All-in-One digital microfluidics pipeline for proteomic sample preparation and analysis

• Published in: Chemical science (Cambridge) Vol. 14; no. 11; pp. 2887 - 29
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: England Royal Society of Chemistry 15.03.2023; The Royal Society of Chemistry
• Subjects: Additives; Alkylation; Automation; Cancer; Chemistry; Contaminants; Digestion; High performance liquid chromatography; Isotopic labeling; Mass spectrometry; Microfluidics; Proteins
• ISSN: 2041-6520; 2041-6539
• DOI: 10.1039/d3sc00560g

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. The All-in-One digital microfluidic pipeline allows for end-to-end automation of processing and analysis of mass-limited proteomic samples.