Fig 1.
Strain-dependent expression and solubility of ETA.
(A) Total ETA expression as percentage of total cellular protein across 12 engineered E. coli strains. (B) Soluble ETA yield (mg/L) for each strain under optimal conditions (12°C induction). Data are mean ± SD (n = 3). p < 0.001 vs. BL21(DE3) control based on one-way ANOVA with Tukey post-hoc test.
Fig 2.
Impact of temperature and redox additives on ETA solubility.
(A) Soluble ETA yield across four induction temperatures in SHuffle T7. Linear regression line shown with 95% confidence band. (B) Effect of redox additives on soluble yield at 12°C. Data are mean ± SD (n = 3). Different letters indicate statistically significant differences (p < 0.05, one-way ANOVA with Tukey’s post-hoc test).
Fig 3.
Chaperone optimization and structural validation.
(A) Soluble ETA yield in SHuffle T7 co-expressing different chaperone systems at 12°C. Data are mean ± SD (n = 3). Statistical significance determined by one-way ANOVA with Tukey’s post-hoc test. (B) SDS-PAGE analysis of purified ETA under reducing (R, + DTT) and non-reducing (NR, -DTT) conditions. M, molecular weight marker.
Table 1.
Structural and functional characterization of optimized recombinant ETA.
Table 2.
Feature importance ranking from machine learning model.
Fig 4.
Machine learning model performance and interpretation.
(A) Correlation between predicted and observed soluble ETA yields for the test dataset (n = 115 conditions). Solid line represents perfect prediction, dashed lines show 95% confidence interval. (B) SHAP summary plot showing impact of top features on model output. Each point represents a single prediction from the test set.