1887

Abstract

A metabolite profiling approach has been implemented to elucidate metabolic adaptation at set culture conditions in five Mycobacterium species (two fast- and three slow-growing) with the potential to act as model organisms for Mycobacterium tuberculosis (Mtb). Analysis has been performed over designated growth phases and under representative environments (nutrient and oxygen depletion) experienced by Mtb during infection. The procedure was useful in determining a range of metabolites (60–120 compounds) covering nucleotides, amino acids, organic acids, saccharides, fatty acids, glycerols, -esters, -phosphates and isoprenoids. Among these classes of compounds, key biomarker metabolites, which can act as indicators of pathway/process activity, were identified. In numerous cases, common metabolite traits were observed for all five species across the experimental conditions (e.g. uracil indicating DNA repair). Amino acid content, especially glutamic acid, highlighted the different properties between the fast- and slow-growing mycobacteria studied (e.g. nitrogen assimilation). The greatest similarities in metabolite composition between fast- and slow-growing mycobacteria were apparent under hypoxic conditions. A comparison to previously reported transcriptomic data revealed a strong correlation between changes in transcription and metabolite content. Collectively, these data validate the changes in the transcription at the metabolite level, suggesting transcription exists as one of the predominant modes of cellular regulation in Mycobacterium. Sectors with restricted correlation between metabolites and transcription (e.g. hypoxic cultivation) warrant further study to elucidate and exploit post-transcriptional modes of regulation. The strong correlation between the laboratory conditions used and data derived from in vivo conditions, indicate that the approach applied is a valuable addition to our understanding of cell regulation in these Mycobacterium species.

Loading

Article metrics loading...

/content/journal/micro/10.1099/mic.0.000325
2016-08-01
2019-09-22
Loading full text...

Full text loading...

/deliver/fulltext/micro/162/8/1456.html?itemId=/content/journal/micro/10.1099/mic.0.000325&mimeType=html&fmt=ahah

References

  1. Amon J. , Titgemeyer F. , Burkovski A. . ( 2009;). A genomic view on nitrogen metabolism and nitrogen control in mycobacteria. . J Mol Microbiol Biotechnol 17: 20–29. [CrossRef] [PubMed]
    [Google Scholar]
  2. Archuleta R. J. , Yvonne Hoppes P. , Primm T. P. . ( 2005;). Mycobacterium avium enters a state of metabolic dormancy in response to starvation. . Tuberculosis 85: 147–158. [CrossRef] [PubMed]
    [Google Scholar]
  3. Bacon J. , Alderwick L. J. , Allnutt J. A. , Gabasova E. , Watson R. , Hatch K. A. , Clark S. O. , Jeeves R. E. , Marriott A. et al. ( 2014;). Non-replicating Mycobacterium tuberculosis elicits a reduced infectivity profile with corresponding modifications to the cell wall and extracellular matrix. . PLoS One 9: e87329. [CrossRef] [PubMed]
    [Google Scholar]
  4. Barry I. I. I. C. E. . ( 2001;). Mycobacterium smegmatis: an absurd model for tuberculosis?. Trends Microbiol 9: 473–474. [CrossRef]
    [Google Scholar]
  5. Betts J. C. , Lukey P. T. , Robb L. C. , McAdam R. A. , Duncan K. . ( 2002;). Evaluation of a nutrient starvation model of Mycobacterium tuberculosis persistence by gene and protein expression profiling. . Mol Microbiol 43: 717–731. [CrossRef] [PubMed]
    [Google Scholar]
  6. Boshoff H. I. , Lun D. S. . ( 2010;). Systems biology approaches to understanding mycobacterial survival mechanisms. . Drug Discov Today: Dis Mech 7: e75e82. [CrossRef] [PubMed]
    [Google Scholar]
  7. Chao M. C. , Rubin E. J. . ( 2010;). Letting sleeping dos lie: does dormancy play a role in tuberculosis?. Annu Rev Microbiol 64: 293–311. [CrossRef] [PubMed]
    [Google Scholar]
  8. Cossu A. , Sechi L. A. , Zanetti S. , Rosu V. . ( 2012;). Gene expression profiling of Mycobacterium avium subsp . paratuberculosis in simulated multi-stress conditions and within THP-1 cells reveals a new kind of interactive intramacrophage behaviour. . BMC Microbiol 12: 87. [CrossRef] [PubMed]
    [Google Scholar]
  9. Crellin P. K. , Luo C. -Y. , Morita Y. S. . ( 2013;). Metabolism of plasma membrane lipids in mycobacteria and corynebacteria. . In Lipid Metabolism , pp. 119–148. Edited by Baez P. R. V. .
    [Google Scholar]
  10. Cunningham A. F. , Spreadbury C. L. . ( 1998;). Mycobacterial stationary phase induced by low oxygen tension: cell wall thickening and localization of the 16-kilodalton alpha-crystallin homolog. . J Bacteriol 180: 801–808.[PubMed]
    [Google Scholar]
  11. Dhiman R. K. , Mahapatra S. , Slayden R. A. , Boyne M. E. , Lenaerts A. , Hinshaw J. C. , Angala S. K. , Chatterjee D. , Biswas K. et al. ( 2009;). Menaquinone synthesis is critical for maintaining mycobacterial viability during exponential growth and recovery from non-replicating persistence. . Mol Microbiol 72: 85–97. [CrossRef] [PubMed]
    [Google Scholar]
  12. Drapal M. , Perez-Fons L. , Wheeler P. R. , Fraser P. D. . ( 2014;). The application of metabolite profiling to Mycobacterium spp.: determination of metabolite changes associated with growth. . J Microbiol Methods 106: 23–32. [CrossRef] [PubMed]
    [Google Scholar]
  13. Eoh H. , Rhee K. Y. . ( 2013;). Multifunctional essentiality of succinate metabolism in adaptation to hypoxia in Mycobacterium tuberculosis . . Proc Natl Acad Sci U S A 110: 6554–6559. [CrossRef] [PubMed]
    [Google Scholar]
  14. Gago G. , Diacovich L. , Arabolaza A. , Tsai S. C. , Gramajo H. . ( 2011;). Fatty acid biosynthesis in actinomycetes. . FEMS Microbiol Rev 35: 475–497. [CrossRef] [PubMed]
    [Google Scholar]
  15. Garton N. J. , Christensen H. , Minnikin D. E. , Adegbola R. A. , Barer M. R. . ( 2002;). Intracellular lipophilic inclusions of mycobacteria in vitro and in sputum. . Microbiology 148: 2951–2958. [CrossRef] [PubMed]
    [Google Scholar]
  16. Hampshire T. , Soneji S. , Bacon J. , James B. W. , Hinds J. , Laing K. , Stabler R. A. , Marsh P. D. , Butcher P. D. . ( 2004;). Stationary phase gene expression of Mycobacterium tuberculosis following a progressive nutrient depletion: a model for persistent organisms?. Tuberculosis 84: 228–238. [CrossRef] [PubMed]
    [Google Scholar]
  17. Harrigan G. G. , Goodacre R. . ( 2003;). Introduction. . In Metabolic Profiling - Its Role in Biomarker Discovery and Gene Function Analysis, pp. 1–9. Edited by Harrigan G. G. , Goodacre R. . United States of America:: Kluwer Academic Publishers;.[CrossRef]
    [Google Scholar]
  18. Harth G. , Horwitz M. A. . ( 1999;). An inhibitor of exported Mycobacterium tuberculosis glutamine synthetase selectively blocks the growth of pathogenic mycobacteria in axenic culture and in human monocytes: extracellular proteins as potential novel drug targets. . J Exp Med 189: 1425–1436.[PubMed] [CrossRef]
    [Google Scholar]
  19. Jones M. O. , Perez-Fons L. , Robertson F. P. , Bramley P. M. , Fraser P. D. . ( 2013;). Functional characterization of long-chain prenyl diphosphate synthases from tomato. . Biochem J 449: 729–740. [CrossRef] [PubMed]
    [Google Scholar]
  20. Kanehisa M. , Goto S. , Hattori M. , Aoki-Kinoshita K. F. , Itoh M. , Kawashima S. , Katayama T. , Araki M. , Hirakawa M. . ( 2006;). From genomics to chemical genomics: new developments in KEGG. . Nucleic Acids Res 34: D354–357. [CrossRef] [PubMed]
    [Google Scholar]
  21. Lee P. C. , Salomon C. , Mijts B. , Schmidt-Dannert C. . ( 2008;). Biosynthesis of ubiquinone compounds with conjugated prenyl side chains. . Appl Environ Microbiol 74: 6908–6917. [CrossRef] [PubMed]
    [Google Scholar]
  22. Low K. L. , Rao P. S. , Shui G. , Bendt A. K. , Pethe K. , Dick T. , Wenk M. R. . ( 2009;). Triacylglycerol utilization is required for regrowth of in vitro hypoxic nonreplicating Mycobacterium bovis bacillus Calmette- Guerin. . J Bacteriol 191: 5037–5043. [CrossRef] [PubMed]
    [Google Scholar]
  23. Mathew R. , Kruthiventi A. K. , Prasad J. V. , Kumar S. P. , Srinu G. , Chatterji D. . ( 2010;). Inhibition of mycobacterial growth by plumbagin derivatives. . Chem Biol Drug Des 76: 34–42. [CrossRef] [PubMed]
    [Google Scholar]
  24. Mora L. , Bramley P. M. , Fraser P. D. . ( 2013;). Development and optimisation of a label-free quantitative proteomic procedure and its application in the assessment of genetically modified tomato fruit. . Proteomics 13: 2016–2030. [CrossRef] [PubMed]
    [Google Scholar]
  25. Nogueira M. , Mora L. , Enfissi E. M. , Bramley P. M. , Fraser P. D. . ( 2013;). Subchromoplast sequestration of carotenoids affects regulatory mechanisms in tomato lines expressing different carotenoid gene combinations. . Plant Cell 25: 4560–4579. [CrossRef] [PubMed]
    [Google Scholar]
  26. Rafidinarivo E. , Lanéelle M. A. , Montrozier H. , Valero-Guillén P. , Astola J. , Luquin M. , Promé J. C. , Daffé M. . ( 2009;). Trafficking pathways of mycolic acids: structures, origin, mechanism of formation, and storage form of mycobacteric acids. . J Lipid Res 50: 477–490. [CrossRef] [PubMed]
    [Google Scholar]
  27. Robertson F. P. , Koistinen P. K. , Gerrish C. , Halket J. M. , Patel R. K. , Fraser P. D. , Bramley P. M. . ( 2012;). Proteome changes in tomato lines transformed with phytoene synthase-1 in the sense and antisense orientations. . J Exp Bot 63: 6035–6043. [CrossRef] [PubMed]
    [Google Scholar]
  28. Russell D. G. , VanderVen B. C. , Lee W. , Abramovitch R. B. , Kim M. J. , Homolka S. , Niemann S. , Rohde K. H. . ( 2010;). Mycobacterium tuberculosis wears what it eats. . Cell Host Microbe 8: 68–76. [CrossRef] [PubMed]
    [Google Scholar]
  29. Sassetti C. M. , Rubin E. J. . ( 2003;). Genetic requirements for mycobacterial survival during infection. . Proc Natl Acad Sci U S A 100: 12989–12994. [CrossRef] [PubMed]
    [Google Scholar]
  30. Sassetti C. M. , Boyd D. H. , Rubin E. J. . ( 2003;). Genes required for mycobacterial growth defined by high density mutagenesis. . Mol Microbiol 48: 77–84. [CrossRef] [PubMed]
    [Google Scholar]
  31. Selishcheva A. A. , Sorokoumova G. M. , Nazarova E. V. . ( 2012;). Lipid surrounding of mycobacteria: lethal and resuscitating effects. . In Understanding Tuberculosis–Deciphering the Secret Life of the Bacilli, pp. 239–256 . Edited by Cardona. P.-J. . InTech;.
    [Google Scholar]
  32. Shi L. , Sohaskey C. D. , Pfeiffer C. , Datta P. , Parks M. , McFadden J. , North R. J. , Gennaro M. L. . ( 2010;). Carbon flux rerouting during Mycobacterium tuberculosis growth arrest. . Mol Microbiol 78: 1199–1215. [CrossRef] [PubMed]
    [Google Scholar]
  33. Singhal A. , Arora G. , Sajid A. , Maji A. , Bhat A. , Virmani R. , Upadhyay S. , Nandicoori V. K. , Sengupta S. et al. ( 2013;). Regulation of homocysteine metabolism by Mycobacterium tuberculosis S-adenosylhomocysteine hydrolase. . Sci Rep 3: 2264. [CrossRef] [PubMed]
    [Google Scholar]
  34. Smeulders M. J. , Keer J. , Speight R. A. , Williams H. D. . ( 1999;). Adaptation of Mycobacterium smegmatis to stationary phase. . J Bacteriol 181: 270–283.[PubMed]
    [Google Scholar]
  35. Stehr M. , Elamin A. A. , Singh M. . ( 2013;). Lipid inclusions in mycobacterial infections. . In Tuberculosis–Current Issues in Diagnosis and Management. Edited by Mahboub B. . InTech.
    [Google Scholar]
  36. Venkatesh J. , Kumar P. , Krishna P. S. , Manjunath R. , Varshney U. . ( 2003;). Importance of uracil DNA glycosylase in Pseudomonas aeruginosa and Mycobacterium smegmatis, G+C-rich bacteria, in mutation prevention, tolerance to acidified nitrite, and endurance in mouse macrophages. . J Biol Chem 278: 24350–24358. [CrossRef] [PubMed]
    [Google Scholar]
  37. Walker R. W. , Barakat H. , Hung J. G. . ( 1970;). The positional distribution of fatty acids in the phospholipids and triglycerides of Mycobacterium smegmatis and M. bovis BCG. . Lipids 5: 684–691. [CrossRef] [PubMed]
    [Google Scholar]
  38. Wang R. , Prince J. T. , Marcotte E. M. . ( 2005;). Mass spectrometry of the M . smegmatis proteome: protein expression levels correlate with function, operons, and codon bias. . Genome Res 15: 1118–1126. [CrossRef] [PubMed]
    [Google Scholar]
  39. Wayne L. G. , Hayes L. G. . ( 1996;). An in vitro model for sequential study of shiftdown of Mycobacterium tuberculosis through two stages of nonreplicating persistence. . Infect Immun 64: 2062–2069.[PubMed]
    [Google Scholar]
  40. Wayne L. G. , Sohaskey C. D. . ( 2001;). Nonreplicating persistence of Mycobacterium tuberculosis . . Annu Rev Microbiol 55: 139–163. [CrossRef] [PubMed]
    [Google Scholar]
  41. Zeng L. , Shi T. , Zhao Q. , Xie J. . ( 2013;). Mycobacterium sulfur metabolism and implications for novel drug targets. . Cell Biochem Biophys 65: 77–83. [CrossRef] [PubMed]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/micro/10.1099/mic.0.000325
Loading
/content/journal/micro/10.1099/mic.0.000325
Loading

Data & Media loading...

Supplementary File 1



PDF
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error