Recent technological advances in single cell RNA-Seq have highlighted the possibility of a hitherto unrecognized cell-to cell variability in many cell types across a wide range of tissues and organs. Such variability results in the multiple subtypes of cells of a single type. This variability results in differing cell biological capabilities, which has important consequences for drug therapy for complex diseases. A systems pharmacology approach that takes into account variable responses of the subtypes could be useful in development of effective combination therapy. Our systems pharmacology approaches includes integration of computational modeling whereby we combine graph theory and dynamical models to analyze single cell transcriptomic data so as to identify relevant regulatory pathways and subnetworks involved in a model system that produces a whole cell response to receptor stimulation which in vivo can play a role recovery from pathophysiology in response to drugs. Based on these criteria we have been studying G protein coupled cannabinoid 1 receptor regulated neurite outgrowth of primary neurons in vitro to identify targetable nodes for combination drug therapy that can be tested to treat injury to the optic nerve in rats in vivo. After injury, two receptor agonists drugs applied at the cell body and the two other two drugs at the injury site restores light dependent electrophysiological signals in the visual cortex. Although we see signal reliably in the visual cortex, the amplitude of restored signal is small. We hypothesize that identifying genes responsible for long neurites in subtypes of cells using single cell RNA-Seq will map cellular mechanisms to identify drugs for regeneration of denser axonal bundles and lead to greater restoration of the light stimulated electrophysiological signals in the visual cortex. To test this hypothesis we have three specific aims: 1) Will analyze variability of single cell transcriptomic responses to receptor activation to identify the determinants that control cells to put out long neurites in a population of cells. 2) Will use computational systems biology to develop integrated network and dynamical models to identify the subcellular processes and drugs that regulate the expression of up and downregulated genes in cells with long neurites. 3) Will use the optic nerve injury model in rats to test if neurite lengthening drugs along with or substituting for the current four-drug combination results in increased density of regenerated fibers and higher amplitude of the electrophysiological responses in the visual cortex. We anticipate this will provide general fundamental understanding of the subcellular processes that control cell-to cell variability in whole cell responses and how to use it for efficacious drug therapy.

Public Health Relevance

This study is focus on understanding how cell-to-cell variability identified by single cell technologies within tissues contribute to differential responses to drug therapy. Using information from cellular pathways, we have developed an initial four-drug combination therapy for nerve injury. In the coming term we propose to use cutting edge single cell technologies to understand how to design combination drug therapy to counter cell-to cell variability to yield robust therapeutic responses.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM137056-01
Application #
9945326
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Brazhnik, Paul
Project Start
2020-09-01
Project End
2024-06-30
Budget Start
2020-09-01
Budget End
2021-06-30
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Icahn School of Medicine at Mount Sinai
Department
Pharmacology
Type
Schools of Medicine
DUNS #
078861598
City
New York
State
NY
Country
United States
Zip Code
10029