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Adnane M, de Almeida AM, Chapwanya A. Unveiling the power of proteomics in advancing tropical animal health and production. Trop Anim Health Prod 2024; 56:182. [PMID: 38825622 DOI: 10.1007/s11250-024-04037-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Accepted: 05/20/2024] [Indexed: 06/04/2024]
Abstract
Proteomics, the large-scale study of proteins in biological systems has emerged as a pivotal tool in the field of animal and veterinary sciences, mainly for investigating local and rustic breeds. Proteomics provides valuable insights into biological processes underlying animal growth, reproduction, health, and disease. In this review, we highlight the key proteomics technologies, methodologies, and their applications in domestic animals, particularly in the tropical context. We also discuss advances in proteomics research, including integration of multi-omics data, single-cell proteomics, and proteogenomics, all of which are promising for improving animal health, adaptation, welfare, and productivity. However, proteomics research in domestic animals faces challenges, such as sample preparation variation, data quality control, privacy and ethical considerations relating to animal welfare. We also provide recommendations for overcoming these challenges, emphasizing the importance of following best practices in sample preparation, data quality control, and ethical compliance. We therefore aim for this review to harness the full potential of proteomics in advancing our understanding of animal biology and ultimately improve animal health and productivity in local breeds of diverse animal species in a tropical context.
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Affiliation(s)
- Mounir Adnane
- Department of Biomedicine, Institute of Veterinary Sciences, University of Tiaret, Tiaret, 14000, Algeria.
| | - André M de Almeida
- LEAF-Linking Landscape, Environment, Agriculture and Food Research Center, Associate Laboratory TERRA, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, Lisboa, 1349-017, Portugal
| | - Aspinas Chapwanya
- Department of Clinical Sciences, Ross University School of Veterinary Medicine, Basseterre, 00265, Saint Kitts and Nevis
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2
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Jin L, Wang F, Wang X, Harvey BP, Bi Y, Hu C, Cui B, Darcy AT, Maull JW, Phillips BR, Kim Y, Jenkins GJ, Sornasse TR, Tian Y. Identification of Plasma Biomarkers from Rheumatoid Arthritis Patients Using an Optimized Sequential Window Acquisition of All THeoretical Mass Spectra (SWATH) Proteomics Workflow. Proteomes 2023; 11:32. [PMID: 37873874 PMCID: PMC10594463 DOI: 10.3390/proteomes11040032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/28/2023] [Accepted: 10/02/2023] [Indexed: 10/25/2023] Open
Abstract
Rheumatoid arthritis (RA) is a systemic autoimmune and inflammatory disease. Plasma biomarkers are critical for understanding disease mechanisms, treatment effects, and diagnosis. Mass spectrometry-based proteomics is a powerful tool for unbiased biomarker discovery. However, plasma proteomics is significantly hampered by signal interference from high-abundance proteins, low overall protein coverage, and high levels of missing data from data-dependent acquisition (DDA). To achieve quantitative proteomics analysis for plasma samples with a balance of throughput, performance, and cost, we developed a workflow incorporating plate-based high abundance protein depletion and sample preparation, comprehensive peptide spectral library building, and data-independent acquisition (DIA) SWATH mass spectrometry-based methodology. In this study, we analyzed plasma samples from both RA patients and healthy donors. The results showed that the new workflow performance exceeded that of the current state-of-the-art depletion-based plasma proteomic platforms in terms of both data quality and proteome coverage. Proteins from biological processes related to the activation of systemic inflammation, suppression of platelet function, and loss of muscle mass were enriched and differentially expressed in RA. Some plasma proteins, particularly acute-phase reactant proteins, showed great power to distinguish between RA patients and healthy donors. Moreover, protein isoforms in the plasma were also analyzed, providing even deeper proteome coverage. This workflow can serve as a basis for further application in discovering plasma biomarkers of other diseases.
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Affiliation(s)
- Liang Jin
- Research & Development, AbbVie, North Chicago, IL 60064, USA; (L.J.); (B.P.H.); (B.C.); (A.T.D.); (J.W.M.); (T.R.S.)
| | - Fei Wang
- Research & Development, AbbVie, North Chicago, IL 60064, USA; (L.J.); (B.P.H.); (B.C.); (A.T.D.); (J.W.M.); (T.R.S.)
| | - Xue Wang
- Research & Development, AbbVie, North Chicago, IL 60064, USA; (L.J.); (B.P.H.); (B.C.); (A.T.D.); (J.W.M.); (T.R.S.)
| | - Bohdan P. Harvey
- Research & Development, AbbVie, North Chicago, IL 60064, USA; (L.J.); (B.P.H.); (B.C.); (A.T.D.); (J.W.M.); (T.R.S.)
| | - Yingtao Bi
- Research & Development, AbbVie, North Chicago, IL 60064, USA; (L.J.); (B.P.H.); (B.C.); (A.T.D.); (J.W.M.); (T.R.S.)
| | - Chenqi Hu
- DMPK, Takeda Development Center Americas Inc., Cambridge, MA 02142, USA; (C.H.)
| | - Baoliang Cui
- Research & Development, AbbVie, North Chicago, IL 60064, USA; (L.J.); (B.P.H.); (B.C.); (A.T.D.); (J.W.M.); (T.R.S.)
| | - Anhdao T. Darcy
- Research & Development, AbbVie, North Chicago, IL 60064, USA; (L.J.); (B.P.H.); (B.C.); (A.T.D.); (J.W.M.); (T.R.S.)
| | - John W. Maull
- Research & Development, AbbVie, North Chicago, IL 60064, USA; (L.J.); (B.P.H.); (B.C.); (A.T.D.); (J.W.M.); (T.R.S.)
| | - Ben R. Phillips
- Research & Development, AbbVie, North Chicago, IL 60064, USA; (L.J.); (B.P.H.); (B.C.); (A.T.D.); (J.W.M.); (T.R.S.)
| | - Youngjae Kim
- DMPK, Takeda Development Center Americas Inc., Cambridge, MA 02142, USA; (C.H.)
| | - Gary J. Jenkins
- Research & Development, AbbVie, North Chicago, IL 60064, USA; (L.J.); (B.P.H.); (B.C.); (A.T.D.); (J.W.M.); (T.R.S.)
| | - Thierry R. Sornasse
- Research & Development, AbbVie, North Chicago, IL 60064, USA; (L.J.); (B.P.H.); (B.C.); (A.T.D.); (J.W.M.); (T.R.S.)
| | - Yu Tian
- Research & Development, AbbVie, North Chicago, IL 60064, USA; (L.J.); (B.P.H.); (B.C.); (A.T.D.); (J.W.M.); (T.R.S.)
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Su T, Hollas MAR, Fellers RT, Kelleher NL. Identification of Splice Variants and Isoforms in Transcriptomics and Proteomics. Annu Rev Biomed Data Sci 2023; 6:357-376. [PMID: 37561601 PMCID: PMC10840079 DOI: 10.1146/annurev-biodatasci-020722-044021] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/12/2023]
Abstract
Alternative splicing is pivotal to the regulation of gene expression and protein diversity in eukaryotic cells. The detection of alternative splicing events requires specific omics technologies. Although short-read RNA sequencing has successfully supported a plethora of investigations on alternative splicing, the emerging technologies of long-read RNA sequencing and top-down mass spectrometry open new opportunities to identify alternative splicing and protein isoforms with less ambiguity. Here, we summarize improvements in short-read RNA sequencing for alternative splicing analysis, including percent splicing index estimation and differential analysis. We also review the computational methods used in top-down proteomics analysis regarding proteoform identification, including the construction of databases of protein isoforms and statistical analyses of search results. While many improvements in sequencing and computational methods will result from emerging technologies, there should be future endeavors to increase the effectiveness, integration, and proteome coverage of alternative splicing events.
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Affiliation(s)
- Taojunfeng Su
- Department of Molecular Biosciences, Northwestern University, Evanston, Illinois, USA;
| | - Michael A R Hollas
- Proteomics Center of Excellence, Northwestern University, Evanston, Illinois, USA
| | - Ryan T Fellers
- Proteomics Center of Excellence, Northwestern University, Evanston, Illinois, USA
| | - Neil L Kelleher
- Department of Molecular Biosciences, Northwestern University, Evanston, Illinois, USA;
- Proteomics Center of Excellence, Northwestern University, Evanston, Illinois, USA
- Department of Chemistry, Northwestern University, Evanston, Illinois, USA
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Melby JA, Brown KA, Gregorich ZR, Roberts DS, Chapman EA, Ehlers LE, Gao Z, Larson EJ, Jin Y, Lopez JR, Hartung J, Zhu Y, McIlwain SJ, Wang D, Guo W, Diffee GM, Ge Y. High sensitivity top-down proteomics captures single muscle cell heterogeneity in large proteoforms. Proc Natl Acad Sci U S A 2023; 120:e2222081120. [PMID: 37126723 PMCID: PMC10175728 DOI: 10.1073/pnas.2222081120] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Accepted: 04/05/2023] [Indexed: 05/03/2023] Open
Abstract
Single-cell proteomics has emerged as a powerful method to characterize cellular phenotypic heterogeneity and the cell-specific functional networks underlying biological processes. However, significant challenges remain in single-cell proteomics for the analysis of proteoforms arising from genetic mutations, alternative splicing, and post-translational modifications. Herein, we have developed a highly sensitive functionally integrated top-down proteomics method for the comprehensive analysis of proteoforms from single cells. We applied this method to single muscle fibers (SMFs) to resolve their heterogeneous functional and proteomic properties at the single-cell level. Notably, we have detected single-cell heterogeneity in large proteoforms (>200 kDa) from the SMFs. Using SMFs obtained from three functionally distinct muscles, we found fiber-to-fiber heterogeneity among the sarcomeric proteoforms which can be related to the functional heterogeneity. Importantly, we detected multiple isoforms of myosin heavy chain (~223 kDa), a motor protein that drives muscle contraction, with high reproducibility to enable the classification of individual fiber types. This study reveals single muscle cell heterogeneity in large proteoforms and establishes a direct relationship between sarcomeric proteoforms and muscle fiber types, highlighting the potential of top-down proteomics for uncovering the molecular underpinnings of cell-to-cell variation in complex systems.
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Affiliation(s)
- Jake A. Melby
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI53706
| | - Kyle A. Brown
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI53706
| | - Zachery R. Gregorich
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI53706
| | - David S. Roberts
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI53706
| | - Emily A. Chapman
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI53706
| | - Lauren E. Ehlers
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI53706
| | - Zhan Gao
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, WI53705
| | - Eli J. Larson
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI53706
| | - Yutong Jin
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI53706
| | - Justin R. Lopez
- Department of Kinesiology, University of Wisconsin-Madison, Madison, WI53706
| | - Jared Hartung
- Department of Kinesiology, University of Wisconsin-Madison, Madison, WI53706
| | - Yanlong Zhu
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, WI53705
- Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI53705
| | - Sean J. McIlwain
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI53705
| | | | - Wei Guo
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI53706
| | - Gary M. Diffee
- Department of Kinesiology, University of Wisconsin-Madison, Madison, WI53706
| | - Ying Ge
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI53706
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, WI53705
- Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI53705
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Mezentsev Y, Ershov P, Yablokov E, Kaluzhskiy L, Kupriyanov K, Gnedenko O, Ivanov A. Protein Interactome Profiling of Stable Molecular Complexes in Biomaterial Lysate. Int J Mol Sci 2022; 23:ijms232415697. [PMID: 36555337 PMCID: PMC9779103 DOI: 10.3390/ijms232415697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 12/05/2022] [Accepted: 12/07/2022] [Indexed: 12/14/2022] Open
Abstract
Most proteins function as part of various complexes, forming via stable and dynamic protein-protein interactions (PPIs). The profiling of PPIs expands the fundamental knowledge about the structures, functions, and regulation patterns of protein complexes and intracellular molecular machineries. Protein interactomics aims at solving three main tasks: (1) identification of protein partners and parts of complex intracellular structures; (2) analysis of PPIs parameters (affinity, molecular-recognition specificity, kinetic rate constants, and thermodynamic-parameters determination); (3) the study of the functional role of novel PPIs. The purpose of this work is to update the current state and prospects of multi-omics approaches to profiling of proteins involved in the formation of stable complexes. Methodological paradigm includes a development of protein-extraction and -separation techniques from tissues or cellular lysates and subsequent identification of proteins using mass-spectrometry analysis. In addition, some aspects of authors' experimental platforms, based on high-performance size-exclusion chromatography, procedures of molecular fishing, and protein identification, as well as the possibilities of interactomic taxonomy of each protein, are discussed.
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