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Growth Rate-Dependent Global Effects on Gene Expression in Bacteria
Open accessAbstract
Bacterial gene expression depends not only on specific regulatory mechanisms, but also on bacterial growth, because important global parameters such as the abundance of RNA polymerases and ribosomes are all growth-rate dependent. Understanding of these global effects is necessary for a quantitative understanding of gene regulation and for the design of synthetic genetic circuits. We find that the observed growth-rate dependence of constitutive gene expression can be explained by a simple model using the measured growth-rate dependence of the relevant cellular parameters. More complex growth dependencies for genetic circuits involving activators, repressors, and feedback control were analyzed and verified experimentally with synthetic circuits. Additional results suggest a feedback mechanism mediated by general growth-dependent effects that does not require explicit gene regulation if the expressed protein affects cell growth. This mechanism can lead to growth bistability and promote the acquisition of important physiological functions such as antibiotic resistance and tolerance (persistence).
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“In the simplest case, the total proteome is partitioned into a growth rate-independent fraction that may include negatively autoregulated housekeeping genes (Klumpp et al, 2009), and growth rate-dependent fractions, one for ribosomal and other translational proteins, and one for metabolic proteins, including transporters and catabolic and anabolic enzymes (Scott et al, 2010; Scott & Hwa, 2011).”
From Emergence of robust growth laws from optimal regulation of ribosome synthesis (2014) · cites this paper as Klumpp et al, 2009
In the citing paper
“Naively, one might expect modularity of cellular organization to insulate typical genetic circuits from the physiology of cell growth. This does not appear to be the case (Klumpp et al, 2009)”
From Emergence of robust growth laws from optimal regulation of ribosome synthesis (2014) · cites this paper as Klumpp et al, 2009
In the citing paper
“In fact, the bottom-up approach cannot even predict the growth rate dependence of gene expression from an unregulated (or “constitutive”) promoter, which is often taken as the reference state in the study of gene regulatory processes [see (Klumpp et al, 2009) for more discussion of the shortcomings of the bottom-up approach].”
From Emergence of robust growth laws from optimal regulation of ribosome synthesis (2014) · cites this paper as Klumpp et al, 2009
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Experiments in molecular genetics
Miller, J. H. (1972) · Medical Entomology and Zoology · Cited by 27,157
One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products.
Datsenko, K., & Wanner, B. (2000) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.120163297 · Cited by 15,902
Stochastic Gene Expression in a Single Cell
Elowitz, M. B., Levine, A. J., Siggia, E. D., & Swain, P. S. (2002) · Science · doi:10.1126/science.1070919 · Cited by 5,441
A synthetic oscillatory network of transcriptional regulators
Elowitz, M., & Leibler, S. (2000) · Nature · doi:10.1038/35002125 · Cited by 4,812
Construction of a genetic toggle switch in Escherichia coli
Gardner, T. S., Cantor, C. R., & Collins, J. J. (2000) · Nature · doi:10.1038/35002131 · Cited by 4,310
Network motifs in the transcriptional regulation network of Escherichia coli
Shen-Orr, S. S., Milo, R., Mangan, S., & Alon, U. S. (2002) · Nature Genetics · doi:10.1038/ng881 · Cited by 2,970
Bacterial Persistence as a Phenotypic Switch
Balaban, N. Q., Merrin, J., Chait, R., Kowalik, L., & Leibler, S. (2004) · Science · doi:10.1126/science.1099390 · Cited by 2,952
Culture Medium for Enterobacteria
Neidhardt, F. C., Bloch, P. L., & Smith, D. F. (1974) · Journal of Bacteriology · doi:10.1128/jb.119.3.736-747.1974 · Cited by 2,903
Lutz, R. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.6.1203 · Cited by 1,694
Molecular mechanisms that confer antibacterial drug resistance
Walsh, C. T. (2000) · Nature · doi:10.1038/35021219 · Cited by 1,579
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Research works printed but not linked: 1
- Willumsen, B.M. (1975). Expression of constitutive genes in E. coli as function of growth rate (M. Sc. Thesis, University of Copenhagen).
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Items 401–500 of 702
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Martin, Y., Page, M., Blanchet, C., & de Jong, H. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-2920-4 · Cited by 9
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York, P. S., Cummins, S. F., Lucas, T., Blomberg, S. P., Degnan, B. M., & Degnan, B. M. (2011) · Aquaculture · doi:10.1016/j.aquaculture.2011.12.019 · Cited by 9
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Quero, F. J., Aidelberg, G., Vielfaure, H., de Kermadec, Y. H., Cazaux, S., Pandi, A., Pascual-Garrigos, A., Arce, A., Sakyi, S. A., Gaudenz, U., et al. (2025) · PLoS Biology · doi:10.1371/journal.pbio.3003199 · Cited by 5
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Zhu, H., Xiong, Y., Jiang, Z., Liu, Q., & Wang, J. (2024) · Advanced Science · doi:10.1002/advs.202304548 · Cited by 4
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Metadata
- Authors
- Klumpp, S., Zhang, Z., & Hwa, T.
- Affiliations
- University of California San Diego (US)
- Corresponding author
- Klumpp, Stefan
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2009-12
- Volume
- 139
- Issue
- 7
- Pages
- 1366-1375
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC2818994
- OpenAlex
- W2115606218
- Cited by
- 703
- References
- 77
- Citations by year
- 2026: 47 · 2025: 41 · 2024: 37 · 2023: 40 · 2022: 54 · 2021: 36 · 2020: 44 · 2019: 48 · 2018: 53 · 2017: 36 · 2016: 40 · 2015: 53 · 2014: 47 · 2013: 51 · 2012: 34
- FWCI
- 10.21
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion)
- Max Planck Digital Library (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- National Institute of General Medical Sciences (R01GM077298, R01-GM77298)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Keywords
- bacterial growth rate, constitutive expression, synthetic gene circuits, ribosome abundance, feedback control, antibiotic resistance, antibiotic tolerance, persistence
- MeSH terms
- Escherichia coli, Homeostasis, Gene Expression Regulation, Bacterial, Feedback, Physiological, Regulatory Elements, Transcriptional, Gene Regulatory Networks
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