1
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Goel RK, Bithi N, Emili A. Trends in co-fractionation mass spectrometry: A new gold-standard in global protein interaction network discovery. Curr Opin Struct Biol 2024; 88:102880. [PMID: 38996623 DOI: 10.1016/j.sbi.2024.102880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2024] [Revised: 06/13/2024] [Accepted: 06/19/2024] [Indexed: 07/14/2024]
Abstract
Co-fractionation mass spectrometry (CF-MS) uses biochemical fractionation to isolate and characterize macromolecular complexes from cellular lysates without the need for affinity tagging or capture. In recent years, this has emerged as a powerful technique for elucidating global protein-protein interaction networks in a wide variety of biospecimens. This review highlights the latest advancements in CF-MS experimental workflows including machine learning-guided analyses, for uncovering dynamic and high-resolution protein interaction landscapes with enhanced sensitivity, accuracy and throughput, enabling better biophysical characterization of endogenous protein complexes. By addressing challenges and emergent opportunities in the field, this review underscores the transformative potential of CF-MS in advancing our understanding of functional protein interaction networks in health and disease.
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Affiliation(s)
- Raghuveera Kumar Goel
- Division of Oncology, Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University (OHSU), Portland, OR, USA.
| | - Nazmin Bithi
- Division of Oncology, Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University (OHSU), Portland, OR, USA
| | - Andrew Emili
- Division of Oncology, Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University (OHSU), Portland, OR, USA.
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2
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Alves G, Ogurtsov AY, Porterfield H, Maity T, Jenkins LM, Sacks DB, Yu YK. Multiplexing the Identification of Microorganisms via Tandem Mass Tag Labeling Augmented by Interference Removal through a Novel Modification of the Expectation Maximization Algorithm. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:1138-1155. [PMID: 38740383 PMCID: PMC11157548 DOI: 10.1021/jasms.3c00445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 04/12/2024] [Accepted: 04/17/2024] [Indexed: 05/16/2024]
Abstract
Having fast, accurate, and broad spectrum methods for the identification of microorganisms is of paramount importance to public health, research, and safety. Bottom-up mass spectrometer-based proteomics has emerged as an effective tool for the accurate identification of microorganisms from microbial isolates. However, one major hurdle that limits the deployment of this tool for routine clinical diagnosis, and other areas of research such as culturomics, is the instrument time required for the mass spectrometer to analyze a single sample, which can take ∼1 h per sample, when using mass spectrometers that are presently used in most institutes. To address this issue, in this study, we employed, for the first time, tandem mass tags (TMTs) in multiplex identifications of microorganisms from multiple TMT-labeled samples in one MS/MS experiment. A difficulty encountered when using TMT labeling is the presence of interference in the measured intensities of TMT reporter ions. To correct for interference, we employed in the proposed method a modified version of the expectation maximization (EM) algorithm that redistributes the signal from ion interference back to the correct TMT-labeled samples. We have evaluated the sensitivity and specificity of the proposed method using 94 MS/MS experiments (covering a broad range of protein concentration ratios across TMT-labeled channels and experimental parameters), containing a total of 1931 true positive TMT-labeled channels and 317 true negative TMT-labeled channels. The results of the evaluation show that the proposed method has an identification sensitivity of 93-97% and a specificity of 100% at the species level. Furthermore, as a proof of concept, using an in-house-generated data set composed of some of the most common urinary tract pathogens, we demonstrated that by using the proposed method the mass spectrometer time required per sample, using a 1 h LC-MS/MS run, can be reduced to 10 and 6 min when samples are labeled with TMT-6 and TMT-10, respectively. The proposed method can also be used along with Orbitrap mass spectrometers that have faster MS/MS acquisition rates, like the recently released Orbitrap Astral mass spectrometer, to further reduce the mass spectrometer time required per sample.
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Affiliation(s)
- Gelio Alves
- National
Center for Biotechnology Information, National Library of Medicine,
National Institutes of Health, Bethesda, Maryland 20894, United States
| | - Aleksey Y. Ogurtsov
- National
Center for Biotechnology Information, National Library of Medicine,
National Institutes of Health, Bethesda, Maryland 20894, United States
| | - Harry Porterfield
- Department
of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Tapan Maity
- Laboratory
of Cell Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Lisa M. Jenkins
- Laboratory
of Cell Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - David B. Sacks
- Department
of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, Maryland 20892, United States
| | - Yi-Kuo Yu
- National
Center for Biotechnology Information, National Library of Medicine,
National Institutes of Health, Bethesda, Maryland 20894, United States
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3
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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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4
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Figueroa-Navedo AM, Ivanov AR. Experimental and data analysis advances in thermal proteome profiling. CELL REPORTS METHODS 2024; 4:100717. [PMID: 38412830 PMCID: PMC10921035 DOI: 10.1016/j.crmeth.2024.100717] [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: 11/06/2023] [Revised: 12/17/2023] [Accepted: 02/05/2024] [Indexed: 02/29/2024]
Abstract
Method development for mass spectrometry (MS)-based thermal shift proteomic assays have advanced to probe small molecules with known and unknown protein-ligand interaction mechanisms and specificity, which is predominantly used in characterization of drug-protein interactions. In the discovery of target and off-target protein-ligand interactions, a thorough investigation of method development and their impact on the sensitivity and accuracy of protein-small molecule and protein-protein interactions is warranted. In this review, we discuss areas of improvement at each stage of thermal proteome profiling data analysis that includes processing of MS-based data, method development, and their effect on the overall quality of thermal proteome profiles. We also overview the optimization of experimental strategies and prioritization of an increased number of independent biological replicates over the number of evaluated temperatures.
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Affiliation(s)
- Amanda M Figueroa-Navedo
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA
| | - Alexander R Ivanov
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA.
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5
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Madern M, Reiter W, Stanek F, Hartl N, Mechtler K, Hartl M. A Causal Model of Ion Interference Enables Assessment and Correction of Ratio Compression in Multiplex Proteomics. Mol Cell Proteomics 2024; 23:100694. [PMID: 38097181 PMCID: PMC10828822 DOI: 10.1016/j.mcpro.2023.100694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 12/01/2023] [Accepted: 12/11/2023] [Indexed: 01/29/2024] Open
Abstract
Multiplex proteomics using isobaric labeling tags has emerged as a powerful tool for the simultaneous relative quantification of peptides and proteins across multiple experimental conditions. However, the quantitative accuracy of the approach is largely compromised by ion interference, a phenomenon that causes fold changes to appear compressed. The degree of compression is generally unknown, and the contributing factors are poorly understood. In this study, we thoroughly characterized ion interference at the MS2 level using a defined two-proteome experimental system with known ground-truth. We discovered remarkably poor agreement between the apparent precursor purity in the isolation window and the actual level of observed reporter ion interference in MS2 scans-a discrepancy that we found resolved by considering cofragmentation of peptide ions hidden within the spectral "noise" of the MS1 isolation window. To address this issue, we developed a regression modeling strategy to accurately predict reporter ion interference in any dataset. Finally, we demonstrate the utility of our procedure for improved fold change estimation and unbiased PTM site-to-protein normalization. All computational tools and code required to apply this method to any MS2 TMT dataset are documented and freely available.
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Affiliation(s)
- Moritz Madern
- Max Perutz Labs, Mass Spectrometry Facility, Vienna Biocenter Campus (VBC), Vienna, Austria; Department for Biochemistry and Cell Biology, Center for Molecular Biology, University of Vienna, Vienna Biocenter Campus (VBC), Vienna, Austria
| | - Wolfgang Reiter
- Max Perutz Labs, Mass Spectrometry Facility, Vienna Biocenter Campus (VBC), Vienna, Austria; Department for Biochemistry and Cell Biology, Center for Molecular Biology, University of Vienna, Vienna Biocenter Campus (VBC), Vienna, Austria
| | - Florian Stanek
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter Campus (VBC), Vienna, Austria
| | - Natascha Hartl
- Max Perutz Labs, Mass Spectrometry Facility, Vienna Biocenter Campus (VBC), Vienna, Austria
| | - Karl Mechtler
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter Campus (VBC), Vienna, Austria
| | - Markus Hartl
- Max Perutz Labs, Mass Spectrometry Facility, Vienna Biocenter Campus (VBC), Vienna, Austria; Department for Biochemistry and Cell Biology, Center for Molecular Biology, University of Vienna, Vienna Biocenter Campus (VBC), Vienna, Austria.
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6
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Shuken SR, McAlister GC, Barshop WD, Canterbury JD, Bergen D, Huang J, Huguet R, Paulo JA, Zabrouskov V, Gygi SP, Yu Q. Deep Proteomic Compound Profiling with the Orbitrap Ascend Tribrid Mass Spectrometer Using Tandem Mass Tags and Real-Time Search. Anal Chem 2023; 95:15180-15188. [PMID: 37811788 PMCID: PMC10785648 DOI: 10.1021/acs.analchem.3c01701] [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] [Indexed: 10/10/2023]
Abstract
Tandem mass tags (TMT) and tribrid mass spectrometers are a powerful combination for high-throughput proteomics with high quantitative accuracy. Increasingly, this technology is being used to map the effects of drugs on the proteome. However, the depth of proteomic profiling is still limited by sensitivity and speed. The new Orbitrap Ascend mass spectrometer was designed to address these limitations with a combination of hardware and software improvements. We evaluated the performance of the Ascend in multiple contexts including deep proteomic profiling. We found that the Ascend exhibited increased sensitivity, yielding higher signal-to-noise ratios than the Orbitrap Eclipse with shorter injection times. As a result, higher numbers of peptides and proteins were identified and quantified, especially with low sample input. TMT measurements had significantly improved signal-to-noise ratios, improving quantitative precision. In a fractionated 16plex sample that profiled proteomic differences across four human cell lines, the Ascend was able to quantify hundreds more proteins than the Eclipse, many of them low-abundant proteins, and the Ascend was able to quantify >8000 proteins in 30% less instrument time. We used the Ascend to analyze 8881 proteins in HCT116 cancer cells treated with covalent sulfolane/sulfolene inhibitors of peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (PIN1), a phosphorylation-specific peptidyl-prolyl cis-trans isomerase implicated in several cancers. We characterized these PIN1 inhibitors' effects on the proteome and identified discrepancies among the different compounds, which will facilitate a better understanding of the structure-activity relationship of this class of compounds. The Ascend was able to quantify statistically significant, potentially therapeutically relevant changes in proteins that the Eclipse could not detect.
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Affiliation(s)
- Steven R Shuken
- Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, Massachusetts 02115, United States
| | - Graeme C McAlister
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - William D Barshop
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - Jesse D Canterbury
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - David Bergen
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - Jingjing Huang
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - Romain Huguet
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - João A Paulo
- Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, Massachusetts 02115, United States
| | - Vlad Zabrouskov
- Thermo Fisher Scientific, 355 River Oaks Pkwy, San Jose, California 95134, United States
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, Massachusetts 02115, United States
| | - Qing Yu
- Department of Cell Biology, Harvard Medical School, 240 Longwood Avenue, Boston, Massachusetts 02115, United States
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7
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Bowser BL, Robinson RAS. Enhanced Multiplexing Technology for Proteomics. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2023; 16:379-400. [PMID: 36854207 DOI: 10.1146/annurev-anchem-091622-092353] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.
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Affiliation(s)
- Bailey L Bowser
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee, USA;
| | - Renã A S Robinson
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee, USA;
- Department of Neurology, Vanderbilt University Medical Center, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt Memory and Alzheimer's Center, Nashville, Tennessee, USA
- Vanderbilt Institute of Chemical Biology, Vanderbilt School of Medicine, Nashville, Tennessee, USA
- Vanderbilt Brain Institute, Vanderbilt School of Medicine, Nashville, Tennessee, USA
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8
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Vajrychova M, Salovska B, Pimkova K, Fabrik I, Hodny Z. SILAC-IodoTMT for Assessment of the Cellular Proteome and Its Redox Status. Methods Mol Biol 2023; 2603:259-268. [PMID: 36370286 DOI: 10.1007/978-1-0716-2863-8_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Stable isotope labeling by amino acids in cell culture (SILAC) and iodoacetyl tandem mass tag (iodoTMT) are well-implemented mass spectrometry-based approaches for quantification of proteins and for site-mapping of cysteine modification. We describe here a combination of SILAC and iodoTMT to assess ongoing changes in the global proteome and cysteine modification levels using liquid chromatography separation coupled with high-resolution mass spectrometry (LC-MS/MS).
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Affiliation(s)
- Marie Vajrychova
- Biomedical Research Center, University Hospital Hradec Kralove, Hradec Kralove, Czech Republic.
| | - Barbora Salovska
- Department of Genome Integrity, Institute of Molecular Genetics of the Czech Academy of Science, Prague, Czech Republic
- Yale Cancer Biology Institute, Yale University, West Haven, CT, USA
| | - Kristyna Pimkova
- Biomedical Research Center, University Hospital Hradec Kralove, Hradec Kralove, Czech Republic
- BIOCEV, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Ivo Fabrik
- Biomedical Research Center, University Hospital Hradec Kralove, Hradec Kralove, Czech Republic
| | - Zdenek Hodny
- Department of Genome Integrity, Institute of Molecular Genetics of the Czech Academy of Science, Prague, Czech Republic
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9
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Sialana F, Roumeliotis TI, Bouguenina H, Chan Wah Hak L, Wang H, Caldwell J, Collins I, Chopra R, Choudhary JS. SimPLIT: Simplified Sample Preparation for Large-Scale Isobaric Tagging Proteomics. J Proteome Res 2022; 21:1842-1856. [PMID: 35848491 PMCID: PMC9361352 DOI: 10.1021/acs.jproteome.2c00092] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Large scale proteomic profiling of cell lines can reveal molecular signatures attributed to variable genotypes or induced perturbations, enabling proteogenomic associations and elucidation of pharmacological mechanisms of action. Although isobaric labeling has increased the throughput of proteomic analysis, the commonly used sample preparation workflows often require time-consuming steps and costly consumables, limiting their suitability for large scale studies. Here, we present a simplified and cost-effective one-pot reaction workflow in a 96-well plate format (SimPLIT) that minimizes processing steps and demonstrates improved reproducibility compared to alternative approaches. The workflow is based on a sodium deoxycholate lysis buffer and a single detergent cleanup step after peptide labeling, followed by quick off-line fractionation and MS2 analysis. We showcase the applicability of the workflow in a panel of colorectal cancer cell lines and by performing target discovery for a set of molecular glue degraders in different cell lines, in a 96-sample assay. Using this workflow, we report frequently dysregulated proteins in colorectal cancer cells and uncover cell-dependent protein degradation profiles of seven cereblon E3 ligase modulators (CRL4CRBN). Overall, SimPLIT is a robust method that can be easily implemented in any proteomics laboratory for medium-to-large scale TMT-based studies for deep profiling of cell lines.
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Affiliation(s)
- Fernando
J. Sialana
- Functional
Proteomics Group, The Institute of Cancer Research, Chester Beatty Laboratories, London SW3 6JB, U.K.
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Theodoros I. Roumeliotis
- Functional
Proteomics Group, The Institute of Cancer Research, Chester Beatty Laboratories, London SW3 6JB, U.K.
| | - Habib Bouguenina
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Laura Chan Wah Hak
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Hannah Wang
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - John Caldwell
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Ian Collins
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Rajesh Chopra
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Jyoti S. Choudhary
- Functional
Proteomics Group, The Institute of Cancer Research, Chester Beatty Laboratories, London SW3 6JB, U.K.
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10
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Konno R, Matsui T, Ito H, Kawashima Y, Itakura M, Kodera Y. Highly accurate and precise quantification strategy using stable isotope dimethyl labeling coupled with GeLC-MS/MS. Biochem Biophys Res Commun 2021; 550:37-42. [PMID: 33684618 DOI: 10.1016/j.bbrc.2021.02.101] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 02/22/2021] [Indexed: 02/08/2023]
Abstract
Shotgun proteomics is a powerful method for comprehensively identifying and quantifying tryptic peptides, but it is difficult to analyze proteolytic events. One-dimensional gel and liquid chromatography-tandem mass spectrometry (GeLC-MS/MS) enables the separation of proteolytic fragments using SDS-PAGE followed by identification using LC-MS/MS. GeLC-MS/MS is thus an excellent method for identifying fragmentation. However, the lower reproducibility of gel extraction and nano flow LC-MS/MS can produce inaccurate results in comparative analyses of protein quantification among samples. In this study, a novel GeLC-MS/MS method coupled with stable isotope dimethyl labeling was developed. In the method, a mixture of light- and heavy-labeled samples is loaded onto an SDS-PAGE gel, and proteins with different isotopes in one extracted band are quantitatively analyzed by one-shot injection. This procedure enables accurate determination of the abundance ratio of peptides between two samples, even in cases of low peptide abundance, and it is not affected by the reproducibility of the gel extraction or LC-MS procedures. Therefore, our new GeLC-MS/MS method coupled with stable isotope dimethyl labeling provides high accuracy and comprehensive peptide comparisons, enabling the detection of proteolysis events caused by disease or physiological processes.
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Affiliation(s)
- Ryo Konno
- Department of Physics, School of Science, Kitasato University, 1-15-1 Kitasato, Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan
| | - Takashi Matsui
- Department of Physics, School of Science, Kitasato University, 1-15-1 Kitasato, Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan; Center for Disease Proteomics, School of Science, Kitasato University, 1-15-1 Kitasato, Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan
| | - Hiroaki Ito
- Department of Physics, School of Science, Kitasato University, 1-15-1 Kitasato, Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan
| | - Yusuke Kawashima
- Department of Applied Genomics, Kazusa DNA Research Institute, 2-6-7 Kazusakamatari, Kisarazu, Chiba, 292-0818, Japan
| | - Makoto Itakura
- Center for Disease Proteomics, School of Science, Kitasato University, 1-15-1 Kitasato, Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan; Department of Biochemistry, Kitasato University School of Medicine, 1-15-1 Kitasato, Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan
| | - Yoshio Kodera
- Department of Physics, School of Science, Kitasato University, 1-15-1 Kitasato, Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan; Center for Disease Proteomics, School of Science, Kitasato University, 1-15-1 Kitasato, Minami-ku, Sagamihara, Kanagawa, 252-0373, Japan.
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11
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Zinn N, Werner T, Doce C, Mathieson T, Boecker C, Sweetman G, Fufezan C, Bantscheff M. Improved Proteomics-Based Drug Mechanism-of-Action Studies Using 16-Plex Isobaric Mass Tags. J Proteome Res 2021; 20:1792-1801. [PMID: 33621079 DOI: 10.1021/acs.jproteome.0c00900] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Multiplexed quantitative proteomics enabled complex workflows to study the mechanisms by which small molecule drugs interact with the proteome such as thermal proteome profiling (TPP) or multiplexed proteome dynamics profiling (mPDP). TPP measures changes in protein thermal stability in response to drug treatment and thus informs on direct targets and downstream regulation events, while the mPDP approach enables the discovery of regulated protein synthesis and degradation events caused by small molecules and other perturbations. The isobaric mass tags available for multiplexed proteomics have thus far limited the efficiency and sensitivity by which such experiments could be performed. Here we evaluate a recent generation of 16-plex isobaric mass tags and demonstrate the sensitive and time efficient identification of Staurosporine targets in HepG2 cell extracts by recording full thermal denaturation/aggregation profiles of vehicle and compound treated samples in a single mass spectrometry experiment. In 2D-TPP experiments, isothermal titration over seven concentrations per temperature enabled comprehensive selectivity profiling of Staurosporine with EC50 values for kinase targets tightly matching to the kinobeads gold standard assay. Finally, we demonstrate time and condition-based multiplexing of dynamic SILAC labeling experiments to delineate proteome-wide effects of the molecular glue Indisulam on synthesis and degradation rates.
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Affiliation(s)
- Nico Zinn
- Cellzome GmbH, a GSK Company, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Thilo Werner
- Cellzome GmbH, a GSK Company, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Carola Doce
- Cellzome GmbH, a GSK Company, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Toby Mathieson
- Cellzome GmbH, a GSK Company, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Christine Boecker
- Cellzome GmbH, a GSK Company, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Gavain Sweetman
- Cellzome GmbH, a GSK Company, Meyerhofstr. 1, 69117 Heidelberg, Germany
| | - Christian Fufezan
- Cellzome GmbH, a GSK Company, Meyerhofstr. 1, 69117 Heidelberg, Germany.,Institute of Pharmacy and Molecular Biotechnology, Heidelberg University, 69120 Heidelberg, Germany
| | - Marcus Bantscheff
- Cellzome GmbH, a GSK Company, Meyerhofstr. 1, 69117 Heidelberg, Germany
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12
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Chen CT, Wang JH, Cheng CW, Hsu WC, Ko CL, Choong WK, Sung TY. Multi-Q 2 software facilitates isobaric labeling quantitation analysis with improved accuracy and coverage. Sci Rep 2021; 11:2233. [PMID: 33500498 PMCID: PMC7838301 DOI: 10.1038/s41598-021-81740-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 01/06/2021] [Indexed: 12/12/2022] Open
Abstract
Mass spectrometry-based proteomics using isobaric labeling for multiplex quantitation has become a popular approach for proteomic studies. We present Multi-Q 2, an isobaric-labeling quantitation tool which can yield the largest quantitation coverage and improved quantitation accuracy compared to three state-of-the-art methods. Multi-Q 2 supports identification results from several popular proteomic data analysis platforms for quantitation, offering up to 12% improvement in quantitation coverage for accepting identification results from multiple search engines when compared with MaxQuant and PatternLab. It is equipped with various quantitation algorithms, including a ratio compression correction algorithm, and results in up to 336 algorithmic combinations. Systematic evaluation shows different algorithmic combinations have different strengths and are suitable for different situations. We also demonstrate that the flexibility of Multi-Q 2 in customizing algorithmic combination can lead to improved quantitation accuracy over existing tools. Moreover, the use of complementary algorithmic combinations can be an effective strategy to enhance sensitivity when searching for biomarkers from differentially expressed proteins in proteomic experiments. Multi-Q 2 provides interactive graphical interfaces to process quantitation and to display ratios at protein, peptide, and spectrum levels. It also supports a heatmap module, enabling users to cluster proteins based on their abundance ratios and to visualize the clustering results. Multi-Q 2 executable files, sample data sets, and user manual are freely available at http://ms.iis.sinica.edu.tw/COmics/Software_Multi-Q2.html.
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Affiliation(s)
- Ching-Tai Chen
- Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei, 115, Taiwan.
| | - Jen-Hung Wang
- Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei, 115, Taiwan.,Bioinformatics Program, Taiwan International Graduate Program, Academia Sinica, Taipei, 115, Taiwan.,Institute of Biomedical Informatics, National Yang-Ming University, Taipei, 112, Taiwan
| | - Cheng-Wei Cheng
- Genomics Research Center, Academia Sinica, Taipei, 115, Taiwan
| | - Wei-Che Hsu
- Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei, 115, Taiwan
| | - Chu-Ling Ko
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, 92093, USA
| | - Wai-Kok Choong
- Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei, 115, Taiwan
| | - Ting-Yi Sung
- Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei, 115, Taiwan.
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13
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Vitrinel B, Iannitelli DE, Mazzoni EO, Christiaen L, Vogel C. Simple Method to Quantify Protein Abundances from 1000 Cells. ACS OMEGA 2020; 5:15537-15546. [PMID: 32637829 PMCID: PMC7331059 DOI: 10.1021/acsomega.0c01191] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 06/09/2020] [Indexed: 05/29/2023]
Abstract
The rise of single-cell transcriptomics has created an urgent need for similar approaches that use a minimal number of cells to quantify expression levels of proteins. We integrated and optimized multiple recent developments to establish a proteomics workflow to quantify proteins from as few as 1000 mammalian stem cells. The method uses chemical peptide labeling, does not require specific equipment other than cell lysis tools, and quantifies >2500 proteins with high reproducibility. We validated the method by comparing mouse embryonic stem cells and in vitro differentiated motor neurons. We identify differentially expressed proteins with small fold changes and a dynamic range in abundance similar to that of standard methods. Protein abundance measurements obtained with our protocol compared well to corresponding transcript abundance and to measurements using standard inputs. The protocol is also applicable to other systems, such as fluorescence-activated cell sorting (FACS)-purified cells from the tunicate Ciona. Therefore, we offer a straightforward and accurate method to acquire proteomics data from minimal input samples.
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Affiliation(s)
- Burcu Vitrinel
- Center
for Genomics and Systems Biology, Department of Biology, New York University, New York, New York 10003, United States
- Center
for Developmental Genetics, Department of Biology, New York University, New York, New York 10003, United States
| | - Dylan E. Iannitelli
- Center
for Developmental Genetics, Department of Biology, New York University, New York, New York 10003, United States
| | - Esteban O. Mazzoni
- Center
for Developmental Genetics, Department of Biology, New York University, New York, New York 10003, United States
- NYU
Neuroscience Institute, NYU Langone Medical
Center, New York, New York 10016, United
States
| | - Lionel Christiaen
- Center
for Developmental Genetics, Department of Biology, New York University, New York, New York 10003, United States
| | - Christine Vogel
- Center
for Genomics and Systems Biology, Department of Biology, New York University, New York, New York 10003, United States
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14
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Rose CM, Erickson BK, Schweppe DK, Viner R, Choi J, Rogers J, Bomgarden R, Gygi SP, Kirkpatrick DS. TomahaqCompanion: A Tool for the Creation and Analysis of Isobaric Label Based Multiplexed Targeted Assays. J Proteome Res 2018; 18:594-605. [PMID: 30501201 DOI: 10.1021/acs.jproteome.8b00767] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Triggered by Offset, Multiplexed, Accurate mass, High resolution, and Absolute Quantitation (TOMAHAQ) is a recently introduced targeted proteomics method that combines peptide and sample multiplexing. TOMAHAQ assays enable sensitive and accurate multiplexed quantification by implementing an intricate data collection scheme that comprises multiple MSn scans, mass inclusion lists, and data-driven filters. Consequently, manual creation of TOMAHAQ methods can be time-consuming and error prone, while the resulting TOMAHAQ data may not be compatible with common mass spectrometry analysis pipelines. To address these concerns we introduce TomahaqCompanion, an open-source desktop application that enables rapid creation of TOMAHAQ methods and analysis of TOMAHAQ data. Starting from a list of peptide sequences, a user can perform each step of TOMAHAQ assay development including (1) generation of priming run target list, (2) analysis of priming run data, (3) generation of TOMAHAQ method file, and (4) analysis and export of quantitative TOMAHAQ data. We demonstrate the flexibility of TomahaqCompanion by creating a variety of methods testing TOMAHAQ parameters (e.g., number of SPS notches, run length, etc.). Lastly, we analyze an interference sample comprising heavy yeast peptides, a standard human peptide mixture, TMT11-plex, and super heavy TMT (shTMT) isobaric labels to demonstrate ∼10-200 attomol limit of quantification within a complex background using TOMAHAQ.
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Affiliation(s)
- Christopher M Rose
- Department of Microchemistry, Proteomics and Lipidomics , Genentech , South San Francisco , California 94080 , United States
| | - Brian K Erickson
- Department of Cell Biology , Harvard Medical School , Boston , Massachusetts 02115 , United States
| | - Devin K Schweppe
- Department of Cell Biology , Harvard Medical School , Boston , Massachusetts 02115 , United States
| | - Rosa Viner
- Thermo Fisher Scientific , San Jose , California 95134 , United States
| | - Jae Choi
- Thermo Fisher Scientific , Rockford , Illinois 61101 , United States
| | - John Rogers
- Thermo Fisher Scientific , Rockford , Illinois 61101 , United States
| | - Ryan Bomgarden
- Thermo Fisher Scientific , Rockford , Illinois 61101 , United States
| | - Steven P Gygi
- Department of Cell Biology , Harvard Medical School , Boston , Massachusetts 02115 , United States
| | - Donald S Kirkpatrick
- Department of Microchemistry, Proteomics and Lipidomics , Genentech , South San Francisco , California 94080 , United States
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