@article{BrotmanLandauPninietal.2012, author = {Brotman, Yariv and Landau, Udi and Pnini, Smadar and Lisec, Jan and Balazadeh, Salma and M{\"u}ller-R{\"o}ber, Bernd and Zilberstein, Aviah and Willmitzer, Lothar and Chet, Ilan and Viterbo, Ada}, title = {The LysM Receptor-Like Kinase LysM RLK1 is required to activate defense and abiotic-stress responses induced by overexpression of fungal chitinases in arabidopsis plants}, series = {Molecular plant}, volume = {5}, journal = {Molecular plant}, number = {5}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {1674-2052}, doi = {10.1093/mp/sss021}, pages = {1113 -- 1124}, year = {2012}, abstract = {Application of crab shell chitin or pentamer chitin oligosaccharide to Arabidopsis seedlings increased tolerance to salinity in wild-type but not in knockout mutants of the LysM Receptor-Like Kinase1 (CERK1/LysM RLK1) gene, known to play a critical role in signaling defense responses induced by exogenous chitin. Arabidopsis plants overexpressing the endochitinase chit36 and hexoaminidase excy1 genes from the fungus Trichoderma asperelleoides T203 showed increased tolerance to salinity, heavy-metal stresses, and Botrytis cinerea infection. Resistant lines, overexpressing fungal chitinases at different levels, were outcrossed to lysm rlk1 mutants. Independent homozygous hybrids lost resistance to biotic and abiotic stresses, despite enhanced chitinase activity. Expression analysis of 270 stress-related genes, including those induced by reactive oxygen species (ROS) and chitin, revealed constant up-regulation (at least twofold) of 10 genes in the chitinase-overexpressing line and an additional 76 salt-induced genes whose expression was not elevated in the lysm rlk1 knockout mutant or the hybrids harboring the mutation. These findings elucidate that chitin-induced signaling mediated by LysM RLK1 receptor is not limited to biotic stress response but also encompasses abiotic-stress signaling and can be conveyed by ectopic expression of chitinases in plants.}, language = {en} } @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{deAbreueLimaLiWenetal.2018, author = {de Abreu e Lima, Francisco Anastacio and Li, Kun and Wen, Weiwei and Yan, Jianbing and Nikoloski, Zoran and Willmitzer, Lothar and Brotman, Yariv}, title = {Unraveling lipid metabolism in maize with time-resolved multi-omics data}, series = {The plant journal}, volume = {93}, journal = {The plant journal}, number = {6}, publisher = {Wiley}, address = {Hoboken}, issn = {0960-7412}, doi = {10.1111/tpj.13833}, pages = {1102 -- 1115}, year = {2018}, abstract = {Maize is the cereal crop with the highest production worldwide, and its oil is a key energy resource. Improving the quantity and quality of maize oil requires a better understanding of lipid metabolism. To predict the function of maize genes involved in lipid biosynthesis, we assembled transcriptomic and lipidomic data sets from leaves of B73 and the high-oil line By804 in two distinct time-series experiments. The integrative analysis based on high-dimensional regularized regression yielded lipid-transcript associations indirectly validated by Gene Ontology and promoter motif enrichment analyses. The co-localization of lipid-transcript associations using the genetic mapping of lipid traits in leaves and seedlings of a B73 x By804 recombinant inbred line population uncovered 323 genes involved in the metabolism of phospholipids, galactolipids, sulfolipids and glycerolipids. The resulting association network further supported the involvement of 50 gene candidates in modulating levels of representatives from multiple acyl-lipid classes. Therefore, the proposed approach provides high-confidence candidates for experimental testing in maize and model plant species.}, language = {en} } @article{deAbreueLimaWillmitzerNikoloski2018, author = {de Abreu e Lima, Francisco Anastacio and Willmitzer, Lothar and Nikoloski, Zoran}, title = {Classification-driven framework to predict maize hybrid field performance from metabolic profiles of young parental roots}, series = {PLoS one}, volume = {13}, journal = {PLoS one}, number = {4}, publisher = {PLoS}, address = {San Fransisco}, issn = {1932-6203}, doi = {10.1371/journal.pone.0196038}, pages = {16}, year = {2018}, abstract = {Maize (Zea mays L.) is a staple food whose production relies on seed stocks that largely comprise hybrid varieties. Therefore, knowledge about the molecular determinants of hybrid performance (HP) in the field can be used to devise better performing hybrids to address the demands for sustainable increase in yield. Here, we propose and test a classification-driven framework that uses metabolic profiles from in vitro grown young roots of parental lines from the Dent x Flint maize heterotic pattern to predict field HP. We identify parental analytes that best predict the metabolic inheritance patterns in 328 hybrids. We then demonstrate that these analytes are also predictive of field HP (0.64 >= r >= 0.79) and discriminate hybrids of good performance (accuracy of 87.50\%). Therefore, our approach provides a cost-effective solution for hybrid selection programs.}, language = {en} } @article{DuwenigSteupWillmitzeretal.1997, author = {Duwenig, Elke and Steup, Martin and Willmitzer, Lothar and Kossmann, Jens}, title = {Antisense inhibition of cytosolic phosphorylase in potato plants (Solanum tuberosum L.) affects tuber sprouting and flower formation with only little impact on carbohydrate metabolism}, year = {1997}, language = {en} } @article{FeherLisecRoemischMargletal.2014, author = {Feher, Kristen and Lisec, Jan and Roemisch-Margl, Lilla and Selbig, Joachim and Gierl, Alfons and Piepho, Hans-Peter and Nikoloski, Zoran and Willmitzer, Lothar}, title = {Deducing hybrid performance from parental metabolic profiles of young primary roots of maize by using a multivariate diallel approach}, series = {PLoS one}, volume = {9}, journal = {PLoS one}, number = {1}, publisher = {PLoS}, address = {San Fransisco}, issn = {1932-6203}, doi = {10.1371/journal.pone.0085435}, pages = {9}, year = {2014}, language = {en} } @article{JuerchottGuoCatchpoleetal.2011, author = {Juerchott, Kathrin and Guo, Ke-Tai and Catchpole, Gareth and Feher, Kristen and Willmitzer, Lothar and Schichor, Christian and Selbig, Joachim}, title = {Comparison of metabolite profiles in U87 glioma cells and mesenchymal stem cells}, series = {Biosystems : journal of biological and information processing sciences}, volume = {105}, journal = {Biosystems : journal of biological and information processing sciences}, number = {2}, publisher = {Elsevier}, address = {Oxford}, issn = {0303-2647}, doi = {10.1016/j.biosystems.2011.05.005}, pages = {130 -- 139}, year = {2011}, abstract = {Gas chromatography-mass spectrometry (GC-MS) profiles were generated from U87 glioma cells and human mesenchymal stem cells (hMSC). 37 metabolites representing glycolysis intermediates, TCA cycle metabolites, amino acids and lipids were selected for a detailed analysis. The concentrations of these. metabolites were compared and Pearson correlation coefficients were used to calculate the relationship between pairs of metabolites. Metabolite profiles and correlation patterns differ significantly between the two cell lines. These profiles can be considered as a signature of the underlying biochemical system and provide snap-shots of the metabolism in mesenchymal stem cells and tumor cells.}, language = {en} } @article{KehrHaebelBlechschmidtSchneideretal.1999, author = {Kehr, Julia and Haebel, Sophie and Blechschmidt-Schneider, Sabine and Willmitzer, Lothar and Steup, Martin and Fisahn, Joachim}, title = {Analysis of phloem protein patterns from different organs of Cucurbita maxima Duch. by matrix-assisted laser desorption/ionization time of flight mass spectroscopy combined with sodium dodecyl sufate-polyacryilamide gel electrophoresis}, year = {1999}, 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{LisecSteinfathMeyeretal.2009, author = {Lisec, Jan and Steinfath, Matthias and Meyer, Rhonda C. and Selbig, Joachim and Melchinger, Albrecht E. and Willmitzer, Lothar and Altmann, Thomas}, title = {Identification of heterotic metabolite QTL in Arabidopsis thaliana RIL and IL populations}, issn = {0960-7412}, doi = {10.1111/j.1365-313X.2009.03910.x}, year = {2009}, abstract = {Two mapping populations of a cross between the Arabidopsis thaliana accessions Col-0 and C24 were cultivated and analyzed with respect to the levels of 181 metabolites to elucidate the biological phenomenon of heterosis at the metabolic level. The relative mid-parent heterosis in the F-1 hybrids was <20\% for most metabolic traits. The first mapping population consisting of 369 recombinant inbred lines (RILs) and their test cross progeny with both parents allowed us to determine the position and effect of 147 quantitative trait loci (QTL) for metabolite absolute mid-parent heterosis (aMPH). Furthermore, we identified 153 and 83 QTL for augmented additive (Z(1)) and dominance effects (Z(2)), respectively. We identified putative candidate genes for these QTL using the ARACYC database (http://www.arabidopsis.org/ biocyc), and calculated the average degree of dominance, which was within the dominance and over-dominance range for most metabolites. Analyzing a second population of 41 introgression lines (ILs) and their test crosses with the recurrent parent, we identified 634 significant differences in metabolite levels. Nine per cent of these effects were classified as over-dominant, according to the mode of inheritance. A comparison of both approaches suggested epistasis as a major contributor to metabolite heterosis in Arabidopsis. A linear combination of metabolite levels was shown to significantly correlate with biomass heterosis (r = 0.62).}, language = {en} }