Quantitative Prediction of miRNA-mRNA Interaction Based on Equilibrium Concentrations

MicroRNAs (miRNAs) suppress gene expression by forming a duplex with a target messenger RNA (mRNA), blocking translation or initiating cleavage. Computational approaches have proven valuable for predicting which mRNAs can be targeted by a given miRNA, but currently available prediction methods do not address the extent of duplex formation under physiological conditions. Some miRNAs can at low concentrations bind to target mRNAs, whereas others are unlikely to bind within a physiologically relevant concentration range. Here we present a novel approach in which we find potential target sites on mRNA that minimize the calculated free energy of duplex formation, compute the free energy change involved in unfolding these sites, and use these energies to estimate the extent of duplex formation at specified initial concentrations of both species. We compare our predictions to experimentally confirmed miRNA-mRNA interactions (and non-interactions) in Drosophila melanogaster and in human. Although our method does not predict whether the targeted mRNA is degraded and/or its translation to protein inhibited, our quantitative estimates generally track experimentally supported results, indicating that this approach can be used to predict whether an interaction occurs at specified concentrations. Our approach offers a more-quantitative understanding of post-translational regulation in different cell types, tissues, and developmental conditions

Glial Processes at the Drosophila Larval Neuromuscular Junction Match Synaptic Growth

Glia are integral participants in synaptic physiology, remodeling and maturation from blowflies to humans, yet how glial structure is coordinated with synaptic growth is unknown. To investigate the dynamics of glial development at the Drosophila larval neuromuscular junction (NMJ), we developed a live imaging system to establish the relationship between glia, neuronal boutons, and the muscle subsynaptic reticulum. Using this system we observed processes from two classes of peripheral glia present at the NMJ. Processes from the subperineurial glia formed a blood-nerve barrier around the axon proximal to the first bouton. Processes from the perineurial glial extended beyond the end of the blood-nerve barrier into the NMJ where they contacted synapses and extended across non-synaptic muscle. Growth of the glial processes was coordinated with NMJ growth and synaptic activity. Increasing synaptic size through elevated temperature or the highwire mutation increased the extent of glial processes at the NMJ and conversely blocking synaptic activity and size decreased the presence and size of glial processes. We found that elevated temperature was required during embryogenesis in order to increase glial expansion at the nmj. Therefore, in our live imaging system, glial processes at the NMJ are likely indirectly regulated by synaptic changes to ensure the coordinated growth of all components of the tripartite larval NMJ

Phytotoxic Effects of (±)-Catechin In vitro, in Soil, and in the Field

BACKGROUND: Exploring the residence time of allelochemicals released by plants into different soils, episodic exposure of plants to allelochemicals, and the effects of allelochemicals in the field has the potential to improve our understanding of interactions among plants. METHODOLOGY/PRINCIPAL FINDINGS: We conducted experiments in India and the USA to understand the dynamics of soil concentrations and phytotoxicity of (+/-)-catechin, an allelopathic compound exuded from the roots of Centaurea maculosa, to other plants in vitro and in soil. Experiments with single and pulsed applications into soil were conducted in the field. Experimental application of (+/-)-catechin to soils always resulted in concentrations that were far lower than the amounts added but within the range of reported natural soil concentrations. Pulses replenished (+/-)-catechin levels in soils, but consistently at concentrations much lower than were applied, and even pulsed concentrations declined rapidly. Different natural soils varied substantially in the retention of (+/-)-catechin after application but consistent rapid decreases in concentrations over time suggested that applied experimental concentrations may overestimate concentrations necessary for phytotoxicity by over an order of magnitude. (+/-)-Catechin was not phytotoxic to Bambusa arundinacea in natural Indian soil in a single pulse, but soil concentrations at the time of planting seeds were either undetectable or very low. However, a single dose of (+/-)-catechin suppressed the growth of bamboo in sand, in soil mixed with organic matter, and Koeleria macrantha in soils from Montana and Romania, and in field applications at 40 microg l(-1). Multiple pulses of (+/-)-catechin were inhibitory at very low concentrations in Indian soil. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that (+/-)-catechin is highly dynamic in natural soils, but is phytotoxic well below natural concentrations measured in some soils and applied at low concentrations in the field. However, there is substantial conditionality in the effects of the allelochemical

Accurate Inference of Subtle Population Structure (and Other Genetic Discontinuities) Using Principal Coordinates

Accurate inference of genetic discontinuities between populations is an essential component of intraspecific biodiversity and evolution studies, as well as associative genetics. The most widely-used methods to infer population structure are model-based, Bayesian MCMC procedures that minimize Hardy-Weinberg and linkage disequilibrium within subpopulations. These methods are useful, but suffer from large computational requirements and a dependence on modeling assumptions that may not be met in real data sets. Here we describe the development of a new approach, PCO-MC, which couples principal coordinate analysis to a clustering procedure for the inference of population structure from multilocus genotype data.PCO-MC uses data from all principal coordinate axes simultaneously to calculate a multidimensional "density landscape", from which the number of subpopulations, and the membership within subpopulations, is determined using a valley-seeking algorithm. Using extensive simulations, we show that this approach outperforms a Bayesian MCMC procedure when many loci (e.g. 100) are sampled, but that the Bayesian procedure is marginally superior with few loci (e.g. 10). When presented with sufficient data, PCO-MC accurately delineated subpopulations with population F(st) values as low as 0.03 (G'(st)>0.2), whereas the limit of resolution of the Bayesian approach was F(st) = 0.05 (G'(st)>0.35).We draw a distinction between population structure inference for describing biodiversity as opposed to Type I error control in associative genetics. We suggest that discrete assignments, like those produced by PCO-MC, are appropriate for circumscribing units of biodiversity whereas expression of population structure as a continuous variable is more useful for case-control correction in structured association studies

Natural products in modern life science

With a realistic threat against biodiversity in rain forests and in the sea, a sustainable use of natural products is becoming more and more important. Basic research directed against different organisms in Nature could reveal unexpected insights into fundamental biological mechanisms but also new pharmaceutical or biotechnological possibilities of more immediate use. Many different strategies have been used prospecting the biodiversity of Earth in the search for novel structure–activity relationships, which has resulted in important discoveries in drug development. However, we believe that the development of multidisciplinary incentives will be necessary for a future successful exploration of Nature. With this aim, one way would be a modernization and renewal of a venerable proven interdisciplinary science, Pharmacognosy, which represents an integrated way of studying biological systems. This has been demonstrated based on an explanatory model where the different parts of the model are explained by our ongoing research. Anti-inflammatory natural products have been discovered based on ethnopharmacological observations, marine sponges in cold water have resulted in substances with ecological impact, combinatory strategy of ecology and chemistry has revealed new insights into the biodiversity of fungi, in depth studies of cyclic peptides (cyclotides) has created new possibilities for engineering of bioactive peptides, development of new strategies using phylogeny and chemography has resulted in new possibilities for navigating chemical and biological space, and using bioinformatic tools for understanding of lateral gene transfer could provide potential drug targets. A multidisciplinary subject like Pharmacognosy, one of several scientific disciplines bridging biology and chemistry with medicine, has a strategic position for studies of complex scientific questions based on observations in Nature. Furthermore, natural product research based on intriguing scientific questions in Nature can be of value to increase the attraction for young students in modern life science

Interaction for Immersive Analytics

International audienceIn this chapter, we briefly review the development of natural user interfaces and discuss their role in providing human-computer interaction that is immersive in various ways. Then we examine some opportunities for how these technologies might be used to better support data analysis tasks. Specifically, we review and suggest some interaction design guidelines for immersive analytics. We also review some hardware setups for data visualization that are already archetypal. Finally, we look at some emerging system designs that suggest future directions

Stage-Specific Changes in Plasmodium Metabolism Required for Differentiation and Adaptation to Different Host and Vector Environments

Malaria parasites (Plasmodium spp.) encounter markedly different (nutritional) environments during their complex life cycles in the mosquito and human hosts. Adaptation to these different host niches is associated with a dramatic rewiring of metabolism, from a highly glycolytic metabolism in the asexual blood stages to increased dependence on tricarboxylic acid (TCA) metabolism in mosquito stages. Here we have used stable isotope labelling, targeted metabolomics and reverse genetics to map stage-specific changes in Plasmodium berghei carbon metabolism and determine the functional significance of these changes on parasite survival in the blood and mosquito stages. We show that glutamine serves as the predominant input into TCA metabolism in both asexual and sexual blood stages and is important for complete male gametogenesis. Glutamine catabolism, as well as key reactions in intermediary metabolism and CoA synthesis are also essential for ookinete to oocyst transition in the mosquito. These data extend our knowledge of Plasmodium metabolism and point towards possible targets for transmission-blocking intervention strategies. Furthermore, they highlight significant metabolic differences between Plasmodium species which are not easily anticipated based on genomics or transcriptomics studies and underline the importance of integration of metabolomics data with other platforms in order to better inform drug discovery and design