PTM-Shepherd: Analysis and Summarization of Post-Translational and Chemical Modifications From Open Search Results
Open searching has proven to be an effective strategy for identifying both known and unknown modifications in shotgun proteomics experiments. Rather than being limited to a small set of user-specified modifications, open searches identify peptides with any mass shift that may correspond to a single...
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Published in | Molecular & cellular proteomics Vol. 20; p. 100018 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
2021
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Subjects | |
Online Access | Get full text |
ISSN | 1535-9476 1535-9484 1535-9484 |
DOI | 10.1074/mcp.TIR120.002216 |
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Abstract | Open searching has proven to be an effective strategy for identifying both known and unknown modifications in shotgun proteomics experiments. Rather than being limited to a small set of user-specified modifications, open searches identify peptides with any mass shift that may correspond to a single modification or a combination of several modifications. Here we present PTM-Shepherd, a bioinformatics tool that automates characterization of post-translational modification profiles detected in open searches based on attributes, such as amino acid localization, fragmentation spectra similarity, retention time shifts, and relative modification rates. PTM-Shepherd can also perform multiexperiment comparisons for studying changes in modification profiles, e.g., in data generated in different laboratories or under different conditions. We demonstrate how PTM-Shepherd improves the analysis of data from formalin-fixed and paraffin-embedded samples, detects extreme underalkylation of cysteine in some data sets, discovers an artifactual modification introduced during peptide synthesis, and uncovers site-specific biases in sample preparation artifacts in a multicenter proteomics profiling study.
[Display omitted]
•Comprehensive open-search annotation.•Sensitive modification detection.•Identification of batch effects.•Novel post-translational modification discovery.
Proteomics open searches require extensive post hoc analysis to be useful. PTM-Shepherd provides comprehensive open search annotation from peptide-spectrum match lists, including modification ID, localization, and effects on spectral similarity (SS) and retention time (RT). These features can be used to find batch effect and new post-translational modifications, and inform subsequent closed searches. It is available as a standalone JAR and as part of the FragPipe suite. |
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AbstractList | Open searching has proven to be an effective strategy for identifying both known and unknown modifications in shotgun proteomics experiments. Rather than being limited to a small set of user-specified modifications, open searches identify peptides with any mass shift that may correspond to a single modification or a combination of several modifications. Here we present PTM-Shepherd, a bioinformatics tool that automates characterization of PTM profiles detected in open searches based on attributes such as amino acid localization, fragmentation spectra similarity, retention time shifts, and relative modification rates. PTM-Shepherd can also perform multi-experiment comparisons for studying changes in modification profiles, e.g. in data generated in different laboratories or under different conditions. We demonstrate how PTM-Shepherd improves the analysis of data from formalin-fixed paraffin-embedded samples, detects extreme underalkylation of cysteine in some datasets, discovers an artefactual modification introduced during peptide synthesis, and uncovers site-specific biases in sample preparation artifacts in a multi-center proteomics profiling study. Open searching has proven to be an effective strategy for identifying both known and unknown modifications in shotgun proteomics experiments. Rather than being limited to a small set of user-specified modifications, open searches identify peptides with any mass shift that may correspond to a single modification or a combination of several modifications. Here we present PTM-Shepherd, a bioinformatics tool that automates characterization of post-translational modification profiles detected in open searches based on attributes, such as amino acid localization, fragmentation spectra similarity, retention time shifts, and relative modification rates. PTM-Shepherd can also perform multiexperiment comparisons for studying changes in modification profiles, e.g., in data generated in different laboratories or under different conditions. We demonstrate how PTM-Shepherd improves the analysis of data from formalin-fixed and paraffin-embedded samples, detects extreme underalkylation of cysteine in some data sets, discovers an artifactual modification introduced during peptide synthesis, and uncovers site-specific biases in sample preparation artifacts in a multicenter proteomics profiling study.Open searching has proven to be an effective strategy for identifying both known and unknown modifications in shotgun proteomics experiments. Rather than being limited to a small set of user-specified modifications, open searches identify peptides with any mass shift that may correspond to a single modification or a combination of several modifications. Here we present PTM-Shepherd, a bioinformatics tool that automates characterization of post-translational modification profiles detected in open searches based on attributes, such as amino acid localization, fragmentation spectra similarity, retention time shifts, and relative modification rates. PTM-Shepherd can also perform multiexperiment comparisons for studying changes in modification profiles, e.g., in data generated in different laboratories or under different conditions. We demonstrate how PTM-Shepherd improves the analysis of data from formalin-fixed and paraffin-embedded samples, detects extreme underalkylation of cysteine in some data sets, discovers an artifactual modification introduced during peptide synthesis, and uncovers site-specific biases in sample preparation artifacts in a multicenter proteomics profiling study. Open searching has proven to be an effective strategy for identifying both known and unknown modifications in shotgun proteomics experiments. Rather than being limited to a small set of user-specified modifications, open searches identify peptides with any mass shift that may correspond to a single modification or a combination of several modifications. Here we present PTM-Shepherd, a bioinformatics tool that automates characterization of post-translational modification profiles detected in open searches based on attributes, such as amino acid localization, fragmentation spectra similarity, retention time shifts, and relative modification rates. PTM-Shepherd can also perform multiexperiment comparisons for studying changes in modification profiles, e.g., in data generated in different laboratories or under different conditions. We demonstrate how PTM-Shepherd improves the analysis of data from formalin-fixed and paraffin-embedded samples, detects extreme underalkylation of cysteine in some data sets, discovers an artifactual modification introduced during peptide synthesis, and uncovers site-specific biases in sample preparation artifacts in a multicenter proteomics profiling study. [Display omitted] •Comprehensive open-search annotation.•Sensitive modification detection.•Identification of batch effects.•Novel post-translational modification discovery. Proteomics open searches require extensive post hoc analysis to be useful. PTM-Shepherd provides comprehensive open search annotation from peptide-spectrum match lists, including modification ID, localization, and effects on spectral similarity (SS) and retention time (RT). These features can be used to find batch effect and new post-translational modifications, and inform subsequent closed searches. It is available as a standalone JAR and as part of the FragPipe suite. |
ArticleNumber | 100018 |
Author | Kong, Andy T. Nesvizhskii, Alexey I. Geiszler, Daniel J. Avtonomov, Dmitry M. Leprevost, Felipe da Veiga Yu, Fengchao |
Author_xml | – sequence: 1 givenname: Daniel J. orcidid: 0000-0002-7691-8534 surname: Geiszler fullname: Geiszler, Daniel J. organization: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA – sequence: 2 givenname: Andy T. orcidid: 0000-0002-4708-7815 surname: Kong fullname: Kong, Andy T. organization: Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA – sequence: 3 givenname: Dmitry M. orcidid: 0000-0002-8758-3901 surname: Avtonomov fullname: Avtonomov, Dmitry M. organization: Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA – sequence: 4 givenname: Fengchao orcidid: 0000-0002-7695-3698 surname: Yu fullname: Yu, Fengchao organization: Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA – sequence: 5 givenname: Felipe da Veiga orcidid: 0000-0002-8228-5374 surname: Leprevost fullname: Leprevost, Felipe da Veiga organization: Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA – sequence: 6 givenname: Alexey I. orcidid: 0000-0002-2806-7819 surname: Nesvizhskii fullname: Nesvizhskii, Alexey I. email: nesvi@med.umich.edu organization: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33262148$$D View this record in MEDLINE/PubMed |
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Keywords | SS CAA RT MS BI IAA PSM UCEC Open searching, PTM, Post-translational modification, Mass-tolerant search, Localization, Spectral similarity, Retention time LUAD PTMs EGS QC FDR FFPE JHU SNR PNNL TMT CPTAC CCRCC Tandem Mass Spectrometry Post-translational modifications Protein Identification Bioinformatics Quality control and metrics |
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SubjectTerms | Open searching, PTM, Post-translational modification, Mass-tolerant search, Localization, Spectral similarity, Retention time |
Title | PTM-Shepherd: Analysis and Summarization of Post-Translational and Chemical Modifications From Open Search Results |
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