Dataset Information

Assay for characterizing adsorption-properties of surfaces (APS)

ABSTRACT: Analytes, from sample preparation, until entering an analytical instrument, are prone to adsorb to surfaces, driven by the chemical properties of the surface and the liquids they are dissolved in. This problem can be addressed with internal standards when a single or few known analytes are quantified that are usually not available in omics. However, minimal to no loss of analytes is the aim. Here, we present a novel assay for qualifying and quantifying interactions responsible for adsorption of molecules to surfaces (APS) by using LC-MS/MS-based differential quantitative analysis. To reflect a broad range of chemical interactions with surfaces, a reference mixture of thousands of tryptic peptides, with known compositions was selected, representing a variety of different chemical characteristics. The assay was tested by investigating the adsorption properties of several different vials with different surface chemistries. A significant number of hydrophobic peptides adsorbed to conventional polypropylene vials. In contrast, only few peptides adsorbed to polypropylene vials, assigned as low-protein-binding. The highest number of peptides adsorbed to glass vials driven by electrostatic interactions. In summary, the new assay is suitable to characterize adsorption properties of different surfaces and to approximate the loss of analytes during sample preparation.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Bente Siebels

LAB HEAD: Hartmut Schlueter

PROVIDER: PXD044268 | Pride | 2024-08-30

REPOSITORIES: Pride

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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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Assay for characterizing adsorption-properties of surfaces (APS)

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