Genomic sequencing and predictions of susceptibility

Advances in whole genome sequencing and the application of online tools for real-time detection of AMR determinants is essential for control and prevention strategies to combat the increasing threat of AMR.

(Click to expand)

The principle of in silico AMR determinant detection using a search algorithm to query input DNA

Hendriksen RS, et al. (2019) Using Genomics to Track Global Antimicrobial Resistance. Front. Public Health 7:242:

Advances in whole genome sequencing and the application of online tools for real-time detection of AMR determinants is essential for control and prevention strategies to combat the increasing threat of AMR. Raw reads are fed through AMR databases and if any genes are identified, a report will be generated in plain language.

The sequence-based monitoring approach to track global antimicrobial resistance using bioinformatics tools:

Gather

• Sequence isolate
• Assemble genome

⤋

Evaluate

• Identify resistance genotype
• Perform SNP analysis or wgMLST

⤋

Assess

• Compare to source baselines
• Compare to phenotype

⤋

Analyze

• Look for new mechanisms
• Look for first emergence in region or source

⤋

Trend

• Determine trends of known mechanisms
• Identify new combinations of resistance genes

⤋

Report

• Present online in accessible formats
• Share globally

At present, at least 47 online available resources for in silico AMR prediction are published in the scientific literature. They range from basic AMR reference databases that can be embedded in the user’s own bioinformatics pipeline, to systems having a well-curated database with integrated search tools. These bioinformatics resources have interfaces of different complexity that require different skills in bioinformatics and microbiology for performing the sequence analyses and interpreting the results.

Pathways:

• For known resistance genes: gather, evaluate, assess
• For new resistance mechanisms: analyse, trend and report