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XB-ART-52097
Anal Bioanal Chem 2016 Jul 01;40817:4743-9. doi: 10.1007/s00216-016-9564-2.
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Optimization and comparison of bottom-up proteomic sample preparation for early-stage Xenopus laevis embryos.

Peuchen EH , Sun L , Dovichi NJ .


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Xenopus laevis is an important model organism in developmental biology. While there is a large literature on changes in the organism's transcriptome during development, the study of its proteome is at an embryonic state. Several papers have been published recently that characterize the proteome of X. laevis eggs and early-stage embryos; however, proteomic sample preparation optimizations have not been reported. Sample preparation is challenging because a large fraction (~90 % by weight) of the egg or early-stage embryo is yolk. We compared three common protein extraction buffer systems, mammalian Cell-PE LB(TM) lysing buffer (NP40), sodium dodecyl sulfate (SDS), and 8 M urea, in terms of protein extraction efficiency and protein identifications. SDS extracts contained the highest concentration of proteins, but this extract was dominated by a high concentration of yolk proteins. In contrast, NP40 extracts contained ~30 % of the protein concentration as SDS extracts, but excelled in discriminating against yolk proteins, which resulted in more protein and peptide identifications. We then compared digestion methods using both SDS and NP40 extraction methods with one-dimensional reverse-phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS). NP40 coupled to a filter-aided sample preparation (FASP) procedure produced nearly twice the number of protein and peptide identifications compared to alternatives. When NP40-FASP samples were subjected to two-dimensional RPLC-ESI-MS/MS, a total of 5171 proteins and 38,885 peptides were identified from a single stage of embryos (stage 2), increasing the number of protein identifications by 23 % in comparison to other traditional protein extraction methods.

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References [+] :
Cox, Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. 2014, Pubmed