The site of the Media Sphera Publishers contains materials intended solely for healthcare professionals.
By closing this message, you confirm that you are a certified medical professional or a student of a medical educational institution.

Sharov T.N.

Volgograd Plague Control Research Institute

Viktorov D.V.

Department of Microbiology, Volgograd Plague Control Research Institute

Toporkov A.V.

Volgograd Plague Control Research Institute

Proteomic analysis in microbiology

Authors:

Sharov T.N., Viktorov D.V., Toporkov A.V.

More about the authors

Read: 2468 times


To cite this article:

Sharov TN, Viktorov DV, Toporkov AV. Proteomic analysis in microbiology. Molecular Genetics, Microbiology and Virology. 2023;41(1):3‑9. (In Russ.)
https://doi.org/10.17116/molgen2023410113

Recommended articles:

References:

  1. Maccarrone G, Bonfiglio J, Silberstein S, Turck C, Martins-de-Souza D. Characterization of a Protein Interactome by Co-Immunoprecipitation and Shotgun Mass Spectrometry. Methods Mol Biol. 2017;1546:223-234.  https://doi.org/10.1007/978-1-4939-6730-8_19
  2. Noor Z, Beom S, Baker M, Ranganathan S, Mohamedali A. Mass spectrometry-based protein identification in proteomics-a review. Brief Bioinform. 2021;22(2):1620-1638. https://doi.org/10.1093/bib/bbz163
  3. Haraf A, Mensching L, Keller C, Rading S, Scheffold M, Palkowitsch L, et al. Systematic Affinity Purification Coupled to Mass Spectrometry Identified p62 as Part of the Cannabinoid Receptor CB2 Interactome. Front Mol. Neurosci. 2019;12:224.  https://doi.org/10.3389/fnmol.2019.00224
  4. Strasser S, Ghazi P, Starchenko A, Boukhali M, Edwards A, Suarez-Lopez L, et al. Substrate-based kinase activity inference identifies MK2 as driver of colitis. Integr Biol. 2019;11:301-314. 
  5. Keller L, Babin B, Lakemeyer M, Bogyo M. Activity-based protein profiling in bacteria: Applications for identification of therapeutic targets and characterization of microbial communities. Curr Opin Chem Biol. 2020;54:45-53.  https://doi.org/10.1016/j.cbpa.2019.10.007
  6. Bender J, Schmidt C. Mass spectrometry of membrane protein complexes. Biol Chem. 2019;400(7):813-829.  https://doi.org/10.1515/hsz-2018-0443
  7. Low T, Syafruddin S, Mohtar M, Vellaichamy A, Rahman N, Pung Y, et al. Recent progress in mass spectrometry-based strategies for elucidating protein-protein interactions. Cell Mol Life Sci. 2021;78(13):5325-5339. https://doi.org/10.1007/s00018-021-03856-0
  8. Vitorino R, Guedes S, Trindade F, Correia I, Moura G, Carvalho P, et al. De novo sequencing of proteins by mass spectrometry. Expert Rev Proteomics. 2020;17(7-8):595-607.  https://doi.org/10.1080/14789450.2020.1831387
  9. Johnson R, Searle B, Nunn B, Gilmore J, Phillips M, Amemiya C, et al. Assessing Protein Sequence Database Suitability Using De Novo Sequencing. Mol Cell Proteomics. 2020;19(1):198-208.  https://doi.org/10.1074/mcp. TIR119.001752
  10. Suckau D, Evers W, Belau E, Pengelley S, Resemann A, Tang W, et al. Use of PASEF for Accelerated Protein Sequence Confirmation and De Novo Sequencing with High Data Quality. Methods Mol Biol. 2022;2313:207-217.  https://doi.org/10.1007/978-1-0716-1450-1_12
  11. Lasch P, Schneider A, Blumenscheit C, Doellinger J. Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS1) and in Silico Peptide Mass Libraries. Mol Cell Proteomics. 2020;19(12):2125-2138.
  12. Sadygov R. Using SEQUEST with theoretically complete sequence databases. J Am Soc Mass Spectrom. 2015;26(11):1858-1864. https://doi.org/10.1007/s13361-015-1228-5 5
  13. Song Z, Chen L, Zhang C, Xu D. Design and implementation of probability-based scoring function for peptide mass fingerprinting protein identification. Conf Proc IEEE Eng Med Biol Soc. 2006;2006:4556-4559. https://doi.org/10.1109/IEMBS.2006.260150
  14. Mortensen P, Gouw JW, Olsen JV, Ong SE, Rigbolt KT, Bunkenborg J, et al. MSQuant, an open source platform for mass spectrometry-based quantitative proteomics. J. Proteome Res. 2010;9:393-403.  https://doi.org/10.1021/pr900721e
  15. Shuai M, Luo-Shi-Yuan Zuo, Miao Z, Gou W, Xu F, Zengliang Jiang, et al. Multi-omics analyses reveal relationships among dairy consumption, gut microbiota and cardiometabolic health. EBioMedicine. 2021;66:103284. https://doi.org/10.1016/j.ebiom.2021.103284
  16. Kim H, Lee S, Park H. Target-small decoy search strategy for false discovery rate estimation. BMC Bioinformatics. 2019;20(1):438.  https://doi.org/10.1186/s12859-019-3034-8
  17. Wang X, Jones D, Shaw T, Cho J, Wang Y, Tan H, et al. Target-Decoy-Based False Discovery Rate Estimation for Large-Scale Metabolite Identification. J Proteome Res. 2018;17(7):2328-2334. https://doi.org/10.1021/acs.jproteome.8b00019
  18. Tyanova S, Temu T, Cox J. The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat Protoc. 2016;11:2301-2319. https://doi.org/10.1038/nprot.2016.136
  19. Kim H, Lee S, Park H. Target-small decoy search strategy for false discovery rate estimation. BMC Bioinforma. 2019;20:438.  https://doi.org/10.1186/s12859-019-3034-8
  20. Macek B, Forchhammer K, Hardouin J, Weber-Ban E, Grangeasse C, Mijakovic I. Protein post-translational modifications in bacteria. Nat Rev Microbiol. 2019;17(11):651-664.  https://doi.org/10.1038/s41579-019-0243-0
  21. Margreitter C, Petrov D, Zagrovic B. Vienna-PTM web server: a toolkit for MD simulations of protein post-translational modifications. Nucleic Acids Res. 2013;41(Web Server issue):W422-6.  https://doi.org/10.1093/nar/gkt416
  22. Svetlicic E, Doncevic L, Ozdanovac L, Janes A, Tustonic T, Stajduhar A, et al. Direct Identification of Urinary Tract Pathogens by MALDI-TOF/TOF Analysis and De Novo Peptide Sequencing. Molecules. 2022;27(17):5461.
  23. Bornberg-Bauer E, Hlouchova K, Lange A. Structure and function of naturally evolved de novo proteins. Curr Opin Struct Biol. 2021;68:175-183.  https://doi.org/10.1016/j.sbi.2020.11.010
  24. Lebedev A, Vasileva I, Samgina T. FT-MS in the de novo top-down sequencing of natural nontryptic peptides. Mass Spectrom Rev. 2022;41(2):284-313.  https://doi.org/10.1002/mas.21678
  25. Islam M, Mohamedali A, Fernandes C, Baker M, Ranganathan S. De Novo Peptide Sequencing: Deep Mining of High-Resolution Mass Spectrometry Data. Methods Mol Biol. 2017;1549:119-134.  https://doi.org/10.1007/978-1-4939-6740-7_10
  26. Tran NH, Zhang X, Xin L, Shan B, Li M. De novo peptide sequencing by deep learning. Proce Nat Acad Sci. 2017;114:8247-8252. https://doi.org/10.1073/pnas.1705691114
  27. Wang X, Li Y, Wu Z, Wang H, Tan H, Peng J. JUMP: A tag-based database search tool for peptide identification with high sensitivity and accuracy. Mol Cell Proteomics. 2014;13:3663-3673. https://doi.org/10.1074/mcp.O114.039586
  28. Medzihradszky KF, Chalkley RJ. Lessons in de novo peptide sequencing by tandem mass spectrometry. Mass Spectrom Rev. 2015;34(1):43-63.  https://doi.org/10.1002/mas.21406
  29. Macek B, Forchhammer K, Hardouin J, Weber-Ban E, Grangeasse C, Mijakovic I. Protein post-translational modifications in bacteria. Nat Rev Microbiol. 2019;17(11):651-664.  https://doi.org/10.1038/s41579-019-0243-0
  30. Macek B, Forchhammer K, Hardouin J, Weber-Ban E, Grangeasse C. Mijakovic I. Protein post-translational modifications in bacteria. Nature Reviews Microbiology. 2019;17:651-664.  https://doi.org/10.1038/s41579-019-0243-0
  31. Perchey RT, Tonini L, Tosolini M, Fournié J-J, Lopez F, Besson A, Pont F. PTMselect: Optimization of protein modifications discovery by mass spectrometry. Sci Rep. 2019;9:4181. https://doi.org/10.1038/s41598-019-40873-3
  32. Li Q, Shortreed MR, Wenger CD, Frey BL, Schaffer LV, Scalf M, Smith LM. Global Post-Translational Modification Discovery. J Proteome Res. 2017;16:1383-1390. https://doi.org/10.1021/acs.jproteome.6b00034
  33. Nesvizhskii AI. Proteogenomics: Concepts, applications and computational strategies. Nat Methods. 2014;11:1114.
  34. Li YF, Arnold RJ, Li Y, Radivojac P, Sheng Q, Tang HA. Bayesian approach to protein inference problem in shotgun proteomics. J Comput Biol. 2009;16:1183-1193. https://doi.org/10.1089/cmb.2009.0018
  35. Tyanova S, Temu T, Cox J. The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat Protoc. 2016;11:2301-2319. https://doi.org/10.1038/nprot.2016.136
  36. Chen Y, Wang F, Xu F, Yang T. Mass Spectrometry-Based Protein Quantification. Adv Exp Med Biol. 2016;919:255-279.  https://doi.org/10.1007/978-3-319-41448-5_15
  37. Smith K, Fields J, Voogt R, Deng B, Lam Y, Mintz K. Alteration in abundance of specific membrane proteins of Aggregatibacter actinomycetemcomitans is attributed to deletion of the inner membrane protein MorC. Proteomics. 2015;15(11):1859-1867.
  38. Amaranto M, Vaccarello P, Correa E, Barra J, Godino A. Novel intein-based self-cleaving affinity tag for recombinant protein production in Escherichia coli. J Biotechnol. 2021;332:126-134.  https://doi.org/10.1016/j.jbiotec.2021.04.003
  39. Lasch P, Schneider A, Blumenscheit C, Doellinger J. Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS 1) and in Silico Peptide Mass Libraries. Mol Cell Proteomics. 2020;19(12):2125-2139. https://doi.org/10.1074/mcp.TIR120.002061
  40. Nahnsen S, Bielow C, Reinert K, Kohlbacher O. Tools for label-free peptide quantification. Mol Cell Proteomics. 2013;12:549-556.  https://doi.org/10.1074/mcp.R112.025163
  41. Cox J, Hein M, Luber C, Paron I, Nagaraj N, Mann M. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol Cell Proteomics. 2014;13:2513-2526. https://doi.org/10.1074/mcp.M113.031591
  42. Saleh S, Staes A, Deborggraeve S, Gevaert K. Targeted Proteomics for Studying Pathogenic Bacteria. Proteomics. 2019;19(16):e1800435. https://doi.org/10.1002/pmic.201800435
  43. Silva W, Oliveira L, Soares S, Sousa C, Tavares G, Resende C. Quantitative Proteomic Analysis of the Response of Probiotic Putative Lactococcus lactis NCDO 2118 Strain to Different Oxygen Availability Under Temperature Variation. Front Microbiol. 2019;10:759. 
  44. Ryan D, Spraggins J, Caprioli R. Protein identification strategies in MALDI imaging mass spectrometry: a brief review. Curr Opin Chem Biol. 2019;48:64-72.  https://doi.org/10.1016/j.cbpa.2018.10.023
  45. Fujiwara Y, Furuta M, Manabe S, Koga Y, Yasunaga M, Matsumura Y. Imaging mass spectrometry for the precise design of antibody-drug conjugates. Sci Rep. 2016;6:24954. https://doi.org/10.1038/srep24954
  46. Brockmann E, Bauwens AD, Soltwisch J, Dreisewerd K. Advanced Methods for MALDI-MS Imaging of the Chemical Communication in Microbial Communities. Anal Chem. 2019;91(23):15081-15089. https://doi.org/10.1021/acs.analchem.9b03772
  47. Baker TC, Han J, Borchers CH. Recent advancements in matrix-assisted laser desorption/ionization mass spectrometry imaging. Curr Opin Biotechnol. 2017;43:62-69.  https://doi.org/10.1016/j.copbio.2016.09.003
  48. Kallback P, Shariatgorji M, Nilsson A, Andren PE. Novel mass spectrometry imaging software assisting labeled normalization and quantitation of drugs and neuropeptides directly in tissue sections. J Proteomics. 2012;75:4941-4951. https://doi.org/10.1016/j.jprot.2012.07.034

Email Confirmation

An email was sent to test@gmail.com with a confirmation link. Follow the link from the letter to complete the registration on the site.

Email Confirmation

We use cооkies to improve the performance of the site. By staying on our site, you agree to the terms of use of cооkies. To view our Privacy and Cookie Policy, please. click here.