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Title: Proteomic analysis of Chlorella vulgaris: Potential targets for enhanced lipid accumulation

Abstract

Oleaginous microalgae are capable of producing large quantities of fatty acids and triacylglycerides. As such, they are promising feedstocks for the production of biofuels and bioproducts. Genetic strain-engineering strategies offer a means to accelerate the commercialization of algal biofuels by improving the rate and total accumulation of microalgal lipids. However, the industrial potential of these organisms remains to be met, largely due to the incomplete knowledgebase surrounding the mechanisms governing the induction of algal lipid biosynthesis. Such strategies require further elucidation of genes and gene products controlling algal lipid accumulation. In this study, we have set out to examine these mechanisms and identify novel strain-engineering targets in the oleaginous microalga, Chlorella vulgaris. Comparative shotgun proteomic analyses have identified a number of novel targets, including previously unidentified transcription factors and proteins involved in cell signaling and cell cycle regulation. These results lay the foundation for strain-improvement strategies and demonstrate the power of translational proteomic analysis.

Authors:
; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE. Office of Energy Efficiency and Renewable Energy Biomass Program
OSTI Identifier:
1260919
Report Number(s):
NREL/JA-5100-58983
Journal ID: ISSN 1874-3919
DOE Contract Number:
AC36-08GO28308
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Proteomics; Journal Volume: 93; Journal Issue: C
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; 59 BASIC BIOLOGICAL SCIENCES; microalgae; lipid; proteomics; cell cycle; metabolic engineering; biofuels

Citation Formats

Guarnieri, Michael T., Nag, Ambarish, Yang, Shihui, and Pienkos, Philip T. Proteomic analysis of Chlorella vulgaris: Potential targets for enhanced lipid accumulation. United States: N. p., 2013. Web. doi:10.1016/j.jprot.2013.05.025.
Guarnieri, Michael T., Nag, Ambarish, Yang, Shihui, & Pienkos, Philip T. Proteomic analysis of Chlorella vulgaris: Potential targets for enhanced lipid accumulation. United States. doi:10.1016/j.jprot.2013.05.025.
Guarnieri, Michael T., Nag, Ambarish, Yang, Shihui, and Pienkos, Philip T. Fri . "Proteomic analysis of Chlorella vulgaris: Potential targets for enhanced lipid accumulation". United States. doi:10.1016/j.jprot.2013.05.025.
@article{osti_1260919,
title = {Proteomic analysis of Chlorella vulgaris: Potential targets for enhanced lipid accumulation},
author = {Guarnieri, Michael T. and Nag, Ambarish and Yang, Shihui and Pienkos, Philip T.},
abstractNote = {Oleaginous microalgae are capable of producing large quantities of fatty acids and triacylglycerides. As such, they are promising feedstocks for the production of biofuels and bioproducts. Genetic strain-engineering strategies offer a means to accelerate the commercialization of algal biofuels by improving the rate and total accumulation of microalgal lipids. However, the industrial potential of these organisms remains to be met, largely due to the incomplete knowledgebase surrounding the mechanisms governing the induction of algal lipid biosynthesis. Such strategies require further elucidation of genes and gene products controlling algal lipid accumulation. In this study, we have set out to examine these mechanisms and identify novel strain-engineering targets in the oleaginous microalga, Chlorella vulgaris. Comparative shotgun proteomic analyses have identified a number of novel targets, including previously unidentified transcription factors and proteins involved in cell signaling and cell cycle regulation. These results lay the foundation for strain-improvement strategies and demonstrate the power of translational proteomic analysis.},
doi = {10.1016/j.jprot.2013.05.025},
journal = {Journal of Proteomics},
number = C,
volume = 93,
place = {United States},
year = {Fri Nov 01 00:00:00 EDT 2013},
month = {Fri Nov 01 00:00:00 EDT 2013}
}
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