Estimating decay kinetic parameters and persistence of bacteria in water is essential for future modelling

Abstract

The aim of this work was to obtain decay kinetic parameters for bacteria sedimentation–resuspension in water. For that, synthetic water matrices prepared with four particle sizes at 2.5 and 5 g/l, were spiked with Escherichia coli and Enterococcus faecalis, selected as Gram-negative and -positive models, respectively. Matrices with bacteria without solids were used as controls. Turbidity was measured and culturable bacteria decay was evaluated using membrane filtration over time. Also, the persistence of culturable E. faecalis and its DNA (detected by real-time PCR) was compared. When no colonies were detected, water matrices were mixed to re-suspend sediments and surface samples were collected and analysed. Spearman test was applied to find correlation between bacteria and turbidity. A persistence coefficient (PC) was defined and several kinetic parameters (decay rate constants, R2, T90) were calculated from experimental data. While culturable E. coli disappeared from the surface of all water matrices with turbidity (p < 0.05), E. faecalis only showed strong and positive correlation in matrices with higher turbidity and smaller particles. E. coli decayed slower when interacting with smallest solids (<44 μm) than with the largest ones (>149 μm), being T90 3–4 times higher in the former. Also, it reappeared and persisted in the surface of all matrices after resuspension despite solid concentration (PC: 0.5−0.9). Instead, culturable E. faecalis, persisted less (lower PC values) in matrices with 2.5 g/l than with 5 g/l and no logic relation was observed for any rate constant with particle size. E. faecalis DNA remained in suspension for longer periods until the end of the experience as seen through their lower rate constants (kDNA < 0.05 h−1). Accurate decay kinetic parameters, like the ones obtained here, are crucial for modelling the fate and transport of bacteria in water and to perform a robust and realistic quantitative risk assessment.