Phylogenetic analysis of the tenascin gene family: evidence of origin early in the chordate lineage

Background  

Tenascins are a family of glycoproteins found primarily in the extracellular matrix of embryos where they help to regulate cell proliferation, adhesion and migration. In order to learn more about their origins and relationships to each other, as well as to clarify the nomenclature used to describe them, the tenascin genes of the urochordate Ciona intestinalis, the pufferfish Tetraodon nigroviridis and Takifugu rubripes and the frog Xenopus tropicalis were identified and their gene organization and predicted protein products compared with the previously characterized tenascins of amniotes.     

Ant genomics sheds light on the molecular regulation of social organization

Ants are powerful model systems for the study of cooperation and sociality. In this review, we discuss how recent advances in ant genomics have contributed to our understanding of the evolution and organization of insect societies at the molecular level.     

INFLAM – INFLAMmation in Brain and Vessels with Iron Nanoparticles and Cell Trafficking: A Multiscale Approach of Tissue Microenvironment,Iron Nanostructure and Iron Biotransformation

Background

Inflammation is a share process in atherosclerosis and stroke and is thought to be a key player in the evolution of these diseases. Ten years ago, inflammation imaging with magnetic resonance imaging (MRI) was considered very promising for both pre-clinical and clinical studies of atherosclerosis and stroke.

Haplotyping cryptic Adélie penguin taxa using low-cost,high-resolution melt curves

Distinguishing morphologically cryptic taxa, by definition, requires genetic data such as DNA sequences. However, DNA sequences may not be obtained easily for taxa from remote sites. Here we provide the details of a high-resolution melt-curve-based method using taxon-specific primers that can distinguish two taxa of Adélie penguins, and that will be usable in Antarctica when combined with some of the newly developed field-deployable thermal cyclers. We suggest that the wider adoption of field-deployable polymerase-chain-reaction-based techniques will enable faster assignation of haplotype to individuals in situ, and so allow the targeting of observations and sample collection to specimens relevant to the research question. Targeting individuals will also reduce the need to repeatedly handle animals and reduce the time and travel required to complete field work.     

Attenuation of pattern recognition receptor signaling is mediated by a MAP kinase kinase kinase

Pattern recognition receptors (PRRs) play a key role in plant and animal innate immunity. PRR binding of their cognate ligand triggers a signaling network and activates an immune response. Activation of PRR signaling must be controlled prior to ligand binding to prevent spurious signaling and immune activation. Flagellin perception in Arabidopsis through FLAGELLIN‐SENSITIVE 2 (FLS2) induces the activation of mitogen‐activated protein kinases (MAPKs) and immunity. However, the precise molecular mechanism that connects activated FLS2 to downstream MAPK cascades remains unknown. Here, we report the identification of a differentially phosphorylated MAP kinase kinase kinase that also interacts with FLS2. Using targeted proteomics and functional analysis, we show that MKKK7 negatively regulates flagellin‐triggered signaling and basal immunity and this requires phosphorylation of MKKK7 on specific serine residues. MKKK7 attenuates MPK6 activity and defense gene expression. Moreover, MKKK7 suppresses the reactive oxygen species burst downstream of FLS2, suggesting that MKKK7‐mediated attenuation of FLS2 signaling occurs through direct modulation of the FLS2 complex.     

Structural sensitivity of biological models revisited

Enhancing the predictive power of models in biology is a challenging issue. Among the major difficulties impeding model development and implementation are the sensitivity of outcomes to variations in model parameters, the problem of choosing of particular expressions for the parametrization of functional relations, and difficulties in validating models using laboratory data and/or field observations. In this paper, we revisit the phenomenon which is referred to as structural sensitivity of a model. Structural sensitivity arises as a result of the interplay between sensitivity of model outcomes to variations in parameters and sensitivity to the choice of model functions, and this can be somewhat of a bottleneck in improving the models predictive power. We provide a rigorous definition of structural sensitivity and we show how we can quantify the degree of sensitivity of a model based on the Hausdorff distance concept. We propose a simple semi-analytical test of structural sensitivity in an ODE modeling framework. Furthermore, we emphasize the importance of directly linking the variability of field/experimental data and model predictions, and we demonstrate a way of assessing the robustness of modeling predictions with respect to data sampling variability. As an insightful illustrative example, we test our sensitivity analysis methods on a chemostat predator-prey model, where we use laboratory data on the feeding of protozoa to parameterize the predator functional response.