Combined /omics approaches to understand and control library enriched microbial cell factories

生物过程发展所需的动态生物行为理解不能仅仅通过个体水平/组学研究来预测，因为这种方法只讲述了故事的一部分。因此，我们将实施一种分析技术，基于在大肠杆菌中表达的几种不同的基于质粒的基因组文库(来自两种细菌，大肠杆菌和空肠弯曲菌)，并结合微阵列(信使RNA水平)和蛋白质组(细胞的蛋白质补体)的测量，以了解和改进分泌型糖基化蛋白的生产生物过程。这些类型的蛋白质的生产对制药业非常重要，因为对人类具有治疗重要性的近四分之三的蛋白质是糖基化的(要么释放，要么在临床和临床前开发中)。从最简单的生物体到最复杂的生物体，将信息从基因组转移到蛋白质的过程是普遍的，也是生命的核心。理解和量化这一过程对于科学进步至关重要。有了这些信息，就有可能操纵生物体来实现预期的生物技术目标，例如生产用于医疗目的的蛋白质，以及取代合成化学品。基因组序列是对生物体运作方式进行编程的代码。基因组测序为识别基因和分配这些基因的潜在功能提供了一个信息数据库，并允许比较不同物种的相似基因。当基因启动一种生物功能时，就会产生一种信息，最终形成一种蛋白质。已经开发出了在数千个基因中利用这种信息信息的实验技术，例如Scales(文库丰富的多尺度分析)。这一信息领域被称为转录学。然而，转录学不能仅仅用来预测未来生物技术发展所需的动态生物行为，因为这种方法只讲述了故事的一部分。尺度中缺失的信息是这些基因信息是如何被使用的。我们需要的是对来自基因组的信息和蛋白质的生产进行综合研究。为了实现这一点，我们还将实施一种分析技术，类似于专注于蛋白质而不是基因组的标尺。重要的是要检查生物体的蛋白质补充(称为蛋白质组)，因为观察到的生物体的身体健康和行为是由其基因组与环境的相互作用决定的，这种相互作用直接源于蛋白质，而不是基因组及其随后的信息(转录组)。使用我们研究蛋白质的技术(称为MLPPTM)，以及研究基因组信息的实验技术，如Scale，我们将能够提供一项综合研究，产生关于哪些蛋白质帮助赋予细胞某些特性的更深层次的知识。在这种情况下，我们试图了解哪些蛋白质会增强细胞产生糖基化蛋白质(那些带有连接的寡糖的蛋白质)的能力。这一点很重要，因为大多数应用于人类健康的蛋白质都是糖蛋白。细菌通常被认为不能产生这些蛋白质，因此使用了更复杂的生物体(如哺乳动物)。细菌更容易理解，生长更快，成本更低，因此如果它们能被设计成适当地生产糖基化蛋白质，将非常有吸引力。将在这里实施的检测包含过表达文库的大肠杆菌的综合转录和蛋白质组学技术将使我们能够在成功时改善细菌中糖基化蛋白质的生产，并为未来制造治疗性蛋白质的高效生物过程奠定基础。

The dynamic biological behaviour understanding needed for bioprocess development cannot be predicted solely by individual level /omic studies, since this approach only tells a proportion of the story. Therefore, we will implement an analytical technique, based on several different plasmid based genomic libraries (from two bacteria, Escherichia coli and Campylobacter jejuni) expressed in E. coli, coupled with measurements at the microarray (messenger RNA level) and proteome (protein complement of the cell) scale, to understand and improve the secreted glycosylated protein production bioprocess. Production of these types of proteins is very important to the pharmaceuticals industry, since nearly three quarters of proteins with human therapeutic importance are glycosylated (either released or in clinical and preclinical development). From the simplest to the most complex organisms, the process of transferring information from the genome to make proteins is universal and central to life. Understanding and quantifying this process is essential for scientific advancement. With such information it will become possible to manipulate organisms to achieve a desired biotechnological goal, such as production of proteins for medicinal purposes, and the replacement of synthetic chemicals. A genome sequence is the code for programming the way an organism functions. Sequencing the genome provides a database of information for identifying genes and assigning the potential function of these genes, and allows for comparison of similar genes across species. When genes switch on to start a biological function, a message is generated, that eventually makes a protein. Experimental technologies that exploit this message information across thousand of genes have been developed, such as SCALEs (multi-Scale Analysis of Library Enrichment). This field of information is known as transcriptomics. Transcriptomics, however, cannot be used solely to predict the dynamic biological behaviour needed for future biotechnology development, since this approach only tells a proportion of the story. The information missing from SCALEs is how these gene messages are used. What is needed is an integrated study of the message from the genome with the production of proteins. In order to achieve this, we also will implement an analytical technique, similar to SCALEs that will concentrate on the proteins rather than the genome. It is important to examine the protein complement of the organism (known as the proteome), because the observed physical health and behaviour of an organism is determined by the interaction of its genome with the environment, and this interaction is directly due to the proteins, rather than the genome, and its subsequent message (the transcriptome). Using our technique (called MLPPTM) which studies proteins, and experimental techniques such as SCALEs, which study the message from the genome, we will be able to provide an integrated study which generates a deeper knowledge of which proteins help give a cell certain properties. In this case, we seek to understand which proteins will give a cell an enhanced ability to generate glycosylated proteins (those with a linked oligosaccharide). This is important because the majority of proteins applied towards human heath applications are glycoproteins. Bacteria have not generally been thought of as being able to produce these proteins, and so more complicated organisms (eg from mammals), have been used instead. Bacteria are simpler to understand, grow faster and cheaper, and so would be very attractive if they could be designed to produce glycosylated proteins properly. The integrated transcriptomic and proteomic techniques examining E.coli containing overexpression libraries to be implemented here will allow us, when successful, to improve on glycosylated protein production in a bacterium, and set the scene for future efficient bioprocesses for making therapeutic proteins.