Publication: Use of Whole Genome Sequencing to Determine the Microevolution of Mycobacterium tuberculosis during an Outbreak
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Date
2013
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Public Library of Science
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Kato-Maeda, Midori, Christine Ho, Ben Passarelli, Niaz Banaei, Jennifer Grinsdale, Laura Flores, Jillian Anderson, et al. 2013. Use of whole genome sequencing to determine the microevolution of Mycobacterium tuberculosis during an outbreak. PLoS ONE 8(3): e58235.
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Abstract
Rationale: Current tools available to study the molecular epidemiology of tuberculosis do not provide information about the directionality and sequence of transmission for tuberculosis cases occurring over a short period of time, such as during an outbreak. Recently, whole genome sequencing has been used to study molecular epidemiology of Mycobacterium tuberculosis over short time periods. Objective: To describe the microevolution of M. tuberculosis during an outbreak caused by one drug-susceptible strain. Method and Measurements: We included 9 patients with tuberculosis diagnosed during a period of 22 months, from a population-based study of the molecular epidemiology in San Francisco. Whole genome sequencing was performed using Illumina’s sequencing by synthesis technology. A custom program written in Python was used to determine single nucleotide polymorphisms which were confirmed by PCR product Sanger sequencing. Main results: We obtained an average of 95.7% (94.1–96.9%) coverage for each isolate and an average fold read depth of 73 (1 to 250). We found 7 single nucleotide polymorphisms among the 9 isolates. The single nucleotide polymorphisms data confirmed all except one known epidemiological link. The outbreak strain resulted in 5 bacterial variants originating from the index case A1 with 0–2 mutations per transmission event that resulted in a secondary case. Conclusions: Whole genome sequencing analysis from a recent outbreak of tuberculosis enabled us to identify microevolutionary events observable during transmission, to determine 0–2 single nucleotide polymorphisms per transmission event that resulted in a secondary case, and to identify new epidemiologic links in the chain of transmission.
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Keywords
Biology, Computational Biology, Genomics, Genome Evolution, Evolutionary Biology, Forms of Evolution, Microevolution, Microbiology, Bacteriology, Bacterial Evolution, Medicine, Epidemiology, Molecular Epidemiology, Infectious Diseases, Bacterial Diseases, Tuberculosis, Tropical Diseases (Non-Neglected)
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