PROJECT SUMMARY/ABSTRACT The primary goal of this Administrative Supplement application is to develop a fundamental understanding of the Alzheimer’s disease-associated changes in brain-wide protein AMPylation. Protein AMPylation is conferred by dedicated AMPylases, which exist as a single copy in most metazoans. These enzymes are increasingly recognized to control proteostasis, modulating how and when amyloidogenic proteins, such as β-amyloid peptide (Aβ), α-synuclein (α-Syn) and polyglutamine repeat proteins, aggregate. The goals of the parent award (R35 MIRA) are to 1) dissect the mechanistic and physiological impact of FIC-1/FICD-mediated protein AMPylation on proteostasis, and 2) elucidate the mechanistic basis of protein AMPylation in the cytoplasm and nucleus. Our research program is utilizing four complementary model systems: the nematode C. elegans, purified proteins for in vitro biochemistry, human cell lines and in vivo mouse models, each offering its unique set of advantages to examine the consequences of aberrant protein AMPylation. In preliminary work expanding from the parent award, we determined that the conserved AMPylase, FICD, accumulates in the nucleus of Alzheimer’s disease patient neurons, whereas the enzyme resides perinuclear in neurons of neurologically unaffected brain tissue. Recent advances in tool and assay development now make it feasible to assess protein AMPylation in human brain tissue by immunofluorescence staining and immunoblotting approaches. This proposed supplement will allow us to identify changes in protein AMPylation in specific brain regions and cell types with the goal of defining a pathogenic role for these changes during the initiation and progression of Alzheimer’s disease and age-related dementias. This project will deliver a first-in-kind map of protein AMPylation in the human brain and establish novel links between protein AMPylation and Alzheimer’s disease. We will annotate, curate, and rapidly disseminate the data to the broad scientific community prior to publication to maximize the utility of these data for meta-analysis and systems biology research.