Browsing by Author "Carneiro, Jorge"
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- Allelic penetrance approach as a tool to model twolocusPublication . Sepúlveda, Nuno; Paulino, Carlos Daniel; Carneiro, Jorge; Penha-Gonçalves, CarlosMany binary phenotypes do not follow a classical Mendelian inheritance pattern. Interaction between genetic and environmental factors is thought to contribute to the incomplete penetrance phenomena often observed in these complex binary traits. Several two-locus models for penetrance have been proposed to aid the genetic dissection of binary traits. Such models assume linear genetic effects of both loci in different mathematical scales of penetrance, resembling the analytical framework of quantitative traits. However, changes in phenotypic scale are difficult to envisage in binary traits and limited genetic interpretation is extractable from current modeling of penetrance. To overcome this limitation, we derived an allelic penetrance approach that partitioned incomplete penetrance into the alleles controlling the phenotype and into the genetic background and environmental factors. We applied this approach to formulate dominance and recessiveness in a single biallelic locus and to model different genetic mechanisms for the joint action of two biallelic loci. We fit the models to data on the susceptibility of mice following infections with Listeria monocytogenes and Plasmodium berghei. These models gain in genetic interpretation, because they specify the alleles that are responsible for the genetic (inter)action and their genetic nature (dominant or recessive), and predict genotypic combinations determining the phenotype. Further, we show via computer simulations that the proposed models produce penetrance patterns not captured by traditional twolocus models. This approach provides a new analysis framework for dissecting mechanisms of interlocus joint action in binary traits using genetic crosses.
- Diversity and plasticity of Th cell types predicted from regulatory network modellingPublication . Naldi, Aurélien; Carneiro, Jorge; Chaouiya, Claudine; Thieffry, DenisAlternative cell differentiation pathways are believed to arise from the concerted action of signalling pathways and transcriptional regulatory networks. However, the prediction of mammalian cell differentiation from the knowledge of the presence of specific signals and transcriptional factors is still a daunting challenge. In this respect, the vertebrate hematopoietic system, with its many branching differentiation pathways and cell types, is a compelling case study. In this paper, we propose an integrated, comprehensive model of the regulatory network and signalling pathways controlling Th cell differentiation. As most available data are qualitative, we rely on a logical formalism to perform extensive dynamical analyses. To cope with the size and complexity of the resulting network, we use an original model reduction approach together with a stable state identification algorithm. To assess the effects of heterogeneous environments on Th cell differentiation, we have performed a systematic series of simulations considering various prototypic environments. Consequently, we have identified stable states corresponding to canonical Th1, Th2, Th17 and Treg subtypes, but these were found to coexist with other transient hybrid cell types that co-express combinations of Th1, Th2, Treg and Th17 markers in an environment-dependent fashion. In the process, our logical analysis highlights the nature of these cell types and their relationships with canonical Th subtypes. Finally, our logical model can be used to explore novel differentiation pathways in silico.
- Estimating Attractor Reachability in Asynchronous Logical ModelsPublication . Mendes, Nuno D.; Henriques, Rui; Remy, Elisabeth; Carneiro, Jorge; Monteiro, Pedro T.; Chaouiya, ClaudineLogical models are well-suited to capture salient dynamical properties of regulatory networks. For networks controlling cell fate decisions, cell fates are associated with model attractors (stable states or cyclic attractors) whose identification and reachability properties are particularly relevant. While synchronous updates assume unlikely instantaneous or identical rates associated with component changes, the consideration of asynchronous updates is more realistic but, for large models, may hinder the analysis of the resulting non-deterministic concurrent dynamics. This complexity hampers the study of asymptotical behaviors, and most existing approaches suffer from efficiency bottlenecks, being generally unable to handle cyclical attractors and quantify attractor reachability. Here, we propose two algorithms providing probability estimates of attractor reachability in asynchronous dynamics. The first algorithm, named Firefront, exhaustively explores the state space from an initial state, and provides quasi-exact evaluations of the reachability probabilities of model attractors. The algorithm progresses in breadth, propagating the probabilities of each encountered state to its successors. Second, Avatar is an adapted Monte Carlo approach, better suited for models with large and intertwined transient and terminal cycles. Avatar iteratively explores the state space by randomly selecting trajectories and by using these random walks to estimate the likelihood of reaching an attractor. Unlike Monte Carlo simulations, Avatar is equipped to avoid getting trapped in transient cycles and to identify cyclic attractors. Firefront and Avatar are validated and compared to related methods, using as test cases logical models of synthetic and biological networks. Both algorithms are implemented as new functionalities of GINsim 3.0, a well-established software tool for logical modeling, providing executable GUI, Java API, and scripting facilities.
- A first-takes-all model of centriole copy number control based on cartwheel elongationPublication . Dias Louro, Marco António; Bettencourt-Dias, Mónica; Carneiro, Jorge
- Niflumic acid disrupts marine spermatozoan chemotaxis without impairing the spatiotemporal detection of chemoattractant gradientsPublication . Guerrero, Adán; Espinal, Jesús; Wood, Christopher D; Rendón, Juan M; Carneiro, Jorge; Martínez-Mekler, Gustavo; Darszon, AlbertoIn many broadcast-spawning marine organisms, oocytes release chemicals that guide conspecific spermatozoa towards them through chemotaxis. In the sea urchin Lytechinus pictus, the chemoattractant peptide speract triggers a train of fluctuations of intracellular Ca(2+) concentration in the sperm flagella. Each transient Ca(2+) elevation leads to a momentary increase in flagellar bending asymmetry, known as a chemotactic turn. Furthermore, chemotaxis requires a precise spatiotemporal coordination between the Ca(2+)-dependent turns and the form of chemoattractant gradient. Spermatozoa that perform Ca(2+)-dependent turns while swimming down the chemoattractant gradient, and conversely suppress turning events while swimming up the gradient, successfully approach the center of the gradient. Previous experiments in Strongylocentrotus purpuratus sea urchin spermatozoa showed that niflumic acid (NFA), an inhibitor of several ion channels, drastically altered the speract-induced Ca(2+) fluctuations and swimming patterns. In this study, mathematical modeling of the speract-dependent Ca(2+) signaling pathway suggests that NFA, by potentially affecting hyperpolarization-activated and cyclic nucleotide-gated channels, Ca(2+)-regulated Cl(-) channels and/or Ca(2+)-regulated K(+) channels, may alter the temporal organization of Ca(2+) fluctuations, and therefore disrupt chemotaxis. We used a novel automated method for analyzing sperm behavior and we identified that NFA does indeed disrupt chemotactic responses of L. pictus spermatozoa, although the temporal coordination between the Ca(2+)-dependent turns and the form of chemoattractant gradient is unaltered. Instead, NFA disrupts sperm chemotaxis by altering the arc length traveled during each chemotactic turning event. This alteration in the chemotactic turn trajectory disorientates spermatozoa at the termination of the turning event. We conclude that NFA disrupts chemotaxis without affecting how the spermatozoa decode environmental cues.
- A Novel Quantitative Fluorescent Reporter Assay for RAG Targets and RAG ActivityPublication . Trancoso, Inês; Bonnet, Marie; Gardner, Rui; Carneiro, Jorge; Barreto, Vasco M.; Demengeot, Jocelyne; Sarmento, Leonor M.Recombination-Activating Genes (RAG) 1 and 2 form the site specific recombinase that mediates V(D)J recombination, a process of DNA editing required for lymphocyte development and responsible for their diverse repertoire of antigen receptors. Mistargeted RAG activity associates with genome alteration and is responsible for various lymphoid tumors. Moreover several non-lymphoid tumors express RAG ectopically. A practical and powerful tool to perform quantitative assessment of RAG activity and to score putative RAG-Recognition signal sequences (RSS) is required in the fields of immunology, oncology, gene therapy, and development. Here we report the detailed characterization of a novel fluorescence-based reporter of RAG activity, named GFPi, a tool that allows measuring recombination efficiency (RE) by simple flow cytometry analysis. GFPi can be produced both as a plasmid for transient transfection experiments in cell lines or as a retrovirus for stable integration in the genome, thus supporting ex vivo and in vivo studies. The GFPi assay faithfully quantified endogenous and ectopic RAG activity as tested in genetically modified fibroblasts, tumor derived cell lines, developing pre-B cells, and hematopoietic cells. The GFPi assay also successfully ranked the RE of various RSS pairs, including bona fide RSS associated with V(D)J segments, artificial consensus sequences modified or not at specific nucleotides known to affect their efficiencies, or cryptic RSS involved in RAG-dependent activation of oncogenes. Our work validates the GFPi reporter as a practical quantitative tool for the study of RAG activity and RSS efficiencies. It should turn useful for the study of RAG-mediated V(D)J and aberrant rearrangements, lineage commitment, and vertebrate evolution.
- PLK4 trans-Autoactivation Controls Centriole Biogenesis in SpacePublication . Lopes, Carla A.M.; Jana, Swadhin Chandra; Cunha-Ferreira, Inês; Zitouni, Sihem; Bento, Inês; Duarte, Paulo; Gilberto, Samuel; Freixo, Francisco; Guerrero, Adán; Francia, Maria; Lince-Faria, Mariana; Carneiro, Jorge; Bettencourt-Dias, MónicaCentrioles are essential for cilia and centrosome assembly. In centriole-containing cells, centrioles always form juxtaposed to pre-existing ones, motivating a century-old debate on centriole biogenesis control. Here, we show that trans-autoactivation of Polo-like kinase 4 (PLK4), the trigger of centriole biogenesis, is a critical event in the spatial control of that process. We demonstrate that centrioles promote PLK4 activation through its recruitment and local accumulation. Though centriole removal reduces the proportion of active PLK4, this is rescued by concentrating PLK4 to the peroxisome lumen. Moreover, while mild overexpression of PLK4 only triggers centriole amplification at the existing centriole, higher PLK4 levels trigger both centriolar and cytoplasmatic (de novo) biogenesis. Hence, centrioles promote their assembly locally and disfavor de novo synthesis. Similar mechanisms enforcing the local concentration and/or activity of other centriole components are likely to contribute to the spatial control of centriole biogenesis under physiological conditions.
- Quantifying the Length and Variance of the Eukaryotic Cell Cycle Phases by a Stochastic Model and Dual Nucleoside Pulse LabellingPublication . Weber, Tom Serge; Jaehnert, Irene; Schichor, Christian; Or-Guil, Michal; Carneiro, JorgeA fundamental property of cell populations is their growth rate as well as the time needed for cell division and its variance. The eukaryotic cell cycle progresses in an ordered sequence through the phases G1, S, G2, and M, and is regulated by environmental cues and by intracellular checkpoints. Reflecting this regulatory complexity, the length of each phase varies considerably in different kinds of cells but also among genetically and morphologically indistinguishable cells. This article addresses the question of how to describe and quantify the mean and variance of the cell cycle phase lengths. A phase-resolved cell cycle model is introduced assuming that phase completion times are distributed as delayed exponential functions, capturing the observations that each realization of a cycle phase is variable in length and requires a minimal time. In this model, the total cell cycle length is distributed as a delayed hypoexponential function that closely reproduces empirical distributions. Analytic solutions are derived for the proportions of cells in each cycle phase in a population growing under balanced growth and under specific non-stationary conditions. These solutions are then adapted to describe conventional cell cycle kinetic assays based on pulse labelling with nucleoside analogs. The model fits well to data obtained with two distinct proliferating cell lines labelled with a single bromodeoxiuridine pulse. However, whereas mean lengths are precisely estimated for all phases, the respective variances remain uncertain. To overcome this limitation, a redesigned experimental protocol is derived and validated in silico. The novelty is the timing of two consecutive pulses with distinct nucleosides that enables accurate and precise estimation of both the mean and the variance of the length of all phases. The proposed methodology to quantify the phase length distributions gives results potentially equivalent to those obtained with modern phase-specific biosensor-based fluorescent imaging.
- To err is robotic, to tolerate immunological: fault detection in multirobot systemsPublication . Tarapore, Danesh; Lima, Pedro U; Carneiro, Jorge; Christensen, Anders LyhneFault detection and fault tolerance represent two of the most important and largely unsolved issues in the field of multirobot systems (MRS). Efficient, long-term operation requires an accurate, timely detection, and accommodation of abnormally behaving robots. Most existing approaches to fault-tolerance prescribe a characterization of normal robot behaviours, and train a model to recognize these behaviours. Behaviours unrecognized by the model are consequently labelled abnormal or faulty. MRS employing these models do not transition well to scenarios involving temporal variations in behaviour (e.g., online learning of new behaviours, or in response to environment perturbations). The vertebrate immune system is a complex distributed system capable of learning to tolerate the organism's tissues even when they change during puberty or metamorphosis, and to mount specific responses to invading pathogens, all without the need of a genetically hardwired characterization of normality. We present a generic abnormality detection approach based on a model of the adaptive immune system, and evaluate the approach in a swarm of robots. Our results reveal the robust detection of abnormal robots simulating common electro-mechanical and software faults, irrespective of temporal changes in swarm behaviour. Abnormality detection is shown to be scalable in terms of the number of robots in the swarm, and in terms of the size of the behaviour classification space.