Motwalli Olaa, Essack Magbubah, Jankovic Boris R, Ji Boyang, Liu Xinyao, Ansari Hifzur Rahman, Hoehndorf Robert, Gao Xin, Arold Stefan T, Mineta Katsuhiko, Archer John A C, Gojobori Takashi, Mijakovic Ivan, Bajic Vladimir B
Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia.
Division of Systems & Synthetic Biology, Department of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, 41296, Gothenburg, Sweden.
BMC Genomics. 2017 Jan 5;18(1):33. doi: 10.1186/s12864-016-3389-4.
Finding 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.
Here 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.
To 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.
寻找一种能够在工业规模上生产高能量密度生物燃料的原料，已成为可再生能源生产面临的一项紧迫挑战。一些微生物能够产生游离脂肪酸（FFA），作为生产此类高能量密度生物燃料的前体。特别是，光合蓝细菌能够将二氧化碳直接转化为FFA。然而，目前的工程菌株需要经过几轮工程改造，才能达到具有商业可行性的FFA生产水平；因此，需要构建工程改造需求较少的新型底盘菌株。尽管已对120多种蓝细菌基因组进行了测序，但尚未对这些菌株产生和分泌FFA的天然潜力进行系统评估。
在此，我们提出了FFA SC（FFASC），这是一种基于蓝细菌菌株蛋白质组评估其产生和分泌FFA潜力的计算机筛选方法。通过文献检索，汇编了64种蛋白质，其中大多数影响FFA的产生，少数影响FFA的分泌。这些蛋白质被分类为49个直系同源组（OG），有助于创建用于评估生物体产生和分泌FFA潜力的算法评分/排名规则。在125种蓝细菌菌株中，FFASC鉴定出20种候选底盘菌株，它们产生和分泌FFA的潜力高于经过专门工程改造的参考菌株聚球藻属PCC 7002。我们进一步表明，排名靠前的蓝细菌菌株是单细胞的，主要包括原绿球藻（原绿球藻目）和海洋聚球藻（色球藻目），它们在系统发育上聚类。此外，有两类主要的酶对FFA产生的影响最大：一类确保脂质生物合成的前体可用性，另一类参与应对与FFA合成相关的氧化应激。
据我们所知，FFASC是第一种用于筛选蓝细菌蛋白质组产生和分泌FFA潜力的计算机方法，也是首次尝试将源自遗传特征对该目的有利/不利的标准进行参数化。因此，FFASC有助于将实验评估仅聚焦于最有前景的蓝细菌。
