Building Better Microbial Growth Models: Estimating the Influence of Nutrient Diffusion Rate on the Transition Period from Exponential to Stationary Phase Using Escherichia coli k-12

Introduction: One of the long term goals in modeling microbial growth in foods is development of more mechanistically-based models. Currently, most models are based on studies in liquid culture where growth kinetics are largely independent of inoculum size. However, in solid matrices, it can be hypothesized that the initial inoculum size would affect nutrient diffusion rates during late exponential and early stationary phase, thus affecting the shape of growth curve. 

Purpose: The purpose of the study was to evaluate if inoculum size influences the growth kinetics of Escherichia coli K-12 in a solid matrix.

Methods: E.coli K-12 cells were grown in BHI broth to early stationary phase and then diluted to obtain the desired inoculum sizes (from 10² to 10⁶ CFU/ml). The inocula were transferred to 2% (wv/vol) agar system, solidified, and then overlaid with additional top agar to prevent surface growth. The cultures were incubated at 37°C and sampled for designated time period until early stationary phase. Viable counts data were fitted using Baranyi model (IPMP 2013). 

Results: The movements of E.coli K-12 cells were restricted resulting in the formation of micro-colonies in the agar matrix. With lower inoculum sizes, the longer transport distance resulted in limiting nutrient diffusion during late exponential phase. The transition period from exponential to stationary phase was influenced strongly by inoculum size, with higher inoculum sizes leading to a more abrupt transition, while lower inoculum sizes lead to more gradual attainment of maximum population densities.

Significance: The results show the possibility of developing more effective growth models that better depict the growth of bacteria in solid food systems. These results are an important step in developing more mechanistically-based food safety and food quality models that take into consideration of phase-dependent physiological events.