PSEA-Quant: A Protein Set Enrichment Analysis on Label-Free and Label-Based Protein Quantification Data

The majority of large-scale proteomics quantification methods yield long lists of quantified proteins that are often difficult to interpret and poorly reproduced. Computational approaches are required to analyze such intricate quantitative proteomics data sets. We propose a statistical approach to computationally identify protein sets (e.g., Gene Ontology (GO) terms) that are significantly enriched with abundant proteins with reproducible quantification measurements across a set of replicates. To this end, we developed PSEA-Quant, a protein set enrichment analysis algorithm for label-free and label-based protein quantification data sets. It offers an alternative approach to classic GO analyses, models protein annotation biases, and allows the analysis of samples originating from a single condition, unlike analogous approaches such as GSEA and PSEA. We demonstrate that PSEA-Quant produces results complementary to GO analyses. We also show that PSEA-Quant provides valuable information about the biological processes involved in cystic fibrosis using label-free protein quantification of a cell line expressing a CFTR mutant. Finally, PSEA-Quant highlights the differences in the mechanisms taking place in the human, rat, and mouse brain frontal cortices based on tandem mass tag quantification. Our approach, which is available online, will thus improve the analysis of proteomics quantification data sets by providing meaningful biological insights

Sheathless Capillary Electrophoresis-Tandem Mass Spectrometry for Top-Down Characterization of <i>Pyrococcus furiosus</i> Proteins on a Proteome Scale

Intact protein analysis via top-down mass spectrometry (MS) provides the unique capability of fully characterizing protein isoforms and combinatorial post-translational modifications (PTMs) compared to the bottom-up MS approach. Front-end protein separation poses a challenge for analyzing complex mixtures of intact proteins on a proteomic scale. Here we applied capillary electrophoresis (CE) through a sheathless capillary electrophoresis-electrospray ionization (CESI) interface coupled to an Orbitrap Elite mass spectrometer to profile the proteome from <i>Pyrococcus furiosus</i>. CESI-top-down MS analysis of <i>Pyrococcus furiosus</i> cell lysate identified 134 proteins and 291 proteoforms with a total sample consumption of 270 ng in 120 min of total analysis time. Truncations and various PTMs were detected, including acetylation, disulfide bonds, oxidation, glycosylation, and hypusine. This is the largest scale analysis of intact proteins by CE-top-down MS to date

Sheathless Capillary Electrophoresis-Tandem Mass Spectrometry for Top-Down Characterization of <i>Pyrococcus furiosus</i> Proteins on a Proteome Scale

Intact protein analysis via top-down mass spectrometry (MS) provides the unique capability of fully characterizing protein isoforms and combinatorial post-translational modifications (PTMs) compared to the bottom-up MS approach. Front-end protein separation poses a challenge for analyzing complex mixtures of intact proteins on a proteomic scale. Here we applied capillary electrophoresis (CE) through a sheathless capillary electrophoresis-electrospray ionization (CESI) interface coupled to an Orbitrap Elite mass spectrometer to profile the proteome from <i>Pyrococcus furiosus</i>. CESI-top-down MS analysis of <i>Pyrococcus furiosus</i> cell lysate identified 134 proteins and 291 proteoforms with a total sample consumption of 270 ng in 120 min of total analysis time. Truncations and various PTMs were detected, including acetylation, disulfide bonds, oxidation, glycosylation, and hypusine. This is the largest scale analysis of intact proteins by CE-top-down MS to date

Discovery of Cell Compartment Specific Protein–Protein Interactions using Affinity Purification Combined with Tandem Mass Spectrometry

Affinity purification combined with tandem mass spectrometry (AP-MS/MS) is a well-established method used to discover interaction partners for a given protein of interest. Because most AP-MS/MS approaches are performed using the soluble fraction of whole cell extracts (WCE), information about the cellular compartments where the interactions occur is lost. More importantly, classical AP-MS/MS often fails to identify interactions that take place in the nonsoluble fraction of the cell, for example, on the chromatin or membranes; consequently, protein complexes that are less soluble are underrepresented. In this paper, we introduce a method called multiple cell compartment AP-MS/MS (MCC-AP-MS/MS), which identifies the interactions of a protein independently in three fractions of the cell: the cytoplasm, the nucleoplasm, and the chromatin. We show that this fractionation improves the sensitivity of the method when compared to the classical affinity purification procedure using soluble WCE while keeping a very high specificity. Using three proteins known to localize in various cell compartments as baits, the CDK9 subunit of transcription elongation factor P-TEFb, the RNA polymerase II (RNAP II)-associated protein 4 (RPAP4), and the largest subunit of RNAP II, POLR2A, we show that MCC-AP-MS/MS reproducibly yields fraction-specific interactions. Finally, we demonstrate that this improvement in sensitivity leads to the discovery of novel interactions of RNAP II carboxyl-terminal domain (CTD) interacting domain (CID) proteins with POLR2A

Physiological and Molecular Alterations Promoted by <i>Schizotetranychus oryzae</i> Mite Infestation in Rice Leaves

Infestation of phytophagous mite <i>Schizotetranychus oryzae</i> in rice causes critical yield losses. To better understand this interaction, we employed Multidimensional Protein Identification Technology (MudPIT) approach to identify differentially expressed proteins. We detected 18 and 872 unique proteins in control and infested leaves, respectively, along with 32 proteins more abundant in control leaves. <i>S. oryzae</i> infestation caused decreased abundance of proteins related to photosynthesis (mostly photosystem II-related), carbon assimilation and energy production, chloroplast detoxification, defense, and fatty acid and gibberellin synthesis. On the contrary, infestation caused increased abundance of proteins involved in protein modification and degradation, gene expression at the translation level, protein partitioning to different organelles, lipid metabolism, actin cytoskeleton remodeling, and synthesis of jasmonate, amino acid, and molecular chaperones. Our results also suggest that <i>S. oryzae</i> infestation promotes cell-wall remodeling and interferes with ethylene biosynthesis in rice leaves. Proteomic data were positively correlated with enzymatic assays and RT-qPCR analysis. Our findings describe the protein expression patterns of infested rice leaves and suggest that the acceptor side of PSII is probably the major damaged target in the photosynthetic apparatus. These data will be useful in future biotechnological approaches aiming to induce phytophagous mite resistance in rice