Mimicking the in vivo Environment – The Effect of Crowding on RNA and Biomacromolecular Folding and Activity

In vitro studies on macromolecules, like proteins and nucleic acids, are mostly carried out in highly diluted systems where the molecules are studied under artificial conditions. These experimental conditions are optimized for both the system under investigation and the technique used. However, these conditions often do not reflect the in vivo situation and are therefore inappropriate for a reliable prediction of the native behavior of the molecules and their interactions under in vivo conditions. The intracellular environment is packed with cosolutes (macromolecules, metabolites, etc.) that create 'macromolecular crowding'. The addition of natural or synthetic macromolecules to the sample solution enables crowding to be mimicked. In this surrounding most of the studied biomolecules show a more compact structure, an increased activity, and a decrease of salt requirement for structure formation and function. Herein, we refer to a collection of examples for proteins and nucleic acids and their interactions in crowding environments and present in detail the effect of cosolutes on RNA folding and activity using a group II intron ribozyme as an example

Social inertia in collaboration networks

This work is a study of the properties of collaboration networks employing the formalism of weighted graphs to represent their one-mode projection. The weight of the edges is directly the number of times that a partnership has been repeated. This representation allows us to define the concept of "social inertia" that measures the tendency of authors to keep on collaborating with previous partners. We use a collection of empirical datasets to analyze several aspects of the social inertia: 1) its probability distribution, 2) its correlation with other properties, and 3) the correlations of the inertia between neighbors in the network. We also contrast these empirical results with the predictions of a recently proposed theoretical model for the growth of collaboration networks.Comment: 7 pages, 5 figure

Purification and Characterization of a Gamma-Like DNA-Polymerase From \u3ci\u3eChenopodium album\u3c/i\u3e L.

A DNA polymerase activity from mitochondria of the dicotyledonous angiosperm Chenopodium album L. was purified almost 9000 fold by successive column chromatography steps on DEAE cellulose, heparin agarose and ssDNA cellulose. The enzyme was characterized as a gamma-class polymerase, based on its resistance to inhibitors of the nuclear DNA polymerase alpha and its preference for poly(rA).(dT)12-18 over activated DNA in vitro. The molecular weight was estimated to be 80,000 - 90,000. A 3\u27 to 5\u27 exonuclease activity was found to be tightly associated with the DNA polymerase activity through all purification steps. This is the first report of an association between a DNA polymerase and an exonuclease activity in plant mitochondria

Complex Systems Science: Dreams of Universality, Reality of Interdisciplinarity

Using a large database (~ 215 000 records) of relevant articles, we empirically study the "complex systems" field and its claims to find universal principles applying to systems in general. The study of references shared by the papers allows us to obtain a global point of view on the structure of this highly interdisciplinary field. We show that its overall coherence does not arise from a universal theory but instead from computational techniques and fruitful adaptations of the idea of self-organization to specific systems. We also find that communication between different disciplines goes through specific "trading zones", ie sub-communities that create an interface around specific tools (a DNA microchip) or concepts (a network).Comment: Journal of the American Society for Information Science and Technology (2012) 10.1002/asi.2264

Mapping quantitative resistance to septoria tritici blotch in spelt wheat

The foliar wheat disease septoria tritici blotch can cause significant yield losses. A source of resistance has been mapped on chromosome 7D of spelt wheat, Triticum aestivum L. subsp. spelta (L.) Thell. The microsatellite-based genetic map was constructed from a set of 87 single-chromosome recombinant doubled-haploid lines bred from the cross between the landrace ‘Chinese Spring’ and a ‘Chinese Spring’-based line carrying chromosome 7D from spelt wheat. Two regions of the chromosome were associated with isolate-specific QTL expressed one at the seedling and another at the adult plant stage. The seedling resistance locus QStb.ipk-7D1 was found in the centromeric region of chromosome 7D, which corresponds to the location of the major resistance genes Stb4 originating from bread wheat cultivar ‘Tadinia’ and Stb5 originating from Triticum tauschii. The adult resistance locus QStb.ipk-7D2 was found on the short arm of chromosome 7D in a similar position to the locus Lr34/Yr18 known to be effective against multiple pathogens. Composite interval mapping confirmed QStb.ipk-7D1 and QStb.ipk-7D2 to be two distinct loci.Facultad de Ciencias Agrarias y Forestale

Stick, Flick, Click: DNA-guided Fluorescent Labeling of Long RNA for Single-molecule FRET

Exploring the spatiotemporal dynamics of biomolecules on a single-molecule level requires innovative ways to make them spectroscopically visible. Fluorescence resonance energy transfer (FRET) uses a pair of organic dyes as reporters to measure distances along a predefined biomolecular reaction coordinate. For this nanoscopic ruler to work, the fluorescent labels need to be coupled onto the molecule of interest in a bioorthogonal and site-selective manner. Tagging large non-coding RNAs with single-nucleotide precision is an open challenge. Here we summarize current strategies in labeling riboswitches and ribozymes for fluorescence spectroscopy and FRET in particular. A special focus lies on our recently developed, DNA-guided approach that inserts two fluorophores through a stepwise process of templated functionality transfer and click chemistry

Interfaces for science: Conceptualizing an interactive graphical interface

6,849.32 new research journal articles are published every day. The exponential growth of Scientific Knowledge Objects (SKOs) on the Web, makes searches time-consuming. Access to the right and relevant SKOs is vital for research, which calls for several topics, including the visualization of science dynamics. We present an interface model aimed to represent of the relations that emerge in the science social space dynamics, namely through the visualization and navigation of the relational structures between researchers, SKOs, knowledge domains, subdomains, and topics. This interface considers the relationship between the researcher who reads and shares the relevant articles and the researcher who wants to find the most relevant SKOs within a subject matter. This article presents the first iteration of the conceptualization process of the interface layout, its interactivity and visualization structures. It is essential to consider the hierarchical and relational structures/algorithms to represent the science social space dynamics. These structures are not being used as analysis tools, because it is not objective to show the linkage properties of these relationships. Instead, they are used as a means of representing, navigating and exploring these relationships. To sum up, this article provides a framework and fundamental guidelines for an interface layout that explores the social science space dynamics between the researcher who seeks relevant SKOs and the researchers who read and share them.This work has been supported by COMPETE: POCI-01-0145-FEDER- 007043 and FCT - Fundação para a Ciência e Tecnologia within the Project Scope: (UID/CEC/00319/2013) and the Project IViSSEM: ref: POCI-010145-FEDER-28284

Quantifying structure in networks

We investigate exponential families of random graph distributions as a framework for systematic quantification of structure in networks. In this paper we restrict ourselves to undirected unlabeled graphs. For these graphs, the counts of subgraphs with no more than k links are a sufficient statistics for the exponential families of graphs with interactions between at most k links. In this framework we investigate the dependencies between several observables commonly used to quantify structure in networks, such as the degree distribution, cluster and assortativity coefficients.Comment: 17 pages, 3 figure

Enhanced retinal image registration accuracy using expectation maximisation and variable bin-sized mutual information

While retinal images (RI) assist in the diagnosis of various eye conditions and diseases such as glaucoma and diabetic retinopathy, their innate features including low contrast homogeneous and nonuniformly illuminated regions, present a particular challenge for retinal image registration (RIR). Recently, the hybrid similarity measure, Expectation Maximization for Principal Component Analysis with Mutual Information (EMPCA-MI) has been proposed for RIR. This paper investigates incorporating various fixed and adaptive bin size selection strategies to estimate the probability distribution in the mutual information (MI) stage of EMPCA-MI, and analyses their corresponding effect upon RIR performance. Experimental results using a clinical mono-modal RI dataset confirms that adaptive bin size selection consistently provides both lower RIR errors and superior robustness compared to the empirically determined fixed bin sizes

FRET-guided modeling of nucleic acids

The functional diversity of RNAs is encoded in their innate conformational heterogeneity. The combination of single-molecule spectroscopy and computational modeling offers new attractive opportunities to map structural transitions within nucleic acid ensembles. Here, we describe a framework to harmonize single-molecule Förster resonance energy transfer (FRET) measurements with molecular dynamics simulations and de novo structure prediction. Using either all-atom or implicit fluorophore modeling, we recreate FRET experiments in silico, visualize the underlying structural dynamics and quantify the reaction coordinates. Using multiple accessible-contact volumes as a post hoc scoring method for fragment assembly in Rosetta, we demonstrate that FRET can be used to filter a de novo RNA structure prediction ensemble by refuting models that are not compatible with in vitro FRET measurement. We benchmark our FRET-assisted modeling approach on double-labeled DNA strands and validate it against an intrinsically dynamic manganese(II)-binding riboswitch. We show that a FRET coordinate describing the assembly of a four-way junction allows our pipeline to recapitulate the global fold of the riboswitch displayed by the crystal structure. We conclude that computational fluorescence spectroscopy facilitates the interpretability of dynamic structural ensembles and improves the mechanistic understanding of nucleic acid interactions