Biology subjects

Paczkowski, J.

Publications and source records attributed to Paczkowski, J..

5 recordsLinked to original sources

bioRxiv2026

Proteolytic feedback of quorum sensing promotes infection by Pseudomonas aeruginosa

Quorum sensing (QS) enables bacteria to coordinate collective behaviors in response to population density. However, the mechanisms by which QS circuits are reset or attenuated remain poorly understood. In Pseudomonas aeruginosa, the LuxR-type transcription factor RhlR controls virulence gene expression at high cell density, requiring both its cognate acyl-homoserine lactone signal and the accessory protein PqsE for full activity. Here, we show that RhlR abundance is actively controlled by ATP-dependent proteolysis through a self-limiting negative feedback loop. We identify an N-terminal degron within RhlR that is protected from protease recognition by PqsE binding and is required for degradation by both the Lon and the ClpP1-ClpP2 protease complex. Removal of this degron stabilizes RhlR, advancing the timing of QS-regulated gene expression, enhancing biofilm formation, imposes a competitive fitness cost in vitro, and reduced virulence in an acute mouse lung infection. Mechanistically, RhlR directly activates transcription of clpP2, encoding a subunit of the protease complex required for its own degradation, establishing a self-limiting negative feedback loop. Disruption of RhlR DNA binding stabilizes the receptor through dual effects on reduced clpP2 expression and increased PqsE availability via the loss of RhlR-dependent repression of pqsE. Together, these findings reveal proteolytic turnover as an underappreciated regulatory layer of QS-activation and establish a mechanism for how receptor turnover may facilitate the transition away from high-cell density states.

microbiology↗

bioRxiv2024

Pseudomonas aeruginosa Alkyl Quinolone Response is dampened by Enterococcus faecalis

The bacterium Pseudomonas aeruginosa is an opportunistic pathogen that can cause lung, skin, wound, joint, urinary tract, and eye infections. While P. aeruginosa is known to exhibit a robust competitive response towards other bacterial species, this bacterium is frequently identified in polymicrobial infections where multiple species survive. For example, in prosthetic joint infections (PJIs), P. aeruginosa can be identified along with other pathogenic bacteria including Staphylococcus aureus, Enterococcus faecalis, and Corynebacterium striatum. Here we have explored the survival and behavior of such microbes and find that E. faecalis readily survives culturing with P. aeruginosa while other tested species do not. In each of the tested conditions, E. faecalis growth remained unchanged by the presence of P. aeruginosa, indicating a unique mutualistic interaction between the two species. We find that E. faecalis proximity leads P. aeruginosa to attenuate competitive behaviors as exemplified by reduced production of Pseudomonas quinolone signal (PQS) and pyocyanin. Reduced alkyl quinolones is important to E. faecalis as it will grow in supernatant from a quinolone mutant but not P. aeruginosa wildtype in planktonic culture. The reduced pyocyanin production of P. aeruginosa is attributable to production of ornithine by E. faecalis, which we recapitulate by adding exogenous ornithine to P. aeruginosa mono-cultures. Similarly, co-culture with an ornithine-deficient strain of E. faecalis leads P. aeruginosa to yield near mono-culture amounts of pyocyanin. Here, we directly demonstrate how notorious pathogens such as P. aeruginosa might persist in polymicrobial infections under the influence of metabolites produced by other bacterial species. ImportanceWhile we now appreciate that many infections are polymicrobial, we understand little of the specific actions between a given set of microbes to enable combinatorial survival and pathogenesis. The bacteria Pseudomonas aeruginosa and Enterococcus faecalis are both prevalent pathogens in wound, urinary tract, and bacteremic infections. While P. aeruginosa often kills other species in standard laboratory culture conditions, we present here that E. faecalis can be reliably co-cultured with P. aeruginosa. We specifically detail that ornithine produced by E. faecalis reduces the Pseudomonas Quinolone Signal response of P. aeruginosa. This reduction of the Pseudomonas Quinolone Signal response aids E. faecalis growth.

microbiology↗

bioRxiv2024

Ligand binding determines proteolytic stability of Vibrio LuxR/HapR quorum sensing transcription factors

In Vibrio species, quorum sensing signaling culminates in the production of the master transcription factor SmcR that regulates group behavior genes in a density-dependent manner. Previously, we identified a small molecule thiophenesulfonamide inhibitor called PTSP that targets the SmcR family of proteins and blocks activity in vivo. Here, we used structure-function analyses to identify eight PTSP-interacting residues in the ligand binding pocket that are required for PTSP inhibition of Vibrio vulnificus SmcR. Binding of PTSP to SmcR drives allosteric unfolding of the N-terminal DNA-binding domain and, in this state, SmcR is degraded by the ClpAP protease. SmcR degradation controls the timing of the phenotypic switch between high and low cell density, and strains expressing degradation-resistant smcR alleles are impervious to changes in cell density state. These studies implicate ligand binding as a mediator of SmcR protein stability and function, which dictates the timing of quorum sensing gene expression in three Vibrio pathogens. Significance StatementSmcR family proteins were discovered in the 1990s as central regulators of quorum sensing gene expression and later discovered to be conserved in all studied Vibrio species. SmcR homologs regulate a wide range of genes involved in pathogenesis, including but not limited to genes involved in biofilm production and toxin secretion. As archetypal members of the broad class of TetR-type transcription factors, each SmcR type protein has a predicted ligand binding pocket. However, no ligand has been identified for these proteins that control their function as regulators. Here, we used SmcR-specific chemical inhibitors to determine that ligand binding drives proteolytic degradation in vivo, the first demonstration of SmcR function connected to ligand binding for this historical protein family.

microbiology↗

bioRxiv2023

Promoter selectivity of the RhlR quorum-sensing transcription factor receptor in Pseudomonas aeruginosa is coordinated by distinct and overlapping dependencies on C4-homoserine lactone and PqsE

Quorum sensing is a mechanism of bacterial cell-cell communication that relies on the production and detection of small molecule autoinducers, which facilitate the synchronous expression of genes involved in group behaviors, such as virulence factor production and biofilm formation. The Pseudomonas aeruginosa quorum sensing network consists of multiple interconnected transcriptional regulators, with the transcription factor, RhlR, acting as one of the main drivers of quorum sensing behaviors. RhlR is a LuxR-type transcription factor that regulates its target genes when bound to its cognate autoinducer, C4-homoserine lactone, which is synthesized by RhlI. RhlR function is also regulated by the metallo-{beta}-hydrolase enzyme, PqsE. We recently showed that PqsE binds RhlR to alter its affinity for promoter DNA, a new mechanism of quorum-sensing receptor activation. Here, we perform ChIP-seq analyses of RhlR to map the binding of RhlR across the P. aeruginosa genome, and to determine the impact of C4-homoserine lactone and PqsE on RhlR binding to different sites across the P. aeruginosa genome. We identify 40 RhlR binding sites, all but three of which are associated with genes known to be regulated by RhlR. C4-homoserine lactone is required for maximal binding of RhlR to many of its DNA sites. Moreover, C4-homoserine lactone is required for maximal RhlR-dependent transcription activation from all sites, regardless of whether it impacts RhlR binding to DNA. PqsE is required for maximal binding of RhlR to many DNA sites, with similar effects on RhlR-dependent transcription activation from those sites. However, the effects of PqsE on RhlR specificity are distinct from those of C4-homoserine lactone, and PqsE is sufficient for RhlR binding to some DNA sites in the absence of C4-homoserine lactone. Together, C4-homoserine lactone and PqsE are required for RhlR binding at the large majority of its DNA sites. Thus, our work reveals three distinct modes of activation by RhlR: i) when RhlR is unbound by autoinducer but bound by PqsE, ii) when RhlR is bound by autoinducer but not bound by PqsE, and iii) when RhlR is bound by both autoinducer and PqsE, establishing a stepwise mechanism for the progression of the RhlR-RhlI-PqsE quorum sensing pathway in P. aeruginosa. AUTHOR SUMMARYPseudomonas aeruginosa represents a serious threat to public health in the United States because of its intrinsic mechanisms of antimicrobial resistance. One of the primary drivers of its antimicrobial resistance profile is biofilm formation. Biofilms are multicellular communities that are formed in an ordered mechanism by the collective. In the case of P. aeruginosa, biofilm formation is controlled by a cell-cell communication process called quorum sensing. Quorum sensing underpins transcriptional changes in a bacterium that allows for the transition from individual, planktonic behaviors to group, sessile behaviors. Group behaviors are behaviors that are only beneficial to engage in once a critical threshold of kin population is reached. The transition to group behaviors is mediated by quorum sensing through an interconnected regulatory system, with the transcription factor receptor RhlR regulating the expression of hundreds of genes. RhlR-dependent transcription relies on the detection of a ligand produced by its partner synthase, RhlI, and an accessory binding protein that alters its affinity for promoter DNA, PqsE, resulting in a dual regulatory mechanism that was not previously observed in quorum sensing. The main goal of this study was to determine the molecular basis for promoter selection by RhlR using bacterial genetics and DNA-based sequencing methods for measuring site-specific protein binding. Our approach established the entirety of the RhlR direct regulon and the contributions of each of the known regulators to RhlR-dependent promoter binding and gene regulation.

microbiology↗

bioRxiv2021

Towns and Trails Drive Carnivore Connectivity using a Step Selection Approach

Global increases in human activity threaten connectivity of animal populations. Protection and restoration of animal movement corridors requires robust models to forecast the effects of human activity on connectivity. Recent advances in the field of animal movement ecology and step selection functions offer new approaches for estimating connectivity. We show how a combination of hidden Markov movement models and step selection functions can be used to simulate realistic movement paths with multiple behavioral states. Simulated paths can be used to generate utilization distributions and estimate changes in connectivity for multiple land use scenarios. We applied movement models to 20 years of grizzly bear (Ursus arctos) and gray wolf (Canis lupus) data collected in and around Banff National Park, Canada. These carnivores avoided areas near towns in all seasons, avoided areas of high trail density in most seasons, and campgrounds during summer and fall. We simulated movement paths for three landscape scenarios: reference conditions with no anthropogenic development, current conditions, and future conditions with expanded town footprints and trail networks. We counted the number of paths that crossed valley-wide, digital transects through mountain tourist towns of Banff and Canmore, Alberta. We divided current and future crossing rates by the reference crossing rates to estimate connectivity. Current connectivity rates ranged between 7 and 45% of reference values with an average of 21% for grizzly bears and 25% for wolves. Potential town expansion and increased development of trails further decreased connectivity an average of 6% in future scenarios. Anthropogenic developments reduced the amount of available high quality large carnivore habitat in the Bow Valley by an average of 14% under current conditions and 16% under future conditions. Our approach for estimating connectivity provides a robust and flexible method for combining movement models with step selection analyses to estimate connectivity for a variety of species.

ecology↗