Chinese liquor is one of the well-known distilled spirits in the world, and it has a long history of thousands of years. Daqu is a fermentation starter and substrate complex used to initiate fermentation for the production of Chinese liquor. It is an important saccharifying and fermenting agent and has significant impact on the flavor of the product [1]. According to the aromas of distillate, Daqu is mainly categorized into three different types: Luzhou-flavor (strong-flavor), soy sauce-flavor, and light-flavor, which depend on different manufacture techniques [2]. Generally, Daqu was produced through solid fermentation of grain via a natural inoculation of microbial communities originated from production environment, and the process often involves three stages: shaping, ripening and drying [3].

A diverse microbial community is associated with the Daqu, and consists of various types of bacteria, yeasts and filamentous fungi. Therefore, Daqu can be considered as a complex system containing materials (wheat, barley and/or pea), microbial community, and abundant enzymes originating from the microbes [4,5]. Already, some research has revealed the microbial community in Daqu based on culture-dependent and culture-independent methods including polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and phospholipid fatty acid (PLFA) [3,6-8]. Zheng et al. [6] isolated and identified 190 microbial strains from Fen-Daqu by culture-dependent approach, which comprised 109 bacteria and 81 yeasts and moulds. Recently, the development of lipid- and nucleic acid-based profiling techniques has enabled the elucidation of microbial community structures in complex ecosystem, and has led to the discovery of new genes [9-11]. Unfortunately, knowledge of community structure does not necessarily provide useful information on functions such as metabolic capacity, population dynamics, and physiological responses to variable environmental conditions. Metaproteomics, also termed community proteomics, is the study of all proteins expressed at a given time in an ecosystem, and it provides an insight into cellular and community activity-information unavailable from any other approaches [12]. Microbial metaproteomics has been applied in diverse environments such as soil, marine, and human intestinal tract [13-16]. In this study, the proteins isolated from the Daqu extract were investigated based on metaproteomic method. To the best of our knowledge, this is the first report of metaproteome in Daqu. These results may aid the advancement of research on the function of Daqu and promote the technological development of Daqu manufacture.

Daqu sample

Daqu samples were collected from Xufu liquor brewing enterprise in Yibin city, Sichuan Province, China. Three matured Daqu blocks (having been stored for 3 months of maturation) were randomly selected from upper, middle and lower layers, respectively, in order to obtain an adequate representation. The samples collected from each layer were fully mixed and stored in sterile polyethylene bags at -20°C for further analysis.

Preparation of metaproteome from Daqu extract

The extract of Daqu was prepared according to Zhang et al. [17] with some modifications. Briefly, 5 g of Daqu sample was soaked in 10 ml of 50 mM acetate buffer (pH 4.2, containing 90 mM NaCl) for 12 h. The suspension was centrifuged twice (10000 g, 10 min) to remove the large particles. The supernatant was then filtered through a 0.45 μm filter (Sangon Biotech, Shanghai, China) and prepared for metaproteome extraction. The extracted proteins were treated with Clean-up Kit (BioRad, Hercules, CA, USA) according to the manufacturer’s protocols, and dissolved in lysis buffer (8 M urea, 2% CHAPS, 0.5% IPG buffer). The protein concentration was determined by using the BioRad Protein Assay Kit (BioRad) with BAS as a standard.

2D gel electrophoresis and protein identification

The protein sample was applied to immobilize pH gradient strips (18 cm, pH 3-10, BioRad) with a final concentration of 700 μg protein in 350 μl rehydration buffers. Isoelectric focusing (IEF) and SDS-PAGE were performed according to the method described by Zhang et al. [17]. After SDS-PAGE, the 2D gels were stained with 0.1% Coomassie blue R-250. Three parallel gels were consistent replicates, and the stained gels were scanned using Imagescanner (GE Healthcare).

The proteins spots were excised using gel plugs, transferred to Eppendorf tubes, then digested with 20 μl of 10 ng/μl proteomics sequencing grade trypsin at 37°C for 16 h and rehydrated in 500 μl of 50 mM NH₄HCO₃ (pH 8.0). Supernatants of 0.5 μl were spotted directly onto the MALDI plate, and samples were analyzed on the Applied Biosystem 4700 Proteomics Analyzer MALDI-TOF/TOF (Applied Biosystems, Framingham, MA) in positive ion reflector mode [18]. Mass spectra were obtained for each sample by accumulating of 700-4000 Da mass range. For the MS/MS spectra, 5 most abundant precursor ions per sample were selected for subsequent fragmentation, and 1000-1200 Da laser shots were accumulated per precursor ion. The criterion for precursor selection was a minimum S/N of 50. GPS Explorer (v2.0, Applied Biosystems) was used as an interface between the raw data from the mass spectrometer. Both MS/MS and MS data were used for the identification of proteins candidates in the NCBI database by using Mascot (Matrix Science) with the following selection criteria: NCBInr database, taxonomy of all entries, trypsin of the digestion enzyme, one missed cleavage site, parent ion mass tolerance at 100 ppm, MS/MS mass tolerance of 0.5 Da, carbamidomethylation of cysteine (global modification), and methionine oxidation (variable modification). The probability score (95% confidence interval) calculated by the software was used as criteria for correct identification [17,19]. In addition, given the complexity of Daqu sample, the mass spectra were firstly searched against the “all entries” database in NCBInr, then the Bacteria, Fungi, and “others” databases were separately selected to avoid the failed matching. After the comparison against NCBI’s “nr” database through BLAST, sequences could be classified by using the lowest common ancestor analysis based on Unipept database, which is a web application available at unipept.ugent.be.

Metaproteomic profile of Daqu extract was obtained by 2-DE and the representative map was shown in Figure 1. A total of 45 proteins spots were excised, and only 21 spots representing 20 proteins were successfully identified. This might be ascribed to the incomplete genome information available on environmental microbes [17]. A detailed analysis of this result showed that 17 spots representing 16 proteins originated from the secretion of bacteria, and yeasts (Table 1). Three proteins (spots 5, 6 and 21) originated from B. subtilis, and 3 proteins (spots 8, 9 and 17) originated from B. licheniformis were identified in Daqu sample. Previous reports demonstrated that Bacillus species including B. subtilis, B. licheniformis, and B. cereus were dominant in strong-flavor Daqu, and were frequently detected in Daqu [2,6]. The majority of Bacillus species secretes various hydrolytic enzymes and form heat-resistant spores, and the existence of such microbes may facilitate the conversion of starch into fermentable carbohydrates. In addition, Bacillus spp. produces nitrogenous flavor compounds such as diverse pyrazines, which may contribute to the Daqu flavor [2,5]. Nucleoside diphosphate kinase (spot 12), originating from Staphylococcus carnosus was identified in Daqu sample, and Staphylococcus was also identified in Daqu revealed by nested PCR-DGGE [2]. Generally, S. carnosus produces 3-methyl-1-butanol, 2-butanone, acetoin, and methyl-branched ketones, which may play an important role in liquor manufacture [20]. Two Chromosomal replication initiator proteins DnaA (spots 2 and 3) originating from Clostridium acetobutylicum was identified in Daqu extract. The Clostridium strains favorably ferment starch materials and typically produce a solvent mixture of acetone, butanol and ethanol [21]. Moreover, Clostridium was reported as important microorganism in the pit mud of Chinese liquor [22]. In addition, it should be noted that 2 proteins (ATP synthase subunit alpha and Elongation factor Ts), 1 protein (Cytochrome c-556), and 1 protein (Elongation factor 2) were identified from Nitrobacter winogradskyi, Agrobacterium tumefaciens and Neurospora crassa, respectively. Such strains were first identified in Daqu, and the functions of these microbes should be further elucidated.

Figure 1: Metaproteomic profile of Daqu extract. The identified proteins are indicated by arrows and numbers and listed in Table 1.

Table 1: Proteins identification in Daqu extract.

Yeasts are the most important group of microorganisms contributing to liquor quality in the solid-state fermentation process of Chinese liquor. In this study, three proteins (spots 7, 10 and 16) were determined to originate from S. cerevisiae, which was also detected in strong-flavor, soy sauce-flavor and light-flavor Daqu samples [6,23]. However, previous studies showed that the band density of S. cerevisiae was relatively weak in DGGE profiles, and only one strain of S. cerevisiae was obtained by culture-dependent method, suggesting that S. cerevisiae was not a dominant microbe in Daqu [6,24]. Generally, S. cerevisiae usually dominates in alcoholic fermentations due to its higher ethanol tolerance and ability to grow under strictly anaerobic conditions [6]. Chromosome transmission fidelity protein (spot 19), secreted by Schizosaccharomyces pombe was also detected in Daqu extract, implying potential function of S. pombe in liquor fermentation. Previous research demonstrated that the population of yeasts in Daqu was less than 100 CFU/g, and the number in mature Daqu was less than that in ripening period of Daqu. This may be that most yeasts had died after ripening process of Daqu [24].

Compared to the PCR-based data, the metaproteomic approach just identified a few fungal genera and some new genera in Daqu sample. This may be the limitations in metaproteocmic method, which requires enough proteomic and genomic information being available on the environmental microbes. Thus, alternate research approaches could help gain a comprehensive understanding of the microbial community and its function in Daqu.

In this study, metaproteomic approach was employed to investigate the ecosystem of Daqu, the starter culture of Chinese liquor, and this has not been reported prior to this study. A total of 17 proteins originated from the secretion of microbes were identified, and strains Nitrobacter winogradskyi, Agrobacterium tumefaciens, and Neurospora crassa were firstly identified in Daqu. Results presented in this study further enhance our understanding of the microbial community in Daqu, and the functions of the proteins from microbes in Daqu remains to be elucidated.

Chongde Wu and Rongqing Zhou designed the study and prepared the manuscript, Jingcheng Deng and Guiqiang He performed the experiment. All authors review and approved the final manuscript.

This work was financially supported by the National Natural Science Foundation of China (31301546), Fundamental Research Funds for the Central Universities (No. SCU2015D008), and Open Funding Project of Liquor Making Biological Technology and Application of Key Laboratory of Sichuan Province (NJ2014-12).