The plant compound rosmarinic acid induces a broad quorum sensing response in Pseudomonas aeruginosa PAO1

Systematic mapping of chemoreceptor specificities for Pseudomonas aeruginosa

IMPORTANCE

Chemotaxis of motile bacteria has multiple physiological functions. It enables bacteria to locate optimal ecological niches, mediates collective behaviors, and can play an important role in infection. These multiple functions largely depend on ligand specificities of chemoreceptors, and the number and identities of chemoreceptors show high diversity between organisms. Similar diversity is observed for the spectra of chemoeffectors, which include not only chemicals of high metabolic value but also bacterial, plant, and animal signaling molecules. However, the systematic identification of chemoeffectors and their mapping to specific chemoreceptors remains a challenge. Here, we combined several in vivo and in vitro approaches to establish a systematic screening strategy for the identification of receptor ligands and we applied it to identify a number of new physiologically relevant chemoeffectors for the important opportunistic human pathogen P. aeruginosa. This strategy can be equally applicable to map specificities of sensory domains from a wide variety of receptor types and bacteria.

Quorum sensing interference by phenolic compounds - A matter of bacterial misunderstanding

Over the past decade, numerous publications have emerged in the literature focusing on the inhibition of quorum sensing (QS) by plant extracts and phenolic compounds. However, there is still a scarcity of studies that delve into the specific mechanisms by which these compounds inhibit QS. Thus, our question is whether phenolic compounds can inhibit QS in a specific or indirect manner and to elucidate the underlying mechanisms involved. This study is focused on the most studied QS system, namely, autoinducer type 1 (AI-1), represented by N-acyl-homoserine lactone (AHL) signals and the AHL-mediated QS responses. Here, we analyzed the recent literature in order to understand how phenolic compounds act at the cellular level, at sub-inhibitory concentrations, and evaluated by which QS inhibition mechanisms they may act. The biotechnological application of QS inhibitors holds promising prospects for the pharmaceutical and food industries, serving as adjunct therapies and in the prevention of biofilms on various surfaces.

The Molecular Architecture of Pseudomonas aeruginosa Quorum-Sensing Inhibitors

The survival selection pressure caused by antibiotic-mediated bactericidal and bacteriostatic activity is one of the important inducements for bacteria to develop drug resistance. Bacteria gain drug resistance through spontaneous mutation so as to achieve the goals of survival and reproduction. Quorum sensing (QS) is an intercellular communication system based on cell density that can regulate bacterial virulence and biofilm formation. The secretion of more than 30 virulence factors of P. aeruginosa is controlled by QS, and the formation and diffusion of biofilm is an important mechanism causing the multidrug resistance of P. aeruginosa, which is also closely related to the QS system. There are three main QS systems in P. aeruginosa: las system, rhl system, and pqs system. Quorum-sensing inhibitors (QSIs) can reduce the toxicity of bacteria without affecting the growth and enhance the sensitivity of bacterial biofilms to antibiotic treatment. These characteristics make QSIs a popular topic for research and development in the field of anti-infection. This paper reviews the research progress of the P. aeruginosa quorum-sensing system and QSIs, targeting three QS systems, which will provide help for the future research and development of novel quorum-sensing inhibitors.

Mechanisms, Anti-Quorum-Sensing Actions, and Clinical Trials of Medicinal Plant Bioactive Compounds against Bacteria: A Comprehensive Review

Bacterial strains have developed an ability to resist antibiotics via numerous mechanisms. Recently, researchers conducted several studies to identify natural bioactive compounds, particularly secondary metabolites of medicinal plants, such as terpenoids, flavonoids, and phenolic acids, as antibacterial agents. These molecules exert several mechanisms of action at different structural, cellular, and molecular levels, which could make them candidates or lead compounds for developing natural antibiotics. Research findings revealed that these bioactive compounds can inhibit the synthesis of DNA and proteins, block oxidative respiration, increase membrane permeability, and decrease membrane integrity. Furthermore, recent investigations showed that some bacterial strains resist these different mechanisms of antibacterial agents. Researchers demonstrated that this resistance to antibiotics is linked to a microbial cell-to-cell communication system called quorum sensing (QS). Consequently, inhibition of QS or quorum quenching is a promising strategy to not only overcome the resistance problems but also to treat infections. In this respect, various bioactive molecules, including terpenoids, flavonoids, and phenolic acids, exhibit numerous anti-QS mechanisms via the inhibition of auto-inducer releases, sequestration of QS-mediated molecules, and deregulation of QS gene expression. However, clinical applications of these molecules have not been fully covered, which limits their use against infectious diseases. Accordingly, the aim of the present work was to discuss the role of the QS system in bacteria and its involvement in virulence and resistance to antibiotics. In addition, the present review summarizes the most recent and relevant literature pertaining to the anti-quorum sensing of secondary metabolites and its relationship to antibacterial activity.

A catalogue of signal molecules that interact with sensor kinases, chemoreceptors and transcriptional regulators

Bacteria have evolved many different signal transduction systems that sense signals and generate a variety of responses. Generally, most abundant are transcriptional regulators, sensor histidine kinases and chemoreceptors. Typically, these systems recognize their signal molecules with dedicated ligand-binding domains (LBDs), which, in turn, generate a molecular stimulus that modulates the activity of the output module. There are an enormous number of different LBDs that recognize a similarly diverse set of signals. To give a global perspective of the signals that interact with transcriptional regulators, sensor kinases and chemoreceptors, we manually retrieved information on the protein-ligand interaction from about 1,200 publications and 3D structures. The resulting 811 proteins were classified according to the Pfam family into 127 groups. These data permit a delineation of the signal profiles of individual LBD families as well as distinguishing between families that recognize signals in a promiscuous manner and those that possess a well-defined ligand range. A major bottleneck in the field is the fact that the signal input of many signaling systems is unknown. The signal repertoire reported here will help the scientific community design experimental strategies to identify the signaling molecules for uncharacterised sensor proteins.

Phloretin, an Apple Phytoalexin, Affects the Virulence and Fitness of Pectobacterium brasiliense by Interfering With Quorum-Sensing

The effects of phloretin a phytoalexin from apple, was tested on Pectobacterium brasiliense (Pb1692), an emerging soft-rot pathogen of potato. Exposure of Pb1692 to 0.2 mM phloretin a concentration that does not affect growth, or to 0.4 mM a 50% growth inhibiting concentration (50% MIC), reduced motility, biofilm formation, secretion of plant cell wall-degrading enzymes, production of acyl-homoserine lactone (AHL) signaling molecules and infection, phenotypes that are associated with bacterial population density-dependent system known as quorum sensing (QS). To analyze the effect of growth inhibition on QS, the activity of ciprofloxacin, an antibiotic that impairs cell division, was compared to that of phloretin at 50% MIC. Unlike phloretin, the antibiotic hardly affected the tested phenotypes. The use of DH5α, a QS-negative Escherichia coli strain, transformed with an AHL synthase (ExpI) from Pb1692, allowed to validate direct inhibition of AHL production by phloretin, as demonstrated by two biosensor strains, Chromobacterium violaceaum (CV026) and E. coli (pSB401). Expression analysis of virulence-related genes revealed downregulation of QS-regulated genes (expI, expR, luxS, rsmB), plant cell wall degrading enzymes genes (pel, peh and prt) and motility genes (motA, fim, fliA, flhC and flhD) following exposure to both phloretin concentrations. The results support the inhibition of ExpI activity by phloretin. Docking simulations were used to predict the molecular associations between phloretin and the active site of ExpI, to suggest a likely mode of action for the compound's inhibition of virulence.

Chemotaxis of Beneficial Rhizobacteria to Root Exudates: The First Step towards Root-Microbe Rhizosphere Interactions

Chemotaxis, the ability of motile bacteria to direct their movement in gradients of attractants and repellents, plays an important role during the rhizosphere colonization by rhizobacteria. The rhizosphere is a unique niche for plant-microbe interactions. Root exudates are highly complex mixtures of chemoeffectors composed of hundreds of different compounds. Chemotaxis towards root exudates initiates rhizobacteria recruitment and the establishment of bacteria-root interactions. Over the last years, important progress has been made in the identification of root exudate components that play key roles in the colonization process, as well as in the identification of the cognate chemoreceptors. In the first part of this review, we summarized the roles of representative chemoeffectors that induce chemotaxis in typical rhizobacteria and discussed the structure and function of rhizobacterial chemoreceptors. In the second part we reviewed findings on how rhizobacterial chemotaxis and other root-microbe interactions promote the establishment of beneficial rhizobacteria-plant interactions leading to plant growth promotion and protection of plant health. In the last part we identified the existing gaps in the knowledge and discussed future research efforts that are necessary to close them.

Genomic context of the two integrons of ST-111 Pseudomonas aeruginosa AG1: A VIM-2-carrying old-acquaintance and a novel IMP-18-carrying integron

Pseudomonas aeruginosa is an opportunist and versatile organism responsible for infections mainly in immunocompromised hosts. This pathogen has high intrinsic resistance to most antimicrobials. P. aeruginosa AG1 (PaeAG1) is a Costa Rican high-risk ST-111 strain with resistance to multiple antibiotics, including carbapenems, due to the activity of VIM-2 and IMP-18 metallo-β-lactamases (MBLs). These genes are harbored in two class 1 integrons located inone out of the 57 PaeAG1 genomic islands. However, the genomic context associated to these determinants in PaeAG1 and other P. aeruginosa strains is unclear. Thus, we first assessed the transcriptional activity of VIM-2 and IMP-18 genes when exposed to imipenem (a carbapenem) by RT-qPCR. To select related genomes to PaeAG1, we implemented a pan-genome analysis to define and up-date the phylogenetic relationship among complete P. aeruginosa genomes. We also studied the PaeAG1 genomic islands content in the related strains and finally we described the architecture and possible evolutionary steps of the genomic regions around the VIM-2- and IMP-18-carrying integrons. Expression of VIM-2 and IMP-18 genes was demonstrated to be induced after imipenem exposure. In a subsequent comparative genomics analysis with 211 strains, the P. aeruginosa pan-genome revealed that complete genome sequences are able to separate clones by MLST profile, including a clear ST-111 cluster with PaeAG1. The PaeAG1 genomic islands were found to define a diverse presence/absence pattern among related genomes. Finally, landscape reconstruction of genomic regions showed that VIM-2-carrying integron (In59-like) is an old-acquaintance element harbored in the same known region found in other two ST-111 strains. Also, PaeAG1 has an exclusive genomic region containing a novel IMP-18-carrying integron (registered as In1666), with an arrangement never reported before. Altogether, we provide new insights about the genomic determinants associated with the resistance to carbapenems in this high-risk P. aeruginosa using comparative genomics.

Molecular Determinants of Antibiotic Resistance in the Costa Rican Pseudomonas aeruginosa AG1 by a Multi-omics Approach: A Review of 10 Years of Study

Pseudomonas aeruginosa AG1 (PaeAG1) is a Costa Rican strain that was isolated in 2010 in a major Hospital. This strain has resistance to multiple antibiotics such as β-lactams (including carbapenems), aminoglycosides, and fluoroquinolones. PaeAG1 is considered critical (Priority 1) due to its resistance to carbapenems, and it was the first report of a P. aeruginosa isolate carrying both VIM-2 and IMP-18 genes encoding for metallo-β-lactamases (MBL) enzymes (both with carbapenemase activity). Owing to these traits, we have studied this model for 10 years using diverse approaches including multi-omics. In this review, we summarize the main points of the different steps that we have studied in PaeAG1: preliminary analyses of this strain at the genomic and phenomic levels revealed that this microorganism has particular features of antibiotic resistance. In the multi-omics approach, the genome assembly was the initial step to identify the genomic determinants of this strain, including virulence factors, antibiotic resistance genes, as well as a complex accessory genome. Second, a comparative genomic approach was implemented to define and update the phylogenetic relationship among complete P. aeruginosa genomes, the genomic island content in other strains, and the architecture of the two MBL-carrying integrons. Third, the proteomic profile of PaeAG1 was studied after exposure to antibiotics using 2-dimensional gel electrophoresis (2D-GE). Fourth, to study the central response to multiple perturbations in P. aeruginosa, i.e., the core perturbome, a machine learning approach was used. The analysis revealed biological functions and determinants that are shared by different disturbances. Finally, to evaluate the effects of ciprofloxacin (CIP) on PaeAG1, a growth curve comparison, differential expression analysis (RNA-Seq), and network analysis were performed. Using the results of the core perturbome (pathways that also were found in this perturbation with CIP), it was possible to identify the “exclusive” response and determinants of PaeAG1 after exposure to CIP. Altogether, after a decade of study using a multi-omics approach (at genomics, comparative genomics, perturbomics, transcriptomics, proteomics, and phenomics levels), we have provided new insights about the genomic and transcriptomic determinants associated with antibiotic resistance in PaeAG1. These results not only partially explain the high-risk condition of this strain that enables it to conquer nosocomial environments and its multi-resistance profile, but also this information may eventually be used as part of the strategies to fight this pathogen.

Transcriptomic determinants of the response of ST-111 Pseudomonas aeruginosa AG1 to ciprofloxacin identified by a top-down systems biology approach

Pseudomonas aeruginosa is an opportunistic pathogen that thrives in diverse environments and causes a variety of human infections. Pseudomonas aeruginosa AG1 (PaeAG1) is a high-risk sequence type 111 (ST-111) strain isolated from a Costa Rican hospital in 2010. PaeAG1 has both blaVIM-2 and blaIMP-18 genes encoding for metallo-β-lactamases, and it is resistant to β-lactams (including carbapenems), aminoglycosides, and fluoroquinolones. Ciprofloxacin (CIP) is an antibiotic commonly used to treat P. aeruginosa infections, and it is known to produce DNA damage, triggering a complex molecular response. In order to evaluate the effects of a sub-inhibitory CIP concentration on PaeAG1, growth curves using increasing CIP concentrations were compared. We then measured gene expression using RNA-Seq at three time points (0, 2.5 and 5 h) after CIP exposure to identify the transcriptomic determinants of the response (i.e. hub genes, gene clusters and enriched pathways). Changes in expression were determined using differential expression analysis and network analysis using a top–down systems biology approach. A hybrid model using database-based and co-expression analysis approaches was implemented to predict gene–gene interactions. We observed a reduction of the growth curve rate as the sub-inhibitory CIP concentrations were increased. In the transcriptomic analysis, we detected that over time CIP treatment resulted in the differential expression of 518 genes, showing a complex impact at the molecular level. The transcriptomic determinants were 14 hub genes, multiple gene clusters at different levels (associated to hub genes or as co-expression modules) and 15 enriched pathways. Down-regulation of genes implicated in several metabolism pathways, virulence elements and ribosomal activity was observed. In contrast, amino acid catabolism, RpoS factor, proteases, and phenazines genes were up-regulated. Remarkably, > 80 resident-phage genes were up-regulated after CIP treatment, which was validated at phenomic level using a phage plaque assay. Thus, reduction of the growth curve rate and increasing phage induction was evidenced as the CIP concentrations were increased. In summary, transcriptomic and network analyses, as well as the growth curves and phage plaque assays provide evidence that PaeAG1 presents a complex, concentration-dependent response to sub-inhibitory CIP exposure, showing pleiotropic effects at the systems level. Manipulation of these determinants, such as phage genes, could be used to gain more insights about the regulation of responses in PaeAG1 as well as the identification of possible therapeutic targets. To our knowledge, this is the first report of the transcriptomic analysis of CIP response in a ST-111 high-risk P. aeruginosa strain, in particular using a top-down systems biology approach.

Small RNAs as Fundamental Players in the Transference of Information During Bacterial Infectious Diseases

Communication shapes life on Earth. Transference of information has played a paramount role on the evolution of all living or extinct organisms since the appearance of life. Success or failure in this process will determine the prevalence or disappearance of a certain set of genes, the basis of Darwinian paradigm. Among different molecules used for transmission or reception of information, RNA plays a key role. For instance, the early precursors of life were information molecules based in primitive RNA forms. A growing field of research has focused on the contribution of small non-coding RNA forms due to its role on infectious diseases. These are short RNA species that carry out regulatory tasks in cis or trans. Small RNAs have shown their relevance in fine tuning the expression and activity of important regulators of essential genes for bacteria. Regulation of targets occurs through a plethora of mechanisms, including mRNA stabilization/destabilization, driving target mRNAs to degradation, or direct binding to regulatory proteins. Different studies have been conducted during the interplay of pathogenic bacteria with several hosts, including humans, animals, or plants. The sRNAs help the invader to quickly adapt to the change in environmental conditions when it enters in the host, or passes to a free state. The adaptation is achieved by direct targeting of the pathogen genes, or subversion of the host immune system. Pathogens trigger also an immune response in the host, which has been shown as well to be regulated by a wide range of sRNAs. This review focuses on the most recent host-pathogen interaction studies during bacterial infectious diseases, providing the perspective of the pathogen.

Naringenin Inhibition of the Pseudomonas aeruginosa Quorum Sensing Response Is Based on Its Time-Dependent Competition With N-(3-Oxo-dodecanoyl)-L-homoserine Lactone for LasR Binding

Bacterial quorum sensing (QS) is a cell-to-cell communication system that governs the expression of a large set of genes involved in bacterial-host interactions, including the production of virulence factors. Conversely, the hosts can produce anti-QS compounds to impair virulence of bacterial pathogens. One of these inhibitors is the plant flavonoid naringenin, which impairs the production of QS-regulated Pseudomonas aeruginosa virulence factors. In the present work, we analyze the molecular basis for such inhibition. Our data indicate that naringenin produces its effect by directly binding the QS regulator LasR, hence competing with its physiological activator, N-(3-oxo-dodecanoyl)-L-homoserine lactone (3OC12-HSL). The in vitro analysis of LasR binding to its cognate target DNA showed that the capacity of naringenin to outcompete 3OC12-HSL, when the latter is previously bound to LasR, is low. By using an E. coli LasR-based biosensor strain, which does not produce 3OC12-HSL, we determined that the inhibition of LasR is more efficient when naringenin binds to nascent LasR than when this regulator is already activated through 3OC12-HSL binding. According to these findings, at early exponential growth phase, when the amount of 3OC12-HSL is low, naringenin should proficiently inhibit the P. aeruginosa QS response, whereas at later stages of growth, once 3OC12-HSL concentration reaches a threshold enough for binding LasR, naringenin would not efficiently inhibit the QS response. To test this hypothesis, we analyze the potential effect of naringenin over the QS response by adding naringenin to P. aeruginosa cultures at either time zero (early inhibition) or at stationary growth phase (late inhibition). In early inhibitory conditions, naringenin inhibited the expression of QS-regulated genes, as well as the production of the QS-regulated virulence factors, pyocyanin and elastase. Nevertheless, in late inhibitory conditions, the P. aeruginosa QS response was not inhibited by naringenin. Therefore, this time-dependent inhibition may compromise the efficiency of this flavonoid, which will be effective just when used against bacterial populations presenting low cellular densities, and highlight the importance of searching for QS inhibitors whose mechanism of action does not depend on the QS status of the population.

Functional Annotation of Bacterial Signal Transduction Systems: Progress and Challenges

Bacteria possess a large number of signal transduction systems that sense and respond to different environmental cues. Most frequently these are transcriptional regulators, two-component systems and chemosensory pathways. A major bottleneck in the field of signal transduction is the lack of information on signal molecules that modulate the activity of the large majority of these systems. We review here the progress made in the functional annotation of sensor proteins using high-throughput ligand screening approaches of purified sensor proteins or individual ligand binding domains. In these assays, the alteration in protein thermal stability following ligand binding is monitored using Differential Scanning Fluorimetry. We illustrate on several examples how the identification of the sensor protein ligand has facilitated the elucidation of the molecular mechanism of the regulatory process. We will also discuss the use of virtual ligand screening approaches to identify sensor protein ligands. Both approaches have been successfully applied to functionally annotate a significant number of bacterial sensor proteins but can also be used to study proteins from other kingdoms. The major challenge consists in the study of sensor proteins that do not recognize signal molecules directly, but that are activated by signal molecule-loaded binding proteins.