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Analytical BiochemistryMolecular BiologyPeer-reviewed journal article

Screening for Potential Interaction Partners with Surface Plasmon Resonance Imaging Coupled to MALDI Mass Spectrometry

Ulrike Anders, Maya Gulotti-Georgieva, Susann Zelger‐PaulusiD, Fatima-Ezzahra Hibti, Chiraz Frydman, Detlev SuckauiD, Roland K. O. SigeliD, Renato ZenobiiD

PDFDOIPreprint

Abstract

We coupled SPR imaging (SPRi) with matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) to identify new potential RNA binders. Here, we improve this powerful method, especially by optimizing the proteolytic digestion (type of reducing agent, its concentration, and incubation time), to work with complex mixtures, specifically a lysate of the rough mitochondrial fraction from yeast. The advantages of this hyphenated method compared to column-based or separate analyses are (i) rapid and direct visual readout from the SPRi array, (ii) possibility of high-throughput analysis of different interactions in parallel, (iii) high sensitivity, and (iv) no sample loss or contamination due to elution or micro-recovery procedures. The model system used is a catalytically active RNA (group IIB intron from Saccharomyces cerevisiae, Sc.ai5{gamma}) and its cofactor Mss116. The protein supports the RNA folding process and thereby the subsequent excision of the intronic RNA from the coding part. Using the novel approach of coupling SPR with MALDI MS, we report the identification of potential RNA-binding proteins from a crude yeast mitochondrial lysate in a non-targeted approach. Our results show that proteins other than the well-known cofactor Mss116 interact with Sc.ai5{gamma} (Dbp8, Prp8, Mrp13, and Cullin-3), suggesting that the intron folding and splicing are regulated by more than one cofactor in vivo. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/082776v3_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@50a09borg.highwire.dtl.DTLVardef@1602253org.highwire.dtl.DTLVardef@6d9cc7org.highwire.dtl.DTLVardef@4ff0f0_HPS_FORMAT_FIGEXP M_FIG C_FIG Author contributionUlrike Anders and Maya Gulotti-Georgieva contributed equally to this work.

Citations
4
FWCI
0.36
Field percentile
41th percentile

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