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Mycobacterium tuberculosis virulence lipid PDIM inhibits autophagy in mice

Nature Microbiology (2024)Cite this article

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Abstract

Mycobacterium tuberculosis (Mtb) infects several lung macrophage populations, which have distinct abilities to restrict Mtb. What enables Mtb survival in certain macrophage populations is not well understood. Here we used transposon sequencing analysis of Mtb in wild-type and autophagy-deficient mouse macrophages lacking ATG5 or ATG7, and found that Mtb genes involved in phthiocerol dimycocerosate (PDIM) virulence lipid synthesis confer resistance to autophagy. Using ppsD mutant Mtb, we found that PDIM inhibits LC3-associated phagocytosis (LAP) by inhibiting phagosome recruitment of NADPH oxidase. In mice, PDIM protected Mtb from LAP and classical autophagy. During acute infection, PDIM was dispensable for Mtb survival in alveolar macrophages but required for survival in non-alveolar macrophages in an autophagy-dependent manner. During chronic infection, autophagy-deficient mice succumbed to infection with PDIM-deficient Mtb, with impairments in B-cell accumulation in lymphoid follicles. These findings demonstrate that PDIM contributes to Mtb virulence and immune evasion, revealing a contributory role for autophagy in B-cell responses.

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Fig. 1: PDIM confers resistance to Atg5, Atg7, Nox2 and Rbcn.
Fig. 2: PDIM inhibits the NADPH oxidase and LAP in macrophages.
Fig. 3: PDIM protects Mtb from Atg5, Atg7, Nox2, Rbcn and Atg14-dependent processes in vivo.
Fig. 4: Atg5, Atg7 and Atg14 are required to control ΔppsD Mtb in macrophages in vivo.
Fig. 5: Autophagy protects mice during chronic infection with ΔppsD Mtb.
Fig. 6: Autophagy is required for B-cell follicles during chronic infection with ΔppsD Mtb.

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Data availability

The Tn-Seq datasets generated and analysed during the current study are available at GEO (GSE271206). Additional data are available in the source data files. Source data are provided with this paper.

Code availability

No proprietary code was used. The TRANSIT software is available and has been previously described52. The source code is distributed under the GNU GPL v.3 license and can be obtained from GitHub at https://github.com/mad-lab/transit.

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Acknowledgements

We dedicate this paper to the memory of our dear colleague, Guozhe Yang. This work was supported by Washington University School of Medicine, NIH AI087682, and AI130454 to J.A.P.; NIH AI132130 to C.M.S.; and Arnold O. Beckman Postdoctoral Fellowship to A.J.O. We thank the Genome Technology Access Center at the McDonnell Genome Institute at Washington University School of Medicine for help with genomic analysis. The Center is partially supported by NCI Cancer Center Support Grant #P30 CA91842 to the Siteman Cancer Center from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. This publication is solely the responsibility of the authors and does not necessarily represent the official view of NCRR or NIH. We thank the Pulmonary Morphology Core (WUSM) for histologic services, the Hope Center Alafi Neuroimaging Lab for slide scanning, and the Bursky Center for Human Immunology and Immunotherapy (WUSM) for cytokine analysis. We thank M. Dinauer (WUSM), H. W. Virgin (WUSM), C. Stallings (WUSM), and D. Young (St Jude’s Children’s Research Hospital) for their generosity in providing mice; A. K. Barczak (Ragon Institute of Mass General, MIT, Harvard) for providing PDIM mutant strains; S. Tan for the rv2390c’::GFP, smyc’::mCherry plasmid; T. Ioerger (Texas A&M College of Engineering) and M. DeJesus (Texas A&M College of Engineering) for help with TRANSIT; W. Beatty for help with electron microscopy; and members of the Philips laboratory for helpful discussions.

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Author notes

  1. Deceased: Guozhe Yang.

Authors and Affiliations

  1. Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St Louis, MO, USA

    Ekansh Mittal, G. V. R. Krishna Prasad, Sandeep Upadhyay, Jully Sadadiwala, Guozhe Yang & Jennifer A. Philips

  2. Department of Molecular Microbiology, Washington University School of Medicine, St Louis, MO, USA

    G. V. R. Krishna Prasad, Sandeep Upadhyay, Jully Sadadiwala, Guozhe Yang & Jennifer A. Philips

  3. Department of Microbiology and Physiological Systems, UMass Chan Medical School, Worcester, MA, USA

    Andrew J. Olive & Christopher M. Sassetti

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Contributions

E.M. conceptualized the project, conducted formal analysis, investigation and visualization, developed the methodology, wrote the original draft, and reviewed and edited the manuscript. G.V.R.K.P. conducted formal analysis, investigation and visualization. S.U. and J.S. conducted investigations. A.J.O. conducted investigations, supervised the project and acquired funding acquisition. G.Y. procured resources. C.M.S. procured resources, supervised the project and acquired funding. J.A.P. conceptualized the project, procured resources, conducted formal analysis, supervised the project, acquired funding, performed visualization, wrote the original draft, administered the project, and reviewed and edited the manuscript.

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Correspondence to Ekansh Mittal or Jennifer A. Philips.

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Extended data

Extended Data Fig. 1 PDIM and ESX-1 elicit different damage responses from macrophages.

(a-d) WT BMDMs were infected for 3 h with (a) PKH-labeled H37Rv (WT), ΔppsD, ΔppsD::ppsD, or ΔesxA Mtb; or with (b-d) GFP-expressing H37Rv (WT), ΔdrrB Mtb, or ΔesxA Mtb prepared using a 5μm filter. Automated image analysis was used to quantify the MFI of (a-b) CHMP1A, (c) CHMP1B, (d) CHMP4B colocalized with individual bacilli from 5 fields. Data consists of more than 89 bacilli per group. Data are means ± SEM from one representative experiment of three. One-way ANOVA with Tukey’s multiple comparisons test.

Source data

Extended Data Fig. 2 Intracellular growth of Erdman is restricted by autophagy while intracellular growth of H37Rv is unaffected.

(a) Atg7 cKO and (b) Atg14 cKO BMDMs and their respective controls were infected with H37Rv or Erdman Mtb at MOI 5. CFU were calculated 4 hpi, 3 dpi, and 5 dpi. Data show the mean ± SEM of one representative experiment from at least 2 independent experiments. Data from at least 5 samples per group. p value comparing Erdman Mtb in WT and KO BMDMs at 5 dpi; two-way ANOVA with Tukey’s multiple comparisons test.

Source data

Extended Data Fig. 3 PDIM inhibits NADPH oxidase recruitment to Mtb phagosomes.

(a-d) WT BMDMs were infected with GFP-expressing Mtb strains for 4 h. Single cell bacterial suspension was generated by (a-b) slow speed spin or (c−d) passage through a 5μm filter. (a, c-d) IF maximum-intensity projection images of (a) p40phox, (c) LC3 and p40phox, and (d) LC3 and GAL3. Scale bar, 10 μm for leftmost panels and 2.5μm for all zoomed images. Boxed areas in the merged image are shown in higher magnification in the rightmost panels. (b) Automated image analysis was used to quantify the MFI of p40phox colocalized with individual bacilli from 5 fields. Data consists of more than 100 bacilli per group. Data are means ± SEM from one representative experiment of three. Unpaired two-tailed t test. Automated quantification of MFI of panels c and d are shown in Fig. 2g–j.

Source data

Extended Data Fig. 4 Growth of ΔppsD Mtb in the spleen is restricted by Atg5, Atg7, and Atg14 and not significantly impacted by Nox2 or Rbcn.

(a-h) (a and f) Atg5 cKO; (b and g) Atg7 cKO; (c) Nox2 KO; (d) Rbcn KO; and (e and h) Atg14 cKO mice and their littermate controls were infected by aerosol with (a-e) low dose (CFU ~ 100) ΔppsD or ΔppsD::ppsD or (f-h) high dose (CFU ~ 1000-1500) GFP-expressing H37Rv (WT) or ΔppsD Mtb as described in Fig. 3. (a-e) In low dose experiments, CFU were enumerated from spleen 17 dpi for Atg5 cKO and 14 and 28 dpi for Atg7 cKO, Atg14 cKO, Nox2 KO and Rbcn KO; n = 5 per group for Atg5 cKO, Atg7 cKO, Atg14 cKO, and Rbcn KO while n = 10 per group for Nox2 KO. (f-h) In high dose experiments, CFU were enumerated from spleens at 17 dpi, and n = 5 mice per group for all indicated strains. All low and high dose experiments were done twice except Atg7 cKO at low dose. The Atg7 cKO was tested once at low dose, and 2 times at high dose. Data show the mean ± SEM; p-value from Brown Forsythe and Welch ANOVA with Dunnett’s (T3) multiple comparisons test with pre-selected comparisons for panel a, b, f-h and unpaired two-tailed t test for panel c-e.

Source data

Extended Data Fig. 5 Lung cytokine levels in mice infected with ΔppsD Mtb, the complemented strain, or H37Rv (WT).

(a) Atg5 and Atg7 Cre−/− (WT) control mice were infected by aerosol with low dose ΔppsD or ΔppsD::ppsD Mtb. (b) Atg5, Atg7 and Atg14 Cre−/− (WT) littermate control mice were infected by aerosol with high dose H37Rv (WT) or ΔppsD Mtb as shown in Fig. 3. The cytokine levels in lung homogenates were analyzed by multiplex cytokine kit (a) 14 dpi and (b) 17 dpi. Each data point represents one mouse; n = 10 mice per group for panel a, and n = 15 mice per group for panel b; data show the mean ± SEM; p value from unpaired, two-tailed t test.

Source data

Extended Data Fig. 6 Lung IL-1β, IL-6, GM-CSF, and TNF-α levels from ΔppsD Mtb infected mice were elevated in Atg5, Atg7, and Atg14 cKO mice and not significantly impacted by Nox2 or Rbcn.

(a-e) Indicated mouse strains were infected by aerosol with low dose ΔppsD Mtb as described in Fig. 3. Cytokine levels in lung homogenates of ΔppsD Mtb-infected (a) Atg5 cKO, (b) Atg7 cKO, (c) Atg14 cKO, (d) Nox2 KO and (e) Rbcn KO 14 dpi. Each data point represents one mouse; n = 5 for Atg5 and Atg7; n = 6 for Atg14 and Rbcn; n = 10 for Nox2 mice per group; data show the mean ± SEM; unpaired two-tailed t test.

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Extended Data Fig. 7 Gating strategy for lung myeloid and lymphoid cells.

(a-b) Flow cytometry plots of lung cells from a control mouse to illustrate gating strategy for myeloid (a) and lymphoid (b) cells. FSC−A: forward scatter (area); SSC-A: side scatter (area); FSC-W: forward scatter (width); FVD: fixable viability dye.

Extended Data Fig. 8 Myeloid and lymphoid responses are not significantly different in Cre-/- (WT) mice infected with WT Mtb compared to ΔppsD Mtb with the exception of the number of NK1.1 cells.

(a-c) Atg5, Atg7 or Atg14 cKO and littermate control mice were infected by aerosol with high dose (CFU ~ 1000-1500) GFP-expressing H37Rv or ΔppsD, and lungs were harvested 17 dpi for flow cytometry as described in Fig. 4. Number of (a) myeloid and (b) lymphoid cells from infected lungs of all WT (Cre−/− mice. (c) Number of NK1.1 cells from indicated Atg cKO mice. Each data point represents one mouse. Data consists of 15-20 mice per group for panel a and b, and 9-15 mice per group for panel c. Error bars indicate SEM; p-value from Brown Forsythe and Welch ANOVA with Dunnett’s (T3) multiple comparisons test with pre-selected comparisons.

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Extended Data Fig. 9 Impact of PDIM, autophagy, and PMN-depletion on myeloid responses in the lung.

(a-b) Atg5, Atg7 or Atg14 cKO and littermate control mice were infected by aerosol with high dose (CFU ~ 1000-1500) GFP-expressing H37Rv or ΔppsD Mtb, and lungs were harvested 17 dpi for flow cytometry as described in Fig. 3. Number of (a) PMNs or (b) infected PMNs in the lungs. (c−f) Atg14 cKO mice and littermate controls were infected with high dose GFP-expressing ΔppsD Mtb and treated with antibody to deplete PMNs (white bars) or isotype control (orange bars). Number of (c and e) myeloid and (d and f) infected myeloid cells in (c−d) Atg14 Cre-/- (WT) mice or (e-f) Atg14 Cre+/- (cKO) mice with or without PMNs depletion. PMN depletion led to more (c) recruitment and (d) infection of non-AMs in the Atg14 Cre-/- (WT) mice while no difference was seen in the (e) recruitment or (f) infection of non-AM in the Atg14 Cre+/- (cKO) mice. Each data point represents one mouse. Data consists of 8-15 mice per group for panel a, b; and 5 mice per group for panel c−f. Error bars indicate SEM; p-value from Brown Forsythe and Welch ANOVA with Dunnett’s (T3) multiple comparisons test with pre-selected comparisons for panel a-c, e, and f; unpaired two tailed t-test for panel d.

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Extended Data Fig. 10 Analysis of myeloid cells and hematoxylin and eosin (H&E) staining of lungs during chronic infection in autophagy-deficient mice.

(a-e) Atg7 or Atg14 cKO and littermate control mice were infected by aerosol with high dose (CFU ~ 1000-1500) ΔppsD Mtb as described in Fig. 5. The inflammatory infiltrate in the lungs was analyzed by flow cytometry and immune histopathology at 100 days for Atg5, 200 days for Atg7, 130 days for Atg14. Number of (a-b) myeloid cells in (a) Atg7 and (b) Atg14-deficient mice and controls. Each data point represents one mouse. Error bars indicate SEM. P-value from one-way ANOVA with Sidak’s multiple comparisons test with pre-selected pair. (c−e) Histopathology of lungs from ΔppsD Mtb-infected Atg-deficient mice from same experiment. Lungs were harvested, embedded in paraffin, sectioned, and stained with H&E. Images shown are representative of at least 3 mice per group from one experiment. Scale bars = 500 μM.

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Supplementary information

Supplementary Information

Gating strategy for Fig. 2o.

Reporting Summary

Supplementary Table 1

Tn-Seq results from infection of BMDMs from Atg5 and Atg7 cKO mice compared to corresponding littermate controls. P values were obtained by resampling as described (https://transit.readthedocs.io/en/latest/method_resampling.html; DeJesus, M. A., Ambadipudi, C., Baker, R., Sassetti, C. & Ioerger, T. R. TRANSIT - a software tool for Himar1 Tn-Seq analysis. PLoS Comput. Biol. 11, e1004401 (2015)); adj. P value accounts for multiple testing.

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Statistical source data for Fig. 1c–h.

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Statistical source data for Fig. 2b,e–j,l,n,p.

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Supporting WB gels for Fig. 2c.

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Statistical source data for Fig. 3a–k.

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Statistical source data for Fig. 4a,d–i,m,n.

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Statistical source data for Fig. 5a–c,e–g,i–k.

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Statistical source data for Fig. 6a,b,d,f,h.

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Statistical source data for Extended Data Fig. 1a–d.

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Statistical source data for Extended Data Fig. 2a,b.

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Statistical source data for Extended Data Fig. 3b.

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Statistical source data for Extended Data Fig. 4a–h.

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Statistical source data for Extended Data Fig. 5a,b.

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Statistical source data for Extended Data Fig. 6a–e.

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Statistical source data for Extended Data Fig. 8a–c.

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Statistical source data for Extended Data Fig. 9a–f.

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Statistical source data for Extended Data Fig. 10a,b.

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Mittal, E., Prasad, G.V.R.K., Upadhyay, S. et al. Mycobacterium tuberculosis virulence lipid PDIM inhibits autophagy in mice. Nat Microbiol (2024). https://doi.org/10.1038/s41564-024-01797-5

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