Evidence map›Paper›PMID 39932940›Full record

ArticlePloS one2025

Detection of hepatitis B virus mRNA from single cell RNA sequencing data without prior knowledge.

Nicolaas Van Renne, Thomas Vanwolleghem

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Liver Macrophages in the Pathogenesis of Viral Hepatitis.Current issues in molecular biology · 2026
    Review
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Nicolaas Van RenneViral Hepatitis Research Group, Laboratory of Experimental Medicine and Pediatrics, Antwerp University, Antwerp, Belgium.ORCID 0000-0002-3053-8835
Thomas VanwolleghemViral Hepatitis Research Group, Laboratory of Experimental Medicine and Pediatrics, Antwerp University, Antwerp, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Hepatitis B, ChronicHepatitis B virusRNA, MessengerRNA, ViralSequence Analysis, RNASingle-Cell AnalysisFemaleHepatitis B Surface AntigensHepatocytesHumansLiverMaleHepatitis B Surface AntigensRNA, MessengerRNA, Viral

Identifiers

PMID39932940
PMCPMC11813074

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.