Publications

For investigations into fate specification and cell rearrangements in live images of preimplantation embryos, automated and accurate 3D instance segmentation of nuclei is invaluable; however, the performance of segmentation methods is limited by the images' low signal-to-noise ratio and high voxel anisotropy and the nuclei's dense packing and variable shapes. Supervised machine learning approaches have the potential to radically improve segmentation accuracy but are hampered by a lack of fully annotated 3D data. In this work, we first establish a novel mouse line expressing near-infrared nuclear reporter H2B-miRFP720. H2B-miRFP720 is the longest wavelength nuclear reporter in mice and can be imaged simultaneously with other reporters with minimal overlap. We then generate a dataset, which we call BlastoSPIM, of 3D microscopy images of H2B-miRFP720-expressing embryos with ground truth for nuclear instance segmentation. Using BlastoSPIM, we benchmark the performance of five convolutional neural networks and identify Stardist-3D as the most accurate instance segmentation method across preimplantation development. Stardist-3D, trained on BlastoSPIM, performs robustly up to the end of preimplantation development (> 100 nuclei) and enables studies of fate patterning in the late blastocyst. We, then, demonstrate BlastoSPIM's usefulness as pre-train data for related problems. BlastoSPIM and its corresponding Stardist-3D models are available at: blastospim.flatironinstitute.org.

In the fruit fly Drosophila melanogaster, two cells in a cyst of 16 interconnected cells have the potential to become the oocyte, but only one of these will assume an oocyte fate as the cysts transition through regions 2a and 2b of the germarium. The mechanism of specification depends on a polarized microtubule network, a dynein dependent Egl:BicD mRNA cargo complex, a special membranous structure called the fusome and its associated proteins, and the translational regulator orb. In this work, we have investigated the role of orb and the fusome in oocyte specification. We show here that specification is a stepwise process. Initially, orb mRNAs accumulate in the two pro-oocytes in close association with the fusome. This association is accompanied by the activation of the orb autoregulatory loop, generating high levels of Orb. Subsequently, orb mRNAs become enriched in only one of the pro-oocytes, the presumptive oocyte, and this is followed, with a delay, by Orb localization to the oocyte. We find that fusome association of orb mRNAs is essential for oocyte specification in the germarium, is mediated by the orb 3′ UTR, and requires Orb protein. We also show that the microtubule minus end binding protein Patronin functions downstream of orb in oocyte specification. Finally, in contrast to a previously proposed model for oocyte selection, we find that the choice of which pro-oocyte becomes the oocyte does not seem to be predetermined by the amount of fusome material in these two cells, but instead depends upon a competition for orb gene products.

The decision to stop growing and mature into an adult is a critical point in development that determines adult body size, impacting multiple aspects of an adult’s biology. In many animals, growth cessation is a consequence of hormone release that appears to be tied to the attainment of a particular body size or condition. Nevertheless, the size-sensing mechanism animals use to initiate hormone synthesis is poorly understood. Here, we develop a simple mathematical model of growth cessation in Drosophila melanogaster, which is ostensibly triggered by the attainment of a critical weight (CW) early in the last instar. Attainment of CW is correlated with the synthesis of the steroid hormone ecdysone, which causes a larva to stop growing, pupate, and metamorphose into the adult form. Our model suggests that, contrary to expectation, the size-sensing mechanism that initiates metamorphosis occurs before the larva reaches CW; that is, the critical-weight phenomenon is a downstream consequence of an earlier size-dependent developmental decision, not a decision point itself. Further, this size-sensing mechanism does not require a direct assessment of body size but emerges from the interactions between body size, ecdysone, and nutritional signaling. Because many aspects of our model are evolutionarily conserved among all animals, the model may provide a general framework for understanding how animals commit to maturing from their juvenile to adult form.

During vertebrate organ morphogenesis, large collectives of cells robustly self-organize to form architectural units (bones, villi, follicles) whose form persists into adulthood. Over the past few decades, mechanisms of organ morphogenesis have been developed predominantly through molecular, genetic, and cellular frameworks. More recently, there has been a resurgence of interest in collective cell and tissue mechanics during organ formation. This approach has amplified the need to clarify and unambiguously link events across biological length scales. Doing so may require reassessing canonical models that continue to guide the field. The most recognized model for organ formation centers around morphogens as determinants of gene expression and morphological patterns. The classical view of a morphogen is that morphogen gradients specify differential gene expression in a distinct spatial order. Because morphogen expression colocalizes with emerging feather and hair follicles, the skin has served as a paradigmatic example of such morphogen prepatterning mechanisms.

When a founder cell and its progeny divide with incomplete cytokinesis, a network forms in which each intercellular bridge corresponds to a past mitotic event. Such networks are required for gamete production in many animals, and different species have evolved diverse final network topologies. Although mechanisms regulating network assembly have been identified in particular organisms, we lack a quantitative framework to understand network assembly and inter-species variability. Motivated by cell networks responsible for oocyte production in invertebrates, where the final topology is typically invariant within each species, we devised a mathematical model for generating cell networks, in which each node is an oscillator and, after a full cycle, the node produces a daughter to which it remains connected. These cell cycle oscillations are transient and coupled via diffusion over the edges of the network. By variation of three biologically motivated parameters, our model generates nearly all such networks currently reported across invertebrates. Furthermore, small parameter variations can rationalize cases of intra-species variation. Because cell networks outside of the ovary often form less deterministically, we propose model generalizations to account for sources of stochasticity.

Large cells often rely on cytoplasmic flows for intracellular transport, maintaining homeostasis, and positioning cellular components. Understanding the mechanisms of these flows is essential for gaining insights into cell function, developmental processes, and evolutionary adaptability. Here, we focus on a class of self-organized cytoplasmic stirring mechanisms that result from fluid-structure interactions between cytoskeletal elements at the cell cortex. Drawing inspiration from streaming flows in late-stage fruit fly oocytes, we propose an analytically tractable active carpet theory. This model deciphers the origins and three-dimensional spatio-temporal organization of such flows. Through a combination of simulations and weakly nonlinear theory, we establish the pathway of the streaming flow to its global attractor: a cell-spanning vortical twister. Our study reveals the inherent symmetries of this emergent flow, its low-dimensional structure, and illustrates how complex fluid-structure interaction aligns with classical solutions in Stokes flow. This framework can be easily adapted to elucidate a broad spectrum of self-organized, cortex-driven intracellular flows.

High wall shear stress (WSS) is associated with risk of atherosclerotic plaque rupture, but there are numerous gaps in validating ultrasound-derived measurements of the parameter. Two major challenges are using simple models of stenosis and only evaluating WSS along a single 2D plane. To overcome these limitations, a novel simulation framework is herein demonstrated. The framework first models volumetric blood flow in actual stenosed human carotid artery geometries (using an immersed interface method (IIM) fluid structure interaction solver) and calculates the associated WSS. Then, the framework projects the modeled blood flow onto scatterers in Field II simulations of its ultrasonic interrogation. Volumetric ultrasound vector Doppler (VD) imaging using an elevationally swept L7-4 linear array was simulated in Field II, with variations in transmit sequences and flow conditions. In a ~55% stenosed human carotid artery under 600 mL/min flow, Bland-Altman analysis showed that a 3-angle plane wave (PW) transmit scheme estimated WSS with 0.04±0.64 Pa error (bias ± 95% CI) relative to the IIM ground truth, whereas transmitting with 5 angles increased accuracy, but decreased precision to -0.01±1.07 Pa, due to aliasing. These findings illustrate that the simulation framework enables direct comparison of data acquisition and processing methods for efficient development, validation, and refinement of WSS estimation methods in realistic clinical environments.

The extracellular signal–regulated kinase (ERK) controls multiple critical processes in the cell and is deregulated in human cancers, congenital abnormalities, immune diseases, and neurodevelopmental syndromes. Catalytic activity of ERK requires dual phosphorylation by an upstream kinase, in a mechanism that can be described by two sequential Michaelis-Menten steps. The estimation of individual reaction rate constants from kinetic data in the full mechanism has proved challenging. Here, we present an analytically tractable approach to parameter estimation that is based on the phase plane representation of ERK activation and yields two combinations of six reaction rate constants in the detailed mechanism. These combinations correspond to the ratio of the specificities of two consecutive phosphorylations and the probability that monophosphorylated substrate does not dissociate from the enzyme before the second phosphorylation. The presented approach offers a language for comparing the effects of mutations that disrupt ERK activation and function in vivo. As an illustration, we use phase plane representation to analyze dual phosphorylation under heterozygous conditions, when two enzyme variants compete for the same substrate.

Vertebrate groups have evolved strikingly diverse color patterns. However, it remains unknown to what extent the diversification of such patterns has been shaped by the proximate, developmental mechanisms that regulate their formation. While these developmental mechanisms have long been inaccessible empirically, here we take advantage of recent insights into rodent pattern formation to investigate the role of development in shaping pattern diversification across rodents. Based on a broad survey of museum specimens, we first establish that various rodents have independently evolved diverse patterns consisting of longitudinal stripes, varying across species in number, color, and relative positioning. We then interrogate this diversity using a simple model that incorporates recent molecular and developmental insights into stripe formation in African striped mice. Our results suggest that, on the one hand, development has facilitated pattern diversification: The diversity of patterns seen across species can be generated by a single developmental process, and small changes in this process suffice to recapitulate observed evolutionary changes in pattern organization. On the other hand, development has constrained diversification: Constraints on stripe positioning limit the scope of evolvable patterns, and although pattern organization appears at first glance phylogenetically unconstrained, development turns out to impose a cryptic constraint. Altogether, this work reveals that pattern diversification in rodents can in part be explained by the underlying development and illustrates how pattern formation models can be leveraged to interpret pattern evolution.

Animal pigment patterns are excellent models to elucidate mechanisms of biological organization. Although theoretical simulations, such as Turing reaction–diffusion systems, recapitulate many animal patterns, they are insufficient to account for those showing a high degree of spatial organization and reproducibility. Here, we study the coat of the African striped mouse (Rhabdomys pumilio) to uncover how periodic stripes form. Combining transcriptomics, mathematical modelling and mouse transgenics, we show that the Wnt modulator Sfrp2 regulates the distribution of hair follicles and establishes an embryonic prepattern that foreshadows pigment stripes. Moreover, by developing in vivo gene editing in striped mice, we find that Sfrp2 knockout is sufficient to alter the stripe pattern. Strikingly, mutants exhibited changes in pigmentation, revealing that Sfrp2 also regulates hair colour. Lastly, through evolutionary analyses, we find that striped mice have evolved lineage-specific changes in regulatory elements surrounding Sfrp2, many of which may be implicated in modulating the expression of this gene. Altogether, our results show that a single factor controls coat pattern formation by acting both as an orienting signalling mechanism and a modulator of pigmentation. More broadly, our work provides insights into how spatial patterns are established in developing embryos and the mechanisms by which phenotypic novelty originates.