Drivers and sites of variable DNA methylation in Mycobacterium tuberculosis clinical isolates


Identification: Modlin-Samuel


Description

Drivers and sites of variable DNA methylation in Mycobacterium tuberculosis clinical isolates
1Samuel J. Modlin, 1Derek Conkle-Gutierrez, 1Calvin Kim, 1Scott N. Mitchell, 1Christopher Morrissey, 2Brian C. Weinrick, 3William R. Jacobs Jr., 1Sarah M. Ramirez-Busby, 1,4Sven E. Hoffner, and 1Faramarz Valafar*

1Laboratory for Pathogenesis of Clinical Drug Resistance and Persistence, San Diego State University, San Diego, CA, USA
2Trudeau Institute, Saranac Lake, NY, USA
3Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY, USA
4Department of Public Health Sciences, Karolinska Institute, Stockholm, Sweden

Whole genome sequencing has been transformative for our understanding of genetic diversity in the Mycobacterium tuberculosis complex (MTBC).
Yet there has been limited description of epigenomic diversity in the MTBC. We analyzed sequencing kinetics of single-molecule real-time sequencing data to fully assemble DNA methylomes from 93 phylogeographically diverse MTBC clinical isolates. We identify drivers and sites of methylomic diversity across the MTBC. First, through heterogeneity analysis we identify and describe "Intercellular mosaic methylation" (IMM), a form of prokaryotic DNA methylation heterogeneity distinct from established forms. Though rare overall, constitutive IMM is nearly ubiquitous in Beijing isolates, suggesting IMM might confer an adaptive advantage to the Beijing sublineage. Second, integrative analysis of methylomes and transcriptional data revealed widespread promoter methylation in MTBC, including many clinically important genes, and evidence for DNA methylation directly influencing promoter strength. Third, comparing within and across methylomes identified 351 sites that are especially variable across isolates which, when considered alongside the apparent effect of promoter methylation on transcription, suggest these sites may confer epigenomic-driven phenotypic variability across clinical isolates. This dataset and our findings provide a basis for future work delineating the roles of DNA adenine methylation in MTBC physiology and adaptive evolution.

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