Contrasted host specificity of gut and endosymbiont bacterial communities in alpine grasshoppers and crickets

Abstract Bacteria colonize the body of macroorganisms to form associations ranging from parasitic to mutualistic. Endosymbiont and gut symbiont communities are distinct microbiomes whose compositions are influenced by host ecology and evolution. Although the composition of horizontally acquired symbiont communities can correlate to host species identity (i.e. harbor host specificity) and host phylogeny (i.e. harbor phylosymbiosis), we hypothesize that the microbiota structure of vertically inherited symbionts (e.g. endosymbionts like Wolbachia) is more strongly associated with the host species identity and phylogeny than horizontally acquired symbionts (e.g. most gut symbionts). Here, using 16S metabarcoding on 336 guts from 24 orthopteran species (grasshoppers and crickets) in the Alps, we observed that microbiota correlated to host species identity, i.e. hosts from the same species had more similar microbiota than hosts from different species. This effect was ~5 times stronger for endosymbionts than for putative gut symbionts. Although elevation correlated with microbiome composition, we did not detect phylosymbiosis for endosymbionts and putative gut symbionts: closely related host species did not harbor more similar microbiota than distantly related species. Our findings indicate that gut microbiota of studied orthopteran species is more correlated to host identity and habitat than to the host phylogeny. The higher host specificity in endosymbionts corroborates the idea that—everything else being equal—vertically transmitted microbes harbor stronger host specificity signal, but the absence of phylosymbiosis suggests that host specificity changes quickly on evolutionary time scales.


Ensifera
Supplementary Figure 4. Relative read counts of endosymbionts in different species and different sex.The plot depicts the relative read counts (Y-axis) of the samples in different host species and sex (X-axis).The lower and upper hinges correspond to the first and third quartiles (the 25th and 75th percentiles).The upper whisker extends from the hinge to the largest value no further than 1.5 * IQR from the hinge (where IQR is the inter-quartile range, or distance between the first and third quartiles).The lower whisker extends from the hinge to the smallest value at most 1.5 * IQR of the hinge.Data beyond the end of the whiskers are called "outlier" points and are plotted individually.5. Alpha-diversity estimates.The plot depicts alpha diversity (Y-axis, Chao1 metric) of the samples in different host species (X-axis).The lower and upper hinges correspond to the first and third quartiles (the 25th and 75th percentiles).The upper whisker extends from the hinge to the largest value no further than 1.5 * IQR from the hinge (where IQR is the inter-quartile range, or distance between the first and third quartiles).The lower whisker extends from the hinge to the smallest value at most 1.5 * IQR of the hinge.Data beyond the end of the whiskers are called "outlier" points and are plotted individually.

E. Statistics
Supplementary Figure 11.Beta-diversity analysis with Jaccard beta-diversity metric.The figure illustrates (panels A-B) and report statistical measures (panel C) of host specificity.Panel A-B are multidimensional representations of microbiome composition (NMDS axes based on Jaccard dissimilarities between samples) for endosymbiont (panel A) and gut symbiont communities (panel B).Panel C depicts the strength of the effect (Y-axis) of different host factors (X-axis) on microbiota composition (PERMANOVA model on betadiversity).The "host species" effect measures the strength of host specificity at the species level.The asterisk refers to the level of significance of the corresponding factor in the PERMANOVA models.
. Sampling campaign design.A) The plot illustrates the distribution of samples from different host species in different sampling sites along the elevational gradient.B) Map of the sampling sites.phylogeny.Phylogenies of ASVs inferred from partial 16S sequences using a backbone phylogeny using representative Wolbachia full 16S sequences.ASVs from the metabarcoding data is represented in brown while full 16S sequences from genome assemblies are represented with the other colors (see legend).

3 .
Taxonomic composition of the samples.The plot depicts the relative read counts (Y-axis) of the samples (X-axis) for both Caelifera (right panel) and Ensifera (left panel).Taxonomic composition at the Family level (within Orders) is provided.
read counts of the most dominant endosymbiont ASV.The plot depicts the distribution of the relative read counts (Y-axis) of the dominant ASV in each sample samples for different endosymbionts (left and right panels).The lower and upper hinges correspond to the first and third quartiles (the 25th and 75th percentiles).The upper whisker extends from the hinge to the largest value no further than 1.5 * IQR from the hinge (where IQR is the inter-quartile range, or distance between the first and third quartiles).The lower whisker extends from the hinge to the smallest value at most 1.5 * IQR of the hinge.Data beyond the end of the whiskers are called "outlying" points and are plotted individually.-diversity analysis on unrarefied data.The figure illustrates (panels A-B) and report statistical measures (panel C) of host specificity.Panel A-B are multidimensional representations of microbiome composition (NMDS axes based on Bray-Curtis dissimilarities between samples) for endosymbiont (panel A) and gut symbiont communities (panel B).Panel C depicts the strength of the effect (Y-axis) of different host factors (X-axis) on microbiota composition (PERMANOVA model on beta-diversity).The "host species" effect measures the strength of host specificity at the species level.The asterisk refers to the level of significance of the corresponding factor in the PERMANOVA models -diversity analysis with Aitchison beta-diversity metric.The figure illustrates (panels A-B) and report statistical measures (panel C) of host specificity.Panel A-B are multidimensional representations of microbiome composition (PCoA axes based on Aitchison dissimilarities between samples) for endosymbiont (panel A) and gut symbiont communities (panel B).Panel C depicts the strength of the effect (Y-axis) of different host factors (X-axis) on microbiota composition (PERMANOVA model on betadiversity).The "host species" effect measures the strength of host specificity at the species level.The asterisk refers to the level of significance of the corresponding factor in the PERMANOVA models The figure depicts the strength of the effect (Y-axis) of different host factors (X-axis) on microbiota composition (PERMANOVA model on beta-diversity) when permutation are constrained by sampling sites.The "host species" effect measures the strength of host specificity at the species level.The asterisk refers to the level of significance of the corresponding factor in the PERMANOVA models.Different panel corresponds to different beta-diversity metrics.

Supplementary Table 5. Effect of host species and Sex on endosymbiont relative read count.
Table depicts the results of ANOVA tests for different subset of the data.

Supplementary Figures Supplementary Figure 1
Table depict mean statistics (n=100 repetition) of PERMANOVA models (Bray Curtis metric) run for endosymbionts and putative gut symbionts for balanced sampling (4 individuals in 15 species).