Ahmad Ahmad, Pathania Ruchi, Srivastava Shireesh
DBT-ICGEB Center for Advanced Bioenergy Research, International Centre for Genetic Engineering and Biotechnology, New Delhi 110067, India.
Department of Biotechnology, Noida International University, Noida, U.P. 203201, India.
Metabolites. 2020 Apr 29;10(5):177. doi: 10.3390/metabo10050177.
Marine cyanobacteria are promising microbes to capture and convert atmospheric CO and light into biomass and valuable industrial bio-products. Yet, reports on metabolic characteristics of non-model cyanobacteria are scarce. In this report, we show that an Indian euryhaline sp. BDU 130192 has biomass accumulation comparable to a model marine cyanobacterium and contains approximately double the amount of total carbohydrates, but significantly lower protein levels compared to sp. PCC 7002 cells. Based on its annotated chromosomal genome sequence, we present a genome scale metabolic model (GSMM) of this cyanobacterium, which we have named as Syn706. The model includes 706 genes, 908 reactions, and 900 metabolites. The difference in the flux balance analysis (FBA) predicted flux distributions between sp. PCC 7002 and sp. BDU130192 strains mimicked the differences in their biomass compositions. Model-predicted oxygen evolution rate for sp. BDU130192 was found to be close to the experimentally-measured value. The model was analyzed to determine the potential of the strain for the production of various industrially-useful products without affecting growth significantly. This model will be helpful to researchers interested in understanding the metabolism as well as to design metabolic engineering strategies for the production of industrially-relevant compounds.
海洋蓝藻细菌是很有前景的微生物,能够捕获大气中的二氧化碳并将其与光转化为生物质以及有价值的工业生物产品。然而,关于非模式蓝藻细菌代谢特征的报道却很稀少。在本报告中,我们表明一种印度广盐性蓝藻细菌菌株BDU 130192的生物质积累量与一种模式海洋蓝藻细菌相当,其总碳水化合物含量约为后者的两倍,但与聚球藻属PCC 7002菌株相比,蛋白质水平显著更低。基于其注释的染色体基因组序列,我们构建了这种蓝藻细菌的基因组规模代谢模型(GSMM),并将其命名为Syn706。该模型包含706个基因、908个反应和900种代谢物。聚球藻属PCC 7002菌株和BDU130192菌株之间通量平衡分析(FBA)预测的通量分布差异反映了它们生物质组成的差异。发现BDU130192菌株模型预测的氧气释放速率接近实验测量值。对该模型进行了分析,以确定该菌株在不显著影响生长的情况下生产各种工业有用产品的潜力。该模型将有助于研究人员理解其代谢过程,以及设计用于生产与工业相关化合物的代谢工程策略。