Construction of Synthetic Microbiota for Reproducible Flavor Compound Metabolism in Chinese Light-Aroma-Type Liquor Produced by Solid-State Fermentation

Abstract

Natural microbiota plays an essential role in flavor compounds used in traditional food fermentation; however, the fluctuation in natural microbiota results in inconsistency in food quality. Thus, it is critical to reveal the core microbiota for flavor compound production and to construct a synthetic core microbiota for use in constant food fermentation. Here, we reveal the core microbiota based on their flavor production and cooccurrence performance, using Chinese light-aroma-type liquor as a model system. Five genera, Lactobacillus, Saccharomyces, Pichia, Geotrichum, and Candida, were identified to be the core microbiota. The synthetic core microbiota of these five genera presented a reproducible dynamic profile similar to that in the natural microbiota. A Monte Carlo test showed that the effects of five environmental factors (lactic acid, ethanol, and acetic acid contents, moisture, and pH) on the synthetic microbiota distribution were highly significant (P Ͻ 0.01), similar to those effects on a natural fermentation system. In addition, 77.27% of the flavor compounds produced by the synthetic core microbiota showed a similar dynamic profile ( Ͼ 0) with that in the natural liquor fermentation process, and the flavor profile presented a similar composition. It indicated that the synthetic core microbiota is efficient for reproducible flavor metabolism. This work established a method for identifying core microbiota and constructing a synthetic microbiota for reproducible flavor compounds. This work is of great significance for the tractable and constant production of various fermented foods. IMPORTANCE The transformation from natural fermentation to synthetic fermentation is essential in constructing a constant food fermentation process, which is the premise for stably making high-quality food. According to flavor-producing and cooccurring functions in dominant microbes, we provided a system-level approach to identify the core microbiota in Chinese light-aroma-type liquor fermentation. In addition, we successfully constructed a synthetic core microbiota to simulate the microbial community succession and flavor compound production in the in vitro system. The constructed synthetic core microbiota could not only facilitate a mechanistic understanding of the structure and function of the microbiota but also be beneficial for constructing a tractable and reproducible food fermentation process.

Physicochemical Factors Affecting Microbiota Dynamics During Traditional Solid-State Fermentation of Chinese Strong-Flavor Baijiu

“…However, starch and moisture had significant effects only on fungi composition during the TCSSF process. Previous studies also revealed that the performances of microorganisms were associated with complex microbial interactions (Liu et al, 2017;Wang et al, 2019), whereas microbial interactions were associated with microbial succession and diversity (Tan et al, 2019). From a network perspective, TCSSF possessed relatively stable microbiomes compared with SCSSF, which was probably due to the milder physicochemical conditions.…”

Temperature-Induced Annual Variation in Microbial Community Changes and Resulting Metabolome Shifts in a Controlled Fermentation System

“…Using Uclust (V. 1.2.22), we clustered the trimmed sequences into operational taxonomic units (OTUs) with 97% sequence similarity ( 69 ). Databases EzBioCloud ( www.ezbiocloud.net , a public database of bacterial sequences) and Central Bureau of Fungal Cultures (CBS-KNAW, www.wi.knaw.nl , a public database of fungal sequences) were used for sequence alignment of bacterial 16S rRNA genes and fungal ITS2 regions, respectively ( 27 ).…”

“…Five-gram subsamples were added to 10 ml ddH 2 O, placed in an ultrasonic cleaner (AS30600B; Autoscience, Tianjin, China) for 30 min, and centrifuged at 8,000 × g for 10 min. After filtering using an 0.2-μm-pore-size filter, the filtrate was used to analyze metabolite concentrations ( 27 ). Metabolites were detected using gas chromatography-mass spectrometry (Agilent 6890N GC system and Agilent 5975 mass selective detector; Agilent, Santa Clara, CA) with condition details based on a previous study ( 65 ).…”

“…Even individual microorganisms adapt their functioning in response to changes in their surroundings through differential gene expression, resulting in a change of their expressed metabolites ( 23 , 24 ). Many of these microbe-derived metabolites are used in a variety of ways for human purposes ( 25 ), such as to produce antibiotics ( 26 ), ethanol ( 27 ), and organic acids ( 28 ). Yet, we are often limited in our understanding, especially in complicated community settings, of how changes in microbial composition translate to functional changes that are visible in the metabolome profile.…”

Functional Microbiota for Polypeptide Degradation during Hypertonic Moromi-Fermentation of Pixian Broad Bean Paste

“…Amplicons were posted to Beijing Auwigene Tech. Ltd. (Beijing, China) for high-throughput sequencing by using Miseq Benchtop Sequencer (Illumina, San Diego, CA, USA) for 2 × 300 bp pair-end sequencing [24].…”