Advancing Urinary Protein Biomarker Discovery by Data-Independent Acquisition on a Quadrupole-Orbitrap Mass Spectrometer.
Advancing Urinary Protein Biomarker Discovery by Data-Independent Acquisition on a Quadrupole-Orbitrap Mass Spectrometer.
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DOI：
10.1021/acs.jproteome.5b00826
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发表时间：
2015-11-06
影响因子：
4.4
通讯作者：
Steen H
中科院分区：
文献类型：
--
作者：
Muntel J;Xuan Y;Berger ST;Reiter L;Bachur R;Kentsis A;Steen H
数据独立采集（DIA）策略的承诺是对样品中存在的蛋白质进行全面和可重复的数字定性和定量记录。我们开发了一种快速、稳健的尿蛋白质组综合定位DIA方法，使大规模的尿蛋白质组学研究成为可能。与数据依赖采集（DDA）实验相比，我们的DIA实验在DDA数据（DIA = ~8%; DDA = ~16%）观察到的变异系数的一半下，每个样品鉴定的肽和蛋白质数量增加了一倍。我们还测试了不同的光谱库及其对整体蛋白质和肽鉴定的影响及其再现性，这清楚地证明了样品类型特异性光谱库是可靠数据分析的首选。为了证明生物标志物发现实验的适用性，我们分析了急诊科腹痛患儿的87份尿液样本。在不到4天的时间内，整个样品具有高蛋白质组覆盖率（约1300个蛋白质/样品）。该数据集揭示了卵巢囊肿和尿路感染的优秀生物标志物候选物。我们优化的DIA工作流程提高了吞吐量和定量性能，可以同时有效地发现和验证候选生物标志物，而无需对选定蛋白质进行早期偏向。
The promises of data-independent acquisition (DIA) strategies are a comprehensive and reproducible digital qualitative and quantitative record of the proteins present in a sample. We developed a fast and robust DIA method for comprehensive mapping of the urinary proteome that enables large scale urine proteomics studies. Compared to a data-dependent acquisition (DDA) experiments, our DIA assay doubled the number of identified peptides and proteins per sample at half the coefficients of variation observed for DDA data (DIA = ~8%; DDA = ~16%). We also tested different spectral libraries and their effects on overall protein and peptide identifications and their reproducibilities, which provided clear evidence that sample type-specific spectral libraries are preferred for reliable data analysis. To show applicability for biomarker discovery experiments, we analyzed a sample set of 87 urine samples from children seen in the emergency department with abdominal pain. The whole set was analyzed with high proteome coverage (~1300 proteins/sample) in less than 4 days. The data set revealed excellent biomarker candidates for ovarian cyst and urinary tract infection. The improved throughput and quantitative performance of our optimized DIA workflow allow for the efficient simultaneous discovery and verification of biomarker candidates without the requirement for an early bias toward selected proteins.