@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{SchwenderKoenigKlapperstuecketal.2014,
  author    = {Schwender, Joerg and Koenig, Christina and Klapperstueck, Matthias and Heinzel, Nicolas and Munz, Eberhard and Hebbelmann, Inga and Hay, Jordan O. and Denolf, Peter and De Bodt, Stefanie and Redestig, Henning and Caestecker, Evelyne and Jakob, Peter M. and Borisjuk, Ljudmilla and Rolletschek, Hardy},
  title     = {Transcript abundance on its own cannot be used to infer fluxes in central metabolism},
  series = {Frontiers in Plant Science},
  volume    = {5},
  journal   = {Frontiers in Plant Science},
  issn      = {1664-462X},
  doi       = {10.3389/fpls.2014.00668},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-114586},
  year      = {2014},
  abstract  = {An attempt has been made to define the extent to which metabolic flux in central plant metabolism is reflected by changes in the transcriptome and metabolome, based on an analysis of in vitro cultured immature embryos of two oilseed rape (Brassica napus) accessions which contrast for seed lipid accumulation. Metabolic flux analysis (MFA) was used to constrain a flux balance metabolic model which included 671 biochemical and transport reactions within the central metabolism. This highly confident flux information was eventually used for comparative analysis of flux vs. transcript (metabolite). Metabolite profiling succeeded in identifying 79 intermediates within the central metabolism, some of which differed quantitatively between the two accessions and displayed a significant shift corresponding to flux. An RNA-Seq based transcriptome analysis revealed a large number of genes which were differentially transcribed in the two accessions, including some enzymes/proteins active in major metabolic pathways. With a few exceptions, differential activity in the major pathways (glycolysis, TCA cycle, amino acid, and fatty acid synthesis) was not reflected in contrasting abundances of the relevant transcripts. The conclusion was that transcript abundance on its own cannot be used to infer metabolic activity/fluxes in central plant metabolism. This limitation needs to be borne in mind in evaluating transcriptome data and designing metabolic engineering experiments.},
  language  = {en}
}