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A platform for rapidly mapping the molecular and systemic dynamics of aging

Periodic Reporting for period 2 - SYSAGING (A platform for rapidly mapping the molecular and systemic dynamics of aging)

Reporting period: 2021-07-01 to 2022-12-31

Over the last century, preventative approaches have been dramatically more effective than therapeutics at reducing the societal burden of disease. Historic killers such as smallpox, polio, and tuberculosis were beaten not by new therapies, but by vaccines and sanitation improvements that eliminated the context in which infectious diseases flourished. For today’s biggest killers, cardiovascular disease, cancer, and diabetes, we have only the most basic preventative measures. Our best advice—eat well and exercise—would be familiar to doctors in ancient Greece. To continue last century's progress in improving human health, we need to develop better preventative strategies against age-related diseases. We need to identify and disrupt the physiologic processes that, throughout life, increase the risk of disease.

Yet, age-related diseases are difficult to prevent because they have many causes, arising from a complex interaction between many genes, diet, and environment. It is increasingly clear that most age-related diseases do not arise from a linear chain of events involving a small number of molecules. Instead, age-related diseases emerge from interactions among large networks of genes, influenced by environmental factors, whose cumulative contribution throughout life determines the risk of falling ill. To study the complex interaction between many causal factors that contribute to disease risk, we need new methods capable of measuring high-dimensional dynamics of physiologic change during aging.

In this project, we develop an integrative platform combining transcriptomic profiling, in vivo biosensors, and new imaging technology. To collect data across multiple spatial scales—molecules, cells, individuals, and populations—we pursue three objectives: 1) to develop a set of transcriptomic and functional genetic approaches to study how gene regulation is altered by age, 2) to develop new imaging and vermiculture approaches for studying age-associated changes in behavior and lifespan 3) to characterize the effect of lifespan-extending interventions on age-associated changes in gene regulation and lifespan to better understand the relationship between the two.

This project is designed to clarify the relationship between the aging dynamics at the molecular level and aging dynamics at the organismal-level. Combining molecular genetics with theoretic approaches, we build quantitative models of how complex diseases emerge from slow molecular-level changes, making methodological progress toward rapid characterization of the determinants of age-associated diseases.
Our team has made substantial progress on each of the main objectives of the proposal. First, we have developed an optimized single-nematode transcriptomic approach based on Smart-Seq2 protocols, scaling down existing nematode transcriptomic protocols that previously required thousands of individuals to perform well on single nematodes. We have applied this method in a series of collaborative projects leading to publications and most recently we have applied it to measure the effect of aging on gene activity distributions ( GADS ) as described in the project proposal. From single nematode data, we find that we are able to build co-expression networks of genes that change together during aging. These co-expression networks allow us to perform de novo discovery of causal physiologic interactions, which we have validated in a large RNAi screen. Originally, we had imagined such analysis would be possible only using time series of GAD distributions, but we find physiologic interactions can be identified using single, cross-sectional measurements of aging populations. This is possible because of the asynchronous nature of aging, such that in an aged population chronologically synchronized individuals are physiologically non-synchronous, such that some individuals are physiologically older than others. This heterogeneity in respect to aging allows us to identify genes that co-vary in aging from a single cross-sectional population—a much faster protocol than longitudinal, time-series measurements. Our manuscript describing this method, which we call “Asynch-Seq”, is currently in review.

The second objective of our ERC project involves the development of a new nematode imaging and culturing system for studying aging under tightly controlled environmental conditions. We have developed a miniaturized and simplified pump and liquid handling system that allows us to scale up our microfluidic studies, allowing us to observe several microfluidic chips using a single imaging device. Importantly, the new approach solves the technical limitation we encountered, in which air bubbles gradually accumulate in microfluidic devices over the course of measurement. Also as part of the second objective, we have developed and publically released a new version of our image analysis platform that can simultaneously measure the behavioral aging and lifespan across populations of C. elegans. We focused on a specific aspect of behavior that is robustly measured by our imaging approach: the cessation of vigorous movement. Animals cease moving vigorously several days before death, and we reasoned that relating the timing of these two events allows us to better study the dynamics of aging. A manuscript describing this work entitled “A Hierarchical Process Model Links Behavioral Aging and Lifespan in C. elegans” has recently been accepted for publication in PLoS Computational Biology.

The third objective of our ERC project focuses on using genetic and environmental interventions that alter lifespan to study the dynamics of aging. In particular, our project involves generating a multi-scale atlas describing the molecular and phenotypic effects of lifespan-extending interventions in aging. In the early stages of the project, we identified a potential confounding factor present in our original approach: the genetic variants that affect lifespan also tend to affect developmental processes. We became concerned that some aspects of our time-series approach might conflate the effects of interventions on aging with the effects of interventions on development. Therefore, we persued an alternative to genetically-encoded mutants for altering lifespan, reasoning that the auxin-inducible degron (AID) system could be used to intervene in aging only during adulthood, degrading target proteins only after development has ended. Whereas in the project proposal we had suggested that the AID system only be used to validate targets, we have subsequently found that we can deploy the AID system to collect a much more robust multi-scale atlas, an atlas un-confounded by developmental effects. We have generated a set of AID-tagged proteins important in aging which we find to robustly alter lifespan. We have already used this AID line to collect a high-resolution transcriptomic time series, and we will use them in our Asynch-Seq analyses as well. The added advantage of our modified protocol is that the AID system allows us to consider not just a single “dosage” of an intervention, comparing a long-lived mutant population to a wild-type population, but a wide range of lifespans obtained by varying the degree of gene knockdown using a range of auxin concentrations. This graduated approach has already been validated in our “Hierarchical Process model” manuscript and we will be writing up the results of our work an additional manuscript that we expect to pre-print in the second half of 2022.
Finally, during this reporting period we have established in our laboratory a rapid CRISPR genome editing pipeline. The adoption of CRISPR techniques in the lab has been a resounding success, and we can now produce two to four AID-tagged transgenic nematode lines a month. This genome-editing pipeline will crucially support our target-validation efforts during future reporting periods.
We continue to pursue the project goals as outlined in the proposal, applying our methods to characterize a variety of genetic and environmental perturbations to aging. This work moves beyond the state of the art by 1) developing and validating a new single-nematode transcriptomic approach 2) developing and validating an approach for mapping physiologic networks in aging using population asynchrony, which we call “Asynch-Seq” as described in the previous section 3) Application of our new vermiculture system for measuring movement and lifespan at large scale using our automated imaging system 4) assembling a multi-scale atlas of interventions in aging.