Fungal Community Succession and Assembly Mechanisms during the Post-ripening Process of Nongxiang Daqu

doi:10.13560/j.cnki.biotech.bull.1985.2025-1459

Abstract

Abstract:

Objective This study investigates the changes in fermentation performance, fungal community composition, and dynamic succession patterns of different grades of Nongxiang Daqu during the post-ripening period (0–90 days), aiming to elucidate the assembly mechanisms of the fungal community. Method We used high-throughput sequencing technology to track the dynamic succession of fungal communities in different grades of Daqu (premium, first-grade, and second-grade) during post-ripening, and to explore the correlations between these communities and biochemical indicators. We also applied neutral and null models to analyze the assembly patterns of the fungal communities during the post-ripening process. Result During post-ripening, the esterification capacity, saccharification capacity, fermentation capacity, and cellulase activity of Daqu increased significantly (P<0.05), with premium-grade Daqu exhibiting significantly higher values than first-grade and second-grade Daqu. Thermoascus (44.18%–54.51%), Thermomyces (37.88%–49.42%), and Aspergillus (1.69%–6.31%) were not only the dominant fungal genera shared by three Daqu grades but also served as key differential taxa that differentiated between Daqu grades and post-ripening stages. Moreover, we observed significant correlations between biochemical indicators of Daqu and fungal communities. Specifically, esterification capacity showed a significant positive correlation with Pichia and a highly significant negative correlation with Byssochlamys and Wickerhamomyces. Saccharification and fermentation capacities were significantly positively correlated with Thermomyces and significantly negatively correlated with Byssochlamys. Cellulase, acidic protease, and alkaline protease activities were significantly positively correlated with Candida and significantly negatively correlated with Wickerhamomyces. Neutral and null model analyses reveal that stochastic processes predominantly affect the dynamic succession of fungal communities in different grades of Daqu during post-ripening, with drift and dispersal limitation serving as the primary drivers of stochastic changes in community assembly. Conclusion The fungal community structure of premium Daqu is more stable, and its biochemical indicators are superior. Particularly after three months of post-ripening, the characteristics of Daqu approach an ideal state, making it suitable for liquor production.

Key words: Nongxiang Daqu, grade difference, post-ripening process, biochemical indicators, fungal community characteristics, succession pattern

ZHANG Ru-min, ZHANG Bo, LIN Jie-hao, QIAO Jing, ZHAO Hong-yuan, GUO Xiao-peng, REN Hai-wei. Fungal Community Succession and Assembly Mechanisms during the Post-ripening Process of Nongxiang Daqu[J]. Biotechnology Bulletin, 2026, 42(5): 203-212.

Figures/Tables 7

Fig. 1 Biochemical indicators of different grades of Daqu during the post-ripening processP, F, and S refer to premium, first, and second grades of Daqu, respectively. 0, 45, and 90 refer to post-ripening for 0 d, 45 d, and 90 d, respectively. Different capital letters indicate significant differences (P<0.05) between Daqu of the same grade at different post-ripening stages, while different lowercase letters indicate significant differences (P<0.05) between Daqu of different grades at the same post-ripening stage, the same below

Fig. 2 Analysis of fungal community alpha diversity during the post-ripening process of different grades of Daqu

Fig. 3 Similarity of fungal OTU composition (A) and principal component analysis (B) in different grades of Daqu

Fig. 4 Species composition of different grades of Daqu during the post-ripening process at phylum(A) and genus (B)

Fig. 5 Bar chart of LDA at the fungi genus level for different grades of Daqu in the post-ripening process

Fig. 6 Correlation of dominant fungal genera with biochemical indicators(A) and dominant bacterial genera(B) in DaquCorrelations were calculated with Pearson’s method, * P<0.05, and ** P<0.01. The bacterial abundance data in Figure B were derived from the published results of our research group [15]

Fig. 7 Neutral models (A-F) and null models (G, H) of fungi in Daqu of different grades and ripening periodsA: 0 d; B: 45 d; C: 90 d; D: premium grade of Daqu; E: first grade of Daqu; F: second grade of Daqu. The solid blue line indicates the best fit of the neutral model, and the dashed lines represent the 95% confidence interval of the model prediction. The Rsqr value represents the overall goodness-of-fit of the neutral community model. A higher Rsqr value indicates a greater influence of stochastic processes and a lesser influence of deterministic processes on the microbial community

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