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Abstract
Shotgun proteomics is the method of choice for large-scale protein identification. However, the use of a robust statistical workflow to validate such identification is mandatory to minimize false matches, ambiguities, and amplification of error rates from spectra to proteins. In this chapter we emphasize the key concepts to take into account when processing the output of a search engine to obtain reliable peptide or protein identifications. We assume that the reader is already familiar with tandem mass spectrometry so we can focus on the use of statistical confidence methods. After introducing the key concepts we present different software tools and how to use them with an example dataset.
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Affiliation(s)
- Gorka Prieto
- Department of Communications Engineering, Faculty of Engineering of Bilbao, University of the Basque Country (UPV/EHU), Bilbao, Spain.
| | - Jesús Vázquez
- Laboratory of Cardiovascular Proteomics, Centro Nacional de Investigaciones Cardiovasculares (CNIC) and CIBER de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
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2
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González-Gomariz J, Guruceaga E, López-Sánchez M, Segura V. Proteogenomics in the context of the Human Proteome Project (HPP). Expert Rev Proteomics 2019; 16:267-275. [PMID: 30654666 DOI: 10.1080/14789450.2019.1571916] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
INTRODUCTION The technological and scientific progress performed in the Human Proteome Project (HPP) has provided to the scientific community a new set of experimental and bioinformatic methods in the challenging field of shotgun and SRM/MRM-based Proteomics. The requirements for a protein to be considered experimentally validated are now well-established, and the information about the human proteome is available in the neXtProt database, while targeted proteomic assays are stored in SRMAtlas. However, the study of the missing proteins continues being an outstanding issue. Areas covered: This review is focused on the implementation of proteogenomic methods designed to improve the detection and validation of the missing proteins. The evolution of the methodological strategies based on the combination of different omic technologies and the use of huge publicly available datasets is shown taking the Chromosome 16 Consortium as reference. Expert commentary: Proteogenomics and other strategies of data analysis implemented within the C-HPP initiative could be used as guidance to complete in a near future the catalog of the human proteins. Besides, in the next years, we will probably witness their use in the B/D-HPP initiative to go a step forward on the implications of the proteins in the human biology and disease.
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Affiliation(s)
- José González-Gomariz
- a Bioinformatics Platform, Center for Applied Medical Research , University of Navarra , Pamplona , Spain.,b IdiSNA , Navarra Institute for Health Research , Pamplona , Spain
| | - Elizabeth Guruceaga
- a Bioinformatics Platform, Center for Applied Medical Research , University of Navarra , Pamplona , Spain.,b IdiSNA , Navarra Institute for Health Research , Pamplona , Spain
| | - Macarena López-Sánchez
- a Bioinformatics Platform, Center for Applied Medical Research , University of Navarra , Pamplona , Spain
| | - Victor Segura
- a Bioinformatics Platform, Center for Applied Medical Research , University of Navarra , Pamplona , Spain.,b IdiSNA , Navarra Institute for Health Research , Pamplona , Spain
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3
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Martínez-Bartolomé S, Medina-Aunon JA, López-García MÁ, González-Tejedo C, Prieto G, Navajas R, Salazar-Donate E, Fernández-Costa C, Yates JR, Albar JP. PACOM: A Versatile Tool for Integrating, Filtering, Visualizing, and Comparing Multiple Large Mass Spectrometry Proteomics Data Sets. J Proteome Res 2018; 17:1547-1558. [DOI: 10.1021/acs.jproteome.7b00858] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Salvador Martínez-Bartolomé
- Proteomics Laboratory, National Center for Biotechnology, CSIC, Madrid 28049, Spain
- Department of Chemical Physiology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | | | | | | | - Gorka Prieto
- Department of Communications Engineering, University of the Basque Country (UPV/EHU), Bilbao 48013, Spain
| | - Rosana Navajas
- Proteomics Laboratory, National Center for Biotechnology, CSIC, Madrid 28049, Spain
| | | | - Carolina Fernández-Costa
- Department of Chemical Physiology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
- Immunology, Centro de Investigaciones Biomédicas (CINBIO), Centro singular de Investigación de Galicia: Instituto de Investigación Sanitaria Galicia Sur (IIS-GS), University of Vigo, Campus Universitario, s/n, Vigo 36310, Spain
| | - John R. Yates
- Department of Chemical Physiology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Juan Pablo Albar
- Proteomics Laboratory, National Center for Biotechnology, CSIC, Madrid 28049, Spain
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4
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Wang Y, Chen Y, Zhang Y, Wei W, Li Y, Zhang T, He F, Gao Y, Xu P. Multi-Protease Strategy Identifies Three PE2 Missing Proteins in Human Testis Tissue. J Proteome Res 2017; 16:4352-4363. [PMID: 28959888 DOI: 10.1021/acs.jproteome.7b00340] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Although 5 years of the missing proteins (MPs) study have been completed, searching for MPs remains one of the core missions of the Chromosome-Centric Human Proteome Project (C-HPP). Following the next-50-MPs challenge of the C-HPP, we have focused on the testis-enriched MPs by various strategies since 2015. On the basis of the theoretical analysis of MPs (2017-01, neXtProt) using multiprotease digestion, we found that nonconventional proteases (e.g. LysargiNase, GluC) could improve the peptide diversity and sequence coverage compared with Trypsin. Therefore, a multiprotease strategy was used for searching more MPs in the same human testis tissues separated by 10% SDS-PAGE, followed by high resolution LC-MS/MS system (Q Exactive HF). A total of 7838 proteins were identified. Among them, three PE2 MPs in neXtProt 2017-01 have been identified: beta-defensin 123 ( Q8N688 , chr 20q), cancer/testis antigen family 45 member A10 ( P0DMU9 , chr Xq), and Histone H2A-Bbd type 2/3 ( P0C5Z0 , chr Xq). However, because only one unique peptide of ≥9 AA was identified in beta-defensin 123 and Histone H2A-Bbd type 2/3, respectively, further analysis indicates that each falls under the exceptions clause of the HPP Guidelines v2.1. After a spectrum quality check, isobaric PTM and single amino acid variant (SAAV) filtering, and verification with a synthesized peptide, and based on overlapping peptides from different proteases, these three MPs should be considered as exemplary examples of MPs found by exceptional criteria. Other MPs were considered as candidates but need further validation. All MS data sets have been deposited to the ProteomeXchange with identifier PXD006465.
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Affiliation(s)
- Yihao Wang
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China.,Department of Pharmacology and Toxicology, Beijing Institute of Radiation Medicine , Beijing 100850, China
| | - Yang Chen
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China
| | - Yao Zhang
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, College of Ecology and Evolution, Sun Yat-Sen University , Guangzhou 510275, China
| | - Wei Wei
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China
| | - Yanchang Li
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China
| | - Tao Zhang
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China
| | - Fuchu He
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China
| | - Yue Gao
- Department of Pharmacology and Toxicology, Beijing Institute of Radiation Medicine , Beijing 100850, China
| | - Ping Xu
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China.,Key Laboratory of Combinatorial Biosynthesis and Drug Discovery of Ministry of Education, School of Pharmaceutical Sciences, Wuhan University , Wuhan 430072, China.,Graduate School, Anhui Medical University , Hefei 230032, China.,Tianjin Baodi Hospital , Tianjin 301800, China
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5
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Segura V, Garin-Muga A, Guruceaga E, Corrales FJ. Progress and pitfalls in finding the 'missing proteins' from the human proteome map. Expert Rev Proteomics 2016; 14:9-14. [PMID: 27885863 DOI: 10.1080/14789450.2017.1265450] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
INTRODUCTION The Human Proteome Project was launched with two main goals: the comprehensive and systematic definition of the human proteome map and the development of ready to use analytical tools to measure relevant proteins in their biological context in health and disease. Despite the great progress in this endeavour, there is still a group of reluctant proteins with no, or scarce, experimental evidence supporting their existence. These are called the 'missing proteins' and represent one of the biggest challenges to complete the human proteome map. Areas covered: This review focuses on the description of the missing proteome based on the HUPO standards, the analysis of the reasons explaining the difficulty of detecting missing proteins and the strategies currently used in the search for missing proteins. The present and future of the quest for the missing proteins is critically revised hereafter. Expert commentary: An overarching multidisciplinary effort is currently being done under the HUPO umbrella to allow completion of the human proteome map. It is expected that the detection of missing proteins will grow in the coming years since the methods and the best tissue/cell type sample for their search are already on the table.
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Affiliation(s)
- Victor Segura
- a Proteomics and Bioinformatics Laboratory, CIMA , University of Navarra , Pamplona , Spain
| | - Alba Garin-Muga
- a Proteomics and Bioinformatics Laboratory, CIMA , University of Navarra , Pamplona , Spain
| | - Elizabeth Guruceaga
- a Proteomics and Bioinformatics Laboratory, CIMA , University of Navarra , Pamplona , Spain
| | - Fernando J Corrales
- a Proteomics and Bioinformatics Laboratory, CIMA , University of Navarra , Pamplona , Spain
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6
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Multiplexed mass spectrometry monitoring of biomarker candidates for osteoarthritis. J Proteomics 2016; 152:216-225. [PMID: 27865793 DOI: 10.1016/j.jprot.2016.11.012] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Revised: 11/10/2016] [Accepted: 11/14/2016] [Indexed: 12/22/2022]
Abstract
The methods currently available for the diagnosis and monitoring of osteoarthritis (OA) are very limited and lack sensitivity. Being the most prevalent rheumatic disease, one of the most disabling pathologies worldwide and currently untreatable, there is a considerable interest pointed in the verification of specific biological markers for improving its diagnosis and disease progression studies. Considering the remarkable development of targeted proteomics methodologies in the frame of the Human Proteome Project, the aim of this work was to develop and apply a MRM-based method for the multiplexed analysis of a panel of 6 biomarker candidates for OA encoded by the Chromosome 16, and another 8 proteins identified in previous shotgun studies as related with this pathology, in specimens derived from the human joint and serum. The method, targeting 35 different peptides, was applied to samples from human articular chondrocytes, healthy and osteoarthritic cartilage, synovial fluid and serum. Subsequently, a verification analysis of the biomarker value of these proteins was performed by single point measurements on a set of 116 serum samples, leading to the identification of increased amounts of Haptoglobin and von Willebrand Factor in OA patients. Altogether, the present work provides a tool for the multiplexed monitoring of 14 biomarker candidates for OA, and verifies for the first time the increased amount of two of these circulating markers in patients diagnosed with this disease. SIGNIFICANCE We have developed an MRM method for the identification and relative quantification of a panel of 14 protein biomarker candidates for osteoarthritis. This method has been applied to analyze human articular chondrocytes, articular cartilage, synovial fluid, and finally a collection of 116 serum samples from healthy controls and patients suffering different degrees of osteoarthritis, in order to verify the biomarker usefulness of the candidates. HPT and VWF were validated as increased in OA patients.
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Psatha K, Kollipara L, Voutyraki C, Divanach P, Sickmann A, Rassidakis GZ, Drakos E, Aivaliotis M. Deciphering lymphoma pathogenesis via state-of-the-art mass spectrometry-based quantitative proteomics. J Chromatogr B Analyt Technol Biomed Life Sci 2016; 1047:2-14. [PMID: 27979587 DOI: 10.1016/j.jchromb.2016.11.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Revised: 10/18/2016] [Accepted: 11/04/2016] [Indexed: 12/13/2022]
Abstract
Mass spectrometry-based quantitative proteomics specifically applied to comprehend the pathogenesis of lymphoma has incremental value in deciphering the heterogeneity in complex deregulated molecular mechanisms/pathways of the lymphoma entities, implementing the current diagnostic and therapeutic strategies. Essential global, targeted and functional differential proteomics analyses although still evolving, have been successfully implemented to shed light on lymphoma pathogenesis to discover and explore the role of potential lymphoma biomarkers and drug targets. This review aims to outline and appraise the present status of MS-based quantitative proteomic approaches in lymphoma research, introducing the current state-of-the-art MS-based proteomic technologies, the opportunities they offer in biological discovery in human lymphomas and the related limitation issues arising from sample preparation to data evaluation. It is a synopsis containing information obtained from recent research articles, reviews and public proteomics repositories (PRIDE). We hope that this review article will aid, assimilate and assess all the information aiming to accelerate the development and validation of diagnostic, prognostic or therapeutic targets for an improved and empowered clinical proteomics application in lymphomas in the nearby future.
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Affiliation(s)
- Konstantina Psatha
- Institute of Molecular Biology and Biotechnology, FORTH, Heraklion, Greece; School of Medicine, National and Kapodistrian University of Athens, Athens, Greece; Department of Pathology, School of Medicine, University of Crete, Heraklion, Greece
| | - Laxmikanth Kollipara
- Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany
| | | | - Peter Divanach
- Institute of Molecular Biology and Biotechnology, FORTH, Heraklion, Greece
| | - Albert Sickmann
- Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany; Department of Chemistry, College of Physical Sciences, University of Aberdeen, Aberdeen, Scotland, United Kingdom; Medizinische Fakultät, Medizinische Proteom-Center (MPC), Ruhr-Universität Bochum, Bochum, Germany
| | - George Z Rassidakis
- School of Medicine, National and Kapodistrian University of Athens, Athens, Greece; Department of Pathology and Cytology, Karolinska University Hospital and Karolinska Institute, Radiumhemmet, Stockholm, SE-17176, Sweden
| | - Elias Drakos
- Department of Pathology, School of Medicine, University of Crete, Heraklion, Greece
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Garin-Muga A, Odriozola L, Martínez-Val A, Del Toro N, Martínez R, Molina M, Cantero L, Rivera R, Garrido N, Dominguez F, Sanchez Del Pino MM, Vizcaíno JA, Corrales FJ, Segura V. Detection of Missing Proteins Using the PRIDE Database as a Source of Mass Spectrometry Evidence. J Proteome Res 2016; 15:4101-4115. [PMID: 27581094 PMCID: PMC5099979 DOI: 10.1021/acs.jproteome.6b00437] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
![]()
The current catalogue of the human
proteome is not yet complete,
as experimental proteomics evidence is still elusive for a group of
proteins known as the missing proteins. The Human Proteome Project
(HPP) has been successfully using technology and bioinformatic resources
to improve the characterization of such challenging proteins. In this
manuscript, we propose a pipeline starting with the mining of the
PRIDE database to select a group of data sets potentially enriched
in missing proteins that are subsequently analyzed for protein identification
with a method based on the statistical analysis of proteotypic peptides.
Spermatozoa and the HEK293 cell line were found to be a promising
source of missing proteins and clearly merit further attention in
future studies. After the analysis of the selected samples, we found
342 PSMs, suggesting the presence of 97 missing proteins in human
spermatozoa or the HEK293 cell line, while only 36 missing proteins
were potentially detected in the retina, frontal cortex, aorta thoracica,
or placenta. The functional analysis of the missing proteins detected
confirmed their tissue specificity, and the validation of a selected
set of peptides using targeted proteomics (SRM/MRM assays) further
supports the utility of the proposed pipeline. As illustrative examples,
DNAH3 and TEPP in spermatozoa, and UNCX and ATAD3C in HEK293 cells
were some of the more robust and remarkable identifications in this
study. We provide evidence indicating the relevance to carefully analyze
the ever-increasing MS/MS data available from PRIDE and other repositories
as sources for missing proteins detection in specific biological matrices
as revealed for HEK293 cells.
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Affiliation(s)
- Alba Garin-Muga
- Proteomics and Bioinformatics Unit, Center for Applied Medical Research, University of Navarra , 31008, Pamplona, Spain
| | - Leticia Odriozola
- Proteomics and Bioinformatics Unit, Center for Applied Medical Research, University of Navarra , 31008, Pamplona, Spain.,IdiSNA, Navarra Institute for Health Research , 31008, Pamplona, Spain
| | - Ana Martínez-Val
- Proteomics Unit, Spanish National Cancer Research Centre , 28029, Madrid, Spain
| | - Noemí Del Toro
- European Molecular Biology Laboratory, European Bioinformatics Institute , Wellcome Trust GenomeCampus, Hinxton, Cambridge, CB10 1SD, U.K
| | - Rocío Martínez
- Proteomics and Bioinformatics Unit, Center for Applied Medical Research, University of Navarra , 31008, Pamplona, Spain
| | - Manuela Molina
- Proteomics and Bioinformatics Unit, Center for Applied Medical Research, University of Navarra , 31008, Pamplona, Spain
| | - Laura Cantero
- Proteomics Unit (SCSIE), University of Valencia , 46010, Valencia, Spain
| | - Rocío Rivera
- Andrology Laboratory and Sperm Bank, Instituto Universitario IVI , 46015, Valencia, Spain
| | - Nicolás Garrido
- Andrology Laboratory and Sperm Bank, Instituto Universitario IVI , 46015, Valencia, Spain
| | | | | | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute , Wellcome Trust GenomeCampus, Hinxton, Cambridge, CB10 1SD, U.K
| | - Fernando J Corrales
- Proteomics and Bioinformatics Unit, Center for Applied Medical Research, University of Navarra , 31008, Pamplona, Spain.,IdiSNA, Navarra Institute for Health Research , 31008, Pamplona, Spain.,Division of Hepatology and Gene Therapy, Center for Applied Medical Research, University of Navarra , 31008, Pamplona, Spain
| | - Victor Segura
- Proteomics and Bioinformatics Unit, Center for Applied Medical Research, University of Navarra , 31008, Pamplona, Spain.,IdiSNA, Navarra Institute for Health Research , 31008, Pamplona, Spain
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9
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Poverennaya EV, Kopylov AT, Ponomarenko EA, Ilgisonis EV, Zgoda VG, Tikhonova OV, Novikova SE, Farafonova TE, Kiseleva YY, Radko SP, Vakhrushev IV, Yarygin KN, Moshkovskii SA, Kiseleva OI, Lisitsa AV, Sokolov AS, Mazur AM, Prokhortchouk EB, Skryabin KG, Kostrjukova ES, Tyakht AV, Gorbachev AY, Ilina EN, Govorun VM, Archakov AI. State of the Art of Chromosome 18-Centric HPP in 2016: Transcriptome and Proteome Profiling of Liver Tissue and HepG2 Cells. J Proteome Res 2016; 15:4030-4038. [PMID: 27527821 DOI: 10.1021/acs.jproteome.6b00380] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
A gene-centric approach was applied for a large-scale study of expression products of a single chromosome. Transcriptome profiling of liver tissue and HepG2 cell line was independently performed using two RNA-Seq platforms (SOLiD and Illumina) and also by Droplet Digital PCR (ddPCR) and quantitative RT-PCR. Proteome profiling was performed using shotgun LC-MS/MS as well as selected reaction monitoring with stable isotope-labeled standards (SRM/SIS) for liver tissue and HepG2 cells. On the basis of SRM/SIS measurements, protein copy numbers were estimated for the Chromosome 18 (Chr 18) encoded proteins in the selected types of biological material. These values were compared with expression levels of corresponding mRNA. As a result, we obtained information about 158 and 142 transcripts for HepG2 cell line and liver tissue, respectively. SRM/SIS measurements and shotgun LC-MS/MS allowed us to detect 91 Chr 18-encoded proteins in total, while an intersection between the HepG2 cell line and liver tissue proteomes was ∼66%. In total, there were 16 proteins specifically observed in HepG2 cell line, while 15 proteins were found solely in the liver tissue. Comparison between proteome and transcriptome revealed a poor correlation (R2 ≈ 0.1) between corresponding mRNA and protein expression levels. The SRM and shotgun data sets (obtained during 2015-2016) are available in PASSEL (PASS00697) and ProteomeExchange/PRIDE (PXD004407). All measurements were also uploaded into the in-house Chr 18 Knowledgebase at http://kb18.ru/protein/matrix/416126 .
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Affiliation(s)
| | - Arthur T Kopylov
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia
| | - Elena A Ponomarenko
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia
| | | | - Victor G Zgoda
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia
| | - Olga V Tikhonova
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia
| | - Svetlana E Novikova
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia
| | - Tatyana E Farafonova
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia
| | - Yana Yu Kiseleva
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia
| | - Sergey P Radko
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia
| | - Igor V Vakhrushev
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia
| | - Konstantin N Yarygin
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia
| | - Sergei A Moshkovskii
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia.,Pirogov Russian National Research Medical University , Ostrovitianov Str. 1, Moscow 117997, Russia
| | - Olga I Kiseleva
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia
| | - Andrey V Lisitsa
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia
| | - Alexey S Sokolov
- Center "Bioengineering" Russian Academy of Sciences , Prospect 60-let Oktyabrya, 7, Build.1, Moscow 119071, Russia
| | - Alexander M Mazur
- Center "Bioengineering" Russian Academy of Sciences , Prospect 60-let Oktyabrya, 7, Build.1, Moscow 119071, Russia
| | - Egor B Prokhortchouk
- Center "Bioengineering" Russian Academy of Sciences , Prospect 60-let Oktyabrya, 7, Build.1, Moscow 119071, Russia
| | - Konstantin G Skryabin
- Center "Bioengineering" Russian Academy of Sciences , Prospect 60-let Oktyabrya, 7, Build.1, Moscow 119071, Russia
| | - Elena S Kostrjukova
- Scientific Research Institute of Physical-Chemical Medicine , Malaya Pirogovskaya, 1a, Moscow 119435, Russia
| | - Alexander V Tyakht
- Scientific Research Institute of Physical-Chemical Medicine , Malaya Pirogovskaya, 1a, Moscow 119435, Russia
| | - Alexey Yu Gorbachev
- Scientific Research Institute of Physical-Chemical Medicine , Malaya Pirogovskaya, 1a, Moscow 119435, Russia
| | - Elena N Ilina
- Scientific Research Institute of Physical-Chemical Medicine , Malaya Pirogovskaya, 1a, Moscow 119435, Russia
| | - Vadim M Govorun
- Scientific Research Institute of Physical-Chemical Medicine , Malaya Pirogovskaya, 1a, Moscow 119435, Russia
| | - Alexander I Archakov
- Institute of Biomedical Chemistry , Pogodinskaya Street, 10, Moscow 119121, Russia
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10
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Zhao M, Wei W, Cheng L, Zhang Y, Wu F, He F, Xu P. Searching Missing Proteins Based on the Optimization of Membrane Protein Enrichment and Digestion Process. J Proteome Res 2016; 15:4020-4029. [PMID: 27485413 DOI: 10.1021/acs.jproteome.6b00389] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
A membrane protein enrichment method composed of ultracentrifugation and detergent-based extraction was first developed based on MCF7 cell line. Then, in-solution digestion with detergents and eFASP (enhanced filter-aided sample preparation) with detergents were compared with the time-consuming in-gel digestion method. Among the in-solution digestion strategies, the eFASP combined with RapiGest identified 1125 membrane proteins. Similarly, the eFASP combined with sodium deoxycholate identified 1069 membrane proteins; however, the in-gel digestion characterized 1091 membrane proteins. Totally, with the five digestion methods, 1390 membrane proteins were identified with ≥1 unique peptides, among which 1345 membrane proteins contain unique peptides ≥2. This is the biggest membrane protein data set for MCF7 cell line and even breast cancer tissue samples. Interestingly, we identified 13 unique peptides belonging to 8 missing proteins (MPs). Finally, eight unique peptides were validated by synthesized peptides. Two proteins were confirmed as MPs, and another two proteins were candidate detections.
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Affiliation(s)
- Mingzhi Zhao
- State Key Laboratory of Proteomics, National Engineering Research Center for Protein Drugs, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing Institute of Radiation Medicine , Beijing 102206, P. R. China
| | - Wei Wei
- State Key Laboratory of Proteomics, National Engineering Research Center for Protein Drugs, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing Institute of Radiation Medicine , Beijing 102206, P. R. China
| | - Long Cheng
- Department of Medical Molecular Biology, Beijing Institute of Biotechnology , 27 Tai-Ping Lu Road, Beijing 100850, China
| | - Yao Zhang
- State Key Laboratory of Proteomics, National Engineering Research Center for Protein Drugs, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing Institute of Radiation Medicine , Beijing 102206, P. R. China.,Institute of Microbiology, Chinese Academy of Science , Beijing 100101, China
| | - Feilin Wu
- State Key Laboratory of Proteomics, National Engineering Research Center for Protein Drugs, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing Institute of Radiation Medicine , Beijing 102206, P. R. China.,Life Science College, Southwest Forestry University , Kunming 650224, P. R. China
| | - Fuchu He
- State Key Laboratory of Proteomics, National Engineering Research Center for Protein Drugs, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing Institute of Radiation Medicine , Beijing 102206, P. R. China
| | - Ping Xu
- State Key Laboratory of Proteomics, National Engineering Research Center for Protein Drugs, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing Institute of Radiation Medicine , Beijing 102206, P. R. China.,Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, and Wuhan University School of Pharmaceutical Sciences , Wuhan 430071, P. R. China.,Anhui Medical University , Hefei 230032, Anhui, P. R. China
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11
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Sallou O, Duek PD, Darde TA, Collin O, Lane L, Chalmel F. PepPSy: a web server to prioritize gene products in experimental and biocuration workflows. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2016; 2016:baw070. [PMID: 27173522 PMCID: PMC4865363 DOI: 10.1093/database/baw070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/26/2015] [Accepted: 04/13/2016] [Indexed: 12/03/2022]
Abstract
Among the 20 000 human gene products predicted from genome annotation, about 3000 still lack validation at protein level. We developed PepPSy, a user-friendly gene expression-based prioritization system, to help investigators to determine in which human tissues they should look for an unseen protein. PepPSy can also be used by biocurators to revisit the annotation of specific categories of proteins based on the ‘omics’ data housed by the system. In this study, it was used to prioritize 21 dubious protein-coding genes among the 616 annotated in neXtProt for reannotation. PepPSy is freely available at http://peppsy.genouest.org. Database URL:http://peppsy.genouest.org.
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Affiliation(s)
- Olivier Sallou
- Genouest Bioinformatics Platform, IRISA, Campus de Beaulieu, Rennes 35042, France
| | - Paula D Duek
- CALIPHO Group, SIB Swiss Institute of Bioinformatics, CMU, Michel Servet 1, Geneva 1211, Switzerland
| | - Thomas A Darde
- Genouest Bioinformatics Platform, IRISA, Campus de Beaulieu, Rennes 35042, France IRSET, Inserm U1085, 9 avenue du Professeur Léon Bernard, Rennes 35000, France
| | - Olivier Collin
- Genouest Bioinformatics Platform, IRISA, Campus de Beaulieu, Rennes 35042, France
| | - Lydie Lane
- CALIPHO Group, SIB Swiss Institute of Bioinformatics, CMU, Michel Servet 1, Geneva 1211, Switzerland Department of Human Protein Sciences, Faculty of Medicine, University of Geneva, CMU, Michel Servet 1, Geneva 1211, Switzerland
| | - Frédéric Chalmel
- IRSET, Inserm U1085, 9 avenue du Professeur Léon Bernard, Rennes 35000, France
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12
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Locard-Paulet M, Pible O, Gonzalez de Peredo A, Alpha-Bazin B, Almunia C, Burlet-Schiltz O, Armengaud J. Clinical implications of recent advances in proteogenomics. Expert Rev Proteomics 2016; 13:185-99. [DOI: 10.1586/14789450.2016.1132169] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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13
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Proteogenomic Analysis of Single Amino Acid Polymorphisms in Cancer Research. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2016; 926:93-113. [PMID: 27686808 DOI: 10.1007/978-3-319-42316-6_7] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
The integration of genomics and proteomics has led to the emergence of proteogenomics, a field of research successfully applied to the characterization of cancer samples. The diagnosis, prognosis and response to therapy of cancer patients will largely benefit from the identification of mutations present in their genome. The current state of the art of high throughput experiments for genome-wide detection of somatic mutations in cancer samples has allowed the development of projects such as the TCGA, in which hundreds of cancer genomes have been sequenced. This huge amount of data can be used to generate protein sequence databases in which each entry corresponds to a mutated peptide associated with certain cancer types. In this chapter, we describe a bioinformatics workflow for creating these databases and detecting mutated peptides in cancer samples from proteomic shotgun experiments. The performance of the proposed method has been evaluated using publicly available datasets from four cancer cell lines.
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14
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Nguyen TD, Vidal-Cortes O, Gallardo O, Abian J, Carrascal M. LymPHOS 2.0: an update of a phosphosite database of primary human T cells. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2015; 2015:bav115. [PMID: 26708986 PMCID: PMC4691341 DOI: 10.1093/database/bav115] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2015] [Accepted: 11/16/2015] [Indexed: 01/07/2023]
Abstract
LymPHOS is a web-oriented database containing peptide and protein sequences and spectrometric information on the phosphoproteome of primary human T-Lymphocytes. Current release 2.0 contains 15 566 phosphorylation sites from 8273 unique phosphopeptides and 4937 proteins, which correspond to a 45-fold increase over the original database description. It now includes quantitative data on phosphorylation changes after time-dependent treatment with activators of the TCR-mediated signal transduction pathway. Sequence data quality has also been improved with the use of multiple search engines for database searching. LymPHOS can be publicly accessed at http://www.lymphos.org. Database URL:http://www.lymphos.org.
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Affiliation(s)
- Tien Dung Nguyen
- CSIC/UAB Proteomics Laboratory, Instituto De Investigaciones Biomédicas De Barcelona-Consejo Superior De Investigaciones Científicas (IIBB-CSIC/IDIBAPS), Rosellón 161 6a Planta, Barcelona E-08036, Spain
| | - Oriol Vidal-Cortes
- CSIC/UAB Proteomics Laboratory, Instituto De Investigaciones Biomédicas De Barcelona-Consejo Superior De Investigaciones Científicas (IIBB-CSIC/IDIBAPS), Rosellón 161 6a Planta, Barcelona E-08036, Spain
| | - Oscar Gallardo
- CSIC/UAB Proteomics Laboratory, Instituto De Investigaciones Biomédicas De Barcelona-Consejo Superior De Investigaciones Científicas (IIBB-CSIC/IDIBAPS), Rosellón 161 6a Planta, Barcelona E-08036, Spain
| | - Joaquin Abian
- CSIC/UAB Proteomics Laboratory, Instituto De Investigaciones Biomédicas De Barcelona-Consejo Superior De Investigaciones Científicas (IIBB-CSIC/IDIBAPS), Rosellón 161 6a Planta, Barcelona E-08036, Spain
| | - Montserrat Carrascal
- CSIC/UAB Proteomics Laboratory, Instituto De Investigaciones Biomédicas De Barcelona-Consejo Superior De Investigaciones Científicas (IIBB-CSIC/IDIBAPS), Rosellón 161 6a Planta, Barcelona E-08036, Spain
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15
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Kitata RB, Dimayacyac-Esleta BRT, Choong WK, Tsai CF, Lin TD, Tsou CC, Weng SH, Chen YJ, Yang PC, Arco SD, Nesvizhskii AI, Sung TY, Chen YJ. Mining Missing Membrane Proteins by High-pH Reverse-Phase StageTip Fractionation and Multiple Reaction Monitoring Mass Spectrometry. J Proteome Res 2015. [PMID: 26202522 DOI: 10.1021/acs.jproteome.5b00477] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Despite significant efforts in the past decade toward complete mapping of the human proteome, 3564 proteins (neXtProt, 09-2014) are still "missing proteins". Over one-third of these missing proteins are annotated as membrane proteins, owing to their relatively challenging accessibility with standard shotgun proteomics. Using nonsmall cell lung cancer (NSCLC) as a model study, we aim to mine missing proteins from disease-associated membrane proteome, which may be still largely under-represented. To increase identification coverage, we employed Hp-RP StageTip prefractionation of membrane-enriched samples from 11 NSCLC cell lines. Analysis of membrane samples from 20 pairs of tumor and adjacent normal lung tissue was incorporated to include physiologically expressed membrane proteins. Using multiple search engines (X!Tandem, Comet, and Mascot) and stringent evaluation of FDR (MAYU and PeptideShaker), we identified 7702 proteins (66% membrane proteins) and 178 missing proteins (74 membrane proteins) with PSM-, peptide-, and protein-level FDR of 1%. Through multiple reaction monitoring using synthetic peptides, we provided additional evidence of eight missing proteins including seven with transmembrane helix domains. This study demonstrates that mining missing proteins focused on cancer membrane subproteome can greatly contribute to map the whole human proteome. All data were deposited into ProteomeXchange with the identifier PXD002224.
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Affiliation(s)
- Reta Birhanu Kitata
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.,Department of Chemistry, National Tsing Hua University , 101, Sec 2, Kuang-Fu Road, Hsinchu 30013, Taiwan.,Molecular Science and Technology Program, Taiwan International Graduate Program, Academia Sinica , No. 1, Roosevelt Road, Sec. 4, Taipei 10617, Taiwan
| | - Baby Rorielyn T Dimayacyac-Esleta
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.,Institute of Chemistry, University of the Philippines , Diliman Quezon City, Philippines
| | - Wai-Kok Choong
- Institute of Information Science, Academia Sinica , 128 Academia Road, Section 2, Taipei 115, Taiwan
| | - Chia-Feng Tsai
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan
| | - Tai-Du Lin
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.,Department of Biochemical Sciences, National Taiwan University , 1 Roosevelt Road, Sec. 4, Taipei 106, Taiwan
| | - Chih-Chiang Tsou
- Department of Computational Medicine and Bioinformatics and Department of Pathology, University of Michigan Medical School , 1301 Catherine, Ann Arbor, Michigan 48109, United States
| | - Shao-Hsing Weng
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.,Genome and Systems Biology Degree Program, National Taiwan University , 1, Roosevelt Road, Section 4, Taipei 10617, Taiwan
| | - Yi-Ju Chen
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan
| | - Pan-Chyr Yang
- Department of Internal Medicine, National Taiwan University Hospital , 1 Jen-Ai Road, Section 1, Taipei 10051, Taiwan.,National Taiwan University College of Medicine , No. 1, Section 1, Ren'ai Road, Taipei 100, Taiwan.,Institute of Biomedical Science, Academia Sinica , 128 Academia Road, Section 2, Taipei 115, Taiwan
| | - Susan D Arco
- Institute of Chemistry, University of the Philippines , Diliman Quezon City, Philippines
| | - Alexey I Nesvizhskii
- Department of Computational Medicine and Bioinformatics and Department of Pathology, University of Michigan Medical School , 1301 Catherine, Ann Arbor, Michigan 48109, United States
| | - Ting-Yi Sung
- Institute of Information Science, Academia Sinica , 128 Academia Road, Section 2, Taipei 115, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.,Department of Chemistry, National Tsing Hua University , 101, Sec 2, Kuang-Fu Road, Hsinchu 30013, Taiwan.,Molecular Science and Technology Program, Taiwan International Graduate Program, Academia Sinica , No. 1, Roosevelt Road, Sec. 4, Taipei 10617, Taiwan
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16
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Díez P, Droste C, Dégano RM, González-Muñoz M, Ibarrola N, Pérez-Andrés M, Garin-Muga A, Segura V, Marko-Varga G, LaBaer J, Orfao A, Corrales FJ, De Las Rivas J, Fuentes M. Integration of Proteomics and Transcriptomics Data Sets for the Analysis of a Lymphoma B-Cell Line in the Context of the Chromosome-Centric Human Proteome Project. J Proteome Res 2015. [PMID: 26216070 DOI: 10.1021/acs.jproteome.5b00474] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
A comprehensive study of the molecular active landscape of human cells can be undertaken to integrate two different but complementary perspectives: transcriptomics, and proteomics. After the genome era, proteomics has emerged as a powerful tool to simultaneously identify and characterize the compendium of thousands of different proteins active in a cell. Thus, the Chromosome-centric Human Proteome Project (C-HPP) is promoting a full characterization of the human proteome combining high-throughput proteomics with the data derived from genome-wide expression profiling of protein-coding genes. Here we present a full proteomic profiling of a human lymphoma B-cell line (Ramos) performed using a nanoUPLC-LTQ-Orbitrap Velos proteomic platform, combined to an in-depth transcriptomic profiling of the same cell type. Data are available via ProteomeXchange with identifier PXD001933. Integration of the proteomic and transcriptomic data sets revealed a 94% overlap in the proteins identified by both -omics approaches. Moreover, functional enrichment analysis of the proteomic profiles showed an enrichment of several functions directly related to the biological and morphological characteristics of B-cells. In turn, about 30% of all protein-coding genes present in the whole human genome were identified as being expressed by the Ramos cells (stable average of 30% genes along all the chromosomes), revealing the size of the protein expression-set present in one specific human cell type. Additionally, the identification of missing proteins in our data sets has been reported, highlighting the power of the approach. Also, a comparison between neXtProt and UniProt database searches has been performed. In summary, our transcriptomic and proteomic experimental profiling provided a high coverage report of the expressed proteome from a human lymphoma B-cell type with a clear insight into the biological processes that characterized these cells. In this way, we demonstrated the usefulness of combining -omics for a comprehensive characterization of specific biological systems.
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Affiliation(s)
- Paula Díez
- Department of Medicine and General Cytometry Service-Nucleus, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain.,Proteomics Unit. Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain
| | - Conrad Droste
- Bioinformatics and Functional Genomics Research Group, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain
| | - Rosa M Dégano
- Proteomics Unit. Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain
| | - María González-Muñoz
- Department of Medicine and General Cytometry Service-Nucleus, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain
| | - Nieves Ibarrola
- Proteomics Unit. Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain
| | - Martín Pérez-Andrés
- Department of Medicine and General Cytometry Service-Nucleus, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain
| | - Alba Garin-Muga
- Division of Hepatology and Gene Therapy, Proteomics and Bioinformatics Unit, Centre for Applied Medical Research (CIMA), University of Navarra , 31008 Pamplona, Spain
| | - Víctor Segura
- Division of Hepatology and Gene Therapy, Proteomics and Bioinformatics Unit, Centre for Applied Medical Research (CIMA), University of Navarra , 31008 Pamplona, Spain
| | - Gyorgy Marko-Varga
- Clinical Protein Science and Imaging, Biomedical Centre, Department of Biomedical Engineering, Lund University , BMC D13, 221 84 Lund, Sweden
| | - Joshua LaBaer
- Biodesign Institute, Arizona State University , 1001 South McAllister Avenue, Tempe, Arizona 85287, United States
| | - Alberto Orfao
- Department of Medicine and General Cytometry Service-Nucleus, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain
| | - Fernando J Corrales
- Division of Hepatology and Gene Therapy, Proteomics and Bioinformatics Unit, Centre for Applied Medical Research (CIMA), University of Navarra , 31008 Pamplona, Spain
| | - Javier De Las Rivas
- Bioinformatics and Functional Genomics Research Group, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain
| | - Manuel Fuentes
- Department of Medicine and General Cytometry Service-Nucleus, Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain.,Proteomics Unit. Cancer Research Centre (IBMCC/CSIC/USAL/IBSAL), 37007 Salamanca, Spain
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17
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Krasnov GS, Dmitriev AA, Kudryavtseva AV, Shargunov AV, Karpov DS, Uroshlev LA, Melnikova NV, Blinov VM, Poverennaya EV, Archakov AI, Lisitsa AV, Ponomarenko EA. PPLine: An Automated Pipeline for SNP, SAP, and Splice Variant Detection in the Context of Proteogenomics. J Proteome Res 2015; 14:3729-37. [DOI: 10.1021/acs.jproteome.5b00490] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- George Sergeevich Krasnov
- Engelhardt
Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 111991 Russia
- Orekhovich
Institute of Biomedical Chemistry, Russian Academy of Medical Sciences, Moscow, 119121 Russia
- Mechnikov Research Institute of Vaccines and Sera, Moscow, 105064 Russia
| | | | - Anna Viktorovna Kudryavtseva
- Engelhardt
Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 111991 Russia
- Herzen
Moscow Cancer Research Institute, Ministry of Healthcare of the Russian Federation, Moscow, 125284 Russia
| | - Alexander Valerievich Shargunov
- Orekhovich
Institute of Biomedical Chemistry, Russian Academy of Medical Sciences, Moscow, 119121 Russia
- Mechnikov Research Institute of Vaccines and Sera, Moscow, 105064 Russia
| | - Dmitry Sergeevich Karpov
- Engelhardt
Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 111991 Russia
- Orekhovich
Institute of Biomedical Chemistry, Russian Academy of Medical Sciences, Moscow, 119121 Russia
| | | | | | - Vladimir Mikhailovich Blinov
- Orekhovich
Institute of Biomedical Chemistry, Russian Academy of Medical Sciences, Moscow, 119121 Russia
- Mechnikov Research Institute of Vaccines and Sera, Moscow, 105064 Russia
| | | | | | - Andrey Valerievich Lisitsa
- Orekhovich
Institute of Biomedical Chemistry, Russian Academy of Medical Sciences, Moscow, 119121 Russia
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18
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Parker SJ, Rost H, Rosenberger G, Collins BC, Malmström L, Amodei D, Venkatraman V, Raedschelders K, Van Eyk JE, Aebersold R. Identification of a Set of Conserved Eukaryotic Internal Retention Time Standards for Data-independent Acquisition Mass Spectrometry. Mol Cell Proteomics 2015. [PMID: 26199342 DOI: 10.1074/mcp.o114.042267] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Accurate knowledge of retention time (RT) in liquid chromatography-based mass spectrometry data facilitates peptide identification, quantification, and multiplexing in targeted and discovery-based workflows. Retention time prediction is particularly important for peptide analysis in emerging data-independent acquisition (DIA) experiments such as SWATH-MS. The indexed RT approach, iRT, uses synthetic spiked-in peptide standards (SiRT) to set RT to a unit-less scale, allowing for normalization of peptide RT between different samples and chromatographic set-ups. The obligatory use of SiRTs can be costly and complicates comparisons and data integration if standards are not included in every sample. Reliance on SiRTs also prevents the inclusion of archived mass spectrometry data for generation of the peptide assay libraries central to targeted DIA-MS data analysis. We have identified a set of peptide sequences that are conserved across most eukaryotic species, termed Common internal Retention Time standards (CiRT). In a series of tests to support the appropriateness of the CiRT-based method, we show: (1) the CiRT peptides normalized RT in human, yeast, and mouse cell lysate derived peptide assay libraries and enabled merging of archived libraries for expanded DIA-MS quantitative applications; (2) CiRTs predicted RT in SWATH-MS data within a 2-min margin of error for the majority of peptides; and (3) normalization of RT using the CiRT peptides enabled the accurate SWATH-MS-based quantification of 340 synthetic isotopically labeled peptides that were spiked into either human or yeast cell lysate. To automate and facilitate the use of these CiRT peptide lists or other custom user-defined internal RT reference peptides in DIA workflows, an algorithm was designed to automatically select a high-quality subset of datapoints for robust linear alignment of RT for use. Implementations of this algorithm are available for the OpenSWATH and Skyline platforms. Thus, CiRT peptides can be used alone or as a complement to SiRTs for RT normalization across peptide spectral libraries and in quantitative DIA-MS studies.
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Affiliation(s)
- Sarah J Parker
- ‡‡Advanced Clinical Biosystems Research Institute, The Heart Institute, and Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California
| | - Hannes Rost
- §Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland; ¶PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - George Rosenberger
- §Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland; ¶PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Ben C Collins
- §Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | | | | | - Vidya Venkatraman
- ‡‡Advanced Clinical Biosystems Research Institute, The Heart Institute, and Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California
| | - Koen Raedschelders
- ‡‡Advanced Clinical Biosystems Research Institute, The Heart Institute, and Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California
| | - Jennifer E Van Eyk
- From the ‡Department of Medicine, Johns Hopkins University, Baltimore Maryland; ‡‡Advanced Clinical Biosystems Research Institute, The Heart Institute, and Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California
| | - Ruedi Aebersold
- §Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland; §§Faculty of Science, University of Zurich, Zurich, Switzerland
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19
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Tabas-Madrid D, Alves-Cruzeiro J, Segura V, Guruceaga E, Vialas V, Prieto G, García C, Corrales FJ, Albar JP, Pascual-Montano A. Proteogenomics Dashboard for the Human Proteome Project. J Proteome Res 2015; 14:3738-49. [DOI: 10.1021/acs.jproteome.5b00466] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Daniel Tabas-Madrid
- ProteoRed-ISCIII, National Center for Biotechnology-CSIC (CNB), C/Darwin 3, Madrid 28049, Spain
| | - Joao Alves-Cruzeiro
- ProteoRed-ISCIII, National Center for Biotechnology-CSIC (CNB), C/Darwin 3, Madrid 28049, Spain
| | - Victor Segura
- ProteoRed-ISCIII,
Center for Applied Medical Research (CIMA), University of Navarra, Avda. Pío XII, 55, Pamplona E-31008, Spain
| | - Elizabeth Guruceaga
- ProteoRed-ISCIII,
Center for Applied Medical Research (CIMA), University of Navarra, Avda. Pío XII, 55, Pamplona E-31008, Spain
| | - Vital Vialas
- ProteoRed-ISCIII, National Center for Biotechnology-CSIC (CNB), C/Darwin 3, Madrid 28049, Spain
| | - Gorka Prieto
- Department
of Communication Engineering E.T.S. Ingenierı́a de Bilbao, University of the Basque Country (UPV/EHU), Alda. Urquijo, s/n, Bilbao 48013, Spain
| | - Carlos García
- Computer
Science Faculty, Complutense University of Madrid (UCM), C/ Jose
Garcı́á Santesmases 9, Madrid 28040, Spain
| | - Fernando J. Corrales
- ProteoRed-ISCIII,
Center for Applied Medical Research (CIMA), University of Navarra, Avda. Pío XII, 55, Pamplona E-31008, Spain
| | - Juan Pablo Albar
- ProteoRed-ISCIII, National Center for Biotechnology-CSIC (CNB), C/Darwin 3, Madrid 28049, Spain
| | - Alberto Pascual-Montano
- ProteoRed-ISCIII, National Center for Biotechnology-CSIC (CNB), C/Darwin 3, Madrid 28049, Spain
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20
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Chen Y, Li Y, Zhong J, Zhang J, Chen Z, Yang L, Cao X, He QY, Zhang G, Wang T. Identification of Missing Proteins Defined by Chromosome-Centric Proteome Project in the Cytoplasmic Detergent-Insoluble Proteins. J Proteome Res 2015; 14:3693-709. [DOI: 10.1021/pr501103r] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Yang Chen
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Yaxing Li
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Jiayong Zhong
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Jing Zhang
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Zhipeng Chen
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Lijuan Yang
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Xin Cao
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Qing-Yu He
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Gong Zhang
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Tong Wang
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
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21
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Campos A, Díaz R, Martínez-Bartolomé S, Sierra J, Gallardo O, Sabidó E, López-Lucendo M, Ignacio Casal J, Pasquarello C, Scherl A, Chiva C, Borras E, Odena A, Elortza F, Azkargorta M, Ibarrola N, Canals F, Albar JP, Oliveira E. Multicenter experiment for quality control of peptide-centric LC-MS/MS analysis - A longitudinal performance assessment with nLC coupled to orbitrap MS analyzers. J Proteomics 2015; 127:264-74. [PMID: 25982386 DOI: 10.1016/j.jprot.2015.05.012] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2015] [Revised: 05/07/2015] [Accepted: 05/11/2015] [Indexed: 11/19/2022]
Abstract
Proteomic technologies based on mass spectrometry (MS) have greatly evolved in the past years, and nowadays it is possible to routinely identify thousands of peptides from complex biological samples in a single LC-MS/MS experiment. Despite the advancements in proteomic technologies, the scientific community still faces important challenges in terms of depth and reproducibility of proteomics analyses. Here, we present a multicenter study designed to evaluate long-term performance of LC-MS/MS platforms within the Spanish Proteomics Facilities Network (ProteoRed-ISCIII). The study was performed under well-established standard operating procedures, and demonstrated that it is possible to attain qualitative and quantitative reproducibility over time. Our study highlights the importance of deploying quality assessment metrics routinely in individual laboratories and in multi-laboratory studies. The mass spectrometry data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000205.This article is part of a Special Issue entitled: HUPO 2014.
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Affiliation(s)
- Alex Campos
- ProteoRed-ISCIII, Proteomics Platform, Barcelona Science Park, Barcelona, Spain; Integromics, Madrid, Spain.
| | - Ramón Díaz
- ProteoRed-ISCIII, Proteomics Platform, Barcelona Science Park, Barcelona, Spain
| | | | | | - Oscar Gallardo
- ProteoRed-ISCIII, CSIC/UAB Proteomics Laboratory, Instituto de Investigaciones Biomédicas de Barcelona, Spanish National Research Council, Barcelona, Spain
| | - Eduard Sabidó
- ProteoRed-ISCIII, Proteomics Unit, Universitat Pompeu Fabra (UPF) and Centre de Regulació Genòmica (CRG), Barcelona, Spain
| | - Maria López-Lucendo
- ProteoRed-ISCIII, Proteomics Facility and Functional Proteomics Laboratory, Centro de Investigaciones, Biológicas, Madrid, Spain
| | - J Ignacio Casal
- ProteoRed-ISCIII, Proteomics Facility and Functional Proteomics Laboratory, Centro de Investigaciones, Biológicas, Madrid, Spain
| | | | - Alexander Scherl
- Department of Human Protein Sciences, CMU, University of Geneva, Switzerland
| | - Cristina Chiva
- ProteoRed-ISCIII, Proteomics Unit, Universitat Pompeu Fabra (UPF) and Centre de Regulació Genòmica (CRG), Barcelona, Spain
| | - Eva Borras
- ProteoRed-ISCIII, Proteomics Unit, Universitat Pompeu Fabra (UPF) and Centre de Regulació Genòmica (CRG), Barcelona, Spain
| | - Antonia Odena
- ProteoRed-ISCIII, Proteomics Platform, Barcelona Science Park, Barcelona, Spain
| | - Félix Elortza
- ProteoRed-ISCIII, Proteomics Platform, CIC bioGUNE, CIBERehd, Technology Park of Bizkaia, Derio, Spain
| | - Mikel Azkargorta
- ProteoRed-ISCIII, Proteomics Platform, CIC bioGUNE, CIBERehd, Technology Park of Bizkaia, Derio, Spain
| | - Nieves Ibarrola
- ProteoRed-ISCIII, Centro de Investigación del Cáncer and Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain
| | - Francesc Canals
- ProteoRed-ISCIII, Proteomic Laboratory, Vall d'Hebron Institute of Oncology-VHIO, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Juan P Albar
- ProteoRed-ISCIII, Proteomics Facility, Centro Nacional de Biotecnología - CSIC, Madrid, Spain
| | - Eliandre Oliveira
- ProteoRed-ISCIII, Proteomics Platform, Barcelona Science Park, Barcelona, Spain
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22
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Guruceaga E, Sanchez del Pino MM, Corrales FJ, Segura V. Prediction of a Missing Protein Expression Map in the Context of the Human Proteome Project. J Proteome Res 2015; 14:1350-60. [DOI: 10.1021/pr500850u] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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23
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Pinto SM, Manda SS, Kim MS, Taylor K, Selvan LDN, Balakrishnan L, Subbannayya T, Yan F, Prasad TSK, Gowda H, Lee C, Hancock WS, Pandey A. Functional annotation of proteome encoded by human chromosome 22. J Proteome Res 2014; 13:2749-60. [PMID: 24669763 PMCID: PMC4059257 DOI: 10.1021/pr401169d] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
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As
part of the chromosome-centric human proteome project (C-HPP)
initiative, we report our progress on the annotation of chromosome 22.
Chromosome 22, spanning 51 million base pairs, was the first chromosome
to be sequenced. Gene dosage alterations on this chromosome have been
shown to be associated with a number of congenital anomalies. In addition,
several rare but aggressive tumors have been associated with this
chromosome. A number of important gene families including immunoglobulin
lambda locus, Crystallin beta family, and APOBEC gene family are located
on this chromosome. On the basis of proteomic profiling of 30 histologically
normal tissues and cells using high-resolution mass spectrometry,
we show protein evidence of 367 genes on chromosome 22. Importantly,
this includes 47 proteins, which are currently annotated as “missing”
proteins. We also confirmed the translation start sites of 120 chromosome 22-encoded
proteins. Employing a comprehensive proteogenomics analysis pipeline,
we provide evidence of novel coding regions on this chromosome which
include upstream ORFs and novel exons in addition to correcting existing
gene structures. We describe tissue-wise expression of the proteins
and the distribution of gene families on this chromosome. These data
have been deposited to ProteomeXchange with the identifier PXD000561.
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Affiliation(s)
- Sneha M Pinto
- Institute of Bioinformatics, International Tech Park , Bangalore, Karnataka 560066, India
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24
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Guruceaga E, Monteiro MB, Mora MI, Ortiz L, Corrales FJ, Segura V. Chromosome Transcriptome Profiling in the Context of High-Throughput Proteomics Studies. TRANSLATIONAL BIOINFORMATICS 2014. [DOI: 10.1007/978-94-017-9202-8_3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/06/2022]
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