Detection of hepatitis B virus mRNA from single cell RNA sequencing data without prior knowledge - Nicolaas Van Renne; Thomas Vanwolleghem (PLoS ONE, 2025)
The ability to detect microbial reads from sequencing data has significantly advanced microbiome and infectious disease research. Recently, INVADEseq introduced a technique to extract microbial reads from single-cell RNA sequencing (scRNA-seq) data following 16S rRNA amplification. We hypothesized that this approach could be leveraged to detect viruses in eukaryotic cells without such amplification or prior knowledge, provided they produce viral mRNAs containing poly-A tails. To test this, we aimed to detect Hepatitis B Virus (HBV) reads from liver samples of patients with chronic HBV infection, both with and without HBsAg loss. We successfully detected HBV reads in the liver of viraemic patients, predominantly in hepatocytes and, to a lesser extent, in Kupffer cells. Functionally cured HBV patients with HBsAg loss had undetectable HBV mRNA in the liver. This study demonstrates the ability to extract and identify viral reads from scRNA-seq data without prior knowledge and without specific amplification. This approach can be used for screening scRNA-seq data for the presence of viral reads at single-cell resolution, potentially enhancing our understanding of the cellular distribution of viruses and virus-host interactions.