rhAMR: A comprehensive and cost-effective resistome profiling method

Authors: KENNEY, SOPHIA - Pennsylvania State University; SIEBEL, SAMANTHA - Pennsylvania State University; CHUNG, TAEJUNG - Pennsylvania State University; BIERLY, STEPHANIE - Pennsylvania State University; VAN SYOC, EMILY - Pennsylvania State University; SAPRE, ANJALI - Walter Reed Army Institute; Miles, Asha; KOVAC, JASNA - Pennsylvania State University; GANDA, ERIKA - Pennsylvania State University

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 4/14/2023
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Antimicrobial resistance (AMR) is a global threat to human and animal health, requiring a One Health approach to surveillance, prevention, and management. Surveillance of this problem is maintained through molecular tools that allow regulatory agencies and researchers to monitor the prevalence and trends in antimicrobial resistance potential, otherwise referred to as the resistome. Existing techniques include isolate-based screening, shotgun metagenomics and qPCR that each have their own limitations. Isolate-based screening and qPCR provide a partial picture of the AMR landscape, representing only single isolates or detecting a limited number of resistance genes. Shotgun metagenomics remedies these limitations but is ultimately not cost effective since AMR genes comprise a small fraction of sample metagenomes. To address these limitations, we developed and performed proof-of-concept experiments establishing a new resistome profiling method, rhAMR. This technique leverages the multiplexing capabilities of rhPCR technology, allowing for high throughput targeted PCR and sequencing of AMR genes. Using the MEGARes2.0 database, primer panels were constructed, covering a total of 7,364 targets in silico. With a subset of these targets, rhAMR performance was evaluated in mock microbiomes comprised of up to 30 strains of enteric bacteria with known resistomes. Serially diluted spike-in strains possessing unique resistance genes were used to evaluate detection limits. To determine performance in samples with potentially more experimental variability, rhAMR was also applied to human fecal and turkey cloacal swab samples with known resistome profiles. Following PCR amplification of the targets, samples were sequenced using the Illumina MiSeq platform. Sequencing reads were processed using AMR++v2.02: a shotgun metagenomics analysis pipeline that integrates various steps of resistome analysis including quality control, filtering nonbacterial DNA, and amplicon mapping. Alignment count files were generated and combined into a count matrix from the summed number of local alignments per sample from which relative abundances were calculated. Using the known resistome profiles for each sample pool, rhAMR’s sensitivity and specificity was determined. Without optimization, the panel with 6,196 targets performed with an average 89.2% sensitivity across all included sample pools. rhAMR was able to detect decreases in spike-in-specific genes as low as 1:1000 relative to the rest of the sample pool. In mock microbiomes specifically, 96 genes were detected with 85.4% sensitivity and 57.3% specificity with as few as 15,000 reads per sample. Future optimization targeting specificity will strengthen the tool’s viability as a comprehensive and cost-effective method for AMR profiling across multiple reservoirs, pursuant to the One Health approach necessary for improving AMR surveillance and research.