Non-gene-editing microbiome engineering of spontaneous food fermentation microbiota-Limitation control, design control, and integration

Non-gene-editing microbiome engineering (NgeME) is the rational design and control of natural microbial consortia to perform desired functions. Traditional NgeME approaches use selected environmental variables to force natural microbial consortia to perform the desired functions. Spontaneous food fermentation, the oldest kind of traditional NgeME, transforms foods into various fermented products using natural microbial networks. In traditional NgeME, spontaneous food fermentation microbiotas (SFFMs) are typically formed and controlled manually by the establishment of limiting factors in small batches with little mechanization. However, limitation control generally leads to trade-offs between efficiency and the quality of fermentation. Modern NgeME approaches based on synthetic microbial ecology have been developed using designed microbial communities to explore assembly mechanisms and target functional enhancement of SFFMs. This has greatly improved our understanding of microbiota control, but such approaches still have shortcomings compared to traditional NgeME. Here, we comprehensively describe research on mechanisms and control strategies for SFFMs based on traditional and modern NgeME. We discuss the ecological and engineering principles of the two approaches to enhance the understanding of how best to control SFFM. We also review recent applied and theoretical research on modern NgeME and propose an integrated in vitro synthetic microbiota model to bridge gaps between limitation control and design control for SFFM.

Challenges and perspectives of quantitative microbiome profiling in food fermentations

Spontaneously fermented foods are consumed and appreciated for thousands of years although they are usually produced with fluctuated productivity and quality, potentially threatening both food safety and food security. To guarantee consistent fermentation productivity and quality, it is essential to control the complex microbiota, the most crucial factor in food fermentations. The prerequisite for the control is to comprehensively understand the structure and function of the microbiota. How to quantify the actual microbiota is of paramount importance. Among various microbial quantitative methods evolved, quantitative microbiome profiling, namely to quantify all microbial taxa by absolute abundance, is the best method to understand the complex microbiota, although it is still at its pioneering stage for food fermentations. Here, we provide an overview of microbial quantitative methods, including the development from conventional methods to the advanced quantitative microbiome profiling, and the application examples of these methods. Moreover, we address potential challenges and perspectives of quantitative microbiome profiling methods, as well as future research needs for the ultimate goal of rational and optimal control of microbiota in spontaneous food fermentations. Our review can serve as reference for the traditional food fermentation sector for stable fermentation productivity, quality and safety.

Dynamic and Functional Characteristics of Predominant Species in Industrial Paocai as Revealed by Combined DGGE and Metagenomic Sequencing

The microbial community during the fermentation of industrial paocai, a lactic acid fermented vegetable food, was investigated via combined denaturing gradient gel electrophoresis (DGGE) and metagenomic sequencing. Firmicutes and Proteobacteria were identified as the dominant phyla during the fermentation. DGGE results of the bacterial community analysis showed that many genera were observed during the fermentation of industrial paocai, but the same predominant genus and species were observed: Lactobacillus and Lactobacillus (L.) alimentarius/L. paralimentarius. The abundance of L. alimentarius/L. paralimentarius increased fast during the initial stage of fermentation and approximately remained constant during the later stage. Metagenomic sequencing was used to finally identify the predominant species and their genetic functions. Metabolism was the primary functions of the microbial community in industrial paocai fermentation, including carbohydrate metabolism (CM), overview (OV), amino acid metabolism (AAM), nucleotide metabolism (NM), energy metabolism (EM), etc. The predominant species L. alimentarius and L. paralimentarius were involved in plenty of pathways in metabolism and played different roles in the metabolism of carbohydrate, amino acid, lipid to form flavor compounds during industrial paocai fermentation. This study provided valuable information about the predominant species in industrial paocai and its functional properties, which could enable us to advance our understanding of the fermentation mechanism during fermentation of industrial paocai. Our results will advance the understanding of the microbial roles in the industrial paocai fermentation and provide a theoretical basis for improving the quality of industrial paocai products.