Evaluation of sample preparation methods for label-free quantitative profiling of salivary proteome

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Zhang, Xi
Sadowski, Pawel
Punyadeera, Chamindie
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2020
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Abstract

Saliva has become one of the more attractive body fluids for protein biomarker discovery studies because of its ease of collection, non-invasiveness and multiple samples can be collected from an individual at a single time point. With the development of modern data acquisition strategies, such as Sequential Window Acquisition of all Theoretical Mass Spectrometry (SWATH-MS), the quality of saliva sample preparation has become a crucial factor for a successful protein identification and quantification. Several sample preparation methods have been proposed, but there has been no systematic evaluation conducted to date that compared each of these methods. We have therefore, performed an extensive assessment using technical and biological repeats to evaluate the number of protein IDs and repeatability of three most commonly used techniques, in-solution digestion, filter-aided sample preparation (FASP) and in stage-tip (iST) digestion. We discovered that in the case of human saliva sample, FASP provided the highest number of proteins (human and microbial) identifiable from a pool saliva sample, and there were no significant differences in terms of repeatability among the three methods investigated.

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Journal of Proteomics

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210

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© 2020 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.

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Biochemistry and cell biology

Plant biology

Medical biochemistry and metabolomics

Science & Technology

Life Sciences & Biomedicine

Biochemical Research Methods

Biochemistry & Molecular Biology

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Zhang, X; Sadowski, P; Punyadeera, C, Evaluation of sample preparation methods for label-free quantitative profiling of salivary proteome, Journal of Proteomics, 2020, 210, pp. 103532

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