MetaCrop: a detailed database of crop plant metabolism

Grafahrend-Belau, Eva; Weise, Stéphan; Koschützki, Dirk; Scholz, Uwe; Junker, Björn H.; Schreiber, Falk

doi:10.1093/nar/gkm835

Cited by 40 publications

(32 citation statements)

References 26 publications

(35 reference statements)

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“…Although PlantCyc is not the first metabolic pathway database containing plant-only data (e.g. MetaCrop [Grafahrend-Belau et al, 2008]), it is by far the most comprehensive in coverage. We applied our system to the recently sequenced genome of Populus trichocarpa to build a metabolic pathway database, which we named PoplarCyc.…”

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confidence: 99%

Creation of a Genome-Wide Metabolic Pathway Database for Populus trichocarpa Using a New Approach for Reconstruction and Curation of Metabolic Pathways for Plants

et al. 2010

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Metabolic networks reconstructed from sequenced genomes or transcriptomes can help visualize and analyze large-scale experimental data, predict metabolic phenotypes, discover enzymes, engineer metabolic pathways, and study metabolic pathway evolution. We developed a general approach for reconstructing metabolic pathway complements of plant genomes. Two new reference databases were created and added to the core of the infrastructure: a comprehensive, all-plant reference pathway database, PlantCyc, and a reference enzyme sequence database, RESD, for annotating metabolic functions of protein sequences. PlantCyc (version 3.0) includes 714 metabolic pathways and 2,619 reactions from over 300 species. RESD (version 1.0) contains 14,187 literature-supported enzyme sequences from across all kingdoms. We used RESD, PlantCyc, and MetaCyc (an all-species reference metabolic pathway database), in conjunction with the pathway prediction software Pathway Tools, to reconstruct a metabolic pathway database, PoplarCyc, from the recently sequenced genome of Populus trichocarpa. PoplarCyc (version 1.0) contains 321 pathways with 1,807 assigned enzymes. Comparing PoplarCyc (version 1.0) with AraCyc (version 6.0, Arabidopsis [Arabidopsis thaliana]) showed comparable numbers of pathways distributed across all domains of metabolism in both databases, except for a higher number of AraCyc pathways in secondary metabolism and a 1.5-fold increase in carbohydrate metabolic enzymes in PoplarCyc. Here, we introduce these new resources and demonstrate the feasibility of using them to identify candidate enzymes for specific pathways and to analyze metabolite profiling data through concrete examples. These resources can be searched by text or BLAST, browsed, and downloaded from our project Web site (http:// plantcyc.org).

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confidence: 99%

Creation of a Genome-Wide Metabolic Pathway Database for Populus trichocarpa Using a New Approach for Reconstruction and Curation of Metabolic Pathways for Plants

et al. 2010

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“…To facilitate the construction of crop plant metabolic models, we developed MetaCrop (Grafahrend-Belau et al 2008). MetaCrop is a curated multispecies plant metabolic pathway database focusing on crop plant metabolism.…”

Section: Model Reconstructionmentioning

confidence: 99%

Plant Metabolic Pathways: Databases and Pipeline for Stoichiometric Analysis

Grafahrend-Belau

Junker

Schreiber

2012

Seed Development: OMICS Technologies Toward Improvement of Seed Quality and Crop Yield

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Mathematical modeling of plant metabolism offers new approaches to improve the understanding of complex biological processes. In this chapter an overview of resources and tools available for the reconstruction of stoichiometric models and their constraint-based analysis is given, focusing on plant metabolic pathways. To facilitate and support the modeling of metabolism, a pipeline for the constraint-based analysis of crop plant metabolic models is described and the proposed framework is applied in a case study of storage metabolism in developing barley seeds.Keywords Constraint-based analysis (CBA) · CBA software · Crop plant metabolism · Flux balance analysis · Modeling pipeline · Plant metabolic pathway databases IntroductionBioinformatics has become an integral part of biological research, including basic and applied plant science. To understand the complexity inherent in the vast amount of data gathered by large-scale profiling of biological features (e.g., transcriptomics, proteomics, and metabolomics data), new approaches need to be developed with focus on the management, visualization, integration, analysis, modelization, and prediction of these data. Mathematical modeling of metabolism provides new concepts and methods to elucidate the structure, dynamics, and behavior of complex biological processes. In silico models of biological systems can be applied to verify and extend the understanding of complex metabolic processes, to generate and test hypothesis, and to explore in silico scenarios, thus supplementing or even replacing experiments.In plant research, the issue of modeling metabolism is constantly gaining attention. Several mathematical modeling approaches applied to plant metabolism exist

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“…MetaCrop is a database that summarizes manually curated information (such as reactions, locations, transport processes, reaction kinetics, literature references) about metabolic pathways in crop plants (metacrop.ipk-gatersleben.de) [4]. The pathways have been drawn with SBGN-ED and the entire SBGN maps are available in MetaCrop as clickable image maps for online exploration and as SBGN-ML files for download and usage in other LibSBGN supporting tools.…”

Section: Metacropmentioning

confidence: 99%