# Stress Response Pathways Regulating Protein Homeostasis

> **NIH NIH R35** · STANFORD UNIVERSITY · 2024 · $283,312

## Abstract

Project Abstract
Cellular stress response pathways are fundamental survival strategies that regulate protein homeostasis and
are misregulated in myriad diseases and aging. The mechanisms by which stress response pathways regulate
protein homeostasis, how well these mechanisms can perform, and why they fail in disease are major open
questions. We explore these questions from both a molecular and biophysical perspective. Over the next five
years, we plan to explore how cells detect and respond to defective protein translation, a process called
Ribosome-associated Quality Control (RQC). A major focus area will be CArboxyl-terminal Tails (CAT tails), a
form of protein synthesis we discovered in which ribosomes elongate defective proteins without guidance from
an mRNA template. We will also study biophysical responses to stress, including viscoadaptation, a stress
response we discovered in which cells regulate the diffusivity of biomolecules. We have a wealth of expertise
and experimental tools to continue our track record of making fundamental discoveries in stress response
pathways. Studying cellular stress response pathways at both the molecular and biophysical levels will lead to
deep insights into cell survival and the cell biology of disease.

## Key facts

- **NIH application ID:** 10841913
- **Project number:** 1R35GM153301-01
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Onn Brandman
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $283,312
- **Award type:** 1
- **Project period:** 2024-05-01 → 2029-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10841913

## Citation

> US National Institutes of Health, RePORTER application 10841913, Stress Response Pathways Regulating Protein Homeostasis (1R35GM153301-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10841913. Licensed CC0.

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