## 5 Conclusions  
Herein, we presented an integrated metatranscriptomic and untargeted metabolomic analysis in NLS fermentation. Not only the metabolite profiles but also the contributed active functional microbiota for key volatile flavors was comprehensively studied based on the O2 PLS-DA model. A total of 395, 83, and 181 metabolites were detected in LC-MS, GC-MS, and HS-SPME-GC-MS, respectively. There were 73 and 130 strong correlations between microbes with VIP \(>\) 1.0 and the top 20 volatile flavors comprehensively analyzed at the genus and species level, respectively. The correlation analysis revealed that bacterial genera of _Streptococcus_, _Lactobacillus_, _Pediococcus_, _Campylobacter_, _Yersinia_, and _Weissella_, and fungal genera of _Talamomyces_, _Apergillus_, _Mixia_, _Rhizophagus_, and _Gloeophyllum_ were the active functional microbiota for the flavor generation. It was found that different _Lactobacillus_ species performed unique functions during NLS fermentation, suggesting the succession of _Lactobacillus_ with diversified functions is vital for NLS flavor generation. Our results further improved the understanding of the mechanism in NLS fermentation, which could be useful for improving the LFB quality.  
**Supplementary Materials:** The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/foods12224140/s1](https://www.mdpi.com/article/10.3390/foods12224140/s1)]([https://www.mdpi.com/article/10.3390/foods12224140/s1](https://www.mdpi.com/article/10.3390/foods12224140/s1)), Table S1: Numbers of genera and species in fermented grains based on the metatranscriptomic sequencing; Table S2: 395 polar compounds identified by LC-MS during NLS fermentation; Table S3: 83 compounds identified by derivative GC-MS during NLS fermentation; Table S4: 181 VOCs identified by HS-SPME-GC-MS during NLS fermentation; Figure S1: Fermentation time points and methods of sampling for untargeted metabolomics; Figure S2: Distribution of microorganisms at the superkingdom level; Figure S3: Hierarchical cluster analysis of compounds during NLS fermentation based on the LC-MS detection; Figure S4: Hierarchical cluster analysis of compounds during NLS fermentation based on the GC-MS detection; Figure S5: Hierarchical cluster analysis of compounds during NLS fermentation based on the SPME-GC-MS detection; Figure S6: Correlation analysis between microbiota and volatile compounds by O2 PLSDA model.  
**Author Contributions:** Conceptualization, Y.P., Y.W., J.W. and G.L.; methodology, W.H.; software, Q.L.; validation, Y.P., Y.W. and Q.L.; formal analysis, S.Z. and Y.W.; investigation, W.H.; resources, W.H.; data curation, C.D.; writing--original draft preparation, Y.P. and Y.W.; writing--review and editing, Y.P., Y.W., W.H., S.Z., C.D., Q.L., J.W. and G.L. visualization, Q.L.; supervision, J.W. and G.L.; project administration, Y.P. and Y.W.; funding acquisition, Y.P. and G.L. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the National Key Research and Development Program (grant no. 2021 YFC2100600) and the National Natural Science Foundation of China (grant no. 31770056).  
**Data Availability Statement:** The metatranscriptomic data presented in this work can be found in the repository NCBI SRA under accession number (PRJNA773513). Metabolomic data used to support the findings of this study can be made available by the corresponding author upon request.  
**Acknowledgments:** We appreciate [PERSON] from LC-Bio Technology Company Limited for the help in bioinformatics.  
Conflicts of Interest: Authors [PERSON], [PERSON], [PERSON] and [PERSON] were employed by the company Beijing Shunxin Agriculture Company Limited. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.