Literature DB >> 30282776

Quantifying Homologous Proteins and Proteoforms.

Dmitry Malioutov1, Tianchi Chen2, Edoardo Airoldi3, Jacob Jaffe4, Bogdan Budnik5, Nikolai Slavov6.   

Abstract

Many proteoforms-arising from alternative splicing, post-translational modifications (PTM), or paralogous genes-have distinct biological functions, such as histone PTM proteoforms. However, their quantification by existing bottom-up mass-spectrometry (MS) methods is undermined by peptide-specific biases. To avoid these biases, we developed and implemented a first-principles model (HIquant) for quantifying proteoform stoichiometries. We characterized when MS data allow inferring proteoform stoichiometries by HIquant and derived an algorithm for optimal inference. We applied this algorithm to infer proteoform stoichiometries in two experimental systems that supported rigorous bench-marking: alkylated proteoforms spiked-in at known ratios and endogenous histone 3 PTM proteoforms quantified relative to internal heavy standards. When compared with the benchmarks, the proteoform stoichiometries interfered by HIquant without using external standards had relative error of 5-15% for simple proteoforms and 20-30% for complex proteoforms. A HIquant server is implemented at: https://web.northeastern.edu/slavov/2014HIquant/.
© 2019 Malioutov et al.

Keywords:  Algorithms; Bioinformatics; Bioinformatics Software; Mass Spectrometry; Mathematical Modeling

Mesh:

Substances:

Year:  2018        PMID: 30282776      PMCID: PMC6317479          DOI: 10.1074/mcp.TIR118.000947

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  43 in total

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Review 2.  Top-down proteomics.

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Journal:  Anal Chem       Date:  2004-06-01       Impact factor: 6.986

3.  Peptide and protein sequence analysis by electron transfer dissociation mass spectrometry.

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Journal:  Proc Natl Acad Sci U S A       Date:  2004-06-21       Impact factor: 11.205

4.  Multidimensional liquid chromatography separation of intact proteins by chromatographic focusing and reversed phase of the human serum proteome: optimization and protein database.

Authors:  Simon Sheng; Dawn Chen; Jennifer E Van Eyk
Journal:  Mol Cell Proteomics       Date:  2005-09-27       Impact factor: 5.911

Review 5.  Mass spectrometry-based proteomics turns quantitative.

Authors:  Shao-En Ong; Matthias Mann
Journal:  Nat Chem Biol       Date:  2005-10       Impact factor: 15.040

Review 6.  The complex language of chromatin regulation during transcription.

Authors:  Shelley L Berger
Journal:  Nature       Date:  2007-05-24       Impact factor: 49.962

Review 7.  Decoding protein modifications using top-down mass spectrometry.

Authors:  Nertila Siuti; Neil L Kelleher
Journal:  Nat Methods       Date:  2007-10       Impact factor: 28.547

8.  Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation.

Authors:  Peng Lu; Christine Vogel; Rong Wang; Xin Yao; Edward M Marcotte
Journal:  Nat Biotechnol       Date:  2006-12-24       Impact factor: 54.908

Review 9.  Regulation of apoptosis by alternative pre-mRNA splicing.

Authors:  Christian Schwerk; Klaus Schulze-Osthoff
Journal:  Mol Cell       Date:  2005-07-01       Impact factor: 17.970

10.  Temporal analysis of phosphotyrosine-dependent signaling networks by quantitative proteomics.

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Journal:  Nat Biotechnol       Date:  2004-08-15       Impact factor: 54.908

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  8 in total

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Journal:  Trends Biochem Sci       Date:  2018-11-22       Impact factor: 13.807

Review 2.  Deep Profiling of Cellular Heterogeneity by Emerging Single-Cell Proteomic Technologies.

Authors:  Liwei Yang; Justin George; Jun Wang
Journal:  Proteomics       Date:  2019-12-02       Impact factor: 3.984

3.  DO-MS: Data-Driven Optimization of Mass Spectrometry Methods.

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Journal:  J Proteome Res       Date:  2019-05-28       Impact factor: 4.466

4.  Improving Proteoform Identifications in Complex Systems Through Integration of Bottom-Up and Top-Down Data.

Authors:  Leah V Schaffer; Robert J Millikin; Michael R Shortreed; Mark Scalf; Lloyd M Smith
Journal:  J Proteome Res       Date:  2020-07-10       Impact factor: 4.466

5.  Putting Humpty Dumpty Back Together Again: What Does Protein Quantification Mean in Bottom-Up Proteomics?

Authors:  Deanna L Plubell; Lukas Käll; Bobbie-Jo Webb-Robertson; Lisa M Bramer; Ashley Ives; Neil L Kelleher; Lloyd M Smith; Thomas J Montine; Christine C Wu; Michael J MacCoss
Journal:  J Proteome Res       Date:  2022-02-27       Impact factor: 4.466

6.  Beyond Protein Sequence: Protein Isomerization in Alzheimer's Disease.

Authors:  Harrison Specht; Nikolai Slavov
Journal:  J Proteome Res       Date:  2022-02-04       Impact factor: 4.466

Review 7.  Inferring Protein-Protein Interaction Networks From Mass Spectrometry-Based Proteomic Approaches: A Mini-Review.

Authors:  Kumar Yugandhar; Shagun Gupta; Haiyuan Yu
Journal:  Comput Struct Biotechnol J       Date:  2019-06-20       Impact factor: 7.271

8.  Quantitative analysis of Y-Chromosome gene expression across 36 human tissues.

Authors:  Alexander K Godfrey; Sahin Naqvi; Lukáš Chmátal; Joel M Chick; Richard N Mitchell; Steven P Gygi; Helen Skaletsky; David C Page
Journal:  Genome Res       Date:  2020-05-27       Impact factor: 9.043

  8 in total

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