MicroRNA Gene Expression States Underlying Individual Variation in Aging and Lifespan in Isogenic C. elegans
Date of Award
Doctor of Philosophy (PhD)
Average lifespan differs greatly between species, but lifespan among same-species individuals is also highly variable. While much effort has been devoted to uncovering longevity-associated traits and lifespan-extending perturbations in humans and model organisms, how differences in lifespan arise between individuals is unknown. Studies of human identical twins demonstrate that surprisingly little of the variation in lifespan between individuals can be explained by genetics and shared environment. Furthermore, even genetically identical C. elegans reared in highly homogeneous environments display a degree of variability in lifespan similar to that of outbred human populations. Thus, longevity must be determined at least in part by non-genetic, nonenvironmental processes of stochastic origin. Understanding what these processes are and how they arise may provide key insights into why some individuals live longer or age more
successfully than others.
We hypothesized that some of the variability in lifespan results from early-life stochastic differences in expression of important regulatory genes, initiating persistent gene expression states that ultimately determine lifespan and cause otherwise identical individuals to diverge on different aging trajectories. This dissertation aims most principally to prove the existence of such regulatory genes (e.g., “biomarkers of lifespan”) and characterize the resulting gene expression states that define long- and short-lived individuals in C. elegans, a model organism and workhorse in aging biology.
As described herein, the most straightforward approach to identifying biomarkers of lifespan is to first screen for genes whose expression early in life correlates with or predicts future longevity among homogenous individuals. However, this approach presents significant technical challenges. Large populations of C. elegans must be observed to generate statistically significant results, yet single-worm resolution is required to accurately measure lifespan. Lifespan measurements, which are typically taken manually through microscope observation, are laborious and subject to operator bias and technical error. In the first part of this dissertation, we describe a novel high-throughput screening platform that can identify biomarkers of lifespan from fluorescent gene expression libraries in C. elegans. This platform utilizes liquid-based culturing techniques, automated fluorescence microscopy, custom software, and modified flatbed scanners to screen thousands of individual animals in parallel. We found that our methods consistently select mir-71, a known biomarker of lifespan, as a positive hit. Furthermore, our workflow is generalizable to any number of lifespan or aging screening applications requiring high throughput.
In the second part of this dissertation, we used a high-density, single-animal culture device to examine the relationship between future lifespan and expression of 22 different microRNA (miRNA) reporters (PmiRNA::GFP) in individual C. elegans with unprecedented temporal resolution. miRNAs, short non-coding RNAs that repress translation of many target transcripts, have been identified as both positive and negative markers of future longevity in C. elegans. miRNAs do not only act as biomarkers of lifespan but also as functional determinants of longevity, promoting or antagonizing longevity in C. elegans through canonical aging pathways. We showed that expression levels of nearly half of the miRNA reporters we tested effectively predict future lifespan, indicating that long- vs. short-lived individuals are highly divergent in terms of gene regulation. These lifespan-predictive reporters represent diverse spatial and temporal expression patterns, suggesting that the regulatory states underlying long and short life are not specific to a particular tissue or a single regulatory process. We further found that the gene-regulatory processes reported on by two of the most lifespan-predictive transgenes are distinct from the insulin/insulin-like growth factor (IGF-1) signaling (IIS) pathway. Last, we demonstrated a hierarchy among several reporters expressed in different tissues, suggesting that they act as readouts of an organism-wide, cell-nonautonomous process that acts to set each individual’s lifespan.
The work presented in this dissertation improves our understanding of aging and lifespan variability among wild-type, unperturbed, and isogenic individuals, which has not been well-studied in the field. We have linked longevity to specific gene expression states among
homogenous individuals, which will provide a basis for further study into how these states arise and their functional consequences on aging and lifespan.
Tim Schedl, Michael Vahey, Stephen Pak, Barak Cohen,
Engineering Commons, Family, Life Course, and Society Commons, Genetics Commons, Gerontology Commons