1
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Lai X, Qi G. Using long columns to quantify over 9200 unique protein groups from brain tissue in a single injection on an Orbitrap Exploris 480 mass spectrometer. J Proteomics 2024; 308:105285. [PMID: 39159862 DOI: 10.1016/j.jprot.2024.105285] [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: 07/13/2024] [Revised: 08/14/2024] [Accepted: 08/16/2024] [Indexed: 08/21/2024]
Abstract
The most exciting advancement in LC-MS/MS-based bottom-up proteomics has centered around enhancing mass spectrometers. Among these, the latest and most advanced mass spectrometer for bottom-up proteomics is the Orbitrap Astral that has the highest scan rate to accelerate throughput and the highest sensitivity to handle a very small amount of peptide samples and to achieve deeper proteomics. However, its affordability remains a challenge for most laboratories. While significant strides have been made in improving mass spectrometry, advancing liquid chromatography (LC) to achieve deeper proteomics has not achieved significant successes since the innovation of Multidimensional Protein Identification Technology (MudPIT) in 2001. To achieve deeper proteomics in a less labor-intensive and more reproducible approach while using a more cost-effective mass spectrometer, such as the Orbitrap Exploris 480, we evaluated trap columns as long as 40 cm and analytical column as long as 600 cm besides sample loading amount, gradient time, and analytical column particle size to enable a fractionation-free method for a single injection to obtain deeper proteomics. The length of trap and analytic columns is the key factor. Using a 30 cm trap column and 250 cm analytical column with other optimized LC conditions, we quantified over 9200 unique protein groups from brain tissue in a single injection using a 24-h gradient on an Orbitrap Exploris 480 mass spectrometer.
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Affiliation(s)
- Xianyin Lai
- Biotechnology Discovery Research, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA.
| | - Guihong Qi
- Biotechnology Discovery Research, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
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2
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Picciani M, Gabriel W, Giurcoiu VG, Shouman O, Hamood F, Lautenbacher L, Jensen CB, Müller J, Kalhor M, Soleymaniniya A, Kuster B, The M, Wilhelm M. Oktoberfest: Open-source spectral library generation and rescoring pipeline based on Prosit. Proteomics 2024; 24:e2300112. [PMID: 37672792 DOI: 10.1002/pmic.202300112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 08/17/2023] [Accepted: 08/18/2023] [Indexed: 09/08/2023]
Abstract
Machine learning (ML) and deep learning (DL) models for peptide property prediction such as Prosit have enabled the creation of high quality in silico reference libraries. These libraries are used in various applications, ranging from data-independent acquisition (DIA) data analysis to data-driven rescoring of search engine results. Here, we present Oktoberfest, an open source Python package of our spectral library generation and rescoring pipeline originally only available online via ProteomicsDB. Oktoberfest is largely search engine agnostic and provides access to online peptide property predictions, promoting the adoption of state-of-the-art ML/DL models in proteomics analysis pipelines. We demonstrate its ability to reproduce and even improve our results from previously published rescoring analyses on two distinct use cases. Oktoberfest is freely available on GitHub (https://github.com/wilhelm-lab/oktoberfest) and can easily be installed locally through the cross-platform PyPI Python package.
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Affiliation(s)
- Mario Picciani
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Wassim Gabriel
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Victor-George Giurcoiu
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Omar Shouman
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Firas Hamood
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Ludwig Lautenbacher
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Cecilia Bang Jensen
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Julian Müller
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Mostafa Kalhor
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Armin Soleymaniniya
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Bernhard Kuster
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Matthew The
- Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Mathias Wilhelm
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
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3
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Hevér H, Xue A, Nagy K, Komka K, Vékey K, Drahos L, Révész Á. Can We Boost N-Glycopeptide Identification Confidence? Smart Collision Energy Choice Taking into Account Structure and Search Engine. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:333-343. [PMID: 38286027 PMCID: PMC10853973 DOI: 10.1021/jasms.3c00375] [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: 10/27/2023] [Revised: 12/22/2023] [Accepted: 01/04/2024] [Indexed: 01/31/2024]
Abstract
High confidence and reproducibility are still challenges in bottom-up mass spectrometric N-glycopeptide identification. The collision energy used in the MS/MS measurements and the database search engine used to identify the species are perhaps the two most decisive factors. We investigated how the structural features of N-glycopeptides and the choice of the search engine influence the optimal collision energy, delivering the highest identification confidence. We carried out LC-MS/MS measurements using a series of collision energies on a large set of N-glycopeptides with both the glycan and peptide part varied and studied the behavior of Byonic, pGlyco, and GlycoQuest scores. We found that search engines show a range of behavior between peptide-centric and glycan-centric, which manifests itself already in the dependence of optimal collision energy on m/z. Using classical statistical and machine learning methods, we revealed that peptide hydrophobicity, glycan and peptide masses, and the number of mobile protons also have significant and search-engine-dependent influence, as opposed to a series of other parameters we probed. We envisioned an MS/MS workflow making a smart collision energy choice based on online available features such as the hydrophobicity (described by retention time) and glycan mass (potentially available from a scout MS/MS). Our assessment suggests that this workflow can lead to a significant gain (up to 100%) in the identification confidence, particularly for low-scoring hits close to the filtering limit, which has the potential to enhance reproducibility of N-glycopeptide analyses. Data are available via MassIVE (MSV000093110).
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Affiliation(s)
- Helga Hevér
- MS
Proteomics Research Group, HUN-REN Research
Centre for Natural Sciences, Magyar Tudósok körútja 2., Budapest H-1117, Hungary
| | - Andrea Xue
- MS
Proteomics Research Group, HUN-REN Research
Centre for Natural Sciences, Magyar Tudósok körútja 2., Budapest H-1117, Hungary
| | - Kinga Nagy
- MS
Proteomics Research Group, HUN-REN Research
Centre for Natural Sciences, Magyar Tudósok körútja 2., Budapest H-1117, Hungary
- Faculty
of Science, Institute of Chemistry, Hevesy György PhD School
of Chemistry, Eötvös Loránd
University, Pázmány
Péter sétány 1/A, Budapest H-1117, Hungary
| | - Kinga Komka
- Department
of Chemical and Environmental Process Engineering, Budapest University of Technology and Economics, Budapest H-1111, Hungary
| | - Károly Vékey
- MS
Proteomics Research Group, HUN-REN Research
Centre for Natural Sciences, Magyar Tudósok körútja 2., Budapest H-1117, Hungary
| | - László Drahos
- MS
Proteomics Research Group, HUN-REN Research
Centre for Natural Sciences, Magyar Tudósok körútja 2., Budapest H-1117, Hungary
| | - Ágnes Révész
- MS
Proteomics Research Group, HUN-REN Research
Centre for Natural Sciences, Magyar Tudósok körútja 2., Budapest H-1117, Hungary
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4
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Szabó D, Gömöry Á, Ludányi K, Vékey K, Drahos L. Very Low-Pressure CID Experiments: High Energy Transfer and Fragmentation Pattern at the Single Collision Regime. Molecules 2023; 29:211. [PMID: 38202794 PMCID: PMC10780993 DOI: 10.3390/molecules29010211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 12/20/2023] [Accepted: 12/25/2023] [Indexed: 01/12/2024] Open
Abstract
We have performed CID experiments on a triple quadrupole instrument, lowering the collision gas pressure by 50 times compared to its conventional value. The results show that at very low-collision gas pressure, single collisions dominate the spectra. Indirectly, these results suggest that under conventional conditions, 20-50 collisions may be typical in CID experiments. The results show a marked difference between low- and high-pressure CID spectra, the latter being characterized in terms of 'slow heating' and predominance of consecutive reactions. The results indicate that under single collision conditions, the collisional energy transfer efficiency is very high: nearly 100% of the center of mass kinetic energy is converted to internal energy.
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Affiliation(s)
- Dániel Szabó
- MS Proteomics Research Group, HUN-REN Research Centre for Natural Sciences, H-1117 Budapest, Hungary (Á.G.); (K.V.)
| | - Ágnes Gömöry
- MS Proteomics Research Group, HUN-REN Research Centre for Natural Sciences, H-1117 Budapest, Hungary (Á.G.); (K.V.)
| | - Krisztina Ludányi
- Department of Pharmaceutics, Semmelweis University, Hőgyes Endre 7–9, H-1092 Budapest, Hungary;
| | - Károly Vékey
- MS Proteomics Research Group, HUN-REN Research Centre for Natural Sciences, H-1117 Budapest, Hungary (Á.G.); (K.V.)
| | - László Drahos
- MS Proteomics Research Group, HUN-REN Research Centre for Natural Sciences, H-1117 Budapest, Hungary (Á.G.); (K.V.)
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5
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De La Toba EA, Anapindi KDB, Sweedler JV. Assessment and Comparison of Database Search Engines for Peptidomic Applications. J Proteome Res 2023; 22:3123-3134. [PMID: 36809008 PMCID: PMC10440370 DOI: 10.1021/acs.jproteome.2c00307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
Protein database search engines are an integral component of mass spectrometry-based peptidomic analyses. Given the unique computational challenges of peptidomics, many factors must be taken into consideration when optimizing search engine selection, as each platform has different algorithms by which tandem mass spectra are scored for subsequent peptide identifications. In this study, four different database search engines, PEAKS, MS-GF+, OMSSA, and X! Tandem, were compared with Aplysia californica and Rattus norvegicus peptidomics data sets, and various metrics were assessed such as the number of unique peptide and neuropeptide identifications, and peptide length distributions. Given the tested conditions, PEAKS was found to have the highest number of peptide and neuropeptide identifications out of the four search engines in both data sets. Furthermore, principal component analysis and multivariate logistic regression were employed to determine whether specific spectral features contribute to false C-terminal amidation assignments by each search engine. From this analysis, it was found that the primary features influencing incorrect peptide assignments were the precursor and fragment ion m/z errors. Finally, an assessment employing a mixed species protein database was performed to evaluate search engine precision and sensitivity when searched against an enlarged search space containing human proteins.
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Affiliation(s)
- Eduardo A. De La Toba
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, 61801
- Department of Chemistry, University of Illinois at Urbana-Champaign, 61801
| | - Krishna D. B. Anapindi
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, 61801
- Department of Chemistry, University of Illinois at Urbana-Champaign, 61801
| | - Jonathan V. Sweedler
- Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, 61801
- Department of Chemistry, University of Illinois at Urbana-Champaign, 61801
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6
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Nagy K, Gellén G, Papp D, Schlosser G, Révész Á. Optimum collision energies for proteomics: The impact of ion mobility separation. JOURNAL OF MASS SPECTROMETRY : JMS 2023; 58:e4957. [PMID: 37415399 DOI: 10.1002/jms.4957] [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: 12/22/2022] [Revised: 05/28/2023] [Accepted: 06/19/2023] [Indexed: 07/08/2023]
Abstract
Ion mobility spectrometry (IMS) is a widespread separation technique used in various research fields. It can be coupled to liquid chromatography-mass spectrometry (LC-MS/MS) methods providing an additional separation dimension. During IMS, ions are subjected to multiple collisions with buffer gas, which may cause significant ion heating. The present project addresses this phenomenon from the bottom-up proteomics point of view. We performed LC-MS/MS measurements on a cyclic ion mobility mass spectrometer with varied collision energy (CE) settings both with and without IMS. We investigated the CE dependence of identification score, using Byonic search engine, for more than 1000 tryptic peptides from HeLa digest standard. We determined the optimal CE values-giving the highest identification score-for both setups (i.e., with and without IMS). Results show that lower CE is advantageous when IMS separation is applied, by 6.3 V on average. This value belongs to the one-cycle separation configuration, and multiple cycles may supposedly have even larger impact. The effect of IMS is also reflected in the trends of optimal CE values versus m/z functions. The parameters suggested by the manufacturer were found to be almost optimal for the setup without IMS; on the other hand, they are obviously too high with IMS. Practical consideration on setting up a mass spectrometric platform hyphenated to IMS is also presented. Furthermore, the two CID (collision induced dissociation) fragmentation cells of the instrument-located before and after the IMS cell-were also compared, and we found that CE adjustment is needed when the trap cell is used for activation instead of the transfer cell. Data have been deposited in the MassIVE repository (MSV000090944).
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Affiliation(s)
- Kinga Nagy
- MS Proteomics Research Group, Research Centre for Natural Sciences, Budapest, H-1117, Hungary
- Hevesy György PhD School of Chemistry, Faculty of Science, Institute of Chemistry, Eötvös Loránd University, Budapest, H-1117, Hungary
| | - Gabriella Gellén
- MTA-ELTE Lendület Ion Mobility Mass Spectrometry Research Group, Faculty of Science, Institute of Chemistry, Eötvös Loránd University, Budapest, H-1117, Hungary
| | - Dávid Papp
- Hevesy György PhD School of Chemistry, Faculty of Science, Institute of Chemistry, Eötvös Loránd University, Budapest, H-1117, Hungary
- MTA-ELTE Lendület Ion Mobility Mass Spectrometry Research Group, Faculty of Science, Institute of Chemistry, Eötvös Loránd University, Budapest, H-1117, Hungary
| | - Gitta Schlosser
- MTA-ELTE Lendület Ion Mobility Mass Spectrometry Research Group, Faculty of Science, Institute of Chemistry, Eötvös Loránd University, Budapest, H-1117, Hungary
| | - Ágnes Révész
- MS Proteomics Research Group, Research Centre for Natural Sciences, Budapest, H-1117, Hungary
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7
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Révész Á, Hevér H, Steckel A, Schlosser G, Szabó D, Vékey K, Drahos L. Collision energies: Optimization strategies for bottom-up proteomics. MASS SPECTROMETRY REVIEWS 2023; 42:1261-1299. [PMID: 34859467 DOI: 10.1002/mas.21763] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 11/17/2021] [Accepted: 11/17/2021] [Indexed: 06/07/2023]
Abstract
Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.
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Affiliation(s)
- Ágnes Révész
- MS Proteomics Research Group, Institute of Organic Chemistry, Research Centre for Natural Sciences, Budapest, Hungary
| | - Helga Hevér
- Chemical Works of Gedeon Richter Plc, Budapest, Hungary
| | - Arnold Steckel
- Department of Analytical Chemistry, MTA-ELTE Lendület Ion Mobility Mass Spectrometry Research Group, Institute of Chemistry, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Gitta Schlosser
- Department of Analytical Chemistry, MTA-ELTE Lendület Ion Mobility Mass Spectrometry Research Group, Institute of Chemistry, ELTE Eötvös Loránd University, Budapest, Hungary
| | - Dániel Szabó
- MS Proteomics Research Group, Institute of Organic Chemistry, Research Centre for Natural Sciences, Budapest, Hungary
| | - Károly Vékey
- MS Proteomics Research Group, Institute of Organic Chemistry, Research Centre for Natural Sciences, Budapest, Hungary
| | - László Drahos
- MS Proteomics Research Group, Institute of Organic Chemistry, Research Centre for Natural Sciences, Budapest, Hungary
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8
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Hevér H, Nagy K, Xue A, Sugár S, Komka K, Vékey K, Drahos L, Révész Á. Diversity Matters: Optimal Collision Energies for Tandem Mass Spectrometric Analysis of a Large Set of N-Glycopeptides. J Proteome Res 2022; 21:2743-2753. [PMID: 36201757 DOI: 10.1021/acs.jproteome.2c00519] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Identification and characterization of N-glycopeptides from complex samples are usually based on tandem mass spectrometric measurements. Experimental settings, especially the collision energy selection method, fundamentally influence the obtained fragmentation pattern and hence the confidence of the database search results ("score"). Using standards of naturally occurring glycoproteins, we mapped the Byonic and pGlyco search engine scores of almost 200 individual N-glycopeptides as a function of collision energy settings on a quadrupole time of flight instrument. The resulting unprecedented amount of peptide-level information on such a large and diverse set of N-glycopeptides revealed that the peptide sequence heavily influences the energy for the highest score on top of an expected general linear trend with m/z. Search engine dependence may also be noteworthy. Based on the trends, we designed an experimental method and tested it on HeLa, blood plasma, and monoclonal antibody samples. As compared to the literature, these notably lower collision energies in our workflow led to 10-50% more identified N-glycopeptides, with higher scores. We recommend a simple approach based on a small set of reference N-glycopeptides easily accessible from glycoprotein standards to ease the precise determination of optimal methods on other instruments. Data sets can be accessed via the MassIVE repository (MSV000089657 and MSV000090218).
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Affiliation(s)
- Helga Hevér
- MS Proteomics Research Group, Eötvös Loránd Research Network, Research Centre for Natural Sciences, Magyar Tudósok körútja 2, Budapest H-1117, Hungary.,Chemical Works of Gedeon Richter Plc, Gyömríi út 19-21, Budapest 1103, Hungary
| | - Kinga Nagy
- MS Proteomics Research Group, Eötvös Loránd Research Network, Research Centre for Natural Sciences, Magyar Tudósok körútja 2, Budapest H-1117, Hungary.,Hevesy György PhD School of Chemistry, Faculty of Science, Institute of Chemistry, Eötvös Loránd University, Pázmány Péter sétány 1/A, Budapest H-1117, Hungary
| | - Andrea Xue
- MS Proteomics Research Group, Eötvös Loránd Research Network, Research Centre for Natural Sciences, Magyar Tudósok körútja 2, Budapest H-1117, Hungary
| | - Simon Sugár
- MS Proteomics Research Group, Eötvös Loránd Research Network, Research Centre for Natural Sciences, Magyar Tudósok körútja 2, Budapest H-1117, Hungary
| | - Kinga Komka
- Department of Chemical and Environmental Process Engineering, Budapest University of Technology and Economics, Budapest H-1111, Hungary
| | - Károly Vékey
- MS Proteomics Research Group, Eötvös Loránd Research Network, Research Centre for Natural Sciences, Magyar Tudósok körútja 2, Budapest H-1117, Hungary
| | - László Drahos
- MS Proteomics Research Group, Eötvös Loránd Research Network, Research Centre for Natural Sciences, Magyar Tudósok körútja 2, Budapest H-1117, Hungary
| | - Ágnes Révész
- MS Proteomics Research Group, Eötvös Loránd Research Network, Research Centre for Natural Sciences, Magyar Tudósok körútja 2, Budapest H-1117, Hungary
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Abstract
Paleoproteomics, the study of ancient proteins, is a rapidly growing field at the intersection of molecular biology, paleontology, archaeology, paleoecology, and history. Paleoproteomics research leverages the longevity and diversity of proteins to explore fundamental questions about the past. While its origins predate the characterization of DNA, it was only with the advent of soft ionization mass spectrometry that the study of ancient proteins became truly feasible. Technological gains over the past 20 years have allowed increasing opportunities to better understand preservation, degradation, and recovery of the rich bioarchive of ancient proteins found in the archaeological and paleontological records. Growing from a handful of studies in the 1990s on individual highly abundant ancient proteins, paleoproteomics today is an expanding field with diverse applications ranging from the taxonomic identification of highly fragmented bones and shells and the phylogenetic resolution of extinct species to the exploration of past cuisines from dental calculus and pottery food crusts and the characterization of past diseases. More broadly, these studies have opened new doors in understanding past human-animal interactions, the reconstruction of past environments and environmental changes, the expansion of the hominin fossil record through large scale screening of nondiagnostic bone fragments, and the phylogenetic resolution of the vertebrate fossil record. Even with these advances, much of the ancient proteomic record still remains unexplored. Here we provide an overview of the history of the field, a summary of the major methods and applications currently in use, and a critical evaluation of current challenges. We conclude by looking to the future, for which innovative solutions and emerging technology will play an important role in enabling us to access the still unexplored "dark" proteome, allowing for a fuller understanding of the role ancient proteins can play in the interpretation of the past.
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Affiliation(s)
- Christina Warinner
- Department
of Anthropology, Harvard University, Cambridge, Massachusetts 02138, United States
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig 04103, Germany
| | - Kristine Korzow Richter
- Department
of Anthropology, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Matthew J. Collins
- Department
of Archaeology, Cambridge University, Cambridge CB2 3DZ, United Kingdom
- Section
for Evolutionary Genomics, Globe Institute,
University of Copenhagen, Copenhagen 1350, Denmark
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10
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Steckel A, Révész Á, Papp D, Uray K, Drahos L, Schlosser G. Stepwise Collision Energy-Resolved Tandem Mass Spectrometric Experiments for the Improved Identification of Citrullinated Peptides. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2022; 33:1176-1186. [PMID: 35621259 DOI: 10.1021/jasms.2c00031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The use of tandem mass spectrometry (MS/MS) is a fundamental prerequisite of reliable protein identification and quantification in mass-spectrometry-based proteomics. In bottom-up and middle-down proteomics, proteins are identified by the characteristic fragments of their constituting peptides. Post-translational modifications (PTMs) often further complicate proteome analyses. Citrullination is an increasingly studied PTM converting arginines to citrullines (Cit, X) and is implicated in several autoimmune and neurological diseases as well as different types of cancer. Confirmation of citrullination is known to be very challenging since it results in the same molecular mass change as Asn/Gln deamidation. In this study, we explore which MS/MS characteristics can be used for the reliable identification of citrullination. We synthesized several peptides incorporating Cit residues that model enzymatic cleavages of different proteins with verified or putative citrullination. Collision-induced dissociation was used to investigate the energy dependence of Byonic and Mascot scores and confirmed sequence coverage (CSC) along with the neutral loss of HNCO characteristic to citrulline side chains. We found that although the recommended values (19-45 V) for ramped collision energy settings cover the optimal Mascot, Byonic, or %CSC scores effectively, the diagnostic HNCO loss from precursors and fragments may reach their maximum intensities at lower and higher collision energies, respectively. Therefore, we suggest broadening the ramp range to ∼5-60 V to obtain more favorable identification rates for citrullinated peptides. We also found that Byonic was more successful in correctly identifying citrullinated peptides with deamidated residues than Mascot.
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Affiliation(s)
- Arnold Steckel
- MTA-ELTE Lendület Ion Mobility Mass Spectrometry Research Group, ELTE Eötvös Loránd University, Institute of Chemistry, Department of Analytical Chemistry, Pázmány Péter sétány 1/A, 1117 Budapest, Hungary
| | - Ágnes Révész
- Research Centre for Natural Sciences, MS Proteomics Research Group, Magyar tudósok körútja 2, 1117 Budapest, Hungary
| | - Dávid Papp
- MTA-ELTE Lendület Ion Mobility Mass Spectrometry Research Group, ELTE Eötvös Loránd University, Institute of Chemistry, Department of Analytical Chemistry, Pázmány Péter sétány 1/A, 1117 Budapest, Hungary
- Hevesy György PhD School of Chemistry, ELTE Eötvös Loránd University, Pázmány Péter sétány 1/A, 1117 Budapest, Hungary
| | - Katalin Uray
- MTA-ELTE Research Group of Peptide Chemistry, Eötvös Loránd Research Network (ELKH), ELTE Eötvös Loránd University, Pázmány Péter sétány 1/A, 1117 Budapest, Hungary
| | - László Drahos
- Research Centre for Natural Sciences, MS Proteomics Research Group, Magyar tudósok körútja 2, 1117 Budapest, Hungary
| | - Gitta Schlosser
- MTA-ELTE Lendület Ion Mobility Mass Spectrometry Research Group, ELTE Eötvös Loránd University, Institute of Chemistry, Department of Analytical Chemistry, Pázmány Péter sétány 1/A, 1117 Budapest, Hungary
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11
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Lu L, Scalf M, Shortreed MR, Smith LM. Mesh Fragmentation Improves Dissociation Efficiency in Top-down Proteomics. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:1319-1325. [PMID: 33754701 PMCID: PMC8783543 DOI: 10.1021/jasms.0c00462] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Top-down proteomics is a key mass spectrometry-based technology for comprehensive analysis of proteoforms. Proteoforms exhibit multiple high charge states and isotopic forms in full MS scans. The dissociation behavior of proteoforms in different charge states and subjected to different collision energies is highly variable. The current widely employed data-dependent acquisition (DDA) method selects a narrow m/z range (corresponding to a single proteoform charge state) for dissociation from the most abundant precursors. We describe here Mesh, a novel dissociation strategy, to dissociate multiple charge states of one proteoform with multiple collision energies. We show that the Mesh strategy has the potential to generate fragment ions with improved sequence coverage and improve identification ratios in top-down proteomic analyses of complex samples. The strategy is implemented within an open-source instrument control software program named MetaDrive to perform real time deconvolution and precursor selection.
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Affiliation(s)
- Lei Lu
- Department of Chemistry, University of Wisconsin, Madison, Wisconsin 53706, United States
| | - Mark Scalf
- Department of Chemistry, University of Wisconsin, Madison, Wisconsin 53706, United States
| | - Michael R. Shortreed
- Department of Chemistry, University of Wisconsin, Madison, Wisconsin 53706, United States
| | - Lloyd M. Smith
- Department of Chemistry, University of Wisconsin, Madison, Wisconsin 53706, United States
- Corresponding Author Phone: (608) 263-2594. Fax: (608) 265-6780.
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