Abstract
BackgroundCyanobacteria are one of the target groups of organisms explored for production of free fatty acids (FFAs) as biofuel precursors. Experimental evaluation of cyanobacterial potential for FFA production is costly and time consuming. Thus, computational approaches for comparing and ranking cyanobacterial strains for their potential to produce biofuel based on the characteristics of their predicted proteomes can be of great importance.ResultsTo enable such comparison and ranking, and to assist biotechnology developers and researchers in selecting strains more likely to be successfully engineered for the FFA production, we developed the Biofuel Producer Screen (BioPS) platform (http://www.cbrc.kaust.edu.sa/biops). BioPS relies on the estimation of the predicted proteome makeup of cyanobacterial strains to produce and secrete FFAs, based on the analysis of well-studied cyanobacterial strains with known FFA production profiles. The system links results back to various external repositories such as KEGG, UniProt and GOLD, making it easier for users to explore additional related information.ConclusionTo our knowledge, BioPS is the first tool that screens and evaluates cyanobacterial strains for their potential to produce and secrete FFAs based on strain’s predicted proteome characteristics, and rank strains based on that assessment. We believe that the availability of such a platform (comprising both a prediction tool and a repository of pre-evaluated stains) would be of interest to biofuel researchers. The BioPS system will be updated annually with information obtained from newly sequenced cyanobacterial genomes as they become available, as well as with new genes that impact FFA production or secretion.
Highlights
Biofuels derived from cyanobacteria are recognized as a promising alternative energy resource [1, 2]
To enable such comparison and ranking, and to assist biotechnology developers and researchers in selecting strains more likely to be successfully engineered for the free fatty acid (FFA) production, we developed the Biofuel Producer Screen (BioPS) platform
BioPS relies on the estimation of the predicted proteome makeup of cyanobacterial strains to produce and secrete FFAs, based on the analysis of well-studied cyanobacterial strains with known FFA production profiles
Summary
Biofuels derived from cyanobacteria are recognized as a promising alternative energy resource [1, 2]. FFA associated research in this organism, as well as in E. coli and yeast, have primarily been focused on the naturally abundant long-chain (C14– C18) fatty acids (FAs) [7,8,9,10,11], even though medium-chain (C4–C12) fatty acid precursors were used to produce fuel with improved quality [12,13,14] and are known to be valuable industrial chemicals [15, 16] These factors suggest that the increase in production and secretion of FFAs should be coupled with the tailoring of chain-length specificity. Computational approaches for comparing and ranking cyanobacterial strains for their potential to produce biofuel based on the characteristics of their predicted proteomes can be of great importance
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