Effect of Physioxia on Protein Levels in Adult Mouse (Mus Musculus) Neural Stem and Progenitor Cells

Abstract

Neural Stem and Progenitor Cells (NSPCs) from the adult subventricular zone hold therapeutic potential for a variety of neurological diseases due to their capabilities of self-renewal and potential for differentiation into the cell types of the brain. The potential for autologous cell replacement using NSPCs in cases of neurological injury or disease alleviates many of the ethical and practical issues that are a concern of other stem cell varieties. However, an understanding of many of the basic mechanisms that influence NSPC behaviour under normal physiological conditions is still required to develop appropriate strategies for NSPC expansion in vitro or for endogenous recruitment. Typically studies of NSPCs are conducted under conditions of atmospheric O2 levels, when in reality NSPCs reside in a niche that is subject to much lower concentrations of O2. As such, most studies concerning NSPCs may be limited in terms of their physiological relevance, and culture at lower levels of O2 may better approximate the conditions NSPCs experience in situ within their neurological niche. With this in mind, adult mouse (Mus musculus) NSPCs were cultured in both physiologically relevant levels of O2 (5%) and atmospheric conditions (21% O2) and then subsequently harvested for quantitative proteomic analysis using a data-independent acquisition (DIA) mass spectrometry (MS)-based approach. While cell count experiments suggested there was a difference in cellular activity between NSPCs in each treatment, there were no statistically significant changes in individual protein levels between O2 treatment groups following MS analysis, likely due to high variation among samples. However, MSanalysis still resulted in the identification of 878 unique proteins across treatment groups with quantitative protein expression values. To the best of our knowledge, this is the first quantitative accounting of the proteome of adult NSPCs from mice using DIA-MS-based techniques, which has resulted in a data set that can be compared to future studies of NSPCs. Additionally, this paper provides a framework for future studies by implementing coarse-grain functional categorization of proteins in order to reduce a large proteomic data set into a partitioning scheme that may be more amenable to deriving biologically meaningful conclusions.