A fine kinetic balance of interactions directs transcription factor hubs to genes.

Eukaryotic gene regulation relies on the binding of sequence-specific transcription factors (TFs). TFs bind chromatin transiently yet occupy their target sites by forming high-local concentration microenvironments (hubs and condensates) that increase the frequency of binding events. Despite their ubiquity, such microenvironments have been difficult to study in endogenous contexts due to technical limitations. Here, we overcome these limitations and investigate how hubs drive TF occupancy at their targets. Using a DNA binding perturbation to a hub-forming TF, Zelda, in Drosophila embryos, we find that hub properties, including the stability and frequencies of associations to targets, are key determinants of TF occupancy. Our data suggest that the targeting of these hubs is driven not just by specific DNA motif recognition, but also by a fine-tuned kinetic balance of interactions between TFs and their co-binding partners.

Localization of the Drosophila pioneer factor GAF to subnuclear foci is driven by DNA binding and required to silence satellite repeat expression.

The eukaryotic genome is organized to enable the precise regulation of gene expression. This organization is established as the embryo transitions from a fertilized gamete to a totipotent zygote. To understand the factors and processes that drive genomic organization, we focused on the pioneer factor GAGA factor (GAF) that is required for early development in Drosophila. GAF transcriptionally activates the zygotic genome and is localized to subnuclear foci. This non-uniform distribution is driven by binding to highly abundant GA repeats. At GA repeats, GAF is necessary to form heterochromatin and silence transcription. Thus, GAF is required to establish both active and silent regions. We propose that foci formation enables GAF to have opposing transcriptional roles within a single nucleus. Our data support a model in which the subnuclear concentration of transcription factors acts to organize the nucleus into functionally distinct domains essential for the robust regulation of gene expression.

Actin Filaments Couple the Protrusive Tips to the Nucleus through the I-BAR Domain Protein IRSp53 during the Migration of Cells on 1D Fibers.

The cell migration cycle, well-established in 2D, proceeds with forming new protrusive structures at the cell membrane and subsequent redistribution of contractile machinery. Three-dimensional (3D) environments are complex and composed of 1D fibers, and 1D fibers are shown to recapitulate essential features of 3D migration. However, the establishment of protrusive activity at the cell membrane and contractility in 1D fibrous environments remains partially understood. Here the role of membrane curvature regulator IRSp53 is examined as a coupler between actin filaments and plasma membrane during cell migration on single, suspended 1D fibers. IRSp53 depletion reduced cell-length spanning actin stress fibers that originate from the cell periphery, protrusive activity, and contractility, leading to uncoupling of the nucleus from cellular movements. A theoretical model capable of predicting the observed transition of IRSp53-depleted cells from rapid stick-slip migration to smooth and slower migration due to reduced actin polymerization at the cell edges is developed, which is verified by direct measurements of retrograde actin flow using speckle microscopy. Overall, it is found that IRSp53 mediates actin recruitment at the cellular tips leading to the establishment of cell-length spanning fibers, thus demonstrating a unique role of IRSp53 in controlling cell migration in 3D.

Quantitative biophysical metrics for rapid evaluation of ovarian cancer metastatic potential.

Ovarian cancer is routinely diagnosed long after the disease has metastasized through the fibrous submesothelium. Despite extensive research in the field linking ovarian cancer progression to increasingly poor prognosis, there are currently no validated cellular markers or hallmarks of ovarian cancer that can predict metastatic potential. To discern disease progression across a syngeneic mouse ovarian cancer progression model, here we fabricated extracellular matrix mimicking suspended fiber networks: cross-hatches of mismatch diameters for studying protrusion dynamics, aligned same diameter networks of varying interfiber spacing for studying migration, and aligned nanonets for measuring cell forces. We found that migration correlated with disease while a force-disease biphasic relationship exhibited F-actin stress fiber network dependence. However, unique to suspended fibers, coiling occurring at the tips of protrusions and not the length or breadth of protrusions displayed the strongest correlation with metastatic potential. To confirm that our findings were more broadly applicable beyond the mouse model, we repeated our studies in human ovarian cancer cell lines and found that the biophysical trends were consistent with our mouse model results. Altogether, we report complementary high throughput and high content biophysical metrics capable of identifying ovarian cancer metastatic potential on a timescale of hours.

Single-molecule tracking technologies for quantifying the dynamics of gene regulation in cells, tissue and embryos.

For decades, we have relied on population and time-averaged snapshots of dynamic molecular scale events to understand how genes are regulated during development and beyond. The advent of techniques to observe single-molecule kinetics in increasingly endogenous contexts, progressing from in vitro studies to living embryos, has revealed how much we have missed. Here, we provide an accessible overview of the rapidly expanding family of technologies for single-molecule tracking (SMT), with the goal of enabling the reader to critically analyse single-molecule studies, as well as to inspire the application of SMT to their own work. We start by overviewing the basics of and motivation for SMT experiments, and the trade-offs involved when optimizing parameters. We then cover key technologies, including fluorescent labelling, excitation and detection optics, localization and tracking algorithms, and data analysis. Finally, we provide a summary of selected recent applications of SMT to study the dynamics of gene regulation.

Semantic Segmentation of Smartphone Wound Images: Comparative Analysis of AHRF and CNN-Based Approaches.

Smartphone wound image analysis has recently emerged as a viable way to assess healing progress and provide actionable feedback to patients and caregivers between hospital appointments. Segmentation is a key image analysis step, after which attributes of the wound segment (e.g. wound area and tissue composition) can be analyzed. The Associated Hierarchical Random Field (AHRF) formulates the image segmentation problem as a graph optimization problem. Handcrafted features are extracted, which are then classified using machine learning classifiers. More recently deep learning approaches have emerged and demonstrated superior performance for a wide range of image analysis tasks. FCN, U-Net and DeepLabV3 are Convolutional Neural Networks used for semantic segmentation. While in separate experiments each of these methods have shown promising results, no prior work has comprehensively and systematically compared the approaches on the same large wound image dataset, or more generally compared deep learning vs non-deep learning wound image segmentation approaches. In this paper, we compare the segmentation performance of AHRF and CNN approaches (FCN, U-Net, DeepLabV3) using various metrics including segmentation accuracy (dice score), inference time, amount of training data required and performance on diverse wound sizes and tissue types. Improvements possible using various image pre- and post-processing techniques are also explored. As access to adequate medical images/data is a common constraint, we explore the sensitivity of the approaches to the size of the wound dataset. We found that for small datasets (< 300 images), AHRF is more accurate than U-Net but not as accurate as FCN and DeepLabV3. AHRF is also over 1000x slower. For larger datasets (> 300 images), AHRF saturates quickly, and all CNN approaches (FCN, U-Net and DeepLabV3) are significantly more accurate than AHRF.

Cancer Cells Sense Fibers by Coiling on them in a Curvature-Dependent Manner.

Metastatic cancer cells sense the complex and heterogeneous fibrous extracellular matrix (ECM) by formation of protrusions, and our knowledge of how cells physically recognize these fibers remains in its infancy. Here, using suspended ECM-mimicking isodiameter fibers ranging from 135 to 1,000 nm, we show that metastatic breast cancer cells sense fiber diameters differentially by coiling (wrapping-around) on them in a curvature-dependent manner, whereas non-tumorigenic cells exhibit diminished coiling. We report that coiling occurs at the tip of growing protrusions and the coil width and coiling rate increase in a curvature-dependent manner, but time to maximum coil width occurs biphasically. Interestingly, bundles of 135-nm diameter fibers recover coiling width and rate on 1,000-nm-diameter fibers. Coiling also coincides with curvature-dependent persistent and ballistic transport of endogenous granules inside the protrusions. Altogether, our results lay the groundwork to link biophysical sensing with biological signaling to quantitate pro- and anti-invasive fibrous environments. VIDEO ABSTRACT.

Integrating nanofibers with biochemical gradients to investigate physiologically-relevant fibroblast chemotaxis.

Persistent cell migration can occur due to anisotropy in the extracellular matrix (ECM), the gradient of a chemo-effector, or a combination of both. Through a variety of in vitro platforms, the contributions of either stimulus have been extensively studied, while the combined effect of both cues remains poorly described. Here, we report an integrative microfluidic chemotaxis assay device that enables the study of single cell chemotaxis on ECM-mimicking, aligned, and suspended nanofibers. Using this assay, we evaluated the effect of fiber spacing on the morphology and chemotaxis response of embryonic murine NIH/3T3 fibroblasts in the presence of temporally invariant, linear gradients of platelet-derived growth factor-BB (PDGF-BB). We found that the strength of PDGF-mediated chemotaxis response depends on not only the gradient slope but also the cell morphology. Low aspect ratio (3.4 ± 0.2) cells on flat substrata exhibited a chemotaxis response only at a PDGF-BB gradient of 0-10 ng mL-1. However, high aspect ratio (19.1 ± 0.7) spindle-shaped cells attached to individual fibers exhibited maximal chemotaxis response at a ten-fold shallower gradient of 0-1 ng mL-1, which was robustly maintained up to 0-10 ng mL-1. Quadrilateral-shaped cells of intermediate aspect ratio (13.6 ± 0.8) attached to two fibers exhibited a weaker response compared to the spindle-shaped cells, but still stronger compared to cells attached to 2D featureless substrata. Through pharmacological inhibition, we show that the mesenchymal chemotaxis pathway is conserved in cells on fibers. Altogether, our findings show that chemotaxis on ECM-mimicking fibers is modulated by fiber spacing-driven cell shape and can be significantly different from the behavior observed on flat 2D substrata. We envisage that this microfluidic platform will have wide applicability in understanding the combined role of ECM architecture and chemotaxis in physiological and pathological processes.

Design of Fiber Networks for Studying Metastatic Invasion.

Cancer metastasis, the dissemination of cancer cells from the primary tumor site to distal organs in the body, is one of the leading causes of cancer-related deaths globally. It is now appreciated that metastatic cells take advantage of specific features of surrounding fibrous extracellular matrix that favors invasion. However, the exact contributions of the role of fiber feature size, orientation, and organization remain only partially described. Here using non-electrospinning Spinneret based Tunable Engineered Parameters (STEP) fiber platform, we detail our quantitative findings over the past decade on cancer cell behavior in environments of controlled fiber dimensions, orientation, and hierarchy that can mimic essential features of native ECM. We present a biophysical model of invasion along aligned fibers that starts with cells forming protrusions followed by invasion of cells from a monolayer in single, multi-cell chain and collective modes. Using a mismatch of fiber diameters, we describe a new method to protrutype single protrusions and describe migratory behavior of cells in different shapes. Altogether, control over fiber geometry and network architecture enables the STEP platform to unlock a new paradigm in the interrogation of the fundamental biophysical mechanisms underlying the migratory journey of cells during cancer metastasis.

Cancer Protrusions on a Tightrope: Nanofiber Curvature Contrast Quantitates Single Protrusion Dynamics.

Cell migration is studied with the traditional focus on protrusion-driven cell body displacement, while less is known on morphodynamics of individual protrusions themselves, especially in fibrous environments mimicking extracellular matrix. Here, using suspended fibers, we report integrative and multiscale abilities to study protrusive behavior independent of cell body migration. By manipulating the diameter of fibers in orthogonal directions, we constrain cell migration along large diameter (2 µm) base fibers, while solely allowing cells to sense, initiate, and mature protrusions on orthogonally deposited high-curvature/low diameter (∼100, 200, and 600 nm) protrusive fibers and low-curvature (∼300 and 600 nm width) protrusive flat ribbons. In doing so, we report a set of morphodynamic metrics that precisely quantitate protrusion dynamics. Protrusion growth and maturation occur by rapid broadening at the base to achieve long lengths, a behavior dramatically influenced by curvature. While flat ribbons universally induce the formation of broad and long protrusions, we quantitatively protrutype protrusive behavior of two highly invasive cancer cell lines and find breast adenocarcinoma (MDA-MB-231) to exhibit sensitivity to fiber curvature higher than that of brain glioblastoma DBTRG-05MG. Furthermore, while actin and microtubules localize within protrusions of all sizes, we quantify protrusion size-driven localization of vimentin and, contrary to current understanding, report that vimentin is not required to form protrusions. Using multiple protrusive fibers, we quantify high coordination between hierarchical branches of individual protrusions and describe how the spatial configuration of multiple protrusions regulates cell migratory state. Finally, we describe protrusion-driven shedding and collection of cytoplasmic debris.