Microbiology Spectrum (Aug 2022)
Optimizing Conditions in the Acid Tolerance Test for Potential Probiotics Using Response Surface Methodology
Abstract
ABSTRACT Acid tolerance is an important feature of probiotic development. It is one of the factors underlying the beneficial effects of probiotics in the intestine. However, the methods used by different researchers to test acid tolerance vary, causing confusion in the interpretation of the results. Therefore, in this study, we determine the optimal conditions for the acid tolerance test using response surface methodology. The factors of pH (2.5 to 3.5), exposure time (1 to 2 h), and pepsin (presence or absence) were used as independent variables, and the survival rates of seven strains (Lacticaseibacillus casei KACC 12413, Lactiplantibacillus plantarum KACC 15357, Limosilactobacillus fermentum KACC 11441, Lactiplantibacillus plantarum WCFS1, Lacticaseibacillus rhamnosus GG, Lactiplantibacillus plantarum KCTC 21024, and Lactiplantibacillus plantarum WiKim 0112) known to have probiotic properties were used as dependent variables. The results of the analysis of variance (ANOVA) indicated that the pH value and exposure time in acidic environments significantly affected the acid tolerance test model, and their interaction also had an effect (P < 0.05). Using the ANOVA results, the condition of the acid tolerance test was optimized with a target of an 85% survival rate for each strain. The optimized conditions of the acid tolerance test were as follows: pH 2.92, exposure time of 1.73 h, and presence of pepsin and pH 3, exposure time of 1.98 h, and absence of pepsin. These results can optimize strain selection with rigorous acid tolerance without confusion by unifying the conditions for the acid tolerance test. IMPORTANCE The acid tolerance test, which is the first step in selecting probiotics, is not standardized and can often cause confusion in the interpretation of results. Thus, in the present study, we optimized the conditions for the acid tolerance test using response surface methodology. These optimized conditions can be used to screen for strains with acid tolerance.
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