“Macrophage memory emerges from coordinated transcription factor and chromatin dynamics”
Wang, A.G.*; Son, M.*; Gorin, A.; Kenna, E.; Padhi, A.; Keisham, B.; Schauer, A.; Hoffmann, A.; Tay, S†
Cell Systems (accepted)
Microtissue Signaling Dynamics
OUR RESEARCH
Probing underlying patterns in complex tissue signaling dynamics
Cells within tissue respond to and secrete various biochemical signals to communicate local disease information and coordinate immune responses at both the tissue and organism levels. Although the spatial and temporal dynamics of signaling molecules contain valuable insights into disease progression and the efficacy of immune responses, these dynamics can vary significantly depending on the disease context, tissue state, stochastic cell responses, and from patient to patient. To overcome this complexity and enhance our understanding of the core mechanisms, we aim to collect multimodal data from tissues and deduce accurate — yet intuitive — models of pathogenesis or carcinogenesis under various conditions. To achieve our goal, we are developing advanced microfluidic platforms to quantify immune signaling and response dynamics in primary tissues (“microtissues”), and are integrating these empirical results with various mathematical approaches, including but not limited to network simulation, information theory, chaos theory, and deep learning. Ultimately, we will endeavor to identify a set of parameters most indicative of disease and tissue state, and formulate optimal therapeutic strategies for treating autoimmune diseases and cancer.
RESEARCH PROJECTS
Microfluidic device for skin tissue and sequential secretome measurement
High-throughput platform for dynamic quantification of tissue responses
- Spatiotemporal measurement of transcription factor (NFκB) dynamics at the single-cell level within tissue
- Multiomics: Integration of microfluidics with mass-spectrometry
- Development of user-friendly and robust platform for broader application of microtissues
Virtual tissue: Simulating diffusion of pathogenic stimuli and immune signaling in 3-D tissue
Neural network analysis for RNA-seq/proteomics prediction using multifaceted data
Minimal and intuitive model for understanding the signaling dynamics of cellular network in tissue
- Virtual tissue: comprehensive simulation of intracellular and extracellular signaling networks in tissue
- Mathematical analyses including geometric scattering, information theory, chaos theory, and analytical solution.
- Neural network analysis to enhance the accuracy of prediction
PUBLICATIONS
*: First author; †: Corresponding author; Underlined: Affiliated with CZ Biohub
