scholarly journals Arabidopsis Proteome and the Mass Spectral Assay Library

2019 ◽  
Author(s):  
Huoming Zhang ◽  
Pei Liu ◽  
Tiannan Guo ◽  
Huayan Zhao ◽  
Dalila Bensaddek ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Abscisic Acid ◽  
Acid Stress ◽  
Model Organism ◽  
Mass Spectrometry Data ◽  
Mass Spectral ◽  
Novel Proteins ◽  
Data Independent Acquisition ◽  
Arabidopsis Proteome ◽  
Expression Atlas

AbstractArabidopsis is an important model organism and the first plant with its genome sequenced. Knowledge from studying this species has either direct or indirect applications to agriculture and human health. Quantitative proteomics by data-independent acquisition (SWATH/DIA-MS) was recently developed and considered as a high-throughput targetedlike approach for accurate proteome quantitation. In this approach, a high-quality and comprehensive library is a prerequisite. Here, we generated a protein expression atlas of 10 organs of Arabidopsis and created a library consisting of 15,514 protein groups, 187,265 unique peptide sequences, and 278,278 precursors. The identified protein groups correspond to ~56.5% of the predicted proteome. Further proteogenomics analysis identified 28 novel proteins. We subsequently applied DIA-mass spectrometry using this library to quantify the effect of abscisic acid on Arabidopsis. We were able to recover 8,793 protein groups with 1,787 of them being differentially expressed which includes 65 proteins known to respond to abscisic acid stress. Mass spectrometry data are available via ProteomeXchange with identifier PXD012710 for data-dependent acquisition and PXD014032 for DIA analyses.

scholarly journals Arabidopsis proteome and the mass spectral assay library

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Huoming Zhang ◽  
Pei Liu ◽  
Tiannan Guo ◽  
Huayan Zhao ◽  
Dalila Bensaddek ◽  
...  
Keyword(s):  
Quantitative Proteomics ◽  
Model Organism ◽  
Massively Parallel ◽  
Spectral Library ◽  
Mass Spectral ◽  
Novel Proteins ◽  
Data Independent Acquisition ◽  
Arabidopsis Proteome ◽  
Expression Atlas ◽  
Targeted Approach

AbstractArabidopsis is an important model organism and the first plant with its genome completely sequenced. Knowledge from studying this species has either direct or indirect applications for agriculture and human health. Quantitative proteomics by data-independent acquisition mass spectrometry (SWATH/DIA-MS) was recently developed and is considered as a high-throughput, massively parallel targeted approach for accurate proteome quantification. In this approach, a high-quality and comprehensive spectral library is a prerequisite. Here, we generated an expression atlas of 10 organs of Arabidopsis and created a library consisting of 15,514 protein groups, 187,265 unique peptide sequences, and 278,278 precursors. The identified protein groups correspond to ~56.5% of the predicted proteome. Further proteogenomics analysis identified 28 novel proteins. We applied DIA-MS using this library to quantify the effect of abscisic acid on Arabidopsis. We were able to recover 8,793 protein groups of which 1,787 were differentially expressed. MS data are available via ProteomeXchange with identifier PXD012708 and PXD012710 for data-dependent acquisition and PXD014032 for DIA analyses.

Group-DIA: analyzing multiple data-independent acquisition mass spectrometry data files

2015 ◽  
Vol 12 (12) ◽  
pp. 1105-1106 ◽  
Author(s):  
Yuanyue Li ◽  
Chuan-Qi Zhong ◽  
Xiaozheng Xu ◽  
Shaowei Cai ◽  
Xiurong Wu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Mass Spectrometry Data ◽  
Data Independent Acquisition ◽  
Multiple Data ◽  
Data Files

scholarly journals Implementing the re-use of public DIA proteomics datasets: from the PRIDE database to Expression Atlas

2021 ◽  
Author(s):  
Mathias Walzer ◽  
David Garcia-Seisdedos ◽  
Ananth Prakash ◽  
Paul Brack ◽  
Peter Crowther ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Statistical Analysis ◽  
Free Software ◽  
Analysis Software ◽  
Analysis Pipeline ◽  
The Public ◽  
Data Independent Acquisition ◽  
Metadata Annotation ◽  
Expression Atlas ◽  
Quantitative Results

Rising numbers of mass spectrometry proteomics datasets available in the public domain, increasingly include volumes generated from Data Independent Acquisition approaches, SWATH-MS in particular. Unlike Data Dependent Acquisition datasets, their re-use is limited, partially due to challenges in combination and use of free software for analysis in the non-specialist laboratory. We introduce a (re-)analysis pipeline for SWATH-MS data available in the PRIDE database, which includes a harmonised combination of metadata annotation protocols, automated workflows for MS data, statistical analysis and results integration into the resource Expression Atlas. Automation is orchestrated with Nextflow, using containerised open analysis software tools, rendering the pipeline readily available, reproducible and easy to update. To demonstrate its utility, we reanalysed 10 public DIA datasets, 1,278 individual SWATH-MS runs, stored in PRIDE. The robustness of the analysis was evaluated and compared to the results obtained in the original publications. The final results were exported into Expression Atlas, making quantitative results from SWATH-MS experiments more widely available and integrated with results from other reanalysed proteomics and transcriptomics datasets.

scholarly journals PECAN: library-free peptide detection for data-independent acquisition tandem mass spectrometry data

2017 ◽  
Vol 14 (9) ◽  
pp. 903-908 ◽  
Author(s):  
Ying S Ting ◽  
Jarrett D Egertson ◽  
James G Bollinger ◽  
Brian C Searle ◽  
Samuel H Payne ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Tandem Mass Spectrometry ◽  
Mass Spectrometry Data ◽  
Tandem Mass ◽  
Free Peptide ◽  
Data Independent Acquisition ◽  
Peptide Detection ◽  
Tandem Mass Spectrometry Data

scholarly journals Metaproteomics boosted up by untargeted data-independent acquisition data analysis framework

2020 ◽  
Author(s):  
Sami Pietilä ◽  
Tomi Suomi ◽  
Laura L. Elo
Keyword(s):  
Mass Spectrometry ◽  
Open Source Software ◽  
Previous Method ◽  
Mass Spectrometry Data ◽  
Analysis Framework ◽  
Spectral Library ◽  
Microbial Composition ◽  
Data Independent Acquisition ◽  
Open Source Software Package ◽  
First Time

AbstractMass spectrometry based metaproteomics is a relatively new field of research that provides the ability to characterize the functionality of microbiota. Recently, we were the first to demonstrate the applicability of data-independent acquisition (DIA) mass spectrometry to the analysis of complex metaproteomic samples. This allowed us to circumvent many of the drawbacks of the conventionally used data-dependent acquisition (DDA) mass spectrometry, mainly the limited reproducibility when analyzing samples with complex microbial composition. However, the previous method still required additional DDA data on the samples to assist the DIA analysis. Here, we introduce, for the first time, a DIA metaproteomics approach that does not require any DDA data, but instead replaces a spectral library generated from DDA data with a pseudospectral library generated directly from the metaproteomics DIA samples. We demonstrate that using the new DIA-only approach, we can achieve higher peptide yields than with the DDA-assisted approach, while the amount of required mass spectrometry data is reduced to a single DIA run per sample. The new DIA-only metaproteomics approach is implemented as open-source software package DIAtools 2.0, which is freely available from DockerHub.

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