CellGeo: a computational platform for the analysis of shape changes in cells with complex geometries

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.

filoVision - using deep learning and tip markers to automate filopodia analysis

Filopodia are slender, actin-filled membrane projections used by various cell types for environment exploration. Analyzing filopodia often involves visualizing them using actin, filopodia tip or membrane markers. Due to the diversity of cell types that extend filopodia, from amoeboid to mammalian, it can be challenging for some to find a reliable filopodia analysis workflow suited for their cell type and preferred visualization method. The lack of an automated workflow capable of analyzing amoeboid filopodia with only a filopodia tip label prompted the development of filoVision. filoVision is an adaptable deep learning platform featuring the tools filoTips and filoSkeleton. filoTips labels filopodia tips and the cytosol using a single tip marker, allowing information extraction without actin or membrane markers. In contrast, filoSkeleton combines tip marker signals with actin labeling for a more comprehensive analysis of filopodia shafts in addition to tip protein analysis. The ZeroCostDL4Mic deep learning framework facilitates accessibility and customization for different datasets and cell types, making filoVision a flexible tool for automated analysis of tip-marked filopodia across various cell types and user data.

Septins provide microenvironment sensing and cortical actomyosin partitioning in motile amoeboid T lymphocytes

The all-terrain motility of lymphocytes in tissues and tissue-like gels is best described as amoeboid motility. For amoeboid motility, lymphocytes do not require specific biochemical or structural modifications to the surrounding extracellular matrix. Instead, they rely on changing shape and steric interactions with the microenvironment. However, the exact mechanism of amoeboid motility remains elusive. Here, we report that septins participate in amoeboid motility of T cells, enabling the formation of F-actin and α-actinin-rich cortical rings at the sites of cell cortex-indenting collisions with the extracellular matrix. Cortical rings compartmentalize cells into chains of spherical segments that are spatially conformed to the available lumens, forming transient "hourglass"-shaped steric locks onto the surrounding collagen fibers. The steric lock facilitates pressure-driven peristaltic propulsion of cytosolic content by individually contracting cell segments. Our results suggest that septins provide microenvironment-guided partitioning of actomyosin contractility and steric pivots required for amoeboid motility of T cells in tissue-like microenvironments.

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.

Two Rac1 pools integrate the direction and coordination of collective cell migration

Integration of collective cell direction and coordination is believed to ensure collective guidance for efficient movement. Previous studies demonstrated that chemokine receptors PVR and EGFR govern a gradient of Rac1 activity essential for collective guidance of Drosophila border cells, whose mechanistic insight is unknown. By monitoring and manipulating subcellular Rac1 activity, here we reveal two switchable Rac1 pools at border cell protrusions and supracellular cables, two important structures responsible for direction and coordination. Rac1 and Rho1 form a positive feedback loop that guides mechanical coupling at cables to achieve migration coordination. Rac1 cooperates with Cdc42 to control protrusion growth for migration direction, as well as to regulate the protrusion-cable exchange, linking direction and coordination. PVR and EGFR guide correct Rac1 activity distribution at protrusions and cables. Therefore, our studies emphasize the existence of a balance between two Rac1 pools, rather than a Rac1 activity gradient, as an integrator for the direction and coordination of collective cell migration.

Previous studies suggested a chemokine receptor governed gradient of Rac1 activity is essential for collective guidance of Drosophila border cells. Here, Zhou et al. report that two distinct Rac1 pools at protrusions and cables, not Rac1 activity gradient, integrate the direction and coordination for collective guidance.

TNTdetect.AI: A Deep Learning Model for Automated Detection and Counting of Tunneling Nanotubes in Microscopy Images

Simple Summary

Microscopy is central to many areas of biomedical science research, including cancer research, and is critical for understanding basic pathophysiology, mechanisms of action, and treatment response. However, analysis of the numerous images generated from microscopy readouts is usually performed manually, a process that is tedious and time-consuming. Moreover, manual analysis of microscopy images may limit both accuracy and reproducibility. Here, we used an artificial intelligence approach to analyze tunnelling nanotubes (TNTs), a feature of cancer cells that may contribute to their aggressiveness, but which are hard to identify and count. Our approach labeled and detected TNTs and cancer cells from microscopy images and generated TNT-to-cell ratios comparable to those of human experts. Continued refinement of this process will provide a new approach to the analysis of TNTs. Additionally, this approach has the potential to enhance drug screens intended to assess therapeutic efficacy of experimental agents and to reproducibly assess TNTs as a potential biomarker of response to cancer therapy.

Abstract

Background: Tunneling nanotubes (TNTs) are cellular structures connecting cell membranes and mediating intercellular communication. TNTs are manually identified and counted by a trained investigator; however, this process is time-intensive. We therefore sought to develop an automated approach for quantitative analysis of TNTs. Methods: We used a convolutional neural network (U-Net) deep learning model to segment phase contrast microscopy images of both cancer and non-cancer cells. Our method was composed of preprocessing and model development. We developed a new preprocessing method to label TNTs on a pixel-wise basis. Two sequential models were employed to detect TNTs. First, we identified the regions of images with TNTs by implementing a classification algorithm. Second, we fed parts of the image classified as TNT-containing into a modified U-Net model to estimate TNTs on a pixel-wise basis. Results: The algorithm detected 49.9% of human expert-identified TNTs, counted TNTs, and calculated the number of TNTs per cell, or TNT-to-cell ratio (TCR); it detected TNTs that were not originally detected by the experts. The model had 0.41 precision, 0.26 recall, and 0.32 f-1 score on a test dataset. The predicted and true TCRs were not significantly different across the training and test datasets (p = 0.78). Conclusions: Our automated approach labeled and detected TNTs and cells imaged in culture, resulting in comparable TCRs to those determined by human experts. Future studies will aim to improve on the accuracy, precision, and recall of the algorithm.

Reconstructing data-driven governing equations for cell phenotypic transitions: integration of data science and systems biology

Cells with the same genome can exist in different phenotypes and can change between distinct phenotypes when subject to specific stimuli and microenvironments. Some examples include cell differentiation during development, reprogramming for induced pluripotent stem cells and transdifferentiation, cancer metastasis and fibrosis progression. The regulation and dynamics of cell phenotypic conversion is a fundamental problem in biology, and has a long history of being studied within the formalism of dynamical systems. A main challenge for mechanism-driven modeling studies is acquiring sufficient amount of quantitative information for constraining model parameters. Advances in quantitative experimental approaches, especially high throughput single-cell techniques, have accelerated the emergence of a new direction for reconstructing the governing dynamical equations of a cellular system from quantitative single-cell data, beyond the dominant statistical approaches. Here I review a selected number of recent studies using live- and fixed-cell data and provide my perspective on future development.

Reconstructing data-driven governing equations for cell phenotypic transitions: integration of data science and systems biology

Cells with the same genome can exist in different phenotypes and can change between distinct phenotypes when subject to specific stimuli and microenvironments. Some examples include cell differentiation during development, reprogramming for induced pluripotent stem cells and transdifferentiation, cancer metastasis and fibrosis progression. The regulation and dynamics of cell phenotypic conversion is a fundamental problem in biology, and has a long history of being studied within the formalism of dynamical systems. A main challenge for mechanism-driven modeling studies is acquiring sufficient amount of quantitative information for constraining model parameters. Advances in quantitative experimental approaches, especially high throughput single-cell techniques, have accelerated the emergence of a new direction for reconstructing the governing dynamical equations of a cellular system from quantitative single-cell data, beyond the dominant statistical approaches. Here I review a selected number of recent studies using live- and fixed-cell data and provide my perspective on future development.

Nuclear fascin regulates cancer cell survival

Fascin is an important regulator of F-actin bundling leading to enhanced filopodia assembly. Fascin is also overexpressed in most solid tumours where it supports invasion through control of F-actin structures at the periphery and nuclear envelope. Recently, fascin has been identified in the nucleus of a broad range of cell types but the contributions of nuclear fascin to cancer cell behaviour remain unknown. Here, we demonstrate that fascin bundles F-actin within the nucleus to support chromatin organisation and efficient DDR. Fascin associates directly with phosphorylated Histone H3 leading to regulated levels of nuclear fascin to support these phenotypes. Forcing nuclear fascin accumulation through the expression of nuclear-targeted fascin-specific nanobodies or inhibition of Histone H3 kinases results in enhanced and sustained nuclear F-actin bundling leading to reduced invasion, viability, and nuclear fascin-specific/driven apoptosis. These findings represent an additional important route through which fascin can support tumourigenesis and provide insight into potential pathways for targeted fascin-dependent cancer cell killing.

Dissecting protein tyrosine phosphatase signaling by engineered chemogenetic control of its activity

Protein tyrosine phosphatases (PTPases) are critical mediators of dynamic cell signaling. A tool capable of identifying transient signaling events downstream of PTPases is essential to understand phosphatase function on a physiological time scale. We report a broadly applicable protein engineering method for allosteric regulation of PTPases. This method enables dissection of transient events and reconstruction of individual signaling pathways. Implementation of this approach for Shp2 phosphatase revealed parallel MAPK and ROCK II dependent pathways downstream of Shp2, mediating transient cell spreading and migration. Furthermore, we show that the N-SH2 domain of Shp2 regulates MAPK-independent, ROCK II-dependent cell migration. Engineered targeting of Shp2 activity to different protein complexes revealed that Shp2-FAK signaling induces cell spreading whereas Shp2-Gab1 or Shp2-Gab2 mediates cell migration. We identified specific transient morphodynamic processes induced by Shp2 and determined the role of individual signaling pathways downstream of Shp2 in regulating these events. Broad application of this approach is demonstrated by regulating PTP1B and PTP-PEST phosphatases.

Inhibition of Rho-associated protein kinase activity enhances oxidative phosphorylation to support corneal endothelial cell migration

Corneal endothelial cell (CEC) dysfunction causes corneal edema and severe visual impairment that require transplantation to restore vision. To address the unmet need of organ shortage, descemetorhexis without endothelial keratoplasty has been specifically employed to treat early stage Fuchs endothelial corneal dystrophy, which is pathophysiologically related to oxidative stress and exhibits centrally located corneal guttae. After stripping off central Descemet's membrane, rho-associated protein kinase (ROCK) inhibitor has been found to facilitate CEC migration, an energy-demanding task, thereby achieving wound closure. However, the correlation between ROCK inhibition and the change in bioenergetic status of CECs remained to be elucidated. Through transcriptomic profiling, we found that the inhibition of ROCK activity by the selective inhibitor, ripasudil or Y27632, promoted enrichment of oxidative phosphorylation (OXPHOS) gene set in bovine CECs (BCECs). Functional analysis revealed that ripasudil, a clinically approved anti-glaucoma agent, enhanced mitochondrial respiration, increased spare respiratory capacity, and induced overexpression of electron transport chain components through upregulation of AMP-activated protein kinase (AMPK) pathway. Accelerated BCEC migration and in vitro wound healing by ripasudil were diminished by OXPHOS and AMPK inhibition, but not by glycolysis inhibition. Correspondingly, lamellipodial protrusion and actin assembly that were augmented by ripasudil became reduced with additional OXPHOS or AMPK inhibition. These results indicate that ROCK inhibition induces metabolic reprogramming toward OXPHOS to support migration of CECs.

Differential modulation of endothelial cytoplasmic protrusions after exposure to graphene-family nanomaterials

Engineered nanomaterials offer the benefit of having systematically tunable physicochemical characteristics (e.g., size, dimensionality, and surface chemistry) that highly dictate the biological activity of a material. Among the most promising engineered nanomaterials to date are graphene-family nanomaterials (GFNs), which are 2-D nanomaterials (2DNMs) with unique electrical and mechanical properties. Beyond engineering new nanomaterial properties, employing safety-by-design through considering the consequences of cell-material interactions is essential for exploring their applicability in the biomedical realm. In this study, we asked the effect of GFNs on the endothelial barrier function and cellular architecture of vascular endothelial cells. Using micropatterned cell pairs as a reductionist in vitro model of the endothelium, the progression of cytoskeletal reorganization as a function of GFN surface chemistry and time was quantitatively monitored. Here, we show that the surface oxidation of GFNs (graphene, reduced graphene oxide, partially reduced graphene oxide, and graphene oxide) differentially affect the endothelial barrier at multiple scales; from the biochemical pathways that influence the development of cellular protrusions to endothelial barrier integrity. More oxidized GFNs induce higher endothelial permeability and the increased formation of cytoplasmic protrusions such as filopodia. We found that these changes in cytoskeletal organization, along with barrier function, can be potentiated by the effect of GFNs on the Rho/Rho-associated kinase (ROCK) pathway. Specifically, GFNs with higher surface oxidation elicit stronger ROCK2 inhibitory behavior as compared to pristine graphene sheets. Overall, findings from these studies offer a new perspective towards systematically controlling the surface-dependent effects of GFNs on cytoskeletal organization via ROCK2 inhibition, providing insight for implementing safety-by-design principles in GFN manufacturing towards their targeted biomedical applications.

Methods for assessment of membrane protrusion dynamics

Membrane protrusions are a critical facet of cell function. Mediating fundamental processes such as cell migration, cell-cell interactions, phagocytosis, as well as assessment and remodeling of the cell environment. Different protrusion types and morphologies can promote different cellular functions and occur downstream of distinct signaling pathways. As such, techniques to quantify and understand the inner workings of protrusion dynamics are critical for a comprehensive understanding of cell biology. In this chapter, we describe approaches to analyze cellular protrusions and correlate physical changes in cell morphology with biochemical signaling processes. We address methods to quantify and characterize protrusion types and velocity, mathematical approaches to predictive models of cytoskeletal changes, and implementation of protein engineering and biosensor design to dissect cell signaling driving protrusive activity. Combining these approaches allows cell biologists to develop a comprehensive understanding of the dynamics of membrane protrusions.

Current approaches to fate mapping and lineage tracing using image data

Visualizing, tracking and reconstructing cell lineages in developing embryos has been an ongoing effort for well over a century. Recent advances in light microscopy, labelling strategies and computational methods to analyse complex image datasets have enabled detailed investigations into the fates of cells. Combined with powerful new advances in genomics and single-cell transcriptomics, the field of developmental biology is able to describe the formation of the embryo like never before. In this Review, we discuss some of the different strategies and applications to lineage tracing in live-imaging data and outline software methodologies that can be applied to various cell-tracking challenges.

α2β1 integrins spatially restrict Cdc42 activity to stabilise adherens junctions

Background

Keratinocytes form the main protective barrier in the skin to separate the underlying tissue from the external environment. In order to maintain this barrier, keratinocytes form robust junctions between neighbouring cells as well as with the underlying extracellular matrix. Cell–cell adhesions are mediated primarily through cadherin receptors, whereas the integrin family of transmembrane receptors is predominantly associated with assembly of matrix adhesions. Integrins have been shown to also localise to cell–cell adhesions, but their role at these sites remains unclear.

Results

Here we show that α2β1 integrins are enriched at mature keratinocyte cell–cell adhesions, where they play a crucial role in organising cytoskeletal networks to stabilize adherens junctions. Loss of α2β1 integrin has significant functional phenotypes associated with cell–cell adhesion destabilisation, including increased proliferation, reduced migration and impaired barrier function. Mechanistically, we show that α2β1 integrins suppress activity of Src and Shp2 at cell–cell adhesions leading to enhanced Cdc42–GDI interactions and stabilisation of junctions between neighbouring epithelial cells.

Conclusion

Our data reveals a new role for α2β1 integrins in controlling integrity of epithelial cell–cell adhesions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01054-9.

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.

Light-regulated allosteric switch enables temporal and subcellular control of enzyme activity

Engineered allosteric regulation of protein activity provides significant advantages for the development of robust and broadly applicable tools. However, the application of allosteric switches in optogenetics has been scarce and suffers from critical limitations. Here, we report an optogenetic approach that utilizes an engineered Light-Regulated (LightR) allosteric switch module to achieve tight spatiotemporal control of enzymatic activity. Using the tyrosine kinase Src as a model, we demonstrate efficient regulation of the kinase and identify temporally distinct signaling responses ranging from seconds to minutes. LightR-Src off-kinetics can be tuned by modulating the LightR photoconversion cycle. A fast cycling variant enables the stimulation of transient pulses and local regulation of activity in a selected region of a cell. The design of the LightR module ensures broad applicability of the tool, as we demonstrate by achieving light-mediated regulation of Abl and bRaf kinases as well as Cre recombinase.

Shape-to-graph mapping method for efficient characterization and classification of complex geometries in biological images

With the ever-increasing quality and quantity of imaging data in biomedical research comes the demand for computational methodologies that enable efficient and reliable automated extraction of the quantitative information contained within these images. One of the challenges in providing such methodology is the need for tailoring algorithms to the specifics of the data, limiting their areas of application. Here we present a broadly applicable approach to quantification and classification of complex shapes and patterns in biological or other multi-component formations. This approach integrates the mapping of all shape boundaries within an image onto a global information-rich graph and machine learning on the multidimensional measures of the graph. We demonstrated the power of this method by (1) extracting subtle structural differences from visually indistinguishable images in our phenotype rescue experiments using the endothelial tube formations assay, (2) training the algorithm to identify biophysical parameters underlying the formation of different multicellular networks in our simulation model of collective cell behavior, and (3) analyzing the response of U2OS cell cultures to a broad array of small molecule perturbations.

In this paper, we present a methodology that is based on mapping an arbitrary set of outlines onto a complete, strictly defined structure, in which every point representing the shape becomes a terminal point of a global graph. Because this mapping preserves the whole complexity of the shape, it allows for extracting the full scope of geometric features of any scale. Importantly, an extensive set of graph-based metrics in each image makes integration with machine learning routines highly efficient even for a small data sets and provide an opportunity to backtrack the subtle morphological features responsible for the automated distinction into image classes. The resulting tool provides efficient, versatile, and robust quantification of complex shapes and patterns in experimental images.

The Density and Length of Filopodia Associate with the Activity of Hyaluronan Synthesis in Tumor Cells

Filopodia are multifunctional finger-like plasma membrane protrusions with bundles of actin filaments that exist in virtually all cell types. It has been known for some time that hyaluronan synthesis activity induces filopodial growth. However, because of technical challenges in the studies of these slender and fragile structures, no quantitative analyses have been performed so far to indicate their association with hyaluronan synthesis. In this work we comprehensively address the direct quantification of filopodial traits, covering for the first time length and density measurements in a series of human cancer cell lines with variable levels of hyaluronan synthesis. The synthesis and plasma membrane binding of hyaluronan were manipulated with hyaluronan synthase 3 (HAS3) and hyaluronan receptor CD44 overexpression, and treatments with mannose, 4-methylumbelliferone (4-MU), and glucosamine. The results of this work show that the growth of filopodia was associated with the levels of hyaluronan synthesis but was not dependent on CD44 expression. The results confirm the hypothesis that abundance and length of filopodia in cancer cells is associated with the activity of hyaluronan synthesis.

3D nanoplasmonic biosensor for detection of filopodia in cells

Filopodia are thin finger-like protrusions from cells and they are hard to detect using electrical, mechanical, or optical sensors because of their nanometer scale features. Besides, the signals from filopodia and the cell membrane are often mixed together which makes the detection of filopodia challenging. Here, a 3D nanoplasmonic biosensor with microposts is proposed to overcome these limitations. By using suitable chemical coating and physical dimensions, the signals from filopodia and the cell membrane were separated by having the microposts keep the cell membrane from making contact with the nanoplasmonic biosensor. The filopodia were detected by the 3D asymmetrical nanopillars with sharp Fano resonance. The sensitivity and figure of merit of the nanoplasmonic biosensor were 650 nm per refractive index unit and 28.3, respectively. A large peak shift of 6 nm was observed for the detection of MC3T3 osteoblastic cell filopodia at a concentration of 1300 cells per mm². To the best of our knowledge, this is the first demonstration of filopodia detection using nanoplasmonic biosensors, where microposts were used to separate the cell membrane from filopodia and the 3D nanoplasmonic biosensors were used to monitor filopodia on the nanometer scale. These combined 3D micro- and nano-structures allow filopodia to be detected using different sensors without interference from the cell membrane.

FMNL2 regulates dynamics of fascin in filopodia

Filopodia are peripheral F-actin-rich structures that enable cell sensing of the microenvironment. Fascin is an F-actin-bundling protein that plays a key role in stabilizing filopodia to support efficient adhesion and migration. Fascin is also highly up-regulated in human cancers, where it increases invasive cell behavior and correlates with poor patient prognosis. Previous studies have shown that fascin phosphorylation can regulate F-actin bundling, and that this modification can contribute to subcellular fascin localization and function. However, the factors that regulate fascin dynamics within filopodia remain poorly understood. In the current study, we used advanced live-cell imaging techniques and a fascin biosensor to demonstrate that fascin phosphorylation, localization, and binding to F-actin are highly dynamic and dependent on local cytoskeletal architecture in cells in both 2D and 3D environments. Fascin dynamics within filopodia are under the control of formins, and in particular FMNL2, that binds directly to dephosphorylated fascin. Our data provide new insight into control of fascin dynamics at the nanoscale and into the mechanisms governing rapid cytoskeletal adaptation to environmental changes. This filopodia-driven exploration stage may represent an essential regulatory step in the transition from static to migrating cancer cells.

Re-track: Software to analyze the retraction and protrusion velocities of neurites, filopodia and other structures

We have developed new software, Re-track, that will quantify the rates of retraction and protrusion of structures emanating from the central core of a cell, such as neurites or filopodia. Re-Track, uses time-lapse images of cells in TIFF format and calculates the velocity of retraction or protrusion of a selected structure. The software uses a flexible moving boundary and has the ability to correct this boundary throughout analysis. Re-Track is fast, platform independent, and user friendly, and it can be used to follow biological events such as changes in neuronal connections, tip-growing cells such as moss, adaptive migration of cells, and similar behavior in non-biological systems.

Neural crest cells bulldoze through the microenvironment using Aquaporin 1 to stabilize filopodia

Neural crest migration requires cells to move through an environment filled with dense extracellular matrix and mesoderm to reach targets throughout the vertebrate embryo. Here, we use high-resolution microscopy, computational modeling, and in vitro and in vivo cell invasion assays to investigate the function of Aquaporin 1 (AQP-1) signaling. We find that migrating lead cranial neural crest cells express AQP-1 mRNA and protein, implicating a biological role for water channel protein function during invasion. Differential AQP-1 levels affect neural crest cell speed and direction, as well as the length and stability of cell filopodia. Furthermore, AQP-1 enhances matrix metalloprotease activity and colocalizes with phosphorylated focal adhesion kinases. Colocalization of AQP-1 with EphB guidance receptors in the same migrating neural crest cells has novel implications for the concept of guided bulldozing by lead cells during migration.

Actin protrusions push at apical junctions to maintain E-cadherin adhesion

Cadherin-mediated cell-cell adhesion is actin-dependent, but the precise role of actin in maintaining cell-cell adhesion is not fully understood. Actin polymerization-dependent protrusive activity is required to push distally separated cells close enough to initiate contact. Whether protrusive activity is required to maintain adhesion in confluent sheets of epithelial cells is not known. By electron microscopy as well as live cell imaging, we have identified a population of protruding actin microspikes that operate continuously near apical junctions of polarized Madin-Darby canine kidney (MDCK) cells. Live imaging shows that microspikes containing E-cadherin extend into gaps between E-cadherin clusters on neighboring cells, while reformation of cadherin clusters across the cell-cell boundary correlates with microspike withdrawal. We identify Arp2/3, EVL, and CRMP-1 as 3 actin assembly factors necessary for microspike formation. Depleting these factors from cells using RNA interference (RNAi) results in myosin II-dependent unzipping of cadherin adhesive bonds. Therefore, actin polymerization-dependent protrusive activity operates continuously at cadherin cell-cell junctions to keep them shut and to prevent myosin II-dependent contractility from tearing cadherin adhesive contacts apart.

Engineering proteins for allosteric control by light or ligands

Control of protein activity in living cells can reveal the role of spatiotemporal dynamics in signaling circuits. Protein analogs with engineered allosteric responses can be particularly effective in the interrogation of protein signaling, as they can replace endogenous proteins with minimal perturbation of native interactions. However, it has been a challenge to identify allosteric sites in target proteins where insertion of responsive domains produces an allosteric response comparable to the activity of native proteins. Here, we describe a detailed protocol to generate genetically encoded analogs of proteins that can be allosterically controlled by either rapamycin or blue light, as well as experimental procedures to produce and test these analogs in vitro and in mammalian cell lines. We describe computational methods, based on crystal structures or homology models, to identify effective sites for insertion of either an engineered rapamycin-responsive (uniRapR) domain or the light-responsive light-oxygen-voltage 2 (LOV2) domain. The inserted domains allosterically regulate the active site, responding to rapamycin with irreversible activation, or to light with reversible inactivation at higher spatial and temporal resolution. These strategies have been successfully applied to catalytic domains of protein kinases, Rho family GTPases, and guanine exchange factors (GEFs), as well as the binding domain of a GEF Vav2. Computational tasks can be completed within a few hours, followed by 1-2 weeks of experimental validation. We provide protocols for computational design, cloning, and experimental testing of the engineered proteins, using Src tyrosine kinase, GEF Vav2, and Rho GTPase Rac1 as examples.

Time-Variant SRC Kinase Activation Determines Endothelial Permeability Response

In the current model of endothelial barrier regulation, the tyrosine kinase SRC is purported to induce disassembly of endothelial adherens junctions (AJs) via phosphorylation of VE cadherin, and thereby increase junctional permeability. Here, using a chemical biology approach to temporally control SRC activation, we show that SRC exerts distinct time-variant effects on the endothelial barrier. We discovered that the immediate effect of SRC activation was to transiently enhance endothelial barrier function as the result of accumulation of VE cadherin at AJs and formation of morphologically distinct reticular AJs. Endothelial barrier enhancement via SRC required phosphorylation of VE cadherin at Y731. In contrast, prolonged SRC activation induced VE cadherin phosphorylation at Y685, resulting in increased endothelial permeability. Thus, time-variant SRC activation differentially phosphorylates VE cadherin and shapes AJs to fine-tune endothelial barrier function. Our work demonstrates important advantages of synthetic biology tools in dissecting complex signaling systems.

3-D Quantification of Filopodia in Motile Cancer Cells

We present a 3D bioimage analysis workflow to quantitatively analyze single, actin-stained cells with filopodial protrusions of diverse structural and temporal attributes, such as number, length, thickness, level of branching, and lifetime, in time-lapse confocal microscopy image data. Our workflow makes use of convolutional neural networks trained using real as well as synthetic image data, to segment the cell volumes with highly heterogeneous fluorescence intensity levels and to detect individual filopodial protrusions, followed by a constrained nearest-neighbor tracking algorithm to obtain valuable information about the spatio-temporal evolution of individual filopodia. We validated the workflow using real and synthetic 3-D time-lapse sequences of lung adenocarcinoma cells of three morphologically distinct filopodial phenotypes and show that it achieves reliable segmentation and tracking performance, providing a robust, reproducible and less time-consuming alternative to manual analysis of the 3D+t image data.

Analyzing temporal dynamics of cell deformation and intracellular movement with video feature aggregation

BACKGROUND

The research and analysis of cellular physiological properties has been an essential approach to studying some biological and biomedical problems. Temporal dynamics of cells therein are used as a quantifiable indicator of cellular response to extracellular cues and physiological stimuli.

METHODS

This work presents a novel image-based framework to profile and model the cell dynamics in live-cell videos. In the framework, the cell dynamics between frames are represented as frame-level features from cell deformation and intracellular movement. On the one hand, shape context is introduced to enhance the robustness of measuring the deformation of cellular contours. On the other hand, we employ Scale-Invariant Feature Transform (SIFT) flow to simultaneously construct the complementary movement field and appearance change field for the cytoplasmic streaming. Then, time series modeling is performed on these frame-level features. Specifically, temporal feature aggregation is applied to capture the video-wide temporal evolution of cell dynamics.

RESULTS

Our results demonstrate that the proposed cell dynamic features can effectively capture the cell dynamics in videos. They also prove that the Movement Field and Appearance Change Field Feature (MFAFF) can more precisely model the cytoplasmic streaming. Besides, temporal aggregation of cell dynamic features brings a substantial absolute increase of classification performance.

CONCLUSION

Experimental results demonstrate that the proposed framework outperforms competing mainstreaming approaches on the aforementioned datasets. Thus, our method has potential for cell dynamics analysis in videos.

Centrosome guides spatial activation of Rac to control cell polarization and directed cell migration

The centrosome acts as a controller by balancing the formation of centrosomal and acentrosomal microtubules, the modulation of focal adhesion signaling and the activation of local Rac1 at the cell front, which then coordinates cell polarization during directed cell migration.

Directed cell migration requires centrosome-mediated cell polarization and dynamical control of focal adhesions (FAs). To examine how FAs cooperate with centrosomes for directed cell migration, we used centrosome-deficient cells and found that loss of centrosomes enhanced the formation of acentrosomal microtubules, which failed to form polarized structures in wound-edge cells. In acentrosomal cells, we detected higher levels of Rac1-guanine nucleotide exchange factor TRIO (Triple Functional Domain Protein) on microtubules and FAs. Acentrosomal microtubules deliver TRIO to FAs for Rac1 regulation. Indeed, centrosome disruption induced excessive Rac1 activation around the cell periphery via TRIO, causing rapid FA turnover, a disorganized actin meshwork, randomly protruding lamellipodia, and loss of cell polarity. This study reveals the importance of centrosomes to balance the assembly of centrosomal and acentrosomal microtubules and to deliver microtubule-associated TRIO proteins to FAs at the cell front for proper spatial activation of Rac1, FA turnover, lamillipodial protrusion, and cell polarization, thereby allowing directed cell migration.

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

Growth cones are complex, motile structures at the tip of an outgrowing neurite. They often exhibit a high density of filopodia (thin actin bundles), which complicates the unbiased quantification of their morphologies by software. Contemporary image processing methods require extensive tuning of segmentation parameters, require significant manual curation, and are often not sufficiently adaptable to capture morphology changes associated with switches in regulatory signals. To overcome these limitations, we developed Growth Cone Analyzer (GCA). GCA is designed to quantify growth cone morphodynamics from time-lapse sequences imaged both in vitro and in vivo, but is sufficiently generic that it may be applied to nonneuronal cellular structures. We demonstrate the adaptability of GCA through the analysis of growth cone morphological variation and its relation to motility in both an unperturbed system and in the context of modified Rho GTPase signaling. We find that perturbations inducing similar changes in neurite length exhibit underappreciated phenotypic nuance at the scale of the growth cone.

Ena/VASP processive elongation is modulated by avidity on actin filaments bundled by the filopodia cross-linker fascin

Ena/VASP tetramers are processive actin elongation factors that localize to diverse F-actin networks composed of filaments bundled by different cross-linking proteins, such as filopodia (fascin), lamellipodia (fimbrin), and stress fibers (α-actinin). Previously, we found that Ena takes approximately threefold longer processive runs on trailing barbed ends of fascin-bundled F-actin. Here, we used single-molecule TIRFM (total internal reflection fluorescence microscopy) and developed a kinetic model to further dissect Ena/VASP’s processive mechanism on bundled filaments. We discovered that Ena’s enhanced processivity on trailing barbed ends is specific to fascin bundles, with no enhancement on fimbrin or α-actinin bundles. Notably, Ena/VASP’s processive run length increases with the number of both fascin-bundled filaments and Ena “arms,” revealing avidity facilitates enhanced processivity. Consistently, Ena tetramers form more filopodia than mutant dimer and trimers in Drosophila culture cells. Moreover, enhanced processivity on trailing barbed ends of fascin-bundled filaments is an evolutionarily conserved property of Ena/VASP homologues, including human VASP and Caenorhabditis elegans UNC-34. These results demonstrate that Ena tetramers are tailored for enhanced processivity on fascin bundles and that avidity of multiple arms associating with multiple filaments is critical for this process. Furthermore, we discovered a novel regulatory process whereby bundle size and bundling protein specificity control activities of a processive assembly factor.

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.

Filopodia Quantification Using FiloQuant

Filopodia are fingerlike membrane protrusions that are extended by cells in vitro and in vivo. Due to important roles in sensing the extracellular microenvironment, filopodia and filopodia-like protrusions have been implicated in numerous biological processes including epithelial sheet zippering in development and wound healing and in cancer progression. Recently, there has been an explosion in the number of software available to analyze specific features of cell protrusions with the aim of gaining mechanistic insights into the action of filopodia and filopodia-like structures. In this methods chapter, we highlight an open-access software called FiloQuant that has been developed to specifically quantify the length, density, and dynamics of filopodia and filopodia-like structures from in vitro and in vivo generated samples. We provide step-by-step protocols on (i) how to install FiloQuant in the ImageJ platform (Fiji), (ii) how to quantify filopodia and filopodia-like protrusions from single images using FiloQuant, and (iii) how to track filopodial protrusions from live-cell imaging experiments using FiloQuant and TrackMate.

FiloGen: A Model-Based Generator of Synthetic 3-D Time-Lapse Sequences of Single Motile Cells With Growing and Branching Filopodia

The existence of diverse image datasets accompanied by reference annotations is a crucial prerequisite for an objective benchmarking of bioimage analysis methods. Nevertheless, such a prerequisite is hard to satisfy for time lapse, multidimensional fluorescence microscopy image data, manual annotations of which are laborious and often impracticable. In this paper, we present a simulation system capable of generating 3-D time-lapse sequences of single motile cells with filopodial protrusions of user-controlled structural and temporal attributes, such as the number, thickness, length, level of branching, and lifetime of filopodia, accompanied by inherently generated reference annotations. The proposed simulation system involves three globally synchronized modules, each being responsible for a separate task: the evolution of filopodia on a molecular level, linear elastic deformation of the entire cell with filopodia, and the synthesis of realistic, time-coherent cell texture. Its flexibility is demonstrated by generating multiple synthetic 3-D time-lapse sequences of single lung cancer cells of two different phenotypes, qualitatively and quantitatively resembling their real counterparts acquired using a confocal fluorescence microscope.

Computational design of chemogenetic and optogenetic split proteins

Controlling protein activity with chemogenetics and optogenetics has proven to be powerful for testing hypotheses regarding protein function in rapid biological processes. Controlling proteins by splitting them and then rescuing their activity through inducible reassembly offers great potential to control diverse protein activities. Building split proteins has been difficult due to spontaneous assembly, difficulty in identifying appropriate split sites, and inefficient induction of effective reassembly. Here we present an automated approach to design effective split proteins regulated by a ligand or by light (SPELL). We develop a scoring function together with an engineered domain to enable reassembly of protein halves with high efficiency and with reduced spontaneous assembly. We demonstrate SPELL by applying it to proteins of various shapes and sizes in living cells. The SPELL server (spell.dokhlab.org) offers an automated prediction of split sites.

Designing split protein approaches is time consuming and often results in high background activity due to spontaneous assembly. Here the authors present an automated approach which uses a split energy scoring function to identify optimal protein split sites and reduces spontaneous assembly.

EdgeProps: A Computational Platform for Correlative Analysis of Cell Dynamics and Near-Edge Protein Activity

Developing molecular tools to visualize and control Rho GTPase signaling in living cells has been instrumental in elucidating the mechanisms of cytoskeletal reorganization and causal relationships between activation events in cell function. An indispensable part of such studies is the quantitative characterization of the spatiotemporal GTPase activity. Here we present a computational pipeline, EdgeProps, designed for comparative/correlative analysis of cell dynamics (edge velocity) and near-edge protein activity (intensity of a fluorescent signal). The tool offers a user-friendly interface with three functional modules for processing, visualization, and statistical characterization of single-cell imaging data.

Computational Analysis of Cell Dynamics in Videos with Hierarchical-Pooled Deep-Convolutional Features

Computational analysis of cellular appearance and its dynamics is used to investigate physiological properties of cells in biomedical research. In consideration of the great success of deep learning in video analysis, we first introduce two-stream convolutional networks (ConvNets) to automatically learn the biologically meaningful dynamics from raw live-cell videos. However, the two-stream ConvNets lack the ability to capture long-range video evolution. Therefore, a novel hierarchical pooling strategy is proposed to model the cell dynamics in a whole video, which is composed of trajectory pooling for short-term dynamics and rank pooling for long-range ones. Experimental results demonstrate that the proposed pipeline effectively captures the spatiotemporal dynamics from the raw live-cell videos and outperforms existing methods on our cell video database.

In vivo imaging of emerging endocrine cells reveals a requirement for PI3K-regulated motility in pancreatic islet morphogenesis

The three-dimensional architecture of the pancreatic islet is integral to beta cell function, but the process of islet formation remains poorly understood due to the difficulties of imaging internal organs with cellular resolution. Within transparent zebrafish larvae, the developing pancreas is relatively superficial and thus amenable to live imaging approaches. We performed in vivo time-lapse and longitudinal imaging studies to follow islet development, visualizing both naturally occurring islet cells and cells arising with an accelerated timecourse following an induction approach. These studies revealed previously unappreciated fine dynamic protrusions projecting between neighboring and distant endocrine cells. Using pharmacological compound and toxin interference approaches, and single-cell analysis of morphology and cell dynamics, we determined that endocrine cell motility is regulated by phosphoinositide 3-kinase (PI3K) and G-protein-coupled receptor (GPCR) signaling. Linking cell dynamics to islet formation, perturbation of protrusion formation disrupted endocrine cell coalescence, and correlated with decreased islet cell differentiation. These studies identified novel cell behaviors contributing to islet morphogenesis, and suggest a model in which dynamic exploratory filopodia establish cell-cell contacts that subsequently promote cell clustering.

Summary: Pancreatic endocrine cells extend previously unrecognized dynamic, flexible, fine projections to guide clustering into a compacted islet in a process regulated by PI3K and GPCR.

FiloQuant reveals increased filopodia density during breast cancer progression

Defective filopodia formation is linked to pathologies such as cancer, wherein actively protruding filopodia, at the invasive front, accompany cancer cell dissemination. Despite wide biological significance, delineating filopodia function in complex systems remains challenging and is particularly hindered by lack of compatible methods to quantify filopodia properties. Here, we present FiloQuant, a freely available ImageJ plugin, to detect filopodia-like protrusions in both fixed- and live-cell microscopy data. We demonstrate that FiloQuant can extract quantifiable information, including protrusion dynamics, density, and length, from multiple cell types and in a range of microenvironments. In cellular models of breast ductal carcinoma in situ, we reveal a link between filopodia formation at the cell-matrix interface, in collectively invading cells and 3D tumor spheroids, and the in vitro invasive capacity of the carcinoma. Finally, using intravital microscopy, we observe that tumor spheroids display filopodia in vivo, supporting a potential role for these protrusions during tumorigenesis.

Filopodyan: An open-source pipeline for the analysis of filopodia

Filopodia have important sensory and mechanical roles in motile cells. The recruitment of actin regulators, such as ENA/VASP proteins, to sites of protrusion underlies diverse molecular mechanisms of filopodia formation and extension. We developed Filopodyan (filopodia dynamics analysis) in Fiji and R to measure fluorescence in filopodia and at their tips and bases concurrently with their morphological and dynamic properties. Filopodyan supports high-throughput phenotype characterization as well as detailed interactive editing of filopodia reconstructions through an intuitive graphical user interface. Our highly customizable pipeline is widely applicable, capable of detecting filopodia in four different cell types in vitro and in vivo. We use Filopodyan to quantify the recruitment of ENA and VASP preceding filopodia formation in neuronal growth cones, and uncover a molecular heterogeneity whereby different filopodia display markedly different responses to changes in the accumulation of ENA and VASP fluorescence in their tips over time.

Cell migration, intercalation and growth regulate mammalian cochlear extension

Developmental remodeling of the sensory epithelium of the cochlea is required for the formation of an elongated, tonotopically organized auditory organ, but the cellular processes that mediate these events are largely unknown. We used both morphological assessments of cellular rearrangements and time-lapse imaging to visualize cochlear remodeling in mouse. Analysis of cell redistribution showed that the cochlea extends through a combination of radial intercalation and cell growth. Live imaging demonstrated that concomitant cellular intercalation results in a brief period of epithelial convergence, although subsequent changes in cell size lead to medial-lateral spreading. Supporting cells, which retain contact with the basement membrane, exhibit biased protrusive activity and directed movement along the axis of extension. By contrast, hair cells lose contact with the basement membrane, but contribute to continued outgrowth through increased cell size. Regulation of cellular protrusions, movement and intercalation within the cochlea all require myosin II. These results establish, for the first time, many of the cellular processes that drive the distribution of sensory cells along the tonotopic axis of the cochlea.

Engineering extrinsic disorder to control protein activity in living cells

Optogenetic and chemogenetic control of proteins has revealed otherwise inaccessible facets of signaling dynamics. Here, we use light- or ligand-sensitive domains to modulate the structural disorder of diverse proteins, thereby generating robust allosteric switches. Sensory domains were inserted into nonconserved, surface-exposed loops that were tight and identified computationally as allosterically coupled to active sites. Allosteric switches introduced into motility signaling proteins (kinases, guanosine triphosphatases, and guanine exchange factors) controlled conversion between conformations closely resembling natural active and inactive states, as well as modulated the morphodynamics of living cells. Our results illustrate a broadly applicable approach to design physiological protein switches.

A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex signaling mechanisms underlying filopodial initiation, elongation and subsequent stabilization or retraction, it is crucial to determine the spatio-temporal protein activity in these dynamic structures. To analyze protein function in filopodia, we recently developed a semi-automated tracking algorithm that adapts to filopodial shape-changes, thus allowing parallel analysis of protrusion dynamics and relative protein concentration along the whole filopodial length. Here, we present a detailed step-by-step protocol for optimized cell handling, image acquisition and software analysis. We further provide instructions for the use of optional features during image analysis and data representation, as well as troubleshooting guidelines for all critical steps along the way. Finally, we also include a comparison of the described image analysis software with other programs available for filopodia quantification. Together, the presented protocol provides a framework for accurate analysis of protein dynamics in filopodial protrusions using image analysis software.

Characterization of single cell dynamic morphology by local deformation pattern modeling

Computational analysis of cell dynamic morphology in time-lapse images has become a new topic of biomedical research. For single cell, it is a challenging task to consider the spatial inconsistency and the temporal accumulation of cell deformation. This paper introduces an innovative automate analysis method, in which temporal features of contour point deformation are captured and then local deformation pattern is modeled to characterize cell dynamic morphology and predict cell activation statue. We applied the method to classify lymphocyte videos of multiple groups. Experimental results demonstrate that the proposed method overcomes existing methods in accuracy and robustness.

Mathematical modeling for meshwork formation of endothelial cells in fibrin gels

Vasculogenesis is the earliest process in development for spontaneous formation of a primitive capillary network from endothelial progenitor cells. When human umbilical vein endothelial cells (HUVECs) are cultured on Matrigel, they spontaneously form a network structure which is widely used as an in vitro model of vasculogenesis. Previous studies indicated that chemotaxis or gel deformation was involved in spontaneous pattern formation. In our study, we analyzed the mechanism of vascular pattern formation using a different system, meshwork formation by HUVECs embedded in fibrin gels. Unlike the others, this experimental system resulted in a perfusable endothelial network in vitro. We quantitatively observed the dynamics of endothelial cell protrusion and developed a mathematical model for one-dimensional dynamics. We then extended the one-dimensional model to two-dimensions. The model showed that random searching by endothelial cells was sufficient to generate the observed network structure in fibrin gels.