Identifying differences in protein expression levels by spectral counting and feature selection

Spectral counting is a strategy to quantify relative protein concentrations in pre-digested protein mixtures analyzed by liquid chromatography online with tandem mass spectrometry. In the present study, we used combinations of normalization and statistical (feature selection) methods on spectral counting data to verify whether we could pinpoint which and how many proteins were differentially expressed when comparing complex protein mixtures. These combinations were evaluated on real, but controlled, experiments (yeast lysates were spiked with protein markers at different concentrations to simulate differences), which were therefore verifiable. The following normalization methods were applied: total signal, Z-normalization, hybrid normalization, and log preprocessing. The feature selection methods were: the Golub index, the Student t-test, a strategy based on the weighting used in a forward-support vector machine (SVM-F) model, and SVM recursive feature elimination. The results showed that Z-normalization combined with SVM-F correctly identified which and how many protein markers were added to the yeast lysates for all different concentrations. The software we used is available at http://pcarvalho.com/patternlab.

Identification of membrane proteins in the hyperthermophilic archaeon pyrococcus furiosus using proteomics and prediction programs.

Cell-free extracts from the hyperthermophilic archaeon Pyrococcus furiosus were separated into membrane and cytoplasmic fractions and each was analyzed by 2D-gel electrophoresis. A total of 66 proteins were identified, 32 in the membrane fraction and 34 in the cytoplasmic fraction. Six prediction programs were used to predict the subcellular locations of these proteins. Three were based on signal-peptides (SignalP, TargetP, and SOSUISignal) and three on transmembrane-spanning alpha-helices (TSEG, SOSUI, and PRED-TMR2). A consensus of the six programs predicted that 23 of the 32 proteins (72%) from the membrane fraction should be in the membrane and that all of the proteins from the cytoplasmic fraction should be in the cytoplasm. Two membrane-associated proteins predicted to be cytoplasmic by the programs are also predicted to consist primarily of transmembrane-spanning beta-sheets using porin protein models, suggesting that they are, in fact, membrane components. An ATPase subunit homolog found in the membrane fraction, although predicted to be cytoplasmic, is most likely complexed with other ATPase subunits in the membrane fraction. An additional three proteins predicted to be cytoplasmic but found in the membrane fraction, may be cytoplasmic contaminants. These include a chaperone homolog that may have attached to denatured membrane proteins during cell fractionation. Omitting these three proteins would boost the membrane-protein predictability of the models to near 80%. A consensus prediction using all six programs for all 2242 ORFs in the P. furiosus genome estimates that 24% of the ORF products are found in the membrane. However, this is likely to be a minimum value due to the programs' inability to recognize certain membrane-related proteins, such as subunits associated with membrane complexes and porin-type proteins.