Introduction: CD4 T cell subsets play pivotal roles in immune surveillance and homeostasis, but their comprehensive characterization demands exploration beyond surface receptor profiles. Our focus extends to the biophysical properties of CD4 subtypes, specifically morphology and motility, as essential measurements to probe immune functions. Aging induces significant changes in the biophysical properties of CD4 subsets, both in differentiation and behaviors, necessitating a deeper understanding of aging mechanisms2. This approach holds promise for cellular reprogramming, biological insight, and potentially redefining CD4 subtypes entirely. By integrating biophysical signatures with immunological profiling, we aim to elucidate the intricate interplay between cellular mechanics and immunophenotypes. This approach will not only enables a comprehensive understanding of CD4 T cell biology but could sheds light on the interconnections between aging, immune dysfunction, and chronic diseases. Moreover, our investigation seeks to delineate age-associated alterations in CD4 subtype behavior and differentiation, offering insights into the nuanced dynamics of the aging immune landscape. Through this interdisciplinary lens, we anticipate uncovering novel mechanisms underlying CD4 T cell aging and identifying potential targets for interventions aimed at preserving immune homeostasis in aging individuals. In summary, this endeavor represents a paradigm shift in the study of T cell biology, emphasizing the integration of biophysical metrics with immunological profiling to decode the complexities of CD4 subtype dynamics in aging.
Materials and
Methods: We have developed a novel multi-disciplinary approaches (Figure 1) to reveal a fundamental understanding of how functional T cell behaviors change during aging, and identify putative drivers of T cell behaviors. The proposed work will be conducted utilizing isolated T cells sourced from multiple murine donors. These diverse cell populations were cultured in a 1mg/mL Type 1 collagen hydrogel at a density of 20,000 cells per well in 96 well plates and allowed to settle. Utilizing 40X magnification, we captured images of the cells every 2 minutes for a minimum of 4 hours. The acquired frames were subjected to segmentation using either CellProfiler or CellPose, and subsequently, masks were tracked to extract features from individual cells. Cell trajectories were divided into 40-minute intervals, and these intervals underwent comprehensive dynamic analysis. Leveraging information on cell motility, average morphology, and morphology changes over the trajectory (morphodynamics), we employed K-MEANS clustering. Collaborative efforts with experts in the field of immunology will facilitate access to differentiated T cell populations. Subsequently, these cells have undergone rigorous examination through time-lapse microscopy imaging, followed by comprehensive profiling utilizing state-of-the-art single-cell behavioral analysis technology recently developed in our lab for this purpose. These findings are to be validated for their reprogramming potential.
Results, Conclusions, and Discussions: So far, we have successfully isolated naïve CD4 cells from multiple mouse donors, along with CD8 naïve, in-vitro-generated memory-like, effector, central memory, and tissue resident memory cells, obtained across multiple young and old mouse populations. Instructivfe signals efficiently differentiated these subtypes as confirmed with flow cytometry, and unique morphological and translocative properties were observed between some subsets. Interestingly, distinct clustering patterns emerged based on cell subtype, such as Th0, Th1, Th2, and so forth. Our findings reveal the considerable potential of utilizing biophysical parameters alone to discern cell state, fate, and behavior. Next steps include replication of these baseline characterizations, introducing perturbations through supplemented media when hydrating the gels, and differentiation from naïve states to provide a platform for investigating the influence of external factors on intrinsic cellular properties and phenotypes. These results lay the foundation for further exploration into the dynamic interplay between biophysical cues and cellular behaviors.
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