Abstract
Bacterial spores are important in food processing due to their ubiquity, resistance to high temperature and chemical inactivation. This work aims to study the effect of ultraviolet C (UVC) on the spores of Bacillus subtilis and Bacillus velezensis at a molecular and individual level to guide in deciding on the right parameters that must be applied during the processing of liquid foods. The spores were treated with UVC using phosphate buffer saline (PBS) as a suspension medium and their lethality rate was determined for each sample. Purified spore samples of B. velezensis and B. subtilis were treated under one pass in a UVC reactor to inactivate the spores. The resistance pattern of the spores to UVC treatment was determined using dipicolinic acid (Ca-DPA) band of spectral analysis obtained from Raman spectroscopy. Flow cytometry analysis was also done to determine the effect of the UVC treatment on the spore samples at the molecular level. Samples were processed for SEM and the percentage spore surface hydrophobicity was also determined using the Microbial Adhesion to Hydrocarbon (MATH) assay to predict the adhesion strength to a stainless-steel surface. The result shows the maximum lethality rate to be 6.5 for B. subtilis strain SRCM103689 (B47) and highest percentage hydrophobicity was 54.9% from the sample B. velezensis strain LPL-K103 (B44). The difference in surface hydrophobicity for all isolates was statistically significant (P < 0.05). Flow cytometry analysis of UVC treated spore suspensions clarifies them further into sub-populations unaccounted for by plate counting on growth media. The Raman spectroscopy identified B4002 as the isolate possessing the highest concentration of Ca-DPA. The study justifies the critical role of Ca-DPA in spore resistance and the possible sub-populations after UVC treatment that may affect product shelf-life and safety. UVC shows a promising application in the inactivation of resistant spores though there is a need to understand the effects at the molecular level to design the best parameters during processing.
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