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Esch-sur-Alzette, Luxembourg

Del Sol I.C.A.,Luxembourg Center for Systems Biomedicine | Del Sol I.C.A.,University of Luxembourg
Stem Cells

Transcription factor cross-repression is an important concept in cellular differentiation. A bistable toggle switch constitutes a molecular mechanism that determines cellular commitment and provides stability to transcriptional programs of binary cell fate choices. Experiments support that perturbations of these toggle switches can interconvert these binary cell fate choices, suggesting potential reprogramming strategies. However, more complex types of cellular transitions could involve perturbations of combinations of different types of multistable motifs. Here, we introduce a method that generalizes the concept of transcription factor cross-repression to systematically predict sets of genes, whose perturbations induce cellular transitions between any given pair of cell types. Furthermore, to our knowledge, this is the first method that systematically makes these predictions without prior knowledge of potential candidate genes and pathways involved, providing guidance on systems where little is known. Given the increasing interest of cellular reprogramming in medicine and basic research, our method represents a useful computational methodology to assist researchers in the field in designing experimental strategies. © AlphaMed Press. Source

Mojtahedi M.,University of Calgary | D'Herouel A.F.,Institute for Systems Biology | D'Herouel A.F.,Luxembourg Center for Systems Biomedicine | Huang S.,University of Calgary | Huang S.,Institute for Systems Biology
Nucleic Acids Research

Digital PCR (dPCR) exploits limiting dilution of a template into an array of PCR reactions. From this array the number of reactions that contain at least one (as opposed to zero) initial template is determined, allowing inferring the original template concentration. Here we present a novel protocol to efficiently infer the concentration of a sample and its optimal dilution for dPCR from few targeted qPCR assays. By taking advantage of the real-time amplification feature of qPCR as opposed to relying on endpoint PCR assessment as in standard dPCR prior knowledge of template concentration is not necessary. This eliminates the need for serial dilutions in a separate titration and reduces the number of necessary reactions. We describe the theory underlying our approach and discuss experimental moments that contribute to uncertainty. We present data from a controlled experiment where the initial template concentration is known as proof of principle and apply our method on directly monitoring transcript level change during cell differentiation as well as gauging amplicon numbers in cDNA samples after pre-amplification. © The Author(s) 2014. Source

Yuan Y.,University of Cambridge | Glover K.,University of Cambridge | Goncalves J.,University of Cambridge | Goncalves J.,Luxembourg Center for Systems Biomedicine

Motivated by the fact that transfer functions do not contain structural information about networks (dependency of state variables), dynamical structure functions were introduced to capture causal relationships between measured nodes in networks. From the dynamical structure functions, (a) we show that the actual number of hidden states can be larger than the number of hidden states estimated from the corresponding transfer function; (b) we can obtain partial information about the true state-space equation, which cannot in general be obtained from the transfer function. Based on these properties, this paper proposes algorithms to find minimal realisations for a given dynamical structure function. This helps to estimate the minimal number of hidden states, to better understand the complexity of the network, and to identify potential targets for new measurements. © 2015 Elsevier Ltd. Source

Heinaniemi M.,University of Luxembourg | Heinaniemi M.,Luxembourg Center for Systems Biomedicine | Heinaniemi M.,University of Eastern Finland | Nykter M.,Tampere University of Technology | And 14 more authors.
Nature Methods

The distinct cell types of multicellular organisms arise owing to constraints imposed by gene regulatory networks on the collective change of gene expression across the genome, creating self-stabilizing expression states, or attractors. We curated human expression data comprising 166 cell types and 2,602 transcription-regulating genes and developed a data-driven method for identifying putative determinants of cell fate built around the concept of expression reversal of gene pairs, such as those participating in toggle-switch circuits. This approach allows us to organize the cell types into their ontogenic lineage relationships. Our method identifies genes in regulatory circuits that control neuronal fate, pluripotency and blood cell differentiation, and it may be useful for prioritizing candidate factors for direct conversion of cell fate. © 2013 Nature America, Inc. All rights reserved. Source

Diederich N.J.,Center Hospitalier Of Luxembourg | Diederich N.J.,Luxembourg Center for Systems Biomedicine | Parent A.,Laval University
Journal of the Neurological Sciences

In Parkinson's disease (PD) many motor and non-motor symptoms are difficult to explain in terms of a purely ascending degeneration process as described by Braak. This essay proposes phylogenetic considerations for consolidating the multidimensional elements of PD. Subtle clinical analysis paired with ethological comparisons as well as patho-anatomical data suggests that disrupted automatic gait control, olfactory deficits, selected visual deficits, impaired emotional face recognition, and REM sleep behavior disorder could be due to dysfunction of phylogenetically ancient networks. Neuroanatomical and behavioral findings lead to a reconsideration of the basal ganglia, to be viewed as the nuclear core of a widely distributed neural network that arborizes throughout the primordial core of the neuraxis, including the brainstem. Fragility of the resulting multiple, closed, ancillary loops that link brainstem and forebrain components of the basal ganglia may be a nodal point, pivotal to the pathogenesis of PD. Other primitive neural networks, such as those located at cardiac or gastro-intestinal levels, may share the same vulnerability. Such a network-based hypothesis overrides the need of a fixed temporal ordering of symptoms based on putative caudal-cephalic propagation patterns of pathological lesions. It also creates testable, secondary hypotheses such as differential gene expression in different neural networks, potential early epigenetic influences, concepts of "overuse" or maladaptation of primitive networks to the constraints of adult life, and system frailty due to irreparable mitochondrial "exhaustion" in highly energy consuming postmitotic cells. © 2011 Elsevier B.V. All rights reserved. Source

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