RESULTS: Here, we investigated the microbial dynamics by next-generation sequencing, and outlined a differential non-targeted metabolite profiling in the process of serofluid dish fermentation using the method of hydrophilic interaction liquid chromatography column with ultra-high-performance liquid chromatography-quadruple time-of-flight mass spectrometry. Lactobacillus was the leading genus of bacteria, while Pichia and Issatchenkia were the dominant fungi. They all accumulated during fermentation. In total, 218 differential metabolites were identified, of which organic acids, amino acids, sugar and sugar alcohols, fatty acids, and esters comprised the majority. The constructed metabolic network showed that tricarboxylic acid cycle, urea cycle, sugar metabolism, amino acids metabolism, choline metabolism, and flavonoid metabolism were regulated by the fermentation. Furthermore, correlation analysis revealed that the leading fungi, Pichia and Issatchenkia, were linked to organic acids, amino acid and sugar metabolism, flavonoids, and several other flavor and functional components. Antibacterial tests indicated the antibacterial effect of serofluid soup against Salmonella and Staphylococcus.
CONCLUSION: This work provides new insights into the complex microbial and metabolic networks during serofluid dish fermentation, and a theoretical basis for the optimization of its industrial production. © 2020 Society of Chemical Industry.
METHODS: The mid-stream urine was collected from 96 patients diagnosed with dengue fever at Penang General Hospital (PGH) and 50 healthy volunteers. Urine samples were analyzed with proton nuclear magnetic resonance (1H NMR) spectroscopy, followed by chemometric multivariate analysis. NMR signals highlighted in the orthogonal partial least square-discriminant analysis (OPLS-DA) S-plots were selected and identified using Human Metabolome Database (HMDB) and Chenomx Profiler. A highly predictive model was constructed from urine profile of dengue infected patients versus healthy individuals with the total R2Y (cum) value 0.935, and the total Q2Y (cum) value 0.832.
RESULTS: Data showed that dengue infection is related to amino acid metabolism, tricarboxylic acid intermediates cycle and β-oxidation of fatty acids. Distinct variations in certain metabolites were recorded in infected patients including amino acids, various organic acids, betaine, valerylglycine, myo-inositol and glycine.
CONCLUSION: Metabolomics approach provides essential insight into host metabolic disturbances following dengue infection.