@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{LiangRiosMiguelJaricketal.2021,
  author    = {Liang, Chunguang and Rios-Miguel, Ana B. and Jarick, Marcel and Neurgaonkar, Priya and Girard, Myriam and Fran{\c{c}}ois, Patrice and Schrenzel, Jacques and Ibrahim, Eslam S. and Ohlsen, Knut and Dandekar, Thomas},
  title     = {Staphylococcus aureus transcriptome data and metabolic modelling investigate the interplay of Ser/Thr kinase PknB, its phosphatase Stp, the glmR/yvcK regulon and the cdaA operon for metabolic adaptation},
  series = {Microorganisms},
  volume    = {9},
  journal   = {Microorganisms},
  number    = {10},
  issn      = {2076-2607},
  doi       = {10.3390/microorganisms9102148},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-248459},
  year      = {2021},
  abstract  = {Serine/threonine kinase PknB and its corresponding phosphatase Stp are important regulators of many cell functions in the pathogen S. aureus. Genome-scale gene expression data of S. aureus strain NewHG (sigB\(^+\)) elucidated their effect on physiological functions. Moreover, metabolic modelling from these data inferred metabolic adaptations. We compared wild-type to deletion strains lacking pknB, stp or both. Ser/Thr phosphorylation of target proteins by PknB switched amino acid catabolism off and gluconeogenesis on to provide the cell with sufficient components. We revealed a significant impact of PknB and Stp on peptidoglycan, nucleotide and aromatic amino acid synthesis, as well as catabolism involving aspartate transaminase. Moreover, pyrimidine synthesis was dramatically impaired by stp deletion but only slightly by functional loss of PknB. In double knockouts, higher activity concerned genes involved in peptidoglycan, purine and aromatic amino acid synthesis from glucose but lower activity of pyrimidine synthesis from glucose compared to the wild type. A second transcriptome dataset from S. aureus NCTC 8325 (sigB\(^-\)) validated the predictions. For this metabolic adaptation, PknB was found to interact with CdaA and the yvcK/glmR regulon. The involved GlmR structure and the GlmS riboswitch were modelled. Furthermore, PknB phosphorylation lowered the expression of many virulence factors, and the study shed light on S. aureus infection processes.},
  language  = {en}
}
@article{AmpattuHagmannLiangetal.2017,
  author    = {Ampattu, Biju Joseph and Hagmann, Laura and Liang, Chunguang and Dittrich, Marcus and Schl{\"u}ter, Andreas and Blom, Jochen and Krol, Elizaveta and Goesmann, Alexander and Becker, Anke and Dandekar, Thomas and M{\"u}ller, Tobias and Schoen, Christoph},
  title     = {Transcriptomic buffering of cryptic genetic variation contributes to meningococcal virulence},
  series = {BMC Genomics},
  volume    = {18},
  journal   = {BMC Genomics},
  number    = {282},
  doi       = {10.1186/s12864-017-3616-7},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-157534},
  year      = {2017},
  abstract  = {Background: Commensal bacteria like Neisseria meningitidis sometimes cause serious disease. However, genomic comparison of hyperinvasive and apathogenic lineages did not reveal unambiguous hints towards indispensable virulence factors. Here, in a systems biological approach we compared gene expression of the invasive strain MC58 and the carriage strain α522 under different ex vivo conditions mimicking commensal and virulence compartments to assess the strain-specific impact of gene regulation on meningococcal virulence. Results: Despite indistinguishable ex vivo phenotypes, both strains differed in the expression of over 500 genes under infection mimicking conditions. These differences comprised in particular metabolic and information processing genes as well as genes known to be involved in host-damage such as the nitrite reductase and numerous LOS biosynthesis genes. A model based analysis of the transcriptomic differences in human blood suggested ensuing metabolic flux differences in energy, glutamine and cysteine metabolic pathways along with differences in the activation of the stringent response in both strains. In support of the computational findings, experimental analyses revealed differences in cysteine and glutamine auxotrophy in both strains as well as a strain and condition dependent essentiality of the (p)ppGpp synthetase gene relA and of a short non-coding AT-rich repeat element in its promoter region. Conclusions: Our data suggest that meningococcal virulence is linked to transcriptional buffering of cryptic genetic variation in metabolic genes including global stress responses. They further highlight the role of regulatory elements for bacterial virulence and the limitations of model strain approaches when studying such genetically diverse species as N. meningitidis.},
  language  = {en}
}