Spatial Analysis of Expression Patterns Predicts Genetic Interactions at the Mid-Hindbrain Boundary

The isthmic organizer mediating differentiation of mid- and hindbrain during vertebrate development is characterized by a well-defined pattern of locally restricted gene expression domains around the mid-hindbrain boundary (MHB). This pattern is established and maintained by a regulatory network between several transcription and secreted factors that is not yet understood in full detail. In this contribution we show that a Boolean analysis of the characteristic spatial gene expression patterns at the murine MHB reveals key regulatory interactions in this network. Our analysis employs techniques from computational logic for the minimization of Boolean functions. This approach allows us to predict also the interplay of the various regulatory interactions. In particular, we predict a maintaining, rather than inducing, effect of Fgf8 on Wnt1 expression, an issue that remained unclear from published data. Using mouse anterior neural plate/tube explant cultures, we provide experimental evidence that Fgf8 in fact only maintains but does not induce ectopic Wnt1 expression in these explants. In combination with previously validated interactions, this finding allows for the construction of a regulatory network between key transcription and secreted factors at the MHB. Analyses of Boolean, differential equation and reaction-diffusion models of this network confirm that it is indeed able to explain the stable maintenance of the MHB as well as time-courses of expression patterns both under wild-type and various knock-out conditions. In conclusion, we demonstrate that similar to temporal also spatial expression patterns can be used to gain information about the structure of regulatory networks. We show, in particular, that the spatial gene expression patterns around the MHB help us to understand the maintenance of this boundary on a systems level

Odefy -- From discrete to continuous models

<p>Abstract</p> <p>Background</p> <p>Phenomenological information about regulatory interactions is frequently available and can be readily converted to Boolean models. Fully quantitative models, on the other hand, provide detailed insights into the precise dynamics of the underlying system. In order to connect discrete and continuous modeling approaches, methods for the conversion of Boolean systems into systems of ordinary differential equations have been developed recently. As biological interaction networks have steadily grown in size and complexity, a fully automated framework for the conversion process is desirable.</p> <p>Results</p> <p>We present <it>Odefy</it>, a MATLAB- and Octave-compatible toolbox for the automated transformation of Boolean models into systems of ordinary differential equations. Models can be created from sets of Boolean equations or graph representations of Boolean networks. Alternatively, the user can import Boolean models from the CellNetAnalyzer toolbox, GINSim and the PBN toolbox. The Boolean models are transformed to systems of ordinary differential equations by multivariate polynomial interpolation and optional application of sigmoidal Hill functions. Our toolbox contains basic simulation and visualization functionalities for both, the Boolean as well as the continuous models. For further analyses, models can be exported to SQUAD, GNA, MATLAB script files, the SB toolbox, SBML and R script files. Odefy contains a user-friendly graphical user interface for convenient access to the simulation and exporting functionalities. We illustrate the validity of our transformation approach as well as the usage and benefit of the Odefy toolbox for two biological systems: a mutual inhibitory switch known from stem cell differentiation and a regulatory network giving rise to a specific spatial expression pattern at the mid-hindbrain boundary.</p> <p>Conclusions</p> <p>Odefy provides an easy-to-use toolbox for the automatic conversion of Boolean models to systems of ordinary differential equations. It can be efficiently connected to a variety of input and output formats for further analysis and investigations. The toolbox is open-source and can be downloaded at <url>http://cmb.helmholtz-muenchen.de/odefy</url>.</p

Data-driven modelling of biological multi-scale processes

Biological processes involve a variety of spatial and temporal scales. A holistic understanding of many biological processes therefore requires multi-scale models which capture the relevant properties on all these scales. In this manuscript we review mathematical modelling approaches used to describe the individual spatial scales and how they are integrated into holistic models. We discuss the relation between spatial and temporal scales and the implication of that on multi-scale modelling. Based upon this overview over state-of-the-art modelling approaches, we formulate key challenges in mathematical and computational modelling of biological multi-scale and multi-physics processes. In particular, we considered the availability of analysis tools for multi-scale models and model-based multi-scale data integration. We provide a compact review of methods for model-based data integration and model-based hypothesis testing. Furthermore, novel approaches and recent trends are discussed, including computation time reduction using reduced order and surrogate models, which contribute to the solution of inference problems. We conclude the manuscript by providing a few ideas for the development of tailored multi-scale inference methods.Comment: This manuscript will appear in the Journal of Coupled Systems and Multiscale Dynamics (American Scientific Publishers

Úloha genů rodiny vent v časném embryonálním vývoji a ve vývoji mozku

6 III ABSTRACT (ENGLISH) In chordates, the central nervous system (CNS) is derived from the dorsal part of gastrula. Induced dorsal part of the embryo - the neural plate - gives rise to the neural tube or primordial brain. The developing dorsal part of the embryo is shaped by BMP/Smad signaling from the ventral part. Using the basal chordate amphioxus, we show here the conserved evolutionary role BMP/Smad signaling in axial cell fate determination. Pharmalogical inhibition of BMP/Smad signaling induces dorsalization of Branchiostoma floridae (amphioxus) and Oryzias latipes (medaka) embryos and expansion of neural plate markers. We provide evidence for the presence of the positive regulatory loop within the BMP/Smad signaling network of amphioxus. Thus, our data suggest that early emergence of a positive feedback loop within the BMP/Smad signaling network may represent a crucial molecular event in the evolutionary history of the chordate cell fate determination. The dorso-ventral body axis formation is mediated by genes of the vent family, which are the direct targets of BMP/Smad signaling. The function of vent gene family in early development is relatively well known, however, its role in developing CNS is not yet clear. Therefore, we decided to manipulate vox transcription factor, a vent family member....7 IV ABSTRAKT (CZECH) Centrální nervová soustava (CNS) je u všech strunatců odvozena z hřbetní strany vyvíjejícího se embrya. Postupným vlivem signalizace vzniká z hřbetní strany neurální ploténka, ze které se následně vyvine budoucí mozek spolu s neurální trubicí. Budoucí CNS je formována účinkem BMP/Smad signalizační dráhy z břišní části embrya směrem k hřbetní. Konzervovanou roli této BMP/Smad signalizační dráhy v průběhu evoluce zde ukazujeme potvrzením jejího vlivu při stanovení buněčného osudu v rámci tělní osy i v případě bazálního strunatce Branchiostoma floridae (kopinatce). U kopinatce vede farmakologická inhibice BMP/Smad signalizační dráhy k rozšíření exprese genů typických pro neurální ploténku a k dorzalizaci embrya, stejně tak jako u ryby Oryzias latipes (medaka). Poskytujeme důkaz přítomnosti pozitivní autoregulace BMP/Smad signalizační dráhy u kopinatce. Zároveň naše data naznačují možnost časného vzniku pozitivní autoregulace BMP/Smad signalizační dráhy jako klíčové události v evoluční historii stanovení buněčného osudu u strunatců. Tvorba dorso-ventrální osy těla je zprostředkovány geny genové rodiny vent, které jsou přímým cílem BMP/Smad signalizace. Ačkoliv je funkce genů genové rodiny vent jako transpčních faktorů v rámci časného embryonálního vývoje poměrně dobře popsána, jejich role...Department of Cell BiologyKatedra buněčné biologieFaculty of SciencePřírodovědecká fakult

A Unilateral Negative Feedback Loop Between miR-200 microRNAs and Sox2/E2F3 Controls Neural Progenitor Cell-Cycle Exit and Differentiation

MicroRNAs have emerged as key posttranscriptional regulators of gene expression during vertebrate development. We show that the miR-200 family plays a crucial role for the proper generation and survival of ventral neuronal populations in the murine midbrain/hindbrain region, including midbrain dopaminergic neurons, by directly targeting the pluripotency factor Sox2 and the cell-cycle regulator E2F3 in neural stem/progenitor cells. The lack of a negative regulation of Sox2 and E2F3 by miR-200 in conditional Dicer1 mutants (En1(+/Cre); Dicer1(flox/flox) mice) and after miR-200 knockdown in vitro leads to a strongly reduced cell-cycle exit and neuronal differentiation of ventral midbrain/hindbrain (vMH) neural progenitors, whereas the opposite effect is seen after miR-200 overexpression in primary vMH cells. Expression of miR-200 is in turn directly regulated by Sox2 and E2F3, thereby establishing a unilateral negative feedback loop required for the cell-cycle exit and neuronal differentiation of neural stem/progenitor cells. Our findings suggest that the posttranscriptional regulation of Sox2 and E2F3 by miR-200 family members might be a general mechanism to control the transition from a pluripotent/multipotent stem/progenitor cell to a postmitotic and more differentiated cell

The Role of Lmx1a and Lmx1b in Regulating Mesencephalon Development and Dopamine Neuron Specification

One of the most challenging questions in developmental biology is how neurons are specified, acquire their distinct characteristics and find their correct innervations to form functional circuits. The development of different subsets of neurons involves the expression of a program intrinsic to each cell type and the response to extrinsic environmental influences represented by soluble factors. Breakthroughs in the understanding of the genetic programs that controls the specification of ventral cell fates in the spinal cord and hindbrain, have provided useful tools for the study of similar genetic networks in the more complex rostral regions of the central nervous system, such as the mesencephalon (also called midbrain). Midbrain dopamine (mDA) neurons are born in the ventral midline of the midbrain and regulate important functions in the brain, including motor control, cognition, emotions and learning. The degeneration of mDA neurons is the major hallmark of Parkinson s disease (PD). The lack of knowledge regarding the factors involving in the early specification of mDA neurons has been one of the obstacles in applying embryonic stem cell (ESC)-based replacement therapy for PD. In paper I, we showed that Lmx1a and Msx1/2 are two key components in the development of mDA neurons. Lmx1a is necessary and sufficient for the acquisition of the proper mDA fate by activating the expression of downstream mDA neuron markers, while Msx1/2 synergizes with Lmx1a by suppressing alternative cell fates and promoting the progression of neurogenesis. Furthermore, we applied this knowledge to ESCs and showed that forced expression of Lmx1a could efficiently induce bona fide mDA neurons. In paper II, we continued to evaluate the role of Lmx1a in the mouse and compared the function of Lmx1a with its close homolog Lmx1b during mDA development. Surprisingly, loss of Lmx1a resulted in a moderate reduction of mDA neurons, which was partly due to the delayed conversion of floor plate into a neurogenic region at an early stage. Lmx1b could compensate to large extent for the loss of Lmx1a in mDA neuron generation as the compound genotype of the Lmx1 genes displayed a dose-dependent effect. Importantly, we showed that Lmx1a and Lmx1b have distinct roles in specifying two subgroups, i.e. medial and lateral mDA neurons. In addition, we revealed the function of Lmx1b in patterning other ventral cell types, i.e. oculomotor (OM) neurons and red nucleus (RN) cells. Loss of Lmx1b caused a dramatic reduction of OM neurons. By contrast, RN cells were born prematurely and were overproduced. Our current findings establish that Lmx1b influences the differentiation of multiple neuronal subtypes in the ventral midbrain, while the activity of Lmx1a in the ventral midbrain appears devoted to the differentiation of mDA neurons

Modeling of dynamic systems with Petri nets and fuzzy logic

Aktuelle Methoden zur dynamischen Modellierung von biologischen Systemen sind für Benutzer ohne mathematische Ausbildung oft wenig verständlich. Des Weiteren fehlen sehr oft genaue Daten und detailliertes Wissen über Konzentrationen, Reaktionskinetiken oder regulatorische Effekte. Daher erfordert eine computergestützte Modellierung eines biologischen Systems, mit Unsicherheiten und grober Information umzugehen, die durch qualitatives Wissen und natürlichsprachliche Beschreibungen zur Verfügung gestellt wird. Der Autor schlägt einen neuen Ansatz vor, mit dem solche Beschränkungen überwunden werden können. Dazu wird eine Petri-Netz-basierte graphische Darstellung von Systemen mit einer leistungsstarken und dennoch intuitiven Fuzzy-Logik-basierten Modellierung verknüpft. Der Petri Netz und Fuzzy Logik (PNFL) Ansatz erlaubt eine natürlichsprachlich-basierte Beschreibung von biologischen Entitäten sowie eine Wenn-Dann-Regel-basierte Definition von Reaktionen. Beides kann einfach und direkt aus qualitativem Wissen abgeleitet werden. PNFL verbindet damit qualitatives Wissen und quantitative Modellierung.Current approaches in dynamic modeling of biological systems often lack comprehensibility,n especially for users without mathematical background. Additionally, exact data or detailed knowledge about concentrations, reaction kinetics or regulatory effects is missing. Thus, computational modeling of a biological system requires dealing with uncertainty and rough information provided by qualitative knowledge and linguistic descriptions. The author proposes a new approach to overcome such limitations by combining the graphical representation provided by Petri nets with the modeling of dynamics by powerful yet intuitive fuzzy logic based systems. The Petri net and fuzzy logic (PNFL) approach allows natural language based descriptions of biological entities as well as if-then rule based definitions of reactions, both of which can be easily and directly derived from qualitative knowledge. PNFL bridges the gap between qualitative knowledge and quantitative modeling