Quantitative Proteomics Reveals Temporal Proteomic Changes in Signaling Pathways during BV2 Mouse Microglial Cell Activation

The
development of systematic proteomic quantification techniques
in systems biology research has enabled one to perform an in-depth
analysis of cellular systems. We have developed a systematic proteomic
approach that encompasses the spectrum from global to targeted analysis
on a single platform. We have applied this technique to an activated
microglia cell system to examine changes in the intracellular and
extracellular proteomes. Microglia become activated when their homeostatic
microenvironment is disrupted. There are varying degrees of microglial
activation, and we chose to focus on the proinflammatory reactive
state that is induced by exposure to such stimuli as lipopolysaccharide
(LPS) and interferon-gamma (IFN-γ). Using an improved shotgun
proteomics approach, we identified 5497 proteins in the whole-cell
proteome and 4938 proteins in the secretome that were associated with
the activation of BV2 mouse microglia by LPS or IFN-γ. Of the
differentially expressed proteins in stimulated microglia, we classified
pathways that were related to immune-inflammatory responses and metabolism.
Our label-free parallel reaction monitoring (PRM) approach made it
possible to comprehensively measure the hyper-multiplex quantitative
value of each protein by high-resolution mass spectrometry. Over 450
peptides that corresponded to pathway proteins and direct or indirect
interactors via the STRING database were quantified by label-free
PRM in a single run. Moreover, we performed a longitudinal quantification
of secreted proteins during microglial activation, in which neurotoxic
molecules that mediate neuronal cell loss in the brain are released.
These data suggest that latent pathways that are associated with neurodegenerative
diseases can be discovered by constructing and analyzing a pathway
network model of proteins. Furthermore, this systematic quantification
platform has tremendous potential for applications in large-scale
targeted analyses. The proteomics data for discovery and label-free
PRM analysis have been deposited to the ProteomeXchange Consortium
with identifiers and , respectively.