Endophilin is an essential protein for membrane dynamics. It harbors a BAR (Bin–Amphiphysin–Rvs) domain, which acts as a basic modual for shaping membranes. Deletion of Endophilin impairs endocytosis, which leads to defects in cellular signaling. Despite the importance, how Endophilin is regulated remains elusive. Here, we propose that the bending activity of the Endophilin BAR domain is modulated by phosphorylation. We will use biophyiscal/biochemical approaches to investigate Endophilin-membrane interactions. Our result will provide new insights into molecular mechanisms for controling membrane dynamics. We use liposomes as an in vitro model. We follow the kinetics of Endophilin-membrane interactions using fluorescent probes. We identify key residues for Endophilin-membrane binding using site-directed mutagenesis. We believe this research will help us understand the mechanism for shaping cellular membranes, in particular, how Endophilin BAR domain bends membranes.

Understanding how the brain processes information using neural circuits remains a challenging task. For example, although neurons in the mammalian visual cortex are known to be specialized for processing particular visual features, such as motion, color or depth, little progress has been made on elucidating the underlying circuit diagrams. To address this problem, we have developed a system with a Java-based user interface that can apply optimization strategies to rapidly test competing models against large amounts of neurophysiological data, parallelizing the computational load across a cluster of workstations, to uncover plausible circuit models. In order to demonstrate the effectiveness of this system, we are applying it to understand the function of motion-sensitive neurons in the primate visual cortex. These neurons are direction selective (DS), meaning that they respond well to a visual stimulus moving in one direction but not in others. Previous studies demonstrated that this response also changes with stimulus speed: as the visual world moves faster, the neurons appear to operate on a shorter timescale. Current mathematical models for DS neurons, which are based on filters that change position linearly with time, predict the response to some stimuli but do not account for the ability of the neuronal response to adapt to changes in speed. We hypothesize that a model using a filter that changes position nonlinearly with time will better explain the experimental data. To discover this filter, we are building several candidate models and will apply our optimization system to test their performance against our own experimental data. We will test these nonlinear filter models against an alternative that uses multiple linear filters, each tuned for a different velocity. If our approach can improve upon current models for DS neurons, it may offer neuroscientists a powerful tool for revealing neural circuits that underlie visual perception.

The brain effortlessly carries out the daunting task of visual perception by utilizing millions of neurons to process various aspects of the visual scene. The systematic arrangement of these cells across the primary visual cortex (V1) can be described by a set of superimposed maps that convey the orientation, scale, location and eye of origin of the image features that best excite the neurons. Current theory suggests these maps are arranged such that all combinations of stimulus parameters are covered equally and continuously in local regions across the visual cortex. This idea is appealing because it corresponds to the intuition that we should be able to see the features of a simple shape equally well at any rotation and at a variety of distances, and it is important because it places a constraint on the architecture of the cortex. To examine whether this constraint fits with other known anatomical and physiological measurements, we have conducted computer simulations to measure the evenness of coverage in large-scale, biologically plausible models of V1. We presented a large combination of visual stimuli to the model and computed a coverage metric, c', defined in the literature as the standard deviation divided by the mean of cortical activity across all stimuli. Taken together, c' and the associated map of neuronal activity in stimulus space reveal the coverage uniformity of map variable combinations. We found that our original models had a striking imbalance in activity across spatial scale, which counterintuitively arose from the assumption of a uniform change in neuronal receptive field (RF) size across the visual cortex. In these models, there were equal numbers of neurons with small and large RFs. Based on our observations, we are developing an improved model that uses a nonlinear distribution of RF sizes in an attempt to preserve uniform coverage.

In liver transplantation, increased overall fat content in donor livers causes poor graft function and lower patient survival post-transplant. Longer waiting lists combined with a shortage of organs has resulted in transplant surgeons considering moderately steatotic livers as a part of extended donor criteria. Clinically, the fatty infiltration is diagnosed by the lipid droplet size. Macrovesicular steatosis refers to large droplets or vesicles that distort the nucleus, while microvesicular steatosis refers to droplets equal to or less than the size of the hepatic cell nucleus. While macrovesicular steatosis negatively impacts graft function, livers with microvesicular steatosis result in patient outcomes that are almost the same as that of nonsteatotic livers. Therefore, a method to quantify the amount and droplet size of hepatic steatosis can be an innovative tool for transplant surgeons. In our previous studies, sound speed and attenuation correlated with the presence of visually observable fat. However, significant variabilities were discovered in the attenuation. The next step in this research involves exploring the effect of lipid droplet size on attenuation, using an attenuation spectroscopy method developed in colloid science research. If the total fat content is known, mixture rules based on a volume average of the fat and non-fat components can be used to estimate the intrinsic attenuation at a given frequency. Beyond this estimate, excess attenuation attributable to interactions between fat and non-fat phases of the mixture can be estimated using a coupled-phase model. Here, we quantitatively evaluate the excess attenuation caused by small lipid droplets by comparing attenuation measurements of well-characterized dairy products with model predictions. Results confirm that sub-micron sized lipid droplets produce a measurable amount of excess attenuation at 1 MHz. These results suggest that analogous measurements may be made in quantifying the amount of microvesicular steatosis present in livers with known overall fat percentage.

My project is to reveal mechanisms that regulate the abundance and the distribution of dopamine receptors in C. elegans. The neurotransmitter dopamine carries out its modulatory activities though transmembrane dopamine receptors. These receptors that reside on plasma membranes bind extracellular dopamine and propagate activities through G-protein coupled signaling pathways. The abundance and location of dopamine receptors are highly dynamic, which permits dopamine to modulate brain activities in response to physical changes such as stress and ageing. Here, I propose to image fluorescently tagged dopamine receptors in living worms. I will use CRISPR/Cas9-mediated gene editing approaches to insert fluorescent tags into genes encoding dopamine receptors, which results transgenes located in near native gene environment (such as promoters and 3' UTR regions). To quantify the abundance of dopamine receptors on plasma membranes, I will tag a pH-sensitive green fluorescent protein (pHluorin) to extracellular domains of dopamine receptors. When dopamine receptors are in transporter vesicles, the pHluorin fluorescence is quenched because extracellular domains of dopamine receptors reside in the acidic vesicle lumen. Once dopamine receptors are delivered onto plasma membrane, the pHluorin fluorescence becomes visible as pH is neutralized. To monitor the total amount of dopamine receptors, I will introduce a pH-insensitive red fluorescent protein to the intracellular domain of dopamine receptors. The ratio between green and red fluorescence will indicate the surface fraction of dopamine receptors. As a control, I will conduct pharmacological and behavior assays to test whether the engineered dopamine receptors are functional in vivo. Results from this study will allow us to visualize how dopamine receptors are regulated to support brain functions.