Identification of Core Regulatory Genes and Metabolic Pathways for the n-Propanol Synthesis in Saccharomyces cerevisiae

RT-qPCR based quantitative analysis of ARO and ADH genes in Saccharomyces cerevisiae and Metschnikowia pulcherrima strains growth white grape juice

BACKGROUND

Yeast biosynthesizes fusel alcohols in fermentation through amino acid catabolism via the Ehrlich pathway. ARO8 and ARO9 genes are involved in the first step of the Ehrlich pathway, while ADH2 and ADH5 genes are involved in the last step. In this study, we describe RT-qPCR methods to determine the gene expression level of genes (ARO8, ARO9, ADH2, ADH5) found in Saccharomyces cerevisiae (Sc) and Metschnikowia pulcherrima (Mp) strains growth pasteurized white grape juice.

METHODS AND RESULTS

We used RNA extraction and cDNA synthesis protocols. The RT-qPCR efficiency of primer pairs was evaluated by generating a standard curve through serial dilution of yeast-derived cDNA. Method performance criteria were determined for each RT-qPCR assay. Then, we evaluated the gene expression levels of the four genes in all samples. RNA extraction and cDNA synthesis from yeast samples demonstrated the method's capability to generate high-yield, high-purity nucleic acids, supporting further RT-qPCR analysis. The highest normalized gene expression levels of ARO8 and ARO9 were observed in SC1, SC4, and SC5 samples. No significant difference in ADH2 gene expression among Mp strains was observed during the examination of ADH2 and ADH5 genes (p < 0.05). We observed no expression of the ADH5 gene in Mp strains except MP6 strain. The expression of ADH2 and ADH5 genes was higher in Sc strains compared to Mp strains.

CONCLUSIONS

The results suggest that the proposed RT-qPCR methods can measure gene expression of ARO8, ARO9, ADH2, and ADH5 in Sc and Mp strains growing in pasteurized white grape juice.

Exploring the impact of initial moisture content on microbial community and flavor generation in Xiaoqu baijiu fermentation

Moisture is essential in microbiota succession and flavor formation during baijiu fermentation. However, it remains unknown how moisture content affects microbiota, metabolism, and their relationship. Here, we compared the difference in volatiles, microbiota characteristics, and potential functions with different initial moisture contents (50 %, 55 %, 60 %, 65 %, 70 %). Results showed that the ratio of ethyl acetate to ethyl lactate and total volatile compounds content increased as the moisture content was elevated from 50 % to 70 %. As increasing moisture content, fermentation system microbiota dominated by Lactobacillus was formed more rapidly. Lactobacillus, Dekkera, and Pediococcus were positively correlated with moisture, promoting the production of propanol, acetic acid, butyric acid, and 2-butanol. The complexity and stability of ecological networks enhanced as moisture content increased (R2 = 0.94, P = 0.004). Our study revealed that moisture-drive microbiota was a critical contributor to flavor formation, providing the theoretical basis for moisture control to regulate flavor compounds.

Comparing the differences of physicochemical properties and volatiles in semi-dry Hakka rice wine and traditional sweet rice wine via HPLC, GC-MS and E-tongue analysis

This study aimed to explore effects of indica rice addition, rice soaking time and rice soup addition on total sugar and alcohol content of semi-dry Hakka rice wine (HRW) and compare its difference in physicochemical properties and volatiles with traditional sweet rice wine (TSRW) via HPLC, GC-MS and E-tongue. The optimal fermentation conditions of semi-dry HRW were 50 % indica rice addition, 12 h rice soaking time and 85 % rice soup addition. The total sugar (16.13 mg/mL) of semi-dry HRW was significantly lower than that of TSRW (135.79 mg/mL), especially the trehalose, glucose, sucrose and maltose. Its alcohol content was significantly higher than that of TSRW. There were significant differences in volatile components between semi-dry HRW and TSRW, especially esters, alcohols and ketones, but no significant differences in organic acids and amino acids. Results obtained could provide reference data for improving the fermentation process and quality of semi-dry HRW.

Biosynthesis pathways of expanding carbon chains for producing advanced biofuels

Because the thermodynamic property is closer to gasoline, advanced biofuels (C ≥ 6) are appealing for replacing non-renewable fossil fuels using biosynthesis method that has presented a promising approach. Synthesizing advanced biofuels (C ≥ 6), in general, requires the expansion of carbon chains from three carbon atoms to more than six carbon atoms. Despite some specific biosynthesis pathways that have been developed in recent years, adequate summary is still lacking on how to obtain an effective metabolic pathway. Review of biosynthesis pathways for expanding carbon chains will be conducive to selecting, optimizing and discovering novel synthetic route to obtain new advanced biofuels. Herein, we first highlighted challenges on expanding carbon chains, followed by presentation of two biosynthesis strategies and review of three different types of biosynthesis pathways of carbon chain expansion for synthesizing advanced biofuels. Finally, we provided an outlook for the introduction of gene-editing technology in the development of new biosynthesis pathways of carbon chain expansion.

Control of N-Propanol Production in Simulated Liquid State Fermentation of Chinese Baijiu by Response Surface Methodology

N-propanol is a vital flavor compound of Chinese baijiu, and the proper n-propanol contents contribute to the rich flavor of Chinese baijiu. However, the excessive content of n-propanol in liquor will reduce the drinking comfort. Based on the Box–Behnken design principle, the response surface test was used to optimize the factors affecting the production of n-propanol in a simulated liquid state fermentation of Chinese baijiu, and the best combination of factors to reduce n-propanol content was determined. Results showed that the content ratio of additional glucose to threonine and temperature had a significant effect on the production of n-propanol (p = 0.0009 < 0.01 and p = 0.0389 < 0.05, respectively). The best combination of fermentation parameters obtained was: the ratio of additional glucose to threonine content was 6:4, the temperature was 32 °C, and the initial pH was 4.40. Under these conditions, the production of n-propanol was 53.84 ± 0.12 mg/L, which was close to the theoretical value. Thus, the fermentation parameter model obtained through response surface optimization is reliable and can provide technical guidance for regulating the production of n-propanol and realizing high-quality baijiu brewing.