Guided self-organization and cortical plate formation in human brain organoids.

Three-dimensional cell culture models have either relied on the self-organizing properties of mammalian cells or used bioengineered constructs to arrange cells in an organ-like configuration. While self-organizing organoids excel at recapitulating early developmental events, bioengineered constructs reproducibly generate desired tissue architectures. Here, we combine these two approaches to reproducibly generate human forebrain tissue while maintaining its self-organizing capacity. We use poly(lactide-co-glycolide) copolymer (PLGA) fiber microfilaments as a floating scaffold to generate elongated embryoid bodies. Microfilament-engineered cerebral organoids (enCORs) display enhanced neuroectoderm formation and improved cortical development. Furthermore, reconstitution of the basement membrane leads to characteristic cortical tissue architecture, including formation of a polarized cortical plate and radial units. Thus, enCORs model the distinctive radial organization of the cerebral cortex and allow for the study of neuronal migration. Our data demonstrate that combining 3D cell culture with bioengineering can increase reproducibility and improve tissue architecture

Combinatorial binding leads to diverse regulatory responses:Lmd is a tissue-specific modulator of Mef2 activity

Understanding how complex patterns of temporal and spatial expression are regulated is central to deciphering genetic programs that drive development. Gene expression is initiated through the action of transcription factors and their cofactors converging on enhancer elements leading to a defined activity. Specific constellations of combinatorial occupancy are therefore often conceptualized as rigid binding codes that give rise to a common output of spatio-temporal expression. Here, we assessed this assumption using the regulatory input of two essential transcription factors within the Drosophila myogenic network. Mutations in either Myocyte enhancing factor 2 (Mef2) or the zinc-finger transcription factor lame duck (lmd) lead to very similar defects in myoblast fusion, yet the underlying molecular mechanism for this shared phenotype is not understood. Using a combination of ChIP-on-chip analysis and expression profiling of loss-of-function mutants, we obtained a global view of the regulatory input of both factors during development. The majority of Lmd-bound enhancers are co-bound by Mef2, representing a subset of Mef2's transcriptional input during these stages of development. Systematic analyses of the regulatory contribution of both factors demonstrate diverse regulatory roles, despite their co-occupancy of shared enhancer elements. These results indicate that Lmd is a tissue-specific modulator of Mef2 activity, acting as both a transcriptional activator and repressor, which has important implications for myogenesis. More generally, this study demonstrates considerable flexibility in the regulatory output of two factors, leading to additive, cooperative, and repressive modes of co-regulation

Model-based method for transcription factor target identification with limited data

We present a computational method for identifying potential targets of a transcription factor (TF) using wild-type gene expression time series data. For each putative target gene we fit a simple differential equation model of transcriptional regulation, and the model likelihood serves as a score to rank targets. The expression profile of the TF is modeled as a sample from a Gaussian process prior distribution that is integrated out using a nonparametric Bayesian procedure. This results in a parsimonious model with relatively few parameters that can be applied to short time series datasets without noticeable overfitting. We assess our method using genome-wide chromatin immunoprecipitation (ChIP-chip) and loss-of-function mutant expression data for two TFs, Twist, and Mef2, controlling mesoderm development in Drosophila. Lists of top-ranked genes identified by our method are significantly enriched for genes close to bound regions identified in the ChIP-chip data and for genes that are differentially expressed in loss-of-function mutants. Targets of Twist display diverse expression profiles, and in this case a model-based approach performs significantly better than scoring based on correlation with TF expression. Our approach is found to be comparable or superior to ranking based on mutant differential expression scores. Also, we show how integrating complementary wild-type spatial expression data can further improve target ranking performance

Qualitative Dynamical Modelling Can Formally Explain Mesoderm Specification and Predict Novel Developmental Phenotypes

International audienceGiven the complexity of developmental networks, it is often difficult to predict the effect of genetic perturbations, even within coding genes. Regulatory factors generally have pleiotropic effects, exhibit partially redundant roles, and regulate highly interconnected pathways with ample cross-talk. Here, we delineate a logical model encompassing 48 components and 82 regulatory interactions involved in mesoderm specification during Drosophila development, thereby providing a formal integration of all available genetic information from the literature. The four main tissues derived from mesoderm correspond to alternative stable states. We demonstrate that the model can predict known mutant phenotypes and use it to systematically predict the effects of over 300 new, often non-intuitive, loss- and gain-of-function mutations, and combinations thereof. We further validated several novel predictions experimentally, thereby demonstrating the robustness of model. Logical modelling can thus contribute to formally explain and predict regulatory outcomes underlying cell fate decisions

Temporal ChIP-on-chip reveals Biniou as a universal regulator of the visceral muscle transcriptional network

Smooth muscle plays a prominent role in many fundamental processes and diseases, yet our understanding of the transcriptional network regulating its development is very limited. The FoxF transcription factors are essential for visceral smooth muscle development in diverse species, although their direct regulatory role remains elusive. We present a transcriptional map of Biniou (a FoxF transcription factor) and Bagpipe (an Nkx factor) activity, as a first step to deciphering the developmental program regulating Drosophila visceral muscle development. A time course of chromatin immunoprecipitatation followed by microarray analysis (ChIP-on-chip) experiments and expression profiling of mutant embryos reveal a dynamic map of in vivo bound enhancers and direct target genes. While Biniou is broadly expressed, it regulates enhancers driving temporally and spatially restricted expression. In vivo reporter assays indicate that the timing of Biniou binding is a key trigger for the time span of enhancer activity. Although bagpipe and biniou mutants phenocopy each other, their regulatory potential is quite different. This network architecture was not apparent from genetic studies, and highlights Biniou as a universal regulator in all visceral muscle, regardless of its developmental origin or subsequent function. The regulatory connection of a number of Biniou target genes is conserved in mice, suggesting an ancient wiring of this developmental program

Guided self-organization and cortical plate formation in human brain organoids.

Three-dimensional cell culture models have either relied on the self-organizing properties of mammalian cells or used bioengineered constructs to arrange cells in an organ-like configuration. While self-organizing organoids excel at recapitulating early developmental events, bioengineered constructs reproducibly generate desired tissue architectures. Here, we combine these two approaches to reproducibly generate human forebrain tissue while maintaining its self-organizing capacity. We use poly(lactide-co-glycolide) copolymer (PLGA) fiber microfilaments as a floating scaffold to generate elongated embryoid bodies. Microfilament-engineered cerebral organoids (enCORs) display enhanced neuroectoderm formation and improved cortical development. Furthermore, reconstitution of the basement membrane leads to characteristic cortical tissue architecture, including formation of a polarized cortical plate and radial units. Thus, enCORs model the distinctive radial organization of the cerebral cortex and allow for the study of neuronal migration. Our data demonstrate that combining 3D cell culture with bioengineering can increase reproducibility and improve tissue architecture

Regulatory graph for the signalling/transcriptional network controlling drosophila mesoderm specification.

<p>Built with the software GINsim, this regulatory graph encompasses the main regulatory factors and interactions involved in mesoderm specification (stages 8–10), as documented by published (molecular) genetic and functional genomic data. Ellipses denote Boolean nodes, whereas rectangles denote multilevel nodes. Light green filling denotes input nodes, most corresponding to factors expressed in and acting from the ectoderm. Yellow filling denotes output factors, mostly effector genes and tissue markers. Blue or grey filling denotes internal nodes expressed in the mesoderm. Green arrows and red blunt arrows denote activations and inhibitions, respectively. Logical rules are further associated with each node to define its behaviour depending on regulatory inputs (cf. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005073#pcbi.1005073.s006" target="_blank">S1 Table</a>). To ease the dynamical analysis of this regulatory graph, we performed a reduction of this regulatory graph (cf. Material and methods), making implicit the twelve grey components. This logical model is provided as supporting data, including comprehensive annotations and bibliographical references.</p

Key signalling pathways and markers genes involved in mesoderm specification.

<p>A, B: In situ hybridizations for Tin and Bin during mesoderm specification at stages 8 and 9–10. Tin is implicated in the formation of VM and H, while Bin participates only in the development of VM. Initially, the expression of Tin is mainly due to Twist activation. Later, Tin expression needs the presence of Dpp, Tin itself, in combination with Pan. C: Graphical representations of the main pathways activated by signals coming from the ectoderm, encompassing target transcription factors and cross-regulations underlying the specification of VM, H, FB and SM. In the absence of these factors, these tissues do not form or are severely reduced. Black and light grey arcs denote active and inactive regulations, depending on stage or tissue. Normal and blunt end arrows denote activations and inhibitions, respectively.</p