SREL Reprint #3662

Escaping the fate of Sisyphus: assessing resistome hybridization baits for antimicrobial resistance gene capture

Megan S. Beaudry1, Jesse C. Thomas1,2, Rodrigo P. Baptista3,4, Amanda H. Sullivan1,3,
William Norfolk1, Alison Devault5, Jacob Enk5, Troy J. Kieran1, Olin E. Rhodes Jr2,6,
K. Allison Perry-Dow7, Laura J. Rose7, Natalia J. Bayona-Vásquez1,3,8,
Adelumola Oladeinde9, Erin K. Lipp1, Susan Sanchez10, and Travis C. Glenn1,3

1Department of Environmental Health Science, University of Georgia, Athens, GA, 30602
2Savannah River Ecology Laboratory, University of Georgia, Aiken, SC, 29808
3Institute of Bioinformatics, University of Georgia, Athens, GA, 30602
4Center for Tropical and Emerging Diseases, University of Georgia, Athens, GA, 30602
5Daicel Arbor Biosciences, 5840 Interface Dr., Suite 101, Ann Arbor, MI, 48103
6Odum School of Ecology, University of Georgia, Athens, GA, 30602
7Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA
8Division of Natural Science and Mathematics, Oxford College, Emory University, Oxford, GA, 30054
9Bacterial Epidemiology and Antimicrobial Resistance Research Unit, U.S. National Poultry Research Center,
USDA Agricultural Research Service, Athens, GA, 30605
10Department of Infectious Diseases, University of Georgia, Athens, GA, 30602

Abstract: Finding, characterizing and monitoring reservoirs for antimicrobial resistance (AMR) is vital to protecting public health. Hybridization capture baits are an accurate, sensitive and cost-effective technique used to enrich and characterize DNA sequences of interest, including antimicrobial resistance genes (ARGs), in complex environmental samples. We demonstrate the continued utility of a set of 19 933 hybridization capture baits designed from the Comprehensive Antibiotic Resistance Database (CARD)v1.1.2 and Pathogenicity Island Database (PAIDB)v2.0, targeting 3565 unique nucleotide sequences that confer resistance. We demonstrate the efficiency of our bait set on a custom-made resistance mock community and complex environmental samples to increase the proportion of on-target reads as much as >200-fold. However, keeping pace with newly discovered ARGs poses a challenge when studying AMR, because novel ARGs are continually being identified and would not be included in bait sets designed prior to discovery. We provide imperative information on how our bait set performs against CARDv3.3.1, as well as a generalizable approach for deciding when and how to update hybridization capture bait sets. This research encapsulates the full life cycle of baits for hybridization capture of the resistome from design and validation (both in silico and in vitro) to utilization and forecasting updates and retirement.

SREL Reprint #3662

Beaudry, M. S., J. C. Thomas, R. P. Baptista, A. H. Sullivan, W. Norfolk, A. Devault, J. Enk, T. J. Kieran, O. E. Rhodes Jr., K. A. Perry-Dow, L. J. Rose, N. J. Bayona-Vásquez, A. Oladeinde, E. K. Lipp, S. Sanchez, and T. C. Glenn. 2021. Escaping the fate of Sisyphus: assessing resistome hybridization baits for antimicrobial resistance gene capture. Environmental Microbiology 23(12): 7523-7537.

This information was provided by the University of Georgia's Savannah River Ecology Laboratory (srel.uga.edu).