Automated profiling of growth cone heterogeneity defines relations between morphology and motility

A convex-hull based method with manifold projections for detecting cell protrusions

Cell protrusions play an important role in a variety of cell physiological processes. In this paper, we propose a convex-hull based method, combined with manifold projections, to detect cell protrusions. A convex hull is generated based on the cell surface. We consider the cell surface and the boundary of its convex hull as two manifolds, which are diffeomorphic, and define a depth function based on the distance between the cell surface and its convex hull boundary. The extreme points of the depth function represent the positions of cell protrusions. To find the extreme points easily, we project the points on the cell surface onto the boundary of the convex hull and expand them in spherical polar coordinates. We conducted experiments on three types of cell protrusions. The proposed method achieved the average precision of 98.9%, 95.6%, and 94.7% on blebs, filopodia, and lamellipodia, respectively. Experiments on three datasets show that the proposed method has a robust performance.

Tunnelling nanotube formation is driven by Eps8/IRSp53-dependent linear actin polymerization

Tunnelling nanotubes (TNTs) connect distant cells and mediate cargo transfer for intercellular communication in physiological and pathological contexts. How cells generate these actin-mediated protrusions to span lengths beyond those attainable by canonical filopodia remains unknown. Through a combination of micropatterning, microscopy, and optical tweezer-based approaches, we demonstrate that TNTs formed through the outward extension of actin achieve distances greater than the mean length of filopodia and that branched Arp2/3-dependent pathways attenuate the extent to which actin polymerizes in nanotubes, thus limiting their occurrence. Proteomic analysis using epidermal growth factor receptor kinase substrate 8 (Eps8) as a positive effector of TNTs showed that, upon Arp2/3 inhibition, proteins enhancing filament turnover and depolymerization were reduced and Eps8 instead exhibited heightened interactions with the inverted Bin/Amphiphysin/Rvs (I-BAR) domain protein IRSp53 that provides a direct connection with linear actin polymerases. Our data reveals how common protrusion players (Eps8 and IRSp53) form tunnelling nanotubes, and that when competing pathways overutilizing such proteins and monomeric actin in Arp2/3 networks are inhibited, processes promoting linear actin growth dominate to favour tunnelling nanotube formation.

Mapping the Localization of Proteins Within Filopodia Using FiloMap

Filopodia are fingerlike membrane protrusions extended by cells to sense their environment. Filopodia are widely used by migrating cells in vivo and directly contribute to several physiological processes and diseases. Due to the essential roles of filopodia in sensing the extracellular environment, there is a need to characterize their composition and ultrastructure further. This chapter highlights FiloMap, an image analysis pipeline that utilizes Fiji and R to map the localization of proteins within filopodia from microscopy images. I provide step-by-step protocols on (a) setting up FiloMap in Fiji and R, (b) extracting line intensity profiles from filopodia stainings in Fiji, (c) further analyzing line intensity profiles in R, and (d) creating filopodia maps to compare the localization of multiple proteins within filopodia. Notably, while FiloMap was written to analyze filopodia, the analysis pipeline described here can also analyze and compile any line intensity profiles.

Neuronal filopodia: From stochastic dynamics to robustness of brain morphogenesis

Brain development relies on dynamic morphogenesis and interactions of neurons. Filopodia are thin and highly dynamic membrane protrusions that are critically required for neuronal development and neuronal interactions with the environment. Filopodial interactions are typically characterized by non-deterministic dynamics, yet their involvement in developmental processes leads to stereotypic and robust outcomes. Here, we discuss recent advances in our understanding of how filopodial dynamics contribute to neuronal differentiation, migration, axonal and dendritic growth and synapse formation. Many of these advances are brought about by improved methods of live observation in intact developing brains. Recent findings integrate known and novel roles ranging from exploratory sensors and decision-making agents to pools for selection and mechanical functions. Different types of filopodial dynamics thereby reveal non-deterministic subcellular decision-making processes as part of genetically encoded brain development.

Emerging machine learning approaches to phenotyping cellular motility and morphodynamics

Cells respond heterogeneously to molecular and environmental perturbations. Phenotypic heterogeneity, wherein multiple phenotypes coexist in the same conditions, presents challenges when interpreting the observed heterogeneity. Advances in live cell microscopy allow researchers to acquire an unprecedented amount of live cell image data at high spatiotemporal resolutions. Phenotyping cellular dynamics, however, is a nontrivial task and requires machine learning (ML) approaches to discern phenotypic heterogeneity from live cell images. In recent years, ML has proven instrumental in biomedical research, allowing scientists to implement sophisticated computation in which computers learn and effectively perform specific analyses with minimal human instruction or intervention. In this review, we discuss how ML has been recently employed in the study of cell motility and morphodynamics to identify phenotypes from computer vision analysis. We focus on new approaches to extract and learn meaningful spatiotemporal features from complex live cell images for cellular and subcellular phenotyping.

Data science in cell imaging

Cell imaging has entered the 'Big Data' era. New technologies in light microscopy and molecular biology have led to an explosion in high-content, dynamic and multidimensional imaging data. Similar to the 'omics' fields two decades ago, our current ability to process, visualize, integrate and mine this new generation of cell imaging data is becoming a critical bottleneck in advancing cell biology. Computation, traditionally used to quantitatively test specific hypotheses, must now also enable iterative hypothesis generation and testing by deciphering hidden biologically meaningful patterns in complex, dynamic or high-dimensional cell image data. Data science is uniquely positioned to aid in this process. In this Perspective, we survey the rapidly expanding new field of data science in cell imaging. Specifically, we highlight how data science tools are used within current image analysis pipelines, propose a computation-first approach to derive new hypotheses from cell image data, identify challenges and describe the next frontiers where we believe data science will make an impact. We also outline steps to ensure broad access to these powerful tools - democratizing infrastructure availability, developing sensitive, robust and usable tools, and promoting interdisciplinary training to both familiarize biologists with data science and expose data scientists to cell imaging.

Abl signaling directs growth of a pioneer axon in Drosophila by shaping the intrinsic fluctuations of actin

The fundamental problem in axon growth and guidance is understanding how cytoplasmic signaling modulates the cytoskeleton to produce directed growth cone motility. Live imaging of the TSM1 axon of the developing Drosophila wing has shown that the essential role of the core guidance signaling molecule, Abelson (Abl) tyrosine kinase, is to modulate the organization and spatial localization of actin in the advancing growth cone. Here, we dissect in detail the properties of that actin organization and its consequences for growth cone morphogenesis and motility. We show that advance of the actin mass in the distal axon drives the forward motion of the dynamic filopodial domain that defines the growth cone. We further show that Abl regulates both the width of the actin mass and its internal organization, spatially biasing the intrinsic fluctuations of actin to achieve net advance of the actin, and thus of the dynamic filopodial domain of the growth cone, while maintaining the essential coherence of the actin mass itself. These data suggest a model whereby guidance signaling systematically shapes the intrinsic, stochastic fluctuations of actin in the growth cone to produce axon growth and guidance.

Molecular basis of the functions of the mammalian neuronal growth cone revealed using new methods

The neuronal growth cone is a highly motile, specialized structure for extending neuronal processes. This structure is essential for nerve growth, axon pathfinding, and accurate synaptogenesis. Growth cones are important not only during development but also for plasticity-dependent synaptogenesis and neuronal circuit rearrangement following neural injury in the mature brain. However, the molecular details of mammalian growth cone function are poorly understood. This review examines molecular findings on the function of the growth cone as a result of the introduction of novel methods such superresolution microscopy and (phospho)proteomics. These results increase the scope of our understating of the molecular mechanisms of growth cone behavior in the mammalian brain.