Bacillus subtilis 168 Thermal Inactivation Kinetics: Virtual Prediction of D and Z Values

This study leverages the SwarmLabs virtual experiment engine to conduct a cross-analysis of the biology scenario for Bacillus subtilis 168 (subtilis) in BG-11 Medium (cyanobacteria). The scenario employs an unknown kinetics model, utilizing a GP surrogate model and active learning strategies to extract the optimal parameter combination with the minimum number of experiments.

Experimental Scenario: Microbial Thermal Death Kinetics

This scenario simulates the growth behavior of Bacillus subtilis 168 in BG-11 Medium (cyanobacteria), with the core model based on unknown kinetics and key parameters including the specific growth rate μ_max, half-saturation constant Ks, and others.

Strain Profile: Bacillus subtilis 168

Bacillus subtilis 168 is a model strain commonly used in biology research.

Culture medium formulation: BG-11 Medium (cyanobacteria)

BG-11 medium (cyanobacteria) is the standard culture medium for Bacillus subtilis 168.

Cross-analysis: Biological dynamics of *Bacillus subtilis* 168 × BG-11 Medium (cyanobacteria)

Combining the genomic features of Bacillus subtilis 168 (phylum: Bacillota) with the nutrient composition of BG-11 Medium (cyanobacteria) enables accurate prediction of growth curves in biological scenarios within a virtual environment. This combination covers the complete parameter space, ranging from a maximum specific growth rate of 0.72 to a half-saturation constant of 0.02.

Recommended Parameters for Virtual Experiments

Based on this combination of scenario, strain, and culture medium, the SwarmLabs virtual experiment engine can automatically execute the following workflow:

• Fit the dynamics curve of the unknown system using a GP surrogate model (noise_var=0.03²)
• Through the active learning strategy, reduced from 16 runs of full factorial experiments to ~12
• VirtualLab Guard Three-state validation gate: Regions with prediction confidence below the threshold are automatically flagged as "needs verification".
• Output the fitted curve with uncertainty intervals, targeting an R² > 0.95 (consistent with Monod 1949).

From Literature to Virtual Experiments: Thermal Death Kinetics of Bacillus subtilis 168: Virtual Prediction of D- and Z-Values

Through the SwarmLabs virtual experiment engine, researchers can rapidly assess the biological dynamics of Bacillus subtilis 168 in BG-11 Medium (cyanobacteria) without performing actual wet-lab experiments. This "data-driven research" model compresses traditional R&D cycles from weeks to mere hours, providing a novel technical pathway for microbiology research and industrial fermentation optimization.