1
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Blaise O, Duchesne C, Capuzzo E, Nahori MA, Fernandes J, Connor MG, Hamon MA, Pizarro-Cerda J, Lataillade JJ, McGuckin C, Rousseau A, Banzet S, Dussurget O, Frescaline N. Infected wound repair correlates with collagen I induction and NOX2 activation by cold atmospheric plasma. NPJ Regen Med 2024; 9:28. [PMID: 39358383 PMCID: PMC11447178 DOI: 10.1038/s41536-024-00372-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 09/20/2024] [Indexed: 10/04/2024] Open
Abstract
Cold atmospheric plasma (CAP) is a promising complement to tissue repair and regenerative medicine approaches. CAP has therapeutic potential in infected cutaneous wounds by mechanisms which remain enigmatic. Here, CAP is shown to activate phagocyte NADPH oxidase complex NOX2. CAP induced increased intracellular reactive oxygen species, alleviated by NOX2 inhibitors. Genetic and pharmacological inhibitions of NOX2 in macrophages and bioengineered skin infected with Staphylococcus aureus and treated with CAP reduced intracellular oxidants and increased bacterial survival. CAP triggered Rac activation and phosphorylation of p40phox and p47phox required for NOX2 assembly and activity. Furthermore, CAP induced collagen I expression by fibroblasts. Infection and healing kinetics showed that murine skin wounds infected with S. aureus and treated with CAP are characterized by decreased bacterial burden, increased length of neoepidermis and extracellular matrix formation. Collectively, our findings identify mechanisms triggered by CAP that subdue infection and result in enhanced repair following skin injury.
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Affiliation(s)
- Océane Blaise
- Institut Pasteur, Université Paris Cité, CNRS UMR6047, Unité de Recherche Yersinia, Paris, France
- École Polytechnique, Sorbonne Université, CNRS UMR7648, Laboratoire de Physique des Plasmas, Palaiseau, France
| | - Constance Duchesne
- Institut Pasteur, Université Paris Cité, CNRS UMR6047, Unité de Recherche Yersinia, Paris, France
- École Polytechnique, Sorbonne Université, CNRS UMR7648, Laboratoire de Physique des Plasmas, Palaiseau, France
| | - Elena Capuzzo
- Institut Pasteur, Université Paris Cité, CNRS UMR6047, Unité de Recherche Yersinia, Paris, France
| | - Marie-Anne Nahori
- Institut Pasteur, Université Paris Cité, CNRS UMR6047, Unité des Toxines Bactériennes, Paris, France
| | | | - Michael G Connor
- Institut Pasteur, Université Paris Cité, Unité Chromatine et Infection, Paris, France
| | - Mélanie A Hamon
- Institut Pasteur, Université Paris Cité, Unité Chromatine et Infection, Paris, France
| | - Javier Pizarro-Cerda
- Institut Pasteur, Université Paris Cité, CNRS UMR6047, Unité de Recherche Yersinia, Paris, France
| | | | | | - Antoine Rousseau
- École Polytechnique, Sorbonne Université, CNRS UMR7648, Laboratoire de Physique des Plasmas, Palaiseau, France
| | - Sébastien Banzet
- Centre de Transfusion Sanguine des Armées, Clamart, France
- Institut de Recherche Biomédicale des Armées, INSERM UMRS-MD 1197, Brétigny-sur-Orge, France
| | - Olivier Dussurget
- Institut Pasteur, Université Paris Cité, CNRS UMR6047, Unité de Recherche Yersinia, Paris, France.
| | - Nadira Frescaline
- Institut Pasteur, Université Paris Cité, CNRS UMR6047, Unité de Recherche Yersinia, Paris, France.
- Centre de Transfusion Sanguine des Armées, Clamart, France.
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2
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Jiang Y, Rex DA, Schuster D, Neely BA, Rosano GL, Volkmar N, Momenzadeh A, Peters-Clarke TM, Egbert SB, Kreimer S, Doud EH, Crook OM, Yadav AK, Vanuopadath M, Hegeman AD, Mayta M, Duboff AG, Riley NM, Moritz RL, Meyer JG. Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry. ACS MEASUREMENT SCIENCE AU 2024; 4:338-417. [PMID: 39193565 PMCID: PMC11348894 DOI: 10.1021/acsmeasuresciau.3c00068] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 05/03/2024] [Accepted: 05/03/2024] [Indexed: 08/29/2024]
Abstract
Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this Review will serve as a handbook for researchers who are new to the field of bottom-up proteomics.
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Affiliation(s)
- Yuming Jiang
- Department
of Computational Biomedicine, Cedars Sinai
Medical Center, Los Angeles, California 90048, United States
- Smidt Heart
Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
- Advanced
Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los
Angeles, California 90048, United States
| | - Devasahayam Arokia
Balaya Rex
- Center for
Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore 575018, India
| | - Dina Schuster
- Department
of Biology, Institute of Molecular Systems
Biology, ETH Zurich, Zurich 8093, Switzerland
- Department
of Biology, Institute of Molecular Biology
and Biophysics, ETH Zurich, Zurich 8093, Switzerland
- Laboratory
of Biomolecular Research, Division of Biology and Chemistry, Paul Scherrer Institute, Villigen 5232, Switzerland
| | - Benjamin A. Neely
- Chemical
Sciences Division, National Institute of
Standards and Technology, NIST, Charleston, South Carolina 29412, United States
| | - Germán L. Rosano
- Mass
Spectrometry
Unit, Institute of Molecular and Cellular
Biology of Rosario, Rosario, 2000 Argentina
| | - Norbert Volkmar
- Department
of Biology, Institute of Molecular Systems
Biology, ETH Zurich, Zurich 8093, Switzerland
| | - Amanda Momenzadeh
- Department
of Computational Biomedicine, Cedars Sinai
Medical Center, Los Angeles, California 90048, United States
- Smidt Heart
Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
- Advanced
Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los
Angeles, California 90048, United States
| | - Trenton M. Peters-Clarke
- Department
of Pharmaceutical Chemistry, University
of California—San Francisco, San Francisco, California, 94158, United States
| | - Susan B. Egbert
- Department
of Chemistry, University of Manitoba, Winnipeg, Manitoba, R3T 2N2 Canada
| | - Simion Kreimer
- Smidt Heart
Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
- Advanced
Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los
Angeles, California 90048, United States
| | - Emma H. Doud
- Center
for Proteome Analysis, Indiana University
School of Medicine, Indianapolis, Indiana, 46202-3082, United States
| | - Oliver M. Crook
- Oxford
Protein Informatics Group, Department of Statistics, University of Oxford, Oxford OX1 3LB, United
Kingdom
| | - Amit Kumar Yadav
- Translational
Health Science and Technology Institute, NCR Biotech Science Cluster 3rd Milestone Faridabad-Gurgaon
Expressway, Faridabad, Haryana 121001, India
| | | | - Adrian D. Hegeman
- Departments
of Horticultural Science and Plant and Microbial Biology, University of Minnesota, Twin Cities, Minnesota 55108, United States
| | - Martín
L. Mayta
- School
of Medicine and Health Sciences, Center for Health Sciences Research, Universidad Adventista del Plata, Libertador San Martin 3103, Argentina
- Molecular
Biology Department, School of Pharmacy and Biochemistry, Universidad Nacional de Rosario, Rosario 2000, Argentina
| | - Anna G. Duboff
- Department
of Chemistry, University of Washington, Seattle, Washington 98195, United States
| | - Nicholas M. Riley
- Department
of Chemistry, University of Washington, Seattle, Washington 98195, United States
| | - Robert L. Moritz
- Institute
for Systems biology, Seattle, Washington 98109, United States
| | - Jesse G. Meyer
- Department
of Computational Biomedicine, Cedars Sinai
Medical Center, Los Angeles, California 90048, United States
- Smidt Heart
Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States
- Advanced
Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los
Angeles, California 90048, United States
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3
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Leduc A, Khoury L, Cantlon J, Khan S, Slavov N. Massively parallel sample preparation for multiplexed single-cell proteomics using nPOP. Nat Protoc 2024:10.1038/s41596-024-01033-8. [PMID: 39117766 DOI: 10.1038/s41596-024-01033-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 05/27/2024] [Indexed: 08/10/2024]
Abstract
Single-cell proteomics by mass spectrometry (MS) allows the quantification of proteins with high specificity and sensitivity. To increase its throughput, we developed nano-proteomic sample preparation (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 using the plexDIA MS multiplexing method, which uses non-isobaric mass tags to barcode peptides from different samples for data-independent acquisition, demonstrates accurate quantification of ~3,000-3,700 proteins per human cell. A separate implementation with isobaric mass tags and prioritized data acquisition demonstrates analysis of 1,827 single cells at a rate of >1,000 single cells per day at a depth of 800-1,200 proteins per human cell. The protocol is implemented by using a cell-dispensing and liquid-handling robot-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 d to prepare >3,000 single cells. We provide metrics and software (the QuantQC R package) for quality control and data exploration. QuantQC supports the robust scaling of nPOP to higher plex reagents for achieving reliable and scalable single-cell proteomics.
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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, USA.
| | - Luke Khoury
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA, USA
| | | | - Saad Khan
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA, 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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4
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Orsburn BC. The Carrier Proteome Should Be Reassessed for Each Mass Analyzer Architecture. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:1644-1646. [PMID: 39029089 DOI: 10.1021/jasms.4c00173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/21/2024]
Abstract
A clever utilization of classic proteomics reagents now allows the effective amplification of the peptide sequencing potential in shotgun proteomics. The application of this method has helped usher in the exciting new field of single cell proteomics. While it was easy to first think that this approach was finally the answer for the polymerase chain reaction in protein chemistry, limitations were carefully described by the authors and others. A study by Cheung et al. systematically identified the consequences of higher concentration carrier proteomes and defined the "carrier proteome limit" [Cheung et al. Nat. Methods 2021, 18, 76]. While this work has been replicated by others, every analysis published to date has used a variation of the same mass analyzer. When the same analysis is performed on alternative instruments, these limits appear to be very different and can be attributed to defined characteristics of each mass analyzer. Specifically, in mass analyzers with a higher relative intrascan linear dynamic range, increased carrier channels appear less detrimental to quantitative accuracy. As such, we may be limiting the power of isobaric peptide signal "amplification" by restricting ourselves to traditional mass analyzer options for shotgun proteomics.
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Affiliation(s)
- Benjamin C Orsburn
- The Johns Hopkins University Medical School, Baltimore, Maryland 21215, United States
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5
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Mun DG, Bhat FA, Joshi N, Sandoval L, Ding H, Jain A, Peterson JA, Kang T, Pujari GP, Tomlinson JL, Budhraja R, Zenka RM, Kannan N, Kipp BR, Dasari S, Gaspar-Maia A, Smoot RL, Kandasamy RK, Pandey A. Diversity of post-translational modifications and cell signaling revealed by single cell and single organelle mass spectrometry. Commun Biol 2024; 7:884. [PMID: 39030393 PMCID: PMC11271535 DOI: 10.1038/s42003-024-06579-7] [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: 03/08/2024] [Accepted: 07/11/2024] [Indexed: 07/21/2024] Open
Abstract
The rapid evolution of mass spectrometry-based single-cell proteomics now enables the cataloging of several thousand proteins from single cells. We investigated whether we could discover cellular heterogeneity beyond proteome, encompassing post-translational modifications (PTM), protein-protein interaction, and variants. By optimizing the mass spectrometry data interpretation strategy to enable the detection of PTMs and variants, we have generated a high-definition dataset of single-cell and nuclear proteomic-states. The data demonstrate the heterogeneity of cell-states and signaling dependencies at the single-cell level and reveal epigenetic drug-induced changes in single nuclei. This approach enables the exploration of previously uncharted single-cell and organellar proteomes revealing molecular characteristics that are inaccessible through RNA profiling.
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Affiliation(s)
- Dong-Gi Mun
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Firdous A Bhat
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Neha Joshi
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
- Manipal Academy of Higher Education, Manipal, 576104, Karnataka, India
| | - Leticia Sandoval
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA
| | - Husheng Ding
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Anu Jain
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
| | | | - Taewook Kang
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Ganesh P Pujari
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
| | | | - Rohit Budhraja
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Roman M Zenka
- Proteomics Core, Mayo Clinic, Rochester, MN, 55905, USA
| | - Nagarajan Kannan
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Benjamin R Kipp
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Surendra Dasari
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA
| | - Alexandre Gaspar-Maia
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA
| | - Rory L Smoot
- Department of Surgery, Mayo Clinic, Rochester, MN, 55905, USA
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, USA
| | - Richard K Kandasamy
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA.
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA.
| | - Akhilesh Pandey
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA.
- Manipal Academy of Higher Education, Manipal, 576104, Karnataka, India.
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA.
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6
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Fu Y, Tao J, Liu T, Liu Y, Qiu J, Su D, Wang R, Luo W, Cao Z, Weng G, Zhang T, Zhao Y. Unbiasedly decoding the tumor microenvironment with single-cell multiomics analysis in pancreatic cancer. Mol Cancer 2024; 23:140. [PMID: 38982491 PMCID: PMC11232163 DOI: 10.1186/s12943-024-02050-7] [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: 05/07/2024] [Accepted: 06/21/2024] [Indexed: 07/11/2024] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a poor prognosis and limited therapeutic options. Research on the tumor microenvironment (TME) of PDAC has propelled the development of immunotherapeutic and targeted therapeutic strategies with a promising future. The emergence of single-cell sequencing and mass spectrometry technologies, coupled with spatial omics, has collectively revealed the heterogeneity of the TME from a multiomics perspective, outlined the development trajectories of cell lineages, and revealed important functions of previously underrated myeloid cells and tumor stroma cells. Concurrently, these findings necessitated more refined annotations of biological functions at the cell cluster or single-cell level. Precise identification of all cell clusters is urgently needed to determine whether they have been investigated adequately and to identify target cell clusters with antitumor potential, design compatible treatment strategies, and determine treatment resistance. Here, we summarize recent research on the PDAC TME at the single-cell multiomics level, with an unbiased focus on the functions and potential classification bases of every cellular component within the TME, and look forward to the prospects of integrating single-cell multiomics data and retrospectively reusing bulk sequencing data, hoping to provide new insights into the PDAC TME.
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Affiliation(s)
- Yifan Fu
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
- 4+4 Medical Doctor Program, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Jinxin Tao
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Tao Liu
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Yueze Liu
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Jiangdong Qiu
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Dan Su
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Ruobing Wang
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Wenhao Luo
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Zhe Cao
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Guihu Weng
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Taiping Zhang
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
- Clinical Immunology Center, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
| | - Yupei Zhao
- General Surgery Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
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7
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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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8
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Orsburn BC. Single cell proteomics by mass spectrometry reveals deep epigenetic insight into the actions of an orphan histone deacetylase inhibitor. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.05.574437. [PMID: 38260471 PMCID: PMC10802306 DOI: 10.1101/2024.01.05.574437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Epigenetic programming has been shown to play a role in nearly every human system and disease where anyone has thought to look. However, the levels of heterogeneity at which epigenetic or epiproteomic modifications occur at single cell resolution across a population remains elusive. While recent advances in sequencing technology have allowed between 1 and 3 histone post-translational modifications to be analyzed in each single cell, over twenty separate chemical PTMs are known to exist, allowing thousands of possible combinations. Single cell proteomics by mass spectrometry (SCP) is an emerging technology in which hundreds or thousands of proteins can be directly quantified in typical human cells. As the proteins detected and quantified by SCP are heavily biased toward proteins of highest abundance, chromatin proteins are an attractive target for analysis. To this end, I applied SCP to the analysis of cancer cells treated with mocetinostat, a class specific histone deacetylase inhibitor. I find that 16 PTMs can be confidently identified and localized with high site specificity in single cells. In addition, the high abundance of histone proteins allows higher throughput methods to be utilized for SCP than previously described. While quantitative accuracy suffers when analyzing more than 700 cells per day, 9 histone proteins can be measured in single cells analyzed at even 3,500 cells per day, a throughput 10-fold greater than any previous report. In addition, the unbiased global approach utilized herein identifies a previously uncharacterized response to this drug through the S100-A8/S100-A9 protein complex partners. This response is observed in nearly every cell of the over 1,000 analyzed in this study, regardless of the relative throughput of the method utilized. While limitations exist in the methods described herein, current technologies can easily improve upon the results presented here to allow comprehensive analysis of histone PTMs to be performed in any mass spectrometry lab. All raw and processed data described in this study has been made publicly available through the ProteomeXchange/MASSIVE repository system as MSV000093434.
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9
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Eberhard CD, Orsburn BC. Acetic acid is a superior ion pairing modifier for sub-nanogram and single cell proteomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.01.551522. [PMID: 37577694 PMCID: PMC10418182 DOI: 10.1101/2023.08.01.551522] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
A recent study demonstrated a substantial increase in peptide signal and corresponding proteome coverage when employing 0.5% acetic acid (AA) as the ion pairing modifier in place of the 0.1% formic acid traditionally used in shotgun proteomics. In this study, we investigated the effect of modifier in the context of sub-nanogram and single cell proteomics (SCP). We first evaluated a tryptic digest standard down to 20 picograms total load on column on a TIMSTOF SCP system. In line with the previous results, we observed a signal increase when using AA, leading to increased proteome coverage at every peptide load assessed. Relative improvements were more apparent at lower concentrations, with a 20 picogram peptide digest demonstrating a striking 1.8-fold increase to over 2,000 protein groups identified in a 30 minute analysis. Furthermore, we find that this increase in signal can be leveraged to reduce ramp times, leading to 1.7x more scans across each peak and improvements in quantification as measured by %CVs. When evaluating single cancer cells, approximately 13% more peptide groups were identified on average when employing AA in the place of FA. All vendor raw and processed data are available through ProteomeXchange as PXD046002 and PXD051590.
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10
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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] [Grants] [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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11
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Coorssen JR, Padula MP. Proteomics-The State of the Field: The Definition and Analysis of Proteomes Should Be Based in Reality, Not Convenience. Proteomes 2024; 12:14. [PMID: 38651373 PMCID: PMC11036260 DOI: 10.3390/proteomes12020014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Revised: 04/17/2024] [Accepted: 04/17/2024] [Indexed: 04/25/2024] Open
Abstract
With growing recognition and acknowledgement of the genuine complexity of proteomes, we are finally entering the post-proteogenomic era. Routine assessment of proteomes as inferred correlates of gene sequences (i.e., canonical 'proteins') cannot provide the necessary critical analysis of systems-level biology that is needed to understand underlying molecular mechanisms and pathways or identify the most selective biomarkers and therapeutic targets. These critical requirements demand the analysis of proteomes at the level of proteoforms/protein species, the actual active molecular players. Currently, only highly refined integrated or integrative top-down proteomics (iTDP) enables the analytical depth necessary to provide routine, comprehensive, and quantitative proteome assessments across the widest range of proteoforms inherent to native systems. Here we provide a broad perspective of the field, taking in historical and current realities, to establish a more balanced understanding of where the field has come from (in particular during the ten years since Proteomes was launched), current issues, and how things likely need to proceed if necessary deep proteome analyses are to succeed. We base this in our firm belief that the best proteomic analyses reflect, as closely as possible, the native sample at the moment of sampling. We also seek to emphasise that this and future analytical approaches are likely best based on the broad recognition and exploitation of the complementarity of currently successful approaches. This also emphasises the need to continuously evaluate and further optimize established approaches, to avoid complacency in thinking and expectations but also to promote the critical and careful development and introduction of new approaches, most notably those that address proteoforms. Above all, we wish to emphasise that a rigorous focus on analytical quality must override current thinking that largely values analytical speed; the latter would certainly be nice, if only proteoforms could thus be effectively, routinely, and quantitatively assessed. Alas, proteomes are composed of proteoforms, not molecular species that can be amplified or that directly mirror genes (i.e., 'canonical'). The problem is hard, and we must accept and address it as such, but the payoff in playing this longer game of rigorous deep proteome analyses is the promise of far more selective biomarkers, drug targets, and truly personalised or even individualised medicine.
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Affiliation(s)
- Jens R. Coorssen
- Department of Biological Sciences, Faculty of Mathematics and Science, Brock University, St. Catharines, ON L2S 3A1, Canada
- Institute for Globally Distributed Open Research and Education (IGDORE), St. Catharines, ON L2N 4X2, Canada
| | - Matthew P. Padula
- School of Life Sciences and Proteomics, Lipidomics and Metabolomics Core Facility, Faculty of Science, University of Technology Sydney, Sydney, NSW 2007, Australia
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12
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Schairer J, Plathe F, Hudelmaier S, Belau E, Pengelley S, Kruse L, Neusüß C. Ion mobility in gas and liquid phases: How much orthogonality is obtained in capillary electrophoresis-ion mobility-mass spectrometry? Electrophoresis 2024; 45:735-742. [PMID: 38085142 DOI: 10.1002/elps.202300210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 11/16/2023] [Accepted: 11/30/2023] [Indexed: 04/28/2024]
Abstract
Ion mobility-mass spectrometry (IM-MS) is an ever-evolving tool to separate ions in the gas phase according to electrophoretic mobility with subsequent mass determination. CE is rarely coupled to IM-MS, possibly due to similar separation mechanisms based on electrophoretic mobility. Here, we investigate the orthogonality of CE and ion mobility (IM) by analyzing a complex peptide mixture (tryptic digest of HeLa proteins) with trapped ion mobility mass spectrometry (TIMS-MS). Using the nanoCEasy interface, excellent sensitivity was achieved by identifying thousands of peptides and achieving a peak capacity of 7500 (CE: 203-323 in a 150 cm long capillary, IM: 27-31). Plotting CE versus mass and CE versus (inverse) mobility, a clear grouping in curved striped patterns is observed according to the charge-to-size and mass-to-charge ratios. The peptide charge in the acidic background electrolyte can be estimated from the number of basic amino acids, with a few exceptions where neighboring effects reduce the positive charge. A surprisingly high orthogonality of CE and IM is observed, which is obviously caused by solvation effects leading to different charges and sizes in the liquid phase compared to the gas phase. A high orthogonality of CE and ion mobility is expected to be observed for other peptide samples as well as other substance classes, making CE-IM-MS a promising tool for various applications.
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Affiliation(s)
- Jasmin Schairer
- Faculty of Chemistry, Aalen University, Aalen, Germany
- Faculty of Science, University of Tübingen, Tübingen, Germany
| | | | | | | | | | - Lena Kruse
- Faculty of Chemistry, Aalen University, Aalen, Germany
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13
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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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14
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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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15
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Orsburn BC. Analyzing Posttranslational Modifications in Single Cells. Methods Mol Biol 2024; 2817:145-156. [PMID: 38907153 DOI: 10.1007/978-1-0716-3934-4_12] [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
With the rapid expansion of capabilities in the analysis of proteins in single cells, we can now identify multiple classes of protein posttranslational modifications on some of these proteins. Each new technology that has increased the number of proteins measured per cell has likewise increased our ability to identify and quantify modified peptides. In this chapter, I will discuss our current capabilities, concerns, and challenges specific to this emerging field of study and the inevitable demand for services, providing a general review of concepts that should be considered.
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Affiliation(s)
- Benjamin C Orsburn
- The Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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16
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Eberhard CD, Orsburn BC. A Multiplexed Single-Cell Proteomic Workflow Applicable to Drug Treatment Studies. Methods Mol Biol 2024; 2823:1-10. [PMID: 39052210 DOI: 10.1007/978-1-0716-3922-1_1] [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: 07/27/2024]
Abstract
It is now well accepted that individual cells within a population will respond to treatment of the same drug in a heterogenous manner. Recent advances have allowed, for the first time, the quantitative analysis of the proteomes of single human cells by mass spectrometry. A major focus of many groups, including our own, has been to use this emerging technology to rapidly identify subpopulations of cells with unique drug response and adaptation methods. While the technology in single-cell proteomics today is progressing at a truly staggering rate, we will detail our current methods for applying highly multiplexed single-cell proteomics to drug treatment studies.
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Affiliation(s)
- Colten D Eberhard
- The Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Benjamin C Orsburn
- The Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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17
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Jenkins C, Orsburn BC. Simple Tool for Rapidly Assessing the Quality of Multiplexed Single Cell Proteomics Data. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2615-2619. [PMID: 37991989 DOI: 10.1021/jasms.3c00238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Recent advances in the sensitivity and speed of mass spectrometers coupled with improved sample preparation methods have enabled the field of single cell proteomics to proliferate. While heavy development is occurring in the label free space, dramatic improvements in throughput are provided by multiplexing with tandem mass tags. Hundreds or thousands of single cells can be analyzed with this method, yielding large data sets which may contain poor data arising from loss of material during cell sorting or poor digestion, labeling, and lysis. To date, no tools have been described that can assess data quality prior to data processing. We present herein a lightweight python script and accompanying graphic user interface that can rapidly quantify reporter ion peaks within each MS/MS spectrum in a file. With simple summary reports, we can identify single cell samples that fail to pass a set quality threshold, thus reducing analysis time waste. In addition, this tool, Diagnostic Ion Data Analysis Reduction (DIDAR), will create reduced MGF files containing only spectra possessing a user-specified number of single cell reporter ions. By reducing the number of spectra that have excessive zero values, we can speed up sample processing with little loss in data completeness as these spectra are removed in later stages in data processing workflows. DIDAR and the DIDAR GUI are compatible with all modern operating systems and are available at: https://github.com/orsburn/DIDARSCPQC. All files described in this study are available at www.massive.ucsd.edu as accession MSV000088887.
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Affiliation(s)
- Conor Jenkins
- The University of Maryland, College Park, Maryland 20737, United States
| | - Benjamin C Orsburn
- The Johns Hopkins University Medical School, Baltimore, Maryland 21215, United States
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18
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Ctortecka C, Hartlmayr D, Seth A, Mendjan S, Tourniaire G, Udeshi ND, Carr SA, Mechtler K. An Automated Nanowell-Array Workflow for Quantitative Multiplexed Single-Cell Proteomics Sample Preparation at High Sensitivity. Mol Cell Proteomics 2023; 22:100665. [PMID: 37839701 PMCID: PMC10684380 DOI: 10.1016/j.mcpro.2023.100665] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 10/03/2023] [Accepted: 10/06/2023] [Indexed: 10/17/2023] Open
Abstract
Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lags. Here, we introduce the proteoCHIP, a universal option for single-cell proteomics sample preparation including multiplexed labeling up to 16-plex with high sensitivity and throughput. The automated processing using a commercial system combining single-cell isolation and picoliter dispensing, the cellenONE, reduces final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error-prone manual sample handling and overcoming evaporation. The specialized proteoCHIP design allows direct injection of single cells via a standard autosampler resulting in around 1500 protein groups per TMT10-plex with reduced or eliminated need for a carrier proteome. We evaluated the effect of wider precursor isolation windows at single-cell input levels and found that using 2 Da isolation windows increased overall sensitivity without significantly impacting interference. Using the dedicated mass spectrometry acquisition strategies detailed here, we identified on average close to 2000 proteins per TMT10-plex across 170 multiplexed single cells that readily distinguished human cell types. Overall, our workflow combines highly efficient sample preparation, chromatographic and ion mobility-based filtering, rapid wide-window data-dependent acquisition analysis, and intelligent data analysis for optimal multiplexed single-cell proteomics. This versatile and automated proteoCHIP-based sample preparation approach is sufficiently sensitive to drive biological applications of single-cell proteomics and can be readily adopted by proteomics laboratories.
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Affiliation(s)
- Claudia Ctortecka
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria; Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
| | - David Hartlmayr
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria; Cellenion SASU, Lyon, France
| | | | - Sasha Mendjan
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Vienna, Austria
| | | | - Namrata D Udeshi
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Steven A Carr
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
| | - Karl Mechtler
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria; Cellenion SASU, Lyon, France; Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Vienna, Austria; The Gregor Mendel Institute of Molecular Plant Biology of the Austrian Academy of Sciences (GMI), Vienna BioCenter (VBC), Vienna, Austria.
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19
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Orsburn BC. Metabolomic, Proteomic, and Single-Cell Proteomic Analysis of Cancer Cells Treated with the KRAS G12D Inhibitor MRTX1133. J Proteome Res 2023; 22:3703-3713. [PMID: 37983312 PMCID: PMC10696623 DOI: 10.1021/acs.jproteome.3c00212] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Indexed: 11/22/2023]
Abstract
Mutations in KRAS are common drivers of human cancers and are often those with the poorest overall prognosis for patients. A recently developed compound, MRTX1133, has shown promise in inhibiting the activity of KRASG12D mutant proteins, which is one of the main drivers of pancreatic cancer. To better understand the mechanism of action of this compound, I performed both proteomics and metabolomics on four KRASG12D mutant pancreatic cancer cell lines. To obtain increased granularity in the proteomic observations, single-cell proteomics was successfully performed on two of these lines. Following quality filtering, a total of 1498 single cells were analyzed. From these cells, 3140 total proteins were identified with approximately 953 proteins quantified per cell. At 48 h of treatment, two distinct populations of cells can be observed based on the level of effectiveness of the drug in decreasing the total abundance of the KRAS protein in each respective cell, with results that are effectively masked in the bulk cell analysis. All mass spectrometry data and processed results are publicly available at www.massive.ucsd.edu at accessions PXD039597, PXD039601, and PXD039600.
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Affiliation(s)
- Benjamin C. Orsburn
- The Department of Pharmacology and
Molecular Sciences, The Johns Hopkins University
School of Medicine, Baltimore, Maryland 21205, United States
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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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Orsburn BC. An integrated method for single cell proteomics with simultaneous measurements of intracellular drug concentration implicates new mechanisms for adaptation to KRAS G12D inhibitors. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.18.567669. [PMID: 38014353 PMCID: PMC10680798 DOI: 10.1101/2023.11.18.567669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
It is well established that a population of single human cells will often respond to the same drug treatment in a heterogeneous manner. In the context of chemotherapeutics, these diverse responses may lead to individual adaptation mechanisms and ultimately multiple distinct methods of resistance. The obvious question from a pharmacology perspective is how intracellular concentrations of active drug varies between individual cells, and what role does that variation play in drug response heterogeneity? To date, no integrated methods for rapidly measuring intracellular drug levels while simultaneously measuring drug responses have been described. This study describes a method for single cell preparation that allows proteins to be extracted and digested from single cells while maintaining conditions for small molecules to be simultaneously measured. The method as described allows up to 40 cells to be analyzed per instrument per day. When applied to a KRASG12D small molecule inhibitor I observe a wide degree of intracellular levels of the drug, and that proteomic responses largely stratify based on the concentration of drug within each single cell. Further work is in progress to develop and standardize this method and - more importantly - to normalize drug measurements against direct measurements of cell volume. However, these preliminary results appear promising for the identification of single cells with unique drug response mechanisms. All data described in this study has been made publicly available through the ProteomeXchange consortium under accession PXD046002.
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Affiliation(s)
- Benjamin C. Orsburn
- The Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, USA, 21205
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22
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Ahmad R, Budnik B. A review of the current state of single-cell proteomics and future perspective. Anal Bioanal Chem 2023; 415:6889-6899. [PMID: 37285026 PMCID: PMC10632274 DOI: 10.1007/s00216-023-04759-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 05/12/2023] [Accepted: 05/16/2023] [Indexed: 06/08/2023]
Abstract
Single-cell methodologies and technologies have started a revolution in biology which until recently has primarily been limited to deep sequencing and imaging modalities. With the advent and subsequent torrid development of single-cell proteomics over the last 5 years, despite the fact that proteins cannot be amplified like transcripts, it has now become abundantly clear that it is a worthy complement to single-cell transcriptomics. In this review, we engage in an assessment of the current state of the art of single-cell proteomics including workflow, sample preparation techniques, instrumentation, and biological applications. We investigate the challenges associated with working with very small sample volumes and the acute need for robust statistical methods for data interpretation. We delve into what we believe is a promising future for biological research at single-cell resolution and highlight some of the exciting discoveries that already have been made using single-cell proteomics, including the identification of rare cell types, characterization of cellular heterogeneity, and investigation of signaling pathways and disease mechanisms. Finally, we acknowledge that there are a number of outstanding and pressing problems that the scientific community vested in advancing this technology needs to resolve. Of prime importance is the need to set standards so that this technology becomes widely accessible allowing novel discoveries to be easily verifiable. We conclude with a plea to solve these problems rapidly so that single-cell proteomics can be part of a robust, high-throughput, and scalable single-cell multi-omics platform that can be ubiquitously applied to elucidating deep biological insights into the diagnosis and treatment of all diseases that afflict us.
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Affiliation(s)
- Rushdy Ahmad
- Wyss Institute for Biologically Inspired Engineering at Harvard University, 3 Blackfan Circle, Boston, MA, 02115, USA
| | - Bogdan Budnik
- Wyss Institute for Biologically Inspired Engineering at Harvard University, 3 Blackfan Circle, Boston, MA, 02115, USA.
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23
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KIM S, KAMARULZAMAN L, TANIGUCHI Y. Recent methodological advances towards single-cell proteomics. PROCEEDINGS OF THE JAPAN ACADEMY. SERIES B, PHYSICAL AND BIOLOGICAL SCIENCES 2023; 99:306-327. [PMID: 37673661 PMCID: PMC10749393 DOI: 10.2183/pjab.99.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 07/20/2023] [Indexed: 09/08/2023]
Abstract
Studying the central dogma at the single-cell level has gained increasing attention to reveal hidden cell lineages and functions that cannot be studied using traditional bulk analyses. Nonetheless, most single-cell studies exploiting genomic and transcriptomic levels fail to address information on proteins that are central to many important biological processes. Single-cell proteomics enables understanding of the functional status of individual cells and is particularly crucial when the specimen is composed of heterogeneous entities of cells. With the growing importance of this field, significant methodological advancements have emerged recently. These include miniaturized and automated sample preparation, multi-omics analyses, and combined analyses of multiple techniques such as mass spectrometry and microscopy. Moreover, artificial intelligence and single-molecule detection technologies have advanced throughput and improved sensitivity limitations, respectively, over conventional methods. In this review, we summarize cutting-edge methodologies for single-cell proteomics and relevant emerging technologies that have been reported in the last 5 years, and provide an outlook on this research field.
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Affiliation(s)
- Sooyeon KIM
- Laboratory for Cell Systems Control, Center for Biosystems Dynamics Research, RIKEN, Suita, Osaka, Japan
- Institute for Integrated Cell-Material Sciences (iCeMS), Kyoto University, Sakyo-ku, Kyoto, Japan
| | - Latiefa KAMARULZAMAN
- Laboratory for Cell Systems Control, Center for Biosystems Dynamics Research, RIKEN, Suita, Osaka, Japan
- Graduate School of Frontier Biosciences, Osaka University, Suita, Osaka, Japan
| | - Yuichi TANIGUCHI
- Laboratory for Cell Systems Control, Center for Biosystems Dynamics Research, RIKEN, Suita, Osaka, Japan
- Institute for Integrated Cell-Material Sciences (iCeMS), Kyoto University, Sakyo-ku, Kyoto, Japan
- Graduate School of Frontier Biosciences, Osaka University, Suita, Osaka, Japan
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24
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Végvári Á, Zhang X, Zubarev RA. Toward Single Bacterium Proteomics. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2098-2106. [PMID: 37713396 PMCID: PMC10557376 DOI: 10.1021/jasms.3c00242] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 08/14/2023] [Accepted: 09/12/2023] [Indexed: 09/17/2023]
Abstract
Bacteria are orders of magnitude smaller than mammalian cells, and while single cell proteomics (SCP) currently detects and quantifies several thousands of proteins per mammalian cell, it is not clear whether conventional SCP methods will be suitable for bacteria. Here we report on the first successful attempt to detect proteins from individual Escherichia coli bacteria, with validation of our findings by comparison with two bacteria samples and bulk proteomics data. Data are available via ProteomeXchange with the identifier PXD043473.
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Affiliation(s)
- Ákos Végvári
- Division of Chemistry I,
Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - Xuepei Zhang
- Division of Chemistry I,
Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - Roman A. Zubarev
- Division of Chemistry I,
Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-171 77 Stockholm, Sweden
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25
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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: 14] [Impact Index Per Article: 14.0] [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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26
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Orsburn BC. Metabolomic, proteomic and single cell proteomic analysis of cancer cells treated with the KRAS G12D inhibitor MRTX1133. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.23.533981. [PMID: 36993160 PMCID: PMC10055375 DOI: 10.1101/2023.03.23.533981] [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] [Indexed: 06/19/2023]
Abstract
Mutations in KRAS are common drivers of human cancers and are often those with the poorest overall prognosis for patients. A recently developed compound, MRTX1133, has shown promise in inhibiting the activity of KRASG12D mutant proteins, one of the main drivers in pancreatic cancer. To better understand the mechanism of action of this compound I performed both proteomics and metabolomics on four KRASG12D mutant pancreatic cancer cell lines. To obtain increased granularity in the proteomic observations, single cell proteomics was successfully performed on two of these lines. Following quality filtering, a total of 1,498 single cells were analyzed. From these cells 3,140 total proteins were identified with approximately 953 proteins quantified per cell. At 48 hours of treatment, two distinct populations of cells can be observed based on the level of effectiveness of the drug in decreasing total abundance of the KRAS protein in each respective cell, results that are effectively masked in the bulk cell analysis. All mass spectrometry data and processed results are publicly available at the www.massive.ucsd.edu at accessions PXD039597, PXD039601 and PXD039600.
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Affiliation(s)
- Benjamin C. Orsburn
- The Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, USA, 21205
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27
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Warshanna A, Orsburn BC. SCP Viz - A universal graphical user interface for single protein analysis in single cell proteomics datasets. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.29.555397. [PMID: 37693496 PMCID: PMC10491148 DOI: 10.1101/2023.08.29.555397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Single cell proteomics (SCP) requires the analysis of dozens to thousands of single human cells to draw biological conclusions. However, assessing of the abundance of single proteins in output data presents a considerable challenge, and no simple universal solutions currently exist. To address this, we developed SCP Viz, a statistical package with a graphical user interface that can handle small and large scale SCP output from any instrument or data processing software. In this software, the abundance of individual proteins can be plotted in a variety of ways, using either unadjusted or normalized outputs. These outputs can also be transformed or imputed within the software. SCP Viz offers a variety of plotting options which can help identify significantly altered proteins between groups, both before and after quantitative transformations. Upon the discovery of subpopulations of single cells, users can easily regroup the cells of interest using straightforward text-based filters. When used in this way, SCP Viz allows users to visualize proteomic heterogeneity at the level of individual proteins, cells, or identified subcellular populations. SCP Viz is compatible with output files from MaxQuant, FragPipe, SpectroNaut, and Proteome Discoverer, and should work equally well with other formats. SCP Viz is publicly available at https://github.com/orsburn/SCPViz. For demonstrations, users can download our test data from GitHub and use an online version that accepts user input for analysis at https://orsburnlab.shinyapps.io/SCPViz/.
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Affiliation(s)
- Ahmed Warshanna
- The Department of Pharmacology and Molecular Sciences; The Johns Hopkins University School of Medicine, Baltimore, MD, USA, 21205
| | - Benjamin C. Orsburn
- The Department of Pharmacology and Molecular Sciences; The Johns Hopkins University School of Medicine, Baltimore, MD, USA, 21205
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28
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Matzinger M, Mechtler K. Improving single cell proteomics experiments: how can we best utilize latest-generation data acquisition and MS instrument architecture? Expert Rev Proteomics 2023; 20:193-195. [PMID: 37715641 DOI: 10.1080/14789450.2023.2260954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 08/02/2023] [Accepted: 08/07/2023] [Indexed: 09/18/2023]
Affiliation(s)
| | - Karl Mechtler
- Institute of Molecular Pathology (IMP), Vienna, Austria
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Vienna, Austria
- Gregor Mendel Institute of Molecular Plant Biology (GMI) of the Austrian Academy of Sciences, Vienna, Austria
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29
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Slavov N. Single-cell proteomics: quantifying post-transcriptional regulation during development with mass-spectrometry. Development 2023; 150:dev201492. [PMID: 37387573 PMCID: PMC10323229 DOI: 10.1242/dev.201492] [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: 07/01/2023]
Abstract
Many developmental processes are regulated post-transcriptionally. Such post-transcriptional regulatory mechanisms can now be analyzed by robust single-cell mass spectrometry methods that allow accurate quantification of proteins and their modification in single cells. These methods can enable quantitative exploration of protein synthesis and degradation mechanisms that contribute to developmental cell fate specification. Furthermore, they may support functional analysis of protein conformations and activities in single cells, and thus link protein functions to developmental processes. This Spotlight provides an accessible introduction to single-cell mass spectrometry methods and suggests initial biological questions that are ripe for investigation.
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Affiliation(s)
- 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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30
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Rojas BE, Iglesias AA. Integrating multiple regulations on enzyme activity: the case of phospho enolpyruvate carboxykinases. AOB PLANTS 2023; 15:plad053. [PMID: 37608926 PMCID: PMC10441589 DOI: 10.1093/aobpla/plad053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 07/27/2023] [Indexed: 08/24/2023]
Abstract
Data on protein post-translational modifications (PTMs) increased exponentially in the last years due to the refinement of mass spectrometry techniques and the development of databases to store and share datasets. Nevertheless, these data per se do not create comprehensive biochemical knowledge. Complementary studies on protein biochemistry are necessary to fully understand the function of these PTMs at the molecular level and beyond, for example, designing rational metabolic engineering strategies to improve crops. Phosphoenolpyruvate carboxykinases (PEPCKs) are critical enzymes for plant metabolism with diverse roles in plant development and growth. Multiple lines of evidence showed the complex regulation of PEPCKs, including PTMs. Herein, we present PEPCKs as an example of the integration of combined mechanisms modulating enzyme activity and metabolic pathways. PEPCK studies strongly advanced after the production of the recombinant enzyme and the establishment of standardized biochemical assays. Finally, we discuss emerging open questions for future research and the challenges in integrating all available data into functional biochemical models.
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Affiliation(s)
- Bruno E Rojas
- Instituto de Agrobiotecnología del Litoral, UNL, CONICET, FBCB, Santa Fe, Argentina
| | - Alberto A Iglesias
- Instituto de Agrobiotecnología del Litoral, UNL, CONICET, FBCB, Santa Fe, Argentina
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31
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Schäfer JA, Sutandy FXR, Münch C. Omics-based approaches for the systematic profiling of mitochondrial biology. Mol Cell 2023; 83:911-926. [PMID: 36931258 DOI: 10.1016/j.molcel.2023.02.015] [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: 11/11/2022] [Revised: 02/06/2023] [Accepted: 02/14/2023] [Indexed: 03/18/2023]
Abstract
Mitochondria are essential for cellular functions such as metabolism and apoptosis. They dynamically adapt to the changing environmental demands by adjusting their protein, nucleic acid, metabolite, and lipid contents. In addition, the mitochondrial components are modulated on different levels in response to changes, including abundance, activity, and interaction. A wide range of omics-based approaches has been developed to be able to explore mitochondrial adaptation and how mitochondrial function is compromised in disease contexts. Here, we provide an overview of the omics methods that allow us to systematically investigate the different aspects of mitochondrial biology. In addition, we show examples of how these methods have provided new biological insights. The emerging use of these toolboxes provides a more comprehensive understanding of the processes underlying mitochondrial function.
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Affiliation(s)
- Jasmin Adriana Schäfer
- Institute of Biochemistry II, Goethe University Frankfurt, Theodor-Stern-Kai 7, Haus 75, 60590 Frankfurt am Main, Germany
| | - F X Reymond Sutandy
- Institute of Biochemistry II, Goethe University Frankfurt, Theodor-Stern-Kai 7, Haus 75, 60590 Frankfurt am Main, Germany
| | - Christian Münch
- Institute of Biochemistry II, Goethe University Frankfurt, Theodor-Stern-Kai 7, Haus 75, 60590 Frankfurt am Main, Germany.
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32
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Orsburn BC. Time-of-Flight Fragmentation Spectra Generated by the Proteomic Analysis of Single Human Cells Do Not Exhibit Atypical Fragmentation Patterns. J Proteome Res 2023; 22:1003-1008. [PMID: 36700448 PMCID: PMC10502792 DOI: 10.1021/acs.jproteome.2c00715] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Indexed: 01/27/2023]
Abstract
Recent work detailed the unique characteristics of fragmentation spectra derived from peptides from single human cells. This valuable report utilized an ultrahigh-field Orbitrap and directly compared the spectra obtained from high-concentration bulk cell HeLa lysates to those obtained from nanogram dilutions of the same and from nanowell-processed single HeLa cells. The analysis demonstrated marked differences between the fragmentation spectra generated at high and single-cell loads, most strikingly, the loss of high-mass y-series fragment ions. As significant differences exist in the physics of Orbitrap and time-of-flight mass analyzers, a comparison appeared warranted. A similar analysis was performed using isolated single pancreatic cancer cells compared to pools consisting of 100 cells. While a reanalysis of the prior Orbitrap data supports the author's original findings, the same trends are not observed in time-of-flight mass spectra of peptides from single human cells. The results are particularly striking when directly comparing the matched intensity fragment values between bulk and single-cell data generated on the same mass analyzers. Instrument acquisition files, processed data, and spectrum libraries are publicly available on MASSIVE via accession MSV000090635.
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Affiliation(s)
- Benjamin C. Orsburn
- The Department of Pharmacology
and Molecular SciencesThe Johns Hopkins
University School of Medicine, Baltimore, Maryland21205, United States
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33
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Single-cell proteomics enabled by next-generation sequencing or mass spectrometry. Nat Methods 2023; 20:363-374. [PMID: 36864196 DOI: 10.1038/s41592-023-01791-5] [Citation(s) in RCA: 84] [Impact Index Per Article: 84.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 01/24/2023] [Indexed: 03/04/2023]
Abstract
In the last decade, single-cell RNA sequencing routinely performed on large numbers of single cells has greatly advanced our understanding of the underlying heterogeneity of complex biological systems. Technological advances have also enabled protein measurements, further contributing to the elucidation of cell types and states present in complex tissues. Recently, there have been independent advances in mass spectrometric techniques bringing us one step closer to characterizing single-cell proteomes. Here we discuss the challenges of detecting proteins in single cells by both mass spectrometry and sequencing-based methods. We review the state of the art for these techniques and propose that there is a space for technological advancements and complementary approaches that maximize the advantages of both classes of technologies.
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