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Mesenchymal stem cells offer a drug-tolerant and immune-privileged niche to Mycobacterium tuberculosis.

ABSTRACT: Anti-tuberculosis (TB) drugs, while being highly potent in vitro, require prolonged treatment to control Mycobacterium tuberculosis (Mtb) infections in vivo. We report here that mesenchymal stem cells (MSCs) shelter Mtb to help tolerate anti-TB drugs. MSCs readily take up Mtb and allow unabated mycobacterial growth despite having a functional innate pathway of phagosome maturation. Unlike macrophage-resident ones, MSC-resident Mtb tolerates anti-TB drugs remarkably well, a phenomenon requiring proteins ABCC1, ABCG2 and vacuolar-type H⁺ATPases. Additionally, the classic pro-inflammatory cytokines IFNγ and TNFα aid mycobacterial growth within MSCs. Mechanistically, evading drugs and inflammatory cytokines by MSC-resident Mtb is dependent on elevated PGE2 signaling, which we verify in vivo analyzing sorted CD45^-Sca1⁺CD73⁺-MSCs from lungs of infected mice. Moreover, MSCs are observed in and around human tuberculosis granulomas, harboring Mtb bacilli. We therefore propose, targeting the unique immune-privileged niche, provided by MSCs to Mtb, can have a major impact on tuberculosis prevention and cure.

SUBMITTER: Jain N

PROVIDER: S-EPMC7297998 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Mesenchymal stem cells offer a drug-tolerant and immune-privileged niche to Mycobacterium tuberculosis.

Jain Neharika N Kalam Haroon H Singh Lakshyaveer L Sharma Vartika V Kedia Saurabh S Das Prasenjit P Ahuja Vineet V Kumar Dhiraj D

Nature communications 20200616 1

Anti-tuberculosis (TB) drugs, while being highly potent in vitro, require prolonged treatment to control Mycobacterium tuberculosis (Mtb) infections in vivo. We report here that mesenchymal stem cells (MSCs) shelter Mtb to help tolerate anti-TB drugs. MSCs readily take up Mtb and allow unabated mycobacterial growth despite having a functional innate pathway of phagosome maturation. Unlike macrophage-resident ones, MSC-resident Mtb tolerates anti-TB drugs remarkably well, a phenomenon requiring p ...[more]

PMID: 32546788

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Project description:BackgroundMycobacterium tuberculosis (M.tb) is the causative agent of tuberculosis, killing ~1.7 million people annually. The remarkable capacity of this pathogen to escape the host immune system for decades and then to cause active tuberculosis disease, makes M.tb a successful pathogen. Currently available anti-mycobacterial therapy has poor compliance due to requirement of prolonged treatment resulting in accelerated emergence of drug resistant strains. Hence, there is an urgent need to identify new chemical entities with novel mechanism of action and potent activity against the drug resistant strains.ResultsThis study describes novel computational models developed for predicting inhibitors against both replicative and non-replicative phase of drug-tolerant M.tb under carbon starvation stage. These models were trained on highly diverse dataset of 2135 compounds using four classes of binary fingerprint namely PubChem, MACCS, EState, SubStructure. We achieved the best performance Matthews correlation coefficient (MCC) of 0.45 using the model based on MACCS fingerprints for replicative phase inhibitor dataset. In case of non-replicative phase, Hybrid model based on PubChem, MACCS, EState, SubStructure fingerprints performed better with maximum MCC value of 0.28. In this study, we have shown that molecular weight, polar surface area and rotatable bond count of inhibitors (replicating and non-replicating phase) are significantly different from non-inhibitors. The fragment analysis suggests that substructures like hetero_N_nonbasic, heterocyclic, carboxylic_ester, and hetero_N_basic_no_H are predominant in replicating phase inhibitors while hetero_O, ketone, secondary_mixed_amine are preferred in the non-replicative phase inhibitors. It was observed that nitro, alkyne, and enamine are important for the molecules inhibiting bacilli residing in both the phases. In this study, we introduced a new algorithm based on Matthews correlation coefficient called MCCA for feature selection and found that this algorithm is better or comparable to frequency based approach.ConclusionIn this study, we have developed computational models to predict phase specific inhibitors against drug resistant strains of M.tb grown under carbon starvation. Based on simple molecular properties, we have derived some rules, which would be useful in robust identification of tuberculosis inhibitors. Based on these observations, we have developed a webserver for predicting inhibitors against drug tolerant M.tb H37Rv available at http://crdd.osdd.net/oscadd/mdri/.

Dataset Information

Mesenchymal stem cells offer a drug-tolerant and immune-privileged niche to Mycobacterium tuberculosis.

Publications

Mesenchymal stem cells offer a drug-tolerant and immune-privileged niche to Mycobacterium tuberculosis.

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