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• W2894897551 abstract "Method8 April 2019Open Access Transparent process Defining the RNA interactome by total RNA-associated protein purification Vadim Shchepachev Vadim Shchepachev Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK Search for more papers by this author Stefan Bresson Stefan Bresson Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK Search for more papers by this author Christos Spanos Christos Spanos Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK Search for more papers by this author Elisabeth Petfalski Elisabeth Petfalski Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK Search for more papers by this author Lutz Fischer Lutz Fischer Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany Search for more papers by this author Juri Rappsilber Corresponding Author Juri Rappsilber [email protected] orcid.org/0000-0001-5999-1310 Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany Search for more papers by this author David Tollervey Corresponding Author David Tollervey [email protected] orcid.org/0000-0003-2894-2772 Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK Search for more papers by this author Vadim Shchepachev Vadim Shchepachev Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK Search for more papers by this author Stefan Bresson Stefan Bresson Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK Search for more papers by this author Christos Spanos Christos Spanos Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK Search for more papers by this author Elisabeth Petfalski Elisabeth Petfalski Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK Search for more papers by this author Lutz Fischer Lutz Fischer Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany Search for more papers by this author Juri Rappsilber Corresponding Author Juri Rappsilber [email protected] orcid.org/0000-0001-5999-1310 Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany Search for more papers by this author David Tollervey Corresponding Author David Tollervey [email protected] orcid.org/0000-0003-2894-2772 Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK Search for more papers by this author Author Information Vadim Shchepachev1, Stefan Bresson1, Christos Spanos1, Elisabeth Petfalski1, Lutz Fischer2, Juri Rappsilber *,1,2 and David Tollervey *,1 1Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK 2Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany *Corresponding author. Tel: +44 131 651 7056; E-mail: [email protected] *Corresponding author. Tel: +44 131 650 7092; E-mail: [email protected] Molecular Systems Biology (2019)15:e8689https://doi.org/10.15252/msb.20188689 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract The RNA binding proteome (RBPome) 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), RNAs were labelled with 4-thiouracil prior to 350 nm crosslinking. PAR-TRAPP in yeast identified hundreds of RNA binding proteins, strongly enriched for canonical RBPs. 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 tRNAs. 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 RBPome characterization. Synopsis This study presents TRAPP (total RNA-associated protein purification), a large-scale approach that allows the rapid identification of all RNA-binding proteins and quantification of dynamic changes following exposure to stress. TRAPP allows rapid identification of the RNA-bound proteome in both eukaryotes (S. cerevisiae) and bacteria (E. coli). PAR-TRAPP in yeast quantified changes in the RNA-bound proteome on stress, revealing specific defects in 60S ribosome maturation. iTRAPP mapped 524 unique RNA-peptide crosslinks from 178 proteins, with amino acid resolution. Introduction Interactions between RNA and proteins play key roles in many aspects of cell metabolism. However, the identification of protein–RNA interaction sites has long been challenging, particularly in living cells. Individual protein–RNA interactions can be characterized, if known, by mutagenic and biochemical approaches, but this has always been labour-intensive. The difficulty is compounded by the fact that many interactions do not fall within characterized interaction domains, and even apparently well-characterized RNA binding domains can show multiple modes of RNA interaction (Clery et al, 2013), making detailed predictions less reliable. For large-scale characterization of protein–RNA interactions, a significant advance was the development of RNA immunoprecipitation (RIP) with or without formaldehyde crosslinking, allowing the identification of RNAs associated with target proteins, although not the site of association (Niranjanakumari et al, 2002; Gilbert et al, 2004; Hurt et al, 2004; Motamedi et al, 2004; Huang et al, 2005; Gilbert & Svejstrup, 2006). Subsequently, UV crosslinking approaches were developed that allow accurate identification of the binding sites for individual proteins on RNA molecules, transcriptome-wide (Maly et al, 1980; Wagenmakers et al, 1980; Mital et al, 1993; Urlaub et al, 2000; Rhode et al, 2003; Doneanu et al, 2004; Granneman et al, 2009, 2010; Bley et al, 2011; Van Nostrand et al, 2016). Two major approaches have been adopted for crosslinking. Short wavelength, 254 nm UVC irradiation can directly induce nucleotide–protein crosslinking and was used in initial crosslinking and immunoprecipitation (CLIP) analyses, as well as CRAC analyses in yeast. Subsequently, photoactivatable ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP) was developed, in which 4-thiouracil is fed to the cells and incorporated into nascent transcripts, allowing RNA–protein crosslinking to be induced by longer wavelength, ~350–365 nm UVA irradiation. Both approaches have been used extensively in many systems (reviewed in Darnell, 2010). The reciprocal analyses of proteins that are bound to RNA were more difficult to develop, at least in part because proteomic approaches do not provide the amplification offered by PCR. However, UV crosslinking and RNA enrichment have been used to successfully identify many poly(A)+ RNA binding proteins present in human cells and other systems (Baltz et al, 2012; Castello et al, 2012; Kwon et al, 2013). This technique was an important advance but, like RIP, identifies the species involved but not the site of interaction, and is limited to mature mRNAs. To identify the total RNA-bound proteome, the approach of 5-ethynyluridine (EU) labelling of RNAs followed by biotin ligation using the click reaction (RICK) was recently developed (Bao et al, 2018; Huang et al, 2018) as well as approaches based on phase separation, in which RNA–protein conjugates are recovered from an aqueous/phenol interface (Queiroz et al, 2019; Trendel et al, 2019). In addition, MS analyses have been developed to identify the precise amino acid at the site of RNA–protein crosslinking (Kramer et al, 2014). The TRAPP techniques for identification of RNA–protein interaction are based on recovery of denatured RNA–protein complexes on silica beads, followed by mass spectrometry. They additionally permit identification of the peptide, and indeed the amino acid, that is crosslinked to RNA during UV irradiation in living cells. We applied TRAPP to identify RNA binding proteins from yeast and Escherichia coli following crosslinking in actively growing cells. These approaches should allow characterization of the protein–RNA interactome at steady state, as well as dynamic changes following stress exposure, in almost any system. Results Development of the TRAPP protocol In all TRAPP techniques, we initially covalently linked all RNAs to associated proteins by UV crosslinking in actively growing cells. Detailed protocols for each of the TRAPP workflows are given in Materials and Methods. In the TRAPP approach, ~750 ml cultures of actively growing yeast were irradiated at 254 nm (UVC). We initially irradiated with 1.4 J cm−2, since similar doses have previously been used in many publications mapping protein-binding sites on RNA in yeast and E. coli (e.g. see Bohnsack et al, 2012; Sy et al, 2018). The workflow is outlined in Fig 1A. To quantify protein recovery by mass spectrometry in the presence and absence of UV crosslinking, the analyses incorporated stable isotope labelling with amino acids in cell culture (SILAC) (Ong et al, 2002) combined with the MaxQuant software package (Cox & Mann, 2008). For this, yeast strains that were auxotrophic for lysine and arginine (lys9∆0, arg4∆0) were grown in the presence of lysine and arginine or [13C6]-lysine plus [13C6]-arginine. Isotope-labelled and isotope-unlabelled cells were mixed after irradiation but prior to cell lysis. In all experiments, label swaps between crosslinked and non-crosslinked samples were included to confirm that the labelling did not affect the outcome of the analyses (Fig EV1A–C). Figure 1. TRAPP and PAR-TRAPP reveal the yeast RBPome TRAPP and PAR-TRAPP workflows used to identify RNA-interacting proteins with SILAC MS-MS. See the main text for details. Scatter plot of Log2 SILAC ratios +UVC/−UVC (1,360 mJ cm−2) for Saccharomyces cerevisiae proteins, quantified with TRAPP. Proteins were subdivided based on the indicated GO term categories. Proteins belonging to GO terms “membrane” and “DNA binding” do not contain proteins mapping to GO terms “RNA metabolic process”, “RNA binding”, “ribonucleoprotein complex”. Black dots represent proteins that failed to pass statistical significance cut-off (P-value adjusted < 0.05). Scatter plot of Log2 SILAC ratios +UVA/−UVA for S. cerevisiae proteins, quantified with PAR-TRAPP. Proteins were subdivided based on the indicated GO term categories. Proteins belonging to GO terms “small molecule metabolism”, “membrane” and “DNA binding” do not contain proteins mapping to GO terms “RNA metabolic process”, “RNA binding”, “ribonucleoprotein complex”. Black dots represent proteins that failed to pass statistical significance cut-off (P-value adjusted < 0.05). See Methods and Protocols for calculation of significance. Venn diagram showing the overlap between proteins identified in TRAPP and PAR-TRAPP and proteins of intermediary metabolism annotated in the yeast metabolome database (YMDB). 5 most enriched GO terms amongst proteins identified only in TRAPP or exclusively in PAR-TRAPP. 6 most significantly enriched domains (lowest P-value) in PAR-TRAPP-identified proteins were selected if the same domain was enriched amongst TRAPP-identified proteins. Domain fold enrichment in the recovered proteins is plotted on the x-axis, while colour indicates log10 Benjamini–Hochberg adjusted P-value. Download figure Download PowerPoint Click here to expand this figure. Figure EV1. TRAPP and PAR-TRAPP techniques and reproducibility Pairwise Pearson correlation coefficients for protein Log2 +UV/−UV ratios obtained in S. cerevisiae with TRAPP and PAR-TRAPP experiments. Forward isotopic labelling and reverse isotopic labelling are indicated as “FWD” and “RV”, respectively. Data for Escherichia coli 1 forward and 2 reverse labelling TRAPP repeats were processed as in (A). The analysis of S. cerevisiae forward and reverse PAR-TRAPP experiments upon sorbic acid exposure performed as in (A). Effect of 4tU and UVA treatments on the growth of yeast cells. Exponentially growing yeast cells were treated for 2 h with 4-thiouracil at the indicated concentrations. The cultures were then irradiated with 350 nm UVA light in the eBox for 30 s delivering 5.8 J cm−2. The lag time of treated cultures was measured by monitoring samples growth curve with Tecan sunrise instrument. Samples: “4tU wash out +UVA”—growth delay of 4-thiouracil-treated UVA-irradiated cells, compared to UVA-exposed sample. 4tU was removed prior to irradiation; “4tU w/o wash out +UVA”—As sample 1, but 4tU persisted in the media while cells were irradiated; “4tU alone”—growth delay of cells treated with 4tU for 2 h as compared to untreated cells without irradiation. Frontal view on the eBox irradiation apparatus. The frontal door and the shutters are not present on the picture. Red arrows indicate rails for shutters, designed to prevent sample exposure to UV light, while the lamps are warming up for stable UVA output. The UVA transparent sample tray made of borosilicate glass is placed between the two UVA lamp banks. Download figure Download PowerPoint Briefly, irradiated cells were harvested by centrifugation, resuspended in buffer containing 2 M guanidine thiocyanate plus 50% phenol, and lysed by beating with zirconia beads. The lysate was cleared by centrifugation and adjusted to pH 4 by adding 3 M sodium acetate. The cleared lysate was incubated with silica beads in batch for 60 min. The beads were extensively washed in denaturing buffer: first in buffer containing 4 M guanidine thiocyanate, 1 M sodium acetate pH 4, then in low salt buffer with 80% ethanol. The ethanol wash is expected to reduce recovery of bound DNA (Avison, 2008). Nucleic acids and RNA-bound proteins were eluted from the column in Tris buffer. The eluate was treated with RNase A + T1 to degrade RNA, and proteins were resolved in a polyacrylamide gel in order to remove degraded RNA, followed by in-gel trypsin digestion and LC-MS/MS analysis. The PAR-TRAPP approach is similar to TRAPP, except that cells were metabolically labelled by addition of 4-thiouracil (4tU) to the culture (final concentration 0.5 mM) for 3 h prior to irradiation, in addition to SILAC labelling. 4tU is rapidly incorporated into RNA as 4-thiouridine, thus sensitizing RNA to UVA crosslinking. However, 4tU strongly absorbs UV irradiation and confers considerable UV resistance on the culture (Fig EV1D). Cells were therefore rapidly harvested by filtration and resuspended in medium lacking 4tU immediately prior to irradiation at ~350 nm (UVA). Previous analyses using labelling with 4tU and UVA irradiation in yeast and other systems have generally involved significant crosslinking times (typically 30 min in a Stratalinker with 360 nm UV at 4 mJ s−1 cm−2), raising concerns about changes in RNA–protein interactions during this extended period of irradiation. We therefore constructed a crosslinking device (Fig EV1E) that delivers a substantially increased UV dose, allowing irradiation times of only 38 s to be used to deliver the equivalent dose of 7.3 J cm−2. Subsequent treatment was as described above for TRAPP. In principle, silica binding can enrich both RNA- and DNA-bound proteins, although UV crosslinking to dsDNA is expected to be inefficient and bound DNA should be reduced during ethanol washing of the silica beads (Angelov et al, 1988; Avison, 2008). To compare recovery of proteins bound to RNA versus DNA, samples recovered following initial silica binding and elution were treated with either DNase I, RNase A + T1 or cyanase (to degrade both RNA and DNA) and then rebound to silica, as outlined in Fig EV2A. Following washing and elution from the silica column, proteins were separated by SDS–polyacrylamide gel electrophoresis and visualized by silver staining (Fig EV2B and C). Nucleic acids were separated by agarose gel electrophoresis and visualized by SYBR safe staining to confirm degradation. Degradation of DNA had little effect on protein recovery, whereas this was substantially reduced by RNase treatment (Fig EV2D). The predominant proteins correspond to the added RNases. Cyanase-treated samples showed a low level of protein recovery (Fig EV2C), presumably due to residual nucleic acids surviving the treatment (Fig EV2D). We conclude that the TRAPP protocol predominately recovers RNA-bound proteins. Click here to expand this figure. Figure EV2. TRAPP protocol predominately recovers RNA-bound proteins The experimental set-up indicating the stages when samples are collected. Coloured circles designate treatment with the indicated enzyme. Samples are purified following the TRAPP protocol as described in Materials and Methods. After RNase A and RNase T1 treatment to degrade the co-purifying RNA, sample was resolved on polyacrylamide gel and silver staining was performed. TRAPP-purified samples were treated with the indicated enzymes and loaded onto silica once again. After elution, nucleic acids were resolved with agarose gel electrophoresis (see Fig EV2D), while the remainder of the sample was treated with the indicated enzyme followed by polyacrylamide gel electrophoresis and silver staining. Same as in (C), but the samples were collected before the second nuclease treatment and were then resolved on a SYBR Safe stained agarose gel. * denotes residual nucleic acid species in the cyanase-treated sample. Download figure Download PowerPoint Figure 2. The effect of UVC dose in Saccharomyces cerevisiae on the proteins identified in TRAPP Venn diagram showing the overlap between proteins identified in TRAPP using the indicated UVC irradiation regime. Scatter plot of Log2 SILAC ratios +UVC/−UVC (for the indicated UV doses) for S. cerevisiae proteins, quantified with TRAPP. Proteins were subdivided based on the indicated GO term categories. Proteins, belonging to GO terms “membrane” and “small molecule metabolism” do not contain proteins mapping to GO terms “RNA metabolic process”, “RNA binding”, “ribonucleoprotein complex”. Black dots represent proteins that failed to pass statistical significance cut-off (P-value adjusted < 0.05). Proteins, identified in TRAPP and PAR-TRAPP were subdivided into 2 categories: “RNA biology” proteins (GO terms “RNA metabolic process”, “RNA binding”, “ribonucleoprotein complex”) (orange bars); Proteins, not classified with either of the 3 GO terms above (blue bars). Numbers of proteins in each category are plotted per experiment. Proteins quantified in both TRAPP and PAR-TRAPP were filtered to remove proteins annotated with GO terms “RNA metabolic process”, “RNA binding”, “ribonucleoprotein complex” (blue bars in Fig 2C). The remaining proteins were split into 10 bins by abundance (see Materials and Methods). For each bin, the ratio between enriched to detected proteins was calculated as well as median protein abundance as reported by PaxDb. Download figure Download PowerPoint In the absence of UV irradiation (-UVC), a low level of protein recovery was also visible following RNA binding to silica (Fig EV2C). These proteins apparently bind RNA in the absence of crosslinking, even following denaturation, likely due to the mixed mode of RNA binding, involving both hydrophobic interactions with nucleotide bases and charge interactions with the phosphate backbone. These will be underestimated in SILAC quantitation of TRAPP analyses, potentially generating a small number of false-negative results. They can, however, be identified in iTRAPP (see below). We noted that a small number of proteins showed reduced recovery following UV exposure. We attribute this to crosslinking with other macromolecules, e.g. lipids, that are not retained by silica binding. MaxQuant quantitation initially failed to return a value for many peptides in TRAPP MS/MS data, predominately due to the absence of a detectable peptide in the −UV samples for the SILAC pairs (Fig EV3A–F). These “missing” peptides were strongly enriched for known RNA binding proteins, presumably because low abundance proteins that are efficiently purified are detected following crosslinking but not in the negative control. We addressed this problem by imputation of the missing values using the imputeLCMD R package (see Materials and Methods and Fig EV3G–O) (Lazar et al, 2016). Click here to expand this figure. Figure EV3. Quantification of TRAPP and PAR-TRAPP data The percentage of peptides with reported intensity in +UV sample, but not in −UV sample (superenriched peptides) by MaxQuant in Saccharomyces cerevisiae TRAPP (at 1,360 mJ cm−2) SILAC quantification experiments without (black bars) or with (grey bars) “requantify” option enabled. 3 biological repeats had light-labelled cells UV irradiated (1F, 2F,3F), while three other repeats (1R, 2R, 3R) had heavy-labelled cells UV irradiated. The data of S. cerevisiae PAR-TRAPP experiments were analysed the same way as in (A). The data of E. coli TRAPP experiments were analysed the same way as in (A), except the 2 biological repeats, which had light-labelled cells UV irradiated, were labelled 1R and 2R. The percentage of peptides with reported intensity in −UV sample, but not in +UV sample (superdepleted peptides) by MaxQuant in S. cerevisiae TRAPP (at 1,360 mJ cm−2) without (dotted) or with (chequered) “requantify” option enabled. Sample labelling as in (A). The data of S. cerevisiae PAR-TRAPP experiments were analysed the same way as in (D). The data of E. coli TRAPP (at 1,360 mJ cm−2) experiments were analysed the same way as in (D), sample labelling was as in panel (C). Box plot of Log10 peptide intensity of −UV peptides from S. cerevisiae TRAPP (at 1,360 mJ cm−2) (blue) samples (labelling as in (A)), plotted together with Log10 peptide intensity values imputed by imputeLCMD R package for −UV samples (orange). Box represents values between 25th and 75th percentiles, while whiskers represent 10th and 90th percentiles. All other data are represented as points below or above 10th or 90th percentiles, respectively. Line inside the box shows median value. Histogram of peptide intensity frequency obtained from −UV sample (1F), plotted for intensities from 0 to 5 × 105 units. Colour labelling is as in (G). Same as panel (H), performed for sample 1R which had reversed SILAC labelling, compared to the sample analysed in panel (H). Box plot of Log10 peptide intensity of −UV peptides from S. cerevisiae PAR-TRAPP (blue) samples (labelling as in (B)), plotted together with Log10 peptide intensity values imputed by imputeLCMD R package for −UV samples (orange). Histogram of peptide intensity frequency obtained from −UV sample (1F), plotted for intensities from 0 to 5 × 105 units. Colour labelling is as in (J). Same analysis as panel (K), performed for sample 1R which had reversed SILAC labelling, compared to the sample analysed in panel (K). Box plot of Log10 peptide intensity of −UV peptides from E. coli TRAPP (at 1,360 mJ cm−2) (blue) samples (labelling as in (C)), plotted together with Log10 peptide intensity values imputed by imputeLCMD R package for −UV samples (orange). Histogram of peptide intensity frequency obtained from −UV sample (1F), plotted for intensities from 0 to 5 × 105 units. Colour labelling is as in (M). Same analysis as panel (N), performed for sample 1R which had reversed SILAC labelling, compared to the sample analysed in panel (N). Download figure Download PowerPoint TRAPP with 1.4 J cm−2 UVC in Saccharomyces cerevisiae identified 1,434 significantly enriched proteins, of which 1,360 were enriched more than twofold (Fig EV4A, Dataset EV1). Proteins annotated with the GO term “translation” had the highest average fold enrichment, which is expected in the total RNA-interacting proteome (Fig 1B). It was previously reported that proteins involved in intermediary metabolism can interact with RNA (e.g. see Beckmann et al, 2015; Queiroz et al, 2019; Trendel et al, 2019). Consistent with this, we observed significant enrichment for proteins annotated with GO term “small molecule metabolic process” (Fig 1B). Furthermore, 377 proteins enriched in TRAPP were annotated in the Yeast Metabolome Database (YMDB) (Ramirez-Gaona et al, 2017) to be enzymes or transporters associated with pathways of intermediary metabolism (Fig 1D). In particular, the majority of enzymes involved in glycolysis and/or gluconeogenesis were identified in TRAPP (Fig EV5) with average enrichment of more than fourfold. In addition, most of the structural components of the proteasome and many membrane-associated proteins were identified as RNA-binders by TRAPP. Click here to expand this figure. Figure EV4. Volcano plots for protein enrichment in TRAPP with different UV exposure A–G. Volcano plot showing Log2 UV fold enrichment plotted against – Log10 per protein for the following experiments: (A) Saccharomyces cerevisiae TRAPP at 1,360 mJ cm−2; (B) S. cerevisiae PAR-TRAPP at 7.2 J cm−2; (C) S. cerevisiae TRAPP at 400 mJ cm−2; (D) S. cerevisiae TRAPP at 800 mJ cm−2; (E) E. coli TRAPP at 1,360 mJ cm−2; (F) E. coli TRAPP at 800 mJ cm−2; (G) E. coli TRAPP at 400 mJ cm−2. Download figure Download PowerPoint Click here to expand this figure. Figure EV5. Glycolytic enzymes identified in TRAPPGlycolysis pathway in yeast Saccharomyces cerevisiae, indicating intermediate metabolites and participating enzymes. Proteins identified as enriched by TRAPP (1.4 J cm−2) and PAR-TRAPP are shown with grey and white stars, respectively. Download figure Download PowerPoint Applying PAR-TRAPP identified twofold fewer significantly enriched proteins than found with TRAPP (Fig EV4B, Dataset EV2). However, PAR-TRAPP recovered a notably higher proportion of characterized RNA binding proteins relative to proteins with less obvious connection to RNA. Only 116 (15% of total) proteins implicated in intermediary metabolism by the YMDB were identified amongst the PAR-TRAPP hits, relative to 377 (26% of total) in TRAPP (Fig 1D Dataset EV2). Furthermore, proteins annotated with the GO terms “glycolysis”, “membrane part” and “proteasome” were substantially reduced relative to TRAPP (Fig 1C). We performed GO term analyses on proteins that were exclusively found enriched in TRAPP or PAR-TRAPP (Fig 1D and E). The most enriched GO terms for TRAPP-specific proteins were related to metabolic processes and the proteasome, whereas PAR-TRAPP-specific proteins featured rRNA processing, mRNA processing and RNA splicing. Furthermore, while both TRAPP and PAR-TRAPP demonstrated over-representation for known RNA-interacting domains within the enriched proteins (Dataset EV3), in PAR-TRAPP this trend was more pronounced both in terms of higher fold enrichment and enrichment P-values (Fig 1F). In these initial analyses, PAR-TRAPP clearly outperformed TRAPP. However, it seemed possible that the dose of 1.4 J cm−2 UVC, previously optimized for recovery of RNAs bound to specific proteins, might not be optimal for recovery of the RNA-bound proteome. We therefore performed TRAPP using lower doses of 800 and 400 mJ cm−2 UVC (Fig EV4C and D). As expected, reduced UVC exposure was associated with decreased numbers of statistically significant UV enriched proteins, with 482 core proteins enriched in TRAPP under all UVC exposure regimes (Figs 2A and EV4A, C and D). Reduced recovery was seen both for proteins annotated with selected “RNA biology” GO terms as well as amongst other proteins, such as metabolic enzymes and proteasome cofactors (Fig 2B and C). However, the latter proteins demonstrated higher attrition rate with reduction of UVC, presumably due to lower UV fold enrichment at the highest dose for these proteins in comparison with RNA biology” GO terms TRAPP hits. At the same time, amongst annotated, RNA-related proteins, there was relative enrichment for abundant, translation-related proteins (translation factors, ribosomal proteins), which were readily detected at all 3 UVC doses tested. UVA crosslinking in PAR-TRAPP recovered similar number of annotated, RNA-related proteins as TRAPP with the highest dose of UVC, while recovery of other proteins was similar to TRAPP with the lowest exposure to UVC (Fig 2C). We assessed the correlation between cellular abundance and the likelihood of being reported as RNA-interacting protein by TRAPP and PAR-TRAPP. As TRAPP shows high enrichment for proteins involved in translation, “RNA biology” GO terms proteins were excluded from this analysis. Strikingly, this analysis revealed a clear trend for abundant proteins to be scored as enriched in TRAPP with 60–90% of proteins within the two most abundant bins were scored as enriched in +UVC, whereas no such correlation was observed in PAR-TRAPP data (Fig 2D). Only confidently identified proteins were included in each analysis, so this is unlikely to reflect a detection bias. Since the trend is not observed in PAR-TRAPP, it also see" @default.
• W2894897551 created "2018-10-12" @default.
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• W2894897551 date "2019-04-01" @default.
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• W2894897551 title "Defining the<scp>RNA</scp>interactome by total<scp>RNA</scp>‐associated protein purification" @default.
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