Recipient Organization
TEXAS A&M UNIVERSITY
750 AGRONOMY RD STE 2701
COLLEGE STATION,TX 77843-0001
Performing Department
(N/A)
Non Technical Summary
Bovine respiratory disease (BRD) is one of the most serious and costly health challenges facing the U.S. beef industry. It affects millions of cattle each year, leading to major economic losses for producers, higher veterinary and treatment costs, reduced animal welfare, and inefficiencies in food production. Improving how this disease is understood and managed is critical to supporting American agriculture and maintaining a safe, affordable food supply. One of the bacteria linked to BRD is Mycoplasma bovis. Traditionally, this bacterium has been viewed as a problem mainly in chronic cases that do not respond well to treatment. Because of this assumption, its role in early stages of the disease has largely been overlooked. New evidence from our preliminary work suggests that Mycoplasma bovis may also contribute to early BRD by worsening the effects of other harmful bacteria. This challenges long-held assumptions and highlights the need to update current approaches to diagnosing and managing BRD. The goal of this project is to improve the ability of veterinarians and producers to detect, predict, and manage BRD more effectively. We will study how Mycoplasma bovis behaves in healthy cattle and in cattle with both early and chronic forms of the disease in a major beef-producing region of Texas. We will also examine how this bacterium interacts with other disease-causing bacteria and with the normal microbes found in cattle and their environment. By better understanding these interactions and how they change over time, this research will help identify earlier warning signs of disease and support more targeted and responsible treatment decisions. Ultimately, the findings will provide practical tools to reduce disease losses, improve animal welfare, and lower production costs. This work directly supports the economic sustainability of U.S. beef producers, strengthens food security, and promotes science-based decision-making in animal health. The results will help ensure that public and private investments in livestock health deliver meaningful benefits to producers, consumers, and the broader agricultural economy.
Animal Health Component
40%
Research Effort Categories
Basic
60%
Applied
40%
Developmental
0%
Goals / Objectives
The overall objective for this project is to reevaluate the role of Mycoplasma bovis in bovine respiratory disease (BRD) in beef cattle. We will complete the following Specific Aims:Specific Aim 1: Detect genes associated with virulence, persistence, and antibiotic resistance in the M. bovis genome. We will characterize the genetic background of M. bovis isolates recovered from healthy cattle and those with acute and chronic BRD.Specific Aim 2: Interrogate M. bovis colonization patterns during acute and chronic BRD and its relationship with other BRD pathogens, the microbiome, and cattle gene expression. We will infer the associations of M. bovis with other BRD pathogens, the respiratory and environmental microbiomes, and cattle gene expression throughout the spectrum of clinical BRD.Specific Aim 3: Assess the within- and between-host strain variability of M. bovis during BRD. We will detect M. bovis dynamics at the strain level in the respiratory tract of beef cattle using M. bovis-enriched sequencing.
Project Methods
Study OverviewThis project integrates amatched case-control studyand alongitudinal cohort studyto investigate the role ofMycoplasma bovisand other bovine respiratory disease (BRD) agents in cattle health, combining microbiological, genomic, transcriptomic, and statistical approaches.Case-Control StudyStudy Design and PopulationA matched case-control study will be conducted across10 commercial feedlots in the Texas Panhandle. Cattle diagnosed withacute BRDorchronic BRDwill be randomly selected and individually matched to healthy controls from the same pen. The case definitions are as follows:Acute BRD cases: CIS 2-3, first antimicrobial treatment, thoracic ultrasound score (USS6) 2-4. Animals requiring a second BRD treatment will be excluded with their matched controls.Chronic BRD cases: CIS 2-3 plus ≥3 antimicrobial treatments, poor performance (ADG <1.0 lb or BCS <3), and USS score 5.Controls: Healthy cattle from the same pen.Animal-level data collected include sex, days since arrival, body weight, and BRD status.Sample CollectionThe following samples will be collected: nasopharyngeal swabs(for culture, DNA, and RNA), jugular blood(RNA), and ropes and water trough samples from feedlot pens. All samples will be transported at 4°C to the VERO laboratory.Microbiology and Molecular MethodsNasopharyngeal swabs will be cultured on PPLO agar under microaerophilic conditions to isolateMycoplasma-like colonies. Pure isolates will be expanded, verified for purity, and confirmed asM. bovisusingSYBR Green qPCR targeting the uvrC gene. One isolate per calf will be selected for downstream analyses.DNA and RNA will be extracted from isolates, swabs, blood, ropes and water samples using Qiagen-based protocols and stored at −80°C.Whole Genome Sequencing (WGS)ConfirmedM. bovisisolates will undergo whole genome amplification, followed byOxford Nanopore Technologies (ONT)library preparation and sequencing onR10.4.1 flow cellsusing MinION Mk1C devices. Sequencing will target ~300× coverage per isolate. High-accuracy basecalling will be performed using Dorado.Detection of BRD PathogensBacterial agents(M. bovis, M. haemolytica, H. somni, P. multocida) will be quantified using multiplex digital qPCR. Viral agents(BVDV, BRSV, BPIV3, BCoV) will be detected using multiplex digital RT-qPCR. Appropriate ATCC strains and synthetic controls will be used.Host Gene ExpressionExpression of 10 immune-related genes in whole blood will be measured by RT-qPCR using the 2^−ΔΔCT method, normalized to housekeeping genes.Microbiome ProfilingFull-length16S rRNA gene sequencingwill be conducted on nasopharyngeal, rope, and water DNA using ONT barcoded libraries, targeting ~100,000 reads per sample.Bioinformatics and Data AnalysisGenome assembly, annotation, pangenome, SNP, and antimicrobial resistance analyses will use tools including Flye, Prokka, Roary, Snippy, and ABRicate. Microbiome data will be processed with Filtlong, Centrifuge, and Pavian. Associations betweenM. bovisgenomics, resistance, colonization patterns, co-infecting pathogens, and health status will be assessed using conditional logistic regression, Fisher exact tests, and pangenome-wide association tools (Scoary2, Pyseer). Machine learning approaches (e.g., Random Forest, Elastic Net, kNN) will integrate microbiome, gene expression, and pathogen dynamics data to predictM. boviscolonization.Longitudinal StudyStudy DesignAcase-control study nested within three longitudinal cohortsof high-risk beef cattle (100 animals per cohort) will be conducted at the WTAMU Research Feedlot. Animals will be followed for50 days.Sampling and ClassificationNasopharyngeal swabs will be collected atarrival (day 0)and ondays 14 and 28. Cattle will be monitored daily using CIS scores and thoracic ultrasound (at arrival). At the end of the study, cattle will be classified as:Healthy: CIS 0-1 throughout the studyAcute BRD cases: CIS 2-3 with one antimicrobial treatmentAnimals with lung lesions at arrival or ambiguous disease status will be excluded.Sequencing and BioinformaticsDNA from swabs will undergotarget enrichment forM. bovisand be sequenced on anIllumina NovaSeq (2×150 bp)platform. Host DNA will be removed bioinformatically. Strain-level composition will be inferred using pseudoalignment (Themisto) andmSWEEP.Data AnalysisMycoplasma bovis within-host variabilitywill be measured using richness and evenness metrics. Mycoplasma bovis between-host variabilitywill be assessed using Jaccard distances. Associations betweenM. bovisdiversity, time, and health outcomes will be evaluated using mixed-effects logistic regression and PERMANOVA.