The Venus flytrap trigger hair-specific potassium channel KDM1 can reestablish the K+ gradient required for hapto-electric signaling.

The carnivorous plant Dionaea muscipula harbors multicellular trigger hairs designed to sense mechanical stimuli upon contact with animal prey. At the base of the trigger hair, mechanosensation is transduced into an all-or-nothing action potential (AP) that spreads all over the trap, ultimately leading to trap closure and prey capture. To reveal the molecular basis for the unique functional repertoire of this mechanoresponsive plant structure, we determined the transcriptome of D. muscipula's trigger hair. Among the genes that were found to be highly specific to the trigger hair, the Shaker-type channel KDM1 was electrophysiologically characterized as a hyperpolarization- and acid-activated K+-selective channel, thus allowing the reuptake of K+ ions into the trigger hair's sensory cells during the hyperpolarization phase of the AP. During trap development, the increased electrical excitability of the trigger hair is associated with the transcriptional induction of KDM1. Conversely, when KDM1 is blocked by Cs+ in adult traps, the initiation of APs in response to trigger hair deflection is reduced, and trap closure is suppressed. KDM1 thus plays a dominant role in K+ homeostasis in the context of AP and turgor formation underlying the mechanosensation of trigger hair cells and thus D. muscipula's hapto-electric signaling.

BCdatabaser: on-the-fly reference database creation for (meta-)barcoding.

SUMMARY: DNA barcoding and meta-barcoding have become irreplaceable in research and applications, where identification of taxa alone or within a mixture, respectively, becomes relevant. Pioneering studies were in the microbiological context, yet nowadays also plants and animals become targeted. Given the variety of markers used, formatting requirements for classifiers and constant growth of primary databases, there is a need for dedicated reference database creation. We developed a web and command-line interface to generate such on-the-fly for any applicable marker and taxonomic group with optional filtering, formatting and restriction specific for (meta-)barcoding purposes. Also, databases optionally receive a DOI, making them well-documented with meta-data, publicly sharable and citable. AVAILABILITY AND IMPLEMENTATION: source code: https://www.github.com/molbiodiv/bcdatabaser, webservice: https://bcdatabaser.molecular.eco, documentation: https://molbiodiv.github.io/bcdatabaser.

Venus flytrap carnivorous lifestyle builds on herbivore defense strategies.

Although the concept of botanical carnivory has been known since Darwin's time, the molecular mechanisms that allow animal feeding remain unknown, primarily due to a complete lack of genomic information. Here, we show that the transcriptomic landscape of the Dionaea trap is dramatically shifted toward signal transduction and nutrient transport upon insect feeding, with touch hormone signaling and protein secretion prevailing. At the same time, a massive induction of general defense responses is accompanied by the repression of cell death-related genes/processes. We hypothesize that the carnivory syndrome of Dionaea evolved by exaptation of ancient defense pathways, replacing cell death with nutrient acquisition.

WHAMY is a novel actin polymerase promoting myoblast fusion, macrophage cell motility and sensory organ development in Drosophila.

Wiskott-Aldrich syndrome proteins (WASPs) are nucleation-promoting factors (NPF) that differentially control the Arp2/3 complex. In Drosophila, three different family members, SCAR (also known as WAVE), WASP and WASH (also known as CG13176), have been analyzed so far. Here, we characterized WHAMY, the fourth Drosophila WASP family member. whamy originated from a wasp gene duplication and underwent a sub-neofunctionalization. Unlike WASP, we found that WHAMY specifically interacted with activated Rac1 through its two CRIB domains, which were sufficient for targeting WHAMY to lamellipodial and filopodial tips. Biochemical analyses showed that WHAMY promoted exceptionally fast actin filament elongation, although it did not activate the Arp2/3 complex. Loss- and gain-of-function studies revealed an important function of WHAMY in membrane protrusions and cell migration in macrophages. Genetic data further implied synergistic functions between WHAMY and WASP during morphogenesis. Double mutants were late-embryonic lethal and showed severe defects in myoblast fusion. Trans-heterozygous mutant animals showed strongly increased defects in sensory cell fate specification. Thus, WHAMY is a novel actin polymerase with an initial partitioning of ancestral WASP functions in development and subsequent acquisition of a new function in cell motility during evolution.

ALVIS: interactive non-aggregative visualization and explorative analysis of multiple sequence alignments.

Sequence Logos and its variants are the most commonly used method for visualization of multiple sequence alignments (MSAs) and sequence motifs. They provide consensus-based summaries of the sequences in the alignment. Consequently, individual sequences cannot be identified in the visualization and covariant sites are not easily discernible. We recently proposed Sequence Bundles, a motif visualization technique that maintains a one-to-one relationship between sequences and their graphical representation and visualizes covariant sites. We here present Alvis, an open-source platform for the joint explorative analysis of MSAs and phylogenetic trees, employing Sequence Bundles as its main visualization method. Alvis combines the power of the visualization method with an interactive toolkit allowing detection of covariant sites, annotation of trees with synapomorphies and homoplasies, and motif detection. It also offers numerical analysis functionality, such as dimension reduction and classification. Alvis is user-friendly, highly customizable and can export results in publication-quality figures. It is available as a full-featured standalone version (http://www.bitbucket.org/rfs/alvis) and its Sequence Bundles visualization module is further available as a web application (http://science-practice.com/projects/sequence-bundles).

ITS2 Database V: Twice as Much.

The internal transcribed spacer 2 (ITS2) is a well-established marker for phylogenetic analyses in eukaryotes. A reliable resource for reference sequences and their secondary structures is the ITS2 database (http://its2.bioapps.biozentrum.uni-wuerzburg.de/). However, the database was last updated in 2011. Here, we present a major update of the underlying data almost doubling the number of entities. This increases the number of taxa represented within all major eukaryotic clades. Moreover, additional data has been added to underrepresented groups and some new groups have been added. The broader coverage across the tree of life improves phylogenetic analyses and the capability of ITS2 as a DNA barcode.

Evolutionary and structural analyses of mammalian haloacid dehalogenase-type phosphatases AUM and chronophin provide insight into the basis of their different substrate specificities.

Mammalian haloacid dehalogenase (HAD)-type phosphatases are an emerging family of phosphatases with important functions in physiology and disease, yet little is known about the basis of their substrate specificity. Here, we characterize a previously unexplored HAD family member (gene annotation, phosphoglycolate phosphatase), which we termed AUM, for aspartate-based, ubiquitous, Mg(2+)-dependent phosphatase. AUM is a tyrosine-specific paralog of the serine/threonine-specific protein and pyridoxal 5'-phosphate-directed HAD phosphatase chronophin. Comparative evolutionary and biochemical analyses reveal that a single, differently conserved residue in the cap domain of either AUM or chronophin is crucial for phosphatase specificity. We have solved the x-ray crystal structure of the AUM cap fused to the catalytic core of chronophin to 2.65 Å resolution and present a detailed view of the catalytic clefts of AUM and chronophin that explains their substrate preferences. Our findings identify a small number of cap domain residues that encode the different substrate specificities of AUM and chronophin.

proovread: large-scale high-accuracy PacBio correction through iterative short read consensus.

MOTIVATION: Today, the base code of DNA is mostly determined through sequencing by synthesis as provided by the Illumina sequencers. Although highly accurate, resulting reads are short, making their analyses challenging. Recently, a new technology, single molecule real-time (SMRT) sequencing, was developed that could address these challenges, as it generates reads of several thousand bases. But, their broad application has been hampered by a high error rate. Therefore, hybrid approaches that use high-quality short reads to correct erroneous SMRT long reads have been developed. Still, current implementations have great demands on hardware, work only in well-defined computing infrastructures and reject a substantial amount of reads. This limits their usability considerably, especially in the case of large sequencing projects. RESULTS: Here we present proovread, a hybrid correction pipeline for SMRT reads, which can be flexibly adapted on existing hardware and infrastructure from a laptop to a high-performance computing cluster. On genomic and transcriptomic test cases covering Escherichia coli, Arabidopsis thaliana and human, proovread achieved accuracies up to 99.9% and outperformed the existing hybrid correction programs. Furthermore, proovread-corrected sequences were longer and the throughput was higher. Thus, proovread combines the most accurate correction results with an excellent adaptability to the available hardware. It will therefore increase the applicability and value of SMRT sequencing. AVAILABILITY AND IMPLEMENTATION: proovread is available at the following URL: http://proovread.bioapps.biozentrum.uni-wuerzburg.de.

Analysis of the human protein interactome and comparison with yeast, worm and fly interaction datasets.

We present the first analysis of the human proteome with regard to interactions between proteins. We also compare the human interactome with the available interaction datasets from yeast (Saccharomyces cerevisiae), worm (Caenorhabditis elegans) and fly (Drosophila melanogaster). Of >70,000 binary interactions, only 42 were common to human, worm and fly, and only 16 were common to all four datasets. An additional 36 interactions were common to fly and worm but were not observed in humans, although a coimmunoprecipitation assay showed that 9 of the interactions do occur in humans. A re-examination of the connectivity of essential genes in yeast and humans indicated that the available data do not support the presumption that the number of interaction partners can accurately predict whether a gene is essential. Finally, we found that proteins encoded by genes mutated in inherited genetic disorders are likely to interact with proteins known to cause similar disorders, suggesting the existence of disease subnetworks. The human interaction map constructed from our analysis should facilitate an integrative systems biology approach to elucidating the cellular networks that contribute to health and disease states.

ISAAC - InterSpecies Analysing Application using Containers.

BACKGROUND: Information about genes, transcripts and proteins is spread over a wide variety of databases. Different tools have been developed using these databases to identify biological signals in gene lists from large scale analysis. Mostly, they search for enrichments of specific features. But, these tools do not allow an explorative walk through different views and to change the gene lists according to newly upcoming stories. RESULTS: To fill this niche, we have developed ISAAC, the InterSpecies Analysing Application using Containers. The central idea of this web based tool is to enable the analysis of sets of genes, transcripts and proteins under different biological viewpoints and to interactively modify these sets at any point of the analysis. Detailed history and snapshot information allows tracing each action. Furthermore, one can easily switch back to previous states and perform new analyses. Currently, sets can be viewed in the context of genomes, protein functions, protein interactions, pathways, regulation, diseases and drugs. Additionally, users can switch between species with an automatic, orthology based translation of existing gene sets. As todays research usually is performed in larger teams and consortia, ISAAC provides group based functionalities. Here, sets as well as results of analyses can be exchanged between members of groups. CONCLUSIONS: ISAAC fills the gap between primary databases and tools for the analysis of large gene lists. With its highly modular, JavaEE based design, the implementation of new modules is straight forward. Furthermore, ISAAC comes with an extensive web-based administration interface including tools for the integration of third party data. Thus, a local installation is easily feasible. In summary, ISAAC is tailor made for highly explorative interactive analyses of gene, transcript and protein sets in a collaborative environment.

The protein composition of the digestive fluid from the venus flytrap sheds light on prey digestion mechanisms.

The Venus flytrap (Dionaea muscipula) is one of the most well-known carnivorous plants because of its unique ability to capture small animals, usually insects or spiders, through a unique snap-trapping mechanism. The animals are subsequently killed and digested so that the plants can assimilate nutrients, as they grow in mineral-deficient soils. We deep sequenced the cDNA from Dionaea traps to obtain transcript libraries, which were used in the mass spectrometry-based identification of the proteins secreted during digestion. The identified proteins consisted of peroxidases, nucleases, phosphatases, phospholipases, a glucanase, chitinases, and proteolytic enzymes, including four cysteine proteases, two aspartic proteases, and a serine carboxypeptidase. The majority of the most abundant proteins were categorized as pathogenesis-related proteins, suggesting that the plant's digestive system evolved from defense-related processes. This in-depth characterization of a highly specialized secreted fluid from a carnivorous plant provides new information about the plant's prey digestion mechanism and the evolutionary processes driving its defense pathways and nutrient acquisition.

DYSCALCULIA, a Venus flytrap mutant without the ability to count action potentials.

The Venus flytrap Dionaea muscipula estimates prey nutrient content by counting trigger hair contacts initiating action potentials (APs) and calcium waves traveling all over the trap.1,2,3 A first AP is associated with a subcritical rise in cytosolic calcium concentration, but when the second AP arrives in time, calcium levels pass the threshold required for fast trap closure. Consequently, memory function and decision-making are timed via a calcium clock.3,4 For higher numbers of APs elicited by the struggling prey, the Ca2+ clock connects to the networks governed by the touch hormone jasmonic acid (JA), which initiates slow, hermetic trap sealing and mining of the animal food stock.5 Two distinct phases of trap closure can be distinguished within Dionaea's hunting cycle: (1) very fast trap snapping requiring two APs and crossing of a critical cytosolic Ca2+ level and (2) JA-dependent slow trap sealing and prey processing induced by more than five APs. The Dionaea mutant DYSC is still able to fire touch-induced APs but does not snap close its traps and fails to enter the hunting cycle after prolonged mechanostimulation. Transcriptomic analyses revealed that upon trigger hair touch/AP stimulation, activation of calcium signaling is largely suppressed in DYSC traps. The observation that external JA application restored hunting cycle progression together with the DYSC phenotype and its transcriptional landscape indicates that DYSC cannot properly read, count, and decode touch/AP-induced calcium signals that are key in prey capture and processing.

ITS2 database IV: interactive taxon sampling for internal transcribed spacer 2 based phylogenies.

The first step of any molecular phylogenetic analysis is the selection of the species and sequences to be included, the taxon sampling. Already here different pitfalls exist. Sequences can contain errors, annotations in databases can be inaccurate and even the taxonomic classification of a species can be wrong. Usually, these artefacts become evident only after calculation of the phylogenetic tree. Following, the taxon sampling has to be corrected iteratively. This can become tedious and time consuming, as in most cases the taxon sampling is de-coupled from the further steps of the phylogenetic analysis. Here, we present the ITS2 Workbench (http://its2.bioapps.biozentrum.uni-wuerzburg.de/), which eliminates this problem by a tight integration of taxon sampling, secondary structure prediction, multiple alignment and phylogenetic tree calculation. The ITS2 Workbench has access to more than 280,000 ITS2 sequences and their structures provided by the ITS2 database enabling sequence-structure based alignment and tree reconstruction. This allows the interactive improvement of the taxon sampling throughout the whole phylogenetic tree reconstruction process. Thus, the ITS2 Workbench enables a fast, interactive and iterative taxon sampling leading to more accurate ITS2 based phylogenies.

The ITS2 Database III--sequences and structures for phylogeny.

The internal transcribed spacer 2 (ITS2) is a widely used phylogenetic marker. In the past, it has mainly been used for species level classifications. Nowadays, a wider applicability becomes apparent. Here, the conserved structure of the RNA molecule plays a vital role. We have developed the ITS2 Database (http://its2.bioapps.biozentrum.uni-wuerzburg.de) which holds information about sequence, structure and taxonomic classification of all ITS2 in GenBank. In the new version, we use Hidden Markov models (HMMs) for the identification and delineation of the ITS2 resulting in a major redesign of the annotation pipeline. This allowed the identification of more than 160,000 correct full length and more than 50,000 partial structures. In the web interface, these can now be searched with a modified BLAST considering both sequence and structure, enabling rapid taxon sampling. Novel sequences can be annotated using the HMM based approach and modelled according to multiple template structures. Sequences can be searched for known and newly identified motifs. Together, the database and the web server build an exhaustive resource for ITS2 based phylogenetic analyses.

Protein interaction networks--more than mere modules.

It is widely believed that the modular organization of cellular function is reflected in a modular structure of molecular networks. A common view is that a "module" in a network is a cohesively linked group of nodes, densely connected internally and sparsely interacting with the rest of the network. Many algorithms try to identify functional modules in protein-interaction networks (PIN) by searching for such cohesive groups of proteins. Here, we present an alternative approach independent of any prior definition of what actually constitutes a "module". In a self-consistent manner, proteins are grouped into "functional roles" if they interact in similar ways with other proteins according to their functional roles. Such grouping may well result in cohesive modules again, but only if the network structure actually supports this. We applied our method to the PIN from the Human Protein Reference Database (HPRD) and found that a representation of the network in terms of cohesive modules, at least on a global scale, does not optimally represent the network's structure because it focuses on finding independent groups of proteins. In contrast, a decomposition into functional roles is able to depict the structure much better as it also takes into account the interdependencies between roles and even allows groupings based on the absence of interactions between proteins in the same functional role. This, for example, is the case for transmembrane proteins, which could never be recognized as a cohesive group of nodes in a PIN. When mapping experimental methods onto the groups, we identified profound differences in the coverage suggesting that our method is able to capture experimental bias in the data, too. For example yeast-two-hybrid data were highly overrepresented in one particular group. Thus, there is more structure in protein-interaction networks than cohesive modules alone and we believe this finding can significantly improve automated function prediction algorithms.

Detecting species-site dependencies in large multiple sequence alignments.

Multiple sequence alignments (MSAs) are one of the most important sources of information in sequence analysis. Many methods have been proposed to detect, extract and visualize their most significant properties. To the same extent that site-specific methods like sequence logos successfully visualize site conservations and sequence-based methods like clustering approaches detect relationships between sequences, both types of methods fail at revealing informational elements of MSAs at the level of sequence-site interactions, i.e. finding clusters of sequences and sites responsible for their clustering, which together account for a high fraction of the overall information of the MSA. To fill this gap, we present here a method that combines the Fisher score-based embedding of sequences from a profile hidden Markov model (pHMM) with correspondence analysis. This method is capable of detecting and visualizing group-specific or conflicting signals in an MSA and allows for a detailed explorative investigation of alignments of any size tractable by pHMMs. Applications of our methods are exemplified on an alignment of the Neisseria surface antigen LP2086, where it is used to detect sites of recombinatory horizontal gene transfer and on the vitamin K epoxide reductase family to distinguish between evolutionary and functional signals.

Evolution of an RNP assembly system: a minimal SMN complex facilitates formation of UsnRNPs in Drosophila melanogaster.

In vertebrates, assembly of spliceosomal uridine-rich small nuclear ribonucleoproteins (UsnRNPs) is mediated by the SMN complex, a macromolecular entity composed of the proteins SMN and Gemins 2-8. Here we have studied the evolution of this machinery using complete genome assemblies of multiple model organisms. The SMN complex has gained complexity in evolution by a blockwise addition of Gemins onto an ancestral core complex composed of SMN and Gemin2. In contrast to this overall evolutionary trend to more complexity in metazoans, orthologs of most Gemins are missing in dipterans. In accordance with these bioinformatic data a previously undescribed biochemical purification strategy elucidated that the dipteran Drosophila melanogaster contains an SMN complex of remarkable simplicity. Surprisingly, this minimal complex not only mediates the assembly reaction in a manner very similar to its vertebrate counterpart, but also prevents misassembly onto nontarget RNAs. Our data suggest that only a minority of Gemins are required for the assembly reaction per se, whereas others may serve additional functions in the context of UsnRNP biogenesis. The evolution of the SMN complex is an interesting example of how the simplification of a biochemical process contributes to genome compaction.

How to Grow a Tree: Plant Voltage-Dependent Cation Channels in the Spotlight of Evolution.

Phylogenetic analysis can be a powerful tool for generating hypotheses regarding the evolution of physiological processes. Here, we provide an updated view of the evolution of the main cation channels in plant electrical signalling: the Shaker family of voltage-gated potassium channels and the two-pore cation (K+) channel (TPC1) family. Strikingly, the TPC1 family followed the same conservative evolutionary path as one particular subfamily of Shaker channels (Kout) and remained highly invariant after terrestrialisation, suggesting that electrical signalling was, and remains, key to survival on land. We note that phylogenetic analyses can have pitfalls, which may lead to erroneous conclusions. To avoid these in the future, we suggest guidelines for analyses of ion channel evolution in plants.

The ITS2 Database II: homology modelling RNA structure for molecular systematics.

An increasing number of phylogenetic analyses are based on the internal transcribed spacer 2 (ITS2). They mainly use the fast evolving sequence for low-level analyses. When considering the highly conserved structure, the same marker could also be used for higher level phylogenies. Furthermore, structural features of the ITS2 allow distinguishing different species from each other. Despite its importance, the correct structure is only rarely found by standard RNA folding algorithms. To overcome this hindrance for a wider application of the ITS2, we have developed a homology modelling approach to predict the structure of RNA and present the results of modelling the ITS2 in the ITS2 Database. Here, we describe the database and the underlying algorithms which allowed us to predict the structure for 86 784 sequences, which is more than 55% of all GenBank entries concerning the ITS2. These are not equally distributed over all genera. There is a substantial amount of genera where the structure of nearly all sequences is predicted whereas for others no structure at all was found despite high sequence coverage. These genera might have evolved an ITS2 structure diverging from the standard one. The current version of the ITS2 Database can be accessed via http://its2.bioapps.biozentrum.uni-wuerzburg.de.