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Jiang YR, Zhu L, Cao LR, Wu Q, Chen JB, Wang Y, Wu J, Zhang TY, Wang ZL, Guan ZY, Xu QQ, Fan QX, Shi SW, Wang HF, Pan JZ, Fu XD, Wang Y, Fang Q. Simultaneous deep transcriptome and proteome profiling in a single mouse oocyte. Cell Rep 2023; 42:113455. [PMID: 37976159 DOI: 10.1016/j.celrep.2023.113455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 09/23/2023] [Accepted: 11/01/2023] [Indexed: 11/19/2023] Open
Abstract
Although single-cell multi-omics technologies are undergoing rapid development, simultaneous transcriptome and proteome analysis of a single-cell individual still faces great challenges. Here, we developed a single-cell simultaneous transcriptome and proteome (scSTAP) analysis platform based on microfluidics, high-throughput sequencing, and mass spectrometry technology to achieve deep and joint quantitative analysis of transcriptome and proteome at the single-cell level, providing an important resource for understanding the relationship between transcription and translation in cells. This platform was applied to analyze single mouse oocytes at different meiotic maturation stages, reaching an average quantification depth of 19,948 genes and 2,663 protein groups in single mouse oocytes. In particular, we analyzed the correlation of individual RNA and protein pairs, as well as the meiosis regulatory network with unprecedented depth, and identified 30 transcript-protein pairs as specific oocyte maturational signatures, which could be productive for exploring transcriptional and translational regulatory features during oocyte meiosis.
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Affiliation(s)
- Yi-Rong Jiang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou 310058, China
| | - Le Zhu
- School of Medicine, Liangzhu Laboratory, Zhejiang University, Hangzhou 311113, China
| | - Lan-Rui Cao
- School of Medicine, Liangzhu Laboratory, Zhejiang University, Hangzhou 311113, China
| | - Qiong 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
| | - Yu Wang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou 310058, China; ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou 311200, China
| | - Jie Wu
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou 310058, China
| | | | | | - Zhi-Ying Guan
- 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
| | - Shao-Wen Shi
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou 311200, China
| | - Hui-Feng Wang
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou 311200, China
| | - Jian-Zhang Pan
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou 310058, China; ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou 311200, China
| | - Xu-Dong Fu
- School of Medicine, Liangzhu Laboratory, Zhejiang University, Hangzhou 311113, China; Center of Stem Cell and Regenerative Medicine and Bone Marrow Transplantation Center of the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310011, China.
| | - Yongcheng Wang
- School of Medicine, Liangzhu Laboratory, Zhejiang University, Hangzhou 311113, China; Department of Laboratory Medicine, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310011, China.
| | - Qun Fang
- Institute of Microanalytical Systems, Department of Chemistry, Zhejiang University, Hangzhou 310058, China; 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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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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3
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Mukherjee P, Park SH, Pathak N, Patino CA, Bao G, Espinosa HD. Integrating Micro and Nano Technologies for Cell Engineering and Analysis: Toward the Next Generation of Cell Therapy Workflows. ACS NANO 2022; 16:15653-15680. [PMID: 36154011 DOI: 10.1021/acsnano.2c05494] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
The emerging field of cell therapy offers the potential to treat and even cure a diverse array of diseases for which existing interventions are inadequate. Recent advances in micro and nanotechnology have added a multitude of single cell analysis methods to our research repertoire. At the same time, techniques have been developed for the precise engineering and manipulation of cells. Together, these methods have aided the understanding of disease pathophysiology, helped formulate corrective interventions at the cellular level, and expanded the spectrum of available cell therapeutic options. This review discusses how micro and nanotechnology have catalyzed the development of cell sorting, cellular engineering, and single cell analysis technologies, which have become essential workflow components in developing cell-based therapeutics. The review focuses on the technologies adopted in research studies and explores the opportunities and challenges in combining the various elements of cell engineering and single cell analysis into the next generation of integrated and automated platforms that can accelerate preclinical studies and translational research.
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Affiliation(s)
- Prithvijit Mukherjee
- Department of Mechanical Engineering, Northwestern University, Evanston, Illinois 60208, United States
- Theoretical and Applied Mechanics Program, Northwestern University, Evanston, Illinois 60208, United States
| | - So Hyun Park
- Department of Bioengineering, Rice University, 6500 Main Street, Houston, Texas 77030, United States
| | - Nibir Pathak
- Department of Mechanical Engineering, Northwestern University, Evanston, Illinois 60208, United States
- Theoretical and Applied Mechanics Program, Northwestern University, Evanston, Illinois 60208, United States
| | - Cesar A Patino
- Department of Mechanical Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Gang Bao
- Department of Bioengineering, Rice University, 6500 Main Street, Houston, Texas 77030, United States
| | - Horacio D Espinosa
- Department of Mechanical Engineering, Northwestern University, Evanston, Illinois 60208, United States
- Theoretical and Applied Mechanics Program, Northwestern University, Evanston, Illinois 60208, United States
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4
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Källberg J, Xiao W, Van Assche D, Baret JC, Taly V. Frontiers in single cell analysis: multimodal technologies and their clinical perspectives. LAB ON A CHIP 2022; 22:2403-2422. [PMID: 35703438 DOI: 10.1039/d2lc00220e] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Single cell multimodal analysis is at the frontier of single cell research: it defines the roles and functions of distinct cell types through simultaneous analysis to provide unprecedented insight into cellular processes. Current single cell approaches are rapidly moving toward multimodal characterizations. It replaces one-dimensional single cell analysis, for example by allowing for simultaneous measurement of transcription and post-transcriptional regulation, epigenetic modifications and/or surface protein expression. By providing deeper insights into single cell processes, multimodal single cell analyses paves the way to new understandings in various cellular processes such as cell fate decisions, physiological heterogeneity or genotype-phenotype linkages. At the forefront of this, microfluidics is key for high-throughput single cell analysis. Here, we present an overview of the recent multimodal microfluidic platforms having a potential in biomedical research, with a specific focus on their potential clinical applications.
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Affiliation(s)
- Julia Källberg
- Centre de Recherche des Cordeliers, INSERM, CNRS, Université Paris Cité, Sorbonne Université, USPC, Equipe labellisée Ligue Nationale contre le cancer, Paris, France.
| | - Wenjin Xiao
- Centre de Recherche des Cordeliers, INSERM, CNRS, Université Paris Cité, Sorbonne Université, USPC, Equipe labellisée Ligue Nationale contre le cancer, Paris, France.
| | - David Van Assche
- University of Bordeaux, CNRS, Centre de Recherche Paul Pascal, UMR 5031, Pessac 33600, France.
| | - Jean-Christophe Baret
- University of Bordeaux, CNRS, Centre de Recherche Paul Pascal, UMR 5031, Pessac 33600, France.
- Institut Universitaire de France, Paris 75005, France
| | - Valerie Taly
- Centre de Recherche des Cordeliers, INSERM, CNRS, Université Paris Cité, Sorbonne Université, USPC, Equipe labellisée Ligue Nationale contre le cancer, Paris, France.
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5
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Xie H, Ding X. The Intriguing Landscape of Single-Cell Protein Analysis. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2105932. [PMID: 35199955 PMCID: PMC9036017 DOI: 10.1002/advs.202105932] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 01/27/2022] [Indexed: 05/15/2023]
Abstract
Profiling protein expression at single-cell resolution is essential for fundamental biological research (such as cell differentiation and tumor microenvironmental examination) and clinical precision medicine where only a limited number of primary cells are permitted. With the recent advances in engineering, chemistry, and biology, single-cell protein analysis methods are developed rapidly, which enable high-throughput and multiplexed protein measurements in thousands of individual cells. In combination with single cell RNA sequencing and mass spectrometry, single-cell multi-omics analysis can simultaneously measure multiple modalities including mRNAs, proteins, and metabolites in single cells, and obtain a more comprehensive exploration of cellular signaling processes, such as DNA modifications, chromatin accessibility, protein abundance, and gene perturbation. Here, the recent progress and applications of single-cell protein analysis technologies in the last decade are summarized. Current limitations, challenges, and possible future directions in this field are also discussed.
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Affiliation(s)
- Haiyang Xie
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
| | - Xianting Ding
- State Key Laboratory of Oncogenes and Related GenesInstitute for Personalized MedicineSchool of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200030China
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6
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Su Y, Ko ME, Cheng H, Zhu R, Xue M, Wang J, Lee JW, Frankiw L, Xu A, Wong S, Robert L, Takata K, Yuan D, Lu Y, Huang S, Ribas A, Levine R, Nolan GP, Wei W, Plevritis SK, Li G, Baltimore D, Heath JR. Multi-omic single-cell snapshots reveal multiple independent trajectories to drug tolerance in a melanoma cell line. Nat Commun 2020; 11:2345. [PMID: 32393797 PMCID: PMC7214418 DOI: 10.1038/s41467-020-15956-9] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Accepted: 04/02/2020] [Indexed: 12/12/2022] Open
Abstract
The determination of individual cell trajectories through a high-dimensional cell-state space is an outstanding challenge for understanding biological changes ranging from cellular differentiation to epigenetic responses of diseased cells upon drugging. We integrate experiments and theory to determine the trajectories that single BRAFV600E mutant melanoma cancer cells take between drug-naive and drug-tolerant states. Although single-cell omics tools can yield snapshots of the cell-state landscape, the determination of individual cell trajectories through that space can be confounded by stochastic cell-state switching. We assayed for a panel of signaling, phenotypic, and metabolic regulators at points across 5 days of drug treatment to uncover a cell-state landscape with two paths connecting drug-naive and drug-tolerant states. The trajectory a given cell takes depends upon the drug-naive level of a lineage-restricted transcription factor. Each trajectory exhibits unique druggable susceptibilities, thus updating the paradigm of adaptive resistance development in an isogenic cell population.
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Affiliation(s)
- Yapeng Su
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, USA
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
- Institute for Systems Biology, Seattle, Washington, USA
| | - Melissa E Ko
- Cancer Biology Program, Stanford University School of Medicine, Stanford, California, USA
| | - Hanjun Cheng
- Institute for Systems Biology, Seattle, Washington, USA
| | - Ronghui Zhu
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Min Xue
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, USA
- Department of Chemistry, University of California, Riverside, Riverside, California, USA
| | - Jessica Wang
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Jihoon W Lee
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, USA
| | - Luke Frankiw
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Alexander Xu
- Institute for Systems Biology, Seattle, Washington, USA
| | - Stephanie Wong
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Lidia Robert
- Department of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Kaitlyn Takata
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA
| | - Dan Yuan
- Institute for Systems Biology, Seattle, Washington, USA
| | - Yue Lu
- Institute for Systems Biology, Seattle, Washington, USA
| | - Sui Huang
- Institute for Systems Biology, Seattle, Washington, USA
| | - Antoni Ribas
- Department of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- Department of Molecular and Medical Pharmacology, UCLA, Los Angeles, California, USA
- Department of Surgery, UCLA, Los Angeles, California, USA
- Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, California, USA
| | - Raphael Levine
- Department of Molecular and Medical Pharmacology, UCLA, Los Angeles, California, USA
- Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, California, USA
- The Fritz Haber Research Center, The Hebrew University, Jerusalem, Israel
| | - Garry P Nolan
- Department of Microbiology and Immunology, Stanford University, Stanford, California, USA
| | - Wei Wei
- Institute for Systems Biology, Seattle, Washington, USA
- Department of Molecular and Medical Pharmacology, UCLA, Los Angeles, California, USA
- Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, California, USA
| | | | - Guideng Li
- Center of Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
- Suzhou Institute of Systems Medicine, Suzhou, China.
| | - David Baltimore
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, USA.
| | - James R Heath
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, USA.
- Institute for Systems Biology, Seattle, Washington, USA.
- Department of Molecular and Medical Pharmacology, UCLA, Los Angeles, California, USA.
- Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, California, USA.
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7
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Liu L, Yang H, Men D, Wang M, Gao X, Zhang T, Chen D, Xue C, Wang Y, Wang J, Chen J. Development of microfluidic platform capable of high-throughput absolute quantification of single-cell multiple intracellular proteins from tumor cell lines and patient tumor samples. Biosens Bioelectron 2020; 155:112097. [PMID: 32090869 DOI: 10.1016/j.bios.2020.112097] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 02/10/2020] [Accepted: 02/12/2020] [Indexed: 12/31/2022]
Abstract
Quantification of single-cell proteins plays key roles in cell heterogeneity while due to technical limitations absolute numbers of multiple intracellular proteins from large populations of single cells were still missing, leading to compromised results in cell-type classifications. This paper presents a microfluidic platform capable of high-throughput absolute quantification of single-cell multiple types of intracellular proteins where cells stained with fluorescent labelled antibodies are aspirated into the constriction microchannels with excited fluorescent signals detected and translated into numbers of binding sites of targeted proteins based on calibration curves formed by flushing gradient solutions of fluorescent labelled antibodies directly into constriction microchannels. Based on this approach, single-cell numbers of binding sites of β-actin, α-tubulin and β-tubulin from tens of thousands of five representative tumor cell lines were first quantified, reporting cell-type classification rates of 83.0 ± 7.1%. Then single-cell numbers of binding sites of β-actin, biotin and RhoA from thousands of five tumor cell lines with varieties in malignant levels were quantified, reporting cell-type classification rates of 93.7 ± 2.8%. Furthermore, single-cell numbers of binding sites of Ras, c-Myc and p53 from thousands of cells derived from two oral tumor lines of CAL 27, WSU-HN6 and two oral tumor patient samples were quantified, contributing to high classifications of both tumor cell lines (98.6%) and tumor patient samples (83.4%). In conclusion, the developed microfluidic platform was capable of quantifying multiple intracellular proteins from large populations of single cells, and the collected data of protein expressions enabled effective cell-type classifications.
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Affiliation(s)
- Lixing Liu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China
| | - Hongyu Yang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China; School of Future Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Dong Men
- State Key Laboratory of Virology, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, China
| | - Meng Wang
- Peking University School of Stomatology, Beijing, China
| | - Xiaolei Gao
- Peking University School of Stomatology, Beijing, China
| | - Ting Zhang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China; School of Future Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Deyong Chen
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China; School of Future Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Chunlai Xue
- Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China
| | - Yixiang Wang
- Peking University School of Stomatology, Beijing, China.
| | - Junbo Wang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China; School of Future Technology, University of Chinese Academy of Sciences, Beijing, China.
| | - Jian Chen
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China; School of Future Technology, University of Chinese Academy of Sciences, Beijing, China.
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8
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Peng A, Mao X, Zhong J, Fan S, Hu Y. Single-Cell Multi-Omics and Its Prospective Application in Cancer Biology. Proteomics 2020; 20:e1900271. [PMID: 32223079 DOI: 10.1002/pmic.201900271] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 02/29/2020] [Indexed: 01/24/2023]
Abstract
In recent years, the emergence of single-cell omics technologies, which can profile genomics, transcriptomics, epigenomics, and proteomics, has provided unprecedented insights into characteristics of cancer, enabling higher resolution and accuracy to decipher the cellular and molecular mechanisms relating to tumorigenesis, evolution, metastasis, and immune responses. Single-cell multi-omics technologies, which are developed based on the combination of multiple single-cell mono-omics technologies, can simultaneously analyze RNA expression, single nucleotide polymorphism, epigenetic modification, or protein abundance, enabling the in-depth understanding of gene expression regulatory mechanisms. In this review, the state-of-the-art single-cell multi-omics technologies are summarized and the prospects of their application in cancer biology are discussed.
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Affiliation(s)
- Anghui Peng
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510000, China
| | - Xiying Mao
- Department of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Jiawei Zhong
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510000, China
| | - Shuxin Fan
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510000, China
| | - Youjin Hu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510000, China
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9
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Affiliation(s)
- Iulia M. Lazar
- Department of Biological Sciences, Academy of Integrated Sciences, Virginia Tech, Blacksburg, Virginia 24061, United States
- Carilion School of Medicine, Academy of Integrated Sciences, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - Nicholas S. Gulakowski
- Systems Biology, Academy of Integrated Sciences, Virginia Tech, Blacksburg, Virginia 24061, United States
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