Data files for "A novel inhibitor of P. aeruginosa folate metabolism exploits metabolic differences for narrow-spectrum antibiotic targeting"
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ABSTRACT:
INSTRUMENT(S): Orbitrap Exploris 480
ORGANISM(S): Pseudomonas Aeruginosa Pa14 (ncbitaxon:652611)
SUBMITTER: 
Zemer Gitai
PROVIDER: MSV000093598 | MassIVE | Thu Dec 07 07:55:00 GMT 2023
REPOSITORIES: MassIVE
Similar Datasets
Project description:A novel inhibitor of P. aeruginosa folate metabolism exploits metabolic differences for narrow-spectrum antibiotic targeting
| PRJNA1051048 | ENA
Project description:Pseudomonas aeruginosa is a leading cause of hospital acquired infections for which the development of new antibiotics is urgently needed. Unlike most enteric bacteria, P. aeruginosa lacks thymidine kinase and thymidine phosphorylase activity, and thus cannot scavenge exogenous thymine. An appealing strategy to selectively target P. aeruginosa while leaving the healthy microbiome largely intact would thus be to disrupt thymidine synthesis while providing exogenous thymine. However, this approach was previously intractable because known antibiotics that perturb thymidine synthesis are largely inactive against P. aeruginosa. Here, we characterize a novel dihydrofolate reductase inhibitor, fluorofolin, that exhibits significant activity against P. aeruginosa in culture and in a mouse thigh infection model. Fluorofolin is active against a wide range of clinical P. aeruginosa isolates resistant to known antibiotics, including critical antibiotic development priorities expressing the beta-lactamases KPC-5 and NDM-1. Importantly, in the presence of thymine supplementation, fluorofolin activity is selective for P. aeruginosa. Resistance to fluorofolin can emerge through overexpression of the efflux pumps MexCD-OprJ and MexEF-OprN. However, these mutants also decrease pathogenesis, in part due to increased export of quorum sensing precursors leading to decreased virulence factor production. Our findings thus demonstrate how understanding species-specific genetic differences and discovery of an antibiotic with a widely conserved target can enable selective targeting of important pathogens while revealing new tradeoffs between resistance and pathogenesis.
2024-02-07 | GSE249862 | GEO
Project description:Deep learning-guided discovery of a narrow-spectrum antibiotic against Acinetobacter baumannii
| PRJNA884833 | ENA
Project description:Acinetobacter baumannii is a nosocomial Gram-negative pathogen that often displays multidrug-resistance due to its robust outer membrane and its ability to acquire and retain extracellular DNA. Moreover, it can survive for prolonged durations on surfaces and is resistant to desiccation. Discovering new antibiotics against A. baumannii has proven challenging through conventional screening approaches. Fortunately, machine learning methods allow for the rapid exploration of chemical space, increasing the probability of discovering new chemical matter with antibacterial activity against this burdensome pathogen. Here, we screened ~7,500 molecules for those that inhibited the growth of A. baumannii in vitro. We trained a deep neural network with this growth inhibition dataset and performed predictions on the Drug Repurposing Hub for structurally novel molecules with activity against A. baumannii. Through this approach, we discovered abaucin, an antibacterial compound with narrow-spectrum activity against A. baumannii, which could overcome intrinsic and acquired resistance mechanisms in clinical isolates. Further investigations revealed that abaucin perturbs lipoprotein trafficking through a mechanism involving LolE, a functionally conserved protein that contributes to shuttling lipoproteins from the inner membrane to the outer membrane. Moreover, abaucin was able to control an A. baumannii infection in a murine wound model. Together, this work highlights the utility of machine learning in discovering new antibiotics and describes a promising lead with narrow-spectrum activity against a challenging Gram-negative pathogen.
2023-02-01 | GSE214305 | GEO
Project description:Surfing motility is a novel form of surface adaptation exhibited by the nosocomial pathogen, Pseudomonas aeruginosa, in the presence of the glycoprotein mucin that is found in high abundance at mucosal surfaces especially the lungs of cystic fibrosis and bronchiectasis patients. Here we investigated the adaptive antibiotic resistance of P. aeruginosa under conditions in which surfing occurs compared to cells undergoing swimming. P. aeruginosa surfing cells were significantly more resistant to several classes of antibiotics including aminoglycosides, carbapenems, polymyxins, and fluroquinolones. This was confirmed by incorporation of antibiotics into growth medium, which revealed a concentration-dependent inhibition of surfing motility that occurred at concentrations much higher than those needed to inhibit swimming. To investigate the basis of resistance, RNA-Seq was performed and revealed that surfing influenced the expression of numerous genes. Included amongst genes dysregulated under surfing conditions were multiple genes from the Pseudomonas resistome, which are known to affect antibiotic resistance when mutated. Screening transposon mutants in these surfing-dysregulated resistome genes revealed that several of these mutants exhibited changes in susceptibility to one or more antibiotics under surfing conditions, consistent with a contribution to the observed adaptive resistance. In particular, several mutants in resistome genes, including armR, recG, atpB, clpS, nuoB, and certain hypothetical genes such as PA5130, PA3576 and PA4292, showed contributions to broad-spectrum resistance under surfing conditions and could be complemented by their respective cloned genes. Therefore, we propose that surfing adaption led to extensive multidrug adaptive resistance as a result of the collective dysregulation of diverse genes.
2018-06-26 | GSE110044 | GEO
Project description:Pseudomonas aeruginosa is known to tolerate antibiotic therapy during infection. This prevents clearance of infection and negatively impacts patient outcomes. Here, we report the transcriptome sequence of antibiotic-treated and untreated P. aeruginosa cultures and the differential gene expression observed when treated cells are compared to untreated cells.
2018-10-31 | GSE120602 | GEO
Project description:Raw MS files for the manuscript, "A novel inhibitor of P. aeruginosa folate metabolism exploits metabolic differences for narrow-spectrum antibiotic targeting", by Chain et al.
2023-12-07 | MSV000093598 | GNPS
Project description:Bacteria in biofilms have higher antibiotic tolerance than their planktonic counterparts. A major outstanding question is the degree to which the biofilm-specific cellular state and its constituent genetic determinants contribute to this hyper-tolerant phenotype. Here, using genome-wide functional profiling of a complex, heterogeneous mutant population of Pseudomonas aeruginosa MPAO1, we identified large sets of mutations that contribute to antibiotic tolerance predominantly in the biofilm or planktonic setting only. Our mixed population-based experimental design recapitulated the complexity of natural biofilms and, unlike previous studies, revealed clinically observed behaviors including the emergence of quorum sensing-deficient mutants. Our study revealed a substantial contribution of the cellular state to the antibiotic tolerance of biofilms, providing a rational foundation for the development of novel therapeutics against P. aeruginosa biofilm-associated infections. This dataset compares the expression of SAH108, a strain with enhanced antibiotic tolerance in the biofilm state, to expression in wild-type strains.
2011-11-21 | GSE26142 | GEO
Project description:ObjectivesTo provide updated estimates of narrow- and broad-spectrum antibiotic use among U.S. children.Data sourcesLinked nationally representative data from the 2004-2010 Medical Expenditure Panel Survey Household Component and the 2000 Decennial Census.Study designRelationships between individual-, family-, and community-level characteristics and the use of antibiotics overall and in the treatment of respiratory tract infections (RTIs) are examined using multinomial choice models.Principal findingsMore than one quarter (27.3 percent) of children used at least one antibiotic each year with 12.8 percent using broad-spectrum and 18.5 percent using narrow-spectrum antibiotics. Among children with use, more than two-thirds (68.6 percent) used antibiotics to treat RTIs. Multivariate models revealed many differences across groups in antibiotic use, overall and in the treatment of RTIs. Differential use was associated with a broad range of factors related to need (e.g., age, health status), resources (e.g., insurance status, parental income, and education), race-ethnicity, and Census region.ConclusionsDespite encouraging reports regarding the declining use of antibiotics, large differences in use associated with resources, race-ethnicity, and Census regions suggest a need for further improvement in the judicious and appropriate prescribing of antibiotics for U.S. children.
| S-EPMC4450932 | biostudies-literature
Project description:Bacteria in biofilms have higher antibiotic tolerance than their planktonic counterparts. A major outstanding question is the degree to which the biofilm-specific cellular state and its constituent genetic determinants contribute to this hyper-tolerant phenotype. Here, using genome-wide functional profiling of a complex, heterogeneous mutant population of Pseudomonas aeruginosa MPAO1, we identified large sets of mutations that contribute to antibiotic tolerance predominantly in the biofilm or planktonic setting only. Our mixed population-based experimental design recapitulated the complexity of natural biofilms and, unlike previous studies, revealed clinically observed behaviors including the emergence of quorum sensing-deficient mutants. Our study revealed a substantial contribution of the cellular state to the antibiotic tolerance of biofilms, providing a rational foundation for the development of novel therapeutics against P. aeruginosa biofilm-associated infections. This dataset compares the expression of SAH108, a strain with enhanced antibiotic tolerance in the biofilm state, to expression in wild-type strains. We compared the expression of two biological replicates from strain SAH108 to samples from three wild-type, reference strains. All samples were collected from exponentially-growing planktonic cultures.
2011-11-21 | E-GEOD-26142 | biostudies-arrayexpress