An evolutionary and functional assessment of regulatory network motifs.

BackgroundCellular functions are regulated by complex webs of interactions that might be schematically represented as networks. Two major examples are transcriptional regulatory networks, describing the interactions among transcription factors and their targets, and protein-protein interaction networks. Some patterns, dubbed motifs, have been found to be statistically over-represented when biological networks are compared to randomized versions thereof. Their function in vitro has been analyzed both experimentally and theoretically, but their functional role in vivo, that is, within the full network, and the resulting evolutionary pressures remain largely to be examined.ResultsWe investigated an integrated network of the yeast Saccharomyces cerevisiae comprising transcriptional and protein-protein interaction data. A comparative analysis was performed with respect to Candida glabrata, Kluyveromyces lactis, Debaryomyces hansenii and Yarrowia lipolytica, which belong to the same class of hemiascomycetes as S. cerevisiae but span a broad evolutionary range. Phylogenetic profiles of genes within different forms of the motifs show that they are not subject to any particular evolutionary pressure to preserve the corresponding interaction patterns. The functional role in vivo of the motifs was examined for those instances where enough biological information is available. In each case, the regulatory processes for the biological function under consideration were found to hinge on post-transcriptional regulatory mechanisms, rather than on the transcriptional regulation by network motifs.ConclusionThe overabundance of the network motifs does not have any immediate functional or evolutionary counterpart. A likely reason is that motifs within the networks are not isolated, that is, they strongly aggregate and have important edge and/or node sharing with the rest of the network

Whole Genome Duplications and a ‘Function’ for Junk DNA? Facts and Hypotheses

International audienceBACKGROUND: The lack of correlation between genome size and organismal complexity is understood in terms of the massive presence of repetitive and non-coding DNA. This non-coding subgenome has long been called "junk" DNA. However, it might have important functions. Generation of junk DNA depends on proliferation of selfish DNA elements and on local or global DNA duplication followed by genic non-functionalization. METHODOLOGY/PRINCIPAL FINDINGS: Evidence from genomic analyses and experimental data indicates that Whole Genome Duplications (WGD) are often followed by a return to the diploid state, through DNA deletions and intra/interchromosomal rearrangements. We use simple theoretical models and simulations to explore how a WGD accompanied by sequence deletions might affect the dosage balance often required among several gene products involved in regulatory processes. We find that potential genomic deletions leading to changes in nuclear and cell volume might potentially perturb gene dosage balance. CONCLUSIONS/SIGNIFICANCE: The potentially negative impact of DNA deletions can be buffered if deleted genic DNA is, at least temporarily, replaced by repetitive DNA so that the nuclear/cell volume remains compatible with normal living. Thus, we speculate that retention of non-functionalized non-coding DNA, and replacement of deleted DNA through proliferation of selfish elements, might help avoid dosage imbalances in cycles of polyploidization and diploidization, which are particularly frequent in plants

Combining Microfluidics, Optogenetics and Calcium Imaging to Study Neuronal Communication In Vitro

International audienceIn this paper we report the combination of microfluidics, optogenetics and calcium imaging as a cheap and convenient platform to study synaptic communication between neuronal populations in vitro. We first show that Calcium Orange indicator is compatible in vitro with a commonly used Channelrhodopsine-2 (ChR2) variant, as standard calcium imaging conditions did not alter significantly the activity of transduced cultures of rodent primary neurons. A fast, robust and scalable process for micro-chip fabrication was developed in parallel to build micro-compartmented cultures. Coupling optical fibers to each micro-compartment allowed for the independent control of ChR2 activation in the different populations without crosstalk. By analyzing the post-stimuli activity across the different populations, we finally show how this platform can be used to evaluate quantitatively the effective connectivity between connected neuronal populations

Rich dynamics and functional organization on topographically designed neuronal networks in vitro

Neuronal cultures are a prominent experimental tool to understand complex functional organization in neuronal assemblies. However, neurons grown on flat surfaces exhibit a strongly coherent bursting behavior with limited functionality. To approach the functional richness of naturally formed neuronal circuits, here we studied neuronal networks grown on polydimethylsiloxane (PDMS) topographical patterns shaped as either parallel tracks or square valleys.We followed the evolution of spontaneous activity in these cultures along 20 days in vitro using fluorescence calcium imaging. The networks were characterized by rich spatiotemporal activity patterns that comprised from small regions of the culture to its whole extent. Effective connectivity analysis revealed the emergence of spatially compact functional modules that were associated with both the underpinned topographical features and predominant spatiotemporal activity fronts. Our results showthe capacity of spatial constraints tomold activity and functional organization, bringing new opportunities to comprehend the structure-function relationship in living neuronal circuits

Memory decay and loss of criticality in quorum percolation

International audienceIn this paper, we present the effects of memory decay on a bootstrap percolation model applied to randomdirected graphs (quorum percolation). The addition of decay was motivated by its natural occurrence in physicalsystems previously described by percolation theory, such as cultured neuronal networks, where decay originatesfrom ionic leakage through the membrane of neurons and/or synaptic depression. Surprisingly, this featurealone appears to change the critical behavior of the percolation transition, where discontinuities are replacedby steep but finite slopes. Using different numerical approaches, we show evidence for this qualitative changeeven for very small decay values. In experiments where the steepest slopes can not be resolved and still appearas discontinuities, decay produces nonetheless a quantitative difference on the location of the apparent criticalpoint. We discuss how this shift impacts network connectivity previously estimated without considering decay.In addition to this particular example, we believe that other percolation models are worth reinvestigating, takinginto account similar sorts of memory decay

An evolutionary and functional assessment of regulatory network motifs.

BackgroundCellular functions are regulated by complex webs of interactions that might be schematically represented as networks. Two major examples are transcriptional regulatory networks, describing the interactions among transcription factors and their targets, and protein-protein interaction networks. Some patterns, dubbed motifs, have been found to be statistically over-represented when biological networks are compared to randomized versions thereof. Their function in vitro has been analyzed both experimentally and theoretically, but their functional role in vivo, that is, within the full network, and the resulting evolutionary pressures remain largely to be examined.ResultsWe investigated an integrated network of the yeast Saccharomyces cerevisiae comprising transcriptional and protein-protein interaction data. A comparative analysis was performed with respect to Candida glabrata, Kluyveromyces lactis, Debaryomyces hansenii and Yarrowia lipolytica, which belong to the same class of hemiascomycetes as S. cerevisiae but span a broad evolutionary range. Phylogenetic profiles of genes within different forms of the motifs show that they are not subject to any particular evolutionary pressure to preserve the corresponding interaction patterns. The functional role in vivo of the motifs was examined for those instances where enough biological information is available. In each case, the regulatory processes for the biological function under consideration were found to hinge on post-transcriptional regulatory mechanisms, rather than on the transcriptional regulation by network motifs.ConclusionThe overabundance of the network motifs does not have any immediate functional or evolutionary counterpart. A likely reason is that motifs within the networks are not isolated, that is, they strongly aggregate and have important edge and/or node sharing with the rest of the network

Effects of inhibitory neurons on the quorum percolation model and dynamical extension with the Brette-Gerstner model

International audienceThe Quorum Percolation model (QP) has been designed in the context of neuro-biology to describe the initiation of activity bursts occurring in neuronal cultures from the point of view of statistical physics rather than from a dynamical synchronization approach. This paper aims at investigating an extension of the original QP model by taking into account the presence of inhibitory neurons in the cultures (IQP model). The first part of this paper is focused on an equivalence between the presence of inhibitory neurons and a reduction of the network connectivity. By relying on a simple topological argument, we show that the mean activation behavior of networks containing a fraction η of inhibitory neu-rons can be mapped onto purely excitatory networks with an appropriately modified wiring, provided that η remains in the range usually observed in neu-ronal cultures, namely η 20%. As a striking result, we show that such a mapping enables to predict the evolution of the critical point of the IQP model with the fraction of inhibitory neurons. In a second part, we bridge the gap between the description of bursts in the framework of percolation and the temporal description of neural networks activity by showing how dynamical simulations of bursts with an adaptive exponential integrate-and-fire model lead to a mean description of bursts activation which is captured by Quorum Percolation

Quantitative exploration of specific transcription factor binding in the presence of different levels of non specific binding.

<p>Quantitative exploration of specific transcription factor binding in the presence of different levels of non specific binding. Consider a TF ([TF] = 1 nM) that specifically recognizes 10 binding sites/nucleus. Specific recognition takes place with Ks' ranging between 10⁸ to 10¹⁴) while non-specific recognition takes place with much lower affinity. Intranuclear concentration of specific target sites is about 3.10⁻¹¹M (assuming a nuclear volume of 5.10⁻¹³L). The initial concentration of irrelevant DNA binding sites is assumed to be 7 orders of magnitude higher than sDNA. The color scale represents the ratio of the concentration of TF bound to specific site on DNA in the case WGD+ (leaving TF and its targets duplicated) over the concentration of TF bound to specific sites before WGD. For low non-specific binding the concentration of specifically bound TF targets in WGD+ is twice as much as in the case without WGD (blue zone). In presence of significant non-specific binding, the concentration of specifically bound sites can be as much as 4× higher than without duplication as the synthesis of TFs is doubled whereas non-specific binding sites available for sequestration are in identical concentration. The example of TF1 and TF2 (in balance) is displayed. TF1 and TF2 have the same global concentration but TF1 binds only specifically and TF2 has substantial non-specific binding. Under the scenario WGD+, TF2 might form as much as two times more complexes than TF1, which obviously would perturb their balance.</p

Effective non-universality of the quorum percolation model on directed graphs with Gaussian in-degree

International audienceWe investigate a model derived from bootstrap percolation on a directed random graph with Gaussian in-degree useful in describing the collective behavior of dissociated neuronal networks. By developing a continuous version of the model, we were able to provide accurate values of the critical thresholds and exponents associated with the occurrence of a giant cluster. As a main result, it turns out that the values of the exponents calculated over a numerical accessible range covering more than two orders of magnitude below the critical point exhibit a slight dependence upon the connectivity of the graph