A Bioinformatics Guide to Plant Microbiome Analysis

Abstract

Recent evidence for intimate relationship of plants with their microbiota shows that plants host individual and diverse microbial communities that are essential for their survival. Understanding their relatedness using genome-based and high-throughput techniques remains a hot topic in microbiome research. Molecular analysis of the plant holobiont necessitates the application of specific sampling and preparatory steps that also consider sources of unwanted information, such as soil, co-amplified plant organelles, human DNA, and other contaminations. Here, we review state-of-the-art and present practical guidelines regarding experimental and computational aspects to be considered in molecular plant–microbiome studies. We discuss sequencing and “omics” techniques with a focus on the requirements needed to adapt these methods to individual research approaches. The choice of primers and sequence databases is of utmost importance for amplicon sequencing, while the assembly and binning of shotgun metagenomic sequences is crucial to obtain quality data. We discuss specific bioinformatic workflows to overcome the limitation of genome database resources and for covering large eukaryotic genomes such as fungi. In transcriptomics, it is necessary to account for the separation of host mRNA or dual-RNAseq data. Metaproteomics approaches provide a snapshot of the protein abundances within a plant tissue which requires the knowledge of complete and well-annotated plant genomes, as well as microbial genomes. Metabolomics offers a powerful tool to detect and quantify small molecules and molecular changes at the plant–bacteria interface if the necessary requirements with regard to (secondary) metabolite databases are considered. We highlight data integration and complementarity which should help to widen our understanding of the interactions among individual players of the plant holobiont in the future.

Differences in the Endophytic Microbiome of Olive Cultivars Infected by Xylella fastidiosa across Seasons

“…Strategies to study the plant microbiome compositions rely on the isolation and identification of cultivable microorganisms (cultivation-dependent), or massive sequencing (cultivation-independent) [ 22 , 23 , 24 ]. The majority of the currently available studies rely on the analysis of next generation sequencing (NGS) datasets from 16S ribosomal RNA gene (16S rRNA) sequences from bacteria or fungi (internal transcribed spacer, ITS) [ 25 ]. However, information on the whole microbiome can be also obtained through whole metagenome shotgun sequencing (WMSS) [ 26 , 27 ], a strategy that allows gathering microbial data at very high depth.…”

Deciphering the Omics of Plant-Microbe Interaction: Perspectives and New Insights

“…Thus, plant microbiome deciphering needs large scale sequencing coverage along with a replication of experiments for robust analysis, and substantial computational and financial support [ 92 , 93 ]. Moreover, the interpretation of data on RNA, microbial DNA, and protein sequence gets hampered due to reduced rates in the high-confidence annotation.…”

Optimization of the second internal transcribed spacer (ITS2) for characterizing land plants from soil

“…Considering some previous studies have suggested that read abundance cannot reliably be used as a proxy for the relative natural abundance of plants in a sample (e.g., [25][26][27][28][29][30]), we compared the taxonomic composition observed when total read counts and total sequence counts were used to generate TAC. In this study, the most appropriate sample for this comparison would be the pooled positive control, given angiosperm, fern, gymnosperm and moss DNA were pooled for sequencing in equal amounts.…”