scholarly journals What is the Burden of Antimicrobial Resistance Genes in Selected Ready-to-Eat Foods?

2021 ◽  
Author(s):  
Dr Edward Haynes ◽  
Chris Conyers ◽  
Dr Marc Kennedy ◽  
Roy Macarthur ◽  
Sam McGreig ◽  
...  
Keyword(s):  
Food Safety ◽  
Antimicrobial Resistance ◽  
Resistance Genes ◽  
Food Chain ◽  
Bacterial Infections ◽  
Action Plan ◽  
Good Practice ◽  
Metagenomic Sequencing ◽  
Antimicrobial Resistance Genes ◽  
The Uk

This study was designed to get a broad estimate of the presence and the types of antimicrobial resistance genes across 52 simple ready-to-eat foods. It was also carried out to understand the benefits and drawbacks of using metagenomic sequencing, a fairly new technology, to study AMR genes. An antimicrobial is any substance that kills or inhibits the growth of microorganisms. It includes antibiotics which are used to treat bacterial infections in both humans and animals. Given the relevant selective pressures, the bacteria itself can change and find ways to survive the effects of an antimicrobials. This results in the bacteria becoming resistant to the ‘killing’ effects of antimicrobials and is known as ‘antimicrobial resistance’. The more we use antimicrobials and antibiotics and the way that we use them can increase the chance that bacteria will become resistant to antimicrobials. This is important as it can lead to infections that become more difficult to treat with drugs and poses a risk to the public health. T Addressing AMR is a national strategic priority for the UK Government which has led to the development of a new 20-year Vision for AMR and the 5-year National Action Plan (NAP), which runs until 2024. The NAP lays out how the UK will address the AMR challenge and takes a ‘One-Health’ approach which spans people, animals, agriculture, food and the environment. The NAP includes a specific section on the importance of better food safety to limit the contamination of foods and spread of AMR. This section emphasises the need to strengthen the evidence base for AMR and food safety through research, surveillance and promoting good practice across the food chain. The FSA is playing its part by continuing to fill evidence gaps on the role that food plays in AMR through the commissioning of research and surveillance. We are also promoting and improving UK food hygiene (‘4Cs’ messages) across the food chain that will help reduce exposure to AMR bacteria.

scholarly journals Culture-Independent Genotyping, Virulence and Antimicrobial Resistance Gene Identification of Staphylococcus aureus from Orthopaedic Implant-Associated Infections

2021 ◽  
Vol 9 (4) ◽  
pp. 707
Author(s):  
J. Christopher Noone ◽  
Fabienne Antunes Ferreira ◽  
Hege Vangstein Aamot
Keyword(s):  
Staphylococcus Aureus ◽  
Antimicrobial Resistance ◽  
Resistance Genes ◽  
Virulence Gene ◽  
Orthopaedic Implant ◽  
Metagenomic Sequencing ◽  
Gene Detection ◽  
Shotgun Metagenomic Sequencing ◽  
Antimicrobial Resistance Genes ◽  
Culture Independent

Our culture-independent nanopore shotgun metagenomic sequencing protocol on biopsies has the potential for same-day diagnostics of orthopaedic implant-associated infections (OIAI). As OIAI are frequently caused by Staphylococcus aureus, we included S. aureus genotyping and virulence gene detection to exploit the protocol to its fullest. The aim was to evaluate S. aureus genotyping, virulence and antimicrobial resistance genes detection using the shotgun metagenomic sequencing protocol. This proof of concept study included six patients with S. aureus-associated OIAI at Akershus University Hospital, Norway. Five tissue biopsies from each patient were divided in two: (1) conventional microbiological diagnostics and genotyping, and whole genome sequencing (WGS) of S. aureus isolates; (2) shotgun metagenomic sequencing of DNA from the biopsies. Consensus sequences were analysed using spaTyper, MLST, VirulenceFinder, and ResFinder from the Center for Genomic Epidemiology (CGE). MLST was also compared using krocus. All spa-types, one CGE and four krocus MLST results matched Sanger sequencing results. Virulence gene detection matched between WGS and shotgun metagenomic sequencing. ResFinder results corresponded to resistance phenotype. S. aureus spa-typing, and identification of virulence and antimicrobial resistance genes are possible using our shotgun metagenomics protocol. MLST requires further optimization. The protocol has potential application to other species and infection types.

scholarly journals Multi-omic surveillance of Escherichia coli and Klebsiella spp. in hospital sink drains and patients

2020 ◽  
Author(s):  
B Constantinides ◽  
KK Chau ◽  
TP Quan ◽  
G Rodger ◽  
M Andersson ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Antimicrobial Resistance ◽  
Resistance Genes ◽  
Bacterial Infections ◽  
Wide Spectrum ◽  
Klebsiella Oxytoca ◽  
Clinical Disease ◽  
E Coli ◽  
Antimicrobial Resistance Genes ◽  
Wide Range

ABSTRACTEscherichia coli and Klebsiella spp. are important human pathogens that cause a wide spectrum of clinical disease. In healthcare settings, sinks and other wastewater sites have been shown to be reservoirs of antimicrobial-resistant E. coli and Klebsiella spp., particularly in the context of outbreaks of resistant strains amongst patients. Without focusing exclusively on resistance markers or a clinical outbreak, we demonstrate that many hospital sink drains are abundantly and persistently colonised with diverse populations of E. coli, Klebsiella pneumoniae and Klebsiella oxytoca, including both antimicrobial-resistant and susceptible strains. Using whole genome sequencing (WGS) of 439 isolates, we show that environmental bacterial populations are largely structured by ward and sink, with only a handful of lineages, such as E. coli ST635, being widely distributed, suggesting different prevailing ecologies which may vary as a result of different inputs and selection pressures. WGS of 46 contemporaneous patient isolates identified one (2%; 95% CI 0.05-11%) E. coli urine infection-associated isolate with high similarity to a prior sink isolate, suggesting that sinks may contribute to up to 10% of infections caused by these organisms in patients on the ward over the same timeframe. Using metagenomics from 20 sink-timepoints, we show that sinks also harbour many clinically relevant antimicrobial resistance genes including blaCTX-M, blaSHV and mcr, and may act as niches for the exchange and amplification of these genes. Our study reinforces the potential role of sinks in contributing to Enterobacterales infection and antimicrobial resistance in hospital patients, something that could be amenable to intervention.IMPORTANCEEscherichia coli and Klebsiella spp. cause a wide range of bacterial infections, including bloodstream, urine and lung infections. Previous studies have shown that sink drains in hospitals may be part of transmission chains in outbreaks of antimicrobial-resistant E. coli and Klebsiella spp., leading to colonisation and clinical disease in patients. We show that even in non-outbreak settings, contamination of sink drains by these bacteria is common across hospital wards, and that many antimicrobial resistance genes can be found and potentially exchanged in these sink drain sites. Our findings demonstrate that the colonisation of handwashing sink drains by these bacteria in hospitals is likely contributing to some infections in patients, and that additional work is needed to further quantify this risk, and to consider appropriate mitigating interventions.

scholarly journals Merging Metagenomics and Spatial Epidemiology To Understand the Distribution of Antimicrobial Resistance Genes from Enterobacteriaceae in Wild Owls

2020 ◽  
Vol 86 (20) ◽  
Author(s):  
Elizabeth A. Miller ◽  
Julia B. Ponder ◽  
Michelle Willette ◽  
Timothy J. Johnson ◽  
Kimberly L. VanderWaal
Keyword(s):  
Antimicrobial Resistance ◽  
Resistance Genes ◽  
Spatial Epidemiology ◽  
Anthropogenic Sources ◽  
Resistant Bacteria ◽  
Metagenomic Sequencing ◽  
Wild Animals ◽  
Natural Ecosystems ◽  
Content Type ◽  
Antimicrobial Resistance Genes

ABSTRACT Antimicrobial resistance (AMR) is a well-documented phenomenon in bacteria from many natural ecosystems, including wild animals. However, the specific determinants and spatial distribution of resistant bacteria and antimicrobial resistance genes (ARGs) in the environment remain incompletely understood. In particular, information regarding the importance of anthropogenic sources of AMR relative to that of other biological and ecological influences is lacking. We conducted a cross-sectional study of AMR in great horned owls (Bubo virginianus) and barred owls (Strix varia) admitted to a rehabilitation center in the midwestern United States. A combination of selective culture enrichment and shotgun metagenomic sequencing was used to identify ARGs from Enterobacteriaceae. Overall, the prevalence of AMR was comparable to that in past studies of resistant Enterobacteriaceae in raptors, with acquired ARGs being identified in 23% of samples. Multimodel regression analyses identified seasonality and owl age to be important predictors of the likelihood of the presence of ARGs, with birds sampled during warmer months being more likely to harbor ARGs than those sampled during cooler months and with birds in their hatch year being more likely to harbor β-lactam ARGs than adults. Beyond host-specific determinants, ARG-positive owls were also more likely to be recovered from areas of high agricultural land cover. Spatial clustering analyses identified a significant high-risk cluster of tetracycline resistance gene-positive owls in the southern sampling range, but this could not be explained by any predictor variables. Taken together, these results highlight the complex distribution of AMR in natural environments and suggest that both biological and anthropogenic factors play important roles in determining the emergence and persistence of AMR in wildlife. IMPORTANCE Antimicrobial resistance (AMR) is a multifaceted problem that poses a worldwide threat to human and animal health. Recent reports suggest that wildlife may play an important role in the emergence, dissemination, and persistence of AMR. As such, there have been calls for better integration of wildlife into current research on AMR, including the use of wild animals as biosentinels of AMR contamination in the environment. A One Health approach can be used to gain a better understanding of all AMR sources and pathways, particularly those at the human-animal-environment interface. Our study focuses on this interface in order to assess the effect of human-impacted landscapes on AMR in a wild animal. This work highlights the value of wildlife rehabilitation centers for environmental AMR surveillance and demonstrates how metagenomic sequencing within a spatial epidemiology framework can be used to address questions surrounding AMR complexity in natural ecosystems.

scholarly journals ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Achal Dhariwal ◽  
Roger Junges ◽  
Tsute Chen ◽  
Fernanda C Petersen
Keyword(s):  
Antimicrobial Resistance ◽  
Resistance Gene ◽  
High Throughput ◽  
Resistance Genes ◽  
Visual Analytics ◽  
Gene List ◽  
Metagenomic Sequencing ◽  
High Throughput Analysis ◽  
Antimicrobial Resistance Genes ◽  
Antimicrobial Resistance Gene

Abstract The study of resistomes using whole metagenomic sequencing enables high-throughput identification of resistance genes in complex microbial communities, such as the human microbiome. Over recent years, sophisticated and diverse pipelines have been established to facilitate raw data processing and annotation. Despite the progress, there are no easy-to-use tools for comprehensive visual, statistical and functional analysis of resistome data. Thus, exploration of the resulting large complex datasets remains a key bottleneck requiring robust computational resources and technical expertise, which creates a significant hurdle for advancements in the field. Here, we introduce ResistoXplorer, a user-friendly tool that integrates recent advancements in statistics and visualization, coupled with extensive functional annotations and phenotype collection, to enable high-throughput analysis of common outputs generated from metagenomic resistome studies. ResistoXplorer contains three modules—the ‘Antimicrobial Resistance Gene Table’ module offers various options for composition profiling, functional profiling and comparative analysis of resistome data; the ‘Integration’ module supports integrative exploratory analysis of resistome and microbiome abundance profiles derived from metagenomic samples; finally, the ‘Antimicrobial Resistance Gene List’ module enables users to intuitively explore the associations between antimicrobial resistance genes and the microbial hosts using network visual analytics to gain biological insights. ResistoXplorer is publicly available at http://www.resistoxplorer.no.

scholarly journals Indexed variation graphs for efficient and accurate resistome profiling

2018 ◽  
Author(s):  
Will P.M. Rowe ◽  
Martyn D Winn
Keyword(s):  
Antimicrobial Resistance ◽  
Resistance Genes ◽  
Bacterial Infections ◽  
Gene Diversity ◽  
Graph Representation ◽  
Local Alignment ◽  
Sequencing Data ◽  
Metagenomic Sequence ◽  
Antimicrobial Resistance Genes ◽  
Antimicrobial Resistance Gene

AbstractBackgroundAntimicrobial resistance remains a major threat to global health. Profiling the collective antimicrobial resistance genes within a metagenome (the “resistome”) facilitates greater understanding of antimicrobial resistance gene diversity and dynamics. In turn, this can allow for gene surveillance, individualised treatment of bacterial infections and more sustainable use of antimicrobials. However, resistome profiling can be complicated by high similarity between reference genes, as well as the sheer volume of sequencing data and the complexity of analysis workflows. We have developed an efficient and accurate method for resistome profiling that addresses these complications and improves upon currently available tools.ResultsOur method combines a variation graph representation of gene sets with an LSH Forest indexing scheme to allow for fast classification of metagenomic sequence reads using similarity-search queries. Subsequent hierarchical local alignment of classified reads against graph traversals enables accurate reconstruction of full-length gene sequences using a scoring scheme. We provide our implementation, GROOT, and show it to be both faster and more accurate than a current reference-dependent tool for resistome profiling. GROOT runs on a laptop and can process a typical 2 gigabyte metagenome in 2 minutes using a single CPU.ConclusionWe present a method for resistome profiling that utilises a novel index and search strategy to accurately type resistance genes in metagenomic samples. The use of variation graphs yields several advantages over other methods using linear reference sequences. Our method is not restricted to resistome profiling and has the potential to improve current metagenomic workflows. The implementation is written in Go and is available at https://github.com/will-rowe/groot (MIT license).

scholarly journals The fecal resistome of dairy cattle is associated with diet during nursing

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Jinxin Liu ◽  
Diana H. Taft ◽  
Maria X. Maldonado-Gomez ◽  
Daisy Johnson ◽  
Michelle L. Treiber ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Gut Microbiota ◽  
Dairy Cattle ◽  
Resistance Genes ◽  
Early Life ◽  
Dairy Calves ◽  
Health Concern ◽  
Metagenomic Sequencing ◽  
Global Public Health ◽  
Antimicrobial Resistance Genes

Abstract Antimicrobial resistance is a global public health concern, and livestock play a significant role in selecting for resistance and maintaining such reservoirs. Here we study the succession of dairy cattle resistome during early life using metagenomic sequencing, as well as the relationship between resistome, gut microbiota, and diet. In our dataset, the gut of dairy calves serves as a reservoir of 329 antimicrobial resistance genes (ARGs) presumably conferring resistance to 17 classes of antibiotics, and the abundance of ARGs declines gradually during nursing. ARGs appear to co-occur with antibacterial biocide or metal resistance genes. Colostrum is a potential source of ARGs observed in calves at day 2. The dynamic changes in the resistome are likely a result of gut microbiota assembly, which is closely associated with diet transition in dairy calves. Modifications in the resistome may be possible via early-life dietary interventions to reduce overall antimicrobial resistance.

Antimicrobial resistance in Bacillus-based biopesticide products

Microbiology ◽  
2021 ◽  
Vol 167 (8) ◽  
Author(s):  
Mo Kaze ◽  
Lauren Brooks ◽  
Mark Sistrom
Keyword(s):  
Antimicrobial Resistance ◽  
Resistance Genes ◽  
Bacterial Infections ◽  
Agricultural Practices ◽  
Resistant Bacteria ◽  
Multiple Drug ◽  
Drug Classes ◽  
Antimicrobial Resistance Genes ◽  
Microbiological Techniques ◽  
High Concentrations

The crisis of antimicrobial resistant bacterial infections is one of the most pressing public health issues. Common agricultural practices have been implicated in the generation of antimicrobial resistant bacteria. Biopesticides, live bacteria used for pest control, are non-pathogenic and considered safe for consumption. Application of bacteria-based pesticides to crops in high concentrations raises the possibility of unintentional contributions to the movement and generation of antimicrobial resistance genes in the environment. However, the presence of clinically relevant antimicrobial resistance genes and their resistance phenotypes are currently unknown. Here we use a combination of multiple bioinformatic and microbiological techniques to define resistomes of widely used biopesticides and determine how the presence of suspected antimicrobial resistance genes translates to observable resistance phenotypes in several biopesticide products. Our results demonstrate that biopesticide products are reservoirs of clinically relevant antimicrobial resistance genes and bear resistance to multiple drug classes.

scholarly journals ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data

2020 ◽  
Author(s):  
Achal Dhariwal ◽  
Roger Junges ◽  
Tsute Chen ◽  
Fernanda Cristina Petersen
Keyword(s):  
Antimicrobial Resistance ◽  
Resistance Gene ◽  
High Throughput ◽  
Resistance Genes ◽  
Visual Analytics ◽  
Gene List ◽  
Metagenomic Sequencing ◽  
High Throughput Analysis ◽  
Antimicrobial Resistance Genes ◽  
Antimicrobial Resistance Gene

ABSTRACTThe study of resistomes using whole metagenomic sequencing enables high throughput identification of resistance genes in complex microbial communities, such as the human microbiome. Over recent years, sophisticated and diverse pipelines have been established to facilitate raw data processing and annotation. Despite the progress, there are no easy-to-use tools for comprehensive visual, statistical, and functional analysis of resistome data. Thus, exploration of the resulting large complex datasets remains a key bottleneck requiring robust computational resources and technical expertise, which creates a significant hurdle for advancements in the field. Here, we introduce ResistoXplorer, a user-friendly tool that integrates recent advancements in statistics and visualization, coupled with extensive functional annotations and phenotype collection, to enable high-throughput analysis of common outputs generated from metagenomic resistome studies. ResistoXplorer contains three modules- the ‘Antimicrobial Resistance Gene Table’ module offers various options for composition profiling, functional profiling and comparative analysis of resistome data; the ‘Integration’ module supports integrative exploratory analysis of resistome and microbiome abundance profiles derived from metagenomic samples; finally, the ‘Antimicrobial Resistance Gene List’ module enables users to intuitively explore the associations between antimicrobial resistance genes and the microbial hosts using network visual analytics to gain biological insights. ResistoXplorer is publicly available at http://www.resistoxplorer.no.

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