Taxonomic and Functional Microbiome of Irrigation water and Ralstonia-Infected Ironwood (Casuarina equisetifolia) tree

Abstract

Microbiomics is an emerging field of research to identify the microbiota sharing the same niche, analyze the microbial genome, and unravel the interactions between the microbiome, host, and the environment, resulting in disease complexity. Also, the microbial community sharing the same niche maybe commensal, symbiotic, or pathogenic. With the advent of high-throughput DNA sequencing, independent of culture-based approaches allowed analysis of complex characteristics of the microbiome. This study focused on employing the next-generation sequencing platforms to investigate microbiomes of two ecosystems. The first ecosystem being the microbial structure and function of Hawaiian stream and spring water irrigation water systems, in addition to a technical comparison of employed technologies for microbial studies. The second ecosystem was to unravel the endophytic bacterial and fungal microbiota of ironwood trees, associated with Ralstonia infection, for deep insight into this complex and cryptic pathosystem. The need of studying the Hawaiian stream and spring water irrigation water systems is because of the water scarcity and a simultaneous need to increase food security. There has been a shift in agriculture irrigation systems from freshwater to alternative water sources such as reclaimed or recycled water. Irrigation water can be an important source of plant and food-borne pathogen contaminating plants and fresh produce, in addition to diverse unidentified bacterial consortia, agricultural waste, and antibiotic resistance genes (ARGs). The first objective of this study aimed to explore the bacterial microbiota from different irrigation water sources, and associated taro field water, from different geographical locations, in addition to investigating the function of the bacterial community discovered in the stream and spring water systems on Oahu, Hawaii. To analyze the bacterial community of 12 different irrigation water samples, high-quality DNA was isolated, sequenced for the V3-V4 region of 16S rRNA, full-length 16S rRNA, and shotgun metagenomic using Illumina iSeq100, Oxford Nanopore MinION, and Illumina NovaSeq100, respectively. Technical comparison of the short amplicon-based analysis provided a high resolution of taxonomic classification at the phylum level, whereas full 16S rRNA could validated the microbial classification of samples sequenced for short amplicon and shotgun metagenomic to the genus and species level. Functional comparison of stream and spring water revealed only 12% shared genes with a total of 95 ARGs with variable abundance. Therefore, this study provides a better understanding of the selection of appropriate sequencing platforms and pipelines to study irrigation water microbiome. Deciphering microbial communities and their functions will also be beneficial in the formulation of better disease management strategies. For the second ecosystem to be investigated, endophytic microbiota of the ironwood tree was the focus of the study. Ironwood is an important cultural and ecological component of the Island of Guam which has been subjected to different biotic (mainly Ralstonia infection) and abiotic stresses causing tree decline. However, little research is known about the complex Ironwood-Ralstonia pathosystem which could assist in managing the “disease complex”. The difficulty in studying this disease complex in the past was mainly the failure to isolate the causal agent, Ralstonia species, from symptomatic trees. Instead, other bacterial genera like Klebsiella and Pseudomonas were commonly isolated from infected trees. In addition, inconsistent wet wood symptoms, failure/inconsistent to prove Koch’s postulates, and incomplete knowledge about associated factors in disease development results in “disease complexity”. This study aimed to characterize the endophytic bacterial and fungal microbiota of 101 ironwood tree samples associated with Ralstonia infection and other factors, using amplicon-based approach targeting 16S rRNA and ITS gene region. Overall, Proteobacteria and Basidiomycota were the dominant bacterial and fungal phyla identified from the samples. Owing to the poorly annotated fungal database, a high number of reads remained unclassified for fungal classification. Whereas better resolution was obtained for bacterial genus classification, identifying Ralstonia in infected samples with higher accuracy. Samples infected with Ralstonia showed significantly lower bacterial richness and diversity, indicating ability of pathogens to impact endophytic microbial selection within the plant system. Furthermore, influence of Ralstonia was observed in affecting the fungal diversity and richness significantly in addition to Ganodermataceae infection and xylem conductivity. Based on this study, it is evident that deciphering the endophytic microbiota and knowing the role of associated biotic and abiotic factors can be advantageous to devise microbial bioformulations and develop efficient disease management strategies.