摘要
利用白云岩喀斯特土壤微生物16S rRNA V4及ITS1区的高通量测序数据,分析土壤微生物群落结构特征。基于PICRUSt算法预测土壤微生物群落功能基因组,应用皮尔逊相关系数解析土壤性质与土壤微生物群落多样性及代谢通路的相关性。结果显示:白云岩喀斯特土壤微生物主要分布于15个菌门,其中以变形菌门(Proteobacteria)、酸杆菌门(Acidobacteria)、放线菌门(Actinobacteria)、子囊菌门(Ascomycota)、担子菌门(Basidiomycota)和接合菌门(Zygomycota)为最主要的优势菌门。基于PICRUSt功能基因预测,共获得6208个同源功能基因(KEGG Orthology),富集于311条代谢通路(metabolism pathway)。其中与氨基酸代谢、碳水化合物代谢等有关的基因在种类和数量上都占预测功能基因中的绝对优势。相关性分析表明:土壤微生物多样性与土壤性质间存在相关性,尤其以土壤微生物多样性与Emg^2+间相关性最为显著。61条代谢通路与土壤交换钙(ECa^2+)、土壤有机碳(SOC)、土壤总磷(STP)、土壤总钾(TK)、pH以及土壤交换镁(Emg^2+)相关。Emg^2+与包括精氨酸和脯氨酸代谢、丙酮酸代谢在内的31条代谢通路显著正相关。
The composition of soil microbial community was analyzed by using the high throughput sequencings amplified by the 16S rRNA V4 and ITS1 of soil metagenome.Using the algorithm of PICRUSt,we predicted the functional genome of soil microbial community.The relationship between the soil properties of karst rocky desertification with the diversity of soil microbial community,as well as metabolism pathways was analyzed by Pearson's correlation coefficient.Results:There were 15 phyla bacteria mainly distributed in the soil,which included Proteobacteria,Acidobacteria,Actinobacteria,Ascomycota,Basidiomycota and Zygomycota.6208 KEGG Orthology enriching in 311 metabolism pathways were predicted by PICRUSt analysis,which related with amino acid metabolism,carbohydrate metabolism.The ralative analysis found that the correlation existed between the diversity of soil microbial community and soil properties,especially the significantly correlation between the diversity of soil microbial community and Emg^2+.Soil ECa^2+,SOC,STP,TK,pH and Emg^2+were correlated with 61 KEGG pathway.Emg^2+was positively correlated with 31 metabolic pathways,including arginine and proline metabolism and pyruvate metabolism.
作者
唐婧
李欲轲
何馨竹
汤晓辛
TANG Jing;LI Yuke;HE Xinzhu;TANG Xiaoxin(The Labrary of Plant Physiology and Development in Guizhou Province/School of Life Science,Guizhou Normal University,Guiyang,Guizhou 550001,China)
出处
《贵州师范大学学报（自然科学版）》
CAS
2020年第5期20-28,共9页
Journal of Guizhou Normal University：Natural Sciences
基金
贵州省科技合作项目(黔科合LH字[2016]7208号)
贵州省重点实验室项目(黔科合计Z字[2011]4005号)
教育部长江学者和创新团队发展计划资助(PCSIRT-1227)
贵州师范大学博士科研资助项目(GZNUD[2017]1)。
作者简介
唐婧(1983-),女,博士,高级实验师,研究方向:微生物代谢调控,E-mail:eva-830827@163.com.
