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Optimization of proteomics sample preparation for identification of host and bacterial proteins in mouse feces

Analytical and Bioanalytical Chemistry volume 414, pages 2317–2331 (2022)Cite this article

Abstract

Bottom-up proteomics is a powerful method for the functional characterization of mouse gut microbiota. To date, most of the bottom-up proteomics studies of the mouse gut rely on limited amounts of fecal samples. With mass-limited samples, the performance of such analyses is highly dependent on the protein extraction protocols and contaminant removal strategies. Here, protein extraction protocols (using different lysis buffers) and contaminant removal strategies (using different types of filters and beads) were systematically evaluated to maximize quantitative reproducibility and the number of identified proteins. Overall, our results recommend a protein extraction method using a combination of sodium dodecyl sulfate (SDS) and urea in Tris–HCl to yield the greatest number of protein identifications. These conditions led to an increase in the number of proteins identified from gram-positive bacteria, such as Firmicutes and Actinobacteria, which is a challenging task. Our analysis further confirmed these conditions led to the extraction of non-abundant bacterial phyla such as Proteobacteria. In addition, we found that, when coupled to our optimized extraction method, suspension trap (S-Trap) outperforms other contaminant removal methods by providing the most reproducible method while producing the greatest number of protein identifications. Overall, our optimized sample preparation workflow is straightforward and fast, and requires minimal sample handling. Furthermore, our approach does not require high amounts of fecal samples, a vital consideration in proteomics studies where mice produce smaller amounts of feces due to a particular physiological condition. Our final method provides efficient digestion of mouse fecal material, is reproducible, and leads to high proteomic coverage for both host and microbiome proteins.

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Data availability

The mass spectrometry proteomics data have been deposited to the ProteomeXchange [29] Consortium via the PRIDE [30] partner repository with the dataset identifier PXD027788.

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Acknowledgements

We thank the OSU Campus Chemical Instrument Center for access to the timsTOF Pro purchased with grant S10 OD026945 from the National Institutes of Health.

Funding

This work was funded by the grant number 5R01AI43288 from the National Institutes of Health.

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Authors and Affiliations

  1. Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, USA

    Maryam Baniasad, Yongseok Kim & Vicki H. Wysocki

  2. Department of Soil and Crop Sciences, The Colorado State University, Fort Collins, CO, USA

    Michael Shaffer, Ikaia Leleiwi, Rebecca A. Daly & Kelly C. Wrighton

  3. Department of Microbiology, The Ohio State University, Columbus, OH, USA

    Anice Sabag-Daigle & Brian M. M. Ahmer

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  1. Maryam Baniasad
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  2. Yongseok Kim
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Correspondence to Vicki H. Wysocki.

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Mouse experiments in this study were performed in accordance with protocols approved by The Ohio State University Institutional Animal Care and Use Committee (IACUC; OSU 2009A0035-R4).

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Baniasad, M., Kim, Y., Shaffer, M. et al. Optimization of proteomics sample preparation for identification of host and bacterial proteins in mouse feces. Anal Bioanal Chem 414, 2317–2331 (2022). https://doi.org/10.1007/s00216-022-03885-z

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