Specifying RNA-Binding Regions in Proteins by Peptide Cross-Linking and Affinity Purification

RNA-binding proteins (RBPs) allow cells to carry out pre-RNA processing and post-transcriptional regulation of gene expression, and aberrations in RBP functions have been linked to many diseases, including neurological disorders and cancer. Human cells encode thousands of RNA-binding proteins with unique RNA-binding properties. These properties are regulated through modularity of a large variety of RNA-binding domains, rendering RNA–protein interactions difficult to study. Recently, the introduction of proteomics methods has provided novel insights into RNA-binding proteins at a systems level. However, determining the exact protein sequence regions that interact with RNA remains challenging and laborious, especially considering that many RBPs lack canonical RNA-binding domains. Here we describe a streamlined proteomic workflow called peptide cross-linking and affinity purification (pCLAP) that allows rapid characterization of RNA-binding regions in proteins. pCLAP is based upon the combined use of UV cross-linking and enzymatic digestion of RNA-bound proteins followed by single-shot mass spectrometric analysis. To benchmark our method, we identified the binding regions for polyadenylated RNA-binding proteins in HEK293 cells, allowing us to map the mRNA interaction regions of more than 1000 RBPs with very high reproducibility from replicate single-shot analyses. Our results show specific enrichment of many known RNA-binding regions on many known RNA-binding proteins, confirming the specificity of our approach

Specifying RNA-Binding Regions in Proteins by Peptide Cross-Linking and Affinity Purification

RNA-binding proteins (RBPs) allow cells to carry out pre-RNA processing and post-transcriptional regulation of gene expression, and aberrations in RBP functions have been linked to many diseases, including neurological disorders and cancer. Human cells encode thousands of RNA-binding proteins with unique RNA-binding properties. These properties are regulated through modularity of a large variety of RNA-binding domains, rendering RNA–protein interactions difficult to study. Recently, the introduction of proteomics methods has provided novel insights into RNA-binding proteins at a systems level. However, determining the exact protein sequence regions that interact with RNA remains challenging and laborious, especially considering that many RBPs lack canonical RNA-binding domains. Here we describe a streamlined proteomic workflow called peptide cross-linking and affinity purification (pCLAP) that allows rapid characterization of RNA-binding regions in proteins. pCLAP is based upon the combined use of UV cross-linking and enzymatic digestion of RNA-bound proteins followed by single-shot mass spectrometric analysis. To benchmark our method, we identified the binding regions for polyadenylated RNA-binding proteins in HEK293 cells, allowing us to map the mRNA interaction regions of more than 1000 RBPs with very high reproducibility from replicate single-shot analyses. Our results show specific enrichment of many known RNA-binding regions on many known RNA-binding proteins, confirming the specificity of our approach

Medicago truncatula and Glycine max: Different Drought Tolerance and Similar Local Response of the Root Nodule Proteome

Legume crops present important agronomical and environmental advantages mainly due to their capacity to reduce atmospheric N₂ to ammonium via symbiotic nitrogen fixation (SNF). This process is very sensitive to abiotic stresses such as drought, but the mechanism underlying this response is not fully understood. The goal of the current work is to compare the drought response of two legumes with high economic impact and research importance, Medicago truncatula and Glycine max, by characterizing their root nodule proteomes. Our results show that, although M. truncatula exhibits lower water potential values under drought conditions compared to G. max, SNF declined analogously in the two legumes. Both of their nodule proteomes are very similar, and comparable down-regulation responses in the diverse protein functional groups were identified (mainly proteins related to the metabolism of carbon, nitrogen, and sulfur). We suggest lipoxygenases and protein turnover as newly recognized players in SNF regulation. Partial drought conditions applied to a split-root system resulted in the local down-regulation of the entire proteome of drought-stressed nodules in both legumes. The high degree of similarity between both legume proteomes suggests that the vast amount of research conducted on M. truncatula could be applied to economically important legume crops, such as soybean

<i>mzGroupAnalyzer</i>-Predicting Pathways and Novel Chemical Structures from Untargeted High-Throughput Metabolomics Data

<div><p>The metabolome is a highly dynamic entity and the final readout of the genotype x environment x phenotype (GxExP) relationship of an organism. Monitoring metabolite dynamics over time thus theoretically encrypts the whole range of possible chemical and biochemical transformations of small molecules involved in metabolism. The bottleneck is, however, the sheer number of unidentified structures in these samples. This represents the next challenge for metabolomics technology and is comparable with genome sequencing 30 years ago. At the same time it is impossible to handle the amount of data involved in a metabolomics analysis manually. Algorithms are therefore imperative to allow for automated <i>m/z</i> feature extraction and subsequent structure or pathway assignment. Here we provide an automated pathway inference strategy comprising measurements of metabolome time series using LC- MS with high resolution and high mass accuracy. An algorithm was developed, called <i>mzGroupAnalyzer</i>, to automatically explore the metabolome for the detection of metabolite transformations caused by biochemical or chemical modifications. Pathways are extracted directly from the data and putative novel structures can be identified. The detected <i>m/z</i> features can be mapped on a van Krevelen diagram according to their H/C and O/C ratios for pattern recognition and to visualize oxidative processes and biochemical transformations. This method was applied to <i>Arabidopsis thaliana</i> treated simultaneously with cold and high light. Due to a protective antioxidant response the plants turn from green to purple color via the accumulation of flavonoid structures. The detection of potential biochemical pathways resulted in 15 putatively new compounds involved in the flavonoid-pathway. These compounds were further validated by product ion spectra from the same data. The <i>mzGroupAnalyzer</i> is implemented in the graphical user interface (GUI) of the metabolomics toolbox COVAIN (Sun & Weckwerth, 2012, Metabolomics 8: 81–93). The strategy can be extended to any biological system.</p></div

Medicago truncatula and Glycine max: Different Drought Tolerance and Similar Local Response of the Root Nodule Proteome

Legume crops present important agronomical and environmental advantages mainly due to their capacity to reduce atmospheric N₂ to ammonium via symbiotic nitrogen fixation (SNF). This process is very sensitive to abiotic stresses such as drought, but the mechanism underlying this response is not fully understood. The goal of the current work is to compare the drought response of two legumes with high economic impact and research importance, Medicago truncatula and Glycine max, by characterizing their root nodule proteomes. Our results show that, although M. truncatula exhibits lower water potential values under drought conditions compared to G. max, SNF declined analogously in the two legumes. Both of their nodule proteomes are very similar, and comparable down-regulation responses in the diverse protein functional groups were identified (mainly proteins related to the metabolism of carbon, nitrogen, and sulfur). We suggest lipoxygenases and protein turnover as newly recognized players in SNF regulation. Partial drought conditions applied to a split-root system resulted in the local down-regulation of the entire proteome of drought-stressed nodules in both legumes. The high degree of similarity between both legume proteomes suggests that the vast amount of research conducted on M. truncatula could be applied to economically important legume crops, such as soybean

Medicago truncatula and Glycine max: Different Drought Tolerance and Similar Local Response of the Root Nodule Proteome

Legume crops present important agronomical and environmental advantages mainly due to their capacity to reduce atmospheric N₂ to ammonium via symbiotic nitrogen fixation (SNF). This process is very sensitive to abiotic stresses such as drought, but the mechanism underlying this response is not fully understood. The goal of the current work is to compare the drought response of two legumes with high economic impact and research importance, Medicago truncatula and Glycine max, by characterizing their root nodule proteomes. Our results show that, although M. truncatula exhibits lower water potential values under drought conditions compared to G. max, SNF declined analogously in the two legumes. Both of their nodule proteomes are very similar, and comparable down-regulation responses in the diverse protein functional groups were identified (mainly proteins related to the metabolism of carbon, nitrogen, and sulfur). We suggest lipoxygenases and protein turnover as newly recognized players in SNF regulation. Partial drought conditions applied to a split-root system resulted in the local down-regulation of the entire proteome of drought-stressed nodules in both legumes. The high degree of similarity between both legume proteomes suggests that the vast amount of research conducted on M. truncatula could be applied to economically important legume crops, such as soybean

Structure validation of <i>m/z</i> 1121 by MS³ product ion scans.

<p>Both MS² fragments <i>m/z</i> 535 and 873 result in the core cyanidin structure by undergoing MS³ fragmentation. <i>m/z</i> 1077, the putatively decarboxylized form of 1121, yields <i>m/z</i> 491, as observed in the MS² spectrum already, by scission of the 3-O-glycosidic bond. Fragment <i>m/z</i> 873 arises again from the breaking of the glycosidic bond at 5-O. <i>m/z</i> 1017 would comply with the complete removal of the rest of the former malonyl group together with a water loss (−60 u). A putative structure is given.</p

Putative compounds including their <i>mzGroupAnalyzer</i>- predicted sum formulas, the corresponding exact mass as well as dominant MS² product ion fragments.

<p>The nomenclature is according to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096188#pone.0096188-Tohge1" target="_blank">[33]</a>. Compounds <i>m/z</i> 1125, 1197 and 1211 were found in <i>Matthiola incana</i> by <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096188#pone.0096188-Saito1" target="_blank">[39]</a>.</p

Scheme of the <i>mzGroupAnalyzer</i> and <i>Pathway Viewer</i> algorithm and GUI implementation.

<p>The program reads the <i>m/z</i> features which are extracted from Xcalibur, as well as the user predefined reaction rules. Then it finds transformations between all pairs of <i>m/z</i> features, and reports the frequency of transformations for the listed and not listed but potentially existing rules. Next, the program starts searching pathways inside the <i>m/z</i> features' network. A shorter path existing in other longer paths is removed, thereby non-redundant pathways are obtained. Then, <i>mzGroupAnalyzer</i> opens the Pathway Viewer, in which pathways satisfying user-defined filtering options will be displayed on the panel. The pathway diagram, which consists of reaction rules, <i>m/z</i> feature names, compositions and time points, can be plotted by clicking the table. Finally, all the results, including the frequency table of transformations, the interconnected network visualization file (in Pajek's format), the inferred pathways and a Matlab workspace (suffixed with mzStruct.mat) containing all results, will be exported to the user-specified folder.</p

After oxidative stress the <i>Arabidopsis thaliana</i> plants turn from green into purple indicating a dramatic shift in metabolism, specifically elevated flavonoid biosynthesis involved in oxidative stress protection [6].

<p><b>A</b> Plants turns from green to purple under high light and cold temperature treatment. <b>B</b> Van Krevelen diagram of the most abundant <i>m/z</i> values of unstressed (green dots) and 20-day cold stressed (purple dots) Arabidopsis plants. A clear shift of metabolism in the stressed plants is visible.</p