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      Combining antibiotics with antivirulence compounds can have synergistic effects and reverse selection for antibiotic resistance in Pseudomonas aeruginosa

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      PLOS Biology
      Public Library of Science (PLoS)

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          Abstract

          Antibiotics are losing efficacy due to the rapid evolution and spread of resistance. Treatments targeting bacterial virulence factors have been considered as alternatives because they target virulence instead of pathogen viability, and should therefore exert weaker selection for resistance than conventional antibiotics. However, antivirulence treatments rarely clear infections, which compromises their clinical applications. Here, we explore the potential of combining antivirulence drugs with antibiotics against the opportunistic human pathogen Pseudomonas aeruginosa. We combined two antivirulence compounds (gallium, a siderophore quencher, and furanone C-30, a quorum sensing [QS] inhibitor) together with four clinically relevant antibiotics (ciprofloxacin, colistin, meropenem, tobramycin) in 9×9 drug concentration matrices. We found that drug-interaction patterns were concentration dependent, with promising levels of synergies occurring at intermediate drug concentrations for certain drug pairs. We then tested whether antivirulence compounds are potent adjuvants, especially when treating antibiotic resistant (AtbR) clones. We found that the addition of antivirulence compounds to antibiotics could restore growth inhibition for most AtbR clones, and even abrogate or reverse selection for resistance in five drug combination cases. Molecular analyses suggest that selection against resistant clones occurs when resistance mechanisms involve restoration of protein synthesis, but not when efflux pumps are up-regulated. Altogether, our work provides a first systematic analysis of antivirulence-antibiotic combinatorial treatments and suggests that such combinations have the potential to be both effective in treating infections and in limiting the spread of antibiotic resistance.

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          Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database

          The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches.
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            Pseudomonas aeruginosa: all roads lead to resistance.

            Pseudomonas aeruginosa is often resistant to multiple antibiotics and consequently has joined the ranks of 'superbugs' due to its enormous capacity to engender resistance. It demonstrates decreased susceptibility to most antibiotics due to low outer membrane permeability coupled to adaptive mechanisms and can readily achieve clinical resistance. Newer research, using mutant library screens, microarray technologies and mutation frequency analysis, has identified very large collections of genes (the resistome) that when mutated lead to resistance as well as new forms of adaptive resistance that can be triggered by antibiotics themselves, in in vivo growth conditions or complex adaptations such as biofilm growth or swarming motility. Copyright © 2011 Elsevier Ltd. All rights reserved.
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              Challenges of antibacterial discovery.

              The discovery of novel small-molecule antibacterial drugs has been stalled for many years. The purpose of this review is to underscore and illustrate those scientific problems unique to the discovery and optimization of novel antibacterial agents that have adversely affected the output of the effort. The major challenges fall into two areas: (i) proper target selection, particularly the necessity of pursuing molecular targets that are not prone to rapid resistance development, and (ii) improvement of chemical libraries to overcome limitations of diversity, especially that which is necessary to overcome barriers to bacterial entry and proclivity to be effluxed, especially in Gram-negative organisms. Failure to address these problems has led to a great deal of misdirected effort.
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                Author and article information

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                Journal
                PLOS Biology
                PLoS Biol
                Public Library of Science (PLoS)
                1545-7885
                August 18 2020
                August 18 2020
                : 18
                : 8
                : e3000805
                Article
                10.1371/journal.pbio.3000805
                e97d338b-e65c-44e3-b46c-56c93d9cc7a1
                © 2020

                http://creativecommons.org/licenses/by/4.0/

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