International Journal of Food Microbiology Exploring the Impacts Of
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International Journal of Food Microbiology 297 (2019) 32–40 Contents lists available at ScienceDirect International Journal of Food Microbiology journal homepage: www.elsevier.com/locate/ijfoodmicro Exploring the impacts of raw materials and environments on the microbiota T in Chinese Daqu starter ⁎ Hai Dua,1, Xueshan Wanga,1, Yuhang Zhangb, Yan Xua, a Key Laboratory of Industrial Biotechnology of Ministry of Education, Synergetic Innovation Center of Food Safety and Nutrition, School of Biotechnology, Jiangnan University, 1800 Lihu Avenue, Wuxi, Jiangsu 214122, People's Republic of China b Hengshui Laobaigan Distillery Group, Hengshui 053000, Hebei, People's Republic of China ARTICLE INFO ABSTRACT Keywords: Many traditional fermented foods and beverages in both eastern and western countries are produced with the Microbial source tracking addition of starter cultures. Daqu is the undefined starter used for Chinese liquor, which contributed many Environmental microbiota fermentation functional fungal and bacterial communities to liquor fermentation process. However, the sources Solid-state fermentation (SSF) of these microbial communities and how these microorganisms formed in Daqu are still unclear. In this study, Chinese Daqu starter high-throughput sequencing combined with microbial source tracking analysis were applied to analyze the High-throughput sequencing sources of the microbial communities in Daqu. We found fungal communities in Daqu were mainly originated from Daqu making environments (mainly tools and indoor ground), including Saccharomycopsis fibuligera, Pichia kudriavzevii, Rhizopus oryzae, Sterigmatomyces elviae, Aspergillus flavus/oryzae, Hyphopichia burtonii and Lichtheimia corymbifera. Meanwhile, most of bacterial communities in Daqu were from raw materials, including Gammaproteobacteria, Alphaproteobacteria and Bacilli. During Daqu-making process, the abundance of Gammaproteobacteria and Alphaproteobacteria that were not beneficial to liquor fermentation declined, but the abundance of the fermentation functional yeasts and Bacilli increased. Moreover, network analysis showed the bacteria in Daqu might be the drivers for the microbial succession during the Daqu-making process. This study shows that the Daqu production technology is a good way to screen fermentation functional microorganisms from complex environmental microbial communities. 1. Introduction for many traditional oriental fermented foods and beverages, for ex- ample, liquor, rice wine, sake, vinegar and soy sauce (Jin et al., 2017). Fermented foods and beverages are widely consumed both in Typically, Daqu is an important saccharifying and fermenting agent for eastern (Chinese liquor and kimchi) and western (bread and cheese) traditional vinegar (Li et al., 2016b) and liquor (Zheng et al., 2014) in countries (Alfonzo et al., 2017; Jung et al., 2012; Wolfe et al., 2014; China. Our previous studies have showed that Daqu contributes Zheng et al., 2014). Many fermented foods and beverages are produced 61.06–80.00% of fungi during Chinese light-flavor liquor fermentation, with the addition of defined or undefined starter cultures. Defined mainly Pichia and Saccharomycopsis (Wang et al., 2018). Pichia is the starter cultures have often replaced traditional undefined cultures due major fermentation functional fungus during liquor fermentation, to their superior performance and reliability (Parente et al., 2016). which can utilized sucrose and glucose to produce various aromatic However, undefined starters are still used in the manufacture ofmany compounds, including ethanol, ethyl acetate and 4‑hydroxy‑2‑butanon traditional fermented foods and beverages, such as cheeses (Parente, (Li et al., 2016a; Li et al., 2011). Saccharomycopsis is known to produce 2006), kombucha (Marsh et al., 2014) and Chinese liquor (Zheng et al., extracellular proteolytic and saccharolytic enzymes with high activities 2014). (Huang et al., 2017; Li et al., 2017). However, where the microbial Daqu, an undefined starter culture, is one kind of jiuqu (a sortof communities in Daqu originated from and how these microorganisms equivalence of Koji) (Zhu and Tramper, 2013). Daqu can provide di- enriched in Daqu are unclear. verse microorganisms, which can secrete diverse enzymes, such as The production of Daqu is a traditional spontaneous solid-state amylases, proteinases, cellulases, and phytases. Similar starters are used fermentation (SSF) process in an open-work environment (Huang et al., ⁎ Corresponding author. E-mail address: [email protected] (Y. Xu). 1 These authors contributed equally to this work. https://doi.org/10.1016/j.ijfoodmicro.2019.02.020 Received 14 November 2018; Received in revised form 26 February 2019; Accepted 27 February 2019 Available online 28 February 2019 0168-1605/ © 2019 Elsevier B.V. All rights reserved. H. Du, et al. International Journal of Food Microbiology 297 (2019) 32–40 2017). During fermentation, the non-autoclaved raw materials (wheat) between 08:00–12:00 am for three days at the beginning of Daqu- will be exposed to many environments (such as air, ground and making process. The PBS solutions were filtered through a 0.22 μm equipment surface) on its journey from raw materials to mature Daqu cellulose nitrate filter (Solarbio, Beijing, China) to capture the aerosol (Li, et al., 2016). Thus, both the raw materials and the processing en- samples. The other environmental samples [tools (grinder and mold), vironments act as important sources for Daqu microbiota. Therefore, indoor ground and outdoor ground samples] were collected with sterile study on the microbiota in raw materials and environments is necessary degreasing cotton pre-moistened with sterile 0.1 M PBS. Degreasing for understanding the microbial ecosystem of Daqu, and is critical to cotton were rubbed across the tools and ground surface (1.00 m2). control and rationalize the Daqu fermentation process. Finally, all 21 samples (triplicate mature Daqu, new Daqu, raw mate- Several research groups have reported the microbial community rials, tools, air, indoor ground and outdoor ground samples) were compositions in low-temperature Daqu (Li et al., 2013; Zheng et al., transferred into lab on ice and stored at −80 °C until DNA extraction. 2014), medium-temperature Daqu (Zhang et al., 2014) and high-tem- perature Daqu (Su et al., 2015; Xiong et al., 2014). Previous study 2.2. Total DNA extraction, amplification and sequencing showed that bacterial communities in low-temperature Daqu are dominated by Firmicutes and Actinobacteria, and nearly all of the We isolated the total DNA via the EZNA™ (Easy Nucleic Acid fungal communities are Pichia kudriavzevii, a member of Sacchar- Isolation) Soil DNA Kit (Omega bio-tek; Norcross, GA) according to the omycetaceae (Li et al., 2013). Metatranscriptomics has been used to manufacturer protocol. For bacteria, the universal primer sets F338 and explore the fermentation functional microbial communities in medium- barcode-R806 were used to amplify the V3-V4 hypervariable region of temperature Daqu, and indicated fungi are the most active community the 16S rRNA gene (Soergel et al., 2012). For fungi, primers ITS3 and members (Huang et al., 2017). Moreover, Xiong et al. showed that the ITS4 were used to amplify the internal transcribed spacer (ITS) region microbes in the high-temperature Daqu were mainly thermotolerant (Hertz et al., 2016). PCR products were purified and carefully assessed and thermophilic microbes (Xiong et al., 2014). However, to our via Thermo Scientific NanoDrop 8000 UV–Vis Spectrophotometer knowledge, only Liu et al. (Liu et al., 2010) tried to analyze the mi- (NanoDrop Technologies, Wilmington, DE). Then the barcoded PCR crobial community of wheat (raw materials) based on culture method, products were sequenced via a Miseq Benchtop Sequencer for 250 bp and indicated the strains isolated from wheat were the same with those pair-end sequencing (2 × 250 bp; Illumina, San Diego, CA). isolated from Daqu. Nevertheless, the origins of the microbial com- We processed all the raw sequences generated via Qiime (v1.8.0) munities and how these microorganisms formed in Daqu has seldom (Caporaso et al., 2010). In brief, the raw sequences were quality been investigated. trimmed, the sequences with quality scores < 30 were trimmed, and In this study, to better understand the origins of microbiota and how only the sequences over 200 bp in length were chosen for further ana- these microorganisms formed in Daqu, high throughput sequencing was lysis. After that, the sequences that had non-assigned tags, had N base, applied to analyze the microbial community structure in Daqu, raw or did not perfectly match the PCR primer were removed (Caporaso materials and environments during Daqu fermentation. Microbial et al., 2010). We removed the chimera sequences via the Uchime al- source tracking was further applied to analyze the origins of microbiota gorithm (Edgar et al., 2011). Then a distance matrix was calculated in Daqu. Network analysis was used to analyze the interactions among from the aligned sequences, and OTUs were clustered with a 97% the microorganisms in Daqu. This study provides new insights into identity threshold by Qiime's uclust pipeline (Edgar, 2010). Before where the microbial communities in Daqu originated from and how the further analysis, singleton OTUs were removed. Then the representative microbial community structure in Daqu formed. sequence from each clustered OTU was aligned to the Greengenes da- tabase (v13.8) (DeSantis et al.,