Taxonomic and Functional Compositions of the Small Intestinal Microbiome in Neonatal Calves Provide a Framework for Understanding Early Life Gut Health

Abstract

A lack of information on the intestinal microbiome of neonatal calves prevents the use of microbial intervention strategies to improve calf gut health. This study profiled the taxonomic and functional composition of the small intestinal luminal microbiome of neonatal calves using whole-genome sequencing of the metagenome, aiming to understand the dynamics of microbial establishment during early life. Despite highly individualized microbial communities, we identified two distinct taxonomy-based clusters from the collective luminal microbiomes comprising a high level of either Lactobacillus or Bacteroides Among the clustered microbiomes, Lactobacillus-dominant ileal microbiomes had significantly lower abundances of Bacteroides, Prevotella, Roseburia, Ruminococcus, and Veillonella compared to the Bacteroides-dominated ileal microbiomes. In addition, the upregulated ileal genes of the Lactobacillus-dominant calves were related to leukocyte and lymphocyte chemotaxis, the cytokine/chemokine-mediated signaling pathway, and inflammatory responses, while the upregulated ileal genes of the Bacteroides-dominant calves were related to cell adhesion, response to stimulus, cell communication and regulation of mitogen-activated protein kinase cascades. The functional profiles of the luminal microbiomes also revealed two distinct clusters consisting of functions related to either high protein metabolism or sulfur metabolism. A lower abundance of Bifidobacterium and a higher abundance of sulfur-reducing bacteria (SRB) were observed in the sulfur metabolism-dominant cluster (0.2% ± 0.1%) compared to the protein metabolism-dominant cluster (12.6% ± 5.7%), suggesting an antagonistic relationship between SRB and Bifidobacterium, which both compete for cysteine. These distinct taxonomic and functional clusters may provide a framework to further analyze interactions between the intestinal microbiome and the immune function and health of neonatal calves.IMPORTANCE Dietary interventions to manipulate neonatal gut microbiota have been proposed to generate long-term impacts on hosts. Currently, our understanding of the early gut microbiome of neonatal calves is limited to 16S rRNA gene amplicon based microbial profiling, which is a barrier to developing dietary interventions to improve calf gut health. The use of a metagenome sequencing-based approach in the present study revealed high individual animal variation in taxonomic and functional abundance of intestinal microbiome and potential impacts of early microbiome on mucosal immune responses during the preweaning period. During this developmental period, age- and diet-related changes in microbial diversity, richness, density, and the abundance of taxa and functions were observed. A correlation-based approach to further explore the individual animal variation revealed potential enterotypes that can be linked to calf gut health, which may pave the way to developing strategies to manipulate the microbiome and improve calf health.

Keywords: gut microbiome; metagenomics; mucosal immune system; neonatal calves.

FIG 1

Postnatal changes in the small intestinal microbiomes of preweaned dairy calves. (A) Individual calf variation of the relative abundance of four main bacterial phyla in the digesta-associated communities collected from three different regions of the small intestine at three different ages. Each data point represents an individual calf, and the bar represents the mean relative abundance of a small intestinal region or an age group. The upper panel presents all three age groups within a small intestinal region (15 data points/phylum, 3 charts for 3 intestinal regions), and the lower panel presents all three small intestinal regions within an age category (15 data points/phylum, 3 charts for 3 age groups). (B) The abundance of the small intestinal subsystems (level 1 microbial functions of the SEED hierarchy, only the abundant subsystems [mean relative abundance >1%] are presented). Numerical values represent individual calf IDs. 1W, 1-week-old calves; 3W, 3-week-old calves; 6W, 6-week-old calves. Each data series represents relative abundance of detected subsystems.

FIG 2

Clustering of the collective microbial profiles based on taxonomic/functional similarities. (A) Clustering of calves based on microbial taxonomic composition. (B) Clustering of calves based on microbial functional abundance. Numbers on the x axis represent calf IDs. PJ, proximal jejunum; DJ, distal jejunum; IL, ileum. Abundances of bacterial genera between two function-based clusters are compared using Metastats, and data are presented as means ± the SEM. Clustering is based on the Spearman rank correlation coefficient between two samples generated either based on the relative abundance of 27 bacterial genera identified in at least 50% of samples or based on the relative abundance of subsystems. Each row and column represent an individual microbial profile generated from small intestinal samples (45 microbial profiles).

FIG 3

Ileal mucosal immune-related genes and functions of calves belong to two taxonomic clusters. (A) Functions of the genes upregulated/enriched in taxonomic clusters. (Upper panel) Functions of the genes enriched in the ileal tissue of the Lactobacillus-dominant calves; (lower panel) functions of the genes enriched in the ileal tissue of the Bacteroides-dominant calves. Functional enrichment was performed using GO enrichment analysis in Gene Ontology Consortium. The P value indicates significance for the enrichment in the data set of the listed GO identifier. A P value close to zero, that is, a higher –log(P), means that the group of genes associated with the particular GO term is more significant and it is less likely the observed annotation of the particular GO term to a group of genes occurs by chance. (B) Main genes annotated to enriched immune functions. Each bar represents the fold change expression of annotated genes. The fold change is calculated by dividing the expression of genes (counts per million [cpm]) in Lactobacillus-dominant calves by the expression of genes (mean cpm) in Bacteroides-dominant calves for the Lactobacillus-dominant cluster and vice versa for the Bacteroides-dominant cluster. CXCL9, chemokine ligand 9; CXCL10, chemokine ligand 10; CXCL11, chemokine ligand 11; PLCE1, phospholipase C epsilon 1; CCL22, C-C motif chemokine ligand 22; EGFR, epidermal growth factor receptor.