Authors: Schuyler D. Smith, Jinlyung Choi, Nicole Ricker, Fan Yang, Heather Allen, Adina Howe


Abstract

Monitoring the spread of antibiotic resistance genes in environmental ecosystems faces significant obstacles, predominantly due to the cost and efficiency of methods available for the task. We developed Diversity of Antibiotic Resistance genes and Transfer Elements-Quantitative Monitoring (DARTE-QM), a method implementing high-throughput sequencing to simultaneously target thousands of antibiotic resistant genes representing a full-spectrum of antibiotic resistance classes seen in environmental systems. In this study, we demonstrate DARTE-QM screening 673 antibiotic resistant genes in environmental samples originating from manure, soil, and animal feces, in addition to a mock-community used as a control to test performance. DARTE-QM offers a supplemental approach to studying antibiotic resistance in environments, showing advantages in efficiency, ergo ability to scale for many samples, that may alleviate obstacles for researchers in this area.



Metagenome Comparison

Data

Antibioti Resistance Genes

File Description
ARG Database fasta format file of the targeted ARG database
Forward Primers fasta format file of the forward primers
Reverse Primers fasta format file of the reverse primers
Target ARGs table of target ARG classifications

Mock Community

File Description
Mock Strain Info file containing information about each community member of the mock
Mock Genomes fasta format file of the genomes of mock community members

Samples

File Description
Sequencing Data where to find the raw sequence files
Sample ARG Counts count tables for ARGs by sample
Sample Metadata file containing metadata for each of the samples analyzed


Packages and Functions

R-Packages

Package Description
Cran Packages R-packages used for analysis installed from CRAN
Github Packages R-packages used for analysis installed from Github

R-Functions

Function Description
Rarefy Randomly sample features without replacement from each column until a given count
Rarefaction Assess diversity richness by rarefying to increasing sample abundance
Rarefaction Curve Create a graphical dipiction of the rarefaction




Schuyler Smith
Ph.D. Student - Bioinformatics and Computational Biology
Iowa State University. Ames, IA.