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Yang J, Li Y, Ye J, Wang J, Lu H, Yao X. Characterization of the TCR β Chain Repertoire in Peripheral Blood from Hepatitis B Vaccine Responders and Non-Responders. J Inflamm Res 2022; 15:939-951. [PMID: 35210805 PMCID: PMC8856041 DOI: 10.2147/jir.s347702] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 01/26/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Hepatitis B (HepB) vaccination can effectively prevent the prevalence of hepatitis B virus (HBV) infection. However, the incidence of vaccination failure is about 5~10% and the underlying molecular mechanisms are poorly understood. T cells have an essential role in the recipient's immune response to vaccine, which could be elucidated by high-throughput sequencing (HTS) and bioinformatics analysis. METHODS We conducted HTS of the T cell receptor β chain (TRB) complementarity-determining region 3 (CDR3) repertoires in eighteen positive responders (responders) and 10 negative responders (non-responders) who all had HepB vaccination, the repertoire features of BV, BJ and V-J genes and their diversity, respectively, were compared between the positive and negative responders using the Mann-Whitney test. Moreover, the relatively conserved motifs in CDR3 were revealed and compared to those in the other group's report. RESULTS The diversity of TRB CDR3 and the frequencies of BV27 and BV7-9 are significantly increased for HepB vaccine responders compared to those in non-responders. The motifs of CDR3s in BV27/J1-1, BV27/J2-5, and BV7-9/J2-5, respectively, were most expressed as "NTE", "QETQ", and "GG-Q (E)-ETQ". Moreover, the motif "KLNSPL" was determined in nearly 80% CDR3s in BV27/J1-6 from HepB vaccine responders for the first time. CONCLUSION Our results present the comprehensive profiles of TRB CDR3 in the HepB vaccine responders and non-responders after standard vaccination protocol and determine the relatively conservative motifs of CDR3s that may respond to the HepB vaccine. Further results suggest that the profile of TRB repertoire could distinguish the HepB vaccine responders from non-responders and provide a new target for optimizing and improving the efficiency of the HepB vaccine.
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Affiliation(s)
- Jiezuan Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Infectious Diseases, Hangzhou, People’s Republic of China
| | - Yongtao Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Infectious Diseases, Hangzhou, People’s Republic of China
| | - Jing Ye
- Department of Surgical ICU, The Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, People’s Republic of China
| | - Ju Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Infectious Diseases, Hangzhou, People’s Republic of China
| | - Haifeng Lu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Infectious Diseases, Hangzhou, People’s Republic of China
| | - Xinsheng Yao
- Department of Immunology, Research Center for Medicine & Biology, Innovation & Practice Base for Graduate Students Education, Zunyi Medical University, Zunyi, People’s Republic of China
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2
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Wei L, Zhao T, Zhang J, Mao Q, Gong G, Sun Y, Chen Y, Wang M, Tan D, Gong Z, Li B, Niu J, Li S, Gong H, Zou L, Zhou W, Jia Z, Tang Y, Fei L, Hu Y, Shang X, Han J, Zhang B, Wu Y. Efficacy and safety of a nanoparticle therapeutic vaccine in patients with chronic hepatitis B: A randomized clinical trial. Hepatology 2022; 75:182-195. [PMID: 34396571 DOI: 10.1002/hep.32109] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 06/28/2021] [Accepted: 07/31/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND AIM HBV DNA can be reduced using antiviral drugs in patients with chronic hepatitis B (CHB); however, the rate of HBeAg seroconversion remains low. A clinical trial was conducted to assess the efficacy and safety of a de novo designed liposome-based nanoparticle lipopeptide vaccine, εPA-44, for CHB. APPROACH AND RESULTS A two-stage phase 2 trial, which included a 76-week, randomized, double-blind, placebo-controlled trial (stage 1) and a 68-week open-label extension (stage 2), was conducted in 15 centers across China (Clinicaltrials.gov No. NCT00869778). In stage 1, 360 human leukocyte antigen A2 (HLA-A2)-positive and HBeAg-positive patients were randomly and equally distributed to receive six subcutaneous injections of 600 µg or 900 µg εPA-44 or placebo at week 0, 4, 8, 12, 20, and 28. In stage 2, 183 patients received extended 900 µg εPA-44, and 26 patients were observed for relapse without further treatment. The primary endpoint was the percentage of patients with HBeAg seroconversion at week 76. At week 76, patients receiving 900 µg εPA-44 achieved significantly higher HBeAg seroconversion rate (38.8%) versus placebo (20.2%) (95% CI, 6.9-29.6%; p = 0.002). With a combined endpoint of HBeAg seroconversion, alanine aminotransferase normalization and HBV DNA < 2,000 IU/mL, both 900 µg (18.1%) and 600 µg (14.3%), resulted in significantly higher rate versus placebo (5.0%) (p = 0.002 and p = 0.02, respectively) at week 76. In stage 2, none (0 of 20) of 900 µg εPA-44-treated patients experienced serologic relapse. The safety profile of εPA-44 was comparable to that of placebo. CONCLUSIONS Among HLA-A2-positive patients with progressive CHB, a finite duration of 900 µg εPA-44 monotherapy resulted in significantly higher HBeAg seroconversion rate than placebo and sustained off-treatment effect. A phase 3 trial is ongoing (ChiCTR2100043708).
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Affiliation(s)
- Lai Wei
- Peking University People's Hospital, Peking University Hepatology institute, Beijing, China
| | - Tingting Zhao
- Chongqing International Institute for Immunology, Chongqing, China
| | - Ji Zhang
- Institute of Immunology, PLA, Army Medical University, Chongqing, China
| | - Qing Mao
- Infectious Diseases Institute of PLA, Southwest Hospital, Army Medical University, Chongqing, China
| | - Guozhong Gong
- Infectious Diseases Department, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yongtao Sun
- Infectious Diseases Department, Tangdu Hospital, Fourth Military Medical University, Xi'an, China
| | - Yongping Chen
- Infectious Diseases Department, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Maorong Wang
- Infectious Diseases Department, The 81th Hospital of PLA, Nanjing, China
| | - Deming Tan
- Infectious Diseases Department, Xiangya Hospital of Central South University, Changsha, China
| | - Zuojiong Gong
- Infectious Diseases Department, Renmin Hospital of Wuhan University, Wuhan, China
| | - Baosen Li
- Infectious Diseases Department, 302 Military Hospital, Beijing, China
| | - Junqi Niu
- Infectious Diseases Department, The First Hospital of Jilin University, Changchun, China
| | - Shuchen Li
- Infectious Diseases Department, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Huanyu Gong
- Infectious Diseases Department, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Liyun Zou
- Institute of Immunology, PLA, Army Medical University, Chongqing, China
| | - Wei Zhou
- Institute of Immunology, PLA, Army Medical University, Chongqing, China
| | - Zhengcai Jia
- Institute of Immunology, PLA, Army Medical University, Chongqing, China
| | - Yan Tang
- Institute of Immunology, PLA, Army Medical University, Chongqing, China
| | - Lei Fei
- Institute of Immunology, PLA, Army Medical University, Chongqing, China
| | - Yang Hu
- Institute of Immunology, PLA, Army Medical University, Chongqing, China
| | - Xiaoyun Shang
- Institute of Immunology, PLA, Army Medical University, Chongqing, China
| | - Junfeng Han
- Institute of Immunology, PLA, Army Medical University, Chongqing, China
| | - Bei Zhang
- Department of Immunology, Medical College of Qingdao University, Qingdao, China
| | - Yuzhang Wu
- Institute of Immunology, PLA, Army Medical University, Chongqing, China
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3
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Liu H, Pan W, Tang C, Tang Y, Wu H, Yoshimura A, Deng Y, He N, Li S. The methods and advances of adaptive immune receptors repertoire sequencing. Theranostics 2021; 11:8945-8963. [PMID: 34522220 PMCID: PMC8419057 DOI: 10.7150/thno.61390] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 06/09/2021] [Indexed: 12/13/2022] Open
Abstract
The adaptive immune response is a powerful tool, capable of recognizing, binding to, and neutralizing a vast number of internal and external threats via T or B lymphatic receptors with widespread sets of antigen specificities. The emergence of high-throughput sequencing technology and bioinformatics provides opportunities for research in the fields of life sciences and medicine. The analysis and annotation for immune repertoire data can reveal biologically meaningful information, including immune prediction, target antigens, and effective evaluation. Continuous improvements of the immunological repertoire sequencing methods and analysis tools will help to minimize the experimental and calculation errors and realize the immunological information to meet the clinical requirements. That said, the clinical application of adaptive immune repertoire sequencing requires appropriate experimental methods and standard analytical tools. At the population cell level, we can acquire the overview of cell groups, but the information about a single cell is not obtained accurately. The information that is ignored may be crucial for understanding the heterogeneity of each cell, gene expression and drug response. The combination of high-throughput sequencing and single-cell technology allows us to obtain single-cell information with low-cost and high-throughput. In this review, we summarized the current methods and progress in this area.
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Affiliation(s)
- Hongmei Liu
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou 412007, China
| | - Wenjing Pan
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou 412007, China
| | - Congli Tang
- State Key Laboratory of Bioelectronics, Southeast University, Nanjing 210096, China
| | - Yujie Tang
- State Key Laboratory of Bioelectronics, Southeast University, Nanjing 210096, China
| | - Haijing Wu
- Department of Dermatology, Second Xiangya Hospital, Central South University, Hu-nan Key Laboratory of Medical Epigenomics, Changsha, Hunan, China
| | - Akihiko Yoshimura
- Department of Microbiology and Immunology, Keio University School of Medicine, Tokyo, Japan
| | - Yan Deng
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou 412007, China
| | - Nongyue He
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou 412007, China
- State Key Laboratory of Bioelectronics, Southeast University, Nanjing 210096, China
| | - Song Li
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou 412007, China
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4
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Patel DN, Yeagley M, Arturo JF, Falasiri S, Chobrutskiy BI, Gozlan EC, Blanck G. A comparison of immune receptor recombination databases sourced from tumour exome or RNAseq files: Verifications of immunological distinctions between primary and metastatic melanoma. Int J Immunogenet 2021; 48:409-418. [PMID: 34298587 DOI: 10.1111/iji.12550] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 07/11/2021] [Indexed: 02/07/2023]
Abstract
It became apparent several years ago that RNAseq and exome files prepared from tissue could be mined for adaptive immune receptor (IR) recombinations, which has given extra value to datasets originally intended for gene expression or mutation studies. For example, recovery of IR recombination reads from tumour specimen genomics files can correlate with survival rates. In particular, many benchmarking processes have been applied to the two sets of the IR recombination reads obtained from the cancer genome atlas files, but these two sets have never been directly compared. Here we show that both sets largely agree regarding several parameters. For example, recovery of TRB recombination reads from both WXS and RNAseq files representing metastatic melanoma was associated with a better outcome (p < .0004 in both cases); and T-cell receptor recombination read recovery, for both genomics file types, associated very strongly with T-cell gene expression markers. However, the use of CDR3 chemical features for survival distinctions was not consistent. This topic, and the surprising result that both datasets indicated that primary melanoma with recovery of IR recombination reads, in stark contrast to metastatic melanoma, represents a worse outcome, are discussed.
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Affiliation(s)
- Dhruv N Patel
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Michelle Yeagley
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Juan F Arturo
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Shayan Falasiri
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Boris I Chobrutskiy
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Etienne C Gozlan
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - George Blanck
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.,Department of Immunology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
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5
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Yan D, Yang J, Ji Z, Wang J, Lu X, Huang Y, Zhong C, Li L. Profiling T cell receptor β-chain in responders after immunization with recombinant hepatitis B vaccine. J Gene Med 2021; 23:e3367. [PMID: 34048625 DOI: 10.1002/jgm.3367] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 05/22/2021] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND T cells with edited T cell receptor β-chain variable (TRBV) are involved in the immune response to recombinant hepatitis B surface antigen (rHBsAg) vaccine and the production of hepatitis B surface antibody (HBsAb). The immune repertoire (IR) profile and mechanism of vaccination positive responders (VPR) with rHBsAg are not fully understood. METHODS The IR of six VPRs (HBsAb+, HbsAg-) with rHBsAg vaccination was established by the high throughput sequencing technique and bioinformatics analysis and compared with those in five vaccination negative responders (VNRs) (HbsAb-, HbsAg-) who were also inoculated with rHBsAg. The repertoire features of the BV, BJ and V (CDR3) J genes and immune diversity in peripheral blood mononuclear cells, respectively, were analyzed for each subject. RESULTS There was no significant difference in sequencing amplification indices of each sample. However, TRBV15/BJ2-3 demonstrated significantly high expression levels in VPR compared to those in the VNR group (both p < 0.05). Further results showed that the BV15/BJ2-5 level was significantly increased for VPR compared to that of VNR group. Interestingly, the motif of CDR3 in TRBV15/BJ2-5 was mostly expressed as "GGETQ" or "GETQ". Additionally, there was no remarkable difference between the two groups of distribution with respect to the different clone expression levels of V (CDR3) J. CONCLUSIONS The features of IR in the VPR and VNR will contribute to the exploration of the mechanism of the positive response to rHBsAg, and also contribute to development of optimized hepatitis B vaccine, in addition to providing a partial interpretation of the VNR who has a relatively low infection with HBV.
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Affiliation(s)
- Dong Yan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases; National Clinical Research Center for Infectious Diseases; the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiezuan Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases; National Clinical Research Center for Infectious Diseases; the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhongkang Ji
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases; National Clinical Research Center for Infectious Diseases; the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ju Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases; National Clinical Research Center for Infectious Diseases; the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaoqing Lu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases; National Clinical Research Center for Infectious Diseases; the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yandi Huang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases; National Clinical Research Center for Infectious Diseases; the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chengli Zhong
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases; National Clinical Research Center for Infectious Diseases; the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lanjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases; National Clinical Research Center for Infectious Diseases; the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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6
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Xiao D, Wang J, Chen Z, Jin X, Xie Y, Yan D, Yang J. Restricted TcR β chain CDR3 clonotype is associated with resolved acute hepatitis B subjects. BMC Infect Dis 2021; 21:111. [PMID: 33485302 PMCID: PMC7825183 DOI: 10.1186/s12879-021-05816-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2020] [Accepted: 01/17/2021] [Indexed: 02/08/2023] Open
Abstract
Background T cells play an important role in the prognosis of hepatitis B virus (HBV) infection, and are involved in the seroconversion of a patient from HBsAb negative to positive. To compare the T-cell receptor β-chain variable region (TcRBV) complementarity-determining region 3 (CDR3) in subjects with or without hepatitis B surface antigen (HBsAg) convert to hepatitis B surface antibody (HBsAb), the TcRBV was determined using high throughput sequencing (HTS). Methods The clonotype and diversity of CDR3 in peripheral blood mononuclear cells of subjects with resolved acute hepatitis B (AHB, HBsAb+, HBsAg-) (n = 5), chronic hepatitis B (CHB, HBsAb-, HBsAg+) (n = 5), and healthy controls (HC, HBsAb-, HBsAg-) (n = 3) were determined and analyzed using HTS (MiSeq). Results The overlapping rate of CDR3 clones of any two samples in AHB group was 2.00% (1.74% ~ 2.30%), CHB group was 1.77% (1.43% ~ 2.61%), and HC group was 1.82% (1.62% ~ 2.12%), and there was no significant difference among the three groups by Kruskal-Wallis H test. However, among the top 10 cumulative frequencies of clonotypes, only the frequency of clonotype (TcRBV20–1/BD1/BJ1–2) in AHB group was lower than that of HC group (P < 0.001). Moreover, exclude the 10 top clonotypes, there are 57 markedly different frequency of clones between AHB and CHB groups (18 clones up, 39 clones down), 179 (180–1) different clones between AHB and HC groups, and 134 different clones between CHB and HC groups. With regard to BV and BJ genotypes, there was no significant different frequency among the groups. Furthermore, there was no significant difference in the diversity of TcRBV CDR3 among the three groups (P > 0.05). Conclusions Thus, there are 57 TcRBV clonotypes that may be related to HBsAg seroconversion of AHB subjects, but the diversity of TcRBV CDR3 is not significantly related to the HBsAb positive status. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-021-05816-2.
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Affiliation(s)
- Dangsheng Xiao
- Zhejiang Provincial Key Laboratory for Diagnosis and Treatment of Aging and Physic-chemical Injury Diseases, Department of Geriatrics, the First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Ju Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Zhitao Chen
- Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Xiuyuan Jin
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Yirui Xie
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Dong Yan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China.
| | - Jiezuan Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China.
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7
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Ni Q, Zhang J, Zheng Z, Chen G, Christian L, Grönholm J, Yu H, Zhou D, Zhuang Y, Li QJ, Wan Y. VisTCR: An Interactive Software for T Cell Repertoire Sequencing Data Analysis. Front Genet 2020; 11:771. [PMID: 32849789 PMCID: PMC7416706 DOI: 10.3389/fgene.2020.00771] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 06/29/2020] [Indexed: 11/13/2022] Open
Abstract
Recent progress in high throughput sequencing technologies has provided an opportunity to probe T cell receptor (TCR) repertoire, bringing about an explosion of TCR sequencing data and analysis tools. For easier and more heuristic analysis TCR sequencing data, we developed a client-based HTML program (VisTCR). It has a data storage module and a data analysis module that integrate multiple cutting-edge analysis algorithms in a hierarchical fashion. Researchers can group and re-group samples for different analysis purposes by customized "Experiment Design File." Moreover, the VisTCR provides a user-friendly interactive interface, by all the TCR analysis methods and visualization results can be accessed and saved as tables or graphs in the process of analysis. The source code is freely available at https://github.com/qingshanni/VisTCR.
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Affiliation(s)
- Qingshan Ni
- Biomedical Analysis Center, Army Medical University, Chongqing, China.,Chongqing Key Laboratory of Cytomics, Chongqing, China
| | - Jianyang Zhang
- Biomedical Analysis Center, Army Medical University, Chongqing, China.,Chongqing Key Laboratory of Cytomics, Chongqing, China
| | | | - Gang Chen
- Biomedical Analysis Center, Army Medical University, Chongqing, China.,Chongqing Key Laboratory of Cytomics, Chongqing, China
| | - Laura Christian
- Department of Immunology, Duke University Medical Center, Durham, NC, United States
| | - Juha Grönholm
- Molecular Development of the Immune System Section, NIAID Clinical Genomics Program, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Haili Yu
- Biomedical Analysis Center, Army Medical University, Chongqing, China.,Chongqing Key Laboratory of Cytomics, Chongqing, China
| | - Daxue Zhou
- Biomedical Analysis Center, Army Medical University, Chongqing, China.,Chongqing Key Laboratory of Cytomics, Chongqing, China
| | - Yuan Zhuang
- Department of Immunology, Duke University Medical Center, Durham, NC, United States
| | - Qi-Jing Li
- Department of Immunology, Duke University Medical Center, Durham, NC, United States
| | - Ying Wan
- Biomedical Analysis Center, Army Medical University, Chongqing, China.,Chongqing Key Laboratory of Cytomics, Chongqing, China
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8
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Li G, Li J, Zhang H, Zhang Y, Liu D, Hao Y, Han J, Du J, Zhu L, Zeng Y, Li B, Li R, Song C, Zhang F, Chen C, Zhao H, Zeng H. Partial recovery of disturbed V-J pairing profiles of T-cell receptor in people living with HIV receiving long-term antiretroviral therapy. SCIENCE CHINA-LIFE SCIENCES 2020; 64:152-161. [PMID: 32567004 PMCID: PMC7306449 DOI: 10.1007/s11427-020-1718-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Accepted: 05/16/2020] [Indexed: 02/07/2023]
Abstract
Chronic human immunodeficiency virus (HIV) infection not only causes a gradual loss of CD4+ T cells but also leads to a disturbance of the T cell receptor (TCR) repertoire. In people living with HIV (PLWH), monitoring TCR repertoire is challenged by the inconsistency of complementarity determining region 3 (CDR3) and limited cell numbers in clinical samples. Thus, a quantitative method is necessary for monitoring the TCR repertoire in PLWH. We characterized the TCR V-J pairing profile of naïve and memory CD4+ T cells in healthy donors, HIV-infected antiretroviral therapy (ART)-naïve patients and long-term (over 5 years) ART-experienced patients by performing TCR sequencing. We developed a V-J index with 18 parameters which were subdivided into five categories (expression coverage, cumulative percentage of the top tenth percentile, diversity, intra-individual similarity and inter-individual similarity). In ART-naïve patients, 14 of the 18 parameters were significantly altered. Long-term ART recovered ten parameters. The four unrecovered parameters were related to inter-individual similarity. Therefore, these findings indicate that long-term ART could only partially recover TCR V-J pairs and introduce newly impacted V-J pairs. Moreover, these results provide new insights into the V-J pairing of the TCR and into the disturbance of TCR repertoire in HIV infection.
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MESH Headings
- Adult
- Anti-Retroviral Agents/therapeutic use
- CD4 Lymphocyte Count
- CD4-Positive T-Lymphocytes/immunology
- CD4-Positive T-Lymphocytes/metabolism
- Complementarity Determining Regions/genetics
- Complementarity Determining Regions/immunology
- Female
- HIV Infections/drug therapy
- HIV Infections/genetics
- HIV Infections/immunology
- Humans
- Immunoglobulin Joining Region/genetics
- Immunoglobulin Joining Region/immunology
- Immunoglobulin Variable Region/genetics
- Immunoglobulin Variable Region/immunology
- Immunologic Memory/immunology
- Male
- Receptors, Antigen, T-Cell/genetics
- Receptors, Antigen, T-Cell/immunology
- Receptors, Antigen, T-Cell/metabolism
- Receptors, Antigen, T-Cell, alpha-beta/genetics
- Receptors, Antigen, T-Cell, alpha-beta/immunology
- Receptors, Antigen, T-Cell, alpha-beta/metabolism
- Time Factors
- Young Adult
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Affiliation(s)
- Guoli Li
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, 100015, China
| | - Jiarui Li
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, 100015, China
| | - Henghui Zhang
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, 100015, China
| | - Yu Zhang
- Clinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
| | - Di Liu
- Computational Virology Group, Center for Bacteria and Virus Resources and Application, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430071, China
- University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Yu Hao
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, 100015, China
| | - Junyan Han
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, 100015, China
| | - Juan Du
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, 100015, China
| | - Liuluan Zhu
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, 100015, China
| | - Yongqin Zeng
- Clinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
| | - Bei Li
- Clinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
| | - Rui Li
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, 100015, China
| | - Chuan Song
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, 100015, China
| | - Fujie Zhang
- Clinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China
| | - Chen Chen
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China.
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, 100015, China.
| | - Hongxin Zhao
- Clinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China.
| | - Hui Zeng
- Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, China.
- Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, 100015, China.
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9
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Chobrutskiy BI, Yeagley M, Diviney A, Zaman S, Gozlan EC, Tipping P, Koohestani DM, Roca AM, Blanck G. A scoring system for the electrostatic complementarities of T-cell receptors and cancer-mutant amino acids: multi-cancer analyses of associated survival rates. Immunology 2020; 159:373-383. [PMID: 31821535 DOI: 10.1111/imm.13165] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 12/02/2019] [Accepted: 12/05/2019] [Indexed: 12/21/2022] Open
Abstract
The anti-tumor immune response is considered to be due to the T-cell receptor (TCR) binding to tumor antigens, which can be either wild-type, early stem cell proteins, presumably foreign to a developed immune system; or mutant peptides, foreign to the immune system because of a mutant amino acid (aa) or otherwise somatically altered aa sequence. Recently, very large numbers of TCR complementarity-determining region-3 (CDR3) aa sequences obtained from tumor specimens have become available. We developed a novel algorithm for assessing the complementarity of tumor mutant peptides and TCR CDR3s, based on the retrieval of TCR CDR3 aa sequences from both tumor specimen and patient blood exomes and by using an automated process of assessing CDR3 and mutant aa electrical charges. Results indicated many instances where high electrostatic complementarity was associated with a higher survival rate. In particular, our approach led to the identification of specific genes contributing significantly to the complementary, TCR CDR3-mutant aa. These results suggest a novel approach to tumor immunoscoring and may lead to the identification of high-priority neo-antigen, peptide vaccines; or to the identification of ex vivo stimulants of tumor-infiltrating lymphocytes.
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Affiliation(s)
- Boris I Chobrutskiy
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Michelle Yeagley
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Andrea Diviney
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Saif Zaman
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Etienne C Gozlan
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Price Tipping
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Darush M Koohestani
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Andrea M Roca
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - George Blanck
- Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.,Immunology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
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10
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Wu SG, Pan W, Liu H, Byrne-Steele ML, Brown B, Depinet M, Hou X, Han J, Li S. High throughput sequencing of T-cell receptor repertoire using dry blood spots. J Transl Med 2019; 17:47. [PMID: 30777078 PMCID: PMC6379990 DOI: 10.1186/s12967-019-1796-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Accepted: 02/09/2019] [Indexed: 11/12/2022] Open
Abstract
Background Immunology research, particularly next generation sequencing (NGS) of the immune T-cell receptor β (TCRβ) repertoire, has advanced progression in several fields, including treatment of various cancers and autoimmune diseases. This study aimed to identify the TCR repertoires from dry blood spots (DBS), a method that will help collecting real-world data for biomarker applications. Methods Finger-prick blood was collected onto a Whatman filter card. RNA was extracted from DBS of the filter card, and fully automated multiplex PCR was performed to generate a TCRβ chain library for next generation sequencing (NGS) analysis of unique CDR3s (uCDR3). Results We demonstrated that the dominant clonotypes from the DBS results recapitulated those found in whole blood. According to the statistical analysis and laboratory confirmation, 40 of 2-mm punch disks from the filter cards were enough to detect the shared top clones and have strong correlation in the uCDR3 discovery with whole blood. uCDR3 discovery was neither affected by storage temperatures (room temperature versus − 20 °C) nor storage durations (1, 14, and 28 days) when compared to whole blood. About 74–90% of top 50 uCDR3 clones of whole blood could also be detected from DBS. A low rate of clonotype sharing, 0.03–1.5%, was found among different individuals. Conclusions The DBS-based TCR repertoire profiling method is minimally invasive, provides convenient sampling, and incorporates fully automated library preparation. The system is sensitive to low RNA input, and the results are highly correlated with whole blood uCDR3 discovery allowing study scale-up to better understand the relationship and mutual influences between the immune and diseases. Electronic supplementary material The online version of this article (10.1186/s12967-019-1796-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Shang-Gin Wu
- Department of Internal Medicine, National Taiwan University Hospital, National Taiwan University, Taipei, 10002, Taiwan.,Department of Internal Medicine, National Taiwan University Cancer Center, National Taiwan University, Taipei, 10672, Taiwan
| | - Wenjing Pan
- HudsonAlpha Institute for Biotechnology, 601 Genome Way, Huntsville, AL, 35806, USA.,iRepertoire Inc., 800 Hudson Way Suite 2319, Huntsville, AL, 35806, USA
| | - Hongna Liu
- iCubate Inc., Huntsville, AL, 35806, USA
| | | | - Brittany Brown
- iRepertoire Inc., 800 Hudson Way Suite 2319, Huntsville, AL, 35806, USA
| | - Mollye Depinet
- iRepertoire Inc., 800 Hudson Way Suite 2319, Huntsville, AL, 35806, USA
| | - Xiaohong Hou
- iRepertoire Inc., 800 Hudson Way Suite 2319, Huntsville, AL, 35806, USA
| | - Jian Han
- HudsonAlpha Institute for Biotechnology, 601 Genome Way, Huntsville, AL, 35806, USA. .,iRepertoire Inc., 800 Hudson Way Suite 2319, Huntsville, AL, 35806, USA.
| | - Song Li
- iRepertoire Inc., 800 Hudson Way Suite 2319, Huntsville, AL, 35806, USA.
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