GGCX promotes Eurasian avian-like H1N1 swine influenza virus adaption to interspecies receptor binding
Bibliographic record
Abstract
The Eurasian avian-like (EA) H1N1 swine influenza virus (SIV) possesses the capacity to instigate the next influenza pandemic, owing to its heightened affinity for the human-type α-2,6 sialic acid (SA) receptor. Nevertheless, the molecular mechanisms underlying the switch in receptor binding preferences of EA H1N1 SIV remain elusive. In this study, we conduct a comprehensive genome-wide CRISPR/Cas9 knockout screen utilizing EA H1N1 SIV in porcine kidney cells. Knocking out the enzyme gamma glutamyl carboxylase (GGCX) reduces virus replication in vitro and in vivo by inhibiting the carboxylation modification of viral haemagglutinin (HA) and the adhesion of progeny viruses, ultimately impeding the replication of EA H1N1 SIV. Furthermore, GGCX is revealed to be the determinant of the D225E substitution of EA H1N1 SIV, and GGCX-medicated carboxylation modification of HA 225E contributes to the receptor binding adaption of EA H1N1 SIV to the α-2,6 SA receptor. Taken together, our CRISPR screen has elucidated a novel function of GGCX in the support of EA H1N1 SIV adaption for binding to α-2,6 SA receptor. Consequently, GGCX emerges as a prospective antiviral target against the infection and transmission of EA H1N1 SIV.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".