Peng Jiaxi, Chan Calvin, Zhang Shuailong, Sklavounos Alexandros A, Olson Maxwell E, Scott Erica Y, Hu Yechen, Rajesh Vigneshwar, Li Bingyu B, Chamberlain M Dean, Zhang Shen, Peng Hui, Wheeler Aaron R
Department of Chemistry, University of Toronto 80 St. George Street Toronto ON M5S 3H6 Canada
Donnelly Centre for Cellular and Biomolecular Research, University of Toronto 160 College Street Toronto ON M5S 3E1 Canada.
Chem Sci. 2023 Feb 22;14(11):2887-2900. doi: 10.1039/d3sc00560g. eCollection 2023 Mar 15.
Highly sensitive and reproducible analysis of samples containing low amounts of protein is restricted by sample loss and the introduction of contaminants during processing. Here, we report an All-in-One digital microfluidic (DMF) pipeline for proteomic sample reduction, alkylation, digestion, isotopic labeling and analysis. The system features end-to-end automation, with integrated thermal control for digestion, optimized droplet additives for sample manipulation and analysis, and an automated interface to liquid chromatography with tandem mass spectrometry (HPLC-MS/MS). Dimethyl labeling was integrated into the pipeline to allow for relative quantification of the trace samples at the nanogram level, and the new pipeline was applied to evaluating cancer cell lines and cancer tissue samples. Several known proteins (including HSP90AB1, HSPB1, LDHA, ENO1, PGK1, KRT18, and AKR1C2) and pathways were observed between model breast cancer cell lines related to hormone response, cell metabolism, and cell morphology. Furthermore, differentially quantified proteins (such as PGS2, UGDH, ASPN, LUM, COEA1, and PRELP) were found in comparisons of healthy and cancer breast tissues, suggesting potential utility of the All-in-One pipeline for the emerging application of proteomic cancer sub-typing. In sum, the All-in-One pipeline represents a powerful new tool for automated proteome processing and analysis, with the potential to be useful for evaluating mass-limited samples for a wide range of applications.
对低蛋白含量样本进行高灵敏度和可重复性分析受到样本损失以及处理过程中污染物引入的限制。在此，我们报告了一种用于蛋白质组学样本还原、烷基化、消化、同位素标记和分析的一体化数字微流控（DMF）流程。该系统具有端到端自动化功能，集成了用于消化的热控制、用于样本处理和分析的优化液滴添加剂，以及与液相色谱 - 串联质谱（HPLC - MS/MS）的自动化接口。二甲基标记被整合到该流程中，以实现纳克级微量样本的相对定量，并且新流程被应用于评估癌细胞系和癌组织样本。在与激素反应、细胞代谢和细胞形态相关的模型乳腺癌细胞系之间观察到了几种已知蛋白质（包括HSP90AB1、HSPB1、LDHA、ENO1、PGK1、KRT18和AKR1C2）及相关通路。此外，在健康乳腺组织与癌组织的比较中发现了差异定量的蛋白质（如PGS2、UGDH、ASPN、LUM、COEA1和PRELP），这表明一体化流程在蛋白质组学癌症亚型新兴应用方面具有潜在用途。总之，一体化流程代表了一种用于自动化蛋白质组处理和分析的强大新工具，有可能用于评估广泛应用中质量受限的样本。
