Department of Biology, California State University Bakersfield, Bakersfield, CA 93311, USA.
Department of Biological Sciences, Arkansas State University, Jonesboro, AR 72467, USA.
Biosensors (Basel). 2020 Feb 13;10(2):12. doi: 10.3390/bios10020012.
The development of new C-320 electronic-nose (e-nose) methods for pre-symptomatic detection of White-Nose Syndrome (WNS) in bats has required efficacy studies of instrument capabilities to discriminate between major sources of volatile organic compounds (VOCs) derived from clinical samples. In this phase-2 study, we further tested this e-nose for capabilities to distinguish between bat species based on differences in whole-body VOC emissions. Live healthy individuals of nine bat species were temporarily captured outside of caves in Arkansas and Louisiana. VOC emissions from bats were collected using newly developed portable air collection and sampling-chamber devices in tandem. Sensor-array output responses to bat VOC emissions were compared to those of 22 pure VOC analytical standards from five chemical classes. Distinct smellprint signatures were produced from e-nose analyses of VOC metabolites derived from individual bat species. Smellprint patterns were analyzed using 2-dimensional and 3-dimensional Principal Component Analysis (PCA) to produce aroma map plots showing effective discrimination between bat species with high statistical significance. These results demonstrate potential instrument efficacy for distinguishing between species-specific, bat-derived VOC metabolite emissions as major components of clinical samples collected from bats in caves for disease detection prior to symptom development. This study provided additional information required to fully test the efficacy of a portable e-nose instrument for diagnostic applications in subsequent phase-3 testing of noninvasive, early WNS disease detection in intra-cave hibernating bats.
为了开发用于在蝙蝠出现症状前检测白鼻综合征(WNS)的新型 C-320 电子鼻(e-nose)方法,需要对仪器区分源自临床样本的主要挥发性有机化合物(VOC)来源的能力进行功效研究。在本阶段 2 研究中,我们进一步测试了该 e-nose 基于整个身体 VOC 排放差异区分蝙蝠物种的能力。在阿肯色州和路易斯安那州的洞穴外,暂时捕获了 9 种蝙蝠的健康个体。使用新开发的便携式空气收集和采样室设备串联收集蝙蝠的 VOC 排放物。将传感器阵列对蝙蝠 VOC 排放物的响应与来自五个化学类别的 22 种纯 VOC 分析标准品进行比较。从个体蝙蝠物种的 VOC 代谢物的 e-nose 分析中产生了独特的气味特征。使用二维和三维主成分分析(PCA)分析气味特征模式,以产生香气图谱,显示出具有高度统计学意义的种间有效区分。这些结果表明,该仪器在区分物种特异性、蝙蝠衍生的 VOC 代谢物排放方面具有潜在的功效,这些排放物是从洞穴中采集的蝙蝠临床样本中的主要成分,用于在出现症状前进行疾病检测。这项研究提供了在后续的第 3 阶段测试中充分测试便携式 e-nose 仪器用于非侵入性、早期 WNS 疾病检测的诊断应用所需的额外信息,该测试涉及对洞穴内冬眠蝙蝠进行无创、早期 WNS 疾病检测。