The healthy equine uterus harbors a distinct core microbiome plus a rich and diverse microbiome that varies with geographical location

Abstract

The goal of this study was to understand the composition and existence of the resident uterine microbiome in healthy mares and to establish the presence of a core microbiome for the healthy equine uterus. We analyzed the microbiomes of 35 healthy mares that are long-time residents of three farms in Oklahoma, Louisiana, and Australia as well as that of 19 mares purchased from scattered owners in the Southern Mid-Western states of the United States. Over 6 million paired-end reads of the V4 region of the 16S rRNA gene were obtained resulting in 19,542 unique Amplicon Sequence Variants (ASVs). ASVs were assigned to 17 known phyla and 213 known genera. Most abundant genera across all animals were Pseudomonas (27%) followed by Lonsdalea (8%), Lactobacillus (7.5%), Escherichia/Shigella (4.5%), and Prevotella (3%). Oklahoma and Louisiana samples were dominated by Pseudomonas (75%). Lonsdalea (28%) was the most abundant genus in the Australian samples but was not found in any other region. Microbial diversity, richness, and evenness of the equine uterine microbiome is largely dependent on the geographical location of the animal. However, we observed a core uterine microbiome consisting of Lactobacillus, Escherichia/Shigella, Streptococcus, Blautia, Staphylococcus, Klebsiella, Acinetobacter, and Peptoanaerobacter.

Figure 1

Rarefaction curves for all samples used for this study. Each curve is color coded based on the group it belongs to; Australia (n = 14), Oklahoma (n = 9), Louisiana (n = 12) and Dispersed (n = 19).

Figure 2

Box plot representing the alpha-diversity values for microbial communities recovered from endometrial lavage samples of healthy mares. The samples are grouped, and color coded according to their geographical origin (i.e., Oklahoma, Louisiana, Australia and Dispersed). Chao and Observed ASV metrices measure species richness while Shannon and Simpson indices measure evenness. ANOVA (Chao1 and Observed ASVs) and Kruskal–Wallis tests (Shannon and Simpson) were utilized to conduct between group comparisons.

Figure 3

Non-metric multidimensional scaling (NMDS) plots depicting the distribution of endometrial lavage samples based on their microbial composition (beta diversity). The samples are color coded based on their geographical origin. NMDS1 and NMDS2 values were calculated based on the Bray–Curtis Index. The conventional 95% confidence interval around the centroid of each grouping (based on its multivariate t-value distribution) is marked by the ellipses.

Figure 4

Hierarchical clustering dendrogram drawn at genus level, using Bray–Curtis Index as the distance measure and Ward’s method as the clustering algorithm. Samples from Australia, Oklahoma, Louisiana, and Dispersed animals are color coded based on their geographical origin.

Figure 5

Molecular Phylogenetic analysis of the endometrial microbial community recovered (represented by the most abundant 104 ASVs). The Maximum Likelihood method, based on Tamua-Nei model, was used to infer the evolutionary relationships. A set of probable tree topologies were inferred from a Maximum Composite Likelihood (MCL) pairwise distance matrix, using Neighbor-Join and BioNJ algorithms. The illustrated tree is the one with the highest log likelihood. All pertaining analyses were conducted using MEGA7.

Figure 6

Significant features or bio markers that are differentially abundant in the endometrial lavage samples when grouped according to their geographical origin. 92 consensus differentially abundant genera were identified using LEfSe and DESeq2 algorithms, the top 50 of them are illustrated in the figure in ascending order of their LDA score. The bars, representing individual genera are color coded to indicate the sample group (geographical origin) in which they are most abundant.

Figure 7

The microbial community structure and composition of endometrial lavage samples of mares belonging to Oklahoma, Louisiana, Australia, and Dispersed groups. Stacked bar graphs generated depict the relative abundance of the top 10 phyla (a) and genera (b) identified and grouped according to their geographical origin.

Figure 8

A four set Venn diagram illustrating the most prevalent bacterial genera identified in endometrial lavage samples from Australia, Oklahoma, Louisiana, and Dispersed animals (with a groupwise relative abundance > 0.1%). Eight bacterial genera (Lactobacillus, Escherichia/Shigella, Streptococcus, Blautia, Staphylococcus, Klebsiella, Acinetobacter, Peptoanaerobacter) in the intersection of all four sets, was defined as the core microbiome.