Associate Professor, Department of Biology
Ph.D. Stanford University
B.S. Stanford Univeristy
Research Interests: Function and development of neural circuits for visual processing
Overview: How do we make sense of the visual world around us? Our brain takes a pattern of photons hitting the retina and continually creates a coherent representation of what we see – detecting objects and landmarks rather than just perceiving an array of pixels. This image processing allows us to perform a range of visual tasks, such as recognizing a friend’s face, finding your way to the grocery store, and catching a frisbee. However, how these computational feats are achieved by the neural circuitry of the visual system is largely unknown. Furthermore, this circuitry is wired up by a range of cellular processes, such as arbor growth, synapse formation, and activity-dependent plasticity, and thus these developmental mechanisms effectively determine how we see the world.
Our research is focused on understanding how neural circuits perform the image processing that allows us to perform complex visual behaviors, and how these circuits are assembled during development. We use in vivo recording techniques, including high-density extracellular recording and two-photon imaging, along with molecular genetic tools to dissect neural circuits, such as cell-type specific markers, optogenetic activation and inactivation, tracing of neural pathways, and in vivo imaging of dendritic and synaptic structure. We have also implemented behavioral tasks for mice so we can perform quantitative pyschophysics to measure the animal’s perception, and we use theoretical models to understand general computational principles being instantiated by a neural circuit.
TU-Tagging: A Method for Identifying Layer-Enriched Neuronal Genes in Developing Mouse Visual Cortex.
eNeuro. 2017 Sep-Oct;4(5):
Authors: Tomorsky J, DeBlander L, Kentros CG, Doe CQ, Niell CM
Thiouracil (TU)-tagging is an intersectional method for covalently labeling newly transcribed RNAs within specific cell types. Cell type specificity is generated through targeted transgenic expression of the enzyme uracil phosphoribosyl transferase (UPRT); temporal specificity is generated through a pulse of the modified uracil analog 4TU. This technique has been applied in mouse using a Cre-dependent UPRT transgene, CA>GFPstop>HA-UPRT, to profile RNAs in endothelial cells, but it remained untested whether 4TU can cross the blood-brain barrier (BBB) or whether this transgene can be used to purify neuronal RNAs. Here, we crossed the CA>GFPstop>HA-UPRT transgenic mouse to a Sepw1-cre line to express UPRT in layer 2/3 of visual cortex or to an Nr5a1-cre line to express UPRT in layer 4 of visual cortex. We purified thiol-tagged mRNA from both genotypes at postnatal day (P)12, as well as from wild-type (WT) mice not expressing UPRT (background control). We found that a comparison of Sepw1-purified RNA to WT or Nr5a1-purified RNA allowed us to identify genes enriched in layer 2/3 of visual cortex. Here, we show that Cre-dependent UPRT expression can be used to purify cell type-specific mRNA from the intact mouse brain and provide the first evidence that 4TU can cross the BBB to label RNA in vivo.
PMID: 29085897 [PubMed - in process]