Behdad Saba, Pakdel Abbas, Massudi Reza
Department of Animal Science, College of Agriculture, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Department of Animal Science, College of Agriculture, Isfahan University of Technology, Isfahan, Iran.
Front Cell Infect Microbiol. 2024 Nov 13;14:1395949. doi: 10.3389/fcimb.2024.1395949. eCollection 2024.
Paratuberculosis is a granulomatous intestinal infection that affects ruminant animals worldwide. The disease is often detected when most animals are already infected due to the long incubation period and the high transmissibility of the infectious agent. The lack of a comprehensive method to diagnose Paratuberculosis is a global challenge. Therefore, a non-destructive, fast, and cost-effective diagnostic method for early detection of Paratuberculosis is crucial.
Near-infrared spectroscopy (NIRS) and Aquaphotomics have the potential to diagnose the disease by detecting changes in biological fluids. This study aimed to investigate the diagnostic ability of NIRS and Aquaphotomics for Paratuberculosis in dairy cattle by monitoring and data mining of saliva. The diagnostic models were developed according to saliva spectra of dairy cattle in the NIR range and 12 water absorbance bands from 100 to 200 days after calving in two groups: positive and negative, based on the same results of seven ELISA tests of blood plasma, as a reference test.
Both NIRS and Aquaphotomics methods had high diagnostic accuracy. Using QDA and SVM models, 99% total accuracy, 98% sensitivity, and 100% specificity were achieved in internal validation. The total accuracy in external validation was 90%. This study presents two novel approaches to diagnosing Paratuberculosis in dairy cattle using saliva.
The study found that changes in water absorbance spectral patterns of saliva caused by complex physiological changes, such as the amount of antibody related to Paratuberculosis in dairy cattle as biomarkers, are crucial in detecting Paratuberculosis using NIRS and Aquaphotomics.
副结核病是一种肉芽肿性肠道感染病，影响着全球的反刍动物。由于潜伏期长且病原体传播性高，该病往往在大多数动物已被感染时才被发现。缺乏一种全面的副结核病诊断方法是一项全球性挑战。因此，一种用于早期检测副结核病的非破坏性、快速且经济高效的诊断方法至关重要。
近红外光谱法（NIRS）和水相代谢组学有潜力通过检测生物体液中的变化来诊断该病。本研究旨在通过对奶牛唾液的监测和数据挖掘，探究NIRS和水相代谢组学对奶牛副结核病的诊断能力。基于血浆的七次酶联免疫吸附测定（ELISA）测试的相同结果作为参考测试，根据奶牛产后100至200天内近红外范围内的唾液光谱以及12个吸水波段，在阳性和阴性两组中建立诊断模型。
NIRS和水相代谢组学方法均具有较高的诊断准确性。在内部验证中，使用二次判别分析（QDA）和支持向量机（SVM）模型，总准确率达到99%，灵敏度为98%，特异性为100%。外部验证中的总准确率为90%。本研究提出了两种利用唾液诊断奶牛副结核病的新方法。
该研究发现，唾液吸水光谱模式的变化是由复杂的生理变化引起的，例如奶牛体内与副结核病相关的抗体量作为生物标志物，这在使用NIRS和水相代谢组学检测副结核病中至关重要。
