Global quantification of the yeast proteome

Lead Research Organisation: University of Manchester
Department Name: Life Sciences


An inventory of the proteins in a cell. A traditional approach to understanding the living cell is to reduce cell complexity to individual parts . We now recognize that this is no longer enough; we need to take a global view of the cell and study it as an integrated system. This 'systems level' approach requires new technologies, and has been led by the ability to measure all of the messenger RNA molecules, the working copies of the genetic blueprint, in a single experiment. But, these mRNA molecules are intermediaries for the true cellular machines, the proteins, and arguably we ought to be studying the latter. However, for many reasons there are no equivalent approaches for large scale quantitative measurement of all proteins in a cell. Yet, if we are to understand the cell as a complex, dynamic system (protein levels go up and down), as well as the complicated interplay between them, we need to have an 'inventory of parts'. We have devised a new technology that is able to measure, very accurately, the number of molecules of each protein and we wish to take on the challenge of building a protein inventory for the best studied cell, that of the baker's yeast. To supplement these data, we also know how to measure how rapidly the parts (proteins) of the cell are made and recycled. This will be the first inventory that has been built that leaves the yeast proteins unaltered whilst being measured and will be of great value to the biological community. To do this we need to roll this technique out on a grand scale to attempt to quantify over 4000 proteins, requiring a long-term project with expertise in yeast biology, protein chemistry, mass spectrometry and bioinformatics. The protein parts are mostly assembled into machines that do the work of the cell. By understanding how such complex machinery is made, we will begin to understand how the cell balances flexibility of response (in time, and in terms of types of machine) with quality control, manufacturing principles and energy costs. Once generated, we will make all our data available to the biological community both from our own website, and also international repositories.

Technical Summary

System level analysis of the cell requires statistically confident knowledge of the amounts of each protein in the cell. The gold standard approach to protein quantification is based on stable isotope internal standards and mass spectrometric determination of the analyte signal relative to that of the standard. For even a simple proteome, such as Saccharomyces cerevisiae, this is a daunting challenge, but, following our discovery and development of QconCAT technology, is now feasible. QconCATs are artificial proteins that comprise concatamers of proteolytic peptides, each of which is an internal standard for quantification of an analyte protein. We will design and build approximately 200 QconCATs to quantify at least 4000 yeast proteins in a demanding study between two Universities with a long track record of collaboration and innovation. We will also conduct robust quality control measures, ensuring very low technical variance, as well as using biological replicates to assess biological variability on a per protein basis. In addition to quantification of each of these proteins, we will use incomplete metabolic labelling to assess the rate at which each protein is turned over (synthesised and degraded) in the cell. These two parameters (quantity and degradation rate) complete the 'state equation' for protein expression, linking transcript level and translational activity and permitting development of a new model of global protein expression. We will generate a wholly new data set that can be used by biologists across the yeast community, and which will inform and develop new systems level analyses of this important model organism. Joint with BB/G009112/1.


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Description We have developed technology to deliver absolute quantitative of the proteins present in a eukaryotic cell, using yeast as an example system. The method is called "QconCAT" and we have now successfully (and directly) quantified over 1100 proteins. Matched numbers are also being generated for protein turnover.

Having reaquired some of the mass spectrometry data on a more modern instrument we are now able to offer more definitive conclusions on the effects of epitope tagging on general proteome, by measuring the changes in intracellular protein abundance in yeast for the tagged protein (on-target) and the rest of the proteome (off-target). This shows that there are often large changes to the proteome, which has implications for biotech researchers using epitope tagged proteins for various applications (such as protein-protein interaction mapping and protein quantification).
Exploitation Route We will distribute the QconCATs upon request, and the key data (the peptides and their designed transitions) will be available from international repositories linked to the ProteomeXchange project. We have also developed theoretical frameworks for designing Qpeptides and applying this to demonsrator systems such as the chaperone proteins in yeast.

Update 2020: A new improved version of the QconCAT standard protocol has been developed and published by Beynon and colleagues, which we now term ALACAT. This uses an improved design protocol with spacer peptides, synthetic biology and cell free synthesis to generate higher fidelity standards as a much faster rate. It has leveraged further funding from BBSRC via a BBR grant BB/S02025X/1 which has just started. The QconCAT grant primed this research. The new standards will be distributed to interested UK groups and it has also leveraged funding and interest from the Rosalind Franklin Institute
Sectors Agriculture, Food and Drink,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology

Description Several other groups have used the QconCAT technology successfully based on our good practice, both within the UK and internationally (judging by published papers). Our data will contribute to international repositories on proteomics. We are writing up a study conducted on the effect of epitope tagging on protein abundance levels in cells, monitorring this via mass spectrometry (having reaquired selected sets of data). This shows that there is often a marked off-target effect on the proteome, and would have consequences for biotechnology sector
First Year Of Impact 2016
Sector Agriculture, Food and Drink,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology
Title Yeast QconCATs 
Description The set of recombinant proteins we produced for absolute quantification of yeast proteins are available, on request from the Liverpool team. The designs themselves are the main deliverable, and the supplementary material of the published paper contains details on this. 
Type Of Material Technology assay or reagent 
Year Produced 2016 
Provided To Others? Yes  
Impact Various groups have benefitted from QconCAT technology, though I don't have details of specific examples. The Liverpool part of this collaborative project has handled this aspect, but I thought it was worth noting for the project as a whole. 
Description Waters collaborations 
Organisation Waters Corporation
Department Waters Corporation Centre of Mass Spectrometry Excellence
Country United Kingdom 
Sector Private 
PI Contribution We helped enable software pipelines for procesing of selected reaction monitorring data for Waters and their customers. This was essential as the key downstream tools could not function with the customers data formats.
Collaborator Contribution Provision of data and inclusion of Dr Lawless on a publication
Impact A publication - Alberio T, McMahon K, Cuccurullo M, Gethings LA, Lawless C, Zibetti M, Lopiano L, Vissers JP, Fasano M. Verification of a Parkinson's disease protein signature in T-lymphocytes by multiple reaction monitoring. J Proteome Res. 2014 Aug 1;13(8):3554-61. doi: 10.1021/pr401142p. Epub 2014 Jul 1. PubMed PMID: 24946097.
Start Year 2014
Title CONSequence 
Description Webtool for the prediction of peptide properties, in order to select the best ones for use in targetted mass spectrometry experiments. It uses a variety of machine learning tools to learn from properties of good "flyers" and then predict them. 
Type Of Technology Webtool/Application 
Year Produced 2012 
Impact It is being included in a wider Galaxy-based pipeline GIO developed by Prof Conrad Bessant at QMUL, with whom we collaborate. This should increase its exposure to the proteomics community. 
Title McPred 
Description A webtool for use in quantitative proteomics experimental design that examine candidate proteins performs an in silico digest and assesses which peptides are most likely to be fully cleaved (least likely to be missed cleaved) and hence, the peptides best suited to be surrogates in a targetted proteoimics experiment. It could also be used to inform quantitative proteomics data analysis pipelines more generally. 
Type Of Technology Webtool/Application 
Year Produced 2012 
Impact The tools has been ported for use, alongside CONSeQuence, to the GIO resource at QMUL for use in the their proteomics focused Galaxy pipeline 
Description Lawless school visit 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Schools
Results and Impact Dr Lawless visited a local primary school to promote science as a career option giving a short presentation including material on data analysis
Year(s) Of Engagement Activity 2010
Description Quantitative proteomics training course 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact We participate in a Training Course, administered via the Biochemical Society, which aims to provide introductory (and advanced) training in Quantitative proteomics and particularly data handling and analysis with hands-on advice. This involves industrial colleagues as well as academics in delivering the course, which we follow with a 2-day meeting on Quantitative proteomics. It is run in Chester, successfully in our view, and is in its 3rd incarnation. Feedback has been excellent. We have it branded with BBSRC and DDIP (the sLoLa project) this year (April 2016) so it will be seen as a BBSRC output too thanks to our involvment (this is being actioned as I type - 08/03/16). It has followed on from previous years when we linked it to a previous LoLa grant to Beynon/Hubbard (BB/G009058/1).
Year(s) Of Engagement Activity 2014,2016