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Methods in Molecular Biology (Clifton,... 2023Antimicrobial resistance (AMR) is one of the threats to our world according to the World Health Organization (WHO). Resistance is an evolutionary dynamic process where... (Review)
Review
Antimicrobial resistance (AMR) is one of the threats to our world according to the World Health Organization (WHO). Resistance is an evolutionary dynamic process where host-associated microbes have to adapt to their stressful environments. AMR could be classified according to the mechanism of resistance or the biome where resistance takes place. Antibiotics are one of the stresses that lead to resistance through antibiotic resistance genes (ARGs). The resistome could be defined as the collection of all ARGs in an organism's genome or metagenome. Currently, there is a growing body of evidence supporting that the environment is the largest source of ARGs, but to what extent the environment does contribute to the antimicrobial resistance evolution is a matter of investigation. Monitoring the ARGs transfer route from the environment to humans and vice versa is a nature-to-nature feedback loop where you cannot set an accurate starting point of the evolutionary event. Thus, tracking resistome evolution and transfer to and from different biomes is crucial for the surveillance and prediction of the next resistance outbreak.Herein, we review the overlap between clinical and environmental resistomes and the available databases and computational analysis tools for resistome analysis through ARGs detection and characterization in bacterial genomes and metagenomes. Till this moment, there is no tool that can predict the resistance evolution and dynamics in a distinct biome. But, hopefully, by understanding the complicated relationship between the environmental and clinical resistome, we could develop tools that track the feedback loop from nature to nature in terms of evolution, mobilization, and transfer of ARGs.
Topics: Humans; Bacteria; Drug Resistance, Microbial; Anti-Bacterial Agents; Genome, Bacterial; Metagenome; Genes, Bacterial; Metagenomics
PubMed: 37258869
DOI: 10.1007/978-1-0716-3072-3_15 -
Proceedings of the National Academy of... Nov 2020Antibiotic use is a key driver of antibiotic resistance. Understanding the quantitative association between antibiotic use and resulting resistance is important for...
Antibiotic use is a key driver of antibiotic resistance. Understanding the quantitative association between antibiotic use and resulting resistance is important for predicting future rates of antibiotic resistance and for designing antibiotic stewardship policy. However, the use-resistance association is complicated by "spillover," in which one population's level of antibiotic use affects another population's level of resistance via the transmission of bacteria between those populations. Spillover is known to have effects at the level of families and hospitals, but it is unclear if spillover is relevant at larger scales. We used mathematical modeling and analysis of observational data to address this question. First, we used dynamical models of antibiotic resistance to predict the effects of spillover. Whereas populations completely isolated from one another do not experience any spillover, we found that if even 1% of interactions are between populations, then spillover may have large consequences: The effect of a change in antibiotic use in one population on antibiotic resistance in that population could be reduced by as much as 50%. Then, we quantified spillover in observational antibiotic use and resistance data from US states and European countries for three pathogen-antibiotic combinations, finding that increased interactions between populations were associated with smaller differences in antibiotic resistance between those populations. Thus, spillover may have an important impact at the level of states and countries, which has ramifications for predicting the future of antibiotic resistance, designing antibiotic resistance stewardship policy, and interpreting stewardship interventions.
Topics: Anti-Bacterial Agents; Antimicrobial Stewardship; Bacteria; Cross-Sectional Studies; Drug Resistance, Bacterial; Drug Resistance, Microbial; Europe; Hospitals; Humans; Streptococcus pneumoniae; United States
PubMed: 33139558
DOI: 10.1073/pnas.2013694117 -
The Science of the Total Environment May 2023An ever-increasing number of newly synthesised nanoparticles have a constantly expanding range of applications. The large-scale implementation of nanoparticles will... (Review)
Review
An ever-increasing number of newly synthesised nanoparticles have a constantly expanding range of applications. The large-scale implementation of nanoparticles will inevitably lead to intentional or accidental contamination of various environments. Since the major benefit of using several metallic nanoparticles is antimicrobial activity, these emerging contaminants may have a potentially hazardous impact on the development and spread of antibiotic resistance - a challenge that threats infection therapy worldwide. Few studies underline that metallic nanoparticles may affect the emergence and evolution of resistance via mutations and horizontal transfer between different bacterial species. Due to the complexity of factors and mechanisms involved in disseminating antibiotic resistance, it is crucial to investigate if metallic nanoparticles play a significant role in this process through co-selection ability and pressure exerted on bacteria. The aim of this review is to summarise the current research on mutations and three main horizontal gene transfer modes facilitated by nanoparticles. Here, the current results in the field are presented, major knowledge gaps and the necessity for more environmentally relevant studies are discussed.
Topics: Anti-Bacterial Agents; Drug Resistance, Microbial; Bacteria; Metal Nanoparticles; Gene Transfer, Horizontal; Drug Resistance, Bacterial
PubMed: 36740055
DOI: 10.1016/j.scitotenv.2023.162029 -
The American Journal of Nursing Dec 2017What if our prescribing practices are wrong?
What if our prescribing practices are wrong?
Topics: Anti-Bacterial Agents; Drug Resistance, Microbial; Humans; Practice Patterns, Physicians'
PubMed: 29189251
DOI: 10.1097/01.NAJ.0000527492.32234.1d -
The Science of the Total Environment Mar 2022The spread of antibiotic resistance among bacterial pathogens is to a large extent mediated by mobile antibiotic resistance genes (ARGs). The prevalence and geographic...
The spread of antibiotic resistance among bacterial pathogens is to a large extent mediated by mobile antibiotic resistance genes (ARGs). The prevalence and geographic distribution of several newly discovered ARGs, as well as some clinically important ARGs conferring resistance to last resort antibiotics, are largely unknown. Targeted analysis of wastewater samples could allow estimations of carriage in the population connected to the sewers as well as release to the environment. Here we quantified ARGs conferring resistance to linezolid (optrA and cfr(A)) and colistin (mcr-1, -2, -3, -4 and -5) and the recently discovered gar (aminoglycoside ARG) and sul4 (sulphonamide ARG) in raw hospital and municipal wastewater as well as treated municipal wastewater during five years in a low antibiotic resistance prevalence setting (Gothenburg, Sweden). Additionally, variations in bacterial composition of the wastewaters characterized by 16S rRNA sequencing were related to the variations of the ARGs in an attempt to reveal if the presence of known or suspected bacterial host taxa could explain the presence of the ARGs in wastewater. The mcr-1, mcr-3, mcr-4, mcr-5, sul4 and gar genes were detected regularly in all types of wastewater samples while optrA and cfr(A) were detected only in hospital wastewater. The most abundant genes were mcr-3 and mcr-5, especially in municipal wastewater. The detection of optrA was restricted to a peak during one year. Most of the ARGs correlated with taxa previously described as bacterial hosts and associated with humans. Although some of the tentative hosts may include bacteria also thriving in wastewater environments, detection of the ARGs in the wastewaters could reflect their presence in the gut flora of the contributing populations. If so, they could already today or in the near future hinder treatment of bacterial infections in a setting where they currently are rarely targeted/detected during clinical surveillance.
Topics: Anti-Bacterial Agents; Drug Resistance, Microbial; Genes, Bacterial; Hospitals; Humans; RNA, Ribosomal, 16S; Sweden; Wastewater
PubMed: 34748849
DOI: 10.1016/j.scitotenv.2021.151433 -
Molecular Biology and Evolution Apr 2017Can we exploit our burgeoning understanding of molecular evolution to slow the progress of drug resistance? One role of an infection clinician is exactly that: to...
UNLABELLED
Can we exploit our burgeoning understanding of molecular evolution to slow the progress of drug resistance? One role of an infection clinician is exactly that: to foresee trajectories to resistance during antibiotic treatment and to hinder that evolutionary course. But can this be done at a hospital-wide scale? Clinicians and theoreticians tried to when they proposed two conflicting behavioral strategies that are expected to curb resistance evolution in the clinic, these are known as "antibiotic cycling" and "antibiotic mixing." However, the accumulated data from clinical trials, now approaching 4 million patient days of treatment, is too variable for cycling or mixing to be deemed successful. The former implements the restriction and prioritization of different antibiotics at different times in hospitals in a manner said to "cycle" between them. In antibiotic mixing, appropriate antibiotics are allocated to patients but randomly. Mixing results in no correlation, in time or across patients, in the drugs used for treatment which is why theorists saw this as an optimal behavioral strategy. So while cycling and mixing were proposed as ways of controlling evolution, we show there is good reason why clinical datasets cannot choose between them: by re-examining the theoretical literature we show prior support for the theoretical optimality of mixing was misplaced. Our analysis is consistent with a pattern emerging in data: neither cycling or mixing is a priori better than the other at mitigating selection for antibiotic resistance in the clinic.
KEY WORDS
: antibiotic cycling, antibiotic mixing, optimal control, stochastic models.
Topics: Anti-Bacterial Agents; Biological Evolution; Dose-Response Relationship, Drug; Drug Resistance, Bacterial; Drug Resistance, Microbial; Evolution, Molecular; Hospitals; Humans; Models, Biological; Models, Theoretical; Treatment Outcome
PubMed: 28096304
DOI: 10.1093/molbev/msw292 -
Environmental Pollution (Barking, Essex... Jan 2018Antibiotic resistance is a worsening global concern, and the environmental behaviors and migration patterns of antibiotic resistance genes (ARGs) have attracted... (Review)
Review
Antibiotic resistance is a worsening global concern, and the environmental behaviors and migration patterns of antibiotic resistance genes (ARGs) have attracted considerable interest. Understanding the long-range transport of ARG pollution is crucial. In this study, we characterized the dynamics of ARG changes after their release into aquatic environments and demonstrated the importance of traditional chemical contaminants in the transmission mechanisms of ARGs. We hypothesized that the main route of ARG proliferation switches from active transmission to passive transmission. This antibiotic-dominated switch is motivated and affected by non-corresponding contaminants. The effect of anthropogenic activities gradually weakens from inland aquatic environments to ocean environments; however, the effect of changes in environmental conditions is enhanced along this gradient. The insights discussed in this study will help to improve the understanding of the distribution and migration of ARG pollution in various aquatic environments, and provide a modern perspective to reveal the effect of corresponding contaminants and non-corresponding contaminants in the process of antibiotic resistance proliferation.
Topics: Anti-Bacterial Agents; Drug Resistance, Microbial; Environment; Environmental Monitoring; Genes, Bacterial; Water Microbiology; Water Pollutants, Chemical; Water Pollution, Chemical
PubMed: 28986079
DOI: 10.1016/j.envpol.2017.08.078 -
Med (New York, N.Y.) Apr 2021Antibiotic resistance challenges public health on many fronts, and it is increasingly clear that it must be addressed in the environment to control emerging resistance...
Antibiotic resistance challenges public health on many fronts, and it is increasingly clear that it must be addressed in the environment to control emerging resistance and infections in humans and animals. Here, we outline how the US Centers for Disease Control and Prevention is addressing antibiotic resistance in the environment.
Topics: Anti-Bacterial Agents; Antifungal Agents; Centers for Disease Control and Prevention, U.S.; Drug Resistance, Fungal; Drug Resistance, Microbial; United States
PubMed: 35590159
DOI: 10.1016/j.medj.2021.03.011 -
Water Research Oct 2020Antibiotic resistance has become a global public health concern, rendering common infections untreatable. Given the widespread occurrence, increasing attention is being... (Review)
Review
Antibiotic resistance has become a global public health concern, rendering common infections untreatable. Given the widespread occurrence, increasing attention is being turned toward environmental pathways that potentially contribute to antibiotic resistance gene (ARG) dissemination outside the clinical realm. Studies during the past decade have clearly proved the increased ARG pollution trend along with gradient of anthropogenic interference, mainly through marker-ARG detection by PCR-based approaches. However, accurate source-tracking has been always confounded by various factors in previous studies, such as autochthonous ARG level, spatiotemporal variability and environmental resistome complexity, as well as inherent method limitation. The rapidly developed metagenomics profiles ARG occurrence within the sample-wide genomic context, opening a new avenue for source tracking of environmental ARG pollution. Coupling with machine-learning classification, it has been demonstrated the potential of metagenomic ARG profiles in unambiguously assigning source contribution. Through identifying indicator ARG and recovering ARG-host genomes, metagenomics-based analysis will further increase the resolution and accuracy of source tracking. In this review, challenges and progresses in source-tracking studies on environmental ARG pollution will be discussed, with specific focus on recent metagenomics-guide approaches. We propose an integrative metagenomics-based framework, in which coordinated efforts on experimental design and metagenomic analysis will assist in realizing the ultimate goal of robust source-tracking in environmental ARG pollution.
Topics: Anti-Bacterial Agents; Drug Resistance, Microbial; Genes, Bacterial; Metagenome; Metagenomics
PubMed: 33086465
DOI: 10.1016/j.watres.2020.116127 -
Journal of Hazardous Materials Oct 2021The emergence and spread of antibiotic resistance genes (ARGs) have become major concerns for both public health and environmental ecosystems. Emerging pollutants (EPs)... (Review)
Review
The emergence and spread of antibiotic resistance genes (ARGs) have become major concerns for both public health and environmental ecosystems. Emerging pollutants (EPs) that accumulate in environmental compartments also pose a potential risk for the enrichment of ARGs in indigenous microorganisms. This paper presents a comprehensive review of the effects and intrinsic mechanisms of EPs, including microplastics, engineered nanomaterials, disinfection byproducts, pharmaceuticals, and personal care products, on the occurrence and dissemination of ARGs. State-of-the-art methods for identifying culture-independent ARG-host interactions and monitoring horizontal gene transfer (HGT) processes in real-time are first reviewed. The contributions of EPs to the abundance and diversity of ARGs are then summarized. Finally, we discussed the underlying mechanisms related to the regulation of HGT, increased mutagenesis, and the evolution of microbial communities. Further details of three HGT (i.e., conjugation, transformation, and transduction) frequency patterns in response to various EPs are also examined. This review contemplates and reassesses the risks of ARG evolution posed by the manufacture and application of EPs.
Topics: Anti-Bacterial Agents; Drug Resistance, Microbial; Environmental Pollutants; Genes, Bacterial; Microbiota; Plastics
PubMed: 34273886
DOI: 10.1016/j.jhazmat.2021.126602