Decoding the synergistic mechanisms of functional microbial agents on the microecology and metabolic function in medium-high temperature Daqu starter for enhancing aromatic flavor

Abstract

Utilizing functional Daqu has emerged as an effective strategy to enhance aromatic compounds in Chinese Baijiu. However, research on how functional microbial agents enhance aromatics-producing enzymes and maintain community homeostasis in functional Daqu remains limited. Herein, we reveal the mechanisms of functional microbial agents for enhancing aromatic compounds through reducing interspecies interactions and simplifying the ecological network to drive the aggregated distribution of lactic acid bacteria, and inducing a localized microecology comprised of Aspergillus, Pichia, Millerozyma, Pseudomonas, Paenibacillus, and Rhizomucor, effectively boosting the expression of key enzymes for aromatic synthesis. Functional microbial agents significantly enhance the key enzyme activities (515.9 nmol/h/g and 6.1 U/g for PrAO and ALDH) compared with traditional Daqu (198.6 nmol/h/g and 0.9 U/g), improving the content of aromatic compounds with an increase of 185.57 %. These results revealed the mechanisms of functional Daqu in aromatic compounds production, thus contributing to improve Baijiu quality.

Keywords: Aromatics-producing enzymes; Ecological interaction; Enhanced aromatic compounds; Functional microbial agents; Metabolic function.

Graphical abstract

Fig. 1

Schematic diagram illustrating the functional Daqu preparation process.

Fig. 2

Effects of functional agents on physicochemical and enzymatic properties during MHT-Daqu preparation, including temperature (A), moisture (B), acidity (C), saccharifying ability (D), liquefying ability (E), fermenting ability (F), and esterifying ability (G). B and K represent functional and traditional Daqu, respectively. BX and KX denote core temperatures of functional and traditional Daqu, while BF and KF indicate Qu-room temperatures for functional and traditional Daqu.

Fig. 3

Effects of functional agents on volatile flavors and aroma-producing enzymes during MHT-Daqu preparation. Principal component analysis of all volatile metabolites (A) and aromatic compounds (B), the total content of each chemical category (C), the content of phenylethanol, phenylacetaldehyde, and ethyl phenylacetate (D), primary amine oxidase activity (E), aldehyde dehydrogenase activity (F), and Spearman's correlations between enzyme activity and target metabolites (G). (* 0.01 < p ≤ 0.05, ** 0.001 < p ≤ 0.01, *** p ≤ 0.001).

Fig. 4

Effects of functional agents on α-diversity (A), β-diversity (B), bacterial community structure (C), and fungal community structure (D) during MHT-Daqu preparation. (* 0.01 < p ≤ 0.05, ** 0.001 < p ≤ 0.01, *** p ≤ 0.001).

Fig. 5

Microbial co-occurrence network analysis (|p| > 0.7 and p < 0.05) and temporal distribution for traditional Daqu (A) and functional Daqu (B). Topological parameters, including the number of nodes, edges, average degree, network diameter (ND), modularity, average clustering coefficient, and average path length (APL), are listed below the networks. Node size indicates the number of edges connected to each node. Early refers to the first stage (days 3 to 11); middle refers to the second stage (days 18 to 30); late refers to the storage period (M1-M3). Arrows indicate the fermentation progression of MHT-Daqu. Microbes with module changes following bioaugmentation are highlighted in bold black font; those with shifts in distribution stages without module changes are indicated in green font. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 6

Environmental response and metabolic function of microbiomes. Mantel test of modules and related variables for traditional Daqu (A) and functional Daqu (B). Metabolic pathways of alcohols, acids, and aromatic compounds (C), and the abundance variation of expressed enzymes (D) during MHT-Daqu production. In the mantel test, edges colour indicate statistical significance, edge widths represent the correlation strength, and solid/dashed edges denote positive/negative correlations, respectively. The r-value is derived from Spearman's correlation coefficient (* 0.01 < p ≤ 0.05, ** 0.001 < p ≤ 0.01, *** p ≤ 0.001). Temp, temperature; SA, saccharifying ability; LA, liquefying ability; FA, fermenting ability; EA, esterifying ability; PE, phenylethanol; PA, phenylacetaldehyde; EP, ethyl phenylacetate; PrAO, primary amine oxidase; ALDH, aldehyde dehydrogenase. In the metabolic pathways, enzymes with increased expression after biofortification are shown in red font; blue backgrounds indicate alcohols and acids, while yellow backgrounds indicate aromatic compounds. The pentagram indicates PrAO and ALDH. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)