Mycobacterium tuberculosis carrying a rifampicin drug resistance mutation reprograms macrophage metabolism through cell wall lipid changes

Howard, Nicole; Marín, Nancy D.; Ahmed, Mushtaq; Rosa, Bruce A.; Martin, John; Bambousková, Monika; Sergushichev, Alexey; Loginicheva, Ekaterina; Kurepina, Natalia; Rangel-Moreno, Javier; Chen, Liang; Kreiswirth, Barry N; Klein, Robyn S.; Balada-Llasat, Joan-Miquel; Torrelles, Jordi B.; Amarasinghe, Gaya K.; Mitreva, Makedonka; Artyomov, Maxim N.; Hsu, Fong‐Fu; Mathema, Barun; Khader, Shabaana A.

doi:10.1038/s41564-018-0245-0

Cited by 95 publications

(114 citation statements)

References 52 publications

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“…We noticed a distinct shift towards longer DIM chain lengths consistent with the reported increase in molecular mass of DIM during Mtb infection 17 . The residual bacterial contamination of the macrophage membrane fractions was less than 1500 cfu, well below the threshold for detection of DIM extracted directly from bacteria (between 10 5 and 10 7 cfu, see Fig. S1b ).…”

Section: Resultsmentioning

confidence: 84%

“…Indeed, Mtb strains lacking DIM are drastically attenuated 3 and are more likely to be killed by the early pulmonary innate immune response 4 , when the bacteria encounter macrophages. Recent work has revealed that DIM modulate macrophage metabolism 5 and immune functions 6, 7 . In particular, DIM increase the ability of Mtb to infect macrophages by modulating phagocytosis 8 , a fundamental immune process involving membrane remodeling.…”

Section: Introductionmentioning

confidence: 99%

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The conical shape of DIM lipids promotes Mycobacterium tuberculosis infection of macrophages

Augenstreich

Haanappel

Ferré

et al. 2019

Preprint

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24Phthiocerol dimycocerosate (DIM) is a major virulence factor of the pathogen 25 Mycobacterium tuberculosis (Mtb). While this lipid promotes the entry of Mtb into 26 macrophages, which occurs via phagocytosis, its molecular mechanism of action is 27 unknown. Here, we combined biophysical, cell biology, and modelling approaches to 28 reveal the molecular mechanism of DIM action on macrophage membranes leading to 29 the first step of Mtb infection. MALDI-TOF mass spectrometry showed that DIM 30 molecules are transferred from the Mtb envelope to macrophage membranes during 31 infection. Multi-scale molecular modeling and 31 P-NMR experiments revealed that DIM 32 adopts a conical shape in membranes and aggregate in the stalks formed between 33 two opposing lipid bilayers. Infection of macrophages pre-treated with lipids of various 34shapes uncovered a general role for conical lipids in promoting phagocytosis. Taken 35 together, these results reveal how the molecular shape of a mycobacterial lipid can 36 modulate the biological function of macrophages. 37 38 we developed a multidisciplinary approach combining multiscale Molecular Dynamics 73 (MD) simulations, solid-state NMR and cell biology experiments. This revealed how 74 the molecular shape of DIM can affect macrophage membranes to promote 75 phagocytosis. 76 77 78 RESULTS 79 80 DIM are transferred to host cell membranes during macrophage infection 81First, we used MALDI-TOF mass spectrometry to assess whether DIM added 82 to host cells is incorporated into their membranes. Human macrophage (THP-1) cells 83 Figure 1: DIM are transferred from the bacterial envelope to macrophage membranes. (a) Structure of the DIM family of lipids, where m denotes the range of carbon atoms on the phthiocerol moiety, and n and p on the mycocerosate moieties. (b) MALDI-TOF mass spectra of purified DIM and of the membrane fraction of macrophages treated with DIM. (c) MALDI-TOF mass spectra of WT Mtb (HR37v) and of the membrane fraction of macrophages infected by H37Rv or by the H37RvDlppX mutant. M: low intensity peak corresponding to the detection of the matrix molecule in the DIM region of interest. The star symbol highlights the mass of the DIM molecule chosen for the modelling, with m=18, n=17, and p=4.

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Section: Resultsmentioning

confidence: 84%

Section: Introductionmentioning

confidence: 99%

The conical shape of DIM lipids promotes Mycobacterium tuberculosis infection of macrophages

Augenstreich

Haanappel

Ferré

et al. 2019

Preprint

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“…Many M. tuberculosis-host factors are involved in this first encounter interface at the initial stages of the infection. First, the constitution of the M. tuberculosis cell envelope, which is strain-dependent, from the worldwide used laboratory strains (M. tuberculosis H 37 R a , M. tuberculosis H 37 R v , and M. tuberculosis Erdman), to the highly transmissible CDC1551, to the hypervirulent HN878, and to several relevant drugresistant M. tuberculosis clinical isolates in endemic TB areas (12)(13)(14)(15)(16). We will discuss their cell envelope glycolipid constitution in relation to their infection outcome.…”

Section: Introductionmentioning

confidence: 99%

Underestimated Manipulative Roles of Mycobacterium tuberculosis Cell Envelope Glycolipids During Infection

2019

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The Mycobacterium tuberculosis cell envelope has been evolving over time to make the bacterium transmissible and adaptable to the human host. In this context, the M. tuberculosis cell envelope contains a peripheral barrier full of lipids, some of them unique, which confer M. tuberculosis with a unique shield against the different host environments that the bacterium will encounter at the different stages of infection. This lipid barrier is mainly composed of glycolipids that can be characterized by three different subsets: trehalose-containing, mannose-containing, and 6-deoxy-pyranose-containing glycolipids. In this review, we explore the roles of these cell envelope glycolipids in M. tuberculosis virulence and pathogenesis, drug resistance, and further, how these glycolipids may dictate the M. tuberculosis cell envelope evolution from ancient to modern strains. Finally, we address how these M. tuberculosis cell envelope glycolipids are impacted by the host lung alveolar environment, their role in vaccination and masking host immunity, and subsequently the impact of these glycolipids in shaping how M. tuberculosis interacts with host cells, manipulating their immune response to favor the establishment of an infection.

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“…This module contains genes related to transcription and nucleotide synthesis, the known target pathway of Rif (Wishart et al (2017)). Other pathways represented here are lipid metabolism and error-prone synthesis and repair, both known mechanisms of resistance to Rif (Howard et al (2018); Boshoff et al (2003) Table 2: Response TopNets of all 18 drugs are connected graphs with > 50% nodes in a single connected component (CC). In contrast, the graphs induced by the same number of top DEGs, and by randomly sampling the same number of nodes or edges as the TopNet are highly disconnected.…”

Section: Rif Exposure Topnet Reveals the Perturbation Of Nucleotide Smentioning

confidence: 99%

PathExt: a general framework for path-based mining of omics-integrated biological networks

Sambaturu

Pusadkar

Hannenhalli

et al. 2020

Preprint

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Motivation: Large scale transcriptomic data are routinely used to prioritize genes underlying specific phenotypes. Current approaches largely focus on differentially expressed genes (DEGs), despite the recognition that phenotypes emerge via a network of interactions between genes and proteins, many of which may not be differentially expressed. Furthermore, many practical applications lack sufficient samples or an appropriate control to robustly identify statistically significant DEGs. Results: We provide a computational tool -PathExt, which, in contrast to differential genes, identifies differentially active paths when a control is available, and most active paths otherwise, in an omics-integrated biological network. The sub-network comprising such paths, referred to as the Top-Net, captures the most relevant genes and processes underlying the specific biological context. The TopNet forms a well-connected graph, reflecting the tight orchestration in biological systems. Two key advantages of PathExt are (i) it can extract characteristic genes and pathways even when only a single sample is available, and (ii) it can be used to study a system even in the absence of an appropriate control. We demonstrate the utility of PathExt via two diverse sets of case studies, to characterize (a) Mycobacterium tuberculosis (M.tb) response upon exposure to 18 antibacterial drugs where only one transcriptomic sample is available for each exposure; and (b) tissue-relevant genes and processes using transcriptomic data from GTEx (Genotype-Tissue Expression) for 39 human tissues. Overall, PathExt is a general tool for prioritizing context-relevant genes in any omics-integrated biological network for any condition(s) of interest, even with a single sample or in the absence of appropriate controls. Availability: The source code for PathExt is available at https://github.com/NarmadaSambaturu/PathExt. Contact: nchandra@iisc.ac.in, sridhar.hannenhalli@nih.gov

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Mycobacterium tuberculosis carrying a rifampicin drug resistance mutation reprograms macrophage metabolism through cell wall lipid changes

Cited by 95 publications

References 52 publications

The conical shape of DIM lipids promotes Mycobacterium tuberculosis infection of macrophages

The conical shape of DIM lipids promotes Mycobacterium tuberculosis infection of macrophages

Underestimated Manipulative Roles of Mycobacterium tuberculosis Cell Envelope Glycolipids During Infection

PathExt: a general framework for path-based mining of omics-integrated biological networks

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