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Replication of the Ordered, Nonredundant Library of Pseudomonas aeruginosa strain PA14 Transposon Insertion Mutants
Published on: May 4, 2018
Model-driven characterization of functional diversity of Pseudomonas aeruginosa clinical isolates with broadly
Mohammad Mazharul Islam1, Glynis L Kolling1, Emma M Glass1
1Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, 22903.
Abstract:
Pseudomonas aeruginosa is a leading cause of infections in immunocompromised individuals and in healthcare settings. This study aims to understand the relationships between phenotypic diversity and the functional metabolic landscape of P. aeruginosa clinical isolates. To better understand the metabolic repertoire of P. aeruginosa in infection, we deeply profiled a representative set from a library of 971 clinical P. aeruginosa isolates with corresponding patient metadata and bacterial phenotypes. The genotypic clustering based on whole-genome sequencing of the isolates, multi-locus sequence types, and the phenotypic clustering generated from a multi-parametric analysis were compared to each other to assess the genotype-phenotype correlation. Genome-scale metabolic network reconstructions were developed for each isolate through amendments to an existing PA14 network reconstruction. These network reconstructions show diverse metabolic functionalities and enhance the collective P. aeruginosa pangenome metabolic repertoire. Characterizing this rich set of clinical P. aeruginosa isolates allows for a deeper understanding of the genotypic and metabolic diversity of the pathogen in a clinical setting and lays a foundation for further investigation of the metabolic landscape of this pathogen and host-associated metabolic differences during infection.
Insights
This study explores the metabolic diversity of Pseudomonas aeruginosa clinical isolates. Understanding these metabolic capabilities is key to combating infections in vulnerable patients.
Area of Science:
- Microbiology
- Metabolic Engineering
- Genomics
Background:
- Pseudomonas aeruginosa is a significant cause of infections, particularly in immunocompromised individuals and healthcare settings.
- Understanding the metabolic diversity of P. aeruginosa is crucial for developing effective treatments and infection control strategies.
Approach:
- Deeply profiled a library of 971 clinical P. aeruginosa isolates, including patient metadata and phenotypes.
- Compared genotypic clustering (whole-genome sequencing, multi-locus sequence types) with phenotypic clustering to assess genotype-phenotype correlations.
- Developed genome-scale metabolic network reconstructions for each isolate, enhancing the P. aeruginosa pangenome metabolic repertoire.
Key Points:
- Significant genotypic and metabolic diversity was observed among clinical P. aeruginosa isolates.
- Metabolic network reconstructions revealed diverse functionalities, expanding the known metabolic capabilities of the species.
- Established a strong correlation between genotypic and phenotypic characteristics, providing insights into isolate adaptation.
Conclusions:
- Characterization of clinical P. aeruginosa isolates deepens the understanding of genotypic and metabolic diversity in clinical settings.
- This work provides a foundation for investigating the pathogen's metabolic landscape and host-pathogen metabolic interactions during infection.
- Highlights the potential for targeted metabolic interventions against P. aeruginosa infections.
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