1
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Veličković M, Fillmore TL, Attah IK, Posso C, Pino JC, Zhao R, Williams SM, Veličković D, Jacobs JM, Burnum-Johnson KE, Zhu Y, Piehowski PD. Coupling Microdroplet-Based Sample Preparation, Multiplexed Isobaric Labeling, and Nanoflow Peptide Fractionation for Deep Proteome Profiling of the Tissue Microenvironment. Anal Chem 2024. [PMID: 39089681 DOI: 10.1021/acs.analchem.4c00523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity in a cell-type-specific manner to better understand and predict the function of complex biological systems such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverage due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (microdroplet processing in one pot for trace samples), multiplexed isobaric labeling, and a nanoflow peptide fractionation approach. The integrated workflow allowed us to maximize proteome coverage of laser-isolated tissue samples containing nanogram levels of proteins. We demonstrated that the deep spatial proteomics platform can quantify more than 5000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 μm2) and differentiate unique protein abundance patterns in pancreas. Furthermore, the use of the microPOTS chip eliminated the requirement for advanced microfabrication capabilities and specialized nanoliter liquid handling equipment, making it more accessible to proteomic laboratories.
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Affiliation(s)
- Marija Veličković
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Thomas L Fillmore
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Isaac Kwame Attah
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Camilo Posso
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - James C Pino
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Rui Zhao
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Sarah M Williams
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Dušan Veličković
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Jon M Jacobs
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Kristin E Burnum-Johnson
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Ying Zhu
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Paul D Piehowski
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
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2
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Oliinyk D, Will A, Schneidmadel FR, Böhme M, Rinke J, Hochhaus A, Ernst T, Hahn N, Geis C, Lubeck M, Raether O, Humphrey SJ, Meier F. µPhos: a scalable and sensitive platform for high-dimensional phosphoproteomics. Mol Syst Biol 2024; 20:972-995. [PMID: 38907068 PMCID: PMC11297287 DOI: 10.1038/s44320-024-00050-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 06/06/2024] [Accepted: 06/11/2024] [Indexed: 06/23/2024] Open
Abstract
Mass spectrometry has revolutionized cell signaling research by vastly simplifying the analysis of many thousands of phosphorylation sites in the human proteome. Defining the cellular response to perturbations is crucial for further illuminating the functionality of the phosphoproteome. Here we describe µPhos ('microPhos'), an accessible phosphoproteomics platform that permits phosphopeptide enrichment from 96-well cell culture and small tissue amounts in <8 h total processing time. By greatly minimizing transfer steps and liquid volumes, we demonstrate increased sensitivity, >90% selectivity, and excellent quantitative reproducibility. Employing highly sensitive trapped ion mobility mass spectrometry, we quantify ~17,000 Class I phosphosites in a human cancer cell line using 20 µg starting material, and confidently localize ~6200 phosphosites from 1 µg. This depth covers key signaling pathways, rendering sample-limited applications and perturbation experiments with hundreds of samples viable. We employ µPhos to study drug- and time-dependent response signatures in a leukemia cell line, and by quantifying 30,000 Class I phosphosites in the mouse brain we reveal distinct spatial kinase activities in subregions of the hippocampal formation.
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Affiliation(s)
- Denys Oliinyk
- Functional Proteomics, Jena University Hospital, 07747, Jena, Germany
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
| | - Andreas Will
- Functional Proteomics, Jena University Hospital, 07747, Jena, Germany
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
| | - Felix R Schneidmadel
- Functional Proteomics, Jena University Hospital, 07747, Jena, Germany
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
| | - Maximilian Böhme
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
- Klinik für Innere Medizin II, Jena University Hospital, 07747, Jena, Germany
| | - Jenny Rinke
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
- Klinik für Innere Medizin II, Jena University Hospital, 07747, Jena, Germany
| | - Andreas Hochhaus
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
- Klinik für Innere Medizin II, Jena University Hospital, 07747, Jena, Germany
| | - Thomas Ernst
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany
- Klinik für Innere Medizin II, Jena University Hospital, 07747, Jena, Germany
| | - Nina Hahn
- Section of Translational Neuroimmunology, Department of Neurology, Jena University Hospital, 07747, Jena, Germany
- Center for Sepsis Control and Care, Jena University Hospital, 07747, Jena, Germany
| | - Christian Geis
- Section of Translational Neuroimmunology, Department of Neurology, Jena University Hospital, 07747, Jena, Germany
- Center for Sepsis Control and Care, Jena University Hospital, 07747, Jena, Germany
| | - Markus Lubeck
- Bruker Daltonics GmbH & Co. KG, 28359, Bremen, Germany
| | | | - Sean J Humphrey
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, 3052, Victoria, Australia.
| | - Florian Meier
- Functional Proteomics, Jena University Hospital, 07747, Jena, Germany.
- Comprehensive Cancer Center Central Germany, 07747, Jena, Germany.
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3
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van Schie M, Weijers D. Arabidopsis enters the single-cell proteomics era. THE NEW PHYTOLOGIST 2024. [PMID: 39039795 DOI: 10.1111/nph.19992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Affiliation(s)
- Monique van Schie
- Laboratory of Biochemistry, Wageningen University, 6708WE, Wageningen, the Netherlands
| | - Dolf Weijers
- Laboratory of Biochemistry, Wageningen University, 6708WE, Wageningen, the Netherlands
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4
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Ctortecka C, Clark NM, Boyle BW, Seth A, Mani DR, Udeshi ND, Carr SA. Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications. Nat Commun 2024; 15:5707. [PMID: 38977691 PMCID: PMC11231172 DOI: 10.1038/s41467-024-49651-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 06/14/2024] [Indexed: 07/10/2024] Open
Abstract
The recent technological and computational advances in mass spectrometry-based single-cell proteomics have pushed the boundaries of sensitivity and throughput. However, reproducible quantification of thousands of proteins within a single cell remains challenging. To address some of those limitations, we present a dedicated sample preparation chip, the proteoCHIP EVO 96 that directly interfaces with the Evosep One. This, in combination with the Bruker timsTOF demonstrates double the identifications without manual sample handling and the newest generation timsTOF Ultra identifies up to 4000 with an average of 3500 protein groups per single HEK-293T without a carrier or match-between runs. Our workflow spans 4 orders of magnitude, identifies over 50 E3 ubiquitin-protein ligases, and profiles key regulatory proteins upon small molecule stimulation. This study demonstrates that the proteoCHIP EVO 96-based sample preparation with the timsTOF Ultra provides sufficient proteome depth to study complex biology beyond cell-type classifications.
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Affiliation(s)
| | | | - Brian W Boyle
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - D R Mani
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Steven A Carr
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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5
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Weng L, Yan G, Liu W, Tai Q, Gao M, Zhang X. Picoliter Single-Cell Reactor for Proteome Profiling by In Situ Cell Lysis, Protein Immobilization, Digestion, and Droplet Transfer. J Proteome Res 2024; 23:2441-2451. [PMID: 38833655 DOI: 10.1021/acs.jproteome.4c00117] [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: 06/06/2024]
Abstract
Global profiling of single-cell proteomes can reveal cellular heterogeneity, thus benefiting precision medicine. However, current mass spectrometry (MS)-based single-cell proteomic sample processing still faces technical challenges associated with processing efficiency and protein recovery. Herein, we present an innovative sample processing platform based on a picoliter single-cell reactor (picoSCR) for single-cell proteome profiling, which involves in situ protein immobilization and sample transfer. PicoSCR helped minimize surface adsorptive losses by downscaling the processing volume to 400 pL with a contact area of less than 0.4 mm2. Besides, picoSCR reached highly efficient cell lysis and digestion within 30 min, benefiting from optimal reagent and high reactant concentrations. Using the picoSCR-nanoLC-MS system, over 1400 proteins were identified from an individual HeLa cell using data-dependent acquisition mode. Proteins with copy number below 1000 were identified, demonstrating this system with a detection limit of 1.7 zmol. Furthermore, we profiled the proteome of circulating tumor cells (CTCs). Data are available via ProteomeXchange with the identifier PXD051468. Proteins associated with epithelial-mesenchymal transition and neutrophil extracellular traps formation (which are both related to tumor metastasis) were observed in all CTCs. The cellular heterogeneity was revealed by differences in signaling pathways within individual cells. These results highlighted the potential of the picoSCR platform to help discover new biomarkers and explore differences in biological processes between cells.
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Affiliation(s)
- Lingxiao Weng
- Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai 200438, China
| | - Guoquan Yan
- Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai 200438, China
| | - Wei Liu
- Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai 200438, China
| | - Qunfei Tai
- Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai 200438, China
| | - Mingxia Gao
- Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai 200438, China
- Pharmacy Department, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai 201399, China
| | - Xiangmin Zhang
- Department of Chemistry, Institutes of Biomedical Sciences, Fudan University, Shanghai 200438, China
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6
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Zhang S, Ghalandari B, Chen Y, Wang Q, Liu K, Sun X, Ding X, Song S, Jiang L, Ding X. Boronic Acid-Rich Lanthanide Metal-Organic Frameworks Enable Deep Proteomics with Ultratrace Biological Samples. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2401559. [PMID: 38958107 DOI: 10.1002/adma.202401559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 06/21/2024] [Indexed: 07/04/2024]
Abstract
Label-free proteomics is widely used to identify disease mechanism and potential therapeutic targets. However, deep proteomics with ultratrace clinical specimen remains a major technical challenge due to extensive contact loss during complex sample pretreatment. Here, a hybrid of four boronic acid-rich lanthanide metal-organic frameworks (MOFs) with high protein affinity is introduced to capture proteins in ultratrace samples jointly by nitrogen-boronate complexation, cation-π and ionic interactions. A MOFs Aided Sample Preparation (MASP) workflow that shrinks sample volume and integrates lysis, protein capture, protein digestion and peptide collection steps into a single PCR tube to minimize sample loss caused by non-specific absorption, is proposed further. MASP is validated to quantify ≈1800 proteins in 10 HEK-293T cells. MASP is applied to profile cerebrospinal fluid (CSF) proteome from cerebral stroke and brain damaged patients, and identified ≈3700 proteins in 1 µL CSF. MASP is further demonstrated to detect ≈9600 proteins in as few as 50 µg mouse brain tissues. MASP thus enables deep, scalable, and reproducible proteome on precious clinical samples with low abundant proteins.
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Affiliation(s)
- Shuang Zhang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Behafarid Ghalandari
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Youming Chen
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Qingwen Wang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Kun Liu
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Xinyi Sun
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Xinwen Ding
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Sunfengda Song
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Lai Jiang
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
| | - Xianting Ding
- Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
- State Key Laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China
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7
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Montes C, Zhang J, Nolan TM, Walley JW. Single-cell proteomics differentiates Arabidopsis root cell types. THE NEW PHYTOLOGIST 2024. [PMID: 38923440 DOI: 10.1111/nph.19923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 06/09/2024] [Indexed: 06/28/2024]
Abstract
Single-cell proteomics (SCP) is an emerging approach to resolve cellular heterogeneity within complex tissues of multi-cellular organisms. Here, we demonstrate the feasibility of SCP on plant samples using the model plant Arabidopsis thaliana. Specifically, we focused on examining isolated single cells from the cortex and endodermis, which are two adjacent root cell types derived from a common stem cell lineage. From 756 root cells, we identified 3763 proteins and 1118 proteins/cell. Ultimately, we focus on 3217 proteins quantified following stringent filtering. Of these, we identified 596 proteins whose expression is enriched in either the cortex or endodermis and are able to differentiate these closely related plant cell types. Collectivity, this study demonstrates that SCP can resolve neighboring cell types with distinct functions, thereby facilitating the identification of biomarkers and candidate proteins to enable functional genomics.
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Affiliation(s)
- Christian Montes
- Department of Plant Pathology, Entomology, and Microbiology, Iowa State University, Ames, IA, 50011, USA
| | - Jingyuan Zhang
- Department of Biology, Duke University, Durham, NC, 27708, USA
| | - Trevor M Nolan
- Department of Biology, Duke University, Durham, NC, 27708, USA
- Howard Hughes Medical Institute, Duke University, Durham, NC, 27708, USA
| | - Justin W Walley
- Department of Plant Pathology, Entomology, and Microbiology, Iowa State University, Ames, IA, 50011, USA
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8
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Pang M, Jones JJ, Wang TY, Quan B, Kubat NJ, Qiu Y, Roukes ML, Chou TF. Increasing Proteome Coverage Through a Reduction in Analyte Complexity in Single-Cell Equivalent Samples. J Proteome Res 2024. [PMID: 38832920 DOI: 10.1021/acs.jproteome.4c00062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2024]
Abstract
The advancement of sophisticated instrumentation in mass spectrometry has catalyzed an in-depth exploration of complex proteomes. This exploration necessitates a nuanced balance in experimental design, particularly between quantitative precision and the enumeration of analytes detected. In bottom-up proteomics, a key challenge is that oversampling of abundant proteins can adversely affect the identification of a diverse array of unique proteins. This issue is especially pronounced in samples with limited analytes, such as small tissue biopsies or single-cell samples. Methods such as depletion and fractionation are suboptimal to reduce oversampling in single cell samples, and other improvements on LC and mass spectrometry technologies and methods have been developed to address the trade-off between precision and enumeration. We demonstrate that by using a monosubstrate protease for proteomic analysis of single-cell equivalent digest samples, an improvement in quantitative accuracy can be achieved, while maintaining high proteome coverage established by trypsin. This improvement is particularly vital for the field of single-cell proteomics, where single-cell samples with limited number of protein copies, especially in the context of low-abundance proteins, can benefit from considering analyte complexity. Considerations about analyte complexity, alongside chromatographic complexity, integration with data acquisition methods, and other factors such as those involving enzyme kinetics, will be crucial in the design of future single-cell workflows.
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Affiliation(s)
- Marion Pang
- Division of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| | - Jeff J Jones
- Division of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| | - Ting-Yu Wang
- Division of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| | - Baiyi Quan
- Division of Physics, Mathematics and Astronomy, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| | - Nicole J Kubat
- Division of Physics, Mathematics and Astronomy, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| | - Yanping Qiu
- Division of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
| | - Michael L Roukes
- Division of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
- Division of Physics, Mathematics and Astronomy, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
- Division of Engineering and Applied Science, California Institute of Technology, 1200 East California Blvd, Pasadena, California 91125, United States
| | - Tsui-Fen Chou
- Division of Biology and Biological Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
- Proteome Exploration Laboratory, Beckman Institute, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91125, United States
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9
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Cross J, Rai A, Fang H, Claridge B, Greening DW. Rapid and in-depth proteomic profiling of small extracellular vesicles for ultralow samples. Proteomics 2024; 24:e2300211. [PMID: 37786918 DOI: 10.1002/pmic.202300211] [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: 08/18/2023] [Revised: 09/20/2023] [Accepted: 09/20/2023] [Indexed: 10/04/2023]
Abstract
The integration of robust single-pot, solid-phase-enhanced sample preparation with powerful liquid chromatography-tandem mass spectrometry (LC-MS/MS) is routinely used to define the extracellular vesicle (EV) proteome landscape and underlying biology. However, EV proteome studies are often limited by sample availability, requiring upscaling cell cultures or larger volumes of biofluids to generate sufficient materials. Here, we have refined data independent acquisition (DIA)-based MS analysis of EV proteome by optimizing both protein enzymatic digestion and chromatography gradient length (ranging from 15 to 44 min). Our short 15 min gradient length can reproducibly quantify 1168 (from as little as 500 pg of EV peptides) to 3882 proteins groups (from 50 ng peptides), including robust quantification of 22 core EV marker proteins. Compared to data-dependent acquisition, DIA achieved significantly greater EV proteome coverage and quantification of low abundant protein species. Moreover, we have achieved optimal magnetic bead-based sample preparation tailored to low quantities of EVs (0.5 to 1 µg protein) to obtain sufficient peptides for MS quantification of 1908-2340 protein groups. We demonstrate the power and robustness of our pipeline in obtaining sufficient EV proteomes granularity of different cell sources to ascertain known EV biology. This underscores the capacity of our optimised workflow to capture precise and comprehensive proteome of EVs, especially from ultra-low sample quantities (sub-nanogram), an important challenge in the field where obtaining in-depth proteome information is essential.
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Affiliation(s)
- Jonathon Cross
- Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Alin Rai
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Department of Cardiovascular Research, Translation and Implementation (CaRTI), School of Agriculture, Biomedicine and Environment, La Trobe University, Bundoora, Australia
| | - Haoyun Fang
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
| | - Bethany Claridge
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Department of Cardiovascular Research, Translation and Implementation (CaRTI), School of Agriculture, Biomedicine and Environment, La Trobe University, Bundoora, Australia
| | - David W Greening
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Department of Cardiovascular Research, Translation and Implementation (CaRTI), School of Agriculture, Biomedicine and Environment, La Trobe University, Bundoora, Australia
- Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
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10
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Yang Z, Jin K, Chen Y, Liu Q, Chen H, Hu S, Wang Y, Pan Z, Feng F, Shi M, Xie H, Ma H, Zhou H. AM-DMF-SCP: Integrated Single-Cell Proteomics Analysis on an Active Matrix Digital Microfluidic Chip. JACS AU 2024; 4:1811-1823. [PMID: 38818059 PMCID: PMC11134390 DOI: 10.1021/jacsau.4c00027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 03/08/2024] [Accepted: 03/08/2024] [Indexed: 06/01/2024]
Abstract
Single-cell proteomics offers unparalleled insights into cellular diversity and molecular mechanisms, enabling a deeper understanding of complex biological processes at the individual cell level. Here, we develop an integrated sample processing on an active-matrix digital microfluidic chip for single-cell proteomics (AM-DMF-SCP). Employing the AM-DMF-SCP approach and data-independent acquisition (DIA), we identify an average of 2258 protein groups in single HeLa cells within 15 min of the liquid chromatography gradient. We performed comparative analyses of three tumor cell lines: HeLa, A549, and HepG2, and machine learning was utilized to identify the unique features of these cell lines. Applying the AM-DMF-SCP to characterize the proteomes of a third-generation EGFR inhibitor, ASK120067-resistant cells (67R) and their parental NCI-H1975 cells, we observed a potential correlation between elevated VIM expression and 67R resistance, which is consistent with the findings from bulk sample analyses. These results suggest that AM-DMF-SCP is an automated, robust, and sensitive platform for single-cell proteomics and demonstrate the potential for providing valuable insights into cellular mechanisms.
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Affiliation(s)
- Zhicheng Yang
- Department
of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai
Institute of Materia Medica, Chinese Academy
of Sciences, Shanghai 201203, China
- University
of the Chinese Academy of Sciences, Beijing 100049, China
| | - Kai Jin
- CAS
Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical
Engineering and Technology, Chinese Academy
of Sciences, Suzhou 215163, China
| | - Yimin Chen
- Department
of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai
Institute of Materia Medica, Chinese Academy
of Sciences, Shanghai 201203, China
- University
of the Chinese Academy of Sciences, Beijing 100049, China
| | - Qian Liu
- Department
of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai
Institute of Materia Medica, Chinese Academy
of Sciences, Shanghai 201203, China
| | - Hongxu Chen
- School
of Chinese Materia Medica, Nanjing University
of Chinese Medicine, 138 Xianlin Avenue, Nanjing, Jiangsu 210023, China
| | - Siyi Hu
- CAS
Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical
Engineering and Technology, Chinese Academy
of Sciences, Suzhou 215163, China
| | - Yuqiu Wang
- Department
of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai
Institute of Materia Medica, Chinese Academy
of Sciences, Shanghai 201203, China
| | - Zilu Pan
- Division
of Antitumor Pharmacology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Fang Feng
- Division
of Antitumor Pharmacology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Mude Shi
- Guangdong
ACXEL Micro & Nano Tech Co. Ltd., Foshan, Guangdong Province 528000, China
| | - Hua Xie
- University
of the Chinese Academy of Sciences, Beijing 100049, China
- Zhongshan
Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Zhongshan 528400, China
- Division
of Antitumor Pharmacology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Hanbin Ma
- CAS
Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical
Engineering and Technology, Chinese Academy
of Sciences, Suzhou 215163, China
- Guangdong
ACXEL Micro & Nano Tech Co. Ltd., Foshan, Guangdong Province 528000, China
| | - Hu Zhou
- Department
of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai
Institute of Materia Medica, Chinese Academy
of Sciences, Shanghai 201203, China
- University
of the Chinese Academy of Sciences, Beijing 100049, China
- Hangzhou
Institute for Advanced Study, University
of Chinese Academy of Sciences, Hangzhou 310024, China
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11
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Marie AL, Gao Y, Ivanov AR. Native N-glycome profiling of single cells and ng-level blood isolates using label-free capillary electrophoresis-mass spectrometry. Nat Commun 2024; 15:3847. [PMID: 38719792 PMCID: PMC11079027 DOI: 10.1038/s41467-024-47772-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 04/12/2024] [Indexed: 05/12/2024] Open
Abstract
The development of reliable single-cell dispensers and substantial sensitivity improvement in mass spectrometry made proteomic profiling of individual cells achievable. Yet, there are no established methods for single-cell glycome analysis due to the inability to amplify glycans and sample losses associated with sample processing and glycan labeling. In this work, we present an integrated platform coupling online in-capillary sample processing with high-sensitivity label-free capillary electrophoresis-mass spectrometry for N-glycan profiling of single mammalian cells. Direct and unbiased quantitative characterization of single-cell surface N-glycomes are demonstrated for HeLa and U87 cells, with the detection of up to 100 N-glycans per single cell. Interestingly, N-glycome alterations are unequivocally detected at the single-cell level in HeLa and U87 cells stimulated with lipopolysaccharide. The developed workflow is also applied to the profiling of ng-level amounts (5-500 ng) of blood-derived protein, extracellular vesicle, and total plasma isolates, resulting in over 170, 220, and 370 quantitated N-glycans, respectively.
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Affiliation(s)
- Anne-Lise Marie
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Ave., Boston, MA, 02115, US
| | - Yunfan Gao
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Ave., Boston, MA, 02115, US
| | - Alexander R Ivanov
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, 360 Huntington Ave., Boston, MA, 02115, US.
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12
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Makhmut A, Qin D, Hartlmayr D, Seth A, Coscia F. An Automated and Fast Sample Preparation Workflow for Laser Microdissection Guided Ultrasensitive Proteomics. Mol Cell Proteomics 2024; 23:100750. [PMID: 38513891 PMCID: PMC11067455 DOI: 10.1016/j.mcpro.2024.100750] [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: 12/08/2023] [Revised: 03/13/2024] [Accepted: 03/18/2024] [Indexed: 03/23/2024] Open
Abstract
Spatial tissue proteomics integrating whole-slide imaging, laser microdissection, and ultrasensitive mass spectrometry is a powerful approach to link cellular phenotypes to functional proteome states in (patho)physiology. To be applicable to large patient cohorts and low sample input amounts, including single-cell applications, loss-minimized and streamlined end-to-end workflows are key. We here introduce an automated sample preparation protocol for laser microdissected samples utilizing the cellenONE robotic system, which has the capacity to process 192 samples in 3 h. Following laser microdissection collection directly into the proteoCHIP LF 48 or EVO 96 chip, our optimized protocol facilitates lysis, formalin de-crosslinking, and tryptic digest of low-input archival tissue samples. The seamless integration with the Evosep ONE LC system by centrifugation allows 'on-the-fly' sample clean-up, particularly pertinent for laser microdissection workflows. We validate our method in human tonsil archival tissue, where we profile proteomes of spatially-defined B-cell, T-cell, and epithelial microregions of 4000 μm2 to a depth of ∼2000 proteins and with high cell type specificity. We finally provide detailed equipment templates and experimental guidelines for broad accessibility.
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Affiliation(s)
- Anuar Makhmut
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany
| | - Di Qin
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany
| | | | | | - Fabian Coscia
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany.
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13
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Khan S, Conover R, Asthagiri AR, Slavov N. Dynamics of Single-Cell Protein Covariation during Epithelial-Mesenchymal Transition. J Proteome Res 2024. [PMID: 38663020 DOI: 10.1021/acs.jproteome.4c00277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
Physiological processes, such as the epithelial-mesenchymal transition (EMT), are mediated by changes in protein interactions. These changes may be better reflected in protein covariation within a cellular cluster than in the temporal dynamics of cluster-average protein abundance. To explore this possibility, we quantified proteins in single human cells undergoing EMT. Covariation analysis of the data revealed that functionally coherent protein clusters dynamically changed their protein-protein correlations without concomitant changes in the cluster-average protein abundance. These dynamics of protein-protein correlations were monotonic in time and delineated protein modules functioning in actin cytoskeleton organization, energy metabolism, and protein transport. These protein modules are defined by protein covariation within the same time point and cluster and, thus, reflect biological regulation masked by the cluster-average protein dynamics. Thus, protein correlation dynamics across single cells offers a window into protein regulation during physiological transitions.
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Affiliation(s)
- Saad Khan
- Department of Bioengineering, Northeastern University, Boston, Massachusetts 02115, United States
- Department of Biology, Northeastern University, Boston, Massachusetts 02115, United States
| | - Rachel Conover
- Department of Bioengineering, Northeastern University, Boston, Massachusetts 02115, United States
| | - Anand R Asthagiri
- Department of Bioengineering, Northeastern University, Boston, Massachusetts 02115, United States
- Department of Biology, Northeastern University, Boston, Massachusetts 02115, United States
- Department of Chemical Engineering, Northeastern University, Boston, Massachusetts 02115, United States
| | - Nikolai Slavov
- Department of Bioengineering, Northeastern University, Boston, Massachusetts 02115, United States
- Department of Biology, Northeastern University, Boston, Massachusetts 02115, United States
- Parallel Squared Technology Institute, Watertown, Massachusetts 02472, United States
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14
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Mansuri MS, Bathla S, Lam TT, Nairn AC, Williams KR. Optimal conditions for carrying out trypsin digestions on complex proteomes: From bulk samples to single cells. J Proteomics 2024; 297:105109. [PMID: 38325732 PMCID: PMC10939724 DOI: 10.1016/j.jprot.2024.105109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 01/10/2024] [Accepted: 01/31/2024] [Indexed: 02/09/2024]
Abstract
To identify proteins by the bottom-up mass spectrometry workflow, enzymatic digestion is essential to break down proteins into smaller peptides amenable to both chromatographic separation and mass spectrometric analysis. Trypsin is the most extensively used protease due to its high cleavage specificity and generation of peptides with desirable positively charged N- and C-terminal amino acid residues that are amenable to reverse phase HPLC separation and MS/MS analyses. However, trypsin can yield variable digestion profiles and its protein cleavage activity is interdependent on trypsin source and quality, digestion time and temperature, pH, denaturant, trypsin and substrate concentrations, composition/complexity of the sample matrix, and other factors. There is therefore a need for a more standardized, general-purpose trypsin digestion protocol. Based on a review of the literature we delineate optimal conditions for carrying out trypsin digestions of complex proteomes from bulk samples to limiting amounts of protein extracts. Furthermore, we highlight recent developments and technological advances used in digestion protocols to quantify complex proteomes from single cells. SIGNIFICANCE: Currently, bottom-up MS-based proteomics is the method of choice for global proteome analysis. Since trypsin is the most utilized protease in bottom-up MS proteomics, delineating optimal conditions for carrying out trypsin digestions of complex proteomes in samples ranging from tissues to single cells should positively impact a broad range of biomedical research.
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Affiliation(s)
- M Shahid Mansuri
- Yale/NIDA Neuroproteomics Center, New Haven, CT 06511, USA; Molecular Biophysics and Biochemistry, Yale University School of Medicine, New Haven, CT 06511, USA.
| | - Shveta Bathla
- Yale/NIDA Neuroproteomics Center, New Haven, CT 06511, USA; Department of Psychiatry, Yale School of Medicine, New Haven, CT 06511, USA
| | - TuKiet T Lam
- Yale/NIDA Neuroproteomics Center, New Haven, CT 06511, USA; Molecular Biophysics and Biochemistry, Yale University School of Medicine, New Haven, CT 06511, USA; Keck MS & Proteomics Resource, Yale School of Medicine, New Haven, CT 06511, USA
| | - Angus C Nairn
- Yale/NIDA Neuroproteomics Center, New Haven, CT 06511, USA; Department of Psychiatry, Yale School of Medicine, New Haven, CT 06511, USA
| | - Kenneth R Williams
- Yale/NIDA Neuroproteomics Center, New Haven, CT 06511, USA; Molecular Biophysics and Biochemistry, Yale University School of Medicine, New Haven, CT 06511, USA; Keck MS & Proteomics Resource, Yale School of Medicine, New Haven, CT 06511, USA.
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15
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Burton NR, Backus KM. Functionalizing tandem mass tags for streamlining click-based quantitative chemoproteomics. Commun Chem 2024; 7:80. [PMID: 38600184 PMCID: PMC11006884 DOI: 10.1038/s42004-024-01162-x] [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: 12/01/2023] [Accepted: 03/27/2024] [Indexed: 04/12/2024] Open
Abstract
Mapping the ligandability or potential druggability of all proteins in the human proteome is a central goal of mass spectrometry-based covalent chemoproteomics. Achieving this ambitious objective requires high throughput and high coverage sample preparation and liquid chromatography-tandem mass spectrometry analysis for hundreds to thousands of reactive compounds and chemical probes. Conducting chemoproteomic screens at this scale benefits from technical innovations that achieve increased sample throughput. Here we realize this vision by establishing the silane-based cleavable linkers for isotopically-labeled proteomics-tandem mass tag (sCIP-TMT) proteomic platform, which is distinguished by early sample pooling that increases sample preparation throughput. sCIP-TMT pairs a custom click-compatible sCIP capture reagent that is readily functionalized in high yield with commercially available TMT reagents. Synthesis and benchmarking of a 10-plex set of sCIP-TMT reveal a substantial decrease in sample preparation time together with high coverage and high accuracy quantification. By screening a focused set of four cysteine-reactive electrophiles, we demonstrate the utility of sCIP-TMT for chemoproteomic target hunting, identifying 789 total liganded cysteines. Distinguished by its compatibility with established enrichment and quantification protocols, we expect sCIP-TMT will readily translate to a wide range of covalent chemoproteomic applications.
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Affiliation(s)
- Nikolas R Burton
- Department of Biological Chemistry, David Geffen School of Medicine, UCLA, Los Angeles CA, USA
- Department of Chemistry and Biochemistry, UCLA, Los Angeles, CA, USA
| | - Keriann M Backus
- Department of Biological Chemistry, David Geffen School of Medicine, UCLA, Los Angeles CA, USA.
- Department of Chemistry and Biochemistry, UCLA, Los Angeles, CA, USA.
- Molecular Biology Institute, UCLA, Los Angeles, CA, USA.
- DOE Institute for Genomics and Proteomics, UCLA, Los Angeles, CA, USA.
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, UCLA, Los Angeles, CA, USA.
- Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA, USA.
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16
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Khan S, Conover R, Asthagiri AR, Slavov N. Dynamics of single-cell protein covariation during epithelial-mesenchymal transition. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.21.572913. [PMID: 38187715 PMCID: PMC10769332 DOI: 10.1101/2023.12.21.572913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Physiological processes, such as epithelial-mesenchymal transition (EMT), are mediated by changes in protein interactions. These changes may be better reflected in protein covariation within cellular cluster than in the temporal dynamics of cluster-average protein abundance. To explore this possibility, we quantified proteins in single human cells undergoing EMT. Covariation analysis of the data revealed that functionally coherent protein clusters dynamically changed their protein-protein correlations without concomitant changes in cluster-average protein abundance. These dynamics of protein-protein correlations were monotonic in time and delineated protein modules functioning in actin cytoskeleton organization, energy metabolism and protein transport. These protein modules are defined by protein covariation within the same time point and cluster and thus reflect biological regulation masked by the cluster-average protein dynamics. Thus, protein correlation dynamics across single cells offer a window into protein regulation during physiological transitions.
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Affiliation(s)
- Saad Khan
- Department of Bioengineering, Northeastern University, Boston, MA, USA
- Department of Biology, Northeastern University, Boston, MA, USA
| | - Rachel Conover
- Department of Bioengineering, Northeastern University, Boston, MA, USA
| | - Anand R. Asthagiri
- Department of Bioengineering, Northeastern University, Boston, MA, USA
- Department of Biology, Northeastern University, Boston, MA, USA
- Department of Chemical Engineering, Northeastern University, Boston, MA, USA
| | - Nikolai Slavov
- Department of Bioengineering, Northeastern University, Boston, MA, USA
- Department of Biology, Northeastern University, Boston, MA, USA
- Parallel Squared Technology Institute, Watertown, MA 02472, USA
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17
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Konno R, Ishikawa M, Nakajima D, Endo Y, Ohara O, Kawashima Y. Universal Pretreatment Development for Low-input Proteomics Using Lauryl Maltose Neopentyl Glycol. Mol Cell Proteomics 2024; 23:100745. [PMID: 38447790 PMCID: PMC10999711 DOI: 10.1016/j.mcpro.2024.100745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 02/23/2024] [Accepted: 03/01/2024] [Indexed: 03/08/2024] Open
Abstract
In recent years, there has been a growing demand for low-input proteomics, particularly in the context of single-cell proteomics (SCP). In this study, we have developed a lauryl maltose neopentyl glycol (LMNG)-assisted sample preparation (LASP) method. This method effectively reduces protein and peptide loss in samples by incorporating LMNG, a surfactant, into the digestion solution and subsequently removing the LMNG simply via reversed phase solid-phase extraction. The advantage of removing LMNG during sample preparation for general proteomic analysis is the prevention of mass spectrometry (MS) contamination. When we applied the LASP method to the low-input SP3 method and on-bead digestion in coimmunoprecipitation-MS, we observed a significant improvement in the recovery of the digested peptides. Furthermore, we have established a simple and easy sample preparation method for SCP based on the LASP method and identified a median of 1175 proteins from a single HEK239F cell using liquid chromatography (LC)-MS/MS with a throughput of 80 samples per day.
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Affiliation(s)
- Ryo Konno
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Masaki Ishikawa
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Daisuke Nakajima
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Yusuke Endo
- Department of Frontier Research and Development, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Osamu Ohara
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan
| | - Yusuke Kawashima
- Department of Applied Genomics, Kazusa DNA Research Institute, Kisarazu, Chiba, Japan; Graduate School of Science, Kitasato University, Sagamihara, Kanagawa, Japan.
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18
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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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19
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Ye Z, Sabatier P, Martin-Gonzalez J, Eguchi A, Lechner M, Østergaard O, Xie J, Guo Y, Schultz L, Truffer R, Bekker-Jensen DB, Bache N, Olsen JV. One-Tip enables comprehensive proteome coverage in minimal cells and single zygotes. Nat Commun 2024; 15:2474. [PMID: 38503780 PMCID: PMC10951212 DOI: 10.1038/s41467-024-46777-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 03/11/2024] [Indexed: 03/21/2024] Open
Abstract
Mass spectrometry (MS)-based proteomics workflows typically involve complex, multi-step processes, presenting challenges with sample losses, reproducibility, requiring substantial time and financial investments, and specialized skills. Here we introduce One-Tip, a proteomics methodology that seamlessly integrates efficient, one-pot sample preparation with precise, narrow-window data-independent acquisition (nDIA) analysis. One-Tip substantially simplifies sample processing, enabling the reproducible identification of >9000 proteins from ~1000 HeLa cells. The versatility of One-Tip is highlighted by nDIA identification of ~6000 proteins in single cells from early mouse embryos. Additionally, the study incorporates the Uno Single Cell Dispenser™, demonstrating the capability of One-Tip in single-cell proteomics with >3000 proteins identified per HeLa cell. We also extend One-Tip workflow to analysis of extracellular vesicles (EVs) extracted from blood plasma, demonstrating its high sensitivity by identifying >3000 proteins from 16 ng EV preparation. One-Tip expands capabilities of proteomics, offering greater depth and throughput across a range of sample types.
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Affiliation(s)
- Zilu Ye
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, China.
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark.
| | - Pierre Sabatier
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Javier Martin-Gonzalez
- Core Facility for Transgenic Mice, Department of Experimental Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Akihiro Eguchi
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Maico Lechner
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Ole Østergaard
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Jingsheng Xie
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, China
| | - Yuan Guo
- Tecan Group Ltd., Männedorf, Switzerland
| | | | | | | | | | - Jesper V Olsen
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark.
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20
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Dorey A, Howorka S. Nanopore DNA sequencing technologies and their applications towards single-molecule proteomics. Nat Chem 2024; 16:314-334. [PMID: 38448507 DOI: 10.1038/s41557-023-01322-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 07/14/2023] [Indexed: 03/08/2024]
Abstract
Sequencing of nucleic acids with nanopores has emerged as a powerful tool offering rapid readout, high accuracy, low cost and portability. This label-free method for sequencing at the single-molecule level is an achievement on its own. However, nanopores also show promise for the technologically even more challenging sequencing of polypeptides, something that could considerably benefit biological discovery, clinical diagnostics and homeland security, as current techniques lack portability and speed. Here we survey the biochemical innovations underpinning commercial and academic nanopore DNA/RNA sequencing techniques, and explore how these advances can fuel developments in future protein sequencing with nanopores.
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Affiliation(s)
- Adam Dorey
- Department of Chemistry & Institute of Structural Molecular Biology, University College London, London, UK.
| | - Stefan Howorka
- Department of Chemistry & Institute of Structural Molecular Biology, University College London, London, UK.
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21
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Shen B, Pade LR, Nemes P. The 15-min (Sub)Cellular Proteome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.15.580399. [PMID: 38405838 PMCID: PMC10888744 DOI: 10.1101/2024.02.15.580399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Single-cell mass spectrometry (MS) opens a proteomic window onto the inner workings of cells. Here, we report the discovery characterization of the subcellular proteome of single, identified embryonic cells in record speed and molecular coverage. We integrated subcellular capillary microsampling, fast capillary electrophoresis (CE), high-efficiency nano-flow electrospray ionization, and orbitrap tandem MS. In proof-of-principle tests, we found shorter separation times to hinder proteome detection using DDA, but not DIA. Within a 15-min effective separation window, CE data-independent acquisition (DIA) was able to identify 1,161 proteins from single HeLa-cell-equivalent (∼200 pg) proteome digests vs. 401 proteins by the reference data-dependent acquisition (DDA) on the same platform. The approach measured 1,242 proteins from subcellular niches in an identified cell in the live Xenopus laevis (frog) embryo, including many canonical components of organelles. CE-MS with DIA enables fast, sensitive, and deep profiling of the (sub)cellular proteome, expanding the bioanalytical toolbox of cell biology. Authorship Contributions P.N. and B.S. designed the study. L.R.P. collected the X. laevis cell aspirates. B.S. prepared and measured the samples. B.S. and P.N. analyzed the data and interpreted the results. P.N. and B.S. wrote the manuscript. All the authors commented on the manuscript.
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22
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Wang Y, Guan ZY, Shi SW, Jiang YR, Zhang J, Yang Y, Wu Q, Wu J, Chen JB, Ying WX, Xu QQ, Fan QX, Wang HF, Zhou L, Wang L, Fang J, Pan JZ, Fang Q. Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell. Nat Commun 2024; 15:1279. [PMID: 38341466 PMCID: PMC10858870 DOI: 10.1038/s41467-024-45659-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Accepted: 01/29/2024] [Indexed: 02/12/2024] Open
Abstract
The shotgun proteomic analysis is currently the most promising single-cell protein sequencing technology, however its identification level of ~1000 proteins per cell is still insufficient for practical applications. Here, we develop a pick-up single-cell proteomic analysis (PiSPA) workflow to achieve a deep identification capable of quantifying up to 3000 protein groups in a mammalian cell using the label-free quantitative method. The PiSPA workflow is specially established for single-cell samples mainly based on a nanoliter-scale microfluidic liquid handling robot, capable of achieving single-cell capture, pretreatment and injection under the pick-up operation strategy. Using this customized workflow with remarkable improvement in protein identification, 2449-3500, 2278-3257 and 1621-2904 protein groups are quantified in single A549 cells (n = 37), HeLa cells (n = 44) and U2OS cells (n = 27) under the DIA (MBR) mode, respectively. Benefiting from the flexible cell picking-up ability, we study HeLa cell migration at the single cell proteome level, demonstrating the potential in practical biological research from single-cell insight.
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Affiliation(s)
- Yu Wang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
- College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China
| | - Zhi-Ying Guan
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Shao-Wen Shi
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
| | - Yi-Rong Jiang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Jie Zhang
- Department of Cell Biology, China Medical University, Shenyang, 110122, China
| | - Yi Yang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
| | - Qiong Wu
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Jie Wu
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Jian-Bo Chen
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Wei-Xin Ying
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Qin-Qin Xu
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Qian-Xi Fan
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
| | - Hui-Feng Wang
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
| | - Li Zhou
- Shanghai Omicsolution Co., Shanghai, 201100, China
| | - Ling Wang
- Shanghai Omicsolution Co., Shanghai, 201100, China
| | - Jin Fang
- Department of Cell Biology, China Medical University, Shenyang, 110122, China
| | - Jian-Zhang Pan
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China
| | - Qun Fang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou, 310058, China.
- Single-cell Proteomics Research Center, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 311200, China.
- Key Laboratory of Excited-State Materials of Zhejiang Province, Zhejiang University, Hangzhou, 310007, China.
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23
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Matzinger M, Schmücker A, Yelagandula R, Stejskal K, Krššáková G, Berger F, Mechtler K, Mayer RL. Micropillar arrays, wide window acquisition and AI-based data analysis improve comprehensiveness in multiple proteomic applications. Nat Commun 2024; 15:1019. [PMID: 38310095 PMCID: PMC10838342 DOI: 10.1038/s41467-024-45391-z] [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: 03/02/2023] [Accepted: 01/19/2024] [Indexed: 02/05/2024] Open
Abstract
Comprehensive proteomic analysis is essential to elucidate molecular pathways and protein functions. Despite tremendous progress in proteomics, current studies still suffer from limited proteomic coverage and dynamic range. Here, we utilize micropillar array columns (µPACs) together with wide-window acquisition and the AI-based CHIMERYS search engine to achieve excellent proteomic comprehensiveness for bulk proteomics, affinity purification mass spectrometry and single cell proteomics. Our data show that µPACs identify ≤50% more peptides and ≤24% more proteins, while offering improved throughput, which is critical for large (clinical) proteomics studies. Combining wide precursor isolation widths of m/z 4-12 with the CHIMERYS search engine identified +51-74% and +59-150% more proteins and peptides, respectively, for single cell, co-immunoprecipitation, and multi-species samples over a conventional workflow at well-controlled false discovery rates. The workflow further offers excellent precision, with CVs <7% for low input bulk samples, and accuracy, with deviations <10% from expected fold changes for regular abundance two-proteome mixes. Compared to a conventional workflow, our entire optimized platform discovered 92% more potential interactors in a protein-protein interaction study on the chromatin remodeler Smarca5/Snf2h. These include previously described Smarca5 binding partners and undescribed ones including Arid1a, another chromatin remodeler with key roles in neurodevelopmental and malignant disorders.
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Affiliation(s)
- Manuel Matzinger
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter, Vienna, Austria.
| | - Anna Schmücker
- Gregor Mendel Institute of Molecular Plant Biology (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria
- MRC (Medical Research Council) London Institute of Medical Sciences, Du Cane Road, London, W12 0NN, UK
- Institute of Clinical Sciences, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London, W12 0NN, UK
| | - Ramesh Yelagandula
- Gregor Mendel Institute of Molecular Plant Biology (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria
- Institute of Molecular Biotechnology (IMBA), Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria
- Laboratory of Epigenetics, Cell Fate & Disease, Centre for DNA Fingerprinting and Diagnostics (CDFD), Uppal, Hyderabad, India
| | - Karel Stejskal
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter, Vienna, Austria
- Gregor Mendel Institute of Molecular Plant Biology (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria
- Institute of Molecular Biotechnology (IMBA), Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria
| | - Gabriela Krššáková
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter, Vienna, Austria
- Gregor Mendel Institute of Molecular Plant Biology (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria
- Institute of Molecular Biotechnology (IMBA), Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria
| | - Frédéric Berger
- Gregor Mendel Institute of Molecular Plant Biology (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria
| | - Karl Mechtler
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter, Vienna, Austria.
- Gregor Mendel Institute of Molecular Plant Biology (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria.
- Institute of Molecular Biotechnology (IMBA), Austrian Academy of Sciences, Vienna BioCenter (VBC), Vienna, Austria.
| | - Rupert L Mayer
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter, Vienna, Austria.
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24
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Tarn C, Wu YZ, Wang KF. PepPre: Promote Peptide Identification Using Accurate and Comprehensive Precursors. J Proteome Res 2024; 23:574-584. [PMID: 38157563 DOI: 10.1021/acs.jproteome.3c00293] [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: 01/03/2024]
Abstract
Accurate and comprehensive peptide precursor ions are crucial to tandem mass-spectrometry-based peptide identification. An identification engine can derive great advantages from the search space reduction enabled by credible and detailed precursors. Furthermore, by considering multiple precursors per spectrum, both the number of identifications and the spectrum explainability can be substantially improved. Here, we introduce PepPre, which detects precursors by decomposing peaks into multiple isotope clusters using linear programming methods. The detected precursors are scored and ranked, and the high-scoring ones are used for subsequent peptide identification. PepPre is evaluated both on regular and cross-linked peptide data sets and compared with 11 methods. The experimental results show that PepPre achieves a remarkable increase of 203% in PSM and 68% in peptide identifications compared to instrument software for regular peptides and 99% in PSM and 27% in peptide pair identifications for cross-linked peptides, surpassing the performance of all other evaluated methods. In addition to the increased identification numbers, further credibility evaluations evidence the reliability of the identified results. Moreover, by widening the isolation window of data acquisition from 2 to 8 Th, with PepPre, an engine is able to identify at least 64% more PSMs, thereby demonstrating the potential advantages of wide-window data acquisition. PepPre is open-source and available at http://peppre.ctarn.io.
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Affiliation(s)
- Ching Tarn
- Institute of Computing Technology, Chinese Academy of Sciences, 100190 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Yu-Zhuo Wu
- Institute of Computing Technology, Chinese Academy of Sciences, 100190 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
| | - Kai-Fei Wang
- Institute of Computing Technology, Chinese Academy of Sciences, 100190 Beijing, China
- University of Chinese Academy of Sciences, 100049 Beijing, China
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25
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Omenn GS, Lane L, Overall CM, Lindskog C, Pineau C, Packer NH, Cristea IM, Weintraub ST, Orchard S, Roehrl MHA, Nice E, Guo T, Van Eyk JE, Liu S, Bandeira N, Aebersold R, Moritz RL, Deutsch EW. The 2023 Report on the Proteome from the HUPO Human Proteome Project. J Proteome Res 2024; 23:532-549. [PMID: 38232391 PMCID: PMC11026053 DOI: 10.1021/acs.jproteome.3c00591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Since 2010, the Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify the protein parts list and (2) to make proteomics an integral part of multiomics studies of human health and disease. The HPP relies on international collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE-KB using HPP Guidelines for quality assurance, integration and curation of MS and non-MS protein data by neXtProt, plus extensive use of antibody profiling carried out by the Human Protein Atlas. According to the neXtProt release 2023-04-18, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 neXtProt predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry (MS) in accordance with HPP Guidelines and 944 by a variety of non-MS methods. The number of neXtProt PE2, PE3, and PE4 missing proteins now stands at 1381. Achieving the unambiguous identification of 93% of predicted proteins encoded from across all chromosomes represents remarkable experimental progress on the Human Proteome parts list. Meanwhile, there are several categories of predicted proteins that have proved resistant to detection regardless of protein-based methods used. Additionally there are some PE1-4 proteins that probably should be reclassified to PE5, specifically 21 LINC entries and ∼30 HERV entries; these are being addressed in the present year. Applying proteomics in a wide array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams and the antibody and pathology resource pillars. Current progress has positioned the HPP to transition to its Grand Challenge Project focused on determining the primary function(s) of every protein itself and in networks and pathways within the context of human health and disease.
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Affiliation(s)
- Gilbert S. Omenn
- University of Michigan, Ann Arbor, Michigan 48109, United States
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Lydie Lane
- CALIPHO Group, SIB Swiss Institute of Bioinformatics and University of Geneva, 1015 Lausanne, Switzerland
| | - Christopher M. Overall
- University of British Columbia, Vancouver, BC V6T 1Z4, Canada, Yonsei University Republic of Korea
| | | | - Charles Pineau
- University Rennes, Inserm U1085, Irset, 35042 Rennes, France
| | | | | | - Susan T. Weintraub
- University of Texas Health Science Center-San Antonio, San Antonio, Texas 78229-3900, United States
| | | | - Michael H. A. Roehrl
- Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, United States
| | | | - Tiannan Guo
- Westlake Center for Intelligent Proteomics, Westlake Laboratory, Westlake University, Hangzhou 310024, Zhejiang Province, China
| | - Jennifer E. Van Eyk
- Advanced Clinical Biosystems Research Institute, Smidt Heart Institute, Cedars-Sinai Medical Center, 127 South San Vicente Boulevard, Pavilion, 9th Floor, Los Angeles, CA, 90048, United States
| | - Siqi Liu
- BGI Group, Shenzhen 518083, China
| | - Nuno Bandeira
- University of California, San Diego, La Jolla, CA, 92093, United States
| | - Ruedi Aebersold
- Institute of Molecular Systems Biology in ETH Zurich, 8092 Zurich, Switzerland
- University of Zurich, 8092 Zurich, Switzerland
| | - Robert L. Moritz
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Eric W. Deutsch
- Institute for Systems Biology, Seattle, Washington 98109, United States
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26
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Ctortecka C, Clark NM, Boyle B, Seth A, Mani DR, Udeshi ND, Carr SA. Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.20.576369. [PMID: 38328197 PMCID: PMC10849471 DOI: 10.1101/2024.01.20.576369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Mass spectrometry (MS)-based single-cell proteomics (SCP) has gained massive attention as a viable complement to other single cell approaches. The rapid technological and computational advances in the field have pushed the boundaries of sensitivity and throughput. However, reproducible quantification of thousands of proteins within a single cell at reasonable proteome depth to characterize biological phenomena remains a challenge. To address some of those limitations we present a combination of fully automated single cell sample preparation utilizing a dedicated chip within the picolitre dispensing robot, the cellenONE. The proteoCHIP EVO 96 can be directly interfaced with the Evosep One chromatographic system for in-line desalting and highly reproducible separation with a throughput of 80 samples per day. This, in combination with the Bruker timsTOF MS instruments, demonstrates double the identifications without manual sample handling. Moreover, relative to standard high-performance liquid chromatography, the Evosep One separation provides further 2-fold improvement in protein identifications. The implementation of the newest generation timsTOF Ultra with our proteoCHIP EVO 96-based sample preparation workflow reproducibly identifies up to 4,000 proteins per single HEK-293T without a carrier or match-between runs. Our current SCP depth spans over 4 orders of magnitude and identifies over 50 biologically relevant ubiquitin ligases. We complement our highly reproducible single-cell proteomics workflow to profile hundreds of lipopolysaccharide (LPS)-perturbed THP-1 cells and identified key regulatory proteins involved in interleukin and interferon signaling. This study demonstrates that the proteoCHIP EVO 96-based SCP sample preparation with the timsTOF Ultra provides sufficient proteome depth to study complex biology beyond cell-type classifications.
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Affiliation(s)
- Claudia Ctortecka
- Broad Institute of MIT and Harvard, 415 Main Street, 02142 Cambridge, MA, USA
| | - Natalie M. Clark
- Broad Institute of MIT and Harvard, 415 Main Street, 02142 Cambridge, MA, USA
| | - Brian Boyle
- Broad Institute of MIT and Harvard, 415 Main Street, 02142 Cambridge, MA, USA
| | - Anjali Seth
- Cellenion SASU, 60F avenue Rockefeller, 69008 Lyon, France
| | - D. R. Mani
- Broad Institute of MIT and Harvard, 415 Main Street, 02142 Cambridge, MA, USA
| | - Namrata D. Udeshi
- Broad Institute of MIT and Harvard, 415 Main Street, 02142 Cambridge, MA, USA
| | - Steven A. Carr
- Broad Institute of MIT and Harvard, 415 Main Street, 02142 Cambridge, MA, USA
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27
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Naval P, Pañeda LP, Athanasopoulou M, Teppo JS, Zubarev RA, Végvári Á. EquiCP: Targeted Single-Cell Proteomics by Mass Spectrometry with Isobaric Labeled Multiplexing. Methods Mol Biol 2024; 2817:133-143. [PMID: 38907152 DOI: 10.1007/978-1-0716-3934-4_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/23/2024]
Abstract
Nontargeted single-cell proteomics analysis by mass spectrometry with sample multiplexing utilizing isobaric labeling is often performed using a carrier proteome. The presented protocol describes a targeted approach that replaces the carrier proteome with a set of synthetic peptides from selected proteins, which improves the identification and quantification of these proteins in single human cells.
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Affiliation(s)
- Prajakta Naval
- Division of Chemistry I, Department of Medical Biochemistry & Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Laura Pérez Pañeda
- Division of Chemistry I, Department of Medical Biochemistry & Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Maria Athanasopoulou
- Division of Chemistry I, Department of Medical Biochemistry & Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Jaakko S Teppo
- Drug Research Program and Division of Pharmaceutical Chemistry and Technology, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland
| | - Roman A Zubarev
- Division of Chemistry I, Department of Medical Biochemistry & Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Ákos Végvári
- Division of Chemistry I, Department of Medical Biochemistry & Biophysics, Karolinska Institutet, Stockholm, Sweden.
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28
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Orsburn BC. Analyzing Posttranslational Modifications in Single Cells. Methods Mol Biol 2024; 2817:145-156. [PMID: 38907153 DOI: 10.1007/978-1-0716-3934-4_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/23/2024]
Abstract
With the rapid expansion of capabilities in the analysis of proteins in single cells, we can now identify multiple classes of protein posttranslational modifications on some of these proteins. Each new technology that has increased the number of proteins measured per cell has likewise increased our ability to identify and quantify modified peptides. In this chapter, I will discuss our current capabilities, concerns, and challenges specific to this emerging field of study and the inevitable demand for services, providing a general review of concepts that should be considered.
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Affiliation(s)
- Benjamin C Orsburn
- The Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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29
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Grégoire S, Vanderaa C, Dit Ruys SP, Kune C, Mazzucchelli G, Vertommen D, Gatto L. Standardized Workflow for Mass-Spectrometry-Based Single-Cell Proteomics Data Processing and Analysis Using the scp Package. Methods Mol Biol 2024; 2817:177-220. [PMID: 38907155 DOI: 10.1007/978-1-0716-3934-4_14] [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
Mass-spectrometry (MS)-based single-cell proteomics (SCP) explores cellular heterogeneity by focusing on the functional effectors of the cells-proteins. However, extracting meaningful biological information from MS data is far from trivial, especially with single cells. Currently, data analysis workflows are substantially different from one research team to another. Moreover, it is difficult to evaluate pipelines as ground truths are missing. Our team has developed the R/Bioconductor package called scp to provide a standardized framework for SCP data analysis. It relies on the widely used QFeatures and SingleCellExperiment data structures. In addition, we used a design containing cell lines mixed in known proportions to generate controlled variability for data analysis benchmarking. In this chapter, we provide a flexible data analysis protocol for SCP data using the scp package together with comprehensive explanations at each step of the processing. Our main steps are quality control on the feature and cell level, aggregation of the raw data into peptides and proteins, normalization, and batch correction. We validate our workflow using our ground truth data set. We illustrate how to use this modular, standardized framework and highlight some crucial steps.
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Affiliation(s)
- Samuel Grégoire
- Computational Biology and Bioinformatics Unit, de Duve Institute, UCLouvain, Brussels, Belgium
| | - Christophe Vanderaa
- Computational Biology and Bioinformatics Unit, de Duve Institute, UCLouvain, Brussels, Belgium
| | | | - Christopher Kune
- Laboratory of Mass Spectrometry, MolSys Research Unit, University of Liège, Liège, Belgium
| | - Gabriel Mazzucchelli
- Laboratory of Mass Spectrometry, MolSys Research Unit, University of Liège, Liège, Belgium
- GIGA Proteomics Facility, University of Liège, Liège, Belgium
| | - Didier Vertommen
- Protein Phosphorylation Unit, de Duve Institute, UCLouvain, Brussels, Belgium
| | - Laurent Gatto
- Computational Biology and Bioinformatics Unit, de Duve Institute, UCLouvain, Brussels, Belgium.
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30
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Xu Z, Zou R, Horn NC, Kitata RB, Shi T. Robust Surfactant-Assisted One-Pot Sample Preparation for Label-Free Single-Cell and Nanoscale Proteomics. Methods Mol Biol 2024; 2817:85-96. [PMID: 38907149 DOI: 10.1007/978-1-0716-3934-4_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/23/2024]
Abstract
With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk cells. However, such bulk measurement obscures cell-to-cell heterogeneity, precluding proteome profiling of single cells and small numbers of cells of interest. To address this issue, in the recent 5 years, there has been a surge of small sample preparation methods developed for robust and effective collection and processing of single cells and small numbers of cells for in-depth MS-based proteome profiling. Based on their broad accessibility, they can be categorized into two types: methods based on specific devices and those based on standard PCR tubes or multi-well plates. In this chapter, we describe the detailed protocol of our recently developed, easily adoptable, Surfactant-assisted One-Pot (SOP) sample preparation coupled with MS method termed SOP-MS for label-free single-cell and nanoscale proteomics. SOP-MS capitalizes on the combination of an MS-compatible surfactant, n-dodecyl-β-D-maltoside (DDM), and standard low-bind PCR tube or multi-well plate for "all-in-one" one-pot sample preparation without sample transfer. With its robust and convenient features, SOP-MS can be readily implemented in any MS laboratory for single-cell and nanoscale proteomics. With further improvements in MS detection sensitivity and sample throughput, we believe that SOP-MS could open an avenue for single-cell proteomics with broad applicability in biological and biomedical research.
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Affiliation(s)
- Zhangyang Xu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Rongge Zou
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Nina C Horn
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Reta Birhanu Kitata
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Tujin Shi
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
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31
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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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32
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Mayer RL, Mechtler K. Immunopeptidomics in the Era of Single-Cell Proteomics. BIOLOGY 2023; 12:1514. [PMID: 38132340 PMCID: PMC10740491 DOI: 10.3390/biology12121514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/04/2023] [Accepted: 12/06/2023] [Indexed: 12/23/2023]
Abstract
Immunopeptidomics, as the analysis of antigen peptides being presented to the immune system via major histocompatibility complexes (MHC), is being seen as an imperative tool for identifying epitopes for vaccine development to treat cancer and viral and bacterial infections as well as parasites. The field has made tremendous strides over the last 25 years but currently still faces challenges in sensitivity and throughput for widespread applications in personalized medicine and large vaccine development studies. Cutting-edge technological advancements in sample preparation, liquid chromatography as well as mass spectrometry, and data analysis, however, are currently transforming the field. This perspective showcases how the advent of single-cell proteomics has accelerated this transformation of immunopeptidomics in recent years and will pave the way for even more sensitive and higher-throughput immunopeptidomics analyses.
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Affiliation(s)
- Rupert L. Mayer
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter, 1030 Vienna, Austria
| | - Karl Mechtler
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter, 1030 Vienna, Austria
- Gregor Mendel Institute of Molecular Plant Biology (GMI), Austrian Academy of Sciences, Vienna BioCenter (VBC), 1030 Vienna, Austria
- Institute of Molecular Biotechnology (IMBA), Austrian Academy of Sciences, Vienna BioCenter (VBC), 1030 Vienna, Austria
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33
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Jenkins C, Orsburn BC. Simple Tool for Rapidly Assessing the Quality of Multiplexed Single Cell Proteomics Data. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2615-2619. [PMID: 37991989 DOI: 10.1021/jasms.3c00238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Recent advances in the sensitivity and speed of mass spectrometers coupled with improved sample preparation methods have enabled the field of single cell proteomics to proliferate. While heavy development is occurring in the label free space, dramatic improvements in throughput are provided by multiplexing with tandem mass tags. Hundreds or thousands of single cells can be analyzed with this method, yielding large data sets which may contain poor data arising from loss of material during cell sorting or poor digestion, labeling, and lysis. To date, no tools have been described that can assess data quality prior to data processing. We present herein a lightweight python script and accompanying graphic user interface that can rapidly quantify reporter ion peaks within each MS/MS spectrum in a file. With simple summary reports, we can identify single cell samples that fail to pass a set quality threshold, thus reducing analysis time waste. In addition, this tool, Diagnostic Ion Data Analysis Reduction (DIDAR), will create reduced MGF files containing only spectra possessing a user-specified number of single cell reporter ions. By reducing the number of spectra that have excessive zero values, we can speed up sample processing with little loss in data completeness as these spectra are removed in later stages in data processing workflows. DIDAR and the DIDAR GUI are compatible with all modern operating systems and are available at: https://github.com/orsburn/DIDARSCPQC. All files described in this study are available at www.massive.ucsd.edu as accession MSV000088887.
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Affiliation(s)
- Conor Jenkins
- The University of Maryland, College Park, Maryland 20737, United States
| | - Benjamin C Orsburn
- The Johns Hopkins University Medical School, Baltimore, Maryland 21215, United States
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34
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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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35
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Lanz MC, Fuentes Valenzuela L, Elias JE, Skotheim JM. Cell Size Contributes to Single-Cell Proteome Variation. J Proteome Res 2023; 22:3773-3779. [PMID: 37910793 PMCID: PMC10802137 DOI: 10.1021/acs.jproteome.3c00441] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2023]
Abstract
Accurate measurements of the molecular composition of single cells will be necessary for understanding the relationship between gene expression and function in diverse cell types. One of the most important phenotypes that differs between cells is their size, which was recently shown to be an important determinant of proteome composition in populations of similarly sized cells. We, therefore, sought to test if the effects of the cell size on protein concentrations were also evident in single-cell proteomics data. Using the relative concentrations of a set of reference proteins to estimate a cell's DNA-to-cell volume ratio, we found that differences in the cell size explain a significant amount of cell-to-cell variance in two published single-cell proteome data sets.
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Affiliation(s)
- Michael C Lanz
- Department of Biology, Stanford University, Stanford, California 94305, United States
- Chan Zuckerberg Biohub, Stanford, California 94305, United States
| | | | - Joshua E Elias
- Chan Zuckerberg Biohub, Stanford, California 94305, United States
| | - Jan M Skotheim
- Department of Biology, Stanford University, Stanford, California 94305, United States
- Chan Zuckerberg Biohub, Stanford, California 94305, United States
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36
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Leduc A, Koury L, Cantlon J, Slavov N. Massively parallel sample preparation for multiplexed single-cell proteomics using nPOP. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.27.568927. [PMID: 38076795 PMCID: PMC10705290 DOI: 10.1101/2023.11.27.568927] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Single-cell proteomics by mass spectrometry (MS) allows quantifying proteins with high specificity and sensitivity. To increase its throughput, we developed nPOP, a method for parallel preparation of thousands of single cells in nanoliter volume droplets deposited on glass slides. Here, we describe its protocol with emphasis on its flexibility to prepare samples for different multiplexed MS methods. An implementation with plexDIA demonstrates accurate quantification of about 3,000 - 3,700 proteins per human cell. The protocol is implemented on the CellenONE instrument and uses readily available consumables, which should facilitate broad adoption. nPOP can be applied to all samples that can be processed to a single-cell suspension. It takes 1 or 2 days to prepare over 3,000 single cells. We provide metrics and software for quality control that can support the robust scaling of nPOP to higher plex reagents for achieving reliable high-throughput single-cell protein analysis.
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Affiliation(s)
- Andrew Leduc
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA 02115, USA
| | - Luke Koury
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA 02115, USA
| | | | - Nikolai Slavov
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, Boston, MA 02115, USA
- Parallel Squared Technology Institute, Watertown, MA 02472, USA
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37
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Davis S, Scott C, Oetjen J, Charles PD, Kessler BM, Ansorge O, Fischer R. Deep topographic proteomics of a human brain tumour. Nat Commun 2023; 14:7710. [PMID: 38001067 PMCID: PMC10673928 DOI: 10.1038/s41467-023-43520-8] [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: 03/01/2023] [Accepted: 11/13/2023] [Indexed: 11/26/2023] Open
Abstract
The spatial organisation of cellular protein expression profiles within tissue determines cellular function and is key to understanding disease pathology. To define molecular phenotypes in the spatial context of tissue, there is a need for unbiased, quantitative technology capable of mapping proteomes within tissue structures. Here, we present a workflow for spatially-resolved, quantitative proteomics of tissue that generates maps of protein abundance across tissue slices derived from a human atypical teratoid-rhabdoid tumour at three spatial resolutions, the highest being 40 µm, to reveal distinct abundance patterns of thousands of proteins. We employ spatially-aware algorithms that do not require prior knowledge of the fine tissue structure to detect proteins and pathways with spatial abundance patterns and correlate proteins in the context of tissue heterogeneity and cellular features such as extracellular matrix or proximity to blood vessels. We identify PYGL, ASPH and CD45 as spatial markers for tumour boundary and reveal immune response-driven, spatially-organised protein networks of the extracellular tumour matrix. Overall, we demonstrate spatially-aware deep proteo-phenotyping of tissue heterogeneity, to re-define understanding tissue biology and pathology at the molecular level.
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Affiliation(s)
- Simon Davis
- Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
- Chinese Academy for Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
| | - Connor Scott
- Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Janina Oetjen
- Bruker Daltonics GmbH & Co. KG, Fahrenheitstraße 4, 28359, Bremen, Germany
| | - Philip D Charles
- Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
| | - Benedikt M Kessler
- Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
- Chinese Academy for Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK
| | - Olaf Ansorge
- Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Roman Fischer
- Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK.
- Chinese Academy for Medical Sciences Oxford Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, UK.
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38
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Orsburn BC. An integrated method for single cell proteomics with simultaneous measurements of intracellular drug concentration implicates new mechanisms for adaptation to KRAS G12D inhibitors. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.18.567669. [PMID: 38014353 PMCID: PMC10680798 DOI: 10.1101/2023.11.18.567669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
It is well established that a population of single human cells will often respond to the same drug treatment in a heterogeneous manner. In the context of chemotherapeutics, these diverse responses may lead to individual adaptation mechanisms and ultimately multiple distinct methods of resistance. The obvious question from a pharmacology perspective is how intracellular concentrations of active drug varies between individual cells, and what role does that variation play in drug response heterogeneity? To date, no integrated methods for rapidly measuring intracellular drug levels while simultaneously measuring drug responses have been described. This study describes a method for single cell preparation that allows proteins to be extracted and digested from single cells while maintaining conditions for small molecules to be simultaneously measured. The method as described allows up to 40 cells to be analyzed per instrument per day. When applied to a KRASG12D small molecule inhibitor I observe a wide degree of intracellular levels of the drug, and that proteomic responses largely stratify based on the concentration of drug within each single cell. Further work is in progress to develop and standardize this method and - more importantly - to normalize drug measurements against direct measurements of cell volume. However, these preliminary results appear promising for the identification of single cells with unique drug response mechanisms. All data described in this study has been made publicly available through the ProteomeXchange consortium under accession PXD046002.
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Affiliation(s)
- Benjamin C. Orsburn
- The Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, USA, 21205
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39
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Ivanov A, Marie AL, Gao Y. In-capillary sample processing coupled to label-free capillary electrophoresis-mass spectrometry to decipher the native N-glycome of single mammalian cells and ng-level blood isolates. RESEARCH SQUARE 2023:rs.3.rs-3500983. [PMID: 38014012 PMCID: PMC10680937 DOI: 10.21203/rs.3.rs-3500983/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
The development of reliable single-cell dispensers and substantial sensitivity improvement in mass spectrometry made proteomic profiling of individual cells achievable. Yet, there are no established methods for single-cell glycome analysis due to the inability to amplify glycans and sample losses associated with sample processing and glycan labeling. In this work, we developed an integrated platform coupling online in-capillary sample processing with high-sensitivity label-free capillary electrophoresis-mass spectrometry for N-glycan profiling of single mammalian cells. Direct and unbiased characterization and quantification of single-cell surface N-glycomes were demonstrated for HeLa and U87 cells, with the detection of up to 100 N-glycans per single cell. Interestingly, N-glycome alterations were unequivocally detected at the single-cell level in HeLa and U87 cells stimulated with lipopolysaccharide. The developed workflow was also applied to the profiling of ng-level amounts of blood-derived protein, extracellular vesicle, and total plasma isolates, resulting in over 170, 220, and 370 quantitated N-glycans, respectively.
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40
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Ahmad R, Budnik B. A review of the current state of single-cell proteomics and future perspective. Anal Bioanal Chem 2023; 415:6889-6899. [PMID: 37285026 PMCID: PMC10632274 DOI: 10.1007/s00216-023-04759-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 05/12/2023] [Accepted: 05/16/2023] [Indexed: 06/08/2023]
Abstract
Single-cell methodologies and technologies have started a revolution in biology which until recently has primarily been limited to deep sequencing and imaging modalities. With the advent and subsequent torrid development of single-cell proteomics over the last 5 years, despite the fact that proteins cannot be amplified like transcripts, it has now become abundantly clear that it is a worthy complement to single-cell transcriptomics. In this review, we engage in an assessment of the current state of the art of single-cell proteomics including workflow, sample preparation techniques, instrumentation, and biological applications. We investigate the challenges associated with working with very small sample volumes and the acute need for robust statistical methods for data interpretation. We delve into what we believe is a promising future for biological research at single-cell resolution and highlight some of the exciting discoveries that already have been made using single-cell proteomics, including the identification of rare cell types, characterization of cellular heterogeneity, and investigation of signaling pathways and disease mechanisms. Finally, we acknowledge that there are a number of outstanding and pressing problems that the scientific community vested in advancing this technology needs to resolve. Of prime importance is the need to set standards so that this technology becomes widely accessible allowing novel discoveries to be easily verifiable. We conclude with a plea to solve these problems rapidly so that single-cell proteomics can be part of a robust, high-throughput, and scalable single-cell multi-omics platform that can be ubiquitously applied to elucidating deep biological insights into the diagnosis and treatment of all diseases that afflict us.
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Affiliation(s)
- Rushdy Ahmad
- Wyss Institute for Biologically Inspired Engineering at Harvard University, 3 Blackfan Circle, Boston, MA, 02115, USA
| | - Bogdan Budnik
- Wyss Institute for Biologically Inspired Engineering at Harvard University, 3 Blackfan Circle, Boston, MA, 02115, USA.
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41
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Stepler KE, Hannah SC, Taneyhill LA, Nemes P. Deep Proteome of the Developing Chick Midbrain. J Proteome Res 2023; 22:3264-3274. [PMID: 37616547 DOI: 10.1021/acs.jproteome.3c00291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
The epithelial-to-mesenchymal transition (EMT) and migration of cranial neural crest cells within the midbrain are critical processes that permit proper craniofacial patterning in the early embryo. Disruptions in these processes not only impair development but also lead to various diseases, underscoring the need for their detailed understanding at the molecular level. The chick embryo has served historically as an excellent model for human embryonic development, including cranial neural crest cell EMT and migration. While these developmental events have been characterized transcriptionally, studies at the protein level have not been undertaken to date. Here, we applied mass spectrometry (MS)-based proteomics to establish a deep proteomics profile of the chick midbrain region during early embryonic development. Our proteomics method combines optimal lysis conditions, offline fractionation, separation on a nanopatterned stationary phase (μPAC) using nanoflow liquid chromatography, and detection using quadrupole-ion trap-Orbitrap tribrid high-resolution tandem MS. Identification of >5900 proteins and >450 phosphoproteins in this study marks the deepest coverage of the chick midbrain proteome to date. These proteins have known roles in pathways related to neural crest cell EMT and migration such as signaling, proteolysis/extracellular matrix remodeling, and transcriptional regulation. This study offers valuable insight into important developmental processes occurring in the midbrain region and demonstrates the utility of proteomics for characterization of tissue microenvironments during chick embryogenesis.
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Affiliation(s)
- Kaitlyn E Stepler
- Department of Chemistry & Biochemistry, University of Maryland, College Park, Maryland 20742, United States
| | - Seth C Hannah
- Department of Chemistry & Biochemistry, University of Maryland, College Park, Maryland 20742, United States
- Department of Animal & Avian Sciences, University of Maryland, College Park, Maryland 20742, United States
| | - Lisa A Taneyhill
- Department of Animal & Avian Sciences, University of Maryland, College Park, Maryland 20742, United States
| | - Peter Nemes
- Department of Chemistry & Biochemistry, University of Maryland, College Park, Maryland 20742, United States
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42
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Végvári Á, Zhang X, Zubarev RA. Toward Single Bacterium Proteomics. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2098-2106. [PMID: 37713396 PMCID: PMC10557376 DOI: 10.1021/jasms.3c00242] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 08/14/2023] [Accepted: 09/12/2023] [Indexed: 09/17/2023]
Abstract
Bacteria are orders of magnitude smaller than mammalian cells, and while single cell proteomics (SCP) currently detects and quantifies several thousands of proteins per mammalian cell, it is not clear whether conventional SCP methods will be suitable for bacteria. Here we report on the first successful attempt to detect proteins from individual Escherichia coli bacteria, with validation of our findings by comparison with two bacteria samples and bulk proteomics data. Data are available via ProteomeXchange with the identifier PXD043473.
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Affiliation(s)
- Ákos Végvári
- Division of Chemistry I,
Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - Xuepei Zhang
- Division of Chemistry I,
Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - Roman A. Zubarev
- Division of Chemistry I,
Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-171 77 Stockholm, Sweden
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43
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Sanchez-Avila X, Truong T, Xie X, Webber KGI, Johnston SM, Lin HJL, Axtell NB, Puig-Sanvicens V, Kelly RT. Easy and Accessible Workflow for Label-Free Single-Cell Proteomics. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2374-2380. [PMID: 37594399 PMCID: PMC11002963 DOI: 10.1021/jasms.3c00240] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/19/2023]
Abstract
Single-cell proteomics (SCP) can provide information that is unattainable through either bulk-scale protein measurements or single-cell profiling of other omes. Maximizing proteome coverage often requires custom instrumentation, consumables, and reagents for sample processing and separations, which has limited the accessibility of SCP to a small number of specialized laboratories. Commercial platforms have become available for SCP cell isolation and sample preparation, but the high cost of these platforms and the technical expertise required for their operation place them out of reach of many interested laboratories. Here, we assessed the new HP D100 Single Cell Dispenser for label-free SCP. The low-cost instrument proved highly accurate and reproducible for dispensing reagents in the range from 200 nL to 2 μL. We used the HP D100 to isolate and prepare single cells for SCP within 384-well PCR plates. When the well plates were immediately centrifuged following cell dispensing and again after reagent dispensing, we found that ∼97% of wells that were identified in the instrument software as containing a single cell indeed provided the proteome coverage expected of a single cell. This commercial dispenser combined with one-step sample processing provides a very rapid and easy-to-use workflow for SCP with no reduction in proteome coverage relative to a nanowell-based workflow, and the commercial well plates also facilitate autosampling with unmodified instrumentation. Single-cell samples were analyzed using home-packed 30 μm i.d. nanoLC columns as well as commercially available 50 μm i.d. columns. The commercial columns resulted in ∼35% fewer identified proteins. However, combined with the well plate-based preparation platform, the presented workflow provides a fully commercial and relatively low-cost alternative for SCP sample preparation and separation, which should greatly broaden the accessibility of SCP to other laboratories.
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Affiliation(s)
- Ximena Sanchez-Avila
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Xiaofeng Xie
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Kei G I Webber
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - S Madisyn Johnston
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Hsien-Jung L Lin
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Nathaniel B Axtell
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | | | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
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44
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Petrosius V, Aragon-Fernandez P, Üresin N, Kovacs G, Phlairaharn T, Furtwängler B, Op De Beeck J, Skovbakke SL, Goletz S, Thomsen SF, Keller UAD, Natarajan KN, Porse BT, Schoof EM. Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition. Nat Commun 2023; 14:5910. [PMID: 37737208 PMCID: PMC10517177 DOI: 10.1038/s41467-023-41602-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 09/07/2023] [Indexed: 09/23/2023] Open
Abstract
Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount of material encapsulated in a single cell however, raises significant technical challenges to molecular profiling. Due to extensive optimization efforts, single-cell proteomics by Mass Spectrometry (scp-MS) has emerged as a powerful tool to facilitate proteome profiling from ultra-low amounts of input, although further development is needed to realize its full potential. To this end, we carry out comprehensive analysis of orbitrap-based data-independent acquisition (DIA) for limited material proteomics. Notably, we find a fundamental difference between optimal DIA methods for high- and low-load samples. We further improve our low-input DIA method by relying on high-resolution MS1 quantification, thus enhancing sensitivity by more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we are able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we demonstrate the capability of our approach by profiling mouse embryonic stem cell culture conditions, showcasing heterogeneity in global proteomes and highlighting distinct differences in key metabolic enzyme expression in distinct cell subclusters.
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Affiliation(s)
- Valdemaras Petrosius
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Pedro Aragon-Fernandez
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Nil Üresin
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
| | - Gergo Kovacs
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Teeradon Phlairaharn
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
- The Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, 2200, Denmark
- Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Martinsried, 82152, Germany
- MaxPlanck Institute of Biochemistry, Martinsried, 82152, Germany
| | - Benjamin Furtwängler
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
| | - Jeff Op De Beeck
- Thermo Fisher Scientific, Technologiepark-Zwijnaarde 82, B-9052, Gent, Belgium
| | - Sarah L Skovbakke
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Steffen Goletz
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Simon Francis Thomsen
- Department of Dermatology, Bispebjerg Hospital and Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ulrich Auf dem Keller
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Kedar N Natarajan
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark
| | - Bo T Porse
- The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
- Dept of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Erwin M Schoof
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs, Lyngby, Denmark.
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45
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Woessmann J, Petrosius V, Üresin N, Kotol D, Aragon-Fernandez P, Hober A, auf dem Keller U, Edfors F, Schoof EM. Assessing the Role of Trypsin in Quantitative Plasma and Single-Cell Proteomics toward Clinical Application. Anal Chem 2023; 95:13649-13658. [PMID: 37639361 PMCID: PMC10500548 DOI: 10.1021/acs.analchem.3c02543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 08/08/2023] [Indexed: 08/31/2023]
Abstract
Mass spectrometry-based bottom-up proteomics is rapidly evolving and routinely applied in large-scale biomedical studies. Proteases are a central component of every bottom-up proteomics experiment, digesting proteins into peptides. Trypsin has been the most widely applied protease in proteomics due to its characteristics. With ever-larger cohort sizes and possible future clinical application of mass spectrometry-based proteomics, the technical impact of trypsin becomes increasingly relevant. To assess possible biases introduced by trypsin digestion, we evaluated the impact of eight commercially available trypsins in a variety of bottom-up proteomics experiments and across a range of protease concentrations and storage times. To investigate the universal impact of these technical attributes, we included bulk HeLa cell lysate, human plasma, and single HEK293 cells, which were analyzed over a range of selected reaction monitoring (SRM), data-independent acquisition (DIA), and data-dependent acquisition (DDA) instrument methods on three LC-MS instruments. The quantification methods employed encompassed both label-free approaches and absolute quantification utilizing spike-in heavy-labeled recombinant protein fragment standards. Based on this extensive data set, we report variations between commercial trypsins, their source, and their concentration. Furthermore, we provide suggestions on the handling of trypsin in large-scale studies.
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Affiliation(s)
- Jakob Woessmann
- Department
of Biotechnology and Biomedicine, Technical
University of Denmark, 2800 Kgs. Lyngby, Denmark
- Science
for Life Laboratory, KTH—Royal Institute
of Technology, SE-171 65 Solna, Sweden
- Department
of Protein Science, KTH—Royal Institute
of Technology, SE-106 91 Stockholm, Sweden
| | - Valdemaras Petrosius
- Department
of Biotechnology and Biomedicine, Technical
University of Denmark, 2800 Kgs. Lyngby, Denmark
| | - Nil Üresin
- The
Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
- Biotech
Research and Innovation Centre (BRIC), University
of Copenhagen, 2200 Copenhagen, Denmark
| | - David Kotol
- Science
for Life Laboratory, KTH—Royal Institute
of Technology, SE-171 65 Solna, Sweden
- Department
of Protein Science, KTH—Royal Institute
of Technology, SE-106 91 Stockholm, Sweden
| | - Pedro Aragon-Fernandez
- Department
of Biotechnology and Biomedicine, Technical
University of Denmark, 2800 Kgs. Lyngby, Denmark
| | - Andreas Hober
- Science
for Life Laboratory, KTH—Royal Institute
of Technology, SE-171 65 Solna, Sweden
- Department
of Protein Science, KTH—Royal Institute
of Technology, SE-106 91 Stockholm, Sweden
| | - Ulrich auf dem Keller
- Department
of Biotechnology and Biomedicine, Technical
University of Denmark, 2800 Kgs. Lyngby, Denmark
| | - Fredrik Edfors
- Science
for Life Laboratory, KTH—Royal Institute
of Technology, SE-171 65 Solna, Sweden
- Department
of Protein Science, KTH—Royal Institute
of Technology, SE-106 91 Stockholm, Sweden
| | - Erwin M. Schoof
- Department
of Biotechnology and Biomedicine, Technical
University of Denmark, 2800 Kgs. Lyngby, Denmark
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46
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Thielert M, Itang ECM, Ammar C, Rosenberger FA, Bludau I, Schweizer L, Nordmann TM, Skowronek P, Wahle M, Zeng W, Zhou X, Brunner A, Richter S, Levesque MP, Theis FJ, Steger M, Mann M. Robust dimethyl-based multiplex-DIA doubles single-cell proteome depth via a reference channel. Mol Syst Biol 2023; 19:e11503. [PMID: 37602975 PMCID: PMC10495816 DOI: 10.15252/msb.202211503] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 07/17/2023] [Accepted: 07/25/2023] [Indexed: 08/22/2023] Open
Abstract
Single-cell proteomics aims to characterize biological function and heterogeneity at the level of proteins in an unbiased manner. It is currently limited in proteomic depth, throughput, and robustness, which we address here by a streamlined multiplexed workflow using data-independent acquisition (mDIA). We demonstrate automated and complete dimethyl labeling of bulk or single-cell samples, without losing proteomic depth. Lys-N digestion enables five-plex quantification at MS1 and MS2 level. Because the multiplexed channels are quantitatively isolated from each other, mDIA accommodates a reference channel that does not interfere with the target channels. Our algorithm RefQuant takes advantage of this and confidently quantifies twice as many proteins per single cell compared to our previous work (Brunner et al, PMID 35226415), while our workflow currently allows routine analysis of 80 single cells per day. Finally, we combined mDIA with spatial proteomics to increase the throughput of Deep Visual Proteomics seven-fold for microdissection and four-fold for MS analysis. Applying this to primary cutaneous melanoma, we discovered proteomic signatures of cells within distinct tumor microenvironments, showcasing its potential for precision oncology.
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Affiliation(s)
- Marvin Thielert
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Ericka CM Itang
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Constantin Ammar
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Florian A Rosenberger
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Isabell Bludau
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Lisa Schweizer
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Thierry M Nordmann
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Patricia Skowronek
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Maria Wahle
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Wen‐Feng Zeng
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Xie‐Xuan Zhou
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
| | - Andreas‐David Brunner
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
- Boehringer Ingelheim Pharma GmbH & Co. KG, Drug Discovery SciencesBiberach an der RissGermany
| | - Sabrina Richter
- Helmholtz Zentrum München – German Research Center for Environmental HealthInstitute of Computational BiologyNeuherbergGermany
- TUM School of Life Sciences WeihenstephanTechnical University of MunichFreisingGermany
| | - Mitchell P Levesque
- Department of DermatologyUniversity of Zurich, University of Zurich HospitalZurichSwitzerland
| | - Fabian J Theis
- Helmholtz Zentrum München – German Research Center for Environmental HealthInstitute of Computational BiologyNeuherbergGermany
- TUM School of Life Sciences WeihenstephanTechnical University of MunichFreisingGermany
| | - Martin Steger
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
- New address: NEOsphere Biotechnologies GmbHPlaneggGermany
| | - Matthias Mann
- Department of Proteomics and Signal TransductionMax Planck Institute of BiochemistryMartinsriedGermany
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical SciencesUniversity of CopenhagenCopenhagenDenmark
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47
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Johnston SM, Webber KGI, Xie X, Truong T, Nydegger A, Lin HJL, Nwosu A, Zhu Y, Kelly RT. Rapid, One-Step Sample Processing for Label-Free Single-Cell Proteomics. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:1701-1707. [PMID: 37410391 PMCID: PMC11017373 DOI: 10.1021/jasms.3c00159] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/07/2023]
Abstract
Sample preparation for single-cell proteomics is generally performed in a one-pot workflow with multiple dispensing and incubation steps. These hours-long processes can be labor intensive and lead to long sample-to-answer times. Here we report a sample preparation method that achieves cell lysis, protein denaturation, and digestion in 1 h using commercially available high-temperature-stabilized proteases with a single reagent dispensing step. Four different one-step reagent compositions were evaluated, and the mixture providing the highest proteome coverage was compared to the previously employed multistep workflow. The one-step preparation increases proteome coverage relative to the previous multistep workflow while minimizing labor input and the possibility of human error. We also compared sample recovery between previously used microfabricated glass nanowell chips and injection-molded polypropylene chips and found the polypropylene provided improved proteome coverage. Combined, the one-step sample preparation and the polypropylene substrates enabled the identification of an average of nearly 2400 proteins per cell using a standard data-dependent workflow with Orbitrap mass spectrometers. These advances greatly simplify sample preparation for single-cell proteomics and broaden accessibility with no compromise in terms of proteome coverage.
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Affiliation(s)
- S Madisyn Johnston
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Kei G I Webber
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Xiaofeng Xie
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Alissia Nydegger
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Hsien-Jung L Lin
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Andikan Nwosu
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Ying Zhu
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
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48
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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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49
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Veličković M, Fillmore TL, Attah K, Posso C, Pino JC, Zhao R, Williams SM, Veličković D, Jacobs JM, Burnum-Johnson KE, Zhu Y, Piehowski PD. Coupling microdroplet-based sample preparation, multiplexed isobaric labeling, and nanoflow peptide fractionation for deep proteome profiling of tissue microenvironment. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.13.531822. [PMID: 36993277 PMCID: PMC10055005 DOI: 10.1101/2023.03.13.531822] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity at a cell-type-specific level to better understand and predict the function of complex biological systems, such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverages due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (Microdroplet Processing in One pot for Trace Samples), the multiplexed isobaric labelling, and a nanoflow peptide fractionation approach. The integrated workflow allowed to maximize proteome coverage of laser-isolated tissue samples containing nanogram proteins. We demonstrated the deep spatial proteomics can quantify more than 5,000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 µm2) and reveal unique islet microenvironments.
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