Enabling technologies for high performance mass spectrometry applications

高性能质谱应用的支持技术

基本信息

  • 批准号:
    RGPIN-2020-06170
  • 负责人:
  • 金额:
    $ 3.5万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2022
  • 资助国家:
    加拿大
  • 起止时间:
    2022-01-01 至 2023-12-31
  • 项目状态:
    已结题

项目摘要

Mass spectrometry (MS) has become the most preferred analytical tool because of its superior sensitivity and resolution, as well as the structural information it provides. Of the currently available MS methods, liquid and gas chromatography (LC and GC) coupled with MS have been the most widely used. However, LC/GC-MS in many cases suffer from long analysis time and low sensitivity, that increase the cost of analyses and prohibit the use of MS in many situations that could have helped by the MS technology, such as food, environmental and pharmaceutical analysis, as well as its application in clinical and point of care settings. The proposed research program aims to address some major issues that are impeding the application of MS methods and make some of the currently time-consuming methods high throughput, and improve the performance other MS methods. Applications of the new methods for the study of protein structure and structure dynamics are proposed. Sample extraction and sample enrichment often determine the quality of the analytical methods and their successful implementation. We will explore the use of new solvent systems such as deep eutectic solvents with mechanochemical method for solute specific extraction and enrichment. New liquid and solid extraction methods will be developed for ambient ionization mass spectrometry (AIMS) detection to speed up the analytical process while maintaining sensitivity and specificity. We will focus on one of the AIMS technologies called direct analysis in real time mass spectrometry (DART-MS). The combination of the extraction systems with AIMS will allow us to analyze environmental and biological samples in much shorter times than the currently used LC-MS methods. Physicochemical properties of the solvents and the solids, and their interaction with the analytes will be studied, as well as the effect of these properties on the ionization and detection efficiency of AIMS. For more complex systems a separation step must be added before the analytes are introduced into the MS. We will continue to develop novel methods to use capillary electrophoresis mass spectrometry (CEMS). Of particular interest is our efforts in capillary isoelectric focusing (cIEF) MS. We have demonstrated that this method is feasible, and our next step is to explore the possibility of combining IEF with tandem mass spectrometry for the study of minute structural differences in protein isomers. CE-MS can be a powerful tool for the study of protein structural dynamics and conformation changes in solution in their native states. We will develop new method to monitor the hydrogen-deuterium exchange (HDX) to characterize the part of the protein molecules that are exposed to the solution, and the parts of that are protected by their tertiary structures, as well as their conformational changes and disulfide bonds scramble in different kind of stress conditions.
质谱(MS)由于其优越的灵敏度和分辨率以及它提供的结构信息而成为最受欢迎的分析工具。在现有的质谱分析方法中,液相和气相色谱(LC和GC)联用质谱法是应用最广泛的方法。然而,LC/GC-MS在许多情况下存在分析时间长和灵敏度低的问题,这增加了分析成本,并禁止在许多情况下使用MS技术,例如食品,环境和药物分析,以及它在临床和护理点环境中的应用。本课题旨在解决目前阻碍质谱方法应用的一些主要问题,使目前一些耗时的方法具有高通量,并提高其他质谱方法的性能。提出了新方法在蛋白质结构和结构动力学研究中的应用。样品的提取和富集往往决定了分析方法的质量及其成功实施。我们将探索利用机械化学方法的新型溶剂体系如深共晶溶剂进行溶质特异性萃取和富集。新的液体和固体萃取方法将被开发用于环境电离质谱(AIMS)检测,以加快分析过程,同时保持灵敏度和特异性。我们将重点介绍AIMS的一项技术,称为实时质谱直接分析(DART-MS)。萃取系统与AIMS的结合将使我们能够在比目前使用的LC-MS方法更短的时间内分析环境和生物样品。将研究溶剂和固体的物理化学性质及其与分析物的相互作用,以及这些性质对AIMS电离和检测效率的影响。对于更复杂的系统,必须在分析物引入质谱之前添加一个分离步骤。我们将继续开发新的方法来使用毛细管电泳质谱(CEMS)。我们特别感兴趣的是我们在毛细管等电聚焦(cIEF) ms方面的努力。我们已经证明了这种方法是可行的,我们的下一步是探索将IEF与串联质谱相结合的可能性,以研究蛋白质异构体的微小结构差异。CE-MS是研究蛋白质结构动力学和天然状态下溶液中构象变化的有力工具。我们将开发新的方法来监测氢-氘交换(HDX),以表征蛋白质分子暴露在溶液中的部分,以及被其三级结构保护的部分,以及它们的构象变化和二硫键在不同压力条件下的争夺。

项目成果

期刊论文数量(0)
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会议论文数量(0)
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Chen, David其他文献

Perceptions of Person-Centered Care Following Spinal Cord Injury
Open Data: Implications on Privacy in Healthcare Research.
Cytokines and acute heart failure.
  • DOI:
    10.1097/01.ccm.0000297160.48694.90
  • 发表时间:
    2008-01-01
  • 期刊:
  • 影响因子:
    8.8
  • 作者:
    Chen, David;Assad-Kottner, Christian;Torre-Amione, Guillermo
  • 通讯作者:
    Torre-Amione, Guillermo
Improved Interpretability of Machine Learning Model Using Unsupervised Clustering: Predicting Time to First Treatment in Chronic Lymphocytic Leukemia
  • DOI:
    10.1200/cci.18.00137
  • 发表时间:
    2019-05-21
  • 期刊:
  • 影响因子:
    4.2
  • 作者:
    Chen, David;Goya, Gaurav;Ngufor, Che G.
  • 通讯作者:
    Ngufor, Che G.
Safety of neoadjuvant chemotherapy in patients with muscle-invasive bladder cancer and malignant ureteric obstruction.
  • DOI:
    10.1111/bju.15410
  • 发表时间:
    2022-03
  • 期刊:
  • 影响因子:
    4.5
  • 作者:
    Strother, Marshall C.;Kutikov, Alexander;Epstein, Matthew;Bochner, Emily;Deng, Mengying;Handorf, Elizabeth;Lewis, Bianca;Ghatalia, Pooja;Greenberg, Richard E.;Chen, David;Viterbo, Rosalia;Anari, Fern;Smaldone, Marc C.;Zibelman, Matthew R.;Uzzo, Robert G.;Plimack, Elizabeth R.;Geynisman, Daniel M.
  • 通讯作者:
    Geynisman, Daniel M.

Chen, David的其他文献

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{{ truncateString('Chen, David', 18)}}的其他基金

Enabling technologies for high performance mass spectrometry applications
高性能质谱应用的支持技术
  • 批准号:
    RGPIN-2020-06170
  • 财政年份:
    2021
  • 资助金额:
    $ 3.5万
  • 项目类别:
    Discovery Grants Program - Individual
Enabling technologies for high performance mass spectrometry applications
高性能质谱应用的支持技术
  • 批准号:
    RGPIN-2020-06170
  • 财政年份:
    2020
  • 资助金额:
    $ 3.5万
  • 项目类别:
    Discovery Grants Program - Individual
Testing for concerted or independent voltage sensor movement in ion channels
测试离子通道中一致或独立的电压传感器运动
  • 批准号:
    541140-2019
  • 财政年份:
    2019
  • 资助金额:
    $ 3.5万
  • 项目类别:
    University Undergraduate Student Research Awards
Chemical Separation and Detection Techniques and Their Wide Ranging Applications
化学分离和检测技术及其广泛应用
  • 批准号:
    RGPIN-2015-06286
  • 财政年份:
    2019
  • 资助金额:
    $ 3.5万
  • 项目类别:
    Discovery Grants Program - Individual
Measurement of streaming potential for determination of capillary surface characteristics
测量流动电位以确定毛细管表面特性
  • 批准号:
    531138-2018
  • 财政年份:
    2018
  • 资助金额:
    $ 3.5万
  • 项目类别:
    Engage Grants Program
Chemical Separation and Detection Techniques and Their Wide Ranging Applications
化学分离和检测技术及其广泛应用
  • 批准号:
    RGPIN-2015-06286
  • 财政年份:
    2018
  • 资助金额:
    $ 3.5万
  • 项目类别:
    Discovery Grants Program - Individual
Chemical Separation and Detection Techniques and Their Wide Ranging Applications
化学分离和检测技术及其广泛应用
  • 批准号:
    RGPIN-2015-06286
  • 财政年份:
    2017
  • 资助金额:
    $ 3.5万
  • 项目类别:
    Discovery Grants Program - Individual
Chemical Separation and Detection Techniques and Their Wide Ranging Applications
化学分离和检测技术及其广泛应用
  • 批准号:
    RGPIN-2015-06286
  • 财政年份:
    2016
  • 资助金额:
    $ 3.5万
  • 项目类别:
    Discovery Grants Program - Individual
Molecular imprint polymer for urine biomarker isolation
用于尿液生物标志物分离的分子印迹聚合物
  • 批准号:
    484791-2015
  • 财政年份:
    2015
  • 资助金额:
    $ 3.5万
  • 项目类别:
    Engage Grants Program
Chemical Separation and Detection Techniques and Their Wide Ranging Applications
化学分离和检测技术及其广泛应用
  • 批准号:
    RGPIN-2015-06286
  • 财政年份:
    2015
  • 资助金额:
    $ 3.5万
  • 项目类别:
    Discovery Grants Program - Individual

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