AUTHOR=Centeno-Martinez Ruth Eunice , Mohan Suraj , Davidson Josiah Levi , Schoonmaker Jon P. , Ault Aaron , Verma Mohit S. , Johnson Timothy A. TITLE=The bovine nasal fungal community and associations with bovine respiratory disease JOURNAL=Frontiers in Veterinary Science VOLUME=10 YEAR=2023 URL=https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2023.1165994 DOI=10.3389/fvets.2023.1165994 ISSN=2297-1769 ABSTRACT=Introduction

Effective identification and treatment of bovine respiratory disease (BRD) is an ongoing health and economic issue for the dairy and beef cattle industries. Bacteria pathogens Pasteurellamultocida, Mycoplasmabovis, Mannheimia haemolytica, and Histophilus somni and the virus Bovine herpesvirus-1 (BHV-1), Bovine parainfluenza-3 virus (BPIV-3), Bovine respiratory syncytial virus (BRSV), Bovine adenovirus 3 (BAdV3), bovine coronavirus (BoCV) and Bovine viral diarrhea virus (BVDV) have commonly been identified in BRD cattle; however, no studies have investigated the fungal community and how it may also relate to BRD.

Methods

The objective of this study was to understand if the nasal mycobiome differs between a BRD-affected (n = 56) and visually healthy (n = 73) Holstein steers. Fungal nasal community was determined by using Internal Transcribed Spacer (ITS) sequencing.

Results

The phyla, Ascomycota and Basidiomycota, and the genera, Trichosporon and Issatchenkia, were the most abundant among all animals, regardless of health status. We identified differences between healthy and BRD animals in abundance of Trichosporon and Issatchenkia orientalis at a sub-species level that could be a potential indicator of BRD. No differences were observed in the nasal fungal alpha and beta diversity between BRD and healthy animals. However, the fungal community structure was affected based on season, specifically when comparing samples collected in the summer to the winter season. We then performed a random forest model, based on the fungal community and abundance of the BRD-pathobionts (qPCR data generated from a previous study using the same animals), to classify healthy and BRD animals and determine the agreement with visual diagnosis. Classification of BRD or healthy animals using ITS sequencing was low and agreed with the visual diagnosis with an accuracy of 51.9%. A portion of the ITS-predicted BRD animals were not predicted based on the abundance of BRD pathobionts. Lastly, fungal and bacterial co-occurrence were more common in BRD animals than healthy animals.

Discussion

The results from this novel study provide a baseline understanding of the fungal diversity and composition in the nasal cavity of BRD and healthy animals, upon which future interaction studies, including other nasal microbiome members to further understand and accurately diagnose BRD, can be designed.