Cellular sialoglycans are differentially required for endosomal and cell-surface entry of SARS-CoV-2 in lung cell lines
Bibliographic record
Abstract
Cell entry of severe acute respiratory coronavirus-2 (SARS-CoV-2) and other CoVs can occur via two distinct routes. Following receptor binding by the spike glycoprotein, membrane fusion can be triggered by spike cleavage either at the cell surface in a transmembrane serine protease 2 (TMPRSS2)-dependent manner or within endosomes in a cathepsin-dependent manner. Cellular sialoglycans have been proposed to aid in CoV attachment and entry, although their functional contributions to each entry pathway are unknown. In this study, we used genetic and enzymatic approaches to deplete sialic acid from cell surfaces and compared the requirement for sialoglycans during endosomal and cell-surface CoV entry using lentiviral particles pseudotyped with the spike proteins of different sarbecoviruses. We show that entry of SARS-CoV-1, WIV1-CoV and WIV16-CoV, like the SARS-CoV-2 omicron variant, depends on endosomal cathepsins and requires cellular sialoglycans for entry. Ancestral SARS-CoV-2 and the delta variant can use either pathway for entry, but only require sialic acid for endosomal entry in cells lacking TMPRSS2. Binding of SARS-CoV-2 spike protein to cells did not require sialic acid, nor was sialic acid required for SARS-CoV-2 entry in TMRPSS2-expressing cells. These findings suggest that cellular sialoglycans are not strictly required for SARS-CoV-2 attachment, receptor binding or fusion, but rather promote endocytic entry of SARS-CoV-2 and related sarbecoviruses. In contrast, the requirement for sialic acid during entry of MERS-CoV pseudoparticles and authentic HCoV-OC43 was not affected by TMPRSS2 expression, consistent with a described role for sialic acid in merbecovirus and embecovirus cell attachment. Overall, these findings clarify the role of sialoglycans in SARS-CoV-2 entry and suggest that cellular sialoglycans mediate endosomal, but not cell-surface, SARS-CoV-2 entry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".