In silico screening for candidate chassis strains of free fatty acid-producing cyanobacteria

BMC Genomics

Methodology Article

Stefan T. Arold¹  John A. C. Archer¹  Robert Hoehndorf¹  Takashi Gojobori¹  Magbubah Essack¹  Xin Gao¹  Vladimir B. Bajic¹  Olaa Motwalli¹  Boris R. Jankovic¹  Katsuhiko Mineta¹  Boyang Ji²  Ivan Mijakovic²  Hifzur Rahman Ansari³  Xinyao Liu⁴ 

[1] Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), 23955-6900, Thuwal, Kingdom of Saudi Arabia;Division of Systems & Synthetic Biology, Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, 41296, Gothenburg, Sweden;Pathogen Genomics Laboratory, Biological and Environmental Sciences and Engineering (BESE) Division, King Abdullah University of Science and Technology (KAUST), 23955-6900, Thuwal, Kingdom of Saudi Arabia;SABIC Corporate Research and Development (CRD), 23955-6900, Thuwal, Kingdom of Saudi Arabia;

关键词: Cyanobacteria;    Free fatty acids;    Biofuel;    Screening method;    Cell factories;    Bioinformatics;    Optimization;    Computer science;   

DOI  :  10.1186/s12864-016-3389-4

 received in 2016-08-08, accepted in 2016-12-07,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundFinding a source from which high-energy-density biofuels can be derived at an industrial scale has become an urgent challenge for renewable energy production. Some microorganisms can produce free fatty acids (FFA) as precursors towards such high-energy-density biofuels. In particular, photosynthetic cyanobacteria are capable of directly converting carbon dioxide into FFA. However, current engineered strains need several rounds of engineering to reach the level of production of FFA to be commercially viable; thus new chassis strains that require less engineering are needed. Although more than 120 cyanobacterial genomes are sequenced, the natural potential of these strains for FFA production and excretion has not been systematically estimated.ResultsHere we present the FFA SC (FFASC), an in silico screening method that evaluates the potential for FFA production and excretion of cyanobacterial strains based on their proteomes. A literature search allowed for the compilation of 64 proteins, most of which influence FFA production and a few of which affect FFA excretion. The proteins are classified into 49 orthologous groups (OGs) that helped create rules used in the scoring/ranking of algorithms developed to estimate the potential for FFA production and excretion of an organism. Among 125 cyanobacterial strains, FFASC identified 20 candidate chassis strains that rank in their FFA producing and excreting potential above the specifically engineered reference strain, Synechococcus sp. PCC 7002. We further show that the top ranked cyanobacterial strains are unicellular and primarily include Prochlorococcus (order Prochlorales) and marine Synechococcus (order Chroococcales) that cluster phylogenetically. Moreover, two principal categories of enzymes were shown to influence FFA production the most: those ensuring precursor availability for the biosynthesis of lipids, and those involved in handling the oxidative stress associated to FFA synthesis.ConclusionTo our knowledge FFASC is the first in silico method to screen cyanobacteria proteomes for their potential to produce and excrete FFA, as well as the first attempt to parameterize the criteria derived from genetic characteristics that are favorable/non-favorable for this purpose. Thus, FFASC helps focus experimental evaluation only on the most promising cyanobacteria.

【 授权许可】

CC BY   
© The Author(s). 2017