Genome-Scale Model Reveals Metabolic Basis of Biomass Partitioning in a Model Diatom
Artikel i vetenskaplig tidskrift, 2016

Diatoms are eukaryotic microalgae that contain genes from various sources, including bacteria and the secondary endosymbiotic host. Due to this unique combination of genes, diatoms are taxonomically and functionally distinct from other algae and vascular plants and confer novel metabolic capabilities. Based on the genome annotation, we performed a genome-scale metabolic network reconstruction for the marine diatom Phaeodactylum tricornutum. Due to their endosymbiotic origin, diatoms possess a complex chloroplast structure which complicates the prediction of subcellular protein localization. Based on previous work we implemented a pipeline that exploits a series of bioinformatics tools to predict protein localization. The manually curated reconstructed metabolic network iLB1027_lipid accounts for 1,027 genes associated with 4,456 reactions and 2,172 metabolites distributed across six compartments. To constrain the genome-scale model, we determined the organism specific biomass composition in terms of lipids, carbohydrates, and proteins using Fourier transform infrared spectrometry. Our simulations indicate the presence of a yet unknown glutamine-ornithine shunt that could be used to transfer reducing equivalents generated by photosynthesis to the mitochondria. The model reflects the known biochemical composition of P. tricornutum in defined culture conditions and enables metabolic engineering strategies to improve the use of P. tricornutum for biotechnological applications.

metabolities

diatoms

lipids

chloroplasts

Författare

Jennifer Levering

University of California

Jared Broddrick

University of California

Christopher L. Dupont

J. Craig Venter Institute

Graham Peers

Colorado State University

Karen Beeri

J. Craig Venter Institute

Joshua Mayers

Chalmers, Biologi och bioteknik, Industriell bioteknik

Alessandra A. Gallina

University of California

Colorado State University

Andrew E. Allen

Scripps Institution of Oceanography

J. Craig Venter Institute

B. Palsson

University of California

Karsten Zengler

University of California

PLoS ONE

1932-6203 (ISSN)

Vol. 11 e0155038

Ämneskategorier

Bioinformatik och systembiologi

DOI

10.1371/journal.pone.0155038

PubMed

27152931