1
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Wang XY, Xu YM, Lau ATY. Proteogenomics in Cancer: Then and Now. J Proteome Res 2023; 22:3103-3122. [PMID: 37725793 DOI: 10.1021/acs.jproteome.3c00196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/21/2023]
Abstract
For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.
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Affiliation(s)
- Xiu-Yun Wang
- Laboratory of Cancer Biology and Epigenetics, Department of Cell Biology and Genetics, Shantou University Medical College, Shantou, Guangdong 515041, People's Republic of China
| | - Yan-Ming Xu
- Laboratory of Cancer Biology and Epigenetics, Department of Cell Biology and Genetics, Shantou University Medical College, Shantou, Guangdong 515041, People's Republic of China
| | - Andy T Y Lau
- Laboratory of Cancer Biology and Epigenetics, Department of Cell Biology and Genetics, Shantou University Medical College, Shantou, Guangdong 515041, People's Republic of China
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2
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Vašíček J, Skiadopoulou D, Kuznetsova KG, Wen B, Johansson S, Njølstad PR, Bruckner S, Käll L, Vaudel M. Finding haplotypic signatures in proteins. Gigascience 2022; 12:giad093. [PMID: 37919975 PMCID: PMC10622322 DOI: 10.1093/gigascience/giad093] [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: 04/13/2023] [Revised: 09/24/2023] [Accepted: 10/08/2023] [Indexed: 11/04/2023] Open
Abstract
BACKGROUND The nonrandom distribution of alleles of common genomic variants produces haplotypes, which are fundamental in medical and population genetic studies. Consequently, protein-coding genes with different co-occurring sets of alleles can encode different amino acid sequences: protein haplotypes. These protein haplotypes are present in biological samples and detectable by mass spectrometry, but they are not accounted for in proteomic searches. Consequently, the impact of haplotypic variation on the results of proteomic searches and the discoverability of peptides specific to haplotypes remain unknown. FINDINGS Here, we study how common genetic haplotypes influence the proteomic search space and investigate the possibility to match peptides containing multiple amino acid substitutions to a publicly available data set of mass spectra. We found that for 12.42% of the discoverable amino acid substitutions encoded by common haplotypes, 2 or more substitutions may co-occur in the same peptide after tryptic digestion of the protein haplotypes. We identified 352 spectra that matched to such multivariant peptides, and out of the 4,582 amino acid substitutions identified, 6.37% were covered by multivariant peptides. However, the evaluation of the reliability of these matches remains challenging, suggesting that refined error rate estimation procedures are needed for such complex proteomic searches. CONCLUSIONS As these procedures become available and the ability to analyze protein haplotypes increases, we anticipate that proteomics will provide new information on the consequences of common variation, across tissues and time.
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Affiliation(s)
- Jakub Vašíček
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen 5021, Norway
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen 5008, Norway
| | - Dafni Skiadopoulou
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen 5021, Norway
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen 5008, Norway
| | - Ksenia G Kuznetsova
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen 5021, Norway
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen 5008, Norway
| | - Bo Wen
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, United States
| | - Stefan Johansson
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen 5021, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen 5021, Norway
| | - Pål R Njølstad
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen 5021, Norway
- Children and Youth Clinic, Haukeland University Hospital, Bergen 5021, Norway
| | - Stefan Bruckner
- Chair of Visual Analytics, Institute for Visual and Analytic Computing, University of Rostock, Rostock 18051, Germany
| | - Lukas Käll
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH–Royal Institute of Technology, Solna 17121, Sweden
| | - Marc Vaudel
- Mohn Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen 5021, Norway
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen 5008, Norway
- Department of Genetics and Bioinformatics, Health Data and Digitalization, Norwegian Institute of Public Health, Oslo 0473, Norway
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3
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Choong WK, Sung TY. Multiaspect Examinations of Possible Alternative Mappings of Identified Variant Peptides: A Case Study on the HEK293 Cell Line. ACS OMEGA 2022; 7:16454-16467. [PMID: 35601313 PMCID: PMC9118379 DOI: 10.1021/acsomega.2c00466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 04/20/2022] [Indexed: 06/15/2023]
Abstract
Adopting proteogenomics approach to validate single nucleotide variation events by identifying corresponding single amino acid variant peptides from mass spectrometry (MS)-based proteomics data facilitates translational and clinical research. Although variant peptides are usually identified from MS data with a stringent false discovery rate (FDR), FDR control could fail to eliminate dubious results caused by several issues; thus, postexamination to eliminate dubious results is required. However, comprehensive postexaminations of identification results are still lacking. Therefore, we propose a framework of three bottom-up levels, peptide-spectrum match, peptide, and variant event levels, that consists of rigorous 11-aspect examinations from the MS perspective to further confirm the reliability of variant events. As a proof of concept and showing feasibility, we demonstrate 11 examinations on the identified variant peptides from an HEK293 cell line data set, where various database search strategies were applied to maximize the number of identified variant PSMs with an FDR <1% for postexaminations. The results showed that only FDR criterion is insufficient to validate identified variant peptides and the 11 postexaminations can reveal low-confidence variant events detected by shotgun proteomics experiments. Therefore, we suggest that postexaminations of identified variant events based on the proposed framework are necessary for proteogenomics studies.
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4
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Levitsky LI, Kuznetsova KG, Kliuchnikova AA, Ilina IY, Goncharov AO, Lobas AA, Ivanov MV, Lazarev VN, Ziganshin RH, Gorshkov MV, Moshkovskii SA. Validating Amino Acid Variants in Proteogenomics Using Sequence Coverage by Multiple Reads. J Proteome Res 2022; 21:1438-1448. [PMID: 35536917 DOI: 10.1021/acs.jproteome.2c00033] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Mass spectrometry-based proteome analysis implies matching the mass spectra of proteolytic peptides to amino acid sequences predicted from genomic sequences. Reliability of peptide variant identification in proteogenomic studies is often lacking. We propose a way to interpret shotgun proteomics results, specifically in the data-dependent acquisition mode, as protein sequence coverage by multiple reads as it is done in nucleic acid sequencing for calling of single nucleotide variants. Multiple reads for each sequence position could be provided by overlapping distinct peptides, thus confirming the presence of certain amino acid residues in the overlapping stretch with a lower false discovery rate. Overlapping distinct peptides originate from miscleaved tryptic peptides in combination with their properly cleaved counterparts and from peptides generated by multiple proteases after the same specimen is subject to parallel digestion and analyzed separately. We illustrate this approach using publicly available multiprotease data sets and our own data generated for the HEK-293 cell line digests obtained using trypsin, LysC, and GluC proteases. Totally, up to 30% of the whole proteome was covered by tryptic peptides with up to 7% covered twofold and more. The proteogenomic analysis of the HEK-293 cell line revealed 36 single amino acid variants, seven of which were supported by multiple reads.
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Affiliation(s)
- Lev I Levitsky
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 2, Leninsky Prospect, Moscow 119334, Russia
| | - Ksenia G Kuznetsova
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia
| | - Anna A Kliuchnikova
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia.,Pirogov Russian National Research Medical University, 1, Ostrovityanova, Moscow 117997, Russia
| | - Irina Y Ilina
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia
| | - Anton O Goncharov
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia.,Pirogov Russian National Research Medical University, 1, Ostrovityanova, Moscow 117997, Russia
| | - Anna A Lobas
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 2, Leninsky Prospect, Moscow 119334, Russia
| | - Mark V Ivanov
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 2, Leninsky Prospect, Moscow 119334, Russia
| | - Vassili N Lazarev
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia.,Moscow Institute of Physics and Technology (State University), 9, Institutskiy per., Dolgoprudny, Moscow Region 141701, Russia
| | - Rustam H Ziganshin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 16/10, Miklukho-Maklaya, Moscow 117997, Russia
| | - Mikhail V Gorshkov
- V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 38, bld. 2, Leninsky Prospect, Moscow 119334, Russia
| | - Sergei A Moshkovskii
- Federal Research and Clinical Center of Physical-Chemical Medicine, 1a, Malaya Pirogovskaya, Moscow 119435, Russia.,Pirogov Russian National Research Medical University, 1, Ostrovityanova, Moscow 117997, Russia
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5
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Aggarwal S, Raj A, Kumar D, Dash D, Yadav AK. False discovery rate: the Achilles' heel of proteogenomics. Brief Bioinform 2022; 23:6582880. [PMID: 35534181 DOI: 10.1093/bib/bbac163] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 03/14/2022] [Accepted: 04/12/2022] [Indexed: 12/25/2022] Open
Abstract
Proteogenomics refers to the integrated analysis of the genome and proteome that leverages mass-spectrometry (MS)-based proteomics data to improve genome annotations, understand gene expression control through proteoforms and find sequence variants to develop novel insights for disease classification and therapeutic strategies. However, proteogenomic studies often suffer from reduced sensitivity and specificity due to inflated database size. To control the error rates, proteogenomics depends on the target-decoy search strategy, the de-facto method for false discovery rate (FDR) estimation in proteomics. The proteogenomic databases constructed from three- or six-frame nucleotide database translation not only increase the search space and compute-time but also violate the equivalence of target and decoy databases. These searches result in poorer separation between target and decoy scores, leading to stringent FDR thresholds. Understanding these factors and applying modified strategies such as two-pass database search or peptide-class-specific FDR can result in a better interpretation of MS data without introducing additional statistical biases. Based on these considerations, a user can interpret the proteogenomics results appropriately and control false positives and negatives in a more informed manner. In this review, first, we briefly discuss the proteogenomic workflows and limitations in database construction, followed by various considerations that can influence potential novel discoveries in a proteogenomic study. We conclude with suggestions to counter these challenges for better proteogenomic data interpretation.
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Affiliation(s)
- Suruchi Aggarwal
- Translational Health Science and Technology Institute, NCR Biotech Science Cluster, 3rd milestone, PO Box No. 04, Faridabad-Gurgaon Expressway, Faridabad-121001, Haryana, India
| | - Anurag Raj
- GN Ramachandran Knowledge Centre for Genome Informatics, CSIR-Institute of Genomics & Integrative Biology, South Campus, Mathura Road, New Delhi 110025, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad-201002, India
| | - Dhirendra Kumar
- GN Ramachandran Knowledge Centre for Genome Informatics, CSIR-Institute of Genomics & Integrative Biology, South Campus, Mathura Road, New Delhi 110025, India
| | - Debasis Dash
- GN Ramachandran Knowledge Centre for Genome Informatics, CSIR-Institute of Genomics & Integrative Biology, South Campus, Mathura Road, New Delhi 110025, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad-201002, India
| | - Amit Kumar Yadav
- Translational Health Science and Technology Institute, NCR Biotech Science Cluster, 3rd milestone, PO Box No. 04, Faridabad-Gurgaon Expressway, Faridabad-121001, Haryana, India
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6
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Saburina IN, Kosheleva NV, Kopylov AT, Lipina TV, Krasina ME, Zurina IM, Gorkun AA, Girina SS, Pulin AA, Kaysheva AL, Morozov SG. Proteomic and electron microscopy study of myogenic differentiation of alveolar mucosa multipotent mesenchymal stromal cells in three-dimensional culture. Proteomics 2021; 22:e2000304. [PMID: 34674377 DOI: 10.1002/pmic.202000304] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 08/24/2021] [Accepted: 10/08/2021] [Indexed: 12/15/2022]
Abstract
Myocyte differentiation is featured by adaptation processes, including mitochondria repopulation and cytoskeleton re-organization. The difference between monolayer and spheroid cultured cells at the proteomic level is uncertain. We cultivated alveolar mucosa multipotent mesenchymal stromal cells in spheroids in a myogenic way for the proper conditioning of ECM architecture and cell morphology, which induced spontaneous myogenic differentiation of cells within spheroids. Electron microscopy analysis was used for the morphometry of mitochondria biogenesis, and proteomic was used complementary to unveil events underlying differences between two-dimensional/three-dimensional myoblasts differentiation. The prevalence of elongated mitochondria with an average area of 0.097 μm2 was attributed to monolayer cells 7 days after the passage. The population of small mitochondria with a round shape and area of 0.049 μm2 (p < 0.05) was observed in spheroid cells cultured under three-dimensional conditions. Cells in spheroids were quantitatively enriched in proteins of mitochondria biogenesis (DNM1L, IDH2, SSBP1), respiratory chain (ACO2, ATP5I, COX5A), extracellular proteins (COL12A1, COL6A1, COL6A2), and cytoskeleton (MYL6, MYL12B, MYH10). Most of the Rab-related transducers were inhibited in spheroid culture. The proteomic assay demonstrated delicate mechanisms of mitochondria autophagy and repopulation, cytoskeleton assembling, and biogenesis. Differences in the ultrastructure of mitochondria indicate active biogenesis under three-dimensional conditions.
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Affiliation(s)
- Irina N Saburina
- FSBSI Institute of General Pathology and Pathophysiology, Moscow, Russian Federation
| | - Nastasia V Kosheleva
- FSBSI Institute of General Pathology and Pathophysiology, Moscow, Russian Federation.,Institute for Regenerative Medicine, Sechenov First Moscow State Medical University, Moscow, Russian Federation.,World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov University, Moscow, Russia
| | - Arthur T Kopylov
- FSBSI Institute of General Pathology and Pathophysiology, Moscow, Russian Federation.,World-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov University, Moscow, Russia.,Department of Proteomic Research, Institute of Biomedical Chemistry, Moscow, Russian Federation
| | - Tatiana V Lipina
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russian Federation
| | - Marina E Krasina
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russian Federation
| | - Irina M Zurina
- FSBSI Institute of General Pathology and Pathophysiology, Moscow, Russian Federation.,Institute for Regenerative Medicine, Sechenov First Moscow State Medical University, Moscow, Russian Federation
| | - Anastasiya A Gorkun
- FSBSI Institute of General Pathology and Pathophysiology, Moscow, Russian Federation.,Institute for Regenerative Medicine, Sechenov First Moscow State Medical University, Moscow, Russian Federation
| | - Svetlana S Girina
- FSBSI Institute of General Pathology and Pathophysiology, Moscow, Russian Federation
| | - Andrey A Pulin
- Pirogov National Medical Surgical Center, Moscow, Russian Federation
| | - Anna L Kaysheva
- Department of Proteomic Research, Institute of Biomedical Chemistry, Moscow, Russian Federation
| | - Sergey G Morozov
- FSBSI Institute of General Pathology and Pathophysiology, Moscow, Russian Federation
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7
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Carbonara K, Andonovski M, Coorssen JR. Proteomes Are of Proteoforms: Embracing the Complexity. Proteomes 2021; 9:38. [PMID: 34564541 PMCID: PMC8482110 DOI: 10.3390/proteomes9030038] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 08/24/2021] [Accepted: 08/29/2021] [Indexed: 12/17/2022] Open
Abstract
Proteomes are complex-much more so than genomes or transcriptomes. Thus, simplifying their analysis does not simplify the issue. Proteomes are of proteoforms, not canonical proteins. While having a catalogue of amino acid sequences provides invaluable information, this is the Proteome-lite. To dissect biological mechanisms and identify critical biomarkers/drug targets, we must assess the myriad of proteoforms that arise at any point before, after, and between translation and transcription (e.g., isoforms, splice variants, and post-translational modifications [PTM]), as well as newly defined species. There are numerous analytical methods currently used to address proteome depth and here we critically evaluate these in terms of the current 'state-of-the-field'. We thus discuss both pros and cons of available approaches and where improvements or refinements are needed to quantitatively characterize proteomes. To enable a next-generation approach, we suggest that advances lie in transdisciplinarity via integration of current proteomic methods to yield a unified discipline that capitalizes on the strongest qualities of each. Such a necessary (if not revolutionary) shift cannot be accomplished by a continued primary focus on proteo-genomics/-transcriptomics. We must embrace the complexity. Yes, these are the hard questions, and this will not be easy…but where is the fun in easy?
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Affiliation(s)
| | | | - Jens R. Coorssen
- Faculties of Applied Health Sciences and Mathematics & Science, Departments of Health Sciences and Biological Sciences, Brock University, 1812 Sir Isaac Brock Way, St. Catharines, ON L2S 3A1, Canada; (K.C.); (M.A.)
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8
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Badalanloo K, Naji T, Ahmadi R. Cytotoxic and Apoptotic Effects of Celecoxib and Topotecan on AGS and HEK 293 Cell Lines. J Gastrointest Cancer 2020; 53:99-104. [PMID: 33200341 DOI: 10.1007/s12029-020-00434-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
PURPOSE This study is aimed to assess the anti-cancer effects of Celecoxib and topotecan against Human Gastric cancer cell line (AGS) in comparison to the control in an in-vitro study. METHODS In this experimental study, Celecoxib and topotecan was prepared at concentrations of 500, 250, 125, 62.5, 31.2, 15.6 and 7.8 mg/ml. The effect of celecoxib and topotecan separately and in mixed form were investigated on AGS and normal HEK cells. To investigate the cell survival, MTT method was used to study the pathway of apoptosis using flowcytometry and Caspase kits based on colorimetric. Finally, one-way ANOVA and t-test were used to analyze the data. RESULTS The results of this study indicated that Celecoxib was cytotoxic against AGS and HEK cell lines. The topotecan indicated a significant cytotoxicity against AGS cells and was not toxic against HEK cell line. Our results indicated that Celecoxib and topotecan have synergist effects against AGS and HEK cell lines and were more effective than separate celecoxib or topotecan. CONCLUSION The mixture of clecoxib and topotecan was more effective than celecoxib and topotecan in separate form. Our results indicated that use mixed forms of treatments can cause excellent therapeutic effects and can cause less side effects.
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Affiliation(s)
- Kimia Badalanloo
- Department of Basic Sciences, Faculty of Pharmacy and Pharmaceutical Sciences, Islamic Azad University, Tehran, Iran
| | - Tahereh Naji
- Department of Basic Sciences, Faculty of Pharmacy and Pharmaceutical Sciences, Islamic Azad University, Tehran, Iran.
| | - Rahim Ahmadi
- Department of Physiology, Faculty of Basic Sciences, Hamadan Branch, Islamic Azad University, Hamadan, Iran
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9
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Choong WK, Wang JH, Sung TY. MinProtMaxVP: Generating a minimized number of protein variant sequences containing all possible variant peptides for proteogenomic analysis. J Proteomics 2020; 223:103819. [PMID: 32407886 DOI: 10.1016/j.jprot.2020.103819] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Revised: 05/04/2020] [Accepted: 05/09/2020] [Indexed: 12/12/2022]
Abstract
Identifying single-amino-acid variants (SAVs) from mass spectrometry-based experiments is critical for validating single-nucleotide variants (SNVs) at the protein level to facilitate biomedical research. Currently, two approaches are usually applied to convert SNV annotations into SAV-harboring protein sequences. One approach generates one sequence containing exactly one SAV, and the other all SAVs. However, they may neglect the possibility of SAV combinations, e.g., haplotypes, existing in bio-samples. Therefore, it is necessary to consider all SAV combinations of a protein when generating SAV-harboring protein sequences. In this paper, we propose MinProtMaxVP, a novel approach which selects a minimized number of SAV-harboring protein sequences generated from the exhaustive approach, while still accommodating all possible variant peptides, by solving a classic set covering problem. Our study on known haplotype variations of TAS2R38 justifies the necessity for MinProtMaxVP to consider all combinations of SAVs. The performance of MinProtMaxVP is demonstrated by an in silico study on OR2T27 with five SAVs and real experimental data of the HEK293 cell line. Furthermore, assuming simulated somatic and germline variants of OR2T27 in tumor and normal tissues demonstrates that when adopting the appropriate somatic and germline SAV integration strategy, MinProtMaxVP is adaptable to labeling and label-free mass spectrometry-based experiments. SIGNIFICANCE: We present MinProtMaxVP, a novel approach to generate SAV-harboring protein sequences for constructing a customized protein sequence database, which is used in database searching for variant peptide identification. This approach outperforms the existing approaches in generating all possible variant peptides to be included in protein sequences and possibly leading to identification of more variant peptides in proteogenomic analysis.
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Affiliation(s)
- Wai-Kok Choong
- Institute of Information Science, Academia Sinica, Nankang, Taipei 11529, Taiwan
| | - Jen-Hung Wang
- Institute of Information Science, Academia Sinica, Nankang, Taipei 11529, Taiwan
| | - Ting-Yi Sung
- Institute of Information Science, Academia Sinica, Nankang, Taipei 11529, Taiwan.
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10
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Gonzales Hurtado PA, Morrison R, Ribeiro JMC, Magale H, Attaher O, Diarra BS, Mahamar A, Barry A, Dicko A, Duffy PE, Fried M. Proteomics Pipeline for Identifying Variant Proteins in Plasmodium falciparum Parasites Isolated from Children Presenting with Malaria. J Proteome Res 2019; 18:3831-3839. [PMID: 31549843 PMCID: PMC11097108 DOI: 10.1021/acs.jproteome.9b00169] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Plasmodium falciparum variant antigens named erythrocyte membrane protein 1 (PfEMP1) are important targets for developing a protective immunity to malaria caused by P. falciparum. One of the major challenges in P. falciparum proteomics studies is identifying PfEMP1s at the protein level due to antigenic variation. To identify these PfEMP1s using shotgun proteomics, we developed a pipeline that searches high-resolution mass spectrometry spectra against a custom protein sequence database. A local alignment algorithm, LAX, was developed as a part of the pipeline that matches peptide sequences to the most similar PfEMP1 and calculates a weight value based on peptide's uniqueness used for PfEMP1 protein inference. The pipeline was first validated in the analysis of a laboratory strain with a known PfEMP1, then it was implemented on the analysis of parasite isolates from malaria-infected pregnant women and finally on the analysis of parasite isolates from malaria-infected children where there was an increase of PfEMP1s identified in 27 out of 31 isolates using the expanded database.
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Affiliation(s)
- Patricia A. Gonzales Hurtado
- Laboratory of Malaria Immunology and Vaccinology, National Institute of Allergy and Infectious Disease, NIH, Bethesda, Maryland 20852, United States
| | - Robert Morrison
- Laboratory of Malaria Immunology and Vaccinology, National Institute of Allergy and Infectious Disease, NIH, Bethesda, Maryland 20852, United States
| | - Jose M. C. Ribeiro
- Laboratory of Malaria Vector Research, National Institute of Allergy and Infectious Disease, NIH, Bethesda, Maryland 20852, United States
| | - Hussein Magale
- Laboratory of Malaria Immunology and Vaccinology, National Institute of Allergy and Infectious Disease, NIH, Bethesda, Maryland 20852, United States
| | - Oumar Attaher
- Malaria Research & Training Center, Faculty of Medicine, Pharmacy and Dentistry, University of Sciences Techniques and Technologies of Bamako, P.O. Box 1805, Bamako, 1. 20892, Mali
| | - Bacary S. Diarra
- Malaria Research & Training Center, Faculty of Medicine, Pharmacy and Dentistry, University of Sciences Techniques and Technologies of Bamako, P.O. Box 1805, Bamako, 1. 20892, Mali
| | - Almahamoudou Mahamar
- Malaria Research & Training Center, Faculty of Medicine, Pharmacy and Dentistry, University of Sciences Techniques and Technologies of Bamako, P.O. Box 1805, Bamako, 1. 20892, Mali
| | - Amadou Barry
- Malaria Research & Training Center, Faculty of Medicine, Pharmacy and Dentistry, University of Sciences Techniques and Technologies of Bamako, P.O. Box 1805, Bamako, 1. 20892, Mali
| | - Alassane Dicko
- Malaria Research & Training Center, Faculty of Medicine, Pharmacy and Dentistry, University of Sciences Techniques and Technologies of Bamako, P.O. Box 1805, Bamako, 1. 20892, Mali
| | - Patrick E. Duffy
- Laboratory of Malaria Immunology and Vaccinology, National Institute of Allergy and Infectious Disease, NIH, Bethesda, Maryland 20852, United States
| | - Michal Fried
- Laboratory of Malaria Immunology and Vaccinology, National Institute of Allergy and Infectious Disease, NIH, Bethesda, Maryland 20852, United States
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11
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Abuei H, Behzad-Behbahani A, Faghihi F, Farhadi A, Rafiei Dehbidi GR, Pirouzfar M, Zare F. The Effect of Bacterial Peptide p28 on Viability and Apoptosis Status of P53-null HeLa Cells. Adv Pharm Bull 2019; 9:668-673. [PMID: 31857973 PMCID: PMC6912191 DOI: 10.15171/apb.2019.078] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Revised: 06/09/2019] [Accepted: 06/18/2019] [Indexed: 01/26/2023] Open
Abstract
Purpose: Despite all the efforts for discovery of efficient anti-cancer therapeutics, cancer is still a major health concern worldwide. p28 is a bacterial small peptide which has been widely investigated due to its preferential cell internalization and anti-cancer activities. Intracellularly, p28 offers its anti-cancer traits by impeding the degradation of tumor-suppressor protein "p53". In this study, we investigated the potency of p28 in inducing apoptosis or decreasing cell viability in p53-null "HeLa" cell line. Methods: The coding sequence for p28 peptide was obtained from Pseudomonas aeruginosa by PCR amplification of the p28 gene. The coding gene was cloned in pET-28a vector and transformed into E. coli bacterial host. Subsequently, the expressed peptide was purified using Ni-NTA chromatography system and introduced into the target cells. The anti-proliferative and apoptotic activity of p28 on HeLa and HEK-293 cells were investigated using MTT and PEAnnexin V Flowcytometry assays. Results: Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and Western blotting confirmed the expression of p28 peptide in the bacterial host. Bradford assay revealed a concentration of 0.05 mg/mL for the purified p28. MTT assay of cells treated with p28 at concentrations of 0, 0.5, 1, 2 and 2.5 µM indicated 24h viability values of 97%, 89%, 88%, 87% and 84% for HeLa cells, respectively. Data obtained from flowcytometry analyses revealed 24h apoptosis rate of 7.17%, 8.05%, 8.63% and 8.84% for HeLa cells treated with 0, 0.5, 1, and 2 µM p28, respectively. Conclusion: MTT and flowcytometry apoptosis assays suggest no statistically significant effect of p28 on the viability and apoptosis status of p53-null HeLa cells when results compared to data obtained from HEK-293 cells (P>0.05). These results imply that anti-cancer efficacy of p28 is directly dependent on the presence of p53, suggesting p28 as an inappropriate therapeutic agent for treatment of cancers with negative p53 status.
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Affiliation(s)
- Haniyeh Abuei
- Department of Medical Laboratory Sciences, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Abbas Behzad-Behbahani
- Diagnostic Laboratory Sciences and Technology Research Center, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Fatemeh Faghihi
- Department of Oral and Maxillofacial Pathology, School of Dentistry, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Ali Farhadi
- Diagnostic Laboratory Sciences and Technology Research Center, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Gholam Reza Rafiei Dehbidi
- Diagnostic Laboratory Sciences and Technology Research Center, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mohammad Pirouzfar
- Department of Medical Laboratory Sciences, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Farahnaz Zare
- Diagnostic Laboratory Sciences and Technology Research Center, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran
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12
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Levitsky LI, Kliuchnikova AA, Kuznetsova KG, Karpov DS, Ivanov MV, Pyatnitskiy MA, Kalinina OV, Gorshkov MV, Moshkovskii SA. Adenosine-to-Inosine RNA Editing in Mouse and Human Brain Proteomes. Proteomics 2019; 19:e1900195. [PMID: 31576663 DOI: 10.1002/pmic.201900195] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2019] [Revised: 09/25/2019] [Indexed: 12/30/2022]
Abstract
Proteogenomics is based on the use of customized genome or RNA sequencing databases for interrogation of shotgun proteomics data in search for proteome-level evidence of genome variations or RNA editing. In this work, the products of adenosine-to-inosine RNA editing in human and murine brain proteomes are identified using publicly available brain proteome LC-MS/MS datasets and an RNA editome database compiled from several sources. After filtering of false-positive results, 20 and 37 sites of editing in proteins belonging to 14 and 32 genes are identified for murine and human brain proteomes, respectively. Eight sites of editing identified with high spectral counts overlapped between human and mouse brain samples. Some of these sites have been previously reported using orthogonal methods, such as α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) glutamate receptors, CYFIP2, coatomer alpha. Also, differential editing between neurons and microglia is demonstrated in this work for some of the proteins from primary murine brain cell cultures. Because many edited sites are still not characterized functionally at the protein level, the results provide a necessary background for their further analysis in normal and diseased cells and tissues using targeted proteomic approaches.
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Affiliation(s)
- Lev I Levitsky
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, 119991, Russia
| | - Anna A Kliuchnikova
- Institute of Biomedical Chemistry, 10 Pogodinskaya st., Moscow, 119121, Russia.,Department of Biochemistry, Pirogov Russian National Research Medical University, 1 Ostrovityanova st., Moscow, 117997, Russia
| | - Ksenia G Kuznetsova
- Institute of Biomedical Chemistry, 10 Pogodinskaya st., Moscow, 119121, Russia
| | - Dmitry S Karpov
- Institute of Biomedical Chemistry, 10 Pogodinskaya st., Moscow, 119121, Russia.,Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 119991, Russia
| | - Mark V Ivanov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, 119991, Russia
| | - Mikhail A Pyatnitskiy
- Institute of Biomedical Chemistry, 10 Pogodinskaya st., Moscow, 119121, Russia.,Onco Genotest LLC, Moscow, 125047, Russia.,Department of Technologies for Complex System Modelling, National Research University Higher School of Economics, Moscow, 101000, Russia
| | - Olga V Kalinina
- Helmholtz Institute for Pharmaceutical Research Saarland, Helmholtz Centre for Infection Research, Saarbrücken, 66123, Germany.,Medical Faculty, Saarland University, Kirrberger Straße, Homburg, 66421, Germany
| | - Mikhail V Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, 119991, Russia.,Moscow Institute of Physics and Technology (State University), Dolgoprudny, 141700, Moscow Region, Russia
| | - Sergei A Moshkovskii
- Institute of Biomedical Chemistry, 10 Pogodinskaya st., Moscow, 119121, Russia.,Department of Biochemistry, Pirogov Russian National Research Medical University, 1 Ostrovityanova st., Moscow, 117997, Russia
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13
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Low TY, Mohtar MA, Ang MY, Jamal R. Connecting Proteomics to Next‐Generation Sequencing: Proteogenomics and Its Current Applications in Biology. Proteomics 2018; 19:e1800235. [DOI: 10.1002/pmic.201800235] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Revised: 10/09/2018] [Indexed: 12/17/2022]
Affiliation(s)
- Teck Yew Low
- UKM Medical Molecular Biology Institute (UMBI)Universiti Kebangsaan Malaysia 56000 Kuala Lumpur Malaysia
| | - M. Aiman Mohtar
- UKM Medical Molecular Biology Institute (UMBI)Universiti Kebangsaan Malaysia 56000 Kuala Lumpur Malaysia
| | - Mia Yang Ang
- UKM Medical Molecular Biology Institute (UMBI)Universiti Kebangsaan Malaysia 56000 Kuala Lumpur Malaysia
| | - Rahman Jamal
- UKM Medical Molecular Biology Institute (UMBI)Universiti Kebangsaan Malaysia 56000 Kuala Lumpur Malaysia
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14
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Kuznetsova KG, Kliuchnikova AA, Ilina IU, Chernobrovkin AL, Novikova SE, Farafonova TE, Karpov DS, Ivanov MV, Goncharov AO, Ilgisonis EV, Voronko OE, Nasaev SS, Zgoda VG, Zubarev RA, Gorshkov MV, Moshkovskii SA. Proteogenomics of Adenosine-to-Inosine RNA Editing in the Fruit Fly. J Proteome Res 2018; 17:3889-3903. [DOI: 10.1021/acs.jproteome.8b00553] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
| | - Anna A. Kliuchnikova
- Institute of Biomedical Chemistry, Moscow, Russia
- Pirogov Russian National Research Medical University (RNRMU), Moscow, Russia
| | | | | | | | | | - Dmitry S. Karpov
- Institute of Biomedical Chemistry, Moscow, Russia
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - Mark V. Ivanov
- Institute of Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
- Moscow Institute of Physics and Technology (State University), Dolgoprudny, Moscow Region, Russia
| | - Anton O. Goncharov
- Institute of Biomedical Chemistry, Moscow, Russia
- Pirogov Russian National Research Medical University (RNRMU), Moscow, Russia
| | | | | | - Shamsudin S. Nasaev
- Pirogov Russian National Research Medical University (RNRMU), Moscow, Russia
| | | | - Roman A. Zubarev
- Karolinska Institutet, Stockholm, Sweden
- I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Mikhail V. Gorshkov
- Institute of Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
- Moscow Institute of Physics and Technology (State University), Dolgoprudny, Moscow Region, Russia
| | - Sergei A. Moshkovskii
- Institute of Biomedical Chemistry, Moscow, Russia
- Pirogov Russian National Research Medical University (RNRMU), Moscow, Russia
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15
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Rendleman J, Choi H, Vogel C. Integration of large-scale multi-omic datasets: a protein-centric view. ACTA ACUST UNITED AC 2018; 11:74-81. [PMID: 30906903 DOI: 10.1016/j.coisb.2018.09.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Innovative mass spectrometry-based proteomics has enabled routine measurements of protein abundance, localization, interactions, and modifications, covering unique aspects of gene expression regulation and function. It is now time to move from isolated analyses of these datasets toward true integration of proteomics with other data types to gain insights from the interactions and interdependencies of biomolecules. When combined with genomic or transcriptomic data, proteomics expands genome annotation to identify variant or missing genes. Dynamic proteomic measurements can move analysis from predominantly concentration-based framework to that of synthesis and degradation of proteins. Proteomic data from thousands of cancer patients can foster identification of novel pathogenic mutations via detection of protein sequence changes that lead to dysregulated pathways in various tumors. Such comprehensive efforts can exploit the synergy arising from large and complex datasets to advance virtually every field of biology.
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Affiliation(s)
- Justin Rendleman
- Center for Genomics and Systems Biology, New York University, Department of Biology, New York, USA
| | - Hyungwon Choi
- Department of Medicine, Yong Loo Lin School of Medicine, National University Singapore, Singapore.,Institute of Molecular and Cell Biology, Agency for Science, Technology, and Research, Singapore
| | - Christine Vogel
- Center for Genomics and Systems Biology, New York University, Department of Biology, New York, USA
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16
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Robin T, Bairoch A, Müller M, Lisacek F, Lane L. Large-Scale Reanalysis of Publicly Available HeLa Cell Proteomics Data in the Context of the Human Proteome Project. J Proteome Res 2018; 17:4160-4170. [DOI: 10.1021/acs.jproteome.8b00392] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Thibault Robin
- CALIPHO Group, SIB Swiss Institute of Bioinformatics, CMU, Rue Michel-Servet 1, CH-1211 Geneva, Switzerland
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CMU, Rue Michel-Servet 1, CH-1211 Geneva, Switzerland
- Computer Science Department, University of Geneva, CH-1211 Geneva, Switzerland
- Department of Microbiology and Molecular Medicine, Faculty of Medicine, University of Geneva, CH-1211 Geneva, Switzerland
| | - Amos Bairoch
- CALIPHO Group, SIB Swiss Institute of Bioinformatics, CMU, Rue Michel-Servet 1, CH-1211 Geneva, Switzerland
- Department of Microbiology and Molecular Medicine, Faculty of Medicine, University of Geneva, CH-1211 Geneva, Switzerland
| | - Markus Müller
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, Genopode Building, Quartier Sorge, CH-1015 Lausanne, Switzerland
| | - Frédérique Lisacek
- Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, CMU, Rue Michel-Servet 1, CH-1211 Geneva, Switzerland
- Computer Science Department, University of Geneva, CH-1211 Geneva, Switzerland
- Section of Biology, University of Geneva, CH-1211 Geneva, Switzerland
| | - Lydie Lane
- CALIPHO Group, SIB Swiss Institute of Bioinformatics, CMU, Rue Michel-Servet 1, CH-1211 Geneva, Switzerland
- Department of Microbiology and Molecular Medicine, Faculty of Medicine, University of Geneva, CH-1211 Geneva, Switzerland
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17
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Mamie Lih TS, Choong WK, Chen YJ, Sung TY. Evaluating the Possibility of Detecting Variants in Shotgun Proteomics via LeTE-Fusion Analysis Pipeline. J Proteome Res 2018; 17:2937-2952. [PMID: 30088773 DOI: 10.1021/acs.jproteome.8b00052] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
In proteogenomic studies, many genome-annotated events, for example, single amino acid variation (SAAV) and short INDEL, are often unobserved in shotgun proteomics. Therefore, we propose an analysis pipeline called LeTE-fusion (Le, peptide length; T, theoretical values; E, experimental data) to first investigate whether peptides with certain lengths are observed more often in mass spectrometry (MS)-based proteomics, which may hinder peptide identification causing difficulty in detecting genome-annotated events. By applying LeTE-fusion on different MS-based proteome data sets, we found peptides within 7-20 amino acids are more frequently identified, possibly attributed to MS-related factors instead of proteases. We then further extended the usage of LeTE-fusion on four variant-containing-sequence data sets (SAAV-only) with various sample complexity up to the whole human proteome scale, which yields theoretically ∼70% variants observable in an ideal shotgun proteomics. However, only ∼40% of variants might be detectable in real shotgun proteomic experiments when LeTE-fusion utilizes the experimentally observed variant-site-containing wild-type peptides in PeptideAtlas to estimate the expected observable coverage of variants. Finally, we conducted a case study on HEK293 cell line with variants reported at genomic level that were also identified in shotgun proteomics to demonstrate the efficacy of LeTE-fusion on estimating expected observable coverage of variants. To the best of our knowledge, this is the first study to systematically investigate the detection limits of genome-annotated events via shotgun proteomics using such analysis pipeline.
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18
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Solovyeva EM, Lobas AA, Kopylov AT, Ilina IY, Levitsky LI, Moshkovskii SA, Gorshkov MV. FractionOptimizer: a method for optimal peptide fractionation in bottom-up proteomics. Anal Bioanal Chem 2018; 410:3827-3833. [PMID: 29663059 DOI: 10.1007/s00216-018-1054-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 03/21/2018] [Accepted: 03/29/2018] [Indexed: 12/15/2022]
Abstract
Recent advances in mass spectrometry and separation technologies created the opportunities for deep proteome characterization using shotgun proteomics approaches. The "real world" sample complexity and high concentration range limit the sensitivity of this characterization. The common strategy for increasing the sensitivity is sample fractionation prior to analysis either at the protein or the peptide level. Typically, fractionation at the peptide level is performed using linear gradient high-performance liquid chromatography followed by uniform fraction collection. However, this way of peptide fractionation results in significantly suboptimal operation of the mass spectrometer due to the non-uniform distribution of peptides between the fractions. In this work, we propose an approach based on peptide retention time prediction allowing optimization of chromatographic conditions and fraction collection procedures. An open-source software implementing the approach called FractionOptimizer was developed and is available at http://hg.theorchromo.ru/FractionOptimizer . The performance of the developed tool was demonstrated for human embryonic kidney (HEK293) cell line lysate. In these experiments, we improved the uniformity of the peptides distribution between fractions. Moreover, in addition to 13,492 peptides, we found 6787 new peptides not identified in the experiments without fractionation and up to 800 new proteins (or 25%). Graphical abstract The analysis workflow employing FractionOptimizer software.
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Affiliation(s)
- Elizaveta M Solovyeva
- Moscow Institute of Physics and Technology (State University), Dolgoprudny, Moscow Region, 141701, Russia.,V.L. Talrose Institute for Energy Problems of Chemical Physics, RAS, Moscow, 119334, Russia
| | - Anna A Lobas
- V.L. Talrose Institute for Energy Problems of Chemical Physics, RAS, Moscow, 119334, Russia
| | | | - Irina Y Ilina
- Institute of Biomedical Chemistry, Moscow, 119121, Russia
| | - Lev I Levitsky
- V.L. Talrose Institute for Energy Problems of Chemical Physics, RAS, Moscow, 119334, Russia
| | - Sergei A Moshkovskii
- Institute of Biomedical Chemistry, Moscow, 119121, Russia.,Pirogov Russian National Research Medical University, Moscow, 117997, Russia
| | - Mikhail V Gorshkov
- V.L. Talrose Institute for Energy Problems of Chemical Physics, RAS, Moscow, 119334, Russia.
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19
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Lobas AA, Pyatnitskiy MA, Chernobrovkin AL, Ilina IY, Karpov DS, Solovyeva EM, Kuznetsova KG, Ivanov MV, Lyssuk EY, Kliuchnikova AA, Voronko OE, Larin SS, Zubarev RA, Gorshkov MV, Moshkovskii SA. Proteogenomics of Malignant Melanoma Cell Lines: The Effect of Stringency of Exome Data Filtering on Variant Peptide Identification in Shotgun Proteomics. J Proteome Res 2018; 17:1801-1811. [PMID: 29619825 DOI: 10.1021/acs.jproteome.7b00841] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
The identification of genetically encoded variants at the proteome level is an important problem in cancer proteogenomics. The generation of customized protein databases from DNA or RNA sequencing data is a crucial stage of the identification workflow. Genomic data filtering applied at this stage may significantly modify variant search results, yet its effect is generally left out of the scope of proteogenomic studies. In this work, we focused on this impact using data of exome sequencing and LC-MS/MS analyses of six replicates for eight melanoma cell lines processed by a proteogenomics workflow. The main objectives were identifying variant peptides and revealing the role of the genomic data filtering in the variant identification. A series of six confidence thresholds for single nucleotide polymorphisms and indels from the exome data were applied to generate customized sequence databases of different stringency. In the searches against unfiltered databases, between 100 and 160 variant peptides were identified for each of the cell lines using X!Tandem and MS-GF+ search engines. The recovery rate for variant peptides was ∼1%, which is approximately three times lower than that of the wild-type peptides. Using unfiltered genomic databases for variant searches resulted in higher sensitivity and selectivity of the proteogenomic workflow and positively affected the ability to distinguish the cell lines based on variant peptide signatures.
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Affiliation(s)
- Anna A Lobas
- Moscow Institute of Physics and Technology (State University) , Dolgoprudny 141700 , Moscow Region , Russia.,V.L. Talrose Institute for Energy Problems of Chemical Physics , Russian Academy of Sciences , Moscow 119334 , Russia
| | - Mikhail A Pyatnitskiy
- Institute of Biomedical Chemistry , Moscow 119121 , Russia.,Higher School of Economics , Moscow 101000 , Russia
| | | | - Irina Y Ilina
- Institute of Biomedical Chemistry , Moscow 119121 , Russia
| | - Dmitry S Karpov
- Institute of Biomedical Chemistry , Moscow 119121 , Russia.,Engelhardt Institute of Molecular Biology , Russian Academy of Sciences , Moscow 119991 , Russia
| | - Elizaveta M Solovyeva
- V.L. Talrose Institute for Energy Problems of Chemical Physics , Russian Academy of Sciences , Moscow 119334 , Russia
| | | | - Mark V Ivanov
- V.L. Talrose Institute for Energy Problems of Chemical Physics , Russian Academy of Sciences , Moscow 119334 , Russia
| | - Elena Y Lyssuk
- Institute of Gene Biology , Russian Academy of Sciences , Moscow 119334 , Russia
| | - Anna A Kliuchnikova
- Institute of Biomedical Chemistry , Moscow 119121 , Russia.,Pirogov Russian National Research Medical University , Moscow 117997 , Russia
| | - Olga E Voronko
- Institute of Biomedical Chemistry , Moscow 119121 , Russia
| | - Sergey S Larin
- Institute of Gene Biology , Russian Academy of Sciences , Moscow 119334 , Russia
| | | | - Mikhail V Gorshkov
- V.L. Talrose Institute for Energy Problems of Chemical Physics , Russian Academy of Sciences , Moscow 119334 , Russia
| | - Sergei A Moshkovskii
- Institute of Biomedical Chemistry , Moscow 119121 , Russia.,Pirogov Russian National Research Medical University , Moscow 117997 , Russia
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20
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Moshkovskii SA, Ivanov MV, Kuznetsova KG, Gorshkov MV. Identification of Single Amino Acid Substitutions in Proteogenomics. BIOCHEMISTRY (MOSCOW) 2018; 83:250-258. [DOI: 10.1134/s0006297918030057] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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21
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Heunis T, Dippenaar A, Warren RM, van Helden PD, van der Merwe RG, Gey van Pittius NC, Pain A, Sampson SL, Tabb DL. Proteogenomic Investigation of Strain Variation in Clinical Mycobacterium tuberculosis Isolates. J Proteome Res 2017; 16:3841-3851. [PMID: 28820946 DOI: 10.1021/acs.jproteome.7b00483] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Mycobacterium tuberculosis consists of a large number of different strains that display unique virulence characteristics. Whole-genome sequencing has revealed substantial genetic diversity among clinical M. tuberculosis isolates, and elucidating the phenotypic variation encoded by this genetic diversity will be of the utmost importance to fully understand M. tuberculosis biology and pathogenicity. In this study, we integrated whole-genome sequencing and mass spectrometry (GeLC-MS/MS) to reveal strain-specific characteristics in the proteomes of two clinical M. tuberculosis Latin American-Mediterranean isolates. Using this approach, we identified 59 peptides containing single amino acid variants, which covered ∼9% of all coding nonsynonymous single nucleotide variants detected by whole-genome sequencing. Furthermore, we identified 29 distinct peptides that mapped to a hypothetical protein not present in the M. tuberculosis H37Rv reference proteome. Here, we provide evidence for the expression of this protein in the clinical M. tuberculosis SAWC3651 isolate. The strain-specific databases enabled confirmation of genomic differences (i.e., large genomic regions of difference and nonsynonymous single nucleotide variants) in these two clinical M. tuberculosis isolates and allowed strain differentiation at the proteome level. Our results contribute to the growing field of clinical microbial proteogenomics and can improve our understanding of phenotypic variation in clinical M. tuberculosis isolates.
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Affiliation(s)
- Tiaan Heunis
- DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University , Cape Town 7505, South Africa
| | - Anzaan Dippenaar
- DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University , Cape Town 7505, South Africa
| | - Robin M Warren
- DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University , Cape Town 7505, South Africa
| | - Paul D van Helden
- DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University , Cape Town 7505, South Africa
| | - Ruben G van der Merwe
- DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University , Cape Town 7505, South Africa
| | - Nicolaas C Gey van Pittius
- DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University , Cape Town 7505, South Africa
| | - Arnab Pain
- Pathogen Genomics Laboratory, BESE Division, King Abdullah University of Science and Technology , Thuwal 23955, Saudi Arabia
| | - Samantha L Sampson
- DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University , Cape Town 7505, South Africa
| | - David L Tabb
- DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University , Cape Town 7505, South Africa
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22
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Ivanov MV, Lobas AA, Karpov DS, Moshkovskii SA, Gorshkov MV. Comparison of False Discovery Rate Control Strategies for Variant Peptide Identifications in Shotgun Proteogenomics. J Proteome Res 2017; 16:1936-1943. [DOI: 10.1021/acs.jproteome.6b01014] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Mark V. Ivanov
- Institute
for Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia
- Moscow Institute of Physics and Technology (State University), Moscow Region, Dolgoprudny 141700, Russia
| | - Anna A. Lobas
- Institute
for Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia
- Moscow Institute of Physics and Technology (State University), Moscow Region, Dolgoprudny 141700, Russia
| | - Dmitry S. Karpov
- Institute of Biomedical Chemistry, Moscow 119121, Russia
- Engelhardt
Institute of Molecular Biology, Russian Academy of Sciences, Moscow 119991, Russia
| | - Sergei A. Moshkovskii
- Institute of Biomedical Chemistry, Moscow 119121, Russia
- Pirogov Russian National Research Medical University, Moscow 117997, Russia
| | - Mikhail V. Gorshkov
- Institute
for Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia
- Moscow Institute of Physics and Technology (State University), Moscow Region, Dolgoprudny 141700, Russia
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23
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Kliuchnikova A, Kuznetsova K, Moshkovskii S. ADAR-mediated messenger RNA editing: analysis at the proteome level. ACTA ACUST UNITED AC 2016; 62:510-519. [DOI: 10.18097/pbmc20166205510] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Post-transcriptional RNA editing by RNA specific adenosine deaminases (ADAR) was discovered more than two decades ago. It provides additional regulation of animal and human transcriptome. In most cases, it occurs in nervous tissue, where, as a result of the reaction, adenosine is converted to inosine in particular sites of RNA. In case of messenger RNA, during translation, inosine is recognized as guanine leading to amino acid substitutions. Those substitutions are shown to affect substantially the function of proteins, e.g. subunits of the glutamate receptor. Nevertheless, most of the works on RNA editing use analysis of nucleic acids, even those which deal with a coding RNA. In this review, we propose the use of shotgun proteomics based on high resolution liquid chromatography and mass spectrometry for investigation of the effects of RNA editing at the protein level. Recently developed methods of big data processing allow combining the results of various omics techniques, being referred to as proteogenomics. The proposed proteogenomic approach for the analysis of RNA editing at the protein level will directly conduct a qualitative and quantitative analysis of protein edited sequences in the scale of whole proteome.
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Affiliation(s)
| | | | - S.A. Moshkovskii
- Institute of Biomedical Chemistry, Moscow, Russia; Pirogov Russian National Research Medical University, Moscow, Russia
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