1
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Gupta P, O’Neill H, Wolvetang E, Chatterjee A, Gupta I. Advances in single-cell long-read sequencing technologies. NAR Genom Bioinform 2024; 6:lqae047. [PMID: 38774511 PMCID: PMC11106032 DOI: 10.1093/nargab/lqae047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 04/18/2024] [Accepted: 04/29/2024] [Indexed: 05/24/2024] Open
Abstract
With an increase in accuracy and throughput of long-read sequencing technologies, they are rapidly being assimilated into the single-cell sequencing pipelines. For transcriptome sequencing, these techniques provide RNA isoform-level information in addition to the gene expression profiles. Long-read sequencing technologies not only help in uncovering complex patterns of cell-type specific splicing, but also offer unprecedented insights into the origin of cellular complexity and thus potentially new avenues for drug development. Additionally, single-cell long-read DNA sequencing enables high-quality assemblies, structural variant detection, haplotype phasing, resolving high-complexity regions, and characterization of epigenetic modifications. Given that significant progress has primarily occurred in single-cell RNA isoform sequencing (scRiso-seq), this review will delve into these advancements in depth and highlight the practical considerations and operational challenges, particularly pertaining to downstream analysis. We also aim to offer a concise introduction to complementary technologies for single-cell sequencing of the genome, epigenome and epitranscriptome. We conclude by identifying certain key areas of innovation that may drive these technologies further and foster more widespread application in biomedical science.
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Affiliation(s)
- Pallavi Gupta
- University of Queensland – IIT Delhi Research Academy, Hauz Khas, New Delhi 110016, India
- Australian Institute of Bioengineering and Nanotechnology (AIBN), The University of Queensland, St Lucia, QLD 4072, Australia
- Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India
| | - Hannah O’Neill
- Department of Pathology, Dunedin School of Medicine, University of Otago, 58 Hanover Street, Dunedin 9054, New Zealand
| | - Ernst J Wolvetang
- Australian Institute of Bioengineering and Nanotechnology (AIBN), The University of Queensland, St Lucia, QLD 4072, Australia
| | - Aniruddha Chatterjee
- Department of Pathology, Dunedin School of Medicine, University of Otago, 58 Hanover Street, Dunedin 9054, New Zealand
| | - Ishaan Gupta
- Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India
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2
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Zhu M, Yi Y, Jiang K, Liang Y, Li L, Zhang F, Zheng X, Yin H. Single-cell combined with transcriptome sequencing to explore the molecular mechanism of cell communication in idiopathic pulmonary fibrosis. J Cell Mol Med 2024; 28:e18499. [PMID: 38887981 PMCID: PMC11184282 DOI: 10.1111/jcmm.18499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 05/14/2024] [Accepted: 06/08/2024] [Indexed: 06/20/2024] Open
Abstract
Idiopathic pulmonary fibrosis (IPF) is a common, chronic, and progressive lung disease that severely impacts human health and survival. However, the intricate molecular underpinnings of IPF remains elusive. This study aims to delve into the nuanced molecular interplay of cellular interactions in IPF, thereby laying the groundwork for innovative therapeutic approaches in the clinical field of IPF. Sophisticated bioinformatics methods were employed to identify crucial biomarkers essential for the progression of IPF. The GSE122960 single-cell dataset was obtained from the Gene Expression Omnibus (GEO) compendium, and intercellular communication potentialities were scrutinized via CellChat. The random survival forest paradigm was established using the GSE70866 dataset. Quintessential genes were selected through Kaplan-Meier (KM) curves, while immune infiltration examinations, functional enrichment critiques and nomogram paradigms were inaugurated. Analysis of intercellular communication revealed an intimate potential connections between macrophages and various cell types, pinpointing five cardinal genes influencing the trajectory and prognosis of IPF. The nomogram paradigm, sculpted from these seminal genes, exhibits superior predictive prowess. Our research meticulously identified five critical genes, confirming their intimate association with the prognosis, immune infiltration and transcriptional governance of IPF. Interestingly, we discerned these genes' engagement with the EPITHELIAL_MESENCHYMAL_TRANSITION signalling pathway, which may enhance our understanding of the molecular complexity of IPF.
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Affiliation(s)
- Minggao Zhu
- Intensive Care UnitThe First Affiliated Hospital of Jinan UniversityGuangzhouGuangdongChina
| | - Yuhu Yi
- Intensive Care UnitThe First Affiliated Hospital of Jinan UniversityGuangzhouGuangdongChina
| | - Kui Jiang
- Department of NephrologyThe First Affiliated Hospital of Jinan UniversityGuangzhouGuangdongChina
| | - Yongzhi Liang
- Intensive Care UnitThe First Affiliated Hospital of Jinan UniversityGuangzhouGuangdongChina
| | - Lijun Li
- Intensive Care UnitThe First Affiliated Hospital of Jinan UniversityGuangzhouGuangdongChina
| | - Feng Zhang
- Intensive Care UnitThe First Affiliated Hospital of Jinan UniversityGuangzhouGuangdongChina
| | - Xinglong Zheng
- Intensive Care UnitThe First Affiliated Hospital of Jinan UniversityGuangzhouGuangdongChina
| | - Haiyan Yin
- Intensive Care UnitThe First Affiliated Hospital of Jinan UniversityGuangzhouGuangdongChina
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3
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Zhang YF, Yi ZJ, Zhang WF, Yang L, Qi F, Yu T, Zhu Z, Li MJ, Cheng Y, Zhao L, Gong JP, Li PZ. Single-Cell Sequencing Reveals MYOF-Enriched Monocyte/Macrophage Subcluster as a Favorable Prognostic Factor in Sepsis. Adv Biol (Weinh) 2024; 8:e2300673. [PMID: 38456367 DOI: 10.1002/adbi.202300673] [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: 12/10/2023] [Revised: 02/13/2024] [Indexed: 03/09/2024]
Abstract
This research utilized single-cell RNA sequencing to map the immune cell landscape in sepsis, revealing 28 distinct cell clusters and categorizing them into nine major types. Delving into the monocyte/macrophage subclusters, 12 unique subclusters are identified and pathway enrichment analyses are conducted using KEGG and GO, discovering enriched pathways such as oxidative phosphorylation and antigen processing. Further GSVA and AUCell assessments show varied activation of interferon pathways, especially in subclusters 4 and 11. The clinical correlation analysis reveals genes significantly linked to survival outcomes. Additionally, cellular differentiation in these subclusters is explored. Building on these insights, the differential gene expression within these subclusters is specifically scrutinized, which reveal MYOF as a key gene with elevated expression levels in the survivor group. This finding is further supported by in-depth pathway enrichment analysis and the examination of cellular differentiation trajectories, where MYOF's role became evident in the context of immune response regulation and sepsis progression. Validating the role of the MYOF gene in sepsis, a dose-dependent response to LPS in THP-1 cells and C57 mice is observed. Finally, inter-cellular communications are analyzed, particularly focusing on the MYOF+Mono/Macro subcluster, which indicates a pivotal role in immune regulation and potential therapeutic targeting.
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Affiliation(s)
- Yi-Fan Zhang
- Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Zhu-Jun Yi
- Department of Hepatobiliary Surgery, Chongqing University Three Gorges Hospital, Chongqing, 404100, China
| | - Wen-Feng Zhang
- Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Lian Yang
- Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Feng Qi
- Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Ting Yu
- Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Zhu Zhu
- Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Ming-Jie Li
- Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Yao Cheng
- Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Lei Zhao
- Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Jian-Ping Gong
- Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
| | - Pei-Zhi Li
- Department of Hepatobiliary Surgery, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China
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4
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Köhler AR, Haußer J, Harsch A, Bernhardt S, Häußermann L, Brenner LM, Lungu C, Olayioye MA, Bashtrykov P, Jeltsch A. Modular dual-color BiAD sensors for locus-specific readout of epigenome modifications in single cells. CELL REPORTS METHODS 2024; 4:100739. [PMID: 38554702 PMCID: PMC11045877 DOI: 10.1016/j.crmeth.2024.100739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 02/01/2024] [Accepted: 02/28/2024] [Indexed: 04/02/2024]
Abstract
Dynamic changes in the epigenome at defined genomic loci play crucial roles during cellular differentiation and disease development. Here, we developed dual-color bimolecular anchor detector (BiAD) sensors for high-sensitivity readout of locus-specific epigenome modifications by fluorescence microscopy. Our BiAD sensors comprise an sgRNA/dCas9 complex as anchor and double chromatin reader domains as detector modules, both fused to complementary parts of a split IFP2.0 fluorophore, enabling its reconstitution upon binding of both parts in close proximity. In addition, a YPet fluorophore is recruited to the sgRNA to mark the genomic locus of interest. With these dual-color BiAD sensors, we detected H3K9me2/3 and DNA methylation and their dynamic changes upon RNAi or inhibitor treatment with high sensitivity at endogenous genomic regions. Furthermore, we showcased locus-specific H3K36me2/3 readout as well as H3K27me3 and H3K9me2/3 enrichment on the inactive X chromosome, highlighting the broad applicability of our dual-color BiAD sensors for single-cell epigenome studies.
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Affiliation(s)
- Anja R Köhler
- Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Johannes Haußer
- Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Annika Harsch
- Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Steffen Bernhardt
- Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Lilia Häußermann
- Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Lisa-Marie Brenner
- Institute of Cell Biology and Immunology, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Cristiana Lungu
- Institute of Cell Biology and Immunology, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Monilola A Olayioye
- Institute of Cell Biology and Immunology, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Pavel Bashtrykov
- Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany
| | - Albert Jeltsch
- Institute of Biochemistry and Technical Biochemistry, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany.
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5
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Shen W, Liu C, Hu Y, Lei Y, Wong HS, Wu S, Zhou XM. Leveraging cross-source heterogeneity to improve the performance of bulk gene expression deconvolution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.07.588458. [PMID: 38645128 PMCID: PMC11030304 DOI: 10.1101/2024.04.07.588458] [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
A main limitation of bulk transcriptomic technologies is that individual measurements normally contain contributions from multiple cell populations, impeding the identification of cellular heterogeneity within diseased tissues. To extract cellular insights from existing large cohorts of bulk transcriptomic data, we present CSsingle, a novel method designed to accurately deconvolve bulk data into a predefined set of cell types using a scRNA-seq reference. Through comprehensive benchmark evaluations and analyses using diverse real data sets, we reveal the systematic bias inherent in existing methods, stemming from differences in cell size or library size. Our extensive experiments demonstrate that CSsingle exhibits superior accuracy and robustness compared to leading methods, particularly when dealing with bulk mixtures originating from cell types of markedly different cell sizes, as well as when handling bulk and single-cell reference data obtained from diverse sources. Our work provides an efficient and robust methodology for the integrated analysis of bulk and scRNA-seq data, facilitating various biological and clinical studies.
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Affiliation(s)
- Wenjun Shen
- Department of Bioinformatics, Shantou University Medical College, Shantou, Guangdong 515041, China
| | - Cheng Liu
- Department of Computer Science, Shantou University, Shantou, Guangdong 515041, China
| | - Yunfei Hu
- Department of Computer Science, Vanderbilt University, Nashville, TN 37235, USA
| | - Yuanfang Lei
- Department of Bioinformatics, Shantou University Medical College, Shantou, Guangdong 515041, China
| | - Hau-San Wong
- Department of Computer Sciences, City University of Hong Kong, Kowloon, Hong Kong
| | - Si Wu
- Department of Computer Science, South China University of Technology, Guangzhou, Guangdong 510006, China
| | - Xin Maizie Zhou
- Department of Computer Science, Vanderbilt University, Nashville, TN 37235, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
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6
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Jeong M, Choi JH, Jang H, Sohn DH, Wang Q, Lee J, Yao L, Lee EJ, Fan J, Pratelli M, Wang EH, Snyder CN, Wang XY, Shin S, Gittis AH, Sung TC, Spitzer NC, Lim BK. Viral vector-mediated transgene delivery with novel recombinase systems for targeting neuronal populations defined by multiple features. Neuron 2024; 112:56-72.e4. [PMID: 37909037 PMCID: PMC10916502 DOI: 10.1016/j.neuron.2023.09.038] [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: 07/18/2022] [Revised: 05/21/2023] [Accepted: 09/26/2023] [Indexed: 11/02/2023]
Abstract
A comprehensive understanding of neuronal diversity and connectivity is essential for understanding the anatomical and cellular mechanisms that underlie functional contributions. With the advent of single-cell analysis, growing information regarding molecular profiles leads to the identification of more heterogeneous cell types. Therefore, the need for additional orthogonal recombinase systems is increasingly apparent, as heterogeneous tissues can be further partitioned into increasing numbers of specific cell types defined by multiple features. Critically, new recombinase systems should work together with pre-existing systems without cross-reactivity in vivo. Here, we introduce novel site-specific recombinase systems based on ΦC31 bacteriophage recombinase for labeling multiple cell types simultaneously and a novel viral strategy for versatile and robust intersectional expression of any transgene. Together, our system will help researchers specifically target different cell types with multiple features in the same animal.
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Affiliation(s)
- Minju Jeong
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Jun-Hyeok Choi
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Hyeonseok Jang
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Dong Hyun Sohn
- Department of Microbiology and Immunology, Pusan National University School of Medicine, Yangsan 50612, Republic of Korea
| | - Qingdi Wang
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Joann Lee
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Li Yao
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Eun Ji Lee
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Jiachen Fan
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Marta Pratelli
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Eric H Wang
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Christen N Snyder
- Department of Biological Sciences and Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Xiao-Yun Wang
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Sora Shin
- Center for Neurobiology Research, Fralin Biomedical Research Institute at Virginia Tech Carilion, Virginia Tech, Roanoke, VA, USA; Department of Human Nutrition, Foods, and Exercise, Virginia Tech, Blacksburg, VA, USA
| | - Aryn H Gittis
- Department of Biological Sciences and Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Tsung-Chang Sung
- Transgenic Core, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Nicholas C Spitzer
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Byung Kook Lim
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, USA.
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7
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Zou DD, Sun YZ, Li XJ, Wu WJ, Xu D, He YT, Qi J, Tu Y, Tang Y, Tu YH, Wang XL, Li X, Lu FY, Huang L, Long H, He L, Li X. Single-cell sequencing highlights heterogeneity and malignant progression in actinic keratosis and cutaneous squamous cell carcinoma. eLife 2023; 12:e85270. [PMID: 38099574 PMCID: PMC10783873 DOI: 10.7554/elife.85270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 12/14/2023] [Indexed: 01/12/2024] Open
Abstract
Cutaneous squamous cell carcinoma (cSCC) is the second most frequent of the keratinocyte-derived malignancies with actinic keratosis (AK) as a precancerous lesion. To comprehensively delineate the underlying mechanisms for the whole progression from normal skin to AK to invasive cSCC, we performed single-cell RNA sequencing (scRNA-seq) to acquire the transcriptomes of 138,982 cells from 13 samples of six patients including AK, squamous cell carcinoma in situ (SCCIS), cSCC, and their matched normal tissues, covering comprehensive clinical courses of cSCC. We identified diverse cell types, including important subtypes with different gene expression profiles and functions in major keratinocytes. In SCCIS, we discovered the malignant subtypes of basal cells with differential proliferative and migration potential. Differentially expressed genes (DEGs) analysis screened out multiple key driver genes including transcription factors along AK to cSCC progression. Immunohistochemistry (IHC)/immunofluorescence (IF) experiments and single-cell ATAC sequencing (scATAC-seq) data verified the expression changes of these genes. The functional experiments confirmed the important roles of these genes in regulating cell proliferation, apoptosis, migration, and invasion in cSCC tumor. Furthermore, we comprehensively described the tumor microenvironment (TME) landscape and potential keratinocyte-TME crosstalk in cSCC providing theoretical basis for immunotherapy. Together, our findings provide a valuable resource for deciphering the progression from AK to cSCC and identifying potential targets for anticancer treatment of cSCC.
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Affiliation(s)
- Dan-Dan Zou
- Department of Dermatology, First Affiliated Hospital of Kunming Medical UniversityYunnanChina
- Department of Dermatology, The Affiliated Hospital of Kunming University of Science and Technology, The First People's Hospital of Yunnan Province, KunmingYunnanChina
| | - Ya-Zhou Sun
- Clinical Big Data Research Center, The Seventh Affiliated Hospital of Sun Yat-sen UniversityShenzhen, GuangdongChina
- School of Medical, Shenzhen Campus of Sun Yat-sen UniversityShenzhen, GuangdongChina
| | - Xin-Jie Li
- School of Medical, Shenzhen Campus of Sun Yat-sen UniversityShenzhen, GuangdongChina
| | - Wen-Juan Wu
- Department of Dermatology, First Affiliated Hospital of Kunming Medical UniversityYunnanChina
| | - Dan Xu
- Department of Dermatology, First Affiliated Hospital of Kunming Medical UniversityYunnanChina
| | - Yu-Tong He
- School of Medical, Shenzhen Campus of Sun Yat-sen UniversityShenzhen, GuangdongChina
| | - Jue Qi
- Department of Dermatology, First Affiliated Hospital of Kunming Medical UniversityYunnanChina
| | - Ying Tu
- Department of Dermatology, First Affiliated Hospital of Kunming Medical UniversityYunnanChina
| | - Yang Tang
- Department of Dermatology, First Affiliated Hospital of Kunming Medical UniversityYunnanChina
| | - Yun-Hua Tu
- Department of Dermatology, First Affiliated Hospital of Kunming Medical UniversityYunnanChina
| | - Xiao-Li Wang
- Department of Dermatology, Changzheng Hospital, Naval Medical UniversityShanghaiChina
| | - Xing Li
- Department of Dermatology, People's Hospital of Chuxiong Yi Autonomous Prefecture, ChuxiongYunnanChina
| | - Feng-Yan Lu
- Department of Dermatology, Qujing Affiliated Hospital of Kunming Medical University, The First People’s Hospital of QujingYunnanChina
| | - Ling Huang
- Department of Dermatology, First Affiliated Hospital of Dali University, DaliYunnanChina
| | - Heng Long
- Wenshan Zhuang and Miao Autonomous Prefecture Dermatology Clinic, Wenshan Zhuang and Miao Autonomous Prefecture Specialist Hospital of Dermatology, WenshanYunnanChina
| | - Li He
- Department of Dermatology, First Affiliated Hospital of Kunming Medical UniversityYunnanChina
| | - Xin Li
- School of Medical, Shenzhen Campus of Sun Yat-sen UniversityShenzhen, GuangdongChina
- Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen UniversityGuangdongChina
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8
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Lu H, Zhang H, Li L. Chemical tagging mass spectrometry: an approach for single-cell omics. Anal Bioanal Chem 2023; 415:6901-6913. [PMID: 37466681 PMCID: PMC10729908 DOI: 10.1007/s00216-023-04850-0] [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: 04/10/2023] [Revised: 07/04/2023] [Accepted: 07/06/2023] [Indexed: 07/20/2023]
Abstract
Single-cell (SC) analysis offers new insights into the study of fundamental biological phenomena and cellular heterogeneity. The superior sensitivity, high throughput, and rich chemical information provided by mass spectrometry (MS) allow MS to emerge as a leading technology for molecular profiling of SC omics, including the SC metabolome, lipidome, and proteome. However, issues such as ionization suppression, low concentration, and huge span of dynamic concentrations of SC components lead to poor MS response for certain types of molecules. It is noted that chemical tagging/derivatization has been adopted in SCMS analysis, and this strategy has been proven an effective solution to circumvent these issues in SCMS analysis. Herein, we review the basic principle and general strategies of chemical tagging/derivatization in SCMS analysis, along with recent applications of chemical derivatization to single-cell metabolomics and multiplexed proteomics, as well as SCMS imaging. Furthermore, the challenges and opportunities for the improvement of chemical derivatization strategies in SCMS analysis are discussed.
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Affiliation(s)
- Haiyan Lu
- School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Hua Zhang
- School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Lingjun Li
- School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA.
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA.
- Lachman Institute for Pharmaceutical Development, School of Pharmacy, University of Wisconsin-Madison, Madison, WI, 53705, USA.
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9
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Gao MY, Wang JQ, He J, Gao R, Zhang Y, Li X. Single-Cell RNA-Sequencing in Astrocyte Development, Heterogeneity, and Disease. Cell Mol Neurobiol 2023; 43:3449-3464. [PMID: 37552355 DOI: 10.1007/s10571-023-01397-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Accepted: 07/29/2023] [Indexed: 08/09/2023]
Abstract
Astrocytes are the most plentiful cell type in the central nervous system (CNS) and perform complicated functions in health and disease. It is obvious that different astrocyte subpopulations, or activation states, are relevant with specific genomic programs and functions. In recent years, the emergence of new technologies such as single-cell RNA sequencing (scRNA-seq) has made substantial advance in the characterization of astrocyte heterogeneity, astrocyte developmental trajectory, and its role in CNS diseases which has had a significant impact on neuroscience. In this review, we present an overview of astrocyte development, heterogeneity, and its essential role in the physiological and pathological environments of the CNS. We focused on the critical role of single-cell sequencing in revealing astrocyte development, heterogeneity, and its role in different CNS diseases.
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Affiliation(s)
- Meng-Yuan Gao
- A National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, Key Laboratory of Medicinal Resources and Natural Pharmaceutical Chemistry (Shaanxi Normal University), The Ministry of Education, College of Life Sciences, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China
| | - Jia-Qi Wang
- A National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, Key Laboratory of Medicinal Resources and Natural Pharmaceutical Chemistry (Shaanxi Normal University), The Ministry of Education, College of Life Sciences, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China
| | - Jin He
- A National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, Key Laboratory of Medicinal Resources and Natural Pharmaceutical Chemistry (Shaanxi Normal University), The Ministry of Education, College of Life Sciences, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China
| | - Rui Gao
- A National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, Key Laboratory of Medicinal Resources and Natural Pharmaceutical Chemistry (Shaanxi Normal University), The Ministry of Education, College of Life Sciences, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China
| | - Yuan Zhang
- A National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, Key Laboratory of Medicinal Resources and Natural Pharmaceutical Chemistry (Shaanxi Normal University), The Ministry of Education, College of Life Sciences, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China
| | - Xing Li
- A National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, Key Laboratory of Medicinal Resources and Natural Pharmaceutical Chemistry (Shaanxi Normal University), The Ministry of Education, College of Life Sciences, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China.
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10
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An Z, Liu W, Li W, Wei M, An C. Application of single-cell RNA sequencing in head and neck squamous cell carcinoma. Chin J Cancer Res 2023; 35:331-342. [PMID: 37691894 PMCID: PMC10485914 DOI: 10.21147/j.issn.1000-9604.2023.04.01] [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: 07/07/2023] [Accepted: 08/21/2023] [Indexed: 09/12/2023] Open
Abstract
Single-cell RNA sequencing has been broadly applied to head and neck squamous cell carcinoma (HNSCC) for characterizing the heterogeneity and genomic mutations of HNSCC benefiting from the advantage of single-cell resolution. We summarized most of the current studies and aimed to explore their research methods and ideas, as well as how to transform them into clinical applications. Through single-cell RNA sequencing, we found the differences in tumor cells' expression programs and differentiation tracks. The studies of immune microenvironment allowed us to distinguish immune cell subpopulations, the extensive expression of immune checkpoints, and the complex crosstalk network between immune cells and non-immune cells. For cancer-associated fibroblasts (CAFs), single-cell RNA sequencing had made an irreplaceable contribution to the exploration of their differentiation status, specific CAFs markers, and the interaction with tumor cells and immune cells. In addition, we demonstrated in detail how single-cell RNA sequencing explored the HNSCC epithelial-to-mesenchymal transition (EMT) model and the mechanism of drug resistance, as well as its clinical value.
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Affiliation(s)
- Zhaohong An
- Department of Head & Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Wan Liu
- Department of Head & Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen Center, Shenzhen 518000, China
| | - Wenbin Li
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Minghui Wei
- Department of Head & Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen Center, Shenzhen 518000, China
| | - Changming An
- Department of Head & Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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11
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Hegarty C, Neto N, Cahill P, Floudas A. Computational approaches in rheumatic diseases - Deciphering complex spatio-temporal cell interactions. Comput Struct Biotechnol J 2023; 21:4009-4020. [PMID: 37649712 PMCID: PMC10462794 DOI: 10.1016/j.csbj.2023.08.005] [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: 04/04/2023] [Revised: 08/04/2023] [Accepted: 08/04/2023] [Indexed: 09/01/2023] Open
Abstract
Inflammatory arthritis, including rheumatoid (RA), and psoriatic (PsA) arthritis, are clinically and immunologically heterogeneous diseases with no identified cure. Chronic inflammation of the synovial tissue ushers loss of function of the joint that severely impacts the patient's quality of life, eventually leading to disability and life-threatening comorbidities. The pathogenesis of synovial inflammation is the consequence of compounded immune and stromal cell interactions influenced by genetic and environmental factors. Deciphering the complexity of the synovial cellular landscape has accelerated primarily due to the utilisation of bulk and single cell RNA sequencing. Particularly the capacity to generate cell-cell interaction networks could reveal evidence of previously unappreciated processes leading to disease. However, there is currently a lack of universal nomenclature as a result of varied experimental and technological approaches that discombobulates the study of synovial inflammation. While spatial transcriptomic analysis that combines anatomical information with transcriptomic data of synovial tissue biopsies promises to provide more insights into disease pathogenesis, in vitro functional assays with single-cell resolution will be required to validate current bioinformatic applications. In order to provide a comprehensive approach and translate experimental data to clinical practice, a combination of clinical and molecular data with machine learning has the potential to enhance patient stratification and identify individuals at risk of arthritis that would benefit from early therapeutic intervention. This review aims to provide a comprehensive understanding of the effect of computational approaches in deciphering synovial inflammation pathogenesis and discuss the impact that further experimental and novel computational tools may have on therapeutic target identification and drug development.
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Affiliation(s)
- Ciara Hegarty
- Translational Immunology lab, School of Biotechnology, Dublin City University, Dublin, Ireland
| | - Nuno Neto
- Trinity Centre for Biomedical Engineering, Trinity College Dublin, Ireland
| | - Paul Cahill
- Vascular Biology lab, School of Biotechnology, Dublin City University, Dublin, Ireland
| | - Achilleas Floudas
- Translational Immunology lab, School of Biotechnology, Dublin City University, Dublin, Ireland
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12
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Heydari AA, Sindi SS. Deep learning in spatial transcriptomics: Learning from the next next-generation sequencing. BIOPHYSICS REVIEWS 2023; 4:011306. [PMID: 38505815 PMCID: PMC10903438 DOI: 10.1063/5.0091135] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 12/19/2022] [Indexed: 03/21/2024]
Abstract
Spatial transcriptomics (ST) technologies are rapidly becoming the extension of single-cell RNA sequencing (scRNAseq), holding the potential of profiling gene expression at a single-cell resolution while maintaining cellular compositions within a tissue. Having both expression profiles and tissue organization enables researchers to better understand cellular interactions and heterogeneity, providing insight into complex biological processes that would not be possible with traditional sequencing technologies. Data generated by ST technologies are inherently noisy, high-dimensional, sparse, and multi-modal (including histological images, count matrices, etc.), thus requiring specialized computational tools for accurate and robust analysis. However, many ST studies currently utilize traditional scRNAseq tools, which are inadequate for analyzing complex ST datasets. On the other hand, many of the existing ST-specific methods are built upon traditional statistical or machine learning frameworks, which have shown to be sub-optimal in many applications due to the scale, multi-modality, and limitations of spatially resolved data (such as spatial resolution, sensitivity, and gene coverage). Given these intricacies, researchers have developed deep learning (DL)-based models to alleviate ST-specific challenges. These methods include new state-of-the-art models in alignment, spatial reconstruction, and spatial clustering, among others. However, DL models for ST analysis are nascent and remain largely underexplored. In this review, we provide an overview of existing state-of-the-art tools for analyzing spatially resolved transcriptomics while delving deeper into the DL-based approaches. We discuss the new frontiers and the open questions in this field and highlight domains in which we anticipate transformational DL applications.
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13
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Khare K, Pandey R. Cellular heterogeneity in disease severity and clinical outcome: Granular understanding of immune response is key. Front Immunol 2022; 13:973070. [PMID: 36072602 PMCID: PMC9441806 DOI: 10.3389/fimmu.2022.973070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 07/26/2022] [Indexed: 12/15/2022] Open
Abstract
During an infectious disease progression, it is crucial to understand the cellular heterogeneity underlying the differential immune response landscape that will augment the precise information of the disease severity modulators, leading to differential clinical outcome. Patients with COVID-19 display a complex yet regulated immune profile with a heterogeneous array of clinical manifestation that delineates disease severity sub-phenotypes and worst clinical outcomes. Therefore, it is necessary to elucidate/understand/enumerate the role of cellular heterogeneity during COVID-19 disease to understand the underlying immunological mechanisms regulating the disease severity. This article aims to comprehend the current findings regarding dysregulation and impairment of immune response in COVID-19 disease severity sub-phenotypes and relate them to a wide array of heterogeneous populations of immune cells. On the basis of the findings, it suggests a possible functional correlation between cellular heterogeneity and the COVID-19 disease severity. It highlights the plausible modulators of age, gender, comorbidities, and hosts' genetics that may be considered relevant in regulating the host response and subsequently the COVID-19 disease severity. Finally, it aims to highlight challenges in COVID-19 disease that can be achieved by the application of single-cell genomics, which may aid in delineating the heterogeneity with more granular understanding. This will augment our future pandemic preparedness with possibility to identify the subset of patients with increased diseased severity.
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Affiliation(s)
- Kriti Khare
- Immunology and Infectious Disease Biology, INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) laboratory, CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Rajesh Pandey
- Immunology and Infectious Disease Biology, INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) laboratory, CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
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14
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Gao G, Deng A, Liang S, Liu S, Fu X, Zhao X, Yu Z. Integration of Bulk RNA Sequencing and Single-Cell RNA Sequencing to Reveal Uveal Melanoma Tumor Heterogeneity and Cells Related to Survival. Front Immunol 2022; 13:898925. [PMID: 35865532 PMCID: PMC9294459 DOI: 10.3389/fimmu.2022.898925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 06/06/2022] [Indexed: 11/13/2022] Open
Abstract
Molecular classification based on transcriptional characteristics is often used to study tumor heterogeneity. Human cancer has different cell populations with distinct transcription in tumors, and their heterogeneity is the focus of tumor therapy. Our purpose was to explore the tumor heterogeneity of uveal melanoma (UM) through RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq). Based on the consensus clustering assays of the prognosis-related immune gene set, the immune subtype (IS) of UM and its corresponding immune characteristics were comprehensively analyzed. The heterogeneous cell groups and corresponding marker genes of UM were identified from GSE138433 using scRNA-seq analysis. Pseudotime trajectory analysis and SCENIC analysis were conducted to explore the trajectory of cell differentiation and the regulatory network of single-cell transcription factors (TFs). Based on 37 immune gene sets, UM was divided into two different immune subtypes (IS1 and IS2). The two kinds of ISs have different characteristics in prognosis, immune-related molecules, immune score, and immune cell infiltration. According to 11,988 cells of scRNA-seq data from six UM samples, 11 cell clusters and 10 cell types were identified. The subsets of C1, C4, C5, C8, and C9 were related to the prognosis of UM, and different TF–target gene regulatory networks were involved. These five cell subsets differentiated into 3 different states. Our results provided valuable information about the heterogeneity of UM tumors and the expression patterns of TFs in different cell types.
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15
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Liang Z, Zheng R, Chen S, Yan X, Li M. A deep matrix factorization based approach for single-cell RNA-seq data clustering. Methods 2022; 205:114-122. [PMID: 35777719 DOI: 10.1016/j.ymeth.2022.06.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 05/28/2022] [Accepted: 06/24/2022] [Indexed: 11/17/2022] Open
Abstract
The rapid development of single-cell sequencing technologies makes it possible to analyze cellular heterogeneity at the single-cell level. Cell clustering is one of the most fundamental and common steps in the heterogeneity analysis. However, due to the high noise level, high dimensionality and high sparsity, accurate cell clustering is still challengeable. Here, we present DeepCI, a new clustering approach for scRNA-seq data. Using two autoencoders to obtain cell embedding and gene embedding, DeepCI can simultaneously learn cell low-dimensional representation and clustering. In addition, the recovered gene expression matrix can be obtained by the matrix multiplication of cell and gene embedding. To evaluate the performance of DeepCI, we performed it on several real scRNA-seq datasets for clustering and visualization analysis. The experimental results show that DeepCI obtains the overall better performance than several popular single cell analysis methods. We also evaluated the imputation performance of DeepCI by a dedicated experiment. The corresponding results show that the imputed gene expression of known specific marker gene can greatly improve the accuracy of cell type classification.
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Affiliation(s)
- Zhenlan Liang
- School of Computer Science and Engineering, Central South University, Changsha 410083, China
| | - Ruiqing Zheng
- School of Computer Science and Engineering, Central South University, Changsha 410083, China.
| | - Siqi Chen
- School of Computer Science and Engineering, Central South University, Changsha 410083, China
| | - Xuhua Yan
- School of Computer Science and Engineering, Central South University, Changsha 410083, China
| | - Min Li
- School of Computer Science and Engineering, Central South University, Changsha 410083, China.
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16
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Shen Y, Lian D, Shi K, Gao Y, Hu X, Yu K, Zhao Q, Feng C. Cancer Risk and Mutational Patterns Following Organ Transplantation. Front Cell Dev Biol 2022; 10:956334. [PMID: 35837331 PMCID: PMC9274140 DOI: 10.3389/fcell.2022.956334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 06/13/2022] [Indexed: 12/24/2022] Open
Abstract
The rapid development of medical technology and widespread application of immunosuppressive drugs have improved the success rate of organ transplantation significantly. However, the use of immunosuppressive agents increases the frequency of malignancy greatly. With the prospect of “precision medicine” for tumors and development of next-generation sequencing technology, more attention has been paid to the application of high-throughput sequencing technology in clinical oncology research, which is mainly applied to the early diagnosis of tumors and analysis of tumor-related genes. All generations of cancers carry somatic mutations, meanwhile, significant differences were observed in mutational signatures across tumors. Systematic sequencing of cancer genomes from patients after organ transplantation can reveal DNA damage and repair processes in exposed cancer cells and their precursors. In this review, we summarize the application of high-throughput sequencing and organoids in the field of organ transplantation, the mutational patterns of cancer genomes, and propose a new research strategy for understanding the mechanism of cancer following organ transplantation.
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Affiliation(s)
- Yangyang Shen
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Di Lian
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Kai Shi
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Yuefeng Gao
- College of Applied Engineering, Henan University of Science and Technology, Sanmenxia, China
- Sanmenxia Polytechnic, Sanmenxia, China
| | - Xiaoxiang Hu
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Kun Yu
- College of Animal Science and Technology, China Agricultural University, Beijing, China
- *Correspondence: Kun Yu, ; Qian Zhao, ; Chungang Feng,
| | - Qian Zhao
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
- *Correspondence: Kun Yu, ; Qian Zhao, ; Chungang Feng,
| | - Chungang Feng
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
- *Correspondence: Kun Yu, ; Qian Zhao, ; Chungang Feng,
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17
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Van der Ent MA, Svilar D, Cleuren AC. Molecular analysis of vascular gene expression. Res Pract Thromb Haemost 2022; 6:e12718. [PMID: 35599705 PMCID: PMC9118339 DOI: 10.1002/rth2.12718] [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: 12/31/2021] [Revised: 03/17/2022] [Accepted: 04/12/2022] [Indexed: 12/04/2022] Open
Abstract
A State of the Art lecture entitled "Molecular Analysis of Vascular Gene Expression" was presented at the ISTH Congress in 2021. Endothelial cells (ECs) form a critical interface between the blood and underlying tissue environment, serving as a reactive barrier to maintain tissue homeostasis. ECs play an important role in not only coagulation, but also in the response to inflammation by connecting these two processes in the host defense against pathogens. Furthermore, ECs tailor their behavior to the needs of the microenvironment in which they reside, resulting in a broad display of EC phenotypes. While this heterogeneity has been acknowledged for decades, the contributing molecular mechanisms have only recently started to emerge due to technological advances. These include high-throughput sequencing combined with methods to isolate ECs directly from their native tissue environment, as well as sequencing samples at a high cellular resolution. In addition, the newest technologies simultaneously quantitate and visualize a multitude of RNA transcripts directly in tissue sections, thus providing spatial information. Understanding how ECs function in (patho)physiological conditions is crucial to develop new therapeutics as many diseases can directly affect the endothelium. Of particular relevance for thrombotic disorders, EC dysfunction can lead to a procoagulant, proinflammatory phenotype with increased vascular permeability that can result in coagulopathy and tissue damage, as seen in a number of infectious diseases, including sepsis and coronavirus disease 2019. In light of the current pandemic, we will summarize relevant new data on the latter topic presented during the 2021 ISTH Congress.
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Affiliation(s)
| | - David Svilar
- Department of PediatricsUniversity of MichiganAnn ArborMichiganUSA,Life Sciences InstituteUniversity of MichiganAnn ArborMichiganUSA
| | - Audrey C.A. Cleuren
- Life Sciences InstituteUniversity of MichiganAnn ArborMichiganUSA,Cardiovascular Biology Research ProgramOklahoma Medical Research FoundationOklahoma CityOklahomaUSA
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18
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Bowers SL, Meng Q, Molkentin JD. Fibroblasts orchestrate cellular crosstalk in the heart through the ECM. NATURE CARDIOVASCULAR RESEARCH 2022; 1:312-321. [PMID: 38765890 PMCID: PMC11101212 DOI: 10.1038/s44161-022-00043-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 03/02/2022] [Indexed: 05/22/2024]
Abstract
Cell communication is needed for organ function and stress responses, especially in the heart. Cardiac fibroblasts, cardiomyocytes, immune cells, and endothelial cells comprise the major cell types in ventricular myocardium that together coordinate all functional processes. Critical to this cellular network is the non-cellular extracellular matrix (ECM) that provides structure and harbors growth factors and other signaling proteins that affect cell behavior. The ECM is not only produced and modified by cells within the myocardium, largely cardiac fibroblasts, it also acts as an avenue for communication among all myocardial cells. In this Review, we discuss how the development of therapeutics to combat cardiac diseases, specifically fibrosis, relies on a deeper understanding of how the cardiac ECM is intertwined with signaling processes that underlie cellular activation and behavior.
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Affiliation(s)
| | | | - Jeffery D. Molkentin
- Cincinnati Children’s Hospital, Division of Molecular Cardiovascular Biology; University of Cincinnati, Department of Pediatrics, Cincinnati, OH
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19
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Gong X, Zhang H, Xu X, Ding Y, Yang X, Cheng Z, Tao D, Hu C, Xiang Y, Sun Y. Tracing PRX1 + cells during molar formation and periodontal ligament reconstruction. Int J Oral Sci 2022; 14:5. [PMID: 35078971 PMCID: PMC8789835 DOI: 10.1038/s41368-021-00155-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Revised: 12/15/2021] [Accepted: 12/28/2021] [Indexed: 12/11/2022] Open
Abstract
Neural crest-derived mesenchymal stem cells (MSCs) are known to play an essential function during tooth and skeletal development. PRX1+ cells constitute an important MSC subtype that is implicated in osteogenesis. However, their potential function in tooth development and regeneration remains elusive. In the present study, we first assessed the cell fate of PRX1+ cells during molar development and periodontal ligament (PDL) formation in mice. Furthermore, single-cell RNA sequencing analysis was performed to study the distribution of PRX1+ cells in PDL cells. The behavior of PRX1+ cells during PDL reconstruction was investigated using an allogeneic transplanted tooth model. Although PRX1+ cells are spatial specific and can differentiate into almost all types of mesenchymal cells in first molars, their distribution in third molars is highly limited. The PDL formation is associated with a high number of PRX1+ cells; during transplanted teeth PDL reconstruction, PRX1+ cells from the recipient alveolar bone participate in angiogenesis as pericytes. Overall, PRX1+ cells are a key subtype of dental MSCs involved in the formation of mouse molar and PDL and participate in angiogenesis as pericytes during PDL reconstruction after tooth transplantation.
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Affiliation(s)
- Xuyan Gong
- Department of Implantology, School & Hospital of Stomatology, Tongji University, Shanghai, China.,Shanghai Engineering Research Center of Tooth Restoration and Regeneration, Shanghai, China
| | - Han Zhang
- Department of Implantology, School & Hospital of Stomatology, Tongji University, Shanghai, China.,Shanghai Engineering Research Center of Tooth Restoration and Regeneration, Shanghai, China
| | - Xiaoqiao Xu
- Department of Implantology, School & Hospital of Stomatology, Tongji University, Shanghai, China.,Shanghai Engineering Research Center of Tooth Restoration and Regeneration, Shanghai, China
| | - Yunpeng Ding
- Department of Implantology, School & Hospital of Stomatology, Tongji University, Shanghai, China.,Shanghai Engineering Research Center of Tooth Restoration and Regeneration, Shanghai, China
| | - Xingbo Yang
- Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China
| | - Zhiyang Cheng
- Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China
| | - Dike Tao
- Department of Implantology, School & Hospital of Stomatology, Tongji University, Shanghai, China.,Shanghai Engineering Research Center of Tooth Restoration and Regeneration, Shanghai, China
| | - Congjiao Hu
- Department of Implantology, School & Hospital of Stomatology, Tongji University, Shanghai, China.,Shanghai Engineering Research Center of Tooth Restoration and Regeneration, Shanghai, China
| | - Yaozu Xiang
- Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China
| | - Yao Sun
- Department of Implantology, School & Hospital of Stomatology, Tongji University, Shanghai, China. .,Shanghai Engineering Research Center of Tooth Restoration and Regeneration, Shanghai, China.
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20
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Chen HY, Palendira U, Feng CG. Navigating the cellular landscape in tissue: Recent advances in defining the pathogenesis of human disease. Comput Struct Biotechnol J 2022; 20:5256-5263. [PMID: 36212528 PMCID: PMC9519395 DOI: 10.1016/j.csbj.2022.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 09/04/2022] [Accepted: 09/04/2022] [Indexed: 11/19/2022] Open
Affiliation(s)
- Helen Y. Chen
- Immunology and Host Defence Group, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, NSW, Australia
- Charles Perkins Centre, The University of Sydney, NSW, Australia
- Centenary Institute, The University of Sydney, NSW, Australia
| | - Umaimainthan Palendira
- Immunology and Host Defence Group, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, NSW, Australia
- Charles Perkins Centre, The University of Sydney, NSW, Australia
- Centenary Institute, The University of Sydney, NSW, Australia
| | - Carl G. Feng
- Immunology and Host Defence Group, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, NSW, Australia
- Charles Perkins Centre, The University of Sydney, NSW, Australia
- Centenary Institute, The University of Sydney, NSW, Australia
- Corresponding author at: Level 5 (East) The Charles Perkins Centre (D17), The University of Sydney, NSW, 2006, Australia
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21
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Samad T, Wu SM. Single cell RNA sequencing approaches to cardiac development and congenital heart disease. Semin Cell Dev Biol 2021; 118:129-135. [PMID: 34006454 PMCID: PMC8434959 DOI: 10.1016/j.semcdb.2021.04.023] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 04/26/2021] [Accepted: 04/26/2021] [Indexed: 12/27/2022]
Abstract
The development of single cell RNA sequencing technologies has accelerated the ability of scientists to understand healthy and disease states of the cardiovascular system. Congenital heart defects occur in approximately 40,000 births each year and 1 out of 4 children are born with critical congenital heart disease requiring surgical interventions and a lifetime of monitoring. An understanding of how the normal heart develops and how each cell contributes to normal and pathological anatomy is an important goal in pediatric cardiovascular research. Single cell sequencing has provided the tools to increase the ability to discover rare cell types and novel genes involved in normal cardiac development. Knowledge of gene expression of single cells within cardiac tissue has contributed to the understanding of how each cell type contributes to the anatomic structures of the heart. In this review, we summarize how single cell RNA sequencing has been utilized to understand cardiac developmental processes and congenital heart disease. We discuss the advantages and disadvantages of whole cell versus single nuclei RNA sequencing and describe the approaches to analyze the interactomes, transcriptomes, and differentiation trajectory from single cell data. We summarize the currently available single cell RNA sequencing technologies and technical aspects of performing single cell analysis and how to overcome common obstacles. We also review data from the recently published human and mouse fetal heart atlases and advancements that have occurred within the field due to the application of these single cell tools. Finally we highlight the potential for single cell technologies to uncover novel mechanisms of disease pathogenesis by leveraging findings from genome wide association studies.
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Affiliation(s)
- Tahmina Samad
- Department of Cardiothoracic Surgery, Stanford University School of Medicine, Stanford, CA, USA; Clinical and Translational Research Program, Stanford University School of Medicine, Stanford, CA, USA; Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Sean M Wu
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA; Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA, USA.
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22
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Abstract
Single-cell RNA sequencing (scRNA-seq) is a comprehensive technical tool to analyze intracellular and intercellular interaction data by whole transcriptional profile analysis. Here, we describe the application in biomedical research, focusing on the immune system during organ transplantation and rejection. Unlike conventional transcriptome analysis, this method provides a full map of multiple cell populations in one specific tissue and presents a dynamic and transient unbiased method to explore the progression of allograft dysfunction, starting from the stress response to final graft failure. This promising sequencing technology remarkably improves individualized organ rejection treatment by identifying decisive cellular subgroups and cell-specific interactions.
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23
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Vallejo J, Cochain C, Zernecke A, Ley K. Heterogeneity of immune cells in human atherosclerosis revealed by scRNA-Seq. Cardiovasc Res 2021; 117:2537-2543. [PMID: 34343272 DOI: 10.1093/cvr/cvab260] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 07/02/2021] [Accepted: 07/30/2021] [Indexed: 12/14/2022] Open
Abstract
Immune cells in atherosclerosis include T, B, natural killer (NK) and NKT cells, macrophages, monocytes, dendritic cells (DCs), neutrophils and mast cells. Advances in single cell RNA sequencing (sRNA-Seq) have refined our understanding of immune cell subsets. Four recent studies have used scRNA-Seq of immune cells in human atherosclerotic lesions and peripheral blood mononuclear cells (PBMCs), some including cell surface phenotypes revealed by oligonucleotide-tagged antibodies, which confirmed known and identified new immune cell subsets and identified genes significantly upregulated in PBMCs from HIV+ subjects with atherosclerosis compared to PBMCs from matched HIV+ subjects without atherosclerosis. The ability of scRNA-Seq to identify cell types is greatly augmented by adding cell surface phenotype using antibody sequencing. In this review we summarize the latest data obtained by scRNA-Seq on plaques and human PBMCs in human subjects with atherosclerosis.
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Affiliation(s)
- Jenifer Vallejo
- Division of Inflammation Biology, La Jolla Institute for Immunology, California, USA
| | - Clément Cochain
- Institute of Experimental Biomedicine, University Hospital Würzburg, Germany.,Comprehensive Heart Failure Center, University Hospital Würzburg, Germany
| | - Alma Zernecke
- Institute of Experimental Biomedicine, University Hospital Würzburg, Germany
| | - Klaus Ley
- Division of Inflammation Biology, La Jolla Institute for Immunology, California, USA.,Department of Bioengineering, University of California San Diego, California, USA
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24
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Suen TK, Al B, Placek K. Cell-to-cell proteome variability: life in a cycle. Signal Transduct Target Ther 2021; 6:229. [PMID: 34112757 PMCID: PMC8192947 DOI: 10.1038/s41392-021-00655-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 05/10/2021] [Accepted: 05/16/2021] [Indexed: 11/09/2022] Open
Affiliation(s)
- Tsz Kin Suen
- Immunology and Metabolism, Life and Medical Sciences Institute, University of Bonn, Bonn, Germany
| | - Burcu Al
- Immunology and Metabolism, Life and Medical Sciences Institute, University of Bonn, Bonn, Germany
| | - Katarzyna Placek
- Immunology and Metabolism, Life and Medical Sciences Institute, University of Bonn, Bonn, Germany.
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Chong ZX, Ho WY, Yeap SK, Wang ML, Chien Y, Verusingam ND, Ong HK. Single-cell RNA sequencing in human lung cancer: Applications, challenges, and pathway towards personalized therapy. J Chin Med Assoc 2021; 84:563-576. [PMID: 33883467 DOI: 10.1097/jcma.0000000000000535] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Lung cancer is one of the most prevalent human cancers, and single-cell RNA sequencing (scRNA-seq) has been widely used to study human lung cancer at the cellular, genetic, and molecular level. Even though there are published reviews, which summarized the applications of scRNA-seq in human cancers like breast cancer, there is lack of a comprehensive review, which could effectively highlight the broad use of scRNA-seq in studying lung cancer. This review, therefore, was aimed to summarize the various applications of scRNA-seq in human lung cancer research based on the findings from different published in vitro, in vivo, and clinical studies. The review would first briefly outline the concept and principle of scRNA-seq, followed by the discussion on the applications of scRNA-seq in studying human lung cancer. Finally, the challenges faced when using scRNA-seq to study human lung cancer would be discussed, and the potential applications and challenges of scRNA-seq to facilitate the development of personalized cancer therapy in the future would be explored.
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Affiliation(s)
- Zhi-Xiong Chong
- Faculty of Science and Engineering, University of Nottingham Malaysia, Semenyih, Selangor, Malaysia
| | - Wan-Yong Ho
- Faculty of Science and Engineering, University of Nottingham Malaysia, Semenyih, Selangor, Malaysia
| | - Swee-Keong Yeap
- China-ASEAN College of Marine Sciences, Xiamen University Malaysia, Sepang, Selangor, Malaysia
| | - Mong-Lien Wang
- Institute of Pharmacology, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
- Institute of Food Safety and Health Risk Assessment, School of Pharmaceutical Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
| | - Yueh Chien
- Institute of Pharmacology, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan, ROC
| | - Nalini Devi Verusingam
- Institute of Pharmacology, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan, ROC
- Centre for Stem Cell Research, Faculty of Medicine and Health Sciences, Universiti Tunku Abdul Rahman, Selangor, Malaysia
- National Cancer Council (MAKNA), Kuala Lumpur, Malaysia
| | - Han-Kiat Ong
- Centre for Stem Cell Research, Faculty of Medicine and Health Sciences, Universiti Tunku Abdul Rahman, Selangor, Malaysia
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You M, Rong R, Zeng Z, Li H, Xia X, Ji D. Single-cell RNA sequencing: A new opportunity for retinal research. WILEY INTERDISCIPLINARY REVIEWS-RNA 2021; 12:e1652. [PMID: 33754496 DOI: 10.1002/wrna.1652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 03/01/2021] [Accepted: 03/02/2021] [Indexed: 11/08/2022]
Abstract
Single-cell RNA sequencing (scRNA-seq) is a technology for single-cell transcriptome analysis that can be used to characterize complex dynamics of various retinal cell types. It provides deep scrutiny into the gene expression character of diverse cell types, lending insight into all the biological processes being carried out. The scRNA-seq is an alternative to regular RNA-seq, which does not achieve cellular heterogeneity. The retina, is a part of the central nervous system (CNS) and consists of six types of neurons and several types of glial cells. Studying retinal cell heterogeneity is important for understanding retinal diseases. Currently, scRNA-seq is employed to assess retina development and retinal disease pathogenesis and has improved our understanding of the relationship between the retina, its visual pathways, and the brain. Moreover, this technology provides new ideas on the sensitivity and molecular mechanisms of cell subtypes involved in retinal-related diseases. The application of scRNA-seq technology has given us a deeper understanding of the latest advancements and challenges in retinal development and diseases. We advocate scRNA-seq as one of the important tools for developing novel therapies for retinal diseases. This article is categorized under: RNA Methods > RNA Analyses in Cells RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.
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Affiliation(s)
- Mengling You
- Department of Ophthalmology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Ophthalmology, Changsha, Hunan, China
| | - Rong Rong
- Department of Ophthalmology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Ophthalmology, Changsha, Hunan, China
| | - Zhou Zeng
- Department of Ophthalmology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Ophthalmology, Changsha, Hunan, China
| | - Haibo Li
- Department of Ophthalmology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Ophthalmology, Changsha, Hunan, China
| | - Xiaobo Xia
- Department of Ophthalmology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Ophthalmology, Changsha, Hunan, China
| | - Dan Ji
- Department of Ophthalmology, Xiangya Hospital, Central South University, Changsha, China.,Hunan Key Laboratory of Ophthalmology, Changsha, Hunan, China
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Phan QM, Sinha S, Biernaskie J, Driskell RR. Single-cell transcriptomic analysis of small and large wounds reveals the distinct spatial organization of regenerative fibroblasts. Exp Dermatol 2021; 30:92-101. [PMID: 33237598 PMCID: PMC7839523 DOI: 10.1111/exd.14244] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 11/19/2020] [Accepted: 11/19/2020] [Indexed: 12/30/2022]
Abstract
Wound-induced hair follicle neogenesis (WIHN) has been an important model to study hair follicle regeneration during wound repair. However, the cellular and molecular components of the dermis that make large wounds more regenerative are not fully understood. Here, we compare and contrast recently published scRNA-seq data of small scarring wounds to wounds that regenerate in hope to elucidate the role of fibroblasts lineages in WIHN. Our analysis revealed an over-representation of the newly identified upper wound fibroblasts in regenerative wound conditions, which express the retinoic acid binding protein Crabp1. This regenerative cell type shares a similar gene signature to the murine papillary fibroblast lineage, which are necessary to support hair follicle morphogenesis and homeostasis. RNA velocity analysis comparing scarring and regenerating wounds revealed the divergent trajectories towards upper and lower wound fibroblasts and that the upper populations were closely associated with the specialized dermal papilla. We also provide analyses and explanation reconciling the inconsistency between the histological lineage tracing and the scRNA-seq data from recent reports investigating large wounds. Finally, we performed a computational test to map the spatial location of upper wound fibroblasts in large wounds which revealed that upper peripheral fibroblasts might harbour equivalent regenerative competence as those in the centre. Overall, our scRNA-seq reanalysis combining multiple samples suggests that upper wound fibroblasts are required for hair follicle regeneration and that papillary fibroblasts may migrate from the wound periphery to the centre during wound re-epithelialization. Moreover, data from this publication are made available on our searchable web resource: https://skinregeneration.org/.
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Affiliation(s)
- Quan M. Phan
- School of Molecular BiosciencesWashington State UniversityPullmanWAUSA
| | - Sarthak Sinha
- Department of Comparative Biology and Experimental MedicineFaculty of Veterinary MedicineUniversity of CalgaryCalgaryABCanada
| | - Jeff Biernaskie
- Department of Surgery, Cumming School of MedicineAlberta Children's Hospital Research InstituteHotchkiss Brain Institute University of CalgaryCalgaryABCanada
| | - Ryan R. Driskell
- School of Molecular BiosciencesWashington State UniversityPullmanWAUSA
- Center for Reproductive BiologyWashington State UniversityPullmanWAUSA
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