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Han Y, Wennersten SA, Pandi BP, Ng DCM, Lau E, Lam MPY. A Ratiometric Catalog of Protein Isoform Shifts in the Cardiac Fetal Gene Program. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.09.588716. [PMID: 38645170 PMCID: PMC11030362 DOI: 10.1101/2024.04.09.588716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
The fetal genetic program orchestrates cardiac development and the re-expression of fetal genes is thought to underlie cardiac disease and adaptation. Here, a proteomics ratio test using mass spectrometry is applied to find protein isoforms with statistically significant usage differences in the fetal vs. postnatal mouse heart. Changes in isoform usage ratios are pervasive at the protein level, with 104 significant events observed, including 88 paralog-derived isoform switching events and 16 splicing-derived isoform switching events between fetal and postnatal hearts. The ratiometric proteomic comparisons rediscovered hallmark fetal gene signatures including a postnatal switch from fetal β (MYH7) toward ɑ (MYH6) myosin heavy chains and from slow skeletal muscle (TNNI1) toward cardiac (TNNI3) troponin I. Altered usages in metabolic proteins are prominent, including a platelet to muscle phosphofructokinase (PFKP - PFKM), enolase 1 to 3 (ENO1 - ENO3), and alternative splicing of pyruvate kinase M2 toward M1 (PKM2 - PKM1) isoforms in glycolysis. The data also revealed a parallel change in mitochondrial proteins in cardiac development, suggesting the shift toward aerobic respiration involves also a remodeling of the mitochondrial protein isoform proportion. Finally, a number of glycolytic protein isoforms revert toward their fetal forms in adult hearts under pathological cardiac hypertrophy, suggesting their functional roles in adaptive or maladaptive response, but this reversal is partial. In summary, this work presents a catalog of ratiometric protein markers of the fetal genetic program of the mouse heart, including previously unreported splice isoform markers.
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Affiliation(s)
- Yu Han
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Sara A Wennersten
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Boomathi P Pandi
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Dominic C M Ng
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Edward Lau
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Maggie P Y Lam
- Department of Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
- Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO 80045, USA
- Consortium for Fibrosis Research and Translation, University of Colorado School of Medicine, Aurora, CO 80045, USA
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2
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Manda V, Pavelka J, Lau E. Proteomics applications in next generation induced pluripotent stem cell models. Expert Rev Proteomics 2024; 21:217-228. [PMID: 38511670 PMCID: PMC11065590 DOI: 10.1080/14789450.2024.2334033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 03/08/2024] [Indexed: 03/22/2024]
Abstract
INTRODUCTION Induced pluripotent stem (iPS) cell technology has transformed biomedical research. New opportunities now exist to create new organoids, microtissues, and body-on-a-chip systems for basic biology investigations and clinical translations. AREAS COVERED We discuss the utility of proteomics for attaining an unbiased view into protein expression changes during iPS cell differentiation, cell maturation, and tissue generation. The ability to discover cell-type specific protein markers during the differentiation and maturation of iPS-derived cells has led to new strategies to improve cell production yield and fidelity. In parallel, proteomic characterization of iPS-derived organoids is helping to realize the goal of bridging in vitro and in vivo systems. EXPERT OPINIONS We discuss some current challenges of proteomics in iPS cell research and future directions, including the integration of proteomic and transcriptomic data for systems-level analysis.
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Affiliation(s)
- Vyshnavi Manda
- Department of Medicine, Division of Cardiology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Consortium for Fibrosis Research and Translation, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Jay Pavelka
- Department of Medicine, Division of Cardiology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Consortium for Fibrosis Research and Translation, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Edward Lau
- Department of Medicine, Division of Cardiology, University of Colorado School of Medicine, Aurora, Colorado, USA
- Consortium for Fibrosis Research and Translation, University of Colorado School of Medicine, Aurora, Colorado, USA
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3
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Wang Y, Xie Z, Kutschera E, Adams JI, Kadash-Edmondson KE, Xing Y. rMATS-turbo: an efficient and flexible computational tool for alternative splicing analysis of large-scale RNA-seq data. Nat Protoc 2024; 19:1083-1104. [PMID: 38396040 DOI: 10.1038/s41596-023-00944-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 11/02/2023] [Indexed: 02/25/2024]
Abstract
Pre-mRNA alternative splicing is a prevalent mechanism for diversifying eukaryotic transcriptomes and proteomes. Regulated alternative splicing plays a role in many biological processes, and dysregulated alternative splicing is a feature of many human diseases. Short-read RNA sequencing (RNA-seq) is now the standard approach for transcriptome-wide analysis of alternative splicing. Since 2011, our laboratory has developed and maintained Replicate Multivariate Analysis of Transcript Splicing (rMATS), a computational tool for discovering and quantifying alternative splicing events from RNA-seq data. Here we provide a protocol for the contemporary version of rMATS, rMATS-turbo, a fast and scalable re-implementation that maintains the statistical framework and user interface of the original rMATS software, while incorporating a revamped computational workflow with a substantial improvement in speed and data storage efficiency. The rMATS-turbo software scales up to massive RNA-seq datasets with tens of thousands of samples. To illustrate the utility of rMATS-turbo, we describe two representative application scenarios. First, we describe a broadly applicable two-group comparison to identify differential alternative splicing events between two sample groups, including both annotated and novel alternative splicing events. Second, we describe a quantitative analysis of alternative splicing in a large-scale RNA-seq dataset (~1,000 samples), including the discovery of alternative splicing events associated with distinct cell states. We detail the workflow and features of rMATS-turbo that enable efficient parallel processing and analysis of large-scale RNA-seq datasets on a compute cluster. We anticipate that this protocol will help the broad user base of rMATS-turbo make the best use of this software for studying alternative splicing in diverse biological systems.
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Affiliation(s)
- Yuanyuan Wang
- Bioinformatics Interdepartmental Graduate Program, University of California, Los Angeles, Los Angeles, CA, USA
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Zhijie Xie
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Eric Kutschera
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jenea I Adams
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Genomics and Computational Biology Graduate Program, University of Pennsylvania, Philadelphia, PA, USA
| | - Kathryn E Kadash-Edmondson
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Yi Xing
- Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
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Korchak JA, Jeffery ED, Bandyopadhyay S, Jordan BT, Lehe M, Watts EF, Fenix A, Wilhelm M, Sheynkman GM. IS-PRM-based peptide targeting informed by long-read sequencing for alternative proteome detection. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.01.587549. [PMID: 38617311 PMCID: PMC11014528 DOI: 10.1101/2024.04.01.587549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Alternative splicing is a major contributor of transcriptomic complexity, but the extent to which transcript isoforms are translated into stable, functional protein isoforms is unclear. Furthermore, detection of relatively scarce isoform-specific peptides is challenging, with many protein isoforms remaining uncharted due to technical limitations. Recently, a family of advanced targeted MS strategies, termed internal standard parallel reaction monitoring (IS-PRM), have demonstrated multiplexed, sensitive detection of pre-defined peptides of interest. Such approaches have not yet been used to confirm existence of novel peptides. Here, we present a targeted proteogenomic approach that leverages sample-matched long-read RNA sequencing (LR RNAseq) data to predict potential protein isoforms with prior transcript evidence. Predicted tryptic isoform-specific peptides, which are specific to individual gene product isoforms, serve as "triggers" and "targets" in the IS-PRM method, Tomahto. Using the model human stem cell line WTC11, LR RNAseq data were generated and used to inform the generation of synthetic standards for 192 isoform-specific peptides (114 isoforms from 55 genes). These synthetic "trigger" peptides were labeled with super heavy tandem mass tags (TMT) and spiked into TMT-labeled WTC11 tryptic digest, predicted to contain corresponding endogenous "target" peptides. Compared to DDA mode, Tomahto increased detectability of isoforms by 3.6-fold, resulting in the identification of five previously unannotated isoforms. Our method detected protein isoform expression for 43 out of 55 genes corresponding to 54 resolved isoforms. This LR RNA seq-informed Tomahto targeted approach, called LRP-IS-PRM, is a new modality for generating protein-level evidence of alternative isoforms - a critical first step in designing functional studies and eventually clinical assays.
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Affiliation(s)
- Jennifer A. Korchak
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Erin D. Jeffery
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Saikat Bandyopadhyay
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Ben T. Jordan
- Cancer Genomics Research Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD USA
| | - Micah Lehe
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Emily F. Watts
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Aidan Fenix
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Mathias Wilhelm
- Computational Mass Spectrometry, Technical University of Munich (TUM), D-85354 Freising, Germany
| | - Gloria M. Sheynkman
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
- UVA Comprehensive Cancer Center, University of Virginia, Charlottesville, VA, USA
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Dube DK, Dube S, Shi H, Benz P, Randhawa S, Fan Y, Wang J, Ma Z, Sanger JW, Sanger JM, Poiesz BJ. Sarcomeric tropomyosin expression during human iPSC differentiation into cardiomyocytes. Cytoskeleton (Hoboken) 2024. [PMID: 38470291 DOI: 10.1002/cm.21850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 01/31/2024] [Accepted: 02/21/2024] [Indexed: 03/13/2024]
Abstract
Tropomyosin (TPM) is an essential sarcomeric component, stabilizing the thin filament and facilitating actin's interaction with myosin. In mammals, including humans, there are four TPM genes (TPM1, TPM2, TPM3, and TPM4) each of which generates a multitude of TPM isoforms via alternative splicing and using different promoters. In this study, we have examined the expression of transcripts as well as proteins of various sarcomeric TPM isoforms during human inducible pluripotent stem cell differentiation into cardiomyocytes. During the differentiation time course, we harvested cells on Days 0, 5, 10, 15, and 20 to analyze for various sarcomeric TPM transcripts by qRT-PCR and for sarcomeric TPM proteins using two-dimensional Western blot with sarcomeric TPM-specific CH1 monoclonal antibody followed by mass spectra analyses. Our results show increasing levels of total TPM transcripts and proteins during the period of differentiation, but varying levels of specific TPM isoforms during the same period. By Day 20, the rank order of TPM transcripts was TPM1α > TPM1κ > TPM2α > TPM1μ > TPM3α > TPM4α. TPM1α was the dominant protein produced with some TPM2 and much less TPM1κ and μ. Interestingly, small amounts of two lower molecular weight TPM3 isoforms were detected on Day 15. To the best of our knowledge this is the first demonstration of TPM1μ non-muscle isoform protein expression before and during cardiac differentiation.
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Affiliation(s)
- Dipak K Dube
- Department of Medicine, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Syamalima Dube
- Department of Medicine, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Huaiyu Shi
- Department of Biomedical and Chemical Engineering, Syracuse University, Syracuse, New York, USA
| | - Patricia Benz
- Department of Medicine, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Samender Randhawa
- Department of Medicine, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Yingli Fan
- Department of Cell and Developmental Biology, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Jusuo Wang
- Department of Cell and Developmental Biology, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Zhen Ma
- Department of Biomedical and Chemical Engineering, Syracuse University, Syracuse, New York, USA
| | - Joseph W Sanger
- Department of Cell and Developmental Biology, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Jean M Sanger
- Department of Cell and Developmental Biology, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Bernard J Poiesz
- Department of Medicine, SUNY Upstate Medical University, Syracuse, New York, USA
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6
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Pandi B, Brenman S, Black A, Ng DCM, Lau E, Lam MPY. Tissue Usage Preference and Intrinsically Disordered Region Remodeling of Alternative Splicing Derived Proteoforms in the Heart. J Proteome Res 2024. [PMID: 38456420 DOI: 10.1021/acs.jproteome.3c00789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2024]
Abstract
A computational analysis of mass spectrometry data was performed to uncover alternative splicing derived protein variants across chambers of the human heart. Evidence for 216 non-canonical isoforms was apparent in the atrium and the ventricle, including 52 isoforms not documented on SwissProt and recovered using an RNA sequencing derived database. Among non-canonical isoforms, 29 show signs of regulation based on statistically significant preferences in tissue usage, including a ventricular enriched protein isoform of tensin-1 (TNS1) and an atrium-enriched PDZ and LIM Domain 3 (PDLIM3) isoform 2 (PDLIM3-2/ALP-H). Examined variant regions that differ between alternative and canonical isoforms are highly enriched with intrinsically disordered regions. Moreover, over two-thirds of such regions are predicted to function in protein binding and RNA binding. The analysis here lends further credence to the notion that alternative splicing diversifies the proteome by rewiring intrinsically disordered regions, which are increasingly recognized to play important roles in the generation of biological function from protein sequences.
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7
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Solovyeva EM, Utzinger S, Vissières A, Mitchelmore J, Ahrné E, Hermes E, Poetsch T, Ronco M, Bidinosti M, Merkl C, Serluca FC, Fessenden J, Naumann U, Voshol H, Meyer AS, Hoersch S. Integrative Proteogenomics for Differential Expression and Splicing Variation in a DM1 Mouse Model. Mol Cell Proteomics 2024; 23:100683. [PMID: 37993104 PMCID: PMC10770608 DOI: 10.1016/j.mcpro.2023.100683] [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: 07/31/2022] [Revised: 09/02/2023] [Accepted: 11/17/2023] [Indexed: 11/24/2023] Open
Abstract
Dysregulated mRNA splicing is involved in the pathogenesis of many diseases including cancer, neurodegenerative diseases, and muscular dystrophies such as myotonic dystrophy type 1 (DM1). Comprehensive assessment of dysregulated splicing on the transcriptome and proteome level has been methodologically challenging, and thus investigations have often been targeting only few genes. Here, we performed a large-scale coordinated transcriptomic and proteomic analysis to characterize a DM1 mouse model (HSALR) in comparison to wild type. Our integrative proteogenomics approach comprised gene- and splicing-level assessments for mRNAs and proteins. It recapitulated many known instances of aberrant mRNA splicing in DM1 and identified new ones. It enabled the design and targeting of splicing-specific peptides and confirmed the translation of known instances of aberrantly spliced disease-related genes (e.g., Atp2a1, Bin1, Ryr1), complemented by novel findings (Flnc and Ywhae). Comparative analysis of large-scale mRNA and protein expression data showed quantitative agreement of differentially expressed genes and splicing patterns between disease and wild type. We hence propose this work as a suitable blueprint for a robust and scalable integrative proteogenomic strategy geared toward advancing our understanding of splicing-based disorders. With such a strategy, splicing-based biomarker candidates emerge as an attractive and accessible option, as they can be efficiently asserted on the mRNA and protein level in coordinated fashion.
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Affiliation(s)
- Elizaveta M Solovyeva
- Research Informatics, Biomedical Research at Novartis, Basel, Switzerland; V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, Russia.
| | - Stephan Utzinger
- Diseases of Aging and Regenerative Medicine, Biomedical Research at Novartis, Basel, Switzerland
| | | | - Joanna Mitchelmore
- Diseases of Aging and Regenerative Medicine, Biomedical Research at Novartis, Basel, Switzerland
| | - Erik Ahrné
- Discovery Sciences, Biomedical Research at Novartis, Basel, Switzerland
| | - Erwin Hermes
- Discovery Sciences, Biomedical Research at Novartis, Basel, Switzerland
| | - Tania Poetsch
- Discovery Sciences, Biomedical Research at Novartis, Basel, Switzerland
| | - Marie Ronco
- Diseases of Aging and Regenerative Medicine, Biomedical Research at Novartis, Basel, Switzerland
| | - Michael Bidinosti
- Diseases of Aging and Regenerative Medicine, Biomedical Research at Novartis, Basel, Switzerland
| | - Claudia Merkl
- Diseases of Aging and Regenerative Medicine, Biomedical Research at Novartis, Basel, Switzerland
| | - Fabrizio C Serluca
- Research Informatics, Biomedical Research at Novartis, Cambridge, Massachusetts, USA
| | - James Fessenden
- Neurodegenerative Diseases, Biomedical Research at Novartis, Cambridge, Massachusetts, USA
| | - Ulrike Naumann
- Discovery Sciences, Biomedical Research at Novartis, Basel, Switzerland
| | - Hans Voshol
- Discovery Sciences, Biomedical Research at Novartis, Basel, Switzerland
| | - Angelika S Meyer
- Diseases of Aging and Regenerative Medicine, Biomedical Research at Novartis, Basel, Switzerland
| | - Sebastian Hoersch
- Research Informatics, Biomedical Research at Novartis, Basel, Switzerland.
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Dam SH, Olsen LR, Vitting-Seerup K. Expression and splicing mediate distinct biological signals. BMC Biol 2023; 21:220. [PMID: 37858135 PMCID: PMC10588054 DOI: 10.1186/s12915-023-01724-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 10/04/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND Through alternative splicing, most human genes produce multiple isoforms in a cell-, tissue-, and disease-specific manner. Numerous studies show that alternative splicing is essential for development, diseases, and their treatments. Despite these important examples, the extent and biological relevance of splicing are currently unknown. RESULTS To solve this problem, we developed pairedGSEA and used it to profile transcriptional changes in 100 representative RNA-seq datasets. Our systematic analysis demonstrates that changes in splicing, on average, contribute to 48.1% of the biological signal in expression analyses. Gene-set enrichment analysis furthermore indicates that expression and splicing both convey shared and distinct biological signals. CONCLUSIONS These findings establish alternative splicing as a major regulator of the human condition and suggest that most contemporary RNA-seq studies likely miss out on critical biological insights. We anticipate our results will contribute to the transition from a gene-centric to an isoform-centric research paradigm.
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Affiliation(s)
- Søren Helweg Dam
- Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Lars Rønn Olsen
- Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Kristoffer Vitting-Seerup
- Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Denmark.
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Pandi B, Brenman S, Black A, Ng DCM, Lau E, Lam MPY. Tissue Usage Preference and Intrinsically Disordered Region Remodeling of Alternative Splicing Derived Proteoforms in the Heart. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.08.561375. [PMID: 37873130 PMCID: PMC10592692 DOI: 10.1101/2023.10.08.561375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
A computational analysis of mass spectrometry data was performed to uncover alternative splicing derived protein variants across chambers of the human heart. Evidence for 216 non-canonical isoforms was apparent in the atrium and the ventricle, including 52 isoforms not documented on SwissProt and recovered using an RNA sequencing derived database. Among non-canonical isoforms, 29 show signs of regulation based on statistically significant preferences in tissue usage, including a ventricular enriched protein isoform of tensin-1 (TNS1) and an atrium-enriched PDZ and LIM Domain 3 (PDLIM3) isoform 2 (PDLIM3-2/ALP-H). Examined variant regions that differ between alternative and canonical isoforms are highly enriched in intrinsically disordered regions, and over two-thirds of such regions are predicted to function in protein binding and/or RNA binding. The analysis here lends further credence to the notion that alternative splicing diversifies the proteome by rewiring intrinsically disordered regions, which are increasingly recognized to play important roles in the generation of biological function from protein sequences.
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Affiliation(s)
- Boomathi Pandi
- Department of Medicine/Division of Cardiology, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Stella Brenman
- Department of Medicine/Division of Cardiology, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Alexander Black
- Department of Medicine/Division of Cardiology, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Dominic C. M. Ng
- Department of Medicine/Division of Cardiology, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Edward Lau
- Department of Medicine/Division of Cardiology, University of Colorado School of Medicine, Aurora, CO 80045, USA
- Consortium for Fibrosis Research and Translation (CFReT), University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Maggie P. Y. Lam
- Department of Medicine/Division of Cardiology, University of Colorado School of Medicine, Aurora, CO 80045, USA
- Department of Biochemistry & Molecular Genetics, University of Colorado School of Medicine, Aurora, CO 80045, USA
- Consortium for Fibrosis Research and Translation (CFReT), University of Colorado School of Medicine, Aurora, CO 80045, USA
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10
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Dou Y, Liu Y, Yi X, Olsen LK, Zhu H, Gao Q, Zhou H, Zhang B. SEPepQuant enhances the detection of possible isoform regulations in shotgun proteomics. Nat Commun 2023; 14:5809. [PMID: 37726316 PMCID: PMC10509223 DOI: 10.1038/s41467-023-41558-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 09/06/2023] [Indexed: 09/21/2023] Open
Abstract
Shotgun proteomics is essential for protein identification and quantification in biomedical research, but protein isoform characterization is challenging due to the extensive number of peptides shared across proteins, hindering our understanding of protein isoform regulation and their roles in normal and disease biology. We systematically assess the challenge and opportunities of shotgun proteomics-based protein isoform characterization using in silico and experimental data, and then present SEPepQuant, a graph theory-based approach to maximize isoform characterization. Using published data from one induced pluripotent stem cell study and two human hepatocellular carcinoma studies, we demonstrate the ability of SEPepQuant in addressing the key limitations of existing methods, providing more comprehensive isoform-level characterization, identifying hundreds of isoform-level regulation events, and facilitating streamlined cross-study comparisons. Our analysis provides solid evidence to support a widespread role of protein isoform regulation in normal and disease processes, and SEPepQuant has broad applications to biological and translational research.
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Affiliation(s)
- Yongchao Dou
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Yuejia Liu
- School of Chinese Materia Medica, Nanjing University of Chinese Medicine, 138 Xianlin Avenue, 210023, Nanjing, Jiangsu, China
| | - Xinpei Yi
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Lindsey K Olsen
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Hongwen Zhu
- Department of Analytical Chemistry, State Key Laboratory of Drug Research and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, 201203, Shanghai, China
| | - Qiang Gao
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, and Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, 180 Fenglin Road, 200032, Shanghai, China
| | - Hu Zhou
- School of Chinese Materia Medica, Nanjing University of Chinese Medicine, 138 Xianlin Avenue, 210023, Nanjing, Jiangsu, China
- Department of Analytical Chemistry, State Key Laboratory of Drug Research and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, 201203, Shanghai, China
| | - Bing Zhang
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, 77030, USA.
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA.
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11
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Engelhard CA, Khani S, Derdak S, Bilban M, Kornfeld JW. Nanopore sequencing unveils the complexity of the cold-activated murine brown adipose tissue transcriptome. iScience 2023; 26:107190. [PMID: 37564700 PMCID: PMC10410515 DOI: 10.1016/j.isci.2023.107190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 04/28/2023] [Accepted: 06/16/2023] [Indexed: 08/12/2023] Open
Abstract
Alternative transcription increases transcriptome complexity by expression of multiple transcripts per gene. Annotation and quantification of transcripts using short-read sequencing is non-trivial. Long-read sequencing aims at overcoming these problems by sequencing full-length transcripts. Activation of brown adipose tissue (BAT) thermogenesis involves major transcriptomic remodeling and positively affects metabolism via increased energy expenditure. We benchmark Oxford Nanopore Technology (ONT) long-read sequencing protocols to Illumina short-read sequencing assessing alignment characteristics, gene and transcript detection and quantification, differential gene and transcript expression, transcriptome reannotation, and differential transcript usage (DTU). We find ONT sequencing is superior to Illumina for transcriptome reassembly, reducing the risk of false-positive events by unambiguously mapping reads to transcripts. We identified novel isoforms of genes undergoing DTU in cold-activated BAT including Cars2, Adtrp, Acsl5, Scp2, Aldoa, and Pde4d, validated by real-time PCR. The reannotated murine BAT transcriptome established here provides a framework for future investigations into the regulation of BAT.
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Affiliation(s)
- Christoph Andreas Engelhard
- Department for Biochemistry and Molecular Biology (BMB), University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark
| | - Sajjad Khani
- Max Planck Institute for Metabolism Research, Gleueler Strasse 50, 50931 Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Ageing-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Sophia Derdak
- Core Facilities, Medical University of Vienna, Lazarettgasse 14, 1090 Vienna, Austria
| | - Martin Bilban
- Department of Laboratory Medicine & Core Facilities, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria
| | - Jan-Wilhelm Kornfeld
- Department for Biochemistry and Molecular Biology (BMB), University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark
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12
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Desai H, Ofori S, Boatner L, Yu F, Villanueva M, Ung N, Nesvizhskii AI, Backus K. Multi-omic stratification of the missense variant cysteinome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.12.553095. [PMID: 37645963 PMCID: PMC10461992 DOI: 10.1101/2023.08.12.553095] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Cancer genomes are rife with genetic variants; one key outcome of this variation is gain-ofcysteine, which is the most frequently acquired amino acid due to missense variants in COSMIC. Acquired cysteines are both driver mutations and sites targeted by precision therapies. However, despite their ubiquity, nearly all acquired cysteines remain uncharacterized. Here, we pair cysteine chemoproteomics-a technique that enables proteome-wide pinpointing of functional, redox sensitive, and potentially druggable residues-with genomics to reveal the hidden landscape of cysteine acquisition. For both cancer and healthy genomes, we find that cysteine acquisition is a ubiquitous consequence of genetic variation that is further elevated in the context of decreased DNA repair. Our chemoproteogenomics platform integrates chemoproteomic, whole exome, and RNA-seq data, with a customized 2-stage false discovery rate (FDR) error controlled proteomic search, further enhanced with a user-friendly FragPipe interface. Integration of CADD predictions of deleteriousness revealed marked enrichment for likely damaging variants that result in acquisition of cysteine. By deploying chemoproteogenomics across eleven cell lines, we identify 116 gain-of-cysteines, of which 10 were liganded by electrophilic druglike molecules. Reference cysteines proximal to missense variants were also found to be pervasive, 791 in total, supporting heretofore untapped opportunities for proteoform-specific chemical probe development campaigns. As chemoproteogenomics is further distinguished by sample-matched combinatorial variant databases and compatible with redox proteomics and small molecule screening, we expect widespread utility in guiding proteoform-specific biology and therapeutic discovery.
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Affiliation(s)
- Heta Desai
- Biological Chemistry Department, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA
- Molecular Biology Institute, UCLA, Los Angeles, CA, 90095, USA
| | - Samuel Ofori
- Biological Chemistry Department, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA
| | - Lisa Boatner
- Biological Chemistry Department, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA
- Department of Chemistry and Biochemistry, UCLA, Los Angeles, CA, 90095, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Miranda Villanueva
- Biological Chemistry Department, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA
- Molecular Biology Institute, UCLA, Los Angeles, CA, 90095, USA
| | - Nicholas Ung
- Biological Chemistry Department, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA
- Department of Chemistry and Biochemistry, UCLA, Los Angeles, CA, 90095, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Pathology, University of Michigan, Ann Arbor, MI, 48109, USA
- Molecular Biology Institute, UCLA, Los Angeles, CA, 90095, USA
- DOE Institute for Genomics and Proteomics, UCLA, Los Angeles, CA, 90095, USA
- Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA, 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, UCLA, Los Angeles, CA, 90095, USA
| | - Alexey I Nesvizhskii
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Pathology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Keriann Backus
- Biological Chemistry Department, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA
- Department of Chemistry and Biochemistry, UCLA, Los Angeles, CA, 90095, USA
- Molecular Biology Institute, UCLA, Los Angeles, CA, 90095, USA
- DOE Institute for Genomics and Proteomics, UCLA, Los Angeles, CA, 90095, USA
- Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA, 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, UCLA, Los Angeles, CA, 90095, USA
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13
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Chapman EA, Aballo TJ, Melby JA, Zhou T, Price SJ, Rossler KJ, Lei I, Tang PC, Ge Y. Defining the Sarcomeric Proteoform Landscape in Ischemic Cardiomyopathy by Top-Down Proteomics. J Proteome Res 2023; 22:931-941. [PMID: 36800490 PMCID: PMC10115148 DOI: 10.1021/acs.jproteome.2c00729] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
Ischemic cardiomyopathy (ICM) is a prominent form of heart failure, but the molecular mechanisms underlying ICM remain relatively understudied due to marked phenotypic heterogeneity. Alterations in post-translational modifications (PTMs) and isoform switches in sarcomeric proteins play important roles in cardiac pathophysiology. Thus, it is essential to define sarcomeric proteoform landscape to better understand ICM. Herein, we have implemented a top-down liquid chromatography (LC)-mass spectrometry (MS)-based proteomics method for the identification and quantification of sarcomeric proteoforms in the myocardia of donors without heart diseases (n = 16) compared to end-stage ICM patients (n = 16). Importantly, quantification of post-translational modifications (PTMs) and expression reveal significant changes in various sarcomeric proteins extracted from ICM tissues. Changes include altered phosphorylation and expression of cardiac troponin I (cTnI) and enigma homologue 2 (ENH2) as well as an increase in muscle LIM protein (MLP) and calsarcin-1 (Cal-1) phosphorylation in ICM hearts. Our results imply that the contractile apparatus of the sarcomere is severely dysregulated during ICM. Thus, this is the first study to uncover significant molecular changes to multiple sarcomeric proteins in the LV myocardia of the end-stage ICM patients using liquid chromatography-mass spectrometry (LC-MS)-based top-down proteomics. Raw data are available via the PRIDE repository with identifier PXD038066.
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Affiliation(s)
- Emily A. Chapman
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Timothy J. Aballo
- Molecular and Cellular Pharmacology Training Program, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA
| | - Jake A. Melby
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Tianhua Zhou
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Scott J. Price
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
| | - Kalina J. Rossler
- Molecular and Cellular Pharmacology Training Program, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA
| | - Ienglam Lei
- Department of Cardiac Surgery, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Paul C. Tang
- Department of Cardiac Surgery, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Ying Ge
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA
- Molecular and Cellular Pharmacology Training Program, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA
- Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, USA
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14
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Lin TT, Zhang T, Kitata RB, Liu T, Smith RD, Qian WJ, Shi T. Mass spectrometry-based targeted proteomics for analysis of protein mutations. MASS SPECTROMETRY REVIEWS 2023; 42:796-821. [PMID: 34719806 PMCID: PMC9054944 DOI: 10.1002/mas.21741] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 09/28/2021] [Accepted: 10/07/2021] [Indexed: 05/03/2023]
Abstract
Cancers are caused by accumulated DNA mutations. This recognition of the central role of mutations in cancer and recent advances in next-generation sequencing, has initiated the massive screening of clinical samples and the identification of 1000s of cancer-associated gene mutations. However, proteomic analysis of the expressed mutation products lags far behind genomic (transcriptomic) analysis. With comprehensive global proteomics analysis, only a small percentage of single nucleotide variants detected by DNA and RNA sequencing have been observed as single amino acid variants due to current technical limitations. Proteomic analysis of mutations is important with the potential to advance cancer biomarker development and the discovery of new therapeutic targets for more effective disease treatment. Targeted proteomics using selected reaction monitoring (also known as multiple reaction monitoring) and parallel reaction monitoring, has emerged as a powerful tool with significant advantages over global proteomics for analysis of protein mutations in terms of detection sensitivity, quantitation accuracy and overall practicality (e.g., reliable identification and the scale of quantification). Herein we review recent advances in the targeted proteomics technology for enhancing detection sensitivity and multiplexing capability and highlight its broad biomedical applications for analysis of protein mutations in human bodily fluids, tissues, and cell lines. Furthermore, we review recent applications of top-down proteomics for analysis of protein mutations. Unlike the commonly used bottom-up proteomics which requires digestion of proteins into peptides, top-down proteomics directly analyzes intact proteins for more precise characterization of mutation isoforms. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale targeted detection and quantification of important protein mutations are discussed.
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Affiliation(s)
- Tai-Tu Lin
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Tong Zhang
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Reta B. Kitata
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Tao Liu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Richard D. Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
| | - Tujin Shi
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, USA
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15
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Wang H, Cheng Q, Zhai Z, Cui X, Li M, Ye R, Sun L, Shen H. Transcriptomic and Proteomic Analyses of Celery Cytoplasmic Male Sterile Line and Its Maintainer Line. Int J Mol Sci 2023; 24:ijms24044194. [PMID: 36835607 PMCID: PMC9967367 DOI: 10.3390/ijms24044194] [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: 10/02/2022] [Revised: 12/22/2022] [Accepted: 12/27/2022] [Indexed: 02/22/2023] Open
Abstract
Male sterility is a common phenomenon in the plant kingdom and based on the organelles harboring the male-sterility genes, it can be classified into the genic male sterility (GMS) and the cytoplasmic male sterility (CMS). In every generation, CMS can generate 100% male-sterile population, which is very important for the breeders to take advantage of the heterosis and for the seed producers to guarantee the seed purity. Celery is a cross-pollinated plant with the compound umbel type of inflorescence which carries hundreds of small flowers. These characteristics make CMS the only option to produce the commercial hybrid celery seeds. In this study, transcriptomic and proteomic analyses were performed to identify genes and proteins that are associated with celery CMS. A total of 1255 differentially expressed genes (DEGs) and 89 differentially expressed proteins (DEPs) were identified between the CMS and its maintainer line, then 25 genes were found to differentially expressed at both the transcript and protein levels. Ten DEGs involved in the fleece layer and outer pollen wall development were identified by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, most of which were down-regulated in the sterile line W99A. These DEGs and DEPs were mainly enriched in the pathways of "phenylpropanoid/sporopollenin synthesis/metabolism", "energy metabolism", "redox enzyme activity" and "redox processes". Results obtained in this study laid a foundation for the future investigation of mechanisms of pollen development as well as the reasons for the CMS in celery.
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Affiliation(s)
- Haoran Wang
- Beijing Key Laboratory of Growth and Developmental Regulation for Protected Vegetable Crops, China Agricultural University, Beijing 100193, China
- Department of Vegetable Science, College of Horticulture, China Agricultural University, No. 2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China
| | - Qing Cheng
- Beijing Key Laboratory of Growth and Developmental Regulation for Protected Vegetable Crops, China Agricultural University, Beijing 100193, China
- Department of Vegetable Science, College of Horticulture, China Agricultural University, No. 2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China
| | - Ziqi Zhai
- Beijing Key Laboratory of Growth and Developmental Regulation for Protected Vegetable Crops, China Agricultural University, Beijing 100193, China
- Department of Vegetable Science, College of Horticulture, China Agricultural University, No. 2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China
| | - Xiangyun Cui
- Beijing Key Laboratory of Growth and Developmental Regulation for Protected Vegetable Crops, China Agricultural University, Beijing 100193, China
- Department of Vegetable Science, College of Horticulture, China Agricultural University, No. 2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China
| | - Mingxuan Li
- Beijing Key Laboratory of Growth and Developmental Regulation for Protected Vegetable Crops, China Agricultural University, Beijing 100193, China
- Department of Vegetable Science, College of Horticulture, China Agricultural University, No. 2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China
| | - Ruiquan Ye
- Beijing Key Laboratory of Growth and Developmental Regulation for Protected Vegetable Crops, China Agricultural University, Beijing 100193, China
- Department of Vegetable Science, College of Horticulture, China Agricultural University, No. 2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China
| | - Liang Sun
- Beijing Key Laboratory of Growth and Developmental Regulation for Protected Vegetable Crops, China Agricultural University, Beijing 100193, China
- Department of Vegetable Science, College of Horticulture, China Agricultural University, No. 2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China
- Correspondence: (L.S.); (H.S.); Tel.: +86-10-6273-1014 (L.S.); +86-10-6273-2831 (H.S.)
| | - Huolin Shen
- Beijing Key Laboratory of Growth and Developmental Regulation for Protected Vegetable Crops, China Agricultural University, Beijing 100193, China
- Department of Vegetable Science, College of Horticulture, China Agricultural University, No. 2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China
- Correspondence: (L.S.); (H.S.); Tel.: +86-10-6273-1014 (L.S.); +86-10-6273-2831 (H.S.)
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16
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Identification of Alternative Splicing in Proteomes of Human Melanoma Cell Lines without RNA Sequencing Data. Int J Mol Sci 2023; 24:ijms24032466. [PMID: 36768787 PMCID: PMC9916885 DOI: 10.3390/ijms24032466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 01/06/2023] [Accepted: 01/13/2023] [Indexed: 01/31/2023] Open
Abstract
Alternative splicing is one of the main regulation pathways in living cells beyond simple changes in the level of protein expression. Most of the approaches proposed in proteomics for the identification of specific splicing isoforms require a preliminary deep transcriptomic analysis of the sample under study, which is not always available, especially in the case of the re-analysis of previously acquired data. Herein, we developed new algorithms for the identification and validation of protein splice isoforms in proteomic data in the absence of RNA sequencing of the samples under study. The bioinformatic approaches were tested on the results of proteome analysis of human melanoma cell lines, obtained earlier by high-resolution liquid chromatography and mass spectrometry (LC-MS). A search for alternative splicing events for each of the cell lines studied was performed against the database generated from all known transcripts (RefSeq) and the one composed of peptide sequences, which included all biologically possible combinations of exons. The identifications were filtered using the prediction of both retention times and relative intensities of fragment ions in the corresponding mass spectra. The fragmentation mass spectra corresponding to the discovered alternative splicing events were additionally examined for artifacts. Selected splicing events were further validated at the mRNA level by quantitative PCR.
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17
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Sun B, Kekenes-Huskey PM. Myofilament-associated proteins with intrinsic disorder (MAPIDs) and their resolution by computational modeling. Q Rev Biophys 2023; 56:e2. [PMID: 36628457 PMCID: PMC11070111 DOI: 10.1017/s003358352300001x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
The cardiac sarcomere is a cellular structure in the heart that enables muscle cells to contract. Dozens of proteins belong to the cardiac sarcomere, which work in tandem to generate force and adapt to demands on cardiac output. Intriguingly, the majority of these proteins have significant intrinsic disorder that contributes to their functions, yet the biophysics of these intrinsically disordered regions (IDRs) have been characterized in limited detail. In this review, we first enumerate these myofilament-associated proteins with intrinsic disorder (MAPIDs) and recent biophysical studies to characterize their IDRs. We secondly summarize the biophysics governing IDR properties and the state-of-the-art in computational tools toward MAPID identification and characterization of their conformation ensembles. We conclude with an overview of future computational approaches toward broadening the understanding of intrinsic disorder in the cardiac sarcomere.
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Affiliation(s)
- Bin Sun
- Research Center for Pharmacoinformatics (The State-Province Key Laboratories of Biomedicine-Pharmaceutics of China), Department of Medicinal Chemistry and Natural Medicine Chemistry, College of Pharmacy, Harbin Medical University, Harbin 150081, China
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18
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Holguin-Cruz JA, Foster LJ, Gsponer J. Where protein structure and cell diversity meet. Trends Cell Biol 2022; 32:996-1007. [PMID: 35537902 DOI: 10.1016/j.tcb.2022.04.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 04/08/2022] [Accepted: 04/12/2022] [Indexed: 01/21/2023]
Abstract
Protein-protein interaction networks - interactomes - are charted with the hope to understand how phenotypes emerge and how they are altered in disease states. Early efforts to map interactomes have focused on the assembly of context agnostic, reference networks. However, recent studies have mapped interactomes across different cell lines and tissues, finding highly variable interactomes due to the rewiring of protein-protein interactions in different contexts. Increasing evidence points to significant links between protein structure and interactome diversity seen across cell types and tissues. We discuss how recent findings support the key role of alternative splicing and phosphorylation, two well-established regulators of protein structural and functional diversity, in defining cell type- and tissue-specific interactomes. Moreover, we show that intrinsically disordered protein regions are most favorably equipped to support interactome rewiring by acting as hubs of protein structure and function regulation.
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Affiliation(s)
- Jorge A Holguin-Cruz
- Michael Smith Laboratories, Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, Canada
| | - Leonard J Foster
- Michael Smith Laboratories, Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, Canada
| | - Jörg Gsponer
- Michael Smith Laboratories, Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, Canada.
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19
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Shaw TI, Zhao B, Li Y, Wang H, Wang L, Manley B, Stewart PA, Karolak A. Multi-omics approach to identifying isoform variants as therapeutic targets in cancer patients. Front Oncol 2022; 12:1051487. [PMID: 36505834 PMCID: PMC9730332 DOI: 10.3389/fonc.2022.1051487] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 11/07/2022] [Indexed: 11/25/2022] Open
Abstract
Cancer-specific alternatively spliced events (ASE) play a role in cancer pathogenesis and can be targeted by immunotherapy, oligonucleotide therapy, and small molecule inhibition. However, identifying actionable ASE targets remains challenging due to the uncertainty of its protein product, structure impact, and proteoform (protein isoform) function. Here we argue that an integrated multi-omics profiling strategy can overcome these challenges, allowing us to mine this untapped source of targets for therapeutic development. In this review, we will provide an overview of current multi-omics strategies in characterizing ASEs by utilizing the transcriptome, proteome, and state-of-art algorithms for protein structure prediction. We will discuss limitations and knowledge gaps associated with each technology and informatics analytics. Finally, we will discuss future directions that will enable the full integration of multi-omics data for ASE target discovery.
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Affiliation(s)
- Timothy I. Shaw
- Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States,*Correspondence: Timothy I. Shaw,
| | - Bi Zhao
- Department of Machine Learning, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States
| | - Yuxin Li
- Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - Hong Wang
- Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - Liang Wang
- Department of Tumor Biology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States
| | - Brandon Manley
- Department of Genitourinary Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States
| | - Paul A. Stewart
- Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States
| | - Aleksandra Karolak
- Department of Machine Learning, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States
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20
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Han Y, Wennersten SA, Wright JM, Ludwig RW, Lau E, Lam MPY. Proteogenomics reveals sex-biased aging genes and coordinated splicing in cardiac aging. Am J Physiol Heart Circ Physiol 2022; 323:H538-H558. [PMID: 35930447 PMCID: PMC9448281 DOI: 10.1152/ajpheart.00244.2022] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 07/20/2022] [Accepted: 07/31/2022] [Indexed: 01/24/2023]
Abstract
The risks of heart diseases are significantly modulated by age and sex, but how these factors influence baseline cardiac gene expression remains incompletely understood. Here, we used RNA sequencing and mass spectrometry to compare gene expression in female and male young adult (4 mo) and early aging (20 mo) mouse hearts, identifying thousands of age- and sex-dependent gene expression signatures. Sexually dimorphic cardiac genes are broadly distributed, functioning in mitochondrial metabolism, translation, and other processes. In parallel, we found over 800 genes with differential aging response between male and female, including genes in cAMP and PKA signaling. Analysis of the sex-adjusted aging cardiac transcriptome revealed a widespread remodeling of exon usage patterns that is largely independent from differential gene expression, concomitant with upstream changes in RNA-binding protein and splice factor transcripts. To evaluate the impact of the splicing events on cardiac proteoform composition, we applied an RNA-guided proteomics computational pipeline to analyze the mass spectrometry data and detected hundreds of putative splice variant proteins that have the potential to rewire the cardiac proteome. Taken together, the results here suggest that cardiac aging is associated with 1) widespread sex-biased aging genes and 2) a rewiring of RNA splicing programs, including sex- and age-dependent changes in exon usages and splice patterns that have the potential to influence cardiac protein structure and function. These changes contribute to the emerging evidence for considerable sexual dimorphism in the cardiac aging process that should be considered in the search for disease mechanisms.NEW & NOTEWORTHY Han et al. used proteogenomics to compare male and female mouse hearts at 4 and 20 mo. Sex-biased cardiac genes function in mitochondrial metabolism, translation, autophagy, and other processes. Hundreds of cardiac genes show sex-by-age interactions, that is, sex-biased aging genes. Cardiac aging is accompanied with a remodeling of exon usage in functionally coordinated genes, concomitant with differential expression of RNA-binding proteins and splice factors. These features represent an underinvestigated aspect of cardiac aging that may be relevant to the search for disease mechanisms.
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Grants
- R21-HL150456 HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R00-HL144829 HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R00 HL127302 NHLBI NIH HHS
- R03-OD032666 HHS | NIH | NIH Office of the Director (OD)
- R01 HL141278 NHLBI NIH HHS
- F32 HL149191 NHLBI NIH HHS
- F32-HL149191 HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R00-HL127302 HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- R21 HL150456 NHLBI NIH HHS
- R03 OD032666 NIH HHS
- R00 HL144829 NHLBI NIH HHS
- R01-HL141278 HHS | NIH | National Heart, Lung, and Blood Institute (NHLBI)
- University of Colorado
- University of Colorado School of Medicine, Anschutz Medical Campus
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Affiliation(s)
- Yu Han
- Department of Medicine, Anschutz Medical Campus, University of Colorado School of Medicine, Aurora, Colorado
| | - Sara A Wennersten
- Department of Medicine, Anschutz Medical Campus, University of Colorado School of Medicine, Aurora, Colorado
| | - Julianna M Wright
- Department of Medicine, Anschutz Medical Campus, University of Colorado School of Medicine, Aurora, Colorado
| | - R W Ludwig
- Department of Medicine, Anschutz Medical Campus, University of Colorado School of Medicine, Aurora, Colorado
| | | | - Maggie P Y Lam
- Department of Medicine, Anschutz Medical Campus, University of Colorado School of Medicine, Aurora, Colorado
- Department of Biochemistry and Molecular Genetics, Anschutz Medical Campus, University of Colorado School of Medicine, Aurora, Colorado
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21
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Velaga R, Koo KM, Mainwaring PN. Harnessing gene fusion-derived neoantigens for 'cold' breast and prostate tumor immunotherapy. Immunotherapy 2022; 14:1165-1179. [PMID: 36043380 DOI: 10.2217/imt-2022-0081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Breast and prostate cancers are generally considered immunologically 'cold' tumors due to multiple mechanisms rendering them unresponsive to immune checkpoint blockade therapies. With little success in garnering positive outcomes in modern immunotherapeutic clinical trials, it is prudent to re-examine the role of immunogenic neoantigens in these cold tumors. Gene fusions are driver mutations in hormone-driven cancers that can result in alternative mutation-specific neoantigens to promote immunotherapy sensitivity. This review focuses on 1) gene fusion formation mechanisms in neoantigen generation; 2) gene fusion neoantigens in cancer immunotherapeutic strategies and associated clinical trials; and 3) challenges and opportunities in computational and liquid biopsy technologies. This review is anticipated to initiate further research into gene fusion neoantigens of cold tumors for further experimental validation.
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Affiliation(s)
- Ravi Velaga
- Breast Surgery, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan
| | - Kevin M Koo
- XING Technologies Pty Ltd, Brisbane, QLD 4073, Australia.,The University of Queensland Centre for Clinical Research (UQCCR), Brisbane, QLD 4029, Australia
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22
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Proteotranscriptomics - A facilitator in omics research. Comput Struct Biotechnol J 2022; 20:3667-3675. [PMID: 35891789 PMCID: PMC9293588 DOI: 10.1016/j.csbj.2022.07.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 07/04/2022] [Accepted: 07/04/2022] [Indexed: 11/26/2022] Open
Abstract
Applications in omics research, such as comparative transcriptomics and proteomics, require the knowledge of the species-specific gene sequence and benefit from a comprehensive high-quality annotation of the coding genes to achieve high coverage. While protein-coding genes can in simple cases be detected by scanning the genome for open reading frames, in more complex genomes exonic sequences are separated by introns. Despite advances in sequencing technologies that allow for ever-growing numbers of genomes, the quality of many of the provided genome assemblies do not reach reference quality. These non-contiguous assemblies with gaps and the necessity to predict splice sites limit accurate gene annotation from solely genomic data. In contrast, the transcriptome only contains transcribed gene regions, is devoid of introns and thus provides the optimal basis for the identification of open reading frames. The additional integration of proteomics data to validate predicted protein-coding genes further enriches for accurate gene models. This review outlines the principles of the proteotranscriptomics approach, discusses common challenges and suggests methods for improvement.
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23
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Ferrández-Peral L, Zhan X, Alvarez-Estape M, Chiva C, Esteller-Cucala P, García-Pérez R, Julià E, Lizano E, Fornas Ò, Sabidó E, Li Q, Marquès-Bonet T, Juan D, Zhang G. Transcriptome innovations in primates revealed by single-molecule long-read sequencing. Genome Res 2022; 32:gr.276395.121. [PMID: 35840341 PMCID: PMC9435740 DOI: 10.1101/gr.276395.121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 07/12/2022] [Indexed: 11/24/2022]
Abstract
Transcriptomic diversity greatly contributes to the fundamentals of disease, lineage-specific biology, and environmental adaptation. However, much of the actual isoform repertoire contributing to shaping primate evolution remains unknown. Here, we combined deep long- and short-read sequencing complemented with mass spectrometry proteomics in a panel of lymphoblastoid cell lines (LCLs) from human, three other great apes, and rhesus macaque, producing the largest full-length isoform catalog in primates to date. Around half of the captured isoforms are not annotated in their reference genomes, significantly expanding the gene models in primates. Furthermore, our comparative analyses unveil hundreds of transcriptomic innovations and isoform usage changes related to immune function and immunological disorders. The confluence of these evolutionary innovations with signals of positive selection and their limited impact in the proteome points to changes in alternative splicing in genes involved in immune response as an important target of recent regulatory divergence in primates.
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Affiliation(s)
| | | | | | - Cristina Chiva
- Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
| | | | | | - Eva Julià
- Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
| | - Esther Lizano
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
| | - Òscar Fornas
- Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
| | - Eduard Sabidó
- Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
| | - Qiye Li
- BGI-Shenzhen, Shenzhen 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tomàs Marquès-Bonet
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, 08003 Barcelona, Spain
- Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain
- CNAG-CRG, Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain
| | - David Juan
- Institute of Evolutionary Biology (UPF-CSIC), PRBB, 08003 Barcelona, Spain
| | - Guojie Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, DK-2100 Copenhagen 2200, Denmark
- Evolutionary and Organismal Biology Research Center, School of Medicine, Zhejiang University, Hangzhou 310058, China
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24
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Tay AP, Hamey JJ, Martyn GE, Wilson LOW, Wilkins MR. Identification of Protein Isoforms Using Reference Databases Built from Long and Short Read RNA-Sequencing. J Proteome Res 2022; 21:1628-1639. [PMID: 35612954 DOI: 10.1021/acs.jproteome.1c00968] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Alternative splicing can lead to distinct protein isoforms. These can have different functions in specific cells and tissues or in different developmental stages. In this study, we explored whether transcripts assembled from long read, nanopore-based, direct RNA-sequencing (RNA-seq) could improve the identification of protein isoforms in human K562 cells. By comparing with Illumina-based short read RNA-seq, we showed that a large proportion of Ensembl transcripts (5949/14,326) and genes expressing alternatively spliced transcripts (486/2981) identified with long direct reads were missed by short paired-end reads. By co-analyzing proteomic and transcriptomic data, we also showed that some peptides (826/35,976), proteins (262/3215), and protein isoforms arising from distinct transcript variants (574/1212) identified with isoform-specific peptides via custom long-read-based databases were missed in Illumina-derived databases. Finally, we generated unequivocal peptide evidence for a set of protein isoforms and showed that long read, direct RNA-seq allows the discovery of novel protein isoforms not already in reference databases or custom databases built from short read RNA-seq data. Our analysis highlights the benefits of long read RNA-seq data in the generation of reference databases to increase tandem mass spectrometry (MS/MS) identification of protein isoforms.
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Affiliation(s)
- Aidan P Tay
- School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, New South Wales 2052, Australia.,Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Sydney, New South Wales 2113, Australia.,Applied Biosciences, Macquarie University, Sydney, New South Wales 2109, Australia
| | - Joshua J Hamey
- School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Gabriella E Martyn
- School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Laurence O W Wilson
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Sydney, New South Wales 2113, Australia.,Applied Biosciences, Macquarie University, Sydney, New South Wales 2109, Australia
| | - Marc R Wilkins
- School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, New South Wales 2052, Australia
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25
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Abnormal global alternative RNA splicing in COVID-19 patients. PLoS Genet 2022; 18:e1010137. [PMID: 35421082 PMCID: PMC9089920 DOI: 10.1371/journal.pgen.1010137] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Revised: 05/10/2022] [Accepted: 03/08/2022] [Indexed: 12/25/2022] Open
Abstract
Viral infections can alter host transcriptomes by manipulating host splicing machinery. Despite intensive transcriptomic studies on SARS-CoV-2, a systematic analysis of alternative splicing (AS) in severe COVID-19 patients remains largely elusive. Here we integrated proteomic and transcriptomic sequencing data to study AS changes in COVID-19 patients. We discovered that RNA splicing is among the major down-regulated proteomic signatures in COVID-19 patients. The transcriptome analysis showed that SARS-CoV-2 infection induces widespread dysregulation of transcript usage and expression, affecting blood coagulation, neutrophil activation, and cytokine production. Notably, CD74 and LRRFIP1 had increased skipping of an exon in COVID-19 patients that disrupts a functional domain, which correlated with reduced antiviral immunity. Furthermore, the dysregulation of transcripts was strongly correlated with clinical severity of COVID-19, and splice-variants may contribute to unexpected therapeutic activity. In summary, our data highlight that a better understanding of the AS landscape may aid in COVID-19 diagnosis and therapy. Despite intensive studies on the transcriptional signatures of COVID-19 patients, how SARS-CoV-2 affects AS landscape and the contribution of AS to the pathogenesis of COVID-19 remain largely elusive. By profiling the lung transcriptome and lung proteome of nine patients who died of COVID-19 during the first wave of the pandemic in Wuhan, China, we obtained molecular insights into the AS of cellular transcripts upon SARS-CoV-2 infection. Interestingly, SARS-CoV-2 proteins directly engage host spliceosome to dysregulate essential steps of mature mRNA production and result in widespread dysregulation of cellular function. Taken together, our findings shed light on COVID-19 molecular mechanism and offer potential therapeutic targets for severe COVID-19 disease.
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26
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Miller RM, Jordan BT, Mehlferber MM, Jeffery ED, Chatzipantsiou C, Kaur S, Millikin RJ, Dai Y, Tiberi S, Castaldi PJ, Shortreed MR, Luckey CJ, Conesa A, Smith LM, Deslattes Mays A, Sheynkman GM. Enhanced protein isoform characterization through long-read proteogenomics. Genome Biol 2022; 23:69. [PMID: 35241129 PMCID: PMC8892804 DOI: 10.1186/s13059-022-02624-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 02/02/2022] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND The detection of physiologically relevant protein isoforms encoded by the human genome is critical to biomedicine. Mass spectrometry (MS)-based proteomics is the preeminent method for protein detection, but isoform-resolved proteomic analysis relies on accurate reference databases that match the sample; neither a subset nor a superset database is ideal. Long-read RNA sequencing (e.g., PacBio or Oxford Nanopore) provides full-length transcripts which can be used to predict full-length protein isoforms. RESULTS We describe here a long-read proteogenomics approach for integrating sample-matched long-read RNA-seq and MS-based proteomics data to enhance isoform characterization. We introduce a classification scheme for protein isoforms, discover novel protein isoforms, and present the first protein inference algorithm for the direct incorporation of long-read transcriptome data to enable detection of protein isoforms previously intractable to MS-based detection. We have released an open-source Nextflow pipeline that integrates long-read sequencing in a proteomic workflow for isoform-resolved analysis. CONCLUSIONS Our work suggests that the incorporation of long-read sequencing and proteomic data can facilitate improved characterization of human protein isoform diversity. Our first-generation pipeline provides a strong foundation for future development of long-read proteogenomics and its adoption for both basic and translational research.
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Affiliation(s)
- Rachel M. Miller
- grid.14003.360000 0001 2167 3675Department of Chemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Ben T. Jordan
- grid.27755.320000 0000 9136 933XDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA USA
| | - Madison M. Mehlferber
- grid.27755.320000 0000 9136 933XDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA USA ,grid.27755.320000 0000 9136 933XDepartment of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA USA
| | - Erin D. Jeffery
- grid.27755.320000 0000 9136 933XDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA USA
| | | | - Simi Kaur
- grid.14003.360000 0001 2167 3675Department of Chemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Robert J. Millikin
- grid.14003.360000 0001 2167 3675Department of Chemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Yunxiang Dai
- grid.14003.360000 0001 2167 3675Department of Chemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Simone Tiberi
- grid.7400.30000 0004 1937 0650Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland ,grid.7400.30000 0004 1937 0650Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
| | - Peter J. Castaldi
- grid.62560.370000 0004 0378 8294Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA USA ,grid.62560.370000 0004 0378 8294Division of General Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA USA
| | - Michael R. Shortreed
- grid.14003.360000 0001 2167 3675Department of Chemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Chance John Luckey
- grid.27755.320000 0000 9136 933XDepartment of Pathology, University of Virginia, Charlottesville, VA USA
| | - Ana Conesa
- grid.4711.30000 0001 2183 4846Institute for Integrative Systems Biology, Spanish National Research Council (CSIC), Paterna, Spain ,grid.15276.370000 0004 1936 8091Microbiology and Cell Science Department, Institute for Food and Agricultural Sciences, University of Florida, Gainesville, FL USA
| | - Lloyd M. Smith
- grid.14003.360000 0001 2167 3675Department of Chemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Anne Deslattes Mays
- grid.420089.70000 0000 9635 8082 Office of Data Science and Sharing, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Rockville, MD USA
| | - Gloria M. Sheynkman
- grid.27755.320000 0000 9136 933XDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA USA ,grid.27755.320000 0000 9136 933XCenter for Public Health Genomics, University of Virginia, Charlottesville, VA USA ,grid.27755.320000 0000 9136 933XUVA Cancer Center, University of Virginia, Charlottesville, VA USA
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27
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Gonzalez-Teran B, Pittman M, Felix F, Thomas R, Richmond-Buccola D, Hüttenhain R, Choudhary K, Moroni E, Costa MW, Huang Y, Padmanabhan A, Alexanian M, Lee CY, Maven BEJ, Samse-Knapp K, Morton SU, McGregor M, Gifford CA, Seidman JG, Seidman CE, Gelb BD, Colombo G, Conklin BR, Black BL, Bruneau BG, Krogan NJ, Pollard KS, Srivastava D. Transcription factor protein interactomes reveal genetic determinants in heart disease. Cell 2022; 185:794-814.e30. [PMID: 35182466 PMCID: PMC8923057 DOI: 10.1016/j.cell.2022.01.021] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 08/20/2021] [Accepted: 01/25/2022] [Indexed: 02/08/2023]
Abstract
Congenital heart disease (CHD) is present in 1% of live births, yet identification of causal mutations remains challenging. We hypothesized that genetic determinants for CHDs may lie in the protein interactomes of transcription factors whose mutations cause CHDs. Defining the interactomes of two transcription factors haplo-insufficient in CHD, GATA4 and TBX5, within human cardiac progenitors, and integrating the results with nearly 9,000 exomes from proband-parent trios revealed an enrichment of de novo missense variants associated with CHD within the interactomes. Scoring variants of interactome members based on residue, gene, and proband features identified likely CHD-causing genes, including the epigenetic reader GLYR1. GLYR1 and GATA4 widely co-occupied and co-activated cardiac developmental genes, and the identified GLYR1 missense variant disrupted interaction with GATA4, impairing in vitro and in vivo function in mice. This integrative proteomic and genetic approach provides a framework for prioritizing and interrogating genetic variants in heart disease.
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Affiliation(s)
- Barbara Gonzalez-Teran
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA
| | - Maureen Pittman
- Gladstone Institutes, San Francisco, CA, USA; Department of Epidemiology & Biostatistics, Institute for Computational Health Sciences, and Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA
| | - Franco Felix
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA
| | | | - Desmond Richmond-Buccola
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA
| | - Ruth Hüttenhain
- Gladstone Institutes, San Francisco, CA, USA; Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA
| | | | | | - Mauro W Costa
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA
| | - Yu Huang
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA
| | - Arun Padmanabhan
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA; Division of Cardiology, Department of Medicine, University of California, San Francisco, CA, USA
| | - Michael Alexanian
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA
| | - Clara Youngna Lee
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA
| | - Bonnie E J Maven
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA; Developmental and Stem Cell Biology Graduate Program, University of California San Francisco, San Francisco, CA, USA
| | - Kaitlen Samse-Knapp
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA
| | - Sarah U Morton
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Michael McGregor
- Gladstone Institutes, San Francisco, CA, USA; Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA
| | - Casey A Gifford
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA
| | - J G Seidman
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Christine E Seidman
- Department of Genetics, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA; Cardiovascular Division, Brigham and Women's Hospital, Boston, MA, USA
| | - Bruce D Gelb
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Bruce R Conklin
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA
| | - Brian L Black
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Benoit G Bruneau
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA; Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA; Division of Cardiology, Department of Pediatrics, UCSF School of Medicine, San Francisco, CA, USA
| | - Nevan J Krogan
- Gladstone Institutes, San Francisco, CA, USA; Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA; Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA
| | - Katherine S Pollard
- Gladstone Institutes, San Francisco, CA, USA; Chan Zuckerberg Biohub, San Francisco, CA, USA; Department of Epidemiology & Biostatistics, Institute for Computational Health Sciences, and Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA.
| | - Deepak Srivastava
- Gladstone Institutes, San Francisco, CA, USA; Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA; Division of Cardiology, Department of Pediatrics, UCSF School of Medicine, San Francisco, CA, USA; Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA.
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28
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Korsching E, Matschke J, Hotfilder M. Splice variants denote differences between a cancer stem cell side population of EWSR1‑ERG‑based Ewing sarcoma cells, its main population and EWSR1‑FLI‑based cells. Int J Mol Med 2022; 49:39. [PMID: 35088879 PMCID: PMC8815407 DOI: 10.3892/ijmm.2022.5094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 12/17/2021] [Indexed: 11/06/2022] Open
Abstract
Ewing sarcoma is a challenging cancer entity, which, besides the characteristic presence of a fusion gene, is driven by multiple alternative splicing events. So far, splice variants in Ewing sarcoma cells were mainly analyzed for EWSR1‑FLI1. The present study provided a comprehensive alternative splicing study on CADO‑ES1, an Ewing model cell line for an EWSR1‑ERG fusion gene. Based on a well‑-characterized RNA‑sequencing dataset with extensive control mechanisms across all levels of analysis, the differential spliced genes in Ewing cancer stem cells were ATP13A3 and EPB41, while the main population was defined by ACADVL, NOP58 and TSPAN3. All alternatively spliced genes were further characterized by their Gene Ontology (GO) terms and by their membership in known protein complexes. These results confirm and extend previous studies towards a systematic whole‑transcriptome analysis. A highlight is the striking segregation of GO terms associated with five basic splice events. This mechanistic insight, together with a coherent integration of all observations with prior knowledge, indicates that EWSR1‑ERG is truly a close twin to EWSR1‑FLI1, but still exhibits certain individuality. Thus, the present study provided a measure of variability in Ewing sarcoma, whose understanding is essential both for clinical procedures and basic mechanistic insight.
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Affiliation(s)
- Eberhard Korsching
- Institute of Bioinformatics, Faculty of Medicine, University of Münster, D‑48149 Münster, Germany
| | - Julian Matschke
- Institute of Bioinformatics, Faculty of Medicine, University of Münster, D‑48149 Münster, Germany
| | - Marc Hotfilder
- Department of Pediatric Hematology and Oncology, University Hospital Münster, D‑48149 Münster, Germany
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29
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Reixachs-Solé M, Eyras E. Uncovering the impacts of alternative splicing on the proteome with current omics techniques. WILEY INTERDISCIPLINARY REVIEWS. RNA 2022; 13:e1707. [PMID: 34979593 PMCID: PMC9542554 DOI: 10.1002/wrna.1707] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Revised: 11/27/2021] [Accepted: 11/29/2021] [Indexed: 12/15/2022]
Abstract
The high‐throughput sequencing of cellular RNAs has underscored a broad effect of isoform diversification through alternative splicing on the transcriptome. Moreover, the differential production of transcript isoforms from gene loci has been recognized as a critical mechanism in cell differentiation, organismal development, and disease. Yet, the extent of the impact of alternative splicing on protein production and cellular function remains a matter of debate. Multiple experimental and computational approaches have been developed in recent years to address this question. These studies have unveiled how molecular changes at different steps in the RNA processing pathway can lead to differences in protein production and have functional effects. New and emerging experimental technologies open exciting new opportunities to develop new methods to fully establish the connection between messenger RNA expression and protein production and to further investigate how RNA variation impacts the proteome and cell function. This article is categorized under:RNA Processing > Splicing Regulation/Alternative Splicing Translation > Regulation RNA Evolution and Genomics > Computational Analyses of RNA
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Affiliation(s)
- Marina Reixachs-Solé
- The John Curtin School of Medical Research, Australian National University, Canberra, Australian Capital Territory, Australia.,EMBL Australia Partner Laboratory Network and the Australian National University, Canberra, Australian Capital Territory, Australia
| | - Eduardo Eyras
- The John Curtin School of Medical Research, Australian National University, Canberra, Australian Capital Territory, Australia.,EMBL Australia Partner Laboratory Network and the Australian National University, Canberra, Australian Capital Territory, Australia.,Catalan Institution for Research and Advanced Studies, Barcelona, Spain.,Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
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30
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Wang X, Wong LM, McElvain ME, Martire S, Lee WH, Li CZ, Fisher FA, Maheshwari RL, Wu ML, Imun MC, Murad R, Warshaviak DT, Yin J, Kamb A, Xu H. A rational approach to assess off-target reactivity of a dual-signal integrator for T cell therapy. Toxicol Appl Pharmacol 2022; 437:115894. [DOI: 10.1016/j.taap.2022.115894] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 01/15/2022] [Accepted: 01/19/2022] [Indexed: 01/16/2023]
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31
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Mehlferber MM, Jeffery ED, Saquing J, Jordan BT, Sheynkman L, Murali M, Genet G, Acharya BR, Hirschi KK, Sheynkman GM. Characterization of protein isoform diversity in human umbilical vein endothelial cells via long-read proteogenomics. RNA Biol 2022; 19:1228-1243. [PMID: 36457147 PMCID: PMC9721438 DOI: 10.1080/15476286.2022.2141938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Abstract
Endothelial cells (ECs) comprise the lumenal lining of all blood vessels and are critical for the functioning of the cardiovascular system. Their phenotypes can be modulated by alternative splicing of RNA to produce distinct protein isoforms. To characterize the RNA and protein isoform landscape within ECs, we applied a long read proteogenomics approach to analyse human umbilical vein endothelial cells (HUVECs). Transcripts delineated from PacBio sequencing serve as the basis for a sample-specific protein database used for downstream mass-spectrometry (MS) analysis to infer protein isoform expression. We detected 53,863 transcript isoforms from 10,426 genes, with 22,195 of those transcripts being novel. Furthermore, the predominant isoform in HUVECs does not correspond with the accepted "reference isoform" 25% of the time, with vascular pathway-related genes among this group. We found 2,597 protein isoforms supported through unique peptides, with an additional 2,280 isoforms nominated upon incorporation of long-read transcript evidence. We characterized a novel alternative acceptor for endothelial-related gene CDH5, suggesting potential changes in its associated signalling pathways. Finally, we identified novel protein isoforms arising from a diversity of RNA splicing mechanisms supported by uniquely mapped novel peptides. Our results represent a high-resolution atlas of known and novel isoforms of potential relevance to endothelial phenotypes and function.[Figure: see text].
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Affiliation(s)
- Madison M. Mehlferber
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA,Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Erin D. Jeffery
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Jamie Saquing
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Ben T. Jordan
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Leon Sheynkman
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Mayank Murali
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA
| | - Gael Genet
- Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Bipul R. Acharya
- Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA, USA,Cardiovascular Research Center, University of Virginia, Charlottesville, VA, USA,Wellcome Centre for Cell-Matrix Research, Faculty of Biology, Medicine and Health, the University of Manchester, UK
| | - Karen K. Hirschi
- Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA, USA,Cardiovascular Research Center, University of Virginia, Charlottesville, VA, USA
| | - Gloria M. Sheynkman
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA,Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, Virginia, USA,Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA,UVA Comprehensive Cancer Center, University of Virginia, Charlottesville, Virginia, USA,CONTACT Gloria M. Sheynkman The Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
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32
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Han Y, Li LZ, Kastury NL, Thomas CT, Lam MPY, Lau E. Transcriptome features of striated muscle aging and predictability of protein level changes. Mol Omics 2021; 17:796-808. [PMID: 34328155 PMCID: PMC8511094 DOI: 10.1039/d1mo00178g] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
We performed total RNA sequencing and multi-omics analysis comparing skeletal muscle and cardiac muscle in young adult (4 months) vs. early aging (20 months) mice to examine the molecular mechanisms of striated muscle aging. We observed that aging cardiac and skeletal muscles both invoke transcriptomic changes in innate immune system and mitochondria pathways but diverge in extracellular matrix processes. On an individual gene level, we identified 611 age-associated signatures in skeletal and cardiac muscles, including a number of myokine and cardiokine encoding genes. Because RNA and protein levels correlate only partially, we reason that differentially expressed transcripts that accurately reflect their protein counterparts will be more valuable proxies for proteomic changes and by extension physiological states. We applied a computational data analysis workflow to estimate which transcriptomic changes are more likely relevant to protein-level regulation using large proteogenomics data sets. We estimate about 48% of the aging-associated transcripts predict protein levels well (r ≥ 0.5). In parallel, a comparison of the identified aging-regulated genes with public human transcriptomics data showed that only 35-45% of the identified genes show an age-dependent expression in corresponding human tissues. Thus, integrating both RNA-protein correlation and human conservation across data sources, we nominate 134 prioritized aging striated muscle signatures that are predicted to correlate strongly with protein levels and that show age-dependent expression in humans. The results here reveal new details into how aging reshapes gene expression in striated muscles at the transcript and protein levels.
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Affiliation(s)
- Yu Han
- Department of Medicine, Consortium for Fibrosis Research & Translation, University of Colorado School of Medicine, Aurora, CO 80045, USA.
| | - Lauren Z Li
- Department of Medicine, Consortium for Fibrosis Research & Translation, University of Colorado School of Medicine, Aurora, CO 80045, USA.
| | - Nikhitha L Kastury
- Department of Medicine, Consortium for Fibrosis Research & Translation, University of Colorado School of Medicine, Aurora, CO 80045, USA.
| | - Cody T Thomas
- Department of Medicine, Consortium for Fibrosis Research & Translation, University of Colorado School of Medicine, Aurora, CO 80045, USA.
| | - Maggie P Y Lam
- Department of Medicine, Consortium for Fibrosis Research & Translation, University of Colorado School of Medicine, Aurora, CO 80045, USA.
- Department of Biochemistry and Molecular Genetics, Consortium for Fibrosis Research & Translation, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Edward Lau
- Department of Medicine, Consortium for Fibrosis Research & Translation, University of Colorado School of Medicine, Aurora, CO 80045, USA.
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Wojtkiewicz M, Berg Luecke L, Castro C, Burkovetskaya M, Mesidor R, Gundry RL. Bottom-up proteomic analysis of human adult cardiac tissue and isolated cardiomyocytes. J Mol Cell Cardiol 2021; 162:20-31. [PMID: 34437879 PMCID: PMC9620472 DOI: 10.1016/j.yjmcc.2021.08.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 07/07/2021] [Accepted: 08/04/2021] [Indexed: 12/30/2022]
Abstract
The heart is composed of multiple cell types, each with a specific function. Cell-type-specific approaches are necessary for defining the intricate molecular mechanisms underlying cardiac development, homeostasis, and pathology. While single-cell RNA-seq studies are beginning to define the chamber-specific cellular composition of the heart, our views of the proteome are more limited because most proteomics studies have utilized homogenized human cardiac tissue. To promote future cell-type specific analyses of the human heart, we describe the first method for cardiomyocyte isolation from cryopreserved human cardiac tissue followed by flow cytometry for purity assessment. We also describe a facile method for preparing isolated cardiomyocytes and whole cardiac tissue homogenate for bottom-up proteomic analyses. Prior experience in dissociating cardiac tissue or proteomics is not required to execute these methods. We compare different sample preparation workflows and analysis methods to demonstrate how these can impact the depth of proteome coverage achieved. We expect this how-to guide will serve as a starting point for investigators interested in general and cell-type-specific views of the cardiac proteome.
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Affiliation(s)
- Melinda Wojtkiewicz
- CardiOmics Program, Center for Heart and Vascular Research, Division of Cardiovascular Medicine, Department of Cellular and Integrative Physiology, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Linda Berg Luecke
- CardiOmics Program, Center for Heart and Vascular Research, Division of Cardiovascular Medicine, Department of Cellular and Integrative Physiology, University of Nebraska Medical Center, Omaha, NE 68198, USA; Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Chase Castro
- CardiOmics Program, Center for Heart and Vascular Research, Division of Cardiovascular Medicine, Department of Cellular and Integrative Physiology, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Maria Burkovetskaya
- CardiOmics Program, Center for Heart and Vascular Research, Division of Cardiovascular Medicine, Department of Cellular and Integrative Physiology, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Roneldine Mesidor
- CardiOmics Program, Center for Heart and Vascular Research, Division of Cardiovascular Medicine, Department of Cellular and Integrative Physiology, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Rebekah L Gundry
- CardiOmics Program, Center for Heart and Vascular Research, Division of Cardiovascular Medicine, Department of Cellular and Integrative Physiology, University of Nebraska Medical Center, Omaha, NE 68198, USA.
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34
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Zhong Y, Yan W, Ruan J, Fang M, Lapidus RG, Du S, Fang S. A novel XBP1 variant is highly enriched in cancer tissues and is specifically required for cancer cell survival. Biochem Biophys Res Commun 2021; 562:69-75. [PMID: 34038755 PMCID: PMC8206033 DOI: 10.1016/j.bbrc.2021.05.038] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 05/12/2021] [Indexed: 01/08/2023]
Abstract
XBP1 is a basic leucine zipper (bZIP) transcription factor and a key mediator of the endoplasmic reticulum (ER) stress-activated unfolded protein response (UPR). XBP1-mediated transcription facilitates cell adaptation to ER stress and also promotes tumor progression, while suppressing anti-tumor immunity. Here we report a novel XBP1 variant, namely XBP1 variant 1 (XBP1v1, Xv1 for short), that is specifically required for survival of cancer cells. Xv1 contains a cryptic first exon that is conserved only in humans and great apes. Comparing to XBP1, Xv1 encodes a protein with a different N-terminal sequence containing 25 amino acids. Analysis of RNAseq database reveals that Xv1 is broadly expressed across cancer types but almost none in normal tissues. Elevated Xv1 expression is associated with poor survival of patients with several types of cancer. Knockdown of Xv1 induces death of multiple cancer cell lines but has little effect on non-cancerous cells in vitro. Moreover, knockdown of Xv1 also inhibits growth of a xenograft breast tumor in mice. Together, our results indicate that Xv1 is essential for survival of cancer cells.
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Affiliation(s)
- Yongwang Zhong
- Center for Biomedical Engineering and Technology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA; Department of Physiology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Wenjing Yan
- Center for Biomedical Engineering and Technology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA; Department of Physiology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Jingjing Ruan
- Center for Biomedical Engineering and Technology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA; Department of Pulmonary Medicine, Anhui Medical University First Affiliated Hospital, Hefei, Anhui, 230032, China
| | - Mike Fang
- Case Western Reserve University, Cleveland, OH, USA
| | - Rena G Lapidus
- Translational Laboratory Shared Service, UM Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Shaojun Du
- Department of Biochemistry and Molecular Biology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Shengyun Fang
- Center for Biomedical Engineering and Technology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA; Department of Physiology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA; Department of Biochemistry and Molecular Biology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA; Program in Oncology, UM Greenebaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
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35
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Importance of evaluating protein glycosylation in pluripotent stem cell-derived cardiomyocytes for research and clinical applications. Pflugers Arch 2021; 473:1041-1059. [PMID: 33830329 PMCID: PMC8245383 DOI: 10.1007/s00424-021-02554-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Revised: 03/01/2021] [Accepted: 03/06/2021] [Indexed: 01/21/2023]
Abstract
Proper protein glycosylation is critical to normal cardiomyocyte physiology. Aberrant glycosylation can alter protein localization, structure, drug interactions, and cellular function. The in vitro differentiation of human pluripotent stem cells into cardiomyocytes (hPSC-CM) has become increasingly important to the study of protein function and to the fields of cardiac disease modeling, drug testing, drug discovery, and regenerative medicine. Here, we offer our perspective on the importance of protein glycosylation in hPSC-CM. Protein glycosylation is dynamic in hPSC-CM, but the timing and extent of glycosylation are still poorly defined. We provide new data highlighting how observed changes in hPSC-CM glycosylation may be caused by underlying differences in the protein or transcript abundance of enzymes involved in building and trimming the glycan structures or glycoprotein gene products. We also provide evidence that alternative splicing results in altered sites of glycosylation within the protein sequence. Our findings suggest the need to precisely define protein glycosylation events that may have a critical impact on the function and maturation state of hPSC-CM. Finally, we provide an overview of analytical strategies available for studying protein glycosylation and identify opportunities for the development of new bioinformatic approaches to integrate diverse protein glycosylation data types. We predict that these tools will promote the accurate assessment of protein glycosylation in future studies of hPSC-CM that will ultimately be of significant experimental and clinical benefit.
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36
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Han Y, Wood SD, Wright JM, Dostal V, Lau E, Lam MPY. Computation-assisted targeted proteomics of alternative splicing protein isoforms in the human heart. J Mol Cell Cardiol 2021; 154:92-96. [PMID: 33549679 DOI: 10.1016/j.yjmcc.2021.01.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 01/17/2021] [Accepted: 01/19/2021] [Indexed: 02/06/2023]
Abstract
Alternative splicing is prevalent in the heart and implicated in many cardiovascular diseases, but not every alternative transcript is translated and detecting non-canonical isoforms at the protein level remains challenging. Here we show the use of a computation-assisted targeted proteomics workflow to detect protein alternative isoforms in the human heart. We build on a recent strategy to integrate deep RNA-seq and large-scale mass spectrometry data to identify candidate translated isoform peptides. A machine learning approach is then applied to predict their fragmentation patterns and design protein isoform-specific parallel reaction monitoring detection (PRM) assays. As proof-of-principle, we built PRM assays for 29 non-canonical isoform peptides and detected 22 peptides in a human heart lysate. The predictions-aided PRM assays closely mirrored synthetic peptide standards for non-canonical sequences. This approach may be useful for validating non-canonical protein identification and discovering functionally relevant isoforms in the heart.
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Affiliation(s)
- Yu Han
- Department of Medicine-Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America; Department of Consortium for Fibrosis Research & Translation, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America
| | - Silas D Wood
- Department of Medicine-Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America
| | - Julianna M Wright
- Department of Medicine-Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America
| | - Vishantie Dostal
- Department of Medicine-Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America; Department of Consortium for Fibrosis Research & Translation, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America
| | - Edward Lau
- Department of Medicine-Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America; Department of Consortium for Fibrosis Research & Translation, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America
| | - Maggie P Y Lam
- Department of Medicine-Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America; Department of Biochemistry & Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America; Department of Consortium for Fibrosis Research & Translation, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, United States of America.
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37
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Salovska B, Zhu H, Gandhi T, Frank M, Li W, Rosenberger G, Wu C, Germain PL, Zhou H, Hodny Z, Reiter L, Liu Y. Isoform-resolved correlation analysis between mRNA abundance regulation and protein level degradation. Mol Syst Biol 2021; 16:e9170. [PMID: 32175694 PMCID: PMC7073818 DOI: 10.15252/msb.20199170] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2019] [Revised: 02/06/2020] [Accepted: 02/12/2020] [Indexed: 12/15/2022] Open
Abstract
Profiling of biological relationships between different molecular layers dissects regulatory mechanisms that ultimately determine cellular function. To thoroughly assess the role of protein post‐translational turnover, we devised a strategy combining pulse stable isotope‐labeled amino acids in cells (pSILAC), data‐independent acquisition mass spectrometry (DIA‐MS), and a novel data analysis framework that resolves protein degradation rate on the level of mRNA alternative splicing isoforms and isoform groups. We demonstrated our approach by the genome‐wide correlation analysis between mRNA amounts and protein degradation across different strains of HeLa cells that harbor a high grade of gene dosage variation. The dataset revealed that specific biological processes, cellular organelles, spatial compartments of organelles, and individual protein isoforms of the same genes could have distinctive degradation rate. The protein degradation diversity thus dissects the corresponding buffering or concerting protein turnover control across cancer cell lines. The data further indicate that specific mRNA splicing events such as intron retention significantly impact the protein abundance levels. Our findings support the tight association between transcriptome variability and proteostasis and provide a methodological foundation for studying functional protein degradation.
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Affiliation(s)
- Barbora Salovska
- Yale Cancer Biology Institute, Yale University, West Haven, CT, USA.,Department of Genome Integrity, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czech Republic
| | - Hongwen Zhu
- Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
| | | | - Max Frank
- European Molecular Biology Laboratory, Heidelberg, Germany
| | - Wenxue Li
- Yale Cancer Biology Institute, Yale University, West Haven, CT, USA
| | | | - Chongde Wu
- Yale Cancer Biology Institute, Yale University, West Haven, CT, USA
| | - Pierre-Luc Germain
- Institute for Neuroscience, D-HEST, ETH Zurich, Zurich, Switzerland.,Statistical Bioinformatics Lab, DMLS, University of Zürich, Zurich, Switzerland
| | - Hu Zhou
- Department of Analytical Chemistry and CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
| | - Zdenek Hodny
- Department of Genome Integrity, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czech Republic
| | | | - Yansheng Liu
- Yale Cancer Biology Institute, Yale University, West Haven, CT, USA.,Department of Pharmacology, Yale University School of Medicine, New Haven, CT, USA
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38
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Dermit M, Peters-Clarke TM, Shishkova E, Meyer JG. Peptide Correlation Analysis (PeCorA) Reveals Differential Proteoform Regulation. J Proteome Res 2020; 20:1972-1980. [PMID: 33325715 DOI: 10.1021/acs.jproteome.0c00602] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Shotgun proteomics techniques infer the presence and quantity of proteins using peptide proxies produced by cleavage of the proteome with a protease. Most protein quantitation strategies assume that multiple peptides derived from a protein will behave quantitatively similar across treatment groups, but this assumption may be false due to (1) heterogeneous proteoforms and (2) technical artifacts. Here we describe a strategy called peptide correlation analysis (PeCorA) that detects quantitative disagreements between peptides mapped to the same protein. PeCorA fits linear models to assess whether a peptide's change across treatment groups differs from all other peptides assigned to the same protein. PeCorA revealed that ∼15% of proteins in a mouse microglia stress data set contain at least one discordant peptide. Inspection of the discordant peptides shows the utility of PeCorA for the direct and indirect detection of regulated post-translational modifications (PTMs) and also for the discovery of poorly quantified peptides. The exclusion of poorly quantified peptides before protein quantity summarization decreased false-positives in a benchmark data set. Finally, PeCorA suggests that the inactive isoform of prothrombin, a coagulation cascade protease, is more abundant in plasma from COVID-19 patients relative to non-COVID-19 controls. PeCorA is freely available as an R package that works with arbitrary tables of quantified peptides.
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Affiliation(s)
- Maria Dermit
- Centre for Cancer Cell and Molecular Biology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, United Kingdom
| | - Trenton M Peters-Clarke
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Evgenia Shishkova
- National Center for Quantitative Biology of Complex Systems, Madison, Wisconsin 53706, United States.,Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Jesse G Meyer
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States.,Department of Biochemistry, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, Wisconsin 53226, United States
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39
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Wen B, Zeng W, Liao Y, Shi Z, Savage SR, Jiang W, Zhang B. Deep Learning in Proteomics. Proteomics 2020; 20:e1900335. [PMID: 32939979 PMCID: PMC7757195 DOI: 10.1002/pmic.201900335] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 09/14/2020] [Indexed: 12/17/2022]
Abstract
Proteomics, the study of all the proteins in biological systems, is becoming a data-rich science. Protein sequences and structures are comprehensively catalogued in online databases. With recent advancements in tandem mass spectrometry (MS) technology, protein expression and post-translational modifications (PTMs) can be studied in a variety of biological systems at the global scale. Sophisticated computational algorithms are needed to translate the vast amount of data into novel biological insights. Deep learning automatically extracts data representations at high levels of abstraction from data, and it thrives in data-rich scientific research domains. Here, a comprehensive overview of deep learning applications in proteomics, including retention time prediction, MS/MS spectrum prediction, de novo peptide sequencing, PTM prediction, major histocompatibility complex-peptide binding prediction, and protein structure prediction, is provided. Limitations and the future directions of deep learning in proteomics are also discussed. This review will provide readers an overview of deep learning and how it can be used to analyze proteomics data.
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Affiliation(s)
- Bo Wen
- Lester and Sue Smith Breast CenterBaylor College of MedicineHoustonTX77030USA
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTX77030USA
| | - Wen‐Feng Zeng
- Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS)Chinese Academy of SciencesInstitute of Computing TechnologyBeijing100190China
| | - Yuxing Liao
- Lester and Sue Smith Breast CenterBaylor College of MedicineHoustonTX77030USA
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTX77030USA
| | - Zhiao Shi
- Lester and Sue Smith Breast CenterBaylor College of MedicineHoustonTX77030USA
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTX77030USA
| | - Sara R. Savage
- Lester and Sue Smith Breast CenterBaylor College of MedicineHoustonTX77030USA
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTX77030USA
| | - Wen Jiang
- Lester and Sue Smith Breast CenterBaylor College of MedicineHoustonTX77030USA
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTX77030USA
| | - Bing Zhang
- Lester and Sue Smith Breast CenterBaylor College of MedicineHoustonTX77030USA
- Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTX77030USA
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40
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Dostal V, Wood SD, Thomas CT, Han Y, Lau E, Lam MPY. Proteomic signatures of acute oxidative stress response to paraquat in the mouse heart. Sci Rep 2020; 10:18440. [PMID: 33116222 PMCID: PMC7595225 DOI: 10.1038/s41598-020-75505-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 10/15/2020] [Indexed: 01/11/2023] Open
Abstract
The heart is sensitive to oxidative damage but a global view on how the cardiac proteome responds to oxidative stressors has yet to fully emerge. Using quantitative tandem mass spectrometry, we assessed the effects of acute exposure of the oxidative stress inducer paraquat on protein expression in mouse hearts. We observed widespread protein expression changes in the paraquat-exposed heart especially in organelle-containing subcellular fractions. During cardiac response to acute oxidative stress, proteome changes are consistent with a rapid reduction of mitochondrial metabolism, coupled with activation of multiple antioxidant proteins, reduction of protein synthesis and remediation of proteostasis. In addition to differential expression, we saw evidence of spatial reorganizations of the cardiac proteome including the translocation of hexokinase 2 to more soluble fractions. Treatment with the antioxidants Tempol and MitoTEMPO reversed many proteomic signatures of paraquat but this reversal was incomplete. We also identified a number of proteins with unknown function in the heart to be triggered by paraquat, suggesting they may have functions in oxidative stress response. Surprisingly, protein expression changes in the heart correlate poorly with those in the lung, consistent with differential sensitivity or stress response in these two organs. The results and data set here could provide insights into oxidative stress responses in the heart and avail the search for new therapeutic targets.
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Affiliation(s)
- Vishantie Dostal
- Department of Medicine, Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.,Department of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.,Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.,Consortium for Fibrosis Research & Translation, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Silas D Wood
- Department of Medicine, Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.,Department of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.,Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.,Consortium for Fibrosis Research & Translation, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Cody T Thomas
- Department of Medicine, Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.,Department of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Yu Han
- Department of Medicine, Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.,Department of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.,Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.,Consortium for Fibrosis Research & Translation, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Edward Lau
- Department of Medicine, Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.,Department of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.,Consortium for Fibrosis Research & Translation, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Maggie P Y Lam
- Department of Medicine, Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA. .,Department of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA. .,Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA. .,Consortium for Fibrosis Research & Translation, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.
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41
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Han Y, Wright JM, Lau E, Lam MPY. Determining Alternative Protein Isoform Expression Using RNA Sequencing and Mass Spectrometry. STAR Protoc 2020; 1:100138. [PMID: 33377032 PMCID: PMC7757315 DOI: 10.1016/j.xpro.2020.100138] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Alternative splicing greatly expands the coding capacity of the human genome, but how many alternative transcripts are translated as proteins or carry functional importance remains unknown and awaits experimental verification. Here, we describe a protocol that combines transcriptomics (RNA-seq) and proteomics (mass spectrometry [MS]) analyses to identify alternative isoforms in proteomes. This workflow is applicable to custom-generated RNA-seq and MS data from matching samples, as well as the reanalysis of existing transcriptomics and proteomics datasets in public repositories. For complete details on the use and execution of this protocol, please refer to Lau et al. (2019).
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Affiliation(s)
- Yu Han
- Department of Medicine-Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.,Consortium for Fibrosis Research & Translation, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Julianna M Wright
- Department of Medicine-Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Edward Lau
- Department of Medicine-Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.,Consortium for Fibrosis Research & Translation, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Maggie Pui Yu Lam
- Department of Medicine-Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.,Biochemistry & Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.,Consortium for Fibrosis Research & Translation, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
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42
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Adhikari S, Nice EC, Deutsch EW, Lane L, Omenn GS, Pennington SR, Paik YK, Overall CM, Corrales FJ, Cristea IM, Van Eyk JE, Uhlén M, Lindskog C, Chan DW, Bairoch A, Waddington JC, Justice JL, LaBaer J, Rodriguez H, He F, Kostrzewa M, Ping P, Gundry RL, Stewart P, Srivastava S, Srivastava S, Nogueira FCS, Domont GB, Vandenbrouck Y, Lam MPY, Wennersten S, Vizcaino JA, Wilkins M, Schwenk JM, Lundberg E, Bandeira N, Marko-Varga G, Weintraub ST, Pineau C, Kusebauch U, Moritz RL, Ahn SB, Palmblad M, Snyder MP, Aebersold R, Baker MS. A high-stringency blueprint of the human proteome. Nat Commun 2020; 11:5301. [PMID: 33067450 PMCID: PMC7568584 DOI: 10.1038/s41467-020-19045-9] [Citation(s) in RCA: 127] [Impact Index Per Article: 31.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 09/25/2020] [Indexed: 02/07/2023] Open
Abstract
The Human Proteome Organization (HUPO) launched the Human Proteome Project (HPP) in 2010, creating an international framework for global collaboration, data sharing, quality assurance and enhancing accurate annotation of the genome-encoded proteome. During the subsequent decade, the HPP established collaborations, developed guidelines and metrics, and undertook reanalysis of previously deposited community data, continuously increasing the coverage of the human proteome. On the occasion of the HPP's tenth anniversary, we here report a 90.4% complete high-stringency human proteome blueprint. This knowledge is essential for discerning molecular processes in health and disease, as we demonstrate by highlighting potential roles the human proteome plays in our understanding, diagnosis and treatment of cancers, cardiovascular and infectious diseases.
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Affiliation(s)
- Subash Adhikari
- Faculty of Medicine, Health and Human Sciences, Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, 2109, Australia
| | - Edouard C Nice
- Faculty of Medicine, Health and Human Sciences, Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, 2109, Australia
- Faculty of Medicine, Nursing and Health Sciences, Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC, 3800, Australia
| | - Eric W Deutsch
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA, 98109, USA
| | - Lydie Lane
- Faculty of Medicine, SIB-Swiss Institute of Bioinformatics and Department of Microbiology and Molecular Medicine, University of Geneva, CMU, Michel-Servet 1, 1211, Geneva, Switzerland
| | - Gilbert S Omenn
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, 48109-2218, USA
| | - Stephen R Pennington
- UCD Conway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Dublin, Ireland
| | - Young-Ki Paik
- Yonsei Proteome Research Center, 50 Yonsei-ro, Sudaemoon-ku, Seoul, 120-749, South Korea
| | | | - Fernando J Corrales
- Functional Proteomics Laboratory, Centro Nacional de Biotecnología-CSIC, Proteored-ISCIII, 28049, Madrid, Spain
| | - Ileana M Cristea
- Department of Molecular Biology, Princeton University, Princeton, NJ, 08544, USA
| | - Jennifer E Van Eyk
- Cedars Sinai Medical Center, Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Los Angeles, CA, 90048, USA
| | - Mathias Uhlén
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 17121, Solna, Sweden
| | - Cecilia Lindskog
- Rudbeck Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, 75185, Uppsala, Sweden
| | - Daniel W Chan
- Department of Pathology and Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, 21224, USA
| | - Amos Bairoch
- Faculty of Medicine, SIB-Swiss Institute of Bioinformatics and Department of Microbiology and Molecular Medicine, University of Geneva, CMU, Michel-Servet 1, 1211, Geneva, Switzerland
| | - James C Waddington
- UCD Conway Institute of Biomolecular and Biomedical Research, School of Medicine, University College Dublin, Dublin, Ireland
| | - Joshua L Justice
- Department of Molecular Biology, Princeton University, Princeton, NJ, 08544, USA
| | - Joshua LaBaer
- Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Henry Rodriguez
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, NIH, Bethesda, MD, 20892, USA
| | - Fuchu He
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China
| | - Markus Kostrzewa
- Bruker Daltonik GmbH, Microbiology and Diagnostics, Fahrenheitstrasse, 428359, Bremen, Germany
| | - Peipei Ping
- Cardiac Proteomics and Signaling Laboratory, Department of Physiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Rebekah L Gundry
- CardiOmics Program, Center for Heart and Vascular Research, Division of Cardiovascular Medicine and Department of Cellular and Integrative Physiology, University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Peter Stewart
- Department of Chemical Pathology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
| | | | - Sudhir Srivastava
- Cancer Biomarkers Research Branch, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Suite 5E136, Rockville, MD, 20852, USA
| | - Fabio C S Nogueira
- Proteomics Unit and Laboratory of Proteomics, Institute of Chemistry, Federal University of Rio de Janeiro, Av Athos da Silveria Ramos, 149, 21941-909, Rio de Janeiro, RJ, Brazil
| | - Gilberto B Domont
- Proteomics Unit and Laboratory of Proteomics, Institute of Chemistry, Federal University of Rio de Janeiro, Av Athos da Silveria Ramos, 149, 21941-909, Rio de Janeiro, RJ, Brazil
| | - Yves Vandenbrouck
- University of Grenoble Alpes, Inserm, CEA, IRIG-BGE, U1038, 38000, Grenoble, France
| | - Maggie P Y Lam
- Departments of Medicine-Cardiology and Biochemistry and Molecular Genetics, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
- Consortium for Fibrosis Research and Translation, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Sara Wennersten
- Division of Cardiology, Department of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Juan Antonio Vizcaino
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Marc Wilkins
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Jochen M Schwenk
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 17121, Solna, Sweden
| | - Emma Lundberg
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 17121, Solna, Sweden
| | - Nuno Bandeira
- Department of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Drive, Mail Code 0404, La Jolla, CA, 92093-0404, USA
| | | | - Susan T Weintraub
- Department of Biochemistry and Structural Biology, University of Texas Health Science Center San Antonio, UT Health, 7703 Floyd Curl Drive, San Antonio, TX, 78229-3900, USA
| | - Charles Pineau
- University of Rennes, Inserm, EHESP, IREST, UMR_S 1085, F-35042, Rennes, France
| | - Ulrike Kusebauch
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA, 98109, USA
| | - Robert L Moritz
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA, 98109, USA
| | - Seong Beom Ahn
- Faculty of Medicine, Health and Human Sciences, Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, 2109, Australia
| | - Magnus Palmblad
- Leiden University Medical Center, Leiden, 2333, The Netherlands
| | - Michael P Snyder
- Department of Genetics, Stanford School of Medicine, Stanford, CA, 94305, USA
| | - Ruedi Aebersold
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA, 98109, USA
- Faculty of Science, University of Zurich, Zurich, Switzerland
| | - Mark S Baker
- Faculty of Medicine, Health and Human Sciences, Department of Biomedical Sciences, Macquarie University, North Ryde, NSW, 2109, Australia.
- Department of Genetics, Stanford School of Medicine, Stanford, CA, 94305, USA.
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Rodriguez JM, Pozo F, di Domenico T, Vazquez J, Tress ML. An analysis of tissue-specific alternative splicing at the protein level. PLoS Comput Biol 2020; 16:e1008287. [PMID: 33017396 PMCID: PMC7561204 DOI: 10.1371/journal.pcbi.1008287] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 10/15/2020] [Accepted: 08/25/2020] [Indexed: 01/09/2023] Open
Abstract
The role of alternative splicing is one of the great unanswered questions in cellular biology. There is strong evidence for alternative splicing at the transcript level, and transcriptomics experiments show that many splice events are tissue specific. It has been suggested that alternative splicing evolved in order to remodel tissue-specific protein-protein networks. Here we investigated the evidence for tissue-specific splicing among splice isoforms detected in a large-scale proteomics analysis. Although the data supporting alternative splicing is limited at the protein level, clear patterns emerged among the small numbers of alternative splice events that we could detect in the proteomics data. More than a third of these splice events were tissue-specific and most were ancient: over 95% of splice events that were tissue-specific in both proteomics and RNAseq analyses evolved prior to the ancestors of lobe-finned fish, at least 400 million years ago. By way of contrast, three in four alternative exons in the human gene set arose in the primate lineage, so our results cannot be extrapolated to the whole genome. Tissue-specific alternative protein forms in the proteomics analysis were particularly abundant in nervous and muscle tissues and their genes had roles related to the cytoskeleton and either the structure of muscle fibres or cell-cell connections. Our results suggest that this conserved tissue-specific alternative splicing may have played a role in the development of the vertebrate brain and heart. We manually curated a set of 255 splice events detected in a large-scale tissue-based proteomics experiment and found that more than a third had evidence of significant tissue-specific differences. Events that were significantly tissue-specific at the protein level were highly conserved; almost 75% evolved over 400 million years ago. The tissues in which we found most evidence for tissue-specific splicing were nervous tissues and cardiac tissues. Genes with tissue-specific events in these two tissues had functions related to important cellular structures in brain and heart tissues. These splice events may have been essential for the development of vertebrate heart and muscle. However, our data set may not be representative of alternative exons as a whole. We found that most tissue specific splicing was strongly conserved, but just 5% of annotated alternative exons in the human gene set are ancient. More than three quarters of alternative exons are primate-derived. Although the analysis does not provide a definitive answer to the question of the functional role of alternative splicing, our results do indicate that alternative splice variants may have played a significant part in the evolution of brain and heart tissues in vertebrates.
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Affiliation(s)
- Jose Manuel Rodriguez
- Cardiovascular Proteomics Laboratory, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Calle Melchor Fernandez, Madrid, Spain
| | - Fernando Pozo
- Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Calle Melchor Fernandez, Madrid, Spain
| | - Tomas di Domenico
- Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Calle Melchor Fernandez, Madrid, Spain
| | - Jesus Vazquez
- Cardiovascular Proteomics Laboratory, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Calle Melchor Fernandez, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Michael L. Tress
- Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Calle Melchor Fernandez, Madrid, Spain
- * E-mail:
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Distinct hypertrophic cardiomyopathy genotypes result in convergent sarcomeric proteoform profiles revealed by top-down proteomics. Proc Natl Acad Sci U S A 2020; 117:24691-24700. [PMID: 32968017 PMCID: PMC7547245 DOI: 10.1073/pnas.2006764117] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Hypertrophic cardiomyopathy (HCM) is the most common heritable heart disease. Although the genetic cause of HCM has been linked to mutations in genes encoding sarcomeric proteins, the ability to predict clinical outcomes based on specific mutations in HCM patients is limited. Moreover, how mutations in different sarcomeric proteins can result in highly similar clinical phenotypes remains unknown. Posttranslational modifications (PTMs) and alternative splicing regulate the function of sarcomeric proteins; hence, it is critical to study HCM at the level of proteoforms to gain insights into the mechanisms underlying HCM. Herein, we employed high-resolution mass spectrometry-based top-down proteomics to comprehensively characterize sarcomeric proteoforms in septal myectomy tissues from HCM patients exhibiting severe outflow track obstruction (n = 16) compared to nonfailing donor hearts (n = 16). We observed a complex landscape of sarcomeric proteoforms arising from combinatorial PTMs, alternative splicing, and genetic variation in HCM. A coordinated decrease of phosphorylation in important myofilament and Z-disk proteins with a linear correlation suggests PTM cross-talk in the sarcomere and dysregulation of protein kinase A pathways in HCM. Strikingly, we discovered that the sarcomeric proteoform alterations in the myocardium of HCM patients undergoing septal myectomy were remarkably consistent, regardless of the underlying HCM-causing mutations. This study suggests that the manifestation of severe HCM coalesces at the proteoform level despite distinct genotype, which underscores the importance of molecular characterization of HCM phenotype and presents an opportunity to identify broad-spectrum treatments to mitigate the most severe manifestations of this genetically heterogenous disease.
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45
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Yu F, Teo GC, Kong AT, Haynes SE, Avtonomov DM, Geiszler DJ, Nesvizhskii AI. Identification of modified peptides using localization-aware open search. Nat Commun 2020; 11:4065. [PMID: 32792501 PMCID: PMC7426425 DOI: 10.1038/s41467-020-17921-y] [Citation(s) in RCA: 114] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Accepted: 07/27/2020] [Indexed: 11/25/2022] Open
Abstract
Identification of post-translationally or chemically modified peptides in mass spectrometry-based proteomics experiments is a crucial yet challenging task. We have recently introduced a fragment ion indexing method and the MSFragger search engine to empower an open search strategy for comprehensive analysis of modified peptides. However, this strategy does not consider fragment ions shifted by unknown modifications, preventing modification localization and limiting the sensitivity of the search. Here we present a localization-aware open search method, in which both modification-containing (shifted) and regular fragment ions are indexed and used in scoring. We also implement a fast mass calibration and optimization method, allowing optimization of the mass tolerances and other key search parameters. We demonstrate that MSFragger with mass calibration and localization-aware open search identifies modified peptides with significantly higher sensitivity and accuracy. Comparing MSFragger to other modification-focused tools (pFind3, MetaMorpheus, and TagGraph) shows that MSFragger remains an excellent option for fast, comprehensive, and sensitive searches for modified peptides in shotgun proteomics data.
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Affiliation(s)
- Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Guo Ci Teo
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Andy T Kong
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Sarah E Haynes
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Dmitry M Avtonomov
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Daniel J Geiszler
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.
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