Biology subjects

Dai, S.-X.

Publications and source records attributed to Dai, S.-X..

3 recordsLinked to original sources

bioRxiv2022

Multi-omics integrated analysis reveals a specific phenotype of CD8+ T cell may contribute to immunothromosis via Th17 response in severe and critical COVID-19

T lymphocyte reduction and immunosenescence frequently occur in severe and critical coronavirus disease 2019 (COVID-19) patients, which may cause immunothrombosis and numerous sequelae. This study integrated analyzed multi-omics data from healthy donors, pneumonia, COVID-19 patients (mild & moderate, severe, and critical), and convalescences, including clinical, laboratory test, PBMC bulk RNA-seq, PBMC scRNA-seq and TCR-seq, BAL scRNA-seq, and lung proteome. We revealed that there are certain associations among T lymphocyte reduction, CD8+ T cell senescence, Th17 immune activation, and immunothrombosis. A specific phenotype (S. P.) CD8+ T cells were identified in severe and critical COVID-19 patients in both PBMC and BAL scRNA-seq, which showed highly TCR homology with terminal effector CD8+ T cells and senescent CD8+ T cells. Pseudotime analysis showed that the S. P. CD8+ T cells were located in the transition trajectory from mild to severe disease. Which may be activated by terminal effector CD8+ T cells or senescent CD8+ T cells, thereby promoting Th17 cell differentiation. This phenomenon was absent in healthy donors, mild and moderate COVID-19 patients, or convalescences. Our findings are an important reference for avoiding the conversion of patients with mild to severe diseases and provide insight into the future prevention and control of COVID-19 and its variants.

bioinformatics↗

bioRxiv2017

Anti-HIV activity prediction and enrichment identify novel human targets for Anti-HIV therapy

Human immunodeficiency virus (HIV) relies heavily on the host proteins to facilitate its entry and replication. Currently, more than 4000 human proteins are recorded to be involved in the HIV-1 life cycle. Identifying appropriate anti-HIV targets from so many host proteins is crucial to anti-HIV drug development, but a challenging work. Here we combined anti-HIV activity prediction and enrichment analysis to identify novel human targets for anti-HIV therapy. We firstly developed an accurate prediction tool named Anti-HIV-Predictor (AUC>0.96) to predict the anti-HIV activity of given compounds. Using this tool, we predicted 10488 anti-HIV compounds from ChEMBLdb. Then, based on this result and relationships of targets and compounds, we inferred 73 anti-HIV targets that enriched with anti-HIV compounds. The functional annotation and network analysis revealed that they directly or indirectly interact with 20 HIV proteins through neuropeptide signaling, GPCR signaling, cell surface signaling pathway, and so on. Nearly half of these targets overlap with the NCBI HIV dataset. However, the percentage of known therapeutic targets in these targets is significantly higher than that in the NCBI HIV dataset. After a series of feature analysis, we identified 13 novel human targets with high potential as anti-HIV targets, the inhibitors of which have experimentally confirmed anti-HIV activity. It is noteworthy that the inhibitors of REN and CALCA have better anti-HIV activity than CCR5 inhibitors. Taken together, our findings provide novel human targets for the host-oriented anti-HIV drug development and should significantly advance current anti-HIV research.

bioinformatics↗

bioRxiv2016

Efficient repositioning of approved drugs as anti-HIV agents using Anti-HIV-Predictor

Development of new, effective and affordable drugs against HIV is urgently needed. In this study, we developed a worlds first web server called Anti-HIV-Predictor (http://bsb.kiz.ac.cn:70/hivpre) for predicting anti-HIV activity of given compounds. This server is rapid and accurate (accuracy >93% and AUC > 0.958). We applied the server to screen 1835 approved drugs for anti-HIV therapy. Totally 67 drugs were predicted to have anti-HIV activity, 25 of which are anti-HIV drugs. Then we experimentally evaluated 35 predicted new anti-HIV compounds by assays of syncytia formation, p24 quantification, cytotoxicity. Finally, we repurposed 7 approved drugs (cetrorelix, dalbavancin, daunorubicin, doxorubicin, epirubicin, idarubicin and valrubicin) as new anti-HIV agents. The original indication of these drugs is involved in a variety of diseases such as female infertility and cancer. Anti-HIV-Predictor and the 7 repurposed anti-HIV agents provided here demonstrate the efficacy of this strategy for discovery of new anti-HIV agents.

bioinformatics↗