Biology subjects

Zenkov, V. S.

Publications and source records attributed to Zenkov, V. S..

3 recordsLinked to original sources

bioRxiv2025

Liver sinusoid constraints make random search of CD8 T cells for Plasmodium parasites efficient

A relatively small number of liver-localized CD8 T cells can provide sterilizing protection against exposure to Plasmodium sporozoites. Previously published mathematical model-based simulations of randomly searching for an infection T cells, assuming that T cells move in open (3D) space or on a regular lattice, suggested that some degree of attraction is needed for cells to find the infection. Yet, in our previous experiments we failed to find evidence of attraction towards the infection in most T cells. Because the movement of liver-localized T cells is confined to sinusoids, the blood vessels of the liver, T cells may in fact be attracted to the infection site via the sinusoids. In new experiments we imaged Plasmodium-specific CD8 T cells, sporozoites, and liver sinusoids simultaneously. We also developed a new method to model imaged sinusoids as graphs and to simulate movement of T cells on graphs, and new tests to detect biased cell movement on graphs. As before, our previously published open space/3D-based metric suggested that few T cells are attracted to the infection site in presence of moderate cluster of T cells. However, with our new graph-based metric we could not detect attraction when constraining T cell movement to sinusoids. Surprisingly, simulations of T cells searching for an infection via liver sinusoids showed that a relatively small number of T cells (1 cell/imaging volume or <10^5 cell/liver), moving without attraction at experimentally observed speeds, is sufficient to find the infection within 24 hours, well below the expected lifespan of the Plasmodium liver stage in mice. Our results suggest that the constrained environment of the tissue structure makes a random search more effective, and that detecting T cell attraction towards specific areas may arise as an artifact of metrics designed for open space/3D. Our results thus call for a re-evaluation of the implicit assumption that attraction is necessary for T cells to find infections in tissues.

immunology↗

bioRxiv2021

Negative correlation between average speed and average turning angle naturally arises for sparsely sampled cell movement data

Mechanisms regulating cell movement are not fully understood. One feature of cell movement that determines how far cells displace from an initial position is persistence, the ability to perform movements in a direction similar to the previous movement direction. Persistence is thus determined by turning angles between two sequential displacements and be characterized by an average turning angle or persistence time. Recent studies found that a cells average speed and turning are negatively correlated, suggesting a fundamental cell-intrinsic program whereby cells with a lower turning ability (i.e., larger persistence time) are intrinsically faster (or faster cells turn less). By simulating correlated or persistent random walks (PRWs) using two different frameworks (one based on von Mises-Fisher (vMF) distribution and another based on Ornstein-Uhlenbeck (OU) process) we show that the negative correlation between speed and turning naturally arises when cell trajectories are sub-sampled, i.e., when the frequency of sampling is lower than frequency at which cells make movements. This effect is strongest when the sampling frequency is on the order of magnitude with the typical cell persistence time and when cells vary in persistence time. Both conditions are observed for datasets of T cell movements in vivo that we have analyzed. In simulations the correlation arises due to randomness of cell movements resulting in highly variable persistence times for individual cells that with sub-sampling leads to large variability of average cell speeds. Interestingly, previously suggested methodology of calculating displacement of cell cohorts with different speeds resulted in similar results whether or not there is a cell-intrinsic correlation between cell speed and persistence. For both vMF- and OU-based simulations of PRWs we could find parameter values (distribution of persistence times, speeds, and sampling frequency) that matched experimentally measured correlations between speed and turning for two datasets of T cell movement in vivo suggesting that such simple correlations are not fully informative on the intrinsic link between speed and persistence. Our results thus suggest that sub-sampling may contribute to (and perhaps fully explains) the observed correlation between speed and turning at least for some cell trajectory data and emphasize the role of sampling frequency in inference of critical cellular parameters of cell motility such as speeds. Secondary AbstractMeasurement of cell movements often results in a negative correlation between average speed and average turning angle suggesting an existence of a universal, cell-intrinsic movement program. We show that such a negative correlation may arise if cells in the population differ in their ability for persistent movement when the movement data are sub-sampled. We show that sub-sampling of cell trajectories generated using two different frameworks of persistent random walk can match the experimentally observed correlation between speed and turning for T cell movements in vivo.

immunology↗

bioRxiv2020

A minority of liver-localized CD8 T cells demonstrate difficult-to-detect attraction to Plasmodium-infected hepatocytes

Malaria is a disease caused by Plasmodium parasites, resulting in over 200 million infections and 400,000 deaths every year. A critical step of malaria infection is when sporozoites, injected by mosquitoes, travel to the liver and form liver stages. Malaria vaccine candidates which induce large numbers of malaria-specific CD8 T cells in mice are able to eliminate all liver stages, preventing fulminant malaria. However, how CD8 T cells find all parasites in 48 hours of the liver stage lifespan is not well understood. Using intravital microscopy of murine livers, we generated unique data on T cell search for malaria liver stages within a few hours after infection. To detect attraction of T cells to an infection site, we used the von Mises-Fisher distribution in 3D, similar to the 2D von Mises distribution previously used in ecology. Our results suggest that the vast majority (70-95%) of malaria-specific and non-specific liver-localized CD8 T cells did not display attraction towards the infection site, suggesting that the search for malaria liver stages occurs randomly. However, a small fraction (15-20%) displayed weak but detectable attraction towards parasites which already had been surrounded by several T cells. We found that speeds and turning angles correlated with attraction, suggesting that understanding mechanisms that determine the speed of T cell movement in the liver may improve the efficacy of future T cell-based vaccines. Stochastic simulations suggest that a small movement bias towards the parasite dramatically reduces the number of CD8 T cells needed to eliminate all malaria liver stages, but to detect such attraction by individual cells requires data from long imaging experiments which are not currently feasible. Importantly, as far as we know this is the first demonstration of how activated/memory CD8 T cells might search for the pathogen in nonlymphoid tissues a few hours after infection. We have also established a framework for how attraction of individual T cells towards a location in 3D can be rigorously evaluated.

immunology↗