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Ultrafast and Reproducible Proteomics from Small amounts of Heart Tissue Enabled by Azo and timsTOF Pro

ABSTRACT: Data for the manuscript "Ultrafast and Reproducible Proteomics from Small amounts of Heart Tissue Enabled by Azo and timsTOF Pro".

INSTRUMENT(S): timsTOF Pro

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Ying Ge

PROVIDER: MSV000087476 | MassIVE | Fri May 21 07:26:00 BST 2021

REPOSITORIES: MassIVE

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Publications

Ultrafast and Reproducible Proteomics from Small Amounts of Heart Tissue Enabled by Azo and timsTOF Pro.

Aballo Timothy J TJ Roberts David S DS Melby Jake A JA Buck Kevin M KM Brown Kyle A KA Ge Ying Y

Journal of proteome research 20210708 8

Global bottom-up mass spectrometry (MS)-based proteomics is widely used for protein identification and quantification to achieve a comprehensive understanding of the composition, structure, and function of the proteome. However, traditional sample preparation methods are time-consuming, typically including overnight tryptic digestion, extensive sample cleanup to remove MS-incompatible surfactants, and offline sample fractionation to reduce proteome complexity prior to online liquid chromatograph ...[more]

PMID: 34236868

Similar Datasets

Ultrafast and Reproducible Proteomics from Small Amounts of Heart Tissue Enabled by Azo and timsTOF Pro.

Project description:Global bottom-up mass spectrometry (MS)-based proteomics is widely used for protein identification and quantification to achieve a comprehensive understanding of the composition, structure, and function of the proteome. However, traditional sample preparation methods are time-consuming, typically including overnight tryptic digestion, extensive sample cleanup to remove MS-incompatible surfactants, and offline sample fractionation to reduce proteome complexity prior to online liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Thus, there is a need for a fast, robust, and reproducible method for protein identification and quantification from complex proteomes. Herein, we developed an ultrafast bottom-up proteomics method enabled by Azo, a photocleavable, MS-compatible surfactant that effectively solubilizes proteins and promotes rapid tryptic digestion, combined with the Bruker timsTOF Pro, which enables deeper proteome coverage through trapped ion mobility spectrometry (TIMS) and parallel accumulation-serial fragmentation (PASEF) of peptides. We applied this method to analyze the complex human cardiac proteome and identified nearly 4000 protein groups from as little as 1 mg of human heart tissue in a single one-dimensional LC-TIMS-MS/MS run with high reproducibility. Overall, we anticipate this ultrafast, robust, and reproducible bottom-up method empowered by both Azo and the timsTOF Pro will be generally applicable and greatly accelerate the throughput of large-scale quantitative proteomic studies. Raw data are available via the MassIVE repository with identifier MSV000087476.

| S-EPMC8349881 | biostudies-literature

Oxonium Ion-Guided Ion Mobility-Assisted Glycoproteomics on the timsTOF Pro

Project description:Spatial separation of ions in the gas-phase, providing information about their size as collisional cross-sections, can readily be achieved through ion mobility. The timsTOF Pro combines a trapped ion mobility device with a quadrupole, collision cell and a time-of-flight analyser to enable the analysis of ions at great speed. Here, we show that the timsTOF Pro is capable of physically separating N-glycopeptides from non-modified peptides and producing high-quality fragmentation spectra, both beneficial for glycoproteomics analyses of complex samples. The glycan moieties enlarge the size of glycopeptides compared to non-modified peptides, yielding a clear cluster in the mobilogram that, next to increased dynamic range from the physical separation of glycopeptides and non-modified peptides, can be used to make an effective selection filter for directing the mass spectrometer to analytes of interest. This new approach was applied to selected glycoproteins, human plasma- and neutrophil-derived glycopeptides. We show that the achieved physical separation, combined with the focussing of the mass spectrometer, allows for improved extraction of information from the samples, even at shorter LC gradients of 15 min. We validated our approach on human neutrophil and plasma samples of known make-up, in which we captured the anticipated glycan heterogeneity (paucimannose, phosphomannose, high mannose, hybrid and complex glycans) from diverse biological samples (plasma and neutrophils) at the expected abundances. As the method is compatible with off-the-shelve data acquisition routines and data analysis software, it can readily be applied by any laboratory with a timsTOF Pro and is reproducible as demonstrated by an inter-laboratory comparison between two laboratories.

2023-01-17 | PXD034845 | Pride

LC-MS/MS interactomics analysis of Praf2 with timsTOF Pro

Project description:LC-MS/MS interactomics analysis of Praf2 using TurboID with timsTOF Pro.

2023-12-20 | PXD029019 | Pride

PASEF technology on timsTOF Pro improves quality of FPOP analysis

Project description:Fast photochemical oxidation of proteins (FPOP) is a modern technique for studying protein folding, conformations, interactions, etc. In this work, timsTOF Pro mass spectrometer coupled with trapped ion mobility spectrometry was used for identification of oxidative modifications in a model protein. Multiple modifications on the same residues, including six modifications of histidine, were successfully resolved. Moreover, PASEF technology allows successful sequencing even minor populations of modified peptides.

2021-06-10 | PXD020509 | Pride

dia-PASEF HeLa dilution series 0.2ng - 200ng on Bruker timsTOF Pro 2

Project description:Different sample preparation methods were tested for HeLa proteome analysis. A sample obtained using sodium deoxycholate-based lysis allowed identification of the highest number of proteins. For this sample, a dilution series was acquired in triplicates ranging from 0.2ng to 200ng. All measurements were performed on Bruker timsTOF Pro 2 operated in dia-PASEF mode and analysed library-free using DIA-NN 1.8.

2022-06-20 | PXD029836 | Pride

timsTOF HT improves protein identification and quantitative reproducibility for deep unbiased plasma protein biomarker discovery (Loading curve dataset)

Project description:Mass spectrometry (MS) has emerged as a valuable tool for plasma proteome profiling and disease biomarker discovery. However, wide range of plasma protein concentrations along with technical and biological variabilities, continue to present significant challenges for deep and reproducible protein quantitation across large patient cohorts. Here we demonstrate the qualitative and quantitative performance gain of the timsTOF HT over the timsTOF Pro 2 mass spectrometer in the analysis of neat (unfractionated) and Proteograph™ (PG)-processed plasma across a wide range of peptide loading masses and liquid chromatography (LC) gradients. We observed up to a 76% increase in total plasma peptide precursors identified and a >2-fold boost in quantifiable plasma peptide precursors (CV<20%) with timsTOF HT compared to timsTOF Pro 2. In an exploratory study of 20 late-stage cancer and 20 control sampleswe observed a ~50% increase in total and statistically significant plasma peptide precursors (q<0.05) with timsTOF HT compared to Pro 2. Our data demonstrated the superior performance of timsTOF HT in identifying and quantifying differences between biologically diverse samples, which can improve disease biomarker discovery in large cohort studies. Moreover, researchers can leverage datasets from this study to optimize their LCMS workflows for plasma protein profiling and biomarker discovery. See the details in a paper, entitled "timsTOF HT improves protein identification and quantitative reproducibility for deep unbiased plasma protein biomarker discovery".

2024-01-16 | PXD047854 | Pride

timsTOF HT improves protein identification and quantitative reproducibility for deep unbiased plasma protein biomarker discovery (Cancer cohort dataset)

2024-01-16 | PXD047839 | Pride

GNPS - Feature-Based Molecular Networking with Ion Mobility Spectrometry (timsTOF Pro in PASEF mode) with MetaboScape

Project description:NIST1950 SRM samples analyzed on timsTOF Pro in Parallel-Accumulation Serial Fragmentation (PASEF) mode. Data provided by Bruker's team.

2019-10-01 | MSV000084402 | GNPS

Proteomic Analysis of Human Conjunctival Cells and Tears Collected with Schirmer Strips Using TimsTOF Pro

Project description:This study aimed to investigate the human tear proteins extracted from whole (W) Schirmer strips (ScS) and their two parts, the bulb (B) and the rest of the strip (R) with a comprehensive proteomic approach using a trapped ion mobility mass spectrometer, the timsTOF Pro. Eight ScS were collected from two healthy subjects at 4 different visits to be separated into three batches: 4W, 4B and 4R. In total, 1582 proteins were identified in the W, B and R batches. Among all iden-tified proteins, binding proteins (43.4%) and those with catalytic activity (42.2%) constituted more than 80% of the molecular functions. The most represented biological processes were cel-lular processes (31.2%), metabolic processes (20.8%) and biological regulation (13.1%). Enzymes were the most represented protein class (41 %), consisting mainly of hydrolases (47.5%), oxi-doreductases (22.1%) and transferases (16.7%). The bulb (B), which is in contact with the conjunc-tiva, might collect both tear and cell proteins and therefore promote identification of more pro-teins. Processing B and R separately before MS analysis, combined with the high data acquisition speed and the addition of ion-mobility-based separation in timsTOF Pro, can bring a new dimension to biomarker investigations of a limited sample such as tear fluid.

2022-01-27 | PXD030334 | Pride

Proteomics Tool Spike-in dataset analyzed on a timsTOF Pro

Project description:Label-free proteomics enables the unbiased quantification of thousands of proteins across large sample cohorts. Commonly used mass spectrometry-based proteomic workflows rely on data dependent acquisition (DDA). However, its stochastic selection of peptide features for fragmentation-based identification inevitably results in high rates of missing values, which prohibits the integration of larger cohorts as the number of recurrently detected peptides is a limiting factor. Peptide identity propagation (PIP) can mitigate this challenge, allowing to transfer sequencing information between samples. However, despite the promise of these approaches, current methods remain limited either in sensitivity or reliability and there is a lack of robust and widely applicable software. Here we prepared a tool spike-in data set which can be used to evaluate PIP on timsTOF Pro data.

2021-07-10 | PXD021425 | Pride

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