Literature DB >> 31748916

Multi-tissue to whole plant metabolic modelling.

Rahul Shaw1, C Y Maurice Cheung2.   

Abstract

Genome-scale metabolic models have been successfully applied to study the metabolism of multiple plant species in the past decade. While most existing genome-scale modelling studies have focussed on studying the metabolic behaviour of individual plant metabolic systems, there is an increasing focus on combining models of multiple tissues or organs to produce multi-tissue models that allow the investigation of metabolic interactions between tissues and organs. Multi-tissue metabolic models were constructed for multiple plants including Arabidopsis, barley, soybean and Setaria. These models were applied to study various aspects of plant physiology including the division of labour between organs, source and sink tissue relationship, growth of different tissues and organs and charge and proton balancing. In this review, we outline the process of constructing multi-tissue genome-scale metabolic models, discuss the strengths and challenges in using multi-tissue models, review the current status of plant multi-tissue and whole plant metabolic models and explore the approaches for integrating genome-scale metabolic models into multi-scale plant models.

Entities:  

Keywords:  Constraint-based model; Genome-scale metabolic model; Model integration; Multi-tissue model; Plant metabolic modelling; Whole plant model

Mesh:

Year:  2019        PMID: 31748916     DOI: 10.1007/s00018-019-03384-y

Source DB:  PubMed          Journal:  Cell Mol Life Sci        ISSN: 1420-682X            Impact factor:   9.261


  42 in total

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4.  A Genome-Scale Metabolic Model of Soybean (Glycine max) Highlights Metabolic Fluxes in Seedlings.

Authors:  Thiago Batista Moreira; Rahul Shaw; Xinyu Luo; Oishik Ganguly; Hyung-Seok Kim; Lucas Gabriel Ferreira Coelho; Chun Yue Maurice Cheung; Thomas Christopher Rhys Williams
Journal:  Plant Physiol       Date:  2019-06-06       Impact factor: 8.340

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6.  Systems properties of the Haemophilus influenzae Rd metabolic genotype.

Authors:  J S Edwards; B O Palsson
Journal:  J Biol Chem       Date:  1999-06-18       Impact factor: 5.157

7.  Leaf carbohydrate controls over Arabidopsis growth and response to elevated CO2: an experimentally based model.

Authors:  Daniel P Rasse; Pierre Tocquin
Journal:  New Phytol       Date:  2006       Impact factor: 10.151

Review 8.  Impact of systems biology on metabolic engineering of Saccharomyces cerevisiae.

Authors:  Jens Nielsen; Michael C Jewett
Journal:  FEMS Yeast Res       Date:  2007-08-29       Impact factor: 2.796

Review 9.  Genetic modification of plant architecture and variety improvement in rice.

Authors:  X-C Yang; C-M Hwa
Journal:  Heredity (Edinb)       Date:  2008-08-20       Impact factor: 3.821

10.  A mass and charge balanced metabolic model of Setaria viridis revealed mechanisms of proton balancing in C4 plants.

Authors:  Rahul Shaw; C Y Maurice Cheung
Journal:  BMC Bioinformatics       Date:  2019-06-27       Impact factor: 3.169

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  5 in total

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Authors:  Anze Zupanic; Hans C Bernstein; Ines Heiland
Journal:  Cell Mol Life Sci       Date:  2020-01-13       Impact factor: 9.261

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Journal:  Plant Physiol       Date:  2022-03-04       Impact factor: 8.340

3.  Elucidating Plant-Microbe-Environment Interactions Through Omics-Enabled Metabolic Modelling Using Synthetic Communities.

Authors:  Ashley E Beck; Manuel Kleiner; Anna-Katharina Garrell
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Review 4.  Environment-coupled models of leaf metabolism.

Authors:  Nadine Töpfer
Journal:  Biochem Soc Trans       Date:  2021-02-26       Impact factor: 5.407

Review 5.  Exploring synergies between plant metabolic modelling and machine learning.

Authors:  Marta Sampaio; Miguel Rocha; Oscar Dias
Journal:  Comput Struct Biotechnol J       Date:  2022-04-16       Impact factor: 6.155

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