DNA Aptamers for the Recovery and Identification Cryptosporidium parvum oocysts in Liquid Municipal Wastes

用于回收和鉴定液体城市废物中小隐孢子虫卵囊的 DNA 适体

基本信息

  • 批准号:
    530924-2018
  • 负责人:
  • 金额:
    $ 1.82万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Engage Grants Program
  • 财政年份:
    2018
  • 资助国家:
    加拿大
  • 起止时间:
    2018-01-01 至 2019-12-31
  • 项目状态:
    已结题

项目摘要

Cryptosporidium parvum is an intestinal protozoan parasite that can cause severe diarrhea in humans and many**animals, release large numbers of oocysts (eggs) in the feces of those infected which then can contaminate soil,**liquid and solid wastes. Cryptosporidium has caused many outbreaks of gastroenteritis. In many cases**wastewater effluent is discharged into source waters used for drinking water, recreation and agriculture. Due to**the human health risk, it has been recommended by Health Canada to routinely monitor drinking water treatment**plant source waters for oocyst concentrations. However, routine methods for concentration and detection of the**oocysts with immunofluorescence microscopy have low or variable recovery rates, are time consuming and**require highly skilled lab personnel. This research will help in the development of a sensitive aptamer-based**electrochemical biosensor method which can detect and quantify C. parvum in samples of liquid municipal wastes**and can help to mitigate pathogen discharges into the water environment.
隐孢子虫是一种肠道原生动物寄生虫,可引起人类和许多 ** 动物严重腹泻,在感染者的粪便中释放大量卵囊(卵),然后污染土壤,** 液体和固体废物。隐孢子虫引起了许多胃肠炎的爆发。在许多情况下,** 废水排放到饮用水、娱乐和农业用水的源沃茨。由于 ** 对人类健康的风险,加拿大卫生部建议定期监测饮用水处理 ** 厂水源沃茨中的卵囊浓度。然而,常规的浓缩和免疫荧光显微镜检测卵囊的方法回收率低或可变,耗时且需要高度熟练的实验室人员。本研究将有助于开发一种灵敏的基于适体的电化学生物传感器方法,用于检测和定量C。在城市液体废物样本中,** 可以减少病原体排放到水环境中。

项目成果

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Ormeci, Banu其他文献

Eliminating false positives in a qPCR assay for the detection of the uidA gene in Escherichia coli
  • DOI:
    10.2166/wh.2013.201
  • 发表时间:
    2013-01-01
  • 期刊:
  • 影响因子:
    2.3
  • 作者:
    Kibbee, Richard;Linklater, Natalie;Ormeci, Banu
  • 通讯作者:
    Ormeci, Banu
Wastewater Surveillance of SARS-CoV-2 at a Canadian University Campus and the Impact of Wastewater Characteristics on Viral RNA Detection
  • DOI:
    10.1021/acsestwater.2c00060
  • 发表时间:
    2022-05-12
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Bitter, Lena Carolin;Kibbee, Richard;Ormeci, Banu
  • 通讯作者:
    Ormeci, Banu
Development of a sensitive and false-positive free PMA-qPCR viability assay to quantify VBNC Escherichia coli and evaluate disinfection performance in wastewater effluent
  • DOI:
    10.1016/j.mimet.2016.12.004
  • 发表时间:
    2017-01-01
  • 期刊:
  • 影响因子:
    2.2
  • 作者:
    Kibbee, Richard J.;Ormeci, Banu
  • 通讯作者:
    Ormeci, Banu
Monitoring of Cyanobacteria in Water Using Spectrophotometry and First Derivative of Absorbance
  • DOI:
    10.3390/w12010124
  • 发表时间:
    2020-01-01
  • 期刊:
  • 影响因子:
    3.4
  • 作者:
    Agberien, Adogbeji Valentine;Ormeci, Banu
  • 通讯作者:
    Ormeci, Banu
Stabilisation and dewatering of primary sludge using ferrate(VI) pre-treatment followed by freeze-thaw in simulated drainage beds
  • DOI:
    10.1016/j.jenvman.2017.10.065
  • 发表时间:
    2018-06-15
  • 期刊:
  • 影响因子:
    8.7
  • 作者:
    Diak, James;Ormeci, Banu
  • 通讯作者:
    Ormeci, Banu

Ormeci, Banu的其他文献

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{{ truncateString('Ormeci, Banu', 18)}}的其他基金

Optimization of sludge conditioning and dewatering using sludge network strength and residual polymer concentration
利用污泥网络强度和残留聚合物浓度优化污泥调理和脱水
  • 批准号:
    RGPIN-2016-06246
  • 财政年份:
    2022
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Optimization of sludge conditioning and dewatering using sludge network strength and residual polymer concentration
利用污泥网络强度和残留聚合物浓度优化污泥调理和脱水
  • 批准号:
    RGPIN-2016-06246
  • 财政年份:
    2021
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Optimization of sludge conditioning and dewatering using sludge network strength and residual polymer concentration
利用污泥网络强度和残留聚合物浓度优化污泥调理和脱水
  • 批准号:
    RGPIN-2016-06246
  • 财政年份:
    2020
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Optimization of sludge conditioning and dewatering using sludge network strength and residual polymer concentration
利用污泥网络强度和残留聚合物浓度优化污泥调理和脱水
  • 批准号:
    RGPIN-2016-06246
  • 财政年份:
    2019
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Optimization of sludge conditioning and dewatering using sludge network strength and residual polymer concentration
利用污泥网络强度和残留聚合物浓度优化污泥调理和脱水
  • 批准号:
    RGPIN-2016-06246
  • 财政年份:
    2018
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Optimization of sludge conditioning and dewatering using sludge network strength and residual polymer concentration
利用污泥网络强度和残留聚合物浓度优化污泥调理和脱水
  • 批准号:
    RGPIN-2016-06246
  • 财政年份:
    2017
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Wastewater Treatment Engineering
废水处理工程
  • 批准号:
    1000226345-2011
  • 财政年份:
    2016
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Canada Research Chairs
Optimization of sludge conditioning and dewatering using sludge network strength and residual polymer concentration
利用污泥网络强度和残留聚合物浓度优化污泥调理和脱水
  • 批准号:
    RGPIN-2016-06246
  • 财政年份:
    2016
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Discovery Grants Program - Individual
Wastewater Treatment Engineering
废水处理工程
  • 批准号:
    1226345-2011
  • 财政年份:
    2015
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Canada Research Chairs
ANR - Next generation sludge treatment: optimization of treatment performance through online monitoring of holistic sludge properties
ANR - 下一代污泥处理:通过在线监测污泥整体特性优化处理性能
  • 批准号:
    463663-2014
  • 财政年份:
    2014
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Strategic Projects - Group

相似国自然基金

Aptamers新型分子探针的构建及对乳腺癌超早期MR诊断的实验研究
  • 批准号:
    81101091
  • 批准年份:
    2011
  • 资助金额:
    21.0 万元
  • 项目类别:
    青年科学基金项目

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肽适体与细胞朊病毒蛋白相互作用用于治疗神经退行性疾病
  • 批准号:
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Collaborative Research: NSF/MCB: Repurposing metabolite-responsive aptamers for real-time sensing and dynamic control of Cas6-mediated metabolon assembly
合作研究:NSF/MCB:重新利用代谢物响应适体,用于 Cas6 介导的代谢物组装的实时传感和动态控制
  • 批准号:
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Ultimate Two-Stage Selection of Nucleic Acid Aptamers as Novel Molecular Recognition Elements
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