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Bourmaud A, Gallien S, Domon B. High Resolution/Accurate Mass Targeted Proteomics. QUANTITATIVE PROTEOMICS 2014. [DOI: 10.1039/9781782626985-00026] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Targeted proteomics has emerged as the predominant method for quantitative analyses of peptides to complement shotgun LC/MS studies. Targeted measurements are routinely performed using the technique of selected reaction monitoring (SRM) on triple quadrupole instruments. However, the approach suffers from limitations inherent to the SRM technique. First, the selectivity of measurements is often insufficient to effectively discriminate the analytes from the complex background commonly encountered in biological samples. Second, the number of peptides analyzed in one experiment remains limited. The recent development of high resolution/accurate mass instruments, in conjunction with various acquisition methods, has opened new avenues for quantitative proteomic studies. An overview of the analytical capabilities of a high resolution hybrid quadrupole–orbitrap instrument for quantitative applications is presented and discussed in this chapter. The measurements are performed either on precursor ions (selected ion monitoring mode) or on fragment ions (parallel reaction monitoring mode), which overcome, in many instances, the selectivity issue encountered in complex samples, as illustrated on various examples. It clearly demonstrates the potential of high resolution mass measurements for quantitative proteomic applications.
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Affiliation(s)
- A. Bourmaud
- Luxembourg Clinical Proteomics Center (LCP) CRP-Santé, Strassen Luxembourg
| | - S. Gallien
- Luxembourg Clinical Proteomics Center (LCP) CRP-Santé, Strassen Luxembourg
| | - B. Domon
- Luxembourg Clinical Proteomics Center (LCP) CRP-Santé, Strassen Luxembourg
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Martínez-Morillo E, Nielsen HM, Batruch I, Drabovich AP, Begcevic I, Lopez MF, Minthon L, Bu G, Mattsson N, Portelius E, Hansson O, Diamandis EP. Assessment of peptide chemical modifications on the development of an accurate and precise multiplex selected reaction monitoring assay for apolipoprotein e isoforms. J Proteome Res 2014; 13:1077-87. [PMID: 24392642 DOI: 10.1021/pr401060x] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Apolipoprotein E (ApoE) is a polymorphic protein that plays a major role in lipid metabolism in the central nervous system and periphery. It has three common allelic isoforms, ApoE2, ApoE3, and ApoE4, that differ in only one or two amino acids. ApoE isoforms have been associated with the occurrence and progression of several pathological conditions, such as coronary atherosclerosis and Alzheimer's disease. The aim of this study was to develop a mass spectrometry (MS)-based assay for absolute quantification of ApoE isoforms in cerebrospinal fluid and plasma samples using isotope-labeled peptides. The assay included five tryptic peptides: CLAVYQAGAR (ApoE2), LGADMEDVCGR (ApoE2 and 3), LAVYQAGAR (ApoE3 and 4), LGADMEDVR (ApoE4), and LGPLVEQGR (total ApoE). Both cerebrospinal fluid and plasma samples were assayed to validate the method. The digestion yield and the extension of chemical modifications in selected amino acid residues (methionine oxidation, glutamine deamidation, and cyclization of N-terminus carbamidomethylcysteine) were also studied. The ApoE phenotype was successfully assigned to all samples analyzed in a blinded manner. The method showed good linearity (R(2) > 0.99) and reproducibility (within laboratory imprecision <13%). The comparison of the MS-based assay with an ELISA for total ApoE concentration showed a moderate correlation (R(2) = 0.59). This MS-based assay can serve as an important tool in clinical studies aiming to elucidate the association between ApoE genotype, total ApoE, and ApoE isoform concentrations in various disorders related to ApoE polymorphisms.
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Affiliation(s)
- Eduardo Martínez-Morillo
- Lunenfeld-Tanenbaum Research Institute, Joseph and Wolf Lebovic Health Complex, Mount Sinai Hospital , 60 Murray Street, Toronto, Ontario, M5T 3L9 Canada
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54
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Lyon D, Weckwerth W, Wienkoop S. Mass Western for absolute quantification of target proteins and considerations about the instrument of choice. Methods Mol Biol 2014; 1072:199-208. [PMID: 24136524 DOI: 10.1007/978-1-62703-631-3_15] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
The Mass Western describes the absolute quantification of proteins based on stable isotope labeled integral standard peptides and liquid chromatography coupled selective reaction monitoring triple quadrupole mass spectrometry (LC-SRM/MS). Here, we present a detailed workflow including tips and we discuss advantages and disadvantages of using different types of MS for absolute quantification.
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Affiliation(s)
- David Lyon
- Department of Molecular Systems Biology, University of Vienna, Vienna, Austria
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Abstract
Moving past the discovery phase of proteomics, the term targeted proteomics combines multiple approaches investigating a certain set of proteins in more detail. One such targeted proteomics approach is the combination of liquid chromatography and selected or multiple reaction monitoring mass spectrometry (SRM, MRM). SRM-MS requires prior knowledge of the fragmentation pattern of peptides, as the presence of the analyte in a sample is determined by measuring the m/z values of predefined precursor and fragment ions. Using scheduled SRM-MS, many analytes can robustly be monitored allowing for high-throughput sample analysis of the same set of proteins over many conditions. In this chapter, fundaments of SRM-MS are explained as well as an optimized SRM pipeline from assay generation to data analyzed.
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Affiliation(s)
- H Alexander Ebhardt
- Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule (ETH) Zürich, Zürich, Switzerland
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56
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Martínez-Morillo E, García Hernández P, Begcevic I, Kosanam H, Prieto García B, Alvarez Menéndez FV, Diamandis EP. Identification of novel biomarkers of brain damage in patients with hemorrhagic stroke by integrating bioinformatics and mass spectrometry-based proteomics. J Proteome Res 2013; 13:969-81. [PMID: 24295473 DOI: 10.1021/pr401111h] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Hemorrhagic stroke (HS) is a significant cause of mortality that requires rapid diagnosis and prompt medical attention. A time-efficient diagnostic test to assist in the early classification of patients with stroke would be of great value. The aims here were to (a) select "brain-specific" proteins using a bioinformatics approach, (b) develop selected reaction monitoring (SRM) assays for candidate proteins, and (c) quantify these proteins in cerebrospinal fluid (CSF). "The Human Protein Atlas" and the "Peptide Atlas" were used to select proteins specifically and abundantly expressed in brain tissue, excluding high-abundance plasma proteins. Protein extracts from brain tissue were used for SRM assay development of proteins of interest. The levels of 68 "brain-specific" proteins were measured by SRM in 36 age-matched patients, including individuals with HS (n = 15), ischemic stroke (n = 11), and controls (n = 10). Additionally, S100B was measured using an electrochemoluminometric immunoassay. CSF levels of S100B and eight of the "brain-specific" proteins (NSE, GFAP, α-Inx, MBP, MT3, NFM, β-Syn, and γ-Syn) were increased in a subset of samples from HS patients, especially in those individuals with intraventricular hemorrhage and poor outcome. Seven of these proteins (S100B, NSE, GFAP, α-Inx, MBP, NFM, and β-Syn) showed significant differences between patients with and without brain hemorrhage. Novel biomarkers of brain injury (α-Inx, NFM, and β-Syn) were identified in the CSF of patients with HS. Investigating the role of these proteins in blood with more sensitive methods is warranted.
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Affiliation(s)
- Eduardo Martínez-Morillo
- Lunenfeld-Tanenbaum Research Institute, Joseph and Wolf Lebovic Health Complex, Mount Sinai Hospital , Toronto, Ontario M5T 1A8, Canada
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57
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Schubert OT, Mouritsen J, Ludwig C, Röst HL, Rosenberger G, Arthur PK, Claassen M, Campbell DS, Sun Z, Farrah T, Gengenbacher M, Maiolica A, Kaufmann SHE, Moritz RL, Aebersold R. The Mtb proteome library: a resource of assays to quantify the complete proteome of Mycobacterium tuberculosis. Cell Host Microbe 2013; 13:602-612. [PMID: 23684311 DOI: 10.1016/j.chom.2013.04.008] [Citation(s) in RCA: 136] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2013] [Revised: 03/27/2013] [Accepted: 04/15/2013] [Indexed: 12/18/2022]
Abstract
Research advancing our understanding of Mycobacterium tuberculosis (Mtb) biology and complex host-Mtb interactions requires consistent and precise quantitative measurements of Mtb proteins. We describe the generation and validation of a compendium of assays to quantify 97% of the 4,012 annotated Mtb proteins by the targeted mass spectrometric method selected reaction monitoring (SRM). Furthermore, we estimate the absolute abundance for 55% of all Mtb proteins, revealing a dynamic range within the Mtb proteome of over four orders of magnitude, and identify previously unannotated proteins. As an example of the assay library utility, we monitored the entire Mtb dormancy survival regulon (DosR), which is linked to anaerobic survival and Mtb persistence, and show its dynamic protein-level regulation during hypoxia. In conclusion, we present a publicly available research resource that supports the sensitive, precise, and reproducible quantification of virtually any Mtb protein by a robust and widely accessible mass spectrometric method.
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Affiliation(s)
- Olga T Schubert
- Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland; Systems Biology Graduate School, Zurich, CH-8057, Switzerland
| | - Jeppe Mouritsen
- Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland; Molecular Life Sciences Graduate School, Zurich, CH-8093, Switzerland
| | - Christina Ludwig
- Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland
| | - Hannes L Röst
- Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland; Systems Biology Graduate School, Zurich, CH-8057, Switzerland
| | - George Rosenberger
- Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland; Systems Biology Graduate School, Zurich, CH-8057, Switzerland
| | - Patrick K Arthur
- Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Ghana
| | - Manfred Claassen
- Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland
| | | | - Zhi Sun
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Terry Farrah
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Martin Gengenbacher
- Department of Immunology, Max Planck Institute for Infection Biology, Berlin D-10117, Germany
| | - Alessio Maiolica
- Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland
| | - Stefan H E Kaufmann
- Department of Immunology, Max Planck Institute for Infection Biology, Berlin D-10117, Germany
| | | | - Ruedi Aebersold
- Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland; Faculty of Science, University of Zurich, Zurich CH-8057, Switzerland.
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58
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Pre-analytical and analytical variability in absolute quantitative MRM-based plasma proteomic studies. Bioanalysis 2013; 5:2837-56. [DOI: 10.4155/bio.13.245] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Quantitative plasma proteomics, through the use of targeted MRM-MS and isotopically labeled standards, is emerging as a popular technique to address biological- and biomedical-centered queries. High precision and accuracy are essential in such measurements, particularly in protein biomarker research where translation to the clinic is sought. Standardized procedures and routine performance evaluation of all stages of the workflow (both pre-analytical and analytical) are therefore imperative to satisfy these requisites and enable high inter-laboratory reproducibility and transferability. In this review, we first discuss the pre-analytical and analytical variables that can affect the precision and accuracy of ‘absolute’ quantitative plasma proteomic measurements. Proposed strategies to limit such variability will then be highlighted and unmet needs for future exploration will be noted. Although there is no way to conduct a truly comprehensive review on this broad, rapidly changing topic, we have highlighted key aspects and included references to review articles on various sub-topics.
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59
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Bruce C, Stone K, Gulcicek E, Williams K. Proteomics and the analysis of proteomic data: 2013 overview of current protein-profiling technologies. ACTA ACUST UNITED AC 2013; Chapter 13:13.21.1-13.21.17. [PMID: 23504934 DOI: 10.1002/0471250953.bi1321s41] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
Mass spectrometry has become a major tool in the study of proteomes. The analysis of proteolytic peptides and their fragment ions by this technique enables the identification and quantitation of the precursor proteins in a mixture. However, deducing chemical structures and then protein sequences from mass-to-charge ratios is a challenging computational task. Software tools incorporating powerful algorithms and statistical methods improved our ability to process the large quantities of proteomics data. Repositories of spectral data make both data analysis and experimental design more efficient. New approaches in quantitative and statistical proteomics make possible a greater coverage of the proteome, the identification of more post-translational modifications, and a greater sensitivity in the quantitation of targeted proteins.
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Affiliation(s)
- Can Bruce
- W.M. Keck Foundation Biotechnology Resource Laboratory and Molecular Biochemistry and Biophysics Department, Yale University, New Haven, Connecticut, USA
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60
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Bao Y, Waldemarson S, Zhang G, Wahlander A, Ueberheide B, Myung S, Reed B, Molloy K, Padovan JC, Eriksson J, Neubert TA, Chait BT, Fenyö D. Detection and correction of interference in SRM analysis. Methods 2013; 61:299-303. [PMID: 23707623 DOI: 10.1016/j.ymeth.2013.05.008] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2012] [Revised: 05/15/2013] [Accepted: 05/15/2013] [Indexed: 11/16/2022] Open
Abstract
Selected Reaction Monitoring (SRM) is a method of choice for accurate quantitation of low-abundance proteins in complex backgrounds. This strategy is, however, sensitive to interference from other components in the sample that have the same precursor and fragment masses as the monitored transitions. We present here an approach to detect interference by using the expected relative intensity of SRM transitions. We also designed an algorithm to automatically detect the linear range of calibration curves. These approaches were applied to the experimental data of Clinical Proteomic Tumor Analysis Consortium (CPTAC) Verification Work Group Study 7 and show that the corrected measurements provide more accurate quantitation than the uncorrected data.
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Affiliation(s)
- Y Bao
- Laboratory of Computational Proteomics, Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, NY, USA
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61
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Colangelo CM, Chung L, Bruce C, Cheung KH. Review of software tools for design and analysis of large scale MRM proteomic datasets. Methods 2013; 61:287-98. [PMID: 23702368 DOI: 10.1016/j.ymeth.2013.05.004] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2013] [Revised: 05/06/2013] [Accepted: 05/11/2013] [Indexed: 12/13/2022] Open
Abstract
Selective or Multiple Reaction monitoring (SRM/MRM) is a liquid-chromatography (LC)/tandem-mass spectrometry (MS/MS) method that enables the quantitation of specific proteins in a sample by analyzing precursor ions and the fragment ions of their selected tryptic peptides. Instrumentation software has advanced to the point that thousands of transitions (pairs of primary and secondary m/z values) can be measured in a triple quadrupole instrument coupled to an LC, by a well-designed scheduling and selection of m/z windows. The design of a good MRM assay relies on the availability of peptide spectra from previous discovery-phase LC-MS/MS studies. The tedious aspect of manually developing and processing MRM assays involving thousands of transitions has spurred to development of software tools to automate this process. Software packages have been developed for project management, assay development, assay validation, data export, peak integration, quality assessment, and biostatistical analysis. No single tool provides a complete end-to-end solution, thus this article reviews the current state and discusses future directions of these software tools in order to enable researchers to combine these tools for a comprehensive targeted proteomics workflow.
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Affiliation(s)
- Christopher M Colangelo
- W.M. Keck Foundation Biotechnology Resource Laboratory, School of Medicine, Yale University, New Haven, CT 06510, USA.
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62
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Gallien S, Duriez E, Demeure K, Domon B. Selectivity of LC-MS/MS analysis: Implication for proteomics experiments. J Proteomics 2013; 81:148-58. [DOI: 10.1016/j.jprot.2012.11.005] [Citation(s) in RCA: 104] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2012] [Revised: 11/02/2012] [Accepted: 11/04/2012] [Indexed: 01/08/2023]
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63
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Picotti P, Clément-Ziza M, Lam H, Campbell DS, Schmidt A, Deutsch EW, Röst H, Sun Z, Rinner O, Reiter L, Shen Q, Michaelson JJ, Frei A, Alberti S, Kusebauch U, Wollscheid B, Moritz RL, Beyer A, Aebersold R. A complete mass-spectrometric map of the yeast proteome applied to quantitative trait analysis. Nature 2013; 494:266-70. [PMID: 23334424 PMCID: PMC3951219 DOI: 10.1038/nature11835] [Citation(s) in RCA: 257] [Impact Index Per Article: 23.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2011] [Accepted: 11/30/2012] [Indexed: 12/25/2022]
Abstract
Experience from different fields of life sciences suggests that accessible, complete reference maps of the components of the system under study are highly beneficial research tools. Examples of such maps include libraries of the spectroscopic properties of molecules, or databases of drug structures in analytical or forensic chemistry. Such maps, and methods to navigate them, constitute reliable assays to probe any sample for the presence and amount of molecules contained in the map. So far, attempts to generate such maps for any proteome have failed to reach complete proteome coverage. Here we use a strategy based on high-throughput peptide synthesis and mass spectrometry to generate an almost complete reference map (97% of the genome-predicted proteins) of the Saccharomyces cerevisiae proteome. We generated two versions of this mass-spectrometric map, one supporting discovery-driven (shotgun) and the other supporting hypothesis-driven (targeted) proteomic measurements. Together, the two versions of the map constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. To show the utility of the maps, we applied them to a protein quantitative trait locus (QTL) analysis, which requires precise measurement of the same set of peptides over a large number of samples. Protein measurements over 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, influencing the levels of related proteins. Our results suggest that selective pressure favours the acquisition of sets of polymorphisms that adapt protein levels but also maintain the stoichiometry of functionally related pathway members.
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Affiliation(s)
- Paola Picotti
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland.
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64
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Jacoby RP, Millar AH, Taylor NL. Application of selected reaction monitoring mass spectrometry to field-grown crop plants to allow dissection of the molecular mechanisms of abiotic stress tolerance. FRONTIERS IN PLANT SCIENCE 2013; 4:20. [PMID: 23407798 PMCID: PMC3571200 DOI: 10.3389/fpls.2013.00020] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2012] [Accepted: 01/27/2013] [Indexed: 05/18/2023]
Abstract
One major constraint upon the application of molecular crop breeding approaches is the small number of genes linked to agronomically desirable traits through defined biochemical mechanisms. Proteomic investigations of crop plants under abiotic stress treatments have identified many proteins that differ in control versus stress comparisons, however, this broad profiling of cell physiology is poorly suited to ranking the effects and identifying the specific proteins that are causative in agronomically relevant traits. Here we will reason that insights into a protein's function, its biochemical process and links to stress tolerance are more likely to arise through approaches that evaluate these differential abundances of proteins and include varietal comparisons, precise discrimination of protein isoforms, enrichment of functionally related proteins, and integration of proteomic datasets with physiological measurements of both lab and field-grown plants. We will briefly explain how applying the emerging proteomic technology of multiplexed selective reaction monitoring mass spectrometry with its accuracy and throughput can facilitate and enhance these approaches and provide a clear means to rank the growing cohort of stress responsive proteins. We will also highlight the benefit of integrating proteomic analyses with cultivar-specific genetic databases and physiological assessments of cultivar performance in relevant field environments for revealing deeper insights into molecular crop improvement.
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Affiliation(s)
| | | | - Nicolas L. Taylor
- Australian Research Council Centre of Excellence in Plant Energy Biology and Centre for Comparative Analysis of Biomolecular Networks, The University of Western AustraliaCrawley, WA, Australia
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65
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Domon B. Considerations on selected reaction monitoring experiments: Implications for the selectivity and accuracy of measurements. Proteomics Clin Appl 2012; 6:609-14. [DOI: 10.1002/prca.201200111] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2012] [Accepted: 10/01/2012] [Indexed: 11/09/2022]
Affiliation(s)
- Bruno Domon
- Luxembourg Clinical Proteomics Center (LCP); CRP-Santé; Strassen Luxembourg
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66
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Gaudet P, Argoud-Puy G, Cusin I, Duek P, Evalet O, Gateau A, Gleizes A, Pereira M, Zahn-Zabal M, Zwahlen C, Bairoch A, Lane L. neXtProt: organizing protein knowledge in the context of human proteome projects. J Proteome Res 2012. [PMID: 23205526 DOI: 10.1021/pr300830v] [Citation(s) in RCA: 104] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
About 5000 (25%) of the ~20400 human protein-coding genes currently lack any experimental evidence at the protein level. For many others, there is only little information relative to their abundance, distribution, subcellular localization, interactions, or cellular functions. The aim of the HUPO Human Proteome Project (HPP, www.thehpp.org ) is to collect this information for every human protein. HPP is based on three major pillars: mass spectrometry (MS), antibody/affinity capture reagents (Ab), and bioinformatics-driven knowledge base (KB). To meet this objective, the Chromosome-Centric Human Proteome Project (C-HPP) proposes to build this catalog chromosome-by-chromosome ( www.c-hpp.org ) by focusing primarily on proteins that currently lack MS evidence or Ab detection. These are termed "missing proteins" by the HPP consortium. The lack of observation of a protein can be due to various factors including incorrect and incomplete gene annotation, low or restricted expression, or instability. neXtProt ( www.nextprot.org ) is a new web-based knowledge platform specific for human proteins that aims to complement UniProtKB/Swiss-Prot ( www.uniprot.org ) with detailed information obtained from carefully selected high-throughput experiments on genomic variation, post-translational modifications, as well as protein expression in tissues and cells. This article describes how neXtProt contributes to prioritize C-HPP efforts and integrates C-HPP results with other research efforts to create a complete human proteome catalog.
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Affiliation(s)
- Pascale Gaudet
- CALIPHO Group, SIB-Swiss Institute of Bioinformatics, Faculty of Medicine, University of Geneva, CMU-1, rue Michel Servet 1211 Geneva 4, Switzerland
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67
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Label-free quantitative proteomics trends for protein-protein interactions. J Proteomics 2012; 81:91-101. [PMID: 23153790 DOI: 10.1016/j.jprot.2012.10.027] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2012] [Revised: 10/24/2012] [Accepted: 10/31/2012] [Indexed: 12/14/2022]
Abstract
Understanding protein interactions within the complexity of a living cell is challenging, but techniques coupling affinity purification and mass spectrometry have enabled important progress to be made in the past 15 years. As identification of protein-protein interactions is becoming easier, the quantification of the interaction dynamics is the next frontier. Several quantitative mass spectrometric approaches have been developed to address this issue that vary in their strengths and weaknesses. While isotopic labeling approaches continue to contribute to the identification of regulated interactions, techniques that do not require labeling are becoming increasingly used in the field. Here, we describe the major types of label-free quantification used in interaction proteomics, and discuss the relative merits of data dependent and data independent acquisition approaches in label-free quantification. This article is part of a Special Issue entitled: From protein structures to clinical applications.
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68
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Baker ES, Liu T, Petyuk VA, Burnum-Johnson KE, Ibrahim YM, Anderson GA, Smith RD. Mass spectrometry for translational proteomics: progress and clinical implications. Genome Med 2012; 4:63. [PMID: 22943415 PMCID: PMC3580401 DOI: 10.1186/gm364] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
The utility of mass spectrometry (MS)-based proteomic analyses and their clinical applications have been increasingly recognized over the past decade due to their high sensitivity, specificity and throughput. MS-based proteomic measurements have been used in a wide range of biological and biomedical investigations, including analysis of cellular responses and disease-specific post-translational modifications. These studies greatly enhance our understanding of the complex and dynamic nature of the proteome in biology and disease. Some MS techniques, such as those for targeted analysis, are being successfully applied for biomarker verification, whereas others, including global quantitative analysis (for example, for biomarker discovery), are more challenging and require further development. However, recent technological improvements in sample processing, instrumental platforms, data acquisition approaches and informatics capabilities continue to advance MS-based applications. Improving the detection of significant changes in proteins through these advances shows great promise for the discovery of improved biomarker candidates that can be verified pre-clinically using targeted measurements, and ultimately used in clinical studies - for example, for early disease diagnosis or as targets for drug development and therapeutic intervention. Here, we review the current state of MS-based proteomics with regard to its advantages and current limitations, and we highlight its translational applications in studies of protein biomarkers.
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Affiliation(s)
- Erin Shammel Baker
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Tao Liu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Vladislav A Petyuk
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | | | - Yehia M Ibrahim
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Gordon A Anderson
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Richard D Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
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69
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Abstract
Selected reaction monitoring mass spectrometry is an emerging targeted proteomics technology that allows for the investigation of complex protein samples with high sensitivity and efficiency. It requires extensive knowledge about the sample for the many parameters needed to carry out the experiment to be set appropriately. Most studies today rely on parameter estimation from prior studies, public databases, or from measuring synthetic peptides. This is efficient and sound, but in absence of prior data, de novo parameter estimation is necessary. Computational methods can be used to create an automated framework to address this problem. However, the number of available applications is still small. This review aims at giving an orientation on the various bioinformatical challenges. To this end, we state the problems in classical machine learning and data mining terms, give examples of implemented solutions and provide some room for alternatives. This will hopefully lead to an increased momentum for the development of algorithms and serve the needs of the community for computational methods. We note that the combination of such methods in an assisted workflow will ease both the usage of targeted proteomics in experimental studies as well as the further development of computational approaches.
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Affiliation(s)
- Daniel Reker
- ETH Zurich, Wolfgang-Pauli-Strasse 16, 8093 Zurich, Switzerland
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70
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Hüttenhain R, Soste M, Selevsek N, Röst H, Sethi A, Carapito C, Farrah T, Deutsch EW, Kusebauch U, Moritz RL, Niméus-Malmström E, Rinner O, Aebersold R. Reproducible quantification of cancer-associated proteins in body fluids using targeted proteomics. Sci Transl Med 2012; 4:142ra94. [PMID: 22786679 PMCID: PMC3766734 DOI: 10.1126/scitranslmed.3003989] [Citation(s) in RCA: 195] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The rigorous testing of hypotheses on suitable sample cohorts is a major limitation in translational research. This is particularly the case for the validation of protein biomarkers; the lack of accurate, reproducible, and sensitive assays for most proteins has precluded the systematic assessment of hundreds of potential marker proteins described in the literature. Here, we describe a high-throughput method for the development and refinement of selected reaction monitoring (SRM) assays for human proteins. The method was applied to generate such assays for more than 1000 cancer-associated proteins, which are functionally related to candidate cancer driver mutations. We used the assays to determine the detectability of the target proteins in two clinically relevant samples: plasma and urine. One hundred eighty-two proteins were detected in depleted plasma, spanning five orders of magnitude in abundance and reaching below a concentration of 10 ng/ml. The narrower concentration range of proteins in urine allowed the detection of 408 proteins. Moreover, we demonstrate that these SRM assays allow reproducible quantification by monitoring 34 biomarker candidates across 83 patient plasma samples. Through public access to the entire assay library, researchers will be able to target their cancer-associated proteins of interest in any sample type using the detectability information in plasma and urine as a guide. The generated expandable reference map of SRM assays for cancer-associated proteins will be a valuable resource for accelerating and planning biomarker verification studies.
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Affiliation(s)
- Ruth Hüttenhain
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8093 Zurich, Switzerland.
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71
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Gillet LC, Navarro P, Tate S, Röst H, Selevsek N, Reiter L, Bonner R, Aebersold R. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol Cell Proteomics 2012. [PMID: 22261725 DOI: 10.1074/mcp.o111.016717 [epub ahead of print]] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2023] Open
Abstract
Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400-1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics.
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Affiliation(s)
- Ludovic C Gillet
- Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich, 8093 Zürich, Switzerland
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Gillet LC, Navarro P, Tate S, Röst H, Selevsek N, Reiter L, Bonner R, Aebersold R. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol Cell Proteomics 2012; 11:O111.016717. [PMID: 22261725 PMCID: PMC3433915 DOI: 10.1074/mcp.o111.016717] [Citation(s) in RCA: 1895] [Impact Index Per Article: 157.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2011] [Revised: 01/18/2012] [Indexed: 11/06/2022] Open
Abstract
Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400-1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics.
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Affiliation(s)
- Ludovic C. Gillet
- From the ‡Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich (ETH Zürich), 8093 Zürich, Switzerland
| | - Pedro Navarro
- From the ‡Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich (ETH Zürich), 8093 Zürich, Switzerland
| | | | - Hannes Röst
- From the ‡Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich (ETH Zürich), 8093 Zürich, Switzerland
| | - Nathalie Selevsek
- From the ‡Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich (ETH Zürich), 8093 Zürich, Switzerland
| | - Lukas Reiter
- From the ‡Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich (ETH Zürich), 8093 Zürich, Switzerland
- ¶Biognosys AG, 8952 Schlieren, Switzerland, and
| | - Ron Bonner
- §ABSciex, Concord, L4K 4V8 Ontario, Canada
| | - Ruedi Aebersold
- From the ‡Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich (ETH Zürich), 8093 Zürich, Switzerland
- the ‖Faculty of Science, University of Zürich, 8057 Zürich, Switzerland
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73
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Gillet LC, Navarro P, Tate S, Röst H, Selevsek N, Reiter L, Bonner R, Aebersold R. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol Cell Proteomics 2012; 11:O111.016717. [PMID: 22261725 DOI: 10.1074/mcp.0111.016717] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/21/2023] Open
Abstract
Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400-1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics.
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Affiliation(s)
- Ludovic C Gillet
- Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich, 8093 Zürich, Switzerland
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