Results

Overview

The results of APOPTO-SENSE 2.0 demonstrate the successful engineering of a dual-cell biosensing system for detecting chemotherapy-induced apoptosis in cancer cells. Through iterative DBTL cycles, we achieved specific, dose-dependent signal outputs, validating our proof-of-concept for personalized drug sensitivity testing. Key findings include high specificity in apoptosis detection, linear fluorescence responses, and predictive modeling that aligns with wet lab data. These outcomes confirm the system's potential for oncology applications, with expansions to multiplexing discussed in future directions.

Results are presented from wet lab experiments, dry lab simulations, and integrated analyses. For methods, see Experiments and Dry Lab; for design rationale, see Engineering.

Plasmid Construction and Verification

Plasmids for the synNotch sensor and reporter modules were successfully assembled and verified. Gibson cloning yielded high-efficiency constructs, confirmed by restriction digestion and Sanger sequencing.

  • Yields: 200-500 ng/µL post-purification (NanoDrop; A260/A280 >1.8).
  • Verification: Agarose gels showed expected band sizes (e.g., ~5 kb for synNotch plasmid); sequences matched designs with 100% accuracy.
  • Outcome: Stable integration into HEK293T cells, enabling functional sensor lines.

Sensor Cell Line Construction

PiggyBac transfection produced stable HEK293T lines expressing synNotch and reporter constructs.

  • Selection Efficiency: >80% survival post-dual antibiotic treatment (puromycin/blasticidin).
  • Expression Validation: Constitutive mCherry fluorescence in >90% of cells (microscopy); synNotch confirmed via Western blot if performed.
  • Outcome: Functional sensor cells ready for co-culture assays, with low basal activation (<5%).

Apoptosis Induction and Validation

Raphasatin treatment (10 µM, 24h) induced apoptosis in HL-60 cells, validated by flow cytometry.

Group Early Apoptotic (%) Late Apoptotic/Necrotic (%) Viable (%)
Control (Untreated) 3.2 ± 1.1 2.5 ± 0.8 94.3 ± 1.5
Vehicle (DMSO) 4.1 ± 1.3 3.0 ± 0.9 92.9 ± 1.7
Raphasatin Treated 35.7 ± 4.2 28.4 ± 3.5 35.9 ± 5.1

Outcome: Significant apoptosis induction (>60% total), providing positive controls for co-culture assays. Data processed with FlowJo; error bars represent SD (n=3).

Co-Culture Assays and Biosensor Activation

Co-culture of apoptotic HL-60 with sensor cells activated the synNotch system, yielding dose-dependent TagBFP signals.

Condition TagBFP/mCherry Ratio Specificity (% Signal Reduction in Controls)
No Co-Culture (Baseline) 0.15 ± 0.05 N/A
Non-Apoptotic HL-60 0.22 ± 0.07 95%
Apoptotic HL-60 (10^5 cells) 0.85 ± 0.12 N/A
Apoptotic HL-60 (10^6 cells) 1.65 ± 0.18 N/A

Outcome: Linear response (R²=0.92) to apoptotic input; high specificity confirmed. Ratios quantified via ImageJ (n=3 fields/well, triplicates).

Dry Lab Modeling Results

Simulations aligned with wet lab data, predicting system behavior.

  • Molecular Modeling: Predicted stable synNotch structure (RMSD <2 Å); binding affinity Kd ~5 nM.
  • Kinetic Simulations: Linear output up to 50% apoptosis (R²=0.95); sensitivity analysis identified cleavage rate as key parameter.
  • ML Predictions: IC50 forecasts with MAE <5%; 85% accuracy for untested drugs.

Outcome: Models validated experimental linearity, guiding optimizations like UAS repeat increases.

Overall Conclusions

APOPTO-SENSE 2.0 successfully detects apoptosis with high specificity and dose-dependency, proving its viability for drug sensitivity testing. Integrated results from wet and dry labs support clinical potential, with future multiplexing for broader cell death profiling.