Biology subjects

Torres, D. J.

Publications and source records attributed to Torres, D. J..

3 recordsLinked to original sources

bioRxiv2022

Quantitative analyses of T cell motion in tissue reveals factors driving T cell search in tissues

T cells are required to clear infection, moving first in lymph nodes to interact with antigen bearing dendritic cells leading to activation. T cells then move to sites of infection to find and clear infection. T cell motion plays a role in how quickly a T cell finds its target, from initial naive T cell activation by a dendritic cell to interaction with target cells in infected tissue. To better understand how different tissue environments might affect T cell motility, we compared multiple features of T cell motion including speed, persistence, turning angle, directionality, and confinement of motion from T cells moving in multiple tissues using tracks collected with microscopy from murine tissues. We quantitatively analyzed naive T cell motility within the lymph node and compared motility parameters with activated CD8 T cells moving within the villi of small intestine and lung under different activation conditions. Our motility analysis found that while the speeds and the overall displacement of T cells vary within all tissues analyzed, T cells in all tissues tended to persist at the same speed, particularly if the previous speed is very slow (less than 2 {micro}m/min) or very fast (greater than 8 {micro}m/min) with the exception of T cells in the villi for speeds greater than 10 {micro}m/min. Interestingly, we found that turning angles of T cells in the lung show a marked population of T cells turning at close to 180o, while T cells in lymph nodes and villi do not exhibit this "reversing" movement. Additionally, T cells in the lung showed significantly decreased meandering ratios and increased confinement compared to T cells in lymph nodes and villi. The combination of these differences in motility patterns led to a decrease in the total volume scanned by T cells in lung compared to T cells in lymph node and villi. These results suggest that the tissue environment in which T cells move can impact the type of motility and ultimately, the efficiency of T cell search for target cells within specialized tissues such as the lung.

immunology↗

bioRxiv2022

CXCR4 controls movement and degranulation of CD8+ T cells in the influenza-infected lung via differential effects on interaction and tissue scanning

Effector CD8+ T cell interactions are critical in controlling viral infection by directly killing infected cells but overabundant or sustained activation also exacerbates tissue damage. Chemokines promote the trafficking of effector CD8+ T cells into infected tissues, but we know little about how chemokines regulate the function of CD8+ T cells within tissues. Using a murine model of influenza A virus infection, we found that expression of the chemokine receptor CXCR4 by lung-infiltrating cytotoxic T cells correlated with the expression of the degranulation marker CD107a. Inhibition of CXCR4 reduced activation, adhesion, and degranulation of cytotoxic T cells in vitro and in vivo. Moreover, in live influenza-infected lung tissue, T cells stopped moving in lung regions with high levels of influenza antigen, and CXCR4 was essential for CD8+ T cells to execute this arrest signal fully. In contrast, CXCR4 increased the motility of CD8+ T cells in low-influenza areas of the lung. We also found that CXCR4 stimulated the effector function of lung-infiltrating cytotoxic T cells even after clearance of influenza virus, and inhibition of CXCR4 expedited the recovery of influenza-infected mice, despite delayed clearance of the replication-competent virus. Our results suggest that CXCR4 promotes the interaction strength of cytotoxic T cells in lung tissue through combined effects on T cell movement and interaction with virally infected target cells in influenza infected-lungs.

immunology↗

bioRxiv2021

Linear regression of sampling distributions of the mean

We show that the simple and multiple linear regression coefficients and the coefficient of determination R2 computed from sampling distributions of the mean (with or without replacement) are equal to the regression coefficients and coefficient of determination computed with individual data. Moreover, the standard error of estimate is reduced by the square root of the group size for sampling distributions of the mean. The result has applications when formulating a distance measure between two genes in a hierarchical clustering algorithm. We show that the Pearson R coefficient can measure how differential expression in one gene correlates with differential expression in a second gene.

bioinformatics↗