Proteolytic Activation of the 1918 Influenza Virus Hemagglutinin
Bibliographic record
Abstract
Proteolytic activation of the hemagglutinin (HA) protein is indispensable for influenza virus infectivity, and the tissue expression of the responsible cellular proteases impacts viral tropism and pathogenicity. The HA protein critically contributes to the exceptionally high pathogenicity of the 1918 influenza virus, but the mechanisms underlying cleavage activation of the 1918 HA have not been characterized. The neuraminidase (NA) protein of the 1918 influenza virus allows trypsin-independent growth in canine kidney cells (MDCK). However, it is at present unknown if the 1918 NA, like the NA of the closely related strain A/WSN/33, facilitates HA cleavage activation by recruiting the proprotease plasminogen. Moreover, it is not known which pulmonary proteases activate the 1918 HA. We provide evidence that NA-dependent, trypsin-independent cleavage activation of the 1918 HA is cell line dependent and most likely plasminogen independent since the 1918 NA failed to recruit plasminogen and neither exogenous plasminogen nor the presence of the A/WSN/33 NA promoted efficient cleavage of the 1918 HA. The transmembrane serine protease TMPRSS4 was found to be expressed in lung tissue and was shown to cleave the 1918 HA. Accordingly, coexpression of the 1918 HA with TMPRSS4 or the previously identified HA-processing protease TMPRSS2 allowed trypsin-independent infection by pseudotypes bearing the 1918 HA, indicating that these proteases might support 1918 influenza virus spread in the lung. In summary, we show that the previously reported 1918 NA-dependent spread of the 1918 influenza virus is a cell line-dependent phenomenon and is not due to plasminogen recruitment by the 1918 NA. Moreover, we provide evidence that TMPRSS2 and TMPRSS4 activate the 1918 HA by cleavage and therefore may promote viral spread in lung tissue.
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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) | 0.001 | 0.001 |
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".