@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{BeisserGrohmeKopkaetal.2012, author = {Beisser, Daniela and Grohme, Markus A. and Kopka, Joachim and Frohme, Marcus and Schill, Ralph O. and Hengherr, Steffen and Dandekar, Thomas and Klau, Gunnar W. and Dittrich, Marcus and M{\"u}ller, Tobias}, title = {Integrated pathway modules using time-course metabolic profiles and EST data from Milnesium tardigradum}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-75241}, year = {2012}, abstract = {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.}, subject = {Milnesium tardigradum}, language = {en} }