Co-fermented milk beverage has better stability and contains more health-promoting amino acid metabolites than single-strain-fermented milk beverage over one-month storage

A novel rhodamine B fluorescence probe for rapid identification of different amino acids by high efficiency fluorescence spectrum-mass spectrometry

Introduction

Rapid detection of amino acids plays an important role in the field of medical diagnosis. By combining Rhodamine B with triphenylamine, a novel double-response fluorescence probe (E)-4-((4-(((3',6'-bis(diethylamino)-3-oxospiro[isoindoline-1,9'-xanthen]-2-yl)imino)methyl)phenyl)(phenyl)amino)benzaldehyde (RBTPA) was prepared for rapid identification of different amino acids.

Methods

Under daylight and 365 nm irradiation, it was found that the color change was most bright at pH = 3, and changed to dim at pH = 4. When pH = 3 and pH = 4, the photophysical properties of the two strong acids are very different. The maximum redshift of UV absorption light is 110 nm, and the maximum fluorescence emission intensity is 4 times different.

Results and Discussion

In order to further observe their binding structure analysis with different amino acids, qualitative analysis of each response structure was determined by mass spectrometry according to different molecular weights. The fluorescence probe RBTPA has two different isomers for recognition response in aldehyde group and imine group, respectively.

The interaction between Lactobacillus delbrueckii ssp. bulgaricus M58 and Streptococcus thermophilus S10 can enhanced texture and flavor profile of fermented milk: Insights from metabolomics analysis

Lactobacillus delbrueckii ssp. bulgaricus M58 (M58) and Streptococcus thermophilus S10 (S10) are 2 dairy starter strains known for their favorable fermentation characteristics. Therefore, this research aimed to study the effects of 1-d low-temperature ripening on the physicochemical properties and metabolomics of fermented milk. Initially, the performance of single (M58 or S10) and dual (M58+S10) strain fermentation was assessed, revealing that the M58+S10 combination resulted in a shortened fermentation time, a stable gel structure, and desirable viscosity, suggesting positive strain interactions. Subsequently, non-targeted metabolomics analyses using LC-MS and GC-MS were performed to comparatively analyze M58+S10 fermented milk samples collected at the end of fermentation and after 1-d low-temperature ripening. The results showed a significant increase in almost all small peptides and dodecanedioic acid in the samples after one day of ripening, while there was a substantial decrease in indole and amino acid metabolites. Moreover, notable increases were observed in high-quality flavor compounds, such as geraniol, delta-nonalactone, 1-hexanol,2-ethyl-, methyl jasmonate, and undecanal. This study provides valuable insights into the fermentation characteristics of the dual bacterial starter consisting of M58 and S10 strains and highlights the specific contribution of the low-temperature ripening step to the overall quality of fermented milk.

Binary probiotic fermentation promotes signal (cyclic AMP) exchange to increases the number of viable probiotics, anthocyanins and polyphenol content, and the odor scores of wolfberry fermented beverages

The effects and underlying molecular mechanisms of binary probiotics (Lactiplantibacillus plantarum subsp. plantarum CGMCC 1.5953 and Lacticaseibacillus casei CGMCC 1.5956) on the quality of wolfberry fermented beverages (WFB) were investigated. The results indicated that binary probiotics increased the number of probiotics, anthocyanin (89.92 ± 1.64 mg/L), polyphenol content (283.04 ± 3.81 µg/mL), and odor score (24.19) in WFB. Metabolomics found that they could enhance signal exchange (cyclic AMP) between binary probiotics and improve the utilization of citrulline, d-proline, d-glucose, and d-galactose through galactose metabolism and amino acid biosynthesis pathway to promote probiotics growth. Furthermore, HS-SPME-GC-MS and GS-IMS revealed that the improvement in flavor was mainly due to an increase in the content of the aromatic flavor substances 3-heptanol, glutaraldehyde, and 2-heptanone, and a decrease in the content of the off-flavor substances methyl isobutyl ketone-D and 2-undecanone. This is strategically important for the development of WFB with high probiotic content and unique flavor.

Interaction between lactic acid bacteria and Polygonatum sibiricum saponins and its application to microencapsulated co-delivery

This study aimed to investigate the interaction between L.casei and L.bulgaricus with Polygonatum sibiricum saponins (PSS) and to explore the co-microencapsulation to reduce their loss rate during storage and consumption. 1% PSS was added to the culture broth, and it was found that the growth and metabolism of the strains were accelerated, especially in the compound probiotic group, indicating that PSS has potential for prebiotics. LC-MS observed significant differences in the composition and content of saponins in PSS. The metabolomics results suggest that the addition of PSS resulted in significant changes in the metabolites of probiotics. In addition, it was found that the combination of probiotics and PSS may have stronger hypoglycemic ability (ɑ-glucosidase, HepG2). Finally, a co-microencapsulated delivery system was constructed using zein and isomaltooligosaccharide. This system can achieve more excellent resistance of probiotics and PSS in gastrointestinal fluids, effectively transporting both to the small intestine.

Multifunctional-separation-mode ion chromatography method for determining major metabolites during multiple parallel fermentation of rice wine

Facile and effective analysis methods are desirable for elucidating the behaviours of metabolites during fermentation reactions. Herein, a multifunctional-separation-mode ion chromatography (MFS-IC) method was developed for the simultaneous monitoring of major metabolites during multiple parallel fermentation, including those related to central carbon metabolism (saccharification, glycolysis, alcoholic fermentation, and the tricarboxylic acid (TCA) cycle). The use of two types of sulfo-modified size-exclusion columns and phthalic acid as the eluent allowed the separation of oligosaccharides (disaccharides, trisaccharides, and tetrasaccharides), glucose, pyruvate, and major organic acids during the TCA cycle (cis-aconitate, citrate, iso-citrate, malate, fumarate, and succinate but not α-ketoglutarate) from other non-target analytes. The MFS-IC method was successfully applied to monitoring the major metabolites in the rice wine brewing process. This approach can contribute to an improved understanding of metabolite behaviour during fermentation without requiring the use of expensive advanced instrumentation methods such as liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry.

Mapping multi-omics characteristics related to short-term PM2.5 trajectory and their impact on type 2 diabetes in middle-aged and elderly adults in Southern China

The relationship between PM2.5 and metabolic diseases, including type 2 diabetes (T2D), has become increasingly prominent, but the molecular mechanism needs to be further clarified. To help understand the mechanistic association between PM2.5 exposure and human health, we investigated short-term PM2.5 exposure trajectory-related multi-omics characteristics from stool metagenome and metabolome and serum proteome and metabolome in a cohort of 3267 participants (age: 64.4 ± 5.8 years) living in Southern China. And then integrate these features to examine their relationship with T2D. We observed significant differences in overall structure in each omics and 193 individual biomarkers between the high- and low-PM2.5 groups. PM2.5-related features included the disturbance of microbes (carbohydrate metabolism-associated Bacteroides thetaiotaomicron), gut metabolites of amino acids and carbohydrates, serum biomarkers related to lipid metabolism and reducing n-3 fatty acids. The patterns of overall network relationships among the biomarkers differed between T2D and normal participants. The subnetwork membership centered on the hub nodes (fecal rhamnose and glycylproline, serum hippuric acid, and protein TB182) related to high-PM2.5, which well predicted higher T2D prevalence and incidence and a higher level of fasting blood glucose, HbA1C, insulin, and HOMA-IR. Our findings underline crucial PM2.5-related multi-omics biomarkers linking PM2.5 exposure and T2D in humans.