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Zhou S, Lin N, Yu L, Su X, Liu Z, Yu X, Gao H, Lin S, Zeng Y. Single-cell multi-omics in the study of digestive system cancers. Comput Struct Biotechnol J 2024; 23:431-445. [PMID: 38223343 PMCID: PMC10787224 DOI: 10.1016/j.csbj.2023.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 12/07/2023] [Accepted: 12/07/2023] [Indexed: 01/16/2024] Open
Abstract
Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.
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Affiliation(s)
- Shuang Zhou
- The Second Clinical Medical School of Fujian Medical University, Quanzhou, Fujian Province, China
- The Clinical Center of Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
| | - Nanfei Lin
- The Clinical Center of Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
| | - Liying Yu
- The Clinical Center of Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
| | - Xiaoshan Su
- Department of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Fujian Medical University, Respirology Medicine Centre of Fujian Province, Quanzhou, China
| | - Zhenlong Liu
- Lady Davis Institute for Medical Research, Jewish General Hospital, & Division of Experimental Medicine, Department of Medicine, McGill University, Montreal, QC, Canada
| | - Xiaowan Yu
- Clinical Laboratory, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
| | - Hongzhi Gao
- The Clinical Center of Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
| | - Shu Lin
- Centre of Neurological and Metabolic Research, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
- Diabetes and Metabolism Division, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, Sydney, NSW 2010, Australia
| | - Yiming Zeng
- Department of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Fujian Medical University, Respirology Medicine Centre of Fujian Province, Quanzhou, China
- Fujian Provincial Key Laboratory of Lung Stem Cells, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
- Jinan Microecological Biomedicine Shandong Laboratory, Jinan, Shandong Province, China
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2
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Tan W, Chen J, Wang Y, Xiang K, Lu X, Han Q, Hou M, Yang J. Single-cell RNA sequencing in diabetic kidney disease: a literature review. Ren Fail 2024; 46:2387428. [PMID: 39099183 DOI: 10.1080/0886022x.2024.2387428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 07/06/2024] [Accepted: 07/29/2024] [Indexed: 08/06/2024] Open
Abstract
Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD), and its pathogenesis has not been clarified. Current research suggests that DKD involves multiple cell types and extra-renal factors, and it is particularly important to clarify the pathogenesis and identify new therapeutic targets. Single-cell RNA sequencing (scRNA-seq) technology is high-throughput sequencing of the transcriptomes of individual cells at the single-cell level, which is an effective technology for exploring the development of diseases by comparing genetic information, reflecting the differences in genetic information between cells, and identifying different cell subpopulations. Accumulating evidence supports the role of scRNA-seq in revealing the pathogenesis of diabetes and strengthening our understanding of the molecular mechanisms of DKD. We reviewed the scRNA-seq data this time. Then, we analyzed and discussed the applications of scRNA-seq technology in DKD research, including annotation of cell types, identification of novel cell types (or subtypes), identification of intercellular communication, analysis of cell differentiation trajectories, gene expression detection, and analysis of gene regulatory networks, and lastly, we explored the future perspectives of scRNA-seq technology in DKD research.
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Affiliation(s)
- Wei Tan
- Department of Nephrology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jiaoyan Chen
- Department of Nephrology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yunyan Wang
- Department of Nephrology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Kui Xiang
- Department of Nephrology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xianqiong Lu
- Department of Nephrology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Qiuyu Han
- Department of Nephrology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Mingyue Hou
- Department of Nephrology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jurong Yang
- Department of Nephrology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
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3
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Ahmed HS. The Multifaceted Role of L-Type Amino Acid Transporter 1 at the Blood-Brain Barrier: Structural Implications and Therapeutic Potential. Mol Neurobiol 2024:10.1007/s12035-024-04506-9. [PMID: 39325101 DOI: 10.1007/s12035-024-04506-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2024] [Accepted: 09/14/2024] [Indexed: 09/27/2024]
Abstract
L-type amino acid transporter 1 (LAT1) is integral to the transport of large neutral amino acids across the blood-brain barrier (BBB), playing a crucial role in brain homeostasis and the delivery of therapeutic agents. This review explores the multifaceted role of LAT1 in neurological disorders, including its structural and functional aspects at the BBB. Studies using advanced BBB models, such as induced pluripotent stem cell (iPSC)-derived systems and quantitative proteomic analyses, have demonstrated LAT1's significant impact on drug permeability and transport efficiency. In Alzheimer's disease, LAT1-mediated delivery of anti-inflammatory and neuroprotective agents shows promise in overcoming BBB limitations. In Parkinson's disease, LAT1's role in transporting L-DOPA and other therapeutic agents highlights its potential in enhancing treatment efficacy. In phenylketonuria, studies have revealed polymorphisms and genetic variations of LAT1, which could be correlated to disease severity. Prodrugs of valproic acid, pregabalin, and gabapentin help use LAT1-mediated transport to increase the therapeutic activity and bioavailability of the prodrug in the brain. LAT1 has also been studied in neurodevelopment disorders like autism spectrum disorders and Rett syndrome, along with neuropsychiatric implications in depression. Its implications in neuro-oncology, especially in transporting therapeutic agents into cancer cells, show immense future potential. Phenotypes of LAT1 have also shown variations in the general population affecting their ability to respond to painkillers and anti-inflammatory drugs. Furthermore, LAT1-targeted approaches, such as functionalized nanoparticles and prodrugs, show promise in overcoming chemoresistance and enhancing drug delivery to the brain. The ongoing exploration of LAT1's structural characteristics and therapeutic applications reiterates its critical role in advancing treatments for neurological disorders.
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Affiliation(s)
- H Shafeeq Ahmed
- Bangalore Medical College and Research Institute, Bangalore, 560002, Karnataka, India.
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4
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Jin W, Pei J, Roy JR, Jayaraman S, Ahalliya RM, Kanniappan GV, Mironescu M, Palanisamy CP. Comprehensive review on single-cell RNA sequencing: A new frontier in Alzheimer's disease research. Ageing Res Rev 2024; 100:102454. [PMID: 39142391 DOI: 10.1016/j.arr.2024.102454] [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: 07/08/2024] [Revised: 08/07/2024] [Accepted: 08/09/2024] [Indexed: 08/16/2024]
Abstract
Alzheimer's disease (AD) is a multifaceted neurodegenerative condition marked by gradual cognitive deterioration and the loss of neurons. While conventional bulk RNA sequencing techniques have shed light on AD pathology, they frequently obscure the cellular diversity within brain tissues. The advent of single-cell RNA sequencing (scRNA-seq) has transformed our capability to analyze the cellular composition of AD, allowing for the detection of unique cell populations, rare cell types, and gene expression alterations at an individual cell level. This review examines the use of scRNA-seq in AD research, focusing on its contributions to understanding cellular diversity, disease progression, and potential therapeutic targets. We discuss key technological innovations, data analysis techniques, and challenges associated with scRNA-seq in studying AD. Furthermore, we highlight recent studies that have utilized scRNA-seq to identify novel biomarkers, uncover disease-associated pathways, and elucidate the role of non-neuronal cells, such as microglia and astrocytes, in AD pathogenesis. By providing a comprehensive overview of advancements in scRNA-seq for unraveling cellular heterogeneity in AD, this review highlights the transformative impact of scRNA-seq on our comprehension of disease mechanisms and the creation of targeted treatments.
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Affiliation(s)
- Wengang Jin
- Qinba State Key Laboratory of Biological Resources and Ecological Environment, 2011 QinLing-Bashan Mountains Bioresources Comprehensive Development C. I. C, Shaanxi Province Key Laboratory of Bio-Resources, College of Bioscience and Bioengineering, Shaanxi University of Technology, Hanzhong 723001, China
| | - JinJin Pei
- Qinba State Key Laboratory of Biological Resources and Ecological Environment, 2011 QinLing-Bashan Mountains Bioresources Comprehensive Development C. I. C, Shaanxi Province Key Laboratory of Bio-Resources, College of Bioscience and Bioengineering, Shaanxi University of Technology, Hanzhong 723001, China
| | - Jeane Rebecca Roy
- Department of Anatomy, Bhaarath Medical College and hospital, Bharath Institute of Higher Education and Research (BIHER), Chennai, Tamil Nadu 600073, India
| | - Selvaraj Jayaraman
- Centre of Molecular Medicine and Diagnostics (COMManD), Department of Biochemistry, Saveetha Dental College & Hospital, Saveetha Institute of Medical & Technical Sciences, Saveetha University, Chennai 600077, India
| | - Rathi Muthaiyan Ahalliya
- Department of Biochemistry and Cancer Research Centre, FASCM, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu 641021, India
| | - Gopalakrishnan Velliyur Kanniappan
- Center for Global Health Research, Saveetha Medical College & Hospital, Saveetha Institute of Medical and Technical Sciences (SIMATS), Thandalam, Chennai, Tamil Nadu 602105, India.
| | - Monica Mironescu
- Faculty of Agricultural Sciences Food Industry and Environmental Protection, Lucian Blaga University of Sibiu, Bv. Victoriei 10, Sibiu 550024, Romania.
| | - Chella Perumal Palanisamy
- Department of Chemical Technology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.
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5
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Ali A, Manzoor S, Ali T, Asim M, Muhammad G, Ahmad A, Jamaludin MI, Devaraj S, Munawar N. Innovative aspects and applications of single cell technology for different diseases. Am J Cancer Res 2024; 14:4028-4048. [PMID: 39267684 PMCID: PMC11387862 DOI: 10.62347/vufu1836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2024] [Accepted: 08/24/2024] [Indexed: 09/15/2024] Open
Abstract
Recent developments in single-cell technologies have provided valuable insights from cancer genomics to complex microbial communities. Single-cell technologies including the RNA-seq, next-generation sequencing (NGS), epigenomics, genomics, and transcriptomics can be used to uncover the single cell nature and molecular characterization of individual cells. These technologies also reveal the cellular transition states, evolutionary relationships between genes, the complex structure of single-cell populations, cell-to-cell interaction leading to biological discoveries and more reliable than traditional bulk technologies. These technologies are becoming the first choice for the early detection of inflammatory biomarkers affecting the proliferation and progression of tumor cells in the tumor microenvironment and improving the clinical efficacy of patients undergoing immunotherapy. These technologies also hold a central position in the detection of checkpoint inhibitors and thus determining the signaling pathways evoked by tumor invasion. This review addressed the emerging approaches of single cell-based technologies in cancer immunotherapies and different human diseases at cellular and molecular levels and the emerging role of sequencing technologies leading to drug discovery. Advancements in these technologies paved for discovering novel diagnostic markers for better understanding the pathological and biochemical mechanisms also for controlling the rate of different diseases.
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Affiliation(s)
- Ashiq Ali
- Department of Histology and Embryology, Shantou University Medical College Shantou 515041, Guangdong, China
| | - Saba Manzoor
- Department of Zoology, University of Sialkot Sialkot 51310, Pakistan
| | - Tayyab Ali
- Clinico-Molecular Biochemistry Laboratory, Department of Biochemistry, University of Agriculture Faisalabad 38000, Pakistan
| | - Muhammad Asim
- Clinico-Molecular Biochemistry Laboratory, Department of Biochemistry, University of Agriculture Faisalabad 38000, Pakistan
| | - Ghulam Muhammad
- Jinnah Burn and Reconstructive Surgery Centre, Jinnah Hospital, Allama Iqbal Medical College Lahore 54000, Pakistan
| | - Aftab Ahmad
- Biochemistry/Center for Advanced Studies in Agriculture and Food Security (CAS-AFS), University of Agriculture Faisalabad 38040, Pakistan
| | - Mohamad Ikhwan Jamaludin
- BioInspired Device and Tissue Engineering Research Group (BioInspira), Department of Biomedical Engineering and Health Sciences, Faculty of Electrical Engineering, Universiti Teknologi Malaysia Johor Bahru 81310, Johor, Malaysia
| | - Sutha Devaraj
- Graduate School of Medicine, Perdana University Wisma Chase Perdana, Changkat Semantan, Damansara Heights, Kuala Lumpur 50490, Malaysia
| | - Nayla Munawar
- Department of Chemistry, College of Science, United Arab Emirates University Al-Ain 15551, United Arab Emirates
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6
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Nam Y, Kim J, Jung SH, Woerner J, Suh EH, Lee DG, Shivakumar M, Lee ME, Kim D. Harnessing Artificial Intelligence in Multimodal Omics Data Integration: Paving the Path for the Next Frontier in Precision Medicine. Annu Rev Biomed Data Sci 2024; 7:225-250. [PMID: 38768397 DOI: 10.1146/annurev-biodatasci-102523-103801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
The integration of multiomics data with detailed phenotypic insights from electronic health records marks a paradigm shift in biomedical research, offering unparalleled holistic views into health and disease pathways. This review delineates the current landscape of multimodal omics data integration, emphasizing its transformative potential in generating a comprehensive understanding of complex biological systems. We explore robust methodologies for data integration, ranging from concatenation-based to transformation-based and network-based strategies, designed to harness the intricate nuances of diverse data types. Our discussion extends from incorporating large-scale population biobanks to dissecting high-dimensional omics layers at the single-cell level. The review underscores the emerging role of large language models in artificial intelligence, anticipating their influence as a near-future pivot in data integration approaches. Highlighting both achievements and hurdles, we advocate for a concerted effort toward sophisticated integration models, fortifying the foundation for groundbreaking discoveries in precision medicine.
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Affiliation(s)
- Yonghyun Nam
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
| | - Jaesik Kim
- Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sang-Hyuk Jung
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
| | - Jakob Woerner
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
| | - Erica H Suh
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
| | - Dong-Gi Lee
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
| | - Manu Shivakumar
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
| | - Matthew E Lee
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
| | - Dokyoon Kim
- Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA;
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7
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Kim GD, Shin SI, Jung SW, An H, Choi SY, Eun M, Jun CD, Lee S, Park J. Cell Type- and Age-Specific Expression of lncRNAs across Kidney Cell Types. J Am Soc Nephrol 2024; 35:870-885. [PMID: 38621182 PMCID: PMC11230714 DOI: 10.1681/asn.0000000000000354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 04/08/2024] [Indexed: 04/17/2024] Open
Abstract
Key Points
We constructed a single-cell long noncoding RNA atlas of various tissues, including normal and aged kidneys.We identified age- and cell type–specific expression changes of long noncoding RNAs in kidney cells.
Background
Accumulated evidence demonstrates that long noncoding RNAs (lncRNAs) regulate cell differentiation and homeostasis, influencing kidney aging and disease. Despite their versatility, the function of lncRNA remains poorly understood because of the lack of a reference map of lncRNA transcriptome in various cell types.
Methods
In this study, we used a targeted single-cell RNA sequencing method to enrich and characterize lncRNAs in individual cells. We applied this method to various mouse tissues, including normal and aged kidneys.
Results
Through tissue-specific clustering analysis, we identified cell type–specific lncRNAs that showed a high correlation with known cell-type marker genes. Furthermore, we constructed gene regulatory networks to explore the functional roles of differentially expressed lncRNAs in each cell type. In the kidney, we observed dynamic expression changes of lncRNAs during aging, with specific changes in glomerular cells. These cell type– and age-specific expression patterns of lncRNAs suggest that lncRNAs may have a potential role in regulating cellular processes, such as immune response and energy metabolism, during kidney aging.
Conclusions
Our study sheds light on the comprehensive landscape of lncRNA expression and function and provides a valuable resource for future analysis of lncRNAs (https://gist-fgl.github.io/sc-lncrna-atlas/).
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Affiliation(s)
- Gyeong Dae Kim
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - So-I Shin
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - Su Woong Jung
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
- Division of Nephrology, Department of Internal Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Hyunsu An
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - Sin Young Choi
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - Minho Eun
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - Chang-Duk Jun
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - Sangho Lee
- Division of Nephrology, Department of Internal Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Jihwan Park
- School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
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8
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Awuah WA, Roy S, Tan JK, Adebusoye FT, Qiang Z, Ferreira T, Ahluwalia A, Shet V, Yee ALW, Abdul‐Rahman T, Papadakis M. Exploring the current landscape of single-cell RNA sequencing applications in gastric cancer research. J Cell Mol Med 2024; 28:e18159. [PMID: 38494861 PMCID: PMC10945075 DOI: 10.1111/jcmm.18159] [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: 07/24/2023] [Revised: 12/22/2023] [Accepted: 01/12/2024] [Indexed: 03/19/2024] Open
Abstract
Gastric cancer (GC) represents a major global health burden and is responsible for a significant number of cancer-related fatalities. Its complex nature, characterized by heterogeneity and aggressive behaviour, poses considerable challenges for effective diagnosis and treatment. Single-cell RNA sequencing (scRNA-seq) has emerged as an important technique, offering unprecedented precision and depth in gene expression profiling at the cellular level. By facilitating the identification of distinct cell populations, rare cells and dynamic transcriptional changes within GC, scRNA-seq has yielded valuable insights into tumour progression and potential therapeutic targets. Moreover, this technology has significantly improved our comprehension of the tumour microenvironment (TME) and its intricate interplay with immune cells, thereby opening avenues for targeted therapeutic strategies. Nonetheless, certain obstacles, including tumour heterogeneity and technical limitations, persist in the field. Current endeavours are dedicated to refining protocols and computational tools to surmount these challenges. In this narrative review, we explore the significance of scRNA-seq in GC, emphasizing its advantages, challenges and potential applications in unravelling tumour heterogeneity and identifying promising therapeutic targets. Additionally, we discuss recent developments, ongoing efforts to overcome these challenges, and future prospects. Although further enhancements are required, scRNA-seq has already provided valuable insights into GC and holds promise for advancing biomedical research and clinical practice.
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Affiliation(s)
| | - Sakshi Roy
- School of MedicineQueen's University BelfastBelfastUK
| | | | | | - Zekai Qiang
- Department of Oncology & MetabolismThe University of SheffieldSheffieldUK
| | - Tomas Ferreira
- Department of Clinical Neurosciences, School of Clinical MedicineUniversity of CambridgeCambridgeUK
| | | | - Vallabh Shet
- Faculty of MedicineBangalore Medical College and Research InstituteBangaloreKarnatakaIndia
| | | | | | - Marios Papadakis
- Department of Surgery II, University Hospital Witten‐HerdeckeUniversity of Witten‐HerdeckeWuppertalGermany
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9
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Chang JT, Liu LB, Wang PG, An J. Single-cell RNA sequencing to understand host-virus interactions. Virol Sin 2024; 39:1-8. [PMID: 38008383 PMCID: PMC10877424 DOI: 10.1016/j.virs.2023.11.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 11/23/2023] [Indexed: 11/28/2023] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) has allowed for the profiling of host and virus transcripts and host-virus interactions at single-cell resolution. This review summarizes the existing scRNA-seq technologies together with their strengths and weaknesses. The applications of scRNA-seq in various virological studies are discussed in depth, which broaden the understanding of the immune atlas, host-virus interactions, and immune repertoire. scRNA-seq can be widely used for virology in the near future to better understand the pathogenic mechanisms and discover more effective therapeutic strategies.
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Affiliation(s)
- Jia-Tong Chang
- Department of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, China
| | - Li-Bo Liu
- Department of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, China
| | - Pei-Gang Wang
- Department of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, China.
| | - Jing An
- Department of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, China.
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10
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Wei N, Lee C, Duan L, Galdos FX, Samad T, Raissadati A, Goodyer WR, Wu SM. Cardiac Development at a Single-Cell Resolution. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1441:253-268. [PMID: 38884716 DOI: 10.1007/978-3-031-44087-8_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
Mammalian cardiac development is a complex, multistage process. Though traditional lineage tracing studies have characterized the broad trajectories of cardiac progenitors, the advent and rapid optimization of single-cell RNA sequencing methods have yielded an ever-expanding toolkit for characterizing heterogeneous cell populations in the developing heart. Importantly, they have allowed for a robust profiling of the spatiotemporal transcriptomic landscape of the human and mouse heart, revealing the diversity of cardiac cells-myocyte and non-myocyte-over the course of development. These studies have yielded insights into novel cardiac progenitor populations, chamber-specific developmental signatures, the gene regulatory networks governing cardiac development, and, thus, the etiologies of congenital heart diseases. Furthermore, single-cell RNA sequencing has allowed for the exquisite characterization of distinct cardiac populations such as the hard-to-capture cardiac conduction system and the intracardiac immune population. Therefore, single-cell profiling has also resulted in new insights into the regulation of cardiac regeneration and injury repair. Single-cell multiomics approaches combining transcriptomics, genomics, and epigenomics may uncover an even more comprehensive atlas of human cardiac biology. Single-cell analyses of the developing and adult mammalian heart offer an unprecedented look into the fundamental mechanisms of cardiac development and the complex diseases that may arise from it.
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Affiliation(s)
- Nicholas Wei
- Stanford University, Cardiovascular Institute, Stanford, CA, USA
| | - Carissa Lee
- Stanford University, Cardiovascular Institute, Stanford, CA, USA
| | - Lauren Duan
- Stanford University, Cardiovascular Institute, Stanford, CA, USA
| | | | - Tahmina Samad
- Stanford University, Cardiovascular Institute, Stanford, CA, USA
| | | | | | - Sean M Wu
- Stanford University, Cardiovascular Institute, Stanford, CA, USA.
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11
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Gilmour KM, Daley MA, Egginton S, Kelber A, McHenry MJ, Patek SN, Sane SP, Schulte PM, Terblanche JS, Wright PA, Franklin CE. Through the looking glass: attempting to predict future opportunities and challenges in experimental biology. J Exp Biol 2023; 226:jeb246921. [PMID: 38059428 DOI: 10.1242/jeb.246921] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023]
Abstract
To celebrate its centenary year, Journal of Experimental Biology (JEB) commissioned a collection of articles examining the past, present and future of experimental biology. This Commentary closes the collection by considering the important research opportunities and challenges that await us in the future. We expect that researchers will harness the power of technological advances, such as '-omics' and gene editing, to probe resistance and resilience to environmental change as well as other organismal responses. The capacity to handle large data sets will allow high-resolution data to be collected for individual animals and to understand population, species and community responses. The availability of large data sets will also place greater emphasis on approaches such as modeling and simulations. Finally, the increasing sophistication of biologgers will allow more comprehensive data to be collected for individual animals in the wild. Collectively, these approaches will provide an unprecedented understanding of 'how animals work' as well as keys to safeguarding animals at a time when anthropogenic activities are degrading the natural environment.
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Affiliation(s)
| | - Monica A Daley
- Department of Ecology and Evolutionary Biology, University of California, Irvine, Irvine, CA 92697, USA
| | - Stuart Egginton
- School of Biomedical Sciences, University of Leeds, Leeds LS2 9JT, UK
| | - Almut Kelber
- Department of Biology, Lund University, 22362 Lund, Sweden
| | - Matthew J McHenry
- Department of Ecology and Evolutionary Biology, University of California, Irvine, Irvine, CA 92697, USA
| | - Sheila N Patek
- Biology Department, Duke University, Durham, NC 27708, USA
| | - Sanjay P Sane
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, GKVK Campus, Bellary Road, Bangalore, Karnataka 560065, India
| | - Patricia M Schulte
- Department of Zoology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - John S Terblanche
- Center for Invasion Biology, Department of Conservation Ecology & Entomology, Stellenbosch University, Stellenbosch 7602, South Africa
| | - Patricia A Wright
- Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada
| | - Craig E Franklin
- School of the Environment, The University of Queensland, St. Lucia, Brisbane 4072, Australia
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12
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Liu Y, Wu G. The utilization of single-cell sequencing technology in investigating the immune microenvironment of ccRCC. Front Immunol 2023; 14:1276658. [PMID: 38090562 PMCID: PMC10715415 DOI: 10.3389/fimmu.2023.1276658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 11/07/2023] [Indexed: 12/18/2023] Open
Abstract
The growth and advancement of ccRCC are strongly associated with the presence of immune infiltration and the tumor microenvironment, comprising tumor cells, immune cells, stromal cells, vascular cells, myeloid-derived cells, and extracellular matrix (ECM). Nevertheless, as a result of the diverse and constantly evolving characteristics of the tumor microenvironment, prior advanced sequencing methods have frequently disregarded specific less prevalent cellular traits at varying intervals, thereby concealing their significance. The advancement and widespread use of single-cell sequencing technology enable us to comprehend the source of individual tumor cells and the characteristics of a greater number of individual cells. This, in turn, minimizes the impact of intercellular heterogeneity and temporal heterogeneity of the same cell on experimental outcomes. This review examines the attributes of the tumor microenvironment in ccRCC and provides an overview of the progress made in single-cell sequencing technology and its particular uses in the current focus of immune infiltration in ccRCC.
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Affiliation(s)
| | - Guangzhen Wu
- Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
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13
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Martín-Zamora FM, Davies BE, Donnellan RD, Guynes K, Martín-Durán JM. Functional genomics in Spiralia. Brief Funct Genomics 2023; 22:487-497. [PMID: 37981859 PMCID: PMC10658182 DOI: 10.1093/bfgp/elad036] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 07/12/2023] [Accepted: 07/25/2023] [Indexed: 11/21/2023] Open
Abstract
Our understanding of the mechanisms that modulate gene expression in animals is strongly biased by studying a handful of model species that mainly belong to three groups: Insecta, Nematoda and Vertebrata. However, over half of the animal phyla belong to Spiralia, a morphologically and ecologically diverse animal clade with many species of economic and biomedical importance. Therefore, investigating genome regulation in this group is central to uncovering ancestral and derived features in genome functioning in animals, which can also be of significant societal impact. Here, we focus on five aspects of gene expression regulation to review our current knowledge of functional genomics in Spiralia. Although some fields, such as single-cell transcriptomics, are becoming more common, the study of chromatin accessibility, DNA methylation, histone post-translational modifications and genome architecture are still in their infancy. Recent efforts to generate chromosome-scale reference genome assemblies for greater species diversity and optimise state-of-the-art approaches for emerging spiralian research systems will address the existing knowledge gaps in functional genomics in this animal group.
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Affiliation(s)
- Francisco M Martín-Zamora
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK
| | - Billie E Davies
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK
| | - Rory D Donnellan
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK
| | - Kero Guynes
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK
| | - José M Martín-Durán
- School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK
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14
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Zhao H, Jiang R, Zhang C, Feng Z, Wang X. The regulatory role of cancer stem cell marker gene CXCR4 in the growth and metastasis of gastric cancer. NPJ Precis Oncol 2023; 7:86. [PMID: 37679408 PMCID: PMC10484911 DOI: 10.1038/s41698-023-00436-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 08/17/2023] [Indexed: 09/09/2023] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) are increasingly used for screening genes involved in carcinogenesis due to their capacity for dissecting cellular heterogeneity. This study aims to reveal the molecular mechanism of the cancer stem cells (CSCs) marker gene CXCR4 in gastric cancer (GC) growth and metastasis through scRNA-seq combined with bulk RNA-seq. GC-related scRNA-seq data were downloaded from the GEO database, followed by UMAP cluster analysis. Non-malignant cells were excluded by the K-means algorithm. Bulk RNA-seq data and clinical sample information were downloaded from the UCSC Xena database. GO and KEGG pathway analyses validated the correlation between genes and pathways. In vitro and in vivo functional assays were used to examine the effect of perturbed CXCR4 on malignant phenotypes, tumorigenesis, and liver metastasis. A large number of highly variable genes were identified in GC tissue samples. The top 20 principal components were selected, and the cells were clustered into 6 cell types. The C4 cell cluster from malignant epithelial cells might be CSCs. CXCR4 was singled out as a marker gene of CSCs. GC patients with high CXCR4 expression had poor survival. Knockdown of CXCR4 inhibited the malignant phenotypes of CSCs in vitro and curtailed tumorigenesis and liver metastasis in nude mice. CSC marker gene CXCR4 may be a key gene facilitating malignant phenotypes of CSCs, which thus promotes tumor growth and liver metastasis of GC.
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Affiliation(s)
- Hongying Zhao
- Department of Oncology, Xuzhou City Cancer Hospital, Xuzhou Third People's Hospital, Xuzhou Hospital Affiliated to Jiangsu University, Xuzhou, 221000, PR China.
| | - Rongke Jiang
- Department of Oncology, Xuzhou City Cancer Hospital, Xuzhou Third People's Hospital, Xuzhou Hospital Affiliated to Jiangsu University, Xuzhou, 221000, PR China
| | | | | | - Xue Wang
- Department of Oncology, Xuzhou City Cancer Hospital, Xuzhou Third People's Hospital, Xuzhou Hospital Affiliated to Jiangsu University, Xuzhou, 221000, PR China
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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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Zhang L, Parvin R, Chen M, Hu D, Fan Q, Ye F. High-throughput microfluidic droplets in biomolecular analytical system: A review. Biosens Bioelectron 2023; 228:115213. [PMID: 36906989 DOI: 10.1016/j.bios.2023.115213] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 02/13/2023] [Accepted: 03/06/2023] [Indexed: 03/11/2023]
Abstract
Droplet microfluidic technology has revolutionized biomolecular analytical research, as it has the capability to reserve the genotype-to-phenotype linkage and assist for revealing the heterogeneity. Massive and uniform picolitre droplets feature dividing solution to the level that single cell and single molecule in each droplet can be visualized, barcoded, and analyzed. Then, the droplet assays can unfold intensive genomic data, offer high sensitivity, and screen and sort from a large number of combinations or phenotypes. Based on these unique advantages, this review focuses on up-to-date research concerning diverse screening applications utilizing droplet microfluidic technology. The emerging progress of droplet microfluidic technology is first introduced, including efficient and scaling-up in droplets encapsulation, and prevalent batch operations. Then the new implementations of droplet-based digital detection assays and single-cell muti-omics sequencing are briefly examined, along with related applications such as drug susceptibility testing, multiplexing for cancer subtype identification, interactions of virus-to-host, and multimodal and spatiotemporal analysis. Meanwhile, we specialize in droplet-based large-scale combinational screening regarding desired phenotypes, with an emphasis on sorting for immune cells, antibodies, enzymatic properties, and proteins produced by directed evolution methods. Finally, some challenges, deployment and future perspective of droplet microfluidics technology in practice are also discussed.
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Affiliation(s)
- Lexiang Zhang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Wenzhou, Zhejiang, 325000, China; Zhejiang Engineering Research Center for Tissue Repair Materials, Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang, 325000, China
| | - Rokshana Parvin
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Wenzhou, Zhejiang, 325000, China; Zhejiang Engineering Research Center for Tissue Repair Materials, Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang, 325000, China
| | - Mingshuo Chen
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Wenzhou, Zhejiang, 325000, China; Zhejiang Engineering Research Center for Tissue Repair Materials, Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang, 325000, China
| | - Dingmeng Hu
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Wenzhou, Zhejiang, 325000, China; Zhejiang Engineering Research Center for Tissue Repair Materials, Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang, 325000, China
| | - Qihui Fan
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Wenzhou, Zhejiang, 325000, China; Zhejiang Engineering Research Center for Tissue Repair Materials, Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang, 325000, China; Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing, 100190, China.
| | - Fangfu Ye
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Wenzhou, Zhejiang, 325000, China; Zhejiang Engineering Research Center for Tissue Repair Materials, Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang, 325000, China; Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing, 100190, China.
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17
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van Vliet EA, Hildebrand MS, Mills JD, Brennan GP, Eid T, Masino SA, Whittemore V, Bindila L, Wang KK, Patel M, Perucca P, Reid CA. A companion to the preclinical common data elements for genomics, transcriptomics, and epigenomics data in rodent epilepsy models. A report of the TASK3-WG4 omics working group of the ILAE/AES joint translational TASK force. Epilepsia Open 2022. [PMID: 35950645 DOI: 10.1002/epi4.12640] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 02/22/2022] [Indexed: 11/06/2022] Open
Abstract
The International League Against Epilepsy/American Epilepsy Society (ILAE/AES) Joint Translational Task Force established the TASK3 working groups to create common data elements (CDEs) for various preclinical epilepsy research disciplines. The aim of the CDEs is to improve the standardization of experimental designs across a range of epilepsy research-related methods. Here, we have generated CDE tables with key parameters and case report forms (CRFs) containing the essential contents of the study protocols for genomics, transcriptomics, and epigenomics in rodent models of epilepsy, with a specific focus on adult rats and mice. We discuss the important elements that need to be considered for genomics, transcriptomics, and epigenomics methodologies, providing a rationale for the parameters that should be collected. This is the first in a two-part series of omics papers with the second installment to cover proteomics, lipidomics, and metabolomics in adult rodents.
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Affiliation(s)
- Erwin A van Vliet
- Center for Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam UMC location University of Amsterdam, Department of (Neuro)Pathology, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Michael S Hildebrand
- Epilepsy Research Centre, Department of Medicine (Austin Health), The University of Melbourne, Heidelberg, Victoria, Australia
- Murdoch Children's Research Institute, The Royal Children's Hospital, Parkville, Victoria, Australia
| | - James D Mills
- Amsterdam UMC location University of Amsterdam, Department of (Neuro)Pathology, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Gary P Brennan
- UCD School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Dublin, Ireland
- FutureNeuro Research Centre, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Tore Eid
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Susan A Masino
- Neuroscience Program and Psychology Department, Life Sciences Center, Trinity College, Hartford, Connecticut, USA
| | - Vicky Whittemore
- Division of Neuroscience, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Laura Bindila
- Clinical Lipidomics Unit, Institute of Physiological Chemistry, University Medical Center of the Johannes Gutenberg University of Mainz, Mainz, Germany
| | - Kevin K Wang
- Department of Emergency Medicine, Psychiatry and Neuroscience, University of Florida, Gainesville, Florida, USA
- Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, North Florida/South Georgia Veterans Health System, Gainesville, Florida, USA
| | - Manisha Patel
- Department of Pharmaceutical Sciences, University of Colorado, Aurora, Colorado, USA
| | - Piero Perucca
- Epilepsy Research Centre, Department of Medicine (Austin Health), The University of Melbourne, Heidelberg, Victoria, Australia
- Bladin-Berkovic Comprehensive Epilepsy Program, Austin Health, Heidelberg, Victoria, Australia
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Department of Neurology, The Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Department of Neurology, Alfred Health, Melbourne, Victoria, Australia
| | - Christopher A Reid
- Epilepsy Research Centre, Department of Medicine (Austin Health), The University of Melbourne, Heidelberg, Victoria, Australia
- Murdoch Children's Research Institute, The Royal Children's Hospital, Parkville, Victoria, Australia
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria, Australia
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18
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Wu J, Ding Y, Wang J, Lyu F, Tang Q, Song J, Luo Z, Wan Q, Lan X, Xu Z, Chen L. Single‐cell RNA
sequencing in oral science: Current awareness and perspectives. Cell Prolif 2022; 55:e13287. [PMID: 35842899 PMCID: PMC9528768 DOI: 10.1111/cpr.13287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 05/10/2022] [Accepted: 05/29/2022] [Indexed: 11/30/2022] Open
Abstract
The emergence of single‐cell RNA sequencing enables simultaneous sequencing of thousands of cells, making the analysis of cell population heterogeneity more efficient. In recent years, single‐cell RNA sequencing has been used in the investigation of heterogeneous cell populations, cellular developmental trajectories, stochastic gene transcriptional kinetics, and gene regulatory networks, providing strong support in life science research. However, the application of single‐cell RNA sequencing in the field of oral science has not been reviewed comprehensively yet. Therefore, this paper reviews the development and application of single‐cell RNA sequencing in oral science, including fields of tissue development, teeth and jaws diseases, maxillofacial tumors, infections, etc., providing reference and prospects for using single‐cell RNA sequencing in studying the oral diseases, tissue development, and regeneration.
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Affiliation(s)
- Jie Wu
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Guanghua School of Stomatology, Hospital of Stomatology, Guangdong Provincial Key Laboratory of Stomatology Sun Yat‐sen University Guangzhou China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
| | - Yumei Ding
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
| | - Jinyu Wang
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
| | - Fengyuan Lyu
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
- Center of Stomatology, Tongji Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
| | - Qingming Tang
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
| | - Jiangyuan Song
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
| | - Zhiqiang Luo
- National Engineering Research Center for Nanomedicine College of Life Science and Technolog Huazhong University of Science and Technology Wuhan China
| | - Qian Wan
- Hubei Key Laboratory of Natural Medicinal Chemistry and Resource Evaluation, School of Pharmacy Huazhong University of Science and Technology Wuhan China
- Institute of Brain Research Huazhong University of Science and Technology Wuhan China
| | - Xiaoli Lan
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Key Laboratory of Molecular Imaging Wuhan China
| | - Zhi Xu
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
| | - Lili Chen
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
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19
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Li X, Li S, Wu B, Xu Q, Teng D, Yang T, Sun Y, Zhao Y, Li T, Liu D, Yang S, Gong W, Cai J. Landscape of Immune Cells Heterogeneity in Liver Transplantation by Single-Cell RNA Sequencing Analysis. Front Immunol 2022; 13:890019. [PMID: 35619708 PMCID: PMC9127089 DOI: 10.3389/fimmu.2022.890019] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 04/11/2022] [Indexed: 12/18/2022] Open
Abstract
Rejection is still a critical barrier to the long-term survival of graft after liver transplantation, requiring clinicians to unveil the underlying mechanism of liver transplant rejection. The cellular diversity and the interplay between immune cells in the liver graft microenvironment remain unclear. Herein, we performed single-cell RNA sequencing analysis to delineate the landscape of immune cells heterogeneity in liver transplantation. T cells, NK cells, B cells, and myeloid cell subsets in human liver and blood were enriched to characterize their tissue distribution, gene expression, and functional modules. The proportion of CCR6+CD4+ T cells increased within an allograft, suggesting that there are more memory CD4+ T cells after transplantation, in parallel with exhausted CTLA4+CD8+ T and actively proliferating MKI67+CD8+ T cells increased significantly, where they manifested heterogeneity, distinct function, and homeostatic proliferation. Remarkably, the changes of CD1c+ DC, CADM+ DC, MDSC, and FOLR3+ Kupffer cells increase significantly, but the proportion of CD163+ Kupffer, APOE+ Kupffer, and GZMA+ Kupffer decreased. Furthermore, we identified LDLR as a novel marker of activated MDSC to prevent liver transplant rejection. Intriguingly, a subset of CD4+CD8+FOXP3+ T cells included in CTLA4+CD8+ T cells was first detected in human liver transplantation. Furthermore, intercellular communication and gene regulatory analysis implicated the LDLR+ MDSC and CTLA4+CD8+ T cells interact through TIGIT-NECTIN2 signaling pathway. Taken together, these findings have gained novel mechanistic insights for understanding the immune landscape in liver transplantation, and it outlines the characteristics of immune cells and provides potential therapeutic targets in liver transplant rejection.
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Affiliation(s)
- Xinqiang Li
- Organ Transplantation Center, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Shipeng Li
- Department of General Surgery, Jiaozuo Women's and Children's Hospital, Jiaozuo, China.,The Second Clinical Medical College, Capital Medical University, Beijing, China
| | - Bin Wu
- Organ Transplantation Center, Affiliated Hospital of Qingdao University, Qingdao, China.,Institute of Organ Donation and Transplantation, Medical College of Qingdao University, Qingdao, China
| | - Qingguo Xu
- Organ Transplantation Center, Affiliated Hospital of Qingdao University, Qingdao, China.,Institute of Organ Donation and Transplantation, Medical College of Qingdao University, Qingdao, China
| | - Dahong Teng
- Organ Transplantation Center, Affiliated Hospital of Qingdao University, Qingdao, China.,Institute of Organ Donation and Transplantation, Medical College of Qingdao University, Qingdao, China
| | - Tongwang Yang
- Organ Transplantation Center, Affiliated Hospital of Qingdao University, Qingdao, China.,Institute of Organ Donation and Transplantation, Medical College of Qingdao University, Qingdao, China
| | - Yandong Sun
- Organ Transplantation Center, Affiliated Hospital of Qingdao University, Qingdao, China.,Institute of Organ Donation and Transplantation, Medical College of Qingdao University, Qingdao, China
| | - Yang Zhao
- Department of Urology Surgery, Peking Union Medical College Hospital, Beijing, China
| | - Tianxiang Li
- Organ Transplantation Center, Affiliated Hospital of Qingdao University, Qingdao, China.,Institute of Organ Donation and Transplantation, Medical College of Qingdao University, Qingdao, China
| | - Dan Liu
- Organ Transplantation Center, Affiliated Hospital of Qingdao University, Qingdao, China.,Institute of Organ Donation and Transplantation, Medical College of Qingdao University, Qingdao, China
| | - Shuang Yang
- Department of Molecular Biology, Medical College, Nankai University, Tianjin, China
| | - Weihua Gong
- Department of Surgery, Second Affiliated Hospital of School of Medicine, Zhejiang University, Hangzhou, China
| | - Jinzhen Cai
- Organ Transplantation Center, Affiliated Hospital of Qingdao University, Qingdao, China.,Institute of Organ Donation and Transplantation, Medical College of Qingdao University, Qingdao, China
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20
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Alberico H, Fleischmann Z, Bobbitt T, Takai Y, Ishihara O, Seki H, Anderson RA, Telfer EE, Woods DC, Tilly JL. Workflow Optimization for Identification of Female Germline or Oogonial Stem Cells in Human Ovarian Cortex Using Single-Cell RNA Sequence Analysis. Stem Cells 2022; 40:523-536. [PMID: 35263439 PMCID: PMC9199849 DOI: 10.1093/stmcls/sxac015] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 02/15/2022] [Indexed: 11/16/2022]
Abstract
In 2004, the identification of female germline or oogonial stem cells (OSCs) that can support post-natal oogenesis in ovaries of adult mice sparked a major paradigm shift in reproductive biology. Although these findings have been independently verified, and further extended to include identification of OSCs in adult ovaries of many species ranging from pigs and cows to non-human primates and humans, a recent study rooted in single-cell RNA sequence analysis (scRNA-seq) of adult human ovarian cortical tissue claimed that OSCs do not exist, and that other groups working with OSCs following isolation by magnetic-assisted or fluorescence-activated cell sorting have mistaken perivascular cells (PVCs) for germ cells. Here we report that rare germ lineage cells with a gene expression profile matched to OSCs but distinct from that of other cells, including oocytes and PVCs, can be identified in adult human ovarian cortical tissue by scRNA-seq after optimization of analytical workflow parameters. Deeper cell-by-cell expression profiling also uncovered evidence of germ cells undergoing meiosis-I in adult human ovaries. Lastly, we show that, if not properly controlled for, PVCs can be inadvertently isolated during flow cytometry protocols designed to sort OSCs because of inherently high cellular autofluorescence. However, human PVCs and human germ cells segregate into distinct clusters following scRNA-seq due to non-overlapping gene expression profiles, which would preclude the mistaken identification and use of PVCs as OSCs during functional characterization studies.
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Affiliation(s)
- Hannah Alberico
- Laboratory of Aging and Infertility Research, Department of Biology, Northeastern University, Boston, MA 02115, USA
| | - Zoë Fleischmann
- Laboratory of Aging and Infertility Research, Department of Biology, Northeastern University, Boston, MA 02115, USA
| | - Tyler Bobbitt
- Laboratory of Aging and Infertility Research, Department of Biology, Northeastern University, Boston, MA 02115, USA
| | - Yasushi Takai
- Department of Obstetrics and Gynecology, Saitama Medical Center, Saitama Medical University, Saitama 350-0495, Japan
| | - Osamu Ishihara
- Department of Obstetrics and Gynecology, Saitama Medical Center, Saitama Medical University, Saitama 350-0495, Japan
| | - Hiroyuki Seki
- Department of Obstetrics and Gynecology, Saitama Medical Center, Saitama Medical University, Saitama 350-0495, Japan
| | - Richard A Anderson
- MRC Centre for Reproductive Health, Queens Medical Research Institute, University of Edinburgh, Edinburgh EH14 1DJ, UK
| | - Evelyn E Telfer
- Institute of Cell Biology, University of Edinburgh, Edinburgh EH14 1DJ, UK
| | - Dori C Woods
- Laboratory of Aging and Infertility Research, Department of Biology, Northeastern University, Boston, MA 02115, USA
| | - Jonathan L Tilly
- Laboratory of Aging and Infertility Research, Department of Biology, Northeastern University, Boston, MA 02115, USA
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21
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Han Y, Wang D, Peng L, Huang T, He X, Wang J, Ou C. Single-cell sequencing: a promising approach for uncovering the mechanisms of tumor metastasis. J Hematol Oncol 2022; 15:59. [PMID: 35549970 PMCID: PMC9096771 DOI: 10.1186/s13045-022-01280-w] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 04/28/2022] [Indexed: 02/08/2023] Open
Abstract
Single-cell sequencing (SCS) is an emerging high-throughput technology that can be used to study the genomics, transcriptomics, and epigenetics at a single cell level. SCS is widely used in the diagnosis and treatment of various diseases, including cancer. Over the years, SCS has gradually become an effective clinical tool for the exploration of tumor metastasis mechanisms and the development of treatment strategies. Currently, SCS can be used not only to analyze metastasis-related malignant biological characteristics, such as tumor heterogeneity, drug resistance, and microenvironment, but also to construct metastasis-related cell maps for predicting and monitoring the dynamics of metastasis. SCS is also used to identify therapeutic targets related to metastasis as it provides insights into the distribution of tumor cell subsets and gene expression differences between primary and metastatic tumors. Additionally, SCS techniques in combination with artificial intelligence (AI) are used in liquid biopsy to identify circulating tumor cells (CTCs), thereby providing a novel strategy for treating tumor metastasis. In this review, we summarize the potential applications of SCS in the field of tumor metastasis and discuss the prospects and limitations of SCS to provide a theoretical basis for finding therapeutic targets and mechanisms of metastasis.
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Affiliation(s)
- Yingying Han
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Dan Wang
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Lushan Peng
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Tao Huang
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Xiaoyun He
- Departments of Ultrasound Imaging, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
| | - Junpu Wang
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China. .,Department of Pathology, School of Basic Medicine, Central South University, Changsha, 410031, Hunan, China. .,Key Laboratory of Hunan Province in Neurodegenerative Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
| | - Chunlin Ou
- Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China. .,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
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22
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Mani DR, Krug K, Zhang B, Satpathy S, Clauser KR, Ding L, Ellis M, Gillette MA, Carr SA. Cancer proteogenomics: current impact and future prospects. Nat Rev Cancer 2022; 22:298-313. [PMID: 35236940 DOI: 10.1038/s41568-022-00446-5] [Citation(s) in RCA: 76] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/21/2022] [Indexed: 02/07/2023]
Abstract
Genomic analyses in cancer have been enormously impactful, leading to the identification of driver mutations and development of targeted therapies. But the functions of the vast majority of somatic mutations and copy number variants in tumours remain unknown, and the causes of resistance to targeted therapies and methods to overcome them are poorly defined. Recent improvements in mass spectrometry-based proteomics now enable direct examination of the consequences of genomic aberrations, providing deep and quantitative characterization of tumour tissues. Integration of proteins and their post-translational modifications with genomic, epigenomic and transcriptomic data constitutes the new field of proteogenomics, and is already leading to new biological and diagnostic knowledge with the potential to improve our understanding of malignant transformation and therapeutic outcomes. In this Review we describe recent developments in proteogenomics and key findings from the proteogenomic analysis of a wide range of cancers. Considerations relevant to the selection and use of samples for proteogenomics and the current technologies used to generate, analyse and integrate proteomic with genomic data are described. Applications of proteogenomics in translational studies and immuno-oncology are rapidly emerging, and the prospect for their full integration into therapeutic trials and clinical care seems bright.
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Affiliation(s)
- D R Mani
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA.
| | - Karsten Krug
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Bing Zhang
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, USA
| | - Shankha Satpathy
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Karl R Clauser
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
| | - Li Ding
- Department of Medicine and Genetics, Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO, USA
| | - Matthew Ellis
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, USA
| | - Michael A Gillette
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
- Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Steven A Carr
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA.
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23
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Ahmed R, Zaman T, Chowdhury F, Mraiche F, Tariq M, Ahmad IS, Hasan A. Single-Cell RNA Sequencing with Spatial Transcriptomics of Cancer Tissues. Int J Mol Sci 2022; 23:3042. [PMID: 35328458 PMCID: PMC8955933 DOI: 10.3390/ijms23063042] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Revised: 02/02/2022] [Accepted: 03/07/2022] [Indexed: 01/27/2023] Open
Abstract
Single-cell RNA sequencing (RNA-seq) techniques can perform analysis of transcriptome at the single-cell level and possess an unprecedented potential for exploring signatures involved in tumor development and progression. These techniques can perform sequence analysis of transcripts with a better resolution that could increase understanding of the cellular diversity found in the tumor microenvironment and how the cells interact with each other in complex heterogeneous cancerous tissues. Identifying the changes occurring in the genome and transcriptome in the spatial context is considered to increase knowledge of molecular factors fueling cancers. It may help develop better monitoring strategies and innovative approaches for cancer treatment. Recently, there has been a growing trend in the integration of RNA-seq techniques with contemporary omics technologies to study the tumor microenvironment. There has been a realization that this area of research has a huge scope of application in translational research. This review article presents an overview of various types of single-cell RNA-seq techniques used currently for analysis of cancer tissues, their pros and cons in bulk profiling of transcriptome, and recent advances in the techniques in exploring heterogeneity of various types of cancer tissues. Furthermore, we have highlighted the integration of single-cell RNA-seq techniques with other omics technologies for analysis of transcriptome in their spatial context, which is considered to revolutionize the understanding of tumor microenvironment.
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Affiliation(s)
- Rashid Ahmed
- Department of Mechanical and Industrial Engineering, College of Engineering, Qatar University, Doha 2713, Qatar
- Biomedical Research Centre, Qatar University, Doha 2713, Qatar
- Department of Biotechnology, Faculty of Natural and Applied Sciences, Mirpur University of Science and Technology, Mirpur 10250 AJK, Pakistan;
- Nick Holonyak Jr. Micro and Nanotechnology Laboratory, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA;
| | - Tariq Zaman
- College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA;
| | - Farhan Chowdhury
- Department of Mechanical Engineering and Energy Processes, Southern Illinois University Carbondale, Carbondale, IL 62901, USA;
| | - Fatima Mraiche
- Department of Pharmaceutical Sciences, College of Pharmacy, QU Health, Qatar University, Doha 2713, Qatar;
| | - Muhammad Tariq
- Department of Biotechnology, Faculty of Natural and Applied Sciences, Mirpur University of Science and Technology, Mirpur 10250 AJK, Pakistan;
| | - Irfan S. Ahmad
- Nick Holonyak Jr. Micro and Nanotechnology Laboratory, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA;
- Department of Agricultural and Biological Engineering, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA
- Carle Illinois College of Medicine, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA
| | - Anwarul Hasan
- Department of Mechanical and Industrial Engineering, College of Engineering, Qatar University, Doha 2713, Qatar
- Biomedical Research Centre, Qatar University, Doha 2713, Qatar
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24
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Luo L, Gribskov M, Wang S. Bibliometric review of ATAC-Seq and its application in gene expression. Brief Bioinform 2022; 23:6543486. [PMID: 35255493 PMCID: PMC9116206 DOI: 10.1093/bib/bbac061] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 02/06/2022] [Accepted: 02/09/2022] [Indexed: 11/30/2022] Open
Abstract
With recent advances in high-throughput next-generation sequencing, it is possible to describe the regulation and expression of genes at multiple levels. An assay for transposase-accessible chromatin using sequencing (ATAC-seq), which uses Tn5 transposase to sequence protein-free binding regions of the genome, can be combined with chromatin immunoprecipitation coupled with deep sequencing (ChIP-seq) and ribonucleic acid sequencing (RNA-seq) to provide a detailed description of gene expression. Here, we reviewed the literature on ATAC-seq and described the characteristics of ATAC-seq publications. We then briefly introduced the principles of RNA-seq, ChIP-seq and ATAC-seq, focusing on the main features of the techniques. We built a phylogenetic tree from species that had been previously studied by using ATAC-seq. Studies of Mus musculus and Homo sapiens account for approximately 90% of the total ATAC-seq data, while other species are still in the process of accumulating data. We summarized the findings from human diseases and other species, illustrating the cutting-edge discoveries and the role of multi-omics data analysis in current research. Moreover, we collected and compared ATAC-seq analysis pipelines, which allowed biological researchers who lack programming skills to better analyze and explore ATAC-seq data. Through this review, it is clear that multi-omics analysis and single-cell sequencing technology will become the mainstream approach in future research.
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Affiliation(s)
- Liheng Luo
- School of Life Sciences, Northwestern Polytechnical University, Xi'an, Shaanxi, China, 710072
| | - Michael Gribskov
- Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA
| | - Sufang Wang
- School of Life Sciences, Northwestern Polytechnical University, Xi'an, Shaanxi, China, 710072
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25
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Ascensión AM, Araúzo-Bravo MJ, Izeta A. Challenges and Opportunities for the Translation of Single-Cell RNA Sequencing Technologies to Dermatology. Life (Basel) 2022; 12:67. [PMID: 35054460 PMCID: PMC8781146 DOI: 10.3390/life12010067] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/21/2021] [Accepted: 12/28/2021] [Indexed: 12/19/2022] Open
Abstract
Skin is a complex and heterogeneous organ at the cellular level. This complexity is beginning to be understood through the application of single-cell genomics and computational tools. A large number of datasets that shed light on how the different human skin cell types interact in homeostasis-and what ceases to work in diverse dermatological diseases-have been generated and are publicly available. However, translation of these novel aspects to the clinic is lacking. This review aims to summarize the state-of-the-art of skin biology using single-cell technologies, with a special focus on skin pathologies and the translation of mechanistic findings to the clinic. The main implications of this review are to summarize the benefits and limitations of single-cell analysis and thus help translate the emerging insights from these novel techniques to the bedside.
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Affiliation(s)
- Alex M. Ascensión
- Tissue Engineering Group, Biodonostia Health Research Institute, 20014 Donostia-San Sebastián, Spain;
- Computational Biology and Systems Biomedicine Group, Biodonostia Health Research Institute, 20014 Donostia-San Sebastián, Spain;
| | - Marcos J. Araúzo-Bravo
- Computational Biology and Systems Biomedicine Group, Biodonostia Health Research Institute, 20014 Donostia-San Sebastián, Spain;
- Max Planck Institute for Molecular Biomedicine, 48167 Muenster, Germany
- IKERBASQUE, Basque Foundation for Science, 48012 Bilbao, Spain
| | - Ander Izeta
- Tissue Engineering Group, Biodonostia Health Research Institute, 20014 Donostia-San Sebastián, Spain;
- School of Engineering, Tecnun-University of Navarra, 20009 Donostia-San Sebastián, Spain
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26
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Verma D, Nayak N, Singh A, Singh AK, Garg N. Advancement of Single-Cell Sequencing in Medulloblastoma. Methods Mol Biol 2022; 2423:65-83. [PMID: 34978689 DOI: 10.1007/978-1-0716-1952-0_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] [Indexed: 06/14/2023]
Abstract
Single-cell sequencing is a promising attempt to investigate the genomic, transcriptomic, and multiomic level of individual cell in the larger population of cells. The outward evolution of the technique from a manual method to the automation of single-cell sequencing is cogent. Lately, single-cell sequencing is widely used in various fields of science and has applications in neurobiology, immunity, cancer, microbiology, reproduction, and digestion. This chapter introduces the reader to the details of single-cell sequencing, currently used in several small-scale and commercial platforms. The advancement of single-cell sequencing in brain cancer sheds light on questions unanswered so far in the field of oncology.
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Affiliation(s)
- Deepanshu Verma
- School of Basic Sciences and BioX center, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India
| | - Namyashree Nayak
- School of Basic Sciences and BioX center, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India
| | - Ashuthosh Singh
- School of Basic Sciences and BioX center, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India
| | - Ashutosh Kumar Singh
- School of Basic Sciences and BioX center, Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India
| | - Neha Garg
- Department of Medicinal Chemistry, Faculty of Ayurveda, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh, India.
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27
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Li X, Wang CY. From bulk, single-cell to spatial RNA sequencing. Int J Oral Sci 2021; 13:36. [PMID: 34782601 PMCID: PMC8593179 DOI: 10.1038/s41368-021-00146-0] [Citation(s) in RCA: 160] [Impact Index Per Article: 53.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Revised: 10/25/2021] [Accepted: 10/25/2021] [Indexed: 01/19/2023] Open
Abstract
RNA sequencing (RNAseq) can reveal gene fusions, splicing variants, mutations/indels in addition to differential gene expression, thus providing a more complete genetic picture than DNA sequencing. This most widely used technology in genomics tool box has evolved from classic bulk RNA sequencing (RNAseq), popular single cell RNA sequencing (scRNAseq) to newly emerged spatial RNA sequencing (spRNAseq). Bulk RNAseq studies average global gene expression, scRNAseq investigates single cell RNA biology up to 20,000 individual cells simultaneously, while spRNAseq has ability to dissect RNA activities spatially, representing next generation of RNA sequencing. This article highlights these technologies, characteristic features and suitable applications in precision oncology.
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Affiliation(s)
- Xinmin Li
- UCLA Technology Center for Genomics & Bioinformatics, Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
| | - Cun-Yu Wang
- Laboratory of Molecular Signaling, Division of Oral Biology and Medicine, School of Dentistry and Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, CA, USA.
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, UCLA, Los Angeles, CA, USA.
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28
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Bomidi C, Robertson M, Coarfa C, Estes MK, Blutt SE. Single-cell sequencing of rotavirus-infected intestinal epithelium reveals cell-type specific epithelial repair and tuft cell infection. Proc Natl Acad Sci U S A 2021; 118:e2112814118. [PMID: 34732579 PMCID: PMC8609316 DOI: 10.1073/pnas.2112814118] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/14/2021] [Indexed: 12/20/2022] Open
Abstract
Intestinal epithelial damage is associated with most digestive diseases and results in detrimental effects on nutrient absorption and production of hormones and antimicrobial defense molecules. Thus, understanding epithelial repair and regeneration following damage is essential in developing therapeutics that assist in rapid healing and restoration of normal intestinal function. Here we used a well-characterized enteric virus (rotavirus) that damages the epithelium at the villus tip but does not directly damage the intestinal stem cell, to explore the regenerative transcriptional response of the intestinal epithelium at the single-cell level. We found that there are specific Lgr5+ cell subsets that exhibit increased cycling frequency associated with significant expansion of the epithelial crypt. This was accompanied by an increase in the number of immature enterocytes. Unexpectedly, we found rotavirus infects tuft cells. Transcriptional profiling indicates tuft cells respond to viral infection through interferon-related pathways. Together these data provide insights as to how the intestinal epithelium responds to insults by providing evidence of stimulation of a repair program driven by stem cells with involvement of tuft cells that results in the production of immature enterocytes that repair the damaged epithelium.
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Affiliation(s)
- Carolyn Bomidi
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030
| | - Matthew Robertson
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030
| | - Cristian Coarfa
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030
| | - Mary K Estes
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030;
- Department of Medicine, Baylor College of Medicine, Houston, TX 77030
| | - Sarah E Blutt
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030;
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29
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Zhou WM, Yan YY, Guo QR, Ji H, Wang H, Xu TT, Makabel B, Pilarsky C, He G, Yu XY, Zhang JY. Microfluidics applications for high-throughput single cell sequencing. J Nanobiotechnology 2021; 19:312. [PMID: 34635104 PMCID: PMC8507141 DOI: 10.1186/s12951-021-01045-6] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 09/16/2021] [Indexed: 12/22/2022] Open
Abstract
The inherent heterogeneity of individual cells in cell populations plays significant roles in disease development and progression, which is critical for disease diagnosis and treatment. Substantial evidences show that the majority of traditional gene profiling methods mask the difference of individual cells. Single cell sequencing can provide data to characterize the inherent heterogeneity of individual cells, and reveal complex and rare cell populations. Different microfluidic technologies have emerged for single cell researches and become the frontiers and hot topics over the past decade. In this review article, we introduce the processes of single cell sequencing, and review the principles of microfluidics for single cell analysis. Also, we discuss the common high-throughput single cell sequencing technologies along with their advantages and disadvantages. Lastly, microfluidics applications in single cell sequencing technology for the diagnosis of cancers and immune system diseases are briefly illustrated.
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Affiliation(s)
- Wen-Min Zhou
- Key Laboratory of Molecular Target & Clinical Pharmacology , The State & NMPA Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences & the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, 511436, People's Republic of China
| | - Yan-Yan Yan
- School of Medicine, Shanxi Datong University, Datong, 037009, People's Republic of China
| | - Qiao-Ru Guo
- Key Laboratory of Molecular Target & Clinical Pharmacology , The State & NMPA Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences & the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, 511436, People's Republic of China
| | - Hong Ji
- Key Laboratory of Molecular Target & Clinical Pharmacology , The State & NMPA Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences & the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, 511436, People's Republic of China
| | - Hui Wang
- Guangzhou Institute of Pediatrics/Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510623, People's Republic of China
| | - Tian-Tian Xu
- Guangzhou Institute of Pediatrics/Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510623, People's Republic of China
| | - Bolat Makabel
- Xinjiang Institute of Materia Medica, Urumqi, 830004, People's Republic of China
| | - Christian Pilarsky
- Department of Surgery, Friedrich-Alexander University of Erlangen-Nuremberg (FAU), University Hospital of Erlangen, Erlangen, Germany
| | - Gen He
- Key Laboratory of Molecular Target & Clinical Pharmacology , The State & NMPA Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences & the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, 511436, People's Republic of China.
| | - Xi-Yong Yu
- Key Laboratory of Molecular Target & Clinical Pharmacology , The State & NMPA Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences & the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, 511436, People's Republic of China.
| | - Jian-Ye Zhang
- Key Laboratory of Molecular Target & Clinical Pharmacology , The State & NMPA Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences & the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, 511436, People's Republic of China.
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30
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Dissecting the human kidney allograft transcriptome: single-cell RNA sequencing. Curr Opin Organ Transplant 2021; 26:43-51. [PMID: 33315769 DOI: 10.1097/mot.0000000000000840] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
PURPOSE OF REVIEW Single-cell RNA sequencing (scRNA-seq) has provided opportunities to interrogate kidney allografts at a hitherto unavailable molecular level of resolution. Understanding of this technology is essential to better appreciate the relevant biomedical literature. RECENT FINDINGS Sequencing is a technique to determine the order of nucleotides in a segment of RNA or DNA. RNA-seq of kidney allograft tissues has revealed novel mechanistic insights but does not provide information on individual cell types and cell states. scRNA-seq enables to study the transcriptome of individual cells and assess the transcriptional differences and similarities within a population of cells. Initial studies on rejecting kidney allograft tissues in humans have identified the transcriptional profile of the active players of the innate and adaptive immune system. Application of scRNA-seq in a preclinical model of kidney transplantation has revealed that allograft-infiltrating myeloid cells follow a trajectory of differentiation from monocytes to proinflammatory macrophages and exhibit distinct interactions with kidney allograft parenchymal cells; myeloid cell expression of Axl played a major role in promoting intragraft myeloid cell and T-cell differentiation. SUMMARY The current review discusses the technical aspects of scRNA-seq and summarizes the application of this technology to dissect the human kidney allograft transcriptome.
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31
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Oh S, Gray DHD, Chong MMW. Single-Cell RNA Sequencing Approaches for Tracing T Cell Development. THE JOURNAL OF IMMUNOLOGY 2021; 207:363-370. [PMID: 34644259 DOI: 10.4049/jimmunol.2100408] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 05/20/2021] [Indexed: 01/17/2023]
Abstract
T cell development occurs in the thymus, where uncommitted progenitors are directed into a range of sublineages with distinct functions. The goal is to generate a TCR repertoire diverse enough to recognize potential pathogens while remaining tolerant of self. Decades of intensive research have characterized the transcriptional programs controlling critical differentiation checkpoints at the population level. However, greater precision regarding how and when these programs orchestrate differentiation at the single-cell level is required. Single-cell RNA sequencing approaches are now being brought to bear on this question, to track the identity of cells and analyze their gene expression programs at a resolution not previously possible. In this review, we discuss recent advances in the application of these technologies that have the potential to yield unprecedented insight to T cell development.
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Affiliation(s)
- Seungyoul Oh
- St. Vincent's Institute of Medical Research, Fitzroy, Victoria, Australia.,Department of Medicine (St. Vincent's), The University of Melbourne, Fitzroy, Victoria, Australia
| | - Daniel H D Gray
- The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia; and.,Department of Medical Biology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Mark M W Chong
- St. Vincent's Institute of Medical Research, Fitzroy, Victoria, Australia; .,Department of Medicine (St. Vincent's), The University of Melbourne, Fitzroy, Victoria, Australia
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32
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Ma F, Zhang S, Song L, Wang B, Wei L, Zhang F. Applications and analytical tools of cell communication based on ligand-receptor interactions at single cell level. Cell Biosci 2021; 11:121. [PMID: 34217372 PMCID: PMC8254218 DOI: 10.1186/s13578-021-00635-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 06/22/2021] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Cellular communication is an essential feature of multicellular organisms. Binding of ligands to their homologous receptors, which activate specific cell signaling pathways, is a basic type of cellular communication and intimately linked to many degeneration processes leading to diseases. MAIN BODY This study reviewed the history of ligand-receptor and presents the databases which store ligand-receptor pairs. The recently applications and research tools of ligand-receptor interactions for cell communication at single cell level by using single cell RNA sequencing have been sorted out. CONCLUSION The summary of the advantages and disadvantages of analysis tools will greatly help researchers analyze cell communication at the single cell level. Learning cell communication based on ligand-receptor interactions by single cell RNA sequencing gives way to developing new target drugs and personalizing treatment.
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Affiliation(s)
- Fen Ma
- Department of Microbiology, Harbin Medical University, Harbin, 150081 China
- Wu Lien-Teh Institute, Harbin Medical University, Harbin, 150081 China
| | - Siwei Zhang
- Department of Microbiology, Harbin Medical University, Harbin, 150081 China
- Wu Lien-Teh Institute, Harbin Medical University, Harbin, 150081 China
| | - Lianhao Song
- Department of Microbiology, Harbin Medical University, Harbin, 150081 China
- Wu Lien-Teh Institute, Harbin Medical University, Harbin, 150081 China
| | - Bozhi Wang
- Department of Microbiology, Harbin Medical University, Harbin, 150081 China
- Wu Lien-Teh Institute, Harbin Medical University, Harbin, 150081 China
| | - Lanlan Wei
- Department of Microbiology, Harbin Medical University, Harbin, 150081 China
- Wu Lien-Teh Institute, Harbin Medical University, Harbin, 150081 China
- Shenzhen Third People‘s Hospital, Second Hospital, Affiliated to Southern University of Science and Technology, Shenzhen, 518112 China
| | - Fengmin Zhang
- Department of Microbiology, Harbin Medical University, Harbin, 150081 China
- Wu Lien-Teh Institute, Harbin Medical University, Harbin, 150081 China
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33
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Gautam V, Mittal A, Kalra S, Mohanty SK, Gupta K, Rani K, Naidu S, Mishra T, Sengupta D, Ahuja G. EcTracker: Tracking and elucidating ectopic expression leveraging large-scale scRNA-seq studies. Brief Bioinform 2021; 22:6309926. [PMID: 34184038 DOI: 10.1093/bib/bbab237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 05/31/2021] [Accepted: 06/01/2021] [Indexed: 11/13/2022] Open
Abstract
Dramatic genomic alterations, either inducible or in a pathological state, dismantle the core regulatory networks, leading to the activation of normally silent genes. Despite possessing immense therapeutic potential, accurate detection of these transcripts is an ever-challenging task, as it requires prior knowledge of the physiological gene expression levels. Here, we introduce EcTracker, an R-/Shiny-based single-cell data analysis web server that bestows a plethora of functionalities that collectively enable the quantitative and qualitative assessments of bona fide cell types or tissue-specific transcripts and, conversely, the ectopically expressed genes in the single-cell ribonucleic acid sequencing datasets. Moreover, it also allows regulon analysis to identify the key transcriptional factors regulating the user-selected gene signatures. To demonstrate the EcTracker functionality, we reanalyzed the CRISPR interference (CRISPRi) dataset of the human embryonic stem cells differentiated into endoderm lineage and identified the prominent enrichment of a specific gene signature in the SMAD2 knockout cells whose identity was ambiguous in the original study. The key distinguishing features of EcTracker lie within its processing speed, availability of multiple add-on modules, interactive graphical user interface and comprehensiveness. In summary, EcTracker provides an easy-to-perform, integrative and end-to-end single-cell data analysis platform that allows decoding of cellular identities, identification of ectopically expressed genes and their regulatory networks, and therefore, collectively imparts a novel dimension for analyzing single-cell datasets.
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Affiliation(s)
- Vishakha Gautam
- Indraprastha Institute of Information Technology, Delhi, India
| | - Aayushi Mittal
- Indraprastha Institute of Information Technology, Delhi, India
| | - Siddhant Kalra
- Indraprastha Institute of Information Technology, Delhi, India
| | | | - Krishan Gupta
- Indraprastha Institute of Information Technology, Delhi, India
| | - Komal Rani
- Indraprastha Institute of Information Technology, Delhi, India
| | - Srivatsava Naidu
- Department of Biomedical Engineering, Indian Institute of Technology Ropar, India
| | | | - Debarka Sengupta
- Department of Computational Biology and Department of Computer Science at the Indraprastha Institute of Information Technology, India
| | - Gaurav Ahuja
- Department of Computational Biology at the Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), India
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Dai X, Xu F, Wang S, Mundra PA, Zheng J. PIKE-R2P: Protein-protein interaction network-based knowledge embedding with graph neural network for single-cell RNA to protein prediction. BMC Bioinformatics 2021; 22:139. [PMID: 34078261 PMCID: PMC8170782 DOI: 10.1186/s12859-021-04022-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 02/11/2021] [Indexed: 12/05/2022] Open
Abstract
Background Recent advances in simultaneous measurement of RNA and protein abundances at single-cell level provide a unique opportunity to predict protein abundance from scRNA-seq data using machine learning models. However, existing machine learning methods have not considered relationship among the proteins sufficiently. Results We formulate this task in a multi-label prediction framework where multiple proteins are linked to each other at the single-cell level. Then, we propose a novel method for single-cell RNA to protein prediction named PIKE-R2P, which incorporates protein–protein interactions (PPI) and prior knowledge embedding into a graph neural network. Compared with existing methods, PIKE-R2P could significantly improve prediction performance in terms of smaller errors and higher correlations with the gold standard measurements. Conclusion The superior performance of PIKE-R2P indicates that adding the prior knowledge of PPI to graph neural networks can be a powerful strategy for cross-modality prediction of protein abundances at the single-cell level.
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Affiliation(s)
- Xinnan Dai
- School of Information Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Pudong District, Shanghai, 201210, China
| | - Fan Xu
- School of Information Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Pudong District, Shanghai, 201210, China
| | - Shike Wang
- School of Information Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Pudong District, Shanghai, 201210, China
| | - Piyushkumar A Mundra
- Molecular Oncology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, Manchester, UK
| | - Jie Zheng
- School of Information Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Pudong District, Shanghai, 201210, China.
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Chen Y, Song J, Ruan Q, Zeng X, Wu L, Cai L, Wang X, Yang C. Single-Cell Sequencing Methodologies: From Transcriptome to Multi-Dimensional Measurement. SMALL METHODS 2021; 5:e2100111. [PMID: 34927917 DOI: 10.1002/smtd.202100111] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 03/26/2021] [Indexed: 06/14/2023]
Abstract
Cells are the basic building blocks of biological systems, with inherent unique molecular features and development trajectories. The study of single cells facilitates in-depth understanding of cellular diversity, disease processes, and organization of multicellular organisms. Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for the interrogation of gene expression patterns and the dynamics of single cells, allowing cellular heterogeneity to be dissected at unprecedented resolution. Nevertheless, measuring at only transcriptome level or 1D is incomplete; the cellular heterogeneity reflects in multiple dimensions, including the genome, epigenome, transcriptome, spatial, and even temporal dimensions. Hence, integrative single cell analysis is highly desired. In addition, the way to interpret sequencing data by virtue of bioinformatic tools also exerts critical roles in revealing differential gene expression. Here, a comprehensive review that summarizes the cutting-edge single-cell transcriptome sequencing methodologies, including scRNA-seq, spatial and temporal transcriptome profiling, multi-omics sequencing and computational methods developed for scRNA-seq data analysis is provided. Finally, the challenges and perspectives of this field are discussed.
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Affiliation(s)
- Yingwen Chen
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, The Key Laboratory of Chemical Biology of Fujian Province, State Key Laboratory of Physical Chemistry of Solid Surfaces, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China
| | - Jia Song
- Institute of Molecular Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China
| | - Qingyu Ruan
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, The Key Laboratory of Chemical Biology of Fujian Province, State Key Laboratory of Physical Chemistry of Solid Surfaces, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China
| | - Xi Zeng
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, The Key Laboratory of Chemical Biology of Fujian Province, State Key Laboratory of Physical Chemistry of Solid Surfaces, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China
| | - Lingling Wu
- Institute of Molecular Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China
| | - Linfeng Cai
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, The Key Laboratory of Chemical Biology of Fujian Province, State Key Laboratory of Physical Chemistry of Solid Surfaces, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China
| | - Xuanqun Wang
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, The Key Laboratory of Chemical Biology of Fujian Province, State Key Laboratory of Physical Chemistry of Solid Surfaces, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China
| | - Chaoyong Yang
- The MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, The Key Laboratory of Chemical Biology of Fujian Province, State Key Laboratory of Physical Chemistry of Solid Surfaces, Collaborative Innovation Center of Chemistry for Energy Materials, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China
- Institute of Molecular Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China
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Schlieben LD, Prokisch H, Yépez VA. How Machine Learning and Statistical Models Advance Molecular Diagnostics of Rare Disorders Via Analysis of RNA Sequencing Data. Front Mol Biosci 2021; 8:647277. [PMID: 34141720 PMCID: PMC8204083 DOI: 10.3389/fmolb.2021.647277] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 05/10/2021] [Indexed: 12/11/2022] Open
Abstract
Rare diseases, although individually rare, collectively affect approximately 350 million people worldwide. Currently, nearly 6,000 distinct rare disorders with a known molecular basis have been described, yet establishing a specific diagnosis based on the clinical phenotype is challenging. Increasing integration of whole exome sequencing into routine diagnostics of rare diseases is improving diagnostic rates. Nevertheless, about half of the patients do not receive a genetic diagnosis due to the challenges of variant detection and interpretation. During the last years, RNA sequencing is increasingly used as a complementary diagnostic tool providing functional data. Initially, arbitrary thresholds have been applied to call aberrant expression, aberrant splicing, and mono-allelic expression. With the application of RNA sequencing to search for the molecular diagnosis, the implementation of robust statistical models on normalized read counts allowed for the detection of significant outliers corrected for multiple testing. More recently, machine learning methods have been developed to improve the normalization of RNA sequencing read count data by taking confounders into account. Together the methods have increased the power and sensitivity of detection and interpretation of pathogenic variants, leading to diagnostic rates of 10-35% in rare diseases. In this review, we provide an overview of the methods used for RNA sequencing and illustrate how these can improve the diagnostic yield of rare diseases.
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Affiliation(s)
- Lea D. Schlieben
- School of Medicine, Institute of Human Genetics, Technical University of Munich, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Holger Prokisch
- School of Medicine, Institute of Human Genetics, Technical University of Munich, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Vicente A. Yépez
- School of Medicine, Institute of Human Genetics, Technical University of Munich, Munich, Germany
- Department of Informatics, Technical University of Munich, Munich, Germany
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Ramesh P, Shivde R, Jaishankar D, Saleiro D, Le Poole IC. A Palette of Cytokines to Measure Anti-Tumor Efficacy of T Cell-Based Therapeutics. Cancers (Basel) 2021; 13:821. [PMID: 33669271 PMCID: PMC7920025 DOI: 10.3390/cancers13040821] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 02/08/2021] [Accepted: 02/10/2021] [Indexed: 12/12/2022] Open
Abstract
Cytokines are key molecules within the tumor microenvironment (TME) that can be used as biomarkers to predict the magnitude of anti-tumor immune responses. During immune monitoring, it has been customary to predict outcomes based on the abundance of a single cytokine, in particular IFN-γ or TGF-β, as a readout of ongoing anti-cancer immunity. However, individual cytokines within the TME can exhibit dual opposing roles. For example, both IFN-γ and TGF-β have been associated with pro- and anti-tumor functions. Moreover, cytokines originating from different cellular sources influence the crosstalk between CD4+ and CD8+ T cells, while the array of cytokines expressed by T cells is also instrumental in defining the mechanisms of action and efficacy of treatments. Thus, it becomes increasingly clear that a reliable readout of ongoing immunity within the TME will have to include more than the measurement of a single cytokine. This review focuses on defining a panel of cytokines that could help to reliably predict and analyze the outcomes of T cell-based anti-tumor therapies.
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Affiliation(s)
- Prathyaya Ramesh
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL 60611, USA; (P.R.); (R.S.); (D.J.); (D.S.)
- Department of Dermatology, Northwestern University, Chicago, IL 60611, USA
| | - Rohan Shivde
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL 60611, USA; (P.R.); (R.S.); (D.J.); (D.S.)
- Department of Dermatology, Northwestern University, Chicago, IL 60611, USA
| | - Dinesh Jaishankar
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL 60611, USA; (P.R.); (R.S.); (D.J.); (D.S.)
- Department of Dermatology, Northwestern University, Chicago, IL 60611, USA
| | - Diana Saleiro
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL 60611, USA; (P.R.); (R.S.); (D.J.); (D.S.)
- Division of Hematology-Oncology, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - I. Caroline Le Poole
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL 60611, USA; (P.R.); (R.S.); (D.J.); (D.S.)
- Department of Dermatology, Northwestern University, Chicago, IL 60611, USA
- Department of Microbiology and Immunology, Northwestern University at Chicago, Chicago, IL 60611, USA
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Altered visual processing in the mdx52 mouse model of Duchenne muscular dystrophy. Neurobiol Dis 2021; 152:105288. [PMID: 33556541 DOI: 10.1016/j.nbd.2021.105288] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 01/26/2021] [Accepted: 02/03/2021] [Indexed: 02/06/2023] Open
Abstract
The mdx52 mouse model of Duchenne muscular dystrophy (DMD) is lacking exon 52 of the DMD gene that is located in a hotspot mutation region causing cognitive deficits and retinal anomalies in DMD patients. This deletion leads to the loss of the dystrophin proteins, Dp427, Dp260 and Dp140, while Dp71 is preserved. The flash electroretinogram (ERG) in mdx52 mice was previously characterized by delayed dark-adapted b-waves. A detailed description of functional ERG changes and visual performances in mdx52 mice is, however, lacking. Here an extensive full-field ERG repertoire was applied in mdx52 mice and WT littermates to analyze retinal physiology in scotopic, mesopic and photopic conditions in response to flash, sawtooth and/or sinusoidal stimuli. Behavioral contrast sensitivity was assessed using quantitative optomotor response (OMR) to sinusoidally modulated luminance gratings at 100% or 50% contrast. The mdx52 mice exhibited reduced amplitudes and delayed implicit times in dark-adapted ERG flash responses, particularly in their b-wave and oscillatory potentials, and diminished amplitudes of light-adapted flash ERGs. ERG responses to sawtooth stimuli were also diminished and delayed for both mesopic and photopic conditions in mdx52 mice and the first harmonic amplitudes to photopic sine-wave stimuli were smaller at all temporal frequencies. OMR indices were comparable between genotypes at 100% contrast but significantly reduced in mdx52 mice at 50% contrast. The complex ERG alterations and disturbed contrast vision in mdx52 mice include features observed in DMD patients and suggest altered photoreceptor-to-bipolar cell transmission possibly affecting contrast sensitivity. The mdx52 mouse is a relevant model to appraise the roles of retinal dystrophins and for preclinical studies related to DMD.
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Hayrabedyan S, Kostova P, Zlatkov V, Todorova K. Single-cell transcriptomics in the context of long-read nanopore sequencing. BIOTECHNOL BIOTEC EQ 2021. [DOI: 10.1080/13102818.2021.1988868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
Affiliation(s)
- Soren Hayrabedyan
- Laboratory of Reproductive OMICs Technologies, Institute of Biology and Immunology of Reproduction, Bulgarian Academy of Sciences, Sofia, Bulgaria
| | - Petya Kostova
- Gynecology Clinic, National Oncology Hospital, Sofia, Bulgaria
| | - Viktor Zlatkov
- Department of Obstetrics and Gynecology, Faculty of Medicine, Medical University of Sofia, Sofia, Bulgaria
| | - Krassimira Todorova
- Laboratory of Reproductive OMICs Technologies, Institute of Biology and Immunology of Reproduction, Bulgarian Academy of Sciences, Sofia, Bulgaria
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40
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Estermann MA, Smith CA. Applying Single-Cell Analysis to Gonadogenesis and DSDs (Disorders/Differences of Sex Development). Int J Mol Sci 2020; 21:E6614. [PMID: 32927658 PMCID: PMC7555471 DOI: 10.3390/ijms21186614] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 09/07/2020] [Accepted: 09/08/2020] [Indexed: 12/20/2022] Open
Abstract
The gonads are unique among the body's organs in having a developmental choice: testis or ovary formation. Gonadal sex differentiation involves common progenitor cells that form either Sertoli and Leydig cells in the testis or granulosa and thecal cells in the ovary. Single-cell analysis is now shedding new light on how these cell lineages are specified and how they interact with the germline. Such studies are also providing new information on gonadal maturation, ageing and the somatic-germ cell niche. Furthermore, they have the potential to improve our understanding and diagnosis of Disorders/Differences of Sex Development (DSDs). DSDs occur when chromosomal, gonadal or anatomical sex are atypical. Despite major advances in recent years, most cases of DSD still cannot be explained at the molecular level. This presents a major pediatric concern. The emergence of single-cell genomics and transcriptomics now presents a novel avenue for DSD analysis, for both diagnosis and for understanding the molecular genetic etiology. Such -omics datasets have the potential to enhance our understanding of the cellular origins and pathogenesis of DSDs, as well as infertility and gonadal diseases such as cancer.
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Affiliation(s)
| | - Craig A. Smith
- Department of Anatomy and Developmental Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton 3800, Victoria, Australia;
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Abstract
Cells are known to be the most fundamental building block of life[...].
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Affiliation(s)
- Tuhin Subhra Santra
- Department of Engineering Design, Indian Institute of Technology Madras, Tamil Nadu 600036, India
| | - Fan-Gang Tseng
- Department of Engineering and System Science, National Tsing Hua University, Hsinchu 30013, Taiwan;
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Abstract
The immune system is composed of heterogeneous populations of immune cells that regulate physiological processes and protect organisms against diseases. Single cell technologies have been used to assess immune cell responses at the single cell level, which are crucial for identifying the causes of diseases and elucidating underlying biological mechanisms to facilitate medical therapy. In the present review we first discuss the most recent advances in the development of single cell technologies to investigate cell signaling, cell-cell interactions and cell migration. Each technology's advantages and limitations and its applications in immunology are subsequently reviewed. The latest progress toward commercialization, the remaining challenges and future perspectives for single cell technologies in immunology are also briefly discussed.
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Affiliation(s)
- Jane Ru Choi
- Centre for Blood Research, Life Sciences Centre, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada.,Department of Mechanical Engineering, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
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Gupta RK, Kuznicki J. Biological and Medical Importance of Cellular Heterogeneity Deciphered by Single-Cell RNA Sequencing. Cells 2020; 9:E1751. [PMID: 32707839 PMCID: PMC7463515 DOI: 10.3390/cells9081751] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 07/15/2020] [Accepted: 07/20/2020] [Indexed: 01/01/2023] Open
Abstract
The present review discusses recent progress in single-cell RNA sequencing (scRNA-seq), which can describe cellular heterogeneity in various organs, bodily fluids, and pathologies (e.g., cancer and Alzheimer's disease). We outline scRNA-seq techniques that are suitable for investigating cellular heterogeneity that is present in cell populations with very high resolution of the transcriptomic landscape. We summarize scRNA-seq findings and applications of this technology to identify cell types, activity, and other features that are important for the function of different bodily organs. We discuss future directions for scRNA-seq techniques that can link gene expression, protein expression, cellular function, and their roles in pathology. We speculate on how the field could develop beyond its present limitations (e.g., performing scRNA-seq in situ and in vivo). Finally, we discuss the integration of machine learning and artificial intelligence with cutting-edge scRNA-seq technology, which could provide a strong basis for designing precision medicine and targeted therapy in the future.
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Affiliation(s)
- Rishikesh Kumar Gupta
- International Institute of Molecular and Cell Biology in Warsaw, Trojdena 4, 02-109 Warsaw Poland;
- Postgraduate School of Molecular Medicine, Warsaw Medical University, 61 Żwirki i Wigury St., 02-091 Warsaw, Poland
| | - Jacek Kuznicki
- International Institute of Molecular and Cell Biology in Warsaw, Trojdena 4, 02-109 Warsaw Poland;
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Ding S, Chen X, Shen K. Single-cell RNA sequencing in breast cancer: Understanding tumor heterogeneity and paving roads to individualized therapy. Cancer Commun (Lond) 2020; 40:329-344. [PMID: 32654419 PMCID: PMC7427308 DOI: 10.1002/cac2.12078] [Citation(s) in RCA: 102] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Revised: 06/27/2020] [Accepted: 06/29/2020] [Indexed: 12/18/2022] Open
Abstract
Single‐cell RNA sequencing (scRNA‐seq) is a novel technology that allows transcriptomic analyses of individual cells. During the past decade, scRNA‐seq sensitivity, accuracy, and efficiency have improved due to innovations including more sensitive, automated, and cost‐effective single‐cell isolation methods with higher throughput as well as ongoing technological development of scRNA‐seq protocols. Among the variety of current approaches with distinct features, researchers can choose the most suitable method to carry out their research. By profiling single cells in a complex population mix, scRNA‐seq presents great advantages over traditional sequencing methods in dissecting heterogeneity in cell populations hidden in bulk analysis and exploring rare cell types associated with tumorigenesis and metastasis. scRNA‐seq studies in recent years in the field of breast cancer research have clustered breast cancer cell populations with different molecular subtypes to identify distinct populations that may correlate with poor prognosis and drug resistance. The technology has also been used to explain tumor microenvironment heterogeneity by identifying distinct immune cell subsets that may be associated with immunosurveillance and are potential immunotherapy targets. Moreover, scRNA‐seq has diverse applications in breast cancer research besides exploring heterogeneity, including the analysis of cell‐cell communications, regulatory single‐cell states, immune cell distributions, and more. scRNA‐seq is also a promising tool that can facilitate individualized therapy due to its ability to define cell subsets with potential treatment targets. Although scRNA‐seq studies of therapeutic selection in breast cancer are currently limited, the application of this technology in this field is prospective. Joint efforts and original ideas are needed to better implement scRNA‐seq technologies in breast cancer research to pave the way for individualized treatment management. This review provides a brief introduction on the currently available scRNA‐seq approaches along with their corresponding strengths and weaknesses and may act as a reference for the selection of suitable methods for research. We also discuss the current applications of scRNA‐seq in breast cancer research for tumor heterogeneity analysis, individualized therapy, and the other research directions mentioned above by reviewing corresponding published studies. Finally, we discuss the limitations of current scRNA‐seq technologies and technical problems that remain to be overcome.
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Affiliation(s)
- Shuning Ding
- Department of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, P. R. China
| | - Xiaosong Chen
- Department of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, P. R. China
| | - Kunwei Shen
- Department of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, P. R. China
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