Proteomics

Dataset Information

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Spectral entropy as a measure of the metaproteome complexity


ABSTRACT: The diversity and complexity of the microbiome's genomic landscape are not always mirrored in its proteomic profile. Despite the anticipated proteomic diversity, observed complexities of microbiome sample are often lower than expected. Two main factors contribute to this discrepancy: limitations in mass spectrometry's detection sensitivity and bioinformatics challenges in metaproteomics identification. This study introduces a novel approach to evaluating sample complexity directly at the full mass spectrum (MS1) level rather than relying on peptide identifications. When analyzing under identical mass spectrometry conditions, microbiome samples displayed significantly higher complexity, as evidenced by the spectral entropy and peptide candidate entropy, compared to single-species samples. The research provides solid evidence for the complexity of microbiome in proteomics indicating the optimization potential of the bioinformatics workflow.

INSTRUMENT(S): Orbitrap Exploris 480

ORGANISM(S): Gut Metagenome

TISSUE(S): Feces

SUBMITTER: Haonan Duan  

LAB HEAD: Daniel Figeys

PROVIDER: PXD050781 | Pride | 2024-05-27

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
20221208_Ailing_Jumpstart_C.raw Raw
20221208_Ailing_Jumpstart_D.raw Raw
20221208_Ailing_Jumpstart_E.raw Raw
Ailing_20230306_DOSETEST_PF_1.raw Raw
Ailing_20230306_DOSETEST_PF_2.raw Raw
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Publications

Spectral entropy as a measure of the metaproteome complexity.

Duan Haonan H   Ning Zhibin Z   Zhang Ailing A   Figeys Daniel D  

Proteomics 20240525 16


The diversity and complexity of the microbiome's genomic landscape are not always mirrored in its proteomic profile. Despite the anticipated proteomic diversity, observed complexities of microbiome samples are often lower than expected. Two main factors contribute to this discrepancy: limitations in mass spectrometry's detection sensitivity and bioinformatics challenges in metaproteomics identification. This study introduces a novel approach to evaluating sample complexity directly at the full m  ...[more]

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