Discovery Proteomics
In discovery proteomics, the most abundant proteins are indiscriminately detected and quantitated by LC-MSMS. Mostly bottom-up proteomics approaches are used. Here proteins are extracted from a sample. The proteins are then digested into peptides. The peptides are then separated by liquid chromatography and analysed by mass spectrometry. The mass spectrometer detects peptide masses/charge ratios and measures their intensities.
In Data-Dependent Analysis (DDA), the most abundant peptides are selected for fragmentation. The fragmentation spectra are then detected and used for peptide spectral matching (PSM). Peptides are used to infer protein identity and abundance. Only the peptides selected for fragmentation can be identified and used to identify proteins.
In Data-Independent Analysis (DIA), collections of peptides are selected for fragmentation in defined mass ranges. Using a spectral library, selected peptide fragments are extracted from the fragmentation spectra. These fragments are used to determine peptide abundance, which is translated to proteins abundance. If later additional information is available the spectra may be searched again for additional proteins.
Relative protein abundance between sample groups is then functionally annotated to determine the mechanism responsible for the differences observed in the biological systems.
Sample Preparation
Data Generation
Mass spectrometers consist of three parts; A source, an analyser and a detector. Peptides are ionised and introduced into the mass spectrometer via the source. The mass analyser separates peptides based on their mass/charge ratio, and the detector then measures them. The resultant data is a mass/charge ratio and intensity value for each analyte.
A diversity of state of the art mass spectrometers are available locally. Different configuration of sources, analysers and detectors enable slightly different analysis methodologies. The local machines were selected for specific functions, to address a diversity of local needs. It is important to consult with an expert when choosing the mass spectrometer to be used for a specific project.
Databases
Proteomics databases which contain protein sequences for peptide spectral matching
Peptide Spectral Matching
Tandem mass spectra matched to theoretical spectra from protein sequence database
Quantitation Analysis
Once peptides have been identified and relative protein abundances determined, statistical tests determine which of the protein as significantly deferentially expressed between biological conditions and require further study.
Functional Annotation
Once a list of significantly deferentially expressed proteins has been determined. These proteins need to be functionally annotated in order to determine what potential roles they may be playing in the biological system. Using over-representation analysis and gene set enrichment, proteins can be assigned to functional units. The classification of these functional units are found within gene ontologies, metabolic pathways and signalling pathway databases.
Bioinformaticians
Bioinformaticians are available to assist you with your project.
The earlier you contact them the more assistance they will be able to offer. In particular, the experimental design is critical in ensuring the success of any project. Contacting a statistician and ensuring your experiment has enough statistical power will go a long way to ensuring its success.
Selecting the best technology for your project will ensure you get the best results for the your project. Omics research is costly, choosing the most appropriate technology for you experiment and budget is therefor critical.
It is best to first run a pilot study and having an expert check the quality of the results before continuing with the bulk of the analysis. The pilot project will also allow you to familiaries yourself with the sample analysis process, the data generated and the means of analysis, before embarking on the main project.
Once you have produced the data, you will realise omics technologies produce mountains of data. It often requires some expertise in handling big data, to deal with the amounts of data produced. Fortunately we have tools and resources to store and process your data making it easy for you to understand. Contact our team of expert bioninformaticians for assistance on all levels of your project.
