The Next Dimension in Proteomics

Cells, tissues, and organisms, including humans, are made of a variety of molecules, including proteins. Proteins are the 'molecular machines' responsible for everything a cell does, from replication to processing nutrients. A typical cell might have 10's of thousands of proteins doing myriad particular chemical 'jobs', including synthesizing or recycling other proteins, so the complement of proteins is constantly changing. The field of proteomics involves detecting as many of these proteins as possible, understanding how they change with time and in reaction to stress or chemical treatment. Knowing this information will allow bioscientists, from basic researchers to clinicians, to better understand what is occurring in the cell under conditions of malnutrition, disease, healthy aging, drought, or even pharmaceutical treatment. Developing better methods to measure the 'proteome' accurately and with sufficient detail is a key underpinning research goal which results in better science, better technology, and ultimately better health and healthier food.

We have recently developed a new technology, called 2-dimensional mass spectrometry, which offers the capability to sequence all peptide/protein components in a sample, rather than a select few. We have demonstrated the technology works in several publications and in preliminary data on a whole proteomic analysis of yeast herein, but there are some particular challenges which we must address before the vision can be attained. This proposal aims to solve those challenges.

Firstly, we will optimise our detection and fragmentation methods to increase protein sequence coverage. Secondly, we will fully characterise the technique to determine the sensitivity, resolution, accuracy, dynamic range, and capacity for quantitation and detection of protein modifications. Thirdly, we will develop a set of algorithms which will convert raw 2-dimensional MS data into protein sequence information and integrate those algorithms into a web-based data processing pipeline for automated proteomic data analysis. Finally, we will compare our newly developed 2-dimensional MS proteomic data sets with existing proteomic methodologies on the exact same set of samples, to clearly show the improvements (both delivered and potential) provided by doing proteomics with an extra dimension.

The overall result of this project will be the development of protocols and methods for optimal proteomic analysis using this exciting new technology and a web-based data analysis pipeline which can process the raw 2-dimensional mass spectrometry data into protein sequence information for whole cells and tissues.

We have recently developed 2-dimensional mass spectrometry (2DMS) to the point where it can now be applied to complex mixtures of proteins and generate unbiased sequence information about all proteins/peptides in proteomics samples. However, for this vision to be realised, a set of challenges must be solved, which is the goal of this proposal.

The test-sample to study for optimizing these methods will be yeast cells, and we will focus on high resolution 2DMS and new fragmentation methods to generate as much information as possible for all the proteins detected in these cells.

Specifically, we will:
1. develop high sequence coverage and depth in proteomic samples using the fragmentation methods of IR-ECD, EID, and UVPD.
2. develop differential extraction protocols which will extract as many detectable proteins and peptides from a sample as possible using solid-phase microextraction and a sample preparation robot.
3. characterise the capabilities of 2DMS with respect to resolution, accuracy, sensitivity, dynamic range, limits of detection, and quantitation.
4. develop top-down methodologies for 2DMS using a combined method called MS/2DMS, and characterise its performance in terms of sequence cleavage coverage and the ability to detect and quantify post-translational modifications.
5. develop algorithms for conversion of raw 2DMS data into protein sequence information including peakpicking, charge-state determination, isotopic distribution alignment, and develop new algorithms for extraction of the new information in 2DMS data contained in neutral-loss lines and precursor scan lines.
6. develop a web-based data analysis pipeline on the Warwick HPC linux clusters for 2DMS data using these algorithms to convert raw data into pseudo MS/MS scan lines for proteomics database search engines.
7. automate the uploading of the peaklists and sequences to online proteomics databases such as PRIDE.
8. directly compare 2DMS with LC-MS/MS for proteomics.

We have recently developed an exciting new 2-dimensional mass spectrometry (2DMS) technology that can be applied in the area of proteomics, provided the challenges discussed herein are solved.

Economy
The proteomics market is substantial, with the annual market for proteomics equipment alone was >$10 billion in 2013 and is expected to reach >$20 billion by 2018. The total research and development effort using proteomics is far larger as these are fundamental tools that allow industrial and research scientists to detect proteins and protein changes in cells as a response to stimuli such as pharmaceutical treatment, disease, or drought. Furthermore, the recent results from various proteomics conferences (including ASMS, HUPO, and the recent BSPR conference in Reading) show that a series of new and credible biomarkers are being developed based on modern proteomics techniques. Fundamental new technologies, like 2DMS, will have a large, long-term impact.

New developments in 2DMS technology, such as those discussed herein, are likely to generate new intellectual property, which can be patented and licensed to commercial agencies such as Bruker UK, Ltd. As it currently exists, the 2DMS technique can already be implemented on any FTICR mass spectrometer, but the bottleneck is in the data processing. The data processing software will clearly also have intellectual property associated with it which can be licensed for further commercial impact.

People:
Economically, this project will train two PDRAs specifically, and those PDRAs will help to train PhD, MSc, and undergraduate project students in the methods of advanced mass spectrometry and proteomics. These trained personnel are a currently limiting resource for the UK bio-pharma, clinical, and medical industries, and they will have a large, long-term impact on that industry. The PDRA's will also be trained in science engagement with the public as part of their outreach activities described in the 'Pathways to Impact' plan.

Science:
Overall, the 2DMS developments proposed herein will improve proteomics, which will improve data quality and analysis for proteomic samples throughout the biochemistry, pharmaceutical, medical, and clinical fields. The ability to know precisely which proteins are present and how they are modified will have a large impact scientifically.

Society:
More specifically, as deliverables for the 'Pathways to Impact Plan', this project will provide a series of software packages and tools for researchers in this area, will provide new teaching materials in mass spectrometry related to 2-dimensional MS techniques, and will generate an internet video of the experiment and technique to help train the next generation of students. Additionally, we will collaborate with our industrial partners to support CASE and other industrially funded PhD students to train those students on samples of interest to our partners, and thereby get those same partners interested and integrated into using these advanced mass spectrometry techniques.

Finally, the ultimate benefit of this research is that it will generate better instruments and methods to generate better proteomic data. This will lead on to better understanding of the underlying causes of aging, health, and disease. That understanding will lead to improved healthcare, diet, and disease treatment which will result in longer, healthier lives.