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Growth Rate-Dependent Global Effects on Gene Expression in Bacteria
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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 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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“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
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“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
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Cites
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. A., & Wanner, B. L. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.120163297 · Cited by 14,881
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
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 501–600 of 702
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Lam, N. M., Tsang, T. F., Qu, J., Tsang, M. W., Tao, Y., Kan, C. H., Zou, Q., Chan, K. H., Chu, A. J., Ma, C., et al. (2024) · Applied and Environmental Microbiology · doi:10.1128/aem.00717-24 · Cited by 3
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Zhou, H., Zhang, Z., Velo, J., Huo, J., Smith, S., Ho, A., & Saier, M. H. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf172 · Cited by 3
Self-citationUnderstanding the development of bacterial colony: Physiology, new technology, and modeling
Zhu, J., Chu, P., & Fu, X. (2025) · Quantitative Biology · doi:10.1002/qub2.95 · Cited by 5
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Excitable dynamics through toxin-induced mRNA cleavage in bacteria
Vet, S., Vandervelde, A., & Gelens, L. (2019) · PLoS ONE · doi:10.1371/journal.pone.0212288 · Cited by 3
Recent Progress in DNA Parts Standardization and Characterization
Deb, S. S., & Reshamwala, S. M. S. (2020) · Springer eBooks · doi:10.1007/978-981-15-0081-7_4 · Cited by 3
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Phan, T., He, C., Loladze, I., Prater, C., Elser, J. J., & Kuang, Y. (2022) · Heliyon · doi:10.1016/j.heliyon.2022.e09820 · Cited by 3
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Rostain, W., Landrain, T. E., Rodrigo, G., & Jaramillo, A. (2014) · Methods in molecular biology · doi:10.1007/978-1-4939-1878-2_4 · Cited by 3
Malakar, P. (2015) · The Open Microbiology Journal · doi:10.2174/1874285801509010008 · Cited by 3
Protocol for the Standardisation of Transcriptional Measurements
Hirst, C. D., Ainsworth, C., Baldwin, G. S., Kitney, R. I., & Freemont, P. S. (2015) · Springer protocols handbooks/Springer protocols · doi:10.1007/8623_2015_148 · Cited by 3
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Baetica, A.-A., Leong, Y. P., Olsman, N., & Murray, R. M. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/455493 · Cited by 3
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Microbial competition reduces interaction distances to the low µm-rangePreprint
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The role of division stochasticity on the robustness of bacterial size dynamicsPreprint
Nieto, C., Arias-Castro, J. C., Sánchez, C. M., Vargas-García, C. A., Singh, A., & Pedraza, J. M. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.07.27.501776 · Cited by 3
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Kong, L.-W., Shi, W., Tian, X., & Lai, Y. (2023) · eLife · doi:10.7554/elife.89170 · Cited by 3
Evolutionary barriers to horizontal gene transfer in macrophage-associatedSalmonella
Bhatia, R. P., Kirit, H. A., Lewis, C. M., Sankaranarayanan, K., & Bollback, J. P. (2023) · Evolution Letters · doi:10.1093/evlett/qrad020 · Cited by 3
Energy Aware Technology Mapping of Genetic Logic Circuits
Kubaczka, E., Gehri, M., Marlhens, J. J. M., Schwarz, T., Molderings, M., Engelmann, N., García, H. G., Hochberger, C., & Koeppl, H. (2024) · bioRxiv · doi:10.1021/acssynbio.4c00395 · Cited by 2
Momin, H., Appukuttan, D., & Venkatesh, K. V. (2025) · Microbial Cell Factories · doi:10.1186/s12934-025-02658-4 · Cited by 2
Spratt, M. R., & Lane, K. M. (2026) · Current Biology · doi:10.1016/j.cub.2026.06.001 · Cited by 3
Park, J., Chang, S., Kang, H., Yi, S., Jang, I.-H., Lee, K.-A., Kim, D.-H., & Kim, J. (2025) · Journal of Microbiology and Biotechnology · doi:10.4014/jmb.2503.07031 · Cited by 2
Bistability in type I toxin-antitoxin systems may lead to stress-induced persister formation
Marković, S. S., Djordjevic, M., Ou, H., & Djordjevic, M. (2025) · npj Systems Biology and Applications · doi:10.1038/s41540-025-00639-2 · Cited by 2
Modeling periodic transcriptions in tandem gene systems
Wu, W., Tan, S., Tang, M., & Sun, Q. (2026) · Mathematical Biosciences · doi:10.1016/j.mbs.2026.109648 · Cited by 2
Shape-dependent bounds on cell growth rates
Landy, J. (2014) · Europhysics Letters (EPL) · doi:10.1209/0295-5075/105/68002 · Cited by 2
Sources of stochasticity in constitutive and autoregulated gene expression
Marathe, R., Gomez, D., & Klumpp, S. (2012) · Physica Scripta · doi:10.1088/0031-8949/2012/t151/014068 · Cited by 2
Self-citationHoffmann, M., & Galle, J. (2018) · npj Systems Biology and Applications · doi:10.1038/s41540-018-0049-0 · Cited by 2
Ecological Adaptability of Bacillus to Extreme Oligotrophy in the Cuatro Cienegas Basin
Valdivia-Anistro, J. A., Eguiarte, L. E., & Souza, V. (2018) · Cuatro ciénegas basin: an endangered hyperdiverse oasis · doi:10.1007/978-3-319-95855-2_9 · Cited by 2
Ab initio scaling laws between noise and mean of gene expression
Rodrigo, G. (2019) · Physical review. E · doi:10.1103/physreve.100.032415 · Cited by 2
Chakraborty, P., & Ghosh, S. (2021) · IEEE India Conference · doi:10.1109/indicon52576.2021.9691638 · Cited by 2
Dimitriou, N. M., Demirag, E., Strati, K., & Mitsis, G. D. (2023) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2023.107920 · Cited by 2
Carta, A., Madalena Chaves, A., & Gouzé, J. (2013) · IFAC Proceedings Volumes · doi:10.3182/20130904-3-fr-2041.00140 · Cited by 2
Neves, D., Liebal, U. W., Nies, S. C., Alter, T. B., Pitzler, C., Blank, L. M., & Ebert, B. E. (2023) · ACS Synthetic Biology · doi:10.1021/acssynbio.3c00084 · Cited by 2
Techasuwanphorn, P., Wattanachaisaereekul, S., Jullawateelert, J., Plongthongkum, N., Jangbua, P., & Waraho‐Zhmayev, D. (2019) · Biomedical Engineering International Conference · doi:10.1109/bmeicon47515.2019.8990262 · Cited by 2
Hands-free control of heterologous gene expression in batch culturesPreprint
Borkowski, O., Endy, D., & Subsoontorn, P. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/150375 · Cited by 2
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Silva, M. A. M., Matúte, T., Núñez, I., Valdes, A., Ruiz, C. A., Peña, G. A. V., Federici, F., & Rudge, T. J. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/590299 · Cited by 2
An analytical theory of balanced cellular growthPreprint
Dourado, H., & Lercher, M. J. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/607374 · Cited by 2
Cell fate determination by Lamarckian molecule-inheritance and chancePreprint
Bruggeman, F. J., Schouten, J., de Groot, D. H., & Planqué, R. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/618199 · Cited by 2
Iyer, M. S., Pal, A., Srinivasan, S., Somvanshi, P. R., & Venkatesh, K. V. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.17.209353 · Cited by 2
Systemic IgG repertoire as a biomarker for translocating gut microbiota membersPreprint
Vujkovic-Cvijin, I., Welles, H. C., Ha, C. W. Y., Huq, L., Mistry, S., Brenchley, J. M., Trinchieri, G., Devkota, S., & Belkaid, Y. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.08.17.456549 · Cited by 2
Igler, C., Fourcade, C., Waldminghaus, T., Pauler, F. M., Santhanam, B., Tkačik, G., & Guet, C. C. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.20.465141 · Cited by 2
Declining old pole physiology gradually enhances gene expression asymmetry in bacteriaPreprint
Proenca, A. M., Tuğrul, M., Nath, A., & Steiner, U. K. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.07.552301 · Cited by 2
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Ren, Z., Weyer, H., Würthner, L., Li, D., Sou, C., Villarreal, D., Frey, E., & Jun, S. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.15.553443 · Cited by 2
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Kong, L.-W., Shi, W., Tian, X., & Lai, Y. (2023) · eLife · doi:10.7554/elife.89170.1 · Cited by 2
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Reding, C. (2022) · ISME Communications · doi:10.1038/s43705-022-00186-5 · Cited by 1
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Ewert, M., Nunn, B. L., Firth, E., & Junge, K. (2025) · Microorganisms · doi:10.3390/microorganisms13020251 · Cited by 1
Tiara, A., Nurjanah, S., & Wulandari, Z. (2025) · Jurnal Teknologi dan Industri Pangan · doi:10.6066/jtip.2025.36.1.40 · Cited by 1
Mu, X., Schmitz, A. C., Ding, Z., Li, W., Singh, A., & Zhang, F. (2025) · Nature Communications · doi:10.1038/s41467-025-67733-1 · Cited by 1
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Choudhary, D., & Vincent, M. S. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.116966 · Cited by 1
Transcriptional competition biases the effects of second messengers in Escherichia coli
Ripamonti, A., Lacassin, M., Droghetti, R., Bokinsky, G., & Lagomarsino, M. C. (2026) · Cell Systems · doi:10.1016/j.cels.2026.101609 · Cited by 1
Baumann, C. T., Hydorn, M. A., Cooke, S. F., Dworkin, J. E., & Rosenthal, A. Z. (2026) · Science Advances · doi:10.1126/sciadv.adz1707 · Cited by 1
Limits and frontiers of microbial phenotype measurements
Caro, T. A., Schaible, G. A., Cremer, J., Haruta, S., & Shou, W. (2026) · Current Opinion in Microbiology · doi:10.1016/j.mib.2026.102822 · Cited by 1
Sidarta, M., Baruah, L., Skúoy, P. H. Ú., Schäfer, A.-B., Johnsson, O., Frisk, E., Didelot, P., Andrekson, L., & Wenzel, M. (2026) · Microbiology Spectrum · doi:10.1128/spectrum.01532-26 · Cited by 1
Mechanisms and economy of molecular machines
Klumpp, S. (2012) · Physica Scripta · doi:10.1088/0031-8949/2012/t151/014066 · Cited by 1
Self-citationvon Wulffen, J., Buchholz, P. C. F., Sawodny, O., & Feuer, R. (2015) · IEEE International Conference on Bioinformatics and Bioengineering (BIBE) · doi:10.1109/bibe.2015.7367691 · Cited by 1
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Lunz, D., & Bonnans, J. F. (2023) · SIAM Journal on Applied Mathematics · doi:10.1137/22m1476113 · Cited by 1
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Dannenberg, S., Penning, J., Simm, A., & Klumpp, S. (2023) · Journal of Bacteriology · doi:10.1128/jb.00047-23 · Cited by 1
Self-citationYang, X., Yang, J., Huang, H., Yan, X., Li, X., & Lin, Z. (2024) · Synthetic and Systems Biotechnology · doi:10.1016/j.synbio.2024.04.003 · Cited by 1
Du, M., Scarpelli, A., Younger, A. K. D., Bates, D. G., & Leonard, J. N. (2016) · ACS Synthetic Biology · doi:10.1021/acssynbio.5b00217 · Cited by 1
Graovac, S., Rodic, A., Djordjevic, M., Severinov, K., & Djordjević, M. (2019) · Molecules · doi:10.3390/molecules24010198 · Cited by 1
Dissecting cell-size control strategies through stochastic processes
Nieto, C., Vargas-García, C. A., & Pedraza, J. M. (2019) · IEEE Colombian Conference on Automatic Control (CCAC) · doi:10.1109/ccac.2019.8921329 · Cited by 1
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Nikolados, E.-M., Weiße, A. Y., & Oyarzún, D. A. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1032-9_13 · Cited by 1
[Advances in synthetic physiology of artificial genetic parts].
Ji, X., Zhao, H., & Lou, C. (2017) · PubMed · doi:10.13345/j.cjb.170008 · Cited by 1
Kaneko, K., & Furusawa, C. (2021) · Springer eBooks · doi:10.1007/978-3-030-71737-7_3 · Cited by 1
How Do Bacteria Maximize Their Cellular Assets?
Kim, J. (2021) · Microbiology and Biotechnology Letters · doi:10.48022/mbl.2110.10010 · Cited by 1
Vinas, N. (2015) · TigerPrints (Clemson University) · Cited by 1
Kocharunchitt, C. (2012) · UTAS Research Repository · doi:10.25959/23207264 · Cited by 1
Zhao, X. (2018) · ERA: Education and Research Archive (University of Alberta) · doi:10.7939/r3mw28w80 · Cited by 1
Walker, C., Ryu, S., Giannone, R. J., Garcia, S., & Trinh, C. T. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/753525 · Cited by 1
Ali, M. Z., Parisutham, V., Choubey, S., & Brewster, R. C. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/865527 · Cited by 1
Accurate reconstruction of dynamic gene expression and growth rate profiles from noisy measurementsPreprint
Vidal, G., Vidal-Céspedes, C., & Rudge, T. J. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.16.435606 · Cited by 1
Transcriptional regulation of central metabolism in Escherichia coli
van Rijsewijk, B. R. B. H. (2012) · Repository for Publications and Research Data (ETH Zurich) · doi:10.3929/ethz-a-007196085 · Cited by 1
Robustness of DNA Looping Across Multiple Divisions in Individual BacteriaPreprint
Chang, C., Garcia-Alcala, M., Saiz, L., Vilar, J. M. G., & Cluzel, P. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.12.28.474367 · Cited by 1
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Almeida, B. L. B., Bahrudeen, M. N. M., Chauhan, V., Dash, S., Kandavalli, V. K., Häkkinen, A., Lloyd‐Price, J., Palma, C. S. D., Baptista, I. S. C., Gupta, A., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.07.483226 · Cited by 1
Prazeres, D. M. F. (2011) · doi:10.1002/9780470939918.ch13 · Cited by 1
Long-term history dependence of growth rates of E. coli after nutrient shiftsPreprint
Christodoulou, D., Mukherjee, A., Wegmann, R., Pagano, A., Sharma, V., Linker, S. M., Chang, Y., Palme, J., Sauer, U., & Basan, M. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.22.554350 · Cited by 1
Stevanovic, M., Carvalho, J. P. T., Bittihn, P., & Schultz, D. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.09.22.558994 · Cited by 1
Ritz, D., Martin, R., Bush, M., Villagrana, J., Deng, Y., & Schultz, D. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.20.614194 · Cited by 1
Chaguza, C., Arends, D. W., Lo, S. W., Putri, I. H., York, A., Lees, J. A., Wyllie, A. L., Weinberger, D. M., Bentley, S. D., de Jonge, M. I., et al. (2025) · eLife · doi:10.7554/elife.105555 · Cited by 2
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Kucharova, V. (2012) · NORA - Norwegian Open Research Archives · Cited by 1
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Roychoudhury, A., Pincus, D., & Mani, M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.08.15.744912 · Cited by 1
DETERMINING THE GENOTYPE-PHENOTYPE CONNECTION IN SYNTHETIC INDUCIBLE GENE EXPRESSION SYSTEMS
Adams, R. (2012) · Digital Commons-TMC (Texas Medical Center)
Alfitouri, A. D. (2012) · Nottingham ePrints (University of Nottingham)
Harnessing Saccharomyces cerevisiae Genetics for Cell Engineering
Wingler, L. M. (2011) · doi:10.7916/d8ff40p1
Distributional Fingerprinting of Cell Population Phenotypes and Drug Activities
Li, B. (2015) · DukeSpace (Duke University)
AUTOMATIC COMPUTATIONAL DESIGN OF SYNTHETIC GENOMES
Carrera, J. (2012) · RiuNet (Universitat Politècnica de València) · doi:10.4995/thesis/10251/35380
Flux balance analysis to model microbial metabolism for electricity generation
Mao, L. (2013) · Lincoln University Research Archive (Lincoln University)
Multiple unnecessary protein sources and cost to growth rate in E. coli
Bruneaux, L. (2013) · Digital Access to Scholarship at Harvard (DASH) (Harvard University)
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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