Dataset Information

Expanding the Characterization of Microbial Ecosystems using DIA-PASEF Metaproteomics

ABSTRACT: Metaproteomics is gaining momentum in microbiome research due to the multi-dimensional information it provides. However, current approaches have reached their detection limits. We present a highly-sensitive metaproteomic workflow using the extra information captured by Parallel Accumulation-Serial Fragmentation (PASEF) technology. The comparison of different acquisition modes and data analysis software packages showed that DIA-PASEF and DIA-NN doubled protein identifications in the mouse gut microbiota and, importantly, also in the host proteome compared to DDA-PASEF. DIA-PASEF significantly improved peptide detection reproducibility and quantification accuracy, which resulted in more than twofold identified taxa, reaching depths comparable to metagenomic studies. Consequently, DIA-PASEF exhibited improved coverage of functional networks revealing 131 additional pathways compared to DDA-PASEF. We applied our optimized workflow to a pre-clinical mouse model of chronic pain, in which we deciphered novel host-microbiome interactions. In summary, we present here a metaproteomic approach that paves the way for increasing the functional characterization of microbiome ecosystems and is applicable to diverse fields of biological research.

INSTRUMENT(S): timsTOF Pro

ORGANISM(S): Microbiota

TISSUE(S): Feces

SUBMITTER: Feng Xian

LAB HEAD: Manuela Schmidt

PROVIDER: PXD040947 | Pride | 2023-05-04

REPOSITORIES: Pride

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			Action	DRS
	Meta_DDA_10Pools_ExperimentalDesign.txt	Txt
	Meta_DDA_10Pools_Raw.rar	Other
	Meta_DDA_10Pools_proteome.txt	Txt
	Meta_DDA_10Pools_search.csv	Csv
	Meta_DDA_Different_Peptide_Quantities_ExperimentalDesign.txt	Txt

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Project description:A quadrupole time-of-flight mass spectrometry coupled with a trapped ion mobility mass spectrometer operated in parallel accumulation-serial fragmentation mode has recently emerged as proteome profiling platform capable of providing four dimensional features of elution time, collision cross section, precursor and fragment ion masses of peptides. The PASEF mode has demonstrated its superior performance by providing nearly 100% ion sampling efficiency both in data-dependent acquisition and data-independent acquisition modes without sacrificing sensitivity. In addition, the substantial gain in selectivity has been proven in targeted measurements using PASEF integrated parallel reaction monitoring mode. However, because these are emerging technologies in the field of proteomics, their applicability to clinical samples has been less investigated. Cerebrospinal fluid is in direct contact with brain and has been shown to contain biomarkers related to a variety of neurological diseases although the proteomics data have been mainly generated using orbitrap-based mass spectrometers. Thus, we acquired in-depth proteome profiles of human CSF in DDA mode to generate a spectral library of 3,478 proteins. The benefit of applying the spectral library to PRM experiments was demonstrated by using CSF samples from 15 Alzheimer’s disease patients and 19 controls and utilizing the spectral library to determine elution times and ion mobility values of targeting peptide. Further, we acquired DIA data from the same CSF samples, and analyzed using the spectral library without additional efforts to generate study-specific library, which also resulted in sensitive protein identification compared to a library-free approach. Overall, we established resource of CSF proteome profiles with 4D features and demonstrated the significant gain for designing and analyzing targeted and DIA studies, which is expected to facilitate 4D proteomics of CSF to study various neurological disorders.

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Expanding the Characterization of Microbial Ecosystems using DIA-PASEF Metaproteomics

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