Project description:Comparison of two solid-phase extraction (SPE) methods for the identification and quantification of porcine retinal protein markers by LC MS/MS
Project description:Label-free absolute quantitative proteomics is commonly used for absolute quantification of the proteome or specific proteins of interest in various biological samples. Current label-free absolute protein quantification (APQ) methods determine MS1 intensities, MS2 spectral counts or intensities to absolutely quantify protein concentrations from data obtained from data-dependent acquisition (DDA). In recent years, label-free data-independent acquisition (DIA) has seen increasing use as a powerful tool for relative protein quantification. Here we present a novel label-free DIA-based absolute protein quantification (DIA-APQ) method for the absolute quantification of protein expressions from DIA data. To validate this method, both DDA and DIA experiments were performed on 36 individual human liver microsome and S9 samples. The DIA-APQ assay was able to quantify approximately twice as many proteins as the DDA MS1-based APQ method whereas protein concentrations determined by the two methods were comparable. To evaluate the accuracy of the DIA-APQ method, we absolutely quantified carboxylesterase 1 concentrations in human liver samples using an established SILAC internal standard-based proteomic assay; the SILAC results were consistent with those obtained from DIA-APQ analysis. Finally, we employed a unique algorithm in DIA-APQ to distribute the MS signals from shared peptides to different protein isoforms and successfully applied the DIA-APQ method to the absolute quantification of several drug-metabolizing enzyme isoforms in human liver microsomes. This novel DIA-based APQ method not only provides a powerful approach for absolutely quantifying entire proteomes and specific candidate proteins, but also has with the capacity differentiating protein isoforms.
Project description:The goal of this project is to compare label free quantification, chemical labeling with tandem mass tags, and data independent acquisition discovery proteomics approaches using lung squamous cell carcinomas and adjacent lung tissues.
Project description:The goal of this project is to compare label free quantification, chemical labeling with tandem mass tags, and data independent acquisition discovery proteomics approaches using lung squamous cell carcinomas and adjacent lung tissues.
Project description:The goal of this project is to compare label free quantification, chemical labeling with tandem mass tags, and data independent acquisition discovery proteomics approaches using lung squamous cell carcinomas and adjacent lung tissues.
Project description:The endosymbiotic interaction established by cnidarians and photosynthetic dinoflagellate algae is the foundation of coral reef ecosystems. This essential interaction is globally threatened to breakdown by anthropogenic disturbance. As such, it is compelling to understand the molecular mechanisms underpinning the cnidarian-algal association. We investigated phosphorylation-mediated protein signaling as a mechanism of regulation of the cnidarian-algal interaction, and we report on the generation of the first phosphoproteome for the coral model system Aiptasia. Using mass spectrometry-based phosphoproteomics in data-independent acquisition (DIA) allowed consistent quantification of over 3,000 phosphopeptides totaling more than 1,600 phosphoproteins across aposymbiotic (symbiont-free) and symbiotic anemones. Additionally, to allow for discrimination between translational regulation and post-translational phosphorylation, we generated a total proteome dataset from the same anemones and used it for phosphopeptide normalization against protein amount. While quantification of protein phosphorylation relied upon the generation of a spectrum library generated by data-dependent acquisition (DDA), total protein quantification in DIA was conducted "library-free" (directDIA) in SpectronautX. DirectDIA allowed consistent quantification of 20,215 peptides, totaling 4,121 proteins (3,518 protein groups) across biological samples.
Project description:The goal of this project is to compare label free quantification, chemical labeling with tandem mass tags, and data independent acquisition discovery proteomics approaches using lung squamous cell carcinomas and adjacent lung tissues.