Evidence map›Paper›PMID 42092617›Full record

ArticleJHEP reports : innovation in hepatology2026

Development of a CRISPR-Cas13-based antiviral strategy against hepatitis E virus.

Emely Richter, Mara Klöhn, Maximilian K Nocke, Marcel Edgar Friedrich, Daniel Todt, Eike Steinmann, Yannick Brüggemann

Abstract read
In one paragraph

Article in JHEP reports : innovation in hepatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Emely RichterDepartment of Molecular and Medical Virology, Ruhr University Bochum, Bochum, Germany; Hepatitis E Virus Research Hub (HepE-Hub), Bochum, Germany.
Mara KlöhnDepartment of Molecular and Medical Virology, Ruhr University Bochum, Bochum, Germany; Hepatitis E Virus Research Hub (HepE-Hub), Bochum, Germany.
Maximilian K NockeDepartment of Molecular and Medical Virology, Ruhr University Bochum, Bochum, Germany; Hepatitis E Virus Research Hub (HepE-Hub), Bochum, Germany; Department of Translational and Computational Infection Research (TRACiR), Ruhr University Bochum, Bochum, Germany; European Virus Bioinformatics Center (EVBC), Jena, Germany.
Marcel Edgar FriedrichDepartment of Molecular and Medical Virology, Ruhr University Bochum, Bochum, Germany; Hepatitis E Virus Research Hub (HepE-Hub), Bochum, Germany.
Daniel TodtDepartment of Molecular and Medical Virology, Ruhr University Bochum, Bochum, Germany; Hepatitis E Virus Research Hub (HepE-Hub), Bochum, Germany; Department of Translational and Computational Infection Research (TRACiR), Ruhr University Bochum, Bochum, Germany; European Virus Bioinformatics Center (EVBC), Jena, Germany.
Eike SteinmannDepartment of Molecular and Medical Virology, Ruhr University Bochum, Bochum, Germany; Hepatitis E Virus Research Hub (HepE-Hub), Bochum, Germany; German Centre for Infection Research (DZIF), External Partner Site, Bochum, Germany.
Yannick BrüggemannDepartment of Molecular and Medical Virology, Ruhr University Bochum, Bochum, Germany; Hepatitis E Virus Research Hub (HepE-Hub), Bochum, Germany. Electronic address: yannick.brueggemann@ruhr-uni-bochum.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND &

aimsEffective antiviral drugs remain unavailable for many clinically relevant pathogens, including the hepatitis E virus (HEV). This study aimed to evaluate the CRISPR/Cas13d system as a potential antiviral strategy against HEV.

methodsWe developed a reporter assay to screen CRISPR RNAs (crRNAs) targeting conserved regions of the HEV genome and tested their antiviral activity in human hepatoma cells using a robust HEV cell culture model. HEV replication was assessed using a subgenomic replicon, infectious particle production was quantified by immunofluorescence and titration assays. A bioinformatic analysis was performed to identify a minimal set of crRNAs capable of broadly targeting circulating human pathogenic HEV strains.

resultsA crRNA screen identified multiple functional crRNAs targeting HEV-3, with ORF1-targeting crRNAs significantly reducing viral capsid expression (p <0.01) and the number of HEV-infected cells (p <0.01). Cas13d-mediated targeting led to robust reduction of HEV replication and markedly lowered infectious virus production in vitro (p <0.001). Bioinformatic analysis revealed that just three distinct crRNAs could cover ∼94% of known HEV genomes with zero mismatches, while four crRNAs achieved complete coverage.

conclusionsOur findings demonstrate that CRISPR/Cas13d can target HEV replication and viral progeny production in vitro. The identification of a minimal crRNA set capable of broadly targeting circulating HEV strains suggests that the CRISPR/Cas13d system may offer an antiviral strategy to address challenges related to viral evolution and treatment escape. IMPACT AND IMPLICATIONS: This study establishes CRISPR/Cas13d as a proof-of-concept antiviral strategy against hepatitis E virus (HEV), demonstrating suppression of viral replication and particle production in vitro. By identifying a minimal set of broadly effective crRNAs, we provide a framework for targeting diverse HEV variants and buffering against viral evolution. These findings highlight the potential of CRISPR-based systems as innovative antiviral strategies.

Indexed as

Antiviral AgentsCRISPR-Cas SystemsHepatitis EHepatitis E virusGenome, ViralHumansVirus ReplicationAntiviral AgentsAntiviralsCRISPR-Cas13Hepatitis E virus (HEV)

Identifiers

PMID42092617
PMCPMC13277442

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.