## 4 Discussion  
The multi-omics approach by DNA-based metagenomics coupled with metabolomics was effective in revealing the mechanisms of traditional fermentation [20; 21]. However, the microbial community from the metagenomic and metatranscriptomic sequencing varied significantly [22; 23]. Metotranscriptomic analysis can help us to find the active functional microbiota [11; 24]. Based on the above considerations, integrated metatranscriptomics, and metabolomics analysis were adopted in NLS fermentation, helping to explore the metabolite profiles and the contributed active functional microbiota for flavor generation. Figure 7: Correlation analysis between microbiota with VIP \(>\) 1 and volatile compounds by O2 PLS-DA model. (**A**) Significantly correlated network between the important genera with VIP \(>\) 1 and the top 20 volatile compounds. (**B**) Significant correlated network between the important species with VIP \(>\) 1 and the top 20 volatile compounds. Only strong correlations (\(\,\mathrm{i}\,\mathrm{r}\mathrm{o}\mathrm{h}\mathrm{o}\mathrm{l}\)\(>\) 0.8, \(\,p\)\(<\) 0.05)) were displayed. Yellow and grey nodes represent the compounds and t microbiota, respectively. Metabolites from the fermented grains contribute to baijiu flavor generation, and they are the precursors or the final substances [20; 25]. In order to comprehensively understand the metabolite profiles of NLS fermentation, three detection approaches, including LC-MS, GC-MS, and HS-SPME-GC-MS, were applied. In LC-MS detection, 395 metabolites were identified, and the number of polar water-soluble metabolites was far more than the 54 compounds reported in other LFB fermentation [8]. Among all the detected compounds, the concentrations of all alcohols and alditols other than 1-hexadecanol were increased with the fermentation. A total of 39 amino acids displayed a similar pattern with alcohols. However, the concentrations of the other 10 amino acids were decreased from days 0 to 28. The concentration of most aldehydes, which contributed to flavor generation, exhibited an increased pattern with fermentation [7; 26]. At the early stage of fermentation, carbohydrates and peptides were degraded to small molecular sugars, short peptides, or amino acids, which made the concentration of most sugars decrease until the end of fermentation. However, the contents of some sugars, including glucose, increased to a higher level from 0 to 28 days of fermentation, which might regulate the microbial metabolic diversity in baijiu fermentation [27]. The contents of 58 organic acids, including lactic acid and linoleic acid, were increased with fermentation, which is consistent with the previous reports [28]. Meanwhile, some organic acids undergo esterification to form esters, which could endow mild and pleasant flavors to baijiu [29]. However, the abundances of the other 29 organic acids decreased with the fermentation process, indicating the content changes in organic acids showed a complicated distribution. For 83 metabolites detected in GC-MS, they contained 2 alcohols, 12 sugars, 31 organic acids, 5 alditols, 19 amino acids, and 14 other compounds according to the compound's structure. A total of 19 amino acids and 2 alcohols all exhibited an increased pattern with the fermentation, indicating they were rich in the final products and contributed to flavor generation. The number of esters accounted for the highest proportion among all compounds detected in HS-SPME-GC-MS. Ethyl acetate, ethyl lactate, ethyl acrylate, ethyl decanoate, ethyl oleate, and ethyl laurate were dominant aromatic substances in NLS fermentation, and their contents and proportions endowed the unique flavor of baijiu [30; 31; 32; 33; 34; 35; 36; 37; 38; 39]. Ethyl acetate had a high odor threshold value (32.6 mg/L), and the aromatic contribution was not remarkable [2]. However, ethyl acetate, with the highest production, could give a refreshing fragrance.