Hydrogen sulfide (H₂S) is involved in numerous pathophysiological processes and shares overlapping functions with CO and •NO. However, the importance of host-derived H₂S in microbial pathogenesis is unknown. Here we show that Mtb-infected mice deficient in the H₂S-producing enzyme cystathionine β-synthase (CBS) survive longer with reduced organ burden, and that pharmacological inhibition of CBS reduces Mtb bacillary load in mice. High-resolution respirometry, transcriptomics and mass spectrometry establish that H₂S stimulates Mtb respiration and bioenergetics predominantly via cytochrome bd oxidase, and that H₂S reverses •NO-mediated inhibition of Mtb respiration. Further, exposure of Mtb to H₂S regulates genes involved in sulfur and copper metabolism and the Dos regulon. Our results indicate that Mtb exploits host-derived H₂S to promote growth and disease, and suggest that host-directed therapies targeting H₂S production may be potentially useful for the management of tuberculosis and other microbial infections.

Mycobacterium tuberculosis (Mtb) disrupts glycolytic flux in infected myeloid cells through an unclear mechanism. Flux through the glycolytic pathway in myeloid cells is inextricably linked to the availability of NAD⁺, which is maintained by NAD⁺ salvage and lactate metabolism. Using lung tissue from tuberculosis (TB) patients and myeloid deficient LDHA (Ldha^LysM−/−) mice, we demonstrate that glycolysis in myeloid cells is essential for protective immunity in TB. Glycolytic myeloid cells are essential for the early recruitment of multiple classes of immune cells and IFNγ-mediated protection. We identify NAD⁺ depletion as central to the glycolytic inhibition caused by Mtb. Lastly, we show that the NAD⁺ precursor nicotinamide exerts a host-dependent, antimycobacterial effect, and that nicotinamide prophylaxis and treatment reduce Mtb lung burden in mice. These findings provide insight into how Mtb alters host metabolism through perturbation of NAD(H) homeostasis and reprogramming of glycolysis, highlighting this pathway as a potential therapeutic target.

Accurate lipid annotation is crucial for understanding the role of lipids in health and disease and identifying therapeutic targets. However, annotating the wide variety of lipid species in biological samples remains challenging in untargeted lipidomic studies. In this work, we present a lipid annotation workflow based on LC-MS and MS/MS strategies, the combination of four bioinformatic tools, and a decision tree to support the accurate annotation and semi-quantification of the lipid species present in lung tissue from control mice. The proposed workflow allowed us to generate a lipid lung-based ATLAS (LiLA), which was then employed to unveil the lipidomic signatures of the Mycobacterium tuberculosis infection at two different time points for a deeper understanding of the disease progression. This workflow, combined with manual inspection strategies of MS/MS data, can enhance the annotation process for lipidomic studies and guide the generation of sample-specific lipidome maps. LiLA serves as a freely available data resource that can be employed in future studies to address lipidomic alterations in mice lung tissue.

Accurate lipid annotation is crucial for understanding the role of lipids in health and disease and identifying therapeutic targets. However, annotating the wide variety of lipid species in biological samples remains challenging in untargeted lipidomic studies. In this work, we present an optimized lipid annotation workflow based on the combination of LC-MS and MS/MS strategies, four bioinformatic tools, and a decision-tree-based approach to support the accurate annotation and semi-quantification of the lipid species present in lung tissue from control mice. The developed workflow allowed us to generate a lipid lung-based ATLAS (LiLA), which was then employed to unveil the lipidomic signatures of the Mycobacterium tuberculosis (Mtb) infection at two different time points for a deeper understanding of the disease progression. This workflow, combined with manual inspection strategies of MS/MS data, can enhance the annotation process for lipidomic studies and guide the generation of sample-specific lipidome maps. LiLA serves as a freely available data resource that can be employed in future studies to address lipidomic alterations in mice lung tissue.