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Record W4385660799 · doi:10.1101/2023.08.07.552328

AAV-HBV mouse model replicates immune exhaustion patterns of chronic HBV patients at single-cell level

2023· preprint· en· W4385660799 on OpenAlexaff
Nádia Conceição‐Neto, Qinglin Han, Zhiyuan Yao, Wim Pierson, Qun Wu, Koen Dockx, Liese Aerts, Dries De Maeyer, Koen Van Den Berge, Chris Li, George Kukolj, Ren Zhu, Ondřej Podlaha, Isabel Nájera, Ellen Van Gulck

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsMcGill University
Fundersnot available
KeywordsImmune systemTIGITImmunologyCD8T cellFlow cytometryBiologyCytotoxic T cellHepatitis B virusVirologyMedicineVirus

Abstract

fetched live from OpenAlex

Abstract Background and Aims Unresolved hepatitis B virus (HBV) infection leads to a progressive state of immune exhaustion that impairs resolution of infection, leading to chronic infection (CHB). The immune-competent AAV-HBV mouse is a common HBV preclinical immune competent model, though a comprehensive characterization of the liver immune microenvironment and its translatability to human infection is still lacking. We investigated the intrahepatic immune profile of the AAV-HBV mouse model at a single-cell level and compared with data from CHB patients in immune tolerant (IT) and immune active (IA) clinical stages. Methods Immune exhaustion was profiled through an iterative subclustering approach for cell-typing analyses of single-cell RNA-sequencing data in CHB donors and compared to the AAV-HBV mouse model 24-weeks post-transduction to assess its translatability. This was validated using an exhaustion flow cytometry panel at 40 weeks post-transduction. Results Using single-cell RNA-sequencing, CD8 pre-exhausted T-cells with self-renewing capacity ( TCF7 +), and terminally exhausted CD8 T-cells ( TCF7 -) were detected in the AAV-HBV model. These terminally exhausted CD8 T-cells (expressing Pdcd1 , Tox , Lag3 , Tigit ) were significantly enriched versus control mice and independently identified through flow cytometry. Importantly, comparison to CHB human data showed a similar exhausted CD8 T-cell population in IT and IA donors, but not in healthy individuals. Conclusions Long term high titer AAV-HBV mouse liver transduction led to T-cell exhaustion, as evidenced by expression of classical immune checkpoint markers at mRNA and protein levels. In both IT and IA donors, a similar CD8 exhausted T-cell population was identified, with increased frequency observed in IA donors. These data support the use of the AAV-HBV mouse model to study T-cell exhaustion in HBV infection and the effect of immune-based therapeutic interventions. Lay Summary The AAV-HBV mouse model is used as a research tool to study hepatitis B infection. In this study we evaluated the translation value from mouse to human with regards to T-cell exhaustion. Highlights AAV-HBV mice transduced with a high titer vector showed presence of CD8 exhausted T-cells after 24 weeks. High titer transduced mice, but not lower titer show increased expression of LAG-3, TOX, TIM-3 and TIGIT in CD8 T-cells. PD-1 was increased in CD8 T-cells, independent of HBV transduction titer. A similar exhausted CD8 T-cell population could be found in chronic HBV donors, but not in healthy individuals. Graphical abstract

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.217
Teacher spread0.187 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2023
Admission routes1
Has abstractyes

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