Stress Decreases Host Viral Resistance and Increases Covid Susceptibility in Embryonic Stem Cells
Bibliographic record
Abstract
Abstract Stress-induced changes in viral receptor and susceptibility gene expression were measured in embryonic stem cells (ESC) and differentiated progeny. Rex1 promoter-Red Fluorescence Protein reporter ESC were tested by RNAseq after 72hr exposures to control hyperosmotic sorbitol under stemness culture (NS) to quantify stress forced differentiation (SFD) transcriptomic programs. Control ESC cultured with stemness factor removal produced normal differentiation (ND). Bulk RNAseq transcriptomic analysis showed significant upregulation of two genes involved in Covid-19 cell uptake, Vimentin (VIM) and Transmembrane Serine Protease 2 (TMPRSS2). SFD increased the hepatitis A virus receptor (Havcr1) and the transplacental Herpes simplex 1 (HSV1) virus receptor (Pvrl1) compared with ESC undergoing ND. Several other coronavirus receptors, Glutamyl Aminopep tidase (ENPEP) and Dipeptidyl Peptidase 4 (DPP4) were upregulated significantly in SFD>ND. Although stressed ESC are more susceptible to infection due to increased expression of viral receptors and decreased resistance, the necessary Covid-19 receptor, angiotensin converting enzyme (ACE)2, was not expressed in our experiments. TMPRSS2, ENPEP, and DPP4 mediate Coronavirus uptake, but are also markers of extra-embry onic endoderm (XEN), which arise from ESC undergoing ND or SFD. Mouse and human ESCs differentiated to XEN increase TMPRSS2 and other Covid-19 uptake-mediating gene expression, but only some lines express ACE2. Covid-19 susceptibility appears to be genotype-specific and not ubiquitous. Of the 30 gene ontology (GO) groups for viral susceptibility, 15 underwent significant stress-forced changes. Of these, 4 GO groups mediated negative viral regulation and most genes in these increase in ND and decrease with SFD, thus suggesting that stressed increases ESC viral susceptibility.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".