Contribution of human embryonic stem cells to mouse blastocysts

AbstractIn addition to their potential for cell-based therapies in the treatment of disease and injury, the broad developmental capacity of human embryonic stem cells (hESCs) offers potential for studying the origins of all human cell types. To date, the emergence of specialized cells from hESCs has commonly been studied in tissue culture or in teratomas, yet these methods have stopped short of demonstrating the ESC potential exhibited in the mouse (mESCs), which can give rise to every cell type when combined with blastocysts. Due to obvious barriers precluding the use of human embryos in similar cell mixing experiments with hESCs, human/non-human chimeras may need to be generated for this purpose. Our results show that hESCs can engraft into mouse blastocysts, where they proliferate and differentiate in vitro and persist in mouse/human embryonic chimeras that implant and develop in the uterus of pseudopregnant foster mice. Embryonic chimeras generated in this way offer the opportunity to study the behavior of specialized human cell types in a non-human animal model. Our data demonstrate the feasibility of this approach, using mouse embryos as a surrogate for hESC differentiation

A database of microRNA expression patterns in Xenopus laevis

MicroRNAs (miRNAs) are short, non-coding RNAs around 22 nucleotides long. They inhibit gene expression either by translational repression or by causing the degradation of the mRNAs they bind to. Many are highly conserved amongst diverse organisms and have restricted spatio-temporal expression patterns during embryonic development where they are thought to be involved in generating accuracy of developmental timing and in supporting cell fate decisions and tissue identity. We determined the expression patterns of 180 miRNAs in Xenopus laevis embryos using LNA oligonucleotides. In addition we carried out small RNA-seq on different stages of early Xenopus development, identified 44 miRNAs belonging to 29 new families and characterized the expression of 5 of these. Our analyses identified miRNA expression in many organs of the developing embryo. In particular a large number were expressed in neural tissue and in the somites. Surprisingly none of the miRNAs we have looked at show expression in the heart. Our results have been made freely available as a resource in both XenMARK and Xenbase

The fidelity of dynamic signaling by noisy biomolecular networks

This is the final version of the article. Available from Public Library of Science via the DOI in this record.Cells live in changing, dynamic environments. To understand cellular decision-making, we must therefore understand how fluctuating inputs are processed by noisy biomolecular networks. Here we present a general methodology for analyzing the fidelity with which different statistics of a fluctuating input are represented, or encoded, in the output of a signaling system over time. We identify two orthogonal sources of error that corrupt perfect representation of the signal: dynamical error, which occurs when the network responds on average to other features of the input trajectory as well as to the signal of interest, and mechanistic error, which occurs because biochemical reactions comprising the signaling mechanism are stochastic. Trade-offs between these two errors can determine the system's fidelity. By developing mathematical approaches to derive dynamics conditional on input trajectories we can show, for example, that increased biochemical noise (mechanistic error) can improve fidelity and that both negative and positive feedback degrade fidelity, for standard models of genetic autoregulation. For a group of cells, the fidelity of the collective output exceeds that of an individual cell and negative feedback then typically becomes beneficial. We can also predict the dynamic signal for which a given system has highest fidelity and, conversely, how to modify the network design to maximize fidelity for a given dynamic signal. Our approach is general, has applications to both systems and synthetic biology, and will help underpin studies of cellular behavior in natural, dynamic environments.We acknowledge support from a Medical Research Council and Engineering and Physical Sciences Council funded Fellowship in Biomedical Informatics (CGB) and a Scottish Universities Life Sciences Alliance chair in Systems Biology (PSS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Deep-learning analysis of micropattern-based organoids enables high-throughput drug screening of Huntington's disease models

Organoids are carrying the promise of modeling complex disease phenotypes and serving as a powerful basis for unbiased drug screens, potentially offering a more efficient drug-discovery route. However, unsolved technical bottlenecks of reproducibility and scalability have prevented the use of current organoids for high-throughput screening. Here, we present a method that overcomes these limitations by using deep-learning-driven analysis for phenotypic drug screens based on highly standardized micropattern-based neural organoids. This allows us to distinguish between disease and wild-type phenotypes in complex tissues with extremely high accuracy as well as quantify two predictors of drug success: efficacy and adverse effects. We applied our approach to Huntington's disease (HD) and discovered that bromodomain inhibitors revert complex phenotypes induced by the HD mutation. This work demonstrates the power of combining machine learning with phenotypic drug screening and its successful application to reveal a potentially new druggable target for HD

WNT signaling memory is required for ACTIVIN to function as a morphogen in human gastruloids

Self-organization of discrete fates in human gastruloids is mediated by a hierarchy of signaling pathways. How these pathways are integrated in time, and whether cells maintain a memory of their signaling history remains obscure. Here, we dissect the temporal integration of two key pathways, WNT and ACTIVIN, which along with BMP control gastrulation. CRISPR/Cas9-engineered live reporters of SMAD1, 2 and 4 demonstrate that in contrast to the stable signaling by SMAD1, signaling and transcriptional response by SMAD2 is transient, and while necessary for pluripotency, it is insufficient for differentiation. Pre-exposure to WNT, however, endows cells with the competence to respond to graded levels of ACTIVIN, which induces differentiation without changing SMAD2 dynamics. This cellular memory of WNT signaling is necessary for ACTIVIN morphogen activity. A re-evaluation of the evidence gathered over decades in model systems, re-enforces our conclusions and points to an evolutionarily conserved mechanism

Huntingtin CAG expansion impairs germ layer patterning in synthetic human 2D gastruloids through polarity defects

Huntington's disease (HD) is a fatal neurodegenerative disorder caused by an expansion of the CAG repeats in the huntingtin gene (HTT). Although HD has been shown to have a developmental component, how early during human embryogenesis the HTT-CAG expansion can cause embryonic defects remains unknown. Here, we demonstrate a specific and highly reproducible CAG length-dependent phenotypic signature in a synthetic model for human gastrulation derived from human embryonic stem cells (hESCs). Specifically, we observed a reduction in the extension of the ectodermal compartment that is associated with enhanced activin signaling. Surprisingly, rather than a cell-autonomous effect, tracking the dynamics of TGFβ signaling demonstrated that HTT-CAG expansion perturbs the spatial restriction of activin response. This is due to defects in the apicobasal polarization in the context of the polarized epithelium of the 2D gastruloid, leading to ectopic subcellular localization of TGFβ receptors. This work refines the earliest developmental window for the prodromal phase of HD to the first 2 weeks of human development, as modeled by our 2D gastruloids

Maternal xNorrin, a Canonical Wnt Signaling Agonist and TGF-β Antagonist, Controls Early Neuroectoderm Specification in Xenopus

Xenopus maternal Norrin, which activates Wnt signaling but inhibits TGF-β family molecules, is essential for neuroectoderm formation. Loss of TGF-β inhibition in Norrin may contribute to the development of Norrie disease

Transcription factor site dependencies in human, mouse and rat genomes

<p>Abstract</p> <p>Background</p> <p>It is known that transcription factors frequently act together to regulate gene expression in eukaryotes. In this paper we describe a computational analysis of transcription factor site dependencies in human, mouse and rat genomes.</p> <p>Results</p> <p>Our approach for quantifying tendencies of transcription factor binding sites to co-occur is based on a binding site scoring function which incorporates dependencies between positions, the use of information about the structural class of each transcription factor (major/minor groove binder), and also considered the possible implications of varying GC content of the sequences. Significant tendencies (dependencies) have been detected by non-parametric statistical methodology (permutation tests). Evaluation of obtained results has been performed in several ways: reports from literature (many of the significant dependencies between transcription factors have previously been confirmed experimentally); dependencies between transcription factors are not biased due to similarities in their DNA-binding sites; the number of dependent transcription factors that belong to the same functional and structural class is significantly higher than would be expected by chance; supporting evidence from GO clustering of targeting genes. Based on dependencies between two transcription factor binding sites (second-order dependencies), it is possible to construct higher-order dependencies (networks). Moreover results about transcription factor binding sites dependencies can be used for prediction of groups of dependent transcription factors on a given promoter sequence. Our results, as well as a scanning tool for predicting groups of dependent transcription factors binding sites are available on the Internet.</p> <p>Conclusion</p> <p>We show that the computational analysis of transcription factor site dependencies is a valuable complement to experimental approaches for discovering transcription regulatory interactions and networks. Scanning promoter sequences with dependent groups of transcription factor binding sites improve the quality of transcription factor predictions.</p

Sarcophine-Diol, a Skin Cancer Chemopreventive Agent, Inhibits Proliferation and Stimulates Apoptosis in Mouse Melanoma B16F10 Cell Line

Sarcodiol (SD) is a semi-synthetic derivative of sarcophine, a marine natural product. In our previous work, we reported the significant chemopreventive effects of SD against non-melanoma skin cancer both in vitro and in vivo mouse models. In this investigation, we extended this work to study the effect of sarcodiol on melanoma development, the more deadly form of skin cancer, using the mouse melanoma B16F10 cell line. In this study we report that SD inhibits the de novo DNA synthesis and enhances fragmentation of DNA. We also evaluated the antitumor effect of SD on melanoma cell viability using several biomarkers for cell proliferation and apoptosis. SD inhibits the expression levels of signal transducers and activators of transcription protein (STAT-3) and cyclin D1, an activator of cyclin-dependent kinase 4 (Cdk4). SD treatment also enhances cellular level of tumor suppressor protein 53 (p53) and stimulates cleavage of the nuclear poly (ADP-ribose) polymerase (cleaved-PARP). SD also enhances cellular levels of cleaved Caspase-3, -8, -9 and stimulates enzymatic activities of Caspase-3, -8 and -9. These results, in addition to inhibition of cell viability, suggest that SD inhibits melanoma cell proliferation by arresting the cell-division cycle in a Go quiescent phase and activates programmed cell death (apoptosis) via extrinsic and intrinsic pathways. Finally, these studies demonstrate that SD shows a very promising chemopreventive effect in melanoma B16F10 tumor cells

Speed-Dependent Cellular Decision Making in Nonequilibrium Genetic Circuits

Despite being governed by the principles of nonequilibrium transitions, gene expression dynamics underlying cell fate decision is poorly understood. In particular, the effect of signaling speed on cellular decision making is still unclear. Here we show that the decision between alternative cell fates, in a structurally symmetric circuit, can be biased depending on the speed at which the system is forced to go through the decision point. The circuit consists of two mutually inhibiting and self-activating genes, forced by two external signals with identical stationary values but different transient times. Under these conditions, slow passage through the decision point leads to a consistently biased decision due to the transient signaling asymmetry, whereas fast passage reduces and eventually eliminates the switch imbalance. The effect is robust to noise and shows that dynamic bifurcations, well known in nonequilibrium physics, are important for the control of genetic circuits