甘肃农业大学：食品科学与工程学院（文献讲义）High-throughput sequencing approach to characterize dynamic changes of the fungal and bacterial communities during the production of sufu, a traditional Chinese fermented soybean food.pdf_大学文库

Contents lists available at ScienceDirect Food Microbiology journal homepage: www.elsevier.com/locate/fm High-throughput sequencing approach to characterize dynamic changes of the fungal and bacterial communities during the production of sufu, a traditional Chinese fermented soybean food Dandan Xua,b , Peng Wanga,b , Xin Zhanga , Jian Zhanga,b , Yong Suna , Lihua Gaoa , Wenping Wanga,∗ a Beijing Academy of Food Sciences, 100068, Beijing, China b Beijing Food Brewing Institute, 100050, Beijing, China ARTICLE INFO Keywords: Sufu Fermentation Fungal communities Bacterial communities High-throughput sequencing ABSTRACT Red sufu is a traditional food produced by the fermentation of soybean. In this study, sufu samples were periodically collected during the whole fermentation to investigate the dynamic changes of fungal and bacterial communities using high-throughput sequencing technology. The overall process can be divided into pre- and post-fermentation. During post-fermentation, the pH value showed a gradual decrease over time while the amino nitrogen content increased. Trichosporon, Actinomucor and Cryptococcus were the main genera in pre-fermentation while Monascus and Aspergillus were dominant in post-fermentation. This huge shift in fungal composition was caused by process procedure of pouring dressing mixture. However, the bacterial composition was not greatly changed after pouring dressing mixture, the Acinetobacter and Enterobacter were the predominant genera throughout the whole process. Furthermore, Bacillus species were first detected after adding dressing mixture, but declined abruptly to a very low level (0.07%) by the end of the fermentation. Our work demonstrates the dynamic changes of physicochemical properties and microbial composition in every fermentation stage, the knowledge of which could potentially serve as a foundation for improving the safety and quality of sufu in the future. 1. Introduction Sufu is a soft, cheese-like traditional food produced by the microbial fermentation of soybean (Yang et al., 2014b). In China it has been widely consumed as an appetizer and a side dish since the Wei Dynasty (220–265 CE) (Chung et al., 2005). Since it is made from fermented tofu, which is a good protein and calcium source, sufu is known as a healthy and low cholesterol food of plant origin (Qiu et al., 2018). It is becoming increasingly popular in Asia because of its unique flavor and taste. On the basis of the different microbial starter culture, sufu can be classified into mould-fermented and bacteria-fermented (Han et al., 2004). The mould-fermented sufu is the most dominant type among all sufu types (Han et al., 2003). The red sufu is a typical mould-fermented sufu in China. It is manufactured by first cultivating a fungus such as Actinomucor, Mucor, or Rhizopus on the surface of tofu cubes to prepare the pehtze. The prepared pehtze is salted in water for about 5 days, during which time the pehtze absorbs salt. The high concentration of salt can inhibit the continued growth of mould and reduce the contamination of bacteria in the environment while imparting salty taste to the pehtze. Then the salt-pehtze were carefully placed in the sterilized glass bottle, the dressing mixture was subsequently poured into it. The salt-pehtze ripens in the dressing mixture in a time period of 3 months. Various enzymes secreted by the microorganisms decompose the raw materials into alcohols, aldehydes, organic acids, esters, and amino acids through a series of biochemical processes thereby imparting a pleasant taste. Until now, studies in sufu are mainly focused on its biochemical and physiological properties, antioxidant activity, safety assessment, volatile components etc. (Cai et al., 2016; Chen et al., 2012; Huang et al., 2011b; Ma et al., 2013b; Moy and Chou, 2010; Moy et al., 2012; Xia et al., 2014). It has been shown that the microbial community plays an important role during the long period of food fermentation (Song et al., 2017). However, studies investigating the microbial dynamic changes in the fermentation of sufu are limited. Yan et al. analyzed the mesophilic aerobic bacteria (TMAB), lactic acid bacteria (LAB), and fungal properties during sufu manufacturing using the flat colony counting method, and found that TMAB, LAB, and fungal counts were low in https://doi.org/10.1016/j.fm.2019.103340 Received 29 January 2019; Received in revised form 19 September 2019; Accepted 20 September 2019 ∗ Corresponding author. Beijing Academy of Food Sciences, No. 70. Yangqiao Road, Beijing, 100068, China. E-mail address: wwpsmn@163.com (W. Wang). Food Microbiology 86 (2020) 103340 Available online 21 September 2019 0740-0020/ © 2019 Elsevier Ltd. All rights reserved. T

tofu. After fermentation, an increased microbial count in the pehtze was observed. A significant decline in microbial count occurred after salting, and almost no fungal growth (< 1 log cfu/g) could be detected (Ma et al., 2013a). Feng et al. evaluated the bacterial flora during the ripening of Kedong sufu (a typical bacteria-fermented sufu) using polymerase chain reaction denaturing gradient gel electrophoresis (PCR-DGGE) and culturing methods. They found that Enterococcus avium, Enterococcus faecalis, and Staphylococcus carnosus were the dominant microflora throughout the fermentation of sufu (Feng et al., 2013). Since the results from other studies are only for microorganisms that can be easily cultivated, methods that rely on culture have been insufficient to fully understand the microbial population. PCR-DGGE is a common method for evaluating the composition of microorganisms, but it is time consuming and has limited ability to detect rare or uncultivable microorganisms (Hong et al., 2016). High-throughput sequencing has been widely used to characterize the composition of the microbial community of fermented food, such as wine, vinegar, soy sauce, etc. (Sulaiman et al., 2014; Tang et al., 2017; Wang et al., 2016). Based on this technology, the aims of this study were as follows: 1) investigate the dynamic changes of physicochemical properties and fungal structure during sufu fermentation and their correlation with process procedures, 2) identify the relative abundance and diversity of bacteria taxa in sufu samples, which is crucial for the flavor and security of fermented food. 2. Materials and methods 2.1. Sufu preparation and sample collection Red sufu samples were prepared and collected at the Wangzhihe Food Co. Ltd. A diagram of the production and sampling points with sample names are presented in Fig. 1. Simply, pehtze is prepared by inoculating Actinomucor elegans on the surface of tofu cubes, then salting the pehtze for about 5 days, and dispense the salt-pehtze into wide-mouthed glass bottles and ripens in the dressing mixture for a period of 3 months. The dressing mixture of red sufu mainly consists of red kojic rice (cooked rice inoculated with Monascus purpureus), edible alcohol, sugar, chiang (flour paste fermented by Aspergilus oryzae) and spices. Sufu samples were collected periodically at 9 different stages of fermentation: tofu (T), pehtze which inoculated with A. elegans for 24 h (A24), 48 h (A48), salt-pehtze (S), fermentation of sufu for 0 day (D0), 5 days (D5), 1 month (M1), 2 months (M2), 3 months (M3). Samples were collected from five independent batches and used as replicates. A total of 45 samples were transported into the lab on ice and stored at −80 °C until further use. 2.2. Physicochemical analysis Five grams of the sufu samples were homogenized with 50 mL of distilled water followed by pH measurements using a pH meter (Mettler Toledo). The amino nitrogen content and NaCl concentration were determined according to SB/T10170-2007 standard. Sufu samples (20 g) were boiled with distilled water (80 mL) with gentle stirring. Boiled sufu slurry was diluted to 200 mL with distilled water. The sufu solution was filtered with dry filter paper and then the filtrate was used to measure amino nitrogen content and NaCl concentration. 10 mL of the filtrate was mixed with 50 mL water and titrated to pH 8.2 with 0.05 mol/L NaOH and then 10 mL of 36% (w/v) formalin solution was added. The mixture was titrated to pH 9.2 with 0.05 mol/L NaOH. The volume of consumed NaOH for raising pH (from 8.2 to 9.2) was recorded to determine amino nitrogen content. To determine the NaCl concentration, 2 mL of the filtrate was mixed with 50 mL water and titrated with 0.100 mol/L AgNO3 using 5% (w/v) K2CrO4 solution (1 mL) as an indicator. The titration was terminated when the solution appeared orange. The content of reducing sugar was determined according to previous study (Van Waes et al., 1998). Samples from the same stage of the five independent batches were mixed for physicochemical analysis. All tests were carried out in triplicate. 2.3. DNA extraction Five grams of sufu samples were mixed with 25 mL 0.1 mol/L TrisHCl (pH 8.0), shaken well, and filtered through three layers of sterile gauze. The filtrate was centrifuged at 10,000×g for 20 min at 4 °C. The pellets were used for DNA extraction by GMO food DNA Extraction Kit (Tiangen, Beijing, China) following the manufacturer's protocol. The total DNA concentration and quality were checked using a NanoDrop 2000 (Thermo) spectrophotometer and agarose gel electrophoresis. 2.4. 16S rRNA gene amplicon sequencing and ITS amplicon sequencing Variable regions V3–V4 on microbial 16S rRNA gene of bacteria and the ITS2 region of fungi were amplified using PCR (95 °C for 3 min, followed by 30 cycles at 98 °C for 20 s, 58 °C for 15s, 72 °C for 20 s and a final extension at 72 °C for 5 min). The microbial 16S rRNA gene were amplified by forward primer F341 5′- ACTCCTACGGGRSGCAGCAG -3′ and reverse primer R806 5′- GGACTACVVGGGTATCTAATC -3′ (Klindworth et al., 2013). ITS2 were amplified with forward primer F2045 5′-GCATCGATGAAGAACGCAGC-3′ and reverse primer R2390 5′-TCCTCCGCTTATTGATATGC-3′ (Hirokazu et al., 2012). PCR reactions were performed in 30 μL mixture containing 15 μL of 2 × KAPA Fig. 1. The production diagram of sufu used in this study with the sampling points indicated. Tofu (T), pehtze which inoculated with A. elegans for 24 h (A24), 48 h (A48), salt-pehtze (S), fermentation of sufu for 0 day (D0), 5 days (D5), 1 month (M1), 2 months (M2), 3 months (M3). D. Xu, et al. Food Microbiology 86 (2020) 103340 2

Library Amplification ReadyMix, 1 μL of each primer (10 μmol/L), 10 ng of template DNA and ddH2O. PCR products were detected using 2% agarose gel electrophoresis, and then purified by AxyPrep DNA gel Extraction Kit (AXYGEN). Amplicon libraries were quantified using a Qubit 2.0 Fluorometer (Thermo Fisher Scientific). Amplicons were then sequenced using Illumina HiSeq PE250 at Realbio Genomics Institute (Shanghai, China). 2.5. Bioinformatics analysis The paired-end reads were assembled into longer tags after sequencing and then quality-filtered. Tags were restricted between 220 bp and 500 bp and the average Phred score of bases was not 3 ambiguous N. Bioinformatic analyses were performed using QIIME (v1.7.0) on the extracted high-quality sequences (Caporaso et al., 2010). First, the sequences were aligned using PyNAST (Caporaso et al., 2009) and clustered under 100% sequence identity using UCLUST (Edgar, 2010) to obtain the unique sequence set and clustered into operational taxonomic units (OTUs). Then these representative sequences were further classified into operational taxonomic units (OTUs) with a 97% similarity using UCLUST. Each representative sequence was assigned to a taxa by Ribosomal Database Project, (RDP, Release 11.5) (Cole et al., 2006) and Greengenes (Release 13.8) (DeSantis et al., 2006) to obtain the taxonomy information of phylum, class, order, family, genus and species. 2.6. Statistics analysis Differences in the relative abundances of taxonomic levels between samples were evaluated using the Mann-Whitney test. Values of P 7% from A24 to D5, but dramatically declined to 0.64% at M1. Meanwhile Lactococcus declined rapidly from M1 to M3. Streptococcus and Weissella were also the main genera during the pehtze stage, but they became less abundant in the following stages. Pseudomonas and Klebsiella were more abundant in the ripening fermentation stage than the pehtze stage. Bacillus was not detected during the pre-fermentation stage (A24, A48, and S). D. Xu, et al. Food Microbiology 86 (2020) 103340 3

However, it was spotted at D0 which increased significantly from D5 to M2. The abundance of Bacillus declined rapidly to an extremely low abundance (0.07%) at the end of the ripening fermentation stage (Fig. 5B). The Shannon index showed that the diversity of the bacterial communities increased slightly at D0, then showed no significant differences in M1 and M2, but declined in M3 (Supplementary Table S1), mainly because of the dominance of Acinetobacter. The structure of the bacterial communities in the samples from the 9 different stages was also compared using weighted and unweighted UniFrac PCoA. Although some overlap was presented in the score plots among the samples from the 9 stages, the data points were largely separated in both weighted (accounting for 35.12% and 18.35% of the total variance by the first 2 principal components (PC), respectively; Fig. S1A) and unweighted (accounting for 14.00% and 10.90% of the total variance by the first 2 PC, respectively; Fig. S1B) analyses. By weighted analysis, the samples from stage T was obviously separated from all the other stages, and only M3 was separated from the other stages. By unweighted analysis, the samples from stage T were also separated from all the other stages. Except stage T, M2 and M3 were significantly clustered separately and different from the other stages. A further multivariate ANOVA test showed significant differences in the bacterial communities from the 9 different stages based on the weighted (P < 0.05) UniFrac analysis (Fig. S2A). The M2 and M3 stages were significantly different from other stages. The pre-fermentation stage could significantly separate from the post-fermentation. For the unweighted (P < 0.05) UniFrac analysis, compared to other groups, the most significant difference in bacterial composition was found in samples from stage T (Fig. S2B). According to the bioplot of RDA in S and M3 (Fig. 6A), three different bacteria represented the main microbial changes of the two timespots. Acinetobacter was observed in the left part of the plot, indicating that it was much more abundant in S than M3. However, Qingshengfania and Propionibacterium were observed in the other side of the plot, indicating that these bacteria were more abundant in M3 than S. Fig. 6B shows that different bacteria represented two different time points which is a similar observation to Fig. 6A. Raoultella, Klebsiella, and Empedobacter were spotted in the left side of plot, showing they were more abundant in A48 than S. On the right side, Streptococcus and Weissella were observed, showing they can represent S by having a higher abundance than A48. 4. Discussion Sufu is a typical, traditional Chinese fermented soybean curd; it is Fig. 2. Physicochemical changes in sufu. (A) pH mean values at various fermentation stages. The initial pH was 6.07 which significantly increased to 6.39 at saltpehtze stage (P < 0.05). From D0 to M3, the pH value showed a gradual decrease. (B) NaCl concentration at various fermentation stages. The NaCl concentration peaked at the salt-pehtze stage (13.6%) and decreased significantly at D0 (8.02%) (P < 0.05). (C) Amino nitrogen content at various fermentation stages. The amino nitrogen content peaked at the end of the pehtze stage (0.65%) and decreased significantly to 0.26% at D0 (P < 0.05). Thereafter, the amino nitrogen continued to rise from 0.26% to 0.59% during the ripening fermentation stage. (D) Reducing sugar at various fermentation stages. Reducing sugar was not detected before pouring dressing mixture. It peaked at M1 (10.20%) and was significantly higher than that of other stages during the post-fermentation (P < 0.05). Different letters indicate significant differences (P < 0.05). Tofu (T), pehtze which inoculated with A. elegans for 24 h (A24), 48 h (A48), salt-pehtze (S), fermentation of sufu for 0 day (D0), 5 days (D5), 1 month (M1), 2 months (M2), 3 months (M3). D. Xu, et al. Food Microbiology 86 (2020) 103340 4

physicochemical environment (Liu et al., 2018). Expectedly, the NaCl concentration peaked at the salt-pehtze stage and then declined significantly after D0 due to the salt-free dressing mixture (P < 0.05). Due to similar osmotic pressures between sufu and the mixture, the NaCl concentrations equalized over time (Zhang et al., 2014). The concentration of amino nitrogen was significantly lower in the salt-pehtze stage than in the pehtze stage (P < 0.05). This was probably because the salt water diluted the amino nitrogen content and the microbial activity. A previous study showed that initially the microbial count increased considerably but declined significantly after salting, indicating that the amino nitrogen content may be related to the lower bacterial and fungal activity responsible for producing the amino acids (Ma et al., 2013a). Proteolysis plays an equally important role during its ripening. The degradation of protein in sufu leads to the liberation of free amino acids, which results in the increase of amino nitrogen concentration during the ripening (Han et al., 2003). Researchers found that from tofu to pehtze stages, total counts of mesophilic aerobic bacteria, bacterial endospores (spores), Bacillus cereus, LAB, Enterobacteriaceae and fungi increased. All of them decreased after the salting of pehtze. The most likely explanation of this phenomenon could be that the fungi, particularly the mould starters do not survive after the pehtze preparation, owing to the combination of salt and ethanol in the dressing mixture applied for the maturation of sufu (Han et al., 2004). This was similar with our own fungi results and may, in some extents, explain why fungi results showed a clear difference before and after dressing mixture. The Trichosporon and Actinomucor were dominant at pehtze stage while Cryptococcus and Actinomucor were dominant at salt-pehtze stage but had a low abundance after adding dressing mixture. Trichosporon spp. are basidiomycetous yeast-like anamorphic organisms, they were widely found in various fermented food including cereal and soybean fermentations (Tamang et al., 2016) and some species were used for lipid production (Huang et al., 2011a; Shen et al., 2013). Trichosporon were able to utilize different carbohydrates and carbon sources and to degrade urea (Colombo et al., 2011). Cryptococcus genus are covered in a thin layer of glycoprotein capsular material, which help protect cells from physical and biological stresses. They were also suggested to prevent water loss from cells, enhance acquisition of trace levels of nutrients in oligotrophic environments and maintain growth conditions under the salt stress (Breierová et al., 2005). This outstanding characteristic helped Cryptococcus remain dominant in salt-pehtze stage. In salt-pehtze stage, the mould starters were still abundant, though the NaCl concentration was already the highest. But then they almost disappeared in the post-fermentation stage (D0 to M3) due to relatively high levels of ethanol in the mixture. Study showed that the relative abundances of ethanol and ethylene glycol increased significantly in 5 d after dressing mixture and remained at a relatively high level (more than 90% combined) until the end of ripening fermentation stage (Liu et al., 2018). This suggested that the salt and ethanol may wipe out the mould starter when combined. Instead, Monascus and Aspergillus became dominant during the ripening fermentation stage. Meyerozyma, Millerozyma and Pichia were also the main genera at D0 and D5, but they were less abundant during M1 to M3. Monascus is one of the traditionally used fungi in fermented food items and it produces pigments, alcohol, organic acids, protease and amylase (Srianta et al., 2014; Tallapragada et al., 2017; Wan et al., 2015), it can also produce antibiotic substances against pathogenic bacteria when grown on an appropriate medium (Tseng et al., 2000). M. purpureus is one of the typically used Monascus species for fermentation of soy source and sufu. In current study, it was used as inocula in cooked rice to produce red kojic rice, then it was brought into sufu as a part of the dressing mixture. Red kojic rice contains many kinds of pigments produced by M. purpureus such as red, yellow and orange but in general the color tone was red (Srianta et al., 2014). So, it was one of the main reasons that causes sufu to be red-colored. As for Aspergillus, it is defined as a group of conidial fungi. Some species were widely used as a mould starter in commercial microbial fermentations of food industries such as soy sauce and alcoholic beverages (Kim et al., 2017; Masayuki et al., 2008). It was also used to improve nutritional quality of soybean food. Besides, feeding soybean meals with Aspergillus can increase protein content and reduce peptide size within the meal (Hong et al., 2004). This may associate with down-size of peptides and lifted level of amino nitrogen in the post-fermentation. In current study, Aspergillus oryzae was used for fermentation of chiang and introduced to the dressing mixture. Studies showed that it was generally considered a safe nontoxic fungus and safe to use in industrial fermentations (Blumenthal, 2004; Li et al., 2016b). Also, Monascus and Aspergillus were the main fungi used for preparing the dressing mixture. The dressing mixture largely changed the composition of sufu fungal composition. Although red sufu is mainly fermented by fungi, bacteria also played an important role. Proteobacteria was the most abundant phylum throughout the production at the phylum level, Acinetobacter and Enterobacter were the predominant genus throughout the whole fermentation process. The bacterial structure was relatively stable after A48, though the processing procedures and physicochemical properties of the sufu changed a lot. The microbes may contribute to this stability to a greater extent because the sufu production is carried out under non-sterile conditions and unknown functional microbes may cause contamination (Han et al., 2004). The dominant genera Acinetobacter and Enterobacter are both Gram-negative bacteria. Acinetobacter are widely distributed in nature, and commonly present in soil and water (Doughari et al., 2011). Some species of Acinetobacter are harmful pathogens (Peleg et al., 2008) but they have also been found in various fermented food (Silva et al., 2008; Thanh et al., 2016; Yang et al., 2014a). Acinetobacter calcoaceticus was able to grow and to produce biosurfactant on cashew apple juice, thereby reducing the surface tension (Rocha et al., 2006). Many species of Enterobacter were also used or found in fermented food (Drudy et al., 2006). Studies showed that Enterobacter cloacae increased the lysine content when fermenting the corn meal together with Bacillus lichiniformis, the concentrations of lysine, methionine, tryptophan, and total folacin increased significantly (Fields and Yoa, 1990). Pseudomonas is one of the major bacteria in fermented food such as kimchi and doubanjiang (Kang et al., 2006; Li et al., 2016a). In this current study, it was more abundant in the postFig. 4. Analysis of similarity among sufu samples fermented by different times based on the relative abundance of fungal OTUs (operational taxonomic units). Tofu (T), pehtze which inoculated with A. elegans for 24 h (A24), 48 h (A48), salt-pehtze (S), fermentation of sufu for 0 day (D0), 5 days (D5), 1 month (M1), 2 months (M2), 3 months (M3). D. Xu, et al. Food Microbiology 86 (2020) 103340 6

fermentation stage than the pre-fermentation stage. Functionally, Pseudomonas was found significantly correlated to six carbonic compound metabolites and all the nitrogenous metabolites except lysine (Li et al., 2017). As mentioned earlier, the function of Pseudomonas to metabolize lysine can be supplemented by Enterobacter. Empedobacter were very abundant before M1 but finally declined to less than 2%, and they were also found in fermentation starter used to brew Xiaoqu liquor and may influence the different flavors of liquor from different regions (Wu et al., 2017). Streptococcus were used to ferment various food and drinks, such as soy and yoghurt. For example, Streptococcus thermophilus is found in fermented milk products and it is classified as a lactic acid bacterium to produce yoghurt (Kiliç et al., 1996). It was reported that S. thermophilus can also be used to produce antioxidant and recover chitin in the fermentation of shrimp head (Mao et al., 2013). S. thermophilus could be used efficiently in deproteinizing the shrimp head thus the content of amino nitrogen increased continuously during the fermentation. In our research, during the pehtze stages, the amino nitrogen content increased to the peak, this was consistent with the deproteinization function of Streptococcus. Weissella belong to the group of LAB found in many fermented foods, including soy sauce, fermented soybean and sausage, and they were very important microbes in many fermented food, which were used to improve food quality and shorten the fermentation period (Ammor and Mayo, 2007). Weissella paramesenteroides Fig. 5. Relative abundance of bacterial composition in sufu samples during the fermentation process at phylum level (A) and genus level (B). Tofu (T), pehtze which inoculated with A. elegans for 24 h (A24), 48 h (A48), salt-pehtze (S), fermentation of sufu for 0 day (D0), 5 days (D5), 1 month (M1), 2 months (M2), 3 months (M3). D. Xu, et al. Food Microbiology 86 (2020) 103340 7

CQ03 isolated from soy sauce moromi exhibited strong capability in secretion of protease and produced more umami tasting amino acids than other isolates (Hu et al., 2017). Similar like Streptococcus, the relative abundance of Weissella were much higher in the pehtze stages than other stages. This was consistent with increased level of amino nitrogen. The high abundance of Streptococcus and Weissella during the pehtze stages may work together to increase the amino nitrogen content. Bacillus contain species that are important in food industries and research, Bacillus species produce a number of volatile compounds and play a key role in fermented foods (Li et al., 2019; Tamang et al., 2016). But some species of Bacillus are common pathogens, especially B. cereus, that may cause food poisoning (Granum, 1994). Studies have shown that when B. cereus levels were significantly lower than the toxic threshold, the hazard for consumers were reduced (Andersson et al., 1995; Han et al., 2004). Our study showed that in M3, the abundance of Bacillus dramatically declined to 0.07%. Bacillus species are also renowned for their strong amylase and protease activities (Wei et al., 2013) that partially explains its reduced abundance due to the decreased level of starch and protein as fermentation progressed. The previous study showed that though sufu product does not include pasteurization and the pre-fermentation environment is open to air, sufu is a relatively safe product (Shi and Fung, 2000). But the constant presence of opportunistic contaminants are still food safety risks. The first appearance of Bacillus was right after D0, which implied the Bacillus was originated from dressing mixture. Bacillus species were abundant in the first few days of the post-fermentation, this instability made sufu quality still unpredictable and unstable. As the demand of safety and quality increased, suppressing or wiping out the potential pathogen is vital for sufu manufacturing. To increase stability of sufu quality, higher standard of dressing mixture is required. Also, further studies are needed to investigate the specific strains of Bacillus to nurture the functional ones and target killing the B. cereus. Besides Bacillus, studies showed that other common food-borne pathogens including Escherichia coli O157:H7, Salmonella typhimurium, Staphylococcus aureus, and Listeria monocytogenes during sufu fermentation and aging were under the threshold levels. All of these were decreased to non-detectable levels after the few months of fermentation (Shi and Fung, 2000). 5. Conclusions In this study, we measured the physicochemical properties of the sufu as well as the fungal and bacterial composition during the whole fermentation process. To the best of our knowledge, this is the first study that explores the microbial successions of sufu in a period of more than 3 months using high-throughput sequencing technology. Our study produced a dataset with sequencing data from 90 samples obtained at 9 different fermentation stages. Trichosporon, Actinomucor and Cryptococcus were the main genera in pre-fermentation while Monascus and Aspergillus were dominant in post-fermentation. This huge shift in fungal composition was correlated with process procedure of pouring dressing mixture. But the bacterial composition was not greatly changed after pouring dressing mixture, the Acinetobacter and Enterobacter were the predominant genera throughout the whole process. As no bacterial starter was inoculated during the whole process, this relatively stable bacterial structure may relate to fermentation environment. In conclusion, this study provides a better understanding of the dynamic changes in the microbial community and dominant microbe at each fermentation stage in sufu. The interaction between microbial structure and processing procedures were also discussed and considered, which provides theoretical support for optimizing the microbial structure of sufu fermentation stages and improving product quality. Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements The National Key R&D Program of China (2016YFD0400500) and Beijing Postdoctoral Research Foundation (2018-ZZ-120) supported this work. Thanks Dr. Guo Zhuang for his instructive advices and kind help with sequencing data analysis. Thanks to Mr. Austin James Faust and his help with the language editing. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.fm.2019.103340. Fig. 6. Bioplot of RDA for qualitative variables between time spots S and M3 (A), or A48 and S (B). RDA = Redundancy analysis. Pehtze which inoculated with A. elegans for 48 h (A48), salt-pehtze (S), fermentation of sufu for 3 months (M3). D. Xu, et al. Food Microbiology 86 (2020) 103340 8

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