Dataset Information

Comprehensive Metabolite Profiling and Microbial Communities of Doenjang (Fermented Soy Paste) and Ganjang (Fermented Soy Sauce): A Comparative Study.

ABSTRACT: Doenjang and ganjang are secondary fermented soybean products from meju (primary fermented product) following a complex fermentation process that separates the products into solid (doenjang) and liquid (ganjang) states. We performed a comparative study on gas chromatography mass spectrometry-(GC-MS) and liquid chromatography mass spectrometry-(LC-MS) based metabolite profiling with fungal and bacterial microbial community analysis of doenjang and ganjang during fermentation. Metabolite profiling and microbial community data showed distinct patterns, depending on the fermentation process. The relative levels of metabolic patterns were similar and most of the microorganisms produced halophilic or halotolerant microbes during the fermentation period in doenjang and ganjang. In the doenjang end products, isoflavones, soyasaponins, and amino acids were largely distributed and Debaryomyces and Staphylococcus were dominant, whereas the biogenic amine and phenylpropanoid contents were highly distributed in the ganjang end products, with higher levels of Meyerozyma and Tetragenococcus. Our results demonstrate that the quality of doenjang and ganjang is predominantly influenced by the microbiome and by metabolite changes during fermentation. Moreover, the present study provides a platform for comparing samples in different states.

SUBMITTER: Song DH

PROVIDER: S-EPMC8003076 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Koji making is a pre-fermentation stage in soy sauce manufacturing that impacts final product quality. Previous studies have provided valuable insights into the microbial species present in koji. However, changes in microbial community functional potential during koji-making are not well-known, nor are the associations among microbial populations and flavoring characteristics. In the present study, we investigated the succession of microbial communities, microbial community functional potential, metabolite profiles, and associations among microbial community members/functions with metabolites during koji making using shotgun metagenomic and metabolomic analyses. Firmicutes, Proteobacteria, and Ascomycota were identified as the most abundant microbial phyla in early koji making (0-12 h). Aspergillus (fungi) and Weissella (bacteria) exhibited marked abundance increases (0.98-38.45% and 0.31-30.41%, respectively) after 48 h of fermentation. Metabolite analysis revealed that aspartic acid, lysine, methyl acetate, isovaleraldehyde, and isoamyl alcohol concentrations increased ∼7-, 9-, 5-, 49-, and 10-fold after 48 h of fermentation. Metagenomic profiling demonstrated that koji communities were dominated by genes related to carbohydrate metabolism and amino acid metabolism, but functional profiles exhibited marked shifts after 24 h of fermentation. The abundances of genes within the categories of carbohydrate and amino acid metabolism all increased during koji making, except for pyruvate metabolism, glycolysis/gluconeogenesis, and the citrate cycle. Correlational analyses indicated that Aspergillus, Lactococcus, Enterococcus, Corynebacterium, and Kocuria abundances were positively correlated with 15 amino acid concentrations (all p < 0.05), while Weissella abundances were positively correlated with concentrations of volatile flavor compounds, including eight amino acids, phenylacetaldehyde, acetic acid, 2,3-butanediol, ethyl acetate, and ethanol (p < 0.05). These results provide valuable information for understanding the microbial-associated mechanisms of flavor formation during koji making.

Project description:Microorganisms play essential roles in flavor formation during soy sauce fermentation. Different soy sauce fermentation types significantly affect flavor formation. However, comparisons of microbial communities and metabolites between different fermentation types have been little studied. Here, we investigated variation in microbial communities, metabolite profiles, and metabolic pathways during Japanese-type (JP) and Cantonese-type (CP) fermentation. Free amino acids and volatile compound profiles varied significantly between fermentation types, with JP samples containing higher contents of esters (39.84%; p < 0.05), alcohols (44.70%; p < 0.05) in the 120 d fermentation samples. Volatile compound profiles varied significantly between fermentation types, with JP samples containing higher contents of esters, alcohols, and free amino acids (p < 0.05). Metagenomic analysis indicated that both JP and CP communities were dominated by Tetragenococcus, Staphylococcus, Weissella (bacteria), and Aspergillus (fungi), but the two communities varied differently over time. Tetragenococcus drastically increased in abundance throughout the fermentation (from 0.02 to 59.2%) in JP fermentation, whereas Tetragenococcus (36.7%) and Staphylococcus (29.7%) dominated at 120 d of fermentation in CP fermentation. Metagenomic functional profiles revealed that the abundances of most genes involved with carbohydrate, amino acid, and lipid metabolism exhibited significant differences between fermentation types (p < 0.05) during the middle to late fermentation stages. Furthermore, predicted metabolic pathways for volatile substance biosynthesis differed between JP and CP fermentation, likely explaining the differences in flavor metabolite profiles. In addition, most of the genes associated with flavor generation were affiliated with Tetragenococcus, Weissella, Staphylococcus, Bacillus, and Aspergillus, suggesting that these microbes play important roles in flavor production during soy sauce fermentation. This study significantly improves our understanding of microbial functions and their metabolic roles in flavor formation during different soy sauce fermentation processes.

Dataset Information

Comprehensive Metabolite Profiling and Microbial Communities of Doenjang (Fermented Soy Paste) and Ganjang (Fermented Soy Sauce): A Comparative Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets