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Article summary:
1. This article evaluates the ability of four different methods (MIC determination, cfu counting of E. coli, cfu counting of aerobic bacteria, and metagenomic shotgun sequencing) to predict expected tetracycline resistance in 10 Danish integrated slaughter pig herds.
2. Metagenomic read-mapping was found to be more reliable than culture-based techniques for predicting expected tetracycline resistance based on antimicrobial consumption.
3. Pen floor manure samples were found to represent rectal samples well when analysed using metagenomics, as they contain the same DNA with the exception of a few contaminating taxa that proliferate in the extraintestinal environment.
Article analysis:
This article provides an evaluation of four different methods for monitoring antimicrobial resistance (AMR) in livestock and other reservoirs. The authors present a workflow from sampling to interpretation showing how resistance monitoring can be carried out in swine herds using a metagenomic approach. The article is well written and provides detailed information about the methods used and their results.
The authors provide evidence for their claims by citing relevant research studies and providing data from their own experiments. However, there are some potential biases that should be noted. For example, the study only evaluated 10 Danish integrated slaughter pig herds which may not be representative of all swine herds worldwide or even all swine herds in Denmark. Additionally, the authors do not explore any counterarguments or alternative approaches to AMR monitoring which could have provided a more balanced view on the topic.
In conclusion, this article provides an informative overview of AMR monitoring using metagenomics and presents evidence for its efficacy in predicting tetracycline resistance based on antimicrobial consumption. However, it should be noted that further research is needed to evaluate its effectiveness in other contexts and settings before it can be recommended as part of routine livestock resistance monitoring programmes or integrated One Health monitoring programmes worldwide.