Surveillance is a key factor in the management of and response to antimicrobial resistance. Determining which microbes are resistant to what antimicrobial agents, how widespread those strains are, and which are causing the most problems enables the prioritization of research and funding globally. One group of researchers from the University of Illinois at Urbana-Champaign has developed a novel way to improve the sensitivity of metagenomics methods for detecting AMR in wastewater.
Studies have indicated that wastewater is a promising target for AMR surveillance. Wastewater contains antimicrobial organisms themselves, as well as the genes that enable their resistance, and antimicrobial drugs. There is information to be gained from measuring all three. The researchers at University of Illinois specifically targeted the detection of antimicrobial resistant genes in wastewater. Their goal was to increase the sensitivity of metagenomic methods, which are typically not sensitive enough for this application. Metagenomic methods provide a broader picture of the genetic makeup of a sample as compared with a more targeted method like qPCR – the most common method for detecting antimicrobial genes in wastewater currently.
In metagenomics, DNA sequences are randomly split, sequenced, and then aggregated statistically. Because AMR genes make up an incredibly small percentage of the genetic material found in wastewater, sensitivity is a problem. To tip the scales in the favour of detecting AMR genes in the samples, the team used CRISPR-Cas9 to target fragmentation of gene sequences so that AMR genes would be easier to detect. This lowered the detection limit for antimicrobial genes by a full order of magnitude.
The team is looking for other opportunities where CRISPR-Cas9-enhanced metagenomics could be used to improve testing.
You can read more in the journal article, published in Water Research http://dx.doi.org/10.1016/j.watres.2024.123056
