Biomarker Metabolites Discriminate between Physiological States of Field, Cave and White-nose Syndrome Diseased Bats.

Analysis of volatile organic compound (VOC) emissions using electronic-nose (e-nose) devices has shown promise for early detection of white-nose syndrome (WNS) in bats. Tricolored bats, Perimyotis subflavus, from three separate sampling groups defined by environmental conditions, levels of physical activity, and WNS-disease status were captured temporarily for collection of VOC emissions to determine relationships between these combinations of factors and physiological states, Pseudogymnoascus destructans (Pd)-infection status, and metabolic conditions. Physiologically active (non-torpid) healthy individuals were captured outside of caves in Arkansas and Louisiana. In addition, healthy and WNS-diseased torpid bats were sampled within caves in Arkansas. Whole-body VOC emissions from bats were collected using portable air-collection and sampling-chamber devices in tandem. Electronic aroma-detection data using three-dimensional Principal Component Analysis provided strong evidence that the three groups of bats had significantly different e-nose aroma signatures, indicative of different VOC profiles. This was confirmed by differences in peak numbers, peak areas, and tentative chemical identities indicated by chromatograms from dual-column GC-analyses. The numbers and quantities of VOCs present in whole-body emissions from physiologically active healthy field bats were significantly greater than those of torpid healthy and diseased cave bats. Specific VOCs were identified as chemical biomarkers of healthy and diseased states, environmental conditions (outside and inside of caves), and levels of physiological activity. These results suggest that GC/E-nose dual-technologies based on VOC-detection and analyses of physiological states, provide noninvasive alternative means for early assessments of Pd-infection, WNS-disease status, and other physiological states.

Assessment of the Portable C-320 Electronic Nose for Discrimination of Nine Insectivorous Bat Species: Implications for Monitoring White-Nose Syndrome.

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.

Detection of Emerald Ash Borer Infestations in Living Green Ash by Noninvasive Electronic-Nose Analysis of Wood Volatiles.

The emerald ash borer (EAB) has been the most destructive and costly nonnative insect to threaten the health of ash (Fraxinus) species in North America for at least the past 25 years. The development of methods for detecting visually-hidden EAB galleries at early stages of infestation would provide a useful tool to more effectively facilitate the planning and implementation of targeted EAB pest-suppression and management activities. We tested the efficacy of using a dual-technology electronic-nose (e-nose)/gas chromatograph device as a means for detection of EAB infestations in green ash trees in different EAB-decline classes by analysis of VOC emissions in sapwood. We found significant differences in VOC profiles for trees from the four decline classes. The VOC composition, quantities, and types of volatile metabolites present in headspace volatiles varied considerably across sample types, and resulted in distinct e-nose smellprint patterns that were characteristic of each unique chemical composition. In addition, specific VOC metabolites were identified as potential healthy and EAB-infestation biomarkers, indicative of the health states of individual trees. Few significant differences in major bark phenolic compounds were found between ash decline classes using LC-MS. The e-nose was effective in discriminating between uninfested and EAB-infested trees based on sapwood VOC emissions.