A Comparative Computer Simulation of Dendritic Morphology

Computational modeling of neuronal morphology is a powerful tool for understanding developmental processes and structure-function relationships. We present a multifaceted approach based on stochastic sampling of morphological measures from digital reconstructions of real cells. We examined how dendritic elongation, branching, and taper are controlled by three morphometric determinants: Branch Order, Radius, and Path Distance from the soma. Virtual dendrites were simulated starting from 3,715 neuronal trees reconstructed in 16 different laboratories, including morphological classes as diverse as spinal motoneurons and dentate granule cells. Several emergent morphometrics were used to compare real and virtual trees. Relating model parameters to Branch Order best constrained the number of terminations for most morphological classes, except pyramidal cell apical trees, which were better described by a dependence on Path Distance. In contrast, bifurcation asymmetry was best constrained by Radius for apical, but Path Distance for basal trees. All determinants showed similar performance in capturing total surface area, while surface area asymmetry was best determined by Path Distance. Grouping by other characteristics, such as size, asymmetry, arborizations, or animal species, showed smaller differences than observed between apical and basal, pointing to the biological importance of this separation. Hybrid models using combinations of the determinants confirmed these trends and allowed a detailed characterization of morphological relations. The differential findings between morphological groups suggest different underlying developmental mechanisms. By comparing the effects of several morphometric determinants on the simulation of different neuronal classes, this approach sheds light on possible growth mechanism variations responsible for the observed neuronal diversity

Genetically manipulated phages with improved pH resistance for oral administration in veterinary medicine

Orally administered phages to control zoonotic pathogens face important challenges, mainly related to the hostile conditions found in the gastrointestinal tract (GIT). These include temperature, salinity and primarily pH, which is exceptionally low in certain compartments. Phage survival under these conditions can be jeopardized and undermine treatment. Strategies like encapsulation have been attempted with relative success, but are typically complex and require several optimization steps. Here we report a simple and efficient alternative, consisting in the genetic engineering of phages to display lipids on their surfaces. Escherichia coli phage T7 was used as a model and the E. coli PhoE signal peptide was genetically fused to its major capsid protein (10A), enabling phospholipid attachment to the phage capsid. The presence of phospholipids on the mutant phages was confirmed by High Performance Thin Layer Chromatography, Dynamic Light Scattering and phospholipase assays. The stability of phages was analysed in simulated GIT conditions, demonstrating improved stability of the mutant phages with survival rates 102107 pfu.mL1 higher than wild-type phages. Our work demonstrates that phage engineering can be a good strategy to improve phage tolerance to GIT conditions, having promising application for oral administration in veterinary medicine.This work was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684) and under the scope of the Project PTDC/BBB-BSS/6471/2014 (POCI-01-0145-FEDER-016678). Franklin L. Nobrega and Ana Rita Costa acknowledge FCT for grants SFRH/BD/86462/2012 and SFRH/BPD/94648/2013, respectively. Melvin F. Siliakus acknowledges funding from the Biobased Ecologically Balanced Sustainable Industrial Chemistry (BE-BASIC) foundation. Electron microscopy work was performed at the Wageningen Electron Microscopy Centre (WEMC) of Wageningen University