High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples from a variety of sources, including fresh-frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot solid-phase-enhanced sample preparation (SP3) on a liquid handling robot for automated processing (autoSP3) of tissue lysates in a 96-well format. AutoSP3 performs unbiased protein purification and digestion, and delivers peptides that can be directly analyzed by LCMS, thereby significantly reducing hands-on time, reducing variability in protein quantification, and improving longitudinal reproducibility. We demonstrate the distinguishing ability of autoSP3 to process low-input samples, reproducibly quantifying 500-1,000 proteins from 100 to 1,000 cells. Furthermore, we applied this approach to a cohort of clinical FFPE pulmonary adenocarcinoma (ADC) samples and recapitulated their separation into known histological growth patterns. Finally, we integrated autoSP3 with AFA ultrasonication for the automated end-to-end sample preparation and LCMS analysis of 96 intact tissue samples. Collectively, this constitutes a generic, scalable, and cost-effective workflow with minimal manual intervention, enabling reproducible tissue proteomics in a broad range of clinical and non-clinical applications.

中文翻译：

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使用 SP3 进行自动化样品制备，用于低输入临床蛋白质组学。


高通量和简化的工作流程对于临床蛋白质组学中对各种来源（包括新鲜冷冻组织、FFPE 组织或血液）样品进行标准化处理至关重要。为了实现这一目标，我们在液体处理机器人上实施了单罐固相增强样品制备 (SP3)，用于以 96 孔格式自动处理 (autoSP3) 组织裂解液。 AutoSP3 执行无偏的蛋白质纯化和消化，并提供可通过 LCMS 直接分析的肽，从而显着减少动手时间，减少蛋白质定量的变异性，并提高纵向重现性。我们展示了 autoSP3 处理低输入样品的独特能力，可重复地定量 100 至 1,000 个细胞中的 500-1,000 种蛋白质。此外，我们将这种方法应用于一组临床 FFPE 肺腺癌 (ADC) 样本，并将它们的分离概括为已知的组织学生长模式。最后，我们将 autoSP3 与 AFA 超声处理相结合，对 96 个完整组织样本进行自动化端到端样本制备和 LCMS 分析。总的来说，这构成了一个通用的、可扩展的、具有成本效益的工作流程，只需最少的人工干预，从而在广泛的临床和非临床应用中实现可重复的组织蛋白质组学。