Thrust 1
Intracellular Cellular Signaling and Integration
Understanding how calcium signal decoding controls subcellular organization at the intracellular scale.
Project 1A: Calcium-driven control of actin dynamics in dendritic spines
Objectives
Project 1A determines how calcium (Ca2+) signal decoding controls subcellular actin organization by quantifying neuronal dendritic spine regulation. Objectives: (1) Integrate Ca2+ flux signals and polymerizing actin; (2) Establish the bidirectional regulation of the actin network and the Ca2+/CaM/CaMKII signaling axis in neuronal dendritic spines.
Research Highlights
Ca²⁺-Actin Coupling in Dendritic Spines
New hypotheses on Ca2+-dependent regulation of actin in spines via computational modeling and imaging experiments using MCell framework simulations.
Figure 17. We build upon our previous achievements in a biophysical mechanistic model of Ca2+- dependent activation of enzymes that act on actin modifying proteins we are building simulations at various scales to investigate the strength and dynamics of coupling between Ca2+-dependent signaling and actin polymerization in the MCell framework.
Figure 18. (Left) Red: Biocytin-filled neurons labeled with streptavidin-Alexa Fluor 594 conjugate (SA594). Green: CTB488 retrograde labeling. Using Airyscan, the outline of dendritic spines out of dendrite is clearly shown. Stimulated neurons were flowed with biocytin and labeled with streptavidin-Alexa Fluor 594 conjugate (SA594). (Right) Quantification of different types of spine structure and quantification the geometrical features of each. Grey is labeled as dendrite, and blue is indicated as dendritic spines. N=820 spine was detected through IMARIS software. Out of the 820 spines, thin spines were 14, stubby spines were 632, and mushroom spines were 174.
Project 1B: Whole cell Ca²⁺ signaling and actin dynamics
Objectives
Project 1B uses advanced imaging and deep learning techniques to analyze actin corrals in egg cells, revealing changes post-fertilization. A novel deep learning architecture was developed to extract subtle features from super-resolution data.
Research Highlights
Egg Cortex Imaging and Deep Learning
Analysis of actin corrals in egg cells with novel deep learning approaches to extract subtle features from super-resolution data.
Figure 19. Selected results-to-date and ongoing studies in Thrust 1B. See text for further information.