The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Large‐scale 13 C‐flux analysis reveals distinct transcriptional control of respiratory and fermentative metabolism in Escherichia coli
Open accessAbstract
Despite our increasing topological knowledge on regulation networks in model bacteria, it is largely unknown which of the many co-occurring regulatory events actually control metabolic function and the distribution of intracellular fluxes. Here, we unravel condition-dependent transcriptional control of Escherichia coli metabolism by large-scale (13)C-flux analysis in 91 transcriptional regulator mutants on glucose and galactose. In contrast to the canonical respiro-fermentative glucose metabolism, fully respiratory galactose metabolism depends exclusively on the phosphoenol-pyruvate (PEP)-glyoxylate cycle. While 2/3 of the regulators directly or indirectly affected absolute flux rates, the partitioning between different pathways remained largely stable with transcriptional control focusing primarily on the acetyl-CoA branch point. Flux distribution control was achieved by nine transcription factors on glucose, including ArcA, Fur, PdhR, IHF A and IHF B, but was exclusively mediated by the cAMP-dependent Crp regulation of the PEP-glyoxylate cycle flux on galactose. Five further transcription factors affected this flux only indirectly through cAMP and Crp by increasing the galactose uptake rate. Thus, E. coli actively limits its galactose catabolism at the expense of otherwise possible faster growth.
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Construction of Escherichia coli K‐12 in‐frame, single‐gene knockout mutants: the Keio collection
Baba, T., Ara, T., Hasegawa, M., Takai, Y., Okumura, Y., Baba, M., Datsenko, K. A., Tomita, M., Wanner, B. L., & Mori, H. (2006) · Molecular Systems Biology · doi:10.1038/msb4100050 · Cited by 7,858
The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli
Feist, A. M., & Palsson, B. Ø. (2008) · Nature Biotechnology · doi:10.1038/nbt1401 · Cited by 545 · cited 2×
“Key elements of such systems biology approaches are genome-scale models of metabolic stoichiometry (Feist and Palsson, 2008) and the detailed topology of transcriptional regulatory networks that describe all known interactions between transcription factors and their target genes (Gama-Castro et al,…”
Salgado, H. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj156 · Cited by 368
Cited by
Genome‐scale models of metabolism and gene expression extend and refine growth phenotype prediction
O'Brien, E. J., Lerman, J. A., Chang, R. L., Hyduke, D. R., & Palsson, B. Ø. (2013) · Molecular Systems Biology · doi:10.1038/msb.2013.52 · Cited by 471
Metabolic Fluxes in an Illuminated Arabidopsis Rosette
Szecowka, M., Heise, R., Tohge, T., Nunes-Nesi, A., Vosloh, D., Huege, J., Feil, R., Lunn, J., Nikoloski, Z., Stitt, M., et al. (2013) · The Plant Cell · doi:10.1105/tpc.112.106989 · Cited by 347
Pyruvate cycle increases aminoglycoside efficacy and provides respiratory energy in bacteria
Su, Y.-B., Peng, B., Li, H., Cheng, Z.-X., Zhang, T.-T., Zhu, J.-X., Li, D., Li, M.-Y., Ye, J.-Z., Du, C.-C., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1714645115 · Cited by 271
Khodayari, A., & Maranas, C. D. (2016) · Nature Communications · doi:10.1038/ncomms13806 · Cited by 230
Functioning of a metabolic flux sensor in Escherichia coli
Kochanowski, K., Volkmer, B., Gerosa, L., Haverkorn van Rijsewijk, B. R., Schmidt, A., & Heinemann, M. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1202582110 · Cited by 196
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Metadata
- Authors
- Haverkorn van Rijsewijk, B. R. B., Nanchen, A., Nallet, S., Kleijn, R. J., & Sauer, U.
- Venue
- Molecular Systems Biology
- Published
- 2011-01
- Volume
- 7
- Issue
- 1
- Pages
- 477-477
- ISSN
- 1744-4292 (ISSN-L)
- OpenAlex
- W2163433435
- Cited by
- 159
- References
- 3
- FWCI
- 7.52
- Type
- journal article
- Language
- en
- Open access
- gold
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