@article{AlluSojaWuetal.2014,
  author    = {Allu, Annapurna Devi and Soja, Aleksandra Maria and Wu, Anhui and Szymanski, Jedrzej and Balazadeh, Salma},
  title     = {Salt stress and senescence: identification of cross-talk regulatory components},
  series = {Journal of experimental botany},
  volume    = {65},
  journal   = {Journal of experimental botany},
  number    = {14},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0022-0957},
  doi       = {10.1093/jxb/eru173},
  pages     = {3993 -- 4008},
  year      = {2014},
  abstract  = {Leaf senescence is an active process with a pivotal impact on plant productivity. It results from extensive signalling cross-talk coordinating environmental factors with intrinsic age-related mechanisms. Although many studies have shown that leaf senescence is affected by a range of external parameters, knowledge about the regulatory systems that govern the interplay between developmental programmes and environmental stress is still vague. Salinity is one of the most important environmental stresses that promote leaf senescence and thus affect crop yield. Improving salt tolerance by avoiding or delaying senescence under stress will therefore play an important role in maintaining high agricultural productivity. Experimental evidence suggests that hydrogen peroxide (H2O2) functions as a common signalling molecule in both developmental and salt-induced leaf senescence. In this study, microarray-based gene expression profiling on Arabidopsis thaliana plants subjected to long-term salinity stress to induce leaf senescence was performed, together with co-expression network analysis for H2O2-responsive genes that are mutually up-regulated by salt induced-and developmental leaf senescence. Promoter analysis of tightly co-expressed genes led to the identification of seven cis-regulatory motifs, three of which were known previously, namely CACGTGT and AAGTCAA, which are associated with reactive oxygen species (ROS)-responsive genes, and CCGCGT, described as a stress-responsive regulatory motif, while the others, namely ACGCGGT, AGCMGNC, GMCACGT, and TCSTYGACG were not characterized previously. These motifs are proposed to be novel elements involved in the H2O2-mediated control of gene expression during salinity stress-triggered and developmental senescence, acting through upstream transcription factors that bind to these sites.},
  language  = {en}
}
@phdthesis{Szymanski2009,
  author    = {Szymanski, Jedrzej},
  title     = {Integration of correlative relationships in metabolic and transcript data from model organisms : arabidopsis thaliana and escherichia coli},
  address   = {Potsdam},
  pages     = {XIII, 137 S. : graph. Darst.},
  year      = {2009},
  language  = {en}
}
@misc{SzymanskiJozefczukNikoloskietal.2009,
  author    = {Szymanski, Jedrzej and Jozefczuk, Szymon and Nikoloski, Zoran and Selbig, Joachim and Nikiforova, Victoria and Catchpole, Gareth and Willmitzer, Lothar},
  title     = {Stability of metabolic correlations under changing environmental conditions in Escherichia coli : a systems approach},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-45253},
  year      = {2009},
  abstract  = {Background: Biological systems adapt to changing environments by reorganizing their cellula r and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underl ying metabolic network. Methodology/Principal Findings: Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic conditiondependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple ob servation s about the changes of metabolic concentrations. The approach was tested with Escherichia colias a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diau xie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical path ways, and (3) ind ependently of the response scale, based on their importance in the reorganization of the cor relation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response. Conclusions/Significance: Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-ba sed approach does not rely on major changes in concentration to identify metabolites important for st ress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches.},
  language  = {en}
}