@article{TomeNaegeleAdamoetal.2014,
  author    = {Tome, Filipa and N{\"a}gele, Thomas and Adamo, Mattia and Garg, Abhroop and Marco-Ilorca, Carles and Nukarinen, Ella and Pedrotti, Lorenzo and Peviani, Alessia and Simeunovic, Andrea and Tatkiewicz, Anna and Tomar, Monika and Gamm, Magdalena},
  title     = {The low energy signaling network},
  series = {Frontiers in Plant Science},
  volume    = {5},
  journal   = {Frontiers in Plant Science},
  number    = {353},
  issn      = {1664-462X},
  doi       = {10.3389/fpls.2014.00353},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-115813},
  year      = {2014},
  abstract  = {Stress impacts negatively on plant growth and crop productivity, causing extensive losses to agricultural production worldwide. Throughout their life, plants are often confronted with multiple types of stress that affect overall cellular energy status and activate energy-saving responses. The resulting low energy syndrome (LES) includes transcriptional, translational, and metabolic reprogramming and is essential for stress adaptation. The conserved kinases sucrose-non-fermenting-1-related protein kinase-1 (SnRK1) and target of rapamycin (TOR) play central roles in the regulation of LES in response to stress conditions, affecting cellular processes and leading to growth arrest and metabolic reprogramming. We review the current understanding of how TOR and SnRK1 are involved in regulating the response of plants to low energy conditions. The central role in the regulation of cellular processes, the reprogramming of metabolism, and the phenotypic consequences of these two kinases will be discussed in light of current knowledge and potential future developments.},
  language  = {en}
}
@article{NukarinenNaegelePedrottietal.2016,
  author    = {Nukarinen, Ella and N{\"a}gele, Thomas and Pedrotti, Lorenzo and Wurzinger, Bernhard and Mair, Andrea and Landgraf, Ramona and B{\"o}rnke, Frederik and Hanson, Johannes and Teige, Markus and Baena-Gonzalez, Elena and Dr{\"o}ge-Laser, Wolfgang and Weckwerth, Wolfram},
  title     = {Quantitative phosphoproteomics reveals the role of the AMPK plant ortholog SnRK1 as a metabolic master regulator under energy deprivation},
  series = {Scientific Reports},
  volume    = {6},
  journal   = {Scientific Reports},
  number    = {31697},
  doi       = {10.1038/srep31697},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-167638},
  year      = {2016},
  abstract  = {Since years, research on SnRK1, the major cellular energy sensor in plants, has tried to define its role in energy signalling. However, these attempts were notoriously hampered by the lethality of a complete knockout of SnRK1. Therefore, we generated an inducible amiRNA::SnRK1α2 in a snrk1α1 knock out background (snrk1α1/α2) to abolish SnRK1 activity to understand major systemic functions of SnRK1 signalling under energy deprivation triggered by extended night treatment. We analysed the in vivo phosphoproteome, proteome and metabolome and found that activation of SnRK1 is essential for repression of high energy demanding cell processes such as protein synthesis. The most abundant effect was the constitutively high phosphorylation of ribosomal protein S6 (RPS6) in the snrk1α1/α2 mutant. RPS6 is a major target of TOR signalling and its phosphorylation correlates with translation. Further evidence for an antagonistic SnRK1 and TOR crosstalk comparable to the animal system was demonstrated by the in vivo interaction of SnRK1α1 and RAPTOR1B in the cytosol and by phosphorylation of RAPTOR1B by SnRK1α1 in kinase assays. Moreover, changed levels of phosphorylation states of several chloroplastic proteins in the snrk1α1/α2 mutant indicated an unexpected link to regulation of photosynthesis, the main energy source in plants.},
  language  = {en}
}
@article{NaglerNaegeleGillietal.2018,
  author    = {Nagler, Matthias and N{\"a}gele, Thomas and Gilli, Christian and Fragner, Lena and Korte, Arthur and Platzer, Alexander and Farlow, Ashley and Nordborg, Magnus and Weckwerth, Wolfram},
  title     = {Eco-Metabolomics and Metabolic Modeling: Making the Leap From Model Systems in the Lab to Native Populations in the Field},
  series = {Frontiers in Plant Science},
  volume    = {9},
  journal   = {Frontiers in Plant Science},
  number    = {1556},
  issn      = {1664-462X},
  doi       = {10.3389/fpls.2018.01556},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-189560},
  year      = {2018},
  abstract  = {Experimental high-throughput analysis of molecular networks is a central approach to characterize the adaptation of plant metabolism to the environment. However, recent studies have demonstrated that it is hardly possible to predict in situ metabolic phenotypes from experiments under controlled conditions, such as growth chambers or greenhouses. This is particularly due to the high molecular variance of in situ samples induced by environmental fluctuations. An approach of functional metabolome interpretation of field samples would be desirable in order to be able to identify and trace back the impact of environmental changes on plant metabolism. To test the applicability of metabolomics studies for a characterization of plant populations in the field, we have identified and analyzed in situ samples of nearby grown natural populations of Arabidopsis thaliana in Austria. A. thaliana is the primary molecular biological model system in plant biology with one of the best functionally annotated genomes representing a reference system for all other plant genome projects. The genomes of these novel natural populations were sequenced and phylogenetically compared to a comprehensive genome database of A. thaliana ecotypes. Experimental results on primary and secondary metabolite profiling and genotypic variation were functionally integrated by a data mining strategy, which combines statistical output of metabolomics data with genome-derived biochemical pathway reconstruction and metabolic modeling. Correlations of biochemical model predictions and population-specific genetic variation indicated varying strategies of metabolic regulation on a population level which enabled the direct comparison, differentiation, and prediction of metabolic adaptation of the same species to different habitats. These differences were most pronounced at organic and amino acid metabolism as well as at the interface of primary and secondary metabolism and allowed for the direct classification of population-specific metabolic phenotypes within geographically contiguous sampling sites.},
  language  = {en}
}