Dataset Information

Evaluating sequence alignment for metaproteomics applications

ABSTRACT: This dataset was utilized to assess the performance of a novel de novo metaproteomics pipeline, which performs sequence alignment of de novo sequences from complete metaproteomics experiments. Traditionally, metaproteomics data annotation relies on database searching that requires sample-specific databases derived from whole metagenome sequencing experiments. Creating these databases, however, is a complex, time-consuming, and error prone process, which can introduce biases affecting the outcomes and conclusions, highlighting the need for alternative methods. The evaluated approach offers rapid and orthogonal insights into metaproteomics data.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Saccharomyces Cerevisiae (baker's Yeast)

SUBMITTER: Martin Pabst

LAB HEAD: Martin Pabst

PROVIDER: PXD050548 | Pride | 2024-10-10

REPOSITORIES: Pride

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			Action	DRS
	JvE_13012022_Accumulibacter_180_DDA01.raw	Raw
	JvE_13012022_Accumulibacter_180_DDA02.raw	Raw
	MDR_16062023_Yeast_Ref_500ng_DDA01.raw	Raw
	MP_1362023_Yeast_Ref_500ng_DDA_01.raw	Raw
	MP_CL20122020_Kust_Ac_t0_S12_DDA01.raw	Raw

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Project description:A Metaproteomic Workflow for Sample Preparation and Data Analysis Applied to Mouse Faeces: 1 MTD project_description Many diseases have been associated with gut microbiome abnormalities. The root cause of such diseases is not only due to bacterial dysbiosis, but also to change in bacterial functions, which are best studied by proteomic approaches. Although bacterial proteomics is well established, metaproteomics is hindered by challenges associated with the sample physical structure, contaminating proteins, the simultaneous analysis of hundreds of species and the subsequent data analysis. Here, we present a systematic assessment of sample preparation and data analysis methodologies applied to LC-MS/MS metaproteomics experiment. We could show that low speed centrifugation (LSC) has a significant impact on both peptide identifications and reproducibility. LSC led to increase in peptide and proteins identifications compare to no LSC. Notably, the dominant bacterial phyla, i.e. Firmicutes and Bacteroidetes, showed divergent representation between LSC and no-LSC. In terms of data processing, protein sequence databases derived from mouse faeces metagenome provided at least four times more MS/MS identification compared to databases of concatenated single organisms. We also demonstrated that two-steps database search strategy comes at the expense of a dramatic rise in number of false positives compared to single-step strategy. Overall, we found a positive correlation between matching metaproteome and metagenome abundance, which could be linked to core microbial functions, such as glycolysis-gluconeogenesis, citrate cycle and carbon metabolism. We observed significant overlap and correlation at the phylum, class, order and family taxonomic levels between taxonomy-derived from metagenome and metaproteome. Notably, nearly all functional categories (e.g., membrane transport, translation, transcription) were differentially abundant in the metaproteome (activity) compared to what would be expected from the metagenome (potential). In conclusion, these results highlight the need to perform metaproteomics when studying complex microbiome samples.

Project description:Many diseases have been associated with gut microbiome abnormalities. The root cause of such diseases is not only due to bacterial dysbiosis, but also to change in bacterial functions, which are best studied by proteomic approaches. Although bacterial proteomics is well established, metaproteomics is hindered by challenges associated with the sample physical structure, contaminating proteins, the simultaneous analysis of hundreds of species and the subsequent data analysis. Here, we present a systematic assessment of sample preparation and data analysis methodologies applied to LC-MS/MS metaproteomics experiment. We could show that low speed centrifugation (LSC) has a significant impact on both peptide identifications and reproducibility. LSC led to increase in peptide and proteins identifications compare to no LSC. Notably, the dominant bacterial phyla, i.e. Firmicutes and Bacteroidetes, showed divergent representation between LSC and no-LSC. In terms of data processing, protein sequence databases derived from mouse faeces metagenome provided at least four times more MS/MS identification compared to databases of concatenated single organisms. We also demonstrated that two-steps database search strategy comes at the expense of a dramatic rise in number of false positives compared to single-step strategy. Overall, we found a positive correlation between matching metaproteome and metagenome abundance, which could be linked to core microbial functions, such as glycolysis-gluconeogenesis, citrate cycle and carbon metabolism. We observed significant overlap and correlation at the phylum, class, order and family taxonomic levels between taxonomy-derived from metagenome and metaproteome. Notably, nearly all functional categories (e.g., membrane transport, translation, transcription) were differentially abundant in the metaproteome (activity) compared to what would be expected from the metagenome (potential). In conclusion, these results highlight the need to perform metaproteomics when studying complex microbiome samples.

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Evaluating sequence alignment for metaproteomics applications

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