Published March 1, 2016
Journal of Environmental Quality speciAl section
Antibiotics in Agroecosystems: stAte of the science
Antibiotics in Agroecosystems: Introduction to the Special Section
Alison M. Franklin,* Diana S. Aga, Eddie Cytryn, Lisa M. Durso, Jean E. McLain, Amy Pruden, Marilyn C. Roberts, 
Michael J. Rothrock, Jr., Daniel D. Snow, John E. Watson, and Robert S. Dungan*
Abstract ince the discovery of penicillin in 1928 by Alexander Fleming and the inception of the “antibiotic era,” the use of 
The presence of antibiotic drug residues, antibiotic resistant bacteria, and Santibiotics in medicinal and agricultural practices has sig-
antibiotic resistance genes in agroecosystems has become a significant nificantly advanced public health and food production (Knapp 
area of research in recent years and is a growing public health concern. 
While antibiotics are used in both human medicine and agricultural et al., 2010). Antibiotics became widely available for use in 
practices, the majority of their use occurs in animal production where human and veterinary medicine in the 1940s and have been used 
historically they have been used for growth promotion, in addition as feed additives for growth promotion in livestock since 1950 
to the prevention and treatment of disease. The widespread use of 
antibiotics and the application of animal wastes to agricultural lands (Halling-Sørensen et al., 1998; Kumar et al., 2005; Kummerer, 
play major roles in the introduction of antibiotic-related contamination 2009). Current worldwide consumption of antibiotic com-
into the environment. Overt toxicity in organisms directly exposed to pounds is approximately 100,000 to 200,000 Mg per year (Hollis 
antibiotics in agroecosystems is typically not a major concern because and Ahmed, 2013; Van Boeckel et al., 2014). The use of large 
environmental concentrations are generally lower than therapeutic 
doses. However, the impacts of introducing antibiotic contaminants quantities of antibiotics raises concerns and questions about the 
into the environment are unknown, and concerns have been raised release of these drugs and the increasing prevalence of antibiotic 
about the health of humans, animals, and ecosystems. Despite resistant bacteria (ARB) and antibiotic resistance genes (ARGs) 
increased research focused on the occurrence and fate of antibiotics in the environment. If antibiotic resistance continues to rise, 
and antibiotic resistance over the past decade, standard methods and 
practices for analyzing environmental samples are limited and future effective treatments for a large number of infectious diseases in 
research needs are becoming evident. To highlight and address these human and animal health may be jeopardized (CDC, 2013). 
issues in detail, this special collection of papers was developed with a Furthermore, ecological health, including nutrient cycling, may 
framework of five core review papers that address the (i) overall state be altered by shifts in indigenous aquatic and terrestrial micro-
of science of antibiotics and antibiotic resistance in agroecosystems 
using a causal model, (ii) chemical analysis of antibiotics found in the bial communities that are affected by the enrichment and/or 
environment, (iii) need for background and baseline data for studies release of antibiotics, ARB, and ARGs into the environment.
of antibiotic resistance in agroecosystems with a decision-making tool While the use of antibiotic drugs is believed to selectively 
to assist in designing research studies, as well as (iv) culture- and (v) enrich ARB and ARGs, large knowledge gaps remain when 
molecular-based methods for analyzing antibiotic resistance in the 
environment. With a focus on the core review papers, this introduction examining the relationship between antibiotic drugs, ARB, and 
summarizes the current state of science for analyzing antibiotics and ARGs in diverse agricultural and environmental systems. In 
antibiotic resistance in agroecosystems, discusses current knowledge these complex systems, discerning direct links between the pres-
gaps, and develops future research priorities. This introduction also 
contains a glossary of terms used in the core reivew papers of this ence or absence of antibiotic drugs and the occurrence of anti-
special section. The purpose of the glossary is to provide a common biotic resistance is challenging due to many factors. Foremost 
terminology that clearly characterizes the concepts shared throughout among these challenges is the natural phenomenon of ARGs 
the narratives of each review paper.
core ideas A.M. Franklin and J.E. Watson, Pennsylvania State Univ., Dep. of Ecosystem Science 
and Management, 116 ASI Building, University Park, PA 16802, USA; D.S. Aga, Dep. 
•	 Antibiotic resistant bacteria are an emerging threat to human, ani- of Chemistry, Univ. at Buffalo, The State University of New York, Buffalo, NY 14260, 
mal, and ecological health. USA; E. Cytryn, Institute of Soil, Water and Environmental Sciences, Volcani Center, 
•	 Agroecosystems often contain elevated levels of antibiotics and Agricultural Research Organization, P.O. Box 6, Bet Dagan 50-250, Israel; L.M. Durso, 
antibiotic resistance. USDA-ARS, Agroecosystem Management Research Unit, 251 Filley Hall, UNL East 
•	 The impact of antibiotics at low concentrations in the environment Campus, Lincoln, NE, 68583, USA; J.E. McLain, Water Resources Research Center, 
is not fully known. University of Arizona, 350 N. Campbell Ave., Tucson AZ 85719, USA; A. Pruden, 
Civil and Environmental Engineering, Virginia Tech, 403 Durham Hall, Blacksburg, 
•	 Research is needed to understand the spread of antibiotic resis- VA 24061, USA; M.C. Roberts, Environmental and Occupational Health Services, 
tance within and beyond agroecosystems. Box 357234, Univ. of Washington, 1959 NE Pacific St., Seattle, WA 98195; M.J. 
•	 Standardized approaches will help bring a consensus among scien- Rothrock, Jr., USDA-ARS, U.S. National Poultry Research Center, 950 College Station 
tific community datasets. Rd., Athens, GA, 30605, USA; D.D. Snow, Nebraska Water Center/School of Natural 
Resources, Univ. of Nebraska-Lincoln, Lincoln, NE, USA; R.S. Dungan, USDA-ARS, 
Copyright © American Society of Agronomy, Crop Science Society of America, and Northwest Irrigation and Soils Research Laboratory, 3793 N. 3600 E., Kimberly, ID 
Soil Science Society of America. 5585 Guilford Rd., Madison, WI 53711 USA. 83341, USA. Assigned to Editor Ed Gregorich.
All rights reserved. 
 Abbreviations: ARB, antibiotic resistant bacteria; ARG, antibiotic resistance 
J. Environ. Qual. 45:377–393 (2016) gene; ELISA, enzyme-linked immunosorbent assay; FISH, fluorescent in situ 
doi:10.2134/jeq2016.01.0023 hybridization; HGT, horizontal gene transfer; LC/MS/MS, liquid chromatography 
Received 19 Jan. 2016.  and tandem mass spectrometry; MIC, minimum inhibitory concentration; 
Accepted 5 Feb. 2016.  MGE, mobile genetic element; PCR, polymerase chain reaction; qPCR, real-time 
*Corresponding author (alisonfranklin@psu.edu; robert.dungan@ars.usda.gov). quantitative polymerase chain reaction.
377
being present within microorganisms due to intrinsic resistance. extremely variable and heterogeneous, especially with regard to 
Bacteria can acquire resistance during horizontal gene transfer microbial community composition. Direct comparisons cannot 
(HGT) of mobile genetic elements (MGEs) that contain not be made easily between pristine environments and those affected 
only ARGs but also other functional genes. The spread of resis- by antibiotic resistance because land-use and past histories are 
tance can occur quickly due to HGT and the rapid growth of not equivalent (Franklin and Mills, 2009); however, pristine 
microorganisms, both of which facilitate the passage of advanta- environments allow us to see that ARB and ARGs exist naturally.
geous mutations and genetic elements (Normark and Normark, The ways in which antibiotics and antibiotic resistance are 
2002). These uncertainties create a number of challenges related measured play an important role in our ability to make compari-
to determining the environmental fate, bioavailability, and sons between published research studies. The types of antibiotic 
effects of antibiotics, ARB, and ARGs in agroecosystems. compounds, ARB, and/or ARGs that are analyzed need to be 
Recently, the World Health Organization released a spe- carefully considered and taken into account when drawing con-
cial report (WHO, 2014) that suggests that antibiotic failure clusions about how levels of antibiotics and antibiotic resistance 
is already a global reality and that investigation of antibiotic within a particular environment may have changed as a result of 
drugs, ARB, and ARGs in the environment is a critical area for agroecosystem practices (Levy, 2002). If the types and quantities 
future research. Of special interest are those agroecosystems in of ARB and ARGs in an environment are being altered, then the 
which antibiotic use is nontherapeutic and mitigation efforts to impact on human, animal, and ecological health may be signifi-
prevent antibiotics, biologically active degradation compounds cant. Antibiotic compounds, ARB, and ARGs have the potential 
(i.e., metabolites), ARB, and ARGs from reaching the environ- to move throughout an ecosystem or between ecosystems, and 
ment are limited or nonexistent. Unlike human biosolids and the possible effects on environmental health are intimately con-
wastewaters that undergo treatment before land application, nected with the health of humans and animals, a concept known 
it is common for untreated animal waste to be applied to land. as “One Health” (Papadopoulos and Wilmer, 2011).
As a result, coordinated full-scale investigations concerning the The majority of research and public concern about antibiotics 
impact of agroecosystems on the spread of antibiotic resistance and antibiotic resistance in the environment has centered on the 
in the wider environment are necessary to elucidate the potential potential risks to humans and animals that consume and utilize 
influence of these systems on the development, movement, and antibiotic drugs for the prevention and treatment of disease 
survival or persistence of ARB and ARGs. (Snary et al., 2004; Ashbolt et al., 2013). Even when antibiotics 
entering the environment are below clinically determined 
Critical Research Areas and Priorities minimum inhibitory concentrations (MICs), research has 
Many hurdles exist in the identification and quantification of shown that some antibiotics can lead to increased abundance 
antibiotic drugs, metabolites, ARB, and ARGs in agroecosystems of ARGs within susceptible organisms and shifts in microbial 
and in determining the specific human and agricultural practices community structure (Liu et al., 2011). In particular, alterations 
that may be sources and/or facilitate the spread of antibiotics and in environmental microbial populations can have negative 
antibiotic resistance. First, antibiotic use in humans and animals impacts on critical processes, especially in soil systems where 
is not the only cause of enrichment of ARB and ARGs. Resistance microorganisms perform important biological transformations 
can be an innate characteristic of certain bacterial species (Cox of carbon and nutrients (Ding and He, 2010), thereby affecting 
and Wright, 2013). For example, Pseudomonas aeruginosa has a plant growth and ecosystem functions (Van der Heijden et al., 
high intrinsic resistance to numerous antibiotics without prior 2008; Lau and Lennon, 2011; Wagg et al., 2011). Consequently, 
exposure to those compounds (Hancock and Speert, 2000). in addition to human and animal health, ecological health could 
Moreover, many bacteria and fungi in the environment can pro- be jeopardized by the release of antibiotics and development 
duce compounds that are structurally similar to antibiotics and of antibiotic resistance in agroecosystems, and the health of 
serve both communication and antagonistic functions (Linares ecosystems should be an additional area of future research.
et al., 2006). These low molecular weight compounds are some-
times produced at concentrations that are high enough to exert Contents of the Special Section
an effect similar to antibiotics, enriching ARB and ARGs in soil This special section contains five core review papers, 19 tech-
and water environments (Aminov, 2010). In these instances, the nical, review, and issues papers (Table 1), and a glossary of com-
presence of antibiotics, ARB, and ARGs does not equate to an monly used terms. The topics include the occurrence (Durso et al., 
anthropogenic impact. 2016; McCall et al., 2016), detection (Wallace and Aga, 2016), 
Because the study of anthropogenic sources of antibiotics and dissemination (Hafner et al., 2016; Ruuskanen et al., 2016; Sura 
antibiotic resistance in the environment is relatively new, levels et al., 2016), fate (Amarakoon et al., 2016; Kulesza et al., 2016; 
that existed before the extensive use of antibiotics in human med- Liu et al., 2016; Xu et al., 2016; Youngquist et al., 2016), plant 
icine and agroecosystems are not well characterized. Defining the uptake (Franklin et al., 2016; Kumar and Gupta, 2016), micro-
amount of antibiotics and ARB that would occur naturally in the biology (Nordenholt et al., 2016; Roberts and Schwarz, 2016; 
environment is challenging (Durso et al., 2012). Environmental Rothrock et al., 2016a; Whitehead and Cotta, 2016; Zwonitzer et 
systems that have already been affected due to anthropogenic al., 2016), and ecological risk (Subbiah et al., 2016) of antibiotics 
inputs of antibiotic-related contamination cannot be analyzed and/or antibiotic resistance in agroecosystems and surrounding 
to determine what the levels were in the system before current natural areas. The antibiotic drugs, ARB, and ARGs discussed in 
or past antibiotic inputs. Furthermore, attempting to define and this special section are predominantly associated with animal pro-
use pristine systems is difficult since environmental systems are duction but also include fruit and vegetable production, as well as 
378 Journal of Environmental Quality 
those associated with the application of biosolids to agricultural the pathways by which humans, animals, and all other biota may 
lands. The core review papers, the main focus of this introduc- be exposed to antibiotics and antibiotic resistance are complex 
tion, examine critical research priorities and directions including and poorly understood. The potential effects of environmental 
(i) causal model of antibiotics and antibiotic resistance pathways exposures on human, animal, and ecosystem health are unclear. 
in agroecosystems (Williams-Nguyen et al., 2016), (ii) detection, In recent years, causal modeling diagrams have been used in an 
measurement, and risk assessment of antibiotics (Aga et al., 2016), attempt to illustrate and visualize ordered relationships between 
(iii) baseline and background levels of antibiotic resistance with factors in complex systems, typically as it relates to epidemiology. 
a decision-making tool (Rothrock et al., 2016b), and (iv) culture- Causal modeling helps to minimize bias and makes assumptions 
(McLain et al., 2016) and (v) molecular-based (Luby et al., 2016) explicit when assessing causal effects from data (Shrier and Platt, 
methods of antibiotic resistance detection. These reviews provide 2008; Joffe et al., 2012). To help illustrate pathways by which 
a synthesis of available information on past and current research exposure to antibiotic drugs, ARB, and ARGs may occur and 
as well as current needs and ways of improving research strategies relate to expected effects, a causal model was proposed for agro-
so that knowledge of antibiotics and antibiotic resistance in agro- ecosystems (Williams-Nguyen et al., 2016). The causal model 
ecosystems can be improved. takes a One Health approach and describes the key interactions 
between antibiotics, ARB, and ARGs as well as their resulting 
Summary of Core Review Papers interactions within the agroecosystem and on three specific 
Antibiotics and Antibiotic Resistance in Agroecosystems: endpoints: (i) human health, (ii) ecosystem function, and (iii) agricultural system productivity. This review evaluates the cur-
State of the Science rent state of understanding of these interactions using available 
As noted by Williams-Nguyen et al. (2016), large quantities literature so that key knowledge gaps can be identified.
of antibiotics are routinely introduced to agroecosystems, yet 
table 1. list of papers in the special section Antibiotics in Agroecosystems: state of the science.
reference title category
Williams-Nguyen et al. (2016) Antibiotics and antibiotic resistance in agroecosystems: State of the science Core review
Aga et al. (2016) Challenges in the measurement of antibiotics and in evaluating their impacts in Core review
agroecosystems: A critical review
Rothrock et al. (2016b) How should we be determining background and baseline antibiotic resistance levels in Core review
agroecosystem research?
McLain et al. (2016) Culture-based methods for detection of antibiotic resistance in agroecosystems: Core review
Advantages, challenges, and gaps in Knowledge
Luby et al. (2016) Molecular methods for assessment of antibiotic resistance in agricultural ecosystems: Core review
Prospects and challenges
Amarakoon et al. (2016) Dissipation of antimicrobials in feedlot manure compost after oral administration versus Technical
fortification after excretion
Durso et al. (2016) Assessment of selected antibiotic resistances in ungrazed native Nebraska prairie soils Technical
Franklin et al. (2016) Uptake of three antibiotics and an antiepileptic drug by wheat crops spray irrigated with Technical
wastewater treatment plant effluent
Hafner et al. (2016) Evaluation of monensin transport to shallow groundwater after irrigation with dairy lagoon Technical
water
Kulesza et al. (2016) Manure injection affects the fate of pirlimycin in surface runoff and soil Technical
Kumar and Gupta (2016) A framework to predict uptake of trace organic compounds by plants Technical
Liu et al. (2016) Sorption of lincomycin by manure-derived biochars from water Technical
McCall et al. (2016) Metagenomic comparison of antibiotic resistance genes associated with liquid and Technical
dewatered biosolids
Nordenholt et al. (2016) Veterinary antibiotic effects on atrazine degradation and soil microorganisms Technical
Roberts and Schwarz (2016) Tetracycline and phenicol resistance genes and mechanisms: Importance for agriculture, the Review
environment, and humans
Rothrock et al. (2016a) Antibiotic resistance patterns of major zoonotic pathogens from all-natural, antibiotic-free, Technical
pasture-raised broiler flocks in the southeastern United States
Ruuskanen et al. (2016) Fertilizing with animal manure disseminates antibiotic resistance genes to the farm Technical
environment
Subbiah et al. (2016) Not all antibiotic use practices in food-animal agriculture afford the same risk Issues
Sura et al. (2016) Transport of three antimicrobials in runoff from windrows of composting beef cattle manure Technical
Wallace and Aga (2016) Enhancing extraction and detection of veterinary antibiotics in solid and liquid fractions of Technical
manure
Whitehead and Cotta (2016) Examination of the aerobic microflora of swine feces and stored swine manure Technical
Xu et al. (2016) Dissipation of antimicrobial resistance determinants in composted and stockpiled beef Technical
cattle manure
Youngquist et al. (2016) Fate of antibiotics and antibiotic resistance during digestion and composting: A review Review
Zwonitzer et al. (2016) Quantifying attachment and antibiotic resistance of Escherichia coli from conventional and Technical
organic swine manure
Journal of Environmental Quality 379
Increased use of antibiotics globally, coupled with advance- environmentally relevant concentrations, cyanobacterial species 
ments in analytical technology, has resulted in more frequent are affected (Guo et al., 2015). While studies have also shown a 
detection of antibiotic compounds and, to a lesser extent, their toxic response to antibiotics in invertebrates and fish, once again 
metabolites, in a variety of agroecosystem compartments, includ- the concentrations at which adverse effects occur are orders of 
ing soil, water, sediment, and biota (Kolpin et al., 2002; Aga et magnitude higher than what is typically considered as environ-
al., 2005; Batt et al., 2006; Pruden et al., 2012; Zhang et al., mentally relevant.
2013). Despite advances in detection methods, limited data are Research investigating the impacts of antibiotics on eco-
available on the occurrence and fate of antibiotics in agroecosys- system function primarily focuses on soil microorganisms. 
tems, as well as their spatial and temporal distribution. Recently, Microcosm studies have shown that antibiotics in the environ-
predictive modeling has been proposed as an alternative to large- ment have the potential to alter the microbial biomass, affect 
scale and high-cost monitoring programs to assist in estimating community structure, and modify functional endpoints such 
expected concentrations of antibiotics at the landscape-scale as substrate-induced respiration, iron reduction, ammonifica-
(Boxall et al., 2014). These models rely on accurate antibiotic tion, N-mineralization, and nitrification (Schmitt et al., 2004; 
usage data as well as mechanistic knowledge of the metabolism, Hammesfahr et al., 2008; Gutiérrez et al., 2010; Kleineidam et 
fate and transport, and landscape and hydrologic processes; how- al., 2010; Solis et al., 2011; Toth et al., 2011). These alterations 
ever, usage data is not universally available, and data for a number in soil microbial function may in turn affect higher-level organ-
of medically important antibiotic classes are lacking. isms and ecosystem processes. Little is known about the effects of 
A number of pathways have been identified for the introduc- ARB or ARGs on ecosystem function. Various hypotheses have 
tion of antibiotics into agroecosystems, and their effect on the been proposed for alterations in microbial diversity, function, 
abundance and proliferation of ARB and ARGs may depend and composition (Martinez, 2009), as well as effects on wildlife 
on the specific pathway. Land application of manure solids and health (Gillings, 2014), but more evidence is necessary for their 
wastewater is a common route for antibiotics to enter the envi- thorough evaluation.
ronment. Application of manure, with or without antibiotics, While effects of single antibiotic compounds in agroecosys-
is a common practice and is known to increase both ARB and tems have been selectively characterized, toxicological impacts of 
ARGs (Pruden et al., 2006; Zhou et al., 2010; Udikovic-Kolic et mixtures are not well understood. Limited research on antibiotic 
al., 2014), but available data are limited, with inconsistent results mixtures has shown that combinations of compounds can often 
on both short- and long-term environmental impacts (Auerbach result in synergistic, antagonistic and additive effects, depending 
et al., 2007; Munir and Xagoraraki, 2011; Negreanu et al., 2012; on the compounds present (Yang et al., 2008; Liu et al., 2014). 
McLain and Williams, 2014), highlighting the need for further In addition, not only will mixtures of antibiotics be present, but 
research. so will their metabolites and other environmental toxins, such 
Although ARB and ARGs are present in manure, biosolids, as metals, which have been shown to affect mixture toxicity and 
and wastewater effluent, separating the effects of these compounds further enrich for ARB (Majewsky et al., 2014; Yu et al., 2015). 
from preexisting resistance found in populations of native Predicting the biological effects of these mixtures is challenging 
bacteria adds another level of complexity to modeling efforts. because changes in the composition of compounds can change 
Separating resistance of the pristine soils from that induced by mixture toxicity from synergistic to antagonistic due to altera-
the release of ARB, ARGs, and trace levels of antibiotics would tion in relative contribution of each compound (Liu et al., 2014). 
help confirm the relationship between antibiotic use with Given the complex mixtures of contaminants found in agroeco-
antibiotics and antibiotic resistance present in agroecosystems. systems, future environmental risk assessment of antibiotics must 
Another confounding factor when investigating antibiotic also evaluate the effects of these mixtures.
resistance is the intrinsic relationship between ARB and ARGs Finally, the expected link between the occurrence of ARB 
and the risks associated with each. Antibiotic resistant bacteria in the environment and agricultural systems has yet to be deter-
pose a direct risk to the three-agroecosystem health endpoints mined. The ARB from environmental sources are likely to spread 
based on the extensive studies of pathogenic bacteria. On the to agricultural systems given the documented links between 
other hand, ARGs pose an indirect risk with impacts linked to wildlife (e.g., birds) and common foodborne pathogens in agri-
HGT, yet little information is known about the transport and cultural products (Greig et al., 2015), indicating evidence of 
fate of extracellular DNA in the environment. transfer to animals and crops within an agroecosystem.
Currently, the health effects in humans who are exposed to 
low levels of antibiotics and ARB from environmental sources Challenges in the Measurement of Antibiotics and in 
are unknown. For antibiotics, various pathways exist for human Evaluating Their Impacts in Agroecosystems
exposure, including ingestion of contaminated food and water Detection and measurement of antibiotic residues are essen-
and inhalation of contaminated dust particles. Antibiotic tial for understanding their potential to adversely affect human 
residues have been measured in food crops, water sources, and health, ecosystem function, and agricultural systems, including 
animal-based food products, but often at levels several orders animal health. While the importance of accurate measurements 
of magnitude lower than the acceptable daily intake values is clear, prioritizing which antibiotics to measure is difficult. The 
in developed countries (Holmes et al., 2007). Although the potential for an antibiotic to have adverse impacts in agroecosys-
effects of long-term chronic exposures to low levels of antibiot- tems is directly related to its original use, in vivo, and its environ-
ics in humans have yet to be investigated, data suggest that low mental persistence and inherent biological activity. Not only is 
levels of antibiotics may select for ARB and/or ARGs (Lin et the wide variety of antibiotic compounds of concern, but some 
al., 2014). Off-target effects of antibiotics have shown that at 
380 Journal of Environmental Quality 
of their transformation products and metabolites may also affect selectivity for detecting antibiotics ( Johnson et al., 1990). Ion 
biological activity and therefore need to be considered when trap mass spectrometry can help identify transformation prod-
conducting environmental studies. Aga et al. (2016) examine the ucts, which is critical, as many transformation products retain 
state of the science for detection, quantification, and risk assess- antimicrobial properties (Diaz-Cruz and Barcelo, 2007).
ment of antibiotics and their transformation products in the Currently, standard methods do not exist for detection of 
agroecosystem. antibiotics in environmental samples, although some laborato-
The concentration of antibiotics and their metabolites in ries have used some variation of USEPA Method 1694 (USEPA, 
different environmental compartments vary greatly, but resi- 2007). Because methods are not yet standardized, well-described 
dues have been detected up to levels of milligram per kilogram procedures, including details of validation, are necessary to help 
in animal manure for persistent compounds, such as tetracy- make comparisons between studies. In addition, methods and 
clines and sulfonamides (Haller et al., 2002; Aga et al., 2005). procedures for determining limits of detection vary between lab-
Depending on environmental conditions, physicochemical char- oratories and have been the subject of environmental literature 
acteristics, and routes of entry, environmental concentrations of for decades (Keith et al., 1983). Without regulations to monitor 
the antibiotics and/or their metabolites typically decrease over the occurrence antibiotics in the environment, however, other 
time due to irreversible sorption to particulate matter, dispersion, means to stimulate development of standard analytical methods 
and/or degradation. In most environmental compartments, the are needed.
concentrations eventually fall below the limits of detection by Costs for quantifying antibiotics can be prohibitive in 
most analytical methods (Homem and Santos, 2011). However, some instances, leading to the development of screening tools 
even subinhibitory and nonlethal concentrations of antibiotics to quickly detect and measure antibiotics and to estimate bio-
and/or their metabolites have been shown to act as signaling availability. Enzyme-linked immunosorbent assay (ELISA) is 
molecules between microorganisms and may contribute to the often used as a screening tool and a semiquantitative method 
evolution of antibiotic resistance (Aminov, 2010). for determining total analyte concentrations within a class of 
The development of sensitive analytical methods is needed antibiotics (Aga et al., 2005). The value of this approach is that 
to measure environmentally relevant concentrations of antibiot- the ELISA has the ability to estimate bioavailability regardless 
ics in complex environmental samples. While instrumentation of a compound’s structure, while targeted analysis using LC/
has improved greatly in recent years with detection limits in MS/MS would not detect an unknown transformation product. 
the picogram per gram or parts per trillion range, difficulties in Bioreporters, genetically engineered cells capable of producing 
separating antibiotics and their degradation products from com- detectable signals in the presence of a target compound, may 
plex matrices (e.g., soils, manures, and wastewaters) still limits also be a useful alternative to chemical analysis (Meighen, 1991). 
the ability to accurately and reproducibly measure them (Wilga These tools have been used in aqueous and solid samples, and 
et al., 2008). An even greater challenge is the determination of matrix effects are corrected using a control strain that constitu-
the ecological implications and significance of the biologically tively produces bioluminescence. Bioreporters have already been 
available (bioavailable) fractions of antibiotics at their predicted developed for the detection of macrolides (Möhrle et al., 2007) 
environmental concentrations. The definition of bioavailability and tetracyclines (Korpela et al., 1998).
often varies considerably, mainly due to lack of standard meth- Whereas numerous studies have examined the occurrence of 
ods to measure this fraction in the environment. In addition, antibiotics in manure, soil, water and other matrices, less work 
bioavailability is dependent on the chemical analysis of extracted has focused on ecological effects and risk. To accurately assess 
compounds, which in turn depends on the efficiencies of the risk, toxicity data on antibiotics, transformation products, and 
extraction method. Unfortunately, absolute recovery of mul- contaminant mixtures are essential, but currently lacking. Due 
tiple residues from environmental matrices is typically not pos- to high costs of regional and national monitoring programs, 
sible, and even with improved analytical techniques, the fraction predictive models have become necessary to evaluate exposure 
recovered from soil or other matrices may not necessarily corre- and ecological risks of antibiotics in agroecosystems. Various 
spond with the fraction that plants or microbes are exposed to in proposed models have been useful in representing toxicity data 
the environment (Naidu, 2008). based on the type and concentration of contaminants (Loewe 
Quantitative analysis often requires elaborate extraction and and Muischnek, 1926; Bliss, 1939; Gonzalez-Pleiter et al., 
clean-up procedures to minimize interferences. The extraction 2013). Continued development of sensitive and robust analyti-
and clean-up technique of choice for aqueous samples is solid cal methods will permit improved measurement of bioavailable 
phase extraction (SPE) because of improved selectivity, speci- fractions of these compounds and improve risk analysis. Large-
ficity and reproducibility, minimal organic solvent consump- scale efforts involving multiple agencies and university research 
tion, shorter sample preparation time, ease of operation, and groups would be valuable in attempting to unify information 
the potential for automation (Poole, 2003). Preparation of solid and approaches to improve fate and risk assessment of antibiot-
and semisolid samples, such as manure or soil, is extremely chal- ics in agroecosystems.
lenging due to high concentrations of natural organic matter. 
Instrumental analysis using high performance liquid chromatog- How Should We Be Determining Background and 
raphy and tandem mass spectrometry (LC/MS/MS) has become Baseline Antibiotic Resistance Levels in Agroecosystem 
the primary analytical tool for quantification of antibiotics. Research?
High-resolution instruments such as quadrupole time-of-flight 
and Orbitrap MS (Thermo Scientific) are best suited for identi- While research in isolated and pristine environments indicates 
fication of unknowns, whereas triple quadrupole provides high that antibiotic resistance is an ancient phenomenon (Bhullar et 
Journal of Environmental Quality 381
al., 2012), the use of anthropogenic antibiotics also influences the sources that are widespread, which creates difficulty in acquiring 
presence of antibiotic compounds, ARB, and ARGs in an envi- background data (Chee-Sanford et al., 2009; Munir et al., 2011; 
ronment. Consequently, Rothrock et al. (2016b) emphasize that Garder et al., 2014). However, waters downstream of point 
the determination of background and baseline levels of antibi- sources of antibiotic-related contamination (e.g., wastewater 
otic resistance is crucial for an accurate assessment of the impacts treatment plant, animal feedlot) have consistently contained ele-
of anthropogenic inputs in agroecosystems. Universally accepted vated levels of ARGs compared with upstream (i.e., background) 
definitions of background and baseline levels are not found in samples (Sapkota et al., 2007; Storteboom et al., 2010). Similar 
the literature; therefore, for this review article, background is challenges in obtaining background and baseline data have 
defined as the concentration in an environment not influenced been observed in other agroecosystems, including aquaculture 
by local human activity, and baseline as the numerical average (Schmidt et al., 2000; Sobecky and Hazen, 2009; McDaniel et 
and/or range of antibiotic drugs, ARB, and/or ARGs levels pres- al., 2010; Seyfried et al., 2010; Tamminen et al., 2011) and hor-
ent at the beginning of a study (Rothrock et al., 2016b). Without ticulture (Duffy et al., 2011; Walsh et al., 2011; Popowska et al., 
knowledge of background and/or baseline levels at the begin- 2012). Given these inconsistent results and lack of background 
ning of a study, it is difficult to draw conclusions regarding the data, more information about antibiotic resistance in agroecosys-
impact of human activities in applied animal production systems tems is necessary to understand the links between environmen-
(Durso and Cook, 2014). Normalization of antibiotic resistance tal, human, and animal systems.
found in agroecosystems against background and baseline levels Despite some knowledge gaps in surveillance programs, suc-
will (i) allow evaluation of significant alterations in the occur- cessful antibiotic resistance surveillance programs exist globally 
rence of ARB and/or ARGs within a study, (ii) improve the abil- (DANMAP, 2014; NethMap, 2014; CDC, 2015; EUCAST, 
ity to compare results between studies, and (iii) identify links 2015; Public Health Agency of Canada, 2015). However, for 
between agricultural or environmental activities and treatments. datasets to be successfully correlated and compared, surveillance 
Research questions and experimental designs should be prop- programs would need to use standardized testing methods for 
erly framed so that background and baselines levels are estab- antibiotic resistance monitoring (Wray and Gnanou, 2000). 
lished and the data collected accurately assess impact. In addition, While attempts have been made to prioritize which antibiotic 
bacterial communities associated with antibiotic resistance need drugs from human and animal medicine should be examined 
to be considered during the experimental design phase. Native in antibiotic resistance research (Boxall et al., 2003; FDA, 
ARB are those that are ubiquitous in the environment before 2003; WHO, 2011), determining which drugs that may enter 
any anthropogenic influences; selected ARB are the subset of the agroecosystems pose the greatest risk to human, animal, and/
native community that are enriched in affected environments or ecological health is difficult. Therefore, with the purpose of 
following the application of manure or wastewater or release of aiding scientists working in agroecosystem research, an antibi-
antibiotic compounds; and adapted ARB are the gastrointesti- otic resistance decision-making tool (AR-DMT) was created to 
nal tract–associated bacteria that enter the environment through assist in selection of the most important and relevant antibiotics 
manure application and are incorporated into the soil flora. to evaluate given particular research goals/criteria, as well as to 
Animal manures are a major source of antibiotics, ARB, guide the experimental design process (Rothrock et al., 2016b). 
and ARGs that can potentially reach the environment. While Antibiotics are rated using three main criteria: (i) use within 
animals being fed antibiotics appear to have increased levels of agroecosystems, (ii) ranking within major scientific databases 
ARB and ARGs in their manure (Durso et al., 2012; Zhang et al., and surveillance programs, and (iii) target bacteria or ARB for 
2013), the effects of manure application in soil are less clear, with treatment. In short, once the user has provided the data of inter-
variable responses in ARB and ARG levels that do not directly est, the tool will provide the rankings of all of the World Health 
correlate with animals receiving antibiotic treatments (Udikovic- Organization critically important antibiotics for those specific 
Kolic et al., 2014). Likewise, ARB and ARGs are present in bio- search criteria (allowing the user to further investigate the most 
solids with HGT being demonstrated, yet data about biosolid appropriate class- or drug-specific ARG targets based on research 
application and the effects on ARB and ARGs in agroecosystems design or goals).
are contradictory (D’Costa et al., 2006; Brooks et al., 2007; Given the expansive diversity of antibiotic resistance–related 
Munir and Xagoraraki, 2011). targets, the agroecosystem antibiotic resistance research com-
The degree to which the resistome in modern soils has been munity is encouraged to begin a standardization of (i) defini-
influenced by human antibiotic use since the beginning of the tions of background and baseline antibiotic resistance levels, (ii) 
antibiotic era is not clear. While analyzing the resistomes of assessments of within and between study normalization, and (iii) 
background soils would help gauge the impact of agroeco- determination of the most appropriate antibiotic resistance–
systems on antibiotic resistance, few studies have focused on related targets in each agroecosystem. Adoption of these criteria 
background resistomes, and even fewer have included appro- when conducting antibiotic resistance–related research in agro-
priate background soils when analyzing impacted agricultural ecosystems would assist in accurately assessing the impacts of any 
soils. Based on research to date, soils appear to harbor distinct treatment or management regime. In addition, the inclusion of 
ARGs compared with human-associated microbial communities these data in publications would unify the scientific literature, 
(Gibson et al., 2015), and the large diversity of ARGs in soil may allowing for a broader and more accurate understanding of the 
favor preexisting genotypes rather than selecting for new ARGs direct and indirect effects that agriculture has on antibiotic resis-
(Udikovic-Kolic et al., 2014). tance in the environment.
The release of antibiotics, ARB, and/or ARGs into surface 
and groundwaters is often associated with urban and agricultural 
382 Journal of Environmental Quality 
Culture-based Methods for Detection of Antibiotic been found to be reliable and comparable in clinical settings. 
Resistance in Agroecosystems: Advantages, Challenges, The choice of method predominantly depends on the scope of research, but other considerations include laboratory limitations 
and Gaps in Knowledge and whether qualitative or quantitative results are desired (Baker 
The review by McLain et al. (2016) addresses the current et al., 1991; Joyce et al., 1992). While agar disk diffusion stud-
knowledge of culture-based techniques for the assessment of ies report numbers of isolates that are susceptible and resistant, 
antibiotic resistance in agroecosystems, including the wide-range broth microdilution methods are more quantitative and produce 
of methods, bacterial groups, and antibiotics commonly tar- MIC50 values that represent the concentration at which ≥50% of 
geted for resistance studies, data interpretation, and confound- the isolates in a population are inhibited. Given the quantitative 
ing factors. Numerous culture-based methods exist for analyzing nature of this method, researchers are encouraged to not overem-
antibiotic resistance in environmental bacteria with target bac- phasize MIC50 values in small test populations (10–30 isolates), 
teria isolated on either general or selective media. While culture when a few strains with high MIC values may skew the MIC50. 
techniques are time consuming, they have distinct advantages, Questions remain, however, regarding how many isolates are 
including direct identification and analysis of antibiotic resis- necessary per sample and how many samples within an agroeco-
tance in individual bacterial isolates. Culture-based methods system must be analyzed to produce a representative dataset for 
provide opportunities to link phenotypic and genotypic charac- accurate analysis of antibiotic resistance (Persoons et al., 2011).
teristics and assess ARG transfer potential, allowing for greater Culture-based methods have certain limitations, including 
understanding of overall resistance patterns, as well as identifi- inherent culture bias. Most of the bacterial species in soil and 
cation of multiple-antibiotic resistance within single organisms. water are not able to be cultivated; therefore, culture-based 
Standard clinical classification protocols exist that categorize approaches apply only to a small subset of the microbial spe-
a bacterial isolate as resistant, susceptible, or intermediate to an cies and do not provide the full spectrum of diversity present in 
antibiotic based on the bacterium’s growth at defined antibiotic environmental samples. When ARB are identified using both 
concentrations, known as breakpoints (Silley, 2012). In clini- culture- and molecular-based techniques, the results have been 
cal settings, these breakpoints, measured as MICs, are used to found to be different (Garcia-Armisen et al., 2013). Another 
determine specific dosage formulations for antibiotic treatment. notable limitation is that culture methods do not identify bac-
The MIC is the lowest concentration that will inhibit micro- teria that are in the viable but nonculturable state. This state has 
bial growth following overnight incubation for rapidly grown important implications with regard to antibiotic resistance, since 
bacteria (Andrews, 2001). These clinical breakpoint concentra- bacteria become resistant to antibiotics, yet have the potential to 
tions can alter over time and vary between the United States and eventually return to being metabolically active and pathogenic 
Europe, with standards published by the Clinical and Laboratory (Ehrlich et al., 2002). Another potential culture bias with regard 
Standards Institute (CLSI, 2015) and the European Committee to antibiotic resistance is the presence of persister cells that are 
on Antimicrobial Susceptibility Testing (EUCAST, 2015). dormant variants of regular cells and highly tolerant to antibiot-
The microorganisms that are commonly targeted in culture- ics (Lewis, 2010).
based studies to evaluate antibiotic resistance in agroecosystems Even with their limitations, culture-based methods are the 
are microbial groups that are clinically relevant and easy to cul- basis of international surveillance efforts to monitor antibiotic 
ture. Frequently, these target microorganisms are also indicators resistance, and standardized molecular methods are presently not 
of water quality. Generally, the most common microbes targeted available to replace them. While direct polymerase chain reaction 
for environmental analysis are Escherichia coli, Enterococcus spp., (PCR)-based and metagenomic techniques show great promise 
Salmonella spp., and Staphylococcus spp., and recent research in helping to characterize ARG diversity and abundance in com-
has suggested the addition of Aeromonas spp., Klebsiella pneu- plex environments, these methods do not enable functional vali-
monia, and Pseudomonas aeruginosa (Berendonk et al., 2015). dation of identified resistance mechanisms and generally cannot 
Salmonella spp. account for 38% of foodborne illnesses in the correlate between bacterial phyla and specific ARGs. Multiple 
United States (CDC, 2013). Enterococcus spp. and E. coli are cur- studies have compared the effectiveness of culture-based and 
rently used as water quality indicators by the USEPA (USEPA, phenotypic characterization with culture-independent methods 
2012), and Klebsiella pneumonia has been suggested as a model that generally target specific antibiotic resistant genes instead of 
organism based on its high persistence in the environment and bacteria, but no single method or group of methods has been 
animal guts (Tzouvelekis et al., 2012). The antibiotics selected identified as providing more accurate results ( Jorgensen and 
for these studies are typically those used in agriculture, as well as Ferraro, 2009; Campbell et al., 2011; Nordmann et al., 2012). 
those prescribed for human use. Other considerations for anti- Future assessment of antibiotic resistance in the environment 
biotic selection include mechanism of action and the extent to will depend on standardized methods and techniques that incor-
which they are used for prophylaxis, growth promotion, or treat- porate culture- and molecular-based procedures.
ment of disease in animals.
Before antibiotic resistance testing, identification of bacte- Molecular Methods for Assessment of Antibiotic Resistance 
rial isolates is essential. Once target organisms have been suc- in Agricultural Ecosystems: Prospects  and Challenges
cessfully isolated and identified, antibiotic resistance testing Luby et al. (2016) discuss existing molecular techniques for 
can be performed via three common methods: broth and agar identifying and tracking antibiotic resistance in agricultural eco-
dilution, agar disk diffusion, and E-tests. These three methods systems. Molecular methods offer the distinct advantage of pro-
for the analysis of antibiotic resistance are well standardized and viding direct information about the extractable pool of DNA, 
reproducible. The results for these culture-based techniques have 
Journal of Environmental Quality 383
RNA, and/or proteins within a sample. The isolated DNA, target DNA during the PCR reaction. As a quantitative method, 
RNA, or protein(s) can be sequenced and directly compared determination and reporting of limits of quantification are criti-
against publicly available databases. Utilization of molecular cal. In addition, normalization to 16S rRNA genes is believed to 
methods also helps to avoid biases associated with culture-based aid in accounting for minor variations in extraction efficiency as 
methods. For the analysis of antibiotic resistance in agroecosys- well as providing information about the proportion of total bac-
tems, molecular methods offer a means of tracking the fate of teria carrying ARGs in the sample (Pruden et al., 2006; Knapp 
various antibiotic resistance indicators in and between systems. et al., 2010; Heuer et al., 2011). Quantification of ARGs with 
Utilization of molecular methods as a measure of antibiotic qPCR methods has been successfully conducted on samples 
resistance analysis does require certain knowledge, including from diverse agroecosystems, including swine lagoons (Koike 
familiarity with common molecular techniques, properly framed et al., 2007), groundwater (Koike et al., 2007), river sediments 
research questions based on specific molecular targets, and (Pei et al., 2006), and manure and soil (Heuer and Smalla, 2007). 
awareness of advantages and disadvantages of various methods The development of qPCR arrays is a promising way to analyze 
for the correct interpretation of data. multiple targets; however, it may be best used as a screening tool 
Antibiotic resistant genes are the most common molecular since the limit of detection is higher than traditional qPCR. 
targets of interest when assessing antibiotic resistance in envi- One major drawback of PCR-based methods is that sequences 
ronmental samples. These genes encode various functions that for the genes of interest must be known and selected ahead of 
allow bacteria to survive and grow in the presence of antibi- time, which may bias the results and overlook key genetic ele-
otic concentrations that are inhibitory to susceptible cells. ments associated with antibiotic resistance.
Following the extraction of DNA from a sample, ARGs are Horizontal gene transfer is a key process to characterize since 
normally identified by PCR-based methods and, more recently, it is the means by which antibiotic resistance actually spreads 
by metagenomic techniques. However, the identification of an among bacteria. Documentation of HGT occurrence and poten-
ARG in a sample only indicates the potential for resistance tial can occur through PCR-based analysis of specific marker 
since the gene may not be expressed, may be in a nonfunctional genes associated with MGEs (Nandi et al., 2004), retrospective 
form (mutated or incomplete), or may be present in a dead cell genome or metagenome analysis (Nesme et al., 2014; Nesme and 
or as extracellular DNA. Simonet, 2015), and direct assays of transfer including conju-
Other common targets for antibiotic resistance analysis gation, transduction, and transformation (Coque et al., 2008; 
include RNA and proteins, which can be targeted to specifically Musovic et al., 2010; Seitz and Blokesch, 2013). Direct assays are 
track expression of antibiotic resistance mechanisms. However, useful for determining mechanisms of action, host ranges, and 
RNA- and protein-based methods are challenging techniques, transfer rates of ARGs on mobile elements as well as identifying 
and, as a result, DNA-based methods are generally preferred whether ARGs are functional. However, these analyses require 
for tracking ARGs. Horizontal gene transfer allows bacteria to that the recipient cells be culturable, which limits their applica-
share ARGs through MGEs, such as plasmids, integrons, and tion, especially in agroecosystem research. The use of a reporter 
transposons. Several studies have incorporated the analysis of gene, such as green fluorescent protein, could reduce the need for 
markers associated with MGEs when analyzing ARGs in soil and culturing and selection steps while still confirming that the genes 
manure (Nandi et al., 2004; Binh et al., 2008; Popowska et al., of interest are actually being expressed under the conditions of 
2012; Klümper et al., 2015), which provides a line of evidence the study (Klümper et al., 2015).
that gene transfer may be a factor in the proliferation of ARGs. The development of next-generation DNA sequencing 
Traditional PCR is one of the most popular methods of methods has led to a new era of molecular characterization of 
detecting known ARGs in environmental samples since it is environmental ecosystems. These technologies circumvent 
highly sensitive, provides relatively rapid results in 2 to 3 h, and the need for PCR and provide a broad snapshot of the ARGs, 
produces direct information about the DNA sequence of inter- MGEs, virulence genes, and various other functional genes in the 
est. Polymerase chain reaction is an enzyme-dependent reaction samples of interest. Application of metagenomic approaches to 
that utilizes highly specific primers that recognize sections of a agroecosystems has revealed a wide range of ARGs and MGEs 
target gene and amplify it. However, challenges and limitations (Kristiansson et al., 2011; Bengtsson-Palme et al., 2014). It also 
exist for applying PCR to samples from agroecosystems. One of provides broad contextual information beyond identification 
the most significant challenges is that PCR is dependent on the of ARGs and other targets of interest. Identification of HGT 
extraction of DNA, which should be optimized for the matrix elements can provide information about how ARGs may pass 
of interest to capture clean DNA from as many different kinds from one environment to another (Nesme and Simonet, 2015). 
of bacteria as possible and applied consistently across samples Identification of genes of interest from metagenomic datasets 
intended for comparison. When working with environmental is facilitated by publicly available databases and tools; however, 
samples, sequencing a subset of the PCR products obtained numerous challenges are associated with data analysis, and fur-
during analysis is advisable to verify that PCR is amplifying the ther development of approaches and consensus in the scientific 
intended product. community for standardized analysis would be beneficial.
Real-time quantitative PCR (qPCR) provides the same ben- Combining molecular- and culture-based methods presents 
efits as PCR, while yielding additional information about the some advantages and can assist in linking genotype with pheno-
copy number (or abundance) of a particular ARG. For qPCR, type. However, most culture-based assays require a great deal of 
use of a probe that fluoresces when bound to the target DNA or time and only recover a small subset of the total bacterial com-
dyes, like SYBR Green (Thermo Fisher Scientific), that bind to munity. A summary of the major pros and cons associated with 
double-stranded DNA allows detection of the amplification of using molecular- and culture-based methods is found in Table 
384 Journal of Environmental Quality 
2. Recent work has focused on expanding molecular-based tech- while also identifying those that are not known. The need for 
niques into single, rapid assays that would provide information risk assessment of antibiotics and antibiotic resistance in the 
about antibiotic resistance phenotypes. These molecular phe- environment is also critical but hindered by the lack of knowl-
notype methods include membrane hybridization ( Jindal et al., edge about the quantities and types of antibiotic drugs, ARB, 
2006) and fluorescent in situ hybridization (FISH) methods and ARGs that are present and where within the agroecosystem 
(Zhou et al., 2009) and have been applied to manure and soil they are located. Lastly, although selection of targets is normally 
samples. While membrane hybridization scales up more easily, driven by human and animal health, ecological health should be 
FISH has the capability of identifying resistant microorganisms another consideration.
when used in combination with phylogenetic probes (Zhou et Well-developed standard methods for accurate analysis of 
al., 2009). antibiotics, ARB, and ARGs from environmental samples are 
Regardless of the method or combination of methods rare. While methods have been developed for analysis of antibi-
selected, experimental design is paramount and must be care- otics and antibiotic resistance in clinical settings, these methods 
fully planned to address the research question(s) of interest. cannot readily be applied in environmental settings. The matrices 
Antibiotic resistance in agroecosystems is multifaceted not only found in agroecosystems are complex and routinely contain com-
because of the diverse environments within these systems but also pounds that interfere with subsequent analysis. Because standard 
because of the complexity of the origins of antibiotic resistance. methods have not been developed for antibiotic research in the 
A successful research design involves (i) inclusion of appropri- environment, most laboratories must develop their own meth-
ate controls and accounting for background and/or baseline ods. This severely limits the ability to make comparisons between 
antibiotic resistance, (ii) obtaining representative samples and samples analyzed in different laboratories and hinders risk assess-
statistical resolution in systems that may be spatially heteroge- ment analysis. The development of standard methods for the 
neous and temporally variable, (iii) accurately capturing the fac- detection and quantification of antibiotics, ARB, and ARGs in 
tors that may play critical roles in the field (e.g., application of agroecosystems is a critical research need.
manure, temperature, precipitation), (iv) garnering insight into Surveillance programs for monitoring antibiotics and anti-
ARG hosts and viability, and (v) combining methods to support biotic resistance in the environment are lacking to date. The 
multiple lines of evidence to support conclusions. development and implementation of these types of programs at 
local, national and international levels would provide long term, 
Knowledge Gaps and Future Research comprehensive information about how and where antibiotics 
Directions and antibiotic resistance are affecting agroecosystems. These programs would provide information about the overall impacts 
Currently, the pathways that allow antibiotic compounds, within agroecosystems to assist in determining areas that require 
ARB, and ARGs to move through the environment are not fully additional research focus. Surveillance data would also assist in 
understood. The causal model presented by Williams-Nguyen et identifying environmental reservoirs of antibiotics, ARB, and 
al. (2016) helps identify the environmental sectors or reservoirs ARGs; routes that allow these contaminants into and out of 
where these antibiotic contaminants may be found and outlines agroecosystems; and pathways that pose potential health risks 
the main pathways by which they may move through agroeco- to humans, animals, and other biota by allowing contact with 
systems. Yet this information is not complete, and additional contaminants.
research is necessary to fully elucidate current reservoirs and 
pathways of antibiotic-related contaminants in the environment, 
table 2. pros and cons associated with the use of culture- and molecular-based methods to evaluate antibiotic resistance is agroecosystems.
culture techniques
pros cons
•	Direct	identification	and	analysis	of	antibiotic	resistance	in	individual	 •	Time	consuming;	results	can	take	days
isolates
•	Opportunity	to	link	results	with	phenotypic	and	genotypic	 •	There	is	an	inherent	cultivation	bias;	easily	cultivated	microbes	are	
characteristics generally targeted most often
•	Ability	to	assess	antibiotic	resistance	gene	transfer	potential •	Not	all	microogansims	are	culturable;	cannot	identify	bacteria	that	are	
viable but nonculturable
•	Do	not	require	complex	instrumentation	and	can	be	performed	at	a	
relatively low cost
•	Can	be	used	to	determine	clinical	breakpoint	concentrations
molecular techniques
pros cons
•	Direct	detection	of	target	nucleic	acid	without	cultivation •	Entire	DNA	pool	cannot	be	extracted	from	environmental	samples
•	High	specificity	and	sensitivity •	Inability	to	distinguish	between	nonviable	and	viable	microorganisms	
and extracellular DNA
•	Results	obtained	from	traditional	polymerase	chain	reaction	(PCR)	and	 •	Detection	of	antibiotic	resistance	gene	only	indicates	a	potential	for	
real-time quantitative polymerase chain reaction (qPCR) within a few resistance
hours
•	Next-generation	sequencing	circumvents	need	for	PCR	and	provides	a	 •	While	useful	for	determining	gene	expression,	it	is	difficult	to	analyze	
broader snapshot of genes RNA and proteins
Journal of Environmental Quality 385
Conclusions This can be expressed in percentage by multiplying the ratio 
by 100. Absolute recovery does not take into account any 
The analysis of antibiotics and antibiotic resistance in agro- matrix suppression or enhancement in the detection system.
ecosystems is an important area of research that requires a One 
Health approach to fully understand the health implications of Acquired resistance. Antibiotic or antimicrobial resistance 
antibiotic drugs, ARB, and ARGs in the environment. Since the coded by genes obtained by transformation, transduction, 
use of antibiotics is not diminishing and incidences of antibiotic or conjugation. The term acquired resistance is typically used 
resistance are on the rise in human and animal populations, a in contrast to intrinsic or inherent resistance, in that the or-
greater understanding of the transport and fate of antibiotics, ganism exhibiting acquired resistance was previously sus-
ARB, and ARGs in the environment is critical to determine the ceptible to an antibiotic or antimicrobial.
possible risks and impacts on human, animal, and ecological 
health. While food production systems and biosolid applications Agroecosystem. Region of agricultural production func-
are recognized as significant input sources of antibiotic-related tionally defined as an ecosystem: land or water areas used 
contaminants, the direct and indirect impacts in agroecosys- for agricultural purposes (poultry houses, feedlots, aquacul-
tems are not known. Development of standard methods and ture, crop production fields and pastures, greenhouses, and 
practices among the scientific community is necessary for accu- adjacent areas including surface water, soil, and groundwa-
rate identification and quantification of antibiotics, ARB, and ter). Includes living and nonliving components and agricul-
ARGs in soil, water, manure and other environmental matrices. tural inputs and outputs such as feed, manure, fertilizers, 
Additional focus on standard research methods and practices and biosolids.
is a critical first step in obtaining the reliable data necessary to Antibacterial. Any natural, semisynthetic, or synthetic 
provide a comprehensive evaluation of antibiotics and antibiotic compound that results in bacterial cell death or inhibition 
resistance in agroecosystems and begin to determine the poten- of bacterial growth. Disinfectants and antiseptics with an-
tial risks to human, animal, and ecological health. tibacterial activity are considered antibacterial, as are iono-
Glossary phores (see Fig. 1).
The accurate analysis and discussion of antibiotic resistance Antibiotic. A chemical used to treat infectious bacterial 
in agroecosystems requires a precise and standardized vocabu- diseases in humans, animals, or plants that results in bac-
lary, in addition to the use of adequate experimental controls. terial cell death or inhibition of bacterial growth. This in-
Many terms used when describing antibiotic resistance research cludes natural, semisynthetic, and synthetic compounds. 
have meanings that vary across disciplines or do not have clearly Antibiotics are a subset of antibacterials (see Fig. 1).
established definitions. For example, the terms antimicrobial and Antibiotic class. A group of chemically related antibiotics 
antibiotic are often used interchangeably; however, in this review, having a similar mode of action on susceptible bacteria.
antimicrobial is defined as a natural, semisynthetic or synthetic 
chemical that kills or inhibits the growth of microorganisms, and Antibiotic resistance. The ability of a microorganism to 
antibiotics are described as the subset of antibacterial compounds survive and/or grow in the presence of an antibiotic at a 
that target bacteria (Fig. 1). concentration that would normally prevent its growth or 
Absolute recovery. The ratio of the instrument response reproduction.
(e.g., area) of the analyte spiked into the sample before ex- Antibiotic resistance gene (ARG). A gene conferring 
traction to the response of the analyte spiked in a pure solvent resistance to one or more antibiotics or different antibi-
(standard solution), defined at a particular concentration. otic classes. Genes involved in the transfer or expression 
fig. 1. concept diagram of antimicrobial chemicals, 
which may be natural, semisynthetic, or synthetic 
and are used to kill or inhibit the growth of microor-
ganisms. Antibiotics, a subset of antibacterials, are 
a type of antimicrobial used in the treatment and 
prevention of bacterial infections.
386 Journal of Environmental Quality 
of resistance genes are not included in this definition since However, since the potential exists for two or more cells to 
they are considered mobile genetic elements, not ARGs. stick to each other, land in the same place on the agar, and 
result in only a single colony instead of more, it is customary 
Antibiotic resistant bacteria (ARB). Bacteria able to grow to refer to the plate counts in terms of number of colonies, 
in the presence of an antibiotic at a particular concentra- not number of cells.
tion. The specific concentration is either determined empir-
ically by clinical standards that correlate phenotypic isolate Concentrated animal feeding operation (CAFO). 
measurements with treatment failure, or epidemiologically Regulated animal agriculture enterprise that utilizes high-
by determining the concentration of the target drug that density livestock production requiring feed delivery to the 
inhibits the growth of the majority of strains in a species. animals, as opposed to grazing, where designation is given 
on the basis of the number of animal units (e.g., 1000 or 
Antibiotic resistant determinant (ARD). An older term more cattle in the United States) or in the collection and 
that is equivalent to ARG. It is generally no longer used discharge of livestock waste.
and has been replaced by the term antibiotic resistance gene 
(ARG). Conjugation. Cell-to-cell mediated gene transfer of a mo-
bilizable genetic element, plasmid, or transposon. It requires 
Antimicrobial. Any chemical compound (natural or that a live donor and live recipient have physical contact 
synthetic) that inhibits growth or kills microorganisms. with each other and be actively growing.
Antimicrobials include antibacterial, antiviral, antiproto-
zoal, and antifungal compounds. Disinfectants, antiseptics, Epidemiological cutoff value (ECOFF). The normal dis-
and ionophores are also considered antimicrobial agents. tribution of MIC breakpoints (see below) in a given bacte-
This is a general term for agents used against all microbes, rial species.
not just bacteria (see Fig. 1).
European Committee on Antimicrobial Susceptibility 
Antimicrobial resistance. The ability of a microorganism Testing (EUCAST). A standing European committee 
to grow and survive the toxic effects of exposure to an anti- aimed at developing MIC breakpoints (see below) for se-
microbial agent. lected antibiotics toward specific bacteria. Can be consid-
ered the European counterpart of the Clinical Laboratory 
Background. The concentration of antimicrobial drugs, an- Standards Institute.
tibiotic resistant bacteria, or antibiotic resistance genes that 
would exist without a local anthropogenic source or stressor Extraction recovery. The ratio of the instrument response 
being present. Background can be represented by a range (e.g., area) of the analyte spiked into the sample before ex-
rather than an absolute value. traction to the response of the analyte spiked in a sample 
after extraction (sample matrix), defined at a particular 
Baseline. Concentration of antibiotic drug, resistant bac- concentration. This can be expressed in percentage by mul-
teria, or resistance genes representing the present state of tiplying the ratio by 100. Extraction efficiency accounts for 
the sampled environment and used to provide information matrix suppression or enhancement in the detection system 
against which any changes can be measured. because the analyte response is relative to the signal of the 
Broad host range plasmid (BHP). A plasmid that can be spiked standard in the sample matrix.
transferred and maintained in phylogenetically diverse bac- Feed additive. A food supplement for livestock production, 
teria, which represent multiple genera. including vitamins, amino acids, fatty acids, minerals, ste-
Clinical Laboratory Standards Institute (CLSI). A US- roid hormones, and antimicrobials.
based not-for-profit organization established with the ob- Horizontal gene transfer (HGT). Transfer of genes and/
jective of developing clinical and laboratory practices and or mobile elements between bacteria in a manner other 
promoting their use worldwide. Among other things, the than traditional meiosis. The three most studied mecha-
CLSI develops MIC (see below) guidelines for specific an- nisms of HGT in bacteria are conjugation, transformation, 
tibiotics against various human-associated commensals and and transduction, although other mechanisms exist. Lateral 
pathogens. gene transfer is occasionally used as a synonym.
Clonal. In reference to bacteria, this term refers to bacterial Integrons. A mobile genetic element found on bacterial 
cells arising via the process of binary fission from a single chromosomes and/or plasmids composed of an integrase-
source and are assumed to be more closely related to each encoding gene and an integration site where gene cassettes 
other than isolates from other clones. can be inserted via site-specific recombination. Integrons of-
Colony-forming unit (CFU). A unit used to evaluate the ten harbor antibiotic resistance genes. They can collect mul-
number of viable bacteria or fungal cells in a sample. The tiple gene cassettes and are therefore often associated with 
process of calculating colony forming units includes serial multidrug resistance. Not unique to prokaryotes.
dilutions of the sample, plating on agar medium, and count- Internal standard. A known amount of compound that is 
ing the resulting colonies. The intention is to separate cells, added to samples, blanks, and calibration solutions that has 
so that each individual cell grows into a bacterial colony. a very similar structure and behavior with the analyte, yet 
Journal of Environmental Quality 387
different enough to have a separate and distinguishable sig- ratios than selected ion monitoring that is performed in a 
nal from the analyte. Inefficiencies in sample preparation, single quadrupole LC/MS.
matrix effects, and drift in instrument performance should 
have similar effects on the signals of both the analyte and Limit of detection (LOD). In analytical chemistry, LOD 
the internal standard; thus, using the ratio of the two signals is the lowest amount of analyte that gives a signal that is dis-
in calculating analyte concentrations reduces variability and tinguishable from the background signal of the sample ma-
improves accuracy of the analytical method. trix in the absence of that analyte. The LOD is typically cal-
culated as the analyte concentration corresponding to three 
Intrinsic resistance. Antibiotic or antimicrobial resistance times the standard deviation of the blank signal (n = 7). In 
that results from the structural or functional properties microbiology, LOD is the lowest number of target cells or 
inherent to a particular bacterial species. These inherent genes that can be detected and measured per unit of mass or 
properties predate the antibiotic era and are chromosom- volume using a specific assay.
ally encoded or bacteria lack a pathway/target site. These 
traits are transmitted vertically from mother to daughter Limit of quantification (LOQ). The lowest concentration 
cells. For example, Gram-negative bacteria are intrinsically of a compound that can be determined with both precision 
resistant to vancomycin due to the inability of the drug to and accuracy, under a stated level of confidence (e.g., 95% 
cross the outer membrane, and anaerobic bacteria are intrin- confidence level). The LOQ is typically calculated as the an-
sically resistant to aminoglycosides because uptake of the alyte concentration corresponding to 10 times the standard 
drug is linked to electron transport, which is not present in deviation of the blank signal (n = 7).
anaerobic bacteria. The term is used in contrast to acquired Matrix effects. The combined effects on an analytical signal 
resistance. The term innate resistance is sometimes used as a from components of a sample other than the analyte result-
synonym for intrinsic resistance. For example, if the genus, ing in reduced accuracy, reproducibility, and sensitivity of a 
such as mycoplasma, does not make a cell wall, they have method. Matrix effects can cause signal suppression or en-
always been intrinsically resistant to all b-lactam antibiotics. hancement in analysis by gas or liquid chromatography with 
Ionophores. A chemical compound that facilitates the mass spectrometric detection. Percentage matrix effects can 
transport of ions across a cell membrane, either by binding be evaluated by determining the ratio of the analyte response 
with the ion or by creating a channel through the mem- recorded for the analyte spiked in a sample after extraction 
brane. Ionophores disrupt membrane potentials by con- (sample matrix) to the response of the same amount of ana-
ducting ions through a lipid membrane in the absence of lyte spiked in a pure solvent (standard solution).
a protein pore and thus exhibit cytotoxic properties. Used Metabolites. Reaction products formed during the biologi-
as antimicrobial agents in food animal production, iono- cal degradation of chemical compounds through enzyme-
phores alter rumen fermentation by increasing the amount catalyzed reactions that leads to conjugation, bond cleavage, 
of food that is digested by the animal. Ionophores are com- isomerization, and/or other chemical modifications on the 
monly classified as antibiotics; however, they are not used in parent compound.
human medicine.
Minimum inhibitory concentration (MIC). A measure-
Isotope dilution. A method of standard addition by which ment equal to the lowest concentration of the target drug 
a known amount of a stable isotope-labeled analyte is add- that is able to inhibit the visible growth of a bacterium after 
ed to a sample before extraction. The concentration of the a specified period of time, most commonly an overnight in-
unknown analyte (native) is then determined based on its cubation using a standardized method.
signal relative to the signal of the known isotope-labeled 
analog and a previously determined response factor. The Mobile genetic element (MGE). Genes involved in the 
response factor is the ratio of the detector response of the transfer or expression of resistance genes and DNA that 
same amounts of the native analyte and isotope-labeled move within cells or between genomes, including integrons, 
analyte. Quantification by isotope dilution provides an au- plasmids, insertion sequences, transposons, conjugative 
tomatic correction for sample losses and matrix effects in transposons, and bacteriophage. Antibiotic resistance genes 
the target analyte concentration because the isotope-labeled are normally associated with MGEs; however, a MGE does 
analyte is subjected to the same conditions and procedures not have to be associated with an ARG.
as the unknown native analyte.
Multi-drug resistance (MDR). In general, the state where-
LC/MS/MS. An analytical method that involves separa- by a microbe is classified as resistant to more than two or 
tion of multiple analytes using high performance liquid three antibiotic classes; however, a specific functional defi-
chromatography (LC) and detection by tandem mass spec- nition varies widely. In human and veterinary treatment 
trometry (MS/MS). Trace analysis of organic compounds settings, the term refers to a demonstrated resistance of iso-
such as antibiotics using LC/MS/MS is typically performed lates. However, the term is also widely used when describ-
using multiple reaction monitoring in a triple quadrupole ing the carriage of ARGs, which may or may not have the 
MS but may also be performed in an ion-trap MS. LC/MS/ capacity to be expressed. One common definition is that an 
MS is more selective and provides higher signal-to-noise organism carries more than two or three different resistance 
genes or mutations in different targets that confer resistance 
388 Journal of Environmental Quality 
to different classes of antibiotics. When used in this way, the ensure the integrity of results and that specific criteria are 
term does not apply when a single ARG confers resistance met. QA/QC typically includes a number of different tech-
to multiple classes of antibiotics such as the erm genes con- niques used to validate the results of analytical measure-
ferring resistance to macrolides, lincosamides, and strepto- ments, including the preparation and analysis of fortified 
gramin B. Due to the lack of consensus on the definition matrix and laboratory blanks, replicate sample analysis, or 
of this term, it is recommended that it be clearly defined in inclusion of a surrogate for monitoring recovery between 
the materials and methods sections when reporting in the samples.
scientific literature.
Resistome. The resistance gene reservoir; all existing antibi-
National Antimicrobial Resistance Monitoring System otic resistance genes (ARGs) in both pathogenic and non-
for Enteric Bacteria (NARMS). A public health surveil- pathogenic bacteria, usually defined within a given site, e.g., 
lance system that tracks changes in the antimicrobial sus- “the human gut resistome,” or “the soil resistome.”
ceptibility of certain enteric (intestinal) bacteria found in ill 
people, retail meats, and food animals in the United States. Silent/cryptic resistance. Phenotypic susceptibility to the 
target antibiotic concurrent with carriage of genes that code 
Narrow-host-range plasmids (NHP). Plasmids that are for resistance to the target but are not expressed. This type 
only shared within genera or between isolates within a single of resistance may become clinically important if expression 
species. The Haemophilus plasmids are an example of NHP. is restored by mutation or mobilization.
One Health. The concept that human, veterinary, and en- Solid phase extraction (SPE). A sample preparation tech-
vironmental health are not separate entities, but are inter- nique that combines clean-up and concentration of analytes 
connected. It is the collaborative effort of multiple disci- into one procedure by passing the liquid sample through a 
plines—working locally, nationally, and globally—to attain solid stationary phase to separate the target analytes from 
optimal health for people, animals, and the environment. the rest of the sample matrix. Separation of analytes can be 
achieved by selectively adsorbing them in the solid station-
Plasmid. Small, heritable, double-stranded DNA distinct ary phase and letting the rest of the sample components pass 
from the chromosome. It can replicate independently or through, or vice versa. In practice, many other compounds 
integrate into bacterial chromosome and often carry nones- in the sample, other than the target analytes, are coextracted 
sential host genes, including ARGs. and concentrated with the analytes, potentially leading to 
Polymerase chain reaction (PCR). A technology in mo- significant matrix effects.
lecular biology used to amplify a piece of DNA across sev- Standard addition (SA). A quantification method where-
eral orders of magnitude, generating thousands to millions by a known amount of analyte is added to the sample, before 
of copies of a particular DNA sequence. The method relies or after extraction. If added before extraction, losses during 
on thermal cycling, consisting of cycles of repeated heating sample extraction can be taken into account; this approach 
and cooling of the reaction for DNA melting and enzymatic can be time consuming and costly and may only be possible 
replication of the DNA. Primers (short DNA fragments) if enough sample is available for extraction of spiked and un-
containing sequences complementary to the target region, spiked samples. If added after extraction, sample processing 
along with a DNA polymerase, the enzyme catalyzing DNA is shortened but losses during extraction are not corrected 
replication, are key components to enable selective and re- for in the quantification of the analyte. One-point standard 
peated amplification. addition, whereby only one concentration of analyte is add-
Pressurized liquid extraction (PLE). A method of sample ed to a sample, can be performed if the concentration of the 
extraction that incorporates the use of liquid solvents at in- analyte and the added sample are within the linear range. 
creased temperature and pressure, sometimes approaching If the unknown concentrations in the samples are expected 
the supercritical region. Increased temperature results in to be widely variable, a series of increasing concentrations 
higher rates of diffusion and increased solubility while the of standards are added into various samples; the total addi-
increased pressure keeps the solvent from reaching its boil- tive signal from the analyte and the standard added are plot-
ing point. The combination allows for efficient extraction ted against the concentration added. A linear regression of 
while limiting solvent consumption. these responses, extrapolated to zero, is used to calculate the 
concentration of the analyte in the original sample.
Proto-resistance. A state whereby a sample contains genes 
with no current activity against antibiotics but that have the Surrogate. A compound that is chemically similar to the 
potential to gain this function, i.e., genes that confer sub- analyte of interest and is added in known amounts to sam-
minimum inhibitory concentration (MIC) levels of resis- ples. Surrogates are used to determine extraction efficiencies 
tance that combined with subsequent mutations or acquisi- and matrix interferences and, therefore, should behave simi-
tion of additional genes can generate full MICs. larly to the analytes in the experimental samples.
Quality assurance/quality control (QA/QC). The com- Transduction. Viral-mediated transfer of bacterial DNA 
plete set of procedures used to measure and document from one host cell to another; primarily among closely re-
the quality of data produced from an analytical process to lated strains.
Journal of Environmental Quality 389
Transformation product. In chemistry: stable, or relatively Baker, C.N., S.A. Stocker, D.H. Culver, and C. Thornsberry. 1991. Comparison 
stable, intermediary compounds formed by the incomplete of the E test to agar dilution, broth microdilution, and agar diffusion susceptibility testing techniques by using a special challenge set of bacteria. 
mineralization of a parent compound. In biology: a mosaic J. Clin. Microbiol. 29:533–538.
gene that has some new nonhost DNA sequences mixed Batt, A.L., D.D. Snow, and D.S. Aga. 2006. Occurrence of sulfonamide 
with host DNA, often conferring new properties such as antimicrobials in private water wells in Washington County, 
Idaho, USA. Chemosphere 64:1963–1971. doi:10.1016/j.
increased resistance to an antibiotic. chemosphere.2006.01.029
Bengtsson-Palme, J., F. Boulund, J. Fick, E. Kristiansson, and D.G.J. Larsson. 
Transposons and conjugative transposons. Transposons 2014. Shotgun metagenomics reveals a wide array of antibiotic resistance 
are small self-contained segments of DNA that can insert genes and mobile elements in a polluted lake in India. Front. Microbiol. 
themselves into a chromosome or plasmids within a host 5:1–14. doi:10.3389/fmicb.2014.00648
Berendonk, T.U., C.M. Manaia, C. Merlin, D. Fatta-Kassinos, E. Cytryn, 
bacterial cell. Conjugative transposons have the same ability F. Walsh, H. Burgmann, H. Sorum, M. Norstrom, M.-N. Pons, 
to move within a host among different DNA regions but N. Kreuzinger, P. Huovinen, S. Stefani, T. Schwartz, V. Kisand, F. 
also carry additional genes that allow transfer from one host Baquero, and J.L. Martinez. 2015. Tacking antibiotic resistance: 
The environmental framework. Nat. Rev. Microbiol. 13:310–317. 
bacterial cell to another. doi:10.1038/nrmicro3439
Bhullar, K., N. Waglechner, A. Pawlowski, K. Koteva, E.D. Banks, M.D. Johnston, 
Vertical gene transfer. In bacteria, the transfer of genetic H.A. Barton, and G.D. Wright. 2012. Antibiotic resistance is prevalent in 
material from mother to daughter cells through asexual re- an isolated cave microbiome. PLoS ONE 7:E34953. doi:10.1371/journal.
production. The term clonal, or clonal spread, is a synonym. pone.0034953
Binh, C.T.T., H. Heuer, M. Kaupenjohann, and K. Smalla. 2008. Piggery 
Wastewater. Spent or used water that has been adversely manure used for soil fertilization is a reservoir for transferable antibiotic resistance plasmids. FEMS Microbiol. Ecol. 66:25–37. 
affected by anthropogenic processes (agricultural, indus- doi:10.1111/j.1574-6941.2008.00526.x
trial, and municipal), typically resulting in diminished or Bliss, C.I. 1939. The toxicity of poisons applied jointly. Ann. Appl. Biol. 26:585–
impaired quality. 615. doi:10.1111/j.1744-7348.1939.tb06990.x
Boxall, A.B.A., L.A. Fogg, P. Kay, P.A. Blackwel, E.J. Pemberton, and A. Croxford. 
Wastewater treatment plant (WWTP). A facility that re- 2003. Prioritisation of veterinary medicines in the UK environment. Toxicol. Lett. 142:207–218. doi:10.1016/S0378-4274(03)00067-5
ceives wastewaters from domestic and/or industrial sources Boxall, A.B.A., V.D.J. Keller, J.O. Straub, S.C. Monteiro, R. Fussell, and R.J. 
and that through a combination of physical, chemical, and Williams. 2014. Exploiting monitoring data in environmental exposure 
biological processes, treats the wastewater to reduce concen- modelling and risk assessment of pharmaceuticals. Environ. Int. 73:176–185. doi:10.1016/j.envint.2014.07.018
trations of regulated contaminants. Brooks, J.P., S.L. Maxwell, C. Rensing, C.P. Gerba, and I.L. Pepper. 2007. 
Occurrence of antibiotic-resistant bacteria and endotoxin associated 
with the land application of biosolids. Can. J. Microbiol. 53:616–622. 
Acknowledgments doi:10.1139/W07-021
We thank all of the authors who contributed papers to this special Campbell, P.J., G.P. Morlock, R.D. Sikes, T.L. Dalton, B. Metchock, A.M. 
section, which would not have been possible without their efforts. This Starks, D.P. Hooks, Cowan, L.S., B.B. Plikaytis, and J.E. Posey. 2011. 
project was supported by the Agriculture and Food Research Initiative Molecular detection of mutations associated with first- and second-line 
Competitive Grant no. 2013-68003-21256 from the USDA National drug resistance compared to conventional drug susceptibility testing of Mycobacterium tuberculosis. Antimicrob. Agents Chemother. 55:2032–
Institute of Food and Agriculture. 2041. doi:10.1128/AAC.01550-10
CDC. 2013. Antibiotic resistance threats in the United States, 2013. Centers 
References for Disease Control and Prevention. http://www.cdc.gov/drugresistance/
threat-report-2013 (accessed 22 Dec. 2015).
Aga, D.S., M. Lenczewski, D.D. Snow, J. Muurinen, J. Sallach, and J. Wallace. CDC. 2015. National Antimicrobial Resistance Monitoring System for Enteric 
2016. Challenges in the measurement of antibiotics and in evaluating their Bacteria (NARMS). Centers for Disease Control and Prevention. http://
impacts in agroecosystems: A critical review. J. Environ. Qual. 45:407– www.cdc.gov/narms (accessed 22 Dec. 2015).
419. doi:10.2134/jeq2015.07.0393 Chee-Sanford, J.C., R.I. Mackie, S. Koike, I.G. Krapac, Y.F. Lin, A.C. Yannarell, S. 
Aga, D.S., S. O’Connor, S. Ensley, J.O. Payero, D. Snow, and D. Tarkalson. 2005. Maxwell, and R.I. Aminov. 2009. Fate and transport of antibiotic residues 
Determination of the persistence of tetracycline antibiotics and their and antibiotic resistance genes following land application of manure. J. 
degradates in manure-amended soil using enzyme-linked immunosorbent Environ. Qual. 38: 1086–1108. doi:10.2134/jeq2008.0128
assay and liquid chromatography-mass spectrometry. J. Agric. Food Chem. 
53:7165–7171. doi:10.1021/jf050415+ CLSI. 2015. CLSI Standards Center. Clinical Laboratory Standards Institute. http://clsi.org/standards/ (accessed 22 Dec. 2015).
Amarakoon, I.D., F. Zvomuya, S. Sura, F.J. Larney, A.J. Cessna, S. Xu, and T.A. 
McAllister. 2016. Dissipation of antimicrobials in feedlot manure compost Coque T.M., F. Baquero, R. Canton. 2008. Increasing prevalence of ESBL-
after oral administration versus fortification after excretion. J. Environ. producing Enterobacteriaceae in Europe. Euro Surveill. 13:5437–5453.
Qual. 45:503–510. doi:10.2134/jeq2015.07.0408 Cox, G., and G.D. Wright. 2013. Intrinsic antibiotic resistance: Mechanisms, 
Aminov, R.I. 2010. A brief history of the antibiotic era: Lessons learned origins, challenges, and solutions. Int. J. Med. Microbiol. 303:287–292. 
and challenges for the future. Front. Microbiol. 1:134. doi:10.3389/ doi:10.1016/j.ijmm.2013.02.009
fmicb.2010.00134 DANMAP. 2014. DANMAP 2013: Use of antimicrobial agents and occurrence 
Andrews, J.M. 2001. Determination of minimum inhibitory concentrations. J. of antimicrobial resistance in bacteria from food animals, food, and humans 
Antimicrob. Chemother. 48:5–16. doi:10.1093/jac/48.suppl_1.5 in Denmark. http://www.danmap.org/~/media/Projekt%20sites/Danmap/DANMAP%20reports/DANMAP%202013/DANMAP%20
Ashbolt, N.J., A. Amézquita, T. Backhaus, P. Borriello, K.K. Brandt, P. 2013.ashx (accessed 22 Dec. 2015)
Collignon, A. Coors, R. Finley, W.H. Gaze, T. Heberer, J.R. Lawrence, 
D.G. Larsson, S.A. McEwen, J.J. Ryan, J. Schönfeld, P. Silley, J.R. Snape, D’Costa, V.M., K.M. McGrann, D.W. Hughes, and G.D. Wright. 2006. 
C. Van den Eede, and E.E. Topp. 2013. Human health risk assessment Sampling the antibiotic resistome. Science 311:374–377. doi:10.1126/
(HHRA) for environmental development and transfer of antibiotic science.1120800
resistance. Environ. Health Perspect. 121:993–1001. doi:10.1289/ Diaz-Cruz, M.S., and D. Barcelo. 2007. Recent advances in LC-MS residue 
ehp.1206316 analysis of veterinary medicines in the terrestrial environment. TrAC, 
Auerbach, E.A., E.E. Seyfried, and K.D. McMahon. 2007. Tetracycline resistance Trends Anal. Chem. 26:637–646. doi:10.1016/j.trac.2007.04.004
genes in activated sludge wastewater treatment plants. Water Res. Ding, C., and J. He. 2010. Effect of antibiotics in the environment on microbial 
41:1143–1151. doi:10.1016/j.watres.2006.11.045 populations. Appl. Microbiol. Biotechnol. 87:925–941. doi:10.1007/
s00253-010-2649-5
390 Journal of Environmental Quality 
Duffy, B., F. Walsh, C. Pelludat, E. Holliger, C. Oulevet, and F. Widmer. Hammesfahr, U., H. Heuer, B. Manzke, K. Smalla, and S. Thiele-Bruhn. 2008. 
2011. Environmental monitoring of antibiotic resistance and impact Impact of the antibiotic sulfadiazine and pig manure on the microbial 
of streptomycin use on orchard bacterial communities. Acta Hortic. community structure in agricultural soils. Soil Biol. Biochem. 40:1583–
896:483–488. doi:10.17660/ActaHortic.2011.896.71 1591. doi:10.1016/j.soilbio.2008.01.010
Durso, L.M., and K.L. Cook. 2014. Impacts of antibiotic use in agriculture: Hancock, R.E., and D.P. Speert. 2000. Antibiotic resistance in Pseudomonas 
What are the benefits and risks? Curr. Opin. Microbiol. 19:37–44. aeruginosa: Mechanisms and impact on treatment. Drug Resist. Updat. 
doi:10.1016/j.mib.2014.05.019 3:247–255. doi:10.1054/drup.2000.0152
Durso, L.M., D.N. Miller, and B.J. Weinhold. 2012. Distribution and Heuer, H., H. Schmitt, and K. Smalla. 2011. Antibiotic resistance gene spread 
quantification of antibiotic resistant genes and bacteria across agricultural due to manure application on agricultural fields. Curr. Opin. Microbiol. 
and non-agricultural metagenomes. PLoS One 7:e48325 doi:10.1371/ 14:236–243. doi:10.1016/j.mib.2011.04.009
journal.pone.0048325 Heuer, H., and K. Smalla. 2007. Manure and sulfadiazine synergistically 
Durso, L.M., D.A. Wedin, J.E. Gilley, D.N. Miller, and D.B. Marx. 2016. increased bacterial antibiotic resistance in soil over at least two months. 
Assessment of selected antibiotic resistances in ungrazed native Nebraska Environ. Microbiol. 9:657–666. doi:10.1111/j.1462-2920.2006.01185.x
prairie soils. J. Environ. Qual. 45:454–462. doi:10.2134/jeq2015.06.0280 Hollis, A., and Z. Ahmed. 2013. Preserving antibiotics, rationally. N. Engl. J. 
Ehrlich, G.D., R. Veeh, X. Wang, J.W. Costerton, J.D. Hayes, F.Z. Hu, B.J. Daigle, Med. 369:2474. doi:10.1056/NEJMp1311479
M.D. Ehrlich, and J.D. Post. 2002. Mucosal biofilm formation on middle- Holmes, P., A. Boxall, P. Johnson, K. James, L. Assem, and L.S. Levy. 2007. 
ear mucosa in the chinchilla model of otitis media. JAMA 287:1710–1715. Evaluation of the potential risks to consumers from indirect exposure 
EUCAST. 2015. European Committee on Antimicrobial Susceptibility Testing. to veterinary medicines: Final report to UK Veterinary Medicines 
http://www.eucast.org/ (accessed 22 Dec. 2015). Directorate. Institute of Environment and Health, Bedfordshire, UK.
FDA. 2003. Evaluating the safety of antimicrobial new animal drugs with regard Homem, V., and L. Santos. 2011. Degradation and removal methods of 
to their microbiological effects on bacteria of human health concern. antibiotics from aqueous matrices: A review. J. Environ. Manage. 92:2304–
No. 152. US Dep. of Health and Human Services, Food and Drug 2347. doi:10.1016/j.jenvman.2011.05.023
Administration. http://www.fda.gov/downloads/AnimalVeterinary/ Jindal, A., S. Kocherginskaya, A. Mehboob, M. Robert, R.I. Mackie, L. 
GuidanceComplianceEnforcement/GuidanceforIndustry/UCM052519. Raskin, and J.L. Zilles. 2006. Antimicrobial use and resistance in swine 
pdf (accessed 22 Dec. 2015) waste treatment systems. Appl. Environ. Microbiol. 72:7813–7820. 
Franklin, R.B., and A.L. Mills. 2009. Importance of spatially structured doi:10.1128/AEM.01087-06
environmental heterogeneity in controlling microbial community Joffe, M., M. Gambhir, M. Chadeau-Hyam, and P. Vineis. 2012. Causal 
composition at small spatial scales in an agricultural field. Soil Biol. diagrams in systems epidemiology. Emerg. Themes Epidemiol. 9:1. 
Biochem. 41:1833–1840. doi:10.1016/j.soilbio.2009.06.003 doi:10.1186/1742-7622-9-1
Franklin, A.M., C.F. Williams, D.M. Andrews, E.E. Woodward, and J.E. Watson. Johnson, J.V., R.A. Yost, P.E. Kelley, and D.C. Bradford. 1990. Tandem-in-
2016. Uptake of three antibiotics and an antiepileptic drug by wheat crops space and tandem in-time mass Spectrometry: Triple quadrupoles 
spray irrigated with wastewater treatment plant effluent. J. Environ. Qual. and quadrupole ion traps. Anal. Chem. 62:2162–2172. doi:10.1021/
45:546–554. doi:10.2134/jeq2015.05.0257 ac00219a003
Garcia-Armisen, T., A. Anzil, P. Cornelis, M. Chevreuil, and P. Servais. 2013. Jorgensen, J.H., and M.J. Ferraro. 2009. Antimicrobial susceptibility testing: A 
Identification of antimicrobial resistant bacteria in rivers: Insights review of general principles and contemporary practices. Clin. Infect. Dis. 
into the cultivation bias. Water Res. 47:4938–4947. doi:10.1016/j. 49(1): 1749–1755.
watres.2013.05.036 Joyce, L.F., J. Downes, K. Stockman, and J.H. Andrew. 1992. Comparison of five 
Garder, J.L., T.B. Moorman, and M.L. Soupir. 2014. Transport and persistence methods, including the PDM Epsilometer test (E test), for antimicrobial 
of tylosin-resistant enterococci, erm genes, and tylosin in soil and drainage susceptibility testing of Pseudomonas aeruginosa. J. Clin. Microbiol. 
water from fields receiving swine manure. J. Environ. Qual. 43:1484–1493. 30:2709–2713.
doi:10.2134/jeq2013.09.0379 Keith, L.H., W. Crummett, J.J. Deegan, R.A. Libby, J.K. Taylor, and G. Wentler. 
Gibson, M.K., K.J. Forsberg, and G. Dantas. 2015. Improved annotation of 1983. Principles of environmental analysis. Anal. Chem. 55:2210–2218. 
antibiotic resistance determinants reveals microbial resistomes cluster by doi:10.1021/ac00264a003
ecology. ISME J. 9:207–216. doi:10.1038/ismej.2014.106 Kleineidam, K., S. Sharma, A. Kotzerke, H. Heuer, S. Thiele-Bruhn, K. Smalla, et 
Gillings, M. 2014. Pollution by antibiotics and resistance genes: Dissemination al. 2010. Effect of sulfadiazine on abundance and diversity of denitrifying 
into Australian wildlife. In: A. Stow, et al., editors, Austral ark: The state of bacteria by determining nirK and nirS genes in two arable soils. Microb. 
wildlife in Australia and New Zealand. Cambridge Univ. Press, Cambridge, Ecol. 60:703–707. doi:10.1007/s00248-010-9691-9
UK. p. 186–196. Klümper, U., I. Riber, A. Dechesne, A. Sannazzarro, L.H. Hansen, S.J. 
Gonzalez-Pleiter, M., S. Gonzalo, I. Rodea-Palomares, F. Leganes, R. Rosal, K. Sorensen, and B.F. Smets. 2015. Broad host range plasmids can invade 
Boltes, et al. 2013. Toxicity of five antibiotics and their mixtures towards an unexpectedly diverse fraction of a soil bacterial community. ISME J. 
photosynthetic aquatic organisms: Implications for environmental 9:934–945. doi:10.1038/ismej.2014.191
risk assessment. Water Res. 47:2050–2064. doi:10.1016/j. Knapp, C.W., J. Dolfing, P.A. Ehlert, and D.W. Graham. 2010. Evidence of 
watres.2013.01.020 increasing antibiotic resistance gene abundance in archived soils since 
Greig, J., A. Rajic, I. Young, M. Mascarenhas, L. Waddell, and J. LeJeune. 2015. 1940. Environ. Sci. Technol. 44:580–587. doi:10.1021/es901221x
A scoping review of the role of wildlife in the transmission of bacterial Koike, S., I.G. Krapac, H.D. Oliver, A.C. Yannarell, J.C. Chee-Sanford, R.I. 
pathogens and antimicrobial resistance to the food chain. Zoonoses Public Aminov, and R.I. Mackie. 2007. Monitoring and source tracking of 
Health 62:269–284. doi:10.1111/zph.12147 tetracycline resistance genes in lagoons and groundwater adjacent to 
Guo, R., W. Xie, and J. Chen. 2015. Assessing the combined effects from two swine production facilities over a 3-year period. Appl. Environ. Microbiol. 
kinds of cephalosporins on green alga (Chlorella pyrenoidosa) based 73:4813–4823. doi:10.1128/AEM.00665-07
on response surface methodology. Food Chem. Toxicol. 78:116–121. Kolpin, D.W., E.T. Furlong, M.T. Meyer, E.M. Thurman, S.D. Zaugg, L.B. Barber, 
doi:10.1016/j.fct.2015.02.007 et al. 2002. Pharmaceuticals, hormones, and other organic wastewater 
Gutiérrez, I.R., N. Watanabe, T. Harter, B. Glaser, and M. Radke. 2010. Effect of contaminants in U.S. Streams, 1999-2000: A national reconnaissance. 
sulfonamide antibiotics on microbial diversity and activity in a Californian Environ. Sci. Technol. 36:1202–1211. doi:10.1021/es011055j
Mollic Haploxeralf. J. Soils Sediments 10:537–544. doi:10.1007/ Korpela, M.T., J.S. Kurittu, J.T. Karvinen, and M.T. Karp. 1998. A recombinant 
s11368-009-0168-8 Escherichia coli sensor strain for the detection of tetracyclines. Anal. Chem. 
Hafner, S.C., T. Harter, and S.J. Parikh. 2016. Evaluation of monensin transport 70:4457–4462. doi:10.1021/ac980740e
to shallow groundwater after irrigation with dairy lagoon water. J. Environ. Kristiansson, E., J. Fick, A. Janzon, R. Grabic, C. Rutgersson, B. Weijdegard, 
Qual. 45:480–487. doi:10.2134/jeq2015.05.0251 H. Soderstrom, and D.G.J. Larsson. 2011. Pyrosequencing of antibiotic-
Haller, M.Y., S.R. Muller, C.S. McArdell, A.C. Alder, and M.J.F. Suter. 2002. contaminated river sediments reveals high levels of resistance and gene 
Quantification of veterinary antibiotics (sulphonamides and trimethoprim) transfer elements. PLoS ONE 6:e17038. doi:10.1371/journal.pone.0017038
in animal manure by liquid chromatography-mass spectrometry. J. Kulesza, S.B., R.O. Maguire, K. Xia, J. Cushman, K. Knowlton, and P. Ray. 2016. 
Chromatogr. A 952:111–120. doi:10.1016/S0021-9673(02)00083-3 Manure injection affects the fate of pirlimycin in surface runoff and soil. J. 
Halling-Sørensen, B., S.N. Nielson, P.F. Lanzky, F. Ingerslev, H.C. Holten Environ. Qual. 45:511–518. doi:10.2134/jeq2015.06.0266
Lutzhøft, and S.E. Jørgensen. 1998. Occurrence, fate and effects of Kumar, K., and S.C. Gupta. 2016. A framework to predict uptake of trace 
pharmaceutical substances in the environment: A review. Chemosphere organic compounds by plants. J. Environ. Qual. 45:555–564. doi:10.2134/
36:357–393. doi:10.1016/S0045-6535(97)00354-8 jeq2015.06.0261
Journal of Environmental Quality 391
Kumar, K., S.C. Gupta, Y. Changer, and A.K. Singh. 2005. Antibiotic use in Nandi, S., J.J. Maurer, C. Hofacre, and A.O. Summers. 2004. Gram-positive bacteria 
agriculture and their impact on the terrestrial environment. Adv. Agron. are a major reservoir of Class 1 antibiotic resistance integrons in poultry litter. 
87:1–54. doi:10.1016/S0065-2113(05)87001-4 Proc. Natl. Acad. Sci. USA 101:7118–7122. doi:10.1073/pnas.0306466101
Kummerer, K. 2009. Antibiotics in the aquatic environment: A review. Part I. Negreanu, Y., Z. Pasternak, E. Jurkevitch, and E. Cytryn. 2012. Impact of treated 
Chemosphere 75:417–434. doi:10.1016/j.chemosphere.2008.11.086 wastewater irrigation on antibiotic resistance in agricultural soils. Environ. 
Lau, J.A., and J.T. Lennon. 2011. Evolutionary ecology of plant–microbe Sci. Technol. 46:4800–4808. doi:10.1021/es204665b
interactions: Soil microbial structure alters selection on plant traits. New Nesme, J., S. Cecillon, T.O. Delmont, J.M. Monier, T.M. Vogel, and P. Simonet. 
Phytol. 192(1):215–224. doi:10.1111/j.1469-8137.2011.03790.x 2014. Large scale metagenomic-based study of antibiotic resistance in the 
Levy, S.B. 2002. Factors impacting on the problem of antibiotic resistance. J. environment. Curr. Biol. 24:1096–1100. doi:10.1016/j.cub.2014.03.036
Antimicrob. Chemother. 49:25–30. doi:10.1093/jac/49.1.25 Nesme, J., and P. Simonet. 2015. The soil resistome: A critical review on antibiotic 
Lewis, K. 2010. Persister cells. Annu. Rev. Microbiol. 64:357–372. doi:10.1146/ resistance origins, ecology and dissemination potential in telluric bacteria. 
annurev.micro.112408.134306 Environ. Microbiol. 17:913–930. doi:10.1111/1462-2920.12631
Lin, D., K. Chen, R. Li, L. Liu, J. Guo, W. Yao, et al. 2014. Selection of NethMap. 2014. Consumption of antimicrobial agents and antimicrobial resistance 
target mutation in rat gastrointestinal tract E. coli by minute dosage of among medically important bacteria in the Netherlands in 2013. National 
enrofloxacin. Front. Microbiol. 5:468. Institute for Public Health and the Environment of the Netherlands. https://
Linares, J.F., I. Gustafsson, F. Baquero, and J. Martinez. 2006. Antibiotics as www.wageningenur.nl/upload_mm/1/a/1/0704c512-5b42-4cef-8c1b-
intermicrobial signaling agents instead of weapons. Proc. Natl. Acad. Sci. 60e9e3fb2a62_NethMap-MARAN2014.pdf (accessed 22 Dec. 2015).
USA 103:19484–19489. doi:10.1073/pnas.0608949103 Nordenholt, R.M., K.W. Goyne, R.J. Kremer, C.-H. Lin, R.N. Lerch, and K.S. 
Liu, A., A. Fong, E. Beckett, J. Yuan, C. Tamae, L. Medrano, M. Maiz, C. Veum. 2016. Veterinary antibiotic effects on atrazine degradation and soil 
Wahba, C. Lee, K. Lee, K.P. Tran, H. Yang, R.M. Hoffman, A. Salih, and microorganisms. J. Environ. Qual. 45:565–575. doi:10.2134/jeq2015.05.0235
J.H. Miller. 2011. Selective advantage of resistant strains at race levels of Nordmann, P., L. Poirel, and L. Dortet. 2012. Rapid detection of carbapenemase-
antibiotics: A simple and ultrasensitive color detection of antibiotics producing Enterobacteriaceae. Emerg. Infect. Dis. 18:1503–1507. 
and genotoxic agents. Antimicrob. Agents Chemother. 55:1204–1210. doi:10.3201/eid1809.120355
doi:10.1128/AAC.01182-10 Normark, B.H., and S. Normark. 2002. Evolution and spread of antibiotic resistance. 
Liu, C.-H., Y.-H. Chuang, H. Li, B.J. Teppen, S.A. Boyd, J.M. Gonzalez, C.T. J. Intern. Med. 252:91–106. doi:10.1046/j.1365-2796.2002.01026.x
Johnston, J. Lehmann, and W. Zhang. 2016. Sorption of lincomycin Papadopoulos, A., and S. Wilmer. 2011. One Health: A primer. National 
by manure-derived biochars from water. J. Environ. Qual. 45:519–527. Collaborating Centre for Environmental Health, Vancouver, BC, Canada. 
doi:10.2134/jeq2015.06.0320 http://ncceh.ca/sites/default/files/One_Health_Primer_Nov_2011.pdf 
Liu, Y., J. Zhang, B. Gao, and S. Feng. 2014. Combined effects of two antibiotic (accessed 13 Jan. 2016).
contaminants on Microcystis aeruginosa. J. Hazard. Mater. 279:148–155. Pei, R., S.-C. Kim, K.H. Carlson, and A. Pruden. 2006. Effect of river landscape on the 
doi:10.1016/j.jhazmat.2014.07.002 sediment concentrations of antibiotics and corresponding antibiotic resistance 
Loewe, S., and H. Muischnek. 1926. Combinated effects: Announcement— genes (ARG). Water Res. 40:2427–2435. doi:10.1016/j.watres.2006.04.017
Implements to the problem. (In German.) Naunyn Schmiedebergs Arch. Persoons, D., K. Bollaerts, A. Srnet, L. Herman, M. Heyndrickx, A. Martel, P. 
Exp. Pathol. Pharmakol. 114:313–326. doi:10.1007/BF01952257 Butaye, B. Catry, F. Haesebrouck, and J. Dewult. 2011. The importance 
Luby, E., A.M. Ibekwe, J. Zilles, and A. Pruden. 2016. Molecular methods of sample size in determination of a flock-level antimicrobial resistance 
for assessment of antibiotic resistance in agricultural ecosystems: profile for Escherichia coli in broilers. Microb. Drug Resist. 17:513–519. 
Prospects and challenges. J. Environ. Qual. 45:441–453. doi:10.2134/ doi:10.1089/mdr.2011.0048
jeq2015.07.0367 Poole, C.F. 2003. New trends in solid-phase extraction. TrAC. Trends Analyt. 
Majewsky, M., D. Wagner, M. Delay, S. Brase, V. Yargeau, and H. Horn. 2014. Chem. 22:362–373. doi:10.1016/S0165-9936(03)00605-8
Antibacterial activity of sulfamethoxazole transformation products (TPs): Popowska, M., M. Rzeczycka, A. Miernik, A. Krawczyk-Balska, F. Walsh, 
General relevance for sulfonamide TPs modified at the para position. and B. Duffy. 2012. Influence of soil use on prevalence of tetracycline, 
Chem. Res. Toxicol. 27:1821–1828. doi:10.1021/tx500267x streptomycin and erythromycin resistance and associated resistance 
Martinez, J.L. 2009. Environmental pollution by antibiotics and by antibiotic genes. Antimicrob. Agents Chemother. 56:1434–1443. doi:10.1128/
resistance determinants. Environ. Pollut. 157:2893–2902. doi:10.1016/j. AAC.05766-11
envpol.2009.05.051 Pruden, A., M. Arabi, and H.N. Storteboom. 2012. Correlation between 
McCall, C.A., E. Bent, T.S. Jørgensen, K.E. Dunfield, and M.B. Habash. upstream human activities and riverine antibiotic resistance genes. Environ. 
2016. Metagenomic comparison of antibiotic resistance genes associated Sci. Technol. 46:11541–11549. doi:10.1021/es302657r
with liquid and dewatered biosolids. J. Environ. Qual. 45:463–470. Pruden, A., R.T. Pei, H. Storteboom, and K.H. Carlson. 2006. Antibiotic 
doi:10.2134/jeq2015.05.0255 resistance genes as emerging contaminants: Studies in northern Colorado. 
McDaniel, L.D., E. Young, J. Delaney, F. Ruhnau, K.B. Ritchie, and J.H. Paul. Environ. Sci. Technol. 40:7445–7450. doi:10.1021/es060413l
2010. High frequency of horizontal gene transfer in the oceans. Science Public Health Agency of Canada. 2015. Canadian Integrated Program for 
330:50. doi:10.1126/science.1192243 Antimicrobial Resistance Surveillance (CIPARS) reports. http://www.
McLain, J.E., E. Cytryn, L.M. Durso, and S. Young. 2016. Culture-based phac-aspc.gc.ca/cipars-picra/pubs-eng.php (accessed 22 Dec. 2015).
methods for detection of antibiotic resistance in agroecosystems: Roberts, M.C., and S. Schwarz. 2016. Tetracycline and phenicol resistance 
Advantages, challenges, and gaps in knowledge. J. Environ. Qual. 45:434– genes and mechanisms: Importance for agriculture, the environment, and 
440. doi:10.2134/jeq2015.06.0317 humans. J. Environ. Qual. 45:576–592. doi:10.2134/jeq2015.04.0207
McLain, J.E., and C.F. Williams. 2014. Sustainability of water reclamations: Rothrock, M.J., Jr., K.L. Hiett, J.Y. Guard, and C.R. Jackson. 2016a. Antibiotic 
Long-term recharge with reclaimed wastewater does not enhance resistance patterns of major zoonotic pathogens from all-natural, 
antibiotic resistance in sediment bacteria. Sustainability 6:1313–1327. antibiotic-free, pasture-raised broiler flocks in the southeastern United 
doi:10.3390/su6031313 States. J. Environ. Qual. 45:593–603. doi:10.2134/jeq2015.07.0366
Meighen, E.A. 1991. Molecular biology of bacterial bioluminescence. Microbiol. Rothrock, M.J., Jr., P.L. Keen, K.L. Cook, L.M. Durso, A.M. Franklin, and R.S. 
Rev. 55:123–142. Dungan. 2016b. How should we be determining background and baseline 
Möhrle, V., M. Stadler, and G. Eberz. 2007. Biosensor-guided screening for antibiotic resistance levels in agroecosystem research? J. Environ. Qual. 
macrolides. Anal. Bioanal. Chem. 388: 1117–1125. 45:420–431. doi:10.2134/jeq2015.06.0327
Munir, M., K. Wong, and I. Xagoraraki. 2011. Release of antibiotic resistant Ruuskanen, M., J. Muurinen, A. Meierjohan, K. Pärnänen, M. Tamminen, C. 
bacteria and genes in the effluent and biosolids of five wastewater utilities Lyra, L. Kronberg, and M. Virta. 2016. Fertilizing with animal manure 
in Michigan. Water Res. 45:681–693. doi:10.1016/j.watres.2010.08.033 disseminates antibiotic resistance genes to the farm environment. J. 
Munir, M., and I. Xagoraraki. 2011. Levels of antibiotic resistance genes in Environ. Qual. 45:488–493. doi:10.2134/jeq2015.05.0250
manure, biosolids, and fertilized soil. J. Environ. Qual. 40:248–255. Sapkota, A.R., F.C. Curriero, K.E. Gibson, and K.J. Schwab. 2007. Antibiotic- 
doi:10.2134/jeq2010.0209 resistant enterococci and fecal indicators in surface water and groundwater 
Musovic, S., A. Dechesne, J. Sorensen, and B.F. Smets. 2010. Novel assay to assess impacted by a concentrated swine feeding operation. Environ. Health 
permissiveness of a soil microbial community toward receipt of mobile Perspect. 115:1040–1045. doi:10.1289/ehp.9770
genetic elements. Appl. Environ. Microbiol. 76:4813–4818. doi:10.1128/ Schmidt, A.S., M.S. Bruun, I. Dalsgaard, K. Pedersen, and J.L. Larsen. 2000. 
AEM.02713-09 Occurrence of antimicrobial resistance in fish-pathogenic bacteria 
Naidu, R. 2008. Chemical bioavailability in terrestrial environments. Elsevier, associated with four Danish rainbow trout farms. Appl. Environ. 
Oxford, UK. Microbiol. 66:4908–4915. doi:10.1128/AEM.66.11.4908-4915.2000
392 Journal of Environmental Quality 
Schmitt, H., P. Van Beelen, J. Tolls, and C.L. Van Leeuwen. 2004. Pollution- Van der Heijden, M.G.A., R.D. Bardgett, and N.M. van Straalen. 2008. The 
induced community tolerance of soil microbial communities caused by the unseen majority: Soil microbes as drivers of plant diversity and productivity. 
antibiotic sulfachloropyridazine. Environ. Sci. Technol. 38:1148–1153. Ecol. Lett. 11(3):296–310. doi:10.1111/j.1461-0248.2007.01139.x
doi:10.1021/es034685p Wagg, C., J. Jansa, B. Schmid, and M.G.A. van der Heijden. 2011. Belowground 
Seitz, P., and M. Blokesch. 2013. Cues and regulatory pathways involved in biodiversity effects of plant symbionts support aboveground productivity. 
natural competence and transformation in pathogenic and environmental Ecol. Lett. 14(10):1001–1009. doi:10.1111/j.1461-0248.2011.01666.x
Gram-negative bacteria. FEMS Microbiol. Rev. 37:336–363. Wallace, J.S., and D.S. Aga. 2016. Enhancing extraction and detection of 
doi:10.1111/j.1574-6976.2012.00353.x veterinary antibiotics in solid and liquid fractions of manure. J. Environ. 
Seyfried, E.E., R.J. Newton, K.F. Rubert, IV, J.A. Pedersen, and K.D. McMahon. Qual. 45:471–479. doi:10.2134/jeq2015.05.0246
2010. Occurrence of tetracycline resistance genes in aquaculture Walsh, F., A. Ingenfeld, M. Zampicolli, M. Hilber-Bodmer, J.E. Frey, and B. 
facilities with varying use of oxytetracycline. Microb. Ecol. 59:799–807. Duffy. 2011. Real-time PCR methods for quantitative monitoring of 
doi:10.1007/s00248-009-9624-7 streptomycin and tetracycline resistance genes in agricultural ecosystems. J. 
Shrier, I., and R.W. Platt. 2008. Reducing bias through directed acyclic graphs. Microbiol. Methods 86:150–155. doi:10.1016/j.mimet.2011.04.011
BMC Med. Res. Methodol. 8:70. doi:10.1186/1471-2288-8-70 Whitehead, T.R., and M.A. Cotta. 2016. Examination of the aerobic microflora 
Silley. P. 2012. Susceptibility testing methods, resistance, and breakpoints: What of swine feces and stored swine manure. J. Environ. Qual. 45:604–608. 
do these terms really mean? Rev. Sci. Tech. 31:33–41. doi:10.2134/jeq2015.05.0248
Snary, E.L., A.K. Louise, H.C. Davison, C.J. Teale, and M. Wooldridge. 2004. Wilga, J., A. Kot-Wasik, and J. Namiesnik. 2008. Studies of human and veterinary 
Antimicrobial resistance: A microbial risk assessment perspective. J. drugs’ fate and environmental solid samples: Analytical problems. J. 
Antimicrob. Chemother. 53:906–907. doi:10.1093/jac/dkh182 Chromatogr. Sci. 46:601–608. doi:10.1093/chromsci/46.7.601
Sobecky, P.A., and T.H. Hazen. 2009. Horizontal gene transfer and mobile Williams-Nguyen, J., J. Sallach, S. Bartlelt-Hunt, A.B.A. Boxall, L.M. Durso, 
genetic elements in marine systems. Methods Mol. Biol. 532:435–453. J.E. McLain, R. Singer, D.D. Snow, and J. Zilles. 2016. Antibiotics and 
doi:10.1007/978-1-60327-853-9_25 antibiotic resistance in agroecosystems: State of the science. J. Environ. 
Solis, Y., G. Chavarria, F. Garcia, and C. Rodriguez. 2011. Exposure of a Qual. 45:394–406. doi:10.2134/jeq2015.07.0336
tropical soil to mg/kg of oxytetracycline elicits hormetic responses in the WHO. 2011. Critically important antimicrobials for human medicine. 3rd 
catabolic activities of its microbial community. Dose Response 9:434–441. rev. World Health Organization, Geneva. http://apps.who.int/iris/
doi:10.2203/dose-response.10-045.Rodriguez bitstream/10665/77376/1/9789241504485_eng.pdf (accessed 22 Dec. 
Storteboom, H., M. Arabi, J.G. Davis, B. Crimi, and A. Pruden. 2010. Tracking 2015).
antibiotic resistance genes in the South Platte river basin using molecular WHO. 2014. Antibiotic resistance: Global report on surveillance 2014. 
signatures of urban, agricultural, and pristine sources. Environ. Sci. World Health Organization, Geneva. http://apps.who.int/iris/
Technol. 44:7397–7404. doi:10.1021/es101657s bitstream/10665/112642/1/9789241564748_eng.pdf (accessed 22 Dec. 
Subbiah, M., S.M. Mitchell, and D.R. Call. 2016. Not all antibiotic use practices 2015).
in food-animal agriculture afford the same risk. J. Environ. Qual. 45:618– Wray, C., and J.C. Gnanou. 2000. Antibiotic resistance monitoring in bacteria 
629. doi:10.2134/jeq2015.06.0297 of animal origin: Analysis of national monitoring programmes. Int. J. 
Sura, S., D. Degenhardt, A.J. Cessna, F.J. Larney, A.F. Olson, and T.A. Antimicrob. Agents 14:291–294. doi:10.1016/S0924-8579(00)00139-4
McAllister. 2016. Transport of three antimicrobials in runoff from Xu, S., S. Sura, R. Zaheer, G. Wang, A. Smith, S. Cook, A.F. Olson, A.J. Cessna, 
windrows of composting beef cattle manure. J. Environ. Qual. 45:494– F.J. Larney, and T.A. McAllister. 2016. Dissipation of antimicrobial 
502. doi:10.2134/jeq2015.05.0254 resistance determinants in composted and stockpiled beef cattle manure. J. 
Tamminen, M., A. Karkman, A. Lõhmus, W.I. Muziasari, H. Takasu, S. Wada, Environ. Qual. 45:528–536. doi:10.2134/jeq2015.03.0146
S. Suzuki, and M. Virta. 2011. Tetracycline resistance genes persist at Yang, L.H., G.G. Ying, H.C. Su, J.L. Stauber, M.S. Adams and M.T. Binet. 2008. 
aquaculture farms in the absence of selection pressure. Environ. Sci. Growth-inhibiting effects of 12 antibacterial agents and their mixtures 
Technol. 45:386–391. doi:10.1021/es102725n on the freshwater microalga Pseudokirchneriella subcapitata. Environ. 
Toth, J.D., Y.C. Feng, and Z.X. Dou. 2011. Veterinary antibiotics at Toxicol. Chem. 27: 1201–1208.
environmentally relevant concentrations inhibit soil iron reduction Youngquist, C., S. Mitchell, and C. Cogger. 2016. Fate of antibiotics and 
and nitrification. Soil Biol. Biochem. 43:2470–2472. doi:10.1016/j. antibiotic resistance during digestion and composting: A review. J. 
soilbio.2011.09.004 Environ. Qual. 45:537–545. doi:10.2134/jeq2015.05.0256
Tzouvelekis, L.S., A. Markogiannakis, M. Psichogiou, P.T. Tassios, and G.L. Yu, Z., D. Yin, and H. Deng. 2015. The combinational effects between 
Daikos. 2012. Carbapenemases in Klebsiella pneumoniae and other sulfonamides and metals on nematode Caenorhabditis elegans. Ecotoxicol. 
Enterobacteriaceae: An evolving crisis of global dimensions. Clin. Environ. Saf. 111:66–71. doi:10.1016/j.ecoenv.2014.09.026
Microbiol. Rev. 25:682–707. doi:10.1128/CMR.05035-11 Zhang, Y.P., C.Q. Zhang, D.B. Parker, D.D. Snow, Z. Zhou, and X. Li. 2013. 
Udikovic-Kolic, N., F. Wichmann, N.A. Broderick, and J. Handelsman. 2014. Occurrence of antimicrobials and antimicrobial resistance genes in beef 
Bloom of resident antibiotic-resistant bacteria in soil following manure cattle storage ponds and swine treatment lagoons. Sci. Total Environ. 463–
fertilization. Proc. Natl. Acad. Sci. USA 111:15202–15207. doi:10.1073/ 464:631–638. doi:10.1016/j.scitotenv.2013.06.016
pnas.1409836111 Zhou, Z., L. Raskin, and J.L. Zilles. 2009. Identification of macrolide resistant 
USEPA. 2007. Method 1694: Pharmaceuticals and personal care products microorganisms on antimicrobial-free swine farms. Appl. Environ. 
in water, soil, sediment, and biosolids by HPLC/MS/MS. USEPA, Microbiol. 75:5814–5820. doi:10.1128/AEM.00977-09
Washington, DC. http://www.epa.gov/sites/production/files/2015-10/ Zhou, Z., L. Raskin, and J.L. Zilles. 2010. Effects of swine manure on macrolide, 
documents/method_1694_2007.pdf (accessed 13 Jan. 2016) lincosamide, and streptogramin b antimicrobial resistance in soils. Appl. 
USEPA. 2012. Recreational water quality criteria. 820-F-12-058. USEPA, Environ. Microbiol. 76:2218–2224. doi:10.1128/AEM.02183-09
Office of Water, Washington, DC. http://www.epa.gov/sites/production/ Zwonitzer, M.R., M.L. Soupir, L.R. Jarboe, and D.R. Smith. 2016. Quantifying 
files/2015-10/documents/rwqc2012.pdf (accessed 19 Jan. 2016) attachment and antibiotic resistance of Escherichia coli from conventional 
Van Boeckel, T.P., S. Gandra, A. Ashok, Q. Caudron, B.T. Grenfell, S.A. Levin, and organic swine manure. J. Environ. Qual. 45:609–617. doi:10.2134/
and R. Laxminarayan. 2014. Global antibiotic consumption 2000 to jeq2015.05.0245
2010: An analysis of national pharmaceutical sales data. Lancet Infect. Dis. 
14:742–750. doi:10.1016/S1473-3099(14)70780-7
Journal of Environmental Quality 393