Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Deep proteome analysis by DIA-MS

ABSTRACT: To expand proteome coverage, the MS range in DIA-MS was examined. In addition, we analyzed host proteins in the feces of control and repeated social defeat stress (R-SDS) model mice by DIA-MS with an optimal MS range.

ORGANISM(S): Homo Sapiens (human) Mus Musculus (mouse)

SUBMITTER: Yusuke Kawashima

PROVIDER: PXD032698 | JPOST Repository | Thu Apr 28 00:00:00 BST 2022

REPOSITORIES: jPOST

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	feces_Control_No-FAIMS-1.raw	Raw
	feces_Control_No-FAIMS-2.raw	Raw
	feces_Control_No-FAIMS-3.raw	Raw
	feces_Control_No-FAIMS-4.raw	Raw
	feces_Control_No-FAIMS-5.raw	Raw

Items per page:

1 - 5 of 20

Publications

Single-Shot 10K Proteome Approach: Over 10,000 Protein Identifications by Data-Independent Acquisition-Based Single-Shot Proteomics with Ion Mobility Spectrometry.

Kawashima Yusuke Y Nagai Hirotaka H Konno Ryo R Ishikawa Masaki M Nakajima Daisuke D Sato Hironori H Nakamura Ren R Furuyashiki Tomoyuki T Ohara Osamu O

Journal of proteome research 20220506 6

The evolution of mass spectrometry (MS) and analytical techniques has led to the demand for proteome analysis with high proteome coverage in single-shot measurements. Focus has been placed on data-independent acquisition (DIA)-MS and ion mobility spectrometry as techniques for deep proteome analysis. We aimed to expand the proteome coverage by single-shot measurements using optimizing high-field asymmetric waveform ion mobility spectrometry parameters in DIA-MS. With our established proteome ana ...[more]

PMID: 35522919

Similar Datasets

Deep proteome analysis by DIA-MS with FAIMS

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

Boloria dia

Project description:Boloria dia overview

| PRJNA1163491 | ENA

Rapid and in-depth coverage of the (phospho-)proteome with deep libraries and optimal window design for dia-PASEF

Project description:Data-independent acquisition (DIA) methods have become increasingly attractive in mass spectrometry (MS)-based proteomics, because they enable high data completeness and a wide dynamic range. Recently, we combined DIA with parallel accumulation – serial fragmentation (dia-PASEF) on a Bruker trapped ion mobility separated (TIMS) quadrupole time-of-flight (TOF) mass spectrometer. This requires alignment of the ion mobility separation with the downstream mass selective quadrupole, leading to a more complex scheme for dia-PASEF window placement compared to DIA. To achieve high data completeness and deep proteome coverage, here we employ variable isolation windows that are placed optimally depending on precursor density in the m/z and ion mobility plane. This Automatic Isolation Design procedure is implemented in the freely available py_diAID package. In combination with in-depth project-specific proteomics libraries and the Evosep LC system, we reproducibly identified over 7,700 proteins in a human cancer cell line in 44 minutes with quadruplicate single-shot injections at high sensitivity. Even at a throughput of 100 samples per day (11 minutes LC gradients), we consistently quantified more than 6,000 proteins in mammalian cell lysates by injecting four replicates. We found that optimal dia-PASEF window placement facilitates in-depth phosphoproteomics with very high sensitivity, quantifying more than 35,000 phosphosites in a human cancer cell line stimulated with an epidermal growth factor (EGF) in triplicate 21 minutes runs. This covers a substantial part of the regulated phosphoproteome with high sensitivity, opening up for extensive systems-biological studies.

2022-08-11 | PXD034128 | Pride

Elstera litoralis strain:Dia-1

Project description:Elstera litoralis strain:Dia-1 Genome sequencing and assembly

| PRJNA278930 | ENA

Stutzerimonas stutzeri strain:DIA-8

Project description:Stutzerimonas stutzeri strain:DIA-8 Genome sequencing and assembly

| PRJNA1072647 | ENA

scRNAseq RAT DIA WT and DMD 12months

Project description:scRNAseq RAT DIA WT and DMD 12months

| PRJNA814255 | ENA

Optimization of the workflow for deep CSF proteome analysis by enrichment of extracellular vesicles

Project description:Proteome analysis of cerebrospinal fluid is associated with many of the same challenges that has to be faced when analyzing other biofluids like plasma or urine. Most importantly is the high dynamic range of protein concentrations, which makes it difficult to quantify more than a thousand proteins in a singleshot analysis of a tryptic digest of a raw sample. In addition, cerebrospinal fluid—especially when collected from children—is a much more scarce and precious sample as compare to urine and plasma. The aim of this work therefore was to find the optimal way to process and analyze cerebrospinal fluid from a minimal amount of sample and still obtain the deepest possible cerebrospinal fluid proteome. The work shows that enrichment of extracellular vesicles by ultracentrifugation increases the complexity of the cerebrospinal fluid proteome by two-fold or more. Thus, by following the enrichment protocol, more than two thousand proteins can routinely be quantified reproducibly by label-free quantification and data independent acquisition (DIA) in single-shot LC-MSMS runs of less than one hour. The project also present an optimized workflow for cerebrospinal fluid proteomics that enables a high-throughput method with a short chromatographic gradient (12 min) allowing analysis of hundred samples per day and still obtaining deep proteome coverage, especially when including a study-specific spectral library generated by repeated injection and gas-phase fractionation of pooled samples.

2024-10-16 | PXD052666 | Pride

Evaluation of data-independent acquisition workflows for deep proteome coverage of EPS-urine

Project description:Here, we investigated the performance of DIA-MS on a cohort of urines collected from prostate cancer patients against DDA-MS. The performance of several commonly used DIA-MS analysis approaches were examined with our cohort-specific spectral libraries, library-free and a pan-human library. An enhanced prostate cancer urine spectral library was generated for improved proteomic coverage.

2024-01-03 | MSV000093759 | MassIVE

ProteomicAnalysis(DIA)ofmuscleinvasivebladdercancerpatient-derivedxenografts

Project description:Accesstoproteomicfiles(DIA)ofMIBCpatient-derivedxenografts(N=8)

| EGAD00010002512 | EGA

Deep plasma proteome profiling by enrichment of extracellular vesicles

Project description:This work show that enrichment of extracellular vesicles by ultracentrifugation increases the plasma proteome depth by an order of magnitude. Following the enrichment protocol, more than two thousand proteins can routinely be quantified reproducibly by label-free quantification and data independent acquisition (DIA) in single-shot LC-MSMS runs of less than one hour. The project also present an optimized workflow for plasma proteomics that enables high-throughput with very short chromatographic gradients analyzing hundred samples per day with deep proteome coverage, especially when including study-specific spectral libraries generated by repeated injection and gas-phase fractionation of pooled samples

2022-12-04 | PXD037340 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data