Bt和Bar基因转化对水稻不同组织生态位微生物群落组成及潜在功能影响

【目的】转Bt基因和Bar基因植物的微生态效应是环境安全评价的重要因素,但关于Bt基因和Bar基因转化引起的水稻基因型改变对水稻不同组织生态位微生物群落组成和潜在功能的影响还无系统研究。【方法】以转Bt基因和Bar基因水稻T1C-1及其亲本对照Minghui63为研究对象,基于细菌16S rRNA基因和真菌ITS高通量测序技术,分析抽穗期T1C-1和Minghui63根际土壤微生物以及根、茎、叶内生菌的群落结构和潜在功能。【结果】细菌和真菌群落多样性在水稻不同组织生态位之间发生显著变化,地下部分组织生态位(根际土壤和根系)微生物多样性显著高于地上部分(叶和茎)。T1C-1显著影响叶片内生真菌的香农指数和辛普森指数,而对茎和根的内生菌以及根际土壤微生物多样性无显著影响。叶片内生真菌曲霉菌属(Aspergillus)和篮状菌属(Talaromyces)相对丰度在T1C-1显著增加,推测其参与碳素代谢、能量代谢和转录作用酶合成等过程。T1C-1和Minghui63微生物群落关联网络分析表明,T1C-1的平均聚类系数和平均度显著高于Minghui63,因而T1C-1提高了相关微生物群落网络复杂程度。通过重建未观测状态对群落进行系统发育研究(phylogenetic investigation of communities by reconstruction of unobserved states,PICRUSt2),对叶片内生真菌功能酶基因进行功能预测,相对于Minghui63,T1C-1显著改变了碳素代谢、脂类代谢和能量代谢等途径。【结论】相较于根际土壤,叶片内生真菌的群落组成和潜在功能对T1C-1更敏感。尽管如此,T1C-1并未导致叶片内生真菌的多样性指数降低。为了更准确地评估转基因植物的微生态效应,我们需要加强对不同组织生态位内生菌多样性的关注。

Inferring microbial interaction networks based on consensus similarity network fusion

With the rapid accumulation of high-throughput metagenomic sequencing data,it is possible to infer microbial species relations in a microbial community systematically.In recent years,some approaches have been proposed for identifying microbial interaction network.These methods often focus on one dataset without considering the advantage of data integration.In this study,we propose to use a similarity network fusion(SNF)method to infer microbial relations.The SNF efficiently integrates the similarities of species derived from different datasets by a cross-network diffusion process.We also introduce consensus k-nearest neighborhood(Ck-NN)method instead of k-NN in the original SNF(we call the approach CSNF).The final network represents the augmented species relationships with aggregated evidence from various datasets,taking advantage of complementarity in the data.We apply the method on genus profiles derived from three microbiome datasets and we find that CSNF can discover the modular structure of microbial interaction network which cannot be identified by analyzing a single dataset.