Circulating microRNAs associated with immune competence in Angus cattle

Abstract

An immune competence (IC) trait has been developed in livestock to combat infectious diseases through selective breeding. Here, we investigate whether circulating host-encoded microRNAs (miRNAs) are associated with immune responses to a commercial multivalent clostridial and leptospiral vaccine in Australian Angus steers, a proxy measure for IC. A total of 332 animals from 2 herds in New South Wales, Australia-Herd 1 (n = 168) and Herd 2 (n = 164)-were IC phenotyped on the day of yard weaning. Within a herd, animals were ranked by their antibody- (Ab-IR) and cell-mediated (Cell-IR) immune responses, and animals identified as "high" or "low" were in the top or bottom 7% of animals for each, respectively. A total of 47 steers that were identified as either low Cell-IR (n = 12), high Cell-IR (n = 11), low Ab-IR (n = 12), or high Ab-IR (n = 12) were selected for miRNA analysis. The IC score, a weighted average incorporating both Ab-IR and Cell-IR rankings, was calculated for selected steers. Our results indicate that the IC phenotype is associated with differences in circulating miRNA profiles. Linear regression modeling identified a potential association between pre-vaccination miR-150 levels and IC scores, while logistic regression modeling suggested that pre-vaccination miR-150 may differentiate IC high and low steers. Machine learning classification models further identified a 5-miRNA signature (miR-192, miR-150, miR-2285co, miR-155, and let-7a-5p) that classified high IC steers with 94% accuracy in this dataset. The findings of this pilot study suggest that circulating miRNAs warrant further investigation as potential predictors of immune response to vaccination and may provide insights into miRNA-regulated pathways involved in vaccine-induced immunity.

Keywords: biomarker; cattle; disease; immune competence; microRNA; vaccine.

Figure 1.

Overview of samples investigated by miRNA profiling by number, property and timepoint. (A) Sera samples from 2 herds of Australian Angus cattle were collected. (B) Sample numbers shown by herd and timepoint. (C) IC classification of the 47 steers according to high or low Cell-IR and Ab-IR.

Figure 2.

Distribution of phenotypic values for immune response traits in Angus steers. Histograms showing the distribution of standardized residual values for (A) Cell-mediated immune response (Cell-IR), (B) antibody-mediated immune response (Ab-IR), and (C) Immune Competence score (IC). Vertical dashed lines indicate the cutoffs for high (positive score) and low (negative score) responders, defined as the top and bottom 7% for Cell-IR and Ab-IR, and the top and bottom 25% for IC.

Figure 3.

miRNA composition and variance in bovine sera. (A) Abundance and (B) inter-sample coefficient of variance (CoV) for all of the 556 miRNAs identified across all sera samples. Bar charts reflect the number of miRNAs (with a minimum cutoff of 5 reads/sample) based on (C) herd and timepoint of sample collection post-vaccination for (D) Herd 1 and (E) Herd 2. Mean miRNA counts were compared using the Mann—Whitney U test. Boxes in the figure represent the 25th to 75th percentile, the line in the box represents the median, and whiskers represent 1.5× interquartile range. ns: not significant. P-value > 0.05

Figure 4.

miRNA profiles classify IC scores. (A) Feature (miRNA) selection lineplot showing the performance metrics of a Logistic Regression model with increasing numbers of miRNAs for IC class prediction. MicroRNAs were selected using RFE to identify the most predictive miRNAs with each combination of miRNAs randomly assessed 1,000 times. Shaded areas are the 95% CI. (B) Confusion matrix showing classification performance of the ML model. (C) A SHAP beeswarm plot demonstrating the impact of each miRNA feature, in order of importance based on mean absolute SHAP values, on the IC class prediction. Each point on the plot corresponds to a single prediction for an instance in the dataset.