Sherwood Cantu (steambridge4)

The proteome quantification capability of this method was demonstrated by triplex labeling of a yeast proteome spiked with bovine serum albumin (BSA) over a 10-fold dynamic range. With the yeast proteins as the background, BSA was detected at ratios of 1.145.069.78 when spiked at 1510 ratios. The raw mass data is available on the ProteomeXchange with the identifier PXD 018790.Top-down mass spectrometry (MS)-based proteomics enable a comprehensive analysis of proteoforms with molecular specificity to achieve a proteome-wide understanding of protein functions. However, the lack of a universal software for top-down proteomics is becoming increasingly recognized as a major barrier, especially for newcomers. Here, we have developed MASH Explorer, a universal, comprehensive, and user-friendly software environment for top-down proteomics. MASH Explorer integrates multiple spectral deconvolution and database search algorithms into a single, universal platform which can process top-down proteomics data from various vendor formats, for the first time. It addresses the urgent need in the rapidly growing top-down proteomics community and is freely available to all users worldwide. With the critical need and tremendous support from the community, we envision that this MASH Explorer software package will play an integral role in advancing top-down proteomics to realize its full potential for biomedical research.Metadata is essential in proteomics data repositories and is crucial to interpret and reanalyze the deposited data sets. For every proteomics data set, we should capture at least three levels of metadata (i) data set description, (ii) the sample to data files related information, and (iii) standard data file formats (e.g., mzIdentML, mzML, or mzTab). While the data set description and standard data file formats are supported by all ProteomeXchange partners, the information regarding the sample to data files is mostly missing. Recently, members of the European Bioinformatics Community for Mass Spectrometry (EuBIC) have created an open-source project called Sample to Data file format for Proteomics (https//github.com/bigbio/proteomics-metadata-standard/) to enable the standardization of sample metadata of public proteomics data sets. Here, the project is presented to the proteomics community, and we call for contributors, including researchers, journals, and consortiums to provide feedback about the format. We believe this work will improve reproducibility and facilitate the development of new tools dedicated to proteomics data analysis.Aberrant protein synthesis and protein expression are a hallmark of many conditions ranging from cancer to Alzheimer's. Blood-based biomarkers indicative of changes in proteomes have long been held to be potentially useful with respect to disease prognosis and treatment. However, most biomarker efforts have focused on unlabeled plasma proteomics that include nonmyeloid origin proteins with no attempt to dynamically tag acute changes in proteomes. Herein we report a method for evaluating de novo protein synthesis in whole blood liquid biopsies. Using a modification of the "bioorthogonal noncanonical amino acid tagging" (BONCAT) protocol, rodent whole blood samples were incubated with l-azidohomoalanine (AHA) to allow incorporation of this selectively reactive non-natural amino acid within nascent polypeptides. Notably, failure to incubate the blood samples with EDTA prior to implementation of azide-alkyne "click" reactions resulted in the inability to detect probe incorporation. This live-labeling assay was sensitive to inhibition with anisomycin and nascent, tagged polypeptides were localized to a variety of blood cells using FUNCAT. Using labeled rodent blood, these tagged peptides could be consistently identified through standard LC/MS-MS detection of known blood proteins across a variety of experimental conditions. Furthermore, this assay could be expanded to measure de novo protein synthesis in hu