PXD072536

PXD072536 is an original dataset announced via ProteomeXchange.

Title	MetaSpaR-DIA: Enabling Accurate Metaproteomic DIA Analysis Independent of Spectral Libraries and Metagenomic Sequencing
Description	Background Metaproteomics provides comprehensive insights into the taxonomic composition and functional dynamics of microbiome communities across ecologically diverse niches. However, the inherent complexity and highly dynamic nature of microbial communities pose significant obstacles to achieving accurate and comprehensive metaproteomic profiling. Data-independent acquisition (DIA) mass spectrometry has emerged as a powerful quantitative approach, offering high proteome coverage, excellent reproducibility and robust quantitative accuracy. However, the immense scale of candidate sequences in metaproteomics currently precludes the direct application of DIA strategy, unless supplemented by metagenomic sequencing or data-dependent acquisition (DDA)‐based spectral library construction, thereby limiting the widespread applicability of DIA in metaproteomic research. Results Herein, we introduce MetaSpaR-DIA, a search space reduction strategy for DIA-based metaproteomic quantification, which obviates the need for sample-specific metagenomic sequencing and DDA-based spectral libraries. By randomly partitioning publicly available reference catalogs into appropriately equal-sized subsets and implementing an iterative false discovery rate (FDR) control strategy, MetaSpaR-DIA enables the construction of a reduced, sample-specific database with markedly decreased search space, thereby facilitating accurate and high-coverage metaproteomic quantification. MetaSpaR-DIA enables peptide identification with < 2% actual FDR in simulated microbial communities and demonstrates high peptide coverage and quantitative accuracy comparable to metagenomic-based DIA method, and provides more comprehensive functional and taxonomic annotation in spike-in fecal samples. The MetaSpaR-DIA pipeline was further applied to investigate gut microbiota functional dynamics during Alzheimer's disease (AD) progression. Energy metabolism dysregulation along with the subsequent oxidative stress, may accelerate disease progression. Observed alterations in short-chain fatty acid synthesis further indicate potential avenues for disease modulation and therapeutic intervention. Conclusion Overall1, we developed an efficient workflow for large-scale DIA-based metaproteomic analysis without the need for additional experimental procedures and has strong potential for widespread applicability, particularly for studies involving rare or limited microbiome samples. This method demonstrated excellent quantitative performance in profiling microbial communities and was further applied to explore functional dynamics in the mice gut microbiome during the progression of AD. MetaSpaR-DIA is expected to provide novel insights into gut microbiota-mediated pathogenesis and advance the application of DIA-based metaproteomics to a wide range of research fields.
HostingRepository	iProX
AnnounceDate	2025-12-30
AnnouncementXML	Submission_2025-12-30_18:59:28.509.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Songduo Wang
SpeciesList	scientific name: Clostridium butyricum; NCBI TaxID: 1492; scientific name: Escherichia coli 90.0091; NCBI TaxID: 1005400; scientific name: Enterococcus casseliflavus ATCC 49996; NCBI TaxID: 1158603; scientific name: Klebsiella aerogenes KCTC 2190; NCBI TaxID: 1028307;
ModificationList	No PTMs are included in the dataset
Instrument	Orbitrap Exploris 480

Revision	Datetime	Status	ChangeLog Entry
0	2025-12-30 18:58:39	ID requested
⏵ 1	2025-12-30 18:59:29	announced

Dataset with its publication pending

submitter keyword: Metaproteomics, Data-independent acquisition, Reference catalogs, search space reduction, Alzheimer’s disease

Lihua Zhang
contact affiliation	Dalian Institute of chemical physics
contact email	lihuazhang@dicp.ac.cn
lab head
Songduo Wang
contact affiliation	Dalian Institute of chemical physics
contact email	songduowang@dicp.ac.cn
dataset submitter

iProX dataset URI