Applying Whole Genome Sequencing to Define and Predict Antimicrobial Resistance

One of the largest global public health crises is the rise of antimicrobial-resistant infections. Globally, over 700,000 people die from antimicrobial-resistant infections annually and this number is projected to increase to 10 million deaths per year by 2050. A potential solution to addressing this threat, is the introduction of new diagnostics to support antimicrobial stewardship and infection prevention and control initiatives. Bacterial whole genome sequencing (WGS) approaches can be applied to address these initiatives by detecting the resistome (e.g. all antimicrobial resistance genes in a given organism) and assessing genetic relatedness of isolates, among others. In this webinar, we will discuss how WGS can be applied to define mechanisms of antimicrobial resistance to novel agents among multidrug-resistant organisms. Understanding the mechanisms of AMR are critical to generating robust databases and prediction pipelines to be able to accurately predict phenotypic antimicrobial susceptibility testing (AST) results. We will then discuss WGS for predicting phenotypic antimicrobial susceptibility testing results, including the advantages and disadvantages of this approach and present data applying different sequencing and analysis methods. Last, we will review the status of applying WGS for predicting antimicrobial susceptibility testing results for patient care.

 

Learning Objectives