# Network-Driven Dynamics of Replicative Aging

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2024 · $560,533

## Abstract

Project Summary
 This project aims at integrating computational modeling and innovative measurement technologies to
understand the complexity of single-cell aging and the emergent dynamics from the underlying regulatory
networks. Aging is closely associated with many diseases, such cancer, diabetes, and neurodegenerative
diseases. Advances in understanding the basic biology of aging will facilitate the development of new
interventional strategies to mitigate age-related diseases and prolong human healthspan. Although studies in
model organisms have identified many genes and factors that influence lifespan in eukaryotes, emerging
challenges are to understand how these genes and factors interact and operate dynamically to drive the aging
process and to determine the lifespan. During the previous funding period, our multidisciplinary team, using
microfluidic and imaging technologies combined with computational modeling, discovered that isogenic yeast
cells age with two distinct forms: one with decreased ribosomal DNA (rDNA) silencing and nucleolar decline
(Mode 1) whereas the other with heme depletion and mitochondrial decline (Mode 2). We further identified a
core molecular circuit, consisting of the lysine deacetylase Sir2 and the heme-activated protein (HAP)
transcriptional complex, that governs the fate decision toward one of the aging paths in single cells. Building
upon these results, for the next funding period, we will investigate the age-dependent dynamics of the energy
homeostasis and protein homeostasis systems, two conserved aging hallmark pathways in eukaryotes, and their
interactions with the Sir2-HAP fate-decision circuit. In Aim 1, we will quantitatively characterize the interactions
between aging and the energy homeostasis system and develop a model that simulates the aging dynamics of
the system. In Aim 2, we will quantitatively characterize the interactions between aging and the protein
homeostasis system and develop a dynamic model of proteostasis in aging based on the data collected. In Aim
3, we will combine experiments with modeling to characterize, simulate, and predict single-cell aging trajectories
and lifespan under complex environmental conditions, with a combination of different nutrients and stresses. The
proposed research will advance a quantitative and predictive understanding of regulatory networks underlying
single-cell aging under complex environmental conditions, laying the foundation for interventional strategies for
ameliorating age-related diseases and promoting longevity.

## Key facts

- **NIH application ID:** 10837845
- **Project number:** 5R01AG056440-07
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** JEFF M HASTY
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $560,533
- **Award type:** 5
- **Project period:** 2017-08-01 → 2028-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10837845

## Citation

> US National Institutes of Health, RePORTER application 10837845, Network-Driven Dynamics of Replicative Aging (5R01AG056440-07). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10837845. Licensed CC0.

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