1
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Lai X, Qi G. Using long columns to quantify over 9200 unique protein groups from brain tissue in a single injection on an Orbitrap Exploris 480 mass spectrometer. J Proteomics 2024; 308:105285. [PMID: 39159862 DOI: 10.1016/j.jprot.2024.105285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2024] [Revised: 08/14/2024] [Accepted: 08/16/2024] [Indexed: 08/21/2024]
Abstract
The most exciting advancement in LC-MS/MS-based bottom-up proteomics has centered around enhancing mass spectrometers. Among these, the latest and most advanced mass spectrometer for bottom-up proteomics is the Orbitrap Astral that has the highest scan rate to accelerate throughput and the highest sensitivity to handle a very small amount of peptide samples and to achieve deeper proteomics. However, its affordability remains a challenge for most laboratories. While significant strides have been made in improving mass spectrometry, advancing liquid chromatography (LC) to achieve deeper proteomics has not achieved significant successes since the innovation of Multidimensional Protein Identification Technology (MudPIT) in 2001. To achieve deeper proteomics in a less labor-intensive and more reproducible approach while using a more cost-effective mass spectrometer, such as the Orbitrap Exploris 480, we evaluated trap columns as long as 40 cm and analytical column as long as 600 cm besides sample loading amount, gradient time, and analytical column particle size to enable a fractionation-free method for a single injection to obtain deeper proteomics. The length of trap and analytic columns is the key factor. Using a 30 cm trap column and 250 cm analytical column with other optimized LC conditions, we quantified over 9200 unique protein groups from brain tissue in a single injection using a 24-h gradient on an Orbitrap Exploris 480 mass spectrometer.
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Affiliation(s)
- Xianyin Lai
- Biotechnology Discovery Research, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA.
| | - Guihong Qi
- Biotechnology Discovery Research, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
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2
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Tran NH, Qiao R, Mao Z, Pan S, Zhang Q, Li W, Xin L, Li M, Shan B. NovoBoard: a comprehensive framework for evaluating the false discovery rate and accuracy of de novo peptide sequencing. Mol Cell Proteomics 2024:100849. [PMID: 39321875 DOI: 10.1016/j.mcpro.2024.100849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Revised: 08/27/2024] [Accepted: 09/18/2024] [Indexed: 09/27/2024] Open
Abstract
De novo peptide sequencing is one of the most fundamental research areas in mass spectrometry (MS) based proteomics. Many methods have often been evaluated using a couple of simple metrics that do not fully reflect their overall performance. Moreover, there has not been an established method to estimate the false discovery rate (FDR) of de novo peptide-spectrum matches (PSMs). Here we propose NovoBoard, a comprehensive framework to evaluate the performance of de novo peptide sequencing methods. The framework consists of diverse benchmark datasets (including tryptic, nontryptic, immunopeptidomics, and different species), and a standard set of accuracy metrics to evaluate the fragment ions, amino acids, and peptides of the de novo results. More importantly, a new approach is designed to evaluate de novo peptide sequencing methods on target-decoy spectra and to estimate and validate their FDRs. Our FDR estimation provides valuable information to assess the reliability of new peptides identified by de novo sequencing tools, especially when no ground-truth information is available to evaluate their accuracy. The FDR estimation can also be used to evaluate the capability of de novo peptide sequencing tools to distinguish between de novo PSMs and random matches. Our results thoroughly reveal the strengths and weaknesses of different de novo peptide sequencing methods, and how their performances depend on specific applications and the types of data.
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Affiliation(s)
- Ngoc Hieu Tran
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Rui Qiao
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Zeping Mao
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada; David R. Cheriton School of Computer Science, University of Waterloo, Ontario, Canada
| | - Shengying Pan
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Qing Zhang
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Wenting Li
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada
| | - Lei Xin
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada.
| | - Ming Li
- David R. Cheriton School of Computer Science, University of Waterloo, Ontario, Canada.
| | - Baozhen Shan
- Bioinformatics Solutions Inc., Waterloo, Ontario, Canada.
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3
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Fröhlich K, Fahrner M, Brombacher E, Seredynska A, Maldacker M, Kreutz C, Schmidt A, Schilling O. Data-Independent Acquisition: A Milestone and Prospect in Clinical Mass Spectrometry-Based Proteomics. Mol Cell Proteomics 2024; 23:100800. [PMID: 38880244 PMCID: PMC11380018 DOI: 10.1016/j.mcpro.2024.100800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 06/08/2024] [Accepted: 06/13/2024] [Indexed: 06/18/2024] Open
Abstract
Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given m/z range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.
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Affiliation(s)
- Klemens Fröhlich
- Proteomics Core Facility, Biozentrum Basel, University of Basel, Basel, Switzerland
| | - Matthias Fahrner
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany
| | - Eva Brombacher
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany; Centre for Integrative Biological Signaling Studies (CIBSS), University of Freiburg, Freiburg, Germany; Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Freiburg, Germany; Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Adrianna Seredynska
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany; Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Maximilian Maldacker
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Clemens Kreutz
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany; Centre for Integrative Biological Signaling Studies (CIBSS), University of Freiburg, Freiburg, Germany
| | - Alexander Schmidt
- Proteomics Core Facility, Biozentrum Basel, University of Basel, Basel, Switzerland
| | - Oliver Schilling
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany.
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4
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Lapcik P, Synkova K, Janacova L, Bouchalova P, Potesil D, Nenutil R, Bouchal P. A hybrid DDA/DIA-PASEF based assay library for a deep proteotyping of triple-negative breast cancer. Sci Data 2024; 11:794. [PMID: 39025866 PMCID: PMC11258311 DOI: 10.1038/s41597-024-03632-2] [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: 02/14/2024] [Accepted: 07/10/2024] [Indexed: 07/20/2024] Open
Abstract
Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, and deeper proteome coverage is needed for its molecular characterization. We present comprehensive library of targeted mass spectrometry assays specific for TNBC and demonstrate its applicability. Proteins were extracted from 105 TNBC tissues and digested. Aliquots were pooled, fractionated using hydrophilic chromatography and analyzed by LC-MS/MS in data-dependent acquisition (DDA) parallel accumulation-serial fragmentation (PASEF) mode on timsTOF Pro LC-MS system. 16 individual lysates were analyzed in data-independent acquisition (DIA)-PASEF mode. Hybrid library was generated in Spectronaut software and covers 244,464 precursors, 168,006 peptides and 11,564 protein groups (FDR = 1%). Application of our library for pilot quantitative analysis of 16 tissues increased identification numbers in Spectronaut 18.5 and DIA-NN 1.8.1 software compared to library-free setting, with Spectronaut achieving the best results represented by 190,310 precursors, 140,566 peptides, and 10,463 protein groups. In conclusion, we introduce assay library that offers the deepest coverage of TNBC proteome to date. The TNBC library is available via PRIDE repository (PXD047793).
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Grants
- NU22-08-00230 Ministerstvo Zdravotnictví Ceské Republiky (Ministry of Health of the Czech Republic)
- NU22-08-00230 Ministerstvo Zdravotnictví Ceské Republiky (Ministry of Health of the Czech Republic)
- NU22-08-00230 Ministerstvo Zdravotnictví Ceské Republiky (Ministry of Health of the Czech Republic)
- NU22-08-00230 Ministerstvo Zdravotnictví Ceské Republiky (Ministry of Health of the Czech Republic)
- LX22NPO5102 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LX22NPO5102 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LX22NPO5102 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LX22NPO5102 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- CZ.02.1.01/0.0/0.0/18_046/0015974 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
- LM2023033 Ministerstvo Školství, Mládeže a Tělovýchovy (Ministry of Education, Youth and Sports)
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Affiliation(s)
- Petr Lapcik
- Department of Biochemistry, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Klara Synkova
- Department of Biochemistry, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Lucia Janacova
- Department of Biochemistry, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - Pavla Bouchalova
- Department of Biochemistry, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - David Potesil
- Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Rudolf Nenutil
- Department of Oncological Pathology, Masaryk Memorial Cancer Institute, Brno, Czech Republic
| | - Pavel Bouchal
- Department of Biochemistry, Faculty of Science, Masaryk University, Brno, Czech Republic.
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5
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Patel SK, Bons J, Rose JP, Chappel JR, Beres RL, Watson MA, Webster C, Burton JB, Bruderer R, Desprez PY, Reiter L, Campisi J, Baker ES, Schilling B. Exosomes Released from Senescent Cells and Circulatory Exosomes Isolated from Human Plasma Reveal Aging-associated Proteomic and Lipid Signatures. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.22.600215. [PMID: 38979258 PMCID: PMC11230204 DOI: 10.1101/2024.06.22.600215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Senescence emerged as a significant mechanism of aging and age-related diseases, offering an attractive target for clinical interventions. Senescent cells release a senescence-associated secretory phenotype (SASP), including exosomes that may act as signal transducers between distal tissues, propagating secondary or bystander senescence and signaling throughout the body. However, the composition of exosome SASP remains underexplored, presenting an opportunity for novel unbiased discovery. Here, we present a detailed proteomic and lipidomic analysis of exosome SASP using mass spectrometry from human plasma from young and older individuals and from tissue culture of senescent primary human lung fibroblasts. We identified ~1,300 exosome proteins released by senescent fibroblasts induced by three different senescence inducers causing most exosome proteins to be differentially regulated with senescence. In parallel, a human plasma cohort from young and old individuals revealed over 1,350 exosome proteins and 171 plasma exosome proteins were regulated when comparing old vs young individuals. Of the age-regulated plasma exosome proteins, we observed 52 exosome SASP factors that were also regulated in exosomes from the senescent fibroblasts, including serine protease inhibitors (SERPINs), Prothrombin, Coagulation factor V, Plasminogen, and Reelin. In addition, 247 lipids were identified with high confidence in all exosome samples. Following the senescence inducers, a majority of the identified phosphatidylcholine, phosphatidylethanolamine, and sphingomyelin species increased significantly indicating cellular membrane changes. The most notable categories of significantly changed proteins were related to extracellular matrix remodeling and inflammation, both potentially detrimental pathways that can damage surrounding tissues and even induce secondary or bystander senescence. Our findings reveal mechanistic insights and potential senescence biomarkers, enabling a better approach to surveilling the senescence burden in the aging population and offering promising therapeutic targets for interventions.
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6
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Baker C, Bruderer R, Abbott J, Arthur JSC, Brenes AJ. Optimizing Spectronaut Search Parameters to Improve Data Quality with Minimal Proteome Coverage Reductions in DIA Analyses of Heterogeneous Samples. J Proteome Res 2024; 23:1926-1936. [PMID: 38691771 PMCID: PMC11165578 DOI: 10.1021/acs.jproteome.3c00671] [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: 10/12/2023] [Revised: 01/18/2024] [Accepted: 04/19/2024] [Indexed: 05/03/2024]
Abstract
Data-independent acquisition has seen breakthroughs that enable comprehensive proteome profiling using short gradients. As the proteome coverage continues to increase, the quality of the data generated becomes much more relevant. Using Spectronaut, we show that the default search parameters can be easily optimized to minimize the occurrence of false positives across different samples. Using an immunological infection model system to demonstrate the impact of adjusting search settings, we analyzed Mus musculus macrophages and compared their proteome to macrophages spiked withCandida albicans. This experimental system enabled the identification of "false positives" as Candida albicans peptides and proteins should not be present in the Mus musculus-only samples. We show that adjusting the search parameters reduced "false positive" identifications by 89% at the peptide and protein level, thereby considerably increasing the quality of the data. We also show that these optimized parameters incurred a moderate cost, only reducing the overall number of "true positive" identifications across each biological replicate by <6.7% at both the peptide and protein level. We believe the value of our updated search parameters extends beyond a two-organism analysis and would be of great value to any DIA experiment analyzing heterogeneous populations of cell types or tissues.
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Affiliation(s)
- Christa
P. Baker
- Division
of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom
| | | | - James Abbott
- Data
Analysis Group, Division of Computational Biology, School of Life
Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom
| | - J. Simon C. Arthur
- Division
of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom
| | - Alejandro J. Brenes
- Division
of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Dundee DD1 5EH, United Kingdom
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7
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Thiery J, Fahrner M. Integration of proteomics in the molecular tumor board. Proteomics 2024; 24:e2300002. [PMID: 38143279 DOI: 10.1002/pmic.202300002] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 12/03/2023] [Accepted: 12/05/2023] [Indexed: 12/26/2023]
Abstract
Cancer remains one of the most complex and challenging diseases in mankind. To address the need for a personalized treatment approach for particularly complex tumor cases, molecular tumor boards (MTBs) have been initiated. MTBs are interdisciplinary teams that perform in-depth molecular diagnostics to cooperatively and interdisciplinarily advise on the best therapeutic strategy. Current molecular diagnostics are routinely performed on the transcriptomic and genomic levels, aiming to identify tumor-driving mutations. However, these approaches can only partially capture the actual phenotype and the molecular key players of tumor growth and progression. Thus, direct investigation of the expressed proteins and activated signaling pathways provide valuable complementary information on the tumor-driving molecular characteristics of the tissue. Technological advancements in mass spectrometry-based proteomics enable the robust, rapid, and sensitive detection of thousands of proteins in minimal sample amounts, paving the way for clinical proteomics and the probing of oncogenic signaling activity. Therefore, proteomics is currently being integrated into molecular diagnostics within MTBs and holds promising potential in aiding tumor classification and identifying personalized treatment strategies. This review introduces MTBs and describes current clinical proteomics, its potential in precision oncology, and highlights the benefits of multi-omic data integration.
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Affiliation(s)
- Johanna Thiery
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Matthias Fahrner
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany
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8
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Kidane YH, Lee FH, Smith MF, Wang C, Mirza JB, Sharma S, Lobo AA, Dewan KC, Chen J, Diaz TE, Pla MM, Foster MW, Bowles DE. Proteomic and phosphoproteomic characterization of cardiovascular tissues after long term exposure to simulated space radiation. Front Physiol 2024; 15:1248276. [PMID: 38699144 PMCID: PMC11063234 DOI: 10.3389/fphys.2024.1248276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 02/09/2024] [Indexed: 05/05/2024] Open
Abstract
Introduction: It may take decades to develop cardiovascular dysfunction following exposure to high doses of ionizing radiation from medical therapy or from nuclear accidents. Since astronauts may be exposed continually to a complex space radiation environment unlike that experienced on Earth, it is unresolved whether there is a risk to cardiovascular health during long-term space exploration missions. Previously, we have described that mice exposed to a single dose of simplified Galactic Cosmic Ray (GCR5-ion) develop cardiovascular dysfunction by 12 months post-radiation. Methods: To investigate the biological basis of this dysfunction, here we performed a quantitative mass spectrometry-based proteomics analysis of heart tissue (proteome and phosphoproteome) and plasma (proteome only) from these mice at 8 months post-radiation. Results: Differentially expressed proteins (DEPs) for irradiated versus sham irradiated samples (fold-change ≥1.2 and an adjusted p-value of ≤0.05) were identified for each proteomics data set. For the heart proteome, there were 87 significant DEPs (11 upregulated and 76 downregulated); for the heart phosphoproteome, there were 60 significant differentially phosphorylated peptides (17 upregulated and 43 downregulated); and for the plasma proteome, there was only one upregulated protein. A Gene Set Enrichment Analysis (GSEA) technique that assesses canonical pathways from BIOCARTA, KEGG, PID, REACTOME, and WikiPathways revealed significant perturbation in pathways in each data set. For the heart proteome, 166 pathways were significantly altered (36 upregulated and 130 downregulated); for the plasma proteome, there were 73 pathways significantly altered (25 upregulated and 48 downregulated); and for the phosphoproteome, there were 223 pathways significantly affected at 0.1 adjusted p-value cutoff. Pathways related to inflammation were the most highly perturbed in the heart and plasma. In line with sustained inflammation, neutrophil extracellular traps (NETs) were demonstrated to be increased in GCR5-ion irradiated hearts at 12-month post irradiation. NETs play a fundamental role in combating bacterial pathogens, modulating inflammatory responses, inflicting damage on healthy tissues, and escalating vascular thrombosis. Discussion: These findings suggest that a single exposure to GCR5-ion results in long-lasting changes in the proteome and that these proteomic changes can potentiate acute and chronic health issues for astronauts, such as what we have previously described with late cardiac dysfunction in these mice.
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Affiliation(s)
- Yared H. Kidane
- Center for Pediatric Bone Biology and Translational Research, Scottish Rite for Children, Dallas, TX, United States
| | - Franklin H. Lee
- Department of Surgery, Duke University Medical Center, Durham, NC, United States
| | - Matthew F. Smith
- Department of Surgery, Duke University Medical Center, Durham, NC, United States
| | - Chunbo Wang
- Department of Surgery, Duke University Medical Center, Durham, NC, United States
| | - Jacqueline Barbera Mirza
- Dr. Kiran C. Patel College of Allopathic Medicine, Nova Southeastern University, Fort Lauderdale, FL, United States
| | - Saachi Sharma
- Stanton College Preparatory School, Jacksonville, FL, United States
| | - Alejandro A. Lobo
- Department of Surgery, Duke University Medical Center, Durham, NC, United States
| | - Krish C. Dewan
- Department of Surgery, Duke University Medical Center, Durham, NC, United States
| | - Jengwei Chen
- Department of Surgery, Duke University Medical Center, Durham, NC, United States
- Department of Surgery, National Taiwan University Hospital, Taipei, Taiwan
| | - Thomas E. Diaz
- Eshelman School of Pharmacy, Chapel Hill, NC, United States
| | | | - Matthew W. Foster
- Duke Proteomics and Metabolomics Core Facility, Duke University Medical Center, Durham, NC, United States
| | - Dawn E. Bowles
- Department of Surgery, Duke University Medical Center, Durham, NC, United States
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9
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Konno R, Ishikawa M, Nakajima D, Endo Y, Ohara O, Kawashima Y. Universal Pretreatment Development for Low-input Proteomics Using Lauryl Maltose Neopentyl Glycol. Mol Cell Proteomics 2024; 23:100745. [PMID: 38447790 PMCID: PMC10999711 DOI: 10.1016/j.mcpro.2024.100745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 02/23/2024] [Accepted: 03/01/2024] [Indexed: 03/08/2024] Open
Abstract
In recent years, there has been a growing demand for low-input proteomics, particularly in the context of single-cell proteomics (SCP). In this study, we have developed a lauryl maltose neopentyl glycol (LMNG)-assisted sample preparation (LASP) method. This method effectively reduces protein and peptide loss in samples by incorporating LMNG, a surfactant, into the digestion solution and subsequently removing the LMNG simply via reversed phase solid-phase extraction. The advantage of removing LMNG during sample preparation for general proteomic analysis is the prevention of mass spectrometry (MS) contamination. When we applied the LASP method to the low-input SP3 method and on-bead digestion in coimmunoprecipitation-MS, we observed a significant improvement in the recovery of the digested peptides. Furthermore, we have established a simple and easy sample preparation method for SCP based on the LASP method and identified a median of 1175 proteins from a single HEK239F cell using liquid chromatography (LC)-MS/MS with a throughput of 80 samples per day.
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Affiliation(s)
- Ryo Konno
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Masaki Ishikawa
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Daisuke Nakajima
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Yusuke Endo
- Department of Frontier Research and Development, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Osamu Ohara
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Yusuke Kawashima
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan; Graduate School of Science, Kitasato University, Sagamihara, Kanagawa, Japan.
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10
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Sajic T, Ferreira Gomes CK, Gasser M, Caputo T, Bararpour N, Landaluce-Iturriria E, Augsburger M, Walter N, Hainard A, Lopez-Mejia IC, Fracasso T, Thomas A, Gilardi F. SMYD3: a new regulator of adipocyte precursor proliferation at the early steps of differentiation. Int J Obes (Lond) 2024; 48:557-566. [PMID: 38148333 PMCID: PMC10978492 DOI: 10.1038/s41366-023-01450-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 12/06/2023] [Accepted: 12/12/2023] [Indexed: 12/28/2023]
Abstract
BACKGROUND In obesity, adipose tissue undergoes a remodeling process characterized by increased adipocyte size (hypertrophia) and number (hyperplasia). The ability to tip the balance toward the hyperplastic growth, with recruitment of new fat cells through adipogenesis, seems to be critical for a healthy adipose tissue expansion, as opposed to a hypertrophic growth that is accompanied by the development of inflammation and metabolic dysfunction. However, the molecular mechanisms underlying the fine-tuned regulation of adipose tissue expansion are far from being understood. METHODS We analyzed by mass spectrometry-based proteomics visceral white adipose tissue (vWAT) samples collected from C57BL6 mice fed with a HFD for 8 weeks. A subset of these mice, called low inflammation (Low-INFL), showed reduced adipose tissue inflammation, as opposed to those developing the expected inflammatory response (Hi-INFL). We identified the discriminants between Low-INFL and Hi-INFL vWAT samples and explored their function in Adipose-Derived human Mesenchymal Stem Cells (AD-hMSCs) differentiated to adipocytes. RESULTS vWAT proteomics allowed us to quantify 6051 proteins. Among the candidates that most differentiate Low-INFL from Hi-INFL vWAT, we found proteins involved in adipocyte function, including adiponectin and hormone sensitive lipase, suggesting that adipocyte differentiation is enhanced in Low-INFL, as compared to Hi-INFL. The chromatin modifier SET and MYND Domain Containing 3 (SMYD3), whose function in adipose tissue was so far unknown, was another top-scored hit. SMYD3 expression was significantly higher in Low-INFL vWAT, as confirmed by western blot analysis. Using AD-hMSCs in culture, we found that SMYD3 mRNA and protein levels decrease rapidly during the adipocyte differentiation. Moreover, SMYD3 knock-down before adipocyte differentiation resulted in reduced H3K4me3 and decreased cell proliferation, thus limiting the number of cells available for adipogenesis. CONCLUSIONS Our study describes an important role of SMYD3 as a newly discovered regulator of adipocyte precursor proliferation during the early steps of adipogenesis.
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Affiliation(s)
- Tatjana Sajic
- Unit of Forensic Toxicology and Chemistry, CURML, Lausanne and Geneva University Hospitals, Lausanne, Geneva, Switzerland
- Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | | | - Marie Gasser
- Unit of Forensic Toxicology and Chemistry, CURML, Lausanne and Geneva University Hospitals, Lausanne, Geneva, Switzerland
- Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Tiziana Caputo
- Section on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
| | - Nasim Bararpour
- Stanford Center for Genomics and Personalized Medicine, Stanford, CA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
| | | | - Marc Augsburger
- Unit of Forensic Toxicology and Chemistry, CURML, Lausanne and Geneva University Hospitals, Lausanne, Geneva, Switzerland
| | - Nadia Walter
- Proteomics Core Facility, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Alexandre Hainard
- Proteomics Core Facility, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | | | - Tony Fracasso
- Unit of Forensic Medicine, CURML, Lausanne and Geneva University Hospitals, Lausanne, Geneva, Switzerland
| | - Aurélien Thomas
- Unit of Forensic Toxicology and Chemistry, CURML, Lausanne and Geneva University Hospitals, Lausanne, Geneva, Switzerland
- Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Federica Gilardi
- Unit of Forensic Toxicology and Chemistry, CURML, Lausanne and Geneva University Hospitals, Lausanne, Geneva, Switzerland.
- Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.
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11
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Hamza GM, Raghunathan R, Ashenden S, Zhang B, Miele E, Jarnuczak AF. Proteomics of prostate cancer serum and plasma using low and high throughput approaches. Clin Proteomics 2024; 21:21. [PMID: 38475692 DOI: 10.1186/s12014-024-09461-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 02/12/2024] [Indexed: 03/14/2024] Open
Abstract
Despite progress, MS-based proteomics in biofluids, especially blood, faces challenges such as dynamic range and throughput limitations in biomarker and disease studies. In this work, we used cutting-edge proteomics technologies to construct label-based and label-free workflows, capable of quantifying approximately 2,000 proteins in biofluids. With 70µL of blood and a single depletion strategy, we conducted an analysis of a homogenous cohort (n = 32), comparing medium-grade prostate cancer patients (Gleason score: 7(3 + 4); TNM stage: T2cN0M0, stage IIB) to healthy donors. The results revealed dozens of differentially expressed proteins in both plasma and serum. We identified the upregulation of Prostate Specific Antigen (PSA), a well-known biomarker for prostate cancer, in the serum of cancer cohort. Further bioinformatics analysis highlighted noteworthy proteins which appear to be differentially secreted into the bloodstream, making them good candidates for further exploration.
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Affiliation(s)
| | - Rekha Raghunathan
- Bioanalytical and Biomarker, Prevail Therapeutics, Wholly Owned Subsidiary of Eli Lilly and Company, New York, NY, 10016, USA
| | | | - Bairu Zhang
- Discovery Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Eric Miele
- Discovery Sciences, R&D, AstraZeneca, Cambridge, UK.
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12
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Strauss MT, Bludau I, Zeng WF, Voytik E, Ammar C, Schessner JP, Ilango R, Gill M, Meier F, Willems S, Mann M. AlphaPept: a modern and open framework for MS-based proteomics. Nat Commun 2024; 15:2168. [PMID: 38461149 PMCID: PMC10924963 DOI: 10.1038/s41467-024-46485-4] [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: 12/20/2022] [Accepted: 02/20/2024] [Indexed: 03/11/2024] Open
Abstract
In common with other omics technologies, mass spectrometry (MS)-based proteomics produces ever-increasing amounts of raw data, making efficient analysis a principal challenge. A plethora of different computational tools can process the MS data to derive peptide and protein identification and quantification. However, during the last years there has been dramatic progress in computer science, including collaboration tools that have transformed research and industry. To leverage these advances, we develop AlphaPept, a Python-based open-source framework for efficient processing of large high-resolution MS data sets. Numba for just-in-time compilation on CPU and GPU achieves hundred-fold speed improvements. AlphaPept uses the Python scientific stack of highly optimized packages, reducing the code base to domain-specific tasks while accessing the latest advances. We provide an easy on-ramp for community contributions through the concept of literate programming, implemented in Jupyter Notebooks. Large datasets can rapidly be processed as shown by the analysis of hundreds of proteomes in minutes per file, many-fold faster than acquisition. AlphaPept can be used to build automated processing pipelines with web-serving functionality and compatibility with downstream analysis tools. It provides easy access via one-click installation, a modular Python library for advanced users, and via an open GitHub repository for developers.
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Affiliation(s)
- Maximilian T Strauss
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
- NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Isabell Bludau
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Wen-Feng Zeng
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Eugenia Voytik
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Constantin Ammar
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Julia P Schessner
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | | | | | - Florian Meier
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
- Functional Proteomics, Jena University Hospital, Jena, Germany
| | - Sander Willems
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Matthias Mann
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
- NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
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13
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Fröhlich K, Furrer R, Schori C, Handschin C, Schmidt A. Robust, Precise, and Deep Proteome Profiling Using a Small Mass Range and Narrow Window Data-Independent-Acquisition Scheme. J Proteome Res 2024; 23:1028-1038. [PMID: 38275131 PMCID: PMC10913089 DOI: 10.1021/acs.jproteome.3c00736] [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: 11/05/2023] [Revised: 12/20/2023] [Accepted: 12/26/2023] [Indexed: 01/27/2024]
Abstract
In recent years, a plethora of different data-independent acquisition methods have been developed for proteomics to cover a wide range of requirements. Current deep proteome profiling methods rely on fractionations, elaborate chromatography, and mass spectrometry setups or display suboptimal quantitative precision. We set out to develop an easy-to-use one shot DIA method that achieves high quantitative precision and high proteome coverage. We achieve this by focusing on a small mass range of 430-670 m/z using small isolation windows without overlap. With this new method, we were able to quantify >9200 protein groups in HEK lysates with an average coefficient of variance of 3.2%. To demonstrate the power of our newly developed narrow mass range method, we applied it to investigate the effect of PGC-1α knockout on the skeletal muscle proteome in mice. Compared to a standard data-dependent acquisition method, we could double proteome coverage and, most importantly, achieve a significantly higher quantitative precision, as compared to a previously proposed DIA method. We believe that our method will be especially helpful in quantifying low abundant proteins in samples with a high dynamic range. All raw and result files are available at massive.ucsd.edu (MSV000092186).
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Affiliation(s)
- Klemens Fröhlich
- Proteomics
Core Facility, Biozentrum Basel, University
of Basel, 4056 Basel, Switzerland
| | - Regula Furrer
- Biozentrum
Basel, University of Basel, 4056 Basel, Switzerland
| | - Christian Schori
- Proteomics
Core Facility, Biozentrum Basel, University
of Basel, 4056 Basel, Switzerland
| | | | - Alexander Schmidt
- Proteomics
Core Facility, Biozentrum Basel, University
of Basel, 4056 Basel, Switzerland
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14
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Hartley B, Bassiouni W, Roczkowsky A, Fahlman R, Schulz R, Julien O. Data-Independent Acquisition Proteomics and N-Terminomics Methods Reveal Alterations in Mitochondrial Function and Metabolism in Ischemic-Reperfused Hearts. J Proteome Res 2024; 23:844-856. [PMID: 38264990 PMCID: PMC10846531 DOI: 10.1021/acs.jproteome.3c00754] [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: 11/11/2023] [Revised: 01/06/2024] [Accepted: 01/10/2024] [Indexed: 01/25/2024]
Abstract
Myocardial ischemia-reperfusion (IR) (stunning) injury triggers changes in the proteome and degradome of the heart. Here, we utilize quantitative proteomics and comprehensive degradomics to investigate the molecular mechanisms of IR injury in isolated rat hearts. The control group underwent aerobic perfusion, while the IR injury group underwent 20 min of ischemia and 30 min of reperfusion to induce a stunning injury. As MMP-2 activation has been shown to contribute to myocardial injury, hearts also underwent IR injury with ARP-100, an MMP-2-preferring inhibitor, to dissect the contribution of MMP-2 to IR injury. Using data-independent acquisition (DIA) and mass spectroscopy, we quantified 4468 proteins in ventricular extracts, whereby 447 proteins showed significant alterations among the three groups. We then used subtiligase-mediated N-terminomic labeling to identify more than a hundred specific cleavage sites. Among these protease substrates, 15 were identified following IR injury. We identified alterations in numerous proteins involved in mitochondrial function and metabolism following IR injury. Our findings provide valuable insights into the biochemical mechanisms of myocardial IR injury, suggesting alterations in reactive oxygen/nitrogen species handling and generation, fatty acid metabolism, mitochondrial function and metabolism, and cardiomyocyte contraction.
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Affiliation(s)
- Bridgette Hartley
- Department
of Biochemistry, University of Alberta, Edmonton T6G 2H7, Canada
| | - Wesam Bassiouni
- Department
of Pharmacology, University of Alberta, Edmonton T6G 2S2, Canada
| | - Andrej Roczkowsky
- Department
of Pharmacology, University of Alberta, Edmonton T6G 2S2, Canada
| | - Richard Fahlman
- Department
of Biochemistry, University of Alberta, Edmonton T6G 2H7, Canada
| | - Richard Schulz
- Department
of Pharmacology, University of Alberta, Edmonton T6G 2S2, Canada
- Department
of Pediatrics, University of Alberta, Edmonton T6G 2S2, Canada
| | - Olivier Julien
- Department
of Biochemistry, University of Alberta, Edmonton T6G 2H7, Canada
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15
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Younas A, Younas N, Iqbal MJ, Ferrer I, Zerr I. Comparative interactome mapping of Tau-protein in classical and rapidly progressive Alzheimer's disease identifies subtype-specific pathways. Neuropathol Appl Neurobiol 2024; 50:e12964. [PMID: 38374702 DOI: 10.1111/nan.12964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 12/27/2023] [Accepted: 01/16/2024] [Indexed: 02/21/2024]
Abstract
AIMS Tau is a key player in Alzheimer's disease (AD) and other Tauopathies. Tau pathology in the brain directly correlates with neurodegeneration in AD. The recent identification of a rapid variant of AD demands an urgent need to uncover underlying mechanisms leading to differential progression in AD. Accordingly, we aimed to dissect the underlying differential mechanisms of toxicity associated with the Tau protein in AD subtypes and to find out subtype-dependent biomarkers and therapeutic targets. METHODS To identify and characterise subtype-specific Tau-associated mechanisms of pathology, we performed comparative interactome mapping of Tau protein in classical AD (cAD) and rapidly progressive AD (rpAD) cases using co-immunoprecipitation coupled with quantitative mass spectrometry. The mass spectrometry data were extensively analysed using several bioinformatics approaches. RESULTS The comparative interactome mapping of Tau protein revealed distinct and unique interactors (DPYSL4, ARHGEF2, TUBA4A and UQCRC2) in subtypes of AD. Interestingly, an analysis of the Tau-interacting proteins indicated enrichment of mitochondrial organisation processes, including negative regulation of mitochondrion organisation, mitochondrial outer membrane permeabilisation involved in programmed cell death, regulation of autophagy of mitochondrion and necroptotic processes, specifically in the rpAD interactome. While, in cAD, the top enriched processes were related to oxidation-reduction process, transport and monocarboxylic acid metabolism. CONCLUSIONS Overall, our results provide a comprehensive map of Tau-interacting protein networks in a subtype-dependent manner and shed light on differential functions/pathways in AD subtypes. This comprehensive map of the Tau-interactome has provided subsets of disease-related proteins that can serve as novel biomarkers/biomarker panels and new drug targets.
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Affiliation(s)
- Abrar Younas
- National Reference Center for Surveillance of TSE, Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Department of Biological Sciences, Faculty of Sciences, University of Sialkot, Sialkot, Pakistan
| | - Neelam Younas
- National Reference Center for Surveillance of TSE, Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
| | - Muhammad Javed Iqbal
- Department of Biotechnology, Faculty of Sciences, University of Sialkot, Sialkot, Pakistan
| | - Isidre Ferrer
- Department of Pathology and Experimental Therapeutics, University of Barcelona, Hospitalet de Llobregat, Spain
| | - Inga Zerr
- National Reference Center for Surveillance of TSE, Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
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16
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Deng B, Vanagas L, Alonso AM, Angel SO. Proteomics Applications in Toxoplasma gondii: Unveiling the Host-Parasite Interactions and Therapeutic Target Discovery. Pathogens 2023; 13:33. [PMID: 38251340 PMCID: PMC10821451 DOI: 10.3390/pathogens13010033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 12/25/2023] [Accepted: 12/27/2023] [Indexed: 01/23/2024] Open
Abstract
Toxoplasma gondii, a protozoan parasite with the ability to infect various warm-blooded vertebrates, including humans, is the causative agent of toxoplasmosis. This infection poses significant risks, leading to severe complications in immunocompromised individuals and potentially affecting the fetus through congenital transmission. A comprehensive understanding of the intricate molecular interactions between T. gondii and its host is pivotal for the development of effective therapeutic strategies. This review emphasizes the crucial role of proteomics in T. gondii research, with a specific focus on host-parasite interactions, post-translational modifications (PTMs), PTM crosstalk, and ongoing efforts in drug discovery. Additionally, we provide an overview of recent advancements in proteomics techniques, encompassing interactome sample preparation methods such as BioID (BirA*-mediated proximity-dependent biotin identification), APEX (ascorbate peroxidase-mediated proximity labeling), and Y2H (yeast two hybrid), as well as various proteomics approaches, including single-cell analysis, DIA (data-independent acquisition), targeted, top-down, and plasma proteomics. Furthermore, we discuss bioinformatics and the integration of proteomics with other omics technologies, highlighting its potential in unraveling the intricate mechanisms of T. gondii pathogenesis and identifying novel therapeutic targets.
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Affiliation(s)
- Bin Deng
- Department of Biology and VBRN Proteomics Facility, University of Vermont, Burlington, VT 05405, USA
| | - Laura Vanagas
- Laboratorio de Parasitología Molecular, Instituto Tecnológico de Chascomús (CONICET-UNSAM), Chascomús 7130, Provincia de Buenos Aires, Argentina; (L.V.); (S.O.A.); (A.M.A.)
- Escuela de Bio y Nanotecnologías (UNSAM), 25 de Mayo y Francia. C.P., San Martín 1650, Provincia de Buenos Aires, Argentina
| | - Andres M. Alonso
- Laboratorio de Parasitología Molecular, Instituto Tecnológico de Chascomús (CONICET-UNSAM), Chascomús 7130, Provincia de Buenos Aires, Argentina; (L.V.); (S.O.A.); (A.M.A.)
- Escuela de Bio y Nanotecnologías (UNSAM), 25 de Mayo y Francia. C.P., San Martín 1650, Provincia de Buenos Aires, Argentina
| | - Sergio O. Angel
- Laboratorio de Parasitología Molecular, Instituto Tecnológico de Chascomús (CONICET-UNSAM), Chascomús 7130, Provincia de Buenos Aires, Argentina; (L.V.); (S.O.A.); (A.M.A.)
- Escuela de Bio y Nanotecnologías (UNSAM), 25 de Mayo y Francia. C.P., San Martín 1650, Provincia de Buenos Aires, Argentina
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17
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Azimi A, Jabbour S, Patrick E, Fernandez-Penas P. Non-invasive diagnosis of early cutaneous squamous cell carcinoma. Exp Dermatol 2023; 32:1946-1959. [PMID: 37688398 DOI: 10.1111/exd.14921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 07/28/2023] [Accepted: 08/27/2023] [Indexed: 09/10/2023]
Abstract
Early cutaneous squamous cell carcinoma (cSCC) can be challenging to diagnose using clinical criteria as it could present similar to actinic keratosis (AK) or Bowen's disease (BD), precursors of cSCC. Currently, histopathological assessment of an invasive biopsy is the gold standard for diagnosis. A non-invasive diagnostic approach would reduce patient and health system burden. Therefore, this study used non-invasive sampling by tape-stripping coupled with data-independent acquisition mass spectrometry (DIA-MS) proteomics to profile the proteome of histopathologically diagnosed AK, BD and cSCC, as well as matched normal samples. Proteomic data were analysed to identify proteins and biological functions that are significantly different between lesions. Additionally, a support vector machine (SVM) machine learning algorithm was used to assess the usefulness of proteomic data for the early diagnosis of cSCC. A total of 696 proteins were identified across the samples studied. A machine learning model constructed using the proteomic data classified premalignant (AK + BD) and malignant (cSCC) lesions at 77.5% accuracy. Differential abundance analysis identified 144 and 21 protein groups that were significantly changed in the cSCC, and BD samples compared to the normal skin, respectively (adj. p < 0.05). Changes in pivotal carcinogenic pathways such as LXR/RXR activation, production of reactive oxygen species, and Hippo signalling were observed that may explain the progression of cSCC from premalignant lesions. In summary, this study demonstrates that DIA-MS analysis of tape-stripped samples can identify non-invasive protein biomarkers with the potential to be developed into a complementary diagnostic tool for early cSCC.
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Affiliation(s)
- Ali Azimi
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
- Department of Dermatology, Westmead Hospital, Westmead, New South Wales, Australia
| | - Steven Jabbour
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
- Department of Dermatology, Westmead Hospital, Westmead, New South Wales, Australia
| | - Ellis Patrick
- Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
- School of Mathematics and Statistics, Faculty of Science, The University of Sydney, Camperdown, New South Wales, Australia
- Sydney Precision Data Science Centre, The University of Sydney, Camperdown, New South Wales, Australia
| | - Pablo Fernandez-Penas
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
- Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
- Department of Dermatology, Westmead Hospital, Westmead, New South Wales, Australia
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18
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Kitata RB, Yang JC, Chen YJ. Advances in data-independent acquisition mass spectrometry towards comprehensive digital proteome landscape. MASS SPECTROMETRY REVIEWS 2023; 42:2324-2348. [PMID: 35645145 DOI: 10.1002/mas.21781] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 12/17/2021] [Accepted: 01/21/2022] [Indexed: 06/15/2023]
Abstract
The data-independent acquisition mass spectrometry (DIA-MS) has rapidly evolved as a powerful alternative for highly reproducible proteome profiling with a unique strength of generating permanent digital maps for retrospective analysis of biological systems. Recent advancements in data analysis software tools for the complex DIA-MS/MS spectra coupled to fast MS scanning speed and high mass accuracy have greatly expanded the sensitivity and coverage of DIA-based proteomics profiling. Here, we review the evolution of the DIA-MS techniques, from earlier proof-of-principle of parallel fragmentation of all-ions or ions in selected m/z range, the sequential window acquisition of all theoretical mass spectra (SWATH-MS) to latest innovations, recent development in computation algorithms for data informatics, and auxiliary tools and advanced instrumentation to enhance the performance of DIA-MS. We further summarize recent applications of DIA-MS and experimentally-derived as well as in silico spectra library resources for large-scale profiling to facilitate biomarker discovery and drug development in human diseases with emphasis on the proteomic profiling coverage. Toward next-generation DIA-MS for clinical proteomics, we outline the challenges in processing multi-dimensional DIA data set and large-scale clinical proteomics, and continuing need in higher profiling coverage and sensitivity.
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Affiliation(s)
| | - Jhih-Ci Yang
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
- Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Applied Chemistry, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
- Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Chemistry, National Taiwan University, Taipei, Taiwan
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19
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Reilly L, Lara E, Ramos D, Li Z, Pantazis CB, Stadler J, Santiana M, Roberts J, Faghri F, Hao Y, Nalls MA, Narayan P, Liu Y, Singleton AB, Cookson MR, Ward ME, Qi YA. A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline. CELL REPORTS METHODS 2023; 3:100593. [PMID: 37729920 PMCID: PMC10626189 DOI: 10.1016/j.crmeth.2023.100593] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 06/30/2023] [Accepted: 08/24/2023] [Indexed: 09/22/2023]
Abstract
Here, we present a standardized, "off-the-shelf" proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high throughput and scalability. This integrated pipeline streamlines a fully automated sample preparation platform, a data-independent acquisition (DIA) coupled with high-field asymmetric waveform ion mobility spectrometer (FAIMS) interface, and an optimized library-free DIA database search strategy. Our systematic evaluation of FAIMS-DIA showing single compensation voltage (CV) at -35 V not only yields the deepest proteome coverage but also best correlates with DIA without FAIMS. Our in-depth comparison of direct-DIA database search engines shows that Spectronaut outperforms others, providing the highest quantifiable proteins. Next, we apply three common DIA strategies in characterizing human induced pluripotent stem cell (iPSC)-derived neurons and show single-shot mass spectrometry (MS) using single-CV (-35 V)-FAIMS-DIA results in >9,000 quantifiable proteins with <10% missing values, as well as superior reproducibility and accuracy compared with other existing DIA methods.
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Affiliation(s)
- Luke Reilly
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Erika Lara
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Daniel Ramos
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Ziyi Li
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Data Tecnica International, LLC, Glen Echo, MD, USA
| | - Caroline B Pantazis
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Julia Stadler
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Marianita Santiana
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Jessica Roberts
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Faraz Faghri
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA; Data Tecnica International, LLC, Glen Echo, MD, USA
| | - Ying Hao
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA; Data Tecnica International, LLC, Glen Echo, MD, USA
| | - Priyanka Narayan
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Genetics and Biochemistry Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20814, USA
| | - Yansheng Liu
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Andrew B Singleton
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Mark R Cookson
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Michael E Ward
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Yue A Qi
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
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20
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Rose JP, Schurman CA, King CD, Bons J, Patel SK, Burton JB, O’Broin A, Alliston T, Schilling B. Deep coverage and quantification of the bone proteome provides enhanced opportunities for new discoveries in skeletal biology and disease. PLoS One 2023; 18:e0292268. [PMID: 37816044 PMCID: PMC10564166 DOI: 10.1371/journal.pone.0292268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 09/15/2023] [Indexed: 10/12/2023] Open
Abstract
Dysregulation of cell signaling in chondrocytes and in bone cells, such as osteocytes, osteoblasts, osteoclasts, and an elevated burden of senescent cells in cartilage and bone, are implicated in osteoarthritis (OA). Mass spectrometric analyses provides a crucial molecular tool-kit to understand complex signaling relationships in age-related diseases, such as OA. Here we introduce a novel mass spectrometric workflow to promote proteomic studies of bone. This workflow uses highly specialized steps, including extensive overnight demineralization, pulverization, and incubation for 72 h in 6 M guanidine hydrochloride and EDTA, followed by proteolytic digestion. Analysis on a high-resolution Orbitrap Eclipse and Orbitrap Exploris 480 mass spectrometer using Data-Independent Acquisition (DIA) provides deep coverage of the bone proteome, and preserves post-translational modifications, such as hydroxyproline. A spectral library-free quantification strategy, directDIA, identified and quantified over 2,000 protein groups (with ≥ 2 unique peptides) from calcium-rich bone matrices. Key components identified were proteins of the extracellular matrix (ECM), bone-specific proteins (e.g., secreted protein acidic and cysteine rich, SPARC, and bone sialoprotein 2, IBSP), and signaling proteins (e.g., transforming growth factor beta-2, TGFB2), and lysyl oxidase homolog 2 (LOXL2), an important protein in collagen crosslinking. Post-translational modifications (PTMs) were identified without the need for specific enrichment. This includes collagen hydroxyproline modifications, chemical modifications for collagen self-assembly and network formation. Multiple senescence factors were identified, such as complement component 3 (C3) protein of the complement system and many matrix metalloproteinases, that might be monitored during age-related bone disease progression. Our innovative workflow yields in-depth protein coverage and quantification strategies to discover underlying biological mechanisms of bone aging and to provide tools to monitor therapeutic interventions. These novel tools to monitor the bone proteome open novel horizons to investigate bone-specific diseases, many of which are age-related.
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Affiliation(s)
- Jacob P. Rose
- Buck Institute for Research on Aging, Novato, CA, United States of America
| | | | - Christina D. King
- Buck Institute for Research on Aging, Novato, CA, United States of America
| | - Joanna Bons
- Buck Institute for Research on Aging, Novato, CA, United States of America
| | - Sandip K. Patel
- Buck Institute for Research on Aging, Novato, CA, United States of America
| | - Jordan B. Burton
- Buck Institute for Research on Aging, Novato, CA, United States of America
| | - Amy O’Broin
- Buck Institute for Research on Aging, Novato, CA, United States of America
| | - Tamara Alliston
- Department of Orthopaedic Surgery, University of California, San Francisco, CA, Unted States of America
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, United States of America
| | - Birgit Schilling
- Buck Institute for Research on Aging, Novato, CA, United States of America
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21
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Bennike TB. Advances in proteomics: characterization of the innate immune system after birth and during inflammation. Front Immunol 2023; 14:1254948. [PMID: 37868984 PMCID: PMC10587584 DOI: 10.3389/fimmu.2023.1254948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 09/26/2023] [Indexed: 10/24/2023] Open
Abstract
Proteomics is the characterization of the protein composition, the proteome, of a biological sample. It involves the large-scale identification and quantification of proteins, peptides, and post-translational modifications. This review focuses on recent developments in mass spectrometry-based proteomics and provides an overview of available methods for sample preparation to study the innate immune system. Recent advancements in the proteomics workflows, including sample preparation, have significantly improved the sensitivity and proteome coverage of biological samples including the technically difficult blood plasma. Proteomics is often applied in immunology and has been used to characterize the levels of innate immune system components after perturbations such as birth or during chronic inflammatory diseases like rheumatoid arthritis (RA) and inflammatory bowel disease (IBD). In cancers, the tumor microenvironment may generate chronic inflammation and release cytokines to the circulation. In these situations, the innate immune system undergoes profound and long-lasting changes, the large-scale characterization of which may increase our biological understanding and help identify components with translational potential for guiding diagnosis and treatment decisions. With the ongoing technical development, proteomics will likely continue to provide increasing insights into complex biological processes and their implications for health and disease. Integrating proteomics with other omics data and utilizing multi-omics approaches have been demonstrated to give additional valuable insights into biological systems.
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Affiliation(s)
- Tue Bjerg Bennike
- Medical Microbiology and Immunology, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
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22
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Zhang B, Bassani-Sternberg M. Current perspectives on mass spectrometry-based immunopeptidomics: the computational angle to tumor antigen discovery. J Immunother Cancer 2023; 11:e007073. [PMID: 37899131 PMCID: PMC10619091 DOI: 10.1136/jitc-2023-007073] [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] [Accepted: 07/21/2023] [Indexed: 10/31/2023] Open
Abstract
Identification of tumor antigens presented by the human leucocyte antigen (HLA) molecules is essential for the design of effective and safe cancer immunotherapies that rely on T cell recognition and killing of tumor cells. Mass spectrometry (MS)-based immunopeptidomics enables high-throughput, direct identification of HLA-bound peptides from a variety of cell lines, tumor tissues, and healthy tissues. It involves immunoaffinity purification of HLA complexes followed by MS profiling of the extracted peptides using data-dependent acquisition, data-independent acquisition, or targeted approaches. By incorporating DNA, RNA, and ribosome sequencing data into immunopeptidomics data analysis, the proteogenomic approach provides a powerful means for identifying tumor antigens encoded within the canonical open reading frames of annotated coding genes and non-canonical tumor antigens derived from presumably non-coding regions of our genome. We discuss emerging computational challenges in immunopeptidomics data analysis and tumor antigen identification, highlighting key considerations in the proteogenomics-based approach, including accurate DNA, RNA and ribosomal sequencing data analysis, careful incorporation of predicted novel protein sequences into reference protein database, special quality control in MS data analysis due to the expanded and heterogeneous search space, cancer-specificity determination, and immunogenicity prediction. The advancements in technology and computation is continually enabling us to identify tumor antigens with higher sensitivity and accuracy, paving the way toward the development of more effective cancer immunotherapies.
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Affiliation(s)
- Bing Zhang
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | - Michal Bassani-Sternberg
- Ludwig Institute for Cancer Research, University of Lausanne, Lausanne, Switzerland
- Department of Oncology, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
- Agora Cancer Research Centre, Lausanne, Switzerland
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23
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Teunissen CE, Kimble L, Bayoumy S, Bolsewig K, Burtscher F, Coppens S, Das S, Gogishvili D, Fernandes Gomes B, Gómez de San José N, Mavrina E, Meda FJ, Mohaupt P, Mravinacová S, Waury K, Wojdała AL, Abeln S, Chiasserini D, Hirtz C, Gaetani L, Vermunt L, Bellomo G, Halbgebauer S, Lehmann S, Månberg A, Nilsson P, Otto M, Vanmechelen E, Verberk IMW, Willemse E, Zetterberg H. Methods to Discover and Validate Biofluid-Based Biomarkers in Neurodegenerative Dementias. Mol Cell Proteomics 2023; 22:100629. [PMID: 37557955 PMCID: PMC10594029 DOI: 10.1016/j.mcpro.2023.100629] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 07/24/2023] [Accepted: 07/31/2023] [Indexed: 08/11/2023] Open
Abstract
Neurodegenerative dementias are progressive diseases that cause neuronal network breakdown in different brain regions often because of accumulation of misfolded proteins in the brain extracellular matrix, such as amyloids or inside neurons or other cell types of the brain. Several diagnostic protein biomarkers in body fluids are being used and implemented, such as for Alzheimer's disease. However, there is still a lack of biomarkers for co-pathologies and other causes of dementia. Such biofluid-based biomarkers enable precision medicine approaches for diagnosis and treatment, allow to learn more about underlying disease processes, and facilitate the development of patient inclusion and evaluation tools in clinical trials. When designing studies to discover novel biofluid-based biomarkers, choice of technology is an important starting point. But there are so many technologies to choose among. To address this, we here review the technologies that are currently available in research settings and, in some cases, in clinical laboratory practice. This presents a form of lexicon on each technology addressing its use in research and clinics, its strengths and limitations, and a future perspective.
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Affiliation(s)
- Charlotte E Teunissen
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands.
| | - Leighann Kimble
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; KIN Center for Digital Innovation, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Sherif Bayoumy
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Katharina Bolsewig
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Felicia Burtscher
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Salomé Coppens
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; National Measurement Laboratory at LGC, Teddington, United Kingdom
| | - Shreyasee Das
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; ADx NeuroSciences, Gent, Belgium
| | - Dea Gogishvili
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Bárbara Fernandes Gomes
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Nerea Gómez de San José
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Neurology, University of Ulm, Ulm, Germany
| | - Ekaterina Mavrina
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; KIN Center for Digital Innovation, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Francisco J Meda
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Pablo Mohaupt
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; LBPC-PPC, IRMB CHU Montpellier, INM INSERM, Université de Montpellier, Montpellier, France
| | - Sára Mravinacová
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
| | - Katharina Waury
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Anna Lidia Wojdała
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Sanne Abeln
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Davide Chiasserini
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Section of Physiology and Biochemistry, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Christophe Hirtz
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; LBPC-PPC, IRMB CHU Montpellier, INM INSERM, Université de Montpellier, Montpellier, France
| | - Lorenzo Gaetani
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Lisa Vermunt
- Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Giovanni Bellomo
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Steffen Halbgebauer
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Neurology, University of Ulm, Ulm, Germany; German Center for Neurodegenerative Diseases (DZNE e.V.), Ulm, Germany
| | - Sylvain Lehmann
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; LBPC-PPC, IRMB CHU Montpellier, INM INSERM, Université de Montpellier, Montpellier, France
| | - Anna Månberg
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
| | - Peter Nilsson
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
| | - Markus Otto
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Neurology, University of Ulm, Ulm, Germany; Department of Neurology, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Eugeen Vanmechelen
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; ADx NeuroSciences, Gent, Belgium
| | - Inge M W Verberk
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Eline Willemse
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Henrik Zetterberg
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK; UK Dementia Research Institute at UCL, London, UK; Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
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24
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Buljan M, Banaei-Esfahani A, Blattmann P, Meier-Abt F, Shao W, Vitek O, Tang H, Aebersold R. A computational framework for the inference of protein complex remodeling from whole-proteome measurements. Nat Methods 2023; 20:1523-1529. [PMID: 37749212 PMCID: PMC10555833 DOI: 10.1038/s41592-023-02011-w] [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: 12/30/2020] [Accepted: 08/16/2023] [Indexed: 09/27/2023]
Abstract
Protein complexes are responsible for the enactment of most cellular functions. For the protein complex to form and function, its subunits often need to be present at defined quantitative ratios. Typically, global changes in protein complex composition are assessed with experimental approaches that tend to be time consuming. Here, we have developed a computational algorithm for the detection of altered protein complexes based on the systematic assessment of subunit ratios from quantitative proteomic measurements. We applied it to measurements from breast cancer cell lines and patient biopsies and were able to identify strong remodeling of HDAC2 epigenetic complexes in more aggressive forms of cancer. The presented algorithm is available as an R package and enables the inference of changes in protein complex states by extracting functionally relevant information from bottom-up proteomic datasets.
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Affiliation(s)
- Marija Buljan
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
- EMPA, Swiss Federal Laboratories for Materials Science and Technology, St Gallen, Switzerland.
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
| | - Amir Banaei-Esfahani
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
- Department of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland
| | - Peter Blattmann
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
- Idorsia Pharmaceuticals, Allschwil, Switzerland
| | - Fabienne Meier-Abt
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
- Department of Medical Oncology and Hematology, University and University Hospital Zurich, Zurich, Switzerland
- Institute of Medical Genetics, University of Zurich, Zurich, Switzerland
| | - Wenguang Shao
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
- State Key Laboratory of Microbial Metabolism, School of Life Science & Biotechnology, and Joint International Research Laboratory of Metabolic & Developmental Sciences, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Olga Vitek
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA
| | - Hua Tang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - 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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25
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Zhang F, Ge W, Huang L, Li D, Liu L, Dong Z, Xu L, Ding X, Zhang C, Sun Y, A J, Gao J, Guo T. A Comparative Analysis of Data Analysis Tools for Data-Independent Acquisition Mass Spectrometry. Mol Cell Proteomics 2023; 22:100623. [PMID: 37481071 PMCID: PMC10458344 DOI: 10.1016/j.mcpro.2023.100623] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 06/12/2023] [Accepted: 07/18/2023] [Indexed: 07/24/2023] Open
Abstract
Data-independent acquisition (DIA) mass spectrometry-based proteomics generates reproducible proteome data. The complex processing of the DIA data has led to the development of multiple data analysis tools. In this study, we assessed the performance of five tools (OpenSWATH, EncyclopeDIA, Skyline, DIA-NN, and Spectronaut) using six DIA datasets obtained from TripleTOF, Orbitrap, and TimsTOF Pro instruments. By comparing identification and quantification metrics and examining shared and unique cross-tool identifications, we evaluated both library-based and library-free approaches. Our findings indicate that library-free approaches outperformed library-based methods when the spectral library had limited comprehensiveness. However, our results also suggest that constructing a comprehensive library still offers benefits for most DIA analyses. This study provides comprehensive guidance for DIA data analysis tools, benefiting both experienced and novice users of DIA-mass spectrometry technology.
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Affiliation(s)
- Fangfei Zhang
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China.
| | - Weigang Ge
- Westlake Omics, Ltd, Hangzhou, Zhejiang Province, China
| | | | - Dan Li
- Westlake Omics, Ltd, Hangzhou, Zhejiang Province, China
| | - Lijuan Liu
- Westlake Omics, Ltd, Hangzhou, Zhejiang Province, China
| | - Zhen Dong
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
| | - Luang Xu
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
| | - Xuan Ding
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
| | - Cheng Zhang
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
| | - Yingying Sun
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
| | - Jun A
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
| | - Jinlong Gao
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
| | - Tiannan Guo
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China.
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26
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George AL, Sidgwick FR, Watt JE, Martin MP, Trost M, Marín-Rubio JL, Dueñas ME. Comparison of Quantitative Mass Spectrometric Methods for Drug Target Identification by Thermal Proteome Profiling. J Proteome Res 2023; 22:2629-2640. [PMID: 37439223 PMCID: PMC10407934 DOI: 10.1021/acs.jproteome.3c00111] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Indexed: 07/14/2023]
Abstract
Thermal proteome profiling (TPP) provides a powerful approach to studying proteome-wide interactions of small therapeutic molecules and their target and off-target proteins, complementing phenotypic-based drug screens. Detecting differences in thermal stability due to target engagement requires high quantitative accuracy and consistent detection. Isobaric tandem mass tags (TMTs) are used to multiplex samples and increase quantification precision in TPP analysis by data-dependent acquisition (DDA). However, advances in data-independent acquisition (DIA) can provide higher sensitivity and protein coverage with reduced costs and sample preparation steps. Herein, we explored the performance of different DIA-based label-free quantification approaches compared to TMT-DDA for thermal shift quantitation. Acute myeloid leukemia cells were treated with losmapimod, a known inhibitor of MAPK14 (p38α). Label-free DIA approaches, and particularly the library-free mode in DIA-NN, were comparable of TMT-DDA in their ability to detect target engagement of losmapimod with MAPK14 and one of its downstream targets, MAPKAPK3. Using DIA for thermal shift quantitation is a cost-effective alternative to labeled quantitation in the TPP pipeline.
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Affiliation(s)
- Amy L. George
- Laboratory
for Biological Mass Spectrometry, Biosciences Institute, Newcastle University, Newcastle-upon-Tyne NE2 4HH, U.K.
| | - Frances R. Sidgwick
- Laboratory
for Biological Mass Spectrometry, Biosciences Institute, Newcastle University, Newcastle-upon-Tyne NE2 4HH, U.K.
| | - Jessica E. Watt
- Newcastle
Cancer Centre, Northern Institute for Cancer Research, Medical School, Newcastle University, Paul O’Gorman Building, Framlington Place, Newcastle upon Tyne NE2 4HH, U.K.
| | - Mathew P. Martin
- Newcastle
Cancer Centre, Northern Institute for Cancer Research, Medical School, Newcastle University, Paul O’Gorman Building, Framlington Place, Newcastle upon Tyne NE2 4HH, U.K.
| | - Matthias Trost
- Laboratory
for Biological Mass Spectrometry, Biosciences Institute, Newcastle University, Newcastle-upon-Tyne NE2 4HH, U.K.
| | - José Luis Marín-Rubio
- Laboratory
for Biological Mass Spectrometry, Biosciences Institute, Newcastle University, Newcastle-upon-Tyne NE2 4HH, U.K.
| | - Maria Emilia Dueñas
- Laboratory
for Biological Mass Spectrometry, Biosciences Institute, Newcastle University, Newcastle-upon-Tyne NE2 4HH, U.K.
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27
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Mehta S, Bernt M, Chambers M, Fahrner M, Föll MC, Gruening B, Horro C, Johnson JE, Loux V, Rajczewski AT, Schilling O, Vandenbrouck Y, Gustafsson OJR, Thang WCM, Hyde C, Price G, Jagtap PD, Griffin TJ. A Galaxy of informatics resources for MS-based proteomics. Expert Rev Proteomics 2023; 20:251-266. [PMID: 37787106 DOI: 10.1080/14789450.2023.2265062] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 09/06/2023] [Indexed: 10/04/2023]
Abstract
INTRODUCTION Continuous advances in mass spectrometry (MS) technologies have enabled deeper and more reproducible proteome characterization and a better understanding of biological systems when integrated with other 'omics data. Bioinformatic resources meeting the analysis requirements of increasingly complex MS-based proteomic data and associated multi-omic data are critically needed. These requirements included availability of software that would span diverse types of analyses, scalability for large-scale, compute-intensive applications, and mechanisms to ease adoption of the software. AREAS COVERED The Galaxy ecosystem meets these requirements by offering a multitude of open-source tools for MS-based proteomics analyses and applications, all in an adaptable, scalable, and accessible computing environment. A thriving global community maintains these software and associated training resources to empower researcher-driven analyses. EXPERT OPINION The community-supported Galaxy ecosystem remains a crucial contributor to basic biological and clinical studies using MS-based proteomics. In addition to the current status of Galaxy-based resources, we describe ongoing developments for meeting emerging challenges in MS-based proteomic informatics. We hope this review will catalyze increased use of Galaxy by researchers employing MS-based proteomics and inspire software developers to join the community and implement new tools, workflows, and associated training content that will add further value to this already rich ecosystem.
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Affiliation(s)
- Subina Mehta
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
| | - Matthias Bernt
- Helmholtz Centre for Environmental Research - UFZ, Department Computational Biology, Leipzig, Germany
| | | | - Matthias Fahrner
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Melanie Christine Föll
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA
| | - Bjoern Gruening
- Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Freiburg, Germany
| | - Carlos Horro
- Proteomics Unit, Department of Biomedicine, University of Bergen, Bergen, Norway
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - James E Johnson
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN, USA
| | - Valentin Loux
- Université Paris-Saclay, INRAE, MaIAGE, Jouy-en-Josas, France
- Université Paris-Saclay, INRAE, BioinfOmics, MIGALE bioinformatics facility, Jouy-en-Josas, France
| | - Andrew T Rajczewski
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
| | - Oliver Schilling
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | | | - W C Mike Thang
- Queensland Cyber Infrastructure Foundation (QCIF), Australia
- Institute of Molecular Bioscience, University of Queensland, St Lucia, Australia
| | - Cameron Hyde
- Queensland Cyber Infrastructure Foundation (QCIF), Australia
- Sippy Downs, University of the Sunshine Coast, Australia
| | - Gareth Price
- Queensland Cyber Infrastructure Foundation (QCIF), Australia
- Institute of Molecular Bioscience, University of Queensland, St Lucia, Australia
| | - Pratik D Jagtap
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
| | - Timothy J Griffin
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, MN, USA
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Babu M, Snyder M. Multi-Omics Profiling for Health. Mol Cell Proteomics 2023; 22:100561. [PMID: 37119971 PMCID: PMC10220275 DOI: 10.1016/j.mcpro.2023.100561] [Citation(s) in RCA: 36] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 04/20/2023] [Accepted: 04/23/2023] [Indexed: 05/01/2023] Open
Abstract
The world has witnessed a steady rise in both non-infectious and infectious chronic diseases, prompting a cross-disciplinary approach to understand and treating disease. Current medical care focuses on treating people after they become patients rather than preventing illness, leading to high costs in treating chronic and late-stage diseases. Additionally, a "one-size-fits all" approach to health care does not take into account individual differences in genetics, environment, or lifestyle factors, decreasing the number of people benefiting from interventions. Rapid advances in omics technologies and progress in computational capabilities have led to the development of multi-omics deep phenotyping, which profiles the interaction of multiple levels of biology over time and empowers precision health approaches. This review highlights current and emerging multi-omics modalities for precision health and discusses applications in the following areas: genetic variation, cardio-metabolic diseases, cancer, infectious diseases, organ transplantation, pregnancy, and longevity/aging. We will briefly discuss the potential of multi-omics approaches in disentangling host-microbe and host-environmental interactions. We will touch on emerging areas of electronic health record and clinical imaging integration with muti-omics for precision health. Finally, we will briefly discuss the challenges in the clinical implementation of multi-omics and its future prospects.
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Affiliation(s)
- Mohan Babu
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Michael Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA.
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29
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Zhao J, Yang Y, Teng M, Zheng J, Wang B, Mallawaarachchi V, Lin Y, Fang Z, Shen C, Yu S, Yang F, Qiao L, Wang L. Metaproteomics profiling of the microbial communities in fermentation starters ( Daqu) during multi-round production of Chinese liquor. Front Nutr 2023; 10:1139836. [PMID: 37324728 PMCID: PMC10267310 DOI: 10.3389/fnut.2023.1139836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Accepted: 05/09/2023] [Indexed: 06/17/2023] Open
Abstract
Introduction The special flavor and fragrance of Chinese liquor are closely related to microorganisms in the fermentation starter Daqu. The changes of microbial community can affect the stability of liquor yield and quality. Methods In this study, we used data-independent acquisition mass spectrometry (DIA-MS) for cohort study of the microbial communities of a total of 42 Daqu samples in six production cycles at different times of a year. The DIA MS data were searched against a protein database constructed by metagenomic sequencing. Results The microbial composition and its changes across production cycles were revealed. Functional analysis of the differential proteins was carried out and the metabolic pathways related to the differential proteins were explored. These metabolic pathways were related to the saccharification process in liquor fermentation and the synthesis of secondary metabolites to form the unique flavor and aroma in the Chinese liquor. Discussion We expect that the metaproteome profiling of Daqu from different production cycles will serve as a guide for the control of fermentation process of Chinese liquor in the future.
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Affiliation(s)
- Jinzhi Zhao
- Kweichow Moutai Group, Renhuai, Guizhou, China
- Department of Chemistry, Fudan University, Shanghai, China
| | - Yi Yang
- Department of Chemistry, Fudan University, Shanghai, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | | | | | - Bing Wang
- College of Food Science and Technology, Shanghai Ocean University, Shanghai, China
| | - Vijini Mallawaarachchi
- College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia
- Flinders Accelerator for Microbiome Exploration, Flinders University, Bedford Park, SA, Australia
| | - Yu Lin
- College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia
| | - Ziyu Fang
- Department of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute, Troy, NY, United States
| | | | - Shaoning Yu
- Zhejiang Provincial Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis, Institute of Mass Spectrometry, School of Material Science and Chemical Engineering, Ningbo University, Ningbo, Zhejiang, China
| | - Fan Yang
- Kweichow Moutai Group, Renhuai, Guizhou, China
| | - Liang Qiao
- Department of Chemistry, Fudan University, Shanghai, China
| | - Li Wang
- Kweichow Moutai Group, Renhuai, Guizhou, China
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30
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Zong Y, Wang Y, Yang Y, Zhao D, Wang X, Shen C, Qiao L. DeepFLR facilitates false localization rate control in phosphoproteomics. Nat Commun 2023; 14:2269. [PMID: 37080984 PMCID: PMC10119288 DOI: 10.1038/s41467-023-38035-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 04/06/2023] [Indexed: 04/22/2023] Open
Abstract
Protein phosphorylation is a post-translational modification crucial for many cellular processes and protein functions. Accurate identification and quantification of protein phosphosites at the proteome-wide level are challenging, not least because efficient tools for protein phosphosite false localization rate (FLR) control are lacking. Here, we propose DeepFLR, a deep learning-based framework for controlling the FLR in phosphoproteomics. DeepFLR includes a phosphopeptide tandem mass spectrum (MS/MS) prediction module based on deep learning and an FLR assessment module based on a target-decoy approach. DeepFLR improves the accuracy of phosphopeptide MS/MS prediction compared to existing tools. Furthermore, DeepFLR estimates FLR accurately for both synthetic and biological datasets, and localizes more phosphosites than probability-based methods. DeepFLR is compatible with data from different organisms, instruments types, and both data-dependent and data-independent acquisition approaches, thus enabling FLR estimation for a broad range of phosphoproteomics experiments.
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Affiliation(s)
- Yu Zong
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, China
| | - Yuxin Wang
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, China
- Department of Computer Science, and Institute of Modern Languages and Linguistics, Fudan University, Shanghai, China
| | - Yi Yang
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, China
| | - Dan Zhao
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, China
| | | | | | - Liang Qiao
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, China.
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31
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Kedia-Mehta N, Pisarska MM, Rollings C, O'Neill C, De Barra C, Foley C, Wood NAW, Wrigley-Kelly N, Veerapen N, Besra G, Bergin R, Jones N, O'Shea D, Sinclair LV, Hogan AE. The proliferation of human mucosal-associated invariant T cells requires a MYC-SLC7A5-glycolysis metabolic axis. Sci Signal 2023; 16:eabo2709. [PMID: 37071733 DOI: 10.1126/scisignal.abo2709] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2023]
Abstract
Mucosal-associated invariant T (MAIT) cells are an abundant population of innate T cells that recognize bacterial ligands and play a key role in host protection against bacterial and viral pathogens. Upon activation, MAIT cells undergo proliferative expansion and increase their production of effector molecules such as cytokines. In this study, we found that both mRNA and protein abundance of the key metabolism regulator and transcription factor MYC was increased in stimulated MAIT cells. Using quantitative mass spectrometry, we identified the activation of two MYC-controlled metabolic pathways, amino acid transport and glycolysis, both of which were necessary for MAIT cell proliferation. Last, we showed that MAIT cells isolated from people with obesity showed decreased MYC mRNA abundance upon activation, which was associated with defective MAIT cell proliferation and functional responses. Collectively, our data uncover the importance of MYC-regulated metabolism for MAIT cell proliferation and provide additional insight into the molecular basis for the functional defects of MAIT cells in obesity.
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Affiliation(s)
- Nidhi Kedia-Mehta
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, Maynooth, Co Kildare, Ireland
| | - Marta M Pisarska
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, Maynooth, Co Kildare, Ireland
- National Children's Research Centre, Dublin 12, Ireland
| | - Christina Rollings
- Division of Cell Signaling and Immunology, School of Life Sciences, University of Dundee, Dundee, UK
| | - Chloe O'Neill
- National Children's Research Centre, Dublin 12, Ireland
| | | | - Cathriona Foley
- Department of Biological Sciences, Munster Technological University, Cork, Ireland
| | - Nicole A W Wood
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, Maynooth, Co Kildare, Ireland
- National Children's Research Centre, Dublin 12, Ireland
| | - Neil Wrigley-Kelly
- St. Vincent's University Hospital, Dublin 4, Ireland
- University College Dublin, Dublin 4, Ireland
| | | | - Gurdyal Besra
- School of Biosciences, University of Birmingham, Birmingham, UK
| | - Ronan Bergin
- National Children's Research Centre, Dublin 12, Ireland
| | - Nicholas Jones
- Institute of Life Science, Swansea University Medical School, Swansea, UK
| | - Donal O'Shea
- National Children's Research Centre, Dublin 12, Ireland
- St. Vincent's University Hospital, Dublin 4, Ireland
- University College Dublin, Dublin 4, Ireland
| | - Linda V Sinclair
- Division of Cell Signaling and Immunology, School of Life Sciences, University of Dundee, Dundee, UK
| | - Andrew E Hogan
- Kathleen Lonsdale Institute for Human Health Research, Maynooth University, Maynooth, Co Kildare, Ireland
- National Children's Research Centre, Dublin 12, Ireland
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32
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Messner CB, Demichev V, Wang Z, Hartl J, Kustatscher G, Mülleder M, Ralser M. Mass spectrometry-based high-throughput proteomics and its role in biomedical studies and systems biology. Proteomics 2023; 23:e2200013. [PMID: 36349817 DOI: 10.1002/pmic.202200013] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 10/13/2022] [Accepted: 10/13/2022] [Indexed: 11/11/2022]
Abstract
There are multiple reasons why the next generation of biological and medical studies require increasing numbers of samples. Biological systems are dynamic, and the effect of a perturbation depends on the genetic background and environment. As a consequence, many conditions need to be considered to reach generalizable conclusions. Moreover, human population and clinical studies only reach sufficient statistical power if conducted at scale and with precise measurement methods. Finally, many proteins remain without sufficient functional annotations, because they have not been systematically studied under a broad range of conditions. In this review, we discuss the latest technical developments in mass spectrometry (MS)-based proteomics that facilitate large-scale studies by fast and efficient chromatography, fast scanning mass spectrometers, data-independent acquisition (DIA), and new software. We further highlight recent studies which demonstrate how high-throughput (HT) proteomics can be applied to capture biological diversity, to annotate gene functions or to generate predictive and prognostic models for human diseases.
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Affiliation(s)
- Christoph B Messner
- Precision Proteomics Center, Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland
| | - Vadim Demichev
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Ziyue Wang
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Johannes Hartl
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Georg Kustatscher
- Wellcome Centre for Cell Biology, University of Edinburgh, Max Born Crescent, Edinburgh, Scotland, UK
| | - Michael Mülleder
- Core Facility High Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Markus Ralser
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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33
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Boekweg H, Payne SH. Challenges and Opportunities for Single-cell Computational Proteomics. Mol Cell Proteomics 2023; 22:100518. [PMID: 36828128 PMCID: PMC10060113 DOI: 10.1016/j.mcpro.2023.100518] [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: 12/07/2022] [Revised: 02/15/2023] [Accepted: 02/17/2023] [Indexed: 02/25/2023] Open
Abstract
Single-cell proteomics is growing rapidly and has made several technological advancements. As most research has been focused on improving instrumentation and sample preparation methods, very little attention has been given to algorithms responsible for identifying and quantifying proteins. Given the inherent difference between bulk data and single-cell data, it is necessary to realize that current algorithms being employed on single-cell data were designed for bulk data and have underlying assumptions that may not hold true for single-cell data. In order to develop and optimize algorithms for single-cell data, we need to characterize the differences between single-cell data and bulk data and assess how current algorithms perform on single-cell data. Here, we present a review of algorithms responsible for identifying and quantifying peptides and proteins. We will give a review of how each type of algorithm works, assumptions it relies on, how it performs on single-cell data, and possible optimizations and solutions that could be used to address the differences in single-cell data.
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Affiliation(s)
- Hannah Boekweg
- Biology Department, Brigham Young University, Provo, Utah, USA
| | - Samuel H Payne
- Biology Department, Brigham Young University, Provo, Utah, USA.
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Arora D, Hackenberg Y, Li J, Winter D. Updates on the study of lysosomal protein dynamics: possibilities for the clinic. Expert Rev Proteomics 2023; 20:47-55. [PMID: 36919490 DOI: 10.1080/14789450.2023.2190515] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
INTRODUCTION The lysosome is the main degradative organelle of almost all mammalian cells, fulfilling important functions in macromolecule recycling, metabolism, and signaling. Lysosomal dysfunction is connected to a continuously growing number of pathologic conditions, and lysosomal proteins present potential biomarkers for a variety of diseases. Therefore, there is an increasing interest in their analysis in patient samples. AREAS COVERED We provide an overview of OMICs studies which identified lysosomal proteins as potential biomarkers for pathological conditions, covering proteomics, genomics, and transcriptomics approaches, identified through PubMed searches. With respect to discovery proteomics analyses, mainly lysosomal luminal and associated proteins were detected, while membrane proteins were found less frequently. Comprehensive coverage of the lysosomal proteome was only achieved by ultra-deep-coverage studies, but targeted approaches allowed for the reproducible quantification of lysosomal proteins in diverse sample types. EXPERT OPINION The low abundance of lysosomal proteins complicates their reproducible analysis in patient samples. Whole proteome shotgun analyses fail in many instances to cover the lysosomal proteome, which is due to under-sampling and/or a lack of sensitivity. With the current state of the art, targeted proteomics assays provide the best performance for the characterization of lysosomal proteins in patient samples.
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Affiliation(s)
- Dhriti Arora
- Institute for Biochemistry and Molecular Biology, Medical Faculty, University of Bonn, Bonn, Germany
| | - Yannic Hackenberg
- Institute for Biochemistry and Molecular Biology, Medical Faculty, University of Bonn, Bonn, Germany
| | - Jiaran Li
- Institute for Biochemistry and Molecular Biology, Medical Faculty, University of Bonn, Bonn, Germany
| | - Dominic Winter
- Institute for Biochemistry and Molecular Biology, Medical Faculty, University of Bonn, Bonn, Germany
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35
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Hodge SH, Krauss MZ, Kaymak I, King JI, Howden AJ, Panic G, Grencis RK, Swann JR, Sinclair LV, Hepworth MR. Amino acid availability acts as a metabolic rheostat to determine the magnitude of ILC2 responses. J Exp Med 2023; 220:e20221073. [PMID: 36571761 PMCID: PMC9794837 DOI: 10.1084/jem.20221073] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 11/15/2022] [Accepted: 12/16/2022] [Indexed: 12/27/2022] Open
Abstract
Group 2 innate lymphoid cells (ILC2) are functionally poised, tissue-resident lymphocytes that respond rapidly to damage and infection at mucosal barrier sites. ILC2 reside within complex microenvironments where they are subject to cues from both the diet and invading pathogens-including helminths. Emerging evidence suggests ILC2 are acutely sensitive not only to canonical activating signals but also perturbations in nutrient availability. In the context of helminth infection, we identify amino acid availability as a nutritional cue in regulating ILC2 responses. ILC2 are found to be uniquely preprimed to import amino acids via the large neutral amino acid transporters Slc7a5 and Slc7a8. Cell-intrinsic deletion of these transporters individually impaired ILC2 expansion, while concurrent loss of both transporters markedly impaired the proliferative and cytokine-producing capacity of ILC2. Mechanistically, amino acid uptake determined the magnitude of ILC2 responses in part via tuning of mTOR. These findings implicate essential amino acids as a metabolic requisite for optimal ILC2 responses within mucosal barrier tissues.
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Affiliation(s)
- Suzanne H. Hodge
- Lydia Becker Institute of Immunology and Inflammation, University of Manchester, Manchester, UK
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Maria Z. Krauss
- Lydia Becker Institute of Immunology and Inflammation, University of Manchester, Manchester, UK
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Irem Kaymak
- Lydia Becker Institute of Immunology and Inflammation, University of Manchester, Manchester, UK
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - James I. King
- Lydia Becker Institute of Immunology and Inflammation, University of Manchester, Manchester, UK
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Andrew J.M. Howden
- Cell Signalling and Immunology Division, School of Life Sciences, University of Dundee, Dundee, UK
| | - Gordana Panic
- Division of Integrative Systems Medicine and Digestive Diseases, Imperial College London, South Kensington, UK
- School of Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Richard K. Grencis
- Lydia Becker Institute of Immunology and Inflammation, University of Manchester, Manchester, UK
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
| | - Jonathan R. Swann
- Division of Integrative Systems Medicine and Digestive Diseases, Imperial College London, South Kensington, UK
- School of Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Linda V. Sinclair
- Cell Signalling and Immunology Division, School of Life Sciences, University of Dundee, Dundee, UK
| | - Matthew R. Hepworth
- Lydia Becker Institute of Immunology and Inflammation, University of Manchester, Manchester, UK
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
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36
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Qureshi HA, Azimi A, Wells J, Fernandez-Penas P. Tape stripped stratum corneum samples are suitable for diagnosis and comprehensive proteomic investigation in mycosis fungoides. Proteomics Clin Appl 2023; 17:e2200039. [PMID: 36824058 DOI: 10.1002/prca.202200039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 01/19/2023] [Accepted: 02/17/2023] [Indexed: 02/25/2023]
Abstract
BACKGROUND Mycosis Fungoides (MF) is a common cutaneous T-cell lymphoma. It can sometimes be challenging to diagnose MF using current clinico-histopathological criteria. Non-invasive molecular profiling analysis has the potential to aid the diagnosis and understanding of MF. METHOD Lesional and body site matched normal stratum corneum samples were obtained from the same MF patients (n = 28) using adhesive discs, followed by proteomic analyses using data-independent acquisition mass spectrometry (DIA-MS). Differential abundance analyses and bioinformatic analyses were performed to identify differentially abundant proteins and altered biofunctions between the MF and normal stratum corneum samples. RESULTS In total, 1303 proteins were identified, of which 290 proteins were significantly changed in the MF cohort compared to the normal stratum corneum. Ingenuity pathway analysis (IPA) predicted the significant inhibition of cell death of cancer cells and significant activation of immune-related activities and viral infection in the MF lesions. MF lesions were also associated with upstream regulators relating to immuno-oncologic dysfunctions. The top-250 variating proteins efficiently separated normal stratum corneum from matched MF samples. CONCLUSION Non-invasive proteomic analysis could transform the diagnosis of MF by reducing the need for invasive biopsy. The identification of altered biological functions may serve as useful biomarkers to predict MF progression.
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Affiliation(s)
- Hafsa Anees Qureshi
- Department of Dermatology, Westmead Hospital, Westmead, New South Wales, Australia
- Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
| | - Ali Azimi
- Department of Dermatology, Westmead Hospital, Westmead, New South Wales, Australia
- Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
| | - Jillian Wells
- Department of Dermatology, Westmead Hospital, Westmead, New South Wales, Australia
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
| | - Pablo Fernandez-Penas
- Department of Dermatology, Westmead Hospital, Westmead, New South Wales, Australia
- Centre for Cancer Research, The Westmead Institute for Medical Research, The University of Sydney, Westmead, New South Wales, Australia
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Westmead, New South Wales, Australia
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37
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Wiskott K, Gilardi F, Hainard A, Sanchez JC, Thomas A, Sajic T, Fracasso T. Blood proteome of acute intracranial hemorrhage in infant victims of abusive head trauma. Proteomics 2023; 23:e2200078. [PMID: 36576318 DOI: 10.1002/pmic.202200078] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 12/02/2022] [Accepted: 12/19/2022] [Indexed: 12/29/2022]
Abstract
Abusive head trauma (AHT) is a leading cause of mortality and morbidity in infants. While the reported incidence is close to 40 cases per 100'000 births/year, misdiagnoses are commonly observed in cases with atypical, subacute, or chronic presentation. Currently, standard clinical evaluation of inflicted intracranial hemorrhagic injury (ICH) in infants urgently requires a screening test able to identify infants who need additional investigations. Blood biomarkers characteristic of AHT may assist in detecting these infants, improving prognosis through early medical care. To date, the application of innovative omics technologies in retrospective studies of AHT in infants is rare, due also to the blood serum and cerebrospinal fluid of AHT cases being scarce and not systematically accessible. Here, we explored the circulating blood proteomes of infants with severe AHT and their atraumatic controls. We discovered 165 circulating serum proteins that display differential changes in AHT cases compared with atraumatic controls. The peripheral blood proteomes of pediatric AHT commonly reflect: (i) potentially secreted proteome from injured brain, and (ii) proteome dysregulated in the system's circulation by successive biological events following acute ICH. This study opens up a novel opportunity for research efforts in clinical screening of AHT cases.
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Affiliation(s)
- Kim Wiskott
- Forensic medicine unit, University Center of Legal Medicine, Geneva 4, Switzerland
| | - Federica Gilardi
- Faculty Unit of Toxicology, University Center of Legal Medicine, Lausanne University Hospital, Lausanne 25, Switzerland.,Unit of Forensic Toxicology and Chemistry, CURML, Lausanne University Hospital and Geneva University Hospital, Geneva, Switzerland
| | - Alexandre Hainard
- Proteomics Core Facility, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Jean-Charles Sanchez
- Translational Biomarker Group, Department of Internal Medicine, University of Geneva, Geneva, Switzerland
| | - Aurelien Thomas
- Faculty Unit of Toxicology, University Center of Legal Medicine, Lausanne University Hospital, Lausanne 25, Switzerland.,Unit of Forensic Toxicology and Chemistry, CURML, Lausanne University Hospital and Geneva University Hospital, Geneva, Switzerland
| | - Tatjana Sajic
- Faculty Unit of Toxicology, University Center of Legal Medicine, Lausanne University Hospital, Lausanne 25, Switzerland.,Unit of Forensic Toxicology and Chemistry, CURML, Lausanne University Hospital and Geneva University Hospital, Geneva, Switzerland
| | - Tony Fracasso
- Forensic medicine unit, University Center of Legal Medicine, Geneva 4, Switzerland
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38
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Zhao J, Yang Y, Xu H, Zheng J, Shen C, Chen T, Wang T, Wang B, Yi J, Zhao D, Wu E, Qin Q, Xia L, Qiao L. Data-independent acquisition boosts quantitative metaproteomics for deep characterization of gut microbiota. NPJ Biofilms Microbiomes 2023; 9:4. [PMID: 36693863 PMCID: PMC9873935 DOI: 10.1038/s41522-023-00373-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 01/11/2023] [Indexed: 01/26/2023] Open
Abstract
Metaproteomics can provide valuable insights into the functions of human gut microbiota (GM), but is challenging due to the extreme complexity and heterogeneity of GM. Data-independent acquisition (DIA) mass spectrometry (MS) has been an emerging quantitative technique in conventional proteomics, but is still at the early stage of development in the field of metaproteomics. Herein, we applied library-free DIA (directDIA)-based metaproteomics and compared the directDIA with other MS-based quantification techniques for metaproteomics on simulated microbial communities and feces samples spiked with bacteria with known ratios, demonstrating the superior performance of directDIA by a comprehensive consideration of proteome coverage in identification as well as accuracy and precision in quantification. We characterized human GM in two cohorts of clinical fecal samples of pancreatic cancer (PC) and mild cognitive impairment (MCI). About 70,000 microbial proteins were quantified in each cohort and annotated to profile the taxonomic and functional characteristics of GM in different diseases. Our work demonstrated the utility of directDIA in quantitative metaproteomics for investigating intestinal microbiota and its related disease pathogenesis.
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Affiliation(s)
- Jinzhi Zhao
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China
| | - Yi Yang
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, 311200, Hangzhou, China
| | - Hua Xu
- Department of Core Facility of Basic Medical Sciences, and Department of Psychiatry of Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, 200000, Shanghai, China
| | - Jianxujie Zheng
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China
| | - Chengpin Shen
- Shanghai Omicsolution Co., Ltd, 201100, Shanghai, China
| | - Tian Chen
- Changhai Hospital, The Naval Military Medical University, 200433, Shanghai, China
| | - Tao Wang
- Department of Core Facility of Basic Medical Sciences, and Department of Psychiatry of Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, 200000, Shanghai, China
| | - Bing Wang
- College of Food Science and Technology, Shanghai Ocean University, 201306, Shanghai, China
| | - Jia Yi
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China
| | - Dan Zhao
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China
| | - Enhui Wu
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China
| | - Qin Qin
- Changhai Hospital, The Naval Military Medical University, 200433, Shanghai, China.
| | - Li Xia
- Department of Core Facility of Basic Medical Sciences, and Department of Psychiatry of Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, 200000, Shanghai, China.
| | - Liang Qiao
- Department of Chemistry, Shanghai Stomatological Hospital, Fudan University, 200000, Shanghai, China.
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39
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Carrillo-Rodriguez P, Selheim F, Hernandez-Valladares M. Mass Spectrometry-Based Proteomics Workflows in Cancer Research: The Relevance of Choosing the Right Steps. Cancers (Basel) 2023; 15:555. [PMID: 36672506 PMCID: PMC9856946 DOI: 10.3390/cancers15020555] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 01/12/2023] [Indexed: 01/19/2023] Open
Abstract
The qualitative and quantitative evaluation of proteome changes that condition cancer development can be achieved with liquid chromatography-mass spectrometry (LC-MS). LC-MS-based proteomics strategies are carried out according to predesigned workflows that comprise several steps such as sample selection, sample processing including labeling, MS acquisition methods, statistical treatment, and bioinformatics to understand the biological meaning of the findings and set predictive classifiers. As the choice of best options might not be straightforward, we herein review and assess past and current proteomics approaches for the discovery of new cancer biomarkers. Moreover, we review major bioinformatics tools for interpreting and visualizing proteomics results and suggest the most popular machine learning techniques for the selection of predictive biomarkers. Finally, we consider the approximation of proteomics strategies for clinical diagnosis and prognosis by discussing current barriers and proposals to circumvent them.
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Affiliation(s)
- Paula Carrillo-Rodriguez
- Proteomics Unit of University of Bergen (PROBE), University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway
- Vall d’Hebron Institute of Oncology (VHIO), 08035 Barcelona, Spain
| | - Frode Selheim
- Proteomics Unit of University of Bergen (PROBE), University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway
| | - Maria Hernandez-Valladares
- Proteomics Unit of University of Bergen (PROBE), University of Bergen, Jonas Lies vei 91, 5009 Bergen, Norway
- Department of Physical Chemistry, University of Granada, Avenida de la Fuente Nueva S/N, 18071 Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, 18012 Granada, Spain
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40
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Zhao J, Yang Y, Chen L, Zheng J, Lv X, Li D, Fang Z, Shen C, Mallawaarachchi V, Lin Y, Yu S, Yang F, Wang L, Qiao L. Quantitative metaproteomics reveals composition and metabolism characteristics of microbial communities in Chinese liquor fermentation starters. Front Microbiol 2023; 13:1098268. [PMID: 36699582 PMCID: PMC9868298 DOI: 10.3389/fmicb.2022.1098268] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 12/12/2022] [Indexed: 01/11/2023] Open
Abstract
Introduction Daqu, the Chinese liquor fermentation starter, contains complex microbial communities that are important for the yield, quality, and unique flavor of produced liquor. However, the composition and metabolism of microbial communities in the different types of high-temperature Daqu (i.e., white, yellow, and black Daqu) have not been well understood. Methods Herein, we used quantitative metaproteomics based on data-independent acquisition (DIA) mass spectrometry to analyze a total of 90 samples of white, yellow, and black Daqu collected in spring, summer, and autumn, revealing the taxonomic and metabolic profiles of different types of Daqu across seasons. Results Taxonomic composition differences were explored across types of Daqu and seasons, where the under-fermented white Daqu showed the higher microbial diversity and seasonal stability. It was demonstrated that yellow Daqu had higher abundance of saccharifying enzymes for raw material degradation. In addition, considerable seasonal variation of microbial protein abundance was discovered in the over-fermented black Daqu, suggesting elevated carbohydrate and amino acid metabolism in autumn black Daqu. Discussion We expect that this study will facilitate the understanding of the key microbes and their metabolism in the traditional fermentation process of Chinese liquor production.
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Affiliation(s)
- Jinzhi Zhao
- Department of Chemistry and Shanghai Stomatological Hospital, Fudan University, Shanghai, China
| | - Yi Yang
- Department of Chemistry and Shanghai Stomatological Hospital, Fudan University, Shanghai, China
| | | | - Jianxujie Zheng
- Department of Chemistry and Shanghai Stomatological Hospital, Fudan University, Shanghai, China
| | - Xibin Lv
- Kweichow Moutai Group, Renhuai, Guizhou, China
| | - Dandan Li
- Department of Chemistry and Shanghai Stomatological Hospital, Fudan University, Shanghai, China
| | - Ziyu Fang
- Department of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute, Troy, NY, United States
| | | | - Vijini Mallawaarachchi
- College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia
| | - Yu Lin
- College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia
| | - Shaoning Yu
- Zhejiang Provincial Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis, Institute of Mass Spectrometry, School of Material Science and Chemical Engineering, Ningbo University, Ningbo, China
| | - Fan Yang
- Kweichow Moutai Group, Renhuai, Guizhou, China
| | - Li Wang
- Kweichow Moutai Group, Renhuai, Guizhou, China
| | - Liang Qiao
- Department of Chemistry and Shanghai Stomatological Hospital, Fudan University, Shanghai, China
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41
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Lou R, Cao Y, Li S, Lang X, Li Y, Zhang Y, Shui W. Benchmarking commonly used software suites and analysis workflows for DIA proteomics and phosphoproteomics. Nat Commun 2023; 14:94. [PMID: 36609502 PMCID: PMC9822986 DOI: 10.1038/s41467-022-35740-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 12/20/2022] [Indexed: 01/07/2023] Open
Abstract
A plethora of software suites and multiple classes of spectral libraries have been developed to enhance the depth and robustness of data-independent acquisition (DIA) data processing. However, how the combination of a DIA software tool and a spectral library impacts the outcome of DIA proteomics and phosphoproteomics data analysis has been rarely investigated using benchmark data that mimics biological complexity. In this study, we create DIA benchmark data sets simulating the regulation of thousands of proteins in a complex background, which are collected on both an Orbitrap and a timsTOF instruments. We evaluate four commonly used software suites (DIA-NN, Spectronaut, MaxDIA and Skyline) combined with seven different spectral libraries in global proteome analysis. Moreover, we assess their performances in analyzing phosphopeptide standards and TNF-α-induced phosphoproteome regulation. Our study provides a practical guidance on how to construct a robust data analysis pipeline for different proteomics studies implementing the DIA technique.
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Affiliation(s)
- Ronghui Lou
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ye Cao
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Shanshan Li
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China
| | - Xiaoyu Lang
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yunxia Li
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Yaoyang Zhang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
- Shanghai Key Laboratory of Aging Studies, 100 Haike Rd., Shanghai, 201210, China.
| | - Wenqing Shui
- iHuman Institute, ShanghaiTech University, Shanghai, 201210, China.
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
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42
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Lenčo J, Jadeja S, Naplekov DK, Krokhin OV, Khalikova MA, Chocholouš P, Urban J, Broeckhoven K, Nováková L, Švec F. Reversed-Phase Liquid Chromatography of Peptides for Bottom-Up Proteomics: A Tutorial. J Proteome Res 2022; 21:2846-2892. [PMID: 36355445 DOI: 10.1021/acs.jproteome.2c00407] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The performance of the current bottom-up liquid chromatography hyphenated with mass spectrometry (LC-MS) analyses has undoubtedly been fueled by spectacular progress in mass spectrometry. It is thus not surprising that the MS instrument attracts the most attention during LC-MS method development, whereas optimizing conditions for peptide separation using reversed-phase liquid chromatography (RPLC) remains somewhat in its shadow. Consequently, the wisdom of the fundaments of chromatography is slowly vanishing from some laboratories. However, the full potential of advanced MS instruments cannot be achieved without highly efficient RPLC. This is impossible to attain without understanding fundamental processes in the chromatographic system and the properties of peptides important for their chromatographic behavior. We wrote this tutorial intending to give practitioners an overview of critical aspects of peptide separation using RPLC to facilitate setting the LC parameters so that they can leverage the full capabilities of their MS instruments. After briefly introducing the gradient separation of peptides, we discuss their properties that affect the quality of LC-MS chromatograms the most. Next, we address the in-column and extra-column broadening. The last section is devoted to key parameters of LC-MS methods. We also extracted trends in practice from recent bottom-up proteomics studies and correlated them with the current knowledge on peptide RPLC separation.
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Affiliation(s)
- Juraj Lenčo
- Department of Analytical Chemistry, Faculty of Pharmacy in Hradec Králové, Charles University, Heyrovského 1203/8, 500 05Hradec Králové, Czech Republic
| | - Siddharth Jadeja
- Department of Analytical Chemistry, Faculty of Pharmacy in Hradec Králové, Charles University, Heyrovského 1203/8, 500 05Hradec Králové, Czech Republic
| | - Denis K Naplekov
- Department of Analytical Chemistry, Faculty of Pharmacy in Hradec Králové, Charles University, Heyrovského 1203/8, 500 05Hradec Králové, Czech Republic
| | - Oleg V Krokhin
- Department of Internal Medicine, Manitoba Centre for Proteomics and Systems Biology, University of Manitoba, 799 JBRC, 715 McDermot Avenue, WinnipegR3E 3P4, Manitoba, Canada
| | - Maria A Khalikova
- Department of Analytical Chemistry, Faculty of Pharmacy in Hradec Králové, Charles University, Heyrovského 1203/8, 500 05Hradec Králové, Czech Republic
| | - Petr Chocholouš
- Department of Analytical Chemistry, Faculty of Pharmacy in Hradec Králové, Charles University, Heyrovského 1203/8, 500 05Hradec Králové, Czech Republic
| | - Jiří Urban
- Department of Chemistry, Faculty of Science, Masaryk University, Kamenice 5, 625 00Brno, Czech Republic
| | - Ken Broeckhoven
- Department of Chemical Engineering (CHIS), Faculty of Engineering, Vrije Universiteit Brussel, Pleinlaan 2, 1050Brussel, Belgium
| | - Lucie Nováková
- Department of Analytical Chemistry, Faculty of Pharmacy in Hradec Králové, Charles University, Heyrovského 1203/8, 500 05Hradec Králové, Czech Republic
| | - František Švec
- Department of Analytical Chemistry, Faculty of Pharmacy in Hradec Králové, Charles University, Heyrovského 1203/8, 500 05Hradec Králové, Czech Republic
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43
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Stejskal K, Jeff ODB, Matzinger M, Dürnberger G, Boychenko A, Jacobs P, Mechtler K. Deep Proteome Profiling with Reduced Carryover Using Superficially Porous Microfabricated nanoLC Columns. Anal Chem 2022; 94:15930-15938. [PMID: 36356180 PMCID: PMC9685595 DOI: 10.1021/acs.analchem.2c01196] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
![]()
In the field of liquid chromatography–mass spectrometry
(LC–MS)-based proteomics, increases in the sampling depth and
proteome coverage have mainly been accomplished by rapid advances
in mass spectrometer technology. The comprehensiveness and quality
of the data that can be generated do, however, also depend on the
performance provided by nano-liquid chromatography (nanoLC) separations.
Proper selection of reversed-phase separation columns can be important
to provide the MS instrument with peptides at the highest possible
concentration and separated at the highest possible resolution. In
the current contribution, we evaluate the use of the prototype generation
2 μPAC nanoLC columns, which use C18-functionalized superficially
porous micropillars as a stationary phase. When compared to traditionally
used fully porous silica stationary phases, more precursors could
be characterized when performing single shot data-dependent LC–MS/MS
analyses of a human cell line tryptic digest. Up to 30% more protein
groups and 60% more unique peptides were identified for short gradients
(10 min) and limited sample amounts (10–100 ng of cell lysate
digest). With LC–MS gradient times of 10, 60, 120, and 180
min, respectively, we identified 2252, 6513, 7382, and 8174 protein
groups with 25, 500, 1000, and 2000 ng of the sample loaded on the
column. Reduction of sample carryover to the next run (up to 2 to
3%) and decreased levels of methionine oxidation (up to 3-fold) were
identified as additional figures of merit. When analyzing a disuccinimidyl
dibutyric urea-crosslinked synthetic library, 29 to 59 more unique
crosslinked peptides could be identified at an experimentally validated
false discovery rate of 1–2%.
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Affiliation(s)
- Karel Stejskal
- IMBA─Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Dr. Bohr Gasse 3, A-1030 Vienna, Austria
| | - Op de Beeck Jeff
- Thermo Fisher Scientific, Technologiepark-Zwijnaarde 82, B-9052 Gent, Belgium
| | - Manuel Matzinger
- IMP─Institute of Molecular Pathology, Campus-Vienna-Biocenter 1, A-1030 Vienna, Austria
| | - Gerhard Dürnberger
- Gregor Mendel Institute of Molecular Plant Biology of the Austrian Academy of Sciences, Dr. Bohr Gasse 3, A-1030 Vienna, Austria
| | | | - Paul Jacobs
- Thermo Fisher Scientific, Technologiepark-Zwijnaarde 82, B-9052 Gent, Belgium
| | - Karl Mechtler
- IMP─Institute of Molecular Pathology, Campus-Vienna-Biocenter 1, A-1030 Vienna, Austria
- IMBA─Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Dr. Bohr Gasse 3, A-1030 Vienna, Austria
- Gregor Mendel Institute of Molecular Plant Biology of the Austrian Academy of Sciences, Dr. Bohr Gasse 3, A-1030 Vienna, Austria
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44
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Study on Tissue Homogenization Buffer Composition for Brain Mass Spectrometry-Based Proteomics. Biomedicines 2022; 10:biomedicines10102466. [PMID: 36289728 PMCID: PMC9598821 DOI: 10.3390/biomedicines10102466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 09/26/2022] [Accepted: 09/27/2022] [Indexed: 11/25/2022] Open
Abstract
Mass spectrometry-based proteomics aims to study the proteome both qualitatively and quantitatively. A key step in proteomic analysis is sample preparation, which is crucial for reliable results. We investigated the effect of the composition of the homogenization buffer used to extract proteins from brain tissue on the yield of protein extraction and the number and type of extracted proteins. Three different types of buffers were compared—detergent-based buffer (DB), chaotropic agent-based buffer (CAB) and buffer without detergent and chaotropic agent (DFB). Based on label-free quantitative protein analysis, detergent buffer was identified as the most suitable for global proteomic profiling of brain tissue. It allows the most efficient extraction of membrane proteins, synaptic and synaptic membrane proteins along with ribosomal, mitochondrial and myelin sheath proteins, which are of particular interest in the field of neurodegenerative disorders research.
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45
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Mackmull MT, Nagel L, Sesterhenn F, Muntel J, Grossbach J, Stalder P, Bruderer R, Reiter L, van de Berg WDJ, de Souza N, Beyer A, Picotti P. Global, in situ analysis of the structural proteome in individuals with Parkinson's disease to identify a new class of biomarker. Nat Struct Mol Biol 2022; 29:978-989. [PMID: 36224378 DOI: 10.1038/s41594-022-00837-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 08/18/2022] [Indexed: 12/23/2022]
Abstract
Parkinson's disease (PD) is a prevalent neurodegenerative disease for which robust biomarkers are needed. Because protein structure reflects function, we tested whether global, in situ analysis of protein structural changes provides insight into PD pathophysiology and could inform a new concept of structural disease biomarkers. Using limited proteolysis-mass spectrometry (LiP-MS), we identified 76 structurally altered proteins in cerebrospinal fluid (CSF) of individuals with PD relative to healthy donors. These proteins were enriched in processes misregulated in PD, and some proteins also showed structural changes in PD brain samples. CSF protein structural information outperformed abundance information in discriminating between healthy participants and those with PD and improved the discriminatory performance of CSF measures of the hallmark PD protein α-synuclein. We also present the first analysis of inter-individual variability of a structural proteome in healthy individuals, identifying biophysical features of variable protein regions. Although independent validation is needed, our data suggest that global analyses of the human structural proteome will guide the development of novel structural biomarkers of disease and enable hypothesis generation about underlying disease processes.
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Affiliation(s)
- Marie-Therese Mackmull
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
| | - Luise Nagel
- Cluster of Excellence Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Fabian Sesterhenn
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
| | | | - Jan Grossbach
- Cluster of Excellence Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Patrick Stalder
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
| | | | | | - Wilma D J van de Berg
- Amsterdam UMC location Vrije Universiteit Amsterdam, Section Clinical Neuroanatomy and Biobanking, Department Anatomy and Neurosciences, Amsterdam, the Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Natalie de Souza
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland.,Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Andreas Beyer
- Cluster of Excellence Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany. .,Faculty of Medicine and University Hospital of Cologne, and Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany. .,Institute for Genetics, Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany.
| | - Paola Picotti
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland.
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46
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Mukherjee A, Ghosh S, Biswas D, Rao A, Shetty P, Epari S, Moiyadi A, Srivastava S. Clinical Proteomics for Meningioma: An Integrated Workflow for Quantitative Proteomics and Biomarker Validation in Formalin-Fixed Paraffin-Embedded Tissue Samples. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2022; 26:512-520. [PMID: 36036964 DOI: 10.1089/omi.2022.0082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Clinical proteomics is a rapidly emerging frontier in laboratory medicine. High-throughput proteomic investigations of biopsy tissues provide mechanistic insights into complex human diseases. For large-scale proteomics, formalin-fixed and paraffin-embedded (FFPE) tissue samples offer a viable alternative to fresh-frozen (FF) tissues that have restricted availability. In this context, meningioma is one of the most common primary brain tumors where innovation in diagnostics and therapeutic targets can benefit from clinical proteomics. We present here an integrated workflow for quantitative proteomics and biomarker validation of meningioma FFPE tissues. Applying label-free quantitative (LFQ) proteomics, we reproducibly (Pearson's correlation: 0.84-0.91) obtained an in-depth proteome coverage (nearly 4000 proteins per sample) from 120 min gradient of single unfractionated mass spectrometry run. Furthermore, building upon LFQ data and literature curated set of meningioma-associated proteins, we validated VIM, AHNAK, and CLU from FFPE tissues using selected reaction monitoring (SRM) assay and compared its performance with FF tissues. This study illustrates how knowledge from label-free proteomics can be integrated for selecting peptides for targeted validation and suggests that FFPE tissues are comparable to FF tissues for SRM assays. This quantitative clinical proteomics workflow is scalable for large-scale clinical diagnostics studies in the future, for example, utilizing the global repository of FFPE tissues in meningioma and possibly in other cancers.
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Affiliation(s)
- Arijit Mukherjee
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Susmita Ghosh
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Deeptarup Biswas
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | - Aishwarya Rao
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
| | | | | | | | - Sanjeeva Srivastava
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, India
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47
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Raghunathan R, Turajane K, Wong LC. Biomarkers in Neurodegenerative Diseases: Proteomics Spotlight on ALS and Parkinson’s Disease. Int J Mol Sci 2022; 23:ijms23169299. [PMID: 36012563 PMCID: PMC9409485 DOI: 10.3390/ijms23169299] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 08/13/2022] [Accepted: 08/14/2022] [Indexed: 11/21/2022] Open
Abstract
Neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD) are both characterized by pathogenic protein aggregates that correlate with the progressive degeneration of neurons and the loss of behavioral functions. Both diseases lack biomarkers for diagnosis and treatment efficacy. Proteomics is an unbiased quantitative tool capable of the high throughput quantitation of thousands of proteins from minimal sample volumes. We review recent proteomic studies in human tissues, plasma, cerebrospinal fluid (CSF), and exosomes in ALS and PD that identify proteins with potential utility as biomarkers. Further, we review disease-related post-translational modifications in key proteins TDP43 in ALS and α-synuclein in PD studies, which may serve as biomarkers. We compare relative and absolute quantitative proteomic approaches in key biomarker studies in ALS and PD and discuss recent technological advancements which may identify suitable biomarkers for the early-diagnosis treatment efficacy of these diseases.
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48
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Ishikawa M, Konno R, Nakajima D, Gotoh M, Fukasawa K, Sato H, Nakamura R, Ohara O, Kawashima Y. Optimization of Ultrafast Proteomics Using an LC-Quadrupole-Orbitrap Mass Spectrometer with Data-Independent Acquisition. J Proteome Res 2022; 21:2085-2093. [PMID: 35914019 PMCID: PMC9442788 DOI: 10.1021/acs.jproteome.2c00121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
![]()
Proteomics has become an increasingly important tool
in medical
and medicinal applications. It is necessary to improve the analytical
throughput for these applications, particularly in large-scale drug
screening to enable measurement of a large number of samples. In this
study, we aimed to establish an ultrafast proteomic method based on
5-min gradient LC and quadrupole-Orbitrap mass spectrometer (Q-Orbitrap
MS). We precisely optimized data-independent acquisition (DIA) parameters
for 5-min gradient LC and reached a depth of >5000 and 4200 proteins
from 1000 and 31.25 ng of HEK293T cell digest in a single-shot run,
respectively. The throughput of our method enabled the measurement
of approximately 80 samples/day, including sample loading, column
equilibration, and wash running time. We demonstrated that our method
is applicable for the screening of chemical responsivity via a cell
stimulation assay. These data show that our method enables the capture
of biological alterations in proteomic profiles with high sensitivity,
suggesting the possibility of large-scale screening of chemical responsivity.
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Affiliation(s)
- Masaki Ishikawa
- Laboratory of Clinical Omics Research, Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Ryo Konno
- Laboratory of Clinical Omics Research, Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Daisuke Nakajima
- Laboratory of Clinical Omics Research, Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Mari Gotoh
- Institute for Human Life Innovatiaon, Ochanomizu University, Bunkyo-ku, Tokyo 112-8610, Japan
| | - Keiko Fukasawa
- Institute for Human Life Innovatiaon, Ochanomizu University, Bunkyo-ku, Tokyo 112-8610, Japan
| | - Hironori Sato
- Laboratory of Clinical Omics Research, Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Ren Nakamura
- Laboratory of Clinical Omics Research, Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Osamu Ohara
- Laboratory of Clinical Omics Research, Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Yusuke Kawashima
- Laboratory of Clinical Omics Research, Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
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49
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Wang Y, Lih TSM, Chen L, Xu Y, Kuczler MD, Cao L, Pienta KJ, Amend SR, Zhang H. Optimized data-independent acquisition approach for proteomic analysis at single-cell level. Clin Proteomics 2022; 19:24. [PMID: 35810282 PMCID: PMC9270744 DOI: 10.1186/s12014-022-09359-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 05/26/2022] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND Single-cell proteomic analysis provides valuable insights into cellular heterogeneity allowing the characterization of the cellular microenvironment which is difficult to accomplish in bulk proteomic analysis. Currently, single-cell proteomic studies utilize data-dependent acquisition (DDA) mass spectrometry (MS) coupled with a TMT labelled carrier channel. Due to the extremely imbalanced MS signals among the carrier channel and other TMT reporter ions, the quantification is compromised. Thus, data-independent acquisition (DIA)-MS should be considered as an alternative approach towards single-cell proteomic study since it generates reproducible quantitative data. However, there are limited reports on the optimal workflow for DIA-MS-based single-cell analysis. METHODS We report an optimized DIA workflow for single-cell proteomics using Orbitrap Lumos Tribrid instrument. We utilized a breast cancer cell line (MDA-MB-231) and induced drug resistant polyaneuploid cancer cells (PACCs) to evaluate our established workflow. RESULTS We found that a short LC gradient was preferable for peptides extracted from single cell level with less than 2 ng sample amount. The total number of co-searching peptide precursors was also critical for protein and peptide identifications at nano- and sub-nano-gram levels. Post-translationally modified peptides could be identified from a nano-gram level of peptides. Using the optimized workflow, up to 1500 protein groups were identified from a single PACC corresponding to 0.2 ng of peptides. Furthermore, about 200 peptides with phosphorylation, acetylation, and ubiquitination were identified from global DIA analysis of 100 cisplatin resistant PACCs (20 ng). Finally, we used this optimized DIA approach to compare the whole proteome of MDA-MB-231 parental cells and induced PACCs at a single-cell level. We found the single-cell level comparison could reflect real protein expression changes and identify the protein copy number. CONCLUSIONS Our results demonstrate that the optimized DIA pipeline can serve as a reliable quantitative tool for single-cell as well as sub-nano-gram proteomic analysis.
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Affiliation(s)
- Yuefan Wang
- Department of Pathology, Johns Hopkins University, Baltimore, MD, 21287, USA
| | | | - Lijun Chen
- Department of Pathology, Johns Hopkins University, Baltimore, MD, 21287, USA
| | - Yuanwei Xu
- Department of Pathology, Johns Hopkins University, Baltimore, MD, 21287, USA
| | - Morgan D Kuczler
- Cancer Ecology Center, The Brady Urological Institute, Johns Hopkins School of Medicine, 600 N. Wolfe Street, Baltimore, MD, 21287, USA
| | - Liwei Cao
- Department of Pathology, Johns Hopkins University, Baltimore, MD, 21287, USA
| | - Kenneth J Pienta
- Cancer Ecology Center, The Brady Urological Institute, Johns Hopkins School of Medicine, 600 N. Wolfe Street, Baltimore, MD, 21287, USA
| | - Sarah R Amend
- Cancer Ecology Center, The Brady Urological Institute, Johns Hopkins School of Medicine, 600 N. Wolfe Street, Baltimore, MD, 21287, USA
| | - Hui Zhang
- Department of Pathology, Johns Hopkins University, Baltimore, MD, 21287, USA.
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Demichev V, Szyrwiel L, Yu F, Teo GC, Rosenberger G, Niewienda A, Ludwig D, Decker J, Kaspar-Schoenefeld S, Lilley KS, Mülleder M, Nesvizhskii AI, Ralser M. dia-PASEF data analysis using FragPipe and DIA-NN for deep proteomics of low sample amounts. Nat Commun 2022; 13:3944. [PMID: 35803928 PMCID: PMC9270362 DOI: 10.1038/s41467-022-31492-0] [Citation(s) in RCA: 117] [Impact Index Per Article: 58.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 06/20/2022] [Indexed: 11/28/2022] Open
Abstract
The dia-PASEF technology uses ion mobility separation to reduce signal interferences and increase sensitivity in proteomic experiments. Here we present a two-dimensional peak-picking algorithm and generation of optimized spectral libraries, as well as take advantage of neural network-based processing of dia-PASEF data. Our computational platform boosts proteomic depth by up to 83% compared to previous work, and is specifically beneficial for fast proteomic experiments and those with low sample amounts. It quantifies over 5300 proteins in single injections recorded at 200 samples per day throughput using Evosep One chromatography system on a timsTOF Pro mass spectrometer and almost 9000 proteins in single injections recorded with a 93-min nanoflow gradient on timsTOF Pro 2, from 200 ng of HeLa peptides. A user-friendly implementation is provided through the incorporation of the algorithms in the DIA-NN software and by the FragPipe workflow for spectral library generation.
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Affiliation(s)
- Vadim Demichev
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany.
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK.
- Department of Biochemistry and Milner Therapeutics Institute, University of Cambridge, Cambridge, UK.
| | - Lukasz Szyrwiel
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Guo Ci Teo
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | | | - Agathe Niewienda
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Daniela Ludwig
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Jens Decker
- Bruker Daltonics GmbH & Co. KG, Bremen, Germany
| | | | - Kathryn S Lilley
- Department of Biochemistry and Milner Therapeutics Institute, University of Cambridge, Cambridge, UK
| | - Michael Mülleder
- Core Facility High-Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
| | - Markus Ralser
- Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, UK
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