LFQProfiler and RNP<sup>xl</sup>: Open-Source Tools for Label-Free Quantification and Protein–RNA Cross-Linking Integrated into Proteome Discoverer

Veit, J.; Sachsenberg, Timo; Chernev, Aleksandar; Aicheler, Fabian; Urlaub, Henning; Kohlbacher, Oliver

doi:10.1021/acs.jproteome.6b00407

Cited by 30 publications

(49 citation statements)

References 34 publications

(62 reference statements)

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“…Identifying the mass shift for peptides bound to fragmented RNA requires their annotation by specialist search engines. We compared the results of interpreting spectra using the published RNP XL pipeline (Veit et al , ) and the Xi search engine, which was designed for peptide–peptide crosslinks (Giese et al , ; preprint: Mendes et al , ) (https://github.com/Rappsilber-Laboratory/XiSearch). Better results were obtained with Xi (see Appendix Supplementary Methods), which was used for subsequent analyses.…”

Section: Resultsmentioning

confidence: 99%

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Defining the RNA interactome by total RNA ‐associated protein purification

Shchepachev

Bresson

Spanos

et al. 2019

Molecular Systems Biology

123

137

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The RNA binding proteome ( RBP ome) was previously investigated using UV crosslinking and purification of poly(A)‐associated proteins. However, most cellular transcripts are not polyadenylated. We therefore developed total RNA ‐associated protein purification ( TRAPP ) based on 254 nm UV crosslinking and purification of all RNA –protein complexes using silica beads. In a variant approach ( PAR ‐ TRAPP ), RNA s were labelled with 4‐thiouracil prior to 350 nm crosslinking. PAR ‐ TRAPP in yeast identified hundreds of RNA binding proteins, strongly enriched for canonical RBP s. In comparison, TRAPP identified many more proteins not expected to bind RNA , and this correlated strongly with protein abundance. Comparing TRAPP in yeast and E. coli showed apparent conservation of RNA binding by metabolic enzymes. Illustrating the value of total RBP purification, we discovered that the glycolytic enzyme enolase interacts with tRNA s. Exploiting PAR ‐ TRAPP to determine the effects of brief exposure to weak acid stress revealed specific changes in late 60S ribosome biogenesis. Furthermore, we identified the precise sites of crosslinking for hundreds of RNA –peptide conjugates, using iTRAPP , providing insights into potential regulation. We conclude that TRAPP is a widely applicable tool for RBP ome characterization.

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Section: Resultsmentioning

confidence: 99%

“…RNP xl plugin: We utilized RNP xl plugin (Veit et al , ) for Proteome discoverer version 2.1.1.21 (Thermo Fisher Scientific). MS1 tolerance 6 ppm; MS2 tolerance 20 ppm; enzyme—trypsin\p; missed cleavages allowed—2; maximum RNA length—3 nucleotides of which one has to be 4tU.…”

Section: Methodsmentioning

confidence: 99%

Defining the RNA interactome by total RNA ‐associated protein purification

Shchepachev

Bresson

Spanos

et al. 2019

Molecular Systems Biology

123

137

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“…This direct feedback on the visible subset of the data allows users to fine-tune parameters and understand the effect of the data processing intuitively. Selected OpenMS tools (e.g., label-free quantification for proteomics, RNA-protein cross-linking, non-targeted metabolite quantification) have also been integrated into commercial workflow engines and analysis suites (Proteome Discoverer and Compound Discoverer [15] ). This integration brings the OpenMS tools into a platform many users are already familiar with.…”

Section: Visualizationmentioning

confidence: 99%

“…With the new release of OpenMS 2.0 (http://www.openms.org/download/openms-binaries/), we have extended its functionality and provide a large number of pre-built user-oriented tools and workflows for reproducible MS data analysis (see Supplementary Note 1). We have also fully integrated OpenMS with graphical workflow systems (such as KNIME [13] , Galaxy [14] , Proteome Discoverer, or Compound Discoverer [15] ) making it it more easily accessible to experimental life scientists and more powerful in the hands of bioinformaticians. For a guide to getting started, see Box 1.…”

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confidence: 99%

OpenMS: a flexible open-source software platform for mass spectrometry data analysis

et al. 2016

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“…via thiouridine provides unique information about protein-RNA interfaces and entire complex architectures [124,125]. Systematic integration of restraint information from protein-RNA crosslinks is now being used in an automated way [126] and can define and validate RNP models in the future.…”

Section: Biochemical Assaysmentioning

confidence: 99%

Integrated structural biology to unravel molecular mechanisms of protein-RNA recognition

Schlundt

Tants

Sattler

2017

Methods

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Recent advances in RNA sequencing technologies have greatly expanded our knowledge of the RNA landscape in cells, often with spatiotemporal resolution. These techniques identified many new (often non-coding) RNA molecules. Large-scale studies have also discovered novel RNA binding proteins (RBPs), which exhibit single or multiple RNA binding domains (RBDs) for recognition of specific sequence or structured motifs in RNA. Starting from these large-scale approaches it is crucial to unravel the molecular principles of protein-RNA recognition in ribonucleoprotein complexes (RNPs) to understand the underlying mechanisms of gene regulation. Structural biology and biophysical studies at highest possible resolution are key to elucidate molecular mechanisms of RNA recognition by RBPs and how conformational dynamics, weak interactions and cooperative binding contribute to the formation of specific, context-dependent RNPs. While large compact RNPs can be well studied by X-ray crystallography and cryo-EM, analysis of dynamics and weak interaction necessitates the use of solution methods to capture these properties. Here, we illustrate methods to study the structure and conformational dynamics of protein-RNA complexes in solution starting from the identification of interaction partners in a given RNP. Biophysical and biochemical techniques support the characterization of a protein-RNA complex and identify regions relevant in structural analysis. Nuclear magnetic resonance (NMR) is a powerful tool to gain information on folding, stability and dynamics of RNAs and characterize RNPs in solution. It provides crucial information that is complementary to the static pictures derived from other techniques. NMR can be readily combined with other solution techniques, such as small angle X-ray and/or neutron scattering (SAXS/SANS), electron paramagnetic resonance (EPR), and Förster resonance energy transfer (FRET), which provide information about overall shapes, internal domain arrangements and dynamics. Principles of protein-RNA recognition and current approaches are reviewed and illustrated with recent studies.

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LFQProfiler and RNP^xl: Open-Source Tools for Label-Free Quantification and Protein–RNA Cross-Linking Integrated into Proteome Discoverer

Cited by 30 publications

References 34 publications

Defining the RNA interactome by total RNA ‐associated protein purification

Defining the RNA interactome by total RNA ‐associated protein purification

OpenMS: a flexible open-source software platform for mass spectrometry data analysis

Integrated structural biology to unravel molecular mechanisms of protein-RNA recognition

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LFQProfiler and RNPxl: Open-Source Tools for Label-Free Quantification and Protein–RNA Cross-Linking Integrated into Proteome Discoverer

Cited by 30 publications

References 34 publications

Defining the RNA interactome by total RNA ‐associated protein purification

Defining the RNA interactome by total RNA ‐associated protein purification

OpenMS: a flexible open-source software platform for mass spectrometry data analysis

Integrated structural biology to unravel molecular mechanisms of protein-RNA recognition

Contact Info

Product

Resources

About

LFQProfiler and RNP^xl: Open-Source Tools for Label-Free Quantification and Protein–RNA Cross-Linking Integrated into Proteome Discoverer