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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 2024:100800. [PMID: 38880244 DOI: 10.1016/j.mcpro.2024.100800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [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 mass-to-charge 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, 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, Germany; Centre for Integrative Biological Signaling Studies (CIBSS), University of Freiburg, Germany; Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Germany; Faculty of Biology, University of Freiburg, Germany
| | - Adrianna Seredynska
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany; Faculty of Biology, University of Freiburg, Germany
| | - Maximilian Maldacker
- Institute for Surgical Pathology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany; Faculty of Biology, University of Freiburg, Germany
| | - Clemens Kreutz
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Germany; Centre for Integrative Biological Signaling Studies (CIBSS), University of 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, Germany; German Cancer Consortium (DKTK) and Cancer Research Center (DKFZ), Freiburg, Germany
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2
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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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3
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Jiang Y, DeBord D, Vitrac H, Stewart J, Haghani A, Van Eyk JE, Fert-Bober J, Meyer JG. The Future of Proteomics is Up in the Air: Can Ion Mobility Replace Liquid Chromatography for High Throughput Proteomics? J Proteome Res 2024; 23:1871-1882. [PMID: 38713528 PMCID: PMC11161313 DOI: 10.1021/acs.jproteome.4c00248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/09/2024]
Abstract
The coevolution of liquid chromatography (LC) with mass spectrometry (MS) has shaped contemporary proteomics. LC hyphenated to MS now enables quantification of more than 10,000 proteins in a single injection, a number that likely represents most proteins in specific human cells or tissues. Separations by ion mobility spectrometry (IMS) have recently emerged to complement LC and further improve the depth of proteomics. Given the theoretical advantages in speed and robustness of IMS in comparison to LC, we envision that ongoing improvements to IMS paired with MS may eventually make LC obsolete, especially when combined with targeted or simplified analyses, such as rapid clinical proteomics analysis of defined biomarker panels. In this perspective, we describe the need for faster analysis that might drive this transition, the current state of direct infusion proteomics, and discuss some technical challenges that must be overcome to fully complete the transition to entirely gas phase proteomics.
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Affiliation(s)
- Yuming Jiang
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
- The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Daniel DeBord
- MOBILion Systems Inc., Chadds Ford, Pennsylvania 19317, United States
| | - Heidi Vitrac
- MOBILion Systems Inc., Chadds Ford, Pennsylvania 19317, United States
| | - Jordan Stewart
- MOBILion Systems Inc., Chadds Ford, Pennsylvania 19317, United States
| | - Ali Haghani
- The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Jennifer E Van Eyk
- The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Justyna Fert-Bober
- The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Jesse G Meyer
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
- The Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
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4
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Wang J, Tan H, Fu Y, Mishra A, Sun H, Wang Z, Wu Z, Wang X, Serrano GE, Beach TG, Peng J, High AA. Evaluation of Protein Identification and Quantification by the diaPASEF Method on timsTOF SCP. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:1253-1260. [PMID: 38754071 DOI: 10.1021/jasms.4c00067] [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: 05/18/2024]
Abstract
Accurate and precise quantification is crucial in modern proteomics, particularly in the context of exploring low-amount samples. While the innovative 4D-data-independent acquisition (DIA) quantitative proteomics facilitated by timsTOF mass spectrometers gives enhanced sensitivity and selectivity for protein identification, the diaPASEF (parallel accumulation-serial fragmentation combined with data-independent acquisition) parameters have not been systematically optimized, and a comprehensive evaluation of the quantification is currently lacking. In this study, we conducted a thorough optimization of key parameters on a timsTOF SCP instrument, including sample loading amount (50 ng), ramp/accumulation time (140 ms), isolation window width (20 m/z), and gradient time (60 min). To further improve the identification of proteins in low-amount samples, we utilized different column settings and introduced 0.02% n-dodecyl-β-d-maltoside (DDM) in the sample reconstitution solution, resulting in a remarkable 19-fold increase in protein identification at the single-cell-equivalent level. Moreover, a comprehensive comparison of protein quantification using a tandem mass tag reporter (TMT-reporter), complement TMT ions (TMTc), and diaPASEF revealed a strong correlation between these methods. Both diaPASEF and TMTc have effectively addressed the issue of ratio compression, highlighting the diaPASEF method's effectiveness in achieving accurate quantification data compared to TMT reporter quantification. Additionally, an in-depth analysis of in-group variation positioned diaPASEF between the TMT-reporter and TMTc methods. Therefore, diaPASEF quantification on the timsTOF SCP instrument emerges as a precise and accurate methodology for quantitative proteomics, especially for samples with small amounts.
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Affiliation(s)
- Ju Wang
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Haiyan Tan
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Yingxue Fu
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Ashutosh Mishra
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Huan Sun
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Zhen Wang
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Zhiping Wu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Xusheng Wang
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Geidy E Serrano
- Banner Sun Health Research Institute, Sun City, Arizona 85351, United States
| | - Thomas G Beach
- Banner Sun Health Research Institute, Sun City, Arizona 85351, United States
| | - Junmin Peng
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Anthony A High
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
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5
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Wakamatsu M, Muramatsu H, Sato H, Ishikawa M, Konno R, Nakajima D, Hamada M, Okuno Y, Kawashima Y, Hama A, Ito M, Iwafuchi H, Takahashi Y, Ohara O. Integrated proteogenomic analysis for inherited bone marrow failure syndrome. Leukemia 2024; 38:1256-1265. [PMID: 38740980 PMCID: PMC11147772 DOI: 10.1038/s41375-024-02263-1] [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: 02/17/2024] [Revised: 04/19/2024] [Accepted: 04/23/2024] [Indexed: 05/16/2024]
Abstract
Recent advances in in-depth data-independent acquisition proteomic analysis have enabled comprehensive quantitative analysis of >10,000 proteins. Herein, an integrated proteogenomic analysis for inherited bone marrow failure syndrome (IBMFS) was performed to reveal their biological features and to develop a proteomic-based diagnostic assay in the discovery cohort; dyskeratosis congenita (n = 12), Fanconi anemia (n = 11), Diamond-Blackfan anemia (DBA, n = 9), Shwachman-Diamond syndrome (SDS, n = 6), ADH5/ALDH2 deficiency (n = 4), and other IBMFS (n = 18). Unsupervised proteomic clustering identified eight independent clusters (C1-C8), with the ribosomal pathway specifically downregulated in C1 and C2, enriched for DBA and SDS, respectively. Six patients with SDS had significantly decreased SBDS protein expression, with two of these not diagnosed by DNA sequencing alone. Four patients with ADH5/ALDH2 deficiency showed significantly reduced ADH5 protein expression. To perform a large-scale rapid IBMFS screening, targeted proteomic analysis was performed on 417 samples from patients with IBMFS-related hematological disorders (n = 390) and healthy controls (n = 27). SBDS and ADH5 protein expressions were significantly reduced in SDS and ADH5/ALDH2 deficiency, respectively. The clinical application of this first integrated proteogenomic analysis would be useful for the diagnosis and screening of IBMFS, where appropriate clinical screening tests are lacking.
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Affiliation(s)
- Manabu Wakamatsu
- Department of Pediatrics, Nagoya University Graduate School of Medicine, Showa-ku, Nagoya, 466-8560, Japan
| | - Hideki Muramatsu
- Department of Pediatrics, Nagoya University Graduate School of Medicine, Showa-ku, Nagoya, 466-8560, Japan.
| | - Hironori Sato
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, 292-0818, Japan
- Department of Pediatrics, Chiba University Graduate School of Medicine, Chuo-ku, Chiba, 260-8670, Japan
| | - Masaki Ishikawa
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, 292-0818, Japan
| | - Ryo Konno
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, 292-0818, Japan
| | - Daisuke Nakajima
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, 292-0818, Japan
| | - Motoharu Hamada
- Department of Pediatrics, Nagoya University Graduate School of Medicine, Showa-ku, Nagoya, 466-8560, Japan
- Department of Virology, Nagoya City University Graduate School of Medical Sciences, Mizuho-ku, Nagoya, 464-0083, Japan
| | - Yusuke Okuno
- Department of Virology, Nagoya City University Graduate School of Medical Sciences, Mizuho-ku, Nagoya, 464-0083, Japan
| | - Yusuke Kawashima
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, 292-0818, Japan.
| | - Asahito Hama
- Department of Hematology and Oncology, Children's Medical Center, Japanese Red Cross Aichi Medical Center Nagoya First Hospital, Nakamura-ku, Nagoya, 453-8511, Japan
| | - Masafumi Ito
- Department of Pathology, Japanese Red Cross Aichi Medical Center Nagoya First Hospital, Nakamura-ku, Nagoya, 453-8511, Japan
| | - Hideto Iwafuchi
- Department of Pathology, Shizuoka Children's Hospital, Aoi-ku, Shizuoka, 420-095, Japan
| | - Yoshiyuki Takahashi
- Department of Pediatrics, Nagoya University Graduate School of Medicine, Showa-ku, Nagoya, 466-8560, Japan
| | - Osamu Ohara
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, 292-0818, Japan
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6
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Yazaki J, Yamanashi T, Nemoto S, Kobayashi A, Han YW, Hasegawa T, Iwase A, Ishikawa M, Konno R, Imami K, Kawashima Y, Seita J. Mapping adipocyte interactome networks by HaloTag-enrichment-mass spectrometry. Biol Methods Protoc 2024; 9:bpae039. [PMID: 38884001 PMCID: PMC11180226 DOI: 10.1093/biomethods/bpae039] [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: 05/01/2024] [Revised: 05/19/2024] [Accepted: 05/28/2024] [Indexed: 06/18/2024] Open
Abstract
Mapping protein interaction complexes in their natural state in vivo is arguably the Holy Grail of protein network analysis. Detection of protein interaction stoichiometry has been an important technical challenge, as few studies have focused on this. This may, however, be solved by artificial intelligence (AI) and proteomics. Here, we describe the development of HaloTag-based affinity purification mass spectrometry (HaloMS), a high-throughput HaloMS assay for protein interaction discovery. The approach enables the rapid capture of newly expressed proteins, eliminating tedious conventional one-by-one assays. As a proof-of-principle, we used HaloMS to evaluate the protein complex interactions of 17 regulatory proteins in human adipocytes. The adipocyte interactome network was validated using an in vitro pull-down assay and AI-based prediction tools. Applying HaloMS to probe adipocyte differentiation facilitated the identification of previously unknown transcription factor (TF)-protein complexes, revealing proteome-wide human adipocyte TF networks and shedding light on how different pathways are integrated.
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Affiliation(s)
- Junshi Yazaki
- Laboratory for Integrative Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
- Faculty of Agriculture, Laboratory for Genome Biology, Setsunan University, Osaka, 573-0101, Japan
| | - Takashi Yamanashi
- Laboratory for Integrative Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
- Medical Data Deep Learning Team, Advanced Data Science Project, RIKEN Information R&D and Strategy Headquarters, RIKEN, Tokyo, 103-0027, Japan
- School of Integrative and Global Majors, University of Tsukuba, Tsukuba, 305-8577, Japan
| | - Shino Nemoto
- Laboratory for Intestinal Ecosystem, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Atsuo Kobayashi
- Laboratory for Integrative Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Yong-Woon Han
- Laboratory for Integrative Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Tomoko Hasegawa
- Laboratory for Integrative Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Akira Iwase
- Cell Function Research Team, RIKEN Center for Sustainable Resource Science, Yokohama, 230-0045, Japan
| | - Masaki Ishikawa
- Department of Applied Genomics, Technology Development Team, Kazusa DNA Research Institute, Kisarazu, 292-0818, Japan
| | - Ryo Konno
- Department of Applied Genomics, Technology Development Team, Kazusa DNA Research Institute, Kisarazu, 292-0818, Japan
| | - Koshi Imami
- Proteome Homeostasis Research Unit, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
| | - Yusuke Kawashima
- Department of Applied Genomics, Technology Development Team, Kazusa DNA Research Institute, Kisarazu, 292-0818, Japan
| | - Jun Seita
- Laboratory for Integrative Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan
- Medical Data Deep Learning Team, Advanced Data Science Project, RIKEN Information R&D and Strategy Headquarters, RIKEN, Tokyo, 103-0027, Japan
- School of Integrative and Global Majors, University of Tsukuba, Tsukuba, 305-8577, Japan
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7
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Lertruangpanya K, Roytrakul S, Surarit R, Horsophonphong S. Comparative proteomic analysis of dental pulp from supernumerary and normal permanent teeth. Clin Oral Investig 2024; 28:321. [PMID: 38758416 PMCID: PMC11101566 DOI: 10.1007/s00784-024-05698-z] [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: 02/12/2024] [Accepted: 04/26/2024] [Indexed: 05/18/2024]
Abstract
OBJECTIVES To obtain and compare the protein profiles of supernumerary and normal permanent dental pulp tissues. MATERIALS AND METHODS Dental pulp tissues were obtained from supernumerary and normal permanent teeth. Proteins were extracted and analyzed by liquid chromatography-tandem mass spectrometry (LC/MS-MS). Protein identification and quantification from MS data was performed with MaxQuant. Statistical analysis was conducted using Metaboanalyst to identify differentially expressed proteins (DEPs) (P-value < 0.05, fold-change > 2). Gene Ontology enrichment analyses were performed with gProfiler. RESULTS A total of 3,534 proteins were found in normal dental pulp tissue and 1,093 in supernumerary dental pulp tissue, with 174 DEPs between the two groups. This analysis revealed similar functional characteristics in terms of cellular component organization, cell differentiation, developmental process, and response to stimulus, alongside exclusive functions unique to normal permanent dental pulp tissues such as healing, vascular development and cell death. Upon examination of DEPs, these proteins were associated with the processes of wound healing and apoptosis. CONCLUSIONS This study provides a comprehensive understanding of the protein profile of dental pulp tissue, including the first such profiling of supernumerary permanent dental pulp. There are functional differences between the proteomic profiles of supernumerary and normal permanent dental pulp tissue, despite certain biological similarities between the two groups. Differences in protein expression were identified, and the identified DEPs were linked to the healing and apoptosis processes. CLINICAL RELEVANCE This discovery enhances our knowledge of supernumerary and normal permanent pulp tissue, and serves as a valuable reference for future studies on supernumerary teeth.
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Affiliation(s)
- Kritkamon Lertruangpanya
- Department of Pediatric Dentistry, Faculty of Dentistry, Mahidol University, 6 Yothi Road, Ratchathewi, Bangkok, Thailand
| | - Sittiruk Roytrakul
- Functional Proteomics Technology Laboratory, National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathumthani, Thailand
| | - Rudee Surarit
- Department of Oral Biology, Faculty of Dentistry, Mahidol University, Bangkok, Thailand
- Faculty of Dentistry, Siam University, Bangkok, Thailand
| | - Sivaporn Horsophonphong
- Department of Pediatric Dentistry, Faculty of Dentistry, Mahidol University, 6 Yothi Road, Ratchathewi, Bangkok, Thailand.
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8
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Mansuri MS, Bathla S, Lam TT, Nairn AC, Williams KR. Optimal conditions for carrying out trypsin digestions on complex proteomes: From bulk samples to single cells. J Proteomics 2024; 297:105109. [PMID: 38325732 PMCID: PMC10939724 DOI: 10.1016/j.jprot.2024.105109] [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: 11/13/2023] [Revised: 01/10/2024] [Accepted: 01/31/2024] [Indexed: 02/09/2024]
Abstract
To identify proteins by the bottom-up mass spectrometry workflow, enzymatic digestion is essential to break down proteins into smaller peptides amenable to both chromatographic separation and mass spectrometric analysis. Trypsin is the most extensively used protease due to its high cleavage specificity and generation of peptides with desirable positively charged N- and C-terminal amino acid residues that are amenable to reverse phase HPLC separation and MS/MS analyses. However, trypsin can yield variable digestion profiles and its protein cleavage activity is interdependent on trypsin source and quality, digestion time and temperature, pH, denaturant, trypsin and substrate concentrations, composition/complexity of the sample matrix, and other factors. There is therefore a need for a more standardized, general-purpose trypsin digestion protocol. Based on a review of the literature we delineate optimal conditions for carrying out trypsin digestions of complex proteomes from bulk samples to limiting amounts of protein extracts. Furthermore, we highlight recent developments and technological advances used in digestion protocols to quantify complex proteomes from single cells. SIGNIFICANCE: Currently, bottom-up MS-based proteomics is the method of choice for global proteome analysis. Since trypsin is the most utilized protease in bottom-up MS proteomics, delineating optimal conditions for carrying out trypsin digestions of complex proteomes in samples ranging from tissues to single cells should positively impact a broad range of biomedical research.
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Affiliation(s)
- M Shahid Mansuri
- Yale/NIDA Neuroproteomics Center, New Haven, CT 06511, USA; Molecular Biophysics and Biochemistry, Yale University School of Medicine, New Haven, CT 06511, USA.
| | - Shveta Bathla
- Yale/NIDA Neuroproteomics Center, New Haven, CT 06511, USA; Department of Psychiatry, Yale School of Medicine, New Haven, CT 06511, USA
| | - TuKiet T Lam
- Yale/NIDA Neuroproteomics Center, New Haven, CT 06511, USA; Molecular Biophysics and Biochemistry, Yale University School of Medicine, New Haven, CT 06511, USA; Keck MS & Proteomics Resource, Yale School of Medicine, New Haven, CT 06511, USA
| | - Angus C Nairn
- Yale/NIDA Neuroproteomics Center, New Haven, CT 06511, USA; Department of Psychiatry, Yale School of Medicine, New Haven, CT 06511, USA
| | - Kenneth R Williams
- Yale/NIDA Neuroproteomics Center, New Haven, CT 06511, USA; Molecular Biophysics and Biochemistry, Yale University School of Medicine, New Haven, CT 06511, USA; Keck MS & Proteomics Resource, Yale School of Medicine, New Haven, CT 06511, USA.
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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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Nalehua MR, Zaia J. A critical evaluation of ultrasensitive single-cell proteomics strategies. Anal Bioanal Chem 2024; 416:2359-2369. [PMID: 38358530 DOI: 10.1007/s00216-024-05171-6] [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: 09/25/2023] [Revised: 01/20/2024] [Accepted: 01/23/2024] [Indexed: 02/16/2024]
Abstract
Success of mass spectrometry characterization of the proteome of single cells allows us to gain a greater understanding than afforded by transcriptomics alone but requires clear understanding of the tradeoffs between analytical throughput and precision. Recent advances in mass spectrometry acquisition techniques, including updated instrumentation and sample preparation, have improved the quality of peptide signals obtained from single cell data. However, much of the proteome remains uncharacterized, and higher throughput techniques often come at the expense of reduced sensitivity and coverage, which diminish the ability to measure proteoform heterogeneity, including splice variants and post-translational modifications, in single cell data analysis. Here, we assess the growing body of ultrasensitive single-cell approaches and their tradeoffs as researchers try to balance throughput and precision in their experiments.
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Affiliation(s)
| | - Joseph Zaia
- Bioinformatics Program, Boston University, Boston, MA, USA.
- Department of Biochemistry and Cell Biology, Boston University, Boston, MA, USA.
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11
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Zeng H, Zhang YQ, Wang YF, Du XX, Xiao WX, Li H. Design and experiment of high-field asymmetric waveform ion mobility spectrometry chip based on an integrated temperature control printed circuit board structure. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2024; 38:e9699. [PMID: 38355881 DOI: 10.1002/rcm.9699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 11/26/2023] [Accepted: 12/14/2023] [Indexed: 02/16/2024]
Abstract
RATIONALE During the detection of volatile organic compounds (VOC) using high-field asymmetric waveform ion mobility spectrometry (FAIMS), the ambient temperature significantly impacts the accuracy of planar FAIMS. To mitigate the influence of ambient temperature on detection accuracy and enhance resolution, a FAIMS system based on the inner impedance characteristics of a printed circuit board (PCB) was designed for temperature control. METHODS This study, conducted under standard atmospheric pressure, aimed to assess the signal stability of a planar FAIMS instrument with and without temperature control, and the effect of temperature change on the detection ability of acetone, ethanol, and their mixture was studied using PCB self-heating. RESULTS Experimental results demonstrated that the base noise in FAIMS with temperature control was 0.2 pA, whereas that in FAIMS without temperature control was 1.8 pA. Notably, with increasing temperature, the detection ability of FAIMS changes accordingly. The optimal relative detection ability of acetone was observed when the electrode plate was heated to 45°C under an electric field of 15 kV/cm. CONCLUSIONS This study provides a novel approach to improve the resolving power of FAIMS systems and their signal-to-noise ratio. The utilization of a PCB-based temperature control proved effective in stabilizing FAIMS signal characteristics and optimizing detection capabilities, particularly for VOCs such as acetone. These findings have significant implications for improving the accuracy and resolving power of FAIMS systems in VOC detection applications.
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Affiliation(s)
- Hao Zeng
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin, Guangxi, China
| | - Yu-Qiao Zhang
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin, Guangxi, China
| | - Yi-Fei Wang
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin, Guangxi, China
| | - Xiao-Xia Du
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin, Guangxi, China
- Guangxi Colleges and Universities Key Laboratory of Biomedical Sensors and Intelligent Instruments, Guilin, Guangxi, China
| | - Wen-Xiang Xiao
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin, Guangxi, China
- Guangxi Colleges and Universities Key Laboratory of Biomedical Sensors and Intelligent Instruments, Guilin, Guangxi, China
| | - Hua Li
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin, Guangxi, China
- Guangxi Colleges and Universities Key Laboratory of Biomedical Sensors and Intelligent Instruments, Guilin, Guangxi, China
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12
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Yue L, Gong T, Jiang W, Qian L, Gong W, Sun Y, Cai X, Xu H, Liu F, Wang H, Li S, Zhu Y, Zheng Z, Wu Q, Guo T. Proteomic profiling of ovarian clear cell carcinomas identifies prognostic biomarkers for chemotherapy. Proteomics 2024; 24:e2300242. [PMID: 38171885 DOI: 10.1002/pmic.202300242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 11/17/2023] [Accepted: 11/20/2023] [Indexed: 01/05/2024]
Abstract
Clear cell ovarian carcinoma (CCOC) is a relatively rare subtype of ovarian cancer (OC) with high degree of resistance to standard chemotherapy. Little is known about the underlying molecular mechanisms, and it remains a challenge to predict its prognosis after chemotherapy. Here, we first analyzed the proteome of 35 formalin-fixed paraffin-embedded (FFPE) CCOC tissue specimens from a cohort of 32 patients with CCOC (H1 cohort) and characterized 8697 proteins using data-independent acquisition mass spectrometry (DIA-MS). We then performed proteomic analysis of 28 fresh frozen (FF) CCOC tissue specimens from an independent cohort of 24 patients with CCOC (H2 cohort), leading to the identification of 9409 proteins with DIA-MS. After bioinformatics analysis, we narrowed our focus to 15 proteins significantly correlated with the recurrence free survival (RFS) in both cohorts. These proteins are mainly involved in DNA damage response, extracellular matrix (ECM), and mitochondrial metabolism. Parallel reaction monitoring (PRM)-MS was adopted to validate the prognostic potential of the 15 proteins in the H1 cohort and an independent confirmation cohort (H3 cohort). Interferon-inducible transmembrane protein 1 (IFITM1) was observed as a robust prognostic marker for CCOC in both PRM data and immunohistochemistry (IHC) data. Taken together, this study presents a CCOC proteomic data resource and a single promising protein, IFITM1, which could potentially predict the recurrence and survival of CCOC.
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Affiliation(s)
- Liang Yue
- School of Life Sciences, Fudan University, Shanghai, China
- Westlake 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
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Tingting Gong
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University
| | - Wenhao Jiang
- Westlake 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
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Liujia Qian
- Westlake 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
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Wangang Gong
- Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
- Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Yaoting Sun
- Westlake 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
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Xue Cai
- Westlake 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
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Heli Xu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Fanghua Liu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - He Wang
- Westlake 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
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Sainan Li
- Westlake 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
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- National Health Commission Key Laboratory of Reproductive Health, Institute of Reproductive and Child Health, Peking University, Beijing, China
| | - Yi Zhu
- Westlake 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
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Zhiguo Zheng
- Zhejiang Cancer Hospital, Hangzhou, Zhejiang, China
- Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Qijun Wu
- Department of Clinical Epidemiology, Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Tiannan Guo
- Westlake 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
- Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
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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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Jiang Y, Meyer JG. 1.4 min Plasma Proteome Profiling via Nanoparticle Protein Corona and Direct Infusion Mass Spectrometry. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.06.579213. [PMID: 38370692 PMCID: PMC10871276 DOI: 10.1101/2024.02.06.579213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Non-invasive detection of protein biomarkers in plasma is crucial for clinical purposes. Liquid chromatography mass spectrometry (LC-MS) is the gold standard technique for plasma proteome analysis, but despite recent advances, it remains limited by throughput, cost, and coverage. Here, we introduce a new hybrid method, which integrates direct infusion shotgun proteome analysis (DISPA) with nanoparticle (NP) protein coronas enrichment for high throughput and efficient plasma proteomic profiling. We realized over 280 protein identifications in 1.4 minutes collection time, which enables a potential throughput of approximately 1,000 samples daily. The identified proteins are involved in valuable pathways and 44 of the proteins are FDA approved biomarkers. The robustness and quantitative accuracy of this method were evaluated across multiple NPs and concentrations with a mean coefficient of variation at 17%. Moreover, different protein corona profiles were observed among various nanoparticles based on their distinct surface modifications, and all NP protein profiles exhibited deeper coverage and better quantification than neat plasma. Our streamlined workflow merges coverage and throughput with precise quantification, leveraging both DISPA and NP protein corona enrichments. This underscores the significant potential of DISPA when paired with NP sample preparation techniques for plasma proteome studies.
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Affiliation(s)
- Yuming Jiang
- Department of Computational Biomedicine, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
- Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
- Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Jesse G. Meyer
- Department of Computational Biomedicine, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
- Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
- Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
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15
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Tomioka R, Tomioka A, Ogata K, Chan HJ, Chen LY, Guzman UH, Xuan Y, Olsen JV, Chen YJ, Ishihama Y. Extending the Coverage of Lys-C/Trypsin-Based Bottom-up Proteomics by Cysteine S-Aminoethylation. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:386-396. [PMID: 38287222 DOI: 10.1021/jasms.3c00448] [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: 01/31/2024]
Abstract
To improve the coverage in bottom-up proteomics, S-aminoethylation of cysteine residues (AE-Cys) was carried out with 2-bromoethylamine, followed by cleavage with lysyl endopeptidase (Lys-C) or Lys-C/trypsin. A model study with bovine serum albumin showed that the C-terminal side of AE-Cys was successfully cleaved by Lys-C. The frequency of side reactions at amino acids other than Cys was less than that in the case of carbamidomethylation of Cys with iodoacetamide. Proteomic analysis of A549 cell extracts in the data-dependent acquisition mode after AE-Cys modification afforded a greater number of identified protein groups, especially membrane proteins. In addition, label-free quantification of proteins in mouse nonsmall cell lung cancer (NSCLC) tissue in the data-independent acquisition mode after AE-Cys modification showed improved NSCLC pathway coverage and greater reproducibility. Furthermore, the AE-Cys method could identify an epidermal growth factor receptor peptide containing the T790 M mutation site, a well-established lung-cancer-related mutation site that has evaded conventional bottom-up methods. Finally, AE-Cys was found to fully mimic Lys in terms of collision-induced dissociation fragmentation, ion mobility separation, and cleavage by Lys-C/trypsin, except for sulfoxide formation during sample preparation.
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Affiliation(s)
- Ryota Tomioka
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
- Biopharmaceutical Research Division, Shionogi & Co., Ltd., Toyonaka 561-0825, Osaka, Japan
| | - Ayana Tomioka
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | - Kosuke Ogata
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | - Hsin-Ju Chan
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan
| | - Li-Yu Chen
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan
| | - Ulises H Guzman
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen N DK-2200, Denmark
| | - Yue Xuan
- Thermo Fisher Scientific GmbH, Bremen 28199, Germany
| | - Jesper V Olsen
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen N DK-2200, Denmark
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan
| | - Yasushi Ishihama
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
- Laboratory of Clinical and Analytical Chemistry, National Institute of Biomedical Innovation, Health and Nutrition, Ibaraki 567-0085, Osaka, Japan
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16
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Ziegler AR, Dufour A, Scott NE, Edgington-Mitchell LE. Ion Mobility-Based Enrichment-Free N-Terminomics Analysis Reveals Novel Legumain Substrates in Murine Spleen. Mol Cell Proteomics 2024; 23:100714. [PMID: 38199506 PMCID: PMC10862022 DOI: 10.1016/j.mcpro.2024.100714] [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: 07/28/2023] [Revised: 12/19/2023] [Accepted: 01/02/2024] [Indexed: 01/12/2024] Open
Abstract
Aberrant levels of the asparaginyl endopeptidase legumain have been linked to inflammation, neurodegeneration, and cancer, yet our understanding of this protease is incomplete. Systematic attempts to identify legumain substrates have been previously confined to in vitro studies, which fail to mirror physiological conditions and obscure biologically relevant cleavage events. Using high-field asymmetric waveform ion mobility spectrometry (FAIMS), we developed a streamlined approach for proteome and N-terminome analyses without the need for N-termini enrichment. Compared to unfractionated proteomic analysis, we demonstrate FAIMS fractionation improves N-termini identification by >2.5 fold, resulting in the identification of >2882 unique N-termini from limited sample amounts. In murine spleens, this approach identifies 6366 proteins and 2528 unique N-termini, with 235 cleavage events enriched in WT compared to legumain-deficient spleens. Among these, 119 neo-N-termini arose from asparaginyl endopeptidase activities, representing novel putative physiological legumain substrates. The direct cleavage of selected substrates by legumain was confirmed using in vitro assays, providing support for the existence of physiologically relevant extra-lysosomal legumain activity. Combined, these data shed critical light on the functions of legumain and demonstrate the utility of FAIMS as an accessible method to improve depth and quality of N-terminomics studies.
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Affiliation(s)
- Alexander R Ziegler
- Department of Biochemistry and Pharmacology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Antoine Dufour
- Department of Physiology and Pharmacology, University of Calgary, Calgary, Alberta, Canada; McCaig Institute for Bone and Joint Health, University of Calgary, Calgary, Alberta, Canada
| | - Nichollas E Scott
- Department of Microbiology and Immunology, Peter Doherty Institute, The University of Melbourne, Parkville, Victoria, Australia.
| | - Laura E Edgington-Mitchell
- Department of Biochemistry and Pharmacology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.
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17
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Nakajima D, Konno R, Miyashita Y, Ishikawa M, Ohara O, Kawashima Y. Proteome Analysis of Serum Purified Using Solanum tuberosum and Lycopersicon esculentum Lectins. Int J Mol Sci 2024; 25:1315. [PMID: 38279312 PMCID: PMC10816257 DOI: 10.3390/ijms25021315] [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: 12/27/2023] [Revised: 01/17/2024] [Accepted: 01/19/2024] [Indexed: 01/28/2024] Open
Abstract
Serum and plasma exhibit a broad dynamic range of protein concentrations, posing challenges for proteome analysis. Various technologies have been developed to reduce this complexity, including high-abundance depletion methods utilizing antibody columns, extracellular vesicle enrichment techniques, and trace protein enrichment using nanobead cocktails. Here, we employed lectins to address this, thereby extending the scope of biomarker discovery in serum or plasma using a novel approach. We enriched serum proteins using 37 different lectins and subjected them to LC-MS/MS analysis with data-independent acquisition. Solanum tuberosum lectin (STL) and Lycopersicon esculentum lectin (LEL) enabled the detection of more serum proteins than the other lectins. STL and LEL bind to N-acetylglucosamine oligomers, emphasizing the significance of capturing these oligomer-binding proteins when analyzing serum trace proteins. Combining STL and LEL proved more effective than using them separately, allowing us to identify over 3000 proteins from serum through single-shot proteome analysis. We applied the STL/LEL trace-protein enrichment method to the sera of systemic lupus erythematosus model mice. This revealed differences in >1300 proteins between the systemic lupus erythematosus model and control mouse sera, underscoring the utility of this method for biomarker discovery.
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Affiliation(s)
- Daisuke Nakajima
- Department of Applied Genomics, Kazusa DNA Research Institute, 2-5-23 Kazusa Kamatari, Kisarazu 292-0818, Chiba, Japan; (D.N.); (R.K.); (Y.M.); (M.I.); (O.O.)
| | - Ryo Konno
- Department of Applied Genomics, Kazusa DNA Research Institute, 2-5-23 Kazusa Kamatari, Kisarazu 292-0818, Chiba, Japan; (D.N.); (R.K.); (Y.M.); (M.I.); (O.O.)
| | - Yasuomi Miyashita
- Department of Applied Genomics, Kazusa DNA Research Institute, 2-5-23 Kazusa Kamatari, Kisarazu 292-0818, Chiba, Japan; (D.N.); (R.K.); (Y.M.); (M.I.); (O.O.)
- Department of Developmental Biology, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba 260-8670, Chiba, Japan
| | - Masaki Ishikawa
- Department of Applied Genomics, Kazusa DNA Research Institute, 2-5-23 Kazusa Kamatari, Kisarazu 292-0818, Chiba, Japan; (D.N.); (R.K.); (Y.M.); (M.I.); (O.O.)
| | - Osamu Ohara
- Department of Applied Genomics, Kazusa DNA Research Institute, 2-5-23 Kazusa Kamatari, Kisarazu 292-0818, Chiba, Japan; (D.N.); (R.K.); (Y.M.); (M.I.); (O.O.)
| | - Yusuke Kawashima
- Department of Applied Genomics, Kazusa DNA Research Institute, 2-5-23 Kazusa Kamatari, Kisarazu 292-0818, Chiba, Japan; (D.N.); (R.K.); (Y.M.); (M.I.); (O.O.)
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18
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Zmyslia M, Fröhlich K, Dao T, Schmidt A, Jessen-Trefzer C. Deep Proteomic Investigation of Metabolic Adaptation in Mycobacteria under Different Growth Conditions. Proteomes 2023; 11:39. [PMID: 38133153 PMCID: PMC10747050 DOI: 10.3390/proteomes11040039] [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: 09/26/2023] [Revised: 11/22/2023] [Accepted: 12/05/2023] [Indexed: 12/23/2023] Open
Abstract
Understanding the complex mechanisms of mycobacterial pathophysiology and adaptive responses presents challenges that can hinder drug development. However, employing physiologically relevant conditions, such as those found in human macrophages or simulating physiological growth conditions, holds promise for more effective drug screening. A valuable tool in this pursuit is proteomics, which allows for a comprehensive analysis of adaptive responses. In our study, we focused on Mycobacterium smegmatis, a model organism closely related to the pathogenic Mycobacterium tuberculosis, to investigate the impact of various carbon sources on mycobacterial growth. To facilitate this research, we developed a cost-effective, straightforward, and high-quality pipeline for proteome analysis and compared six different carbon source conditions. Additionally, we have created an online tool to present and analyze our data, making it easily accessible to the community. This user-friendly platform allows researchers and interested parties to explore and interpret the results effectively. Our findings shed light on mycobacterial adaptive physiology and present potential targets for drug development, contributing to the fight against tuberculosis.
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Affiliation(s)
- Mariia Zmyslia
- Faculty of Chemistry and Pharmacy, University of Freiburg, Albertstrasse 21, 79104 Freiburg, Germany; (M.Z.); (T.D.)
| | - Klemens Fröhlich
- Proteomics Core Facility, Biozentrum Basel, University of Basel, Spitalstrasse 41, 4056 Basel, Switzerland; (K.F.); (A.S.)
| | - Trinh Dao
- Faculty of Chemistry and Pharmacy, University of Freiburg, Albertstrasse 21, 79104 Freiburg, Germany; (M.Z.); (T.D.)
- Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Albertstrasse 19A, 79104 Freiburg, Germany
- The Center for Integrative Biological Signaling Studies, University of Freiburg, 79104 Freiburg, Germany
| | - Alexander Schmidt
- Proteomics Core Facility, Biozentrum Basel, University of Basel, Spitalstrasse 41, 4056 Basel, Switzerland; (K.F.); (A.S.)
| | - Claudia Jessen-Trefzer
- Faculty of Chemistry and Pharmacy, University of Freiburg, Albertstrasse 21, 79104 Freiburg, Germany; (M.Z.); (T.D.)
- The Center for Integrative Biological Signaling Studies, University of Freiburg, 79104 Freiburg, Germany
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19
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Rodriguez Gallo MC, Li Q, Talasila M, Uhrig RG. Quantitative Time-Course Analysis of Osmotic and Salt Stress in Arabidopsis thaliana Using Short Gradient Multi-CV FAIMSpro BoxCar DIA. Mol Cell Proteomics 2023; 22:100638. [PMID: 37704098 PMCID: PMC10663867 DOI: 10.1016/j.mcpro.2023.100638] [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: 02/16/2023] [Revised: 08/22/2023] [Accepted: 08/27/2023] [Indexed: 09/15/2023] Open
Abstract
A major limitation when undertaking quantitative proteomic time-course experimentation is the tradeoff between depth-of-analysis and speed-of-analysis. In high complexity and high dynamic range sample types, such as plant extracts, balance between resolution and time is especially apparent. To address this, we evaluate multiple compensation voltage (CV) high field asymmetric waveform ion mobility spectrometry (FAIMSpro) settings using the latest label-free single-shot Orbitrap-based DIA acquisition workflows for their ability to deeply quantify the Arabidopsis thaliana seedling proteome. Using a BoxCarDIA acquisition workflow with a -30 -50 -70 CV FAIMSpro setting, we were able to consistently quantify >5000 Arabidopsis seedling proteins over a 21-min gradient, facilitating the analysis of ∼42 samples per day. Utilizing this acquisition approach, we then quantified proteome-level changes occurring in Arabidopsis seedling shoots and roots over 24 h of salt and osmotic stress, to identify early and late stress response proteins and reveal stress response overlaps. Here, we successfully quantify >6400 shoot and >8500 root protein groups, respectively, quantifying nearly ∼9700 unique protein groups in total across the study. Collectively, we pioneer a short gradient, multi-CV FAIMSpro BoxCarDIA acquisition workflow that represents an exciting new analysis approach for undertaking quantitative proteomic time-course experimentation in plants.
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Affiliation(s)
- M C Rodriguez Gallo
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Q Li
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - M Talasila
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - R G Uhrig
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada; Department of Biochemistry, University of Alberta, Edmonton, Alberta, Canada.
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20
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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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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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Heil L, Damoc E, Arrey TN, Pashkova A, Denisov E, Petzoldt J, Peterson AC, Hsu C, Searle BC, Shulman N, Riffle M, Connolly B, MacLean BX, Remes PM, Senko MW, Stewart HI, Hock C, Makarov AA, Hermanson D, Zabrouskov V, Wu CC, MacCoss MJ. Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data-Independent Acquisition. J Proteome Res 2023; 22:3290-3300. [PMID: 37683181 PMCID: PMC10563156 DOI: 10.1021/acs.jproteome.3c00357] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Indexed: 09/10/2023]
Abstract
We evaluate the quantitative performance of the newly released Asymmetric Track Lossless (Astral) analyzer. Using data-independent acquisition, the Thermo Scientific Orbitrap Astral mass spectrometer quantifies 5 times more peptides per unit time than state-of-the-art Thermo Scientific Orbitrap mass spectrometers, which have long been the gold standard for high-resolution quantitative proteomics. Our results demonstrate that the Orbitrap Astral mass spectrometer can produce high-quality quantitative measurements across a wide dynamic range. We also use a newly developed extracellular vesicle enrichment protocol to reach new depths of coverage in the plasma proteome, quantifying over 5000 plasma proteins in a 60 min gradient with the Orbitrap Astral mass spectrometer.
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Affiliation(s)
- Lilian
R. Heil
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Eugen Damoc
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | - Tabiwang N. Arrey
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | - Anna Pashkova
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | - Eduard Denisov
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | - Johannes Petzoldt
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | | | - Chris Hsu
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Brian C. Searle
- Pelotonia
Institute for Immuno-Oncology, The Ohio
State University Comprehensive Cancer Center, Columbus, Ohio 43210, United States
- Department
of Biomedical Informatics, The Ohio State
University, Columbus, Ohio 43210, United States
| | - Nicholas Shulman
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Michael Riffle
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Brian Connolly
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Brendan X. MacLean
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Philip M. Remes
- Thermo
Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Michael W. Senko
- Thermo
Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Hamish I. Stewart
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | - Christian Hock
- Thermo
Fisher Scientific, Hanna-Kunath
Ste. 11, 28199 Bremen, Germany
| | | | - Daniel Hermanson
- Thermo
Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Vlad Zabrouskov
- Thermo
Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Christine C. Wu
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Michael J. MacCoss
- Department
of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
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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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Heil LR, Damoc E, Arrey TN, Pashkova A, Denisov E, Petzoldt J, Peterson AC, Hsu C, Searle BC, Shulman N, Riffle M, Connolly B, MacLean BX, Remes PM, Senko MW, Stewart HI, Hock C, Makarov AA, Hermanson D, Zabrouskov V, Wu CC, MacCoss MJ. Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data Independent Acquisition. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.03.543570. [PMID: 37398334 PMCID: PMC10312564 DOI: 10.1101/2023.06.03.543570] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
We evaluate the quantitative performance of the newly released Asymmetric Track Lossless (Astral) analyzer. Using data independent acquisition, the Thermo Scientific™ Orbitrap™ Astral™ mass spectrometer quantifies 5 times more peptides per unit time than state-of-the-art Thermo Scientific™ Orbitrap™ mass spectrometers, which have long been the gold standard for high resolution quantitative proteomics. Our results demonstrate that the Orbitrap Astral mass spectrometer can produce high quality quantitative measurements across a wide dynamic range. We also use a newly developed extra-cellular vesicle enrichment protocol to reach new depths of coverage in the plasma proteome, quantifying over 5,000 plasma proteins in a 60-minute gradient with the Orbitrap Astral mass spectrometer.
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Affiliation(s)
- Lilian R. Heil
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Eugen Damoc
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | - Tabiwang N. Arrey
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | - Anna Pashkova
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | - Eduard Denisov
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | - Johannes Petzoldt
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | | | - Chris Hsu
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Brian C. Searle
- Pelotonia Institute for Immuno-Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio 43210, United States
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio 43210, United States
| | - Nicholas Shulman
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Michael Riffle
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Brian Connolly
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Brendan X. MacLean
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Philip M. Remes
- Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Michael W. Senko
- Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Hamish I. Stewart
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | - Christian Hock
- Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany
| | | | - Daniel Hermanson
- Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Vlad Zabrouskov
- Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States
| | - Christine C. Wu
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
| | - Michael J. MacCoss
- Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States
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25
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Jiang Y, Salladay-Perez I, Momenzadeh A, Covarrubias AJ, Meyer JG. Simultaneous Multi-Omics Analysis by Direct Infusion Mass Spectrometry (SMAD-MS). BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.26.546628. [PMID: 37425781 PMCID: PMC10326973 DOI: 10.1101/2023.06.26.546628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Combined multi-omics analysis of proteomics, polar metabolomics, and lipidomics requires separate liquid chromatography-mass spectrometry (LC-MS) platforms for each omics layer. This requirement for different platforms limits throughput and increases costs, preventing the application of mass spectrometry-based multi-omics to large scale drug discovery or clinical cohorts. Here, we present an innovative strategy for simultaneous multi-omics analysis by direct infusion (SMAD) using one single injection without liquid chromatography. SMAD allows quantification of over 9,000 metabolite m/z features and over 1,300 proteins from the same sample in less than five minutes. We validated the efficiency and reliability of this method and then present two practical applications: mouse macrophage M1/M2 polarization and high throughput drug screening in human 293T cells. Finally, we demonstrate relationships between proteomic and metabolomic data are discovered by machine learning.
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Affiliation(s)
- Yuming Jiang
- Department of Computational Biomedicine, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
- Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
- Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Ivan Salladay-Perez
- Department of Molecular Biology, Immunology, and Molecular Genetics, University of California, Los Angeles, 90095, USA
| | - Amanda Momenzadeh
- Department of Computational Biomedicine, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
- Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
- Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Anthony J. Covarrubias
- Department of Molecular Biology, Immunology, and Molecular Genetics, University of California, Los Angeles, 90095, USA
| | - Jesse G. Meyer
- Department of Computational Biomedicine, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
- Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
- Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
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26
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Kawashima Y, Ishikawa M, Konno R, Nakajima D, Ohara O. Development of a Simple and Stable NanoESI Spray System Using Suction Wind from the MS Inlet. J Proteome Res 2023; 22:1564-1569. [PMID: 37036810 DOI: 10.1021/acs.jproteome.3c00146] [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: 04/11/2023]
Abstract
Improving the reproducibility of proteome analysis systems presents a challenge; therefore, in this study, we developed a new insertion spray ionization (InSpIon) system wherein an InSpIon tube was designed with a spray tip inserted into the tube. This system stabilized the spray and subsequently improved the reproducibility of the analysis.
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Affiliation(s)
- Yusuke Kawashima
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Masaki Ishikawa
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Ryo Konno
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Daisuke Nakajima
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Osamu Ohara
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
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Kanno T, Konno R, Miyako K, Nakajima T, Yokoyama S, Sasamoto S, Asou HK, Ohzeki J, Kawashima Y, Hasegawa Y, Ohara O, Endo Y. Characterization of proteogenomic signatures of differentiation of CD4+ T cell subsets. DNA Res 2022; 30:6964968. [PMID: 36579714 PMCID: PMC9886070 DOI: 10.1093/dnares/dsac054] [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: 09/02/2022] [Revised: 12/22/2022] [Accepted: 12/28/2022] [Indexed: 12/30/2022] Open
Abstract
Functionally distinct CD4+ helper T (Th) cell subsets, including Th1, Th2, Th17, and regulatory T cells (Treg), play a pivotal role in the regulation of acquired immunity. Although the key proteins involved in the regulation of Th cell differentiation have already been identified how the proteogenomic landscape changes during the Th cell activation remains unclear. To address this issue, we characterized proteogenomic signatures of differentiation to each Th cell subsets by RNA sequencing and liquid chromatography-assisted mass spectrometry, which enabled us to simultaneously quantify more than 10,000 protein-coding transcripts and 8,000 proteins in a single-shot. The results indicated that T cell receptor activation affected almost half of the transcript and protein levels in a low correlative and gene-specific manner, and specific cytokine treatments modified the transcript and protein profiles in a manner specific to each Th cell subsets: Th17 and Tregs particularly exhibited unique proteogenomic signatures compared to other Th cell subsets. Interestingly, the in-depth proteome data revealed that mRNA profiles alone were not enough to delineate functional changes during Th cell activation, suggesting that the proteogenomic dataset obtained in this study serves as a unique and indispensable data resource for understanding the comprehensive molecular mechanisms underlying effector Th cell differentiation.
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Affiliation(s)
| | | | - Keisuke Miyako
- Department of Applied Genomics Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Takahiro Nakajima
- Department of Frontier Research and Development, Laboratory of Medical Omics Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Satoru Yokoyama
- Department of Frontier Research and Development, Laboratory of Medical Omics Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Shigemi Sasamoto
- Department of Frontier Research and Development, Laboratory of Medical Omics Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Hikari K Asou
- Department of Frontier Research and Development, Laboratory of Medical Omics Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Junichiro Ohzeki
- Department of Frontier Research and Development, Laboratory of Medical Omics Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Yusuke Kawashima
- Department of Applied Genomics Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Yoshinori Hasegawa
- Department of Applied Genomics Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Osamu Ohara
- Department of Applied Genomics Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
| | - Yusuke Endo
- To whom correspondence should be addressed. Tel. +81-438-52-3929, Fax: +81-438-52-3954. (Y.E.)
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Makarov D, Kielkowski P. Chemical Proteomics Reveals Protein Tyrosination Extends Beyond the Alpha-Tubulins in Human Cells. Chembiochem 2022; 23:e202200414. [PMID: 36218090 PMCID: PMC10099736 DOI: 10.1002/cbic.202200414] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 10/10/2022] [Indexed: 01/25/2023]
Abstract
Tubulin detyrosination-tyrosination cycle regulates the stability of microtubules. With respect to α-tubulins, the tyrosination level is maintained by a single tubulin-tyrosine ligase (TTL). However, the precise dynamics and tubulin isoforms which undergo (de)tyrosination in neurons are unknown. Here, we exploit the substrate promiscuity of the TTL to introduce an O-propargyl-l-tyrosine to neuroblastoma cells and neurons. Mass spectrometry-based chemical proteomics in neuroblastoma cells using the O-propargyl-l-tyrosine probe revealed previously discussed tyrosination of TUBA4A, MAPRE1, and other non-tubulin proteins. This finding was further corroborated in differentiating neurons. Together we present the method for tubulin tyrosination profiling in living cells. Our results show that detyrosination-tyrosination is not restricted to α-tubulins with coded C-terminal tyrosine and is thus involved in fine-tuning of the tubulin and non-tubulin proteins during neuronal differentiation.
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Affiliation(s)
- Dmytro Makarov
- LMU München, Department of Chemistry, Institute for Chemical Epigenetics - Munich (ICEM), Würmtalstrasse 201, 81375, Munich, Germany
| | - Pavel Kielkowski
- LMU München, Department of Chemistry, Institute for Chemical Epigenetics - Munich (ICEM), Würmtalstrasse 201, 81375, Munich, Germany
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Proteotranscriptomics - A facilitator in omics research. Comput Struct Biotechnol J 2022; 20:3667-3675. [PMID: 35891789 PMCID: PMC9293588 DOI: 10.1016/j.csbj.2022.07.007] [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: 03/15/2022] [Revised: 07/04/2022] [Accepted: 07/04/2022] [Indexed: 11/26/2022] Open
Abstract
Applications in omics research, such as comparative transcriptomics and proteomics, require the knowledge of the species-specific gene sequence and benefit from a comprehensive high-quality annotation of the coding genes to achieve high coverage. While protein-coding genes can in simple cases be detected by scanning the genome for open reading frames, in more complex genomes exonic sequences are separated by introns. Despite advances in sequencing technologies that allow for ever-growing numbers of genomes, the quality of many of the provided genome assemblies do not reach reference quality. These non-contiguous assemblies with gaps and the necessity to predict splice sites limit accurate gene annotation from solely genomic data. In contrast, the transcriptome only contains transcribed gene regions, is devoid of introns and thus provides the optimal basis for the identification of open reading frames. The additional integration of proteomics data to validate predicted protein-coding genes further enriches for accurate gene models. This review outlines the principles of the proteotranscriptomics approach, discusses common challenges and suggests methods for improvement.
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