“Next Generation Sequencing” (NGS) has the potential to provide a rapid and inexpensive method to analyse the composition of microbial communities without the need to culture microorganisms. We evaluated the potential of using NGS combined with computational analyses and data visualisation for high-resolution analysis of microbial communities in an insect gut microbiome.
Diamondback moth (DBM), (Plutella xylostella L. (Lepidoptera: Plutellidae)) is a major insect pest that attacks and causes serious yield losses to Brassica crops. Bacteria in the gut of DBM were studied as model system. Baseline gut bacterial diversity within and between three insect populations were assessed using single laboratory population fed on cabbage and two field populations fed on cabbage and broccoli.
Polymerase chain reaction (PCR) amplification of the 16S ribosomal RNA V3 region was conducted and sequence diversity analysed using DGGE and Sanger sequencing. Bacterial diversity observed via the DGGE analysis was used to validate Ion Torrent semiconductor sequencing of 16S rRNA gene short partial sequences (∼200bp). Quantitative Insight Into Microbial Ecology (QIIME) and Operational taxonomic unit management mining tool (OTUMAMi) were used to perform the NGS analysis of approximately 1,500,000 reads. Sequence analysis, principle component analysis (PCA) and a species richness index were used to identify and quantify the bacterial diversity and relative abundance within and between DBM populations.
DGGE analysis identified Firmicutes and Proteobacteria as the major bacterial phyla and Lacotobacilliceae and Carnobacilliceae as the major families present in the gut of the three insect populations. NGS and statistical analyses identified both major and rare bacterial taxa at OTU levels and quantified their relative abundance in the three insect populations. Differences in composition of bacterial OTUs in three genera (Lactobacillus, Pseudomonas and Actinomycetales) were identified in field and laboratory-reared populations.
Results validated the use of NGS in community analysis and demonstrated that NGS can provide both greater resolution of species identity and an analysis on relative abundance compared with PCR-DGGE and Sanger sequencing.