ArticlemBio2015
Phylogenetic Distribution of CRISPR-Cas Systems in Antibiotic-Resistant Pseudomonas aeruginosa.
Article in mBio, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 131 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
131 citing papers in PubMed, 234 citations in OpenAlex.
- The application of the CRISPR-Cas system in Pseudomonas aeruginosa infections.Molecular biology reports · 2026Review
- The H-NS homologues MvaT and MvaU repress CRISPR-Cas inPhilosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Article
- Comparative genomics ofJournal of bacteriology · 2025Article
- Innovative approaches to combat antibiotic resistance: integrating CRISPR/Cas9 and nanoparticles against biofilm-driven infections.BMC medicine · 2025Review
- Detection of the ST111 Global High-RiskCurrent issues in molecular biology · 2025Article
- Bacteriophages inMicrobial genomics · 2025Article
- Diversity and Role of Prophages inGenes · 2025Article
- Article
- Role of CRISPR-Cas system as a new approach in fighting the antimicrobial resistance of bacterial and viral pathogens.Infectious diseases & immunity · 2025Review
- Carbapenem-ResistantAntibiotics (Basel, Switzerland) · 2025Review
- Molecular epidemiological study of Pseudomonas aeruginosa strains isolated from hospitals in Brazil by MLST and CRISPR/Cas system analysis.Molecular genetics and genomics : MGG · 2025Article
- AvirulentmicroLife · 2025Article
- Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains.Computational and structural biotechnology journal · 2024Article
- Isolation and Characterization of Lytic Bacteriophages Capable of Infecting Diverse Multidrug-Resistant Strains ofPharmaceuticals (Basel, Switzerland) · 2024Article
- Article
- Role of CRISPR-Cas systems and anti-CRISPR proteins in bacterial antibiotic resistance.Heliyon · 2024Review
- Making the leap from technique to treatment - genetic engineering is paving the way for more efficient phage therapy.Biochemical Society transactions · 2024Review
- Keeping up with the pathogens: improved antimicrobial resistance detection and prediction from Pseudomonas aeruginosa genomes.Genome medicine · 2024Article
- Prevalence of the CRISPR-cas system and its association with antibiotic resistance in clinical Klebsiella pneumoniae isolates.BMC infectious diseases · 2024Article
- Blunted blades: new CRISPR-derived technologies to dissect microbial multi-drug resistance and biofilm formation.mSphere · 2024Review
71 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
21 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
unlabelledPseudomonas aeruginosa is an antibiotic-refractory pathogen with a large genome and extensive genotypic diversity. Historically, P. aeruginosa has been a major model system for understanding the molecular mechanisms underlying type I clustered regularly interspaced short palindromic repeat (CRISPR) and CRISPR-associated protein (CRISPR-Cas)-based bacterial immune system function. However, little information on the phylogenetic distribution and potential role of these CRISPR-Cas systems in molding the P. aeruginosa accessory genome and antibiotic resistance elements is known. Computational approaches were used to identify and characterize CRISPR-Cas systems within 672 genomes, and in the process, we identified a previously unreported and putatively mobile type I-C P. aeruginosa CRISPR-Cas system. Furthermore, genomes harboring noninhibited type I-F and I-E CRISPR-Cas systems were on average ~300 kb smaller than those without a CRISPR-Cas system. In silico analysis demonstrated that the accessory genome (n = 22,036 genes) harbored the majority of identified CRISPR-Cas targets. We also assembled a global spacer library that aided the identification of difficult-to-characterize mobile genetic elements within next-generation sequencing (NGS) data and allowed CRISPR typing of a majority of P. aeruginosa strains. In summary, our analysis demonstrated that CRISPR-Cas systems play an important role in shaping the accessory genomes of globally distributed P. aeruginosa isolates. IMPORTANCE: P. aeruginosa is both an antibiotic-refractory pathogen and an important model system for type I CRISPR-Cas bacterial immune systems. By combining the genome sequences of 672 newly and previously sequenced genomes, we were able to provide a global view of the phylogenetic distribution, conservation, and potential targets of these systems. This analysis identified a new and putatively mobile P. aeruginosa CRISPR-Cas subtype, characterized the diverse distribution of known CRISPR-inhibiting genes, and provided a potential new use for CRISPR spacer libraries in accessory genome analysis. Our data demonstrated the importance of CRISPR-Cas systems in modulating the accessory genomes of globally distributed strains while also providing substantial data for subsequent genomic and experimental studies in multiple fields. Understanding why certain genotypes of P. aeruginosa are clinically prevalent and adept at horizontally acquiring virulence and antibiotic resistance elements is of major clinical and economic importance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.