Pipeline for antimicrobial resistance gene quantification from host tissue

Authors: Svaren, Levi; Li, Wenli

Submitted to: Current Protocols in Bioinformatics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/27/2025
Publication Date: 3/27/2025
Citation: Svaren, L.M., Li, W. 2025. Pipeline for antimicrobial resistance gene quantification from host tissue. Current Protocols in Bioinformatics. https://doi.org/10.1002/cpz1.70116.
DOI: https://doi.org/10.1002/cpz1.70116

Interpretive Summary: Antibiotics are frequently used in food production animals to control disease and improve productivity. However, application of antibiotics in food animals promotes the development of antimicrobial resistance (AMR), and subsequently wide spread of AMR bacteria throughout the food chain, endangering the wellbeing and health of both animals and humans. In humans, it’s well documented that the gut microbiome harbors a diverse range of AMR bacteria, called the resistome. Similar knowledge in food animals is largely lacking. The first step to effectively mitigate AMR in food animals is to identify the expression and abundance of AMR genes in the gastrointestinal tract. We have developed a straightforward bioinformatics pipeline to interrogate the resistome using gut tissue RNA sequencing data of any species. In this paper, we walk readers through initial command line set up and tool installation through transcript quantification and variant analysis. Using open-source tools, we made this analytical pipeline easy to implement and generate results ready to incorporate into publishable reports. Thus, this tool will benefit a wide range of researchers who are interested in using high-throughput sequencing data to study AMR in food animals, but lack the expertise or experience in bioinformatics.

Technical Abstract: Antibiotics are frequently used in food production animals to control disease and improve productivity. However, application of antibiotics in food animals promotes the development of antimicrobial resistance (AMR), and subsequently wide spread of AMR bacteria throughout the food chain, endangering the wellbeing and health of both animals and humans. In humans, it’s well documented that the gut microbiome harbors a diverse range of AMR bacteria, called the resistome. Similar knowledge in food animals is largely lacking. The first step to effectively mitigate AMR in food animals is to identify the expression and abundance of AMR genes in the gastrointestinal tract. Gut tissue RNA sequencing (GTRS) allows us to capture metabolically active transcripts from both the host and the microbes attached to the gut epithelium. Ideally, AMR genes can be quantified using GTRS data. This approach also enables us to study the relationship between host and microbe. However, for the majority of these GTRS studies, only host transcriptome changes were reported, leaving the microbial AMR largely untouched, mainly due to the lack of an easily implementable bioinformatics workflow. Here we present a straightforward pipeline using common command-line bioinformatics tools for the interrogation of resistomes using GTRS of any species. The sequencing reads from the host are considered noise and filtered out. Then, transcript quantification of AMR genes is performed, followed by analysis of the single nucleotide polymorphisms (SNPs) in the AMR genes. In this paper, we walk readers through initial command line set up and tool installation through transcript quantification and SNP analysis. Using open-source tools, we made this analytical pipeline easy to implement and generate results ready to incorporate into publishable reports. Thus, this tool benefits a wide range of researchers who are interested in using high-throughput sequencing data to study AMR in food animals, but lack the expertise or experience in bioinformatics.