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Record W4414440271 · doi:10.1016/j.jhepr.2025.101596

Development of a CRE/CREB-driven HBx responsive HBV cell culture reporter system for antiviral drug evaluation

2025· article· en· W4414440271 on OpenAlexaff
Muhammad Atif Zahoor, Nahla FadlElMawla, Adrian Kuipery, Joshua B. Feld, Avisha Chowdhury, Alexander I. Mosa, Adam J. Gehring, Jordan J. Feld

Bibliographic record

VenueJHEP Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersGilead SciencesGlaxoSmithKline
KeywordsHBxcccDNAHepatitis B virusAntiviral drugDrug developmentCell cultureDNAChronic hepatitis

Abstract

fetched live from OpenAlex

Background & Aims Chronic hepatitis B virus (HBV) is a major cause of chronic liver disease, cirrhosis, and hepatocellular carcinoma. Current therapies, including nucleot(s)ide analogues (NAs) and interferon alpha (IFNα), fail to eliminate covalently closed circular DNA (cccDNA), highlighting the urgent need for novel therapeutic approaches. A quantifiable cell-based reporter system is highly desirable for the discovery and evaluation of new antiviral agents. Exploiting the ability of HBx to activate CREB [cyclic adenosine monophosphate (cAMP) response element binding protein] signaling, we aimed to establish a cell-based system capable of detecting HBx expression during HBV infection and suitable for screening compounds with anti-HBV activity. Methods We generated an HBx-responsive cell line stably expressing nano-luciferase (nLuc) under the control of viral cAMP-response element (vCRE) derived from human T-cell leukemia virus-1 core promoter. The system was used to evaluate various drug inhibitors in HBV-infected cells. Results The vCRE-nLuc system was confirmed to be responsive to HBx using pHBV1.3-wild type, pHBV1.3-null-X and pMyc-HBx constructs (p<0.0001). HBV infection with both culture-derived and patient-derived clinical isolates (genotypes A-E) significantly increased luciferase activity (p<0.0001). Treatment with HBx inhibitors (siRNA, specific HBx inhibitors), as well as IFNα reduced luciferase production (p<0.0001). In contrast, antivirals that do not interfere with protein production (tenofovir), or viral entry (Myrcludex B) showed no effect (p<0.05), underscoring the specificity of the system for identifying compounds that inhibit protein production and/or HBx function. Finally, HepG2.2.15 cells carrying HBV and transduced with vCRE-nLuc confirmed the system's suitability for monitoring HBV infection. Conclusions We established a vCRE-nLuc-driven HBx-responsive cell line for quantitative monitoring of HBV infection and evaluation of antiviral drugs. This system holds potential for identifying new anti-HBV agents and advancing our understanding of HBV replication. Impact and Implications The HBx-responsive vCRE-nLuc reporter system provides a sensitive and scalable platform to monitor HBV infection and evaluate antiviral compounds targeting HBx function. Its ability to detect HBx activity from both laboratory and clinical HBV isolates underscore its translational relevance. By enabling selective screening of HBx-targeting agents, this system may advance efforts to silence cccDNA and accelerate the development of curative therapies for chronic hepatitis B.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.326
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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