Comparison of gizzard and intestinal microbiota of wild neotropical birds

<div><p>Gut bacterial communities have been shown to be influenced by diet, host phylogeny and anatomy, but most of these studies have been done in captive animals. Here we compare the bacterial communities in the digestive tract of wild birds. We characterized the gizzard and intestinal microbiota among 8 wild Neotropical bird species, granivorous or frugivorous species of the orders Columbiformes and Passeriformes. We sequenced the V4 region of the <i>16S rRNA</i> gene in 94 collected samples from 32 wild birds from 5 localities, and compared bacterial communities by foraging guild, organ, locality and bird taxonomy. <i>16S rRNA</i> gene-based sequencing data were examined using QIIME with linear discriminant analysis effect size (LEfSe) and metabolic pathways were predicted using PICRUSt algorism. We identified 8 bacterial phyla, dominated by Firmicutes, Actinobacteria and Proteobacteria. Beta diversity analyses indicated significant separation of gut communities by bird orders (Columbiformes vs. Passerifomes) and between bird species (<i>p</i><0.01). In lower intestine, PICRUSt shows a predominance of carbohydrate metabolism in granivorous birds and xenobiotics biodegradation pathways in frugivorous birds. Gizzard microbiota was significantly richer in granivorous, in relation to frugivorous birds (Chao 1; non-parametric t-test, <i>p</i><0.05), suggesting a microbial gizzard function, beyond grinding food. The results suggest that the most important factor separating the bacterial community structure was bird taxonomy, followed by foraging guild. However, variation between localities is also likely to be important, but this could not been assessed with our study design.</p></div

Beta diversity of bacterial communities in different organs of frugivorous and granivorous birds.

<p>A, B, C) Principal coordinates analysis (PCoA) of unweighted UniFrac distances. D, E F) Linear discriminatory analyses (LEfSe) of bacterial taxa discriminant of frugivorous and granivorous birds (LDA>3). Histogram showing OTUs that are more abundant in granivorous and frugivorous birds by gizzard, upper and lower intestine.</p

Alpha diversity of gut bacterial communities by frugivorous and granivorous birds in different organs.

<p>A, B and C) Bacterial community richness (Chao1 index) for the gizzard, upper and lower intestine. D, E and F) Relative abundances of phyla (%) present in the gizzard, upper and lower intestine. Different letters above boxplots indicate significant differences (non-parametric t-test ≤0.05).</p

Linear discriminatory analyses (LEfSe) comparing KEGG module predictions using PICRUSt in different organs from granivorous and frugivorous birds (LDA>2).

<p>Linear discriminatory analyses (LEfSe) comparing KEGG module predictions using PICRUSt in different organs from granivorous and frugivorous birds (LDA>2).</p

Beta diversity of gut bacterial communities by bird taxonomy in different organs.

<p>A, B, C) Principal coordinates analysis (PCoA) of unweighted UniFrac distances of bacterial communities by bird orders (Columbiformes and Passeriformes). D, E, F) PCoA of unweighted UniFrac distances of bacterial communities by bird species.</p

Additional file 2: of Can the intake of antiparasitic secondary metabolites explain the low prevalence of hemoparasites among wild Psittaciformes?

Figure S1. Locations of the sampled population at Rasa I., Palawan, Philippines, in the Indo-Malayan zoogeographical region. Figure S2. Locations of the sampled populations in New Caledonia, Australasian zoogeographical region. Figure S3. Locations of the sampled population in the Chatham Is., Australasian zoogeographical region. Figure S4. Locations of the sampled populations in New Zealand, Australasian zoogeographical region. Figure S5. Locations of the sampled populations in the Neotropical zoogeographical region. (PDF 1271 kb

Additional file 4: of Can the intake of antiparasitic secondary metabolites explain the low prevalence of hemoparasites among wild Psittaciformes?

Scripts and combined dataset to analyse the presence of hemoparasites in Psittaciformes. Analyses and the combined dataset for the effects of diet, habitat, climate, screening method (as factors) and species (as a random variable) on the presence of parasites in the studied individuals using a binomial General Lineal Mixed-Effects Model and model averaging based on Akaike information criterion (AIC) with R. Scripts for the 10-fold cross validation and the calculations of parasite detection probability are also provided. (TXT 34 kb

Additional file 1: of Can the intake of antiparasitic secondary metabolites explain the low prevalence of hemoparasites among wild Psittaciformes?

Table S1. Hemoparasites in wild Psittaciformes. Malaria parasites (Plasmodium), related intracellular haemosporidians (Haemoproteus and Leucocytozoon), the unicellular parasitic flagellate protozoans (Trypanosoma), and microfilaria reported in wild populations of Psittaciformes. The probability of detection for adults is based on a simulation (see Additional file 4) of the probability that the parasites will actually be detected given the sample size and an expected true prevalence based on the prevalences observed in wild Psittaciformes. The habitat and climate classification follow the references in Table 1. (XLSX 34 kb

Additional file 3: of Can the intake of antiparasitic secondary metabolites explain the low prevalence of hemoparasites among wild Psittaciformes?

Table S2. Main food items consumed by the Psittaciformes species in the localities where the blood parasite sampling was carried out. Details on the species, main food items and parts consumed are provided. The presence of secondary metabolites with antimalarial/general antiparasitic plant secondary metabolites, anthelmintic, antimicrobial, and antioxidant properties is indicated. Source references are provided. (XLSX 29 kb