Nasal pathobiont abundance is a moderate feedlot-dependent indicator of bovine respiratory disease in beef cattle

Abstract

Background: Bovine respiratory disease (BRD) poses a persistent challenge in the beef cattle industry, impacting both animal health and economic aspects. Several risk factors make an animal susceptible to BRD, including bacteria such as Mannheimia haemolytica, Pasteurella multocida, Histophilus somni, and Mycoplasma bovis. Despite efforts to characterize and quantify these bacteria in the nasal cavity for disease diagnosis, more research is needed to understand if there is a pathobiont abundance threshold for clinical signs of respiratory disease, and if the results are similar across feedlots. This study aims to compare the nasal microbiome community diversity and composition, along with the abundance of four bacterial pathogens and associated serotypes, in apparently healthy and BRD-affected beef cattle. Nasal swabs were collected from four beef feedlots across the US, covering the years 2019 to 2022. The study included post-weaned beef cattle with diverse housing conditions.

Results: Quantification of BRD-associated pathogens effectively distinguished BRD-affected from apparently healthy beef cattle, surpassing the efficacy of 16S rRNA gene sequencing of the nasal microbiome community. Specifically, H. somni, M. bovis, and M. haemolytica had higher abundance in the BRD-affected group. Utilizing the abundance of these pathobionts and analyzing their combined abundance with machine learning models resulted in an accuracy of approximately 63% for sample classification into disease status. Moreover, there were no significant differences in nasal microbiome diversity (alpha and beta) between BRD-affected and apparently healthy cattle; instead, differences were detected between feedlots.

Conclusions: Notably, this study sheds light on the beef cattle nasal microbiome community composition, revealing specific differences between BRD-affected and apparently healthy cattle. Pathobiont abundance was increased in some, but not all farms. Nonetheless, more research is needed to determine if these differences are consistent across other studies. Additionally, future research should consider bacterial-viral interactions in the beef nasal metagenome.

Keywords: 16S rRNA gene; BRD-pathobionts; Beef cattle; Bovine respiratory disease; qPCR.

Fig. 1

Nasal microbiome taxa with an average relative abundance > 2% per sample at the phylum (a), family (b) and genus (c) taxonomic levels in both BRD-affected and apparently healthy beef cattle. If only one group (apparently healthy or BRD) surpassed the 2% threshold (red dashed line), then both groups were reported

Fig. 2

Genera from beef cattle nasal swabs with an average relative abundance > 2% (red dashed line) in at least one health group (BRD-affected and apparently healthy cattle) from at least one of the four feedlots. The relative abundance of all the groups at all feedlots were all plotted to maintain data consistency

Fig. 3

Differentially abundant taxa in BRD-affected relative to apparently healthy cattle when grouping all feedlots (a). Differentially abundant in the BRD-affected group compared to the apparently healthy group in IN (b) and TX (c)

Fig. 4

Beef nasal alpha and beta diversity. Alpha diversity between BRD-affected and apparently healthy cattle (a) and across all the four feedlots (b). Beta diversity between BRD-affected and apparently healthy cattle divided by feedlot and determined by Weighted UniFrac (c) and Bray-Curtis Dissimilarity (d) and only by feedlot determined by Weighted UniFrac (e) and Bray-Curtis Dissimilarity (f)

Fig. 5

Prevalence of the BRD-pathobionts between apparently healthy and BRD-affected beef cattle sampled in CO, ID, IN, and TX. Prevalence values represent only the cattle that tested positive (present) for each pathobionts. Chi-squared tests were completed to indicate significance: * P < 0.05, ** P < 0.01, *** P < 0.001

Fig. 6

BRD-pathobiont abundance (log₁₀) between disease statuses (a) and divided by feedlots (b). Red, gold, and blue triangles represent the group mean