We propose and define a reservoir offset voltage as a voltage commonly applied to both reservoirs of a quantum dot and study the functions in p-channel Si quantum dots. By the reservoir offset voltage, the electrochemical potential of the quantum dot can be modulated. In addition, when quantum dots in different channels are capacitively coupled, the reservoir offset voltage of one of the QDs can work as a gate voltage for the others. Our results show that the technique will lead to reduction of the number of gate electrodes, which is advantageous for future qubit integration. In addition, the mature conventional complementary metal–oxide–semiconductor (CMOS) fabrication process can be applied for Si QD fabrication, which should be advantageous for large-scale qubit integration6. Recently, several research groups have been studying various Si QD structures toward the integration of Si spin qubits12. One issue for the integration is that increasing the number of gate electrodes per qubit leads to increasing the number of wires from room temperature, which conflicts the limitation of space for wiring at cryogenic temperatures. In addition, characteristic variation among qubits will also become a problem for the integration14. To tackle these problems, we proposed and utilized a reservoir offset voltage which is a voltage commonly applied to both reservoirs of a QD. In the study of transistors, this voltage is understood to work as a relative gate voltage. Here, we apply the technique to QDs and thereby demonstrate the use of the reservoirs of a QD as gate electrode. We believe that the technique leads to a reduction of the number of gates without complicating structures.A spin in a Si quantum dot (QD) is an attractive system for implementing quantum information processing because it has a small qubit size and relatively long coherence times which come from a low abundance of nuclear spins in natural Si21, which enable the potential modulation methods using the reservoir offset voltage by taking advantages of the strong, sharp quantum confinements. In the present study, we confirm the operating principle of the reservoir offset voltage by simulation and applied the technique to p-channel QD devices. In p-channel Si QDs, hole spin manipulation is possible only with AC electric fields thanks to strong spin–orbit couplings of holes, which is advantageous for future qubit integration25. At first, we perform a band structure simulation to investigate the detailed mechanism of the reservoir offset voltage technique. Next, we experimentally demonstrate potential energy tuning in QDs by the reservoir offset voltage at 4.2 K and confirm that the operating principle shown in the simulation can explain the experimental results.Our group has been fabricating physically defined Si QD devices21. At first, a 40 nm-thick silicon-on-insulator (SOI) substrate is etched to form single QD (SQD), double QD (DQD), and side gates (SGs) by reactive ion etching technique after electron beam lithography. Next, following thermal passivation of the Si surface, a 75 nm-thick SiO2 layer and then a poly-Si top gate (TG) are deposited by low-pressure chemical vapor deposition technique. Then, to create Ohmic contacts, boron ions are implanted into SOI layer except for the part of SOI which is covered with TG with the accelerating voltage of 22 keV and a doping density of Figure 28. Here, we performed simulation using a simple p-channel MOS field effect transistor (MOSFET) model to study the changes in the energy bands and the number of holes induced in the reservoirs by the reservoir offset voltage  and 100 mV (orange line). We found that the threshold voltage shifts by about 100 mV. This is because the reservoir offset voltage causes a potential difference between the channel and the gate. In this case, the positive reservoir offset voltage is applied such that it accumulates holes. Typically, in MOS-based QD devices, Coulomb oscillations appear in the threshold region34. Therefore, the offset bias effect is confirmed for Vg fixed close to the threshold voltage in the calculation of the energy bands. The valence band edge EV, the conduction band edge EC, and the Fermi level EF at Si surface along the channel direction at Vg = 0 V are calculated with changing Voffset from 0 to 100 mV as a simulation parameter. The results obtained for Voffset = 0 mV (black), 50 mV (red), and 100 mV (orange) are shown in Fig. y axis by the positive reservoir offset voltage; in addition, the energy difference ∆E between EV and EF also changes at the same time. The number of induced holes at the Si/SiO2 interface depends on ∆E. Figure E at the center of the channel on Si/SiO2 interface as a function of the reservoir offset voltage Voffset for Vg = 0 V and Vbias = 4 mV. It turned out that the increase of Voffset reduces ∆E and thus increases the number of holes induced in reservoirs , are applied to the SQD (DQD), and thereby, peak positions of the SQD (DQD) characteristic are shifted to positive Vg_DQD direction as the reservoir offset voltage increases. Considering from the simulation results in Fig. Voffset1 of 0 mV (red star in Fig. Next, we experimentally demonstrated the potential modulation in p-channel QD systems by the reservoir offset voltage at a temperature of 4.2 K. Figure Voffset1 of 50 mV is applied, changing from the condition at the red star, a positive reservoir offset voltage shifts the Fermi levels into the direction that the hole number in the QD increases, which plays the same role as a negative gate voltage. On the other hand, the positive reservoir offset voltage accumulates holes in reservoirs and works like a positive gate voltage for the QD as well, through Coulomb repulsion (green circle in Fig. When Voffset1 of 50 mV, 18 and 18. This is the principle of the potential modulation function of the reservoir offset voltage. The potential modulation function will facilitate the realization of the single-hole limit; it can reduce the number of holes while lowering the tunnel barrier heights. On the other hand, a side gate voltage can also reduce the number of holes but increases the barrier heights. This difference comes from the sign of the applied voltages and indicates an advantage of the reservoir offset voltage technique.In order to know how much energy shift occurs by reservoir offset voltage, a positive SG voltage is applied to compensate the energy shift. When the SG voltage compensation and the reservoir offset voltage are applied, the same Coulomb peak as without SG voltage compensation and reservoir offset voltage appears (blue triangle in Fig. Voffset1, and they disappear as Voffset1 increases, in analogy with SG voltage dependence. In our device, the DQD and SQD are physically isolated from each other but still electrostatically coupled. Therefore, as pointed out in Fig. Voffset1 is considered to induce the gating effect by hole accumulation in the reservoirs of the SQD. From these results, we confirmed that not only SGs but also a QD can be used to tune the potential of another QD by applying the reservoir offset voltage, possibly leading to further reduction of the number of gates.To observe the other function of the reservoir offset voltage, gating function, we performed another measurement. In the measurement, we applied a reservoir offset voltage to an SQD and monitored the current flowing through the nearby DQD. Here, we expand the operating range of the reservoir offset voltage to hundreds of millivolts for visibility of the gating function. Figure 36.In conclusion, we study the functions of the reservoir offset voltages from simulation and experiments for physically defined p-channel Si QDs. We demonstrate that the reservoir offset voltages control the potentials of an SQD and a DQD relatively to the Fermi level, respectively. In addition, we observe that the reservoir offset voltage to the SQD works as a gate voltage for the adjacent DQD through Coulomb repulsion due to accumulated holes in the SQD reservoirs. From these results, we conclude that the reservoir offset voltage can lead to reduction of gate electrodes and/or flexibility of control in physically defined Si QD devices. We believe that this technique is advantageous also for other QDs based on different semiconductors, with strong isolation such as physically defined and nanowire-based QDs


The chemical modification of ribonucleotides plays an integral role in the biology of diverse viruses and their eukaryotic host cells. Mapping the precise identity, location, and abundance of modified ribonucleotides remains a key goal of many studies aimed at characterizing the function and importance of a given modification. While mapping of specific RNA modifications through short-read sequencing approaches has powered a wealth of new discoveries in the past decade, this approach is limited by inherent biases and an absence of linkage information. Moreover, in viral contexts, the challenge is increased due to the compact nature of viral genomes giving rise to many overlapping transcript isoforms that cannot be adequately resolved using short-read sequencing approaches. The recent emergence of nanopore sequencing, specifically the ability to directly sequence native RNAs from virus-infected host cells, provides not just a new methodology for mapping modified ribonucleotides but also a new conceptual framework for what can be derived from the resulting sequencing data. In this minireview, we provide a detailed overview of how nanopore direct RNA sequencing works, the computational approaches applied to identify modified ribonucleotides, and the core concepts underlying both. We further highlight recent studies that have applied this approach to interrogating viral biology and finish by discussing key experimental considerations and how we predict that these methodologies will continue to evolve. N6-methyladenosine (m6A), first discovered in 1975  and a range of RNA polymerase II accessory proteins  along with a variety of hnRNPs and multiple members of the IGF2BP family  sequence contexts, most DRACH sequences are not modified , N6,2′-O-dimethyladenosine (m6Am) (–5C) (1A) (–7G) (–O-methylation (Nm) (–http://genesilico.pl/modomics) (Since the discovery of pseudouridine (ψ) in 1957 . Despite3– in 1975 , 13. Thi in 1975 , long in in 1975 , primary in 1975 , 16. Forproteins –19. m6A P family –23. m6A  and FTO –26. Whilmodified . m6A hasnd decay , 28–32. e (m6Am) –36, 5-mem) (–5C) , 38, 1-m5C) (1A) –41, 7-meA) (–7G) –44, and ion (Nm) –47. For 6A installed on host and viral mRNAs has been shown to have both proviral and antiviral effects  , and N4-acetylcytidine (ac4C), have all been shown to be installed on viral mRNAs  , 62 and S-CoV-2) . Other R viruses . These m viruses .6A were published (6A-Seq (m6A sequencing), these techniques combine immunoprecipitation with antibodies against m6A and subsequent short-read (Illumina) sequencing to enrich for RNA fragments containing m6A, prepared in parallel with either a nonspecific or no immunoprecipitation control. Once sequenced, reads from m6A-containing RNA fragments are enriched over the background control at m6A sites and provide a resolution range of 50 to 200 nucleotides (nt). These studies were the first to determine that m6A modifications are both abundant and enriched within long internal exons and in 3′ untranslated regions (UTRs). This was later followed by newer antibody-dependent protocols such as miCLIP-Seq   (6A-label-seq (a metabolic labeling method to detect mRNA m6A transcriptome-wide at base resolution)    , m6A-labolution) , m6A-SEA method) , and m6Auencing)  provide proaches , 75, as proaches . While t5  potential sequence combinations that must be considered during base calling. Add in just a few modified ribonucleotides such as m1A, m6A, and pseudouridine, and the number of sequence combinations changes to 75 . There thus remains a burden on finding alternative approaches to detecting RNA modifications in DRS data sets, a challenge that has been embraced by the wider scientific community. At the time of writing, nanopore DRS approaches had been used to detect a wide range of RNA modifications, including m6A, internal m7G, m5C, Ψ, Nm, and 5-hydroxymethylcytosine (5hmC)  described a first approach to sequencing the full length of native RNA molecules extracted from a cellular context . They te82–e (5hmC) . This wae (5hmC) .6A) compared to an identical data set in which the modification is absent (in vitro-transcribed (IVT) RNA. Putative modified ribonucleotides are subsequently identified through one or more statistical tests, usually based on contingency tables  at each position across a set of identical reads, one can identify hot spots of increased error rate. However, hot spots may also originate from natural within-sample polymorphisms and the presence of homopolymers, as well as stochastic factors. To correct for this, most error rate approaches utilize a comparative strategy in which hot spots are considered real only if they appear in a data set known to contain a given modification  to predict m6A modifications at RRACH motifs within yeast strains (6A within circular RNAs (circRNAs) , with resulting area under the receiver operating characteristic (ROC) curves (AUCs) ranging from ~0.54 to 0.92 . Eligos2 was subsequently used to demonstrate that the sequence contexts of putative m6A sites identified in yeast and human data sets were enriched for DRACH motifs  of >1 in control versus treatment samples are classified as methylated. The authors applied DiffErr to study m6A in Arabidopsis thaliana with 66% of predicted sites being within five bases of a miCLIP peak  . AnotherircRNAs) . P valueH motifs . DRUMMERH motifs  that is LIP peak .6A detection. JACUSA2 considers three potential events that may arise from errors  and examines only 5-mers with a central A . This results in a 30-feature matrix  that subsequently undergoes dimensionality reduction to identify characteristic patterns of m6A modifications. Using a comparative approach, the authors identified multiple m6A sites located in DRACH sequence contexts, and when this was extended to focus on the EEF2 gene locus, they reported both a novel and previously identified m6A site .Signal-level approaches detect modified ribonucleotides by directly leveraging the raw electrical signal information collected during nanopore sequencing runs. As a first step, every signal-level approach requires “resquiggling” of the data. Resquiggling describes the process by which the raw signal for each individual read is dissected into “events” that are overlaid onto read alignments by using specialist algorithms included in the nanopolish  and Tombde novo, and sample comparison. For DRS data sets, the sample comparison approach is specifically recommended and provides two models for analysis (i) model_sample_compare, and (ii) level_sample_compare. These methods compare two sets of reads to identify differences at each reference position based on signal-level distributions by using standard univariate statistical tests, i.e., the KS test, the U test, and the t test. While the original presentation of this tool focused on DNA modifications, Tombo has recently been used to look at m5C modifications in the transcriptomes of porcine reproductive and respiratory syndrome virus  before analysis of m6A in yeast and human RNAs. Conceptually similar to Nanocompore, xPore also uses a GMM to compare differences in signal intensity (but not dwell time) between modified and unmodified data sets , using DRS from wild-type (WT) and METTL3 knockout (KO) HEK293 T cells, and they obtained an AUC of 0.86. However, when the analysis was extended to all k-mers, the rate of false positives increased. nanoRMS utilizes signal intensity, dwell time, and base quality/probability information to perform either unsupervised or supervised clustering that assigns reads into modified and unmodified groups. When running a supervised clustering method, which is generally suited to low-stoichiometry contexts such as m6A on mRNA, comparative data sets  are required. By contrast, unsupervised clustering is used to predict RNA modifications in a single sample alone. The limitation is that this is generally able to predict only specific RNA modifications in high-stoichiometry contexts, e.g., pseudouridine in rRNAs. In the original publication, nanoRMS processed comparative DRS data sets to predict pseudouridine modifications within yeast RNAs and, further, identified two new pseudouridines in yeast 15s mitochondrial rRNA  and may be particularly useful for screening data sets and generating preliminary analyses. The first of these, MINES, specifically detects m6A modifications by harnessing Tombo’s de novo algorithm by filtering putatively modified sites to keep only those located within a 30-nucleotide window centered within a DRACH motif . The stoichiometric values obtained postfiltering were combined with publicly available miCLIP results to train a classifier. The prediction accuracy of the classifier ranged from 67 to 83% and was heavily reliant on DRACH sequence contexts. Nanom6A extracts features such as the median, mean, and standard deviation of signal for each 5-mer and uses these to train an ensemble learning model on RRACH motifs   -obtainedon calls . Trainin DiffErr  was initCaenorhabditis elegans, Drosophila melanogaster, and human fecal bacteria were split into two subsets. For each sample, half underwent Illumina bisulfite sequencing to map pseudouridine sites  which were used as training labels, while the other half underwent nanopore DRS sequencing to obtain training features. After filtering for pseudouridine sites that passed a read coverage of 20, 640 modified and 689 randomly selected unmodified U sites were used for training. This resulted in an AUC of 0.938 on the test data set, with downstream analysis on HeLa cells (in the presence/absence of interferon treatment) further validating their results.Penguin focuses on detection of pseudouridine and extracts 5-mers, mean, standard deviation, and length of signal. 5-mers are further filtered to retain only those containing a uracil at the center . A gold Taken together, it is clear that a wealth of methodologies exist by which DRS data sets can be used to identify putatively modified nucleotides. The choice of error rate versus signal-level approaches offers researchers semiorthologous approaches with which to analyze the same data set. However, caution must be applied here, as a recent study demonstrated that both error rate and signal-level approaches have “blind spots” that may result in potential false negatives  . Moreove5C) in both the conserved leader sequence (LS) and downstream open reading frames (ORFs). The validity of the reported signal has not, at the time of this writing, been confirmed by orthologous approaches . The subsequent emergence of the betacoronavirus SARS-CoV-2 in late 2019 led to a rash of studies aiming to identify and characterize the role of RNA modification in coronavirus biology  controls, suggesting that these are false positives. A second study soon followed in which a small number of sgRNAs from SARS-CoV-2 and the related human betacoronavirus HCoV-OC43 were shown to harbor m6A modifications. The first of these utilized DRUMMER and Eligos2 to perform comparative analyses of DRS data sets derived from SARS-CoV-2 (A549+ACE2) and HCoV-OC43 (MRC-5)-infected cells that were treated with either a specific METTL3 inhibitor or a noninhibiting control  , while the loss of modified ribonucleotides from the viral RNAs was determined by a comparative analysis of infections of normal human dermal fibroblasts (NHDFs) with an HSV-1 wild type or an ICP27 null mutant. The comparative analysis was performed using an alpha version of DRUMMER, which reported that only around 25% of modified sites were located within or proximal to AC dinucleotides within DRACH motifs. It was thus inferred, but not validated, that the remaining sites represent other modified ribonucleotides.Beyond human coronaviruses, the use of nanopore DRS in detecting viral RNA modifications has thus far been limited, with just two studies published to date , 116. ThAs is demonstrated above, the breadth and depth of computational approaches for detecting modified ribonucleotides in nanopore DRS data present virologists with a wide range of analytical options but also require a careful consideration of the underlying aims of individual experiments and the resulting data quality. Based on our own experiences with adenoviruses, herpesviruses, and betacoronaviruses, we have curated a list of the following parameters that we consider to be critical for consideration in the design and execution of nanopore-based RNA modification studies in viral contexts.RNA modification detection tools require that DRS data sets are aligned against the transcriptome of the organism of interest. In viral contexts, this remains problematic, as very few viruses possess high-quality annotations. In the absence of such annotations, alignment of DRS reads often produces a subset of artefactual results in which the annotation for a given sequence read does not exist and leads to a subset of reads being assigned to an alternative transcript isoform instead. This typically hinders RNA modification analysis through the generation of false-positive and/or false-negative results. This can be remedied by either (i) generating a new high-quality transcriptome annotation or (ii) limiting the analysis to the exome level . The former remains a complex, time-consuming, but ultimately valuable undertaking that can be partially accomplished using computational annotation tools such as StringTie2  and FLAIRegardless of whether pursuing exome- or isoform-level alignments, filtering of DRS read alignments prior to RNA modification detection can significantly improve sensitivity and accuracy. Standard measures should include screening for and removing adapter sequences from DRS reads, as well as removing secondary and supplementary alignments. This latter measure may also include rejecting individual reads with multiple primary alignments . A further step that is particularly relevant for isoform-level  analyses involves removing all primary read alignments that do not extend to within 50 nt of the defined 5′ end of a given transcript.The use of at least two biological replicates per condition is recommended. Several tools have inbuilt support for such analyses , while others require additional scripting to merge results from individual analyses. The principal benefit of including biological replicates is to enhance the identification of consistently modified sites while also providing measures of stochastic variation.6A, inhibition of METTL3 enzymatic activity or the generation of METTL3 conditional knockout cell lines significantly enhances sensitivity relative to RNA silencing strategies. Error rate analysis tools are particular insensitive to RNA silencing strategies, presumably due to reduced stoichiometric differences between conditions. The use of IVT RNAs is another increasingly popular strategy, although this generally limits comparative approaches to reporting the presence/or absence, but not the identity, of all modifications within the RNA isoform being compared.Comparative analyses rely on comparing conditions in which a given modified ribonucleotide is present at differing levels. In our experience with mChoosing the right tool for a given analysis is a complex process. Read depth is a critical factor for several tools  , 107. Ot6A) in the coming years. This is driven by ongoing improvements in the DRS chemistry that will further reduce error rates and make modified ribonucleotides easier to distinguish from their unmodified counterparts. Whether such improvements will ultimately limit the utility of error rate approaches to RNA modification detection remains uncertain. We further anticipate that computational approaches for RNA modification detection will increasingly focus on the accurate measurement of stoichiometry, through both refinement of existing tools such as Nanocompore, xPore, and nanoRMS and the development and release of novel tools.The field of nanopore sequencing is moving rapidly, pushed by constant biological and computational innovations. As noted above, native support for the identification of several DNA modifications was recently integrated into Guppy, and it is reasonable to expect similar support for some RNA modifications . Such developments would also place within reach the ultimate goal of identifying the presence, identity, and specific location of modified ribonucleotides within individual RNA molecules.In looking further toward the future, we expect that comparative analysis approaches for profiling RNA modifications will eventually become defunct, replaced by a combination of native detection during base calling and the use of advanced signal-level algorithms capable of reporting multiple different types of RNA modifications within a single analysis (e.g., mTo conclude in the context of viral RNA biology, the key limitation at present remains the general lack of well-annotated transcriptomes. Without these, viral RNA modification studies will be restricted to exome-level analyses that lack resolution. While resolving this will take time, it is notable that an increasing number of studies are addressing this issue across the viral spectrum , 119–123119–


Small RNA sequencing (sRNA-Seq) approaches unveiled sequences derived from longer non-coding RNAs, such as transfer RNA (tRNA) and ribosomal RNA (rRNA) fragments, known as tRFs and rRFs, respectively. However, rRNAs and RNAs shorter than 16 nt are often depleted from library preparations/sequencing analyses, although they may be functional. Here, we sought to obtain a complete repertoire of small RNAs by sequencing the total RNA from 11 samples of 6 different eukaryotic organisms, from yeasts to human, in an extended 8- to 30-nt window of RNA length. The 8- to 15-nt window essentially contained fragments of longer non-coding RNAs, such as microRNAs, PIWI-associated RNAs (piRNAs), small nucleolar RNAs (snoRNAs), tRNAs and rRNAs. Notably, unusually short RNAs < 16 nt were more abundant than those >16 nt in bilaterian organisms. A new RT-qPCR method confirmed that two unusually short rRFs of 12 and 13 nt were more overly abundant (~3-log difference) than two microRNAs. We propose to not deplete rRNA and to reduce the lower threshold of RNA length to include unusually short RNAs in sRNA-Seq analyses and datasets, as their abundance and diversity support their potential role and importance as biomarkers of disease and/or mediators of cellular function. Studies in the 1990s related to small non-coding RNAs (sRNAs)  were scaNowadays, several sRNA families, such as PIWI-associated RNAs (piRNAs) , small nRecently, a plethora of studies, made possible by the use and the development of high-throughput sequencing (HTS) , have idSmall RNA sequencing (sRNA-Seq) approaches are designed to determine sRNA sequences and their relative abundance, which depend on the method used for library generation ,26. For Although some sequences shorter than 16 nt are degradation products, several might still be functional. Our laboratory previously reported the serendipitous discovery of a 12 nt semi-microRNA (smiRNAs) able to prevent the repression induced by the microRNA from which it originated , suggestThe limitations we are facing in small RNA research are those we impose on ourselves and the technologies we are using rather than the technologies themselves. To challenge the current dogma of restraining our view and interest to RNA species longer than 16 nt, we lowered the 16-nt threshold to 8-nt, which is still arbitrary, while keeping the upper 30-nt limit.The focus of the present study was to gather evidence about the differential enrichment of the small RNAs in the 8- to 30-nt range and to further highlight the existence of 8- to 15-nt RNA species, by sRNA-Seq analysis of 11 different biological samples from 6 different species, from yeast to human, thereby providing an unprecedented view of unusually short RNAs in eukaryotes.We have pursued the analysis of some of the results we have obtained and recently reported the identification of a new family of unusually short RNAs mapping to ribosomal RNA 5.8S, which we named dodecaRNAs (doRNAs), according to the number of core nucleotides (12 nt) their members contain .We hope that sharing our approach, findings, and complete datasets of eukaryotic RNA species between 8 and 30 nt in length, especially those in the 8- to 15-nt window, will stimulate research in that new area of unusually short RNAs.A. thaliana  were more abundant than 13-nt RNAs  [The 17- to 19-nt peak  observedSNORD30 . It was (HEK293) . SnoRNAs(HEK293) , but theAssessment of RNA sequence diversity through the analysis of unique sequences revealed that the relatively abundant 12- and 13-nt sequences were not correspondingly diverse, as shown by their relatively lower content in unique sequences . Indeed,S. pombe  to unusually short sRNAs found in the 8- to 15-nt window, both in terms of sequence and relative abundance. Even if the first window  was twice as large as the smaller  and contained the well-known family of microRNAs, we found a higher abundance of RNAs in the 8- to 15-nt window in mouse and Drosophila samples G,H. Thisrevisiae I,J, whiles pombe J.Although the number of samples we analyzed is small, it seems that in bilaterian organisms unusually short RNAs are particularly conserved and more abundant than sRNAs found in the window of 16- to 30-nt standard-length, while the opposite trend was observed in yeasts and plant. However, we did not observe this pattern in terms of diversity, as represented by the number of unique reads .We then performed analyses of conserved RNA sequences between the bilaterian species , as they might give some indications of their functionality. We obtained 181, 46, and 28 sequences shorter than 15-nt from conserved rRNAs, tRNAs, and microRNAs, respectively . The conSequences obtained by sRNA-Seq were first annotated by mapping against downloaded databases of defined sRNA classes, including, among others, rRFs, tRFs, snoRNAs, microRNAs, and the piRNAs, providing an unprecedented, systematic analysis of RNA species from six eukaryotic organisms and between 8- and 30-nt in length.As observed in the nearly 2000 small RNA libraries listed by Li et al. , analysiHowever, a high level of RNA diversity was observed in the 19- to 24-nt range, as reflected by the large number of unique sequences found among all species in which microRNAs are found . Thus, bOur data suggest that, although the preparation of an 8- to 30-nt library may not be the best to study only 19- to 24-nt RNAs, such as microRNAs, it allows a comparison of their relative abundance versus the other sRNAs detected, including their derived fragments, such as semi-microRNAs for microRNAs. Moreover, as these sequences are more abundant than microRNAs, it may facilitate their detection and use as biomarkers. However, their length poses a challenge to their rapid detection and their accurate quantitation.The microRNA and their fragment reads were almost not detectable in the 8- to 15-nt window A–C, whilLength distribution plotting of the reads mapping to microRNA sequences unveiled a large abundance of 19- to 24-nt RNAs A that waIn total, we discovered between 886 and 3705 unique microRNA-derived sequences in the 8- to 15-nt window, depending on the sample . ListingpiRNAs are a class of small non-coding RNAs of 24- to 30-nt initially identified as repressors of germ cell transposition ,41, and Mus musculus  dominates the 29-nt peak, constituting between 45% and 94% of the reads . SimilarThe three most abundant 9- to 12-nt sdRNAs detected in our samples are listed in Although these analyses do not confirm these sdRNAs to be functional or more than stable by-products, the preponderance of discrete unusually short sdRNAs in all of our samples, from yeasts to human, as well as their origin  in mouse, human, fly, and plant, or specific motif , support some specificity in the biogenesis process and/or a conservation mechanism, both of which deserve further investigations.tRFs are a rapidly growing class of non-coding RNAs, as several studies have contributed to improve our knowledge of their expression , biogeneOur study expands on the latter by reporting the presence of tRFs in all of our eukaryotic samples across the 8- to 30-nt window of RNA length . tRFs arTo get further insight into their family affiliation, biogenesis or mode of degradation, we grouped tRFs according to their sequence and aligned them on the shortest, common seed sequence , tRFs. WrRFs formed the most abundant class of RNA found in our sRNA-Seq datasets, representing between 16% and 95% of the reads in the 8- to 15-nt window, and between 9% and 70% of the reads in the 16- to 30-nt window . ExpansiAs we did with tRFs, we gathered all rRFs having a common motif or sequence together , rRFs. TSome rRF sequences exhibited a peculiar profile of abnormally high read counts .Heatmap analysis of rRF abundance according to their length confirmed the high abundance of 12-, 13- and 18-nt sequences , while miR-25 and miR-30a represented only 257 and 96 RPM, a ~3-log difference A. In mouWe have thus developed a specific and sensitive RT-qPCR method based on splinted 5′ ligation to detect two particularly abundant rRFs of 12 and 13 nt that differ by only a single nucleotide at the 5′ extremity . We usedRT-qPCR analyses of the same human and mouse samples that were previously analyzed by sRNA-Seq confirmed the existence of the 12- and the 13-nt rRFs, and their relative abundance to each other; the 13-nt rRF being 5 times more abundant than the 12-nt rRF in human samples B. More iTogether, the results obtained through the use of our new RT-qPCR detection method, tailored to monitor unusually short RNA species, allowed us to confirm our sequencing results, document the differential enrichment of 12- and 13-nt rRFs between human and mouse samples, and highlight their ~3-log higher levels of expression compared to individual microRNAs.Although the cellular role and function of the newly discovered, unusually short RNAs in this study have yet to be elucidated, our results support their presence as genuine, as confirmed and quantitated by RT-qPCR and as suggested by the accumulation of rRFs of discrete length in all the samples analyzed. Regardless as to whether these sRNAs are stable degradation by-products or fulfill a specific function within cells, their systematic removal from sRNA-Seq analyses definitely hampers their study and their characterization, and it contributes to perpetuating the concept that unusually short RNAs are devoid of interest and utility.However, it is necessary to relativize our results with respect to the potential bias introduced during the construction of the sequencing library. Indeed, although some unusually short sequences seem to represent a majority share in our results  was approved by our institutional human ethics committee (B14-08-2103). The participants provided their written informed consent to participate in this study, in accordance with the Declaration of Helsinki.This study was carried out in accordance with the guidelines, regulations, and requirements of the Canadian Council of Animal Care for Animals Used for Scientific Purposes. Experiments were performed in accordance with the latest guidelines and using a protocol approved by the Université Laval Animal Welfare Committee.2 and used between passages 2 to 6. Cultured human embryonic kidney 293  were maintained in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% (v/v) fetal bovine serum (FBS), 1 mM sodium pyruvate, 100 units/mL penicillin, 100 μg/mL streptomycin, and 2 mM L-glutamine in a humidified incubator under 5% CO2 at 37 °C.Human blood polymorphonuclear leukocytes (PMN) were isolated from venous blood collected from four healthy donors and pooled, as described in Laffont et al. . Human uMouse blood PMN were isolated from four healthy 12- to 15-week-old mice, as described in Duchez et al. , and pooAdult flies were purchased from the University of California in San Diego (UCSD) Drosophila Species Stock Center  and snap-frozen in liquid nitrogen before storage at −80 °C.Arabidopsis thaliana, accession Colombia (Col-0) was obtained from the ABRC . Seeds were sown in autoclaved Pro-Mix BX potting mix , watered with sterile distilled water (300 mL/pot/week), and placed in a growth chamber . After 7 days, seedlings of uniform size were transferred to pots containing Pro-Mix BX potting mix and grown for 14 days prior to being harvested for RNA extraction.® reagent or TRIzol LS® reagent for liquid samples , following the manufacturer’s recommendations. Contaminating DNA was degraded using DNase I  treatment.Total RNA samples were prepared using TRIzolFor primary blood PMN samples involving cell isolation, we used a pooling strategy involving equal mixing of total RNA samples derived from independent biological samples. Pooling of small RNA samples is effective in reducing data variability, and it reduces the number of replicates, hence lowering the cost for subsequent steps . For eacThe quality and the concentration of the total RNA samples were verified using a NanoDrop ND-1000  and gel separation . The sRNhttps://www.arraystar.com/, accessed on 17 May 2022) and refined using R (Free Software Foundation). Only the reads that were identical, both in length and in sequence, were considered as a unique read. TPM normalizations were not based on cell types—the increased number of chromosome/gene copies may contribute to increase the abundance of sRNAs in the cancerous HEK293 and N2a cell lines compared to primary cells.Clean reads matching the quality standards were processed to remove the adaptor sequence, leading to sRNA trimmed reads. All reports displayed here were generated through the standard analysis pipeline of Arraystar Inc.,   may hamper proper identification. Since the sequenced sRNAs may contain mismatches, and to allow detection of modified RNA species, such as those derived from tRNAs, rRNAs or piRNAs, we proceeded with our analyses by accepting one mismatch. Many piRNA sequences are actually derived from tRNA, or rRNA genes . To avoi® Green PCR Kits  in 96-well plates using the CFX96 Touch™ Real-Time PCR Detection System  and specific Custom LNA Oligonucleotides . doRNA, C-doRNA, microRNA-25 (miR-25), and microRNA-30a (miR-30a) copy numbers were determined with a standard curve built using synthetic RNAs . In compliance with the MIQE guidelines, the small nucleolar RNA U6 was used as a reference gene for normalization [This specific quantification method was set up, experimentally validated, and described in Lambert et al. . The spllization .


Genotoxic agents, that are used in cancer therapy, elicit the reprogramming of the transcriptome of cancer cells. These changes reflect the cellular response to stress and underlie some of the mechanisms leading to drug resistance. Here, we profiled genome-wide changes in pre-mRNA splicing induced by cisplatin in breast cancer cells. Among the set of cisplatin-induced alternative splicing events we focused on COASY, a gene encoding a mitochondrial enzyme involved in coenzyme A biosynthesis. Treatment with cisplatin induces the production of a short isoform of COASY lacking exons 4 and 5, whose depletion impedes mitochondrial function and decreases sensitivity to cisplatin. We identified RBM39 as a major effector of the cisplatin-induced effect on COASY splicing. RBM39 also controls a genome-wide set of alternative splicing events partially overlapping with the cisplatin-mediated ones. Unexpectedly, inactivation of RBM39 in response to cisplatin involves its interaction with the AP-1 family transcription factor c-Jun that prevents RBM39 binding to pre-mRNA. Our findings therefore uncover a novel cisplatin-induced interaction between a splicing regulator and a transcription factor that has a global impact on alternative splicing and contributes to drug resistance. By selecting which regions of the pre-mRNA are retained (exons) or removed (introns) to form the mature transcript, AS controls qualitative diversity of the transcriptome and expands the functional repertoire of the proteome. Pre-mRNA splicing is accomplished by the spliceosome, a large dynamic and complex molecular machine comprising 5 small nuclear RNAs and more than 300 proteins . AS takecterized ,3. Recencterized . Especiacterized . Howevercterized .e.g. breast and non-small cell lung cancers, colorectal adeno-carcinoma and acute myeloid leukemia among others and was recently implicated in sensitivity of cancerous cells to Indisulam, an anticancer sulfonamide  is an SR rich protein with two central RNA recognition motifs (RRM) and one C-terminal U2AF homology motif. Consensus on its specific RNA binding sequences has not yet been reached ,11. In afonamide . In addifonamide . RBM39 cfonamide ,20. The Treatment of cancer is still largely based on the use of chemotherapeutic drugs among which DNA-damaging agents such as cisplatin have held a prominent position for decades. Cisplatin, one of the most widely used anticancer drugs induces cell death through binding to genomic and mitochondrial DNA. It establishes inter- and intra-strand crosslinks affecting replication as well as transcription and leads to cell cycle arrest, apoptosis and ROS production by the mitochondria ,22.One of the main problems in chemotherapeutic treatments remains the acquisition of drug resistance by cancer cells along important side effects . UnderstDNA-damaging agents trigger a complex network of responses called the DNA-damage response (DDR) that culminates in dramatic reprogramming of gene expression, which mostly relies on NF-κB and p53 and leads to the activation of DNA-damage repair and tolerance processes and cell-cycle checkpoint pathways ,28. Recede novo biosynthesis of coenzyme A cofactor with its two catalytic domains: the 4’ -phosphopantetheine adenylyltransferase (PPAT) and the dephospho-CoA kinase (d-pCoAK) (Coenzyme A synthase (COASY), localised in mitochondrial membranes, carries-out the final two steps of the d-pCoAK) . Both std-pCoAK) ,38. Linkd-pCoAK)  (ii) it d-pCoAK)  and (iiid-pCoAK) .In this study, we attempted to uncover the molecular mechanisms by which DNA damage impacts splicing decisions in cancer cells and the functional contribution of DNA damage-induced splicing changes to cellular sensitivity to genotoxic drugs. As a prototypical model to address these questions, we identified genome-wide changes in mRNA splicing induced by cisplatin in breast cancer cells and characterized the underlying regulatory pathways and the functional relevance of AS to drug sensitivity.cis-diamineplatinum (II) dichloride (P4394)], camptothecin (C9911), doxorubicin (D1515), H2O2 (H1009) and etoposide (E1383) were purchased from Sigma-Aldrich . The stock solution of cisplatin (2.5 mM in water) was kept at –20°C and renewed every month. JNK-IN-8 (420150) was purchased from Calbiochem  and MitoTracker Red CMXROS (9082) from Cell Signaling Technology . RNAse A (740505) was from Macherey-Nagel . Accutase (L0950-100) was from Biowest . The list of primary and secondary antibodies used in this study is provided in Cisplatin . In our experimental conditions, cisplatin treatment led to 23% of cells being apoptotic after 24 h, a percentage that regularly increased with time (i.e. |log2 Fold Change (FC)| ≥ 1, adj P-value < 0.05 and transcripts per kilobase million (TPM) ≥ 1 in at least one condition), differential analysis of RNA levels between treated and non-treated cells revealed that a total of 2,310 RNAs were differentially expressed (DE) following cisplatin treatment, the large majority of which were mRNAs   and carried out a comparative RNA sequencing (RNA-seq) analysis with untreated controls. MCF-7 cells were chosen because they are considered relatively resistant to this genotoxic agent    Figure . The kno) Figure . Depletis Figure . The imps Figure . Becauses Figure .COASY and other representative c-Jun/RBM39-dependent a-SE was unaffected by the JNK-IN-8 inhibitor (n = 468) against the C3 transcription factor target gene set from the Molecular Signatures Database (MSigDB) and found no significant overlap for AP-1 related gene set. We then built our own set of 306 experimentally verified AP-1 dependent genes defined as the interaction between two publicly available lists, TREDD  associated with TFs such as p53 and NF-κB that coordinate expression of specific sets of genes  whose knockdown modified inclusion of E4–5 of COASY. Interestingly, the siRNAs with the largest effects (i.e. ΔΨ>20%) all led to a reduction in E4–5 inclusion, similarly to cisplatin. The majority of these siRNA were directed against members of the core spliceosome, including subunits of the SF3A , SF3B (i.e. SF3B4) and U2 auxiliary factor (U2AF) (i.e. U2AF1) complexes, all of which are associated with U2 snRNP, and PRPF8, a key spliceosome assembly factor. Three notable exceptions were i) SR-A1  a poorly characterized SR family protein, ii) MBNL1 (Muscleblind-like 1), a RBP known for its role in muscular dystrophy and, (iii) RBM39. RBM39 is a U2AF-related splicing factor that also plays a role in transcriptional regulation and translation .,83.COASYRBM39 is upregulated in most cancers and its inhibition is lethal or cytostatic in several cellular models of breast cancers . AlthougCOASY E4–5. Our findings also raise two corollary issues. First, not all cisplatin-induced a-SE are found in the set of RBM39-dependent events, suggesting that other RBPs might be involved in mediating the effects of cisplatin on AS. In addition, whereas RBM39 knockdown recapitulates a large proportion of the effects of cisplatin on SE, only a small fraction of RBM39-dependent a-SE events  are sensitive to cisplatin. Several non-exclusive mechanisms could underlie this specificity. For instance, cisplatin-mediated inactivation of RBM39 could occur only at specific cassette exons. Alternatively, RBM39- and cisplatin-dependent exons could be those that are the most sensitive to RBM39 presence or those whose splicing relies on multiple cisplatin-sensitive RBPs, in addition to RBM39. Along these lines, combinatorial control of alternative splicing by multiple RBPs during oxaliplatin-induced DDR has been reported  . Comparireported . The issOne of the most unexpected findings in this study relates to the mechanism by which cisplatin promotes inactivation of RBM39 splicing activity. Based on a limited number of published examples, the emerging trend is that the DDR achieves reprogramming of the splicing landscape by promoting post-translational modifications of splicing factors or modifying their expression levels or intracellular localisation . In our COASY pre-mRNA , more sophisticated modes of action are being described. For instance, TFs control splicing by interfering with RNA polymerase II elongation (‘kinetics’ model), by recruiting splicing effectors to sites of transcription (‘promoter or gene-body recruitment’ models) or more recently, by actively participating in splicing complexes ,7,90,91.A Figure , p53  and one U2AF homology motif  in its C-terminal region . While aOur study uncovers an entirely novel pathway and its associated molecular effectors that underly the splicing changes downstream of the DDR. Our results also illustrate how reprogramming of splicing processes allows expression of specific spicing isoforms, that functionally contribute to the DDR. In addition to COASY-short isoform, RBM39 and c-Jun, it is likely that other splicing variants, controlled by other SFs and TFs also contribute to DDR-related processes. Identification of these pathways in the context of oncogenic processes or drug resistance should allow the development of better therapeutic molecules integrating the multiple layers of gene regulation.https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE195842.RNA-seq data generated in this study have been deposited to GEO under accession GSE195842: gkac1130_Supplemental_FilesClick here for additional data file.


Distinguishing circular RNA reads from reads derived from the linear host transcript is a challenging task because of sequence overlap. We developed a computational approach, CiLiQuant, that determines the relative circular and linear abundance of transcripts and gene loci using back-splice and unambiguous forward-splice junction reads generated by existing mapping and circular RNA discovery tools. Circular RNAs (circRNAs) are a novel class of non-coding RNAs found in eukaryotic transcriptomes that result from a process called back-splicing during RNA maturation. In recent years, circRNAs are attracting considerable research attention and evidence of their involvement in normal development and disease has been reported . Due to https://github.com/OncoRNALab/CiLiQuant). For each gene, the pipeline classifies forward-splice junctions as having a linear or ambiguous origin based on their overlap with detected back-splice junctions  and NCI-H23  cells were cultured at 37°C, 5% CO2 in DMEM, low glucose, GlutaMAX Supplement, pyruvate  and RPMI 1640 Medium, HEPES , respectively. 10% fetal bovine serum (FBS)  and 1% Penicillin-Streptomycin   were added to both media. RNA was isolated from the cells using the miRNeasy Mini kit  according to the manufacturer’s instructions, including an on-column DNase treatment . After isolation, the RNA concentration was measured (NanoDrop) and the RNA quality was evaluated . For each cell line, the RNA was first pooled and then divided into two samples, each containing 1 µg RNA in 100 µL nuclease-free water. First, ribosomal RNA (rRNA) was removed with the NEBNext rRNA Depletion Kit , following the manufacturer’s instructions. Next, Ribonuclease R (RNAse R) treatment (RNR07250 (250 U), Lucigen) was performed according to our previously described protocol . In summNFATC3 in HLF cells. In the total RNA-sequencing data from HLF and NCIH23 cell lines, 20% of genes that have at least one forward-splice junction read have at least one back-splice junction read as well . For those genes with circular transcripts, we observed that the average of true linear counts per junction can be at least 2 times overestimated in 7–8% of the genes compared to the average of all forward-splice counts per junction obtained with STAR mapping (CiLiQuant determines whether detected forward-splice junction reads have an ambiguous (linear or circular) origin by looking at overlap with detected back-splice junctions . The cla mapping . The imp mapping . Similar mapping .CiLiQuant also calculates circular-to-linear fractions at both the gene and individual back-splice level . The bacRNase R digests linear RNAs while keeping circular RNA molecules intact. In https://github.com/OncoRNALab/CiLiQuant), platform independent and can be initiated using a single command. Other count-based strategies that determine circular-to-linear RNA ratios rely on the maximally expressed transcript or on splice reads flanking the circRNA  signal in aggregated gene counts. Any gene with partially overlapping circRNAs or multi-exon circRNAs potentially suffers from ambiguous reads. These reads are often mistakenly considered as read evidence for linear transcripts , this increased to 3 hours for 50 M paired-end read data . Parallelization is possible by splitting up the reference file, for example by chromosome.In conclusion, the CiLiQuant pipeline distinguishes linear only from potentially mixed junction reads and determines the circular contribution in RNA sequencing data in a systematic and uniform way.


Resonance frequency signatures were processed using fast Fourier transform in an attempt to differentiate between RNA (control) and RNA (BC) via frequency response. RNA (BC) demonstrated a characteristic signal at 0.02 GHz, as well as a phase shift at 0.031, and 0.070 GHZ from RNA (control). These features could offer early BC diagnosis. This is the first time to describe an optical methodology based on nonlinear polarization as a facile principle to distinguish and identify RNA alterations in BC by their characteristic fingerprint spectral signature.Different cancers are caused by accumulation of numerous genetic and epigenetic changes. Recently, nonlinear polarization has been considered as a marvelous tool for several medical applications. The capability of nonlinear polarization, to monitor any changes in RNA's spectral signature due to breast cancer (BC) was evaluated. Blood samples, from healthy controls and BC patients, were collected for whole blood preparation for genomic total RNA purification. Total RNA samples were stimulated with a light-emitting diode (LED) source of 565 nm; the resonance frequency of investigated RNA samples was captured and processed  Nonlinear polarization has been considered as a marvelous tool for several medical applications, and the capability to monitor any changes in RNA's spectral signature due to breast cancer was evaluated by hyperspectral camera. Mutations in several other rare susceptible genes for instance TP53, STK11, PTEN, and CHEK2 were found to contribute to induction of breast cancer.2 The genetic information, crucial for the identity and function of each eukaryotic cell, is stored in the DNA.3 The process of transcription generates RNA by using the genome as a template, depending on certain functional genomic elements.4 Genetic information on DNA is encoded by the four bases adenine (A), guanine (G), cytosine (C), and thymine (T).5 Cancer genomes are highly enriched with mutational signatures, which may be regarded as a type of base substitution  or as the deletion/insertion of one or more bases.6 Exposure to UV light can cause adjacent pyrimidines to dimerize, while oxidative damage can cause several lesions that are mutagenic if not repaired.7 Moreover, some of the hydrogen atoms on each of the four bases can change their location to produce a tautomer.8 An amino group (–NH2) can tautomerize to an imino form (–NH). Likewise, a keto group can tautomerize to an enol form.5 These mutations in BC genomes cause corresponding RNA alterations and modifications in the order of the transcribed purine and pyrimidine bases.6,9Breast cancer (BC) is considered the leading cause of worldwide cancer deaths in females.10 Dielectric properties of macromolecules  can be determined from light absorption and emission.11 This means that a macromolecule exhibiting anisotropies in light absorption/emission, will exhibit characteristic polarization properties.12Macroscopic level investigation of polarized light effects on total RNA can reveal information about structural bonds, electronic states, electronic alignments, and dielectric properties.Macromolecular polarization properties include:13❖ Depolarization: the ability to depolarize incident polarized light.14❖ Di-attenuation: the dependence of light transmission on the incident polarization state.15❖ Polarizance: the ability to polarize un-polarized incident light.16❖ Retardance: the ability to generate a phase shift in the electric vector of incident polarized light.via partial separation of positive and negative charges.17,18 The macroscopic equivalence of dipole moment is the polarization P.19N, e, and d were number of dipoles per unit volume, electronic charge, and displacement, respectively.20,21When the oscillating electric field is applied on macromolecules; the electric field induces dipole moment 22 The induced dipole simply re-emits electric field at the same frequency known as Rayleigh scattering.23,24 Linear spectroscopy cannot secure consistent information about macromolecule chemical structure (i.e. RNA disorder). Nonlinear spectroscopy is related to the interaction of intense light with matter.25 Laser sources, can secure high light intensities to modify material optical properties.26 Light waves can then interact with each other, exchanging momentum and energy.27 This interaction of light waves can result in generation of new optical frequencies.28 Intense irradiance can excite many molecules to the high-energy state. This yields vibrations at all frequencies corresponding to all energy differences.29 Nonlinear relationship between the polarization and the electric field appears only with strong fields with generation of new electric field, with new frequencies 2ω1, 2ω2, |ω1 + ω2|, and |ω1 − ω2|.30 The phenomenon where 2ω1 and 2ω2 frequencies are produced is called second harmonic generation (SHG).31 Sum frequency generation (SFG) occurred at |ω1 + ω2|. Difference frequency generation (DFG) occur at |ω1 − ω2| as shown in 32The induced dipole moment can exchange energy, and can oscillate at resonant frequency with the incident electric field.33RNA as macromolecules with an alternating electron donating and accepting groups can offer characteristic signature when stimulated with intense laser beam.34 It could be considered as a way to study these molecules and answer how their structure controls the functional events inside the cell. These modalities may assist researchers in designing scenes and find out how numerous factors powerfully interact.35Hyperspectral imaging at RNA level may provide innovative nonlinear signatures to assess RNA functions; such signature can monitor any RNA mutation due to BC.Thus, the current study describes an optical methodology based on nonlinear polarization for spatial and spectroscopic characterization of RNA samples from BC patients and healthy volunteers to determine their spectral fingerprint signature. Latest advances in hyperspectral imaging offered unique capability for precise measurements of nonlinear polarization signature. Blood samples from five healthy controls and five BC patients were collected for whole blood preparation for total RNA purification. Total RNA samples were illuminated with LED source of 565 nm; characteristic resonance frequencies of investigated samples were captured and processed using hyperspectral camera.2.2.1Five newly diagnosed BC female patients, who haven't received any chemotherapy or radiotherapy, were recruited from the clinical oncology clinic, Ain Shams University Hospitals, Cairo, Egypt. Diagnosis was based on mammogram and cell biopsy. The study also included five healthy age volunteers to serve as healthy control. Informed consent was obtained from every patient and the study was approved by the Ethical Committee of Research, Ain Shams University Hospitals. Furthermore, the study was carried out in accordance with the regulations and recommendations of the Declaration of Helsinki.2.2For each participant, two blood samples were collected on EDTA vacutainers for whole blood preparation. Whole blood was used for complete blood count determination and total RNA purification.2.2.1Hemoglobin (Hgb), red blood cell (RBC) count, total leukocyte count (TLC) and platelet count determinations were performed using Z2TM Coulter Counter®, Analyzer, Coulter Electronics, USA.2.2.2Total RNA was extracted and purified using a QIAamp RNA blood mini kit  according to the manufacturer's protocol. Quantitation and purity assessment was performed using the NanoDrop® (ND)-1000 spectrophotometer .2.3Nonlinear polarization can offer wealth of information about chemical and physical properties of RNA macromolecule. This approach can find attractive biomedical applications. 10 mW laser source working at 656 nm was focused using microscopic lens to illuminate investigated total RNA samples. The scattered and the re-emitted radiations were collected using hyperspectral camera .Scattered and re-emitted resonance frequency signals were processed using custom digital processing algorithm for frequency and phase domain analysis. The frequency and phase responses were calculated to discriminate RNA (control), and RNA (BC). The difference in resonance frequency signature and phase shift could be ascribed to RNA gene mutations due to BC.2.4ap < 0.001, bp < 0.01, cp < 0.05 vs. RNA (BC) group. Statistical analyses graphs were drawn using Prism, version 8 .All statistical demographic analysis was performed using SPSS version 23 software package . Data are presented as mean ± standard deviation. Statistical significance between all groups was analyzed by using the 3.3.137The clinical and demographic data of the control and BC groups are summarized in 3.236 This signature could provide information about RNA mutation  related to BC. This approach could offer early diagnosis of BC as well as early treatment. Nonlinear resonance frequency response of investigated RNA samples, including RNA (control) and RNA (BC) are represented in ESI .The change in harmonic oscillation response could be correlated to chemical change and disorder of absorber size, location, and organization.It is obvious that each macromolecule demonstrated its characteristic nonpolarized resonance frequency signature. Resonance RNA (BC) frequency signature differ slightly from RNA (control). In an attempt to determine the spectral oscillation signature for investigated RNA samples; normalized resonance frequency signatures were calculated to eliminate the effect of polarized light intensity .Due to the changes in molecular electronic configuration, absorber size in the order (nm); the re-emitted signature will be in the range of visible and near IR.3.3RNA alterations are accompanied with changes in its optical and dielectric properties when stimulated with laser light. Resonance frequency radiation could offer a fingerprint signature of the macromolecule chemical structure and physical properties. Chemical structural arrangements that create differential absorption of different polarization states can exhibit light attenuation. The resonance frequency attenuation of investigated RNA samples is demonstrated in 3.4via frequency response change  and RNA (BC) e change .RNA (BC) demonstrated characteristic frequency signal from RNA (control). RNA (BC) demonstrated frequency band 0.004–0.01 GHz, and characteristic signal at 0.02 GHz. The phase change of RNA (BC) to RNA (control) was calculated from frequency signal as demonstrated in RNA (BC) demonstrated phase shift at 0.031, and 0.07 GHZ. These phase shift could be ascribed to change in chemical structure and dielectric properties due to BC.Statistical analysis of obtained results was performed; the histogram for the frequency distribution of 5 signal observations of RNA (control), and RNA (BC) response was calculated. The mean values for the RNA (control), and RNA (BC) are 0.0783 and 0.0852, respectively. The standard deviation for the RNA (control) and RNA (BC) are 0.0020 and 0.0027, respectively . It can 4.via their specific fingerprint nonlinear resonance frequency signature. RNA (BC) demonstrated characteristic frequency signal and phase shift from RNA (control). RNA (BC) demonstrated characteristic signal at 0.02 GHz; furthermore RNA (BC) demonstrated phase shift at 0.031, and 0.07 GHZ from RNA (control). We hope that our study will assist more researchers and pave the way for finding out how numerous factors powerfully interact in order to utilizing non-linear polarization in direct, fast, non-invasive diagnosis of BC.BC included RNA mutations with changes in RNA chemical structure, and physical properties . This is the first time to report an optical approach based on nonlinear polarization to identify RNA alterations in BC All experimental and investigation trials was approved and validated from “Ain Shams University” – Medical College – Ethics Committee.The authors stated and declare that there is no conflict or competing of interests.


Most processes of the recognition and formation of specific complexes in living systems begin with collisions in solutions or quasi-solutions. Then, the thermodynamic regulation of complex formation and fine tuning of complexes come into play. Precise regulation is very important in all cellular processes, including genome editing using the CRISPR–Cas9 tool. The Cas9 endonuclease is an essential component of the CRISPR–Cas-based genome editing systems. The attainment of high-specificity and -efficiency Cas9 during targeted DNA cleavage is the main problem that limits the practical application of the CRISPR–Cas9 system. In this study, we analyzed the thermodynamics of interaction of a complex’s components of Cas9–RNA/DNA through experimental and computer simulation methods. We found that there is a small energetic preference during Cas9–RNA/DNA formation from the Cas9–RNA and DNA/DNA duplex. The small difference in binding energy is relevant for biological interactions and could be part of the sequence-specific recognition of double-stranded DNA by the CRISPR–Cas9 system. CRISPR –Cas (CRISPR-associated proteins) systems offer bacteria-adaptive protection against extraneous nucleic acids ,2. CRISPTo improve the accuracy of Cas9 as a genomic editing tool, more detailed studies of protein structure, protein–ligand and protein–protein interactions are required. The current method for determining the spatial structure is to obtain the crystal structure of the protein , but thiS. pyogenes using hydrogen–deuterium exchange mass spectrometry [Selecting the target region of the genome is the first step when using CRISPR–Cas9. Therefore, an important issue is the selection of a gRNA sequence with different cleavage efficiencies at the target site. The molecular mechanisms of recognition specificity and cleavage efficiency still remain incompletely understood. One of the major problems limiting the in vivo applicability of CRISPR–Cas9 systems is off-target DNA cleavage. To understand the molecular basis of off-target binding, extensive experiments have been performed ,18,19,20trometry . Howevertrometry . They prtrometry , actual trometry ,26,27,28trometry , molecultrometry , anti-CRtrometry  and the trometry . To dateHere, we report the thermodynamic analysis of interactions accompanying Cas9–RNA/ssDNA complex formation performed by ITC experiments and by computer simulation. From the processing of the experimental data, we obtained the thermodynamic characteristics of the formation of the Cas9–RNA/DNA complex. The data allow us to reasonably conclude that small differences in ΔG for the fully complementary complex and the duplex containing a single nucleotide substitution are the drivers for discrimination of the correct/incorrect complex by Cas9 nuclease. Our data show the physicochemical basis for DNA processing by Cas9 and opens up perspectives for fine tuning of the CRISPR–Cas9 system.The thermodynamics of the Cas9–RNA complex interaction with double-stranded DNA is important for understanding the specificity of CRISPR–Cas9. Alkan and colleagues in their study  developeA schematic diagram of the possible processes accompanying Cas9–RNA/ssDNA complex formation in vitro is presented in Therefore, we studied all the interactions presented in n) of 0.83 corresponding to bimolecular complex formation. The difference of n from the stoichiometric value equal to 1 could be caused by the 20% accuracy error of the spectrophotometric method used in the work for oligonucleotide concentration measurement [http://rna.tbi.univie.ac.at) [In the first step, the interaction of Cas9 with RNA was studied in order to find their concentrations for effective Cas9–RNA complex formation and further analysis. Furthermore, for the correct interpretation of the obtained thermodynamic parameters, it is important to analyze the possible interaction of components of the system. For this purpose, we analyzed the dissociation of possible self-complementary complexes by determining the thermal effects of RNA, ssDNA, and dsDNA dilution in buffer. Dilution of every studied nucleic acid into the solution did not lead to transition in the titration curves. The absence of thermal effects for dsDNA means that the formed duplex is sufficiently stable and does not dissociate upon dilution. In the case of dilution of RNA and ssDNA1, significant thermal effects are observed without transitions. This could be caused by the rearrangement of the intramolecular structure or dissociation of the RNA/RNA dimer. To determine the formation of intermolecular nucleic acid complexes—ssDNA/ssDNA1 (or dsDNA) and ssDNA/RNA—their components were mixed. In both cases, thermal effects were observed. A well-defined transition is found at the dsDNA formation, with a binding constant of 0.2 μM, an enthalpy of complexation of −212 kcal/mol and, close to unity, a chain interaction stoichiometry   revealedIn the study of the interaction of ssDNA with RNA, the thermal effects corresponding to the interaction are observed only at the first injections. Thus, it is impossible to reliably determine the thermodynamic parameters of complex formation due to the high measurement error. The thermodynamic parameters obtained by ITC using the independent binding model are summarized in n) close to 0.1, i.e., only 10% of the RNA is able to interact with DNA. In addition to the inability of all RNA molecules to interact with DNA, the rearrangement of the intramolecular RNA complex into a conformation capable of interacting with RNA requires additional energy consumption. As a result, the ΔH° value observed at n = 0.1 is significantly different from the expected one. Nevertheless, the value of the dissociation constant at 0.64 μM indicates the formation of a stable complex, which correlates with the calculated melting temperature. The calculated ΔH° and ΔS° values differ significantly from the experimental results. This difference can be explained by the formation of secondary structures by the RNA chain in the DNA binding region. RNA structuring was confirmed by analyzing the secondary structure using the RNAFold webserver . Most ofTherefore, the formation of a stable DNA/DNA duplex and RNA stable secondary structure formation resulted in the absence of thermal effects for the interaction of RNA with dsDNA by ITC measurement .To determine the optimal concentrations of RNA and Cas9 for titration in the subsequent study on the main binding process by the Cas9–RNA complex with DNA , the RNAThe significant difference in the stoichiometry of the Cas9–RNA complex from unity also indicates that the RNA forms intramolecular complexes as shown above, which results in the prevention of protein binding. This highly enthalpic binding with non-unity could be also explained by Cas9 interaction with the RNA dimer. The RNA/RNA dissociation was found in ITC experiments of RNA dilution in buffer. Based on these data, we chose the stoichiometry of Cas9–RNA as 5/1 to be sure that all RNA molecules were in complex with the protein, to study the interaction of Cas9–RNA with DNA. This was required to prevent the free form of RNA binding to the DNA. However, with this excess of protein, free Cas9 can interact with ssDNA or dsDNA, which could affect the studied thermodynamic parameters. Therefore, we tested the possibility of Cas9 interacting with ssDNA or dsDNA and showed no interaction of Cas9 with ssDNA and dsDNA .Afterwards, taking into account the data on the possible interaction of all components, the formation of the Cas9–RNA complex with dsDNA was studied via ITC e,f. SmalTo determine the thermodynamic effects more reliably, we examined the interaction of the Cas9–RNA complex with ssDNA. The values obtained were ΔH° at −49.27 kcal/mol, ΔS° at −128.6 kcal/mol·K and ΔG° −10.93 kcal/mol, which are comparable to the parameters obtained in the interaction of Cas9–RNA with dsDNA. This could also suggest that Cas9 interacts with the RNA dimer in the absence of DNA.Based on the interaction energies of the components of the complexes, one can judge such characteristics as, for example, specificity and selectivity. The obtained small differences in ΔG are the drivers for the determination of the correct/incorrect complex by the Cas9 nuclease.To verify the experimental data, we performed computer simulations of the Cas9–RNA/DNA and Cas9–RNA complexes, the native form of Cas9, as well as RNA/DNA and dsDNA duplexes, and RNA and ssDNA separately using molecular dynamics. The obtained MD trajectories were analyzed by MMPB (GB)SA methods in order to calculate the thermodynamic parameters of the interaction between the components of the studied system  and subsMolecular dynamics (MD) simulations for Cas9–RNA/DNA and Cas9–RNA complexes, the Cas9 protein, RNA/DNA and dsDNA duplexes began with the crystallographic structure of the Cas9–RNA/DNA complex (PDB ID: 4OO8), as described in the methods section. The whole structure of Cas9 was dynamic along the MD trajectory, which was evidenced by the RMSD values of the protein . High vaThe Cα-based RMSD calculations showed that the structure of the enzyme in the complex with RNA remains relatively stable starting from ~10 ns, and the deviation values lie in the range of 5–5.5 Å . For theTo determine the conformations most represented in the trajectory, we performed a cluster analysis of the molecular dynamics trajectories. The representation of clusters as a function of dynamics time is shown in Along with the protein analysis, the trajectories containing nucleic acids were analyzed for RNA structure flexibility. The RNA from the original complex was taken as a starting point for the simulation. The RNA molecule contains five self-complementary sites (four loops). RNA in the unbound state, i.e., without protein and DNA, fluctuates freely in space, but the hairpin structure remains stable. When the RNA/DNA complex is formed, the RNA at the complementarity site with DNA is stabilized by complementary interactions, although the entire molecule remains highly mobile. As expected in the complex with Cas9, the RNA molecule slightly deviates from its initial position, which is due to tight RNA–enzyme interactions.To estimate the thermodynamic parameters of the formation of Cas9–RNA/DNA, Cas9–RNA, RNA/DNA, and dsDNA complexes, the free binding energies were calculated using the MM-PBSA (PB) and MM-GBSA (GB) methods . To obtaWhen we analyzed the formation of the Cas9–RNA/DNA complex, the trajectories of the complex components were isolated from the trajectory of the initial system, and the binding energy of the complex components was calculated. It amounted to ΔE = −363.9 ± 0.2 and ΔE = −149.0 ± 0.2 kcal/mol for the MM-GBSA and MM-PBSA methods, respectively. In the case of Cas9–RNA complex formation, we used component trajectories derived from the trajectory of the complex itself for thermodynamic analysis. In this case, the energy values are ΔE = −820.0 ± 0.3 (GB) and ΔE = −948.2 ± 0.4 (PB) kcal/mol.2 = 0.99 , was obtained from Addgene  (39312). Cas9 protein was prepared and purified similar to the previously described protocol .v/v) glycerol, 1 mM dithiothreitol (DTT), 1 mM EDTA) at 4 °C overnight. The eluent of SpyCas9 was further purified over a HiTrap SP FF  column equilibrated with IEX buffer B . Then, IEX buffer B was changed to the SEC buffer . Purified Cas9 enzyme was concentrated with an MWCO centrifugal concentrator . Concentration was determined by UV absorbance at 280 nm.In brief, protein expression was induced in Rosetta 2 DE3 cells  with 0.2 mM IPTG at 18 °C for 16 h. Cell pellets were resuspended in 15 mL of chilled lysis buffer  per cell pellet from 1 L culture. Resuspended cells were homogenized and clarified by centrifugation. His-Select Ni resin  was equilibrated with lysis buffer. The cleared lysate was loaded onto the column, attached to an FPLC system, and equilibrated with wash buffer  at 4 °C. The supernatant was washed in 50 mL volumes of wash buffer. Protein was eluted with 50 mL of elution buffer . Furthermore, 0.5 mg of TEV protease was added per 50 mg of protein and the sample was dialyzed against 2 L of dialysis buffer -2A-GFP  with corresponding protospacer. The DNA template contained the T7 promoter to generate double-stranded promoter regions, which support in vitro transcription by T7 RNA polymerase . In vitrThe interaction of Cas9 with nucleic acids was analyzed using the Nano ITC isothermal titration calorimeter . All ITC measurements were carried out at 25 °C with 200 rpm stirring and 300 s delay between successive injections at 1–2 μL using a syringe 50 μL in volume to the sample cell (190 μL). Measurements were run in the overfilled mode to prevent air bubbles, liquid evaporation or the presence of the vapor phase. All experiments were performed in the buffer containing 150 mM NaCl, 20 mM HEPES, pH = 7.6. During the key experiment, the cell contained the preassembled Cas9–sgRNA complex with concentrations of 6 μM and 1 μM, respectively. The dsDNA at a concentration of 25 μM was gradually added to the cell. In the second experiment, the cell also contained Cas9 (5 μM) in the complex sgRNA (1 μM), to which ssDNA solution (10 μM) was added. The thermodynamic parameters of complex formation were determined by adding the sgRNA solution (62.5 μM) to the Cas9 (5 μM) in the cell.We obtained the parameters of DNA duplex formation by mixing a DNA strand complementary to RNA (20 μM) with a second strand in the cell (2 μM). Additionally, we conducted an experiment by adding a DNA duplex at a concentration of 25 μM to an RNA solution (cell) with a concentration of 10 μM.We carried out control experiments by adding RNA (50 μM), dsDNA (25 μM), and ssDNA (20 μM) solutions to the buffer in the cell.The data were processed with the NanoAnalyze software . Models of independent binding or dimer dissociation were applied to determine thermodynamic parameters and stoichiometry of binding.S. pysogenes Cas9 (SpCas) with PDB ID 4OO8 as the starting structure of the triple complex of the protein with guide RNA (sgRNA) and ssDNA [2+ ions, arranged according to [We used the crystal structure of the protein nd ssDNA . The inind ssDNA , and thend ssDNA . The finrding to .2+ ion was coordinated by the carboxylate moieties of Asp-10, Glu-762 and Glu-766 amino acids. The second Mg2+ ion was located next to the first, and coordinated by Asp-10, Glu-766 and His-983 amino acids. Additionally, the third was arranged by His-1297 and Asp-1328 amino acids. The first two Mg2+ ions are located in the RuvC domain of the Cas9 protein and play a critical role in the cleavage of the DNA substrate. It is known that Asp-10 is involved in the cleavage of non-complementary DNA strands, and the Mg2+ ion is required by Cas9 to ensure enzymatic activity [One Mgactivity .+ ions and solvated with water molecules using tLEaP. The TIP3P with truncated “cubic” periodic boundary conditions with a distance of 8 Å was used as an explicit water model. Thus, the Cas9–RNA/DNA complex contained 56,490, the Cas9–RNA complex contained 56,705 and the native protein model had 57,282 water molecules.The ff14SB force field was used ,48 for t2 and water molecules were allowed to relax. In a second step, the restriction was removed to allow all atoms to move freely. Both minimization steps were realized in 1000 cycles. After the energy minimization step, each Cas9-containing system was heated gradually from 1 to 300 K for 125 ps with periodic boundary conditions. The SHAKE algorithm was applied to constrain all bond lengths involving hydrogen to their equilibrium distance. Density equilibration was carried out sequentially for 50 ps and the whole system for 500 ps without constraint. Equilibrium molecular dynamics simulations of 100 ns duration for the Cas9 protein or its complexes with nucleic acids were performed in the NPT ensemble. We analyzed the obtained trajectories using CPPTRAJ [To reduce undesirable steric interactions and direct the Cas9 contain systems  to energetically favorable conformations, we used a two-step process of energy minimization by the steepest descent method. In the first step, the solvated elements of the system (complexes and the protein itself) were held at a harmonic force constant of 25 kcal/mol-Å CPPTRAJ  and UCSF CPPTRAJ .The starting structures of RNA and the RNA complex with ssDNA were obtained from the initial structure of the Cas9–RNA/DNA. We generated the dsDNA complex using XLEaP. Nucleic acid complexes were pre-minimized, and then neutralized and solvated using tLEaP as described above. Thus, 29,919 molecules of water were added to the RNA/DNA complex, 28,912 to the RNA complex, and 7700 to the dsDNA complex.We performed the energy minimization, heating, and equilibration steps the same way as for the protein-containing models. The CPPTRAJ and UCSF Chimera were used to analyze molecular dynamics trajectories.We analyzed the obtained molecular dynamics trajectories using molecular mechanics energies combined with the molecular mechanics energies combined with the Poisson–Boltzmann or generalized born and surface area continuum solvation (MM-PBSA and MM-GBSA) to calculate the thermodynamic parameters of the Cas9–RNA/DNA, Cas9–RNA, RNA/DNA, and DNA/DNA complexes.While studying the thermodynamic aspects of complex formation, the complex is divided into a so-called “receptor” and “ligand” molecule. The topology files for the components of the complexes being studied were generated before the analysis by CPPTRAJ. The ionic strength of the solution was taken equal to 100 mM of monovalent cations. Each step of the MD trajectory was used in the calculations.d of Cas9 interactions with nucleic acids could help to model the formation of complexes in solution. Our data open up perspectives for the fine tuning of the CRISPR–Cas9 system based on knowledge of the thermodynamic characteristics of each component of the complex.This study shed light on the first step of DNA processing by CRISPR–Cas systems—formation of the Cas9–RNA/DNA complex. We analyzed the thermodynamics of the interaction of a complex’s components by experimental and computer simulation methods. The in vitro experiments using isothermal titration calorimetry showed the complexity of the studied system. We have found that non-profit nucleic acid interactions complicate the thermodynamic analysis. Nonetheless, we found that there is a small energetic preference during Cas9–RNA/DNA formation from the Cas9–RNA and DNA/DNA duplex. These experimental findings were confirmed by molecular dynamics simulations and analysis of the trajectories via MM-PBSA and MM-GBSA analysis. The small difference in binding energy is relevant for biological interactions and could be part of sequence-specific recognition of the double-stranded DNA CRISPR–Cas9 system. Obtained thermodynamic parameters and K


Solution NMR spectroscopy is a well-established tool with unique advantages for structural studies of RNA molecules. However, for large RNA sequences, the NMR resonances often overlap severely. A reliable way to perform resonance assignment and allow further analysis despite spectral crowding is the use of site-specific isotope labeling in sample preparation. While solid-phase oligonucleotide synthesis has several advantages, RNA length and availability of isotope-labeled building blocks are persistent issues. Purely enzymatic methods represent an alternative and have been presented in the literature. In this study, we report on a method in which we exploit the preference of T7 RNA polymerase for nucleotide monophosphates over triphosphates for the 5’ position, which allows 5’-labeling of RNA. Successive ligation to an unlabeled RNA strand generates a site-specifically labeled RNA. We show the successful production of such an RNA sample for NMR studies, report on experimental details and expected yields, and present the surprising finding of a previously hidden set of peaks which reveals conformational exchange in the RNA structure. This study highlights the feasibility of site-specific isotope-labeling of RNA with enzymatic methods. Nuclear magnetic resonance spectroscopy (NMR) is a versatile tool to study the structure and dynamics of RNA at high resolution –4. Unfor13C or 15N-labeled nucleotides is solid-phase oligonucleotide synthesis (SPOS). Since these building blocks are often synthesized in-house, they can be modified, atom-specifically labeled or both [The most common method for site-specific incorporation of  or both , 10. Whiin vitro transcription (IVT) have been presented, and can be divided in chemo-enzymatic approaches [Methods for site-specific incorporation of isotope-labeled nucleotides with proaches –13 and pproaches . The forproaches . Liu andproaches . Both thin-vitro-transcribed labeled and unlabeled strands. These strands are then cleaved with RNase H and internal ribozymes, so that labeled fragments can be ligated to unlabeled ones, which yields a long RNA, with specific isotope-labeled segments [Instead of single nucleotides, shorter fragments can be labeled site-specifically and then be ligated to a larger unlabeled RNA fragment(s), which still reduces signal overlap significantly. Duss et al. presented a cut-and-paste protocol, based on segments , 16.Purely enzymatic methods to incorporate site-specific NMR labels and modifications have been exploiting the fact that T7 RNA polymerase (T7RNAP) favors nucleotide monophosphates (NMP) over nucleotide triphosphates (NTP) in the first position, even though the enzyme will use NTPs if no NMPs are present , 18. TheThis article describes a similar workflow, which incorporates a site-specific isotope-labeled nucleotide into an RNA molecule using only established methods based on T7 IVT. Our approach is similar to the method published by Lebars and coworkers and therefore strengthens the general validity of such site-specific RNA labeling methods. Importantly, compared to most other studies, we use adenosine-monophosphate (AMP) instead of guanosine-monophosphate (GMP) , 20. Ini13C/15N-labeled AMP in the 5’ position of a 16 nt RNA fragment, to then site-specifically label a longer RNA after ligation of a second RNA strand with T4 DNA ligase. We present the successful incorporation of a single 13C/15N-labeled adenosine into a 46 nt RNA fragment stemming from helix-44 in the human ribosome [In brief, we utilize T7 RNA polymerase to incorporate a ribosome , which wAll RNA molecules were prepared using T7 IVT from a single-stranded template (double-stranded in the promoter region), which were 2’-OMe modified at the last two nucleotides of the template strand , 25. TraFull-length RNA (A31 in bold):ACG GUC GAA CUU GAC C -3’5 ’- GGU UUA GUG AGG CCC UCG GAU UUC GAG AAG 5’-RNA fragment:5’- GGU UUA GUG AGG CCC UCG GAU UUC GAG AAG -3’3’-RNA fragment:3’- ACG GUC GAA CUU GAC C -3’2O and mixed by pipetting.DNA templates for 5’-RNA fragment and 3’-RNA fragment see  were ordTemplate sequences with promoter complement indicated in italics are shown below:Full-length DNA template:TA TAG TGA GTC GTA TTA -3’5’-mGmGT CAA GTT CGA CCG TCT TCT CGA AAT CCG AGG GCC TCA CTA AAC C5’-DNA fragment template:5’- mCmUT CTC GAA ATC CGA GGG CCT CAC TAA ACCTAT AGT GAG TCG TAT TA-3’3’-DNA fragment template:TA TAG TGA GTC GTA TTA -3’5’- mGmGT CAA GTT CGA CCG T5’- TAA TAC GAC TCA CTA TA -3’T7 promoter: T7 promoter and respective template oligo were annealed by mixing both DNA strands to a final concentration of 25 μM each and heating to 95°C for 5 minutes and successive cooling at room temperature for 30 minutes.2: 10–50 mM, Tris-Cl: 60–200 mM, DTT: 10–60 mM, Spermidine: 2–20 mM, NMP: 0–20 mM, NTPs: 3–8 mM and DMSO: 0–20%.The IVT conditions for all 3 constructs were optimized by rational variation in small scale before production and purification in large scale. Reactions were prepared at 50 μL in parallel and incubated for 1.5 hours at 37°C. 1 μL of each IVT reaction was quenched in 9 μL gel loading dye  and heated to 95°C for 2 minutes. 1 μL of the solution was loaded onto a 20% denaturing PAGE. Concentration ranges screened were: MgClE.coli and purified by His-tag affinity purification and size-exclusion chromatography by the protein science facility (PSF) at the Karolinska Institute.Conditions giving the strongest target band were then scaled up to 10 mL for purification and NMR sample preparation see . ReagentAll analytical gels were performed in 20% polyacrylamide gels (acrylamide:bisacrylamide 19:1) using 8x12 cm plates in a mini-PROTEAN system (BioRad). Acrylamide solution was prepared in 1X TBE buffer  and 8 M urea. 5 mL acrylamide solution were polymerized in a 15 mL centrifuge tube by adding 4 μL N,N,N,N-tetramethylethylenediamine (TEMED) and 40 μL 10% ammonium persulfate (APS) solution (v/w). The solution was mixed by inverting before pouring between the prepared glass plates (0.75 mm spacer). Gels were run in 1X TBE buffer at 350 V for typically 60–75 minutes. The wells were cleaned from urea by flushing with running buffer using a syringe before loading the sample.1 μL sample was diluted in 9 μL loading solution  and heated to 95°C for 2 minutes. Typically, 1 μL of the diluted sample was loaded onto the gel. Gels were stained with SYBRGold (Thermo) according to the manufacturer’s instructions and imaged in an Amersham ImageQuant 800 UV at 498 nm excitation wavelength.HPLC purification was performed following previously published methods , 27. LarThe Dionex Ultimate 3000 UHPLC system (Thermo) was equipped as follows: DNAPac PA200 22x250 Preparative column, LPG-3400RS Pump, TCC-3000RS Column thermostat, AFC-3000 Fraction collector, VWD-3100 Detector. Buffer A: 20 mM sodium acetate, 20 mM sodium perchlorate, pH 6.5. Buffer B: 20 mM sodium acetate, 600 mM sodium perchlorate, pH 6.5. Buffers were degassed and filtered before use. Column temperature: 75°C. Flow rate: 8 mL/min. Injection loop: 5 mL. Pump sequences: 0–10 min: 0% buffer B, 10–40 min: elution gradient, 40–50 min: 100% buffer B, 50–60 min: 0% buffer B. Elution gradients: 5’-RNA (30 nt): 22–30% buffer B, 3’-RNA (16 nt): 15–25% buffer B, Full-length RNA (46 nt): 15–45% buffer B.Collected fractions were tested for RNA of interest by loading 0.1 μL on a 20% denaturing PAGE.2O and mixed by pipetting.Ligation splints were obtained from IDT as standard DNA oligos, with the ‘Standard Desalting’ purification option. Received oligos were diluted to 100 μM in MilliQ H5’- AGT TCG ACC GTC TTC TCG AAA -3’Ligation splint 21 nt: 5’- CAA GTT CGA CCG TCT TCT CGA AAT CC -3’Ligation splint 26 nt: 2, 1 mM ATP, 10 mM DTT, 15 μM 5’-RNA fragment, 15 μM 3’-RNA fragment, 22.5 μM ligation splint, 2.5% PEG 4000 (w/v), 10% DMSO (v/v), 10 u/μL T4 DNA ligase  for 48 hours at room temperature. Especially the combination of both PEG and DMSO with the long reaction time of 48 h seemed to make a large difference in the success of the reaction, which is where our conditions deviate from commercial suppliers. No difference in yield was found between the ligation splints. Ligation reactions have been purified by IE HPLC as described above, using a gradient of 15–45% buffer B.RNA ligations with T4 DNA ligase were optimized in 20 μL scale before scale-up of labeled samples by concentration variation of PEG 4000 (0–20%), DMSO (0–40%), reaction time  and temperature . Final conditions were: 50 mM Tris-HCl pH 7.5, 10 mM MgClThe concentrated HPLC fractions were DNase I-digested in 6 mL at 1 u/μL in 1X DNase buffer (Thermo) for 15 minutes at 37°C and purified by ion-exchange HPLC as described above.2O (v/v) was added to reach sample volume of 250 μL and transferred to a Shigemi tube.For folding, NMR samples have been diluted to 10–50 μM in NMR buffer  by heating to 95°C for 5 minutes and snap-cooled in a water/ice/salt mixture for 30 minutes. The sample was then concentrated to 225 μL in a centrifugal filter unit . 10% DNMR experiments were acquired on a 600 MHz Bruker Avance III spectrometer equipped with 5 mm HCNP QXI Cryo-probe at 298 K. Spectra were processed using the Bruker Topspin 3.6 and 4.0.6 software.1H,13C-HSQC spectra for the A1-labeled 3’-RNA fragment (300 μM) were recorded with 128 indirect points and 8 scans. 1H,13C-HSQC spectra for the A31-labeled full-length RNA (230 μM) were recorded with 256 points in the indirect dimension and 200 scans, summing up to 24 hours measurement time, and with 350 indirect points and 16 scans for the A/U-labeled sample (1.3 mM). 2D F1-13C-edited [C-edited  experimeWe chose the 46 nt construct  because 13C/15N labeled AMP (at 10 mM) was used at 3.3x excess over the other NTPs (3 mM each), as it was optimized in small scale reactions. A denaturing PAGE shows a product of 16 nt after IE HPLC purification , as expected for a signal originating from a single 13C/15N-labeled adenosine nucleotide  and added to stoichiometric amounts of the A-labeled 3’-fragment in the ligation reaction. The ligation reaction was prepared at a scale of 8.5 mL, which contains all of the produced labeled 3’-RNA fragment at a final concentration of 15 μM. During optimization of the ligation reaction, we found a combination DMSO and PEG-4000 to give the highest ligation yields over the reaction time of 48 hours.The concentration of the final NMR sample was 230 μM in 250 μL, which equals 58 nmol labeled full-length RNA and implies a ligation yield, including IE HPLC purification, of 45%. In comparison, Lebars et al. and Duss et al. reported on 50 and 100% ligation yield respectively, however, using T4 RNA ligases instead of T4 DNA ligase , 20. At The ligation of 3’-RNA and 5’-RNA fragments was confirmed by denaturing PAGE and NMR spectroscopy. Denaturing PAGE shows a ligated band, indicating the successful formation of the 46 nt construct , lane 4.1H,13C-HSQC spectra of the full-length RNA sample after HPLC purification and snap-cooling, shows four peaks which overlap exactly with the A/U-labeled sample for the fully labeled construct  and variation of MgClT buffer , 35. UltT buffer . IncreasThe method is expected to work at a higher yield for integration of site-specific guanosine residues, as all native T7RNAP promoters contain at least two guanosine nucleotides at the 5’ end of the transcript. Probably for this reason most previous publications used GMP at the site of labeling or modification , 20. DesNext to isotope-labeled nucleotides, certain modifications or even oligonucleotides could be incorporated by the same protocol, as their 5’-incorporation has been shown before , 38, 39.Another limitation of the method is the position of the label. While T7 IVT has no upper length limit (within the size limit of solution NMR), short sequences (below 15 nt) are difficult to synthesize. Labels closer to the 3’ or 5’ termini of the full-length RNA could potentially be prepared in conjuction with a cis-cleaving ribozyme or with solid-phase oligonucleotide synthesis instead.Alternative routes for ligation include T4 RNA ligase 1 and 2, which are known to be highly efficient, and differ with regard to their sequence and structure specificity –45. Alsoin vitro transcription and successive RNA ligation) over chemo-enzymatic methods. The weak point of the method is the sequence-dependency of incorporation efficiency of the labeled nucleotide monophosphate at the 5’-end of the labeled RNA strand. By thoroughly reporting on yields and limitations, we hope to encourage researchers to use this approach to overcome limitations from spectral crowding in NMR studies of large RNA molecules.In this report, we show another application of purely enzymatic site-specific labeling of RNA by IVT with isotope-labeled nucleotide monophosphate and successive ligation to an unlabeled fragment . FinallyS1 Raw image(PDF)Click here for additional data file.