Tuberculous meningitis (TBM) is one of the most devastating forms of tuberculosis (TB), with mortality rates as high as 50%. Despite dismal outcomes, few data are available on optimizing the approach to treatment of TBM. While several interventional TBM trials are underway, they face tremendous barriers that could impede the knowledge gained from these essential studies. First, TBM is exceptionally difficult to diagnose, which directly impacts selection of the right trial population on which to test treatment regimens. Second, although the host immune response may be a major driver of poor outcomes in TBM, our understanding of the immunopathogenesis of TBM and how it may be targeted with host-directed therapy is in its infancy. Third, dedicated resources to develop and sustain research capacity are often limited in low- and middle-income countries (LMIC) where TB is endemic and where data-driven treatment strategies for TBM are urgently needed. This ancillary study will use metagenomic, transcriptomic, and bioinformatics tools to augment the knowledge gained from a randomized controlled trial of an investigational treatment regimen on functional outcomes and mortality in patients with TBM.