The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Condition-Dependent Cell Volume and Concentration of Escherichia coli to Facilitate Data Conversion for Systems Biology Modeling
Open accessAbstract
Systems biology modeling typically requires quantitative experimental data such as intracellular concentrations or copy numbers per cell. In order to convert population-averaging omics measurement data to intracellular concentrations or cellular copy numbers, the total cell volume and number of cells in a sample need to be known. Unfortunately, even for the often studied model bacterium Escherichia coli this information is hardly available and furthermore, certain measures (e.g. cell volume) are also dependent on the growth condition. In this work, we have determined these basic data for E. coli cells when grown in 22 different conditions so that respective data conversions can be done correctly. First, we determine growth-rate dependent cell volumes. Second, we show that in a 1 ml E. coli sample at an optical density (600 nm) of 1 the total cell volume is around 3.6 µl for all conditions tested. Third, we demonstrate that the cell number in a sample can be determined on the basis of the sample's optical density and the cells' growth rate. The data presented will allow for conversion of E. coli measurement data normalized to optical density into volumetric cellular concentrations and copy numbers per cell--two important parameters for systems biology model development.
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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
CellProfiler: image analysis software for identifying and quantifying cell phenotypes
Carpenter, A. E., Jones, T. R., Lamprecht, M. R., Clarke, C., Kang, I. H., Friman, O., Guertin, D. A., Chang, J. H., Lindquist, R. A., Moffat, J., et al. (2006) · Genome Biology · doi:10.1186/gb-2006-7-10-r100 · Cited by 5,157
Systems biology: a brief overview
Kitano, H. (2002) · Science · doi:10.1126/science.1069492 · Cited by 4,265
Schaechter, M., MaalOe, O., & Kjeldgaard, N. O. (1958) · Journal of General Microbiology · doi:10.1099/00221287-19-3-592 · Cited by 1,435
A comprehensive library of fluorescent transcriptional reporters for Escherichia coli
Zaslaver, A., Bren, A., Ronen, M., Itzkovitz, S., Kikoin, I., Shavit, S., Liebermeister, W., Surette, M. G., & Alon, U. (2006) · Nature Methods · doi:10.1038/nmeth895 · Cited by 777
Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics
Picotti, P., Bodenmiller, B., Mueller, L. N., Domon, B., & Aebersold, R. (2009) · Cell · doi:10.1016/j.cell.2009.05.051 · Cited by 744
Multiple High-Throughput Analyses Monitor the Response of E. coli to Perturbations
Ishii, N., Nakahigashi, K., Baba, T., Robert, M., Soga, T., Kanai, A., Hirasawa, T., Naba, M., Hirai, K., Hoque, A., et al. (2007) · Science · doi:10.1126/science.1132067 · Cited by 674
Just-in-time transcription program in metabolic pathways
Zaslaver, A., Mayo, A. E., Rosenberg, R., Bashkin, P., Sberro, H., Tsalyuk, M., Surette, M. G., & Alon, U. (2004) · Nature Genetics · doi:10.1038/ng1348 · Cited by 471
Loferer-Krößbacher, M., Klima, J., & Psenner, R. (1998) · Applied and Environmental Microbiology · doi:10.1128/aem.64.2.688-694.1998 · Cited by 406
Absolute quantitation of intracellular metabolite concentrations by an isotope ratio-based approach
Bennett, B. D., Yuan, J., Kimball, E. H., & Rabinowitz, J. D. (2008) · Nature Protocols · doi:10.1038/nprot.2008.107 · Cited by 384
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Venturelli, O. S., Carr, A. V., Fisher, G., Hsu, R. H., Lau, R., Bowen, B. P., Hromada, S., Northen, T., & Arkin, A. P. (2018) · Molecular Systems Biology · doi:10.15252/msb.20178157 · Cited by 544
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
Self-citationEscherichia coli achieves faster growth by increasing catalytic and translation rates of proteins
Valgepea, K., Adamberg, K., Seiman, A., & Vilu, R. (2013) · Molecular BioSystems · doi:10.1039/c3mb70119k · Cited by 145
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Metadata
- Authors
- Volkmer, B., & Heinemann, M.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2011-07-29
- Volume
- 6
- Issue
- 7
- Pages
- e23126
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2003409413
- Cited by
- 351
- References
- 30
- FWCI
- 7.17
- Type
- journal article
- Language
- en
- Open access
- gold
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