DOI: 10.5061/dryad.8cz8w9gnc
title: Data from: Microbiomes of a specialist caterpillar are consistent across different habitats but also resemble the local soil microbial communities

description: Background: Insect-associated microorganisms can provide a wide range of
 benefits to their host, but insect dependency on these microbes varies
 greatly. The origin and functionality of insect microbiomes is not well
 understood. Many caterpillars can harbor symbionts in their gut that
 impact host metabolism, nutrient uptake and pathogen protection. Despite
 our lack of knowledge on the ecological factors driving microbiome
 assemblages of wild caterpillars, they seem to be highly variable and
 influenced by diet and environment. Several recent studies have shown that
 shoot-feeding caterpillars acquire part of their microbiome from the soil.
 Here, we examine microbiomes of a monophagous caterpillar (Tyria
 jacobaeae) collected from its natural host plant (Jacobaeae vulgaris)
 growing in three different environments: coastal dunes, natural inland
 grasslands and riverine grasslands, and compare the bacterial communities
 of the wild caterpillars to those of soil samples collected from
 underneath each of the host plants from which the caterpillars were
 collected. Results: The microbiomes of the caterpillars were dominated by
 Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes. Only 5% of
 the total bacterial diversity represented 86.2% of the total caterpillar’s
 microbiome. Interestingly, we found a high consistency of dominant
 bacteria within the family Burkholderiaceae in all caterpillar samples
 across the three habitats. There was one amplicon sequence variant
 belonging to the genus Ralstonia that represented on average 53% of total
 community composition across all caterpillars. On average, one quarter of
 the caterpillar microbiome was shared with the soil. Conclusions: We found
 that the monophagous caterpillars collected from fields located more than
 100 kilometers apart were all dominated by a single Ralstonia. The
 remainder of the bacterial communities that were present resembled the
 local microbial communities in the soil in which the host plant was
 growing. Our findings provide an example of a caterpillar that has just a
 few key associated bacteria, but that also contains a community of low
 abundant bacteria characteristic of soil communities.
description: Study sites and sample
 collection We
 selected three characteristic habitats in The Netherlands in which ragwort
 plants and cinnabar moths occur in their native range: coastal dunes
 (Meijendel), inland natural grasslands (Veluwe) and riverine grasslands
 (Wageningen) and sampled in three localities within each habitat. At each
 locality, ten <i>Jacobaeae vulgaris </i>plants on which
 <i>Tyria jacobaeae</i> caterpillars were feeding were selected
 (SI Figure S1). Plants were located at a distance
 of at least 10 m to each other (except for two sampling localities in
 riverine grasslands where the smallest distance between two plants was 8.3
 and 9.2 m). Around the stem of each plant, five soil samples from the top
 5 cm layer were taken using a 20 cm soil borer with 2 cm diameter and
 pooled together. Caterpillars collected from each individual plant were
 kept together (with a minimum of 3 and a maximum of 10 caterpillars
 collected per plant). All samples were stored in a cooler with ice until
 processing in the laboratory on the same day. Fresh weight of each
 individual caterpillar was recorded (SI Figure
 S2; SI Table S1). All caterpillars
 were surface sterilized by dipping them for 30 seconds in the following
 solutions: 70% ethanol, 2.0% bleach, and then rinsed twice with autoclaved
 demineralized water. Caterpillars were surface sterilized to enrich the
 samples for gut rather than surface microbes while leaving gut microbes
 intact [20]. Both caterpillar and soil samples were stored at -20 °C until
 further processing. Caterpillar samples were lyophilized prior to DNA
 extractions.  DNA extraction and library
 preparation To
 obtain a representative sample of caterpillars feeding on one plant, DNA
 was extracted collectively from three homogenized caterpillars, from
 approximately 10 mg of dry, lyophilized sample. In total, 270 caterpillars
 were used in this study (9 study locations x 10 plants x 3 caterpillars
 per sample). Extractions were performed using the MP Biomedicals FastDNA™
 Spin Kit (MP Biomedicals, Solon, Ohio, USA) following the manufacturer’s
 protocol with the following modifications. Samples homogenized with Cell
 Lysis Solution in the FastPrep® Instrument (MP Biomedicals) for 20 seconds
 (speed setting of 6.0) were incubated at room temperature for 1 hour. An
 extra washing step was included, and the final eluted DNA was additionally
 precipitated prior further purification using standard ethanol
 precipitation method with potassium acetate. From approximately 0.35 g of soil
 samples, DNA was extracted from 90 samples using DNeasy PowerSoil Kit DNA
 (Qiagen, Hilden, Germany) following the manufacturer’s protocol.
 Approximately 10 ng of
 template DNA was used for PCR using primers 515FB [21] and 806RB [22]
 targeting the V4 habitat of the 16S rRNA gene [23]. The PCR mixture (25
 µl) contained 12.5 µl Phusion Flash High Fidelity PCR Master Mix (Thermo
 Scientific), 1.25 µl of each of the primers (10 µM). The conditions were
 45 s at 98 °C, followed by 30 cycles for caterpillars and 25 for soil
 samples of 98 °C for 5 s, 55 °C for 5 s, and 72 °C for 10 s with a final
 extension of 1 min at 72 °C. The PCR products were purified using
 Agencourt AMPure XP magnetic beads (Beckman Coulter, Brea, CA, USA).
 Adapters and barcodes were added to samples using Nextera XT DNA library
 preparation kit sets A-B (Illumina, San Diego, CA, USA). The final PCR
 product was purified again with AMPure beads, verified using agarose gel
 electrophoresis and quantified with a Nanodrop spectrophotometer (Thermo
 Scientific, Hudson, NH, USA) before equimolar pooling. Separate libraries
 were prepared for bacterial communities derived from caterpillar and soil
 samples (96 samples per library) including extraction negatives. Libraries
 were sequenced at McGill University and Genome Quebec Innovation
 Center. Sequence
 processing Raw
 reads were processed into ASVs (amplicon sequence variants) using the
 DADA2 pipeline [24], and taxonomic identification was performed by
 querying against the SILVA database with SINA classifier [25]. Reads that
 could not be assigned to Bacteria (i.e. Archaea, Eukaryotes, mitochondria,
 chloroplast, and unidentified) and all the bacterial ASVs present in the
 extraction negatives were excluded. The percentage of mitochondria and
 chloroplast reads was variable between samples, as it is often reported in
 insect gut microbiome studies [26], but did not significantly differ
 between localities or regions (SI Figure S2). Caterpillar and soil
 datasets were filtered separately due to their inherent differences in
 bacterial diversity. Only samples with sequencing depth ranging from five
 times more to five times less than the mean sequencing depth of
 caterpillar or soil samples were kept for further analysis. To explore
 general patterns of bacterial diversity among samples, the caterpillar and
 soil datasets were resampled to the lowest sequencing depth of 3,849 and
 13,731 reads, respectively. This resulted in removing three caterpillar
 samples (one from each habitat); while all soil samples were kept. The
 combined rarefied datasets resulted in 1,570,653 reads assigned to 41,089
 bacterial ASVs, of which 11,685 ASVs were present in high abundance
 (&gt;0.1% relative abundance). Microbiome analysis
 Alpha diversity for
 caterpillar and soil was assessed on the rarefied datasets by calculating
 the estimated species richness, Shannon diversity (the exponential of
 Shannon entropy), and Simpson diversity (the inverse Simpson
 concentration) [27], using the <i>iNEXT</i> R package [28].
 These indices are based on sample-size interpolation and extrapolation
 sampling curves [29], and represent the diversity estimates for rarefied
 and extrapolated samples with respect to the number of samples within
 localities. The estimated diversity was compared between habitats using
 the nonparametric Wilcoxon test with pairwise adjusted (Holm) p-values.
 Because caterpillars in the natural populations varied in size (see
 SI Table S1 and Figure S3 for average weights),
 to assess potential associations between the fresh biomass of caterpillars
 and their microbial species diversity or community composition, we used
 the Spearman rank correlation coefficient, and multivariate GLMs (see
 method description below), respectively. Moreover, to test whether spatial
 distribution of the sampled localities had an effect on the structure of
 bacterial communities in caterpillars, we computed a Mantel test
 correlation between the distance among localities in kilometers,
 calculated with the <i>geosphere</i> R package [30] on the
 geographic coordinates, and the Bray-Curtis dissimilarity matrix bacterial
 composition of caterpillars. The rarefied relative abundance data were
 squared-root transformed and Wisconsin double-standardized before the
 calculation of the Bray-Curtis dissimilarity matrix using the
 <i>vegan</i> R package [31]. This standardization scales the
 variability of different samples to each other. To display differences in
 microbiome composition of caterpillar and soil samples among localities
 within the three habitats, we generated Principal Coordinates Analysis
 (PCoA) ordination plots using the <i>ape</i> R package [32],
 using the squared-root transformed and Wisconsin double-standardized data.
 To reduce the influence of taxa present in few samples to the overall
 community composition, only ASVs present in at least three caterpillar or
 soil samples with a relative abundance higher than 0.1% in each dataset
 were included in the PCoA. The homogeneity of dispersion of the microbiome
 data was tested using <i>betadisper</i> function in
 <i>vegan</i> R package, and for both caterpillars and soil in
 the nine localities within the three habitats, data were overdispersed. We
 recognize that distance-based approaches can perform poorly when the data
 presents strong mean-variance relationships [33], therefore we used it
 only as a means to visualize differences in microbiomes. To assess caterpillar and soil
 microbiome community differences between localities and within habitats,
 we used a multivariate model-based approach [34], using the
 <i>mvabund</i> R package [35]. The microbiome structure of
 caterpillars or soil within locations or habitats was tested in separate
 models. We used a GLM with negative binomial distribution and a log-link
 function to account for the overdispersion of the data. In the
 multivariate GLM, a model was fit to each ASV and the log-likelihood ratio
 (LR) of each model was summed to create an overall sum-of-LR [34].
 Examination of the residual plots from the models showed no clear patterns
 indicating that the negative binomial GLM model was appropriate.
 Significance of the models was evaluated using 999 resampling iterations
 with PIT-trap resampling [36]. In addition, a linear discriminant analysis
 coupled with effect size measurements (LEfSe) based on Wilcoxon sum-rank
 test [37] was used to screen for differentially abundant bacteria at any
 taxonomic level among the three habitats.