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Colón Rosado JA, Sun L. Solid-Phase Microextraction-Aided Capillary Zone Electrophoresis-Mass Spectrometry: Toward Bottom-Up Proteomics of Single Human Cells. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:1120-1127. [PMID: 38514245 DOI: 10.1021/jasms.3c00429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
Capillary zone electrophoresis-mass spectrometry (CZE-MS) has been recognized as a valuable technique for the proteomics of mass-limited biological samples (i.e., single cells). However, its broad adoption for single cell proteomics (SCP) of human cells has been impeded by the low sample loading capacity of CZE, only allowing us to use less than 5% of the available peptide material for each measurement. Here we present a reversed-phase-based solid-phase microextraction (RP-SPME)-CZE-MS platform to solve the issue, paving the way for SCP of human cells using CZE-MS. The RP-SPME-CZE system was constructed in one fused silica capillary with zero dead volume for connection via in situ synthesis of a frit, followed by packing C8 beads into the capillary to form a roughly 2 mm long SPME section. Peptides captured by SPME were eluted with a buffer containing 30% (v/v) acetonitrile and 50 mM ammonium acetate (pH 6.5), followed by dynamic pH junction-based CZE-MS. The SPME-CZE-MS enabled the injection of nearly 40% of the available peptide sample for each measurement. The system identified 257 ± 24 proteins and 523 ± 69 peptides (N = 2) using a Q-Exactive HF mass spectrometer when only 0.25 ng of a commercial HeLa cell digest was available in the sample vial and 0.1 ng of the sample was injected. The amount of available peptide is equivalent to the protein mass of one HeLa cell. The data indicate that SPME-CZE-MS is ready for SCP of human cells.
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Affiliation(s)
- Jorge A Colón Rosado
- Department of Chemistry, Michigan State University, 578 S Shaw Lane, East Lansing, Michigan 48824, United States
| | - Liangliang Sun
- Department of Chemistry, Michigan State University, 578 S Shaw Lane, East Lansing, Michigan 48824, United States
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2
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Zhao Z, Guo Y, Chowdhury T, Anjum S, Li J, Huang L, Cupp-Sutton KA, Burgett A, Shi D, Wu S. Top-Down Proteomics Analysis of Picogram-Level Complex Samples Using Spray-Capillary-Based Capillary Electrophoresis-Mass Spectrometry. Anal Chem 2024; 96:8763-8771. [PMID: 38722793 DOI: 10.1021/acs.analchem.4c01119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Proteomics analysis of mass-limited samples has become increasingly important for understanding biological systems in physiologically relevant contexts such as patient samples, multicellular organoids, spheroids, and single cells. However, relatively low sensitivity in top-down proteomics methods makes their application to mass-limited samples challenging. Capillary electrophoresis (CE) has emerged as an ideal separation method for mass-limited samples due to its high separation resolution, ultralow detection limit, and minimal sample volume requirements. Recently, we developed "spray-capillary", an electrospray ionization (ESI)-assisted device, that is capable of quantitative ultralow-volume sampling (e.g., pL-nL level). Here, we developed a spray-capillary-CE-MS platform for ultrasensitive top-down proteomics analysis of intact proteins in mass-limited complex biological samples. Specifically, to improve the sensitivity of the spray-capillary platform, we incorporated a polyethylenimine (PEI)-coated capillary and optimized the spray-capillary inner diameter. Under optimized conditions, we successfully detected over 200 proteoforms from 50 pg of E. coli lysate. To our knowledge, the spray-capillary CE-MS platform developed here represents one of the most sensitive detection methods for top-down proteomics. Furthermore, in a proof-of-principle experiment, we detected 261 ± 65 and 174 ± 45 intact proteoforms from fewer than 50 HeLa and OVCAR-8 cells, respectively, by coupling nanodroplet-based sample preparation with our optimized CE-MS platform. Overall, our results demonstrate the capability of the modified spray-capillary CE-MS platform to perform top-down proteomics analysis on picogram amounts of samples. This advancement presents the possibility of meaningful top-down proteomics analysis of mass-limited samples down to the level of single mammalian cells.
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Affiliation(s)
- Zhitao Zhao
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Yanting Guo
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Trishika Chowdhury
- Department of Chemistry and Biochemistry, University of Alabama, 250 Hackberry Ln, Tuscaloosa, Alabama 35487, United States
| | - Samin Anjum
- Department of Chemistry and Biochemistry, University of Alabama, 250 Hackberry Ln, Tuscaloosa, Alabama 35487, United States
| | - Jiaxue Li
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Lushuang Huang
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Kellye A Cupp-Sutton
- Department of Chemistry and Biochemistry, University of Alabama, 250 Hackberry Ln, Tuscaloosa, Alabama 35487, United States
| | - Anthony Burgett
- Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences, 1110 N. Stonewall Ave., Oklahoma City, Oklahoma 73117, United States
| | - Dingjing Shi
- Department of Psychology, University of Oklahoma, 455 W Lindsey Street, Norman, Oklahoma 73069, United States
| | - Si Wu
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
- Department of Chemistry and Biochemistry, University of Alabama, 250 Hackberry Ln, Tuscaloosa, Alabama 35487, 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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Marie AL, Gao Y, Ivanov AR. Native N-glycome profiling of single cells and ng-level blood isolates using label-free capillary electrophoresis-mass spectrometry. Nat Commun 2024; 15:3847. [PMID: 38719792 PMCID: PMC11079027 DOI: 10.1038/s41467-024-47772-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 04/12/2024] [Indexed: 05/12/2024] Open
Abstract
The development of reliable single-cell dispensers and substantial sensitivity improvement in mass spectrometry made proteomic profiling of individual cells achievable. Yet, there are no established methods for single-cell glycome analysis due to the inability to amplify glycans and sample losses associated with sample processing and glycan labeling. In this work, we present an integrated platform coupling online in-capillary sample processing with high-sensitivity label-free capillary electrophoresis-mass spectrometry for N-glycan profiling of single mammalian cells. Direct and unbiased quantitative characterization of single-cell surface N-glycomes are demonstrated for HeLa and U87 cells, with the detection of up to 100 N-glycans per single cell. Interestingly, N-glycome alterations are unequivocally detected at the single-cell level in HeLa and U87 cells stimulated with lipopolysaccharide. The developed workflow is also applied to the profiling of ng-level amounts (5-500 ng) of blood-derived protein, extracellular vesicle, and total plasma isolates, resulting in over 170, 220, and 370 quantitated N-glycans, respectively.
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Affiliation(s)
- Anne-Lise Marie
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Ave., Boston, MA, 02115, US
| | - Yunfan Gao
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Ave., Boston, MA, 02115, US
| | - Alexander R Ivanov
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Ave., Boston, MA, 02115, US.
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5
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Greguš M, Koller A, Ray S, Ivanov AR. Improved Data Acquisition Settings on Q Exactive HF-X and Fusion Lumos Tribrid Orbitrap-Based Mass Spectrometers for Proteomic Analysis of Limited Samples. J Proteome Res 2024. [PMID: 38690845 DOI: 10.1021/acs.jproteome.4c00181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2024]
Abstract
Deep proteomic profiling of complex biological and medical samples available at low nanogram and subnanogram levels is still challenging. Thorough optimization of settings, parameters, and conditions in nanoflow liquid chromatography-tandem mass spectrometry (MS)-based proteomic profiling is crucial for generating informative data using amount-limited samples. This study demonstrates that by adjusting selected instrument parameters, e.g., ion injection time, automated gain control, and minimally altering the conditions for resuspending or storing the sample in solvents of different compositions, up to 15-fold more thorough proteomic profiling can be achieved compared to conventionally used settings. More specifically, the analysis of 1 ng of the HeLa protein digest standard by Q Exactive HF-X Hybrid Quadrupole-Orbitrap and Orbitrap Fusion Lumos Tribrid mass spectrometers yielded an increase from 1758 to 5477 (3-fold) and 281 to 4276 (15-fold) peptides, respectively, demonstrating that higher protein identification results can be obtained using the optimized methods. While the instruments applied in this study do not belong to the latest generation of mass spectrometers, they are broadly used worldwide, which makes the guidelines for improving performance desirable to a wide range of proteomics practitioners.
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Affiliation(s)
- Michal Greguš
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Ave., Boston, Massachusetts 02115, United States
| | - Antonius Koller
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Ave., Boston, Massachusetts 02115, United States
| | - Somak Ray
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Ave., Boston, Massachusetts 02115, United States
| | - Alexander R Ivanov
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Ave., Boston, Massachusetts 02115, United States
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6
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Nalehua MR, Zaia J. A critical evaluation of ultrasensitive single-cell proteomics strategies. Anal Bioanal Chem 2024; 416:2359-2369. [PMID: 38358530 DOI: 10.1007/s00216-024-05171-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 01/20/2024] [Accepted: 01/23/2024] [Indexed: 02/16/2024]
Abstract
Success of mass spectrometry characterization of the proteome of single cells allows us to gain a greater understanding than afforded by transcriptomics alone but requires clear understanding of the tradeoffs between analytical throughput and precision. Recent advances in mass spectrometry acquisition techniques, including updated instrumentation and sample preparation, have improved the quality of peptide signals obtained from single cell data. However, much of the proteome remains uncharacterized, and higher throughput techniques often come at the expense of reduced sensitivity and coverage, which diminish the ability to measure proteoform heterogeneity, including splice variants and post-translational modifications, in single cell data analysis. Here, we assess the growing body of ultrasensitive single-cell approaches and their tradeoffs as researchers try to balance throughput and precision in their experiments.
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Affiliation(s)
| | - Joseph Zaia
- Bioinformatics Program, Boston University, Boston, MA, USA.
- Department of Biochemistry and Cell Biology, Boston University, Boston, MA, USA.
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7
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Truong T, Kelly RT. What's new in single-cell proteomics. Curr Opin Biotechnol 2024; 86:103077. [PMID: 38359605 PMCID: PMC11068367 DOI: 10.1016/j.copbio.2024.103077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 01/19/2024] [Indexed: 02/17/2024]
Abstract
In recent years, single-cell proteomics (SCP) has advanced significantly, enabling the analysis of thousands of proteins within single mammalian cells. This progress is driven by advances in experimental design, with maturing label-free and multiplexed methods, optimized sample preparation, and innovations in separation techniques, including ultra-low-flow nanoLC. These factors collectively contribute to improved sensitivity, throughput, and reproducibility. Cutting-edge mass spectrometry platforms and data acquisition approaches continue to play a critical role in enhancing data quality. Furthermore, the exploration of spatial proteomics with single-cell resolution offers significant promise for understanding cellular interactions, giving rise to various phenotypes. SCP has far-reaching applications in cancer research, biomarker discovery, and developmental biology. Here, we provide a critical review of recent advances in the field of SCP.
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Affiliation(s)
- Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, United States
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, United States.
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8
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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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9
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Shen B, Pade LR, Nemes P. The 15-min (Sub)Cellular Proteome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.15.580399. [PMID: 38405838 PMCID: PMC10888744 DOI: 10.1101/2024.02.15.580399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Single-cell mass spectrometry (MS) opens a proteomic window onto the inner workings of cells. Here, we report the discovery characterization of the subcellular proteome of single, identified embryonic cells in record speed and molecular coverage. We integrated subcellular capillary microsampling, fast capillary electrophoresis (CE), high-efficiency nano-flow electrospray ionization, and orbitrap tandem MS. In proof-of-principle tests, we found shorter separation times to hinder proteome detection using DDA, but not DIA. Within a 15-min effective separation window, CE data-independent acquisition (DIA) was able to identify 1,161 proteins from single HeLa-cell-equivalent (∼200 pg) proteome digests vs. 401 proteins by the reference data-dependent acquisition (DDA) on the same platform. The approach measured 1,242 proteins from subcellular niches in an identified cell in the live Xenopus laevis (frog) embryo, including many canonical components of organelles. CE-MS with DIA enables fast, sensitive, and deep profiling of the (sub)cellular proteome, expanding the bioanalytical toolbox of cell biology. Authorship Contributions P.N. and B.S. designed the study. L.R.P. collected the X. laevis cell aspirates. B.S. prepared and measured the samples. B.S. and P.N. analyzed the data and interpreted the results. P.N. and B.S. wrote the manuscript. All the authors commented on the manuscript.
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10
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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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Koutrouli M, Nastou K, Piera Líndez P, Bouwmeester R, Rasmussen S, Martens L, Jensen LJ. FAVA: high-quality functional association networks inferred from scRNA-seq and proteomics data. Bioinformatics 2024; 40:btae010. [PMID: 38192003 PMCID: PMC10868155 DOI: 10.1093/bioinformatics/btae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 12/07/2023] [Accepted: 01/05/2024] [Indexed: 01/10/2024] Open
Abstract
MOTIVATION Protein networks are commonly used for understanding how proteins interact. However, they are typically biased by data availability, favoring well-studied proteins with more interactions. To uncover functions of understudied proteins, we must use data that are not affected by this literature bias, such as single-cell RNA-seq and proteomics. Due to data sparseness and redundancy, functional association analysis becomes complex. RESULTS To address this, we have developed FAVA (Functional Associations using Variational Autoencoders), which compresses high-dimensional data into a low-dimensional space. FAVA infers networks from high-dimensional omics data with much higher accuracy than existing methods, across a diverse collection of real as well as simulated datasets. FAVA can process large datasets with over 0.5 million conditions and has predicted 4210 interactions between 1039 understudied proteins. Our findings showcase FAVA's capability to offer novel perspectives on protein interactions. FAVA functions within the scverse ecosystem, employing AnnData as its input source. AVAILABILITY AND IMPLEMENTATION Source code, documentation, and tutorials for FAVA are accessible on GitHub at https://github.com/mikelkou/fava. FAVA can also be installed and used via pip/PyPI as well as via the scverse ecosystem https://github.com/scverse/ecosystem-packages/tree/main/packages/favapy.
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Affiliation(s)
- Mikaela Koutrouli
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark
| | - Katerina Nastou
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark
| | - Pau Piera Líndez
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark
| | - Robbin Bouwmeester
- VIB-UGent Center for Medical Biotechnology, VIB, 9052 Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, 9052 Ghent, Belgium
| | - Simon Rasmussen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, VIB, 9052 Ghent, Belgium
- Department of Biomolecular Medicine, Ghent University, 9052 Ghent, Belgium
| | - Lars Juhl Jensen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark
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12
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Guise AJ, Misal SA, Carson R, Chu JH, Boekweg H, Van Der Watt D, Welsh NC, Truong T, Liang Y, Xu S, Benedetto G, Gagnon J, Payne SH, Plowey ED, Kelly RT. TDP-43-stratified single-cell proteomics of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis. Cell Rep 2024; 43:113636. [PMID: 38183652 PMCID: PMC10926001 DOI: 10.1016/j.celrep.2023.113636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 11/02/2023] [Accepted: 12/14/2023] [Indexed: 01/08/2024] Open
Abstract
A limitation of conventional bulk-tissue proteome studies in amyotrophic lateral sclerosis (ALS) is the confounding of motor neuron (MN) signals by admixed non-MN proteins. Here, we leverage laser capture microdissection and nanoPOTS single-cell mass spectrometry-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control tissues. In a follow-up analysis, we examine the impact of stratification of MNs based on cytoplasmic transactive response DNA-binding protein 43 (TDP-43)+ inclusion pathology on the profiles of 2,238 proteins. We report extensive overlap in differentially abundant proteins identified in ALS MNs with or without overt TDP-43 pathology, suggesting early and sustained dysregulation of cellular respiration, mRNA splicing, translation, and vesicular transport in ALS. Together, these data provide insights into proteome-level changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein dynamics in human neurologic diseases.
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Affiliation(s)
| | - Santosh A Misal
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, USA
| | - Richard Carson
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, USA
| | | | - Hannah Boekweg
- Biology Department, Brigham Young University, Provo, UT 84602, USA
| | | | | | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, USA
| | - Yiran Liang
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, USA
| | | | | | | | - Samuel H Payne
- Biology Department, Brigham Young University, Provo, UT 84602, USA
| | | | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602, USA.
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13
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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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14
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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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15
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Zheng R, Matzinger M, Mayer RL, Valenta A, Sun X, Mechtler K. A High-Sensitivity Low-Nanoflow LC-MS Configuration for High-Throughput Sample-Limited Proteomics. Anal Chem 2023; 95:18673-18678. [PMID: 38088903 PMCID: PMC10753523 DOI: 10.1021/acs.analchem.3c03058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 11/16/2023] [Accepted: 11/21/2023] [Indexed: 12/27/2023]
Abstract
This work demonstrates the utility of high-throughput nanoLC-MS and label-free quantification (LFQ) for sample-limited bottom-up proteomics analysis, including single-cell proteomics (SCP). Conditions were optimized on a 50 μm internal diameter (I.D.) column operated at 100 nL/min in the direct injection workflow to balance method sensitivity and sample throughput from 24 to 72 samples/day. Multiple data acquisition strategies were also evaluated for proteome coverage, including data-dependent acquisition (DDA), wide-window acquisition (WWA), and wide-window data-independent acquisition (WW-DIA). Analyzing 250 pg HeLa digest with a 10-min LC gradient (72 samples/day) provided >900, >1,800, and >3,000 protein group identifications for DDA, WWA, and WW-DIA, respectively. Total method cycle time was further reduced from 20 to 14.4 min (100 samples/day) by employing a trap-and-elute workflow, enabling 70% mass spectrometer utilization. The method was applied to library-free DIA analysis of single-cell samples, yielding >1,700 protein groups identified. In conclusion, this study provides a high-sensitivity, high-throughput nanoLC-MS configuration for sample-limited proteomics.
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Affiliation(s)
- Runsheng Zheng
- Thermo
Fisher Scientific, Dornier Str. 4, 82110 Germering, Germany
| | - Manuel Matzinger
- IMP—Institute
of Molecular Pathology, Campus-Vienna-Biocenter 1, A-1030 Vienna, Austria
| | - Rupert L. Mayer
- IMP—Institute
of Molecular Pathology, Campus-Vienna-Biocenter 1, A-1030 Vienna, Austria
| | - Alec Valenta
- Thermo
Fisher Scientific, Dornier Str. 4, 82110 Germering, Germany
| | - Xuefei Sun
- Thermo
Fisher Scientific, 1228 Titan Way, Sunnyvale, California 94085, United States
| | - Karl Mechtler
- IMP—Institute
of Molecular Pathology, Campus-Vienna-Biocenter 1, A-1030 Vienna, Austria
- IMBA—Institute
of Molecular Biotechnology of the Austrian Academy of Sciences, Dr. Bohr Gasse 3, A-1030 Vienna, Austria
- Gregor
Mendel Institute of Molecular Plant Biology of the Austrian Academy
of Sciences, Dr. Bohr
Gasse 3, A-1030 Vienna, Austria
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16
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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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17
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Ivanov A, Marie AL, Gao Y. In-capillary sample processing coupled to label-free capillary electrophoresis-mass spectrometry to decipher the native N-glycome of single mammalian cells and ng-level blood isolates. RESEARCH SQUARE 2023:rs.3.rs-3500983. [PMID: 38014012 PMCID: PMC10680937 DOI: 10.21203/rs.3.rs-3500983/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
The development of reliable single-cell dispensers and substantial sensitivity improvement in mass spectrometry made proteomic profiling of individual cells achievable. Yet, there are no established methods for single-cell glycome analysis due to the inability to amplify glycans and sample losses associated with sample processing and glycan labeling. In this work, we developed an integrated platform coupling online in-capillary sample processing with high-sensitivity label-free capillary electrophoresis-mass spectrometry for N-glycan profiling of single mammalian cells. Direct and unbiased characterization and quantification of single-cell surface N-glycomes were demonstrated for HeLa and U87 cells, with the detection of up to 100 N-glycans per single cell. Interestingly, N-glycome alterations were unequivocally detected at the single-cell level in HeLa and U87 cells stimulated with lipopolysaccharide. The developed workflow was also applied to the profiling of ng-level amounts of blood-derived protein, extracellular vesicle, and total plasma isolates, resulting in over 170, 220, and 370 quantitated N-glycans, respectively.
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18
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Li M, Ma M, Li L. Development of novel isobaric tags enables accurate and sensitive multiplexed proteomics using complementary ions. Anal Bioanal Chem 2023; 415:6951-6960. [PMID: 37530794 PMCID: PMC10729713 DOI: 10.1007/s00216-023-04877-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Revised: 07/14/2023] [Accepted: 07/18/2023] [Indexed: 08/03/2023]
Abstract
High-throughput quantitative analysis of the cells' proteomes across multiple conditions such as various perturbations and different time points is essential for gaining insights into treatment-induced biological responses or disease pathological states. The advancements in mass spectrometry instrumentation and isobaric labeling methods provided useful tools to help address such demands. However, the current widely adopted isobaric labeling methods such as tandem mass tag (TMT) and isobaric tags for relative and absolute quantitation (iTRAQ) are based on low-mass reporter ions, which are indistinguishable among different peptide analytes, to achieve relative quantification. Therefore, these methods intrinsically suffer from severe ratio distortion when analyzing complex samples due to peptide coelution and cofragmentation. Here, we developed a novel set of isobaric tags named dimethylated leucine complementary ion (DiLeuC) and relied on complementary ions for relative quantification, in which the complementary ions are the remanent peptide segments after fragmentation in the high-mass range. Since those residual peptide fragments are precursor-specific, they retain the relative abundance information in an interference-free manner even in a complex matrix environment. The quantification accuracy of our method was validated in a two-proteome model where the yeast proteome was spiked with a strong background human proteome as interference. In addition, we also applied this strategy to single-cell proteome analysis, demonstrating its potential utility for sensitive high-throughput quantitative proteomics.
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Affiliation(s)
- Miyang Li
- Department of Chemistry, University of WI-Madison, Madison, WI, 53706, USA
| | - Min Ma
- School of Pharmacy, University of WI-Madison, 777 Highland Avenue, Madison, WI, 53705, USA
| | - Lingjun Li
- Department of Chemistry, University of WI-Madison, Madison, WI, 53706, USA.
- School of Pharmacy, University of WI-Madison, 777 Highland Avenue, Madison, WI, 53705, USA.
- Lachman Institute for Pharmaceutical Development, School of Pharmacy, University of WI-Madison, Madison, WI, 53705, USA.
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19
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Liu J, Chen B, Zhang R, Li Y, Chen R, Zhu S, Wen S, Luan T. Recent progress in analytical strategies of arsenic-binding proteomes in living systems. Anal Bioanal Chem 2023; 415:6915-6929. [PMID: 37410126 DOI: 10.1007/s00216-023-04812-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 06/10/2023] [Accepted: 06/15/2023] [Indexed: 07/07/2023]
Abstract
Arsenic (As) is one of the most concerning elements due to its high exposure risks to organisms and ecosystems. The interaction between arsenicals and proteins plays a pivotal role in inducing their biological effects on living systems, e.g., arsenicosis. In this review article, the recent advances in analytical techniques and methods of As-binding proteomes were well summarized and discussed, including chromatographic separation and purification, biotin-streptavidin pull-down probes, in situ imaging using novel fluorescent probes, and protein identification. These analytical technologies could provide a growing body of knowledge regarding the composition, level, and distribution of As-binding proteomes in both cells and biological samples, even at the organellar level. The perspectives on analysis of As-binding proteomes are also proposed, e.g., isolation and identification of minor proteins, in vivo targeted protein degradation (TPD) technologies, and spatial As-binding proteomics. The application and development of sensitive, accurate, and high-throughput methodologies of As-binding proteomics would enable us to address the key molecular mechanisms underlying the adverse health effects of arsenicals.
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Affiliation(s)
- Jiahui Liu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510275, China
| | - Baowei Chen
- Southern Marine Science and Engineering Guangdong Laboratory, School of Marine Sciences, Sun Yat-sen University, Zhuhai, 519082, China
| | - Ruijia Zhang
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510275, China
| | - Yizheng Li
- Southern Marine Science and Engineering Guangdong Laboratory, School of Marine Sciences, Sun Yat-sen University, Zhuhai, 519082, China
| | - Ruohong Chen
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510275, China
| | - Siqi Zhu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510275, China
| | - Shijun Wen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Tiangang Luan
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, 510275, China.
- Institute of Environmental and Ecological Engineering, Guangdong University of Technology, Guangzhou, 510006, China.
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20
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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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21
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Stepler KE, Hannah SC, Taneyhill LA, Nemes P. Deep Proteome of the Developing Chick Midbrain. J Proteome Res 2023; 22:3264-3274. [PMID: 37616547 DOI: 10.1021/acs.jproteome.3c00291] [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: 08/26/2023]
Abstract
The epithelial-to-mesenchymal transition (EMT) and migration of cranial neural crest cells within the midbrain are critical processes that permit proper craniofacial patterning in the early embryo. Disruptions in these processes not only impair development but also lead to various diseases, underscoring the need for their detailed understanding at the molecular level. The chick embryo has served historically as an excellent model for human embryonic development, including cranial neural crest cell EMT and migration. While these developmental events have been characterized transcriptionally, studies at the protein level have not been undertaken to date. Here, we applied mass spectrometry (MS)-based proteomics to establish a deep proteomics profile of the chick midbrain region during early embryonic development. Our proteomics method combines optimal lysis conditions, offline fractionation, separation on a nanopatterned stationary phase (μPAC) using nanoflow liquid chromatography, and detection using quadrupole-ion trap-Orbitrap tribrid high-resolution tandem MS. Identification of >5900 proteins and >450 phosphoproteins in this study marks the deepest coverage of the chick midbrain proteome to date. These proteins have known roles in pathways related to neural crest cell EMT and migration such as signaling, proteolysis/extracellular matrix remodeling, and transcriptional regulation. This study offers valuable insight into important developmental processes occurring in the midbrain region and demonstrates the utility of proteomics for characterization of tissue microenvironments during chick embryogenesis.
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Affiliation(s)
- Kaitlyn E Stepler
- Department of Chemistry & Biochemistry, University of Maryland, College Park, Maryland 20742, United States
| | - Seth C Hannah
- Department of Chemistry & Biochemistry, University of Maryland, College Park, Maryland 20742, United States
- Department of Animal & Avian Sciences, University of Maryland, College Park, Maryland 20742, United States
| | - Lisa A Taneyhill
- Department of Animal & Avian Sciences, University of Maryland, College Park, Maryland 20742, United States
| | - Peter Nemes
- Department of Chemistry & Biochemistry, University of Maryland, College Park, Maryland 20742, United States
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22
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Petrosius V, Aragon-Fernandez P, Üresin N, Kovacs G, Phlairaharn T, Furtwängler B, Op De Beeck J, Skovbakke SL, Goletz S, Thomsen SF, Keller UAD, Natarajan KN, Porse BT, Schoof EM. Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition. Nat Commun 2023; 14:5910. [PMID: 37737208 PMCID: PMC10517177 DOI: 10.1038/s41467-023-41602-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 09/07/2023] [Indexed: 09/23/2023] Open
Abstract
Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount of material encapsulated in a single cell however, raises significant technical challenges to molecular profiling. Due to extensive optimization efforts, single-cell proteomics by Mass Spectrometry (scp-MS) has emerged as a powerful tool to facilitate proteome profiling from ultra-low amounts of input, although further development is needed to realize its full potential. To this end, we carry out comprehensive analysis of orbitrap-based data-independent acquisition (DIA) for limited material proteomics. Notably, we find a fundamental difference between optimal DIA methods for high- and low-load samples. We further improve our low-input DIA method by relying on high-resolution MS1 quantification, thus enhancing sensitivity by more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we are able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we demonstrate the capability of our approach by profiling mouse embryonic stem cell culture conditions, showcasing heterogeneity in global proteomes and highlighting distinct differences in key metabolic enzyme expression in distinct cell subclusters.
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Affiliation(s)
- Valdemaras Petrosius
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Pedro Aragon-Fernandez
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Nil Üresin
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
| | - Gergo Kovacs
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Teeradon Phlairaharn
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
- The Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, 2200, Denmark
- Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Martinsried, 82152, Germany
- MaxPlanck Institute of Biochemistry, Martinsried, 82152, Germany
| | - Benjamin Furtwängler
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
| | - Jeff Op De Beeck
- Thermo Fisher Scientific, Technologiepark-Zwijnaarde 82, B-9052, Gent, Belgium
| | - Sarah L Skovbakke
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Steffen Goletz
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Simon Francis Thomsen
- Department of Dermatology, Bispebjerg Hospital and Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ulrich Auf dem Keller
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Kedar N Natarajan
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Bo T Porse
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
- Dept of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Erwin M Schoof
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark.
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23
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Greguš M, Ivanov AR, Wilson SR. Ultralow flow liquid chromatography and related approaches: A focus on recent bioanalytical applications. J Sep Sci 2023; 46:e2300440. [PMID: 37528733 PMCID: PMC11087205 DOI: 10.1002/jssc.202300440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 07/25/2023] [Accepted: 07/26/2023] [Indexed: 08/03/2023]
Abstract
Ultralow flow LC employs ultra-narrow bore columns and mid-range pL/min to low nL/min flow rates (i.e., ≤20 nL/min). The separation columns that are used under these conditions are typically 2-30 μm in inner diameter. Ultralow flow LC systems allow for exceptionally high sensitivity and frequently high resolution. There has been an increasing interest in the analysis of scarce biological samples, for example, circulating tumor cells, extracellular vesicles, organelles, and single cells, and ultralow flow LC was efficiently applied to such samples. Hence, advances towards dedicated ultralow flow LC instrumentation, technical approaches, and higher throughput (e.g., tens-to-hundreds of single cells analyzed per day) were recently made. Here, we review the types of ultralow flow LC technology, followed by a discussion of selected representative ultralow flow LC applications, focusing on the progress made in bioanalysis of amount-limited samples during the last 10 years. We also discuss several recently reported high-sensitivity applications utilizing flow rates up to 100 nL/min, which are below commonly used nanoLC flow rates. Finally, we discuss the path forward for future developments of ultralow flow LC.
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Affiliation(s)
- Michal Greguš
- Department of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, Massachusetts, USA
| | - Alexander R. Ivanov
- Department of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, Massachusetts, USA
| | - Steven Ray Wilson
- Hybrid Technology Hub-Centre of Excellence, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
- Department of Chemistry, University of Oslo, Oslo, Norway
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24
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Truong T, Webber KGI, Madisyn Johnston S, Boekweg H, Lindgren CM, Liang Y, Nydegger A, Xie X, Tsang TM, Jayatunge DADN, Andersen JL, Payne SH, Kelly RT. Data-Dependent Acquisition with Precursor Coisolation Improves Proteome Coverage and Measurement Throughput for Label-Free Single-Cell Proteomics. Angew Chem Int Ed Engl 2023; 62:e202303415. [PMID: 37380610 PMCID: PMC10529037 DOI: 10.1002/anie.202303415] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 06/20/2023] [Accepted: 06/28/2023] [Indexed: 06/30/2023]
Abstract
We combined efficient sample preparation and ultra-low-flow liquid chromatography with a newly developed data acquisition and analysis scheme termed wide window acquisition (WWA) to quantify >3,000 proteins from single cells in rapid label-free analyses. WWA employs large isolation windows to intentionally co-isolate and co-fragment adjacent precursors along with the selected precursor. Optimized WWA increased the number of MS2-identified proteins by ≈40 % relative to standard data-dependent acquisition. For a 40-min LC gradient operated at ≈15 nL/min, we identified an average of 3,524 proteins per single-cell-sized aliquot of protein digest. Reducing the active gradient to 20 min resulted in a modest 10 % decrease in proteome coverage. Using this platform, we compared protein expression between single HeLa cells having an essential autophagy gene, atg9a, knocked out, with their isogenic WT parental line. Similar proteome coverage was observed, and 268 proteins were significantly up- or downregulated. Protein upregulation primarily related to innate immunity, vesicle trafficking and protein degradation.
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Affiliation(s)
- Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, 84602, USA
| | - Kei G I Webber
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, 84602, USA
| | - S Madisyn Johnston
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, 84602, USA
| | - Hannah Boekweg
- Department of Biology, Brigham Young University, Provo, UT, 84602, USA
| | - Caleb M Lindgren
- Department of Biology, Brigham Young University, Provo, UT, 84602, USA
| | - Yiran Liang
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, 84602, USA
| | - Alissia Nydegger
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, 84602, USA
| | - Xiaofeng Xie
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, 84602, USA
| | - Tsz-Ming Tsang
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, 84602, USA
| | - D A Dasun N Jayatunge
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, 84602, USA
| | - Joshua L Andersen
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, 84602, USA
| | - Samuel H Payne
- Department of Biology, Brigham Young University, Provo, UT, 84602, USA
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, 84602, USA
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25
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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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26
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Mun DG, Bhat FA, Ding H, Madden BJ, Natesampillai S, Badley AD, Johnson KL, Kelly RT, Pandey A. Optimizing single cell proteomics using trapped ion mobility spectrometry for label-free experiments. Analyst 2023; 148:3466-3475. [PMID: 37395315 PMCID: PMC10370902 DOI: 10.1039/d3an00080j] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 03/10/2023] [Indexed: 07/04/2023]
Abstract
Although single cell RNA-seq has had a tremendous impact on biological research, a corresponding technology for unbiased mass spectrometric analysis of single cells has only recently become available. Significant technological breakthroughs including miniaturized sample handling have enabled proteome profiling of single cells. Furthermore, trapped ion mobility spectrometry (TIMS) in combination with parallel accumulation-serial fragmentation operated in data-dependent acquisition mode (DDA-PASEF) allowed improved proteome coverage from low-input samples. It has been demonstrated that modulating the ion flux in TIMS affects the overall performance of proteome profiling. However, the effect of TIMS settings on the analysis of low-input samples has been less investigated. Thus, we sought to optimize the conditions of TIMS with regard to ion accumulation/ramp times and ion mobility range for low-input samples. We observed that an ion accumulation time of 180 ms and monitoring a narrower ion mobility range from 0.7 to 1.3 V s cm-2 resulted in a substantial gain in the depth of proteome coverage and in detecting proteins with low abundance. We used these optimized conditions for proteome profiling of sorted human primary T cells, which yielded an average of 365, 804, 1116, and 1651 proteins from single, five, ten, and forty T cells, respectively. Notably, we demonstrated that the depth of proteome coverage from a low number of cells was sufficient to delineate several essential metabolic pathways and the T cell receptor signaling pathway. Finally, we showed the feasibility of detecting post-translational modifications including phosphorylation and acetylation from single cells. We believe that such an approach could be applied to label-free analysis of single cells obtained from clinically relevant samples.
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Affiliation(s)
- Dong-Gi Mun
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First ST SW, Rochester, MN 55905, USA.
| | - Firdous A Bhat
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First ST SW, Rochester, MN 55905, USA.
| | - Husheng Ding
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First ST SW, Rochester, MN 55905, USA.
| | | | | | - Andrew D Badley
- Division of Infectious Diseases, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, USA
| | - Akhilesh Pandey
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First ST SW, Rochester, MN 55905, USA.
- Manipal Academy of Higher Education, Manipal, 576104, Karnataka, India
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA
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27
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Hu M, Zhang Y, Yuan Y, Ma W, Zheng Y, Gu Q, Xie XS. Correlated Protein Modules Revealing Functional Coordination of Interacting Proteins Are Detected by Single-Cell Proteomics. J Phys Chem B 2023. [PMID: 37368753 DOI: 10.1021/acs.jpcb.3c00014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
Single-cell proteomics has attracted a lot of attention in recent years because it offers more functional relevance than single-cell transcriptomics. However, most work to date has focused on cell typing, which has been widely accomplished by single-cell transcriptomics. Here we report the use of single-cell proteomics to measure the correlation between the translational levels of a pair of proteins in a single mammalian cell. In measuring pairwise correlations among ∼1000 proteins in a population of homogeneous K562 cells under a steady-state condition, we observed multiple correlated protein modules (CPMs), each containing a group of highly positively correlated proteins that are functionally interacting and collectively involved in certain biological functions, such as protein synthesis and oxidative phosphorylation. Some CPMs are shared across different cell types while others are cell-type specific. Widely studied in omics analyses, pairwise correlations are often measured by introducing perturbations into bulk samples. However, some correlations of gene or protein expression under the steady-state condition would be masked by perturbation. The single-cell correlations probed in our experiment reflect intrinsic steady-state fluctuations in the absence of perturbation. We note that observed correlations between proteins are experimentally more distinct and functionally more relevant than those between corresponding mRNAs measured in single-cell transcriptomics. By virtue of single-cell proteomics, functional coordination of proteins is manifested through CPMs.
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Affiliation(s)
- Mo Hu
- Beijing Advanced Innovation Center for Genomics, Peking University, Beijing 100871, China
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
| | - Yutong Zhang
- Beijing Advanced Innovation Center for Genomics, Peking University, Beijing 100871, China
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China
- College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Yuan Yuan
- Beijing Advanced Innovation Center for Genomics, Peking University, Beijing 100871, China
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China
- College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Wenping Ma
- Beijing Advanced Innovation Center for Genomics, Peking University, Beijing 100871, China
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences (CLS), Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Yinghui Zheng
- Beijing Advanced Innovation Center for Genomics, Peking University, Beijing 100871, China
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China
| | | | - X Sunney Xie
- Beijing Advanced Innovation Center for Genomics, Peking University, Beijing 100871, China
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
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28
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Guise AJ, Misal SA, Carson R, Boekweg H, Watt DVD, Truong T, Liang Y, Chu JH, Welsh NC, Gagnon J, Payne SH, Plowey ED, Kelly RT. TDP-43-stratified single-cell proteomic profiling of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.08.544233. [PMID: 37333094 PMCID: PMC10274884 DOI: 10.1101/2023.06.08.544233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Unbiased proteomics has been employed to interrogate central nervous system (CNS) tissues (brain, spinal cord) and fluid matrices (CSF, plasma) from amyotrophic lateral sclerosis (ALS) patients; yet, a limitation of conventional bulk tissue studies is that motor neuron (MN) proteome signals may be confounded by admixed non-MN proteins. Recent advances in trace sample proteomics have enabled quantitative protein abundance datasets from single human MNs (Cong et al., 2020b). In this study, we leveraged laser capture microdissection (LCM) and nanoPOTS (Zhu et al., 2018c) single-cell mass spectrometry (MS)-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control donor spinal cord tissues, leading to the identification of 2515 proteins across MNs samples (>900 per single MN) and quantitative comparison of 1870 proteins between disease groups. Furthermore, we studied the impact of enriching/stratifying MN proteome samples based on the presence and extent of immunoreactive, cytoplasmic TDP-43 inclusions, allowing identification of 3368 proteins across MNs samples and profiling of 2238 proteins across TDP-43 strata. We found extensive overlap in differential protein abundance profiles between MNs with or without obvious TDP-43 cytoplasmic inclusions that together point to early and sustained dysregulation of oxidative phosphorylation, mRNA splicing and translation, and retromer-mediated vesicular transport in ALS. Our data are the first unbiased quantification of single MN protein abundance changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein abundance changes in human neurologic diseases.
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Affiliation(s)
| | - Santosh A. Misal
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602
| | - Richard Carson
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602
| | - Hannah Boekweg
- Biology Department, Brigham Young University, Provo, UT 84602, USA
| | | | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602
| | - Yiran Liang
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602
| | | | | | | | - Samuel H. Payne
- Biology Department, Brigham Young University, Provo, UT 84602, USA
| | | | - Ryan T. Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT 84602
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29
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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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30
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A rapid and sensitive single-cell proteomic method based on fast liquid-chromatography separation, retention time prediction and MS1-only acquisition. Anal Chim Acta 2023; 1251:341038. [PMID: 36925302 DOI: 10.1016/j.aca.2023.341038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 02/28/2023] [Accepted: 03/01/2023] [Indexed: 03/06/2023]
Abstract
Single-cell analysis has received much attention in recent years for elucidating the widely existing cellular heterogeneity in biological systems. However, the ability to measure the proteome in single cells is still far behind that of transcriptomics due to the lack of sensitive and high-throughput mass spectrometry methods. Herein, we report an integrated strategy termed "SCP-MS1" that combines fast liquid chromatography (LC) separation, deep learning-based retention time (RT) prediction and MS1-only acquisition for rapid and sensitive single-cell proteome analysis. In SCP-MS1, the peptides were identified via four-dimensional MS1 feature (m/z, RT, charge and FAIMS CV) matching, therefore relieving MS acquisition from the time consuming and information losing MS2 step and making this method particularly compatible with fast LC separation. By completely omitting the MS2 step, all the MS analysis time was utilized for MS1 acquisition in SCP-MS1 and therefore led to 65%-138% increased MS1 feature collection. Unlike "match between run" methods that still needed MS2 information for RT alignment, SCP-MS1 used deep learning-based RT prediction to transfer the measured RTs in long gradient bulk analyses to short gradient single cell analyses, which was the key step to enhance both identification scale and matching accuracy. Using this strategy, more than 2000 proteins were obtained from 0.2 ng of peptides with a 14-min active gradient at a false discovery rate (FDR) of 0.8%. Comparing with the DDA method, improved quantitative performance was also observed for SCP-MS1 with approximately 50% decreased median coefficient of variation of quantified proteins. For single-cell analysis, 1715 ± 204 and 1604 ± 224 proteins were quantified in single 293T and HeLa cells, respectively. Finally, SCP-MS1 was applied to single-cell proteome analysis of sorafenib resistant and non-resistant HepG2 cells and revealed clear cellular heterogeneity in the resistant population that may be masked in bulk studies.
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31
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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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32
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Peng J, Chan C, Meng F, Hu Y, Chen L, Lin G, Zhang S, Wheeler AR. Comparison of Database Searching Programs for the Analysis of Single-Cell Proteomics Data. J Proteome Res 2023; 22:1298-1308. [PMID: 36892105 DOI: 10.1021/acs.jproteome.2c00821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/10/2023]
Abstract
Single-cell proteomics is emerging as an important subfield in the proteomics and mass spectrometry communities, with potential to reshape our understanding of cell development, cell differentiation, disease diagnosis, and the development of new therapies. Compared with significant advancements in the "hardware" that is used in single-cell proteomics, there has been little work comparing the effects of using different "software" packages to analyze single-cell proteomics datasets. To this end, seven popular proteomics programs were compared here, applying them to search three single-cell proteomics datasets generated by three different platforms. The results suggest that MSGF+, MSFragger, and Proteome Discoverer are generally more efficient in maximizing protein identifications, that MaxQuant is better suited for the identification of low-abundance proteins, that MSFragger is superior in elucidating peptide modifications, and that Mascot and X!Tandem are better for analyzing long peptides. Furthermore, an experiment with different loading amounts was carried out to investigate changes in identification results and to explore areas in which single-cell proteomics data analysis may be improved in the future. We propose that this comparative study may provide insight for experts and beginners alike operating in the emerging subfield of single-cell proteomics.
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Affiliation(s)
- Jiaxi Peng
- Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada.,Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada.,Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario M5S 3G9, Canada
| | - Calvin Chan
- Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada
| | - Fei Meng
- Clinical Research Center for Reproduction and Genetics in Hunan Province, Reproductive and Genetic Hospital of CITIC-XIANGYA, Changsha, Hunan 410000, China
| | - Yechen Hu
- Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada.,Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada.,Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario M5S 3G9, Canada
| | - Lingfan Chen
- Fujian Province New Drug Safety Evaluation Centre, Fujian Medical University, Fuzhou Fujian 350108, China
| | - Ge Lin
- Clinical Research Center for Reproduction and Genetics in Hunan Province, Reproductive and Genetic Hospital of CITIC-XIANGYA, Changsha, Hunan 410000, China.,Laboratory of Reproductive and Stem Cell Engineering, NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Central South University, Changsha, Hunan 410075, China
| | - Shen Zhang
- Clinical Research Center for Reproduction and Genetics in Hunan Province, Reproductive and Genetic Hospital of CITIC-XIANGYA, Changsha, Hunan 410000, China
| | - Aaron R Wheeler
- Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada.,Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada.,Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario M5S 3G9, Canada
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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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Gatto L, Aebersold R, Cox J, Demichev V, Derks J, Emmott E, Franks AM, Ivanov AR, Kelly RT, Khoury L, Leduc A, MacCoss MJ, Nemes P, Perlman DH, Petelski AA, Rose CM, Schoof EM, Van Eyk J, Vanderaa C, Yates JR, Slavov N. Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments. Nat Methods 2023; 20:375-386. [PMID: 36864200 PMCID: PMC10130941 DOI: 10.1038/s41592-023-01785-3] [Citation(s) in RCA: 39] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 01/24/2023] [Indexed: 03/04/2023]
Abstract
Analyzing proteins from single cells by tandem mass spectrometry (MS) has recently become technically feasible. While such analysis has the potential to accurately quantify thousands of proteins across thousands of single cells, the accuracy and reproducibility of the results may be undermined by numerous factors affecting experimental design, sample preparation, data acquisition and data analysis. We expect that broadly accepted community guidelines and standardized metrics will enhance rigor, data quality and alignment between laboratories. Here we propose best practices, quality controls and data-reporting recommendations to assist in the broad adoption of reliable quantitative workflows for single-cell proteomics. Resources and discussion forums are available at https://single-cell.net/guidelines .
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Affiliation(s)
- Laurent Gatto
- Computational Biology and Bioinformatics Unit, de Duve Institute, Université Catholique de Louvain, Brussels, Belgium
| | - Ruedi Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Juergen Cox
- Max Planck Institute of Biochemistry, Martinsried, Germany
| | | | - Jason Derks
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA
| | - Edward Emmott
- Centre for Proteome Research, Department of Biochemistry and Systems Biology, University of Liverpool, Liverpool, UK
| | - Alexander M Franks
- Department of Statistics and Applied Probability, University of California Santa Barbara, Santa Barbara, CA, USA
| | - Alexander R Ivanov
- Department of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, USA
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA
| | - Luke Khoury
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA
| | - Andrew Leduc
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA
| | | | - Peter Nemes
- Department of Chemistry and Biochemistry, University of Maryland, College Park, MD, USA
| | - David H Perlman
- Merck Exploratory Science Center, Merck Sharp & Dohme Corp., Cambridge, MA, USA
| | - Aleksandra A Petelski
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA
- Parallel Squared Technology Institute, Watertown, MA, USA
| | - Christopher M Rose
- Department of Microchemistry, Proteomics and Lipidomics, Genentech Inc., South San Francisco, CA, USA
| | - Erwin M Schoof
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | | | - Christophe Vanderaa
- Computational Biology and Bioinformatics Unit, de Duve Institute, Université Catholique de Louvain, Brussels, Belgium
| | - John R Yates
- Departments of Molecular Medicine and Neurobiology, the Scripps Research Institute, La Jolla, CA, USA
| | - Nikolai Slavov
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single-Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA.
- Parallel Squared Technology Institute, Watertown, MA, USA.
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35
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Single-cell proteomics enabled by next-generation sequencing or mass spectrometry. Nat Methods 2023; 20:363-374. [PMID: 36864196 DOI: 10.1038/s41592-023-01791-5] [Citation(s) in RCA: 43] [Impact Index Per Article: 43.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 01/24/2023] [Indexed: 03/04/2023]
Abstract
In the last decade, single-cell RNA sequencing routinely performed on large numbers of single cells has greatly advanced our understanding of the underlying heterogeneity of complex biological systems. Technological advances have also enabled protein measurements, further contributing to the elucidation of cell types and states present in complex tissues. Recently, there have been independent advances in mass spectrometric techniques bringing us one step closer to characterizing single-cell proteomes. Here we discuss the challenges of detecting proteins in single cells by both mass spectrometry and sequencing-based methods. We review the state of the art for these techniques and propose that there is a space for technological advancements and complementary approaches that maximize the advantages of both classes of technologies.
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36
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Liang Y, Zhang L, Zhang Y. Chromatographic separation of peptides and proteins for characterization of proteomes. Chem Commun (Camb) 2023; 59:270-281. [PMID: 36504223 DOI: 10.1039/d2cc05568f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Characterization of proteomes aims to comprehensively characterize proteins in cells or tissues via two main strategies: (1) bottom-up strategy based on the separation and identification of enzymatic peptides; (2) top-down strategy based on the separation and identification of intact proteins. However, it is challenged by the high complexity of proteomes. Consequently, the improvements in peptide and protein separation technologies for simplifying the sample should be critical. In this feature article, separation columns for peptide and protein separation were introduced, and peptide separation technologies for bottom-up proteomic analysis as well as protein separation technologies for top-down proteomic analysis were summarized. The achievement, recent development, limitation and future trends are discussed. Besides, the outlook on challenges and future directions of chromatographic separation in the field of proteomics was also presented.
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Affiliation(s)
- Yu Liang
- CAS Key Lab of Separation Sciences for Analytical Chemistry, National Chromatographic Research and Analysis Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.
| | - Lihua Zhang
- CAS Key Lab of Separation Sciences for Analytical Chemistry, National Chromatographic Research and Analysis Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.
| | - Yukui Zhang
- CAS Key Lab of Separation Sciences for Analytical Chemistry, National Chromatographic Research and Analysis Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.
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37
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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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38
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Lapizco-Encinas BH, Zhang YV. Microfluidic systems in clinical diagnosis. Electrophoresis 2023; 44:217-245. [PMID: 35977346 DOI: 10.1002/elps.202200150] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 08/10/2022] [Accepted: 08/11/2022] [Indexed: 02/01/2023]
Abstract
The use of microfluidic devices is highly attractive in the field of biomedical and clinical assessments, as their portability and fast response time have become crucial in providing opportune therapeutic treatments to patients. The applications of microfluidics in clinical diagnosis and point-of-care devices are continuously growing. The present review article discusses three main fields where miniaturized devices are successfully employed in clinical applications. The quantification of ions, sugars, and small metabolites is examined considering the analysis of bodily fluids samples and the quantification of this type of analytes employing real-time wearable devices. The discussion covers the level of maturity that the devices have reached as well as cost-effectiveness. The analysis of proteins with clinical relevance is presented and organized by the function of the proteins. The last section covers devices that can perform single-cell metabolomic and proteomic assessments. Each section discusses several strategically selected recent reports on microfluidic devices successfully employed for clinical assessments, to provide the reader with a wide overview of the plethora of novel systems and microdevices developed in the last 5 years. In each section, the novel aspects and main contributions of each reviewed report are highlighted. Finally, the conclusions and future outlook section present a summary and speculate on the future direction of the field of miniaturized devices for clinical applications.
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Affiliation(s)
- Blanca H Lapizco-Encinas
- Microscale Bioseparations Laboratory and Biomedical Engineering Department, Rochester Institute of Technology, Rochester, New York, USA
| | - Yan Victoria Zhang
- Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, Rochester, New York, USA
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39
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Wu Y, Zhang W, Zhao Y, Wang X, Guo G. Technology development trend of electrospray ionization mass spectrometry for single-cell proteomics. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
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40
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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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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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van der Pan K, Kassem S, Khatri I, de Ru AH, Janssen GMC, Tjokrodirijo RTN, al Makindji F, Stavrakaki E, de Jager AL, Naber BAE, de Laat IF, Louis A, van den Bossche WBL, Vogelezang LB, Balvers RK, Lamfers MLM, van Veelen PA, Orfao A, van Dongen JJM, Teodosio C, Díez P. Quantitative proteomics of small numbers of closely-related cells: Selection of the optimal method for a clinical setting. Front Med (Lausanne) 2022; 9:997305. [PMID: 36237552 PMCID: PMC9553008 DOI: 10.3389/fmed.2022.997305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 08/31/2022] [Indexed: 11/13/2022] Open
Abstract
Mass spectrometry (MS)-based proteomics profiling has undoubtedly increased the knowledge about cellular processes and functions. However, its applicability for paucicellular sample analyses is currently limited. Although new approaches have been developed for single-cell studies, most of them have not (yet) been standardized and/or require highly specific (often home-built) devices, thereby limiting their broad implementation, particularly in non-specialized settings. To select an optimal MS-oriented proteomics approach applicable in translational research and clinical settings, we assessed 10 different sample preparation procedures in paucicellular samples of closely-related cell types. Particularly, five cell lysis protocols using different chemistries and mechanical forces were combined with two sample clean-up techniques (C18 filter- and SP3-based), followed by tandem mass tag (TMT)-based protein quantification. The evaluation was structured in three phases: first, cell lines from hematopoietic (THP-1) and non-hematopoietic (HT-29) origins were used to test the approaches showing the combination of a urea-based lysis buffer with the SP3 bead-based clean-up system as the best performer. Parameters such as reproducibility, accessibility, spatial distribution, ease of use, processing time and cost were considered. In the second phase, the performance of the method was tested on maturation-related cell populations: three different monocyte subsets from peripheral blood and, for the first time, macrophages/microglia (MAC) from glioblastoma samples, together with T cells from both tissues. The analysis of 50,000 cells down to only 2,500 cells revealed different protein expression profiles associated with the distinct cell populations. Accordingly, a closer relationship was observed between non-classical monocytes and MAC, with the latter showing the co-expression of M1 and M2 macrophage markers, although pro-tumoral and anti-inflammatory proteins were more represented. In the third phase, the results were validated by high-end spectral flow cytometry on paired monocyte/MAC samples to further determine the sensitivity of the MS approach selected. Finally, the feasibility of the method was proven in 194 additional samples corresponding to 38 different cell types, including cells from different tissue origins, cellular lineages, maturation stages and stimuli. In summary, we selected a reproducible, easy-to-implement sample preparation method for MS-based proteomic characterization of paucicellular samples, also applicable in the setting of functionally closely-related cell populations.
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Affiliation(s)
- Kyra van der Pan
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Sara Kassem
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Indu Khatri
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
- Leiden Computational Biology Center, LUMC, Leiden, Netherlands
| | - Arnoud H. de Ru
- Center for Proteomics and Metabolomics, LUMC, Leiden, Netherlands
| | | | | | - Fadi al Makindji
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | | | - Anniek L. de Jager
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Brigitta A. E. Naber
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Inge F. de Laat
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | - Alesha Louis
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
| | | | | | | | | | | | - Alberto Orfao
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca-CSIC), Salamanca, Spain
- Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
| | - Jacques J. M. van Dongen
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca-CSIC), Salamanca, Spain
- Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
- *Correspondence: Jacques J. M. van Dongen
| | - Cristina Teodosio
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca-CSIC), Salamanca, Spain
- Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
| | - Paula Díez
- Department of Immunology, Leiden University Medical Center (LUMC), Leiden, Netherlands
- Translational and Clinical Research Program, Cancer Research Center (IBMCC; University of Salamanca-CSIC), Salamanca, Spain
- Cytometry Service, NUCLEUS, Department of Medicine, University of Salamanca and Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain
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44
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Guerrero L, Paradela A, Corrales FJ. Targeted Proteomics for Monitoring One-Carbon Metabolism in Liver Diseases. Metabolites 2022; 12:metabo12090779. [PMID: 36144184 PMCID: PMC9501948 DOI: 10.3390/metabo12090779] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 08/18/2022] [Accepted: 08/19/2022] [Indexed: 11/16/2022] Open
Abstract
Liver diseases cause approximately 2 million deaths per year worldwide and had an increasing incidence during the last decade. Risk factors for liver diseases include alcohol consumption, obesity, diabetes, the intake of hepatotoxic substances like aflatoxin, viral infection, and genetic determinants. Liver cancer is the sixth most prevalent cancer and the third in mortality (second in males). The low survival rate (less than 20% in 5 years) is partially explained by the late diagnosis, which remarks the need for new early molecular biomarkers. One-carbon metabolism integrates folate and methionine cycles and participates in essential cell processes such as redox homeostasis maintenance and the regulation of methylation reactions through the production of intermediate metabolites such as cysteine and S-Adenosylmethionine. One-carbon metabolism has a tissue specific configuration, and in the liver, the participating enzymes are abundantly expressed—a requirement to maintain hepatocyte differentiation. Targeted proteomics studies have revealed significant differences in hepatocellular carcinoma and cirrhosis, suggesting that monitoring one-carbon metabolism enzymes can be useful for stratification of liver disease patients and to develop precision medicine strategies for their clinical management. Here, reprogramming of one-carbon metabolism in liver diseases is described and the role of mass spectrometry to follow-up these alterations is discussed.
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Affiliation(s)
- Laura Guerrero
- Centro Nacional de Biotecnología (CNB), CSIC. C/Darwin 3, 28049 Madrid, Spain
| | - Alberto Paradela
- Centro Nacional de Biotecnología (CNB), CSIC. C/Darwin 3, 28049 Madrid, Spain
| | - Fernando J. Corrales
- Centro Nacional de Biotecnología (CNB), CSIC. C/Darwin 3, 28049 Madrid, Spain
- National Institute for the Study of Liver and Gastrointestinal Diseases (CIBERehd, Carlos III Health Institute), 28029 Madrid, Spain
- Correspondence: ; Tel.: +34-91-585-46-96
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45
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Portero EP, Pade L, Li J, Choi SB, Nemes P. Single-Cell Mass Spectrometry of Metabolites and Proteins for Systems and Functional Biology. NEUROMETHODS 2022; 184:87-114. [PMID: 36699808 PMCID: PMC9872963 DOI: 10.1007/978-1-0716-2525-5_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Molecular composition is intricately intertwined with cellular function, and elucidation of this relationship is essential for understanding life processes and developing next-generational therapeutics. Technological innovations in capillary electrophoresis (CE) and liquid chromatography (LC) mass spectrometry (MS) provide previously unavailable insights into cellular biochemistry by allowing for the unbiased detection and quantification of molecules with high specificity. This chapter presents our validated protocols integrating ultrasensitive MS with classical tools of cell, developmental, and neurobiology to assess the biological function of important biomolecules. We use CE and LC MS to measure hundreds of metabolites and thousands of proteins in single cells or limited populations of tissues in chordate embryos and mammalian neurons, revealing molecular heterogeneity between identified cells. By pairing microinjection and optical microscopy, we demonstrate cell lineage tracing and testing the roles the dysregulated molecules play in the formation and maintenance of cell heterogeneity and tissue specification in frog embryos (Xenopus laevis). Electrophysiology extends our workflows to characterizing neuronal activity in sections of mammalian brain tissues. The information obtained from these studies mutually strengthen chemistry and biology and highlight the importance of interdisciplinary research to advance basic knowledge and translational applications forward.
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Affiliation(s)
| | | | - Jie Li
- Department of Chemistry & Biochemistry, University of Maryland, 8051 Regents Drive, College Park, MD 20742
| | - Sam B. Choi
- 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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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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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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Kelly RT. Let’s Get Small: Miniaturizing Separations for Single-Cell Analysis. LCGC NORTH AMERICA 2022. [DOI: 10.56530/lcgc.na.us2479y3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Direct profiling of biochemical expression within single cells provides insights into cellular processes that are lost when ensemble averages are measured across populations of cells. Advanced separations coupled with mass spectrometry (MS) can now quantify more than 1000 proteins within single cells. Further miniaturization of separations will greatly extend the reach of single-cell proteomics, metabolomics, and lipidomics, but key challenges in instrumentation, column technology, and ionization sources must be addressed.
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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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Abstract
Single-cell proteomics is a promising field to provide direct yet comprehensive molecular insights into cellular functions without averaging effects. Here, we address a grand technical challenge impeding the maturation of single-cell proteomics─protein adsorption loss (PAL). Even though widely known, there is currently no quantitation on how profoundly and selectively PAL has affected single-cell proteomics. Therefore, the mitigations to this challenge have been generic, and their efficacy was only evaluated by the size of the resolved proteome with no specificity on individual proteins. We use the existing knowledge of PAL, protein expression, and the typical surface area used in single-cell proteomics to discuss the severity of protein loss. We also summarize the current solutions to this challenge and briefly review the available methods to characterize the physical and chemical properties of protein surface adsorption. By citing successful strategies in single-cell genomics for measurement errors in individual transcripts, we pinpoint the urgency to benchmark PAL at the proteome scale with individual protein resolution. Finally, orthogonal single-cell proteomic techniques that have the potential to cross validate PAL are proposed. We hope these efforts can promote the fruition of single-cell proteomics in the near future.
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Affiliation(s)
- Bingyun Sun
- Department of Chemistry, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada.,Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada
| | - Sharwan Kumar
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada
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