Browsing by Issue Date, starting with "2018-09-07"
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- In search of the Goldilocks zone for hybrid speciationPublication . Blanckaert, Alexandre; Bank, ClaudiaHybridization has recently gained considerable interest both as a unique opportunity for observing speciation mechanisms and as a potential engine for speciation. The latter remains a controversial topic. It was recently hypothesized that the reciprocal sorting of genetic incompatibilities from parental species could result in hybrid speciation, when the hybrid population maintains a mixed combination of the parental incompatibilities that prevents further gene exchange with both parental populations. However, the specifics of the purging/sorting process of multiple incompatibilities have not been examined theoretically. We here investigate the allele-frequency dynamics of an isolated hybrid population that results from a single hybridization event. Using models of two or four loci, we investigate the fate of one or two genetic incompatibilities of the Dobzhansky-Muller type (DMIs). We study how various parameters affect both the sorting/purging of the DMIs and the probability of observing hybrid speciation by reciprocal sorting. We find that the probability of hybrid speciation is strongly dependent on the linkage architecture (i.e. the order and recombination rate between loci along chromosomes), the population size of the hybrid population, and the initial relative contributions of the parental populations to the hybrid population. We identify a Goldilocks zone for specific linkage architectures and intermediate recombination rates, in which hybrid speciation becomes highly probable. Whereas an equal contribution of parental populations to the hybrid population maximizes the hybrid speciation probability in the Goldilocks zone, other linkage architectures yield unintuitive asymmetric maxima. We provide an explanation for this pattern, and discuss our results both with respect to the best conditions for observing hybrid speciation in nature and their implications regarding patterns of introgression in hybrid zones.
- Dipeptidyl Peptidase-4 Is a Pro-Recovery Mediator During Acute Hepatotoxic Damage and Mirrors Severe Shifts in Kupffer CellsPublication . Duarte, Nádia; Coelho, Inês; Holovanchuk, Denys; Inês Almeida, Joana; Penha-Gonçalves, Carlos; Paula Macedo, MariaDipeptidyl peptidase-4 (DPP-4 or clusters of differentiation [CD]26) is a multifunctional molecule with established roles in metabolism. Pharmacologic inhibition of DPP-4 is widely used to improve glycemic control through regulation of the incretin effect. Colaterally, CD26/DPP-4 inhibition appears to be beneficial in many inflammatory conditions, namely in delaying progression of liver pathology. Nevertheless, the exact implications of CD26/DPP-4 enzymatic activity in liver dysfunction remain unclear. In this work, we investigated the involvement of CD26/DPP-4 in experimental mouse models of induced hepatocyte damage that severely impact Kupffer cell (KC) populations. Liver dysfunction was evaluated in CD26 knockout (KO) and B6 wild-type mice during acute liver damage induced by acetaminophen, chronic liver damage induced by carbon tetrachloride, and KC-depleting treatment with clodronate-loaded liposomes. We found that necrosis resolution after hepatotoxic injury was delayed in CD26KO mice and in B6 mice treated with the CD26/DPP-4 inhibitor sitagliptin, suggesting that DPP-4 enzymatic activity plays a role in recovering from acute liver damage. Interestingly, the severe KC population reduction in acute and chronic liver injury was concomitant with increased CD26/DPP-4 serum levels. Remarkably, both chronic liver damage and noninflammatory depletion of KCs by clodronate liposomes were marked by oscillation in CD26/DPP-4 serum activity that mirrored the kinetics of liver KC depletion/recovery. Conclusion:CD26/DPP-4 enzymatic activity contributes to necrosis resolution during recovery from acute liver injury. Serum CD26/DPP-4 is elevated when severe perturbations are imposed on KC populations, regardless of patent liver damage. We propose that serum CD26/DPP-4 is a potential systemic surrogate marker of severe impairments in the KC population imposed by clinical and subclinical liver conditions.
- 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.