2292: Broad-Range Detection of Canine Tick-Borne Disease and Improved Diagnostics Using Next-Generation Sequencing

Grant Status: Open

Grant Amount: $60,717
Dr. Pedro Paul Diniz, DVM, PhD, Western University of Health Sciences
August 1, 2016 - February 28, 2018
Sponsor(s): American Shih Tzu Club, Inc., American Whippet Club, Bull Terrier Club of America, Cyclone County Kennel Club, English Springer Spaniel Field Trial Association, English Springer Spaniel Field Trial Association Foundation, Gordon Setter Club of America, Inc., Keeshond Club of America, Norwegian Elkhound Association of America, Inc., Scottish Terrier Club of America, Siberian Husky Club of America, Inc., TarTan Gordon Setter Club, Welsh Springer Spaniel Club of America
Breed(s): -All Dogs
Research Program Area: Tick-Borne Disease

Abstract

Diagnostic tests based on the detection of DNA of infectious organisms from clinical samples have revolutionized veterinary medicine in the last decades. Currently, diagnostic panels for several vector-borne organisms are available through universities and private laboratories in the USA and abroad. However, the vast majority of results from clinically ill dogs are negative for tick-borne diseases, which frustrates veterinarians and dog owners trying to reach a definitive diagnosis and improve treatment options. These panels are based on the detection of previously known DNA sequences of each pathogen, with little room for detecting new organisms. Consequently, the current assays may suffer from "myopia": a self-fulfilling effect that prevents the detection of new or emerging organisms. Using an innovative approach, the investigators will employ next-generation sequencing (NGS) to overcome the limitations of current diagnostic technology. With NGS, the investigators can generate millions of individual gene sequencing reads from each clinical sample, allowing for the identification and characterization of multiple organisms from a single sample. Testing samples from dogs naturally exposed to tick-borne diseases, NGS will detect not only new organisms but also characterize genetic differences among known organisms. The resulting dataset of a large number of DNA sequences of known tick-borne organisms and previously undetected organisms in naturally-infected dogs will support the development of diagnostic tools to simultaneously advance canine and human health.

Publication(s)

None at this time.

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