Proteogenomic Investigation of Strain Variation in Clinical Mycobacterium tuberculosis Isolates

Tiaan Heunis, Anzaan Dippenaar, Robin M. Warren, Paul D. van Helden, Ruben G. van der Merwe, Nicolaas C. Gey van Pittius, Arnab Pain, Samantha L. Sampson, David L. Tabb

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


Mycobacterium tuberculosis consists of a large number of different strains that display unique virulence characteristics. Whole-genome sequencing has revealed substantial genetic diversity among clinical M. tuberculosis isolates, and elucidating the phenotypic variation encoded by this genetic diversity will be of utmost importance to fully understand M. tuberculosis biology and pathogenicity. In this study we integrated whole-genome sequencing and mass spectrometry (GeLC-MS/MS) to reveal strain-specific characteristics in the proteomes of two clinical M. tuberculosis Latin American-Mediterranean isolates. Using this approach we identified 59 peptides containing single amino acid variants, which covered ~9% of all total coding nonsynonymous single nucleotide variants detected by whole-genome sequencing. Furthermore, we identified 29 distinct peptides that mapped to a hypothetical protein not present in the M. tuberculosis H37Rv reference proteome. Here we provide evidence for the expression of this protein in the clinical M. tuberculosis SAWC3651 isolate. The strain-specific databases enabled confirmation of genomic differences (i.e. large genomic regions of difference and nonsynonymous single nucleotide variants) in these two clinical M. tuberculosis isolates and allowed strain differentiation at the proteome level. Our results contribute to the growing field of clinical microbial proteogenomics and can improve our understanding of phenotypic variation in clinical M. tuberculosis isolates.
Original languageEnglish (US)
Pages (from-to)3841-3851
Number of pages11
JournalJournal of Proteome Research
Issue number10
StatePublished - Sep 11 2017

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was supported by the South African National Research Foundation (NRF), South African Medical Research Council (SAMRC), Harry Crossley Foundation, Claude Leon Foundation, the Department of Biomedical Sciences, Stellenbosch University and King Abdullah University of Science and Technology (KAUST award number BAS/1/1020-01-01). S.L. Sampson is funded by the South African Research Chairs Initiative of the Department of Science and Technology and NRF of South Africa, award number UID 86539. D.L. Tabb is funded by the SAMRC under the South African Tuberculosis Bioinformatics Initiative.


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