基于宏基因组学的不同陈化时间烟草源功能微生物筛选

Screening of tobacco-derived functional microorganismswith different aging time based on metagenomics

利用宏基因组学解析云南烟叶在不同陈化时间表面微生物群落结构及功能基因演替,跟踪烟叶陈化过程中的中性香味成分动态变化,分析微生物、酶基因与中性香味成分的相关性,并指导筛选烟草源功能微生物。结果表明:在烟叶陈化第3、6、9和12个月时,其表面优势菌属分别为鞘氨醇单胞菌属(Sphingomonas)、肠杆菌属(Enterobacte)、泛菌属(Pantoea)和不动杆菌属(Acinetobacter);陈化过程中烟叶的中性香味成分如苯甲醇、苯乙醛、2-乙酰基吡咯、茄酮、大马酮、巨豆三烯酮等总体呈增长趋势,糠醛和β-环柠檬醛则呈现先增加后降低的趋势,烃类化合物含量呈下降趋势;克雷伯菌属(Klebsiella)与β-大马酮、巨豆三烯酮和茄酮等呈显著正相关,不动杆菌属(Acinetobacter)与2-乙酰基呋喃,芳樟醇、巨豆三烯酮呈显著正相关,大部分碳水化合物活性酶与苯乙醛、苯甲醛、糠醇和西柏烯等成分呈负相关,多数糖苷酶与中性香味成分呈正相关;在烟叶陈化过程中共筛选得到75株微生物,微生物种类及其功能与宏基因组分析结果基本吻合,说明宏基因组分析结果可以指导微生物筛选工作,增强筛选目的性,提高筛选效率。

The community structure and functional gene succession of surface microorganisms in Yunnan tobacco leaves at different aging stages were analyzed based on metagenomics. The changes of neutral aroma components during the aging of tobacco leaves were traced. The correlation between microorganisms, enzyme gene and neutral aroma components was explored, and a screening method for tobacco-derived functional microorganisms was established. The results showed at the 3rd, 6th, 9th and 12th month of aging, the dominant genera were Sphingomonas, Enterobacter, Pantoea, and Acinetobacter,respectively. The neutral aroma components in tobacco leaves such as benzyl alcohol, phenylacetaldehyde, 2-acetylpyrrole, solanone, damascenone and megastigmatrienone had an increasing trend. Furfural and β-cyclocitral had a first increase and then decrease trend. The content of hydrocarbons decreased. Klebsiella had a significant positive correlation with β-damascenone, megastrienone and solanone. Acinetobacter had a significant positive correlation with 2-acetylfuran, linalool and megastrienone. Phenylethylaldehyde, benzaldehyde, furfuryl alcohol and cypressene were negatively correlated with almost all carbohydrate synthase, and most glycosidase families were positively correlated with neutral aroma components. A total of 75 strains of microorganisms were screened during tobacco leaf aging, and the microbial types and functions were basically consistent with the results of metagenome analysis, indicating that the analysis results of metagenome could guide microbial screening, enhance the purpose of screening, and improve screening efficiency.