To explore the effects of microbial community changes on the key flavor substances in base Baijiu, this study analyzed the microbiome of the pre-pit fermentation grains using high-throughput sequencing technology and determined the flavor substances of the base Baijiu by GC-FID. The results showed the microbial community changed dynamically between the different rounds, as well as bacteria and fungi displayed different succession patterns. Next, the variations of skeletal flavor substances in the base Baijiu were analyzed by multiomics, and it was found that alcohols, acids, and esters were the most abundant, accounting for 88.16–98.87% of the total flavor substances, and decreased with the increase of the rounds. By calculating the Spearman coefficient, it was found that microorganisms such as Acinetobacter, Oceanobacillus, Saccharomyces, and Byssochlamys were significantly correlated with the n-Propano and 2,3-Butanediol and other components in the base Baijiu. Finally, 15 flavor substances such as Acetaldehyde, Propionaldehyde, and Isobutyraldehyde were identified as key substances by OAV analysis. This study is the first to reveal the potential association between the microbial community of pre-pit fermentation grains and flavor of base Baijiu and has the benefit of improving the quality of base Baijiu.

Antibody stability and affinity are two important features of its applications in therapy and diagnosis. Antibody display technologies such as yeast and bacterial displays have been successfully used for improving both affinity and stability. Although mammalian cell display has also been utilized for maturing antibody affinity, it has not been applied for improving antibody stability. Previously, we developed a Chinese hamster ovary (CHO) cell display platform in which activation-induced cytidine deaminase (AID) was used to induce antibody mutation, and antibody affinity was successfully matured using the platform. In the current study, we developed thermo-resistant (TR) CHO cells for the purpose of maturing both antibody stability and affinity. We cultured TR CHO cells displaying an antibody mutant library and labeled them at temperatures above 41 °C, enriching cells that displayed antibody mutants with both the highest affinities and the highest display levels. To evaluate our system, we chose three antibodies to improve their affinities and stabilities. We succeeded in simultaneously improving both affinities and stabilities of all three antibodies. Of note, we obtained an anti-TNFα antibody mutant with a Tm (dissolution temperature) value 12 °C higher and affinity 160-fold greater than the parent antibody after two rounds of cell proliferation and flow cytometric sorting. By using CHO cells with its advantages in protein folding, post-translational modifications, and code usage, this procedure is likely to be widely used in maturing antibodies and other proteins in the future.

In view of the technical bottleneck of microbial dynamic monitoring during the solid-state fermentation of traditional Baijiu, this study introduced green fluorescent protein (GFP) labeling technology into the dominant Saccharomyces cerevisiae of Jiang-flavored Baijiu to construct the chromosomal integration engineering strain named FSC01. By designing an integrated recombinant plasmid containing the GFP gene and the geneticmycin resistance gene, an engineered strain that stably expresses fluorescent proteins was obtained by electroconversion. Flow cytometry verification showed that FSC01 showed excellent linear responses in the pure microbial system (R² = 0.998) and the complex matrix of Baijiu jiupei (R² = 0.981), with a detection limit of 10² cells/mL, and the detection cycle was shortened to 10 min. Solid-state fermentation simulation experiments show that the inoculation volume of FSC01 of 10⁵ cells/kg can not only ensure the effective identification of fluorescence signals, but also does not significantly interfere with the growth and growth patterns of the original yeast (p > 0.05), which is highly consistent with the results of the traditional plate counting method. Dynamic monitoring shows that Saccharomyces cerevisiae during fermentation presents a typical succession pattern of “increase first and then decrease”, reaching a peak on the 7th day (1.2 × 10⁷ cells/g), which is positively correlated with the base alcohol yield rate (26.7%). Compared with metagenomic (72 h) and PMA-qPCR (4 h) methods, this technology breaks through the limitations of specificity and timeliness of live bacteria detection, and provides a single-cell-level dynamic analysis tool for the digitization of traditional brewing processes. In the future, it will be expanded to monitor key functional microorganisms such as lactic acid bacteria through a multi-color fluorescent labeling system, and optimized pretreatment to eliminate starch granule interference, and promote the in-depth application of synthetic biology technology in the traditional fermentation industry.