1
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Zhang S, Ghalandari B, Chen Y, Wang Q, Liu K, Sun X, Ding X, Song S, Jiang L, Ding X. Boronic Acid-Rich Lanthanide Metal-Organic Frameworks Enable Deep Proteomics with Ultratrace Biological Samples. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2401559. [PMID: 38958107 DOI: 10.1002/adma.202401559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 06/21/2024] [Indexed: 07/04/2024]
Abstract
Label-free proteomics is widely used to identify disease mechanism and potential therapeutic targets. However, deep proteomics with ultratrace clinical specimen remains a major technical challenge due to extensive contact loss during complex sample pretreatment. Here, a hybrid of four boronic acid-rich lanthanide metal-organic frameworks (MOFs) with high protein affinity is introduced to capture proteins in ultratrace samples jointly by nitrogen-boronate complexation, cation-π and ionic interactions. A MOFs Aided Sample Preparation (MASP) workflow that shrinks sample volume and integrates lysis, protein capture, protein digestion and peptide collection steps into a single PCR tube to minimize sample loss caused by non-specific absorption, is proposed further. MASP is validated to quantify ≈1800 proteins in 10 HEK-293T cells. MASP is applied to profile cerebrospinal fluid (CSF) proteome from cerebral stroke and brain damaged patients, and identified ≈3700 proteins in 1 µL CSF. MASP is further demonstrated to detect ≈9600 proteins in as few as 50 µg mouse brain tissues. MASP thus enables deep, scalable, and reproducible proteome on precious clinical samples with low abundant proteins.
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Affiliation(s)
- Shuang Zhang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Behafarid Ghalandari
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Youming Chen
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Qingwen Wang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Kun Liu
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Xinyi Sun
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Xinwen Ding
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Sunfengda Song
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Lai Jiang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Xianting Ding
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
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2
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Xie X, Truong T, Huang S, Johnston SM, Hovanski S, Robinson A, Webber KGI, Lin HJL, Mun DG, Pandey A, Kelly RT. Multicolumn Nanoflow Liquid Chromatography with Accelerated Offline Gradient Generation for Robust and Sensitive Single-Cell Proteome Profiling. Anal Chem 2024; 96:10534-10542. [PMID: 38915247 DOI: 10.1021/acs.analchem.4c00878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Peptide separations that combine high sensitivity, robustness, peak capacity, and throughput are essential for extending bottom-up proteomics to smaller samples including single cells. To this end, we have developed a multicolumn nanoLC system with offline gradient generation. One binary pump generates gradients in an accelerated fashion to support multiple analytical columns, and a single trap column interfaces with all analytical columns to reduce required maintenance and simplify troubleshooting. A high degree of parallelization is possible, as one sample undergoes separation while the next sample plus its corresponding mobile phase gradient are transferred into the storage loop and a third sample is loaded into a sample loop. Selective offline elution from the trap column into the sample loop prevents salts and hydrophobic species from entering the analytical column, thus greatly enhancing column lifetime and system robustness. With this design, samples can be analyzed as fast as every 20 min at a flow rate of just 40 nL/min with close to 100% MS utilization time and continuously for as long as several months without column replacement. We utilized the system to analyze the proteomes of single cells from a multiple myeloma cell line upon treatment with the immunomodulatory imide drug lenalidomide.
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Affiliation(s)
- Xiaofeng Xie
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
- MicrOmics Technologies, LLC, Spanish Fork, Utah 84660, United States
| | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
- MicrOmics Technologies, LLC, Spanish Fork, Utah 84660, United States
| | - Siqi Huang
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - S Madisyn Johnston
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Simon Hovanski
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Abigail Robinson
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Kei G I Webber
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Hsien-Jung L Lin
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Dong-Gi Mun
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Akhilesh Pandey
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55905, United States
- Manipal Academy of Higher Education, Manipal, Karnataka 576104, India
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
- MicrOmics Technologies, LLC, Spanish Fork, Utah 84660, United States
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3
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Montes C, Zhang J, Nolan TM, Walley JW. Single-cell proteomics differentiates Arabidopsis root cell types. THE NEW PHYTOLOGIST 2024. [PMID: 38923440 DOI: 10.1111/nph.19923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 06/09/2024] [Indexed: 06/28/2024]
Abstract
Single-cell proteomics (SCP) is an emerging approach to resolve cellular heterogeneity within complex tissues of multi-cellular organisms. Here, we demonstrate the feasibility of SCP on plant samples using the model plant Arabidopsis thaliana. Specifically, we focused on examining isolated single cells from the cortex and endodermis, which are two adjacent root cell types derived from a common stem cell lineage. From 756 root cells, we identified 3763 proteins and 1118 proteins/cell. Ultimately, we focus on 3217 proteins quantified following stringent filtering. Of these, we identified 596 proteins whose expression is enriched in either the cortex or endodermis and are able to differentiate these closely related plant cell types. Collectivity, this study demonstrates that SCP can resolve neighboring cell types with distinct functions, thereby facilitating the identification of biomarkers and candidate proteins to enable functional genomics.
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Affiliation(s)
- Christian Montes
- Department of Plant Pathology, Entomology, and Microbiology, Iowa State University, Ames, IA, 50011, USA
| | - Jingyuan Zhang
- Department of Biology, Duke University, Durham, NC, 27708, USA
| | - Trevor M Nolan
- Department of Biology, Duke University, Durham, NC, 27708, USA
- Howard Hughes Medical Institute, Duke University, Durham, NC, 27708, USA
| | - Justin W Walley
- Department of Plant Pathology, Entomology, and Microbiology, Iowa State University, Ames, IA, 50011, USA
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4
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Faktor J, Kote S, Bienkowski M, Hupp TR, Marek-Trzonkowska N. Novel FFPE proteomics method suggests prolactin induced protein as hormone induced cytoskeleton remodeling spatial biomarker. Commun Biol 2024; 7:708. [PMID: 38851810 PMCID: PMC11162451 DOI: 10.1038/s42003-024-06354-8] [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: 01/20/2023] [Accepted: 05/20/2024] [Indexed: 06/10/2024] Open
Abstract
Robotically assisted proteomics provides insights into the regulation of multiple proteins achieving excellent spatial resolution. However, developing an effective method for spatially resolved quantitative proteomics of formalin fixed paraffin embedded tissue (FFPE) in an accessible and economical manner remains challenging. We introduce non-robotic In-insert FFPE proteomics approach, combining glass insert FFPE tissue processing with spatial quantitative data-independent mass spectrometry (DIA). In-insert approach identifies 450 proteins from a 5 µm thick breast FFPE tissue voxel with 50 µm lateral dimensions covering several tens of cells. Furthermore, In-insert approach associated a keratin series and moesin (MOES) with prolactin-induced protein (PIP) indicating their prolactin and/or estrogen regulation. Our data suggest that PIP is a spatial biomarker for hormonally triggered cytoskeletal remodeling, potentially useful for screening hormonally affected hotspots in breast tissue. In-insert proteomics represents an alternative FFPE processing method, requiring minimal laboratory equipment and skills to generate spatial proteotype repositories from FFPE tissue.
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Affiliation(s)
- Jakub Faktor
- International Centre for Cancer Vaccine Science, University of Gdansk, Kladki 24, 80-822, Gdansk, Poland.
| | - Sachin Kote
- International Centre for Cancer Vaccine Science, University of Gdansk, Kladki 24, 80-822, Gdansk, Poland.
| | - Michal Bienkowski
- Medical University of Gdansk, University of Gdansk, Mariana Smoluchowskiego 17, 80-214, Gdansk, Poland
| | - Ted R Hupp
- International Centre for Cancer Vaccine Science, University of Gdansk, Kladki 24, 80-822, Gdansk, Poland
| | - Natalia Marek-Trzonkowska
- International Centre for Cancer Vaccine Science, University of Gdansk, Kladki 24, 80-822, Gdansk, Poland
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5
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Tan YC, Low TY, Lee PY, Lim LC. Single-cell proteomics by mass spectrometry: Advances and implications in cancer research. Proteomics 2024; 24:e2300210. [PMID: 38727198 DOI: 10.1002/pmic.202300210] [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: 05/05/2023] [Revised: 02/22/2024] [Accepted: 04/29/2024] [Indexed: 06/16/2024]
Abstract
Cancer harbours extensive proteomic heterogeneity. Inspired by the prior success of single-cell RNA sequencing (scRNA-seq) in characterizing minute transcriptomics heterogeneity in cancer, researchers are now actively searching for information regarding the proteomics counterpart. Therefore recently, single-cell proteomics by mass spectrometry (SCP) has rapidly developed into state-of-the-art technology to cater the need. This review aims to summarize application of SCP in cancer research, while revealing current development progress of SCP technology. The review also aims to contribute ideas into research gaps and future directions, ultimately promoting the application of SCP in cancer research.
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Affiliation(s)
- Yong Chiang Tan
- School of Postgraduate Studies, International Medical University, Kuala Lumpur, Malaysia
| | - Teck Yew Low
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Pey Yee Lee
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Lay Cheng Lim
- Department of Life Sciences, School of Pharmacy, International Medical University, Kuala Lumpur, Malaysia
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6
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Yang Z, Jin K, Chen Y, Liu Q, Chen H, Hu S, Wang Y, Pan Z, Feng F, Shi M, Xie H, Ma H, Zhou H. AM-DMF-SCP: Integrated Single-Cell Proteomics Analysis on an Active Matrix Digital Microfluidic Chip. JACS AU 2024; 4:1811-1823. [PMID: 38818059 PMCID: PMC11134390 DOI: 10.1021/jacsau.4c00027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 03/08/2024] [Accepted: 03/08/2024] [Indexed: 06/01/2024]
Abstract
Single-cell proteomics offers unparalleled insights into cellular diversity and molecular mechanisms, enabling a deeper understanding of complex biological processes at the individual cell level. Here, we develop an integrated sample processing on an active-matrix digital microfluidic chip for single-cell proteomics (AM-DMF-SCP). Employing the AM-DMF-SCP approach and data-independent acquisition (DIA), we identify an average of 2258 protein groups in single HeLa cells within 15 min of the liquid chromatography gradient. We performed comparative analyses of three tumor cell lines: HeLa, A549, and HepG2, and machine learning was utilized to identify the unique features of these cell lines. Applying the AM-DMF-SCP to characterize the proteomes of a third-generation EGFR inhibitor, ASK120067-resistant cells (67R) and their parental NCI-H1975 cells, we observed a potential correlation between elevated VIM expression and 67R resistance, which is consistent with the findings from bulk sample analyses. These results suggest that AM-DMF-SCP is an automated, robust, and sensitive platform for single-cell proteomics and demonstrate the potential for providing valuable insights into cellular mechanisms.
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Affiliation(s)
- Zhicheng Yang
- Department
of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai
Institute of Materia Medica, Chinese Academy
of Sciences, Shanghai 201203, China
- University
of the Chinese Academy of Sciences, Beijing 100049, China
| | - Kai Jin
- CAS
Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical
Engineering and Technology, Chinese Academy
of Sciences, Suzhou 215163, China
| | - Yimin Chen
- Department
of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai
Institute of Materia Medica, Chinese Academy
of Sciences, Shanghai 201203, China
- University
of the Chinese Academy of Sciences, Beijing 100049, China
| | - Qian Liu
- Department
of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai
Institute of Materia Medica, Chinese Academy
of Sciences, Shanghai 201203, China
| | - Hongxu Chen
- School
of Chinese Materia Medica, Nanjing University
of Chinese Medicine, 138 Xianlin Avenue, Nanjing, Jiangsu 210023, China
| | - Siyi Hu
- CAS
Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical
Engineering and Technology, Chinese Academy
of Sciences, Suzhou 215163, China
| | - Yuqiu Wang
- Department
of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai
Institute of Materia Medica, Chinese Academy
of Sciences, Shanghai 201203, China
| | - Zilu Pan
- Division
of Antitumor Pharmacology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Fang Feng
- Division
of Antitumor Pharmacology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Mude Shi
- Guangdong
ACXEL Micro & Nano Tech Co. Ltd., Foshan, Guangdong Province 528000, China
| | - Hua Xie
- University
of the Chinese Academy of Sciences, Beijing 100049, China
- Zhongshan
Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Zhongshan 528400, China
- Division
of Antitumor Pharmacology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Hanbin Ma
- CAS
Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical
Engineering and Technology, Chinese Academy
of Sciences, Suzhou 215163, China
- Guangdong
ACXEL Micro & Nano Tech Co. Ltd., Foshan, Guangdong Province 528000, China
| | - Hu Zhou
- Department
of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai
Institute of Materia Medica, Chinese Academy
of Sciences, Shanghai 201203, China
- University
of the Chinese Academy of Sciences, Beijing 100049, China
- Hangzhou
Institute for Advanced Study, University
of Chinese Academy of Sciences, Hangzhou 310024, China
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7
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Peters-Clarke TM, Coon JJ, Riley NM. Instrumentation at the Leading Edge of Proteomics. Anal Chem 2024; 96:7976-8010. [PMID: 38738990 DOI: 10.1021/acs.analchem.3c04497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2024]
Affiliation(s)
- Trenton M Peters-Clarke
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Joshua J Coon
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Morgridge Institute for Research, Madison, Wisconsin 53715, United States
| | - Nicholas M Riley
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
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8
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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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9
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Truong T, Kelly RT. What's new in single-cell proteomics. Curr Opin Biotechnol 2024; 86:103077. [PMID: 38359605 PMCID: PMC11068367 DOI: 10.1016/j.copbio.2024.103077] [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: 10/27/2023] [Accepted: 01/19/2024] [Indexed: 02/17/2024]
Abstract
In recent years, single-cell proteomics (SCP) has advanced significantly, enabling the analysis of thousands of proteins within single mammalian cells. This progress is driven by advances in experimental design, with maturing label-free and multiplexed methods, optimized sample preparation, and innovations in separation techniques, including ultra-low-flow nanoLC. These factors collectively contribute to improved sensitivity, throughput, and reproducibility. Cutting-edge mass spectrometry platforms and data acquisition approaches continue to play a critical role in enhancing data quality. Furthermore, the exploration of spatial proteomics with single-cell resolution offers significant promise for understanding cellular interactions, giving rise to various phenotypes. SCP has far-reaching applications in cancer research, biomarker discovery, and developmental biology. Here, we provide a critical review of recent advances in the field of SCP.
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Affiliation(s)
- Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, United States
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, United States.
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10
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Lin A, Ramaswamy Y, Misra A. Developmental heterogeneity of vascular cells: Insights into cellular plasticity in atherosclerosis? Semin Cell Dev Biol 2024; 155:3-15. [PMID: 37316416 DOI: 10.1016/j.semcdb.2023.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 05/30/2023] [Accepted: 06/06/2023] [Indexed: 06/16/2023]
Abstract
Smooth muscle cells, endothelial cells and macrophages display remarkable heterogeneity within the healthy vasculature and under pathological conditions. During development, these cells arise from numerous embryological origins, which confound with different microenvironments to generate postnatal vascular cell diversity. In the atherosclerotic plaque milieu, all these cell types exhibit astonishing plasticity, generating a variety of plaque burdening or plaque stabilizing phenotypes. And yet how developmental origin influences intraplaque cell plasticity remains largely unexplored despite evidence suggesting this may be the case. Uncovering the diversity and plasticity of vascular cells is being revolutionized by unbiased single cell whole transcriptome analysis techniques that will likely continue to pave the way for therapeutic research. Cellular plasticity is only just emerging as a target for future therapeutics, and uncovering how intraplaque plasticity differs across vascular beds may provide key insights into why different plaques behave differently and may confer different risks of subsequent cardiovascular events.
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Affiliation(s)
- Alexander Lin
- Atherosclerosis and Vascular Remodeling Group, Heart Research Institute, Sydney, NSW, Australia; School of Biomedical Engineering, Faculty of Engineering, The University of Sydney, Sydney, NSW, Australia
| | - Yogambha Ramaswamy
- School of Biomedical Engineering, Faculty of Engineering, The University of Sydney, Sydney, NSW, Australia
| | - Ashish Misra
- Atherosclerosis and Vascular Remodeling Group, Heart Research Institute, Sydney, NSW, Australia; Heart Research Institute, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
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11
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Wang Y, Guan ZY, Shi SW, Jiang YR, Zhang J, Yang Y, Wu Q, Wu J, Chen JB, Ying WX, Xu QQ, Fan QX, Wang HF, Zhou L, Wang L, Fang J, Pan JZ, Fang Q. Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell. Nat Commun 2024; 15:1279. [PMID: 38341466 PMCID: PMC10858870 DOI: 10.1038/s41467-024-45659-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Accepted: 01/29/2024] [Indexed: 02/12/2024] Open
Abstract
The shotgun proteomic analysis is currently the most promising single-cell protein sequencing technology, however its identification level of ~1000 proteins per cell is still insufficient for practical applications. Here, we develop a pick-up single-cell proteomic analysis (PiSPA) workflow to achieve a deep identification capable of quantifying up to 3000 protein groups in a mammalian cell using the label-free quantitative method. The PiSPA workflow is specially established for single-cell samples mainly based on a nanoliter-scale microfluidic liquid handling robot, capable of achieving single-cell capture, pretreatment and injection under the pick-up operation strategy. Using this customized workflow with remarkable improvement in protein identification, 2449-3500, 2278-3257 and 1621-2904 protein groups are quantified in single A549 cells (n = 37), HeLa cells (n = 44) and U2OS cells (n = 27) under the DIA (MBR) mode, respectively. Benefiting from the flexible cell picking-up ability, we study HeLa cell migration at the single cell proteome level, demonstrating the potential in practical biological research from single-cell insight.
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Affiliation(s)
- Yu Wang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
- College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China
| | - Zhi-Ying Guan
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Shao-Wen Shi
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
| | - Yi-Rong Jiang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Jie Zhang
- Department of Cell Biology, China Medical University, Shenyang, 110122, China
| | - Yi Yang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
| | - Qiong Wu
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Jie Wu
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Jian-Bo Chen
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Wei-Xin Ying
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Qin-Qin Xu
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Qian-Xi Fan
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Hui-Feng Wang
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
| | - Li Zhou
- Shanghai Omicsolution Co., Shanghai, 201100, China
| | - Ling Wang
- Shanghai Omicsolution Co., Shanghai, 201100, China
| | - Jin Fang
- Department of Cell Biology, China Medical University, Shenyang, 110122, China
| | - Jian-Zhang Pan
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
| | - Qun Fang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China.
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China.
- Key Laboratory of Excited-State Materials of Zhejiang Province, Zhejiang University, Hangzhou, 310007, China.
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12
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Williams OHL, Rusli O, Ezzedinloo L, Dodgen TM, Clegg JK, Rijs NJ. Automated Structural Activity Screening of β-Diketonate Assemblies with High-Throughput Ion Mobility-Mass Spectrometry. Angew Chem Int Ed Engl 2024; 63:e202313892. [PMID: 38012094 DOI: 10.1002/anie.202313892] [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: 11/08/2023] [Accepted: 11/27/2023] [Indexed: 11/29/2023]
Abstract
Embracing complexity in design, metallo-supramolecular self-assembly presents an opportunity for fabricating materials of economic significance. The array of accessible supramolecules is alluring, along with favourable energy requirements. Implementation is hampered by an inability to efficiently characterise complex mixtures. The stoichiometry, size, shape, guest binding properties and reactivity of individual components and combinations thereof are inherently challenging to resolve. A large combinatorial library of four transition metals (Fe, Cu, Ni and Zn), and six β-diketonate ligands at different molar ratios and pH was robotically prepared and directly analysed over multiple timepoints with electrospray ionisation travelling wave ion mobility-mass spectrometry. The dataset was parsed for self-assembling activity without first attempting to structurally assign individual species. Self-assembling systems were readily categorised without manual data-handling, allowing efficient screening of self-assembly activity. This workflow clarifies solution phase supramolecular assembly processes without manual, bottom-up processing. The complex behaviour of the self-assembling systems was reduced to simpler qualities, which could be automatically processed.
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Affiliation(s)
| | - Olivia Rusli
- School of Chemistry, UNSW Sydney, Sydney, NSW, 2052, Australia
| | - Lida Ezzedinloo
- School of Chemistry, UNSW Sydney, Sydney, NSW, 2052, Australia
| | - Tyren M Dodgen
- Waters Corporation Australia, Rydalmere, NSW, 2116, Australia
| | - Jack K Clegg
- School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Queensland, 4072, Australia
| | - Nicole J Rijs
- School of Chemistry, UNSW Sydney, Sydney, NSW, 2052, Australia
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13
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Truong T, Sanchez-Avila X, Webber KGI, Johnston SM, Kelly RT. Efficient and Sensitive Sample Preparation, Separations, and Data Acquisition for Label-Free Single-Cell Proteomics. Methods Mol Biol 2024; 2817:67-84. [PMID: 38907148 DOI: 10.1007/978-1-0716-3934-4_7] [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] [Indexed: 06/23/2024]
Abstract
We describe a sensitive and efficient workflow for label-free single-cell proteomics that spans sample preparation, liquid chromatography separations, and mass spectrometry data acquisition. The Tecan Uno Single Cell Dispenser provides rapid cell isolation and nanoliter-volume reagent dispensing within 384-well PCR plates. A newly developed sample processing workflow achieves cell lysis, protein denaturation, and digestion in 1 h with a single reagent dispensing step. Low-flow liquid chromatography coupled with wide-window data-dependent acquisition results in the quantification of nearly 3000 proteins per cell using an Orbitrap Exploris 480 mass spectrometer. This approach greatly broadens accessibility to sensitive single-cell proteome profiling for nonspecialist laboratories.
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Affiliation(s)
- Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA
| | - Ximena Sanchez-Avila
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA
| | - Kei G I Webber
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA
| | - S Madisyn Johnston
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA.
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14
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Grégoire S, Vanderaa C, Dit Ruys SP, Kune C, Mazzucchelli G, Vertommen D, Gatto L. Standardized Workflow for Mass-Spectrometry-Based Single-Cell Proteomics Data Processing and Analysis Using the scp Package. Methods Mol Biol 2024; 2817:177-220. [PMID: 38907155 DOI: 10.1007/978-1-0716-3934-4_14] [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] [Indexed: 06/23/2024]
Abstract
Mass-spectrometry (MS)-based single-cell proteomics (SCP) explores cellular heterogeneity by focusing on the functional effectors of the cells-proteins. However, extracting meaningful biological information from MS data is far from trivial, especially with single cells. Currently, data analysis workflows are substantially different from one research team to another. Moreover, it is difficult to evaluate pipelines as ground truths are missing. Our team has developed the R/Bioconductor package called scp to provide a standardized framework for SCP data analysis. It relies on the widely used QFeatures and SingleCellExperiment data structures. In addition, we used a design containing cell lines mixed in known proportions to generate controlled variability for data analysis benchmarking. In this chapter, we provide a flexible data analysis protocol for SCP data using the scp package together with comprehensive explanations at each step of the processing. Our main steps are quality control on the feature and cell level, aggregation of the raw data into peptides and proteins, normalization, and batch correction. We validate our workflow using our ground truth data set. We illustrate how to use this modular, standardized framework and highlight some crucial steps.
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Affiliation(s)
- Samuel Grégoire
- Computational Biology and Bioinformatics Unit, de Duve Institute, UCLouvain, Brussels, Belgium
| | - Christophe Vanderaa
- Computational Biology and Bioinformatics Unit, de Duve Institute, UCLouvain, Brussels, Belgium
| | | | - Christopher Kune
- Laboratory of Mass Spectrometry, MolSys Research Unit, University of Liège, Liège, Belgium
| | - Gabriel Mazzucchelli
- Laboratory of Mass Spectrometry, MolSys Research Unit, University of Liège, Liège, Belgium
- GIGA Proteomics Facility, University of Liège, Liège, Belgium
| | - Didier Vertommen
- Protein Phosphorylation Unit, de Duve Institute, UCLouvain, Brussels, Belgium
| | - Laurent Gatto
- Computational Biology and Bioinformatics Unit, de Duve Institute, UCLouvain, Brussels, Belgium.
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15
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Yang Y, Tian R. Fully Integrated Online Strategy for Highly Sensitive Proteome Profiling. Methods Mol Biol 2024; 2817:57-65. [PMID: 38907147 DOI: 10.1007/978-1-0716-3934-4_6] [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] [Indexed: 06/23/2024]
Abstract
Low-input proteomics, which treats tens to hundreds of mammalian cells, is the gap between standard proteomics and single-cell proteomics. Low-input proteomics is widely applicable and needs special sample preparation methods to achieve deep proteome profiling. This chapter describes protocols for the preparation and application of an easy-to-use and scalable device for processing low-input samples. Protein preconcentration, impurity removal, reduction, alkylation, digestion, and desalting are fully integrated into this workflow, and the device can be directly connected to online nanoLC-MS to avoid sample transfer.
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Affiliation(s)
- Yun Yang
- International Academy of Phronesis Medicine (Guang Dong), Guangzhou, China
- South China Institute of Biomedicine, Guangzhou, China
| | - Ruijun Tian
- Department of Chemistry, School of Science, Southern University of Science and Technology, Shenzhen, China.
- Research Center for Chemical Biology and Omics Analysis, School of Science, Southern University of Science and Technology, Shenzhen, China.
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16
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Xu Z, Zou R, Horn NC, Kitata RB, Shi T. Robust Surfactant-Assisted One-Pot Sample Preparation for Label-Free Single-Cell and Nanoscale Proteomics. Methods Mol Biol 2024; 2817:85-96. [PMID: 38907149 DOI: 10.1007/978-1-0716-3934-4_8] [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: 06/23/2024]
Abstract
With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk cells. However, such bulk measurement obscures cell-to-cell heterogeneity, precluding proteome profiling of single cells and small numbers of cells of interest. To address this issue, in the recent 5 years, there has been a surge of small sample preparation methods developed for robust and effective collection and processing of single cells and small numbers of cells for in-depth MS-based proteome profiling. Based on their broad accessibility, they can be categorized into two types: methods based on specific devices and those based on standard PCR tubes or multi-well plates. In this chapter, we describe the detailed protocol of our recently developed, easily adoptable, Surfactant-assisted One-Pot (SOP) sample preparation coupled with MS method termed SOP-MS for label-free single-cell and nanoscale proteomics. SOP-MS capitalizes on the combination of an MS-compatible surfactant, n-dodecyl-β-D-maltoside (DDM), and standard low-bind PCR tube or multi-well plate for "all-in-one" one-pot sample preparation without sample transfer. With its robust and convenient features, SOP-MS can be readily implemented in any MS laboratory for single-cell and nanoscale proteomics. With further improvements in MS detection sensitivity and sample throughput, we believe that SOP-MS could open an avenue for single-cell proteomics with broad applicability in biological and biomedical research.
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Affiliation(s)
- Zhangyang Xu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Rongge Zou
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Nina C Horn
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Reta Birhanu Kitata
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Tujin Shi
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
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17
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Pade LR, Stepler KE, Portero EP, DeLaney K, Nemes P. Biological mass spectrometry enables spatiotemporal 'omics: From tissues to cells to organelles. MASS SPECTROMETRY REVIEWS 2024; 43:106-138. [PMID: 36647247 PMCID: PMC10668589 DOI: 10.1002/mas.21824] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 09/14/2022] [Accepted: 09/17/2022] [Indexed: 06/17/2023]
Abstract
Biological processes unfold across broad spatial and temporal dimensions, and measurement of the underlying molecular world is essential to their understanding. Interdisciplinary efforts advanced mass spectrometry (MS) into a tour de force for assessing virtually all levels of the molecular architecture, some in exquisite detection sensitivity and scalability in space-time. In this review, we offer vignettes of milestones in technology innovations that ushered sample collection and processing, chemical separation, ionization, and 'omics analyses to progressively finer resolutions in the realms of tissue biopsies and limited cell populations, single cells, and subcellular organelles. Also highlighted are methodologies that empowered the acquisition and analysis of multidimensional MS data sets to reveal proteomes, peptidomes, and metabolomes in ever-deepening coverage in these limited and dynamic specimens. In pursuit of richer knowledge of biological processes, we discuss efforts pioneering the integration of orthogonal approaches from molecular and functional studies, both within and beyond MS. With established and emerging community-wide efforts ensuring scientific rigor and reproducibility, spatiotemporal MS emerged as an exciting and powerful resource to study biological systems in space-time.
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Affiliation(s)
- Leena R. Pade
- Department of Chemistry & Biochemistry, University of Maryland, 8051 Regents Drive, College Park, MD 20742
| | - Kaitlyn E. Stepler
- Department of Chemistry & Biochemistry, University of Maryland, 8051 Regents Drive, College Park, MD 20742
| | - Erika P. Portero
- Department of Chemistry & Biochemistry, University of Maryland, 8051 Regents Drive, College Park, MD 20742
| | - Kellen DeLaney
- Department of Chemistry & Biochemistry, University of Maryland, 8051 Regents Drive, College Park, MD 20742
| | - Peter Nemes
- Department of Chemistry & Biochemistry, University of Maryland, 8051 Regents Drive, College Park, MD 20742
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18
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Zheng R, Matzinger M, Mayer RL, Valenta A, Sun X, Mechtler K. A High-Sensitivity Low-Nanoflow LC-MS Configuration for High-Throughput Sample-Limited Proteomics. Anal Chem 2023; 95:18673-18678. [PMID: 38088903 PMCID: PMC10753523 DOI: 10.1021/acs.analchem.3c03058] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 11/16/2023] [Accepted: 11/21/2023] [Indexed: 12/27/2023]
Abstract
This work demonstrates the utility of high-throughput nanoLC-MS and label-free quantification (LFQ) for sample-limited bottom-up proteomics analysis, including single-cell proteomics (SCP). Conditions were optimized on a 50 μm internal diameter (I.D.) column operated at 100 nL/min in the direct injection workflow to balance method sensitivity and sample throughput from 24 to 72 samples/day. Multiple data acquisition strategies were also evaluated for proteome coverage, including data-dependent acquisition (DDA), wide-window acquisition (WWA), and wide-window data-independent acquisition (WW-DIA). Analyzing 250 pg HeLa digest with a 10-min LC gradient (72 samples/day) provided >900, >1,800, and >3,000 protein group identifications for DDA, WWA, and WW-DIA, respectively. Total method cycle time was further reduced from 20 to 14.4 min (100 samples/day) by employing a trap-and-elute workflow, enabling 70% mass spectrometer utilization. The method was applied to library-free DIA analysis of single-cell samples, yielding >1,700 protein groups identified. In conclusion, this study provides a high-sensitivity, high-throughput nanoLC-MS configuration for sample-limited proteomics.
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Affiliation(s)
- Runsheng Zheng
- Thermo
Fisher Scientific, Dornier Str. 4, 82110 Germering, Germany
| | - Manuel Matzinger
- IMP—Institute
of Molecular Pathology, Campus-Vienna-Biocenter 1, A-1030 Vienna, Austria
| | - Rupert L. Mayer
- IMP—Institute
of Molecular Pathology, Campus-Vienna-Biocenter 1, A-1030 Vienna, Austria
| | - Alec Valenta
- Thermo
Fisher Scientific, Dornier Str. 4, 82110 Germering, Germany
| | - Xuefei Sun
- Thermo
Fisher Scientific, 1228 Titan Way, Sunnyvale, California 94085, United States
| | - Karl Mechtler
- IMP—Institute
of Molecular Pathology, Campus-Vienna-Biocenter 1, A-1030 Vienna, Austria
- IMBA—Institute
of Molecular Biotechnology of the Austrian Academy of Sciences, Dr. Bohr Gasse 3, A-1030 Vienna, Austria
- Gregor
Mendel Institute of Molecular Plant Biology of the Austrian Academy
of Sciences, Dr. Bohr
Gasse 3, A-1030 Vienna, Austria
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19
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Mayer RL, Mechtler K. Immunopeptidomics in the Era of Single-Cell Proteomics. BIOLOGY 2023; 12:1514. [PMID: 38132340 PMCID: PMC10740491 DOI: 10.3390/biology12121514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/04/2023] [Accepted: 12/06/2023] [Indexed: 12/23/2023]
Abstract
Immunopeptidomics, as the analysis of antigen peptides being presented to the immune system via major histocompatibility complexes (MHC), is being seen as an imperative tool for identifying epitopes for vaccine development to treat cancer and viral and bacterial infections as well as parasites. The field has made tremendous strides over the last 25 years but currently still faces challenges in sensitivity and throughput for widespread applications in personalized medicine and large vaccine development studies. Cutting-edge technological advancements in sample preparation, liquid chromatography as well as mass spectrometry, and data analysis, however, are currently transforming the field. This perspective showcases how the advent of single-cell proteomics has accelerated this transformation of immunopeptidomics in recent years and will pave the way for even more sensitive and higher-throughput immunopeptidomics analyses.
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Affiliation(s)
- Rupert L. Mayer
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter, 1030 Vienna, Austria
| | - Karl Mechtler
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter, 1030 Vienna, Austria
- Gregor Mendel Institute of Molecular Plant Biology (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC), 1030 Vienna, Austria
- Institute of Molecular Biotechnology (IMBA), Austrian Academy of Sciences, Vienna BioCenter (VBC), 1030 Vienna, Austria
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20
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Leduc A, Koury L, Cantlon J, Slavov N. Massively parallel sample preparation for multiplexed single-cell proteomics using nPOP. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.27.568927. [PMID: 38076795 PMCID: PMC10705290 DOI: 10.1101/2023.11.27.568927] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Single-cell proteomics by mass spectrometry (MS) allows quantifying proteins with high specificity and sensitivity. To increase its throughput, we developed nPOP, a method for parallel preparation of thousands of single cells in nanoliter volume droplets deposited on glass slides. Here, we describe its protocol with emphasis on its flexibility to prepare samples for different multiplexed MS methods. An implementation with plexDIA demonstrates accurate quantification of about 3,000 - 3,700 proteins per human cell. The protocol is implemented on the CellenONE instrument and uses readily available consumables, which should facilitate broad adoption. nPOP can be applied to all samples that can be processed to a single-cell suspension. It takes 1 or 2 days to prepare over 3,000 single cells. We provide metrics and software for quality control that can support the robust scaling of nPOP to higher plex reagents for achieving reliable high-throughput single-cell protein analysis.
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Affiliation(s)
- Andrew Leduc
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA 02115, USA
| | - Luke Koury
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA 02115, USA
| | | | - Nikolai Slavov
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA 02115, USA
- Parallel Squared Technology Institute, Watertown, MA 02472, USA
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21
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Zhang S, Ghalandari B, Wang A, Li S, Chen Y, Wang Q, Jiang L, Ding X. Superparamagnetic Composite Nanobeads Anchored with Molecular Glues for Ultrasensitive Label-free Proteomics. Angew Chem Int Ed Engl 2023; 62:e202309806. [PMID: 37653561 DOI: 10.1002/anie.202309806] [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: 07/12/2023] [Revised: 08/31/2023] [Accepted: 08/31/2023] [Indexed: 09/02/2023]
Abstract
Mass spectrometry has emerged as a mainstream technique for label-free proteomics. However, proteomic coverage for trace samples is constrained by adsorption loss during repeated elution at sample pretreatment. Here, we demonstrated superparamagnetic composite nanoparticles functionalized with molecular glues (MGs) to enrich proteins in trace human biofluid. We showed high protein binding (>95 %) and recovery (≈90 %) rates by anchor-nanoparticles. We further proposed a Streamlined Workflow based on Anchor-nanoparticles for Proteomics (SWAP) method that enabled unbiased protein capture, protein digestion and pure peptides elution in one single tube. We demonstrated SWAP to quantify over 2500 protein groups with 100 HEK 293T cells. We adopted SWAP to profile proteomics with trace aqueous humor samples from cataract (n=15) and wet age-related macular degeneration (n=8) patients, and quantified ≈1400 proteins from 5 μL aqueous humor. SWAP simplifies sample preparation steps, minimizes adsorption loss and improves protein coverage for label-free proteomics with previous trace samples.
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Affiliation(s)
- Shuang Zhang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Behafarid Ghalandari
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Aiting Wang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Sijie Li
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Youming Chen
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Qingwen Wang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Lai Jiang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Xianting Ding
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
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22
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Li J, Huang L, Guo Y, Cupp-Sutton KA, Wu S. An automated spray-capillary platform for the microsampling and CE-MS analysis of picoliter- and nanoliter-volume samples. Anal Bioanal Chem 2023; 415:6961-6973. [PMID: 37581707 PMCID: PMC10843549 DOI: 10.1007/s00216-023-04870-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 07/01/2023] [Accepted: 07/04/2023] [Indexed: 08/16/2023]
Abstract
Capillary electrophoresis mass spectrometry (CE-MS) is an emerging analytical tool for microscale biological sample analysis that offers high separation resolution, low detection limit, and low sample consumption. We recently developed a novel microsampling device, "spray-capillary," for quantitative low-volume sample extraction (as low as 15 pL/s) and online CE-MS analysis. This platform can efficiently analyze picoliter samples (e.g., single cells) with minimal sample loss and no additional offline sample-handling steps. However, our original spray-capillary-based experiments required manual manipulation of the sample inlet for sample collection and separation, which is time consuming and requires proficiency in device handling. To optimize the performance of spray-capillary CE-MS analysis, we developed an automated platform for robust, high-throughput analysis of picoliter samples using a commercially available CE autosampler. Our results demonstrated high reproducibility among 50 continuous runs using the standard peptide angiotensin II (Ang II), with an RSD of 14.70% and 0.62% with respect to intensity and elution time, respectively. We also analyzed Ang II using varying injection times to evaluate the capability of the spray-capillary to perform quantitative sampling and found high linearity for peptide intensity with respect to injection time (R2 > 0.99). These results demonstrate the capability of the spray-capillary sampling platform for high-throughput quantitative analysis of low-volume, low-complexity samples using pressure elution (e.g., direct injection). To further evaluate and optimize the automated spray-capillary platform to analyze complex biological samples, we performed online CE-MS analysis on Escherichia coli lysate digest spiked with Ang II using varying injection times. We maintained high linearity of intensity with respect to injection time for Ang II and E. coli peptides (R2 > 0.97 in all cases). Furthermore, we observed good CE separation and high reproducibility between automated runs. Overall, we demonstrated that the automated spray-capillary CE-MS platform can efficiently and reproducibly sample picoliter and nanoliter biological samples for high-throughput proteomics analysis.
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Affiliation(s)
- Jiaxue Li
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Room 2210, Norman, OK, 73019, USA
| | - Lushuang Huang
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Room 2210, Norman, OK, 73019, USA
| | - Yanting Guo
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Room 2210, Norman, OK, 73019, USA
| | - Kellye A Cupp-Sutton
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Room 2210, Norman, OK, 73019, USA.
| | - Si Wu
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Room 2210, Norman, OK, 73019, USA.
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23
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Chan C, Peng J, Rajesh V, Scott EY, Sklavounos AA, Faiz M, Wheeler AR. Digital Microfluidics for Microproteomic Analysis of Minute Mammalian Tissue Samples Enabled by a Photocleavable Surfactant. J Proteome Res 2023; 22:3242-3253. [PMID: 37651704 DOI: 10.1021/acs.jproteome.3c00281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
Proteome profiles of precious tissue samples have great clinical potential for accelerating disease biomarker discovery and promoting novel strategies for early diagnosis and treatment. However, tiny clinical tissue samples are often difficult to handle and analyze with conventional proteomic methods. Automated digital microfluidic (DMF) workflows facilitate the manipulation of size-limited tissue samples. Here, we report the assessment of a DMF microproteomics workflow enabled by a photocleavable surfactant for proteomic analysis of minute tissue samples. The surfactant 4-hexylphenylazosulfonate (Azo) was found to facilitate fast droplet movement on DMF and enhance the proteomics analysis. Comparisons of Azo and n-Dodecyl β-d-maltoside (DDM) using small samples of HeLa digest standards and MCF-7 cell digests revealed distinct differences at the peptide level despite similar results at the protein level. The DMF microproteomics workflow was applied for the sample preparation of ∼3 μg biopsies from murine brain tissue. A total of 1969 proteins were identified in three samples, including established neural biomarkers and proteins related to synaptic signaling. Going forward, we propose that the Azo-enabled DMF workflow has the potential to advance the practical clinical application of DMF for the analysis of size-limited tissue samples.
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Affiliation(s)
- Calvin Chan
- Department of Chemistry, University of Toronto, Toronto M5S 3H6, Ontario, Canada
| | - Jiaxi Peng
- Department of Chemistry, University of Toronto, Toronto M5S 3H6, Ontario, Canada
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto M5S 3E1, Ontario, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto M5S 3G9, Ontario, Canada
| | - Vigneshwar Rajesh
- Department of Chemistry, University of Toronto, Toronto M5S 3H6, Ontario, Canada
| | - Erica Y Scott
- Department of Chemistry, University of Toronto, Toronto M5S 3H6, Ontario, Canada
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto M5S 3E1, Ontario, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto M5S 3G9, Ontario, Canada
- Department of Surgery, University of Toronto, Toronto M5S 1A8, Ontario, Canada
| | - Alexandros A Sklavounos
- Department of Chemistry, University of Toronto, Toronto M5S 3H6, Ontario, Canada
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto M5S 3E1, Ontario, Canada
| | - Maryam Faiz
- Department of Surgery, University of Toronto, Toronto M5S 1A8, Ontario, Canada
| | - Aaron R Wheeler
- Department of Chemistry, University of Toronto, Toronto M5S 3H6, Ontario, Canada
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto M5S 3E1, Ontario, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto M5S 3G9, Ontario, Canada
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24
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Sanchez-Avila X, Truong T, Xie X, Webber KGI, Johnston SM, Lin HJL, Axtell NB, Puig-Sanvicens V, Kelly RT. Easy and Accessible Workflow for Label-Free Single-Cell Proteomics. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2374-2380. [PMID: 37594399 PMCID: PMC11002963 DOI: 10.1021/jasms.3c00240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/19/2023]
Abstract
Single-cell proteomics (SCP) can provide information that is unattainable through either bulk-scale protein measurements or single-cell profiling of other omes. Maximizing proteome coverage often requires custom instrumentation, consumables, and reagents for sample processing and separations, which has limited the accessibility of SCP to a small number of specialized laboratories. Commercial platforms have become available for SCP cell isolation and sample preparation, but the high cost of these platforms and the technical expertise required for their operation place them out of reach of many interested laboratories. Here, we assessed the new HP D100 Single Cell Dispenser for label-free SCP. The low-cost instrument proved highly accurate and reproducible for dispensing reagents in the range from 200 nL to 2 μL. We used the HP D100 to isolate and prepare single cells for SCP within 384-well PCR plates. When the well plates were immediately centrifuged following cell dispensing and again after reagent dispensing, we found that ∼97% of wells that were identified in the instrument software as containing a single cell indeed provided the proteome coverage expected of a single cell. This commercial dispenser combined with one-step sample processing provides a very rapid and easy-to-use workflow for SCP with no reduction in proteome coverage relative to a nanowell-based workflow, and the commercial well plates also facilitate autosampling with unmodified instrumentation. Single-cell samples were analyzed using home-packed 30 μm i.d. nanoLC columns as well as commercially available 50 μm i.d. columns. The commercial columns resulted in ∼35% fewer identified proteins. However, combined with the well plate-based preparation platform, the presented workflow provides a fully commercial and relatively low-cost alternative for SCP sample preparation and separation, which should greatly broaden the accessibility of SCP to other laboratories.
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Affiliation(s)
- Ximena Sanchez-Avila
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Xiaofeng Xie
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Kei G I Webber
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - S Madisyn Johnston
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Hsien-Jung L Lin
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Nathaniel B Axtell
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | | | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
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25
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Thielert M, Itang ECM, Ammar C, Rosenberger FA, Bludau I, Schweizer L, Nordmann TM, Skowronek P, Wahle M, Zeng W, Zhou X, Brunner A, Richter S, Levesque MP, Theis FJ, Steger M, Mann M. Robust dimethyl-based multiplex-DIA doubles single-cell proteome depth via a reference channel. Mol Syst Biol 2023; 19:e11503. [PMID: 37602975 PMCID: PMC10495816 DOI: 10.15252/msb.202211503] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 07/17/2023] [Accepted: 07/25/2023] [Indexed: 08/22/2023] Open
Abstract
Single-cell proteomics aims to characterize biological function and heterogeneity at the level of proteins in an unbiased manner. It is currently limited in proteomic depth, throughput, and robustness, which we address here by a streamlined multiplexed workflow using data-independent acquisition (mDIA). We demonstrate automated and complete dimethyl labeling of bulk or single-cell samples, without losing proteomic depth. Lys-N digestion enables five-plex quantification at MS1 and MS2 level. Because the multiplexed channels are quantitatively isolated from each other, mDIA accommodates a reference channel that does not interfere with the target channels. Our algorithm RefQuant takes advantage of this and confidently quantifies twice as many proteins per single cell compared to our previous work (Brunner et al, PMID 35226415), while our workflow currently allows routine analysis of 80 single cells per day. Finally, we combined mDIA with spatial proteomics to increase the throughput of Deep Visual Proteomics seven-fold for microdissection and four-fold for MS analysis. Applying this to primary cutaneous melanoma, we discovered proteomic signatures of cells within distinct tumor microenvironments, showcasing its potential for precision oncology.
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Affiliation(s)
- Marvin Thielert
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Ericka CM Itang
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Constantin Ammar
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Florian A Rosenberger
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Isabell Bludau
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Lisa Schweizer
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Thierry M Nordmann
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Patricia Skowronek
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Maria Wahle
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Wen‐Feng Zeng
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Xie‐Xuan Zhou
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Andreas‐David Brunner
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
- Boehringer Ingelheim Pharma GmbH & Co. KG, Drug Discovery SciencesBiberach an der RissGermany
| | - Sabrina Richter
- Helmholtz Zentrum München – German Research Center for Environmental HealthInstitute of Computational BiologyNeuherbergGermany
- TUM School of Life Sciences WeihenstephanTechnical University of MunichFreisingGermany
| | - Mitchell P Levesque
- Department of DermatologyUniversity of Zurich, University of Zurich HospitalZurichSwitzerland
| | - Fabian J Theis
- Helmholtz Zentrum München – German Research Center for Environmental HealthInstitute of Computational BiologyNeuherbergGermany
- TUM School of Life Sciences WeihenstephanTechnical University of MunichFreisingGermany
| | - Martin Steger
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
- New address: NEOsphere Biotechnologies GmbHPlaneggGermany
| | - Matthias Mann
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical SciencesUniversity of CopenhagenCopenhagenDenmark
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26
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Abstract
Missing values are a notable challenge when analyzing mass spectrometry-based proteomics data. While the field is still actively debating the best practices, the challenge increased with the emergence of mass spectrometry-based single-cell proteomics and the dramatic increase in missing values. A popular approach to deal with missing values is to perform imputation. Imputation has several drawbacks for which alternatives exist, but currently, imputation is still a practical solution widely adopted in single-cell proteomics data analysis. This perspective discusses the advantages and drawbacks of imputation. We also highlight 5 main challenges linked to missing value management in single-cell proteomics. Future developments should aim to solve these challenges, whether it is through imputation or data modeling. The perspective concludes with recommendations for reporting missing values, for reporting methods that deal with missing values, and for proper encoding of missing values.
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Affiliation(s)
- Christophe Vanderaa
- Computational Biology and Bioinformatics Unit (CBIO), de Duve Institute, UCLouvain, 1200 Brussels, Belgium
| | - Laurent Gatto
- Computational Biology and Bioinformatics Unit (CBIO), de Duve Institute, UCLouvain, 1200 Brussels, Belgium
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27
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Johnston SM, Webber KGI, Xie X, Truong T, Nydegger A, Lin HJL, Nwosu A, Zhu Y, Kelly RT. Rapid, One-Step Sample Processing for Label-Free Single-Cell Proteomics. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:1701-1707. [PMID: 37410391 PMCID: PMC11017373 DOI: 10.1021/jasms.3c00159] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/07/2023]
Abstract
Sample preparation for single-cell proteomics is generally performed in a one-pot workflow with multiple dispensing and incubation steps. These hours-long processes can be labor intensive and lead to long sample-to-answer times. Here we report a sample preparation method that achieves cell lysis, protein denaturation, and digestion in 1 h using commercially available high-temperature-stabilized proteases with a single reagent dispensing step. Four different one-step reagent compositions were evaluated, and the mixture providing the highest proteome coverage was compared to the previously employed multistep workflow. The one-step preparation increases proteome coverage relative to the previous multistep workflow while minimizing labor input and the possibility of human error. We also compared sample recovery between previously used microfabricated glass nanowell chips and injection-molded polypropylene chips and found the polypropylene provided improved proteome coverage. Combined, the one-step sample preparation and the polypropylene substrates enabled the identification of an average of nearly 2400 proteins per cell using a standard data-dependent workflow with Orbitrap mass spectrometers. These advances greatly simplify sample preparation for single-cell proteomics and broaden accessibility with no compromise in terms of proteome coverage.
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Affiliation(s)
- S Madisyn Johnston
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Kei G I Webber
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Xiaofeng Xie
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Alissia Nydegger
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Hsien-Jung L Lin
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Andikan Nwosu
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Ying Zhu
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
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28
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Matzinger M, Mayer RL, Mechtler K. Label-free single cell proteomics utilizing ultrafast LC and MS instrumentation: A valuable complementary technique to multiplexing. Proteomics 2023; 23:e2200162. [PMID: 36806919 PMCID: PMC10909491 DOI: 10.1002/pmic.202200162] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 02/09/2023] [Accepted: 02/10/2023] [Indexed: 02/21/2023]
Abstract
The ability to map a proteomic fingerprint to transcriptomic data would master the understanding of how gene expression translates into actual phenotype. In contrast to nucleic acid sequencing, in vitro protein amplification is impossible and no single cell proteomic workflow has been established as gold standard yet. Advances in microfluidic sample preparation, multi-dimensional sample separation, sophisticated data acquisition strategies, and intelligent data analysis algorithms have resulted in major improvements to successfully analyze such tiny sample amounts with steadily boosted performance. However, among the broad variation of published approaches, it is commonly accepted that highest possible sensitivity, robustness, and throughput are still the most urgent needs for the field. While many labs have focused on multiplexing to achieve these goals, label-free SCP is a highly promising strategy as well whenever high dynamic range and unbiased accurate quantification are needed. We here focus on recent advances in label-free single-cell mass spectrometry workflows and try to guide our readers to choose the best method or combinations of methods for their specific applications. We further highlight which techniques are most propitious in the future and which applications but also limitations we foresee for the field.
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Affiliation(s)
- Manuel Matzinger
- Research Institute of Molecular Pathology (IMP)Vienna BioCenterViennaAustria
| | - Rupert L. Mayer
- Research Institute of Molecular Pathology (IMP)Vienna BioCenterViennaAustria
| | - Karl Mechtler
- Research Institute of Molecular Pathology (IMP)Vienna BioCenterViennaAustria
- Gregor Mendel Institute of Molecular Plant Biology (GMI), Austrian Academy of SciencesVienna BioCenter (VBC)ViennaAustria
- Institute of Molecular Biotechnology (IMBA), Austrian Academy of SciencesVienna BioCenter (VBC)ViennaAustria
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29
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Stutzmann C, Peng J, Wu Z, Savoie C, Sirois I, Thibault P, Wheeler AR, Caron E. Unlocking the potential of microfluidics in mass spectrometry-based immunopeptidomics for tumor antigen discovery. CELL REPORTS METHODS 2023; 3:100511. [PMID: 37426761 PMCID: PMC10326451 DOI: 10.1016/j.crmeth.2023.100511] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
The identification of tumor-specific antigens (TSAs) is critical for developing effective cancer immunotherapies. Mass spectrometry (MS)-based immunopeptidomics has emerged as a powerful tool for identifying TSAs as physical molecules. However, current immunopeptidomics platforms face challenges in measuring low-abundance TSAs in a precise, sensitive, and reproducible manner from small needle-tissue biopsies (<1 mg). Inspired by recent advances in single-cell proteomics, microfluidics technology offers a promising solution to these limitations by providing improved isolation of human leukocyte antigen (HLA)-associated peptides with higher sensitivity. In this context, we highlight the challenges in sample preparation and the rationale for developing microfluidics technology in immunopeptidomics. Additionally, we provide an overview of promising microfluidic methods, including microchip pillar arrays, valved-based systems, droplet microfluidics, and digital microfluidics, and discuss the latest research on their application in MS-based immunopeptidomics and single-cell proteomics.
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Affiliation(s)
| | - Jiaxi Peng
- Department of Chemistry, University of Toronto, Toronto, ON, Canada
| | - Zhaoguan Wu
- CHU Sainte Justine Research Center, Montreal, QC, Canada
| | | | | | - Pierre Thibault
- Institute for Research in Immunology and Cancer, University of Montreal, Montreal, QC, Canada
- Department of Chemistry, University of Montreal, Montreal, QC, Canada
| | - Aaron R. Wheeler
- Department of Chemistry, University of Toronto, Toronto, ON, Canada
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada
| | - Etienne Caron
- CHU Sainte Justine Research Center, Montreal, QC, Canada
- Department of Pathology and Cellular Biology, University of Montreal, Montreal, QC, Canada
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30
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Tiwari S, Nizet O, Dillon N. Development of a high-throughput minimum inhibitory concentration (HT-MIC) testing workflow. Front Microbiol 2023; 14:1079033. [PMID: 37303796 PMCID: PMC10249070 DOI: 10.3389/fmicb.2023.1079033] [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: 10/24/2022] [Accepted: 04/24/2023] [Indexed: 06/13/2023] Open
Abstract
The roots of the minimum inhibitory concentration (MIC) determination go back to the early 1900s. Since then, the test has undergone modifications and advancements in an effort to increase its dependability and accuracy. Although biological investigations use an ever-increasing number of samples, complicated processes and human error sometimes result in poor data quality, which makes it challenging to replicate scientific conclusions. Automating manual steps using protocols decipherable by machine can ease procedural difficulties. Originally relying on manual pipetting and human vision to determine the results, modern broth dilution MIC testing procedures have incorporated microplate readers to enhance sample analysis. However, current MIC testing procedures are unable to simultaneously evaluate a large number of samples efficiently. Here, we have created a proof-of-concept workflow using the Opentrons OT-2 robot to enable high-throughput MIC testing. We have further optimized the analysis by incorporating Python programming for MIC assignment to streamline the automation. In this workflow, we performed MIC tests on four different strains, three replicates per strain, and analyzed a total of 1,152 wells. Comparing our workflow to a conventional plate MIC procedure, we find that the HT-MIC method is 800% faster while simultaneously boasting a 100% accuracy. Our high-throughput MIC workflow can be adapted in both academic and clinical settings since it is faster, more efficient, and as accurate than many conventional methods.
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Affiliation(s)
- Suman Tiwari
- Department of Biological Sciences, University of Texas at Dallas, Richardson, TX, United States
| | - Oliver Nizet
- La Jolla Country Day School, La Jolla, CA, United States
| | - Nicholas Dillon
- Department of Biological Sciences, University of Texas at Dallas, Richardson, TX, United States
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31
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Liang Y, Truong T, Saxton AJ, Boekweg H, Payne SH, Van Ry PM, Kelly RT. HyperSCP: Combining Isotopic and Isobaric Labeling for Higher Throughput Single-Cell Proteomics. Anal Chem 2023; 95:8020-8027. [PMID: 37167627 PMCID: PMC10246935 DOI: 10.1021/acs.analchem.3c00906] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Recent developments in mass spectrometry-based single-cell proteomics (SCP) have resulted in dramatically improved sensitivity, yet the relatively low measurement throughput remains a limitation. Isobaric and isotopic labeling methods have been separately applied to SCP to increase throughput through multiplexing. Here we combined both forms of labeling to achieve multiplicative scaling for higher throughput. Two-plex stable isotope labeling of amino acids in cell culture (SILAC) and isobaric tandem mass tag (TMT) labeling enabled up to 28 single cells to be analyzed in a single liquid chromatography-mass spectrometry (LC-MS) analysis, in addition to carrier, reference, and negative control channels. A custom nested nanowell chip was used for nanoliter sample processing to minimize sample losses. Using a 145-min total LC-MS cycle time, ∼280 single cells were analyzed per day. This measurement throughput could be increased to ∼700 samples per day with a high-duty-cycle multicolumn LC system producing the same active gradient. The labeling efficiency and achievable proteome coverage were characterized for multiple analysis conditions.
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Affiliation(s)
- Yiran Liang
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Aubrianna J Saxton
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Hannah Boekweg
- Department of Biology, Brigham Young University, Provo, Utah 84602, United States
| | - Samuel H Payne
- Department of Biology, Brigham Young University, Provo, Utah 84602, United States
| | - Pam M Van Ry
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
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32
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Eshghi A, Xie X, Hardie D, Chen MX, Izaguirre F, Newman R, Zhu Y, Kelly RT, Goodlett DR. Sample Preparation Methods for Targeted Single-Cell Proteomics. J Proteome Res 2023. [PMID: 37093777 DOI: 10.1021/acs.jproteome.2c00429] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
We compared three cell isolation and two proteomic sample preparation methods for single-cell and near-single-cell analysis. Whole blood was used to quantify hemoglobin (Hb) and glycated-Hb (gly-Hb) in erythrocytes using targeted mass spectrometry and stable isotope-labeled standard peptides. Each method differed in cell isolation and sample preparation as follows: 1) FACS and automated preparation in one-pot for trace samples (autoPOTS); 2) limited dilution via microscopy and a novel rapid one-pot sample preparation method that circumvented the need for the solid-phase extraction, low-volume liquid handling instrumentation and humidified incubation chamber; and 3) CellenONE-based cell isolation and the same one-pot sample preparation method used for limited dilution. Only the CellenONE device routinely isolated single-cells from which Hb was measured to be 540-660 amol per red blood cell (RBC), which was comparable to the calculated SI reference range for mean corpuscular hemoglobin (390-540 amol/RBC). FACSAria sorter and limited dilution could routinely isolate single-digit cell numbers, to reliably quantify CMV-Hb heterogeneity. Finally, we observed that repeated measures, using 5-25 RBCs obtained from N = 10 blood donors, could be used as an alternative and more efficient strategy than single RBC analysis to measure protein heterogeneity, which revealed multimodal distribution, unique for each individual.
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Affiliation(s)
- Azad Eshghi
- University of Victoria - Genome BC Proteomics Centre, Victoria, British Columbia V8Z 5N3, Canada
| | - Xiaofeng Xie
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84604, United States
| | - Darryl Hardie
- University of Victoria - Genome BC Proteomics Centre, Victoria, British Columbia V8Z 5N3, Canada
| | - Michael X Chen
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
- Department of Laboratory Medicine, Pathology, and Medical Genetics, Vancouver Island Health Authority, Vancouver, British Columbia V9A 2P8, Canada
- Division of Medical Sciences, University of Victoria, Victoria, British Columbia V8P 5C2, Canada
| | - Fabiana Izaguirre
- Cellenion SASU, 60 Avenue Rockefeller, Bâtiment BioSerra2, Lyon, Auvergne-Rhône-Alpes 69008, France
| | - Rachael Newman
- University of Victoria - Genome BC Proteomics Centre, Victoria, British Columbia V8Z 5N3, Canada
| | - Ying Zhu
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84604, United States
| | - David R Goodlett
- University of Victoria - Genome BC Proteomics Centre, Victoria, British Columbia V8Z 5N3, Canada
- International Centre for Cancer Vaccine Science, University of Gdansk, Gdansk, Pomerania 80-309, Poland
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33
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Mansuri MS, Williams K, Nairn AC. Uncovering biology by single-cell proteomics. Commun Biol 2023; 6:381. [PMID: 37031277 PMCID: PMC10082756 DOI: 10.1038/s42003-023-04635-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 02/25/2023] [Indexed: 04/10/2023] Open
Abstract
Recent technological advances have opened the door to single-cell proteomics that can answer key biological questions regarding how protein expression, post-translational modifications, and protein interactions dictate cell state in health and disease.
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Affiliation(s)
- M Shahid Mansuri
- Yale/NIDA Neuroproteomics Center and Department of Molecular Biophysics and Biochemistry, Yale School of Medicine, New Haven, Connecticut, USA
| | - Kenneth Williams
- Yale/NIDA Neuroproteomics Center and Department of Molecular Biophysics and Biochemistry, Yale School of Medicine, New Haven, Connecticut, USA
| | - Angus C Nairn
- Yale/NIDA Neuroproteomics Center and Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA.
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34
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Veličković M, Fillmore TL, Attah K, Posso C, Pino JC, Zhao R, Williams SM, Veličković D, Jacobs JM, Burnum-Johnson KE, Zhu Y, Piehowski PD. Coupling microdroplet-based sample preparation, multiplexed isobaric labeling, and nanoflow peptide fractionation for deep proteome profiling of tissue microenvironment. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.13.531822. [PMID: 36993277 PMCID: PMC10055005 DOI: 10.1101/2023.03.13.531822] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity at a cell-type-specific level to better understand and predict the function of complex biological systems, such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverages due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (Microdroplet Processing in One pot for Trace Samples), the multiplexed isobaric labelling, and a nanoflow peptide fractionation approach. The integrated workflow allowed to maximize proteome coverage of laser-isolated tissue samples containing nanogram proteins. We demonstrated the deep spatial proteomics can quantify more than 5,000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 µm2) and reveal unique islet microenvironments.
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35
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Peng J, Chan C, Meng F, Hu Y, Chen L, Lin G, Zhang S, Wheeler AR. Comparison of Database Searching Programs for the Analysis of Single-Cell Proteomics Data. J Proteome Res 2023; 22:1298-1308. [PMID: 36892105 DOI: 10.1021/acs.jproteome.2c00821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/10/2023]
Abstract
Single-cell proteomics is emerging as an important subfield in the proteomics and mass spectrometry communities, with potential to reshape our understanding of cell development, cell differentiation, disease diagnosis, and the development of new therapies. Compared with significant advancements in the "hardware" that is used in single-cell proteomics, there has been little work comparing the effects of using different "software" packages to analyze single-cell proteomics datasets. To this end, seven popular proteomics programs were compared here, applying them to search three single-cell proteomics datasets generated by three different platforms. The results suggest that MSGF+, MSFragger, and Proteome Discoverer are generally more efficient in maximizing protein identifications, that MaxQuant is better suited for the identification of low-abundance proteins, that MSFragger is superior in elucidating peptide modifications, and that Mascot and X!Tandem are better for analyzing long peptides. Furthermore, an experiment with different loading amounts was carried out to investigate changes in identification results and to explore areas in which single-cell proteomics data analysis may be improved in the future. We propose that this comparative study may provide insight for experts and beginners alike operating in the emerging subfield of single-cell proteomics.
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Affiliation(s)
- Jiaxi Peng
- Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada.,Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada.,Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario M5S 3G9, Canada
| | - Calvin Chan
- Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada
| | - Fei Meng
- Clinical Research Center for Reproduction and Genetics in Hunan Province, Reproductive and Genetic Hospital of CITIC-XIANGYA, Changsha, Hunan 410000, China
| | - Yechen Hu
- Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada.,Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada.,Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario M5S 3G9, Canada
| | - Lingfan Chen
- Fujian Province New Drug Safety Evaluation Centre, Fujian Medical University, Fuzhou Fujian 350108, China
| | - Ge Lin
- Clinical Research Center for Reproduction and Genetics in Hunan Province, Reproductive and Genetic Hospital of CITIC-XIANGYA, Changsha, Hunan 410000, China.,Laboratory of Reproductive and Stem Cell Engineering, NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Central South University, Changsha, Hunan 410075, China
| | - Shen Zhang
- Clinical Research Center for Reproduction and Genetics in Hunan Province, Reproductive and Genetic Hospital of CITIC-XIANGYA, Changsha, Hunan 410000, China
| | - Aaron R Wheeler
- Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada.,Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada.,Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario M5S 3G9, Canada
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36
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Matzinger M, Müller E, Dürnberger G, Pichler P, Mechtler K. Robust and Easy-to-Use One-Pot Workflow for Label-Free Single-Cell Proteomics. Anal Chem 2023; 95:4435-4445. [PMID: 36802514 PMCID: PMC9996606 DOI: 10.1021/acs.analchem.2c05022] [Citation(s) in RCA: 45] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
Abstract
The analysis of ultralow input samples or even individual cells is essential to answering a multitude of biomedical questions, but current proteomic workflows are limited in their sensitivity and reproducibility. Here, we report a comprehensive workflow that includes improved strategies for all steps, from cell lysis to data analysis. Thanks to convenient-to-handle 1 μL sample volume and standardized 384-well plates, the workflow is easy for even novice users to implement. At the same time, it can be performed semi-automatized using CellenONE, which allows for the highest reproducibility. To achieve high throughput, ultrashort gradient lengths down to 5 min were tested using advanced μ-pillar columns. Data-dependent acquisition (DDA), wide-window acquisition (WWA), data-independent acquisition (DIA), and commonly used advanced data analysis algorithms were benchmarked. Using DDA, 1790 proteins covering a dynamic range of four orders of magnitude were identified in a single cell. Using DIA, proteome coverage increased to more than 2200 proteins identified from single-cell level input in a 20 min active gradient. The workflow enabled differentiation of two cell lines, demonstrating its suitability to cellular heterogeneity determination.
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Affiliation(s)
- Manuel Matzinger
- Institute of Molecular Pathology (IMP), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
| | - Elisabeth Müller
- Institute of Molecular Pathology (IMP), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
| | - Gerhard Dürnberger
- Gregor Mendel Institute of Molecular Plant Biology (GMI) of the Austrian Academy of Sciences, Dr. Bohrgasse 3, 1030 Vienna, Austria
| | - Peter Pichler
- Institute of Molecular Pathology (IMP), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
| | - Karl Mechtler
- Institute of Molecular Pathology (IMP), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria.,Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Dr. Bohrgasse 3, 1030 Vienna, Austria.,Gregor Mendel Institute of Molecular Plant Biology (GMI) of the Austrian Academy of Sciences, Dr. Bohrgasse 3, 1030 Vienna, Austria
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37
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Gatto L, Aebersold R, Cox J, Demichev V, Derks J, Emmott E, Franks AM, Ivanov AR, Kelly RT, Khoury L, Leduc A, MacCoss MJ, Nemes P, Perlman DH, Petelski AA, Rose CM, Schoof EM, Van Eyk J, Vanderaa C, Yates JR, Slavov N. Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments. Nat Methods 2023; 20:375-386. [PMID: 36864200 PMCID: PMC10130941 DOI: 10.1038/s41592-023-01785-3] [Citation(s) in RCA: 39] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 01/24/2023] [Indexed: 03/04/2023]
Abstract
Analyzing proteins from single cells by tandem mass spectrometry (MS) has recently become technically feasible. While such analysis has the potential to accurately quantify thousands of proteins across thousands of single cells, the accuracy and reproducibility of the results may be undermined by numerous factors affecting experimental design, sample preparation, data acquisition and data analysis. We expect that broadly accepted community guidelines and standardized metrics will enhance rigor, data quality and alignment between laboratories. Here we propose best practices, quality controls and data-reporting recommendations to assist in the broad adoption of reliable quantitative workflows for single-cell proteomics. Resources and discussion forums are available at https://single-cell.net/guidelines .
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Affiliation(s)
- Laurent Gatto
- Computational Biology and Bioinformatics Unit, de Duve Institute, Université Catholique de Louvain, Brussels, Belgium
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Juergen Cox
- Max Planck Institute of Biochemistry, Martinsried, Germany
| | | | - Jason Derks
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA
| | - Edward Emmott
- Centre for Proteome Research, Department of Biochemistry and Systems Biology, University of Liverpool, Liverpool, UK
| | - Alexander M Franks
- Department of Statistics and Applied Probability, University of California Santa Barbara, Santa Barbara, CA, USA
| | - Alexander R Ivanov
- Department of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, USA
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA
| | - Luke Khoury
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA
| | - Andrew Leduc
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA
| | | | - Peter Nemes
- Department of Chemistry and Biochemistry, University of Maryland, College Park, MD, USA
| | - David H Perlman
- Merck Exploratory Science Center, Merck Sharp & Dohme Corp., Cambridge, MA, USA
| | - Aleksandra A Petelski
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA
- Parallel Squared Technology Institute, Watertown, MA, USA
| | - Christopher M Rose
- Department of Microchemistry, Proteomics and Lipidomics, Genentech Inc., South San Francisco, CA, USA
| | - Erwin M Schoof
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | | | - Christophe Vanderaa
- Computational Biology and Bioinformatics Unit, de Duve Institute, Université Catholique de Louvain, Brussels, Belgium
| | - John R Yates
- Departments of Molecular Medicine and Neurobiology, the Scripps Research Institute, La Jolla, CA, USA
| | - Nikolai Slavov
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA.
- Parallel Squared Technology Institute, Watertown, MA, USA.
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38
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Vanderaa C, Gatto L. The Current State of Single-Cell Proteomics Data Analysis. Curr Protoc 2023; 3:e658. [PMID: 36633424 DOI: 10.1002/cpz1.658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Sound data analysis is essential to retrieve meaningful biological information from single-cell proteomics experiments. This analysis is carried out by computational methods that are assembled into workflows, and their implementations influence the conclusions that can be drawn from the data. In this work, we explore and compare the computational workflows that have been used over the last four years and identify a profound lack of consensus on how to analyze single-cell proteomics data. We highlight the need for benchmarking of computational workflows and standardization of computational tools and data, as well as carefully designed experiments. Finally, we cover the current standardization efforts that aim to fill the gap, list the remaining missing pieces, and conclude with lessons learned from the replication of published single-cell proteomics analyses. © 2023 Wiley Periodicals LLC.
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Affiliation(s)
- Christophe Vanderaa
- Computational Biology and Bioinformatics Unit (CBIO), de Duve Institute, Université catholique de Louvain, Belgium
| | - Laurent Gatto
- Computational Biology and Bioinformatics Unit (CBIO), de Duve Institute, Université catholique de Louvain, Belgium
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39
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Wu Y, Zhang W, Zhao Y, Wang X, Guo G. Technology development trend of electrospray ionization mass spectrometry for single-cell proteomics. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
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40
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Cupp-Sutton KA, Fang M, Wu S. Separation methods in single-cell proteomics: RPLC or CE? INTERNATIONAL JOURNAL OF MASS SPECTROMETRY 2022; 481:116920. [PMID: 36211475 PMCID: PMC9542495 DOI: 10.1016/j.ijms.2022.116920] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Cellular heterogeneity is commonly investigated using single-cell genomics and transcriptomics to investigate biological questions such as disease mechanism, therapeutic screening, and genomic and transcriptomic diversity between cellular populations and subpopulations at the cellular level. Single-cell mass spectrometry (MS)-based proteomics enables the high-throughput examination of protein expression at the single-cell level with wide applicability, and with spatial and temporal resolution, applicable to the study of cellular development, disease, effect of treatment, etc. The study of single-cell proteomics has lagged behind genomics and transcriptomics largely because proteins from single-cell samples cannot be amplified as DNA and RNA can using well established techniques such as PCR. Therefore, analytical methods must be robust, reproducible, and sensitive enough to detect the very small amount of protein within a single cell. To this end, nearly every step of the proteomics process has been extensively altered and improved to facilitate the proteomics analysis of single cells including cell counting and sorting, lysis, protein digestion, sample cleanup, separation, MS data acquisition, and data analysis. Here, we have reviewed recent advances in single-cell protein separation using nano reversed phase liquid chromatography (nRPLC) and capillary electrophoresis (CE) to inform application driven selection of separation techniques in the laboratory setting.
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Affiliation(s)
| | - Mulin Fang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK 73019
| | - Si Wu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK 73019
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41
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Dachs J, Vila-Costa M. Toward a Multi-Omics-Based Single-Cell Environmental Chemistry and Toxicology. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:10550-10552. [PMID: 35819366 PMCID: PMC9352308 DOI: 10.1021/acs.est.2c02831] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Indexed: 06/15/2023]
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42
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Nwosu AJ, Misal SA, Truong T, Carson RH, Webber KGI, Axtell NB, Liang Y, Johnston SM, Virgin KL, Smith EG, Thomas GV, Morgan T, Price JC, Kelly RT. In-Depth Mass Spectrometry-Based Proteomics of Formalin-Fixed, Paraffin-Embedded Tissues with a Spatial Resolution of 50-200 μm. J Proteome Res 2022; 21:2237-2245. [PMID: 35916235 PMCID: PMC9767749 DOI: 10.1021/acs.jproteome.2c00409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Formalin-fixed, paraffin-embedded (FFPE) tissues are banked in large repositories to cost-effectively preserve valuable specimens for later study. With the rapid growth of spatial proteomics, FFPE tissues can serve as a more accessible alternative to more commonly used frozen tissues. However, extracting proteins from FFPE tissues is challenging due to cross-links formed between proteins and formaldehyde. Here, we have adapted the nanoPOTS sample processing workflow, which was previously applied to single cells and fresh-frozen tissues, to profile protein expression from FFPE tissues. Following the optimization of extraction solvents, times, and temperatures, we identified an average of 1312 and 3184 high-confidence master proteins from 10 μm thick FFPE-preserved mouse liver tissue squares having lateral dimensions of 50 and 200 μm, respectively. The observed proteome coverage for FFPE tissues was on average 88% of that achieved for similar fresh-frozen tissues. We also characterized the performance of our fully automated sample preparation and analysis workflow, termed autoPOTS, for FFPE spatial proteomics. This modified nanodroplet processing in one pot for trace samples (nanoPOTS) and fully automated processing in one pot for trace sample (autoPOTS) workflows provides the greatest coverage reported to date for high-resolution spatial proteomics applied to FFPE tissues. Data are available via ProteomeXchange with identifier PXD029729.
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Affiliation(s)
- Andikan J Nwosu
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Santosh A Misal
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Richard H Carson
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Kei G I Webber
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Nathaniel B Axtell
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Yiran Liang
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - S Madisyn Johnston
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Kenneth L Virgin
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Ethan G Smith
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - George V Thomas
- Knight Cancer Center, Oregon Health & Science University, Portland, Oregon 97239, United States
| | - Terry Morgan
- Department of Pathology, Oregon Health & Science University, Portland, Oregon 97239, United States
| | - John C Price
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
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43
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Beck L, Geiger T. MS-based technologies for untargeted single-cell proteomics. Curr Opin Biotechnol 2022; 76:102736. [DOI: 10.1016/j.copbio.2022.102736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 03/19/2022] [Accepted: 04/24/2022] [Indexed: 11/28/2022]
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44
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Yan S, Bhawal R, Yin Z, Thannhauser TW, Zhang S. Recent advances in proteomics and metabolomics in plants. MOLECULAR HORTICULTURE 2022; 2:17. [PMID: 37789425 PMCID: PMC10514990 DOI: 10.1186/s43897-022-00038-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 06/20/2022] [Indexed: 10/05/2023]
Abstract
Over the past decade, systems biology and plant-omics have increasingly become the main stream in plant biology research. New developments in mass spectrometry and bioinformatics tools, and methodological schema to integrate multi-omics data have leveraged recent advances in proteomics and metabolomics. These progresses are driving a rapid evolution in the field of plant research, greatly facilitating our understanding of the mechanistic aspects of plant metabolisms and the interactions of plants with their external environment. Here, we review the recent progresses in MS-based proteomics and metabolomics tools and workflows with a special focus on their applications to plant biology research using several case studies related to mechanistic understanding of stress response, gene/protein function characterization, metabolic and signaling pathways exploration, and natural product discovery. We also present a projection concerning future perspectives in MS-based proteomics and metabolomics development including their applications to and challenges for system biology. This review is intended to provide readers with an overview of how advanced MS technology, and integrated application of proteomics and metabolomics can be used to advance plant system biology research.
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Affiliation(s)
- Shijuan Yan
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Ruchika Bhawal
- Proteomics and Metabolomics Facility, Institute of Biotechnology, Cornell University, 139 Biotechnology Building, 526 Campus Road, Ithaca, NY, 14853, USA
| | - Zhibin Yin
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | | | - Sheng Zhang
- Proteomics and Metabolomics Facility, Institute of Biotechnology, Cornell University, 139 Biotechnology Building, 526 Campus Road, Ithaca, NY, 14853, USA.
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45
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Masuda T, Inamori Y, Furukawa A, Yamahiro M, Momosaki K, Chang CH, Kobayashi D, Ohguchi H, Kawano Y, Ito S, Araki N, Ong SE, Ohtsuki S. Water Droplet-in-Oil Digestion Method for Single-Cell Proteomics. Anal Chem 2022; 94:10329-10336. [PMID: 35817413 PMCID: PMC9330287 DOI: 10.1021/acs.analchem.1c05487] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
![]()
Recent advances in
single-cell proteomics highlight the promise
of sensitive analyses in limited cell populations. However, technical
challenges remain for sample recovery, throughput, and versatility.
Here, we first report a water droplet-in-oil digestion (WinO) method
based on carboxyl-coated beads and phase transfer surfactants for
proteomic analysis using limited sample amounts. This method was developed
to minimize the contact area between the sample solution and the container
to reduce the loss of proteins and peptides by adsorption. This method
increased protein and peptide recovery 10-fold. The proteome profiles
obtained from 100 cells using the WinO method highly correlated with
those from 10,000 cells using the in-solution digestion method. We
successfully applied the WinO method to single-cell proteomics and
quantified 462 proteins. Using the WinO method, samples can be easily
prepared in a multi-well plate, making it a widely applicable and
suitable method for single-cell proteomics.
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Affiliation(s)
- Takeshi Masuda
- Department of Pharmaceutical Microbiology, Faculty of Life Sciences, Kumamoto University, Kumamoto 862-0973, Japan.,Department of Pharmaceutical Microbiology, Graduate School of Pharmaceutical Sciences, Kumamoto University, Kumamoto 862-0973, Japan
| | - Yuma Inamori
- Department of Pharmaceutical Microbiology, Graduate School of Pharmaceutical Sciences, Kumamoto University, Kumamoto 862-0973, Japan
| | - Arisu Furukawa
- Department of Pharmaceutical Microbiology, Graduate School of Pharmaceutical Sciences, Kumamoto University, Kumamoto 862-0973, Japan
| | - Maki Yamahiro
- Department of Pharmaceutical Microbiology, School of Pharmacy, Kumamoto University, Kumamoto 862-0973, Japan
| | - Kazuki Momosaki
- Department of Pharmaceutical Microbiology, School of Pharmacy, Kumamoto University, Kumamoto 862-0973, Japan
| | - Chih-Hsiang Chang
- Department of Tumor Genetics and Biology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto 860-8556, Japan
| | - Daiki Kobayashi
- Department of Tumor Genetics and Biology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto 860-8556, Japan.,Department of Omics Biology, Graduate School of Medical and Dental Sciences, Niigata University, Niigata 951-8510, Japan
| | - Hiroto Ohguchi
- Division of Disease Epigenetics, Institute of Resource Development and Analysis, Kumamoto University, Kumamoto 860-0811, Japan
| | - Yawara Kawano
- Department of Hematology, Rheumatology, and Infectious Diseases, Faculty of Life Sciences, Kumamoto University, Kumamoto 860-8556, Japan
| | - Shingo Ito
- Department of Pharmaceutical Microbiology, Faculty of Life Sciences, Kumamoto University, Kumamoto 862-0973, Japan.,Department of Pharmaceutical Microbiology, Graduate School of Pharmaceutical Sciences, Kumamoto University, Kumamoto 862-0973, Japan
| | - Norie Araki
- Department of Tumor Genetics and Biology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto 860-8556, Japan
| | - Shao-En Ong
- Department of Pharmacology, University of Washington, Seattle, Washington 98195, United States
| | - Sumio Ohtsuki
- Department of Pharmaceutical Microbiology, Faculty of Life Sciences, Kumamoto University, Kumamoto 862-0973, Japan.,Department of Pharmaceutical Microbiology, Graduate School of Pharmaceutical Sciences, Kumamoto University, Kumamoto 862-0973, Japan
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46
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Mund A, Brunner AD, Mann M. Unbiased spatial proteomics with single-cell resolution in tissues. Mol Cell 2022; 82:2335-2349. [PMID: 35714588 DOI: 10.1016/j.molcel.2022.05.022] [Citation(s) in RCA: 77] [Impact Index Per Article: 38.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 05/05/2022] [Accepted: 05/18/2022] [Indexed: 12/19/2022]
Abstract
Mass spectrometry (MS)-based proteomics has become a powerful technology to quantify the entire complement of proteins in cells or tissues. Here, we review challenges and recent advances in the LC-MS-based analysis of minute protein amounts, down to the level of single cells. Application of this technology revealed that single-cell transcriptomes are dominated by stochastic noise due to the very low number of transcripts per cell, whereas the single-cell proteome appears to be complete. The spatial organization of cells in tissues can be studied by emerging technologies, including multiplexed imaging and spatial transcriptomics, which can now be combined with ultra-sensitive proteomics. Combined with high-content imaging, artificial intelligence and single-cell laser microdissection, MS-based proteomics provides an unbiased molecular readout close to the functional level. Potential applications range from basic biological questions to precision medicine.
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Affiliation(s)
- Andreas Mund
- Proteomics Program, The Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Faculty of Health and Medical Sciences, Blegdamsvej 3B, 2200 Copenhagen, Denmark
| | - Andreas-David Brunner
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; Boehringer Ingelheim Pharma GmbH & Co. KG, Drug Discovery Sciences, Birkendorfer Str. 65, D-88397, Biberach Riss, Germany
| | - Matthias Mann
- Proteomics Program, The Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Faculty of Health and Medical Sciences, Blegdamsvej 3B, 2200 Copenhagen, Denmark; Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
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47
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Jassinskaja M, Hansson J. The Opportunity of Proteomics to Advance the Understanding of Intra- and Extracellular Regulation of Malignant Hematopoiesis. Front Cell Dev Biol 2022; 10:824098. [PMID: 35350382 PMCID: PMC8957922 DOI: 10.3389/fcell.2022.824098] [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: 11/28/2021] [Accepted: 02/22/2022] [Indexed: 11/13/2022] Open
Abstract
Fetal and adult hematopoiesis are regulated by largely distinct sets of cell-intrinsic gene regulatory networks as well as extracellular cues in their respective microenvironment. These ontogeny-specific programs drive hematopoietic stem and progenitor cells (HSPCs) in fetus and adult to divergent susceptibility to initiation and progression of hematological malignancies, such as leukemia. Elucidating how leukemogenic hits disturb the intra- and extracellular programs in HSPCs along ontogeny will provide a better understanding of the causes for age-associated differences in malignant hematopoiesis and facilitate the improvement of strategies for prevention and treatment of pediatric and adult acute leukemia. Here, we review current knowledge of the intrinsic and extrinsic programs regulating normal and malignant hematopoiesis, with a particular focus on the differences between infant and adult acute leukemia. We discuss the recent advances in mass spectrometry-based proteomics and its opportunity for resolving the interplay of cell-intrinsic and niche-associated factors in regulating malignant hematopoiesis.
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Affiliation(s)
- Maria Jassinskaja
- Lund Stem Cell Center, Division of Molecular Hematology, Lund University, Lund, Sweden.,York Biomedical Research Institute, Department of Biology, University of York, York, United Kingdom
| | - Jenny Hansson
- Lund Stem Cell Center, Division of Molecular Hematology, Lund University, Lund, Sweden
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48
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Liu X, Rossio V, Thakurta SG, Flora A, Foster L, Bomgarden RD, Gygi SP, Paulo JA. Fe 3+-NTA magnetic beads as an alternative to spin column-based phosphopeptide enrichment. J Proteomics 2022; 260:104561. [PMID: 35331916 DOI: 10.1016/j.jprot.2022.104561] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 03/05/2022] [Accepted: 03/12/2022] [Indexed: 12/18/2022]
Abstract
Protein phosphorylation is a central mechanism of cellular signal transduction in living organisms. Phosphoproteomic studies systematically catalogue and characterize alterations in phosphorylation states across multiple cellular conditions and are often incorporated into global proteomics experiments. Previously, we found that spin column-based Fe3+-NTA enrichment integrated well with our workflow but remained a bottleneck for methods that require higher throughput or a scale that is beyond the capacity of these columns. Here, we compare our well-established spin column-based enrichment strategy with one encompassing magnetic beads. Our data show little difference when using either method in terms of the number of identified phosphopeptides as well as their physicochemical properties. In all, we illustrate how the potentially scalable and automation-friendly magnetic Fe3+-NTA beads can seamlessly substitute spin column-based Fe3+-NTA agarose beads for global phosphoproteome profiling. SIGNIFICANCE: Protein phosphorylation plays a key role in regulating a multitude of biological processes and can lead to insights into disease pathogenesis. Methodologies which can efficiently enrich phosphopeptides in a scalable and high-throughput manner are essential for profiling dynamic phosphoproteomes. Here we compare two phosphopeptide enrichment workflows, a well-established spin column-based strategy with agarose Fe3+-NTA beads and a strategy using magnetic Fe3+-NTA beads. Our data suggest that the scalable and automation-friendly magnetic bead-based workflow is an equivalent, but more flexible, enrichment strategy for phosphoproteome profiling experiments.
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Affiliation(s)
- Xinyue Liu
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Valentina Rossio
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA
| | | | | | | | | | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Joao A Paulo
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA.
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49
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Brunner A, Thielert M, Vasilopoulou C, Ammar C, Coscia F, Mund A, Hoerning OB, Bache N, Apalategui A, Lubeck M, Richter S, Fischer DS, Raether O, Park MA, Meier F, Theis FJ, Mann M. Ultra‐high sensitivity mass spectrometry quantifies single‐cell proteome changes upon perturbation. Mol Syst Biol 2022; 18:e10798. [PMID: 35226415 PMCID: PMC8884154 DOI: 10.15252/msb.202110798] [Citation(s) in RCA: 209] [Impact Index Per Article: 104.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 02/06/2022] [Accepted: 02/08/2022] [Indexed: 12/15/2022] Open
Abstract
Single‐cell technologies are revolutionizing biology but are today mainly limited to imaging and deep sequencing. However, proteins are the main drivers of cellular function and in‐depth characterization of individual cells by mass spectrometry (MS)‐based proteomics would thus be highly valuable and complementary. Here, we develop a robust workflow combining miniaturized sample preparation, very low flow‐rate chromatography, and a novel trapped ion mobility mass spectrometer, resulting in a more than 10‐fold improved sensitivity. We precisely and robustly quantify proteomes and their changes in single, FACS‐isolated cells. Arresting cells at defined stages of the cell cycle by drug treatment retrieves expected key regulators. Furthermore, it highlights potential novel ones and allows cell phase prediction. Comparing the variability in more than 430 single‐cell proteomes to transcriptome data revealed a stable‐core proteome despite perturbation, while the transcriptome appears stochastic. Our technology can readily be applied to ultra‐high sensitivity analyses of tissue material, posttranslational modifications, and small molecule studies from small cell counts to gain unprecedented insights into cellular heterogeneity in health and disease.
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Affiliation(s)
- Andreas‐David Brunner
- Proteomics and Signal Transduction Max‐Planck Institute of Biochemistry Martinsried Germany
| | - Marvin Thielert
- Proteomics and Signal Transduction Max‐Planck Institute of Biochemistry Martinsried Germany
| | - Catherine Vasilopoulou
- Proteomics and Signal Transduction Max‐Planck Institute of Biochemistry Martinsried Germany
| | - Constantin Ammar
- Proteomics and Signal Transduction Max‐Planck Institute of Biochemistry Martinsried Germany
| | - Fabian Coscia
- NNF Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark
| | - Andreas Mund
- NNF Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark
| | | | | | | | | | - Sabrina Richter
- Helmholtz Zentrum München – German Research Center for Environmental Health Institute of Computational Biology Neuherberg Germany
- TUM School of Life Sciences Weihenstephan Technical University of Munich Freising Germany
| | - David S Fischer
- Helmholtz Zentrum München – German Research Center for Environmental Health Institute of Computational Biology Neuherberg Germany
- TUM School of Life Sciences Weihenstephan Technical University of Munich Freising Germany
| | | | | | - Florian Meier
- Proteomics and Signal Transduction Max‐Planck Institute of Biochemistry Martinsried Germany
- Functional Proteomics Jena University Hospital Jena Germany
| | - Fabian J Theis
- Helmholtz Zentrum München – German Research Center for Environmental Health Institute of Computational Biology Neuherberg Germany
- TUM School of Life Sciences Weihenstephan Technical University of Munich Freising Germany
| | - Matthias Mann
- Proteomics and Signal Transduction Max‐Planck Institute of Biochemistry Martinsried Germany
- NNF Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark
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Clark NM, Elmore JM, Walley JW. To the proteome and beyond: advances in single-cell omics profiling for plant systems. PLANT PHYSIOLOGY 2022; 188:726-737. [PMID: 35235661 PMCID: PMC8825333 DOI: 10.1093/plphys/kiab429] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 08/16/2021] [Indexed: 05/19/2023]
Abstract
Recent advances in single-cell proteomics for animal systems could be adapted for plants to increase our understanding of plant development, response to stimuli, and cell-to-cell signaling.
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Affiliation(s)
- Natalie M Clark
- Department of Plant Pathology and Microbiology, Iowa State University, Ames, Iowa 50011, USA
| | - James Mitch Elmore
- Department of Plant Pathology and Microbiology, Iowa State University, Ames, Iowa 50011, USA
| | - Justin W Walley
- Department of Plant Pathology and Microbiology, Iowa State University, Ames, Iowa 50011, USA
- Author for communication:
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