Cophylogeny Reconstruction Allowing for Multiple Associations Through Approximate Bayesian Computation.

Phylogenetic tree reconciliation is extensively employed for the examination of coevolution between host and symbiont species. An important concern is the requirement for dependable cost values when selecting event-based parsimonious reconciliation. Although certain approaches deduce event probabilities unique to each pair of host and symbiont trees, which can subsequently be converted into cost values, a significant limitation lies in their inability to model the invasion of diverse host species by the same symbiont species (termed as a spread event), which is believed to occur in symbiotic relationships. Invasions lead to the observation of multiple associations between symbionts and their hosts (indicating that a symbiont is no longer exclusive to a single host), which are incompatible with the existing methods of coevolution. Here, we present a method called AmoCoala (an enhanced version of the tool Coala) that provides a more realistic estimation of cophylogeny event probabilities for a given pair of host and symbiont trees, even in the presence of spread events. We expand the classical 4-event coevolutionary model to include 2 additional outcomes, vertical and horizontal spreads, that lead to multiple associations. In the initial step, we estimate the probabilities of spread events using heuristic frequencies. Subsequently, in the second step, we employ an approximate Bayesian computation approach to infer the probabilities of the remaining 4 classical events (cospeciation, duplication, host switch, and loss) based on these values. By incorporating spread events, our reconciliation model enables a more accurate consideration of multiple associations. This improvement enhances the precision of estimated cost sets, paving the way to a more reliable reconciliation of host and symbiont trees. To validate our method, we conducted experiments on synthetic datasets and demonstrated its efficacy using real-world examples. Our results showcase that AmoCoala produces biologically plausible reconciliation scenarios, further emphasizing its effectiveness.

Exploring the Robustness of the Parsimonious Reconciliation Method in Host-Symbiont Cophylogeny.

The aim of this paper is to explore the robustness of the parsimonious host-symbiont tree reconciliation method under editing or small perturbations of the input. The editing involves making different choices of unique symbiont mapping to a host in the case where multiple associations exist. This is made necessary by the fact that the tree reconciliation model is currently unable to handle such associations. The analysis performed could however also address the problem of errors. The perturbations are re-rootings of the symbiont tree to deal with a possibly wrong placement of the root specially in the case of fast-evolving species. In order to do this robustness analysis, we introduce a simulation scheme specifically designed for the host-symbiont cophylogeny context, as well as a measure to compare sets of tree reconciliations, both of which are of interest by themselves.

C60 fullerene promotes lung monolayer collapse.

Airborne nanometre-sized pollutants are responsible for various respiratory diseases. Such pollutants can reach the gas-exchange surface in the alveoli, which is lined with a monolayer of lung surfactant. The relationship between physiological effects of pollutants and molecular-level interactions is largely unknown. Here, we determine the effects of carbon nanoparticles on the properties of a model of lung monolayer using molecular simulations. We simulate phase-separated lipid monolayers in the presence of a model pollutant nanoparticle, C60 fullerene. In the absence of nanoparticles, the monolayers collapse only at very low surface tensions (around 0 mN m(-1)). In the presence of nanoparticles, instead, monolayer collapse is observed at significantly higher surface tensions (up to ca 10 mN m(-1)). Collapse at higher tensions is related to lower mechanical rigidity of the monolayer. It is possible that similar mechanisms operate on lung surfactant in vivo, which suggests that health effects of airborne carbon nanoparticles may be mediated by alterations of the mechanical properties of lung surfactant.