Genome scale metabolic reconstruction of Chlorella variabilis for exploring its metabolic potential for biofuels

•Compartmentalized genome scale metabolic model was reconstructed for Chlorella variabilis.•The model, iAJ526, was reconstructed with 1455 reactions, 1236 metabolites and 526 genes.•Growth rates predicted by the model were in fair agreement with experimental results.•Red and blue light wavelengths w...

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Veröffentlicht in:Bioresource technology 2016-08, Vol.213, p.103-110
Hauptverfasser: Juneja, Ankita, Chaplen, Frank W.R., Murthy, Ganti S.
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Murthy, Ganti S.
description •Compartmentalized genome scale metabolic model was reconstructed for Chlorella variabilis.•The model, iAJ526, was reconstructed with 1455 reactions, 1236 metabolites and 526 genes.•Growth rates predicted by the model were in fair agreement with experimental results.•Red and blue light wavelengths were found to be essential and useful for high algal growth. A compartmentalized genome scale metabolic network was reconstructed for Chlorella variabilis to offer insight into various metabolic potentials from this alga. The model, iAJ526, was reconstructed with 1455 reactions, 1236 metabolites and 526 genes. 21% of the reactions were transport reactions and about 81% of the total reactions were associated with enzymes. Along with gap filling reactions, 2 major sub-pathways were added to the model, chitosan synthesis and rhamnose metabolism. The reconstructed model had reaction participation of 4.3 metabolites per reaction and average lethality fraction of 0.21. The model was effective in capturing the growth of C. variabilis under three light conditions (white, red and red+blue light) with fair agreement. This reconstructed metabolic network will serve an important role in systems biology for further exploration of metabolism for specific target metabolites and enable improved characteristics in the strain through metabolic engineering.
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A compartmentalized genome scale metabolic network was reconstructed for Chlorella variabilis to offer insight into various metabolic potentials from this alga. The model, iAJ526, was reconstructed with 1455 reactions, 1236 metabolites and 526 genes. 21% of the reactions were transport reactions and about 81% of the total reactions were associated with enzymes. Along with gap filling reactions, 2 major sub-pathways were added to the model, chitosan synthesis and rhamnose metabolism. The reconstructed model had reaction participation of 4.3 metabolites per reaction and average lethality fraction of 0.21. The model was effective in capturing the growth of C. variabilis under three light conditions (white, red and red+blue light) with fair agreement. 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A compartmentalized genome scale metabolic network was reconstructed for Chlorella variabilis to offer insight into various metabolic potentials from this alga. The model, iAJ526, was reconstructed with 1455 reactions, 1236 metabolites and 526 genes. 21% of the reactions were transport reactions and about 81% of the total reactions were associated with enzymes. Along with gap filling reactions, 2 major sub-pathways were added to the model, chitosan synthesis and rhamnose metabolism. The reconstructed model had reaction participation of 4.3 metabolites per reaction and average lethality fraction of 0.21. The model was effective in capturing the growth of C. variabilis under three light conditions (white, red and red+blue light) with fair agreement. This reconstructed metabolic network will serve an important role in systems biology for further exploration of metabolism for specific target metabolites and enable improved characteristics in the strain through metabolic engineering.</description><subject>Algae</subject><subject>biochemical pathways</subject><subject>Biofuels</subject><subject>Biomass</subject><subject>chitosan</subject><subject>Chlorella - cytology</subject><subject>Chlorella - genetics</subject><subject>Chlorella - growth &amp; development</subject><subject>Chlorella - metabolism</subject><subject>Chlorella variabilis</subject><subject>death</subject><subject>Flux balance analysis</subject><subject>Genome</subject><subject>Genome scale reconstruction</subject><subject>Metabolic Engineering - methods</subject><subject>Metabolic Flux Analysis</subject><subject>Metabolic Networks and Pathways</subject><subject>Metabolic reconstruction</subject><subject>metabolism</subject><subject>metabolites</subject><subject>Models, Theoretical</subject><subject>Phenotype</subject><subject>rhamnose</subject><subject>technology</subject><issn>0960-8524</issn><issn>1873-2976</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkU1v1DAQhi0EotvCX6h85JLUH_FHbqAVFKRKXOBsOd4x9cqJg-1U8O_xsi3i1tPImuedGflB6JqSnhIqb479FFKu4O571t49YT2l-gXaUa14x0YlX6IdGSXptGDDBbos5UgI4VSx1-iCyXEUnOodWm9hSTPg4mwEPEO1U4rB4QwuLaXmzdWQFpw83t_HlCFGix9sDnYKMRTsU8bwa22dsPzAoZb_RqypwlKDjX-pdq7fIJY36JW3scDbx3qFvn_6-G3_ubv7evtl_-GucwPXtdMD0ZR4JeVAR6Gt58wr4hhwQZjwfqKegQPqNHAptdbcDf4wEK7dSJ0g_Aq9O89dc_q5QalmDsWd7l8gbcVQ3XJCUS6eR9WotBJqoA2VZ9TlVEoGb9YcZpt_G0rMSYw5micx5iTGEGaamBa8ftyxTTMc_sWeTDTg_RlofwQPAbIpLsDi4BCai2oOKTy34w8UUaPf</recordid><startdate>20160801</startdate><enddate>20160801</enddate><creator>Juneja, Ankita</creator><creator>Chaplen, Frank W.R.</creator><creator>Murthy, Ganti S.</creator><general>Elsevier Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>20160801</creationdate><title>Genome scale metabolic reconstruction of Chlorella variabilis for exploring its metabolic potential for biofuels</title><author>Juneja, Ankita ; 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A compartmentalized genome scale metabolic network was reconstructed for Chlorella variabilis to offer insight into various metabolic potentials from this alga. The model, iAJ526, was reconstructed with 1455 reactions, 1236 metabolites and 526 genes. 21% of the reactions were transport reactions and about 81% of the total reactions were associated with enzymes. Along with gap filling reactions, 2 major sub-pathways were added to the model, chitosan synthesis and rhamnose metabolism. The reconstructed model had reaction participation of 4.3 metabolites per reaction and average lethality fraction of 0.21. The model was effective in capturing the growth of C. variabilis under three light conditions (white, red and red+blue light) with fair agreement. 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subjects Algae
biochemical pathways
Biofuels
Biomass
chitosan
Chlorella - cytology
Chlorella - genetics
Chlorella - growth & development
Chlorella - metabolism
Chlorella variabilis
death
Flux balance analysis
Genome
Genome scale reconstruction
Metabolic Engineering - methods
Metabolic Flux Analysis
Metabolic Networks and Pathways
Metabolic reconstruction
metabolism
metabolites
Models, Theoretical
Phenotype
rhamnose
technology
title Genome scale metabolic reconstruction of Chlorella variabilis for exploring its metabolic potential for biofuels
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