Cyanobacteria are simple, efficient, genetically-tractable photosynthetic microorganisms which in principle represent ideal biocatalysts for CO2 capture and conversion. However, in practice, genetic instability and low productivity are key, linked problems in engineered cyanobacteria. We took a massively parallel approach, generating and characterising libraries of synthetic promoters and RBSs for the cyanobacterium Synechocystis sp. PCC 6803, and assembling a sparse combinatorial library of millions of metabolic pathway-encoding construct variants. Genetic instability was observed for some variants, which is expected when variants cause metabolic burden. Surprisingly however, in a single combinatorial round without iterative optimisation, 80% of variants chosen at random and cultured photoautotrophically over many generations accumulated the target terpenoid lycopene from atmospheric CO2, apparently overcoming genetic instability. This large-scale parallel metabolic engineering of cyanobacteria provides a new platform for development of genetically stable cyanobacterial biocatalysts for sustainable light-driven production of valuable products directly from CO2, avoiding fossil carbon or competition with food production.

中文翻译：

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组合组装平台能够在蓝藻中设计遗传稳定的代谢途径

蓝藻是简单、高效、遗传易处理的光合微生物，原则上代表了理想的二氧化碳捕获和转化生物催化剂。然而，在实践中，遗传不稳定性和低生产力是工程蓝藻中关键的相关问题。我们采用了一种大规模并行的方法，为蓝藻 Synechocystis sp 生成和表征合成启动子和 RBS 文库。PCC 6803，并组装了数百万个编码代谢途径的构建变体的稀疏组合库。观察到一些变体的遗传不稳定性，当变体引起代谢负担时，这是预期的。然而，令人惊讶的是，在没有迭代优化的单轮组合中，80% 的变体是随机选择并经过多代光自养培养，从大气 CO2 中积累了目标萜类番茄红素，显然克服了遗传不稳定性。这种大规模的蓝藻并行代谢工程为开发遗传稳定的蓝藻生物催化剂提供了一个新平台，用于直接从二氧化碳中可持续光驱动生产有价值的产品，避免化石碳或与食品生产的竞争。