# Decoding temporal epithelial signaling programs to restore homeostasis in acute lung injury

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2022 · $604,139

## Abstract

Abstract
Acute lung injury/acute respiratory distress syndrome (ALI/ARDS) is a common pulmonary
syndrome with high mortality. ALI/ARDS stems from a communication breakdown between lung
epithelial cells and immune cells and is a major factor in severe cases of respiratory infection,
including COVID-19. Treatments for ALI/ARDS are currently limited by inadequate models of
the complex relationships between signaling pathways and lung epithelial cell behavior. A core
network of signaling pathways control epithelial structure and cytokine release and are an
important unexploited point of intervention in ALI/ARDS via existing targeted kinase inhibitors or
metabolic modulators. This core network includes NF-kB, a primary transcription factor for
cytokine release and inflammation, and the kinases ERK, AKT, JNK, p38, mTOR and AMPK,
which modulate cytokine production in response to cellular growth and metabolic status.
Notably, this signaling network also plays a causal role in lung cancer and is involved in other
diseases of the lung epithelium, including fibrosis and COPD. Our lab has developed an
extensive live-cell technology platform for tracking temporal programs of signaling events –
different patterns of timing, intensity, and coordination between these pathways – that govern
epithelial cell fate decisions. Our overall objective is to quantitatively decode how cytokine
secretion is specified by multi-kinase activity programs. Our hypothesis is that accounting for
coinciding phases of signaling activity at the single cell level will significantly improve the
prediction of both overall and local variability in cytokine secretion and will identify metabolic
manipulations that reduce inflammation. Our approach will develop the technology needed to
detect and manipulate temporal signaling programs to restore lung epithelial homeostasis in
ALI/ARDS. Aim 1 will develop a high-content data-driven model correlating signaling programs
to cytokine release on a cell-by-cell basis across multiple conditions. Aim 2 will develop the
capacity to characterize the localized inflammatory environment in subregions of lung epithelium
by examining the dynamic programs of kinase signaling in groups of 10-100 neighboring cells.
In the process, we will provide proof of principle for using panels of fixed immunofluorescence
markers to capture dynamic signaling patterns. Aim 3 will investigate the potential for
manipulating temporal signaling programs with existing pharmacological agents, focusing on the
emerging benefits of AMPK activators as a route to modulate the larger signaling network. Our
multi-disciplinary team will work across the boundaries of pulmonary care, cell biology, and
computational systems modeling to create a technology platform that connects modern single-
cell signal transduction analysis to pressing challenges in lung disease. We anticipate that our
project will identify potential new routes of intervention for ALI/ARDS, as well as revealing
general c...

## Key facts

- **NIH application ID:** 10475871
- **Project number:** 5R01HL151983-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS
- **Principal Investigator:** John G. Albeck
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $604,139
- **Award type:** 5
- **Project period:** 2021-09-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10475871

## Citation

> US National Institutes of Health, RePORTER application 10475871, Decoding temporal epithelial signaling programs to restore homeostasis in acute lung injury (5R01HL151983-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10475871. Licensed CC0.

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