A Co-Opted Hormonal Cascade Activates Dormant Adventitious Root Primordia upon Flooding in Solanum dulcamara.

Soil flooding is a common stress factor affecting plants. To sustain root function in the hypoxic environment, flooding-tolerant plants may form new, aerenchymatous adventitious roots (ARs), originating from preformed, dormant primordia on the stem. We investigated the signaling pathway behind AR primordium reactivation in the dicot species Solanum dulcamara Transcriptome analysis indicated that flooding imposes a state of quiescence on the stem tissue, while increasing cellular activity in the AR primordia. Flooding led to ethylene accumulation in the lower stem region and subsequently to a drop in abscisic acid (ABA) level in both stem and AR primordia tissue. Whereas ABA treatment prevented activation of AR primordia by flooding, inhibition of ABA synthesis was sufficient to activate them in absence of flooding. Together, this reveals that there is a highly tissue-specific response to reduced ABA levels. The central role for ABA in the response differentiates the pathway identified here from the AR emergence pathway known from rice (Oryza sativa). Flooding and ethylene treatment also induced expression of the polar auxin transporter PIN2, and silencing of this gene or chemical inhibition of auxin transport inhibited primordium activation, even though ABA levels were reduced. Auxin treatment, however, was not sufficient for AR emergence, indicating that the auxin pathway acts in parallel with the requirement for ABA reduction. In conclusion, adaptation of S. dulcamara to wet habitats involved co-option of a hormonal signaling cascade well known to regulate shoot growth responses, to direct a root developmental program upon soil flooding.

A series of PDB-related databanks for everyday needs.

We present a series of databanks (http://swift.cmbi.ru.nl/gv/facilities/) that hold information that is computationally derived from Protein Data Bank (PDB) entries and that might augment macromolecular structure studies. These derived databanks run parallel to the PDB, i.e. they have one entry per PDB entry. Several of the well-established databanks such as HSSP, PDBREPORT and PDB_REDO have been updated and/or improved. The software that creates the DSSP databank, for example, has been rewritten to better cope with π-helices. A large number of databanks have been added to aid computational structural biology; some examples are lists of residues that make crystal contacts, lists of contacting residues using a series of contact definitions or lists of residue accessibilities. PDB files are not the optimal presentation of the underlying data for many studies. We therefore made a series of databanks that hold PDB files in an easier to use or more consistent representation. The BDB databank holds X-ray PDB files with consistently represented B-factors. We also added several visualization tools to aid the users of our databanks.

MetIDB: a publicly accessible database of predicted and experimental 1H NMR spectra of flavonoids.

Identification of natural compounds, especially secondary metabolites, has been hampered by the lack of easy to use and accessible reference databases. Nuclear magnetic resonance (NMR) spectroscopy is the most selective technique for identification of unknown metabolites. High quality (1)H NMR (proton nuclear magnetic resonance) spectra combined with elemental composition obtained from mass spectrometry (MS) are essential for the identification process. Here, we present MetIDB, a reference database of experimental and predicted (1)H NMR spectra of 6000 flavonoids. By incorporating the stereochemistry, intramolecular interactions, and solvent effects into the prediction model, chemical shifts and couplings were predicted with great accuracy. A user-friendly web-based interface for MetIDB has been established providing various interfaces to the data and data-mining possibilities. For each compound, additional information is available comprising compound annotation, a (1)H NMR spectrum, 2D and 3D structure with correct stereochemistry, and monoisotopic mass as well as links to other web resources. The combination of chemical formula and (1)H NMR chemical shifts proved to be very efficient in metabolite identification, especially for isobaric compounds. Using this database, the process of flavonoid identification can then be significantly shortened by avoiding repetitive elucidation of already described compounds.

MetiTree: a web application to organize and process high-resolution multi-stage mass spectrometry metabolomics data.

UNLABELLED: Identification of metabolites using high-resolution multi-stage mass spectrometry (MS(n)) data is a significant challenge demanding access to all sorts of computational infrastructures. MetiTree is a user-friendly, web application dedicated to organize, process, share, visualize and compare MS(n) data. It integrates several features to export and visualize complex MS(n) data, facilitating the exploration and interpretation of metabolomics experiments. A dedicated spectral tree viewer allows the simultaneous presentation of three related types of MS(n) data, namely, the spectral data, the fragmentation tree and the fragmentation reactions. MetiTree stores the data in an internal database to enable searching for similar fragmentation trees and matching against other MS(n) data. As such MetiTree contains much functionality that will make the difficult task of identifying unknown metabolites much easier. AVAILABILITY: MetiTree is accessible at http://www.MetiTree.nl. The source code is available at https://github.com/NetherlandsMetabolomicsCentre/metitree/wiki.

A series of PDB related databases for everyday needs.

The Protein Data Bank (PDB) is the world-wide repository of macromolecular structure information. We present a series of databases that run parallel to the PDB. Each database holds one entry, if possible, for each PDB entry. DSSP holds the secondary structure of the proteins. PDBREPORT holds reports on the structure quality and lists errors. HSSP holds a multiple sequence alignment for all proteins. The PDBFINDER holds easy to parse summaries of the PDB file content, augmented with essentials from the other systems. PDB_REDO holds re-refined, and often improved, copies of all structures solved by X-ray. WHY_NOT summarizes why certain files could not be produced. All these systems are updated weekly. The data sets can be used for the analysis of properties of protein structures in areas ranging from structural genomics, to cancer biology and protein design.

Protein structure analysis of mutations causing inheritable diseases. An e-Science approach with life scientist friendly interfaces.

BACKGROUND: Many newly detected point mutations are located in protein-coding regions of the human genome. Knowledge of their effects on the protein's 3D structure provides insight into the protein's mechanism, can aid the design of further experiments, and eventually can lead to the development of new medicines and diagnostic tools. RESULTS: In this article we describe HOPE, a fully automatic program that analyzes the structural and functional effects of point mutations. HOPE collects information from a wide range of information sources including calculations on the 3D coordinates of the protein by using WHAT IF Web services, sequence annotations from the UniProt database, and predictions by DAS services. Homology models are built with YASARA. Data is stored in a database and used in a decision scheme to identify the effects of a mutation on the protein's 3D structure and function. HOPE builds a report with text, figures, and animations that is easy to use and understandable for (bio)medical researchers. CONCLUSIONS: We tested HOPE by comparing its output to the results of manually performed projects. In all straightforward cases HOPE performed similar to a trained bioinformatician. The use of 3D structures helps optimize the results in terms of reliability and details. HOPE's results are easy to understand and are presented in a way that is attractive for researchers without an extensive bioinformatics background.

Rates of Lateral Gene Transfer in Prokaryotes: High but Why?

Lateral gene transfer is of fundamental importance to the evolution of prokaryote genomes and has important practical consequences, as evidenced by the rapid dissemination of antibiotic resistance and virulence determinants. Relatively little effort has so far been devoted to explicitly quantifying the rate at which accessory genes are taken up and lost, but it is possible that the combined rate of lateral gene transfer and gene loss is higher than that of point mutation. What evolutionary forces underlie the rate of lateral gene transfer are not well understood. We here use theory developed to explain the evolution of mutation rates to address this question and explore its consequences for the study of prokaryote evolution.

ODoSE: a webserver for genome-wide calculation of adaptive divergence in prokaryotes.

Quantifying patterns of adaptive divergence between taxa is a major goal in the comparative and evolutionary study of prokaryote genomes. When applied appropriately, the McDonald-Kreitman (MK) test is a powerful test of selection based on the relative frequency of non-synonymous and synonymous substitutions between species compared to non-synonymous and synonymous polymorphisms within species. The webserver ODoSE (Ortholog Direction of Selection Engine) allows the calculation of a novel extension of the MK test, the Direction of Selection (DoS) statistic, as well as the calculation of a weighted-average Neutrality Index (NI) statistic for the entire core genome, allowing for systematic analysis of the evolutionary forces shaping core genome divergence in prokaryotes. ODoSE is hosted in a Galaxy environment, which makes it easy to use and amenable to customization and is freely available at www.odose.nl.