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Building biological models by inferring functional dependencies from experimental data is an important issue in Molecular Biology. To relieve the biologist from this traditionally manual process, various approaches have been proposed to increase the degree of automation. However, available approaches often yield a single model only, rely on specific assumptions, and/or use dedicated, heuristic algorithms that are intolerant to changing circumstances or requirements in the view of the rapid progress made in Biotechnology. Our aim is to provide a declarative solution to the problem by appeal to Answer Set Programming (ASP) overcoming these difficulties. We build upon an existing approach to Automatic Network Reconstruction proposed by part of the authors. This approach has firm mathematical foundations and is well suited for ASP due to its combinatorial flavor providing a characterization of all models explaining a set of experiments. The usage of ASP has several benefits over the existing heuristic algorithms. First, it is declarative and thus transparent for biological experts. Second, it is elaboration tolerant and thus allows for an easy exploration and incorporation of biological constraints. Third, it allows for exploring the entire space of possible models. Finally, our approach offers an excellent performance, matching existing, special-purpose systems.
We present XMM-Newton and Chandra observations of the born-again planetary nebula A 30. These X-ray observations reveal a bright unresolved source at the position of the central star whose X-ray luminosity exceeds by far the model expectations for photospheric emission and for shocks within the stellar wind. We suggest that a “born-again hot bubble” may be responsible for this X-ray emission. Diffuse X-ray emission associated with the petal-like features and one of the H-poor knots seen in the optical is also found. The weakened emission of carbon lines in the spectrum of the diffuse emission can be interpreted as the dilution of stellar wind by mass-loading or as the detection of material ejected during a very late thermal pulse.
To understand the evolution and morphology of planetary nebulae, a detailed knowledge of their central stars is required. Central stars that exhibit emission lines in their spectra, indicating stellar mass-loss allow to study the evolution of planetary nebulae in action. Emission line central stars constitute about 10 % of all central stars. Half of them are practically hydrogen-free Wolf-Rayet type central stars of the carbon sequence, [WC], that show strong emission lines of carbon and oxygen in their spectra. In this contribution we address the weak emission-lines central stars (wels). These stars are poorly analyzed and their hydrogen content is mostly unknown. We obtained optical spectra, that include the important Balmer lines of hydrogen, for four weak emission line central stars. We present the results of our analysis, provide spectral classification and discuss possible explanations for their formation and evolution.
Background: Cysteine is a component in organic compounds including glutathione that have been implicated in the adaptation of plants to stresses. O-acetylserine (thiol) lyase (OAS-TL) catalyses the final step of cysteine biosynthesis. OAS-TL enzyme isoforms are localised in the cytoplasm, the plastids and mitochondria but the contribution of individual OAS-TL isoforms to plant sulphur metabolism has not yet been fully clarified.
Results: The seedling lethal phenotype of the Arabidopsis onset of leaf death3-1 (old3-1) mutant is due to a point mutation in the OAS-A1 gene, encoding the cytosolic OAS-TL. The mutation causes a single amino acid substitution from Gly(162) to Glu(162), abolishing old3-1 OAS-TL activity in vitro. The old3-1 mutation segregates as a monogenic semidominant trait when backcrossed to its wild type accession Landsberg erecta (Ler-0) and the Di-2 accession. Consistent with its semi-dominant behaviour, wild type Ler-0 plants transformed with the mutated old3-1 gene, displayed the early leaf death phenotype. However, the old3-1 mutation segregates in an 11: 4: 1 (wild type: semi-dominant: mutant) ratio when backcrossed to the Colombia-0 and Wassilewskija accessions. Thus, the early leaf death phenotype depends on two semi-dominant loci. The second locus that determines the old3-1 early leaf death phenotype is referred to as odd-ler (for old3 determinant in the Ler accession) and is located on chromosome 3. The early leaf death phenotype is temperature dependent and is associated with increased expression of defence-response and oxidative-stress marker genes. Independent of the presence of the odd-ler gene, OAS-A1 is involved in maintaining sulphur and thiol levels and is required for resistance against cadmium stress.
Conclusions: The cytosolic OAS-TL is involved in maintaining organic sulphur levels. The old3-1 mutation causes genome-dependent and independent phenotypes and uncovers a novel function for the mutated OAS-TL in cell death regulation.
Live cell flattening
(2010)
Eukaryotic cell flattening is valuable for improving microscopic observations, ranging from bright field (BF) to total internal reflection fluorescence (TIRF) microscopy. Fundamental processes, such as mitosis and in vivo actin polymerization, have been investigated using these techniques. Here, we review the well known agar overlayer protocol and the oil overlay method. In addition, we present more elaborate microfluidics-based techniques that provide us with a greater level of control. We demonstrate these techniques on the social amoebae Dictyostelium discoideum, comparing the advantages and disadvantages of each method.
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues.
Results: Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach. Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available.
Conclusions: The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in realistically noisy conditions and with moderate sample sizes.
Multi-color fluorescence imaging experiments of wave forming Dictyostelium cells have revealed that actin waves separate two domains of the cell cortex that differ in their actin structure and phosphoinositide composition. We propose a bistable model of actin dynamics to account for these experimental observation. The model is based on the simplifying assumption that the actin cytoskeleton is composed of two distinct network types, a dendritic and a bundled network. The two structurally different states that were observed in experiments correspond to the stable fixed points in the bistable regime of this model. Each fixed point is dominated by one of the two network types. The experimentally observed actin waves can be considered as trigger waves that propagate transitions between the two stable fixed points.
We present an approach that provides automatic or semi-automatic support for evolution and change management in heterogeneous legacy landscapes where (1) legacy heterogeneous, possibly distributed platforms are integrated in a service oriented fashion, (2) the coordination of functionality is provided at the service level, through orchestration, (3) compliance and correctness are provided through policies and business rules, (4) evolution and correctness-by-design are supported by the eXtreme Model Driven Development paradigm (XMDD) offered by the jABC (Margaria and Steffen in Annu. Rev. Commun. 57, 2004)—the model-driven service oriented development platform we use here for integration, design, evolution, and governance. The artifacts are here semantically enriched, so that automatic synthesis plugins can field the vision of Enterprise Physics: knowledge driven business process development for the end user.
We demonstrate this vision along a concrete case study that became over the past three years a benchmark for Semantic Web Service discovery and mediation. We enhance the Mediation Scenario of the Semantic Web Service Challenge along the 2 central evolution paradigms that occur in practice: (a) Platform migration: platform substitution of a legacy system by an ERP system and (b) Backend extension: extension of the legacy Customer Relationship Management (CRM) and Order Management System (OMS) backends via an additional ERP layer.
Background: Protein phosphorylation is an important post-translational modification influencing many aspects of dynamic cellular behavior. Site-specific phosphorylation of amino acid residues serine, threonine, and tyrosine can have profound effects on protein structure, activity, stability, and interaction with other biomolecules. Phosphorylation sites can be affected in diverse ways in members of any species, one such way is through single nucleotide polymorphisms (SNPs). The availability of large numbers of experimentally identified phosphorylation sites, and of natural variation datasets in Arabidopsis thaliana prompted us to analyze the effect of non-synonymous SNPs (nsSNPs) onto phosphorylation sites.
Results: From the analyses of 7,178 experimentally identified phosphorylation sites we found that: (i) Proteins with multiple phosphorylation sites occur more often than expected by chance. (ii) Phosphorylation hotspots show a preference to be located outside conserved domains. (iii) nsSNPs affected experimental phosphorylation sites as much as the corresponding non-phosphorylated amino acid residues. (iv) Losses of experimental phosphorylation sites by nsSNPs were identified in 86 A. thaliana proteins, among them receptor proteins were overrepresented.
These results were confirmed by similar analyses of predicted phosphorylation sites in A. thaliana. In addition, predicted threonine phosphorylation sites showed a significant enrichment of nsSNPs towards asparagines and a significant depletion of the synonymous substitution. Proteins in which predicted phosphorylation sites were affected by nsSNPs (loss and gain), were determined to be mainly receptor proteins, stress response proteins and proteins involved in nucleotide and protein binding. Proteins involved in metabolism, catalytic activity and biosynthesis were less affected.
Conclusions: We analyzed more than 7,100 experimentally identified phosphorylation sites in almost 4,300 protein-coding loci in silico, thus constituting the largest phosphoproteomics dataset for A. thaliana available to date. Our findings suggest a relatively high variability in the presence or absence of phosphorylation sites between different natural accessions in receptor and other proteins involved in signal transduction. Elucidating the effect of phosphorylation sites affected by nsSNPs on adaptive responses represents an exciting research goal for the future.
It has been suggested that coronal mass ejections (CMEs) remove the magnetic he-licity of their coronal source region from the Sun. Such removal is often regarded to be necessary due to the hemispheric sign preference of the helicity, which inhibits a simple annihilation by reconnection between volumes of opposite chirality. Here we monitor the relative magnetic he-licity contained in the coronal volume of a simulated flux rope CME, as well as the upward flux of relative helicity through horizontal planes in the simulation box. The unstable and erupting flux rope carries away only a minor part of the initial relative helicity; the major part remains in the volume. This is a consequence of the requirement that the current through an expanding loop must decrease if the magnetic energy of the configuration is to decrease as the loop rises, to provide the kinetic energy of the CME.
The Takab complex is composed of a variety of metamorphic rocks including amphibolites, metapelites, mafic granulites, migmatites and meta-ultramafics, which are intruded by the granitoid. The granitoid magmatic activity occurred in relation to the subduction of the Neo-Tethys oceanic crust beneath the Iranian crust during Tertiary times. The granitoids are mainly granodiorite, quartz monzodiorite, monzonite and quartz diorite. Chemically, the magmatic rocks are characterized by ASI < 1.04, AI < 0.87 and high contents of CaO (up to ∼ 14.5 wt %), which are consistent with the I-type magmatic series. Low FeO t /(FeO t +MgO) values (< 0.75) as well as low Nb, Y and K 2 O contents of the investigated rocks resemble the calc-alkaline series. Low SiO 2 , K 2 O/Na 2 O and Al 2 O 3 accompanied by high CaO and FeO contents indicate melting of metabasites as an appropriate source for the intrusions. Negative Ti and Nb anomalies verify a metaluminous crustal origin for the protoliths of the investigated igneous rocks. These are comparable with compositions of the associated mafic migmatites, in the Takab metamorphic complex, which originated from the partial melting of amphibolites. Therefore, crustal melting and a collision-related origin for the Takab calc-alkaline intrusions are proposed here on the basis of mineralogy and geochemical characteristics. The P–T evolution during magmatic crystallization and subsolidus cooling stages is determined by the study of mineral chemistry of the granodiorite and the quartz diorite. Magmatic crystallization pressure and temperature for the quartz-diorite and the granodiorite are estimated to be P ∼ 7.8 ± 2.5 kbar, T ∼ 760 ± 75 ◦C and P ∼ 5 ± 1 kbar, T ∼ 700 ◦C, respectively. Subsolidus conditions are consistent with temperatures of ∼ 620 ◦C and ∼ 600 ◦C, and pressures of ∼ 5 kbar and ∼ 3.5 kbar for the quartz-diorite and the granodiorite, respectively.
Background
Micrometer resolution placement and immobilization of probe molecules is an important step in the preparation of biochips and a wide range of lab-on-chip systems. Most known methods for such a deposition of several different substances are costly and only suitable for a limited number of probes. In this article we present a flexible procedure for simultaneous spatially controlled immobilization of functional biomolecules by molecular ink lithography.
Results
For the bottom-up fabrication of surface bound nanostructures a universal method is presented that allows the immobilization of different types of biomolecules with micrometer resolution. A supporting surface is biotinylated and streptavidin molecules are deposited with an AFM (atomic force microscope) tip at distinct positions. Subsequent incubation with a biotinylated molecule species leads to binding only at these positions. After washing streptavidin is deposited a second time with the same AFM tip and then a second biotinylated molecule species is coupled by incubation. This procedure can be repeated several times. Here we show how to immobilize different types of biomolecules in an arbitrary arrangement whereas most common methods can deposit only one type of molecules. The presented method works on transparent as well as on opaque substrates. The spatial resolution is better than 400 nm and is limited only by the AFM's positional accuracy after repeated z-cycles since all steps are performed in situ without moving the supporting surface. The principle is demonstrated by hybridization to different immobilized DNA oligomers and was validated by fluorescence microscopy.
Conclusions
The immobilization of different types of biomolecules in high-density microarrays is a challenging task for biotechnology. The method presented here not only allows for the deposition of DNA at submicrometer resolution but also for proteins and other molecules of biological relevance that can be coupled to biotin.
Two recent magnetic field models, GRIMM and xCHAOS, describe core field accelerations with similar behavior up to Spherical Harmonic (SH) degree 5, but which differ significantly for higher degrees. These discrepancies, due to different approaches in smoothing rapid time variations of the core field, have strong implications for the interpretation of the secular variation. Furthermore, the amount of smoothing applied to the highest SH degrees is essentially the modeler’s choice. We therefore investigate new ways of regularizing core magnetic field models. Here we propose to constrain field models to be consistent with the frozen flux induction equation by co-estimating a core magnetic field model and a flow model at the top of the outer core. The flow model is required to have smooth spatial and temporal behavior. The implementation of such constraints and their effects on a magnetic field model built from one year of CHAMP satellite and observatory data, are presented. In particular, it is shown that the chosen constraints are efficient and can be used to build reliable core magnetic field secular variation and acceleration model components.
Quantifying uncertainty, variability and likelihood for ordinary differential equation models
(2010)
Background
In many applications, ordinary differential equation (ODE) models are subject to uncertainty or variability in initial conditions and parameters. Both, uncertainty and variability can be quantified in terms of a probability density function on the state and parameter space.
Results
The partial differential equation that describes the evolution of this probability density function has a form that is particularly amenable to application of the well-known method of characteristics. The value of the density at some point in time is directly accessible by the solution of the original ODE extended by a single extra dimension (for the value of the density). This leads to simple methods for studying uncertainty, variability and likelihood, with significant advantages over more traditional Monte Carlo and related approaches especially when studying regions with low probability.
Conclusions
While such approaches based on the method of characteristics are common practice in other disciplines, their advantages for the study of biological systems have so far remained unrecognized. Several examples illustrate performance and accuracy of the approach and its limitations.
An efficient electrocatalytic biosensor for sulfite detection was developed by co-immobilizing sulfite oxidase and cytochrome c with polyaniline sulfonic acid in a layer-by-layer assembly. QCM, UV-Vis spectroscopy and cyclic voltammetry revealed increasing loading of electrochemically active protein with the formation of multilayers. The sensor operates reagentless at low working potential. A catalytic oxidation current was detected in the presence of sulfite at the modified gold electrode, polarized at +0.1 V ( vs. Ag/AgCl 1 M KCl). The stability of the biosensor performance was characterized and optimized. A 17-bilayer electrode has a linear range between 1 and 60 mu M sulfite with a sensitivity of 2.19 mA M-1 sulfite and a response time of 2 min. The electrode retained a stable response for 3 days with a serial reproducibility of 3.8% and lost 20% of sensitivity after 5 days of operation. It is possible to store the sensor in a dry state for more than 2 months. The multilayer electrode was used for determination of sulfite in unspiked and spiked samples of red and white wine. The recovery and the specificity of the signals were evaluated for each sample.
We present varve chronologies for sediments from two maar lakes in the Valle de Santiago region (Central Mexico): Hoya La Alberca (AD 1852-1973) and Hoya Rincn de Parangueo (AD 1839-1943). These are the first varve chronologies for Mexican lakes. The varved sections were anchored with tephras from Colima (1913) and Paricutin (1943/1944) and (210)Pb ages. We compare the sequences using the thickness of seasonal laminae and element counts (Al, Si, S, Cl, K, Ti, Mn, Fe, and Sr) determined by micro X-ray fluorescence spectrometry. The formation of the varve sublaminae is attributed to the strongly seasonal climate regime. Limited rainfall and high evaporation rates in winter and spring induce precipitation of carbonates (high Ca, Sr) enriched in (13)C and (18)O, whereas rainfall in summer increases organic and clastic input (plagioclase, quartz) with high counts of lithogenic elements (K, Al, Ti, and Si). Eolian input of Ti occurs also in the dry season. Moving correlations (5-yr windows) of the Ca and Ti counts show similar development in both sequences until the 1930s. Positive correlations indicate mixing of allochthonous Ti and autochthonous Ca, while negative correlations indicate their separation in sublaminae. Negative excursions in the correlations correspond with historic and reconstructed droughts, El Nio events, and positive SST anomalies. Based on our data, droughts (3-7 year duration) were severe and centred around the following years: the early 1850s, 1865, 1880, 1895, 1905, 1915 and the late 1920s with continuation into the 1930s. The latter dry period brought both lake systems into a critical state making them susceptible to further drying. Groundwater overexploitation due to the expansion of irrigation agriculture in the region after 1940 induced the transition from calcite to aragonite precipitation in Alberca and halite infiltration in Rincn. The proxy data indicate a faster response to increased evaporation for Rincn, the lake with the larger maar dimensions, solar radiation receipt and higher conductivity, whereas the smaller, steeper Alberca maar responded rapidly to increased precipitation.
Special p-forms are forms which have components fµ1…µp equal to +1, -1 or 0 in some orthonormal basis. A p-form ϕ ∈ pRd is called democratic if the set of nonzero components {ϕμ1...μp} is symmetric under the transitive action of a subgroup of O(d,Z) on the indices {1, . . . , d}. Knowledge of these symmetry groups allows us to define mappings of special democratic p-forms in d dimensions to special democratic P-forms in D dimensions for successively higher P = p and D = d. In particular, we display a remarkable nested structure of special forms including a U(3)-invariant 2-form in six dimensions, a G2-invariant 3-form in seven dimensions, a Spin(7)-invariant 4-form in eight dimensions and a special democratic 6-form O in ten dimensions. The latter has the remarkable property that its contraction with one of five distinct bivectors, yields, in the orthogonal eight dimensions, the Spin(7)-invariant 4-form. We discuss various properties of this ten dimensional form.
The satellite era brings new challenges in the development and the implementation of potential field models. Major aspects are, therefore, the exploitation of existing space- and ground-based gravity and magnetic data for the long-term. Moreover, a continuous and near real-time global monitoring of the Earth system, allows for a consistent integration and assimilation of these data into complex models of the Earth’s gravity and magnetic fields, which have to consider the constantly increasing amount of available data. In this paper we propose how to speed up the computation of the normal equation in potential filed modeling by using local multi-polar approximations of the modeling functions. The basic idea is to take advantage of the rather smooth behavior of the internal fields at the satellite altitude and to replace the full available gravity or magnetic data by a collection of local moments. We also investigate what are the optimal values for the free parameters of our method. Results from numerical experiments with spherical harmonic models based on both scalar gravity potential and magnetic vector data are presented and discussed. The new developed method clearly shows that very large datasets can be used in potential field modeling in a fast and more economic manner.
QuantPrime
(2008)
Background
Medium- to large-scale expression profiling using quantitative polymerase chain reaction (qPCR) assays are becoming increasingly important in genomics research. A major bottleneck in experiment preparation is the design of specific primer pairs, where researchers have to make several informed choices, often outside their area of expertise. Using currently available primer design tools, several interactive decisions have to be made, resulting in lengthy design processes with varying qualities of the assays.
Results
Here we present QuantPrime, an intuitive and user-friendly, fully automated tool for primer pair design in small- to large-scale qPCR analyses. QuantPrime can be used online through the internet http://www.quantprime.de/ or on a local computer after download; it offers design and specificity checking with highly customizable parameters and is ready to use with many publicly available transcriptomes of important higher eukaryotic model organisms and plant crops (currently 295 species in total), while benefiting from exon-intron border and alternative splice variant information in available genome annotations. Experimental results with the model plant Arabidopsis thaliana, the crop Hordeum vulgare and the model green alga Chlamydomonas reinhardtii show success rates of designed primer pairs exceeding 96%.
Conclusion
QuantPrime constitutes a flexible, fully automated web application for reliable primer design for use in larger qPCR experiments, as proven by experimental data. The flexible framework is also open for simple use in other quantification applications, such as hydrolyzation probe design for qPCR and oligonucleotide probe design for quantitative in situ hybridization. Future suggestions made by users can be easily implemented, thus allowing QuantPrime to be developed into a broad-range platform for the design of RNA expression assays.
Background: Haplotype inference based on unphased SNP markers is an important task in population genetics. Although there are different approaches to the inference of haplotypes in diploid species, the existing software is not suitable for inferring haplotypes from unphased SNP data in polyploid species, such as the cultivated potato (Solanum tuberosum). Potato species are tetraploid and highly heterozygous.
Results: Here we present the software SATlotyper which is able to handle polyploid and polyallelic data. SATlo-typer uses the Boolean satisfiability problem to formulate Haplotype Inference by Pure Parsimony. The software excludes existing haplotype inferences, thus allowing for calculation of alternative inferences. As it is not known which of the multiple haplotype inferences are best supported by the given unphased data set, we use a bootstrapping procedure that allows for scoring of alternative inferences. Finally, by means of the bootstrapping scores, it is possible to optimise the phased genotypes belonging to a given haplotype inference. The program is evaluated with simulated and experimental SNP data generated for heterozygous tetraploid populations of potato. We show that, instead of taking the first haplotype inference reported by the program, we can significantly improve the quality of the final result by applying additional methods that include scoring of the alternative haplotype inferences and genotype optimisation. For a sub-population of nineteen individuals, the predicted results computed by SATlotyper were directly compared with results obtained by experimental haplotype inference via sequencing of cloned amplicons. Prediction and experiment gave similar results regarding the inferred haplotypes and phased genotypes.
Conclusion: Our results suggest that Haplotype Inference by Pure Parsimony can be solved efficiently by the SAT approach, even for data sets of unphased SNP from heterozygous polyploids. SATlotyper is freeware and is distributed as a Java JAR file. The software can be downloaded from the webpage of the GABI Primary Database at http://www.gabipd.org/projects/satlotyper/. The application of SATlotyper will provide haplotype information, which can be used in haplotype association mapping studies of polyploid plants.