Contribution of sample processing to gut microbiome analysis in the model Lepidoptera, silkworm Bombyx mori

Authors:
Open Access
Publisher website
Google Scholar
Abstract
Microbes that live inside insects play various roles in host biology, ranging from nutrient supplementation to host defense. Although Lepidoptera (butterflies and moths) are one of the most diverse insect taxa and important in natural ecosystems, their microbiotas are little-studied, and to understand their structure and function, it is necessary to identify potential factors that affect microbiome analysis. Using a model organism, the silkworm Bombyx mori, we investigated the effects of different sample types (whole gut, gut content, gut tissue, starvation, or frass) and metagenomic DNA extraction methodologies (small-scale versus large-scale) on the composition and diversity of the caterpillar gut microbial communities. High-throughput 16S rRNA gene sequencing and computational analysis of the resulting data unraveled that DNA extraction has a large effect on the outcome of metagenomic analysis: significant biases were observed in estimates of community diversity and in the ratio between Gram-positive and Gram-negative bacteria. Furthermore, bacterial communities differed significantly among sample types. The gut content and whole gut samples differed least, both had a higher percentage of Enterococcus and Acinetobacter species; whereas the frass and starvation samples differed substantially from the whole gut and were poor representatives of the gut microbiome. Thus, we recommend a small-scale DNA extraction methodology for sampling the whole gut under normal insect rearing conditions whenever possible, as this approach provides the most accurate assessment of the gut microbiome. Our study highlights that evaluation of the optimal sample-processing approach should be the first step taken to confidently assess the contributions of microbiota to Lepidoptera.
Funding Information
  • Max-Planck-Gesellschaft (CARS-18-ZJ0302)
  • Max-Planck-Gesellschaft (2020E10025)
  • Max-Planck-Gesellschaft (31970483)
  • Max-Planck-Gesellschaft (32022081)
  • Earmarked Fund for China Agriculture Research System (CARS-18-ZJ0302)
  • Earmarked Fund for China Agriculture Research System (2020E10025)
  • Earmarked Fund for China Agriculture Research System (31970483)
  • Earmarked Fund for China Agriculture Research System (32022081)
  • Agriculture Research System of China (CARS-18-ZJ0302)
  • Agriculture Research System of China (2020E10025)
  • Agriculture Research System of China (31970483)
  • Agriculture Research System of China (32022081)
  • National Natural Science Foundation of China (CARS-18-ZJ0302)
  • National Natural Science Foundation of China (2020E10025)
  • National Natural Science Foundation of China (31970483)
  • National Natural Science Foundation of China (32022081)

This publication has 63 references indexed in Scilit: