Biology subjects

Losert, W.

Publications and source records attributed to Losert, W..

27 records · Page 2Linked to original sources

bioRxiv2021

Spontaneous polarization and cell guidance on asymmetric nanotopography

Asymmetric nanotopography with sub-cellular dimensions has recently been demonstrated to be able to provide a unidirectional bias in the migration of cells. The details of this guidance depend both on the type of cell studied and the design of the nanotopography. This behavior is not yet well understood, so there is a pressing need for a predictive description of cell migration on such nanotopography that captures both the initiation of migration and the manner in which cell migration evolves. Here, we employ a three-dimensional, physics-based model to study cell guidance on asymmetric nanosawteeth. In agreement with experimental data, our model predicts that asymmetric sawteeth lead both to spontaneous motion and changes in motion phenotypes. Our model demonstrates that asymmetric nano-sawteeth induce a unidirectional bias in guidance direction that is dependent upon the actin polymerization rate and the sawtooth dimensions. Motivated by this model, an analysis of previously reported experimental data indicates that the degree of guidance by asymmetric nanosawteeth increases with the cell velocity.

biophysics↗

bioRxiv2021

Actin dynamics as a multiscale integrator of cellular guidance cues

Cells are able to integrate multiple, and potentially competing, cues to determine a migration direction. For instance, in wound healing, cells follow chemical signals or electric fields to reach the wound edge, regardless of any local guidance cues. To investigate this integration of guidance cues, we monitor the actin-polymerization dynamics of immune cells in response to cues on a subcellular scale (nanotopography) and on the cellular scale (electric fields, EFs). In the fast, amoeboid-type migration, commonly observed in immune cells, actin polymerization at the cells leading edge is the driver of motion. The excitable systems character of actin polymerization leads to self-propagating, two-dimensional wavefronts that enable persistent cell motion. We show that EFs guide these wavefronts, leading to turning of cells when the direction of the EF changes. When nanoridges promote one-dimensional (1D) waves of actin polymerization that move along the ridges (esotaxis), EF guidance along that direction is amplified. 1D actin waves cannot turn or change direction, so cells respond to a change in EF direction by generating new 1D actin waves. At the cellular scale, the emergent response is a turning of the cell. For nanoridges perpendicular to the direction of the EF, the 1D actin waves are guided by the nanotopography, but both the average location of new actin waves and the whole cell motion are guided by the EF. Thus, actin waves respond to each cue on its intrinsic length scale, allowing cells to exhibit versatile responses to the physical microenvironment. Significance StatementEffective cell migration requires the integration of multiple, and sometimes competing, guidance cues. For instance, in wound healing, immune cells are guided towards a wound edge by long-range electrical and chemical cues that may conflict with guidance cues from the local environment. How cells combine and respond to such cues is not well understood. We demonstrate that multiple guidance mechanisms can act simultaneously, but on different scales. Nanotopography, a local mechanical cue, guides individual waves of actin polymerization, thereby biasing the direction cell motion on the time scale of these waves. An external electric field applied at the same time biases the locations of new waves of actin polymerization, leading to overall directed migration over long distance scales.

biophysics↗

bioRxiv2020

The social shape of sperm: Using an integrative machine-learning approach to examine sperm ultrastructure and collective motility

Sperm are one of the most morphologically diverse cell types in nature, yet they also exhibit remarkable behavioral variation, including the formation of collective groups of cells that swim together for motility or transport through the female reproductive tract. Here we take advantage of the natural variation in sperm traits observed across Peromyscus mice to test the hypothesis that the morphology of the rodent sperm head influences their sperm aggregation behavior. Using machine learning and traditional morphometric approaches to quantify and analyze their complex shapes, we show that the elongation of the sperm head is the most distinguishing morphological trait in these rodents and, as predicted, significantly associates with collective sperm movements obtained from in vitro observations. We then successfully use neural network analysis to predict the size and proportion of sperm aggregates from sperm head morphology and show that species whose sperm feature relatively wider heads aggregate more often and form larger groups, providing support for the theoretical prediction that an adhesive region around the equatorial region of the sperm head mediates these unique gametic interactions. Together these findings advance our understanding of how even subtle variation in sperm design can drive differences in sperm function and performance. Subject AreasEvolution, Cellular Biology, Behavior

evolutionary biology↗

bioRxiv2020

Distinct Roles of Tumor-Associated Mutations in Collective Cell Migration

Recent evidence suggests that groups of cells are more likely to form clinically dangerous metastatic tumors, emphasizing the importance of understanding mechanisms underlying collective behavior. The emergent collective behavior of migrating cell sheets in vitro has been shown to be disrupted in tumorigenic cells but the connection between this behavior and in vivo tumorigenicity is unclear. Here we use particle image velocimetry to measure a multi-dimensional collective migration phenotype for genetically defined cell lines that range in their in vivo behavior from non-tumorigenic to aggressively metastatic. By using cells with controlled mutations, we show that PTEN deletion enhances collective migration, while Ras activation suppresses it, even when combined with PTEN deletion. These opposing effects on collective migration phenotype of two mutations that are frequently found in patient tumors could be exploited in clinical assessments of metastatic potential or in the development of novel treatments for metastatic disease.

biophysics↗

bioRxiv2020

Signaling through polymerization and degradation: Analysis and simulations of T cell activation mediated by Bcl10

The adaptive immune system serves as a potent and highly specific defense mechanism against pathogen infection. One component of this system, the effector T cell, facilitates pathogen clearance upon detection of specific antigens by the T cell receptor (TCR). A critical process in effector T cell activation is transmission of signals from the TCR to a key transcriptional regulator, NF-{kappa}B. The transmission of this signal involves a highly dynamic process in which helical filaments of Bcl10, a key protein constituent of the TCR signaling cascade, undergo competing processes of polymeric assembly and macroautophagy-dependent degradation. Through computational analysis of three-dimensional super-resolution microscopy data, we quantitatively characterized TCR-stimulated Bcl10 filament assembly and length dynamics, demonstrating that filaments become shorter over time. Additionally, we developed an image-based bootstrap-like resampling method to quantitatively demonstrate preferred association between autophagosomes and Bcl10-filament ends and punctate-Bcl10 structures, implying that autophagosome-driven macroautophagy is directly responsible for Bcl10 filament shortening. We probe Bcl10 polymerization-depolymerization dynamics with a stochastic Monte-Carlo simulation of nucleation-limited filament assembly and degradation, and we show that high probabilities of filament nucleation in response to TCR engagement could provide the observed robust, homogeneous, and tunable response dynamic. Furthermore, the speed of autophagic degradation of filaments preferentially at filament ends provides effective regulatory control. Taken together, these data suggest that Bcl10 filament growth and degradation act as an excitable system that provides a digital response mechanism and the reliable timing critical for T cell activation and regulatory processes. Author SummaryThe immune system serves to protect organisms against pathogen-mediated disease. While a strong immune response is needed to eliminate pathogens in host organisms, immune responses that are too robust or too persistent can trigger autoimmune disorders, cancer, and a variety of additional serious human pathologies. Thus, a careful balance of activating and inhibitory mechanisms are necessary to prevent detrimental health outcomes of immune responses. For example, activated effector T cells marshal the immune response and direct killing of pathogen-infected cells; however, effector T cells that are chronically activated can damage and destroy healthy tissue. Here, we study an important internal activation pathway in effector T cells that involves the growth and counterbalancing degradation (via a process called macroautophagy) of filamentous cytoplasmic signaling structures. We utilize image analysis of 3-D super-resolution images and Monte Carlo simulations to study a key signal-transduction protein, Bcl10. We found that the speed of filament degradation has the greatest effect on the magnitude and duration of the response, implying that pharmaceutical interventions aimed at macroautophagy may have substantial impact on effector T cell function. Given that filamentous structures are utilized in numerous immune signaling pathways, our analysis methods could have broad applicability in the signal transduction field.

biophysics↗

bioRxiv2019

Quantifying topography-guided actin dynamics across scales using optical flow

Periodic surface topographies with feature sizes comparable to those of in vivo collagen fibers are used to measure and compare actin dynamics for two representative cell types that have markedly different migratory modes and physiological purposes: slowly migrating epithelial MCF10A cells and polarizing, fast migrating, neutrophil-like HL60 cells. Both cell types exhibit reproducible guidance of actin waves (esotaxis) on these topographies, enabling quantitative comparisons of actin dynamics. We adapt a computer-vision algorithm, optical flow, to measure the directions of actin waves at the submicron scale. Clustering the optical flow into regions that move in similar directions enables micron-scale measurements of actin-wave speed and direction. Although the speed and morphology of actin waves differ between MCF10A and HL60 cells, the underlying actin guidance by nanotopography is similar in both cell types at the micron and sub-micron scales.

biophysics↗

bioRxiv2018

RefCell: Multi-dimensional analysis of image-based high-throughput screens based on ‘typical cells’

BackgroundImage-based high-throughput screening (HTS) reveals a high level of heterogeneity in single cells and multiple cellular states may be observed within a single population. Cutting-edge high-dimensional analysis methods are successful in characterizing cellular heterogeneity, but they suffer from the \"curse of dimensionality\" and non-standardized outputs.\n\nResultsHere we introduce RefCell, a multi-dimensional analysis pipeline for image-based HTS that reproducibly captures cells with typical combinations of features in reference states, and uses these \"typical cells\" as a reference for classification and weighting of metrics. RefCell quantitatively assesses the heterogeneous deviations from typical behavior for each analyzed perturbation or sample.\n\nConclusionsWe apply RefCell to the analysis of data from a high-throughput imaging screen of a library of 320 ubiquitin protein targeted siRNAs selected to gain insights into the mechanisms of premature aging (progeria). RefCell yields results comparable to a more complex clustering based single cell analysis method, which both reveal more potential hits than conventional average based analysis.

bioinformatics↗

bioRxiv2018

CytoBinning: immunological insights from multi-dimensional data

New cytometric techniques continue to push the boundaries of multi-parameter quantitative data acquisition at the single-cell level particularly in immunology and medicine. Sophisticated analysis methods for such ever higher dimensional datasets are rapidly emerging, with advanced data representations and dimensional reduction approaches. However, these are not yet standardized and clinical scientists and cell biologists are not yet experienced in their interpretation. More fundamentally their range of statistical validity is not yet fully established. We therefore propose a new method for the automated and unbiased analysis of high-dimensional single cell datasets that is simple and robust, with the goal of reducing this complex information into a familiar 2D scatter plot representation that is of immediate utility to a range of biomedical and clinical settings. Using publicly available flow cytometry and mass cytometry datasets we demonstrate that this method (termed CytoBinning), recapitulates the results of traditional manual cytometric analyses and leads to new and testable hypotheses.

bioinformatics↗

bioRxiv2017

Particle Tracking facilitates real time Motion Compensation in 2D or 3D two-photon imaging of neuronal activity

The application of 2-photon laser scanning microscopy (TPLSM) techniques to measure the dynamics of cellular calcium signals in populations of neurons is an extremely powerful technique for characterizing neural activity within the central nervous system. The use of TPLSM on awake and behaving subjects promises new insights into how neural circuit elements cooperatively interact to form sensory perceptions and generate behavior. A major challenge in imaging such preparations is animal and tissue movement, which leads to shifts in the imagine location (jitter). Although there are surgical and technical approaches to minimize brain motion under these conditions, it is generally unavoidable. The presence of image motion can lead to artifacts, especially since quantification of TPLSM images involves analysis of fluctuations in fluorescence intensities for each neuron, determined from small regions of interest (ROIs) Here, we validated a new motion correction approach to compensate for motion of TPLSM images in the superficial layers of auditory cortex of awake mice. We use a nominally uniform fluorescent signal as a secondary signal to complement the dynamic signals from genetically encoded calcium indicators. We tested motion correction for single plane time lapse imaging a; well as multiplane (i.e. volume) time lapse imaging of cortical tissue. Our procedure of motion compensation relies on locating the brightest neurons and tracking their positions over time using established techniques of particle finding and tracking. The performance of our techniques both for 2D (single plane) and 3D (volume) image sequences is comparable to established techniques in its ability to suppress false neural signals. Object tracking based motion compensation thus offers an alternative approach for motion compensation, one that is we suited for real time feedback control and for analysis of tissue distortions.

neuroscience↗