Genes identified by CARD/RGI but not by Resistomap.

Genes identified by CARD/RGI but not by Resistomap.</p

CARD/RGI most abundant per antibiotic class.

Surveillance methods of circulating antibiotic resistance genes (ARGs) are of utmost importance in order to tackle what has been described as one of the greatest threats to humanity in the 21st century. In order to be effective, these methods have to be accurate, quickly deployable, and scalable. In this study, we compare metagenomic shotgun sequencing (TruSeq DNA sequencing) of wastewater samples with a state-of-the-art PCR-based method (Resistomap HT-qPCR) on four wastewater samples that were taken from hospital, industrial, urban and rural areas. ARGs that confer resistance to 11 antibiotic classes have been identified in these wastewater samples using both methods, with the most abundant observed classes of ARGs conferring resistance to aminoglycoside, multidrug-resistance (MDR), macrolide-lincosamide-streptogramin B (MLSB), tetracycline and beta-lactams. In comparing the methods, we observed a strong correlation of relative abundance of ARGs obtained by the two tested methods for the majority of antibiotic classes. Finally, we investigated the source of discrepancies in the results obtained by the two methods. This analysis revealed that false negatives were more likely to occur in qPCR due to mutated primer target sites, whereas ARGs with incomplete or low coverage were not detected by the sequencing method due to the parameters set in the bioinformatics pipeline. Indeed, despite the good correlation between the methods, each has its advantages and disadvantages which are also discussed here. By using both methods together, a more robust ARG surveillance program can be established. Overall, the work described here can aid wastewater treatment plants that plan on implementing an ARG surveillance program.</div

CARD/RGI alignment results showing reads coverage of gene <i>mexB</i>.

Note that more than 95% of the gene is covered with at least one read in all samples.</p

The region of the <i>mexB</i> gene targeted by Resistomap primers.

The regions are shown as blue and red lines below the CARD sequence for mexB. In grey are conserved amino acids and mutations are represented by colors.</p

Heatmap displaying the relative abundance data of 45 genes with Resistomap primers matching multiple genes in CARD.

Heatmap displaying the relative abundance data of 45 genes with Resistomap primers matching multiple genes in CARD.</p

Pearson correlation breakdown by antibiotic class for single-match genes across all locations.

Pearson correlation breakdown by antibiotic class for single-match genes across all locations.</p

Taxa of bacterial groups in all four samples.

Surveillance methods of circulating antibiotic resistance genes (ARGs) are of utmost importance in order to tackle what has been described as one of the greatest threats to humanity in the 21st century. In order to be effective, these methods have to be accurate, quickly deployable, and scalable. In this study, we compare metagenomic shotgun sequencing (TruSeq DNA sequencing) of wastewater samples with a state-of-the-art PCR-based method (Resistomap HT-qPCR) on four wastewater samples that were taken from hospital, industrial, urban and rural areas. ARGs that confer resistance to 11 antibiotic classes have been identified in these wastewater samples using both methods, with the most abundant observed classes of ARGs conferring resistance to aminoglycoside, multidrug-resistance (MDR), macrolide-lincosamide-streptogramin B (MLSB), tetracycline and beta-lactams. In comparing the methods, we observed a strong correlation of relative abundance of ARGs obtained by the two tested methods for the majority of antibiotic classes. Finally, we investigated the source of discrepancies in the results obtained by the two methods. This analysis revealed that false negatives were more likely to occur in qPCR due to mutated primer target sites, whereas ARGs with incomplete or low coverage were not detected by the sequencing method due to the parameters set in the bioinformatics pipeline. Indeed, despite the good correlation between the methods, each has its advantages and disadvantages which are also discussed here. By using both methods together, a more robust ARG surveillance program can be established. Overall, the work described here can aid wastewater treatment plants that plan on implementing an ARG surveillance program.</div

Heatmap displaying the relative abundance data of 93 genes with matching primers (equivalent genes) in both Resistomap qPCR and CARD/RGI methods.

Heatmap displaying the relative abundance data of 93 genes with matching primers (equivalent genes) in both Resistomap qPCR and CARD/RGI methods.</p

Rarefaction landscape using different gene coverage thresholds for number of antibiotic resistance ontology (ARO) terms, drug classes and AMR gene families for sample S1.

Each line graph contains lines representing the different gene cover thresholds used in the rarefaction analysis (indicated in the legend).</p

The distribution of reads assigned to “Class” taxon using the Kraken tool for the four wastewater samples.

S1 was collected from an urban residential site, S2 from an industrial site, S3 from a healthcare facility, and S4 was collected from a rural sewage treatment plant influent.</p