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Differential Drivers of Antimicrobial Resistance across the World Published as part of the Accounts of Chemical Research special issue “Water for Two Worlds: Urban and Rural Communities”. Peter Vikesland,*,†,‡ Emily Garner,† Suraj Gupta,† Seju Kang,† Ayella Maile-Moskowitz,† and Ni Zhu† †
Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, Virginia 24061, United States Virginia Tech Global Change Center and Virginia Tech Institute of Critical Technology and Applied Science, Virginia Tech, Blacksburg, Virginia 24061, United States
Acc. Chem. Res. Downloaded from pubs.acs.org by EAST CAROLINA UNIV on 03/08/19. For personal use only.
‡
CONSPECTUS: Antimicrobial resistance (AMR) is one of the greatest threats faced by humankind. The development of resistance in clinical and hospital settings has been well documented ever since the initial discovery of penicillin and the subsequent introduction of sulfonamides as clinical antibiotics. In contrast, the environmental (i.e., community-acquired) dimensions of resistance dissemination have been only more recently delineated. The global spread of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) between air, water, soil, and food is now well documented, while the factors that affect ARB and ARG dissemination (e.g., water and air quality, antibiotic fluxes, urbanization, sanitation practices) in these and other environmental matrices are just now beginning to be more fully appreciated. In this Account, we discuss how the global perpetuation of resistance is dictated by highly interconnected socioeconomic risk factors and illustrate that development status should be more fully considered when developing global strategies to address AMR. We first differentiate low to middle income countries (LMICs) and high-income countries (HICs), then we summarize the modes of action of commercially available antibiotics, and then discuss the four primary mechanisms by which bacteria develop resistance to those antibiotics. Resistance is disseminated via both vertical gene transfer (VGT; parent to offspring) as well as by horizontal gene transfer (HGT; cell to cell transference of genetic material). A key challenge hindering attempts to control resistance dissemination is the presence of native, environmental bacteria that can harbor ARGs. Such environmental “resistomes” have potential to transfer resistance to pathogens via HGT. Of particular concern is the development of resistance to antibiotics of last-resort such as the cephalosporins, carbapenems, and polymyxins. We then illustrate how antibiotic use differs in LMICs relative to HICs in terms of the volumes of antibiotics used and their fate within local environments. Antibiotic use in HICs has remained flat over the past 15 years, while in LMICs use over the same period has increased substantially as a result of economic improvements and changes in diet. These use and fate differences impact local citizens and thus the local dissemination of AMR. Various physical, social, and economic circumstances within LMICs potentially favor AMR dissemination. We focus on three physical factors: changing population density, sanitation infrastructure, and solid-waste disposal. We show that high population densities in cities within LMICs that suffer from poor sanitation and solid-waste disposal can potentially impact the dissemination of resistance. In the final section, we discuss potential monitoring approaches to quantify the spread of resistance both within LMICs as well as in HICs. We posit that culture-based approaches, molecular approaches, and cutting-edge nanotechnology-based methods for monitoring ARB and ARGs should be considered both within HICs and, as appropriate, within LMICs.
1. INTRODUCTION The global spread of antimicrobial resistant organisms and antibiotic resistance genes (ARGs) has been described as one of the greatest threats facing humankind in the 21st Century. To put this threat in perspective, it is estimated that during the period between 2014 and 2016 ≈1 million people died due to antibiotic resistant infections and current projections suggest that resistance will cause ≈300 million premature deaths by the year 2050.1 While the factors leading to the spread of resistance are complex, it is generally thought that it can primarily be © XXXX American Chemical Society
attributed to excessive use of antimicrobials in both clinical and agricultural settings.2 Unfortunately, due to the mobility of ARGs and their propensity to be transmitted between people, animals, and environmental reservoirs it is a major challenge to reduce the threat once antimicrobial resistance (AMR) develops. Received: December 18, 2018
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Figure 1. Antimicrobial resistance is a cross-boundary challenge that is driven by clinical, biological, social, political, economic, and environmental drivers and affects not only humans but also domestic and nondomestic animals and ecosystems. Impacts of resistance dissemination exert feedbacks on the drivers that are difficult to predict.
scaffold, (2) modification of the antibiotic target, (3) alteration of the permeability of the cell membrane, and (4) expression of efflux pumps to keep intracellular concentrations of antibiotics below inhibitory levels.7 Bacterial resistance to antibiotics can be acquired both via vertical gene transfer (VGT; i.e., parent to offspring) as well as by horizontal gene transfer (HGT; i.e., the transference of genetic material, such as ARGs, from cell to cell). Several unique properties of antibiotic resistant bacteria (ARB) enable their development and propagation in the environment. Autochthonous (i.e., native, environmental) bacteria constitute environmental reservoirs of ARGs, or “resistomes”,8 that can subsequently be transferred to pathogens via HGT.9 HGT can occur between live cells (i.e., conjugation), via bacteriophage infection (i.e., transduction), or via assimilation of extracellular DNA (i.e., transformation). While the processes underlying HGT are reasonably well characterized under ideal conditions, they are considerably less understood in environmental contexts characterized by the presence of chemical stressors such as antibiotics, metals, and biocides.10 For this reason, the resistomes of different environments incorporate a wide diversity of ARGs that reflect both the natural history of a given environment as well as the imprint of humankind. Chemical stressors in aquatic environments are problematic as they can induce mutations and selectively enrich resistant bacteria. In addition to an antibiotic directly selecting for bacteria carrying ARGs that confer resistance to that compound, co-selection can also occur. Co-selection results from multiple underlying mechanisms: co-resistance (i.e., multiple resistance genes being physically linked on a single genetic element), crossresistance (i.e., a single biochemical system conferring resistance to multiple compounds), or co-regulation (i.e., multiple resistance genes being transcriptionally linked on a single coding region of an organism’s DNA).11 Stressors may confer not only resistance to the present compound, but to other compounds for which resistance elements are genetically or transcriptionally linked, or for which a single system induces resistance. Selection of ARB has been documented even at the
Global perpetuation of resistance is dictated by highly interconnected socioeconomic risk factors (Figure 1). While a great deal is known about the dynamics of AMR in high income countries (HICs; defined by the World Bank as having a per capita gross national income > $12,056), there is less known about such dynamics in low- or middle-income countries (LMICs).3 Unfairly, the majority of the burden of AMR falls on LMICs,4 with most of it carried by the young and the infirm.5 In this Account, we examine how development status impacts AMR propagation. We suggest that many of the factors driving resistance dissemination in LMICs differ from those prevalent in HICs. We support this hypothesis by (1) explaining the biological and chemical phenomena that give rise to resistance, (2) discussing important differences between potential drivers of resistance in HICs relative to LMICs, and (3) examining approaches to quantify the global spread of resistance.
2. ANTIBIOTIC MODES OF ACTION AND ANTIBACTERIAL RESISTANCE There are 10 major classes of antibiotics currently in use. While many antibiotics used today are of synthetic origin, a majority of these classes are defined by naturally derived products that bacteria and fungi produce to protect themselves from other microbes in their vicinity, and a minority are synthetic compounds produced exclusively in the laboratory.6 Table 1 differentiates the primary antibiotic classes by structure and mode of action. While the specifics vary from drug to drug, antibiotics generally inactivate bacterial targets via a few welldefined mechanisms: (1) inhibition of protein synthesis (e.g., tetracylines, aminoglycosides); (2) alteration of cell wall synthesis (e.g., beta-lactams, glycopeptides), (3) interference with DNA replication and bacterial integrity (e.g., fluoroquinolones), (4) disruption of folate biosynthesis (e.g., sulfonamides), and (5) disruption of the integrity of the cell membrane (e.g., lipopeptides).7 Bacteria utilize a limited number of approaches to resist antibiotics. These include (1) inactivation of the antibiotic through enzymatic degradation or modification of the enzymatic B
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Accounts of Chemical Research Table 1. Primary Synthetic and Natural Antibiotic Classes
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Africa, or the eastern Mediterranean. Resistance to carbapenems, the last group of beta-lactams with broad activity against Gram-negative bacteria, and colistin, a polymyxin also with broad-spectrum activity against Gram-negative bacteria, are of rising concern. In 2008 the New Delhi Metallo-beta-lactamase-1 (NDM-1) gene was first identified in a clinical patient who had just returned from India.22 This gene has subsequently been found worldwide and now is regularly detected in environmental samples.24,25 Similarly, colistin resistance attributed to the plasmid-mediated dissemination of the mcr-1 gene was first reported in 201626 and is now found globally.4,27,28
sublethal concentrations at which antibiotics are likely to occur in many environments.12 For example, Gullberg et al.13 found that bacteria sustained plasmids carrying beta-lactam resistance genes even at antibiotic concentrations ≈140 times below the compound’s minimum inhibitory concentration (MIC). Antibiotics are well documented to stimulate HGT,14,15 but other compounds prevalent in environmental samples also select for resistance. Metal-driven selection of ARGs has been documented for a variety of metals, including copper, zinc, nickel, and mercury.11,13,16 Pharmaceuticals, biocides, herbicides, and pesticides can select for resistant organisms, thus posing challenges to environments impacted by such chemicals.17 Recently, the antidepressant fluoxetine and the antimicrobial agent triclosan have been identified as selectors of resistance,18,19 which is particularly concerning given their abundance in many wastewater impacted environments. Disinfectants, such as free chlorine and their disinfection byproducts, can also select for ARB.20,21 Within complex environments the interplay between bacteria, antibiotics, and other chemical stressors that dictate the emergence, persistence, and spread of resistance is imperfectly understood at best. A key global concern is the development of resistance to antibiotics of last-resort such as the cephalosporins, carbapenems, and the polymyxins.22 Global resistance to thirdgeneration cephalosporins has increased due to bacterial acquisition of the capacity to produce extended-spectrum beta-lactamase enzymes (ESBLs) that mediate resistance to most beta-lactams. The estimated current global prevalence of healthy humans colonized by ESBL producing Escherichia coli is ∼14% and is increasing by 5.4% annually.23 Individuals have a higher likelihood of ESBL colonization if they have taken antibiotics within the past 4−12 months, have traveled internationally, or live in the West Pacific, Southeast Asia,
3. ANTIBIOTIC USE IN LMICs VS HICs Collignon and colleagues29 delineate the dissemination of AMR into two separate steps. In Step 1, mutations or HGT elicit development of antimicrobial resistant bacterial phenotypes. In Step 2, vectors (humans, animals) and vehicles (water, food, soil) enable the spread of resistant strains (i.e., contagion). This contagion framework is useful as it separates the primal factors initially responsible for resistance development from those that dictate its spread. AMR resistance rates in LMICs are generally higher than in HICs4 in spite of the fact that per-person consumption of antibiotics is lower within LMICs. This result supports the hypothesis that once resistance develops (i.e., Step 1) environmental, social, and economic factors dictate the magnitude of AMR dissemination. For this reason, global disparities in health spending, poverty, infrastructure, education, and governance and their implications on the spread of AMR have been targeted.29 The use and overuse of antibiotics, both at the clinic and on the farm, is the primary selection pressure pushing the global spread of AMR.2 For this reason, antibiotic stewardship, the activities and policies designed to improve the rational use of D
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Figure 2. (A) Global consumption of antibiotics in terms of defined daily doses (DDDs) as a function of country income classification. Reproduced with permission from ref 4. Copyright 2018 Proceedings of the National Academies of Science of the United States of America. (B) Antimicrobial consumption in chickens in 2010. The purple areas reflect areas where consumption will be >30 kg per 10 km2 in 2030. Reproduced with permission from ref 31. Copyright 2015 Proceedings of the National Academies of Science of the United States of America.
4. POTENTIAL FOCAL POINTS FOR AMR IN LMICs As noted previously, the physical, social, and economic circumstances of many LMICs potentially favor AMR dissemination. We emphasize that the social and economic contexts of AMR dissemination are clearly important; however, they are beyond the scope of this limited Account. We instead focus on three physical factors that have been suggested to impact dissemination within LMICs: changing population density, sanitation infrastructure, and solid-waste disposal.
antibiotics, is a fundamental aspect of international plans to address AMR. Unfortunately, in spite of these efforts, global antibiotic use actually increased 39% in the period from 2000 to 2015 with the majority of the increase due to the growing demand within LMICs driven by their improving economies4 and increased consumption of food animal protein (Figure 2). In 2013, approximately 131,000 tons of antibiotics were consumed by food animals, and this is expected to increase to 200,000 tons by 2030.30 Unfortunately, most antibiotics used for food production are not applied toward disease treatment, but instead for growth promotion and pre-emptive prophylaxis. For example, in a study examining antimicrobial use on Vietnamese chicken farms, it was determined that 84% of the time they were used for prophylaxis, 12% for disease treatment, and 3.8% for a combination of prophylaxis and disease treatment.32 As the economies of LMICs further advance and food animal consumption rises, it is expected that antibiotic use within LMICs will increase until it exceeds that within present day HICs.33 When antibiotics are used, either for medical purposes or for food animal production, they inevitably make their way into the environment. As described in detail by Kookana et al.,34 environmental concentrations of pharmaceuticals, including antibiotics, are dictated by (1) population and local demographics, (2) access to healthcare, (3) the size and nature of pharmaceutical manufacturing in the vicinity, (4) connectivity to wastewater treatment systems, (5) the ecology of the receiving environment, and (6) the local regulatory framework. Given the complicated interplay between these factors both at the local and national level it is not surprising that environmental antibiotic concentrations vary considerably across the globe.35 While there is some suggestion in the literature that antibiotic concentrations within rivers, soils, and other environmental compartments could be higher in LMICs than in HICs, it is not clear if this disparity simply reflects sampling biases or other confounding factors.36 For this reason, there is a need for broader environmental quantification of antibiotics within LMICs and not only within expected zones of high concentration (e.g., downstream from antibiotic manufacturing facilities).
Changing Population Density
The global population is currently 7.6 billion people, with approximately 76% living within LMICs.37 A majority of those 5.8 million live in rural areas; however, that statistic is changing rapidly.38 As people move from rural areas to cities, their living and working conditions transform considerably in both positive and negative ways. In cities, housing density increases and rural, agricultural jobs characterized by high levels of exposure to food animals and antibiotics are replaced by commercial sector jobs with presumed lower exposure. When people move, they also bring diseases with them, including AMR. Migration-mediated AMR dissemination is well documented.24,39,40 Cities provide improved job opportunities and improved health care, but greater risk for infectious disease.38 Increased crowding,41 reduced air quality,42 and weak (or nonexistent) infrastructure increase disease risks, particularly in slums43 and peri-urban areas.44,45 Approximately 0.8 billion of the people in LMICs live within slums often characterized by inadequate sanitation, lack of reliable access to safe and potable water, uncontrolled access to antibiotics, and the potential cohabitation of people and animals with associated likelihood for enhanced dissemination of zoonotic AMR.44 Sanitation Infrastructure
Nutrient rich environments with high bacterial concentrations are ideal settings within which resistance can develop.46 Untreated wastewater is one such environment and has been widely shown to serve as a major vector for ARGs, ARB, and resistant pathogens.47−49 Accordingly, the release of fecal material into receiving bodies, via open defection, within poorly treated sewage, or via illegal discharges, is a key mechanism by which ARGs and ARB enter the environment. Unfortunately, only 39% of the world’s population is served by sanitation that is E
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Accounts of Chemical Research considered “safely managed”, with much of the remaining 61% falling within LMICs. Given this fact, it is not surprising that there are many reports of ARGs and ARB within pit latrine wastes50 and contaminated waterways in both urban and rural areas within LMICs.51,52
to instrument costs are reliant upon centralized facilities. These latter considerations make such approaches cost-prohibitive and thus not appropriate for comprehensive, regular monitoring either in LMICs or in HICs. While field-deployable approaches such as nanopore sequencing61 may one day fill this role, as of yet they remain too costly and experimentally challenging for widespread application. Nonetheless, when nucleic-acid-based approaches are available they are highly useful since they provide capacity to probe environmental resistomes in ways that are not possible via culturing. Molecular methods have enabled characterization of the resistomes of many diverse environmental samples both within LMICs (notably China and India) as well as in HICs and have suggested the potential linkage between fecal contamination and resistance dissemination.8,62−64 An emerging issue with genomic methods, however, is the ever-increasing volume of data available and the challenges associated with attempting to collectively parse it to develop broad, global insights about AMR. To address this challenge, machine and deep learning methods are being developed to analyze genomic or metagenomics data such that the risks associated with different resistomes can be compared or that the ARGs that differentiate one location from another can be identified.65
Solid-Waste Disposal
Each year, approximately 1.85 billion tons of municipal solid waste are produced with 62% of that in LMICs and 38% in HICs.53 On a per capita basis, production of waste in HICs dwarfs that in LMICs, but production rates in LMICs continue to intensify. Waste disposal practices differ from location to location, ranging from centralized collection and landfilling or incineration at one extreme to indiscriminate dumping at the other. In many LICs only 40% of the solid waste is actually collected, while in HICs collection is near 100%. When waste in LMICs is collected it is more likely to be disposed of in an open dump than to be placed into an engineered landfill or incinerated. These differences produce disparities in how individuals interact with solid waste. Many citizens living in LMICs live in closer proximity to and have a more familiar relationship with solid waste than citizens in HICs. Household usage of antibiotics and improper disposal from clinical and hospital settings result in antibiotic disposal within solid wastes.54,55 These antibiotic residues provide localized selective pressures that enhance resistance. Studies have shown that landfill leachate40 can be contaminated by ARGs and ARB, and recently it was shown that groundwater, collected in the vicinity of a MSW landfill, can also be heavily contaminated.56
Nanotechnology Approaches
Nanomaterials-based biosensors are being developed that have potential application for rapid detection of ARGs with high selectivity and low-cost as well as in-field applicability.66 For example, gold nanoparticles (AuNPs) have been developed for the sensitive detection of the mecA gene.67 In this approach, oligonucleotide-functionalized AuNPs were designed to hybridize with a mecA gene fragment. The presence of mecA was then determined based on the change in suspension absorbance due to nanoparticle aggregation. A limit of detection (LOD) of 70 pM (≈4 × 107 genes/μL) was reported. Preconcentration steps should further reduce this LOD. In addition to optical approaches, electrochemical biosensors are also being developed for ARG detection. Recently, Liu et al.68 developed such a biosensor using oligonucleotide-functionalized AuNPs immobilized onto a glassy carbon electrode. A low LOD of 23 pM for mecA was reported. It is expected that as the nanosensor field continues to advance that additional ARGs will be targeted and that LODs will continue to decrease.
5. APPROACHES TO MONITOR AMR In this section, we briefly summarize both culture-based and molecular approaches to monitor resistance in these environments and then assess their potential applicability for monitoring AMR within LMICs. We conclude with a brief introduction to nanomaterial-enabled approaches for resistance monitoring. Culture-Based Approaches
The WHO Global Action Plan for Antimicrobial Resistance has been developed to guide efforts for AMR surveillance and research.57 Within this context, it was recently recommended that ESBL-E. coli is a potential candidate for AMR monitoring because (1) it is can be readily detected using methods established for use in HICs and LMICs, (2) variations in occurrence and density between HICs and LMICs can be quantified, and (3) the approach can be utilized not only for environmental monitoring, but also for comparative food and medical sample evaluation.58 In addition, a number of other culturable bacterial groups (both Gram-positive and Gramnegative) have also been suggested for global environmental monitoring.59 One critical challenge associated with such culture-based approaches is the aforementioned fact that nonpathogenic, environmental bacteria can represent important resistance reservoirs that are not easily cultured and thus avoid detection.60 There are also numerous forms of resistance and relevant strains that could never be captured by a single culture assay.
6. OUTLOOK It is oft stated that AMR does not respect regional or international borders and is a challenge that will only be addressed via collective global action. However, as outlined in this Account, there can be substantial differences in the drivers of dissemination in HICs vs LMICs that must be considered. AMR is a vexing One Health69 challenge that requires work across local, regional, national, and global scales that simultaneously considers humans, animals, plants, and the broader environment. An added consideration in this evaluation should be development status due to its local, regional, and national impact on the drivers of resistance dissemination. Global monitoring efforts that consider development status should provide additional insight into how local policies, practices, and socioeconomic factors influence AMR.
Molecular Approaches
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Nucleic-acid-based approaches such as DNA sequencing and metagenomics now make it possible to track and quantify individual ARGs within and between environmental compartments; however, these methods are operator intensive and due
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Peter Vikesland: 0000-0003-2654-5132 Emily Garner: 0000-0002-1579-155X Notes
The authors declare no competing financial interest. Biographies Peter Vikesland is the Nick Prillaman Professor of Civil and Environmental Engineering at Virginia Tech. He received his bachelor degree from Grinnell College in Chemistry (1993) and M.S. (1995) and Ph.D. (1998) degrees in Civil and Environmental Engineering from the University of Iowa. Vikesland’s research group examines the environmental implications and applications of nanotechnology and the global threat of antimicrobial resistance dissemination. Emily Garner received a Ph.D. in Civil Engineering from Virginia Tech in 2018. She is currently a postdoctoral researcher studying the role of microbial communities in environmental and engineered systems. Suraj Gupta received a M.S. (2018) in Civil and Environmental Engineering from Virginia Tech after receiving his B.Tech (2015) in Chemical Engineering from Visvesvaraya National Institute of Technology. He is currently pursuing an interdisciplinary Ph.D. in Genetics, Bioinformatics and Computational Biology (GBCB) at Virginia Tech. His research interests are in the development of computational approaches to analyze the genomic and metagenomic data. Seju Kang received a M.S. (2018) and B.S. (2016) in Civil and Environmental Engineering from Seoul National University. He is currently pursuing a Ph.D. in Civil and Environmental Engineering at Virginia Tech. His research evaluates the development of nanotechnology enabled approaches to analyte detection. Ayella Maile-Moskowitz received a B.S. in Environmental Science and Technology from the University of Maryland, College Park (2016). She is currently pursuing a Ph.D. in Civil and Environmental Engineering at Virginia Tech. Her research examines the impacts of antibiotic resistance dissemination from wastewater treatment plants on receiving environments. Ni Zhu received a B.S. in Environmental Science and Engineering from National University of Singapore and a Masters of Engineering degree in Civil and Environmental Engineering from Massachusetts Institute of Technology. She is a Ph.D. candidate in Civil and Environmental Engineering at Virginia Tech. Her research focuses on the effects of water chemistry on emerging microbial contaminants and antibiotic resistance in reclaimed water distribution systems.
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ACKNOWLEDGMENTS This material is based upon work supported by the U.S. National Science Foundation (NSF) Award OISE:1545756. REFERENCES
(1) Tackling drug-resistant infections globally: Final report and recommendations. Review on Antimicrobial Resistance, 2016. (2) Holmes, A. H.; Moore, L. S. P.; Sundsfjord, A.; Steinbakk, M.; Regmi, S.; Karkey, A.; Guerin, P. J.; Piddock, L. J. V. Understanding the mechanisms and drivers of antimicrobial resistance. Lancet 2016, 387, 176−187. (3) Rousham, E. K.; Unicomb, L.; Islam, M. A. Human, animal and environmental contributors to antibiotic resistance in low-resource settings: Integrating behavioural, epidemiological and one health approaches. Proc. R. Soc. London, Ser. B 2018, 285, 20180332. (4) Klein, E. Y.; Van Boeckel, T. P.; Martinez, E. M.; Pant, S.; Gandra, S.; Levin, S. A.; Goossens, H.; Laxminarayan, R. Global increase and G
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DOI: 10.1021/acs.accounts.8b00643 Acc. Chem. Res. XXXX, XXX, XXX−XXX
