Predictive modelling of Lactobacillus casei KN291 survival in fermented soy beverage

Modeling of Growth and Organic Acid Kinetics and Evolution of the Protein Profile and Amino Acid Content during Lactiplantibacillus plantarum ITM21B Fermentation in Liquid Sourdough

The application of mathematical modeling to study and characterize lactic acid bacterial strains with pro-technological and functional features has gained attention in recent years to solve the problems relevant to the variabilities of the fermentation processes of sourdough. Since the key factors contributing to the sourdough quality are relevant to the starter strain growth and its metabolic activity, in this study, the cardinal growth parameters for pH, temperature (T), water activity (a_w), and undissociated lactic acid of the sourdough strain Lactiplantibacillus plantarum ITM21B, were determined. The strain growth, pH, organic acids (lactic, acetic, phenyllactic, and hydroxy-phenyllactic), total free amino acids, and proteins were monitored during fermentation of a liquid sourdough based on wheat flour and gluten (Bio21B) after changing the starting T, pH, and inoculum load. Results demonstrated that the different fermentation conditions affected the strain growth and metabolite pattern. The organic acid production and growth performance were modeled in Bio21B, and the resulting predictive model allowed us to simulate in silico the strain performances in liquid sourdough under different scenarios. This mathematical predictive approach can be useful to optimize the fermentation conditions needed to obtain the suitable nutritional and technological characteristics of the L. plantarum ITM21B liquid sourdough.

A Predictive Growth Model for Pro-technological and Probiotic Lacticaseibacillus paracasei Strains Fermenting White Cabbage

Bacterial strains belonging to Lacticaseibacillus paracasei species are generally used as starters in food fermentations and/or as probiotics. In the current study, the growth cardinal parameters of four L. paracasei strains (IMPC2.1, IMPC4.1, P40 and P101), isolated from table olives or human source, were determined. Strains were grown in liquid medium and incubated at several temperatures (10 values from 5.5°C–40°C) and pH (15 values from 3.2 to 9.1) along the growth range. The cardinal temperature model was used to describe temperature effects on the maximum specific growth rate of L. paracasei whereas new equations were developed for the effect of pH. The estimated T_min values ranged between −0.97°C and 1.95°C and were lower than 0°C for strains IMPC4.1 and P101. Strain P40 was able to grow in the most restricted range of temperature (from 1.95°C to 37.46°C), while strain IMPC4.1 was estimated to survive at extreme conditions showing the lowest pH_min. Maximum specific growth rates of L. paracasei IMPC2.1 in white cabbage (Brassica oleracea var. capitata) were used to calculate the correction factor (C_f) defined as the bias between the bacterial maximum specific growth rate in broth and in the food matrix. A simple bi-linear model was also developed for the effect of temperature on the maximum population density reached in white cabbage. This information was further used to simulate the growth of L. paracasei strains in cabbage and predict the time to reach the targeted probiotic level (7 log₁₀ CFU/g) using in silico simulations. This study demonstrates the potential of the predictive microbiology to predict the growth of beneficial and pro-technological strains in foods in order to optimize the fermentative process.

Effect of Probiotic Soy Milk on Serum Levels of Adiponectin, Inflammatory Mediators, Lipid Profile, and Fasting Blood Glucose Among Patients with Type II Diabetes Mellitus

Probiotic therapies are going to be an effective alternative therapeutic strategy in the treatment and management of diabetes. The mechanism behind the essential effects of probiotic therapies in diabetic patients was not fully understood. The objective of this study was to evaluate the effects of probiotic soy milk containing Lactobacillus planetarum A7 on inflammation, lipid profile, fasting blood glucose, and serum adiponectin among patients with type 2 diabetes mellitus. Forty patients with type 2 diabetes, at the age of 35-68 years old, were assigned to two groups in this randomized, double-blind, controlled clinical trial. The patients in the intervention group consumed 200 ml/day of probiotic soy milk containing L. planetarum A7 and those in control group consumed 200 ml/day of pure soy milk for 8 weeks. Serum TNF-α, C reactive protein, adiponectin, lipid profile, and fasting blood glucose were determined before and after intervention. In intervention group, serum adiponectin in pre- and post-treatment did not show any significant changes (2.52 ± 0.74 vs 2.84 ± 0.61, P = 0.658), as well as changes in serum TNF-α and C reactive protein (172.44 ± 5.7 vs 172.83 ± 7.6, P = 0.278, 4.2 ± 1.4 vs 4.5 ± 1.9, P = 0.765, respectively). Low-density cholesterol and high-density cholesterol changed significantly (P = 0.023, P = 0.017, respectively), but fasting blood glucose did not show any significant changes. The results of this study showed that consumption of probiotic soy milk and soy milk has no effect on serum adiponectin and inflammation, but it can change lipid profile among type 2 diabetic patients.

A randomized, double-blind, placebo-controlled, clinical trial on probiotic soy milk and soy milk: effects on epigenetics and oxidative stress in patients with type II diabetes

This clinical trial aimed to discover the effects of probiotic soy milk and soy milk on MLH1 and MSH2 promoter methylation, and oxidative stress among type II diabetic patients. Forty patients with type II diabetes mellitus aged 35-68 years were assigned to two groups in this randomized, double-blind, controlled clinical trial. Patients in the intervention group consumed 200 ml/day of probiotic soy milk containing Lactobacillus plantarum A7, while those in the control group consumed 200 ml/d of conventional soy milk for 8 weeks. Fasting blood samples, anthropometric measurements, and 24-h dietary recalls were collected at the baseline and at the end of the study, respectively. Probiotic soy milk significantly decreased promoter methylation in proximal and distal MLH1 promoter region (P < 0.01 and P < 0.0001, respectively) compared with the baseline values, while plasma concentration of 8-hydroxy-2'-deoxyguanosine (8-OHdG) decreased significantly compared with soy milk (P < 0.05). In addition, a significant increase in superoxide dismutase (SOD) activity was observed in probiotic soy milk group compared with baseline value (P < 0.01). There were no significant changes from baseline in the promoter methylation of MSH2 within either group (P > 0.05). The consumption of probiotic soy milk improved antioxidant status in type II diabetic patients and may decrease promoter methylation among these patients, indicating that probiotic soy milk is a promising agent for diabetes management.