# MOLECULAR MECHANISMS OF NATURAL LIFESPAN VARIATION

> **NIH NIH K01** · VIRGINIA COMMONWEALTH UNIVERSITY · 2020 · $128,703

## Abstract

MOLECULAR MECHANISMS OF NATURAL LIFESPAN VARIATION
Which genes and gene networks are responsible of causing (or retarding) the aging process? Which of these
components can be manipulated to maximize lifespan? Despite the fundamental nature of these questions, we
have very limited understanding of the cellular mechanisms governing aging. From this perspective, our
overarching goal is to apply systems biology approaches to construct a molecular network of longevity, based
on multi-omics datasets from 87 natural yeast isolates. Yeast offers a rich resource of available genetic and
molecular tools as well as established experimental paradigms for characterizing mechanisms of aging and
longevity, and its interaction networks have been previously constructed. Towards this goal, we have
generated three important sets of preliminary data. First, we evaluated replicative lifespan (RLS) of 87 natural
isolates under three metabolic conditions and uncovered a wide diversity of natural variation in aging. Second,
we sequenced the genomes of these strains to characterize their genetic diversity. Third, we found that dietary
restriction and activation of mitochondrial respiration extend lifespan in some genotypes, while in others there
is no response at all. Based on this data we will test the hypothesis that genetic variation and
environmental factors coordinately regulate components of the transcriptional, translational and
metabolic machinery, generating variation in dietary response and aging. Application of data integration
methods to multiple omics resources will facilitate the discovery of underlying biological processes associated
with longevity. We will test this hypothesis in the following Specific Aims: 1) Analyze transcriptomes,
translatomes and metabolomes to link variation in these ‘endo-phenotypes’ to external ‘aging phenotypes’
under different metabolic conditions known to modulate lifespan. 2) Integrate the findings of -omics data and
identify regulatory networks of lifespan control. This innovative approach of data aggregation and processing,
multidimensional data analysis and network-based methods will aid in conceptualizing the molecular
mechanisms that underlie natural variation of aging and aging-related perturbations at an unprecedented scale
and level of detail. Finally, these studies will identify general trends in lifespan control by leveraging our
extensive experience in systems approaches of life history of traits of more complex organisms. The
application proposes a program for expanded training with established mentor and two co-mentors in network,
systems, and computational biology to facilitate the PI's development into an independent investigator focusing
on basic biology of aging. The experience, knowledge, and skills gained through the research plan and career
development activities will carry the candidate forward towards a career as an independent investigator.

## Key facts

- **NIH application ID:** 10002117
- **Project number:** 5K01AG060040-02
- **Recipient organization:** VIRGINIA COMMONWEALTH UNIVERSITY
- **Principal Investigator:** Alaattin Kaya
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $128,703
- **Award type:** 5
- **Project period:** 2019-09-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10002117

## Citation

> US National Institutes of Health, RePORTER application 10002117, MOLECULAR MECHANISMS OF NATURAL LIFESPAN VARIATION (5K01AG060040-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10002117. Licensed CC0.

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