Advancing Multiplexed Isobaric Tag-based Strategies for Proteome Profiling
推进基于多重同量异序标签的蛋白质组分析策略
基本信息
- 批准号:10018062
- 负责人:
- 金额:$ 33.9万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-09-15 至 2024-08-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAlgorithmsAutomobile DrivingAwarenessBenchmarkingBiologicalBiological AssayBiological SciencesBiologyBloodBody FluidsCell LineCell physiologyCerebrospinal FluidCollectionCommunitiesComputer softwareCustomDataData AnalysesData SetDatabasesDevelopmentDisadvantagedEvolutionExpression ProfilingFinancial compensationFission YeastGoalsGrowthHealthHumanHuman Cell LineInjectionsIntelligenceIonsKnowledgeLabelLengthLettersLibrariesManufacturer NameMass Spectrum AnalysisMeasurementMeasuresMetabolismMethodologyMethodsModelingMotivationMusNoiseOcular orbitOrganismPeptidesPerformancePlasmaProteinsProteomeProteomicsReagentReproducibilityResearchResolutionResourcesSaccharomyces cerevisiaeSamplingScanningSeriesSignal TransductionSpecific qualifier valueSpeedTechniquesTechnologyTimeTissuesTranslational ResearchYeastsapplication programming interfacebasecatalystcost effectivedata acquisitionexperimental studyindexinginnovationinsightinstrumentinstrumentationmass analyzernovelprotein expressionprotein functionsearch enginestable isotopeyeast protein
项目摘要
ABSTRACT
Sample multiplexing has been the catalyst for many recent large-scale proteomics initiatives. The advent of
isobaric tagging, as popularized by iTRAQ (isobaric tags for relative and absolute quantitation) and TMT
(tandem mass tag) reagents, has become the quintessential methodology for multiplexed protein expression
profiling. Two major data acquisition methods exist each with its own advantages and disadvantages. First, the
MS2-only method (“MS2-IDQ” herein) can identify (ID) and quantify (Q) a peptide in a single spectrum.
Second, the synchronous precursor selection (SPS)-MS3 method identifies the precursor in the MS2 stage, but
then selects a series of fragment ions from the MS2 stage that are fragmented further and read out as an MS3
spectrum for quantification measurements. MS2-IDQ suffers from the co-isolation and co-fragmentation of
precursor ions (“interference”), and although SPS-MS3 helps to alleviate interference, it is at the expense of
speed, a direct result from the acquisition of long MS3 scans. Here we aim to develop, evaluate, and apply a
novel data acquisition platform that merges the benefits of current methods and alleviates their major caveats.
A recent development on ThermoFisher Scientific's Orbitrap Fusion and Lumos instruments has been the
implementation of an instrument application programming interface (iAPI) that allows for expanded control of
the instrumentation beyond the manufacturer's built-in functionality. Using this interface, the Gygi Lab and
others have begun to create custom on-the-fly real-time search (RTS) algorithms. RTS enables an MS2
spectrum to be searched in real-time and decisions to be made as to whether an MS3 scan is likely to result in
a significant peptide quantification measurement. By omitting MS3 scans, more MS2 spectra can be collected
and new peptides may be identified. Using the iAPI, functions can be added including targeted lists and limits
set for the number of peptides quantified per protein (in the case of very abundant and/or large proteins), which
is useful in translational research, such as the interrogation of plasma samples and other body fluids.
Our Specific Aims are geared toward developing further the methodology for successful application of RTS-
MS3. In Specific Aim 1, we will benchmark emerging algorithms for RTS-MS3 using both the TKO and
HYPER (human-yeast peptide resource) standards for TMT-based proteome profiling. In Specific Aim 2, we
will evaluate the RTS-MS3 platform across several sample types (bacterial cultures, mouse tissues, blood,
cerebral spinal fluid, human cell lines, and yeast cultures) against traditional MS2-IDQ and SPS-MS3 methods
(Specific Aim 2). Finally, in Specific Aim 3 we will apply the RTS-MS3 platform to analyze an entire Yeast
Deletion Strain Collection under two growth conditions, which will produce the largest yeast protein expression
profiling data set to date. Accomplishing these three Specific Aims will establish the RTS-MS3 platform as a
disruptive technology to current isobaric tag-based multiplexing methodology and will mark a paradigm shift in
isobaric tag-based quantitative proteomics.
摘要
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)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Joao A Paulo其他文献
Joao A Paulo的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Joao A Paulo', 18)}}的其他基金
Advancing Multiplexed Isobaric Tag-based Strategies for Proteome Profiling
推进基于多重同量异序标签的蛋白质组分析策略
- 批准号:
10240607 - 财政年份:2019
- 资助金额:
$ 33.9万 - 项目类别:
Advancing Multiplexed Isobaric Tag-based Strategies for Proteome Profiling
推进基于多重同量异序标签的蛋白质组分析策略
- 批准号:
10683398 - 财政年份:2019
- 资助金额:
$ 33.9万 - 项目类别:
Advancing Multiplexed Isobaric Tag-based Strategies for Proteome Profiling
推进基于多重同量异序标签的蛋白质组分析策略
- 批准号:
10473610 - 财政年份:2019
- 资助金额:
$ 33.9万 - 项目类别:
Resolving the role of nicotine-mediated phosphorylation on pancreatic fibrosis
解决尼古丁介导的磷酸化对胰腺纤维化的作用
- 批准号:
8635107 - 财政年份:2013
- 资助金额:
$ 33.9万 - 项目类别:
Resolving the role of nicotine-mediated phosphorylation on pancreatic fibrosis
解决尼古丁介导的磷酸化对胰腺纤维化的作用
- 批准号:
8735012 - 财政年份:2013
- 资助金额:
$ 33.9万 - 项目类别:
Proteomics of Pancreatic Fluid and Urine in Chronic Pancreatitis
慢性胰腺炎胰液和尿液的蛋白质组学
- 批准号:
8257975 - 财政年份:2010
- 资助金额:
$ 33.9万 - 项目类别:
Proteomics of Pancreatic Fluid and Urine in Chronic Pancreatitis
慢性胰腺炎胰液和尿液的蛋白质组学
- 批准号:
8071518 - 财政年份:2010
- 资助金额:
$ 33.9万 - 项目类别:
Proteomics of Pancreatic Fluid and Urine in Chronic Pancreatitis
慢性胰腺炎胰液和尿液的蛋白质组学
- 批准号:
7913684 - 财政年份:2010
- 资助金额:
$ 33.9万 - 项目类别:
相似海外基金
DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
- 批准号:
EP/Y029089/1 - 财政年份:2024
- 资助金额:
$ 33.9万 - 项目类别:
Research Grant
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
- 批准号:
2337776 - 财政年份:2024
- 资助金额:
$ 33.9万 - 项目类别:
Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
- 批准号:
2338816 - 财政年份:2024
- 资助金额:
$ 33.9万 - 项目类别:
Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
- 批准号:
2338846 - 财政年份:2024
- 资助金额:
$ 33.9万 - 项目类别:
Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
- 批准号:
2348261 - 财政年份:2024
- 资助金额:
$ 33.9万 - 项目类别:
Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
- 批准号:
2348346 - 财政年份:2024
- 资助金额:
$ 33.9万 - 项目类别:
Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
- 批准号:
2348457 - 财政年份:2024
- 资助金额:
$ 33.9万 - 项目类别:
Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
- 批准号:
2404989 - 财政年份:2024
- 资助金额:
$ 33.9万 - 项目类别:
Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
- 批准号:
2339310 - 财政年份:2024
- 资助金额:
$ 33.9万 - 项目类别:
Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
- 批准号:
2339669 - 财政年份:2024
- 资助金额:
$ 33.9万 - 项目类别:
Continuing Grant