We are interested in the evolution, transmission, and molecular mechanisms underlying antibiotic resistance. Specifically, the work that feeds into this paper comes from our interest in environmental resistance. Currently, we're trying to build a local database to track spatial temporal variation in antimicrobial resistance using one year's worth of data.
A combination of culture-based techniques and genomics is used to detect and monitor antimicrobial resistance. DNA from samples undergo PCR or shotgun sequencing to profile microbial diversity and detect resistance genes. Additionally, metabarcoding and gene-based AMR panels are used for advanced AMR detection.
Fragmented low molecular weight DNA is known to be a reservoir of AMR genes, but there has been little focus on developing methods specific to high-yield extraction of linear and low molecular weight DNA. Our work focuses on addressing this gap. Our protocol introduces a simple pre-processing step to enrich the proportion of low molecular weight DNA extracted from wastewater.
As a result, this captures environmental AMR in its entirety without excluding free DNA fractions. This protocol can be developed into a kit-free method with a little more work. In turn, this paves the way for development of cost-effective techniques for capturing environmental AMR.
We want to go beyond mutational resistance and explore the contribution of non-genetic mechanisms to antibiotic resistance. We are interested specifically in comparing the relative contributions of horizontal gene transfer and genomic mutations to adaptation to antibiotics in different environments.