1
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Jones RT, Scholtes M, Goodspeed A, Akbarzadeh M, Mohapatra S, Feldman LE, Vekony H, Jean A, Tilton CB, Orman MV, Romal S, Deiter C, Kan TW, Xander N, Araki SP, Joshi M, Javaid M, Clambey ET, Layer R, Laajala TD, Parker SJ, Mahmoudi T, Zuiverloon TC, Theodorescu D, Costello JC. NPEPPS Is a Druggable Driver of Platinum Resistance. Cancer Res 2024; 84:1699-1718. [PMID: 38535994 PMCID: PMC11094426 DOI: 10.1158/0008-5472.can-23-1976] [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: 07/04/2023] [Revised: 12/20/2023] [Accepted: 02/29/2024] [Indexed: 04/05/2024]
Abstract
There is an unmet need to improve the efficacy of platinum-based cancer chemotherapy, which is used in primary and metastatic settings in many cancer types. In bladder cancer, platinum-based chemotherapy leads to better outcomes in a subset of patients when used in the neoadjuvant setting or in combination with immunotherapy for advanced disease. Despite such promising results, extending the benefits of platinum drugs to a greater number of patients is highly desirable. Using the multiomic assessment of cisplatin-responsive and -resistant human bladder cancer cell lines and whole-genome CRISPR screens, we identified puromycin-sensitive aminopeptidase (NPEPPS) as a driver of cisplatin resistance. NPEPPS depletion sensitized resistant bladder cancer cells to cisplatin in vitro and in vivo. Conversely, overexpression of NPEPPS in sensitive cells increased cisplatin resistance. NPEPPS affected treatment response by regulating intracellular cisplatin concentrations. Patient-derived organoids (PDO) generated from bladder cancer samples before and after cisplatin-based treatment, and from patients who did not receive cisplatin, were evaluated for sensitivity to cisplatin, which was concordant with clinical response. In the PDOs, depletion or pharmacologic inhibition of NPEPPS increased cisplatin sensitivity, while NPEPPS overexpression conferred resistance. Our data present NPEPPS as a druggable driver of cisplatin resistance by regulating intracellular cisplatin concentrations. SIGNIFICANCE Targeting NPEPPS, which induces cisplatin resistance by controlling intracellular drug concentrations, is a potential strategy to improve patient responses to platinum-based therapies and lower treatment-associated toxicities.
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Affiliation(s)
- Robert T. Jones
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Mathijs Scholtes
- Department of Urology, Erasmus MC Cancer Institute, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Andrew Goodspeed
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
- University of Colorado Cancer Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Maryam Akbarzadeh
- Department of Urology, Erasmus MC Cancer Institute, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Biochemistry, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Saswat Mohapatra
- Cedars-Sinai Samuel Oschin Comprehensive Cancer Institute, Los Angeles, California
| | - Lily Elizabeth Feldman
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Hedvig Vekony
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Annie Jean
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Charlene B. Tilton
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Michael V. Orman
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Shahla Romal
- Department of Biochemistry, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Cailin Deiter
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Tsung Wai Kan
- Department of Urology, Erasmus MC Cancer Institute, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pathology, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Nathaniel Xander
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Stephanie P. Araki
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Molishree Joshi
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
- Functional Genomics Facility, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Mahmood Javaid
- Department of Anesthesiology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Eric T. Clambey
- Department of Anesthesiology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Ryan Layer
- Computer Science Department, University of Colorado, Boulder, Colorado
- BioFrontiers Institute, University of Colorado, Boulder, Colorado
| | - Teemu D. Laajala
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
- Department of Mathematics and Statistics, University of Turku, Turku, Finland
| | - Sarah J. Parker
- Smidt Heart Institute and Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Tokameh Mahmoudi
- Department of Urology, Erasmus MC Cancer Institute, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Biochemistry, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pathology, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Tahlita C.M. Zuiverloon
- Department of Urology, Erasmus MC Cancer Institute, Erasmus University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Dan Theodorescu
- Cedars-Sinai Samuel Oschin Comprehensive Cancer Institute, Los Angeles, California
- Department of Urology, Cedars-Sinai Medical Center, Los Angeles, California
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, California
| | - James C. Costello
- Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, Colorado
- University of Colorado Cancer Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado
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2
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Osipov A, Nikolic O, Gertych A, Parker S, Hendifar A, Singh P, Filippova D, Dagliyan G, Ferrone CR, Zheng L, Moore JH, Tourtellotte W, Van Eyk JE, Theodorescu D. The Molecular Twin artificial-intelligence platform integrates multi-omic data to predict outcomes for pancreatic adenocarcinoma patients. NATURE CANCER 2024; 5:299-314. [PMID: 38253803 PMCID: PMC10899109 DOI: 10.1038/s43018-023-00697-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 11/30/2023] [Indexed: 01/24/2024]
Abstract
Contemporary analyses focused on a limited number of clinical and molecular biomarkers have been unable to accurately predict clinical outcomes in pancreatic ductal adenocarcinoma. Here we describe a precision medicine platform known as the Molecular Twin consisting of advanced machine-learning models and use it to analyze a dataset of 6,363 clinical and multi-omic molecular features from patients with resected pancreatic ductal adenocarcinoma to accurately predict disease survival (DS). We show that a full multi-omic model predicts DS with the highest accuracy and that plasma protein is the top single-omic predictor of DS. A parsimonious model learning only 589 multi-omic features demonstrated similar predictive performance as the full multi-omic model. Our platform enables discovery of parsimonious biomarker panels and performance assessment of outcome prediction models learning from resource-intensive panels. This approach has considerable potential to impact clinical care and democratize precision cancer medicine worldwide.
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Affiliation(s)
- Arsen Osipov
- Department of Medicine (Medical Oncology), Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Oncology, Pancreatic Cancer Precision Medicine Center of Excellence, Johns Hopkins University, Baltimore, MD, USA
| | | | - Arkadiusz Gertych
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Sarah Parker
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Biomedical Sciences and Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Andrew Hendifar
- Department of Medicine (Medical Oncology), Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | | | | | - Grant Dagliyan
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Cristina R Ferrone
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Lei Zheng
- Department of Oncology, Pancreatic Cancer Precision Medicine Center of Excellence, Johns Hopkins University, Baltimore, MD, USA
| | - Jason H Moore
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Warren Tourtellotte
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jennifer E Van Eyk
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Biomedical Sciences and Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Dan Theodorescu
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
- Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
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3
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Yu F, Teo GC, Kong AT, Fröhlich K, Li GX, Demichev V, Nesvizhskii AI. Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform. Nat Commun 2023; 14:4154. [PMID: 37438352 PMCID: PMC10338508 DOI: 10.1038/s41467-023-39869-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 06/28/2023] [Indexed: 07/14/2023] Open
Abstract
Liquid chromatography (LC) coupled with data-independent acquisition (DIA) mass spectrometry (MS) has been increasingly used in quantitative proteomics studies. Here, we present a fast and sensitive approach for direct peptide identification from DIA data, MSFragger-DIA, which leverages the unmatched speed of the fragment ion indexing-based search engine MSFragger. Different from most existing methods, MSFragger-DIA conducts a database search of the DIA tandem mass (MS/MS) spectra prior to spectral feature detection and peak tracing across the LC dimension. To streamline the analysis of DIA data and enable easy reproducibility, we integrate MSFragger-DIA into the FragPipe computational platform for seamless support of peptide identification and spectral library building from DIA, data-dependent acquisition (DDA), or both data types combined. We compare MSFragger-DIA with other DIA tools, such as DIA-Umpire based workflow in FragPipe, Spectronaut, DIA-NN library-free, and MaxDIA. We demonstrate the fast, sensitive, and accurate performance of MSFragger-DIA across a variety of sample types and data acquisition schemes, including single-cell proteomics, phosphoproteomics, and large-scale tumor proteome profiling studies.
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Affiliation(s)
- Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
| | - Guo Ci Teo
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Andy T Kong
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Klemens Fröhlich
- Proteomics Core Facility, Biozentrum, University of Basel, Basel, Switzerland
| | - Ginny Xiaohe Li
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Vadim Demichev
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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4
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NeuroLINCS Proteomics: Defining human-derived iPSC proteomes and protein signatures of pluripotency. Sci Data 2023; 10:24. [PMID: 36631473 PMCID: PMC9834231 DOI: 10.1038/s41597-022-01687-7] [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: 11/02/2021] [Accepted: 09/07/2022] [Indexed: 01/13/2023] Open
Abstract
The National Institute of Health (NIH) Library of integrated network-based cellular signatures (LINCS) program is premised on the generation of a publicly available data resource of cell-based biochemical responses or "signatures" to genetic or environmental perturbations. NeuroLINCS uses human inducible pluripotent stem cells (hiPSCs), derived from patients and healthy controls, and differentiated into motor neuron cell cultures. This multi-laboratory effort strives to establish i) robust multi-omic workflows for hiPSC and differentiated neuronal cultures, ii) public annotated data sets and iii) relevant and targetable biological pathways of spinal muscular atrophy (SMA) and amyotrophic lateral sclerosis (ALS). Here, we focus on the proteomics and the quality of the developed workflow of hiPSC lines from 6 individuals, though epigenomics and transcriptomics data are also publicly available. Known and commonly used markers representing 73 proteins were reproducibly quantified with consistent expression levels across all hiPSC lines. Data quality assessments, data levels and metadata of all 6 genetically diverse human iPSCs analysed by DIA-MS are parsable and available as a high-quality resource to the public.
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5
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Wang Y, Lih TSM, Chen L, Xu Y, Kuczler MD, Cao L, Pienta KJ, Amend SR, Zhang H. Optimized data-independent acquisition approach for proteomic analysis at single-cell level. Clin Proteomics 2022; 19:24. [PMID: 35810282 PMCID: PMC9270744 DOI: 10.1186/s12014-022-09359-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 05/26/2022] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND Single-cell proteomic analysis provides valuable insights into cellular heterogeneity allowing the characterization of the cellular microenvironment which is difficult to accomplish in bulk proteomic analysis. Currently, single-cell proteomic studies utilize data-dependent acquisition (DDA) mass spectrometry (MS) coupled with a TMT labelled carrier channel. Due to the extremely imbalanced MS signals among the carrier channel and other TMT reporter ions, the quantification is compromised. Thus, data-independent acquisition (DIA)-MS should be considered as an alternative approach towards single-cell proteomic study since it generates reproducible quantitative data. However, there are limited reports on the optimal workflow for DIA-MS-based single-cell analysis. METHODS We report an optimized DIA workflow for single-cell proteomics using Orbitrap Lumos Tribrid instrument. We utilized a breast cancer cell line (MDA-MB-231) and induced drug resistant polyaneuploid cancer cells (PACCs) to evaluate our established workflow. RESULTS We found that a short LC gradient was preferable for peptides extracted from single cell level with less than 2 ng sample amount. The total number of co-searching peptide precursors was also critical for protein and peptide identifications at nano- and sub-nano-gram levels. Post-translationally modified peptides could be identified from a nano-gram level of peptides. Using the optimized workflow, up to 1500 protein groups were identified from a single PACC corresponding to 0.2 ng of peptides. Furthermore, about 200 peptides with phosphorylation, acetylation, and ubiquitination were identified from global DIA analysis of 100 cisplatin resistant PACCs (20 ng). Finally, we used this optimized DIA approach to compare the whole proteome of MDA-MB-231 parental cells and induced PACCs at a single-cell level. We found the single-cell level comparison could reflect real protein expression changes and identify the protein copy number. CONCLUSIONS Our results demonstrate that the optimized DIA pipeline can serve as a reliable quantitative tool for single-cell as well as sub-nano-gram proteomic analysis.
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Affiliation(s)
- Yuefan Wang
- Department of Pathology, Johns Hopkins University, Baltimore, MD, 21287, USA
| | | | - Lijun Chen
- Department of Pathology, Johns Hopkins University, Baltimore, MD, 21287, USA
| | - Yuanwei Xu
- Department of Pathology, Johns Hopkins University, Baltimore, MD, 21287, USA
| | - Morgan D Kuczler
- Cancer Ecology Center, The Brady Urological Institute, Johns Hopkins School of Medicine, 600 N. Wolfe Street, Baltimore, MD, 21287, USA
| | - Liwei Cao
- Department of Pathology, Johns Hopkins University, Baltimore, MD, 21287, USA
| | - Kenneth J Pienta
- Cancer Ecology Center, The Brady Urological Institute, Johns Hopkins School of Medicine, 600 N. Wolfe Street, Baltimore, MD, 21287, USA
| | - Sarah R Amend
- Cancer Ecology Center, The Brady Urological Institute, Johns Hopkins School of Medicine, 600 N. Wolfe Street, Baltimore, MD, 21287, USA
| | - Hui Zhang
- Department of Pathology, Johns Hopkins University, Baltimore, MD, 21287, USA.
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6
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Baxi EG, Thompson T, Li J, Kaye JA, Lim RG, Wu J, Ramamoorthy D, Lima L, Vaibhav V, Matlock A, Frank A, Coyne AN, Landin B, Ornelas L, Mosmiller E, Thrower S, Farr SM, Panther L, Gomez E, Galvez E, Perez D, Meepe I, Lei S, Mandefro B, Trost H, Pinedo L, Banuelos MG, Liu C, Moran R, Garcia V, Workman M, Ho R, Wyman S, Roggenbuck J, Harms MB, Stocksdale J, Miramontes R, Wang K, Venkatraman V, Holewenski R, Sundararaman N, Pandey R, Manalo DM, Donde A, Huynh N, Adam M, Wassie BT, Vertudes E, Amirani N, Raja K, Thomas R, Hayes L, Lenail A, Cerezo A, Luppino S, Farrar A, Pothier L, Prina C, Morgan T, Jamil A, Heintzman S, Jockel-Balsarotti J, Karanja E, Markway J, McCallum M, Joslin B, Alibazoglu D, Kolb S, Ajroud-Driss S, Baloh R, Heitzman D, Miller T, Glass JD, Patel-Murray NL, Yu H, Sinani E, Vigneswaran P, Sherman AV, Ahmad O, Roy P, Beavers JC, Zeiler S, Krakauer JW, Agurto C, Cecchi G, Bellard M, Raghav Y, Sachs K, Ehrenberger T, Bruce E, Cudkowicz ME, Maragakis N, Norel R, Van Eyk JE, Finkbeiner S, Berry J, Sareen D, Thompson LM, Fraenkel E, Svendsen CN, Rothstein JD. Answer ALS, a large-scale resource for sporadic and familial ALS combining clinical and multi-omics data from induced pluripotent cell lines. Nat Neurosci 2022; 25:226-237. [PMID: 35115730 PMCID: PMC8825283 DOI: 10.1038/s41593-021-01006-0] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 12/16/2021] [Indexed: 12/13/2022]
Abstract
Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iPS) cell lines, multi-omic data derived from iPS neurons and longitudinal clinical and smartphone data from over 1,000 patients with ALS. This resource provides population-level biological and clinical data that may be employed to identify clinical-molecular-biochemical subtypes of amyotrophic lateral sclerosis (ALS). A unique smartphone-based system was employed to collect deep clinical data, including fine motor activity, speech, breathing and linguistics/cognition. The iPS spinal neurons were blood derived from each patient and these cells underwent multi-omic analytics including whole-genome sequencing, RNA transcriptomics, ATAC-sequencing and proteomics. The intent of these data is for the generation of integrated clinical and biological signatures using bioinformatics, statistics and computational biology to establish patterns that may lead to a better understanding of the underlying mechanisms of disease, including subgroup identification. A web portal for open-source sharing of all data was developed for widespread community-based data analytics.
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Affiliation(s)
- Emily G Baxi
- Brain Science Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | - Jonathan Li
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Julia A Kaye
- Center for Systems and Therapeutics and the Taube/Koret Center for Neurodegenerative Disease, Gladstone Institutes and the Departments of Neurology and Physiology, University of California, San Francisco, San Francisco, CA, USA
| | - Ryan G Lim
- UCI MIND, University of California, Irvine, CA, USA
| | - Jie Wu
- Department of Biological Chemistry, University of California, Irvine, CA, USA
| | - Divya Ramamoorthy
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Leandro Lima
- Center for Systems and Therapeutics and the Taube/Koret Center for Neurodegenerative Disease, Gladstone Institutes and the Departments of Neurology and Physiology, University of California, San Francisco, San Francisco, CA, USA
| | - Vineet Vaibhav
- Advanced Clinical Biosystems Research Institute, The Barbra Streisand Heart Center, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Andrea Matlock
- Advanced Clinical Biosystems Research Institute, The Barbra Streisand Heart Center, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Aaron Frank
- Cedars-Sinai Biomanufacturing Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Alyssa N Coyne
- Brain Science Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Barry Landin
- Computational Biology Center, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
| | - Loren Ornelas
- Cedars-Sinai Biomanufacturing Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Elizabeth Mosmiller
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sara Thrower
- Department of Neurology, Healey Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Lindsey Panther
- Cedars-Sinai Biomanufacturing Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Emilda Gomez
- Cedars-Sinai Biomanufacturing Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Erick Galvez
- Cedars-Sinai Biomanufacturing Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Daniel Perez
- Cedars-Sinai Biomanufacturing Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Imara Meepe
- Cedars-Sinai Biomanufacturing Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Susan Lei
- Cedars-Sinai Biomanufacturing Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Berhan Mandefro
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Hannah Trost
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Louis Pinedo
- Cedars-Sinai Biomanufacturing Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Maria G Banuelos
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Chunyan Liu
- Cedars-Sinai Biomanufacturing Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Ruby Moran
- Cedars-Sinai Biomanufacturing Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Veronica Garcia
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Michael Workman
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Richie Ho
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Stacia Wyman
- Center for Systems and Therapeutics and the Taube/Koret Center for Neurodegenerative Disease, Gladstone Institutes and the Departments of Neurology and Physiology, University of California, San Francisco, San Francisco, CA, USA
| | | | - Matthew B Harms
- Department of Neurology and Genetics, Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Jennifer Stocksdale
- Department of Psychiatry and Human Behavior and Sue and Bill Gross Stem Cell Center, University of California, Irvine, CA, USA
| | | | - Keona Wang
- Department of Psychiatry and Human Behavior and Sue and Bill Gross Stem Cell Center, University of California, Irvine, CA, USA
| | - Vidya Venkatraman
- Advanced Clinical Biosystems Research Institute, The Barbra Streisand Heart Center, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Ronald Holewenski
- Advanced Clinical Biosystems Research Institute, The Barbra Streisand Heart Center, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Niveda Sundararaman
- Advanced Clinical Biosystems Research Institute, The Barbra Streisand Heart Center, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Rakhi Pandey
- Advanced Clinical Biosystems Research Institute, The Barbra Streisand Heart Center, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Danica-Mae Manalo
- Advanced Clinical Biosystems Research Institute, The Barbra Streisand Heart Center, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Aneesh Donde
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Nhan Huynh
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Miriam Adam
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Brook T Wassie
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Edward Vertudes
- Center for Systems and Therapeutics and the Taube/Koret Center for Neurodegenerative Disease, Gladstone Institutes and the Departments of Neurology and Physiology, University of California, San Francisco, San Francisco, CA, USA
| | - Naufa Amirani
- Center for Systems and Therapeutics and the Taube/Koret Center for Neurodegenerative Disease, Gladstone Institutes and the Departments of Neurology and Physiology, University of California, San Francisco, San Francisco, CA, USA
| | - Krishna Raja
- Center for Systems and Therapeutics and the Taube/Koret Center for Neurodegenerative Disease, Gladstone Institutes and the Departments of Neurology and Physiology, University of California, San Francisco, San Francisco, CA, USA
| | - Reuben Thomas
- Center for Systems and Therapeutics and the Taube/Koret Center for Neurodegenerative Disease, Gladstone Institutes and the Departments of Neurology and Physiology, University of California, San Francisco, San Francisco, CA, USA
| | - Lindsey Hayes
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Alex Lenail
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Aianna Cerezo
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sarah Luppino
- Department of Neurology, Healey Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Alanna Farrar
- Department of Neurology, Healey Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Lindsay Pothier
- Department of Neurology, Healey Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Carolyn Prina
- Department of Neurology and Genetics, Ohio State University Wexner Medical Center, Columbus, OH, USA
| | | | - Arish Jamil
- Department of Neurology, Emory University, Atlanta, GA, USA
| | - Sarah Heintzman
- Department of Neurology and Genetics, Ohio State University Wexner Medical Center, Columbus, OH, USA
| | | | | | - Jesse Markway
- Department of Neurology, Washington University, St. Louis, MO, USA
| | - Molly McCallum
- Department of Neurology, Washington University, St. Louis, MO, USA
| | - Ben Joslin
- Department of Neurology, Northwestern University, Chicago, IL, USA
| | - Deniz Alibazoglu
- Department of Neurology, Northwestern University, Chicago, IL, USA
| | - Stephen Kolb
- Department of Neurology and Genetics, Ohio State University Wexner Medical Center, Columbus, OH, USA
| | | | - Robert Baloh
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | | | - Tim Miller
- Department of Neurology, Washington University, St. Louis, MO, USA
| | | | | | - Hong Yu
- Department of Neurology, Healey Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ervin Sinani
- Department of Neurology, Healey Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Prasha Vigneswaran
- Department of Neurology, Healey Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Alexander V Sherman
- Department of Neurology, Healey Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Omar Ahmad
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Promit Roy
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jay C Beavers
- Microsoft Research, Microsoft Corporation, Redmond, WA, USA
| | - Steven Zeiler
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - John W Krakauer
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Carla Agurto
- Computational Biology Center, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
| | - Guillermo Cecchi
- Computational Biology Center, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
| | - Mary Bellard
- Microsoft University Relations, Microsoft Corporation, Redmond, WA, USA
| | - Yogindra Raghav
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Karen Sachs
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Tobias Ehrenberger
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Elizabeth Bruce
- Microsoft University Relations, Microsoft Corporation, Redmond, WA, USA
| | - Merit E Cudkowicz
- Department of Neurology, Healey Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Nicholas Maragakis
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Raquel Norel
- Computational Biology Center, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
| | - Jennifer E Van Eyk
- Advanced Clinical Biosystems Research Institute, The Barbra Streisand Heart Center, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Steven Finkbeiner
- Center for Systems and Therapeutics and the Taube/Koret Center for Neurodegenerative Disease, Gladstone Institutes and the Departments of Neurology and Physiology, University of California, San Francisco, San Francisco, CA, USA
| | - James Berry
- Department of Neurology, Healey Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Dhruv Sareen
- Cedars-Sinai Biomanufacturing Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Leslie M Thompson
- UCI MIND, University of California, Irvine, CA, USA
- Department of Biological Chemistry, University of California, Irvine, CA, USA
- Department of Psychiatry and Human Behavior and Sue and Bill Gross Stem Cell Center, University of California, Irvine, CA, USA
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Ernest Fraenkel
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Clive N Svendsen
- Cedars-Sinai Biomanufacturing Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jeffrey D Rothstein
- Brain Science Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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7
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Ramani K, Robinson AE, Berlind J, Fan W, Abeynayake A, Binek A, Barbier-Torres L, Noureddin M, Nissen NN, Yildirim Z, Erbay E, Mato JM, Van Eyk JE, Lu SC. S-adenosylmethionine inhibits la ribonucleoprotein domain family member 1 in murine liver and human liver cancer cells. Hepatology 2022; 75:280-296. [PMID: 34449924 PMCID: PMC8766892 DOI: 10.1002/hep.32130] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 07/22/2021] [Accepted: 08/09/2021] [Indexed: 02/03/2023]
Abstract
BACKGROUND AND AIMS Methionine adenosyltransferase 1A (MAT1A) is responsible for S-adenosylmethionine (SAMe) biosynthesis in the liver. Mice lacking Mat1a have hepatic SAMe depletion and develop NASH and HCC spontaneously. Several kinases are activated in Mat1a knockout (KO) mice livers. However, characterizing the phospho-proteome and determining whether they contribute to liver pathology remain open for study. Our study aimed to provide this knowledge. APPROACH AND RESULTS We performed phospho-proteomics in Mat1a KO mice livers with and without SAMe treatment to identify SAMe-dependent changes that may contribute to liver pathology. Our studies used Mat1a KO mice at different ages treated with and without SAMe, cell lines, in vitro translation and kinase assays, and human liver specimens. We found that the most striking change was hyperphosphorylation and increased content of La-related protein 1 (LARP1), which, in the unphosphorylated form, negatively regulates translation of 5'-terminal oligopyrimidine (TOP)-containing mRNAs. Consistently, multiple TOP proteins are induced in KO livers. Translation of TOP mRNAs ribosomal protein S3 and ribosomal protein L18 was enhanced by LARP1 overexpression in liver cancer cells. We identified LARP1-T449 as a SAMe-sensitive phospho-site of cyclin-dependent kinase 2 (CDK2). Knocking down CDK2 lowered LARP1 phosphorylation and prevented LARP1-overexpression-mediated increase in translation. LARP1-T449 phosphorylation induced global translation, cell growth, migration, invasion, and expression of oncogenic TOP-ribosomal proteins in HCC cells. LARP1 expression is increased in human NASH and HCC. CONCLUSIONS Our results reveal a SAMe-sensitive mechanism of LARP1 phosphorylation that may be involved in the progression of NASH to HCC.
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Affiliation(s)
- Komal Ramani
- Karsh Division of Gastroenterology and Hepatology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - Aaron E. Robinson
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305
- Smidt Heart Institute and Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - Joshua Berlind
- Stem Cell Biology and Regenerative Medicine, University of Southern California, Los Angeles, CA 90033
| | - Wei Fan
- Karsh Division of Gastroenterology and Hepatology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - Aushinie Abeynayake
- Karsh Division of Gastroenterology and Hepatology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - Aleksandra Binek
- Smidt Heart Institute and Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - Lucía Barbier-Torres
- Karsh Division of Gastroenterology and Hepatology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - Mazen Noureddin
- Karsh Division of Gastroenterology and Hepatology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048
- Comprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - Nicholas N. Nissen
- Comprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, CA 90048
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - Zehra Yildirim
- Department of Cardiology, Department of Biomedical Sciences and Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - Ebru Erbay
- Department of Cardiology, Department of Biomedical Sciences and Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - José M. Mato
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (Ciberehd), Technology, Derio, Bizkaia 48160, Spain
| | - Jennifer E. Van Eyk
- Smidt Heart Institute and Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048
| | - Shelly C. Lu
- Karsh Division of Gastroenterology and Hepatology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048
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8
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Bundgaard L, Åhrman E, Malmström J, Auf dem Keller U, Walters M, Jacobsen S. Effective protein extraction combined with data independent acquisition analysis reveals a comprehensive and quantifiable insight into the proteomes of articular cartilage and subchondral bone. Osteoarthritis Cartilage 2022; 30:137-146. [PMID: 34547431 DOI: 10.1016/j.joca.2021.09.006] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 08/31/2021] [Accepted: 09/13/2021] [Indexed: 02/02/2023]
Abstract
OBJECTIVE The objectives of this study was to establish a sensitive and reproducible method to map the cartilage and subchondral bone proteomes in quantitative terms, and mine the proteomes for proteins of particular interest in the pathogenesis of osteoarthritis (OA). The horse was used as a model animal. DESIGN Protein was extracted from articular cartilage and subchondral bone samples from three horses in triplicate by pressure cycling technology or ultrasonication. Digested proteins were analysed by data independent acquisition based mass spectrometry. Data was processed using a pre-established spectral library as reference database (FDR 1%). RESULTS We identified to our knowledge the hitherto most comprehensive quantitative cartilage (1758 proteins) and subchondral bone (1482 proteins) proteomes in all species presented to date. Both extraction methods were sensitive and reproducible and the high consistency of the identified proteomes (>97% overlap) indicated that both methods preserved the diversity among the extracted proteins. Proteome mining revealed a substantial number of quantifiable cartilage and bone matrix proteins and proteins involved in osteogenesis and bone remodeling, including ACAN, BGN, PRELP, FMOD, COMP, ACP5, BMP3, BMP6, BGLAP, TGFB1, IGF1, ALP, MMP3, and collagens. A number of proteins, including COMP and TNN, were identified in different protein isoforms with potential unique biological roles. CONCLUSION We have successfully developed two sensitive and reproducible non-species specific workflows enabling a comprehensive quantitative insight into the proteomes of cartilage and subchondral bone. This facilitates the prospect of investigating the molecular events at the osteochondral unit in the pathogenesis of OA in future projects.
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Affiliation(s)
- L Bundgaard
- Section of Medicine and Surgery, Department of Veterinary Clinical Sciences, University of Copenhagen, 2630 Taastrup, Denmark. Section for Protein Science and Biotherapeutics, DTU Bioengineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.
| | - E Åhrman
- Division of Infection Medicine Proteomics, Department of Clinical Sciences, Lund University, Lund 221 84, Sweden.
| | - J Malmström
- Division of Infection Medicine Proteomics, Department of Clinical Sciences, Lund University, Lund 221 84, Sweden.
| | - U Auf dem Keller
- Section for Protein Science and Biotherapeutics, DTU Bioengineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.
| | - M Walters
- Section of Medicine and Surgery, Department of Veterinary Clinical Sciences, University of Copenhagen, 2630 Taastrup, Denmark.
| | - S Jacobsen
- Section of Medicine and Surgery, Department of Veterinary Clinical Sciences, University of Copenhagen, 2630 Taastrup, Denmark.
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9
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Saddic L, Orosco A, Guo D, Milewicz DM, Troxlair D, Heide RV, Herrington D, Wang Y, Azizzadeh A, Parker SJ. Proteomic analysis of descending thoracic aorta identifies unique and universal signatures of aneurysm and dissection. JVS Vasc Sci 2022; 3:85-181. [PMID: 35280433 PMCID: PMC8914561 DOI: 10.1016/j.jvssci.2022.01.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 01/05/2022] [Indexed: 01/05/2023] Open
Abstract
Objective Methods Results Conclusions Diseases of the descending thoracic aorta such as aneurysms and dissections carry a high degree of morbidity and mortality. At present, a complete understanding is still lacking of the genetics that drive these diseases and why some aortic segments dissect in the presence or absence of an aneurysm. We compared and contrasted the whole proteome expression of descending aortas from patients with normal, dissected, aneurysmal, and aneurysmal with dissected pathology aortic tissue. We uncovered potential tissue markers that might serve as future targets for therapy or predictors of disease progression.
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Affiliation(s)
- Louis Saddic
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, Calif
| | - Amanda Orosco
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, Calif
| | - Dongchuan Guo
- Department of Internal Medicine, McGovern Medical School, University of Texas Health Science Center, Houston, Tex
| | - Dianna M. Milewicz
- Department of Internal Medicine, McGovern Medical School, University of Texas Health Science Center, Houston, Tex
| | - Dana Troxlair
- Department of Pathology, Louisiana State University, New Orleans, La
| | | | - David Herrington
- Department of Cardiovascular Medicine, Wake Forest University, Winston-Salem, NC
| | - Yue Wang
- Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, Va
| | - Ali Azizzadeh
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, Calif
| | - Sarah J. Parker
- Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, Calif
- Correspondence: Sarah J. Parker, PhD, Department of Cardiology, Smidt Heart Institute, Cedars Sinai Medical Center, AHSP A9228, 8700 Beverly Blvd, Los Angeles, CA 90048
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10
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Siyal AA, Chen ESW, Chan HJ, Kitata RB, Yang JC, Tu HL, Chen YJ. Sample Size-Comparable Spectral Library Enhances Data-Independent Acquisition-Based Proteome Coverage of Low-Input Cells. Anal Chem 2021; 93:17003-17011. [PMID: 34904835 DOI: 10.1021/acs.analchem.1c03477] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Despite advancements of data-independent acquisition mass spectrometry (DIA-MS) to provide comprehensive and reproducible proteome profiling, its utility in very low-input samples is limited. Due to different proteome complexities and corresponding peptide ion abundances, the conventional LC-MS/MS acquisition and widely used large-scale DIA libraries may not be suitable for the micro-nanogram samples. In this study, we report a sample size-comparable library-based DIA approach to enhance the proteome coverage of low-input nanoscale samples (i.e., nanogram cells, ∼5-50 cells). By constructing sample size-comparable libraries, 2380 and 3586 protein groups were identified from as low as 0.75 (∼5 cells) and 1.5 ng (∼10 cells), respectively, highlighting one of the highest proteome coverage with good reproducibility (86%-99% in triplicate results). For the 0.75 ng sample (∼5 cells), significantly superior identification (2380 proteins) was achieved by small-size library-based DIA, compared to 1908, 1749, and 107 proteins identified from medium-size and large-size libraries and a lung cancer resource spectral library, respectively. A similar trend was observed using a different instrument and data analysis pipeline, indicating the generalized conclusion of the approach. Furthermore, the small-size library uniquely identified 518 (22%) proteins in the low-abundant region and spans over a 5-order dynamic range. Spectral similarity analysis revealed that the fragmentation ion pattern in the DIA-MS/MS spectra of the dataset and spectral library play crucial roles for mapping low abundant proteins. With these spectral libraries made freely available, the optimized library-based DIA strategy and DIA digital map will advance quantitative proteomics applications for mass-limited samples.
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Affiliation(s)
- Asad Ali Siyal
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan.,Department of Chemistry, National Tsing Hua University, Hsinchu 300, Taiwan
| | - Eric Sheng-Wen Chen
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Research Center for Cancer Biology, China Medical University, Taichung 40402, Taiwan
| | - Hsin-Ju Chan
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Department of Chemistry, National Taiwan University, Taipei 106, Taiwan
| | | | - Jhih-Ci Yang
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei 11529, Taiwan.,Department of Applied Chemistry, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | - Hsiung-Lin Tu
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan.,Department of Chemistry, National Taiwan University, Taipei 106, Taiwan.,Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei 11529, Taiwan
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11
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Ho AS, Robinson A, Shon W, Laury A, Raedschelders K, Venkatraman V, Holewinski R, Zhang Y, Shiao SL, Chen MM, Mallen-St Clair J, Lin DC, Zumsteg ZS, Van Eyk JE. Comparative Proteomic Analysis of HPV(+) Oropharyngeal Squamous Cell Carcinoma Recurrence. J Proteome Res 2021; 21:200-208. [PMID: 34846153 DOI: 10.1021/acs.jproteome.1c00757] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Deintensification therapy for human papillomavirus-related oropharyngeal squamous cell carcinoma (HPV(+) OPSCC) is under active investigation. An adaptive treatment approach based on molecular stratification could identify high-risk patients predisposed to recurrence and better select for appropriate treatment regimens. Collectively, 40 HPV(+) OPSCC FFPE samples (20 disease-free, 20 recurrent) were surveyed using mass spectrometry-based proteomic analysis via data-independent acquisition to obtain fold change and false discovery differences. Ten-year overall survival was 100.0 and 27.7% for HPV(+) disease-free and recurrent cohorts, respectively. Of 1414 quantified proteins, 77 demonstrated significant differential expression. Top enriched functional pathways included those involved in programmed cell death (73 proteins, p = 7.43 × 10-30), apoptosis (73 proteins, p = 5.56 × 10-9), β-catenin independent WNT signaling (47 proteins, p = 1.45 × 10-15), and Rho GTPase signaling (69 proteins, p = 1.09 × 10-5). PFN1 (p = 1.0 × 10-3), RAD23B (p = 2.9 × 10-4), LDHB (p = 1.0 × 10-3), and HINT1 (p = 3.8 × 10-3) pathways were significantly downregulated in the recurrent cohort. On functional validation via immunohistochemistry (IHC) staining, 46.9% (PFN1), 71.9% (RAD23B), 59.4% (LDHB), and 84.4% (HINT1) of cases were corroborated with mass spectrometry findings. Development of a multilateral molecular signature incorporating these targets may characterize high-risk disease, predict treatment response, and augment current management paradigms in head and neck cancer.
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12
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Li J, Lim RG, Kaye JA, Dardov V, Coyne AN, Wu J, Milani P, Cheng A, Thompson TG, Ornelas L, Frank A, Adam M, Banuelos MG, Casale M, Cox V, Escalante-Chong R, Daigle JG, Gomez E, Hayes L, Holewenski R, Lei S, Lenail A, Lima L, Mandefro B, Matlock A, Panther L, Patel-Murray NL, Pham J, Ramamoorthy D, Sachs K, Shelley B, Stocksdale J, Trost H, Wilhelm M, Venkatraman V, Wassie BT, Wyman S, Yang S, Van Eyk JE, Lloyd TE, Finkbeiner S, Fraenkel E, Rothstein JD, Sareen D, Svendsen CN, Thompson LM. An integrated multi-omic analysis of iPSC-derived motor neurons from C9ORF72 ALS patients. iScience 2021; 24:103221. [PMID: 34746695 PMCID: PMC8554488 DOI: 10.1016/j.isci.2021.103221] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 06/29/2021] [Accepted: 09/30/2021] [Indexed: 12/13/2022] Open
Abstract
Neurodegenerative diseases are challenging for systems biology because of the lack of reliable animal models or patient samples at early disease stages. Induced pluripotent stem cells (iPSCs) could address these challenges. We investigated DNA, RNA, epigenetics, and proteins in iPSC-derived motor neurons from patients with ALS carrying hexanucleotide expansions in C9ORF72. Using integrative computational methods combining all omics datasets, we identified novel and known dysregulated pathways. We used a C9ORF72 Drosophila model to distinguish pathways contributing to disease phenotypes from compensatory ones and confirmed alterations in some pathways in postmortem spinal cord tissue of patients with ALS. A different differentiation protocol was used to derive a separate set of C9ORF72 and control motor neurons. Many individual -omics differed by protocol, but some core dysregulated pathways were consistent. This strategy of analyzing patient-specific neurons provides disease-related outcomes with small numbers of heterogeneous lines and reduces variation from single-omics to elucidate network-based signatures.
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Affiliation(s)
- Jonathan Li
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ryan G. Lim
- UCI MIND, University of California, Irvine, CA 92697, USA
| | - Julia A. Kaye
- Center for Systems and Therapeutics and the Taube/Koret Center for Neurodegenerative Disease, Gladstone Institutes, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Victoria Dardov
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA
- Advanced Clinical Biosystems Research Institute, The Barbra Streisand Heart Center, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Alyssa N. Coyne
- Brain Science Institute, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
- Department of Neurology and Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
| | - Jie Wu
- Department of Biological Chemistry, University of California, Irvine, CA 92697, USA
| | - Pamela Milani
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Andrew Cheng
- Cellular and Molecular Medicine Program, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
| | | | - Loren Ornelas
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA
| | - Aaron Frank
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA
| | - Miriam Adam
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Maria G. Banuelos
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA
| | - Malcolm Casale
- UCI MIND, University of California, Irvine, CA 92697, USA
- Department of Neurobiology and Behavior, University of California, Irvine, CA 92697, USA
| | - Veerle Cox
- Cellular and Molecular Medicine Program, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
| | - Renan Escalante-Chong
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - J. Gavin Daigle
- Brain Science Institute, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
- Department of Neurology and Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
| | - Emilda Gomez
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA
| | - Lindsey Hayes
- Department of Neurology and Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
| | - Ronald Holewenski
- Advanced Clinical Biosystems Research Institute, The Barbra Streisand Heart Center, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Susan Lei
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA
| | - Alex Lenail
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Leandro Lima
- Center for Systems and Therapeutics and the Taube/Koret Center for Neurodegenerative Disease, Gladstone Institutes, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Berhan Mandefro
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA
| | - Andrea Matlock
- Advanced Clinical Biosystems Research Institute, The Barbra Streisand Heart Center, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Lindsay Panther
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA
| | | | - Jacqueline Pham
- Department of Neurology and Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
| | - Divya Ramamoorthy
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Karen Sachs
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Brandon Shelley
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA
| | - Jennifer Stocksdale
- UCI MIND, University of California, Irvine, CA 92697, USA
- Department of Neurobiology and Behavior, University of California, Irvine, CA 92697, USA
| | - Hannah Trost
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA
| | - Mark Wilhelm
- Brain Science Institute, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
| | - Vidya Venkatraman
- Advanced Clinical Biosystems Research Institute, The Barbra Streisand Heart Center, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Brook T. Wassie
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Stacia Wyman
- Sue and Bill Gross Stem Cell Center, University of California, Irvine, CA 92697, USA
| | - Stephanie Yang
- Brain Science Institute, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
| | | | - Jennifer E. Van Eyk
- Advanced Clinical Biosystems Research Institute, The Barbra Streisand Heart Center, The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Thomas E. Lloyd
- Department of Neurology and Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
| | - Steven Finkbeiner
- Center for Systems and Therapeutics and the Taube/Koret Center for Neurodegenerative Disease, Gladstone Institutes, University of California, San Francisco, San Francisco, CA 94158, USA
- Departments of Neurology and Physiology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Ernest Fraenkel
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Jeffrey D. Rothstein
- Brain Science Institute, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
- Department of Neurology and Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
- Cellular and Molecular Medicine Program, Johns Hopkins University School of Medicine, Baltimore, MA 212056, USA
| | - Dhruv Sareen
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA
| | - Clive N. Svendsen
- The Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA
| | - Leslie M. Thompson
- UCI MIND, University of California, Irvine, CA 92697, USA
- Department of Biological Chemistry, University of California, Irvine, CA 92697, USA
- Department of Neurobiology and Behavior, University of California, Irvine, CA 92697, USA
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA 92697, USA
- Sue and Bill Gross Stem Cell Center, University of California, Irvine, CA 92697, USA
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13
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Ge W, Liang X, Zhang F, Hu Y, Xu L, Xiang N, Sun R, Liu W, Xue Z, Yi X, Sun Y, Wang B, Zhu J, Lu C, Zhan X, Chen L, Wu Y, Zheng Z, Gong W, Wu Q, Yu J, Ye Z, Teng X, Huang S, Zheng S, Liu T, Yuan C, Guo T. Computational Optimization of Spectral Library Size Improves DIA-MS Proteome Coverage and Applications to 15 Tumors. J Proteome Res 2021; 20:5392-5401. [PMID: 34748352 DOI: 10.1021/acs.jproteome.1c00640] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Efficient peptide and protein identifications from data-independent acquisition mass spectrometric (DIA-MS) data typically rely on a project-specific spectral library with a suitable size. Here, we describe subLib, a computational strategy for optimizing the spectral library for a specific DIA data set based on a comprehensive spectral library, requiring the preliminary analysis of the DIA data set. Compared with the pan-human library strategy, subLib achieved a 41.2% increase in peptide precursor identifications and a 35.6% increase in protein group identifications in a test data set of six colorectal tumor samples. We also applied this strategy to 389 carcinoma samples from 15 tumor data sets: up to a 39.2% increase in peptide precursor identifications and a 19.0% increase in protein group identifications were observed. Our strategy for spectral library size optimization thus successfully proved to deepen the proteome coverages of DIA-MS data.
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Affiliation(s)
- Weigang Ge
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Westlake Omics (Hangzhou) Biotechnology Co., Ltd., No. 1, Yunmeng Road, Cloud Town, Xihu District, Hangzhou 310024, Zhejiang Province, China
| | - Xiao Liang
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China
| | - Fangfei Zhang
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China
| | - Yifan Hu
- Westlake Omics (Hangzhou) Biotechnology Co., Ltd., No. 1, Yunmeng Road, Cloud Town, Xihu District, Hangzhou 310024, Zhejiang Province, China
| | - Luang Xu
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China
| | - Nan Xiang
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Westlake Omics (Hangzhou) Biotechnology Co., Ltd., No. 1, Yunmeng Road, Cloud Town, Xihu District, Hangzhou 310024, Zhejiang Province, China
| | - Rui Sun
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China
| | - Wei Liu
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Westlake Omics (Hangzhou) Biotechnology Co., Ltd., No. 1, Yunmeng Road, Cloud Town, Xihu District, Hangzhou 310024, Zhejiang Province, China
| | - Zhangzhi Xue
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China
| | - Xiao Yi
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Westlake Omics (Hangzhou) Biotechnology Co., Ltd., No. 1, Yunmeng Road, Cloud Town, Xihu District, Hangzhou 310024, Zhejiang Province, China
| | - Yaoting Sun
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China
| | - Bo Wang
- Department of Pathology, The First Affiliated Hospital of College of Medicine, Zhejiang University, Hangzhou 310024, Zhejiang Province, China
| | - Jiang Zhu
- Center for Stem Cell Research and Application, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, Hubei Province, China
| | - Cong Lu
- Center for Stem Cell Research and Application, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, Hubei Province, China
| | - Xiaolu Zhan
- Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Lirong Chen
- Department of Pathology, The Second Affiliated Hospital of College of Medicine, Zhejiang University, Hangzhou 310009, Zhejiang Province, China
| | - Yan Wu
- Department of Orthopaedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, Zhejiang Province, China.,Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou 310020, Zhejiang Province, China
| | - Zhiguo Zheng
- The Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou 310022, Zhejiang Province, China.,Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou 310022, Zhejiang Province, China
| | - Wangang Gong
- The Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou 310022, Zhejiang Province, China.,Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou 310022, Zhejiang Province, China
| | - Qijun Wu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang 110000, Liaoning Province, China
| | - Jiekai Yu
- Cancer Institute, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, Zhejiang, China
| | - Zhaoming Ye
- Department of Orthopaedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, Zhejiang Province, China.,Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province, Hangzhou 310020, Zhejiang Province, China
| | - Xiaodong Teng
- Department of Pathology, The First Affiliated Hospital of College of Medicine, Zhejiang University, Hangzhou 310024, Zhejiang Province, China
| | - Shiang Huang
- Center for Stem Cell Research and Application, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, Hubei Province, China
| | - Shu Zheng
- Cancer Institute, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, Zhejiang, China
| | - Tong Liu
- Harbin Medical University Cancer Hospital, Harbin 150081, Heilongjiang Province, China
| | - Chunhui Yuan
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China
| | - Tiannan Guo
- Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China.,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, 18 Shilongshan Road, Hangzhou 310024, Zhejiang Province, China
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14
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Deep representation features from DreamDIA XMBD improve the analysis of data-independent acquisition proteomics. Commun Biol 2021; 4:1190. [PMID: 34650228 PMCID: PMC8517002 DOI: 10.1038/s42003-021-02726-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Accepted: 09/27/2021] [Indexed: 12/24/2022] Open
Abstract
We developed DreamDIAXMBD (denoted as DreamDIA), a software suite based on a deep representation model for data-independent acquisition (DIA) data analysis. DreamDIA adopts a data-driven strategy to capture comprehensive information from elution patterns of peptides in DIA data and achieves considerable improvements on both identification and quantification performance compared with other state-of-the-art methods such as OpenSWATH, Skyline and DIA-NN. Specifically, in contrast to existing methods which use only 6 to 10 selected fragment ions from spectral libraries, DreamDIA extracts additional features from hundreds of theoretical elution profiles originated from different ions of each precursor using a deep representation network. To achieve higher coverage of target peptides without sacrificing specificity, the extracted features are further processed by nonlinear discriminative models under the framework of positive-unlabeled learning with decoy peptides as affirmative negative controls. DreamDIA is publicly available at https://github.com/xmuyulab/DreamDIA-XMBD for high coverage and accuracy DIA data analysis.
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15
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Kim J, Yeon A, Parker SJ, Shahid M, Thiombane A, Cho E, You S, Emam H, Kim DG, Kim M. Alendronate-induced Perturbation of the Bone Proteome and Microenvironmental Pathophysiology. Int J Med Sci 2021; 18:3261-3270. [PMID: 34400895 PMCID: PMC8364444 DOI: 10.7150/ijms.61552] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 07/11/2021] [Indexed: 11/05/2022] Open
Abstract
Objectives: Bisphosphonates (BPs) are powerful inhibitors of osteoclastogenesis and are used to prevent osteoporotic bone loss and reduce the risk of osteoporotic fracture in patients suffering from postmenopausal osteoporosis. Patients with breast cancer or gynecological malignancies being treated with BPs or those receiving bone-targeted therapy for metastatic prostate cancer are at increased risk of bisphosphonate-related osteonecrosis of the jaw (BRONJ). Although BPs markedly ameliorate osteoporosis, their adverse effects largely limit the clinical application of these drugs. This study focused on providing a deeper understanding of one of the most popular BPs, the alendronate (ALN)-induced perturbation of the bone proteome and microenvironmental pathophysiology. Methods: To understand the molecular mechanisms underlying ALN-induced side-effects, an unbiased and global proteomics approach combined with big data bioinformatics was applied. This was followed by biochemical and functional analyses to determine the clinicopathological mechanisms affected by ALN. Results: The findings from this proteomics study suggest that the RIPK3/Wnt/GSK3/β-catenin signaling pathway is significantly perturbed upon ALN treatment, resulting in abnormal angiogenesis, inflammation, anabolism, remodeling, and mineralization in bone cells in an in vitro cell culture system. Conclusion: Our investigation into potential key signaling mechanisms in response to ALN provides a rational basis for suppressing BP-induced adverse effect and presents various therapeutic strategies.
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Affiliation(s)
- Jayoung Kim
- Departments of Surgery and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Medicine, University of California Los Angeles, CA, USA
| | - Austin Yeon
- Departments of Surgery and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Sarah J. Parker
- Smidt Heart Institute, Department of Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Muhammad Shahid
- Departments of Surgery and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Aissatou Thiombane
- Departments of Surgery and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Eunho Cho
- Departments of Surgery and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Sungyong You
- Departments of Surgery and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Hany Emam
- Division of Orthodontics, College of Dentistry, The Ohio State University, Columbus, OH, USA
| | - Do-Gyoon Kim
- Division of Oral Surgery, College of Dentistry, The Ohio State University, Columbus, OH, USA
| | - Minjung Kim
- Department of Cell Biology, Microbiology, and Molecular Biology, University of South Florida, Tampa, FL, USA
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16
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Dabke K, Kreimer S, Jones MR, Parker SJ. A Simple Optimization Workflow to Enable Precise and Accurate Imputation of Missing Values in Proteomic Data Sets. J Proteome Res 2021; 20:3214-3229. [PMID: 33939434 DOI: 10.1021/acs.jproteome.1c00070] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Missing values in proteomic data sets have real consequences on downstream data analysis and reproducibility. Although several imputation methods exist to handle missing values, no single imputation method is best suited for a diverse range of data sets, and no clear strategy exists for evaluating imputation methods for clinical DIA-MS data sets, especially at different levels of protein quantification. To navigate through the different imputation strategies available in the literature, we have established a strategy to assess imputation methods on clinical label-free DIA-MS data sets. We used three DIA-MS data sets with real missing values to evaluate eight imputation methods with multiple parameters at different levels of protein quantification: a dilution series data set, a small pilot data set, and a clinical proteomic data set comparing paired tumor and stroma tissue. We found that imputation methods based on local structures within the data, like local least-squares (LLS) and random forest (RF), worked well in our dilution series data set, whereas imputation methods based on global structures within the data, like BPCA, performed well in the other two data sets. We also found that imputation at the most basic protein quantification level-fragment level-improved accuracy and the number of proteins quantified. With this analytical framework, we quickly and cost-effectively evaluated different imputation methods using two smaller complementary data sets to narrow down to the larger proteomic data set's most accurate methods. This acquisition strategy allowed us to provide reproducible evidence of the accuracy of the imputation method, even in the absence of a ground truth. Overall, this study indicates that the most suitable imputation method relies on the overall structure of the data set and provides an example of an analytic framework that may assist in identifying the most appropriate imputation strategies for the differential analysis of proteins.
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Affiliation(s)
- Kruttika Dabke
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Science, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States.,Graduate Program in Biomedical Sciences, Department of Biomedical Science, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Simion Kreimer
- Advanced Clinical Biosystems Research Institute, Smidt Heart Institute, Departments of Cardiology and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Michelle R Jones
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Science, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Sarah J Parker
- Advanced Clinical Biosystems Research Institute, Smidt Heart Institute, Departments of Cardiology and Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
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17
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Weng S, Wang M, Zhao Y, Ying W, Qian X. Optimised data-independent acquisition strategy recaptures the classification of early-stage hepatocellular carcinoma based on data-dependent acquisition. J Proteomics 2021; 238:104152. [PMID: 33609755 DOI: 10.1016/j.jprot.2021.104152] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 01/21/2021] [Accepted: 02/08/2021] [Indexed: 12/27/2022]
Abstract
Proteomics is increasingly used for exploring disease biomarkers and therapeutic targets. The data-independent acquisition (DIA) method collects all peptide signals in a sample, and provides a convenient way to archive disease-related molecular features for further exploration. In this study, we first established a high-coverage human hepatocellular carcinoma (HCC) spectral library containing 9393 protein groups, 119,903 peptides. Furthermore, we optimised the DIA method with respect to four key parameters: settings for mass spectrometry acquisition, gradient length, amount of sample loading, and length of analytical column. More than 6000 proteins from HepG2 cells could be stably quantified using the optimised one-shot DIA approach with a 2 h gradient time. One-shot DIA identified a similar number of proteins as did multi-fraction data-dependent acquisition (DDA) from the same group of HCC samples, but at a quarter of the total acquisition time. DIA data could recapture the classification results obtained from DDA data, thus paving the way for large-scale, multi-centre proteomics analysis of clinical samples. SIGNIFICANCE: The organ-specific spectral library for HCC and the optimised 2 h DIA approach met the urgent demands for large-scale quantitative proteomics analysis of HCC clinical samples. Compared with multi-fraction-DDA, the optimised one-shot DIA could reach a similar identification while consuming shorter acquisition time, thus making it possible to analyse thousands of clinical samples.
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Affiliation(s)
- Shuang Weng
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China
| | - Mingchao Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China
| | - Yingyi Zhao
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China
| | - Wantao Ying
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China.
| | - Xiaohong Qian
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, China.
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18
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Klein O. Proteomics in Kidney and Cardiovascular Clinical Research. Proteomics Clin Appl 2021; 15:e1900132. [PMID: 33458964 DOI: 10.1002/prca.201900132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Oliver Klein
- Berlin Institute of Health Center for Regenerative Therapies and Berlin-Brandenburg Centre for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Campus Virchow Klinikum (CVK), Augustenburger Platz 1, Berlin, 13353, Germany
- German Center for Cardiovascular Research (DZHK), Partner site Berlin, Berlin, Germany
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19
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Robinson AE, Binek A, Venkatraman V, Searle BC, Holewinski RJ, Rosenberger G, Parker SJ, Basisty N, Xie X, Lund PJ, Saxena G, Mato JM, Garcia BA, Schilling B, Lu SC, Van Eyk JE. Lysine and Arginine Protein Post-translational Modifications by Enhanced DIA Libraries: Quantification in Murine Liver Disease. J Proteome Res 2020; 19:4163-4178. [PMID: 32966080 DOI: 10.1021/acs.jproteome.0c00685] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Proteoforms containing post-translational modifications (PTMs) represent a degree of functional diversity only harnessed through analytically precise simultaneous quantification of multiple PTMs. Here we present a method to accurately differentiate an unmodified peptide from its PTM-containing counterpart through data-independent acquisition-mass spectrometry, leveraging small precursor mass windows to physically separate modified peptidoforms from each other during MS2 acquisition. We utilize a lysine and arginine PTM-enriched peptide assay library and site localization algorithm to simultaneously localize and quantify seven PTMs including mono-, di-, and trimethylation, acetylation, and succinylation in addition to total protein quantification in a single MS run without the need to enrich experimental samples. To evaluate biological relevance, this method was applied to liver lysate from differentially methylated nonalcoholic steatohepatitis (NASH) mouse models. We report that altered methylation and acetylation together with total protein changes drive the novel hypothesis of a regulatory function of PTMs in protein synthesis and mRNA stability in NASH.
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Affiliation(s)
- Aaron E Robinson
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
| | - Aleksandra Binek
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
| | - Vidya Venkatraman
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
| | - Brian C Searle
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Ronald J Holewinski
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
| | - George Rosenberger
- Department of Systems Biology, Columbia University, New York, New York 10027, United States
| | - Sarah J Parker
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
| | - Nathan Basisty
- Buck Institute for Research on Aging, Novato, California 94945, United States
| | - Xueshu Xie
- Buck Institute for Research on Aging, Novato, California 94945, United States
| | - Peder J Lund
- Department of Biochemistry and Biophysics, Epigenetics Institute, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104, United States
| | | | - José M Mato
- CIC bioGUNE, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (Ciberehd), Technology Park of Bizkaia, 48160 Derio, Bizkaia, Spain
| | - Benjamin A Garcia
- Department of Biochemistry and Biophysics, Epigenetics Institute, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104, United States
| | - Birgit Schilling
- Buck Institute for Research on Aging, Novato, California 94945, United States
| | - Shelly C Lu
- Division of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Jennifer E Van Eyk
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
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20
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Zhang F, Ge W, Ruan G, Cai X, Guo T. Data‐Independent Acquisition Mass Spectrometry‐Based Proteomics and Software Tools: A Glimpse in 2020. Proteomics 2020; 20:e1900276. [DOI: 10.1002/pmic.201900276] [Citation(s) in RCA: 116] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 03/27/2020] [Indexed: 01/02/2023]
Affiliation(s)
- Fangfei Zhang
- Key Laboratory of Structural Biology of Zhejiang ProvinceSchool of Life SciencesWestlake University 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
- Institute of Basic Medical SciencesWestlake Institute for Advanced Study 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
| | - Weigang Ge
- Key Laboratory of Structural Biology of Zhejiang ProvinceSchool of Life SciencesWestlake University 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
- Institute of Basic Medical SciencesWestlake Institute for Advanced Study 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
| | - Guan Ruan
- Key Laboratory of Structural Biology of Zhejiang ProvinceSchool of Life SciencesWestlake University 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
- Institute of Basic Medical SciencesWestlake Institute for Advanced Study 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
| | - Xue Cai
- Key Laboratory of Structural Biology of Zhejiang ProvinceSchool of Life SciencesWestlake University 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
- Institute of Basic Medical SciencesWestlake Institute for Advanced Study 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
| | - Tiannan Guo
- Key Laboratory of Structural Biology of Zhejiang ProvinceSchool of Life SciencesWestlake University 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
- Institute of Basic Medical SciencesWestlake Institute for Advanced Study 18 Shilongshan Road Hangzhou Zhejiang Province 310024 China
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21
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Parker SJ, Chen L, Spivia W, Saylor G, Mao C, Venkatraman V, Holewinski RJ, Mastali M, Pandey R, Athas G, Yu G, Fu Q, Troxlair D, Vander Heide R, Herrington D, Van Eyk JE, Wang Y. Identification of Putative Early Atherosclerosis Biomarkers by Unsupervised Deconvolution of Heterogeneous Vascular Proteomes. J Proteome Res 2020; 19:2794-2806. [PMID: 32202800 DOI: 10.1021/acs.jproteome.0c00118] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Coronary artery disease remains a leading cause of death in industrialized nations, and early detection of disease is a critical intervention target to effectively treat patients and manage risk. Proteomic analysis of mixed tissue homogenates may obscure subtle protein changes that occur uniquely in underlying tissue subtypes. The unsupervised 'convex analysis of mixtures' (CAM) tool has previously been shown to effectively segregate cellular subtypes from mixed expression data. In this study, we hypothesized that CAM would identify proteomic information specifically informative to early atherosclerosis lesion involvement that could lead to potential markers of early disease detection. We quantified the proteome of 99 paired abdominal aorta (AA) and left anterior descending coronary artery (LAD) specimens (N = 198 specimens total) acquired during autopsy of young adults free of diagnosed cardiac disease. The CAM tool was then used to segregate protein subsets uniquely associated with different underlying tissue types, yielding markers of normal and fibrous plaque (FP) tissues in LAD and AA (N = 62 lesions markers). CAM-derived FP marker expression was validated against pathologist estimated luminal surface involvement of FP, as well as in an orthogonal cohort of "pure" fibrous plaque, fatty streak, and normal vascular specimens. A targeted mass spectrometry (MS) assay quantified 39 of 62 CAM-FP markers in plasma from women with angiographically verified coronary artery disease (CAD, N = 46) or free from apparent CAD (control, N = 40). Elastic net variable selection with logistic regression reduced this list to 10 proteins capable of classifying CAD status in this cohort with <6% misclassification error, and a mean area under the receiver operating characteristic curve of 0.992 (confidence interval 0.968-0.998) after cross validation. The proteomics-CAM workflow identified lesion-specific molecular biomarker candidates by distilling the most representative molecules from heterogeneous tissue types.
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Affiliation(s)
- Sarah J Parker
- Heart Institute & Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
| | - Lulu Chen
- Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, Virginia 24061, United States
| | - Weston Spivia
- Heart Institute & Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
| | - Georgia Saylor
- Department of Cardiovascular Medicine, Wake Forest University, Winston-Salem, North Carolina 27101, United States
| | - Chunhong Mao
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, Virginia 22904, United States
| | - Vidya Venkatraman
- Heart Institute & Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
| | - Ronald J Holewinski
- Heart Institute & Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
| | - Mitra Mastali
- Heart Institute & Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
| | - Rakhi Pandey
- Heart Institute & Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
| | - Grace Athas
- Department of Pathology, Louisiana State University, New Orleans, Louisiana 70112, United States
| | - Guoqiang Yu
- Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, Virginia 24061, United States
| | - Qin Fu
- Heart Institute & Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
| | - Dana Troxlair
- Department of Pathology, Louisiana State University, New Orleans, Louisiana 70112, United States
| | - Richard Vander Heide
- Department of Pathology, Louisiana State University, New Orleans, Louisiana 70112, United States
| | - David Herrington
- Department of Cardiovascular Medicine, Wake Forest University, Winston-Salem, North Carolina 27101, United States
| | - Jennifer E Van Eyk
- Heart Institute & Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
| | - Yue Wang
- Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, Virginia 24061, United States
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22
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Laperle AH, Sances S, Yucer N, Dardov VJ, Garcia VJ, Ho R, Fulton AN, Jones MR, Roxas KM, Avalos P, West D, Banuelos MG, Shu Z, Murali R, Maidment NT, Van Eyk JE, Tagliati M, Svendsen CN. iPSC modeling of young-onset Parkinson's disease reveals a molecular signature of disease and novel therapeutic candidates. Nat Med 2020; 26:289-299. [PMID: 31988461 DOI: 10.1038/s41591-019-0739-1] [Citation(s) in RCA: 80] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 12/16/2019] [Indexed: 12/21/2022]
Abstract
Young-onset Parkinson's disease (YOPD), defined by onset at <50 years, accounts for approximately 10% of all Parkinson's disease cases and, while some cases are associated with known genetic mutations, most are not. Here induced pluripotent stem cells were generated from control individuals and from patients with YOPD with no known mutations. Following differentiation into cultures containing dopamine neurons, induced pluripotent stem cells from patients with YOPD showed increased accumulation of soluble α-synuclein protein and phosphorylated protein kinase Cα, as well as reduced abundance of lysosomal membrane proteins such as LAMP1. Testing activators of lysosomal function showed that specific phorbol esters, such as PEP005, reduced α-synuclein and phosphorylated protein kinase Cα levels while increasing LAMP1 abundance. Interestingly, the reduction in α-synuclein occurred through proteasomal degradation. PEP005 delivery to mouse striatum also decreased α-synuclein production in vivo. Induced pluripotent stem cell-derived dopaminergic cultures reveal a signature in patients with YOPD who have no known Parkinson's disease-related mutations, suggesting that there might be other genetic contributions to this disorder. This signature was normalized by specific phorbol esters, making them promising therapeutic candidates.
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Affiliation(s)
- A H Laperle
- Cedars-Sinai Board of Governors Regenerative Medicine Institute, Los Angeles, CA, USA
| | - S Sances
- Cedars-Sinai Board of Governors Regenerative Medicine Institute, Los Angeles, CA, USA
| | - N Yucer
- Cedars-Sinai Board of Governors Regenerative Medicine Institute, Los Angeles, CA, USA
| | - V J Dardov
- Cedars-Sinai Board of Governors Regenerative Medicine Institute, Los Angeles, CA, USA
| | - V J Garcia
- Cedars-Sinai Board of Governors Regenerative Medicine Institute, Los Angeles, CA, USA
| | - R Ho
- Cedars-Sinai Board of Governors Regenerative Medicine Institute, Los Angeles, CA, USA
| | - A N Fulton
- Cedars-Sinai Board of Governors Regenerative Medicine Institute, Los Angeles, CA, USA
| | - M R Jones
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Center for Bioinformatics and Functional Genomics, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - K M Roxas
- Cedars-Sinai Board of Governors Regenerative Medicine Institute, Los Angeles, CA, USA
| | - P Avalos
- Cedars-Sinai Board of Governors Regenerative Medicine Institute, Los Angeles, CA, USA
| | - D West
- Cedars-Sinai Board of Governors Regenerative Medicine Institute, Los Angeles, CA, USA
| | - M G Banuelos
- Cedars-Sinai Board of Governors Regenerative Medicine Institute, Los Angeles, CA, USA
| | - Z Shu
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - R Murali
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Samuel Oschin Comprehensive Cancer Institute, Los Angeles, CA, USA
- Research Division of Immunology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - N T Maidment
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - J E Van Eyk
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - M Tagliati
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - C N Svendsen
- Cedars-Sinai Board of Governors Regenerative Medicine Institute, Los Angeles, CA, USA.
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23
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Zhong CQ, Wu R, Chen X, Wu S, Shuai J, Han J. Systematic Assessment of the Effect of Internal Library in Targeted Analysis of SWATH-MS. J Proteome Res 2019; 19:477-492. [DOI: 10.1021/acs.jproteome.9b00669] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Chuan-Qi Zhong
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cellular Signaling Network, School of Life Sciences, Xiamen University, Xiamen 361102, China
| | - Rui Wu
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cellular Signaling Network, School of Life Sciences, Xiamen University, Xiamen 361102, China
| | - Xi Chen
- Medical Research Institute, Wuhan University, Wuhan 430072, China
- SpecAlly Life Technology Co., Ltd., Wuhan 430072, China
| | - Suqin Wu
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cellular Signaling Network, School of Life Sciences, Xiamen University, Xiamen 361102, China
| | - Jianwei Shuai
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cellular Signaling Network, School of Life Sciences, Xiamen University, Xiamen 361102, China
- Department of Physics, Xiamen University, Xiamen 361005, China
| | - Jiahuai Han
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cellular Signaling Network, School of Life Sciences, Xiamen University, Xiamen 361102, China
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24
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Noor Z, Ranganathan S. Bioinformatics approaches for improving seminal plasma proteome analysis. Theriogenology 2019; 137:43-49. [PMID: 31186128 DOI: 10.1016/j.theriogenology.2019.05.036] [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: 10/26/2022]
Abstract
Reproduction efficiency of male animals is one of the key factors influencing the sustainability of livestock. Mass spectrometry (MS) based proteomics has become an important tool for studying seminal plasma proteomes. In this review, we summarize bioinformatics analysis strategies for current proteomics approaches, for identifying novel biomarkers of reproductive robustness.
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Affiliation(s)
- Zainab Noor
- Department of Molecular Sciences, Macquarie University, Sydney, Australia
| | - Shoba Ranganathan
- Department of Molecular Sciences, Macquarie University, Sydney, Australia.
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25
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Fert-Bober J, Murray CI, Parker SJ, Van Eyk JE. Precision Profiling of the Cardiovascular Post-Translationally Modified Proteome: Where There Is a Will, There Is a Way. Circ Res 2019; 122:1221-1237. [PMID: 29700069 DOI: 10.1161/circresaha.118.310966] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
There is an exponential increase in biological complexity as initial gene transcripts are spliced, translated into amino acid sequence, and post-translationally modified. Each protein can exist as multiple chemical or sequence-specific proteoforms, and each has the potential to be a critical mediator of a physiological or pathophysiological signaling cascade. Here, we provide an overview of how different proteoforms come about in biological systems and how they are most commonly measured using mass spectrometry-based proteomics and bioinformatics. Our goal is to present this information at a level accessible to every scientist interested in mass spectrometry and its application to proteome profiling. We will specifically discuss recent data linking various protein post-translational modifications to cardiovascular disease and conclude with a discussion for enablement and democratization of proteomics across the cardiovascular and scientific community. The aim is to inform and inspire the readership to explore a larger breadth of proteoform, particularity post-translational modifications, related to their particular areas of expertise in cardiovascular physiology.
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Affiliation(s)
- Justyna Fert-Bober
- From the Advanced Clinical BioSystems Research Institute, Smidt Heart Institute, Department of Medicine, Cedars Sinai Medical Center, Los Angeles, CA
| | - Christopher I Murray
- From the Advanced Clinical BioSystems Research Institute, Smidt Heart Institute, Department of Medicine, Cedars Sinai Medical Center, Los Angeles, CA
| | - Sarah J Parker
- From the Advanced Clinical BioSystems Research Institute, Smidt Heart Institute, Department of Medicine, Cedars Sinai Medical Center, Los Angeles, CA.
| | - Jennifer E Van Eyk
- From the Advanced Clinical BioSystems Research Institute, Smidt Heart Institute, Department of Medicine, Cedars Sinai Medical Center, Los Angeles, CA
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26
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Noor Z, Wu JX, Pascovici D, Mohamedali A, Molloy MP, Baker MS, Ranganathan S. iSwathX: an interactive web-based application for extension of DIA peptide reference libraries. Bioinformatics 2018; 35:538-539. [DOI: 10.1093/bioinformatics/bty660] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Accepted: 07/20/2018] [Indexed: 11/14/2022] Open
Affiliation(s)
- Zainab Noor
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia
| | - Jemma X Wu
- Australian Proteome Analysis Facility (APAF), Macquarie University, Sydney, NSW, Australia
| | - Dana Pascovici
- Australian Proteome Analysis Facility (APAF), Macquarie University, Sydney, NSW, Australia
| | - Abidali Mohamedali
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia
| | - Mark P Molloy
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia
- Australian Proteome Analysis Facility (APAF), Macquarie University, Sydney, NSW, Australia
| | - Mark S Baker
- Department of Biomedical Sciences, Macquarie University, Sydney, NSW, Australia
| | - Shoba Ranganathan
- Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia
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27
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Parker SJ, Stotland A, MacFarlane E, Wilson N, Orosco A, Venkatraman V, Madrid K, Gottlieb R, Dietz HC, Van Eyk JE. Proteomics reveals Rictor as a noncanonical TGF-β signaling target during aneurysm progression in Marfan mice. Am J Physiol Heart Circ Physiol 2018; 315:H1112-H1126. [PMID: 30004239 DOI: 10.1152/ajpheart.00089.2018] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
The objective of the present study was to 1) analyze the ascending aortic proteome within a mouse model of Marfan syndrome (MFS; Fbn1C1041G/+) at early and late stages of aneurysm and 2) subsequently test a novel hypothesis formulated on the basis of this unbiased proteomic screen that links changes in integrin composition to transforming growth factor (TGF)-β-dependent activation of the rapamycin-independent component of mammalian target of rapamycin (Rictor) signaling pathway. Ingenuity Pathway Analysis of over 1,000 proteins quantified from the in vivo MFS mouse aorta by data-independent acquisition mass spectrometry revealed a predicted upstream regulator, Rictor, that was selectively activated in aged MFS mice. We validated this pattern of Rictor activation in vivo by Western blot analysis for phosphorylation on Thr1135 in a separate cohort of mice and showed in vitro that TGF-β activates Rictor in an integrin-linked kinase-dependent manner in cultured aortic vascular smooth muscle cells. Expression of β3-integrin was upregulated in the aged MFS aorta relative to young MFS mice and wild-type mice. We showed that β3-integrin expression and activation modulated TGF-β-induced Rictor phosphorylation in vitro, and this signaling effect was associated with an altered vascular smooth muscle cell proliferative-migratory and metabolic in vitro phenotype that parallels the in vivo aneurysm phenotype in MFS. These results reveal that Rictor is a novel, context-dependent, noncanonical TGF-β signaling effector with potential pathogenic implications in aortic aneurysm. NEW & NOTEWORTHY We present the most comprehensive quantitative analysis of the ascending aortic aneurysm proteome in Marfan syndrome to date resulting in novel and potentially wide-reaching findings that expression and signaling by β3-integrin constitute a modulator of transforming growth factor-β-induced rapamycin-independent component of mammalian target of rapamycin (Rictor) signaling and physiology in aortic vascular smooth muscle cells.
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Affiliation(s)
- Sarah J Parker
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars-Sinai Medical Center , Los Angeles, California.,Institute for Genetic Medicine, Johns Hopkins University , Baltimore, Maryland
| | - Aleksandr Stotland
- Molecular Cardiobiology, The Heart Institute, Cedars-Sinai Medical Center , Los Angeles, California
| | - Elena MacFarlane
- Institute for Genetic Medicine, Johns Hopkins University , Baltimore, Maryland
| | - Nicole Wilson
- Institute for Genetic Medicine, Johns Hopkins University , Baltimore, Maryland
| | - Amanda Orosco
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars-Sinai Medical Center , Los Angeles, California
| | - Vidya Venkatraman
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars-Sinai Medical Center , Los Angeles, California.,Institute for Genetic Medicine, Johns Hopkins University , Baltimore, Maryland
| | - Kyle Madrid
- Biomedical Sciences, Cedars-Sinai Medical Center , Los Angeles, California
| | - Roberta Gottlieb
- Molecular Cardiobiology, The Heart Institute, Cedars-Sinai Medical Center , Los Angeles, California
| | - Harry C Dietz
- Institute for Genetic Medicine, Johns Hopkins University , Baltimore, Maryland.,Howard Hughes Medical Institute , Chevy Chase, Maryland
| | - Jennifer E Van Eyk
- Advanced Clinical Biosystems Research Institute, The Smidt Heart Institute, Cedars-Sinai Medical Center , Los Angeles, California.,Institute for Genetic Medicine, Johns Hopkins University , Baltimore, Maryland
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28
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Teleman J, Hauri S, Malmström J. Improvements in Mass Spectrometry Assay Library Generation for Targeted Proteomics. J Proteome Res 2017; 16:2384-2392. [PMID: 28516777 DOI: 10.1021/acs.jproteome.6b00928] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
In data-independent acquisition mass spectrometry (DIA-MS), targeted extraction of peptide signals in silico using mass spectrometry assay libraries is a successful method for the identification and quantification of proteins. However, it remains unclear if high quality assay libraries with more accurate peptide ion coordinates can improve peptide target identification rates in DIA analysis. In this study, we systematically improved and evaluated the common algorithmic steps for assay library generation and demonstrate that increased assay quality results in substantially higher identification rates of peptide targets from mouse organ protein lysates measured by DIA-MS. The introduced changes are (1) a new spectrum interpretation algorithm, (2) reapplication of segmented retention time normalization, (3) a ppm fragment mass error matching threshold, (4) usage of internal peptide fragments, and (5) a multilevel false discovery rate calculation. Taken together, these changes yielded 14-36% more identified peptide targets at 1% assay false discovery rate and are implemented in three new open source tools, Fraggle, Tramler, and Franklin, available at https://github.com/fickludd/eviltools . The improved algorithms provide ways to better utilize discovery MS data, translating to substantially increased DIA performance and ultimately better foundations for drawing biological conclusions in DIA-based experiments.
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Affiliation(s)
- Johan Teleman
- Department of Clinical Sciences, Lund University , BMC D13, 221 84 Lund, Sweden.,Department of Immunotechnology, Lund University , Medicon Village (Building 406), 223 81 Lund, Sweden
| | - Simon Hauri
- Department of Clinical Sciences, Lund University , BMC D13, 221 84 Lund, Sweden
| | - Johan Malmström
- Department of Clinical Sciences, Lund University , BMC D13, 221 84 Lund, Sweden
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29
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van den Broek I, Fu Q, Kushon S, Kowalski MP, Millis K, Percy A, Holewinski RJ, Venkatraman V, Van Eyk JE. Application of volumetric absorptive microsampling for robust, high-throughput mass spectrometric quantification of circulating protein biomarkers. CLINICAL MASS SPECTROMETRY 2017. [DOI: 10.1016/j.clinms.2017.08.004] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
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