Novel Strategy to Quantitate Delayed Aging by Caloric Restriction

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PROJECT SUMMARY Aging is associated with causal epigenetic changes that occur throughout the genome, as first shown in yeast and worms. DNA methylation clocks identify CpG sites in human blood and other tissues with age-dependent changes. All such clocks depend on linear regression algorithms or deep learning to select CpGs methylation sites with levels that best fit chronological age; the deviation from the linear regression prediction of chronologi- cal age for each individual is considered, by some, a measure of biological age. Such computation of biological age has several limitations. We developed novel approach “Microscopic Imaging of Epigenetic Landscapes” (MIEL)-clock, which is rooted in the analysis of epigenome topography at the single cell level to measure age- dependent signature of chromatin landscape. MIEL captures patterns of nuclear staining of epigenetic marks and employs automated microscopy and machine learning to determine multiparametric signature of cellular state. We provide preliminary evidence for the power of MIEL-clock to successfully distinguish several types of young and old cells in mice and man. Our preliminary experiments using Doxorubicin (DOX) treatment, and Caloric Restriction (CR) indicate that MIEL-clock successfully detects acceleration of aging after DOX treat- ment and slowdown of aging after CR diet. Because CR robustly and consistently increases maximum lifespan and delays biological aging in diverse species, successfully applied CR regimen serves as an incomparable research tool for understanding the biology of aging. Here we propose to employ CR regimens to determine the power of MIEL-clock to quantitate slowdown of aging process and to directly compare and contrast MIEL- clock, RNA-seq and ATAC-seq signatures of liver hepatocytes in CR and control mice. With the caveat that one-size does not fit all, a diet optimized for genetic background and sex can be applied to beneficially impact healthspan and longevity. Given the composition of our study, completion of Specific Aims will yield a unique dataset directly comparing MIEL-clock to the classical genomic readouts of CR paradigm. The latter constitute a rich data pool for molecular mining of age-associated changes and will serve to corroborate the utility of MIEL-clock as a simple, cost effective, high throughput single-cell readout and screening platform for evaluat- ing dietary interventions with potential to slow down the aging process and identifying small molecules mimet- ics of CR.