A sampling and metagenomic sequencing-based methodology for monitoring antimicrobial resistance in swine herds.

OBJECTIVES: Reliable methods for monitoring antimicrobial resistance (AMR) in livestock and other reservoirs are essential to understand the trends, transmission and importance of agricultural resistance. Quantification of AMR is mostly done using culture-based techniques, but metagenomic read mapping shows promise for quantitative resistance monitoring. METHODS: We evaluated the ability of: (i) MIC determination for Escherichia coli; (ii) cfu counting of E. coli; (iii) cfu counting of aerobic bacteria; and (iv) metagenomic shotgun sequencing to predict expected tetracycline resistance based on known antimicrobial consumption in 10 Danish integrated slaughter pig herds. In addition, we evaluated whether fresh or manure floor samples constitute suitable proxies for intestinal sampling, using cfu counting, qPCR and metagenomic shotgun sequencing. RESULTS: Metagenomic read-mapping outperformed cultivation-based techniques in terms of predicting expected tetracycline resistance based on antimicrobial consumption. Our metagenomic approach had sufficient resolution to detect antimicrobial-induced changes to individual resistance gene abundances. 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. CONCLUSIONS: We present a workflow, from sampling to interpretation, showing how resistance monitoring can be carried out in swine herds using a metagenomic approach. We propose metagenomic sequencing should be part of routine livestock resistance monitoring programmes and potentially of integrated One Health monitoring in all reservoirs.

Robustness in quantifying the abundance of antimicrobial resistance genes in pooled faeces samples from batches of slaughter pigs using metagenomics analysis.

OBJECTIVES: With the continued spread of antimicrobial resistance (AMR) in animals, it is important to assess its occurrence throughout a microbiome quantitatively in order to evaluate significantly affecting factors, e.g. antimicrobial usage. Metagenomics methods make it possible to measure the abundance of AMR genes in complex samples such as pooled faeces samples from batches of slaughter pigs. This study was performed to determine the random error in pooled samples from batches of pigs at slaughter and the measurement error from the metagenomics processes. METHODS: In four farms, two pooled samples were obtained from a batch of slaughter pigs by two individual samplers, and each pooled sample was thereafter processed twice. Hierarchically clustered heatmaps were applied to evaluate dissimilarities between samples. The coefficient of variation was used to calculate the percentage difference between samples from the same farm. RESULTS: Results of the analysis revealed that it was not possible to quantitatively separate the variation arising from sampling and metagenomics processes. They both contributed to the overall measurement error in batches of slaughter pigs. CONCLUSION: Sampling of single pigs in 30 randomly selected pig pens within the farms provides a composition representative for frequently occurring AMR genes present within the farms, while rare genes were not dispersed in a similar manner. Aggregating the resistance abundance at gene family or antimicrobial class level will reduce the apparent variation originating from errors in sampling and metagenomics processing.