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ABSTRACT Tuberculosis (TB) is notoriously difficult to treat, likely due to the complex host-pathogen interactions driven by pathogen heterogeneity. An understudied area of TB pathogenesis is host responses toMycobacterium tuberculosisbacteria (Mtb) that are limited in zinc ions. This distinct population resides in necrotic granulomas and sputum and could be the key player in tuberculosis pathogenicity. In this study, we tested the hypothesis that macrophages differentiate between Mtb grown under zinc limitation or in the standard zinc-replete medium. Using several macrophage infection models, such as murine RAW 264.7 and murine bone marrow-derived macrophages (BMDMs), as well as human THP-1-derived macrophages, we show that macrophages infected with zinc-limited Mtb have increased bacterial burden compared with macrophages infected with zinc-replete Mtb. We further demonstrate that macrophage infection with zinc-limited Mtb trigger higher production of reactive oxygen species (ROS) and cause more macrophage death. Furthermore, the increased ROS production is linked to the increased phagocytosis of zinc-limited Mtb, whereas cell death is not. Finally, transcriptional analysis of RAW 264.7 macrophages demonstrates that macrophages have more robust pro-inflammatory responses when infected with zinc-limited Mtb than zinc-replete Mtb. Together, our findings suggest that Mtb’s access to zinc affects their interaction with macrophages and that zinc-limited Mtb may be influencing TB progression. Therefore, zinc availability in bacterial growth medium should be considered in TB drug and vaccine developments. 

Despite being disproportionately impacted by health disparities, Black, Hispanic, Indigenous, and other underrepresented populations account for a significant minority of graduates in biomedical data science-related disciplines. Given their commitment to educating underrepresented students and trainees, minority serving institutions (MSIs) can play a significant role in enhancing diversity in the biomedical data science workforce. Little has been published about the reach, curricular breadth, and best practices for delivering these data science training programs. The purpose of this paper is to summarize six Research Centers in Minority Institutions (RCMIs) awarded funding from the National Institute of Minority Health Disparities (NIMHD) to develop new data science training programs. A cross-sectional survey was conducted to better understand the demographics of learners served, curricular topics covered, methods of instruction and assessment, challenges, and recommendations by program directors. Programs demonstrated overall success in reach and curricular diversity, serving a broad range of students and faculty, while also covering a broad range of topics. The main challenges highlighted were a lack of resources and infrastructure and teaching learners with varying levels of experience and knowledge. Further investments in MSIs are needed to sustain training efforts and develop pathways for diversifying the biomedical data science workforce.