beta-Arrestin1 modulates lymphoid enhancer factor transcriptional activity through interaction with phosphorylated dishevelled proteins.

One aspect of the function of the beta-arrestins is to serve as scaffold or adapter molecules coupling G-protein coupled receptors (GPCRs) to signal transduction pathways distinct from traditional second messenger pathways. Here we report the identification of Dishevelled 1 and Dishevelled 2 (Dvl1 and Dvl2) as beta-arrestin1 (betaarr1) interacting proteins. Dvl proteins participate as key intermediates in signal transmission from the seven membrane-spanning Frizzled receptors leading to inhibition of glycogen synthase kinase-3beta (GSK-3beta), stabilization of beta-catenin, and activation of the lymphoid enhancer factor (LEF) transcription factor. We find that phosphorylation of Dvl strongly enhances its interaction with betaarr1, suggesting that regulation of Dvl phosphorylation and subsequent interaction with betaarr1 may play a key role in the activation of the LEF transcription pathway. Because coexpression of the Dvl kinases, CK1epsilon and PAR-1, with Dvl synergistically activates LEF reporter gene activity, we reasoned that coexpression of betaarr1 with Dvl might also affect LEF-dependent gene activation. Interestingly, whereas betaarr1 or Dvl alone leads to low-level stimulation of LEF (2- to 5-fold), coexpression of betaarr1 with either Dvl1 or Dvl2 leads to a synergistic activation of LEF (up to 16-fold). Additional experiments with LiCl as an inhibitor of GSK-3beta kinase activity indicate that the step affected by betaarr1 is upstream of GSK-3beta and most likely at the level of Dvl. These results identify betaarr1 as a regulator of Dvl-dependent LEF transcription and suggest that betaarr1 might serve as an adapter molecule that can couple Frizzled receptors and perhaps other GPCRs to these important transcription pathways.

Memory-Based Attentional Guidance: A Window to the Relationship between Working Memory and Attention

Attention, the cognitive means by which we prioritize the processing of a subset of information, is necessary for operating efficiently and effectively in the world. Thus, a critical theoretical question is how information is selected. In the visual domain, working memory (WM)—which refers to the short-term maintenance and manipulation of information that is no longer accessible by the senses—has been highlighted as an important determinant of what is selected by visual attention. Furthermore, although WM and attention have traditionally been conceived as separate cognitive constructs, an abundance of behavioral and neural evidence indicates that these two domains are in fact intertwined and overlapping. The aim of this dissertation is to better understand the nature of WM and attention, primarily through the phenomenon of memory-based attentional guidance, whereby the active maintenance of items in visual WM reliably biases the deployment of attention to memory-matching items in the visual environment. The research presented here employs a combination of behavioral, functional imaging, and computational modeling techniques that address: (1) WM guidance effects with respect to the traditional dichotomy of top-down versus bottom-up attentional control; (2) under what circumstances the contents of WM impact visual attention; and (3) the broader hypothesis of a predictive and competitive interaction between WM and attention. Collectively, these empirical findings reveal the importance of WM as a distinct factor in attentional control and support current models of multiple-state WM, which may have broader implications for how we select and maintain information.