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Record W4404696887 · doi:10.1080/19490976.2024.2431167

Transcriptional profiling of zebrafish intestines identifies macrophages as host cells for human norovirus infection

2024· article· en· W4404696887 on OpenAlexafffund
Emma Roux, Reegan J. Willms, Jana Van Dycke, Álvaro Cortés Calabuig, Lore Van Espen, Geert Schoofs, Jelle Matthijnssens, Johan Neyts, Peter de Witte, Edan Foley, Joana Rocha‐Pereira

Bibliographic record

VenueGut Microbes · 2024
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsUniversity of Alberta
FundersScience and Engineering Research CouncilNatural Sciences and Engineering Research Council of CanadaEuropean CommissionVlaamse regeringKU LeuvenFonds Wetenschappelijk OnderzoekAlberta Innovates
KeywordsBiologyNorovirusZebrafishVirologyGene expression profilingMurine norovirusHost (biology)MicrobiologyProfiling (computer programming)Computational biologyGeneticsVirusGeneGene expression

Abstract

fetched live from OpenAlex

Human noroviruses (HuNoVs) are a major cause of diarrheal disease, yet critical aspects of their biology, including cellular tropism, remain unclear. Although research has traditionally focused on the intestinal epithelium, the hypothesis that HuNoV infects macrophages has been recurrently discussed and is investigated here using a zebrafish larval model. Through single-cell RNA sequencing of dissected zebrafish intestines, we unbiasedly identified macrophages as host cells for HuNoV replication, with all three open reading frames mapped to individual macrophages. Notably, HuNoV preferentially infects actively phagocytosing inflammatory macrophages. HuNoV capsid proteins and double-stranded RNA colocalized within intestinal macrophages of infected zebrafish larvae, and the negative-strand RNA intermediate was detected within FACS-sorted macrophages. Flow cytometry confirmed viral replication within these macrophages, constituting approximately 23% of HuNoV's host cells. Identifying macrophages as host cells prompts a reevaluation of their role in HuNoV pathogenesis, offering new directions for understanding and controlling this infection.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.023
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.031
GPT teacher head0.352
Teacher spread0.321 · 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 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

Citations2
Published2024
Admission routes2
Has abstractyes

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