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Gram-negative bacteria are notoriously resistant to antibiotics, but the extent of the resistance varies broadly between species. We report that in significant human pathogens Acinetobacter baumannii , Pseudomonas aeruginosa , and Burkholderia spp., the differences in antibiotic resistance are largely defined by their penetration into the cell. For all tested antibiotics, the intracellular penetration was determined by a synergistic relationship between active efflux and the permeability barrier. We found that the outer membrane (OM) and efflux pumps select compounds on the basis of distinct properties and together universally protect bacteria from structurally diverse antibiotics. On the basis of their interactions with the permeability barriers, antibiotics can be divided into four clusters that occupy defined physicochemical spaces. Our results suggest that rules of intracellular penetration are intrinsic to these clusters. The identified specificities in the permeability barriers should help in the designing of successful therapeutic strategies against antibiotic-resistant pathogens. IMPORTANCE Multidrug-resistant strains of Gram-negative pathogens rapidly spread in clinics. Significant efforts worldwide are currently directed to finding the rules of permeation of antibiotics across two membrane envelopes of these bacteria. This study created the tools for analysis of and identified the major differences in antibacterial activities that distinguish the permeability barriers of P. aeruginosa , A. baumannii , Burkholderia thailandensis , and B. cepacia . We conclude that synergy between active efflux and the outer membrane barrier universally protects Gram-negative bacteria from antibiotics. We also found that the diversity of antibiotics affected by active efflux and outer membrane barriers is broader than previously thought and that antibiotics cluster according to specific biological determinants such as the requirement of specific porins in the OM, targeting of the OM, or specific recognition by efflux pumps. No universal rules of antibiotic permeation into Gram-negative bacteria apparently exist. Our results suggest that antibiotic clusters are defined by specific rules of permeation and that further studies could lead to their discovery. Multidrug-resistant strains of Gram-negative pathogens rapidly spread in clinics. Significant efforts worldwide are currently directed to finding the rules of permeation of antibiotics across two membrane envelopes of these bacteria. This study created the tools for analysis of and identified the major differences in antibacterial activities that distinguish the permeability barriers of P. aeruginosa , A. baumannii , Burkholderia thailandensis , and B. cepacia . We conclude that synergy between active efflux and the outer membrane barrier universally protects Gram-negative bacteria from antibiotics. We also found that the diversity of antibiotics affected by active efflux and outer membrane barriers is broader than previously thought and that antibiotics cluster according to specific biological determinants such as the requirement of specific porins in the OM, targeting of the OM, or specific recognition by efflux pumps. No universal rules of antibiotic permeation into Gram-negative bacteria apparently exist. Our results suggest that antibiotic clusters are defined by specific rules of permeation and that further studies could lead to their discovery.

Acinetobacter baumannii has emerged as one of the most highly antibiotic-resistant Gram-negative pathogens. The prevalent AdeB multidrug efflux pump mediates resistance to a broad spectrum of clinically relevant antimicrobial agents. Acinetobacter baumannii is a Gram-negative pathogen that has emerged as one of the most highly antibiotic-resistant bacteria worldwide. Multidrug efflux within these highly drug-resistant strains and other opportunistic pathogens is a major cause of failure of drug-based treatments of infectious diseases. The best-characterized multidrug efflux system in A. baumannii is the prevalent A cinetobacter d rug e fflux B (AdeB) pump, which is a member of the resistance-nodulation-cell division (RND) superfamily. Here, we report six structures of the trimeric AdeB multidrug efflux pump in the presence of ethidium bromide using single-particle cryoelectron microscopy (cryo-EM). These structures allow us to directly observe various novel conformational states of the AdeB trimer, including the transmembrane region of trimeric AdeB can be associated with form a trimer assembly or dissociated into “dimer plus monomer” and “monomer plus monomer plus monomer” configurations. We also discover that a single AdeB protomer can simultaneously anchor a number of ethidium ligands and that different AdeB protomers can bind ethidium molecules simultaneously. Combined with molecular dynamics (MD) simulations, we reveal a drug transport mechanism that involves multiple multidrug-binding sites and various transient states of the AdeB membrane protein. Our data suggest that each AdeB protomer within the trimer binds and exports drugs independently. IMPORTANCE Acinetobacter baumannii has emerged as one of the most highly antibiotic-resistant Gram-negative pathogens. The prevalent AdeB multidrug efflux pump mediates resistance to a broad spectrum of clinically relevant antimicrobial agents. Here, we report six cryo-EM structures of the trimeric AdeB pump in the presence of ethidium bromide. We discover that a single AdeB protomer can simultaneously anchor a number of ligands, and different AdeB protomers can bind ethidium molecules simultaneously. The results indicate that each AdeB protomer within the trimer recognizes and extrudes drugs independently.

Efflux pump avoidance and inhibition are desired properties for the optimization of antibacterial activities against Gram-negative bacteria. However, molecular and physicochemical interactions defining the interface between compounds and efflux pumps remain poorly understood. We identified properties that correlate with efflux avoidance and inhibition, are predictive of similar features in structurally diverse compounds, and allow researchers to distinguish between efflux substrates, inhibitors, and avoiders in P. aeruginosa . Antibiotic-resistant bacteria rapidly spread in clinical and natural environments and challenge our modern lifestyle. A major component of defense against antibiotics in Gram-negative bacteria is a drug permeation barrier created by active efflux across the outer membrane. We identified molecular determinants defining the propensity of small peptidomimetic molecules to avoid and inhibit efflux pumps in Pseudomonas aeruginosa , a human pathogen notorious for its antibiotic resistance. Combining experimental and computational protocols, we mapped the fate of the compounds from structure-activity relationships through their dynamic behavior in solution, permeation across both the inner and outer membranes, and interaction with MexB, the major efflux transporter of P. aeruginosa . We identified predictors of efflux avoidance and inhibition and demonstrated their power by using a library of traditional antibiotics and compound series and by generating new inhibitors of MexB. The identified predictors will enable the discovery and optimization of antibacterial agents suitable for treatment of P. aeruginosa infections. IMPORTANCE Efflux pump avoidance and inhibition are desired properties for the optimization of antibacterial activities against Gram-negative bacteria. However, molecular and physicochemical interactions defining the interface between compounds and efflux pumps remain poorly understood. We identified properties that correlate with efflux avoidance and inhibition, are predictive of similar features in structurally diverse compounds, and allow researchers to distinguish between efflux substrates, inhibitors, and avoiders in P. aeruginosa . The developed predictive models are based on the descriptors representative of different clusters comprising a physically intuitive combination of properties. Molecular shape (represented by acylindricity), amphiphilicity (anisotropic polarizability), aromaticity (number of aromatic rings), and the partition coefficient (LogD) are physicochemical predictors of efflux inhibitors, whereas interactions with Pro668 and Leu674 residues of MexB distinguish between inhibitors/substrates and efflux avoiders. The predictive models and efflux rules are applicable to compounds with unrelated chemical scaffolds and pave the way for development of compounds with the desired efflux interface properties.

Transporters of the resistance-nodulation-cell division (RND) superfamily of proteins are the dominant multidrug efflux power of Gram-negative bacteria. The major RND efflux pump of Pseudomonas aeruginosa is MexAB-OprM, in which the inner membrane transporter MexB is responsible for the recognition and binding of compounds. The high importance of this pump in clinical antibiotic resistance made it a subject of intense investigations and a promising target for the discovery of efflux pump inhibitors. This study is focused on a series of peptidomimetic compounds developed as effective inhibitors of MexAB-OprM. We performed multi-copy molecular dynamics simulations, machine-learning (ML) analyses, and site-directed mutagenesis of MexB to investigate interactions of MexB with representatives of efflux avoiders, substrates, and inhibitors. The analysis of both direct and water-mediated protein-ligand interactions revealed characteristic patterns for each class, highlighting significant differences between them. We found that efflux avoiders poorly interact with the access binding site of MexB, and inhibition engages amino acid residues that are not directly involved in binding and transport of substrates. In agreement, machine-learning models selected different residues predictive of MexB substrates and inhibitors. The differences in interactions were further validated by site-directed mutagenesis. We conclude that the substrate translocation and inhibition pathways of MexB split at the interface (between the main putative binding sites) and at the deep binding pocket and that interactions outside of the hydrophobic patch contribute to the inhibition of MexB. This molecular-level information could help in the rational design of new inhibitors and antibiotics less susceptible to the efflux mechanism. Multidrug transporters recognize and expel from cells a broad range of ligands including their own inhibitors. The difference between the substrate translocation and inhibition routes remains unclear. In this study, machine learning and computational and experimental approaches were used to understand dynamics of MexB interactions with its ligands. Our results show that some ligands engage a certain combination of polar and charged residues in MexB binding sites to be effectively expelled into the exit funnel, whereas others engage aromatic and hydrophobic residues that slow down or hinder the next step in the transporter cycle. These findings suggest that all MexB ligands fit into this substrate-inhibitor spectrum depending on their physico-chemical structures and properties.

Two membrane cell envelopes act as selective permeability barriers in Gram-negative bacteria, protecting cells against antibiotics and other small molecules. Significant efforts are being directed toward understanding how small molecules permeate these barriers. In this study, we developed an approach to analyze the permeation of compounds into Gram-negative bacteria and applied it to Pseudomonas aeruginosa , an important human pathogen notorious for resistance to multiple antibiotics. The approach uses mass spectrometric measurements of accumulation of a library of structurally diverse compounds in four isogenic strains of P. aeruginosa with varied permeability barriers. We further developed a machine learning algorithm that generates a deterministic classification model with minimal synonymity between the descriptors. This model predicted good permeators into P. aeruginosa with an accuracy of 89% and precision above 58%. The good permeators are broadly distributed in the property space and can be mapped to six distinct regions representing diverse chemical scaffolds. We posit that this approach can be used for more detailed mapping of the property space and for rational design of compounds with high Gram-negative permeability.

Multidrug efflux transporters are major contributors to the antibiotic resistance of Acinetobacter baumannii in clinical settings. Previous studies showed that these transporters are tightly integrated into the physiology of A. baumannii and have diverse functions. However, for many of the efflux pumps, such functions remain poorly defined. In this study, we characterized two putative drug efflux pumps, AmfAB and AmfCD (Acinetobacter Major Facilitator), that are homologous to EmrAB-like transporters from Escherichia coli and other Gram-negative bacteria. These pumps comprise the Major Facilitator Superfamily (MFS) transporters AmfB and AmfD and the periplasmic membrane fusion proteins AmfA and AmfC, respectively. We inactivated and overproduced these pumps in the wild-type ATCC 17978 strain and its derivative strains lacking the major efflux pumps from the Resistance–Nodulation–Division (RND) superfamily and characterized antibiotic susceptibilities and growth of the strains under stresses typical during human infections. We found that neither AmfAB nor AmfCD contribute to the antibiotic non-susceptibility phenotypes of A. baumannii. The two pumps, however, are critical for the adaptation and growth of the bacterium under acidic stress, whereas AmfCD also contributes to growth under conditions of low iron, high temperature, and in the presence of bile salts. These functions are dependent on the presence of the RND pumps, the inactivation of which further diminishes A. baumannii survival and growth. Our results suggest that MFS transporters contribute to stress survival by affecting the permeability properties of the A. baumannii cell envelope.

The ability Gram-negative pathogens have at adapting and protecting themselves against antibiotics has increasingly become a public health threat. Data-driven models identifying molecular properties that correlate with outer membrane (OM) permeation and growth inhibition while avoiding efflux could guide the discovery of novel classes of antibiotics. Here we evaluate 174 molecular descriptors in 1260 antimicrobial compounds and study their correlations with antibacterial activity in Gram-negative Pseudomonas aeruginosa . The descriptors are derived from traditional approaches quantifying the compounds’ intrinsic physicochemical properties, together with, bacterium-specific from ensemble docking of compounds targeting specific MexB binding pockets, and all-atom molecular dynamics simulations in different subregions of the OM model. Using these descriptors and the measured inhibitory concentrations, we design a statistical protocol to identify predictors of OM permeation/inhibition. We find consistent rules across most of our data highlighting the role of the interaction between the compounds and the OM. An implementation of the rules uncovered in our study is shown, and it demonstrates the accuracy of our approach in a set of previously unseen compounds. Our analysis sheds new light on the key properties drug candidates need to effectively permeate/inhibit P. aeruginosa , and opens the gate to similar data-driven studies in other Gram-negative pathogens. Identifying molecular properties of compounds that best correlate with outer membrane permeation and growth inhibition could guide the discovery of new antibiotics. Here, the authors evaluate 174 molecular descriptors in 1260 antimicrobial compounds and study their correlations with antibacterial activity in Gram-negative Pseudomonas aeruginosa to derive a statistical protocol to identify mechanistic predictors of outer membrane permeation.

Multidrug efflux transporters are major contributors to the antibiotic resistance of Acinetobacter baumannii in clinical settings. Previous studies showed that these transporters are tightly integrated into the physiology of A. baumannii and have diverse functions. However, for many of the efflux pumps, such functions remain poorly defined. In this study, we characterized two putative drug efflux pumps, AmfAB and AmfCD (Acinetobacter Major Facilitator), that are homologous to EmrAB-like transporters from Escherichia coli and other Gram-negative bacteria. These pumps comprise the Major Facilitator Superfamily (MFS) transporters AmfB and AmfD and the periplasmic membrane fusion proteins AmfA and AmfC, respectively. We inactivated and overproduced these pumps in the wild-type ATCC 17978 strain and its derivative strains lacking the major efflux pumps from the Resistance–Nodulation–Division (RND) superfamily and characterized antibiotic susceptibilities and growth of the strains under stresses typical during human infections. We found that neither AmfAB nor AmfCD contribute to the antibiotic non-susceptibility phenotypes of A. baumannii. The two pumps, however, are critical for the adaptation and growth of the bacterium under acidic stress, whereas AmfCD also contributes to growth under conditions of low iron, high temperature, and in the presence of bile salts. These functions are dependent on the presence of the RND pumps, the inactivation of which further diminishes A. baumannii survival and growth. Our results suggest that MFS transporters contribute to stress survival by affecting the permeability properties of the A. baumannii cell envelope.

Transporters of the Resistance-Nodulation-cell Division (RND) superfamily of proteins are the dominant multidrug efflux power of Gram-negative bacteria. The major RND efflux pump of Pseudomonas aeruginosa is MexAB-OprM, in which the inner membrane transporter MexB is responsible for recognition and binding of compounds. The high importance of this pump in clinical antibiotic resistance made it a subject of intense investigations and a promising target for the discovery of efflux pump inhibitors. This study is focused on a series of peptidomimetic compounds developed as effective inhibitors of MexAB-OprM. Previous analyses of antibacterial and biochemical activities showed that these compounds vary broadly in their efficiency as inhibitors or substrates of MexAB and can be categorized into different functional classes. Here, we performed multi-copy molecular dynamics simulations, machine learning analyses and site-directed mutagenesis of MexB to investigate interactions of MexB with representatives of the various classes. The analysis of both direct and water-mediated protein-ligand interactions revealed characteristic patterns for each class, highlighting significant differences between them. We found that efflux avoiders poorly interact with the access binding site of MexB, and inhibition engages amino acid residues that are not directly involved in binding and transport of substrates. In agreement, machine learning models selected different residues predictive of MexB substrates and inhibitors. The differences in interactions were further validated by site-directed mutagenesis. We conclude that the substrate translocation and inhibition pathways of MexB split at the interface (between the main putative binding sites) and at the deep binding pocket, and that interactions outside of the hydrophobic patch contribute to the inhibition of MexB. This molecular-level information could help in the rational design of new inhibitors and antibiotics less susceptible to the efflux mechanism. Multidrug transporters recognize and expel from cells a broad range of ligands including their own inhibitors. The difference between the substrate translocation and inhibition routes remains unclear. In this study, machine learning, computational and experimental approaches were used to understand dynamics of MexB interactions with its ligands. Our results show that some ligands engage a certain combination of polar and charged residues in MexB binding sites to be effectively expelled into the exit funnel, whereas others engage aromatic and hydrophobic residues that slow down or hinder the next step in the transporter cycle. These findings suggest that all MexB ligands fit into this substrate-inhibitor spectrum depending on their physico-chemical structures and properties.