Publications

In early development, cells commit to a single germ fate despite receiving multiple, conflicting inductive cues. Here, we examine how cells in the Drosophila embryo integrate promesodermal and proendodermal signals. We find that proendoderm signals repress transcriptional determinants of mesodermal cell movements during a critical time window in the early embryo. Based on precise optogenetic perturbations, live imaging, and computational modeling, our work provides a framework for quantitative understanding of combinatorial control of gastrulation dynamics. All study data are included in the article and/or supporting information.

Despite recent success in computational design of structured cyclic peptides, de novo design of cyclic peptides that bind to any protein functional site remains difficult. To address this challenge, we develop a computational “anchor extension” methodology for targeting protein interfaces by extending a peptide chain around a non-canonical amino acid residue anchor. To test our approach using a well characterized model system, we design cyclic peptides that inhibit histone deacetylases 2 and 6 (HDAC2 and HDAC6) with enhanced potency compared to the original anchor (IC50 values of 9.1 and 4.4 nM for the best binders compared to 5.4 and 0.6 µM for the anchor, respectively). The HDAC6 inhibitor is among the most potent reported so far. These results highlight the potential for de novo design of high-affinity protein-peptide interfaces, as well as the challenges that remain..

We use theory and numerical computation to determine the shape of an axisymmetric fluid membrane with a resistance to bending and constant area. The membrane connects two rings in the classic geometry that produces a catenoidal shape in a soap film. In our problem, we find infinitely many branches of solutions for the shape and external force as functions of the separation of the rings, analogous to the infinite family of eigenmodes for the Euler buckling of a slender rod. Special attention is paid to the catenoid, which emerges as the shape of maximal allowable separation when the area is less than a critical area equal to the planar area enclosed by the two rings. A perturbation theory argument directly relates the tension of catenoidal membranes to the stability of catenoidal soap films in this regime. When the membrane area is larger than the critical area, we find additional cylindrical tether solutions to the shape equations at large ring separation, and that arbitrarily large ring separations are possible. These results apply for the case of vanishing Gaussian curvature modulus; when the Gaussian curvature modulus is nonzero and the area is below the critical area, the force and the membrane tension diverge as the ring separation approaches its maximum value. We also examine the stability of our shapes and analytically show that catenoidal membranes have markedly different stability properties than their soap film counterparts.

To provide a multi-omics resource and investigate transcriptional regulatory mechanisms, we profile the transcriptome, chromatin accessibility, and methylation status of over 70,000 single nuclei (sn) from adult mouse pituitaries. Paired snRNAseq and snATACseq datasets from individual animals highlight a continuum between developmental epigenetically-encoded cell types and transcriptionally-determined transient cell states. Co-accessibility analysis-based identification of a putative Fshb cis-regulatory domain that overlaps the fertility-linked rs11031006 human polymorphism, followed by experimental validation illustrate the use of this resource for hypothesis generation. We also identify transcriptional and chromatin accessibility programs distinguishing each major cell type. Regulons, which are co-regulated gene sets sharing binding sites for a common transcription factor driver, recapitulate cell type clustering. We identify both cell type-specific and sex-specific regulons that are highly correlated with promoter accessibility, but not with methylation state, supporting the centrality of chromatin accessibility in shaping cell-defining transcriptional programs. The sn multi-omics atlas is accessible at snpituitaryatlas.princeton.edu.

Gene regulatory networks define regulatory relationships between transcription factors and target genes within a biological system, and reconstructing them is essential for understanding cellular growth and function. In this work, we present the Inferelator 3.0, which has been significantly updated to integrate data from distinct cell types to learn context-specific regulatory networks and aggregate them into a shared regulatory network, while retaining the functionality of the previous versions. The Inferelator 3.0 reliably learns informative networks from the model organisms Bacillus subtilis and Saccharomyces cerevisiae. We demonstrate its capabilities by learning networks for multiple distinct neuronal and glial cell types in the developing Mus musculus brain at E18 from a large (1.3 million) single-cell gene expression data set with paired single-cell chromatin accessibility data.

In cellular vortical flows, short but flexible filaments can show simple random walks through their stretch-coil interactions with flow stagnation points. Here, we study the dynamics of semi-rigid filaments long enough to broadly sample the vortical field. Using simulation, we find a surprising variety of long-time transport behavior -- random walks, ballistic transport, and trapping -- depending upon the filament's relative length and effective flexibility. Moreover, we find that filaments execute Lévy walks whose diffusion exponents generally decrease with increasing filament length, until transitioning to Brownian walks. Lyapunov exponents likewise increase with length. Even completely rigid filaments, whose dynamics is finite-dimensional, show a surprising variety of transport states and chaos. Fast filament dispersal is related to an underlying geometry of "conveyor belts". Evidence for these various transport states are found in experiments using arrays of counter-rotating rollers, immersed in a fluid and transporting a flexible ribbon.

Oocytes are large cells that develop into an embryo upon fertilization1. As interconnected germ cells mature into oocytes, some of them grow—typically at the expense of others that undergo cell death. We present evidence that in the nematode Caenorhabditis elegans, this cell-fate decision is mechanical and related to tissue hydraulics. An analysis of germ cell volumes and material fluxes identifies a hydraulic instability that amplifies volume differences and causes some germ cells to grow and others to shrink, a phenomenon that is related to the two-balloon instability. Shrinking germ cells are extruded and they die, as we demonstrate by artificially reducing germ cell volumes via thermoviscous pumping. Our work reveals a hydraulic symmetry-breaking transition central to the decision between life and death in the nematode germline.

Two major hurdles in chimeric antigen receptor (CAR) T cell therapy for solid tumors are ensuring specificity to tumor cells without affecting healthy cells and avoiding tumor escape due to antigen loss. To address these challenges, Hyrenius-Wittsten et al. and Choe et al. developed synthetic notch (synNotch)–CAR T cells targeting solid tumor antigens and used them to treat mouse models of mesothelioma, ovarian cancer, and glioblastoma. In both studies, the authors demonstrated that synNotch-CAR T cells were better at controlling tumors than traditional CAR T cells and did not result in toxicity or damage to healthy tissue. These results suggest that synNotch-CAR T cells may be an effective treatment strategy for solid tumors.

As non-“self” macromolecules, biotherapeutics can trigger an immune response that can reduce drug efficacy, require patients to be taken off therapy, or even cause life-threatening reactions. To enable the flexible and facile design of protein biotherapeutics while reducing the prevalence of T-cell epitopes that drive immune recognition, we have integrated into the Rosetta protein design suite a new scoring term that allows design protocols to account for predicted or experimentally identified epitopes in the optimized objective function. This flexible scoring term can be used in any Rosetta design trajectory, can be targeted to specific regions of a protein, and can be readily extended to work with a variety of epitope predictors. By performing extensive design runs with varied design parameter choices for three case study proteins as well as a larger diverse benchmark, we show that the incorporation of this scoring term enables the effective exploration of an alternative, deimmunized sequence space to discover diverse proteins that are potentially highly deimmunized while retaining physical and chemical qualities similar to those yielded by equivalent nondeimmunizing sequence design protocols.

Systematic study of tissue-specific function of enhancers and their disease associations is a major challenge. We present an integrative machine-learning framework, FENRIR, that integrates thousands of disparate epigenetic and functional genomics datasets to infer tissue-specific functional relationships between enhancers for 140 diverse human tissues and cell types, providing a regulatory-region-centric approach to systematically identify disease-associated enhancers. We demonstrated its power to accurately prioritize enhancers associated with 25 complex diseases. In a case study on autism, FENRIR-prioritized enhancers showed a significant proband-specific de novo mutation enrichment in a large, sibling-controlled cohort, indicating pathogenic signal. We experimentally validated transcriptional regulatory activities of eight enhancers, including enhancers not previously reported with autism, and demonstrated their differential regulatory potential between proband and sibling alleles. Thus, FENRIR is an accurate and effective framework for the study of tissue-specific enhancers and their role in disease. FENRIR can be accessed at fenrir.flatironinstitute.org/.