Investigating the Role of ß-Disodium Glycerophosphate and Urea in Promoting Growth of Streptococcus thermophilus from Omics-Integrated Genome-Scale Models.

This study investigates the impact of urea and ß-GP on the growth of Streptococcus thermophilus S-3, a bacterium commonly used in industrial fermentation processes. Through a series of growth experiments, transcriptome, metabolome, and omics-based analyses, the research demonstrates that both urea and ß-GP can enhance the biomass of S. thermophilus, with urea showing a more significant effect. The optimal urea concentration for growth was determined to be 3 g/L in M17 medium. The study also highlights the metabolic pathways influenced by urea and ß-GP, particularly the galactose metabolism pathway, which is crucial for cell growth when lactose is the substrate. The integration of omics data into the genome-scale metabolic model of S. thermophilus, iCH502, allowed for a more accurate prediction of metabolic fluxes and growth rates. The study concludes that urea can serve as a viable substitute for ß-GP in the cultivation of S. thermophilus, offering potential cost and efficiency benefits in industrial fermentation processes. The findings are supported by validation experiments with 11 additional strains of S. thermophilus, which showed increased biomass in UM17 medium.

Genome-scale reconstruction of the metabolic network in Streptococcus thermophilus S-3 and assess urea metabolism.

BACKGROUND: Streptococcus thermophilus is an important strain widely used in dairy fermentation, with distinct urea metabolism characteristics compared to other lactic acid bacteria. The conversion of urea by S. thermophilus has been shown to affect the flavor and acidification characteristics of milk. Additionally, urea metabolism has been found to significantly increase the number of cells and reduce cell damage under acidic pH conditions, resulting in higher activity. However, the physiological role of urea metabolism in S. thermophilus has not been fully evaluated. A deep understanding of this metabolic feature is of great significance for its production and application. Genome-scale metabolic network models (GEMs) are effective tools for investigating the metabolic network of organisms using computational biology methods. Constructing an organism-specific GEM can assist us in comprehending its characteristic metabolism at a systemic level. RESULTS: In the present study, we reconstructed a high-quality GEM of S. thermophilus S-3 (iCH492), which contains 492 genes, 608 metabolites and 642 reactions. Growth phenotyping experiments were employed to validate the model both qualitatively and quantitatively, yielding satisfactory predictive accuracy (95.83%), sensitivity (93.33%) and specificity (100%). Subsequently, a systematic evaluation of urea metabolism in S. thermophilus was performed using iCH492. The results showed that urea metabolism reduces intracellular hydrogen ions and creates membrane potential by producing and transporting ammonium ions. This activation of glycolytic fluxes and ATP synthase produces more ATP for biomass synthesis. The regulation of fluxes of reactions involving NAD(P)H by urea metabolism improves redox balance. CONCLUSION: Model iCH492 represents the most comprehensive knowledge-base of S. thermophilus to date, serving as a potent tool. The evaluation of urea metabolism led to novel insights regarding the role of urease. © 2023 Society of Chemical Industry.

Improved CNN-Based Indoor Localization by Using RGB Images and DBSCAN Algorithm.

With the intense deployment of wireless systems and the widespread use of intelligent equipment, the requirement for indoor positioning services is increasing, and Wi-Fi fingerprinting has emerged as the most often used approach to identifying indoor target users. The construction time of the Wi-Fi received signal strength (RSS) fingerprint database is short, but the positioning performance is unstable and susceptible to noise. Meanwhile, to strengthen indoor positioning precision, a fingerprints algorithm based on a convolution neural network (CNN) is often used. However, the number of reference points participating in the location estimation has a great influence on the positioning accuracy. There is no standard for the number of reference points involved in position estimation by traditional methods. For the above problems, the grayscale images corresponding to RSS and angle of arrival are fused into RGB images to improve stability. This paper presents a position estimation method based on the density-based spatial clustering of applications with noise (DBSCAN) algorithm, which can select appropriate reference points according to the situation. DBSCAN analyses the CNN output and can choose the number of reference points based on the situation. Finally, the position is approximated using the weighted k-nearest neighbors. The results show that the calculation error of our proposed method is at least 0.1-0.3 m less than that of the traditional method.

Effects of different carbon sources on metabolic profiles of carbohydrates in Streptococcus thermophilus during fermentation.

BACKGROUND: Streptococcus thermophilus is a major starter used in the dairy industry and it could improve the flavor of fermented products. It is necessary to improve biomass of S. thermophilus for its application and industrialization. The utilization of carbon sources directly affects the biomass of S. thermophilus. Therefore, the carbohydrate metabolism of S. thermophilus should be investigated. RESULTS: In the present study, metabolic parameters and gene expression of S. thermophilus S-3 with different carbon sources were investigated. The physicochemical results showed that S. thermophilus S-3 had high lactose utilization. Transcriptome analysis found that approximately 104 genes were annotated onto 15 carbohydrate metabolic pathways, of which 15 unigenes were involved in the phosphotransferase system and 75 were involved in the ATP-binding cassette transporter system. In addition, 171 differentially expressed genes related to carbohydrate metabolism were identified. Expression of the galactose metabolism genes lacSZ and galKTEM increased significantly from the lag phase to the mid-exponential growth phase as a result of the global regulator protein, catabolite control protein A (CcpA). The high expression of galK in the mid- to late- phases indicated that the metabolite galactose is re-transported for intracellular utilization. CcpA regulation may also induce high expressions of glycolytic pathway regulated-genes related to lactose utilization, including ldh, fba, eno, pfkA, bglA, pgi, pgm and pyk, producing optimal glycolytic flux and S. thermophilus S-3 growth. CONCLUSION: The present study provides new insights into the carbon metabolism regulation and provide theoretical support for high-density fermentation of S. thermophilus S-3. © 2022 Society of Chemical Industry.