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通过分析粪便、肺泡气和稳定空气的气味检测奶牛场中的副结核病。

Detection of Paratuberculosis in Dairy Herds by Analyzing the Scent of Feces, Alveolar Gas, and Stable Air.

机构信息

Institute of Molecular Pathogenesis at 'Friedrich-Loeffler-Institut' (Federal Research Institute for Animal Health), Naumburgerstr. 96a, 07743 Jena, Germany.

Rostock Medical Breath Research Analytics and Technologies (RoMBAT), Department of Anesthesia and Intensive Care, Rostock University Medical Center, Schillingallee 35, 18057 Rostock, Germany.

出版信息

Molecules. 2021 May 11;26(10):2854. doi: 10.3390/molecules26102854.

Abstract

Paratuberculosis is an important disease of ruminants caused by ssp. (MAP). Early detection is crucial for successful infection control, but available diagnostic tests are still dissatisfying. Methods allowing a rapid, economic, and reliable identification of animals or herds affected by MAP are urgently required. This explorative study evaluated the potential of volatile organic compounds (VOCs) to discriminate between cattle with and without MAP infections. Headspaces above fecal samples and alveolar fractions of exhaled breath of 77 cows from eight farms with defined MAP status were analyzed in addition to stable air samples. VOCs were identified by GC-MS and quantified against reference substances. To discriminate MAP-positive from MAP-negative samples, VOC feature selection and random forest classification were performed. Classification models, generated for each biological specimen, were evaluated using repeated cross-validation. The robustness of the results was tested by predicting samples of two different sampling days. For MAP classification, the different biological matrices emitted diagnostically relevant VOCs of a unique but partly overlapping pattern (fecal headspace: 19, alveolar gas: 11, stable air: 4-5). Chemically, relevant compounds belonged to hydrocarbons, ketones, alcohols, furans, and aldehydes. Comparing the different biological specimens, VOC analysis in fecal headspace proved to be most reproducible, discriminatory, and highly predictive.

摘要

副结核病是一种由 ssp. (MAP)引起的反刍动物的重要疾病。早期检测对于成功控制感染至关重要,但现有的诊断测试仍然不尽如人意。迫切需要能够快速、经济、可靠地识别受 MAP 影响的动物或畜群的方法。本探索性研究评估了挥发性有机化合物 (VOCs) 区分有和无 MAP 感染牛的潜力。对来自 8 个农场的 77 头奶牛的粪便样本的顶空部分和呼出的肺泡部分进行了分析,此外还分析了稳定的空气样本。通过 GC-MS 鉴定 VOCs,并与参考物质进行定量。为了区分 MAP 阳性和 MAP 阴性样本,进行了 VOC 特征选择和随机森林分类。使用重复交叉验证评估针对每个生物样本生成的分类模型。通过预测两个不同采样日的样本来测试结果的稳健性。对于 MAP 分类,不同的生物基质发出具有独特但部分重叠模式的诊断相关 VOC(粪便顶空:19,肺泡气体:11,稳定空气:4-5)。从化学角度来看,相关化合物属于烃类、酮类、醇类、呋喃类和醛类。比较不同的生物样本,粪便顶空的 VOC 分析被证明是最可重复、最具区分性和高度预测性的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1022/8150929/b56b02f7bd18/molecules-26-02854-g001.jpg

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