PROJECT SUMMARY The African Tuberculosis Bioinformatics Training Program will be a collaborative educational and capacity de- velopment program between the Division of Molecular Biology and Human Genetics (MBHG), and the Centre for Bioinformatics and Computational Biology (CBCB) at Stellenbosch University (SU), South Africa. It includes other African partners (from Madagascar, Mozambique, Namibia, Zambia, Zimbabwe), as well as US investiga- tors with strong bioinformatics background from the Fred Hutchinson Cancer Center (FHCC) and the National Institute on Minority Health and Health Disparities (NIMHD), NIH. Another 20 US-based investigators with a mixture of bioinformatics, and tuberculosis (TB) expertise from 12 institutions will act as mentors. The mentor network spans a spectrum of basic to clinical research, and includes a mix of wet-laboratory, bioinformatics and computational approaches, with a strong emphasis on global health and offers a wealth of experimental data and expertise that will benefit the D43 trainees. The industry partners will offer opportunities for the trainees in bioinformatics applications in a non-academic setting. Objectives of the program are to: 1) Implement a new structured Bioinformatics MSc curriculum, including TB Biology modules, with a strong research training compo- nent, 2) Train students that are well versed in conducting responsible, rigorous and reproducible research, 3) Implement a trainee career development and mentorship program, and its evaluation framework, 4) Strengthen and expand low- and middle-income country (LMIC) and US TB Bioinformatics partnerships, and 5) Implement a faculty development program, and its evaluation process. During the D71 planning phase, a new Bioinformatics curriculum with emphasis on TB was developed. This 2-year MSc program will offer a vigorous coursework component followed by a research project mentored by world-class TB scientists. The MSc program will include a 9-month lecture block (including Statistics, Bioinformatics and TB Biology). Trainees will then be embedded within the SU host laboratory with a 2-month visit to the laboratory of a US-based host, and they will carry out a bioinformatics research project. The program incorporates career development activities for trainees and faculty development initiatives for mentors and LMIC partners. The program will produce at least 16 MSc graduates, equipped with bioinformatics and research skills to position them as future innovators and leaders in infectious disease research. Customized workshops (based on needs assessment with LMIC partners) will strengthen research, supervisory and mentoring capacity. This will help empower LMIC faculty and create an enabling en- vironment, to encourage trainees to return to their home institutions and develop and retain regional capacity. A detailed monitoring and evaluation plan has been developed to assess the program. This integrated approach will make the biggest impact on the current bioinformatics landscape in Southern Africa. It will bring together a productive network of TB researchers, bioinformaticians, US mentors and LMIC partners to implement a TB- focused bioinformatics training program to benefit infectious disease research.

PROJECT NARRATIVE The overall goal of the African Tuberculosis Bioinformatics Training Program is to strengthen bioinformatics training in Africa for infectious diseases, specifically for tuberculosis (TB), a major public health problem on the continent. The Program will address a dearth of trained bioinformaticians with expertise in TB and other infectious diseases, through a structured Master’s in TB bioinformatics, in which trainees will develop subject-specific expertise, complemented by international research visits, and other networking and capacity development opportunities. Trainees will be embedded within a vibrant network of LMIC and US-based mentors who will provide TB biology, bioinformatics and global health expertise together with individual mentoring to support the development of future leaders in infectious disease bioinformatics.