Naturally fermented dairy products contain a rich microbial biodiversity. This study aimed to provide an overview on the bacterial microbiota biodiversity of 85 samples, previously collected across a wide region of China, Mongolia, and Russia. Data from these 85 samples, including 55 yogurts, 18 naturally fermented yak milks, 6 koumisses, and 6 cheeses, were retrieved and collectively analyzed. The most prevalent phyla shared across samples were Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria, which together accounted for 99% of bacterial sequences. The predominant genera were Lactobacillus, Lactococcus, Streptococcus, Acetobacter, Acinetobacter, Leuconostoc, and Macrococcus, which together corresponded to 96.63% of bacterial sequences. Further multivariate statistical analyses revealed significant differences in the microbiota structure across sample geographic origin and type. First, on the principal coordinate score plot, samples representing the 3 main sample collection regions (Russia, Xinjiang, and Tibet) were mostly located respectively in the upper left, lower right, and lower left quadrants, although slight overlapping occurred. In contrast, samples from the minor sampling areas (Inner Mongolia, Mongolia, Gansu, and Sichuan) were predominantly distributed in the lower left quadrant. These results suggest a possible association between sample geographical origin and microbiota composition. Second, bacterial microbiota structure was stratified by sample type. In particular, the microbiota of cheese was largely distinct from the other sample types due to its high abundances of Lactococcus and Streptococcus. The fermented yak milk microbiota was most like that of the yogurts. Koumiss samples had the lowest microbial diversity and richness. In conclusion, both geographic origin and sample type shape the microbial diversity of naturally fermented milk.
Spontaneously fermented dairy products have a long history, and present diverse microorganisms and unique flavors. To provide insight into the bacterial diversity, 80 different types of spontaneously fermented dairy product samples’ sequence data that were downloaded from MG-RAST and NCBI and 8 koumiss and 4 shubat were sequenced by the PacBio SMRT sequencing platform. All samples including butter, sour cream, cottage cheese, yogurt, koumiss, shubat, and cheese, were collected from various regions in Russia, Kazakhstan, Mongolia and Inner Mongolia (China). The results revealed that Firmicutes and Proteobacteria were the most dominant phyla (>99%), and 11 species were identified with a relative abundance exceeding 1%. Furthermore, Streptococcus salivarius, Lactobacillus helveticus, Lactobacillus delbrueckii, Enterobacter xiangfangensis, and Acinetobacter baumannii were the primary bacterial species in the fermented dairy product samples. Principal coordinates analysis showed that koumiss and shubat stood out from the other samples. Moreover, permutational ANOVA tests revealed that the types of fermented dairy products and geographical origin significantly affected microbial diversity. However, different processing techniques did not affect microbial diversity. In addition, results of hierarchical clustering and canonical analysis of the principal coordinates were consistent. In conclusion, geographical origin and types of fermented dairy products determined the bacterial diversity in spontaneously fermented dairy product samples.
To evaluate the effect of the probiotic, Lactobacillus rhamnosus Probio-M9 (Probio-M9), on the quality of life in stressed adults. Methods: Twelve postgraduate student volunteers were recruited. Six volunteers received oral Probio-M9 for 21 days, while the remaining six received a placebo instead. Fecal samples were collected from the volunteers before and after the intervention. Metagenomic sequencing, nontargeted metabonomics, and quality-of-life follow-up questionnaires were used to evaluate the impact of Probio-M9 consumption on the gut microbiota and life quality of the volunteers. Results: Probio-M9 improved the psychological and physiological quality-of-life symptoms significantly in stressed adults (p < 0.05). The probiotic intervention was beneficial in increasing and maintaining the diversity of gut microbiota. The abundance of Barnesiella and Akkermansia increased in the probiotics group. The feature metabolites of pyridoxamine, dopamine, and 5-hydroxytryptamine (5-HT) were positively correlated with Barnesiella and Akkermansia levels, which might be why the mental state of the volunteers in the probiotic group improved after taking Probio-M9. Conclusions: We identified that oral Probio-M9 can regulate the stability of gut microbiota and affect the related beneficial metabolites, thereby affecting the quality of life (QoL) of stressed adults. Probio-M9 might improve the psychological and physiological quality of life in stressed adults via the gut-brain axis pathway. The causal relationship should be further explored in future studies.
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