Comprehensive microbiome and metabolome analyses reveal the physiological mechanism of chlorotic Areca leaves

Abstract

As an important economic crop in tropical areas, Areca catechu L. affects the livelihood of millions of farmers. The Areca yellow leaf phenomenon (AYLP) leads to severe crop losses and plant death. To better understand the relationship of microbes and chlorotic Areca leaves, microbial community structure as well as its correlation with differential metabolites was investigated by high-throughput sequencing and metabolomic approaches. High-throughput sequencing of the internal transcribed spacer 1 and 16S rRNA gene revealed that fungal diversity was dominated by Ascomycota and the bacterial community consisted of Proteobacteria as well as Actinobacteria. The microbiota structure on chlorotic Areca leaves exhibited significant changes based on non-metric multidimensional scaling analysis, which were attributed to 477 bacterial genera and 183 fungal genera. According to the results of the Kruskal-Wallis test, several potential pathogens were enriched on chlorotic Areca leaves. Further analysis based on metabolic pathways predicted by Phylogenetic Investigation of Communities by Reconstruction of Unobserved States revealed the metabolism of half-yellow leaves and yellow leaves microbiota were significantly elevated in amino acid metabolism, carbohydrate metabolism, glycan biosynthesis and metabolism, metabolism of cofactors and vitamins, partial xenobiotics biodegradation and metabolism. Furthermore, 22 significantly variable metabolites in Areca leaves were identified by ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry and statistical analysis. Moreover, we further investigated the correlation between the predominant microbes and differential metabolites. Taken together, the association between AYLP and microbiome of Areca leaves was explored from the microecological perspective by omics techniques, and these findings provide new insights into possible prevention, monitoring and control of AYLP in the future.