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Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions.

ABSTRACT: Noncoding RNAs play important roles in several nuclear processes, including regulating gene expression, chromatin structure, and DNA repair. In most cases, the action of noncoding RNAs is mediated by proteins whose functions are in turn regulated by these interactions with noncoding RNAs. Consistent with this, a growing number of proteins involved in nuclear functions have been reported to bind RNA and in a few cases the RNA-binding regions of these proteins have been mapped, often through laborious, candidate-based methods. Here, we report a detailed protocol to perform a high-throughput, proteome-wide unbiased identification of RNA-binding proteins and their RNA-binding regions. The methodology relies on the incorporation of a photoreactive uridine analog in the cellular RNA, followed by UV-mediated protein-RNA crosslinking, and mass spectrometry analyses to reveal RNA-crosslinked peptides within the proteome. Although we describe the procedure for mouse embryonic stem cells, the protocol should be easily adapted to a variety of cultured cells.

SUBMITTER: Warneford-Thomson R

PROVIDER: S-EPMC5752346 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions.

Warneford-Thomson Robert R He Chongsheng C Sidoli Simone S Garcia Benjamin A BA Bonasio Roberto R

Journal of visualized experiments : JoVE 20170928 127

Noncoding RNAs play important roles in several nuclear processes, including regulating gene expression, chromatin structure, and DNA repair. In most cases, the action of noncoding RNAs is mediated by proteins whose functions are in turn regulated by these interactions with noncoding RNAs. Consistent with this, a growing number of proteins involved in nuclear functions have been reported to bind RNA and in a few cases the RNA-binding regions of these proteins have been mapped, often through labor ...[more]

PMID: 28994809

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Project description:BackgroundSample preparation is a critical process for proteomic studies. Many efficient and reproducible sample preparation methods have been developed for mass spectrometry-based proteomic analysis of human and animal tissues or cells, but no attempt has been made to evaluate these protocols for plants. We here present an LC-MS/MS-based proteomics study of barley leaf aimed at optimization of methods to achieve efficient and unbiased trypsin digestion of proteins prior to LC-MS/MS based sequencing and quantification of peptides. We evaluated two spin filter-aided sample preparation protocols using either sodium dodecyl-sulphate or sodium deoxycholate (SDC), and three in-solution digestion (ISD) protocols using SDC or trichloroacetic acid/acetone precipitation.ResultsThe proteomics workflow identified and quantified up to 1800 barley proteins based on sequencing of up to 6900 peptides per sample. The two spin filter-based protocols provided a 12-38% higher efficiency than the ISD protocols, including more proteins of low abundance. Among the ISD protocols, a simple one-step reduction and S-alkylation method (OP-ISD) was the most efficient for barley leaf sample preparation; it identified and quantified 1500 proteins and displayed higher peptide-to-protein inference ratio and higher average amino acid sequence coverage of proteins. The two spin filter-aided sample preparation protocols are compatible with TMT labelling for quantitative proteomics studies. They exhibited complementary performance as about 30% of the proteins were identified by either one or the other protocol, but also demonstrated a positive bias for membrane proteins when using SDC as detergent.ConclusionsWe provide detailed protocols for efficient plant protein sample preparation for LC-MS/MS-based proteomics studies. Spin filter-based protocols are the most efficient for the preparation of leaf samples for MS-based proteomics. However, a simple protocol provides comparable results although with different peptide digestion profile.

Dataset Information

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions.

Publications

Sample Preparation for Mass Spectrometry-based Identification of RNA-binding Regions.

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