Future trends for proteomics

The awarding of the Nobel Prize in chemistry to Fenn, Tanaka, and Wüthrich for their work on methods for the identification and structural characterisation of biomolecules has heralded the increasing importance of proteomics in biomedical and fundamental research. Today, vendors offer a variety of mass spectrometric instruments to provide a growing number of laboratories access to technologies best suited to address their research questions. The improvements in instrument sophistication have been matched with improvements in analytical software to increase the amount of data obtained from the proteomic samples. The last decade has also seen an increasing integration of automation so that core laboratories can now operate on a 24/7 schedule. Perhaps most importantly, the rising prominence of proteomics is due to the new generation of proteomics researchers being trained worldwide.

Building upon the Human Genome Project, biomedical research was the early proving ground for developments and improvements in proteomics. The earliest experiments looked to unravel the detail of a healthy living cell and compare its characteristics to a cell in a diseased state such as cancer or diabetes. Our early involvement included participation in the Cell Map Project, led by Dr. John Bergeron at McGill University, which aimed to perform the most complete cartography of the rat liver cell by identifying the maximum sets of proteins associated with major organelles (Cell, 2006, Dec 15; 127(6):1265-81). Our experience and expertise has since grown to allow us to collaborate with scientists across the life sciences.

During the past two years we have witnessed an expansion of proteomic applications from the health sciences to plants, bacteria, bio-fuel and nutrients. In these cases proteomics has given invaluable information to the scientists yearning for a deeper understanding of their samples of interest. An example is the proteomic analysis performed for a scientist who created several genomic variants of a crop. Using mass spec techniques we generated lists of expressed proteins for each variant, which allowed the identification of the variant with the highest nutritive value. Under similar experimental strategies, proteomics could be used for the screening of potential candidates, where only those meeting certain targets would be sent for more detailed studies, thus saving time and money.

Proteomics analyses have often been hindered by the extremely low quantity of biological starting material. With the advent of nanoflow HPLC, which allowed reliable chromatographic separation of biomolecules at flowrates of nanoliters per minute, proteomics can now be extended to limited samples. With nanoflow technology, reversed phase chromatographic columns with an internal diameter (ID) of 75 μm were created to accommodate low flow rate separation. This provided a tremendous analytical advantage since 75 μm ID gives a 3750 fold increase in sample concentration as compared to 4.6mm ID columns previously used. An injection of as little as 20 μL of sample is now sufficient to generate results which were impossible to get with the prior chromatographic technology.

Following the improvements in the technologies, the challenge in proteomics has rapidly shifted from analytical techniques to meeting the needs of data handling and interpretation. For example, as soon as nanoflow HPLC was coupled to mass spectrometers, the data size of a single sample analysis now ranges between 400 Mbytes and 1 Gbyte. In core facilities like ours, with multiple instruments running continuously, it was imperative to implement an efficient data management system able to archive and retrieve data, even years after the experiments were conducted. An even more critical aspect concerned the ability to conduct the comprehensive protein database searches required to identify the proteins within the sample. Manually analysing a MS/MS spectrum is now an impossible task, since millions of MS/MS spectra are continuously being generated. Fortunately, several computational database searching programs have been created to process the data and identify the proteins using publicly available and/or internal databases. Additional types of software has emerged recently which can process the proteomic results obtained from the database searches and create graphical outputs that simplifies the examination of the data and allows fast statistical comparisons between samples. Currently, data from comparisons of disease state cells can be compared to their controls in a matter of minutes by a single analyst, in contrast to months or even years for a whole team before this type of software was made available. These computational methodologies for comprehensive and robust analyses further free the scientists to allow them to focus on the results of their research and design their next experiments.

What are the future trends for proteomics?

We are already participating in research projects requiring the integration of genomics and proteomics approaches from any given organism. Several laboratories have already initiated this course of action and these systems biology approaches will increase over the coming years. In biomedical and life science studies striving to advance our understanding of the functional consequences of genetic variation, we increasingly need to be monitoring genome structure and variation, chromatin configuration (epigenomics), gene expression (transcriptomics), and protein expression and interactions. Integrated genomics and proteomics will allow scientists to monitor the level of expression of target proteins on the background of genomic processes to further characterise the behavior of the organism at the molecular level.

As with the progression of proteomics from human biomedical research throughout the life sciences, we are already seeing elements of integrative proteomics being carried out in non-human systems. For example, our Centre has been involved in the genome sequencing of epidemic and non-epidemic strains of the bacterial pathogen C. difficile following outbreaks in Québec (N Engl J Med. 2005, Dec 8; 353(23):2442-9). In order to confirm the localisation and expression of surface layer proteins, we have developed protocols to perform proteomic analyses of cell wall proteins in tandem with genome sequencing. Studies of this nature will aid in bacterial genome annotation of genes and their functions, as well as provide candidates for future studies of antibody based strategies for detection, diagnosis, and vaccine development.

The “omics” technologies have always been characterised by combining multi-disciplinary expertise’s in biology, genetics, computer science, and engineering. This trend is continuing as we are now building the resources to comprehensively study how mutations affect genome structure, gene expression, protein function and interactions to contribute to the complex phenotypic outcomes we observe in diseases, and to offer new insights into future treatment.