Interplay between morphogen-directed positional information systems and physiological signaling

Contact area and tissue growth dynamics shape synthetic juxtacrine signaling patterns

Cell-cell communication through direct contact, or juxtacrine signaling, is important in development, disease, and many areas of physiology. Synthetic forms of juxtacrine signaling can be precisely controlled and operate orthogonally to native processes, making them a powerful reductionist tool with which to address fundamental questions in cell-cell communication in vivo. Here we investigate how cell-cell contact length and tissue growth dynamics affect juxtacrine signal responses through implementing a custom synthetic gene circuit in Drosophila wing imaginal discs alongside mathematical modeling to determine synthetic Notch (synNotch) activation patterns. We find that the area of contact between cells largely determines the extent of synNotch activation, leading to the prediction that the shape of the interface between signal-sending and signal-receiving cells will impact the magnitude of the synNotch response. Notably, synNotch outputs form a graded spatial profile that extends several cell diameters from the signal source, providing evidence that the response to juxtacrine signals can persist in cells as they proliferate away from source cells, or that cells remain able to communicate directly over several cell diameters. Our model suggests the former mechanism may be sufficient, since it predicts graded outputs without diffusion or long-range cell-cell communication. Overall, we identify that cell-cell contact area together with output synthesis and decay rates likely govern the pattern of synNotch outputs in both space and time during tissue growth, insights that may have broader implications for juxtacrine signaling in general.

Biophysical control of plasticity and patterning in regeneration and cancer

Cells and tissues display a remarkable range of plasticity and tissue-patterning activities that are emergent of complex signaling dynamics within their microenvironments. These properties, which when operating normally guide embryogenesis and regeneration, become highly disordered in diseases such as cancer. While morphogens and other molecular factors help determine the shapes of tissues and their patterned cellular organization, the parallel contributions of biophysical control mechanisms must be considered to accurately predict and model important processes such as growth, maturation, injury, repair, and senescence. We now know that mechanical, optical, electric, and electromagnetic signals are integral to cellular plasticity and tissue patterning. Because biophysical modalities underly interactions between cells and their extracellular matrices, including cell cycle, metabolism, migration, and differentiation, their applications as tuning dials for regenerative and anti-cancer therapies are being rapidly exploited. Despite this, the importance of cellular communication through biophysical signaling remains disproportionately underrepresented in the literature. Here, we provide a review of biophysical signaling modalities and known mechanisms that initiate, modulate, or inhibit plasticity and tissue patterning in models of regeneration and cancer. We also discuss current approaches in biomedical engineering that harness biophysical control mechanisms to model, characterize, diagnose, and treat disease states.

Information integration during bioelectric regulation of morphogenesis of the embryonic frog brain

Spatiotemporal patterns of cellular resting potential regulate several aspects of development. One key aspect of the bioelectric code is that transcriptional and morphogenetic states are determined not by local, single-cell, voltage levels but by specific distributions of voltage across cell sheets. We constructed and analyzed a minimal dynamical model of collective gene expression in cells based on inputs of multicellular voltage patterns. Causal integration analysis revealed a higher-order mechanism by which information about the voltage pattern was spatiotemporally integrated into gene activity, as well as a division of labor among and between the bioelectric and genetic components. We tested and confirmed predictions of this model in a system in which bioelectric control of morphogenesis regulates gene expression and organogenesis: the embryonic brain of the frog Xenopus laevis. This study demonstrates that machine learning and computational integration approaches can advance our understanding of the information-processing underlying morphogenetic decision-making, with a potential for other applications in developmental biology and regenerative medicine.

Quantitative insights in tissue growth and morphogenesis with optogenetics

Cells communicate with each other to jointly regulate cellular processes during cellular differentiation and tissue morphogenesis. This multiscale coordination arises through the spatiotemporal activity of morphogens to pattern cell signaling and transcriptional factor activity. This coded information controls cell mechanics, proliferation, and differentiation to shape the growth and morphogenesis of organs. While many of the molecular components and physical interactions have been identified in key model developmental systems, there are still many unresolved questions related to the dynamics involved due to challenges in precisely perturbing and quantitatively measuring signaling dynamics. Recently, a broad range of synthetic optogenetic tools have been developed and employed to quantitatively define relationships between signal transduction and downstream cellular responses. These optogenetic tools can control intracellular activities at the single cell or whole tissue scale to direct subsequent biological processes. In this brief review, we highlight a selected set of studies that develop and implement optogenetic tools to unravel quantitative biophysical mechanisms for tissue growth and morphogenesis across a broad range of biological systems through the manipulation of morphogens, signal transduction cascades, and cell mechanics. More generally, we discuss how optogenetic tools have emerged as a powerful platform for probing and controlling multicellular development.

Hedgehog morphogen gradient is robust towards variations in tissue morphology in Drosophila

During tissue development, gradients of secreted signaling molecules known as morphogens provide cells with positional information. The mechanisms underlying morphogen spreading have been widely studied, however, it remains largely unexplored whether the shape of morphogen gradients is influenced by tissue morphology. Here, we developed an analysis pipeline to quantify the distribution of proteins within a curved tissue. We applied it to the Hedgehog morphogen gradient in the Drosophila wing and eye-antennal imaginal discs, which are flat and curved tissues, respectively. Despite a different expression profile, the slope of the Hedgehog gradient was comparable between the two tissues. Moreover, inducing ectopic folds in wing imaginal discs did not affect the slope of the Hedgehog gradient. Suppressing curvature in the eye-antennal imaginal disc also did not alter the Hedgehog gradient slope but led to ectopic Hedgehog expression. In conclusion, through the development of an analysis pipeline that allows quantifying protein distribution in curved tissues, we show that the Hedgehog gradient is robust towards variations in tissue morphology.

Innovative multidimensional models in a high-throughput-format for different cell types of endocrine origin

The adrenal gland provides an important function by integrating neuronal, immune, vascular, metabolic and endocrine signals under a common organ capsule. It is the central organ of the stress response system and has been implicated in numerous stress-related disorders. While for other diseases, regeneration of healthy organ tissue has been aimed at such approaches are lacking for endocrine diseases - with the exception of type-I-diabetes. Moreover, adrenal tumor formation is very common, however, appropriate high-throughput applications reflecting the high heterogeneity and furthermore relevant 3D-structures in vitro are still widely lacking. Recently, we have initiated the development of standardized multidimensional models of a variety of endocrine cell/tissue sources in a new multiwell-format. Firstly, we confirmed common applicability for pancreatic pseudo-islets. Next, we translated applicability for spheroid establishment to adrenocortical cell lines as well as patient material to establish spheroids from malignant, but also benign adrenal tumors. We aimed furthermore at the development of bovine derived healthy adrenal organoids and were able to establish steroidogenic active organoids containing both, cells of cortical and medullary origin. Overall, we hope to open new avenues for basic research, endocrine cancer and adrenal tissue-replacement-therapies as we demonstrate potential for innovative mechanistic insights and personalized medicine in endocrine (tumor)-biology.

MAPPER: An Open-Source, High-Dimensional Image Analysis Pipeline Unmasks Differential Regulation of Drosophila Wing Features

Phenomics requires quantification of large volumes of image data, necessitating high throughput image processing approaches. Existing image processing pipelines for Drosophila wings, a powerful genetic model for studying the underlying genetics for a broad range of cellular and developmental processes, are limited in speed, precision, and functional versatility. To expand on the utility of the wing as a phenotypic screening system, we developed MAPPER, an automated machine learning-based pipeline that quantifies high-dimensional phenotypic signatures, with each dimension quantifying a unique morphological feature of the Drosophila wing. MAPPER magnifies the power of Drosophila phenomics by rapidly quantifying subtle phenotypic differences in sample populations. We benchmarked MAPPER’s accuracy and precision in replicating manual measurements to demonstrate its widespread utility. The morphological features extracted using MAPPER reveal variable sexual dimorphism across Drosophila species and unique underlying sex-specific differences in morphogen signaling in male and female wings. Moreover, the length of the proximal-distal axis across the species and sexes shows a conserved scaling relationship with respect to the wing size. In sum, MAPPER is an open-source tool for rapid, high-dimensional analysis of large imaging datasets. These high-content phenomic capabilities enable rigorous and systematic identification of genotype-to-phenotype relationships in a broad range of screening and drug testing applications and amplify the potential power of multimodal genomic approaches.

Mechanics and self-organization in tissue development

Self-organization is an all-important feature of living systems that provides the means to achieve specialization and functionality at distinct spatio-temporal scales. Herein, we review this concept by addressing the packing organization of cells, the sorting/compartmentalization phenomenon of cell populations, and the propagation of organizing cues at the tissue level through traveling waves. We elaborate on how different theoretical models and tools from Topology, Physics, and Dynamical Systems have improved the understanding of self-organization by shedding light on the role played by mechanics as a driver of morphogenesis. Altogether, by providing a historical perspective, we show how ideas and hypotheses in the field have been revisited, developed, and/or rejected and what are the open questions that need to be tackled by future research.

Genetic Network Architecture and Environmental Cues Drive Spatial Organization of Phenotypic Division of Labor in Streptomyces coelicolor

A number of bacteria are known to differentiate into cells with distinct phenotypic traits during processes such as biofilm formation or the development of reproductive structures. These cell types, by virtue of their specialized functions, embody a division of labor. However, how bacteria build spatial patterns of differentiated cells is not well understood. Here, we examine the factors that drive spatial patterns in divisions of labor in colonies of Streptomyces coelicolor, a multicellular bacterium capable of synthesizing an array of antibiotics and forming complex reproductive structures (e.g., aerial hyphae and spores). Using fluorescent reporters, we demonstrate that the pathways for antibiotic biosynthesis and aerial hypha formation are activated in distinct waves of gene expression that radiate outwards in S. coelicolor colonies. We also show that the spatiotemporal separation of these cell types depends on a key activator in the developmental pathway, AdpA. Importantly, when we manipulated local gradients by growing competing microbes nearby, or through physical disruption, expression in these pathways could be decoupled and/or disordered, respectively. Finally, the normal spatial organization of these cell types was partially restored with the addition of a siderophore, a public good made by these organisms, to the growth medium. Together, these results indicate that spatial divisions of labor in S. coelicolor colonies are determined by a combination of physiological gradients and regulatory network architecture, key factors that also drive patterns of cellular differentiation in multicellular eukaryotic organisms.

Comparative genomic analysis of human GLI2 locus using slowly evolving fish revealed the ancestral gnathostome set of early developmental enhancers

Background

The zinc finger‐containing transcription factor Gli2, is a key mediator of Hedgehog (Hh) signaling and participates in embryonic patterning of various organs including the central nervous system (CNS) and limbs. Abnormal expression of Gli2 can impede the transcription of Hh target genes through disruption of proper balance between Gli2 and Gli3 functions. Therefore, delineation of enhancers that are required for complementary roles of Glis would allow the interrogation of those pathogenic variants that cause gene dysregulation, and a corresponding abnormal phenotype. Previously, we reported tissue‐specific enhancers for Gli family including Gli2 through direct tetrapod‐teleost comparisons.

Results

Here, we employed the sequence alignments of slowly evolving spotted gar and elephant shark and have identified six novel conserved noncoding elements in human GLI2 containing locus. Zebrafish‐based transgenic assays revealed that combined action of these autonomous CNEs reflects many aspects of Gli2 specific endogenous transcriptional activity, including CNS and pectoral fins.

Conclusion

Taken together with our previous findings, this study suggests that Hh‐signaling controlled deployment of Gli2 activity in embryonic patterning arose in the common ancestor of gnathostomes. These GLI2 specific cis‐regulatory modules will help to identify DNA variants that probably reside outside of coding intervals and are associated with congenital anomalies.

We performed a phylogenetic footprint analyses of human GLI2 containing locus by incorporating relatively slowly evolving gar and elephant shark genomes and have identified multiple novel conserved non‐coding elements (CNEs) that were not predicted by direct human‐teleostcomparisons.

Comparative analyses suggest that majority of the GLI2 associated CNEs identified in the present data and reported previously arose in the common ancestor of gnathostomes but lost in teleosts, presumably because of fast teleost sequence evolution.

Functional testing of GLI2 associated CNEs by employing zebrafish based transgenic reporter assays revealed their tissue specific cis‐regulatory potential that corresponds with the results based on whole‐mount in situ hybridization analysis of gli2 mRNA in zebrafish.

The delineated set of GLI2 associated enhancers can be further interrogated to determine their role in canonical Hh signaling, gene dysregulation, and a corresponding congenital anomaly.