1
|
Tyagi R, Rosa BA, Swain A, Artyomov MN, Jasmer DP, Mitreva M. Intestinal cell diversity and treatment responses in a parasitic nematode at single cell resolution. BMC Genomics 2024; 25:341. [PMID: 38575858 PMCID: PMC10996262 DOI: 10.1186/s12864-024-10203-7] [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: 12/08/2023] [Accepted: 03/08/2024] [Indexed: 04/06/2024] Open
Abstract
BACKGROUND Parasitic nematodes, significant pathogens for humans, animals, and plants, depend on diverse organ systems for intra-host survival. Understanding the cellular diversity and molecular variations underlying these functions holds promise for developing novel therapeutics, with specific emphasis on the neuromuscular system's functional diversity. The nematode intestine, crucial for anthelmintic therapies, exhibits diverse cellular phenotypes, and unraveling this diversity at the single-cell level is essential for advancing knowledge in anthelmintic research across various organ systems. RESULTS Here, using novel single-cell transcriptomics datasets, we delineate cellular diversity within the intestine of adult female Ascaris suum, a parasitic nematode species that infects animals and people. Gene transcripts expressed in individual nuclei of untreated intestinal cells resolved three phenotypic clusters, while lower stringency resolved additional subclusters and more potential diversity. Clusters 1 and 3 phenotypes displayed variable congruence with scRNA phenotypes of C. elegans intestinal cells, whereas the A. suum cluster 2 phenotype was markedly unique. Distinct functional pathway enrichment characterized each A. suum intestinal cell cluster. Cluster 2 was distinctly enriched for Clade III-associated genes, suggesting it evolved within clade III nematodes. Clusters also demonstrated differential transcriptional responsiveness to nematode intestinal toxic treatments, with Cluster 2 displaying the least responses to short-term intra-pseudocoelomic nematode intestinal toxin treatments. CONCLUSIONS This investigation presents advances in knowledge related to biological differences among major cell populations of adult A. suum intestinal cells. For the first time, diverse nematode intestinal cell populations were characterized, and associated biological markers of these cells were identified to support tracking of constituent cells under experimental conditions. These advances will promote better understanding of this and other parasitic nematodes of global importance, and will help to guide future anthelmintic treatments.
Collapse
Affiliation(s)
- Rahul Tyagi
- Division of Infectious Diseases, Department of Internal Medicine, Washington University School of Medicine, 63110, St. Louis, MO, USA
| | - Bruce A Rosa
- Division of Infectious Diseases, Department of Internal Medicine, Washington University School of Medicine, 63110, St. Louis, MO, USA
| | - Amanda Swain
- Department of Pathology and Immunology, Washington University School of Medicine, 63110, Saint Louis, MO, USA
| | - Maxim N Artyomov
- Department of Pathology and Immunology, Washington University School of Medicine, 63110, Saint Louis, MO, USA
| | - Douglas P Jasmer
- Department of Veterinary Microbiology and Pathology, Washington State University, 99164, Pullman, WA, USA.
| | - Makedonka Mitreva
- Division of Infectious Diseases, Department of Internal Medicine, Washington University School of Medicine, 63110, St. Louis, MO, USA.
- Department of Genetics, Washington University School of Medicine, 63110, St. Louis, MO, USA.
- McDonnell Genome Institute, Washington University School of Medicine, 63110, St Louis, MO, USA.
| |
Collapse
|
2
|
Yang B, Hu S, Jiang Y, Xu L, Shu S, Zhang H. Advancements in Single-Cell RNA Sequencing Research for Neurological Diseases. Mol Neurobiol 2024:10.1007/s12035-024-04126-3. [PMID: 38564138 DOI: 10.1007/s12035-024-04126-3] [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: 11/29/2023] [Accepted: 03/18/2024] [Indexed: 04/04/2024]
Abstract
Neurological diseases are a major cause of the global burden of disease. Although the mechanisms of the occurrence and development of neurological diseases are not fully clear, most of them are associated with cells mediating neuroinflammation. Yet medications and other therapeutic options to improve treatment are still very limited. Single-cell RNA sequencing (scRNA-seq), as a delightfully potent breakthrough technology, not only identifies various cell types and response states but also uncovers cell-specific gene expression changes, gene regulatory networks, intercellular communication, and cellular movement trajectories, among others, in different cell types. In this review, we describe the technology of scRNA-seq in detail and discuss and summarize the application of scRNA-seq in exploring neurological diseases, elaborating the corresponding specific mechanisms of the diseases as well as providing a reliable basis for new therapeutic approaches. Finally, we affirm that scRNA-seq promotes the development of the neuroscience field and enables us to have a deeper cellular understanding of neurological diseases in the future, which provides strong support for the treatment of neurological diseases and the improvement of patients' prognosis.
Collapse
Affiliation(s)
- Bingjie Yang
- Department of Neurology, The Fourth Clinical School of Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Shuqi Hu
- Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Department of Neurology, Affiliated Hangzhou First People's Hospital, Westlake University School of Medicine, Hangzhou, Zhejiang, China
| | - Yiru Jiang
- Department of Neurology, The Fourth Clinical School of Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Lei Xu
- Department of Neurology, Zhejiang Rongjun Hospital, Jiaxing, Zhejiang, China
| | - Song Shu
- Department of Neurology, Affiliated Hangzhou First People's Hospital, Westlake University School of Medicine, Hangzhou, Zhejiang, China
| | - Hao Zhang
- Department of Neurology, The Fourth Clinical School of Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
- Department of Neurology, Affiliated Hangzhou First People's Hospital, Westlake University School of Medicine, Hangzhou, Zhejiang, China.
| |
Collapse
|
3
|
Yan H, Ju X, Huang A, Yuan J. Advancements in technology for characterizing the tumor immune microenvironment. Int J Biol Sci 2024; 20:2151-2167. [PMID: 38617534 PMCID: PMC11008272 DOI: 10.7150/ijbs.92525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 03/12/2024] [Indexed: 04/16/2024] Open
Abstract
Immunotherapy plays a key role in cancer treatment, however, responses are limited to a small number of patients. The biological basis for the success of immunotherapy is the complex interaction between tumor cells and tumor immune microenvironment (TIME). Historically, research on tumor immune constitution was limited to the analysis of one or two markers, more novel technologies are needed to interpret the complex interactions between tumor cells and TIME. In recent years, major advances have already been made in depicting TIME at a considerably elevated degree of throughput, dimensionality and resolution, allowing dozens of markers to be labeled simultaneously, and analyzing the heterogeneity of tumour-immune infiltrates in detail at the single cell level, depicting the spatial landscape of the entire microenvironment, as well as applying artificial intelligence (AI) to interpret a large amount of complex data from TIME. In this review, we summarized emerging technologies that have made contributions to the field of TIME, and provided prospects for future research.
Collapse
Affiliation(s)
- Honglin Yan
- Department of Pathology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| | | | | | - Jingping Yuan
- Department of Pathology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| |
Collapse
|
4
|
Luo G, Zeng D, Liu J, Li D, Takiff HE, Song S, Gao Q, Yan B. Temporal and cellular analysis of granuloma development in mycobacterial infected adult zebrafish. J Leukoc Biol 2024; 115:525-535. [PMID: 37982587 DOI: 10.1093/jleuko/qiad145] [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: 11/09/2022] [Revised: 09/25/2023] [Accepted: 11/01/2023] [Indexed: 11/21/2023] Open
Abstract
Because granulomas are a hallmark of tuberculosis pathogenesis, the study of the dynamic changes in their cellular composition and morphological character can facilitate our understanding of tuberculosis pathogenicity. Adult zebrafish infected with Mycobacterium marinum form granulomas that are similar to the granulomas in human patients with tuberculosis and therefore have been used to study host-mycobacterium interactions. Most studies of zebrafish granulomas, however, have focused on necrotic granulomas, while a systematic description of the different stages of granuloma formation in the zebrafish model is lacking. Here, we characterized the stages of granulomas in M. marinum-infected zebrafish, including early immune cell infiltration, nonnecrotizing granulomas, and necrotizing granulomas, using corresponding samples from patients with pulmonary tuberculosis as references. We combined hematoxylin and eosin staining and in situ hybridization to identify the different immune cell types and follow their spatial distribution in the different stages of granuloma development. The macrophages in zebrafish granulomas were shown to belong to distinct subtypes: epithelioid macrophages, foamy macrophages, and multinucleated giant cells. By defining the developmental stages of zebrafish granulomas and the spatial distribution of the different immune cells they contain, this work provides a reference for future studies of mycobacterial granulomas and their immune microenvironments.
Collapse
Affiliation(s)
- Geyang Luo
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Sciences, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity and Shanghai Public Health Clinical Center, Fudan University, 130 Dongan Rd., Xuhui District, 200032 Shanghai, People's Republic of China
| | - Dong Zeng
- Department of Pathology, Shanghai Public Health Clinical Center, Fudan University, 2901 Caolang Rd., Jinshan District, 201508 Shanghai, People's Republic of China
| | - Jianxin Liu
- Center for Tuberculosis Research, Shanghai Public Health Clinical Center, Fudan University, 2901 Caolang Rd., Jinshan District, 201508 Shanghai, People's Republic of China
- School of Medicine, Shanghai Ninth People's Hospital Affiliated to Shanghai JiaoTong University, 639 Manufacturing Bureau Rd., Huangpu District, 200011 Shanghai, People's Republic of China
| | - Duoduo Li
- Department of Pathology, Shanghai Public Health Clinical Center, Fudan University, 2901 Caolang Rd., Jinshan District, 201508 Shanghai, People's Republic of China
| | - Howard E Takiff
- Instituto Venezolano de Investigaciones Científicas, Centro de Microbiología y Biología Celular, Caracas, 1020A, Venezuela
| | - Shu Song
- Department of Pathology, Shanghai Public Health Clinical Center, Fudan University, 2901 Caolang Rd., Jinshan District, 201508 Shanghai, People's Republic of China
| | - Qian Gao
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Sciences, Shanghai Medical College, Shanghai Institute of Infectious Disease and Biosecurity and Shanghai Public Health Clinical Center, Fudan University, 130 Dongan Rd., Xuhui District, 200032 Shanghai, People's Republic of China
| | - Bo Yan
- Center for Tuberculosis Research, Shanghai Public Health Clinical Center, Fudan University, 2901 Caolang Rd., Jinshan District, 201508 Shanghai, People's Republic of China
| |
Collapse
|
5
|
Chang JT, Liu LB, Wang PG, An J. Single-cell RNA sequencing to understand host-virus interactions. Virol Sin 2024; 39:1-8. [PMID: 38008383 PMCID: PMC10877424 DOI: 10.1016/j.virs.2023.11.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 11/23/2023] [Indexed: 11/28/2023] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) has allowed for the profiling of host and virus transcripts and host-virus interactions at single-cell resolution. This review summarizes the existing scRNA-seq technologies together with their strengths and weaknesses. The applications of scRNA-seq in various virological studies are discussed in depth, which broaden the understanding of the immune atlas, host-virus interactions, and immune repertoire. scRNA-seq can be widely used for virology in the near future to better understand the pathogenic mechanisms and discover more effective therapeutic strategies.
Collapse
Affiliation(s)
- Jia-Tong Chang
- Department of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, China
| | - Li-Bo Liu
- Department of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, China
| | - Pei-Gang Wang
- Department of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, China.
| | - Jing An
- Department of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, China.
| |
Collapse
|
6
|
Hume AJ, Olejnik J, White MR, Huang J, Turcinovic J, Heiden B, Bawa PS, Williams CJ, Gorham NG, Alekseyev YO, Connor JH, Kotton DN, Mühlberger E. Heat Inactivation of Nipah Virus for Downstream Single-Cell RNA Sequencing Does Not Interfere with Sample Quality. Pathogens 2024; 13:62. [PMID: 38251369 PMCID: PMC10818917 DOI: 10.3390/pathogens13010062] [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: 11/30/2023] [Revised: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 01/23/2024] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) technologies are instrumental to improving our understanding of virus-host interactions in cell culture infection studies and complex biological systems because they allow separating the transcriptional signatures of infected versus non-infected bystander cells. A drawback of using biosafety level (BSL) 4 pathogens is that protocols are typically developed without consideration of virus inactivation during the procedure. To ensure complete inactivation of virus-containing samples for downstream analyses, an adaptation of the workflow is needed. Focusing on a commercially available microfluidic partitioning scRNA-seq platform to prepare samples for scRNA-seq, we tested various chemical and physical components of the platform for their ability to inactivate Nipah virus (NiV), a BSL-4 pathogen that belongs to the group of nonsegmented negative-sense RNA viruses. The only step of the standard protocol that led to NiV inactivation was a 5 min incubation at 85 °C. To comply with the more stringent biosafety requirements for BSL-4-derived samples, we included an additional heat step after cDNA synthesis. This step alone was sufficient to inactivate NiV-containing samples, adding to the necessary inactivation redundancy. Importantly, the additional heat step did not affect sample quality or downstream scRNA-seq results.
Collapse
Affiliation(s)
- Adam J. Hume
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Judith Olejnik
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Mitchell R. White
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Jessie Huang
- Center for Regenerative Medicine of Boston University and Boston Medical Center, Boston, MA 02118, USA; (J.H.); (P.S.B.); (D.N.K.)
- The Pulmonary Center and Department of Medicine, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA
| | - Jacquelyn Turcinovic
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Baylee Heiden
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Pushpinder S. Bawa
- Center for Regenerative Medicine of Boston University and Boston Medical Center, Boston, MA 02118, USA; (J.H.); (P.S.B.); (D.N.K.)
| | - Christopher J. Williams
- Department of Medicine, Single Cell Sequencing Core Facility, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA;
| | - Nickolas G. Gorham
- Microarray and Sequencing Resource Core Facility, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA;
| | - Yuriy O. Alekseyev
- Department of Pathology and Laboratory Medicine, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA;
| | - John H. Connor
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Darrell N. Kotton
- Center for Regenerative Medicine of Boston University and Boston Medical Center, Boston, MA 02118, USA; (J.H.); (P.S.B.); (D.N.K.)
- The Pulmonary Center and Department of Medicine, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA
| | - Elke Mühlberger
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| |
Collapse
|
7
|
Cohen M, Laux J, Douagi I. Cytometry in High-Containment Laboratories. Methods Mol Biol 2024; 2779:425-456. [PMID: 38526798 DOI: 10.1007/978-1-0716-3738-8_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
The emergence of new pathogens continues to fuel the need for advanced high-containment laboratories across the globe. Here we explore challenges and opportunities for integration of cytometry, a central technology for cell analysis, within high-containment laboratories. We review current applications in infectious disease, vaccine research, and biosafety. Considerations specific to cytometry within high-containment laboratories, such as biosafety requirements, and sample containment strategies are also addressed. We further tour the landscape of emerging technologies, including combination of cytometry with other omics, the application of automation, and artificial intelligence. Finally, we propose a framework to fast track the immersion of advanced technologies into the high-containment research setting to improve global preparedness for new emerging diseases.
Collapse
Affiliation(s)
- Melanie Cohen
- Flow Cytometry Section, Research Technologies Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Julie Laux
- Flow Cytometry Section, Research Technologies Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Iyadh Douagi
- Flow Cytometry Section, Research Technologies Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA.
| |
Collapse
|
8
|
Li LS, Yang L, Zhuang L, Ye ZY, Zhao WG, Gong WP. From immunology to artificial intelligence: revolutionizing latent tuberculosis infection diagnosis with machine learning. Mil Med Res 2023; 10:58. [PMID: 38017571 PMCID: PMC10685516 DOI: 10.1186/s40779-023-00490-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 11/06/2023] [Indexed: 11/30/2023] Open
Abstract
Latent tuberculosis infection (LTBI) has become a major source of active tuberculosis (ATB). Although the tuberculin skin test and interferon-gamma release assay can be used to diagnose LTBI, these methods can only differentiate infected individuals from healthy ones but cannot discriminate between LTBI and ATB. Thus, the diagnosis of LTBI faces many challenges, such as the lack of effective biomarkers from Mycobacterium tuberculosis (MTB) for distinguishing LTBI, the low diagnostic efficacy of biomarkers derived from the human host, and the absence of a gold standard to differentiate between LTBI and ATB. Sputum culture, as the gold standard for diagnosing tuberculosis, is time-consuming and cannot distinguish between ATB and LTBI. In this article, we review the pathogenesis of MTB and the immune mechanisms of the host in LTBI, including the innate and adaptive immune responses, multiple immune evasion mechanisms of MTB, and epigenetic regulation. Based on this knowledge, we summarize the current status and challenges in diagnosing LTBI and present the application of machine learning (ML) in LTBI diagnosis, as well as the advantages and limitations of ML in this context. Finally, we discuss the future development directions of ML applied to LTBI diagnosis.
Collapse
Affiliation(s)
- Lin-Sheng Li
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, the Eighth Medical Center of PLA General Hospital, Beijing, 100091, China
- Hebei North University, Zhangjiakou, 075000, Hebei, China
- Senior Department of Respiratory and Critical Care Medicine, the Eighth Medical Center of PLA General Hospital, Beijing, 100091, China
| | - Ling Yang
- Hebei North University, Zhangjiakou, 075000, Hebei, China
| | - Li Zhuang
- Hebei North University, Zhangjiakou, 075000, Hebei, China
| | - Zhao-Yang Ye
- Hebei North University, Zhangjiakou, 075000, Hebei, China
| | - Wei-Guo Zhao
- Senior Department of Respiratory and Critical Care Medicine, the Eighth Medical Center of PLA General Hospital, Beijing, 100091, China.
| | - Wen-Ping Gong
- Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, the Eighth Medical Center of PLA General Hospital, Beijing, 100091, China.
| |
Collapse
|
9
|
Pan J, Chang Z, Zhang X, Dong Q, Zhao H, Shi J, Wang G. Research progress of single-cell sequencing in tuberculosis. Front Immunol 2023; 14:1276194. [PMID: 37901241 PMCID: PMC10611525 DOI: 10.3389/fimmu.2023.1276194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 09/29/2023] [Indexed: 10/31/2023] Open
Abstract
Tuberculosis is a major infectious disease caused by Mycobacterium tuberculosis infection. The pathogenesis and immune mechanism of tuberculosis are not clear, and it is urgent to find new drugs, diagnosis, and treatment targets. A useful tool in the quest to reveal the enigmas related to Mycobacterium tuberculosis infection and disease is the single-cell sequencing technique. By clarifying cell heterogeneity, identifying pathogenic cell groups, and finding key gene targets, the map at the single cell level enables people to better understand the cell diversity of complex organisms and the immune state of hosts during infection. Here, we briefly reviewed the development of single-cell sequencing, and emphasized the different applications and limitations of various technologies. Single-cell sequencing has been widely used in the study of the pathogenesis and immune response of tuberculosis. We review these works summarizing the most influential findings. Combined with the multi-molecular level and multi-dimensional analysis, we aim to deeply understand the blank and potential future development of the research on Mycobacterium tuberculosis infection using single-cell sequencing technology.
Collapse
Affiliation(s)
| | | | | | | | | | - Jingwei Shi
- Key Laboratory of Pathobiology Ministry of Education, College of Basic Medical Sciences/China-Japan Union Hospital of Jilin University, Jilin University, Changchun, China
| | - Guoqing Wang
- Key Laboratory of Pathobiology Ministry of Education, College of Basic Medical Sciences/China-Japan Union Hospital of Jilin University, Jilin University, Changchun, China
| |
Collapse
|
10
|
Kulkarni S, Endsley JJ, Lai Z, Bradley T, Sharan R. Single-Cell Transcriptomics of Mtb/HIV Co-Infection. Cells 2023; 12:2295. [PMID: 37759517 PMCID: PMC10529032 DOI: 10.3390/cells12182295] [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: 05/31/2023] [Revised: 08/17/2023] [Accepted: 09/11/2023] [Indexed: 09/29/2023] Open
Abstract
Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) co-infection continues to pose a significant healthcare burden. HIV co-infection during TB predisposes the host to the reactivation of latent TB infection (LTBI), worsening disease conditions and mortality. There is a lack of biomarkers of LTBI reactivation and/or immune-related transcriptional signatures to distinguish active TB from LTBI and predict TB reactivation upon HIV co-infection. Characterizing individual cells using next-generation sequencing-based technologies has facilitated novel biological discoveries about infectious diseases, including TB and HIV pathogenesis. Compared to the more conventional sequencing techniques that provide a bulk assessment, single-cell RNA sequencing (scRNA-seq) can reveal complex and new cell types and identify more high-resolution cellular heterogeneity. This review will summarize the progress made in defining the immune atlas of TB and HIV infections using scRNA-seq, including host-pathogen interactions, heterogeneity in HIV pathogenesis, and the animal models employed to model disease. This review will also address the tools needed to bridge the gap between disease outcomes in single infection vs. co-infection. Finally, it will elaborate on the translational benefits of single-cell sequencing in TB/HIV diagnosis in humans.
Collapse
Affiliation(s)
- Smita Kulkarni
- Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | - Janice J. Endsley
- Departments of Microbiology & Immunology and Pathology, The University of Texas Medical Branch, Galveston, TX 77555, USA;
| | - Zhao Lai
- Greehey Children’s Cancer Research Institute, The University of Texas Health San Antonio, San Antonio, TX 78229, USA;
| | - Todd Bradley
- Genomic Medicine Center, Children’s Mercy Research Institute, Children’s Mercy Kansas City, Kansas City, MO 64108, USA;
- Departments of Pediatrics and Pathology and Laboratory Medicine, University of Kansas Medical Center, Kansas City, MO 66160, USA
- Department of Pediatrics, UMKC School of Medicine, Kansas City, MO 64108, USA
| | - Riti Sharan
- Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| |
Collapse
|
11
|
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 2023:10.1007/s11010-023-04840-x. [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] [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.
Collapse
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.
| |
Collapse
|
12
|
Hu H, Feng Z, Shuai XS, Lyu J, Li X, Lin H, Shuai J. Identifying SARS-CoV-2 infected cells with scVDN. Front Microbiol 2023; 14:1236653. [PMID: 37492254 PMCID: PMC10364606 DOI: 10.3389/fmicb.2023.1236653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 06/26/2023] [Indexed: 07/27/2023] Open
Abstract
Introduction Single-cell RNA sequencing (scRNA-seq) is a powerful tool for understanding cellular heterogeneity and identifying cell types in virus-related research. However, direct identification of SARS-CoV-2-infected cells at the single-cell level remains challenging, hindering the understanding of viral pathogenesis and the development of effective treatments. Methods In this study, we propose a deep learning framework, the single-cell virus detection network (scVDN), to predict the infection status of single cells. The scVDN is trained on scRNA-seq data from multiple nasal swab samples obtained from several contributors with varying cell types. To objectively evaluate scVDN's performance, we establish a model evaluation framework suitable for real experimental data. Results and Discussion Our results demonstrate that scVDN outperforms four state-of-the-art machine learning models in identifying SARS-CoV-2-infected cells, even with extremely imbalanced labels in real data. Specifically, scVDN achieves a perfect AUC score of 1 in four cell types. Our findings have important implications for advancing virus research and improving public health by enabling the identification of virus-infected cells at the single-cell level, which is critical for diagnosing and treating viral infections. The scVDN framework can be applied to other single-cell virus-related studies, and we make all source code and datasets publicly available on GitHub at https://github.com/studentiz/scvdn.
Collapse
Affiliation(s)
- Huan Hu
- Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research, Xiamen University, Xiamen, China
- Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, University of Chinese Academy of Sciences, Wenzhou, China
- National Institute for Data Science in Health and Medicine, and State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, Xiamen University, Xiamen, China
| | - Zhen Feng
- First Affiliated Hospital of Wenzhou Medical University, Wenzhou Medical University, Wenzhou, China
| | - Xinghao Steven Shuai
- Department of Biomedical Science, University of California Riverside, Riverside, CA, United States
| | - Jie Lyu
- Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, University of Chinese Academy of Sciences, Wenzhou, China
| | - Xiang Li
- Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research, Xiamen University, Xiamen, China
| | - Hai Lin
- Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, University of Chinese Academy of Sciences, Wenzhou, China
| | - Jianwei Shuai
- Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research, Xiamen University, Xiamen, China
- Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, University of Chinese Academy of Sciences, Wenzhou, China
- National Institute for Data Science in Health and Medicine, and State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, Xiamen University, Xiamen, China
| |
Collapse
|
13
|
Olejnik J, Leon J, Michelson D, Chowdhary K, Galvan-Pena S, Benoist C, Mühlberger E, Hume AJ. Establishment of an Inactivation Method for Ebola Virus and SARS-CoV-2 Suitable for Downstream Sequencing of Low Cell Numbers. Pathogens 2023; 12:342. [PMID: 36839614 PMCID: PMC9958562 DOI: 10.3390/pathogens12020342] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/06/2023] [Accepted: 02/15/2023] [Indexed: 02/22/2023] Open
Abstract
Technologies that facilitate the bulk sequencing of small numbers of cells as well as single-cell RNA sequencing (scRNA-seq) have aided greatly in the study of viruses as these analyses can be used to differentiate responses from infected versus bystander cells in complex systems, including in organoid or animal studies. While protocols for these analyses are typically developed with biosafety level 2 (BSL-2) considerations in mind, such analyses are equally useful for the study of viruses that require higher biosafety containment levels. Many of these workstreams, however, are not directly compatible with the more stringent biosafety regulations of BSL-3 and BSL-4 laboratories ensuring virus inactivation and must therefore be modified. Here we show that TCL buffer (Qiagen), which was developed for bulk sequencing of small numbers of cells and also facilitates scRNA-seq, inactivates both Ebola virus (EBOV) and SARS-CoV-2, BSL-4 and BSL-3 viruses, respectively. We show that additional heat treatment, necessary for the more stringent biosafety concerns for BSL-4-derived samples, was additionally sufficient to inactivate EBOV-containing samples. Critically, this heat treatment had minimal effects on extracted RNA quality and downstream sequencing results.
Collapse
Affiliation(s)
- Judith Olejnik
- Department of Microbiology, Boston University School of Medicine, Boston, MA 02118, USA
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Juliette Leon
- Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
- INSERM UMR 1163, Institut Imagine, University of Paris, 75015 Paris, France
| | - Daniel Michelson
- Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Kaitavjeet Chowdhary
- Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Silvia Galvan-Pena
- Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Christophe Benoist
- Department of Immunology, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Elke Mühlberger
- Department of Microbiology, Boston University School of Medicine, Boston, MA 02118, USA
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Adam J. Hume
- Department of Microbiology, Boston University School of Medicine, Boston, MA 02118, USA
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
- Center for Emerging Infectious Diseases Policy & Research, Boston University, Boston, MA 02118, USA
| |
Collapse
|
14
|
Khozyainova AA, Valyaeva AA, Arbatsky MS, Isaev SV, Iamshchikov PS, Volchkov EV, Sabirov MS, Zainullina VR, Chechekhin VI, Vorobev RS, Menyailo ME, Tyurin-Kuzmin PA, Denisov EV. Complex Analysis of Single-Cell RNA Sequencing Data. BIOCHEMISTRY (MOSCOW) 2023; 88:231-252. [PMID: 37072324 PMCID: PMC10000364 DOI: 10.1134/s0006297923020074] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Single-cell RNA sequencing (scRNA-seq) is a revolutionary tool for studying the physiology of normal and pathologically altered tissues. This approach provides information about molecular features (gene expression, mutations, chromatin accessibility, etc.) of cells, opens up the possibility to analyze the trajectories/phylogeny of cell differentiation and cell-cell interactions, and helps in discovery of new cell types and previously unexplored processes. From a clinical point of view, scRNA-seq facilitates deeper and more detailed analysis of molecular mechanisms of diseases and serves as a basis for the development of new preventive, diagnostic, and therapeutic strategies. The review describes different approaches to the analysis of scRNA-seq data, discusses the advantages and disadvantages of bioinformatics tools, provides recommendations and examples of their successful use, and suggests potential directions for improvement. We also emphasize the need for creating new protocols, including multiomics ones, for the preparation of DNA/RNA libraries of single cells with the purpose of more complete understanding of individual cells.
Collapse
Affiliation(s)
- Anna A Khozyainova
- Laboratory of Cancer Progression Biology, Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, 634050, Russia.
| | - Anna A Valyaeva
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, 119991, Russia
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, 119991, Russia
| | - Mikhail S Arbatsky
- Laboratory of Artificial Intelligence and Bioinformatics, The Russian Clinical Research Center for Gerontology, Pirogov Russian National Medical University, Moscow, 129226, Russia
- School of Public Administration, Lomonosov Moscow State University, Moscow, 119991, Russia
- Faculty of Fundamental Medicine, Lomonosov Moscow State University, Moscow, 119991, Russia
| | - Sergey V Isaev
- Research Institute of Personalized Medicine, National Center for Personalized Medicine of Endocrine Diseases, National Medical Research Center for Endocrinology, Moscow, 117036, Russia
| | - Pavel S Iamshchikov
- Laboratory of Cancer Progression Biology, Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, 634050, Russia
- Laboratory of Complex Analysis of Big Bioimage Data, National Research Tomsk State University, Tomsk, 634050, Russia
| | - Egor V Volchkov
- Department of Oncohematology, Dmitry Rogachev National Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, 117198, Russia
| | - Marat S Sabirov
- Laboratory of Bioinformatics and Molecular Genetics, Koltzov Institute of Developmental Biology of the Russian Academy of Sciences, Moscow, 119334, Russia
| | - Viktoria R Zainullina
- Laboratory of Cancer Progression Biology, Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, 634050, Russia
| | - Vadim I Chechekhin
- Faculty of Fundamental Medicine, Lomonosov Moscow State University, Moscow, 119991, Russia
| | - Rostislav S Vorobev
- Laboratory of Cancer Progression Biology, Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, 634050, Russia
| | - Maxim E Menyailo
- Laboratory of Cancer Progression Biology, Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, 634050, Russia
| | - Pyotr A Tyurin-Kuzmin
- Faculty of Fundamental Medicine, Lomonosov Moscow State University, Moscow, 119991, Russia
| | - Evgeny V Denisov
- Laboratory of Cancer Progression Biology, Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, 634050, Russia
| |
Collapse
|
15
|
Development of Single-Cell Transcriptomics and Its Application in COVID-19. Viruses 2022; 14:v14102271. [PMID: 36298825 PMCID: PMC9611071 DOI: 10.3390/v14102271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 09/30/2022] [Accepted: 10/11/2022] [Indexed: 11/07/2022] Open
Abstract
Over the last three years, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related health crisis has claimed over six million lives and caused USD 12 trillion losses to the global economy. SARS-CoV-2 continuously mutates and evolves with a high basic reproduction number (R0), resulting in a variety of clinical manifestations ranging from asymptomatic infection to acute respiratory distress syndrome (ARDS) and even death. To gain a better understanding of coronavirus disease 2019 (COVID-19), it is critical to investigate the components that cause various clinical manifestations. Single-cell sequencing has substantial advantages in terms of identifying differentially expressed genes among individual cells, which can provide a better understanding of the various physiological and pathological processes. This article reviewed the use of single-cell transcriptomics in COVID-19 research, examined the immune response disparities generated by SARS-CoV-2, and offered insights regarding how to improve COVID-19 diagnosis and treatment plans.
Collapse
|
16
|
Geraldes I, Fernandes M, Fraga AG, Osório NS. The impact of single-cell genomics on the field of mycobacterial infection. Front Microbiol 2022; 13:989464. [PMID: 36246265 PMCID: PMC9562642 DOI: 10.3389/fmicb.2022.989464] [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: 07/08/2022] [Accepted: 09/14/2022] [Indexed: 11/13/2022] Open
Abstract
Genome sequencing projects of humans and other organisms reinforced that the complexity of biological systems is largely attributed to the tight regulation of gene expression at the epigenome and RNA levels. As a consequence, plenty of technological developments arose to increase the sequencing resolution to the cell dimension creating the single-cell genomics research field. Single-cell RNA sequencing (scRNA-seq) is leading the advances in this topic and comprises a vast array of different methodologies. scRNA-seq and its variants are more and more used in life science and biomedical research since they provide unbiased transcriptomic sequencing of large populations of individual cells. These methods go beyond the previous “bulk” methodologies and sculpt the biological understanding of cellular heterogeneity and dynamic transcriptomic states of cellular populations in immunology, oncology, and developmental biology fields. Despite the large burden caused by mycobacterial infections, advances in this field obtained via single-cell genomics had been comparatively modest. Nonetheless, seminal research publications using single-cell transcriptomics to study host cells infected by mycobacteria have become recently available. Here, we review these works summarizing the most impactful findings and emphasizing the different and recent single-cell methodologies used, potential issues, and problems. In addition, we aim at providing insights into current research gaps and potential future developments related to the use of single-cell genomics to study mycobacterial infection.
Collapse
Affiliation(s)
- Inês Geraldes
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's—PT Government Associate Laboratory, Braga, Portugal
| | - Mónica Fernandes
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's—PT Government Associate Laboratory, Braga, Portugal
| | - Alexandra G. Fraga
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's—PT Government Associate Laboratory, Braga, Portugal
| | - Nuno S. Osório
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's—PT Government Associate Laboratory, Braga, Portugal
- *Correspondence: Nuno S. Osório
| |
Collapse
|
17
|
Wu J, Ding Y, Wang J, Lyu F, Tang Q, Song J, Luo Z, Wan Q, Lan X, Xu Z, Chen L. Single‐cell RNA
sequencing in oral science: Current awareness and perspectives. Cell Prolif 2022; 55:e13287. [PMID: 35842899 PMCID: PMC9528768 DOI: 10.1111/cpr.13287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 05/10/2022] [Accepted: 05/29/2022] [Indexed: 11/30/2022] Open
Abstract
The emergence of single‐cell RNA sequencing enables simultaneous sequencing of thousands of cells, making the analysis of cell population heterogeneity more efficient. In recent years, single‐cell RNA sequencing has been used in the investigation of heterogeneous cell populations, cellular developmental trajectories, stochastic gene transcriptional kinetics, and gene regulatory networks, providing strong support in life science research. However, the application of single‐cell RNA sequencing in the field of oral science has not been reviewed comprehensively yet. Therefore, this paper reviews the development and application of single‐cell RNA sequencing in oral science, including fields of tissue development, teeth and jaws diseases, maxillofacial tumors, infections, etc., providing reference and prospects for using single‐cell RNA sequencing in studying the oral diseases, tissue development, and regeneration.
Collapse
Affiliation(s)
- Jie Wu
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Guanghua School of Stomatology, Hospital of Stomatology, Guangdong Provincial Key Laboratory of Stomatology Sun Yat‐sen University Guangzhou China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
| | - Yumei Ding
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
| | - Jinyu Wang
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
| | - Fengyuan Lyu
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
- Center of Stomatology, Tongji Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
| | - Qingming Tang
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
| | - Jiangyuan Song
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
| | - Zhiqiang Luo
- National Engineering Research Center for Nanomedicine College of Life Science and Technolog Huazhong University of Science and Technology Wuhan China
| | - Qian Wan
- Hubei Key Laboratory of Natural Medicinal Chemistry and Resource Evaluation, School of Pharmacy Huazhong University of Science and Technology Wuhan China
- Institute of Brain Research Huazhong University of Science and Technology Wuhan China
| | - Xiaoli Lan
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Key Laboratory of Molecular Imaging Wuhan China
| | - Zhi Xu
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
| | - Lili Chen
- Department of Stomatology, Union Hospital, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- School of Stomatology, Tongji Medical College Huazhong University of Science and Technology Wuhan China
- Hubei Province Key Laboratory of Oral and Maxillofacial Development and Regeneration Wuhan China
| |
Collapse
|
18
|
Becker J, Fakhiri J, Grimm D. Fantastic AAV Gene Therapy Vectors and How to Find Them—Random Diversification, Rational Design and Machine Learning. Pathogens 2022; 11:pathogens11070756. [PMID: 35890005 PMCID: PMC9318892 DOI: 10.3390/pathogens11070756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 06/30/2022] [Accepted: 07/01/2022] [Indexed: 11/16/2022] Open
Abstract
Parvoviruses are a diverse family of small, non-enveloped DNA viruses that infect a wide variety of species, tissues and cell types. For over half a century, their intriguing biology and pathophysiology has fueled intensive research aimed at dissecting the underlying viral and cellular mechanisms. Concurrently, their broad host specificity (tropism) has motivated efforts to develop parvoviruses as gene delivery vectors for human cancer or gene therapy applications. While the sum of preclinical and clinical data consistently demonstrates the great potential of these vectors, these findings also illustrate the importance of enhancing and restricting in vivo transgene expression in desired cell types. To this end, major progress has been made especially with vectors based on Adeno-associated virus (AAV), whose capsid is highly amenable to bioengineering, repurposing and expansion of its natural tropism. Here, we provide an overview of the state-of-the-art approaches to create new AAV variants with higher specificity and efficiency of gene transfer in on-target cells. We first review traditional and novel directed evolution approaches, including high-throughput screening of AAV capsid libraries. Next, we discuss programmable receptor-mediated targeting with a focus on two recent technologies that utilize high-affinity binders. Finally, we highlight one of the latest stratagems for rational AAV vector characterization and optimization, namely, machine learning, which promises to facilitate and accelerate the identification of next-generation, safe and precise gene delivery vehicles.
Collapse
Affiliation(s)
- Jonas Becker
- Department of Infectious Diseases/Virology, Medical Faculty, University of Heidelberg, Center for Integrative Infectious Diseases Research (CIID), BioQuant, 69120 Heidelberg, Germany;
- Faculty of Biosciences, University of Heidelberg, 69120 Heidelberg, Germany
| | - Julia Fakhiri
- Roche Pharma Research and Early Development, Therapeutic Modalities, Roche Innovation Center Munich, Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany
- Correspondence: (J.F.); (D.G.); Tel.: +49-174-3486203 (J.F.); +49-6221-5451331 (D.G.)
| | - Dirk Grimm
- Department of Infectious Diseases/Virology, Medical Faculty, University of Heidelberg, Center for Integrative Infectious Diseases Research (CIID), BioQuant, 69120 Heidelberg, Germany;
- German Center for Infection Research (DZIF), Partner Site Heidelberg, 69120 Heidelberg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Heidelberg, 69120 Heidelberg, Germany
- Correspondence: (J.F.); (D.G.); Tel.: +49-174-3486203 (J.F.); +49-6221-5451331 (D.G.)
| |
Collapse
|
19
|
Dai X, Cai L, He F. Single-cell sequencing: expansion, integration and translation. Brief Funct Genomics 2022; 21:280-295. [PMID: 35753690 DOI: 10.1093/bfgp/elac011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 05/16/2022] [Accepted: 05/24/2022] [Indexed: 12/11/2022] Open
Abstract
With the rapid advancement in sequencing technologies, the concept of omics has revolutionized our understanding of cellular behaviors. Conventional omics investigation approaches measure the averaged behaviors of multiple cells, which may easily hide signals represented by a small-cell cohort, urging for the development of techniques with enhanced resolution. Single-cell RNA sequencing, investigating cell transcriptomics at the resolution of a single cell, has been rapidly expanded to investigate other omics such as genomics, proteomics and metabolomics since its invention. The requirement for comprehensive understanding of complex cellular behavior has led to the integration of multi-omics and single-cell sequencing data with other layers of information such as spatial data and the CRISPR screening technique towards gained knowledge or innovative functionalities. The development of single-cell sequencing in both dimensions has rendered it a unique field that offers us a versatile toolbox to delineate complex diseases, including cancers.
Collapse
|
20
|
Luo L, Gribskov M, Wang S. Bibliometric review of ATAC-Seq and its application in gene expression. Brief Bioinform 2022; 23:6543486. [PMID: 35255493 PMCID: PMC9116206 DOI: 10.1093/bib/bbac061] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 02/06/2022] [Accepted: 02/09/2022] [Indexed: 11/30/2022] Open
Abstract
With recent advances in high-throughput next-generation sequencing, it is possible to describe the regulation and expression of genes at multiple levels. An assay for transposase-accessible chromatin using sequencing (ATAC-seq), which uses Tn5 transposase to sequence protein-free binding regions of the genome, can be combined with chromatin immunoprecipitation coupled with deep sequencing (ChIP-seq) and ribonucleic acid sequencing (RNA-seq) to provide a detailed description of gene expression. Here, we reviewed the literature on ATAC-seq and described the characteristics of ATAC-seq publications. We then briefly introduced the principles of RNA-seq, ChIP-seq and ATAC-seq, focusing on the main features of the techniques. We built a phylogenetic tree from species that had been previously studied by using ATAC-seq. Studies of Mus musculus and Homo sapiens account for approximately 90% of the total ATAC-seq data, while other species are still in the process of accumulating data. We summarized the findings from human diseases and other species, illustrating the cutting-edge discoveries and the role of multi-omics data analysis in current research. Moreover, we collected and compared ATAC-seq analysis pipelines, which allowed biological researchers who lack programming skills to better analyze and explore ATAC-seq data. Through this review, it is clear that multi-omics analysis and single-cell sequencing technology will become the mainstream approach in future research.
Collapse
Affiliation(s)
- Liheng Luo
- School of Life Sciences, Northwestern Polytechnical University, Xi'an, Shaanxi, China, 710072
| | - Michael Gribskov
- Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA
| | - Sufang Wang
- School of Life Sciences, Northwestern Polytechnical University, Xi'an, Shaanxi, China, 710072
| |
Collapse
|
21
|
Zhang P, Li X, Pan C, Zheng X, Hu B, Xie R, Hu J, Shang X, Yang H. Single-cell RNA sequencing to track novel perspectives in HSC heterogeneity. Stem Cell Res Ther 2022; 13:39. [PMID: 35093185 PMCID: PMC8800338 DOI: 10.1186/s13287-022-02718-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 01/06/2022] [Indexed: 12/21/2022] Open
Abstract
As the importance of cell heterogeneity has begun to be emphasized, single-cell sequencing approaches are rapidly adopted to study cell heterogeneity and cellular evolutionary relationships of various cells, including stem cell populations. The hematopoietic stem and progenitor cell (HSPC) compartment contains HSC hematopoietic stem cells (HSCs) and distinct hematopoietic cells with different abilities to self-renew. These cells perform their own functions to maintain different hematopoietic lineages. Undeniably, single-cell sequencing approaches, including single-cell RNA sequencing (scRNA-seq) technologies, empower more opportunities to study the heterogeneity of normal and pathological HSCs. In this review, we discuss how these scRNA-seq technologies contribute to tracing origin and lineage commitment of HSCs, profiling the bone marrow microenvironment and providing high-resolution dissection of malignant hematopoiesis, leading to exciting new findings in HSC biology.
Collapse
|
22
|
Chahine Z, Le Roch KG. Decrypting the complexity of the human malaria parasite biology through systems biology approaches. FRONTIERS IN SYSTEMS BIOLOGY 2022; 2:940321. [PMID: 37200864 PMCID: PMC10191146 DOI: 10.3389/fsysb.2022.940321] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
The human malaria parasite, Plasmodium falciparum, is a unicellular protozoan responsible for over half a million deaths annually. With a complex life cycle alternating between human and invertebrate hosts, this apicomplexan is notoriously adept at evading host immune responses and developing resistance to all clinically administered treatments. Advances in omics-based technologies, increased sensitivity of sequencing platforms and enhanced CRISPR based gene editing tools, have given researchers access to more in-depth and untapped information about this enigmatic micro-organism, a feat thought to be infeasible in the past decade. Here we discuss some of the most important scientific achievements made over the past few years with a focus on novel technologies and platforms that set the stage for subsequent discoveries. We also describe some of the systems-based methods applied to uncover gaps of knowledge left through single-omics applications with the hope that we will soon be able to overcome the spread of this life-threatening disease.
Collapse
|
23
|
Li H, Zhu L, Wang R, Xie L, Chen Y, Duan R, Liu X, Huang Z, Chen B, Li Z, Wang X, Su W. Therapeutic Effect of IL-38 on Experimental Autoimmune Uveitis: Reprogrammed Immune Cell Landscape and Reduced Th17 Cell Pathogenicity. Invest Ophthalmol Vis Sci 2021; 62:31. [PMID: 34967854 PMCID: PMC8727319 DOI: 10.1167/iovs.62.15.31] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 12/13/2021] [Indexed: 11/24/2022] Open
Abstract
Purpose The purpose of this study was to elucidate the effects of interleukin (IL)-38 on experimental autoimmune uveitis (EAU) and its underlying mechanisms. Methods Mice with EAU were treated with IL-38, and the retinas and cervical draining lymph nodes (CDLNs) were analyzed by flow cytometry. Single-cell RNA sequencing (scRNA-seq) was conducted to analyze the immune cell profiles of CDLNs from normal, EAU, and IL-38-treated mice. Results Administration of IL-38 attenuated EAU symptoms and reduced the proportion of T helper 17 (Th17) and T helper 1 (Th1) cells in the retinas and CDLNs. In scRNA-seq analysis, IL-38 downregulated the IL-17 signaling pathway and reduced the expression of Th17 cell pathogenicity-related genes (Csf2 and Il23r), findings which were also confirmed by flow cytometry. In vitro, IL-38 reduced the granulocyte-macrophage colony-stimulating factor (GM-CSF) stimulation function of IL-23 and inhibited IL-23R expression in Th17 cells. Moreover, when co-cultured with Th17 cells, IL-38 prevented IL-23 production in antigen-presenting cells (APCs). Conclusions Our data demonstrate the therapeutic effect of IL-38 on EAU, and suggest that the effect of IL-38 may be caused by dampening of the GM-CSF/IL-23R/IL-23 feedback loop between Th17 cells and APCs.
Collapse
Affiliation(s)
- He Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Lei Zhu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Rong Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Lihui Xie
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Yuxi Chen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Runping Duan
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Xiuxing Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Zhaohao Huang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Binyao Chen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Zhaohuai Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| | - Xianggui Wang
- Eye Center of Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Ophthalmology, Xiangya Hospital, Central South University, Changsha, China
| | - Wenru Su
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangzhou, China
| |
Collapse
|
24
|
Li X, Wang C, Peng T, Chai Z, Ni D, Liu Y, Zhang J, Chen T, Lu S. Atomic-scale insights into allosteric inhibition and evolutional rescue mechanism of Streptococcus thermophilus Cas9 by the anti-CRISPR protein AcrIIA6. Comput Struct Biotechnol J 2021; 19:6108-6124. [PMID: 34900128 PMCID: PMC8632846 DOI: 10.1016/j.csbj.2021.11.010] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 11/10/2021] [Accepted: 11/11/2021] [Indexed: 12/26/2022] Open
Abstract
CRISPR-Cas systems are prokaryotic adaptive immunity against invading phages and plasmids. Phages have evolved diverse protein inhibitors of CRISPR-Cas systems, called anti-CRISPR (Acr) proteins, to neutralize this CRISPR machinery. In response, bacteria have co-evolved Cas variants to escape phage's anti-CRISPR strategies, called anti-anti-CRISPR systems. Here we explore the anti-CRISPR allosteric inhibition and anti-anti-CRISPR rescue mechanisms between Streptococcus thermophilus Cas9 (St1Cas9) and the anti-CRISPR protein AcrIIA6 at the atomic level, by generating mutants of key residues in St1Cas9. Extensive unbiased molecular dynamics simulations show that the functional motions of St1Cas9 in the presence of AcrIIA6 differ substantially from those of St1Cas9 alone. AcrIIA6 binding triggers a shift of St1Cas9 conformational ensemble towards a less catalytically competent state; this state significantly compromises protospacer adjacent motif (PAM) recognition and nuclease activity by altering interdependently conformational dynamics and allosteric signals among nuclease domains, PAM-interacting (PI) regions, and AcrIIA6 binding motifs. Via in vitro DNA cleavage assays, we further elucidate the rescue mechanism of efficiently escaping AcrIIA6 inhibition harboring St1Cas9 triple mutations (G993K/K1008M/K1010E) in the PI domain and identify the evolutionary landscape of such mutational escape within species. Our results provide mechanistic insights into Acr proteins as natural brakes for the CRISPR-Cas systems and a promising potential for the design of allosteric Acr peptidomimetics.
Collapse
Affiliation(s)
- Xinyi Li
- Department of Cardiology, Changzheng Hospital, Naval Medical University, Shanghai 200003, China
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Chengxiang Wang
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Ting Peng
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Zongtao Chai
- Department of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai 200438, China
| | - Duan Ni
- The Charles Perkins Centre, University of Sydney, Sydney, NSW 2006, Australia
| | - Yaqin Liu
- Medicinal Chemistry and Bioinformatics Centre, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Jian Zhang
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
- Medicinal Chemistry and Bioinformatics Centre, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Ting Chen
- Department of Cardiology, Changzheng Hospital, Naval Medical University, Shanghai 200003, China
| | - Shaoyong Lu
- Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
- Medicinal Chemistry and Bioinformatics Centre, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| |
Collapse
|
25
|
Artificial Intelligence in Differential Diagnostics of Meningitis: A Nationwide Study. Diagnostics (Basel) 2021; 11:diagnostics11040602. [PMID: 33800653 PMCID: PMC8065596 DOI: 10.3390/diagnostics11040602] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 03/23/2021] [Accepted: 03/26/2021] [Indexed: 11/17/2022] Open
Abstract
Differential diagnosis between bacterial and viral meningitis is crucial. In our study, to differentiate bacterial vs. viral meningitis, three machine learning (ML) algorithms (multiple logistic regression (MLR), random forest (RF), and naïve-Bayes (NB)) were applied for the two age groups (0-14 and >14 years) of patients with meningitis by both conventional (culture) and molecular (PCR) methods. Cerebrospinal fluid (CSF) neutrophils, CSF lymphocytes, neutrophil-to-lymphocyte ratio (NLR), blood albumin, blood C-reactive protein (CRP), glucose, blood soluble urokinase-type plasminogen activator receptor (suPAR), and CSF lymphocytes-to-blood CRP ratio (LCR) were used as predictors for the ML algorithms. The performance of the ML algorithms was evaluated through a cross-validation procedure, and optimal predictions of the type of meningitis were above 95% for viral and 78% for bacterial meningitis. Overall, MLR and RF yielded the best performance when using CSF neutrophils, CSF lymphocytes, NLR, albumin, glucose, gender, and CRP. Also, our results reconfirm the high diagnostic accuracy of NLR in the differential diagnosis between bacterial and viral meningitis.
Collapse
|
26
|
Zhang Y, Wang D, Peng M, Tang L, Ouyang J, Xiong F, Guo C, Tang Y, Zhou Y, Liao Q, Wu X, Wang H, Yu J, Li Y, Li X, Li G, Zeng Z, Tan Y, Xiong W. Single-cell RNA sequencing in cancer research. JOURNAL OF EXPERIMENTAL & CLINICAL CANCER RESEARCH : CR 2021; 40:81. [PMID: 33648534 PMCID: PMC7919320 DOI: 10.1186/s13046-021-01874-1] [Citation(s) in RCA: 106] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 02/08/2021] [Indexed: 02/06/2023]
Abstract
Single-cell RNA sequencing (scRNA-seq), a technology that analyzes transcriptomes of complex tissues at single-cell levels, can identify differential gene expression and epigenetic factors caused by mutations in unicellular genomes, as well as new cell-specific markers and cell types. scRNA-seq plays an important role in various aspects of tumor research. It reveals the heterogeneity of tumor cells and monitors the progress of tumor development, thereby preventing further cellular deterioration. Furthermore, the transcriptome analysis of immune cells in tumor tissue can be used to classify immune cells, their immune escape mechanisms and drug resistance mechanisms, and to develop effective clinical targeted therapies combined with immunotherapy. Moreover, this method enables the study of intercellular communication and the interaction of tumor cells and non-malignant cells to reveal their role in carcinogenesis. scRNA-seq provides new technical means for further development of tumor research and is expected to make significant breakthroughs in this field. This review focuses on the principles of scRNA-seq, with an emphasis on the application of scRNA-seq in tumor heterogeneity, pathogenesis, and treatment.
Collapse
Affiliation(s)
- Yijie Zhang
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer Metabolism, The Affiliated Cancer Hospital of Xiangya School of Medicine, Hunan Cancer Hospital, Central South University, Changsha, Hunan, China.,Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute, Central South University, Changsha, Hunan, China.,Hunan Key Laboratory of Nonresolving Inflammation and Cancer, Disease Genome Research Center, the Third Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Dan Wang
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute, Central South University, Changsha, Hunan, China
| | - Miao Peng
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute, Central South University, Changsha, Hunan, China
| | - Le Tang
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute, Central South University, Changsha, Hunan, China
| | - Jiawei Ouyang
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute, Central South University, Changsha, Hunan, China
| | - Fang Xiong
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute, Central South University, Changsha, Hunan, China
| | - Can Guo
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute, Central South University, Changsha, Hunan, China
| | - Yanyan Tang
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer Metabolism, The Affiliated Cancer Hospital of Xiangya School of Medicine, Hunan Cancer Hospital, Central South University, Changsha, Hunan, China
| | - Yujuan Zhou
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer Metabolism, The Affiliated Cancer Hospital of Xiangya School of Medicine, Hunan Cancer Hospital, Central South University, Changsha, Hunan, China
| | - Qianjin Liao
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer Metabolism, The Affiliated Cancer Hospital of Xiangya School of Medicine, Hunan Cancer Hospital, Central South University, Changsha, Hunan, China
| | - Xu Wu
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer Metabolism, The Affiliated Cancer Hospital of Xiangya School of Medicine, Hunan Cancer Hospital, Central South University, Changsha, Hunan, China.,Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute, Central South University, Changsha, Hunan, China
| | - Hui Wang
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer Metabolism, The Affiliated Cancer Hospital of Xiangya School of Medicine, Hunan Cancer Hospital, Central South University, Changsha, Hunan, China
| | - Jianjun Yu
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer Metabolism, The Affiliated Cancer Hospital of Xiangya School of Medicine, Hunan Cancer Hospital, Central South University, Changsha, Hunan, China
| | - Yong Li
- Department of Medicine, Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA
| | - Xiaoling Li
- Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute, Central South University, Changsha, Hunan, China
| | - Guiyuan Li
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer Metabolism, The Affiliated Cancer Hospital of Xiangya School of Medicine, Hunan Cancer Hospital, Central South University, Changsha, Hunan, China.,Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute, Central South University, Changsha, Hunan, China.,Hunan Key Laboratory of Nonresolving Inflammation and Cancer, Disease Genome Research Center, the Third Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Zhaoyang Zeng
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer Metabolism, The Affiliated Cancer Hospital of Xiangya School of Medicine, Hunan Cancer Hospital, Central South University, Changsha, Hunan, China.,Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute, Central South University, Changsha, Hunan, China.,Hunan Key Laboratory of Nonresolving Inflammation and Cancer, Disease Genome Research Center, the Third Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yixin Tan
- Department of Dermatology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
| | - Wei Xiong
- NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer Metabolism, The Affiliated Cancer Hospital of Xiangya School of Medicine, Hunan Cancer Hospital, Central South University, Changsha, Hunan, China. .,Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute, Central South University, Changsha, Hunan, China. .,Hunan Key Laboratory of Nonresolving Inflammation and Cancer, Disease Genome Research Center, the Third Xiangya Hospital, Central South University, Changsha, Hunan, China.
| |
Collapse
|
27
|
Park BJ, Ahn HS, Han SH, Go HJ, Kim DH, Choi C, Jung S, Myoung J, Lee JB, Park SY, Song CS, Lee SW, Lee HT, Choi IS. Analysis of the Immune Responses in the Ileum of Gnotobiotic Pigs Infected with the Recombinant GII.p12_GII.3 Human Norovirus by mRNA Sequencing. Viruses 2021; 13:v13010092. [PMID: 33440894 PMCID: PMC7826840 DOI: 10.3390/v13010092] [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: 12/07/2020] [Revised: 12/29/2020] [Accepted: 01/08/2021] [Indexed: 11/20/2022] Open
Abstract
Norovirus genogroup II (NoV GII) induces acute gastrointestinal food-borne illness in humans. Because gnotobiotic pigs can be infected with human norovirus (HuNoV) GII, they are frequently used to analyze the associated pathogenic mechanisms and immune responses, which remain poorly understood. Recently, mRNA sequencing analysis (RNA-Seq) has been used to identify cellular responses to viruses. In this study, we investigated the host immune response and possible mechanisms involved in virus evasion in the ileum of gnotobiotic pigs infected with HuNoV by RNA-Seq. HuNoV was detected in the feces, blood, and tissues of the jejunum, ileum, colon, mesenteric lymph node, and spleen of pigs infected with HuNoV. In analysis of mRNA sequencing, expression of anti-viral protein genes such as OAS1, MX1, and MX2 were largely decreased, whereas type I IFN was increased in pigs infected with HuNoV. In addition, expression of TNF and associated anti-inflammatory cytokine genes such as IL10 was increased in HuNoV-infected pigs. Expression of genes related to natural killer (NK) cell cytotoxicity and CD8+ T cell exhaustion was increased, whereas that of MHC class I genes was decreased. Expression profiles of selected genes were further confirmed by qRT-PCR and Western blot. These results suggest that infection with HuNoV induces NK cell-mediated cytotoxicity but suppresses type I IFN- and CD8+ T cell-mediated antiviral responses.
Collapse
Affiliation(s)
- Byung-Joo Park
- Department of Infectious Diseases, College of Veterinary Medicine, Konkuk University, Gwangjin-gu, Seoul 05029, Korea; (B.-J.P.); (H.-S.A.); (S.-H.H.); (H.-J.G.); (D.-H.K.); (J.-B.L.); (S.-Y.P.); (C.-S.S.); (S.-W.L.)
| | - Hee-Seop Ahn
- Department of Infectious Diseases, College of Veterinary Medicine, Konkuk University, Gwangjin-gu, Seoul 05029, Korea; (B.-J.P.); (H.-S.A.); (S.-H.H.); (H.-J.G.); (D.-H.K.); (J.-B.L.); (S.-Y.P.); (C.-S.S.); (S.-W.L.)
| | - Sang-Hoon Han
- Department of Infectious Diseases, College of Veterinary Medicine, Konkuk University, Gwangjin-gu, Seoul 05029, Korea; (B.-J.P.); (H.-S.A.); (S.-H.H.); (H.-J.G.); (D.-H.K.); (J.-B.L.); (S.-Y.P.); (C.-S.S.); (S.-W.L.)
| | - Hyeon-Jeong Go
- Department of Infectious Diseases, College of Veterinary Medicine, Konkuk University, Gwangjin-gu, Seoul 05029, Korea; (B.-J.P.); (H.-S.A.); (S.-H.H.); (H.-J.G.); (D.-H.K.); (J.-B.L.); (S.-Y.P.); (C.-S.S.); (S.-W.L.)
| | - Dong-Hwi Kim
- Department of Infectious Diseases, College of Veterinary Medicine, Konkuk University, Gwangjin-gu, Seoul 05029, Korea; (B.-J.P.); (H.-S.A.); (S.-H.H.); (H.-J.G.); (D.-H.K.); (J.-B.L.); (S.-Y.P.); (C.-S.S.); (S.-W.L.)
| | - Changsun Choi
- Department of Food and Nutrition, College of Biotechnology and Natural Resources, Chung-Ang University, Anseong, Gyeonggi 17546, Korea; (C.C.); (S.J.)
| | - Soontag Jung
- Department of Food and Nutrition, College of Biotechnology and Natural Resources, Chung-Ang University, Anseong, Gyeonggi 17546, Korea; (C.C.); (S.J.)
| | - Jinjong Myoung
- Korea Zoonosis Research Institute, Chonbuk National University, Jeonju, Jeollabuk-do 54896, Korea;
| | - Joong-Bok Lee
- Department of Infectious Diseases, College of Veterinary Medicine, Konkuk University, Gwangjin-gu, Seoul 05029, Korea; (B.-J.P.); (H.-S.A.); (S.-H.H.); (H.-J.G.); (D.-H.K.); (J.-B.L.); (S.-Y.P.); (C.-S.S.); (S.-W.L.)
| | - Seung-Yong Park
- Department of Infectious Diseases, College of Veterinary Medicine, Konkuk University, Gwangjin-gu, Seoul 05029, Korea; (B.-J.P.); (H.-S.A.); (S.-H.H.); (H.-J.G.); (D.-H.K.); (J.-B.L.); (S.-Y.P.); (C.-S.S.); (S.-W.L.)
| | - Chang-Seon Song
- Department of Infectious Diseases, College of Veterinary Medicine, Konkuk University, Gwangjin-gu, Seoul 05029, Korea; (B.-J.P.); (H.-S.A.); (S.-H.H.); (H.-J.G.); (D.-H.K.); (J.-B.L.); (S.-Y.P.); (C.-S.S.); (S.-W.L.)
| | - Sang-Won Lee
- Department of Infectious Diseases, College of Veterinary Medicine, Konkuk University, Gwangjin-gu, Seoul 05029, Korea; (B.-J.P.); (H.-S.A.); (S.-H.H.); (H.-J.G.); (D.-H.K.); (J.-B.L.); (S.-Y.P.); (C.-S.S.); (S.-W.L.)
| | - Hoon-Taek Lee
- Department of Bioscience and Biotechnology, Konkuk University, Seoul 05029, Korea;
| | - In-Soo Choi
- Department of Infectious Diseases, College of Veterinary Medicine, Konkuk University, Gwangjin-gu, Seoul 05029, Korea; (B.-J.P.); (H.-S.A.); (S.-H.H.); (H.-J.G.); (D.-H.K.); (J.-B.L.); (S.-Y.P.); (C.-S.S.); (S.-W.L.)
- Correspondence: ; Tel.: +82-2049-6228
| |
Collapse
|