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Navarrete-Perea J, Li J, Mitchell DC, Chi A. Synthetic Knockout Protein Standard for Evaluating Interference in Tandem Mass Tag-Based Proteomics. Anal Chem 2024; 96:6836-6846. [PMID: 38640495 DOI: 10.1021/acs.analchem.4c00871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2024]
Abstract
Isobaric labeling is widely used for unbiased, proteome-wide studies, and it provides several advantages, such as fewer missing values among samples and higher quantitative precision. However, ion interference may lead to compressed or distorted observed ratios due to the coelution and coanalysis of peptides. Here, we introduced a synthetic KnockOut standard (sKO) for evaluating interference in tandem mass tags-based proteomics. sKO is made by mixing TMTpro-labeled tryptic peptides derived from four nonhuman proteins and a whole human proteome as background at different proportions. We showcased the utility of the sKO standard by exploring ion interference at different peptide concentrations (up to a 30-fold change in abundance) and using a variety of mass spectrometer data acquisition strategies. We also demonstrated that the sKO standard could provide valuable information for the rational design of acquisition strategies to achieve optimal data quality and discussed its potential applications for high-throughput proteomics workflows development.
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Affiliation(s)
| | - Jiaming Li
- Merck & Co., Inc., Cambridge, Massachusetts 02115, United States
| | | | - An Chi
- Merck & Co., Inc., Cambridge, Massachusetts 02115, United States
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Bowser BL, Patterson KL, Robinson RA. Evaluating cPILOT Data toward Quality Control Implementation. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:1741-1752. [PMID: 37459602 DOI: 10.1021/jasms.3c00179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/03/2023]
Abstract
Multiplexing enables the monitoring of hundreds to thousands of proteins in quantitative proteomics analyses and increases sample throughput. In most mass-spectrometry-based proteomics workflows, multiplexing is achieved by labeling biological samples with heavy isotopes via precursor isotopic labeling or isobaric tagging. Enhanced multiplexing strategies, such as combined precursor isotopic labeling and isobaric tagging (cPILOT), combine multiple technologies to afford an even higher sample throughput. Critical to enhanced multiplexing analyses is ensuring that analytical performance is optimal and that missingness of sample channels is minimized. Automation of sample preparation steps and use of quality control (QC) metrics can be incorporated into multiplexing analyses and reduce the likelihood of missing information, thus maximizing the amount of usable quantitative data. Here, we implemented QC metrics previously developed in our laboratory to evaluate a 36-plex cPILOT experiment that encompassed 144 mouse samples of various tissue types, time points, genotypes, and biological replicates. The evaluation focuses on the use of a sample pool generated from all samples in the experiment to monitor the daily instrument performance and to provide a means for data normalization across sample batches. Our results show that tracking QC metrics enabled the quantification of ∼7000 proteins in each sample batch, of which ∼70% had minimal missing values across up to 36 sample channels. Implementation of QC metrics for future cPILOT studies as well as other enhanced multiplexing strategies will help yield high-quality data sets.
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Affiliation(s)
- Bailey L Bowser
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - Khiry L Patterson
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - Renã As Robinson
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, United States
- Vanderbilt Memory & Alzheimer's Center, Nashville, Tennessee 37212, United States
- Vanderbilt Institute of Chemical Biology, Nashville, Tennessee 37232, United States
- Vanderbilt Brain Institute, Nashville, Tennessee 37232, United States
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Zhang T, Keele GR, Gyuricza IG, Vincent M, Brunton C, Bell TA, Hock P, Shaw GD, Munger SC, de Villena FPM, Ferris MT, Paulo JA, Gygi SP, Churchill GA. Multi-omics analysis identifies drivers of protein phosphorylation. Genome Biol 2023; 24:52. [PMID: 36944993 PMCID: PMC10031968 DOI: 10.1186/s13059-023-02892-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 03/09/2023] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND Phosphorylation of proteins is a key step in the regulation of many cellular processes including activation of enzymes and signaling cascades. The abundance of a phosphorylated peptide (phosphopeptide) is determined by the abundance of its parent protein and the proportion of target sites that are phosphorylated. RESULTS We quantified phosphopeptides, proteins, and transcripts in heart, liver, and kidney tissue samples of mice from 58 strains of the Collaborative Cross strain panel. We mapped ~700 phosphorylation quantitative trait loci (phQTL) across the three tissues and applied genetic mediation analysis to identify causal drivers of phosphorylation. We identified kinases, phosphatases, cytokines, and other factors, including both known and potentially novel interactions between target proteins and genes that regulate site-specific phosphorylation. Our analysis highlights multiple targets of pyruvate dehydrogenase kinase 1 (PDK1), a regulator of mitochondrial function that shows reduced activity in the NZO/HILtJ mouse, a polygenic model of obesity and type 2 diabetes. CONCLUSIONS Together, this integrative multi-omics analysis in genetically diverse CC strains provides a powerful tool to identify regulators of protein phosphorylation. The data generated in this study provides a resource for further exploration.
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Affiliation(s)
- Tian Zhang
- Harvard Medical School, Boston, MA, 02115, USA
| | | | | | | | | | - Timothy A Bell
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Pablo Hock
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Ginger D Shaw
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | | | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Martin T Ferris
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
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Paulo JA. Isobaric labeling: Expanding the breadth, accuracy, depth, and diversity of sample multiplexing. Proteomics 2022; 22:e2200328. [PMID: 36089831 PMCID: PMC10777124 DOI: 10.1002/pmic.202200328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 08/25/2022] [Accepted: 08/26/2022] [Indexed: 11/10/2022]
Abstract
Isobaric labeling has rapidly become a predominant strategy for proteome-wide abundance measurements. Coupled to mass spectrometry, sample multiplexing techniques using isobaric labeling are unparalleled for profiling proteins and posttranslational modifications across multiple samples in a single experiment. Here, I highlight aspects of isobaric labeling in the context of expanding the breadth of multiplexing, improving quantitative accuracy and proteome depth, and developing a wide range of diverse applications. I underscore two facets that enhance quantitative accuracy and reproducibility, specifically the availability of quality control standards for isobaric labeling experiments and the evolution of data acquisition methods. I also emphasize the necessity for standardized methodologies, particularly for emerging high-throughput workflows. Future developments in sample multiplexing will further strengthen the importance of isobaric labeling for comprehensive proteome profiling.
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Affiliation(s)
- Joao A Paulo
- Department of Cell Biology, Blavatnik Institute at Harvard Medical School, Boston, Massachusetts, USA
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5
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Zhang T. TMT29 plex: Higher order multiplexing with inherent interference correction. Proteomics 2022; 22:e2200260. [PMID: 36263995 DOI: 10.1002/pmic.202200260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 08/03/2022] [Accepted: 08/09/2022] [Indexed: 06/08/2023]
Abstract
Tandem mass tag (TMT) technology enables mass spectrometry-based multiplexed sample profiling of protein abundance. The degree of isobaric labeling with TMT has increased from 2 to 6, 11, 16 [1] and recently 18 [2] channels, enabling the development of higher throughput assays. In TMT experiments, measurement of reporter tag intensities is confounded by ratio compression. Although both pre- and post-acquisition methods have been developed to decrease interference, ratio compression remains a problem in complex samples. The work of Sun et al. presented a TMT29-plex workflow that combines the TMT11-plex and TMTpro18-plex labeling strategies and uses their inherent features to address the ratio compression problem, increasing the TMT throughput and quantitative accuracy for potential applications [3].
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Affiliation(s)
- Tian Zhang
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, USA
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Gerdes Gyuricza I, Chick JM, Keele GR, Deighan AG, Munger SC, Korstanje R, Gygi SP, Churchill GA. Genome-wide transcript and protein analysis highlights the role of protein homeostasis in the aging mouse heart. Genome Res 2022; 32:838-852. [PMID: 35277432 PMCID: PMC9104701 DOI: 10.1101/gr.275672.121] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 03/09/2022] [Indexed: 11/25/2022]
Abstract
Investigation of the molecular mechanisms of aging in the human heart is challenging because of confounding factors, such as diet and medications, as well as limited access to tissues from healthy aging individuals. The laboratory mouse provides an ideal model to study aging in healthy individuals in a controlled environment. However, previous mouse studies have examined only a narrow range of the genetic variation that shapes individual differences during aging. Here, we analyze transcriptome and proteome data from 185 genetically diverse male and female mice at ages 6, 12, and 18 mo to characterize molecular changes that occur in the aging heart. Transcripts and proteins reveal activation of pathways related to exocytosis and cellular transport with age, whereas processes involved in protein folding decrease with age. Additional changes are apparent only in the protein data including reduced fatty acid oxidation and increased autophagy. For proteins that form complexes, we see a decline in correlation between their component subunits with age, suggesting age-related loss of stoichiometry. The most affected complexes are themselves involved in protein homeostasis, which potentially contributes to a cycle of progressive breakdown in protein quality control with age. Our findings highlight the important role of post-transcriptional regulation in aging. In addition, we identify genetic loci that modulate age-related changes in protein homeostasis, suggesting that genetic variation can alter the molecular aging process.
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Affiliation(s)
| | - Joel M Chick
- Vividion Therapeutics, San Diego, California 92121, USA
| | | | | | | | - Ron Korstanje
- The Jackson Laboratory, Bar Harbor, Maine 04609, USA
| | - Steven P Gygi
- Harvard Medical School, Boston, Massachusetts 02115, USA
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Navarrete-Perea J, Liu X, Rad R, Gygi JP, Gygi SP, Paulo JA. Assessing interference in isobaric tag-based sample multiplexing using an 18-plex interference standard. Proteomics 2021; 22:e2100317. [PMID: 34918453 DOI: 10.1002/pmic.202100317] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 12/09/2021] [Accepted: 12/09/2021] [Indexed: 11/06/2022]
Abstract
Reporter ion interference remains a limitation of isobaric tag-based sample multiplexing. Advances in instrumentation and data acquisition modes, such as the recently developed real-time database search (RTS), can reduce interference. However, interference persists as does the need to benchmark upstream sample preparation and data acquisition strategies. Here, we present an updated Triple yeast KnockOut (TKO) standard as well as corresponding upgrades to the TKO Viewing Tool (TVT2.5, http://tko.hms.harvard.edu/). Specifically, we expand the TKO standard to incorporate the TMTpro18-plex reagents (TKO18). We also construct a variant thereof which has been digested only with LysC (TKO18L). We compare proteome coverage and interference levels of TKO18 and TKO18L data that are acquired under different data acquisition modes and analyzed using TVT2.5. Our data illustrate that RTS reduces interference while improving proteome coverage and suggest that digesting with LysC alone only modestly reduces interference, albeit at the expense of proteome depth. Collectively, the two new TKO standards coupled with the updated TVT represent a convenient and versatile platform for assessing and developing methods to reduce interference in isobaric tag-based experiments. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Jose Navarrete-Perea
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Xinyue Liu
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Ramin Rad
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Jeremy P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Joao A Paulo
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, 02115, USA
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Popow O, Liu X, Haigis KM, Gygi SP, Paulo JA. A Compendium of Murine (Phospho)Peptides Encompassing Different Isobaric Labeling and Data Acquisition Strategies. J Proteome Res 2021; 20:3678-3688. [PMID: 34043369 PMCID: PMC8254770 DOI: 10.1021/acs.jproteome.1c00247] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Targeted mass spectrometry-based assays typically rely on previously acquired large data sets for peptide target selection. Such repositories are widely available for unlabeled peptides. However, they are less common for isobaric tagged peptides. Here we have assembled two series of six data sets originating from a mouse embryonic fibroblast cell line (NIH/3T3). One series is of peptides derived from a tryptic digest of a whole cell proteome and a second from enriched phosphopeptides. These data sets encompass three labeling approaches (unlabeled, TMT11-labeled, and TMTpro16-labeled) and two data acquisition strategies (ion trap MS2 with and without FAIMS-based gas phase separation). We identified a total of 1 509 526 peptide-spectrum matches which covered 11 482 proteins from the whole cell proteome tryptic digest, and 188 849 phosphopeptides from the phosphopeptide enrichment. The data sets were of similar depth, and while overlap across data sets was modest, protein overlap was high, thus reinforcing the comprehensiveness of these data sets. The data also supported FAIMS as a means to increase data set depth. These data sets provide a rich resource of peptides that may be used as starting points for targeted assays. Future data sets may be compiled for any genome-sequenced organism using the technologies and strategies highlighted herein. The data have been deposited in the ProteomeXchange Consortium with data set identifier PXD024298.
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Affiliation(s)
- Olesja Popow
- Department of Cancer Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Xinyue Liu
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Kevin M Haigis
- Department of Cancer Biology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts 02115, United States
| | - Joao A Paulo
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts 02115, United States
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