Literature DB >> 24685590

Comparison of the theoretical and real-world evolutionary potential of a genetic circuit.

M Razo-Mejia1, J Q Boedicker, D Jones, A DeLuna, J B Kinney, R Phillips.   

Abstract

With the development of next-generation sequencing technologies, many large scale experimental efforts aim to map genotypic variability among individuals. This natural variability in populations fuels many fundamental biological processes, ranging from evolutionary adaptation and speciation to the spread of genetic diseases and drug resistance. An interesting and important component of this variability is present within the regulatory regions of genes. As these regions evolve, accumulated mutations lead to modulation of gene expression, which may have consequences for the phenotype. A simple model system where the link between genetic variability, gene regulation and function can be studied in detail is missing. In this article we develop a model to explore how the sequence of the wild-type lac promoter dictates the fold-change in gene expression. The model combines single-base pair resolution maps of transcription factor and RNA polymerase binding energies with a comprehensive thermodynamic model of gene regulation. The model was validated by predicting and then measuring the variability of lac operon regulation in a collection of natural isolates. We then implement the model to analyze the sensitivity of the promoter sequence to the regulatory output, and predict the potential for regulation to evolve due to point mutations in the promoter region.

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Year:  2014        PMID: 24685590      PMCID: PMC4051709          DOI: 10.1088/1478-3975/11/2/026005

Source DB:  PubMed          Journal:  Phys Biol        ISSN: 1478-3967            Impact factor:   2.583


  49 in total

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Journal:  Science       Date:  2005-02-25       Impact factor: 47.728

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Journal:  J Mol Biol       Date:  1990-07-20       Impact factor: 5.469

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Journal:  Cell       Date:  1985-09       Impact factor: 41.582

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Journal:  J Mol Biol       Date:  1996-01-12       Impact factor: 5.469

6.  Genetic structure of natural populations of Escherichia coli in wild hosts on different continents.

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Journal:  Appl Environ Microbiol       Date:  1999-08       Impact factor: 4.792

7.  The three operators of the lac operon cooperate in repression.

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Journal:  EMBO J       Date:  1990-04       Impact factor: 11.598

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Journal:  Proc Natl Acad Sci U S A       Date:  1982-02       Impact factor: 11.205

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Authors:  H Tagami; H Aiba
Journal:  Nucleic Acids Res       Date:  1995-02-25       Impact factor: 16.971

10.  Quality and position of the three lac operators of E. coli define efficiency of repression.

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Journal:  EMBO J       Date:  1994-07-15       Impact factor: 11.598

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  9 in total

Review 1.  Effective models and the search for quantitative principles in microbial evolution.

Authors:  Benjamin H Good; Oskar Hallatschek
Journal:  Curr Opin Microbiol       Date:  2018-12-06       Impact factor: 7.934

Review 2.  Figure 1 Theory Meets Figure 2 Experiments in the Study of Gene Expression.

Authors:  Rob Phillips; Nathan M Belliveau; Griffin Chure; Hernan G Garcia; Manuel Razo-Mejia; Clarissa Scholes
Journal:  Annu Rev Biophys       Date:  2019-05-06       Impact factor: 12.981

3.  Glucose becomes one of the worst carbon sources for E.coli on poor nitrogen sources due to suboptimal levels of cAMP.

Authors:  Anat Bren; Junyoung O Park; Benjamin D Towbin; Erez Dekel; Joshua D Rabinowitz; Uri Alon
Journal:  Sci Rep       Date:  2016-04-25       Impact factor: 4.379

4.  Self-consistent theory of transcriptional control in complex regulatory architectures.

Authors:  Jasper Landman; Robert C Brewster; Franz M Weinert; Rob Phillips; Willem K Kegel
Journal:  PLoS One       Date:  2017-07-07       Impact factor: 3.240

5.  Connecting single-cell properties to collective behavior in multiple wild isolates of the Enterobacter cloacae complex.

Authors:  Sean Lim; Xiaokan Guo; James Q Boedicker
Journal:  PLoS One       Date:  2019-04-04       Impact factor: 3.240

6.  Predictive shifts in free energy couple mutations to their phenotypic consequences.

Authors:  Griffin Chure; Manuel Razo-Mejia; Nathan M Belliveau; Tal Einav; Zofii A Kaczmarek; Stephanie L Barnes; Mitchell Lewis; Rob Phillips
Journal:  Proc Natl Acad Sci U S A       Date:  2019-08-26       Impact factor: 11.205

7.  Sort-seq under the hood: implications of design choices on large-scale characterization of sequence-function relations.

Authors:  Neil Peterman; Erel Levine
Journal:  BMC Genomics       Date:  2016-03-09       Impact factor: 3.969

8.  Dynamics of Transcription Factor Binding Site Evolution.

Authors:  Murat Tuğrul; Tiago Paixão; Nicholas H Barton; Gašper Tkačik
Journal:  PLoS Genet       Date:  2015-11-06       Impact factor: 5.917

9.  Predicting the impact of promoter variability on regulatory outputs.

Authors:  Naomi N Kreamer; Rob Phillips; Dianne K Newman; James Q Boedicker
Journal:  Sci Rep       Date:  2015-12-17       Impact factor: 4.379

  9 in total

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