Biofluids contain molecules in circulation and from nearby organs that can be indicative of disease states. Characterizing the proteome of biofluids with DIA-MS is an emerging area of interest for biomarker discovery; yet, there is limited consensus on DIA-MS data analysis approaches for analyzing large numbers of biofluids. To evaluate various DIA-MS workflows, we collected urine from a clinically heterogeneous cohort of prostate cancer patients and acquired data in DDA and DIA scan modes. We then searched the DIA data against urine spectral libraries generated using common library generation approaches or a library-free method. We show that DIA-MS doubles the sample throughput compared to standard DDA-MS with minimal losses to peptide detection. We further demonstrate that using a sample-specific spectral library generated from individual urines maximizes peptide detection compared to a library-free approach, a pan-human library, or libraries generated from pooled, fractionated urines. Adding urine subproteomes, such as the urinary extracellular vesicular proteome, to the urine spectral library further improves the detection of prostate proteins in unfractionated urine. Altogether, we present an optimized DIA-MS workflow and provide several high-quality, comprehensive prostate cancer urine spectral libraries that can streamline future biomarker discovery studies of prostate cancer using DIA-MS.

中文翻译：

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用于增强尿液中蛋白质检测的综合前列腺液光谱库

生物流体中含有循环中的分子以及来自附近器官的分子，这些分子可以指示疾病状态。使用 DIA-MS 表征生物流体的蛋白质组是生物标志物发现的一个新兴领域；然而，对于分析大量生物体液的 DIA-MS 数据分析方法，达成的共识有限。为了评估各种 DIA-MS 工作流程，我们从临床异质性前列腺癌患者队列中收集尿液，并以 DDA 和 DIA 扫描模式获取数据。然后，我们根据使用常见库生成方法或无库方法生成的尿液光谱库搜索 DIA 数据。我们表明，与标准 DDA-MS 相比，DIA-MS 的样品通量增加了一倍，并且肽检测损失最小。我们进一步证明，与无库方法、泛人类库或从合并、分级尿液生成的库相比，使用从个体尿液生成的样本特异性谱库可以最大限度地提高肽检测。将尿液亚蛋白质组（例如尿液细胞外囊泡蛋白质组）添加到尿液光谱库中，进一步改善了普通尿液中前列腺蛋白的检测。总之，我们提出了优化的 DIA-MS 工作流程，并提供了几个高质量、全面的前列腺癌尿液光谱库，可以简化未来使用 DIA-MS 进行的前列腺癌生物标志物发现研究。