key: cord-281565-v8s2ski3 authors: Belmonte-Reche, Efres; Serrano-Chacón, Israel; Gonzalez, Carlos; Gallo, Juan; Bañobre-López, Manuel title: Exploring G and C-quadruplex structures as potential targets against the severe acute respiratory syndrome coronavirus 2 date: 2020-08-20 journal: bioRxiv DOI: 10.1101/2020.08.19.257493 sha: doc_id: 281565 cord_uid: v8s2ski3 In this paper we report the analysis of the 2019-nCoV genome and related viruses using an upgraded version of the open-source algorithm G4-iM Grinder. This version improves the functionality of the software, including an easy way to determine the potential biological features affected by the candidates found. The quadruplex definitions of the algorithm were optimized for 2019-nCoV. Using a lax quadruplex definition ruleset, which accepts amongst other parameters two residue G- and C-tracks, hundreds of potential quadruplex candidates were discovered. These sequences were evaluated by their in vitro formation probability, their position in the viral RNA, their uniqueness and their conservation rates (calculated in over three thousand different COVID-19 clinical cases and sequenced at different times and locations during the ongoing pandemic). These results were compared sequentially to other Coronaviridae members, other Group IV (+)ssRNA viruses and the entire realm. Sequences found in common with other species were further analyzed and characterized. Sequences with high scores unique to the 2019-nCoV were studied to investigate the variations amongst similar species. Quadruplex formation of the best candidates was then confirmed experimentally. Using NMR and CD spectroscopy, we found several highly stable RNA quadruplexes that may be suitable theranostic targets against the 2019-nCoV. GRAPHICAL ABSTRACT The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or 2019-nCoV) is a positive-sense single-stranded RNA virus from the Betacoronavirus genus, within the Coronaviridae family of the Nidovirales order. Although it is believed to have originated from a bat-borne coronavirus, (1-3) the 2019-nCoV can spread between humans with no need of other vectors or reservoirs for its transmission. The virus is responsible for the ongoing COVID-19 pandemic that has caused hundreds of thousands of deaths, millions of infected, and a disastrous strain on the economy of most countries and citizens worldwide. The origin of the virus has been traced back to the Chinese city of Wuhan, where the first cases of infected individuals were reported amongst the workers of the Huanan Seafood Market (4, 5) . This wet exotic animal market, where wild animals including bats and pangolins are sold and prepared for consumption, offers ample opportunities for pathogenic bacteria and virus to adapt and thrive. Such circumstances led Cheng and colleagues to predict the current pandemic back in 2007 (6) . In their own words: "the presence of a large reservoir of SARS-CoV-like viruses in horseshoe bats, together with the culture of eating exotic mammals in southern China, is a time bomb. The possibility of the re-emergence of SARS and other novel viruses from animals or laboratories and therefore the need for preparedness should not be ignored". The fight against the 2019-nCoV has now become a global problem. In this current scenario, the scientific community is playing a fundamental role in defeating the virus and minimizing the number of victims. Their work includes, to name a few, the development of fast and reliable detection methods, the identification of therapeutic targets within the virus, and the development of active drugs and vaccines to cure and to prevent infections, respectively. G-Quadruplexes (G4s) and i-Motifs (iMs) have been proposed as therapeutic targets in many disease aetiologies. G4s are Guanine (G) rich DNA or ARN nucleic acid sequences where successive Gs stack in a planar fashion via Hoogstein bonds to form four-stranded structures, stabilized by monovalent cations (7) . iMs on the contrary, are Cytosine (C)-rich regions that fold into tetrameric structures of stranded duplexes (8) (9) (10) . These are sustained by hydrogen bonds between the intercalated nucleotide base pairs C·C + when under acidic physiological conditions. The importance of these genomic secondary structures has been abundantly studied during the last years (11) (12) (13) (14) (15) (16) . They have been found to be regulatory elements in the human genome implicated in key functions such as telomere maintenance and genome transcription regulation, replication and repair (17) . G4 structures have also been identified in fungi (18) (19) (20) (21) , bacteria (22) (23) (24) (25) (26) and parasites (27) (28) (29) (30) (31) (32) . Their occurrence are known in many viruses that afflict humans as well. These include the HIV-1 (33) (34) (35) , Epstein-Barr (36, 37) , human and manatee papilloma (38, 39) , herpes simplex 1 (40, 41) , Hepatitis B (42) , Ebola (43) and Zika (44) viruses. Here they can regulate the viral replication, recombination and virulence (28, 45, 46) . we reported the presence of the known cMyb.S (48) iM within the Epstein-Barr virus (49) . Despite the lack off reports, iMs present great potential as viable targets against viruses. For example, the in silico analysis of the rubella virus revealed an extremely dense genome of potential iMs (density as counts per genomic length) that surpassed its human counterpart by over an order of magnitude (49) . Other viruses, such as the measles and hepacivirus C, were also very rich in potential iMs with densities similar to the human genome. In this work, we wished to contribute to the ongoing effort against the COVID-19 pandemic by investigating the relationship between the 2019-nCoV and quadruplex targets. With this aim, we analysed the prevalence, distribution and relationships of Potential G4 Sequences (PQS) and Potential iM Sequences (PiMS) in its genome. These PQS and PiMS have been assessed according to their potential to form, uniqueness, frequency of appearance, conservation rates between 3297 different 2019-nCoV clinical cases, confirmed quadruplex-forming sequence presence and localization within the genome. The study of the 2019-nCoV and its quadruplex results were expanded to integrate the Coronaviridae family, Group IV of the Baltimore classification and the entire virus realm, as to allow a wider range of interpretation. With all this information at hand, our final objective was to identify biologically important PQS and PiMS candidates in the virus. To substantiate our bioinformatic analysis, we analysed experimentally some of these sequences by CD and NMR spectroscopies. Our in vitro results confirmed the formation of stable quadruplexes that can form in the viral genome, suggesting that they may be suitable targets for new therapeutic or diagnostic agents (46, 50) . Hence, our analysis into the virus realm, and especially the 2019-nCoV, may provide useful insights into using quadruplex structures as targets in future anti-viral treatments. In this work, we have used the G4-iM Grinder (GiG) package for the analysis of all viruses (49) . GiG is an R-based algorithm that locates, quantifies and qualifies PQS, PiMS and their potential higher-order versions in RNA and DNA genomes. In order to extract more information and better analyse the viruses, we first upgraded GiG. Two new functions were developed and are now incorporated in the GiG-package (as of GiG version 1.6.0) named GiG.Seq.Analysis and GiG.df.GenomicFeatures (supplementary material, section 1). To help us locate any G4 or iM already studied in the literature, we updated the GiG's DataBase (GiG.DB) to version 2.5.1. The library now includes 2851 quadruplex-related sequences that can be identified within any of GiG's results. The database is categorized by the capability of the sequence to form or not form quadruplex structures (2141 do, 710 do not), their relation to Gbased or C-based quadruplexes (2568 G4, 283 iM) and the genome type (1858 DNA, 993 RNA). The reference information (including DOI and/or PubMedID) of each sequence is also listed and accessible to facilitate further studies. With these upgrades at hand, we retrieved the 2019-nCoV's reference sequence (GCF_009858895.2) from the NCBI database (51) . We also downloaded those of 18 other viruses which can cause mortal illness in humans, including six other pathogenic Coronavirus, as comparison (supplementary material, section 2). As a workflow, we applied the functions GiG.Seq.Analysis (to study their G-and C-run characteristics), G4iMGrinder (to locate quadruplex candidates) and G4.ListAnalysis (to compare quadruplex results between genomes) from the G4-iM Grinder package (GiG) to all the viruses. The 'size restricted overlapping search and frequency count' method (Method 2, M2A and M2B) was used to locate all the potential candidates. Then, these PQS and PiMS were evaluated by their frequency of appearance in the corresponding genome, the presence of known-to-form quadruplex structures sequences within and their probability of quadruplex-formation score (as the mean of G4Hunter (52) and the adaptation of the PQSfinder algorithm (53) ). To compare between virus species, we calculated the density of potential quadruplex sequences per 100000 nucleotides (Density = 100000 × ℎ ). We previously saw that viruses have a wider-range of PQS and PiMS densities than that of the human, fungi, bacteria and parasite genomes (49) . Some were totally void whilst others were very rich in potential candidates. So, we explored different quadruplex definitions to determine the most useful configurations for the analysis of the viruses at hand. These different definitions control the characteristics of what the algorithm considers a quadruplex. They include the acceptable size of G-or C-repetitions to be considered a run, the acceptable amount of bulges within these runs, the acceptable loop sizes between runs, the acceptable number of runs to constitute a PQS or PiMS, and the total acceptable length of the sequence (Figure 1, A) . A flexible configuration of quadruplex definitions will detect larger amounts of candidates at the expense of requiring more computing power and accepting sequences that are more ambiguous in forming quadruplex structures in vitro (as determined by their score; with longer loops, smaller runs, more bulges and more complementary G/C %, Figure 1 , B). More constrained definitions result in the opposite. Hence, for the analysis, we chose three different configurations: a Lax configuration (which accepts run bulges and longer ranges of runs, loops and total sizes), the Predefined configuration of the package (which restricts sizes but still accepts run bulges), and the original formation. This scale is the mean of G4Hunter (that considers G richness and C skewness for PQS or vice versa for PiMS as factors) (52) and an adaptation of PQSfinder (that considers run, loop and bulge effects on the structure) (53) . Positive values mean that the sequence is more capable of forming G4s, whilst more negative values mean that it is more capable of forming i-Motifs. Values near zero are not good candidates. C. Left, GiG's quadruplex definitions used in this work. Granting more freedom to the quadruplex search will increase the number of structures found, at the expense of requiring more computational power and potentially finding more sequences with ambiguous quadruplex formation potential. C. Right, Total results found within the 2019-nCoV by configuration and score criteria. D. PQS and PiMS densities (per 100000 nucleotides) found per different configuration and score criteria for 19 viruses that cause mortal illness in humans. X scale is in logarithmic scale (base 10). Results are categorized by their score: intense colours (blue for PQS, yellow for PiMS) are the most probable to form in vitro (score over |40|), lighter bars are the density of structures with at least a score of |20| and grey bars are the densities without the score filter (hence accepting all potential structures). The 3297 different 2019-nCoV viral genomes sequenced during the pandemic (from December-2019 to July-2020, by different laboratories worldwide) were retrieved from the online database GISAID (56, 57) . These genomes are the result of filtering the database by their coverage (<1 % N content), completeness (>29000 nucleotides) and association to a clinical patient history (only those that have it). All other viral genomes used were retrieved from the NCBI database. To analyse these genomes, we employed the workflow described in the pre-analysis section using the Lax parameter configuration. We investigated the biological features potentially Data were smoothed using the means-movement function within the JASCO graphing software. Melting transitions were recorded by the monitoring the decrease of the CD signal at 264 nm. Heating rates were 30 °C/h. Transitions were evaluated using a nonlinear least squares fit assuming a two-state model with sloping pre-and post-transitional baselines. Oligonucleotide solutions for CD measurements were prepared at the same buffer conditions as the NMR experiments. Oligonucleotide concentration was of 50 M. We further expanded the search to the remaining viruses classified in the NCBI database To validate the predictions of our bioinformatics search, we selected three candidates using the criteria mentioned in the material and methods section. Two of them were potential G4 forming sequences and the third one was an iM candidate. The first G4 (CoVID-RNA-G4-1) examined is found in the N-gene of the 2019-nCoV with a conservation rate of 99.48 % ( Figure 5, A entry 1) . The NMR spectra of this RNA exhibited a broad set of signals around 11 -12 ppm, characteristic of guanine imino protons involved in Gtetrads. These signals are observed at high temperatures indicating that the G-quadruplex is quite stable ( Figure 5 , B left). Additional signals around 12 -13 ppm, which are characteristic of Watson-Crick base-pairs, can also be observed at low temperature. These interactions may arise from loops between G-tracts or alternative conformation such as hairpin-like structures. The CD spectra of the candidate revealed a positive band at 264 nm and negative band with a minimum at 240 nM consistent with the formation of a G4 of a parallel topology ( Figure 5, D, left) . Melting experiments monitored by CD confirmed the great stability of the G4, whose melting temperature (Tm) was calculated to be 54.4 ºC at [K + ] = 50 mM. Encouraged by these results, we additionally selected another candidate for experimental analysis with a very high conservation rate (CoVID-RNA-G4-2; Figure 5 , A, entry 3). This candidate is located in the orf1ab gene within the nsp3 region. As for the previous analysis, NMR and CD spectra revealed a stable parallel G4quadruplex ( Figure 5 , B and D, right), with a CD-monitored Tm of 48.1 ºC. In this case, the CD spectra presented an additional band at 310 nm, most likely related to the association between two quadruplexes to form a dimeric structure. This is consistent with the number of imino signals observed in the NMR spectra at high temperatures, which suggests the presence of more than two G-tetrads. In the case of PiMS, we selected a very conserved candidate (100 %) found in the orf1ab -nsp12 region of the virus (CoVID-RNA-iM-1; Figure 5 , A entry 4). In NMR, only two small signals appeared in the 12.5 -14.5 ppm range at neutral pH. Under acidic conditions more signals were observable, including a peak at 15 ppm which could be associated with C·C+ iminos. However, further analysis by 2D NMR spectroscopy revealed that this signal arises from an AU base pair (Supplementary material, section 4. Figure 13 ). We must conclude that this sequence, although folded, does not form an iM. This result is not totally unexpected, since the lower stability of RNA vs DNA iM is well known. In spite of this negative result, and to check the capability of our algorithm to detect iMs, we decided to study the DNA version of this sequence (CoVID-DNA-iM-1; Figure 5 , A, entry 5). Most interestingly, the NMR spectra of this DNA oligonucleotide exhibited several imino signals in the 15 -16 ppm range, characteristic of C·C+ base pairs. These signals are observable in the 5.5 to 6.7 pH range ( Figure 5 , C, and Supplementary material, section 4. Figure 14) . Additionally, amino groups from C·C+ (in the 9 - In this work, we have used G4-iM Grinder to analyse the genome of the 2019-nCoV, and that of many other viruses, in search off potential quadruplex (both G4 and iM) therapeutic targets. To or Entamoeba histolytica may be less rich in G and C content (49) , the size of these genomes enables finding rich G-or C-tracks that can ultimately form potential quadruplexes. In most viruses, however, this does not take place because of the small size of the genomes (in the range of tens to hundreds thousand nucleotides versus the tens of millions for the parasites mentioned, and thousands of millions for humans). Furthermore, most of the G4s found in viruses are complex sequences, with short runs and bulges (for example, HIV-1 (33, 35) and Ebola (43)), which elude detection when following traditional quadruplex definitions. To overcome these problems, we took advantage of the great modulability of G4-iM Grinder, and developed, tested and successfully employed a lax quadruplex definition configuration for the analysis. With these settings, the number of candidates found increased greatly and included the complex sequences expected in viruses, at the expense of needing more computational power. With all these updates and configurations at hand, we focused on the reference 2019-nCoV and located 323 PQS and 189 PiMS unique (only occurring once in the genome) sequences dispersed unevenly in the genome. 20 % of these candidates had at least a medium probability of formation (score over |20|). These were concentrated in the orfab gene (especially nsp 1 and 3 areas for PQS; and nsp 3, 4 and 12 for PiMS), the N-gene and S-gene (a highly variable gene that binds to the ACE2 membrane receptor and controls the viral penetration into the cell (3)). The orf3a (related to virulence by necrotic death inducement and cytokine expression (60)), M-gene (which encodes membrane glycoprotein (61)), orf8 and UTR regions also presented these candidates. Here they may play their biological role if formed. Other genes, such as orb7a and b, and orf10 were found totally void of any quadruplex candidates. We calculated the 2019-nCoV candidate's quadruplex conservation rates and quadruplex-related The highest scoring candidates found in 2019-nCoV were however not common to any other Coronaviridae member species. So, we investigated the differences between them through genome alignments and found that most of the sequence versions amongst species (6 out of 8) were still able to form potential quadruplex structures even with modifications. Therefore, these PQS and PiMS, although different from those in the 2019-nCoV, maintain their potential biological role and importance. Expanding the search for common candidates to the entire virus realm, we matched one PQS and PiMS from the 2019-nCoV with the potential quadruplexes found in four viruses from Group I belonging to the Herpesviridae, Podoviridae and Siphoviridae families (all dsDNA). With G4-iM Grinder, we analysed the entire virus realm in a similar fashion to other studies in the literature (62, 63) . However, we used a lax definition of quadruplexes to detect Gand C-structures and focused the comparison of the realm to the 2019-nCoV. Whilst the 2019-nCoV did not present any of the published quadruplex sequences listed in the GiG.DB within its genome, other viruses including a wigeon-afflicting Coronavirus did. In the entire virus realm, 1725 viruses presented at least one confirmed G4 sequence in their genome, while 195 at least one confirmed iM sequence (the dimensional discrepancies between both results may partially be due to the difference in the number of G4 and iM entries in the database; 2568 and 283 respectively). The sheer volume of species with confirmed quadruplex structures in all groups of viruses suggests that quadruplexes may be common and necessary genomic regulatory elements for viruses to "live", thrive and adapt; as seen in other organisms such as humans. However, the prevalence is not homogeneous and varies broadly at the group level although not that much at the family level. For example, some families like Group I's Herpesviridae and We, therefore, selected the best candidates to evaluate in vitro. The highly conserved candidate CoVID-RNA-1 formed a parallel G4 stable even at 45 ºC. This G4, located in the Ngene, can possibly interact with the viral RNA packaging, transcription and replication functions of the virus (64) . The second sequence, CoVID-RNA-2, also formed a stable parallel quadruplex structure. In this case, the quadruplex monomers interacted amongst themselves to form a higher order structure. CoVID-RNA-2 is located in the nsp3 region of orf1ab very near its SUD domain. This area has been associated with the increased pathogenicity of the virus compared to other Coronaviridae that do not present it (65) . Additionally, it has been suggested that the SUD domain interacts with G-quadruplexes of the host. These results, however, open the possibility of an intrinsic gene modulation that may be linked with an increased virulence. Such a hypothesis can be extended to the SARS-CoV, as another stable PQS candidate was found in its genome in the same location (Figure 3, B1 ). For PiMS, the DNA version of a candidate located in the orf1ab gene of the 2019-nCoV and with a 100 % conservation rate formed an iM at almost neutral pH. However, the SARS-CoV version of the iM (which differs by one nucleotide in the first loop, from TT to TG) was unable to form even at pH 5.1. As TT base pairs are common capping positions, the substitution of the T might prevent the folding in SARS-CoV. Additionally, the presence of C in G4s lowers overall stability of the quadruplex as C can base pair with G and ultimately hinder G-quartet formation (66) . For C-based structures, the opposite but with the same effect might also be happening. When we analysed the RNA version of the 2019-nCoV iM, it did not form a quadruplex structure. Despite the fact that the sequences found in 2019-nCoV have an intermediate probability of formation, RNA iMs are known to be less stable than their DNA-versions (59) . Still, G4-iM Grinder methodology identified several more candidates with the potential to form iMs in the virus. These results prove that especially for DNA, G4-iM Grinder can be used to find and characterize iMs in even C-poor genomes. Overall, these results greatly expand the current knowledge we have regarding quadruplexes and the 2019-nCoV (67) , and open the door for targeting viruses in general, and the 2019-nCoV in particular, through the use of these nucleic sequences as therapeutic targets in future anti-viral treatments. The supplementary material is available online and includes information regarding the genomes used, how to access the results and additional figures. 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