Deep proteome coverage of microglia using a streamlined data independent acquisition-based proteomic workflow: method consideration for a phenotypically diverse cell type

As the immune cells of the brain, microglia play a key role in various homeostatic and disease-related processes. In order to carry out their numerous functions, microglia are able to adopt a wide range of phenotypic states. The proteomic landscape represents a more accurate molecular representation of these phenotypes; however, microglia present unique challenges for proteomic analysis. This study implemented a streamlined liquid- and gas-phase fractionation method with data-dependent acquisition (DDA) and parallel accumulation serial fragmentation (PASEF) analysis on a TIMS-TOF instrument to compile a comprehensive protein library obtained from adult-derived, immortalized mouse microglia with minimal starting material (10µg). The empirical library consisted of 9,140 microglial proteins and was utilized to identify an average of 7,264 proteins per run from single-shot, DIA-based analysis of microglia. Additionally, a predicted library facilitated identification of 7,519 average proteins per run from the same DIA data, revealing complementary coverage compared to the empirical library and collectively increased coverage to approximately 8,000 proteins. Importantly, several immune response pathways were uniquely identified with empirical library approach. Overall, we report a simplified, reproducible approach for deep proteome coverage of microglia with low sample input and show the importance of library optimization for this phenotypically diverse cell type.