Physiological Improvement to Enhance <i>Escherichia coli</i> Cell‐Surface Display via Reducing Extracytoplasmic Stress
Bibliographic record
Abstract
Cell physiology was impaired when enhanced yellow fluorescence protein (EYFP) was displayed on the Escherichia coli cell surface, resulting in growth arrest and poor display performance. Coexpression of Skp, a periplasmic chaperone known to interact with several outer membrane proteins for their transport and insertion in the outer membrane, was demonstrated to be effective to restore cell physiology. When Skp was coexpressed with EYFP display, host cells became less sensitive to ethylenediaminetetraacetic acid and sodium dodecyl sulfate, implying that cell physiology was improved. Most importantly, the display performance was highly enhanced as a result of the increased specific fluorescence intensity without growth arrest. The results of transmission electron microscopy indicate that the density of surface-displayed EYFP was highly increased upon Skp coexpression. Cells with EYFP display experienced extracytoplasmic stress, as reflected by the induced promoter activities of three stress-responsive genes, degP, cpxP, and rpoH. The extracytoplasmic stress reflected by the degP promoter activity appears to be consistent with the cell physiology observed phenotypically under various culture conditions for cell-surface display. Therefore, the PdegP::lacZ allele was proposed to be a suitable "sensor" for monitoring the extracytoplasmic stress and cell physiology during the course of E. coli cell-surface display.
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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) | 0.001 | 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) | 0.001 | 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".