Technologies to probe the biophysical properties of aging cells - SUMMARY: The physical properties of the cell interior are crucial for the organization and efficiency of biochemical reactions. The highly crowded and non-thermodynamically equilibrated cellular environment can both enhance binding, and impede particle motion, thereby altering the efficiency of biochemical reactions. These effects are particularly pronounced at the mesoscale (10 - 1000 nm), where metabolic and mechanical perturbations can lead to dramatic changes, including transitions to a glassy, solid-like state. These mesoscale biophysical properties also change during normal development, cancer progression, and aging; therefore, it is increasingly imperative to uncover both the mechanisms that control these properties, and physiological consequences of perturbations to them. It is also of great interest to define these properties in organelles including the nucleus, cytoplasm, endoplasmic reticulum and mitochondria. However, this understanding has been hampered by a lack of reliable and high-throughput tools. Our approach to solving this issue involves the use of microrheology, which is the inference of the physical properties of the cell interior from the motion of probe particles. The previous gold-standards were inorganic particles like Q - dots. However, introducing these particles into cells is low-throughput, damaging, and largely ineffective in organisms with cell walls. To overcome this problem, we have developed self-assembling, Genetically Encoded Multimeric particles (GEMs) that massively increase the efficiency and reproducibility of microrheology experiments. We benchmarked GEMs against gold-standard Q- dots and confirmed that they are better, more passive probes for the cytoplasm and nucleoplasm. GEMs are permanently present in cells after inserting the encoding gene, and transform microrheology into a reliable, high-throughput approach. We have developed and validated an initial set of GEMs with diameters of 20 and 40 nm, and targeted them to the cytoplasm and nucleus. This project comprises three aims: 1. Expanding GEM technology (size, color, and surface properties) to enhance versatility and applicability. 2. Targeting GEMs to previously inaccessible organelles, such as the endoplasmic reticulum and mitochondria. 3. Applying GEM technologies to diverse tissues and cell types in animal models of aging. Additionally, we are committed to advancing software tools for data analysis and GEM detection, incorporating machine learning techniques for enhanced efficiency. By investigating an almost entirely unexplored parameter in animal models of aging, this project seeks to discover mechanisms controlling cellular biophysical properties and the consequences of age-related biophysical perturbations. Ultimately, these findings may enable discovery of mechanisms to correct biophysical perturbations, thereby providing a new avenue towards therapeutics that address age-related diseases.
