Normalizing granuloma vasculature and matrix improves drug delivery and reduces bacterial burden in tuberculosis-infected rabbits

使肉芽肿血管和基质正常化可改善药物输送并减少结核病感染兔的细菌负担

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作者:Meenal Datta #, Laura E Via #, Véronique Dartois #, Danielle M Weiner, Matthew Zimmerman, Firat Kaya, April M Walker, Joel D Fleegle, Isaac D Raplee, Colton McNinch, Maksym Zarodniuk, Walid S Kamoun, Changli Yue, Ashwin S Kumar, Sonu Subudhi, Lei Xu, Clifton E Barry 3rd, Rakesh K Jain

Abstract

Host-directed therapies (HDTs) represent an emerging approach for bacterial clearance during tuberculosis (TB) infection. While most HDTs are designed and implemented for immuno-modulation, other host targets-such as nonimmune stromal components found in pulmonary granulomas-may prove equally viable. Building on our previous work characterizing and normalizing the aberrant granuloma-associated vasculature, here we demonstrate that FDA-approved therapies (bevacizumab and losartan, respectively) can be repurposed as HDTs to normalize blood vessels and extracellular matrix (ECM), improve drug delivery, and reduce bacterial loads in TB granulomas. Granulomas feature an overabundance of ECM and compressed blood vessels, both of which are effectively reduced by losartan treatment in the rabbit model of TB. Combining both HDTs promotes secretion of proinflammatory cytokines and improves anti-TB drug delivery. Finally, alone and in combination with second-line antitubercular agents (moxifloxacin or bedaquiline), these HDTs significantly reduce bacterial burden. RNA sequencing analysis of HDT-treated lung and granuloma tissues implicates up-regulated antimicrobial peptide and proinflammatory gene expression by ciliated epithelial airway cells as a putative mechanism of the observed antitubercular benefits in the absence of chemotherapy. These findings demonstrate that bevacizumab and losartan are well-tolerated stroma-targeting HDTs, normalize the granuloma microenvironment, and improve TB outcomes, providing the rationale to clinically test this combination in TB patients.

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