Zigzag Generalized Lévy Walk: the In Vivo Search Strategy of Immunocytes

Abstract

Immune responses are based on the coordinated searching behaviors of immunocytes that are aimed at tracking down specific targets. The search efficiency of immunocytes significantly affects the speed of initiation and development of immune responses. Previous studies have shown that not only the intermittent walk but also the zigzag turning preference of immunocytes contributes to the search efficiency. However, among existing models describing immunocytes' search strategy, none has captured both features. Here we propose a zigzag generalized Lévy walk model to describe the search strategy of immunocytes more accurately and comprehensively by considering both the intermittent and the zigzag-turning walk features. Based on the analysis of the searching behaviors of typical immune cell types, dendritic cells and leukocytes, in their native physiological environment, we demonstrate that the model can describe the in vivo search strategy of immunocytes well. Furthermore, by analyzing the search efficiency, we find that this type of search strategy enables immunocytes to capture rare targets in approximately half the time than the previously proposed generalized Lévy walk. This study sheds new light on the fundamental mechanisms that drive the efficient initiation and development of immune responses and in turn may lead to the development of novel therapeutic approaches for diseases ranging from infection to cancer.

Liver environment-imposed constraints diversify movement strategies of liver-localized CD8 T cells

“…(S.5)); (iii) Composite models with Pareto tails, approximating Levy and Gaussian tails, with Gamma heads (eqn. (S.9)), and (iv) Convoluted model (generalized Levy walks as described previously 3,30 ), approximating Levy tails in (Pareto) runs and pauses, or observed and unobserved step-lengths), and walked the cell digitally along the sinusoidal path to the next point on the matrix, sampled the step-end coordinates at fixed time intervals. Note that we considered all movements as forward movements, as reverse movements of cells along the sinusoids were the minority in the data (about 20%, Fig.…”

“…Typical intravital imaging experiments allow to collect 3D coordinates of T cells in tissues over time, and with such data one can construct several movement characteristics to determine the type of walk cells exhibit 4,5,18,[30][31][32] . Specifically, the rate of MSD increase with time, distributions of movement lengths and turning angles often allow to determine the walk type 5,31,33 .…”

“…Specifically, the rate of MSD increase with time, distributions of movement lengths and turning angles often allow to determine the walk type 5,31,33 . Scaling the distribution of movement displacements generated for different imaging frequencies also allows to determine the type of cell walk because Levy walks-based movement distributions are thought to be relatively invariant to such rescaling 4,18,32 . Determining the walk type of T cells is important because Levy walks have been shown to be more efficient than Brownian walks in some cases suggesting that Levy walk-based strategies may be evolutionary selected [1][2][3][4]34,35 .…”

A Novel Method for Effective Cell Segmentation and Tracking in Phase Contrast Microscopic Images

“…These eukaryotic cells have different motor forms and properties, and although they are affected by different types of extracellular matrixes, the types of feet that the cells use to exercise, such as the pseudopodium, characterize their basic motility [ 9 ]. The study of these cell migration characteristics is generally conducted through probabilistic model analyses, such as persistent random walk and levy walk, by tracking the positions of cells at each interval in the images of the observed cells after several hours of taking a picture with a real-time microscope [ 7 , 10 ]. Although cell tracking is an effective method for quantitative analysis of cell migration characteristics, this requires a lot of effort and cost.…”

Dynamic visualization of the whole process of cytotoxic T lymphocytes killing B16 tumor cells in vitro

“…8,9 The migration behavior of CTLs in tumor microenvironments during ACT in vivo also has been observed by intravital imaging. 14,18,[22][23][24] Despite that there are some studies presenting the dynamic information of CTLs and tumor cells both in vitro and in vivo, the whole process of CTLs' destruction of tumor cells in vitro, especially how the CTLs specifically kill the target melanoma tumor cells has not yet been clearly revealed.…”