International Journal of Food Microbiology 185 (2014) 112–120
Contents lists available at ScienceDirect
International Journal of Food Microbiology journal homepage: www.elsevier.com/locate/ijfoodmicro
Microbial community dynamics during fermentation of doenjang-meju, traditional Korean fermented soybean Ji Young Jung, Se Hee Lee, Che Ok Jeon ⁎ Department of Life Science, Chung-Ang University, Seoul, 156-756, Republic of Korea
a r t i c l e
i n f o
Article history: Received 4 March 2014 Received in revised form 27 May 2014 Accepted 7 June 2014 Available online 12 June 2014 Keywords: Doenjang-meju fermentation Soybean bricks Microbial community dynamics Aeration Water content
a b s t r a c t Bacterial and fungal community dynamics, along with viable plate counts and water content, were investigated in the exterior and interior regions of doenjang-meju, traditional Korean fermented soybean, during its fermentation process. Measurement of viable cells showed that the meju molding equipment might be an important source of bacterial cells (mostly Bacillus) during doenjang-meju fermentation, whereas fungi might be mostly derived from the fermentation environment including incubation shelves, air, and rice straws. Community analysis using rRNA-targeted pyrosequencing revealed that Bacillus among bacteria and Mucor among fungi were predominant in both the exterior and interior regions of doenjang-meju during the early fermentation period. Bacteria such as Ignatzschineria, Myroides, Enterococcus, Corynebacterium, and Clostridium and fungi such as Geotrichum, Scopulariopsis, Monascus, Fusarium, and eventually Aspergillus were mainly detected as the fermentation progressed. Bacillus, an aerobic bacterial group, was predominant in the exterior regions during the entire fermentation period, while anaerobic, facultative anaerobic, and microaerobic bacteria including Enterococcus, Lactobacillus, Clostridium, Myroides, and Ignatzschineria were much more abundant in the interior regions. Principal component analysis (PCA) also indicated that the bacterial communities in the exterior and interior regions were clearly differentiated, suggesting that aeration might be an important factor in determining the bacterial communities during doenjang-meju fermentation. However, PCA showed that fungal communities were not separated in the exterior and interior regions and Pearson's correlation coefficients showed that the major fungal taxa had significantly positive (Mucor and Geotrichum) or negative (Aspergillus) correlations with the water content during doenjang-meju fermentation, indicating that water content might be a significant factor in determining the fungal communities during doenjang-meju fermentation. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Fermented soybean lumps, called meju in Korean, have been used as major ingredients for the preparation of traditional Korean soybean paste (doenjang), soy sauce (ganjang), and hot pepper paste (gochujang). Two types of traditional Korean meju are produced: doenjang-meju, for the preparation of doenjang and ganjang, and gochujang-meju, for the preparation of gochujang. Generally, in Korea, doenjang-meju is made with soybeans alone, while gochujangmeju is made with the mixture of soybeans and rice. Traditional Korean meju is made by the spontaneous fermentation of steamed raw materials for 1–2 months without the use of starter cultures, which leads to the growth of various microorganisms derived from the surrounding environment including incubation shelves, air, and rice straws (Kim et al., 2013a, 2013b; Lee, 1995).
⁎ Corresponding author at: Department of Life Science, Chung-Ang University, 84, HeukSeok-Ro, Dongjak-Gu, Seoul, 156-756, Republic of Korea. Tel.: +82 2 820 5864; fax: +82 2 821 8132. E-mail address: [email protected] (C.O. Jeon).
http://dx.doi.org/10.1016/j.ijfoodmicro.2014.06.003 0168-1605/© 2014 Elsevier B.V. All rights reserved.
Meju represents a very complex microbial ecosystem comprising bacteria as well as fungi, which are responsible for the hydrolysis of major ingredients including proteins, lipids, carbohydrates, and flavonoid glycosides in meju during fermentation; they are also responsible for the production of various metabolites such as amino acids, organic acids, active metabolites, and aglycones contributing to the nutrition, tastes, flavors, and functionalities in the food products of doenjang, ganjang, and gochujang (Kang et al., 2011; Kim et al., 2010; Kwon et al., 2011; Lee et al., 2012b). Bacterial communities in meju have been extensively studied using culture-based and culture-independent approaches (Kim et al., 2011; Lee et al., 2010; Mo et al., 2010; Park and Oh, 1995), which indicates that Bacillus or its relatives form the predominant bacterial groups in meju (Kim et al., 2011; Lee, 1995; Lee et al., 2010; Mo et al., 2010). However, very few fungal community studies in meju have been performed and fungal groups such as Aspergillus, Scopulariopsis, Cladosporium, Mucor, Lichtheimia, Rhizopus, and Penicillium have been identified in meju (Hong et al., 2011, 2012; Lee et al., 2010). It is widely accepted that environmental variables such as temperature, water content, aeration, and pH are essential factors that influence the microbial communities in microbial ecosystems. In particular,
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
aeration and water content are possibly the most important factors that determine microbial community changes in traditional Korean meju because it is processed in lumps and the spontaneous drying leads to an increase in the porosity of meju during the fermentation period. Water content and aeration (oxygen concentration) are known to be different, depending on the positions of meju lumps and fermentation time, which may govern the distribution and changes in microbial communities in the meju lumps. Previous studies reported that bacterial communities in the interior and exterior regions of meju lumps were quite different (Cho and Lee, 1970; Kim et al., 2011). While bacteria were isolated from all the regions of meju lumps, fungi were only found from the outer layers of meju lumps (Park and Kim, 1970). Doenjang-meju, with the characteristic brick shape, is the most representative traditional Korean meju. Previous studies have been performed only as snap shot analyses on microbial communities of doenjang-meju at a particular time in the entire fermentation period, usually after complete fermentation. To the best of our knowledge, no study has been conducted to investigate the changes in the bacterial and fungal communities in meju during the entire fermentation period. In particular, fungal community analysis of various regions of meju has never performed. Therefore, in this study, we investigated the bacterial and fungal community dynamics, along with viable plate counts and water content, in the interior and exterior regions of doenjang-meju during the entire fermentation period using pyrosequencing that has emerged as a powerful tool elucidating the complex microbial community structures including even minor microbial populations in various fermented foods (Ercolini, 2013; Ercolini et al., 2013; Humblot and Guyot, 2009; Jung et al., 2012, 2013; Lee et al., 2014; Li et al., 2011)
113
and this study will allow for the successful understanding of the microbial mechanisms in traditional Korean meju fermentation.
2. Materials and methods 2.1. Doenjang-meju preparation and sampling Soybean bricks for doenjang-meju fermentation were prepared using yellow soybeans (Glycine max (L.) Merr.) at Sangchon Food Corporation (Yongin, Korea) with some modifications of the traditional manufacturing method. Briefly, approximately 240 kg of dried yellow soybeans were soaked in tap water overnight at room temperature, and then steamed using an oven (Dongil, Korea) with high-pressure steam at 120 °C for 2 h. After cooling to 40 °C, the steamed soybeans were crushed and molded into brick shapes, about 19 × 15 × 8 cm in size. About 200 soybean bricks were manufactured and their outer surface was slightly dried at 40 °C for 20 h in a drying room. The soybean bricks were transferred onto wooden racks and fermented in a fermentation room for 20 days at room temperature (approximately 18–27 °C), and then fermented further with rice straws in the same fermentation room for 42 days. During this period, three soybean bricks were periodically removed and divided into exterior and interior regions at approximately 2-cm depth from the surface of soybean bricks using a saw. These two regions of the soybean bricks were homogenized using a blender (Hanil, Korea) and used for the measurement of water content and the enumeration of bacteria and fungi. We combined 2 g of each homogenized exterior or interior sample from three soybean
Fig. 1. Photographs of cross sectioned doenjang-meju showing (A) meju drying and microbial growth and (B) profiles of water contents and (C) bacterial and fungal abundances in the exterior and interior regions during the doenjang-meju fermentation. The values were derived from triplicate doenjang-meju samples and error bars represent standard deviations.
114
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
bricks together and stored them at − 80 °C, until the bacterial and fungal community analysis. 2.2. Measurement of water content and enumeration of bacteria and fungi Water content in doenjang-meju was measured by weighing 5 g of homogenized samples before and after drying at 105 °C for 24 h in a drying oven. Total number of viable cells of bacteria and fungi in doenjang-meju was determined using a standard viable cell counting method. Briefly, 1 g of homogenized meju samples was resuspended and serially diluted in PBS buffer (137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, 2 mM KH2PO4, pH 7.2). The diluted samples were spread on trypticase soy agar (TSA; BD, USA) and potato-dextrose agar (PDA; BD, USA) for the enumeration of bacteria and fungi, respectively. The agar plates were incubated at 30 °C for 3 days and the number of bacteria and fungi in doenjang-meju was calculated as colony forming units (CFU) per gram. 2.3. Barcoded pyrosequencing for bacterial and fungal community analysis Total genomic DNA from the combined doenjang-meju samples was extracted using a FastDNA Spin kit (MPbio, USA), according to the manufacturer's instructions. Two primer sets, BacF (5′-adaptor B-AC9 F-3′)/BacR (5′-adaptor A-X-AC-541R-3′) (Lee et al., 2012a) and FunF (5′-adaptor B-AG-LR0R -3′)/FunR (5′-adaptor A-X-AG-LR3-3′) (Liu et al., 2012), where X denotes unique 7–11 barcoded sequences inserted between the 454 Life Sciences adaptor A sequence and a common linker AG, were used for the amplification of bacterial 16S rRNA (V1–V3 variable regions) and fungal 28S rRNA (D1–D2 regions) genes, respectively (Supplementary Table S1). All the PCR amplifications were performed in a C1000 thermal cycler (Bio-Rad) with a 50-μl volume containing Taq polymerase mixture (Solgent, Korea), 1 μl genomic DNA, and 20 pmol of each
primer and the cycling regime was as follows: 94 °C for 5 min (1 cycle); 94 °C for 45 s, 55 °C (for bacteria) or 53 °C (for fungi) for 45 s, and 72 °C for 1 min (30 cycles); and 72 °C for 10 min (1 cycle). The PCR amplicons were purified using a PCR purification kit (Solgent, Korea) and their concentrations were carefully measured with an ELISA reader equipped with a Take3 multivolume plate (SynergyMx; BioTek, USA). A composite sample for pyrosequencing was prepared by pooling equal amounts of purified PCR products and then sequenced using a 454 GS-FLX titanium system (Roche, Germany) at Macrogen (Korea). 2.4. Sequence processing and data analyses Bacterial and fungal sequencing reads generated by pyrosequencing were processed and analyzed using the RDP pyrosequencing pipeline (RDPipeline, http://pyro.cme.msu.edu/) (Cole et al., 2014). Through Pipeline Initial Process in RDPipeline, sequencing reads were sorted into specific samples based on their unique barcoded sequences, and then the barcodes were trimmed. Sequencing reads with more than two ambiguous base calls (‘N’), average quality scores below 25 (error, 0.005), or shorter than 300 bp were also removed. Putative chimeric sequencing reads were filtered out using the de novo chimera detection function UCHIME in USEARCH of RDPipeline (Edgar et al., 2011). The processed bacterial and fungal sequencing reads were aligned using the MOTHUR (align.seq) program (Schloss et al., 2009) based on the SILVA database and the MAFFT multiple sequence alignment program (Katoh and Standley, 2013), respectively. The aligned sequences were clustered into operational taxonomic units (OTUs) at a 97% similarity level using the nearest neighbor method available in MOTHUR. Shannon–Weaver (H′) (Shannon and Weaver, 1963), Chao1 (Chao, 1987), and ACE (Chao and Lee, 1992) indices and Good's coverage values were calculated within the MOTHUR program. Rarefaction analysis was also carried out within the MOTHUR program.
Table 1 Summary of the sequencing data sets and statistical analysis of doenjang-meju fermentation samples. Sample (day) Bacteria (exterior)
Bacteria (interior)
Fungi (exterior)
Fungi (interior)
1 7 14 21 28 35 42 49 63 1 7 14 21 28 35 42 49 63 7 14 21 28 35 42 49 63 7 14 21 28 35 42 49 63
Total reads
High-quality reads
OTUs
Shannon–Weaver
Chao1
ACE
Good's coverage
595 4160 4892 5531 7910 4848 5844 1555 2159 4731 4655 1806 3202 1922 3438 367 3547 1298 5083 5024 4256 4210 5926 5993 4419 4272 7910 6253 1914 3043 4691 5733 4048 4937
530 3705 4237 4495 2624 4043 4654 1344 1883 3739 4140 1398 2543 1546 2550 327 2526 1042 4541 4442 3783 3245 4949 4886 3564 3357 4126 5783 1724 2528 4043 4763 3525 3955
6 14 71 104 56 51 104 24 18 42 35 54 115 55 133 21 112 48 24 35 20 46 29 43 26 28 9 14 14 32 20 26 28 20
0.13 0.12 0.90 1.05 1.19 0.48 1.01 0.50 0.40 0.57 0.26 2.15 2.38 2.34 2.69 2.67 2.75 2.22 0.96 1.47 1.14 1.60 0.73 1.22 0.97 0.96 0.06 0.52 0.84 1.60 1.14 1.07 1.35 1.08
9.0 24.5 149.0 210.0 133.5 132.2 173.8 129.0 36.0 112.2 69.0 135.3 245.2 76.1 283.1 21.5 214.2 75.1 63.0 161.5 42.0 88.9 59.3 137.5 65.0 54.3 24.0 28.0 50.0 127.0 29.3 121.0 46.2 35.0
10.5 41.4 258.8 267.0 206.4 167.2 256.9 109.7 60.6 260.5 81.2 134.7 406.9 76.8 399.7 21.9 325.0 111.6 174.9 383.4 59.9 84.4 88.4 409.4 99.8 89.3 79.5 47.1 121.7 253.7 42.8 236.0 112.3 41.9
99.4 99.8 99.1 98.8 98.8 99.3 98.9 98.9 99.5 99.3 99.6 98.1 97.5 98.7 97.1 99.4 97.7 98.1 99.7 99.5 99.7 99.2 99.7 99.4 99.6 99.6 99.9 99.9 99.5 99.2 99.8 99.6 99.6 99.8
OTUs, operational taxonomic units. Diversity indices and Good's coverage were calculated using the MOTHUR at a 3% distance level.
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
The processed bacterial sequencing reads were taxonomically classified into hierarchical bacterial taxa at the phylum and genus levels using the RDP Classifier 2.6 within 16S rRNA training set 9 at an 80% confidence threshold (Wang et al., 2007). For the classification of the processed fungal sequencing reads, the aligned fungal sequences were clustered into OTUs at a 99% similarity level using the nearest neighbor method available in MOTHUR and representative sequences from respective clustered OTU sequences were selected using the sequence selection tool in RDPipeline. The representative fungal sequences were blast-searched against all classified fungal sequences in the NCBI's nt/nr database using the BLASTN algorithm (Altschul et al., 1990) and taxonomically classified into hierarchical fungal taxa showing the best BLASTN matches at the phylum and genus levels. 2.5. Statistical analysis Principal component analysis (PCA) was performed using the MATLAB software program ver. 7.8.0 (MathWorks, USA) on the basis of the relative abundance of bacterial and fungal taxonomic groups classified at the genus level. To investigate the correlation between water content and the respective bacterial and fungal taxonomic groups during doenjang-meju fermentation, Pearson correlation coefficients and P values were calculated using the SPSS statistics package (ver. 12.0; SPSS, USA) on the basis of water content (%) and relative abundance (%) of bacteria and fungi.
115
regions decreased steadily to approximately 8 × 108 CFU/g at day 35, after which, it became almost stable at approximately 8 × 108 CFU/g in both the regions, until the end of the fermentation. Although most fungi grow as hyphae and form mycelia, previous reports have shown that fungal abundance is well correlated with the CFU data (Mayer et al., 2003). Therefore, the fungal abundance in doenjang-meju was also evaluated using a viable cell counting method. Plate counting analysis of fungi indicated that unlike bacteria, fungal colonies were not detected in the initial meju samples (day 0) as well as samples (day 1) tested after the drying period (40 °C, 20 h). Fungal abundance increased rapidly in both the exterior and interior regions during the early meju fermentation period. At day 7, this abundance was slightly higher in the exterior regions than in the interior regions, after which, it slowly increased to the highest peak during the middle period of fermentation (days 21–35). Similar to bacteria, the fungal abundance in the interior regions was slightly higher than that in the exterior regions. 3.2. Changes in bacterial and fungal diversity during the doenjang-meju fermentation A massively parallel barcoded pyrosequencing approach was applied to investigate the microbial communities of doenjang-meju samples showing evident bacterial (1–63 days) and fungal (7–63 days) growth. A total of 140,172 sequencing reads were obtained from a single run with 34 bacterial and fungal PCR amplicons. After removing the low
2.6. Nucleotide sequence accession number The bacterial 16S rRNA and fungal 28S rRNA gene sequencing data from massively parallel barcoded pyrosequencing are publicly available in the NCBI Short Read Archive under accession no. SRP039098 (NCBI BioProject PRJNA239746). 3. Results 3.1. Changes in water content and bacterial and fungal abundance during doenjang-meju fermentation The observations of cross-sectioned doenjang-meju showed that the drying process and microbial growth occurred by moving from outside into inside in the doenjang-meju as the fermentation progressed and the bricks became more porous with evident fungal growth (Fig. 1A). The initial water content of doenjang-meju was approximately 61% (Fig. 1B). During the early fermentation period, water content of the exterior regions decreased very quickly, especially during the drying period at 40 °C for 20 h, while that of the interior regions showed a steady decrease. However, water content of the interior regions decreased very rapidly during the middle fermentation period, which was likely due to the increase in porosity of the exterior regions of doenjangmeju, and eventually, after at 49 days, water content in both the regions of doenjang-meju became approximately similar at 8–9%. The profiles of water content in doenjang-meju during the fermentation period were generally in accordance with those demonstrated by previous reports (Yoo et al., 1998). Bacteria and fungi were easily differentiated on the basis of their colony morphologies and thus enumerated using viable cell counting on TSA and PDA, respectively. The average initial bacterial cell number (day 0) was approximately 103 CFU/ml in both exterior and interior regions. After the drying period at 40 °C for 20 h, bacterial abundance rapidly increased to approximately 8 × 107 CFU/g and 7 × 108 CFU/g in the exterior and interior regions, respectively. While bacterial abundance in the exterior regions was relatively constant until the end of fermentation (63 days), it steadily increased to the highest peak of approximately 9 × 109 CFU/g at day 14 in the interior regions; bacterial abundance in the interior regions remained slightly higher than that in the exterior ones. As fermentation progressed, bacterial abundance in the interior
Fig. 2. Plots showing the relationships between Shannon–Weaver indices of (A) bacteria and (B) fungi and the fermentation time (in days) during the doenjang-meju fermentation.
116
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
quality and chimera sequences, 47,326 bacterial and 63,214 fungal highquality sequences with an average read length of approximately 493 bp and an average of more than 3,251 reads per sample were obtained and their statistical diversities were calculated (Table 1). Good's coverage values indicating estimates of sampling completeness with randomly selected amplicon sequences were 97.1–99.9% at a 3% dissimilarity level, suggesting that the sequencing reads obtained in each sample were sufficient to analyze bacterial and fungal diversity (Table 1). It has been shown that the statistic diversity indices such as OTUs, Shannon–Weaver, Chao1, and ACE observed, are functions of the numbers of sequencing reads obtained (Jung et al., 2013), but the diversity indices showed that bacterial diversity increased during the early fermentation period (Table 1). The plots indicating the relationship between Shannon–Weaver indices, representing both species abundance and evenness present in samples, and fermentation time clearly showed that bacterial diversities increased rapidly in the exterior and interior regions of the doenjang-meju bricks during the early fermentation period (Fig. 2). The plots also showed that bacterial diversity in the interior regions were much higher than that in the exterior regions and that it gradually decreased after the middle period of fermentation until the end. On the other hand, the fungal diversity in the interior regions was very low during the early fermentation period and increased quickly like bacteria as the fermentation progressed. However, the fungal diversity in the exterior regions was much higher than that in the interior regions during the early fermentation period
and was relatively constant during the entire fermentation period. The changes in microbial diversity during the doenjang-meju fermentation were also supported by the rarefaction analysis indicating correlations between OTUs and the sequencing read numbers (Supplementary Fig. S1). 3.3. Changes in bacterial and fungal communities during the doenjang-meju fermentation The bacterial 16S and fungal 28S rRNA gene sequences were classified at both the phylum and genus levels in order to investigate the microbial community changes during the doenjang-meju fermentation. At the phylum level of bacteria, Firmicutes was predominant regardless of the meju interior and exterior regions during the early fermentation period (Fig. 3A and B). Considerable growth of the phyla Proteobacteria and Bacteroidetes was observed in both exterior and interior regions of the doenjang-meju samples after 14 days of fermentation and their relative abundance was much higher in the interior regions than in the exterior ones. These two phyla almost disappeared in the exterior regions after 28 days of fermentation, while they were still evident in the interior regions until the very end, although their relative abundance generally decreased as fermentation progressed. The phylum Actinobacteria was prominently identified only in the interior regions during the late fermentation period. At the genus level of bacteria,
Fig. 3. Bacterial community changes in the (A and C) exterior and (B and D) interior regions during the doenjang-meju fermentation. Data portray (A and B) phylum and (C and D) genus level analyses of bacterial 16S rRNA gene sequences derived from the doenjang-meju samples. The ‘others’ in panels C and D are composed of the genera, each showing a percentage of reads b2.0% of the total reads in all samples.
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
Bacillus was predominant in both meju regions during the early fermentation period (Fig. 3C and D). The growth of the genera Ignatzschineria and Myroides was observed in both exterior and interior regions at relatively high abundance after 14 days of fermentation and their relative abundance was much higher in the latter than in the former regions. After 28 days of fermentation, Ignatzschineria and Myroides almost disappeared and were replaced by Enterococcus in the exterior regions. Members of Ignatzschineria and Myroides were identified in the interior regions even after 28 days of fermentation, and the growth of diverse bacterial groups such as Enterococcus, Corynebacterium, Lactobacillus, Staphylococcus, Oceanobacillus, and Clostridium was also observed. Fig. 3 shows that the genus Bacillus belonging to the phylum Firmicutes was predominant in both interior and exterior regions during the entire fermentation period, suggesting that members of Bacillus probably play key roles in doenjang-meju fermentation. At the phylum level of fungi, Zygomycota and Ascomycota were identified as the predominant phyla during the entire doenjang-meju fermentation (Fig. 4A and B). The phylum Zygomycota was predominant during the early fermentation period and decreased rapidly with the increase of the phylum Ascomycota as the fermentation progressed, and eventually, members of Ascomycota became predominant during the late fermentation period in both the regions. The genus level analysis of the fungal 28S rRNA gene sequences showed that the genera Mucor, Geotrichum, and Rhizopus primarily represented the fungal communities
117
in the exterior regions of the early fermentation samples (day 7), while the genus Mucor was absolutely predominant in the interior regions. As the fermentation progressed, the initially dominant genera decreased and members of other genera such as Scopulariopsis and Fusarium increased. In the interior regions of 14 and 21 day meju samples, members of Rhizopus were rarely detected, while members of Geotrichum became more dominant. Members of Aspergillus were predominant regardless of both exterior and interior regions during the late fermentation period and their abundance was higher in the exterior regions than in the interior ones. Generally, changes in the fungal community occurred faster in the exterior regions than in the interior ones although their succession patterns were similar. 3.4. Multivariate statistical analysis Principal component analysis (PCA) based on the relative abundance of microbial community structures showed that the bacterial communities were separately grouped between the exterior and interior regions regardless of the meju fermentation time except for initial samples (days 1 and 7) of interior regions (Fig. 5A). However, the fungal PCA plot indicated that the fungal communities were distributed into the PC1 and PC2 regions over the meju fermentation time and were not differentiated between exterior and interior regions (Fig. 5B). The bacterial PCA plot showed that Bacillus was the most influential group in the
Fig. 4. Fungal community changes in the (A and C) exterior and (B and D) interior regions during the doenjang-meju fermentation. Data portray (A and B) phylum and (C and D) genus level analyses of fungal 28S rRNA gene sequences derived from the doenjang-meju samples. The others in panels are composed of the phylum or genus groups showing a percentage of reads b2.0% of the total reads in all samples.
118
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
bacterial communities of all exterior and early interior samples and Myroides, Ignatzschineria, and Enterococcus became prominent in the interior regions during the middle and late fermentation periods as shown in Fig. 3C and D. The fungal PCA plot indicated that in both exterior and interior regions, Mucor was primarily dominant during the early fermentation period and Geotrichum became prominent as fermentation progressed, especially in the interior region, and eventually Aspergillus was the most influential fungal group during the late fermentation period as shown in Fig. 4C and D. 4. Discussion
Fig. 5. Principal component analysis (PCA) biplots derived from the relative abundances of (A) bacterial and (B) fungal communities in the exterior and interior regions during the doenjang-meju fermentation. Numbers beside the symbols indicate the fermentation time (in days) of the meju samples. The dotted straight arrows represent the relative loadings of the taxonomic genus groups and their lengths are proportional to their influence on the microbial communities. The directions of the curved arrows in panel B indicate the routes of fungal community changes in the exterior (straight line) and interior (dotted line) regions during the doenjang-meju fermentation.
In Korea, traditional doenjang-meju, a major ingredient of soybean paste and soy sauce, is prepared into a brick shape using steamed (sterilized) soybeans and fermented naturally without the use of starter cultures, indoor or outdoor. Therefore, traditional Korean doenjangmeju fermentation is a solid state fermentation representing very complex bacterial and fungal ecosystems, which makes it difficult to understand the microbial mechanisms of doenjang-meju fermentation process. Given the limited availability of information regarding microbial communities in doenjang-meju, a comprehensive and dynamic study of the microbial ecosystem during doenjang-meju fermentation process remains unaccomplished. In this study, soybean bricks were prepared using steamed soybeans and a pyrosequencing strategy was applied to investigate bacterial and fungal communities in doenjang-meju during the entire fermentation period. There have been some reports that soybeans can be the main source of microorganisms in soybean fermentations (Mulyowidarso et al., 1989, 1990). However, in this study although raw soybeans were heat-treated sufficiently (120 °C, 2 h) to kill all the bacteria including spores, bacterial cells were detected at approximately 103 CFU/g in both exterior and interior regions of the initial soybean bricks (day 0) (Fig. 1C), which suggests that initial bacteria (mostly Bacillus as seen in Fig. 3C and D) are possibly derived from the doenjang-meju molding equipment and that the manufacturing facilities can also be important bacterial sources of doenjang-meju like other traditional food fermentations (Bokulich and Mills, 2013). Specifically, bacterial abundance increased very quickly after the drying period (40 °C, 20 h) (Fig. 1C), which was possibly caused by the growth of Bacillus that is known to grow well at a relatively high temperature (40 °C) (Fig. 3C and D). After the drying period, bacterial abundance in the exterior regions was almost 10 times higher than that in the interior regions; it is possible that Bacillus grows faster due to better aeration of the exterior regions. However, the growth of fungi was not observed even in day 1 samples (Fig. 1C), suggesting that the manufacturing facilities may not be important fungal sources of doenjang-meju. The relatively high temperature (40 °C) may also contribute to the absence of fungal growth in doenjang-meju after the drying period since most fungi favor growth temperatures lower than 40 °C (Pitt and Hocking, 2009).
Table 2 Pearson's correlation coefficients between water contents (%) and bacterial and fungal community composition (%) during the doenjang-meju fermentation period. Bacteria
Pearson's correlation coefficients
Fungi
Pearson's correlation coefficients
Acinetobacter Bacillus Clostridium sensu stricto Corynebacterium Enterococcus Ignatzschineria Lactobacillus Myroides Oceanobacillus Staphylococcus Vagococcus Wohlfahrtiimonas
0.468 −0.073 0.084 −0.283 −0.221 0.234 −0.195 0.327 −0.264 −0.197 0.467 0.376
Mucor Geotrichum Fusarium Aspergillus Scopulariopsis Penicillium Rhizopus Monascus Trichothecium
0.715⁎⁎ 0.603⁎ −0.608⁎ −0.843⁎⁎
* and ** denote statistical significance, where P b 0.05 and P b 0.01, respectively.
−0.437 −0.193 0.131 −0.296 −0.410
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
As fermentation progressed, bacterial groups such as Ignatzschineria and Myroides besides Bacillus and fungal groups such as Mucor, Geotrichum, Monascus, Fusarium, and Aspergillus were identified as major populations, and it was assumed that these microorganisms were derived from the surrounding environment including incubation shelves and air. The soybean bricks were further fermented with rice straws after 21 days of fermentation and the relative abundance of bacteria like Enterococcus, Lactobacillus, Clostridium, Oceanobacillus, and unclassified Bacillales and the fungi Fusarium increased considerably in 28 day samples, which suggested that the rice straws could be sources of these microorganisms in doenjang-meju fermentation (Kim et al., 2013a). It was hypothesized that aeration and water content are the most important factors influencing microbial communities during the doenjang-meju fermentation period since doenjang-meju is fermented in a brick shape and its water content decrease rapidly as fermentation progressed. Fig. 3C and D showed that Bacillus, a typical aerobic bacterial group, was predominant in the exterior regions, while the relative abundance of anaerobic, facultative anaerobic, or microaerobic bacteria including Enterococcus, Lactobacillus, Clostridium, Myroides, and Ignatzschineria was much higher in the interior regions than in the exterior ones, which may be related to the distribution of oxygen concentrations in doenjang-meju bricks. As fermentation progressed, water content in doenjang-meju decreased and the relative abundance of Bacillus increased again during the late fermentation period, which may be due to the increase in porosity (aeration) of doenjang-meju bricks (Fig. 1A). The bacterial PCA plot also indicated that the bacterial communities were grouped separately between the exterior and interior regions except for the initial two samples of the interior regions (Fig. 5A), which also supports the notion that aeration might be an important factor in determining the bacterial communities during the doenjang-meju fermentation. However, the fungal PCA plot showed that unlike bacteria, the fungal communities were not differentiated between the exterior and interior regions, and that changes in the fungal community occurred similarly in both the regions (Figs. 4C, D and 5B), suggesting that aeration might be
119
less important in determining the fungal communities during the doenjang-meju fermentation. To investigate the effects of water content on bacterial and fungal communities, Pearson's correlation coefficients and P values between water content and the compositions of bacterial and fungal community during the meju fermentation period were calculated. Our results showed that all bacterial taxa had a low correlation coefficient with water content, whereas the major fungal taxa such as Mucor, Geotrichum, Fusarium, and Aspergillus, had significantly positive or negative correlation coefficients with water content (P b 0.05, absolute values of Pearson's correlation coefficients of N 0.6) (Table 2). The relative abundance of fungal taxa showing high correlation coefficients was plotted against water content and significant correlation curves were obtained (Fig. 6). Mucor and Geotrichum showed a positive correlation with water content during the doenjang-meju fermentation (Fig. 6A and B), which are well in accordance with the previous reports that Mucor and Geotrichum are less competitive at low water activity conditions (Pitt and Hocking, 2009; Plaza et al., 2003; Sautour et al., 2002). On the other hand, the plots showed that Fusarium and Aspergillus had a negative correlation with water content during the doenjang-meju fermentation (Fig. 6C and D). It has been reported that members of Aspergillus have a high dryness tolerance compared with other fungi (Gibson et al., 1994; Pitt and Christian, 1968; Pitt and Hocking, 2009; Sautour et al., 2002) and our study also showed that members of Aspergillus were predominant in both exterior and interior regions during the late doenjang-meju fermentation period with low water content. Although it has been reported that members of Fusarium generally have a low dryness tolerance, in this study the analysis of Pearson's correlation coefficients showed that Fusarium had a negative correlation with water content during the doenjang-meju fermentation. The soybean bricks were fermented with rice straws which were likely to be the major source of Fusarium after 21 days of fermentation. This might be the reason that Fusarium was rarely detected during the early doenjang-meju samples with high water content, while its abundance increased during the late
Fig. 6. Plots showing relationship between water content and relative abundance of fungal taxa with high Pearson's correlation coefficients (A, Mucor; B, Geotrichum; C, Fusarium; D, Aspergillus) shown in Table 2.
120
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
fermentation period with low water content (Fig. 4C and D). Therefore, the negative correlation between Fusarium abundance and water content during the doenjang-meju fermentation might be unreliable. Fig. 4C and D also showed that the relative abundance of Fusarium did not increase after 28 days of fermentation with the decrease in water content. In conclusion, our study suggests that aeration and water content may be important factors to determine the bacterial and fungal communities, respectively, meaning that the bacterial and fungal successions in doenjangmeju fermentation may be controlled by changing brick size (aeration) of doenjang-meju and humidity of fermentation room (drying rate of doenjang-meju). However, additional analysis of diverse metabolites including amino acids, fungal toxins, and isoflavones is indispensable in parallel along with the analysis of microbial communities to investigate the relationships between microbial communities and metabolites during doenjang-meju fermentation, which will provide a good foundation for the production of safe and high-quality doenjang-meju. Acknowledgments This work was supported by the “Technology Development Program for Agriculture and Forestry (TDPAF) of the Ministry for Agriculture, Food and Rural Affairs” and the “Cooperative Research Program for Agriculture Science & Technology Development (Project titled: Development of starters using laboratory evolution and optimization of culture conditions, Project No. PJ00999302)” Rural Development Administration, Republic of Korea. We are grateful to Dr. S.B. Hong for his kind comments. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.ijfoodmicro.2014.06.003. References Altschul, S.F., Gish, W., Miller, W., Myers, E.W., Lipman, D.J., 1990. Basic local alignment search tool. J. Mol. Biol. 215, 403–410. Bokulich, N.A., Mills, D.A., 2013. Facility-specific “house” microbiome drives microbial landscapes of artisan cheesemaking plants. Appl. Environ. Microbiol. 79, 5214–5223. Chao, A., 1987. Estimating the population size for capture-recapture data with unequal catchability. Biometrics 43, 783–791. Chao, A., Lee, S.M., 1992. Estimating the number of classes via sample coverage. J. Am. Stat. Assoc. 87, 210–217. Cho, D.H., Lee, W.J., 1970. Microbiological studies of Korean native soy-sauce fermentation: a study on the microflora of fermented Korean maeju loaves. J. Korean Agric. Chem. Soc. 13, 35–42. Cole, J.R., Wang, Q., Fish, J.A., Chai, B., McGarrell, D.M., Sun, Y., Brown, C.T., Porras-Alfaro, A., Kuske, C.R., Tiedje, J.M., 2014. Ribosomal database project: data and tools for high throughput rRNA analysis. Nucleic Acids Res. 42, D633–D642. Edgar, R.C., Haas, B.J., Clemente, J.C., Quince, C., Knight, R., 2011. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200. Ercolini, D., 2013. High-throughput sequencing and metagenomics: moving forward in the culture-independent analysis of food microbial ecology. Appl. Environ. Microbiol. 79, 3148–3155. Ercolini, D., Pontonio, E., De Filippis, F., Minervini, F., La Storia, A., Gobbetti, M., Di Cagno, R., 2013. Microbial ecology dynamics during rye and wheat sourdough preparation. Appl. Environ. Microbiol. 79, 7827–7836. Gibson, A.M., Baranyi, J., Pitt, J.I., Eyles, M.J., Roberts, T.A., 1994. Predicting fungal growth: the effect of water activity on Aspergillus flavus and related species. Int. J. Food Microbiol. 23, 419–431. Hong, S.B., Kim, D.H., Lee, M., Baek, S.Y., Kwon, S.W., Samson, R.A., 2011. Taxonomy of Eurotium species isolated from meju. J. Microbiol. 49, 669–674. Hong, S.B., Kim, D.H., Lee, M., Baek, S.Y., Kwon, S.W., Houbraken, J., Samson, R.A., 2012. Zygomycota associated with traditional meju, a fermented soybean starting material for soy sauce and soybean paste. J. Microbiol. 50, 386–393. Humblot, C., Guyot, J.P., 2009. Pyrosequencing of tagged 16S rRNA gene amplicons for rapid deciphering of the microbiomes of fermented foods such as pearl millet slurries. Appl. Environ. Microbiol. 75, 4354–4361. Jung, J.Y., Lee, S.H., Lee, H.J., Seo, H.Y., Park, W.S., Jeon, C.O., 2012. Effects of Leuconostoc mesenteroides starter cultures on microbial communities and metabolites during kimchi fermentation. Int. J. Food Microbiol. 153, 378–387.
Jung, J.Y., Lee, S.H., Lee, H.J., Jeon, C.O., 2013. Microbial succession and metabolite changes during fermentation of saeu-jeot: traditional Korean salted seafood. Food Microbiol. 34, 360–368. Kang, H.J., Yang, H.J., Kim, M.J., Han, E.S., Kim, H.J., Kwon, D.Y., 2011. Metabolomic analysis of meju during fermentation by ultra performance liquid chromatographyquadrupole-time of flight mass spectrometry (UPLC-Q-TOF MS). Food Chem. 127, 1056–1064. Katoh, K., Standley, D.M., 2013. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772–780. Kim, H.G., Hong, J.H., Song, C.K., Shin, H.W., Kim, K.O., 2010. Sensory characteristics and consumer acceptability of fermented soybean paste (doenjang). J. Food Sci. 75, S375–S383. Kim, Y.S., Kim, M.C., Kwon, S.W., Kim, S.J., Park, I.C., Ka, J.O., Weon, H.Y., 2011. Analyses of bacterial communities in meju, a Korean traditional fermented soybean bricks, by cultivation-based and pyrosequencing methods. J. Microbiol. 49, 340–348. Kim, D.H., Kim, S.H., Kwon, S.W., Lee, J.K., Hong, S.B., 2013a. Fungal diversity of rice straw for meju fermentation. J. Microbiol. Biotechnol. 28, 1654–1663. Kim, D.H., Kim, S.H., Kwon, S.W., Lee, J.K., Hong, S.B., 2013b. Mycoflora of soybeans used for meju fermentation. Mycobiology 41, 100–107. Kwon, D.Y., Hong, S.M., Ahn, I.S., Kim, M.J., Yang, H.J., Park, S., 2011. Isoflavonoids and peptides from meju, long-term fermented soybeans, increase insulin sensitivity and exert insulinotropic effects in vitro. Nutrition 27, 244–252. Lee, S.S., 1995. Meju fermentation for a raw material of Korean traditional soy products. Korean J. Mycol. 23, 161–175. Lee, J.H., Kim, T.W., Lee, H., Chang, H.C., Kim, H.Y., 2010. Determination of microbial diversity in meju, fermented cooked soya beans, using nested PCR-denaturing gradient gel electrophoresis. Lett. Appl. Microbiol. 51, 388–394. Lee, H.J., Jung, J.Y., Oh, Y.K., Lee, S.S., Madsen, E.L., Jeon, C.O., 2012a. Comparative survey of rumen microbial communities and metabolites across one caprine and three bovine groups, using barcoded pyrosequencing and 1H nuclear magnetic resonance spectroscopy. Appl. Environ. Microbiol. 78, 5983–5993. Lee, S.Y., Kim, H.Y., Lee, S., Lee, J.M., Muthaiya, M.J., Kim, B.S., Oh, J.Y., Song, C.K., Jeon, E.J., Ryu, H.S., Lee, C.H., 2012b. Mass spectrometry-based metabolite profiling and bacterial diversity characterization of Korean traditional meju during fermentation. J. Microbiol. Biotechnol. 22, 1523–1531. Lee, S.H., Jung, J.Y., Jeon, C.O., 2014. Effects of temperature on microbial succession and metabolite change during saeu-jeot fermentation. Food Microbiol. 38, 16–25. Li, X.R., Ma, E.B., Yan, L.Z., Meng, H., Du, X.W., Zhang, S.W., Quan, Z.X., 2011. Bacterial and fungal diversity in the traditional Chinese liquor fermentation process. Int. J. Food Microbiol. 146, 31–37. Liu, K.L., Porras-Alfaro, A., Kuske, C.R., Eichorst, S.A., Xie, G., 2012. Accurate, rapid taxonomic classification of fungal large-subunit rRNA genes. Appl. Environ. Microbiol. 78, 1523–1533. Mayer, Z., Bagnara, A., Färber, P., Geisen, R., 2003. Quantification of the copy number of nor-1, a gene of the aflatoxin biosynthetic pathway by real-time PCR, and its correlation to the cfu of Aspergillus flavus in foods. Int. J. Food Microbiol. 143, 143–151. Mo, A.Y., Kwon, B., Kamala-Kannan, S., Lee, K.J., Oh, B.T., Kim, D.H., Yang, M.S., Kim, J.H., Park, S.M., 2010. Isolation and characterization of Bacillus polyfermenticus isolated from meju, Korean soybean fermentation starter. World J. Microbiol. Biotechnol. 26, 1099–1105. Mulyowidarso, R.K., Fleet, G.H., Buckle, K.A., 1989. The microbial ecology of soybean soaking for tempe production. Int. J. Food Microbiol. 8, 35–46. Mulyowidarso, R.K., Fleet, G.H., Buckle, K.A., 1990. Association of bacteria with the fungal fermentation of soybean tempe. J. Appl. Bacteriol. 68, 43–47. Park, K.I., Kim, K.J., 1970. Studies on manufacturing of the Korean soy sauce (part I). In Research Report. Cent. Ind. Res. Inst. 20, 89–93. Park, J.M., Oh, H.I., 1995. Changes in microflora and enzyme activities of traditional kochujang meju during fermentation. Korean J. Food Sci. Technol. 27, 56–62. Pitt, J.I., Christian, J.H.B., 1968. Water relations of xerophilic fungi isolated from prunes. Appl. Microbiol. 16, 1853–1858. Pitt, J.I., Hocking, A.D., 2009. Fungi and Food Spoilage, 3rd edn. Springer, New York. Plaza, P., Usall, J., Teixidó, N., Vinãs, I., 2003. Effect of water activity and temperature on germination and growth of Penicillium digitatum, P. italicum and Geotrichum candidum. J. Appl. Microbiol. 94, 549–554. Sautour, M., Mansur, C.S., Divies, C., Bensoussan, M., Dantigny, P., 2002. Comparison of the effects of temperature and water activity on growth rate of food spoilage moulds. J. Ind. Microbiol. Biotechnol. 28, 311–315. Schloss, P.D., Westcott, S.L., Ryabin, T., Hall, J.R., Hartmann, M., Hollister, E.B., Lesniewski, R.A., Oakley, B.B., Parks, D.H., Robinson, C.J., Sahl, J.W., Stres, B., Thallinger, G.G., Van Horn, D.J., Weber, C.F., 2009. Introducing mothur: opensource, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–7541. Shannon, C.E., Weaver, W., 1963. The Mathematical Theory of Communication. University of Illinois Press, Urbana. Wang, Q., Garrity, G.M., Tiedje, J.M., Cole, J.R., 2007. Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267. Yoo, J.Y., Kim, H.G., Kim, W.J., 1998. Physicochemical and microbiological changes of traditional meju during fermentation in Kangweondo area. Korean J. Food Sci. Technol. 30, 908–915.
Contents lists available at ScienceDirect
International Journal of Food Microbiology journal homepage: www.elsevier.com/locate/ijfoodmicro
Microbial community dynamics during fermentation of doenjang-meju, traditional Korean fermented soybean Ji Young Jung, Se Hee Lee, Che Ok Jeon ⁎ Department of Life Science, Chung-Ang University, Seoul, 156-756, Republic of Korea
a r t i c l e
i n f o
Article history: Received 4 March 2014 Received in revised form 27 May 2014 Accepted 7 June 2014 Available online 12 June 2014 Keywords: Doenjang-meju fermentation Soybean bricks Microbial community dynamics Aeration Water content
a b s t r a c t Bacterial and fungal community dynamics, along with viable plate counts and water content, were investigated in the exterior and interior regions of doenjang-meju, traditional Korean fermented soybean, during its fermentation process. Measurement of viable cells showed that the meju molding equipment might be an important source of bacterial cells (mostly Bacillus) during doenjang-meju fermentation, whereas fungi might be mostly derived from the fermentation environment including incubation shelves, air, and rice straws. Community analysis using rRNA-targeted pyrosequencing revealed that Bacillus among bacteria and Mucor among fungi were predominant in both the exterior and interior regions of doenjang-meju during the early fermentation period. Bacteria such as Ignatzschineria, Myroides, Enterococcus, Corynebacterium, and Clostridium and fungi such as Geotrichum, Scopulariopsis, Monascus, Fusarium, and eventually Aspergillus were mainly detected as the fermentation progressed. Bacillus, an aerobic bacterial group, was predominant in the exterior regions during the entire fermentation period, while anaerobic, facultative anaerobic, and microaerobic bacteria including Enterococcus, Lactobacillus, Clostridium, Myroides, and Ignatzschineria were much more abundant in the interior regions. Principal component analysis (PCA) also indicated that the bacterial communities in the exterior and interior regions were clearly differentiated, suggesting that aeration might be an important factor in determining the bacterial communities during doenjang-meju fermentation. However, PCA showed that fungal communities were not separated in the exterior and interior regions and Pearson's correlation coefficients showed that the major fungal taxa had significantly positive (Mucor and Geotrichum) or negative (Aspergillus) correlations with the water content during doenjang-meju fermentation, indicating that water content might be a significant factor in determining the fungal communities during doenjang-meju fermentation. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Fermented soybean lumps, called meju in Korean, have been used as major ingredients for the preparation of traditional Korean soybean paste (doenjang), soy sauce (ganjang), and hot pepper paste (gochujang). Two types of traditional Korean meju are produced: doenjang-meju, for the preparation of doenjang and ganjang, and gochujang-meju, for the preparation of gochujang. Generally, in Korea, doenjang-meju is made with soybeans alone, while gochujangmeju is made with the mixture of soybeans and rice. Traditional Korean meju is made by the spontaneous fermentation of steamed raw materials for 1–2 months without the use of starter cultures, which leads to the growth of various microorganisms derived from the surrounding environment including incubation shelves, air, and rice straws (Kim et al., 2013a, 2013b; Lee, 1995).
⁎ Corresponding author at: Department of Life Science, Chung-Ang University, 84, HeukSeok-Ro, Dongjak-Gu, Seoul, 156-756, Republic of Korea. Tel.: +82 2 820 5864; fax: +82 2 821 8132. E-mail address: [email protected] (C.O. Jeon).
http://dx.doi.org/10.1016/j.ijfoodmicro.2014.06.003 0168-1605/© 2014 Elsevier B.V. All rights reserved.
Meju represents a very complex microbial ecosystem comprising bacteria as well as fungi, which are responsible for the hydrolysis of major ingredients including proteins, lipids, carbohydrates, and flavonoid glycosides in meju during fermentation; they are also responsible for the production of various metabolites such as amino acids, organic acids, active metabolites, and aglycones contributing to the nutrition, tastes, flavors, and functionalities in the food products of doenjang, ganjang, and gochujang (Kang et al., 2011; Kim et al., 2010; Kwon et al., 2011; Lee et al., 2012b). Bacterial communities in meju have been extensively studied using culture-based and culture-independent approaches (Kim et al., 2011; Lee et al., 2010; Mo et al., 2010; Park and Oh, 1995), which indicates that Bacillus or its relatives form the predominant bacterial groups in meju (Kim et al., 2011; Lee, 1995; Lee et al., 2010; Mo et al., 2010). However, very few fungal community studies in meju have been performed and fungal groups such as Aspergillus, Scopulariopsis, Cladosporium, Mucor, Lichtheimia, Rhizopus, and Penicillium have been identified in meju (Hong et al., 2011, 2012; Lee et al., 2010). It is widely accepted that environmental variables such as temperature, water content, aeration, and pH are essential factors that influence the microbial communities in microbial ecosystems. In particular,
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
aeration and water content are possibly the most important factors that determine microbial community changes in traditional Korean meju because it is processed in lumps and the spontaneous drying leads to an increase in the porosity of meju during the fermentation period. Water content and aeration (oxygen concentration) are known to be different, depending on the positions of meju lumps and fermentation time, which may govern the distribution and changes in microbial communities in the meju lumps. Previous studies reported that bacterial communities in the interior and exterior regions of meju lumps were quite different (Cho and Lee, 1970; Kim et al., 2011). While bacteria were isolated from all the regions of meju lumps, fungi were only found from the outer layers of meju lumps (Park and Kim, 1970). Doenjang-meju, with the characteristic brick shape, is the most representative traditional Korean meju. Previous studies have been performed only as snap shot analyses on microbial communities of doenjang-meju at a particular time in the entire fermentation period, usually after complete fermentation. To the best of our knowledge, no study has been conducted to investigate the changes in the bacterial and fungal communities in meju during the entire fermentation period. In particular, fungal community analysis of various regions of meju has never performed. Therefore, in this study, we investigated the bacterial and fungal community dynamics, along with viable plate counts and water content, in the interior and exterior regions of doenjang-meju during the entire fermentation period using pyrosequencing that has emerged as a powerful tool elucidating the complex microbial community structures including even minor microbial populations in various fermented foods (Ercolini, 2013; Ercolini et al., 2013; Humblot and Guyot, 2009; Jung et al., 2012, 2013; Lee et al., 2014; Li et al., 2011)
113
and this study will allow for the successful understanding of the microbial mechanisms in traditional Korean meju fermentation.
2. Materials and methods 2.1. Doenjang-meju preparation and sampling Soybean bricks for doenjang-meju fermentation were prepared using yellow soybeans (Glycine max (L.) Merr.) at Sangchon Food Corporation (Yongin, Korea) with some modifications of the traditional manufacturing method. Briefly, approximately 240 kg of dried yellow soybeans were soaked in tap water overnight at room temperature, and then steamed using an oven (Dongil, Korea) with high-pressure steam at 120 °C for 2 h. After cooling to 40 °C, the steamed soybeans were crushed and molded into brick shapes, about 19 × 15 × 8 cm in size. About 200 soybean bricks were manufactured and their outer surface was slightly dried at 40 °C for 20 h in a drying room. The soybean bricks were transferred onto wooden racks and fermented in a fermentation room for 20 days at room temperature (approximately 18–27 °C), and then fermented further with rice straws in the same fermentation room for 42 days. During this period, three soybean bricks were periodically removed and divided into exterior and interior regions at approximately 2-cm depth from the surface of soybean bricks using a saw. These two regions of the soybean bricks were homogenized using a blender (Hanil, Korea) and used for the measurement of water content and the enumeration of bacteria and fungi. We combined 2 g of each homogenized exterior or interior sample from three soybean
Fig. 1. Photographs of cross sectioned doenjang-meju showing (A) meju drying and microbial growth and (B) profiles of water contents and (C) bacterial and fungal abundances in the exterior and interior regions during the doenjang-meju fermentation. The values were derived from triplicate doenjang-meju samples and error bars represent standard deviations.
114
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
bricks together and stored them at − 80 °C, until the bacterial and fungal community analysis. 2.2. Measurement of water content and enumeration of bacteria and fungi Water content in doenjang-meju was measured by weighing 5 g of homogenized samples before and after drying at 105 °C for 24 h in a drying oven. Total number of viable cells of bacteria and fungi in doenjang-meju was determined using a standard viable cell counting method. Briefly, 1 g of homogenized meju samples was resuspended and serially diluted in PBS buffer (137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, 2 mM KH2PO4, pH 7.2). The diluted samples were spread on trypticase soy agar (TSA; BD, USA) and potato-dextrose agar (PDA; BD, USA) for the enumeration of bacteria and fungi, respectively. The agar plates were incubated at 30 °C for 3 days and the number of bacteria and fungi in doenjang-meju was calculated as colony forming units (CFU) per gram. 2.3. Barcoded pyrosequencing for bacterial and fungal community analysis Total genomic DNA from the combined doenjang-meju samples was extracted using a FastDNA Spin kit (MPbio, USA), according to the manufacturer's instructions. Two primer sets, BacF (5′-adaptor B-AC9 F-3′)/BacR (5′-adaptor A-X-AC-541R-3′) (Lee et al., 2012a) and FunF (5′-adaptor B-AG-LR0R -3′)/FunR (5′-adaptor A-X-AG-LR3-3′) (Liu et al., 2012), where X denotes unique 7–11 barcoded sequences inserted between the 454 Life Sciences adaptor A sequence and a common linker AG, were used for the amplification of bacterial 16S rRNA (V1–V3 variable regions) and fungal 28S rRNA (D1–D2 regions) genes, respectively (Supplementary Table S1). All the PCR amplifications were performed in a C1000 thermal cycler (Bio-Rad) with a 50-μl volume containing Taq polymerase mixture (Solgent, Korea), 1 μl genomic DNA, and 20 pmol of each
primer and the cycling regime was as follows: 94 °C for 5 min (1 cycle); 94 °C for 45 s, 55 °C (for bacteria) or 53 °C (for fungi) for 45 s, and 72 °C for 1 min (30 cycles); and 72 °C for 10 min (1 cycle). The PCR amplicons were purified using a PCR purification kit (Solgent, Korea) and their concentrations were carefully measured with an ELISA reader equipped with a Take3 multivolume plate (SynergyMx; BioTek, USA). A composite sample for pyrosequencing was prepared by pooling equal amounts of purified PCR products and then sequenced using a 454 GS-FLX titanium system (Roche, Germany) at Macrogen (Korea). 2.4. Sequence processing and data analyses Bacterial and fungal sequencing reads generated by pyrosequencing were processed and analyzed using the RDP pyrosequencing pipeline (RDPipeline, http://pyro.cme.msu.edu/) (Cole et al., 2014). Through Pipeline Initial Process in RDPipeline, sequencing reads were sorted into specific samples based on their unique barcoded sequences, and then the barcodes were trimmed. Sequencing reads with more than two ambiguous base calls (‘N’), average quality scores below 25 (error, 0.005), or shorter than 300 bp were also removed. Putative chimeric sequencing reads were filtered out using the de novo chimera detection function UCHIME in USEARCH of RDPipeline (Edgar et al., 2011). The processed bacterial and fungal sequencing reads were aligned using the MOTHUR (align.seq) program (Schloss et al., 2009) based on the SILVA database and the MAFFT multiple sequence alignment program (Katoh and Standley, 2013), respectively. The aligned sequences were clustered into operational taxonomic units (OTUs) at a 97% similarity level using the nearest neighbor method available in MOTHUR. Shannon–Weaver (H′) (Shannon and Weaver, 1963), Chao1 (Chao, 1987), and ACE (Chao and Lee, 1992) indices and Good's coverage values were calculated within the MOTHUR program. Rarefaction analysis was also carried out within the MOTHUR program.
Table 1 Summary of the sequencing data sets and statistical analysis of doenjang-meju fermentation samples. Sample (day) Bacteria (exterior)
Bacteria (interior)
Fungi (exterior)
Fungi (interior)
1 7 14 21 28 35 42 49 63 1 7 14 21 28 35 42 49 63 7 14 21 28 35 42 49 63 7 14 21 28 35 42 49 63
Total reads
High-quality reads
OTUs
Shannon–Weaver
Chao1
ACE
Good's coverage
595 4160 4892 5531 7910 4848 5844 1555 2159 4731 4655 1806 3202 1922 3438 367 3547 1298 5083 5024 4256 4210 5926 5993 4419 4272 7910 6253 1914 3043 4691 5733 4048 4937
530 3705 4237 4495 2624 4043 4654 1344 1883 3739 4140 1398 2543 1546 2550 327 2526 1042 4541 4442 3783 3245 4949 4886 3564 3357 4126 5783 1724 2528 4043 4763 3525 3955
6 14 71 104 56 51 104 24 18 42 35 54 115 55 133 21 112 48 24 35 20 46 29 43 26 28 9 14 14 32 20 26 28 20
0.13 0.12 0.90 1.05 1.19 0.48 1.01 0.50 0.40 0.57 0.26 2.15 2.38 2.34 2.69 2.67 2.75 2.22 0.96 1.47 1.14 1.60 0.73 1.22 0.97 0.96 0.06 0.52 0.84 1.60 1.14 1.07 1.35 1.08
9.0 24.5 149.0 210.0 133.5 132.2 173.8 129.0 36.0 112.2 69.0 135.3 245.2 76.1 283.1 21.5 214.2 75.1 63.0 161.5 42.0 88.9 59.3 137.5 65.0 54.3 24.0 28.0 50.0 127.0 29.3 121.0 46.2 35.0
10.5 41.4 258.8 267.0 206.4 167.2 256.9 109.7 60.6 260.5 81.2 134.7 406.9 76.8 399.7 21.9 325.0 111.6 174.9 383.4 59.9 84.4 88.4 409.4 99.8 89.3 79.5 47.1 121.7 253.7 42.8 236.0 112.3 41.9
99.4 99.8 99.1 98.8 98.8 99.3 98.9 98.9 99.5 99.3 99.6 98.1 97.5 98.7 97.1 99.4 97.7 98.1 99.7 99.5 99.7 99.2 99.7 99.4 99.6 99.6 99.9 99.9 99.5 99.2 99.8 99.6 99.6 99.8
OTUs, operational taxonomic units. Diversity indices and Good's coverage were calculated using the MOTHUR at a 3% distance level.
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
The processed bacterial sequencing reads were taxonomically classified into hierarchical bacterial taxa at the phylum and genus levels using the RDP Classifier 2.6 within 16S rRNA training set 9 at an 80% confidence threshold (Wang et al., 2007). For the classification of the processed fungal sequencing reads, the aligned fungal sequences were clustered into OTUs at a 99% similarity level using the nearest neighbor method available in MOTHUR and representative sequences from respective clustered OTU sequences were selected using the sequence selection tool in RDPipeline. The representative fungal sequences were blast-searched against all classified fungal sequences in the NCBI's nt/nr database using the BLASTN algorithm (Altschul et al., 1990) and taxonomically classified into hierarchical fungal taxa showing the best BLASTN matches at the phylum and genus levels. 2.5. Statistical analysis Principal component analysis (PCA) was performed using the MATLAB software program ver. 7.8.0 (MathWorks, USA) on the basis of the relative abundance of bacterial and fungal taxonomic groups classified at the genus level. To investigate the correlation between water content and the respective bacterial and fungal taxonomic groups during doenjang-meju fermentation, Pearson correlation coefficients and P values were calculated using the SPSS statistics package (ver. 12.0; SPSS, USA) on the basis of water content (%) and relative abundance (%) of bacteria and fungi.
115
regions decreased steadily to approximately 8 × 108 CFU/g at day 35, after which, it became almost stable at approximately 8 × 108 CFU/g in both the regions, until the end of the fermentation. Although most fungi grow as hyphae and form mycelia, previous reports have shown that fungal abundance is well correlated with the CFU data (Mayer et al., 2003). Therefore, the fungal abundance in doenjang-meju was also evaluated using a viable cell counting method. Plate counting analysis of fungi indicated that unlike bacteria, fungal colonies were not detected in the initial meju samples (day 0) as well as samples (day 1) tested after the drying period (40 °C, 20 h). Fungal abundance increased rapidly in both the exterior and interior regions during the early meju fermentation period. At day 7, this abundance was slightly higher in the exterior regions than in the interior regions, after which, it slowly increased to the highest peak during the middle period of fermentation (days 21–35). Similar to bacteria, the fungal abundance in the interior regions was slightly higher than that in the exterior regions. 3.2. Changes in bacterial and fungal diversity during the doenjang-meju fermentation A massively parallel barcoded pyrosequencing approach was applied to investigate the microbial communities of doenjang-meju samples showing evident bacterial (1–63 days) and fungal (7–63 days) growth. A total of 140,172 sequencing reads were obtained from a single run with 34 bacterial and fungal PCR amplicons. After removing the low
2.6. Nucleotide sequence accession number The bacterial 16S rRNA and fungal 28S rRNA gene sequencing data from massively parallel barcoded pyrosequencing are publicly available in the NCBI Short Read Archive under accession no. SRP039098 (NCBI BioProject PRJNA239746). 3. Results 3.1. Changes in water content and bacterial and fungal abundance during doenjang-meju fermentation The observations of cross-sectioned doenjang-meju showed that the drying process and microbial growth occurred by moving from outside into inside in the doenjang-meju as the fermentation progressed and the bricks became more porous with evident fungal growth (Fig. 1A). The initial water content of doenjang-meju was approximately 61% (Fig. 1B). During the early fermentation period, water content of the exterior regions decreased very quickly, especially during the drying period at 40 °C for 20 h, while that of the interior regions showed a steady decrease. However, water content of the interior regions decreased very rapidly during the middle fermentation period, which was likely due to the increase in porosity of the exterior regions of doenjangmeju, and eventually, after at 49 days, water content in both the regions of doenjang-meju became approximately similar at 8–9%. The profiles of water content in doenjang-meju during the fermentation period were generally in accordance with those demonstrated by previous reports (Yoo et al., 1998). Bacteria and fungi were easily differentiated on the basis of their colony morphologies and thus enumerated using viable cell counting on TSA and PDA, respectively. The average initial bacterial cell number (day 0) was approximately 103 CFU/ml in both exterior and interior regions. After the drying period at 40 °C for 20 h, bacterial abundance rapidly increased to approximately 8 × 107 CFU/g and 7 × 108 CFU/g in the exterior and interior regions, respectively. While bacterial abundance in the exterior regions was relatively constant until the end of fermentation (63 days), it steadily increased to the highest peak of approximately 9 × 109 CFU/g at day 14 in the interior regions; bacterial abundance in the interior regions remained slightly higher than that in the exterior ones. As fermentation progressed, bacterial abundance in the interior
Fig. 2. Plots showing the relationships between Shannon–Weaver indices of (A) bacteria and (B) fungi and the fermentation time (in days) during the doenjang-meju fermentation.
116
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
quality and chimera sequences, 47,326 bacterial and 63,214 fungal highquality sequences with an average read length of approximately 493 bp and an average of more than 3,251 reads per sample were obtained and their statistical diversities were calculated (Table 1). Good's coverage values indicating estimates of sampling completeness with randomly selected amplicon sequences were 97.1–99.9% at a 3% dissimilarity level, suggesting that the sequencing reads obtained in each sample were sufficient to analyze bacterial and fungal diversity (Table 1). It has been shown that the statistic diversity indices such as OTUs, Shannon–Weaver, Chao1, and ACE observed, are functions of the numbers of sequencing reads obtained (Jung et al., 2013), but the diversity indices showed that bacterial diversity increased during the early fermentation period (Table 1). The plots indicating the relationship between Shannon–Weaver indices, representing both species abundance and evenness present in samples, and fermentation time clearly showed that bacterial diversities increased rapidly in the exterior and interior regions of the doenjang-meju bricks during the early fermentation period (Fig. 2). The plots also showed that bacterial diversity in the interior regions were much higher than that in the exterior regions and that it gradually decreased after the middle period of fermentation until the end. On the other hand, the fungal diversity in the interior regions was very low during the early fermentation period and increased quickly like bacteria as the fermentation progressed. However, the fungal diversity in the exterior regions was much higher than that in the interior regions during the early fermentation period
and was relatively constant during the entire fermentation period. The changes in microbial diversity during the doenjang-meju fermentation were also supported by the rarefaction analysis indicating correlations between OTUs and the sequencing read numbers (Supplementary Fig. S1). 3.3. Changes in bacterial and fungal communities during the doenjang-meju fermentation The bacterial 16S and fungal 28S rRNA gene sequences were classified at both the phylum and genus levels in order to investigate the microbial community changes during the doenjang-meju fermentation. At the phylum level of bacteria, Firmicutes was predominant regardless of the meju interior and exterior regions during the early fermentation period (Fig. 3A and B). Considerable growth of the phyla Proteobacteria and Bacteroidetes was observed in both exterior and interior regions of the doenjang-meju samples after 14 days of fermentation and their relative abundance was much higher in the interior regions than in the exterior ones. These two phyla almost disappeared in the exterior regions after 28 days of fermentation, while they were still evident in the interior regions until the very end, although their relative abundance generally decreased as fermentation progressed. The phylum Actinobacteria was prominently identified only in the interior regions during the late fermentation period. At the genus level of bacteria,
Fig. 3. Bacterial community changes in the (A and C) exterior and (B and D) interior regions during the doenjang-meju fermentation. Data portray (A and B) phylum and (C and D) genus level analyses of bacterial 16S rRNA gene sequences derived from the doenjang-meju samples. The ‘others’ in panels C and D are composed of the genera, each showing a percentage of reads b2.0% of the total reads in all samples.
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
Bacillus was predominant in both meju regions during the early fermentation period (Fig. 3C and D). The growth of the genera Ignatzschineria and Myroides was observed in both exterior and interior regions at relatively high abundance after 14 days of fermentation and their relative abundance was much higher in the latter than in the former regions. After 28 days of fermentation, Ignatzschineria and Myroides almost disappeared and were replaced by Enterococcus in the exterior regions. Members of Ignatzschineria and Myroides were identified in the interior regions even after 28 days of fermentation, and the growth of diverse bacterial groups such as Enterococcus, Corynebacterium, Lactobacillus, Staphylococcus, Oceanobacillus, and Clostridium was also observed. Fig. 3 shows that the genus Bacillus belonging to the phylum Firmicutes was predominant in both interior and exterior regions during the entire fermentation period, suggesting that members of Bacillus probably play key roles in doenjang-meju fermentation. At the phylum level of fungi, Zygomycota and Ascomycota were identified as the predominant phyla during the entire doenjang-meju fermentation (Fig. 4A and B). The phylum Zygomycota was predominant during the early fermentation period and decreased rapidly with the increase of the phylum Ascomycota as the fermentation progressed, and eventually, members of Ascomycota became predominant during the late fermentation period in both the regions. The genus level analysis of the fungal 28S rRNA gene sequences showed that the genera Mucor, Geotrichum, and Rhizopus primarily represented the fungal communities
117
in the exterior regions of the early fermentation samples (day 7), while the genus Mucor was absolutely predominant in the interior regions. As the fermentation progressed, the initially dominant genera decreased and members of other genera such as Scopulariopsis and Fusarium increased. In the interior regions of 14 and 21 day meju samples, members of Rhizopus were rarely detected, while members of Geotrichum became more dominant. Members of Aspergillus were predominant regardless of both exterior and interior regions during the late fermentation period and their abundance was higher in the exterior regions than in the interior ones. Generally, changes in the fungal community occurred faster in the exterior regions than in the interior ones although their succession patterns were similar. 3.4. Multivariate statistical analysis Principal component analysis (PCA) based on the relative abundance of microbial community structures showed that the bacterial communities were separately grouped between the exterior and interior regions regardless of the meju fermentation time except for initial samples (days 1 and 7) of interior regions (Fig. 5A). However, the fungal PCA plot indicated that the fungal communities were distributed into the PC1 and PC2 regions over the meju fermentation time and were not differentiated between exterior and interior regions (Fig. 5B). The bacterial PCA plot showed that Bacillus was the most influential group in the
Fig. 4. Fungal community changes in the (A and C) exterior and (B and D) interior regions during the doenjang-meju fermentation. Data portray (A and B) phylum and (C and D) genus level analyses of fungal 28S rRNA gene sequences derived from the doenjang-meju samples. The others in panels are composed of the phylum or genus groups showing a percentage of reads b2.0% of the total reads in all samples.
118
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
bacterial communities of all exterior and early interior samples and Myroides, Ignatzschineria, and Enterococcus became prominent in the interior regions during the middle and late fermentation periods as shown in Fig. 3C and D. The fungal PCA plot indicated that in both exterior and interior regions, Mucor was primarily dominant during the early fermentation period and Geotrichum became prominent as fermentation progressed, especially in the interior region, and eventually Aspergillus was the most influential fungal group during the late fermentation period as shown in Fig. 4C and D. 4. Discussion
Fig. 5. Principal component analysis (PCA) biplots derived from the relative abundances of (A) bacterial and (B) fungal communities in the exterior and interior regions during the doenjang-meju fermentation. Numbers beside the symbols indicate the fermentation time (in days) of the meju samples. The dotted straight arrows represent the relative loadings of the taxonomic genus groups and their lengths are proportional to their influence on the microbial communities. The directions of the curved arrows in panel B indicate the routes of fungal community changes in the exterior (straight line) and interior (dotted line) regions during the doenjang-meju fermentation.
In Korea, traditional doenjang-meju, a major ingredient of soybean paste and soy sauce, is prepared into a brick shape using steamed (sterilized) soybeans and fermented naturally without the use of starter cultures, indoor or outdoor. Therefore, traditional Korean doenjangmeju fermentation is a solid state fermentation representing very complex bacterial and fungal ecosystems, which makes it difficult to understand the microbial mechanisms of doenjang-meju fermentation process. Given the limited availability of information regarding microbial communities in doenjang-meju, a comprehensive and dynamic study of the microbial ecosystem during doenjang-meju fermentation process remains unaccomplished. In this study, soybean bricks were prepared using steamed soybeans and a pyrosequencing strategy was applied to investigate bacterial and fungal communities in doenjang-meju during the entire fermentation period. There have been some reports that soybeans can be the main source of microorganisms in soybean fermentations (Mulyowidarso et al., 1989, 1990). However, in this study although raw soybeans were heat-treated sufficiently (120 °C, 2 h) to kill all the bacteria including spores, bacterial cells were detected at approximately 103 CFU/g in both exterior and interior regions of the initial soybean bricks (day 0) (Fig. 1C), which suggests that initial bacteria (mostly Bacillus as seen in Fig. 3C and D) are possibly derived from the doenjang-meju molding equipment and that the manufacturing facilities can also be important bacterial sources of doenjang-meju like other traditional food fermentations (Bokulich and Mills, 2013). Specifically, bacterial abundance increased very quickly after the drying period (40 °C, 20 h) (Fig. 1C), which was possibly caused by the growth of Bacillus that is known to grow well at a relatively high temperature (40 °C) (Fig. 3C and D). After the drying period, bacterial abundance in the exterior regions was almost 10 times higher than that in the interior regions; it is possible that Bacillus grows faster due to better aeration of the exterior regions. However, the growth of fungi was not observed even in day 1 samples (Fig. 1C), suggesting that the manufacturing facilities may not be important fungal sources of doenjang-meju. The relatively high temperature (40 °C) may also contribute to the absence of fungal growth in doenjang-meju after the drying period since most fungi favor growth temperatures lower than 40 °C (Pitt and Hocking, 2009).
Table 2 Pearson's correlation coefficients between water contents (%) and bacterial and fungal community composition (%) during the doenjang-meju fermentation period. Bacteria
Pearson's correlation coefficients
Fungi
Pearson's correlation coefficients
Acinetobacter Bacillus Clostridium sensu stricto Corynebacterium Enterococcus Ignatzschineria Lactobacillus Myroides Oceanobacillus Staphylococcus Vagococcus Wohlfahrtiimonas
0.468 −0.073 0.084 −0.283 −0.221 0.234 −0.195 0.327 −0.264 −0.197 0.467 0.376
Mucor Geotrichum Fusarium Aspergillus Scopulariopsis Penicillium Rhizopus Monascus Trichothecium
0.715⁎⁎ 0.603⁎ −0.608⁎ −0.843⁎⁎
* and ** denote statistical significance, where P b 0.05 and P b 0.01, respectively.
−0.437 −0.193 0.131 −0.296 −0.410
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
As fermentation progressed, bacterial groups such as Ignatzschineria and Myroides besides Bacillus and fungal groups such as Mucor, Geotrichum, Monascus, Fusarium, and Aspergillus were identified as major populations, and it was assumed that these microorganisms were derived from the surrounding environment including incubation shelves and air. The soybean bricks were further fermented with rice straws after 21 days of fermentation and the relative abundance of bacteria like Enterococcus, Lactobacillus, Clostridium, Oceanobacillus, and unclassified Bacillales and the fungi Fusarium increased considerably in 28 day samples, which suggested that the rice straws could be sources of these microorganisms in doenjang-meju fermentation (Kim et al., 2013a). It was hypothesized that aeration and water content are the most important factors influencing microbial communities during the doenjang-meju fermentation period since doenjang-meju is fermented in a brick shape and its water content decrease rapidly as fermentation progressed. Fig. 3C and D showed that Bacillus, a typical aerobic bacterial group, was predominant in the exterior regions, while the relative abundance of anaerobic, facultative anaerobic, or microaerobic bacteria including Enterococcus, Lactobacillus, Clostridium, Myroides, and Ignatzschineria was much higher in the interior regions than in the exterior ones, which may be related to the distribution of oxygen concentrations in doenjang-meju bricks. As fermentation progressed, water content in doenjang-meju decreased and the relative abundance of Bacillus increased again during the late fermentation period, which may be due to the increase in porosity (aeration) of doenjang-meju bricks (Fig. 1A). The bacterial PCA plot also indicated that the bacterial communities were grouped separately between the exterior and interior regions except for the initial two samples of the interior regions (Fig. 5A), which also supports the notion that aeration might be an important factor in determining the bacterial communities during the doenjang-meju fermentation. However, the fungal PCA plot showed that unlike bacteria, the fungal communities were not differentiated between the exterior and interior regions, and that changes in the fungal community occurred similarly in both the regions (Figs. 4C, D and 5B), suggesting that aeration might be
119
less important in determining the fungal communities during the doenjang-meju fermentation. To investigate the effects of water content on bacterial and fungal communities, Pearson's correlation coefficients and P values between water content and the compositions of bacterial and fungal community during the meju fermentation period were calculated. Our results showed that all bacterial taxa had a low correlation coefficient with water content, whereas the major fungal taxa such as Mucor, Geotrichum, Fusarium, and Aspergillus, had significantly positive or negative correlation coefficients with water content (P b 0.05, absolute values of Pearson's correlation coefficients of N 0.6) (Table 2). The relative abundance of fungal taxa showing high correlation coefficients was plotted against water content and significant correlation curves were obtained (Fig. 6). Mucor and Geotrichum showed a positive correlation with water content during the doenjang-meju fermentation (Fig. 6A and B), which are well in accordance with the previous reports that Mucor and Geotrichum are less competitive at low water activity conditions (Pitt and Hocking, 2009; Plaza et al., 2003; Sautour et al., 2002). On the other hand, the plots showed that Fusarium and Aspergillus had a negative correlation with water content during the doenjang-meju fermentation (Fig. 6C and D). It has been reported that members of Aspergillus have a high dryness tolerance compared with other fungi (Gibson et al., 1994; Pitt and Christian, 1968; Pitt and Hocking, 2009; Sautour et al., 2002) and our study also showed that members of Aspergillus were predominant in both exterior and interior regions during the late doenjang-meju fermentation period with low water content. Although it has been reported that members of Fusarium generally have a low dryness tolerance, in this study the analysis of Pearson's correlation coefficients showed that Fusarium had a negative correlation with water content during the doenjang-meju fermentation. The soybean bricks were fermented with rice straws which were likely to be the major source of Fusarium after 21 days of fermentation. This might be the reason that Fusarium was rarely detected during the early doenjang-meju samples with high water content, while its abundance increased during the late
Fig. 6. Plots showing relationship between water content and relative abundance of fungal taxa with high Pearson's correlation coefficients (A, Mucor; B, Geotrichum; C, Fusarium; D, Aspergillus) shown in Table 2.
120
J.Y. Jung et al. / International Journal of Food Microbiology 185 (2014) 112–120
fermentation period with low water content (Fig. 4C and D). Therefore, the negative correlation between Fusarium abundance and water content during the doenjang-meju fermentation might be unreliable. Fig. 4C and D also showed that the relative abundance of Fusarium did not increase after 28 days of fermentation with the decrease in water content. In conclusion, our study suggests that aeration and water content may be important factors to determine the bacterial and fungal communities, respectively, meaning that the bacterial and fungal successions in doenjangmeju fermentation may be controlled by changing brick size (aeration) of doenjang-meju and humidity of fermentation room (drying rate of doenjang-meju). However, additional analysis of diverse metabolites including amino acids, fungal toxins, and isoflavones is indispensable in parallel along with the analysis of microbial communities to investigate the relationships between microbial communities and metabolites during doenjang-meju fermentation, which will provide a good foundation for the production of safe and high-quality doenjang-meju. Acknowledgments This work was supported by the “Technology Development Program for Agriculture and Forestry (TDPAF) of the Ministry for Agriculture, Food and Rural Affairs” and the “Cooperative Research Program for Agriculture Science & Technology Development (Project titled: Development of starters using laboratory evolution and optimization of culture conditions, Project No. PJ00999302)” Rural Development Administration, Republic of Korea. We are grateful to Dr. S.B. Hong for his kind comments. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.ijfoodmicro.2014.06.003. References Altschul, S.F., Gish, W., Miller, W., Myers, E.W., Lipman, D.J., 1990. Basic local alignment search tool. J. Mol. Biol. 215, 403–410. Bokulich, N.A., Mills, D.A., 2013. Facility-specific “house” microbiome drives microbial landscapes of artisan cheesemaking plants. Appl. Environ. Microbiol. 79, 5214–5223. Chao, A., 1987. Estimating the population size for capture-recapture data with unequal catchability. Biometrics 43, 783–791. Chao, A., Lee, S.M., 1992. Estimating the number of classes via sample coverage. J. Am. Stat. Assoc. 87, 210–217. Cho, D.H., Lee, W.J., 1970. Microbiological studies of Korean native soy-sauce fermentation: a study on the microflora of fermented Korean maeju loaves. J. Korean Agric. Chem. Soc. 13, 35–42. Cole, J.R., Wang, Q., Fish, J.A., Chai, B., McGarrell, D.M., Sun, Y., Brown, C.T., Porras-Alfaro, A., Kuske, C.R., Tiedje, J.M., 2014. Ribosomal database project: data and tools for high throughput rRNA analysis. Nucleic Acids Res. 42, D633–D642. Edgar, R.C., Haas, B.J., Clemente, J.C., Quince, C., Knight, R., 2011. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200. Ercolini, D., 2013. High-throughput sequencing and metagenomics: moving forward in the culture-independent analysis of food microbial ecology. Appl. Environ. Microbiol. 79, 3148–3155. Ercolini, D., Pontonio, E., De Filippis, F., Minervini, F., La Storia, A., Gobbetti, M., Di Cagno, R., 2013. Microbial ecology dynamics during rye and wheat sourdough preparation. Appl. Environ. Microbiol. 79, 7827–7836. Gibson, A.M., Baranyi, J., Pitt, J.I., Eyles, M.J., Roberts, T.A., 1994. Predicting fungal growth: the effect of water activity on Aspergillus flavus and related species. Int. J. Food Microbiol. 23, 419–431. Hong, S.B., Kim, D.H., Lee, M., Baek, S.Y., Kwon, S.W., Samson, R.A., 2011. Taxonomy of Eurotium species isolated from meju. J. Microbiol. 49, 669–674. Hong, S.B., Kim, D.H., Lee, M., Baek, S.Y., Kwon, S.W., Houbraken, J., Samson, R.A., 2012. Zygomycota associated with traditional meju, a fermented soybean starting material for soy sauce and soybean paste. J. Microbiol. 50, 386–393. Humblot, C., Guyot, J.P., 2009. Pyrosequencing of tagged 16S rRNA gene amplicons for rapid deciphering of the microbiomes of fermented foods such as pearl millet slurries. Appl. Environ. Microbiol. 75, 4354–4361. Jung, J.Y., Lee, S.H., Lee, H.J., Seo, H.Y., Park, W.S., Jeon, C.O., 2012. Effects of Leuconostoc mesenteroides starter cultures on microbial communities and metabolites during kimchi fermentation. Int. J. Food Microbiol. 153, 378–387.
Jung, J.Y., Lee, S.H., Lee, H.J., Jeon, C.O., 2013. Microbial succession and metabolite changes during fermentation of saeu-jeot: traditional Korean salted seafood. Food Microbiol. 34, 360–368. Kang, H.J., Yang, H.J., Kim, M.J., Han, E.S., Kim, H.J., Kwon, D.Y., 2011. Metabolomic analysis of meju during fermentation by ultra performance liquid chromatographyquadrupole-time of flight mass spectrometry (UPLC-Q-TOF MS). Food Chem. 127, 1056–1064. Katoh, K., Standley, D.M., 2013. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772–780. Kim, H.G., Hong, J.H., Song, C.K., Shin, H.W., Kim, K.O., 2010. Sensory characteristics and consumer acceptability of fermented soybean paste (doenjang). J. Food Sci. 75, S375–S383. Kim, Y.S., Kim, M.C., Kwon, S.W., Kim, S.J., Park, I.C., Ka, J.O., Weon, H.Y., 2011. Analyses of bacterial communities in meju, a Korean traditional fermented soybean bricks, by cultivation-based and pyrosequencing methods. J. Microbiol. 49, 340–348. Kim, D.H., Kim, S.H., Kwon, S.W., Lee, J.K., Hong, S.B., 2013a. Fungal diversity of rice straw for meju fermentation. J. Microbiol. Biotechnol. 28, 1654–1663. Kim, D.H., Kim, S.H., Kwon, S.W., Lee, J.K., Hong, S.B., 2013b. Mycoflora of soybeans used for meju fermentation. Mycobiology 41, 100–107. Kwon, D.Y., Hong, S.M., Ahn, I.S., Kim, M.J., Yang, H.J., Park, S., 2011. Isoflavonoids and peptides from meju, long-term fermented soybeans, increase insulin sensitivity and exert insulinotropic effects in vitro. Nutrition 27, 244–252. Lee, S.S., 1995. Meju fermentation for a raw material of Korean traditional soy products. Korean J. Mycol. 23, 161–175. Lee, J.H., Kim, T.W., Lee, H., Chang, H.C., Kim, H.Y., 2010. Determination of microbial diversity in meju, fermented cooked soya beans, using nested PCR-denaturing gradient gel electrophoresis. Lett. Appl. Microbiol. 51, 388–394. Lee, H.J., Jung, J.Y., Oh, Y.K., Lee, S.S., Madsen, E.L., Jeon, C.O., 2012a. Comparative survey of rumen microbial communities and metabolites across one caprine and three bovine groups, using barcoded pyrosequencing and 1H nuclear magnetic resonance spectroscopy. Appl. Environ. Microbiol. 78, 5983–5993. Lee, S.Y., Kim, H.Y., Lee, S., Lee, J.M., Muthaiya, M.J., Kim, B.S., Oh, J.Y., Song, C.K., Jeon, E.J., Ryu, H.S., Lee, C.H., 2012b. Mass spectrometry-based metabolite profiling and bacterial diversity characterization of Korean traditional meju during fermentation. J. Microbiol. Biotechnol. 22, 1523–1531. Lee, S.H., Jung, J.Y., Jeon, C.O., 2014. Effects of temperature on microbial succession and metabolite change during saeu-jeot fermentation. Food Microbiol. 38, 16–25. Li, X.R., Ma, E.B., Yan, L.Z., Meng, H., Du, X.W., Zhang, S.W., Quan, Z.X., 2011. Bacterial and fungal diversity in the traditional Chinese liquor fermentation process. Int. J. Food Microbiol. 146, 31–37. Liu, K.L., Porras-Alfaro, A., Kuske, C.R., Eichorst, S.A., Xie, G., 2012. Accurate, rapid taxonomic classification of fungal large-subunit rRNA genes. Appl. Environ. Microbiol. 78, 1523–1533. Mayer, Z., Bagnara, A., Färber, P., Geisen, R., 2003. Quantification of the copy number of nor-1, a gene of the aflatoxin biosynthetic pathway by real-time PCR, and its correlation to the cfu of Aspergillus flavus in foods. Int. J. Food Microbiol. 143, 143–151. Mo, A.Y., Kwon, B., Kamala-Kannan, S., Lee, K.J., Oh, B.T., Kim, D.H., Yang, M.S., Kim, J.H., Park, S.M., 2010. Isolation and characterization of Bacillus polyfermenticus isolated from meju, Korean soybean fermentation starter. World J. Microbiol. Biotechnol. 26, 1099–1105. Mulyowidarso, R.K., Fleet, G.H., Buckle, K.A., 1989. The microbial ecology of soybean soaking for tempe production. Int. J. Food Microbiol. 8, 35–46. Mulyowidarso, R.K., Fleet, G.H., Buckle, K.A., 1990. Association of bacteria with the fungal fermentation of soybean tempe. J. Appl. Bacteriol. 68, 43–47. Park, K.I., Kim, K.J., 1970. Studies on manufacturing of the Korean soy sauce (part I). In Research Report. Cent. Ind. Res. Inst. 20, 89–93. Park, J.M., Oh, H.I., 1995. Changes in microflora and enzyme activities of traditional kochujang meju during fermentation. Korean J. Food Sci. Technol. 27, 56–62. Pitt, J.I., Christian, J.H.B., 1968. Water relations of xerophilic fungi isolated from prunes. Appl. Microbiol. 16, 1853–1858. Pitt, J.I., Hocking, A.D., 2009. Fungi and Food Spoilage, 3rd edn. Springer, New York. Plaza, P., Usall, J., Teixidó, N., Vinãs, I., 2003. Effect of water activity and temperature on germination and growth of Penicillium digitatum, P. italicum and Geotrichum candidum. J. Appl. Microbiol. 94, 549–554. Sautour, M., Mansur, C.S., Divies, C., Bensoussan, M., Dantigny, P., 2002. Comparison of the effects of temperature and water activity on growth rate of food spoilage moulds. J. Ind. Microbiol. Biotechnol. 28, 311–315. Schloss, P.D., Westcott, S.L., Ryabin, T., Hall, J.R., Hartmann, M., Hollister, E.B., Lesniewski, R.A., Oakley, B.B., Parks, D.H., Robinson, C.J., Sahl, J.W., Stres, B., Thallinger, G.G., Van Horn, D.J., Weber, C.F., 2009. Introducing mothur: opensource, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–7541. Shannon, C.E., Weaver, W., 1963. The Mathematical Theory of Communication. University of Illinois Press, Urbana. Wang, Q., Garrity, G.M., Tiedje, J.M., Cole, J.R., 2007. Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267. Yoo, J.Y., Kim, H.G., Kim, W.J., 1998. Physicochemical and microbiological changes of traditional meju during fermentation in Kangweondo area. Korean J. Food Sci. Technol. 30, 908–915.
