Cells sense their microenvironment through different mechanisms that result in rearrangement of the inner components of the cells, modulating cellular functions, and their morphology. T lymphocyte cells play a vital role in the immune responses in our body, consistently and rapidly recognizing abnormal cells, and destroying them.

This complex process whereby T cells target foreign pathogens in the body has attracted a great deal of study. Its journey begins with the migration of dendritic cells, another immune cell, to the infection site, there these cells uptake the infection as an antigen on its surface. After migrating to the lymph node, dendritic cells present these antigens to T cells, activating and educating them to sense danger. They themselves then migrate to the infection site to rid of infectious agents.

Little is known about the role, the cell microenvironment plays, in T cell behavior. One of the difficulties in understanding these mechanisms is the level of complexity of immune cells and their migratory behavior, thus requiring advanced imaging, image processing and data extraction methods, to visualize and track the cellular processes more accurately.

This study investigates the impact of different microenvironment conditions on T-lymphocyte cells. We first used a custom segmentation platform [see poster titled: Automated multi-cell segmentation and tracking from live bioimaging datasets, Author: Yanthe E. Pearson] to isolate the cells of interest and subsequently, by comparison of Euclidean distances for centroid linking, obtain their dynamic trajectories. Next, we used a morphing technique to extract the intrinsic properties of the cells. Using our approach, variant cellular variables were extracted, ranging from cell morphological parameters such as size, eccentricity, aspect ratio, migration parameters such as velocity, persistence, and directional bias, and finally intrinsic viscoelastic properties. These time variant parameters are obtained in a semi-automatic fashion and the information is vital, as there have been strong correlation relating cellular dynamics and intrinsic properties to diseases. Post analysis, through exhaustive parameter comparison, we obtain a resultant correlation matrix that potentially would allow biologists to shape a better understanding of T cells mechanisms, in response to different micro environmental stimulus.