Signal Processing during Developmental Multicellular Patterning

Developing design strategies for tissue engineering and regenerative medicine is limited by our nascent understanding of how cell populations self-organize into multicellular structures on synthetic scaffolds. Mechanistic insights can be gleaned from the quantitative analysis of biomolecular signals that drive multicellular patterning during the natural processes of embryonic and adult development. This review describes three critical layers of signal processing that govern multicellular patterning: spatiotemporal presentation of extracellular cues, intracellular signaling networks that mediate crosstalk among extracellular cues, and finally, intranuclear signal integration at the level of transcriptional regulation. At every level in this hierarchy, the quantitative attributes of signals have a profound impact on patterning. We discuss how experiments and mathematical models are being used to uncover these quantitative features and their impact on multicellular phenotype

Predicting Phenotypic Diversity and the Underlying Quantitative Molecular Transitions

During development, signaling networks control the formation of multicellular patterns. To what extent quantitative fluctuations in these complex networks may affect multicellular phenotype remains unclear. Here, we describe a computational approach to predict and analyze the phenotypic diversity that is accessible to a developmental signaling network. Applying this framework to vulval development in C. elegans, we demonstrate that quantitative changes in the regulatory network can render ~500 multicellular phenotypes. This phenotypic capacity is an order-of-magnitude below the theoretical upper limit for this system but yet is large enough to demonstrate that the system is not restricted to a select few outcomes. Using metrics to gauge the robustness of these phenotypes to parameter perturbations, we identify a select subset of novel phenotypes that are the most promising for experimental validation. In addition, our model calculations provide a layout of these phenotypes in network parameter space. Analyzing this landscape of multicellular phenotypes yielded two significant insights. First, we show that experimentally well-established mutant phenotypes may be rendered using non-canonical network perturbations. Second, we show that the predicted multicellular patterns include not only those observed in C. elegans, but also those occurring exclusively in other species of the Caenorhabditis genus. This result demonstrates that quantitative diversification of a common regulatory network is indeed demonstrably sufficient to generate the phenotypic differences observed across three major species within the Caenorhabditis genus. Using our computational framework, we systematically identify the quantitative changes that may have occurred in the regulatory network during the evolution of these species. Our model predictions show that significant phenotypic diversity may be sampled through quantitative variations in the regulatory network without overhauling the core network architecture. Furthermore, by comparing the predicted landscape of phenotypes to multicellular patterns that have been experimentally observed across multiple species, we systematically trace the quantitative regulatory changes that may have occurred during the evolution of the Caenorhabditis genus

Mechanisms of Ephrin Receptor Protein Kinase-Independent Signaling in Amphid Axon Guidance in Caenorhabditis elegans

Eph receptors and their ephrin ligands are key conserved regulators of axon guidance and can function in a variety of signaling modes. Here we analyze the genetic and cellular requirements for Eph signaling in a Caenorhabditis elegans axon guidance choice point, the ventral guidance of axons in the amphid commissure. The C. elegans Eph receptor EFN-1 has both kinase-dependent and kinase-independent roles in amphid ventral guidance. Of the four C. elegans ephrins, we find that only EFN-1 has a major role in amphid axon ventral guidance, and signals in both a receptor kinase-dependent and kinase-independent manner. Analysis of EFN-1 and EFN-1 expression and tissue-specific requirements is consistent with a model in which VAB-1 acts in amphid neurons, interacting with EFN-1 expressed on surrounding cells. Unexpectedly, left-hand neurons are more strongly affected than right-hand neurons by loss of Eph signaling, indicating a previously undetected left-right asymmetry in the requirement for Eph signaling. By screening candidate genes involved in Eph signaling, we find that the Eph kinase-independent pathway involves the ABL-1 nonreceptor tyrosine kinase and possibly the phosphatidylinositol 3-kinase pathway. Overexpression of ABL-1 is sufficient to rescue EFN-1 ventral guidance defects cell autonomously. Our results reveal new aspects of Eph signaling in a single axon guidance decision in vivo