Literature DB >> 28837944

Underground metabolism: network-level perspective and biotechnological potential.

Richard A Notebaart1, Bálint Kintses2, Adam M Feist3, Balázs Papp2.   

Abstract

A key challenge in molecular systems biology is understanding how new pathways arise during evolution and how to exploit them for biotechnological applications. New pathways in metabolic networks often evolve by recruiting weak promiscuous activities of pre-existing enzymes. Here we describe recent systems biology advances to map such 'underground' activities and to predict and analyze their contribution to new metabolic functions. Underground activities are prevalent in cellular metabolism and can form novel pathways that either enable evolutionary adaptation to new environments or provide bypass to genetic lesions. We also illustrate the potential of integrating computational models of underground metabolism and experimental approaches to study the evolution of novel metabolic phenotypes and advance the field of biotechnology.
Copyright © 2017 Elsevier Ltd. All rights reserved.

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Year:  2017        PMID: 28837944     DOI: 10.1016/j.copbio.2017.07.015

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  17 in total

Review 1.  How enzyme promiscuity and horizontal gene transfer contribute to metabolic innovation.

Authors:  Margaret E Glasner; Dat P Truong; Benjamin C Morse
Journal:  FEBS J       Date:  2020-01-10       Impact factor: 5.542

Review 2.  The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology.

Authors:  Troy E Sandberg; Michael J Salazar; Liam L Weng; Bernhard O Palsson; Adam M Feist
Journal:  Metab Eng       Date:  2019-08-08       Impact factor: 9.783

3.  Artificial Gene Amplification in Escherichia coli Reveals Numerous Determinants for Resistance to Metal Toxicity.

Authors:  Kenric J Hoegler; Michael H Hecht
Journal:  J Mol Evol       Date:  2018-01-22       Impact factor: 2.395

4.  Prediction of degradation pathways of phenolic compounds in the human gut microbiota through enzyme promiscuity methods.

Authors:  Daniel Hinojosa-Nogueira; Xabier Cendoya; Francesco Balzerani; Telmo Blasco; Sergio Pérez-Burillo; Iñigo Apaolaza; M Pilar Francino; José Ángel Rufián-Henares; Francisco J Planes
Journal:  NPJ Syst Biol Appl       Date:  2022-07-12

5.  L-Alanine Prototrophic Suppressors Emerge from L-Alanine Auxotroph through Stress-Induced Mutagenesis in Escherichia coli.

Authors:  Harutaka Mishima; Hirokazu Watanabe; Kei Uchigasaki; So Shimoda; Shota Seki; Toshitaka Kumagai; Tomonori Nochi; Tasuke Ando; Hiroshi Yoneyama
Journal:  Microorganisms       Date:  2021-02-25

6.  Reframing gene essentiality in terms of adaptive flexibility.

Authors:  Gabriela I Guzmán; Connor A Olson; Ying Hefner; Patrick V Phaneuf; Edward Catoiu; Lais B Crepaldi; Lucas Goldschmidt Micas; Bernhard O Palsson; Adam M Feist
Journal:  BMC Syst Biol       Date:  2018-12-17

7.  Towards creating an extended metabolic model (EMM) for E. coli using enzyme promiscuity prediction and metabolomics data.

Authors:  Sara A Amin; Elizabeth Chavez; Vladimir Porokhin; Nikhil U Nair; Soha Hassoun
Journal:  Microb Cell Fact       Date:  2019-06-13       Impact factor: 5.328

8.  A bacterial checkpoint protein for ribosome assembly moonlights as an essential metabolite-proofreading enzyme.

Authors:  Ankita J Sachla; John D Helmann
Journal:  Nat Commun       Date:  2019-04-04       Impact factor: 14.919

9.  Enzyme promiscuity shapes adaptation to novel growth substrates.

Authors:  Gabriela I Guzmán; Troy E Sandberg; Ryan A LaCroix; Ákos Nyerges; Henrietta Papp; Markus de Raad; Zachary A King; Ying Hefner; Trent R Northen; Richard A Notebaart; Csaba Pál; Bernhard O Palsson; Balázs Papp; Adam M Feist
Journal:  Mol Syst Biol       Date:  2019-04-08       Impact factor: 11.429

Review 10.  Selecting the Best: Evolutionary Engineering of Chemical Production in Microbes.

Authors:  Denis Shepelin; Anne Sofie Lærke Hansen; Rebecca Lennen; Hao Luo; Markus J Herrgård
Journal:  Genes (Basel)       Date:  2018-05-11       Impact factor: 4.096

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