Nanoscale, Voltage-Driven Application of Bioactive Substances onto Cells with Organized Topography

With Scanning Ion Conductance Microscopy (SICM), a non-contact scanning probe technique, it is possible to obtain information about both the surface topography of live cells and to apply molecules onto specific nanoscale structures. The technique is therefore widely used to apply chemical compounds and to study the properties of molecules on the surface of various cell types. The heart muscle cells, the cardiomyocytes, possess a highly elaborate, unique surface topography including T-tubule openings leading into a cell internal system which exclusively har-bors many proteins necessary for the cells physiological function. Here we applied Isoproterenol into these surface openings by changing the applied voltage over the SICM nanopipette. To determine the grade of precision of our application we used finite element simulations to inves-tigate how the concentration profile varies over the cell surface. We first obtained topography scans of the cardiomyocytes using SICM and then determined the electrophoretic mobility of Isoproterenol in a high ion solution to be -7×10-9 m2/Vs. The simulations showed that the delivery to the T-tubule opening is highly confined to the underlying Z-groove and especially to the first T-tubule opening, where the concen-tration is approximately 6.5 times higher compared to on a flat surface under the same delivery settings. Delivery to the crest, instead of the T-tubule opening, resulted in a much lower concentration, emphasizing the importance of topography on agonist delivery. In conclusion SICM, unlike other techniques, can reliably deliver precise quantities of compounds to the T-tubules of cardiomyocyte

Comparing placentas from normal and abnormal pregnancies

This report describes work carried out at a Mathematics-in-Medicine Study Group. It is believed that placenta shape villous network characteristics are strongly linked to the placenta’s efficiency, and hence to pregnancy outcome. We were asked to consider mathematical ways to describe the shape and other characteristics of a placenta, as well as forming mathematical models for placenta development. In this report we propose a number of possible measure of placental shape, form, and efficiency, which can be computed from images already obtained. We also consider various models for the early development of placentas and the growth of the villous tree

Varied effects of algal symbionts on transcription factor NF-κB in a sea anemone and a coral: possible roles in symbiosis and thermotolerance

Many cnidarians, including the reef-building corals, undergo symbiotic mutualisms with photosynthetic dinoflagellate algae of the family Symbiodiniaceae. These partnerships are sensitive to temperature extremes, which cause symbiont loss and increased coral mortality. Previous studies have implicated host immunity and specifically immunity transcription factor NF-κB as having a role in the maintenance of the cnidarian-algal symbiosis. Here we have further investigated a possible role for NF-κB in establishment and loss of symbiosis in various strains of the anemone Exaiptasia (Aiptasia) and in the coral Pocillopora damicornis. Our results show that NF-κB expression is reduced in Aiptasia larvae and adults that host certain algae strains. Treatment of Aiptasia larvae with a known symbiosis-promoting cytokine, transforming growth factor β, also led to decreased NF-κB expression. We also show that aposymbiotic Aiptasia (with high NF-κB expression) have increased survival following infection with the pathogenic bacterium Serratia marcescens as compared to symbiotic Aiptasia (low NF-κB expression). Furthermore, a P. damicornis coral colony hosting Durusdinium spp. (formerly clade D) symbionts had higher basal NF-κB expression and decreased heat-induced bleaching as compared to two individuals hosting Cladocopium spp. (formerly clade C) symbionts. Lastly, genome-wide gene expression profiling and genomic promoter analysis identified putative NF-κB target genes that may be involved in thermal bleaching, symbiont maintenance, and/or immune protection in P. damicornis. Our results provide further support for the hypothesis that modulation of NF-κB and immunity plays a role in some, but perhaps not all, cnidarian-Symbiodiniaceae partnerships as well as in resistance to pathogens and bleaching.Accepted manuscrip

DNA-binding protein prediction using plant specific support vector machines:validation and application of a new genome annotation tool

There are currently 151 plants with draft genomes available but levels of functional annotation for putative protein products are low. Therefore, accurate computational predictions are essential to annotate genomes in the first instance, and to provide focus for the more costly and time consuming functional assays that follow. DNA-binding proteins are an important class of proteins that require annotation, but current computational methods are not applicable for genome wide predictions in plant species. Here, we explore the use of species and lineage specific models for the prediction of DNA-binding proteins in plants. We show that a species specific support vector machine model based on Arabidopsis sequence data is more accurate (accuracy 81%) than a generic model (74%), and based on this we develop a plant specific model for predicting DNA-binding proteins. We apply this model to the tomato proteome and demonstrate its ability to perform accurate high-throughput prediction of DNA-binding proteins. In doing so, we have annotated 36 currently uncharacterised proteins by assigning a putative DNA-binding function. Our model is publically available and we propose it be used in combination with existing tools to help increase annotation levels of DNA-binding proteins encoded in plant genomes

Survey of variation in human transcription factors reveals prevalent DNA binding changes

Published in final edited form as: Science. 2016 Mar 25; 351(6280): 1450–1454. Published online 2016 Mar 24. doi: 10.1126/science.aad2257Sequencing of exomes and genomes has revealed abundant genetic variation affecting the coding sequences of human transcription factors (TFs), but the consequences of such variation remain largely unexplored. We developed a computational, structure-based approach to evaluate TF variants for their impact on DNA binding activity and used universal protein-binding microarrays to assay sequence-specific DNA binding activity across 41 reference and 117 variant alleles found in individuals of diverse ancestries and families with Mendelian diseases. We found 77 variants in 28 genes that affect DNA binding affinity or specificity and identified thousands of rare alleles likely to alter the DNA binding activity of human sequence-specific TFs. Our results suggest that most individuals have unique repertoires of TF DNA binding activities, which may contribute to phenotypic variation.National Institutes of Health; NHGRI R01 HG003985; P50 HG004233; A*STAR National Science Scholarship; National Science Foundatio

The Maestro (Mro) Gene Is Dispensable for Normal Sexual Development and Fertility in Mice

The mammalian gonad arises as a bipotential primordium from which a testis or ovary develops depending on the chromosomal sex of the individual. We have previously used DNA microarrays to screen for novel genes controlling the developmental fate of the indifferent embryonic mouse gonad. Maestro (Mro), which encodes a HEAT-repeat protein, was originally identified as a gene exhibiting sexually dimorphic expression during mouse gonad development. Wholemount in situ hybridisation analysis revealed Mro to be expressed in the embryonic male gonad from approximately 11.5 days post coitum, prior to overt sexual differentiation. No significant expression was detected in female gonads at the same developmental stage. In order to address its physiological function, we have generated mice lacking Maestro using gene targeting. Male and female mice homozygous for a Mro null allele are viable and fertile. We examined gonad development in homozygous male embryos in detail and observed no differences when compared to wild-type controls. Immunohistochemical analysis of homozygous mutant testes of adult mice revealed no overt abnormalities. Expression profiling using DNA microarrays also indicated no significant differences between homozygote embryonic male gonads and controls. We conclude that Maestro is dispensable for normal male sexual development and fertility in laboratory mice; however, the Mro locus itself does have utility as a site for insertion of transgenes for future studies in the fields of sexual development and Sertoli cell function

From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein