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

Lead Research Organisation: The Francis Crick Institute
Department Name: Research


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.

Technical Summary

We will create a genome-spanning functional proteomic map of the model eukaryote Saccharomyces cerevisiae, and use it to dissect the compendium of metabolism-regulating genes, and to annotate yet unknown genes on the basis of their proteomic footprint. This map will be created by systematically recording SWATH-MS based proteome profiles from 4800 yeast single gene knock-out strains, representing the fraction of gene deletions viable in the absence of rich nutrient supplementation, chosen to enable growth that is informative about biosynthetic metabolism. This unique large-scale project will be facilitated by an academia/industry partnership to establish a high-throughput variant of SWATH-MS technology invented by the collaborating laboratory of Ruedi Aebersold, and be capable to process thousands of samples in a proteomic experiment by combining microflow-chromatography, advanced ionisation techniques, and data independent acquisition.

Planned Impact

This is an academia-industry collaboration with direct impact. The biotechnological industry will obtain the information about which gene has to be manipulated in the genome to affect 80% of enzymes and can use this information to develop new production strains, save money by improving existing production cycles for instance to reduce greenhouse gas emissions. The mass spectrometry manufacturing industry will get access to a workflow that allows implementing proteomics technology in industrial scale projects, including diagnostics and environmental analytics, and improve access to a new market for proteomics. Enabling proteomics for the large scale will directly benefit society, that depends on diagnostics in medicine and environmental analytics for food production and marketing. Finally, the results clearly impact basic science, as we will substantially improve the annotation of ~2000 budding yeast genes that are functionally yet uncharacterised.
Description We have developed the methods required to quantify proteomes on a large scale. A first manuscript detailing a microflow-LC based proteomics method has been published (doi:10.1038/s41598-018-22610-4), while a new DIA software tool (Demichev et al, 2020) was published in Nature Methods. We have a new development, ScanningSWATH, a method for fast proteome measurements, that is available as a preprint (https://doi.org/10.1101/656793)
Exploitation Route The proteomic methods developed as part of this project might prove useful for a broad variety of research projects; they simplify and reduce costs in the generation of large numbers of proteomes, as required not only in academic research, bust also in diagnostics and industrial applications of proteomics.
Sectors Agriculture, Food and Drink,Healthcare,Pharmaceuticals and Medical Biotechnology

Description As part of the project, fast proteomic methods have been developed. These turned out to not only work on yeast but also, to process human plasma. In part, we have supported the development of a new analytical method, 'Scanning-SWATH' that will be market-released in June 2019 by the project partner SCIEX. In parallel, we have obtained bridge funding, to elaborate to which extent these methods can help to stratify patients for Phase III clinical trials, If this proof of concept is successful, we will fund a Start-Up company, that supports Big Pharma in the conduction of clinical trials.
First Year Of Impact 2019
Sector Healthcare,Pharmaceuticals and Medical Biotechnology
Impact Types Economic

Description Mass spectromery 
Organisation AB SCIEX
Country United States 
Sector Private 
PI Contribution Sciex is the industry and technology partner in this project.
Collaborator Contribution Siex provides the technology platform for the project, maintains it, supports travel for the project members, and provides technical advise.
Impact The project just started, so far the output is a published interview about the importance of large academia-industry collaborations in the 'Analytical Scientist;, provided by Ralser and Sciex.
Start Year 2016