Phototropin mediated ultraviolet-B phototropism in etiolated seedlings

Low doses of ultraviolet B (UV-B) light have significant effects on plant morphology [1]. In Arabidopsis, many UV-B induced morphological modifications have been ascribed to the UV-B specific receptor UV resistance locus 8 (UVR8). Recent findings in etiolated Arabidopsis seedlings indicate that UVR8 regulated signaling can induce phototropin independent directional bending towards UV-B light [2]. Here, we study the relative contribution of each of these pathways in UV-B regulated phototropism through kinetic analysis of seedlings. The role of phototropins is favored under reduced light conditions and the higher UVR8 response in the UV-B hypersensitive rup1rup2 mutants is interfering with the fast phototropin-regulated phototropic response. Our data suggest that phototropins are the primary receptors for UV-B induced phototropism in etiolated Arabidopsis seedlings, and the RUP-mediated negative feedback pathway prevents UVR8-mediated signaling to affect the phototropin-dependent response. In conclusion, phototropins are the most important receptors for UV-B induced phototropism in etiolated seedlings, and a RUP-mediated negative feedback pathway prevents UVR8 signaling to interfere with the phototropin dependent response

The origin of biased sequence depth in sequence-independent nucleic acid amplification and optimization for efficient massive parallel sequencing

Sequence Independent Single Primer Amplification is one of the most widely used random amplification approaches in virology for sequencing template preparation. This technique relies on oligonucleotides consisting of a 39 random part used to prime complementary DNA synthesis and a 59 defined tag sequence for subsequent amplification. Recently, this amplification method was combined with next generation sequencing to obtain viral sequences. However, these studies showed a biased distribution of the resulting sequence reads over the analyzed genomes. The aim of this study was to elucidate the mechanisms that lead to biased sequence depth when using random amplification. Avian paramyxovirus type 8 was used as a model RNA virus to investigate these mechanisms. We showed, based on in silico analysis of the sequence depth in relation to GC-content, predicted RNA secondary structure and sequence complementarity to the 39 part of the tag sequence, that the tag sequence has the main contribution to the observed bias in sequence depth. We confirmed this finding experimentally using both fragmented and non-fragmented viral RNAs as well as primers differing in random oligomer length (6 or 12 nucleotides) and in the sequence of the amplification tag. The observed oligonucleotide annealing bias can be reduced by extending the random oligomer sequence and by in silico combining sequence data from SISPA experiments using different 59 defined tag sequences. These findings contribute to the optimization of random nucleic acid amplification protocols that are currently required for downstream applications such as viral metagenomics and microarray analysis

DNase SISPA-next generation sequencing confirms Schmallenberg virus in Belgian field samples and identifies genetic variation in Europe

In 2011, a novel Orthobunyavirus was identified in cattle and sheep in Germany and the Netherlands. This virus was named Schmallenberg virus (SBV). Later, presence of the virus was confirmed using real time RT-PCR in cases of congenital malformations of bovines and ovines in several European countries, including Belgium. In the absence of specific sequencing protocols for this novel virus we confirmed its presence in RT-qPCR positive field samples using DNase SISPA-next generation sequencing (NGS), a virus discovery method based on random amplification and next generation sequencing. An in vitro transcribed RNA was used to construct a standard curve allowing the quantification of viral RNA in the field samples. Two field samples of aborted lambs containing 7.66 and 7.64 log(10) RNA copies per mu L total RNA allowed unambiguous identification of SBV. One sample yielded 192 SBV reads covering about 81% of the L segment, 56% of the M segment and 13% of the S segment. The other sample resulted in 8 reads distributed over the L and M segments. Three weak positive field samples (one from an aborted calf, two from aborted lambs) containing virus quantities equivalent to 4.27-4.89 log(10) RNA copies per mu L did not allow identification using DNase SISPA-NGS. This partial sequence information was compared to the whole genome sequence of SBV isolated from bovines in Germany, identifying several sequence differences. The applied viral discovery method allowed the confirmation of SBV in RT-qPCR positive brain samples. However, the failure to confirm SBV in weak PCR-positive samples illustrates the importance of the selection of properly targeted and fresh field samples in any virus discovery method. The partial sequences derived from the field samples showed several differences compared to the sequences from bovines in Germany, indicating sequence divergence within the epidemic

Protocol of the SOMNIA project : an observational study to create a neurophysiological database for advanced clinical sleep monitoring

Introduction Polysomnography (PSG) is the primary tool for sleep monitoring and the diagnosis of sleep disorders. Recent advances in signal analysis make it possible to reveal more information from this rich data source. Furthermore, many innovative sleep monitoring techniques are being developed that are less obtrusive, easier to use over long time periods and in the home situation. Here, we describe the methods of the Sleep and Obstructive Sleep Apnoea Monitoring with Non-Invasive Applications (SOMNIA) project, yielding a database combining clinical PSG with advanced unobtrusive sleep monitoring modalities in a large cohort of patients with various sleep disorders. The SOMNIA database will facilitate the validation and assessment of the diagnostic value of the new techniques, as well as the development of additional indices and biomarkers derived from new and/or traditional sleep monitoring methods. Methods and analysis We aim to include at least 2100 subjects (both adults and children) with a variety of sleep disorders who undergo a PSG as part of standard clinical care in a dedicated sleep centre. Full-video PSG will be performed according to the standards of the American Academy of Sleep Medicine. Each recording will be supplemented with one or more new monitoring systems, including wrist-worn photoplethysmography and actigraphy, pressure sensing mattresses, multimicrophone recording of respiratory sounds including snoring, suprasternal pressure monitoring and multielectrode electromyography of the diaphragm

REPRESSOR OF ULTRAVIOLET-B PHOTOMORPHOGENESIS function allows efficient phototropin mediated ultraviolet-B phototropism in etiolated seedlings.

Ultraviolet B (UV-B) light is a part of the solar radiation which has significant effects on plant morphology, even at low doses. In Arabidopsis, many of these morphological changes have been attributed to a specific UV-B receptor, UV resistance locus 8 (UVR8). Recent findings showed that next to phototropin regulated phototropism, UVR8 mediated signaling is able of inducing directional bending towards UV-B light in etiolated seedlings of Arabidopsis, in a phototropin independent manner. In this study, kinetic analysis of phototropic bending was used to evaluate the relative contribution of each of these pathways in UV-B mediated phototropism. Diminishing UV-B light intensity favors the importance of phototropins. Molecular and genetic analyses suggest that UV-B is capable of inducing phototropin signaling relying on phototropin kinase activity and regulation of NPH3. Moreover, enhanced UVR8 responses in the UV-B hypersensitive rup1rup2 mutants interferes with the fast phototropin mediated phototropism. Together the data suggest that phototropins are the most important receptors for UV-B induced phototropism in etiolated seedlings, and a RUP mediated negative feedback pathway prevents UVR8 signaling to interfere with the phototropin dependent response

Accurate prediction of kinase-substrate networks using knowledge graphs

Phosphorylation of specific substrates by protein kinases is a key control mechanism for vital cell-fate decisions and other cellular processes. However, discovering specific kinase-substrate relationships is time-consuming and often rather serendipitous. Computational predictions alleviate these challenges, but the current approaches suffer from limitations like restricted kinome coverage and inaccuracy. They also typically utilise only local features without reflecting broader interaction context. To address these limitations, we have developed an alternative predictive model. It uses statistical relational learning on top of phosphorylation networks interpreted as knowledge graphs, a simple yet robust model for representing networked knowledge. Compared to a representative selection of six existing systems, our model has the highest kinome coverage and produces biologically valid high-confidence predictions not possible with the other tools. Specifically, we have experimentally validated predictions of previously unknown phosphorylations by the LATS1, AKT1, PKA and MST2 kinases in human. Thus, our tool is useful for focusing phosphoproteomic experiments, and facilitates the discovery of new phosphorylation reactions. Our model can be accessed publicly via an easy-to-use web interface (LinkPhinder).Phosphorylation of specific substrates by protein kinases is a key control mechanism for vital cell-fate decisions and other cellular processes. However, discovering specific kinase-substrate relationships is time-consuming and often rather serendipitous. Computational predictions alleviate these challenges, but the current approaches suffer from limitations like restricted kinome coverage and inaccuracy. They also typically utilise only local features without reflecting broader interaction context. To address these limitations, we have developed an alternative predictive model. It uses statistical relational learning on top of phosphorylation networks interpreted as knowledge graphs, a simple yet robust model for representing networked knowledge. Compared to a representative selection of six existing systems, our model has the highest kinome coverage and produces biologically valid high-confidence predictions not possible with the other tools. Specifically, we have experimentally validated predictions of previously unknown phosphorylations by the LATS1, AKT1, PKA and MST2 kinases in human. Thus, our tool is useful for focusing phosphoproteomic experiments, and facilitates the discovery of new phosphorylation reactions. Our model can be accessed publicly via an easy-to-use web interface (LinkPhinder)

CubeSpec, A Mission Overview

CubeSpec is an in-orbit demonstration CubeSat mission in the ESA technology programme, developed and funded in Belgium. The goal of the mission is to demonstrate high-spectral-resolution astronomical spectroscopy from a 6-unit CubeSat. The prime science demonstration case for the in-orbit demonstration mission is to unravel the interior of massive stars using asteroseismology by high-cadance monitoring of the variations in spectral line profiles during a few months. The technological challenges are numerous. The 10x20cm aperture telescope and echelle spectrometer have been designed to fit in a 10x10x20cm volume. Under low-Earth orbit thermal variations, maintaining the fast telescope focus and spectrometer alignment is achieved via an athermal design. Straylight rejection and thermal shielding from the Sun and Earth infrared flux is achieved via deploying Earth and Sunshades. The narrow spectrometer slit requires arcsecond-level pointing stability using a performant 3-axis wheel stabilised attitude control system with star tracker augmented with a fine beam steering mechanism controlled in closed loop with a guiding sensor. The high cadence, long-term monitoring requirement of the mission poses specific requirements on the orbit and operational scenarios to enable the required sky visibility. CubeSpec is starting the implementation phase, with a planned launch early 2024

qcML: an exchange format for quality control metrics from mass spectrometry experiments.

Quality control is increasingly recognized as a crucial aspect of mass spectrometry based proteomics. Several recent papers discuss relevant parameters for quality control and present applications to extract these from the instrumental raw data. What has been missing, however, is a standard data exchange format for reporting these performance metrics. We therefore developed the qcML format, an XML-based standard that follows the design principles of the related mzML, mzIdentML, mzQuantML, and TraML standards from the HUPO-PSI (Proteomics Standards Initiative). In addition to the XML format, we also provide tools for the calculation of a wide range of quality metrics as well as a database format and interconversion tools, so that existing LIMS systems can easily add relational storage of the quality control data to their existing schema. We here describe the qcML specification, along with possible use cases and an illustrative example of the subsequent analysis possibilities. All information about qcML is available at http://code.google.com/p/qcml

Bringing High-precision Pointing Knowledge to CubeSats: A Compact Star Tracker

status: publishe