May 2023

MicroRNA Biomarkers for Johne's Disease

Johne's disease costs farmers up to 50% of their annual net profits [1] and the estimated 10-year average annual losse totaling £25.5 million in the UK and 364.31 million euros across losses in the EU [2]. Johne’s disease is also the disease which causes the highest GHG emissions in cattle [3].
This Research Insight explores how microRNA Biomarkers can reliably diagnose early stage Johne’s disease in cattle and predict disease progression, and how it compares to other diagnostic tools.
NEMO-MAP, a microRNA Biomarker will soon be available as a commercial diagnostic tool.

The Problem

Johne's disease is an incurable, highly contagious chronic wasting disease of cattle caused by Mycobacterium avium subspecies paratuberculosis (MAP) [4]. For each animal with clinical disease, 5 to 15 other animals may have silent sub clinical infection [4]. There is no cure available and removing infected animals is necessary to protect the rest of the herd. Aside from being a herd health and productivity issue, Johne’s disease also increases GHG emissions [5].Emissions from UK farms presently amount to about 10% of all UK emissions. Methane emissions by cattle are affected by diet, health, and livestock management.
MAP can increase GHG emissions by up to 24% per unit of milk produced or up to 113% per beef carcass[3, 5].

What are MicroRNAs? MicroRNAs (miRNAs) are short, non coding RNAs involved in regulation of cellular processes, including immune responses against invading pathogens [6] like MAP. Broadly, miRNAs interact with messenger RNA (mRNA) to modify gene expression and prevent protein synthesis. Intense interest has arisen in miRNAs in recent years with respect to their application as diagnostic biomarkers of disease and stress states [7].

How can MicroRNAs Help Diagnose Johne’s Disease?
Cell free microRNAs (miRNAs) circulating in blood and other biofluids, are regulators of various pathological processes, including infectious diseases like MAP [6, 7, 8]. These miRNAs are stable in circulation and can be detected as biomarkers of disease to provide a reliable, rapid and affordable profiling of Johne’s disease.

A New Approach
Preliminary testing of the NEMO (NExtgen miRNA testing with Optimisation) testing technology was carried out on 131 cattle samples, including 65 healthy and 66 diseased animals. Detection of blood miRNA markers were carried out and interpreted with statistical algorithms within an Artificial Intelligence learning model (AI). Extensive
validation, multiple testing and independent AI modelling for repeatability and impartiality have been completed.

NEMO was able to accurately (71.8%) detect Stage I and II of Johne’s disease, with high sensitivity (68.8%) and specificity (74.8%). NEMO is expected to reach up to 90% sensitivity and >90% specificity after AI model training on larger datasets.

How does NEMO Compare with Other Available Tests?

Faecal Culture

Infected animals shed the infectious agent (MAP) causing Johne’s disease in their faeces, which can be detected by faecal cultures. However, MAP is a slow growing microorganism and testing takes at least 5 weeks. Sensitivity of faecal culture is low as infected cattle in early stages of the disease (Stages I and II) who do not shed the agent in their manure or only intermittently and can be missed at testing time.

Antibody Detection

Various serologic tests, including ELISA, agar gel immunodiffusion (AGID) and complement fixation, detect antibodies in the serum and can be used on a herdwide basis to screen for infection. However, antibodies are not detectable in early stages, when the animal is not yet showing clinical signs, but is infectious to other animals. The graph below shows the likely detection of MAP though different tests by cattle age and stage of disease.

NEMO-MAP will be the 1st test able to diagnose Stage I Johne’s disease in cattle with high sensitivity (69% with pilot data, expected to reach 85 to 90%) and will be able to predict the likelihood of progression of the disease to Stage II. NEMO will be able to be used for:

Annual herd wellness checks
Poor performing cattle
Pre calving checks (when transmission risks are high)
Pre purchase of cattle.

NEMO will soon be available as a commercial diagnostic tool.
At this time, a user friendly smartphone application will be in place for sample submission. The lab asks for spun serum to be submitted on the same day as collection. However, should storage be necessary, freezing to -20 ºC is suitable for several weeks.Real time updates on samples and results can be shared between vets and farmers, if desired.

How to use test results?

Because no effective treatment is available, identifying infected cows during the early silent stage of the disease, prior to bacterial shedding and transmission, is essential to protect noninfected animals and improve farming’s productive efficiency. Prediction of disease course is vital for herd management and the NEMO test will provide both diagnosis and prognosis.

References
[1] Shrestha, Shailesh, et al. "Financial vulnerability of dairy farms challenged by Johne's disease to changes in farm payment support." Frontiers in Veterinary Science 5 (2018): 316.
[2] Rasmussen, Philip, et al. "Economic losses due to Johne's disease (paratuberculosis) in dairy cattle." Journal of dairy science 104.3 (2021): 3123-3143.
[3] Grossi, Giampiero, et al. "Livestock and climate change: impact of livestock on climate and mitigation strategies. "Animal Frontiers 9.1 (2019): 69-76.
[4] Matthews, Chloe, Paul D. Cotter, and Jim O’Mahony. "MAP, Johne’s disease and the microbiome; current knowledge and future considerations." Animal Microbiome 3.1 (2021): 34.
[5] National Farmers Union. "Achieving Net Zero: Farming’s 2040 Goal." (2019). www nfuonline com/archive?treeid=137544 & CIEL (2022) ‘Net Zero livestock How farmers can reduce emissions’. www.cielivestock.co.uk/expertise/net-zero-carbon-uk-livestock/report-october-2020/
[6] Panni, Simona, et al. "Non-coding RNA regulatory networks." Biochimica et Biophysica Acta (BBA)- GeneRegulatory Mechanisms 1863.6 (2020): 194417.
[7] Hammond, Scott M. "An overview of microRNAs." Advanced drug delivery reviews 87 (2015): 3-14.
[8] Tribolet, Leon, et al. "MicroRNA biomarkers for infectious diseases: from basic research to biosensing." Frontiers in microbiology 11 (2020): 1197.

Source: https://www.kingshay.com