Mass spectrometry (MS)-based isobaric labeling has developed rapidly into a powerful strategy for high throughput protein quantification. Sample multiplexing and exceptional sensitivity allow for the quantification of tens of thousands of peptides and by inference thousands of proteins from multiple samples in a single mass spectrometry experiment. Accurate quantification demands a consistent and robust sample preparation strategy. Here, we present a detailed workflow for SPS-MS3-based quantitative abundance profiling of Tandem Mass Tag (TMT)-labeled proteins and phosphopeptides, which we have termed the Streamlined (SL)-TMT protocol. We describe a universally-applicable strategy that requires minimal individual sample processing and permits the seamless addition of a phosphopeptide enrichment step (“mini-phos”) with little deviation from the deep proteome analysis. To showcase our workflow, we profile the proteome of wild-type S. cerevisiae yeast grown with either glucose or pyruvate as the carbon source. Here, we have established a streamlined TMT protocol that enables deep proteome and medium-scale phosphoproteome analysis.
Highlights d PCIF1 is an evolutionarily conserved mRNA m6Am methyltransferase d Loss of PCIF1 leads to loss of m6Am, but m6A level or distribution is not affected d m6Am decreases cap-dependent translation; no effect on transcription nor mRNA stability d m6Am-Exo-Seq is a robust methodology that enables global m6Am mapping
Multiplexed quantitative analyses of complex proteomes enable deep biological insight. While a multitude of workflows have been developed for multiplexed analyses, the most quantitatively accurate method (SPS-MS3) suffers from long acquisition duty cycles. We built a new, real-time database search (RTS) platform, Orbiter, to combat the SPS-MS3 method's longer duty cycles. RTS with Orbiter eliminates SPS-MS3 scans if no peptide matches to a given spectrum. With Orbiter's online proteomic analytical pipeline, which includes RTS and false discovery rate analysis, it was possible to process a single spectrum database search in less than 10 ms. The result is a fast, functional means to identify peptide spectral matches using Comet, filter these matches, and more efficiently quantify proteins of interest. Importantly, the use of Comet for peptide spectral matching allowed for a fully featured search, including analysis of post-translational modifications, with well-known and extensively validated scoring. These data could then be used to trigger subsequent scans in an adaptive and flexible manner. In this work we tested the utility of this adaptive data acquisition platform to improve the efficiency and accuracy of multiplexed quantitative experiments. We found that RTS enabled a 2-fold increase in mass spectrometric data acquisition efficiency. Orbiter's RTS quantified more than 8000 proteins across 10 proteomes in half the time of an SPS-MS3 analysis (18 h for RTS, 36 h for SPS-MS3).
SUMMARYThousands of interactions assemble proteins into modules that impart spatial and functional organization to the cellular proteome. Through affinity-purification mass spectrometry, we have created two proteome-scale, cell-line-specific interaction networks. The first, BioPlex 3.0, results from affinity purification of 10,128 human proteins – half the proteome – in 293T cells and includes 118,162 interactions among 14,586 proteins; the second results from 5,522 immunoprecipitations in HCT116 cells. These networks model the interactome at unprecedented scale, encoding protein function, localization, and complex membership. Their comparison validates thousands of interactions and reveals extensive customization of each network. While shared interactions reside in core complexes and involve essential proteins, cell-specific interactions bridge conserved complexes, likely ‘rewiring’ each cell’s interactome. Interactions are gained and lost in tandem among proteins of shared function as the proteome remodels to produce each cell’s phenotype. Viewable interactively online through BioPlexExplorer, these networks define principles of proteome organization and enable unknown protein characterization.
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