PROJECT ABSTRACT/SUMMARY Marie Nancy Séraphin, PhD, is a Research Assistant Professor at the University of Florida (UF), Department of Medicine, and a trainee affiliated with both the UF Emerging Pathogens Institute (UF-EPI) and Clinical and Translational Science Institute (UF-CTSI). Dr. Séraphin has spent the last seven years, including two as a postdoc, acquiring tuberculosis (TB) molecular epidemiology skills. She has experience linking genotyping and whole genome sequence (WGS) with patient clinical data to investigate TB outbreaks. She has nine TB publications, six as the lead author. In the short-term, this K01 award will provide training and professional development opportunities in genomics and bioinformatics. Dr. Séraphin's long-term goal is to become a leader in infectious diseases molecular epidemiology, focusing on TB. Environment: Dr. Séraphin will perform her K01 research with guidance from a multidisciplinary mentoring committee. Each mentor is a leader in their respective field. The lead mentors are Dr. Marco Salemi, an expert in phylogenetic, computational, evolutionary biology, and Dr. Kyle Rohde, an expert in TB genetics, pathogenesis, and diagnostics. Dr. Séraphin will also receive formal training in genomics and bioinformatics and acquire research leadership and grantsmanship skills. Research: Mycobacterium tuberculosis (Mtb) is an incredibly successful pathogen, with an estimated 10 million people newly diagnosed with TB annually. Rapid diagnosis, effective treatment, and contact tracing are public health interventions that decrease TB morbidity and mortality. Routine strain surveillance by WGS of culture- confirmed TB cases facilitates the rapid detection and control of outbreaks to prevent further transmission in communities. More importantly, the rapid detection of outbreaks assures the timely identification of recently infected contacts that can benefit from prophylaxis. Unfortunately, contact tracing activities are currently highly inefficient as TB programs struggle to identify and target efforts towards the 20% of TB cases that generate secondary cases (i.e., super spreaders). This critical public health function could be improved if we capitalize on the extensive Mtb within-host genetic diversity (WHD) that can be profiled with deep WGS. Thus, we propose to assess the utility of Mtb deep WGS as a higher resolution marker of person-to-person transmission and super spreading. Specifically, we propose first assessing variation in WHD transmission (i.e., bottleneck size) under diverse epi scenarios (Aim 1). WHD measurement is likely to be confounded by laboratory processing of specimens and single genome/sample analysis. Thus, we will assess WHD measure bias by sputum decontamination, subculturing, and sputum sampling (Aim 2). Finally, we will test in a pilot study the feasibility of tracking WHD transmission to detect de novo Mtb transmission and superspreaders (Aim 3). The proposed research and the training activities will successfully position Dr. Séraphin for her first R01 and an independent career as a research scientist.

PROJECT NARRATIVE We implicitly assume one identical Mtb population (clone) per TB case with current TB molecular epidemiology approaches. This oversight of the extensive genetic diversity within patients bias reconstruction of transmission links and renders control interventions such as contact tracing inefficient. Deep sequencing to profile within-host genetic diversity shared between cases promises to be a higher resolution maker of person-to-person transmission and a quantitative measure of superspreading that would make contact tracing more efficient than current practice.