# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 4296 | 0 | 1.0000 | Twenty-first century molecular methods for analyzing antimicrobial resistance in surface waters to support One Health assessments. Antimicrobial resistance (AMR) in the environment is a growing global health concern, especially the dissemination of AMR into surface waters due to human and agricultural inputs. Within recent years, research has focused on trying to understand the impact of AMR in surface waters on human, agricultural and ecological health (One Health). While surface water quality assessments and surveillance of AMR have historically utilized culture-based methods, culturing bacteria has limitations due to difficulty in isolating environmental bacteria and the need for a priori information about the bacteria for selective isolation. The use of molecular techniques to analyze AMR at the genetic level has helped to overcome the difficulties with culture-based techniques since they do not require advance knowledge of the bacterial population and can analyze uncultivable environmental bacteria. The aim of this review is to provide an overview of common contemporary molecular methods available for analyzing AMR in surface waters, which include high throughput real-time polymerase chain reaction (HT-qPCR), metagenomics, and whole genome sequencing. This review will also feature how these methods may provide information on human and animal health risks. HT-qPCR works at the nanoliter scale, requires only a small amount of DNA, and can analyze numerous gene targets simultaneously, but may lack in analytical sensitivity and the ability to optimize individual assays compared to conventional qPCR. Metagenomics offers more detailed genomic information and taxonomic resolution than PCR by sequencing all the microbial genomes within a sample. Its open format allows for the discovery of new antibiotic resistance genes; however, the quantity of DNA necessary for this technique can be a limiting factor for surface water samples that typically have low numbers of bacteria per sample volume. Whole genome sequencing provides the complete genomic profile of a single environmental isolate and can identify all genetic elements that may confer AMR. However, a main disadvantage of this technique is that it only provides information about one bacterial isolate and is challenging to utilize for community analysis. While these contemporary techniques can quickly provide a vast array of information about AMR in surface waters, one technique does not fully characterize AMR nor its potential risks to human, animal, or ecological health. Rather, a combination of techniques (including both molecular- and culture-based) are necessary to fully understand AMR in surface waters from a One Health perspective. | 2021 | 33774111 |
| 4297 | 1 | 0.9999 | Predicting clinical resistance prevalence using sewage metagenomic data. Antibiotic resistance surveillance through regional and up-to-date testing of clinical isolates is a foundation for implementing effective empirical treatment. Surveillance data also provides an overview of geographical and temporal changes that are invaluable for guiding interventions. Still, due to limited infrastructure and resources, clinical surveillance data is lacking in many parts of the world. Given that sewage is largely made up of human fecal bacteria from many people, sewage epidemiology could provide a cost-efficient strategy to partly fill the current gap in clinical surveillance of antibiotic resistance. Here we explored the potential of sewage metagenomic data to assess clinical antibiotic resistance prevalence using environmental and clinical surveillance data from across the world. The sewage resistome correlated to clinical surveillance data of invasive Escherichia coli isolates, but none of several tested approaches provided a sufficient resolution for clear discrimination between resistance towards different classes of antibiotics. However, in combination with socioeconomic data, the overall clinical resistance situation could be predicted with good precision. We conclude that analyses of bacterial genes in sewage could contribute to informing management of antibiotic resistance. | 2020 | 33244050 |
| 4030 | 2 | 0.9999 | The human microbiome as a reservoir of antimicrobial resistance. The gut microbiota is amongst the most densely populated microbial ecosystem on earth. While the microbiome exerts numerous health beneficial functions, the high density of micro-organisms within this ecosystem also facilitates horizontal transfer of antimicrobial resistance (AMR) genes to potential pathogenic bacteria. Over the past decades antibiotic susceptibility testing of specific indicator bacteria from the microbiome, such as Escherichia coli, has been the method of choice in most studies. These studies have greatly enlarged our understanding on the prevalence and distribution of AMR and associated risk factors. Recent studies using (functional) metagenomics, however, highlighted the unappreciated diversity of AMR genes in the human microbiome and identified genes that had not been described previously. Next to metagenomics, more targeted approaches such as polymerase chain reaction for detection and quantification of AMR genes within a population are promising, in particular for large-scale epidemiological screening. Here we present an overview of the indigenous microbiota as a reservoir of AMR genes, the current knowledge on this "resistome" and the recent and upcoming advances in the molecular diagnostic approaches to unravel this reservoir. | 2013 | 23616784 |
| 6597 | 3 | 0.9999 | Exploiting a targeted resistome sequencing approach in assessing antimicrobial resistance in retail foods. BACKGROUND: With the escalating risk of antimicrobial resistance (AMR), there are limited analytical options available that can comprehensively assess the burden of AMR carried by clinical/environmental samples. Food can be a potential source of AMR bacteria for humans, but its significance in driving the clinical spread of AMR remains unclear, largely due to the lack of holistic-yet-sensitive tools for surveillance and evaluation. Metagenomics is a culture-independent approach well suited for uncovering genetic determinants of defined microbial traits, such as AMR, present within unknown bacterial communities. Despite its popularity, the conventional approach of non-selectively sequencing a sample's metagenome (namely, shotgun-metagenomics) has several technical drawbacks that lead to uncertainty about its effectiveness for AMR assessment; for instance, the low discovery rate of resistance-associated genes due to their naturally small genomic footprint within the vast metagenome. Here, we describe the development of a targeted resistome sequencing method and demonstrate its application in the characterization of the AMR gene profile of bacteria associated with several retail foods. RESULT: A targeted-metagenomic sequencing workflow using a customized bait-capture system targeting over 4,000 referenced AMR genes and 263 plasmid replicon sequences was validated against both mock and sample-derived bacterial community preparations. Compared to shotgun-metagenomics, the targeted method consistently provided for improved recovery of resistance gene targets with a much-improved target detection efficiency (> 300-fold). Targeted resistome analyses conducted on 36 retail-acquired food samples (fresh sprouts, n = 10; ground meat, n = 26) and their corresponding bacterial enrichment cultures (n = 36) reveals in-depth features regarding the identity and diversity of AMR genes, most of which were otherwise undetected by the whole-metagenome shotgun sequencing method. Furthermore, our findings suggest that foodborne Gammaproteobacteria could be the major reservoir of food-associated AMR genetic determinants, and that the resistome structure of the selected high-risk food commodities are, to a large extent, dictated by microbiome composition. CONCLUSIONS: For metagenomic sequencing-based surveillance of AMR, the target-capture method presented herein represents a more sensitive and efficient approach to evaluate the resistome profile of complex food or environmental samples. This study also further implicates retail foods as carriers of diverse resistance-conferring genes indicating a potential impact on the dissemination of AMR. | 2023 | 36991496 |
| 4051 | 4 | 0.9999 | The human microbiome harbors a diverse reservoir of antibiotic resistance genes. The increasing levels of multi-drug resistance in human pathogenic bacteria are compromising our ability to treat infectious disease. Since antibiotic resistance determinants are readily exchanged between bacteria through lateral gene transfer, there is an increasing interest in investigating reservoirs of antibiotic resistance accessible to pathogens. Due to the high likelihood of contact and genetic exchange with pathogens during disease progression, the human microflora warrants special attention as perhaps the most accessible reservoir of resistance genes. Indeed, numerous previous studies have demonstrated substantial antibiotic resistance in cultured isolates from the human microflora. By applying metagenomic functional selections, we recently demonstrated that the functional repertoire of resistance genes in the human microbiome is much more diverse than suggested using previous culture-dependent methods. We showed that many resistance genes from cultured proteobacteria from human fecal samples are identical to resistance genes harbored by human pathogens, providing strong support for recent genetic exchange of this resistance machinery. In contrast, most of the resistance genes we identified with culture independent metagenomic sampling from the same samples were novel when compared to all known genes in public databases. While this clearly demonstrates that the antibiotic resistance reservoir of the large fraction of the human microbiome recalcitrant to culturing is severely under sampled, it may also suggest that barriers exist to lateral gene transfer between these bacteria and readily cultured human pathogens. If we hope to turn the tide against multidrug resistant infections, we must urgently commit to quantitatively characterizing the resistance reservoirs encoded by our diverse human microbiomes, with a particular focus on routes of exchange of these reservoirs with other microbial communities. | 2010 | 21178459 |
| 4007 | 5 | 0.9999 | Detecting horizontal gene transfer among microbiota: an innovative pipeline for identifying co-shared genes within the mobilome through advanced comparative analysis. Horizontal gene transfer (HGT) is a key driver in the evolution of bacterial genomes. The acquisition of genes mediated by HGT may enable bacteria to adapt to ever-changing environmental conditions. Long-term application of antibiotics in intensive agriculture is associated with the dissemination of antibiotic resistance genes among bacteria with the consequences causing public health concern. Commensal farm-animal-associated gut microbiota are considered the reservoir of the resistance genes. Therefore, in this study, we identified known and not-yet characterized mobilized genes originating from chicken and porcine fecal samples using our innovative pipeline followed by network analysis to provide appropriate visualization to support proper interpretation. | 2024 | 38099617 |
| 3900 | 6 | 0.9999 | Antimicrobial resistance pattern in domestic animal - wildlife - environmental niche via the food chain to humans with a Bangladesh perspective; a systematic review. BACKGROUND: Antimicrobial resistance (AMR) is a growing concern globally, but the impact is very deleterious in the context of Bangladesh. Recent review article on the AMR issue demonstrates the scenario in human medicine; unfortunately, no attempt was taken to address this as One Health issue. The antimicrobial resistance bacteria or genes are circulating in the fragile ecosystems and disseminate into human food chain through direct or indirect ways. In this systematic review we are exploring the mechanism or the process of development of resistance pathogen into human food chain via the domestic animal, wildlife and environmental sources in the context of One Health and future recommendation to mitigate this issue in Bangladesh. RESULTS: Tetracycline resistance genes were presenting in almost all sample sources in higher concentrations against enteric pathogen Escherichia coli. The second most significant antibiotics are amino-penicillin that showed resistant pattern across different source of samples. It is a matter of concerns that cephalosporin tends to acquire resistance in wildlife species that might be an indication of this antibiotic resistance gene or the pathogen been circulating in our surrounding environment though the mechanism is still unclear. CONCLUSIONS: Steps to control antibiotic release and environmental disposal from all uses should be immediate and obligatory. There is a need for detailed system biology analysis of resistance development in-situ. | 2020 | 32838793 |
| 4300 | 7 | 0.9999 | A review: antimicrobial resistance data mining models and prediction methods study for pathogenic bacteria. Antimicrobials have paved the way for medical and social development over the last century and are indispensable for treating infections in humans and animals. The dramatic spread and diversity of antibiotic-resistant pathogens have significantly reduced the efficacy of essentially all antibiotic classes and is a global problem affecting human and animal health. Antimicrobial resistance is influenced by complex factors such as resistance genes and dosing, which are highly nonlinear, time-lagged and multivariate coupled, and the amount of resistance data is large and redundant, making it difficult to predict and analyze. Based on machine learning methods and data mining techniques, this paper reviews (1) antimicrobial resistance data storage and analysis techniques, (2) antimicrobial resistance assessment methods and the associated risk assessment methods for antimicrobial resistance, and (3) antimicrobial resistance prediction methods. Finally, the current research results on antimicrobial resistance and the development trend are summarized to provide a systematic and comprehensive reference for the research on antimicrobial resistance. | 2021 | 34522024 |
| 6707 | 8 | 0.9999 | Investigating the occurrence of antimicrobial resistance in the environment in Canada: a scoping review. Antimicrobial resistance is an environmental, agricultural, and public health problem that is impacting the health of humans and animals. The role of the environment as a source of and transmission pathway for antibiotic resistant bacteria and antibiotic resistance genes is a topic of increasing interest that, to date, has received limited attention. This study aimed to describe the sources and possible pathways contributing to antimicrobial resistance dissemination through bioaerosols, water, and soil in Canada using a scoping review methodology and systems thinking approach. A systems map was created to describe the occurrence and relationships between sources and pathways for antimicrobial resistance dissemination through water, soil, and bioaerosols. The map guided the development of the scoping review protocol, specifically the keywords searched and what data were extracted from the included studies. In total, 103 studies of antimicrobial resistance in water, 67 in soil, and 12 in air were identified. Studies to detect the presence of antimicrobial resistance genes have mainly been conducted at wastewater treatment plants and commercial animal livestock facilities. We also identified elements in the systems map with little or no data available (e.g., retail) that need to be investigated further to have a better understanding of antimicrobial resistance dissemination through different Canadian environments. | 2025 | 40279669 |
| 3892 | 9 | 0.9999 | Tetracycline and Phenicol Resistance Genes and Mechanisms: Importance for Agriculture, the Environment, and Humans. Recent reports have speculated on the future impact that antibiotic-resistant bacteria will have on food production, human health, and global economics. This review examines microbial resistance to tetracyclines and phenicols, antibiotics that are widely used in global food production. The mechanisms of resistance, mode of spread between agriculturally and human-impacted environments and ecosystems, distribution among bacteria, and the genes most likely to be associated with agricultural and environmental settings are included. Forty-six different tetracycline resistance () genes have been identified in 126 genera, with (M) having the broadest taxonomic distribution among all bacteria and (B) having the broadest coverage among the Gram-negative genera. Phenicol resistance genes are organized into 37 groups and have been identified in 70 bacterial genera. The review provides the latest information on tetracycline and phenicol resistance genes, including their association with mobile genetic elements in bacteria of environmental, medical, and veterinary relevance. Knowing what specific antibiotic-resistance genes (ARGs) are found in specific bacterial species and/or genera is critical when using a selective suite of ARGs for detection or surveillance studies. As detection methods move to molecular techniques, our knowledge about which type of bacteria carry which resistance gene(s) will become more important to ensure that the whole spectrum of bacteria are included in future surveillance studies. This review provides information needed to integrate the biology, taxonomy, and ecology of tetracycline- and phenicol-resistant bacteria and their resistance genes so that informative surveillance strategies can be developed and the correct genes selected. | 2016 | 27065405 |
| 6595 | 10 | 0.9999 | Methodological aspects of investigating the resistome in pig farm environments. A typical One Health issue, antimicrobial resistance (AMR) development and its spread among people, animals, and the environment attracts significant research attention. The animal sector is one of the major contributors to the development and dissemination of AMR and accounts for more than 50 % of global antibiotics usage. The use of antibiotics exerts a selective pressure for resistant bacteria in the exposed microbiome, but many questions about the epidemiology of AMR in farm environments remain unanswered. This is connected to several methodological challenges and limitations, such as inconsistent sampling methods, complexity of farm environment samples and the lack of standardized protocols for sample collection, processing and bioinformatical analysis. In this project, we combined metagenomics and bioinformatics to optimise the methodology for reproducible research on the resistome in complex samples from the indoor farm environment. The work included optimizing sample collection, transportation, and storage, as well as DNA extraction, sequencing, and bioinformatic analysis, such as metagenome assembly and antibiotic resistance gene (ARG) detection. Our studies suggest that the current most optimal and cost-effective pipeline for ARG search should be based on Illumina sequencing of sock sample material at high depth (at least 25 M 250 bp PE for AMR gene families and 43 M for gene variants). We present a computational analysis utilizing MEGAHIT assembly to balance the identification of bacteria carrying ARGs with the potential loss of diversity and abundance of resistance genes. Our findings indicate that searching against multiple ARG databases is essential for detecting the highest diversity of ARGs. | 2025 | 39954816 |
| 4189 | 11 | 0.9999 | Antimicrobial resistance at farm level. Bacteria that are resistant to antimicrobials are widespread. This article reviews the distribution of resistant bacteria in farm environments. Humans, animals, and environmental sites are all reservoirs of bacterial communities that contain some bacteria that are susceptible to antimicrobials and others that are resistant. Farm ecosystems provide an environment in which resistant bacteria and genes can emerge, amplify and spread. Dissemination occurs via the food chain and via several other pathways. Ecological, epidemiological, molecular and mathematical approaches are being used to study the origin and expansion of the resistance problem and its relationship to antibiotic usage. The prudent and responsible use of antibiotics is an essential part of an ethical approach to improving animal health and food safety. The responsible use of antibiotics during research is vital, but to fully contribute to the containment of antimicrobial resistance 'prudent use' must also be part of good management practices at all levels of farm life. | 2006 | 17094710 |
| 3888 | 12 | 0.9999 | A Systematic Review of Culture-Based Methods for Monitoring Antibiotic-Resistant Acinetobacter, Aeromonas, and Pseudomonas as Environmentally Relevant Pathogens in Wastewater and Surface Water. PURPOSE OF REVIEW: Mounting evidence indicates that habitats such as wastewater and environmental waters are pathways for the spread of antibiotic-resistant bacteria (ARB) and mobile antibiotic resistance genes (ARGs). We identified antibiotic-resistant members of the genera Acinetobacter, Aeromonas, and Pseudomonas as key opportunistic pathogens that grow or persist in built (e.g., wastewater) or natural aquatic environments. Effective methods for monitoring these ARB in the environment are needed to understand their influence on dissemination of ARB and ARGs, but standard methods have not been developed. This systematic review considers peer-reviewed papers where the ARB above were cultured from wastewater or surface water, focusing on the accuracy of current methodologies. RECENT FINDINGS: Recent studies suggest that many clinically important ARGs were originally acquired from environmental microorganisms. Acinetobacter, Aeromonas, and Pseudomonas species are of interest because their ability to persist and grow in the environment provides opportunities to engage in horizontal gene transfer with other environmental bacteria. Pathogenic strains of these organisms resistant to multiple, clinically relevant drug classes have been identified as an urgent threat. However, culture methods for these bacteria were generally developed for clinical samples and are not well-vetted for environmental samples. The search criteria yielded 60 peer-reviewed articles over the past 20 years, which reported a wide variety of methods for isolation, confirmation, and antibiotic resistance assays. Based on a systematic comparison of the reported methods, we suggest a path forward for standardizing methodologies for monitoring antibiotic resistant strains of these bacteria in water environments. | 2023 | 36821031 |
| 4083 | 13 | 0.9999 | Antibiotic resistance gene discovery in food-producing animals. Numerous environmental reservoirs contribute to the widespread antibiotic resistance problem in human pathogens. One environmental reservoir of particular importance is the intestinal bacteria of food-producing animals. In this review I examine recent discoveries of antibiotic resistance genes in agricultural animals. Two types of antibiotic resistance gene discoveries will be discussed: the use of classic microbiological and molecular techniques, such as culturing and PCR, to identify known genes not previously reported in animals; and the application of high-throughput technologies, such as metagenomics, to identify novel genes and gene transfer mechanisms. These discoveries confirm that antibiotics should be limited to prudent uses. | 2014 | 24994584 |
| 4053 | 14 | 0.9998 | Evidence for the circulation of antimicrobial-resistant strains and genes in nature and especially between humans and animals. The concern over antibiotic-resistant bacteria producing human infections that are difficult to treat has led to a proliferation of studies in recent years investigating resistance in livestock, food products, the environment and people, as well as in the mechanisms of transfer of the genetic elements of resistance between bacteria, and the routes, or risk pathways, by which the spread of resistance might occur. The possibility of transfer of resistant genetic elements between bacteria in mixed populations adds many additional and complex potential routes of spread. There is now considerable evidence that transfer of antimicrobial resistance from food-producing animals to humans directly via the food chain is a likely route of spread. The application of animal wastes to farmland and subsequent leaching into watercourses has also been shown to lead to many potential, but less well-documented, pathways for spread. Often, however, where contamination of water sources, processed foods, and other environmental sites is concerned, specific routes of circulation are unclear and may well involve human sources of contamination. Examination of water sources in particular may be difficult due to dilution and their natural flow. Also, as meat is comparatively easy to examine, and is frequently suspected of being a source of spread, there is some bias in favour of studying this vehicle. Such complexities mean that, with the evidence currently available, it is not possible to prioritise the importance of potential risk pathways and circulation routes. | 2012 | 22849279 |
| 3884 | 15 | 0.9998 | Distribution and quantification of antibiotic resistant genes and bacteria across agricultural and non-agricultural metagenomes. There is concern that antibiotic resistance can potentially be transferred from animals to humans through the food chain. The relationship between specific antibiotic resistant bacteria and the genes they carry remains to be described. Few details are known about the ecology of antibiotic resistant genes and bacteria in food production systems, or how antibiotic resistance genes in food animals compare to antibiotic resistance genes in other ecosystems. Here we report the distribution of antibiotic resistant genes in publicly available agricultural and non-agricultural metagenomic samples and identify which bacteria are likely to be carrying those genes. Antibiotic resistance, as coded for in the genes used in this study, is a process that was associated with all natural, agricultural, and human-impacted ecosystems examined, with between 0.7 to 4.4% of all classified genes in each habitat coding for resistance to antibiotic and toxic compounds (RATC). Agricultural, human, and coastal-marine metagenomes have characteristic distributions of antibiotic resistance genes, and different bacteria that carry the genes. There is a larger percentage of the total genome associated with antibiotic resistance in gastrointestinal-associated and agricultural metagenomes compared to marine and Antarctic samples. Since antibiotic resistance genes are a natural part of both human-impacted and pristine habitats, presence of these resistance genes in any specific habitat is therefore not sufficient to indicate or determine impact of anthropogenic antibiotic use. We recommend that baseline studies and control samples be taken in order to determine natural background levels of antibiotic resistant bacteria and/or antibiotic resistance genes when investigating the impacts of veterinary use of antibiotics on human health. We raise questions regarding whether the underlying biology of each type of bacteria contributes to the likelihood of transfer via the food chain. | 2012 | 23133629 |
| 4298 | 16 | 0.9998 | Genomic and Metagenomic Approaches for Predictive Surveillance of Emerging Pathogens and Antibiotic Resistance. Antibiotic-resistant organisms (AROs) are a major concern to public health worldwide. While antibiotics have been naturally produced by environmental bacteria for millions of years, modern widespread use of antibiotics has enriched resistance mechanisms in human-impacted bacterial environments. Antibiotic resistance genes (ARGs) continue to emerge and spread rapidly. To combat the global threat of antibiotic resistance, researchers must develop methods to rapidly characterize AROs and ARGs, monitor their spread across space and time, and identify novel ARGs and resistance pathways. We review how high-throughput sequencing-based methods can be combined with classic culture-based assays to characterize, monitor, and track AROs and ARGs. Then, we evaluate genomic and metagenomic methods for identifying ARGs and biosynthetic pathways for novel antibiotics from genomic data sets. Together, these genomic analyses can improve surveillance and prediction of emerging resistance threats and accelerate the development of new antibiotic therapies to combat resistance. | 2019 | 31172511 |
| 4304 | 17 | 0.9998 | Dissemination of antibiotic-resistant bacteria across geographic borders. The development of antibiotic-resistant (AR) bacteria in any country is of global importance. After their initial selection and local dissemination, AR bacteria can be transferred across international borders by human travelers, animal and insect vectors, agricultural products, and surface water. The sources and routes of importation of strains of AR bacteria are most often unknown or undetected, because many bacteria carrying resistance genes do not cause disease, and routine surveillance often does not detect them. Control of international dissemination of AR bacteria depends on methods to reduce selection pressure for the development of such bacteria and improved surveillance to detect their subsequent spread. | 2001 | 11438903 |
| 6700 | 18 | 0.9998 | Antimicrobial Resistance in Diverse Ecological Niches-One Health Perspective and Food Safety. Antimicrobial resistance (AMR) is a multi-sectoral, systemic, and global issue worldwide. Antimicrobial use (AMU) is a key factor in the selection of resistant bacteria within different ecological niches, from agriculture to food-producing animals to humans. There is a question regarding the extent to which the use of antibiotics in livestock production and the primary food production sector influences the selection and transmission of resistant bacteria and/or resistant genes throughout the food chain and thus contributes to the complexity in the development of AMR in humans. Although the trends in the prevalence of foodborne pathogens have changed over time, the burden of ecological niches with resistance genes, primarily in commensal microorganisms, is of concern. The implementation of the harmonized surveillance of AMU and AMR would provide comprehensive insights into the actual status of resistance and further interventions leading to its reduction. Tracking AMR in different ecological niches by applying advanced genome-based techniques and developing shared AMR data repositories would strengthen the One Health concept. | 2025 | 40426510 |
| 4190 | 19 | 0.9998 | Insects represent a link between food animal farms and the urban environment for antibiotic resistance traits. Antibiotic-resistant bacterial infections result in higher patient mortality rates, prolonged hospitalizations, and increased health care costs. Extensive use of antibiotics as growth promoters in the animal industry represents great pressure for evolution and selection of antibiotic-resistant bacteria on farms. Despite growing evidence showing that antibiotic use and bacterial resistance in food animals correlate with resistance in human pathogens, the proof for direct transmission of antibiotic resistance is difficult to provide. In this review, we make a case that insects commonly associated with food animals likely represent a direct and important link between animal farms and urban communities for antibiotic resistance traits. Houseflies and cockroaches have been shown to carry multidrug-resistant clonal lineages of bacteria identical to those found in animal manure. Furthermore, several studies have demonstrated proliferation of bacteria and horizontal transfer of resistance genes in the insect digestive tract as well as transmission of resistant bacteria by insects to new substrates. We propose that insect management should be an integral part of pre- and postharvest food safety strategies to minimize spread of zoonotic pathogens and antibiotic resistance traits from animal farms. Furthermore, the insect link between the agricultural and urban environment presents an additional argument for adopting prudent use of antibiotics in the food animal industry. | 2014 | 24705326 |