Journal of NeurochemistryNeurosciencePeer-reviewed journal article
Phosphorylation-dependent control of Arc protein by synaptic plasticity regulator TNIK
Alicyia Walczyk MooradallyiD, Jennifer HolborniD, Karamjeet K. Singh, Marshall W. TyleriD, Debasis PatnaikiD, Hendrik Wesseling, Nicholas J. BrandoniD, Judith A. J. SteeniD, Steffen P. GraetheriD, Stephen J. HaggartyiD, Jasmin LalondeiD
Abstract
Activity-regulated cytoskeleton-associated protein (Arc) is an immediate-early gene product that support neuroplastic changes important for cognitive function and memory formation. As a protein with homology to the retroviral Gag protein, a particular characteristic of Arc is its capacity to self-assemble into virus-like capsids that can package mRNAs and transfer those transcripts to other cells. Although a lot has been uncovered about the contributions of Arc to neuron biology and behavior, very little is known about how different functions of Arc are coordinately regulated both temporally and spatially in neurons. The answer to this question we hypothesized must involve the occurrence of different protein post-translational modifications acting to confer specificity. In this study, we used mass spectrometry and sequence prediction strategies to map novel Arc phosphorylation sites. Our approach led us to recognize serine 67 (S67) and threonine 278 (T278) as residues that can be modified by TNIK, which is a kinase abundantly expressed in neurons that shares many functional overlaps with Arc and has, along with its interacting proteins such as the NMDA receptor, been implicated as a risk factor for psychiatric disorders. Furthermore, characterization of each residue using site-directed mutagenesis to create S67 and T278 mutant variants revealed that TNIK action at those amino acids can strongly influence Arcs subcellular distribution and self-assembly as capsids. Together, our findings reveal an unsuspected connection between Arc and TNIK. Better understanding of the interplay between these two proteins in neuronal cells could lead to new insights about apparition and progression of psychiatric disorders.
- organism: human
- assay: proteomics
- research focus: protein structure prediction
- approach: statistical model
- Citations
- 11
- FWCI
- 1.04
- Field percentile
- top 29%
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