AMRflows: antimicrobials and resistance from manufacturing flows to people: joined up experiments, mathematical modelling and risk analysis
AMRflows: antimicrobials and resistance from manufacturing flows to people: joined up experiments, mathematical modelling and risk analysis
批准号:
NE/T013222/1
负责人:
Jan-Ulrich Kreft
金额:
$100.48万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
未结题
起止时间:
2020 至 --
中文摘要
抗生素和其他药物从多个生产地点排放到河流中,其浓度高到足以选择抗生素耐药基因(ARGs)。这种抗生素混合物可能会选择新的耐药基因组合,这尤其令人担忧,因为这将进一步限制抗生素治疗选择。此外,处理工业废水或生活污水和进入河流的原污水的细菌会混合,促进质粒上携带的抗性基因的水平基因转移(HGT)。然而,抗生素在下游运输的过程中会被稀释,有些会迅速降解,耐药细菌可能无法存活,所以问题是耐药性被选择了多长时间,它能存活多久?耐药性是否会在其他细菌消失之前传播给它们?耐药细菌的传播距离有多远,人类或牲畜的暴露程度如何?为了提出这些问题,评估缓解战略并制定基于证据的全球环境标准,我们将开展一项独特的实验和数学建模方案,包括以下内容:(1)测量抗生素和重金属的浓度、水化学、水位和流速、水沉积物交换、抗生素抗性基因和抗生素抗性细菌的丰度和多样性。(2)对抗性基因在实验反应器中的传播进行量化。(3)在实际可控条件下,在实验规模反应器中对河流样本进行选择研究。(4)研究组织培养和斑马鱼实验室模型耐药菌感染风险及治疗所需抗生素剂量。(5)在小尺度水样上建立并测试抗菌素耐药性(AMR)动态的数学模型,包括抗生素的降解、敏感和耐药细菌的生长和死亡、耐药性选择与抗生素浓度的函数关系、耐药性的HGT。(6)建立河网水流模型并进行试验;这将是大规模的河流。(7)将小尺度AMR动力学和大尺度运移模型结合成一个模型,该模型可以计算化合物的稀释,并跟踪化学物质和细菌在河水、沉积物和洪泛平原中存在的时间,以及它们向下游种群和生态系统传播的程度。联合模型可以在付诸实践之前评估诸如对抗生素生产废物和生活污水进行分开处理等干预措施是否能有效降低耐药性水平。环境AMR路径将跨越两个河流系统进行研究。Musi(海得拉巴)比Adyar(金奈)受抗生素污染更严重。两者都被污水污染。它们的污染通过灌溉、饮用水生产和精神净化流向人类。这些河流有低流量阶段,工业废物和污水集中,细菌传播有限,季风季节流量大,耐药细菌淹没社区。(8)根据组合模型的预测结果和(4)中的实验研究及其他信息,分析人类健康风险。风险分析将包括这些风险的不确定程度,并将有助于制定国际环境标准。这将是改善人类、动物和环境健康的两个主要成果,特别是(i)在污染程度不同的河流系统中就地条件下耐药性(co)选择和转移的定量证据,以及(ii)一个真正新颖的综合抗微生物药物耐药性动力学和运输建模框架,可在全球范围内用作跟踪抗微生物药物耐药性流动的工具。
英文摘要
Antibiotics and other pharmaceuticals are released into rivers from multiple manufacturing sites at concentrations high enough to select for antibiotic resistance genes (ARGs). Such mixtures of antibiotics may select for new combinations of resistance genes, which is particularly concerning as this will further limit antibiotic treatment options. In addition, bacteria from treating manufacturing waste or domestic sewage and raw sewage entering rivers will mingle, facilitating horizontal gene transfer (HGT) of resistance genes carried on plasmids. However, the antibiotics will be diluted while being transported downstream, and some will be quickly degraded, and resistant bacteria may not survive so the question is how long is resistance selected and how long does it survive? Is resistance transmitted to other bacteria before they are lost? How far are resistant bacteria transport and what is the exposure of humans or livestock?In order to ask these questions, evaluate mitigation strategies and develop evidence-based global environmental standards, we will pursue a unique combined experimental and mathematical modelling programme including the following streams:(1) Measure concentrations of antibiotics and heavy metals, water chemistry, water levels and flow rates, water sediment exchange, abundance and diversity of antibiotic resistance genes and antibiotic-resistant bacteria. (2) Quantify transmission of resistance genes in bench-scale reactors. (3) Study selection in the river samples in bench-scale reactors under realistic, controlled conditions. (4) Study the risk of infection by resistant bacteria in tissue culture and Zebrafish laboratory models and the antibiotic dose required for treatment. (5) Build and test a mathematical model of antimicrobial resistance (AMR) dynamics on the small scale of a water sample, including degradation of antibiotics, growth and death of sensitive and resistant bacteria, selection of resistance as a function of antibiotic concentration, HGT of resistance. (6) Build and test a model of water flow for the river network; this will be on the large scale of rivers. (7) Combine the small-scale AMR dynamics and large-scale transport models into a model that can calculate the dilution of the compounds and track how long the chemicals and bacteria have been in the river water, sediments and floodplains and how far they spread to downstream populations and ecosystems.The combined model can evaluate whether interventions such as separate treatment of antibiotic manufacturing waste and domestic sewage would be effective in reducing resistance levels before putting this into practice. The environmental AMR pathways will be examined across two river systems. The Musi (Hyderabad) is more polluted with antibiotics than the Adyar (Chennai). Both are polluted by sewage. Their pollution flows to people via irrigation, drinking water production and spiritual cleansing. These rivers have phases of low flow with concentrated industrial waste and sewage and limited bacterial spread and high flows in the monsoon season, flooding communities with resistant bacteria.(8) Analyse the human health risks based on the predictions of the combined model and the experimental study in (4) and other information. The risk analysis will include the level of uncertainty in those risks and will contribute to the development of international environmental standards.These will be the two main outcomes to improve human, animal and environmental health, specifically (i) quantitative evidence for resistance (co)selection and transfer under in situ conditions in a more and less polluted river system and (ii) a truly novel combined AMR dynamics and transport modelling framework that can be used globally as a tool to track AMRflows.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
EMBRACE-WATERS statement: Recommendations for reporting of studies on antimicrobial resistance in wastewater and related aquatic environments.
Abrace-Waters声明:报告废水和相关水生环境中抗菌素耐药性研究的建议。
DOI:
10.1016/j.onehlt.2021.100339
发表时间:
2021-12
期刊:
One health (Amsterdam, Netherlands)
影响因子:
--
作者:
[Hassoun-Kheir N, Stabholz Y, Kreft JU, de la Cruz R, Dechesne A, Smets BF, Romalde JL, Lema A, Balboa S, García-Riestra C, Torres-Sangiao E, Neuberger A, Graham D, Quintela-Baluja M, Stekel DJ, Graham J, Pruden A, Nesme J, Sørensen SJ, Hough R, Paul M]
通讯作者:
Paul M
DOI:
10.1101/2020.09.14.295766
发表时间:
2020-09
期刊:
bioRxiv
影响因子:
--
作者:
[Sankalp Arya;Alexander Williams;S. Reina;C. Knapp;Jan-Ulrich Kreft;J. Hobman;D. Stekel]
通讯作者:
Sankalp Arya;Alexander Williams;S. Reina;C. Knapp;Jan-Ulrich Kreft;J. Hobman;D. Stekel
Exploring the impacts of physicochemical characteristics and heavy metals fractions on bacterial communities in four rivers.
探索理化特征和重金属组分对四条河流细菌群落的影响。
DOI:
10.1016/j.jenvman.2022.116453
发表时间:
2023
期刊:
Journal of environmental management
影响因子:
8.7
作者:
[Gupta S]
通讯作者:
Gupta S
eGUT: a Tool for Predictive Computer Simulation of the Gut Microbiota and Host Interactions
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批准号:NC/K000683/1
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项目类别:Research Grant
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资助金额:$33.04万
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财政年份:2013
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负责人:Jan-Ulrich Kreft
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依托单位:
海外基金