Analytical framework for estimating antimicrobial resistance gene abundance in metagenomic samples of animal agriculture origin

Antimicrobial resistance (AMR) has become an apex global public health threat that requires a multifaceted One Health approach. According to the CDC, 2.8 million antimicrobial resistant infections occur in the United States each year, resulting in more than 35,000 deaths. Although the development of AMR is incredibly intricate, it is widely recognized that the employment of antibiotics is one of the largest selective pressures of AMR. In many countries, antimicrobial consumption in animal agriculture surpasses that of human usage, and it is estimated that nearly 73% of global antibiotics can be attributed to livestock. Monitoring AMR emergence and historical data on a global scale is crucial when working towards the large-scale mitigation of this public health threat. One tool that can contribute to monitoring AMR is shotgun metagenomics, which entails comprehensive evaluation of the genetic material extracted from all the organisms in a complex sample. This subsequently gives genomic insights into the microorganisms residing in the sample of interest. The Sequence Read Archive (SRA) is a public repository housed by the National Center for Biotechnology Information (NCBI) containing extensive sequence data from metagenomic samples in animal agriculture, as well as the associated spatiotemporal attributes. Here we proposed to develop analytical framework to leverage the SRA and estimate relative antimicrobial resistant gene abundances across animal agriculture on a global scale from publicly available metagenomic sequence information. The developed analytical framework was then employed to evaluate metagenomic samples from cattle and swine housed in the SRA. Estimated abundances are utilized as a proof of concept for evaluating AMR characteristics on a global scale using publicly available, highly heterogenous data. The resulting abundance estimation will offer insights into AMR emergence and dynamics as well as inform further development of mitigation strategies.