How Should We Be Determining Background and Baseline Antibiotic Resistance Levels in Agroecosystem Research?. Issue 2 (1st March 2016)

• Record Type: Journal Article
• Authors: Rothrock, Michael J.; Keen, Patricia L.; Cook, Kimberly L.; Durso, Lisa M.; Franklin, Alison M.; Dungan, Robert S.
• Is Part Of: Journal of Environmental Quality. Volume 45:Issue 2(2016)
• Page Start: 420
• Page End: 431
• Publication Date: 2016-03-01
• Subjects: Agricultural ecology -- Periodicals; Environmental engineering -- Periodicals; Pollution -- Periodicals; 630
• DOI: 10.2134/jeq2015.06.0327
• Languages: English
• ISSNs: 0047-2425

Abstract

Abstract : Although historically, antibiotic resistance has occurred naturally in environmental bacteria, many questions remain regarding the specifics of how humans and animals contribute to the development and spread of antibiotic resistance in agroecosystems. Additional research is necessary to completely understand the potential risks to human, animal, and ecological health in systems altered by antibiotic‐resistance‐related contamination. At present, analyzing and interpreting the effects of human and animal inputs on antibiotic resistance in agroecosystems is difficult, since standard research terminology and protocols do not exist for studying background and baseline levels of resistance in the environment. To improve the state of science in antibiotic‐resistance‐related research in agroecosystems, researchers are encouraged to incorporate baseline data within the study system and background data from outside the study system to normalize the study data and determine the potential impact of antibiotic‐resistance‐related determinants on a specific agroecosystem. Therefore, the aims of this review were to (i) present standard definitions for commonly used terms in environmental antibiotic resistance research and (ii) illustrate the need for research standards (normalization) within and between studies of antibiotic resistance in agroecosystems. To foster synergy among antibiotic resistance researchers, a new surveillance and decision‐making tool is proposed to assist researchers in determining the most relevant and important antibiotic‐resistance‐related targets to focus on in their given agroecosystems. Incorporation of these components within antibiotic‐resistance‐related studies should allow for a more comprehensive and accurate picture of the current and future states of antibiotic resistance in the environment. Core Ideas: Antibiotic resistance studies in agroecosystems are needed to understand potential health risks. Improved baseline and background data for AR in the environment are necessary. Standard terminology and criteria are critical to study AR in agroecosystems. New decision‐making tool is designed to determine the most relevant AR targets.