Automatic and accurate identification of aerobic bacteria, anaerobic bacteria, yeasts, and fungi in clinical samples derived from animals and from feed for pets

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Project Summary This project aims to build at the Connecticut Veterinary Medical Diagnostic Laboratory (CVMDL) the capacity necessary to automatically, rapidly, and accurately identify aerobic bacteria, anaerobic bacteria, yeasts, and fungi in clinical samples derived from animals and in commercial feed for pets. Identification is a step needed before assessing the antimicrobial resistance of bacterial and fungal isolates. The laboratory needs to replace a now considered obsolete automatic identification system used for ID aerobic bacteria (Ommnilog system) with a new system that provides broader capabilities and improved accuracy. The project's goal aligns with the US FDA Veterinary Laboratory Investigation and Response Network (Vet-LIRN) efforts towards tracking antimicrobial resistance in bacteria and fungi isolated from sick animals and feed. To meet the goal of this project, we are requesting funds to acquire an automated system like GEN III OmniLog ID Plus System (Biolog Inc., Hayward, CA, USA) and companion databases including YT (yeast), FF (fungi), AN (anaerobic bacteria) and GEN III for Gram-negative and positive bacteria. This Biolog advanced phenotypic technology provides valuable information on the properties of strains, in addition to a species-level identification. In the system, a proprietary carbon source utilization technology identifies environmental and pathogenic microorganisms by producing a characteristic pattern or "metabolic fingerprint" from discrete test reactions performed within a 96 well microplate. The purchase of a GEN III OmniLog ID Plus System system will enhance the capacity at the CVMDL Microbiology Laboratory to be fully engaged with Vet-LIRN goals. The laboratory recently acquired an advanced automated system to identify bacteria and for reading antibiotic susceptibility plates (BIOMIC V3, Giles Scientific). The use of both systems will potentiate CVMDL’s capabilities.