Harmonisation of in-silico next-generation sequencing based methods for diagnostics and surveillance

Abstract

Improvements in cost and speed of next generation sequencing (NGS) have provided a new pathway for delivering disease diagnosis, molecular typing, and detection of antimicrobial resistance (AMR). Numerous published methods and protocols exist, but a lack of harmonisation has hampered meaningful comparisons between results produced by different methods/protocols vital for global genomic diagnostics and surveillance. As an exemplar, this study evaluated the sensitivity and specificity of five well-established in-silico AMR detection software, produced from whole genome sequencing a panel of 438 Escherichia coli. No significant differences in software performance were observed, suggesting that efforts to harmonise AMR predictions from sequence data should focus on: 1) establishing universal minimum levels of performance thresholds (e.g. a control isolate panel, minimum sensitivity/specificity thresholds); 2) standardising AMR gene identifiers in reference databases and gene nomenclature; 3) producing consistent genotype/phenotype correlations. The study also revealed limitations of in-silico technology on detecting resistance to certain antimicrobials due to lack of specific fine-tuning options in bioinformatics tool or a lack of representation of resistance mechanisms in the reference database. Lastly, we noted user friendliness of tools was also an important consideration. Therefore, our recommendations are timely for widespread standardisation of bioinformatics for genomic diagnostics and surveillance globally.