A novel approach for measuring resistance of Escherichia coli and Listeria monocytogenes to hydrogen peroxide using label-free magnetic resonance imaging and relaxometry

Biomimetic leaves with immobilized catalase for machine learning-enabled validating fresh produce sanitation processes

Washing and sanitation are vital steps during the postharvest processing of fresh produce to reduce the microbial load on the produce surface. Although current process control and validation tools effectively predict sanitizer concentrations in wash water, they have significant limitations in assessing sanitizer effectiveness for reducing microbial counts on produce surfaces. These challenges highlight the urgent need to improve the validation of sanitation processes, especially considering the presence of dynamic organic contaminants and complex surface topographies. This study aims to provide the fresh produce industry with a novel, reliable, and highly accurate method for validating the sanitation efficacy on the produce surface. Our results demonstrate the feasibility of using a food-grade, catalase (CAT)-immobilized biomimetic leaf in combination with vibrational spectroscopy and machine learning to predict microbial inactivation on microgreen surfaces. This was tested using two sanitizers: sodium hypochlorite (NaClO) and hydrogen peroxide (H2O2). The developed CAT-immobilized leaf-replicated PDMS (CAT@L-PDMS) effectively mimics the microscale topographies and bacterial distribution on the leaf surface. Alterations in the FTIR spectra of CAT@L-PDMS, following simulated sanitation processes, indicate chemical changes due to CAT oxidation induced by NaClO or H2O2 treatments, facilitating the subsequent machine learning modeling. Among the five algorithms tested, the competitive adaptive reweighted sampling partial least squares discriminant analysis (CARS-PLSDA) algorithm was the most effective for classifying the inactivation efficacy of E. coli on microgreen leaf surfaces. It predicted bacterial reduction on microgreen surfaces with 100% accuracy in both training and prediction sets for NaClO, and 95% in the training set and 86% in the prediction set for H2O2. This approach can improve the validation of fresh produce sanitation processes and pave the way for future research.

Time Domain (TD) Proton NMR Analysis of the Oxidative Safety and Quality of Lipid-Rich Foods

Food safety monitoring is highly important due to the generation of unhealthy components within many food products during harvesting, processing, storage, transportation and cooking. Current technologies for food safety analysis often require sample extraction and the modification of the complex chemical and morphological structures of foods, and are either time consuming, have insufficient component resolution or require costly and complex instrumentation. In addition to the detection of unhealthy chemical toxins and microbes, food safety needs further developments in (a) monitoring the optimal nutritional compositions in many different food categories and (b) minimizing the potential chemical changes of food components into unhealthy products at different stages from food production until digestion. Here, we review an efficient methodology for overcoming the present analytical limitations of monitoring a food's composition, with an emphasis on oxidized food components, such as polyunsaturated fatty acids, in complex structures, including food emulsions, using compact instruments for simple real-time analysis. An intelligent low-field proton NMR as a time domain (TD) NMR relaxation sensor technology for the monitoring of T₂ (spin-spin) and T₁ (spin-lattice) energy relaxation times is reviewed to support decision-making by producers, retailers and consumers in regard to food safety and nutritional value during production, shipping, storage and consumption.

Biomarkers of oxidative damage in bacteria for the assessment of sanitation efficacy in lettuce wash water

In the fresh produce industry, validation of sanitation efficacy is critical to prevent cross-contamination of produce. The current validation approaches are either based on time-consuming plate counting assays or indirect measurements of chemical properties of wash water. In the study, the focus was to identify biomarkers that can provide direct assessment of oxidative damage in bacteria upon exposure to sanitizers in the presence of fresh produce and correlation of these oxidative biomarkers with logarithmic inactivation of bacteria. Two endogenous bacterial biomarkers, protein carbonylation and thiol oxidation, were evaluated for assessing oxidative damage in Escherichia coli O157:H7 and Listeria innocua during sanitation of pre-cut lettuce leaves with NaOCl or H2O2. Results show that NaOCl treatment was more effective than H2O2 for oxidation of both the intracellular thiols and protein carbonylation in the selected strains. Statistical analysis of the measurements illustrates that oxidation of the intracellular thiol induced by NaOCl or H2O2 was correlated with logarithmic reduction of E. coli O157:H7 and L. innocua. In contrast, changes in the protein carbonylation content were not correlated with reduction in bacterial cell viability. In summary, these results provide a novel approach to validate sanitation efficacy for the fresh produce industry.

Induction and stability of oxidative stress adaptation in Listeria monocytogenes EGD (Bug600) and F1057 in sublethal concentrations of H2O2 and NaOH

Food processing and food handling environments may contain residual levels of sanitizers or cleaners which may trigger oxidative stress adaptation in Listeria monocytogenes. The aim of this study was to determine the induction and stability of oxidative stress adaptation in L. monocytogenes EGD (Bug600) (serotype 1/2a) and F1057 (serotype 4b) at different concentrations and times of sublethal oxidative stress induced by H₂O₂ or sublethal alkali stress induced by NaOH at 37°C. Both L. monocytogenes Bug600 and F1057 strains showed significantly higher survival in lethal oxidative stress (1000ppm H₂O₂) after pre-exposure to 50ppm H₂O₂ for 30min compared to control cells (no pre-exposure to H₂O₂). When the cells were pre-exposed to sublethal alkali stress by NaOH, the oxidative stress adaptation was induced within 5min in L. monocytogenes. The survival of both L. monocytogenes strains was increased by 2 to 4.5 logs in lethal oxidative stress when the cells were pre-exposed to sublethal alkali stress at pH9 from 5 to 120min by NaOH compared to control cells (no pre-exposure to sublethal alkali pH). Two other alkali reagents tested (KOH and NH₄OH) also induced oxidative stress adaptation in L. monocytogenes. For both L. monocytogenes strains, the oxidative stress adaptation induced by sublethal H₂O₂ was reversible in 30min and that induced by sublethal alkali stress was reversible within 60min at 37°C in the absence of such sublethal stress. These findings show that sublethal oxidative or alkali stress conditions can induce oxidative stress adaptation that may increase the risk of survival of L. monocytogenes cells in lethal oxidative stress.