Bacterial Microbiota and Metabolic Character of Traditional Sour Cream and Butter in Buryatia, Russia

Traditional sour cream and butter are widely popular fermented dairy products in Russia for their flavor and nutrition, and contain rich microbial biodiversity, particularly in terms of lactic acid bacteria (LAB). However, few studies have described the microbial communities and metabolic character of traditional sour cream and butter. The objective of this study was to determine the bacterial microbiota and metabolic character of eight samples collected from herdsmen in Buryatia, Russia. Using single-molecule real-time (SMRT) sequencing techniques, we identified a total of 294 species and/or subspecies in 169 bacterial genera, belonging to 14 phyla. The dominant phylum was Firmicutes (81.47%) and the dominant genus was Lactococcus (59.28%). There were differences between the bacterial compositions of the sour cream and butter samples. The relative abundances of Lactococcus lactis, Lactococcus raffinolactis, and Acetobacter cibinongensis were significantly higher in sour cream than in butter, and the abundance of Streptococcusthermophilus was significantly lower in sour cream than in butter. Using a pure culture method, 48 strains were isolated and identified to represent seven genera and 15 species and/or subspecies. Among these isolates, Lactococccus lactis subsp. lactis (22.50%) was the dominant LAB species. Ultra-performance liquid chromatography–quadrupole–time of flight mass spectrometry at elevated energy was used in combination with statistical methods to detect metabolite differences between traditional sour cream and butter. A total of 27,822 metabolites were detected in all samples, and Lys-Lys, isohexanal, palmitic acid, Leu-Val, and 2′-deoxycytidine were the most dominant metabolites found in all samples. In addition, 27 significantly different metabolites were detected between the sour cream and butter samples, including short peptides, organic acids, and amino acids. Based on correlation analyses between the most prevalent bacterial species and the main metabolites in sour cream, we conclude that there may be a connection between the dominant LAB species and these metabolites. This study combined omics techniques to analyze the bacterial diversity and metabolic character of traditional sour cream and butter, and we hope that our findings will enrich species resource libraries and provide valuable resources for further research on dairy product flavor

Understanding the swelling behavior of individual starch granules by ParCS

Starch is a widely used ingredient in food products, acting as a thickening, clouding, and gelling agent. Starch gelatinization is an important process that can influence the texture of food products, therefore, it has been studied extensively by many researchers. A Particle Cohort Study (ParCS) apparatus was used to observe the gelatinization process of individual starch granules from four types of legume starch: yellow pea, red bean, chickpea, and green lentil. This new method allows us to capture and understand the variability between individual granules during the swelling that occurs due to gelatinization. The size as a function of time was measured for a large number of individual granules in order to quantify the intra-sample variability for each type of starch, as this information is not available from the standard techniques for characterizing gelatinization: starch pasting and differential scanning calorimetry (DSC). The swelling of individual starch granules under non-isothermal conditions was recorded and subjected to image analysis for quantifying their sizes. For each type of legume starch, around 180 granules were collected for data analysis. The cumulative size distribution measurements using image analysis were similar to that obtained from the laser diffraction method, except for red bean starch, which showed a smaller size by image analysis. We demonstrate that an empirical model, the Gompertz function, is highly effective at describing the size vs. time data. Using the Gompertz function, the data from image analysis are fitted to obtain and extract two new parameters related to gelatinization that we define for the first time in this manuscript: granule-swelling temperature and granule-swelling time scale. The accuracy of these new parameters is demonstrated by comparison with standard techniques. After proposing an alternative method for interpreting starch pasting data we show a very good correlation between all three techniques. The results indicate that these legume starches have a remarkably low variability in gelatinization properties. This new method of characterization is expected to enable optimization of starch gelatinization properties during large-scale processing of food products.Land and Food Systems, Faculty ofGraduat

A Metabolomics Approach Uncovers Differences between Traditional and Commercial Dairy Products in Buryatia (Russian Federation)

Commercially available and traditional dairy products differ in terms of their manufacturing processes. In this study, commercially available and traditionally fermented cheese, yogurt, and milk beverages were analyzed and compared. The metabolomic technique of ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-Q-TOF) in the MSE mode was used in combination with statistical methods, including univariate analysis and chemometric analysis, to determine the differences in metabolite profiles between commercially and traditionally fermented dairy products. The experimental results were analyzed statistically and showed that traditional and commercial dairy products were well differentiated in both positive and negative ion modes, with significant differences observed between the samples. After screening for metabolite differences, we detected differences between traditional milk beverages and yogurt and their commercial counterparts in terms of the levels of compounds such as l-lysine, l-methionine, l-citrulline, l-proline, l-serine, l-valine and l-homocysteine, and of short peptides such as Asp-Arg, Gly-Arg, His-Pro, Pro-Asn. The greatest difference between commercially available and traditional cheese was in the short peptide composition, as commercially available and traditional cheese is rich in short peptides

PLAGL2-EGFR-HIF-1/2α Signaling Loop Promotes HCC Progression and Erlotinib Insensitivity

Background and Aims: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide, hence a major public health threat. Pleomorphic adenoma gene like-2 (PLAGL2) has been reported to play a role in tumorigenesis. However, its precise function in HCC remains poorly understood. Approach and Results: In this study, we demonstrated that PLAGL2 was up-regulated in HCC compared with that of adjacent nontumorous tissues and also correlated with overall survival times. We further showed that PLAGL2 promoted HCC cell proliferation, migration, and invasion both in vitro and in vivo. PLAGL2 expression was positively correlated with epidermal growth factor receptor (EGFR) expression. Mechanistically, this study demonstrated that PLAGL2 functions as a transcriptional regulator of EGFR and promotes HCC cell proliferation, migration, and invasion through the EGFR-AKT pathway. Moreover, hypoxia was found to significantly induce high expression of PLAGL2, which promoted hypoxia inducible factor 1/2 alpha subunit (HIF1/2A) expression through EGFR. Therefore, this study demonstrated that a PLAGL2-EGFR-HIF1/2A signaling loop promotes HCC progression. More importantly, PLAGL2 expression reduced hepatoma cells’ response to the anti-EGFR drug erlotinib. PLAGL2 knockdown enhanced the response to erlotinib. Conclusions: This study reveals the pivotal role of PLAGL2 in HCC cell proliferation, metastasis, and erlotinib insensitivity. This suggests that PLAGL2 can be a potential therapeutic target of HCC.Fil: Hu, Weiwei. China Pharmaceutical University; ChinaFil: Zheng, Shufang. China Pharmaceutical University; ChinaFil: Guo, Haixin. China Pharmaceutical University; ChinaFil: Dai, Beiying. China Pharmaceutical University; ChinaFil: Ni, Jiaping. China Pharmaceutical University; ChinaFil: Shi, Yaohong. China Pharmaceutical University; ChinaFil: Bian, Hanrui. China Pharmaceutical University; ChinaFil: Li, Lanxin. China Pharmaceutical University; ChinaFil: Shen, Yumeng. China Pharmaceutical University; ChinaFil: Wu, Mo. China Pharmaceutical University; ChinaFil: Tian, Zhoutong. China Pharmaceutical University; ChinaFil: Liu, Guilai. China Pharmaceutical University; ChinaFil: Hossain, Md Amir. China Pharmaceutical University; ChinaFil: Yang, Hongbao. China Pharmaceutical University; ChinaFil: Wang, Duowei. China Pharmaceutical University; ChinaFil: Zhang, Qin. Jiangsu Cancer Hospital; ChinaFil: Yu, Jun. Jiangsu Cancer Hospital; ChinaFil: Birnbaumer, Lutz. Pontificia Universidad Católica Argentina "Santa María de los Buenos Aires". Instituto de Investigaciones Biomédicas. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas; ArgentinaFil: Feng, Jifeng. Jiangsu Cancer Hospital; ChinaFil: Yu, Decai. Medical School Of Nanjing University; ChinaFil: Yang, Yong. China Pharmaceutical University; Chin