Bioturbation effect of fortified Daqu on microbial community and flavor metabolite in Chinese strong-flavor liquor brewing microecosystem

Food Research International 129 (2020) 108851

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Bioturbation effect of fortified Daqu on microbial community and flavor metabolite in Chinese strong-flavor liquor brewing microecosystem Guiqiang Hea, Jun Huanga, Chongde Wua, Yao Jina, Rongqing Zhoua,b, a b

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College of Biomass Science and Engineering, Sichuan University, Chengdu 610065, China National Engineering Research Center of Solid-State Manufacturing, Luzhou 646000, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Bioturbation effect Fortified Daqu Chinese liquor Brewing ecosystem Interspecies interactions Functional microbiota

Traditional spontaneous fermentation in microecosystem with microbial successions and environmental variables results in inconsistent quality of fermented foods. We therefore propose the directional bioturbation for microbiota regulation and metabolites production in food fermentation. Here, we revealed the bioturbation effect of fortified Daqu on microbial community based on taxonomic composition, co-occurrence network, and metabolic potential, using Chinese strong-flavor liquor fermentation as a microecosystem. According to principal coordinate analysis, microbial communities were obviously influenced by the bioturbation of fortified Daqu. More specifically, bioturbation increased the abundances of Caproiciproducens, Clostridium, Aspergillus, Candida, Methanobacterium, and Methanosarcina, while decreased that of Lactobacillus. Meanwhile, higher abundances of most genes that encoding enzymes involved in interspecies hydrogen transfer between hexanoic acid bacteria and methanogens were observed in the bioturbated ecosystem by PICRUSt approach. Additionally, co-occurrence analysis showed that bioturbation increased the diversity and complexity of interspecies interactions in microecosystem, which contributed to higher production of flavor metabolites such as hexanoic acid, ethyl hexanoate, and hexyl hexanoate. These results indicated that the bioturbation of fortified Daqu is feasible for flavor metabolism by interspecies interactions of functional microbiota in liquor fermentation. Taken together, it is of great importance for regulating Chinese liquor and even other foods fermentation by bioturbation.

1. Introduction Microorganisms are multiple and widely distributed in nature ecosystem and play an extremely important role in maintaining the balance of ecological environment. In the nature ecosystem, microbes commonly interact with many different strains and species in complex ecological networks (Luo, Rensing, Chen, Liu, & Shen, 2017; Ramanan, Kim, Cho, Oh, & Kim, 2016; Santelli et al., 2008). It is also clear that, microbial interactions affect the community distribution during ecological succession and evolution (Elias & Banin, 2012). In fact, microbial interactions are often considered as cooperative networks with interspecies working together toward a common goal in the evolution process of ecosystem. However, microbial successions by natural evolution restrict both the occurrence and effectiveness of synergistic interactions within microbial communities (Oliveira, Rene, & Foster, 2014). In recent years, one effective and applicative approach of the directional regulation for ecological system is bioturbation. The bioturbation is frequently used to describe how living organisms affect the microbial communities and their interactions in ecosystem (Kristensen

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et al., 2012). Recently, this approach was widely adopted for bioremediation system, including examples such as ecological aquaculture wastewater (Lukwambe et al., 2018), tidal flat (Li et al., 2019), and lake sediments (Baranov, Lewandowski, & Krause, 2016). Taken as a whole, the bioturbation effect significantly changed the taxonomic composition and structure of the microbial communities and their interspecies interactions, which was conductive to purification of ecosystem. Traditional fermented foods such as vinegar, soy sauce, and sauerkraut are usually produced by natural fermentation involving multi-species community (Marco et al., 2017). These “fermentation domains” are viewed as small-scale microecosystems (as called microenvironment or microhabitat). However, in general, it is difficult to control the microbial successions and environmental variables that affect the fermentation process. Although the traditional fermented foods have been produced for a long history, traditional hand-making in an open environment without strict control results in low production, inconsistent quality, and even security risk (Jin, Zhu, & Xu, 2017). Based on this, we did some exploration and attempt in accelerating foods fermentation and improving effective control by bioturbation. For

Corresponding author at: College of Biomass Science and Engineering, Sichuan University, Chengdu 610065, China. E-mail address: [email protected] (R. Zhou).

https://doi.org/10.1016/j.foodres.2019.108851 Received 4 September 2019; Received in revised form 18 November 2019; Accepted 20 November 2019 Available online 30 November 2019 0963-9969/ © 2019 Published by Elsevier Ltd.

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exhibited higher abundance of Bacillus than that of traditional Daqu, a slight variation of other bacterial genera also was observed between both Daqu.

instance, the bioturbation of Monascus purpureus could increase the abundance of Lactobacillus and Acetobacte, and improved the content of organic acids in Sichuan bran vinegar fermentation process (Ai et al., 2019). Chinese strong-flavor liquor, one of traditional alcoholic beverages, is produced by a spontaneous solid-state fermentation containing various microbes and their complex interactions (Zou, Zhao, & Luo, 2018). Briefly, the raw material mixture are anaerobically fermented for 45–90 days or longer in a mud cellar, which can be considered as a small-scale microecosystem in which complex microbial sucessions and their metabolism processes are carried out. In fact, the microbial communities of brewing microecosystem are extremely complex and their evolutions are affected by cellar age, process parameter, and geographic location (Li et al., 2017; Liang, Luo, Zhang, Wu, & Zhang, 2016; Liu, Tang, Guo, et al., 2017; Zhang, Yuan, Liao, & Zhang, 2017). For example, Bacteroidetes, Methanosarcina, Methanoculleus, and Clostridium kluyveri were significantly positively correlated with the aged pit mud (Zhang et al., 2017). It was also found that there harbored extensive interspecies interactions among microbial communities in the brewing microecosystem (Li et al., 2017). In particular, synergistic interactions between the hexanoic acid bacteria and methanogenic archaea were detected (Tao et al., 2017; Zheng et al., 2015) and the main mechanism was the interspecies hydrogen transfer (Thauer, Kaster, Seedorf, & Hedderich, 2008). Moreover, interspecies hydrogen transfer between the Clostridium and methanogens (Methanobacteria and Methanomicrobia) was beneficial to maintain the stability of the brewing microecosystem and also for the formation of many flavor metabolites (Hu, Du, Ren, & Xu, 2016). At present, one challenging problem for Chinese liquor enterprises is to achieve “ethyl hexanoate-increasing” and “ethyl lactate-decreasing” appropriately during the strong-flavor liquor production (Tao et al., 2016). To solve this problem, directional bioturbation with fortified Daqu, a novel regulation strategy was developed in our present study. Daqu, an important saccharification and fermentation starter, signicantly affects the community diversity and their successions during the brewing process of Chinese liquor. Bacillus species were considered as the functional microbes in Daqu, because they could produce various hydrolytic enzymes and flavor compounds for Chinese liquor fermentation (Wang, Wu, et al., 2017). More importantly, it might reduce the ability of lactic acid-producing by increasing the abundance of Bacillus during the liquor fermentation, because Lactobacillus was negatively related with Bacillus as well as some bacterial species (Wang, Du, & Xu, 2017b). In the present study, using Chinese strong-flavor liquor fermentation as a microecosystem modle, we investigated the bioturbation effect of fortified Daqu manufactured by inoculating Bacillus velezensis and Bacillus subtilis on microbial community and flavor metabolite. Meanwhile, the network correlations of microbial community and the relationships between functional microbiota and major flavor metabolites were established. Therefore, taking the Chinese liquor fermentation as a model microecosystem and performing the bioturbation for microbiota regulation contribute to the constructing of controllable and stable food fermentation process.

2.2. Liquor fermentation by bioturbation of fortified Daqu Liquor fermentation was performed according to the spontaneous solid-state fermentation with a typical recycling process (Jin et al., 2017) (Supplementary Fig. 1a). Simply, the fermented grains (FG) obtained from the last fermentation batch were distilled, cooled, mixed with traditional Daqu and fortified Daqu respectively, put into fermentation cellar, then anaerobically fermented for 60 days. After fermentation, the FG were taken out, mixed with sorghum and rice husk, distilled to collect fresh liquor, then applied to next batch of fermentation as described above. Therefore, the FG and pit mud (PM) obtained after fermentation with traditional Daqu were numbered FG-T and PMT, respectively. Likewise, the FG-F and PM-F were marked in the brewing microecosystem with bioturbation by fortified Daqu. 2.3. Sample collection and flavor compound analysis For FG, seven positions (100 g/each sample position) were taken from the fermentation cellar in upper, middle, and bottom layer, respectively (Supplementary Fig. 1b). These seven positions were mixed uniformly, taken about 500 g as one sample, transferred to sterile polyethylene bags, and then stored at −80 °C until further analysis. Six FG samples were referred to as FG-TU and FG-FU (upper layer), FG-TM and FG-FM (middle layer), FG-TB and FG-FB (bottom layer), respectively. Extraction and determination of flavor compounds of FG were performed by headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry following the method described previously (Ding, Wu, Huang, & Zhou, 2016). Analysis of flavor compounds was conducted in triplicate. The PM samples were taken from the bottom and wall of fermentation cellar when the FG were removed (Supplementary Fig. 1c). For cellar bottom, samples from five locations (four corners and one central, 100 g/each location) were collected, mixed well, and taken about 200 g as one sample. Likewise, samples collected from the central location of four cellar walls were mixed uniformly as another sample. So four PM samples were marked PM-TW and PM-FW (cellar wall), PM-TB and PMFB (cellar bottom), respectively. All of the samples were stored immediately at −80 °C until analysis. 2.4. DNA extraction, PCR amplification, and sequence analysis Total genomic DNA was extracted by using the Fast DNA SPIN extraction kits (MP Biomedicals, Santa Ana, CA, USA) according to the manufacturer’s instructions. The concentration and purity of extracted DNAs were measured using 0.8% agarose gel electrophoresis and a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA), respectively. The specific primers 338F/806R and ITS5/ITS1 (Ai et al., 2019) with the Illumina barcodes were used to amplify the V3-V4 regions of bacterial 16S rRNA gene and ITS1 regions of fungal rRNA gene, respectively. For archaea, PCR amplification was performed using the primers ARC787F (5′-ATTAGATACCCSBGTAGTCC-3′) and ARC1059R (5′-GCCATGCACCWCCTCT-3′). The detailed PCR procedures were conducted according to a previous method (He et al., 2019). After the individual quantification, amplicons were pooled in equal quantities and subjected to high-throughput sequencing with a MiSeq Reagent Kit V3 (Personal, Shanghai, China) for pair-end 2 × 300 bp sequencing. The sequencing data were processed using the Quantitative Insights Into Microbial Ecology (QIIME, http://qiime.org/) as previously described (Caporaso et al., 2010). Briefly, raw sequencing reads with exact matches to the barcodes were assigned to respective samples and identified as valid sequences. The sequences that did not fulfill the

2. Materials and methods 2.1. Daqu starter and community composition The fermentation starters used in this study were traditional Daqu and fortified Daqu, which were originally produced in our previous work (He et al., 2019). Fortified Daqu was manufactured by exogenously inoculating with Bacillus velezensis and Bacillus subtilis, which were isolated from the high-quality Daqu. Briefly, crushed wheats were mixed with water, in which 1% (v/w) of bacterial suspension with B. velezensis:B. subtilis at a ratio of 106:106 cells/mL was contained, and then were pressed to shape Daqu bricks. As expected, fortified Daqu 2

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following criteria (sequence length ≥ 150 bp, no ambiguous bases, mean quality score ≥ 20, and mononucleotide repeats ≤ 8 bp) were removed (Chen & Jiang, 2014). Subsequently, paired-end reads were assembled by using FLASH (v1.2.7, http://ccb.jhu.edu/software/ FLASH/) (Mago & Salzberg, 2011). After chimera detection, the remaining high-quality sequences were clustered into operational taxonomic units (OTUs) at 97% sequence identity by UCLUST (Edgar, 2010). Bacterial and archaeal OTUs taxonomic classification were conducted by BLAST searching the representative sequences set against the Greengenes Database (Release 13.8, http://greengenes. secondgenome.com/) (Desantis et al., 2006), and UNITE Database (Release 5.0, https://unite.ut.ee/) for fungal classification (Kõljalg et al., 2013). 2.5. Bioinformatics and statistical analysis OTU-level alpha diversity indices, such as Chao1 richness estimator and Shannon diversity index, were calculated using the OTU table in QIIME. OTU-level rarefaction curves were generated to compare the richness and evenness of OTUs among samples. Principal coordinate analysis (PCoA) was displayed to evaluate the ecological distances of different samples based on weighted UniFrac distances via EMPeror (Vázquez-Baeza, Pirrung, Gonzalez, & Knight, 2013). Co-occurrence analysis was performed by calculating Spearman’s rank correlations between predominant taxa. Correlations with |RHO| > 0.6 and P < 0.01 were visualized as co-occurrence network using Cytoscape (Shannon et al., 2003). Microbial functions were predicted by PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) (Langille et al., 2013), based on the KEGG PATHWAY Database (http://www.genome.jp/kegg/pathway.html). Redundancy analysis (RDA) was performed to reveal the correlations between microbiota and flavor compounds with Canoco 5.0 software. One-way analysis of variance (ANOVA), principal component analysis (PCA), and linear discriminant analysis effect size (LEfSe) were carried out to evaluate significant differences (P < 0.05) in flavor compounds among samples.

Fig. 1. Principal coordinates analysis (PCoA) of microbial communities in liquor brewing microecosystem.

genus level was displayed. For FG, total abundance of bacterial genera was higher in the upper layer than that in the middle and bottom layers (Fig. 2a). Lactobacillus, a facultative anaerobic bacterium, was the most predominant genus in all layers, and it decreased after bioturbation. More importantly, it can inhibit the growth of pathogenic and spoilage organisms by producing bacteriocin during the fermentation process. An obvious variation was that the abundances of Clostridium, Bacillus, and Caproiciproducens were higher in the bioturbated samples. Among them, Clostridium, a strictly anaerobic genus, seemed to prefer to inhabit in the middle and bottom layers due to less oxygen being present in both layers of FG, and it ranged from 8.1 to 11.1% in the bioturbated samples. On the contrary, Bacillus tended to inhabit in the upper layer, but it was less detectable than Clostridium. Caproiciproducens possessed almost the same abundance in the upper and middle layers, which was higher than that in the bottom layer after bioturbation. For fungi, total abundance of the bottom layer was the highest, and they became more complicated in different layers of FG (Fig. 2b). The abundances of dominant genera including Aspergillus and Candida exhibited a slight fluctuation in different layers, and they increased after bioturbation. Notably, the yeast genus Guehomyces presented much higher abundance in the bottom layer. For PM, the bottom of fermentation cellar harbored a complex microbiota than that of cellar wall because higher abundances observed in the PM-TB and PM-FB. The dominant bacterial genera included Lactobacillus, Caproiciproducens, and Aminobacterium in these samples (Fig. 2c). The abundance of Lactobacillus decreased while that of Caproiciproducens and Clostridium increased in the bioturbated samples. The distribution of fungal abundances showed that only approximately 36.0–58.4% of the reads in the samples were classified into 20 known genera (Fig. 2d). Among them, higher abundances of dominant genera including Candida, Aspergillus, and Trichosporon were observed in the bioturbated samples. Interestingly, most OTUs could not be classified at genus level by UNITE Database (Release 5.0, https://unite.ut.ee/) (Kõljalg et al., 2013), which suggested that some novel microorganisms have not been fully elucidated in the liquor brewing microecosystem. For archaea, the genera were comprised of abundant Methanobacterium (30.3–42.8%), Methanosarcina (22.7–32.4%), and Methanospirillum (15.9–26.4%), as well as a small proportion of Methanobrevibacter, Methanocorpusculum, Methanoculleus, Methanosaeta, and

3. Results 3.1. Bioturbation effect on the diversity of the microbial community In this study, the microbial communities of FG and PM were investigated by Illumina MiSeq sequencing analysis. After filtering the low-quality sequences, effective tags with different phylogenetic OTUs were obtained from the samples for microbial communities via 97% sequence identity cutoff (Supplementary Table 1). Chao1 and Shannon indices also were respectively calculated to describe the species richness and diversity of the microbial communities in the microecosystem (Supplementary Table 1). Moreover, all of the rarefaction curves based on the observed species tended to reach saturation (Supplementary Fig. 2), which demonstrated that the sequencing data were sufficient to evaluate the microbial communities in the microecosystem. Based on the detected OTUs across the samples, PCoA was performed to examine whether the bioturbation of fortified Daqu affects the taxonomic composition and structure of the microbial community (Fig. 1). The first principal-coordinate axis (PCo1) explained 63.2% of the total variation. All of 10 samples were expectedly partitioned into FG and PM. Further analysis showed that both FG and PM samples bioturbated by fortified Daqu formed a distinct cluster away from the traditional Daqu fermentation. These results clearly revealed that the overall structure of the microbial community in the microecosystem was influenced by the bioturbation of fortified Daqu. 3.2. Bioturbation effect on the microbial composition As shown in Fig. 2, the distribution of the relative abundances at the 3

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Fig. 2. Relative abundances of microbial community in the liquor brewing microecosystem at genus level. Bacterial (a) and fungal (b) compositions of FG, and bacterial (c), fungal (d), and archaeal (e) compositions of PM.

(Fig. 3). After bioturbation, the interspecies interactions in the network were altered. 50 pairs of robust correlations, including 30 positive ones, were identified from 41 genera. Before bioturbation, Lactobacillus and Bacillus were both only formed “triangle” correlations with other genera. However, these two genera were constructed two radical and complex “islands” in the bioturbated microecosystem. One “island” was mainly distributed by six bacterial genera including Syntrophomonas, Caproiciproducens, Aminobacterium, Hydrogenispora, Tissierella, and Lactobacillus. Among them, Lactobacillus showed negative correlations with Caproiciproducens, Hydrogenispora, and Tissierella, while the other genera displayed the co-occurrence correlations between them. Another

Methanomassiliicoccus. It was noteworthy that the abundances of Methanobacterium and Methanosarcina increased in the PM when bioturbated with fortified Daqu (Fig. 2e).

3.3. Bioturbation effect on the microbial interspecies interactions Results displayed in Figs. 1 and 2 showed that microbial communities were obviously altered in the microecosystem after bioturbation by fortified Daqu. To explore whether the fortified Daqu affects the interspecies interactions, correlation networks were constructed for the microbial community of the control and bioturbated microecosystem

Fig. 3. Co-occurrence networks of microbial communities in the control (a) and bioturbated microecosystem (b) based on correlation analysis. A connection stands for a statistically significant (P < 0.01) and strong positive (red, Spearman’s rho > 0.6) or negative (green, Spearman’s rho < −0.6) correlation. Size of each node is proportional to the number of connections, the nodes are colored by genera occupancy, and the thickness of edge is proportional to the absolute value of Spearman’s correlation coefficients. 4

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Fig. 4. Abundance variation of the functional genes encoding for key enzymes involved in hexanoic acid synthesis and methanogenesis by PICRUSt analysis. EC:1.1.1.1, alcohol dehydrogenase; EC:1.2.1.10, acetaldehyde dehydrogenase; EC:1.1.1.27, lactate dehydrogenase; EC:1.2.4.1, pyruvate dehydrogenase; EC:2.3.1.9, acetyl-CoA acetyltransferase; EC:1.1.1.157, 3-hydroxybutyryl-CoA dehydrogenase; EC:4.2.1.55, 3-hydroxybutyryl-CoA dehydratase; EC:1.3.99.2, butyryl-CoA dehydrogenase; EC:1.1.1.35, 3-hydroxy-acyl-CoA dehydrogenase; EC:3.1.2.20, acyl-CoA hydrolase; EC:6.2.1.1, Acetyl-CoA synthetase; EC:1.2.99.2, Acetyl-CoA decarbonylase; EC:1.5.99.11, F420-dependent methylene-H4MPT reductases; EC:1.2.99.5, Formyl-MF dehydrogenase; EC:2.3.1.101, Formyl-MF: H4MPT formyl transferase; EC:3.5.4.27, Methenyl-H4MPT cyclohydrolases; EC:2.1.1.86, H4MPT S-methyltransferase; EC:2.8.4.1, Methyl-Coenzyme M reductase.

“island” was comprised of Amycolatopsis, Mesorhizobium, Bacillus, Tomentella, Phoma, and Methylobacterium. Notably, Bacillus was positively correlated with Amycolatopsis, Mesorhizobium, and Methylobacterium. Additionally, the “gemini” and “triangle” formed by other genera, suggesting a relatively poor interaction in this part, also were rearranged after bioturbation. However, the positive correlation between Clostridium-sensu-stricto-12 and Clostridium-sensu-stricto-14 before bioturbation also was observed in the bioturbated microecosystem. All of the above results suggested that the overall network structure of the microbial communities in the microecosystem was altered due to the bioturbation by fortified Daqu.

Lactobacillus abundance in the microecosystem fermented with fortified Daqu (Fig. 2). These results suggested the bioturbation of fortified Daqu might enhance interspecies hydrogen transfer between hexanoic acid bacteria and methanogenic archaea. 3.5. Bioturbation effect on the flavor metabolites in brewing process Not only the microbial communities of brewing microecosystem were analyzed, but also the bioturbation effect of fortified Daqu on fermentation metabolites was investigated (Fig. 5). A total of 27 esters, 5 alcohols, 10 acids, and 9 other compounds including 4 phenols, 2 aldehydes, and 3 ketones were identified (Supplementary Table 2). The flavor metabolites were used as variable vectors for PCA to reveal the bioturbation effect of fortified Daqu on liquor fermentation (Fig. 5a). It appears that the difference of flavor metabolites was significant between the bioturbation fermentation and control samples. Although the both group samples were characterized by most of flavor metabolites, the skeleton flavor compounds changed greatly after bioturbation. Specifically, the samples fermented with traditional Daqu were mainly characterized by ethyl lactate, ethyl oleate, ethyl linoleate, and ethyl hexadecanoate. Whereas the bioturbated samples were mainly signified by ethyl octanoate, hexyl hexanoate, ethyl hexanoate, and hexanoic acid. To further reveal the bioturbation effect of fortified Daqu on the liquor fermentation, we performed LEfSe tests to distinguish the differences of flavor metabolites across samples. Totally, 51 flavor metabolites significantly differentiated among samples (Fig. 5b, LDA > 2, P < 0.05). In particular, the contents of acids including hexanoic acid, heptanoic acid, pentanoic acid, and butanoic acid in the bioturbated

3.4. Bioturbation effect on functional prediction for interspecies hydrogen transfer The abundances of genes encoding for enzymes related to the synthesis of hexanoic acid and methane in PM ecosystem were investigated in detail by using the PICRUSt approach (Fig. 4). As seen from the Fig. 4a, formation of hexanoic acid generally occurs through a carboxylic acid chain elongation process, which uses ethanol or lactic acid as an electron donor based on reversed β-oxidation (Cavalcante, Leitão, Gehring, Angenent, & Santaella, 2016), and methane metabolism mainly occurs in methanogenic archaea (Liu & Whitman, 2010). As shown in Fig. 4b, 13 and 9 enzymes involved in hexanoic acid synthesis and methanogenesis respectively were predicted in the PM microbiota, and the abundances of all the encoding genes except for lactate dehydrogenase (EC:1.1.1.27) were higher in the bioturbated samples. Abundance of the gene encoding for lactate dehydrogenase deceased in the bioturbated PM, which was consistent with the result of decrease in 5

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Fig. 5. Principal components analysis (PCA) of flavor metabolites in FG samples (a). Bar graph (b) and Plot cladogram (c) results on the content of flavor metabolites. Flavor compounds were represented by linear discriminant analysis coupled with effect size (LEfSe) (LDA > 2, P < 0.05). Each number in the atlas represented one compound, listed successively in Supplementary Table 2.

indicating the strong correlations between microbiota and flavor metabolites. Ethly octanoate, ethyl hexanoate, hexyl hexanoate, hexanol, and hexanoic acid were important flavor compounds in Chinese strongflavor liquor, and they were positively correlated with Clostridium, Caproiciproducens, and Bacillus in FG-FM and FG-FB (Fig. 6a). Among these compounds, esters also showed positive relevances with Aspergillus and Candida in the bioturbated samples (Fig. 6b). In addition, a strong and positive relation between Lactobacillus with lactic acid and ethyl lactate was observed (Fig. 6a). Fungal genera including Bullera and Thermomyces were positively related with phenethyl acetate and phenylethanol in the control samples (Fig. 6b).

group were significantly higher than that of control group. Additionally, the contents of main flavor esters such as hexyl hexanoate, ethyl hexanoate, isoamyl hexanoate, butyl hexanoate, ethyl octanoate, and ethyl heptanoate increased after bioturbation. However, the contents of lactic acid, acetic acid, ethyl lactate, ethyl oleate, ethyl hexadecanoate, and ethyl linoleate in the control samples were significantly higher than that of bioturbated samples (Fig. 5c, LDA > 2, P < 0.05).

3.6. Correlations between functional microbiota and major metabolites The potential correlations between core genera and major flavor metabolites in the liquor fermentation process were constructed by RDA (Fig. 6). Overall, the two axes explained 96.5% and 95.2% of the variation in bacterial and fungal community differentiation, respectively,

4. Discussion Chinese strong-flavor liquor is fermented in the mud cellar, which 6

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specifically, the microbial genera in the microecosystem were mainly dominated by Lactobacillus, Caproiciproducens, Clostridium, Aspergillus, Candida, Methanobacterium, and Methanosarcina, which were in agreement with many previous results (Chai et al., 2019; Liu, Tang, Zhao, et al., 2017; Liu, Tang, Guo, et al., 2017; Wang, Du, et al., 2017). Microbial compositions and their abundances of all sampling locations in the microecosystem were different. Higher abundance of bacterial genera in the upper FG might be attributed to a reason that more species tended to favour a comparative low-acidic and micro-aerobic environment. Fungal abundance of the bottom FG was the highest for three possible reasons. First, this might be due to the fungi and their spores of the upper and middle FG infiltrated into the bottom FG along with the Huangshui, thereby causing higher abundance in the bottom layer. In addition, higher microbial abundance of the bottom PM could act as a source of inoculum of microbes into the bottom FG (Wang, Du, et al., 2017), and the inoculation quantity of Daqu starter was also higher in the bottom FG to ensure the homogeneous fermentation. Lastly, high proliferating rate of abundant bacterial genera in the upper FG might compete with fungi for the shared ecological niches (Prosser et al., 2007), resulting in a decrease of fungal abundance in the upper FG. Therefore, the diversity of microbial compositions in different locations might be an important reason why the FG obtained from different layers exhibited significant heterogeneity of flavor compounds. It was more crucial that the synergistic interactions among dominant species in the community were closely related to the quality and stability of liquor brewing microecosystem. In the present study, the diversity and complexity of interspecies interactions were altered after bioturbation by fortified Daqu. Bacillus, as a main exogenous disturber, showed positive correlations with the occurrences of Amycolatopsis, Mesorhizobium, and Methylobacterium after bioturbation. Although the functions of these genera in liquor brewing process remain unclear so far, they were widely concerned in other realms. For example, species of Amycolatopsis, well recognized as producers of antibiotics such as vancomycin and rifamycin, with wide application in medicine and agriculture (Chen, Wu, Shen, & Wang, 2016). So inhibition of the antibiotics produced by Amycolatopsis on pathogenic bacteria might be beneficial for evolving the community to more suitable for liquor fermentation. Mesorhizobium could efficiently utilize benzene and had broad ability of degrading macromolecular substances for production of large amounts of secondary metabolites (Weelink et al., 2007). Methylobacterium could metabolize methanol as a carbon source to production of terpenoids – key flavor compounds in Chinese liquor (Sonntag et al., 2015). Consequently, benzene and methano metabolism by Mesorhizobium and Methylobacterium, respectively, not only alleviated the inhibition on other microbes, but also improved the flavor of liquor. Overall, although Bacillus was not abundant in the brewing microecosystem, it, combined with these fermentative bacteria, contribute to carbon cycling in the anaerobic fermentation system by involving the biological anaerobic digestion process. Surprisingly, an expected negative correlation between Bacillus and Lactobacillus was not observed although it was reported in a previous study (Wang, Du, et al., 2017). It may be due to widespread and complex interspecies interactions among the members of microbial consortia, and can affect the dynamics and function of the microbial communities (Blanchard & Lu, 2015). Besides, bioturbation effect means that targeted microbes and their related metabolites were characterized simultaneously in the field of metabolic engineering. However, dominant genera may not have the ability to produce flavor compounds in the liquor fermentation (Wu, Lin, & Xu, 2014). In this study, higher abundance of Lactobacillus than that of Bacillus and other genera affected the production of flavor metabolites, which, in turn, will altered the interspecies interactions of microbial community. Therefore, bioturbation is expected to rearrange the microbial community and alters their metabolism in the fermentation system. However, the deeper mechanisms, which might be related to interspecific relationships such as quorum sensing and niche differentiation, should

Fig. 6. Correlations of bacterial (a) and fungal (b) genera with major flavor metabolites were constructed by redundancy analysis (RDA).

can be considered as an important micro-ecoreactor for completion a series of complex reactions. These microbial interactions are mainly involved in various metabolic processes, contributing to the production of flavor compounds and maintenance of stability in the brewing ecosystem. However, the quality of fermentation cellar is inevitably affected by environmental factors, process parameters, and microbial successions. For example, the quality and stability of brewing microecosystem is easily destroyed by abundant lactic acid bacteria (Hu et al., 2016), which can directly lead to imbalance of microbiota structure and poor liquor quality. Based on this, directional regulation of brewing microbiota with fortified Daqu was conducted. In the present study, fortified Daqu altered the microbial distribution and flavor metabolites in the liquor brewing process. The results revealed that the microbiota structure of brewing microecosystem evolved to better for production of high-quality Chinese strong-flavor liquor by bioturbation with fortified Daqu. Diversity indices are comprehensive indicators used to assess the diversity of microbial community in environmental ecosystem, including community richness and community diversity (GonzalezMartinez et al., 2018). The Chao1 and Shannon indices were found to be changeable after bioturbation by fortified Daqu, suggesting that the microbial diversity was altered. Further PCoA indicated that these distinct differences of microbial communities could be regarded as indicators for estimating the bioturbation effect of fortified Daqu, because fortified Daqu largely influenced the results of cluster analysis. For example, the abundance of Clostridium kluyveri was considered as one of microbial indicators for distinguishing different maturity levels of PM ecosystem (Zhang et al., 2017). Therefore, the compositions of the dominant microbes, as one of the crucial influencing factors, largely determine the quality of liquor brewing microecosystem. More 7

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functional microbiota, which contributed to production of high-quality Chinese strong-flavor liquor. Therefore, bioturbation, it would provide an opportunity for us to elucidate the mechanisms underlying the interspecies interaction and their metabolisms for flavor metabolites producing in the food fermentation process.

be further studied by metatranscriptome analysis. In present study, most functional genes encoding for enzymes directly related to hexanoic acid synthesis were predicted in the PM microbiota by PICRUSt analysis. The existence of key genes encoding for lactate dehydrogenase and pyruvate dehydrogenase responsible for converting lactic acid to acetyl-CoA, indicating that the PM microbiota possessed metabolic potential for hexanoic acid synthesis via carboxylic acid chain elongation with lactic acid as substrate. This phenomenon was supported by previous study (Zhu et al., 2015), which showed a unique microbiome in PM ecosystem metabolizes lactic acid for hexanoic acid production. Methane metabolism is thought to enhance the interspecies hydrogen transfer between hexanoic acid bacteria and methanogens and enable hexanoic acid formation thermodynamically feasible (Tao et al., 2014). Higher abundances of the genes encoding for enzymes involved in hydrogenotrophic and acetoclastic methanogenesis pathways also were observed in our study. In addition, Caproiciproducens and Clostridium were important genera for production of hexanoic acid in the liquor brewing microecosystem (Liu, Tang, Guo, et al., 2017; Zou, Ye, & Zhang 2018). Therefore, higher abundances of Caproiciproducens, Clostridium, Methanobacterium (hydrogenotrophic methanogen), and Methanosarcina (acetoclastic methanogene) in the bioturbated PM implied that the interspecies hydrogen transfer was likely enhanced between methanogenesis and hexanoic acid synthesis, which might make the brewing microecosystem more favourable for liquor fermentation. More and more studies have demonstrated that acidification of the fermentation cellar is mainly resulted from the accumulation of lactic acid bacteria (LAB). For instance, abundant LAB could inhibit the Clostridium by decreasing the system pH, by accumulating lactic aicd or secreting bacteriocins (Hu et al., 2016). Moreover, high abundance of Lactobacillus was found negatively correlated with hexanoic acid production (Tao et al., 2014). In our present study, these phenomena also were corroborated by the negative correlation between Lactobacillus and Caproiciproducens – a hexanoic acid-producing bacterium in the PM ecosystem (Liu, Tang, Guo, et al., 2017). Recently, Hydrogenispora was detected at high abundance in the PM, and it could produce butanoic acid – a key aroma contributor of Chinese strong-flavor liquor (Chai et al., 2019). A co-exclusion correlation between Lactobacillus and Hydrogenispora in the bioturbated microecosystem also was observed, indicating high abundance of Lactobacillus could affect the stability of PM ecosystem by inhibiting butanoic acid or hexanoic acid production. As expected, the abundances of hexanoic acid-producers Caproiciproducens and Clostridium increased in the liquor brewing microecosystem after bioturbation. This result corresponded to the higher contents of ethyl hexanoate, hexyl hexanoate, and hexanoic acid in the bioturbated samples and positive correlations between these flavor compounds and hexanoic acid-producers. Meanwhile, lower abundance of Lactobacillus and negative relationships with hexanoic acid bacteria and other genera could provide a reason that the contents of lactic acid and ethyl lactate in the bioturbated samples were lower. These results revealed that bioturbation by fortified Daqu was an effective approach for regulating the microbial distribution in microecosystem, which could help to improve the flavor and quality of Chinese strong-flavor liquor.

Author contributions Guiqiang He performed the experiments, analyzed the data, and prepared the manuscript. Jun Huang performed the experiments and contributed to manuscript discussion. Rongqing Zhou contributed to the experimental design, manuscript revision, and overall support of this study. Chongde Wu and Yao Jin contributed to manuscript revision. CRediT authorship contribution statement Guiqiang He: Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing - original draft. Jun Huang: Conceptualization, Funding acquisition, Investigation. Chongde Wu: Methodology, Investigation, Writing - review & editing. Yao Jin: Methodology, Writing - review & editing. Rongqing Zhou: Conceptualization, Funding acquisition, Supervision. Declaration of Competing Interest 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 authors acknowledge the financial support from the National Research Center of Solid-State Brewing (17H1038, 17H1040), Sichuan University − Luzhou City Cooperation (2017CDLZ-S20), and Sichuan Province Science and Technology Support Program (2015KJT0222011SZ). Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.foodres.2019.108851. References Ai, M., Qiu, X., Huang, J., Wu, C. D., Jin, Y., & Zhou, R. Q. (2019). Characterizing the microbial diversity and major metabolites of Sichuan bran vinegar augmented by Monascus purpureus. International Journal of Food Microbiology, 292, 83–90. Baranov, V., Lewandowski, J. R., & Krause, S. (2016). Bioturbation enhances the aerobic respiration of lake sediments in warming lakes. Biology Letters, 12(8), 1–4. Blanchard, A. E., & Lu, T. (2015). Bacterial social interactions drive the emergence of differential spatial colony structures. BMC Systems Biology, 9(1), 59. Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., ... Gordon, J. I. (2010). QIIME allows analysis of high-throughput community sequencing data. Nature Methods, 7(5), 335–336. Cavalcante, W. D. A., Leitão, R. C., Gehring, T. A., Angenent, L. T., & Santaella, S. T. (2016). Anaerobic fermentation for n-caproic acid production: A review. Process Biochemistry, 54, 106–119. Chai, L. J., Xu, P. X., Qian, W., Zhang, X. J., Ma, J., Lu, Z. M., ... Xu, Z. H. (2019). Profiling the Clostridia with butyrate-producing potential in the mud of Chinese liquor fermentation cellar. International Journal of Food Microbiology, 297, 41–50. Chen, H., & Jiang, W. (2014). Application of high-throughput sequencing in understanding human oral microbiome related with health and disease. Frontiers in Microbiology, 5, 508. Chen, S., Wu, Q. H., Shen, Q. Q., & Wang, H. (2016). Progress in understanding the genetic information and biosynthetic pathways behind Amycolatopsis antibiotics, with implications for the continued discovery of novel drugs. Chembiochem, 17(2), 119–128. Desantis, T. Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E. L., Keller, K., ... Andersen, G. L. (2006). Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Applied and Environmental Microbiology, 72(7), 5069–5072. Ding, X. F., Wu, C. D., Huang, J., & Zhou, R. Q. (2016). Characterization of interphase

5. Conclusion The research investigated the bioturbation effect of fortified Daqu on Chinese strong-flavor liquor brewing microecosystem. The results revealed that the bioturbation of fortified Daqu significantly changed the taxonomic composition and structure of the microbial community. Additionally, co-occurrence analysis showed that the interspecies interactions within the microbial communities, especially for interspecies hydrogen transfer, were markedly changed in the presence of fortified Daqu. Furthermore, fortified Daqu promoted the production of ethyl hexanoate, hexyl hexanoate, and hexanoic acid, while decreased contents of lactic acid and ethyl lactate by interspecies interactions of 8

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