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Designer Chromosome One of the ultimate aims of synthetic biology is to build designer organisms from the ground up. Rapid advances in DNA synthesis has allowed the assembly of complete bacterial genomes. Eukaryotic organisms, with their generally much larger and more complex genomes, present an additional challenge to synthetic biologists. Annaluru et al. (p. 55 , published online 27 March) designed a synthetic eukaryotic chromosome based on yeast chromosome III. The designer chromosome, shorn of destabilizing transfer RNA genes and transposons, is ∼14% smaller than its wild-type template and is fully functional with every gene tagged for easy removal.

International audience; Background: Hereditary optic neuropathies (HONs) are a heterogeneous group of disorders that affect retinal ganglion cells (RGCs) and axons that form the optic nerve. Leber's Hereditary Optic Neuropathy and the autosomal dominant optic atrophy related to OPA1 mutations are the most common forms. Nonsyndromic autosomal recessive optic neuropathies are rare and their existence has been long debated. We recently identified the first gene responsible for these conditions, TMEM126A. This gene is highly expressed in retinal cellular compartments enriched in mitochondria and supposed to encode a mitochondrial transmembrane protein of unknown function. Methods: A specific polyclonal antibody targeting the TMEM126A protein has been generated. Quantitative fluorescent in situ hybridization, cellular fractionation, mitochondrial membrane association study, mitochondrial sub compartmentalization analysis by both proteolysis assays and transmission electron microscopy, and expression analysis of truncated TMEM126A constructs by immunofluorescence confocal microscopy were carried out. Results: TMEM126A mRNAs are strongly enriched in the vicinity of mitochondria and encode an inner mitochondrial membrane associated cristae protein. Moreover, the second transmembrane domain of TMEM126A is required for its mitochondrial localization. Conclusions: TMEM126A is a mitochondrial located mRNA (MLR) that may be translated in the mitochondrial surface and the protein is subsequently imported to the inner membrane. These data constitute the first step toward a better understanding of the mechanism of action of TMEM126A in RGCs and support the importance of mitochondrial dysfunction in the pathogenesis of HON. General significance: Local translation of nuclearly encoded mitochondrial mRNAs might be a mechanism for rapid onsite supply of mitochondrial membrane proteins. (C) 2013 Elsevier B.V. All rights reserved.

This article is categorized under: Software > Molecular Modeling Quantum Computing > Theory Development Structure and Mechanism > Computational Biochemistry and Biophysics, Noncovalent interactions are of utmost importance. However, their accurate treatment is still difficult. This is partially induced by the coexistence of many types of interactions and physical phenomena, which hampers generality in simple treatments. The NCI index has been successfully used for nearly over 10 years in order to identify, analyze, and understand noncovalent interactions in a wide variety of systems, ranging from proteins to molecular crystals. In this work, the development and implications of the method will be reviewed, and modern implementations will be presented. Afterward, some sophisticated examples will be given that showcase the current advances toward the fast, robust, and intuitive identification of noncovalent interactions in real space., Agence Nationale de la Recherche, Grant/Award Numbers: ANR-11-IDEX-0004-02, ANR-11-LABX-0037-01; PICS-CNRS; Ecole doctorale 388; H2020 European Research Council, Grant/Award Number: 810367; Institut Universitaire de France; PHC PROCOPE 2017.

While the activity of multiprotein complexes is crucial for cellular metabolism, little is known about the mechanisms that collectively control the expression of their components. Here, we investigate the regulations targeting the biogenesis of the nuclear pore complex (NPC), the macromolecular assembly mediating nucleocytoplasmic exchanges. Systematic analysis of RNA-binding proteins interactomes, together with in vivo and in vitro assays, reveal that a subset of NPC mRNAs are specifically bound by Hek2, a yeast hnRNP K-like protein. Hek2-dependent translational repression and protein turnover are further shown to finely tune the levels of NPC subunits. Strikingly, mutations or physiological perturbations altering pore integrity decrease the levels of the NPC-associated SUMO protease Ulp1, and trigger the accumulation of sumoylated versions of Hek2 unable to bind NPC mRNAs. Our results support the existence of a quality control mechanism involving Ulp1 as a sensor of NPC integrity and Hek2 as a repressor of NPC biogenesis., The nuclear pore complex is crucial for mediating nucleocytoplasmic exchanges. Here the authors use budding yeast to reveal a mechanism responsible of maintaining nucleoporin homeostasis by sensing changes in the complex integrity and further altering the metabolism of the corresponding mRNAs.

Timing is essential for many cellular processes, from cellular responses to external stimuli to the cell cycle and circadian clocks. Many of these processes are based on gene expression. For example, an activated gene may be required to reach in a precise time a threshold level of expression that triggers a specific downstream process. However, gene expression is subject to stochastic fluctuations, naturally inducing an uncertainty in this threshold-crossing time with potential consequences on biological functions and phenotypes. Here, we consider such "timing fluctuations", and we ask how they can be controlled. Our analytical estimates and simulations show that, for an induced gene, timing variability is minimal if the threshold level of expression is approximately half of the steady-state level. Timing fuctuations can be reduced by increasing the transcription rate, while they are insensitive to the translation rate. In presence of self-regulatory strategies, we show that self-repression reduces timing noise for threshold levels that have to be reached quickly, while selfactivation is optimal at long times. These results lay a framework for understanding stochasticity of endogenous systems such as the cell cycle, as well as for the design of synthetic trigger circuits., Comment: 10 pages, 5 figures

A recent burst of dynamic single-cell growth-division data makes it possible to characterize the stochastic dynamics of cell division control in bacteria. Different modeling frameworks were used to infer specific mechanisms from such data, but the links between frameworks are poorly explored, with relevant consequences for how well any particular mechanism can be supported by the data. Here, we describe a simple and generic framework in which two common formalisms can be used interchangeably: (i) a continuous-time division process described by a hazard function and (ii) a discrete-time equation describing cell size across generations (where the unit of time is a cell cycle). In our framework, this second process is a discrete-time Langevin equation with a simple physical analogue. By perturbative expansion around the mean initial size (or inter-division time), we show explicitly how this framework describes a wide range of division control mechanisms, including combinations of time and size control, as well as the constant added size mechanism recently found to capture several aspects of the cell division behavior of different bacteria. As we show by analytical estimates and numerical simulation, the available data are characterized with great precision by the first-order approximation of this expansion. Hence, a single dimensionless parameter defines the strength and the action of the division control. However, this parameter may emerge from several mechanisms, which are distinguished only by higher-order terms in our perturbative expansion. An analytical estimate of the sample size needed to distinguish between second-order effects shows that this is larger than what is available in the current datasets. These results provide a unified framework for future studies and clarify the relevant parameters at play in the control of cell division., 15 pages, 5 figures

The Escherichia coli cell cycle is a classic, but we are still missing some of its essential aspects. The reason is that our knowledge is mostly based on population data, and our grasp of the behavior of single cells is still very limited. Today, new dynamic single-cell data promise to overcome this barrier. Existing data from single cells have already led to findings and hypotheses that challenge standard views, and have raised new questions. Here, we review these recent developments and propose that a systematic exploration of the correlation patterns between ‘cell-cycle intervals’ defined by key molecular events measured in many single cells could lead to a quantitative characterization of the cell cycle in terms of inherent stochasticity and homeostatic controls.

Motivation: MicroRNAs (miRNAs) are a class of endogenes derived from a precursor (pre-miRNA) and involved in post-transcriptional regulation. Experimental identification of novel miRNAs is difficult because they are often transcribed under specific conditions and cell types. Several computational methods were developed to detect new miRNAs starting from known ones or from deep sequencing data, and to validate their pre-miRNAs. Results: We present a genome-wide search algorithm, called MIReNA, that looks for miRNA sequences by exploring a multidimensional space defined by only five (physical and combinatorial) parameters characterizing acceptable pre-miRNAs. MIReNA validates pre-miRNAs with high sensitivity and specificity, and detects new miRNAs by homology from known miRNAs or from deep sequencing data. A performance comparison between MIReNA and four available predictive systems has been done. MIReNA approach is strikingly simple but it turns out to be powerful at least as much as more sophisticated algorithmic methods. MIReNA obtains better results than three known algorithms that validate pre-miRNAs. It demonstrates that machine-learning is not a necessary algorithmic approach for pre-miRNAs computational validation. In particular, machine learning algorithms can only confirm pre-miRNAs that look alike known ones, this being a limitation while exploring species with no known pre-miRNAs. The possibility to adapt the search to specific species, possibly characterized by specific properties of their miRNAs and pre-miRNAs, is a major feature of MIReNA. A parameter adjustment calibrates specificity and sensitivity in MIReNA, a key feature for predictive systems, which is not present in machine learning approaches. Comparison of MIReNA with miRDeep using deep sequencing data to predict miRNAs highlights a highly specific predictive power of MIReNA. Availability: At the address http://www.ihes.fr/˜carbone/data8/ Contact: alessandra.carbone@lip6.fr Supplementary information: Supplementary data are available at Bioinformatics online.

International audience; Flavohemoglobins are the main detoxifiers of nitric oxide (NO) in bacteria and fungi and are induced in response to nitrosative stress. In fungi, the flavohemoglobin encoding gene YHB1 is positively regulated by transcription factors which are activated upon NO exposure. In this study, we show that in the model yeast Saccharomyces cerevisiae and in the human pathogen Candida glabrata, the transcription factor Yap7 constitutively represses YHB1 by binding its promoter. Consequently, YAP7 deletion conferred high NO resistance to the cells. Co-immunoprecipitation experiments and mutant analyses indicated that Yap7 represses YHB1 by recruiting the transcriptional repressor Tup1. In S. cerevisiae, YHB1 repression also involves interaction of Yap7 with the Hap2/3/5 complex through a conserved Hap4-like-bZIP domain, but this interaction has been lost in C. glabrata. The evolutionary origin of this regulation was investigated by functional analyses of Yap7 and of its paralogue Yap5 in different yeast species. These analyses indicated that the negative regulation of YHB1 by Yap7 arose by neofunctionalization after the whole genome duplication which led to the C. glabrata and S. cerevisiae extant species. This work describes a new aspect of the regulation of fungal nitric oxidase and provides detailed insights into its functioning and evolution.

As the elementary building block of eukaryotic chromatin, the nucleosome is at the heart of the compromise between the necessity of compacting DNA in the cell nucleus and the required accessibility to regulatory proteins. The recent availability of genome-wide experimental maps of nucleosome positions for many different organisms and cell types has provided an unprecedented opportunity to elucidate to what extent the DNA sequence conditions the primary structure of chromatin and in turn participates in the chromatin-mediated regulation of nuclear functions, such as gene expression and DNA replication. In this study, we use in vivo and in vitro genome-wide nucleosome occupancy data together with the set of nucleosome-free regions (NFRs) predicted by a physical model of nucleosome formation based on sequence-dependent bending properties of the DNA double-helix, to investigate the role of intrinsic nucleosome occupancy in the regulation of the replication spatio-temporal programme in human. We focus our analysis on the so-called replication U/N-domains that were shown to cover about half of the human genome in the germline (skew-N domains) as well as in embryonic stem cells, somatic and HeLa cells (mean replication timing U-domains). The 'master' origins of replication (MaOris) that border these megabase-sized U/N-domains were found to be specified by a few hundred kb wide regions that are hyper-sensitive to DNase I cleavage, hypomethylated, and enriched in epigenetic marks involved in transcription regulation, the hallmarks of localized open chromatin structures. Here we show that replication U/N-domain borders that are conserved in all considered cell lines have an environment highly enriched in nucleosome-excluding-energy barriers, suggesting that these ubiquitous MaOris have been selected during evolution. In contrast, MaOris that are cell-type-specific are mainly regulated epigenetically and are no longer favoured by a local abundance of intrinsic NFRs encoded in the DNA sequence. At the smaller few hundred bp scale of gene promoters, CpG-rich promoters of housekeeping genes found nearby ubiquitous MaOris as well as CpG-poor promoters of tissue-specific genes found nearby cell-type-specific MaOris, both correspond to in vivo NFRs that are not coded as nucleosome-excluding-energy barriers. Whereas the former promoters are likely to correspond to high occupancy transcription factor binding regions, the latter are an illustration that gene regulation in human is typically cell-type-specific.

International audience; By implementing an external feedback loop one can tightly control the expression of a gene over many cell generations with quantitative accuracy. Controlling precisely the level of a protein of interest will be useful to probe quantitatively the dynamical properties of cellular processes and to drive complex, synthetically-engineered networks. In this chapter we describe a platform for real-time closed-loop control of gene expression in yeast that integrates microscopy for monitoring gene expression at the cell level, microfluidics to manipulate the cells environment and original software for automated imaging, quantification and model predictive control. By using an endogenous osmo-stress responsive promoter and playing with the osmolarity of the cells environment, we demonstrate that long-term control can indeed be achieved for both time-constant and time-varying target profiles, at the population level, and even at the single-cell level.

International audience; Candida albicans causes superficial to systemic infections in immuno-compromised individuals. The concomitant use of fungistatic drugs and the lack of cidal drugs frequently result in strains that could withstand commonly used antifungals, and display multidrug resistance (MDR). In search of novel fungicidals, in this study, we have explored a plant alkaloid berberine (BER) for its antifungal potential. For this, we screened an in-house transcription factor (TF) mutant library of C. albicans strains towards their susceptibility to BER. Our screen of TF mutant strains identified a heat shock factor (HSF1), which has a central role in thermal adaptation, to be most responsive to BER treatment. Interestingly, HSF1 mutant was not only highly susceptible to BER but also displayed collateral susceptibility towards drugs targeting cell wall (CW) and ergosterol biosynthesis. Notably, BER treatment alone could affect the CW integrity as was evident from the growth retardation of MAP kinase and calcineurin pathway null mutant strains and transmission electron microscopy. However, unlike BER, HSF1 effect on CW appeared to be independent of MAP kinase and Calcineurin pathway genes. Additionally, unlike hsf1 null strain, BER treatment of Candida cells resulted in dysfunctional mitochondria, which was evident from its slow growth in non-fermentative carbon source and poor labeling with mitochondrial membrane potential sensitive probe. This phenotype was reinforced with an enhanced ROS levels coinciding with the up-regulated oxidative stress genes in BER-treated cells. Together, our study not only describes the molecular mechanism of BER fungicidal activity but also unravels a new role of evolutionary conserved HSF1, in MDR of Candida.

Besides their large-scale organization in isochores, mammalian genomes display megabase-sized regions, spanning both genes and intergenes, where the strand nucleotide composition asymmetry decreases linearly, possibly due to replication activity. These so-called skew-N domains cover about a third of the human genome and are bordered by two skew upward jumps that were hypothesized to compose a subset of "master" replication origins active in the germline. Skew-N domains were shown to exhibit a particular gene organization. Genes with CpG-rich promoters likely expressed in the germline are over represented near the master replication origins, with large genes being co-oriented with replication fork progression, which suggests some coordination of replication and transcription. In this study, we describe another skew structure that covers ∼13% of the human genome and that is bordered by putative master replication origins similar to the ones flanking skew-N domains. These skew-split-N domains have a shape reminiscent of a N, but split in half, leaving in the center a region of null skew whose length increases with domain size. These central regions (median size ∼860 kb) have a homogeneous composition, i.e. both a null and constant skew and a constant and low GC content. They correspond to heterochromatin gene deserts found in low-GC isochores with an average gene density of 0.81 promoters/Mb as compared to 7.73 promoters/Mb genome wide. The analysis of epigenetic marks and replication timing data confirms that, in these late replicating heterochomatic regions, the initiation of replication is likely to be random. This contrasts with the transcriptionally active euchromatin state found around the bordering well positioned master replication origins. Altogether skew-N domains and skew-split-N domains cover about 50% of the human genome.

International audience; The coordination of cell growth and division is a long-standing problem in biology. Focusing on Escherichia coli in steady growth, we quantify cell division control using a stochastic model, by inferring the division rate as a function of the observable parameters from large empirical datasets of dividing cells. We find that (i) cells have mechanisms to control their size, (ii) size control is effected by changes in the doubling time, rather than in the single-cell elongation rate, (iii) the division rate increases steeply with cell size for small cells, and saturates for larger cells. Importantly, (iv) the current size is not the only variable controlling cell division, but the time spent in the cell cycle appears to play a role, and (v) common tests of cell size control may fail when such concerted control is in place. Our analysis illustrates the mechanisms of cell division control in E. coli. The phenomenological framework presented is sufficiently general to be widely applicable and opens the way for rigorous tests of molecular cell-cycle models.

Previous experiments revealed that DHH1, a RNA helicase involved in the regulation of mRNA stability and translation, complemented the phenotype of a Saccharomyces cerevisiae mutant affected in the expression of genes coding for monocarboxylic-acids transporters, JEN1 and ADY2 (Paiva S, Althoff S, Casal M, Leao C. FEMS Microbiol Lett, 1999, 170:301-306). In wild type cells, JEN1 expression had been shown to be undetectable in the presence of glucose or formic acid, and induced in the presence of lactate. In this work, we show that JEN1 mRNA accumulates in a dhh1 mutant, when formic acid was used as sole carbon source. Dhh1 interacts with the decapping activator Dcp1 and with the deadenylase complex. This led to the hypothesis that JEN1 expression is post-transcriptionally regulated by Dhh1 in formic acid. Analyses of JEN1 mRNAs decay in wild-type and dhh1 mutant strains confirmed this hypothesis. In these conditions, the stabilized JEN1 mRNA was associated to polysomes but no Jen1 protein could be detected, either by measurable lactate carrier activity, Jen1-GFP fluorescence detection or western blots. These results revealed the complexity of the expression regulation of JEN1 in S. cerevisiae and evidenced the importance of DHH1 in this process. Additionally, microarray analyses of dhh1 mutant indicated that Dhh1 plays a large role in metabolic adaptation, suggesting that carbon source changes triggers a complex interplay between transcriptional and post-transcriptional effects., This study was supported by the Portuguese grant POCI/BIA-BCM/57812/2004 (Eixo 2, Medida 2.3, QCAIII - FEDER). N.V. received a FCT PhD fellowship (SFRH/BD/23503/2005). S.M. received a FCT PhD fellowship (SFRH/BD/74790/2010). F.D.'s work is supported by a grant from the Agence pour la Recherche contre le Cancer (ARC). Support to C.B.M.A. by FEDER through POFC-COMPETE and by Portuguese funds from FCT through the project PEst-OE/BIA/UI4050/2014 is also acknowledged. The authors thank Josette Banroques and Kyle Tanner for their advice regarding polysome gradients. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

International audience; The development of a complex system depends on the self-coordinated action of a large number of agents, often determining unexpected global behavior. The case of software evolution has great practical importance: knowledge of what is to be considered atypical can guide developers in recognizing and reacting to abnormal behavior. Although the initial framework of a theory of software exists, the current theoretical achievements do not fully capture existing quantitative data or predict future trends. Here we show that two elementary laws describe the evolution of package sizes in a Linux-based operating system: first, relative changes in size follow a random walk with non-Gaussian jumps; second, each size change is bounded by a limit that is dependent on the starting size, an intriguing behavior that we call ``soft bound.'' Our approach is based on data analysis and on a simple theoretical model, which is able to reproduce empirical details without relying on any adjustable parameter and generates definite predictions. The same analysis allows us to formulate and support the hypothesis that a similar mechanism is shaping the distribution of mammalian body sizes, via size-dependent constraints during cladogenesis. Whereas generally accepted approaches struggle to reproduce the large-mass shoulder displayed by the distribution of extant mammalian species, this is a natural consequence of the softly bounded nature of the process. Additionally, the hypothesis that this model is valid has the relevant implication that, contrary to a common assumption, mammalian masses are still evolving, albeit very slowly.

International audience; The THO complex is involved in transcription, genome stability, and messenger ribonucleoprotein (mRNP) formation, but its precise molecular function remains enigmatic. Under heat shock conditions, THO mutants accumulate large protein-DNA complexes that alter the chromatin density of target genes (heavy chromatin), defining a specific biochemical facet of THO function and a powerful tool of analysis. Here, we show that heavy chromatin distribution is dictated by gene boundaries and that the gene promoter is necessary and sufficient to convey THO sensitivity in these conditions. Single-molecule fluorescence in situ hybridization measurements show that heavy chromatin formation correlates with an unusually high firing pace of the promoter with more than 20 transcription events per minute. Heavy chromatin formation closely follows the modulation of promoter firing and strongly correlates with polymerase occupancy genome wide. We propose that the THO complex is required for tuning the dynamic of gene-nuclear pore association and mRNP release to the same high pace of transcription initiation.

26th International Conference on Yeast Genetics and Molecular Biology, Frankfurt Main, GERMANY, AUG 29-SEP 03, 2013; International audience; no abstract

International audience; In all-atom molecular simulation studies of proteins, each atom in the protein is represented by a point mass and interactions are defined in terms of the atomic positions. In recent years, various simplified approaches have been proposed. These approaches aim to improve computational efficiency and to provide a better physical insight. The simplified models can differ widely in their description of the geometry and the interactions inside the protein. This study explores the most fundamental choice in the simplified protein models: the choice of a coordinate set defining the protein structure. A simplified model can use fewer point masses than the all-atom model and/or eliminate some of the internal coordinates of the molecule by setting them to an average or ideal value. We look at the implications of such choices for the overall protein structure. We find that care must be taken for angular coordinates, where even very small variations can lead to significant changes in the positions of far away atoms. In particular, we show that the phi/psi torsion angles are not a sufficient coordinate set, whereas another coordinate set with two degrees of freedom per residue, virtual C-alpha backbone bond, and torsion angles performs satisfactorily. (C) 2013 AIP Publishing LLC.

Various approaches have explored the covariation of residues in multiple-sequence alignments of homologous proteins to extract functional and structural information. Among those are principal component analysis (PCA), which identifies the most correlated groups of residues, and direct coupling analysis (DCA), a global inference method based on the maximum entropy principle, which aims at predicting residue-residue contacts. In this paper, inspired by the statistical physics of disordered systems, we introduce the Hopfield-Potts model to naturally interpolate between these two approaches. The Hopfield-Potts model allows us to identify relevant ‘patterns’ of residues from the knowledge of the eigenmodes and eigenvalues of the residue-residue correlation matrix. We show how the computation of such statistical patterns makes it possible to accurately predict residue-residue contacts with a much smaller number of parameters than DCA. This dimensional reduction allows us to avoid overfitting and to extract contact information from multiple-sequence alignments of reduced size. In addition, we show that low-eigenvalue correlation modes, discarded by PCA, are important to recover structural information: the corresponding patterns are highly localized, that is, they are concentrated in few sites, which we find to be in close contact in the three-dimensional protein fold., Author Summary Extracting functional and structural information about protein families from the covariation of residues in multiple sequence alignments is an important challenge in computational biology. Here we propose a statistical-physics inspired framework to analyze those covariations, which naturally unifies existing methods in the literature. Our approach allows us to identify statistically relevant ‘patterns’ of residues, specific to a protein family. We show that many patterns correspond to a small number of sites on the protein sequence, in close contact on the 3D fold. Hence, those patterns allow us to make accurate predictions about the contact map from sequence data only. Further more, we show that the dimensional reduction, which is achieved by considering only the statistically most significant patterns, avoids overfitting in small sequence alignments, and improves our capacity of extracting residue contacts in this case.

International audience; The reconstruction of the history of rearrangements and the reconstruction of ancestral genomes are some of the challenges of bioinformatics today. Many algorithms already exist, treating one or the other question but none treating both. These reconstructions are interdependent and we argue on the interest of treating both problems in parallel to lead to a richer and more complete output. We also argue on the importance of redefining several steps of these algorithms to improve both reconstructions: the identification of synteny blocks has to be as precise as possible, and the treatment of multiple genomes has to be based on pairwise comparisons to ensure the most detailed reconstructions. In this article, we highlight novel solutions to these points and focus on the need of explicitly treating overlapping, included, duplicated and unsigned synteny blocks. To do so, we introduce the new notion of synteny pack, which is a representation of local hypothetical intermediate ancestral genomes. We discuss a number of examples on yeast genomes to illustrate the importance of such a definition.

International audience; In bacteria, chromosomal architecture shows strong spatial and temporal organization, and regulates key cellular functions, such as transcription. Tracking the motion of chromosomal loci at short timescales provides information related to both the physical state of the nucleo-protein complex and its local environment, independent of large-scale motions related to genome segregation. Here we investigate the short-time (0.1-10 s) dynamics of fluorescently labelled chromosomal loci in Escherichia coli at different growth rates. At these timescales, we observe for the first time a dependence of the loci's apparent diffusion on both their subcellular localization and chromosomal coordinate, and we provide evidence that the properties of the chromosome are similar in the tested growth conditions. Our results indicate that either non-equilibrium fluctuations due to enzyme activity or the organization of the genome as a polymer-protein complex vary as a function of the distance from the origin of replication.

International audience; The H-NS chromosome-organizing protein in E. coli can stabilize genomic DNA loops, and form oligomeric structures connected to repression of gene expression. Motivated by the link between chromosome organization, protein binding and gene expression, we analyzed publicly available genomic data sets of various origins, from genome-wide protein binding profiles to evolutionary information, exploring the connections between chromosomal organization, gene-silencing, pseudo-gene localization and horizontal gene transfer. We report the existence of transcriptionally silent contiguous areas corresponding to large regions of H-NS protein binding along the genome, their position indicates a possible relationship with the known large-scale features of chromosome organization.

Cell division in photosynthetic organisms is tightly regulated by light. Although the light dependency of the onset of the cell cycle has been well characterized in various phototrophs, little is known about the cellular signaling cascades connecting light perception to cell cycle activation and progression. Here, we demonstrate that diatom-specific cyclin 2 (dsCYC2) in Phaeodactylum tricornutum displays a transcriptional peak within 15 min after light exposure, long before the onset of cell division. The product of dsCYC2 binds to the cyclin-dependent kinase CDKA1 and can complement G1 cyclin-deficient yeast. Consistent with the role of dsCYC2 in controlling a G1-to-S light-dependent cell cycle checkpoint, dsCYC2 silencing decreases the rate of cell division in diatoms exposed to light-dark cycles but not to constant light. Transcriptional induction of dsCYC2 is triggered by blue light in a fluence rate-dependent manner. Consistent with this, dsCYC2 is a transcriptional target of the blue light sensor AUREOCHROME1a, which functions synergistically with the basic leucine zipper (bZIP) transcription factor bZIP10 to induce dsCYC2 transcription. The functional characterization of a cyclin whose transcription is controlled by light and whose activity connects light signaling to cell cycle progression contributes significantly to our understanding of the molecular mechanisms underlying light-dependent cell cycle onset in diatoms.

International audience; We examine the phenomenon of hydrodynamic-induced cooperativity for pairs of flagellated micro-organism swimmers, of which spermatozoa cells are an example. We consider semiflexible swimmers, where inextensible filaments are driven by an internal intrinsic force and torque-free mechanism (intrinsic swimmers). The velocity gain for swimming cooperatively, which depends on both the geometry and the driving, develops as a result of the near-field coupling of bending and hydrodynamic stresses. We identify the regimes where hydrodynamic cooperativity is advantageous and quantify the change in efficiency. When the filaments' axes are parallel, hydrodynamic interaction induces a directional instability that causes semiflexible swimmers that profit from swimming together to move apart from each other. Biologically, this implies that flagella need to select different synchronized collective states and to compensate for directional instabilities (e. g., by binding) in order to profit from swimming together. By analyzing the cooperative motion of pairs of externally actuated filaments, we assess the impact that stress distribution along the filaments has on their collective displacements. DOI: 10.1103/PhysRevE.87.032720

International audience; We designed a microfluidic chemostat consisting of 600 sub-micron trapping/growth channels connected to two feeding channels. The microchemostat traps E. coli cells and forces them to grow in lines for over 50 generations. Excess cells, including the mother cells captured at the start of the process, are removed from both ends of the growth channels by the media flow. With the aid of time-lapse microscopy, we have monitored dynamic properties such as growth rate and GFP expression at the single-cell level for many generations while maintaining a population of bacteria of similar age. We also use the microchemostat to show how the population responds to dynamic changes in the environment. Since more than 100 individual bacterial cells are aligned and immobilized in a single field of view, the microchemostat is an ideal platform for high-throughput intracellular measurements. We demonstrate this capability by tracking with sub-diffraction resolution the movements of fluorescently tagged loci in more than one thousand cells on a single device. The device yields results comparable to conventional agar microscopy experiments with substantial increases in throughput and ease of analysis.

Spatially proximate amino acids in a protein tend to coevolve. A protein's three-dimensional (3D) structure hence leaves an echo of correlations in the evolutionary record. Reverse engineering 3D structures from such correlations is an open problem in structural biology, pursued with increasing vigor as more and more protein sequences continue to fill the data banks. Within this task lies a statistical inference problem, rooted in the following: correlation between two sites in a protein sequence can arise from firsthand interaction but can also be network-propagated via intermediate sites; observed correlation is not enough to guarantee proximity. To separate direct from indirect interactions is an instance of the general problem of inverse statistical mechanics, where the task is to learn model parameters (fields, couplings) from observables (magnetizations, correlations, samples) in large systems. In the context of protein sequences, the approach has been referred to as direct-coupling analysis. Here we show that the pseudolikelihood method, applied to 21-state Potts models describing the statistical properties of families of evolutionarily related proteins, significantly outperforms existing approaches to the direct-coupling analysis, the latter being based on standard mean-field techniques. This improved performance also relies on a modified score for the coupling strength. The results are verified using known crystal structures of specific sequence instances of various protein families. Code implementing the new method can be found at http://plmdca.csc.kth.se/., 19 pages, 16 figures, published version

International audience; We generated a genome-wide replication profile in the genome of Lachancea kluyveri and assessed the relationship between replication and base composition. This species diverged from Saccharomyces cerevisiae before the ancestral whole genome duplication. The genome comprises eight chromosomes among which achromosomal arm of 1Mb has a G + C-content much higher than the rest of the genome. We identified 252 active replication origins in L. kluyveri and found considerable divergence in origin location with S. cerevisiae and with Lachancea waltii. Although some global features of S. cerevisiae replication are conserved: Centromeres replicate early, whereas telomeres replicate late, we found that replication origins both in L. kluyveri and L. waltii do not behave as evolutionary fragile sites. In L. kluyveri, replication timing along chromosomes alternates between regions of early and late activating origins, except for the 1Mb GC-rich chromosomal arm. This chromosomal arm contains an origin consensus motif different from other chromosomes and is replicated early during S-phase. We showed that precocious replication results from the specific absence of late firing origins in this chromosomal arm. In addition, we found a correlation between GC-content and distance from replication origins as well as a lack of replication-associated compositional skew between leading and lagging strands specifically in this GC-rich chromosomal arm. These findings suggest that the unusual base composition in the genome of L. kluyveri could be linked to replication.

17th International Conference on Image Analysis and Processing (ICIAP), Naples, ITALY, SEP 09-13, 2013; International audience; There is a growing interest in using efficient shape complementarity docking algorithms to analyze protein-protein interactions at a large scale. We have realized complete cross-docking of several tens of enzyme/inhibitors proteins. On the one hand, we demonstrate that docking score distributions for the known complexes are not distinguishable from those for the non-interacting pairs. On the other hand, we show that the knowledge of the experimental interfaces applied to the docking conformations permits to retrieve true interaction partners with high accuracy. We further identify the determinants of the molecular recognition between true interactors compared to non-interacting proteins.

International audience; Motile cilia are highly conserved structures in the evolution of organisms, generating the transport of fluid by periodic beating, through remarkably organized behavior in space and time. It is not known how these spatiotemporal patterns emerge and what sets their properties. Individual cilia are nonequilibrium systems with many degrees of freedom. However, their description can be represented by simpler effective force laws that drive oscillations, and paralleled with nonlinear phase oscillators studied in physics. Here a synthetic model of two phase oscillators, where colloidal particles are driven by optical traps, proves the role of the average force profile in establishing the type and strength of synchronization. We find that highly curved potentials are required for synchronization in the presence of noise. The applicability of this approach to biological data is also illustrated by successfully mapping the behavior of cilia in the alga Chlamydomonas onto the coarse-grained model.

Gene networks exhibiting oscillatory dynamics are widespread in biology. The minimal regulatory designs giving rise to oscillations have been implemented synthetically and studied by mathematical modeling. However, most of the available analyses generally neglect the coupling of regulatory circuits with the cellular "chassis" in which the circuits are embedded. For example, the intracellular macromolecular composition of fast-growing bacteria changes with growth rate. As a consequence, important parameters of gene expression, such as ribosome concentration or cell volume, are growth-rate dependent, ultimately coupling the dynamics of genetic circuits with cell physiology. This work addresses the effects of growth rate on the dynamics of a paradigmatic example of genetic oscillator, the repressilator. Making use of empirical growth-rate dependences of parameters in bacteria, we show that the repressilator dynamics can switch between oscillations and convergence to a fixed point depending on the cellular state of growth, and thus on the nutrients it is fed. The physical support of the circuit (type of plasmid or gene positions on the chromosome) also plays an important role in determining the oscillation stability and the growth-rate dependence of period and amplitude. This analysis has potential application in the field of synthetic biology, and suggests that the coupling between endogenous genetic oscillators and cell physiology can have substantial consequences for their functionality., 14 pages, 9 figures (revised version, accepted for publication)

Proteins participating in a protein-protein interaction network can be grouped into homology classes following their common ancestry. Proteins added to the network correspond to genes added to the classes, so that the dynamics of the two objects are intrinsically linked. Here, we first introduce a statistical model describing the joint growth of the network and the partitioning of nodes into classes, which is studied through a combined mean-field and simulation approach. We then employ this unified framework to address the specific issue of the age dependence of protein interactions, through the definition of three different node wiring/divergence schemes. Comparison with empirical data indicates that an age-dependent divergence move is necessary in order to reproduce the basic topological observables together with the age correlation between interacting nodes visible in empirical data. We also discuss the possibility of nontrivial joint partition/topology observables., 14 pages, 7 figures [accepted for publication in PRE]

Background Drug susceptible clinical isolates of Candida albicans frequently become highly tolerant to drugs during chemotherapy, with dreadful consequences to patient health. We used RNA sequencing (RNA-seq) to analyze the transcriptomes of a CDR (Candida Drug Resistance) strain and its isogenic drug sensitive counterpart. Results RNA-seq unveiled differential expression of 228 genes including a) genes previously identified as involved in CDR, b) genes not previously associated to the CDR phenotype, and c) novel transcripts whose function as a gene is uncharacterized. In particular, we show for the first time that CDR acquisition is correlated with an overexpression of the transcription factor encoding gene CZF1. CZF1 null mutants were susceptible to many drugs, independently of known multidrug resistance mechanisms. We show that CZF1 acts as a repressor of β-glucan synthesis, thus negatively regulating cell wall integrity. Finally, our RNA-seq data allowed us to identify a new transcribed region, upstream of the TAC1 gene, which encodes the major CDR transcriptional regulator. Conclusion Our results open new perspectives of the role of Czf1 and of our understanding of the transcriptional and post-transcriptional mechanisms that lead to the acquisition of drug resistance in C. albicans, with potential for future improvements of therapeutic strategies.

SVGMapping: an R package to map omic data sets onto pathways templates

Summary: Different experimental results suggest the presence of an interplay between global transcriptional regulation and chromosome spatial organization in bacteria. The identification and clear visualization of spatial clusters of contiguous genes targeted by specific DNA-binding proteins or sensitive to nucleoid perturbations can elucidate links between nucleoid structure and gene expression patterns. Similarly, statistical analysis to assess correlations between results from independent experiments can provide the integrated analysis needed in this line of research. NuST (Nucleoid Survey tools), based on the Escherichia coli genome, gives the non-expert the possibility to analyze the aggregation of genes or loci sets along the genome coordinate, at different scales of observation. It is useful to discover correlations between different sources of data (e.g. expression, binding or genomic data) and genome organization. A user can use it on datasets in the form of gene lists coming from his/her own experiments or bioinformatic analyses, but also make use of the internal database, which collects data from many published studies. Availability and Implementation: NuST is a web server (available at http://www.lgm.upmc.fr/nust/). The website is implemented in PHP, SQLite and Ajax, with all major browsers supported, while the core algorithms are optimized and implemented in C. NuST has an extensive help page and provides a direct visualization of results as well as different downloadable file formats. A template Perl code for automated access to the web server can be downloaded at http://www.lgm.upmc.fr/nust/downloads/, in order to allow the users to use NuST in systematic bioinformatic analyses. Contact: vittore.scolari@upmc.fr Supplementary information: Supplementary data are available at Bioinformatics online.

Detection of remote homologous proteins is essential for functional and structural classification of protein sequences and for the completion of the annotation for highly divergent genomes. Here, we present two new methods to address these problems. For the first prob- lem, we introduce ILP-SVM Homology that combines inductive logic programming (ILP) and propositional models. It proposes a novel logical representation of physico-chemical properties, conserved amino acid positions and conserved physico-chemical positions in sequence alignments. Based on these signals, ILP finds the most frequent patterns and uses them to train models, such as decision trees and support vector machines. ILP-SVM Homology achieves at least equal performance when compared with other methods. To address the second problem, we propose CASH, a large-scale pipeline to annotate highly divergent genomes. CASH was applied to the Plasmodium falciparum, but it is applicable to any species. In CASH we explore different evolutionary pathways including those that are phylogenetically distant from P. falciparum. As a result, each known domain is represented by an ensemble of heterogeneous models, and the outputs are combined through a meta-classifier that assigns a confidence score to each prediction. Based on this score and on properties as domain co-occurrence, CASH finds the most probable architecture for each query sequence by resolving a multi-objective optimization problem. CASH provides domain annotation for 70% of proteins in P. falciparum, while its competitors achieve at most 58%. We find additional domains into already annotated proteins, and predict domains for proteins with unknown function., La détection d'homologues lointains est essentielle pour le classement fonctionnel et structural des séquences protéiques et pour l'amélioration de l'annotation des génomes très divergents. Pour le classement des séquences, nous présentons la méthode "ILP-SVM homology", combinant la programmation logique inductive (PLI) et les modèles propositionnels. Elle propose une nouvelle représentation logique des propriétés physico-chimiques des résidus et des positions conservées au sein de l'alignement de séquences. Ainsi, PLI trouve les règles les plus fréquentes et les utilise pour la phase d'apprentissage utilisant des modèles d'arbre de décision ou de machine à vecteurs de support. La méthode présente au moins les mêmes performances que les autres méthodes trouvées dans la littérature. Puis, nous proposons la méthode CASH pour annoter les génomes très divergents. CASH a été appliqué à Plasmodium falciparum, mais reste applicable à toutes les espèces. CASH utilise aussi bien l'information issue de génomes proches ou éloignés de P. falciparum. Chaque domaine connu est ainsi représenté par un ensemble de modèles évolutifs, et les sorties sont combinées par un méta-classificateur qui assigne un score de confiance à chaque prédiction. Basé sur ce score et sur des propriétés de co-ocurrences de domaines, CASH trouve l'architecture la plus probable de chaque séquence en appliquant une approche d'optimisation multi-objectif. CASH est capable d'annoter 70% des domaines protéiques de P. falciparum, contre une moyenne de 58% pour ses concurrents. De nouveaux domaines protéiques ont pu être caractérisés au sein de protéines de fonction inconnue ou déjà annotées.

International audience; Steroids are known to induce pleiotropic drug resistance states in hemiascomycetes, with tremendous potential consequences on human fungal infections. The proteins capable of binding to steroids such as progesterone binding protein (PBP), estradiol binding proteins (ESP) are found in yeasts, however, the well known receptor mediated signaling present in higher eukaryotic cells is absent in yeasts and fungi. Steroids are perceived as stress by yeast cells which triggers general stress response leading to activation of heat shock proteins, cell cycle regulators, MDR transporters, etc. In this article, we review the response of yeast to human steroid hormones which affects its cell growth, morphology and virulence. We discuss that a fairly conserved response to steroids at the level of transcription and translation exists between pathogenic and non-pathogenic yeasts. Article from a special issue on steroids and microorganisms. (C) 2010 Elsevier Ltd. All rights reserved.

International audience; Light is an essential source of energy for life on Earth and is one of the most important signals that organisms use to obtain information from the surrounding environment, on land and in the oceans. Prominent marine microalgae, such as diatoms, display a suite of sophisticated responses (physiological, biochemical, and behavioural) to optimize their photosynthesis and growth under changing light conditions. However, the molecular mechanisms controlling diatom responses to light are still largely unknown. Recent progress in marine diatom genomics and genetics, combined with well-established (eco) physiological and biophysical approaches, now offers novel opportunities to address these issues. This review provides a description of the molecular components identified in diatom genomes that are involved in light perception and acclimation mechanisms. How the initial functional characterizations of specific light regulators provide the basis to investigate the conservation or diversification of light-mediated processes in diatoms is also discussed. Hypotheses on the role of the identified factors in determining the growth, distribution, and adaptation of diatoms in different marine environments are reported.

International audience; Despite the scrutiny that has been directed for years at the yeast genome, relatively little is known about the impact of replication on the substitution dynamics in Saccharomyces cerevisiae. Here, we show that the mutation rate increases with the replication timing by more than 30% between the earliest and the latest replicating regions. In addition, we found a mutational asymmetry associated with the polarity of replication resulting in higher rates of substitutions toward C and A than toward G and T in leading strands (reciprocally more substitutions toward G and T in lagging strands). Such mutational asymmetries applied over long evolutionary periods should generate compositional skews between the two DNA strands. Thus, we show that the leading replicating strands present an excess of C over G and of A over T in the genome of S. cerevisiae (reciprocally an excess of G + T over C + A in lagging strands). We also show that the nucleotide frequencies at mutational equilibrium predict a compositional skew at equilibrium very close to the observed skew between leading and lagging strands, suggesting that compositional equilibrium has been nearly attained in the present day genome of S. cerevisiae. Surprisingly, the direction of this skew is inverted compared with the one in the human genome.

Protein function often requires a protein to form a complex or adopt multiple conformations during its functional cycle. Many of these states are transient or unstable and their full structural characterization remains a daunting experimental task. Here, we demonstrate a multi-disciplinary approach that can predict such structures for the common prokaryotic protein class of two-component signal transduction systems (TCS). TCS enable cells to sense and react to external stimuli. A membrane bound sensor histidine kinase (SK) detects an environmental stimulus and forms a complex with a transcription factor/response regulator (RR) transferring a phosphoryl group to mediate a cellular response. The complex is ruled by transient interactions. Despite decades of experimental studies, only few experimental structures are available: none of them trapped during autophosphorylation and only recently was a complex structure of a SK/RR pair structurally resolved [1]. Concurrently, we predicted this complex structure in high agreement (3.5 RMSD) with the experimental work by combining molecular dynamics and statistical genomic analysis [2,3]. Based on this theoretical work, it is now possible to also predict the structural changes occurring during autophosphorylation. Direct coupling analysis [3] identifies innerprotein pairings formed between the HisKa and ATP-binding domains which are not realized in the (inactive) crystal structure. This information can be used in molecular dynamics simulations to identify an active conformation adopted during autophosphorylation in agreement with biochemical mutagenesis data [4].References[1] Casino P et al., Cell 139 (2009), 325-336[2] Schug A et al., Proc Nat Acad Sci USA (2009) 106, 22124-22129[3] Weigt M et al., Proc Nat Acad Sci USA (2009) 106, 67-72[4] Dago, AE et al., The Structural Basis of Histidine Kinase Autophosphorylation: Integrating Genomics, Molecular Dynamics and Mutagenesis (submitted).

A system of active colloidal particles driven by harmonic potentials to oscillate about the vertices of a regular polygon, with hydrodynamic coupling between all particles, is described by a piece-wise linear model which exhibits various patterns of synchronization. Analytical solutions are obtained for this class of dynamical systems. Depending only on the number of particles, the synchronization occurs into states in which nearest neighbors oscillate either in-phase, or anti-phase, or in phase-locked (time-shifted) trajectories., Comment: 12 pages

International audience; Gene expression plays a central role in the orchestration of cellular processes. The use of inducible promoters to change the expression level of a gene from its physiological level has significantly contributed to the understanding of the functioning of regulatory networks. However, from a quantitative point of view, their use is limited to short-term, population-scale studies to average out cell-to-cell variability and gene expression noise and limit the nonpredictable effects of internal feedback loops that may antagonize the inducer action. Here, we show that, by implementing an external feedback loop, one can tightly control the expression of a gene over many cell generations with quantitative accuracy. To reach this goal, we developed a platform for real-time, closed-loop control of gene expression in yeast that integrates microscopy for monitoring gene expression at the cell level, microfluidics to manipulate the cells' environment, and original software for automated imaging, quantification, and model predictive control. By using an endogenous osmostress responsive promoter and playing with the osmolarity of the cells environment, we show that long-term control can, indeed, be achieved for both time-constant and time-varying target profiles at the population and even the single-cell levels. Importantly, we provide evidence that real-time control can dynamically limit the effects of gene expression stochasticity. We anticipate that our method will be useful to quantitatively probe the dynamic properties of cellular processes and drive complex, synthetically engineered networks.

Recent experimental and theoretical approaches have attempted to quantify the physical organization (compaction and geometry) of the bacterial chromosome with its complement of proteins (the nucleoid). The genomic DNA exists in a complex and dynamic protein-rich state, which is highly organised at various length scales. This has implications on modulating (when not enabling) the core biological processes of replication, transcription, segregation. We overview the progress in this area, driven in the last few years by new scientific ideas and new interdisciplinary experimental techniques, ranging from high space- and time-resolution microscopy to high-throughput genomics employing sequencing to map different aspects of the nucleoid-related interactome. The aim of this review is to present the wide spectrum of experimental and theoretical findings coherently, from a physics viewpoint. We also discuss some attempts of interpretation that unify different results, highlighting the role that statistical and soft condensed matter physics, and in particular classic and more modern tools from the theory of polymers, plays in describing this system of fundamental biological importance, and pointing to possible directions for future investigation., Comment: 30 pages, accepted for publication in Reports on Progress in Physics

We studied synteny conservation between 18 yeast species and 13 vertebrate species in order to provide a comparative analysis of the chromosomal plasticity in these 2 phyla. By computing the regions of conserved synteny between all pairwise combinations of species within each group, we show that in vertebrates, the number of conserved synteny blocks exponentially increases along with the divergence between orthologous protein and that concomitantly; the number of genes per block exponentially decreases. The same trends are found in yeasts but only when the mean protein divergence between orthologs remains below 36%. When the average protein divergence exceeds this threshold, the total number of recognizable synteny blocks gradually decreases due to the repeated accumulation of rearrangements. We also show that rearrangement rates are on average 3-fold higher in vertebrates than in yeasts, and are estimated to be of 2 rearrangements/Myr. However, the genome sizes being on average 200 times larger in vertebrates than in yeasts, the normalized rates of chromosome rearrangements (per Mb) are about 50-fold higher in yeast than in vertebrate genomes.

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Colloidal particles moving in a fluid interact via the induced velocity field. The collective dynamic state for a class of actively forced colloids, driven by harmonic potentials via a rule that couples forces to configurations, to perform small oscillations around an average position, is shown by experiment, simulation and theoretical arguments to be determined by the eigenmode structure of the coupling matrix. It is remarkable that the dynamical state can therefore be predicted from the mean spatial configuration of the active colloids, or from an analysis of the fluctuations near equilibrium. This has the surprising consequence that while 2 particles, or polygonal arrays of 4 or more colloids, synchronize with the nearest neighbors in anti-phase, a system of 3 equally spaced colloids synchronizes in-phase. In the absence of thermal fluctuations, the stable dynamical state is predominantly formed by the eigenmode with longest relaxation time., Comment: completed reference to companion paper arXiv:1110.1524

Diatoms are prominent phytoplanktonic organisms that contribute around 40% of carbon assimilation in the oceans. They grow and perform optimally in variable environments, being able to cope with unpredictable changes in the amount and quality of light. The molecular mechanisms regulating diatom light responses are, however, still obscure. Using knockdown Phaeodactylum tricornutum transgenic lines, we reveal the key function of a member of the light-harvesting complex stress-related (LHCSR) protein family, denoted LHCX1, in modulation of excess light energy dissipation. In contrast to green algae, this gene is already maximally expressed in nonstressful light conditions and encodes a protein required for efficient light responses and growth. LHCX1 also influences natural variability in photoresponse, as evidenced in ecotypes isolated from different latitudes that display different LHCX1 protein levels. We conclude, therefore, that this gene plays a pivotal role in managing light responses in diatoms.

International audience; Cryptochromes (Crys) are blue light receptors believed to have evolved from the DNA photolyase protein family, implying that light control and light protection share a common ancient origin. In this paper, we report the identi- fication of five genes of the Cry/photolyase family (CPF) in two green algae of the Ostreococcus genus. Phylogenetic analyses were used to confidently assign three of these sequences to cyclobutane pyrimidine dimer (CPD) photolyases, one of them to a DASH-type Cry, and a third CPF gene has high homology with the recently described diatom CPF1 that displays a bifunctional activity. Both purified OtCPF1 and OtCPF2 proteins show non-covalent binding to flavin adenine dinucleotide (FAD), and additionally to 5,10-methenyl-tetrahydrofolate (MTHF) for OtCPF2. Expression analyses revealed that all five CPF members of Ostreococcus tauri are regulated by light. Furthermore, we show that OtCPF1 and OtCPF2 display photolyase activity and that OtCPF1 is able to interact with the CLOCK:BMAL heterodimer, transcription factors regulat- ing circadian clock function in other organisms. Finally, we provide evidence for the involvement of OtCPF1 in the maintenance of the Ostreococcus circadian clock. This work improves our understanding of the evolutionary transition between photolyases and Crys.

Background Biological networks are highly dynamic in response to environmental and physiological cues. This variability is in contrast to conventional analyses of biological networks, which have overwhelmingly employed static graph models which stay constant over time to describe biological systems and their underlying molecular interactions. Methods To overcome these limitations, we propose here a new statistical modelling framework, the ARTIVA formalism (Auto Regressive TIme VArying models), and an associated inferential procedure that allows us to learn temporally varying gene-regulation networks from biological time-course expression data. ARTIVA simultaneously infers the topology of a regulatory network and how it changes over time. It allows us to recover the chronology of regulatory associations for individual genes involved in a specific biological process (development, stress response, etc.). Results We demonstrate that the ARTIVA approach generates detailed insights into the function and dynamics of complex biological systems and exploits efficiently time-course data in systems biology. In particular, two biological scenarios are analyzed: the developmental stages of Drosophila melanogaster and the response of Saccharomyces cerevisiae to benomyl poisoning. Conclusions ARTIVA does recover essential temporal dependencies in biological systems from transcriptional data, and provide a natural starting point to learn and investigate their dynamics in greater detail.

Communication between distant sites often defines the biological role of a protein: amino acid long-range interactions are as important in binding specificity, allosteric regulation and conformational change as residues directly contacting the substrate. The maintaining of functional and structural coupling of long-range interacting residues requires coevolution of these residues. Networks of interaction between coevolved residues can be reconstructed, and from the networks, one can possibly derive insights into functional mechanisms for the protein family. We propose a combinatorial method for mapping conserved networks of amino acid interactions in a protein which is based on the analysis of a set of aligned sequences, the associated distance tree and the combinatorics of its subtrees. The degree of coevolution of all pairs of coevolved residues is identified numerically, and networks are reconstructed with a dedicated clustering algorithm. The method drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed. We apply the method to four protein families where we show an accurate detection of functional networks and the possibility to treat sets of protein sequences of variable divergence., Author Summary Fine analyses of families of protein sequences reveal the existence of networks of coevolved amino acids. These networks are clusters of residues often entering in physical contact one with the other, and they relate residues which are located far apart on the three dimensional structure. Coevolved residues often play a major biological role in the protein, and the nature of their interactions might be multiple, spanning among binding specificity, allosteric regulation and conformational change of the protein. By carefully tracing the way residues evolved within the phylogenetic tree of sequences of a protein family, the Maximal SubTree Method captures the transition along the time scale evolution of a conserved position to a coevolved position, and provides a numerical evaluation of the degree of coevolution of pairs of coevolved residues in a protein. This combinatorial approach drops the constraints on high sequence divergence limiting the range of applicability of the statistical approaches previously proposed, and it can be applied with high accuracy to families of protein sequences with variable divergence.