1
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Prust N, van der Laarse S, van den Toorn HWP, van Sorge NM, Lemeer S. In-Depth Characterization of the Staphylococcus aureus Phosphoproteome Reveals New Targets of Stk1. Mol Cell Proteomics 2021; 20:100034. [PMID: 33444734 PMCID: PMC7950182 DOI: 10.1074/mcp.ra120.002232] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 12/02/2020] [Accepted: 12/10/2020] [Indexed: 11/26/2022] Open
Abstract
Staphylococcus aureus is a major cause of infections worldwide, and infection results in a variety of diseases. As of no surprise, protein phosphorylation is an important game player in signaling cascades and has been shown to be involved in S. aureus virulence. Albeit long neglected, eukaryotic-type serine/threonine kinases in S. aureus have been implicated in this complex signaling cascades. Due to the substoichiometric nature of protein phosphorylation and a lack of suitable analysis tools, the knowledge of these cascades is, however, to date, still limited. Here, were apply an optimized protocol for efficient phosphopeptide enrichment via Fe3+-IMAC followed by LC-MS/MS to get a better understanding of the impact of protein phosphorylation on the complex signaling networks involved in pathogenicity. By profiling a serine/threonine kinase and phosphatase mutant from a methicillin-resistant S. aureus mutant library, we generated the most comprehensive phosphoproteome data set of S. aureus to date, aiding a better understanding of signaling in bacteria. With the identification of 3800 class I p-sites, we were able to increase the number of identifications by more than 21 times compared with recent literature. In addition, we were able to identify 74 downstream targets of the only reported eukaryotic-type Ser/Thr kinase of the S. aureus strain USA300, Stk1. This work allowed an extensive analysis of the bacterial phosphoproteome and indicates that Ser/Thr kinase signaling is far more abundant than previously anticipated in S. aureus.
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Affiliation(s)
- Nadine Prust
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands; Netherlands Proteomics Center, Utrecht, the Netherlands
| | - Saar van der Laarse
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands; Netherlands Proteomics Center, Utrecht, the Netherlands
| | - Henk W P van den Toorn
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands; Netherlands Proteomics Center, Utrecht, the Netherlands
| | - Nina M van Sorge
- Medical Microbiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; Department of Medical Microbiology and Infection Prevention and Netherlands Reference Laboratory for Bacterial Meningitis, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Simone Lemeer
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands; Netherlands Proteomics Center, Utrecht, the Netherlands.
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2
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Steigenberger B, van den Toorn HWP, Bijl E, Greisch JF, Räther O, Lubeck M, Pieters RJ, Heck AJR, Scheltema RA. Benefits of Collisional Cross Section Assisted Precursor Selection (caps-PASEF) for Cross-linking Mass Spectrometry. Mol Cell Proteomics 2020; 19:1677-1687. [PMID: 32694122 PMCID: PMC8015012 DOI: 10.1074/mcp.ra120.002094] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 07/13/2020] [Indexed: 12/05/2022] Open
Abstract
Ion mobility separates molecules in the gas-phase based on their physico-chemical properties, providing information about their size as collisional cross-sections. The timsTOF Pro combines trapped ion mobility with a quadrupole, collision cell and a TOF mass analyzer, to probe ions at high speeds with on-the-fly fragmentation. Here, we show that on this platform ion mobility is beneficial for cross-linking MS (XL-MS). Cross-linking reagents covalently link amino acids in proximity, resulting in peptide pairs after proteolytic digestion. These cross-linked peptides are typically present at low abundance in the background of normal peptides, which can partially be resolved by using enrichable cross-linking reagents. Even with a very efficient enrichable cross-linking reagent, like PhoX, the analysis of cross-linked peptides is still hampered by the co-enrichment of peptides connected to a partially hydrolyzed reagent - termed mono-linked peptides. For experiments aiming to uncover protein-protein interactions these are unwanted byproducts. Here, we demonstrate that gas-phase separation by ion mobility enables the separation of mono-linked peptides from cross-linked peptide pairs. A clear partition between these two classes is observed at a CCS of 500 Å2 and a monoisotopic mass of 2 kDa, which can be used for targeted precursor selection. A total of 50-70% of the mono-linked peptides are prevented from sequencing, allowing the analysis to focus on sequencing the relevant cross-linked peptide pairs. In applications to both simple proteins and protein mixtures and a complete highly complex lysate this approach provides a substantial increase in detected cross-linked peptides.
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Affiliation(s)
- Barbara Steigenberger
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Netherlands Proteomics Centre, Utrecht, The Netherlands; Department of Chemical Biology & Drug Discovery, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Henk W P van den Toorn
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Netherlands Proteomics Centre, Utrecht, The Netherlands
| | - Emiel Bijl
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Netherlands Proteomics Centre, Utrecht, The Netherlands
| | - Jean-François Greisch
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Netherlands Proteomics Centre, Utrecht, The Netherlands
| | | | | | - Roland J Pieters
- Department of Chemical Biology & Drug Discovery, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Netherlands Proteomics Centre, Utrecht, The Netherlands
| | - Richard A Scheltema
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Netherlands Proteomics Centre, Utrecht, The Netherlands.
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3
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Abstract
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Recent technological
advances have made it possible to investigate
the hitherto rather elusive protein histidine phosphorylation. However,
confident site-specific localization of protein histidine phosphorylation
remains challenging. Here, we address this problem, presenting a mass-spectrometry-based
approach that outperforms classical HCD fragmentation without compromising
sensitivity. We use the phosphohistidine immonium ion as a diagnostic
tool as well as ETD-based fragmentation techniques to achieve unambiguous
identification and localization of histidine-phosphorylation sites.
The work presented here will allow more confident investigation of
the phosphohistidine proteome to reveal the roles of histidine phosphorylation
in cellular signaling events.
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Affiliation(s)
- Clement M Potel
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences , University of Utrecht , Padualaan 8 , 3584 CH Utrecht , The Netherlands.,Netherlands Proteomics Center , Padualaan 8 , 3584 CH Utrecht , The Netherlands
| | - Miao-Hsia Lin
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences , University of Utrecht , Padualaan 8 , 3584 CH Utrecht , The Netherlands.,Netherlands Proteomics Center , Padualaan 8 , 3584 CH Utrecht , The Netherlands
| | - Nadine Prust
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences , University of Utrecht , Padualaan 8 , 3584 CH Utrecht , The Netherlands.,Netherlands Proteomics Center , Padualaan 8 , 3584 CH Utrecht , The Netherlands
| | - Henk W P van den Toorn
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences , University of Utrecht , Padualaan 8 , 3584 CH Utrecht , The Netherlands.,Netherlands Proteomics Center , Padualaan 8 , 3584 CH Utrecht , The Netherlands
| | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences , University of Utrecht , Padualaan 8 , 3584 CH Utrecht , The Netherlands.,Netherlands Proteomics Center , Padualaan 8 , 3584 CH Utrecht , The Netherlands
| | - Simone Lemeer
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences , University of Utrecht , Padualaan 8 , 3584 CH Utrecht , The Netherlands.,Netherlands Proteomics Center , Padualaan 8 , 3584 CH Utrecht , The Netherlands
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4
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Dingess KA, van den Toorn HWP, Mank M, Stahl B, Heck AJR. Toward an efficient workflow for the analysis of the human milk peptidome. Anal Bioanal Chem 2019; 411:1351-1363. [PMID: 30710207 PMCID: PMC6449315 DOI: 10.1007/s00216-018-01566-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 12/07/2018] [Accepted: 12/21/2018] [Indexed: 02/03/2023]
Abstract
There is a growing interest for investigating endogenous peptides from human biofluids which may provide yet unknown functional benefits or provide an early indication of disease states as potential biomarkers. A major technical bottleneck in the investigation of endogenous peptides from body fluids, e.g., serum, urine, saliva, and milk, is that each of these fluids seems to require unique workflows for peptide extraction and analysis. Thus, protocols optimized for serum cannot be directly translated to milk. One biofluid that is readily available, but which has not been extensively explored, is human milk, whose analysis could contribute to our understanding of the immune development of the newborn infant. Due to the occurrence of highly abundant lipids, proteins, and saccharides, milk peptidomics requires dedicated sample preparation steps. The aim of this study was to develop a time and cost-efficient workflow for the analysis of the human milk peptidome, for which we compared peptide extraction methodologies and peptide fragmentation methods. A method using strong acid protein precipitation and analysis by collision-induced dissociation fragmentation was found to be superior to all other test methods, allowing us qualitative and quantitative detection of about 4000 endogenous human milk peptides in a total analysis time of just 18 h.
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Affiliation(s)
- Kelly A Dingess
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Padualaan 8, 3584 CH, Utrecht, The Netherlands.,Netherlands Proteomics Center, Padualaan 8, 3584 CH, Utrecht, The Netherlands
| | - Henk W P van den Toorn
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Padualaan 8, 3584 CH, Utrecht, The Netherlands.,Netherlands Proteomics Center, Padualaan 8, 3584 CH, Utrecht, The Netherlands
| | - Marko Mank
- Early Life Nutrition, Danone Nutricia Research, Uppsalalaan 12, 3584 CT, Utrecht, The Netherlands
| | - Bernd Stahl
- Early Life Nutrition, Danone Nutricia Research, Uppsalalaan 12, 3584 CT, Utrecht, The Netherlands
| | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Padualaan 8, 3584 CH, Utrecht, The Netherlands. .,Netherlands Proteomics Center, Padualaan 8, 3584 CH, Utrecht, The Netherlands.
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5
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Cristobal A, van den Toorn HWP, van de Wetering M, Clevers H, Heck AJR, Mohammed S. Personalized Proteome Profiles of Healthy and Tumor Human Colon Organoids Reveal Both Individual Diversity and Basic Features of Colorectal Cancer. Cell Rep 2017; 18:263-274. [PMID: 28052255 DOI: 10.1016/j.celrep.2016.12.016] [Citation(s) in RCA: 108] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2016] [Revised: 11/23/2016] [Accepted: 12/06/2016] [Indexed: 12/19/2022] Open
Abstract
Diseases at the molecular level are complex and patient dependent, necessitating development of strategies that enable precision treatment to optimize clinical outcomes. Organoid technology has recently been shown to have the potential to recapitulate the in vivo characteristics of the original individual's tissue in a three-dimensional in vitro culture system. Here, we present a quantitative mass-spectrometry-based proteomic analysis and a comparative transcriptomic analysis of human colorectal tumor and healthy organoids derived, in parallel, from seven patients. Although gene and protein signatures can be derived to distinguish the tumor organoid population from healthy organoids, our data clearly reveal that each patient possesses a distinct organoid signature at the proteomic level. We demonstrate that a personalized patient-specific organoid proteome profile can be related to the diagnosis of a patient and with future development contribute to the generation of personalized therapies.
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Affiliation(s)
- Alba Cristobal
- Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research, Utrecht University, Padualaan 8, 3584 Utrecht, the Netherlands; Netherlands Proteomics Center, Padualaan 8, 3584 Utrecht, the Netherlands
| | - Henk W P van den Toorn
- Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research, Utrecht University, Padualaan 8, 3584 Utrecht, the Netherlands; Netherlands Proteomics Center, Padualaan 8, 3584 Utrecht, the Netherlands
| | - Marc van de Wetering
- Princess Maxima Center for Pediatric Oncology, Uppsalalaan 8, 3584 Utrecht, Netherlands
| | - Hans Clevers
- Princess Maxima Center for Pediatric Oncology, Uppsalalaan 8, 3584 Utrecht, Netherlands; Hubrecht Institute, KNAW and University Medical Center Utrecht, Uppsalalaan 8, 3584 Utrecht, Netherlands.
| | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research, Utrecht University, Padualaan 8, 3584 Utrecht, the Netherlands; Netherlands Proteomics Center, Padualaan 8, 3584 Utrecht, the Netherlands.
| | - Shabaz Mohammed
- Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research, Utrecht University, Padualaan 8, 3584 Utrecht, the Netherlands; Netherlands Proteomics Center, Padualaan 8, 3584 Utrecht, the Netherlands; Department of Biochemistry, University of Oxford, New Biochemistry building, South Parks Road, Oxford OX1 3QU, UK; Department of Chemistry, University of Oxford, Chemistry Research Laboratory, Mansfield Road, Oxford OX1 3TA, UK.
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6
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Abstract
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Mass
spectrometry (MS)-based proteomics workflows can crudely be
classified into two distinct regimes, targeting either relatively
small peptides (i.e., 0.7 kDa < Mw <
3.0 kDa) or small to medium sized intact proteins (i.e., 10 kDa < Mw < 30 kDa), respectively, termed bottom-up
and top-down proteomics. Recently, a niche has started to be explored
covering the analysis of middle-range peptides (i.e., 3.0 kDa < Mw < 10 kDa), aptly termed middle-down proteomics.
Although middle-down proteomics can follow, in principle, a modular
workflow similar to that of bottom-up proteomics, we hypothesized
that each of these modules would benefit from targeted optimization
to improve its overall performance in the analysis of middle-range
sized peptides. Hence, to generate middle-range sized peptides from
cellular lysates, we explored the use of the proteases Asp-N and Glu-C
and a nonenzymatic acid induced cleavage. To increase the depth of
the proteome, a strong cation exchange (SCX) separation, carefully
tuned to improve the separation of longer peptides, combined with
reversed phase-liquid chromatography (RP-LC) using columns packed
with material possessing a larger pore size, was used. Finally, after
evaluating the combination of potentially beneficial MS settings,
we also assessed the peptide fragmentation techniques, including higher-energy
collision dissociation (HCD), electron-transfer dissociation (ETD),
and electron-transfer combined with higher-energy collision dissociation
(EThcD), for characterization of middle-range sized peptides. These
combined
improvements clearly improve the detection and sequence coverage of
middle-range peptides and should guide researchers to explore further
how middle-down proteomics may lead to an improved proteome coverage,
beneficial for, among other things, the enhanced analysis of (co-occurring)
post-translational modifications.
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Affiliation(s)
- Alba Cristobal
- Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research, Utrecht University , Padualaan 8, 3584 CH Utrecht, The Netherlands.,Netherlands Proteomics Center , Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Fabio Marino
- Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research, Utrecht University , Padualaan 8, 3584 CH Utrecht, The Netherlands.,Netherlands Proteomics Center , Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Harm Post
- Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research, Utrecht University , Padualaan 8, 3584 CH Utrecht, The Netherlands.,Netherlands Proteomics Center , Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Henk W P van den Toorn
- Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research, Utrecht University , Padualaan 8, 3584 CH Utrecht, The Netherlands.,Netherlands Proteomics Center , Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Shabaz Mohammed
- Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research, Utrecht University , Padualaan 8, 3584 CH Utrecht, The Netherlands.,Netherlands Proteomics Center , Padualaan 8, 3584 CH Utrecht, The Netherlands.,Departments of Chemistry and Biochemistry, University of Oxford , New Biochemistry Building, South Parks Road, Oxford, OX1 3QU Oxfordshire, United Kingdom
| | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research, Utrecht University , Padualaan 8, 3584 CH Utrecht, The Netherlands.,Netherlands Proteomics Center , Padualaan 8, 3584 CH Utrecht, The Netherlands
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7
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Selvan N, Mariappa D, van den Toorn HWP, Heck AJR, Ferenbach AT, van Aalten DMF. The Early Metazoan Trichoplax adhaerens Possesses a Functional O-GlcNAc System. J Biol Chem 2015; 290:11969-82. [PMID: 25778404 PMCID: PMC4424335 DOI: 10.1074/jbc.m114.628750] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2014] [Indexed: 01/09/2023] Open
Abstract
Protein O-GlcNAcylation is a reversible post-translational signaling modification of nucleocytoplasmic proteins that is essential for embryonic development in bilateria. In a search for a reductionist model to study O-GlcNAc signaling, we discovered the presence of functional O-GlcNAc transferase (OGT), O-GlcNAcase (OGA), and nucleocytoplasmic protein O-GlcNAcylation in the most basal extant animal, the placozoan Trichoplax adhaerens. We show via enzymatic characterization of Trichoplax OGT/OGA and genetic rescue experiments in Drosophila melanogaster that these proteins possess activities/functions similar to their bilaterian counterparts. The acquisition of O-GlcNAc signaling by metazoa may have facilitated the rapid and complex signaling mechanisms required for the evolution of multicellular organisms.
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Affiliation(s)
| | - Daniel Mariappa
- MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dow Street, Dundee, DD1 5EH, United Kingdom and
| | - Henk W P van den Toorn
- the Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Albert J R Heck
- the Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
| | | | - Daan M F van Aalten
- From the Division of Molecular Microbiology and MRC Protein Phosphorylation and Ubiquitylation Unit, College of Life Sciences, University of Dundee, Dow Street, Dundee, DD1 5EH, United Kingdom and
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8
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Walzer M, Pernas LE, Nasso S, Bittremieux W, Nahnsen S, Kelchtermans P, Pichler P, van den Toorn HWP, Staes A, Vandenbussche J, Mazanek M, Taus T, Scheltema RA, Kelstrup CD, Gatto L, van Breukelen B, Aiche S, Valkenborg D, Laukens K, Lilley KS, Olsen JV, Heck AJR, Mechtler K, Aebersold R, Gevaert K, Vizcaíno JA, Hermjakob H, Kohlbacher O, Martens L. qcML: an exchange format for quality control metrics from mass spectrometry experiments. Mol Cell Proteomics 2014; 13:1905-13. [PMID: 24760958 PMCID: PMC4125725 DOI: 10.1074/mcp.m113.035907] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2013] [Revised: 03/13/2014] [Indexed: 12/22/2022] Open
Abstract
Quality control is increasingly recognized as a crucial aspect of mass spectrometry based proteomics. Several recent papers discuss relevant parameters for quality control and present applications to extract these from the instrumental raw data. What has been missing, however, is a standard data exchange format for reporting these performance metrics. We therefore developed the qcML format, an XML-based standard that follows the design principles of the related mzML, mzIdentML, mzQuantML, and TraML standards from the HUPO-PSI (Proteomics Standards Initiative). In addition to the XML format, we also provide tools for the calculation of a wide range of quality metrics as well as a database format and interconversion tools, so that existing LIMS systems can easily add relational storage of the quality control data to their existing schema. We here describe the qcML specification, along with possible use cases and an illustrative example of the subsequent analysis possibilities. All information about qcML is available at http://code.google.com/p/qcml.
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Affiliation(s)
- Mathias Walzer
- From the ‡Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Dept. of Computer Science, University of Tuebingen, Germany
| | - Lucia Espona Pernas
- §Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich, 8092 Zurich, Switzerland
| | - Sara Nasso
- ¶Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland; §Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich, 8092 Zurich, Switzerland
| | - Wout Bittremieux
- ‖Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; **Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Antwerp, Belgium
| | - Sven Nahnsen
- From the ‡Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Dept. of Computer Science, University of Tuebingen, Germany
| | - Pieter Kelchtermans
- ‡‡Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium; §§Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; ¶¶Flemish Institute for Technological Research (VITO), Boeretang 200, B-2400 Mol Belgium
| | - Peter Pichler
- ‖‖Research Institute of Molecular Pathology (IMP), Dr. Bohr-Gasse 7, A-1030 Vienna, Austria; Institute of Molecular Biotechnology of the Austrian Academy of Science (IMBA), Dr. Bohr-Gasse 3, A-1030 Vienna, Austria
| | - Henk W P van den Toorn
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, Netherlands; Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, Netherlands
| | - An Staes
- ‡‡Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium; §§Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Jonathan Vandenbussche
- ‡‡Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium; §§Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Michael Mazanek
- ‖‖Research Institute of Molecular Pathology (IMP), Dr. Bohr-Gasse 7, A-1030 Vienna, Austria; Institute of Molecular Biotechnology of the Austrian Academy of Science (IMBA), Dr. Bohr-Gasse 3, A-1030 Vienna, Austria
| | - Thomas Taus
- ‖‖Research Institute of Molecular Pathology (IMP), Dr. Bohr-Gasse 7, A-1030 Vienna, Austria; Institute of Molecular Biotechnology of the Austrian Academy of Science (IMBA), Dr. Bohr-Gasse 3, A-1030 Vienna, Austria
| | - Richard A Scheltema
- Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany
| | - Christian D Kelstrup
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3b, DK-2200 Copenhagen, Denmark
| | - Laurent Gatto
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, CB2 1GA, United Kingdom; Computational Proteomics Unit, Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge, CB2 1GA, UK
| | - Bas van Breukelen
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, Netherlands; Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, Netherlands
| | - Stephan Aiche
- Department of Mathematics and Computer Science, Freie Universität Berlin, Takustr. 9, 14195 Berlin, Germany
| | - Dirk Valkenborg
- ¶¶Flemish Institute for Technological Research (VITO), Boeretang 200, B-2400 Mol Belgium; I-BioStat, Hasselt University, Belgium; CFP-CeProMa, University of Antwerp, Belgium
| | - Kris Laukens
- ‖Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; **Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Antwerp, Belgium
| | - Kathryn S Lilley
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, CB2 1GA, United Kingdom
| | - Jesper V Olsen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3b, DK-2200 Copenhagen, Denmark
| | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, Netherlands; Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, Netherlands
| | - Karl Mechtler
- ‖‖Research Institute of Molecular Pathology (IMP), Dr. Bohr-Gasse 7, A-1030 Vienna, Austria; Institute of Molecular Biotechnology of the Austrian Academy of Science (IMBA), Dr. Bohr-Gasse 3, A-1030 Vienna, Austria
| | - Ruedi Aebersold
- §Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich, 8092 Zurich, Switzerland; Faculty of Science, University of Zurich, Zurich, Switzerland
| | - Kris Gevaert
- ‡‡Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium; §§Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Henning Hermjakob
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Oliver Kohlbacher
- From the ‡Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Dept. of Computer Science, University of Tuebingen, Germany
| | - Lennart Martens
- ‡‡Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium; §§Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium;
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Côté RG, Griss J, Dianes JA, Wang R, Wright JC, van den Toorn HWP, van Breukelen B, Heck AJR, Hulstaert N, Martens L, Reisinger F, Csordas A, Ovelleiro D, Perez-Rivevol Y, Barsnes H, Hermjakob H, Vizcaíno JA. The PRoteomics IDEntification (PRIDE) Converter 2 framework: an improved suite of tools to facilitate data submission to the PRIDE database and the ProteomeXchange consortium. Mol Cell Proteomics 2012; 11:1682-9. [PMID: 22949509 PMCID: PMC3518121 DOI: 10.1074/mcp.o112.021543] [Citation(s) in RCA: 100] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
The original PRIDE Converter tool greatly simplified the process of submitting mass spectrometry (MS)-based proteomics data to the PRIDE database. However, after much user feedback, it was noted that the tool had some limitations and could not handle several user requirements that were now becoming commonplace. This prompted us to design and implement a whole new suite of tools that would build on the successes of the original PRIDE Converter and allow users to generate submission-ready, well-annotated PRIDE XML files. The PRIDE Converter 2 tool suite allows users to convert search result files into PRIDE XML (the format needed for performing submissions to the PRIDE database), generate mzTab skeleton files that can be used as a basis to submit quantitative and gel-based MS data, and post-process PRIDE XML files by filtering out contaminants and empty spectra, or by merging several PRIDE XML files together. All the tools have both a graphical user interface that provides a dialog-based, user-friendly way to convert and prepare files for submission, as well as a command-line interface that can be used to integrate the tools into existing or novel pipelines, for batch processing and power users. The PRIDE Converter 2 tool suite will thus become a cornerstone in the submission process to PRIDE and, by extension, to the ProteomeXchange consortium of MS-proteomics data repositories.
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Affiliation(s)
- Richard G Côté
- Proteomics Services Team, EMBL Outstation, European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
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10
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Hennrich ML, van den Toorn HWP, Groenewold V, Heck AJR, Mohammed S. Ultra Acidic Strong Cation Exchange Enabling the Efficient Enrichment of Basic Phosphopeptides. Anal Chem 2012; 84:1804-8. [DOI: 10.1021/ac203303t] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Affiliation(s)
- Marco L. Hennrich
- Biomolecular Mass Spectrometry and Proteomics
Group, Bijvoet Center for Biomolecular Research and Utrecht Institute
for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
- Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Henk W. P. van den Toorn
- Biomolecular Mass Spectrometry and Proteomics
Group, Bijvoet Center for Biomolecular Research and Utrecht Institute
for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
- Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, The Netherlands
- Netherlands Bioinformatics Centre, Geert Grooteplein 28, 6525 GA Nijmegen, The Netherlands
| | - Vincent Groenewold
- Molecular Cancer Research and Cancer
Genomics Centre, University Medical Center Utrecht, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands
| | - Albert J. R. Heck
- Biomolecular Mass Spectrometry and Proteomics
Group, Bijvoet Center for Biomolecular Research and Utrecht Institute
for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
- Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, The Netherlands
| | - Shabaz Mohammed
- Biomolecular Mass Spectrometry and Proteomics
Group, Bijvoet Center for Biomolecular Research and Utrecht Institute
for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
- Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, The Netherlands
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11
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van den Toorn HWP, Muñoz J, Mohammed S, Raijmakers R, Heck AJR, van Breukelen B. RockerBox: Analysis and Filtering of Massive Proteomics Search Results. J Proteome Res 2011; 10:1420-4. [DOI: 10.1021/pr1010185] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Henk W. P. van den Toorn
- Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
- Netherlands Proteomics Centre, The Netherlands
- Netherlands Bioinformatics Centre, The Netherlands
| | - Javier Muñoz
- Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
- Netherlands Proteomics Centre, The Netherlands
| | - Shabaz Mohammed
- Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
- Netherlands Proteomics Centre, The Netherlands
| | - Reinout Raijmakers
- Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
- Netherlands Proteomics Centre, The Netherlands
| | - Albert J. R. Heck
- Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
- Netherlands Proteomics Centre, The Netherlands
| | - Bas van Breukelen
- Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
- Netherlands Proteomics Centre, The Netherlands
- Netherlands Bioinformatics Centre, The Netherlands
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12
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van Breukelen B, van den Toorn HWP, Drugan MM, Heck AJR. StatQuant: a post-quantification analysis toolbox for improving quantitative mass spectrometry. ACTA ACUST UNITED AC 2009; 25:1472-3. [PMID: 19336442 DOI: 10.1093/bioinformatics/btp181] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
MOTIVATION Mass spectrometric protein quantitation has emerged as a high-throughput tool to yield large amounts of data on peptide and protein abundances. Currently, differential abundance data can be calculated from peptide intensity ratios by several automated quantitation software packages available. There is, however, still a great need for additional processing to validate and refine the quantitation results. Here, we present a software tool, termed StatQuant, that offers a set of statistical tools to process, filter, compare and represent data from several quantitative proteomics software packages such as MSQuant. StatQuant offers the researcher post-processing methods to achieve improved confidence on the obtained protein ratios. AVAILABILITY StatQuant can be downloaded from: (https://gforge.nbic.nl/projects/statquant/) (binary and source code).
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Affiliation(s)
- Bas van Breukelen
- Biomolecular Mass Spectrometry and Proteomics Group, Utrecht University, Utrech, The Netherlands.
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13
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Aye TT, Mohammed S, van den Toorn HWP, van Veen TAB, van der Heyden MAG, Scholten A, Heck AJR. Selectivity in enrichment of cAMP-dependent protein kinase regulatory subunits type I and type II and their interactors using modified cAMP affinity resins. Mol Cell Proteomics 2008; 8:1016-28. [PMID: 19119138 DOI: 10.1074/mcp.m800226-mcp200] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
cAMP regulates cellular functions primarily by activating PKA. The involvement of PKAs in various signaling pathways occurring simultaneously in different cellular compartments necessitates stringent spatial and temporal regulation. This specificity is largely achieved by binding of PKA to protein scaffolds, whereby a distinct group of proteins called A kinase anchoring proteins (AKAPs) play a dominant role. AKAPs are a diverse family of proteins that all bind via a small PKA binding domain to the regulatory subunits of PKA. The binding affinities between PKA and several AKAPs can be different for different isoforms of the regulatory subunits of PKA. Here we employ a combination of affinity chromatography and mass spectrometry-based quantitative proteomics to investigate specificity in PKA-AKAP interactions. Three different immobilized cAMP analogs were used to enrich for PKA and its interacting proteins from several systems; HEK293 and RCC10 cells and rat lung and testis tissues. Stable isotope labeling was used to confidently identify and differentially quantify target proteins and their preferential binding affinity for the three different cAMP analogs. We were able to enrich all four isoforms of the regulatory subunits of PKA and concomitantly identify more than 10 AKAPs. A selective enrichment of the PKA RI isoforms could be achieved; which allowed us to unravel which AKAPs bind preferentially to the RI or RII regulatory domains of PKA. Of the twelve AKAPs detected, seven preferentially bound to RII, whereas the remaining five displayed at least dual specificity with a potential preference for RI. For some of these AKAPs our data provide the first insights into their specificity.
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Affiliation(s)
- Thin Thin Aye
- Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands
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