A metabolism-centric proteomic map on the genomic scale: enabling functional annotation of the unknown genome

了解代谢网络的生物学是生物技术的关键，其中单细胞生物如芽殖酵母用于生产蛋白质，疫苗或抗生素。由类似反应形成的代谢网络在哺乳动物细胞中运作，并且一生中的变化被认为是衰老和年龄相关疾病的主要驱动力。在这里，我们正在申请一个工业/学术合作伙伴关系，通过创建一个跨越酵母基因组的以酶为中心的定量图谱，将对这个最大的细胞系统的理解提高到一个新的水平。我们与工业合作伙伴Sciex建立了一个独特的技术平台，可以在30分钟内定量80%的代谢酶。我们将应用这个平台来测量大约4800种酵母菌株中的酶，每种酵母菌株一次都缺少一个基因。通过这种方式，我们将基因组中的大多数基因与它们影响的代谢物和代谢酶联系起来。这张图将是迄今为止对真核蛋白质组进行的最全面的研究，它既涉及已知的基因，也涉及迄今为止只有很少或没有功能信息的基因。我们将通过两种方式了解新基因的功能，首先通过研究它们对蛋白质组和代谢的直接影响，并根据它们的蛋白质组足迹将它们与已知基因联系起来。由于这些原因，该项目对质谱制造业具有独特的价值，该行业寻求将蛋白质组学技术引入环境分析的可能性，对生物技术，缺乏有关代谢网络的信息，以便他们可以利用它来改善生产周期，以及基础科学，这将获得对新基因功能的独特见解，并可以利用它来开发解决衰老相关疾病的新策略。

Understanding the biology of the metabolic network is key for biotechnology, where single cellular organisms such as budding yeast are used to produce proteins, vaccines or antibiotics. A metabolic network formed from similar reactions operates in mammalian cells, and changes during a lifetime being considered a main driver of ageing and age-associated disorders. Here we are applying for an industrial/academic partnership that will bring a new level into the understanding of this largest of all cellular systems, by creating an enzyme-centric quantitative map that spans the yeast genome. With our industrial partner Sciex, we establish a unique technological platform that can quantify 80% of metabolic enzymes in less than 30 minutes. We will apply this platform to measure enzymes in a collection of ~4800 yeast strains, each of which is lacking one gene at a time. In this way, we connect the majority of all genes in the genome with the metabolites and metabolic enzymes they affect. This map will be the most comprehensive investigation into a eukaryotic proteome conducted so far, and address both already known genes, and genes for which there is only little or no functional information so far available. We will learn about the function of new genes in two ways, first by studying their direct impact on the proteome and metabolism, and by associating them with the already known genes on the basis of their proteomic footprint. For these reasons, the project is of unique value to the mass spec manufacturing industry, that seeks possibilities to bring proteomic technology into environmental analytics, to biotechnology, that lacks information about metabolic networks so that they can exploit it for improving production cycles, and for basic science, that will gain unique insights into the function of novel genes and can use it to develop new strategies for addressing ageing-associated disease.