We are thrilled to share our lab’s next preprint - research for which was supported by the department of energy, BRaVE Phage Foundry (www.phagefoundry.org). This work is graduate student led and >50% of authors are URM and/or first-gen.
Antimicrobial resistance (AMR) is one of the world’s biggest public health threats today. Although several researchers characterize and quantify antimicrobial resistance genes (ARG), only a handful of studies have looked into classifying ARGs by their public health risk. One such framework is by Zhang et al 2021 (published in nature communications). This framework compartmentalizes ARG families into ranks 1 (highest risk), 2, 3, and 4 (lowest risk) based on human-association, their pathogenicity and mobility scores. As a first step, we applied the Zhang ranking to our data on wastewater influent (after running fastq files through the Chan Zuckerberg ID pipeline). Next, we looked at the seasonal stability (aka persistence) of ARG families across the dry and wet seasons, when samples were collected. This is something that is novel to this study. As a final step, we integrated the Zhang ranking to the persistence and mobility scores (as shown in figure 5 above - extracted from the preprint). We found some rank 2 ARG families rising in their RPI scores to be even higher than rank 1 families. This implies that some higher risk ARG families do not persist in the wastewater and some lower risk families persist - both of which warrants further investigation.
Link to preprint in MedRxiv:
Comments