S. cerevisiae PUF protein, Puf5p, by ultraviolet-crosslinking-affinity purification and high-throughput sequencing (HITS-CLIP). The binding sites recognized by Puf5p are diverse, with variable spacer lengths between two specific sequences. Each length of site correlates with a distinct biological function. Crystal structures of Puf5p–RNA complexes reveal that the protein scaffold presents an exceptionally flat and extended interaction surface relative to other PUF proteins. In complexes with RNAs of different lengths, the protein is unchanged. A single PUF protein repeat is sufficient to induce broadening of specificity. Changes in protein architecture, such as alterations in curvature, may lead to evolution of mRNA regulatory networks.Proteins bind and control mRNAs, directing their localization, translation and stability. Members of the PUF family of RNA-binding proteins control multiple mRNAs in a single cell, and play key roles in development, stem cell maintenance and memory formation. Here we identified the mRNA targets of a  Members of the PUF family of RNA-binding proteins bind multiple mRNAs in vivo. Here the authors show that the S. cerevisiae Puf5p binds targets of varying lengths that correlate with biological functions. The RNA-binding sites adopt different structures to adapt to a fixed protein scaffold. RNA-binding proteins control an messenger RNA (mRNA)'s life, including its translation, movement and destruction. These events underlie diverse biological processes, ranging from early development to memory formation. Regulatory proteins bind simultaneously to short RNA sequences, typically in 3′-untranslated regions (3′UTRs), and to protein effectors that determine the RNA's fate. The RNA-binding specificities of the proteins determine which mRNAs are controlled, while effectors determine the outcomes.RNA regulatory networks, in which a single RNA-binding protein controls multiple mRNAs, are widespreadCaenorhabditis elegans, Drosophila and humans control an overlapping battery of mRNAs with established roles in stem cells8Saccharomyces cerevisiae Puf5p binds ∼200 mRNAs that contain 10-nt-long binding elementsPUF proteins are exemplary mRNA regulators4in vivo. These targets possess unexpected diversity of binding element lengths, with the same RNA sequence features at the two ends but varying numbers of nucleotides in between. The lengths of sites correlate with the biological functions of the targets. The crystal structures of Puf5p–RNA complexes revealed that the RNAs assume altered conformations to accommodate a fixed protein architecture. The plasticity in binding element length is driven by the flattened curvature of the PUF protein scaffold. The findings suggest ways in which alterations in protein curvature result in new specificities and enable the evolution of new RNA networks.In this work, we used ultraviolet-crosslinking and high-throughput sequencing to define ∼1,000 high-confidence RNA targets of Puf5p in vivo ultraviolet-crosslinking and high-throughput sequencing  tag. The tagged gene was integrated by homologous recombination into the PUF5 locus. Cells were irradiated during mid-log phase  mapped to unique locations in the plicates . The funplicates . A totalplicates . Of thesplicates . Of the plicates . The oveplicates . The 1,0in vivo17SMX2 and HO mRNAs19We developed stringent criteria to select a set of 1,043 high-confidence targets that we used to identify RNA sequence elements bound by Puf5p. We first defined significant peaks as an enrichment of independent reads in a specific genic region <0.01)We identified five classes of Puf5p-binding elements ranging from 8 to 12 nt, each comprising a 5′-UGUA tetranucleotide sequence and a 3′-UA with a variable length spacer region in between . We perfS. cerevisiae Puf4pC. elegans FBF-2 ; 9-nt sites for ribosome biogenesis ; and 10-nt sites for regulation of gene expression , 11-nt sites for translation  .The majority of the sites bound by Puf5p consist of individual elements, in which only a single site of unambiguous length is present in the CLIP peak . Gene on 3.6e−3) . A totalS. cerevisiae lineage (see the Discussion section).The 8-nt Puf5p elements lie in a subset of mRNAs that also were bound to Puf3p in PAR-CLIP experimentsSMX2 , MFA2 , AAT2  and AMN1  mRNAs . Each RNA corresponded to a high-confidence 3′UTR-binding element in HITS-CLIP . The protein scaffold comprises eight α-helical repeats flanked by a short N-terminal sequence and a C-terminal helix (R8′) . The C-tnd Puf4p . For exand Puf4p .Since the curvature of the Puf5p scaffold is fixed, RNAs of different lengths adopt different conformations, as described below. Recognition of the 5′-UGUA and 3′-UA elements by repeats 5–8 and 1–2, respectively, are identical in all structures. Differences in RNA conformation and recognition are found opposite the central repeats 3 and 4.SMX2 RNA site by recognizing all but the central fifth base.  contact bases A5 and C6  is a proxy for the affinity of the interactionTo examine the evolution of the broad specificity of Puf5p, we probed the RNA-binding preferences of Puf5p proteins from representative species across phylum Ascomycota. This group includes the budding yeasts, filamentous fungi and fission yeasts . We usedes pombe . These pS. pombe Puf3. This protein bound a broad range of site lengths, unlike its orthologues in other species that showed preference for 8-nt sites.Puf5p proteins across Ascomycota exhibited broad binding specificities. Puf5 proteins bound similarly to sites of 9, 10, 11 and 12 nt . The morS. pombe Puf3 appears to have arisen exclusively in the fission yeast lineage, which enabled us to probe how that broadening arose during evolution. We reasoned that the broadening was not due to the identity of the RNA-interacting TRMs, as the residues are identical among all the Puf3p orthologues . To identify the key regions of the proteins that confer specificity, we prepared chimeras in which segments of the S. cerevisiae and S. pombe proteins were exchanged .Two PUF proteins that bind the same site could do so sequentially, competitively or cooperatively. Genetic studies demonstrate that Puf4p and Puf5p redundantly control the decay rate of common targetsWhile 71% of Puf5p targets possess discernible binding elements, 29% do not. RNAs without binding elements may associate with Puf5p indirectly, perhaps through a protein to which it and Puf5p are bound. Crosslinking to RNAs without sites could also be driven by their high concentrations in specific subcellular compartments (such as P-bodies), in which proteins and RNAs are present at high concentrations, and low complexity, Q/N-rich regions present in Puf3p, Puf4p,and Puf5p proteins that could facilitate aggregationRNAs of different lengths adopt a broad range of conformations when bound to Puf5p. The flatter, extended scaffold of Puf5p, combined with its specificity for 5′ and 3′ sequences, imposes the requirement for these RNA conformational variations and permits recognition of 8–12-nt length RNAs. The elegance of this arrangement is that very similar sets of atomic contacts between amino acids and RNA bases are maintained in the different complexes, despite the range of RNA lengths they possess. For example, 18 of the 21 edge-on contacts made between Puf3p and its RNA target are also made in Puf5p bound to a 10-nt length site. In an analogous manner, β-catenin maintains a fixed scaffold to recognize peptides from different ligands (reviewed in ref. S. cerevisiae) or accommodates 8, 9 or 10-nt sites (S. pombe). S. cerevisiae repeat 6, which induces narrow specificity, contains additional residues relative to the same region of the S. pombe protein, which, although not near the RNA-binding residues, may alter the structure with corresponding effects on specificity  already regulated batteries of RNAs with related functions and conserved lengths of sites. Recruitment of Puf5p to these same targets, enabled by its flatter curvature, provided new regulatory inputs and/or redundancy into that same circuit. For example, Puf5p binds regulatory kinasesS. cerevisiae harbouring an integrated TAP tag sequence at the C terminus of the endogenous puf5 locus (GE YSC1178-202231131) per biological replicate. Cells were pelleted, washed with water and distributed into Petri dishes. The cells were ultraviolet irradiated with 1,000-mJ wavelength 254 light. Pelleted cells were snap frozen in liquid nitrogen and then ground with a liquid nitrogen cooled mortar and pestle. The ground material was thawed in ∼10 ml CBB (25 mM Tris (pH 7.5), 150 mM NaCl, 1 mM magnesium acetate, 1 mM imidazole, 2 mM CaCl2, 0.1% IGEPAL, 10 mM β-mercaptoethanol) at 25 °C. A measure of 30 μl of RQ1 DNASE  and 10 μl 1:10,000 dilution of RNAse A (Promega A7973) were added and incubated at 37 °C for 10 min. The lysate was cleared by centrifugation then incubated with 400 μl pre-washed calmodulin Sepharose beads (GE 17-0529-01) rotating at 4 °C for 1 h. Beads were washed with 10 ml CBB and then incubated in 3 ml CEB (10 mM Tris-HCl (pH 8.0), 150 mM NaCl, 1 mM magnesium acetate, 1 mM imidazole, 2 mM EGTA, 0.1% IGEPAL, 10 mM β-mercaptoethanol) for 45 min rotating at 4 °C, followed by washing with 2 ml CEB. The supernatant was incubated with 400 μl pre-washed IgG beads (Life Techonologies 11202D) rotating at 4 °C for 1 h. Following incubation, beads were washed 1 × with PNK (50 mM Tris (pH 7.5), 10 mM MgCl2, 0.5% IGEPAL) buffer, 3 × with high-salt buffer (15 mM Tris (pH 7.5), 5 mM EDTA, 2.5 mM EGTA, 1% Triton X-100, 1% Na-DOC, 0.1% SDS, 1 M NaCl) and then 1 × with PNK buffer.HITS-CLIP was performed on 8 l of 32-γ-ATP, 50 units T4 PNK (Promega M4101) in 1 × PNK buffer at 37 °C for 10 min shaking every 5 min for 15 s. Ten microlitres of 10 mM ATP was added to the reaction and incubated for an additional 5 min. The reaction was quenched by washing 2 × with high-salt buffer and then 2 × with 1 × PNK.Beads were incubated in 1 × PNK pH 6.5 buffer, 1 unit T4 PNK (NEB M0201s), 100 units RNasin (Promega N2511) and 5 units alkaline phosphatase (Promgea M1821 ) at 37 °C for 20 min shaking every 3 min for 15 s followed by washing 2 × with 1 × PNK+EGTA buffer (50 mM Tris (pH 7.5), 20 mM EGTA, 0.5% IGEPAL) and 2 × with 1X PNK buffer. Adaptor ligation was performed in 1 × T4 RNA ligase buffer (NEB), T4 RNA ligase truncated (NEB M0242L) RNasin, 1 μM pre-adenylated 3′-adaptor (5′- TGGAATTCTCGGGTGCCAAGG -3′), 10% PEG400  overnight at 16 °C shaking every minute for 15 s. RNAs were labelled with 5 μl P−1 Proteinase K (Thermo Scientific E00491) in 1 × PK buffer at 37 °C for 20 min while shaking. A measure of 200 μl of 1 × PK 7 M urea was added and then incubated at 37 °C for 20 min. RNA was phenol chloroform extracted and precipitated with ethanol:isopropanol (1:1), NaOAc and glycoblue (Life Technologies AM9516) overnight at −20 °C. The pellets were washed and resuspened in 6.9 μl water.The beads were resupsened in 30 μl of 1 × LDS sample buffer (Life Technologies NP0008) including 1 μl sample reducing agent (Life Technologies NP0004). The reaction was incubated at 70 °C for 10 min and loaded in one lane of a 4–12% NuPAGE Novex Bis-Tris (Life Technologies NP0321BOX) gel. The gel was run at 150 V until the dye front ran off the gel. The complexes were then transferred to a nitrocellulose membrane (Novex LC2001) in a XCell II Blot module (Novex EI0001) at 30 V for 1 h at 4 °C. The membrane was put on a phosphor screen to visualize the Puf5p–RNA complexes. Complexes were cut out of the membrane. Nitrocellulose pieces were then incubated with 200 μl of 4 mg ml−1) T4 RNA ligase, 1 μl  5′-adaptor (5′- GUUCAGAGUUCUACAGUCCGACGAUCNNNNN -3′) and incubated at 16 °C for 2 h. The reaction was quenched by phenol chloroform extraction then precipitated as above.5′-RNA adaptor ligation was performed in 1 × T4 RNA ligase buffer, bovine serum albumin 1 μl (1 mg mlThe pellets were washed and resuspended in 10 μl water. dNTPs (0.5 mM) and 10 uM RT primer (5′- GCCTTGGCACCCGAGAATTCCA -3′) were combined and heated to 65 °C for 5 min then cooled on ice. Reverse transcriptase buffer (1 × ), 10 mM dithiothreitol (DTT), 20 units RNasin and 200 units SuperScript II (Life Techonlogies 18064-022) were combined and incubated at 50 °C for 45 min, 55 °C for 15 min and then 90 °C for 5 min. Reverse transcriptase reactions were PCR amplified by adding 10 μl of the reaction to 15 μl GoGreen Taq (Promega M7123) and 10 μM of each primer . Thirty PCR cycles  were used to amplify the libraries. PCR reactions were purified by 1% agarose TBE gel. Smears corresponding to 150–300 bp were gel purified and ethanol precipitated as above. Libraries were bar-coded (5′- CAAGCAGAAGACGGCATACGAGATXXXXXXGTGACTGGAGTTCCTTGGCACCCGAGAATTCCA -3′) using the same PCR as above for 10 cycles except replacing the reverse primer with bar-coded primer and submitted to the UW-Madison sequencing facility for sequencing on one highly multiplexed Illumnia HighSeq 2000 lane.A measure of 50 μl of IgG beads were removed from CLIP samples and then incubated in 30 μl LDS sample buffer (Life Technologies NP0007). The whole reaction was run on a Novex 6% TBE gel then transferred to PDVF membrane (Millipore IPVH00010). The membrane was probed with TAP Tag Polyclonal Antibody  primary antibody followed by goat anti-mouse secondary antibody .FASTQ files were uploaded to the Galaxy serverS. cerevisiae genome using Bowtie2  and multiple test corrected using Holm–BonferroniThe biological replicates were combined into one list based on the following: (1) each peak had a summit within 10 bases in both replicates; (2) each peak contained a gapped read in both replicates; and (3) each peak had a height >10 reads (third quartile) in both replicates. Functional enrichment was performed using GO analysis. Gene lists were uploaded to YeastMine where the 6-SUMO tagEscherichia coli cells BL21 Star (DE3) carrying the Puf5p plasmid were grown in Terrific Broth media to OD600=∼0.8 and then protein expression was induced with 0.4 mM isopropylthiogalactoside for 20 h at 18 °C. The cell pellet was resuspended in lysis buffer containing 20 mM Tris, pH 8.0; 0.5 M NaCl; 20 mM imidazole; 5% (v/v) glycerol and 0.1% (v/v) β-mercaptoethanol and sonicated on ice. The lysate was cleared by centrifugation and loaded onto a Ni-chelating gravity column (Thermo Scientific). His-SUMO-tagged Puf5p was eluted with a buffer containing 20 mM Tris, pH 8.0; 50 mM NaCl; 0.2 M imidazole and 1 mM DTT. Ulp1 protease was added to remove the His6-SUMO tag, and the protein solution was loaded onto a Hi-Trap heparin column  and eluted with a gradient from 0 to 1 M NaCl in buffer containing 20 mM Tris, pH 8.0, 1 mM DTT. The fractions containing Puf5p were pooled and concentrated by Amicon filters and loaded onto a Superdex 200 16/60 column equilibrated in 20 mM HEPES, pH 7.4; 0.15 M NaCl and 2 mM DTT. The Puf5p peak fractions were pooled and concentrated in column buffer for crystallization and RNA-binding assays.The RNA-binding domain of yeast Puf5p (residues 201–600) was subcloned into the pSMX vector with an N-terminal His−1) was mixed with each of the four different RNAs at a protein:RNA molar ratio of 1:1.2 and incubated on ice for 1 h. Crystals were obtained at 20 °C by hanging drop vapour diffusion, mixing 1 μl Puf5p–RNA complex with 1 μl reservoir solution of 15–20% (w/v) PEG 3350 and 0.1 M citrate Bis-Tris propane (CBTP), pH 7.6. Microseeding was performed to grow larger single crystals. Crystals were cryo-protected in crystallization solution supplemented with 15% (v/v) glycerol and flash frozen in liquid nitrogen. For phasing, a Puf5p:SMX RNA complex crystal was soaked in 17.5% (w/v) PEG 3350, 0.5 M KI, 0.1 M CBTP and 15% (v/v) glycerol for 5 min and then flash frozen.RNAs were purchased from Thermo Scientific. Puf5p  was determined by combining molecular replacement (MR) with iodide single-wavelength anomalous diffraction (SAD)) phasing. The Phenix software suite was used throughout the process of structure determinationRfree=44%. The model was further improved to Rfree=38% using the EMBL Hamburg Auto-Rickshaw web serverRfree=28%  following the manufacturer's instructions. Serially diluted Puf5p was mixed with 100 pM labelled RNA in buffer containing 10 mM HEPES, pH 7.4; 50 mM NaCl; 1 mM EDTA; 0.1 mg ml−1 bovine serum albumin; 0.01% (v/v) Tween 20 and 0.1 mg ml−1 yeast tRNA. After overnight, incubation at 4 °C, 4-μl loading dye (15% v/v Ficoll 400 and 0.01% bromophenol blue) was added to each 20-μl reaction before gel loading. Novex TBE gels  were run at 100 V at 4 °C for 30 min to resolve the samples. The gels were dried and exposed to storage phosphor screens. The screens were scanned using a Molecular Dynamics Typhoon phosphorimaging system . The band intensities were analysed using the ImageQuant. K values were calculated using GraphPad Prism by fitting the data assuming one-site specific binding and a Hill coefficient of 1. ∼93% of Puf5p was active, as determined using the method described in referenceKd values were not adjusted.RNA oligonucleotides were radiolabelled using S. cerevisiae strain YBZ-1 -HIS3, URA3::(lexAop)-lacZ and LexA-MS2 MS2 coat (N55K)). Strains were lithium acetate transformed with appropriate combinations of plasmids and plated on synthetic dextrose media lacking uracil and leucine. Single colonies were selected and allowed to grow to stationary phase, then diluted and grown for about 4 h. OD660 for each culture was measured, then 50 μl of culture was added to 50 μl of Beta-Glo (Promgea E4720) and incubated for 1 h in the dark. Luminescence was measured by microplate reader (BioTech Synergy 4). Raw luminescence was normalized to OD660, and each biological replicate (n=3) was then averaged and s.d. was calculated.Each orthologous PUF RNA-binding domain was cloned into activation domain–protein fusion plasmid, pGADT7 ref. . OligonuAccession codes:The Illumina FASTQ sequence files have been deposited in the Sequence Read Archive (accession numbers SRR2085177 and SRR2084791). The atomic coordinates and structure factors for the crystal structures of Puf5p in complex with SMX2 (PDB IDs: 5BYM and 5BZV), MFA2 (PDB ID: 5BZ1), AAT2 (PDB ID: 5BZU) and AMN1 (PDB ID: 5BZ5) RNAs have been deposited in the Research Collaboratory for Structural Bioinformatics Protein Data Bank.How to cite this article: Wilinski, D. et al. RNA regulatory networks diversified through curvature of the PUF protein scaffold. Nat. Commun. 6:8213 doi: 10.1038/ncomms9213 (2015).Supplementary Figures 1-9 and Supplementary Tables 1-3List of Puf5p target RNAs. Columns indicate properties of each peak or gene information contained in the header. Each row represents a peak.Cytoscape network file.


The most popular RNA library used for RNA sequencing is the poly(A) captured RNA library. This library captures RNA based on the presence of poly(A) tails at the 3′ end. Another type of RNA library for RNA sequencing is the total RNA library which differs from the poly(A) library by capture method and price. The total RNA library costs more and its capture of RNA is not dependent on the presence of poly(A) tails. In practice, only ribosomal RNAs and small RNAs are washed out in the total RNA library preparation. To evaluate the ability of detecting RNA for both RNA libraries we designed a study using RNA sequencing data of the same two breast cancer cell lines from both RNA libraries. We found that the RNA expression values captured by both RNA libraries were highly correlated. However, the number of RNAs captured was significantly higher for the total RNA library. Furthermore, we identify several subsets of protein coding RNAs that were not captured efficiently by the poly(A) library. One of the most noticeable is the histone-encode genes, which lack the poly(A) tail. With the advancement of high throughput sequencing technology, advanced data mining techniques have been developed for high throughput DNA sequencing data , 2. SimiLong noncoding RNA (lncRNA), on the other hand, was traditionally believed to be nonfunctional. However, many recent studies have shown evidence for the functionality of lncRNA , 8, suchWhile it is possible to study lncRNAs using traditional microarrays, RNAseq has been proven to be the superior technology for this purpose due to its greater sensitivity and the ability to detect novel lncRNAs , 20. TheTotal RNA sequencing theoretically should detect more lncRNAs due to its RNA selection independent of the poly(A) tail. However, total RNAseq costs more than mRNA sequencing  and the question of how many more lncRNAs does total RNA sequencing capture compared to mRNA sequencing has not been answered. Moreover, whether the mRNAs captured in total RNA sequencing are comparable to mRNA sequencing also remains unknown. To answer these questions, we designed the following study. We hypothesized that total RNA sequencing generates more relevant data than mRNA sequencing for the purpose of lncRNA research. Total RNA and mRNA libraries of two breast cancer cell line samples were built and sequenced. We analyzed the sequencing data and compared their usability for lncRNA and mRNA research.μg total RNA following the manufacturer's protocol. After ribosomal RNA (rRNA) depletion, samples were then purified using the Agencourt RNAClean XP Kit (Beckman Coulter) according to the Epicentre protocol specifications. After purification, samples were eluted in 11 μL RNase-free water. Next, 1 μL ribosomal depleted samples were run on the Agilent RNA 6000 Pico Chip to confirm rRNA removal. After confirmation of rRNA removal, 8.5 μL rRNA-depleted sample was input into the Illumina TruSeq Stranded RNA Sample Preparation kit (Illumina) for library preparation. The libraries were sequenced on Illumina High HiSeq 2500 with paired-end 100 base pair long reads. Raw RNAseq sequencing data generated from the poly(A) library of the same two cell lines were downloaded from the Gene Expression Omnibus (GEO) (GSM1172877: 19.8 million reads and GSM1172855: 15.3 million reads) for comparative purpose. The poly(A) libraries were prepared using Illumina TruSeq RNA Sample Preparation kit. Poly(A) RNA was purified with oligo dT magnetic beads, and the poly(A) RNA was fragmented with divalent cations followed by reverse transcription into cDNA and ligation of Illumina paired-end oligo adapters to the cDNA fragments. More detail of poly(A) library construction can be found at GEO website.Total RNAseq on two breast cancer cell lines HS578T and BT549 was performed by the Vanderbilt Technologies for Advanced Genomics (VANTAGE) core. Total RNA was isolated with the Aurum Total RNA Mini Kit. All samples were quantified on the QuBit RNA assay. RNA quality was checked using Agilent Bioanalyzer. RNA integrity number (RIN) for both samples was 10. RNAseq data was obtained by first using the Ribo-Zero Magnetic Gold Kit (human/mouse/rat) (Epicentre) to perform ribosomal reduction on 1 The raw data quality was examined using QC3 . AlignmeEven though the RNAseq data were generated from the same cell lines, there could be potential heterogeneity and batch effect because the cell lines were cultured at two different labs and sequenced at two different facilities. To test if there is potential heterogeneity and batch effect, we conducted a cluster analysis using Heatmap3 . UnsuperThe sequencing data went through rigorous quality control. To account for variation in number of reads sequenced within the 4 samples, read counts were adjusted by normalizing the total read count of each sample. In terms of proportion of reads mapped to lncRNA, total RNA library samples (3.62% and 3.23%) had a higher proportion than poly(A) library samples (0.85% and 1.02%). For protein coding RNA, poly(A) library samples (96.34% and 95.38%) mapped a higher proportion of reads than total RNA samples (92.47% and 93.45%). For other species of RNAs, poly(A) library samples (2.81% and 3.59%) and total RNA library samples (3.91% and 3.32%) had similar proportion of reads aligned.http://dx.doi.org/10.1155/2015/862130). All three types of RNAs were detected by both poly(A) and total RNA library building methods. To compare whether RNA expressions are comparable between the two RNA library building methods, we drew a scatter plot and computed their Pearson's correlation coefficients . These results are consistent with previous findings [The distributions of read normalized read counts for protein coding RNA, lncRNA, and other RNAs can be seen in Figure S1 . Furthermore, we compared the number of genes that are differentially expressed between the two libraries' construction methods and found there were much higher expressed RNAs (log2 fold change > 2) for total RNA library samples than poly(A) library samples  tail at their 3′ ends . For exaIn this study, we examined the difference between the RNAs captured through poly(A) and total RNA libraries. Our study was also designed with several limitations. First, we were only able to collect two samples with sequencing data from both RNA libraries. The small sample size might limit our ability to identify true signals. Also, the sample type is limited to breast cancer cell lines. Other tissue types might behave differently.Using sequencing data from two breast cancer cell lines captured using both libraries, we found that, in terms of expression level, both libraries were highly correlated and the correlation was the highest for protein coding RNAs. This suggests that both methods of RNA library construction are capable of generating consistent data for studying protein coding RNAs. For the three types of RNA we defined: protein coding RNA, lncRNA, and other RNAs; at all gene detection thresholds, total RNA library samples consistently identified more RNAs than poly(A) library samples which suggests that the total RNA library is capable of detecting additional RNA not detected by the poly(A) library. Through gene set enrichment analysis we were able to identify that histone-encoding genes were not captured efficiently by the poly(A) RNA library due to their lack of poly(A) tails. This finding is consistent with previous reports , 37. ThrTotal RNA library construction costs around $150 more than a poly(A) library, but it allows the detection of additional RNAs. Whether the extra cost is justifiable should be decided during the experimental design stage of RNAseq study. If the goal is to study lncRNA, then it is better to use total RNA library; if the goal is to study protein coding RNAs, then total RNA library might not be necessary unless histone-encoding genes are of interest.Extracts of medicinal plants used in traditional Korean medicine investigated for cytotoxic activity towards cancer cells.


Influenza A viruses (IAVs) inhibit host gene expression by a process known as host shutoff. Host shutoff limits host innate immune responses and may also redirect the translation apparatus to the production of viral proteins. Multiple IAV proteins regulate host shutoff, including PA-X, a ribonuclease that remains incompletely characterized. We report that PA-X selectively targets host RNA polymerase II (Pol II) transcribed mRNAs, while sparing products of Pol I and Pol III. Interestingly, we show that PA-X can also target Pol II-transcribed RNAs in the nucleus, including non-coding RNAs that are not destined to be translated, and reporter transcripts with RNA hairpin structures that block ribosome loading. Transcript degradation likely occurs in the nucleus, as PA-X is enriched in the nucleus and its nuclear localization correlates with reduction in target RNA levels. Complete degradation of host mRNAs following PA-X-mediated endonucleolytic cleavage is dependent on the host 5’->3’-exonuclease Xrn1. IAV mRNAs are structurally similar to host mRNAs, but are synthesized and modified at the 3’ end by the action of the viral RNA-dependent RNA polymerase complex. Infection of cells with wild-type IAV or a recombinant PA-X-deficient virus revealed that IAV mRNAs resist PA-X-mediated degradation during infection. At the same time, loss of PA-X resulted in changes in the synthesis of select viral mRNAs and a decrease in viral protein accumulation. Collectively, these results significantly advance our understanding of IAV host shutoff, and suggest that the PA-X causes selective degradation of host mRNAs by discriminating some aspect of Pol II-dependent RNA biogenesis in the nucleus. All viruses depend on host components to convert viral mRNAs into proteins. Several viruses, including influenza A virus, encode factors that trigger RNA destruction. The influenza A virus factor that serves in this capacity is known as PA-X. PA-X limits accumulation of host mRNAs and proteins in infected cells and suppresses host responses to infection, but to date its precise mechanism of action remains obscure. Here we report that PA-X selectively targets cellular mRNAs, while sparing viral mRNAs, thereby compromising host gene expression and ensuring priority access of viral mRNAs to the protein synthesis machinery. We demonstrate that complete degradation of mRNAs cut by PA-X is dependent on the host factor Xrn1 and that PA-X likely works in the cell’s nuclei. Interestingly, PA-X targeting appears to be selective for products of host RNA polymerase II, and canonical mRNA processing is required for cleavage. Even though viral mRNAs are spared from PA-X-mediated degradation, PA-X-deficient viruses displayed defects in the synthesis of certain viral mRNAs and decreased viral protein accumulation. Thus, PA-X-mediated host shutoff influences the efficiency of viral gene expression. These studies significantly advance our understanding of this important viral host shutoff protein and may provide future opportunities to limit the pathogenesis of influenza A virus infection. Influenza A virus (IAV) has long been known to carry out host shutoff, and multiple shutoff mechanisms have been reported for this virus, including translation blockade , inhibitnscripts –15. PA-Xnscripts –19, but IAV is a negative strand RNA virus with a genome consisting of eight segments. PA-X protein is encoded on IAV genome segment 3, which also produces polymerase acidic protein (PA), one of the three subunits of the viral RNA-dependent RNA polymerase (RdRp). It is generated by ribosomal pausing on a rare CGU codon that results in a +1 frameshift and read-through of an alternative open reading frame (ORF) ,20. PA-X7G) cap and a 3’ poly-adenylate (poly(A)) tail. 5’ m7G caps are acquired by “cap-snatching”, whereby the PA subunit cleaves nascent host Pol II-transcribed RNAs at a position 10–14 nucleotides downstream from the 5’ cap [7G caps and poly(A) tails allows efficient loading of ribosomes and translation of IAV mRNAs; however, the similarity between host and viral mRNAs raises the question of their susceptibility to PA-X-mediated degradation.RdRp-transcribed IAV mRNAs share essential features with host mRNAs like a 5’ 7-methyl guanosine , whereas Pol I transcribes the rRNA precursor 47S and Pol III transcribes a variety of short ncRNAs including the 5S rRNA. To determine whether PA-X could trigger the degradation of distinct host RNA species, we transfected HEK 293T cells with plasmid reporters encoding an RFP gene driven by a Pol II promoter and a GFP gene under the control of a Pol I-, Pol II-, or Pol III-driven promoter. We observed that ectopic expression of PA-X derived from the A/PuertoRico/8/34 H1N1 (PR8) virus together with these reporters consistently inhibited the accumulation of Pol II-driven RFP and GFP transcripts, whereas Pol I and Pol III-driven GFP transcripts accumulated to high levels . These dTo determine whether PA-X could similarly selectively target endogenous Pol II-driven transcripts, we constructed HEK 293T- and A549-based cell lines that stably express PA-X in a doxycycline-inducible manner (iPA-X cells). In comparison to an inducible RFP control, PA-X expression in the HEK 293T cell lines dramatically reduced endogenous mRNA levels for actin, EEF1A, GAPDH, GUSB, HIST1H3C, tubulin and RPS6, but had a much smaller effect on RPS18 and POLR2A mRNAs . By contin vitro data [We previously found that herpesvirus and coronavirus host shutoff endonucleases employ analogous mechanisms to trigger widespread RNA degradation, whereby endonuclease cleavage of target RNA is followed by processive 5’->3’ degradation by the host exonuclease Xrn1 . To detetro data .Many Pol II-transcribed RNAs are translated. Association with components of the translation apparatus has been shown or proposed to be a determinant of selective mRNA targeting by other host-shutoff RNases, such as HSV-1 vhs ,31 and KIn addition to mRNAs, Pol II also transcribes several ncRNAs, including the long ncRNAs MALAT1 and TP53TG1 and the precursor of the small nuclear RNA U2. Based on our reporter data , we hypoTo determine whether PA-X selectively targets Pol II-transcribed RNA in the context of IAV infection, A549 cells were infected with PR8 or a mutant PR8-PA(fs) virus that should not produce PA-X due to codon optimization that prevents ribosome pausing and frameshifting . As we pWhen determining the titers of recombinant PR8-PA(fs) virus stocks generated in our laboratory, we consistently observed reduction in plaque size compared to the parental wild-type PR8 strain . This super se are not sufficient or necessary for PA-X targeting of mRNAs. Instead they hint at a more universal feature of the 3’ end processing of the Pol II transcribed RNAs that earmark target RNAs for PA-X mediated cleavage. Since mRNA processing and maturation are linked to nuclear export, we compared the PA-X mediated changes in reporter transcript levels between cytoplasmic and nuclear RNA fractions. Importantly, PA-X was able to target both the cytoplasmic and the nuclear pools of the susceptible reporter RNAs (poly(A)-tailed GFP and GFP-hisL), while we failed to detect down-regulation of the HR bearing constructs in either fraction  tail at the 3’ end of the RNA, which is absent from Pol I and Pol III transcripts, and the canonical polyadenylation signal serves to direct termination, cleavage of the RNA and polyadenylation. An alternative stem loop termination signal is used for histone mRNAs , whereasfraction . This deet al. [Although all other host shutoff RNases are proposed to work in the cytoplasm, our results link PA-X targeting to 3’ end processing  and showet al.  highlighet al. . FinallyOur study provides new mechanistic insights into the specificity of PA-X, the most recently identified viral host shutoff nuclease. We demonstrate here for the first time that PA-X is recruited to the nucleus, selectively targets a subset of host transcripts, and is not active against viral mRNAs. Moreover, we uncover a novel route of target discrimination by a viral RNase, which takes advantage of the divergent mRNA biogenesis mechanisms that generate viral and host transcripts. We demonstrate that PA-X shares some specificity features with other host shutoff nucleases, as it selectively targets products of cellular RNA Pol II, while sparing Pol I and Pol III transcripts, and requires host RNases to complete RNA degradation. Interestingly, the mechanism for PA-X targeting of Pol II transcripts is not related to the translatability of the mRNAs. Instead, PA-X targeting is directly linked to synthesis by RNA Pol II complex or early processing events unique to Pol II transcripts. Moreover, we find that PA-X likely degrades RNAs in the nucleus, because it accumulates in this compartment and affects both the nuclear and cytoplasmic fraction of its target RNAs. Both the host shutoff activity of PA-X and the nuclear localization function of the C-terminal X-ORF are dependent on the presence of a set of basic residues in the X-ORF, indicating a correlation between nuclear localization and RNA targeting. Thus, the mechanism of PA-X targeting may be different from other shutoff RNases because it is tightly linked to the mechanism of biogenesis of host and viral mRNAs in the nucleus.Like other host shutoff endonucleases SOX, vhs and nsp1 ,29,37, Pper se is not required. Our data point instead to the processing of Pol II transcripts in the nucleus as the link between PA-X and its target. Importantly, our examination of endogenous and reporter Pol II transcripts that differ in their 3’ end processing suggests that this step in biogenesis may be recognised by PA-X to find its targets. In our experiments, GFP reporters bearing the canonical polyadenylation signal (PAS) or a histone stem loop at the 3’ end were efficiently inhibited by PA-X. By contrast, the same reporter with a templated poly(A) stretch followed by a self-cleaving hammerhead ribozyme sequence was not degraded by PA-X despite being translated -myc-SV40-3’UTR. Clonal populations were selected and several lines were used for all experiments. PA-X expression was induced by addition of doxycycline  for approximately 18 h prior to harvesting, with the exception of half-life experiments, in which doxycycline was added for 4.5 h before actinomycin D addition. HEK 293T shNS  and shXrn1 cells [Mouse embryonic fibroblasts , HeLa Tet-Off (Clontech), HEK 293A (ATCC), HEK 293T (ATCC), A549 (ATCC), and their derivative 293T and A549 “iPA-X” cells were maintained in Dulbecco’s modified Eagle’s medium  supplemented with 10% fetal bovine serum  at 37°C in 5% COn1 cells  were genThe A/PuertoRico/8/34/(H1N1) (PR8) and the recombinant mutant PR8-PA(fs) viruses are described in . Virus sCells grown on glass coverslips were fixed and immunostained according to the protocol in  using moFor steady-state measurements of RNA levels in cells ectopically expressing PA-X protein, RNA was harvested 1 day after transfection or 18 h after PA-X induction in iPA-X cells. For half-life measurements, PA-X (wt or D108A) was induced in A549 iPA-X cells for 4.5 h, followed by addition of actinomycin D at 10 μg/ml final concentration. RNA was collected 0, 2, 4, 6 h after actinomycin D addition, as well as prior to doxycycline treatment.RNA for Northern blotting was harvested and extracted using Trizol reagent (Life Technologies) following manufacturer’s protocol. To isolate cytoplasmic vs. nuclear fractions, cells were lysed in 0.1% NP-40 in Dulbecco’s phosphate buffered saline (DPBS) and the nuclear pellet was spun down. The supernatant was collected as the cytoplasmic fraction. The pellet was washed in 0.1% NP-40 in DPBS, then it was collected as the nuclear fraction. The RNA was extracted from both fractions using Trizol (Life Technologies) following manufacturer’s protocol.The RNA for northern blotting was run on a 1.8% agarose/formaldehyde gel and transferred by capillary action onto nitrocellulose membrane (Bio-Rad) using 10x SSC buffer. Northern blots were probed with probes against the SV40 3’ UTR present in pd2-eGFP-N1 , the firTotal cellular RNA for RT-qPCR in iPA-X and transfected cells was harvested and isolated using Zymo mini-prep kit (Zymo Research) following manufacturer’s protocol. cDNA was generated using iScript (Bio-Rad) from DNase-treated RNA.For analyses of mRNA and vRNA levels in A549 cells infected with IAV, total RNA was isolated at 6, 9, 12, and 15 h post-infection using Qiagen RNeasy Plus kit. For cDNA synthesis, Thermo Maxima H Minus kit was used with gene-specific primer for 18S rRNA combined with either oligo(dT) (for mRNA targets) or influenza vRNA-specific Uni12 primer . To minit-test was used to analyze values for significant differences.Quantitative PCR analysis was performed using iTaq Universal SYBR Green Supermix (Bio-Rad) and Ct values were analyzed using the BioRad CFX Connect Real-Time System qPCR and Bio-Rad CFX Manager 3.1 program analysis. Metabolic labeling and isolation of nascent RNA in A549 cells infected with wild-type PR8 or mutant PR8-PA(fs) viruses was performed using Molecular Probes Click-iT Nascent RNA Capture Kit. At 8 hpi, 0.4 mM Click-iT nucleotide analogue 5-ethynyl uridine (EU) was added to the infection media for 1 hr at 37°C. At 9 hpi monolayers were washed twice with PBS and total RNA was isolated as described using Qiagen RNeasy Plus kit. Biotinylation and subsequent purification of EU-labelled RNA was performed according to the kit manufacturer protocol. cDNA synthesis and qPCR was performed on streptavidin beads as directed by the kit manufacturer protocol and described in methods section above.Total cellular protein was collected in protein lysis buffer ) unless specified otherwise in the text. Proteins were separated on SDS-PAGE gels and transferred onto PVDF membranes (Millipore). Western blots were performed in PBST with 5% milk or TBST with 4% bovine serum albumin. The following antibodies were used: Xrn1 , IAV NS1  < 0.05, 0.01, 0.001 vs. 293T iRFP  or A549 iPA-X D108A #8, shown in (A-C) HEK 293T (A) or A549 (B-C) cells expressing doxycycline-inducible wild-type PA-X-myc (“iPA-X wt”), a catalytically inactive mutant (“iPA-X D108A”) or RFP (“iRFP”) were treated with doxycycline for 18 h to induce expression of PA-X. Total cellular RNA was extracted and RT-qPCR was performed to measure levels of the indicated endogenous RNAs or the PA-X mRNA in panel C. Gene expression normalized by 18S rRNA levels is plotted as fold change in induced (PA-X- or RFP-expressing) vs. uninduced cells. The numbers indicate the clones of HEK293T and A549 iPA-X cells used for this panel. *,**,*** = (EPS)Click here for additional data file.S2 Figp value (Student’s t-test) < 0.05, 0.01, 0.001 vs. 293T iRFP  or A549 iPA-X D108A #8, shown in (A) 293T cells were transfected with Pol II-driven GFP reporters and either PA-X or an empty vector. The hp-GFP construct contains a hairpin close to the 5’ end of the GFP mRNA that blocks its translation. The levels of expression of GFP protein were examined by western blotting. Tubulin is included as a loading control. A representative blot is shown. (B) 293T iPA-X cells (line #7) were transfected with a T7 polymerase expressing construct and an EMCV IRES-containing luciferase reporter driven by the T7 promoter, which results in T7-mediated RNA transcription. PA-X expression was induced 5 h after transfection by doxycycline addition for 18 h. Luciferase activity was measured using a luminescence assay and is plotted as fold change relative to background luminescence levels in cells transfected with the EMCV-luciferase construct alone. Error bars = std. dev. (C-D) HEK 293T (C) or A549 (D) cells expressing doxycycline-inducible wild-type PA-X-myc (“iPA-X wt”), a catalytically inactive mutant (“iPA-X D108A”) or RFP (“iRFP”) were treated with doxycycline for 18 h to induce expression of PA-X. Total cellular RNA was extracted and RT-qPCR was performed to measure levels of the indicated endogenous RNAs. Gene expression normalized by 18S rRNA levels is plotted as fold change in induced (PA-X- or RFP-expressing) vs. uninduced cells. The numbers indicate the clones of HEK293T and A549 iPA-X cells used for this panel. Error bars = s.e.m. *,**,*** = (EPS)Click here for additional data file.S3 Fig(A) PA-X targets both the cytoplasmic and the nuclear pools of susceptible reporter RNAs, and does not degrade the HR bearing constructs in either fraction. HEK 293Ts were transfected with indicated Pol-II driven GFP reporters and either PA-X or empty vector. Total cellular RNA was extracted from nuclear and cytoplasmic fraction and GFP mRNA, 7SL and U2 ncRNA levels were measured by northern blotting. A representative blot is shown. (B) Relative levels of pre-mRNAs and MALAT1 ncRNA in the nuclear vs. cytoplasmic fraction confirm that they are enriched in the nucleus (control for (EPS)Click here for additional data file.S4 Fig(A and B) Spontaneously immortalized mouse embryonic fibroblast (MEF) cells were co-transfected with the NF-kB promoter-driven Firefly luciferase reporter , thymidine kinase promoter-driven Renilla luciferase reporter , and the indicated GFP-fusion protein expression constructs. At 24 h post-transfection, (A) the cells were fixed with 4% paraformaldehyde, stained with Hoechst dye to visualize cell nuclei, and analyzed by fluorescence microscopy. Asterisk indicates 2-times longer exposure for cells transfected with the PA-X-GFP fusion construct due to low level of expression. Scale bar = 20 um. Alternatively, (B) the cells were used to measure Firefly (FF-luc) and Renilla luciferase expression using Dual-Luciferase Reporter Assay kit (Promega). Values are normalized to vector-transfected cells. (C) HeLa Tet-Off cells (Clontech) were co-transfected with tetracycline response element (TRE2) promoter-driven Firefly (FF-luc) and Renilla (Renilla) luciferase reporters and the indicated GFP-fusion protein expression constructs. Luciferase activity was measured at 24 h post-transfection as described in (B). Values are normalized to those in cells transfected with the GFP-X41 fusion construct. In (B) and (C) the error bars represent standard deviation between measurements from 2 independently transfected wells.(TIF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.


Investigations have been conducted regarding the interference of nanoparticles (NPs) with different toxicological assay systems, but there is a lack of validation when conducting routine tests for nucleic acid isolation, quantification, integrity, and purity analyses. The interference of citrate-capped gold nanoparticles (AuNPs) was investigated herein. The AuNPs were added to either BEAS-2B bronchial human cells for 24 h, the isolated pure RNA, or added during the isolation procedure, and the resultant interaction was assessed. Total RNA that was isolated from untreated BEAS-2B cells was spiked with various concentrations (v/v%) of AuNPs and quantified. A decrease in the absorbance spectrum (220–340 nm) was observed in a concentration-dependent manner. The 260 and 280 nm absorbance ratios that traditionally infer RNA purity were also altered. Electrophoresis was performed to determine RNA integrity, but could not differentiate between AuNP-exposed samples. However, the spiked post-isolation samples did produce differences in spectra (190–220 nm), where shifts were observed at a shorter wavelength. These shifts could be due to alterations to chromophores found in nucleic acids. The co-isolation samples, spiked with 100 µL AuNP during the isolation procedure, displayed a peak shift to a longer wavelength and were similar to the results obtained from a 24 h AuNP treatment, under non-cytotoxic test conditions. Moreover, hyperspectral imaging using CytoViva dark field microscopy did not detect AuNP spectral signatures in the RNA isolated from treated cells. However, despite the lack of AuNPs in the final RNA product, structural changes in RNA could still be observed between 190–220 nm. Consequently, full spectral analyses should replace the traditional ratios based on readings at 230, 260, and 280 nm. These are critical points of analyses, validation, and optimization for RNA-based techniques used to assess AuNPs effects. Plasmonic engineered nanoparticles (NPs) are popular in consumer- and medical-based industries due to their unique surface characteristics. However, there is a growing concern regarding NP toxicity. Identifying the toxicity of NPs is, thus, critical given increased exposure and it has become increasingly important to validate assay parameters for techniques used to determine cyto- and genotoxicity. The toxicity of NPs is often determined using conventional colorimetric and optical high-throughput toxicity systems that rely on absorbance, luminescence or fluorescence signals. However, NPs themselves may interfere with these assay mechanisms 260/A280 ratio measures the level of protein contamination, and the A260/A230 ratio indicates whether or not contaminants from the isolation procedure are in the sample  Gene expression assays rely heavily on RNA with excellent quality, as emphasized in the MIQE guidelines 2) and amines (-C-NH2) are found in the nitrogenous bases of the nucleotides of nucleic acids (both DNA and RNA). Phosphodiester linkages form between nucleotides and constitute the backbone of the molecule. Occasionally amino acids, which contain amino and carboxyl groups, may also precipitate with the final nucleic acid samples after the isolation procedure. Rather than only focusing on the traditional wavelengths, it is important to be aware of all the possible peaks that could be observed during spectrophotometry-based analyses of nucleic acids. An example includes where it was reported that, in addition to the well-known band at 259-260 nm, RNA possessed another stronger absorption band in the far ultraviolet range at 188 nm 2+ are needed to stabilize many secondary and tertiary structures within the RNA The UV absorbance of the chromophores that are inherent to nucleic acid structure must be considered when analyzing DNA or RNA using spectrophotometry. Chromophores are chemical groups that absorb UV-visible radiation at a specific wavelength without influencing the other groups in the molecule. Amides  spectrophotometric analyses (ii) electrophoresis analyses (iii) isolation and analyses used for standard gene expression studies. The aim was achieved since an AuNP-spiked sample decreased spectrophotometry-based RNA quantification between 220–340 nm, and interfered with the purity analysis at 230, 260 and 280 nm. In addition, a 24 h treated sample showed slightly discernible effects between 190–220 nm. HSI using CytoViva Dark field microscopy did not detect any AuNP spectral signatures in the isolated RNA from treated cells and the fate of the AuNPs was tracked by UV-Vis absorbance measurements of the eluted flow-through.An overview of the entire experiment is summarized and provided as supplementary information see .4.3H2O aqueous solution 4.3H2O) and trisodium citrate (Na3C6H5O7.2H2O) were purchased from Sigma Aldrich (USA) and used without further purification. This AuNP was fully characterized  was added to 180 mL (0.3 mM) of boiling HAuClized see  and the 2 in a humidified environment), in RPMI-1640 medium with L-glutamine , 10% heat-inactivated fetal bovine serum , 100 units Penicillin per mL culture media and 100 µg Streptomycin per mL culture media , hereafter referred to as RPMI culture medium. The cell monolayer (at 80–90% confluence) was washed with Dulbecco's Phosphate Buffered Saline , and harvested by incubation with a 0.5% trypsin/EDTA  solution. The cells were collected by centrifugation at 200 × g for 5 min. The supernatant was discarded and the cells were subsequently re-suspended in 10 mL RPMI culture media. The cell viability was determined using trypan blue exclusion method . Thereafter, the cells were routinely sub-cultured every 3–4 days at approximately 6 × 103 cells/cm2. Experiments were performed with BEAS-2B bronchial human cells between passages 15 to 20.The bronchial epithelial human cell line, BEAS-2B, was obtained from Sigma Aldrich , originally from the European Collection of Cell Cultures (ECACC), operated by the Health Protection Agency Culture Collections (HPACC). The BEAS-2B cell line was maintained under standard culturing conditions , according to the manufacturer's instructions. In addition, the QIAshredder spin columns  were used to homogenize the samples see . The RNAThe RNA obtained from untreated cells served as the control. The AuNP-spiked samples represent different variations of positive controls. The post-isolation spiked sample was prepared by using the untreated control RNA, which was spiked with various percentages of AuNP. The 25% NP spike had a final concentration (FC) of 0.75 nM. The 50%, 75% and 100% each had an FC of 1.5 nM, 2.25 nM and 3 nM, respectively. The co-isolation spiked sample was prepared by using the untreated cells (in the RNAprotect solution), which were spiked with various volumes of AuNPs, prior to cell lysis and RNA isolation. However, there was no extended incubation time similar to the 24 h AuNP-treated samples. The 25 µL NP spike had an FC of 0.1667 nM. The 50 µL and 100 µL spikes each had an FC of 0.333 and 0.667 nM, respectively. The RNA obtained from untreated cells was also used to prepare an additional spiked sample, where the sample had a constant amount of RNA, but had variable amounts of AuNP. This was a variation of the post-isolation spiked sample, where the untreated control RNA was first diluted and then kept at a constant amount of 20 ng, but still spiked with various percentages of AuNP. Therefore, the 25% NP spike had a constant amount of 20 ng RNA with an AuNP FC of 0.75 nM. The 50%, 75% and 100% each had an AuNP FC of 1.5 nM, 2.1 nM and 3 nM, respectively.260/A280 and A260/A230 ratios. Additional full spectra were obtained from 190 to 840 nm. Post and co-isolation spiked samples were compared to the untreated control and statistical analyses were performed using the Student's T-test . The interpretation of the p-value was based on a significance level of 5%, where: p≤0.005 referred to a very strong presumption against the null hypothesis, which was designated as “very significant”; 0.005≤p≤0.01 referred to a strong presumption against the null hypothesis, which was designated as “significant”; 0.01≤p≤0.05 referred to a low presumption against the null hypothesis, which was designated as “low significance”; p>0.05 referred to a no presumption against the null hypothesis, which was designated as “not significant”.The RNA was analyzed on a Nanodrop 2000c UV-Vis Spectrophotometer, according to the manufacturer's instructions. Traditional UV-Vis spectra were obtained from 220 to 350 nm, where nucleic acid quantification was determined at 260 nm. The purity of each sample was determined using the AFor RNA samples, a 10 µL aliquot was added to 2 µL of a 6xOrange Loading dye containing Orange G and Xylene Cyanol (Fermentas). This was loaded onto a 1% agarose gel and subjected to electrophoresis at 100V, whilst being submerged in 89 mM Tris-borate and 2 mM EDTA at pH 8.3 (TBE) buffer , which was stained with 10 µg/mL ethidium bromide. Images were obtained using GeneSys software version1.3.3.0 on a Syngene G:Box instrument .For uptake studies, cells were seeded in 8-well Millicell EZ slides  prior to treatment. Following incubation, cells were washed with culture media, followed by three washes with DPBS . Cells were fixed at 4°C with 4% formalin in Tris/HCl buffer, at pH 7.4, for 15 min. Slides were washed once with DPBS and air-dried. Cover-slips were immobilized onto slides with Kaiser's gelatin . Dark field images were captured at 60× magnification using the CytoViva 150 Unit integrated onto the Olympus BX43 microscope. Images were acquired using a Dagexcel ×16 camera and the associated software.To investigate the fate of the AuNPs, a drop of either AuNP in Milli-Q water or the isolated RNA from AuNP-treated cells was placed onto a Millicell EZ slide and allowed to dry. Samples were visualized using dark-field microscopy, at 60× magnification and using the CytoViva150 unit integrated onto the Olympus BX43 microscope. Images were acquired using a DAGExcel ×16 camera and software. HSI was performed at 60× magnification using the HSI system 1.1 and ENVI software. A spectral library of the 14 nm AuNPs was created by randomly selecting spectra of AuNPs, where each spectrum of the library represents a single pixel obtained from the HSI scan. In order to investigate the presence of the AuNPs in the RNA sample, the image classification algorithm, spectral angle mapper (SAM), was performed using ENVI software to map the spectral libraries onto the scans. Therefore, the spectral profile collected was representative of a spectral library of the AuNP onto the HSI scan of the RNA.To investigate the fate of the AuNPs throughout the RNA isolation procedure, samples were retained at various steps. The samples collected were from key points in the harvesting and RNA isolation procedure, namely, (1) the cell culture media in which the cells were treated, (2) the PBS used to wash the cells prior to trypsinization, (3) the supernatant following centrifugation of the trypsinized cells, (4) RNAProtect solution supernatant, (5) RLT buffer and ethanol following sample loading onto RNeasy MinElute column, (6) Buffer RW1 following wash step, (7) Buffer RPE following first wash step, and (8) Buffer RPE following second wash step. Full range spectra were obtained (from 190 to 840 nm) on a Nanodrop 2000c UV-Vis Spectrophotometer, according to the manufacturer's instructions. Nuclease free water was used as a blank for all the different samples. For each eluent analyzed (e.g. the first “media” eluent), the absorbance reading of the media eluted from the untreated control represented the background reading, and, was subtracted from the absorbance reading of the media eluted from the AuNP-treated sample, and, the resultant difference in absorbance reading was plotted, where:Difference Abs-media  =  (Abs-media from AuNP-treated) - (Abs-media from untreated control)The most common wavelength range tested before gene expression studies is the 220–340 nm range since the absorbance measurements at 230, 260 and 280 nm are used to calculate RNA yield and purity. Therefore, these wavelengths were included for initial studies . Post-isThe experiment was further expanded upon to include a full spectrum scan in the UV-Vis region, from 190 to 840 nm . DiffereA variation of the post-isolation spiked sample was included, which consisted of RNA isolated from untreated cells. The RNA was diluted and then kept at a constant amount of 20 ng. This diluted RNA was spiked with AuNP in a similar manner to the post-isolation spiked sample series. Differences in spectra were observed between approximately 190 to 220 nm, where peak shifts were observed for AuNP-spiked samples . AlthougThe experiment was expanded upon to include a “co-isolation” step, where various AuNP volumes were added prior to cell lysis and then processed in parallel up to the point of RNA precipitation . It was In The current study also included the assessment of RNA obtained from samples that had been treated with AuNPs for 24 h. Uptake of AuNPs into BEAS-2B cells has been previously observed at 1, 4 and 6 h, with minimal toxicity A few indications of AuNP interference were discernible in the RNA obtained from 24 h AuNP-treated samples . AlthougSince the initial data focused only on a small wavelength range from 220–340 nm (the most common region tested before gene expression studies), the experiment was further expanded upon to include full spectra in the UV-Vis region (190–840 nm). Differences were observed for the 24 h AuNP-treated sample, at wavelengths other than the traditional measurements, i.e. peak shifts were observed at 190–220 nm. In 260/A280 (an indication of protein contamination) is between 1.8 and 2.1. The ideal ratio for RNA for A260/A230 , is ideally above 1.5 (2.0–2.2). A decrease in the absorbance spectrum, from 220 nm to 340 nm,  band should be twice the intensity of the 18S (lower) band There was no discernible difference between the banding patterns of the untreated control RNA to the AuNP post- or co-isolated spiked samples , the culture media is removed from the cells, and then washed with PBS, before being trypsinized. The RNA isolation procedure that followed included wash and centrifugation steps. The AuNPs were tracked through the eluted flow-through or discarded waste (eluents) from all the wash steps produced during the RNA isolation procedure for BEAS-2B cells treated for 24 h. The citrate-capped AuNP has an absorbance at 519 nm. However, it was decided to plot the difference in absorbance readings between the untreated control and the 24 h treated sample, from 450 to 600 nm, per eluent . It was This study was initiated in order to determine if any AuNP interference occurred during the isolation, quantification and integrity analyses of RNA obtained from the BEAS-2B human cell line. This was achieved by assessing the interaction and interference of AuNP with either the isolated RNA sample, or, during the isolation process. This particular AuNP was fully characterized In a recent study, spectral analysis was used to elucidate details regarding the structure and extent of denaturation of DNA induced by weakly charged cationic NPs It is important to note the shared differences and similarities between the samples. For example, both the post- and co-isolation spiked samples had a higher concentration of AuNP than the 24 h treated sample since the spiked samples contained AuNPs that were deliberately added to the RNA sample (at various percentages and volumes). The treated sample only contained a non-cytotoxic concentration 2) at a wavelength of 190, 205 or 214 nm 260/280 ratio. The isolated untreated RNA samples fell within the acceptable range of 1.8 to 2.1 .The interaction of NPs with proteins has recently been reviewed, which explains the effect of NPs on protein stability, solubility etc. 2+ metal ions and, thus, created a different kind of structural instability within the RNA molecule. The wavelength shift between the control and the 24 h AuNP treated RNA sample is most likely the result of a combination of all of the above mentioned interactions. The effect of such interactions of NPs on the transcription and/or translation of RNA may, thus, need further investigation. Therefore, studies are currently underway to assess AuNP-induced alterations, if any, related to the amplification of reference genes or other related genes of interest.It is plausible that the observed wavelength shift in the treated RNA sample could be associated with interactions affecting the amine group or the phosphodiester linkage between the individual nucleotides. AuNPs have a negative surface charge and possess a highly reactive surface, which in turn is able to interact strongly with thiols, disulfides and amines 60, could bind with the minor grooves of dsDNA 60 NP could bind only to the major grooves of the RNA helix. This transformed the configuration from “stretch” to “curl” and stabilized the RNA structure. Consequently, the examples discussed above emphasize the need for in-depth studies of not only nucleic acid quantity, but also quality before using DNA or RNA as the starting material for genetic studies.DNA has also been assessed in other studies in order to determine the putative effects of NPs with regard to not only the quantity, but also the quality of the nucleic acid. In the first example, it was observed that a dA nucleoside could bind to 13 nm AuNPs via the N(7) nitrogen atom of the imidazole ring It was expected that a decrease in the UV-Vis absorbance would be observed in RNA isolated from 24 h AuNP-treated BEAS-2B cells . However260/280 ratio), the wavelength shift observed was most probably due to these AuNPs interacting with the amines found in nitrogenous bases of the nucleic acid. However, these AuNPs could have interacted with the phosphodiester linkage between the individual nucleotides, or even the stabilizing Mg2+ metal ions within the RNA molecule required for secondary and tertiary structures. It was also found that the artificial introduction of an AuNP (spikes), to a control RNA sample, influenced quantification and purity analyses. It was proposed that the decreased absorbance observed could also occur in other NP-related research, where techniques rely on RNA as the starting material. Caution is, thus, advised when only assessing DNA/RNA quantity, since structurally altered or damaged nucleic acids could be falsely interpreted as simply a low yield and, subsequently, produces false genetic expression data. It was recommended that screening of additional wavelengths other than the traditional 230, 260 and 280 nm would give an indication of RNA quality and purity after treatment with any NP and, subsequently, would identify damage that may have occurred. In addition, it was found that electrophoresis performed on the spiked samples was not sensitive enough to detect changes in the RNA integrity. The fate of the AuNPs was determined by tracking the different eluted flow-through or discarded waste from all the wash steps produced during the RNA isolation procedure. CytoViva dark field microscopy, in conjunction with HSI, was used to confirm that the AuNPs did not co-precipitate in the final product. Despite the lack of co-precipitation of the AuNPs with RNA, structural changes in RNA could still be observed. Future studies will, therefore, aim to assess the effect of AuNP-induced structural changes related to the amplification of reference genes and other related genes of interest. The validation procedure reported herein could be used to develop SOPs and contribute towards developing improved hazard identification of NPs, by acting as a template for assessment of NP interference during the isolation, quantification and integrity analysis of RNA from any human cell line.The interaction and interference of AuNP with either isolated pure RNA, or, during the isolation procedure was assessed. It was found that the introduction of AuNPs to BEAS-2B cells produced absorbance peak shifts, which indicated changes in the quality of the isolated RNA. Although the RNA isolated from the 24 h AuNP-treated samples was considered to be suitable for RNA-based techniques when using the traditional methods, additional screening identified changes that are associated with structural alterations of functional groups. The observed wavelength shift between the control and the 24 h AuNP-treated RNA (from 190 to 235 nm), could be associated with either the amine, ester or carboxyl compounds based on their typical wavelength absorption. Since protein did not co-precipitate with the RNA during the isolation procedure Click here for additional data file.Data S2Supporting Figures and Tables. Figure S2.1. Absorbance spectrum of the gold nanoparticles. Figure S2.2. Characterization of the gold nanoparticles in milli-Q water and in culture medium using Transmission Electron Microscopy. Table S2.1. Physicochemical properties of gold nanoparticles in milli-Q water. Table S2.2. Physicochemical properties of gold nanoparticles suspended at 1 nM in culture medium.(DOCX)Click here for additional data file.Data S3Supporting Figures. Figure S3.1. Fate of AuNP during processing. Figure S3.2. Eluent 1. Figure S3.3. Eluent 2. Figure S3.4. Eluent 4. Figure S3.5. Cell pellets and the RNAprotect solution. Figure S3.6. Columns used during the RNA isolation, after the cell lysis buffer was added. Figure S3.7. Wash solutions used after cell lysis and filtration through the various columns.(DOCX)Click here for additional data file.Data S4Supporting Tables. Table S4.1. Purity analysis of untreated control vs. post-isolation AuNP-spiked RNA. Table S4.2. Purity analysis of untreated control vs. co-isolation AuNP-spiked RNA.(DOCX)Click here for additional data file.Data S5Supporting Figures. Figure S5.1. UV-Vis spectroscopy of a universal RNA standard spiked with AuNP. Figure S5.2. UV-Vis spectroscopy of a universal RNA standard spiked with AuNP. (A) First technical repeat. (B) Second technical repeat.(DOCX)Click here for additional data file.


CD)2 from Moloney murine leukemia virus, and ribosome-binding element from turnip crinkle virus. In all three systems, we showed that the incorporation of a map restraint, either experimental or generated from known PDB structure, greatly improves structural precision and accuracy. Importantly, our method does not rely on an initial model assembled from RNA duplexes, and allows full torsional freedom for each nucleotide in the torsion angle simulated annealing refinement. As increasing number of macromolecules can be characterized by both NMR and EM, the marriage between the two techniques would enable better characterization of RNA three-dimensional structures.More than 40% of the RNA structures have been determined using nuclear magnetic resonance (NMR) technique. NMR mainly provides local structural information of protons and works most effectively on relatively small biomacromolecules. Hence structural characterization of large RNAs can be difficult for NMR alone. Electron microscopy (EM) provides global shape information of macromolecules at nanometer resolution, which should be complementary to NMR for RNA structure determination. Here we developed a new energy term in Xplor-NIH against the density map obtained by EM. We conjointly used NMR and map restraints for the structure refinement of three RNA systems — U2/U6 small-nuclear RNA, genome-packing motif (Ψ RNA is intrinsically dynamic [Non-coding RNAs are essential in many aspects of life –6. The s dynamic ,10, and An RNA molecule is a polymer of four types of nucleotides, compared to 20 amino acids in a protein. Owing to the low chemical complexity in RNA primary sequence, the chemical shift dispersion is small and the NMR spectra are often poorly resolved. Moreover, an RNA molecule has a lower density of protons than a protein of the same molecular weight, hence fewer distance restraints per nucleotide can be obtained from the measurement of proton-proton nuclear Overhauser effect (NOE) . The NOEBesides NOE distance restraints, other types of restraints have been incorporated into the RNA structure determination. Residual dipolar coupling (RDC), a type of NMR experiment, provides bond orientation information—often measured for imino groups of RNA—relative to an alignment tensor ,14. Smalde novo determining the structure of a single-chain polypeptide or nucleic acid. On the other hand, EM micrographs suffer from low image contrast, especially for relatively small biomacromolecules. Recent development in cryogenic electron microscopy (cyro-EM), cryogenic electron tomography (cyro-ET), and single-particle reconstruction, however, has permitted more routine visualization of biomacromolecules with molecular weight below 200 kDa [31P than a protein of the same molecular weight (at the expense of lower proton density), an RNA molecule diffracts more electrons than a protein does. All told, the stage is set to marry EM with solution NMR for the RNA structure refinement.Electron microscopy (EM) has become an important technique in structural biology. EM affords global shape information of a macromolecule at nanometer resolution, which should complement the local structural information provided by NMR. Indeed, when the structures of each component are known, large macromolecular assemblies can be modeled by integrating various experimental inputs including both NMR and EM . Howeverσobs are the average and standard deviation of the input map, and σcalc are the average and standard deviation of the back-calculated values from the RNA structure. When optimizing C, the energy associated is kc(1-C), in which kc is the force constant scale. To invoke the map potential term in an Xplor-NIH python script, the following snippet is incorporated.To incorporate the EM data, we developed a new density map potential, and we implemented this term in Xplor-NIH molecular structure determination package , versionfrom atomDensity import AtomDensity, DensityGridDmap = DensityGridDmap.readCCP4from probDistPotTools import create_probDistPotprob = create_probDistPotpotList.append(prob)prob.setScale(10)3 voxel size and Gaussian smooth kernel at various resolutions.The density map potential term currently only reads maps in CCP4 format (the file name here is map1.ccp4), which can be generated experimentally (see below) or downloaded from EM DataBank (EMDB). For the two examples presented in this study, U2/U6 small-nuclear RNA  and riboIn a typical Xplor-NIH run, the restraint table includes both covalent geometrical  and experimental restraints including NOE distance and RDC orientation restraints. Based on RNA secondary structure, hydrogen bonding, base planarity, and dihedral angle restraints  were empWe first examined the 111-nucleotide U2/U6 small-nuclear RNA (snRNA) involved in pre-RNA splicing. U2/U6 comprises a three-way junction arranged in a Y-shape, and its three-dimensional structure has been determined by refining against both NMR and SAXS data. Unfortunately, only the NMR restraints are available from the PDB, whereas the associated SAXS data have not been deposited by the authors . We perfWe generated the density map using the program pdb2vol in the Situs package  at diffeCD)2 from Moloney murine leukemia virus (MMLV) is a dimer with 66 nucleotides in each RNA chain, with a total molecular weight of 42.8 kDa. The (ΨCD)2 has been characterized with cryo-ET—the density map was derived with sub-volume averaging from only 47 particles [The retroviral genome-packing motif (ΨCD)2 dimeric arrangement. Refined without map restraint, the afforded structures converge to an RMS deviation of 3.37±0.45 Å for all heavy atoms in both chains of the (ΨCD)2 (CD)2 is greatly improved, to an RMS deviation of 1.67±0.33 Å (CD)2 is a homodimer and contains fewer secondary structure elements than U2/U6 snRNA, which can explain why better structural convergence is achieved for (ΨCD)2. Importantly, our calculation demonstrated that the RNA structure could be refined to better precision, with the incorporation of a cryo-ET map of a rather poor resolution.We repeated the RNA structure calculation using Xplor-NIH  against e (ΨCD)2 . With th7±0.33 Å . The (ΨCWe further tested our method on a 102-nucleotide ribosome-binding element (RBE) from the 3’-untranslated region of turnip crinkle virus genome. Shaped like a tRNA, the solution structure of RBE was previously characterized with joint refinement against NMR and SAXS data, to an RMS deviation of 1.4±0.2 Å for a 10-model bundle . We repea priori and we give full torsional freedom to each nucleotide in the RNA. For a fairer comparison, we fixed the relative angles between the duplexes in RBE when incorporating additional map restraint but in the absence of the SAXS restraint. We were able to refine the RBE structure to an RMS deviation of 0.76±0.03 Å for a 20-structure bundle  much larger than the value previously reported (1.4±0.2 Å)? In the previously study , the aute bundle  and the In this study, we developed a new potential term in Xplor-NIH , and we The fact that NMR spectroscopy is most effective for biomacromolecules less than 50 kDa has been a major bottleneck for this technique: as the system gets larger, NMR peaks become broader and more peaks can overlap. Notwithstanding, technical development in recent years is pushing the limit on the size of macromolecules that NMR can characterize . Though


This paper presents the development of such a method, a new technique using a cyanine dye called CyT, which can detect both canonical and non-canonical RNA G4 structures from test tubes to living human cells. The ability of CyT to distinguish between G4 and nonG4 RNA offers a promising tool for future RNA G4-based biomarker discovery and potential diagnostic applications.RNA G-quadruplexes (G4s) are one of the key components of the transcriptome that act as efficient post-transcriptional regulatory elements in living cells. To conduct further studies of the unique biological functions of RNA G4s, techniques need to be developed that can efficiently recognize RNA G4 structures under various conditions, in fixed cells and living cells, as well as  As a nurocesses –12. Whilrocesses . Currentrocesses ,15. As Rrocesses , techniqin vitro transcription and radioactive 5′-end-labeling, the technique may be more suitable for studying nucleotide locations in RNA G4s, and not for in situ RNA G4 detection. Recent research has shown that nucleic acids that do not obey the classical description of sequences G2+NL1G2+NL2G2+NL3G2+ could also form G4 structures  are the most accurate techniques and have identified high-resolution structures of RNA G4s ,18. Thesructures –24. Howein living cells  and 610 nm (for CyT).PAGE was performed in 1× TBE buffer solution (0.09 M Tris-boric acid and 0.002 M EDTA) with 12% native gels. Oligonucleotides (5 μM) were loaded on the gel, and electrophoresis was run at 64 V for 2 h at room temperature. After electrophoresis, the gel was stained using either 20 μM CyT in Tris-KA549 cells were cultured in Dulbecco's Modified Eagle's Medium (DMEM) contain 5% fetal bovine serum (FBS), streptomycin (0.1 mg/mL) and penicillin (100 U/mL), under 5% carbon dioxide at 37 °C. Cells grown on Petri dish were fixed for 5 min in cold methanol and 4% formaldehyde, rinsed twice with phosphate-buffered saline (PBS), and then permeabilized with 0.1% Triton X-100/PBS for 30 min at 37 °C. For enzymatic treatments, cells were incubated denaturing buffer and RNase T1 for 5 h at 37 °C after permeabilization. After treatment, cells were incubated with the CyT probe (5 μM) for 5 min. Cellular nuclei were stained with 4′,6-diamidino-2-phenylindole (DAPI), before visualization under a confocal laser scanning microscope (CLSM) (OLYMPUS FV1000-IX81) equipped with an oil immersion 100X objective. CLSM images of DAPI and CyT were collected under excitation at 408 nm and 559 nm, respectively. For living cells, the CyT probe was incubated with the cells for 24 h and visualized, without washing, under the CLSM. Hoechst 33258 (8 μg/mL) was used to stained the nuclei.To demonstrate the feasibility of using a CyT probe for RNA G4 recognition, we compared the fluorescence intensity of CyT on its own or in the presence of various RNA sequences. The results of emission spectra are presented in Figure 5, (1.44 ± 0.29) × 105, (2.81 ± 0.63) × 105, (1.94 ± 0.29) × 105 and (3.49 ± 0.77) × 105 M−1, respectively. In comparison with RNA G4s, the binding strength to tRNA, ssAf17, ssAf22, HP18 and dsNC was much weaker, with binding constants (6.35 ± 2.26) × 104, (4.40 ± 0.38) × 104, (4.03 ± 0.36) × 104, (2.89 ± 0.28) × 104 and (2.42 ± 0.25) × 104 M−1, respectively. Of note, although the binding affinities of CyT to non-RNA G4s were obtained in the range of 104  was confirmed by the Job's plot analysis . The typical titration curves and fitting results according to the 1:1 binding model are presented in Supplementary Figure S2. The binding constants for CyT with Tel22, VEGF, TRF2, BCL-2 and NRAS are (1.17 ± 0.37) × 10ntensity .−1cm−1, while the fluorescence quantum yields of CyT bound to two equivalents of RNA G4s, such as Tel22, VEGF, TRF2, BCL-2 and NRAS, were 0.95, 0.92, 0.79, 0.74 and 0.58, respectively. The relatively high molar absorptivity and fluorescence intensity of the bound-state CyT may lead to CyT acting as a highly sensitive fluorescence probe for RNA G4 detection. Overall, the above results confirm that the CyT probe could be used for the recognition of RNA G4 structures with high specificity and sensitivity through fluorescence light-up.As molar absorptivity and fluorescence intensity are key factors influencing the sensitivity of a fluorescence probe, we evaluated the molar extinction coefficients and quantum yields of CyT bound to RNA G4s. The CyT monomer showed a relatively high molar extinction coefficient of 80 14;000 M+ and Li+ solutions. Figure + and Li+ conditions. As shown in Figure + and Li+, indicating the formation of parallel-type G4 structures. The CD intensity decreased under Li+ condition, compared to K+, which could be explained by the weaker G4 formation capability of Li+, compared to K+  and displayed a predominant absorption band at 650 nm, which was previously assigned to J-aggregates  was studied. A UV-vis titration was conducted by increasing the RNA G4 concentration (from 0.125 to 4 μM), with the CyT concentration fixed at 2 μM. As shown in Figure gregates . Of notegregates . These rgregates . The flu+) (J-aggregates) conditions, the fluorescence intensity of CyT was very weak. In contrast, significant fluorescence enhancement was induced by the bound-state CyT monomer, which can be considered as a unique signature in the recognition of RNA G4 structures.It is worth noting that the enhancement of monomeric CyT fluorescence intensity resulted from the bound-state CyT monomer, and not from the unbound-state monomer itself. As shown in Supplementary Figure S3, under methanol (unbound-state) and Tris-HCl  and subsequently stained using either 20 μM CyT Figure  or SYBR 2+NL1G2+NL2G2+NL3G2+ could also form G4 structures , double-stranded RNA (dsRNA), short hairpin RNA (shRNA) and RNA junction structures. Fluorescence assays showed that CyT strongly lit up RNA G4 structures and barely lit up the tested single-stranded, double-stranded and hairpin RNA structures, tRNAs, and three- and four-way junction structures. As a result we conclude that CyT, with its high specificity for RNA G4, is an excellent probe to stain and light up RNA G4 structures, and not other RNA structures, in the cells.Furthermore, given the structural similarities between DNA and RNA G4s, we determined whether DNA G4 detectors (such as TO) can also be applied as RNA G4 detectors. Although TO is widely used as a selective DNA G4 detector, our results showed that TO does not show any selectivity for RNA G4s, compared with other RNA forms. Therefore, this indicates that a DNA G4 probe may not be suitable for detecting or recognizing RNA G4s without validation.Additionally, our results showed that CyT emitted stronger fluorescence in the presence of RNA G4s, compared with DNA G4s with identical sequences . Although the CyT probe showed very high selectivity for RNA G4s, compared to other RNA forms, and thus can be used to distinguish RNA G4s from other RNA forms, CyT, at the present stage, may not be suitable for distinguishing RNA G4s and DNA G4s with different sequences.in vitro and in living human cells. The ability of CyT to distinguish between G4 and non-G4 RNA offers a promising tool for future RNA G4-based biomarker discovery, with potential diagnostic applications.The molecular probe CyT described in this study showed strong fluorescence enhancement in the presence of RNA G4 structures but did not show such a response toward other RNA forms. Therefore, our results demonstrate that CyT is an effective detector of RNA G4 structures both


Results and comparisons with the existing methods encourage our findings on both aspects.RNA editing is a post-transcriptional alteration of RNA sequences that is able to affect protein structure as well as RNA and protein expression. Adenosine-to-inosine (A-to-I) RNA editing is the most frequent and common post-transcriptional modification in human, where adenosine (A) deamination produces its conversion into inosine (I), which in turn is interpreted by the translation and splicing machineries as guanosine (G). The disruption of the editing machinery has been associated to various human diseases such as cancer or neurodegenerative diseases. This biological phenomenon is catalyzed by members of the adenosine deaminase acting on RNA (ADAR) family of enzymes and occurs on dsRNA structures. Despite the enormous efforts made in the last decade, the real biological function underlying such a phenomenon, as well as ADAR’s substrate features still remain unknown. In this work, we summarize the major computational aspects of predicting and understanding RNA editing events. We also investigate the detection of short motif sequences potentially characterizing RNA editing signals and the use of a logistic regression technique to model a predictor of RNA editing events. The latter, named AIRlINER, an algorithmic approach to assessment of A-to-I RNA editing sites in non-repetitive regions, is available as a web app at:  In recent times, there has been a change in the range of research on many types of diseases. In the past decades, the principal aim was to add information about the molecular pathways involved in some disease through the study of DNA mutations. Lately, the focus has indeed moved to the analysis of post-transcriptional modification events, such as RNA editing. The knowledge that the activity of RNA editing is higher in mammalian brain than in other tissues  RNA editing is now considered the most predominant in mammalians , as seen above. In those cases, up to 60% of adenosines could be edited  based pipelines, have led to important advances, allowing the discovery of a large amount of editing sites in the human transcriptome. Despite the enormous efforts made in recent years, the real biological function underlying such a phenomenon, as well as ADAR’s substrate features still remain unknown.In this work, we give an overview of the current state of knowledge on the editing phenomenon, as well as provide the main features of editing sites as highlighted today. We also investigate, inspired by previous results, methods for the detection of signals characterizing editing events and the prediction of novel A-to-I editing sites in non-repetitive regions. These techniques are based on the analysis of nucleotide profiles within a distance-radius of the probable editing site. Results on the signal detection show that editing sites may not have strong defined signal patterns.InosinePredict   based on the distances between non-Alu editing site, as described below. Next, we applied MEME .In order to validate the filtered motifs, we performed a permutation test using 100 samples of 1,000 randomly taken 3′ UTR sequences (hg19) with masked repetitive regions. As shown in Table Starting from the idea proposed by Pinto et al. , we usedIn order to train our method, we built a dataset composed of 30,280 sequences of 21 nt centered on an adenosine, from the human genome (hg19). According to their provenance, our dataset can be divided equally into two sets: known editing sites and random sites. For the purpose of retrieving known editing sites in non-repetitive regions, only human sites which do not have any repetitive elements in their flanking regions of 2,000 nt were selected from the RADAR database  and P’ can be computed: the first one corresponds to the probability of finding nucleotide j in position i of a region affected by editing, while the second one represents the probability of finding nucleotide j in position i of an un-ER. Starting from these probabilities, we computed the graphs in Figure From such a dataset, two probabilities s be a nucleotide sequence and P(s) its editing probability, using the previously defined probabilities we are able to train a logistic regression model such as:s[i] is the i-th nucleotide in a sequence. Now we can use this model to estimate the editing probability of any sequence of 21 nt centered on an adenosine, and if such probability is >0.5, we can say that such a sequence may be affected by editing.Therefore, let InosinePredict, we used a threshold to establish the presence or absence of editing in a specific sequence. Such a threshold was set to 9.6% for InosinePredict, as shown in Eggington et al.  of 0.5072, while AIRlINER reaches 0.7466. In Figure InosinePredict. Such a variant computes the editing probability of an adenosine by considering its flanking region of 4 nt. This comparison shows that our strategy is superior to InosinePredict even when the prediction is calculated from this same region around an adenosine.Further confirmation of the quality of our methodology is represented by the receiver operating characteristic curves (ROCs), Figure InosinePredict. As further confirmation, we also computed the AUC, which amounts to 0.6763 for AIRlINER, and 0.4498 for InosinePredict.Furthermore, we investigated that ADAR acts on each editing site in our training set by building an additional data set from editing sites experimentally identified in . We then applied the two methodologies and checked how many of them are correctly identified. AIRlINER is able to predict 42 of 52 editing sites and 5 of 7 non-editing sites while http://alpha.dmi.unict.it/airliner/.AIRlINER is available as a web app at the following URL: RNA editing is a post-transcriptional phenomenon that occurs in eukaryotes and contributes to the diversity of transcriptome. A-to-I is the most common form of RNA editing in mammals, altering the sequence of primary RNA transcripts by adenosine deamination. In this last decade, computational methods and RNAseq based approaches to RNA editing discovery have emerged, contributing to the identification of more than a million editing events in human, many of which located close to or within Alu repeats. Despite the enormous efforts made so far, the biological significance of the editing phenomenon remains largely unknown.In the first part of this work, we summarized some of the most important characteristics discovered for RNA editing. Inspired by literature, we investigated the presence of motifs in non-repetitive regions characterizing the editing events, finding a small set of candidates. Moreover, we considered the frequency of the 20 nt centered on each RNA editing site to compute the probability that an adenosine in a non-repetitive region of the genome may be affected by the A-to-I editing phenomenon. Our method, available on line, significantly reduces the number of false negatives with respect to existing methods, thus indicating a better editing-site prediction quality.Future work will concern the use of different motif-detecting algorithms to confirm the consistency of our current findings. Motif detection methods may make use of information from the secondary structure of the editing regions with respect also to the different classes of ADAR. Finally, further investigation is needed to highlight any significant combination of motif patterns.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.http://www.frontiersin.org/Journal/10.3389/fbioe.2015.00018/abstractThe Supplementary Material for this article can be found online at: Click here for additional data file.


A large comparative genomic sequence study has determined the extent of conservation between RNA editing sites within the mammalian evolutionary tree.http://genomebiology.com/2014/15/1/R5See related research by Pinto et al.,  Drosophila melanogaster uncovered a phylogenetic signature of RNA editing [cis-regulatory elements should be highly conserved across Drosophila species. Indeed, cis-elements that promote imperfect dsRNA formation in pre-mRNA, also known as editing complementary sequences (ECS), usually found in introns, are highly conserved  . These e editing . Since Ad Figure a. It is Drosophila transcriptomes. Geographically, editing sites are found in both coding regions (exons) and in non-coding regions  throughout genomes. Another theme from the deep-sequencing era is that much of the informational content of genomes is transcribed into non-coding RNA, whose functions largely remain to be determined. Comparison of RNA editing landscapes between different genetic model organisms has uncovered diverse ADAR substrates and revealed discrepancies within RNA editing systems. While the number of exonic editing sites that lead to non-synonymous amino acid substitutions (genomic recoding) varies significantly across a broad range of organisms, a common theme seems to be emerging. The majority of RNA editing sites are located in non-coding regions within genomes. For example, in the human genome, RNA editing sites are highly over-represented in Alu elements restricted within introns of transcribed genes [Alu elements are lineage-specific repeat genomic sequences, which participate in dsRNA template formation acting as ADAR substrates . In addition, most of the non-coding ESS editing sites (22/59) occur in transcripts of genes that are also edited elsewhere in their coding sequence. Recent studies in Drosophila identified editing sites in ECS non-coding genomic elements [et al. showed that most of the ESS editing sites in non-coding regions are located in potential ECS elements. Furthermore, two of the ESS editing sites are found in miRNAs in agreement with the previously described regulation of miRNA biogenesis and function through RNA editing. Further analysis revealed certain features of the ESS editing set. First, the ESS editing sites display higher levels of expression when compared with the non-conserved editing sites set. Second, the ESS editing set exhibits higher levels of editing and, more importantly, these levels of editing display striking conservation across 15 mice strains and between human and mouse. These observations indicate that the editing levels of the conserved mammalian RNA editing sites are set within the evolutionary tree and that the precise ratios of edited/non-edited repertoires of protein products may contribute to the optimization of cellular physiology. Lastly, similar to the highly conserved RNA editing sites reported in Drosophila, the ESS editing sites are overrepresented in genes that play a pivotal role in nervous system functions such as synaptic release and ion transport. This observation suggests that natural selection acts through RNA editing to evolve RNA structures that are acted upon by ADARs to genetically recode the proteome associated with neurotransmission and thereby fine-tune brain physiology.Due to the degeneracy of the genetic code, RNA editing can cause both synonymous and non-synonymous changes. In elements ,9. Not set al. [in vivo in various animal models, thus uncovering functions of ESS single RNA editing events. Furthermore, the specific characteristics of the non-conserved set of RNA editing sites prompted Pinto et al. to propose that these events are simply a consequence of overactivity of RNA editing enzymes with no apparent evolutionary value. Certainly, particular specific RNA editing events are under intense selective pressure, yet all RNAs are structured to some degree due to the single-stranded nature of RNA. Many RNAs, from all classes, probably serve as poor ADAR substrates (Figure Abnormalities in the RNA editing pathway are associated with multiple nervous system disorders including schizophrenia, epilepsy, suicidal depression and amyotrophic lateral sclerosis . The conet al.  have thes Figure c. Low-leet al. open the doorway for identifying both the conserved and, perhaps equally interesting, non-conserved species-specific RNA editing events that have shaped, and been shaped by, evolution.Multiple reports suggest that the RNA editing pathway is highly sensitive to external and internal stimuli such as temperature and inflammation. Therefore, future studies should aim to investigate how these two different sets of mammalian RNA editing sites respond to alterations of environmental stimuli. Non-conserved RNA editing events within mammalian lineages could represent variations in how RNA editing reshapes a specific transcriptome/proteome in response to external or internal changes in the environment. Such editing sites could represent derived characters, as such, which could then be interpreted as molecular adaptations in cellular functions. Studies such as that by Pinto ADAR: Adenosine deaminase acting on RNA; A-to-I: Adenosine to inosine; cDNA: complementary DNA; dsRNA: double-stranded RNA; ECS: Editing complementary sequence; ESS: Evolutionary selected sites; miRNA: microRNA.The authors declare that they have no competing interests.