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Record W4405668765 · doi:10.1016/j.virol.2024.110374

Imaging of viral replication in live cells by using split fluorescent protein-tagged reporter flaviviruses

2024· article· en· W4405668765 on OpenAlexaff
Ping Yang, Zheng-Jian Wang, Haitao Lu, Jing-Long Ye, Guangchuan Wang, Cheng‐Feng Qin, Qing Ye, Zhongyu Liu

Bibliographic record

VenueVirology · 2024
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsInstitute of Infection and Immunity
FundersBasic and Applied Basic Research Foundation of Guangdong ProvinceSun Yat-sen UniversityInstitute of Zoology, Chinese Academy of SciencesNatural Science Foundation of Guangdong ProvinceNational Natural Science Foundation of China
KeywordsBiologyReplication (statistics)VirologyFluorescenceGreen fluorescent proteinFluorescent proteinViral replicationLive cell imagingCell biologyVirusGeneticsGeneCell

Abstract

fetched live from OpenAlex

The knowledge on the life cycle of flaviviruses is still incomplete, and no direct-acting antivirals against their infections are clinically available. Herein, by screening via a Zika virus (ZIKV) replicon assay, we found that the N-terminus of NS2A exhibited great tolerance to the insertions of different split fluorescent proteins (split-FPs). Furthermore, both ZIKV and dengue virus encoding a split-FP-tagged NS2A propagated efficiently, and the split-FP-tagged ZIKVs had good genetic stability. Robust green fluorescence was observed in the reporter cell lines infected with these viruses and the fluorescence responded to anti-flavivirus chemicals with high specificity and sensitivity. Moreover, the sites of viral RNA replication were illuminated in live cells. Interestingly, by blocking viral RNA synthesis with an NS5 inhibitor, we found a correlation between the morphological characteristics of potential replication organelles and RNA amplification, highlighting that the NS2A-tagged viruses are of great value for the in-depth understanding of flavivirus replication mechanisms.

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 score0.260
Threshold uncertainty score0.408

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 head0.011
GPT teacher head0.289
Teacher spread0.278 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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