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Campbell AJ, Cakar S, Palstrøm NB, Riber LP, Rasmussen LM, Beck HC. A carrier-based quantitative proteomics method applied to biomarker discovery in pericardial fluid. Mol Cell Proteomics 2024:100812. [PMID: 39004188 DOI: 10.1016/j.mcpro.2024.100812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 07/03/2024] [Accepted: 07/10/2024] [Indexed: 07/16/2024] Open
Abstract
Data-dependent liquid chromatography tandem mass spectrometry (LC-MS/MS) is challenged by the large concentration range of proteins in plasma and related fluids. We adapted the SCoPE method from single-cell proteomics to pericardial fluid, where a myocardial tissue carrier was used to aid protein quantification. The carrier proteome and patient samples were labeled with distinct isobaric labels, which allowed separate quantification. Undepleted pericardial fluid from patients with type 2 diabetes mellitus and/or heart failure undergoing heart surgery was analyzed with either a traditional LC-MS/MS method or with the carrier proteome. In total, 1398 proteins were quantified with a carrier, compared to 265 without, and a higher proportion of these proteins were of myocardial origin. The number of differentially expressed proteins also increased nearly four-fold. For patients with both heart failure and type 2 diabetes mellitus, pathway analysis of upregulated proteins demonstrated enrichment of immune activation, blood coagulation, and stress pathways. Overall, our work demonstrates the applicability of a carrier for enhanced protein quantification in challenging biological matrices such as pericardial fluid, with potential applications for biomarker discovery. Mass spectrometry data are available via ProteomeXchange with identifier PXD053450.
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Affiliation(s)
- Amanda J Campbell
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark; Center for Clinical Proteomics (CCP), Odense University Hospital, Odense, Denmark
| | - Samir Cakar
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark; Center for Clinical Proteomics (CCP), Odense University Hospital, Odense, Denmark
| | - Nicolai B Palstrøm
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark; Center for Clinical Proteomics (CCP), Odense University Hospital, Odense, Denmark; Department of Clinical Research, Faculty of Health Science, University of Southern Denmark, Odense, Denmark
| | - Lars P Riber
- Department of Cardiac, Thoracic and Vascular Surgery, Odense University Hospital, Odense, Denmark; Department of Clinical Research, Faculty of Health Science, University of Southern Denmark, Odense, Denmark
| | - Lars M Rasmussen
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark; Center for Clinical Proteomics (CCP), Odense University Hospital, Odense, Denmark; Center for Individualized Medicine in Arterial Diseases (CIMA), Odense University Hospital, Odense, Denmark; Department of Clinical Research, Faculty of Health Science, University of Southern Denmark, Odense, Denmark
| | - Hans C Beck
- Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark; Center for Clinical Proteomics (CCP), Odense University Hospital, Odense, Denmark; Center for Individualized Medicine in Arterial Diseases (CIMA), Odense University Hospital, Odense, Denmark; Department of Clinical Research, Faculty of Health Science, University of Southern Denmark, Odense, Denmark
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2
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Yeo S, Jang J, Jung HJ, Lee H, Lee S, Choe Y. A Zwitterionic Detergent and Catalyst-Based Single-Cell Proteomics Using a Loss-Free Microhole-Collection Disc. Anal Chem 2024. [PMID: 38991018 DOI: 10.1021/acs.analchem.4c00158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2024]
Abstract
Recent advances in single-cell proteomics have solved many bottlenecks, such as throughput, sample recovery, and scalability via nanoscale sample handling. In this study, we aimed for a sensitive mass spectrometry (MS) analysis capable of handling single cells with a conventional mass spectrometry workflow without additional equipment. We achieved seamless cell lysis and TMT labeling in a micro-HOLe Disc (microHOLD) by developing a mass-compatible single solution based on a zwitterionic detergent and a catalyst for single-cell lysis and tandem mass tag labeling without a heat incubation step. This method was developed to avoid peptide loss by surface adsorption and buffer or tube changes by collecting tandem mass tag-labeled peptide through microholes placed in the liquid chromatography injection vials in a single solution. We successfully applied the microHOLD single-cell proteomics method for the analysis of proteome reprogramming in hormone-sensitive prostate cells to develop castration-resistant prostate cancer cells. This novel single-cell proteomics method is not limited by cutting-edge nanovolume handling equipment and achieves high throughput and ultrasensitive proteomics analysis of limited samples, such as single cells.
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Affiliation(s)
- Seungeun Yeo
- Developmental disorders & rare diseases Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea
- School of Pharmacy, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Jaemyung Jang
- Developmental disorders & rare diseases Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea
| | - Hyun Jin Jung
- Developmental disorders & rare diseases Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea
| | - Hyeyoung Lee
- Division of Applied Bioengineering, Dong-Eui University, Busan 47340, Republic of Korea
| | - Sangkyu Lee
- School of Pharmacy, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Youngshik Choe
- Developmental disorders & rare diseases Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea
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3
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Nitz AA, Giraldez Chavez JH, Eliason ZG, Payne SH. Are We There Yet? Assessing the Readiness of Single-Cell Proteomics to Answer Biological Hypotheses. J Proteome Res 2024. [PMID: 38981598 DOI: 10.1021/acs.jproteome.4c00091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/11/2024]
Abstract
Single-cell analysis is an active area of research in many fields of biology. Measurements at single-cell resolution allow researchers to study diverse populations without losing biologically meaningful information to sample averages. Many technologies have been used to study single cells, including mass spectrometry-based single-cell proteomics (SCP). SCP has seen a lot of growth over the past couple of years through improvements in data acquisition and analysis, leading to greater proteomic depth. Because method development has been the main focus in SCP, biological applications have been sprinkled in only as proof-of-concept. However, SCP methods now provide significant coverage of the proteome and have been implemented in many laboratories. Thus, a primary question to address in our community is whether the current state of technology is ready for widespread adoption for biological inquiry. In this Perspective, we examine the potential for SCP in three thematic areas of biological investigation: cell annotation, developmental trajectories, and spatial mapping. We identify that the primary limitation of SCP is sample throughput. As proteome depth has been the primary target for method development to date, we advocate for a change in focus to facilitate measuring tens of thousands of single-cell proteomes to enable biological applications beyond proof-of-concept.
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Affiliation(s)
- Alyssa A Nitz
- Biology Department, Brigham Young University, Provo, Utah 84602, United States
| | | | - Zachary G Eliason
- Biology Department, Brigham Young University, Provo, Utah 84602, United States
| | - Samuel H Payne
- Biology Department, Brigham Young University, Provo, Utah 84602, United States
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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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Stelloo S, Alejo-Vinogradova MT, van Gelder CAGH, Zijlmans DW, van Oostrom MJ, Valverde JM, Lamers LA, Rus T, Sobrevals Alcaraz P, Schäfers T, Furlan C, Jansen PWTC, Baltissen MPA, Sonnen KF, Burgering B, Altelaar MAFM, Vos HR, Vermeulen M. Deciphering lineage specification during early embryogenesis in mouse gastruloids using multilayered proteomics. Cell Stem Cell 2024; 31:1072-1090.e8. [PMID: 38754429 DOI: 10.1016/j.stem.2024.04.017] [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: 04/24/2023] [Revised: 01/10/2024] [Accepted: 04/19/2024] [Indexed: 05/18/2024]
Abstract
Gastrulation is a critical stage in embryonic development during which the germ layers are established. Advances in sequencing technologies led to the identification of gene regulatory programs that control the emergence of the germ layers and their derivatives. However, proteome-based studies of early mammalian development are scarce. To overcome this, we utilized gastruloids and a multilayered mass spectrometry-based proteomics approach to investigate the global dynamics of (phospho) protein expression during gastruloid differentiation. Our findings revealed many proteins with temporal expression and unique expression profiles for each germ layer, which we also validated using single-cell proteomics technology. Additionally, we profiled enhancer interaction landscapes using P300 proximity labeling, which revealed numerous gastruloid-specific transcription factors and chromatin remodelers. Subsequent degron-based perturbations combined with single-cell RNA sequencing (scRNA-seq) identified a critical role for ZEB2 in mouse and human somitogenesis. Overall, this study provides a rich resource for developmental and synthetic biology communities endeavoring to understand mammalian embryogenesis.
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Affiliation(s)
- Suzan Stelloo
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, 6525 GA Nijmegen, the Netherlands.
| | - Maria Teresa Alejo-Vinogradova
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, 6525 GA Nijmegen, the Netherlands
| | - Charlotte A G H van Gelder
- Molecular Cancer Research, Center for Molecular Medicine, Oncode Institute, University Medical Center Utrecht, Utrecht University, 3584 CG Utrecht, the Netherlands
| | - Dick W Zijlmans
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, 6525 GA Nijmegen, the Netherlands
| | - Marek J van Oostrom
- Hubrecht Institute, KNAW (Royal Netherlands Academy of Arts and Sciences), University Medical Center Utrecht, 3584 CT Utrecht, the Netherlands
| | - Juan Manuel Valverde
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, 3584 CA Utrecht, the Netherlands; Netherlands Proteomics Center, 3584 CH Utrecht, the Netherlands
| | - Lieke A Lamers
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, 6525 GA Nijmegen, the Netherlands
| | - Teja Rus
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, 6525 GA Nijmegen, the Netherlands
| | - Paula Sobrevals Alcaraz
- Molecular Cancer Research, Center for Molecular Medicine, Oncode Institute, University Medical Center Utrecht, Utrecht University, 3584 CG Utrecht, the Netherlands
| | - Tilman Schäfers
- Department of Molecular Developmental Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Radboud University Nijmegen, 6525 GA Nijmegen, the Netherlands
| | - Cristina Furlan
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, 6708 WE Wageningen, the Netherlands
| | - Pascal W T C Jansen
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, 6525 GA Nijmegen, the Netherlands
| | - Marijke P A Baltissen
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, 6525 GA Nijmegen, the Netherlands
| | - Katharina F Sonnen
- Hubrecht Institute, KNAW (Royal Netherlands Academy of Arts and Sciences), University Medical Center Utrecht, 3584 CT Utrecht, the Netherlands
| | - Boudewijn Burgering
- Molecular Cancer Research, Center for Molecular Medicine, Oncode Institute, University Medical Center Utrecht, Utrecht University, 3584 CG Utrecht, the Netherlands
| | - Maarten A F M Altelaar
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, 3584 CA Utrecht, the Netherlands; Netherlands Proteomics Center, 3584 CH Utrecht, the Netherlands
| | - Harmjan R Vos
- Molecular Cancer Research, Center for Molecular Medicine, Oncode Institute, University Medical Center Utrecht, Utrecht University, 3584 CG Utrecht, the Netherlands
| | - Michiel Vermeulen
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, 6525 GA Nijmegen, the Netherlands; Division of Molecular Genetics, Netherlands Cancer Institute, 1066 CX Amsterdam, the Netherlands.
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7
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Xie X, Truong T, Huang S, Johnston SM, Hovanski S, Robinson A, Webber KGI, Lin HJL, Mun DG, Pandey A, Kelly RT. Multicolumn Nanoflow Liquid Chromatography with Accelerated Offline Gradient Generation for Robust and Sensitive Single-Cell Proteome Profiling. Anal Chem 2024; 96:10534-10542. [PMID: 38915247 DOI: 10.1021/acs.analchem.4c00878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Peptide separations that combine high sensitivity, robustness, peak capacity, and throughput are essential for extending bottom-up proteomics to smaller samples including single cells. To this end, we have developed a multicolumn nanoLC system with offline gradient generation. One binary pump generates gradients in an accelerated fashion to support multiple analytical columns, and a single trap column interfaces with all analytical columns to reduce required maintenance and simplify troubleshooting. A high degree of parallelization is possible, as one sample undergoes separation while the next sample plus its corresponding mobile phase gradient are transferred into the storage loop and a third sample is loaded into a sample loop. Selective offline elution from the trap column into the sample loop prevents salts and hydrophobic species from entering the analytical column, thus greatly enhancing column lifetime and system robustness. With this design, samples can be analyzed as fast as every 20 min at a flow rate of just 40 nL/min with close to 100% MS utilization time and continuously for as long as several months without column replacement. We utilized the system to analyze the proteomes of single cells from a multiple myeloma cell line upon treatment with the immunomodulatory imide drug lenalidomide.
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Affiliation(s)
- Xiaofeng Xie
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
- MicrOmics Technologies, LLC, Spanish Fork, Utah 84660, United States
| | - Thy Truong
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
- MicrOmics Technologies, LLC, Spanish Fork, Utah 84660, United States
| | - Siqi Huang
- 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
| | - Simon Hovanski
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Abigail Robinson
- 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
| | - Hsien-Jung L Lin
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Dong-Gi Mun
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55905, United States
| | - Akhilesh Pandey
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55905, United States
- Manipal Academy of Higher Education, Manipal, Karnataka 576104, India
| | - Ryan T Kelly
- Department of Chemistry and Biochemistry, Brigham Young University, Provo, Utah 84602, United States
- MicrOmics Technologies, LLC, Spanish Fork, Utah 84660, United States
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8
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Karpov OA, Stotland A, Raedschelders K, Chazarin B, Ai L, Murray CI, Van Eyk JE. Proteomics of the heart. Physiol Rev 2024; 104:931-982. [PMID: 38300522 DOI: 10.1152/physrev.00026.2023] [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: 07/03/2023] [Revised: 12/25/2023] [Accepted: 01/14/2024] [Indexed: 02/02/2024] Open
Abstract
Mass spectrometry-based proteomics is a sophisticated identification tool specializing in portraying protein dynamics at a molecular level. Proteomics provides biologists with a snapshot of context-dependent protein and proteoform expression, structural conformations, dynamic turnover, and protein-protein interactions. Cardiac proteomics can offer a broader and deeper understanding of the molecular mechanisms that underscore cardiovascular disease, and it is foundational to the development of future therapeutic interventions. This review encapsulates the evolution, current technologies, and future perspectives of proteomic-based mass spectrometry as it applies to the study of the heart. Key technological advancements have allowed researchers to study proteomes at a single-cell level and employ robot-assisted automation systems for enhanced sample preparation techniques, and the increase in fidelity of the mass spectrometers has allowed for the unambiguous identification of numerous dynamic posttranslational modifications. Animal models of cardiovascular disease, ranging from early animal experiments to current sophisticated models of heart failure with preserved ejection fraction, have provided the tools to study a challenging organ in the laboratory. Further technological development will pave the way for the implementation of proteomics even closer within the clinical setting, allowing not only scientists but also patients to benefit from an understanding of protein interplay as it relates to cardiac disease physiology.
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Affiliation(s)
- Oleg A Karpov
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
| | - Aleksandr Stotland
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
| | - Koen Raedschelders
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
| | - Blandine Chazarin
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
| | - Lizhuo Ai
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
| | - Christopher I Murray
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
| | - Jennifer E Van Eyk
- Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States
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9
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Long Q, Zhang P, Ou Y, Li W, Yan Q, Yuan X. Single-cell sequencing advances in research on mesenchymal stem/stromal cells. Hum Cell 2024; 37:904-916. [PMID: 38743204 DOI: 10.1007/s13577-024-01076-9] [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: 02/29/2024] [Accepted: 05/04/2024] [Indexed: 05/16/2024]
Abstract
Mesenchymal stem/stromal cells (MSCs), originating from the mesoderm, represent a multifunctional stem cell population capable of differentiating into diverse cell types and exhibiting a wide range of biological functions. Despite more than half a century of research, MSCs continue to be among the most extensively studied cell types in clinical research projects globally. However, their significant heterogeneity and phenotypic instability have significantly hindered their exploration and application. Single-cell sequencing technology emerges as a powerful tool to address these challenges, offering precise dissection of complex cellular samples. It uncovers the genetic structure and gene expression status of individual contained cells on a massive scale and reveals the heterogeneity among these cells. It links the molecular characteristics of MSCs with their clinical applications, contributing to the advancement of regenerative medicine. With the development and cost reduction of single-cell analysis techniques, sequencing technology is now widely applied in fundamental research and clinical trials. This study aimed to review the application of single-cell sequencing in MSC research and assess its prospects.
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Affiliation(s)
- Qingxi Long
- Department of Neurology, Kailuan General Hospital, Affiliated North China University of Science and Technology, Tangshan, 063000, China
| | - Pingshu Zhang
- Department of Neurology, Kailuan General Hospital, Affiliated North China University of Science and Technology, Tangshan, 063000, China
- Hebei Provincial Key Laboratory of Neurobiological Function, Tangshan, 063000, China
| | - Ya Ou
- Department of Neurology, Kailuan General Hospital, Affiliated North China University of Science and Technology, Tangshan, 063000, China
- Hebei Provincial Key Laboratory of Neurobiological Function, Tangshan, 063000, China
| | - Wen Li
- Department of Neurology, Kailuan General Hospital, Affiliated North China University of Science and Technology, Tangshan, 063000, China
| | - Qi Yan
- Department of Neurology, Kailuan General Hospital, Affiliated North China University of Science and Technology, Tangshan, 063000, China
| | - Xiaodong Yuan
- Department of Neurology, Kailuan General Hospital, Affiliated North China University of Science and Technology, Tangshan, 063000, China.
- Hebei Provincial Key Laboratory of Neurobiological Function, Tangshan, 063000, China.
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10
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Riley RM, Negri GL, Cheng SWG, Spencer Miko SE, Morin RD, Morin GB. Mass Spectrometry Acquisition and Fractionation Recommendations for TMT11 and TMT16 Labeled Samples. J Proteome Res 2024. [PMID: 38943634 DOI: 10.1021/acs.jproteome.4c00014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2024]
Abstract
Proteome coverage and accurate protein quantification are both important for evaluating biological systems; however, compromises between quantification, coverage, and mass spectrometry (MS) resources are often necessary. Consequently, experimental parameters that impact coverage and quantification must be adjusted, depending on experimental goals. Among these parameters is offline prefractionation, which is utilized in MS-based proteomics to decrease sample complexity resulting in higher overall proteome coverage upon MS analysis. Prefractionation leads to increases in required MS analysis time, although this is often mitigated by isobaric labeling using tandem-mass tags (TMT), which allow samples to be multiplexed. Here we evaluate common prefractionation schemes, TMT variants, and MS acquisition methods and their impact on protein quantification and coverage. Furthermore, we provide recommendations for experimental design depending on the experimental goals.
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Affiliation(s)
- Ryan M Riley
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver V5Z 1L3, Canada
| | - Gian Luca Negri
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver V5Z 1L3, Canada
| | - S-W Grace Cheng
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver V5Z 1L3, Canada
| | | | - Ryan D Morin
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver V5Z 1L3, Canada
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby V5A 1S6, Canada
| | - Gregg B Morin
- Canada's Michael Smith Genome Sciences Centre, BC Cancer, Vancouver V5Z 1L3, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver V6T 1Z4, Canada
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11
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Peng Y, Jain S, Radivojac P. An algorithm for decoy-free false discovery rate estimation in XL-MS/MS proteomics. Bioinformatics 2024; 40:i428-i436. [PMID: 38940171 DOI: 10.1093/bioinformatics/btae233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2024] Open
Abstract
MOTIVATION Cross-linking tandem mass spectrometry (XL-MS/MS) is an established analytical platform used to determine distance constraints between residues within a protein or from physically interacting proteins, thus improving our understanding of protein structure and function. To aid biological discovery with XL-MS/MS, it is essential that pairs of chemically linked peptides be accurately identified, a process that requires: (i) database search, that creates a ranked list of candidate peptide pairs for each experimental spectrum and (ii) false discovery rate (FDR) estimation, that determines the probability of a false match in a group of top-ranked peptide pairs with scores above a given threshold. Currently, the only available FDR estimation mechanism in XL-MS/MS is the target-decoy approach (TDA). However, despite its simplicity, TDA has both theoretical and practical limitations that impact the estimation accuracy and increase run time over potential decoy-free approaches (DFAs). RESULTS We introduce a novel decoy-free framework for FDR estimation in XL-MS/MS. Our approach relies on multi-sample mixtures of skew normal distributions, where the latent components correspond to the scores of correct peptide pairs (both peptides identified correctly), partially incorrect peptide pairs (one peptide identified correctly, the other incorrectly), and incorrect peptide pairs (both peptides identified incorrectly). To learn these components, we exploit the score distributions of first- and second-ranked peptide-spectrum matches for each experimental spectrum and subsequently estimate FDR using a novel expectation-maximization algorithm with constraints. We evaluate the method on ten datasets and provide evidence that the proposed DFA is theoretically sound and a viable alternative to TDA owing to its good performance in terms of accuracy, variance of estimation, and run time. AVAILABILITY AND IMPLEMENTATION https://github.com/shawn-peng/xlms.
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Affiliation(s)
- Yisu Peng
- Khoury College of Computer Sciences, Northeastern University, Boston, MA 02115, United States
| | - Shantanu Jain
- Khoury College of Computer Sciences, Northeastern University, Boston, MA 02115, United States
- The Institute for Experiential AI, Northeastern University, Boston, MA 02115, United States
| | - Predrag Radivojac
- Khoury College of Computer Sciences, Northeastern University, Boston, MA 02115, United States
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12
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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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13
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Derks J, Jonson T, Leduc A, Khan S, Khoury L, Rafiee MR, Slavov N. Single-nucleus proteomics identifies regulators of protein transport. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.17.599449. [PMID: 38948785 PMCID: PMC11212961 DOI: 10.1101/2024.06.17.599449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
The physiological response of a cell to stimulation depends on its proteome configuration. Therefore, the abundance variation of regulatory proteins across unstimulated single cells can be associatively linked with their response to stimulation. Here we developed an approach that leverages this association across individual cells and nuclei to systematically identify potential regulators of biological processes, followed by targeted validation. Specifically, we applied this approach to identify regulators of nucleocytoplasmic protein transport in macrophages stimulated with lipopolysaccharide (LPS). To this end, we quantified the proteomes of 3,412 individual nuclei, sampling the dynamic response to LPS treatment, and linking functional variability to proteomic variability. Minutes after the stimulation, the protein transport in individual nuclei correlated strongly with the abundance of known protein transport regulators, thus revealing the impact of natural protein variability on functional cellular response. We found that simple biophysical constraints, such as the quantity of nuclear pores, partially explain the variability in LPS-induced nucleocytoplasmic transport. Among the many proteins newly identified to be associated with the response, we selected 16 for targeted validation by knockdown. The knockdown phenotypes confirmed the inferences derived from natural protein and functional variation of single nuclei, thus demonstrating the potential of (sub-)single-cell proteomics to infer functional regulation. We expect this approach to generalize to broad applications and enhance the functional interpretability of single-cell omics data.
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Affiliation(s)
- Jason Derks
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
- Parallel Squared Technology Institute, Watertown, MA 02472, USA
| | - Tobias Jonson
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
| | - Andrew Leduc
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
| | - Saad Khan
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
| | - Luke Khoury
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
| | - Mahmoud-Reza Rafiee
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
| | - Nikolai Slavov
- Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Center, Northeastern University, Boston, MA 02115, USA
- Parallel Squared Technology Institute, Watertown, MA 02472, USA
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14
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Kalhor M, Lapin J, Picciani M, Wilhelm M. Rescoring Peptide Spectrum Matches: Boosting Proteomics Performance by Integrating Peptide Property Predictors Into Peptide Identification. Mol Cell Proteomics 2024; 23:100798. [PMID: 38871251 DOI: 10.1016/j.mcpro.2024.100798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 05/26/2024] [Accepted: 06/09/2024] [Indexed: 06/15/2024] Open
Abstract
Rescoring of peptide spectrum matches originating from database search engines enabled by peptide property predictors is exceeding the performance of peptide identification from traditional database search engines. In contrast to the peptide spectrum match scores calculated by traditional database search engines, rescoring peptide spectrum matches generates scores based on comparing observed and predicted peptide properties, such as fragment ion intensities and retention times. These newly generated scores enable a more efficient discrimination between correct and incorrect peptide spectrum matches. This approach was shown to lead to substantial improvements in the number of confidently identified peptides, facilitating the analysis of challenging datasets in various fields such as immunopeptidomics, metaproteomics, proteogenomics, and single-cell proteomics. In this review, we summarize the key elements leading up to the recent introduction of multiple data-driven rescoring pipelines. We provide an overview of relevant post-processing rescoring tools, introduce prominent data-driven rescoring pipelines for various applications, and highlight limitations, opportunities, and future perspectives of this approach and its impact on mass spectrometry-based proteomics.
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Affiliation(s)
- Mostafa Kalhor
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Joel Lapin
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Mario Picciani
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Mathias Wilhelm
- Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany; Munich Data Science Institute, Technical University of Munich, Garching, Germany.
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15
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Dutta T, Vlassakis J. Microscale measurements of protein complexes from single cells. Curr Opin Struct Biol 2024; 87:102860. [PMID: 38848654 DOI: 10.1016/j.sbi.2024.102860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Revised: 05/07/2024] [Accepted: 05/14/2024] [Indexed: 06/09/2024]
Abstract
Proteins execute numerous cell functions in concert with one another in protein-protein interactions (PPI). While essential in each cell, such interactions are not identical from cell to cell. Instead, PPI heterogeneity contributes to cellular phenotypic heterogeneity in health and diseases such as cancer. Understanding cellular phenotypic heterogeneity thus requires measurements of properties of PPIs such as abundance, stoichiometry, and kinetics at the single-cell level. Here, we review recent, exciting progress in single-cell PPI measurements. Novel technology in this area is enabled by microscale and microfluidic approaches that control analyte concentration in timescales needed to outpace PPI disassembly kinetics. We describe microscale innovations, needed technical capabilities, and methods poised to be adapted for single-cell analysis in the near future.
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Affiliation(s)
- Tanushree Dutta
- Department of Bioengineering, Rice University, Houston, TX 77005, USA. https://twitter.com/duttatanu1717
| | - Julea Vlassakis
- Department of Bioengineering, Rice University, Houston, TX 77005, USA.
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16
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Colón Rosado J, Sun L. Solid-Phase Microextraction-Aided Capillary Zone Electrophoresis-Mass Spectrometry: Toward Bottom-Up Proteomics of Single Human Cells. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:1120-1127. [PMID: 38514245 PMCID: PMC11157658 DOI: 10.1021/jasms.3c00429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 03/02/2024] [Accepted: 03/13/2024] [Indexed: 03/23/2024]
Abstract
Capillary zone electrophoresis-mass spectrometry (CZE-MS) has been recognized as a valuable technique for the proteomics of mass-limited biological samples (i.e., single cells). However, its broad adoption for single cell proteomics (SCP) of human cells has been impeded by the low sample loading capacity of CZE, only allowing us to use less than 5% of the available peptide material for each measurement. Here we present a reversed-phase-based solid-phase microextraction (RP-SPME)-CZE-MS platform to solve the issue, paving the way for SCP of human cells using CZE-MS. The RP-SPME-CZE system was constructed in one fused silica capillary with zero dead volume for connection via in situ synthesis of a frit, followed by packing C8 beads into the capillary to form a roughly 2 mm long SPME section. Peptides captured by SPME were eluted with a buffer containing 30% (v/v) acetonitrile and 50 mM ammonium acetate (pH 6.5), followed by dynamic pH junction-based CZE-MS. The SPME-CZE-MS enabled the injection of nearly 40% of the available peptide sample for each measurement. The system identified 257 ± 24 proteins and 523 ± 69 peptides (N = 2) using a Q-Exactive HF mass spectrometer when only 0.25 ng of a commercial HeLa cell digest was available in the sample vial and 0.1 ng of the sample was injected. The amount of available peptide is equivalent to the protein mass of one HeLa cell. The data indicate that SPME-CZE-MS is ready for SCP of human cells.
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Affiliation(s)
- Jorge
A. Colón Rosado
- Department of Chemistry, Michigan
State University, 578 S Shaw Lane, East Lansing, Michigan 48824, United States
| | - Liangliang Sun
- Department of Chemistry, Michigan
State University, 578 S Shaw Lane, East Lansing, Michigan 48824, United States
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17
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Wang J, Tan H, Fu Y, Mishra A, Sun H, Wang Z, Wu Z, Wang X, Serrano GE, Beach TG, Peng J, High AA. Evaluation of Protein Identification and Quantification by the diaPASEF Method on timsTOF SCP. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:1253-1260. [PMID: 38754071 DOI: 10.1021/jasms.4c00067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2024]
Abstract
Accurate and precise quantification is crucial in modern proteomics, particularly in the context of exploring low-amount samples. While the innovative 4D-data-independent acquisition (DIA) quantitative proteomics facilitated by timsTOF mass spectrometers gives enhanced sensitivity and selectivity for protein identification, the diaPASEF (parallel accumulation-serial fragmentation combined with data-independent acquisition) parameters have not been systematically optimized, and a comprehensive evaluation of the quantification is currently lacking. In this study, we conducted a thorough optimization of key parameters on a timsTOF SCP instrument, including sample loading amount (50 ng), ramp/accumulation time (140 ms), isolation window width (20 m/z), and gradient time (60 min). To further improve the identification of proteins in low-amount samples, we utilized different column settings and introduced 0.02% n-dodecyl-β-d-maltoside (DDM) in the sample reconstitution solution, resulting in a remarkable 19-fold increase in protein identification at the single-cell-equivalent level. Moreover, a comprehensive comparison of protein quantification using a tandem mass tag reporter (TMT-reporter), complement TMT ions (TMTc), and diaPASEF revealed a strong correlation between these methods. Both diaPASEF and TMTc have effectively addressed the issue of ratio compression, highlighting the diaPASEF method's effectiveness in achieving accurate quantification data compared to TMT reporter quantification. Additionally, an in-depth analysis of in-group variation positioned diaPASEF between the TMT-reporter and TMTc methods. Therefore, diaPASEF quantification on the timsTOF SCP instrument emerges as a precise and accurate methodology for quantitative proteomics, especially for samples with small amounts.
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Affiliation(s)
- Ju Wang
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Haiyan Tan
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Yingxue Fu
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Ashutosh Mishra
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Huan Sun
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Zhen Wang
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Zhiping Wu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Xusheng Wang
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Geidy E Serrano
- Banner Sun Health Research Institute, Sun City, Arizona 85351, United States
| | - Thomas G Beach
- Banner Sun Health Research Institute, Sun City, Arizona 85351, United States
| | - Junmin Peng
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
| | - Anthony A High
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States
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18
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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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19
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Shannon AE, Teodorescu RN, Soon N, Heil LR, Jacob CC, Remes PM, Rubinstein MP, Searle BC. A workflow for targeted proteomics assay development using a versatile linear ion trap. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.31.596891. [PMID: 38853838 PMCID: PMC11160733 DOI: 10.1101/2024.05.31.596891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Advances in proteomics and mass spectrometry have enabled the study of limited cell populations, such as single-cell proteomics, where high-mass accuracy instruments are typically required. While triple quadrupoles offer fast and sensitive nominal resolution measurements, these instruments are effectively limited to targeted proteomics. Linear ion traps (LITs) offer a versatile, cost-effective alternative capable of both targeted and global proteomics. We demonstrate a workflow using a newly released, hybrid quadrupole-LIT instrument for developing targeted proteomics assays from global data-independent acquisition (DIA) measurements without needing high-mass accuracy. Gas-phase fraction-based DIA enables rapid target library generation in the same background chemical matrix as each quantitative injection. Using a new software tool embedded within EncyclopeDIA for scheduling parallel reaction monitoring assays, we show consistent quantification across three orders of magnitude of input material. Using this approach, we demonstrate measuring peptide quantitative linearity down to 25x dilution in a background of only a 1 ng proteome without requiring stable isotope labeled standards. At 1 ng total protein on column, we found clear consistency between immune cell populations measured using flow cytometry and immune markers measured using LIT-based proteomics. We believe hybrid quadrupole-LIT instruments represent an economic solution to democratizing mass spectrometry in a wide variety of laboratory settings.
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20
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Kumar R, Zemaitis KJ, Fulcher JM, Paša-Tolić L. Advances in mass spectrometry-enabled multiomics at single-cell resolution. Curr Opin Biotechnol 2024; 87:103096. [PMID: 38432187 DOI: 10.1016/j.copbio.2024.103096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 02/06/2024] [Indexed: 03/05/2024]
Abstract
Biological organisms are multifaceted, intricate systems where slight perturbations can result in extensive changes in gene expression, protein abundance and/or activity, and metabolic flux. These changes occur at different timescales, spatially across cells of heterogeneous origins, and within single-cells. Hence, multimodal measurements at the smallest biological scales are necessary to capture dynamic changes in heterogeneous biological systems. Of the analytical techniques used to measure biomolecules, mass spectrometry (MS) has proven to be a powerful option due to its sensitivity, robustness, and flexibility with regard to the breadth of biomolecules that can be analyzed. Recently, many studies have coupled MS to other analytical techniques with the goal of measuring multiple modalities from the same single-cell. It is with these concepts in mind that we focus this review on MS-enabled multiomic measurements at single-cell or near-single- cell resolution.
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Affiliation(s)
- Rashmi Kumar
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - Kevin J Zemaitis
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - James M Fulcher
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA.
| | - Ljiljana Paša-Tolić
- Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA.
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21
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Li L, Zhang Y, Zhou J, Wang J, Wang L. Single-cell metabolomics in rare disease: From technology to disease. Intractable Rare Dis Res 2024; 13:99-103. [PMID: 38836176 PMCID: PMC11145402 DOI: 10.5582/irdr.2023.01073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 05/12/2024] [Accepted: 05/22/2024] [Indexed: 06/06/2024] Open
Abstract
With the development of clinical experience and technology, rare diseases (RDs) are gradually coming into the limelight. As they often lead to poor prognosis, it is urgent to promote the accuracy and rapidity of diagnosis and promote the development of therapeutic drugs. In recent years, with the rapid improvement of single-cell sequencing technology, the advantages of multi-omics combined application in diseases have been continuously explored. Single-cell metabolomics represents a powerful tool for advancing our understanding of rare diseases, particularly metabolic RDs, and transforming clinical practice. By unraveling the intricacies of cellular metabolism at a single-cell resolution, this innovative approach holds the potential to revolutionize diagnosis, treatment, and management strategies, ultimately improving outcomes for RDs patients. Continued research and technological advancements in single-cell metabolomics are essential for realizing its full potential in the field of RDs diagnosis and therapeutics. It is expected that single-cell metabolomics can be better applied to RDs research in the future, for the benefit of patients and society.
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Affiliation(s)
- Lisha Li
- Laboratory for Reproductive Immunology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
- The Academy of Integrative Medicine of Fudan University, Shanghai, China
- Shanghai Key Laboratory of Female Reproductive Endocrine-related Diseases, Shanghai, China
| | - Yiqin Zhang
- Department of Obstetrics and Gynecology, International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
- Shanghai Key Laboratory Embryo Original Diseases, Shanghai, China
| | - Jing Zhou
- Laboratory for Reproductive Immunology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
- The Academy of Integrative Medicine of Fudan University, Shanghai, China
- Shanghai Key Laboratory of Female Reproductive Endocrine-related Diseases, Shanghai, China
| | - Jing Wang
- Laboratory for Reproductive Immunology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
- The Academy of Integrative Medicine of Fudan University, Shanghai, China
- Shanghai Key Laboratory of Female Reproductive Endocrine-related Diseases, Shanghai, China
| | - Ling Wang
- Laboratory for Reproductive Immunology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China
- The Academy of Integrative Medicine of Fudan University, Shanghai, China
- Shanghai Key Laboratory of Female Reproductive Endocrine-related Diseases, Shanghai, China
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22
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Fan KT, Xu Y, Hegeman AD. Elevated Temperature Effects on Protein Turnover Dynamics in Arabidopsis thaliana Seedlings Revealed by 15N-Stable Isotope Labeling and ProteinTurnover Algorithm. Int J Mol Sci 2024; 25:5882. [PMID: 38892074 PMCID: PMC11172382 DOI: 10.3390/ijms25115882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2024] [Revised: 05/24/2024] [Accepted: 05/26/2024] [Indexed: 06/21/2024] Open
Abstract
Global warming poses a threat to plant survival, impacting growth and agricultural yield. Protein turnover, a critical regulatory mechanism balancing protein synthesis and degradation, is crucial for the cellular response to environmental changes. We investigated the effects of elevated temperature on proteome dynamics in Arabidopsis thaliana seedlings using 15N-stable isotope labeling and ultra-performance liquid chromatography-high resolution mass spectrometry, coupled with the ProteinTurnover algorithm. Analyzing different cellular fractions from plants grown under 22 °C and 30 °C growth conditions, we found significant changes in the turnover rates of 571 proteins, with a median 1.4-fold increase, indicating accelerated protein dynamics under thermal stress. Notably, soluble root fraction proteins exhibited smaller turnover changes, suggesting tissue-specific adaptations. Significant turnover alterations occurred with redox signaling, stress response, protein folding, secondary metabolism, and photorespiration, indicating complex responses enhancing plant thermal resilience. Conversely, proteins involved in carbohydrate metabolism and mitochondrial ATP synthesis showed minimal changes, highlighting their stability. This analysis highlights the intricate balance between proteome stability and adaptability, advancing our understanding of plant responses to heat stress and supporting the development of improved thermotolerant crops.
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Affiliation(s)
- Kai-Ting Fan
- Agricultural Biotechnology Research Center, Academia Sinica, Taipei 115, Taiwan;
| | - Yuan Xu
- MSU-DOE Plant Research Laboratory, Michigan State University, East Lansing, MI 48824, USA
| | - Adrian D. Hegeman
- Departments of Horticultural Science and Plant and Microbial Biology, University of Minnesota, Twin Cities, MN 55108, USA
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23
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Zhao Z, Guo Y, Chowdhury T, Anjum S, Li J, Huang L, Cupp-Sutton KA, Burgett A, Shi D, Wu S. Top-Down Proteomics Analysis of Picogram-Level Complex Samples Using Spray-Capillary-Based Capillary Electrophoresis-Mass Spectrometry. Anal Chem 2024; 96:8763-8771. [PMID: 38722793 DOI: 10.1021/acs.analchem.4c01119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Proteomics analysis of mass-limited samples has become increasingly important for understanding biological systems in physiologically relevant contexts such as patient samples, multicellular organoids, spheroids, and single cells. However, relatively low sensitivity in top-down proteomics methods makes their application to mass-limited samples challenging. Capillary electrophoresis (CE) has emerged as an ideal separation method for mass-limited samples due to its high separation resolution, ultralow detection limit, and minimal sample volume requirements. Recently, we developed "spray-capillary", an electrospray ionization (ESI)-assisted device, that is capable of quantitative ultralow-volume sampling (e.g., pL-nL level). Here, we developed a spray-capillary-CE-MS platform for ultrasensitive top-down proteomics analysis of intact proteins in mass-limited complex biological samples. Specifically, to improve the sensitivity of the spray-capillary platform, we incorporated a polyethylenimine (PEI)-coated capillary and optimized the spray-capillary inner diameter. Under optimized conditions, we successfully detected over 200 proteoforms from 50 pg of E. coli lysate. To our knowledge, the spray-capillary CE-MS platform developed here represents one of the most sensitive detection methods for top-down proteomics. Furthermore, in a proof-of-principle experiment, we detected 261 ± 65 and 174 ± 45 intact proteoforms from fewer than 50 HeLa and OVCAR-8 cells, respectively, by coupling nanodroplet-based sample preparation with our optimized CE-MS platform. Overall, our results demonstrate the capability of the modified spray-capillary CE-MS platform to perform top-down proteomics analysis on picogram amounts of samples. This advancement presents the possibility of meaningful top-down proteomics analysis of mass-limited samples down to the level of single mammalian cells.
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Affiliation(s)
- Zhitao Zhao
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Yanting Guo
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Trishika Chowdhury
- Department of Chemistry and Biochemistry, University of Alabama, 250 Hackberry Ln, Tuscaloosa, Alabama 35487, United States
| | - Samin Anjum
- Department of Chemistry and Biochemistry, University of Alabama, 250 Hackberry Ln, Tuscaloosa, Alabama 35487, United States
| | - Jiaxue Li
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Lushuang Huang
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Kellye A Cupp-Sutton
- Department of Chemistry and Biochemistry, University of Alabama, 250 Hackberry Ln, Tuscaloosa, Alabama 35487, United States
| | - Anthony Burgett
- Department of Pharmaceutical Sciences, University of Oklahoma Health Sciences, 1110 N. Stonewall Ave., Oklahoma City, Oklahoma 73117, United States
| | - Dingjing Shi
- Department of Psychology, University of Oklahoma, 455 W Lindsey Street, Norman, Oklahoma 73069, United States
| | - Si Wu
- Department of Chemistry and Biochemistry, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
- Department of Chemistry and Biochemistry, University of Alabama, 250 Hackberry Ln, Tuscaloosa, Alabama 35487, United States
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24
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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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25
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Peters-Clarke TM, Coon JJ, Riley NM. Instrumentation at the Leading Edge of Proteomics. Anal Chem 2024; 96:7976-8010. [PMID: 38738990 DOI: 10.1021/acs.analchem.3c04497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2024]
Affiliation(s)
- Trenton M Peters-Clarke
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Joshua J Coon
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Morgridge Institute for Research, Madison, Wisconsin 53715, United States
| | - Nicholas M Riley
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
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26
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Zhou H, Li I, Bramlett CS, Wang B, Hao J, Yen DP, Ando Y, Fraser SE, Lu R, Shen K. Label-free metabolic optical biomarkers track stem cell fate transition in real time. SCIENCE ADVANCES 2024; 10:eadi6770. [PMID: 38718114 PMCID: PMC11078180 DOI: 10.1126/sciadv.adi6770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 04/04/2024] [Indexed: 05/12/2024]
Abstract
Tracking stem cell fate transition is crucial for understanding their development and optimizing biomanufacturing. Destructive single-cell methods provide a pseudotemporal landscape of stem cell differentiation but cannot monitor stem cell fate in real time. We established a metabolic optical metric using label-free fluorescence lifetime imaging microscopy (FLIM), feature extraction and machine learning-assisted analysis, for real-time cell fate tracking. From a library of 205 metabolic optical biomarker (MOB) features, we identified 56 associated with hematopoietic stem cell (HSC) differentiation. These features collectively describe HSC fate transition and detect its bifurcate lineage choice. We further derived a MOB score measuring the "metabolic stemness" of single cells and distinguishing their division patterns. This score reveals a distinct role of asymmetric division in rescuing stem cells with compromised metabolic stemness and a unique mechanism of PI3K inhibition in promoting ex vivo HSC maintenance. MOB profiling is a powerful tool for tracking stem cell fate transition and improving their biomanufacturing from a single-cell perspective.
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Affiliation(s)
- Hao Zhou
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
| | - Irene Li
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
| | - Charles S. Bramlett
- Department of Stem Cell Biology and Regenerative Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Bowen Wang
- Department of Stem Cell Biology and Regenerative Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Jia Hao
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
| | - Daniel P. Yen
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
| | - Yuta Ando
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
| | - Scott E. Fraser
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
- Department of Stem Cell Biology and Regenerative Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Translational Imaging Center, University of Southern California, Los Angeles, CA 90089, USA
- Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Rong Lu
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
- Department of Stem Cell Biology and Regenerative Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
- Department of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Keyue Shen
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
- USC Stem Cell, University of Southern California, Los Angeles, CA 90033, USA
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27
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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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28
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Peters-Clarke TM, Liang Y, Mertz KL, Lee KW, Westphall MS, Hinkle JD, McAlister GC, Syka JEP, Kelly RT, Coon JJ. Boosting the Sensitivity of Quantitative Single-Cell Proteomics with Infrared-Tandem Mass Tags. J Proteome Res 2024. [PMID: 38713017 DOI: 10.1021/acs.jproteome.4c00076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Single-cell proteomics is a powerful approach to precisely profile protein landscapes within individual cells toward a comprehensive understanding of proteomic functions and tissue and cellular states. The inherent challenges associated with limited starting material demand heightened analytical sensitivity. Just as advances in sample preparation maximize the amount of material that makes it from the cell to the mass spectrometer, we strive to maximize the number of ions that make it from ion source to the detector. In isobaric tagging experiments, limited reporter ion generation limits quantitative accuracy and precision. The combination of infrared photoactivation and ion parking circumvents the m/z dependence inherent in HCD, maximizing reporter generation and avoiding unintended degradation of TMT reporter molecules in infrared-tandem mass tags (IR-TMT). The method was applied to single-cell human proteomes using 18-plex TMTpro, resulting in 4-5-fold increases in reporter signal compared to conventional SPS-MS3 approaches. IR-TMT enables faster duty cycles, higher throughput, and increased peptide identification and quantification. Comparative experiments showcase 4-5-fold lower injection times for IR-TMT, providing superior sensitivity without compromising accuracy. In all, IR-TMT enhances the dynamic range of proteomic experiments and is compatible with gas-phase fractionation and real-time searching, promising increased gains in the study of cellular heterogeneity.
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Affiliation(s)
- Trenton M Peters-Clarke
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Yiran Liang
- Department of Chemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Keaton L Mertz
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Kenneth W Lee
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Michael S Westphall
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Joshua D Hinkle
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | | | - John E P Syka
- Thermo Fisher Scientific, San Jose, California 95134, United States
| | - Ryan T Kelly
- Department of Chemistry, Brigham Young University, Provo, Utah 84602, United States
| | - Joshua J Coon
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
- National Center for Quantitative Biology of Complex Systems, Madison, Wisconsin 53706, United States
- Morgridge Institute for Research, Madison, Wisconsin 53515, United States
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29
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Yu SH, Chen SC, Wu PS, Kuo PI, Chen TA, Lee HY, Lin MH. Quantification Quality Control Emerges as a Crucial Factor to Enhance Single-Cell Proteomics Data Analysis. Mol Cell Proteomics 2024; 23:100768. [PMID: 38621647 PMCID: PMC11103571 DOI: 10.1016/j.mcpro.2024.100768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 03/12/2024] [Accepted: 04/11/2024] [Indexed: 04/17/2024] Open
Abstract
Mass spectrometry (MS)-based single-cell proteomics (SCP) provides us the opportunity to unbiasedly explore biological variability within cells without the limitation of antibody availability. This field is rapidly developed with the main focuses on instrument advancement, sample preparation refinement, and signal boosting methods; however, the optimal data processing and analysis are rarely investigated which holds an arduous challenge because of the high proportion of missing values and batch effect. Here, we introduced a quantification quality control to intensify the identification of differentially expressed proteins (DEPs) by considering both within and across SCP data. Combining quantification quality control with isobaric matching between runs (IMBR) and PSM-level normalization, an additional 12% and 19% of proteins and peptides, with more than 90% of proteins/peptides containing valid values, were quantified. Clearly, quantification quality control was able to reduce quantification variations and q-values with the more apparent cell type separations. In addition, we found that PSM-level normalization performed similar to other protein-level normalizations but kept the original data profiles without the additional requirement of data manipulation. In proof of concept of our refined pipeline, six uniquely identified DEPs exhibiting varied fold-changes and playing critical roles for melanoma and monocyte functionalities were selected for validation using immunoblotting. Five out of six validated DEPs showed an identical trend with the SCP dataset, emphasizing the feasibility of combining the IMBR, cell quality control, and PSM-level normalization in SCP analysis, which is beneficial for future SCP studies.
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Affiliation(s)
- Sung-Huan Yu
- Institute of Precision Medicine, College of Medicine, National Sun Yat-sen University, Kaohsiung, Taiwan; School of Medicine, College of Medicine, National Sun Yat-sen University, Kaohsiung, Taiwan
| | - Shiau-Ching Chen
- Institute of Precision Medicine, College of Medicine, National Sun Yat-sen University, Kaohsiung, Taiwan
| | - Pei-Shan Wu
- Department of Microbiology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Pei-I Kuo
- Department of Microbiology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Ting-An Chen
- Department of Microbiology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Hsiang-Ying Lee
- Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan; Department of Urology, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Miao-Hsia Lin
- Department of Microbiology, National Taiwan University College of Medicine, Taipei, Taiwan.
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30
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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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31
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Jiménez C, Garrote-de-Barros A, López-Portugués C, Hernández-Sánchez M, Díez P. Characterization of Human B Cell Hematological Malignancies Using Protein-Based Approaches. Int J Mol Sci 2024; 25:4644. [PMID: 38731863 PMCID: PMC11083628 DOI: 10.3390/ijms25094644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 04/19/2024] [Accepted: 04/23/2024] [Indexed: 05/13/2024] Open
Abstract
The maturation of B cells is a complex, multi-step process. During B cell differentiation, errors can occur, leading to the emergence of aberrant versions of B cells that, finally, constitute a malignant tumor. These B cell malignancies are classified into three main groups: leukemias, myelomas, and lymphomas, the latter being the most heterogeneous type. Since their discovery, multiple biological studies have been performed to characterize these diseases, aiming to define their specific features and determine potential biomarkers for diagnosis, stratification, and prognosis. The rise of advanced -omics approaches has significantly contributed to this end. Notably, proteomics strategies appear as promising tools to comprehensively profile the final molecular effector of these cells. In this narrative review, we first introduce the main B cell malignancies together with the most relevant proteomics approaches. Then, we describe the core studies conducted in the field and their main findings and, finally, we evaluate the advantages and drawbacks of flow cytometry, mass cytometry, and mass spectrometry for the profiling of human B cell disorders.
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Affiliation(s)
- Cristina Jiménez
- Hematology Department, University Hospital of Salamanca (HUS/IBSAL), CIBERONC and Cancer Research Institute of Salamanca-IBMCC (USAL-CSIC), 37007 Salamanca, Spain;
| | - Alba Garrote-de-Barros
- Department of Biochemistry and Molecular Biology, Pharmacy School, Universidad Complutense de Madrid, 28040 Madrid, Spain; (A.G.-d.-B.); (M.H.-S.)
- Department of Translational Hematology, Instituto de Investigación Hospital 12 de Octubre (imas12), Hematological Malignancies Clinical Research Unit H12O-CNIO, 28029 Madrid, Spain
| | - Carlos López-Portugués
- Department of Physical and Analytical Chemistry Chemistry, Faculty of Chemistry, University of Oviedo, 33006 Oviedo, Spain;
- Health Research Institute of the Principality of Asturias (ISPA), 33011 Oviedo, Spain
| | - María Hernández-Sánchez
- Department of Biochemistry and Molecular Biology, Pharmacy School, Universidad Complutense de Madrid, 28040 Madrid, Spain; (A.G.-d.-B.); (M.H.-S.)
- Department of Translational Hematology, Instituto de Investigación Hospital 12 de Octubre (imas12), Hematological Malignancies Clinical Research Unit H12O-CNIO, 28029 Madrid, Spain
| | - Paula Díez
- Department of Physical and Analytical Chemistry Chemistry, Faculty of Chemistry, University of Oviedo, 33006 Oviedo, Spain;
- Health Research Institute of the Principality of Asturias (ISPA), 33011 Oviedo, Spain
- Department of Functional Biology, Faculty of Medicine and Health Science, University of Oviedo, 33006 Oviedo, Spain
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32
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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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33
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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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34
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Ren L, Huang D, Liu H, Ning L, Cai P, Yu X, Zhang Y, Luo N, Lin H, Su J, Zhang Y. Applications of single‑cell omics and spatial transcriptomics technologies in gastric cancer (Review). Oncol Lett 2024; 27:152. [PMID: 38406595 PMCID: PMC10885005 DOI: 10.3892/ol.2024.14285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 01/19/2024] [Indexed: 02/27/2024] Open
Abstract
Gastric cancer (GC) is a prominent contributor to global cancer-related mortalities, and a deeper understanding of its molecular characteristics and tumor heterogeneity is required. Single-cell omics and spatial transcriptomics (ST) technologies have revolutionized cancer research by enabling the exploration of cellular heterogeneity and molecular landscapes at the single-cell level. In the present review, an overview of the advancements in single-cell omics and ST technologies and their applications in GC research is provided. Firstly, multiple single-cell omics and ST methods are discussed, highlighting their ability to offer unique insights into gene expression, genetic alterations, epigenomic modifications, protein expression patterns and cellular location in tissues. Furthermore, a summary is provided of key findings from previous research on single-cell omics and ST methods used in GC, which have provided valuable insights into genetic alterations, tumor diagnosis and prognosis, tumor microenvironment analysis, and treatment response. In summary, the application of single-cell omics and ST technologies has revealed the levels of cellular heterogeneity and the molecular characteristics of GC, and holds promise for improving diagnostics, personalized treatments and patient outcomes in GC.
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Affiliation(s)
- Liping Ren
- School of Healthcare Technology, Chengdu Neusoft University, Chengdu, Sichuan 611844, P.R. China
| | - Danni Huang
- Department of Radiology, Central South University Xiangya School of Medicine Affiliated Haikou People's Hospital, Haikou, Hainan 570208, P.R. China
| | - Hongjiang Liu
- School of Computer Science and Technology, Aba Teachers College, Aba, Sichuan 624099, P.R. China
| | - Lin Ning
- School of Healthcare Technology, Chengdu Neusoft University, Chengdu, Sichuan 611844, P.R. China
| | - Peiling Cai
- School of Basic Medical Sciences, Chengdu University, Chengdu, Sichuan 610106, P.R. China
| | - Xiaolong Yu
- Hainan Yazhou Bay Seed Laboratory, Sanya Nanfan Research Institute, Material Science and Engineering Institute of Hainan University, Sanya, Hainan 572025, P.R. China
| | - Yang Zhang
- Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, P.R. China
| | - Nanchao Luo
- School of Computer Science and Technology, Aba Teachers College, Aba, Sichuan 624099, P.R. China
| | - Hao Lin
- Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, P.R. China
| | - Jinsong Su
- Research Institute of Integrated Traditional Chinese Medicine and Western Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, P.R. China
| | - Yinghui Zhang
- School of Healthcare Technology, Chengdu Neusoft University, Chengdu, Sichuan 611844, P.R. China
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35
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Nalehua MR, Zaia J. A critical evaluation of ultrasensitive single-cell proteomics strategies. Anal Bioanal Chem 2024; 416:2359-2369. [PMID: 38358530 DOI: 10.1007/s00216-024-05171-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 01/20/2024] [Accepted: 01/23/2024] [Indexed: 02/16/2024]
Abstract
Success of mass spectrometry characterization of the proteome of single cells allows us to gain a greater understanding than afforded by transcriptomics alone but requires clear understanding of the tradeoffs between analytical throughput and precision. Recent advances in mass spectrometry acquisition techniques, including updated instrumentation and sample preparation, have improved the quality of peptide signals obtained from single cell data. However, much of the proteome remains uncharacterized, and higher throughput techniques often come at the expense of reduced sensitivity and coverage, which diminish the ability to measure proteoform heterogeneity, including splice variants and post-translational modifications, in single cell data analysis. Here, we assess the growing body of ultrasensitive single-cell approaches and their tradeoffs as researchers try to balance throughput and precision in their experiments.
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Affiliation(s)
| | - Joseph Zaia
- Bioinformatics Program, Boston University, Boston, MA, USA.
- Department of Biochemistry and Cell Biology, Boston University, Boston, MA, USA.
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36
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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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37
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Su P, Hollas MAR, Butun FA, Kanchustambham VL, Rubakhin S, Ramani N, Greer JB, Early BP, Fellers RT, Caldwell MA, Sweedler JV, Kafader JO, Kelleher NL. Single Cell Analysis of Proteoforms. J Proteome Res 2024. [PMID: 38497708 DOI: 10.1021/acs.jproteome.4c00075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
We introduce single cell Proteoform imaging Mass Spectrometry (scPiMS), which realizes the benefit of direct solvent extraction and MS detection of intact proteins from single cells dropcast onto glass slides. Sampling and detection of whole proteoforms by individual ion mass spectrometry enable a scalable approach to single cell proteomics. This new scPiMS platform addresses the throughput bottleneck in single cell proteomics and boosts the cell processing rate by several fold while accessing protein composition with higher coverage.
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Affiliation(s)
- Pei Su
- Departments of Molecular Biosciences, Chemistry, Chemical and Biological Engineering, and Feinberg School of Medicine, Northwestern University, Evanston, Illinois 60208, United States
| | - Michael A R Hollas
- Departments of Molecular Biosciences, Chemistry, Chemical and Biological Engineering, and Feinberg School of Medicine, Northwestern University, Evanston, Illinois 60208, United States
| | - Fatma Ayaloglu Butun
- Proteomics Center of Excellence, Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois 60208, United States
| | - Vijaya Lakshmi Kanchustambham
- Proteomics Center of Excellence, Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois 60208, United States
| | - Stanislav Rubakhin
- Beckman Institute and Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Namrata Ramani
- Department of Materials Science and Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Joseph B Greer
- Departments of Molecular Biosciences, Chemistry, Chemical and Biological Engineering, and Feinberg School of Medicine, Northwestern University, Evanston, Illinois 60208, United States
| | - Bryan P Early
- Departments of Molecular Biosciences, Chemistry, Chemical and Biological Engineering, and Feinberg School of Medicine, Northwestern University, Evanston, Illinois 60208, United States
| | - Ryan T Fellers
- Departments of Molecular Biosciences, Chemistry, Chemical and Biological Engineering, and Feinberg School of Medicine, Northwestern University, Evanston, Illinois 60208, United States
| | - Michael A Caldwell
- Proteomics Center of Excellence, Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois 60208, United States
| | - Jonathan V Sweedler
- Beckman Institute and Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Jared O Kafader
- Departments of Molecular Biosciences, Chemistry, Chemical and Biological Engineering, and Feinberg School of Medicine, Northwestern University, Evanston, Illinois 60208, United States
- Proteomics Center of Excellence, Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois 60208, United States
| | - Neil L Kelleher
- Departments of Molecular Biosciences, Chemistry, Chemical and Biological Engineering, and Feinberg School of Medicine, Northwestern University, Evanston, Illinois 60208, United States
- Proteomics Center of Excellence, Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois 60208, United States
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60611, United States
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38
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Buur LM, Declercq A, Strobl M, Bouwmeester R, Degroeve S, Martens L, Dorfer V, Gabriels R. MS 2Rescore 3.0 Is a Modular, Flexible, and User-Friendly Platform to Boost Peptide Identifications, as Showcased with MS Amanda 3.0. J Proteome Res 2024. [PMID: 38491990 DOI: 10.1021/acs.jproteome.3c00785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2024]
Abstract
Rescoring of peptide-spectrum matches (PSMs) has emerged as a standard procedure for the analysis of tandem mass spectrometry data. This emphasizes the need for software maintenance and continuous improvement for such algorithms. We introduce MS2Rescore 3.0, a versatile, modular, and user-friendly platform designed to increase peptide identifications. Researchers can install MS2Rescore across various platforms with minimal effort and benefit from a graphical user interface, a modular Python API, and extensive documentation. To showcase this new version, we connected MS2Rescore 3.0 with MS Amanda 3.0, a new release of the well-established search engine, addressing previous limitations on automatic rescoring. Among new features, MS Amanda now contains additional output columns that can be used for rescoring. The full potential of rescoring is best revealed when applied on challenging data sets. We therefore evaluated the performance of these two tools on publicly available single-cell data sets, where the number of PSMs was substantially increased, thereby demonstrating that MS2Rescore offers a powerful solution to boost peptide identifications. MS2Rescore's modular design and user-friendly interface make data-driven rescoring easily accessible, even for inexperienced users. We therefore expect the MS2Rescore to be a valuable tool for the wider proteomics community. MS2Rescore is available at https://github.com/compomics/ms2rescore.
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Affiliation(s)
- Louise M Buur
- Bioinformatics Research Group, University of Applied Sciences Upper Austria, Hagenberg 4232, Austria
| | - Arthur Declercq
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent 9052, Belgium
- Department of Biomolecular Medicine, Ghent University, Ghent 9052, Belgium
| | - Marina Strobl
- Bioinformatics Research Group, University of Applied Sciences Upper Austria, Hagenberg 4232, Austria
| | - Robbin Bouwmeester
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent 9052, Belgium
- Department of Biomolecular Medicine, Ghent University, Ghent 9052, Belgium
| | - Sven Degroeve
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent 9052, Belgium
- Department of Biomolecular Medicine, Ghent University, Ghent 9052, Belgium
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent 9052, Belgium
- Department of Biomolecular Medicine, Ghent University, Ghent 9052, Belgium
| | - Viktoria Dorfer
- Bioinformatics Research Group, University of Applied Sciences Upper Austria, Hagenberg 4232, Austria
| | - Ralf Gabriels
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent 9052, Belgium
- Department of Biomolecular Medicine, Ghent University, Ghent 9052, Belgium
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39
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Kwon Y, Woo J, Yu F, Williams SM, Markillie LM, Moore RJ, Nakayasu ES, Chen J, Campbell-Thompson M, Mathews CE, Nesvizhskii AI, Qia WJ, Zhu Y. Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.04.583367. [PMID: 38496682 PMCID: PMC10942300 DOI: 10.1101/2024.03.04.583367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in both normal and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 μm and the largest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in terms of identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables to identify protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.
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Affiliation(s)
- Yumi Kwon
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Jongmin Woo
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Fengchao Yu
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, United States
| | - Sarah M. Williams
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Lye Meng Markillie
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Ronald J. Moore
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Ernesto S. Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Jing Chen
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL 32610, United States
| | - Martha Campbell-Thompson
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL 32610, United States
| | - Clayton E. Mathews
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL 32610, United States
| | - Alexey I. Nesvizhskii
- Department of Pathology, University of Michigan, Ann Arbor, MI 48109, United States
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, United States
| | - Wei-Jun Qia
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Ying Zhu
- Department of Microchemistry, Proteomics, Lipidomics and Next Generation Sequencing, Genentech, 1 DNA Way, South San Francisco, CA 94080, United States
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40
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Kashima Y, Reteng P, Haga Y, Yamagishi J, Suzuki Y. Single-cell analytical technologies: uncovering the mechanisms behind variations in immune responses. FEBS J 2024; 291:819-831. [PMID: 36082537 DOI: 10.1111/febs.16622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 08/25/2022] [Accepted: 09/08/2022] [Indexed: 11/30/2022]
Abstract
The immune landscape varies among individuals. It determines the immune response and results in surprisingly diverse symptoms, even in response to similar external stimuli. However, the detailed mechanisms underlying such diverse immune responses have remained mostly elusive. The utilization of recently developed single-cell multimodal analysis platforms has started to answer this question. Emerging studies have elucidated several molecular networks that may explain diversity with respect to age or other factors. An elaborate interplay between inherent physical conditions and environmental conditions has been demonstrated. Furthermore, the importance of modifications by the epigenome resulting in transcriptome variation among individuals is gradually being revealed. Accordingly, epigenomes and transcriptomes are direct indicators of the medical history and dynamic interactions with environmental factors. Coronavirus disease 2019 (COVID-19) has recently become one of the most remarkable examples of the necessity of in-depth analyses of diverse responses with respect to various factors to improve treatment in severe cases and to prevent viral transmission from asymptomatic carriers. In fact, determining why some patients develop serious symptoms is still a pressing issue. Here, we review the current "state of the art" in single-cell analytical technologies and their broad applications to healthy individuals and representative diseases, including COVID-19.
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Affiliation(s)
- Yukie Kashima
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
| | - Patrick Reteng
- Division of Collaboration and Education, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Yasuhiko Haga
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
| | - Junya Yamagishi
- Division of Collaboration and Education, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Yutaka Suzuki
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
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41
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Lin A, Ramaswamy Y, Misra A. Developmental heterogeneity of vascular cells: Insights into cellular plasticity in atherosclerosis? Semin Cell Dev Biol 2024; 155:3-15. [PMID: 37316416 DOI: 10.1016/j.semcdb.2023.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 05/30/2023] [Accepted: 06/06/2023] [Indexed: 06/16/2023]
Abstract
Smooth muscle cells, endothelial cells and macrophages display remarkable heterogeneity within the healthy vasculature and under pathological conditions. During development, these cells arise from numerous embryological origins, which confound with different microenvironments to generate postnatal vascular cell diversity. In the atherosclerotic plaque milieu, all these cell types exhibit astonishing plasticity, generating a variety of plaque burdening or plaque stabilizing phenotypes. And yet how developmental origin influences intraplaque cell plasticity remains largely unexplored despite evidence suggesting this may be the case. Uncovering the diversity and plasticity of vascular cells is being revolutionized by unbiased single cell whole transcriptome analysis techniques that will likely continue to pave the way for therapeutic research. Cellular plasticity is only just emerging as a target for future therapeutics, and uncovering how intraplaque plasticity differs across vascular beds may provide key insights into why different plaques behave differently and may confer different risks of subsequent cardiovascular events.
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Affiliation(s)
- Alexander Lin
- Atherosclerosis and Vascular Remodeling Group, Heart Research Institute, Sydney, NSW, Australia; School of Biomedical Engineering, Faculty of Engineering, The University of Sydney, Sydney, NSW, Australia
| | - Yogambha Ramaswamy
- School of Biomedical Engineering, Faculty of Engineering, The University of Sydney, Sydney, NSW, Australia
| | - Ashish Misra
- Atherosclerosis and Vascular Remodeling Group, Heart Research Institute, Sydney, NSW, Australia; Heart Research Institute, The University of Sydney, Sydney, NSW, Australia; Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
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42
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Xie YR, Castro DC, Rubakhin SS, Trinklein TJ, Sweedler JV, Lam F. Multiscale biochemical mapping of the brain through deep-learning-enhanced high-throughput mass spectrometry. Nat Methods 2024; 21:521-530. [PMID: 38366241 PMCID: PMC10927565 DOI: 10.1038/s41592-024-02171-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 01/08/2024] [Indexed: 02/18/2024]
Abstract
Spatial omics technologies can reveal the molecular intricacy of the brain. While mass spectrometry imaging (MSI) provides spatial localization of compounds, comprehensive biochemical profiling at a brain-wide scale in three dimensions by MSI with single-cell resolution has not been achieved. We demonstrate complementary brain-wide and single-cell biochemical mapping using MEISTER, an integrative experimental and computational mass spectrometry (MS) framework. Our framework integrates a deep-learning-based reconstruction that accelerates high-mass-resolving MS by 15-fold, multimodal registration creating three-dimensional (3D) molecular distributions and a data integration method fitting cell-specific mass spectra to 3D datasets. We imaged detailed lipid profiles in tissues with millions of pixels and in large single-cell populations acquired from the rat brain. We identified region-specific lipid contents and cell-specific localizations of lipids depending on both cell subpopulations and anatomical origins of the cells. Our workflow establishes a blueprint for future development of multiscale technologies for biochemical characterization of the brain.
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Affiliation(s)
- Yuxuan Richard Xie
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Daniel C Castro
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Department of Molecular and Integrative Physiology, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Stanislav S Rubakhin
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Timothy J Trinklein
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Jonathan V Sweedler
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- Department of Molecular and Integrative Physiology, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- Carle-Illinois College of Medicine, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA.
| | - Fan Lam
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- Carle-Illinois College of Medicine, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA.
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43
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Schlotter T, Kloter T, Hengsteler J, Yang K, Zhan L, Ragavan S, Hu H, Zhang X, Duru J, Vörös J, Zambelli T, Nakatsuka N. Aptamer-Functionalized Interface Nanopores Enable Amino Acid-Specific Peptide Detection. ACS NANO 2024; 18:6286-6297. [PMID: 38355286 PMCID: PMC10906075 DOI: 10.1021/acsnano.3c10679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 02/06/2024] [Accepted: 02/08/2024] [Indexed: 02/16/2024]
Abstract
Single-molecule proteomics based on nanopore technology has made significant advances in recent years. However, to achieve nanopore sensing with single amino acid resolution, several bottlenecks must be tackled: controlling nanopore sizes with nanoscale precision and slowing molecular translocation events. Herein, we address these challenges by integrating amino acid-specific DNA aptamers into interface nanopores with dynamically tunable pore sizes. A phenylalanine aptamer was used as a proof-of-concept: aptamer recognition of phenylalanine moieties led to the retention of specific peptides, slowing translocation speeds. Importantly, while phenylalanine aptamers were isolated against the free amino acid, the aptamers were determined to recognize the combination of the benzyl or phenyl and the carbonyl group in the peptide backbone, enabling binding to specific phenylalanine-containing peptides. We decoupled specific binding between aptamers and phenylalanine-containing peptides from nonspecific interactions (e.g., electrostatics and hydrophobic interactions) using optical waveguide lightmode spectroscopy. Aptamer-modified interface nanopores differentiated peptides containing phenylalanine vs. control peptides with structurally similar amino acids (i.e., tyrosine and tryptophan). When the duration of aptamer-target interactions inside the nanopore were prolonged by lowering the applied voltage, discrete ionic current levels with repetitive motifs were observed. Such reoccurring signatures in the measured signal suggest that the proposed method has the possibility to resolve amino acid-specific aptamer recognition, a step toward single-molecule proteomics.
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Affiliation(s)
- Tilman Schlotter
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Tom Kloter
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Julian Hengsteler
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Kyungae Yang
- Department
of Medicine, Columbia University Irving
Medical Center, New York, New York 10032, United States
| | - Lijian Zhan
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Sujeni Ragavan
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Haiying Hu
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Xinyu Zhang
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Jens Duru
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - János Vörös
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Tomaso Zambelli
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Nako Nakatsuka
- Laboratory
of Biosensors and Bioelectronics, Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
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44
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Figueroa-Navedo AM, Ivanov AR. Experimental and data analysis advances in thermal proteome profiling. CELL REPORTS METHODS 2024; 4:100717. [PMID: 38412830 PMCID: PMC10921035 DOI: 10.1016/j.crmeth.2024.100717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 12/17/2023] [Accepted: 02/05/2024] [Indexed: 02/29/2024]
Abstract
Method development for mass spectrometry (MS)-based thermal shift proteomic assays have advanced to probe small molecules with known and unknown protein-ligand interaction mechanisms and specificity, which is predominantly used in characterization of drug-protein interactions. In the discovery of target and off-target protein-ligand interactions, a thorough investigation of method development and their impact on the sensitivity and accuracy of protein-small molecule and protein-protein interactions is warranted. In this review, we discuss areas of improvement at each stage of thermal proteome profiling data analysis that includes processing of MS-based data, method development, and their effect on the overall quality of thermal proteome profiles. We also overview the optimization of experimental strategies and prioritization of an increased number of independent biological replicates over the number of evaluated temperatures.
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Affiliation(s)
- Amanda M Figueroa-Navedo
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA
| | - Alexander R Ivanov
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA.
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45
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Tatarūnas V, Čiapienė I, Giedraitienė A. Precise Therapy Using the Selective Endogenous Encapsidation for Cellular Delivery Vector System. Pharmaceutics 2024; 16:292. [PMID: 38399346 PMCID: PMC10893373 DOI: 10.3390/pharmaceutics16020292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 02/13/2024] [Accepted: 02/16/2024] [Indexed: 02/25/2024] Open
Abstract
Interindividual variability in drug response is a major problem in the prescription of pharmacological treatments. The therapeutic effect of drugs can be influenced by human genes. Pharmacogenomic guidelines for individualization of treatment have been validated and used for conventional dosage forms. However, drugs can often target non-specific areas and produce both desired and undesired pharmacological effects. The use of nanoparticles, liposomes, or other available forms for drug formulation could help to overcome the latter problem. Virus-like particles based on retroviruses could be a potential envelope for safe and efficient drug formulations. Human endogenous retroviruses would make it possible to overcome the host immune response and deliver drugs to the desired target. PEG10 is a promising candidate that can bind to mRNA because it is secreted like an enveloped virus-like extracellular vesicle. PEG10 is a retrotransposon-derived gene that has been domesticated. Therefore, formulations with PEG10 may have a lower immunogenicity. The use of existing knowledge can lead to the development of suitable drug formulations for the precise treatment of individual diseases.
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Affiliation(s)
- Vacis Tatarūnas
- Institute of Cardiology, Lithuanian University of Health Sciences, Sukileliu 15, LT 50103 Kaunas, Lithuania; (V.T.); (I.Č.)
| | - Ieva Čiapienė
- Institute of Cardiology, Lithuanian University of Health Sciences, Sukileliu 15, LT 50103 Kaunas, Lithuania; (V.T.); (I.Č.)
| | - Agnė Giedraitienė
- Institute of Microbiology and Virology, Lithuanian University of Health Sciences, Eiveniu 4, LT 50161 Kaunas, Lithuania
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46
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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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47
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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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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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49
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Pade LR, Lombard-Banek C, Li J, Nemes P. Dilute to Enrich for Deeper Proteomics: A Yolk-Depleted Carrier for Limited Populations of Embryonic (Frog) Cells. J Proteome Res 2024; 23:692-703. [PMID: 37994825 PMCID: PMC10872351 DOI: 10.1021/acs.jproteome.3c00541] [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: 11/24/2023]
Abstract
Abundant proteins challenge deep mass spectrometry (MS) analysis of the proteome. Yolk, the source of food in many developing vertebrate embryos, complicates chemical separation and interferes with detection. We report here a strategy that enhances bottom-up proteomics in yolk-laden specimens by diluting the interferences using a yolk-depleted carrier (YODEC) proteome via isobaric multiplexing quantification. This method was tested on embryos of the South African Clawed Frog (Xenopus laevis), where a >90% yolk proteome content challenges deep proteomics. As a proof of concept, we isolated neural and epidermal fated cell clones from the embryo by dissection or fluorescence-activated cell sorting. Compared with the standard multiplexing carrier approach, YODEC more than doubled the detectable X. laevis proteome, identifying 5,218 proteins from D11 cell clones dissected from the embryo. Ca. ∼80% of the proteins were quantified without dropouts in any of the analytical channels. YODEC with high-pH fractionation quantified 3,133 proteins from ∼8,000 V11 cells that were sorted from ca. 2 embryos (1.5 μg total, or 150 ng yolk-free proteome), marking a 15-fold improvement in proteome coverage vs the standard proteomics approach. About 60% of these proteins were only quantifiable by YODEC, including molecular adaptors, transporters, translation, and transcription factors. While this study was tailored to limited populations of Xenopus cells, we anticipate the approach of "dilute to enrich" using a depleted carrier proteome to be adaptable to other biological models in which abundant proteins challenge deep MS proteomics.
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Affiliation(s)
- Leena R. Pade
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD, 20742
| | - Camille Lombard-Banek
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD, 20742
| | - Jie Li
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD, 20742
| | - Peter Nemes
- Department of Chemistry & Biochemistry, University of Maryland, College Park, MD, 20742
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50
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Veličković M, Wu R, Gao Y, Thairu MW, Veličković D, Munoz N, Clendinen CS, Bilbao A, Chu RK, Lalli PM, Zemaitis K, Nicora CD, Kyle JE, Orton D, Williams S, Zhu Y, Zhao R, Monroe ME, Moore RJ, Webb-Robertson BJM, Bramer LM, Currie CR, Piehowski PD, Burnum-Johnson KE. Mapping microhabitats of lignocellulose decomposition by a microbial consortium. Nat Chem Biol 2024:10.1038/s41589-023-01536-7. [PMID: 38302607 DOI: 10.1038/s41589-023-01536-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Accepted: 12/20/2023] [Indexed: 02/03/2024]
Abstract
The leaf-cutter ant fungal garden ecosystem is a naturally evolved model system for efficient plant biomass degradation. Degradation processes mediated by the symbiotic fungus Leucoagaricus gongylophorus are difficult to characterize due to dynamic metabolisms and spatial complexity of the system. Herein, we performed microscale imaging across 12-µm-thick adjacent sections of Atta cephalotes fungal gardens and applied a metabolome-informed proteome imaging approach to map lignin degradation. This approach combines two spatial multiomics mass spectrometry modalities that enabled us to visualize colocalized metabolites and proteins across and through the fungal garden. Spatially profiled metabolites revealed an accumulation of lignin-related products, outlining morphologically unique lignin microhabitats. Metaproteomic analyses of these microhabitats revealed carbohydrate-degrading enzymes, indicating a prominent fungal role in lignocellulose decomposition. Integration of metabolome-informed proteome imaging data provides a comprehensive view of underlying biological pathways to inform our understanding of metabolic fungal pathways in plant matter degradation within the micrometer-scale environment.
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Affiliation(s)
- Marija Veličković
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Ruonan Wu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Yuqian Gao
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Margaret W Thairu
- Wisconsin Institute for Discovery and Department of Plant Pathology, University of Wisconsin-Madison, Madison, WI, USA
| | - Dušan Veličković
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Nathalie Munoz
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Chaevien S Clendinen
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Aivett Bilbao
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Rosalie K Chu
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Priscila M Lalli
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Kevin Zemaitis
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Carrie D Nicora
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Jennifer E Kyle
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Daniel Orton
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Sarai Williams
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Ying Zhu
- Department of Microchemistry, Proteomics, Lipidomics, and Next Generation Sequencing, Genentech, San Francisco, CA, USA
| | - Rui Zhao
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Matthew E Monroe
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Ronald J Moore
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | | | - Lisa M Bramer
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Cameron R Currie
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
- Department of Biochemistry & Biomedical Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Paul D Piehowski
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Kristin E Burnum-Johnson
- The Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA.
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