Abstract:
:Human tuberculosis is caused by members of the Mycobacterium tuberculosis complex (MTBC) that vary in virulence and transmissibility. While genome-wide association studies have uncovered several mutations conferring drug resistance, much less is known about the factors underlying other bacterial phenotypes. Variation in the outcome of tuberculosis infection and diseases has been attributed primarily to patient and environmental factors, but recent evidence indicates an additional role for the genetic diversity among MTBC clinical strains. Here, we used metabolomics to unravel the effect of genetic variation on the strain-specific metabolic adaptive capacity and vulnerability. To define the functionality of single-nucleotide polymorphisms (SNPs) systematically, we developed a constraint-based approach that integrates metabolomic and genomic data. Our model-based predictions correctly classify SNP effects in pyruvate kinase and suggest a genetic basis for strain-specific inherent baseline susceptibility to the antibiotic para-aminosalicylic acid. Our method is broadly applicable across microbial life, opening possibilities for the development of more selective treatment strategies.
journal_name
Proc Natl Acad Sci U S Aauthors
Øyås O,Borrell S,Trauner A,Zimmermann M,Feldmann J,Liphardt T,Gagneux S,Stelling J,Sauer U,Zampieri Mdoi
10.1073/pnas.1915551117subject
Has Abstractpub_date
2020-04-14 00:00:00pages
8494-8502issue
15eissn
0027-8424issn
1091-6490pii
1915551117journal_volume
117pub_type
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