SARS-CoV-2 Spike Expression at the Surface of Infected Primary Human Airway Epithelial Cells
Bibliographic record
Abstract
Different serological assays were rapidly generated to study humoral responses against the SARS-CoV-2 Spike glycoprotein. Due to the intrinsic difficulty of working with SARS-CoV-2 authentic virus, most serological assays use recombinant forms of the Spike glycoprotein or its receptor binding domain (RBD). Cell-based assays expressing different forms of the Spike, as well as pseudoviral assays, are also widely used. To evaluate whether these assays recapitulate findings generated when the Spike is expressed in its physiological context (at the surface of the infected primary cells), we developed an intracellular staining against the SARS-CoV-2 nucleocapsid (N) to distinguish infected from uninfected cells. Human airway epithelial cells (pAECs) were infected with authentic SARS-CoV-2 D614G or Alpha variants. We observed robust cell-surface expression of the SARS-CoV-2 Spike at the surface of the infected pAECs using the conformational-independent anti-S2 CV3-25 antibody. The infected cells were also readily recognized by plasma from convalescent and vaccinated individuals and correlated with several serological assays. This suggests that the antigenicity of the Spike present at the surface of the infected primary cells is maintained in serological assays involving expression of the native full-length Spike.
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 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".