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In-host population dynamics of M. tuberculosis during treatment failure

Roger Vargas Jr, Luca Freschi, Maximillian Marin, L. Elaine Epperson, Melissa Smith, Irina Oussenko, David Durbin, Michael Strong, Max Salfinger, Maha Reda Farhat
doi: https://doi.org/10.1101/726430
Roger Vargas Jr
1Department of Systems Biology, Harvard Medical School
2Department of Biomedical Informatics, Harvard Medical School
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  • For correspondence: roger_vargas@g.harvard.edu Maha_Farhat@hms.harvard.edu
Luca Freschi
2Department of Biomedical Informatics, Harvard Medical School
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Maximillian Marin
1Department of Systems Biology, Harvard Medical School
2Department of Biomedical Informatics, Harvard Medical School
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L. Elaine Epperson
3Center for Genes, Environment, and Health, National Jewish Health
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Melissa Smith
4Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai
5Icahn Institute of Data Sciences and Genomics Technology
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Irina Oussenko
5Icahn Institute of Data Sciences and Genomics Technology
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David Durbin
6Mycobacteriology Reference Laboratory, Advanced Diagnostic Laboratories, National Jewish Health
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Michael Strong
3Center for Genes, Environment, and Health, National Jewish Health
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Max Salfinger
7College of Public Health, University of South Florida
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Maha Reda Farhat
2Department of Biomedical Informatics, Harvard Medical School
8Pulmonary and Critical Care Medicine, Massachusetts General Hospital
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  • For correspondence: roger_vargas@g.harvard.edu Maha_Farhat@hms.harvard.edu
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ABSTRACT

Tuberculosis (TB) is the leading cause of death globally from an infectious disease. Understanding the dynamics of TB’s causative agent Mycobacterium tuberculosis (Mtb) in host is vital for antibiotic treatment and vaccine design. Here we use longitudinally collected clinical Mtb isolates from the sputa of 307 subjects to investigate Mtb diversity during the course of active TB disease. We excluded cases suspected of reinfection or contamination to analyze data from 200 subjects, 167 of which met microbiological criteria for delayed culture conversion, treatment failure or relapse. Using technical and biological replicate samples, we defined an allele frequency threshold attributable to in-host evolution. Of the 167 subjects with unsuccessful treatment outcome, 16% developed resistance amplification between sampling; 74% of amplification occurred among isolates that were genotypically resistant at the outset. Low abundance resistance variants in the first isolate predicts the fixation of these variants in the subsequent sample. We identify in-host variation in resistance and metabolic genes as well as in genes known to modulate host innate immunity by interacting with TLR2. We confirm these genes to be under positive selection by assessing phylogenetic convergence across a genetically diverse independent sample of 10,018 isolates.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted August 06, 2019.
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In-host population dynamics of M. tuberculosis during treatment failure
Roger Vargas Jr, Luca Freschi, Maximillian Marin, L. Elaine Epperson, Melissa Smith, Irina Oussenko, David Durbin, Michael Strong, Max Salfinger, Maha Reda Farhat
bioRxiv 726430; doi: https://doi.org/10.1101/726430
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In-host population dynamics of M. tuberculosis during treatment failure
Roger Vargas Jr, Luca Freschi, Maximillian Marin, L. Elaine Epperson, Melissa Smith, Irina Oussenko, David Durbin, Michael Strong, Max Salfinger, Maha Reda Farhat
bioRxiv 726430; doi: https://doi.org/10.1101/726430

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