6482
2012
eng
article
1
2013-03-16
--
--
Integrated pathway modules using time-course metabolic profiles and EST data from Milnesium tardigradum
Background: Tardigrades are multicellular organisms, resistant to extreme environmental changes such as heat, drought, radiation and freezing. They outlast these conditions in an inactive form (tun) to escape damage to cellular structures and cell death. Tardigrades are apparently able to prevent or repair such damage and are therefore a crucial model organism for stress tolerance. Cultures of the tardigrade Milnesium tardigradum were dehydrated by removing the surrounding water to induce tun formation. During this process and the subsequent rehydration, metabolites were measured in a time series by GC-MS. Additionally expressed sequence tags are available, especially libraries generated from the active and inactive state. The aim of this integrated analysis is to trace changes in tardigrade metabolism and identify pathways responsible for their extreme resistance against physical stress. Results: In this study we propose a novel integrative approach for the analysis of metabolic networks to identify modules of joint shifts on the transcriptomic and metabolic levels. We derive a tardigrade-specific metabolic network represented as an undirected graph with 3,658 nodes (metabolites) and 4,378 edges (reactions). Time course metabolite profiles are used to score the network nodes showing a significant change over time. The edges are scored according to information on enzymes from the EST data. Using this combined information, we identify a key subnetwork (functional module) of concerted changes in metabolic pathways, specific for de- and rehydration. The module is enriched in reactions showing significant changes in metabolite levels and enzyme abundance during the transition. It resembles the cessation of a measurablemetabolism (e.g. glycolysis and amino acid anabolism) during the tun formation, the production of storage metabolites and bioprotectants, such as DNA stabilizers, and the generation of amino acids and cellular components from monosaccharides as carbon and energy source during rehydration. Conclusions: The functional module identifies relationships among changed metabolites (e.g. spermidine) and reactions and provides first insights into important altered metabolic pathways. With sparse and diverse data available, the presented integrated metabolite network approach is suitable to integrate all existing data and analyse it in a combined manner.
urn:nbn:de:bvb:20-opus-75241
7524
In: BMC Systems Biology (2012) 6: 72, doi:10.1186/1752-0509-6-72
Daniela Beisser
Markus A. Grohme
Joachim Kopka
Marcus Frohme
Ralph O. Schill
Steffen Hengherr
Thomas Dandekar
Gunnar W. Klau
Marcus Dittrich
Tobias Müller
deu
swd
Milnesium tardigradum
eng
uncontrolled
Integrated network analysis
eng
uncontrolled
Functional modules
eng
uncontrolled
Metabolic profiles
eng
uncontrolled
Metabolic pathways
eng
uncontrolled
Trend test
Biowissenschaften; Biologie
open_access
Theodor-Boveri-Institut für Biowissenschaften
Förderzeitraum 2012
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/6482/019_1752_0509_6_72.pdf
12460
2012
eng
e3806
61
article
1
2016-01-19
--
--
The ITS2 Database
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.
Journal of Visual Expression
10.3791/3806
urn:nbn:de:bvb:20-opus-124600
Journal of Visual Expression (61), e3806, doi:10.3791/3806 (2012)
Benjamin Merget
Christian Koetschan
Thomas Hackl
Frank Förster
Thomas Dandekar
Tobias Müller
Jörg Schultz
Matthias Wolf
eng
uncontrolled
homology modeling
eng
uncontrolled
molecular systematics
eng
uncontrolled
internal transcribed spacer 2
eng
uncontrolled
alignment
eng
uncontrolled
genetics
eng
uncontrolled
secondary structure
eng
uncontrolled
ribosomal RNA
eng
uncontrolled
phylogenetic tree
eng
uncontrolled
phylogeny
Datenverarbeitung; Informatik
Chemie und zugeordnete Wissenschaften
Biowissenschaften; Biologie
open_access
Theodor-Boveri-Institut für Biowissenschaften
Institut für Pharmazie und Lebensmittelchemie
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/12460/jove-61-3806.pdf
12308
2012
eng
69-96
6
article
1
2015-12-14
--
--
Transcriptome analysis in tardigrade species reveals specific molecular pathways for stress adaptations
Tardigrades have unique stress-adaptations that allow them to survive extremes of cold, heat, radiation and vacuum. To study this, encoded protein clusters and pathways from an ongoing transcriptome study on the tardigrade \(Milnesium\) \(tardigradum\) were analyzed using bioinformatics tools and compared to expressed sequence tags (ESTs) from \(Hypsibius\) \(dujardini\), revealing major pathways involved in resistance against extreme environmental conditions. ESTs are available on the Tardigrade Workbench along with software and databank updates. Our analysis reveals that RNA stability motifs for \(M.\) \(tardigradum\) are different from typical motifs known from higher animals. \(M.\) \(tardigradum\) and \(H.\) \(dujardini\) protein clusters and conserved domains imply metabolic storage pathways for glycogen, glycolipids and specific secondary metabolism as well as stress response pathways (including heat shock proteins, bmh2, and specific repair pathways). Redox-, DNA-, stress- and protein protection pathways complement specific repair capabilities to achieve the strong robustness of \(M.\) \(tardigradum\). These pathways are partly conserved in other animals and their manipulation could boost stress adaptation even in human cells. However, the unique combination of resistance and repair pathways make tardigrades and \(M.\) \(tardigradum\) in particular so highly stress resistant.
Bioinformatics and biology insights
PMC3342025
10.4137/BBI.S9150
urn:nbn:de:bvb:20-opus-123089
This is an open access article. Unrestricted non-commercial use is permitted provided the original work is properly cited.
Bioinformatics and Biology Insights 2012:6 69–96. doi: 10.4137/BBI.S9150
Frank Förster
Daniela Beisser
Markus A. Grohme
Chunguang Liang
Brahim Mali
Alexander Matthias Siegl
Julia C. Engelmann
Alexander V. Shkumatov
Elham Schokraie
Tobias Müller
Martina Schnölzer
Ralph O. Schill
Marcus Frohme
Thomas Dandekar
eng
uncontrolled
RNA
eng
uncontrolled
expressed sequence tag
eng
uncontrolled
cluster
eng
uncontrolled
protein familiy
eng
uncontrolled
adaption
eng
uncontrolled
tardigrada
eng
uncontrolled
transcriptome
Biowissenschaften; Biologie
open_access
Theodor-Boveri-Institut für Biowissenschaften
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/12308/f_3147-BBI-Transcriptome-Analysis-in-Tardigrade-Species-Reveals-Specific-Molecula.pdf_4261.pdf
13132
2012
eng
e34796
4
7
article
1
2016-04-05
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--
A Critical Evaluation of Network and Pathway-Based Classifiers for Outcome Prediction in Breast Cancer
Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single genes classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single genes classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single genes classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single genes sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single genes classifiers for predicting outcome in breast cancer.
PLoS One
10.1371/journal.pone.0034796
urn:nbn:de:bvb:20-opus-131323
PLoS ONE 7(4): e34796. doi:10.1371/journal.pone.0034796
Christine Staiger
Sidney Cadot
Raul Kooter
Marcus Dittrich
Tobias Müller
Gunnar W. Klau
Lodewyk F. A. Wessels
eng
uncontrolled
modules
eng
uncontrolled
protein-interaction networks
eng
uncontrolled
expression signature
eng
uncontrolled
classification
eng
uncontrolled
set
eng
uncontrolled
metastasis
eng
uncontrolled
stability
eng
uncontrolled
survival
eng
uncontrolled
database
eng
uncontrolled
markers
Datenverarbeitung; Informatik
Biowissenschaften; Biologie
open_access
Theodor-Boveri-Institut für Biowissenschaften
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/13132/Staiger_PlosOne.pdf