Dynamics Of Antibiotic Resistance Research Articles

Modeling the impact of urban and hospital eco-exposomes on antibiotic-resistance dynamics in wastewaters

The emergence and selection of antibiotic resistance is a major public health problem worldwide. The presence of antibiotic-resistant bacteria (ARBs) in natural and anthropogenic environments threatens the sustainability of efforts to reduce resistance in human and animal populations. Here, we use mathematical modeling of the selective effect of antibiotics and contaminants on the dynamics of bacterial resistance in water to analyze longitudinal spatio-temporal data collected in hospital and urban wastewater between 2012 and 2015. Samples were collected monthly during the study period at four different sites in Haute-Savoie, France: hospital and urban wastewater, before and after water treatment plants. Three different categories of exposure variables were collected simultaneously: 1) heavy metals, 2) antibiotics and 3) surfactants for a total of 13 drugs/molecules; in parallel to the normalized abundance of 88 individual genes and mobile genetic elements, mostly conferring resistance to antibiotics. A simple hypothesis-driven model describing weekly antibiotic resistance gene (ARG) dynamics was proposed to fit the available data, assuming that normalized gene abundance is proportional to antibiotic resistant bacteria (ARB) populations in water. The detected compounds were found to influence the dynamics of 17 genes found at multiple sites. While mercury and vancomycin were associated with increased ARG and affected the dynamics of 10 and 12 identified genes respectively, surfactants antagonistically affected the dynamics of three genes. The models proposed here make it possible to analyze the relationship between the persistence of resistance genes in the aquatic environment and specific compounds associated with human activities from longitudinal data. Our analysis of French data over 2012–2015 identified mercury and vancomycin as co-selectors for some ARGs.

Dynamics of antibiotic resistance in the surgical departments of a multidisciplinary hospital using the example of the Republican Hospital n.a. V.A. Baranov

Dynamics of antibiotic resistance in the surgical departments of a multidisciplinary hospital using the example of the Republican Hospital n.a. V.A. Baranov

The Role of the Environment in Dynamics of Antibiotic Resistance in Humans and Animals: A Modelling Study.

Antibiotic resistance is transmitted between animals and humans either directly or indirectly, through transmission via the environment. However, little is known about the contribution of the environment to resistance epidemiology. Here, we use a mathematical model to study the effect of the environment on human resistance levels and the impact of interventions to reduce antibiotic consumption in animals. We developed a model of resistance transmission with human, animal, and environmental compartments. We compared the model outcomes under different transmission scenarios, conducted a sensitivity analysis, and investigated the impacts of curtailing antibiotic usage in animals. Human resistance levels were most sensitive to parameters associated with the human compartment (rate of loss of resistance from humans) and with the environmental compartment (rate of loss of environmental resistance and rate of environment-to-human transmission). Increasing environmental transmission could lead to increased or reduced impact of curtailing antibiotic consumption in animals on resistance in humans. We highlight that environment–human sharing of resistance can influence the epidemiology of resistant bacterial infections in humans and reduce the impact of interventions that curtail antibiotic consumption in animals. More data on resistance in the environment and frequency of human–environment transmission is crucial to understanding antibiotic resistance dynamics.

Assessing bacterial diversity and antibiotic resistance dynamics in wastewater effluent-irrigated soil and vegetables in a microcosm setting

Water scarcity is one of the main challenges in sustainable agricultural development particularly in developing countries therefore, irrigation of food crops with wastewater effluent has become a common practice in order to meet the growing food demand. The aim of this study was to determine the impact of wastewater irrigation on bacterial community and antibiotic resistance dynamics in soil and vegetables in an agricultural setting. To determine bacterial diversity, occurrence and overall dynamics of antibiotic resistant genes (ARGs) in effluent irrigated soil and vegetables, 16S rRNA gene metagenomics, shotgun metagenomics and molecular PCR technique were utilized. A shift in bacterial community profile was observed as notable reduction in proteobacteria and increase in firmicutes phyla from the microcosm soil following wastewater effluent irrigation. Shotgun metagenomics revealed diverse ARGs belonging to at least nine different classes of antibiotics in the effluent wastewater. However, only blaTEM (beta-lactamase) and aadA (aminoglycoside) resistance gene sequences were identified in microcosm soil following irrigation and only blaTEM was detected on effluent irrigated vegetable surfaces (spinach and beetroots). From the study, only blaTEM gene was identified across all samples; effluent wastewater, effluent-treated soil, and vegetables. The data suggests a possible dissemination and persistence of the beta-lactamase blaTEM gene from effluent wastewater into agricultural soil and vegetables. This study enhances our understanding of antibiotic resistance spread and highlights the importance of monitoring antibiotic resistance in agro-systems, which is critical for informing policies aimed at sustainable use of wastewater effluent in water-stressed countries.

Dynamics of antibiotic resistance and its association with bacterial community in a drinking water treatment plant and the residential area.

Drinking water treatment techniques are used globally in the context of water security and public health, yet they are not applicable to antibiotic resistance gene (ARG) contamination. Using high-throughput quantitative PCR, we analyzed the prevalence and diversity of ARGs and mobile genetic elements (MGEs) in water supplies. A total of 224 ARGs and MGEs were detected in all sampling sites. Absolute abundance and detected number of ARGs decreased significantly (P < 0.05) in sand filter water after drinking water treatment and increased thereafter at point-of-use (household tap water). Changes in the composition and diversity of the bacterial community were observed in water samples at different steps. A significant correlation (P < 0.001) between microbial communities and ARG profiles was observed, and variance in ARG profiles could be primarily attributed to community composition (11.9%), and interaction between community composition, environmental factors and MGEs (30.7%). A network analysis was performed, and the results showed eight bacterial phyla were significantly correlated with nine different classes of ARGs, suggesting the potential bacterial host for ARGs. This study suggested that although the absolute abundance of ARGs decreased after treatment of drinking water treatment plants (DWTPs), the rebounded of ARGs in the water distribution system should not be neglected.

Metagenomics and Molecular Analysis of Bacterial Diversity and Antibiotic Resistance Dynamics in Wastewater Effluent-Irrigated Soil and Vegetables in an Agricultural Microcosm Setting

Metagenomics and Molecular Analysis of Bacterial Diversity and Antibiotic Resistance Dynamics in Wastewater Effluent-Irrigated Soil and Vegetables in an Agricultural Microcosm Setting

Динамика антибиотикорезистентности у больных урологического профиля

Динамика антибиотикорезистентности у больных урологического профиля

Prevalence and transmission of antibiotic resistance and microbiota between humans and water environments

The transmission routes for antibiotic resistance genes (ARGs) and microbiota between humans and water environments is poorly characterized. Here, we used high-throughput qPCR analyses and 16S rRNA gene sequencing to examine the occurrence and abundance of antibiotic resistance genes and microbiota in both healthy humans and associated water environments from a Chinese village. Humans carried the most diverse assemblage of ARGs, with 234 different ARGs being detected. The total abundance of ARGs in feces, on skin, and in the effluent from domestic sewage treatment systems were approximately 23, 2, and 7 times higher than their abundance in river samples. In total, 53 ARGs and 28 bacteria genera that were present in human feces could also be found in the influent and effluent of rural sewage treatment systems, and also downstream of the effluent release point. We identified the bacterial taxa that showed a significant association with ARGs (P < 0.01, r > 0.8) by network analysis, supporting the idea that these bacteria could carry some ARGs and transfer between humans and the environment. Analysis of ARGs and microbiota in humans and in water environments helps to define the transmission routes and dynamics of antibiotic resistance within these environments. This study highlights human contribution to the load of ARGs into the environment and suggests means to prevent such dissemination.

Improvisation, therapeutic brokerage and antibiotic (mis)use in India: a qualitative interview study of Hyderabadi physicians and pharmacists

ABSTRACTAntimicrobial resistance (AMR) is widely reported to be a rapidly escalating global health threat. Investigations into the social dimensions of AMR have tended to focus on economically wealthier nations, even though economically poorer countries are a site of considerable and often increasing antibiotic (mis)use. Understanding the global and local dynamics of antibiotic resistance, we propose, requires critical sociological investigation at the nexus of economic development, structural constraints, cultural norms, and infection-management practice. Here, to begin to unpack these intersections, we draw on qualitative interviews with physicians and pharmacists in Hyderabad to explore their accounts of the social dynamics of AMR in India. In particular, we focus on their accounts of practices of improvisation and self-medication with antibiotics; the nexus of informal and formal pharmaceutical economies and the vested interests therein; and the everyday brokering of antibiotics. We posit that responses to AMR need to be deeply embedded in the specificities of everyday practice, local market forces, and regulatory (im)possibilities with attention paid to the locally prevailing cultural norms.

Current perspectives on the dynamics of antibiotic resistance in different reservoirs

Antibiotic resistance consists of a dynamic web. In this review, we describe the path by which different antibiotic residues and antibiotic resistance genes disseminate among relevant reservoirs (human, animal, and environmental settings), evaluating how these events contribute to the current scenario of antibiotic resistance. The relationship between the spread of resistance and the contribution of different genetic elements and events is revisited, exploring examples of the processes by which successful mobile resistance genes spread across different niches. The importance of classic and next generation molecular approaches, as well as action plans and policies which might aid in the fight against antibiotic resistance, are also reviewed.

The population genetics of evolutionary rescue.

Evolutionary rescue occurs when a population that is threatened with extinction by an environmental change adapts to the change sufficiently rapidly to survive. Here we extend the mathematical theory of evolutionary rescue. In particular, we model evolutionary rescue to a sudden environmental change when adaptation involves evolution at a single locus. We consider adaptation using either new mutations or alleles from the standing genetic variation that begin rare. We obtain several results: i) the total probability of evolutionary rescue from either new mutation or standing variation; ii) the conditions under which rescue is more likely to involve a new mutation versus an allele from the standing genetic variation; iii) a mathematical description of the U-shaped curve of total population size through time, conditional on rescue; and iv) the time until the average population size begins to rebound as well as the minimal expected population size experienced by a rescued population. Our analysis requires taking into account a subtle population-genetic effect (familiar from the theory of genetic hitchhiking) that involves “oversampling” of those lucky alleles that ultimately sweep to high frequency. Our results are relevant to conservation biology, experimental microbial evolution, and medicine (e.g., the dynamics of antibiotic resistance).

169 Spectrum and antibiotic resistance dynamics of uropathogens isolated from children and adolescents with community-acquired urinary tract infections in Russia: 2000 – 2011

169 Spectrum and antibiotic resistance dynamics of uropathogens isolated from children and adolescents with community-acquired urinary tract infections in Russia: 2000 – 2011

Models of Fungicide Resistance Dynamics

We describe two classes of models used for fungicide and antibiotic resistance dynamics. One class assumes that the density of the pathogen (or severity of the disease caused by the pathogen) has no feedback effects on the rate at which new infections arise. The second class does not make this assumption. A quantitative relationship between these two classes is derived. We then discuss the two sets of assumptions made in the literature about initial conditions: either both the fungicide-sensitive strain and the -resistant strain are initially at low density, or the sensitive strain is resident at nonlow density and the resistant strain is initially at low density. We show that models of fungicide resistance dynamics with and without density-dependent feedback give contrasting predictions on the effects of pathogen life-cycle parameters and the effects of the fungicide (dose, frequency, use of mixtures, spatial usage restrictions) on the evolution, invasion, and spread of fungicide resistance. We further show that the evaluation of a resistance management strategy requires a very precise definition of what constitutes a good strategy.

System for real-time monitoring of mutation-in-progress

There has been an increasing number of pathogens becoming resistant to multiple classes of antibiotics. The study on how mutation emerges is therefore crucial to promote further understanding in this area. Conventional methods for such studies involve the monitoring of growth by standard plate count and biomolecular sequencing. This is however tedious and not cost effective. The aim of this paper is thus to introduce a novel system that enables real-time monitoring of bacterial 'mutation-in-progress'. This system provides real-time data, thus enabling confirmatory and further work to be performed at the important points when mutation is initiated. The system integrates spectroscopic techniques as the detection system and various supporting systems, such as a nutrient replenishing system, a pH control system and a waste system to allow for extended monitoring. In this paper, the feasibility of monitoring the emergence of ciprofloxacin resistance in Staphylococcus aureus was demonstrated as an initial example. The integrated system was found to require significantly less material resource and manpower compared with conventional techniques. The novel system to monitor bacterial mutation-in-progress is presented. The work reported herein demonstrates such a system to be effective and efficient in performing real-time monitoring of mutation-in-progress, especially in extended time frames for mutation into the weeks and months. With the successful optimization of this system, researchers can learn about the dynamics of antibiotic resistance and further understand how the mutation of bacteria occurs.

Animal and farm influences on the dynamics of antibiotic resistance in faecal Escherichia coli in young dairy calves

It is believed that the intensive use of antibiotics in the management of disease in pre-weaned calves contributes to high levels of antibiotic resistance in commensal and pathogenic bacteria. We described the temporal dynamics of antibiotic-susceptibility patterns seen in bovine enteric Escherichia coli in pre-weaned calves on dairy farms and dedicated calf-rearing facilities. Cohorts of 30 calves at each of six farms were sampled at 2-week intervals during the pre-weaning period. Faecal E. coli isolates were analyzed for antibiotic susceptibility to 12 antibiotics with the disk-diffusion method and grouped using cluster analysis of inhibition-zone patterns. The influences of calf age, farm-type, and individual-calf antibiotic therapy on the clusterings were assessed using stratified analyses and cumulative multinomial logistic regression using generalized estimating equation with antibiotic-resistance cluster as an ordinal-dependent variable. The model controlled for farm and cohort by a nested design and included a repeated measure on calf at each sampling occasion. E. coli from calves 2 weeks of age were more likely to be increasingly multiply resistant than E. coli from day-old calves (OR = 53.6), as were 4- and 6-week-old calves (OR = 29.8 and 16.4, respectively). E. coli from calves on dedicated calf-rearing facilities were more likely to be increasingly multiply resistant than E. coli from dairy-reared calves (OR = 2.4). E. coli from calves treated with antibiotics within 5 days prior to sampling were also more likely to be increasingly multiply resistant than E. coli from calves not exposed to individual antibiotic therapy (OR = 2.0).