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RNA-Seq Analysis Provides Insights for Understanding Photoautotrophic Polyhydroxyalkanoate Production in Recombinant Synechocystis Sp.

Overview of attention for article published in PLOS ONE, January 2014
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Title
RNA-Seq Analysis Provides Insights for Understanding Photoautotrophic Polyhydroxyalkanoate Production in Recombinant Synechocystis Sp.
Published in
PLOS ONE, January 2014
DOI 10.1371/journal.pone.0086368
Pubmed ID
Authors

Nyok-Sean Lau, Choon Pin Foong, Yukio Kurihara, Kumar Sudesh, Minami Matsui

Abstract

The photosynthetic cyanobacterium, Synechocystis sp. strain 6803, is a potential platform for the production of various chemicals and biofuels. In this study, direct photosynthetic production of a biopolymer, polyhydroxyalkanoate (PHA), in genetically engineered Synechocystis sp. achieved as high as 14 wt%. This is the highest production reported in Synechocystis sp. under photoautotrophic cultivation conditions without the addition of a carbon source. The addition of acetate increased PHA accumulation to 41 wt%, and this value is comparable to the highest production obtained with cyanobacteria. Transcriptome analysis by RNA-seq coupled with real-time PCR was performed to understand the global changes in transcript levels of cells subjected to conditions suitable for photoautotrophic PHA biosynthesis. There was lower expression of most PHA synthesis-related genes in recombinant Synechocystis sp. with higher PHA accumulation suggesting that the concentration of these enzymes is not the limiting factor to achieving high PHA accumulation. In order to cope with the higher PHA production, cells may utilize enhanced photosynthesis to drive the product formation. Results from this study suggest that the total flux of carbon is the possible driving force for the biosynthesis of PHA and the polymerizing enzyme, PHA synthase, is not the only critical factor affecting PHA-synthesis. Knowledge of the regulation or control points of the biopolymer production pathways will facilitate the further use of cyanobacteria for biotechnological applications.

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Geographical breakdown

Country Count As %
India 2 2%
Canada 1 1%
Unknown 94 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 20%
Researcher 15 15%
Student > Ph. D. Student 15 15%
Student > Bachelor 10 10%
Professor 5 5%
Other 16 16%
Unknown 17 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 31%
Biochemistry, Genetics and Molecular Biology 16 16%
Engineering 8 8%
Environmental Science 4 4%
Computer Science 3 3%
Other 12 12%
Unknown 24 25%