Exponentially Modified Protein Abundance Index (emPAI) for Estimation of Absolute Protein Amount in Proteomics by the Number of Sequenced Peptides per Protein

Abstract

Proteomic LC-MS approaches combined with genome-annotated databases currently allow identification of thousands of proteins from complex mixtures (1). Approaches have also been developed for relative quantitation using stable isotope labeling (2-4). Recently not only comprehensive quantitation studies between two states (5, 6) but also protein-protein (7, 8), protein-peptide (9), and protein-drug (10) interaction analyses have been reported. So far, however, a comprehensive approach for determining protein concentrations in one sample has not been established. Protein concentrations are one of the most basic and important parameters in quantitative proteomics because the kinetics/dynamics of the cellular proteome is described in terms of changes in the concentrations of proteins in particular compartments. Biological experiments often require at least some information on protein abundance for correct interpretation. In the past, crude quantitative information could be drawn from the intensity of gel staining in comparison to a known amount of marker protein. However, in complex mixture analysis, individual proteins cannot be stained individually, and usually all information about protein abundance is lost. So far, isotope-labeled synthetic peptides have been used as internal standards for absolute quantitation of particular proteins of interest (11,12). This approach is in principle applicable to comprehensive analysis but is hampered by the high cost of isotope-labeled peptides as well as the difficulty of quantitative digestion of proteins in-gel (13).Even a single nano-LC-MS/MS analysis can easily generate a long list of identified proteins with the help of database searching, and additional information can be extracted, such as the hit rank in identification, the probability score, the number of identified peptides per protein, ion counts of identified peptides, LC retention times, and so on. Qualitatively some parameters, such as the hit rank, the score, and the number of peptides per protein (14), can be considered as indicators for protein abundance in the analyzed sample. Among them, the integrated ion counts of the peptides identifying each protein would be the most direct parameter to describe the abundance and has been used to compare protein expression in different states (15). However, a mass spectrometer is not as versatile as an absorbance detector because of limited linearity and possibly because of background and ionization suppression effects (16). Therefore, it is necessary to normalize these parameters to obtain at least approximate quantitative information. The first approach to achieve this, to our knowledge, was to use the number of peptides per protein normalized by the theoretical number of

Proteomic analysis reveals different composition of extracellular vesicles released by two Trypanosoma cruzi strains associated with their distinct interaction with host cells

“…Maximum false peptide and protein discovery rate (FDR) was 1%. Label-free quantitative analysis of Mascot proteomic data was achieved by spectral counting after calculating the exponentially modified protein abundance index (emPAI) for each identified protein [25] (http://www.matrixscience.com/help/quant_empai_help.html). Statistical analysis of the label-free, spectral counting quantitative data was performed by a two-sided Student’s t test, with p  < 0.05 (http://www.matrixscience.com/help/quant_statistics_help.html).…”

Large‐scale proteomic analysis of tyrosine‐phosphorylation induced by T‐cell receptor or B‐cell receptor activation reveals new signaling pathways

“…When multiple accession were obtained with same set of peptides, a representative IPI accession was chosen by the order of priority, (i) IPI accession containing NCBI GeneID, (ii) IPI accession using Swiss-Prot as master sequence, (iii) IPI accession using TrEMBL as master sequence. Semiquantitative estimation of protein abundance was based on the number of identified peptides [20]. The number of identified peptides in each experiment was thus counted and normalized by the number of peptides theoretically detectable with our instrument settings (molecular mass of 900-4000 Da).…”

Comparative proteomics of twoMycoplasma hyopneumoniaestrains andMycoplasma flocculareidentified potential porcine enzootic pneumonia determinants

“…For quantitative comparisons between ortholog proteins shared between (i) M. hyopneumoniae 7448 and M. hyopneumoniae J; (ii) M. hyopneumoniae 7448 and M. flocculare ; and (iii) M. hyopneumoniae J and M. flocculare , the analyzes were based on the exponentially modified protein abundance index (emPAI) values [66]. EmPAI values were calculated for each protein in the Scaffold software, not using the normalization option, to allow intraprotein (between ortholog proteins), and intersample ( M. hyopneumoniae 7448 vs. M. hyopneumoniae J; M. hyopneumoniae 7448 vs. M. flocculare ; or M. hyopneumoniae J vs. M. flocculare ) comparisons.…”