Comprehensive evaluation of fusion transcript detection algorithms and a meta-caller to combine top performing methods in paired-end RNA-seq data.

BACKGROUND: Fusion transcripts are formed by either fusion genes (DNA level) or trans-splicing events (RNA level). They have been recognized as a promising tool for diagnosing, subtyping and treating cancers. RNA-seq has become a precise and efficient standard for genome-wide screening of such aberration events. Many fusion transcript detection algorithms have been developed for paired-end RNA-seq data but their performance has not been comprehensively evaluated to guide practitioners. In this paper, we evaluated 15 popular algorithms by their precision and recall trade-off, accuracy of supporting reads and computational cost. We further combine top-performing methods for improved ensemble detection. RESULTS: Fifteen fusion transcript detection tools were compared using three synthetic data sets under different coverage, read length, insert size and background noise, and three real data sets with selected experimental validations. No single method dominantly performed the best but SOAPfuse generally performed well, followed by FusionCatcher and JAFFA. We further demonstrated the potential of a meta-caller algorithm by combining top performing methods to re-prioritize candidate fusion transcripts with high confidence that can be followed by experimental validation. CONCLUSION: Our result provides insightful recommendations when applying individual tool or combining top performers to identify fusion transcript candidates.

Glycosylation and S-palmitoylation regulate SARS-CoV-2 spike protein intracellular trafficking.

Post-translational modifications (PTMs), such as glycosylation and palmitoylation, are critical to protein folding, stability, intracellular trafficking, and function. Understanding regulation of PTMs of SARS-CoV-2 spike (S) protein could help the therapeutic drug design. Herein, the VSV vector was used to produce SARS-CoV-2 S pseudoviruses to examine the roles of the 611LYQD614 and cysteine-rich motifs in S protein maturation and virus infectivity. Our results show that 611LY612 mutation alters S protein intracellular trafficking and reduces cell surface expression level. It also changes S protein glycosylation pattern and decreases pseudovirus infectivity. The S protein contains four cysteine-rich clusters with clusters I and II as the main palmitoylation sites. Mutations of clusters I and II disrupt S protein trafficking from ER-to-Golgi, suppress pseudovirus production, and reduce spike-mediated membrane fusion activity. Taken together, glycosylation and palmitoylation orchestrate the S protein maturation processing and are critical for S protein-mediated membrane fusion and infection.

Furin and TMPRSS2 Resistant Spike Induces Robust Humoral and Cellular Immunity Against SARS-CoV-2 Lethal Infection.

An effective COVID-19 vaccine against broad SARS-CoV-2 variants is still an unmet need. In the study, the vesicular stomatitis virus (VSV)-based vector was used to express the SARS-CoV-2 Spike protein to identify better vaccine designs. The replication-competent of the recombinant VSV-spike virus with C-terminal 19 amino acid truncation (SΔ19 Rep) was generated. A single dose of SΔ19 Rep intranasal vaccination is sufficient to induce protective immunity against SARS-CoV-2 infection in hamsters. All the clones isolated from the SΔ19 Rep virus contained R682G mutation located at the Furin cleavage site. An additional S813Y mutation close to the TMPRSS2 cleavage site was identified in some clones. The enzymatic processing of S protein was blocked by these mutations. The vaccination of the R682G-S813Y virus produced a high antibody response against S protein and a robust S protein-specific CD8+ T cell response. The vaccinated animals were protected from the lethal SARS-CoV-2 (delta variant) challenge. The S antigen with resistance to enzymatic processes by Furin and TMPRSS2 will provide better immunogenicity for vaccine design.