Single Cell Proteome Mapping of Tissue Heterogeneity Using Microfluidic Nanodroplet Sample Processing and Ultrasensitive LC-MS

Ryan Kelly, Ying Zhu, Yiran Liang, Yongzheng Cong, Paul Piehowski, Maowei Dou, Rui Zhao, Wei-Jun Qian, Kristin Burnum-Johnson, Charles Ansong
2019 Journal of Biomolecular Techniques  
Biological tissues are highly heterogeneous, consisting of a variety of cell types, subpopulations, and substructures. Understanding heterogeneity at the single cell level is of great interest for biomedical research. While MS-based proteomic analyses are capable of quantifying thousands of proteins, the extension to single cell studies has been largely ineffective. This is primarily due to the large sample losses incurred during sample preparation procedures. We have developed nanoPOTS
more » ... plet Processing in One-pot for Trace Samples), which significantly minimize sample losses during proteomic preparation. nanoPOTS utilizes a robotic platform to dispense nanoliter volumes of reagents into photolithographically patterned nanowell reaction vessels. Sample preparation utilizes a novel workflow that eliminates the need for multiple reaction vessels and cleanup steps to process cellular tissue into purified tryptic peptides. Single cells can be isolated into nanowells by fluorescence-activated cell sorting (FACS) or laser capture dissection (LCM), processed, and analyzed with low-flow nanoLC Orbitrap mass spectrometry. To date, we have identified >3,000 protein groups from as few as 10 HeLa cells, which is a level of proteome coverage not previously achieved from fewer than thousands of cells, and ∼700 proteins have been identified from single mammalian cells. To enable high-resolution tissue mapping, we developed an automated method to couple LCM with nanoPOTS. This approach is capable of quantifying ∼2000 proteins in 100-µm tissue voxels. We used this approach to study protein expression difference in single pancreas islets from healthy and Type 1 Diabetes human donors. More recently, a high-resolution mapping method was built to generate protein expression images of mouse uterine tissue sections for blastocyst implantation. The ability to map the proteome with high spatial resolution across tissue regions provides a fundamental way to understand the tissue microenvironment, substructure, and cellular organization from a global proteome perspective.
pmid:31897031 pmcid:PMC6938103 fatcat:vpcgmcu5kvepvklpbu6w4ymxku