1
|
Veličković M, Fillmore TL, Attah IK, 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 the Tissue Microenvironment. Anal Chem 2024; 96:12973-12982. [PMID: 39089681 PMCID: PMC11325296 DOI: 10.1021/acs.analchem.4c00523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity in a cell-type-specific manner to better understand and predict the function of complex biological systems such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverage 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), multiplexed isobaric labeling, and a nanoflow peptide fractionation approach. The integrated workflow allowed us to maximize proteome coverage of laser-isolated tissue samples containing nanogram levels of proteins. We demonstrated that the deep spatial proteomics platform can quantify more than 5000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 μm2) and differentiate unique protein abundance patterns in pancreas. Furthermore, the use of the microPOTS chip eliminated the requirement for advanced microfabrication capabilities and specialized nanoliter liquid handling equipment, making it more accessible to proteomic laboratories.
Collapse
Affiliation(s)
- Marija Veličković
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Thomas L Fillmore
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Isaac Kwame Attah
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Camilo Posso
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - James C Pino
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Rui Zhao
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Sarah M Williams
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Dušan Veličković
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Jon M Jacobs
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Kristin E Burnum-Johnson
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Ying Zhu
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Paul D Piehowski
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| |
Collapse
|
2
|
Wu R, Veličković M, Burnum-Johnson KE. From single cell to spatial multi-omics: unveiling molecular mechanisms in dynamic and heterogeneous systems. Curr Opin Biotechnol 2024; 89:103174. [PMID: 39126877 DOI: 10.1016/j.copbio.2024.103174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Accepted: 07/02/2024] [Indexed: 08/12/2024]
Abstract
Single-cell multi-omics and spatial technology have been widely applied to biomedical studies and recently to environmental studies. The cell size detected by single-cell omics ranges from ∼2 µm (e.g., Bacillus subtilis) to ∼120 µm (e.g., human oocytes). Simultaneous detection of single-cell multi-omics is available to human and plant tissues while limited to microbial samples. Spatial technology enables mapping the detected biomolecules in situ. The recent advances in Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging and Micro/Nanodroplet Processing in One Pot for Trace Samples for the first time allow the application of spatial multi-omics in highly heterogeneous environmental samples composed of plants, fungi, and bacteria. We envision that these technologies will continue to advance our understanding of unique cell types, their developmental trajectory, and the intercellular signaling and interaction within biological samples.
Collapse
Affiliation(s)
- Ruonan Wu
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Marija Veličković
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Kristin E Burnum-Johnson
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, USA.
| |
Collapse
|
3
|
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.
Collapse
Affiliation(s)
- Benjamin C Orsburn
- The Johns Hopkins University Medical School, Baltimore, Maryland 21215, United States
| |
Collapse
|
4
|
Riley RM, Negri GL, Cheng SWG, Spencer Miko SE, Morin RD, Morin GB. Mass Spectrometry Acquisition and Fractionation Recommendations for TMT11 and TMT16 Labeled Samples. J Proteome Res 2024; 23:3704-3715. [PMID: 38943634 DOI: 10.1021/acs.jproteome.4c00014] [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: 07/01/2024]
Abstract
Proteome coverage and accurate protein quantification are both important for evaluating biological systems; however, compromises between quantification, coverage, and mass spectrometry (MS) resources are often necessary. Consequently, experimental parameters that impact coverage and quantification must be adjusted, depending on experimental goals. Among these parameters is offline prefractionation, which is utilized in MS-based proteomics to decrease sample complexity resulting in higher overall proteome coverage upon MS analysis. Prefractionation leads to increases in required MS analysis time, although this is often mitigated by isobaric labeling using tandem-mass tags (TMT), which allow samples to be multiplexed. Here we evaluate common prefractionation schemes, TMT variants, and MS acquisition methods and their impact on protein quantification and coverage. Furthermore, we provide recommendations for experimental design depending on the experimental goals.
Collapse
Affiliation(s)
- Ryan M Riley
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver V5Z 1L3, Canada
| | - Gian Luca Negri
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver V5Z 1L3, Canada
| | - S-W Grace Cheng
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver V5Z 1L3, Canada
| | | | - Ryan D Morin
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver V5Z 1L3, Canada
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby V5A 1S6, Canada
| | - Gregg B Morin
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver V5Z 1L3, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver V6T 1Z4, Canada
| |
Collapse
|
5
|
Callahan A, Chua XY, Griffith AA, Hildebrandt T, Fu G, Hu M, Wen R, Salomon AR. Deep phosphotyrosine characterisation of primary murine T cells using broad spectrum optimisation of selective triggering. Proteomics 2024:e2400106. [PMID: 39091061 DOI: 10.1002/pmic.202400106] [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: 04/01/2024] [Revised: 07/11/2024] [Accepted: 07/12/2024] [Indexed: 08/04/2024]
Abstract
Sequencing the tyrosine phosphoproteome using MS-based proteomics is challenging due to the low abundance of tyrosine phosphorylation in cells, a challenge compounded in scarce samples like primary cells or clinical samples. The broad-spectrum optimisation of selective triggering (BOOST) method was recently developed to increase phosphotyrosine sequencing in low protein input samples by leveraging tandem mass tags (TMT), phosphotyrosine enrichment, and a phosphotyrosine-loaded carrier channel. Here, we demonstrate the viability of BOOST in T cell receptor (TCR)-stimulated primary murine T cells by benchmarking the accuracy and precision of the BOOST method and discerning significant alterations in the phosphoproteome associated with receptor stimulation. Using 1 mg of protein input (about 20 million cells) and BOOST, we identify and precisely quantify more than 2000 unique pY sites compared to about 300 unique pY sites in non-BOOST control samples. We show that although replicate variation increases when using the BOOST method, BOOST does not jeopardise quantitative precision or the ability to determine statistical significance for peptides measured in triplicate. Many pY previously uncharacterised sites on important T cell signalling proteins are quantified using BOOST, and we identify new TCR responsive pY sites observable only with BOOST. Finally, we determine that the phase-spectrum deconvolution method on Orbitrap instruments can impair pY quantitation in BOOST experiments.
Collapse
Affiliation(s)
- Aurora Callahan
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, Rhode Island, USA
| | - Xien Yu Chua
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, Rhode Island, USA
| | - Alijah A Griffith
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, Rhode Island, USA
| | - Tobias Hildebrandt
- Department of Molecular Pharmacology, Physiology, and Biotechnology, Brown University, Providence, Rhode Island, USA
| | - Guoping Fu
- Versiti Blood Research Institute, Milwaukee, Wisconsin, USA
| | - Mengzhou Hu
- Department of Molecular Pharmacology, Physiology, and Biotechnology, Brown University, Providence, Rhode Island, USA
| | - Renren Wen
- Versiti Blood Research Institute, Milwaukee, Wisconsin, USA
| | - Arthur R Salomon
- Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, Rhode Island, USA
- Department of Molecular Pharmacology, Physiology, and Biotechnology, Brown University, Providence, Rhode Island, USA
| |
Collapse
|
6
|
Ghosh G, Shannon AE, Searle BC. Data acquisition approaches for single cell proteomics. Proteomics 2024:e2400022. [PMID: 39088833 DOI: 10.1002/pmic.202400022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2024] [Revised: 07/09/2024] [Accepted: 07/10/2024] [Indexed: 08/03/2024]
Abstract
Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome analysis may overlook, which is essential for understanding disease mechanisms and developing targeted therapies. Mass spectrometry (MS) methods in SCP allow the identification and quantification of thousands of proteins from individual cells. Two major challenges in SCP are the limited material in single-cell samples necessitating highly sensitive analytical techniques and the efficient processing of samples, as each biological sample requires thousands of single cell measurements. This review discusses MS advancements to mitigate these challenges using data-dependent acquisition (DDA) and data-independent acquisition (DIA). Additionally, we examine the use of short liquid chromatography gradients and sample multiplexing methods that increase the sample throughput and scalability of SCP experiments. We believe these methods will pave the way for improving our understanding of cellular heterogeneity and its implications for systems biology.
Collapse
Affiliation(s)
- Gautam Ghosh
- Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio, USA
- Pelotonia Institute for Immuno-Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio, USA
| | - Ariana E Shannon
- Pelotonia Institute for Immuno-Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio, USA
- Department of Biomedical Informatics, The Ohio State University Medical Center, Columbus, Ohio, USA
| | - Brian C Searle
- Ohio State Biochemistry Program, The Ohio State University, Columbus, Ohio, USA
- Pelotonia Institute for Immuno-Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio, USA
- Department of Biomedical Informatics, The Ohio State University Medical Center, Columbus, Ohio, USA
| |
Collapse
|
7
|
Sun F, Li H, Sun D, Fu S, Gu L, Shao X, Wang Q, Dong X, Duan B, Xing F, Wu J, Xiao M, Zhao F, Han JDJ, Liu Q, Fan X, Li C, Wang C, Shi T. Single-cell omics: experimental workflow, data analyses and applications. SCIENCE CHINA. LIFE SCIENCES 2024:10.1007/s11427-023-2561-0. [PMID: 39060615 DOI: 10.1007/s11427-023-2561-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/18/2024] [Indexed: 07/28/2024]
Abstract
Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.
Collapse
Affiliation(s)
- Fengying Sun
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China
| | - Haoyan Li
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Dongqing Sun
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Shaliu Fu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Lei Gu
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Shao
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China
| | - Qinqin Wang
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Dong
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Bin Duan
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Feiyang Xing
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Jun Wu
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Minmin Xiao
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
| | - Fangqing Zhao
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Qi Liu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China.
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China.
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China.
- Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China.
| | - Chen Li
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Chenfei Wang
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Tieliu Shi
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
- Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, School of Statistics, East China Normal University, Shanghai, 200062, China.
| |
Collapse
|
8
|
Campbell AJ, Cakar S, Palstrøm NB, Riber LP, Rasmussen LM, Beck HC. A carrier-based quantitative proteomics method applied to biomarker discovery in pericardial fluid. Mol Cell Proteomics 2024:100812. [PMID: 39004188 DOI: 10.1016/j.mcpro.2024.100812] [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: 12/20/2023] [Revised: 07/03/2024] [Accepted: 07/10/2024] [Indexed: 07/16/2024] Open
Abstract
Data-dependent liquid chromatography tandem mass spectrometry (LC-MS/MS) is challenged by the large concentration range of proteins in plasma and related fluids. We adapted the SCoPE method from single-cell proteomics to pericardial fluid, where a myocardial tissue carrier was used to aid protein quantification. The carrier proteome and patient samples were labeled with distinct isobaric labels, which allowed separate quantification. Undepleted pericardial fluid from patients with type 2 diabetes mellitus and/or heart failure undergoing heart surgery was analyzed with either a traditional LC-MS/MS method or with the carrier proteome. In total, 1398 proteins were quantified with a carrier, compared to 265 without, and a higher proportion of these proteins were of myocardial origin. The number of differentially expressed proteins also increased nearly four-fold. For patients with both heart failure and type 2 diabetes mellitus, pathway analysis of upregulated proteins demonstrated enrichment of immune activation, blood coagulation, and stress pathways. Overall, our work demonstrates the applicability of a carrier for enhanced protein quantification in challenging biological matrices such as pericardial fluid, with potential applications for biomarker discovery. Mass spectrometry data are available via ProteomeXchange with identifier PXD053450.
Collapse
Affiliation(s)
- Amanda J Campbell
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark; Center for Clinical Proteomics (CCP), Odense University Hospital, Odense, Denmark
| | - Samir Cakar
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark; Center for Clinical Proteomics (CCP), Odense University Hospital, Odense, Denmark
| | - Nicolai B Palstrøm
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark; Center for Clinical Proteomics (CCP), Odense University Hospital, Odense, Denmark; Department of Clinical Research, Faculty of Health Science, University of Southern Denmark, Odense, Denmark
| | - Lars P Riber
- Department of Cardiac, Thoracic and Vascular Surgery, Odense University Hospital, Odense, Denmark; Department of Clinical Research, Faculty of Health Science, University of Southern Denmark, Odense, Denmark
| | - Lars M Rasmussen
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark; Center for Clinical Proteomics (CCP), Odense University Hospital, Odense, Denmark; Center for Individualized Medicine in Arterial Diseases (CIMA), Odense University Hospital, Odense, Denmark; Department of Clinical Research, Faculty of Health Science, University of Southern Denmark, Odense, Denmark
| | - Hans C Beck
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark; Center for Clinical Proteomics (CCP), Odense University Hospital, Odense, Denmark; Center for Individualized Medicine in Arterial Diseases (CIMA), Odense University Hospital, Odense, Denmark; Department of Clinical Research, Faculty of Health Science, University of Southern Denmark, Odense, Denmark
| |
Collapse
|
9
|
Kwon Y, Woo J, Yu F, Williams SM, Markillie LM, Moore RJ, Nakayasu ES, Chen J, Campbell-Thompson M, Mathews CE, Nesvizhskii AI, Qian WJ, Zhu Y. Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.04.583367. [PMID: 38496682 PMCID: PMC10942300 DOI: 10.1101/2024.03.04.583367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 µm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.
Collapse
Affiliation(s)
- Yumi Kwon
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Jongmin Woo
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, United States
| | - Sarah M. Williams
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Lye Meng Markillie
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Ronald J. Moore
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Ernesto S. Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Jing Chen
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL 32610, United States
| | - Martha Campbell-Thompson
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL 32610, United States
| | - Clayton E. Mathews
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL 32610, United States
| | - Alexey I. Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, United States
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, United States
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Ying Zhu
- Department of Proteomic and Genomic Technologies, Genentech Inc., 1 DNA Way, South San Francisco, CA 94080, United States
| |
Collapse
|
10
|
Nitz AA, Giraldez Chavez JH, Eliason ZG, Payne SH. Are We There Yet? Assessing the Readiness of Single-Cell Proteomics to Answer Biological Hypotheses. J Proteome Res 2024. [PMID: 38981598 DOI: 10.1021/acs.jproteome.4c00091] [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: 07/11/2024]
Abstract
Single-cell analysis is an active area of research in many fields of biology. Measurements at single-cell resolution allow researchers to study diverse populations without losing biologically meaningful information to sample averages. Many technologies have been used to study single cells, including mass spectrometry-based single-cell proteomics (SCP). SCP has seen a lot of growth over the past couple of years through improvements in data acquisition and analysis, leading to greater proteomic depth. Because method development has been the main focus in SCP, biological applications have been sprinkled in only as proof-of-concept. However, SCP methods now provide significant coverage of the proteome and have been implemented in many laboratories. Thus, a primary question to address in our community is whether the current state of technology is ready for widespread adoption for biological inquiry. In this Perspective, we examine the potential for SCP in three thematic areas of biological investigation: cell annotation, developmental trajectories, and spatial mapping. We identify that the primary limitation of SCP is sample throughput. As proteome depth has been the primary target for method development to date, we advocate for a change in focus to facilitate measuring tens of thousands of single-cell proteomes to enable biological applications beyond proof-of-concept.
Collapse
Affiliation(s)
- Alyssa A Nitz
- Biology Department, Brigham Young University, Provo, Utah 84602, United States
| | | | - Zachary G Eliason
- Biology Department, Brigham Young University, Provo, Utah 84602, United States
| | - Samuel H Payne
- Biology Department, Brigham Young University, Provo, Utah 84602, United States
| |
Collapse
|
11
|
Ctortecka C, Clark NM, Boyle BW, Seth A, Mani DR, Udeshi ND, Carr SA. Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications. Nat Commun 2024; 15:5707. [PMID: 38977691 PMCID: PMC11231172 DOI: 10.1038/s41467-024-49651-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: 01/24/2024] [Accepted: 06/14/2024] [Indexed: 07/10/2024] Open
Abstract
The recent technological and computational advances in mass spectrometry-based single-cell proteomics have pushed the boundaries of sensitivity and throughput. However, reproducible quantification of thousands of proteins within a single cell remains challenging. To address some of those limitations, we present a dedicated sample preparation chip, the proteoCHIP EVO 96 that directly interfaces with the Evosep One. This, in combination with the Bruker timsTOF demonstrates double the identifications without manual sample handling and the newest generation timsTOF Ultra identifies up to 4000 with an average of 3500 protein groups per single HEK-293T without a carrier or match-between runs. Our workflow spans 4 orders of magnitude, identifies over 50 E3 ubiquitin-protein ligases, and profiles key regulatory proteins upon small molecule stimulation. This study demonstrates that the proteoCHIP EVO 96-based sample preparation with the timsTOF Ultra provides sufficient proteome depth to study complex biology beyond cell-type classifications.
Collapse
Affiliation(s)
| | | | - Brian W Boyle
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - D R Mani
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Steven A Carr
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| |
Collapse
|
12
|
Vitale GA, Geibel C, Minda V, Wang M, Aron AT, Petras D. Connecting metabolome and phenotype: recent advances in functional metabolomics tools for the identification of bioactive natural products. Nat Prod Rep 2024; 41:885-904. [PMID: 38351834 PMCID: PMC11186733 DOI: 10.1039/d3np00050h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Indexed: 06/20/2024]
Abstract
Covering: 1995 to 2023Advances in bioanalytical methods, particularly mass spectrometry, have provided valuable molecular insights into the mechanisms of life. Non-targeted metabolomics aims to detect and (relatively) quantify all observable small molecules present in a biological system. By comparing small molecule abundances between different conditions or timepoints in a biological system, researchers can generate new hypotheses and begin to understand causes of observed phenotypes. Functional metabolomics aims to investigate the functional roles of metabolites at the scale of the metabolome. However, most functional metabolomics studies rely on indirect measurements and correlation analyses, which leads to ambiguity in the precise definition of functional metabolomics. In contrast, the field of natural products has a history of identifying the structures and bioactivities of primary and specialized metabolites. Here, we propose to expand and reframe functional metabolomics by integrating concepts from the fields of natural products and chemical biology. We highlight emerging functional metabolomics approaches that shift the focus from correlation to physical interactions, and we discuss how this allows researchers to uncover causal relationships between molecules and phenotypes.
Collapse
Affiliation(s)
- Giovanni Andrea Vitale
- CMFI Cluster of Excellence, Interfaculty Institute of Microbiology and Medicine, University of Tuebingen, Tuebingen, Germany
| | - Christian Geibel
- CMFI Cluster of Excellence, Interfaculty Institute of Microbiology and Medicine, University of Tuebingen, Tuebingen, Germany
| | - Vidit Minda
- Division of Pharmacology and Pharmaceutical Sciences, University of Missouri - Kansas City, Kansas City, USA
- Department of Chemistry and Biochemistry, University of Denver, Denver, USA.
| | - Mingxun Wang
- Department of Computer Science, University of California Riverside, Riverside, USA.
| | - Allegra T Aron
- Department of Chemistry and Biochemistry, University of Denver, Denver, USA.
| | - Daniel Petras
- CMFI Cluster of Excellence, Interfaculty Institute of Microbiology and Medicine, University of Tuebingen, Tuebingen, Germany
- Department of Biochemistry, University of California Riverside, Riverside, USA.
| |
Collapse
|
13
|
Pang M, Jones JJ, Wang TY, Quan B, Kubat NJ, Qiu Y, Roukes ML, Chou TF. Increasing Proteome Coverage Through a Reduction in Analyte Complexity in Single-Cell Equivalent Samples. J Proteome Res 2024. [PMID: 38832920 DOI: 10.1021/acs.jproteome.4c00062] [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: 06/06/2024]
Abstract
The advancement of sophisticated instrumentation in mass spectrometry has catalyzed an in-depth exploration of complex proteomes. This exploration necessitates a nuanced balance in experimental design, particularly between quantitative precision and the enumeration of analytes detected. In bottom-up proteomics, a key challenge is that oversampling of abundant proteins can adversely affect the identification of a diverse array of unique proteins. This issue is especially pronounced in samples with limited analytes, such as small tissue biopsies or single-cell samples. Methods such as depletion and fractionation are suboptimal to reduce oversampling in single cell samples, and other improvements on LC and mass spectrometry technologies and methods have been developed to address the trade-off between precision and enumeration. We demonstrate that by using a monosubstrate protease for proteomic analysis of single-cell equivalent digest samples, an improvement in quantitative accuracy can be achieved, while maintaining high proteome coverage established by trypsin. This improvement is particularly vital for the field of single-cell proteomics, where single-cell samples with limited number of protein copies, especially in the context of low-abundance proteins, can benefit from considering analyte complexity. Considerations about analyte complexity, alongside chromatographic complexity, integration with data acquisition methods, and other factors such as those involving enzyme kinetics, will be crucial in the design of future single-cell workflows.
Collapse
Affiliation(s)
- Marion Pang
- Division of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| | - Jeff J Jones
- Division of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| | - Ting-Yu Wang
- Division of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| | - Baiyi Quan
- Division of Physics, Mathematics and Astronomy, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| | - Nicole J Kubat
- Division of Physics, Mathematics and Astronomy, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| | - Yanping Qiu
- Division of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| | - Michael L Roukes
- Division of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
- Division of Physics, Mathematics and Astronomy, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
- Division of Engineering and Applied Science, California Institute of Technology, 1200 East California Blvd, Pasadena, California 91125, United States
| | - Tsui-Fen Chou
- Division of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| |
Collapse
|
14
|
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
| |
Collapse
|
15
|
Peters-Clarke TM, Liang Y, Mertz KL, Lee KW, Westphall MS, Hinkle JD, McAlister GC, Syka JEP, Kelly RT, Coon JJ. Boosting the Sensitivity of Quantitative Single-Cell Proteomics with Infrared-Tandem Mass Tags. J Proteome Res 2024. [PMID: 38713017 DOI: 10.1021/acs.jproteome.4c00076] [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: 05/08/2024]
Abstract
Single-cell proteomics is a powerful approach to precisely profile protein landscapes within individual cells toward a comprehensive understanding of proteomic functions and tissue and cellular states. The inherent challenges associated with limited starting material demand heightened analytical sensitivity. Just as advances in sample preparation maximize the amount of material that makes it from the cell to the mass spectrometer, we strive to maximize the number of ions that make it from ion source to the detector. In isobaric tagging experiments, limited reporter ion generation limits quantitative accuracy and precision. The combination of infrared photoactivation and ion parking circumvents the m/z dependence inherent in HCD, maximizing reporter generation and avoiding unintended degradation of TMT reporter molecules in infrared-tandem mass tags (IR-TMT). The method was applied to single-cell human proteomes using 18-plex TMTpro, resulting in 4-5-fold increases in reporter signal compared to conventional SPS-MS3 approaches. IR-TMT enables faster duty cycles, higher throughput, and increased peptide identification and quantification. Comparative experiments showcase 4-5-fold lower injection times for IR-TMT, providing superior sensitivity without compromising accuracy. In all, IR-TMT enhances the dynamic range of proteomic experiments and is compatible with gas-phase fractionation and real-time searching, promising increased gains in the study of cellular heterogeneity.
Collapse
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
| | - Yiran Liang
- Department of Chemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Keaton L Mertz
- 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
| | - Kenneth W Lee
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Michael S Westphall
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Joshua D Hinkle
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | | | - John E P Syka
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Ryan T Kelly
- Department of Chemistry, Brigham Young University, Provo, Utah 84602, 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
- National Center for Quantitative Biology of Complex Systems, Madison, Wisconsin 53706, United States
- Morgridge Institute for Research, Madison, Wisconsin 53515, United States
| |
Collapse
|
16
|
Yu SH, Chen SC, Wu PS, Kuo PI, Chen TA, Lee HY, Lin MH. Quantification Quality Control Emerges as a Crucial Factor to Enhance Single-Cell Proteomics Data Analysis. Mol Cell Proteomics 2024; 23:100768. [PMID: 38621647 PMCID: PMC11103571 DOI: 10.1016/j.mcpro.2024.100768] [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: 11/30/2023] [Revised: 03/12/2024] [Accepted: 04/11/2024] [Indexed: 04/17/2024] Open
Abstract
Mass spectrometry (MS)-based single-cell proteomics (SCP) provides us the opportunity to unbiasedly explore biological variability within cells without the limitation of antibody availability. This field is rapidly developed with the main focuses on instrument advancement, sample preparation refinement, and signal boosting methods; however, the optimal data processing and analysis are rarely investigated which holds an arduous challenge because of the high proportion of missing values and batch effect. Here, we introduced a quantification quality control to intensify the identification of differentially expressed proteins (DEPs) by considering both within and across SCP data. Combining quantification quality control with isobaric matching between runs (IMBR) and PSM-level normalization, an additional 12% and 19% of proteins and peptides, with more than 90% of proteins/peptides containing valid values, were quantified. Clearly, quantification quality control was able to reduce quantification variations and q-values with the more apparent cell type separations. In addition, we found that PSM-level normalization performed similar to other protein-level normalizations but kept the original data profiles without the additional requirement of data manipulation. In proof of concept of our refined pipeline, six uniquely identified DEPs exhibiting varied fold-changes and playing critical roles for melanoma and monocyte functionalities were selected for validation using immunoblotting. Five out of six validated DEPs showed an identical trend with the SCP dataset, emphasizing the feasibility of combining the IMBR, cell quality control, and PSM-level normalization in SCP analysis, which is beneficial for future SCP studies.
Collapse
Affiliation(s)
- Sung-Huan Yu
- Institute of Precision Medicine, College of Medicine, National Sun Yat-sen University, Kaohsiung, Taiwan; School of Medicine, College of Medicine, National Sun Yat-sen University, Kaohsiung, Taiwan
| | - Shiau-Ching Chen
- Institute of Precision Medicine, College of Medicine, National Sun Yat-sen University, Kaohsiung, Taiwan
| | - Pei-Shan Wu
- Department of Microbiology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Pei-I Kuo
- Department of Microbiology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Ting-An Chen
- Department of Microbiology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Hsiang-Ying Lee
- Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan; Department of Urology, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Miao-Hsia Lin
- Department of Microbiology, National Taiwan University College of Medicine, Taipei, Taiwan.
| |
Collapse
|
17
|
Peterson C, Boekweg H, Presley E, Payne SH. Pushing the Isotopic Envelope: When carrier channels pollute their neighbors' signals. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.15.587811. [PMID: 38659808 PMCID: PMC11042363 DOI: 10.1101/2024.04.15.587811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Individual cells are the foundational unit of biology, and understanding their functions and interactions is critical to advancing our understanding of health and disease. Single cell proteomics has seen intense interest from mass spectrometrists, with a goal of quantifying the proteome of single cells by adapting current techniques used in bulk samples. To date, most method optimizations research has worked towards increasing the proteome coverage of single cells. One prominent technique multiplexes many individual cells into a single data acquisition event using isobaric labels. Accompanying the single cells, one label is typically used for a mixed set of many cells, called a carrier or boost channel. Although this improves peptide identification rates, several groups have examined the impact on quantitative accuracy as more cells are included in the carrier channel, e.g. 100x or 500x. This manuscript explores how impurities in the multiplexing reagent can lead to inaccurate quantification observed as a measurable signal in the wrong channel. We discover that the severe abundance differential between carrier and single cell, combined with the reagent impurities, can overshadow several channels typically used for single cells. For carrier amounts 100x and above, this contamination can be as abundant as true signal from a single cell. Therefore, we suggest limiting the carrier channel to a minimal amount and balance the goals of identification and quantification.
Collapse
Affiliation(s)
- Connor Peterson
- Biology Department, Brigham Young University, Provo UT 84604
| | - Hannah Boekweg
- Biology Department, Brigham Young University, Provo UT 84604
| | | | - Samuel H. Payne
- Biology Department, Brigham Young University, Provo UT 84604
| |
Collapse
|
18
|
Li W, Yang F, Wang F, Rong Y, Liu L, Wu B, Zhang H, Yao J. scPROTEIN: a versatile deep graph contrastive learning framework for single-cell proteomics embedding. Nat Methods 2024; 21:623-634. [PMID: 38504113 DOI: 10.1038/s41592-024-02214-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 02/16/2024] [Indexed: 03/21/2024]
Abstract
Single-cell proteomics sequencing technology sheds light on protein-protein interactions, posttranslational modifications and proteoform dynamics in the cell. However, the uncertainty estimation for peptide quantification, data missingness, batch effects and high noise hinder the analysis of single-cell proteomic data. It is important to solve this set of tangled problems together, but the existing methods tailored for single-cell transcriptomes cannot fully address this task. Here we propose a versatile framework designed for single-cell proteomics data analysis called scPROTEIN, which consists of peptide uncertainty estimation based on a multitask heteroscedastic regression model and cell embedding generation based on graph contrastive learning. scPROTEIN can estimate the uncertainty of peptide quantification, denoise protein data, remove batch effects and encode single-cell proteomic-specific embeddings in a unified framework. We demonstrate that scPROTEIN is efficient for cell clustering, batch correction, cell type annotation, clinical analysis and spatially resolved proteomic data exploration.
Collapse
Affiliation(s)
- Wei Li
- College of Artificial Intelligence, Nankai University, Tianjin, China
- AI Lab, Tencent, Shenzhen, China
| | - Fan Yang
- AI Lab, Tencent, Shenzhen, China
| | | | - Yu Rong
- AI Lab, Tencent, Shenzhen, China
| | | | | | - Han Zhang
- College of Artificial Intelligence, Nankai University, Tianjin, China.
| | | |
Collapse
|
19
|
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.
Collapse
Affiliation(s)
| | - Joseph Zaia
- Bioinformatics Program, Boston University, Boston, MA, USA.
- Department of Biochemistry and Cell Biology, Boston University, Boston, MA, USA.
| |
Collapse
|
20
|
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.
Collapse
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.
| |
Collapse
|
21
|
Schlotter T, Kloter T, Hengsteler J, Yang K, Zhan L, Ragavan S, Hu H, Zhang X, Duru J, Vörös J, Zambelli T, Nakatsuka N. Aptamer-Functionalized Interface Nanopores Enable Amino Acid-Specific Peptide Detection. ACS NANO 2024; 18:6286-6297. [PMID: 38355286 PMCID: PMC10906075 DOI: 10.1021/acsnano.3c10679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 02/06/2024] [Accepted: 02/08/2024] [Indexed: 02/16/2024]
Abstract
Single-molecule proteomics based on nanopore technology has made significant advances in recent years. However, to achieve nanopore sensing with single amino acid resolution, several bottlenecks must be tackled: controlling nanopore sizes with nanoscale precision and slowing molecular translocation events. Herein, we address these challenges by integrating amino acid-specific DNA aptamers into interface nanopores with dynamically tunable pore sizes. A phenylalanine aptamer was used as a proof-of-concept: aptamer recognition of phenylalanine moieties led to the retention of specific peptides, slowing translocation speeds. Importantly, while phenylalanine aptamers were isolated against the free amino acid, the aptamers were determined to recognize the combination of the benzyl or phenyl and the carbonyl group in the peptide backbone, enabling binding to specific phenylalanine-containing peptides. We decoupled specific binding between aptamers and phenylalanine-containing peptides from nonspecific interactions (e.g., electrostatics and hydrophobic interactions) using optical waveguide lightmode spectroscopy. Aptamer-modified interface nanopores differentiated peptides containing phenylalanine vs. control peptides with structurally similar amino acids (i.e., tyrosine and tryptophan). When the duration of aptamer-target interactions inside the nanopore were prolonged by lowering the applied voltage, discrete ionic current levels with repetitive motifs were observed. Such reoccurring signatures in the measured signal suggest that the proposed method has the possibility to resolve amino acid-specific aptamer recognition, a step toward single-molecule proteomics.
Collapse
Affiliation(s)
- Tilman Schlotter
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Tom Kloter
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Julian Hengsteler
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Kyungae Yang
- Department
of Medicine, Columbia University Irving
Medical Center, New York, New York 10032, United States
| | - Lijian Zhan
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Sujeni Ragavan
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Haiying Hu
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Xinyu Zhang
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Jens Duru
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - János Vörös
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Tomaso Zambelli
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Nako Nakatsuka
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| |
Collapse
|
22
|
Joshi SK, Piehowski P, Liu T, Gosline SJC, McDermott JE, Druker BJ, Traer E, Tyner JW, Agarwal A, Tognon CE, Rodland KD. Mass Spectrometry-Based Proteogenomics: New Therapeutic Opportunities for Precision Medicine. Annu Rev Pharmacol Toxicol 2024; 64:455-479. [PMID: 37738504 PMCID: PMC10950354 DOI: 10.1146/annurev-pharmtox-022723-113921] [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: 09/24/2023]
Abstract
Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding the regulatory processes converting genotypes to phenotypes, often with an emphasis on gaining a deeper understanding of disease processes. Although specific genetic mutations have long been known to drive the development of multiple cancers, gene mutations alone do not always predict prognosis or response to targeted therapy. The benefit of proteogenomics research is that information obtained from proteins and their corresponding pathways provides insight into therapeutic targets that can complement genomic information by providing an additional dimension regarding the underlying mechanisms and pathophysiology of tumors. This review describes the novel insights into tumor biology and drug resistance derived from proteogenomic analysis while highlighting the clinical potential of proteogenomic observations and advances in technique and analysis tools.
Collapse
Affiliation(s)
- Sunil K Joshi
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Division of Hematology and Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Paul Piehowski
- Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Tao Liu
- Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Sara J C Gosline
- Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Jason E McDermott
- Pacific Northwest National Laboratory, Richland, Washington, USA
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, Oregon, USA
| | - Brian J Druker
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Division of Hematology and Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Elie Traer
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Division of Hematology and Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Jeffrey W Tyner
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Division of Hematology and Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, Oregon, USA
| | - Anupriya Agarwal
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Division of Hematology and Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA
- Department of Molecular Microbiology and Immunology, Oregon Health & Science University, Portland, Oregon, USA
| | - Cristina E Tognon
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Division of Hematology and Medical Oncology, Department of Medicine, Oregon Health & Science University, Portland, Oregon, USA
| | - Karin D Rodland
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA;
- Pacific Northwest National Laboratory, Richland, Washington, USA
| |
Collapse
|
23
|
Ctortecka C, Clark NM, Boyle B, Seth A, Mani DR, Udeshi ND, Carr SA. Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.20.576369. [PMID: 38328197 PMCID: PMC10849471 DOI: 10.1101/2024.01.20.576369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Mass spectrometry (MS)-based single-cell proteomics (SCP) has gained massive attention as a viable complement to other single cell approaches. The rapid technological and computational advances in the field have pushed the boundaries of sensitivity and throughput. However, reproducible quantification of thousands of proteins within a single cell at reasonable proteome depth to characterize biological phenomena remains a challenge. To address some of those limitations we present a combination of fully automated single cell sample preparation utilizing a dedicated chip within the picolitre dispensing robot, the cellenONE. The proteoCHIP EVO 96 can be directly interfaced with the Evosep One chromatographic system for in-line desalting and highly reproducible separation with a throughput of 80 samples per day. This, in combination with the Bruker timsTOF MS instruments, demonstrates double the identifications without manual sample handling. Moreover, relative to standard high-performance liquid chromatography, the Evosep One separation provides further 2-fold improvement in protein identifications. The implementation of the newest generation timsTOF Ultra with our proteoCHIP EVO 96-based sample preparation workflow reproducibly identifies up to 4,000 proteins per single HEK-293T without a carrier or match-between runs. Our current SCP depth spans over 4 orders of magnitude and identifies over 50 biologically relevant ubiquitin ligases. We complement our highly reproducible single-cell proteomics workflow to profile hundreds of lipopolysaccharide (LPS)-perturbed THP-1 cells and identified key regulatory proteins involved in interleukin and interferon signaling. This study demonstrates that the proteoCHIP EVO 96-based SCP sample preparation with the timsTOF Ultra provides sufficient proteome depth to study complex biology beyond cell-type classifications.
Collapse
Affiliation(s)
- Claudia Ctortecka
- Broad Institute of MIT and Harvard, 415 Main Street, 02142 Cambridge, MA, USA
| | - Natalie M. Clark
- Broad Institute of MIT and Harvard, 415 Main Street, 02142 Cambridge, MA, USA
| | - Brian Boyle
- Broad Institute of MIT and Harvard, 415 Main Street, 02142 Cambridge, MA, USA
| | - Anjali Seth
- Cellenion SASU, 60F avenue Rockefeller, 69008 Lyon, France
| | - D. R. Mani
- Broad Institute of MIT and Harvard, 415 Main Street, 02142 Cambridge, MA, USA
| | - Namrata D. Udeshi
- Broad Institute of MIT and Harvard, 415 Main Street, 02142 Cambridge, MA, USA
| | - Steven A. Carr
- Broad Institute of MIT and Harvard, 415 Main Street, 02142 Cambridge, MA, USA
| |
Collapse
|
24
|
Naval P, Pañeda LP, Athanasopoulou M, Teppo JS, Zubarev RA, Végvári Á. EquiCP: Targeted Single-Cell Proteomics by Mass Spectrometry with Isobaric Labeled Multiplexing. Methods Mol Biol 2024; 2817:133-143. [PMID: 38907152 DOI: 10.1007/978-1-0716-3934-4_11] [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
Nontargeted single-cell proteomics analysis by mass spectrometry with sample multiplexing utilizing isobaric labeling is often performed using a carrier proteome. The presented protocol describes a targeted approach that replaces the carrier proteome with a set of synthetic peptides from selected proteins, which improves the identification and quantification of these proteins in single human cells.
Collapse
Affiliation(s)
- Prajakta Naval
- Division of Chemistry I, Department of Medical Biochemistry & Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Laura Pérez Pañeda
- Division of Chemistry I, Department of Medical Biochemistry & Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Maria Athanasopoulou
- Division of Chemistry I, Department of Medical Biochemistry & Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Jaakko S Teppo
- Drug Research Program and Division of Pharmaceutical Chemistry and Technology, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
| | - Roman A Zubarev
- Division of Chemistry I, Department of Medical Biochemistry & Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Ákos Végvári
- Division of Chemistry I, Department of Medical Biochemistry & Biophysics, Karolinska Institutet, Stockholm, Sweden.
| |
Collapse
|
25
|
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.
Collapse
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.
| |
Collapse
|
26
|
Park J, Cheung TK, Zhu Y. Microfluidic Sample Preparation for Multiplexed Single-Cell Proteomics Using a Nested Nanowell Chip. Methods Mol Biol 2024; 2823:141-154. [PMID: 39052219 DOI: 10.1007/978-1-0716-3922-1_10] [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
Mass spectrometry-based single-cell proteomics has undergone rapid progress and has become an active research area. However, because of the ultralow amount of proteins in single cells, it is still highly challenging to achieve efficient sample preparation and sensitive LC-MS detection. Here, we provide a detailed protocol for isobaric labeling-based single-cell proteomics relying on a microfluidic droplet-based sample processing technology. The protocol allows for processing both single cells and carrier samples in separate microchips using a commercially available platform (cellenONE) with high sample recovery and high throughput. We also provide an optimized LC-MS method for sensitive and robust data collection.
Collapse
Affiliation(s)
- Junho Park
- Department of Pharmacology, School of Medicine, CHA University, Seongnam-si, Gyeonggi-do, South Korea.
- Proteomics Research Team, CHA Future Medicine Research Institute, Seongnam-si, Gyeonggi-do, South Korea.
| | - Tommy K Cheung
- Department of Microchemistry, Proteomics, Lipidomics and Next Generation Sequencing, Genentech Inc., South San Francisco, CA, USA
| | - Ying Zhu
- Department of Microchemistry, Proteomics, Lipidomics and Next Generation Sequencing, Genentech Inc., South San Francisco, CA, USA.
| |
Collapse
|
27
|
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.
Collapse
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
| |
Collapse
|
28
|
Claushuis B, de Ru AH, Rotman SA, van Veelen PA, Dawson LF, Wren BW, Corver J, Smits WK, Hensbergen PJ. Revised Model for the Type A Glycan Biosynthetic Pathway in Clostridioides difficile Strain 630Δ erm Based on Quantitative Proteomics of cd0241- cd0244 Mutant Strains. ACS Infect Dis 2023; 9:2665-2674. [PMID: 37965964 PMCID: PMC10714395 DOI: 10.1021/acsinfecdis.3c00485] [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: 09/12/2023] [Revised: 10/20/2023] [Accepted: 10/30/2023] [Indexed: 11/16/2023]
Abstract
The bacterial flagellum is involved in a variety of processes including motility, adherence, and immunomodulation. In the Clostridioides difficile strain 630Δerm, the main filamentous component, FliC, is post-translationally modified with an O-linked Type A glycan structure. This modification is essential for flagellar function, since motility is seriously impaired in gene mutants with improper biosynthesis of the Type A glycan. The cd0240-cd0244 gene cluster encodes the Type A biosynthetic proteins, but the role of each gene, and the corresponding enzymatic activity, have not been fully elucidated. Using quantitative mass spectrometry-based proteomics analyses, we determined the relative abundance of the observed glycan variations of the Type A structure in cd0241, cd0242, cd0243, and cd0244 mutant strains. Our data not only confirm the importance of CD0241, CD0242, and CD0243 but, in contrast to previous data, also show that CD0244 is essential for the biosynthesis of the Type A modification. Combined with additional bioinformatic analyses, we propose a revised model for Type A glycan biosynthesis.
Collapse
Affiliation(s)
- Bart Claushuis
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, Leiden 2333 ZA, The Netherlands
| | - Arnoud H. de Ru
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, Leiden 2333 ZA, The Netherlands
| | - Sarah A. Rotman
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, Leiden 2333 ZA, The Netherlands
| | - Peter A. van Veelen
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, Leiden 2333 ZA, The Netherlands
| | - Lisa F. Dawson
- Faculty
of Infectious and Tropical Diseases, London
School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom
| | - Brendan W. Wren
- Faculty
of Infectious and Tropical Diseases, London
School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom
| | - Jeroen Corver
- Department
of Medical Microbiology, Leiden University
Medical Center, Leiden 2333 ZA, The Netherlands
| | - Wiep Klaas Smits
- Department
of Medical Microbiology, Leiden University
Medical Center, Leiden 2333 ZA, The Netherlands
| | - Paul J. Hensbergen
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, Leiden 2333 ZA, The Netherlands
| |
Collapse
|
29
|
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.
Collapse
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
| |
Collapse
|
30
|
Zhang X, Li X, Xiong X. Applying proteomics in metabolic dysfunction-associated steatotic liver disease: From mechanism to biomarkers. Clin Res Hepatol Gastroenterol 2023; 47:102230. [PMID: 37931846 DOI: 10.1016/j.clinre.2023.102230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/13/2023] [Accepted: 10/18/2023] [Indexed: 11/08/2023]
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD), which represents the most common cause of liver disease, is emerging as a major health problem around the world. However, the molecular events that underline the pathogenesis and the progression of MASLD remain to be fully elucidated. Advanced stages of MASLD is strongly associated with liver-related outcomes and overall mortality. Despite this, highly accurate, sensitive, and non-invasive diagnostic tools are currently not aviailable, yet no FDA approved drugs for MASLD. The advance of proteomics has enable the study of protein expression, post-translational modifications (PTMs), subcellular distribution, and interactions. In this review, we discuss insights gained from the recent proteomics studies that shed new light on the pathogenesis, diagnosis and potential theraputic targets of MASLD.
Collapse
Affiliation(s)
- Xiaofu Zhang
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, 180 Fenlin Road, Xuhui District, Shanghai 200032, China
| | - Xiaoying Li
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, 180 Fenlin Road, Xuhui District, Shanghai 200032, China
| | - Xuelian Xiong
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, 180 Fenlin Road, Xuhui District, Shanghai 200032, China.
| |
Collapse
|
31
|
Zhang X, Cao Q, Rajachandran S, Grow EJ, Evans M, Chen H. Dissecting mammalian reproduction with spatial transcriptomics. Hum Reprod Update 2023; 29:794-810. [PMID: 37353907 PMCID: PMC10628492 DOI: 10.1093/humupd/dmad017] [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: 03/19/2023] [Revised: 05/15/2023] [Indexed: 06/25/2023] Open
Abstract
BACKGROUND Mammalian reproduction requires the fusion of two specialized cells: an oocyte and a sperm. In addition to producing gametes, the reproductive system also provides the environment for the appropriate development of the embryo. Deciphering the reproductive system requires understanding the functions of each cell type and cell-cell interactions. Recent single-cell omics technologies have provided insights into the gene regulatory network in discrete cellular populations of both the male and female reproductive systems. However, these approaches cannot examine how the cellular states of the gametes or embryos are regulated through their interactions with neighboring somatic cells in the native tissue environment owing to tissue disassociations. Emerging spatial omics technologies address this challenge by preserving the spatial context of the cells to be profiled. These technologies hold the potential to revolutionize our understanding of mammalian reproduction. OBJECTIVE AND RATIONALE We aim to review the state-of-the-art spatial transcriptomics (ST) technologies with a focus on highlighting the novel biological insights that they have helped to reveal about the mammalian reproductive systems in the context of gametogenesis, embryogenesis, and reproductive pathologies. We also aim to discuss the current challenges of applying ST technologies in reproductive research and provide a sneak peek at what the field of spatial omics can offer for the reproduction community in the years to come. SEARCH METHODS The PubMed database was used in the search for peer-reviewed research articles and reviews using combinations of the following terms: 'spatial omics', 'fertility', 'reproduction', 'gametogenesis', 'embryogenesis', 'reproductive cancer', 'spatial transcriptomics', 'spermatogenesis', 'ovary', 'uterus', 'cervix', 'testis', and other keywords related to the subject area. All relevant publications until April 2023 were critically evaluated and discussed. OUTCOMES First, an overview of the ST technologies that have been applied to studying the reproductive systems was provided. The basic design principles and the advantages and limitations of these technologies were discussed and tabulated to serve as a guide for researchers to choose the best-suited technologies for their own research. Second, novel biological insights into mammalian reproduction, especially human reproduction revealed by ST analyses, were comprehensively reviewed. Three major themes were discussed. The first theme focuses on genes with non-random spatial expression patterns with specialized functions in multiple reproductive systems; The second theme centers around functionally interacting cell types which are often found to be spatially clustered in the reproductive tissues; and the thrid theme discusses pathological states in reproductive systems which are often associated with unique cellular microenvironments. Finally, current experimental and computational challenges of applying ST technologies to studying mammalian reproduction were highlighted, and potential solutions to tackle these challenges were provided. Future directions in the development of spatial omics technologies and how they will benefit the field of human reproduction were discussed, including the capture of cellular and tissue dynamics, multi-modal molecular profiling, and spatial characterization of gene perturbations. WIDER IMPLICATIONS Like single-cell technologies, spatial omics technologies hold tremendous potential for providing significant and novel insights into mammalian reproduction. Our review summarizes these novel biological insights that ST technologies have provided while shedding light on what is yet to come. Our review provides reproductive biologists and clinicians with a much-needed update on the state of art of ST technologies. It may also facilitate the adoption of cutting-edge spatial technologies in both basic and clinical reproductive research.
Collapse
Affiliation(s)
- Xin Zhang
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Qiqi Cao
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Shreya Rajachandran
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Edward J Grow
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Melanie Evans
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Haiqi Chen
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| |
Collapse
|
32
|
Petrosius V, Aragon-Fernandez P, Üresin N, Kovacs G, Phlairaharn T, Furtwängler B, Op De Beeck J, Skovbakke SL, Goletz S, Thomsen SF, Keller UAD, Natarajan KN, Porse BT, Schoof EM. Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition. Nat Commun 2023; 14:5910. [PMID: 37737208 PMCID: PMC10517177 DOI: 10.1038/s41467-023-41602-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 09/07/2023] [Indexed: 09/23/2023] Open
Abstract
Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount of material encapsulated in a single cell however, raises significant technical challenges to molecular profiling. Due to extensive optimization efforts, single-cell proteomics by Mass Spectrometry (scp-MS) has emerged as a powerful tool to facilitate proteome profiling from ultra-low amounts of input, although further development is needed to realize its full potential. To this end, we carry out comprehensive analysis of orbitrap-based data-independent acquisition (DIA) for limited material proteomics. Notably, we find a fundamental difference between optimal DIA methods for high- and low-load samples. We further improve our low-input DIA method by relying on high-resolution MS1 quantification, thus enhancing sensitivity by more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we are able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we demonstrate the capability of our approach by profiling mouse embryonic stem cell culture conditions, showcasing heterogeneity in global proteomes and highlighting distinct differences in key metabolic enzyme expression in distinct cell subclusters.
Collapse
Affiliation(s)
- Valdemaras Petrosius
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Pedro Aragon-Fernandez
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Nil Üresin
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
| | - Gergo Kovacs
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Teeradon Phlairaharn
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
- The Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, 2200, Denmark
- Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Martinsried, 82152, Germany
- MaxPlanck Institute of Biochemistry, Martinsried, 82152, Germany
| | - Benjamin Furtwängler
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
| | - Jeff Op De Beeck
- Thermo Fisher Scientific, Technologiepark-Zwijnaarde 82, B-9052, Gent, Belgium
| | - Sarah L Skovbakke
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Steffen Goletz
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Simon Francis Thomsen
- Department of Dermatology, Bispebjerg Hospital and Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ulrich Auf dem Keller
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Kedar N Natarajan
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Bo T Porse
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
- Dept of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Erwin M Schoof
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark.
| |
Collapse
|
33
|
Gu L, Li X, Zhu W, Shen Y, Wang Q, Liu W, Zhang J, Zhang H, Li J, Li Z, Liu Z, Li C, Wang H. Ultrasensitive proteomics depicted an in-depth landscape for the very early stage of mouse maternal-to-zygotic transition. J Pharm Anal 2023; 13:942-954. [PMID: 37719194 PMCID: PMC10499587 DOI: 10.1016/j.jpha.2023.05.003] [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: 12/29/2022] [Revised: 05/05/2023] [Accepted: 05/08/2023] [Indexed: 09/19/2023] Open
Abstract
Single-cell or low-input multi-omics techniques have revolutionized the study of pre-implantation embryo development. However, the single-cell or low-input proteomic research in this field is relatively underdeveloped because of the higher threshold of the starting material for mammalian embryo samples and the lack of hypersensitive proteome technology. In this study, a comprehensive solution of ultrasensitive proteome technology (CS-UPT) was developed for single-cell or low-input mouse oocyte/embryo samples. The deep coverage and high-throughput routes significantly reduced the starting material and were selected by investigators based on their demands. Using the deep coverage route, we provided the first large-scale snapshot of the very early stage of mouse maternal-to-zygotic transition, including almost 5,500 protein groups from 20 mouse oocytes or zygotes for each sample. Moreover, significant protein regulatory networks centered on transcription factors and kinases between the MII oocyte and 1-cell embryo provided rich insights into minor zygotic genome activation.
Collapse
Affiliation(s)
- Lei Gu
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xumiao Li
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Wencheng Zhu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, 200031, China
| | - Yi Shen
- Shanghai Applied Protein Technology Co., Ltd., Shanghai, 201100, China
| | - Qinqin Wang
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Wenjun Liu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Junfeng Zhang
- Shanghai Applied Protein Technology Co., Ltd., Shanghai, 201100, China
| | - Huiping Zhang
- Shanghai Applied Protein Technology Co., Ltd., Shanghai, 201100, China
| | - Jingquan Li
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Ziyi Li
- Shanghai Applied Protein Technology Co., Ltd., Shanghai, 201100, China
| | - Zhen Liu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, 200031, China
| | - Chen Li
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Hui Wang
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| |
Collapse
|
34
|
Kong L, Li F, Fang W, Du Z, Wang G, Zhang Y, Ge WP, Zhang W, Qin W. Sensitive N-Glycopeptide Profiling of Single and Rare Cells Using an Isobaric Labeling Strategy without Enrichment. Anal Chem 2023; 95:11326-11334. [PMID: 37409763 DOI: 10.1021/acs.analchem.3c01392] [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: 07/07/2023]
Abstract
Single-cell omics is critical in revealing population heterogeneity, discovering unique features of individual cells, and identifying minority subpopulations of interest. As one of the major post-translational modifications, protein N-glycosylation plays crucial roles in various important biological processes. Elucidation of the variation in N-glycosylation patterns at single-cell resolution may largely facilitate the understanding of their key roles in the tumor microenvironment and immune therapy. However, comprehensive N-glycoproteome profiling for single cells has not been achieved due to the extremely limited sample amount and incompatibility with the available enrichment strategies. Here, we have developed an isobaric labeling-based carrier strategy for highly sensitive intact N-glycopeptide profiling for single cells or a small number of rare cells without enrichment. Isobaric labeling has unique multiplexing properties, by which the "total" signal from all channels triggers MS/MS fragmentation for N-glycopeptide identification, while the reporter ions provide quantitative information. In our strategy, a carrier channel using N-glycopeptides obtained from bulk-cell samples significantly improved the "total" signal of N-glycopeptides and, therefore, promoted the first quantitative analysis of averagely 260 N-glycopeptides from single HeLa cells. We further applied this strategy to study the regional heterogeneity of N-glycosylation of microglia in mouse brain and discovered region-specific N-glycoproteome patterns and cell subtypes. In conclusion, the glycocarrier strategy provides an attractive solution for sensitive and quantitative N-glycopeptide profiling of single/rare cells that cannot be enriched by traditional workflows.
Collapse
Affiliation(s)
- Linlin Kong
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Fengzhi Li
- Chinese Institute for Brain Research, Beijing, Beijing 102206, China
| | - Wei Fang
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Zhuokun Du
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Guibin Wang
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Yangjun Zhang
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
| | - Woo-Ping Ge
- Chinese Institute for Brain Research, Beijing, Beijing 102206, China
| | - Wanjun Zhang
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
- College of Chemistry and Materials Science, Hebei University, Baoding 071002, China
| | - Weijie Qin
- National Center for Protein Sciences Beijing, State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, P. R. China
- College of Chemistry and Materials Science, Hebei University, Baoding 071002, China
| |
Collapse
|
35
|
Gosline SJC, Veličković M, Pino JC, Day LZ, Attah IK, Swensen AC, Danna V, Posso C, Rodland KD, Chen J, Matthews CE, Campbell-Thompson M, Laskin J, Burnum-Johnson K, Zhu Y, Piehowski PD. Proteome Mapping of the Human Pancreatic Islet Microenvironment Reveals Endocrine-Exocrine Signaling Sphere of Influence. Mol Cell Proteomics 2023; 22:100592. [PMID: 37328065 PMCID: PMC10460696 DOI: 10.1016/j.mcpro.2023.100592] [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: 11/04/2022] [Revised: 04/24/2023] [Accepted: 06/05/2023] [Indexed: 06/18/2023] Open
Abstract
The need for a clinically accessible method with the ability to match protein activity within heterogeneous tissues is currently unmet by existing technologies. Our proteomics sample preparation platform, named microPOTS (Microdroplet Processing in One pot for Trace Samples), can be used to measure relative protein abundance in micron-scale samples alongside the spatial location of each measurement, thereby tying biologically interesting proteins and pathways to distinct regions. However, given the smaller pixel/voxel number and amount of tissue measured, standard mass spectrometric analysis pipelines have proven inadequate. Here we describe how existing computational approaches can be adapted to focus on the specific biological questions asked in spatial proteomics experiments. We apply this approach to present an unbiased characterization of the human islet microenvironment comprising the entire complex array of cell types involved while maintaining spatial information and the degree of the islet's sphere of influence. We identify specific functional activity unique to the pancreatic islet cells and demonstrate how far their signature can be detected in the adjacent tissue. Our results show that we can distinguish pancreatic islet cells from the neighboring exocrine tissue environment, recapitulate known biological functions of islet cells, and identify a spatial gradient in the expression of RNA processing proteins within the islet microenvironment.
Collapse
Affiliation(s)
- Sara J C Gosline
- Pacific Northwest National Laboratories, Richland, Washington, USA
| | | | - James C Pino
- Pacific Northwest National Laboratories, Richland, Washington, USA
| | - Le Z Day
- Pacific Northwest National Laboratories, Richland, Washington, USA
| | - Isaac K Attah
- Pacific Northwest National Laboratories, Richland, Washington, USA
| | - Adam C Swensen
- Pacific Northwest National Laboratories, Richland, Washington, USA
| | - Vincent Danna
- Pacific Northwest National Laboratories, Richland, Washington, USA
| | - Camilo Posso
- Pacific Northwest National Laboratories, Richland, Washington, USA
| | - Karin D Rodland
- Pacific Northwest National Laboratories, Richland, Washington, USA
| | - Jing Chen
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, Florida, USA
| | - Clayton E Matthews
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, Florida, USA
| | - Martha Campbell-Thompson
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, Florida, USA
| | - Julia Laskin
- Department of Chemistry, Purdue University, West Lafayette, Indiana, USA
| | | | - Ying Zhu
- Pacific Northwest National Laboratories, Richland, Washington, USA
| | - Paul D Piehowski
- Pacific Northwest National Laboratories, Richland, Washington, USA.
| |
Collapse
|
36
|
Takata T, Motoo Y. Novel In Vitro Assay of the Effects of Kampo Medicines against Intra/Extracellular Advanced Glycation End-Products in Oral, Esophageal, and Gastric Epithelial Cells. Metabolites 2023; 13:878. [PMID: 37512585 PMCID: PMC10385496 DOI: 10.3390/metabo13070878] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 07/20/2023] [Accepted: 07/21/2023] [Indexed: 07/30/2023] Open
Abstract
Kampo medicines are Japanese traditional medicines developed from Chinese traditional medicines. The action mechanisms of the numerous known compounds have been studied for approximately 100 years; however, many remain unclear. While components are normally affected through digestion, absorption, and metabolism, in vitro oral, esophageal, and gastric epithelial cell models avoid these influences and, thus, represent superior assay systems for Kampo medicines. We focused on two areas of the strong performance of this assay system: intracellular and extracellular advanced glycation end-products (AGEs). AGEs are generated from glucose, fructose, and their metabolites, and promote lifestyle-related diseases such as diabetes and cancer. While current technology cannot analyze whole intracellular AGEs in cells in some organs, some AGEs can be generated for 1-2 days, and the turnover time of oral and gastric epithelial cells is 7-14 days. Therefore, we hypothesized that we could detect these rapidly generated intracellular AGEs in such cells. Extracellular AEGs (e.g., dietary or in the saliva) bind to the receptor for AGEs (RAGE) and the toll-like receptor 4 (TLR4) on the surface of the epithelial cells and can induce cytotoxicity such as inflammation. The analysis of Kampo medicine effects against intra/extracellular AGEs in vitro is a novel model.
Collapse
Affiliation(s)
- Takanobu Takata
- Division of Molecular and Genetic Biology, Department of Life Science, Medical Research Institute, Kanazawa Medical University, Uchinada 920-0293, Ishikawa, Japan
| | - Yoshiharu Motoo
- Department of Medical Oncology and Kampo Medicines, Komatsu Sophia Hospital, Komatsu 923-0861, Ishikawa, Japan
| |
Collapse
|
37
|
MacKenzie TMG, Cisneros R, Maynard RD, Snyder MP. Reverse-ChIP Techniques for Identifying Locus-Specific Proteomes: A Key Tool in Unlocking the Cancer Regulome. Cells 2023; 12:1860. [PMID: 37508524 PMCID: PMC10377898 DOI: 10.3390/cells12141860] [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: 05/29/2023] [Revised: 06/30/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
A phenotypic hallmark of cancer is aberrant transcriptional regulation. Transcriptional regulation is controlled by a complicated array of molecular factors, including the presence of transcription factors, the deposition of histone post-translational modifications, and long-range DNA interactions. Determining the molecular identity and function of these various factors is necessary to understand specific aspects of cancer biology and reveal potential therapeutic targets. Regulation of the genome by specific factors is typically studied using chromatin immunoprecipitation followed by sequencing (ChIP-Seq) that identifies genome-wide binding interactions through the use of factor-specific antibodies. A long-standing goal in many laboratories has been the development of a 'reverse-ChIP' approach to identify unknown binding partners at loci of interest. A variety of strategies have been employed to enable the selective biochemical purification of sequence-defined chromatin regions, including single-copy loci, and the subsequent analytical detection of associated proteins. This review covers mass spectrometry techniques that enable quantitative proteomics before providing a survey of approaches toward the development of strategies for the purification of sequence-specific chromatin as a 'reverse-ChIP' technique. A fully realized reverse-ChIP technique holds great potential for identifying cancer-specific targets and the development of personalized therapeutic regimens.
Collapse
Affiliation(s)
| | - Rocío Cisneros
- Sarafan ChEM-H/IMA Postbaccalaureate Fellow in Target Discovery, Stanford University, Stanford, CA 94305, USA
| | - Rajan D Maynard
- Genetics Department, Stanford University, Stanford, CA 94305, USA
| | - Michael P Snyder
- Genetics Department, Stanford University, Stanford, CA 94305, USA
| |
Collapse
|
38
|
Yin K, Tong M, Suttapitugsakul S, Xu S, Wu R. Global quantification of newly synthesized proteins reveals cell type- and inhibitor-specific effects on protein synthesis inhibition. PNAS NEXUS 2023; 2:pgad168. [PMID: 37275259 PMCID: PMC10235912 DOI: 10.1093/pnasnexus/pgad168] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/05/2023] [Accepted: 05/15/2023] [Indexed: 06/07/2023]
Abstract
Manipulation of protein synthesis is commonly applied to uncover protein functions and cellular activities. Multiple inhibitors with distinct mechanisms have been widely investigated and employed in bio-related research, but it is extraordinarily challenging to measure and evaluate the synthesis inhibition efficiencies of individual proteins by different inhibitors at the proteome level. Newly synthesized proteins are the immediate and direct products of protein synthesis, and thus their comprehensive quantification provides a unique opportunity to study protein inhibition. Here, we systematically investigate protein inhibition and evaluate different popular inhibitors, i.e. cycloheximide, puromycin, and anisomycin, through global quantification of newly synthesized proteins in several types of human cells (A549, MCF-7, Jurkat, and THP-1 cells). The inhibition efficiencies of protein synthesis are comprehensively measured by integrating azidohomoalanine-based protein labeling, selective enrichment, a boosting approach, and multiplexed proteomics. The same inhibitor results in dramatic variation of the synthesis inhibition efficiencies for different proteins in the same cells, and each inhibitor exhibits unique preferences. Besides cell type- and inhibitor-specific effects, some universal rules are unraveled. For instance, nucleolar and ribosomal proteins have relatively higher inhibition efficiencies in every type of cells treated with each inhibitor. Moreover, proteins intrinsically resistant or sensitive to the inhibition are identified and found to have distinct functions. Systematic investigation of protein synthesis inhibition in several types of human cells by different inhibitors provides valuable information about the inhibition of protein synthesis, advancing our understanding of inhibiting protein synthesis.
Collapse
Affiliation(s)
| | | | - Suttipong Suttapitugsakul
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
| | - Senhan Xu
- School of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Ronghu Wu
- To whom correspondence should be addressed:
| |
Collapse
|
39
|
Wu X, Liu YK, Iliuk AB, Tao WA. Mass spectrometry-based phosphoproteomics in clinical applications. Trends Analyt Chem 2023; 163:117066. [PMID: 37215489 PMCID: PMC10195102 DOI: 10.1016/j.trac.2023.117066] [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] [Indexed: 05/24/2023]
Abstract
Protein phosphorylation is an essential post-translational modification that regulates many aspects of cellular physiology, and dysregulation of pivotal phosphorylation events is often responsible for disease onset and progression. Clinical analysis on disease-relevant phosphoproteins, while quite challenging, provides unique information for precision medicine and targeted therapy. Among various approaches, mass spectrometry (MS)-centered characterization features discovery-driven, high-throughput and in-depth identification of phosphorylation events. This review highlights advances in sample preparation and instrument in MS-based phosphoproteomics and recent clinical applications. We emphasize the preeminent data-independent acquisition method in MS as one of the most promising future directions and biofluid-derived extracellular vesicles as an intriguing source of the phosphoproteome for liquid biopsy.
Collapse
Affiliation(s)
- Xiaofeng Wu
- Department of Chemistry, Purdue University, West Lafayette, IN, USA
| | - Yi-Kai Liu
- Department of Biochemistry, Purdue University, West Lafayette, IN, USA
| | - Anton B. Iliuk
- Department of Biochemistry, Purdue University, West Lafayette, IN, USA
- Tymora Analytical Operations, West Lafayette, IN, USA
| | - W. Andy Tao
- Department of Chemistry, Purdue University, West Lafayette, IN, USA
- Department of Biochemistry, Purdue University, West Lafayette, IN, USA
- Tymora Analytical Operations, West Lafayette, IN, USA
- Center for Cancer Research, Purdue University, West Lafayette, IN, USA
| |
Collapse
|
40
|
Chen M, Jiang J, Hou J. Single-cell technologies in multiple myeloma: new insights into disease pathogenesis and translational implications. Biomark Res 2023; 11:55. [PMID: 37259170 DOI: 10.1186/s40364-023-00502-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 05/12/2023] [Indexed: 06/02/2023] Open
Abstract
Multiple myeloma (MM) is a hematological malignancy characterized by clonal proliferation of plasma cells. Although therapeutic advances have been made to improve clinical outcomes and to prolong patients' survival in the past two decades, MM remains largely incurable. Single-cell sequencing (SCS) is a powerful method to dissect the cellular and molecular landscape at single-cell resolution, instead of providing averaged results. The application of single-cell technologies promises to address outstanding questions in myeloma biology and has revolutionized our understanding of the inter- and intra-tumor heterogeneity, tumor microenvironment, and mechanisms of therapeutic resistance in MM. In this review, we summarize the recently developed SCS methodologies and latest MM research progress achieved by single-cell profiling, including information regarding the cancer and immune cell landscapes, tumor heterogeneities, underlying mechanisms and biomarkers associated with therapeutic response and resistance. We also discuss future directions of applying transformative SCS approaches with contribution to clinical translation.
Collapse
Affiliation(s)
- Mengping Chen
- Department of Hematology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China
| | - Jinxing Jiang
- Department of Hematology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China
| | - Jian Hou
- Department of Hematology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China.
| |
Collapse
|
41
|
Zhang Y. pepDESC: A method for the detection of differentially expressed proteins for mass spectrometry-based single-cell proteomics using peptide-level information. Mol Cell Proteomics 2023:100583. [PMID: 37236439 PMCID: PMC10316082 DOI: 10.1016/j.mcpro.2023.100583] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 04/21/2023] [Accepted: 05/20/2023] [Indexed: 05/28/2023] Open
Abstract
Single-cell proteomics as an emerging field has exhibited potential in revealing cellular heterogeneity at the functional level. However, accurate interpretation of single-cell proteomics data suffers from challenges such as measurement noise, internal heterogeneity, and the limited sample size of label-free quantitative mass spectrometry. Herein, the author describes pepDESC, a method for detecting differentially expressed proteins using peptide-level information designed for label-free quantitative mass spectrometry-based single-cell proteomics. While in this study, the author focuses on the heterogeneity among limited number of samples, pepDESC is also applicable to regular-size proteomics data. By balancing proteome coverage and quantification accuracy using peptide quantification, pepDESC is demonstrated to be effective in real-world single-cell and spike -in benchmark datasets. By applying pepDESC to a published single-mouse macrophages data, the author found a large fraction of differentially expressed proteins among three types of cells, which remarkably revealed distinct dynamics of different cellular functions responding to lipopolysaccharide stimulation.
Collapse
Affiliation(s)
- Yutong Zhang
- Collage of Chemistry and Molecular Engineering, Peking University, 100871 Beijing, China; Beijing Advanced Innovation Center for Genomics, Peking University,100871 Beijing, China; Biomedical Pioneering Innovation Center, Peking University, 100871 Beijing, China
| |
Collapse
|
42
|
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: 13] [Impact Index Per Article: 13.0] [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.
Collapse
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
| |
Collapse
|
43
|
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.
Collapse
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.
| |
Collapse
|
44
|
Phaneuf CG, Aizikov K, Grinfeld D, Kreutzmann A, Mourad D, Lange O, Dai D, Zhang B, Belenky A, Makarov AA, Ivanov AR. Experimental strategies to improve drug-target identification in mass spectrometry-based thermal stability assays. Commun Chem 2023; 6:64. [PMID: 37024568 PMCID: PMC10079678 DOI: 10.1038/s42004-023-00861-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 03/23/2023] [Indexed: 04/08/2023] Open
Abstract
Mass spectrometry (MS)-based thermal stability assays have recently emerged as one of the most promising solutions for the identification of protein-ligand interactions. Here, we have investigated eight combinations of several recently introduced MS-based advancements, including the Phase-Constrained Spectral Deconvolution Method, Field Asymmetric Ion Mobility Spectrometry, and the implementation of a carrier sample as improved MS-based acquisition approaches for thermal stability assays (iMAATSA). We used intact Jurkat cells treated with a commercially available MEK inhibitor, followed by heat treatment, to prepare a set of unfractionated isobarically-labeled proof-of-concept samples to compare the performance of eight different iMAATSAs. Finally, the best-performing iMAATSA was compared to a conventional approach and evaluated in a fractionation experiment. Improvements of up to 82% and 86% were demonstrated in protein identifications and high-quality melting curves, respectively, over the conventional approach in the proof-of-concept study, while an approximately 12% improvement in melting curve comparisons was achieved in the fractionation experiment.
Collapse
Affiliation(s)
- Clifford G Phaneuf
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA
- Sanofi, Disease Profiling and Functional Genomics, Cambridge, MA, USA
| | | | | | | | | | | | - Daniel Dai
- Sanofi, Disease Profiling and Functional Genomics, Cambridge, MA, USA
| | - Bailin Zhang
- Sanofi, Disease Profiling and Functional Genomics, Cambridge, MA, USA
| | | | | | - Alexander R Ivanov
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA.
| |
Collapse
|
45
|
Hou Z, Liu H. Mapping the Protein Kinome: Current Strategy and Future Direction. Cells 2023; 12:cells12060925. [PMID: 36980266 PMCID: PMC10047437 DOI: 10.3390/cells12060925] [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: 01/20/2023] [Revised: 02/23/2023] [Accepted: 03/13/2023] [Indexed: 03/30/2023] Open
Abstract
The kinome includes over 500 different protein kinases, which form an integrated kinase network that regulates cellular phosphorylation signals. The kinome plays a central role in almost every cellular process and has strong linkages with many diseases. Thus, the evaluation of the cellular kinome in the physiological environment is essential to understand biological processes, disease development, and to target therapy. Currently, a number of strategies for kinome analysis have been developed, which are based on monitoring the phosphorylation of kinases or substrates. They have enabled researchers to tackle increasingly complex biological problems and pathological processes, and have promoted the development of kinase inhibitors. Additionally, with the increasing interest in how kinases participate in biological processes at spatial scales, it has become urgent to develop tools to estimate spatial kinome activity. With multidisciplinary efforts, a growing number of novel approaches have the potential to be applied to spatial kinome analysis. In this paper, we review the widely used methods used for kinome analysis and the challenges encountered in their applications. Meanwhile, potential approaches that may be of benefit to spatial kinome study are explored.
Collapse
Affiliation(s)
- Zhanwu Hou
- Center for Mitochondrial Biology and Medicine, Douglas C. Wallace Institute for Mitochondrial and Epigenetic Information Sciences, The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China
| | - Huadong Liu
- School of Health and Life Science, University of Health and Rehabilitation Sciences, Qingdao 266071, China
| |
Collapse
|
46
|
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.
Collapse
|
47
|
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: 5] [Impact Index Per Article: 5.0] [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.
Collapse
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
| |
Collapse
|
48
|
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: 48] [Impact Index Per Article: 48.0] [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.
Collapse
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
| |
Collapse
|
49
|
Zhang H, Delafield DG, Li L. Mass spectrometry imaging: the rise of spatially resolved single-cell omics. Nat Methods 2023; 20:327-330. [PMID: 36899158 DOI: 10.1038/s41592-023-01774-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Affiliation(s)
- Hua Zhang
- School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Daniel G Delafield
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Lingjun Li
- School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin, USA.
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, USA.
| |
Collapse
|
50
|
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 .
Collapse
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.
| |
Collapse
|