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作 者:张嵩元 汪卫东 Songyuan Zhang;Weidong Wang(School of Life Sciences,Peking University,Beijing 100871,China;Sinopec Key Laboratory of MEOR,Petroleum Engineering Technology Research Institute,Shengli Oilfield Company,SINOPEC,Dongying 257000,Shandong Province,China)
机构地区:[1]北京大学生命科学学院,北京100871 [2]中石化重点实验室微生物采油研究中心,胜利油田石油工程技术研究院,山东东营257000
出 处:《微生物学报》2021年第10期3059-3075,共17页Acta Microbiologica Sinica
基 金:中石化重点科技攻关项目(P18087)。
摘 要:鼠李糖脂是一类重要的生物表面活性剂。相比于化学合成的表面活性剂,其具有更优秀的理化性质及环境友好等特点,被广泛应用于微生物采油、环境污染修复等工程中。目前,鼠李糖脂的工业生产主要采用铜绿假单胞菌这一具有致病性的天然合成菌株,与此同时,受菌株遗传背景的限制,优化发酵过程等方法在产量提升方面遇到了一些瓶颈问题。利用基因工程方法对菌株进行改良有望进一步提高鼠李糖脂生产的安全性、产量、产物性能等多项指标,因此受到了越来越广泛的关注。本文综述了近年来利用基因工程方法优化鼠李糖脂生物合成的最新进展,讨论了异源合成、代谢通路改造、基因表达优化、蛋白质工程、底盘工程等多种策略的应用,并展望了一系列可行的研究方向。Rhamnolipid is an important family of biosurfactant synthesized by many natural or engineered bacteria.Due to its excellent chemo-physical properties and environmental friendliness,it has been extensively used in many application scenarios(e.g.,microbial enhanced oil recovery(MEOR),bioremediation),in place of its chemically synthesized counterparts.In commercial production,rhamnolipid is mainly produced by Pseudomonas aeruginosa,a natural producer with pathogenicity.Its genetic context also limits further enhancement of production using fermentation optimization approach.As a solution,genetic engineering approach can improve the bio-safety,yield,and product performance of rhamnolipid production,which has attracted increasing attention.However,few review articles systematically discussed this topic.Herein,we summarized recent advances in rhamnolipid production using genetically engineered microorganisms,particularly focusing on engineering strategies applied(e.g.,heterogeneous production,pathway engineering,gene expression engineering,protein engineering,chassis engineering).Other than high yields,tailor-made rhamnolipid production(producing rhamnolipid mixture of specific composition)was also discussed.Finally,we proposed several potential strategies which may benefit rhamnolipid production:(1)using CRISPR-based tools for genome engineering;(2)gene expression optimization using synthetic promoter library and T7 polymerases;(3)synthetic protein scaffold for enzyme colocalization;(4)learning from polyhydroxyalkanoates(PHA)bioengineering;(5)development of in vivo directed evolution platform and rhamnolipid biosensor;(6)analysis of genome resequencing data.
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