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Title: PlantSEED enables automated annotation and reconstruction of plant primary metabolism with improved compartmentalization and comparative consistency

Abstract

Genome-scale metabolic reconstructions help us to understand and engineer metabolism. Next-generation sequencing technologies are delivering genomes and transcriptomes for an ever-widening range of plants. While such omic data can, in principle, be used to compare metabolic reconstructions in different species, organs and environmental conditions, these comparisons require a standardized framework for the reconstruction of metabolic networks from transcript data. We previously introduced PlantSEED as a framework covering primary metabolism for 10 species. We have now expanded PlantSEED to include 39 species and provide tools that enable automated annotation and metabolic reconstruction from transcriptome data. The algorithm for automated annotation in PlantSEED propagates annotations using a set of signature k-mers (short amino acid sequences characteristic of particular proteins) that identify metabolic enzymes with an accuracy of about 97%. PlantSEED reconstructions are built from a curated template that includes consistent compartmentalization for more than 100 primary metabolic subsystems. Together, the annotation and reconstruction algorithms produce reconstructions without gaps and with more accurate compartmentalization than existing resources. These tools are available via the PlantSEED web interface at , which enables users to upload, annotate and reconstruct from private transcript data and simulate metabolic activity under various conditions using flux balance analysis. We demonstratemore » the ability to compare these metabolic reconstructions with a case study involving growth on several nitrogen sources in roots of four species.« less

Authors:
 [1];  [2];  [3];  [3];  [4];  [2];  [1]
  1. Mathematics and Computer Science Division, Argonne National Laboratory, Argonne IL 60439 USA; Computation Institute, The University of Chicago, Chicago IL 60637 USA
  2. Horticultural Sciences Department, University of Florida, Gainesville FL 32611 USA
  3. Mathematics and Computer Science Division, Argonne National Laboratory, Argonne IL 60439 USA
  4. HudsonAlpha Institute for Biotechnology, Huntsville AL 35806 USA
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1474138
DOE Contract Number:  
AC02-06CH11357
Resource Type:
Journal Article
Journal Name:
The Plant Journal
Additional Journal Information:
Journal Volume: 95; Journal Issue: 6; Journal ID: ISSN 0960-7412
Publisher:
Society for Experimental Biology
Country of Publication:
United States
Language:
English
Subject:
Flux Balance Analysis; Metabolic Modeling; Metabolic Reconstruction; Plant Genomes; Plant Metabolism

Citation Formats

Seaver, Samuel M. D., Lerma-Ortiz, Claudia, Conrad, Neal, Mikaili, Arman, Sreedasyam, Avinash, Hanson, Andrew D., and Henry, Christopher S. PlantSEED enables automated annotation and reconstruction of plant primary metabolism with improved compartmentalization and comparative consistency. United States: N. p., 2018. Web. doi:10.1111/tpj.14003.
Seaver, Samuel M. D., Lerma-Ortiz, Claudia, Conrad, Neal, Mikaili, Arman, Sreedasyam, Avinash, Hanson, Andrew D., & Henry, Christopher S. PlantSEED enables automated annotation and reconstruction of plant primary metabolism with improved compartmentalization and comparative consistency. United States. doi:10.1111/tpj.14003.
Seaver, Samuel M. D., Lerma-Ortiz, Claudia, Conrad, Neal, Mikaili, Arman, Sreedasyam, Avinash, Hanson, Andrew D., and Henry, Christopher S. Thu . "PlantSEED enables automated annotation and reconstruction of plant primary metabolism with improved compartmentalization and comparative consistency". United States. doi:10.1111/tpj.14003.
@article{osti_1474138,
title = {PlantSEED enables automated annotation and reconstruction of plant primary metabolism with improved compartmentalization and comparative consistency},
author = {Seaver, Samuel M. D. and Lerma-Ortiz, Claudia and Conrad, Neal and Mikaili, Arman and Sreedasyam, Avinash and Hanson, Andrew D. and Henry, Christopher S.},
abstractNote = {Genome-scale metabolic reconstructions help us to understand and engineer metabolism. Next-generation sequencing technologies are delivering genomes and transcriptomes for an ever-widening range of plants. While such omic data can, in principle, be used to compare metabolic reconstructions in different species, organs and environmental conditions, these comparisons require a standardized framework for the reconstruction of metabolic networks from transcript data. We previously introduced PlantSEED as a framework covering primary metabolism for 10 species. We have now expanded PlantSEED to include 39 species and provide tools that enable automated annotation and metabolic reconstruction from transcriptome data. The algorithm for automated annotation in PlantSEED propagates annotations using a set of signature k-mers (short amino acid sequences characteristic of particular proteins) that identify metabolic enzymes with an accuracy of about 97%. PlantSEED reconstructions are built from a curated template that includes consistent compartmentalization for more than 100 primary metabolic subsystems. Together, the annotation and reconstruction algorithms produce reconstructions without gaps and with more accurate compartmentalization than existing resources. These tools are available via the PlantSEED web interface at , which enables users to upload, annotate and reconstruct from private transcript data and simulate metabolic activity under various conditions using flux balance analysis. We demonstrate the ability to compare these metabolic reconstructions with a case study involving growth on several nitrogen sources in roots of four species.},
doi = {10.1111/tpj.14003},
journal = {The Plant Journal},
issn = {0960-7412},
number = 6,
volume = 95,
place = {United States},
year = {2018},
month = {8}
}