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Record W2517497469 · doi:10.1093/femsec/fiw172

Editorial: Special section of FEMS Microbiology Ecology on the environmental dimension of antibiotic resistance

2016· editorial· en· W2517497469 on OpenAlexaff
Kornelia Smalla, Pascal Simonet, James M. Tiedje, Edward Topp

Bibliographic record

VenueFEMS Microbiology Ecology · 2016
Typeeditorial
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsAntibiotic resistanceContext (archaeology)Resistance (ecology)BiologyStewardship (theology)One HealthEnvironmental ethicsPublic healthEcologyAntibioticsPolitical scienceMicrobiologyLawMedicinePolitics

Abstract

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The emergence of multi-drug-resistant human pathogens increasingly threatens the successful treatment of bacterial infections, and is now widely regarded as a global public health crisis. Antimicrobial resistance is a global problem, and managing resistance will require global action. As a start, many nations are now developing action plans to mitigate the development of antibiotic resistance. These action plans generally have three pillars, innovation, surveillance and stewardship; and are founded on the One Health concept. Namely, that humans and animals (companion and food animal producing) are inextricably linked to each other through the environment. Thus, research on the environmental dimension of antibiotic resistance has become a priority, within the broader context of maintaining the efficacy of antibiotics of crucial importance to human and animal medicine. This FEMS Microbiology Ecology thematic topic concerns recent progress made in our understanding of the environmental dimension of antibiotic resistance, here coined with the acronym EDAR. Most of the manuscripts were contributed by participants of the Third International Symposium on the Environmental Dimension of Antibiotic Resistance, EDAR3, held in Wernigerode, Germany in May 2015. The EDAR3 meeting follows EDAR2 held in Xiamen China in December 2013, and the original EDAR meeting held in Montebello Canada in March 2012. The consensus statement formulated by the participants of EDAR3 was ‘there are linkages between environmental sources of antibiotic resistance and resistance in clinical pathogens, and human activity can increase, expand and mobilize environmental genes responsible for resistance’. For more detail on the status of progress in the field there are several recent reviews that will be of interest (Finley et al. 2013; Durso and Cook 2014; Jechalke et al. 2014; Berendonk et al. 2015; Huijbers et al. 2015; Nesme and Simonet 2015; Williams-Nguyen et al.2016). Here, we briefly synthesize some major findings communicated in this special thematic issue, and provide some suggestions for priority areas of research concerning the environmental dimension of antibiotic resistance. There is no doubt that continued advances in molecular microbiology, metagenomics and informatics are providing powerful tools to understand the ecology of antibiotic resistance and the associated genetic determinants. Fitzpatrick and Walsh (2016) used an in silico approach to mine 432 publicly available metagenomic datasets from numerous aquatic and terrestrial environments, humans and other creatures. They note the diversity of antibiotic resistance genes to be much greater in human fecal samples than soil or marine environments. However, They note that the resolution and detection limit of shotgun metagenomics is poor relative to the diversity in the microbial pangenome. The means by which antibiotic resistance is transmitted between bacteria in the environment, and under what circumstances, is a crucially important question. Baker et al. (2016) developed a mathematical model for the spread and selection of antibiotic resistance and used it to analyze the spread of resistance within bacterial populations in stored dairy manure slurry. They identified gene transfer rates as a key bottleneck, far more important than fitness cost, bacterial growth rate or abundance, and suggest that decreasing manure storage time might reduce dissemination between bacteria prior to land application. Colombo et al. (2016) evaluated the distribution of antibiotic resistance genes in bacterial and viral communities within an aquaculture facility. They found a similar distribution in both communities, and concluded that phage-mediated transduction mobilizes resistance genes within the microbiome. Li et al. (2016) sequenced four novel IncP-1ɛ plasmids from petroleum-contaminated soil and wastewater, and compared these with 38 other Inc-P plasmids that had previously been reported. Within the collection, almost all of the IncP-1ɛ plasmids carried antibiotic resistance genes, and these were all isolated from manured soils, wastewater or aquatic environments. The authors speculate that IncP-1ɛ might be predominantly carried by enteric bacteria for whom resistance traits would be beneficial. Schaufler et al. (2016) report that a clone of Escherichia coli sequence type ST410 is shared between humans, wildlife and environmental dog feces, suggesting transmission across the three components of the One Health sphere. Finally, Stedtfeld et al. (2016) reported the development of an application to archive and share data concerning the distribution of antibiotic resistance genes and bacteria in environmental and clinical settings. This sort of innovation is important because molecular and bacteriological information will need to be synthesized and distilled into a format that epidemiologists can use to make policy-relevant recommendations. Numerous studies have yielded convincing evidence for enrichment of antibiotic resistance in both terrestrial and aquatic environments impacted by humans. Using a metagenomics approach, Xiao et al. (2016) found a diversity of antibiotic resistance genes in soil from rice paddies, and that the distribution was quite distinct from those in sediment and activated sludge. In a microcosm study, Sandberg and LaPara (2016) found antibiotic resistance genes in soil amended with swine manure to persist for at least six months. In another microcosm study, Hu et al. (2016) evaluated the impact of treatment with cattle manure on the abundance of 52 antibiotic resistance genes. Although the animals had not been treated with antibiotics, there were profound but transient impacts on the abundance and diversity of antibiotic resistance genes in the manured soil. Ibrahim et al. (2016) evaluated the characteristics of a collection of Escherichia coli obtained from a dairy farm, and found a high frequency of carriage of various β-lactamases conferring the extended spectrum β-lactamase phenotype. Recognizing that soils are subject to extreme changes in temperature and moisture, Jechalke et al. (2016) evaluated the impact of wetting and drying on the effects of sulfadiazine exposure on the abundance of several gene targets associated with sulfonamide resistance and horizontal gene transfer. There was in fact little effect of varying moisture on sulfadiazine effects. With respect to the aquatic environment, Pappa et al. (2016) evaluated the characteristics of Pseudomonas aeruginosa isolated from 150 water samples from diverse areas in Greece. They concluded that aquatic isolates of this potential pathogen may represent an important reservoir of antibiotic resistance. Muziasari et al. (2016) used high throughput quantitative PCR to evaluate the distribution of genes in sediments from a fish farm. The sediments were enriched with mobile genetic elements, and genes conferring resistance to the antibiotics used by that farm. Caucci et al. (2016) evaluated the seasonality of antibiotic resistance genes in wastewater treatment plants in Dresden, Germany. Interestingly, they found a higher abundance (normalized to total 16S rRNA gene copies) during autumn and winter that coincided with higher rates of overall antibiotic prescription during those seasons. Wendlandt et al. (2015) characterized genes conferring resistance to macrolides, lincosamides and streptogramin B antibiotics in two Staphylococcus spp. isolated from wastewater effluent and from surface water. They concluded that waterborne staphylococci are a reservoir for erm(44) that vary in the amino acid sequence of the gene products, and that vary in their spectrum of macrolide resistance. An obviously important management strategy for minimizing the impact of humans on the environmental burden of antibiotic resistance is to treat fecal waste streams prior to release, using methods that reduce the quantity of antibiotic resistance genes and antibiotic residues. Using high throughput quantitative PCR, Karkman et al. (2016) found treated municipal waste-water effluent to have a much lower abundance of antibiotic resistance genes and transposases relative to the sewage influent. Zhang, Lin and Yu (2016) evaluated the effect of drinking water treatment on the abundance of antibiotic resistance genes in tap water in China, and found that elimination of certain gene targets was incomplete. Nanosilver is now widely used in a variety of applications and is ending up in sewage treatment plants. In laboratory-scale nitrifying sequencing batch reactors, Ma et al. (2016) found that distinct changes in the profile of antibiotic resistance genes were associated with exposure to nanosilver. In the agricultural context, Glaeser et al. (2016) evaluated the abundance of viable vancomycin-resistant enterococci (VRE) and methicillin-resistant staphylococci in German mesophilic biogas plants treating livestock waste. Both were detected in feedstock, whereas only VRE was detected in the digestate. Likewise, Wolters et al. (2016) evaluated the ability of mesophilic digesters to abate antibiotic resistance genes in manure and concluded that the method did not attenuate the potential for waste to increase antibiotic resistance genes and mobile genetic elements in amended soils. Ibekwe et al. (2016) evaluated the efficacy of constructed wetlands for reducing the abundance of viable antibiotic-resistant Escherichia coli in effluents from swine barns. Passage through the wetland abated the abundance of E. coli, and significantly improved the quality of the effluent. There is a pressing need to better understand the ecology of antibiotic resistance genes and mobile genetic elements. Efforts to ‘connect the dots’ through molecular epidemiology between antibiotic resistance genes in the environment and those in human or animal pathogens are ongoing, and these studies should clarify key transmission pathways. At present, the state of EDAR science consists essentially of exposure assessments; identifying how much of what type of antibiotic resistant bacteria or antibiotic resistant genes are in what matrix, under what circumstances. We have little understanding of what hazard this represents, what might be the relationship between exposure to environmental antibiotic resistance genes and the risk of development of resistance in pathogens of human or animal concern (Ashbolt et al. 2013). An understanding of both antibiotic resistance gene exposure and the hazard that represents is required to develop policy relevant risk assessment models. This will require research into the ecology of antibiotic resistance throughout the One Health continuum. Clearly there is a concern that waste streams are contributing to the development of antibiotic resistance in the environment, and they thus must be well managed. This will require research into the ecology of antibiotic resistance in various settings including wastewater treatment, manure management and wastewater reuse. This is of particular concern in the developing world where the infrastructure for sewage treatment is often lacking and animal manures may not be managed judiciously. Long-range transport of people, migratory birds, long range atmospheric transport of dust and the global trade in foodstuffs connect the microbiomes of each of us. Various mitigation strategies were discussed during the EDAR3 meeting including improvements in sewage treatment, and digestion of animal wastes. The first principle, however, should be more prudent use of antibiotics (O'Neill 2016). Globally, there needs to be more judicious use of antibiotics in human medicine and a significant reduction in antibiotic use in terrestrial and aquatic food production systems. This will require research into the ecology of human and animal pathogens in the host and the broader environment, with a view to maintaining health while reducing antibiotic use. EDAR4 is currently planned to be held in 2017 at Michigan State University in the United States, likely in August. Conflict of interest. None declared.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.018
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.020
Meta-epidemiology (narrow)0.0050.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0050.002
Science and technology studies0.0030.002
Scholarly communication0.0080.004
Open science0.0030.002
Research integrity0.0160.016
Insufficient payload (model declined to judge)0.0180.010

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.236
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations7
Published2016
Admission routes1
Has abstractyes

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