Progress for green chemicals production by microbial manufacturing

doi:10.11949/0438-1157.20221322

Abstract

Abstract:

Microbial manufacturing uses renewable raw materials such as biomass and carbon dioxide for green production of chemicals, which shows a huge potential for reducing carbon dioxide emissions and is an important way to promote the goal of “carbon neutrality”. One of its core contents is the high-efficiency microbial cell factory design and construction. The research progress of metabolic flow analysis and metabolic pathway prediction based on genome-scale metabolic network model is reviewed. Novel genome editing tools are introduced to facilitate the efficient development of microbial cell factories and metabolic regulation strategies are summarized to enhance the productivity of microbial cell factories. In addition, the application of key microbial manufacturing technologies in third-generation manufacturing is outlined. Finally, the future applications and development directions of microbial manufacturing in chemical production are foreseen.

Key words: microbial manufacturing, metabolic network model, genome editing, metabolic regulation, microbial utilization

摘要：

微生物制造利用生物质和二氧化碳等可再生原料进行化学品的绿色生产，显示出了巨大的二氧化碳减排潜力，是促进实现“碳中和”目标的重要途径，其核心内容之一是高效微生物细胞工厂的设计与构建。综述了基于基因组规模代谢网络模型的代谢流分析和代谢途径预测研究进展；介绍了新型基因组编辑工具助力微生物细胞工厂的高效开发；总结了代谢调控策略用于提升细胞工厂生产能力。此外，还概述了微生物制造关键技术在第三代生物制造中的应用。最后，展望了未来微生物制造在化学品生产中的应用和发展方向。

关键词: 微生物制造, 代谢网络模型, 基因组编辑, 代谢调控, 微生物利用

CLC Number:

TQ 072

Haoran BI, Yang ZHANG, Kai WANG, Chenchen XU, Yiying HUO, Biqiang CHEN, Tianwei TAN. Progress for green chemicals production by microbial manufacturing[J]. CIESC Journal, 2023, 74(1): 1-13.

毕浩然, 张洋, 王凯, 徐晨晨, 霍奕影, 陈必强, 谭天伟. 微生物制造绿色化学品研究进展[J]. 化工学报, 2023, 74(1): 1-13.

Figures/Tables 4

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	产品	菌株	底物	改造策略	产量	文献
有机酸	柠檬酸	解脂耶氏酵母	甘油	发酵条件优化，无机营养素限制	112 g/L	[2]
	柠檬酸	黑曲霉	葡萄糖	过表达柠檬酸转运蛋白	109 g/L	[3]
	苹果酸	大肠杆菌	葡萄糖	过表达苹果酸酶，敲除琥珀酸合成基因，增强辅因子供给	21.65 g/L	[4]
	丁二酸	大肠杆菌	葡萄糖	关键基因过表达，两阶段发酵策略	116.2 g/L	[5]
	丁二酸	解脂耶氏酵母	粗甘油	优化发酵曝气率和底物浓度	209.7 g/L	[6]
	戊二酸	谷氨酸棒杆菌	葡萄糖	优化表达外源基因，表达戊二酸外排蛋白	105.3 g/L	[7]
	己二酸	大肠杆菌	葡萄糖/甘油	构建反向己二酸降解途径，两阶段发酵策略	68 g/L	[8]
	阿魏酸	大肠杆菌	甘油/葡萄糖	优化辅因子循环系统，增强前体供给	5.09 g/L	[9]
有机醇	1,3-丙二醇	肺炎克雷伯菌	甘油	阻断2,3-PDO途径，构建NADH再生系统	72.2 g/L	[10]
	1,3-丙二醇	大肠杆菌	葡萄糖	过表达酵母的甘油合成途径和肺炎克雷伯菌的1,3-PDO 合成途径，多基因修饰	135 g/L	[11]
	1,4-丁二醇	大肠杆菌	葡萄糖	优化关键酶的表达，调节能量平衡供应，削弱副产物的合成	120 g/L	[12]
萜类化合物	β-法尼烯	酿酒酵母	甘蔗糖浆	使用非天然反应重连酵母中心碳代谢，多轮菌株突变	130 g/L	[13]
	瓦伦烯	酿酒酵母	葡萄糖	基因筛选，蛋白质工程，耦联生长和生化途径诱导	16.6 g/L	[14]
	角鲨烯	酿酒酵母	葡萄糖、乙醇	过氧化物酶体工程，两阶段发酵策略	11 g/L	[15]
	虾青素	解脂耶氏酵母	葡萄糖	融合β-胡萝卜素酮酶和羟化酶，亚细胞区室化工程	858 mg/L	[16]
脂类	游离脂肪酸	酿酒酵母	葡萄糖	系统工程，敲除脂肪酸降解途径	10.4 g/L	[17]
	脂质	解脂耶氏酵母	乙酸	基于代谢模型和呼吸熵的发酵补料控制策略	115 g/L	[18]
生物大分子	聚羟基烷酸酯（PHA）	嗜盐单胞菌	葡萄糖、废弃葡萄糖酸盐	非无菌发酵工艺，建立发酵补料模型	60.4 g/L	[19]
多糖	肝素前体	大肠杆菌	葡萄糖	发酵溶氧控制	15 g/L	[20]

	产品	菌株	底物	改造策略	产量	文献
有机酸	柠檬酸	解脂耶氏酵母	甘油	发酵条件优化，无机营养素限制	112 g/L	[2]
	柠檬酸	黑曲霉	葡萄糖	过表达柠檬酸转运蛋白	109 g/L	[3]
	苹果酸	大肠杆菌	葡萄糖	过表达苹果酸酶，敲除琥珀酸合成基因，增强辅因子供给	21.65 g/L	[4]
	丁二酸	大肠杆菌	葡萄糖	关键基因过表达，两阶段发酵策略	116.2 g/L	[5]
	丁二酸	解脂耶氏酵母	粗甘油	优化发酵曝气率和底物浓度	209.7 g/L	[6]
	戊二酸	谷氨酸棒杆菌	葡萄糖	优化表达外源基因，表达戊二酸外排蛋白	105.3 g/L	[7]
	己二酸	大肠杆菌	葡萄糖/甘油	构建反向己二酸降解途径，两阶段发酵策略	68 g/L	[8]
	阿魏酸	大肠杆菌	甘油/葡萄糖	优化辅因子循环系统，增强前体供给	5.09 g/L	[9]
有机醇	1,3-丙二醇	肺炎克雷伯菌	甘油	阻断2,3-PDO途径，构建NADH再生系统	72.2 g/L	[10]
	1,3-丙二醇	大肠杆菌	葡萄糖	过表达酵母的甘油合成途径和肺炎克雷伯菌的1,3-PDO 合成途径，多基因修饰	135 g/L	[11]
	1,4-丁二醇	大肠杆菌	葡萄糖	优化关键酶的表达，调节能量平衡供应，削弱副产物的合成	120 g/L	[12]
萜类化合物	β-法尼烯	酿酒酵母	甘蔗糖浆	使用非天然反应重连酵母中心碳代谢，多轮菌株突变	130 g/L	[13]
	瓦伦烯	酿酒酵母	葡萄糖	基因筛选，蛋白质工程，耦联生长和生化途径诱导	16.6 g/L	[14]
	角鲨烯	酿酒酵母	葡萄糖、乙醇	过氧化物酶体工程，两阶段发酵策略	11 g/L	[15]
	虾青素	解脂耶氏酵母	葡萄糖	融合β-胡萝卜素酮酶和羟化酶，亚细胞区室化工程	858 mg/L	[16]
脂类	游离脂肪酸	酿酒酵母	葡萄糖	系统工程，敲除脂肪酸降解途径	10.4 g/L	[17]
	脂质	解脂耶氏酵母	乙酸	基于代谢模型和呼吸熵的发酵补料控制策略	115 g/L	[18]
生物大分子	聚羟基烷酸酯（PHA）	嗜盐单胞菌	葡萄糖、废弃葡萄糖酸盐	非无菌发酵工艺，建立发酵补料模型	60.4 g/L	[19]
多糖	肝素前体	大肠杆菌	葡萄糖	发酵溶氧控制	15 g/L	[20]

算法	发表年份	描述	文献
rFBA	2001	引入转录调控信息，在系统水平上解释、分析和预测转录调控对细胞代谢的影响	[36]
dFBA	2002	研究代谢网络的动力学，实现代谢网络的动态模拟	[38]
OptKnock	2003	对生物量方程和目标产物合成方程进行求解以预测基因敲除靶点	[48]
OptStrain	2004	通过反应添加和删除，指导微生物网络的路径修改	[56]
iFBA	2008	将FBA与调节布尔逻辑和常微分方程相结合	[37]
E-FLUX	2009	利用基因表达的全细胞测量来模拟代谢状态	[40]
PROM	2010	引入了代表基因状态和基因-转录因子相互作用的概率	[42]
OptForce	2010	比较实验菌株与野生型菌株之间的代谢通量差异来预测途径通量上调或下调的靶点	[51]
SimOptStrain	2011	同时考虑基因缺失和非天然反应添加	[57]
GX-FBA	2012	将基因表达数据与FBA（GX-FBA）相结合，使用mRNA表达数据来指导受代谢网络互连性影响的细胞代谢的分级调节	[41]
cFBA	2013	考虑了来自反应化学计量、反应热力学和生态系统的约束	[39]
ReacKnock	2013	实现多基因靶点的预测	[49]
OptSwap	2013	用于微生物辅因子调控策略的预测与设计	[50]
k-OptForce	2014	整合动力学的多基因改造策略预测	[52]

算法	发表年份	描述	文献
rFBA	2001	引入转录调控信息，在系统水平上解释、分析和预测转录调控对细胞代谢的影响	[36]
dFBA	2002	研究代谢网络的动力学，实现代谢网络的动态模拟	[38]
OptKnock	2003	对生物量方程和目标产物合成方程进行求解以预测基因敲除靶点	[48]
OptStrain	2004	通过反应添加和删除，指导微生物网络的路径修改	[56]
iFBA	2008	将FBA与调节布尔逻辑和常微分方程相结合	[37]
E-FLUX	2009	利用基因表达的全细胞测量来模拟代谢状态	[40]
PROM	2010	引入了代表基因状态和基因-转录因子相互作用的概率	[42]
OptForce	2010	比较实验菌株与野生型菌株之间的代谢通量差异来预测途径通量上调或下调的靶点	[51]
SimOptStrain	2011	同时考虑基因缺失和非天然反应添加	[57]
GX-FBA	2012	将基因表达数据与FBA（GX-FBA）相结合，使用mRNA表达数据来指导受代谢网络互连性影响的细胞代谢的分级调节	[41]
cFBA	2013	考虑了来自反应化学计量、反应热力学和生态系统的约束	[39]
ReacKnock	2013	实现多基因靶点的预测	[49]
OptSwap	2013	用于微生物辅因子调控策略的预测与设计	[50]
k-OptForce	2014	整合动力学的多基因改造策略预测	[52]

宿主	原料	产品	生产能力	文献
藻类	CO₂	脂质	7.4 g/(L·d)	[119]
藻类	CO₂	用于乙醇发酵的单糖	129 mg/g干微藻	[120]
藻类	CO₂	氢气	40 ml/L	[121]
电活性细菌	光能、电能和CO₂	H₂和CO混合气	CO∶H₂比例(0.1~6.8)	[122]
沼泽红假单胞菌	光能和CO₂	类胡萝卜素和聚β-羟基丁酸酯	生物质、类胡萝卜素和聚β-羟基丁酸酯产量分别增加到148%、122%和147%	[123]
梭菌	合成气	丙酮、异丙醇	3 g/(L·h)	[124]
产乙酸菌	合成气	乙酸	148 g/(L·d)	[125]
解脂耶氏酵母	从合成气生产的乙酸	脂质	18 g/L，0.19 g/(L·h)	[126]
米曲霉	从合成气生产的乙酸	苹果酸	0.37 g/g	[127]
产乙醇梭菌	从合成气生产的乙酸	PHA	占生物质的24%	[128]
酿酒酵母	CO₂电还原生产的乙酸	葡萄糖、脂肪酸	1.81 g/L葡萄糖，0.5 g/L脂肪酸	[129]
C. necator	电能和CO₂	α-葎草烯	17 mg/CDW	[130]
酿酒酵母	甲醇	丙酮酸	0.26 g/L	[131]