An organocatalytic domino annulation approach via C(sp2)-OMe cleavage to unlock the synthesis of pyranochromenones enabled by HFIP.

Fused pyranochromenone derivatives have extensive applications in medicinal chemistry. Herein, we report the first HFIP/TsOH catalyzed, one-pot domino reaction by cleavage of the C(sp2)-OMe bond. Control experiments reveal that 1,3,5-trimethoxybenzene is rapidly protonated in the presence of HFIP to yield a dearomatized cationic diene intermediate. The gram-scale reaction and late-stage functionalization of natural products justified the practicality of this protocol.

Effect of local active fluctuations on structure and dynamics of flexible biopolymers.

Active fluctuations play a significant role in the structure and dynamics of biopolymers (e.g. chromatin and cytoskeletal proteins) that are instrumental in the functioning of living cells. For a large range of experimentally accessible length and time scales, these polymers can be represented as flexible chains that are subjected to spatially and temporally varying fluctuating forces. In this work, we introduce a mathematical framework that correlates the spatial and temporal patterns of the fluctuations to different observables that describe the dynamics and conformations of the polymer. We demonstrate the power of this approach by analyzing the case of a point fluctuation on the polymer with an exponential decay of correlation in time with a finite time constant. Specifically, we identify the length and time scale over which the behavior of the polymer exhibits a significant departure from the behavior of a Rouse chain and the range of impact of the fluctuation along the chain. Furthermore, we show that the conformation of the polymer retains the memory of the active fluctuation from earlier times. Altogether, this work sets the basis for understanding and interpreting the role of spatio-temporal patterns of fluctuations in the dynamics, conformation, and functionality of biopolymers in living cells.

Leveraging polymer modeling to reconstruct chromatin connectivity from live images.

Chromosomal dynamics plays a central role in a number of critical biological processes, such as transcriptional regulation, genetic recombination, and DNA replication. However, visualization of chromatin is generally limited to live imaging of a few fluorescently labeled chromosomal loci or high-resolution reconstruction of multiple loci from a single time frame. To aid in mapping the underlying chromosomal structure based on parsimonious experimental measurements, we present an exact analytical expression for the evolution of the polymer configuration based on a flexible-polymer model, and we propose an algorithm that tracks the polymer configuration from live images of chromatin marked with several fluorescent marks. Our theory identifies the resolution of microscopy needed to achieve high-accuracy tracking for a given spacing of markers, establishing the statistical confidence in the assignment of genome identity to the visualized marks. We then leverage experimental data of locus-tracking measurements to demonstrate the validity of our modeling approach and to establish a basis for the design of experiments with a desired resolution. Altogether, this work provides a computational approach founded on polymer physics that vastly improves the interpretation of in vivo measurements of biopolymer dynamics.

Maintaining symmetry during body axis elongation.

Bilateral symmetry defines much of the animal kingdom and is crucial for numerous functions of bilaterian organisms. Genetic approaches have discovered highly conserved patterning networks that establish bilateral symmetry in early embryos,1 but how this symmetry is maintained throughout subsequent morphogenetic events remains largely unknown.2 Here we show that the terminal patterning system-which relies on Ras/ERK signaling through activation of the Torso receptor by its ligand Trunk3-is critical for preserving bilateral symmetry during Drosophila body axis elongation, a process driven by cell rearrangements in the two identical lateral regions of the embryo and specified by the dorsal-ventral and anterior-posterior patterning systems.4 We demonstrate that fluctuating asymmetries in this rapid convergent-extension process are attenuated in normal embryos over time, possibly through noise-dissipating forces from the posterior midgut invagination and movement. However, when Torso signaling is attenuated via mutation of Trunk or RNAi directed against downstream Ras/ERK pathway components, body axis elongation results in a characteristic corkscrew phenotype,5 which reflects dramatic reorganization of global tissue flow and is incompatible with viability. Our results reveal a new function downstream of the Drosophila terminal patterning system in potentially active control of bilateral symmetry and should motivate systematic search for similar symmetry-preserving regulatory mechanisms in other bilaterians.

Self-organized intracellular twisters.

Life in complex systems, such as cities and organisms, comes to a standstill when global coordination of mass, energy, and information flows is disrupted. Global coordination is no less important in single cells, especially in large oocytes and newly formed embryos, which commonly use fast fluid flows for dynamic reorganization of their cytoplasm. Here, we combine theory, computing, and imaging to investigate such flows in the Drosophila oocyte, where streaming has been proposed to spontaneously arise from hydrodynamic interactions among cortically anchored microtubules loaded with cargo-carrying molecular motors. We use a fast, accurate, and scalable numerical approach to investigate fluid-structure interactions of 1000s of flexible fibers and demonstrate the robust emergence and evolution of cell-spanning vortices, or twisters. Dominated by a rigid body rotation and secondary toroidal components, these flows are likely involved in rapid mixing and transport of ooplasmic components.

Self-organized intracellular twisters.

Life in complex systems, such as cities and organisms, comes to a standstill when global coordination of mass, energy, and information flows is disrupted. Global coordination is no less important in single cells, especially in large oocytes and newly formed embryos, which commonly use fast fluid flows for dynamic reorganization of their cytoplasm. Here, we combine theory, computing, and imaging to investigate such flows in the Drosophila oocyte, where streaming has been proposed to spontaneously arise from hydrodynamic interactions among cortically anchored microtubules loaded with cargo-carrying molecular motors. We use a fast, accurate, and scalable numerical approach to investigate fluid-structure interactions of 1000s of flexible fibers and demonstrate the robust emergence and evolution of cell-spanning vortices, or twisters. Dominated by a rigid body rotation and secondary toroidal components, these flows are likely involved in rapid mixing and transport of ooplasmic components.

Spatial organization of transcribing loci during early genome activation in Drosophila.

The early Drosophila embryo provides unique experimental advantages for addressing fundamental questions of gene regulation at multiple levels of organization, from individual gene loci to the entire genome. Using 1.5-h-old Drosophila embryos undergoing the first wave of genome activation,1 we detected ∼110 discrete "speckles" of RNA polymerase II (RNA Pol II) per nucleus, two of which were larger and localized to the histone locus bodies (HLBs).2,3 In the absence of the primary driver of Drosophila genome activation, the pioneer factor Zelda (Zld),1,4,5 70% fewer speckles were present; however, the HLBs tended to be larger than wild-type (WT) HLBs, indicating that RNA Pol II accumulates at the HLBs in the absence of robust early-gene transcription. We observed a uniform distribution of distances between active genes in the nuclei of both WT and zld mutant embryos, indicating that early co-regulated genes do not cluster into nuclear sub-domains. However, in instances whereby transcribing genes did come into close 3D proximity (within 400 nm), they were found to have distinct RNA Pol II speckles. In contrast to the emerging model whereby active genes are clustered to facilitate co-regulation and sharing of transcriptional resources, our data support an "individualist" model of gene control at early genome activation in Drosophila. This model is in contrast to a "collectivist" model, where active genes are spatially clustered and share transcriptional resources, motivating rigorous tests of both models in other experimental systems.

Temporal integration of inductive cues on the way to gastrulation.

Markers for the endoderm and mesoderm germ layers are commonly expressed together in the early embryo, potentially reflecting cells' ability to explore potential fates before fully committing. It remains unclear when commitment to a single-germ layer is reached and how it is impacted by external signals. Here, we address this important question in Drosophila, a convenient model system in which mesodermal and endodermal fates are associated with distinct cellular movements during gastrulation. Systematically applying endoderm-inducing extracellular signal-regulated kinase (ERK) signals to the ventral medial embryo-which normally only receives a mesoderm-inducing cue-reveals a critical time window during which mesodermal cell movements and gene expression are suppressed by proendoderm signaling. We identify the ERK target gene huckebein (hkb) as the main cause of the ventral furrow suppression and use computational modeling to show that Hkb repression of the mesoderm-associated gene snail is sufficient to account for a broad range of transcriptional and morphogenetic effects. Our approach, pairing precise signaling perturbations with observation of transcriptional dynamics and cell movements, provides a general framework for dissecting the complexities of combinatorial tissue patterning.

From complex datasets to predictive models of embryonic development.

Modern studies of embryogenesis are increasingly quantitative, powered by rapid advances in imaging, sequencing and genome manipulation technologies. Deriving mechanistic insights from the complex datasets generated by these new tools requires systematic approaches for data-driven analysis of the underlying developmental processes. Here, we use data from our work on signal-dependent gene repression in the Drosophila embryo to illustrate how computational models can compactly summarize quantitative results of live imaging, chromatin immunoprecipitation and optogenetic perturbation experiments. The presented computational approach is ideally suited for integrating rapidly accumulating quantitative data and for guiding future studies of embryogenesis.

Excess dNTPs Trigger Oscillatory Surface Flow in the Early Drosophila Embryo.

During the first 2 hours of Drosophila development, precisely orchestrated nuclear cleavages, cytoskeletal rearrangements, and directed membrane growth lead to the formation of an epithelial sheet around the yolk. The newly formed epithelium remains relatively quiescent during the next hour as it is patterned by maternal inductive signals and zygotic gene products. We discovered that this mechanically quiet period is disrupted in embryos with high levels of dNTPs, which have been recently shown to cause abnormally fast nuclear cleavages and interfere with zygotic transcription. High levels of dNTPs are associated with robust onset of oscillatory two-dimensional flows during the third hour of development. Tissue cartography, particle image velocimetry, and dimensionality reduction techniques reveal that these oscillatory flows are low dimensional and are characterized by the presence of spiral vortices. We speculate that these aberrant flows emerge through an instability triggered by deregulated mechanical coupling between the nascent epithelium and three-dimensional yolk. These results highlight an unexplored connection between a core metabolic process and large-scale mechanics in a rapidly developing embryo.

Self-Similar Dynamics of Nuclear Packing in the Early Drosophila Embryo.

Embryonic development starts with cleavages, a rapid sequence of reductive divisions that result in an exponential increase of cell number without changing the overall size of the embryo. In Drosophila, the final four rounds of cleavages occur at the surface of the embryo and give rise to ∼6000 nuclei under a common plasma membrane. We use live imaging to study the dynamics of this process and to characterize the emergent nuclear packing in this system. We show that the characteristic length scale of the internuclear interaction scales with the density, which allows the densifying embryo to sustain the level of structural order at progressively smaller length scales. This is different from nonliving materials, which typically undergo disorder-order transition upon compression. To explain this dynamics, we use a particle-based model that accounts for density-dependent nuclear interactions and synchronous divisions. We reproduce the pair statistics of the disordered packings observed in embryos and recover the scaling relation between the characteristic length scale and the density both in real and reciprocal space. This result reveals how the embryo can robustly preserve the nuclear-packing structure while being densified. In addition to providing quantitative description of self-similar dynamics of nuclear packings, this model generates dynamic meshes for the computational analysis of pattern formation and tissue morphogenesis.

Interactions and design rules for assembly of porous colloidal mesophases.

Porous mesophases, where well-defined particle-depleted 'void' spaces are present within a particle-rich background fluid, can be self-assembled from colloidal particles interacting via isotropic pair interactions with competing attractions and repulsions. While such structures could be of wide interest for technological applications (e.g., filtration, catalysis, absorption, etc.), relatively few studies have investigated the interactions that lead to these morphologies and how they compare to those that produce other micro-phase-separated structures, such as clusters. In this work, we use inverse methods of statistical mechanics to design model isotropic pair potentials that form porous mesophases. We characterize the resulting porous structures, correlating features of the pair potential with the targeted pore size and the particle packing fraction. The former is primarily encoded by the amplitude and range of the repulsive barrier of the designed pair potential and the latter by the attractive well depth. We observe a trade-off with respect to the packing fraction of the targeted morphology: greater values support more spherical and monodisperse pores that themselves organize into periodic structures, while lower values yield more mobile pores that do not assemble into ordered structures but remain stable over a larger range of packing fraction. We conclude by commenting on the limitations of targeting a specific pore diameter within the present inverse design approach as well as by describing future directions to overcome these limitations.