Optimization of turbidity experiments to estimate the probability of growth for individual bacterial cells

Abstract

Using turbidity measurements to quantify bacterial growth is a common and well-established practice in microbiology. Automated devices offering high throughput analyses have largely contributed to the increase of its use. A main difficulty of this method is that it detects growth only at late exponential phase, making turbidity measurements limited for studies focussing on low cell numbers. This work proposes an improved estimator for the probability of growth of individual cells using turbidity-based measurements, when the initial number of cells is low and random. We modify the currently used estimator for the expected cell number per well, a Poisson-parameter, and show that an optimal scenario is when ca 20% of the wells do not become turbid, resulting in improved accuracy and precision.