Dataset Information

QCeltis Case Study 1: Depleted Plasma QC Dataset

ABSTRACT: A dataset containing depleted plasma samples used as quality control technical replicates (TR) and digestion replicates (DR). Plasma aliquot was shunted to Top14 Abundant Protein Depletion Resin (A36372) based depletion. Depleted plasma samples were processed on a i7 automated liquid handling system (Beckman Coulter) in a 96-well plate for protein denaturation, cysteine reduction and alkylation, and trypsin digestion. Healthy control pooled samples were used as DRs and embedded between samples during digestion. Depleted plasma tryptic peptides were separated by EVOSEP One LC System (Evosep) over a 45-minute gradient injected into an Orbitrap Exploris 480 MS (Thermo Fisher) using DIA-MS settings as described by McArdle and Binek et. al. During MS acquisition, the 4 DRs are run at the beginning of each batch. In addition, pooled, bulk digested plasma samples from Parkinsons Disease patients are included as technical replicates (TRs) at the beginning and middle of every MS batch, with the goal of assessing LC-MS performance.

INSTRUMENT(S): Orbitrap Exploris 480

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

SUBMITTER: Jennifer Van Eyk

PROVIDER: MSV000095742 | MassIVE |

SECONDARY ACCESSION(S): PXD055481

REPOSITORIES: MassIVE

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Publications

<u>Enhancing Proteomics Quality Control: Insights from the Visualization Tool QCeltis</u>.

Vegesna Manasa M Sundararaman Niveda N Bharadwaj Ajay A Washington Kirstin K Pandey Rakhi R Haghani Ali A Chazarin Blandine B Binek Aleksandra A Fu Qin Q Cheng Susan S Herrington David D Van Eyk Jennifer E JE

Journal of proteome research 20250224 3

Large-scale mass-spectrometry-based proteomics experiments are complex and prone to analytical variability, requiring rigorous quality checks across each step in the workflow: sample preparation, chromatography, mass spectrometry, and the bioinformatics stages. This includes quality control (QC) measures that address biological and technical variation. Most QC approaches involve detecting sample outliers and monitoring parameters related to sample preparation and mass spectrometer performance. E ...[more]

PMID: 39992359

Similar Datasets

Project description:Plasma proteomics holds immense potential for clinical research and biomarker discovery, serving as a non-invasive "liquid biopsy" for tissue sampling. Mass spectrometry (MS)-based proteomics, thanks to improvement in speed and robustness, emerges as an ideal technology for exploring the plasma proteome for its unbiased and highly specific protein identification and quantification. Despite its potential, plasma proteomics is still a challenge due to the vast dynamic range of protein abundance, hindering the detection of less abundant proteins. Different approaches can help overcome this challenge. Conventional depletion methods face limitations in cost, throughput, accuracy, and off-target depletion. Nanoparticle-based enrichment shows promise in compressing dynamic range, but cost remains a constraint. Enrichment strategies for extracellular vesicles (EVs) can enhance plasma proteome coverage dramatically, but current methods are still too laborious for large series. Neat plasma remains popular for its cost-effectiveness, time efficiency, and low volume requirement. We used a test set of 33 plasma samples for all evaluations. Samples were digested using Strap and analysed on Evosep and nanoElute coupled to a timsTOF Pro using different elution gradients and ion mobility ranges. Data were mainly analyzed using library-free searched using DIANN. This study explores ways to improve proteome coverage in neat plasma both in MS data acquisition and MS data analysis. We demonstrate the value of sampling smaller hydrophilic peptides, increasing chromatographic separation, and using library-free searches. Additionally, we introduce the EV boost approach, that leverages on the extracellular vesicle fraction to enhances protein identification in neat plasma samples. Globally, out optimized analysis workflow allows the quantification of over 1000 proteins in neat plasma with a 24SPD throughput. We believe that these considerations can be of help independently of the LC-MS platform used.

Dataset Information

QCeltis Case Study 1: Depleted Plasma QC Dataset

Dataset's files

Publications

<u>Enhancing Proteomics Quality Control: Insights from the Visualization Tool QCeltis</u>.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

QCeltis Case Study 1: Depleted Plasma QC Dataset

Dataset's files

Publications

&lt;u&gt;Enhancing Proteomics Quality Control: Insights from the Visualization Tool QCeltis&lt;/u&gt;.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

<u>Enhancing Proteomics Quality Control: Insights from the Visualization Tool QCeltis</u>.