An integrated software for virus community sequencing data analysis

Viral quasispecies quantitative analysis: a novel approach for appraising the immune tolerant phase of chronic hepatitis B virus infection

Few non-invasive models were established for precisely identifying the immune tolerant (IT) phase from chronic hepatitis B (CHB). This study aimed to develop a novel approach that combined next-generation sequencing (NGS) and machine learning algorithms using our recently published viral quasispecies (QS) analysis package. 290 HBeAg positive patients from whom liver biopsies were taken were enrolled and divided into a training group (n = 148) and a validation group (n = 142). HBV DNA was extracted and QS sequences were obtained by NGS. Hierarchical clustering analysis (HCA) and principal component analysis (PCA) based on viral operational taxonomic units (OTUs) were performed to explore the correlations among QS and clinical phenotypes. Three machine learning algorithms, including K-nearest neighbour, support vector machine, and random forest algorithm, were used to construct diagnostic models for IT phase classification. Based on histopathology, 90 IT patients and 200 CHB patients were diagnosed. HBsAg titres for IT patients were higher than those of CHB patients (p < 0.001). HCA and PCA analysis grouped IT and CHB patients into two distinct clusters. The relative abundance of viral OTUs differed mainly within the BCP/precore/core region and was significantly correlated with liver inflammation and fibrosis. For the IT phase classification, all machine-learning models showed higher AUC values compared to models based on HBsAg, APRI, and FIB-4. The relative abundance of viral OTUs reflects the severity of liver inflammation and fibrosis. The novel QS quantitative analysis approach could be used to diagnose IT patients more precisely and reduce the need for liver biopsy.

Variations in SARS-CoV-2 Spike Protein Cell Epitopes and Glycosylation Profiles During Global Transmission Course of COVID-19

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to an outbreak of a pandemic worldwide. For better understanding the viral spike (S) protein variations and its potential effects on the interaction with the host immune system and also in vaccine development, the cell epitopes, glycosylation profile and their changes during the global transmission course were characterized and compared with SARS-CoV for their glycosylation profile. We analyzed totally 7,813 sequences screened from 8,897 whole genome sequences on GISAID database up to April 26, and 18 S protein amino acid variations with relatively high frequency (≥10^-3) were identified. A total of 228 sequences of variants had multiple variations, of note, most of them harboring the D614G mutation. Among the predicted 69 linear B cell epitopes, 175 discontinuous B cell epitopes and 41 cytotoxic T lymphocyte epitopes in the viral S protein, we found that the protein structure and its potential function of some sites changed, such as the linear epitope length shortened and discontinuous epitope disappeared of G476S. In addition, we detected 9 predicted N-glycosylation sites and 3 O-glycosylation sites unique to SARS-CoV-2, but no evidently observed variation of the glycan sites so far. Our findings provided an important snapshot of temporal and geographical distributions on SARS-CoV-2 S protein cell epitopes and glycosylation sites, which would be an essential basis for the selection of vaccine candidates.