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in the Proteomics Era

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  • Authors: Martin Gengenbacher1, Jeppe Mouritsen2, Olga T. Schubert3, Ruedi Aebersold4, Stefan H. E. Kaufmann6
  • Editors: Graham F. Hatfull7, William R. Jacobs Jr.8
  • VIEW AFFILIATIONS HIDE AFFILIATIONS
    Affiliations: 1: Max Planck Institute for Infection Biology, Department of Immunology, Charitéplatz 1, 10117 Berlin, Germany; 2: Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Wolfgang-Pauli Strasse 16, 8093 Zurich, Switzerland; 3: Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Wolfgang-Pauli Strasse 16, 8093 Zurich, Switzerland; 4: Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Wolfgang-Pauli Strasse 16, 8093 Zurich, Switzerland; 5: Faculty of Science, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland; 6: Max Planck Institute for Infection Biology, Department of Immunology, Charitéplatz 1, 10117 Berlin, Germany; 7: University of Pittsburgh, Pittsburgh, PA; 8: Howard Hughes Medical Institute, Albert Einstein College of Medicine, Bronx, NY
    • Source: microbiolspec March 2014 vol. 2 no. 2 doi:10.1128/microbiolspec.MGM2-0020-2013
  • Received 11 June 2013 Accepted 26 July 2013 Published 21 March 2014
  • M. Gengenbacher, [email protected]; S. Kaufmann, [email protected]
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  • Abstract:

    The emerging field of proteomics has contributed greatly to improving our understanding of the human pathogen over the last two decades. In this chapter we provide a comprehensive overview of mycobacterial proteome research and highlight key findings. First, studies employing a combination of two-dimensional gel electrophoresis and mass spectrometry (MS) provided insights into the proteomic composition, initially of the whole bacillus and subsequently of subfractions, such as the cell wall, cytosol, and secreted proteins. Comparison of results obtained under various culture conditions, i.e., acidic pH, nutrient starvation, and low oxygen tension, aiming to mimic facets of the intracellular lifestyle of provided initial clues to proteins relevant for intracellular survival and manipulation of the host cell. Further attempts were aimed at identifying the biological functions of the hypothetical proteins, which still make up a quarter of the gene products of , and at characterizing posttranslational modifications. Recent technological advances in MS have given rise to new methods such as selected reaction monitoring (SRM) and data-independent acquisition (DIA). These targeted, cutting-edge techniques combined with a public database of specific MS assays covering the entire proteome of allow the simple and reliable detection of any mycobacterial protein. Most recent studies attempt not only to identify but also to quantify absolute amounts of single proteins in the complex background of host cells without prior sample fractionation or enrichment. Finally, we will discuss the potential of proteomics to advance vaccinology, drug discovery, and biomarker identification to improve intervention and prevention measures for tuberculosis.

  • Citation: Gengenbacher M, Mouritsen J, Schubert O, Aebersold R, Kaufmann S. 2014. in the Proteomics Era. Microbiol Spectrum 2(2):MGM2-0020-2013. doi:10.1128/microbiolspec.MGM2-0020-2013.

References

1. Edman P. 1949. A method for the determination of amino acid sequence in peptides. Arch Biochem 22:475. [PubMed]
2. Cole ST, Brosch R, Parkhill J, Garnier T, Churcher C, Harris D, Gordon SV, Eiglmeier K, Gas S, Barry CE, III, Tekaia F, Badcock K, Basham D, Brown D, Chillingworth T, Connor R, Davies R, Devlin K, Feltwell T, Gentles S, Hamlin N, Holroyd S, Hornsby T, Jagels K, Krogh A, McLean J, Moule S, Murphy L, Oliver K, Osborne J, Quail MA, Rajandream MA, Rogers J, Rutter S, Seeger K, Skelton J, Squares R, Squares S, Sulston JE, Taylor K, Whitehead S, Barrell BG. 1998. Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence. Nature 393:537–544. [PubMed][CrossRef]
3. Lew JM, Kapopoulou A, Jones LM, Cole ST. 2011. TubercuList: 10 years after. Tuberculosis (Edinb) 91:1–7. [PubMed][CrossRef]
4. Doerks T, van Noort V, Minguez P, Bork P. 2012. Annotation of the M. tuberculosis hypothetical orfeome: adding functional information to more than half of the uncharacterized proteins. PLoS One 7:e34302. [PubMed][CrossRef]
5. Sassetti C, Rubin EJ. 2004. Genetic requirements for mycobacterial survival during infection. Proc Natl Acad Sci USA 100:12989–12994. [PubMed][CrossRef]
6. Talaat AM, Lyons R, Howard ST, Johnston SA. 2004. The temporal expression profile of Mycobacterium tuberculosis infection in mice. Proc Natl Acad Sci USA 101:4602–4607. [PubMed][CrossRef]
7. Hu Y, Movahedzadeh F, Stoker NG, Coates AR. 2006. Deletion of the Mycobacterium tuberculosis alpha-crystallin-like hspX gene causes increased bacterial growth in vivo. Infect Immun 74:861–868. [PubMed][CrossRef]
8. Kumar A, Toledo JC, Patel RP, Lancaster JR, Jr, Steyn AJ. 2007. Mycobacterium tuberculosis DosS is a redox sensor and DosT is a hypoxia sensor. Proc Natl Acad Sci USA 104:11568–11573. [PubMed][CrossRef]
9. Noss EH, Pai RK, Sellati TJ, Radolf JD, Belisle J, Golenbock DT, Boom WH, Harding CV. 2001. Toll-like receptor 2-dependent inhibition of macrophage class II MHC expression and antigen processing by 19-kDa lipoprotein of Mycobacterium tuberculosis. J Immunol 167:910–918. [PubMed]
10. Reddy PV, Puri RV, Khera A, Tyagi AK. 2012. Iron storage proteins are essential for the survival and pathogenesis of Mycobacterium tuberculosis in THP-1 macrophages and the guinea pig model of infection. J Bacteriol 194:567–575. [PubMed][CrossRef]
11. Vergne I, Chua J, Lee HH, Lucas M, Belisle J, Deretic V. 2005. Mechanism of phagolysosome biogenesis block by viable Mycobacterium tuberculosis. Proc Natl Acad Sci USA 102:4033–4038. [PubMed][CrossRef]
12. Walburger A, Koul A, Ferrari G, Nguyen L, Prescianotto-Baschong C, Huygen K, Klebl B, Thompson C, Bacher G, Pieters J. 2004. Protein kinase G from pathogenic mycobacteria promotes survival within macrophages. Science 304:1800–1804. [PubMed][CrossRef]
13. Gygi SP, Rochon Y, Franza BR, Aebersold R. 1999. Correlation between protein and mRNA abundance in yeast. Mol Cell Biol 19:1720–1730. [PubMed]
14. Marguerat S, Schmidt A, Codlin S, Chen W, Aebersold R, Bahler J. 2012. Quantitative analysis of fission yeast transcriptomes and proteomes in proliferating and quiescent cells. Cell 151:671–683. [PubMed][CrossRef]
15. Britton WJ, Hellqvist L, Ivanyi J, Basten A. 1987. Immunopurification of radiolabelled antigens of Mycobacterium leprae and Mycobacterium bovis (bacillus Calmette-Guérin) with monoclonal antibodies. Scand J Immunol 26:149–159. [PubMed]
16. Daugelat S, Gulle H, Schoel B, Kaufmann SH. 1992. Secreted antigens of Mycobacterium tuberculosis: characterization with T lymphocytes from patients and contacts after two-dimensional separation. J Infect Dis 166:186–190. [PubMed]
17. Lee BY, Horwitz MA. 1995. Identification of macrophage and stress-induced proteins of Mycobacterium tuberculosis. J Clin Invest 96:245–249. [PubMed][CrossRef]
18. Mahairas GG, Sabo PJ, Hickey MJ, Singh DC, Stover CK. 1996. Molecular analysis of genetic differences between Mycobacterium bovis BCG and virulent M. bovis. J Bacteriol 178:1274–1282. [PubMed]
19. Sonnenberg MG, Belisle JT. 1997. Definition of Mycobacterium tuberculosis culture filtrate proteins by two-dimensional polyacrylamide gel electrophoresis, N-terminal amino acid sequencing, and electrospray mass spectrometry. Infect Immun 65:4515–4524. [PubMed]
20. Urquhart BL, Atsalos TE, Roach D, Basseal DJ, Bjellqvist B, Britton WL, Humphery-Smith I. 1997. “Proteomic contigs” of Mycobacterium tuberculosis and Mycobacterium bovis (BCG) using novel immobilised pH gradients. Electrophoresis 18:1384–1392. [PubMed][CrossRef]
21. Wallis RS, Paranjape R, Phillips M. 1993. Identification by two-dimensional gel electrophoresis of a 58-kilodalton tumor necrosis factor-inducing protein of Mycobacterium tuberculosis. Infect Immun 61:627–632. [PubMed]
22. Wong DK, Lee BY, Horwitz MA, Gibson BW. 1999. Identification of fur, aconitase, and other proteins expressed by Mycobacterium tuberculosis under conditions of low and high concentrations of iron by combined two-dimensional gel electrophoresis and mass spectrometry. Infect Immun 67:327–336. [PubMed]
23. Mollenkopf HJ, Jungblut PR, Raupach B, Mattow J, Lamer S, Zimny-Arndt U, Schaible UE, Kaufmann SH. 1999. A dynamic two-dimensional polyacrylamide gel electrophoresis database: the mycobacterial proteome via Internet. Electrophoresis 20:2172–2180. [PubMed][CrossRef]
24. Kelkar DS, Kumar D, Kumar P, Balakrishnan L, Muthusamy B, Yadav AK, Shrivastava P, Marimuthu A, Anand S, Sundaram H, Kingsbury R, Harsha HC, Nair B, Prasad TS, Chauhan DS, Katoch K, Katoch VM, Kumar P, Chaerkady R, Ramachandran S, Dash D, Pandey A. 2011. Proteogenomic analysis of Mycobacterium tuberculosis by high resolution mass spectrometry. Mol Cell Proteomics 10:M111. [PubMed][CrossRef]
25. Schubert OT, Mouritsen JC, Ludwig C, Röst H, Rosenberger G, Arthur PK, Claassen M, Campbell DS, Sun Z, Farrah T, Gengenbacher M, Kaufmann SHE, Mortitz RL, Aebersold R. 2013. The Mtb Proteome Library: a resource of assays to quantify the complete proteome of Mycobacterium tuberculosis. Cell Host Microbe 13:602–612. [PubMed][CrossRef]
26. Zheng J, Liu L, Wei C, Leng W, Yang J, Li W, Wang J, Jin Q. 2012. A comprehensive proteomic analysis of Mycobacterium bovis bacillus Calmette-Guérin using high resolution Fourier transform mass spectrometry. J Proteomics 77:357–371. [PubMed][CrossRef]
27. de Souza GA, Malen H, Softeland T, Saelensminde G, Prasad S, Jonassen I, Wiker HG. 2008. High accuracy mass spectrometry analysis as a tool to verify and improve gene annotation using Mycobacterium tuberculosis as an example. BMC Genomics 9:316. [PubMed][CrossRef]
28. Renuse S, Chaerkady R, Pandey A. 2011. Proteogenomics. Proteomics 11:620–630. [PubMed][CrossRef]
29. de Souza GA, Arntzen MO, Fortuin S, Schurch AC, Malen H, McEvoy CR, van Soolingen D, Thiede B, Warren RM, Wiker HG. 2011. Proteogenomic analysis of polymorphisms and gene annotation divergences in prokaryotes using a clustered mass spectrometry-friendly database. Mol Cell Proteomics 10:M110. [PubMed][CrossRef]
30. Jungblut PR, Muller EC, Mattow J, Kaufmann SH. 2001. Proteomics reveals open reading frames in Mycobacterium tuberculosis H37Rv not predicted by genomics. Infect Immun 69:5905–5907. [PubMed]
31. Lew JM, Mao C, Shukla M, Warren A, Will R, Kuznetsov D, Xenarios I, Robertson BD, Gordon SV, Schnappinger D, Cole ST, Sobral B. 2013. Database resources for the tuberculosis community. Tuberculosis (Edinb) 93:12–17. [PubMed][CrossRef]
32. Rosenkrands I, King A, Weldingh K, Moniatte M, Moertz E, Andersen P. 2000. Towards the proteome of Mycobacterium tuberculosis. Electrophoresis 21:3740–3756. [PubMed][CrossRef]
33. Urquhart BL, Cordwell SJ, Humphery-Smith I. 1998. Comparison of predicted and observed properties of proteins encoded in the genome of Mycobacterium tuberculosis H37Rv. Biochem Biophys Res Commun 253:70–79. [PubMed][CrossRef]
34. Gengenbacher M, Kaufmann SH. 2012. Mycobacterium tuberculosis: success through dormancy. FEMS Microbiol Rev 36:514–532. [PubMed][CrossRef]
35. Nagai S, Wiker HG, Harboe M, Kinomoto M. 1991. Isolation and partial characterization of major protein antigens in the culture fluid of Mycobacterium tuberculosis. Infect Immun 59:372–382. [PubMed]
36. Weldingh K, Rosenkrands I, Jacobsen S, Rasmussen PB, Elhay MJ, Andersen P. 1998. Two-dimensional electrophoresis for analysis of Mycobacterium tuberculosis culture filtrate and purification and characterization of six novel proteins. Infect Immun 66:3492–3500. [PubMed]
37. Rosenkrands I, Weldingh K, Jacobsen S, Hansen CV, Florio W, Gianetri I, Andersen P. 2000. Mapping and identification of Mycobacterium tuberculosis proteins by two-dimensional gel electrophoresis, microsequencing and immunodetection. Electrophoresis 21:935–948. [PubMed][CrossRef]
38. Jungblut PR, Schaible UE, Mollenkopf HJ, Zimny-Arndt U, Raupach B, Mattow J, Halada P, Lamer S, Hagens K, Kaufmann SH. 1999. Comparative proteome analysis of Mycobacterium tuberculosis and Mycobacterium bovis BCG strains: towards functional genomics of microbial pathogens. Mol Microbiol 33:1103–1117. [PubMed]
39. Mattow J, Jungblut PR, Schaible UE, Mollenkopf HJ, Lamer S, Zimny-Arndt U, Hagens K, Muller EC, Kaufmann SH. 2001. Identification of proteins from Mycobacterium tuberculosis missing in attenuated Mycobacterium bovis BCG strains. Electrophoresis 22:2936–2946. [PubMed][CrossRef]
40. Mattow J, Schaible UE, Schmidt F, Hagens K, Siejak F, Brestrich G, Haeselbarth G, Muller EC, Jungblut PR, Kaufmann SH. 2003. Comparative proteome analysis of culture supernatant proteins from virulent Mycobacterium tuberculosis H37Rv and attenuated M. bovis BCG Copenhagen. Electrophoresis 24:3405–3420. [PubMed][CrossRef]
41. Simeone R, Bottai D, Brosch R. 2009. ESX/type VII secretion systems and their role in host-pathogen interaction. Curr Opin Microbiol 12:4–10. [PubMed][CrossRef]
42. Albrethsen J, Agner J, Piersma SR, Hojrup P, Pham TV, Weldingh K, Jimenez CR, Andersen P, Rosenkrands I. 2013. Proteomic profiling of Mycobacterium tuberculosis identifies nutrient-starvation-responsive toxin-antitoxin systems. Mol Cell Proteomics 12:1180–1191. [PubMed][CrossRef]
43. Brennan PJ. 2003. Structure, function, and biogenesis of the cell wall of Mycobacterium tuberculosis. Tuberculosis (Edinb) 83:91–97. [PubMed]
44. Sarathy J, Dartois V, Dick T, Gengenbacher M. 2013. Reduced drug uptake in phenotypically resistant nutrient-starved nonreplicating Mycobacterium tuberculosis. Antimicrob Agents Chemother 57:1648–1653. [PubMed][CrossRef]
45. Kaufmann SH, Gengenbacher M. 2012. Recombinant live vaccine candidates against tuberculosis. Curr Opin Biotechnol 23:900–907. [PubMed][CrossRef]
46. Kaufmann SH. 2013. Tuberculosis vaccines: time to think about the next generation. Semin Immunol 25(2) :172–81. [PubMed][CrossRef]
47. Mawuenyega KG, Forst CV, Dobos KM, Belisle JT, Chen J, Bradbury EM, Bradbury AR, Chen X. 2005. Mycobacterium tuberculosis functional network analysis by global subcellular protein profiling. Mol Biol Cell 16:396–404. [PubMed][CrossRef]
48. Wolfe LM, Mahaffey SB, Kruh NA, Dobos KM. 2010. Proteomic definition of the cell wall of Mycobacterium tuberculosis. J Proteome Res 9:5816–5826. [PubMed][CrossRef]
49. Gu S, Chen J, Dobos KM, Bradbury EM, Belisle JT, Chen X. 2003. Comprehensive proteomic profiling of the membrane constituents of a Mycobacterium tuberculosis strain. Mol Cell Proteomics 2:1284–1296. [PubMed][CrossRef]
50. Schmidt F, Donahoe S, Hagens K, Mattow J, Schaible UE, Kaufmann SH, Aebersold R, Jungblut PR. 2004. Complementary analysis of the Mycobacterium tuberculosis proteome by two-dimensional electrophoresis and isotope-coded affinity tag technology. Mol Cell Proteomics 3:24–42. [PubMed][CrossRef]
51. Sinha S, Kosalai K, Arora S, Namane A, Sharma P, Gaikwad AN, Brodin P, Cole ST. 2005. Immunogenic membrane-associated proteins of Mycobacterium tuberculosis revealed by proteomics. Microbiology 151:2411–2419. [PubMed][CrossRef]
52. Xiong Y, Chalmers MJ, Gao FP, Cross TA, Marshall AG. 2005. Identification of Mycobacterium tuberculosis H37Rv integral membrane proteins by one-dimensional gel electrophoresis and liquid chromatography electrospray ionization tandem mass spectrometry. J Proteome Res 4:855–861. [PubMed][CrossRef]
53. Malen H, Pathak S, Softeland T, de Souza GA, Wiker HG. 2010. Definition of novel cell envelope associated proteins in Triton X-114 extracts of Mycobacterium tuberculosis H37Rv. BMC Microbiol 10:132. [PubMed][CrossRef]
54. Bell C, Smith GT, Sweredoski MJ, Hess S. 2012. Characterization of the Mycobacterium tuberculosis proteome by liquid chromatography mass spectrometry-based proteomics techniques: a comprehensive resource for tuberculosis research. J Proteome Res 11:119–130. [PubMed][CrossRef]
55. Wayne LG, Hayes LG. 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]
56. Boon C, Li R, Qi R, Dick T. 2001. Proteins of Mycobacterium bovis BCG induced in the Wayne dormancy model. J Bacteriol 183:2672–2676. [PubMed][CrossRef]
57. Rosenkrands I, Slayden RA, Crawford J, Aagaard C, Barry CE, III, Andersen P. 2002. Hypoxic response of Mycobacterium tuberculosis studied by metabolic labeling and proteome analysis of cellular and extracellular proteins. J Bacteriol 184:3485–3491. [PubMed]
58. Starck J, Kallenius G, Marklund BI, Andersson DI, Akerlund T. 2004. Comparative proteome analysis of Mycobacterium tuberculosis grown under aerobic and anaerobic conditions. Microbiology 150:3821–3829. [PubMed][CrossRef]
59. Loebel RO, Shorr E, Richardson HB. 1933. The influence of adverse conditions upon the respiratory metabolism and growth of human tubercle bacilli. J Bacteriol 26:167–200. [PubMed]
60. Betts JC, Lukey PT, Robb LC, McAdam RA, Duncan K. 2002. Evaluation of a nutrient starvation model of Mycobacterium tuberculosis persistence by gene and protein expression profiling. Mol Microbiol 43:717–731. [PubMed]
61. Fenhalls G, Stevens L, Moses L, Bezuidenhout J, Betts JC, Helden PP, Lukey PT, Duncan K. 2002. In situ detection of Mycobacterium tuberculosis transcripts in human lung granulomas reveals differential gene expression in necrotic lesions. Infect Immun 70:6330–6338. [PubMed]
62. Gordhan BG, Smith DA, Kana BD, Bancroft G, Mizrahi V. 2006. The carbon starvation-inducible genes Rv2557 and Rv2558 of Mycobacterium tuberculosis are not required for long-term survival under carbon starvation and for virulence in SCID mice. Tuberculosis (Edinb) 86:430–437. [PubMed][CrossRef]
63. Florczyk MA, McCue LA, Stack RF, Hauer CR, McDonough KA. 2001. Identification and characterization of mycobacterial proteins differentially expressed under standing and shaking culture conditions, including Rv2623 from a novel class of putative ATP-binding proteins. Infect Immun 69:5777–5785. [PubMed]
64. Yuan Y, Crane DD, Barry CE, III. 1996. Stationary phase-associated protein expression in Mycobacterium tuberculosis: function of the mycobacterial alpha-crystallin homolog. J Bacteriol 178:4484–4492. [PubMed]
65. Mattow J, Siejak F, Hagens K, Becher D, Albrecht D, Krah A, Schmidt F, Jungblut PR, Kaufmann SH, Schaible UE. 2006. Proteins unique to intraphagosomally grown Mycobacterium tuberculosis. Proteomics 6:2485–2494. [PubMed][CrossRef]
66. Monahan IM, Betts J, Banerjee DK, Butcher PD. 2001. Differential expression of mycobacterial proteins following phagocytosis by macrophages. Microbiology 147:459–471. [PubMed]
67. Cho SH, Goodlett D, Franzblau S. 2006. ICAT-based comparative proteomic analysis of non-replicating persistent Mycobacterium tuberculosis. Tuberculosis (Edinb) 86:445–460. [PubMed][CrossRef]
68. Kruh NA, Troudt J, Izzo A, Prenni J, Dobos KM. 2010. Portrait of a pathogen: the Mycobacterium tuberculosis proteome in vivo. PLoS One 5:e13938 [PubMed][CrossRef]
69. Witze ES, Old WM, Resing KA, Ahn NG. 2007. Mapping protein post-translational modifications with mass spectrometry. Nat Methods 4:798–806. [PubMed][CrossRef]
70. Mijakovic I. 2010. Protein phosphorylation in bacteria. Microbe 5:21–25.
71. Salih E. 2005. Phosphoproteomics by mass spectrometry and classical protein chemistry approaches. Mass Spectrom Rev 24:828–846. [PubMed][CrossRef]
72. Casino P, Rubio V, Marina A. 2010. The mechanism of signal transduction by two-component systems. Curr Opin Struct Biol 20:763–771. [PubMed][CrossRef]
73. Chao J, Wong D, Zheng X, Poirier V, Bach H, Hmama Z, Av-Gay Y. 2010. Protein kinase and phosphatase signaling in Mycobacterium tuberculosis physiology and pathogenesis. Biochim Biophys Acta 1804:620–627. [PubMed][CrossRef]
74. Prisic S, Dankwa S, Schwartz D, Chou MF, Locasale JW, Kang CM, Bemis G, Church GM, Steen H, Husson RN. 2010. Extensive phosphorylation with overlapping specificity by Mycobacterium tuberculosis serine/threonine protein kinases. Proc Natl Acad Sci USA 107:7521–7526. [PubMed][CrossRef]
75. Pearce MJ, Mintseris J, Ferreyra J, Gygi SP, Darwin KH. 2008. Ubiquitin-like protein involved in the proteasome pathway of Mycobacterium tuberculosis. Science 322:1104–1107. [PubMed][CrossRef]
76. Striebel F, Imkamp F, Ozcelik D, Weber-Ban E. 2013. Pupylation as a signal for proteasomal degradation in bacteria. Biochim Biophys Acta [Epub ahead of print] doi:10.1016/j.bbamcr.2013.03.022. [PubMed][CrossRef]
77. Festa RA, McAllister F, Pearce MJ, Mintseris J, Burns KE, Gygi SP, Darwin KH. 2010. Prokaryotic ubiquitin-like protein (Pup) proteome of Mycobacterium tuberculosis [corrected]. PLoS One 5:e8589 [PubMed][CrossRef]
78. Poulsen C, Akhter Y, Jeon AH, Schmitt-Ulms G, Meyer HE, Stefanski A, Stuhler K, Wilmanns M, Song YH. 2010. Proteome-wide identification of mycobacterial pupylation targets. Mol Syst Biol 6:386. [PubMed][CrossRef]
79. Watrous J, Burns K, Liu WT, Patel A, Hook V, Bafna V, Barry CE, III, Bark S, Dorrestein PC. 2010. Expansion of the mycobacterial “PUPylome.” Mol Biosyst 6:376–385. [PubMed][CrossRef]
80. Hu LI, Lima BP, Wolfe AJ. 2010. Bacterial protein acetylation: the dawning of a new age. Mol Microbiol 77:15–21. [PubMed][CrossRef]
81. Okkels LM, Muller EC, Schmid M, Rosenkrands I, Kaufmann SH, Andersen P, Jungblut PR. 2004. CFP10 discriminates between nonacetylated and acetylated ESAT-6 of Mycobacterium tuberculosis by differential interaction. Proteomics 4:2954–2960. [PubMed][CrossRef]
82. van Noort V, Seebacher J, Bader S, Mohammed S, Vonkova I, Betts MJ, Kuhner S, Kumar R, Maier T, O'Flaherty M, Rybin V, Schmeisky A, Yus E, Stulke J, Serrano L, Russell RB, Heck AJ, Bork P, Gavin AC. 2012. Cross-talk between phosphorylation and lysine acetylation in a genome-reduced bacterium. Mol Syst Biol 8:571. [PubMed][CrossRef]
83. Kovacs-Simon A, Titball RW, Michell SL. 2011. Lipoproteins of bacterial pathogens. Infect Immun 79:548–561.
84. Sutcliffe IC, Harrington DJ. 2004. Lipoproteins of Mycobacterium tuberculosis: an abundant and functionally diverse class of cell envelope components. FEMS Microbiol Rev 28:645–659. [PubMed][CrossRef]
85. Dobos KM, Swiderek K, Khoo KH, Brennan PJ, Belisle JT. 1995. Evidence for glycosylation sites on the 45-kilodalton glycoprotein of Mycobacterium tuberculosis. Infect Immun 63:2846–2853. [PubMed]
86. Dobos KM, Khoo KH, Swiderek KM, Brennan PJ, Belisle JT. 1996. Definition of the full extent of glycosylation of the 45-kilodalton glycoprotein of Mycobacterium tuberculosis. J Bacteriol 178:2498–2506. [PubMed]
87. Ragas A, Roussel L, Puzo G, Riviere M. 2007. The Mycobacterium tuberculosis cell-surface glycoprotein apa as a potential adhesin to colonize target cells via the innate immune system pulmonary C-type lectin surfactant protein A. J Biol Chem 282:5133–5142. [PubMed][CrossRef]
88. Espitia C, Mancilla R. 1989. Identification, isolation and partial characterization of Mycobacterium tuberculosis glycoprotein antigens. Clin Exp Immunol 77:378–383. [PubMed]
89. Horn C, Namane A, Pescher P, Riviere M, Romain F, Puzo G, Barzu O, Marchal G. 1999. Decreased capacity of recombinant 45/47-kDa molecules (Apa) of Mycobacterium tuberculosis to stimulate T lymphocyte responses related to changes in their mannosylation pattern. J Biol Chem 274:32023–32030. [PubMed]
90. Herrmann JL, O'Gaora P, Gallagher A, Thole JE, Young DB. 1996. Bacterial glycoproteins: a link between glycosylation and proteolytic cleavage of a 19 kDa antigen from Mycobacterium tuberculosis. EMBO J 15:3547–3554. [PubMed]
91. Gonzalez-Zamorano M, Mendoza-Hernandez G, Xolalpa W, Parada C, Vallecillo AJ, Bigi F, Espitia C. 2009. Mycobacterium tuberculosis glycoproteomics based on ConA-lectin affinity capture of mannosylated proteins. J Proteome Res 8:721–733. [PubMed][CrossRef]
92. Liu CF, Tonini L, Malaga W, Beau M, Stella A, Bouyssie D, Jackson MC, Nigou J, Puzo G, Guilhot C, Burlet-Schiltz O, Riviere M. 2013. Bacterial protein- O-mannosylating enzyme is crucial for virulence of Mycobacterium tuberculosis. Proc Natl Acad Sci USA 110:6560–6565. [PubMed][CrossRef]
93. Smith GT, Sweredoski MJ, Hess S. 2013. O-linked glycosylation sites profiling in Mycobacterium tuberculosis culture filtrate proteins. J Proteomics [Epub ahead of print] doi:10.1016/j.jprot.2013.05.011. [PubMed][CrossRef]
94. Hase T, Tanaka H, Suzuki Y, Nakagawa S, Kitano H. 2009. Structure of protein interaction networks and their implications on drug design. PLoS Comput Biol 5:e1000550. [PubMed][CrossRef]
95. Loregian A, Palu G. 2005. Disruption of protein-protein interactions: towards new targets for chemotherapy. J Cell Physiol 204:750–762. [PubMed][CrossRef]
96. Steyn AJ, Joseph J, Bloom BR. 2003. Interaction of the sensor module of Mycobacterium tuberculosis H37Rv KdpD with members of the Lpr family. Mol Microbiol 47:1075–1089. [PubMed]
97. Tharad M, Samuchiwal SK, Bhalla K, Ghosh A, Kumar K, Kumar S, Ranganathan A. 2011. A three-hybrid system to probe in vivo protein-protein interactions: application to the essential proteins of the RD1 complex of M. tuberculosis. PLoS One 6:e27503. [PubMed]
98. Dyer MD, Neff C, Dufford M, Rivera CG, Shattuck D, Bassaganya-Riera J, Murali TM, Sobral BW. 2010. The human-bacterial pathogen protein interaction networks of Bacillus anthracis, Francisella tularensis, and Yersinia pestis. PLoS One 5:e12089. [PubMed][CrossRef]
99. Veyron-Churlet R, Guerrini O, Mourey L, Daffe M, Zerbib D. 2004. Protein-protein interactions within the fatty acid synthase-II system of Mycobacterium tuberculosis are essential for mycobacterial viability. Mol Microbiol 54:1161–1172. [PubMed][CrossRef]
100. O'Hare H, Juillerat A, Dianiskova P, Johnsson K. 2008. A split-protein sensor for studying protein-protein interaction in mycobacteria. J Microbiol Methods 73:79–84. [PubMed]
101. Parikh A, Kumar D, Chawla Y, Kurthkoti K, Khan S, Varshney U, Nandicoori VK. 2013. Development of a new generation of vectors for gene expression, gene replacement, and protein-protein interaction studies in mycobacteria. Appl Environ Microbiol 79:1718–1729. [PubMed][CrossRef]
102. Davis FP, Barkan DT, Eswar N, McKerrow JH, Sali A. 2007. Host pathogen protein interactions predicted by comparative modeling. Protein Sci 16:2585–2596. [PubMed][CrossRef]
103. Malen H, Berven FS, Fladmark KE, Wiker HG. 2007. Comprehensive analysis of exported proteins from Mycobacterium tuberculosis H37Rv. Proteomics 7:1702–1718. [PubMed][CrossRef]
104. Pathak SK, Basu S, Basu KK, Banerjee A, Pathak S, Bhattacharyya A, Kaisho T, Kundu M, Basu J. 2007. Direct extracellular interaction between the early secreted antigen ESAT-6 of Mycobacterium tuberculosis and TLR2 inhibits TLR signaling in macrophages. Nat Immunol 8:610–618. [PubMed][CrossRef]
105. Fortune SM, Jaeger A, Sarracino DA, Chase MR, Sassetti CM, Sherman DR, Bloom BR, Rubin EJ. 2005. Mutually dependent secretion of proteins required for mycobacterial virulence. Proc Natl Acad Sci USA 102:10676–10681. [PubMed][CrossRef]
106. Ramakrishnan L. 2012. Revisiting the role of the granuloma in tuberculosis. Nat Rev Immunol 12:352–366. [PubMed][CrossRef]
107. Zhang F, Xie JP. 2011. Mammalian cell entry gene family of Mycobacterium tuberculosis. Mol Cell Biochem 352:1–10. [PubMed][CrossRef]
108. Garcia-Perez BE, Mondragon-Flores R, Luna-Herrera J. 2003. Internalization of Mycobacterium tuberculosis by macropinocytosis in non-phagocytic cells. Microb Pathog 35:49–55. [PubMed]
109. Gaynor CD, McCormack FX, Voelker DR, McGowan SE, Schlesinger LS. 1995. Pulmonary surfactant protein A mediates enhanced phagocytosis of Mycobacterium tuberculosis by a direct interaction with human macrophages. J Immunol 155:5343–5351. [PubMed]
110. Bulut Y, Michelsen KS, Hayrapetian L, Naiki Y, Spallek R, Singh M, Arditi M. 2005. Mycobacterium tuberculosis heat shock proteins use diverse Toll-like receptor pathways to activate pro-inflammatory signals. J Biol Chem 280:20961–20967. [PubMed][CrossRef]
111. Bach H, Papavinasasundaram KG, Wong D, Hmama Z, Av-Gay Y. 2008. Mycobacterium tuberculosis virulence is mediated by PtpA dephosphorylation of human vacuolar protein sorting 33B. Cell Host Microbe 3:316–322. [PubMed][CrossRef]
112. Saleh MT, Belisle JT. 2000. Secretion of an acid phosphatase (SapM) by Mycobacterium tuberculosis that is similar to eukaryotic acid phosphatases. J Bacteriol 182:6850–6853. [PubMed]
113. Simeone R, Bobard A, Lippmann J, Bitter W, Majlessi L, Brosch R, Enninga J. 2012. Phagosomal rupture by Mycobacterium tuberculosis results in toxicity and host cell death. PLoS Pathog 8:e1002507. [PubMed][CrossRef]
114. Margarit I, Bonacci S, Pietrocola G, Rindi S, Ghezzo C, Bombaci M, Nardi-Dei V, Grifantini R, Speziale P, Grandi G. 2009. Capturing host-pathogen interactions by protein microarrays: identification of novel streptococcal proteins binding to human fibronectin, fibrinogen, and C4BP. FASEB J 23:3100–3112. [PubMed][CrossRef]
115. Frei AP, Jeon OY, Kilcher S, Moest H, Henning LM, Jost C, Pluckthun A, Mercer J, Aebersold R, Carreira EM, Wollscheid B. 2012. Direct identification of ligand-receptor interactions on living cells and tissues. Nat Biotechnol 30:997–1001. [PubMed][CrossRef]
116. Niederweis M, Ehrt S, Heinz C, Klocker U, Karosi S, Swiderek KM, Riley LW, Benz R. 1999. Cloning of the mspA gene encoding a porin from Mycobacterium smegmatis. Mol Microbiol 33:933–945. [PubMed]
117. Stahl C, Kubetzko S, Kaps I, Seeber S, Engelhardt H, Niederweis M. 2001. MspA provides the main hydrophilic pathway through the cell wall of Mycobacterium smegmatis. Mol Microbiol 40:451–464. [PubMed]
118. Senaratne RH, Mobasheri H, Papavinasasundaram KG, Jenner P, Lea EJ, Draper P. 1998. Expression of a gene for a porin-like protein of the OmpA family from Mycobacterium tuberculosis H37Rv. J Bacteriol 180:3541–3547. [PubMed]
119. Song H, Sandie R, Wang Y, Andrade-Navarro MA, Niederweis M. 2008. Identification of outer membrane proteins of Mycobacterium tuberculosis. Tuberculosis (Edinb) 88:526–544. [PubMed][CrossRef]
120. Smeulders MJ, Keer J, Speight RA, Williams HD. 1999. Adaptation of Mycobacterium smegmatis to stationary phase. J Bacteriol 181:270–283. [PubMed]
121. Schwanhausser B, Busse D, Li N, Dittmar G, Schuchhardt J, Wolf J, Chen W, Selbach M. 2011. Global quantification of mammalian gene expression control. Nature 473:337–342. [PubMed][CrossRef]
122. Rao PK, Roxas BA, Li Q. 2008. Determination of global protein turnover in stressed mycobacterium cells using hybrid-linear ion trap-Fourier transform mass spectrometry. Anal Chem 80:396–406. [PubMed][CrossRef]
123. Rao PK, Rodriguez GM, Smith I, Li Q. 2008. Protein dynamics in iron-starved Mycobacterium tuberculosis revealed by turnover and abundance measurement using hybrid-linear ion trap-Fourier transform mass spectrometry. Anal Chem 80:6860–6869. [PubMed][CrossRef]
124. Raju RM, Unnikrishnan M, Rubin DH, Krishnamoorthy V, Kandror O, Akopian TN, Goldberg AL, Rubin EJ. 2012. Mycobacterium tuberculosis ClpP1 and ClpP2 function together in protein degradation and are required for viability in vitro and during infection. PLoS Pathog 8:e1002511. [PubMed][CrossRef]
125. Burns KE, Liu WT, Boshoff HI, Dorrestein PC, Barry CE, III. 2009. Proteasomal protein degradation in Mycobacteria is dependent upon a prokaryotic ubiquitin-like protein. J Biol Chem 284:3069–3075. [PubMed][CrossRef]
126. Park HD, Guinn KM, Harrell MI, Liao R, Voskuil MI, Tompa M, Schoolnik GK, Sherman DR. 2003. Rv3133c/dosR is a transcription factor that mediates the hypoxic response of Mycobacterium tuberculosis. Mol Microbiol 48:833–843. [PubMed]
127. Saini DK, Malhotra V, Dey D, Pant N, Das TK, Tyagi JS. 2004. DevR-DevS is a bona fide two-component system of Mycobacterium tuberculosis that is hypoxia-responsive in the absence of the DNA-binding domain of DevR. Microbiology 150:865–875. [PubMed]
128. Domon B, Aebersold R. 2010. Options and considerations when selecting a quantitative proteomics strategy. Nat Biotechnol 28:710–721. [PubMed][CrossRef]
129. Lange V, Picotti P, Domon B, Aebersold R. 2008. Selected reaction monitoring for quantitative proteomics: a tutorial. Mol Syst Biol 4:222. [PubMed][CrossRef]
130. Picotti P, Bodenmiller B, Mueller LN, Domon B, Aebersold R. 2009. Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics. Cell 138:795–806. [PubMed][CrossRef]
131. Gillet LC, Navarro P, Tate S, Rost H, Selevsek N, Reiter L, Bonner R, Aebersold R. 2012. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol Cell Proteomics 11:O111. [PubMed][CrossRef]
132. Liu Y, Huttenhain R, Surinova S, Gillet LC, Mouritsen J, Brunner R, Navarro P, Aebersold R. 2013. Quantitative measurements of N-linked glycoproteins in human plasma by SWATH-MS. Proteomics 13:1247–1256. [PubMed][CrossRef]
133. Fontan P, Aris V, Ghanny S, Soteropoulos P, Smith I. 2008. Global transcriptional profile of Mycobacterium tuberculosis during THP-1 human macrophage infection. Infect Immun 76:717–725. [PubMed][CrossRef]
134. Rachman H, Strong M, Ulrichs T, Grode L, Schuchhardt J, Mollenkopf H, Kosmiadi GA, Eisenberg D, Kaufmann SH. 2006. Unique transcriptome signature of Mycobacterium tuberculosis in pulmonary tuberculosis. Infect Immun 74:1233–1242. [PubMed][CrossRef]
135. Rohde KH, Veiga DF, Caldwell S, Balazsi G, Russell DG. 2012. Linking the transcriptional profiles and the physiological states of Mycobacterium tuberculosis during an extended intracellular infection. PLoS Pathog 8:e1002769. [PubMed][CrossRef]
136. Schnappinger D, Ehrt S, Voskuil MI, Liu Y, Mangan JA, Monahan IM, Dolganov G, Efron B, Butcher PD, Nathan C, Schoolnik GK. 2003. Transcriptional adaptation of Mycobacterium tuberculosis within macrophages: insights into the phagosomal environment. J Exp Med 198:693–704. [PubMed][CrossRef]
137. Timm J, Post FA, Bekker LG, Walther GB, Wainwright HC, Manganelli R, Chan WT, Tsenova L, Gold B, Smith I, Kaplan G, McKinney JD. 2003. Differential expression of iron-, carbon-, and oxygen-responsive mycobacterial genes in the lungs of chronically infected mice and tuberculosis patients. Proc Natl Acad Sci USA 100:14321–14326. [PubMed][CrossRef]
138. Dhandayuthapani S, Via LE, Thomas CA, Horowitz PM, Deretic D, Deretic V. 1995. Green fluorescent protein as a marker for gene expression and cell biology of mycobacterial interactions with macrophages. Mol Microbiol 17:901–912. [PubMed]
139. Ramakrishnan L, Federspiel NA, Falkow S. 2000. Granuloma-specific expression of Mycobacterium virulence proteins from the glycine-rich PE-PGRS family. Science 288:1436–1439. [PubMed]
140. Lee BY, Jethwaney D, Schilling B, Clemens DL, Gibson BW, Horwitz MA. 2010. The Mycobacterium bovis bacille Calmette-Guerin phagosome proteome. Mol Cell Proteomics 9:32–53. [PubMed][CrossRef]
141. Kataria J, Rukmangadachar LA, Hariprasad G, O J, Tripathi M, Srinivasan A. 2011. Two dimensional difference gel electrophoresis analysis of cerebrospinal fluid in tuberculous meningitis patients. J Proteomics 74:2194–2203. [PubMed][CrossRef]
142. Kashyap RS, Rajan AN, Ramteke SS, Agrawal VS, Kelkar SS, Purohit HJ, Taori GM, Daginawala HF. 2007. Diagnosis of tuberculosis in an Indian population by an indirect ELISA protocol based on detection of antigen 85 complex: a prospective cohort study. BMC Infect Dis 7:74. [PubMed][CrossRef]
143. Bentley-Hibbert SI, Quan X, Newman T, Huygen K, Godfrey HP. 1999. Pathophysiology of antigen 85 in patients with active tuberculosis: antigen 85 circulates as complexes with fibronectin and immunoglobulin G. Infect Immun 67:581–588. [PubMed]
144. Kashino SS, Pollock N, Napolitano DR, Rodrigues V, Jr, Campos-Neto A. 2008. Identification and characterization of Mycobacterium tuberculosis antigens in urine of patients with active pulmonary tuberculosis: an innovative and alternative approach of antigen discovery of useful microbial molecules. Clin Exp Immunol 153:56–62. [PubMed][CrossRef]
145. Picotti P, Rinner O, Stallmach R, Dautel F, Farrah T, Domon B, Wenschuh H, Aebersold R. 2010. High-throughput generation of selected reaction-monitoring assays for proteins and proteomes. Nat Methods 7:43–46. [PubMed][CrossRef]
146. Taylor PJ. 2005. Matrix effects: the Achilles heel of quantitative high-performance liquid chromatography-electrospray-tandem mass spectrometry. Clin Biochem 38:328–334. [PubMed][CrossRef]
147. Chang CY, Picotti P, Huttenhain R, Heinzelmann-Schwarz V, Jovanovic M, Aebersold R, Vitek O. 2012. Protein significance analysis in selected reaction monitoring (SRM) measurements. Mol Cell Proteomics 11:M111. [PubMed][CrossRef]
148. Rost H, Malmstrom L, Aebersold R. 2012. A computational tool to detect and avoid redundancy in selected reaction monitoring. Mol Cell Proteomics 11:540–549. [PubMed][CrossRef]
149. Pathak S, Awuh JA, Leversen NA, Flo TH, Asjo B. 2012. Counting mycobacteria in infected human cells and mouse tissue: a comparison between qPCR and CFU. PLoS One 7:e34931. [PubMed][CrossRef]
150. Barry CE, III, Boshoff HI, Dartois V, Dick T, Ehrt S, Flynn J, Schnappinger D, Wilkinson RJ, Young D. 2009. The spectrum of latent tuberculosis: rethinking the biology and intervention strategies. Nat Rev Microbiol 7:845–855. [PubMed][CrossRef]
151. Dubnau E, Chan J, Mohan VP, Smith I. 2005. Responses of Mycobacterium tuberculosis to growth in the mouse lung. Infect Immun 73:3754–3757. [PubMed][CrossRef]
152. Kaufmann SH, Hussey G, Lambert PH. 2010. New vaccines for tuberculosis. Lancet 375:2110–2119. [PubMed][CrossRef]
153. Comas I, Chakravartti J, Small PM, Galagan J, Niemann S, Kremer K, Ernst JD, Gagneux S. 2010. Human T cell epitopes of Mycobacterium tuberculosis are evolutionarily hyperconserved. Nat Genet 42:498–503. [PubMed][CrossRef]
154. Rammensee HG, Falk K, Rotzschke O. 1993. Peptides naturally presented by MHC class I molecules. Annu Rev Immunol 11:213–244. [PubMed][CrossRef]
155. Ma Z, Lienhardt C, McIlleron H, Nunn AJ, Wang X. 2010. Global tuberculosis drug development pipeline: the need and the reality. Lancet 375:2100–2109. [PubMed][CrossRef]
156. Weiner J, Maertzdorf J, Kaufmann SH. 2013. The dual role of biomarkers for understanding basic principles and devising novel intervention strategies in tuberculosis. Ann NY Acad Sci 1283:22–29. [PubMed][CrossRef]
157. Wallis RS, Pai M, Menzies D, Doherty TM, Walzl G, Perkins MD, Zumla A. 2010. Biomarkers and diagnostics for tuberculosis: progress, needs, and translation into practice. Lancet 375:1920–1937. [PubMed][CrossRef]
158. World Health Organization. 2011. Tuberculosis serodiagnostic tests policy statement 2011. Geneva, WHO.
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/content/journal/microbiolspec/10.1128/microbiolspec.MGM2-0020-2013
2014-03-21
2020-07-03

Abstract:

The emerging field of proteomics has contributed greatly to improving our understanding of the human pathogen over the last two decades. In this chapter we provide a comprehensive overview of mycobacterial proteome research and highlight key findings. First, studies employing a combination of two-dimensional gel electrophoresis and mass spectrometry (MS) provided insights into the proteomic composition, initially of the whole bacillus and subsequently of subfractions, such as the cell wall, cytosol, and secreted proteins. Comparison of results obtained under various culture conditions, i.e., acidic pH, nutrient starvation, and low oxygen tension, aiming to mimic facets of the intracellular lifestyle of provided initial clues to proteins relevant for intracellular survival and manipulation of the host cell. Further attempts were aimed at identifying the biological functions of the hypothetical proteins, which still make up a quarter of the gene products of , and at characterizing posttranslational modifications. Recent technological advances in MS have given rise to new methods such as selected reaction monitoring (SRM) and data-independent acquisition (DIA). These targeted, cutting-edge techniques combined with a public database of specific MS assays covering the entire proteome of allow the simple and reliable detection of any mycobacterial protein. Most recent studies attempt not only to identify but also to quantify absolute amounts of single proteins in the complex background of host cells without prior sample fractionation or enrichment. Finally, we will discuss the potential of proteomics to advance vaccinology, drug discovery, and biomarker identification to improve intervention and prevention measures for tuberculosis.

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in the Proteomics Era
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Citation: Gengenbacher M, Mouritsen J, Schubert O, Aebersold R, Kaufmann S. 2014. in the proteomics era. microbiolspec 2(2): doi:10.1128/microbiolspec.MGM2-0020-2013
/content/microbiolspec/10.1128/microbiolspec.MGM2-0020-2013.fig1
FIGURE 1
Functional annotation and abundance distribution of the proteome. Distribution of functional classes of the proteome as annotated in TubercuList v2.6 release 27 (March 2013), updated with functional annotation for many of the “conserved hypotheticals” and “unknowns” ( 4 ). Distribution of SRM-based absolute label-free abundance estimates for 2,195 proteins of H37Rv in a 1:1 mix of exponential and stationary cultures in rich medium ( 25 ). The concentration is given in femtomoles per microgram of extracted protein.
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FIGURE 1

Functional annotation and abundance distribution of the proteome. Distribution of functional classes of the proteome as annotated in TubercuList v2.6 release 27 (March 2013), updated with functional annotation for many of the “conserved hypotheticals” and “unknowns” ( 4 ). Distribution of SRM-based absolute label-free abundance estimates for 2,195 proteins of H37Rv in a 1:1 mix of exponential and stationary cultures in rich medium ( 25 ). The concentration is given in femtomoles per microgram of extracted protein.

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FIGURE 2
Technology-advanced proteomics. Early approaches identified only a small number of proteins. Combination of 2D-GE and untargeted shotgun mass spectrometry (MS), as well as extensive prefractionation of proteins or peptides, improved identification rates significantly. The latest targeted proteomics techniques, namely SRM, demonstrated identification of virtually all expressed proteins at given states in unfractionated cultures ( 25 ).
microbiolspec/2/2/MGM2-0020-2013-fig2_thmb.gif
microbiolspec/2/2/MGM2-0020-2013-fig2.gif
Image of FIGURE 2

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FIGURE 2

Technology-advanced proteomics. Early approaches identified only a small number of proteins. Combination of 2D-GE and untargeted shotgun mass spectrometry (MS), as well as extensive prefractionation of proteins or peptides, improved identification rates significantly. The latest targeted proteomics techniques, namely SRM, demonstrated identification of virtually all expressed proteins at given states in unfractionated cultures ( 25 ).

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FIGURE 3
Uncovering the proteome. Most of the current knowledge on proteomics has been generated by comparison of bacterial cultures, i.e., rich medium versus hypoxia or nutrient deprivation, conditions that might experience . Subfractions such as culture supernatant, cell wall debris, or the bacterial cytosol were separated by 2D-GE and subsequently analyzed by MS techniques. Study of the proteome during infection remained difficult: Due to the overwhelming protein abundance of the host as compared to the pathogen, enrichment for bacterial fractions was required prior to analysis by 2D-GE and shotgun MS. With the availability of the complete proteome libraries for ( 25 ) and the human host (U. Kusebauch et al., in preparation), SRM will allow simultaneous proteome analysis of the pathogen and the host in complex mixtures.
microbiolspec/2/2/MGM2-0020-2013-fig3_thmb.gif
microbiolspec/2/2/MGM2-0020-2013-fig3.gif
Image of FIGURE 3

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FIGURE 3

Uncovering the proteome. Most of the current knowledge on proteomics has been generated by comparison of bacterial cultures, i.e., rich medium versus hypoxia or nutrient deprivation, conditions that might experience . Subfractions such as culture supernatant, cell wall debris, or the bacterial cytosol were separated by 2D-GE and subsequently analyzed by MS techniques. Study of the proteome during infection remained difficult: Due to the overwhelming protein abundance of the host as compared to the pathogen, enrichment for bacterial fractions was required prior to analysis by 2D-GE and shotgun MS. With the availability of the complete proteome libraries for ( 25 ) and the human host (U. Kusebauch et al., in preparation), SRM will allow simultaneous proteome analysis of the pathogen and the host in complex mixtures.

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FIGURE 4
The Mtb Proteome Library. Proteome mapping: After harvesting bacterial cultures, proteins were extracted and digested with the proteolytic enzyme trypsin. The resulting peptides were fractionated using off-gel isoelectric focusing to reduce sample complexity, and each fraction was analyzed by shotgun MS. The peptide and protein identifications, as well as the corresponding spectra, can be browsed interactively in the PeptideAtlas database (http://www.PeptideAtlas.org). Proteome Library generation: From the collected data, the most MS-suited, unique peptides were selected for every annotated protein of . For proteins that had never been observed previously, representative peptides were predicted. The peptides were synthesized, pooled, and analyzed in SRM-triggered MS2 mode (SRM-MS2). From the resulting spectra the most intense fragment ions, as well as the chromatographic retention times, can be extracted. These MS coordinates, called SRM assays, constitute the synthetic Mtb Proteome Library and can be downloaded from the SRMAtlas database (http://www.SRMAtlas.org). Proteome Library validation: The SRM assays in the synthetic Mtb Proteome Library were validated for the detection of proteins in unfractionated mycobacterial lysates by SRM. The resulting quantitative SRM traces and statistical scores can be viewed in the PASSEL database (http://www.PeptideAtlas.org/passel). Reprinted from reference 25 with permission from Elsevier.
microbiolspec/2/2/MGM2-0020-2013-fig4_thmb.gif
microbiolspec/2/2/MGM2-0020-2013-fig4.gif
Image of FIGURE 4

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FIGURE 4

The Mtb Proteome Library. Proteome mapping: After harvesting bacterial cultures, proteins were extracted and digested with the proteolytic enzyme trypsin. The resulting peptides were fractionated using off-gel isoelectric focusing to reduce sample complexity, and each fraction was analyzed by shotgun MS. The peptide and protein identifications, as well as the corresponding spectra, can be browsed interactively in the PeptideAtlas database (http://www.PeptideAtlas.org). Proteome Library generation: From the collected data, the most MS-suited, unique peptides were selected for every annotated protein of . For proteins that had never been observed previously, representative peptides were predicted. The peptides were synthesized, pooled, and analyzed in SRM-triggered MS2 mode (SRM-MS2). From the resulting spectra the most intense fragment ions, as well as the chromatographic retention times, can be extracted. These MS coordinates, called SRM assays, constitute the synthetic Mtb Proteome Library and can be downloaded from the SRMAtlas database (http://www.SRMAtlas.org). Proteome Library validation: The SRM assays in the synthetic Mtb Proteome Library were validated for the detection of proteins in unfractionated mycobacterial lysates by SRM. The resulting quantitative SRM traces and statistical scores can be viewed in the PASSEL database (http://www.PeptideAtlas.org/passel). Reprinted from reference 25 with permission from Elsevier.

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FIGURE 5
SRM assay specificity in mycobacteria or host background. The theoretical specificity of SRM assays determined by the SRMCollider algorithm is shown as a cumulative plot of the number of peptides that can be uniquely identified with a given number of peptide-fragment ion pairs selected with decreasing intensity. Only background peptides with a chromatographic retention time close to that of the target peptide are considered as interfering background. The solid line indicates mycobacterial background. The dashed line indicates human background. Reprinted from reference 25 with permission from Elsevier.
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FIGURE 5

SRM assay specificity in mycobacteria or host background. The theoretical specificity of SRM assays determined by the SRMCollider algorithm is shown as a cumulative plot of the number of peptides that can be uniquely identified with a given number of peptide-fragment ion pairs selected with decreasing intensity. Only background peptides with a chromatographic retention time close to that of the target peptide are considered as interfering background. The solid line indicates mycobacterial background. The dashed line indicates human background. Reprinted from reference 25 with permission from Elsevier.

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Tables

in the Proteomics Era
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Citation: Gengenbacher M, Mouritsen J, Schubert O, Aebersold R, Kaufmann S. 2014. in the proteomics era. microbiolspec 2(2): doi:10.1128/microbiolspec.MGM2-0020-2013
/content/microbiolspec/10.1128/microbiolspec.MGM2-0020-2013.T1
Table 1
Potential of proteomics for design of TB intervention measures
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Table 1

Potential of proteomics for design of TB intervention measures

Source: microbiolspec March 2014 vol. 2 no. 2 doi:10.1128/microbiolspec.MGM2-0020-2013

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