A universal trade-off between growth and lag in fluctuating environments.


Journal

Nature
ISSN: 1476-4687
Titre abrégé: Nature
Pays: England
ID NLM: 0410462

Informations de publication

Date de publication:
08 2020
Historique:
received: 04 04 2018
accepted: 21 04 2020
pubmed: 17 7 2020
medline: 15 9 2020
entrez: 17 7 2020
Statut: ppublish

Résumé

The rate of cell growth is crucial for bacterial fitness and drives the allocation of bacterial resources, affecting, for example, the expression levels of proteins dedicated to metabolism and biosynthesis

Identifiants

pubmed: 32669712
doi: 10.1038/s41586-020-2505-4
pii: 10.1038/s41586-020-2505-4
pmc: PMC7442741
mid: NIHMS1586769
doi:

Substances chimiques

Acetates 0
Glucose IY9XDZ35W2

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

470-474

Subventions

Organisme : NIGMS NIH HHS
ID : R01 GM095903
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM109069
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM118850
Pays : United States
Organisme : NIGMS NIH HHS
ID : R35 GM136412
Pays : United States

Commentaires et corrections

Type : CommentIn

Références

Scott, M., Gunderson, C. W., Mateescu, E. M., Zhang, Z. & Hwa, T. Interdependence of cell growth and gene expression: origins and consequences. Science 330, 1099–1102 (2010).
pubmed: 21097934
Basan, M. et al. Overflow metabolism in Escherichia coli results from efficient proteome allocation. Nature 528, 99–104 (2015).
pubmed: 26632588 pmcid: 4843128
Hui, S. et al. Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria. Mol. Syst. Biol. 11, 784 (2015).
pubmed: 25678603 pmcid: 4358657
LaCroix, R. A. et al. Use of adaptive laboratory evolution to discover key mutations enabling rapid growth of Escherichia coli K-12 MG1655 on glucose minimal medium. Appl. Environ. Microbiol. 81, 17–30 (2015).
pubmed: 25304508
Utrilla, J. et al. Global rebalancing of cellular resources by pleiotropic point mutations illustrates a multi-scale mechanism of adaptive evolution. Cell Syst. 2, 260–271 (2016).
pubmed: 27135538 pmcid: 4853925
O’Brien, E. J., Utrilla, J. & Palsson, B. O. Quantification and classification of E. coli proteome utilization and unused protein costs across environments. PLOS Comput. Biol. 12, e1004998 (2016).
pubmed: 27351952 pmcid: 4924638
Towbin, B. D. et al. Optimality and sub-optimality in a bacterial growth law. Nat. Commun. 8, 14123 (2017).
pubmed: 28102224 pmcid: 5253639
Schuetz, R., Zamboni, N., Zampieri, M., Heinemann, M. & Sauer, U. Multidimensional optimality of microbial metabolism. Science 336, 601–604 (2012).
pubmed: 22556256
Shoval, O. et al. Evolutionary trade-offs, Pareto optimality, and the geometry of phenotype space. Science 336, 1157–1160 (2012).
pubmed: 22539553
Tendler, A., Mayo, A. & Alon, U. Evolutionary tradeoffs, Pareto optimality and the morphology of ammonite shells. BMC Syst. Biol. 9, 12 (2015).
pubmed: 25884468 pmcid: 4404009
Reimers, A.-M., Knoop, H., Bockmayr, A. & Steuer, R. Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth. Proc. Natl Acad. Sci. USA 114, E6457–E6465 (2017).
pubmed: 28720699
Kotte, O., Volkmer, B., Radzikowski, J. L. & Heinemann, M. Phenotypic bistability in Escherichia coli’s central carbon metabolism. Mol. Syst. Biol. 10, 736 (2014).
pubmed: 24987115 pmcid: 4299493
Baranyi, J. & Roberts, T. A. A dynamic approach to predicting bacterial growth in food. Int. J. Food Microbiol. 23, 277–294 (1994).
pubmed: 7873331
You, C. et al. Coordination of bacterial proteome with metabolism by cyclic AMP signalling. Nature 500, 301–306 (2013).
pubmed: 23925119 pmcid: 4038431
Erickson, D. W. et al. A global resource allocation strategy governs growth transition kinetics of Escherichia coli. Nature 551, 119–123 (2017).
pubmed: 29072300 pmcid: 5901684
Zwaig, N. & Lin, E. C. C. Feedback inhibition of glycerol kinase, a catabolic enzyme in Escherichia coli. Science 153, 755–757 (1966).
pubmed: 5328677
Pettigrew, D. W., Liu, W. Z., Holmes, C., Meadow, N. D. & Roseman, S. A single amino acid change in Escherichia coli glycerol kinase abolishes glucose control of glycerol utilization in vivo. J. Bacteriol. 178, 2846–2852 (1996).
pubmed: 8631672 pmcid: 178019
Lin, E. C. C. Glycerol dissimilation and its regulation in bacteria. Annu. Rev. Microbiol. 30, 535–578 (1976).
pubmed: 825019
Freedberg, W. B., Kistler, W. S. & Lin, E. C. Lethal synthesis of methylglyoxal by Escherichia coli during unregulated glycerol metabolism. J. Bacteriol. 108, 137–144 (1971).
pubmed: 4941552 pmcid: 247042
Goelzer, A. et al. Quantitative prediction of genome-wide resource allocation in bacteria. Metab. Eng. 32, 232–243 (2015).
pubmed: 26498510
Maarleveld, T. R., Wortel, M. T., Olivier, B. G., Teusink, B. & Bruggeman, F. J. Interplay between constraints, objectives, and optimality for genome-scale stoichiometric models. PLoS Comput. Biol. 11, e1004166 (2015).
pubmed: 25849486 pmcid: 4388735
O’Brien, E. J., Lerman, J. A., Chang, R. L., Hyduke, D. R. & Palsson, B. O. Genome-scale models of metabolism and gene expression extend and refine growth phenotype prediction. Mol. Syst. Biol. 9, 693 (2013).
pubmed: 24084808 pmcid: 3817402
Yi, X. & Dean, A. M. Phenotypic plasticity as an adaptation to a functional trade-off. eLife 5, e19307 (2016).
pubmed: 27692064 pmcid: 5072838
Fraebel, D. T. et al. Environment determines evolutionary trajectory in a constrained phenotypic space. eLife 6, e24669 (2017).
pubmed: 28346136 pmcid: 5441876
Vasi, F. K. & Lenski, R. E. Ecological strategies and fitness tradeoffs in Escherichia coli mutants adapted to prolonged starvation. J. Genet. 78, 43–49 (1999).
Rozen, D. E., Philippe, N., Arjan de Visser, J., Lenski, R. E. & Schneider, D. Death and cannibalism in a seasonal environment facilitate bacterial coexistence. Ecol. Lett. 12, 34–44 (2009).
pubmed: 19019196
Ying, B.-W. et al. Evolutionary consequence of a trade-off between growth and maintenance along with ribosomal damages. PLoS ONE 10, e0135639 (2015).
pubmed: 26292224 pmcid: 4546238
Brown, S. D. & Jun, S. Complete genome sequence of Escherichia coli NCM3722. Genome Announc. 3, e00879-15 (2015).
pubmed: 26251500 pmcid: 4541272
Klumpp, S., Zhang, Z. & Hwa, T. Growth rate-dependent global effects on gene expression in bacteria. Cell 139, 1366–1375 (2009).
pubmed: 20064380 pmcid: 2818994
Datsenko, K. A. & Wanner, B. L. One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proc. Natl Acad. Sci. USA 97, 6640–6645 (2000).
pubmed: 10829079
Saka, K. et al. A complete set of Escherichia coli open reading frames in mobile plasmids facilitating genetic studies. DNA Res. 12, 63–68 (2005).
pubmed: 16106753
Baba, T. et al. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Mol. Syst. Biol. 2, 2006.0008 (2006).
pubmed: 16738554 pmcid: 1681482
Thomason, L. C., Costantino, N. & Court, D. L. E. coli genome manipulation by P1 transduction. Curr. Protoc. Mol. Biol. 1.17.1–1.17.8 (2007).
Okumus, B. et al. Mechanical slowing-down of cytoplasmic diffusion allows in vivo counting of proteins in individual cells. Nat. Commun. 7, 11641 (2016).
pubmed: 27189321 pmcid: 4873973
Soupene, E. et al. Physiological studies of Escherichia coli strain MG1655: growth defects and apparent cross-regulation of gene expression. J. Bacteriol. 185, 5611–5626 (2003).
pubmed: 12949114 pmcid: 193769
Lyons, E., Freeling, M., Kustu, S. & Inwood, W. Using genomic sequencing for classical genetics in E. coli K12. PLoS ONE 6, e16717 (2011).
pubmed: 21364914 pmcid: 3045373
Csonka, L. N., Ikeda, T. P., Fletcher, S. A. & Kustu, S. The accumulation of glutamate is necessary for optimal growth of Salmonella typhimurium in media of high osmolality but not induction of the proU operon. J. Bacteriol. 176, 6324–6333 (1994).
pubmed: 7929004 pmcid: 196974
Hirsch, J. P. & Henry, S. A. Expression of the Saccharomyces cerevisiae inositol-1-phosphate synthase (INO1) gene is regulated by factors that affect phospholipid synthesis. Mol. Cell. Biol. 6, 3320–3328 (1986).
pubmed: 3025587 pmcid: 367077
Dowd, S. R., Bier, M. E. & Patton-Vogt, J. L. Turnover of phosphatidylcholine in Saccharomyces cerevisiae. The role of the CDP-choline pathway. J. Biol. Chem. 276, 3756–3763 (2001).
pubmed: 11078727
Jesch, S. A., Zhao, X., Wells, M. T. & Henry, S. A. Genome-wide analysis reveals inositol, not choline, as the major effector of Ino2p-Ino4p and unfolded protein response target gene expression in yeast. J. Biol. Chem. 280, 9106–9118 (2005).
pubmed: 15611057
Wang, P. et al. Robust growth of Escherichia coli. Curr. Biol. 20, 1099–1103 (2010).
pubmed: 20537537 pmcid: 2902570
Norman, T. M., Lord, N. D., Paulsson, J. & Losick, R. Memory and modularity in cell-fate decision making. Nature 503, 481–486 (2013).
pubmed: 24256735 pmcid: 4019345
Bakshi, S. et al. Dynamic regulation of growth and physiology of microbes under complex changing conditions. Preprint at https://www.biorxiv.org/content/10.1101/2020.03.27.006403v2 (2020).
Thévenaz, P., Ruttimann, U. E. & Unser, M. A pyramid approach to subpixel registration based on intensity. IEEE Trans. Image Process. 7, 27–41 (1998).
pubmed: 18267377
Wu, L. et al. Quantitative analysis of the microbial metabolome by isotope dilution mass spectrometry using uniformly
pubmed: 15620880
Hörl, M., Schnidder, J., Sauer, U. & Zamboni, N. Non-stationary
pubmed: 23860906
Buescher, J. M., Moco, S., Sauer, U. & Zamboni, N. Ultrahigh performance liquid chromatography-tandem mass spectrometry method for fast and robust quantification of anionic and aromatic metabolites. Anal. Chem. 82, 4403–4412 (2010).
pubmed: 20433152
Rühl, M. et al. Collisional fragmentation of central carbon metabolites in LC-MS/MS increases precision of
pubmed: 22012626
Yuan, J., Bennett, B. D. & Rabinowitz, J. D. Kinetic flux profiling for quantitation of cellular metabolic fluxes. Nat. Protocols 3, 1328–1340 (2008).
pubmed: 18714301
Oda, Y., Huang, K., Cross, F. R., Cowburn, D. & Chait, B. T. Accurate quantitation of protein expression and site-specific phosphorylation. Proc. Natl Acad. Sci. USA 96, 6591–6596 (1999).
pubmed: 10359756
Fenton, A. W. & Reinhart, G. D. Disentangling the web of allosteric communication in a homotetramer: heterotropic inhibition in phosphofructokinase from Escherichia coli. Biochemistry 48, 12323–12328 (2009).
pubmed: 19905012 pmcid: 2797571

Auteurs

Markus Basan (M)

Department of Systems Biology, Harvard Medical School, Boston, MA, USA. markus@hms.harvard.edu.
Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland. markus@hms.harvard.edu.

Tomoya Honda (T)

Section of Molecular Biology, Division of Biological Sciences, University of California at San Diego, La Jolla, CA, USA.

Dimitris Christodoulou (D)

Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.

Manuel Hörl (M)

Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland.

Yu-Fang Chang (YF)

Department of Systems Biology, Harvard Medical School, Boston, MA, USA.

Emanuele Leoncini (E)

Department of Systems Biology, Harvard Medical School, Boston, MA, USA.

Avik Mukherjee (A)

Department of Systems Biology, Harvard Medical School, Boston, MA, USA.

Hiroyuki Okano (H)

Department of Physics, University of California at San Diego, La Jolla, CA, USA.

Brian R Taylor (BR)

Department of Physics, University of California at San Diego, La Jolla, CA, USA.

Josh M Silverman (JM)

Department of Integrative Structural and Computational Biology, and The Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA, USA.

Carlos Sanchez (C)

Department of Systems Biology, Harvard Medical School, Boston, MA, USA.

James R Williamson (JR)

Department of Integrative Structural and Computational Biology, and The Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA, USA.

Johan Paulsson (J)

Department of Systems Biology, Harvard Medical School, Boston, MA, USA.

Terence Hwa (T)

Section of Molecular Biology, Division of Biological Sciences, University of California at San Diego, La Jolla, CA, USA. thwa@ucsd.edu.
Department of Physics, University of California at San Diego, La Jolla, CA, USA. thwa@ucsd.edu.

Uwe Sauer (U)

Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland. sauer@imsb.biol.ethz.ch.

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