Microproteomic sample preparation
- PMID: 33547857
- DOI: 10.1002/pmic.202000318
Microproteomic sample preparation
Abstract
Multiple applications of proteomics in life and health science, pathology and pharmacology, require handling size-limited cell and tissue samples. During proteomic sample preparation, analyte loss in these samples arises when standard procedures are used. Thus, specific considerations have to be taken into account for processing, that are summarised under the term microproteomics (μPs). Microproteomic workflows include: sampling (e.g., flow cytometry, laser capture microdissection), sample preparation (possible disruption of cells or tissue pieces via lysis, protein extraction, digestion in bottom-up approaches, and sample clean-up) and analysis (chromatographic or electrophoretic separation, mass spectrometric measurements and statistical/bioinformatic evaluation). All these steps must be optimised to reach wide protein dynamic ranges and high numbers of identifications. Under optimal conditions, sampling is adapted to the studied sample types and nature, sample preparation isolates and enriches the whole protein content, clean-up removes salts and other interferences such as detergents or chaotropes, and analysis identifies as many analytes as the instrumental throughput and sensitivity allow. In the suggested review, we present and discuss the current state in μP applications for processing of small number of cells (cell μPs) and microscopic tissue regions (tissue μPs).
Keywords: bottom-up approach; cell microproteomics; mass spectrometry; microproteomics; protein analysis; sample preparation; tissue microproteomics; top-down approach.
© 2021 Wiley-VCH GmbH.
References
REFERENCES
-
- Laputková, G., Bencková, M., Alexovič, M., Schwartzová, V., Talian, I., & Sabo, J. (2017). Proteomic and bioinformatics analysis of human saliva for the dental-risk assessment. Open Life Science, 12(1), 248-265.
-
- Bober, P., Alexovič, M., Tomková, Z., Kilík, R., & Sabo, J. (2019). RHOA and mDia1 promotes apoptosis of breast cancer cells via a high dose of doxorubicin treatment. Open Life Science, 14(1), 619-627.
-
- Longuespée, R., Casadonte, R., Schwamborn, K., & Kriegsmann, M. (2019). Proteomics in pathology: The special issue. Proteomics. Clinical Applications, 13(1), 1800167. https://doi.org/10.1002/prca.201800167
-
- Longuespée, R., Casadonte, R., Schwamborn, K., Reuss, D., Kazdal, D., Kriegsmann, K., Von Deimling, A., Weichert, W., Schirmacher, P., Kriegsmann, J., & Kriegsmann, M. (2018). Proteomics in Pathology. Proteomics, 18(2), 1700361. https://doi.org/10.1002/pmic.201700361
-
- Longuespée, R., Fléron, M., Pottier, C., Quesada-Calvo, F., Meuwis, M.-A., Baiwir, D., Smargiasso, N., Mazzucchelli, G., De Pauw-Gillet, M.-C., Delvenne, P., & De Pauw, E. (2014). Tissue proteomics for the next decade? Towards a molecular dimension in histology. Omics, 18(9), 539-552. https://doi.org/10.1089/omi.2014.0033
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