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Diamantopoulos MA, Adamopoulos PG, Tsiakanikas P, Nisotakis T, Skourou PC, Scorilas A. Unraveling novel mRNA transcripts of the human DNA N-glycosylase 1 (NTHL1) gene with the implementation of an innovative targeted DNA-seq assay. Gene 2024; 930:148856. [PMID: 39147115 DOI: 10.1016/j.gene.2024.148856] [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: 02/15/2024] [Revised: 07/13/2024] [Accepted: 08/12/2024] [Indexed: 08/17/2024]
Abstract
The human NTHL1 gene encodes a DNA glycosylase that plays a key role in the base excision repair (BER) pathway, repairing oxidative DNA damage and maintaining genome integrity. The physiological activity of NTHL1 is crucial in preventing genetic alterations that can lead to cancer. In this study, we employed an innovative targeted DNA sequencing (DNA-seq) methodology to explore the transcriptional landscape of the NTHL1 gene, revealing previously uncharacterized alternative splicing events and novel exons. Our designed approach provided significantly improved sequencing depth and coverage, enabling the identification of novel NTHL1 mRNA transcripts. Bioinformatics analysis confirmed all annotated splice junctions of the main NTHL1 transcripts (v.1 - v.3) and revealed novel mRNA transcripts (NTHL1 v.4 - v.9) derived from splicing events between annotated exons as well as mRNAs containing previously uncharacterized exons (NTHL1 v.10 - v.14). Quantitative PCR analysis highlighted a diverse expression pattern of these novel transcripts across different human cell lines, suggesting cell-specific roles and regulatory mechanisms. Notably, NTHL1 v.5 was overexpressed in luminal A breast cancer cells (MCF-7), while v.13 was prominent in triple negative (BT-20), HER2 + breast cancer (SK-BR-3), prostate, colorectal cancer cells and HEK-293 cells. Our findings suggest that specific novel NTHL1 transcripts may encode protein isoforms with distinct structural features, as indicated by ribosome profiling datasets, while others containing premature termination codons could function as long non-coding RNAs. These insights enhance our understanding of NTHL1 regulatory role and its potential as a biomarker and therapeutic target in human malignancies. This study underscores the importance of exploring the transcriptional diversity of NTHL1 to fully elucidate its role in cancer pathobiology.
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Affiliation(s)
- Marios A Diamantopoulos
- Department of Biochemistry and Molecular Biology, National and Kapodistrian University of Athens, Athens, Greece
| | - Panagiotis G Adamopoulos
- Department of Biochemistry and Molecular Biology, National and Kapodistrian University of Athens, Athens, Greece
| | - Panagiotis Tsiakanikas
- Department of Biochemistry and Molecular Biology, National and Kapodistrian University of Athens, Athens, Greece
| | - Theodoros Nisotakis
- Department of Biochemistry and Molecular Biology, National and Kapodistrian University of Athens, Athens, Greece
| | - Paraskevi C Skourou
- Department of Biochemistry and Molecular Biology, National and Kapodistrian University of Athens, Athens, Greece
| | - Andreas Scorilas
- Department of Biochemistry and Molecular Biology, National and Kapodistrian University of Athens, Athens, Greece.
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2
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Wang C, Huyan T, Guo W, Shu Q, Li Q, Shi J. NTCdb: Single-cell transcriptome database of human inflammatory-associated diseases. Comput Struct Biotechnol J 2024; 23:1978-1989. [PMID: 38765608 PMCID: PMC11098674 DOI: 10.1016/j.csbj.2024.04.057] [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: 01/15/2024] [Revised: 04/22/2024] [Accepted: 04/22/2024] [Indexed: 05/22/2024] Open
Abstract
With both the advancement of technology and the decline in costs, single-cell transcriptomics sequencing has become widespread in the biomedical area in recent years. It can facilitate the pathogenic characteristics at the single-cell level, which will assist clinical researchers in exploring the mechanism of diseases. As a result, single-cell transcriptome data based on clinical samples grew exponentially. However, there is still a lack of a comprehensive database about immunocytes in inflammatory-associated diseases. To address this deficiency, we propose a human inflammatory-associated disease-based single-cell transcriptome database, NTCdb (www.ntcdb.org.cn). NTCdb integrates the open-source data of 1,023,166 cells derived from 11 tissues of 17 inflammatory-associated diseases in a uniform pipeline. It provides a set of analyzing results, including cell communication analysis, enrichment analysis, and Pseudo-Time analysis, to obtain various characteristics of immune cells in inflammatory-associated disease. Taking COVID-19 as a case study, NTCdb displays important information including potentially significant functions of certain cells, genes, and signaling pathways, as well as the commonalities of specific immunocytes between different inflammatory-associated disease.
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Affiliation(s)
| | | | - Wuli Guo
- School of Life Sciences, Northwestern Polytechnical University, Xi’an 710072, China
| | - Qi Shu
- School of Life Sciences, Northwestern Polytechnical University, Xi’an 710072, China
| | | | - Jianyu Shi
- School of Life Sciences, Northwestern Polytechnical University, Xi’an 710072, China
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3
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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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4
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Shoaran M, Sabaie H, Mostafavi M, Rezazadeh M. A comprehensive review of the applications of RNA sequencing in celiac disease research. Gene 2024; 927:148681. [PMID: 38871036 DOI: 10.1016/j.gene.2024.148681] [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: 02/02/2024] [Revised: 06/06/2024] [Accepted: 06/10/2024] [Indexed: 06/15/2024]
Abstract
RNA sequencing (RNA-seq) has undergone substantial advancements in recent decades and has emerged as a vital technique for profiling the transcriptome. The transition from bulk sequencing to single-cell and spatial approaches has facilitated the achievement of higher precision at cell resolution. It provides valuable biological knowledge about individual immune cells and aids in the discovery of the molecular mechanisms that contribute to the development of autoimmune diseases. Celiac disease (CeD) is an autoimmune disorder characterized by a strong immune response to gluten consumption. RNA-seq has led to significantly advanced research in multiple fields, particularly in CeD research. It has been instrumental in studies involving comparative transcriptomics, nutritional genomics and wheat research, cancer research in the context of CeD, genetic and noncoding RNA-mediated epigenetic insights, disease monitoring and biomarker discovery, regulation of mitochondrial functions, therapeutic target identification and drug mechanism of action, dietary factors, immune cell profiling and the immune landscape. This review offers a comprehensive examination of recent RNA-seq technology research in the field of CeD, highlighting future challenges and opportunities for its application.
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Affiliation(s)
- Maryam Shoaran
- Pediatric Health Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Hani Sabaie
- Department of Medical Genetics, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Mehrnaz Mostafavi
- Faculty of Allied Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam Rezazadeh
- Department of Medical Genetics, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
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5
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Lu J, Gu X, Xue C, Shi Q, Jia J, Cheng J, Zeng Y, Chu Q, Yuan X, Bao Z, Li L. Glycyrrhizic acid alleviates concanavalin A-induced acute liver injury by regulating monocyte-derived macrophages. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2024; 133:155586. [PMID: 39159503 DOI: 10.1016/j.phymed.2024.155586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 03/21/2024] [Accepted: 04/01/2024] [Indexed: 08/21/2024]
Abstract
Autoimmune hepatitis (AIH) is characterized by persistent liver inflammation induced by aberrant immune responses. Glycyrrhizic acid (GA), a prominent bioactive ingredient of licorice, has shown potential as a safe and effective treatment for AIH. However, the immune regulatory mechanism by which GA exerts its therapeutic effect on AIH remains elusive. In this study, we found that GA intervention significantly alleviated ConA-induced acute liver injury in mice. Cytometry by time-of-flight (CyTOF) analysis revealed that GA increased the abundance of anti-inflammatory F4/80loCD11bhiMHCIIhi MoMF-1 and decreased the abundance of pro-inflammatory F4/80loCD11bhiiNOShi MoMF-3. Multiplex immunofluorescence demonstrated the infiltration of MoMFs in liver tissues. Single-cell RNA sequencing (scRNA-seq) analysis indicated that GA facilitated the immune activation in MoMFs, regulated gene expression of diverse cytokines secreted by MoMFs, and played a role in shaping the immune microenvironment. By integrating the results of CyTOF with scRNA-seq, our study comprehensively elucidates the immune landscape of ConA-induced liver injury following GA intervention, advancing the understanding of GA's mechanism of action. However, it is important to note that some single-cell data in this study remain raw and require further processing and annotation. Our findings suggest that GA alleviates ConA-induced acute liver injury by regulating the function of MoMFs, opening potential avenues for AIH treatment and management, and providing a theoretical basis for the design of novel MoMFs-centered immunotherapies.
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Affiliation(s)
- Juan Lu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
| | - Xinyu Gu
- Department of Oncology, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, Luoyang, Henan, China
| | - Chen Xue
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Qingmiao Shi
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Junjun Jia
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jinlin Cheng
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yifan Zeng
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Qingfei Chu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xin Yuan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Zhengyi Bao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Lanjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
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6
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Hockenberry MA, Daugird TA, Legant WR. Cell dynamics revealed by microscopy advances. Curr Opin Cell Biol 2024; 90:102418. [PMID: 39159598 PMCID: PMC11392612 DOI: 10.1016/j.ceb.2024.102418] [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: 05/01/2024] [Revised: 07/23/2024] [Accepted: 07/24/2024] [Indexed: 08/21/2024]
Abstract
Cell biology emerges from spatiotemporally coordinated molecular processes. Recent advances in live-cell microscopy, fueled by a surge in optical, molecular, and computational technologies, have enabled dynamic observations from single molecules to whole organisms. Despite technological leaps, there is still an untapped opportunity to fully leverage their capabilities toward biological insight. We highlight how single-molecule imaging has transformed our understanding of biological processes, with a focus on chromatin organization and transcription in the nucleus. We describe how this was enabled by the close integration of new imaging techniques with analysis tools and discuss the challenges to make a comparable impact at larger scales from organelles to organisms. By highlighting recent successful examples, we describe an outlook of ever-increasing data and the need for seamless integration between dataset visualization and quantification to realize the full potential warranted by advances in new imaging technologies.
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Affiliation(s)
- Max A Hockenberry
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, Chapel Hill, NC, USA
| | - Timothy A Daugird
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Wesley R Legant
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Joint Department of Biomedical Engineering, North Carolina State University, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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7
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Schepps S, Xu J, Yang H, Mandel J, Mehta J, Tolotta J, Baker N, Tekmen V, Nikbakht N, Fortina P, Fuentes I, LaFleur B, Cho RJ, South AP. Skin in the game: a review of single-cell and spatial transcriptomics in dermatological research. Clin Chem Lab Med 2024; 62:1880-1891. [PMID: 38656304 DOI: 10.1515/cclm-2023-1245] [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: 11/03/2023] [Accepted: 02/29/2024] [Indexed: 04/26/2024]
Abstract
Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) are two emerging research technologies that uniquely characterize gene expression microenvironments on a cellular or subcellular level. The skin, a clinically accessible tissue composed of diverse, essential cell populations, serves as an ideal target for these high-resolution investigative approaches. Using these tools, researchers are assembling a compendium of data and discoveries in healthy skin as well as a range of dermatologic pathophysiologies, including atopic dermatitis, psoriasis, and cutaneous malignancies. The ongoing advancement of single-cell approaches, coupled with anticipated decreases in cost with increased adoption, will reshape dermatologic research, profoundly influencing disease characterization, prognosis, and ultimately clinical practice.
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Affiliation(s)
- Samuel Schepps
- Department of Dermatology and Cutaneous Biology, 6559 Thomas Jefferson University , Philadelphia, PA, USA
| | - Jonathan Xu
- Department of Dermatology and Cutaneous Biology, 6559 Thomas Jefferson University , Philadelphia, PA, USA
| | - Henry Yang
- Department of Dermatology and Cutaneous Biology, 6559 Thomas Jefferson University , Philadelphia, PA, USA
| | - Jenna Mandel
- Department of Dermatology and Cutaneous Biology, 6559 Thomas Jefferson University , Philadelphia, PA, USA
| | - Jaanvi Mehta
- Department of Dermatology and Cutaneous Biology, 6559 Thomas Jefferson University , Philadelphia, PA, USA
| | - Julianna Tolotta
- Department of Dermatology and Cutaneous Biology, 6559 Thomas Jefferson University , Philadelphia, PA, USA
| | - Nicole Baker
- Department of Dermatology and Cutaneous Biology, 6559 Thomas Jefferson University , Philadelphia, PA, USA
| | - Volkan Tekmen
- Department of Dermatology and Cutaneous Biology, 6559 Thomas Jefferson University , Philadelphia, PA, USA
| | - Neda Nikbakht
- Department of Dermatology and Cutaneous Biology, 6559 Thomas Jefferson University , Philadelphia, PA, USA
- Department of Pharmacology, Physiology and Cancer Biology, 6559 Thomas Jefferson University , Philadelphia, PA, USA
| | - Paolo Fortina
- Department of Pharmacology, Physiology and Cancer Biology, 6559 Thomas Jefferson University , Philadelphia, PA, USA
- International Federation of Clinical Chemistry Working Group on Single Cell and Spatial Transcriptomics, Milan, Italy
| | - Ignacia Fuentes
- International Federation of Clinical Chemistry Working Group on Single Cell and Spatial Transcriptomics, Milan, Italy
- Departamento de Biología Celular y Molecular, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Directora de Investigación Fundación DEBRA Chile, Santiago, Chile
| | - Bonnie LaFleur
- International Federation of Clinical Chemistry Working Group on Single Cell and Spatial Transcriptomics, Milan, Italy
- R. Ken Coit College of Pharmacy, University of Arizona, University of Arizona Cancer Center, Tucson, AZ, USA
| | - Raymond J Cho
- International Federation of Clinical Chemistry Working Group on Single Cell and Spatial Transcriptomics, Milan, Italy
- Department of Dermatology, University of San Francisco, San Francisco, CA, USA
| | - Andrew P South
- Department of Pharmacology, Physiology and Cancer Biology, 6559 Thomas Jefferson University , Philadelphia, PA, USA
- International Federation of Clinical Chemistry Working Group on Single Cell and Spatial Transcriptomics, Milan, Italy
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8
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Ellman DG, Bjerre FA, Bak ST, Mathiesen SB, Harvald EB, Jensen CH, Andersen DC. Protocol to achieve high-resolution single-cell transcriptomics of cardiomyocytes in multiple species. STAR Protoc 2024; 5:103194. [PMID: 39096494 PMCID: PMC11345562 DOI: 10.1016/j.xpro.2024.103194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Revised: 05/17/2024] [Accepted: 06/21/2024] [Indexed: 08/05/2024] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) remains state-of-the-art for transcriptomic cell-mapping. Here, we provide a protocol to generate high-resolution scRNA-seq of rare cardiomyocyte populations (e.g., regenerating/dividing, etc.) from mouse and zebrafish hearts as well as induced pluripotent stem cells, collected in time to achieve detailed transcriptomic insight. We describe the serial steps of viability staining, methanol fixation, storage, and cell sorting to preserve RNA integrity suited for scRNA-seq as well as the quality assessment of the data as shown by examples. For complete details on the use and execution of this protocol, please refer to Bak et al.1.
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Affiliation(s)
- Ditte Gry Ellman
- Andersen Group, Department of Clinical Biochemistry, Odense University Hospital, 5000 Odense C, Denmark; Clinical Institute, University of Southern Denmark, 5230 Odense M, Denmark.
| | - Frederik Adam Bjerre
- Andersen Group, Department of Clinical Biochemistry, Odense University Hospital, 5000 Odense C, Denmark; Clinical Institute, University of Southern Denmark, 5230 Odense M, Denmark; Amplexa Genetics, 5000 Odense C, Denmark
| | - Sara Thornby Bak
- Andersen Group, Department of Clinical Biochemistry, Odense University Hospital, 5000 Odense C, Denmark; Clinical Institute, University of Southern Denmark, 5230 Odense M, Denmark
| | - Sabrina Bech Mathiesen
- Andersen Group, Department of Clinical Biochemistry, Odense University Hospital, 5000 Odense C, Denmark; Clinical Institute, University of Southern Denmark, 5230 Odense M, Denmark
| | - Eva Bang Harvald
- Andersen Group, Department of Clinical Biochemistry, Odense University Hospital, 5000 Odense C, Denmark; Clinical Institute, University of Southern Denmark, 5230 Odense M, Denmark
| | - Charlotte Harken Jensen
- Andersen Group, Department of Clinical Biochemistry, Odense University Hospital, 5000 Odense C, Denmark; Clinical Institute, University of Southern Denmark, 5230 Odense M, Denmark
| | - Ditte Caroline Andersen
- Andersen Group, Department of Clinical Biochemistry, Odense University Hospital, 5000 Odense C, Denmark; Clinical Institute, University of Southern Denmark, 5230 Odense M, Denmark.
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9
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Xiong X, Wang X, Liu CC, Shao ZM, Yu KD. Deciphering breast cancer dynamics: insights from single-cell and spatial profiling in the multi-omics era. Biomark Res 2024; 12:107. [PMID: 39294728 PMCID: PMC11411917 DOI: 10.1186/s40364-024-00654-1] [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: 06/28/2024] [Accepted: 09/10/2024] [Indexed: 09/21/2024] Open
Abstract
As one of the most common tumors in women, the pathogenesis and tumor heterogeneity of breast cancer have long been the focal point of research, with the emergence of tumor metastasis and drug resistance posing persistent clinical challenges. The emergence of single-cell sequencing (SCS) technology has introduced novel approaches for gaining comprehensive insights into the biological behavior of malignant tumors. SCS is a high-throughput technology that has rapidly developed in the past decade, providing high-throughput molecular insights at the individual cell level. Furthermore, the advent of multitemporal point sampling and spatial omics also greatly enhances our understanding of cellular dynamics at both temporal and spatial levels. The paper provides a comprehensive overview of the historical development of SCS, and highlights the most recent advancements in utilizing SCS and spatial omics for breast cancer research. The findings from these studies will serve as valuable references for future advancements in basic research, clinical diagnosis, and treatment of breast cancer.
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Affiliation(s)
- Xin Xiong
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Cancer Institute, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Xin Wang
- Department of Anesthesiology, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Cui-Cui Liu
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Cancer Institute, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Zhi-Ming Shao
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Cancer Institute, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Ke-Da Yu
- Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Cancer Institute, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
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10
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Wang Y, Peng Y, Yang C, Xiong D, Wang Z, Peng H, Wu X, Xiao X, Liu J. Single-cell sequencing analysis of multiple myeloma heterogeneity and identification of new theranostic targets. Cell Death Dis 2024; 15:672. [PMID: 39271659 PMCID: PMC11399131 DOI: 10.1038/s41419-024-07027-4] [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: 04/15/2024] [Revised: 08/16/2024] [Accepted: 08/22/2024] [Indexed: 09/15/2024]
Abstract
Multiple myeloma (MM) is a heterogeneous and incurable tumor characterized by the malignant proliferation of plasma cells. It is necessary to clarify the heterogeneity of MM and identify new theranostic targets. We constructed a single-cell transcriptome profile of 48,293 bone marrow cells from MM patients and health donors (HDs) annotated with 7 continuous B lymphocyte lineages. Through CellChat, we discovered that the communication among B lymphocyte lineages between MM and HDs was disrupted, and unique signaling molecules were observed. Through pseudotime analysis, it was found that the differences between MM and HDs were mainly reflected in plasma cells. These differences are primarily related to various biological processes involving mitochondria. Then, we identified the key subpopulation associated with the malignant proliferation of plasma cells. This group of cells exhibited strong proliferation ability, high CNV scores, high expression of frequently mutated genes, and strong glucose metabolic activity. Furthermore, we demonstrated the therapeutic potential of WNK1 as a target. Our study provides new insights into the development of B cells and the heterogeneity of plasma cells in MM and suggests that WNK1 is a potential therapeutic target for MM.
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Affiliation(s)
- Yanpeng Wang
- Department of Hematology, the Second Xiangya Hospital, School of Life Sciences, Central South University, Changsha, 410011, China
- Hunan Province Key Laboratory of Basic and Applied Hematology, Central South University, Changsha, 410011, China
- Department of Clinical Laboratory, the Affiliated Nanhua Hospital, University of South China, Hengyang, 421001, China
| | - Yuanliang Peng
- Department of Hematology, the Second Xiangya Hospital, School of Life Sciences, Central South University, Changsha, 410011, China
- Hunan Province Key Laboratory of Basic and Applied Hematology, Central South University, Changsha, 410011, China
| | - Chaoying Yang
- Hunan Province Key Laboratory of Basic and Applied Hematology, Central South University, Changsha, 410011, China
| | - Dehui Xiong
- Hunan Province Key Laboratory of Basic and Applied Hematology, Central South University, Changsha, 410011, China
| | - Zeyuan Wang
- Hunan Province Key Laboratory of Basic and Applied Hematology, Central South University, Changsha, 410011, China
| | - Hongling Peng
- Department of Hematology, the Second Xiangya Hospital, School of Life Sciences, Central South University, Changsha, 410011, China.
| | - Xusheng Wu
- Shenzhen Health Development Research and Data Management Center, Shenzhen, 518028, China.
| | - Xiaojuan Xiao
- Hunan Province Key Laboratory of Basic and Applied Hematology, Central South University, Changsha, 410011, China.
| | - Jing Liu
- Department of Hematology, the Second Xiangya Hospital, School of Life Sciences, Central South University, Changsha, 410011, China.
- Hunan Province Key Laboratory of Basic and Applied Hematology, Central South University, Changsha, 410011, China.
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11
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Harding AT, Crossen AJ, Reedy JL, Basham KJ, Hepworth OW, Zhang Y, Shah VS, Harding HB, Surve MV, Simaku P, Kwaku GN, Jensen KN, Otto Y, Ward RA, Thompson GR, Klein BS, Rajagopal J, Sen P, Haber AL, Vyas JM. Single-cell analysis of human airway epithelium identifies cell type-specific responses to Aspergillus and Coccidioides. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.09.612147. [PMID: 39314271 PMCID: PMC11418999 DOI: 10.1101/2024.09.09.612147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Respiratory fungal infections pose a significant threat to human health. Animal models do not fully recapitulate human disease, necessitating advanced models to study human-fungal pathogen interactions. In this study, we utilized primary human airway epithelial cells (hAECs) to recapitulate the lung environment in vitro and investigate cellular responses to two diverse, clinically significant fungal pathogens, Aspergillus fumigatus and Coccidioides posadasii . To understand the mechanisms of early pathogenesis for both fungi, we performed single-cell RNA sequencing of infected hAECs. Analysis revealed that both fungi induced cellular stress and cytokine production. However, the cell subtypes affected and specific pathways differed between fungi, with A. fumigatus and C. posadasii triggering protein-folding-related stress in ciliated cells and hypoxia responses in secretory cells, respectively. This study represents one of the first reports of single-cell transcriptional analysis of hAECs infected with either A. fumigatus or C. posadasii , providing a vital dataset to dissect the mechanism of disease and potentially identify targetable pathways. Importance Fungal infections in the lungs are dreaded complications for those with compromised immune systems and have limited treatment strategies available. These options are restricted further by the increased prevalence of treatment-resistant fungi. Many studies focus on how our immune systems respond to these pathogens, yet airway epithelial cells remain an understudied component of fungal infections in the lungs. Here, the authors provide a transcriptional analysis of primary human airway epithelial cells stimulated by two distinct fungal pathogens, Aspergillus fumigatus and Coccidioides posadasii . These data will enable further mechanistic studies of the contribution of the airway epithelium to initial host responses and represent a powerful new resource for investigators.
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Sharma S, Goel S, Goyal T, Pilania RK, Aggarwal R, Kaur T, Dhaliwal M, Rawat A, Singh S. Single-cell RNA sequencing: an emerging tool revealing dysregulated innate and adaptive immune response at single cell level in Kawasaki disease. Expert Rev Clin Immunol 2024:1-10. [PMID: 39230194 DOI: 10.1080/1744666x.2024.2401105] [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: 02/09/2024] [Revised: 08/07/2024] [Accepted: 09/02/2024] [Indexed: 09/05/2024]
Abstract
INTRODUCTION Kawasaki disease [KD] is a systemic disorder characterized by acute febrile illness due to widespread medium-vessel vasculitis, mainly affecting children. Despite the ongoing advanced research into the disease pathophysiology and molecular mechanisms, the exact etiopathogenesis of KD is still an enigma. Recently, single-cell RNA sequencing [scRNA-seq], has been utilized to elucidate the pathophysiology of KD at a resolution higher than that of previous methods. AREA COVERED In the present article, we re-emphasize the pivotal role of this high-resolution technique, scRNA-seq, in the characterization of immune cell transcriptomic profile and signaling/response pathways in KD and explore the diagnostic, prognostic, and therapeutic potential of this new technique in KD. Using combinations of the search phrases 'KD, scRNA-seq, CAA, childhood vasculitis' a literature search was carried out on Scopus, Google Scholar, and PubMed until the beginning of 2024. EXPERT OPINION scRNA-seq presents a transformative tool for dissecting KD at the cellular level. By revealing rare cell populations, gene expression alterations, and disease-specific pathways, scRNA-seq aids in understanding the intricacies of KD pathogenesis. This review will provide new insights into pathogenesis of KD and the field of applications of scRNA-seq in personalized therapeutics for KD in the future.
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Affiliation(s)
- Saniya Sharma
- Department of Pediatrics, Allergy Immunology Unit, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Sumit Goel
- Department of Pediatrics, Allergy Immunology Unit, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Taru Goyal
- Department of Pediatrics, Allergy Immunology Unit, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Rakesh Kumar Pilania
- Department of Pediatrics, Allergy Immunology Unit, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Ridhima Aggarwal
- Department of Pediatrics, Allergy Immunology Unit, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Taranpreet Kaur
- Department of Pediatrics, Allergy Immunology Unit, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Manpreet Dhaliwal
- Department of Pediatrics, Allergy Immunology Unit, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Amit Rawat
- Department of Pediatrics, Allergy Immunology Unit, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Surjit Singh
- Department of Pediatrics, Allergy Immunology Unit, Postgraduate Institute of Medical Education and Research, Chandigarh, India
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13
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Janda M. Methods in plant science. JOURNAL OF EXPERIMENTAL BOTANY 2024; 75:5163-5168. [PMID: 39259818 DOI: 10.1093/jxb/erae328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2024] [Accepted: 07/25/2024] [Indexed: 09/13/2024]
Affiliation(s)
- Martin Janda
- Faculty of Science, University of South Bohemia in České Budějovice, Branišovská 1760, České Budějovice 37005, Czech Republic
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14
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Shang Y, Wang Z, Xi L, Wang Y, Liu M, Feng Y, Wang J, Wu Q, Xiang X, Chen M, Ding Y. Droplet-based single-cell sequencing: Strategies and applications. Biotechnol Adv 2024; 77:108454. [PMID: 39271031 DOI: 10.1016/j.biotechadv.2024.108454] [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: 04/19/2024] [Revised: 08/22/2024] [Accepted: 09/10/2024] [Indexed: 09/15/2024]
Abstract
Notable advancements in single-cell omics technologies have not only addressed longstanding challenges but also enabled unprecedented studies of cellular heterogeneity with unprecedented resolution and scale. These strides have led to groundbreaking insights into complex biological systems, paving the way for a more profound comprehension of human biology and diseases. The droplet microfluidic technology has become a crucial component in many single-cell sequencing workflows in terms of throughput, cost-effectiveness, and automation. Utilizing a microfluidic chip to encapsulate and profile individual cells within droplets has significantly improved single-cell research. Therefore, this review aims to comprehensively elaborate the droplet microfluidics-assisted omics methods from a single-cell perspective. The strategies for using droplet microfluidics in the realms of genomics, epigenomics, transcriptomics, and proteomics analyses are first introduced. On this basis, the focus then turns to the latest applications of this technology in different sequencing patterns, including mono- and multi-omics. Finally, the challenges and further perspectives of droplet-based single-cell sequencing in both foundational research and commercial applications are discussed.
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Affiliation(s)
- Yuting Shang
- Department of Food Science & Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Zhengzheng Wang
- Department of Food Science & Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Liqing Xi
- Department of Food Science & Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Yantao Wang
- Department of Food Science & Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Meijing Liu
- Department of Food Science & Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Ying Feng
- Department of Food Science & Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Juan Wang
- College of Food Science, South China Agricultural University, Guangzhou 510432, China
| | - Qingping Wu
- National Health Commission Science and Technology Innovation Platform for Nutrition and Safety of Microbial Food, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China
| | - Xinran Xiang
- Jiangsu Key Laboratory of Huaiyang Food Safety and Nutrition Function Evaluation, Jiangsu Collaborative Innovation Center of Regional Modern Agriculture & Environmental Protection, Jiangsu Key Laboratory for Eco-Agricultural Biotechnology Around Hongze Lake, School of Life Science, Huaiyin Normal University, Huai'an 223300, China; Fujian Key Laboratory of Aptamers Technology, Fuzhou General Clinical Medical School (the 900th Hospital), Fujian Medical University, Fuzhou 350001, China.
| | - Moutong Chen
- National Health Commission Science and Technology Innovation Platform for Nutrition and Safety of Microbial Food, Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, China.
| | - Yu Ding
- Department of Food Science & Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
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15
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Rima L, Berchtold C, Arnold S, Fränkl A, Sütterlin R, Dernick G, Schlotterbeck G, Braun T. Single and few cell analysis for correlative light microscopy, metabolomics, and targeted proteomics. LAB ON A CHIP 2024; 24:4321-4332. [PMID: 39132885 PMCID: PMC11318241 DOI: 10.1039/d4lc00269e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Accepted: 07/23/2024] [Indexed: 08/13/2024]
Abstract
The interactions of proteins, membranes, nucleic acid, and metabolites shape a cell's phenotype. These interactions are stochastic, and each cell develops differently, making it difficult to synchronize cell populations. Consequently, studying biological processes at the single- or few-cell level is often necessary to avoid signal dilution below the detection limit or averaging over many cells. We have developed a method to study metabolites and proteins from a small number of or even a single adherent eukaryotic cell. Initially, cells are lysed by short electroporation and aspirated with a microcapillary under a fluorescent microscope. The lysate is placed on a carrier slide for further analysis using liquid-chromatography mass spectrometry (LC-MS) and/or reverse-phase protein (RPPA) approach. This method allows for a correlative measurement of (i) cellular structures and metabolites and (ii) cellular structures and proteins on the single-cell level. The correlative measurement of cellular structure by light-microscopy, metabolites by LC-MS, and targeted protein detection by RPPA was possible on the few-cell level. We discuss the method, potential applications, limitations, and future improvements.
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Affiliation(s)
- Luca Rima
- Biozentrum, University of Basel, Spitalstrasse 41, Basel, Switzerland
| | - Christian Berchtold
- Hochschule für Life Sciences, FHNW Fachhochschule Nordwestschweiz, Switzerland
| | - Stefan Arnold
- Biozentrum, University of Basel, Spitalstrasse 41, Basel, Switzerland
| | - Andri Fränkl
- Biozentrum, University of Basel, Spitalstrasse 41, Basel, Switzerland
| | | | | | - Götz Schlotterbeck
- Hochschule für Life Sciences, FHNW Fachhochschule Nordwestschweiz, Switzerland
| | - Thomas Braun
- Biozentrum, University of Basel, Spitalstrasse 41, Basel, Switzerland
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16
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Yao Z, Li B, Lu Y, Yau ST. Single-cell analysis via manifold fitting: A framework for RNA clustering and beyond. Proc Natl Acad Sci U S A 2024; 121:e2400002121. [PMID: 39226348 PMCID: PMC11406302 DOI: 10.1073/pnas.2400002121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 07/19/2024] [Indexed: 09/05/2024] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) data, susceptible to noise arising from biological variability and technical errors, can distort gene expression analysis and impact cell similarity assessments, particularly in heterogeneous populations. Current methods, including deep learning approaches, often struggle to accurately characterize cell relationships due to this inherent noise. To address these challenges, we introduce scAMF (Single-cell Analysis via Manifold Fitting), a framework designed to enhance clustering accuracy and data visualization in scRNA-seq studies. At the heart of scAMF lies the manifold fitting module, which effectively denoises scRNA-seq data by unfolding their distribution in the ambient space. This unfolding aligns the gene expression vector of each cell more closely with its underlying structure, bringing it spatially closer to other cells of the same cell type. To comprehensively assess the impact of scAMF, we compile a collection of 25 publicly available scRNA-seq datasets spanning various sequencing platforms, species, and organ types, forming an extensive RNA data bank. In our comparative studies, benchmarking scAMF against existing scRNA-seq analysis algorithms in this data bank, we consistently observe that scAMF outperforms in terms of clustering efficiency and data visualization clarity. Further experimental analysis reveals that this enhanced performance stems from scAMF's ability to improve the spatial distribution of the data and capture class-consistent neighborhoods. These findings underscore the promising application potential of manifold fitting as a tool in scRNA-seq analysis, signaling a significant enhancement in the precision and reliability of data interpretation in this critical field of study.
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Affiliation(s)
- Zhigang Yao
- Department of Statistics and Data Science, National University of Singapore, Singapore 117546, Republic of Singapore
| | - Bingjie Li
- Department of Statistics and Data Science, National University of Singapore, Singapore 117546, Republic of Singapore
| | - Yukun Lu
- Department of Statistics and Data Science, National University of Singapore, Singapore 117546, Republic of Singapore
| | - Shing-Tung Yau
- Yau Mathematical Sciences Center, Jingzhai, Tsinghua University, Beijing 100084, China
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17
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Yao ZL, Wang X, Hu CL, Chen FX, Chen HJ, Jiang SJ, Zhao Y, Ji XS. A single-nucleus transcriptomic atlas characterizes cell types and their molecular features in the ovary of adult Nile tilapia. JOURNAL OF FISH BIOLOGY 2024. [PMID: 39235098 DOI: 10.1111/jfb.15911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 07/11/2024] [Accepted: 08/06/2024] [Indexed: 09/06/2024]
Abstract
In fish species, there is limited analysis of signature transcriptome profiles at the single-cell level in gonadal cells. Here, the molecular signatures of distinct ovarian cell categories in adult Nile tilapia (Oreochromis niloticus) were analysed using single-nucleus RNA sequencing (snRNA-seq). We identified four cell types (oogonia, oocytes, granulosa cell, and thecal cell) based on their specifically expressed genes and biological functions. Similarly, we found some key pathways involved in ovarian development that may affect germline-somatic interactions. A cell-to-cell communication network between the distinct cell types was constructed. We found that the bidirectional communication is mandatory for the development of germ cells and somatic cells in fish ovaries, and the granulosa cells and thecal cells play a central regulating role in the cell network in fish ovary. Additionally, we identified some novel candidate marker genes for various types of ovarian cells and also validated them using in situ hybridization. Our work reveals an ovarian atlas at the cellular and molecular levels and contributes to providing insights into oogenesis and gonad development in fish.
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Affiliation(s)
- Zhi Lei Yao
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, China
- Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Shandong Agricultural University, Tai'an, China
| | - Xiao Wang
- Library, Shandong Agricultural University, Tai'an, China
| | - Chun Lei Hu
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, China
- Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Shandong Agricultural University, Tai'an, China
| | - Fu Xiao Chen
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, China
- Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Shandong Agricultural University, Tai'an, China
| | - Hong Ju Chen
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, China
- Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Shandong Agricultural University, Tai'an, China
| | - Shi-Jin Jiang
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, China
- Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Shandong Agricultural University, Tai'an, China
| | - Yan Zhao
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, China
- Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Shandong Agricultural University, Tai'an, China
| | - Xiang Shan Ji
- Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, Shandong Agricultural University, Tai'an, China
- Key Laboratory of Efficient Utilization of Non-grain Feed Resources (Co-construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Shandong Agricultural University, Tai'an, China
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18
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Cai Y. Conjugation of primary amine groups in targeted proteomics. MASS SPECTROMETRY REVIEWS 2024. [PMID: 39229771 DOI: 10.1002/mas.21906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 03/21/2024] [Accepted: 08/12/2024] [Indexed: 09/05/2024]
Abstract
Primary amines, in the form of unmodified N-terminus of peptide/protein and unmodified lysine residue, are perhaps the most important functional groups that can serve as the starting points in proteomic analysis, especially via mass spectrometry-based approaches. A variety of multifunctional probes that conjugate primary amine groups through covalent bonds have been developed and employed to facilitate protein/protein complex characterization, including identification, quantification, structure and localization elucidation, protein-protein interaction investigation, and so forth. As an integral part of more accurate peptide quantification in targeted proteomics, isobaric stable isotope-coded primary amine labeling approaches eventually facilitated protein/peptide characterization at the single-cell level, paving the way for single-cell proteomics. The development and advances in the field can be reviewed in terms of key components of a multifunctional probe: functional groups and chemistry for primary amine conjugation; hetero-bifunctional moiety for separation/enrichment of conjugated protein/protein complex; and functionalized linker/spacer. Perspectives are primarily focused on optimizing primary amine conjugation under physiological conditions to improve characterization of native proteins, especially those associated with the surface of living cells/microorganisms.
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Affiliation(s)
- Yang Cai
- Department of Chemistry, University of New Orleans, New Orleans, Louisiana, USA
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19
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Meier MJ, Harrill J, Johnson K, Thomas RS, Tong W, Rager JE, Yauk CL. Progress in toxicogenomics to protect human health. Nat Rev Genet 2024:10.1038/s41576-024-00767-1. [PMID: 39223311 DOI: 10.1038/s41576-024-00767-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/23/2024] [Indexed: 09/04/2024]
Abstract
Toxicogenomics measures molecular features, such as transcripts, proteins, metabolites and epigenomic modifications, to understand and predict the toxicological effects of environmental and pharmaceutical exposures. Transcriptomics has become an integral tool in contemporary toxicology research owing to innovations in gene expression profiling that can provide mechanistic and quantitative information at scale. These data can be used to predict toxicological hazards through the use of transcriptomic biomarkers, network inference analyses, pattern-matching approaches and artificial intelligence. Furthermore, emerging approaches, such as high-throughput dose-response modelling, can leverage toxicogenomic data for human health protection even in the absence of predicting specific hazards. Finally, single-cell transcriptomics and multi-omics provide detailed insights into toxicological mechanisms. Here, we review the progress since the inception of toxicogenomics in applying transcriptomics towards toxicology testing and highlight advances that are transforming risk assessment.
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Affiliation(s)
- Matthew J Meier
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario, Canada
| | - Joshua Harrill
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, USA
| | - Kamin Johnson
- Predictive Safety Center, Corteva Agriscience, Indianapolis, IN, USA
| | - Russell S Thomas
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, USA
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, United States Food and Drug Administration, Jefferson, AR, USA
- Curriculum in Toxicology & Environmental Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Julia E Rager
- Curriculum in Toxicology & Environmental Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
- The Center for Environmental Medicine, Asthma and Lung Biology, School of Medicine, The University of North Carolina, Chapel Hill, NC, USA
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Carole L Yauk
- Department of Biology, University of Ottawa, Ottawa, Ontario, Canada.
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20
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Yan Z, Xia J, Cao Z, Zhang H, Wang J, Feng T, Shu Y, Zou L. Multi-omics integration reveals potential stage-specific druggable targets in T-cell acute lymphoblastic leukemia. Genes Dis 2024; 11:100949. [PMID: 39071111 PMCID: PMC11282411 DOI: 10.1016/j.gendis.2023.03.022] [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: 10/20/2022] [Accepted: 03/11/2023] [Indexed: 07/30/2024] Open
Abstract
T-cell acute lymphoblastic leukemia (T-ALL), a heterogeneous hematological malignancy, is caused by the developmental arrest of normal T-cell progenitors. The development of targeted therapeutic regimens is impeded by poor knowledge of the stage-specific aberrances in this disease. In this study, we performed multi-omics integration analysis, which included mRNA expression, chromatin accessibility, and gene-dependency database analyses, to identify potential stage-specific druggable targets and repositioned drugs for this disease. This multi-omics integration helped identify 29 potential pathological genes for T-ALL. These genes exhibited tissue-specific expression profiles and were enriched in the cell cycle, hematopoietic stem cell differentiation, and the AMPK signaling pathway. Of these, four known druggable targets (CDK6, TUBA1A, TUBB, and TYMS) showed dysregulated and stage-specific expression in malignant T cells and may serve as stage-specific targets in T-ALL. The TUBA1A expression level was higher in the early T cell precursor (ETP)-ALL cells, while TUBB and TYMS were mainly highly expressed in malignant T cells arrested at the CD4 and CD8 double-positive or single-positive stage. CDK6 exhibited a U-shaped expression pattern in malignant T cells along the naïve to maturation stages. Furthermore, mebendazole and gemcitabine, which target TUBA1A and TYMS, respectively, exerted stage-specific inhibitory effects on T-ALL cell lines, indicating their potential stage-specific antileukemic role in T-ALL. Collectively, our findings might aid in identifying potential stage-specific druggable targets and are promising for achieving more precise therapeutic strategies for T-ALL.
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Affiliation(s)
- Zijun Yan
- Clinical Research Unit, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200062, China
- Institute of Pediatric Infection, Immunity, and Critical Care Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai 200062, China
| | - Jie Xia
- Bioinformatics and BioMedical Bigdata Mining Laboratory, School of Big Health, Guizhou Medical University, Guiyang, Guizhou 554300, China
| | - Ziyang Cao
- Clinical Research Unit, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200062, China
- Institute of Pediatric Infection, Immunity, and Critical Care Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai 200062, China
| | - Hongyang Zhang
- Clinical Research Unit, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200062, China
- Institute of Pediatric Infection, Immunity, and Critical Care Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai 200062, China
| | - Jinxia Wang
- Clinical Research Unit, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200062, China
- Institute of Pediatric Infection, Immunity, and Critical Care Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai 200062, China
| | - Tienan Feng
- Clinical Research Unit, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200062, China
- Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yi Shu
- Center for Clinical Molecular Laboratory Medicine of Children's Hospital of Chongqing Medical University, Chongqing 400014, China
| | - Lin Zou
- Clinical Research Unit, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200062, China
- Institute of Pediatric Infection, Immunity, and Critical Care Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai 200062, China
- Center for Clinical Molecular Laboratory Medicine of Children's Hospital of Chongqing Medical University, Chongqing 400014, China
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21
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Vojnits K, Feng Z, Johnson P, Porras D, Manocha E, Vandersluis S, Pfammatter S, Thibault P, Bhatia M. Targeting of human cancer stem cells predicts efficacy and toxicity of FDA-approved oncology drugs. Cancer Lett 2024; 599:217108. [PMID: 38986735 DOI: 10.1016/j.canlet.2024.217108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Revised: 07/02/2024] [Accepted: 07/04/2024] [Indexed: 07/12/2024]
Abstract
Cancer remains the leading cause of death worldwide with approved oncology drugs continuing to have heterogenous patient responses and accompanied adverse effects (AEs) that limits effectiveness. Here, we examined >100 FDA-approved oncology drugs in the context of stemness using a surrogate model of transformed human pluripotent cancer stem cells (CSCs) vs. healthy stem cells (hSCs) capable of distinguishing abnormal self-renewal and differentiation. Although a proportion of these drugs had no effects (inactive), a larger portion affected CSCs (active), and a unique subset preferentially affected CSCs over hSCs (selective). Single cell gene expression and protein profiling of each drug's FDA recognized target provided a molecular correlation of responses in CSCs vs. hSCs. Uniquely, drugs selective for CSCs demonstrated clinical efficacy, measured by overall survival, and reduced AEs. Our findings reveal that while unintentional, half of anticancer drugs are active against CSCs and associated with improved clinical outcomes. Based on these findings, we suggest ability to target CSC targeting should be included as a property of early onco-therapeutic development.
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Affiliation(s)
- Kinga Vojnits
- Department of Biochemistry and Biomedical Sciences, Faculty of Health Sciences, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON, Canada
| | - Zhuohang Feng
- Department of Biochemistry and Biomedical Sciences, Faculty of Health Sciences, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON, Canada
| | - Paige Johnson
- Department of Biochemistry and Biomedical Sciences, Faculty of Health Sciences, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON, Canada
| | - Deanna Porras
- Department of Biochemistry and Biomedical Sciences, Faculty of Health Sciences, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON, Canada
| | - Ekta Manocha
- Department of Biochemistry and Biomedical Sciences, Faculty of Health Sciences, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON, Canada
| | - Sean Vandersluis
- Department of Biochemistry and Biomedical Sciences, Faculty of Health Sciences, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON, Canada
| | - Sibylle Pfammatter
- Department of Chemistry and Institute for Research in Immunology and Cancer (IRIC), University of Montreal, Montreal, QC, Canada
| | - Pierre Thibault
- Department of Chemistry and Institute for Research in Immunology and Cancer (IRIC), University of Montreal, Montreal, QC, Canada
| | - Mick Bhatia
- Department of Biochemistry and Biomedical Sciences, Faculty of Health Sciences, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, ON, Canada.
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22
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Chen J, Larsson L, Swarbrick A, Lundeberg J. Spatial landscapes of cancers: insights and opportunities. Nat Rev Clin Oncol 2024; 21:660-674. [PMID: 39043872 DOI: 10.1038/s41571-024-00926-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/28/2024] [Indexed: 07/25/2024]
Abstract
Solid tumours comprise many different cell types organized in spatially structured arrangements, with substantial intratumour and intertumour heterogeneity. Advances in spatial profiling technologies over the past decade hold promise to capture the complexity of these cellular architectures to build a holistic view of the intricate molecular mechanisms that shape the tumour ecosystem. Some of these mechanisms act at the cellular scale and are controlled by cell-autonomous programmes or communication between nearby cells, whereas other mechanisms result from coordinated efforts between large networks of cells and extracellular molecules organized into tissues and organs. In this Review we provide insights into the application of single-cell and spatial profiling tools, with a focus on spatially resolved transcriptomic tools developed to understand the cellular architecture of the tumour microenvironment and identify opportunities to use them to improve clinical management of cancers.
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Affiliation(s)
- Julia Chen
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia
- Department of Medical Oncology, St George Hospital, Sydney, New South Wales, Australia
| | - Ludvig Larsson
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden
| | - Alexander Swarbrick
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Sydney, New South Wales, Australia.
- School of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia.
| | - Joakim Lundeberg
- Department of Gene Technology, KTH Royal Institute of Technology, Science for Life Laboratory, Stockholm, Sweden.
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23
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Deng T, Chen G. Single-cell-based molecular classification in systematic treatment of hepatocellular carcinoma: From in silico to bedside. Hepatology 2024; 80:505-507. [PMID: 38546296 DOI: 10.1097/hep.0000000000000874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 03/18/2024] [Indexed: 04/30/2024]
Affiliation(s)
- Tuo Deng
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
- Zhejiang-Germany Interdisciplinary Joint Laboratory of Hepatobiliary-Pancreatic Tumor and Bioengineering
- Zhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, are department of The First Affiliated Hospital of Wenzhou Medical University
| | - Gang Chen
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
- Zhejiang-Germany Interdisciplinary Joint Laboratory of Hepatobiliary-Pancreatic Tumor and Bioengineering
- Zhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, are department of The First Affiliated Hospital of Wenzhou Medical University
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24
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Wang J, Liang Y, Xu C, Gao J, Tong J, Shi L. The heterogeneity of erythroid cells: insight at the single-cell transcriptome level. Cell Tissue Res 2024; 397:179-192. [PMID: 38953986 DOI: 10.1007/s00441-024-03903-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 06/19/2024] [Indexed: 07/04/2024]
Abstract
Erythroid cells, the most prevalent cell type in blood, are one of the earliest products and permeate through the entire process of hematopoietic development in the human body, the oxygen-transporting function of which is crucial for maintaining overall health and life support. Previous investigations into erythrocyte differentiation and development have primarily focused on population-level analyses, lacking the single-cell perspective essential for comprehending the intricate pathways of erythroid maturation, differentiation, and the encompassing cellular heterogeneity. The continuous optimization of single-cell transcriptome sequencing technology, or single-cell RNA sequencing (scRNA-seq), provides a powerful tool for life sciences research, which has a particular superiority in the identification of unprecedented cell subgroups, the analyzing of cellular heterogeneity, and the transcriptomic characteristics of individual cells. Over the past decade, remarkable strides have been taken in the realm of single-cell RNA sequencing technology, profoundly enhancing our understanding of erythroid cells. In this review, we systematically summarize the recent developments in single-cell transcriptome sequencing technology and emphasize their substantial impact on the study of erythroid cells, highlighting their contributions, including the exploration of functional heterogeneity within erythroid populations, the identification of novel erythrocyte subgroups, the tracking of different erythroid lineages, and the unveiling of mechanisms governing erythroid fate decisions. These findings not only invigorate erythroid cell research but also offer new perspectives on the management of diseases related to erythroid cells.
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Affiliation(s)
- Jingwei Wang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Yipeng Liang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Changlu Xu
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Jie Gao
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Jingyuan Tong
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
| | - Lihong Shi
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Tianjin Institutes of Health Science, Tianjin, 301600, China.
- CAMS Center for Stem Cell Medicine, PUMC Department of Stem Cell and Regenerative Medicine, Tianjin, 300020, China.
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25
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Zhang YW, Wu SX, Wang GW, Wan RD, Yang QE. Single-cell analysis identifies critical regulators of spermatogonial development and differentiation in cattle-yak bulls. J Dairy Sci 2024; 107:7317-7336. [PMID: 38642661 DOI: 10.3168/jds.2023-24442] [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: 11/22/2023] [Accepted: 03/11/2024] [Indexed: 04/22/2024]
Abstract
Spermatogenesis is a continuous process in which functional sperm are produced through a series of mitotic and meiotic divisions and morphological changes in germ cells. The aberrant development and fate transitions of spermatogenic cells cause hybrid sterility in mammals. Cattle-yak, a hybrid animal between taurine cattle (Bos taurus) and yak (Bos grunniens), exhibits male-specific sterility due to spermatogenic failure. In the present study, we performed single-cell RNA sequencing analysis to identify differences in testicular cell composition and the developmental trajectory of spermatogenic cells between yak and cattle-yak. The composition and molecular signatures of spermatogonial subtypes were dramatically different between these 2 animals, and the expression of genes associated with stem cell maintenance, cell differentiation and meiotic entry was altered in cattle-yak, indicating the impairment of undifferentiated spermatogonial fate decisions. Cell communication analysis revealed that signaling within different spermatogenic cell subpopulations was weakened, and progenitor spermatogonia were unable to or delayed receiving and sending signals for transformation to the next stage in cattle-yak. Simultaneously, the communication between niche cells and germ cells was also abnormal. Collectively, we obtained the expression profiles of transcriptome signatures of different germ cells and testicular somatic cell populations at the single-cell level and identified critical regulators of spermatogonial differentiation and meiosis in yak and sterile cattle-yak. The findings of this study shed light on the genetic mechanisms that lead to hybrid sterility and speciation in bovid species.
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Affiliation(s)
- Yi-Wen Zhang
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810000, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shi-Xin Wu
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810000, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guo-Wen Wang
- Qinghai Academy of Animal Husbandry and Veterinary Sciences, Xining, Qinghai 810016, China
| | - Rui-Dong Wan
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810000, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qi-En Yang
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810000, China; University of Chinese Academy of Sciences, Beijing 100049, China; Qinghai Key Laboratory of Animal Ecological Genomics, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, Qinghai 810001, China.
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26
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Dance A. What is a cell type, really? The quest to categorize life's myriad forms. Nature 2024; 633:754-756. [PMID: 39317746 DOI: 10.1038/d41586-024-03073-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/26/2024]
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27
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Kim D, Jeong S, Park SM. Unraveling flavivirus pathogenesis: from bulk to single-cell RNA-sequencing strategies. THE KOREAN JOURNAL OF PHYSIOLOGY & PHARMACOLOGY : OFFICIAL JOURNAL OF THE KOREAN PHYSIOLOGICAL SOCIETY AND THE KOREAN SOCIETY OF PHARMACOLOGY 2024; 28:403-411. [PMID: 39198221 PMCID: PMC11362000 DOI: 10.4196/kjpp.2024.28.5.403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 06/18/2024] [Accepted: 07/01/2024] [Indexed: 09/01/2024]
Abstract
The global spread of flaviviruses has triggered major outbreaks worldwide, significantly impacting public health, society, and economies. This has intensified research efforts to understand how flaviviruses interact with their hosts and manipulate the immune system, underscoring the need for advanced research tools. RNA-sequencing (RNA-seq) technologies have revolutionized our understanding of flavivirus infections by offering transcriptome analysis to dissect the intricate dynamics of virus-host interactions. Bulk RNA-seq provides a macroscopic overview of gene expression changes in virus-infected cells, offering insights into infection mechanisms and host responses at the molecular level. Single-cell RNA sequencing (scRNAseq) provides unprecedented resolution by analyzing individual infected cells, revealing remarkable cellular heterogeneity within the host response. A particularly innovative advancement, virus-inclusive single-cell RNA sequencing (viscRNA-seq), addresses the challenges posed by non-polyadenylated flavivirus genomes, unveiling intricate details of virus-host interactions. In this review, we discuss the contributions of bulk RNA-seq, scRNA-seq, and viscRNA-seq to the field, exploring their implications in cell line experiments and studies on patients infected with various flavivirus species. Comprehensive transcriptome analyses from RNA-seq technologies are pivotal in accelerating the development of effective diagnostics and therapeutics, paving the way for innovative treatments and enhancing our preparedness for future outbreaks.
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Affiliation(s)
- Doyeong Kim
- College of Pharmacy, Chungnam National University, Daejeon 34134, Korea
| | - Seonghun Jeong
- College of Pharmacy, Chungnam National University, Daejeon 34134, Korea
| | - Sang-Min Park
- College of Pharmacy, Chungnam National University, Daejeon 34134, Korea
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28
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Xiang L, Rao J, Yuan J, Xie T, Yan H. Single-Cell RNA-Sequencing: Opening New Horizons for Breast Cancer Research. Int J Mol Sci 2024; 25:9482. [PMID: 39273429 PMCID: PMC11395021 DOI: 10.3390/ijms25179482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2024] [Revised: 08/25/2024] [Accepted: 08/29/2024] [Indexed: 09/15/2024] Open
Abstract
Breast cancer is the most prevalent malignant tumor among women with high heterogeneity. Traditional techniques frequently struggle to comprehensively capture the intricacy and variety of cellular states and interactions within breast cancer. As global precision medicine rapidly advances, single-cell RNA sequencing (scRNA-seq) has become a highly effective technique, revolutionizing breast cancer research by offering unprecedented insights into the cellular heterogeneity and complexity of breast cancer. This cutting-edge technology facilitates the analysis of gene expression profiles at the single-cell level, uncovering diverse cell types and states within the tumor microenvironment. By dissecting the cellular composition and transcriptional signatures of breast cancer cells, scRNA-seq provides new perspectives for understanding the mechanisms behind tumor therapy, drug resistance and metastasis in breast cancer. In this review, we summarized the working principle and workflow of scRNA-seq and emphasized the major applications and discoveries of scRNA-seq in breast cancer research, highlighting its impact on our comprehension of breast cancer biology and its potential for guiding personalized treatment strategies.
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Affiliation(s)
- Lingyan Xiang
- Department of Pathology, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Jie Rao
- Department of Pathology, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Jingping Yuan
- Department of Pathology, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Ting Xie
- Department of Pathology, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Honglin Yan
- Department of Pathology, Renmin Hospital of Wuhan University, Wuhan 430060, China
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29
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Liu X, Wang Q, Zhou M, Wang Y, Wang X, Zhou X, Song Q. DrugFormer: Graph-Enhanced Language Model to Predict Drug Sensitivity. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2405861. [PMID: 39206872 DOI: 10.1002/advs.202405861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Revised: 07/19/2024] [Indexed: 09/04/2024]
Abstract
Drug resistance poses a crucial challenge in healthcare, with response rates to chemotherapy and targeted therapy remaining low. Individual patient's resistance is exacerbated by the intricate heterogeneity of tumor cells, presenting significant obstacles to effective treatment. To address this challenge, DrugFormer, a novel graph-augmented large language model designed to predict drug resistance at single-cell level is proposed. DrugFormer integrates both serialized gene tokens and gene-based knowledge graphs for the accurate predictions of drug response. After training on comprehensive single-cell data with drug response information, DrugFormer model presents outperformance, with higher F1, precision, and recall in predicting drug response. Based on the scRNA-seq data from refractory multiple myeloma (MM) and acute myeloid leukemia (AML) patients, DrugFormer demonstrates high efficacy in identifying resistant cells and uncovering underlying molecular mechanisms. Through pseudotime trajectory analysisunique drug-resistant cellular states associated with poor patient outcomes are revealed. Furthermore, DrugFormer identifies potential therapeutic targets, such as COX8A, for overcoming drug resistance across different cancer types. In conclusion, DrugFormer represents a significant advancement in the field of drug resistance prediction, offering a powerful tool for unraveling the heterogeneity of cellular response to drugs and guiding personalized treatment strategies.
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Affiliation(s)
- Xiaona Liu
- Center for Computational Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Qing Wang
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Minghao Zhou
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Yanfei Wang
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
| | - Xuefeng Wang
- Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Xiaobo Zhou
- Center for Computational Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Qianqian Song
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, 32611, USA
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30
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Xie D, An B, Yang M, Wang L, Guo M, Luo H, Huang S, Sun F. Application and research progress of single cell sequencing technology in leukemia. Front Oncol 2024; 14:1389468. [PMID: 39267837 PMCID: PMC11390353 DOI: 10.3389/fonc.2024.1389468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 08/08/2024] [Indexed: 09/15/2024] Open
Abstract
Leukemia is a malignant tumor with high heterogeneity and a complex evolutionary process. It is difficult to resolve the heterogeneity and clonal evolution of leukemia cells by applying traditional bulk sequencing techniques, thus preventing a deep understanding of the mechanisms of leukemia development and the identification of potential therapeutic targets. However, with the development and application of single-cell sequencing technology, it is now possible to investigate the gene expression profile, mutations, and epigenetic features of leukemia at the single-cell level, thus providing a new perspective for leukemia research. In this article, we review the recent applications and advances of single-cell sequencing technology in leukemia research, discuss its potential for enhancing our understanding of the mechanisms of leukemia development, discovering therapeutic targets and personalized treatment, and provide reference guidelines for the significance of this technology in clinical research.
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Affiliation(s)
- Dan Xie
- Medical College, Guizhou University, Guiyang, China
| | - Bangquan An
- Guizhou Provincial People's Hospital, Guiyang, Guizhou, China
| | - Mingyue Yang
- Medical College, Guizhou University, Guiyang, China
| | - Lei Wang
- Medical College, Guizhou University, Guiyang, China
| | - Min Guo
- Medical College, Guizhou University, Guiyang, China
| | - Heng Luo
- State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang, Guizhou, China
- Guizhou Provincial Engineering Research Center for Natural Drugs, Guiyang, Guizhou, China
| | - Shengwen Huang
- Guizhou Provincial People's Hospital, Guiyang, Guizhou, China
| | - Fa Sun
- Medical College, Guizhou University, Guiyang, China
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31
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White BS, de Reyniès A, Newman AM, Waterfall JJ, Lamb A, Petitprez F, Lin Y, Yu R, Guerrero-Gimenez ME, Domanskyi S, Monaco G, Chung V, Banerjee J, Derrick D, Valdeolivas A, Li H, Xiao X, Wang S, Zheng F, Yang W, Catania CA, Lang BJ, Bertus TJ, Piermarocchi C, Caruso FP, Ceccarelli M, Yu T, Guo X, Bletz J, Coller J, Maecker H, Duault C, Shokoohi V, Patel S, Liliental JE, Simon S, Saez-Rodriguez J, Heiser LM, Guinney J, Gentles AJ. Community assessment of methods to deconvolve cellular composition from bulk gene expression. Nat Commun 2024; 15:7362. [PMID: 39191725 PMCID: PMC11350143 DOI: 10.1038/s41467-024-50618-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 07/11/2024] [Indexed: 08/29/2024] Open
Abstract
We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.
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Affiliation(s)
- Brian S White
- Sage Bionetworks, Seattle, WA, USA
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Aurélien de Reyniès
- Centre de Recherche des Cordeliers, INSERM U1138, Université Paris Cité, Paris, France
| | - Aaron M Newman
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Joshua J Waterfall
- INSERM U830 and Translational Research Department, Institut Curie, PSL Research University, Paris, France
| | | | - Florent Petitprez
- Programme Cartes d'Identité des Tumeurs, Ligue Nationale Contre le Cancer, Paris, France
- MRC Centre for Reproductive Health, the Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Yating Lin
- Xiamen University, Xiamen, Fujian, China
| | | | - Martin E Guerrero-Gimenez
- Institute of Biochemistry and Biotechnology, School of Medicine, National University of Cuyo, Mendoza, Argentina
| | | | - Gianni Monaco
- BIOGEM Institute of Molecular Biology and Genetics, Ariano Irpino, AV, Italy
| | | | | | - Daniel Derrick
- Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Alberto Valdeolivas
- Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany
| | - Haojun Li
- Xiamen University, Xiamen, Fujian, China
| | - Xu Xiao
- Xiamen University, Xiamen, Fujian, China
| | - Shun Wang
- Department of Pathology, Cancer Hospital, Chinese Aacdemy of Medical Science, Beijing, China
| | | | | | - Carlos A Catania
- Laboratory of Intelligent Systems (LABSIN), Engineering School, National University of Cuyo, Mendoza, Argentina
| | - Benjamin J Lang
- Department of Radiation Oncology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | | | | | - Francesca P Caruso
- BIOGEM Institute of Molecular Biology and Genetics, Ariano Irpino, AV, Italy
| | - Michele Ceccarelli
- BIOGEM Institute of Molecular Biology and Genetics, Ariano Irpino, AV, Italy
- Sylvester Comprehensive Cancer Center, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida, USA
| | | | | | | | - John Coller
- Stanford Functional Genomics Facility, Stanford University School of Medicine, Stanford, CA, USA
| | - Holden Maecker
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA, USA
| | - Caroline Duault
- Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA, USA
| | - Vida Shokoohi
- Stanford Functional Genomics Facility, Stanford University School of Medicine, Stanford, CA, USA
| | - Shailja Patel
- Translational Applications Service Center, Stanford University School of Medicine, Stanford, CA, USA
| | - Joanna E Liliental
- Translational Applications Service Center, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Julio Saez-Rodriguez
- Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany
| | - Laura M Heiser
- Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | | | - Andrew J Gentles
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Pathology, Stanford University, Stanford, CA, USA.
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32
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Gao Z, Lu Y, Li M, Chong Y, Hong J, Wu J, Wu D, Xi D, Deng W. Application of Pan-Omics Technologies in Research on Important Economic Traits for Ruminants. Int J Mol Sci 2024; 25:9271. [PMID: 39273219 PMCID: PMC11394796 DOI: 10.3390/ijms25179271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2024] [Revised: 08/23/2024] [Accepted: 08/26/2024] [Indexed: 09/15/2024] Open
Abstract
The economic significance of ruminants in agriculture underscores the need for advanced research methodologies to enhance their traits. This review aims to elucidate the transformative role of pan-omics technologies in ruminant research, focusing on their application in uncovering the genetic mechanisms underlying complex traits such as growth, reproduction, production performance, and rumen function. Pan-omics analysis not only helps in identifying key genes and their regulatory networks associated with important economic traits but also reveals the impact of environmental factors on trait expression. By integrating genomics, epigenomics, transcriptomics, metabolomics, and microbiomics, pan-omics enables a comprehensive analysis of the interplay between genetics and environmental factors, offering a holistic understanding of trait expression. We explore specific examples of economic traits where these technologies have been pivotal, highlighting key genes and regulatory networks identified through pan-omics approaches. Additionally, we trace the historical evolution of each omics field, detailing their progression from foundational discoveries to high-throughput platforms. This review provides a critical synthesis of recent advancements, offering new insights and practical recommendations for the application of pan-omics in the ruminant industry. The broader implications for modern animal husbandry are discussed, emphasizing the potential for these technologies to drive sustainable improvements in ruminant production systems.
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Affiliation(s)
- Zhendong Gao
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, Kunming 650201, China
| | - Ying Lu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Mengfei Li
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Yuqing Chong
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Jieyun Hong
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Jiao Wu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Dongwang Wu
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Dongmei Xi
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Weidong Deng
- Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
- State Key Laboratory for Conservation and Utilization of Bio-Resource in Yunnan, Kunming 650201, China
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33
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Qin H, Shi X, Zhou H. scSwinFormer: A Transformer-Based Cell-Type Annotation Method for scRNA-Seq Data Using Smooth Gene Embedding and Global Features. J Chem Inf Model 2024; 64:6316-6323. [PMID: 39101690 DOI: 10.1021/acs.jcim.4c00616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/06/2024]
Abstract
Single-cell omics techniques have made it possible to analyze individual cells in biological samples, providing us with a more detailed understanding of cellular heterogeneity and biological systems. Accurate identification of cell types is critical for single-cell RNA sequencing (scRNA-seq) analysis. However, scRNA-seq data are usually high dimensional and sparse, posing a great challenge to analyze scRNA-seq data. Existing cell-type annotation methods are either constrained in modeling scRNA-seq data or lack consideration of long-term dependencies of characterized genes. In this work, we developed a Transformer-based deep learning method, scSwinFormer, for the cell-type annotation of large-scale scRNA-seq data. Sequence modeling of scRNA-seq data is performed using the smooth gene embedding module, and then, the potential dependencies of genes are captured by the self-attention module. Subsequently, the global information inherent in scRNA-seq data is synthesized using the Cell Token, thereby facilitating accurate cell-type annotation. We evaluated the performance of our model against current state-of-the-art scRNA-seq cell-type annotation methods on multiple real data sets. ScSwinFormer outperforms the current state-of-the-art scRNA-seq cell-type annotation methods in both external and benchmark data set experiments.
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Affiliation(s)
- Hengyu Qin
- School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
| | - Xiumin Shi
- School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
| | - Han Zhou
- School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
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Sun S, Jiang M, Ma S, Ren J, Liu GH. Exploring the heterogeneous targets of metabolic aging at single-cell resolution. Trends Endocrinol Metab 2024:S1043-2760(24)00190-5. [PMID: 39181730 DOI: 10.1016/j.tem.2024.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 07/09/2024] [Accepted: 07/12/2024] [Indexed: 08/27/2024]
Abstract
Our limited understanding of metabolic aging poses major challenges to comprehending the diverse cellular alterations that contribute to age-related decline, and to devising targeted interventions. This review provides insights into the heterogeneous nature of cellular metabolism during aging and its response to interventions, with a specific focus on cellular heterogeneity and its implications. By synthesizing recent findings using single-cell approaches, we explored the vulnerabilities of distinct cell types and key metabolic pathways. Delving into the cell type-specific alterations underlying the efficacy of systemic interventions, we also discuss the complexity of integrating single-cell data and advocate for leveraging computational tools and artificial intelligence to harness the full potential of these data, develop effective strategies against metabolic aging, and promote healthy aging.
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Affiliation(s)
- Shuhui Sun
- Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart Lung and Blood Vessel Diseases, Beijing 100029, China.
| | - Mengmeng Jiang
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Shuai Ma
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Aging Biomarker Consortium, Beijing 100101, China.
| | - Jie Ren
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Aging Biomarker Consortium, Beijing 100101, China; Key Laboratory of RNA Innovation, Science and Engineering, China National Center for Bioinformation, Beijing 100101, China; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing 101408, China; School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Guang-Hui Liu
- Key Laboratory of Organ Regeneration and Reconstruction, State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China; Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Aging Biomarker Consortium, Beijing 100101, China; Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing 100053, China; Aging Translational Medicine Center, Xuanwu Hospital, Capital Medical University, Beijing 100053, China.
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Alzaabi M, Khalili M, Sultana M, Al-Sayegh M. Transcriptional Dynamics and Key Regulators of Adipogenesis in Mouse Embryonic Stem Cells: Insights from Robust Rank Aggregation Analysis. Int J Mol Sci 2024; 25:9154. [PMID: 39273102 PMCID: PMC11395306 DOI: 10.3390/ijms25179154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Revised: 08/07/2024] [Accepted: 08/16/2024] [Indexed: 09/15/2024] Open
Abstract
Embryonic stem cells are crucial for studying developmental biology due to their self-renewal and pluripotency capabilities. This research investigates the differentiation of mouse ESCs into adipocytes, offering insights into obesity and metabolic disorders. Using a monolayer differentiation approach over 30 days, lipid accumulation and adipogenic markers, such as Cebpb, Pparg, and Fabp4, confirmed successful differentiation. RNA sequencing revealed extensive transcriptional changes, with over 15,000 differentially expressed genes linked to transcription regulation, cell cycle, and DNA repair. This study utilized Robust Rank Aggregation to identify critical regulatory genes like PPARG, CEBPA, and EP300. Network analysis further highlighted Atf5, Ccnd1, and Nr4a1 as potential key players in adipogenesis and its mature state, validated through RT-PCR. While key adipogenic factors showed plateaued expression levels, suggesting early differentiation events, this study underscores the value of ESCs in modeling adipogenesis. These findings contribute to our understanding of adipocyte differentiation and have significant implications for therapeutic strategies targeting metabolic diseases.
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Affiliation(s)
- Mouza Alzaabi
- Division of Biology, New York University Abu Dhabi, Saadiyaat Island, Abu Dhabi P.O. Box 129188, United Arab Emirates
| | - Mariam Khalili
- Division of Biology, New York University Abu Dhabi, Saadiyaat Island, Abu Dhabi P.O. Box 129188, United Arab Emirates
| | - Mehar Sultana
- Center for Genomics & Systems Biology, New York University Abu Dhabi, Saadiyaat Island, Abu Dhabi P.O. Box 129188, United Arab Emirates
| | - Mohamed Al-Sayegh
- Division of Biology, New York University Abu Dhabi, Saadiyaat Island, Abu Dhabi P.O. Box 129188, United Arab Emirates
- Center for Genomics & Systems Biology, New York University Abu Dhabi, Saadiyaat Island, Abu Dhabi P.O. Box 129188, United Arab Emirates
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Hainsworth AH, Blackburn TP, Bradshaw EM, Elahi FM, Gorelick PB, Isaacs JD, Wallin A, Williams SC. The promise of molecular science in brain health. What breakthroughs are anticipated in the next 20 years? CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2024; 7:100364. [PMID: 39263555 PMCID: PMC11387710 DOI: 10.1016/j.cccb.2024.100364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 06/28/2024] [Accepted: 08/19/2024] [Indexed: 09/13/2024]
Abstract
Brain health means optimal physiological brain function across the normal life-course. It encompasses not only healthy brain aging but also brain diseases, their diagnosis and treatment. In all these areas, molecular science has advanced our understanding. This multi-disciplinary review combines viewpoints from laboratory science, clinical medicine and the bioscience industry. First, we review the advances that molecular science has brought to brain health in the past twenty years. These include therapeutic antibodies for CNS diseases (multiple sclerosis, Alzheimer disease) and the dramatic introduction of RNA-targeted therapeutics. Second, we highlight areas where greater molecular understanding is needed. Salient examples are the relation of brain structure to cognitive symptoms, and molecular biomarkers for diagnosis, target discovery and testing of interventions. Finally, we speculate on aspects of molecular science that are likely to advance brain health in the next twenty years. These include: cell senescence and chronobiology; gene editing (notably, CRISPR) and RNA targeting (RNA interference, miRNA manipulation); brain-immune interactions; novel drug targets (AQP4, HIF1, Toll-like receptors); and novel chemistry to make new drugs (molecular machines, quantum molecular modelling and "click" chemistry). Early testing of the relationships between molecular pathways and clinical manifestations will drive much-needed breakthroughs in neurology and psychiatry.
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Affiliation(s)
- Atticus H Hainsworth
- Molecular & Clinical Sciences Research Institute, St George's University of London, London, SW17 0RE, UK
- Department of Neurology, St George's University Hospitals NHS Foundation Trust, Blackshaw Road, London, SW17 0QT, UK
| | - Thomas P Blackburn
- Translational Pharmacology BioVentures, Leigh on Sea, Essex, SS9 2UA, UK
- TPBioVentures, Hoboken, NJ, USA
| | - Elizabeth M Bradshaw
- Carol and Gene Ludwig Center for Research on Neurodegeneration, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Fanny M Elahi
- Departments of Neurology and Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, New York, NY 10029-5674, USA
- James J. Peter VA Medical Center, Bronx, NY, USA
| | - Philip B Gorelick
- Davee Department of Neurology, Northwestern University Feinberg School of Medicine, 635 N. Michigan Avenue, Chicago, IL 60611, USA
| | - Jeremy D Isaacs
- Molecular & Clinical Sciences Research Institute, St George's University of London, London, SW17 0RE, UK
- Department of Neurology, St George's University Hospitals NHS Foundation Trust, Blackshaw Road, London, SW17 0QT, UK
| | - Anders Wallin
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Steven Cr Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, Kings College London. SE5 8AF, UK
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Seeler S, Arnarsson K, Dreßen M, Krane M, Doppler SA. Beyond the Heartbeat: Single-Cell Omics Redefining Cardiovascular Research. Curr Cardiol Rep 2024:10.1007/s11886-024-02117-3. [PMID: 39158785 DOI: 10.1007/s11886-024-02117-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/07/2024] [Indexed: 08/20/2024]
Abstract
PURPOSE OF REVIEW This review aims to explore recent advances in single-cell omics techniques as applied to various regions of the human heart, illuminating cellular diversity, regulatory networks, and disease mechanisms. We examine the contributions of single-cell transcriptomics, genomics, proteomics, epigenomics, and spatial transcriptomics in unraveling the complexity of cardiac tissues. RECENT FINDINGS Recent strides in single-cell omics technologies have revolutionized our understanding of the heart's cellular composition, cell type heterogeneity, and molecular dynamics. These advancements have elucidated pathological conditions as well as the cellular landscape in heart development. We highlight emerging applications of integrated single-cell omics, particularly for cardiac regeneration, disease modeling, and precision medicine, and emphasize the transformative potential of these technologies to advance cardiovascular research and clinical practice.
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Affiliation(s)
- Sabine Seeler
- Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University Munich, Lazarettstr. 36, 80636, Munich, Germany
- Institute for Translational Cardiac Surgery (INSURE), Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University Munich, Munich, Germany
| | - Kristjan Arnarsson
- Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University Munich, Lazarettstr. 36, 80636, Munich, Germany
- Institute for Translational Cardiac Surgery (INSURE), Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University Munich, Munich, Germany
| | - Martina Dreßen
- Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University Munich, Lazarettstr. 36, 80636, Munich, Germany
- Institute for Translational Cardiac Surgery (INSURE), Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University Munich, Munich, Germany
| | - Markus Krane
- Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University Munich, Lazarettstr. 36, 80636, Munich, Germany
- Institute for Translational Cardiac Surgery (INSURE), Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University Munich, Munich, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
- Division of Cardiac Surgery, Department of Surgery, Yale School of Medicine, New Haven, CT, USA
| | - Stefanie A Doppler
- Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University Munich, Lazarettstr. 36, 80636, Munich, Germany.
- Institute for Translational Cardiac Surgery (INSURE), Department of Cardiovascular Surgery, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University Munich, Munich, Germany.
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Zhang D, Wen Q, Zhang R, Kou K, Lin M, Zhang S, Yang J, Shi H, Yang Y, Tan X, Yin S, Ou X. From Cell to Gene: Deciphering the Mechanism of Heart Failure With Single-Cell Sequencing. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2308900. [PMID: 39159065 DOI: 10.1002/advs.202308900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Revised: 07/24/2024] [Indexed: 08/21/2024]
Abstract
Heart failure (HF) is a prevalent cardiovascular disease with significant morbidity and mortality rates worldwide. Due to the intricate structure of the heart, diverse cell types, and the complex pathogenesis of HF, further in-depth investigation into the underlying mechanisms is required. The elucidation of the heterogeneity of cardiomyocytes and the intercellular communication network is particularly important. Traditional high-throughput sequencing methods provide an average measure of gene expression, failing to capture the "heterogeneity" between cells and impacting the accuracy of gene function knowledge. In contrast, single-cell sequencing techniques allow for the amplification of the entire genome or transcriptome at the individual cell level, facilitating the examination of gene structure and expression with unparalleled precision. This approach offers valuable insights into disease mechanisms, enabling the identification of changes in cellular components and gene expressions during hypertrophy associated with HF. Moreover, it reveals distinct cell populations and their unique roles in the HF microenvironment, providing a comprehensive understanding of the cellular landscape that underpins HF pathogenesis. This review focuses on the insights provided by single-cell sequencing techniques into the mechanisms underlying HF and discusses the challenges encountered in current cardiovascular research.
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Affiliation(s)
- Dan Zhang
- Key Laboratory of Medical Electrophysiology of Ministry of Education, Institute of Cardiovascular Medicine, Department of Cardiology of the Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, 646000, China
- Department of Rehabilitation Medicine, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Qiang Wen
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jiefang Rd, Wuhan, Hubei, 430022, China
| | - Rui Zhang
- Key Laboratory of Medical Electrophysiology of Ministry of Education, Institute of Cardiovascular Medicine, Department of Cardiology of the Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Kun Kou
- Key Laboratory of Medical Electrophysiology of Ministry of Education, Institute of Cardiovascular Medicine, Department of Cardiology of the Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Miao Lin
- Key Laboratory of Medical Electrophysiology of Ministry of Education, Institute of Cardiovascular Medicine, Department of Cardiology of the Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Shiyu Zhang
- Key Laboratory of Medical Electrophysiology of Ministry of Education, Institute of Cardiovascular Medicine, Department of Cardiology of the Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Jun Yang
- Key Laboratory of Medical Electrophysiology of Ministry of Education, Institute of Cardiovascular Medicine, Department of Cardiology of the Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Hangchuan Shi
- Department of Clinical & Translational Research, University of Rochester Medical Center, 265 Crittenden Blvd, Rochester, NY, 14642, USA
- Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, 601 Elmwood Ave, Rochester, NY, 14642, USA
| | - Yan Yang
- Key Laboratory of Medical Electrophysiology of Ministry of Education, Institute of Cardiovascular Medicine, Department of Cardiology of the Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Xiaoqiu Tan
- Key Laboratory of Medical Electrophysiology of Ministry of Education, Institute of Cardiovascular Medicine, Department of Cardiology of the Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, 646000, China
- Department of Physiology, School of Basic Medical Sciences, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Shigang Yin
- Luzhou Key Laboratory of Nervous system disease and Brain Function, Southwest Medical University, Luzhou, Sichuan, 646000, China
| | - Xianhong Ou
- Key Laboratory of Medical Electrophysiology of Ministry of Education, Institute of Cardiovascular Medicine, Department of Cardiology of the Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, 646000, China
- State Key Laboratory for Chemistry and Molecular Engineering of Medicinal Resources, Guangxi Normal University, Guilin, Guangxi, 541004, China
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So J, Strobel O, Wann J, Kim K, Paul A, Acri DJ, Dabin LC, Peng G, Kim J, Roh HC. Robust single nucleus RNA sequencing reveals depot-specific cell population dynamics in adipose tissue remodeling during obesity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.08.588525. [PMID: 38645263 PMCID: PMC11030456 DOI: 10.1101/2024.04.08.588525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Single nucleus RNA sequencing (snRNA-seq), an alternative to single cell RNA sequencing (scRNA-seq), encounters technical challenges in obtaining high-quality nuclei and RNA, persistently hindering its applications. Here, we present a robust technique for isolating nuclei across various tissue types, remarkably enhancing snRNA-seq data quality. Employing this approach, we comprehensively characterize the depot-dependent cellular dynamics of various cell types underlying adipose tissue remodeling during obesity. By integrating bulk nuclear RNA-seq from adipocyte nuclei of different sizes, we identify distinct adipocyte subpopulations categorized by size and functionality. These subpopulations follow two divergent trajectories, adaptive and pathological, with their prevalence varying by depot. Specifically, we identify a key molecular feature of dysfunctional hypertrophic adipocytes, a global shutdown in gene expression, along with elevated stress and inflammatory responses. Furthermore, our differential gene expression analysis reveals distinct contributions of adipocyte subpopulations to the overall pathophysiology of adipose tissue. Our study establishes a robust snRNA-seq method, providing novel insights into the biological processes involved in adipose tissue remodeling during obesity, with broader applicability across diverse biological systems.
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Liu Y, Hoskins I, Geng M, Zhao Q, Chacko J, Qi K, Persyn L, Wang J, Zheng D, Zhong Y, Rao S, Park D, Cenik ES, Agarwal V, Ozadam H, Cenik C. Translation efficiency covariation across cell types is a conserved organizing principle of mammalian transcriptomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.11.607360. [PMID: 39149359 PMCID: PMC11326257 DOI: 10.1101/2024.08.11.607360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Characterization of shared patterns of RNA expression between genes across conditions has led to the discovery of regulatory networks and novel biological functions. However, it is unclear if such coordination extends to translation, a critical step in gene expression. Here, we uniformly analyzed 3,819 ribosome profiling datasets from 117 human and 94 mouse tissues and cell lines. We introduce the concept of Translation Efficiency Covariation (TEC), identifying coordinated translation patterns across cell types. We nominate potential mechanisms driving shared patterns of translation regulation. TEC is conserved across human and mouse cells and helps uncover gene functions. Moreover, our observations indicate that proteins that physically interact are highly enriched for positive covariation at both translational and transcriptional levels. Our findings establish translational covariation as a conserved organizing principle of mammalian transcriptomes.
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Affiliation(s)
- Yue Liu
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Ian Hoskins
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Michael Geng
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Qiuxia Zhao
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Jonathan Chacko
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Kangsheng Qi
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Logan Persyn
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Jun Wang
- mRNA Center of Excellence, Sanofi, Waltham, MA 02451, USA
| | - Dinghai Zheng
- mRNA Center of Excellence, Sanofi, Waltham, MA 02451, USA
| | - Yochen Zhong
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Shilpa Rao
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Dayea Park
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Elif Sarinay Cenik
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
| | - Vikram Agarwal
- mRNA Center of Excellence, Sanofi, Waltham, MA 02451, USA
| | - Hakan Ozadam
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX 78712, USA
- Present address: Sail Biomedicines, Cambridge, MA, 02141, USA
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Nakajima S, Tsuchiya H, Fujio K. Unraveling immune cell heterogeneity in autoimmune arthritis: insights from single-cell RNA sequencing. Immunol Med 2024:1-13. [PMID: 39120105 DOI: 10.1080/25785826.2024.2388343] [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: 06/11/2024] [Accepted: 07/31/2024] [Indexed: 08/10/2024] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) has transformed our understanding of immune-mediated arthritis, which comprises rheumatoid arthritis and spondyloarthritis. This review outlines the key findings and advancements in scRNA-seq studies focused on the pathogenesis of autoimmune arthritis and its clinical application. In rheumatoid arthritis, scRNA-seq has elucidated the heterogeneity among synovial fibroblasts and immune cell subsets in inflammatory sites, offering insights into disease mechanisms and the differences in treatment responses. Various studies have identified distinct synovial fibroblast subpopulations, such as THY1+ inflammatory and THY1- destructive fibroblasts. Furthermore, scRNA-seq has revealed diverse T cell profiles in the synovium, including peripheral helper T cells and clonally expanded CD8+ T cells, shedding light on potential therapeutic targets and predictive markers of treatment response. Similarly, in spondyloarthritis, particularly psoriatic arthritis and ankylosing spondylitis, scRNA-seq studies have identified distinct cellular profiles associated with disease pathology. Challenges such as cost and sample size limitations persist, but collaborative efforts and utilization of public databases hold promise for overcoming these obstacles. Overall, scRNA-seq emerges as a powerful tool for dissecting cellular heterogeneity and driving precision medicine in immune-mediated arthritis.
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Affiliation(s)
- Sotaro Nakajima
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Haruka Tsuchiya
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Keishi Fujio
- Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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Luo Q, Chen Y, Lan X. COMSE: analysis of single-cell RNA-seq data using community detection-based feature selection. BMC Biol 2024; 22:167. [PMID: 39113021 PMCID: PMC11304914 DOI: 10.1186/s12915-024-01963-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Accepted: 07/10/2024] [Indexed: 08/10/2024] Open
Abstract
BACKGROUND Single-cell RNA sequencing enables studying cells individually, yet high gene dimensions and low cell numbers challenge analysis. And only a subset of the genes detected are involved in the biological processes underlying cell-type specific functions. RESULT In this study, we present COMSE, an unsupervised feature selection framework using community detection to capture informative genes from scRNA-seq data. COMSE identified homogenous cell substates with high resolution, as demonstrated by distinguishing different cell cycle stages. Evaluations based on real and simulated scRNA-seq datasets showed COMSE outperformed methods even with high dropout rates in cell clustering assignment. We also demonstrate that by identifying communities of genes associated with batch effects, COMSE parses signals reflecting biological difference from noise arising due to differences in sequencing protocols, thereby enabling integrated analysis of scRNA-seq datasets of different sources. CONCLUSIONS COMSE provides an efficient unsupervised framework that selects highly informative genes in scRNA-seq data improving cell sub-states identification and cell clustering. It identifies gene subsets that reveal biological and technical heterogeneity, supporting applications like batch effect correction and pathway analysis. It also provides robust results for bulk RNA-seq data analysis.
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Affiliation(s)
- Qinhuan Luo
- Department of Basic Medical Science, School of Medicine, Tsinghua University, Beijing, 100084, China
- MOE Key Laboratory of Bioinformatics, Tsinghua University, Beijing, 100084, China
| | - Yaozhu Chen
- School of Artificial Intelligence, Beijing Normal University, Beijing, 100875, China
| | - Xun Lan
- Department of Basic Medical Science, School of Medicine, Tsinghua University, Beijing, 100084, China.
- Tsinghua-Peking Joint Center for Life Sciences, Tsinghua University, Beijing, 100084, China.
- MOE Key Laboratory of Bioinformatics, Tsinghua University, Beijing, 100084, China.
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Su J, Song Y, Zhu Z, Huang X, Fan J, Qiao J, Mao F. Cell-cell communication: new insights and clinical implications. Signal Transduct Target Ther 2024; 9:196. [PMID: 39107318 PMCID: PMC11382761 DOI: 10.1038/s41392-024-01888-z] [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: 12/29/2023] [Revised: 05/09/2024] [Accepted: 06/02/2024] [Indexed: 09/11/2024] Open
Abstract
Multicellular organisms are composed of diverse cell types that must coordinate their behaviors through communication. Cell-cell communication (CCC) is essential for growth, development, differentiation, tissue and organ formation, maintenance, and physiological regulation. Cells communicate through direct contact or at a distance using ligand-receptor interactions. So cellular communication encompasses two essential processes: cell signal conduction for generation and intercellular transmission of signals, and cell signal transduction for reception and procession of signals. Deciphering intercellular communication networks is critical for understanding cell differentiation, development, and metabolism. First, we comprehensively review the historical milestones in CCC studies, followed by a detailed description of the mechanisms of signal molecule transmission and the importance of the main signaling pathways they mediate in maintaining biological functions. Then we systematically introduce a series of human diseases caused by abnormalities in cell communication and their progress in clinical applications. Finally, we summarize various methods for monitoring cell interactions, including cell imaging, proximity-based chemical labeling, mechanical force analysis, downstream analysis strategies, and single-cell technologies. These methods aim to illustrate how biological functions depend on these interactions and the complexity of their regulatory signaling pathways to regulate crucial physiological processes, including tissue homeostasis, cell development, and immune responses in diseases. In addition, this review enhances our understanding of the biological processes that occur after cell-cell binding, highlighting its application in discovering new therapeutic targets and biomarkers related to precision medicine. This collective understanding provides a foundation for developing new targeted drugs and personalized treatments.
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Affiliation(s)
- Jimeng Su
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
- Cancer Center, Peking University Third Hospital, Beijing, China
- College of Animal Science and Technology, Yangzhou University, Yangzhou, Jiangsu, China
| | - Ying Song
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
- Cancer Center, Peking University Third Hospital, Beijing, China
| | - Zhipeng Zhu
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
- Cancer Center, Peking University Third Hospital, Beijing, China
| | - Xinyue Huang
- Biomedical Research Institute, Shenzhen Peking University-the Hong Kong University of Science and Technology Medical Center, Shenzhen, China
| | - Jibiao Fan
- College of Animal Science and Technology, Yangzhou University, Yangzhou, Jiangsu, China
| | - Jie Qiao
- State Key Laboratory of Female Fertility Promotion, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China.
- National Clinical Research Center for Obstetrics and Gynecology (Peking University Third Hospital), Beijing, China.
- Key Laboratory of Assisted Reproduction (Peking University), Ministry of Education, Beijing, China.
- Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology, Beijing, China.
| | - Fengbiao Mao
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China.
- Cancer Center, Peking University Third Hospital, Beijing, China.
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44
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Oketch DJA, Giulietti M, Piva F. A Comparison of Tools That Identify Tumor Cells by Inferring Copy Number Variations from Single-Cell Experiments in Pancreatic Ductal Adenocarcinoma. Biomedicines 2024; 12:1759. [PMID: 39200223 PMCID: PMC11351975 DOI: 10.3390/biomedicines12081759] [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: 07/23/2024] [Revised: 08/01/2024] [Accepted: 08/02/2024] [Indexed: 09/02/2024] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) technique has enabled detailed analysis of gene expression at the single cell level, enhancing the understanding of subtle mechanisms that underly pathologies and drug resistance. To derive such biological meaning from sequencing data in oncology, some critical processing must be performed, including identification of the tumor cells by markers and algorithms that infer copy number variations (CNVs). We compared the performance of sciCNV, InferCNV, CopyKAT and SCEVAN tools that identify tumor cells by inferring CNVs from scRNA-seq data. Sequencing data from Pancreatic Ductal Adenocarcinoma (PDAC) patients, adjacent and healthy tissues were analyzed, and the predicted tumor cells were compared to those identified by well-assessed PDAC markers. Results from InferCNV, CopyKAT and SCEVAN overlapped by less than 30% with InferCNV showing the highest sensitivity (0.72) and SCEVAN the highest specificity (0.75). We show that the predictions are highly dependent on the sample and the software used, and that they return so many false positives hence are of little use in verifying or filtering predictions made via tumor biomarkers. We highlight how critical this processing can be, warn against the blind use of these software and point out the great need for more reliable algorithms.
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Affiliation(s)
| | - Matteo Giulietti
- Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, 60131 Ancona, Italy
| | - Francesco Piva
- Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, 60131 Ancona, Italy
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45
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Trocchia M, Ventrici A, Modestino L, Cristinziano L, Ferrara AL, Palestra F, Loffredo S, Capone M, Madonna G, Romanelli M, Ascierto PA, Galdiero MR. Innate Immune Cells in Melanoma: Implications for Immunotherapy. Int J Mol Sci 2024; 25:8523. [PMID: 39126091 PMCID: PMC11313504 DOI: 10.3390/ijms25158523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2024] [Revised: 07/31/2024] [Accepted: 08/01/2024] [Indexed: 08/12/2024] Open
Abstract
The innate immune system, composed of neutrophils, basophils, eosinophils, myeloid-derived suppressor cells (MDSCs), macrophages, dendritic cells (DCs), mast cells (MCs), and innate lymphoid cells (ILCs), is the first line of defense. Growing evidence demonstrates the crucial role of innate immunity in tumor initiation and progression. Several studies support the idea that innate immunity, through the release of pro- and/or anti-inflammatory cytokines and tumor growth factors, plays a significant role in the pathogenesis, progression, and prognosis of cutaneous malignant melanoma (MM). Cutaneous melanoma is the most common skin cancer, with an incidence that rapidly increased in recent decades. Melanoma is a highly immunogenic tumor, due to its high mutational burden. The metastatic form retains a high mortality. The advent of immunotherapy revolutionized the therapeutic approach to this tumor and significantly ameliorated the patients' clinical outcome. In this review, we will recapitulate the multiple roles of innate immune cells in melanoma and the related implications for immunotherapy.
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Affiliation(s)
- Marialuisa Trocchia
- Department of Translational Medical Sciences (DiSMeT), University of Naples Federico II, 80138 Naples, Italy; (M.T.); (A.V.); (A.L.F.); (F.P.); (S.L.)
| | - Annagioia Ventrici
- Department of Translational Medical Sciences (DiSMeT), University of Naples Federico II, 80138 Naples, Italy; (M.T.); (A.V.); (A.L.F.); (F.P.); (S.L.)
| | - Luca Modestino
- Department of Internal Medicine and Clinical Immunology, University Hospital of Naples Federico II, 80138 Naples, Italy;
| | - Leonardo Cristinziano
- Center for Basic and Clinical Immunology Research (CISI), University of Naples Federico II, 80138 Naples, Italy;
| | - Anne Lise Ferrara
- Department of Translational Medical Sciences (DiSMeT), University of Naples Federico II, 80138 Naples, Italy; (M.T.); (A.V.); (A.L.F.); (F.P.); (S.L.)
| | - Francesco Palestra
- Department of Translational Medical Sciences (DiSMeT), University of Naples Federico II, 80138 Naples, Italy; (M.T.); (A.V.); (A.L.F.); (F.P.); (S.L.)
| | - Stefania Loffredo
- Department of Translational Medical Sciences (DiSMeT), University of Naples Federico II, 80138 Naples, Italy; (M.T.); (A.V.); (A.L.F.); (F.P.); (S.L.)
- Center for Basic and Clinical Immunology Research (CISI), University of Naples Federico II, 80138 Naples, Italy;
| | - Mariaelena Capone
- Melanoma, Cancer Immunotherapy, and Development Therapeutics Unit, Istituto Nazionale Tumori IRCCS Fondazione “G. Pascale”, 80138 Naples, Italy; (M.C.); (G.M.); (M.R.); (P.A.A.)
| | - Gabriele Madonna
- Melanoma, Cancer Immunotherapy, and Development Therapeutics Unit, Istituto Nazionale Tumori IRCCS Fondazione “G. Pascale”, 80138 Naples, Italy; (M.C.); (G.M.); (M.R.); (P.A.A.)
| | - Marilena Romanelli
- Melanoma, Cancer Immunotherapy, and Development Therapeutics Unit, Istituto Nazionale Tumori IRCCS Fondazione “G. Pascale”, 80138 Naples, Italy; (M.C.); (G.M.); (M.R.); (P.A.A.)
| | - Paolo Antonio Ascierto
- Melanoma, Cancer Immunotherapy, and Development Therapeutics Unit, Istituto Nazionale Tumori IRCCS Fondazione “G. Pascale”, 80138 Naples, Italy; (M.C.); (G.M.); (M.R.); (P.A.A.)
| | - Maria Rosaria Galdiero
- Department of Translational Medical Sciences (DiSMeT), University of Naples Federico II, 80138 Naples, Italy; (M.T.); (A.V.); (A.L.F.); (F.P.); (S.L.)
- Department of Internal Medicine and Clinical Immunology, University Hospital of Naples Federico II, 80138 Naples, Italy;
- Center for Basic and Clinical Immunology Research (CISI), University of Naples Federico II, 80138 Naples, Italy;
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46
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Yan Y, Zhu S, Jia M, Chen X, Qi W, Gu F, Valencak TG, Liu JX, Sun HZ. Advances in single-cell transcriptomics in animal research. J Anim Sci Biotechnol 2024; 15:102. [PMID: 39090689 PMCID: PMC11295521 DOI: 10.1186/s40104-024-01063-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Accepted: 06/12/2024] [Indexed: 08/04/2024] Open
Abstract
Understanding biological mechanisms is fundamental for improving animal production and health to meet the growing demand for high-quality protein. As an emerging biotechnology, single-cell transcriptomics has been gradually applied in diverse aspects of animal research, offering an effective method to study the gene expression of high-throughput single cells of different tissues/organs in animals. In an unprecedented manner, researchers have identified cell types/subtypes and their marker genes, inferred cellular fate trajectories, and revealed cell‒cell interactions in animals using single-cell transcriptomics. In this paper, we introduce the development of single-cell technology and review the processes, advancements, and applications of single-cell transcriptomics in animal research. We summarize recent efforts using single-cell transcriptomics to obtain a more profound understanding of animal nutrition and health, reproductive performance, genetics, and disease models in different livestock species. Moreover, the practical experience accumulated based on a large number of cases is highlighted to provide a reference for determining key factors (e.g., sample size, cell clustering, and cell type annotation) in single-cell transcriptomics analysis. We also discuss the limitations and outlook of single-cell transcriptomics in the current stage. This paper describes the comprehensive progress of single-cell transcriptomics in animal research, offering novel insights and sustainable advancements in agricultural productivity and animal health.
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Affiliation(s)
- Yunan Yan
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Senlin Zhu
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Minghui Jia
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Xinyi Chen
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Wenlingli Qi
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Fengfei Gu
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
- Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, Zhejiang University, Hangzhou, 310058, China
| | - Teresa G Valencak
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
- Agency for Health and Food Safety Austria, 1220, Vienna, Austria
| | - Jian-Xin Liu
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Hui-Zeng Sun
- Institute of Dairy Science, Ministry of Education Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, China.
- Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, Zhejiang University, Hangzhou, 310058, China.
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47
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Zhang J, Wang E, Li Q, Peng Y, Jin H, Naseem S, Sun B, Park S, Choi S, Li X. GSK3 regulation Wnt/β-catenin signaling affects adipogenesis in bovine skeletal muscle fibro/adipogenic progenitors. Int J Biol Macromol 2024; 275:133639. [PMID: 38969042 DOI: 10.1016/j.ijbiomac.2024.133639] [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: 03/28/2024] [Revised: 05/31/2024] [Accepted: 06/22/2024] [Indexed: 07/07/2024]
Abstract
Clarifying the cellular origin and regulatory mechanisms of intramuscular fat (IMF) deposition is crucial for improving beef quality. Here, we used single-nucleus RNA sequencing to analyze the structure and heterogeneity of skeletal muscle cell populations in different developmental stages of Yanbian cattle and identified eight cell types in two developmental stages of calves and adults. Among them, fibro/adipogenic progenitors (FAPs) expressing CD29 (ITGA7)pos and CD56 (NCAM1)neg surface markers were committed to IMF deposition in beef cattle and expressed major Wnt ligands and receptors. LY2090314/XAV-939 was used to activate/inhibit Wnt/β-catenin signal. The results showed that the blockade of Glycogen Synthase Kinase 3 (GSK3) by LY2090314 promoted the stabilization of β-catenin and reduced the expression of genes related adipogenic differentiation (e.g., PPARγ and C/EBPα) in bovine FAPs, confirming the anti-adipogenic effect of GSK3. XAV-939 inhibition of the Wnt/β-catenin pathway promoted the lipid accumulation capacity of FAPs. Furthermore, we found that blocking GSK3 enhanced the paracrine effects of FAPs-MuSCs and increased myotube formation in muscle satellite cells (MuSCs). Overall, our results outline a single-cell atlas of skeletal muscle development in Yanbian cattle, revealed the role of Wnt/GSK3/β-catenin signaling in FAPs adipogenesis, and provide a theoretical basis for further regulation of bovine IMF deposition.
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Affiliation(s)
- Junfang Zhang
- Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China; Engineering Research Center of North-East Cold Region Beef Cattle Science & Technology Innovation, Ministry of Education, Department of Animal Science, Yanbian University, Yanji 133002, China
| | - Enze Wang
- Engineering Research Center of North-East Cold Region Beef Cattle Science & Technology Innovation, Ministry of Education, Department of Animal Science, Yanbian University, Yanji 133002, China
| | - Qiang Li
- Engineering Research Center of North-East Cold Region Beef Cattle Science & Technology Innovation, Ministry of Education, Department of Animal Science, Yanbian University, Yanji 133002, China
| | - Yinghua Peng
- Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Huaina Jin
- Engineering Research Center of North-East Cold Region Beef Cattle Science & Technology Innovation, Ministry of Education, Department of Animal Science, Yanbian University, Yanji 133002, China
| | - Sajida Naseem
- Engineering Research Center of North-East Cold Region Beef Cattle Science & Technology Innovation, Ministry of Education, Department of Animal Science, Yanbian University, Yanji 133002, China
| | - Bin Sun
- Engineering Research Center of North-East Cold Region Beef Cattle Science & Technology Innovation, Ministry of Education, Department of Animal Science, Yanbian University, Yanji 133002, China
| | - Sungkwon Park
- Department of Food Science and Biotechnology, Sejong University, Seoul 05006, Republic of Korea
| | - Seongho Choi
- Department of Animal Science, Chungbuk National University, Cheongju 28644, Republic of Korea
| | - Xiangzi Li
- Engineering Research Center of North-East Cold Region Beef Cattle Science & Technology Innovation, Ministry of Education, Department of Animal Science, Yanbian University, Yanji 133002, China.
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48
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Chow A, Lareau CA. Concepts and new developments in droplet-based single cell multi-omics. Trends Biotechnol 2024:S0167-7799(24)00184-7. [PMID: 39095258 DOI: 10.1016/j.tibtech.2024.07.006] [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: 02/01/2024] [Revised: 05/31/2024] [Accepted: 07/12/2024] [Indexed: 08/04/2024]
Abstract
Single cell sequencing technologies have become a fixture in the molecular profiling of cells due to their ease, flexibility, and commercial availability. In particular, partitioning individual cells inside oil droplets via microfluidic reactions enables transcriptomic or multi-omic measurements for thousands of cells in parallel. Complementing the multitude of biological discoveries from genomics analyses, the past decade has brought new capabilities from assay baselines to enable a deeper understanding of the complex data from single cell multi-omics. Here, we highlight four innovations that have improved the reliability and understanding of droplet microfluidic assays. We emphasize new developments that further orient principles of technology development and guidelines for the design, benchmarking, and implementation of new droplet-based methodologies.
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Affiliation(s)
- Arthur Chow
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Caleb A Lareau
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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49
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Tindall RR, Yang Y, Hernandez I, Qin A, Li J, Zhang Y, Gomez TH, Younes M, Shen Q, Bailey-Lundberg JM, Zhao Z, Kraushaar D, Castro P, Cao Y, Zheng WJ, Ko TC. Aging- and alcohol-associated spatial transcriptomic signature in mouse acute pancreatitis reveals heterogeneity of inflammation and potential pathogenic factors. J Mol Med (Berl) 2024; 102:1051-1061. [PMID: 38940937 PMCID: PMC11269349 DOI: 10.1007/s00109-024-02460-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 03/15/2024] [Accepted: 06/07/2024] [Indexed: 06/29/2024]
Abstract
The rapidly aging population is consuming more alcohol, leading to increased alcohol-associated acute pancreatitis (AAP) with high mortality. However, the mechanisms remain undefined, and currently there are no effective therapies available. This study aims to elucidate aging- and alcohol-associated spatial transcriptomic signature by establishing an aging AAP mouse model and applying Visium spatial transcriptomics for understanding of the mechanisms in the context of the pancreatic tissue. Upon alcohol diet feeding and caerulein treatment, aging mice (18 months) developed significantly more severe AAP with 5.0-fold increase of injury score and 2.4-fold increase of amylase compared to young mice (3 months). Via Visium spatial transcriptomics, eight distinct tissue clusters were revealed from aggregated transcriptomes of aging and young AAP mice: five acinar, two stromal, and one islet, which were then merged into three clusters: acinar, stromal, and islet for the comparative analysis. Compared to young AAP mice, > 1300 differentially expressed genes (DEGs) and approximately 3000 differentially regulated pathways were identified in aging AAP mice. The top five DEGs upregulated in aging AAP mice include Mmp8, Ppbp, Serpina3m, Cxcl13, and Hamp with heterogeneous distributions among the clusters. Taken together, this study demonstrates spatial heterogeneity of inflammatory processes in aging AAP mice, offering novel insights into the mechanisms and potential drivers for AAP development. KEY MESSAGES: Mechanisms regarding high mortality of AAP in aging remain undefined. An aging AAP mouse model was developed recapturing clinical exhibition in humans. Spatial transcriptomics identified contrasted DEGs in aging vs. young AAP mice. Top five DEGs were Mmp8, Ppbp, Serpina3m, Cxcl13, and Hamp in aging vs. young AAP mice. Our findings shed insights for identification of molecular drivers in aging AAP.
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Affiliation(s)
- Rachel R Tindall
- Department of Surgery, UTHealth at Houston, Houston, TX, 77030, USA
| | - Yuntao Yang
- McWilliams School of Biomedical Informatics, UTHealth at Houston, Houston, TX, 77030, USA
| | | | - Amy Qin
- Department of Surgery, UTHealth at Houston, Houston, TX, 77030, USA
| | - Jiajing Li
- Department of Surgery, UTHealth at Houston, Houston, TX, 77030, USA
| | - Yinjie Zhang
- Department of Surgery, UTHealth at Houston, Houston, TX, 77030, USA
| | - Thomas H Gomez
- Center for Laboratory Animal Medicine and Care, UTHealth at Houston, Houston, TX, 77030, USA
| | - Mamoun Younes
- Department of Pathology, George Washington University School of Medicine and Health Sciences, Washington, DC, 20037, USA
| | - Qiang Shen
- Department of Interdisciplinary Oncology, Louisiana State Univ. Health Sciences Center, New Orleans, LA, 70112, USA
| | - Jennifer M Bailey-Lundberg
- Department of Anesthesiology, Critical Care and Pain Medicine, UTHealth at Houston, Houston, TX, 77030, USA
| | - Zhongming Zhao
- Center for Precision Health, McWilliams School of Biomedical Informatics, UTHealth at Houston, Houston, TX, 77030, USA
| | - Daniel Kraushaar
- Genomic and RNA Profiling Core, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Patricia Castro
- Human Tissue Acquisition & Pathology Core, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Yanna Cao
- Department of Surgery, UTHealth at Houston, Houston, TX, 77030, USA.
| | - W Jim Zheng
- McWilliams School of Biomedical Informatics, UTHealth at Houston, Houston, TX, 77030, USA.
| | - Tien C Ko
- Department of Surgery, UTHealth at Houston, Houston, TX, 77030, USA.
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50
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Jia H, Wang W, Zhou Z, Chen Z, Lan Z, Bo H, Fan L. Single-cell RNA sequencing technology in human spermatogenesis: Progresses and perspectives. Mol Cell Biochem 2024; 479:2017-2033. [PMID: 37659974 DOI: 10.1007/s11010-023-04840-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/14/2023] [Indexed: 09/04/2023]
Abstract
Spermatogenesis, a key part of the spermiation process, is regulated by a combination of key cells, such as primordial germ cells, spermatogonial stem cells, and somatic cells, such as Sertoli cells. Abnormal spermatogenesis can lead to azoospermia, testicular tumors, and other diseases related to male infertility. The application of single-cell RNA sequencing (scRNA-seq) technology in male reproduction is gradually increasing with its unique insight into deep mining and analysis. The data cover different periods of neonatal, prepubertal, pubertal, and adult stages. Different types of male infertility diseases including obstructive and non-obstructive azoospermia (NOA), Klinefelter Syndrome (KS), Sertoli Cell Only Syndrome (SCOS), and testicular tumors are also covered. We briefly review the principles and application of scRNA-seq and summarize the research results and application directions in spermatogenesis in different periods and pathological states. Moreover, we discuss the challenges of applying this technology in male reproduction and the prospects of combining it with other technologies.
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Affiliation(s)
- Hanbo Jia
- NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Institute of Reproductive and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China
| | - Wei Wang
- NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Institute of Reproductive and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China
| | - Zhaowen Zhou
- NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Institute of Reproductive and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China
| | - Zhiyi Chen
- NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Institute of Reproductive and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China
| | - Zijun Lan
- NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Institute of Reproductive and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China
| | - Hao Bo
- NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Institute of Reproductive and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China.
- Clinical Research Center for Reproduction and Genetics in Hunan Province, Reproductive and Genetic Hospital of CITIC-Xiangya, Changsha, Hunan, China.
| | - Liqing Fan
- NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Institute of Reproductive and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan, China.
- Clinical Research Center for Reproduction and Genetics in Hunan Province, Reproductive and Genetic Hospital of CITIC-Xiangya, Changsha, Hunan, China.
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