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.

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.

Cells need to sense and respond to their environment. To do this, they have dedicated proteins that interpret outside signals and convert them into appropriate responses that are only active at a specific time and location within the cell. However, in many diseases, including cancer, these signaling proteins are switched on for too long or are active in the wrong place. To better understand why this is the case, researchers manipulate proteins to identify the processes they regulate. One way to do this is to engineer proteins so that they can be controlled by light, turning them either on or off. Ideally, a light-controlled tool can activate proteins at defined times, control proteins in specific locations within the cell and regulate any protein of interest. However, current methods do not combine all of these requirements in one tool, and scientists often have to use different methods, depending on the topic they are researching. Now, Shaaya et al. set out to develop a single tool that combines all required features. The researchers engineered a light-sensitive 'switch' that allowed them to activate a specific protein by illuminating it with blue light and to deactivate it by turning the light off. Unlike other methods, the new tool uses a light-sensitive switch that works like a clamp. In the dark, the clamp is open, which 'stretches' and distorts the protein, rendering it inactive. In light, however, the clamp closes and the structure of the protein and its activity are restored. Moreover, it can activate proteins multiple times, control proteins in specific locations within the cell and it can be applied to a variety of proteins. This specific design makes it possible to combine multiple features in one tool that will both simplify and broaden its use to investigate specific proteins and signaling pathways in a broad range of diseases.

Biomechanics of Endothelial Tubule Formation Differentially Modulated by Cerebral Cavernous Malformation Proteins.

At early stages of organismal development, endothelial cells self-organize into complex networks subsequently giving rise to mature blood vessels. The compromised collective behavior of endothelial cells leads to the development of a number of vascular diseases, many of which can be life-threatening. Cerebral cavernous malformation is an example of vascular diseases caused by abnormal development of blood vessels in the brain. Despite numerous efforts to date, enlarged blood vessels (cavernomas) can be effectively treated only by risky and complex brain surgery. In this work, we use a comprehensive simulation model to dissect the mechanisms contributing to an emergent behavior of the multicellular system. By tightly integrating computational and experimental approaches we gain a systems-level understanding of the basic mechanisms of vascular tubule formation, its destabilization, and pharmacological rescue, which may facilitate the development of new strategies for manipulating collective endothelial cell behavior in the disease context.

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.

Temporal regulation of morphogenetic events in Saccharomyces cerevisiae.

Tip growth in fungi involves highly polarized secretion and modification of the cell wall at the growing tip. The genetic requirements for initiating polarized growth are perhaps best understood for the model budding yeast Saccharomyces cerevisiae. Once the cell is committed to enter the cell cycle by activation of G1 cyclin/cyclin-dependent kinase (CDK) complexes, the polarity regulator Cdc42 becomes concentrated at the presumptive bud site, actin cables are oriented toward that site, and septin filaments assemble into a ring around the polarity site. Several minutes later, the bud emerges. Here, we investigated the mechanisms that regulate the timing of these events at the single-cell level. Septin recruitment was delayed relative to polarity establishment, and our findings suggest that a CDK-dependent septin "priming" facilitates septin recruitment by Cdc42. Bud emergence was delayed relative to the initiation of polarized secretion, and our findings suggest that the delay reflects the time needed to weaken the cell wall sufficiently for the cell to bud. Rho1 activation by Rom2 occurred at around the time of bud emergence, perhaps in response to local cell-wall weakening. This report reveals regulatory mechanisms underlying the morphogenetic events in the budding yeast.