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Rivandi M, Franken A, Yang L, Abramova A, Stamm N, Eberhardt J, Gierke B, Beer M, Fehm T, Niederacher D, Pawlak M, Neubauer H. Miniaturized protein profiling permits targeted signaling pathway analysis in individual circulating tumor cells to improve personalized treatment. J Transl Med 2024; 22:848. [PMID: 39304879 DOI: 10.1186/s12967-024-05616-7] [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: 05/13/2024] [Accepted: 08/18/2024] [Indexed: 09/22/2024] Open
Abstract
BACKGROUND Traditional genomic profiling and mutation analysis of single cells like Circulating Tumor Cells (CTCs) fails to capture post-translational and functional alterations of proteins, often leading to limited treatment efficacy. To overcome this gap, we developed a miniaturized 'protein analysis on the single cell level' workflow-baptized ZeptoCTC. It integrates established technologies for single-cell isolation with sensitive Reverse Phase Protein Array (RPPA) analysis, thus enabling the comprehensive assessment of multiple protein expression and activation in individual CTCs. METHODS The ZeptoCTC workflow involves several critical steps. Firstly, individual cells are labeled and isolated. This is followed by cell lysis and the printing of true single cell lysate preparations onto a ZeptoChip using a modified micromanipulator, CellCelector™. The printed lysates then undergo fluorescence immunoassay RPPA protein detection using a ZeptoReader. Finally, signal quantification is carried out with Image J software, ensuring precise measurement of multiple protein levels. RESULTS The efficacy of ZeptoCTC was demonstrated through various applications. Initially, it was used for measuring EpCAM protein expression, a standard marker for CTC detection, revealing higher levels in single MCF-7 over MDA-MB-231 tumor cells. Furthermore, in Capivasertib (Akt-inhibitor)-treated MCF-7 single cells, ZeptoCTC detected a 2-fold increase in the pAkt/Akt ratio compared to control cells, and confirmed co-performed bulk-cell western blot analysis results. Notably, when applied to individual CTCs from metastasized breast cancer patients, ZeptoCTC revealed significant differences in protein activation levels, particularly in measured pAkt and pErk levels, compared to patient-matched WBCs. Moreover, it successfully differentiated between CTCs from patients with different Akt1 genotypes, highlighting its potential to determine the activation status of druggable cancer driving proteins for individual and targeted treatment decision making. CONCLUSIONS The ZeptoCTC workflow represents a valuable tool in single cell cancer research, crucial for personalized medicine. It permits detailed analysis of key proteins and their activation status of targeted, cancer-driven signaling pathways in single cell samples, aiding in understanding tumor response, progression, and treatment efficacy beyond bulk analysis. The method significantly advances clinical investigations in cancer, improving treatment precision and effectiveness. The workflow will be applicable to protein analysis on other types of single cells like relevant in stem cell, neuropathology and hemopoietic cell research.
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Affiliation(s)
- Mahdi Rivandi
- Department of Obstetrics and Gynecology, University Hospital and Medical Faculty of Heinrich Heine University Duesseldorf, Duesseldorf, Germany
- Center for Integrated Oncology (CIO Aachen, Bonn, Cologne, Duesseldorf), Duesseldorf, Germany
| | - André Franken
- Department of Obstetrics and Gynecology, University Hospital and Medical Faculty of Heinrich Heine University Duesseldorf, Duesseldorf, Germany
- Center for Integrated Oncology (CIO Aachen, Bonn, Cologne, Duesseldorf), Duesseldorf, Germany
| | - Liwen Yang
- Department of Obstetrics and Gynecology, University Hospital and Medical Faculty of Heinrich Heine University Duesseldorf, Duesseldorf, Germany
- Center for Integrated Oncology (CIO Aachen, Bonn, Cologne, Duesseldorf), Duesseldorf, Germany
| | - Anna Abramova
- Department of Obstetrics and Gynecology, University Hospital and Medical Faculty of Heinrich Heine University Duesseldorf, Duesseldorf, Germany
- Center for Integrated Oncology (CIO Aachen, Bonn, Cologne, Duesseldorf), Duesseldorf, Germany
| | - Nadia Stamm
- Department of Obstetrics and Gynecology, University Hospital and Medical Faculty of Heinrich Heine University Duesseldorf, Duesseldorf, Germany
- Center for Integrated Oncology (CIO Aachen, Bonn, Cologne, Duesseldorf), Duesseldorf, Germany
| | | | | | - Meike Beer
- NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany
| | - Tanja Fehm
- Department of Obstetrics and Gynecology, University Hospital and Medical Faculty of Heinrich Heine University Duesseldorf, Duesseldorf, Germany
- Center for Integrated Oncology (CIO Aachen, Bonn, Cologne, Duesseldorf), Duesseldorf, Germany
| | - Dieter Niederacher
- Department of Obstetrics and Gynecology, University Hospital and Medical Faculty of Heinrich Heine University Duesseldorf, Duesseldorf, Germany
- Center for Integrated Oncology (CIO Aachen, Bonn, Cologne, Duesseldorf), Duesseldorf, Germany
| | | | - Hans Neubauer
- Department of Obstetrics and Gynecology, University Hospital and Medical Faculty of Heinrich Heine University Duesseldorf, Duesseldorf, Germany.
- Center for Integrated Oncology (CIO Aachen, Bonn, Cologne, Duesseldorf), Duesseldorf, Germany.
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Cai Y. Conjugation of primary amine groups in targeted proteomics. MASS SPECTROMETRY REVIEWS 2024. [PMID: 39229771 DOI: 10.1002/mas.21906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 03/21/2024] [Accepted: 08/12/2024] [Indexed: 09/05/2024]
Abstract
Primary amines, in the form of unmodified N-terminus of peptide/protein and unmodified lysine residue, are perhaps the most important functional groups that can serve as the starting points in proteomic analysis, especially via mass spectrometry-based approaches. A variety of multifunctional probes that conjugate primary amine groups through covalent bonds have been developed and employed to facilitate protein/protein complex characterization, including identification, quantification, structure and localization elucidation, protein-protein interaction investigation, and so forth. As an integral part of more accurate peptide quantification in targeted proteomics, isobaric stable isotope-coded primary amine labeling approaches eventually facilitated protein/peptide characterization at the single-cell level, paving the way for single-cell proteomics. The development and advances in the field can be reviewed in terms of key components of a multifunctional probe: functional groups and chemistry for primary amine conjugation; hetero-bifunctional moiety for separation/enrichment of conjugated protein/protein complex; and functionalized linker/spacer. Perspectives are primarily focused on optimizing primary amine conjugation under physiological conditions to improve characterization of native proteins, especially those associated with the surface of living cells/microorganisms.
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Affiliation(s)
- Yang Cai
- Department of Chemistry, University of New Orleans, New Orleans, Louisiana, USA
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Li M, Zuo J, Yang K, Wang P, Zhou S. Proteomics mining of cancer hallmarks on a single-cell resolution. MASS SPECTROMETRY REVIEWS 2024; 43:1019-1040. [PMID: 37051664 DOI: 10.1002/mas.21842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 11/25/2022] [Accepted: 03/15/2023] [Indexed: 06/19/2023]
Abstract
Dysregulated proteome is an essential contributor in carcinogenesis. Protein fluctuations fuel the progression of malignant transformation, such as uncontrolled proliferation, metastasis, and chemo/radiotherapy resistance, which severely impair therapeutic effectiveness and cause disease recurrence and eventually mortality among cancer patients. Cellular heterogeneity is widely observed in cancer and numerous cell subtypes have been characterized that greatly influence cancer progression. Population-averaged research may not fully reveal the heterogeneity, leading to inaccurate conclusions. Thus, deep mining of the multiplex proteome at the single-cell resolution will provide new insights into cancer biology, to develop prognostic biomarkers and treatments. Considering the recent advances in single-cell proteomics, herein we review several novel technologies with particular focus on single-cell mass spectrometry analysis, and summarize their advantages and practical applications in the diagnosis and treatment for cancer. Technological development in single-cell proteomics will bring a paradigm shift in cancer detection, intervention, and therapy.
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Affiliation(s)
- Maomao Li
- Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE and State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan, China
| | - Jing Zuo
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, and West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China
| | - Kailin Yang
- Department of Radiation Oncology, Taussig Cancer Center, Cleveland Clinic, Cleveland, Ohio, USA
| | - Ping Wang
- Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE and State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan, China
| | - Shengtao Zhou
- Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE and State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan, China
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Chari T, Gorin G, Pachter L. Biophysically interpretable inference of cell types from multimodal sequencing data. NATURE COMPUTATIONAL SCIENCE 2024; 4:677-689. [PMID: 39317762 DOI: 10.1038/s43588-024-00689-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 08/08/2024] [Indexed: 09/26/2024]
Abstract
Multimodal, single-cell genomics technologies enable simultaneous measurement of multiple facets of DNA and RNA processing in the cell. This creates opportunities for transcriptome-wide, mechanistic studies of cellular processing in heterogeneous cell populations, such as regulation of cell fate by transcriptional stochasticity or tumor proliferation through aberrant splicing dynamics. However, current methods for determining cell types or 'clusters' in multimodal data often rely on ad hoc approaches to balance or integrate measurements, and assumptions ignoring inherent properties of the data. To enable interpretable and consistent cell cluster determination, we present meK-means (mechanistic K-means) which integrates modalities through a unifying model of transcription to learn underlying, shared biophysical states. With meK-means we can cluster cells with nascent and mature mRNA measurements, utilizing the causal, physical relationships between these modalities. This identifies shared transcription dynamics across cells, which induce the observed molecule counts, and provides an alternative definition for 'clusters' through the governing parameters of cellular processes.
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Affiliation(s)
- Tara Chari
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | | | - Lior Pachter
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
- Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA.
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Piana D, Iavarone F, De Paolis E, Daniele G, Parisella F, Minucci A, Greco V, Urbani A. Phenotyping Tumor Heterogeneity through Proteogenomics: Study Models and Challenges. Int J Mol Sci 2024; 25:8830. [PMID: 39201516 PMCID: PMC11354793 DOI: 10.3390/ijms25168830] [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: 06/23/2024] [Revised: 07/31/2024] [Accepted: 08/06/2024] [Indexed: 09/02/2024] Open
Abstract
Tumor heterogeneity refers to the diversity observed among tumor cells: both between different tumors (inter-tumor heterogeneity) and within a single tumor (intra-tumor heterogeneity). These cells can display distinct morphological and phenotypic characteristics, including variations in cellular morphology, metastatic potential and variability treatment responses among patients. Therefore, a comprehensive understanding of such heterogeneity is necessary for deciphering tumor-specific mechanisms that may be diagnostically and therapeutically valuable. Innovative and multidisciplinary approaches are needed to understand this complex feature. In this context, proteogenomics has been emerging as a significant resource for integrating omics fields such as genomics and proteomics. By combining data obtained from both Next-Generation Sequencing (NGS) technologies and mass spectrometry (MS) analyses, proteogenomics aims to provide a comprehensive view of tumor heterogeneity. This approach reveals molecular alterations and phenotypic features related to tumor subtypes, potentially identifying therapeutic biomarkers. Many achievements have been made; however, despite continuous advances in proteogenomics-based methodologies, several challenges remain: in particular the limitations in sensitivity and specificity and the lack of optimal study models. This review highlights the impact of proteogenomics on characterizing tumor phenotypes, focusing on the critical challenges and current limitations of its use in different clinical and preclinical models for tumor phenotypic characterization.
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Affiliation(s)
- Diletta Piana
- Department of Basic Biotechnological Sciences, Intensivological and Perioperative Clinics, Università Cattolica del Sacro Cuore, 00168 Rome, Italy; (D.P.); (F.I.); (F.P.)
- Departmen Unity of Chemistry, Biochemistry and Clinical Molecular Biology, Department of Diagnostic and Laboratory Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (E.D.P.); (A.M.)
| | - Federica Iavarone
- Department of Basic Biotechnological Sciences, Intensivological and Perioperative Clinics, Università Cattolica del Sacro Cuore, 00168 Rome, Italy; (D.P.); (F.I.); (F.P.)
- Departmen Unity of Chemistry, Biochemistry and Clinical Molecular Biology, Department of Diagnostic and Laboratory Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (E.D.P.); (A.M.)
| | - Elisa De Paolis
- Departmen Unity of Chemistry, Biochemistry and Clinical Molecular Biology, Department of Diagnostic and Laboratory Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (E.D.P.); (A.M.)
- Departmental Unit of Molecular and Genomic Diagnostics, Genomics Core Facility, Gemelli Science and Technology Park (G-STeP), Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
| | - Gennaro Daniele
- Phase 1 Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy;
| | - Federico Parisella
- Department of Basic Biotechnological Sciences, Intensivological and Perioperative Clinics, Università Cattolica del Sacro Cuore, 00168 Rome, Italy; (D.P.); (F.I.); (F.P.)
| | - Angelo Minucci
- Departmen Unity of Chemistry, Biochemistry and Clinical Molecular Biology, Department of Diagnostic and Laboratory Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (E.D.P.); (A.M.)
- Departmental Unit of Molecular and Genomic Diagnostics, Genomics Core Facility, Gemelli Science and Technology Park (G-STeP), Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
| | - Viviana Greco
- Department of Basic Biotechnological Sciences, Intensivological and Perioperative Clinics, Università Cattolica del Sacro Cuore, 00168 Rome, Italy; (D.P.); (F.I.); (F.P.)
- Departmen Unity of Chemistry, Biochemistry and Clinical Molecular Biology, Department of Diagnostic and Laboratory Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (E.D.P.); (A.M.)
| | - Andrea Urbani
- Department of Basic Biotechnological Sciences, Intensivological and Perioperative Clinics, Università Cattolica del Sacro Cuore, 00168 Rome, Italy; (D.P.); (F.I.); (F.P.)
- Departmen Unity of Chemistry, Biochemistry and Clinical Molecular Biology, Department of Diagnostic and Laboratory Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy; (E.D.P.); (A.M.)
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Sun F, Li H, Sun D, Fu S, Gu L, Shao X, Wang Q, Dong X, Duan B, Xing F, Wu J, Xiao M, Zhao F, Han JDJ, Liu Q, Fan X, Li C, Wang C, Shi T. Single-cell omics: experimental workflow, data analyses and applications. SCIENCE CHINA. LIFE SCIENCES 2024:10.1007/s11427-023-2561-0. [PMID: 39060615 DOI: 10.1007/s11427-023-2561-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/18/2024] [Indexed: 07/28/2024]
Abstract
Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome, proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field, offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.
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Affiliation(s)
- Fengying Sun
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China
| | - Haoyan Li
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Dongqing Sun
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Shaliu Fu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Lei Gu
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Shao
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China
| | - Qinqin Wang
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xin Dong
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Bin Duan
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China
| | - Feiyang Xing
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Jun Wu
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Minmin Xiao
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
| | - Fangqing Zhao
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Qi Liu
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine, Shanghai East Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Research Institute of Intelligent Computing, Zhejiang Lab, Hangzhou, 311121, China.
- Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China.
| | - Xiaohui Fan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
- National Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314103, China.
- Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China.
| | - Chen Li
- Center for Single-cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Chenfei Wang
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University), Ministry of Education, Orthopaedic Department, Tongji Hospital, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200082, China.
- Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Tieliu Shi
- Department of Clinical Laboratory, the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City), Wuhu, 241000, China.
- Center for Bioinformatics and Computational Biology, Shanghai Key Laboratory of Regulatory Biology, the Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
- Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, School of Statistics, East China Normal University, Shanghai, 200062, China.
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Zhou L, Na J, Liu X, Wu P. Chromophore-Assisted Light Inactivation for Protein Degradation and Its Application in Biomedicine. Bioengineering (Basel) 2024; 11:651. [PMID: 39061733 PMCID: PMC11273424 DOI: 10.3390/bioengineering11070651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 06/24/2024] [Accepted: 06/25/2024] [Indexed: 07/28/2024] Open
Abstract
The functional investigation of proteins holds immense significance in unraveling physiological and pathological mechanisms of organisms as well as advancing the development of novel pharmaceuticals in biomedicine. However, the study of cellular protein function using conventional genetic manipulation methods may yield unpredictable outcomes and erroneous conclusions. Therefore, precise modulation of protein activity within cells holds immense significance in the realm of biomedical research. Chromophore-assisted light inactivation (CALI) is a technique that labels photosensitizers onto target proteins and induces the production of reactive oxygen species through light control to achieve precise inactivation of target proteins. Based on the type and characteristics of photosensitizers, different excitation light sources and labeling methods are selected. For instance, KillerRed forms a fusion protein with the target protein through genetic engineering for labeling and inactivates the target protein via light activation. CALI is presently predominantly employed in diverse biomedical domains encompassing investigations into protein functionality and interaction, intercellular signal transduction research, as well as cancer exploration and therapy. With the continuous advancement of CALI technology, it is anticipated to emerge as a formidable instrument in the realm of life sciences, yielding more captivating outcomes for fundamental life sciences and precise disease diagnosis and treatment.
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Affiliation(s)
- Lvjia Zhou
- State Key Laboratory of Targeting Oncology, National Center for International Research of Bio-Targeting Theranostics, Guangxi Key Laboratory of Bio-Targeting Theranostics, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning 530021, China; (L.Z.); (J.N.)
| | - Jintong Na
- State Key Laboratory of Targeting Oncology, National Center for International Research of Bio-Targeting Theranostics, Guangxi Key Laboratory of Bio-Targeting Theranostics, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning 530021, China; (L.Z.); (J.N.)
| | - Xiyu Liu
- State Key Laboratory of Targeting Oncology, National Center for International Research of Bio-Targeting Theranostics, Guangxi Key Laboratory of Bio-Targeting Theranostics, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning 530021, China; (L.Z.); (J.N.)
| | - Pan Wu
- State Key Laboratory of Targeting Oncology, National Center for International Research of Bio-Targeting Theranostics, Guangxi Key Laboratory of Bio-Targeting Theranostics, Collaborative Innovation Center for Targeting Tumor Diagnosis and Therapy, Guangxi Medical University, Nanning 530021, China; (L.Z.); (J.N.)
- School of Pharmacy, Guangxi Medical University, Nanning 530021, China
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8
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Ge T, Hu W, Zhang Z, He X, Wang L, Han X, Dai Z. Open and closed microfluidics for biosensing. Mater Today Bio 2024; 26:101048. [PMID: 38633866 PMCID: PMC11022104 DOI: 10.1016/j.mtbio.2024.101048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 04/01/2024] [Accepted: 04/03/2024] [Indexed: 04/19/2024] Open
Abstract
Biosensing is vital for many areas like disease diagnosis, infectious disease prevention, and point-of-care monitoring. Microfluidics has been evidenced to be a powerful tool for biosensing via integrating biological detection processes into a palm-size chip. Based on the chip structure, microfluidics has two subdivision types: open microfluidics and closed microfluidics, whose operation methods would be diverse. In this review, we summarize fundamentals, liquid control methods, and applications of open and closed microfluidics separately, point out the bottlenecks, and propose potential directions of microfluidics-based biosensing.
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Affiliation(s)
- Tianxin Ge
- Guangdong Provincial Key Laboratory of Sensing Technology and Biomedical Instrument, School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, No.66, Gongchang Road, Guangming District, Shenzhen, Guangdong, 518107, PR China
| | - Wenxu Hu
- Guangdong Provincial Key Laboratory of Sensing Technology and Biomedical Instrument, School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, No.66, Gongchang Road, Guangming District, Shenzhen, Guangdong, 518107, PR China
| | - Zilong Zhang
- Guangdong Provincial Key Laboratory of Sensing Technology and Biomedical Instrument, School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, No.66, Gongchang Road, Guangming District, Shenzhen, Guangdong, 518107, PR China
| | - Xuexue He
- Guangdong Provincial Key Laboratory of Sensing Technology and Biomedical Instrument, School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, No.66, Gongchang Road, Guangming District, Shenzhen, Guangdong, 518107, PR China
| | - Liqiu Wang
- Department of Mechanical Engineering, The Hong Kong Polytechnic University, 999077, Hong Kong, PR China
| | - Xing Han
- Guangdong Provincial Key Laboratory of Sensing Technology and Biomedical Instrument, School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, No.66, Gongchang Road, Guangming District, Shenzhen, Guangdong, 518107, PR China
| | - Zong Dai
- Guangdong Provincial Key Laboratory of Sensing Technology and Biomedical Instrument, School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, No.66, Gongchang Road, Guangming District, Shenzhen, Guangdong, 518107, PR China
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Xie H, Guo W, Jiang H, Zhang T, Zhao L, Hu J, Gao S, Song S, Xu J, Xu L, Sun X, Ding Y, Jiang L, Ding X. Photosensitive Hydrogel with Temperature-Controlled Reversible Nano-Apertures for Single-Cell Protein Analysis. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2308569. [PMID: 38483955 PMCID: PMC11109651 DOI: 10.1002/advs.202308569] [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: 11/09/2023] [Revised: 02/15/2024] [Indexed: 05/23/2024]
Abstract
Single cell western blot (scWB) is one of the most important methods for cellular heterogeneity profiling. However, current scWB based on conventional photoactive polyacrylamide hydrogel material suffers from the tradeoff between in-gel probing and separation resolution. Here, a highly sensitive temperature-controlled single-cell western blotting (tc-scWB) method is introduced, which is based on a thermo/photo-dualistic-sensitive polyacrylamide hydrogel, namely acrylic acid-functionalized graphene oxide (AFGO) assisted, N-isopropylacrylamide modified polyacrylamide (ANP) hydrogel. The ANP hydrogel is contracted at high-temperature to constrain protein band diffusion during microchip electrophoretic separation, while the gel aperture is expanded under low-temperature for better antibody penetration into the hydrogel. The tc-scWB method enables the separation and profiling of small-molecule-weight proteins with highly crosslinked gel (12% T) in SDS-PAGE. The tc-scWB is demonstrated on three metabolic and ER stress-specific proteins (CHOP, MDH2 and FH) in four pancreatic cell subtypes, revealing the expression of key enzymes in the Krebs cycle is upregulated with enhanced ER stress. It is found that ER stress can regulate crucial enzyme (MDH2 and FH) activities of metabolic cascade in cancer cells, boosting aerobic respiration to attenuate the Warburg effect and promote cell apoptosis. The tc-scWB is a general toolbox for the analysis of low-abundance small-molecular functional proteins at the single-cell level.
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Affiliation(s)
- Haiyang Xie
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Wenke Guo
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Hui Jiang
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Ting Zhang
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Lei Zhao
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Jinjuan Hu
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Shuxin Gao
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Sunfengda Song
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Jiasu Xu
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Li Xu
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Xinyi Sun
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Yi Ding
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Lai Jiang
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Xianting Ding
- Department of Anesthesiology and Surgical Intensive Care UnitXinhua HospitalSchool of Medicine and School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200092China
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
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10
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Tian T, Lin S, Yang C. Beyond single cells: microfluidics empowering multiomics analysis. Anal Bioanal Chem 2024; 416:2203-2220. [PMID: 38008783 DOI: 10.1007/s00216-023-05028-4] [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: 09/09/2023] [Revised: 10/26/2023] [Accepted: 10/30/2023] [Indexed: 11/28/2023]
Abstract
Single-cell multiomics technologies empower simultaneous measurement of multiple types of molecules within individual cells, providing a more profound comprehension compared with the analysis of discrete molecular layers from different cells. Microfluidic technology, on the other hand, has emerged as a pivotal facilitator for high-throughput single-cell analysis, offering precise control and manipulation of individual cells. The primary focus of this review encompasses an appraisal of cutting-edge microfluidic platforms employed in the realm of single-cell multiomics analysis. Furthermore, it discusses technological advancements in various single-cell omics such as genomics, transcriptomics, epigenomics, and proteomics, with their perspective applications. Finally, it provides future prospects of these integrated single-cell multiomics methodologies, shedding light on the possibilities for future biological research.
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Affiliation(s)
- Tian Tian
- Chemistry and Biomedicine Innovation Center (ChemBIC), School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China
| | - Shichao Lin
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province, Xiamen, 361005, China
| | - Chaoyong Yang
- Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province, Xiamen, 361005, China.
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, State Key Laboratory of Physical Chemistry of Solid Surfaces, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China.
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11
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Jyoti TP, Chandel S, Singh R. Flow cytometry: Aspects and application in plant and biological science. JOURNAL OF BIOPHOTONICS 2024; 17:e202300423. [PMID: 38010848 DOI: 10.1002/jbio.202300423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 10/28/2023] [Indexed: 11/29/2023]
Abstract
Flow cytometry is a potent method that enables the quick and concurrent investigation of several characteristics of single cells in solution. Photodiodes or photomultiplier tubes are employed to detect the dispersed and fluorescent light signals that are produced by the laser beam as it passes through the cells. Photodetectors transform the light signals produced by the laser into electrical impulses. A computer then analyses these electrical impulses to identify and measure the various cell populations depending on their fluorescence or light scattering characteristics. Based on their fluorescence or light scattering properties, cell populations can be examined and/or isolated. This review covers the basic principle, components, working and specific biological applications of flow cytometry, including studies on plant, cell and molecular biology and methods employed for data processing and interpretation as well as the potential future relevance of this methodology in light of retrospective analysis and recent advancements in flow cytometry.
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Affiliation(s)
- Thakur Prava Jyoti
- Department of Pharmacognosy, ISF College of Pharmacy, Moga, Punjab, India
| | - Shivani Chandel
- Department of Pharmacognosy, ISF College of Pharmacy, Moga, Punjab, India
| | - Rajveer Singh
- Department of Pharmacognosy, ISF College of Pharmacy, Moga, Punjab, India
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12
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Lui KO, Ma Z, Dimmeler S. SARS-CoV-2 induced vascular endothelial dysfunction: direct or indirect effects? Cardiovasc Res 2024; 120:34-43. [PMID: 38159046 DOI: 10.1093/cvr/cvad191] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 10/18/2023] [Accepted: 11/03/2023] [Indexed: 01/03/2024] Open
Abstract
Clinical evidence reveals that manifestations of endothelial dysfunction are widely observed in COVID-19 and long-COVID patients. However, whether these detrimental effects are caused by direct infection of the endothelium or are indirectly mediated by systemic inflammation has been a matter of debate. It has been well acknowledged that endothelial cells (ECs) of the cardiovascular system ubiquitously express the SARS-CoV-2 entry receptor angiotensin-converting enzyme 2 (ACE2), yet accumulating evidence suggests that it is more predominantly expressed by pericytes and vascular smooth muscle cells of the mammalian blood vessel. Besides, replicative infection of ECs by SARS-CoV-2 has yet to be demonstrated both in vitro and in vivo. In this study, we review latest research on endothelial ACE2 expression in different vascular beds, and the heterogeneity in various EC subsets with differential ACE2 expression in response to SARS-CoV-2. We also discuss ACE2-independent alternative mechanisms underlying endothelial activation in COVID-19, and the clinical manifestations of SARS-CoV-2-induced endothelial dysfunction. Altogether, understanding ACE2-dependent and ACE2-independent mechanisms driving SARS-CoV-2-induced vascular dysfunction would shed light on strategies of more effective therapies targeting cardiovascular complications associated with COVID-19.
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Affiliation(s)
- Kathy O Lui
- Department of Chemical Pathology, and Li Ka Shing Institute of Health Science, Prince of Wales Hospital, The Chinese University of Hong Kong, 30-32 Ngan Shing Street, Sha Tin, New Territories, 999077 Hong Kong, China
| | - Zhangjing Ma
- Department of Chemical Pathology, and Li Ka Shing Institute of Health Science, Prince of Wales Hospital, The Chinese University of Hong Kong, 30-32 Ngan Shing Street, Sha Tin, New Territories, 999077 Hong Kong, China
| | - Stefanie Dimmeler
- Institute for Cardiovascular Regeneration, and Faculty of Biological Sciences, Goethe University Frankfurt, Theodor Stern Kai 7, 60590 Frankfurt, Germany
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13
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Liu H, Guo Z, Gangurde SS, Garg V, Deng Q, Du P, Lu Q, Chitikineni A, Xiao Y, Wang W, Hong Y, Varshney RK, Chen X. A Single-Nucleus Resolution Atlas of Transcriptome and Chromatin Accessibility for Peanut (Arachis Hypogaea L.) Leaves. Adv Biol (Weinh) 2024; 8:e2300410. [PMID: 37828417 DOI: 10.1002/adbi.202300410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 09/02/2023] [Indexed: 10/14/2023]
Abstract
The peanut is an important worldwide cash-crop for edible oil and protein. However, the kinetic mechanisms that determine gene expression and chromatin accessibility during leaf development in peanut represented allotetraploid leguminous crops are poorly understood at single-cell resolution. Here, a single-nucleus atlas of peanut leaves is developed by simultaneously profiling the transcriptome and chromatin accessibility in the same individual-cell using fluorescence-activated sorted single-nuclei. In total, 5930 cells with 50 890 expressed genes are classified into 18 cell-clusters, and 5315 chromatin fragments are enriched with 26 083 target genes in the chromatin accessible landscape. The developmental trajectory analysis reveals the involvement of the ethylene-AP2 module in leaf cell differentiation, and cell-cycle analysis demonstrated that genome replication featured in distinct cell-types with circadian rhythms transcription factors (TFs). Furthermore, dual-omics illustrates that the fatty acid pathway modulates epidermal-guard cells differentiation and providescritical TFs interaction networks for understanding mesophyll development, and the cytokinin module (LHY/LOG) that regulates vascular growth. Additionally, an AT-hook protein AhAHL11 is identified that promotes leaf area expansion by modulating the auxin content increase. In summary, the simultaneous profiling of transcription and chromatin accessibility landscapes using snRNA/ATAC-seq provides novel biological insights into the dynamic processes of peanut leaf cell development at the cellular level.
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Affiliation(s)
- Hao Liu
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
| | - Zenhua Guo
- Rice Research Institute of Heilongjiang Academy of Agriculture Sciences, Heilongjiang Province, Jiamusi, 154026, China
| | - Sunil S Gangurde
- USDA-ARS, Crop Genetics and Breeding Research Unit, Department of Plant Pathology, University of Georgia, Tifton, GA, 31793, USA
| | - Vanika Garg
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University (MU), Murdoch, Western Australia, 6150, Australia
| | - Quanqing Deng
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
| | - Puxuan Du
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
| | - Qing Lu
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
| | - Annapurna Chitikineni
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University (MU), Murdoch, Western Australia, 6150, Australia
| | - Yuan Xiao
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
| | - Wenyi Wang
- College of Agriculture, South China Agriculture University, Guangzhou, Guangdong Province, 510642, China
| | - Yanbin Hong
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
| | - Rajeev K Varshney
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University (MU), Murdoch, Western Australia, 6150, Australia
| | - Xiaoping Chen
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
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14
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Chari T, Gorin G, Pachter L. Biophysically Interpretable Inference of Cell Types from Multimodal Sequencing Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.17.558131. [PMID: 37745403 PMCID: PMC10516047 DOI: 10.1101/2023.09.17.558131] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Multimodal, single-cell genomics technologies enable simultaneous capture of multiple facets of DNA and RNA processing in the cell. This creates opportunities for transcriptome-wide, mechanistic studies of cellular processing in heterogeneous cell types, with applications ranging from inferring kinetic differences between cells, to the role of stochasticity in driving heterogeneity. However, current methods for determining cell types or 'clusters' present in multimodal data often rely on ad hoc or independent treatment of modalities, and assumptions ignoring inherent properties of the count data. To enable interpretable and consistent cell cluster determination from multimodal data, we present meK-Means (mechanistic K-Means) which integrates modalities and learns underlying, shared biophysical states through a unifying model of transcription. In particular, we demonstrate how meK-Means can be used to cluster cells from unspliced and spliced mRNA count modalities. By utilizing the causal, physical relationships underlying these modalities, we identify shared transcriptional kinetics across cells, which induce the observed gene expression profiles, and provide an alternative definition for 'clusters' through the governing parameters of cellular processes.
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Affiliation(s)
- Tara Chari
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California
| | - Gennady Gorin
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California
| | - Lior Pachter
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California
- Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, California
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15
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Yaghoubi Naei V, Bordhan P, Mirakhorli F, Khorrami M, Shrestha J, Nazari H, Kulasinghe A, Ebrahimi Warkiani M. Advances in novel strategies for isolation, characterization, and analysis of CTCs and ctDNA. Ther Adv Med Oncol 2023; 15:17588359231192401. [PMID: 37692363 PMCID: PMC10486235 DOI: 10.1177/17588359231192401] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 07/19/2023] [Indexed: 09/12/2023] Open
Abstract
Over the past decade, the detection and analysis of liquid biopsy biomarkers such as circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) have advanced significantly. They have received recognition for their clinical usefulness in detecting cancer at an early stage, monitoring disease, and evaluating treatment response. The emergence of liquid biopsy has been a helpful development, as it offers a minimally invasive, rapid, real-time monitoring, and possible alternative to traditional tissue biopsies. In resource-limited settings, the ideal platform for liquid biopsy should not only extract more CTCs or ctDNA from a minimal sample volume but also accurately represent the molecular heterogeneity of the patient's disease. This review covers novel strategies and advancements in CTC and ctDNA-based liquid biopsy platforms, including microfluidic applications and comprehensive analysis of molecular complexity. We discuss these systems' operational principles and performance efficiencies, as well as future opportunities and challenges for their implementation in clinical settings. In addition, we emphasize the importance of integrated platforms that incorporate machine learning and artificial intelligence in accurate liquid biopsy detection systems, which can greatly improve cancer management and enable precision diagnostics.
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Affiliation(s)
- Vahid Yaghoubi Naei
- School of Biomedical Engineering, University of Technology Sydney, Sydney, Australia
- Faculty of Medicine, Frazer Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Pritam Bordhan
- School of Biomedical Engineering, University of Technology Sydney, Sydney, Australia
- Faculty of Science, Institute for Biomedical Materials & Devices, University of Technology Sydney, Australia
| | - Fatemeh Mirakhorli
- School of Biomedical Engineering, University of Technology Sydney, Sydney, Australia
| | - Motahare Khorrami
- Immunology Research Center, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Jesus Shrestha
- School of Biomedical Engineering, University of Technology Sydney, Sydney, Australia
| | - Hojjatollah Nazari
- School of Biomedical Engineering, University of Technology Sydney, Sydney, Australia
| | - Arutha Kulasinghe
- Faculty of Medicine, Frazer Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Majid Ebrahimi Warkiani
- School of Biomedical Engineering, University of Technology Sydney, 1, Broadway, Ultimo New South Wales 2007, Australia
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16
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Tan Y, Huang J, Li D, Zou C, Liu D, Qin B. Single-cell RNA sequencing in dissecting microenvironment of age-related macular degeneration: Challenges and perspectives. Ageing Res Rev 2023; 90:102030. [PMID: 37549871 DOI: 10.1016/j.arr.2023.102030] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 04/29/2023] [Accepted: 08/04/2023] [Indexed: 08/09/2023]
Abstract
Age-related macular degeneration (AMD) is the leading cause of blindness in individuals over the age of 50 years, yet its etiology and pathogenesis largely remain uncovered. Single-cell RNA sequencing (scRNA-seq) technologies are recently developed and have a number of advantages over conventional bulk RNA sequencing techniques in uncovering the heterogeneity of complex microenvironments containing numerous cell types and cell communications during various biological processes. In this review, we summarize the latest discovered cellular components and regulatory mechanisms during AMD development revealed by scRNA-seq. In addition, we discuss the main challenges and future directions in exploring the pathophysiology of AMD equipped with single-cell technologies. Our review underscores the importance of multimodal single-cell platforms (such as single-cell spatiotemporal multi-omics and single-cell exosome omics) as new approaches for basic and clinical AMD research in identifying biomarker, characterizing cellular responses to drug treatment and environmental stimulation.
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Affiliation(s)
- Yao Tan
- Shenzhen Aier Eye Hospital, Aier Eye Hospital, Jinan University, Shenzhen, China
| | - Jianguo Huang
- Shenzhen Aier Eye Hospital, Aier Eye Hospital, Jinan University, Shenzhen, China
| | - Deshuang Li
- Shenzhen Aier Eye Hospital, Aier Eye Hospital, Jinan University, Shenzhen, China
| | - Chang Zou
- Shenzhen Aier Eye Hospital, Aier Eye Hospital, Jinan University, Shenzhen, China; Shenzhen Aier Ophthalmic Technology Institute, Shenzhen, China; School of Life and Health Sciences, The Chinese University of Kong Hong, Shenzhen 518000, Guangdong, China.
| | - Dongcheng Liu
- Shenzhen Aier Eye Hospital, Aier Eye Hospital, Jinan University, Shenzhen, China; Shenzhen Aier Ophthalmic Technology Institute, Shenzhen, China.
| | - Bo Qin
- Shenzhen Aier Eye Hospital, Aier Eye Hospital, Jinan University, Shenzhen, China; Shenzhen Aier Ophthalmic Technology Institute, Shenzhen, China; Aier School of Ophthalmology, Central South University, Changsha, China.
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17
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Abstract
The biology of a cell, whether it is a unicellular organism or part of a multicellular network, is influenced by cell type, temporal changes in cell state, and the cell's environment. Spatial cues play a critical role in the regulation of microbial pathogenesis strategies. Information about where the pathogen is-in a tissue or in proximity to a host cell-regulates gene expression and the compartmentalization of gene products in the microbe and the host. Our understanding of host and pathogen identity has bloomed with the accessibility of transcriptomics and proteomics techniques. A missing piece of the puzzle has been our ability to evaluate global transcript and protein expression in the context of the subcellular niche, primary cell, or native tissue environment during infection. This barrier is now lower with the advent of new spatial omics techniques to understand how location regulates cellular functions. This review will discuss how recent advances in spatial proteomics and transcriptomics approaches can address outstanding questions in microbial pathogenesis.
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Affiliation(s)
- Samantha Lempke
- Department of Microbiology, Immunology, and Cancer Biology at the Carter Immunology Center, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Dana May
- Department of Microbiology, Immunology, and Cancer Biology at the Carter Immunology Center, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Sarah E. Ewald
- Department of Microbiology, Immunology, and Cancer Biology at the Carter Immunology Center, University of Virginia School of Medicine, Charlottesville, Virginia, USA
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18
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Gebreyesus ST, Muneer G, Huang CC, Siyal AA, Anand M, Chen YJ, Tu HL. Recent advances in microfluidics for single-cell functional proteomics. LAB ON A CHIP 2023; 23:1726-1751. [PMID: 36811978 DOI: 10.1039/d2lc01096h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Single-cell proteomics (SCP) reveals phenotypic heterogeneity by profiling individual cells, their biological states and functional outcomes upon signaling activation that can hardly be probed via other omics characterizations. This has become appealing to researchers as it enables an overall more holistic view of biological details underlying cellular processes, disease onset and progression, as well as facilitates unique biomarker identification from individual cells. Microfluidic-based strategies have become methods of choice for single-cell analysis because they allow facile assay integrations, such as cell sorting, manipulation, and content analysis. Notably, they have been serving as an enabling technology to improve the sensitivity, robustness, and reproducibility of recently developed SCP methods. Critical roles of microfluidics technologies are expected to further expand rapidly in advancing the next phase of SCP analysis to reveal more biological and clinical insights. In this review, we will capture the excitement of the recent achievements of microfluidics methods for both targeted and global SCP, including efforts to enhance the proteomic coverage, minimize sample loss, and increase multiplexity and throughput. Furthermore, we will discuss the advantages, challenges, applications, and future prospects of SCP.
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Affiliation(s)
- Sofani Tafesse Gebreyesus
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Nano Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
| | - Gul Muneer
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | | | - Asad Ali Siyal
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
| | - Mihir Anand
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Institute of Biochemical Sciences, National Taiwan University, Taipei 10617, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Department of Chemistry, National Taiwan University, Taipei 10617, Taiwan
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
| | - Hsiung-Lin Tu
- Institute of Chemistry, Academia Sinica, Taipei 11529, Taiwan.
- Nano Science and Technology Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Academia Sinica, Taipei 11529, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
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19
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Advances in Mass Spectrometry-Based Single Cell Analysis. BIOLOGY 2023; 12:biology12030395. [PMID: 36979087 PMCID: PMC10045136 DOI: 10.3390/biology12030395] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 02/27/2023] [Accepted: 03/01/2023] [Indexed: 03/06/2023]
Abstract
Technological developments and improvements in single-cell isolation and analytical platforms allow for advanced molecular profiling at the single-cell level, which reveals cell-to-cell variation within the admixture cells in complex biological or clinical systems. This helps to understand the cellular heterogeneity of normal or diseased tissues and organs. However, most studies focused on the analysis of nucleic acids (e.g., DNA and RNA) and mass spectrometry (MS)-based analysis for proteins and metabolites of a single cell lagged until recently. Undoubtedly, MS-based single-cell analysis will provide a deeper insight into cellular mechanisms related to health and disease. This review summarizes recent advances in MS-based single-cell analysis methods and their applications in biology and medicine.
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20
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Zou Y, Ye F, Kong Y, Hu X, Deng X, Xie J, Song C, Ou X, Wu S, Wu L, Xie Y, Tian W, Tang Y, Wong C, Chen Z, Xie X, Tang H. The Single-Cell Landscape of Intratumoral Heterogeneity and The Immunosuppressive Microenvironment in Liver and Brain Metastases of Breast Cancer. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2203699. [PMID: 36529697 PMCID: PMC9929130 DOI: 10.1002/advs.202203699] [Citation(s) in RCA: 94] [Impact Index Per Article: 94.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 11/11/2022] [Indexed: 05/07/2023]
Abstract
Distant metastasis remains the major cause of morbidity for breast cancer. Individuals with liver or brain metastasis have an extremely poor prognosis and low response rates to anti-PD-1/L1 immune checkpoint therapy compared to those with metastasis at other sites. Therefore, it is urgent to investigate the underlying mechanism of anti-PD-1/L1 resistance and develop more effective immunotherapy strategies for these patients. Using single-cell RNA sequencing, a high-resolution map of the entire tumor ecosystem based on 44 473 cells from breast cancer liver and brain metastases is depicted. Identified by canonical markers and confirmed by multiplex immunofluorescent staining, the metastatic ecosystem features remarkable reprogramming of immunosuppressive cells such as FOXP3+ regulatory T cells, LAMP3+ tolerogenic dendritic cells, CCL18+ M2-like macrophages, RGS5+ cancer-associated fibroblasts, and LGALS1+ microglial cells. In addition, PD-1 and PD-L1/2 are barely expressed in CD8+ T cells and cancer/immune/stromal cells, respectively. Interactions of the immune checkpoint molecules LAG3-LGALS3 and TIGIT-NECTIN2 between CD8+ T cells and cancer/immune/stromal cells are found to play dominant roles in the immune escape. In summary, this study dissects the intratumoral heterogeneity and immunosuppressive microenvironment in liver and brain metastases of breast cancer for the first time, providing insights into the most appropriate immunotherapy strategies for these patients.
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Affiliation(s)
- Yutian Zou
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Feng Ye
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Yanan Kong
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Xiaoqian Hu
- School of Biomedical SciencesFaculty of MedicineThe University of Hong Kong21 Sassoon RoadHong Kong999077China
| | - Xinpei Deng
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Jindong Xie
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Cailu Song
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Xueqi Ou
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Song Wu
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Linyu Wu
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Yi Xie
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Wenwen Tian
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Yuhui Tang
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Chau‐Wei Wong
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Zhe‐Sheng Chen
- College of Pharmacy and Health SciencesSt. John's UniversityQueensNYUSA
| | - Xinhua Xie
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
| | - Hailin Tang
- Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer Medicine651 East Dongfeng RoadGuangzhou510060China
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21
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Zhu F, Liu S, Bai X, Liu X, Lin B, Lu Y. Point‐of‐care multiplexed single‐cell protein secretion analysis based on tyramide signal amplification. VIEW 2022. [DOI: 10.1002/viw.20220033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Affiliation(s)
- Fengjiao Zhu
- Department of Biotechnology Dalian Institute of Chemical Physics Chinese Academy of Sciences Dalian China
- University of Chinese Academy of Sciences Beijing China
| | - Songnan Liu
- Department of Biotechnology Dalian Institute of Chemical Physics Chinese Academy of Sciences Dalian China
- University of Chinese Academy of Sciences Beijing China
| | - Xue Bai
- Department of Biotechnology Dalian Institute of Chemical Physics Chinese Academy of Sciences Dalian China
| | - Xianming Liu
- Department of Biotechnology Dalian Institute of Chemical Physics Chinese Academy of Sciences Dalian China
| | - Bingcheng Lin
- Department of Biotechnology Dalian Institute of Chemical Physics Chinese Academy of Sciences Dalian China
| | - Yao Lu
- Department of Biotechnology Dalian Institute of Chemical Physics Chinese Academy of Sciences Dalian China
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22
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Cupp-Sutton KA, Fang M, Wu S. Separation methods in single-cell proteomics: RPLC or CE? INTERNATIONAL JOURNAL OF MASS SPECTROMETRY 2022; 481:116920. [PMID: 36211475 PMCID: PMC9542495 DOI: 10.1016/j.ijms.2022.116920] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Cellular heterogeneity is commonly investigated using single-cell genomics and transcriptomics to investigate biological questions such as disease mechanism, therapeutic screening, and genomic and transcriptomic diversity between cellular populations and subpopulations at the cellular level. Single-cell mass spectrometry (MS)-based proteomics enables the high-throughput examination of protein expression at the single-cell level with wide applicability, and with spatial and temporal resolution, applicable to the study of cellular development, disease, effect of treatment, etc. The study of single-cell proteomics has lagged behind genomics and transcriptomics largely because proteins from single-cell samples cannot be amplified as DNA and RNA can using well established techniques such as PCR. Therefore, analytical methods must be robust, reproducible, and sensitive enough to detect the very small amount of protein within a single cell. To this end, nearly every step of the proteomics process has been extensively altered and improved to facilitate the proteomics analysis of single cells including cell counting and sorting, lysis, protein digestion, sample cleanup, separation, MS data acquisition, and data analysis. Here, we have reviewed recent advances in single-cell protein separation using nano reversed phase liquid chromatography (nRPLC) and capillary electrophoresis (CE) to inform application driven selection of separation techniques in the laboratory setting.
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Affiliation(s)
| | - Mulin Fang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK 73019
| | - Si Wu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK 73019
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23
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Ni C, Zhou Z, Zhu Z, Jiang D, Xiang N. Controllable Size-Independent Three-Dimensional Inertial Focusing in High-Aspect-Ratio Asymmetric Serpentine Microchannels. Anal Chem 2022; 94:15639-15647. [DOI: 10.1021/acs.analchem.2c02361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Chen Ni
- School of Mechanical Engineering and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing211189, China
| | - Zheng Zhou
- School of Mechanical Engineering and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing211189, China
| | - Zhixian Zhu
- School of Mechanical Engineering and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing211189, China
| | - Di Jiang
- College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing210037, China
- Jiangsu Yuyue Medical Equipment and Supply Co., Ltd., Jiangsu, Danyang212300, China
| | - Nan Xiang
- School of Mechanical Engineering and Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University, Nanjing211189, China
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24
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Yu H, Tai Q, Yang C, Weng L, Gao M, Zhang X. Counting Protein Number in a Single Cell by a Picoliter Liquid Operating Technology. Anal Chem 2022; 94:11925-11933. [PMID: 35980697 DOI: 10.1021/acs.analchem.2c02701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Ultra-low-copy number proteins play a crucial role in exploring cellular heterogeneity and the insight of protein biomarkers in a single cell. However, counting ultra-low-copy number target proteins in a single cell remains a grand challenge. Herein, we developed a so-called single-cell picoliter liquid operating technology for counting target proteins in a single cell. An ingenious volume-controllable sampling technique was employed to capture a single cell for subsequent analysis. Remarkably, 50 pL of sample volume was employed for sample preparation, single-cell capture, in-droplet lysis, and target protein immobilization on a functionalized coverslip in a monolayer. Then, target protein antibodies coupled with quantum dots were added and incubated to label those immobilized proteins. After clean-up, a single-view image under 100× objective was taken, and the 80 × 80 μm2 view image was then applied to count the precise copy number of the target proteins in the single cell. Furthermore, good linearity and repeatability were achieved for ultra-low-copy number proteins, ranging from 1 to 1500. Finally, the expression level of human epidermal growth factor receptor 2 in single cells from both MCF-7 and MDA-MB-231 cell lines was also analyzed. In a word, this work stimulated the development of capillary-based single-cell analysis and updated the connotation of counting ultra-low-copy number proteins.
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Affiliation(s)
- Hailong Yu
- Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Qunfei Tai
- Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Chenjie Yang
- Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Lingxiao Weng
- Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Mingxia Gao
- Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
| | - Xiangmin Zhang
- Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
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25
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Nakai K, Wei L. Recent Advances in the Prediction of Subcellular Localization of Proteins and Related Topics. FRONTIERS IN BIOINFORMATICS 2022; 2:910531. [PMID: 36304291 PMCID: PMC9580943 DOI: 10.3389/fbinf.2022.910531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 04/25/2022] [Indexed: 11/13/2022] Open
Abstract
Prediction of subcellular localization of proteins from their amino acid sequences has a long history in bioinformatics and is still actively developing, incorporating the latest advances in machine learning and proteomics. Notably, deep learning-based methods for natural language processing have made great contributions. Here, we review recent advances in the field as well as its related fields, such as subcellular proteomics and the prediction/recognition of subcellular localization from image data.
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Affiliation(s)
- Kenta Nakai
- Institute of Medical Science, The University of Tokyo, Minato-Ku, Japan
- *Correspondence: Kenta Nakai,
| | - Leyi Wei
- School of Software, Shandong University, Jinan, China
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