Although host T cell immune responses to hepatitis B virus (HBV) have been demonstrated to have important influences on the outcome of HBV infection, the development of T cell epitope-based vaccine and T cell therapy and the clinical evaluation of specific T cell function are currently hampered markedly by the lack of validated HBV T cell epitopes covering broad patients. This study aimed to screen T cell epitopes spanning overall HBsAg, HBeAg, HBx and HBpol proteins and presenting by thirteen prevalent human leukocyte antigen (HLA)-A allotypes which gather a total gene frequency of around 95% in China and Northeast Asia populations. 187 epitopes were in silico predicted. Of which, 62 epitopes were then functionally validated as real-world HBV T cell epitopes by ex vivo IFN-γ ELISPOT assay and in vitro co-cultures using peripheral blood mononuclear cells (PBMCs) from HBV infected patients. Furthermore, the HLA-A cross-restrictions of each epitope were identified by peptide competitive binding assay using transfected HMy2.CIR cell lines, and by HLA-A/peptide docking as well as molecular dynamic simulation. Finally, a peptide library containing 105 validated epitopes which cross-binding by 13 prevalent HLA-A allotypes were used in ELISPOT assay to enumerate HBV-specific T cells for 116 patients with HBV infection. The spot forming units (SFUs) was significantly correlated with serum HBsAg level as confirmed by multivariate linear regression analysis. This study functionally validated 62 T cell epitopes from HBV main proteins and elucidated their HLA-A restrictions and provided an alternative ELISPOT assay using validated epitope peptides rather than conventional overlapping peptides for the clinical evaluation of HBV-specific T cell responses.

Organs-on-a-Chip is a microfluidic microphysiological system that uses microfluidic technology to make high-resolution and real-time imaging analysis on the structure and function of living human cells at the level of tissue and organ in vitro. Compared with the traditional two-dimensional cell culture model and animal model, organs-on-a-chip technology can simulate the pathological and toxicological interactions between different organs or tissues more closely and reflect the collaborative response of multiple organs to drugs. Although lots of organs-on-a-chip-related literature have been published, none of current databases have achieved all the following functionalities yet: searching, downloading and analyzing data and results from literature of organs-on-a-chip. To address this need, we established a database named organs-on-a-chip database (OOCDB), as a platform to integrate information related to organs-on-a-chip from various sources: literature, patents, microarray and transcriptome sequencing raw data, many open access data of organs-on-a-chip and organoids, as well as the data generated in our lab. OOCDB comprises dozens of sub databases and analysis tools and each sub database contains a number of data related to organs-on-a-chip, aiming to provide a comprehensive, systematic and convenient search engine for researchers. In addition, it provides functions such as mathematical modeling, three-dimensional model and citation map to meet the needs of researchers and to promote the development of organs-on-a-chip. The organs-on-a-chip database can be visited at http://www.organchip.cn.

Motivation The human major histocompatibility complex (MHC), also known as human leukocyte antigen (HLA), plays an important role in the adaptive immune system by presenting non-self-peptides to T cell receptors. The MHC region has been shown to be associated with a variety of diseases, including autoimmune diseases, organ transplantation and tumours. However, structural analytic tools of HLA are still sparse compared to the number of identified HLA alleles, which hinders the disclosure of its pathogenic mechanism. Result To provide an integrative analysis of HLA, we first collected 1296 amino acid sequences, 256 protein data bank structures, 120 000 frequency data of HLA alleles in different populations, 73 000 publications and 39 000 disease-associated single nucleotide polymorphism sites, as well as 212 modelled HLA heterodimer structures. Then, we put forward two new strategies for building up a toolkit for transplantation and tumour immunotherapy, designing risk alignment pipeline and antigenic peptide prediction pipeline by integrating different resources and bioinformatic tools. By integrating 100 000 calculated HLA conformation difference and online tools, risk alignment pipeline provides users with the functions of structural alignment, sequence alignment, residue visualization and risk report generation of mismatched HLA molecules. For tumour antigen prediction, we first predicted 370 000 immunogenic peptides based on the affinity between peptides and MHC to generate the neoantigen catalogue for 11 common tumours. We then designed an antigenic peptide prediction pipeline to provide the functions of mutation prediction, peptide prediction, immunogenicity assessment and docking simulation. We also present a case study of hepatitis B virus mutations associated with liver cancer that demonstrates the high legitimacy of our antigenic peptide prediction process. HLA3D, including different HLA analytic tools and the prediction pipelines, is available at http://www.hla3d.cn/.

Since the first outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019, its high infectivity led to its prevalence around the world in an exceptionally short time. Efforts have been made to control the ongoing outbreak, and among them, vaccine developments are going on high priority. New clinical trials add to growing evidence that vaccines from many countries were highly effective at preventing SARS-CoV-2 virus infection. One of them is B cell-based vaccines, which were common during a pandemic. However, neutralizing antibody therapy becomes less effective when viruses mutate. In order to tackle the problem, we focused on T-cell immune mechanism. In this study, the mutated strains of the virus were selected globally from India (B.1.617.1 and B.1.617.2), United Kingdom (B.1.1.7), South Africa (B.1.351), and Brazil (P.1), and the overlapping peptides were collected based on mutation sites of S-protein. After that, residue scanning was used to predict the affinity between overlapping peptide and HLA-A*11:01, the most frequent human leukocyte antigen (HLA) allele among the Chinese population. Then, the binding free energy was evaluated with molecular docking to further verify the affinity changes after the mutations happen in the virus genomes. The affinity test results of three epitopes on spike protein from experimental validation were consistent with our predicted results, thereby supporting the inclusion of the epitope 374FSTFKCYGL382 in future vaccine design and providing a useful reference route to improve vaccine development.

Organs-on-a-chip is a microfluidic microphysiological system that uses microfluidic technology to analyze the structure and function of living human cells at the tissue and organ levels in vitro. Organs-on-a-chip technology, as opposed to traditional two-dimensional cell culture and animal models, can more closely simulate pathologic and toxicologic interactions between different organs or tissues and reflect the collaborative response of multiple organs to drugs. Despite the fact that many organs-on-a-chip-related data have been published, none of the current databases have all of the following functions: searching, downloading, as well as analyzing data and results from the literature on organs-on-a-chip. Therefore, we created an organs-on-a-chip database (OOCDB) as a platform to integrate information about organs-on-a-chip from various sources, including literature, patents, raw data from microarray and transcriptome sequencing, several open-access datasets of organs-on-a-chip and organoids, and data generated in our laboratory. OOCDB contains dozens of sub-databases and analysis tools, and each sub-database contains various data associated with organs-on-a-chip, with the goal of providing researchers with a comprehensive, systematic, and convenient search engine. Furthermore, it offers a variety of other functions, such as mathematical modeling, three-dimensional modeling, and citation mapping, to meet the needs of researchers and promote the development of organs-on-a-chip. The OOCDB is available at http://www.organchip.cn.

Chronic hepatitis B virus (HBV), a potentially life-threatening liver disease, makes people vulnerable to serious diseases such as cancer. T lymphocytes play a crucial role in clearing HBV virus, while the pathway depends on the strong binding of T cell epitope peptide and HLA. However, the experimental identification of HLA-restricted HBV antigenic peptides is extremely time-consuming. In this study, we provide a novel prediction strategy based on structure to assess the affinity between the HBV antigenic peptide and HLA molecule. We used residue scanning, peptide docking and molecular dynamics methods to obtain the molecular docking model of HBV peptide and HLA, and then adopted the MM-GBSA method to calculate the binding affinity of the HBV peptide–HLA complex. Overall, we collected 59 structures of HLA-A from Protein Data Bank, and finally obtained 352 numerical affinity results to figure out the optimal bind choice between the HLA-A molecules and 45 HBV T cell epitope peptides. The results were highly consistent with the qualitative affinity level determined by the competitive peptide binding assay, which confirmed that our affinity prediction process based on an HLA structure is accurate and also proved that the homologous modeling strategy for HLA-A molecules in this study was reliable. Hence, our work highlights an effective way by which to predict and screen for HLA-peptide binding that would improve the treatment of HBV infection.