Evidence map›Paper›PMID 40087791›Full record

ArticleAnimal microbiome2025

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

Ruth Eunice Centeno-Delphia, Natalie Glidden, Erica Long, Audrey Ellis, Sarah Hoffman, Kara Mosier, Noelmi Ulloa, Johnnie Junior Cheng, Josiah Levi Davidson, Suraj Mohan and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Animal microbiome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Ruth Eunice Centeno-DelphiaDepartment of Animal Science, Purdue University, 270 S Russell St, room 2020, West Lafayette, IN, USA.
Natalie GliddenDepartment of Animal Science, Purdue University, 270 S Russell St, room 2020, West Lafayette, IN, USA.
Erica LongDepartment of Animal Science, Purdue University, 270 S Russell St, room 2020, West Lafayette, IN, USA.
Audrey EllisDepartment of Animal Science, Purdue University, 270 S Russell St, room 2020, West Lafayette, IN, USA.
Sarah HoffmanDepartment of Animal Science, Purdue University, 270 S Russell St, room 2020, West Lafayette, IN, USA.
Kara MosierDepartment of Animal Science, Purdue University, 270 S Russell St, room 2020, West Lafayette, IN, USA.
Noelmi UlloaEscuela Agrícola Panamericana Zamorano, Valle del Yeguare, Tegucigalpa, Honduras.
Johnnie Junior ChengDepartment of Animal Science, Purdue University, 270 S Russell St, room 2020, West Lafayette, IN, USA.
Josiah Levi DavidsonDepartment of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, USA.
Suraj MohanDepartment of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, USA.
Mohamed KamelDepartment of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, USA.
Josh I SzaszFive Rivers Cattle Feeding, LLC, Johnstown, CO, 80534, USA.
Jon SchoonmakerDepartment of Animal Science, Purdue University, 270 S Russell St, room 2020, West Lafayette, IN, USA.
Jennifer KoziolSchool of Veterinary Medicine, Texas Tech University, Amarillo, TX, USA.
Jacquelyn P BoermanDepartment of Animal Science, Purdue University, 270 S Russell St, room 2020, West Lafayette, IN, USA.
Aaron AultDepartment of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA.
Mohit S VermaDepartment of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, USA.
Timothy A JohnsonDepartment of Animal Science, Purdue University, 270 S Russell St, room 2020, West Lafayette, IN, USA. john2185@purdue.edu.

Funding

National Institute of Food and Agriculture 2020-68014-31302Purdue University's Colleges of Agriculture and Engineering Collaborative Projects Program 2018-006
6 · The paper itself

Abstract

backgroundBovine 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.

resultsQuantification 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.

conclusionsNotably, 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.

Indexed as

16S rRNA geneBeef cattleBovine respiratory diseaseBRD-pathobiontsqPCR

Identifiers

PMID40087791
PMCPMC11909826

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.