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Methods Mol Biol
2023 Jan 01;2636:343-366. doi: 10.1007/978-1-0716-3012-9_19.
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Quantitative Proteomics of Nervous System Regeneration: From Sample Preparation to Functional Data Analyses.
Lee-Liu D
,
Sun L
.
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Mammals have a limited regenerative capacity, especially of the central nervous system. Consequently, any traumatic injury or neurodegenerative disease results in irreversible damage. An important approach to finding strategies to promote regeneration in mammals has been the study of regenerative organisms like Xenopus, the axolotl, and teleost fish. High-throughput technologies like RNA-Seq and quantitative proteomics are starting to provide valuable insight into the molecular mechanisms that drive nervous system regeneration in these organisms. In this chapter, we present a detailed protocol for performing iTRAQ proteomics that can be applied to the analysis of nervous system samples, using Xenopus laevis as an example. The quantitative proteomics protocol and directions for performing functional enrichment data analyses of gene lists (e.g., differentially abundant proteins from a proteomic study, or any type of high-throughput analysis) are aimed at the general bench biologist and do not require previous programming knowledge.
Fig. 1
Workflow summary of the protocol (part I). (a) Summary of acquisition of tissue samples, from tissue dissection to flash freezing them in liquid nitrogen. (b) iTRAQ labeling protocol of peptides, from protein extraction to iTRAQ 8-plex labeling. (c) Schematic design of the SCX–RPLC–ESI–MS/MS (strong cation exchange–reversed-phase liquid chromatography–electrospray ionization–tandem mass spectrometry). (d) Protein identification and quantification and differential protein abundance analysis, performed using MaxQuant and Perseus
Fig. 2
Workflow summary of the protocol (part II). Schematic workflow of the functional analyses that can be performed once differential abundance gene or protein lists are obtained. These include, if needed, finding the human or mouse ortholog for better functional annotation (a), different types of functional analyses, including obtaining all functional annotation available per gene, functional enrichment analysis, and STRING protein–protein association network representation of results (b). Resulting functional analysis terms may be further compared among samples using Venn diagrams (c)
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