The Effects of Chronological Age on Cell Motility upon 2D Microenvironments

Background. Aging is a physiological process characterized by an accumulation of damage and dysfunctions that increases the risk of disease^1,2. Census data indicates that the US population 65 years or older is to increase from ~16% to ~20% by 2050³. There is a need to develop robust aging biomarkers, which are encoded within the propensity of cells to move in 3D substrates, that can be used to map baseline aging trajectories and improve precision medicine^4,5,6. We hypothesize that the observed decrease in cell motility in aged cell samples is not due to a population-wide decrease in cell motility but rather from a differential redistribution of cells among distinct cell motility patterns upon 2D microenvironments.

Methods. To elucidate the notions of redistribution in cell motility states in cells during aging, we will create a high-throughput motility reference that connects distinct single-cell aging trajectories and motility characteristics. A panel of healthy human dermal fibroblasts were seeded upon Collagen-I coated plates and imaged using live-cell confocal microscopy for 8 hours. To evaluate the impact of stressors on the cell motility, senescence was induced on biological replicates of the cells and were also imaged. The movies are analyzed with commercial tracking software Metamorph and CaMI⁷. CaMI is a computational pipeline that utilizes single-cell motility data to identify and classify spatio-temporal behaviors of single cells.

Conclusion. Experiments conducted on 2D collagen surfaces have indicated the effect of aging on motility trends. Current data shows that there is a decrease in displacement of cells prior to their persistence with aging and occurs in a differential shift. We expect to gain a single-cell level analysis of the age-associated patterns of cell motility improving understanding of cellular determinants of aging and robust information regarding individual aging trajectories.

[1] Phillip, et al., Annual Review of Biomedical Engineering (2015) [2] Vigetti, et al., Journal of Biological Chemistry (2008) [3] U.S. Department of Health and Human Services (2020) [4] López-Otín, et al., Cell (2013) [5] Phillip, et al., Nature Biomedical Engineering (2017) [6] Phillip, et al., Communications Biology (2021) [7] Maity, et al., bioRxiv (2022)