Larvae and sample collection
Bait Galleria mellonella larvae were purchased from Anaconda reptiles (Kontich, Belgium) and research-grade Galleria mellonella larvae, grown without antibiotics and hormones, were a gift from Trularv™ (BioSystems™, Devon, U.K.). Upon arrival, the larvae were stored at 4 °C and used within 7 days. Samples from the skin, faeces, fat body and haemolymph from 12 bait and 12 research-grade larvae were obtained after one day of individual incubation in the dark at 37 °C.
DNA extraction and bacterial enrichment
The PowerFecal® DNA isolation kit (with Inhibitor Removal Technology®) was used according to the instructions of the manufacturer.
The isolated DNA samples were diluted 10-fold and used to determine bacterial load by qPCR, using the StepOnePlus real time qPCR system (Applied Biosystems) and SYBR® Green chemistry (PowerUp™ Sybr® Green Master Mix, Applied Biosystems). Primers used were 338F (ACTCCTACGGGAGGCAGCAG) and 518R (ATTACCGCGGCTGCTGG) with the followingcycling program: 3 min at 95 °C; 40 cycles of 1 min at 95 °C, 40 s at 56 °C and 40 s at 72 °C . Based on the difference in Ct-value, an estimation of concentration difference can be made based on the 2–∆∆Ct method.
Illumina MiSeq 16S rRNA amplicon sequencing
The primers used for Illumina MiSeq sequencing were based on the previously described 515F-806R primers and altered for dual-index paired-end sequencing, as described by Kozich et al. (2013) [20, 21]. Briefly, each DNA sample was subjected to dual barcoded PCR, amplifying the V4 region of the 16S rRNA gene using Phusion High-Fidelity DNA polymerase (New England Biolabs, USA). PCR products were purified by the Agencourt AMPure XP magnetic bead capture kit (Beckman Coulter, Suarlee, Belgium), and quantified using the Qubit® 3.0 fluorometer. The library was prepared by pooling all PCR samples in equimolar concentration and loaded onto a 0.8% agarosegel. The product was purified by gel extraction using the Nucleospin® Gel and PCR clean-up (Machery-Nagel). The purified library concentration was determined with the Qubit® 3.0 fluorometer and diluted to a final concentration of 2 nM. The library was denatured with 0.2 N NaOH (Illumina), diluted to 6 pM and spiked with 10% PhiX control DNA (Illumina). The library was loaded onto the flow cell of the v2 chemistry MiSeq reagent kit (paired-end dual indexing sequencing; 2 × 251 bp kit; Illumina, San Diego, California, USA) on the MiSeq Desktop sequencer (M00984, Illumina) at the Centre of Medical Genetics, University of Antwerp, Belgium.
Sequence processing and biostatistical analysis
Raw sequencing reads were filtered and denoised using the DADA2 (Divisive Amplicon Denoising Algorithm 2) pipeline (v 1.1.6), as described in . The DADA2 method is a denoising algorithm that infers the set of most specific biological variants (called amplicon sequence variants (ASVs)) that are not the result of sequencing errors. In short, paired reads were filtered by excluding reads with more than two expected errors and reads that contained undetermined bases. Based on a visual inspection of the quality score profiles, trimming was done by removing first 12 nucleotides on forward and reverse strand. Next, DADA error correction was applied using the error model constructed by alternation of sample inference and error rate estimation until convergence. Forward and reverse reads were then merged into contigs. At this point, chimeras were removed. Taxonomic annotation from the kingdom to the genus level was then assigned to the remaining ASVs, making use of the EzBioCloud 16S rRNA reference database (version mtp1.5, update 2018.05). Finally, ASVs classified as Archaea, Eukarya, chloroplasts or mitochondria were removed. Secondly an alternative analysis was performed containing also non-bacterial ASVs.
The resulting ASV table was imported and analysed in R, using the in-house developed package tidyamplicons (www.github.com/swittouck/tidyamplicons), ggplot2 (v 2.1.0) , and the vegan package (v 2.3–5) . Quality control was performed as described in the Result section. Observed ASV-richness and the inverse Simpson index calculated on the non-normalized read count data were used as alpha-diversity indices. The relative abundances of the top 14 ASVs were plotted to assess the bacterial community composition.