@article{CatchpolePlatzerWeikertetal.2011,
  author    = {Catchpole, Gareth and Platzer, Alexander and Weikert, Cornelia and Kempkensteffen, Carsten and Johannsen, Manfred and Krause, Hans and Jung, Klaus and Miller, Kurt and Willmitzer, Lothar and Selbig, Joachim and Weikert, Steffen},
  title     = {Metabolic profiling reveals key metabolic features of renal cell carcinoma},
  series = {Journal of cellular and molecular medicine : a journal of translational medicine},
  volume    = {15},
  journal   = {Journal of cellular and molecular medicine : a journal of translational medicine},
  number    = {1},
  publisher = {Wiley-Blackwell},
  address   = {Malden},
  issn      = {1582-1838},
  doi       = {10.1111/j.1582-4934.2009.00939.x},
  pages     = {109 -- 118},
  year      = {2011},
  abstract  = {Recent evidence suggests that metabolic changes play a pivotal role in the biology of cancer and in particular renal cell carcinoma (RCC). Here, a global metabolite profiling approach was applied to characterize the metabolite pool of RCC and normal renal tissue. Advanced decision tree models were applied to characterize the metabolic signature of RCC and to explore features of metastasized tumours. The findings were validated in a second independent dataset. Vitamin E derivates and metabolites of glucose, fatty acid, and inositol phosphate metabolism determined the metabolic profile of RCC. alpha-tocopherol, hippuric acid, myoinositol, fructose-1-phosphate and glucose-1-phosphate contributed most to the tumour/normal discrimination and all showed pronounced concentration changes in RCC. The identified metabolic profile was characterized by a low recognition error of only 5\% for tumour versus normal samples. Data on metastasized tumours suggested a key role for metabolic pathways involving arachidonic acid, free fatty acids, proline, uracil and the tricarboxylic acid cycle. These results illustrate the potential of mass spectroscopy based metabolomics in conjunction with sophisticated data analysis methods to uncover the metabolic phenotype of cancer. Differentially regulated metabolites, such as vitamin E compounds, hippuric acid and myoinositol, provide leads for the characterization of novel pathways in RCC.},
  language  = {en}
}
@article{LisecRoemischMarglNikoloskietal.2011,
  author    = {Lisec, Jan and R{\"o}misch-Margl, Lilla and Nikoloski, Zoran and Piepho, Hans-Peter and Giavalisco, Patrick and Selbig, Joachim and Gierl, Alfons and Willmitzer, Lothar},
  title     = {Corn hybrids display lower metabolite variability and complex metabolite inheritance patterns},
  series = {The plant journal},
  volume    = {68},
  journal   = {The plant journal},
  number    = {2},
  publisher = {Wiley-Blackwell},
  address   = {Malden},
  issn      = {0960-7412},
  doi       = {10.1111/j.1365-313X.2011.04689.x},
  pages     = {326 -- 336},
  year      = {2011},
  abstract  = {We conducted a comparative analysis of the root metabolome of six parental maize inbred lines and their 14 corresponding hybrids showing fresh weight heterosis. We demonstrated that the metabolic profiles not only exhibit distinct features for each hybrid line compared with its parental lines, but also separate reciprocal hybrids. Reconstructed metabolic networks, based on robust correlations between metabolic profiles, display a higher network density in most hybrids as compared with the corresponding inbred lines. With respect to metabolite level inheritance, additive, dominant and overdominant patterns are observed with no specific overrepresentation. Despite the observed complexity of the inheritance pattern, for the majority of metabolites the variance observed in all 14 hybrids is lower compared with inbred lines. Deviations of metabolite levels from the average levels of the hybrids correlate negatively with biomass, which could be applied for developing predictors of hybrid performance based on characteristics of metabolite patterns.},
  language  = {en}
}
@article{RohrmannTohgeAlbaetal.2011,
  author    = {Rohrmann, Johannes and Tohge, Takayuki and Alba, Rob and Osorio, Sonia and Caldana, Camila and McQuinn, Ryan and Arvidsson, Samuel Janne and van der Merwe, Margaretha J. and Riano-Pachon, Diego Mauricio and M{\"u}ller-R{\"o}ber, Bernd and Fei, Zhangjun and Nesi, Adriano Nunes and Giovannoni, James J. and Fernie, Alisdair R.},
  title     = {Combined transcription factor profiling, microarray analysis and metabolite profiling reveals the transcriptional control of metabolic shifts occurring during tomato fruit development},
  series = {The plant journal},
  volume    = {68},
  journal   = {The plant journal},
  number    = {6},
  publisher = {Wiley-Blackwell},
  address   = {Malden},
  issn      = {0960-7412},
  doi       = {10.1111/j.1365-313X.2011.04750.x},
  pages     = {999 -- 1013},
  year      = {2011},
  abstract  = {Maturation of fleshy fruits such as tomato (Solanum lycopersicum) is subject to tight genetic control. Here we describe the development of a quantitative real-time PCR platform that allows accurate quantification of the expression level of approximately 1000 tomato transcription factors. In addition to utilizing this novel approach, we performed cDNA microarray analysis and metabolite profiling of primary and secondary metabolites using GC-MS and LC-MS, respectively. We applied these platforms to pericarp material harvested throughout fruit development, studying both wild-type Solanum lycopersicum cv. Ailsa Craig and the hp1 mutant. This mutant is functionally deficient in the tomato homologue of the negative regulator of the light signal transduction gene DDB1 from Arabidopsis, and is furthermore characterized by dramatically increased pigment and phenolic contents. We choose this particular mutant as it had previously been shown to have dramatic alterations in the content of several important fruit metabolites but relatively little impact on other ripening phenotypes. The combined dataset was mined in order to identify metabolites that were under the control of these transcription factors, and, where possible, the respective transcriptional regulation underlying this control. The results are discussed in terms of both programmed fruit ripening and development and the transcriptional and metabolic shifts that occur in parallel during these processes.},
  language  = {en}
}