江南大学陈坚院士团队和贵州茅台集团联合发表关于大曲发酵的研究成果
近日，江南大学陈坚院士团队和贵州茅台集团联合在国际食品期刊《Food Bioscience》发表了题为“Cooperative interaction between Pediococcus and Bacillus communities as a key factor in the high-temperature Thermal differentiation of Daqu”的研究论文。Huabin Tu为第一作者，江南大学陈坚院士和茅台集团Li Wang为共同通讯作者。
大曲要经历三个发酵阶段，第一个阶段的温度能达到 60 至 65 摄氏度。这种高温是酱香型白酒高温大曲最为显著的特征和关键评价指标之一，对其独特的烤香形成起到了重要作用。高温大曲的发酵温度源于微生物群落所产生的代谢热；此外，温度是大曲群落自组装的一个关键因素。在大曲发酵过程中，不同生境中微生物群落之间的相互作用会导致产生不同的代谢热，进而产生不同的发酵结果。高温大曲的发酵一般是在全封闭的发酵车间进行的；因此，这个过程无法完全被控制，会出现温度波动和差异，从而影响产品的质量和稳定性。所以，在相同的初始条件（环境、原料等）下，仅仅由于群落相互作用而导致的大曲温度差异的原因，对于管理大曲生产至关重要。
在持续的热应激环境下，微生物之间的相互作用对于维持产热至关重要。根据不同的条件，微生物会发生几种不同的相互作用，比如竞争、拮抗和共生。共生关系是物种之间积极的双向相互作用；合作共生通常不如竞争和拮抗那么常见。然而，由外部环境因素引起的非生物胁迫能够促进微生物群落之间积极关系的形成，互补细菌之间通过代谢交换产生合作。物种间的合作关系增强了微生物群落的恢复能力和韧性，使其能够应对各种非生物胁迫，如干旱、化学胁迫和抗生素胁迫，从而扩大了一个群落的适应范围。
然而，由于对导致微生物温度升高和产热的关键因素缺乏了解，阻碍了在发酵过程中对产热过程的有效控制。优势菌属Pediococcus的微生物可能会介导这一过程；然而，它们的丰度与在高温大曲高温环境下所观察到的低产热情况相矛盾，这表明大曲微生物群落可能作为一个整体形成了一种适应性更强的新表型。在典型的固态发酵过程中，持续的高温环境会促进积极的相互作用，并刺激核心微生物的生长。
本研究利用实时温度监测、绝对定量扩增子测序和微量热分析的结果，对微生物的合作与竞争在大曲发酵过程中驱动温度差异中的作用进行了探究。据观察，菌属片Pediococcus和Bacillus之间的平衡相互作用是实现高发酵温度的一个关键因素。结果表明，发酵初期的特点是存在竞争和生态位分化，并且随着发酵的进行，高温大曲的微生物群落往往会趋向于合作。相关性网络分析显示，在发酵第 4 天，Pediococcus和Bacillus形成了不同的聚类，每个聚类内部呈正相关，而它们之间则呈显著负相关。相互作用及凝聚指数分析表明，这两个属在大曲的高温发酵过程中都起着至关重要的作用。此外，模拟发酵实验证实，与Pediococcus或Bacillus菌属单独占主导的情况相比，Pediococcus和Bacillus共存能够在高温环境下增强产热。这些研究结果凸显了微生物群落相互作用在调控发酵温度方面的重要性，为优化大曲发酵产品的质量和稳定性提供了宝贵的见解。
Fig. 2. Changes in Microbial Structure and Correlation with Temperature During High-Temperature Daqu Fermentation. (a, b) Differences in composition of (a) bacterial and (b) fungal communities obtained by PCoA. Samples were divided into five groups according to fermentation time, as represented by blue, red, light green, purple, and green circles. (c, d) Absolute quantification of (c) bacteria and (d) fungi in different temperature groups during a single Daqu fermentation cycle. (e, f) Linear regression of (e) total bacterial count and (f) Pediococcus count against temperature during fermentation, with a 95% confidence interval. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3. Biodiversity during High-Temperature Daqu Fermentation. (a, b) Changes in Chao1, Shannon, Simpson diversity index for (a) bacteria and (b) fungi throughout the fermentation process. Group comparisons were performed using a t-test. ∗p < 0.05; ∗∗p < 0.01.
Fig. 4. Correlation Network and Cohesion Analysis of High-Temperature Daqu Fermentation. (a, b) Correlations between (a) total bacteria and (b) top 20 dominant bacterial species in terms of abundance at key nodes during the primary fermentation of high-temperature Daqu, as categorized by interaction. (c, d) Calculation of (c) positive cohesion and (d) negative cohesion within the bacterial community during the primary fermentation of Daqu. Group comparisons were performed using a t-test. ∗p < 0.05; ∗∗p < 0.01; ∗∗∗p < 0.005.
Fig. 5. Core Microorganisms and Their Role in Temperature Differentiation in Daqu. (a) Analysis of bacterial differences in Daqu on days 4–6. (b) Screening criteria for key microorganisms during primary fermentation of high-temperature Daqu, including bacteria with the highest absolute abundance on days 4 and 6, top 20 bacteria with the highest node degree in the correlation network on day 4, and bacteria with higher positive cohesion and lower negative cohesion in the HT group on day 6. (c) Bacterial correlation network in different temperature groups on day 6, with colors indicating the two clustering groups in Fig. 4, with Bacillus and Pediococcus highlighted. (d) Linear regression of the maximum ratio of the absolute content of Pediococcus to Bacillus, with RBacillus:Pediococcus = Pediococcus:Bacillus if Pediococcus is more abundant, and RBacillus:Pediococcus = Bacillus:Pediococcus if Bacillus is more abundant, relative to the fermentation temperature of high-temperature Daqu, with a 95% confidence interval. (e) Temperature differentiation in high-temperature Daqu based on the absolute content ratio of Pediococcus to Bacillus. Data are expressed as mean values with a 95% confidence interval. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 6. Heat Production of Pediococcus and Bacillus Strains at Various Temperatures. (a) Heat production power of two Pediococcus and four Bacillus strains at 25 °C. (b) Heat production power of two Pediococcus and four Bacillus strains at 37 °C. (c) Heat production power of two Pediococcus and four Bacillus strains at 45 °C. (d) Total heat production of six strains consisting of Pediococcus and Bacillus at 25 °C. (e) Total heat production of six strains consisting of Pediococcus and Bacillus at 37 °C. (f) Total heat production of six strains consisting of Pediococcus and Bacillus at 45 °C. Data are presented as averages.
Fig. 7. Thermogenic Power of Pediococcus and Bacillus Mixed Cultures Under Simulated Solid-state Fermentation Conditions. (a) Heat production power and total heat production of mixed Pediococcus and Bacillus cultures at 25 °C. (b) Heat production power and total heat production of mixed Pediococcus and Bacillus cultures at 45 °C. Data are expressed as averages.
https://doi.org/10.1016/j.fbio.2024.105457
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