PXD051104

PXD051104 is an original dataset announced via ProteomeXchange.

Title	metaExpertPro: a computational workflow for metaproteomics spectral library construction and data-independent acquisition mass spectrometry data analysis
Description	Analysis of large-scale data-independent acquisition mass spectrometry (DIA-MS) metaproteomics data remains a computational challenge. Here, we present a computational pipeline called metaExpertPro for metaproteomics data analysis. This pipeline encompasses spectral library generation using data-dependent acquisition MS (DDA-MS), protein identification and quantification using DIA-MS, functional and taxonomic annotation, as well as quantitative matrix generation for both microbiota and hosts. By integrating FragPipe and DIA-NN, metaExpertPro offers compatibility with both Orbitrap and timsTOF MS instruments. To evaluate the depth and accuracy of identification and quantification, we conducted extensive assessments using human fecal samples and benchmark tests. Performance tests conducted on human fecal samples indicated that metaExpertPro quantified an average of 45,000 peptides in a 60-minute diaPASEF injection. Notably, metaExpertPro outperformed three existing software tools by characterizing a higher number of peptides and proteins. Importantly, metaExpertPro maintained a low factual false discovery rate (FDR) of approximately 5% for protein groups across four benchmark tests. Applying a filter of five peptides per genus, metaExpertPro achieved relatively high accuracy (F-score = 0.67–0.90) in genus diversity and showed a high correlation (rSpearman = 0.73–0.82) between the measured and true genus relative abundance in benchmark tests. Additionally, the quantitative results at the protein, taxonomy, and function levels exhibited high reproducibility and consistency across the commonly adopted public human gut microbial protein databases IGC and UHGP. In a metaproteomic analysis of dyslipidemia (DLP) patients, metaExpertPro revealed characteristic alterations in microbial functions and potential interactions between the microbiota and the host.
HostingRepository	PRIDE
AnnounceDate	2024-09-28
AnnouncementXML	Submission_2024-09-28_08:28:49.136.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Tiannan Guo
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	methylthiolated residue; monohydroxylated residue; iodoacetamide derivatized residue
Instrument	timsTOF Pro; Orbitrap Exploris 480

Revision	Datetime	Status	ChangeLog Entry
0	2024-03-31 11:06:41	ID requested
⏵ 1	2024-09-28 08:28:49	announced

10.1016/J.MCPRO.2024.100840;

submitter keyword: computational workflow, data-independent acquisition mass spectrometry, metaproteomics

Tiannan Guo
contact affiliation	1, Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, 310030, China 2, School of Medicine, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, 310030, China 3, Research Center for Industries of the Future, Westlake University, 600 Dunyu Road, Hangzhou, Zhejiang, 310030, China
contact email	guotiannan@westlake.edu.cn
lab head
Tiannan Guo
contact affiliation	Westlake University
contact email	guotiannan@westlake.edu.cn
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2024/09/PXD051104

PRIDE project URI

• PRIDE
  1. PXD051104
     1. Label: PRIDE project
     2. Name: metaExpertPro: a computational workflow for metaproteomics spectral library construction and data-independent acquisition mass spectrometry data analysis