Research

Background

Bovine respiratory disease (BRD) is a major cause of morbidity and mortality in feedlot cattle, leading to economic losses. While many factors play a role in the development of BRD, bacterial infections are an important contributor, and antimicrobial resistance (AMR) in these bacteria hampers control efforts.

Traditional bacterial culture and antibiotic sensitivity tests that are available to diagnose which bacteria are causing a specific BRD case can take days or weeks to produce results. By the time the diagnostic result is available, different bacteria may be responsible for the illness (if the animal is still alive). This delay in the availability of diagnostic information is not practical in large-scale, commercial feedlots.

Complicating things further, not all bacteria are equally capable of causing disease. For example, there are different serotypes (strains) of Mannheimia haemolytica (one of the main BRD bacteria). Serotypes 1 and 6 frequently cause BRD, whereas serotype 2 is typically found in healthy cattle. Some bacteria may also be carrying antibiotic resistance genes while others aren’t, which requires a whole different diagnostic procedure. Similarly, some strains of Histophilus somni, produce a protein (IbpA) that is important in causing disease. Sometimes clusters of antibiotic resistance genes are carried on mobile genetic elements that can be easily traded with other bacteria. This can lead to rapid spread of antibiotic resistance.

This project used technology first developed in a previous ABP funded project.

Objectives

The objectives of this study are to:

1) Design recombinase polymerase amplification (RPA) assays to detect Histophilus somni stains known to cause BRD, and identify mobile genetic elements and antimicrobial resistance genes associated with these and other bacteria from deep nasal swabs obtained from feedlot calves

2) Use RPA to detect the four main bacteria associated with BRD using RPA, their antimicrobial resistance genes, associated mobile genetic elements, and H. somni ipbA genes in samples from calves on arrival, 13 days, and 36 days post-feedlot arrival, as well as from calves that are sick with BRD in a research feedlot

3) Use RPA to detect the four main bacteria associated with BRD, their antimicrobial resistance genes, associated mobile genetic elements, and H. somni ipbA genes in samples from commercial feedlot cattle close to arrival time

4) Evaluate performance of RPA as a diagnostic test

What they did

RPA, first investigated in the previous project, is a diagnostic test that runs at a constant, low temperature, requires minimal equipment or sample preparation, and produces results from extracted DNA in as little as 30 minutes. A new RPA test was developed to detect whether feedlot calves were carrying strains of Histophilus somni with an increased risk of causing disease, and another RPA test was developed that can detect up to three important ARGs simultaneously in deep nasopharyngeal swab (DNPS) samples.

Samples collected from high-risk, auction-mart calves were subjected to these new RPA tests and other recently developed RPA tests that identify bacteria associated with BRD and their mobile genetic elements. Calves were sampled on arrival at a research feedlot and again 13 and 36 days later, and at the time of diagnosis for any calves that became sick with BRD. RPA results were compared to those of bacterial culture and antimicrobial susceptibility testing to determine their sensitivity (can RPA identify samples with a specific gene?) and specificity (can RPA discern samples without a gene target?).

The same tests were applied to samples collected from commercial feedlot calves to determine the performance of RPA under field sampling conditions.

What they learned

This is the first, identified report to develop a real time RPA assay for the detection of multiple important macrolide resistance genes, as well as the first use of a conserved genetic region coding for a specialized H. somni protein (IbpA) as diagnostic target for RPA. The latter RPA test could detect as few as 226 copies of the ibpA gene per sample.

The macrolide AMR RPA assay was able to detect ARGs (msrE, mphE, erm42) in DNPS samples from high-risk, experimental calves, with a clinical sensitivity of 95% and specificity of 57% for detecting the group of assayed macrolide resistance genes under the conditions of the pilot test using selected samples from a single study. The presence of erm42 was low in these samples, making it difficult to evaluate the ability of RPA to detect it accurately.

Using these and previously published RPA tests for important BRD bacteria and mobile genetic elements that allow transmission of groups of AMR genes between these bacteria, RPA was used to test DNPS samples from cattle at different timepoints near the time of arrival at a research feedlot. When compared alongside bacterial culture, RPA was highly specific and able to accurately identify which samples did not contain BRD-associated bacterial pathogens, meaning that a positive test result can be trusted to rule in the presence of these bacterial targets.

The samples obtained from experimental and commercial feedlot cattle were 25-63% positive for one or more mobile genetic element targets and 47-90% positive for any of the macrolide gene targets, while 67% of the H. somni-positive DNPS samples collected from commercial feedlot calves contained the H. somni-disease-associated IbpA protein.

What it means

In this study, new RPA tests were created to identify ARGs specific to macrolide drugs (e.g. tulathromycin) and a protein linked to H. somni disease in cattle. These new tests show promise for identifying genes in BRD-associated bacteria that can contribute to the development of more severe disease and challenges in BRD management.

RPA is fast, easy to use, and requires little equipment to identify ARGs and other genes important to BRD. RPA shows promise as a potential diagnostic method for smaller groups of cattle. However, as a target-based test, it is restricted by the number of known targets we can test for. However, limitations in specificity and speed means that it will likely not become a useful chute-side diagnostic tool at feedlots on a large scale. In addition, as more genes are identified, RPA testing could become limited by the cost of testing for additional targets.