Literature DB >> 24699221

Synthetic biology of metabolism: using natural variation to reverse engineer systems.

Daniel J Kliebenstein1.   

Abstract

A goal of metabolic engineering is to take a plant and introduce new or modify existing pathways in a directed and predictable fashion. However, existing data does not provide the necessary level of information to allow for predictive models to be generated. One avenue to reverse engineer the necessary information is to study the genetic control of natural variation in plant primary and secondary metabolism. These studies are showing that any engineering model will have to incorporate information about 1000s of genes in both the nuclear and organellar genome to optimize the function of the introduced pathway. Further, these genes may interact in an unpredictable fashion complicating any engineering approach as it moves from the one or two gene manipulation to higher order stacking efforts. Finally, metabolic engineering may be influenced by a previously unrecognized potential for a plant to measure the metabolites within it. In combination, these observations from natural variation provide a beginning to help improve current efforts at metabolic engineering.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2014        PMID: 24699221     DOI: 10.1016/j.pbi.2014.03.008

Source DB:  PubMed          Journal:  Curr Opin Plant Biol        ISSN: 1369-5266            Impact factor:   7.834


  8 in total

1.  Natural Variation of Plant Metabolism: Genetic Mechanisms, Interpretive Caveats, and Evolutionary and Mechanistic Insights.

Authors:  Nicole E Soltis; Daniel J Kliebenstein
Journal:  Plant Physiol       Date:  2015-08-13       Impact factor: 8.340

Review 2.  Engineered minichromosomes in plants.

Authors:  James A Birchler
Journal:  Chromosome Res       Date:  2015-02       Impact factor: 5.239

Review 3.  Computational Approaches to Design and Test Plant Synthetic Metabolic Pathways.

Authors:  Anika Küken; Zoran Nikoloski
Journal:  Plant Physiol       Date:  2019-01-15       Impact factor: 8.340

Review 4.  Proteomic approaches in microalgae: perspectives and applications.

Authors:  Vishal Anand; Puneet Kumar Singh; Chiranjib Banerjee; Pratyoosh Shukla
Journal:  3 Biotech       Date:  2017-06-30       Impact factor: 2.406

5.  Genome-wide association mapping within a local Arabidopsis thaliana population more fully reveals the genetic architecture for defensive metabolite diversity.

Authors:  Andrew D Gloss; Amélie Vergnol; Timothy C Morton; Peter J Laurin; Fabrice Roux; Joy Bergelson
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2022-05-30       Impact factor: 6.671

6.  Isolate Dependency of Brassica rapa Resistance QTLs to Botrytis cinerea.

Authors:  Wei Zhang; Soon-Tae Kwon; Fang Chen; Daniel J Kliebenstein
Journal:  Front Plant Sci       Date:  2016-02-17       Impact factor: 5.753

Review 7.  Spotlight on the Roles of Whitefly Effectors in Insect-Plant Interactions.

Authors:  Diana Naalden; Paula J M van Kleeff; Sarmina Dangol; Marieke Mastop; Rebecca Corkill; Saskia A Hogenhout; Merijn R Kant; Robert C Schuurink
Journal:  Front Plant Sci       Date:  2021-07-02       Impact factor: 5.753

8.  Comparative and parallel genome-wide association studies for metabolic and agronomic traits in cereals.

Authors:  Wei Chen; Wensheng Wang; Meng Peng; Liang Gong; Yanqiang Gao; Jian Wan; Shouchuang Wang; Lei Shi; Bin Zhou; Zongmei Li; Xiaoxi Peng; Chenkun Yang; Lianghuan Qu; Xianqing Liu; Jie Luo
Journal:  Nat Commun       Date:  2016-10-04       Impact factor: 14.919

  8 in total

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