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Biotin-dependent cell envelope remodelling is required for Mycobacterium abscessus survival in lung infection

Nature Microbiology volume 8, pages 481–497 (2023)Cite this article

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Abstract

Mycobacterium abscessus is an emerging pathogen causing lung infection predominantly in patients with underlying structural abnormalities or lung disease and is resistant to most frontline antibiotics. As the pathogenic mechanisms of M. abscessus in the context of the lung are not well-understood, we developed an infection model using air–liquid interface culture and performed a transposon mutagenesis and sequencing screen to identify genes differentially required for bacterial survival in the lung. Biotin cofactor synthesis was required for M. abscessus growth due to increased intracellular biotin demand, while pharmacological inhibition of biotin synthesis prevented bacterial proliferation. Biotin was required for fatty acid remodelling, which increased cell envelope fluidity and promoted M. abscessus survival in the alkaline lung environment. Together, these results indicate that biotin-dependent fatty acid remodelling plays a critical role in pathogenic adaptation to the lung niche, suggesting that biotin synthesis and fatty acid metabolism might provide therapeutic targets for treatment of M. abscessus infection.

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Fig. 1: Air–liquid interface culture model for M. abscessus lung infection.
Fig. 2: Biotin synthesis is required in culture medium and lung infection model despite presence of biotin.
Fig. 3: Physiological environments impose demand for biotin synthesis.
Fig. 4: Biotin is required to support fatty acid remodelling that sustains envelope fluidity.
Fig. 5: Physiological pH alters fatty acid profile and imposes increased demand for biotin.

Materials availability

All reagents generated in this study are available upon request from the corresponding author.

Data availability

All relevant data generated in this study are present within the manuscript and its Supplementary Information, with the following exceptions. Whole genome sequencing data for strain T35 are available on SRA (https://www.ncbi.nlm.nih.gov/sra) under project number PRJNA840944, accession number SAMN28571509. Raw TnSeq data are available on SRA under project number PRJNA902827. Source data are provided with this paper.

Code availability

R scripts used for this study are included as Supplementary File 4, and all files called by that R script are included as Supplementary Files 5–8.

References

  1. Winthrop, K. L. et al. Incidence and prevalence of nontuberculous mycobacterial lung disease in a large U.S. managed care health plan, 2008–2015. Ann. Am. Thorac. Soc. 17, 178–185 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Whipps, C. M., Lieggi, C. & Wagner, R. Mycobacteriosis in zebrafish colonies. ILAR J. 53, 95–105 (2012).

    Article  CAS  PubMed  Google Scholar 

  3. Adekambi, T., Ben Salah, S., Khlif, M., Raoult, D. & Drancourt, M. Survival of environmental mycobacteria in Acanthamoeba polyphaga. Appl. Environ. Microbiol. 72, 5974–5981 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Oh, C. T., Moon, C., Jeong, M. S., Kwon, S. H. & Jang, J. Drosophila melanogaster model for Mycobacterium abscessus infection. Microbes Infect. 15, 788–795 (2013).

    Article  CAS  PubMed  Google Scholar 

  5. Zhang, Z. X., Cherng, B. P. Z., Sng, L. H. & Tan, Y. E. Clinical and microbiological characteristics of non-tuberculous mycobacteria diseases in Singapore with a focus on pulmonary disease, 2012–2016. BMC Infect. Dis. 19, 436 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Victoria, L., Gupta, A., Gomez, J. L. & Robledo, J. Mycobacterium abscessus complex: a review of recent developments in an emerging pathogen. Front. Cell Infect. Microbiol. 11, 659997 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Fennelly, K. P. et al. Biofilm formation by Mycobacterium abscessus in a lung cavity. Am. J. Respir. Crit. Care Med. 193, 692–693 (2016).

    Article  PubMed  Google Scholar 

  8. Qvist, T. et al. Chronic pulmonary disease with Mycobacterium abscessus complex is a biofilm infection. Eur. Respir. J. 46, 1823–1826 (2015).

    Article  CAS  PubMed  Google Scholar 

  9. Choi, S. et al. Histopathologic analysis of surgically resected lungs of patients with non-tuberculous mycobacterial lung disease: a retrospective and hypothesis-generating study. Yale J. Biol. Med. 94, 527–535 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Bryant, J. M. et al. Stepwise pathogenic evolution of Mycobacterium abscessus. Science https://doi.org/10.1126/science.abb8699 (2021).

  11. McShane, A. et al. Mucus. Curr. Biol. 31, R938–R945 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Pezzulo, A. A. et al. Reduced airway surface pH impairs bacterial killing in the porcine cystic fibrosis lung. Nature 487, 109–113 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Kim, D. et al. Large pH oscillations promote host defense against human airways infection. J. Exp. Med. 218, e20201831 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Chen, J. et al. Clinical efficacy and adverse effects of antibiotics used to treat Mycobacterium abscessus pulmonary disease. Front. Microbiol. 10, 1977 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Haworth, C. S. et al. British Thoracic Society guidelines for the management of non-tuberculous mycobacterial pulmonary disease (NTM-PD). Thorax 72, ii1–ii64 (2017).

    Article  PubMed  Google Scholar 

  16. Akusobi, C. et al. Transposon mutagenesis in Mycobacterium abscessus identifies an essential penicillin-binding protein involved in septal peptidoglycan synthesis and antibiotic sensitivity. eLife 11, e71947 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Rifat, D., Chen, L., Kreiswirth, B. N. & Nuermberger, E. L. Genome-wide essentiality analysis of Mycobacterium abscessus by saturated transposon mutagenesis and deep sequencing. mBio 12, e0104921 (2021).

    Article  PubMed  Google Scholar 

  18. Sastry, A. V. et al. Machine learning of bacterial transcriptomes reveals responses underlying differential antibiotic susceptibility. mSphere 6, e0044321 (2021).

    Article  PubMed  Google Scholar 

  19. Catherinot, E. et al. Hypervirulence of a rough variant of the Mycobacterium abscessus type strain. Infect. Immun. 75, 1055–1058 (2007).

    Article  CAS  PubMed  Google Scholar 

  20. Roux, A. L. et al. The distinct fate of smooth and rough Mycobacterium abscessus variants inside macrophages. Open Biol. 6, 160185 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Kim, B. R., Kim, B. J., Kook, Y. H. & Kim, B. J. Phagosome escape of rough Mycobacterium abscessus strains in murine macrophage via phagosomal rupture can lead to type I interferon production and their cell-to-cell spread. Front. Immunol. 10, 125 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Feng, Z. et al. Differential responses by human macrophages to infection with Mycobacterium tuberculosis and non-tuberculous mycobacteria. Front. Microbiol. 11, 116 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Dubois, V. et al. Mycobacterium abscessus virulence traits unraveled by transcriptomic profiling in amoeba and macrophages. PLoS Pathog. 15, e1008069 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Laencina, L. et al. Identification of genes required for Mycobacterium abscessus growth in vivo with a prominent role of the ESX-4 locus. Proc. Natl Acad. Sci. USA 115, E1002–E1011 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Byrd, T. F. & Lyons, C. R. Preliminary characterization of a Mycobacterium abscessus mutant in human and murine models of infection. Infect. Immun. 67, 4700–4707 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Lerat, I. et al. In vivo evaluation of antibiotic activity against Mycobacterium abscessus. J. Infect. Dis. 209, 905–912 (2014).

    Article  CAS  PubMed  Google Scholar 

  27. Maggioncalda, E. C. et al. A mouse model of pulmonary Mycobacteroides abscessus infection. Sci. Rep. 10, 3690 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Belardinelli, J. M. et al. Therapeutic efficacy of antimalarial drugs targeting DosRS signaling in Mycobacterium abscessus. Sci. Transl. Med. 14, eabj3860 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Bernut, A., Herrmann, J. L., Ordway, D. & Kremer, L. The diverse cellular and animal models to decipher the physiopathological traits of Mycobacterium abscessus infection. Front. Cell Infect. Microbiol. 7, 100 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Riva, C. et al. A new model of chronic Mycobacterium abscessus lung infection in immunocompetent mice. Int. J. Mol. Sci. 21, 6590 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Dick, T., Shin, S. J., Koh, W. J., Dartois, V. & Gengenbacher, M. Rifabutin is active against Mycobacterium abscessus in mice. Antimicrob. Agents Chemother. 64, e01943-19 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Bernut, A. et al. Mycobacterium abscessus cording prevents phagocytosis and promotes abscess formation. Proc. Natl Acad. Sci. USA 111, E943–E952 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Iakobachvili, N. et al. Mycobacteria-host interactions in human bronchiolar airway organoids. Mol. Microbiol. 117, 682–692 (2022).

    Article  CAS  PubMed  Google Scholar 

  34. Leon-Icaza, S. A. et al. Cystic fibrosis patient-derived bronchial organoids unveil druggable pathways against Mycobacterium abscessus infection. Preprint at bioRxiv https://doi.org/10.1101/2022.01.03.474765 (2022).

  35. Molina-Torres, C. A. et al. Ex vivo infection of murine precision-cut lung tissue slices with Mycobacterium abscessus: a model to study antimycobacterial agents. Ann. Clin. Microbiol. Antimicrob. 19, 52 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Matsuyama, M. et al. Transcriptional response of respiratory epithelium to nontuberculous mycobacteria. Am. J. Respir. Cell Mol. Biol. 58, 241–252 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Zabner, J. et al. Development of cystic fibrosis and noncystic fibrosis airway cell lines. Am. J. Physiol. Lung Cell. Mol. Physiol. 284, L844–L854 (2003).

    Article  CAS  PubMed  Google Scholar 

  38. Andreu, N. et al. Optimisation of bioluminescent reporters for use with mycobacteria. PLoS ONE 5, e10777 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Howard, S. T. et al. Spontaneous reversion of Mycobacterium abscessus from a smooth to a rough morphotype is associated with reduced expression of glycopeptidolipid and reacquisition of an invasive phenotype. Microbiology 152, 1581–1590 (2006).

    Article  CAS  PubMed  Google Scholar 

  40. Akusobi, C. Interrogating Genetic Diversity in Mycobacterium abscessus with Transposon-Sequencing. Ph.D. thesis, Harvard T.H. Chan School of Public Health (2020).

  41. Bindels, D. S. et al. mScarlet: a bright monomeric red fluorescent protein for cellular imaging. Nat. Methods 14, 53–56 (2017).

    Article  CAS  PubMed  Google Scholar 

  42. Kwon, Y. M., Ricke, S. C. & Mandal, R. K. Transposon sequencing: methods and expanding applications. Appl. Microbiol. Biotechnol. 100, 31–43 (2016).

    Article  CAS  PubMed  Google Scholar 

  43. Ersoy, S. C. et al. Correcting a fundamental flaw in the paradigm for antimicrobial susceptibility testing. EBioMedicine 20, 173–181 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Thuy, L. P., Sweetman, L. & Nyhan, W. L. A new immunochemical assay for biotin. Clin. Chim. Acta 202, 191–197 (1991).

    Article  CAS  PubMed  Google Scholar 

  45. Bockman, M. R. et al. Investigation of (S)-(-)-acidomycin: a selective antimycobacterial natural product that inhibits biotin synthase. ACS Infect. Dis. 5, 598–617 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Mann, S. & Ploux, O. 7,8-Diaminoperlargonic acid aminotransferase from Mycobacterium tuberculosis, a potential therapeutic target. Characterization and inhibition studies. FEBS J. 273, 4778–4789 (2006).

    Article  CAS  PubMed  Google Scholar 

  47. Liu, F. et al. Structure-based optimization of pyridoxal 5’-phosphate-dependent transaminase enzyme (BioA) inhibitors that target biotin biosynthesis in Mycobacterium tuberculosis. J. Med. Chem. 60, 5507–5520 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Bockman, M. R. et al. Targeting Mycobacterium tuberculosis biotin protein ligase (MtBPL) with nucleoside-based bisubstrate adenylation inhibitors. J. Med. Chem. 58, 7349–7369 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Kapopoulou, A., Lew, J. M. & Cole, S. T. The MycoBrowser portal: a comprehensive and manually annotated resource for mycobacterial genomes. Tuberculosis 91, 8–13 (2011).

    Article  CAS  PubMed  Google Scholar 

  50. Tong, L. Structure and function of biotin-dependent carboxylases. Cell. Mol. Life Sci. 70, 863–891 (2013).

    Article  CAS  PubMed  Google Scholar 

  51. Lazar, N. et al. Control of biotin biosynthesis in mycobacteria by a pyruvate carboxylase dependent metabolic signal. Mol. Microbiol. 106, 1018–1031 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Ehebauer, M. T. et al. Characterization of the mycobacterial acyl-CoA carboxylase holo complexes reveals their functional expansion into amino acid catabolism. PLoS Pathog. 11, e1004623 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Abuhammad, A. Cholesterol metabolism: a potential therapeutic target in Mycobacteria. Br. J. Pharmacol. 174, 2194–2208 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Serafini, A. et al. Mycobacterium tuberculosis requires glyoxylate shunt and reverse methylcitrate cycle for lactate and pyruvate metabolism. Mol. Microbiol. 112, 1284–1307 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Eoh, H. & Rhee, K. Y. Methylcitrate cycle defines the bactericidal essentiality of isocitrate lyase for survival of Mycobacterium tuberculosis on fatty acids. Proc. Natl Acad. Sci. USA 111, 4976–4981 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. de Mendoza, D. Temperature sensing by membranes. Annu. Rev. Microbiol. 68, 101–116 (2014).

    Article  PubMed  Google Scholar 

  57. Weber, G. & Farris, F. J. Synthesis and spectral properties of a hydrophobic fluorescent probe: 6-propionyl-2-(dimethylamino)naphthalene. Biochemistry 18, 3075–3078 (1979).

    Article  CAS  PubMed  Google Scholar 

  58. Bagatolli, L. A. To see or not to see: lateral organization of biological membranes and fluorescence microscopy. Biochim. Biophys. Acta 1758, 1541–1556 (2006).

    Article  CAS  PubMed  Google Scholar 

  59. Strahl, H., Burmann, F. & Hamoen, L. W. The actin homologue MreB organizes the bacterial cell membrane. Nat. Commun. 5, 3442 (2014).

    Article  PubMed  Google Scholar 

  60. Parasassi, T., De Stasio, G., d’Ubaldo, A. & Gratton, E. Phase fluctuation in phospholipid membranes revealed by Laurdan fluorescence. Biophys. J. 57, 1179–1186 (1990).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Malkin, T. The molecular structure and polymorphism of fatty acids and their derivatives. Prog. Chem. Fats Other Lipids 1, 1–17 (1952).

    Article  CAS  Google Scholar 

  62. Holman, R. T., Johnson, S. B. & Kokmen, E. Deficiencies of polyunsaturated fatty acids and replacement by nonessential fatty acids in plasma lipids in multiple sclerosis. Proc. Natl Acad. Sci. USA 86, 4720–4724 (1989).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Vandal, O. H., Pierini, L. M., Schnappinger, D., Nathan, C. F. & Ehrt, S. A membrane protein preserves intrabacterial pH in intraphagosomal Mycobacterium tuberculosis. Nat. Med. 14, 849–854 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Wenzel, M., Vischer, N. O. E., Strahl, H. & Hamoen, L. W. Assessing membrane fluidity and visualizing fluid membrane domains in bacteria using fluorescent membrane dyes. Bio Protoc. 8, e3063 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Garcia-Heredia, A. et al. Membrane-partitioned cell wall synthesis in mycobacteria. eLife https://doi.org/10.7554/eLife.60263 (2021).

  66. Yuk, H. G. & Marshall, D. L. Adaptation of Escherichia coli O157:H7 to pH alters membrane lipid composition, verotoxin secretion, and resistance to simulated gastric fluid acid. Appl. Environ. Microbiol. 70, 3500–3505 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Al-Beloshei, N. E., Al-Awadhi, H., Al-Khalaf, R. A. & Afzal, M. A comparative study of fatty acid profile and formation of biofilm in Geobacillus gargensis exposed to variable abiotic stress. Can. J. Microbiol. 61, 48–59 (2015).

    Article  CAS  PubMed  Google Scholar 

  68. Kanno, M. et al. pH-induced change in cell susceptibility to butanol in a high butanol-tolerant bacterium, Enterococcus faecalis strain CM4A. Biotechnol. Biofuels 8, 69 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Li, X. et al. Electrolyte transport properties in distal small airways from cystic fibrosis pigs with implications for host defense. Am. J. Physiol. Lung Cell. Mol. Physiol. 310, L670–L679 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  70. Eisenberg, M. A. & Hsiung, S. C. Mode of action of the biotin antimetabolites actithiazic acid and alpha-methyldethiobiotin. Antimicrob. Agents Chemother. 21, 5–10 (1982).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Okami, Y., Kitahara, T., Hamada, M., Naganawa, H. & Kondo, S. Studies on a new amino acid antibiotic, amiclenomycin. J. Antibiot. 27, 656–664 (1974).

    Article  CAS  Google Scholar 

  72. Woong Park, S. et al. Evaluating the sensitivity of Mycobacterium tuberculosis to biotin deprivation using regulated gene expression. PLoS Pathog. 7, e1002264 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  73. Sassetti, C. M. & Rubin, E. J. Genetic requirements for mycobacterial survival during infection. Proc. Natl Acad. Sci. USA 100, 12989–12994 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Carfrae, L. A. et al. Mimicking the human environment in mice reveals that inhibiting biotin biosynthesis is effective against antibiotic-resistant pathogens. Nat. Microbiol. 5, 93–101 (2020).

    Article  CAS  PubMed  Google Scholar 

  75. Kang, N. et al. Outcomes of inhaled amikacin-containing multidrug regimens for Mycobacterium abscessus pulmonary disease. Chest 160, 436–445 (2021).

    Article  CAS  PubMed  Google Scholar 

  76. Gustafsson, J. K. et al. Bicarbonate and functional CFTR channel are required for proper mucin secretion and link cystic fibrosis with its mucus phenotype. J. Exp. Med. 209, 1263–1272 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Ferrera, L., Capurro, V., Delpiano, L., Gianotti, A. & Moran, O. The application of bicarbonate recovers the chemical-physical properties of airway surface liquid in cystic fibrosis epithelia models. Biology 10, 278 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Grof, I. et al. The effect of sodium bicarbonate, a beneficial adjuvant molecule in cystic fibrosis, on bronchial epithelial cells expressing a wild-type or mutant CFTR channel. Int. J. Mol. Sci. https://doi.org/10.3390/ijms21114024 (2020).

  79. Xie, C. et al. A host defense mechanism involving CFTR-mediated bicarbonate secretion in bacterial prostatitis. PLoS ONE 5, e15255 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Dobay, O. et al. Bicarbonate inhibits bacterial growth and biofilm formation of prevalent cystic fibrosis pathogens. Front. Microbiol. 9, 2245 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  81. Farha, M. A., French, S., Stokes, J. M. & Brown, E. D. Bicarbonate alters bacterial susceptibility to antibiotics by targeting the proton motive force. ACS Infect. Dis. 4, 382–390 (2018).

    Article  CAS  PubMed  Google Scholar 

  82. Michl, J., Park, K. C. & Swietach, P. Evidence-based guidelines for controlling pH in mammalian live-cell culture systems. Commun. Biol. 2, 144 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  83. Marinko, J. T. et al. Folding and misfolding of human membrane proteins in health and disease: from single molecules to cellular proteostasis. Chem. Rev. 119, 5537–5606 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Chadda, R. et al. Membrane transporter dimerization driven by differential lipid solvation energetics of dissociated and associated states. eLife 10, e63288 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Budin, I. et al. Viscous control of cellular respiration by membrane lipid composition. Science 362, 1186–1189 (2018).

    Article  CAS  PubMed  Google Scholar 

  86. Kieser, K. J. et al. Phosphorylation of the peptidoglycan synthase PonA1 governs the rate of polar elongation in mycobacteria. PLoS Pathog. 11, e1005010 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  87. Murphy, K. C., Papavinasasundaram, K. & Sassetti, C. M. Mycobacterial recombineering. Methods Mol. Biol. 1285, 177–199 (2015).

    Article  CAS  PubMed  Google Scholar 

  88. Gray, T. E., Guzman, K., Davis, C. W., Abdullah, L. H. & Nettesheim, P. Mucociliary differentiation of serially passaged normal human tracheobronchial epithelial cells. Am. J. Respir. Cell Mol. Biol. 14, 104–112 (1996).

    Article  CAS  PubMed  Google Scholar 

  89. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    Article  CAS  PubMed  Google Scholar 

  90. Sassetti, C. M., Boyd, D. H. & Rubin, E. J. Comprehensive identification of conditionally essential genes in mycobacteria. Proc. Natl Acad. Sci. USA 98, 12712–12717 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Lampe, D. J., Churchill, M. E. & Robertson, H. M. A purified mariner transposase is sufficient to mediate transposition in vitro. EMBO J. 15, 5470–5479 (1996).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Long, J. E. et al. Identifying essential genes in Mycobacterium tuberculosis by global phenotypic profiling. Methods Mol. Biol. 1279, 79–95 (2015).

    Article  CAS  PubMed  Google Scholar 

  93. DeJesus, M. A., Ambadipudi, C., Baker, R., Sassetti, C. & Ioerger, T. R. TRANSIT–a software tool for Himar1 TnSeq analysis. PLoS Comput. Biol. 11, e1004401 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  94. Stein, S. E. An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data. J. Am. Soc. Mass Spectrom. 10, 770–781 (1999).

    Article  CAS  Google Scholar 

  95. Ginies, C., Brillard, J. & Nguyen-The, C. Identification of fatty acids in Bacillus cereus. J. Vis. Exp. https://doi.org/10.3791/54960 (2016).

  96. Agrawal, S. et al. El-MAVEN: a fast, robust, and user-friendly mass spectrometry data processing engine for metabolomics. Methods Mol. Biol. 1978, 301–321 (2019).

    Article  CAS  PubMed  Google Scholar 

  97. Pang, Z. et al. MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights. Nucleic Acids Res. 49, W388–W396 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Layre, E. & Moody, D. B. Lipidomic profiling of model organisms and the world’s major pathogens. Biochimie 95, 109–115 (2013).

    Article  CAS  PubMed  Google Scholar 

  99. Smith, C. A., Want, E. J., O’Maille, G., Abagyan, R. & Siuzdak, G. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal. Chem. 78, 779–787 (2006).

    Article  CAS  PubMed  Google Scholar 

  100. Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank all members of the Rubin and Fortune labs for input and advice on the manuscript; J.-A. Park and C. Mwase for assistance with air–liquid interface cultures; the Biopolymers Facility at Harvard Medical School for sequencing; and the Microscopy Resources on the North Quad (MicRoN) core at Harvard Medical School for assistance with microscopy. Electron microscopy imaging was performed in the HMS Electron Microscopy Facility. M.R.S. is a Merck Fellow of the Damon Runyon Cancer Research Foundation, DRG-2415-20. E.J.R. was supported by a Dean’s Innovation Award from Harvard Medical School, and by NIH/NIAID under award number R21AI156772. A.M. acknowledges support from the Ludwig Center for Metastasis. D.B.M acknowledges NIH R01 AI049313 and NIH U19 AI162584.

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Authors and Affiliations

  1. Department of Immunology and Infectious Disease, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Mark R. Sullivan, Kerry McGowen, Chidiebere Akusobi, Ian D. Wolf & Eric J. Rubin

  2. Department of Medicinal Chemistry, University of Minnesota College of Pharmacy, Minneapolis, MN, USA

    Qiang Liu & Courtney C. Aldrich

  3. Division of Rheumatology, Immunity and Inflammation, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    David C. Young, Jacob A. Mayfield, Sahadevan Raman & D. Branch Moody

  4. Ben May Department for Cancer Research, University of Chicago, Chicago, IL, USA

    Alexander Muir

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M.R.S. and E.J.R. conceptualized the project. M.R.S. and C.A. developed the methodology. M.R.S., D.C.Y. and J.A.M. conducted formal analysis. M.R.S., K.M., I.D.W., D.C.Y., S.R. and A.M. conducted the investigations. J.A.M. developed software. Q.L. and C.C.A. procured resources. M.R.S., D.C.Y. and J.A.M. performed visualization. M.R.S. wrote the original draft. M.R.S., K.M., C.A., D.C.Y., J.A.M., A.M., D.B.M. and E.J.R. reviewed and edited the second draft. M.R.S. and E.J.R. acquired funding. E.J.R., C.C.A. and D.B.M supervised the project.

Corresponding author

Correspondence to Eric J. Rubin.

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Competing interests

D.B.M consults with Pfizer and EnaraBio. The other authors declare no competing interests.

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Nature Microbiology thanks Laurent Kremer, Thomas Dick and Luiz Pedro de Carvalho for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Air-liquid interface culture model system.

(A) Scanning electron microscope images of apical surface of lung epithelial cells at 0 and 14 days after initiation of air-liquid interface. Images were obtained at 2000X magnification. Scale bar = 10 µm. Images representative of 3 biological replicates for day 0, 4 biological replicates for day 14. (B) Scanning electron microscope image of apical surface of lung epithelial cells at 14 days after initiation of air-liquid interface. Image was obtained at 10,000X magnification. Scale bar, 1 µm. Image representative of 4 biological replicates. (C) Widefield microscope images of NuLi-1 lung epithelial cells stained for F-actin, MUC5AC, and with DAPI to highlight nuclei. Images were obtained at 40X magnification. Scale bar, 20 µm. Images representative of 3 biological replicates. (D) Monolayer permeability as measured by amount of sodium fluorescein that penetrated through the epithelial layer at successive days after initiation of air-liquid interface. Data are normalized to empty, collagen-coated transwells and are presented as mean +/− SD. n = 3 biological replicates. (E) Fraction of M. abscessus remaining after aspiration of excess liquid to re-generate air-liquid interface for the M. abscessus type strain ATCC19977 and clinical isolate T35. Data are presented as individual values along with mean +/− SD. n = 6 biological replicates. (F) Colony forming units of M. abscessus ATCC19977 infected at a multiplicity of infection = 1 on the apical surface of lung epithelial cells. n = 3 biological replicates. Data are presented as mean +/− SD. (G) Luminescence emitted by M. abscessus ATCC1997 or clinical isolate T35 in lung infection model infected at the indicated multiplicity of infection (MOI) over 48 hr of infection. Data are presented as mean +/− SD. n = 3 biological replicates per condition. (H) Lactate dehydrogenase (LDH) release from lung epithelial cells at 0 and 24 hr post-infection. LDH release is normalized to uninfected control cells that were lysed to release maximal LDH. Data are presented as individual values along with mean +/− SD. n = 3 biological replicates per condition. (I) Scanning electron microscope image of apical surface of lung infection model at 48 hr post-infection. Image was obtained at 3000X magnification. Scale bar, 5 µm. (J) Number of M. abscessus colony forming units that were detached from the apical surface by vigorous washing after 48 hours in the lung infection model (Extracellular) and those that were attached to or inside the lung epithelial layer (Intracellular). Data are presented as individual values along with mean +/− SD. n = 3 biological replicates.

Extended Data Fig. 2 Development of biotin synthesis pathway knockouts.

(A) Proliferation rate of M. abscessus ATCC19977 grown either in tissue culture medium or on the apical surface of air-liquid interface lung cultures. Data are presented as individual values along with mean +/− SD. n = 3 biological replicates. p-value derived from unpaired, two-tailed t-test. (B) Schematic of biotin biosynthesis pathway. ACP: acyl carrier protein. CoA: coenzyme A. SAM: S-adenosyl methionine. ATP: adenosine triphosphate. AMP: adenosine monophosphate. PPi: inorganic phosphate. (C) Schematic of recombineering knockouts of bioA. zeoR: zeocin resistance cassette (D) Agarose gel electrophoresis of PCR products demonstrating insertion of zeoR into bioA. Expected PCR product sizes are indicated in (C). (E) Agarose gel electrophoresis of PCR products demonstrating excision of zeoR from bioA::zeoR. Expected PCR product sizes are indicated in (C). (D) and (E) are representative of 2 independent experiments.

Extended Data Fig. 3 Characterization of BioA inhibitor compound 36 in M. abscessus.

(A) Luminescence of M. abscessus ATCC19977 grown 48 hr with either vehicle or 16 µM compound 36 treatment. Media were either tissue culture medium or basal medium sampled from infected or mock infected air-liquid interface lung cultures dialyzed against tissue culture medium to replenish small molecules while retaining protein factors. Values are normalized within each condition to vehicle-treated. (B) Luminescence of the indicated M. abscessus clinical isolates grown in tissue culture medium for 48 hr with the specified final concentrations of the BioA inhibitor compound 36 in the medium. Values are normalized within each medium to the vehicle treated condition. (C) Luminescence of M. abscessus ATCC19977 grown in the lung infection model for 48 hr in the presence or absence of 16 µM compound 36 and/or 2 µM biotin added to the basal medium. Values are normalized to the vehicle treated condition. (D) Trypan blue measurement of viability of lung epithelial cells after 48 hr treatment with the indicated concentrations of compound 36. Values are normalized to vehicle treated condition. (E) Uncropped western blot (corresponding to Fig. 3E) for total biotinylated protein in M. abscessus ATCC19977 grown in tissue culture medium with either vehicle or 16 µM compound 36 along with the indicated supplementation of propionate. SYPRO Ruby panel depicts total protein. Blot is representative of 3 independent experiments. (F) Luminescence of M. abscessus ATCC19977 grown in tissue culture medium for 48 hr with either vehicle or 64 µM compound 36 along with the indicated supplementation of cholesterol. Values are normalized within each condition to vehicle-treated. (G) Luminescence of M. abscessus ATCC19977 grown in tissue culture medium for 48 hr with either vehicle or 16 µM compound 36 along with the indicated supplementation of sodium pyruvate. Values are normalized within each condition to vehicle-treated. For all graphs, data are presented as mean +/− SD. n = 3 biological replicates. All p-values derived from unpaired, two-tailed t-tests.

Extended Data Fig. 4 Altered biotin metabolism induces M. abscessus envelope remodeling.

(A) Fluorescence intensity scan from 440 nm to 490 nm from either laurdan stained (+cells, stained) or unstained (+cells, unstained) M. abscessus ATCC19977 samples or samples containing laurdan but no cells (-cells, stained). One representative sample is depicted for each condition. (B) Difference in laurdan generalized polarization (GP) between the same sample measured at 23 °C, then rapidly shifted to 37 °C and re-measured. n = 65 biological replicates. (C) Heatmap depicting relative abundance of 24 fatty acid species measured by GC/MS in M. abscessus ATCC19977 grown 48 hr in tissue culture medium treated either with vehicle or 16 µM compound 36. Samples and fatty acid species are both hierarchically clustered. n = 3 biological replicates. (D) Heatmap depicting relative abundance of 24 fatty acid species measured by GC/MS in M. abscessus ATCC19977 grown 48 hr in tissue culture medium treated with 16 µM compound 36 along with either vehicle or 1 mM sodium propionate. Samples and fatty acid species are both hierarchically clustered. n = 3 biological replicates. (E) Schematic of propionate utilization. CoA: coenzyme A. TCA: tricarboxylic acid. (F) Volcano plots depicting log2-fold change in abundance versus significance for ‘molecular events’ with linked retention time, mass, and intensity representing potential lipid species detected by HPLC/MS. Molecular events detected in M. abscessus ATCC19977 grown 48 hr in tissue culture medium containing vehicle are contrasted against those detected in cells treated with 16 μM compound 36 (left) or with 16 μM compound 36 and 1 mM propionate (right). Peaks significantly changed (p < 0.05 based on two-tailed moderated t-test using linear model and Bayesian shrinkage of variance methods with multiple hypothesis adjustment by the Benjamini-Hochberg method) in both contrasts (red circles) and a peak with the mass of compound 36 (blue outline) are indicated. Peak that is significantly depleted upon compound 36 treatment is depicted as an asterisk in both volcano plots. (G) Plot of retention time versus mass to charge ratio for all significantly changed peaks depicted in (F), which clusters peaks by shared chemical properties. Peaks significant in both contrasts (red), a peak with the mass of compound 36 (blue, [M + H]+) and select alternate compound 36 adducts (blue) are indicated.

Extended Data Fig. 5 pH is a determinant of biotin demand and fatty acid composition.

(A) Correlation between medium pH and sensitivity to biotin synthesis inhibition as measured by ratio of luminescence of M. abscessus ATCC19977 in tissue culture medium treated with 32 µM compound 36 compared to vehicle-treated after 48 hr. Medium pH changes are a secondary effect of adding pools of metabolites from mycobacterial medium to tissue culture medium (see Materials and Methods for composition of pools), and pH was measured by potentiometric pH meter. Data are presented as mean +/− SD. R2 and p-value derived from two-tailed Pearson correlation. Line of best fit derived from simple linear regression. (B) Uncropped western blot (corresponding to Fig. 5B) for total biotinylated protein in M. abscessus ATCC19977 grown in tissue culture medium adjusted to the indicated pH and treated with either vehicle or 16 µM compound 36. SYPRO Ruby panel depicts total protein. Blot is representative of 3 independent experiments. (C) Principal component analysis of M. abscessus ATCC19977 grown in tissue culture medium adjusted to the indicated pH based on GC/MS measurement of 24 fatty acid species. (D) Loading plot depicting individual fatty acid contributions to the principal components displayed in (C). (E) Ratio of colony forming units of M. abscessus ATCC19977 in air-liquid interface lung cultures treated with 128 µM compound 36 compared to vehicle-treated after 48 hr infection. Initial basal pH was adjusted to either 7.6 or 6.8, and final apical pH in each condition was determined to be 7.8 and 7.1, respectively. Data are presented as individual values along with mean +/− SD. n = 3 biological replicates. p-value derived from unpaired, two-tailed t-test. (F) Scanning electron microscope images of apical surface of lung infection model at 48 hr post-infection treated with 128 μM compound 36 with medium pH adjusted to 7.8 or 7.1. Images were obtained at 10,000X magnification. Scale bar = 1 µm. (G) pH of liquid sampled from the basal and apical surfaces of infected air-liquid interface lung cultures treated with 128 µM compound 36 as measured by phenol red absorbance. Data are presented as individual values along with mean +/− SD. n = 3 biological replicates.

Supplementary information

Reporting Summary

Supplementary Table

Table 1. Library statistics for TnSeq. Table 2. Relative requirement for genes responsible for recycling propionate. Table 3. Oligonucleotides used in this study. File 1. Formulation of tissue culture and mycobacterial media. File 2. Resampling analysis of relative gene requirements in lung infection model and tissue culture medium versus input library. File 3. Fatty acid quantitation in various media conditions.

Supplementary File 4

R markdown file with code for LC/MS lipidomic analysis.

Supplementary Data

Sample identification used by code in Supplementary File 4 for negative mode analysis.

Supplementary Data

Sample identification used by code in Supplementary File 4 for positive mode analysis.

Supplementary Data

LC/MS data used by code in Supplementary File 4 for negative mode analysis.

Supplementary Data

LC/MS data used by code in Supplementary File 4 for positive mode analysis.

Source data

Source Data Fig. 1

Uncropped scans of streptavidin-HRP blot.

Source Data Fig. 2

Visible light image to demonstrate protein size markers for streptavidin-HRP blot.

Source Data Fig. 3

SYPRO Ruby staining.

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Sullivan, M.R., McGowen, K., Liu, Q. et al. Biotin-dependent cell envelope remodelling is required for Mycobacterium abscessus survival in lung infection. Nat Microbiol 8, 481–497 (2023). https://doi.org/10.1038/s41564-022-01307-5

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