Introduction to MS-Based Proteomics and Bioconductor Infrastructure
Laurent Gatto
Liquid chromatography (LC) – used to separate what we want to measure.
Generates a chromatogram showing everything which hits a detector over time.
Mass spectrometry (MS) – separates peptides based on precursor ions. Generates
mass spectra (MS1 and MS2) showing the population of ions separated by master
charge.
MS automatically selects high peaks, which are broken into fragments to generate
MS2 ions.
These fragment ions are a representation of the original peptide sequence.
MS1 spectra can be collected over time.
MS2 can be matched against a fasta file of proteins. The full proteome from Uniprot
can be used for this.
In silico digestion with the same enzyme leads to peptides and theoretical spectra.
These can be compared to the MS2 from the experiment.
Only MS2 (not MS1) can be used for identification.
Quantification can be at the MS2 or MS1 level.
This data can be analysed within R as an MSnSet.
This class consists of expression data, feature metadata and sample metadata.
Esets are used more in proteomics rather than ranges, which are usually used now
in genomics.
Pbase, PPI (protein-protein interactions) and subcellular localisation can be used in
this analysis.
Using the MSnBase package can compare two spectra.
Want to “unsplice” the proteins to give the exons in the transcript – to find the
boundaries of the original exons.
aa(p) – converts peptides (p) to amino acids.
The amino acids can then be put into co-ordinate space and combined with
transcript models in GRangesList. Peptides can span more than one exon.
This allows transcripts and peptides to be viewed along the same genomic coordinates.
Spatial Proteomics
Cells have well-defined subcellular structures, which have a major effect on
regulation.
Proteins should be studied in the context of a particular cell type, cellular location,
etc.
To divide proteins by cellular structure:
-
Lyse cells, releasing intact cellular content
Generate a density gradient using a sugar solution, apply the cell content and
centrifuge.
Denser organelles will move to the bottom and lighter organelles to the top –
there is a continuous enrichment of different types of organelles.
Selection of fractions along this gradient gives differential enrichment of
organelles.
Marker proteins can be used to distinguish organelles.
There are a set of BioC packages to analyse this data.
Correlation profiles will show which proteins are in a specific system of interest.