Oral Presentation Australian Society for Microbiology Annual Scientific Meeting 2019

High throughput robotic antimicrobial resistance surveillance system for diverse applications (#184)

Sam Abraham 1 , Rebecca Abraham 1 , Joe Lee 1 , Alec Truswell 1 , Shafi Sahibzada 1 , John Blinco 1 , Mark O'Dea 1 , David Jordan 1
  1. Murdoch University, Murdoch, WA, Australia

Antimicrobial resistance (AMR) is one of the most prominent biosecurity issues affecting animals and humans in modern society. AMR in animals is a major global issue in both disease-causing zoonotic pathogens and commensals in the microbiota of healthy livestock. Globally, antimicrobial resistance surveillance and monitoring is widely acknowledged as a critical response to AMR and is one of the priorities of the WHO Global action plan. There are a number of barriers in effective AMR surveillance in food producing animals. These include high labour costs associated with conventional culture and antimicrobial susceptibility testing, lack of epidemiologically determined representative sample collection and sample size, poor study power and the inability to rapidly genotype resistant isolates. In addition, large national surveys undertaken to date are not truly representative of herd level data and do not provide insights useful for veterinarians and farmers implementing farm control measures via antimicrobial stewardship and infection control. Addressing these barriers requires an inexpensive and accurate means for objectively defining AMR risks at the herd and national level.

With the recent development of automated robotic systems and high throughput next generation sequencing platforms, it is now feasible to develop cost effective tools to monitor AMR on large numbers of representative samples obtained from livestock. Application of this tool to individual herds would deliver an accurate description of their AMR status. This presentation will focus on advancing AMR surveillance through robotic multi-platform integration and identify balancing the role of phenotype and genotype from a One-Health perspective.