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Bactabolize is a tool for high-throughput generation of bacterial strain-specific metabolic models.
Vezina, Ben; Watts, Stephen C; Hawkey, Jane; Cooper, Helena B; Judd, Louise M; Jenney, Adam W J; Monk, Jonathan M; Holt, Kathryn E; Wyres, Kelly L.
Afiliação
  • Vezina B; Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Australia.
  • Watts SC; Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Australia.
  • Hawkey J; Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Australia.
  • Cooper HB; Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Australia.
  • Judd LM; Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Australia.
  • Jenney AWJ; Microbiology Unit, Alfred Health, Melbourne, Australia.
  • Monk JM; Department of Bioengineering, University of California, San Diego, San Diego, United States.
  • Holt KE; Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Australia.
  • Wyres KL; Department of Infection Biology, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Elife ; 122023 10 10.
Article em En | MEDLINE | ID: mdl-37815531
ABSTRACT
Metabolic capacity can vary substantially within a bacterial species, leading to ecological niche separation, as well as differences in virulence and antimicrobial susceptibility. Genome-scale metabolic models are useful tools for studying the metabolic potential of individuals, and with the rapid expansion of genomic sequencing there is a wealth of data that can be leveraged for comparative analysis. However, there exist few tools to construct strain-specific metabolic models at scale. Here, we describe Bactabolize, a reference-based tool which rapidly produces strain-specific metabolic models and growth phenotype predictions. We describe a pan reference model for the priority antimicrobial-resistant pathogen, Klebsiella pneumoniae, and a quality control framework for using draft genome assemblies as input for Bactabolize. The Bactabolize-derived model for K. pneumoniae reference strain KPPR1 performed comparatively or better than currently available automated approaches CarveMe and gapseq across 507 substrate and 2317 knockout mutant growth predictions. Novel draft genomes passing our systematically defined quality control criteria resulted in models with a high degree of completeness (≥99% genes and reactions captured compared to models derived from matched complete genomes) and high accuracy (mean 0.97, n=10). We anticipate the tools and framework described herein will facilitate large-scale metabolic modelling analyses that broaden our understanding of diversity within bacterial species and inform novel control strategies for priority pathogens.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Genoma Bacteriano / Anti-Infecciosos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Genoma Bacteriano / Anti-Infecciosos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article