Offspring Microbiomes Differ Across Breeding Sites in a Panmictic Species

Abstract

High dispersal rates are known to homogenize host's population genetic structure in panmictic species and to disrupt host local adaptation to the environment. Long-distance dispersal might also spread micro-organisms across large geographical areas. However, so far, to which extent selection mechanisms that shape host's population genetics are mirrored in the population structure of the enteric microbiome remains unclear. High dispersal rates and horizontal parental transfer may homogenize bacterial communities between breeding sites (homogeneous hypothesis). Alternatively, strong selection from the local environment may differentiate bacterial communities between breeding sites (heterogeneous hypothesis). Furthermore, selection from age-specific environmental or physiological factors may differentiate the microbiome between juveniles and adults. Here, we analyzed the cloacal bacterial 16S rRNA gene of fledgling greater flamingos, Phoenicopterus roseus, across nine western Mediterranean breeding sites and four breeding seasons (n = 731) and adult birds (n = 27) from a single site. We found that fledgling cloacal microbiome, as measured by alpha diversity, beta diversity, the relative abundance of assigned sequence variants (ASVs) belonging to a phylum and genus composition within phylum, varied significantly between sampling sites and across time within site despite high adult dispersal rates. The spatio-temporal effects were stronger on individual ASV absence/presence than on ASV abundance (i.e., than on core microbiome composition). Spatial effects had a stronger effect than temporal effects, particularly on ASV abundance. Our study supports the heterogeneous hypothesis whereby local environmental conditions select and differentiate bacterial communities, thus countering the homogenizing effects of high-dispersing host species. In addition, differences in core microbiome between adult vs. fledgling samples suggests that differences in age-specific environmental and/or physiological factors result in differential selection pressure of core enteric microbiome between age classes, even within the same environment. In particular, the genus Corynebacterium, associated with both seasonal fat uptake and migration in previous studies, was much more abundant in high-dispersing fledglings than in more resident adults. To conclude, selection mechanisms that shape the host's genetic structure cannot be extended to the genetic structure of the enteric microbiome, which has important implications regarding our understanding of both host local adaptation mechanisms and enteric microbiome population genetics.

Keywords: Phoenicopterus roseus; dispersal; greater flamingos; gut microbiome; population differentiation.

FIGURE 1

Sampling locations of the nine greater flamingo breeding sites. Sample sizes are in the header of sampling unit name and the first number indicates the number of samples successfully sequenced and the second, the number of samples collected. Pie charts represent population level enteric microbiome composition of the six most dominant phyla, and numbers next to pie charts represent the relative abundance of ASV belonging to a phylum.

FIGURE 2

(A) Odds ratio (exponential of parameter estimates) of the GLM (with a Gamma distribution and log link function) of phylogenetic diversity according to sampling unit. The intercept (dotted black line) is fledgling samples from Camargue in 2015. Odds ratio values are displayed as well as significance relative to the intercept (^∗p = 0.05, ^∗∗p = 0.01, ^∗∗∗p < 0.001). (B) Boxplot and mean (red diamonds) of phylogenetic diversity according sampling unit. Data points are jittered to indicate sample size. The dashed red line separates adult samples from fledgling samples.

FIGURE 3

Principle coordinates analysis (PCoA) plots according to: sampling unit for PCoA axis 1 and 2 (A) and PCoA axis 1 and 3 (B) based on the weighted Unifrac distance; and sampling site for PCoA axis 1 and 2 (C) and PCoA axis 1 and 3 (D) based on the unweighted Unifrac distance. Squares represent centroids, and bars are standard errors.

FIGURE 4

Odds ratio (exponential of parameter estimates) of the GLM (with a Binomial distribution and logit link function) of the relative abundance of ASV belonging to phylum within individual according to sampling unit for Proteobacteria (A), Firmicutes (B), Actinobacteria (C), Bacteroidetes (D), Fusobacteria (E), and Synergistetes (F). The intercept (dotted black line) is fledgling samples from Camargue in 2015. Odds ratio values are displayed as well as significance relative to the intercept (^∗p = 0.05, ^∗∗p = 0.01, ^∗∗∗p < 0.001). The dashed red line separates adult samples from fledgling samples.

FIGURE 5

Genus composition with the five most common phyla Proteobacteria (a), Firmicutes (b), Actinobacteria (c), Bacteroidetes (d), and Fusobacteria (e) and the other phyla pooled together (f). Only genera with a frequency of at least 1% are represented. Synergistetes was not plotted since it was dominated by a single ASV. Numbers within barplot represent the relative abundance of each genus within the phylum. The dashed black line separates adult samples from fledgling samples.