A synthetic genomics platform for antibiotic discovery
A synthetic genomics platform for antibiotic discovery
批准号:
2746098
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
抗生素耐药性是一种“缓慢的流行病”。联合国最近的一份报告估计,到2050年,它将导致全球每年1000万人死亡,其经济影响堪比2008年的金融危机。开发工具来解决抗微生物化合物的耐药性是非常重要的,并且已被确定为BBSRC的英国生物科学展望的关键目标。非核糖体肽(nrp)代表了多种次级代谢物,包括许多抗生素和抗生素前体。它们通常由酶组装的氨基酸组成,然后由一系列剪裁酶修饰。通过这种方式,核心抗生素分子可以通过多种方式进行修饰,从而潜在地规避抗生素耐药性机制。我们已经证明,NRP抗生素生产可以实现酵母使用合成生物学的方法。酵母具有无与伦比的遗传工具箱,为发现新型NRP衍生抗生素开辟了新的可能性。在本项目中,该学生将建立一个合成酵母平台,用于生产和筛选新型NRP分子,用于抗生素特性。在轮换项目中建立的细菌共培养系统将用于选择通过SCRaMbLE基因组进化增强青霉素生产的菌株。然后,该菌株将作为基础nrp生产菌株,用于裁剪酶组合的组合原型。生物信息学工具将用于从基因组数据集中识别候选剪裁酶基因,以便在我们的系统中进行测试。基因将被克隆到一个金门图书馆,格式与乱斗兼容。不同基因组合的文库将被引入到nrp生产菌株中,SCRaMbLE将进一步增加宿主基因组和文库的多样性。这些大量多样化的文库将与具有不同抗生素耐药谱的细菌菌株共同培养。酵母细胞在这些条件下的存活将依赖于以某种方式抑制细菌生长,从而避开各自的抗生素抗性机制。在试验中存活下来的菌株将被分离出来并充分表征,以确定任何作为抗生素或抑制抗生素耐药机制的新化合物。这项工作将建立一种可行性的合成酵母方法抗生素的发现,并可能产生新的抗菌化合物。该系统随后可以扩展到包括更广泛的候选剪裁酶和额外的NRP分子。监督小组-本杰明布朗特是合成基因组学专家和国际合成酵母基因组计划的成员。他是第一个成功地在酿酒酵母中设计NRP抗生素生产的团队的一员,并且是第一个证明SCRaMbLE可以用于改善工程途径的生产,包括青霉素。约翰·希普是代谢工程组合方法和合成生物学技术应用于生物技术菌株改良的专家。
英文摘要
Antibiotic resistance is the "slow pandemic". A recent UN report estimates that by 2050 it will be responsible for 10 million deaths a year globally, with an economic impact comparable to the 2008 financial crisis. Development of tools to tackle resistance to antimicrobial compounds is of pressing importance and has been identified as a key objective in the BBSRC's Forward Look for UK Bioscience.Nonribosomal peptides (NRPs) represent a diverse class of secondary metabolites and include many antibiotics and antibiotic precursors. They typically consist of amino acids that are assembled enzymatically and then modified by an array of tailoring enzymes. In this way, a core antibiotic molecule can be modified in many ways, potentially circumventing antibiotic resistance mechanisms. We have shown that NRP antibiotic production can be achieved in yeast using a synthetic biology approach. Yeast has an unparalleled genetic toolbox available, opening up new possibilities for discovering novel NRP-derived antibiotics In this project, the student will establish a synthetic yeast platform for production and screening of novel NRP molecules for antibiotic properties. The bacterial co-culture system established in the rotation project will be used to select a strain that is enhanced for penicillin production through SCRaMbLE genome evolution. This strain will then act as the base NRP-production strain for combinatorial prototyping of tailoring enzyme combinations.Bioinformatics tools will be used to identify candidate tailoring enzyme genes from genomic datasets to be tested in our system. Genes will be cloned into a Golden Gate library with SCRaMbLE-compatible formatting. Libraries of different gene combinations will be introduced to the NRP-production strain and SCRaMbLE will be used to further increase host genome and library diversity. These massively diversified libraries will be co-cultured with bacterial strains with different antibiotic resistance profiles. Survival of the yeast cells in these conditions will be reliant on the inhibition of bacterial growth in a way that evades the respective antibiotic resistance mechanism. Strains surviving the assays will be isolated and fully characterised to identify any novel compounds that act as antibiotics or that inhibit antibiotic resistance mechanisms. This work will establish the feasibility of a synthetic yeast approach to antibiotic discovery and may yield novel antimicrobial compounds. The system could subsequently be expanded to include a wider range of candidate tailoring enzymes and additional NRP molecules. Supervision Team - Benjamin Blount is an expert in synthetic genomics and a member of the International Synthetic Yeast Genome Project. He was part of the first team to successfully engineer NRP antibiotic production into S. cerevisiae yeast and was the first to demonstrate that SCRaMbLE can be used to improve production from engineered pathways, including penicillin. John Heap is an expert in combinatorial approaches to metabolic engineering and the application of synthetic biology techniques to the improvement of strains for biotechnology.
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