Assessing the metabolic impact of nitrogen availability using a compartmentalized maize leaf genome-scale model.

Plant Physiol

Departments of Chemical Engineering (M.S., R.S., C.D.M.) and Bioinformatics and Genomics, Huck Institutes of the Life Sciences (A.K.), Pennsylvania State University, University Park, Pennsylvania 16802;Institut Jean-Pierre Bourgin, Institut National de la Recherche Agronomique, Centre de Versailles-Grignon, Unité Mixte de Recherche 1318 Institut National de la Recherche Agronomique-Agro-ParisTech, Equipe de Recherce Labellisée, Centre National de la Recherche Scientifique 3559, F-78026 Versailles cedex, France (N.A., L.G., G.C., M.M., Z.L., G.M., B.H.); andLancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, United Kingdom (P.J.L.)

Published: November 2014

AI Article Synopsis

  • * This model integrates data on gene-protein-reaction relationships, biomass components like amino acids and proteins, and is based on extensive proteomic and transcriptomic evidence to enhance accuracy.
  • * Compared to the previous model, this updated version includes about four times as many genes and metabolites, and successfully predicts results with 90% accuracy for maize growth under nitrogen-limited conditions.

Article Abstract

Maize (Zea mays) is an important C4 plant due to its widespread use as a cereal and energy crop. A second-generation genome-scale metabolic model for the maize leaf was created to capture C4 carbon fixation and investigate nitrogen (N) assimilation by modeling the interactions between the bundle sheath and mesophyll cells. The model contains gene-protein-reaction relationships, elemental and charge-balanced reactions, and incorporates experimental evidence pertaining to the biomass composition, compartmentalization, and flux constraints. Condition-specific biomass descriptions were introduced that account for amino acids, fatty acids, soluble sugars, proteins, chlorophyll, lignocellulose, and nucleic acids as experimentally measured biomass constituents. Compartmentalization of the model is based on proteomic/transcriptomic data and literature evidence. With the incorporation of information from the MetaCrop and MaizeCyc databases, this updated model spans 5,824 genes, 8,525 reactions, and 9,153 metabolites, an increase of approximately 4 times the size of the earlier iRS1563 model. Transcriptomic and proteomic data have also been used to introduce regulatory constraints in the model to simulate an N-limited condition and mutants deficient in glutamine synthetase, gln1-3 and gln1-4. Model-predicted results achieved 90% accuracy when comparing the wild type grown under an N-complete condition with the wild type grown under an N-deficient condition.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4226342PMC
http://dx.doi.org/10.1104/pp.114.245787DOI Listing

Publication Analysis

Top Keywords

maize leaf
8
model maize
8
wild type
8
type grown
8
model
7
assessing metabolic
4
metabolic impact
4
impact nitrogen
4
nitrogen availability
4
availability compartmentalized
4

Similar Publications

The stomatal phenotype is a crucial microscopic characteristic of the leaf surface, and modulating the stomata of maize leaves can enhance photosynthetic carbon assimilation and water use efficiency, thereby playing a vital role in maize yield formation. The evolving imaging and image processing technologies offer effective tools for precise analysis of stomatal phenotypes. This study employed Jingnongke 728 and its parental inbred to capture stomatal images from various leaf positions and abaxial surfaces during key reproductive stages using rapid scanning electron microscopy.

View Article and Find Full Text PDF

LG1 promotes preligule band formation through directly activating ZmPIN1 genes in maize.

J Genet Genomics

January 2025

State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangdong Laboratory for Lingnan Modern Agriculture, College of Life Sciences, South China Agricultural University, Guangzhou, Guangdong 510642, China. Electronic address:

Increasing plant density is an effective strategy for enhancing crop yield per unit land area. A key architectural trait for crops adapting to high planting density is smaller leaf angle (LA). Previous studies have demonstrated that LG1, a SQUAMOSA BINDING PROTEIN (SBP) transcription factor, plays a critical role in LA establishment.

View Article and Find Full Text PDF

First Report of Causing Black Leaf Spot on in China.

Plant Dis

January 2025

Zhejiang Academy of Agricultural Sciences, Institute of Agro-product Safety and Nutrition, Hangzhou, Zhejiang, China;

Chinese yam ( Turcz.), known for its nutrient-rich underground tubers, is both a food source and a traditional Chinese medicinal plant. It offers significant nutritional and medicinal benefits.

View Article and Find Full Text PDF

Salt stress is a significant environmental factor that impedes maize growth and yield. Exogenous 5-aminolevulinic acid (ALA) has been shown to mitigate the detrimental effects of various environmental stresses on plants. However, its regulatory role in the photosynthesis mechanisms of maize seedlings under salt stress remains poorly understood.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!