Ghosh Amit, Ando David, Gin Jennifer, Runguphan Weerawat, Denby Charles, Wang George, Baidoo Edward E K, Shymansky Chris, Keasling Jay D, García Martín Héctor
Lawrence Berkeley National Laboratory, Biological Systems and Engineering Division, Berkeley, CA, USA; Joint BioEnergy Institute, Emeryville, CA, USA; Indian Institute of Technology (IIT), School of Energy Science and Engineering, Kharagpur, India.
Lawrence Berkeley National Laboratory, Biological Systems and Engineering Division, Berkeley, CA, USA; Joint BioEnergy Institute, Emeryville, CA, USA.
Front Bioeng Biotechnol. 2016 Oct 5;4:76. doi: 10.3389/fbioe.2016.00076. eCollection 2016.
Efficient redirection of microbial metabolism into the abundant production of desired bioproducts remains non-trivial. Here, we used flux-based modeling approaches to improve yields of fatty acids in . We combined C labeling data with comprehensive genome-scale models to shed light onto microbial metabolism and improve metabolic engineering efforts. We concentrated on studying the balance of acetyl-CoA, a precursor metabolite for the biosynthesis of fatty acids. A genome-wide acetyl-CoA balance study showed ATP citrate lyase from as a robust source of cytoplasmic acetyl-CoA and malate synthase as a desirable target for downregulation in terms of acetyl-CoA consumption. These genetic modifications were applied to WRY2, a strain that is capable of producing 460 mg/L of free fatty acids. With the addition of ATP citrate lyase and downregulation of malate synthase, the engineered strain produced 26% more free fatty acids. Further increases in free fatty acid production of 33% were obtained by knocking out the cytoplasmic glycerol-3-phosphate dehydrogenase, which flux analysis had shown was competing for carbon flux upstream with the carbon flux through the acetyl-CoA production pathway in the cytoplasm. In total, the genetic interventions applied in this work increased fatty acid production by ~70%.
将微生物代谢有效地重定向到大量生产所需生物产品仍然并非易事。在此，我们使用基于通量的建模方法来提高[具体微生物]中脂肪酸的产量。我们将碳同位素标记数据与全面的基因组规模模型相结合，以深入了解微生物代谢并改进代谢工程研究。我们专注于研究乙酰辅酶A的平衡，乙酰辅酶A是脂肪酸生物合成的前体代谢物。一项全基因组乙酰辅酶A平衡研究表明，[具体微生物]中的ATP柠檬酸裂解酶是细胞质乙酰辅酶A的强大来源，而苹果酸合酶是在乙酰辅酶A消耗方面下调的理想靶点。这些基因修饰应用于WRY2菌株，该菌株能够产生460毫克/升的游离脂肪酸。通过添加ATP柠檬酸裂解酶并下调苹果酸合酶，工程菌株产生的游离脂肪酸增加了26%。通过敲除细胞质甘油-3-磷酸脱氢酶，游离脂肪酸产量进一步提高了33%，通量分析表明该酶在细胞质中与通过乙酰辅酶A产生途径的碳通量在碳通量上游存在竞争。总的来说，这项工作中应用的基因干预使脂肪酸产量提高了约70%。
