Activation of the <scp>PERK</scp> branch of the unfolded protein response during production reduces specific productivity in <scp>CHO</scp> cells via downregulation of <scp>PDGFRa</scp> and <scp>IRE1a</scp> signaling
Bibliographic record
Abstract
During the course of biopharmaceutical production, heterologous protein expression in Chinese hamster ovary (CHO) cells imposes a high proteostatic burden that requires cellular adaptation. To mitigate such burden, cells utilize the unfolded protein response (UPR), which increases endoplasmic reticulum (ER) capacity to accommodate elevated rates of protein synthesis and folding. In this study, we show that during production the UPR regulates growth factor signaling to modulate growth and protein synthesis. Specifically, the protein kinase R-like ER kinase (PERK) branch of the UPR is responsible for transcriptional down-regulation of platelet-derived growth factor receptor alpha (PDGFRa) and attenuation of the IRE1-alpha (IRE1a) branch of the UPR. PERK knockout (KO) cell lines displayed reduced growth and viability due to higher rates of apoptosis despite having stabilized PDGFRa levels. Knocking out PERK in an apoptosis impaired (Bax/Bak double KO) antibody-expressing cell line prevented apoptotic cell death and revealed that apoptosis was likely triggered by increased ER stress and reactive oxygen species levels in the PERK KO hosts. Our findings suggest that attenuation of IRE1a and PDGFRa signaling by the PERK branch of the UPR reduces ER protein folding capacity and hence specific productivity of CHO cells in order to mitigate UPR and prevent apoptotic cell death. Last, Bax/Bak/PERK triple KO CHO cell lines displayed 2-3 folds higher specific productivity and titer (up to 8 g/L), suggesting that modulation of PERK signaling during production processes can greatly improve specific productivity in CHO cells.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".