Transcription engineering for biosensor-based screening of metagenomic libraries

描述(申请人提供)：对元基因组文库的有效筛选将使人们能够探索自然界中微生物的巨大多样性，这些微生物负责许多有趣和有价值的人类生命所必需的功能。例如，在人体肠道中，细菌群落解毒有害化学物质，合成维生素，帮助消化人体自身无法消化的营养物质，以及其他重要功能。不幸的是，绝大多数细菌不能在实验室中培养，因此生物催化活动的遗传基础往往没有被发现。微生物学的主要生物体大肠杆菌可以容纳这些细菌群落的基因组DNA(称为元基因组文库)的遗传集合。由于两个主要限制，元基因组文库的筛选效率低下。首先，大肠杆菌通常不能识别元基因组文库中的异源启动子。其次，寻找生物催化功能通常涉及筛选小分子的存在，这可能是时间和资源密集型的。建议的解决方案是开发一种不依赖于培养的方法来高通量筛选元基因组文库。在第一个目的中，提出了通过表达原核生物在系统发育上远离宿主的转录机制(sigma因子)，宿主的RNA聚合酶将更好地识别异源启动子，促进元基因组文库中遗传元件的转录。为了从元基因组文库中提高异源基因的表达，将在一系列细菌物种(包括枯草芽孢杆菌和植物乳杆菌)的宿主菌株中表达sigma因子。异源文库的转录将通过将绿色荧光蛋白基因融合到小的文库插入并用流式细胞仪测量荧光来定量。通过改造启动子和核糖体结合位点(RBS)来优化异源Sigma因子的表达水平，以获得良好的表达菌株。利用这个系统，将从土壤细菌中构建一个元基因组文库，并筛选出具有增强丁醇耐受性的基因。在第二个目标中，一个转录激活生物传感器系统将被整合到大肠杆菌中，以检测感兴趣的生物化学。该生物传感器可以检测细胞内的生化浓度并诱导GFP基因的转录。生物传感器将由启动子和RBS工程进行调整，以优化荧光激活细胞分选，这是一种高通量方法。最后，在第三个目标中，将生物传感器系统整合到异源Sigma因子表达菌株中，并转化为大插入的、基于FOSMID的合成元基因组文库。一种前体化学物质将被提供给培养物；如果前体被转化为生物传感器所感知的生化物质，细胞将发出荧光并可被分离。将对这些分离株进行鉴定，以确定与酶活性有关的遗传因素。一旦开发出来，这种方法就有可能快速准确地从难以培养的生物体中识别酶基因，从而提供一种新的手段，通过它来探索更大范围的元基因组空间。

DESCRIPTION (provided by applicant): Effective screening of metagenomic libraries will enable the exploration of the great diversity of microbes in nature that are responsible for many interesting and valuable functions necessary for human life. For example, in the human gut, the bacterial community detoxifies harmful chemicals, synthesizes vitamins, and helps digest nutrients that the human body cannot digest by itself, among other vital functions. Unfortunately, the vast majority of bacteria cannot be cultured in a laboratory, so the genetic basis of the biocatalytic activity often goes undiscovered. The microbiology workhorse organism E. coli can house genetic collections of these bacterial communities' genomic DNA (known as metagenomic libraries). Screening of metagenomic libraries is inefficient due to two main limitations. First, E. coli is often unable to recognize heterologous promoters in the metagenomic library. Second, searching for biocatalytic functions often involves screening for the presence of small molecules, which can be time and resource intensive. The proposed solution is to develop a culture-independent method for high-throughput screening of metagenomic libraries. In the first aim, it is proposed that by expressing transcription machinery (sigma factors) from prokaryotes phylogenetically distant from the host, the host's RNA polymerase will better recognize heterologous promoters, improving transcription of the genetic elements in metagenomic libraries. To improve heterologous gene expression from metagenomic libraries, sigma factors will be expressed in host strains from a range of bacterial species (including Bacillus subtilis and Lactobacillus plantarum). Transcription of heterologous libraries will be quantified by fusing the green fluorescent protein gene to small library inserts and measuring fluorescence with flow cytometry. The expression level of heterologous sigma factors will be optimized by engineering the promoters and ribosomal binding sites (RBS) in order to obtain a good expression strain. Using this system, a metagenomic library will be constructed from soil bacteria and screened for genes imparting enhanced butanol tolerance. In the second aim, a transcriptional activator biosensor system will be incorporated in E. coli to sense a biochemical of interest. The biosensor can sense the intracellular biochemical concentration and induce transcription of the gfp gene. The biosensor will be tuned by promoter and RBS engineering for optimized fluorescence-activated cell sorting, a high-throughput method. Finally, in the third aim, the biosensor system will be incorporated into the heterologous sigma factor expressing strain and transformed with a large-insert, fosmid-based synthetic metagenomic library. A precursor chemical will be supplied to the culture; if the precursor is converted to the biochemical sensed by the biosensor, the cell will fluoresce and can be isolated. These isolates will be characterized to determine the genetic element responsible for the enzymatic activity. Once developed, this method has the potential to quickly and accurately identify enzymatic genes from difficult-to-culture organisms, thereby providing a new means by which to explore a larger part of the large metagenomic space.