An omics-based framework for assessing the health risk of antimicrobial resistance genes.
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ABSTRACT:
SUBMITTER: Zhang AN
PROVIDER: S-EPMC8346589 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:It has been widely recognised that a significant proportion of the world's population suffer inequalities in accessing high quality healthcare and wider services. Within healthcare, antimicrobial resistance (AMR) is a global threat to public health affecting all healthcare systems and growing at an alarming pace. To ensure that national AMR campaigns developed by Public Health England are inclusive of all populations within the target audience a health equity assessment tool (HEAT) was used. The project leads for each campaign completed the HEAT independently with a follow up meeting with the study team to discuss and clarify the responses. A trend analysis was carried out with common themes being used to provide recommendations. The campaigns have demonstrated equality and diversity based on the requirements of the Equality Act 2010, particularly age, sex, and race protected characteristics. Some notable results include the translation of website materials in over 30 languages and reaching individuals in 122 countries. It was however noted that several of the protected characteristics were not applicable. The continuous development of resources with collaboration from a variety of diverse user groups would be advantageous towards aiding future campaign reach. The use of the HEAT has demonstrated the ease and cost-effective way to assess any health inequalities and would be a useful addition to antimicrobial stewardship and public health campaigns.
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Project description:Antimicrobial resistance (AMR) has emerged as one of the most urgent global threats to public health. Accurate detection of AMR phenotypes is critical for reducing the spread of AMR strains. Here, we developed PARMAP (Prediction of Antimicrobial Resistance by MAPping genetic alterations in pan-genome) to predict AMR phenotypes and to identify AMR-associated genetic alterations based on the pan-genome of bacteria by utilizing machine learning algorithms. When we applied PARMAP to 1,597 Neisseria gonorrhoeae strains, it successfully predicted their AMR phenotypes based on a pan-genome analysis. Furthermore, it identified 328 genetic alterations in 23 known AMR genes and discovered many new AMR-associated genetic alterations in ciprofloxacin-resistant N. gonorrhoeae, and it clearly indicated the genetic heterogeneity of AMR genes in different subtypes of resistant N. gonorrhoeae. Additionally, PARMAP performed well in predicting the AMR phenotypes of Mycobacterium tuberculosis and Escherichia coli, indicating the robustness of the PARMAP framework. In conclusion, PARMAP not only precisely predicts the AMR of a population of strains of a given species but also uses whole-genome sequencing data to prioritize candidate AMR-associated genetic alterations based on their likelihood of contributing to AMR. Thus, we believe that PARMAP will accelerate investigations into AMR mechanisms in other human pathogens.
| S-EPMC7642336 | biostudies-literature
Project description:Over the past century, the environment of the Gulf of Mexico has been significantly altered and impaired by extensive human activities. A national commitment to restore the Gulf was finally initiated in response to the unprecedented Deepwater Horizon oil spill in 2010. Consequently, there is a critical need for an assessment framework and associated set of indicators that can characterize the health and sustainability of an ecosystem having the scale and complexity of the Gulf. The assessment framework presented here was developed as an integration of previous ecological risk- and environmental management-based frameworks for assessing ecosystem health. It was designed to identify the natural and anthropogenic drivers, pressures, and stressors impinging on ecosystems and ecosystem services, and the ecological conditions that result, manifested as effects on valued ecosystem components. Four types of societal and ecological responses are identified: reduction of pressures and stressors, remediation of existing stressors, active ecosystem restoration, and natural ecological recovery. From this conceptual framework are derived the specific indicators to characterize ecological condition and progress toward achieving defined ecological health and sustainability goals. Additionally, the framework incorporates a hierarchical structure to communicate results to a diversity of audiences, from research scientists to environmental managers and decision makers, with the level of detail or aggregation appropriate for each targeted audience. Two proof-of-concept studies were conducted to test this integrated assessment and decision framework, a prototype Texas Coastal Ecosystems Report Card, and a pilot study on enhancing rookery islands in the Mission-Aransas Reserve, Texas, USA. This Drivers-Pressures-Stressors-Condition-Responses (DPSCR4 ) conceptual framework is a comprehensive conceptual model of the coupled human-ecological system. Much like its predecessor, the ecological risk assessment framework, the DPSCR4 conceptual framework can be tailored to different scales of complexity, different ecosystem types with different stress regimes, and different environmental settings. Integr Environ Assess Manag 2019;15:544-564. © 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
| S-EPMC6852332 | biostudies-literature
Project description:Antimicrobial resistance (AMR) is a global health crisis that affects all life on Earth. In 2015, the World Health Organization developed guidance to combat AMR in accordance with a One Health framework considering human, animal, and environment sectors of planetary health. This study reviewed global guidance and 25 National Action Plans to evaluate thematic priorities in One Health AMR approaches using a novel framework that additionally facilitated the identification of water-related stewardship gaps, as water resources are recognized as the primary environmental AMR reservoir and dissemination pathway. This review found that global and national stewardship primarily focuses on mitigating antibiotic use in the human and animal sectors, overlooking environmental drivers, particularly diverse environmental waters. The findings of this study highlight the need to broaden the scope of water-related AMR concerns beyond water, sanitation, and hygiene (WASH) infrastructure for water supply and wastewater treatment, and account for environmental waters in AMR development and dissemination, particularly in low-income countries where half a billion people rely on environmental waters to meet daily needs. Equitably accounting for water environments, supplies, and waste in AMR prevention, mitigation, surveillance, and innovation can significantly enhance the integration of environmental objectives in One Health AMR stewardship.
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Project description:Geoengineering by stratospheric aerosol injection has been proposed as a policy response to warming from human emissions of greenhouse gases, but it may produce unequal regional impacts. We present a simple, intuitive risk-based framework for classifying these impacts according to whether geoengineering increases or decreases the risk of substantial climate change, with further classification by the level of existing risk from climate change from increasing carbon dioxide concentrations. This framework is applied to two climate model simulations of geoengineering counterbalancing the surface warming produced by a quadrupling of carbon dioxide concentrations, with one using a layer of sulphate aerosol in the lower stratosphere, and the other a reduction in total solar irradiance. The solar dimming model simulation shows less regional inequality of impacts compared with the aerosol geoengineering simulation. In the solar dimming simulation, 10% of the Earth's surface area, containing 10% of its population and 11% of its gross domestic product, experiences greater risk of substantial precipitation changes under geoengineering than under enhanced carbon dioxide concentrations. In the aerosol geoengineering simulation the increased risk of substantial precipitation change is experienced by 42% of Earth's surface area, containing 36% of its population and 60% of its gross domestic product.
| S-EPMC3923064 | biostudies-literature
Project description:Antimicrobial resistance in Yersinia pestis is rare, yet constitutes a significant international public health and biodefense threat. In 1995, the first multidrug resistant (MDR) isolate of Y. pestis (strain IP275) was identified, and was shown to contain a self-transmissible plasmid (pIP1202) that conferred resistance to many of the antimicrobials recommended for plague treatment and prophylaxis. Comparative analysis of the DNA sequence of Y. pestis plasmid pIP1202 revealed a near identical IncA/C plasmid backbone that is shared by MDR plasmids isolated from Salmonella enterica serotype Newport SL254 and the fish pathogen Yersinia ruckeri YR71. The high degree of sequence identity and gene synteny between the plasmid backbones suggests recent acquisition of these plasmids from a common ancestor. In addition, the Y. pestis pIP1202-like plasmid backbone was detected in numerous MDR enterobacterial pathogens isolated from retail meat samples collected between 2002 and 2005 in the United States. Plasmid-positive strains were isolated from beef, chicken, turkey and pork, and were found in samples from the following states: California, Colorado, Connecticut, Georgia, Maryland, Minnesota, New Mexico, New York and Oregon. Our studies reveal that this common plasmid backbone is broadly disseminated among MDR zoonotic pathogens associated with agriculture. This reservoir of mobile resistance determinants has the potential to disseminate to Y. pestis and other human and zoonotic bacterial pathogens and therefore represents a significant public health concern.
| S-EPMC1819562 | biostudies-literature
Project description:MotivationOmics Pipe (http://sulab.scripps.edu/omicspipe) is a computational framework that automates multi-omics data analysis pipelines on high performance compute clusters and in the cloud. It supports best practice published pipelines for RNA-seq, miRNA-seq, Exome-seq, Whole-Genome sequencing, ChIP-seq analyses and automatic processing of data from The Cancer Genome Atlas (TCGA). Omics Pipe provides researchers with a tool for reproducible, open source and extensible next generation sequencing analysis. The goal of Omics Pipe is to democratize next-generation sequencing analysis by dramatically increasing the accessibility and reproducibility of best practice computational pipelines, which will enable researchers to generate biologically meaningful and interpretable results.ResultsUsing Omics Pipe, we analyzed 100 TCGA breast invasive carcinoma paired tumor-normal datasets based on the latest UCSC hg19 RefSeq annotation. Omics Pipe automatically downloaded and processed the desired TCGA samples on a high throughput compute cluster to produce a results report for each sample. We aggregated the individual sample results and compared them to the analysis in the original publications. This comparison revealed high overlap between the analyses, as well as novel findings due to the use of updated annotations and methods.Availability and implementationSource code for Omics Pipe is freely available on the web (https://bitbucket.org/sulab/omics_pipe). Omics Pipe is distributed as a standalone Python package for installation (https://pypi.python.org/pypi/omics_pipe) and as an Amazon Machine Image in Amazon Web Services Elastic Compute Cloud that contains all necessary third-party software dependencies and databases (https://pythonhosted.org/omics_pipe/AWS_installation.html).
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Project description:This Southeast Asia-Europe research project will use a One Health approach to identify the major parameters responsible for the presence of animal-associated antimicrobial resistant bacteria in animal production facilities in Thailand and the risk of their transmission from animals to humans. We will focus on traditional, small, extensive pig and poultry farms where information on antibiotic use is scarce and animals live in close contact with humans. This cross-sectional study will be based on the epidemiological analysis of the antimicrobial resistance (AMR) present in fecal samples from animals and humans. Extended spectrum beta-lactamase producing Enterobacteriaceae (ESBL-E) and Enterobacteriaceae resistant to colistin will be actively searched in the feces of farm animals (pigs and poultry), small wild rodents and farmers. Phenotypic (selective plating) and genotypic (multilocus seuquence typing and sequencing) methods will be used for the detection of AMR, the identification of antibiotic resistance genes (ARGs) and the characterization of strains carrying resistance genes. Questionnaires will be administered to investigate the effects of antibiotic use, farm characteristics and biosecurity measures on the occurrence of AMR in animals. Subsequently, the fecal carriage of AMR and ARGs in farmers will be compared to a control population with no occupational contacts with animals, thus enabling an estimation of the risk of transmission of AMR/ARGs from animals to farmers.
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Project description:Genome-wide association studies (GWAS) have identified more than 100 schizophrenia (SCZ)-associated loci, but using these findings to illuminate disease biology remains a challenge. Here we present integrative risk gene selector (iRIGS), a Bayesian framework that integrates multi-omics data and gene networks to infer risk genes in GWAS loci. By applying iRIGS to SCZ GWAS data, we predicted a set of high-confidence risk genes, most of which are not the nearest genes to the GWAS index variants. High-confidence risk genes account for a significantly enriched heritability, as estimated by stratified linkage disequilibrium score regression. Moreover, high-confidence risk genes are predominantly expressed in brain tissues, especially prenatally, and are enriched for targets of approved drugs, suggesting opportunities to reposition existing drugs for SCZ. Thus, iRIGS can leverage accumulating functional genomics and GWAS data to advance our understanding of SCZ etiology and potential therapeutics.
| S-EPMC6646046 | biostudies-literature
Project description:It is now widely acknowledged that surveillance of antimicrobial resistance (AMR) must adopt a "One Health" (OH) approach to successfully address the significant threats this global public health issue poses to humans, animals, and the environment. While many protocols exist for the evaluation of surveillance, the specific aspect of the integration of a OH approach into surveillance systems for AMR and antimicrobial Use (AMU), suffers from a lack of common and accepted guidelines and metrics for its monitoring and evaluation functions. This article presents a conceptual framework to evaluate the integration of OH in surveillance systems for AMR and AMU, named the Integrated Surveillance System Evaluation framework (ISSE framework). The ISSE framework aims to assist stakeholders and researchers who design an overall evaluation plan to select the relevant evaluation questions and tools. The framework was developed in partnership with the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS). It consists of five evaluation components, which consider the capacity of the system to: [1] integrate a OH approach, [2] produce OH information and expertise, [3] generate actionable knowledge, [4] influence decision-making, and [5] positively impact outcomes. For each component, a set of evaluation questions is defined, and links to other available evaluation tools are shown. The ISSE framework helps evaluators to systematically assess the different OH aspects of a surveillance system, to gain comprehensive information on the performance and value of these integrated efforts, and to use the evaluation results to refine and improve the surveillance of AMR and AMU globally.
| S-EPMC8024545 | biostudies-literature