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A User Guide to Validation, Annotation, and Evaluation of N-Terminome Datasets with MANTI

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Part of the Methods in Molecular Biology book series (MIMB,volume 2447)

Abstract

A large variety of enrichment procedures for protein N-termini have been developed to trace protease activity and determine precise cleavage sites, as well as other N-terminal protein modifications. Typically, enriched N-terminal peptides are identified by tandem mass spectrometry using standard database search engines, in many cases the popular MaxQuant software package. MaxQuant Advanced N-termini Interpreter (MANTI) is a software package that helps to validate, annotate, and visualize peptide identifications in N-termini datasets in a rapid and straightforward manner. Usage of MANTI and especially its graphical interface Yoğurtlu MANTI in detail are described to enable users to take full advantage of the software package and the multitude of options it has to offer.

Key words

  • N-termini
  • N-terminomics
  • Proteolysis
  • Positional proteomics
  • Bioinformatics
  • MANTI
  • Analysis

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References

  1. Perrar A, Dissmeyer N, Huesgen PF (2019) New beginnings and new ends: methods for large-scale characterization of protein termini and their use in plant biology. J Exp Bot 70:2021–2038. https://doi.org/10.1093/jxb/erz104

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  2. Weng SSH, Demir F, Ergin EK et al (2019) Sensitive determination of proteolytic proteoforms in limited microscale proteome samples. Mol Cell Proteomics 18:2335–2347. https://doi.org/10.1101/566109

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  3. Niedermaier S, Huesgen PF (2019) Positional proteomics for identification of secreted proteoforms released by site-specific processing of membrane proteins. Biochim Biophys Acta Proteins Proteom 1867:140138. https://doi.org/10.1016/j.bbapap.2018.09.004

    CAS  CrossRef  PubMed  Google Scholar 

  4. Tyanova S, Temu T, Cox J (2016) The MaxQuant computational platform for mass spectrometry—based shotgun proteomics. Nat Protoc 11:2301–2319. https://doi.org/10.1038/nprot.2016.136

    CAS  CrossRef  PubMed  Google Scholar 

  5. Röst HL, Sachsenberg T, Aiche S et al (2016) OpenMS: a flexible open-source software platform for mass spectrometry data analysis. Nat Methods 13:741–748. https://doi.org/10.1038/nmeth.3959

    CAS  CrossRef  PubMed  Google Scholar 

  6. Orsburn BC (2021) Proteome discoverer—a community enhanced data processing suite for protein informatics. Proteomes 9:15. https://doi.org/10.3390/proteomes9010015

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  7. Deutsch EW, Mendoza L, Shteynberg D et al (2015) Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics. Prot Clin Appl 9:745–754. https://doi.org/10.1002/prca.201400164

    CAS  CrossRef  Google Scholar 

  8. Demir F, Kizhakkedathu JN, Rinschen MM, Huesgen PF (2021) MANTI: automated annotation of protein N-termini for rapid interpretation of N-terminome data sets. Anal Chem 93:5596–5605. https://doi.org/10.1021/acs.analchem.1c00310

    CAS  CrossRef  PubMed  PubMed Central  Google Scholar 

  9. Bateman A, Martin MJ, O’Donovan C et al (2017) UniProt: the universal protein knowledgebase. Nucleic Acids Res 45:D158–D169. https://doi.org/10.1093/nar/gkw1099

    CAS  CrossRef  Google Scholar 

  10. Sperschneider J, Catanzariti AM, Deboer K et al (2017) LOCALIZER: subcellular localization prediction of both plant and effector proteins in the plant cell. Sci Rep 7:1–14. https://doi.org/10.1038/srep44598

    CrossRef  Google Scholar 

  11. Armenteros JJA, Salvatore M, Emanuelsson O et al (2019) Detecting sequence signals in targeting peptides using deep learning. Life Sci Alliance 2:1–14. https://doi.org/10.26508/lsa.201900429

    CrossRef  Google Scholar 

  12. Fortelny N, Yang S, Pavlidis P et al (2015) Proteome TopFIND 3.0 with TopFINDer and PathFINDer: database and analysis tools for the association of protein termini to pre- and post-translational events. Nucleic Acids Res 43:D290–D297. https://doi.org/10.1093/nar/gku1012

    CAS  CrossRef  PubMed  Google Scholar 

  13. Meyer B, Chiaravalli J, Gellenoncourt S et al (2020) Characterisation of protease activity during SARS-CoV-2 infection identifies novel viral cleavage sites and cellular targets for drug repurposing. Microbiology

    Google Scholar 

  14. Demir F, Niedermaier S, Kizhakkedathu JN, Huesgen PF (2017) Profiling of protein N-termini and their modifications in complex samples. In: Schilling O (ed) Methods in molecular biology. pp 35–50

    Google Scholar 

  15. Tyanova S, Cox J (2018) Perseus: a bioinformatics platform for integrative analysis of proteomics data in cancer research. Methods Mol Biol (Clifton, NJ) 1711:133–148. https://doi.org/10.1007/978-1-4939-7493-1_7

    CAS  CrossRef  Google Scholar 

  16. Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26:1367–1372. https://doi.org/10.1038/nbt.1511

    CAS  CrossRef  PubMed  Google Scholar 

  17. Mann M (2006) Functional and quantitative proteomics using SILAC. Nat Rev Mol Cell Biol 7:952–958. https://doi.org/10.1038/nrm2067

    CAS  CrossRef  PubMed  Google Scholar 

  18. Tsiatsiani L, Stael S, van Damme P et al (2014) Preparation of arabidopsis thaliana seedling proteomes for identifying metacaspase substrates by N-terminal COFRADIC. Methods Mol Biol 1133:255–261. https://doi.org/10.1007/978-1-4939-0357-3

    CAS  CrossRef  PubMed  Google Scholar 

  19. Boersema PJ, Raijmakers R, Lemeer S et al (2009) Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics. Nat Protoc 4:484–494. https://doi.org/10.1038/nprot.2009.21

    CAS  CrossRef  PubMed  Google Scholar 

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Correspondence to Fatih Demir .

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Demir, F., Huesgen, P.F. (2022). A User Guide to Validation, Annotation, and Evaluation of N-Terminome Datasets with MANTI. In: Klemenčič, M., Stael, S., Huesgen, P.F. (eds) Plant Proteases and Plant Cell Death. Methods in Molecular Biology, vol 2447. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2079-3_22

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  • DOI: https://doi.org/10.1007/978-1-0716-2079-3_22

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2078-6

  • Online ISBN: 978-1-0716-2079-3

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