@article{SchokraieWarnkenHotzWagenblattetal.2012, author = {Schokraie, Elham and Warnken, Uwe and Hotz-Wagenblatt, Agnes and Grohme, Markus A. and Hengherr, Steffen and F{\"o}rster, Frank and Schill, Ralph O. and Frohme, Marcus and Dandekar, Thomas and Schn{\"o}lzer, Martina}, title = {Comparative proteome analysis of Milnesium tardigradum in early embryonic state versus adults in active and anhydrobiotic state}, series = {PLoS One}, volume = {7}, journal = {PLoS One}, number = {9}, doi = {10.1371/journal.pone.0045682}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-134447}, pages = {e45682}, year = {2012}, abstract = {Tardigrades have fascinated researchers for more than 300 years because of their extraordinary capability to undergo cryptobiosis and survive extreme environmental conditions. However, the survival mechanisms of tardigrades are still poorly understood mainly due to the absence of detailed knowledge about the proteome and genome of these organisms. Our study was intended to provide a basis for the functional characterization of expressed proteins in different states of tardigrades. High-throughput, high-accuracy proteomics in combination with a newly developed tardigrade specific protein database resulted in the identification of more than 3000 proteins in three different states: early embryonic state and adult animals in active and anhydrobiotic state. This comprehensive proteome resource includes protein families such as chaperones, antioxidants, ribosomal proteins, cytoskeletal proteins, transporters, protein channels, nutrient reservoirs, and developmental proteins. A comparative analysis of protein families in the different states was performed by calculating the exponentially modified protein abundance index which classifies proteins in major and minor components. This is the first step to analyzing the proteins involved in early embryonic development, and furthermore proteins which might play an important role in the transition into the anhydrobiotic state.}, language = {en} } @article{MergetKoetschanHackletal.2012, author = {Merget, Benjamin and Koetschan, Christian and Hackl, Thomas and F{\"o}rster, Frank and Dandekar, Thomas and M{\"u}ller, Tobias and Schultz, J{\"o}rg and Wolf, Matthias}, title = {The ITS2 Database}, series = {Journal of Visual Expression}, volume = {61}, journal = {Journal of Visual Expression}, number = {e3806}, doi = {10.3791/3806}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-124600}, year = {2012}, abstract = {The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades. As ITS2 research mainly focused on the very variable ITS2 sequence, it confined this marker to low-level phylogenetics only. However, the combination of the ITS2 sequence and its highly conserved secondary structure improves the phylogenetic resolution1 and allows phylogenetic inference at multiple taxonomic ranks, including species delimitation. The ITS2 Database presents an exhaustive dataset of internal transcribed spacer 2 sequences from NCBI GenBank accurately reannotated. Following an annotation by profile Hidden Markov Models (HMMs), the secondary structure of each sequence is predicted. First, it is tested whether a minimum energy based fold (direct fold) results in a correct, four helix conformation. If this is not the case, the structure is predicted by homology modeling. In homology modeling, an already known secondary structure is transferred to another ITS2 sequence, whose secondary structure was not able to fold correctly in a direct fold. The ITS2 Database is not only a database for storage and retrieval of ITS2 sequence-structures. It also provides several tools to process your own ITS2 sequences, including annotation, structural prediction, motif detection and BLAST search on the combined sequence-structure information. Moreover, it integrates trimmed versions of 4SALE and ProfDistS for multiple sequence-structure alignment calculation and Neighbor Joining tree reconstruction. Together they form a coherent analysis pipeline from an initial set of sequences to a phylogeny based on sequence and secondary structure. In a nutshell, this workbench simplifies first phylogenetic analyses to only a few mouse-clicks, while additionally providing tools and data for comprehensive large-scale analyses.}, language = {en} } @article{KruegerFriedrichFoersteretal.2012, author = {Krueger, Beate and Friedrich, Torben and F{\"o}rster, Frank and Bernhardt, J{\"o}rg and Gross, Roy and Dandekar, Thomas}, title = {Different evolutionary modifications as a guide to rewire two-component systems}, series = {Bioinformatics and Biology Insights}, volume = {6}, journal = {Bioinformatics and Biology Insights}, doi = {10.4137/BBI.S9356}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-123647}, pages = {97-128}, year = {2012}, abstract = {Two-component systems (TCS) are short signalling pathways generally occurring in prokaryotes. They frequently regulate prokaryotic stimulus responses and thus are also of interest for engineering in biotechnology and synthetic biology. The aim of this study is to better understand and describe rewiring of TCS while investigating different evolutionary scenarios. Based on large-scale screens of TCS in different organisms, this study gives detailed data, concrete alignments, and structure analysis on three general modification scenarios, where TCS were rewired for new responses and functions: (i) exchanges in the sequence within single TCS domains, (ii) exchange of whole TCS domains; (iii) addition of new components modulating TCS function. As a result, the replacement of stimulus and promotor cassettes to rewire TCS is well defined exploiting the alignments given here. The diverged TCS examples are non-trivial and the design is challenging. Designed connector proteins may also be useful to modify TCS in selected cases.}, language = {en} } @article{BuchheimKellerKoetschanetal.2011, author = {Buchheim, Mark A. and Keller, Alexander and Koetschan, Christian and F{\"o}rster, Frank and Merget, Benjamin and Wolf, Matthias}, title = {Internal Transcribed Spacer 2 (nu ITS2 rRNA) Sequence-Structure Phylogenetics: Towards an Automated Reconstruction of the Green Algal Tree of Life}, series = {PLoS ONE}, volume = {6}, journal = {PLoS ONE}, number = {2}, doi = {10.1371/journal.pone.0016931}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-140866}, pages = {e16931}, year = {2011}, abstract = {Background: Chloroplast-encoded genes (matK and rbcL) have been formally proposed for use in DNA barcoding efforts targeting embryophytes. Extending such a protocol to chlorophytan green algae, though, is fraught with problems including non homology (matK) and heterogeneity that prevents the creation of a universal PCR toolkit (rbcL). Some have advocated the use of the nuclear-encoded, internal transcribed spacer two (ITS2) as an alternative to the traditional chloroplast markers. However, the ITS2 is broadly perceived to be insufficiently conserved or to be confounded by introgression or biparental inheritance patterns, precluding its broad use in phylogenetic reconstruction or as a DNA barcode. A growing body of evidence has shown that simultaneous analysis of nucleotide data with secondary structure information can overcome at least some of the limitations of ITS2. The goal of this investigation was to assess the feasibility of an automated, sequence-structure approach for analysis of IT2 data from a large sampling of phylum Chlorophyta. Methodology/Principal Findings: Sequences and secondary structures from 591 chlorophycean, 741 trebouxiophycean and 938 ulvophycean algae, all obtained from the ITS2 Database, were aligned using a sequence structure-specific scoring matrix. Phylogenetic relationships were reconstructed by Profile Neighbor-Joining coupled with a sequence structure-specific, general time reversible substitution model. Results from analyses of the ITS2 data were robust at multiple nodes and showed considerable congruence with results from published phylogenetic analyses. Conclusions/Significance: Our observations on the power of automated, sequence-structure analyses of ITS2 to reconstruct phylum-level phylogenies of the green algae validate this approach to assessing diversity for large sets of chlorophytan taxa. Moreover, our results indicate that objections to the use of ITS2 for DNA barcoding should be weighed against the utility of an automated, data analysis approach with demonstrated power to reconstruct evolutionary patterns for highly divergent lineages.}, language = {en} } @article{AnkenbrandWeberBeckeretal.2016, author = {Ankenbrand, Markus J. and Weber, Lorenz and Becker, Dirk and F{\"o}rster, Frank and Bemm, Felix}, title = {TBro: visualization and management of de novo transcriptomes}, series = {Database}, volume = {2016}, journal = {Database}, doi = {10.1093/database/baw146}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147954}, pages = {baw146}, year = {2016}, abstract = {RNA sequencing (RNA-seq) has become a powerful tool to understand molecular mechanisms and/or developmental programs. It provides a fast, reliable and cost-effective method to access sets of expressed elements in a qualitative and quantitative manner. Especially for non-model organisms and in absence of a reference genome, RNA-seq data is used to reconstruct and quantify transcriptomes at the same time. Even SNPs, InDels, and alternative splicing events are predicted directly from the data without having a reference genome at hand. A key challenge, especially for non-computational personnal, is the management of the resulting datasets, consisting of different data types and formats. Here, we present TBro, a flexible de novo transcriptome browser, tackling this challenge. TBro aggregates sequences, their annotation, expression levels as well as differential testing results. It provides an easy-to-use interface to mine the aggregated data and generate publication-ready visualizations. Additionally, it supports users with an intuitive cart system, that helps collecting and analysing biological meaningful sets of transcripts. TBro's modular architecture allows easy extension of its functionalities in the future. Especially, the integration of new data types such as proteomic quantifications or array-based gene expression data is straightforward. Thus, TBro is a fully featured yet flexible transcriptome browser that supports approaching complex biological questions and enhances collaboration of numerous researchers.}, language = {en} }