1
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Dutta T, Vlassakis J. Microscale measurements of protein complexes from single cells. Curr Opin Struct Biol 2024; 87:102860. [PMID: 38848654 DOI: 10.1016/j.sbi.2024.102860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Revised: 05/07/2024] [Accepted: 05/14/2024] [Indexed: 06/09/2024]
Abstract
Proteins execute numerous cell functions in concert with one another in protein-protein interactions (PPI). While essential in each cell, such interactions are not identical from cell to cell. Instead, PPI heterogeneity contributes to cellular phenotypic heterogeneity in health and diseases such as cancer. Understanding cellular phenotypic heterogeneity thus requires measurements of properties of PPIs such as abundance, stoichiometry, and kinetics at the single-cell level. Here, we review recent, exciting progress in single-cell PPI measurements. Novel technology in this area is enabled by microscale and microfluidic approaches that control analyte concentration in timescales needed to outpace PPI disassembly kinetics. We describe microscale innovations, needed technical capabilities, and methods poised to be adapted for single-cell analysis in the near future.
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Affiliation(s)
- Tanushree Dutta
- Department of Bioengineering, Rice University, Houston, TX 77005, USA. https://twitter.com/duttatanu1717
| | - Julea Vlassakis
- Department of Bioengineering, Rice University, Houston, TX 77005, USA.
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2
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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.
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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
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3
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Peters-Clarke TM, Coon JJ, Riley NM. Instrumentation at the Leading Edge of Proteomics. Anal Chem 2024; 96:7976-8010. [PMID: 38738990 DOI: 10.1021/acs.analchem.3c04497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2024]
Affiliation(s)
- Trenton M Peters-Clarke
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Joshua J Coon
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Morgridge Institute for Research, Madison, Wisconsin 53715, United States
| | - Nicholas M Riley
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
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4
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Konno R, Ishikawa M, Nakajima D, Endo Y, Ohara O, Kawashima Y. Universal Pretreatment Development for Low-input Proteomics Using Lauryl Maltose Neopentyl Glycol. Mol Cell Proteomics 2024; 23:100745. [PMID: 38447790 PMCID: PMC10999711 DOI: 10.1016/j.mcpro.2024.100745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 02/23/2024] [Accepted: 03/01/2024] [Indexed: 03/08/2024] Open
Abstract
In recent years, there has been a growing demand for low-input proteomics, particularly in the context of single-cell proteomics (SCP). In this study, we have developed a lauryl maltose neopentyl glycol (LMNG)-assisted sample preparation (LASP) method. This method effectively reduces protein and peptide loss in samples by incorporating LMNG, a surfactant, into the digestion solution and subsequently removing the LMNG simply via reversed phase solid-phase extraction. The advantage of removing LMNG during sample preparation for general proteomic analysis is the prevention of mass spectrometry (MS) contamination. When we applied the LASP method to the low-input SP3 method and on-bead digestion in coimmunoprecipitation-MS, we observed a significant improvement in the recovery of the digested peptides. Furthermore, we have established a simple and easy sample preparation method for SCP based on the LASP method and identified a median of 1175 proteins from a single HEK239F cell using liquid chromatography (LC)-MS/MS with a throughput of 80 samples per day.
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Affiliation(s)
- Ryo Konno
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Masaki Ishikawa
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Daisuke Nakajima
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Yusuke Endo
- Department of Frontier Research and Development, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Osamu Ohara
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Yusuke Kawashima
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan; Graduate School of Science, Kitasato University, Sagamihara, Kanagawa, Japan.
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5
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Webber KGI, Huang S, Truong T, Heninger JL, Gregus M, Ivanov AR, Kelly RT. Open-tubular trap columns: towards simple and robust liquid chromatography separations for single-cell proteomics. Mol Omics 2024; 20:184-191. [PMID: 38353725 PMCID: PMC10963139 DOI: 10.1039/d3mo00249g] [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: 03/07/2024]
Abstract
Nanoflow liquid chromatography-mass spectrometry is key to enabling in-depth proteome profiling of trace samples, including single cells, but these separations can lack robustness due to the use of narrow-bore columns that are susceptible to clogging. In the case of single-cell proteomics, offline cleanup steps are generally omitted to avoid losses to additional surfaces, and online solid-phase extraction/trap columns frequently provide the only opportunity to remove salts and insoluble debris before the sample is introduced to the analytical column. Trap columns are traditionally short, packed columns used to load and concentrate analytes at flow rates greater than those employed in analytical columns, and since these first encounter the uncleaned sample mixture, trap columns are also susceptible to clogging. We hypothesized that clogging could be avoided by using large-bore porous layer open tubular trap columns (PLOTrap). The low back pressure ensured that the PLOTraps could also serve as the sample loop, thus allowing sample cleanup and injection with a single 6-port valve. We found that PLOTraps could effectively remove debris to avoid column clogging. We also evaluated multiple stationary phases and PLOTrap diameters to optimize performance in terms of peak widths and sample loading capacities. Optimized PLOTraps were compared to conventional packed trap columns operated in forward and backflush modes, and were found to have similar chromatographic performance of backflushed traps while providing improved debris removal for robust analysis of trace samples.
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Affiliation(s)
- Kei G I Webber
- Brigham Young University, Department of Chemistry and Biochemistry, Provo, Utah, 84602, USA.
| | - Siqi Huang
- Brigham Young University, Department of Chemistry and Biochemistry, Provo, Utah, 84602, USA.
| | - Thy Truong
- Brigham Young University, Department of Chemistry and Biochemistry, Provo, Utah, 84602, USA.
| | - Jacob L Heninger
- Brigham Young University, Department of Chemistry and Biochemistry, Provo, Utah, 84602, USA.
| | - Michal Gregus
- Northeastern University, Barnett Institute of Biological and Chemical Analysis, Department of Chemistry and Chemical Biology, College of Science, Boston, MA 02115, USA
| | - Alexander R Ivanov
- Northeastern University, Barnett Institute of Biological and Chemical Analysis, Department of Chemistry and Chemical Biology, College of Science, Boston, MA 02115, USA
| | - Ryan T Kelly
- Brigham Young University, Department of Chemistry and Biochemistry, Provo, Utah, 84602, USA.
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Kwon Y, Woo J, Yu F, Williams SM, Markillie LM, Moore RJ, Nakayasu ES, Chen J, Campbell-Thompson M, Mathews CE, Nesvizhskii AI, Qia 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 both normal and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in 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 largest 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 terms of identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables to identify protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.
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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 Qia
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Ying Zhu
- Department of Microchemistry, Proteomics, Lipidomics and Next Generation Sequencing, Genentech, 1 DNA Way, South San Francisco, CA 94080, United States
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Lin A, Ramaswamy Y, Misra A. Developmental heterogeneity of vascular cells: Insights into cellular plasticity in atherosclerosis? Semin Cell Dev Biol 2024; 155:3-15. [PMID: 37316416 DOI: 10.1016/j.semcdb.2023.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 05/30/2023] [Accepted: 06/06/2023] [Indexed: 06/16/2023]
Abstract
Smooth muscle cells, endothelial cells and macrophages display remarkable heterogeneity within the healthy vasculature and under pathological conditions. During development, these cells arise from numerous embryological origins, which confound with different microenvironments to generate postnatal vascular cell diversity. In the atherosclerotic plaque milieu, all these cell types exhibit astonishing plasticity, generating a variety of plaque burdening or plaque stabilizing phenotypes. And yet how developmental origin influences intraplaque cell plasticity remains largely unexplored despite evidence suggesting this may be the case. Uncovering the diversity and plasticity of vascular cells is being revolutionized by unbiased single cell whole transcriptome analysis techniques that will likely continue to pave the way for therapeutic research. Cellular plasticity is only just emerging as a target for future therapeutics, and uncovering how intraplaque plasticity differs across vascular beds may provide key insights into why different plaques behave differently and may confer different risks of subsequent cardiovascular events.
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Affiliation(s)
- Alexander Lin
- Atherosclerosis and Vascular Remodeling Group, Heart Research Institute, Sydney, NSW, Australia; School of Biomedical Engineering, Faculty of Engineering, The University of Sydney, Sydney, NSW, Australia
| | - Yogambha Ramaswamy
- School of Biomedical Engineering, Faculty of Engineering, The University of Sydney, Sydney, NSW, Australia
| | - Ashish Misra
- Atherosclerosis and Vascular Remodeling Group, Heart Research Institute, Sydney, NSW, Australia; Heart Research Institute, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
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8
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Wang Y, Guan ZY, Shi SW, Jiang YR, Zhang J, Yang Y, Wu Q, Wu J, Chen JB, Ying WX, Xu QQ, Fan QX, Wang HF, Zhou L, Wang L, Fang J, Pan JZ, Fang Q. Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell. Nat Commun 2024; 15:1279. [PMID: 38341466 PMCID: PMC10858870 DOI: 10.1038/s41467-024-45659-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Accepted: 01/29/2024] [Indexed: 02/12/2024] Open
Abstract
The shotgun proteomic analysis is currently the most promising single-cell protein sequencing technology, however its identification level of ~1000 proteins per cell is still insufficient for practical applications. Here, we develop a pick-up single-cell proteomic analysis (PiSPA) workflow to achieve a deep identification capable of quantifying up to 3000 protein groups in a mammalian cell using the label-free quantitative method. The PiSPA workflow is specially established for single-cell samples mainly based on a nanoliter-scale microfluidic liquid handling robot, capable of achieving single-cell capture, pretreatment and injection under the pick-up operation strategy. Using this customized workflow with remarkable improvement in protein identification, 2449-3500, 2278-3257 and 1621-2904 protein groups are quantified in single A549 cells (n = 37), HeLa cells (n = 44) and U2OS cells (n = 27) under the DIA (MBR) mode, respectively. Benefiting from the flexible cell picking-up ability, we study HeLa cell migration at the single cell proteome level, demonstrating the potential in practical biological research from single-cell insight.
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Affiliation(s)
- Yu Wang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
- College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China
| | - Zhi-Ying Guan
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Shao-Wen Shi
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
| | - Yi-Rong Jiang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Jie Zhang
- Department of Cell Biology, China Medical University, Shenyang, 110122, China
| | - Yi Yang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
| | - Qiong Wu
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Jie Wu
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Jian-Bo Chen
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Wei-Xin Ying
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Qin-Qin Xu
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Qian-Xi Fan
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Hui-Feng Wang
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
| | - Li Zhou
- Shanghai Omicsolution Co., Shanghai, 201100, China
| | - Ling Wang
- Shanghai Omicsolution Co., Shanghai, 201100, China
| | - Jin Fang
- Department of Cell Biology, China Medical University, Shenyang, 110122, China
| | - Jian-Zhang Pan
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
| | - Qun Fang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China.
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China.
- Key Laboratory of Excited-State Materials of Zhejiang Province, Zhejiang University, Hangzhou, 310007, China.
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9
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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.
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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
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10
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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.
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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
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11
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Pade LR, Stepler KE, Portero EP, DeLaney K, Nemes P. Biological mass spectrometry enables spatiotemporal 'omics: From tissues to cells to organelles. MASS SPECTROMETRY REVIEWS 2024; 43:106-138. [PMID: 36647247 PMCID: PMC10668589 DOI: 10.1002/mas.21824] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 09/14/2022] [Accepted: 09/17/2022] [Indexed: 06/17/2023]
Abstract
Biological processes unfold across broad spatial and temporal dimensions, and measurement of the underlying molecular world is essential to their understanding. Interdisciplinary efforts advanced mass spectrometry (MS) into a tour de force for assessing virtually all levels of the molecular architecture, some in exquisite detection sensitivity and scalability in space-time. In this review, we offer vignettes of milestones in technology innovations that ushered sample collection and processing, chemical separation, ionization, and 'omics analyses to progressively finer resolutions in the realms of tissue biopsies and limited cell populations, single cells, and subcellular organelles. Also highlighted are methodologies that empowered the acquisition and analysis of multidimensional MS data sets to reveal proteomes, peptidomes, and metabolomes in ever-deepening coverage in these limited and dynamic specimens. In pursuit of richer knowledge of biological processes, we discuss efforts pioneering the integration of orthogonal approaches from molecular and functional studies, both within and beyond MS. With established and emerging community-wide efforts ensuring scientific rigor and reproducibility, spatiotemporal MS emerged as an exciting and powerful resource to study biological systems in space-time.
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Affiliation(s)
- Leena R. Pade
- Department of Chemistry & Biochemistry, University of Maryland, 8051 Regents Drive, College Park, MD 20742
| | - Kaitlyn E. Stepler
- Department of Chemistry & Biochemistry, University of Maryland, 8051 Regents Drive, College Park, MD 20742
| | - Erika P. Portero
- Department of Chemistry & Biochemistry, University of Maryland, 8051 Regents Drive, College Park, MD 20742
| | - Kellen DeLaney
- Department of Chemistry & Biochemistry, University of Maryland, 8051 Regents Drive, College Park, MD 20742
| | - Peter Nemes
- Department of Chemistry & Biochemistry, University of Maryland, 8051 Regents Drive, College Park, MD 20742
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12
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Zhang D, Qiao L. Microfluidics Coupled Mass Spectrometry for Single Cell Multi-Omics. SMALL METHODS 2024; 8:e2301179. [PMID: 37840412 DOI: 10.1002/smtd.202301179] [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: 09/01/2023] [Revised: 10/02/2023] [Indexed: 10/17/2023]
Abstract
Population-level analysis masks significant heterogeneity between individual cells, making it difficult to accurately reflect the true intricacies of life activities. Microfluidics is a technique that can manipulate individual cells effectively and is commonly coupled with a variety of analytical methods for single-cell analysis. Single-cell omics provides abundant molecular information at the single-cell level, fundamentally revealing differences in cell types and biological states among cell individuals, leading to a deeper understanding of cellular phenotypes and life activities. Herein, this work summarizes the microfluidic chips designed for single-cell isolation, manipulation, trapping, screening, and sorting, including droplet microfluidic chips, microwell arrays, hydrodynamic microfluidic chips, and microchips with microvalves. This work further reviews the studies on single-cell proteomics, metabolomics, lipidomics, and multi-omics based on microfluidics and mass spectrometry. Finally, the challenges and future application of single-cell multi-omics are discussed.
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Affiliation(s)
- Dongxue Zhang
- Department of Chemistry, Institutes of Biomedical Sciences, and Minhang Hospital, Fudan University, Shanghai, 20000, China
| | - Liang Qiao
- Department of Chemistry, Institutes of Biomedical Sciences, and Minhang Hospital, Fudan University, Shanghai, 20000, China
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13
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Xiang P, Liyu A, Kwon Y, Hu D, Williams SM, Veličković D, Markillie LM, Chrisler WB, Paša-Tolić L, Zhu Y. Spatial Proteomics toward Subcellular Resolution by Coupling Deep Ultraviolet Laser Ablation with Nanodroplet Sample Preparation. ACS MEASUREMENT SCIENCE AU 2023; 3:459-468. [PMID: 38145026 PMCID: PMC10740121 DOI: 10.1021/acsmeasuresciau.3c00033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 09/17/2023] [Accepted: 09/22/2023] [Indexed: 12/26/2023]
Abstract
Multiplexed molecular profiling of tissue microenvironments, or spatial omics, can provide critical insights into cellular functions and disease pathology. The coupling of laser microdissection with mass spectrometry-based proteomics has enabled deep and unbiased mapping of >1000 proteins. However, the throughput of laser microdissection is often limited due to tedious two-step procedures, sequential laser cutting, and sample collection. The two-step procedure also hinders the further improvement of spatial resolution to <10 μm as needed for subcellular proteomics. Herein, we developed a high-throughput and high-resolution spatial proteomics platform by seamlessly coupling deep ultraviolet (DUV) laser ablation (LA) with nanoPOTS (Nanodroplet Processing in One pot for Trace Samples)-based sample preparation. We demonstrated the DUV-LA system can quickly isolate and collect tissue samples at a throughput of ∼30 spots/min and a spatial resolution down to 2 μm from a 10 μm thick human pancreas tissue section. To improve sample recovery, we developed a proximity aerosol collection approach by placing DMSO droplets close to LA spots. We demonstrated the DUV-LA-nanoPOTS platform can detect an average of 1312, 1533, and 1966 proteins from ablation spots with diameters of 7, 13, and 19 μm, respectively. In a proof-of-concept study, we isolated and profiled two distinct subcellular regions of the pancreas tissue revealed by hematoxylin and eosin (H&E) staining. Quantitative proteomics revealed proteins specifically enriched to subcellular compartments.
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Affiliation(s)
- Piliang Xiang
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, Richland, Washington 99354, United States
| | - Andrey Liyu
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, Richland, Washington 99354, United States
| | - Yumi Kwon
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, Richland, Washington 99354, United States
| | - Dehong Hu
- 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
| | - Lye Meng Markillie
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, Richland, Washington 99354, United States
| | - William B. Chrisler
- Biological
Sciences Division, Pacific Northwest National
Laboratory, Richland, Washington 99354, United States
| | - Ljiljana Paša-Tolić
- Environmental
Molecular Sciences Laboratory, Pacific Northwest
National Laboratory, Richland, Washington 99354, United States
| | - Ying Zhu
- Department
of Microchemistry, Proteomics, Lipidomics and Next Generation Sequencing, Genentech, 1 DNA Way, South San Francisco, California 94080, United States
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14
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Zeng Q, Xia MC, Yin X, Cheng S, Xue Z, Tan S, Gong X, Ye Z. Recent developments in ionization techniques for single-cell mass spectrometry. Front Chem 2023; 11:1293533. [PMID: 38130875 PMCID: PMC10733462 DOI: 10.3389/fchem.2023.1293533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 11/27/2023] [Indexed: 12/23/2023] Open
Abstract
The variation among individual cells plays a significant role in many biological functions. Single-cell analysis is advantageous for gaining insight into intricate biochemical mechanisms rarely accessible when studying tissues as a whole. However, measurement on a unicellular scale is still challenging due to unicellular complex composition, minute substance quantities, and considerable differences in compound concentrations. Mass spectrometry has recently gained extensive attention in unicellular analytical fields due to its exceptional sensitivity, throughput, and compound identification abilities. At present, single-cell mass spectrometry primarily concentrates on the enhancement of ionization methods. The principal ionization approaches encompass nanoelectrospray ionization (nano-ESI), laser desorption ionization (LDI), secondary ion mass spectrometry (SIMS), and inductively coupled plasma (ICP). This article summarizes the most recent advancements in ionization techniques and explores their potential directions within the field of single-cell mass spectrometry.
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Affiliation(s)
- Qingli Zeng
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection & Quarantine, College of Life Sciences, China Jiliang University, Hangzhou, China
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Meng-Chan Xia
- National Anti-Drug Laboratory Beijing Regional Center, Beijing, China
| | - Xinchi Yin
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Simin Cheng
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Zhichao Xue
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Siyuan Tan
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Xiaoyun Gong
- Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing, China
| | - Zihong Ye
- Zhejiang Provincial Key Laboratory of Biometrology and Inspection & Quarantine, College of Life Sciences, China Jiliang University, Hangzhou, China
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15
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Ctortecka C, Hartlmayr D, Seth A, Mendjan S, Tourniaire G, Udeshi ND, Carr SA, Mechtler K. An Automated Nanowell-Array Workflow for Quantitative Multiplexed Single-Cell Proteomics Sample Preparation at High Sensitivity. Mol Cell Proteomics 2023; 22:100665. [PMID: 37839701 PMCID: PMC10684380 DOI: 10.1016/j.mcpro.2023.100665] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 10/03/2023] [Accepted: 10/06/2023] [Indexed: 10/17/2023] Open
Abstract
Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lags. Here, we introduce the proteoCHIP, a universal option for single-cell proteomics sample preparation including multiplexed labeling up to 16-plex with high sensitivity and throughput. The automated processing using a commercial system combining single-cell isolation and picoliter dispensing, the cellenONE, reduces final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error-prone manual sample handling and overcoming evaporation. The specialized proteoCHIP design allows direct injection of single cells via a standard autosampler resulting in around 1500 protein groups per TMT10-plex with reduced or eliminated need for a carrier proteome. We evaluated the effect of wider precursor isolation windows at single-cell input levels and found that using 2 Da isolation windows increased overall sensitivity without significantly impacting interference. Using the dedicated mass spectrometry acquisition strategies detailed here, we identified on average close to 2000 proteins per TMT10-plex across 170 multiplexed single cells that readily distinguished human cell types. Overall, our workflow combines highly efficient sample preparation, chromatographic and ion mobility-based filtering, rapid wide-window data-dependent acquisition analysis, and intelligent data analysis for optimal multiplexed single-cell proteomics. This versatile and automated proteoCHIP-based sample preparation approach is sufficiently sensitive to drive biological applications of single-cell proteomics and can be readily adopted by proteomics laboratories.
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Affiliation(s)
- Claudia Ctortecka
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria; Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
| | - David Hartlmayr
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria; Cellenion SASU, Lyon, France
| | | | - Sasha Mendjan
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Vienna, Austria
| | | | - Namrata D Udeshi
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Steven A Carr
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
| | - Karl Mechtler
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria; Cellenion SASU, Lyon, France; Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Vienna, Austria; The Gregor Mendel Institute of Molecular Plant Biology of the Austrian Academy of Sciences (GMI), Vienna BioCenter (VBC), Vienna, Austria.
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16
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Lu H, Zhang H, Li L. Chemical tagging mass spectrometry: an approach for single-cell omics. Anal Bioanal Chem 2023; 415:6901-6913. [PMID: 37466681 PMCID: PMC10729908 DOI: 10.1007/s00216-023-04850-0] [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: 04/10/2023] [Revised: 07/04/2023] [Accepted: 07/06/2023] [Indexed: 07/20/2023]
Abstract
Single-cell (SC) analysis offers new insights into the study of fundamental biological phenomena and cellular heterogeneity. The superior sensitivity, high throughput, and rich chemical information provided by mass spectrometry (MS) allow MS to emerge as a leading technology for molecular profiling of SC omics, including the SC metabolome, lipidome, and proteome. However, issues such as ionization suppression, low concentration, and huge span of dynamic concentrations of SC components lead to poor MS response for certain types of molecules. It is noted that chemical tagging/derivatization has been adopted in SCMS analysis, and this strategy has been proven an effective solution to circumvent these issues in SCMS analysis. Herein, we review the basic principle and general strategies of chemical tagging/derivatization in SCMS analysis, along with recent applications of chemical derivatization to single-cell metabolomics and multiplexed proteomics, as well as SCMS imaging. Furthermore, the challenges and opportunities for the improvement of chemical derivatization strategies in SCMS analysis are discussed.
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Affiliation(s)
- Haiyan Lu
- School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Hua Zhang
- School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Lingjun Li
- School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA.
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA.
- Lachman Institute for Pharmaceutical Development, School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA.
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17
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Reitz CJ, Kuzmanov U, Gramolini AO. Multi-omic analyses and network biology in cardiovascular disease. Proteomics 2023; 23:e2200289. [PMID: 37691071 DOI: 10.1002/pmic.202200289] [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: 03/17/2023] [Revised: 08/11/2023] [Accepted: 08/22/2023] [Indexed: 09/12/2023]
Abstract
Heart disease remains a leading cause of death in North America and worldwide. Despite advances in therapies, the chronic nature of cardiovascular diseases ultimately results in frequent hospitalizations and steady rates of mortality. Systems biology approaches have provided a new frontier toward unraveling the underlying mechanisms of cell, tissue, and organ dysfunction in disease. Mapping the complex networks of molecular functions across the genome, transcriptome, proteome, and metabolome has enormous potential to advance our understanding of cardiovascular disease, discover new disease biomarkers, and develop novel therapies. Computational workflows to interpret these data-intensive analyses as well as integration between different levels of interrogation remain important challenges in the advancement and application of systems biology-based analyses in cardiovascular research. This review will focus on summarizing the recent developments in network biology-level profiling in the heart, with particular emphasis on modeling of human heart failure. We will provide new perspectives on integration between different levels of large "omics" datasets, including integration of gene regulatory networks, protein-protein interactions, signaling networks, and metabolic networks in the heart.
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Affiliation(s)
- Cristine J Reitz
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada
| | - Uros Kuzmanov
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada
| | - Anthony O Gramolini
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Translational Biology and Engineering Program, Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada
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18
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Li J, Huang L, Guo Y, Cupp-Sutton KA, Wu S. An automated spray-capillary platform for the microsampling and CE-MS analysis of picoliter- and nanoliter-volume samples. Anal Bioanal Chem 2023; 415:6961-6973. [PMID: 37581707 PMCID: PMC10843549 DOI: 10.1007/s00216-023-04870-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 07/01/2023] [Accepted: 07/04/2023] [Indexed: 08/16/2023]
Abstract
Capillary electrophoresis mass spectrometry (CE-MS) is an emerging analytical tool for microscale biological sample analysis that offers high separation resolution, low detection limit, and low sample consumption. We recently developed a novel microsampling device, "spray-capillary," for quantitative low-volume sample extraction (as low as 15 pL/s) and online CE-MS analysis. This platform can efficiently analyze picoliter samples (e.g., single cells) with minimal sample loss and no additional offline sample-handling steps. However, our original spray-capillary-based experiments required manual manipulation of the sample inlet for sample collection and separation, which is time consuming and requires proficiency in device handling. To optimize the performance of spray-capillary CE-MS analysis, we developed an automated platform for robust, high-throughput analysis of picoliter samples using a commercially available CE autosampler. Our results demonstrated high reproducibility among 50 continuous runs using the standard peptide angiotensin II (Ang II), with an RSD of 14.70% and 0.62% with respect to intensity and elution time, respectively. We also analyzed Ang II using varying injection times to evaluate the capability of the spray-capillary to perform quantitative sampling and found high linearity for peptide intensity with respect to injection time (R2 > 0.99). These results demonstrate the capability of the spray-capillary sampling platform for high-throughput quantitative analysis of low-volume, low-complexity samples using pressure elution (e.g., direct injection). To further evaluate and optimize the automated spray-capillary platform to analyze complex biological samples, we performed online CE-MS analysis on Escherichia coli lysate digest spiked with Ang II using varying injection times. We maintained high linearity of intensity with respect to injection time for Ang II and E. coli peptides (R2 > 0.97 in all cases). Furthermore, we observed good CE separation and high reproducibility between automated runs. Overall, we demonstrated that the automated spray-capillary CE-MS platform can efficiently and reproducibly sample picoliter and nanoliter biological samples for high-throughput proteomics analysis.
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Affiliation(s)
- Jiaxue Li
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Room 2210, Norman, OK, 73019, USA
| | - Lushuang Huang
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Room 2210, Norman, OK, 73019, USA
| | - Yanting Guo
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Room 2210, Norman, OK, 73019, USA
| | - Kellye A Cupp-Sutton
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Room 2210, Norman, OK, 73019, USA.
| | - Si Wu
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Room 2210, Norman, OK, 73019, USA.
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19
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Chen Y, Du Z, Zhao H, Fang W, Liu T, Zhang Y, Zhang W, Qin W. SPPUSM: An MS/MS spectra merging strategy for improved low-input and single-cell proteome identification. Anal Chim Acta 2023; 1279:341793. [PMID: 37827637 DOI: 10.1016/j.aca.2023.341793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 08/26/2023] [Accepted: 09/06/2023] [Indexed: 10/14/2023]
Abstract
Single and rare cell analysis provides unique insights into the investigation of biological processes and disease progress by resolving the cellular heterogeneity that is masked by bulk measurements. Although many efforts have been made, the techniques used to measure the proteome in trace amounts of samples or in single cells still lag behind those for DNA and RNA due to the inherent non-amplifiable nature of proteins and the sensitivity limitation of current mass spectrometry. Here, we report an MS/MS spectra merging strategy termed SPPUSM (same precursor-produced unidentified spectra merging) for improved low-input and single-cell proteome data analysis. In this method, all the unidentified MS/MS spectra from multiple test files are first extracted. Then, the corresponding MS/MS spectra produced by the same precursor ion from different files are matched according to their precursor mass and retention time (RT) and are merged into one new spectrum. The newly merged spectra with more fragment ions are next searched against the database to increase the MS/MS spectra identification and proteome coverage. Further improvement can be achieved by increasing the number of test files and spectra to be merged. Up to 18.2% improvement in protein identification was achieved for 1 ng HeLa peptides by SPPUSM. Reliability evaluation by the "entrapment database" strategy using merged spectra from human and E. coli revealed a marginal error rate for the proposed method. For application in single cell proteome (SCP) study, identification enhancement of 28%-61% was achieved for proteins for different SCP data. Furthermore, a lower abundance was found for the SPPUSM-identified peptides, indicating its potential for more sensitive low sample input and SCP studies.
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Affiliation(s)
- Yongle Chen
- State Key Laboratory of Proteomics, Beijing Institute of Lifeomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing, 102206, PR China
| | - Zhuokun Du
- State Key Laboratory of Proteomics, Beijing Institute of Lifeomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing, 102206, PR China
| | - Hongxian Zhao
- State Key Laboratory of Proteomics, Beijing Institute of Lifeomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing, 102206, PR China
| | - Wei Fang
- State Key Laboratory of Proteomics, Beijing Institute of Lifeomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing, 102206, PR China
| | - Tong Liu
- State Key Laboratory of Proteomics, Beijing Institute of Lifeomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing, 102206, PR China
| | - Yangjun Zhang
- State Key Laboratory of Proteomics, Beijing Institute of Lifeomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing, 102206, PR China
| | - Wanjun Zhang
- State Key Laboratory of Proteomics, Beijing Institute of Lifeomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing, 102206, PR China; College of Chemistry and Materials Science, Hebei University, Baoding, 071002, China
| | - Weijie Qin
- State Key Laboratory of Proteomics, Beijing Institute of Lifeomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing, 102206, PR China; College of Chemistry and Materials Science, Hebei University, Baoding, 071002, China.
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20
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Schirmer M, Dusny C. Microbial single-cell mass spectrometry: status, challenges, and prospects. Curr Opin Biotechnol 2023; 83:102977. [PMID: 37515936 DOI: 10.1016/j.copbio.2023.102977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 07/04/2023] [Accepted: 07/05/2023] [Indexed: 07/31/2023]
Abstract
Single-cell analysis uncovers phenotypic differences between cells in a population and dissects their individual physiological states and differences on all omics levels from genome to phenome. Spectrometric observation allows label-free analysis of the metabolome and proteome of individual cells, but is still mainly limited to the analysis of mammalian single cells. Recent progress in mass spectrometry approaches now enables the analysis of microbial single cells - mainly by miniaturizing cell handling, incubation, and improving chip-coupling concepts for analyte ionization by interfacing microfluidic chips and mass spectrometers. This review aims at distilling the enabling principles behind microbial single-cell mass spectrometry and puts them into perspective for the future of the field.
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Affiliation(s)
- Martin Schirmer
- Department of Solar Materials - Microscale Analysis and Engineering, Helmholtz-Centre for Environmental Research - UFZ Leipzig, Leizpig, Germany
| | - Christian Dusny
- Department of Solar Materials - Microscale Analysis and Engineering, Helmholtz-Centre for Environmental Research - UFZ Leipzig, Leizpig, Germany.
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21
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Johnston SM, Webber KGI, Xie X, Truong T, Nydegger A, Lin HJL, Nwosu A, Zhu Y, Kelly RT. Rapid, One-Step Sample Processing for Label-Free Single-Cell Proteomics. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:1701-1707. [PMID: 37410391 PMCID: PMC11017373 DOI: 10.1021/jasms.3c00159] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/07/2023]
Abstract
Sample preparation for single-cell proteomics is generally performed in a one-pot workflow with multiple dispensing and incubation steps. These hours-long processes can be labor intensive and lead to long sample-to-answer times. Here we report a sample preparation method that achieves cell lysis, protein denaturation, and digestion in 1 h using commercially available high-temperature-stabilized proteases with a single reagent dispensing step. Four different one-step reagent compositions were evaluated, and the mixture providing the highest proteome coverage was compared to the previously employed multistep workflow. The one-step preparation increases proteome coverage relative to the previous multistep workflow while minimizing labor input and the possibility of human error. We also compared sample recovery between previously used microfabricated glass nanowell chips and injection-molded polypropylene chips and found the polypropylene provided improved proteome coverage. Combined, the one-step sample preparation and the polypropylene substrates enabled the identification of an average of nearly 2400 proteins per cell using a standard data-dependent workflow with Orbitrap mass spectrometers. These advances greatly simplify sample preparation for single-cell proteomics and broaden accessibility with no compromise in terms of proteome coverage.
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Affiliation(s)
- S Madisyn Johnston
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Kei G I Webber
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Xiaofeng Xie
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Alissia Nydegger
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Hsien-Jung L Lin
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Andikan Nwosu
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Ying Zhu
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
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22
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Yang KL, Yu F, Teo GC, Li K, Demichev V, Ralser M, Nesvizhskii AI. MSBooster: improving peptide identification rates using deep learning-based features. Nat Commun 2023; 14:4539. [PMID: 37500632 PMCID: PMC10374903 DOI: 10.1038/s41467-023-40129-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 07/06/2023] [Indexed: 07/29/2023] Open
Abstract
Peptide identification in liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments relies on computational algorithms for matching acquired MS/MS spectra against sequences of candidate peptides using database search tools, such as MSFragger. Here, we present a new tool, MSBooster, for rescoring peptide-to-spectrum matches using additional features incorporating deep learning-based predictions of peptide properties, such as LC retention time, ion mobility, and MS/MS spectra. We demonstrate the utility of MSBooster, in tandem with MSFragger and Percolator, in several different workflows, including nonspecific searches (immunopeptidomics), direct identification of peptides from data independent acquisition data, single-cell proteomics, and data generated on an ion mobility separation-enabled timsTOF MS platform. MSBooster is fast, robust, and fully integrated into the widely used FragPipe computational platform.
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Affiliation(s)
- Kevin L Yang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
| | - Guo Ci Teo
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Kai Li
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Vadim Demichev
- Department of Biochemistry, Charité Universitätsmedizin, Berlin, Germany
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Markus Ralser
- Department of Biochemistry, Charité Universitätsmedizin, Berlin, Germany
- Nuffield Department of Medicine, The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Alexey I Nesvizhskii
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
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23
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Sunna S, Bowen CA, Ramelow CC, Santiago JV, Kumar P, Rangaraju S. Advances in proteomic phenotyping of microglia in neurodegeneration. Proteomics 2023; 23:e2200183. [PMID: 37060300 PMCID: PMC10528430 DOI: 10.1002/pmic.202200183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 04/04/2023] [Accepted: 04/05/2023] [Indexed: 04/16/2023]
Abstract
Microglia are dynamic resident immune cells of the central nervous system (CNS) that sense, survey, and respond to changes in their environment. In disease states, microglia transform from homeostatic to diverse molecular phenotypic states that play complex and causal roles in neurologic disease pathogenesis, as evidenced by the identification of microglial genes as genetic risk factors for neurodegenerative disease. While advances in transcriptomic profiling of microglia from the CNS of humans and animal models have provided transformative insights, the transcriptome is only modestly reflective of the proteome. Proteomic profiling of microglia is therefore more likely to provide functionally and therapeutically relevant targets. In this review, we discuss molecular insights gained from transcriptomic studies of microglia in the context of Alzheimer's disease as a prototypic neurodegenerative disease, and highlight existing and emerging approaches for proteomic profiling of microglia derived from in vivo model systems and human brain.
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Affiliation(s)
- Sydney Sunna
- Department of Neurology, Emory University,201 Dowman Drive Atlanta Georgia, 30322, United States of America
- Center for Neurodegenerative Diseases, Emory University, Atlanta, GA 30322, USA
| | - Christine A. Bowen
- Department of Neurology, Emory University,201 Dowman Drive Atlanta Georgia, 30322, United States of America
- Center for Neurodegenerative Diseases, Emory University, Atlanta, GA 30322, USA
- Department of Biochemistry, Emory University, Atlanta, GA 30322, USA
| | - Christina C. Ramelow
- Department of Neurology, Emory University,201 Dowman Drive Atlanta Georgia, 30322, United States of America
- Center for Neurodegenerative Diseases, Emory University, Atlanta, GA 30322, USA
| | - Juliet V. Santiago
- Department of Neurology, Emory University,201 Dowman Drive Atlanta Georgia, 30322, United States of America
- Center for Neurodegenerative Diseases, Emory University, Atlanta, GA 30322, USA
| | - Prateek Kumar
- Department of Neurology, Emory University,201 Dowman Drive Atlanta Georgia, 30322, United States of America
- Center for Neurodegenerative Diseases, Emory University, Atlanta, GA 30322, USA
| | - Srikant Rangaraju
- Department of Neurology, Emory University,201 Dowman Drive Atlanta Georgia, 30322, United States of America
- Center for Neurodegenerative Diseases, Emory University, Atlanta, GA 30322, USA
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24
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Liang Y, Truong T, Saxton AJ, Boekweg H, Payne SH, Van Ry PM, Kelly RT. HyperSCP: Combining Isotopic and Isobaric Labeling for Higher Throughput Single-Cell Proteomics. Anal Chem 2023; 95:8020-8027. [PMID: 37167627 PMCID: PMC10246935 DOI: 10.1021/acs.analchem.3c00906] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Recent developments in mass spectrometry-based single-cell proteomics (SCP) have resulted in dramatically improved sensitivity, yet the relatively low measurement throughput remains a limitation. Isobaric and isotopic labeling methods have been separately applied to SCP to increase throughput through multiplexing. Here we combined both forms of labeling to achieve multiplicative scaling for higher throughput. Two-plex stable isotope labeling of amino acids in cell culture (SILAC) and isobaric tandem mass tag (TMT) labeling enabled up to 28 single cells to be analyzed in a single liquid chromatography-mass spectrometry (LC-MS) analysis, in addition to carrier, reference, and negative control channels. A custom nested nanowell chip was used for nanoliter sample processing to minimize sample losses. Using a 145-min total LC-MS cycle time, ∼280 single cells were analyzed per day. This measurement throughput could be increased to ∼700 samples per day with a high-duty-cycle multicolumn LC system producing the same active gradient. The labeling efficiency and achievable proteome coverage were characterized for multiple analysis conditions.
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Affiliation(s)
- Yiran Liang
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Aubrianna J Saxton
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Hannah Boekweg
- Department of Biology, Brigham Young University, Provo, Utah 84602, United States
| | - Samuel H Payne
- Department of Biology, Brigham Young University, Provo, Utah 84602, United States
| | - Pam M Van Ry
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
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25
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Loewa A, Feng JJ, Hedtrich S. Human disease models in drug development. NATURE REVIEWS BIOENGINEERING 2023; 1:1-15. [PMID: 37359774 PMCID: PMC10173243 DOI: 10.1038/s44222-023-00063-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/30/2023] [Indexed: 06/20/2023]
Abstract
Biomedical research is undergoing a paradigm shift towards approaches centred on human disease models owing to the notoriously high failure rates of the current drug development process. Major drivers for this transition are the limitations of animal models, which, despite remaining the gold standard in basic and preclinical research, suffer from interspecies differences and poor prediction of human physiological and pathological conditions. To bridge this translational gap, bioengineered human disease models with high clinical mimicry are being developed. In this Review, we discuss preclinical and clinical studies that benefited from these models, focusing on organoids, bioengineered tissue models and organs-on-chips. Furthermore, we provide a high-level design framework to facilitate clinical translation and accelerate drug development using bioengineered human disease models.
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Affiliation(s)
- Anna Loewa
- Department of Infectious Diseases and Respiratory Medicine, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
| | - James J. Feng
- Department of Chemical and Biological Engineering, University of British Columbia, Vancouver, BC Canada
- Department of Mathematics, University of British Columbia, Vancouver, BC Canada
| | - Sarah Hedtrich
- Department of Infectious Diseases and Respiratory Medicine, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
- Center of Biological Design, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany
- Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC Canada
- Max-Delbrück Center for Molecular Medicine (MCD), Helmholtz Association, Berlin, Germany
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26
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Sharman K, Patterson NH, Weiss A, Neumann EK, Guiberson ER, Ryan DJ, Gutierrez DB, Spraggins JM, Van de Plas R, Skaar EP, Caprioli RM. Rapid Multivariate Analysis Approach to Explore Differential Spatial Protein Profiles in Tissue. J Proteome Res 2023; 22:1394-1405. [PMID: 35849531 PMCID: PMC9845430 DOI: 10.1021/acs.jproteome.2c00206] [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: 01/21/2023]
Abstract
Spatially targeted proteomics analyzes the proteome of specific cell types and functional regions within tissue. While spatial context is often essential to understanding biological processes, interpreting sub-region-specific protein profiles can pose a challenge due to the high-dimensional nature of the data. Here, we develop a multivariate approach for rapid exploration of differential protein profiles acquired from distinct tissue regions and apply it to analyze a published spatially targeted proteomics data set collected from Staphylococcus aureus-infected murine kidney, 4 and 10 days postinfection. The data analysis process rapidly filters high-dimensional proteomic data to reveal relevant differentiating species among hundreds to thousands of measured molecules. We employ principal component analysis (PCA) for dimensionality reduction of protein profiles measured by microliquid extraction surface analysis mass spectrometry. Subsequently, k-means clustering of the PCA-processed data groups samples by chemical similarity. Cluster center interpretation revealed a subset of proteins that differentiate between spatial regions of infection over two time points. These proteins appear involved in tricarboxylic acid metabolomic pathways, calcium-dependent processes, and cytoskeletal organization. Gene ontology analysis further uncovered relationships to tissue damage/repair and calcium-related defense mechanisms. Applying our analysis in infectious disease highlighted differential proteomic changes across abscess regions over time, reflecting the dynamic nature of host-pathogen interactions.
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Affiliation(s)
- Kavya Sharman
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee 37235, United States
- Program in Chemical & Physical Biology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, United States
| | - Nathan Heath Patterson
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee 37235, United States
- Department of Biochemistry, Vanderbilt University, Nashville, Tennessee 37232, United States
| | - Andy Weiss
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee 37212, United States
| | - Elizabeth K Neumann
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee 37235, United States
- Department of Biochemistry, Vanderbilt University, Nashville, Tennessee 37232, United States
| | - Emma R Guiberson
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee 37235, United States
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - Daniel J Ryan
- Pfizer Inc., Chesterfield, Missouri 63017, United States
| | - Danielle B Gutierrez
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - Jeffrey M Spraggins
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee 37235, United States
- Department of Biochemistry, Vanderbilt University, Nashville, Tennessee 37232, United States
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - Raf Van de Plas
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee 37235, United States
- Department of Biochemistry, Vanderbilt University, Nashville, Tennessee 37232, United States
- Delft Center for Systems and Control, Delft University of Technology, 2628 CD Delft, The Netherlands
| | - Eric P Skaar
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee 37212, United States
- Department of Medicine, Vanderbilt University, Nashville, Tennessee 37232, United States
| | - Richard M Caprioli
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee 37235, United States
- Department of Biochemistry, Vanderbilt University, Nashville, Tennessee 37232, United States
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, United States
- Department of Pharmacology, Vanderbilt University, Nashville, Tennessee 37232, United States
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27
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Li M, Zuo J, Yang K, Wang P, Zhou S. Proteomics mining of cancer hallmarks on a single-cell resolution. MASS SPECTROMETRY REVIEWS 2023. [PMID: 37051664 DOI: 10.1002/mas.21842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 11/25/2022] [Accepted: 03/15/2023] [Indexed: 06/19/2023]
Abstract
Dysregulated proteome is an essential contributor in carcinogenesis. Protein fluctuations fuel the progression of malignant transformation, such as uncontrolled proliferation, metastasis, and chemo/radiotherapy resistance, which severely impair therapeutic effectiveness and cause disease recurrence and eventually mortality among cancer patients. Cellular heterogeneity is widely observed in cancer and numerous cell subtypes have been characterized that greatly influence cancer progression. Population-averaged research may not fully reveal the heterogeneity, leading to inaccurate conclusions. Thus, deep mining of the multiplex proteome at the single-cell resolution will provide new insights into cancer biology, to develop prognostic biomarkers and treatments. Considering the recent advances in single-cell proteomics, herein we review several novel technologies with particular focus on single-cell mass spectrometry analysis, and summarize their advantages and practical applications in the diagnosis and treatment for cancer. Technological development in single-cell proteomics will bring a paradigm shift in cancer detection, intervention, and therapy.
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Affiliation(s)
- Maomao Li
- Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE and State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan, China
| | - Jing Zuo
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, and West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China
| | - Kailin Yang
- Department of Radiation Oncology, Taussig Cancer Center, Cleveland Clinic, Cleveland, Ohio, USA
| | - Ping Wang
- Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE and State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan, China
| | - Shengtao Zhou
- Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE and State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan, China
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Liu S, Kumari S, He H, Mishra P, Singh BN, Singh D, Liu S, Srivastava P, Li C. Biosensors integrated 3D organoid/organ-on-a-chip system: A real-time biomechanical, biophysical, and biochemical monitoring and characterization. Biosens Bioelectron 2023; 231:115285. [PMID: 37058958 DOI: 10.1016/j.bios.2023.115285] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 03/25/2023] [Accepted: 03/28/2023] [Indexed: 04/16/2023]
Abstract
As a full-fidelity simulation of human cells, tissues, organs, and even systems at the microscopic scale, Organ-on-a-Chip (OOC) has significant ethical advantages and development potential compared to animal experiments. The need for the design of new drug high-throughput screening platforms and the mechanistic study of human tissues/organs under pathological conditions, the evolving advances in 3D cell biology and engineering, etc., have promoted the updating of technologies in this field, such as the iteration of chip materials and 3D printing, which in turn facilitate the connection of complex multi-organs-on-chips for simulation and the further development of technology-composite new drug high-throughput screening platforms. As the most critical part of organ-on-a-chip design and practical application, verifying the success of organ model modeling, i.e., evaluating various biochemical and physical parameters in OOC devices, is crucial. Therefore, this paper provides a logical and comprehensive review and discussion of the advances in organ-on-a-chip detection and evaluation technologies from a broad perspective, covering the directions of tissue engineering scaffolds, microenvironment, single/multi-organ function, and stimulus-based evaluation, and provides a more comprehensive review of the progress in the significant organ-on-a-chip research areas in the physiological state.
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Affiliation(s)
- Shan Liu
- Sichuan Provincial Key Laboratory for Human Disease Gene Study, Department of Medical Genetics, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Shikha Kumari
- School of Biochemical Engineering, IIT BHU, Varanasi, Uttar Pradesh, India
| | - Hongyi He
- West China School of Medicine & West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Parichita Mishra
- Department of Ageing Research, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, 576104, Karnataka, India
| | - Bhisham Narayan Singh
- Department of Ageing Research, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, 576104, Karnataka, India
| | - Divakar Singh
- School of Biochemical Engineering, IIT BHU, Varanasi, Uttar Pradesh, India
| | - Sutong Liu
- Juxing College of Digital Economics, Haikou University of Economics, Haikou, 570100, China
| | - Pradeep Srivastava
- School of Biochemical Engineering, IIT BHU, Varanasi, Uttar Pradesh, India.
| | - Chenzhong Li
- Biomedical Engineering, School of Medicine, The Chinese University of Hong Kong(Shenzhen), Shenzhen, 518172, China.
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29
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Gebreyesus ST, Muneer G, Huang CC, Siyal AA, Anand M, Chen YJ, Tu HL. Recent advances in microfluidics for single-cell functional proteomics. LAB ON A CHIP 2023; 23:1726-1751. [PMID: 36811978 DOI: 10.1039/d2lc01096h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Single-cell proteomics (SCP) reveals phenotypic heterogeneity by profiling individual cells, their biological states and functional outcomes upon signaling activation that can hardly be probed via other omics characterizations. This has become appealing to researchers as it enables an overall more holistic view of biological details underlying cellular processes, disease onset and progression, as well as facilitates unique biomarker identification from individual cells. Microfluidic-based strategies have become methods of choice for single-cell analysis because they allow facile assay integrations, such as cell sorting, manipulation, and content analysis. Notably, they have been serving as an enabling technology to improve the sensitivity, robustness, and reproducibility of recently developed SCP methods. Critical roles of microfluidics technologies are expected to further expand rapidly in advancing the next phase of SCP analysis to reveal more biological and clinical insights. In this review, we will capture the excitement of the recent achievements of microfluidics methods for both targeted and global SCP, including efforts to enhance the proteomic coverage, minimize sample loss, and increase multiplexity and throughput. Furthermore, we will discuss the advantages, challenges, applications, and future prospects of SCP.
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Affiliation(s)
- Sofani Tafesse Gebreyesus
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Nano Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
| | - Gul Muneer
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | | | - Asad Ali Siyal
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
| | - Mihir Anand
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
| | - Hsiung-Lin Tu
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Nano Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
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30
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Veličković M, Fillmore TL, Attah K, Posso C, Pino JC, Zhao R, Williams SM, Veličković D, Jacobs JM, Burnum-Johnson KE, Zhu Y, Piehowski PD. Coupling microdroplet-based sample preparation, multiplexed isobaric labeling, and nanoflow peptide fractionation for deep proteome profiling of tissue microenvironment. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.13.531822. [PMID: 36993277 PMCID: PMC10055005 DOI: 10.1101/2023.03.13.531822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity at a cell-type-specific level to better understand and predict the function of complex biological systems, such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverages due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (Microdroplet Processing in One pot for Trace Samples), the multiplexed isobaric labelling, and a nanoflow peptide fractionation approach. The integrated workflow allowed to maximize proteome coverage of laser-isolated tissue samples containing nanogram proteins. We demonstrated the deep spatial proteomics can quantify more than 5,000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 µm2) and reveal unique islet microenvironments.
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31
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Yu H, Yang C, Tai Q, Gao M, Zhang X. New Method for Counting and Picking Out Single Circulating Tumor Cells from Microliter-Volume Samples for Tumor Progression Surveillance and Single-Cell Heterogeneity Analysis. Anal Chem 2023; 95:5232-5239. [PMID: 36913664 DOI: 10.1021/acs.analchem.2c04994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2023]
Abstract
Circulating tumor cells (CTCs) are crucial in tumor progression and metastasis, but the knowledge of their roles grows slowly at single-cell levels. Characterizing the rarity and fragility of CTCs by nature, highly stable and efficient single-CTC sampling methods are still lacking, which impedes the development of single-CTC analysis. Herein, an improved, capillary-based single-cell sampling (SiCS) method, the so-called bubble-glue single-cell sampling (bubble-glue SiCS), is introduced. Benefiting from the characteristic that the cells tend to adhere to air bubbles in the solution, single cells can be sampled with bubbles as low as 20 pL with a self-designed microbubble-volume-controlled system. Benefiting from the excellent maneuverability, single CTCs are sampled directly from 10 μL volume of real blood samples after fluorescent labeling. Meanwhile, over 90% of the CTCs obtained survived and well proliferated after the bubble-glue SiCS process, which showed considerable superiority for downstream single-CTC profiling. Furthermore, a highly metastatic breast cancer model of the 4T1 cell line in vivo was employed for the real blood sample analysis. Increases in CTC numbers were observed during the tumor progression process, and significant heterogeneities among individual CTCs were discovered. In all, we propose a novel avenue for target SiCS and provide an alternative technique route for CTC separation and analysis.
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Affiliation(s)
- Hailong Yu
- Department of Chemistry, Fudan University, Shanghai, 200438, China
| | - Chenjie Yang
- Department of Chemistry, Fudan University, Shanghai, 200438, China
| | - Qunfei Tai
- Department of Chemistry, Fudan University, Shanghai, 200438, China
| | - Mingxia Gao
- Department of Chemistry, Fudan University, Shanghai, 200438, China
| | - Xiangmin Zhang
- Department of Chemistry, Fudan University, Shanghai, 200438, China
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32
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Matzinger M, Müller E, Dürnberger G, Pichler P, Mechtler K. Robust and Easy-to-Use One-Pot Workflow for Label-Free Single-Cell Proteomics. Anal Chem 2023; 95:4435-4445. [PMID: 36802514 PMCID: PMC9996606 DOI: 10.1021/acs.analchem.2c05022] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
Abstract
The analysis of ultralow input samples or even individual cells is essential to answering a multitude of biomedical questions, but current proteomic workflows are limited in their sensitivity and reproducibility. Here, we report a comprehensive workflow that includes improved strategies for all steps, from cell lysis to data analysis. Thanks to convenient-to-handle 1 μL sample volume and standardized 384-well plates, the workflow is easy for even novice users to implement. At the same time, it can be performed semi-automatized using CellenONE, which allows for the highest reproducibility. To achieve high throughput, ultrashort gradient lengths down to 5 min were tested using advanced μ-pillar columns. Data-dependent acquisition (DDA), wide-window acquisition (WWA), data-independent acquisition (DIA), and commonly used advanced data analysis algorithms were benchmarked. Using DDA, 1790 proteins covering a dynamic range of four orders of magnitude were identified in a single cell. Using DIA, proteome coverage increased to more than 2200 proteins identified from single-cell level input in a 20 min active gradient. The workflow enabled differentiation of two cell lines, demonstrating its suitability to cellular heterogeneity determination.
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Affiliation(s)
- Manuel Matzinger
- Institute of Molecular Pathology (IMP), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
| | - Elisabeth Müller
- Institute of Molecular Pathology (IMP), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
| | - Gerhard Dürnberger
- Gregor Mendel Institute of Molecular Plant Biology (GMI) of the Austrian Academy of Sciences, Dr. Bohrgasse 3, 1030 Vienna, Austria
| | - Peter Pichler
- Institute of Molecular Pathology (IMP), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
| | - Karl Mechtler
- Institute of Molecular Pathology (IMP), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria.,Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Dr. Bohrgasse 3, 1030 Vienna, Austria.,Gregor Mendel Institute of Molecular Plant Biology (GMI) of the Austrian Academy of Sciences, Dr. Bohrgasse 3, 1030 Vienna, Austria
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33
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Advances in Mass Spectrometry-Based Single Cell Analysis. BIOLOGY 2023; 12:biology12030395. [PMID: 36979087 PMCID: PMC10045136 DOI: 10.3390/biology12030395] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/27/2023] [Accepted: 03/01/2023] [Indexed: 03/06/2023]
Abstract
Technological developments and improvements in single-cell isolation and analytical platforms allow for advanced molecular profiling at the single-cell level, which reveals cell-to-cell variation within the admixture cells in complex biological or clinical systems. This helps to understand the cellular heterogeneity of normal or diseased tissues and organs. However, most studies focused on the analysis of nucleic acids (e.g., DNA and RNA) and mass spectrometry (MS)-based analysis for proteins and metabolites of a single cell lagged until recently. Undoubtedly, MS-based single-cell analysis will provide a deeper insight into cellular mechanisms related to health and disease. This review summarizes recent advances in MS-based single-cell analysis methods and their applications in biology and medicine.
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34
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Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform. Mol Cell Proteomics 2023; 22:100491. [PMID: 36603806 PMCID: PMC9944986 DOI: 10.1016/j.mcpro.2022.100491] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 12/10/2022] [Accepted: 12/20/2022] [Indexed: 01/04/2023] Open
Abstract
Conventional proteomic approaches measure the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of signals arising from subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot unambiguously define and quantify proteoforms, which are intact (i.e., functional) forms of proteins capturing genetic variations, alternatively spliced transcripts and posttranslational modifications. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantitation directly from tissue sections. The spatial TDP platform consisted of a nanodroplet processing in one pot for trace samples-based sample preparation system and an laser capture microdissection-based cell isolation system. We improved the nanodroplet processing in one pot for trace samples sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ∼200 cultured cells as test samples, this approach increased total proteoform identifications from 493 to 700; with newly identified proteoforms primarily corresponding to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed laser capture microdissection-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 509 proteoforms within the union of top-down mass spectrometry-based proteoform identification and characterization and TDPortal identifications to match with features from protein mass extractor. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential posttranslational modification-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.
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35
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Park J, Yu F, Fulcher JM, Williams SM, Engbrecht K, Moore RJ, Clair GC, Petyuk V, Nesvizhskii AI, Zhu Y. Evaluating Linear Ion Trap for MS3-Based Multiplexed Single-Cell Proteomics. Anal Chem 2023; 95:1888-1898. [PMID: 36637389 DOI: 10.1021/acs.analchem.2c03739] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
There is a growing demand to develop high-throughput and high-sensitivity mass spectrometry methods for single-cell proteomics. The commonly used isobaric labeling-based multiplexed single-cell proteomics approach suffers from distorted protein quantification due to co-isolated interfering ions during MS/MS fragmentation, also known as ratio compression. We reasoned that the use of MS3-based quantification could mitigate ratio compression and provide better quantification. However, previous studies indicated reduced proteome coverages in the MS3 method, likely due to long duty cycle time and ion losses during multilevel ion selection and fragmentation. Herein, we described an improved MS acquisition method for MS3-based single-cell proteomics by employing a linear ion trap to measure reporter ions. We demonstrated that linear ion trap can increase the proteome coverages for single-cell-level peptides with even higher gain obtained via the MS3 method. The optimized real-time search MS3 method was further applied to study the immune activation of single macrophages. Among a total of 126 single cells studied, over 1200 and 1000 proteins were quantifiable when at least 50 and 75% nonmissing data were required, respectively. Our evaluation also revealed several limitations of the low-resolution ion trap detector for multiplexed single-cell proteomics and suggested experimental solutions to minimize their impacts on single-cell analysis.
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Affiliation(s)
- Junho Park
- Department of Pharmacology, School of Medicine, CHA University, Seongnam-si, Gyeonggi-do, Seongnam 13488, Republic of Korea
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109-1382, United States
| | - James M Fulcher
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Sarah M Williams
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Kristin Engbrecht
- Nuclear, Chemistry, and Biology Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Ronald J Moore
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Geremy C Clair
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Vladislav Petyuk
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Alexey I Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109-1382, United States
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109-1382, United States
| | - Ying Zhu
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
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36
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Vanderaa C, Gatto L. The Current State of Single-Cell Proteomics Data Analysis. Curr Protoc 2023; 3:e658. [PMID: 36633424 DOI: 10.1002/cpz1.658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Sound data analysis is essential to retrieve meaningful biological information from single-cell proteomics experiments. This analysis is carried out by computational methods that are assembled into workflows, and their implementations influence the conclusions that can be drawn from the data. In this work, we explore and compare the computational workflows that have been used over the last four years and identify a profound lack of consensus on how to analyze single-cell proteomics data. We highlight the need for benchmarking of computational workflows and standardization of computational tools and data, as well as carefully designed experiments. Finally, we cover the current standardization efforts that aim to fill the gap, list the remaining missing pieces, and conclude with lessons learned from the replication of published single-cell proteomics analyses. © 2023 Wiley Periodicals LLC.
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Affiliation(s)
- Christophe Vanderaa
- Computational Biology and Bioinformatics Unit (CBIO), de Duve Institute, Université catholique de Louvain, Belgium
| | - Laurent Gatto
- Computational Biology and Bioinformatics Unit (CBIO), de Duve Institute, Université catholique de Louvain, Belgium
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37
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Wu Y, Zhang W, Zhao Y, Wang X, Guo G. Technology development trend of electrospray ionization mass spectrometry for single-cell proteomics. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
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38
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Insights into protein post-translational modification landscapes of individual human cells by trapped ion mobility time-of-flight mass spectrometry. Nat Commun 2022; 13:7246. [PMID: 36433961 PMCID: PMC9700839 DOI: 10.1038/s41467-022-34919-w] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Accepted: 11/11/2022] [Indexed: 11/26/2022] Open
Abstract
Single cell proteomics is a powerful tool with potential for markedly enhancing understanding of cellular processes. Here we report the development and application of multiplexed single cell proteomics using trapped ion mobility time-of-flight mass spectrometry. When employing a carrier channel to improve peptide signal, this method allows over 40,000 tandem mass spectra to be acquired in 30 min. Using a KRASG12C model human-derived cell line, we demonstrate the quantification of over 1200 proteins per cell with high relative sequence coverage permitting the detection of multiple classes of post-translational modifications in single cells. When cells were treated with a KRASG12C covalent inhibitor, this approach revealed cell-to-cell variability in the impact of the drug, providing insight missed by traditional proteomics. We provide multiple resources necessary for the application of single cell proteomics to drug treatment studies including tools to reduce cell cycle linked proteomic effects from masking pharmacological phenotypes.
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39
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Solt LA. Emerging insights and challenges for understanding T cell function through the proteome. Front Immunol 2022; 13:1028366. [DOI: 10.3389/fimmu.2022.1028366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 10/31/2022] [Indexed: 11/17/2022] Open
Abstract
T cells rapidly transition from a quiescent state into active proliferation and effector function upon exposure to cognate antigen. These processes are tightly controlled by signal transduction pathways that influence changes in chromatin remodeling, gene transcription, and metabolism, all of which collectively drive specific T cell memory or effector cell development. Dysregulation of any of these events can mediate disease and the past several years has shown unprecedented novel approaches to understand these events, down to the single-cell level. The massive explosion of sequencing approaches to assess the genome and transcriptome at the single cell level has transformed our understanding of T cell activation, developmental potential, and effector function under normal and various disease states. Despite these advances, there remains a significant dearth of information regarding how these events are translated to the protein level. For example, resolution of protein isoforms and/or specific post-translational modifications mediating T cell function remains obscure. The application of proteomics can change that, enabling significant insights into molecular mechanisms that regulate T cell function. However, unlike genomic approaches that have enabled exquisite visualization of T cell dynamics at the mRNA and chromatin level, proteomic approaches, including those at the single-cell level, has significantly lagged. In this review, we describe recent studies that have enabled a better understanding of how protein synthesis and degradation change during T cell activation and acquisition of effector function. We also highlight technical advances and how these could be applied to T cell biology. Finally, we discuss future needs to expand upon our current knowledge of T cell proteomes and disease.
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40
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Lageveen‐Kammeijer GSM, Kuster B, Reusch D, Wuhrer M. High sensitivity glycomics in biomedicine. MASS SPECTROMETRY REVIEWS 2022; 41:1014-1039. [PMID: 34494287 PMCID: PMC9788051 DOI: 10.1002/mas.21730] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 08/23/2021] [Accepted: 08/26/2021] [Indexed: 05/15/2023]
Abstract
Many analytical challenges in biomedicine arise from the generally high heterogeneity and complexity of glycan- and glycoconjugate-containing samples, which are often only available in minute amounts. Therefore, highly sensitive workflows and detection methods are required. In this review mass spectrometric workflows and detection methods are evaluated for glycans and glycoproteins. Furthermore, glycomic methodologies and innovations that are tailored for enzymatic treatments, chemical derivatization, purification, separation, and detection at high sensitivity are highlighted. The discussion is focused on the analysis of mammalian N-linked and GalNAc-type O-linked glycans.
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Affiliation(s)
| | - Bernhard Kuster
- Chair for Proteomics and BioanalyticsTechnical University of MunichFreisingGermany
| | - Dietmar Reusch
- Pharma Technical Development EuropeRoche Diagnostics GmbHPenzbergGermany
| | - Manfred Wuhrer
- Leiden University Medical CenterCenter for Proteomics and MetabolomicsLeidenThe Netherlands
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41
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Tajik M, Baharfar M, Donald WA. Single-cell mass spectrometry. Trends Biotechnol 2022; 40:1374-1392. [PMID: 35562238 DOI: 10.1016/j.tibtech.2022.04.004] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/04/2022] [Accepted: 04/09/2022] [Indexed: 01/21/2023]
Abstract
Owing to recent advances in mass spectrometry (MS), tens to hundreds of proteins, lipids, and small molecules can be measured in single cells. The ability to characterize the molecular heterogeneity of individual cells is necessary to define the full assortment of cell subtypes and identify their function. We review single-cell MS including high-throughput, targeted, mass cytometry-based approaches and antibody-free methods for broad profiling of the proteome and metabolome of single cells. The advantages and disadvantages of different methods are discussed, as well as the challenges and opportunities for further improvements in single-cell MS. These methods is being used in biomedicine in several applications including revealing tumor heterogeneity and high-content drug screening.
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Affiliation(s)
- Mohammad Tajik
- School of Chemistry, University of New South Wales, Sydney, New South Wales, 2052, Australia
| | - Mahroo Baharfar
- School of Chemical Engineering, University of New South Wales, Sydney, New South Wales, 2052, Australia
| | - William A Donald
- School of Chemistry, University of New South Wales, Sydney, New South Wales, 2052, Australia.
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42
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Cupp-Sutton KA, Fang M, Wu S. Separation methods in single-cell proteomics: RPLC or CE? INTERNATIONAL JOURNAL OF MASS SPECTROMETRY 2022; 481:116920. [PMID: 36211475 PMCID: PMC9542495 DOI: 10.1016/j.ijms.2022.116920] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Cellular heterogeneity is commonly investigated using single-cell genomics and transcriptomics to investigate biological questions such as disease mechanism, therapeutic screening, and genomic and transcriptomic diversity between cellular populations and subpopulations at the cellular level. Single-cell mass spectrometry (MS)-based proteomics enables the high-throughput examination of protein expression at the single-cell level with wide applicability, and with spatial and temporal resolution, applicable to the study of cellular development, disease, effect of treatment, etc. The study of single-cell proteomics has lagged behind genomics and transcriptomics largely because proteins from single-cell samples cannot be amplified as DNA and RNA can using well established techniques such as PCR. Therefore, analytical methods must be robust, reproducible, and sensitive enough to detect the very small amount of protein within a single cell. To this end, nearly every step of the proteomics process has been extensively altered and improved to facilitate the proteomics analysis of single cells including cell counting and sorting, lysis, protein digestion, sample cleanup, separation, MS data acquisition, and data analysis. Here, we have reviewed recent advances in single-cell protein separation using nano reversed phase liquid chromatography (nRPLC) and capillary electrophoresis (CE) to inform application driven selection of separation techniques in the laboratory setting.
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Affiliation(s)
| | - Mulin Fang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK 73019
| | - Si Wu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK 73019
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43
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Proteomic Profiling of Intra-Islet Features Reveals Substructure-Specific Protein Signatures. Mol Cell Proteomics 2022; 21:100426. [PMID: 36244662 PMCID: PMC9706166 DOI: 10.1016/j.mcpro.2022.100426] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 08/30/2022] [Accepted: 09/04/2022] [Indexed: 11/11/2022] Open
Abstract
Despite their diminutive size, islets of Langerhans play a large role in maintaining systemic energy balance in the body. New technologies have enabled us to go from studying the whole pancreas to isolated whole islets, to partial islet sections, and now to islet substructures isolated from within the islet. Using a microfluidic nanodroplet-based proteomics platform coupled with laser capture microdissection and field asymmetric waveform ion mobility spectrometry, we present an in-depth investigation of protein profiles specific to features within the islet. These features include the islet-acinar interface vascular tissue, inner islet vasculature, isolated endocrine cells, whole islet with vasculature, and acinar tissue from around the islet. Compared to interface vasculature, unique protein signatures observed in the inner vasculature indicate increased innervation and intra-islet neuron-like crosstalk. We also demonstrate the utility of these data for identifying localized structure-specific drug-target interactions using existing protein/drug binding databases.
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44
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Kong Q, Weng Y, Zheng Z, Chen W, Li P, Cai Z, Tian R. Integrated and High-Throughput Approach for Sensitive Analysis of Tyrosine Phosphoproteome. Anal Chem 2022; 94:13728-13736. [PMID: 36179360 DOI: 10.1021/acs.analchem.2c01807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Tyrosine phosphorylation (pTyr) regulates various signaling pathways under normal and cancerous states. Due to their low abundance and transient and dynamic natures, systematic profiling of pTyr sites is challenging. Antibody and engineered binding domain-based approaches have been well applied to pTyr peptide enrichment. However, traditional methods have the disadvantage of a long sample preparation process, which makes them unsuitable for processing limited amount of samples, especially in a high-throughput manner. In this study we developed a 96-well microplate-based approach to integrate all the sample preparation steps starting from cell culture to MS-compatible pTyr peptide enrichment in three consecutive 96-well microplates. By assembling an engineered SH2 domain onto a microplate, nonspecific adsorption of phosphopeptides is greatly reduced, which allows us to remove the Ti-IMAC purification and three C18 desalting steps (after digestion, pTyr enrichment, and Ti-IMAC purification) and, therefore, greatly simplifies the entire pTyr peptide enrichment workflow, especially when processing a large number of samples. Starting with 96-well microplate-cultured, pervanadate-stimulated cells, our approach could enrich 21% more pTyr sites than the traditional serial pTyr enrichment approach and showed good sensitivity and reproducibility in the range of 200 ng to 200 μg peptides. Importantly, we applied this approach to profile tyrosine kinase inhibitor-mediated EGFR signaling pathway and could well differentiate the distinct response of different pTyr sites. Collectively, the integrated 96-well microplate-based approach is valuable for profiling pTyr sites from limited biological samples and in a high-throughput manner.
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Affiliation(s)
- Qian Kong
- Department of Chemistry, College of Science, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China.,Research Center for Chemical Biology and Omics Analysis, College of Science, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China.,State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR 999077, China
| | - Yicheng Weng
- Department of Chemistry, College of Science, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China.,Research Center for Chemical Biology and Omics Analysis, College of Science, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China
| | - Zhendong Zheng
- Department of Chemistry, College of Science, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China.,Research Center for Chemical Biology and Omics Analysis, College of Science, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China
| | - Wendong Chen
- Department of Chemistry, College of Science, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China
| | - Pengfei Li
- Department of Chemistry, College of Science, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China.,Research Center for Chemical Biology and Omics Analysis, College of Science, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China.,Shenzhen Grubbs Institute, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China
| | - Zongwei Cai
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR 999077, China
| | - Ruijun Tian
- Department of Chemistry, College of Science, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China.,Research Center for Chemical Biology and Omics Analysis, College of Science, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China.,Shenzhen Grubbs Institute, Southern University of Science and Technology, 1088 Xueyuan Road, Shenzhen 518055, China
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45
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Senavirathna L, Ma C, Chen R, Pan S. Spectral Library-Based Single-Cell Proteomics Resolves Cellular Heterogeneity. Cells 2022; 11:cells11152450. [PMID: 35954294 PMCID: PMC9368228 DOI: 10.3390/cells11152450] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 07/29/2022] [Accepted: 08/04/2022] [Indexed: 02/07/2023] Open
Abstract
Dissecting the proteome of cell types and states at single-cell resolution, while being highly challenging, has significant implications in basic science and biomedicine. Mass spectrometry (MS)-based single-cell proteomics represents an emerging technology for system-wide, unbiased profiling of proteins in single cells. However, significant challenges remain in analyzing an extremely small amount of proteins collected from a single cell, as a proteome-wide amplification of proteins is not currently feasible. Here, we report an integrated spectral library-based single-cell proteomics (SLB-SCP) platform that is ultrasensitive and well suited for a large-scale analysis. To overcome the low MS/MS signal intensity intrinsically associated with a single-cell analysis, this approach takes an alternative approach by extracting a breadth of information that specifically defines the physicochemical characteristics of a peptide from MS1 spectra, including monoisotopic mass, isotopic distribution, and retention time (hydrophobicity), and uses a spectral library for proteomic identification. This conceptually unique MS platform, coupled with the DIRECT sample preparation method, enabled identification of more than 2000 proteins in a single cell to distinguish different proteome landscapes associated with cellular types and heterogeneity. We characterized individual normal and cancerous pancreatic ductal cells (HPDE and PANC-1, respectively) and demonstrated the substantial difference in the proteomes between HPDE and PANC-1 at the single-cell level. A significant upregulation of multiple protein networks in cancer hallmarks was identified in the PANC-1 cells, functionally discriminating the PANC-1 cells from the HPDE cells. This integrated platform can be built on high-resolution MS and widely accepted proteomic software, making it possible for community-wide applications.
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Affiliation(s)
- Lakmini Senavirathna
- The Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Cheng Ma
- The Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Ru Chen
- Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
| | - Sheng Pan
- The Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Department of Integrative Biology and Pharmacology, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Correspondence:
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46
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Sialana F, Roumeliotis TI, Bouguenina H, Chan Wah Hak L, Wang H, Caldwell J, Collins I, Chopra R, Choudhary JS. SimPLIT: Simplified Sample Preparation for Large-Scale Isobaric Tagging Proteomics. J Proteome Res 2022; 21:1842-1856. [PMID: 35848491 PMCID: PMC9361352 DOI: 10.1021/acs.jproteome.2c00092] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Large scale proteomic profiling of cell lines can reveal molecular signatures attributed to variable genotypes or induced perturbations, enabling proteogenomic associations and elucidation of pharmacological mechanisms of action. Although isobaric labeling has increased the throughput of proteomic analysis, the commonly used sample preparation workflows often require time-consuming steps and costly consumables, limiting their suitability for large scale studies. Here, we present a simplified and cost-effective one-pot reaction workflow in a 96-well plate format (SimPLIT) that minimizes processing steps and demonstrates improved reproducibility compared to alternative approaches. The workflow is based on a sodium deoxycholate lysis buffer and a single detergent cleanup step after peptide labeling, followed by quick off-line fractionation and MS2 analysis. We showcase the applicability of the workflow in a panel of colorectal cancer cell lines and by performing target discovery for a set of molecular glue degraders in different cell lines, in a 96-sample assay. Using this workflow, we report frequently dysregulated proteins in colorectal cancer cells and uncover cell-dependent protein degradation profiles of seven cereblon E3 ligase modulators (CRL4CRBN). Overall, SimPLIT is a robust method that can be easily implemented in any proteomics laboratory for medium-to-large scale TMT-based studies for deep profiling of cell lines.
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Affiliation(s)
- Fernando
J. Sialana
- Functional
Proteomics Group, The Institute of Cancer Research, Chester Beatty Laboratories, London SW3 6JB, U.K.
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Theodoros I. Roumeliotis
- Functional
Proteomics Group, The Institute of Cancer Research, Chester Beatty Laboratories, London SW3 6JB, U.K.
| | - Habib Bouguenina
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Laura Chan Wah Hak
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Hannah Wang
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - John Caldwell
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Ian Collins
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Rajesh Chopra
- Cancer
Research UK Cancer Therapeutics Unit, The
Institute of Cancer Research, London SM2 5NG, U.K.
| | - Jyoti S. Choudhary
- Functional
Proteomics Group, The Institute of Cancer Research, Chester Beatty Laboratories, London SW3 6JB, U.K.
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47
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Nwosu AJ, Misal SA, Truong T, Carson RH, Webber KGI, Axtell NB, Liang Y, Johnston SM, Virgin KL, Smith EG, Thomas GV, Morgan T, Price JC, Kelly RT. In-Depth Mass Spectrometry-Based Proteomics of Formalin-Fixed, Paraffin-Embedded Tissues with a Spatial Resolution of 50-200 μm. J Proteome Res 2022; 21:2237-2245. [PMID: 35916235 PMCID: PMC9767749 DOI: 10.1021/acs.jproteome.2c00409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Formalin-fixed, paraffin-embedded (FFPE) tissues are banked in large repositories to cost-effectively preserve valuable specimens for later study. With the rapid growth of spatial proteomics, FFPE tissues can serve as a more accessible alternative to more commonly used frozen tissues. However, extracting proteins from FFPE tissues is challenging due to cross-links formed between proteins and formaldehyde. Here, we have adapted the nanoPOTS sample processing workflow, which was previously applied to single cells and fresh-frozen tissues, to profile protein expression from FFPE tissues. Following the optimization of extraction solvents, times, and temperatures, we identified an average of 1312 and 3184 high-confidence master proteins from 10 μm thick FFPE-preserved mouse liver tissue squares having lateral dimensions of 50 and 200 μm, respectively. The observed proteome coverage for FFPE tissues was on average 88% of that achieved for similar fresh-frozen tissues. We also characterized the performance of our fully automated sample preparation and analysis workflow, termed autoPOTS, for FFPE spatial proteomics. This modified nanodroplet processing in one pot for trace samples (nanoPOTS) and fully automated processing in one pot for trace sample (autoPOTS) workflows provides the greatest coverage reported to date for high-resolution spatial proteomics applied to FFPE tissues. Data are available via ProteomeXchange with identifier PXD029729.
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Affiliation(s)
- Andikan J Nwosu
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Santosh A Misal
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Richard H Carson
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Kei G I Webber
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Nathaniel B Axtell
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Yiran Liang
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - S Madisyn Johnston
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Kenneth L Virgin
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Ethan G Smith
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - George V Thomas
- Knight Cancer Center, Oregon Health & Science University, Portland, Oregon 97239, United States
| | - Terry Morgan
- Department of Pathology, Oregon Health & Science University, Portland, Oregon 97239, United States
| | - John C Price
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
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48
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Urbiola-Salvador V, Miroszewska D, Jabłońska A, Qureshi T, Chen Z. Proteomics approaches to characterize the immune responses in cancer. BIOCHIMICA ET BIOPHYSICA ACTA. MOLECULAR CELL RESEARCH 2022; 1869:119266. [PMID: 35390423 DOI: 10.1016/j.bbamcr.2022.119266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 03/01/2022] [Accepted: 03/28/2022] [Indexed: 06/14/2023]
Abstract
Despite the dynamic development of cancer research, annually millions of people die of cancer. The human immune system is the major 'guard' against tumor development. Unfortunately, cancer cells have the ability to evade the immune system and continue to grow. The proper understanding of the intricate immune response in tumorigenesis remains the holy grail of cancer immunology and designing effective immunotherapy. To decode the immune responses in cancer, in recent years, proteomics studies have received considerable attention. Proteomics studies focus on the detection and quantification of proteins, which are the effectors of biological functions, and as such, are proven to reflect the cell state more accurately, in comparison to genomic or transcriptomic studies. In this review, we discuss the proteomics studies applied to characterize the immune responses in cancer and tumor immune microenvironment heterogeneity. Further, we describe emerging single-cell proteomics approaches that have the potential to be applied in cancer immunity studies.
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Affiliation(s)
- Víctor Urbiola-Salvador
- Intercollegiate Faculty of Biotechnology of University of Gdańsk and Medical University of Gdańsk, University of Gdańsk, Poland.
| | - Dominika Miroszewska
- Intercollegiate Faculty of Biotechnology of University of Gdańsk and Medical University of Gdańsk, University of Gdańsk, Poland.
| | - Agnieszka Jabłońska
- Intercollegiate Faculty of Biotechnology of University of Gdańsk and Medical University of Gdańsk, University of Gdańsk, Poland.
| | - Talha Qureshi
- Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu, Finland.
| | - Zhi Chen
- Intercollegiate Faculty of Biotechnology of University of Gdańsk and Medical University of Gdańsk, University of Gdańsk, Poland; Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu, Finland.
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Beck L, Geiger T. MS-based technologies for untargeted single-cell proteomics. Curr Opin Biotechnol 2022; 76:102736. [DOI: 10.1016/j.copbio.2022.102736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 03/19/2022] [Accepted: 04/24/2022] [Indexed: 11/28/2022]
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Kwon Y, Piehowski PD, Zhao R, Sontag RL, Moore RJ, Burnum-Johnson KE, Smith RD, Qian WJ, Kelly RT, Zhu Y. Hanging drop sample preparation improves sensitivity of spatial proteomics. LAB ON A CHIP 2022; 22:2869-2877. [PMID: 35838077 PMCID: PMC9320080 DOI: 10.1039/d2lc00384h] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/08/2022] [Indexed: 06/15/2023]
Abstract
Spatial proteomics holds great promise for revealing tissue heterogeneity in both physiological and pathological conditions. However, one significant limitation of most spatial proteomics workflows is the requirement of large sample amounts that blurs cell-type-specific or microstructure-specific information. In this study, we developed an improved sample preparation approach for spatial proteomics and integrated it with our previously-established laser capture microdissection (LCM) and microfluidics sample processing platform. Specifically, we developed a hanging drop (HD) method to improve the sample recovery by positioning a nanowell chip upside-down during protein extraction and tryptic digestion steps. Compared with the commonly-used sitting-drop method, the HD method keeps the tissue pixel away from the container surface, and thus improves the accessibility of the extraction/digestion buffer to the tissue sample. The HD method can increase the MS signal by 7 fold, leading to a 66% increase in the number of identified proteins. An average of 721, 1489, and 2521 proteins can be quantitatively profiled from laser-dissected 10 μm-thick mouse liver tissue pixels with areas of 0.0025, 0.01, and 0.04 mm2, respectively. The improved system was further validated in the study of cell-type-specific proteomes of mouse uterine tissues.
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Affiliation(s)
- Yumi Kwon
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99354, USA.
| | - Paul D Piehowski
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99354, USA.
| | - Rui Zhao
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99354, USA.
| | - Ryan L Sontag
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - Ronald J Moore
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - Kristin E Burnum-Johnson
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99354, USA.
| | - Richard D Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - Ryan T Kelly
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99354, USA.
- Department of Chemistry and Biochemistry, Brigham Young University, C100 BNSN, Provo, UT 84602, USA
| | - Ying Zhu
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99354, USA.
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