@article{YangRajeeveRudeletal.2019,
  author    = {Yang, Manli and Rajeeve, Karthika and Rudel, Thomas and Dandekar, Thomas},
  title     = {Comprehensive Flux Modeling of Chlamydia trachomatis Proteome and qRT-PCR Data Indicate Biphasic Metabolic Differences Between Elementary Bodies and Reticulate Bodies During Infection},
  series = {Frontiers in Microbiology},
  volume    = {10},
  journal   = {Frontiers in Microbiology},
  number    = {2350},
  issn      = {1664-302X},
  doi       = {10.3389/fmicb.2019.02350},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-189434},
  year      = {2019},
  abstract  = {Metabolic adaptation to the host cell is important for obligate intracellular pathogens such as Chlamydia trachomatis (Ct). Here we infer the flux differences for Ct from proteome and qRT-PCR data by comprehensive pathway modeling. We compare the comparatively inert infectious elementary body (EB) and the active replicative reticulate body (RB) systematically using a genome-scale metabolic model with 321 metabolites and 277 reactions. This did yield 84 extreme pathways based on a published proteomics dataset at three different time points of infection. Validation of predictions was done by quantitative RT-PCR of enzyme mRNA expression at three time points. Ct's major active pathways are glycolysis, gluconeogenesis, glycerol-phospholipid (GPL) biosynthesis (support from host acetyl-CoA) and pentose phosphate pathway (PPP), while its incomplete TCA and fatty acid biosynthesis are less active. The modeled metabolic pathways are much more active in RB than in EB. Our in silico model suggests that EB and RB utilize folate to generate NAD(P)H using independent pathways. The only low metabolic flux inferred for EB involves mainly carbohydrate metabolism. RB utilizes energy -rich compounds to generate ATP in nucleic acid metabolism. Validation data for the modeling include proteomics experiments (model basis) as well as qRT-PCR confirmation of selected metabolic enzyme mRNA expression differences. The metabolic modeling is made fully available here. Its detailed insights and models on Ct metabolic adaptations during infection are a useful modeling basis for future studies.},
  language  = {en}
}
@article{ZirkelCecilSchaeferetal.2012,
  author    = {Zirkel, J. and Cecil, A. and Sch{\"a}fer, F. and Rahlfs, S. and Ouedraogo, A. and Xiao, K. and Sawadogo, S. and Coulibaly, B. and Becker, K. and Dandekar, T.},
  title     = {Analyzing Thiol-Dependent Redox Networks in the Presence of Methylene Blue and Other Antimalarial Agents with RT-PCR-Supported in silico Modeling},
  series = {Bioinformatics and Biology Insights},
  volume    = {6},
  journal   = {Bioinformatics and Biology Insights},
  doi       = {10.4137/BBI.S10193},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-123751},
  pages     = {287-302},
  year      = {2012},
  abstract  = {BACKGROUND: In the face of growing resistance in malaria parasites to drugs, pharmacological combination therapies are important. There is accumulating evidence that methylene blue (MB) is an effective drug against malaria. Here we explore the biological effects of both MB alone and in combination therapy using modeling and experimental data. RESULTS: We built a model of the central metabolic pathways in P. falciparum. Metabolic flux modes and their changes under MB were calculated by integrating experimental data (RT-PCR data on mRNAs for redox enzymes) as constraints and results from the YANA software package for metabolic pathway calculations. Several different lines of MB attack on Plasmodium redox defense were identified by analysis of the network effects. Next, chloroquine resistance based on pfmdr/and pfcrt transporters, as well as pyrimethamine/sulfadoxine resistance (by mutations in DHF/DHPS), were modeled in silico. Further modeling shows that MB has a favorable synergism on antimalarial network effects with these commonly used antimalarial drugs. CONCLUSIONS: Theoretical and experimental results support that methylene blue should, because of its resistance-breaking potential, be further tested as a key component in drug combination therapy efforts in holoendemic areas.},
  language  = {en}
}