Due to concerns over bacterial tolerance to sanitizers, FDA and FSIS recommend rotating sanitizers in RTE food processing facilities to better control foodborne pathogens, in particular, Listeria monocytogenes (Lm). These recommendations are nonbinding; whether Lm develops tolerance to common sanitizers remains
inconclusive and debated. Even if Lm develops tolerance through sub-lethal exposure to sanitizers, how long and how strong the tolerance can last should be considered in determining whether sanitizer rotation is needed and how often it should be applied. Lack of consensus and quantitative data on possibility and duration of sanitizer tolerance creates confusions and dilemmas, especially when sanitizer rotation presents considerable challenges in training, compliance, and cost control to the industry. This proposal describes studies to help settle the debate and fill critical knowledge gaps regarding Lm tolerance to chlorine and quaternary ammonium compounds. We will measure residual sanitizer levels in produce processing facilities. We will perform laboratory assays to investigate tolerance development and persistence. We will explore machine-learning-aided tolerance prediction and identify evolutionary signals (or lack thereof) of tolerance development from whole genome sequencing data. Our results will provide the industry and regulators with scientific evidence for substantiating, better implementing, or justifiably shelving sanitizer rotational programs.
There is still no scientific consensus on whether Listeria monocytogenes (Lm) develops sanitizer tolerance. We hypothesize that development of two types of sanitizer tolerance may occur in Lm. First, short-term adaptation to sub-lethal levels of sanitizers induces acquired tolerance, which is transient and not hereditary. Second, long- term selection by sanitizers causes intrinsic tolerance, which is established in Lm populations by evolutionary changes to Lm genomes. To help settle the debate, we will test our hypothesis by distinguishing and investigating both types of tolerance in Lm using chlorine and a quaternary ammonium compound as example sanitizers.
In this study, we will survey residual sanitizer levels in a leafy green and a tomato processing facilities to evaluate if laboratory-derived sanitizer levels optimal for tolerance development are relevant to produce processors. We will assess the possibility of acquired tolerance by measuring the difference in minimum inhibition concentrations (MIC) before and after sanitizer adaptation. We will study how different sanitizer levels and exposure time affect the development of acquired tolerance, including how long the tolerance can last after exposure to sanitizers. We will explore the mechanisms behind the development of acquired sanitizer tolerance by characterizing temporal shifts in Lm transcriptome throughout the duration of the tolerance.
We will assess intrinsic tolerance in a collection of 200-300 strategically selected Lm strains using high-throughput growth kinetics assays. We will search for evolutionary evidence that suggests the development of intrinsic tolerance in recent history by analyzing whole genome sequencing (WGS) data of these strains. We
will build a machine-learning classifier to predict tolerance levels and identify key tolerance predictors from WGS.
This research will provide valuable prerequisite information for determining if sanitizer rotation is necessary for preventing the development of Lm tolerance to sanitizers. Scientific data from the project will also help optimize sanitation practices to mitigate tolerance development and determine frequency for sanitizer rotation if rotation is needed.