@article{KaltdorfSrivastavaGuptaetal.2016,
  author    = {Kaltdorf, Martin and Srivastava, Mugdha and Gupta, Shishir K. and Liang, Chunguang and Binder, Jasmin and Dietl, Anna-Maria and Meir, Zohar and Haas, Hubertus and Osherov, Nir and Krappmann, Sven and Dandekar, Thomas},
  title     = {Systematic Identification of Anti-Fungal Drug Targets by a Metabolic Network Approach},
  series = {Frontiers in Molecular Bioscience},
  volume    = {3},
  journal   = {Frontiers in Molecular Bioscience},
  doi       = {10.3389/fmolb.2016.00022},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147396},
  pages     = {22},
  year      = {2016},
  abstract  = {New antimycotic drugs are challenging to find, as potential target proteins may have close human orthologs. We here focus on identifying metabolic targets that are critical for fungal growth and have minimal similarity to targets among human proteins. We compare and combine here: (I) direct metabolic network modeling using elementary mode analysis and flux estimates approximations using expression data, (II) targeting metabolic genes by transcriptome analysis of condition-specific highly expressed enzymes, and (III) analysis of enzyme structure, enzyme interconnectedness ("hubs"), and identification of pathogen-specific enzymes using orthology relations. We have identified 64 targets including metabolic enzymes involved in vitamin synthesis, lipid, and amino acid biosynthesis including 18 targets validated from the literature, two validated and five currently examined in own genetic experiments, and 38 further promising novel target proteins which are non-orthologous to human proteins, involved in metabolism and are highly ranked drug targets from these pipelines.},
  language  = {en}
}
@article{LupianezVillaescusaCarvalhoetal.2016,
  author    = {Lupia{\~n}ez, Carmen B. and Villaescusa, Maria T. and Carvalho, Agostinho and Springer, Jan and Lackner, Michaela and S{\´a}nchez-Maldonado, Jos{\´e} M. and Canet, Luz M. and Cunha, Cristina and Segura-Catena, Joana and Alcazar-Fuoli, Laura and Solano, Carlos and Fianchi, Luana and Pagano, Livio and Potenza, Leonardo and Aguado, Jos{\´e} M. and Luppi, Mario and Cuenca-Estrella, Manuel and Lass-Fl{\"o}rl, Cornelia and Einsele, Hermann and V{\´a}zquez, Lourdes and R{\´i}os-Tamayo, Rafael and Loeffler, J{\"u}rgen and Jurado, Manuel and Sainz, Juan},
  title     = {Common Genetic Polymorphisms within NF kappa B-Related Genes and the Risk of Developing Invasive Aspergillosis},
  series = {Frontiers in Microbiology},
  volume    = {7},
  journal   = {Frontiers in Microbiology},
  number    = {1243},
  doi       = {10.3389/fmicb.2016.01243},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-165209},
  year      = {2016},
  abstract  = {Invasive Aspergillosis (IA) is an opportunistic infection caused by Aspergillus, a ubiquitously present airborne pathogenic mold. A growing number of studies suggest a major host genetic component in disease susceptibility. Here, we evaluated whether 14 single-nucleotide polymorphisms within NFκB1, NFκB2, RelA, RelB, Rel, and IRF4 genes influence the risk of IA in a population of 834 high-risk patients (157 IA and 677 non-IA) recruited through a collaborative effort involving the aspBIOmics consortium and four European clinical institutions. No significant overall associations between selected SNPs and the risk of IA were found in this large cohort. Although a hematopoietic stem cell transplantation (HSCT)-stratified analysis revealed that carriers of the IRF4rs12203592T/T genotype had a six-fold increased risk of developing the infection when compared with those carrying the C allele (ORREC = 6.24, 95\%CI 1.25-31.2, P = 0.026), the association of this variant with IA risk did not reach significance at experiment-wide significant threshold. In addition, we found an association of the IRF4AATC and IRF4GGTC haplotypes (not including the IRF4rs12203592T risk allele) with a decreased risk of IA but the magnitude of the association was similar to the one observed in the single-SNP analysis, which indicated that the haplotypic effect on IA risk was likely due to the IRF4rs12203592 SNP. Finally, no evidence of significant interactions among the genetic markers tested and the risk of IA was found. These results suggest that the SNPs on the studied genes do not have a clinically relevant impact on the risk of developing IA.},
  language  = {en}
}