Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractDetermination of changes in the microbial and chemical composition of Taga cheese during maturation    Next AbstractCurrent methods for detecting ethylene in plants »

Mol Ecol Resour


Title:Developing noninvasive methodologies to assess koala population health through detecting Chlamydia from scats
Author(s):Cristescu RH; Miller RL; Schultz AJ; Hulse L; Jaccoud D; Johnston S; Hanger J; Booth R; Frere CH;
Address:"Global Change Ecology Research Group, University of the Sunshine Coast, Sippy Downs, Queensland, Australia. School of Agriculture and Food Sciences, University of Queensland, Gatton, Queensland, Australia. Diversity Arrays Technology, University of Canberra, Bruce, Australian Capital Territory, Australia. Endeavour Veterinary Ecology, Toorbul, Queensland, Australia. Australia Zoo Wildlife Hospital, Beerwah, Queensland, Australia"
Journal Title:Mol Ecol Resour
Year:2019
Volume:20190505
Issue:4
Page Number:957 - 969
DOI: 10.1111/1755-0998.12999
ISSN/ISBN:1755-0998 (Electronic) 1755-098X (Linking)
Abstract:"Wildlife diseases are a recognized driver of global biodiversity loss, have substantial economic impacts, and are increasingly becoming a threat to human health. Disease surveillance is critical but remains difficult in the wild due to the substantial costs and potential biases associated with most disease detection methods. Noninvasive scat surveys have been proposed as a health monitoring methodology to overcome some of these limitations. Here, we use the known threat of Chlamydia disease to the iconic, yet vulnerable, koala Phascolarctos cinereus to compare three methods for Chlamydia detection in scats: multiplex quantitative PCR, next generation sequencing, and a detection dog specifically trained on scats from Chlamydia-infected koalas. All three methods demonstrated 100% specificity, while sensitivity was variable. Of particular interest is the variable sensitivity of these diagnostic tests to detect sick individuals (i.e., not only infection as confirmed by Chlamydia-positive swabs, but with observable clinical signs of the disease); for koalas with urogenital tract disease signs, sensitivity was 78% with quantitative PCR, 50% with next generation genotyping and 100% with the detection dog method. This may be due to molecular methods having to rely on high-quality DNA whereas the dog most likely detects volatile organic compounds. The most appropriate diagnostic test will vary with disease prevalence and the specific aims of disease surveillance. Acknowledging that detection dogs might not be easily accessible to all, the future development of affordable and portable 'artificial noses' to detect diseases from scats in the field might enable cost-effective, rapid and large-scale disease surveillance"
Keywords:Animals Biological Assay/*methods Chlamydia/genetics/*isolation & purification Chlamydia Infections/*veterinary Feces/*microbiology High-Throughput Nucleotide Sequencing/*methods Multiplex Polymerase Chain Reaction/*methods *Phascolarctidae Population Hea;
Notes:"MedlineCristescu, Romane H Miller, Russell L Schultz, Anthony J Hulse, Lyndal Jaccoud, Damian Johnston, Stephen Hanger, Jon Booth, Rosie Frere, Celine H eng Gympie Regional Council/ Redland City Council/ Department of Transport and Main Roads, Queensland Government/ Sunshine Coast Council/ Fraser Coast Regional Council/ Comparative Study Evaluation Study England 2019/01/27 Mol Ecol Resour. 2019 Jul; 19(4):957-969. doi: 10.1111/1755-0998.12999. Epub 2019 May 5"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 26-12-2024