Molecular scanner experiment with human plasma: improving protein identification by using intensity distributions of matching peptide masses.
The development of high throughput utilities to identify proteins is a major challenge in present research in the field of proteomics. One such utility, the molecular scanner, uses proteins separated by two-dimensional polyacrylamide gel electrophoresis that are digested in the gel and during transfer onto a collecting membrane. After adding a matrix, the membrane is inserted into a matrix-assisted laser desorption/ionization-time of flight mass spectrometer and a peptide mass fingerprint (PMF) is measured for every scanned site. Since the spacing between scanned sites is much smaller than the size of the most abundant protein spots, there is a certain redundancy in the data that was used in an earlier experiment with Escherichia coli [1] to improve mass calibration and PMF identification results. It was observed that the signal intensity of a peptide mass as a function of the position on the membrane showed similar patterns if peptides stemmed from the same protein. Taking account of these similarities a clustering algorithm was used to find lists of experimental masses with similar intensity distributions, which provided clearer identification of the corresponding proteins. Here, these methods are applied to a human plasma scan, where proteins were highly modified and less separated. The presence of very abundant proteins like albumin and immunoglobulins added another difficulty. The calibration of the initial PMFs was not satisfactory and masses had to be recalibrated. After discarding chemical noise, the membrane was partitioned into regions and for each region protein identification was carried out separately. A new scoring method was used, where the PMF score was multiplied by a factor that measures the similarity of matching peptides. This method proved to be more robust than the method developed in [1] if the region where a protein was found had an extended, nonspherical shape and strong overlap with regions of other proteins. Many proteins annotated on the SWISS-2D PAGE human plasma master gel could be clearly identified and many interesting properties were observed.
Müller
Markus
M
Swiss Institute of Bioinformatics, Geneva, Switzerland. markus.mueller@isb-sib.ch
Gras
Robin
R
Binz
Pierre-Alain
PA
Hochstrasser
Denis F
DF
Appel
Ron D
RD
D000465:Algorithms; D001709:Biotechnology / Q000639:trends; D002138:Calibration; D019992:Databases as Topic; D015180:Electrophoresis, Gel, Two-Dimensional; D004926:Escherichia coli / Q000378:metabolism; D006801:Humans; D006863:Hydrogen-Ion Concentration; D015233:Models, Statistical; D010455:Peptides / Q000737:chemistry*; D010949:Plasma / Q000378:metabolism*; D020543:Proteome; D012984:Software; D013223:Statistics as Topic; D014357:Trypsin / Q000494:pharmacology
D010455:Peptides; D020543:Proteome; D014357:Trypsin