Literature DB >> 25548180

Bacterial growth laws reflect the evolutionary importance of energy efficiency.

Arijit Maitra1, Ken A Dill1.   

Abstract

We are interested in the balance of energy and protein synthesis in bacterial growth. How has evolution optimized this balance? We describe an analytical model that leverages extensive literature data on growth laws to infer the underlying fitness landscape and to draw inferences about what evolution has optimized in Escherichia coli. Is E. coli optimized for growth speed, energy efficiency, or some other property? Experimental data show that at its replication speed limit, E. coli produces about four mass equivalents of nonribosomal proteins for every mass equivalent of ribosomes. This ratio can be explained if the cell's fitness function is the the energy efficiency of cells under fast growth conditions, indicating a tradeoff between the high energy costs of ribosomes under fast growth and the high energy costs of turning over nonribosomal proteins under slow growth. This model gives insight into some of the complex nonlinear relationships between energy utilization and ribosomal and nonribosomal production as a function of cell growth conditions.

Entities:  

Keywords:  bacterial metabolism; energy efficiency; fitness landscape; growth laws; yield

Mesh:

Substances:

Year:  2014        PMID: 25548180      PMCID: PMC4299221          DOI: 10.1073/pnas.1421138111

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  42 in total

1.  Protein-length distributions for the three domains of life.

Authors:  J Zhang
Journal:  Trends Genet       Date:  2000-03       Impact factor: 11.639

2.  Synthesis time of beta-galactosidase in Escherichia coli B/r as a function of growth rate.

Authors:  D G Dalbow; R Young
Journal:  Biochem J       Date:  1975-07       Impact factor: 3.857

Review 3.  Utilization of energy for growth and maintenance in continuous and batch cultures of microorganisms. A reevaluation of the method for the determination of ATP production by measuring molar growth yields.

Authors:  A H Stouthamer; C Bettenhaussen
Journal:  Biochim Biophys Acta       Date:  1973-02-12

4.  Influence of polyamine limitation on the chain growth rates of beta-galactosidase and of its messenger ribonucleic acid.

Authors:  D R Morris; M T Hansen
Journal:  J Bacteriol       Date:  1973-11       Impact factor: 3.490

5.  Chain elongation rate of messenger and polypeptides in slowly growing Escherichia coli.

Authors:  R L Coffman; T E Norris; A L Koch
Journal:  J Mol Biol       Date:  1971-08-28       Impact factor: 5.469

6.  Growth rate of polypeptide chains as a function of the cell growth rate in a mutant of Escherichia coli 15.

Authors:  J Forchhammer; L Lindahl
Journal:  J Mol Biol       Date:  1971-02-14       Impact factor: 5.469

7.  Peptide chain initiation and growth in the induced synthesis of beta-galactosidase.

Authors:  A Kepes; S Beguin
Journal:  Biochim Biophys Acta       Date:  1966-09

8.  The energetics of Escherichia coli during aerobic growth in continuous culture.

Authors:  I S Farmer; C W Jones
Journal:  Eur J Biochem       Date:  1976-08-01

9.  Induction kinetics of the L-arabinose operon of Escherichia coli.

Authors:  R Schleif; W Hess; S Finkelstein; D Ellis
Journal:  J Bacteriol       Date:  1973-07       Impact factor: 3.490

10.  Emergence of robust growth laws from optimal regulation of ribosome synthesis.

Authors:  Matthew Scott; Stefan Klumpp; Eduard M Mateescu; Terence Hwa
Journal:  Mol Syst Biol       Date:  2014-08-22       Impact factor: 11.429

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  56 in total

Review 1.  Predictive biology: modelling, understanding and harnessing microbial complexity.

Authors:  Allison J Lopatkin; James J Collins
Journal:  Nat Rev Microbiol       Date:  2020-05-29       Impact factor: 60.633

2.  Mechanistic links between cellular trade-offs, gene expression, and growth.

Authors:  Andrea Y Weiße; Diego A Oyarzún; Vincent Danos; Peter S Swain
Journal:  Proc Natl Acad Sci U S A       Date:  2015-02-18       Impact factor: 11.205

3.  Prediction of Cellular Burden with Host-Circuit Models.

Authors:  Evangelos-Marios Nikolados; Andrea Y Weiße; Diego A Oyarzún
Journal:  Methods Mol Biol       Date:  2021

Review 4.  Structure and dynamics of bacterial ribosome biogenesis.

Authors:  Joseph H Davis; James R Williamson
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-03-19       Impact factor: 6.237

5.  Evolution of initiator tRNAs and selection of methionine as the initiating amino acid.

Authors:  Souvik Bhattacharyya; Umesh Varshney
Journal:  RNA Biol       Date:  2016-06-20       Impact factor: 4.652

6.  Thermosensitivity of growth is determined by chaperone-mediated proteome reallocation.

Authors:  Ke Chen; Ye Gao; Nathan Mih; Edward J O'Brien; Laurence Yang; Bernhard O Palsson
Journal:  Proc Natl Acad Sci U S A       Date:  2017-10-10       Impact factor: 11.205

7.  Ribosome Dimerization Protects the Small Subunit.

Authors:  Heather A Feaga; Mykhailo Kopylov; Jenny Kim Kim; Marko Jovanovic; Jonathan Dworkin
Journal:  J Bacteriol       Date:  2020-04-27       Impact factor: 3.490

8.  Ribosomes are optimized for autocatalytic production.

Authors:  Shlomi Reuveni; Måns Ehrenberg; Johan Paulsson
Journal:  Nature       Date:  2017-07-19       Impact factor: 49.962

9.  Origin of exponential growth in nonlinear reaction networks.

Authors:  Wei-Hsiang Lin; Edo Kussell; Lai-Sang Young; Christine Jacobs-Wagner
Journal:  Proc Natl Acad Sci U S A       Date:  2020-10-22       Impact factor: 11.205

10.  Benefit of transferred mutations is better predicted by the fitness of recipients than by their ecological or genetic relatedness.

Authors:  Yinhua Wang; Carolina Diaz Arenas; Daniel M Stoebel; Kenneth Flynn; Ethan Knapp; Marcus M Dillon; Andrea Wünsche; Philip J Hatcher; Francisco B-G Moore; Vaughn S Cooper; Tim F Cooper
Journal:  Proc Natl Acad Sci U S A       Date:  2016-04-18       Impact factor: 11.205

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