleles of lasR and have “rewired” the QS circuits to favor RhlR/I as the dominant QS system relative to the PAO1 paradigm ( 17 , 22 , 23 ). Isolate E90 has been characterized as a genetically tractable strain that carries a nonfunctional lasR allele and demonstrates Las-independent RhlR activity and QS phenotypes ( 17 , 24 – 27 ). Another solution lies in an in vitro -evolved lab strain variant that expresses a subset of the RhlR regulon despite the absence of LasR. Kostylev and colleagues proposed that clinical isolates of P. aeruginosa may evolve QS circuitry that favors RhlR-based QS by developing mutations in the LysR-type regulator MexT, supported by their observations of reproducible mexT mutation in lab conditions that require QS for growth ( 28 ). They demonstrated that targeted deletions of just mexT and lasR in strain PAO1 produces the same QS regulation phenotype as the evolved strain, resulting in genetically tractable P. aeruginosa that expresses some RhlR-regulated genes independent of LasR. Therefore, we selected both the clinical isolate E90 and PAO Δ lasR Δ mexT as complimentary models for investigation of antiactivation in rhl -dominated QS. QteE, in contrast to QslA, separately modulates LasR and RhlR Previous work has demonstrated that inactivating mutations in qteE or qslA in strain PAO1 advances the induction of genes regulated by both LasR and RhlR ( 15 ). In this study, we aimed to broaden this understanding to other native QS circuitries through both mutation and over-expression of antiactivator genes. Here, we analyzed clean deletions in qteE or qslA in PAO1 alongside qteE deletions in PAO Δ lasR Δ mexT and E90. To control over-expression of qteE or qslA , we integrated an additional copy of either gene under the control of a synthetic arabinose-inducible promoter into a neutral chromosomal site (P araBAD -qteE , P araBAD -qslA ) ( 29 ). As a readout of RhlR activity, we monitored promoter activity of the rhamnosyl transferase gene rhlA with a plasmid-borne GFP-transcriptional reporter (P rhlA -gfp ) over time, and we used this bulk fluorescence data to calculate time to half-maximal GFP expression as a quantitative analysis of induction timing. rhlA expression has been widely observed as strictly controlled by RhlR, regardless of strain background, so even in the context of active LasR this promoter provides a reliable index of RhlR activation ( 30 , 31 ). In PAO1, deletion of qteE predictably advances timing and magnitude of P rhlA -gfp -derived fluorescence owing to the Las-dependent hierarchy in this strain, while qteE over-expression abolishes it ( Figure 1A ). P rhlA -gfp -derived fluorescence is generally lower in PAO Δ lasR Δ mexT and E90 ( Figure 1C , 1E ). Deletion of qteE in these Las-independent strains shows little additional fluorescence over their isogenic parents and does not significantly reduce time to half-maximal induction, but over-expression still completely abolishes P rhlA -gfp activity in these strains ( Figure 1C , 1E ). On the other hand, deletion of qslA in PAO1 shows slightly earlier P rhlA -gfp activity, but an overall similar magnitude of expression ( Figure 1B ). Surprisingly, this activity is not completely abrogated upon induction of P araBAD -qslA , only delayed. While multiple attempts at construction of qslA deletions in both PAO Δ lasR Δ mexT and E90 proved unsuccessful, we were able to induce overexpression of this gene via P araBAD -qslA . Expression of qslA in PAO Δ lasR Δ mexT reveals an antiactivation effect similar to PAO1, with modest but significant antiactivation of RhlR and P rhlA -gfp activity ( Figure 1D ). The effect of qslA over-expression is even weaker in E90 and barely discernable from WT E90 ( Figure 1F , not significantly different p = 0.5262). Together, these data show that in addition to the strong antiactivation QteE exhibits on LasR when present, this antiactivator also targets RhlR when LasR is absent. In contrast, the antiactivation effect of QslA appears more specific to LasR activity, with only modest dampening of QS activity when LasR control is not present. Download figure Open in new tab Figure 1: Effects of knocking out or over-expressing qteE (A, C, E) or qslA (B, C, F) on P rhlA -gfp expression over time in PAO1 (A, B), PAO Δ lasR Δ mexT (C, D), or E90 (E, F). Inset for (E) shows mean P rhlA -gfp expression in PAO1 in the same assay. “ara ” indicates that the media was supplemented with 0.5% L-arabinose to induce over expression of the following gene. P rhlA -gfp activity was measured as GFP fluorescence and normalized to OD 600 of experimental cultures. The y-axes for each plot are scaled to their maximal GFP levels. All data points show means of three biological replicates, with error bars representing s.e.m. Some error bars may not be visible. For each panel, fluorescence curves are on the left and time-to-half-maximal GFP measurements are on the right. Significant differences of means compared between indicated strains were determined using an unpaired two-tailed t-test (α = 0.05). ns, p > 0.05; **, p ≤ 0.01; **** p ≤ 0.0001. Given our observations that over-expression of antiactivators delays or abolishes P rhlA -gfp induction in most cases, we questioned whether exogenous addition of C4-HSL could restore RhlR activity by increasing the availability of signal to bind and stabilize RhlR dimers. To test this idea, we repeated the over-expression experiments in PAO1 and PAO Δ lasR Δ mexT as detailed in Figure 1 , but with supplementation of 10 μM C4-HSL. For this set of experiments, we also reduced the concentration of arabinose used (100-fold less for P araBAD -qteE , 10-fold less for P araBAD -qslA ) to control antiactivator over-expression so we that we could obtain a non-zero measurements in the conditions without signal supplementation. We observed moderately restored P rhlA -gfp induction timing with C4-HSL supplementation in both PAO1 and PAO Δ lasR Δ mexT cells that over-express qteE ( Figure 2A , 2C ). A similar pattern is present in PAO1 and PAO Δ lasR Δ mexT cells that over-express qslA ; supplementing these cultures with C4-HSL also advanced P rhlA -gfp induction timing, but to a greater degree than the experiments with qteE ( Figure 2B , 2D ). Regardless of the extent to which C4-HSL supplementation advanced timing or increased magnitude of P rhlA -gfp induction with respect to antiactivator deletions, over-expression of either antiactivator in either strain significantly reduced the time to half-maximal induction ( Figure 2 ). Together, these results indicate QteE has RhlR-specific antiactivation activity independent of LasR status in a variety of strain backgrounds, while QslA activity appears to only affect RhlR activity in the laboratory strains and their mutants tested here. Download figure Open in new tab Figure 2: Effects of exogenous C4-HSL on PAO1 (A, C) or PAO Δ lasR Δ mexT (B, D) P rhlA -gfp expression with over-expressed qteE (A, B) or qslA (C, D). “ ara ” indicates that the media was supplemented with 0.005% L-arabinose for over-expressing qteE or 0.05% L-arabinose for over-expressing qslA . “+C4-HSL” indicates that the media was supplemented with 10 μM C4-HSL. P rhlA -gfp activity was measured as GFP fluorescence and normalized to OD 600 of experimental cultures. Axes are scaled to focus on QS induction. All data points show means of three biological replicates, with error bars representing s.e.m. Some error bars may not be visible. For each panel, fluorescence curves are on the left and time-to-half-maximal GFP measurements are on the right. Significant differences of means compared between indicated strains were determined using an unpaired two-tailed t-test (α = 0.05). *, p ≤ 0.05; ***, p ≤ 0.001; ****, p ≤ 0.0001. Deleting qslA sensitizes LasR and RhlR to their signals Given our observations that antiactivators alter RhlR QS induction timing, and that this effect can be C4-HSL signal concentration-dependent, we were curious if antiactivators could alter the threshold concentration for a cell population reach quorum ( 11 , 15 , 16 ). Previous literature has demonstrated that QteE slows the accumulation of both P. aeruginosa AHLs, and that deleting qteE triggers LasR activity (as measured by P lasI induction) at lower concentrations of 3OC12-HSL ( 11 , 16 ). Therefore, we focused our experiments on QslA. To determine if QslA changes the concentration of 3OC12-HSL needed to trigger LasR induction, we introduced lasI and qslA deletion alleles into PAO1 and titrated 3OC12-HSL across a range of concentrations. We then measured LasR QS activity in batch cultures with a plasmid-borne GFP-transcriptional reporter constructed with the same backbone as P rhlA -gfp, but with the strictly LasR-specific promoter for lasI (P lasI -gfp ). Similarly, to test the sensitivity of RhlR to C4-HSL in the context of QslA antiactivation, we introduced rhlI and qslA deletions into PAO Δ lasR Δ mexT and titrated C4-HSL across a range of concentrations, again using the plasmid-borne RhlR-specific P rhlA -gfp reporter. In strain PAO Δ lasI , deletion of qslA results in significantly higher LasR induction at lower signal concentrations than in the parent strain. Supplementing growth media with just 10 nM 3OC12-HSL results in a 10-fold increase of P lasI -gfp in PAO Δ lasI Δ qslA compared to the qslA- proficient strain, nearly reaching maximal P lasI -gfp induction with the lowest supplement concentrations tested ( Figure 3A ). PAO Δ lasI Δ qslA also has a substantially lower saturating 3OC12 concentration than PAO Δ lasI ; the qslA -deficient strain reaches peak P lasI -gfp expression at 100 nM 3OC12, while the parent strain reaches its maximum P lasI -gfp expression 200 nM, the highest concentration tested. Similar to the trend observed for QslA and LasR, deletion of qslA in PAO Δ lasR Δ mexT Δ rhlI results in significantly higher RhlR induction than in the parent strain at the tested C4-HSL concentrations, albeit to a lesser degree ( Figure 3B ). Notably, RhlR reporter activity in PAO Δ lasR Δ mexT Δ rhlI plateaus with additions of 5 μM C4-HSL or greater; in contrast, reporter activity in PAO Δ lasR Δ mexT Δ rhlI Δ qslA continually rises with higher concentrations of C4-HSL. We note that all non-zero signal concentration-matched differences between tested strains were significantly different. Taken together, results of these two experiments indicate that, similar to previous reports of QteE activity, QslA also alters QS induction thresholds in part by modulating sensitivity of LasR and RhlR to their cognate AHLs. Download figure Open in new tab Figure 3: Effects of QteE or QslA on active and soluble LasR and RhlR. (A, B) Effects of QslA on sensitivity of LasR or RhlR to their cognate signals. (A) PAO1 strains were grown in varying concentrations of 3OC12-HSL. (B) PAO Δ lasR Δ mexT strains were grown in varying concentrations of C4-HSL. P l asI -gfp (A) or P rhlA -gfp (B) activity was measured as GFP fluorescence and normalized to OD 600 of experimental cultures. Inset in (B) has reduced axes to emphasize reporter activity at low [C4-HSL]. Data points represent the mean of three biological replicates, and error bars represent s.e.m. Some error bars may not be visible. All non-zero signal concentration-matched differences in (A) and (B) were statistically significant, as assessed by two-tailed t-tests (α = 0.05). (C) LasR and RhlR Western blots. Samples were retrieved from cells harvested after 18 hours of growth (stationary phase). Percent values indicate the amount of L-arabinose supplemented for antiactivator over-expression. Roughly equal amounts of protein were added to each well. Bands from each row are from separate gels and therefore may not be comparable. Blots are representative of replicate experiments. QteE, but not QslA, decreases the amount of active and soluble LasR Effects of antiactivators on AHL sensitivity could either be due to modification of R-protein-signal binding dynamics, or to direct modulation of active R-protein dimer levels through binding and sequestration. Given some previous evidence that QteE is known to destabilize LasR and RhlR dimers, and that QslA can bind LasR monomers to prevent LasR dimerization, we hypothesized the latter ( 11 – 13 ). To test this, we used Western blots to monitor the levels of LasR or RhlR in soluble and insoluble fractions of stationary phase culture cell lysates with deleted or over-expressed antiactivators ( Figure 3C ). Since active LasR and RhlR dimers are soluble in the cytoplasm while inactive LasR and RhlR monomers are not, measuring soluble and insoluble fractions separately provides a proxy for the levels of active and inactive R-protein dimers and monomers, respectively. Over-expressing qteE removes any LasR from the soluble fraction and dramatically increases levels of LasR present in the insoluble fraction ( Figure 3C ). In contrast, over-expressing qteE does not appear to markedly change RhlR levels in the insoluble fraction. No soluble RhlR can be observed in these blots, as is consistent with previous literature noting a lack of RhlR solubility in the absence of C4-HSL, but some insight may be gleaned from data on the insoluble fraction ( 32 , 33 ). These results indicate QteE largely functions by destabilizing soluble and active LasR dimers, as over-expressing qteE appears to force most LasR protein into the insoluble fraction. Interestingly, over-expressing qteE does not change the levels of RhlR in the insoluble fraction but deleting qteE appears to increase this fraction slightly relative to WT. On the other hand, over-expression of qslA has no marked effect on LasR levels or solubility. Over-expression of qslA does appear to change RhlR levels in the insoluble fraction, but it is unclear if this effect is independent of QslA effects on LasR. Overall, these results indicate that while QteE appears to decrease the amounts of active and soluble LasR and RhlR, QslA-mediated antiactivation may work via a different inhibitory mechanism. QteE, but not QslA, is regulated by LasR and RhlR As previous data has shown LasR and RhlR exhibit strong QS-regulated autoinduction, we considered that QteE and QslA, as factors important in QS activation, may also be transcriptionally regulated by QS. Previous microarray studies in PAO1 have suggested that qteE transcription may be repressed by QS under some conditions, but this result has not been substantiated in followup studies ( 7 , 15 ). To clarify the individual roles of LasR and RhlR on antiactivator regulation, we utilized qRT-PCR to measure mRNA transcript levels from either qteE or qslA in stationary phase cultures of PAO1, PAO Δ lasR , and PAO Δ rhlR (OD 600 = 2.0). We observed higher qteE ΔC t values in PAO Δ lasR and PAO Δ rhlR when compared to PAO1 ( Figure 4A ), indicating both R-proteins repress QteE transcription. In contrast, the absence of LasR or RhlR does not change qslA transcription significantly ( Figure 4B ). These results confirm a role for QS regulation of qteE , but not qslA . Download figure Open in new tab Figure 4: QS regulation of QteE or QslA. Expression of qteE (A) and qslA (B) in PAO1, PAO Δ lasR , and PAO Δ rhlR were measured with qRT-PCR. Differences in threshold cycle (ΔC t ) values are normalized to the housekeeping gene rplU . Data points represent biological replicates, with means and error bars indicating s.e.m. Significant differences of means compared between indicated strains were determined using an unpaired two-tailed t-test (α = 0.05). ns, p > 0.05; *, p ≤ 0.05; ***, p ≤ 0.001. QslA effects on QS phenotypes may depend on QteE Our results and previous literature indicate that QteE may exert its regulatory activity at lower cell densities and earlier in the QS cascade than QslA in PAO1, presenting the possibility that QS phenotypes delayed by the latter depend on the presence of QteE ( 11 – 13 ). Analysis of single and multiple antiactivator deletions in PAO1 suggest their effects on QS induction can be additive, but the dependence of QslA activity on qteE status has not been explored ( 15 ). We hypothesized that in the absence of QteE, the dampening effect of QslA on QS regulation and phenotypes would be reduced. We tested this idea by measuring two quorum-controlled virulence phenotypes in stationary phase cultures of a panel of PAO1-derivative mutants. Because the regulatory dependence in question would require a strain background capable of both LasR and RhlR QS, we used the PAO1 lab strain and analyzed phenotypes that are predominantly regulated by LasR (elastase) or RhlR (pyocyanin) in this lineage. We again used antiactivator deletion mutants and our separate chromosomal P araBAD -qteE and P araBAD -qslA over-expression constructs with arabinose supplementation to control antiactivation. As previous studies have demonstrated, deletions of qteE or qslA alone results in increases in both elastase activity and pyocyanin production ( Figure 5 ). Over-expressing qteE in PAO1 and PAO Δ qslA reveals complete abrogation of both elastase activity and pyocyanin production, equivalent to a QS-silent Δ lasR Δ rhlR mutant. Consistent with our hypothesis, over-expressing qslA in PAO1 reduces elastase activity (although not significant (p = 0.2185)) but doing so in PAO Δ qteE has no notable effect on elastase activity ( Figure 5A ). qslA over-expression does slightly reduce pyocyanin production in the context of a Δ qteE deletion mutant, but not significantly in PAO1 ( Figure 5B ). Download figure Open in new tab Figure 5: Antiactivator interdependency in QS-controlled phenotypes. (A) elastase activity and (B) pyocyanin production. Each assay was performed after 18 hours of growth (stationary phase cultures). “ ara-qslA ” and “ ara-qteE ” indicate the presence of an arabinose-inducible construct in the chromosome, and the culture was supplemented with 0.5% L-arabinose to trigger over-expression of the corresponding antiactivator. Values represent the mean of three biological replicates, and error bars represent s.e.m. Letters indicate statistically significant differences of means, as determined using an ordinary one-way ANOVA. Discussion P. aeruginosa uses QS to control gene expression underlying several important phenotypes and population-level behaviors, aiding this bacterium in nutrient acquisition, survival during stress, and virulence during infection ( 34 ). The effectiveness of P. aeruginosa QS in yielding these phenotypes is in part due to factors that tightly control circuit activation and target gene transcription, including several mechanisms that serve to dampen QS ( 3 , 11 , 12 , 35 ). Here, we focused on so-called “antiactivators” of QS: protein factors that interact directly with R-proteins to attenuate activation in populations below quorum. Our results support a model where antiactivation dynamics in P. aeruginosa are nuanced in both the specificity of antiactivator-LuxR-protein interactions, as well as the magnitude of their effects on QS activation. Separating the effects of antiactivation on RhlR from those on LasR has proved challenging due to the hierarchy of QS in laboratory strains. Furthermore, previous antiactivator studies that assess the kinetics of R-protein induction have measured lasB expression, as there is strong QS activation of this gene. The demonstrated promiscuity of the lasB promoter to allow both LasR and RhlR binding has made it difficult to dissect differing effects of antiactivation on the two regulons ( 15 , 36 ). This has a left a notable knowledge gap regarding the effects of antiactivation on RhlR QS. To address this gap, we analyzed the laboratory strain mutant PAO Δ lasR Δ mexT and clinical isolate E90, both demonstrating LasR-independent RhlR QS, alongside PAO1 to parse the individual effects of antiactivators on RhlR activity. Our results show a strong QteE-mediated antiactivation effect on RhlR in a variety of circumstances. Over-expressing qteE not only delays RhlR induction but completely abrogates this activity in all strains tested regardless of the LasR status of the strain. The strength of QteE antiactivation on RhlR was strong enough that even a 100-fold reduction in the typical concentration of arabinose used to induce our synthetic construct still produced significant dampening of target gene activation. It is then notable that deleting qteE in the two strains without LasR, PAO Δ lasR Δ mexT and E90, has no effect on P rhlA -gfp induction. We recognize that qteE may not be well-expressed in the strains with RhlR - dominated QS that we evaluated or may not be expressed in the conditions tested here. In contrast to QteE, over-expressing qslA only influenced RhlR activity in PAO1 and PAO Δ lasR Δ mexT , having no marked effect on RhlR activity in E90. It is intriguing that QslA modulates RhlR induction timing differently in two strain backgrounds exhibiting Las-independent QS. Expression of some RhlR-regulated genes is rescued in PAO Δ lasR Δ mexT via another QS pathway, the Pseudomonas quinolone signal (PQS) system ( 28 , 37 ). QslA could be interacting with the PQS receptor-regulator PqsR in PAO Δ lasR Δ mexT ; such an interaction has been demonstrated in the rhizosphere isolate PA1201 ( 38 ). Confirmation of this interaction in future studies would add another layer of complexity to the QS dynamics in some of the most widely-used laboratory strains of P. aeruginosa. Further investigation of the genomics and QS signaling diversity of additional P. aeruginosa clinical isolates may also further define the role of QslA in strains lacking LasR. We observe that QslA expression, as seen in previous studies of QteE, decreases the sensitivity of LasR and RhlR to their cognate signals ( 11 , 16 ). A potential explanation is that without these antiactivators to sequester inactive LasR and RhlR monomers, any R-protein that is produced can bind its cognate signal and become active without further inhibition, allowing a cell to short-circuit QS and “sense itself” regardless of cell and signal density. Careful experimentation by others at extremely low cell densities has revealed this to be true for the las system in subpopulations of cells, where some LasR gene targets exhibit expression that appears constitutive due to “self-sensing” in the absence of antiactivation ( 16 ). Indeed, we find that addition of the LasR-specific 3OC12-HSL signal to a Δ lasI Δ qslA mutant of PAO1 dramatically advances the induction of a LasR-specific promoter, even at levels 20-fold less than maximal WT signal production. A similar effect is observed with additions of the RhlR-specific C4-HSL signal to a Δ lasR Δ mexT Δ rhlI Δ qslA mutant, although the effect is subdued in comparison the las system. This may reflect a nuance with how RhlR and its cognate signal interact, as compared to most LuxR homologs: in strain PAO1, RhlR exhibits signal sensitivity and binding kinetics that are vastly different from most well-studied QS receptors, with the C4-HSL concentration required for half-maximal activity 50-times higher than any other LuxR protein analyzed ( 39 ). Our results expand the role of antiactivators in preventing self-sensing through LasR; QteE and QslA may also prevent RhlR self-sensing in strains that lack LasR. Our Western analysis shows that over-expression of qteE causes a complete loss of LasR in the soluble fraction and a substantive increase of LasR in the insoluble fraction. This corroborates previous literature that shows inducing qteE expression destabilizes LasR, and the increased insoluble LasR is likely targeted for degradation ( 11 ). Notably, over-expressing qteE has no effect on the level of RhlR in the insoluble fraction, but deleting it raises it. A potential explanation is that leakage from the P araBAD promoter used to trigger over-expression allows sufficient QteE production to attenuate RhlR at a saturating level. While previous work already showed that QteE destabilizes LasR proteins in whole cell lysates, here we provide additional evidence that QteE-mediated destablization may function by forcing inactive LasR monomers into the insoluble fraction ( 11 ). We also recognize that further investigation is needed to find an approach for analyzing RhlR stability in conditions where it retains more solubility, as the overall lack of RhlR solubility in lysates has been observed in other Western analyses. Availability of the C4-HSL signal is required for RhlR binding of target promoters, and addressing the dependence of RhlR solubility on C4-HSL may provide a pathway forward ( 5 ). On the other hand, over-expressing qslA does not markedly change soluble or insoluble levels of LasR; given some evidence that QslA binds inactive LasR monomers to prevent dimerization without necessarily targeting them for degradation, this is not surprising ( 12 , 13 ). While over-expressing qslA does change RhlR levels in the insoluble fraction, this may be due to a downstream effect of QslA attenuating LasR, and RhlR solubility issues may also complicate this interpretation. We sought to address the potential separate effects, if any, of QS regulation via LasR or RhlR on antiactivator expression. Our expression analysis in batch cultures demonstrate that LasR appears to repress transcription of qteE , but not qslA . The finding that qteE is repressed by LasR is in agreement with some previously published RNA transcriptome comparisons of PAO1 and a QS-null mutant ( 7 , 15 , 40 ). While Schuster et al . reported a 29-fold increase in qteE expression in an R-protein-deficient strain compared to WT PAO1 when both tested strains were grown in a rich media, two additional studies reported no change in qteE expression when the same strains were tested in more defined media ( 7 , 15 , 40 ). Given that each study was performed in different strain backgrounds, and with different media and growth phases, the contrast is somewhat unsurprising. The possibility that QteE is indirectly regulated by LasR and RhlR could also explain these differences and cannot be ruled out based on our data. However, a repressive effect of QS on the transcription and availability of QteE could provide P. aeruginosa further means for reinforcing an activated QS state by effectively silencing this mode of antiactivation. Our observation that RhlR is also regulated this way provides further strength for this interpretation. In this view, QteE acts to reinforce the bistability in P. aeruginosa QS response: while QteE is available to bind LasR or RhlR and help keep QS activation low in concordance with cell density, as the signal threshold is reached and QS becomes activated, QteE is in turn repressed to support the QS-active state. QslA does not appear to be QS-controlled, on the other hand. It is possible QslA may instead provide a more stable dampening effect on QS that is overcome upon activation, or this could be due to a general lack in native expression in the conditions of our experiments. The role of antiactivation in influencing heterogeneity in the QS response, particularly at the single-cell level, is a related area poised for active investigation. Heterogeneity in response between individual cells in a population is increasingly recognized as general feature of QS systems, and examples have been presented for both early and transient heterogeneity in the early phases of QS activation, as well as persistent heterogeneity through high cell densities and activation states ( 41 – 44 ). A recent study of the impacts of another negative regulator of QS, the transcriptional repressor of lasI/lasR, RsaL, revealed this repressor provides a degree of stochasticity in single-cell responses within the las system as a quorum threshold is approached ( 45 ). The same study reported greater homogeneity in responses in the rhl QS system, which lacks a transcriptional repressive mechanism analogous to RsaL. Further investigation of divergent QS systems lacking the RsaL- las dynamic, coupled with dissection of the differential regulation and effects of individual antiactivators, should offer utility to future studies of the origins and impacts of QS heterogeneity. We also find that QslA-mediated effects on quorum-controlled phenotypes show some dependence on QteE. Existing structural evidence combined with the lack of similarity between QteE and QslA sequences suggest antiactivators interact with R-proteins separately, yet the layered nature of QS regulation in P. aeruginosa leaves several opportunities for dependent effects. QteE acts to potently silence LasR early in the growth cycle of PAO1, so we expected to observe muted effects of QslA on downstream phenotypes owing to the QS hierarchy present in this strain. However, this effect was only true for elastase production: deletion of qteE does not remove the impact of excess QslA on pyocyanin production. We acknowledge that the magnitude of this effect could be due to levels of QslA not physiologically relevant to native QS systems, but the observed impact could be instructive. There is also reason to suspect nutrient or growth status may dictate how antiactivators affect the differential regulation of specific QS-controlled secretions. The LasR and RhlR regulators are embedded in a network of other regulatory components that push and pull on the activation threshold to tailor the QS response beyond just cell and signal density ( 46 ). The availability of specific macronutrients, for example, can alter the levels of corresponding QS-controlled secretions that contain the nutrient, likely via the stringent response ( 47 ). Pyocyanin production involves a complex phenazine biosynthesis pathway with additional inputs to regulation, particularly through regulators of the PQS system, which may also interact with QslA. Further investigation of the links between the rhl QS and PQS systems may provide further insight in this regard, as will definition of the response to physiological status by antiactivation mechanisms. Our results contribute additional detail to a general understanding of the complex circuitry of P. aeruginosa QS, underscoring a distinct role for QteE in the repression of RhlR QS activity. We demonstrate the differing mechanisms and regulation of QteE and QslA can have distinct consequences for LasR and RhlR function as cells transition from low to high cell densities, and that regulation of these mechanisms is also variable among divergent QS circuits. Our study illustrates that antiactivation is not a single repressive mechanism accomplished by several factors, rather individual antiactivators may have plenary effects on QS (QteE) or more targeted effects on specific R-proteins (QslA), providing finer tuning of QS activation for varying physiological states. Materials and Methods Culture conditions All strains and experimental cultures were grown at 37°C either on LB agar or in LB broth buffered with 50 mM 3-( N -morpholino)-propanesulfonic acid (MOPS), pH = 7.0, with shaking at 250 rpm. When necessary, growth media was supplemented with 100 μg/mL gentamicin or 200 μg/mL carbenicillin to select for marked P. aeruginosa strains, and 10 μg/mL gentamicin or 200 μg/mL carbenicillin to select for E. coli strains carrying plasmids. Reporter plasmids were maintained in P. aeruginosa cultures by growing strains in media supplemented with 100 μg/mL gentamicin. All strains assessed in Figures 1 and 2 grew normally ( Figures S3 and S4 ). Download figure Open in new tab Figure S1: Uncropped plots of those shown in Figure 2 . All data points show means of three biological replicates, and error bars represent s.e.m. Some error bars may not be visible. Download figure Open in new tab Figure S2: Uncropped blots of those shown in Figure 3 . Expected LasR (A, B) or RhlR (C, D) bands are indicated by arrows. Blots are indicative of replicated experiments. Download figure Open in new tab Figure S3: Growth curves of PAO1, PAO Δ lasR Δ mexT , and E90 as measured by OD 600 , under the experimental conditions shown in Figure 1 . All data points show means of three biological replicates, and error bars represent s.e.m. Some error bars may not be visible. Download figure Open in new tab Figure S4: Growth curves of PAO1 (A) and PAO Δ lasR Δ mexT (B) strains tested in Figure 2 , as measured by OD 600 . All data points show means of three biological replicates, and error bars represent s.e.m. Some error bars may not be visible. Strain and plasmid construction A full list of the strains used in this study is detailed in Table 1 . P. aeruginosa PAO1 (UW) or the EPIC isolate E90 were used as the parent strain for all strain construction ( 48 ). In all experiments, PAO1 was used as the wild-type control strain. PAO1, Δ lasR , Δ rhlR, Δ lasR Δ rhlR , and E90 were obtained from the Dandekar Lab at the University of Washington. PAO Δ qteE was obtained from R. Siehnel ( 11 ). The PAO Δ qslA , Δ lasI , and Δ rhlI deletion alleles were constructed using a pEXG2-based suicide delivery vector carried in Escherichia coli S17 following a two-step allelic exchange protocol ( 49 ). A pEXG2-Δ mexT plasmid was obtained from M. Kostylev ( 28 ). The deletion allele for all mutants consists of the first two residues and the last two residues of the protein of interest. Strains with over-expressed qteE or qslA were constructed by inserting an extra copy of the corresponding gene under P araBAD control (arabinose-inducible) into the P. aeruginosa chromosome at a neutral site using a mini-Tn7 mediated integration ( 50 ). Briefly, we cloned the mini-Tn7 machinery, the P araBAD sequence, and the CDS of either qteE or qslA into pUC19T using a modified Gibson Assembly ( 51 , 52 ). The Gm R marker on this plasmid was removed from successful transposon mutants using a Flp-mediated excision ( 50 ). In experimental cultures, over-expression was triggered by supplementing growth media with 0.5% arabinose unless stated otherwise. pPROBE-GT transcriptional reporters for lasI and rhlA were obtained from the Dandekar Lab. View this table: View inline View popup Download powerpoint Table 1: List of strains used in this study GFP Transcriptional Reporter Assays Transcriptional reporter assays were performed using a GFP promoter fusion of lasI or rhlA carried in pPROBE-GT. 18-hour endpoint assays were performed by inoculating experimental strains into 3 mL LB+MOPS, incubating with shaking for 18 hours, then measuring cell density (OD 600 ) and GFP fluorescence (λ excitation = 480 nm, λ emission = 535 nm, gain = 80). Data is reported as a ratio of GFP fluorescence to cell density. GFP time course assays were performed as previously described ( 53 ). Briefly, experimental strains were inoculated at OD 600 = 0.01 into 200 μL LB+MOPS in a black-walled 96-well plate which was incubated at 37°C with shaking. Cell density and fluorescence were measured at 15-minute intervals for 15 hours in a Biotek Synergy H1 microplate reader. GFP reporter activity for each timepoint was normalized to OD 600 of the corresponding strain, and experimental GFP/OD 600 values were corrected by subtraction from an empty promoter-less control pPROBE-GT plasmid. When performing experiments to assess qslA over-expression in E90, the 96-well plate was covered with a Breath Easy sealing membrane and incubated at 37°C with shaking for 7 hours in a standard shaking incubator before being measured in a microplate reader as described above. Statistical analysis of P rhlA -gfp induction timing was performed in GraphPad Prism by measuring time to half-maximal GFP for each replicate and performing an unpaired two-tailed t-test to compare strains of interest (α = 0.05). Growth curves of all strains analyzed were inspected to confirm no differences in growth dynamics were present ( Supplemental Figures S3 , S4 ). Western Blots Cell fractionation as well as the assessment of insoluble and soluble LasR and RhlR levels were performed as per a previously described protocol ( 3 ). Briefly, experimental strains were inoculated into 3 mL LB+MOPS and were incubated at 37°C with shaking for 18 hours. Cells were pelleted and resuspended in LasR Purification Buffer (25 mM Tris-HCL [pH 7.8], 150 mM NaCl, 1 mM dithiothreitol [DTT], 1 mM EDTA, 10% glycerol, 0.05% Tween 20) with added 2 μM 3OC12-HSL and 10 μM C4-HSL. Samples were set to the same OD 600 upon resuspension of the pellets to normalize the total protein content in each sample. Soluble and insoluble fractions were separated by sonicating samples and centrifuging at 55,000 g for 30 minutes at 4°C. The soluble fraction (supernatant) was removed, and the insoluble fraction (pellet) was resuspended in the same volume of LasR Purification Buffer with AHLs. 10 μL of the soluble and insoluble fractions were separated on a 4-12% Bis-Tris gel (Invitrogen). Separated proteins were transferred to a PVDF membrane and probed with polyclonal anti-LasR and anti-RhlR antibodies ( 3 ), then visualized using chemiluminescence detection reagents (Thermo Fisher Scientific). RNA extraction and qRT-PCR Experimental strains were inoculated into 25 mL LB+MOPS at OD 600 = 0.005 and incubated at 37°C with shaking in 125-mL baffled flasks. 1 mL of cells were harvested once the cultures reached OD 600 = 2.0 and immediately stabilized with RNAprotect Bacteria Reagent (Qiagen). The cells were then pelleted and frozen at -80°C until RNA extraction. Pellets were resuspended in QIAzol reagent (Qiagen) and mechanically lysed by bead-beating. RNA extraction was performed using column-based purification via a RNeasy Mini Kit (Qiagen). RNA samples were then treated with Turbo DNase (Invitrogen) and purified with a RNeasy MinElute Cleanup Kit (Qiagen). cDNA was synthesized using an iScript cDNA Synthesis Kit (Bio-Rad). Gene expression was measured using iQ SYBR Green SuperMix (Bio-Rad) on a CF96X real-time PCR thermocycler for 40 cycles. The housekeeping gene rplU was used as a reference gene. A list of primers used for qRT-PCR is detailed in Table 2 . Statistical analysis was performed using a two-tailed unpaired t-test in Graphpad Prism to compare means of expression levels between strains. View this table: View inline View popup Download powerpoint Table 2: List of primers used for qRT-PCR in this study. Elastase activity assays Elastase activity was measured using a variation on an elastin congo red (ECR) assay that allows for high throughput, as previously described ( 15 , 54 ). Briefly, experimental strains were inoculated into 800 μL LB+MOPS in 96-well deep-well blocks at OD 600 = 0.01 that were covered with Breath Easy sealing membranes and incubated at 37°C with shaking. After 18 hours, cells were pelleted at 4000 rpm for 10 minutes. 250 μL supernatant was filtered using 96-well filter plates, and 40 μL filtered supernatant was added to 360 μL ECR buffer (100 mM Tris, 1 mM CaCl 2 , pH = 7.5) with 20 mg/mL ECR. Samples were incubated with ECR in 96-well deep-well blocks and incubated at 37°C with shaking for 3 hours. Insoluble ECR was pelleted at 4000 rpm for 10 minutes, and 200 μL supernatant was transferred to 96-well plates and measured at ABS 495 with a microplate reader. Final absorbance values were normalized to OD 600 of the experimental cultures, and data is reported as fold change from WT samples. Statistical analysis was done in GraphPad Prism by performing an ordinary one-way ANOVA between all strains. Pyocyanin production assays Pyocyanin production was measured using a previously described procedure ( 55 ). Briefly, experimental strains were inoculated into 5 mL LB+MOPS at OD 600 = 0.01 in disposable 14 mL culture tubes (Falcon) and incubated at 37°C with shaking for 18 hours. Pyocyanin was extracted from the cultures using 3 mL chloroform, then extracted again from the organic phase with 660 μL 0.2 M HCl. 200 μL of the aqueous phase containing acidified pyocyanin was measured at ABS 520 with a microplate reader. Final absorbance values were normalized to OD 600 of the experimental cultures, and data is reported as fold change from WT samples. Statistical analysis was done in Graphpad Prism by performing an ordinary one-way ANOVA between all strains. Data availability All data used in this study is contained herein. Acknowledgments V.S. was funded in part by the CFF Student Traineeship Award SRIDHA20H0 and the Levinson Emerging Scholar Award at the University of Washington - Seattle. K.L.A was funded by CFF Fellowship ASFAHL19F0. A.A.D. was supported by NIH grants R01GM125714 and R35GM152107. Funder Information Declared Cystic Fibrosis Foundation, https://ror.org/00ax59295 , SRIDHA20H0 , ASFAHL19F0 National Institutes of Health, https://ror.org/01cwqze88 , R01GM125714 , R35GM152107 Footnotes Competing Interest Statement: The authors declare no competing interest References 1. ↵ Waters CM , Bassler BL . 2005 . Quorum sensing: cell-to-cell communication in bacteria . Annu Rev Cell Dev Biol 21 : 319 – 46 . OpenUrl CrossRef PubMed Web of Science 2. ↵ Fuqua C , Parsek MR , Greenberg EP . 2001 . Regulation of gene expression by cell-to-cell communication: acyl-homoserine lactone quorum sensing . Annu Rev Genet 35 : 439 – 68 . OpenUrl CrossRef PubMed Web of Science 3. ↵ Schuster M , Greenberg EP . 2007 . Early activation of quorum sensing in Pseudomonas aeruginosa reveals the architecture of a complex regulon . BMC Genomics 8 : 287 . OpenUrl CrossRef PubMed 4. ↵ Kiratisin P , Tucker KD , Passador L . 2002 . LasR, a transcriptional activator of Pseudomonas aeruginosa virulence genes, functions as a multimer . J Bacteriol 184 : 4912 – 9 . OpenUrl Abstract / FREE Full Text 5. ↵ Ventre I , Ledgham F , Prima V , Lazdunski A , Foglino M , Sturgis JN . 2003 . Dimerization of the quorum sensing regulator RhlR: development of a method using EGFP fluorescence anisotropy . Mol Microbiol 48 : 187 – 98 . OpenUrl CrossRef PubMed Web of Science 6. ↵ Latifi A , Foglino M , Tanaka K , Williams P , Lazdunski A . 1996 . A hierarchical quorum-sensing cascade in Pseudomonas aeruginosa links the transcriptional activators LasR and RhIR (VsmR) to expression of the stationary-phase sigma factor RpoS . Mol Microbiol 21 : 1137 – 46 . OpenUrl CrossRef PubMed Web of Science 7. ↵ Schuster M , Lostroh CP , Ogi T , Greenberg EP . 2003 . Identification, timing, and signal specificity of Pseudomonas aeruginosa quorum-controlled genes: a transcriptome analysis . J Bacteriol 185 : 2066 – 79 . OpenUrl Abstract / FREE Full Text 8. ↵ Fuqua C , Burbea M , Winans SC . 1995 . Activity of the Agrobacterium Ti plasmid conjugal transfer regulator TraR is inhibited by the product of the traM gene . J Bacteriol 177 : 1367 – 73 . OpenUrl Abstract / FREE Full Text 9. ↵ Hwang I , Cook DM , Farrand SK . 1995 . A new regulatory element modulates homoserine lactone-mediated autoinduction of Ti plasmid conjugal transfer . J Bacteriol 177 : 449 – 58 . OpenUrl Abstract / FREE Full Text 10. ↵ Swiderska A , Berndtson AK , Cha MR , Li L , Beaudoin GM , 3rd , Zhu J , Fuqua C. 2001 . Inhibition of the Agrobacterium tumefaciens TraR quorum-sensing regulator. Interactions with the TraM anti-activator . J Biol Chem 276 : 49449 – 58 . OpenUrl Abstract / FREE Full Text 11. ↵ Siehnel R , Traxler B , An DD , Parsek MR , Schaefer AL , Singh PK . 2010 . A unique regulator controls the activation threshold of quorum-regulated genes in Pseudomonas aeruginosa . Proc Natl Acad Sci U S A 107 : 7916 – 21 . OpenUrl Abstract / FREE Full Text 12. ↵ Seet Q , Zhang LH . 2011 . Anti-activator QslA defines the quorum sensing threshold and response in Pseudomonas aeruginosa . Mol Microbiol 80 : 951 – 65 . OpenUrl CrossRef PubMed 13. ↵ Fan H , Dong Y , Wu D , Bowler MW , Zhang L , Song H . 2013 . QsIA disrupts LasR dimerization in antiactivation of bacterial quorum sensing . Proc Natl Acad Sci U S A 110 : 20765 – 70 . OpenUrl Abstract / FREE Full Text 14. ↵ Sana TG , Lomas R , Gimenez MR , Laubier A , Soscia C , Chauvet C , Conesa A , Voulhoux R , Ize B , Bleves S . 2019 . Differential Modulation of Quorum Sensing Signaling through QslA in Pseudomonas aeruginosa Strains PAO1 and PA14 . J Bacteriol 201 . 15. ↵ Asfahl KL , Schuster M . 2017 . Additive Effects of Quorum Sensing Anti-Activators on Pseudomonas aeruginosa Virulence Traits and Transcriptome . Front Microbiol 8 : 2654 . OpenUrl CrossRef PubMed 16. ↵ Smith P , Schuster M . 2022 . Antiactivators prevent self-sensing in Pseudomonas aeruginosa quorum sensing . Proc Natl Acad Sci U S A 119 : e2201242119 . OpenUrl PubMed 17. ↵ Feltner JB , Wolter DJ , Pope CE , Groleau MC , Smalley NE , Greenberg EP , Mayer-Hamblett N , Burns J , Deziel E , Hoffman LR , Dandekar AA . 2016 . LasR Variant Cystic Fibrosis Isolates Reveal an Adaptable Quorum-Sensing Hierarchy in Pseudomonas aeruginosa . mBio 7 . 18. ↵ Groleau MC , Taillefer H , Vincent AT , Constant P , Deziel E . 2022 . Pseudomonas aeruginosa isolates defective in function of the LasR quorum sensing regulator are frequent in diverse environmental niches . Environ Microbiol 24 : 1062 – 1075 . OpenUrl CrossRef 19. ↵ Hoiby N , Ciofu O , Bjarnsholt T . 2010 . Pseudomonas aeruginosa biofilms in cystic fibrosis . Future Microbiol 5 : 1663 – 74 . OpenUrl CrossRef PubMed Web of Science 20. Rossi E , La Rosa R , Bartell JA , Marvig RL , Haagensen JAJ , Sommer LM , Molin S , Johansen HK . 2021 . Pseudomonas aeruginosa adaptation and evolution in patients with cystic fibrosis . Nat Rev Microbiol 19 : 331 – 342 . OpenUrl CrossRef PubMed 21. ↵ Davies JC . 2002 . Pseudomonas aeruginosa in cystic fibrosis: pathogenesis and persistence . Paediatr Respir Rev 3 : 128 – 34 . OpenUrl CrossRef PubMed 22. ↵ Smith EE , Buckley DG , Wu Z , Saenphimmachak C , Hoffman LR , D’Argenio DA , Miller SI , Ramsey BW , Speert DP , Moskowitz SM , Burns JL , Kaul R , Olson MV . 2006 . Genetic adaptation by Pseudomonas aeruginosa to the airways of cystic fibrosis patients . Proc Natl Acad Sci U S A 103 : 8487 – 92 . OpenUrl Abstract / FREE Full Text 23. ↵ Hoffman LR , Kulasekara HD , Emerson J , Houston LS , Burns JL , Ramsey BW , Miller SI . 2009 . Pseudomonas aeruginosa lasR mutants are associated with cystic fibrosis lung disease progression . J Cyst Fibros 8 : 66 – 70 . OpenUrl CrossRef PubMed Web of Science 24. ↵ Treggiari MM , Rosenfeld M , Mayer-Hamblett N , Retsch-Bogart G , Gibson RL , Williams J , Emerson J , Kronmal RA , Ramsey BW , Group ES . 2009 . Early anti-pseudomonal acquisition in young patients with cystic fibrosis: rationale and design of the EPIC clinical trial and observational study’ . Contemp Clin Trials 30 : 256 – 68 . OpenUrl CrossRef PubMed Web of Science 25. Cruz RL , Asfahl KL , Van den Bossch e S , Coenye T , Crabbe A , Dandekar AA . 2020 . RhlR-Regulated Acyl-Homoserine Lactone Quorum Sensing in a Cystic Fibrosis Isolate of Pseudomonas aeruginosa . mBio 11 . 26. Rosenfeld M , Emerson J , McNamara S , Joubran K , Retsch-Bogart G , Graff GR , Gutierrez HH , Kanga JF , Lahiri T , Noyes B , Ramsey B , Ren CL , Schechter M , Morgan W , Gibson RL , Sites ESGPC . 2010 . Baseline characteristics and factors associated with nutritional and pulmonary status at enrollment in the cystic fibrosis EPIC observational cohort . Pediatr Pulmonol 45 : 934 – 44 . OpenUrl CrossRef PubMed 27. ↵ Cruz RL , Freeman TS , Asfahl KL , Smalley NE , Dandekar AA . 2025 . RhlR-mediated cooperation in cystic fibrosis-adapted isolates of Pseudomonas aeruginosa . J Bacteriol 207 : e0034424 . OpenUrl PubMed 28. ↵ Kostylev M , Kim DY , Smalley NE , Salukhe I , Greenberg EP , Dandekar AA . 2019 . Evolution of the Pseudomonas aeruginosa quorum-sensing hierarchy . Proc Natl Acad Sci U S A 116 : 7027 – 7032 . OpenUrl Abstract / FREE Full Text 29. ↵ Khlebnikov A , Risa O , Skaug T , Carrier TA , Keasling JD . 2000 . Regulatable arabinose-inducible gene expression system with consistent control in all cells of a culture . J Bacteriol 182 : 7029 – 34 . OpenUrl Abstract / FREE Full Text 30. ↵ Ochsner UA , Fiechter A , Reiser J . 1994 . Isolation, characterization, and expression in Escherichia coli of the Pseudomonas aeruginosa rhlAB genes encoding a rhamnosyltransferase involved in rhamnolipid biosurfactant synthesis . J Biol Chem 269 : 19787 – 95 . OpenUrl Abstract / FREE Full Text 31. ↵ Medina G , Juarez K , Valderrama B , Soberon-Chavez G . 2003 . Mechanism of Pseudomonas aeruginosa RhlR transcriptional regulation of the rhlAB promoter . J Bacteriol 185 : 5976 – 83 . OpenUrl Abstract / FREE Full Text 32. ↵ McCready AR , Paczkowski JE , Cong JP , Bassler BL . 2019 . An autoinducer-independent RhlR quorum-sensing receptor enables analysis of RhlR regulation . PLoS Pathog 15 : e1007820 . OpenUrl PubMed 33. ↵ Boursier ME , Moore JD , Heitman KM , Shepardson-Fungairino SP , Combs JB , Koenig LC , Shin D , Brown EC , Nagarajan R , Blackwell HE . 2018 . Structure-Function Analyses of the N-Butanoyl l-Homoserine Lactone Quorum-Sensing Signal Define Features Critical to Activity in RhlR . ACS Chem Biol 13 : 2655 – 2662 . OpenUrl CrossRef PubMed 34. ↵ Schuster M , Sexton DJ , Diggle SP , Greenberg EP . 2013 . Acyl-homoserine lactone quorum sensing: from evolution to application . Annu Rev Microbiol 67 : 43 – 63 . OpenUrl CrossRef PubMed Web of Science 35. ↵ Rampioni G , Bertani I , Zennaro E , Polticelli F , Venturi V , Leoni L . 2006 . The quorum-sensing negative regulator RsaL of Pseudomonas aeruginosa binds to the lasI promoter . J Bacteriol 188 : 815 – 9 . OpenUrl Abstract / FREE Full Text 36. ↵ Pearson JP , Pesci EC , Iglewski BH . 1997 . Roles of Pseudomonas aeruginosa las and rhl quorum-sensing systems in control of elastase and rhamnolipid biosynthesis genes . J Bacteriol 179 : 5756 – 67 . OpenUrl Abstract / FREE Full Text 37. ↵ Tian ZX , Fargier E , Mac Aogain M , Adams C , Wang YP , O’Gara F . 2009 . Transcriptome profiling defines a novel regulon modulated by the LysR-type transcriptional regulator MexT in Pseudomonas aeruginosa . Nucleic Acids Res 37 : 7546 – 59 . OpenUrl CrossRef PubMed Web of Science 38. ↵ Fang YL , Chen B , Zhou L , Jin ZJ , Sun S , He YW . 2018 . The Anti-activator QslA Negatively Regulates Phenazine-1-Carboxylic Acid Biosynthesis by Interacting With the Quorum Sensing Regulator MvfR in the Rhizobacterium Pseudomonas aeruginosa Strain PA1201 . Front Microbiol 9 : 1584 . OpenUrl PubMed 39. ↵ Wellington S , Greenberg EP . 2019 . Quorum Sensing Signal Selectivity and the Potential for Interspecies Cross Talk . mBio 10 . 40. ↵ Wagner VE , Bushnell D , Passador L , Brooks AI , Iglewski BH . 2003 . Microarray analysis of Pseudomonas aeruginosa quorum-sensing regulons: effects of growth phase and environment . J Bacteriol 185 : 2080 – 95 . OpenUrl Abstract / FREE Full Text 41. ↵ Anetzberger C , Pirch T , Jung K . 2009 . Heterogeneity in quorum sensing-regulated bioluminescence of Vibrio harveyi . Mol Microbiol 73 : 267 – 77 . OpenUrl CrossRef PubMed 42. Garmyn D , Gal L , Briandet R , Guilbaud M , Lemaitre JP , Hartmann A , Piveteau P . 2011 . Evidence of autoinduction heterogeneity via expression of the Agr system of Listeria monocytogenes at the single-cell level . Appl Environ Microbiol 77 : 6286 – 9 . OpenUrl Abstract / FREE Full Text 43. Grote J , Krysciak D , Schorn A , Dahlke RI , Soonvald L , Muller J , Hense BA , Schwarzfischer M , Sauter M , Schmeisser C , Streit WR . 2014 . Evidence of autoinducer-dependent and -independent heterogeneous gene expression in Sinorhizobium fredii NGR234 . Appl Environ Microbiol 80 : 5572 – 82 . OpenUrl Abstract / FREE Full Text 44. ↵ Pradhan BB , Chatterjee S . 2014 . Reversible non-genetic phenotypic heterogeneity in bacterial quorum sensing . Mol Microbiol 92 : 557 – 69 . OpenUrl CrossRef PubMed 45. ↵ Mellini M , Letizia M , Caruso L , Guiducci A , Meneghini C , Heeb S , Williams P , Camara M , Visca P , Imperi F , Leoni L , Rampioni G . 2023 . RsaL-driven negative regulation promotes heterogeneity in Pseudomonas aeruginosa quorum sensing . mBio 14 : e0203923 . OpenUrl PubMed 46. ↵ Schuster M , Greenberg EP . 2006 . A network of networks: quorum-sensing gene regulation in Pseudomonas aeruginosa . Int J Med Microbiol 296 : 73 – 81 . OpenUrl CrossRef PubMed Web of Science 47. ↵ Mellbye B , Schuster M . 2014 . Physiological framework for the regulation of quorum sensing-dependent public goods in Pseudomonas aeruginosa . J Bacteriol 196 : 1155 – 64 . OpenUrl Abstract / FREE Full Text 48. ↵ Stover CK , Pham XQ , Erwin AL , Mizoguchi SD , Warrener P , Hickey MJ , Brinkman FS , Hufnagle WO , Kowalik DJ , Lagrou M , Garber RL , Goltry L , Tolentino E , Westbrock-Wadman S , Yuan Y , Brody LL , Coulter SN , Folger KR , Kas A , Larbig K , Lim R , Smith K , Spencer D , Wong GK , Wu Z , Paulsen IT , Reizer J , Saier MH , Hancock RE , Lory S , Olson MV . 2000 . Complete genome sequence of Pseudomonas aeruginosa PAO1, an opportunistic pathogen . Nature 406 : 959 – 64 . OpenUrl CrossRef PubMed Web of Science 49. ↵ Hmelo LR , Borlee BR , Almblad H , Love ME , Randall TE , Tseng BS , Lin C , Irie Y , Storek KM , Yang JJ , Siehnel RJ , Howell PL , Singh PK , Tolker-Nielsen T , Parsek MR , Schweizer HP , Harrison JJ . 2015 . Precision-engineering the Pseudomonas aeruginosa genome with two-step allelic exchange . Nat Protoc 10 : 1820 – 41 . OpenUrl CrossRef PubMed 50. ↵ Choi KH , Schweizer HP . 2006 . mini-Tn7 insertion in bacteria with single attTn7 sites: example Pseudomonas aeruginosa . Nat Protoc 1 : 153 – 61 . OpenUrl CrossRef PubMed 51. ↵ Norrander J , Kempe T , Messing J . 1983 . Construction of improved M13 vectors using oligodeoxynucleotide-directed mutagenesis . Gene 26 : 101 – 6 . OpenUrl CrossRef PubMed Web of Science 52. ↵ Kostylev M , Otwell AE , Richardson RE , Suzuki Y . 2015 . Cloning Should Be Simple: Escherichia coli DH5alpha-Mediated Assembly of Multiple DNA Fragments with Short End Homologies . PLoS One 10 : e0137466 . OpenUrl CrossRef PubMed 53. ↵ Gupta R , Schuster M . 2013 . Negative regulation of bacterial quorum sensing tunes public goods cooperation . ISME J 7 : 2159 – 68 . OpenUrl CrossRef PubMed 54. ↵ Diggle SP , Winzer K , Lazdunski A , Williams P , Camara M . 2002 . Advancing the quorum in Pseudomonas aeruginosa : MvaT and the regulation of N-acylhomoserine lactone production and virulence gene expression . J Bacteriol 184 : 2576 – 86 . OpenUrl Abstract / FREE Full Text 55. ↵ Essar DW , Eberly L , Hadero A , Crawford IP . 1990 . Identification and characterization of genes for a second anthranilate synthase in Pseudomonas aeruginosa: interchangeability of the two anthranilate synthases and evolutionary implications . J Bacteriol 172 : 884 – 900 . OpenUrl Abstract / FREE Full Text View the discussion thread. Back to top Previous Next Posted November 01, 2025. Download PDF Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. 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