Quantitative multiplexed analysis of gene and protein expression patterns in intact cells
EMSL Project ID
51679
Abstract
Understanding the function of metabolic and regulatory pathways requires identifying their spatial and temporal expression patterns under different conditions. Furthermore, predictive modeling and controlled engineering of cells require unmasking variabilities in pathway parameters across genetically identical cells. Unlike a population average, single cell values will provide high resolution variability ranges to guide model parameters for predicting specific phenotypes. Here we propose to increase throughput and multiplexing for quantitative mapping of multiple gene and protein expression patterns simultaneously with the goal to uncover the spatial and temporal patterns of metabolic and regulatory pathways in genetically identical cells. The technology will be developed and demonstrated using Yarrowia lipolytica, a genetically tractable oleaginous yeast. This approach will support EMSL's Digital Phenome decadal goal and current and future user projects studying the spatial and temporal gene and protein expression patterns. Functional application of our technology and technique will tie the transcript levels of genes to cellular phenotypes. We will center our investigation around a regulator XBP1, which drives the transition into quiescence or cell cycle arrest upon nutrient limitation, and regulates the unfolded protein response.
Project Details
Start Date
2020-10-26
End Date
2022-09-30
Status
Closed
Released Data Link
Team
Principal Investigator
Team Members