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:2020
- 资助国家:加拿大
- 起止时间:2020-01-01 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
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)已成为最优选的分析工具,因为它具有出色的灵敏度和分辨率及其提供的结构信息。在当前可用的MS方法中,液态和气相色谱法(LC和GC)与MS相结合的方法最广泛。 但是,在许多情况下,LC/GC-MS遭受了长时间的分析时间和低灵敏度的困扰,这会增加分析的成本并禁止在许多情况下使用MS的使用,这些情况可能会受到MS技术的帮助,例如食品,环境和药品分析,以及其在临床和护理环境中的应用。 拟议的研究计划旨在解决一些阻碍MS方法应用的主要问题,并使一些当前耗时的方法高吞吐量,并提高性能其他MS方法。 提出了新方法用于研究蛋白质结构和结构动力学的应用。
样品提取和样品富集通常决定分析方法的质量及其成功实施。 我们将探索使用新溶剂系统的使用,例如使用机械化学方法的深色溶剂来溶解特定的提取和富集。 将开发新的液体和实心提取方法,用于环境电离质谱法(目标)检测,以加快分析过程,同时保持灵敏度和特异性。 我们将重点关注一种在实时质谱法(DART-MS)中称为直接分析的目标技术。与当前使用的LC-MS方法相比,提取系统与目标的组合将使我们能够在短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特性及其与分析物的相互作用,以及这些特性对目标电离和检测效率的影响。
对于更复杂的系统,必须在将分析物引入MS之前添加分离步骤。 我们将继续开发使用毛细管电泳质谱法(CEMS)的新型方法。 特别令人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可以成为研究蛋白质结构动力学和本地溶液中溶液变化的强大工具。 我们将开发新的方法来监测氢 - 偏见交换(HDX),以表征暴露于溶液的蛋白质分子的一部分,并且部分受到其第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类型的应力条件下争夺。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Chen, David其他文献
Learning to interpret natural language navigation instructions from observations
- DOI:
10.1609/aaai.v25i1.7974 - 发表时间:
2011-01-01 - 期刊:
- 影响因子:0
- 作者:
Chen, David;Mooney, Raymond - 通讯作者:
Mooney, Raymond
Tissue engineered autologous cartilage-bone grafts for temporomandibular joint regeneration
- DOI:
10.1126/scitranslmed.abb6683 - 发表时间:
2020-10-14 - 期刊:
- 影响因子:17.1
- 作者:
Chen, David;Wu, Josephine Y.;Vunjak-Novakovic, Gordana - 通讯作者:
Vunjak-Novakovic, Gordana
Splenosis in patient undergoing robotic assisted laparoscopic radical prostatectomy.
- DOI:
10.1016/j.eucr.2022.102251 - 发表时间:
2022-11 - 期刊:
- 影响因子:0.5
- 作者:
Sykes, Jennifer;Bell, Spencer;Bukavina, Laura;Kutikov, Alexander;Wei, Shuanzeng;Chen, David - 通讯作者:
Chen, David
Natural language processing for identification of hypertrophic cardiomyopathy patients from cardiac magnetic resonance reports.
- DOI:
10.1186/s12911-022-02017-y - 发表时间:
2022-10-18 - 期刊:
- 影响因子:3.5
- 作者:
Dewaswala, Nakeya;Chen, David;Bhopalwala, Huzefa;Kaggal, Vinod C.;Murphy, Sean P.;Bos, J. Martijn;Geske, Jeffrey B.;Gersh, Bernard J.;Ommen, Steve R.;Araoz, Philip A.;Ackerman, Michael J.;Arruda-Olson, Adelaide M. - 通讯作者:
Arruda-Olson, Adelaide M.
Residual enhanced visual vector as a compact signature for mobile visual search
- DOI:
10.1016/j.sigpro.2012.06.005 - 发表时间:
2013-08-01 - 期刊:
- 影响因子:4.4
- 作者:
Chen, David;Tsai, Sam;Girod, Bernd - 通讯作者:
Girod, Bernd
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:2022
- 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:2021
- 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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高性能质谱应用的支持技术
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