Development And Application Of Class Taxonomy-specific Primers For Quantitative Detecting Of Microflora Structure In Gujing Pit Mud Samples

Abundant microbial populations in the Gujing pit mud play a key role in the process of fermenting unique flavor liquor, but more comprehensive studies are needed to decipher and quantify microbial populations in the pit mud. This thesis takes advantage of 16 S r RNA gene sequences of Gujing pit mud to analysis diversity of microbial community structure, on the basis of which the novel class-specific primers were developed and optimized with the utilization of taxon-specific SNPs(Single Nucleotide Polymorphisms), then the compositional quantific ation of the Gujing microbial community was achieved through real-time quantitative PCR(q PCR).The diversity of microbial communities is closely related to environmental factors, and compositional variations could be large under different circumstances. The flavor of Gujing liquor is primarily determined by pit-mud microbial species, in which Clostridia class is regared as the main fragrance-producing bacteria with high concentrations. Phylogenetic analysis showed this class possesses the largest compleity in 16 S r DNA sequences and cannot be separated from several other classes in the phylogenetic tree, hypothetically there is an symbiosis relationship with other classes of microorganisms. The diversity index of 290 high-quality 16 S sequence analysis showed that these sequences contain sufficient information to uncover the actual bacterial composition in the pit mud.High-quality 16 S sequences of Gujing pit mud were subjected to Mafft multiple sequence alignment analysis, then taxon-specific SNPs were selected, followed by the employment of SAP(Simple Allele-discriminating PCR) technology to generate 10 pairs of class-specific primers. Using the pure 16 S DNA samples of each class as template, amplification specificity of each pair of primer was checked. For poor specificity primers, either adjustment of experimental conditions or re-design was conducted. Finally eight pairs of best class-specific primers were determined.Different mixing ratios of eight class templates were tested to further characterizing eight pairs of specific primers; the purpose of this screening was to confirm which class-specific primer(s) can be used for accurate quantification. The results found that, except the primers for the Betaproteobacteria class, the remaining seven pairs of primers had high sensitivity with different concentrations of mixed templates. Subsequently the seven pairs of primers were used to quantify the microbial composotions in the pit mud metagenome samples. The further results showed that except Alphaproteobacteria class, six pairs of class-specific primers(Actinobacteria, Gammaproteobacteria, Bacteroidia, Mollicutes, Bacilli, Synergistia) had promising q PCR performance for accurate quantification. This study not only quantify the contents of different classes in pit mud, but also found the wall samples of the Gujing pit mud had richer microbial population than the bottom samples. The method set-up in the thesis may have a significance applicationto rapidly quantify microflora and dynamically monitor microbial compositional transformation during liquor fermentation.