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Sun F, Li H, Sun D, Fu S, Gu L, Shao X, Wang Q, Dong X, Duan B, Xing F, Wu J, Xiao M, Zhao F, Han JDJ, Liu Q, Fan X, Li C, Wang C, Shi T. Single-cell omics: experimental workflow, data analyses and applications. SCIENCE CHINA. LIFE SCIENCES 2024:10.1007/s11427-023-2561-0. [PMID: 39060615 DOI: 10.1007/s11427-023-2561-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/18/2024] [Indexed: 07/28/2024]
Abstract
Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.
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Affiliation(s)
- Fengying Sun
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China
| | - Haoyan Li
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Dongqing Sun
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Shaliu Fu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Lei Gu
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Shao
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China
| | - Qinqin Wang
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Dong
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Bin Duan
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Feiyang Xing
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Jun Wu
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Minmin Xiao
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
| | - Fangqing Zhao
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Qi Liu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China.
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China.
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China.
- Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China.
| | - Chen Li
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Chenfei Wang
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Tieliu Shi
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
- Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, School of Statistics, East China Normal University, Shanghai, 200062, China.
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Abstract
Metabolomics aims to profile the extensive array of metabolites that exists in different types of matrices using modern analytical techniques. These techniques help to separate, identify, and quantify the plethora of chemical compounds at various analytical platforms. Hence, ion mobility spectrometry (IMS) has emerged as an advanced analytical approach, exclusively owing to the 3D separation of metabolites and their isomers. Furthermore, separated metabolites are identified based on their mass fragmentation pattern and CCS (collision cross-section) values. The IMS provides an advanced alternative dimension to separate the isomeric metabolites with enhanced throughput with lesser chemical noise. Thus, the present review highlights the types, factors affecting the resolution, and applications of IMMS (Ion mobility mass spectrometry) for isomeric separations, and ionic contaminants in the plant samples. Furthermore, an overview of IMS-based applications for the identification of plant metabolites (volatile and non-volatile) over the last few decades has been discussed, followed by future assumptions for creating IM-based databases. Such approaches could be significant to accelerate and improve our knowledge of the vast chemical diversity found in plants.
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Affiliation(s)
- Robin Joshi
- Biotechnology Division, CSIR-Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh, India
- Academy of Scientific and Innovative Research, (AcSIR), Ghaziabad, India
| | - Shruti Sharma
- Academy of Scientific and Innovative Research, (AcSIR), Ghaziabad, India
- Chemical Technology Division, CSIR-Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh, India
| | - Dinesh Kumar
- Academy of Scientific and Innovative Research, (AcSIR), Ghaziabad, India
- Chemical Technology Division, CSIR-Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh, India
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3
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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; 23:2230-2240. [PMID: 38690845 PMCID: PMC11165581 DOI: 10.1021/acs.jproteome.4c00181] [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: 03/07/2024] [Revised: 04/18/2024] [Accepted: 04/23/2024] [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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4
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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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5
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Zimmerman AJ, Greguš M, Ivanov AR. Comprehensive Micro-SPE-Based Bottom-Up Proteomic Workflow for Sensitive Analysis of Limited Samples. Methods Mol Biol 2024; 2817:19-31. [PMID: 38907144 DOI: 10.1007/978-1-0716-3934-4_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/23/2024]
Abstract
Clinical and biological samples are often scarce and precious (e.g., rare cell isolates, microneedle tissue biopsies, small-volume liquid biopsies, and even single cells or organelles). Typical large-scale proteomic methods, where significantly higher protein amounts are analyzed, are not directly transferable to the analysis of limited samples due to their incompatibility with pg-, ng-, and low-μg-level protein sample amounts. Here, we report the on-microsolid-phase extraction tip (OmSET)-based sample preparation workflow for sensitive analysis of limited biological samples to address this challenge. The developed platform was successfully tested for the analysis of 100-10,000 typical mammalian cells and is scalable to allow for lower and larger protein amounts and more samples to be analyzed (i.e., higher throughput of analysis).
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Affiliation(s)
- Alan J Zimmerman
- Department of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, USA
| | - Michal Greguš
- Department of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, USA
| | - Alexander R Ivanov
- Department of Chemistry and Chemical Biology, Barnett Institute of Chemical and Biological Analysis, Northeastern University, Boston, MA, USA.
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6
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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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7
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Zheng R, Matzinger M, Mayer RL, Valenta A, Sun X, Mechtler K. A High-Sensitivity Low-Nanoflow LC-MS Configuration for High-Throughput Sample-Limited Proteomics. Anal Chem 2023; 95:18673-18678. [PMID: 38088903 PMCID: PMC10753523 DOI: 10.1021/acs.analchem.3c03058] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 11/16/2023] [Accepted: 11/21/2023] [Indexed: 12/27/2023]
Abstract
This work demonstrates the utility of high-throughput nanoLC-MS and label-free quantification (LFQ) for sample-limited bottom-up proteomics analysis, including single-cell proteomics (SCP). Conditions were optimized on a 50 μm internal diameter (I.D.) column operated at 100 nL/min in the direct injection workflow to balance method sensitivity and sample throughput from 24 to 72 samples/day. Multiple data acquisition strategies were also evaluated for proteome coverage, including data-dependent acquisition (DDA), wide-window acquisition (WWA), and wide-window data-independent acquisition (WW-DIA). Analyzing 250 pg HeLa digest with a 10-min LC gradient (72 samples/day) provided >900, >1,800, and >3,000 protein group identifications for DDA, WWA, and WW-DIA, respectively. Total method cycle time was further reduced from 20 to 14.4 min (100 samples/day) by employing a trap-and-elute workflow, enabling 70% mass spectrometer utilization. The method was applied to library-free DIA analysis of single-cell samples, yielding >1,700 protein groups identified. In conclusion, this study provides a high-sensitivity, high-throughput nanoLC-MS configuration for sample-limited proteomics.
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Affiliation(s)
- Runsheng Zheng
- Thermo
Fisher Scientific, Dornier Str. 4, 82110 Germering, Germany
| | - Manuel Matzinger
- IMP—Institute
of Molecular Pathology, Campus-Vienna-Biocenter 1, A-1030 Vienna, Austria
| | - Rupert L. Mayer
- IMP—Institute
of Molecular Pathology, Campus-Vienna-Biocenter 1, A-1030 Vienna, Austria
| | - Alec Valenta
- Thermo
Fisher Scientific, Dornier Str. 4, 82110 Germering, Germany
| | - Xuefei Sun
- Thermo
Fisher Scientific, 1228 Titan Way, Sunnyvale, California 94085, United States
| | - Karl Mechtler
- IMP—Institute
of Molecular Pathology, Campus-Vienna-Biocenter 1, A-1030 Vienna, Austria
- IMBA—Institute
of Molecular Biotechnology of the Austrian Academy of Sciences, Dr. Bohr Gasse 3, A-1030 Vienna, Austria
- Gregor
Mendel Institute of Molecular Plant Biology of the Austrian Academy
of Sciences, Dr. Bohr
Gasse 3, A-1030 Vienna, Austria
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Ctortecka C, Hartlmayr D, Seth A, Mendjan S, Tourniaire G, Udeshi ND, Carr SA, Mechtler K. An Automated Nanowell-Array Workflow for Quantitative Multiplexed Single-Cell Proteomics Sample Preparation at High Sensitivity. Mol Cell Proteomics 2023; 22:100665. [PMID: 37839701 PMCID: PMC10684380 DOI: 10.1016/j.mcpro.2023.100665] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 10/03/2023] [Accepted: 10/06/2023] [Indexed: 10/17/2023] Open
Abstract
Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lags. Here, we introduce the proteoCHIP, a universal option for single-cell proteomics sample preparation including multiplexed labeling up to 16-plex with high sensitivity and throughput. The automated processing using a commercial system combining single-cell isolation and picoliter dispensing, the cellenONE, reduces final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error-prone manual sample handling and overcoming evaporation. The specialized proteoCHIP design allows direct injection of single cells via a standard autosampler resulting in around 1500 protein groups per TMT10-plex with reduced or eliminated need for a carrier proteome. We evaluated the effect of wider precursor isolation windows at single-cell input levels and found that using 2 Da isolation windows increased overall sensitivity without significantly impacting interference. Using the dedicated mass spectrometry acquisition strategies detailed here, we identified on average close to 2000 proteins per TMT10-plex across 170 multiplexed single cells that readily distinguished human cell types. Overall, our workflow combines highly efficient sample preparation, chromatographic and ion mobility-based filtering, rapid wide-window data-dependent acquisition analysis, and intelligent data analysis for optimal multiplexed single-cell proteomics. This versatile and automated proteoCHIP-based sample preparation approach is sufficiently sensitive to drive biological applications of single-cell proteomics and can be readily adopted by proteomics laboratories.
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Affiliation(s)
- Claudia Ctortecka
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria; Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
| | - David Hartlmayr
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria; Cellenion SASU, Lyon, France
| | | | - Sasha Mendjan
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Vienna, Austria
| | | | - Namrata D Udeshi
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Steven A Carr
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
| | - Karl Mechtler
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria; Cellenion SASU, Lyon, France; Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Vienna, Austria; The Gregor Mendel Institute of Molecular Plant Biology of the Austrian Academy of Sciences (GMI), Vienna BioCenter (VBC), Vienna, Austria.
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9
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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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Montero-Calle A, Garranzo-Asensio M, Rejas-González R, Feliu J, Mendiola M, Peláez-García A, Barderas R. Benefits of FAIMS to Improve the Proteome Coverage of Deteriorated and/or Cross-Linked TMT 10-Plex FFPE Tissue and Plasma-Derived Exosomes Samples. Proteomes 2023; 11:35. [PMID: 37987315 PMCID: PMC10661291 DOI: 10.3390/proteomes11040035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 09/20/2023] [Accepted: 10/20/2023] [Indexed: 11/22/2023] Open
Abstract
The proteome characterization of complex, deteriorated, or cross-linked protein mixtures as paired clinical FFPE or exosome samples isolated from low plasma volumes (250 µL) might be a challenge. In this work, we aimed at investigating the benefits of FAIMS technology coupled to the Orbitrap Exploris 480 mass spectrometer for the TMT quantitative proteomics analyses of these complex samples in comparison to the analysis of protein extracts from cells, frozen tissue, and exosomes isolated from large volume plasma samples (3 mL). TMT experiments were performed using a two-hour gradient LC-MS/MS with or without FAIMS and two compensation voltages (CV = -45 and CV = -60). In the TMT experiments of cells, frozen tissue, or exosomes isolated from large plasma volumes (3 mL) with FAIMS, a limited increase in the number of identified and quantified proteins accompanied by a decrease in the number of peptides identified and quantified was observed. However, we demonstrated here a noticeable improvement (>100%) in the number of peptide and protein identifications and quantifications for the plasma exosomes isolated from low plasma volumes (250 µL) and FFPE tissue samples in TMT experiments with FAIMS in comparison to the LC-MS/MS analysis without FAIMS. Our results highlight the potential of mass spectrometry analyses with FAIMS to increase the depth into the proteome of complex samples derived from deteriorated, cross-linked samples and/or those where the material was scarce, such as FFPE and plasma-derived exosomes from low plasma volumes (250 µL), which might aid in the characterization of their proteome and proteoforms and in the identification of dysregulated proteins that could be used as biomarkers.
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Affiliation(s)
- Ana Montero-Calle
- Chronic Disease Programme (UFIEC), Instituto de Salud Carlos III, 28220 Majadahonda, Spain; (M.G.-A.); (R.R.-G.)
| | - María Garranzo-Asensio
- Chronic Disease Programme (UFIEC), Instituto de Salud Carlos III, 28220 Majadahonda, Spain; (M.G.-A.); (R.R.-G.)
| | - Raquel Rejas-González
- Chronic Disease Programme (UFIEC), Instituto de Salud Carlos III, 28220 Majadahonda, Spain; (M.G.-A.); (R.R.-G.)
| | - Jaime Feliu
- Translational Oncology Group, La Paz University Hospital (IdiPAZ), 28046 Madrid, Spain;
- Center for Biomedical Research in the Cancer Network (CIBERONC), Instituto de Salud Carlos III, 28046 Madrid, Spain;
| | - Marta Mendiola
- Center for Biomedical Research in the Cancer Network (CIBERONC), Instituto de Salud Carlos III, 28046 Madrid, Spain;
- Molecular Pathology and Therapeutic Targets Group, La Paz University Hospital (IdiPAZ), 28046 Madrid, Spain;
| | - Alberto Peláez-García
- Molecular Pathology and Therapeutic Targets Group, La Paz University Hospital (IdiPAZ), 28046 Madrid, Spain;
| | - Rodrigo Barderas
- Chronic Disease Programme (UFIEC), Instituto de Salud Carlos III, 28220 Majadahonda, Spain; (M.G.-A.); (R.R.-G.)
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11
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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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12
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Olanrewaju GO, Kruse CPS, Wyatt SE. Functional Meta-Analysis of the Proteomic Responses of Arabidopsis Seedlings to the Spaceflight Environment Reveals Multi-Dimensional Sources of Variability across Spaceflight Experiments. Int J Mol Sci 2023; 24:14425. [PMID: 37833871 PMCID: PMC10573023 DOI: 10.3390/ijms241914425] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/14/2023] [Accepted: 09/21/2023] [Indexed: 10/15/2023] Open
Abstract
The human quest for sustainable habitation of extraterrestrial environments necessitates a robust understanding of life's adaptability to the unique conditions of spaceflight. This study provides a comprehensive proteomic dissection of the Arabidopsis plant's responses to the spaceflight environment through a meta-analysis of proteomics data from four separate spaceflight experiments conducted on the International Space Station (ISS) in different hardware configurations. Raw proteomics LC/MS spectra were analyzed for differential expression in MaxQuant and Perseus software. The analysis of dissimilarities among the datasets reveals the multidimensional nature of plant proteomic responses to spaceflight, impacted by variables such as spaceflight hardware, seedling age, lighting conditions, and proteomic quantification techniques. By contrasting datasets that varied in light exposure, we elucidated proteins involved in photomorphogenesis and skotomorphogenesis in plant spaceflight responses. Additionally, with data from an onboard 1 g control experiment, we isolated proteins that specifically respond to the microgravity environment and those that respond to other spaceflight conditions. This study identified proteins and associated metabolic pathways that are consistently impacted across the datasets. Notably, these shared proteins were associated with critical metabolic functions, including carbon metabolism, glycolysis, gluconeogenesis, and amino acid biosynthesis, underscoring their potential significance in Arabidopsis' spaceflight adaptation mechanisms and informing strategies for successful space farming.
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Affiliation(s)
- Gbolaga O. Olanrewaju
- Molecular and Cellular Biology Program, Ohio University, Athens, OH 45701, USA;
- Department of Environmental and Plant Biology, Ohio University, Athens, OH 45701, USA
| | - Colin P. S. Kruse
- Los Alamos National Laboratory, Bioscience Division, Los Alamos, NM 87545, USA;
| | - Sarah E. Wyatt
- Molecular and Cellular Biology Program, Ohio University, Athens, OH 45701, USA;
- Department of Environmental and Plant Biology, Ohio University, Athens, OH 45701, USA
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13
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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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14
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Mota I, Patrucco E, Mastini C, Mahadevan NR, Thai TC, Bergaggio E, Cheong TC, Leonardi G, Karaca-Atabay E, Campisi M, Poggio T, Menotti M, Ambrogio C, Longo DL, Klaeger S, Keshishian H, Sztupinszki ZM, Szallasi Z, Keskin DB, Duke-Cohan JS, Reinhold B, Carr SA, Wu CJ, Moynihan KD, Irvine DJ, Barbie DA, Reinherz EL, Voena C, Awad MM, Blasco RB, Chiarle R. ALK peptide vaccination restores the immunogenicity of ALK-rearranged non-small cell lung cancer. NATURE CANCER 2023; 4:1016-1035. [PMID: 37430060 DOI: 10.1038/s43018-023-00591-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 06/07/2023] [Indexed: 07/12/2023]
Abstract
Anaplastic lymphoma kinase (ALK)-rearranged non-small cell lung cancer (NSCLC) is treated with ALK tyrosine kinase inhibitors (TKIs), but the lack of activity of immune checkpoint inhibitors (ICIs) is poorly understood. Here, we identified immunogenic ALK peptides to show that ICIs induced rejection of ALK+ tumors in the flank but not in the lung. A single-peptide vaccination restored priming of ALK-specific CD8+ T cells, eradicated lung tumors in combination with ALK TKIs and prevented metastatic dissemination of tumors to the brain. The poor response of ALK+ NSCLC to ICIs was due to ineffective CD8+ T cell priming against ALK antigens and is circumvented through specific vaccination. Finally, we identified human ALK peptides displayed by HLA-A*02:01 and HLA-B*07:02 molecules. These peptides were immunogenic in HLA-transgenic mice and were recognized by CD8+ T cells from individuals with NSCLC, paving the way for the development of a clinical vaccine to treat ALK+ NSCLC.
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Affiliation(s)
- Ines Mota
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA
| | - Enrico Patrucco
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Cristina Mastini
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Navin R Mahadevan
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Pathology, Brigham and Women's Hospital, Boston, MA, USA
| | - Tran C Thai
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Elisa Bergaggio
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA
| | - Taek-Chin Cheong
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA
| | - Giulia Leonardi
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA
| | | | - Marco Campisi
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Teresa Poggio
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Matteo Menotti
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Chiara Ambrogio
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Dario L Longo
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
- Molecular Imaging Center, University of Torino, Torino, Italy
- Institute of Biostructures and Bioimaging (IBB), National Research Council of Italy (CNR), Torino, Italy
| | - Susan Klaeger
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Zsófia M Sztupinszki
- Danish Cancer Society Research Center, Copenhagen, Denmark
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA
| | - Zoltan Szallasi
- Danish Cancer Society Research Center, Copenhagen, Denmark
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA
- Department of Bioinformatics, Semmelweis University, Budapest, Hungary
| | - Derin B Keskin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Translational Immunogenomics Laboratory, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Computer Science, Metropolitan College, Boston University, Boston, MA, USA
- Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Jonathan S Duke-Cohan
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Laboratory of Immunobiology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Bruce Reinhold
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Laboratory of Immunobiology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Steven A Carr
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Catherine J Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Kelly D Moynihan
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Darrell J Irvine
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - David A Barbie
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Ellis L Reinherz
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA
| | - Claudia Voena
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Mark M Awad
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Rafael B Blasco
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA.
| | - Roberto Chiarle
- Department of Pathology, Boston Children's Hospital, Boston, MA, USA.
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy.
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15
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Matzinger M, Mayer RL, Mechtler K. Label-free single cell proteomics utilizing ultrafast LC and MS instrumentation: A valuable complementary technique to multiplexing. Proteomics 2023; 23:e2200162. [PMID: 36806919 PMCID: PMC10909491 DOI: 10.1002/pmic.202200162] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 02/09/2023] [Accepted: 02/10/2023] [Indexed: 02/21/2023]
Abstract
The ability to map a proteomic fingerprint to transcriptomic data would master the understanding of how gene expression translates into actual phenotype. In contrast to nucleic acid sequencing, in vitro protein amplification is impossible and no single cell proteomic workflow has been established as gold standard yet. Advances in microfluidic sample preparation, multi-dimensional sample separation, sophisticated data acquisition strategies, and intelligent data analysis algorithms have resulted in major improvements to successfully analyze such tiny sample amounts with steadily boosted performance. However, among the broad variation of published approaches, it is commonly accepted that highest possible sensitivity, robustness, and throughput are still the most urgent needs for the field. While many labs have focused on multiplexing to achieve these goals, label-free SCP is a highly promising strategy as well whenever high dynamic range and unbiased accurate quantification are needed. We here focus on recent advances in label-free single-cell mass spectrometry workflows and try to guide our readers to choose the best method or combinations of methods for their specific applications. We further highlight which techniques are most propitious in the future and which applications but also limitations we foresee for the field.
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Affiliation(s)
- Manuel Matzinger
- Research Institute of Molecular Pathology (IMP)Vienna BioCenterViennaAustria
| | - Rupert L. Mayer
- Research Institute of Molecular Pathology (IMP)Vienna BioCenterViennaAustria
| | - Karl Mechtler
- Research Institute of Molecular Pathology (IMP)Vienna BioCenterViennaAustria
- Gregor Mendel Institute of Molecular Plant Biology (GMI), Austrian Academy of SciencesVienna BioCenter (VBC)ViennaAustria
- Institute of Molecular Biotechnology (IMBA), Austrian Academy of SciencesVienna BioCenter (VBC)ViennaAustria
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16
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Xu T, Wang Q, Wang Q, Sun L. Coupling High-Field Asymmetric Waveform Ion Mobility Spectrometry with Capillary Zone Electrophoresis-Tandem Mass Spectrometry for Top-Down Proteomics. Anal Chem 2023; 95:9497-9504. [PMID: 37254456 PMCID: PMC10540249 DOI: 10.1021/acs.analchem.3c00551] [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: 06/01/2023]
Abstract
Capillary zone electrophoresis-tandem mass spectrometry (CZE-MS/MS) has emerged as an essential technique for top-down proteomics (TDP), providing superior separation efficiency and high detection sensitivity for proteoform analysis. Here, we aimed to further enhance the performance of CZE-MS/MS for TDP via coupling online gas-phase proteoform fractionation using high-field asymmetric waveform ion mobility spectrometry (FAIMS). When the compensation voltage (CV) of FAIMS was changed from -50 to 30 V, the median mass of identified proteoforms increased from less than 10 kDa to about 30 kDa, suggesting that FAIMS can efficiently fractionate proteoforms by their size. CZE-FAIMS-MS/MS boosted the number of proteoform identifications from a yeast sample by nearly 3-fold relative to CZE-MS/MS alone. It particularly benefited the identification of relatively large proteoforms, improving the number of proteoforms in a mass range of 20-45 kDa by 6-fold compared to CZE-MS/MS alone. FAIMS fractionation gained nearly 20-fold better signal-to-noise ratios of randomly selected proteoforms than no FAIMS. We expect that CZE-FAIMS-MS/MS will be a useful tool for further advancing the sensitivity and coverage of TDP. This work shows the first example of coupling CE with ion mobility spectrometry (IMS) for TDP.
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Affiliation(s)
- Tian Xu
- Department of Chemistry, Michigan State University, 578 S Shaw Lane, East Lansing, Michigan 48824, United States
| | - Qianjie Wang
- Department of Chemistry, Michigan State University, 578 S Shaw Lane, East Lansing, Michigan 48824, United States
| | - Qianyi Wang
- 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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17
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Ai L, Binek A, Kreimer S, Ayres M, Stotland A, Van Eyk JE. High-Field Asymmetric Waveform Ion Mobility Spectrometry: Practical Alternative for Cardiac Proteome Sample Processing. J Proteome Res 2023; 22:2124-2130. [PMID: 37040897 PMCID: PMC10243111 DOI: 10.1021/acs.jproteome.3c00027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Indexed: 04/13/2023]
Abstract
Heart tissue sample preparation for mass spectrometry (MS) analysis that includes prefractionation reduces the cellular protein dynamic range and increases the relative abundance of nonsarcomeric proteins. We previously described "IN-Sequence" (IN-Seq) where heart tissue lysate is sequentially partitioned into three subcellular fractions to increase the proteome coverage more than a single direct tissue analysis by mass spectrometry. Here, we report an adaptation of the high-field asymmetric ion mobility spectrometry (FAIMS) coupled to mass spectrometry, and the establishment of a simple one step sample preparation coupled with gas-phase fractionation. The FAIMS approach substantially reduces manual sample handling, significantly shortens the MS instrument processing time, and produces unique protein identification and quantification approximating the commonly used IN-Seq method in less time.
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Affiliation(s)
- Lizhuo Ai
- Department
of Biomedical Sciences, Cedars-Sinai Medical
Center, Los Angeles, California 90048, United States
- Advanced
Clinical Biosystems Research Institute, Smidt Heart institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Aleksandra Binek
- Advanced
Clinical Biosystems Research Institute, Smidt Heart institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Simion Kreimer
- Advanced
Clinical Biosystems Research Institute, Smidt Heart institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Matthew Ayres
- Advanced
Clinical Biosystems Research Institute, Smidt Heart institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Aleksandr Stotland
- Advanced
Clinical Biosystems Research Institute, Smidt Heart institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
| | - Jennifer E. Van Eyk
- Department
of Biomedical Sciences, Cedars-Sinai Medical
Center, Los Angeles, California 90048, United States
- Advanced
Clinical Biosystems Research Institute, Smidt Heart institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, United States
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18
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Phaneuf CG, Aizikov K, Grinfeld D, Kreutzmann A, Mourad D, Lange O, Dai D, Zhang B, Belenky A, Makarov AA, Ivanov AR. Experimental strategies to improve drug-target identification in mass spectrometry-based thermal stability assays. Commun Chem 2023; 6:64. [PMID: 37024568 PMCID: PMC10079678 DOI: 10.1038/s42004-023-00861-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 03/23/2023] [Indexed: 04/08/2023] Open
Abstract
Mass spectrometry (MS)-based thermal stability assays have recently emerged as one of the most promising solutions for the identification of protein-ligand interactions. Here, we have investigated eight combinations of several recently introduced MS-based advancements, including the Phase-Constrained Spectral Deconvolution Method, Field Asymmetric Ion Mobility Spectrometry, and the implementation of a carrier sample as improved MS-based acquisition approaches for thermal stability assays (iMAATSA). We used intact Jurkat cells treated with a commercially available MEK inhibitor, followed by heat treatment, to prepare a set of unfractionated isobarically-labeled proof-of-concept samples to compare the performance of eight different iMAATSAs. Finally, the best-performing iMAATSA was compared to a conventional approach and evaluated in a fractionation experiment. Improvements of up to 82% and 86% were demonstrated in protein identifications and high-quality melting curves, respectively, over the conventional approach in the proof-of-concept study, while an approximately 12% improvement in melting curve comparisons was achieved in the fractionation experiment.
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Affiliation(s)
- Clifford G Phaneuf
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA
- Sanofi, Disease Profiling and Functional Genomics, Cambridge, MA, USA
| | | | | | | | | | | | - Daniel Dai
- Sanofi, Disease Profiling and Functional Genomics, Cambridge, MA, USA
| | - Bailin Zhang
- Sanofi, Disease Profiling and Functional Genomics, Cambridge, MA, USA
| | | | | | - Alexander R Ivanov
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA.
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19
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Aydoğan C, Beltekin B, Alharthi S, Ağca CA, Erdoğan İY. Nano-liquid chromatography with monolithic stationary phase based on naphthyl monomer for proteomics analysis. J Chromatogr A 2023; 1690:463804. [PMID: 36689803 DOI: 10.1016/j.chroma.2023.463804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 01/11/2023] [Accepted: 01/15/2023] [Indexed: 01/18/2023]
Abstract
Monolithic poly(2-vinylnaphthalene-co-divinylbenzene) columns were introduced, for the first time, and were evaluated as the separation media for nano-liquid chromatography (nano-LC). These columns were prepared by in-situ polymerization of 2-vinylnaphthalene (2-VNA) as the functional monomer and divinylbenzene (DVB) as the crosslinker in a fused silica capillary column of 50 µm i.d. Various porogenic solvents, including tetrahydrofuran (THF), dodecanol and toluene were used for morphology optimization. Final monolithic column (referred to as VNA column) was characterized by using scanning electron microscopy (SEM) and chromatographic analyses. Alkylbenzenes (ABs), and polyaromatic hydrocarbons (PAHs) were separated using the VNA column while the column offered excellent hydrophobic and π-π interactions under reversed-phase conditions. Theoretical plates number up to 41,200 plates/m in isocratic mode for ethylbenzene could be achieved. The potential of the final VNA column was demonstrated with a gradient elution in the separation of six intact proteins, including ribonuclease A (RNase A), cytochrome C (Cyt C), lysozyme (Lys), β-lactoglobulin (β-lac), myoglobin (My) and α-chymotrypsinogen (α-chym) in nano LC system. The column was then applied to the peptide analysis of trypsin digested cytochrome C, allowing a high peak capacity up to 1440 and the further proteomics analysis of COS-7 cell line was attempted applying the final monolithic column in nano-LC UV system.
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Affiliation(s)
- Cemil Aydoğan
- Food Analysis and Research Laboratory, Bingöl University, Bingöl, Türkiye; Department of Food Engineering, Bingöl University, Bingöl, Türkiye; Department of Chemistry, Bingöl University, Bingöl, Türkiye.
| | - Büşra Beltekin
- Food Analysis and Research Laboratory, Bingöl University, Bingöl, Türkiye
| | - Sarah Alharthi
- Department of Chemistry, College of Science, Taif University, P.O. Box 11099, Taif, 21944 Saudi Arabia
| | - Can Ali Ağca
- Department of Molecular Biology, Bingöl University, Bingöl, Türkiye
| | - İbrahim Y Erdoğan
- Department of Chemistry, Bingöl University, Bingöl, Türkiye; Faculty of Health Sciences, Bingöl University, Bingöl, Türkiye
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20
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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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21
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High-end ion mobility mass spectrometry: A current review of analytical capacity in omics applications and structural investigations. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116761] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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22
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Stejskal K, Jeff ODB, Matzinger M, Dürnberger G, Boychenko A, Jacobs P, Mechtler K. Deep Proteome Profiling with Reduced Carryover Using Superficially Porous Microfabricated nanoLC Columns. Anal Chem 2022; 94:15930-15938. [PMID: 36356180 PMCID: PMC9685595 DOI: 10.1021/acs.analchem.2c01196] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
![]()
In the field of liquid chromatography–mass spectrometry
(LC–MS)-based proteomics, increases in the sampling depth and
proteome coverage have mainly been accomplished by rapid advances
in mass spectrometer technology. The comprehensiveness and quality
of the data that can be generated do, however, also depend on the
performance provided by nano-liquid chromatography (nanoLC) separations.
Proper selection of reversed-phase separation columns can be important
to provide the MS instrument with peptides at the highest possible
concentration and separated at the highest possible resolution. In
the current contribution, we evaluate the use of the prototype generation
2 μPAC nanoLC columns, which use C18-functionalized superficially
porous micropillars as a stationary phase. When compared to traditionally
used fully porous silica stationary phases, more precursors could
be characterized when performing single shot data-dependent LC–MS/MS
analyses of a human cell line tryptic digest. Up to 30% more protein
groups and 60% more unique peptides were identified for short gradients
(10 min) and limited sample amounts (10–100 ng of cell lysate
digest). With LC–MS gradient times of 10, 60, 120, and 180
min, respectively, we identified 2252, 6513, 7382, and 8174 protein
groups with 25, 500, 1000, and 2000 ng of the sample loaded on the
column. Reduction of sample carryover to the next run (up to 2 to
3%) and decreased levels of methionine oxidation (up to 3-fold) were
identified as additional figures of merit. When analyzing a disuccinimidyl
dibutyric urea-crosslinked synthetic library, 29 to 59 more unique
crosslinked peptides could be identified at an experimentally validated
false discovery rate of 1–2%.
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Affiliation(s)
- Karel Stejskal
- IMBA─Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Dr. Bohr Gasse 3, A-1030 Vienna, Austria
| | - Op de Beeck Jeff
- Thermo Fisher Scientific, Technologiepark-Zwijnaarde 82, B-9052 Gent, Belgium
| | - Manuel Matzinger
- IMP─Institute of Molecular Pathology, Campus-Vienna-Biocenter 1, A-1030 Vienna, Austria
| | - Gerhard Dürnberger
- Gregor Mendel Institute of Molecular Plant Biology of the Austrian Academy of Sciences, Dr. Bohr Gasse 3, A-1030 Vienna, Austria
| | | | - Paul Jacobs
- Thermo Fisher Scientific, Technologiepark-Zwijnaarde 82, B-9052 Gent, Belgium
| | - 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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23
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Phlairaharn T, Grégoire S, Woltereck LR, Petrosius V, Furtwängler B, Searle BC, Schoof EM. High Sensitivity Limited Material Proteomics Empowered by Data-Independent Acquisition on Linear Ion Traps. J Proteome Res 2022; 21:2815-2826. [DOI: 10.1021/acs.jproteome.2c00376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Teeradon Phlairaharn
- 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
- Department of Chemistry, Technical University of Munich, Munich 80333, Germany
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby 2800, Denmark
- Pelotonia Institute for Immuno-Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio 43210, United States
| | - Samuel Grégoire
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby 2800, Denmark
- Computational Biology Unit, de Duve Institute, Université Catholique de Louvain, Brussels 1200, Belgium
| | - Lukas R. Woltereck
- Department of Chemistry, Technical University of Munich, Munich 80333, Germany
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby 2800, Denmark
| | - Valdemaras Petrosius
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby 2800, Denmark
| | - Benjamin Furtwängler
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby 2800, Denmark
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen 2200, Denmark
- Biotech Research and Innovation Center (BRIC), University of Copenhagen, Copenhagen 2200, Denmark
- Novo Nordisk Foundation Center for Stem Cell Biology, DanStem, Faculty of Health Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Brian C. Searle
- Pelotonia Institute for Immuno-Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio 43210, United States
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio 43210, United States
| | - Erwin M. Schoof
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby 2800, Denmark
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24
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Johnson KR, Gao Y, Greguš M, Ivanov AR. On-capillary Cell Lysis Enables Top-down Proteomic Analysis of Single Mammalian Cells by CE-MS/MS. Anal Chem 2022; 94:14358-14367. [PMID: 36194750 PMCID: PMC10118848 DOI: 10.1021/acs.analchem.2c03045] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Proteomic analysis of limited samples and single cells requires specialized methods that prioritize high sensitivity and minimize sample loss. Consequently, sample preparation is one of the most important steps in limited sample analysis workflows to prevent sample loss. In this work, we have eliminated sample handling and transfer steps by processing intact cells directly in the separation capillary, online with capillary electrophoresis coupled to tandem mass spectrometry (CE-MS/MS) for top-down proteomic (TDP) analysis of low numbers of mammalian cancer cells (<10) and single cells. We assessed spray voltage injection of intact cells from a droplet of cell suspension (∼1000 cells) and demonstrated 0-9 intact cells injected with a dependency on the duration of spray voltage application. Spray voltage applied for 2 min injected an average of 7 ± 2 cells and resulted in 33-57 protein and 40-88 proteoform identifications (N = 4). To analyze single cells, manual cell loading by hydrodynamic pressure was used. Replicates of single HeLa cells (N = 4) lysed on the capillary and analyzed by CE-MS/MS demonstrated a range of 17-40 proteins and 23-50 proteoforms identified. An additional cell line, THP-1, was analyzed at the single-cell level, and proteoform abundances were compared to show the capabilities of single-cell TDP (SC-TDP) for assessing cellular heterogeneity. This study demonstrates the initial application of TDP in single-cell proteome-level profiling. These results represent the highest reported identifications from TDP analysis of a single HeLa cell and prove the tremendous potential for CE-MS/MS on-capillary sample processing for high sensitivity analysis of single cells and limited samples.
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Affiliation(s)
- Kendall R Johnson
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
| | - Yunfan Gao
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
| | - Michal Greguš
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Avenue, 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 Avenue, Boston, Massachusetts 02115, United States
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25
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Johnson KR, Greguš M, Ivanov AR. Coupling High-Field Asymmetric Ion Mobility Spectrometry with Capillary Electrophoresis-Electrospray Ionization-Tandem Mass Spectrometry Improves Protein Identifications in Bottom-Up Proteomic Analysis of Low Nanogram Samples. J Proteome Res 2022; 21:2453-2461. [PMID: 36112031 PMCID: PMC10118849 DOI: 10.1021/acs.jproteome.2c00337] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
In this work, we pioneered the assessment of coupling high-field asymmetric waveform ion mobility spectrometry (FAIMS) with ultrasensitive capillary electrophoresis hyphenated with tandem mass spectrometry (CE-MS/MS) to achieve deeper proteome coverage of low nanogram amounts of digested cell lysates. An internal stepping strategy using three or four compensation voltages per analytical run with varied cycle times was tested to determine optimal FAIMS settings and MS parameters for the CE-FAIMS-MS/MS method. The optimized method applied to bottom-up proteomic analysis of 1 ng of HeLa protein digest standard identified 1314 ± 30 proteins, 4829 ± 200 peptide groups, and 7577 ± 163 peptide spectrum matches (PSMs) corresponding to a 16, 25, and 22% increase, respectively, over CE-MS/MS alone, without FAIMS. Furthermore, the percentage of acquired MS/MS spectra that resulted in PSMs increased nearly 2-fold with CE-FAIMS-MS/MS. Label-free quantitation of proteins and peptides was also assessed to determine the precision of replicate analyses from FAIMS methods with increased cycle times. Our results also identified from 1 ng of HeLa protein digest without any prior enrichment 76 ± 9 phosphopeptides, 18% of which were multiphosphorylated. These results represent a 46% increase in phosphopeptide identifications over the control experiments without FAIMS yielding 2.5-fold more multiphosphorylated peptides.
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Affiliation(s)
- Kendall R. Johnson
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Ave., Boston, Massachusetts 02115, United States
| | - 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
| | - 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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26
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A proteomic and RNA-seq transcriptomic dataset of capsaicin-aggravated mouse chronic colitis model. Sci Data 2022; 9:549. [PMID: 36071055 PMCID: PMC9452536 DOI: 10.1038/s41597-022-01637-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 08/11/2022] [Indexed: 11/08/2022] Open
Abstract
An inappropriate diet is a risk factor for inflammatory bowel disease (IBD). It is established that the consumption of spicy food containing capsaicin is strongly associated with the recurrence and worsening of IBD symptoms. Moreover, capsaicin can induce neutrophil accumulation in the lamina propria, contributing to disease deterioration. To uncover the potential signaling pathway involved in capsaicin-induced relapse and the effects of capsaicin on neutrophil activation, we performed proteomic analyses of intestinal tissues from chronic colitis mice following capsaicin administration and transcriptomic analyses of dHL-60 cells after capsaicin stimulation. Collectively, these multiomic analyses identified proteins and genes that may be involved in disease flares, thereby providing new insights for future research.
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27
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Zheng R, Stejskal K, Pynn C, Mechtler K, Boychenko A. Deep Single-Shot NanoLC-MS Proteome Profiling with a 1500 Bar UHPLC System, Long Fully Porous Columns, and HRAM MS. J Proteome Res 2022; 21:2545-2551. [PMID: 36068014 PMCID: PMC9552226 DOI: 10.1021/acs.jproteome.2c00270] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
![]()
This study demonstrates how the latest ultrahigh-performance
liquid
chromatography (UHPLC) technology can be combined with high-resolution
accurate-mass (HRAM) mass spectrometry (MS) and long columns packed
with fully porous particles to improve bottom-up proteomics analysis
with nanoflow liquid chromatography–mass spectrometry (nanoLC-MS)
methods. The increased back pressures from the UHPLC system enabled
the use of 75 μm I.D. × 75 cm columns packed with 2 μm
particles at a typical 300 nL/min flow rate as well as elevated and
reduced flow rates. The constant pressure pump operation at 1500 bar
reduced sample loading and column washing/equilibration stages and
overall overhead time, which maximizes MS utilization time. The versatility
of flow rate optimization to balance the sensitivity, throughput with
sample loading amount, and capability of using longer gradients contributes
to a greater number of peptide and protein identifications for single-shot
bottom-up proteomics experiments. The routine proteome profiling and
precise quantification of >7000 proteins with single-shot nanoLC-MS
analysis open possibilities for large-scale discovery studies with
a deep dive into the protein level alterations. Data are available
via ProteomeXchange with identifier PXD035665.
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Affiliation(s)
- Runsheng Zheng
- Thermo Fisher Scientific, Dornierstrasse 4, 82110 Germering, Germany
| | - Karel Stejskal
- 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
| | - Christopher Pynn
- Thermo Fisher Scientific, Dornierstrasse 4, 82110 Germering, Germany
| | - 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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28
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Gregus M, Zimmerman A, Marie AL, Johnson KR, Ivanov AR. Development of Highly Sensitive LC–MS and CE–MS Methods for In-Depth Proteomic and Glycomic Profiling of Limited Biological Samples. LCGC NORTH AMERICA 2022. [DOI: 10.56530/lcgc.na.ag4186o5] [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
nformative and deep proteomic and glycomic characterization of limited availability biological and medical samples has been a significant challenge. Here, we describe our current and recent efforts in advancing sample preparation as well as miniaturized electric field- and pressure-driven separation approaches interfaced with high-end mass spectrometry (MS) to enhance the sensitivity and depth of proteomic and glycomic profiling of several types of limited biological and clinically relevant samples.
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29
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Webber KGI, Truong T, Johnston SM, Zapata SE, Liang Y, Davis JM, Buttars AD, Smith FB, Jones HE, Mahoney AC, Carson RH, Nwosu AJ, Heninger JL, Liyu AV, Nordin GP, Zhu Y, Kelly RT. Label-Free Profiling of up to 200 Single-Cell Proteomes per Day Using a Dual-Column Nanoflow Liquid Chromatography Platform. Anal Chem 2022; 94:6017-6025. [PMID: 35385261 PMCID: PMC9356711 DOI: 10.1021/acs.analchem.2c00646] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Single-cell proteomics (SCP) has great potential to advance biomedical research and personalized medicine. The sensitivity of such measurements increases with low-flow separations (<100 nL/min) due to improved ionization efficiency, but the time required for sample loading, column washing, and regeneration in these systems can lead to low measurement throughput and inefficient utilization of the mass spectrometer. Herein, we developed a two-column liquid chromatography (LC) system that dramatically increases the throughput of label-free SCP using two parallel subsystems to multiplex sample loading, online desalting, analysis, and column regeneration. The integration of MS1-based feature matching increased proteome coverage when short LC gradients were used. The high-throughput LC system was reproducible between the columns, with a 4% difference in median peptide abundance and a median CV of 18% across 100 replicate analyses of a single-cell-sized peptide standard. An average of 621, 774, 952, and 1622 protein groups were identified with total analysis times of 7, 10, 15, and 30 min, corresponding to a measurement throughput of 206, 144, 96, and 48 samples per day, respectively. When applied to single HeLa cells, we identified nearly 1000 protein groups per cell using 30 min cycles and 660 protein groups per cell for 15 min cycles. We explored the possibility of measuring cancer therapeutic targets with a pilot study comparing the K562 and Jurkat leukemia cell lines. This work demonstrates the feasibility of high-throughput label-free single-cell proteomics.
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Affiliation(s)
- Kei G I Webber
- 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
| | - S Madisyn Johnston
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Sebastian E Zapata
- 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
| | - Jacob M Davis
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Alexander D Buttars
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Fletcher B Smith
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Hailey E Jones
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Arianna C Mahoney
- 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
| | - Andikan J Nwosu
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Jacob L Heninger
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Andrey V Liyu
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Gregory P Nordin
- Department of Electrical Engineering, 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.,Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
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30
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Aydoğan C, Erdoğan İY, El-Rassi Z. Hydrophobic AEROSIL®R972 Fumed Silica Nanoparticles Incorporated Monolithic Nano-Columns for Small Molecule and Protein Separation by Nano-Liquid Chromatography. Molecules 2022; 27:molecules27072306. [PMID: 35408705 PMCID: PMC9000833 DOI: 10.3390/molecules27072306] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 03/28/2022] [Accepted: 03/30/2022] [Indexed: 02/04/2023] Open
Abstract
A new feature of hydrophobic fumed silica nanoparticles (HFSNPs) when they apply to the preparation of monolithic nano-columns using narrow monolithic fused silica capillary columns (e.g., 50-µm inner diameter) was presented. The monolithic nano-columns were synthesized by an in-situ polymerization using butyl methacrylate (BMA) and ethylene dimethacrylate (EDMA) at various concentrations of AEROSIL®R972, called HFSNPs. Dimethyl formamide (DMF) and water were used as the porogenic solvents. These columns (referred to as HFSNP monoliths) were successfully characterized by using scanning electron microscopy (SEM) and reversed-phase nano-LC using alkylbenzenes and polyaromatic hydrocarbons as solute probes. The reproducibility values based on run-to-run, column-to-column and batch-to-batch were found as 2.3%, 2.48% and 2.99% (n = 3), respectively. The optimized column also indicated promising hydrophobic interactions under reversed-phase conditions, while the feasibility of the column allowed high efficiency and high throughput nano-LC separations. The potential of the final HFSNP monolith in relation to intact protein separation was successfully demonstrated using six intact proteins, including ribonuclease A, cytochrome C, carbonic anhydrase isozyme II, lysozyme, myoglobin, and α-chymotrypsinogen A in nano-LC. The results showed that HFSNP-based monolithic nanocolumns are promising materials and are powerful tools for sensitive separations.
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Affiliation(s)
- Cemil Aydoğan
- Food Analysis and Research Laboratory, Bingöl University, Bingöl 12000, Turkey
- Department of Chemistry, Bingöl University, Bingöl 12000, Turkey;
- Department of Food Engineering, Bingöl University, Bingöl 12000, Turkey
- Correspondence: ; Tel.: +90-426-216-19-58; Fax: +90-426-216-00-33
| | - İbrahim Y. Erdoğan
- Department of Chemistry, Bingöl University, Bingöl 12000, Turkey;
- Faculty of Health Sciences, Bingöl University, Bingöl 12000, Turkey
| | - Ziad El-Rassi
- Department of Chemistry, Oklahoma State University, Stillwater, OK 74078, USA;
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31
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Brunner A, Thielert M, Vasilopoulou C, Ammar C, Coscia F, Mund A, Hoerning OB, Bache N, Apalategui A, Lubeck M, Richter S, Fischer DS, Raether O, Park MA, Meier F, Theis FJ, Mann M. Ultra‐high sensitivity mass spectrometry quantifies single‐cell proteome changes upon perturbation. Mol Syst Biol 2022; 18:e10798. [PMID: 35226415 PMCID: PMC8884154 DOI: 10.15252/msb.202110798] [Citation(s) in RCA: 219] [Impact Index Per Article: 109.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 02/06/2022] [Accepted: 02/08/2022] [Indexed: 12/15/2022] Open
Abstract
Single‐cell technologies are revolutionizing biology but are today mainly limited to imaging and deep sequencing. However, proteins are the main drivers of cellular function and in‐depth characterization of individual cells by mass spectrometry (MS)‐based proteomics would thus be highly valuable and complementary. Here, we develop a robust workflow combining miniaturized sample preparation, very low flow‐rate chromatography, and a novel trapped ion mobility mass spectrometer, resulting in a more than 10‐fold improved sensitivity. We precisely and robustly quantify proteomes and their changes in single, FACS‐isolated cells. Arresting cells at defined stages of the cell cycle by drug treatment retrieves expected key regulators. Furthermore, it highlights potential novel ones and allows cell phase prediction. Comparing the variability in more than 430 single‐cell proteomes to transcriptome data revealed a stable‐core proteome despite perturbation, while the transcriptome appears stochastic. Our technology can readily be applied to ultra‐high sensitivity analyses of tissue material, posttranslational modifications, and small molecule studies from small cell counts to gain unprecedented insights into cellular heterogeneity in health and disease.
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Affiliation(s)
- Andreas‐David Brunner
- Proteomics and Signal Transduction Max‐Planck Institute of Biochemistry Martinsried Germany
| | - Marvin Thielert
- Proteomics and Signal Transduction Max‐Planck Institute of Biochemistry Martinsried Germany
| | - Catherine Vasilopoulou
- Proteomics and Signal Transduction Max‐Planck Institute of Biochemistry Martinsried Germany
| | - Constantin Ammar
- Proteomics and Signal Transduction Max‐Planck Institute of Biochemistry Martinsried Germany
| | - Fabian Coscia
- NNF Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark
| | - Andreas Mund
- NNF Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark
| | | | | | | | | | - Sabrina Richter
- Helmholtz Zentrum München – German Research Center for Environmental Health Institute of Computational Biology Neuherberg Germany
- TUM School of Life Sciences Weihenstephan Technical University of Munich Freising Germany
| | - David S Fischer
- Helmholtz Zentrum München – German Research Center for Environmental Health Institute of Computational Biology Neuherberg Germany
- TUM School of Life Sciences Weihenstephan Technical University of Munich Freising Germany
| | | | | | - Florian Meier
- Proteomics and Signal Transduction Max‐Planck Institute of Biochemistry Martinsried Germany
- Functional Proteomics Jena University Hospital Jena Germany
| | - Fabian J Theis
- Helmholtz Zentrum München – German Research Center for Environmental Health Institute of Computational Biology Neuherberg Germany
- TUM School of Life Sciences Weihenstephan Technical University of Munich Freising Germany
| | - Matthias Mann
- Proteomics and Signal Transduction Max‐Planck Institute of Biochemistry Martinsried Germany
- NNF Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark
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32
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Kruse ARS, Spraggins JM. Uncovering Molecular Heterogeneity in the Kidney With Spatially Targeted Mass Spectrometry. Front Physiol 2022; 13:837773. [PMID: 35222094 PMCID: PMC8874197 DOI: 10.3389/fphys.2022.837773] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 01/04/2022] [Indexed: 02/06/2023] Open
Abstract
The kidney functions through the coordination of approximately one million multifunctional nephrons in 3-dimensional space. Molecular understanding of the kidney has relied on transcriptomic, proteomic, and metabolomic analyses of kidney homogenate, but these approaches do not resolve cellular identity and spatial context. Mass spectrometry analysis of isolated cells retains cellular identity but not information regarding its cellular neighborhood and extracellular matrix. Spatially targeted mass spectrometry is uniquely suited to molecularly characterize kidney tissue while retaining in situ cellular context. This review summarizes advances in methodology and technology for spatially targeted mass spectrometry analysis of kidney tissue. Profiling technologies such as laser capture microdissection (LCM) coupled to liquid chromatography tandem mass spectrometry provide deep molecular coverage of specific tissue regions, while imaging technologies such as matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) molecularly profile regularly spaced tissue regions with greater spatial resolution. These technologies individually have furthered our understanding of heterogeneity in nephron regions such as glomeruli and proximal tubules, and their combination is expected to profoundly expand our knowledge of the kidney in health and disease.
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Affiliation(s)
- Angela R. S. Kruse
- Department of Biochemistry, Vanderbilt University, Nashville, TN, United States
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, United States
| | - Jeffrey M. Spraggins
- Department of Biochemistry, Vanderbilt University, Nashville, TN, United States
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, United States
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, United States
- Department of Chemistry, Vanderbilt University, Nashville, TN, United States
- *Correspondence: Jeffrey M. Spraggins,
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33
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Clark NM, Elmore JM, Walley JW. To the proteome and beyond: advances in single-cell omics profiling for plant systems. PLANT PHYSIOLOGY 2022; 188:726-737. [PMID: 35235661 PMCID: PMC8825333 DOI: 10.1093/plphys/kiab429] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 08/16/2021] [Indexed: 05/19/2023]
Abstract
Recent advances in single-cell proteomics for animal systems could be adapted for plants to increase our understanding of plant development, response to stimuli, and cell-to-cell signaling.
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Affiliation(s)
- Natalie M Clark
- Department of Plant Pathology and Microbiology, Iowa State University, Ames, Iowa 50011, USA
| | - James Mitch Elmore
- Department of Plant Pathology and Microbiology, Iowa State University, Ames, Iowa 50011, USA
| | - Justin W Walley
- Department of Plant Pathology and Microbiology, Iowa State University, Ames, Iowa 50011, USA
- Author for communication:
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34
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Johnson KR, Greguš M, Kostas JC, Ivanov AR. Capillary Electrophoresis Coupled to Electrospray Ionization Tandem Mass Spectrometry for Ultra-Sensitive Proteomic Analysis of Limited Samples. Anal Chem 2022; 94:704-713. [PMID: 34983182 PMCID: PMC8770592 DOI: 10.1021/acs.analchem.1c02929] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
In this work, we developed an ultra-sensitive CE-MS/MS method for bottom-up proteomics analysis of limited samples, down to sub-nanogram levels of total protein. Analysis of 880 and 88 pg of the HeLa protein digest standard by CE-MS/MS yielded ∼1100 ± 46 and ∼160 ± 59 proteins, respectively, demonstrating higher protein and peptide identifications than the current state-of-the-art CE-MS/MS-based proteomic analyses with similar amounts of sample. To demonstrate potential applications of our ultra-sensitive CE-MS/MS method for the analysis of limited biological samples, we digested 500 and 1000 HeLa cells using a miniaturized in-solution digestion workflow. From 1-, 5-, and 10-cell equivalents injected from the resulted digests, we identified 744 ± 127, 1139 ± 24, and 1271 ± 6 proteins and 3353 ± 719, 5709 ± 513, and 8527 ± 114 peptide groups, respectively. Furthermore, we performed a comparative assessment of CE-MS/MS and two reversed-phased nano-liquid chromatography (RP-nLC-MS/MS) methods (monolithic and packed columns) for the analysis of a ∼10 ng HeLa protein digest standard. Our results demonstrate complementarity in the protein- and especially peptide-level identifications of the evaluated CE-MS- and RP-nLC-MS-based methods. The techniques were further assessed to detect post-translational modifications and highlight the strengths of the CE-MS/MS approach in identifying potentially important and biologically relevant modified peptides. With a migration window of ∼60 min, CE-MS/MS identified ∼2000 ± 53 proteins on average from a single injection of ∼8.8 ng of the HeLa protein digest standard. Additionally, an average of 232 ± 10 phosphopeptides and 377 ± 14 N-terminal acetylated peptides were identified in CE-MS/MS analyses at this sample amount, corresponding to 2- and 1.5-fold more identifications for each respective modification found by nLC-MS/MS methods.
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Affiliation(s)
- Kendall R Johnson
- Department of Chemistry and Chemical Biology, Northeastern University, Barnett Institute of Chemical and Biological Analysis, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
| | - Michal Greguš
- Department of Chemistry and Chemical Biology, Northeastern University, Barnett Institute of Chemical and Biological Analysis, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
| | - James C Kostas
- Department of Chemistry and Chemical Biology, Northeastern University, Barnett Institute of Chemical and Biological Analysis, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
| | - Alexander R Ivanov
- Department of Chemistry and Chemical Biology, Northeastern University, Barnett Institute of Chemical and Biological Analysis, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
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35
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Siyal AA, Chen ESW, Chan HJ, Kitata RB, Yang JC, Tu HL, Chen YJ. Sample Size-Comparable Spectral Library Enhances Data-Independent Acquisition-Based Proteome Coverage of Low-Input Cells. Anal Chem 2021; 93:17003-17011. [PMID: 34904835 DOI: 10.1021/acs.analchem.1c03477] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Despite advancements of data-independent acquisition mass spectrometry (DIA-MS) to provide comprehensive and reproducible proteome profiling, its utility in very low-input samples is limited. Due to different proteome complexities and corresponding peptide ion abundances, the conventional LC-MS/MS acquisition and widely used large-scale DIA libraries may not be suitable for the micro-nanogram samples. In this study, we report a sample size-comparable library-based DIA approach to enhance the proteome coverage of low-input nanoscale samples (i.e., nanogram cells, ∼5-50 cells). By constructing sample size-comparable libraries, 2380 and 3586 protein groups were identified from as low as 0.75 (∼5 cells) and 1.5 ng (∼10 cells), respectively, highlighting one of the highest proteome coverage with good reproducibility (86%-99% in triplicate results). For the 0.75 ng sample (∼5 cells), significantly superior identification (2380 proteins) was achieved by small-size library-based DIA, compared to 1908, 1749, and 107 proteins identified from medium-size and large-size libraries and a lung cancer resource spectral library, respectively. A similar trend was observed using a different instrument and data analysis pipeline, indicating the generalized conclusion of the approach. Furthermore, the small-size library uniquely identified 518 (22%) proteins in the low-abundant region and spans over a 5-order dynamic range. Spectral similarity analysis revealed that the fragmentation ion pattern in the DIA-MS/MS spectra of the dataset and spectral library play crucial roles for mapping low abundant proteins. With these spectral libraries made freely available, the optimized library-based DIA strategy and DIA digital map will advance quantitative proteomics applications for mass-limited samples.
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Affiliation(s)
- Asad Ali Siyal
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan.,Department of Chemistry, National Tsing Hua University, Hsinchu 300, Taiwan
| | - Eric Sheng-Wen Chen
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Research Center for Cancer Biology, China Medical University, Taichung 40402, Taiwan
| | - Hsin-Ju Chan
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Department of Chemistry, National Taiwan University, Taipei 106, Taiwan
| | | | - Jhih-Ci Yang
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei 11529, Taiwan.,Department of Applied Chemistry, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | - Hsiung-Lin Tu
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan.,Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 115, Taiwan.,Department of Chemistry, National Taiwan University, Taipei 106, Taiwan.,Sustainable Chemical Science and Technology, Taiwan International Graduate Program, Academia Sinica and National Yang Ming Chiao Tung University, Taipei 11529, Taiwan
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36
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Røberg-Larsen H, Lundanes E, Nyman TA, Berven FS, Wilson SR. Liquid chromatography, a key tool for the advancement of single-cell omics analysis. Anal Chim Acta 2021; 1178:338551. [PMID: 34482862 DOI: 10.1016/j.aca.2021.338551] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 04/16/2021] [Accepted: 04/17/2021] [Indexed: 11/28/2022]
Abstract
Single-cell analysis can allow for an in-depth understanding of diseases, diagnostics, and aid the development of therapeutics. However, single-cell analysis is challenging, as samples are both extremely limited in size and complex. But the concept is gaining promise, much due to novel sample preparation approaches and the ever-improving field of mass spectrometry. The mass spectrometer's output is often linked to the preceding compound separation step, typically being liquid chromatography (LC). In this review, we focus on LC's role in single-cell omics. Particle-packed nano LC columns (typically 50-100 μm inner diameter) have traditionally been the tool of choice for limited samples, and are also used for single cells. Several commercial products and systems are emerging with single cells in mind, featuring particle-packed columns or miniaturized pillar array systems. In addition, columns with inner diameters as narrow as 2 μm are being explored to maximize sensitivity. Hence, LC column down-scaling is a key focus in single-cell analysis. But narrow columns are associated with considerable technical challenges, while single cell analysis may be expected to become a "routine" service, requiring higher degrees of robustness and throughput. These challenges and expectations will increase the need and attention for the development (and even the reinvention) of alternative nano LC column formats. Therefore, monolith columns and even open tubular columns may finally find their "killer-application" in single cell analysis.
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Affiliation(s)
| | - Elsa Lundanes
- Department of Chemistry, University of Oslo, Oslo, Norway
| | - Tuula A Nyman
- Department of Immunology, Institute of Clinical Medicine, University of Oslo and Oslo University Hospital, Norway
| | - Frode S Berven
- Department of Biomedicine, Proteomics Unit, University of Bergen, Bergen, Norway
| | - Steven Ray Wilson
- Department of Chemistry, University of Oslo, Oslo, Norway; Hybrid Technology Hub-Centre of Excellence, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo, Oslo, Norway.
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37
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Günyel Z, Aslan H, Demir N, Aydoğan C. Nano-liquid chromatography with a new nano-structured monolithic nanocolumn for proteomics analysis. J Sep Sci 2021; 44:3996-4004. [PMID: 34499809 DOI: 10.1002/jssc.202100454] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 09/01/2021] [Accepted: 09/01/2021] [Indexed: 12/19/2022]
Abstract
Herein, we report the preparation and application of a new nano-structured monolithic nanocolumn based on modified graphene oxide using narrow fused silica capillary column (e.g., 50 μm internal diameter). The nanocolumn was prepared by an in situ polymerization using butyl methacrylate, ethylene dimethacrylate, and methacryloyl graphene oxide nanoparticles. Dimethyl formamide and water were used as the porogenic solvent. After polymerization, the obtained nanocolumn was coated with dimethyloctadecylchlorosilane in order to enhance the hydrophobicity. Both isocratic and gradient nano-liquid chromatographic separations for small molecules (e.g., alkylbenzenes) and macromolecules (e.g., intact proteins) were performed. Theoretical plates number up to 3600 plates/m in isocratic mode for propylbenzene were achieved. It was demonstrated that the feasibility of graphene oxide modified monolithic nanocolumn for high-efficiency and high-throughput nanoscale proteomics analysis. The high resolving power of monolithic nanocolumn yielded sensitive protein separation with narrower peak width while a high-resolution analysis of peptides from trypsin-digested cytochrome C could be obtained. Graphene oxide based monolithic nanocolumns are promising and can allow to powerful tools for trace proteom sample analysis.
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Affiliation(s)
- Zeynep Günyel
- Food Analysis and Research Laboratory, Bingöl University, Bingöl, Turkey
| | - Hakiye Aslan
- Food Analysis and Research Laboratory, Bingöl University, Bingöl, Turkey
| | - Nurullah Demir
- Food Analysis and Research Laboratory, Bingöl University, Bingöl, Turkey
| | - Cemil Aydoğan
- Food Analysis and Research Laboratory, Bingöl University, Bingöl, Turkey.,Department of Chemistry, Bingöl University, Bingöl, Turkey.,Department of Food Engineering, Bingöl University, Bingöl, Turkey
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38
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Martin K, Zhang T, Lin TT, Habowski AN, Zhao R, Tsai CF, Chrisler WB, Sontag RL, Orton DJ, Lu YJ, Rodland KD, Yang B, Liu T, Smith RD, Qian WJ, Waterman ML, Wiley HS, Shi T. Facile One-Pot Nanoproteomics for Label-Free Proteome Profiling of 50-1000 Mammalian Cells. J Proteome Res 2021; 20:4452-4461. [PMID: 34351778 PMCID: PMC8945255 DOI: 10.1021/acs.jproteome.1c00403] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Recent advances in sample preparation enable label-free mass spectrometry (MS)-based proteome profiling of small numbers of mammalian cells. However, specific devices are often required to downscale sample processing volume from the standard 50-200 μL to sub-μL for effective nanoproteomics, which greatly impedes the implementation of current nanoproteomics methods by the proteomics research community. Herein, we report a facile one-pot nanoproteomics method termed SOPs-MS (surfactant-assisted one-pot sample processing at the standard volume coupled with MS) for convenient robust proteome profiling of 50-1000 mammalian cells. Building upon our recent development of SOPs-MS for label-free single-cell proteomics at a low μL volume, we have systematically evaluated its processing volume at 10-200 μL using 100 human cells. The processing volume of 50 μL that is in the range of volume for standard proteomics sample preparation has been selected for easy sample handling with a benchtop micropipette. SOPs-MS allows for reliable label-free quantification of ∼1200-2700 protein groups from 50 to 1000 MCF10A cells. When applied to small subpopulations of mouse colon crypt cells, SOPs-MS has revealed protein signatures between distinct subpopulation cells with identification of ∼1500-2500 protein groups for each subpopulation. SOPs-MS may pave the way for routine deep proteome profiling of small numbers of cells and low-input samples.
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Affiliation(s)
| | | | - Tai-Tu Lin
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Amber N. Habowski
- Department of Microbiology and Molecular Genetics, University of California Irvine, Irvine, California 92697, United States
| | - Rui Zhao
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Chia-Feng Tsai
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - William B. Chrisler
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Ryan L. Sontag
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Daniel J. Orton
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Yong-Jie Lu
- Centre for Cancer Biomarker and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, United Kingdom
| | - Karin D. Rodland
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Bin Yang
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States; Bioproducts, Sciences & Engineering Laboratory, Department of Biological Systems Engineering, Washington State University, Richland, Washington 99354, United States
| | - Tao Liu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Richard D. Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Marian L. Waterman
- Department of Microbiology and Molecular Genetics, University of California Irvine, Irvine, California 92697, United States
| | - H. Steven Wiley
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Tujin Shi
- Corresponding Author Tujin Shi – Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States; Phone: (509) 371-6579;
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39
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Thakur A, Tan Z, Kameyama T, El-Khateeb E, Nagpal S, Malone S, Jamwal R, Nwabufo CK. Bioanalytical strategies in drug discovery and development. Drug Metab Rev 2021; 53:434-458. [PMID: 34310243 DOI: 10.1080/03602532.2021.1959606] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
A reliable, rapid, and effective bioanalytical method is essential for the determination of the pharmacokinetic, pharmacodynamic, and toxicokinetic parameters that inform the safety and efficacy profile of investigational drugs. The overall goal of bioanalytical method development is to elucidate the procedure and operating conditions under which a method can sufficiently extract, qualify, and/or quantify the analyte(s) of interest and/or their metabolites for the intended purpose. Given the difference in the physicochemical properties of small and large molecule drugs, different strategies need to be adopted for the development of an effective and efficient bioanalytical method. Herein, we provide an overview of different sample preparation strategies, analytical platforms, as well as procedures for achieving high throughput for bioanalysis of small and large molecule drugs.
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Affiliation(s)
- Aarzoo Thakur
- Innovations in Food and Chemical Safety, Agency for Science, Technology, and Research, Singapore, Singapore.,Skin Research Institute of Singapore, Agency for Science, Technology, and Research, Singapore, Singapore
| | - Zhiyuan Tan
- Department of Early Clinical Development, dMed-Clinipace, Shanghai, China
| | - Tsubasa Kameyama
- Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Eman El-Khateeb
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK.,Clinical Pharmacy Department, Faculty of Pharmacy, Tanta University, Tanta, Egypt
| | - Shakti Nagpal
- Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore, Singapore
| | | | - Rohitash Jamwal
- College of Pharmacy, University of Rhode Island, Kingston, RI, USA
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40
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Stejskal K, Op de Beeck J, Dürnberger G, Jacobs P, Mechtler K. Ultrasensitive NanoLC-MS of Subnanogram Protein Samples Using Second Generation Micropillar Array LC Technology with Orbitrap Exploris 480 and FAIMS PRO. Anal Chem 2021; 93:8704-8710. [PMID: 34137250 PMCID: PMC8253486 DOI: 10.1021/acs.analchem.1c00990] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 06/03/2021] [Indexed: 12/14/2022]
Abstract
In the light of the ongoing single-cell revolution, scientific disciplines are combining forces to retrieve as much relevant data as possible from trace amounts of biological material. For single-cell proteomics, this implies optimizing the entire workflow from initial cell isolation down to sample preparation, liquid chromatography (LC) separation, mass spectrometer (MS) data acquisition, and data analysis. To demonstrate the potential for single-cell and limited sample proteomics, we report on a series of benchmarking experiments where we combine LC separation on a new generation of micropillar array columns with state-of-the-art Orbitrap MS/MS detection and high-field asymmetric waveform ion mobility spectrometry (FAIMS). This dedicated limited sample column has a reduced cross section and micropillar dimensions that have been further downscaled (interpillar distance and pillar diameter by a factor of 2), resulting in improved chromatography at reduced void times. A dilution series of a HeLa tryptic digest (5-0.05 ng/μL) was used to explore the sensitivity that can be achieved. Comparative processing of the MS/MS data with Sequest HT, MS Amanda, Mascot, and SpectroMine pointed out the benefits of using Sequest HT together with INFERYS when analyzing sample amounts below 1 ng. Here, 2855 protein groups were identified from just 1 ng of HeLa tryptic digest hereby increasing detection sensitivity as compared to a previous contribution by a factor well above 10. By successfully identifying 1486 protein groups from as little as 250 pg of HeLa tryptic digest, we demonstrate outstanding sensitivity with great promise for use in limited sample proteomics workflows.
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Affiliation(s)
- Karel Stejskal
- IMBA
- Institute of Molecular Biotechnology of the Austrian Academy of
Sciences, Dr. Bohr Gasse
3, A-1030 Vienna, Austria
- IMP
- Institute of Molecular Pathology, Campus-Vienna-Biocenter 1, 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
| | - Jeff Op de Beeck
- PharmaFluidics, Technologiepark-Zwijnaarde 82, B-9052 Gent, Belgium
| | - Gerhard Dürnberger
- IMBA
- Institute of Molecular Biotechnology of the Austrian Academy of
Sciences, Dr. Bohr Gasse
3, A-1030 Vienna, Austria
- IMP
- Institute of Molecular Pathology, Campus-Vienna-Biocenter 1, 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
| | - Paul Jacobs
- PharmaFluidics, Technologiepark-Zwijnaarde 82, B-9052 Gent, Belgium
| | - Karl Mechtler
- IMBA
- Institute of Molecular Biotechnology of the Austrian Academy of
Sciences, Dr. Bohr Gasse
3, A-1030 Vienna, Austria
- IMP
- Institute of Molecular Pathology, Campus-Vienna-Biocenter 1, 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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41
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Bian Y, The M, Giansanti P, Mergner J, Zheng R, Wilhelm M, Boychenko A, Kuster B. Identification of 7 000-9 000 Proteins from Cell Lines and Tissues by Single-Shot Microflow LC-MS/MS. Anal Chem 2021; 93:8687-8692. [PMID: 34124897 DOI: 10.1021/acs.analchem.1c00738] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
A current trend in proteomics is to acquire data in a "single-shot" by LC-MS/MS because it simplifies workflows and promises better throughput and quantitative accuracy than schemes that involve extensive sample fractionation. However, single-shot approaches can suffer from limited proteome coverage when performed by data dependent acquisition (ssDDA) on nanoflow LC systems. For applications where sample quantities are not scarce, this study shows that high proteome coverage can be obtained using a microflow LC-MS/MS system operating a 1 mm i.d. × 150 mm column, at a flow-rate of 50 μL/min and coupled to an Orbitrap HF-X mass spectrometer. The results demonstrate the identification of ∼9 000 proteins from 50 μg of protein digest from Arabidopsis roots, 7 500 from mouse thymus, and 7 300 from human breast cancer cells in 3 h of analysis time in a single run. The dynamic range of protein quantification measured by the iBAQ approach spanned 5 orders of magnitude and replicate analysis showed that the median coefficient of variation was below 20%. Together, this study shows that ssDDA by μLC-MS/MS is a robust method for comprehensive and large-scale proteome analysis and which may be further extended to more rapid chromatography and data independent acquisition approaches in the future.̀.
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Affiliation(s)
- Yangyang Bian
- College of Life Science, Northwest University, Taibai North Road 229, Xi'an, Shaanxi 710069, P. R. China.,Chair of Proteomics and Bioanalytics, Technical University of Munich, Emil Erlenmeyer Forum 5, 85354 Freising, Germany
| | - Matthew The
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Emil Erlenmeyer Forum 5, 85354 Freising, Germany
| | - Piero Giansanti
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Emil Erlenmeyer Forum 5, 85354 Freising, Germany
| | - Julia Mergner
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Emil Erlenmeyer Forum 5, 85354 Freising, Germany
| | - Runsheng Zheng
- Thermo Fisher Scientific, Dornierstraße 4, 82110 Germering, Germany
| | - Mathias Wilhelm
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Emil Erlenmeyer Forum 5, 85354 Freising, Germany
| | | | - Bernhard Kuster
- Chair of Proteomics and Bioanalytics, Technical University of Munich, Emil Erlenmeyer Forum 5, 85354 Freising, Germany.,Bavarian Biomolecular Mass Spectrometry Center (BayBioMS), Technical University of Munich, Gregor-Mendel-Straße 4, 85354 Freising, Germany
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42
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Kostas JC, Greguš M, Schejbal J, Ray S, Ivanov AR. Simple and Efficient Microsolid-Phase Extraction Tip-Based Sample Preparation Workflow to Enable Sensitive Proteomic Profiling of Limited Samples (200 to 10,000 Cells). J Proteome Res 2021; 20:1676-1688. [PMID: 33625864 PMCID: PMC7954648 DOI: 10.1021/acs.jproteome.0c00890] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
In-depth LC-MS-based proteomic profiling of limited biological and clinical samples, such as rare cells or tissue sections from laser capture microdissection or microneedle biopsies, has been problematic due, in large, to the inefficiency of sample preparation and attendant sample losses. To address this issue, we developed on-microsolid-phase extraction tip (OmSET)-based sample preparation for limited biological samples. OmSET is simple, efficient, reproducible, and scalable and is a widely accessible method for processing ∼200 to 10,000 cells. The developed method benefits from minimal sample processing volumes (1-3 μL) and conducting all sample processing steps on-membrane within a single microreactor. We first assessed the feasibility of using micro-SPE tips for nanogram-level amounts of tryptic peptides, minimized the number of required sample handling steps, and reduced the hands-on time. We then evaluated the capability of OmSET for quantitative analysis of low numbers of human monocytes. Reliable and reproducible label-free quantitation results were obtained with excellent correlations between protein abundances and the amounts of starting material (R2 = 0.93) and pairwise correlations between sample processing replicates (R2 = 0.95) along with the identification of approximately 300, 1800, and 2000 protein groups from injected ∼10, 100, and 500 cell equivalents, resulting from processing approximately 200, 2000, and 10,000 cells, respectively.
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Affiliation(s)
- James C Kostas
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
| | - Michal Greguš
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
| | - Jan Schejbal
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts 02115, United States
| | - Somak Ray
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Avenue, 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 Avenue, Boston, Massachusetts 02115, United States
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43
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Liang Y, Acor H, McCown MA, Nwosu AJ, Boekweg H, Axtell NB, Truong T, Cong Y, Payne SH, Kelly RT. Fully Automated Sample Processing and Analysis Workflow for Low-Input Proteome Profiling. Anal Chem 2021; 93:1658-1666. [PMID: 33352054 PMCID: PMC8140400 DOI: 10.1021/acs.analchem.0c04240] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Recent advances in sample preparation and analysis have enabled direct profiling of protein expression in single mammalian cells and other trace samples. Several techniques to prepare and analyze low-input samples employ custom fluidics for nanoliter sample processing and manual sample injection onto a specialized separation column. While being effective, these highly specialized systems require significant expertise to fabricate and operate, which has greatly limited implementation in most proteomic laboratories. Here, we report a fully automated platform termed autoPOTS (automated preparation in one pot for trace samples) that uses only commercially available instrumentation for sample processing and analysis. An unmodified, low-cost commercial robotic pipetting platform was utilized for one-pot sample preparation. We used low-volume 384-well plates and periodically added water or buffer to the microwells to compensate for limited evaporation during sample incubation. Prepared samples were analyzed directly from the well plate with a commercial autosampler that was modified with a 10-port valve for compatibility with 30 μm i.d. nanoLC columns. We used autoPOTS to analyze 1-500 HeLa cells and observed only a moderate reduction in peptide coverage for 150 cells and a 24% reduction in coverage for single cells compared to our previously developed nanoPOTS platform. To evaluate clinical feasibility, we identified an average of 1095 protein groups from ∼130 sorted B or T lymphocytes. We anticipate that the straightforward implementation of autoPOTS will make it an attractive option for low-input and single-cell proteomics in many laboratories.
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Affiliation(s)
- Yiran Liang
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Hayden Acor
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Michaela A McCown
- Department of Biology, Brigham Young University, Provo, Utah 84602, United States
| | - Andikan J Nwosu
- 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
| | - Nathaniel B Axtell
- 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
| | - Yongzheng Cong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Samuel H Payne
- Department of Biology, 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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