Deep proteomics of HEK293 cells by DIA-MS with FAIMS
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens (human)
SUBMITTER: Yusuke Kawashima
PROVIDER: PXD026271 | JPOST Repository | Thu May 26 00:00:00 BST 2022
REPOSITORIES: jPOST
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| 210402_HEK_1000ng_F45_IT100_OT90_02.mzML | Mzml | |||
| 210402_HEK_1000ng_F45_IT100_OT90_02.raw | Raw | |||
| HEK_1000ng_F45_IT100OT90_F5.sdia | Other | |||
| oDIA_HEK_1ug.blib | Other | |||
| oDIA_HEK_1ug.tsv | Tabular |
Items per page: 5 1 - 5 of 5 |
Similar Datasets
Project description:We aimed to expand the proteome coverage by single-shot measurements using optimizing high-field asymmetric waveform ion mobility spectrometry (FAIMS) parameters in DIA-MS. In addition, we analyzed host proteins in the feces of control and repeated social defeat stress (R-SDS) model mice with optimal FAIMS parameters in DIA-MS.
2022-04-28 | PXD029853 | JPOST Repository
Project description:Here, we present a standardized, “off-the-shelf” proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high throughput and scalability. This integrated pipeline streamlining a fully automated sample preparation platform, data independent acquisition (DIA) coupled with high field asymmetric waveform ion mobility spectrometer (FAIMS) interface, and an optimized library-free DIA database search strategy. Our systematic evaluation of FAIMS-DIA showed single compensation voltage (CV) at -35V not only yields deepest proteome coverage but also best correlates with DIA without FAIMS. Our in-depth comparison of direct-DIA database search engines showed Spectronaut outperforms others, providing highest quantifiable proteins. Next, we apply three common DIA strategies in characterizing human induced pluripotent stem cell (iPSC)-derived neurons and show single-shot MS using single CV(-35V)-FAIMS-DIA results in >9,000 quantifiable proteins with < 10% missing values, as well as superior reproducibility and accuracy compared to other existing DIA methods.
2023-08-22 | PXD029902 | Pride
Project description:State-of-the-art proteomics-grade mass spectrometers can measure peptide precursors and their fragments with ppm mass accuracy at sequencing speeds of tens of peptides per second with attomolar sensitivity. Here we describe a compact and robust quadrupole-orbitrap mass spectrometer equipped with a front-end High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Interface. The performance of the Orbitrap Exploris 480 mass spectrometer is evaluated in data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes in combination with FAIMS. We demonstrate that different compensation voltages (CVs) for FAIMS are optimal for DDA and DIA, respectively. Combining DIA with FAIMS using single CVs, the instrument surpasses 2500 peptides identified per minute. This enables quantification of >5000 proteins with short online LC gradients delivered by the Evosep One LC system allowing acquisition of 60 samples per day. The raw sensitivity of the instrument is evaluated by analyzing 5 ng of a HeLa digest from which >1000 proteins were reproducibly identified with 5 minute LC gradients using DIA-FAIMS. To demonstrate the versatility of the instrument we recorded an organ-wide map of proteome expression across 12 rat tissues quantified by tandem mass tags and label-free quantification using DIA with FAIMS to a depth of >10,000 proteins.
2020-02-17 | PXD016662 | Pride
Project description:Real patient variability Benchmark Dataset for Optimization of DIA data analysis workflows
| EGAD00010002223 | EGA
Project description:The dia-PASEF technology uses ion mobility separation to reduce signal interferences and increase sensitivity in proteomic experiments. Here we present a two-dimensional peak-picking algorithm and generation of optimized spectral libraries, as well as take advantage of neural network-based processing of dia-PASEF data. Our computational platform boosts proteomic depth by up to 83% compared to previous work, and is specifically beneficial for fast proteomic experiments and those with low sample amounts. It quantifies over 5300 proteins in single injections recorded at 200 samples per day throughput using Evosep One chromatography system on a timsTOF Pro mass spectrometer and almost 9000 proteins in single injections recorded with a 93-min nanoflow gradient on timsTOF Pro 2, from 200 ng of HeLa peptides. A user-friendly implementation is provided through the incorporation of the algorithms in the DIA-NN software and by the FragPipe workflow for spectral library generation.
| S-EPMC9270362 | biostudies-literature
Project description:Protein glycosylation is increasingly recognized as a common protein modification across bacterial species. Within members of the Neisseria genus O-linked protein glycosylation plays important roles in virulence and antigenic variation yet our understanding of the substrates of glycosylation are limited. Recently it was identified that even closely related Neisserial species can possess O-oligosaccharyltransferases, pglOs, that possess varying glycosylation specificities suggesting that distinct targeting activities may impact both the glycoprotome as well as the proteome of Neisserial species. Within this work we explore this concept using of Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) fractionation and Data-Independent Acquisition (DIA) to allow the characterization of differences in the glycoproteomes and proteomes within N. gonorrhoeae strains expressing differing pglO alleles. We demonstrate the utility of FAIMS to expand the known glycoproteome of N. gonorrhoeae and enable comparative glycoproteomics of a recently reported panel of N. gonorrhoeae strains expressing different pglO allelic chimeras (15 pglO enzymes) with unique substrate targeting activities. Combining glycoproteomic insights with DIA proteomics we demonstrate that alterations within pglO alleles have widespread impacts on the proteome of N. gonorrhoeae yet lead to minimal effects on the abundance of glycoproteins. Additionally, while DIA analysis can allow occupancy to be inferred by the absence or presence of peptides known to be modified, we observe a poor correlation between DIA measurements of non-modified versions of glycopeptides and glycoproteomic analysis. Combined this work expands our understanding of the N. gonorrhoeae glycoproteome and supports that the expression of different pglO alleles appears to drive proteomic changes independent of the glycoproteins targeted for glycosylation.
2024-02-01 | PXD044666 | Pride
Project description:Proteomic biomarker discovery using formalin-fixed paraffin-embedded (FFPE) tissue requires robust workflows to support the analysis of large cohorts of patient samples. It also requires finding a reasonable balance between achieving high proteomic depth and limiting overall analysis time. To this end, we evaluated the merits of online coupling of disposable trap column nano-flow liquid chromatography, high-field asymmetric-waveform ion-mobility spectrometry (FAIMS) and tandem mass spectrometry (nLC-FAIMS-MS/MS). The data shows that ≤ 600 ng of peptide digest should be loaded onto the chromatographic part of the system. Careful characterization of the FAIMS settings enabled the choice of optimal combinations of compensation voltages (CV) as a function of the employed LC gradient time. We found nLC-FAIMS-MS/MS to be on par with stage tip-based off-line high pH reversed phase fractionation in terms of proteomic depth and reproducibility of protein quantification (coefficient of variation ≤ 15% for 90 % of all proteins) but requiring 50% less sample and substantially reducing sample handling. Using FFPE material from lymph node, lung and prostate tissue as examples, we show that nLC-FAIMS-MS/MS can identify 5-6,000 proteins from the respective tissue within a total of 3 hours of analysis time.
2021-11-02 | PXD028136 | Pride
Project description:Elstera litoralis strain:Dia-1 Genome sequencing and assembly
| PRJNA278930 | ENA
Project description:Stutzerimonas stutzeri strain:DIA-8 Genome sequencing and assembly
| PRJNA1072647 | ENA