Non-Coding RNA Scientific Board wishes you an exciting and fruitful read.We are delighted to share with you our ninth Journal Club and highlight some of the most interesting papers published recently. We hope to keep you up-to-date with non-coding RNA research works that are outside your study area. The Cell, Carolyn Bertozzi’s group reports on glycoRNAs—glycan-RNA conjugates that reside on the cell surface and interact with anti-dsRNA antibodies and proteins that bind sialic acid. Mammalian glycans are short sugar chains that regulate cellular processes through macromolecular attachment. Although lipids and proteins are well-known targets of glycosylation, RNA is not thought to be a scaffold for glycan modification. In a recent issue of Leveraging expertise in metabolic labeling and biorthogonal chemistry, genetics, and biochemistry, the authors discovered and characterized glycoRNAs in multiple mammalian cell lines and tissues . DespiteAlthough more work is needed to define the range of glycan modifications, determine the precise nature of the glycan-RNA linkage, delineate glycoRNA biosynthesis and trafficking mechanisms, elucidate roles in extracellular biology, and explore the implications for autoimmune and other diseases, this landmark paper “points to a new axis of RNA glycobiology” .Takotsubo cardiomyopathy, also known as broken heart syndrome, is characterized by transient systolic dysfunction of the left ventricle not attributed to coronary artery disease. This condition follows experiences of extreme emotional or physical stress and is more common in women. While cardiologists have known for some time that broken heart syndrome exists, this condition remains poorly understood. Previously shown to be elevated in Takotsubo patients, a recent study assessed miR-16 and miR-26a in a pre-clinical model of Takotsubo-like cardiomyopathy using subcutaneous adrenaline injection [Molecular Cell, Skalska at al. described how nascent RNA binds a set of proteins, thus hindering their activity on chromatin [Non-coding RNAs and enhancer RNAs control protein—chromatin interactions at specific sites through the binding of transcription factors and chromatin remodeling proteins. In a recent paper published in hromatin .The authors observed that the inhibition of RNA Pol II transcription and induction of RNA degradation in mouse ESC produced a wide effect on protein—chromatin interactions: a set of proteins became unbound from chromatin, and another group enriched on chromatin. Moreover, they described how this control takes place, demonstrating that nuclear RNAs affect the direct interaction of proteins with nucleosomes and, furthermore, that the antagonistic action of RNA is due to a physical bond between proteins and RNA. As an example of a generalized mechanism, they described the regulation of P-TEFb , which was one of the most enriched chromatin-associated proteins upon RNA Pol II inhibition. P-TEFb binds nascent pre-mRNAs and is regulated by 7SK ribonucleoprotein. These findings demonstrate a novel and unexpected role of nuclear transcripts as antagonists of interactions between regulatory proteins and chromatin. Further studies are needed to identify the chromatin sites affected by this specific RNA regulation and how RNA contributes to the regulation of chromatin state.Spatial expression analyses of the putative oncogene ciRS-7 in cancer reshape the microRNA sponge theory” [In their article “ theory” , KristenWhen it comes to explaining the oncogenic features of ciRS-7 circRNA, the extremely high number of binding sites for oncosuppressive miR-7 is a characteristic that calls for sponging. However, by employing multiple techniques that allow them to spatially resolve expression patterns, the authors establish that, in colon cancer, ciRS-7 is expressed only in stromal cells, while miR-7 is expressed only in cancer cells. If this was not enough to kill the hypothesis that, in this specific context, ciRS-7 works as a sponge for miR-7, they also show that the positive correlation that is observed between ciRS-7 and putative miR-7 target genes—and that is often taken as indicative of ceRNA-based interaction—is rather ascribable to stromal co-expression and in fact applies also to other stromal circRNAs that do not contain miR-7 binding sites. This work elegantly reminds us that ceRNA-based interactions cannot rely only on correlation, while appropriate gain and loss-of-function experiments are crucial to seal the deal. It also prompts the thorough investigation of co-expression, which should be valued as the prerequisite for a relevant correlation.Frontiers in Genetics, Chiara Siniscalchi and collaborators [Effective therapeutic strategies against the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are desperately needed. In a recent issue of borators  identifyOf interest, the viral target sequences are fully conserved in more recent variants of SARS-CoV-2. Moreover, the authors elegantly prove that miR-15b is able to repress plasmid-driven spike expression.This discovery could have major implications in clinical scenarios, since inhibiting the expression of the spike transcript and targeting viral sequences of SARS-CoV-2 may provide unprecedented therapeutic approaches for the treatment of COVID-19.Science, Poirier and others reported that mammalian stem cells are also able to harness RNAi for antiviral immunity [In mammals, interferon (IFN) signaling pathways are the first line of defense against viral infections for differentiated cells. Stem cells, on the other hand, are refractory to IFN induction and signaling, and they instead utilize constitutively expressed (IFN-independent) restriction factors for protection. Invertebrates and plants do not have an IFN system, and they combat viruses using RNAi. Antiviral RNAi begins with Dicer, which cleaves viral double-stranded RNA (dsRNA) replicative intermediates into small interfering RNAs (siRNAs). These siRNAs subsequently guide the slicing of viral RNAs. In a recent article of immunity .DICER gene, whose canonical protein cuts precursor microRNAs (pre-miRNAs) well but processes dsRNAs poorly. In this study, the authors discovered an alternatively spliced isoform of Dicer called antiviral Dicer (aviD) in stem cells. The aviD transcript lacks exons 7 and 8, resulting in the deletion of a helicase subdomain that negatively regulates Dicer’s ability to process dsRNAs. Accordingly, aviD can effectively dice viral dsRNAs into siRNAs and curb viral infections in stem cells. This antiviral RNAi system does not appear to restrict the replication of DNA viruses, presumably because only RNA viruses can produce a significant amount of dsRNAs.Mammals contain only one It is interesting that different defense strategies are deployed for different cell differentiation statuses. Perhaps mammals have evolved to protect their precious stem cells from the toxic effects of IFN exposure. The scientists here have demonstrated the effectiveness of antiviral RNAi against Zika and COVID-19 viruses. Future research in this area will undoubtedly expedite the improvement of antiviral therapeutics .Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy and is estimated to become the second leading cause of cancer-related deaths by 2030. Surgical resection for localized PDAC is considered the only curative treatment option for long-term survival; however, more than 80% of patients at initial diagnosis have an unresectable or borderline resectable disease, limiting their chances to receive a curative treatment. Unfortunately, even in PDAC patients who undergo surgical resection, the 5-year survival rates are quite poor, ranging between 10% and 25%, primarily due to the local and distant metastasis of disease. These findings highlight the unmet clinical need to identify robust prognostic biomarkers, as well as potential therapeutic targets, which can help improve overall survival outcomes in patients suffering from PDAC. In a recent study published by Shen and colleagues, the authors report exciting novel findings, which reveal that the regulatory loop of circNEIL3 facilitates proliferation and metastasis in PDAC, that the expression levels of this circRNA can be used as a prognostic marker, and that this non-coding RNA may also serve as a potential therapeutic target in PDAC [In this elegant article, the authors identified that increased expression of circNEIL3 in PDAC tumor tissues was an independent risk factor associated with poor prognosis. Subsequent in vitro and in vivo functional experiments supported the oncogenic role of circNEIL3 through its role as a sponge to inhibit the tumor suppressive activity of miR-432-5p. In addition, this functional role of circNEIL3 subsequently promoted A-to-I RNA editing by regulating the expression of ADAR1. The gene regulatory activity of circNEIL3 was reported to be manifested through a feedback loop of the circNEIL3/miR-432-5p/ADAR1/GLI axis, by regulating cell cycle and epithelial-mesenchymal transition (EMT) pathways. These results are quite fascinating and provide novel evidence for a circRNA to serve as a prognostic biomarker, with a potential for therapeutic targeting in this malignancy—opening up a new concept for research and an important step forward as we usher into the era of precision oncology.


The influenza virus nucleoprotein binds to the viral RNA genome and is essential for virus replication. Here, the structure of the nucleoprotein from an H3N2 virus is presented at 2.2 Å resolution. Influenza A viruses of the H1N1 and H3N2 subtypes are responsible for seasonal epidemic events. The influenza nucleoprotein (NP) binds to the viral genomic RNA and is essential for its replication. Efforts are under way to produce therapeutics and vaccines targeting the NP. Despite this, no structure of an NP from an H3N2 virus has previously been determined. Here, the structure of the A/Northern Territory/60/1968 (H3N2) influenza virus NP is presented at 2.2 Å resolution. The structure is highly similar to those of the A/WSN/1933 (H1N1) and A/Hong Kong/483/97 (H5N1) NPs. Nonconserved amino acids are widely dispersed both at the sequence and structural levels. A movement of the 73–90 RNA-binding loop is observed to be the key difference between the structure determined here and previous structures. The data presented here increase the understanding of structural conservation amongst influenza NPs and may aid in the design of universal interventions against influenza. IAVs have a broad host range, covering a wide variety of mammals and birds. However, currently only IAVs of two subtypes, H1N1 and H3N2, exhibit sustained human-to-human transmission.Influenza A viruses (IAVs) make a large contribution to the seasonal influenza burden and have established pandemic potential. The major antigenic components of IAVs are the hemagglutinin and neuraminidase proteins that decorate the viral envelope. These proteins are used to classify IAVs into different subgroups by assigning them H and N numbers , each encoding at least one essential protein. Each segment is assembled into a ribonucleoprotein complex, with the 5′ and 3′ termini both bound by the trimeric influenza virus polymerase. The rest of the segment is bound, on average, every 25 nucleobases  and transformed into competent DH5α cells. Plasmid DNA was then extracted using a QIAprep Spin Miniprep kit (Qiagen) and successful integration of the insert was confirmed by sequencing. The constructs were transformed into Escherichia coli BL21 (DE3) cells and a 50%(v/v) glycerol stock was produced and stored at −80°C.The sequence for the NT60 NP containing an R416A mutation was amplified from the vector pFL-TAP-NP R416A  and grown at 37°C overnight. The following day, the overnight culture was used to inoculate 2 l LB medium at a ratio of 1:100. Once an OD600 of 0.6 had been reached, protein expression was induced by the addition of isopropyl β-d-1-thiogalactopyranoside to a final concentration of 1 mM and the temperature was reduced to 18°C. After 16 h, the bacteria were pelleted by centrifugation at 4000g for 15 min at 4°C. The pellets were then resuspended in 25 ml wash buffer  with the addition of 50 µl 1 M DTT, 2.5 mg RNase A, one SIGMAFAST protease inhibitor tablet (Sigma), 10 µl Benzonase Nuclease (Sigma) and 35 mg lysozyme. The pellet was then resuspended prior to lysis by sonication. The lysed cells were centrifuged at 35 000g for 45 min at 4°C. 1 ml Glutathione Sepharose 4B beads  was added to the clarified supernatant, which was incubated at 4°C for 3 h with gentle rotation. The beads were collected by centrifugation at 2000g at 4°C for 3 min and the supernatant was removed. The beads were then washed five times with high-salt wash buffer . The beads were washed again with wash buffer containing 5 mM DTT before being resuspended in 10 ml wash buffer supplemented with 5 mM DTT, 0.2 mg HRV 3C protease and 5 µl Benzonase Nuclease. After incubation overnight at 4°C with gentle rotation, the beads were pelleted at 2000g for 5 min at 4°C. The supernatant containing released protein was then collected and concentrated.Bacteria from the glycerol stock were used to inoculate 10 ml lysogeny broth (LB) containing ampicillin  equilibrated with a buffer consisting of 25 m2.2.M HEPES–NaOH pH 7.5, 150 mM NaCl. After incubation for 10 min at room temperature, the mixture was subjected to size-exclusion chromatography (SEC) as described earlier. The NP-containing fraction was collected and the A260/A280 ratio was assessed. The ability of the purified NP to bind DNA was assessed by mixing the purified NP in a 4:1 molar ratio with a 100-nucleotide DNA in buffer consisting of 25 mM HEPES–Na pH 7.5, 150 mM NaCl. After incubation for 10 min at room temperature, the mixture was subjected to SEC.The ability of the purified R416A NP to bind RNA was assessed by mixing a 1:1 molar ratio of NP with RNA of either five (5′-AGUAG-3′) or 14 (5′-CCUCUGCUUCUGCU-3′) nucleotides in length in buffer consisting of 25 met al., 2012M HEPES–NaOH pH 7.5, 150 mM NaCl) containing 3 µg NP, 20 µM RNA and a 1:100 dilution of SYPRO Orange (Invitrogen). Melting curves were fitted and melting temperatures were determined using the JTSA web server  values.A number of data sets were collected from cryocooled crystals at Diamond Light Source (DLS), Didcot, UK. Data-collection parameters and merging statistics for the best-diffracting crystal are summarized in Table 32.5.phenix.xtriage . The peak position and the A260/A280 ratio of 0.49 indicate that the NP was successfully stripped of endogenous nucleic acids from the expression host.The NT60 monomeric mutant R416A NP was expressed in NP Fig. 1a. The pb). The melting temperature of the NP mixed with a 14-nucleotide RNA was increased by 2.8°C compared with that of the NP in the absence of RNA , suggesting that this association increased the stability of the NP. Shorter oligoribonucleotides did not significantly increase the melting temperature, although it cannot be excluded that the NP could be stabilized by shorter length RNAs with different sequences.The ability of the monomeric R416A NP to bind RNA was investigated using a ThermoFluor assay, in which the melting temperature of the NP was determined in association with different length RNAs Fig. 1b. The mA260/A280 ratio of the NP-containing fraction was then measured post-SEC. The NP mixed with the five-nucleotide RNA gave an A260/A280 value of 0.53 and the NP mixed with the 14-nucleotide RNA gave a value of 1.05. This indicates that the 14-nucleotide RNA is able to associate with the NP strongly enough to remain bound through SEC, but the five-nucleotide RNA is not. The ability of the R416A NP to bind DNA was also assessed by mixing purified NP in a 4:1 molar ratio with a 100-nucleotide DNA and performing SEC. This produced a second, earlier elution peak  that is likely to represent multiple NPs associating with a single piece of DNA (100-nucleotide DNA has a mass of ∼30.7 kDa).RNA binding was further assessed by mixing the purified R416A NP in a 1:1 molar ratio with a five- or 14-nucleotide RNA. The ak Fig. 1a that ic), with two NPs per asymmetric unit (referred to as chains A and B), in space group P21. The NP structure consists of head and body domains composed primarily of α-helices. A basic groove, thought to be the site of RNA binding, lies at the interface of these two domains. This groove contains a large number of arginine and lysine residues that, whilst located closely together in the folded structure, are dispersed widely in the protein sequence. Both NP chains are resolved from residues 21 to 389. Most of the oligomerization loop could not be resolved, with residues 390–417 and 390–437 disordered in chains A and B, respectively. At the C-terminus, residues 452–461 and 497–498 were not resolved.A range of crystallization trials were set up for the NT60 R416A NP both in the presence or absence of a 1.7-fold molar excess of 14-nucleotide RNA. Despite its ability to bind to and be stabilized by 14-nucleotide RNA, no RNA could be resolved from the crystals produced in its presence. The best-diffracting crystal produced in the absence of RNA gave a maximum resolution of 2.2 Å Fig. 1c, with a) and the structural level . Only one nonconserved residue is present in the basic region forming the predicted RNA-binding groove . A lysine at position 77 in the NT60 and WSN NPs is replaced by an arginine in the HK97 NP, maintaining the basic charge.The amino-acid sequence of the NP is highly conserved amongst IAVs. The NT60 NP shares 93.6% and 91.4% amino-acid sequence identity with the WSN (H1N1) and HK97 (H5N1) NPs, respectively, for which structures have previously been determined. The structure of the NT60 R416A NP is highly similar to other published IAV NP structures, with root-mean-square deviations of 1.2 Å compared with the WSN R416A NP (across 439 pairs), 4.0 Å compared with the WSN NP (across 393 pairs) and 5.5 Å compared with the HK97 NP (across 429 pairs). The differences in the amino-acid sequences of these three IAV NPs are widely dispersed both at the sequence level Fig. 2a and thel Fig. 2b. Only ve Fig. 2c. A lyset al., 2008A of our model we observe that residues 82–89 point away from the RNA-binding groove . The density for this region is incomplete in chain B. The 73–81 region of the loop appears to adopt a more conserved structure. This region of the loop appears to be critical to RNA binding, with simultaneous mutation of the Arg74 and Arg75 residues along with Arg174, Arg175 and Arg221 (which are located on the opposite side of the RNA-binding groove) having been shown to abolish RNA binding (Ng et al., 2008The major difference between the structure presented here and those previously determined is the position of the 73–90 loop, the deletion of which produces an approximately fivefold decrease in RNA-binding affinity (Ng ve Fig. 2d. The det al., 2013et al., 1999We observe that the C-terminus of the NT60 R416A NP folds towards the RNA-binding groove. This was observed for the R416A WSN monomeric mutant NP structure but not in the oligomeric structures. It has been suggested that this folding of the tail reduces the positive charge of this groove (Chenavas We have presented the structure of the NT60 R416A NP at 2.2 Å resolution. The structure is highly similar to that of previously reported NP structures, but contributes to our understanding of structural conservation amongst the NPs from IAVs. This may aid in the design of therapeutics with activity against multiple subtypes of IAV to improve responses to future epidemic and pandemic events.H3N2 influenza virus nucleoprotein, 7nt8PDB reference:


The HFD with KrO was compared to an HFD control group to evaluate the effects on fatty acid composition and associated inflammation in epididymal white adipose tissue (eWAT) and the liver during obesity development. KrO treatment increased the concentrations of EPA and DHA and associated oxylipins, including 18-HEPE, RvE2 and 14-HDHA in eWAT and the liver. Simultaneously, KrO decreased arachidonic acid concentrations and arachidonic-acid-derived oxylipins . In eWAT, KrO activated regulators of adipogenesis , induced a shift towards smaller adipocytes and increased the total adipocyte numbers indicative for hyperplasia. KrO reduced crown-like structures in eWAT, and suppressed HFD-stimulated inflammatory pathways including TNFα and CCL2/MCP-1 signaling. The observed eWAT changes were accompanied by reduced plasma leptin and increased plasma adiponectin levels over time, and improved insulin resistance (HOMA-IR). In the liver, KrO suppressed inflammatory signaling pathways, including those controlled by IL-1β and M-CSF, without affecting liver histology. Furthermore, KrO deactivated hepatic REL-A/p65-NF-κB signaling, consistent with increased PPARα protein expression and a trend towards an increase in IkBα. In conclusion, long-term KrO treatment increased several anti-inflammatory PUFAs and oxylipins in WAT and the liver. These changes were accompanied by beneficial effects on general metabolism and inflammatory tone at the tissue level. The stimulation of adipogenesis by KrO allows for safe fat storage and may, together with more direct PPAR-mediated anti-inflammatory mechanisms, attenuate inflammation.The development of obesity is characterized by the metabolic overload of tissues and subsequent organ inflammation. The health effects of krill oil (KrO) on obesity-associated inflammation remain largely elusive, because long-term treatments with KrO have not been performed to date. Therefore, we examined the putative health effects of 28 weeks of 3% ( Metabolic overload caused by excessive intake of energy-dense foods promotes the development of obesity, which is characterized by inflammation in white adipose tissue (WAT) and the liver . During Krill oil (KrO), a marine oil extracted from Antarctic krill, is rich in phospholipids , most of which are phosphatidylcholines >85%). KrO has a high content of long-chain omega-3 polyunsaturated fatty acids (PUFAs), in particular eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) . Lipids 5%. KrO hw/w) in mice, since the health effects of KrO on obesity-associated organ inflammation remain largely elusive due to the lack of long-term treatment studies using physiologically relevant KrO concentrations. A small number of relatively short studies  KrO supplementation  was treated with an energy-dense high-fat diet . The KrO treatment group received an HFD in which 3% of the total diet was replaced with KrO (KrO diet). The KrO  itself contained EPA ≥150 mg/g and DHA ≥70 mg/g, which is approximately 20% of EPA and DHA fatty acids in KrO. Fatty acids are structural components of lipid species that are efficiently taken up in the intestine (phospholipids). KrO is a marine oil that is particularly rich in phospholipids and the KrO used in this study contained ≥560 mg/g phospholipids, of which ≥480 mg was phosphatidylcholine. At an expected average daily intake of 3 g diet per mouse, the dietary intake of KrO was 0.09 g/mouse/day on average. HFD and KrO diets were isocaloric. A reference group remained on a low-fat control chow diet (n = 6) .All animal experiments were performed in accordance with the Animal Care and Use Committee and ethical approval by an independent Animal Welfare Body . Male Ldlr−/− Leiden mice were obtained from the breeding facility of TNO Metabolic Health Research, Leiden, The Netherlands. All mice were group-housed in an AAALAC-accredited animal facility  and had ad libitum access to food and water. Body weight and blood glucose data obtained before the start of dietary treatment were used to match mice into three comparable groups, to ensure that group differences at the end were attributable to the treatment they received during the study and not due to differences at baseline. The control group . Blood samples were taken from the tail vein at the start of the study and after 8 weeks, 16 weeks and 28 weeks. In week 28, animals were terminated after 5 h fasting via gradual-fill COwww.graphpad.com, accessed on 23 March 2021). Free fatty acids (FFAs) were measured in orlistat  [Analyses of cholesterol, triglycerides, insulin, leptin, adiponectin, ALAT in fasting EDTA plasma and blood glucose were performed as described previously . The bloMO, USA) -treated v/v/v) (Sigma-Aldrich). The vial was briefly vortexed and heated (100 °C for 45 min). After cooling, hexane  and HPLC-grade water were added, and samples were vortexed and centrifuged to separate layers. An aliquot of the hexane layer was used for gas chromatography (GC). GC was carried out using a GC-2010  equipped with a SP-2560, 100-m fused silica capillary column . Fatty acids were identified and calibrated using a standard mixture of defined fatty acids . Fatty acid composition was expressed relatively  and given in absolute concentrations (µg fatty acid per mg WAT or liver tissue).Dry blood spots (DBSs) collected during blood sampling, as well as tissue collected at sacrifice from eWAT and the liver, were analyzed for their fatty acid composition . Briefly, blood was collected during blood sampling after 28 weeks of treatment on filter paper pre-treated with an antioxidant cocktail (Fatty Acid Preservative Solution) and dried at room temperature for 15 min. Tissue samples were weighed and transferred into screw-cap glass vials that contained tritricosanoin as an internal standard (tri-C23:0 TG) . These tissues were homogenized and then extracted with a modified Folch extraction. A portion of the organic layer was transferred to a screw-cap glass vial and dried in a speed vac. The dried tissue samples and a punch of the DBS filter paper in screw-cap glass vials were treated with BTM solution -EET-d11, 0.66 ng/mL 8-iso-PGF2 alpha-d4 and 3.3 ng/mL DHA-d5, all Cayman Chemical, Ann Abor, MI, USA) and 200 µL water was added to the mixture. Samples were incubated for 20 min at −20 °C and centrifuged . Supernatant was diluted with water, acidified to pH ±3.0 using formic acid  and applied to C18 SPE cartridges . The obtained samples were cleaned consecutively with water and n-hexane (VWR) and eluted using methyl formate (Sigma-Aldrich). The eluate was dried at 40 °C under a stream of nitrogen and reconstituted in 40% MeOH. Samples were analyzed using an LC-MS/MS system consisting of two LC-30AD pumps, a SIL-30AC autosampler and a CTO-20AC column oven . Samples were injected with an autosampler (at 6 °C) and separated on a Kinetex C18 column  using a gradient of 0.01% acetic acid  in water  and 0.01% acetic acid in MeOH (eluent B) with the oven at 50 °C. The gradient was as follows: 0.0–1.0 min constant at 30% B, 1.0–1.1 min linear increase to 45% B, 1.1–2.0 min linear increase to 53.5% B, 2.0–4.4 min linear increase to 55.5% B, 4.0–7.0 min linear increase to 90% B, 7.0–7.1 min linear increase to 100% B, 7.1–9.0 min constant at 100% B, 9.0–9.5 min linear decrease to 30% B, 9.5–11.5 min constant at 30% B. Detection was achieved on a Qtrap 6500  equipped with an ESI source. The MS was operated in negative scheduled MRM mode, with the source needle voltage at −4500 V, drying temperature of 450 °C, ion source gas 1 and 2 (both air) at respectively 40 and 30 psi and the nitrogen nebulizer gas at 30 psi. The entrance potential was set to 10 V and the collision gas flow to ‘medium’. Individually optimized parameters for each compound can be found in White adipose and liver tissues from sacrificed mice were homogenized in water at a concentration of 0.33 mg/µL . WAT (10 mg) or liver tissue (2.7 mg) homogenates were mixed with 600 µL MeOH  containing internal standards  relative retention times between samples and authentic standard material. Furthermore, the tandem mass spectra for PDX were closely matched -RvE3 and 18(S)-RvE3 were gifts from Dr. Makoto Arita ; all other standards were obtained from Cayman Chemicals.The detected lipid mediators PDX and RvE matched . In the material . StandarParaffin-embedded 5-µm-thick cross sections of eWAT were stained with hematoxylin-phloxine-saffron and scanned for digital analysis . Cell size and counts of adipocytes were analyzed using Adiposoft . Inflamm2.The histopathological analysis of liver steatosis and hypertrophy was performed on 3-µm-thick hematoxylin-eosin-stained cross sections of the medial lobe using a standardized method for rodent liver histopathology, based on the human NAS scoring system ,30. The 2•4 H2O, 32 mL of 95–97% H2SO4 added to 960 mL of CH3OH:H2O 1:1 v/v). The liver triglyceride bands were quantified with a ChemiDoc Touch Imaging System  using Image-lab version 5.2.1 software (Bio-Rad) and were expressed per mg protein.Total hepatic triglyceride content was determined in crude liver homogenates by following the Bligh and Dyer method for lipid extraction with methanol and chloroform . In the n = 5 chow, n = 9 HFD and n = 9 KrO liver samples, as well as n = 5 chow, n = 8 HFD and n = 10 KrO eWAT samples, were used. DEGs were used as inputs for pathway analysis through Ingenuity Pathway Analysis . IPA uses gene expression data of all known downstream target genes to predict the activation or deactivation of an upstream regulator. Z-scores greater than 2 indicate the enhanced activity of an upstream regulator, whereas a Z-score less than −2 indicates the reduced activity of an upstream regulator [p-value indicates the significance of the gene enrichment of these upstream regulators.Next generation sequencing (NGS) was performed essentially as described . Brieflyn = 4/group) were homogenized in lysis buffer containing 150 mM NaCL, 1 mM EDTA PH = 8, 50 mM Tris-HCL PH = 7.4, 1% Igepal, 0.25% deoxycholate, 0.1% SDS, 1 mM PMSF, 1 mM Na3VO4 and complete mini EDTA-free protease inhibitor . Homogenates were centrifuged at 13,000 rpm for 15 min at 4 °C, and the protein content of the supernatant was determined using the BCA Protein Assay Kit (Thermo Fisher Scientific). Proteins (50 ug) in 2× SDS Laemmli Sample Buffer  were boiled for 5 min at 95 °C. Subsequently, samples were separated on a 4–20% (w/v) SDS-page gel . Proteins were transferred onto Trans-blot Turbo mini PVDF blotting membranes (Bio-Rad) using the MIXED MW program on the Trans-blot Turbo Bio-Rad machine. The blotting membranes were blocked for 1 h with 5% (w/v) milk powder in tris-buffered saline with 0.1% Tween 20 and incubated overnight at 4 °C with either the primary antibody IκBα , PPARα  or αTubulin . Secondary antibody  was added and SuperSignal West Femto (Thermo Fisher Scientific) was used to visualize protein bands. Blots were analyzed with a ChemiDoc Touch Imaging system (Bio-Rad) and band intensities were normalized to αTubulin.Liver tissue from HFD- and KrO-treated mice (t-tests (α = 0.05) if the data were normally distributed with equal variances. Data sets that were not normally distributed or with unequal variances were tested with a Mann–Whitney U test. IPA analysis to determine differentially expressed genes were based on Fisher’s exact test (α = 0.01).All data shown are presented as mean ± standard deviation (SD). The experiments investigated the null hypothesis that KrO does not have beneficial effects on disease parameters relative to controls (HFD). Therefore, KrO was compared to the HFD control group, and data from chow mice were provided as a reference. The significance of differences between KrO and HFD was tested using one-sided During 28 weeks of HFD feeding, body weight increased from 29.4 g to 52.7 g in the HFD control group. EchoMRI analysis showed that the observed weight gain relative to chow could mainly be ascribed to an increase in fat mass . KrO treTo assess whether KrO altered the omega-3 FA content in the circulation, we analyzed the FA composition in dry blood spots . CompareWe next examined whether similar changes would occur at the tissue level . In eWATBy contrast, KrO treatment significantly reduced ARA concentrations in the circulation by 59% compared to HFD (0.4-fold reduction), i.e., below the levels of chow reference mice . In WAT Collectively, these data indicate that KrO treatment affected the lipid composition in the circulation, eWAT and the liver in a comparable way: all tissues showed a marked increase in omega-3 FAs and a decrease in ARA concentrations. The highest absolute concentrations of omega-3 FAs were observed in the liver.We next investigated the possible effects of KrO on WAT histology, and analyzed adipocyte cell size, WAT inflammation (CLS) and the total number of adipocytes in eWAT.2) was similar to that of the chow reference group (4724.4 ± 891.1 µm2). Treatment with KrO significantly reduced the average adipocyte size (4200.1 ± 709.6 µm2) relative to HFD (2) by KrO, whereas the number of large adipocytes (>8000 µm2), which reportedly release many inflammatory mediators [The average adipocyte cell size of the HFD control group . The number of CLSs in HFD was strongly increased relative to chow (2.2 ± 4.8 CLSs per 1000 adipocytes). Treatment with KrO prevented HFD-induced CLS formation and significantly reduced CLS numbers by approximately 42% D, demons2). By contrast, KrO upregulated all EPA- and DHA-derived oxylipins, whereas almost all omega-6 derived pro-inflammatory oxylipins were significantly suppressed with the KrO diet  was similar to that of the chow reference group (1.08 × 107). Interestingly, KrO-fed mice showed a significant 1.4-fold increase in adipocyte numbers (1.54 × 107), which is clearly indicative of hyperplasia .Plasma leptin levels were 2.5 ± 2.0 ng/mL at t = 0 and were increased by HFD, reaching 58.1 ± 10.8 ng/mL in week 28, which differed significantly from the chow reference group (26.6 ± 8.0 ng/mL). KrO significantly attenuated this HFD-evoked increase in leptin (37.7 ± 6.4 ng/mL). Furthermore, the total leptin exposure over time  was significantly reduced by KrO . Plasma Fasting blood glucose levels and HFD-induced increases in plasma insulin levels were reduced with KrO. Subsequently, the HOMA-IR values were significantly lower in the KrO group, indicating that KrO improved insulin resistance. Genome-wide gene expression analysis showed that HFD inactivated upstream regulators that are important in insulin signaling (INSR and IGF1R) in both the liver and eWAT, and KrO counteracted this effect in eWAT .Free fatty acid (FFA) plasma concentrations were not significantly raised with HFD, whereas KrO significantly increased FFAs compared to the HFD in line with the lower insulin concentrations.Plasma ALT and AST levels were significantly increased by the HFD compared to the chow reference diet. This increase in both ALT and AST tended to be less pronounced in the KrO group.Taken together, KrO reduced leptins and increased adiponectin exposure, which was paralleled by an improvement in HOMA-IR.HFD treatment resulted in the development of hepatic steatosis, hepatocellular hypertrophy and the formation of F4/80-positive CLSs, indicating macrophage aggregation around dying hepatocytes A–D. Thesp = 0.066) towards an increase in IκBα protein levals by KrO relative to HFD. PPARα protein expression was significantly correlated with IκBα protein expression (R2 = 0.9)  D–F.2, PGE2, PGF2 and TXB2). By contrast, KrO-treated livers exhibited lower levels of ALA and higher levels of LA, suggesting that the processing of omega-3 FAs is enhanced in the presence of KrO. Indeed, all detectable EPA- and DHA-derived metabolites  were significantly increased with KrO and a strong signal corresponding to genuine resolvin RvE2  was only detectable in KrO-fed mice. Strikingly, KrO suppressed the formation of oxylipins with proinflammatory properties downstream of ARA to such an extent that they were no longer detectable.Next, we investigated whether KrO affected the intrahepatic levels of bioactive lipids using the same oxylipin platform as before. Altogether, KrO quenched inflammatory signaling pathways and upregulated the expression of proteins that can interfere with NF-κB signaling . It also suppressed the accumulation of lipids and oxylipins with pro-inflammatory properties and strongly induced the presence of lipid species that contribute to an anti-inflammatory milieu.This study shows that the fatty acid and oxylipin content of adipose tissue and the liver can be strongly modulated with KrO during the development of obesity, and that KrO treatment attenuates inflammatory processes, resulting in a reduced inflammatory tone. Lipidomic analyses, in conjunction with functional regulator analyses of signaling pathways in adipose tissue and the liver, provided rationales for possible direct and indirect mechanisms by which KrO exerts its effects. One of the direct effects is the increase in anti-inflammatory oxylipins. An important indirect effect is the activation of adipogenic gene expression programs in adipose tissue, accompanied by WAT hyperplasia. The observed increase in WAT storage capacity and the associated decrease in inflammation can contribute to whole-body metabolic health, which is consistent with the observed improvement in insulin resistance  and adipokine concentrations.2, 14-HDHA, 17-HDHA, PDX/10S,17S-diHDHA), whereas it suppressed the HFD-induced formation of ARA-derived oxylipins , which often exert pro-inflammatory effects [2, PGE2 and PGF2 levels in both WAT and the liver, which can stimulate chemotaxis of immune cells [2, PGE2 and PGF2 levels were even lower with KrO compared to the chow diet. Conversely, HFD feeding diminished the levels of anti-inflammatory oxylipins such as 18-HEPE, a precursor for E series resolvins, and 17-HDHA in liver [2, 14-HDHA, 17-HDHA, PDX and other anti-inflammatory oxylipins were increased with KrO in this study and are thought to be directly involved in inflammation resolution mechanisms, as reported by [A general FA compositional analysis revealed that KrO strongly increased the omega-3 PUFA content in the circulation, WAT and the liver , while simultaneously decreasing the omega-6 PUFA content in these organs, with pronounced reductions in ARA. The observed fatty acid composition changes were grosso modo comparable for both organs, yet the absolute omega-3 PUFA concentrations per milligram of tissue were clearly higher in the liver. Importantly, a refined oxylipin LC-MS/MS analysis showed that KrO strongly increased lipid species with anti-inflammatory properties ,36,37 de effects ,39,40,41ne cells ,43 by inne cells ,44. KrO orted by ,46,47,48It is likely that inflammation-resolving oxylipins were formed from their precursor fatty acids present in KrO (EPA and DHA), but these precursors themselves can also be enzymatically synthesized from ALA. The enzymes responsible for omega-3 PUFA processing are the same as those for omega-6 processing but the rate-limiting enzyme, delta-6-desaturase, has a higher preference for omega-3 FAs relative to omega-6 FAs ,50. ThusThe observation that the levels of most PUFAs and oxylipins are higher in the liver than in WAT is consistent with metabolic studies in mice . These tIndeed, pathway and upstream regulator analyses clearly demonstrated a suppression of HFD-induced inflammatory pathways by KrO in WAT and the liver. For example, KrO deactivated multiple inflammatory HFD-stimulated pathways, including those controlled by TNFα, TNF receptor-associated protein 1 (TRAP1) and CCL2 in eWAT, as well as the IL-1β and M-CSF pathways in the liver. Attenuation of TNFα/IL-1β/CCL2-mediated inflammation in metabolic organs has been shown to improve insulin resistance ,54,55, cThe deactivation of TRAP1 by KrO points to reduced oxidative-inflammatory stress in eWAT because TRAP1 is a mitochondrial heat shock protein involved in the maintenance of mitochondrial integrity under stress or pathological conditions .de novo lipogenesis because SREBF1 is significantly activated, and insulin, the transcriptional inducer of Srebp1c, is elevated.In addition, KrO stimulated the activity of PPARγ, RB1, CEBPα, KLF15 and STAT5A, all of which are transcriptional master regulators that orchestrate adipogenesis ,64, and per se, or specific KrO components or metabolites formed from KrO, or a combination of the above, are responsible for the beneficial effects observed in KrO-treated mice. We could have included additional groups to substantiate these findings, for instance, groups in which KrO was administered orally superimposed on the HFD. Another limitation is that we cannot estimate the contribution of the PUFAs attached to phospholipids relative to those in other lipid classes. It is possible that the profound effects of KrO are related to its high phospholipid content and the increased bioavailability of EPA and DHA [n = 15 mice) for high statistical power; the extensive molecular (omics) analyses of adipose tissue and the liver using next-generation sequencing technology to identify activated pathways and upstream regulators in both organs; the profiling of fatty acids in three compartments , which provides information on the relative enrichment of PUFAs in each of these tissues; and one of the most comprehensive oxylipin analysis reported so far, including adipose tissue and the liver. Our oxylipin profiling analyses at the tissue level showed that HFD treatment markedly increased oxylipins with proinflammatory properties, whereas oxylipins with inflammation-resolving properties were reduced. KrO treatment appeared to counteract these HFD-evoked changes. These KrO-dependent changes of the inflammatory tone within eWAT and the liver can, at least partly, be explained by the ingested PUFAs, and similar effects may occur in other species. In a human study, it has been shown that a linear dose–response relationship exists between the intake of EPA and DHA and the levels of anti-inflammatory oxylipins measured in plasma [This study has limitations and strengths. Intrinsic to the set-up of the study, we cannot distinguish whether the replacement of HFD by KrO  and DHA , which cn plasma . This suWe have demonstrated that long-term KrO treatment (28 w) improves the fatty acid composition in the circulation, WAT and the liver. This improvement is characterized by marked elevations in omega-3 FAs and associated oxylipins, which can exert beneficial effects on metabolism  and tissue inflammation. Functional gene expression and pathway analyses, combined with lipidomic analyses, provide rationales for direct and indirect effects of KrO-derived PUFAs and oxylipins on metabolic and inflammatory pathways controlled by PPARα/PPARγ. The stimulatory effect of KrO on adipogenesis and hyperplasia allows for the safe storage of excess fat in adipose tissue and contributes indirectly to the suppression of inflammation. This indirect effect complements the more direct mechanisms that intercept inflammatory pathways on the molecular level.


Large volumes of high-throughput sequencing data have been submitted to the Sequencing Read Archive (SRA). The lack of experimental metadata associated with the data makes reuse and understanding data quality very difficult. In the case of RNA sequencing (RNA-Seq), which reveals the presence and quantity of RNA in a biological sample at any moment, it is necessary to consider that gene expression responds over a short time interval  in many organisms. Therefore, to isolate RNA that accurately reflects the transcriptome at the point of harvest, raw biological samples should be processed by freezing in liquid nitrogen, immersing in RNA stabilization reagent or lysing and homogenizing in RNA lysis buffer containing guanidine thiocyanate as soon as possible. As the number of samples handled simultaneously increases, the time until the RNA is protected can increase. Here, to evaluate the effect of different lag times in RNA protection on RNA-Seq data, we harvested CHO-S cells after 3, 5, 6, and 7 days of cultivation, added RNA lysis buffer in a time course of 15, 30, 45, and 60 min after harvest, and conducted RNA-Seq. These RNA samples showed high RNA integrity number (RIN) values indicating non-degraded RNA, and sequence data from libraries prepared with these RNA samples was of high quality according to FastQC. We observed that, at the same cultivation day, global trends of gene expression were similar across the time course of addition of RNA lysis buffer; however, the expression of some genes was significantly different between the time-course samples of the same cultivation day; most of these differentially expressed genes were related to apoptosis. We conclude that the time lag between sample harvest and RNA protection influences gene expression of specific genes. It is, therefore, necessary to know not only RIN values of RNA and the quality of the sequence data but also how the experiment was performed when acquiring RNA-Seq data from the database. High-throughput sequencing (HTS) has been applied in several fields of biological research since its appearance about a decade ago and has made it possible to collect data with substantially higher-throughput and lower-cost . Large ve.g., FastQC) without metadata containing experiment-specific information. For example, this author has obtained two RNA samples: one isolated from cultured cells in 30 min after sampling, and the other isolated from the same cells in 60 min after sampling; both of these RNA samples prepared in the same laboratory showed high RNA integrity number (RIN) values indicating non-degraded RNA. However, it remains questionable whether data obtained from RNA samples with different time lags from sample harvest to RNA protection can be handled equally. In the case of RNA sequencing (RNA-Seq), it is necessary to consider that changes in gene expression can occur over a short time period  in many organisms. For instance, in the filamentous fungus Aspergillus fumigatus, 23% and 35% of genes were differentially expressed after 30 and 120 min of hypoxia exposure, respectively  200 µL of 1 × PBS is added to the cell pellet and pipetted up and down five times to thoroughly suspend the pellet. (4) The centrifuge tube is centrifuged for 5 min at 300×g and all supernatant is removed. (5) The centrifuge tube is flicked to loosen the cell pellet from the bottom. (6) 350 µL of buffer RLT  is added to the pellet and pipetted up and down five times to mix thoroughly. (7) The entire cell suspension is immediately loaded onto a QIAshredder spin column (QIAGEN) and homogenized by centrifugation for 2 min in a microcentrifuge at maximum speed. When cells are treated by using the above strategy, the time lag until the addition of RNA lysis buffer, which contains guanidine hydrochloride, is critical. Because RNA in cells suspended in RNA lysis buffer immediately inactivates RNases to ensure isolation of intact RNA, the time lag until the addition of this reagent should be as short as possible. If the number of samples is less than 10, RNA lysis buffer can be added to the cell pellet within about 15 min. As the number of samples increases, however, the time it takes for centrifuging and pipette operation for samples becomes longer. As a result, the cells remain in media or 1 × PBS at the conditions (temperature and CO2 concentration) outside the incubator for a long time.Some cultured mammalian cells need to be suspended in 1 × PBS to remove fetal bovine serum and/or media before treatment with RNA lysis buffer. For example, the strategy for RNA sample processing from suspended Chinese hamster ovary (CHO) cells at the author’s laboratory at Nihon BioData Corporation is as follows: (1) The medium containing the suspended CHO cells is transferred from the cell culture flask to a 1.5 mL centrifuge tube. (2) The centrifuge tube is centrifuged for 5 min at 300×Here, to evaluate whether RNA-Seq data obtained from RNA samples with a different lag time until RNA protection can be analyzed equally, we harvested CHO-S cells after 3, 5, 6, and 7 days of cultivation, added RNA lysis buffer at various lag times  and CellProfiler software  cell culture was grown in 20 ml of Gibco CD-CHO medium  containing 400 µL of 200 mM L-Alanyl-L-glutamine  and 40 µL of Gibco Anti-Clumping Agent ; Thermo Fisher Scientific, Waltham, MA, USA) in a 125 mL flask. The flask was shaken (120 rpm) at 37 °C in a humidified 5% COsoftware . The imag and all supernatant was removed. An aliquot of 200 µL of Gibco PBS  was added to the cell pellet and pipetted up and down five times to resuspend thoroughly. The centrifuge tube was centrifuged for 5 min at 300×g and all supernatant was removed. The centrifuge tube was flicked to loosen the cell pellet from the bottom. An aliquot of 350 µL of the buffer RLT , which contains guanidine thiocyanate, was added to the pellet and pipetted up and down five times to mix thoroughly. The time it took to complete these steps was set to 15, 30, 45, or 60 min  after harvest by the addition of RNA lysis buffer. Two persons performed this experiment: one person opened and closed the lids of the tubes, added reagent, and carried out the pipetting, and another put the tubes in and out of a microcentrifuge. The experiment was conducted as follows . A totalr 60 min . The entDRA006016). The metadata associated with the data submission to DDBJ DRA006016 can be obtained from SRA Run Selector (https://www.ncbi.nlm.nih.gov/Traces/study/?acc=DRP004803&o=acc_s%3Aa). The quality of the raw reads was analyzed with FastQC  database was confirmed by using BLASTN searches . Then, the number of genes associated with apoptosis in the common DEGs was counted.All the reads were deposited in the DDBJ Sequence Read Archive  can be analyzed equally, we performed RNA-Seq of RNA isolated from CHO-S cells  with RNA protected at various times  following cell harvest, as shown in Shannon’s information entropy of RNA-Seq data of bach CHO-S cell culture was shown in PCA  and HCA Differentially expressed gene (DEG) analysis was conducted to explore the correlation between the processing lag time  and the gene expression. First, we compared the gene expression of RNA-Seq data between 15 min and each other time period  on each cultivation day. The numbers of common DEGs among the four different days were 4 (15 min vs. 30 min), 10 (15 min vs. 45 min), and 23 (15 min vs. 60 min) . The numPCA and HCA was then performed for genes identified as differentially expressed at least once in DEG analyses. In the PCA plot, PC1 and PC2 appeared to be associated with the processing lag time of each cultivation day . PCA fori.e., time until the addition of RNA lysis buffer) on RNA-Seq, we examined gene expression changes when RNA lysis buffer was added at various times after the harvest of CHO cells. Regardless of the number of days of cell cultivation  or the processing lag time , we obtained high-quality total RNA and high-quality sequence reads from all samples. The results of the value of Shannon’s information entropy  outside the incubator.Several studies have reported that the use of RNA samples with RIN values of around 5.0–7.0 does not negatively affect estimates of the gene expression profile e.g.,  or de noassembly . Howeverassembly , with hiassembly . In the assembly , virus iassembly , and cobassembly  have beeassembly , the timBecause the above results demonstrate that the processing lag time influences the expression level of specific genes, it is necessary to know not only the quality of the data but also how the experiment was performed when acquiring RNA-Seq data from SRA and investigating the expression level of a specific gene. However, detailed information on experimental operations, such as the processing lag time, is usually not described in manuscripts.https://protocolexchange.researchsquare.com/), Protocols.io , Journal of Visualized Experiments , and others. These repositories are an open-access, free platform for sharing, and discussing protocols and can be used during research and manuscript submission to facilitate reproducibility. However, protocol repositories usually do not show the working time of the experiment, even if it is a time-sensitive experiment like RNA isolation. Detailed protocols of this study including the processing time can be found at Protocols.io .In recent years, there has been growing focus on the importance of reporting detailed methods, resulting in several protocol repositories have been begun, such as Nature Protocol Exchange  biology laboratory RCBL;  makes itIn this study, we showed that differences in the time lag from harvesting cells to protecting RNA affect the expression level of specific genes in RNA-seq experiments. As discussed above, the data submitter needs to provide detailed information of the experiment together with the sequence reads. The database user needs to be able to investigate the validity of the data including potential problems with how the experiment was performed when acquiring HTS data from the database. Expression levels of the 23 DEGs identified in this study could potentially be used to help check whether the RNA of biological samples was properly treated.10.7717/peerj.11875/supp-1Supplemental Information 1Black filled circles, black unfilled squares, red filled circles, and red unfilled squares indicate the processing lag times of 15, 30, 45, and 60 min, respectively.Click here for additional data file.10.7717/peerj.11875/supp-2Supplemental Information 2249 genes with GO terms included “apoptotic” or “apoptosis”.Click here for additional data file.


The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection causes Coronavirus Disease 2019 (COVID-19), a pandemic that seriously threatens global health. SARS-CoV-2 propagates by packaging its RNA genome into membrane enclosures in host cells. The packaging of the viral genome into the nascent virion is mediated by the nucleocapsid (N) protein, but the underlying mechanism remains unclear. Here, we show that the N protein forms biomolecular condensates with viral genomic RNA both in vitro and in mammalian cells. While the N protein forms spherical assemblies with homopolymeric RNA substrates that do not form base pairing interactions, it forms asymmetric condensates with viral RNA strands. Cross-linking mass spectrometry (CLMS) identified a region that drives interactions between N proteins in condensates, and deletion of this region disrupts phase separation. We also identified small molecules that alter the size and shape of N protein condensates and inhibit the proliferation of SARS-CoV-2 in infected cells. These results suggest that the N protein may utilize biomolecular condensation to package the SARS-CoV-2 RNA genome into a viral particle. The packaging of the SARS-CoV-2 genome is mediated by the nucleocapsid (N) protein; this study shows that the N protein forms liquid condensates with viral genomic RNA and identifies small molecules that alter these condensates. The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus consists of a 30-kb single-stranded RNA genome packaged into a 100-nm diameter membrane enveloped virion. SARS-CoV-2 encodes for multiple proteins involved in viral assembly and propagation . While tThe mechanism by which N remodels the viral RNA and packages it into a viral particle is not well understood. Recent studies proposed that the replication and packaging of viruses involve liquid–liquid phase separation (LLPS) –18. BiomPrevious studies in positive and negative-sense RNA viruses showed that N proteins drive the formation of phase-separated condensates in the cytosol –25. The In this study, we purified the SARS-CoV-2 N protein from human embryonic kidney (HEK293) cells and observed that N protein forms biomolecular condensates with both homopolymeric and viral genomic RNA under physiological salt conditions in vitro. We also showed that the N protein forms liquid condensates in mammalian cells. Cross-linking mass spectrometry (CLMS) identified 2 regions flanking the CTD with interactions enriched within the condensed phase, and the deletion of one of these regions fully abrogated condensate formation in vitro. Together, our results indicate that the N protein phase separates with genomic RNA of SARS-CoV-2, which may play an important role in the packaging of new viral particles in host cells.sat) of 3.3 ± 1.3 μM for N protein in the presence of 50 ng/μL polyC RNA  N protein in HEK293 cells and purified it in a high salt buffer (1 M NaCl) to eliminate the retention of RNA from human cells  S1A and. ConsistNA ± SE, , lower t50) of 90 ± 1 μM NaCl (± SE)  . The add mM NaCl . The abiCondensate formation of N protein and RNA was dependent on protein–RNA stoichiometry. At 18 μM N protein, condensate formation was not observed in the presence of 0 to 5 ng/μL polyC RNA. Increasing the RNA concentration promoted phase separation with an optimal RNA concentration of 100 to 500 ng/μL, at which charge neutralization occurs with the positively charged N protein . A furthWe also showed that N-polyC condensates exhibit liquid-like, rather than solid-like, material properties. First, these condensates were nearly spherical with an aspect ratio of 1.3 ± 0.6 (mean ± SD). Second, we observed the fusion of condensates with a mean fusion time of 90 ± 30 seconds (mean ± SD) after they come into contact . FinallySimilar to polyC RNA, polyA and polyU RNA substrates produced spherical condensates at micromolar concentrations of the N protein  49]. Ho. Ho49]. Next, we sought to characterize how the N protein interacts with SARS-CoV-2 genomic RNA. The SARS-CoV-2 RNA genome was reverse transcribed and assembled into a DNA plasmid . Using tTo understand the mechanism of phase separation of the N protein, we performed CLMS to identify interactions between different domains of the full-length N protein in the absence of RNA . CLMS deNext, we performed quantitative CLMS measurements  comparinOur mass spectrometry (MS) analysis also found phosphorylation sites on the N protein . While sThe quantitative CLMS experiments show that interactions between R1 and R2 are correlated with the formation of condensates. However, we could not exclude the possibility that some of the changes in pairwise interactions are due to differences in protein structure or electrostatic interactions induced by differences in salt concentrations used for the soluble and condensate phase. To directly test the predictions of the CLMS results, we determined how different domain deletions affected phase separation of the N protein with polyC RNA under the same salt concentration , S8A FigRecent studies proposed that the N protein is phosphorylated early in infection, and this results in localization of N protein with the RTC, where it enhances transcription of subgenomic RNA . HoweverWe next sought to identify small molecules that could interfere with the phase separation of the N protein. The condensates formed by the N protein in the absence or presence of polyC or viral RNA dissolve with the addition of 10% 1,6 hexanediol, indicating that phase separation is driven, at least partially, by hydrophobic interactions  45]. In. In45]. We then tested these drugs in human pulmonary epithelial  and African Green Monkey kidney (Vero-E6) cells infected with SARS-CoV-2 see , as thes50) assay. The supernatant from Vero-E6 cells that had been cultured with virus and drugs was added to uninfected cells, and the viral titer was measured by observing CPE in these cells. In this assay, nelfinavir mesylate, nilotinib, and LDK378 each reduced SARS-CoV-2 titer viability, with nilotinib and LDK378 producing an inhibitory effect similar to remdesivir, which strongly inhibits proliferation of SARS-CoV-2 in infected cells  aTo test whether N protein also phase separates in mammalian cells, we expressed N-GFP in HEK293T cells. We observed the formation of distinct puncta in the cytoplasm of N-GFP–expressing cells, which were not observed in control cells expressing GFP only . FRAP imN = 55 cells, 2 independent experiments)  . In compIn this study, we showed that the SARS-CoV-2 N protein phase separates with viral and nonviral RNA sequences in vitro and the viscosity and shape of these condensates depend on the structure of the RNA substrate. Concurrent studies have shown that the SARS-CoV-2 N protein expressed in bacteria forms biomolecular condensates with RNA in vitro ,63,71–74We also investigated the mechanisms underlying condensate formation using CLMS and protein engineering . PreviouIt remains to be demonstrated whether condensate formation of N protein and the viral genome is essential for the propagation of SARS-CoV-2 in human cells. For example, several viruses have been shown to replicate in viral inclusion bodies that are characterized as phase-separated condensates ,24. A reN condensates may also sequester the viral assemblies from the immune response of the host cell . For exaThe phase separation of N protein with viral RNA may also facilitate the compaction and packaging of the genome into the nascent viral particle  81,82].,82.81,82Phase separation could also provide a macroscopic readout to study N protein and RNA interactions  and suggEscherichia coli cells overnight and performing a gigaprep . For protein expression, HEK293S GNTI- cells (RRID: CVCL_A785) were grown in suspension in Freestyle media  supplemented with 2% fetal bovine serum  and 1% penicillin-streptomycin  to 2 million cells/mL. Cells were spun down for 10 minutes at 1,200 g and resuspended in fresh, antibiotic-free media. For 250-mL cells, the transfection solution was created by mixing 1.8-mL polyethylenimine  dissolved in 20-mL Freestyle media and 0.66-mg DNA dissolved in 20-mL Freestyle media. The mixture was incubated at room temperature for 15 minutes before being adding it to the cell culture. Transfected cell culture was grown for 72 hours at 125 rpm at 37°C with 5% CO2 and 5% humidity.A construct for expressing N protein with a carboxyl-terminal Strep-tag was obtained from the Krogan lab (UCSF). A carboxyl-terminal yBBr labeling site was added for labeling with a fluorescent dye. Deletion mutants, ΔPLD (amino acids 2 to 30: SDNGPQNQRNAPRITFGGPSDSTGSNQNG), ΔSR , ΔR1 , and ΔR2  were generated using Gibson cloning . Sufficient amounts of DNA were obtained by growing 1 L of transfected XL1 Blue g for 10 minutes and resuspended in 50 mL lysis buffer ). Lysis was performed using 15 loose and 15 tight plunges of a Wheaton glass dounce. The lysate was clarified using a 45 minutes, 360,000 g spin in a Ti70 rotor. The supernatant was incubated with 1-mL Streptactin sepharose beads  for 1 hour. Beads were washed with 40 mL of lysis buffer followed by 30 mL labeling buffer . Beads were then collected and incubated with purified Sfp phosphopantetheinyl transferase and an LD655 dye functionalized with CoA  at room temperature for 30 minutes. Beads were washed with 30-mL labeling buffer. If proteins were to be kinase or phosphatase treated, they were additionally washed with 30 mL kinase  or phosphatase  buffer. Protein was eluted in 1 mL fractions in its final buffer supplemented with 10 mM desthiobiotin and concentrated using Amicon Ultra 30K concentrators. For kinase and phosphatase treatment, 5 μL of caseine kinase 2  or 2.5 μL λ phosphatase  was added per 50 μL concentrated protein, respectively, and the samples were incubated at 30°C for 1 hour. Final protein concentration was measured using Bradford reagent, and aliquots were snap frozen in liquid nitrogen.Cells were then harvested at 4,000 For in vitro transcription of long viral RNA, the region of interest was first PCR amplified from a plasmid  to their final concentration and introduced into the flow chamber. Samples were settled onto the coverslip for 25 minutes before imaging. We confirmed that all of the condensates were settled to the surface within 25 minutes, as we did not observe an increase in the number of condensates per viewing area of the coverslip, and we could not detect freely diffusing condensates in the flow chamber after 25 minutes. Different buffers were used for phosphatase-treated  and kinase-treated  samples.Purified protein and RNA samples were diluted into the imaging buffer  illuminator and 100X 1.49 N.A. Plan Apo oil immersion objective . The samples were excited in near-TIRF using 561 and 633 nm laser beams . The fluorescent signal was detected by Andor Ixon electron-multiplying CCD (EMCCD) camera (512 × 512 pixels). The effective pixel size was 160 nm after magnification. 10 single-frame images were acquired for each condition in each replicate.sat), the area of each condensate was quantified with Fiji using the Phansalkar function with a 30-pixel radius and a minimum condensate size of 10 pixels. The volume of the condensates was estimated from 2D projections by taking the semi-principal axis in the z-plane as the geometric average of semi-principal axes in the xy plane. The total volume of the condensates settled per micron squared on the coverslip was quantified. Conditions that resulted in measurable condensate volumes were fit to linear regression in Origin. The x-intercept of the linear regression represents csat, the minimum protein concentration that results in condensate formation. The aspect ratio was calculated for individual condensates in Fiji using the Phansalkar function with a 30-pixel radius and a minimum condensate size of 10 pixels. To measure fusion times, condensates were visualized as they settled on the imaging surface from 5 to 25 minutes after mixing. Movies were recorded at 5 frames per second. Fusion times were calculated as the time between the last frame where 2 condensates appear separated  and the first frame where the fused condensate appears nearly spherical (aspect ratio = 1.1).To calculate the saturation concentration  (64bit) Version 14.0.20.201. Data were background corrected, converted to normalized intensity, and fit to an exponential decay function in Origin.The cross-linking analysis was performed as described by McGilvray and colleagues  with dev18 column  and an M-class NanoAcuity UPLC system . Liquid chromatography–mass spectrometry (LC–MS) runs were 90 minutes long. Precursor ions were measured in the Orbitrap at 120 k resolution. Selected precursor ions (triply charged and higher) were isolated, and the product ions were measured in the Orbitrap at 30 k resolution. Samples that were analyzed for phosphorylation were run similarly except only HCD product ions spectra were collected and doubly charge precursors were included.MS was acquired on an Orbitrap Fusion Lumos coupled with an Easy-Spray nanoelectrospray ion source, a 15 cm × 75 μm PepMap CCross-linked spectra were identified with Protein Prospector 6.2.23  using thhere (or on the MS-Viewer website with search key “jyovxenjny”).Protein Prospector was used to search for phosphopeptides of the linear peptide fractions using the following parameters: tryptic specificity with 2 missed cleavages, 7 and 15 ppm precursor and product ion tolerances, and carbamidomethyl (C) fixed modification. Variable modifications were as above except that Phospho (STY) was included, and only dead-end cross-link modifications were included. Peptides were reported with a maximum expectation value of 0.001, and a minimum prospector score of 15. A site localization in peptide (SLIP) score threshold of 6 was used to determine site localization. All phosphopeptide spectra reported were manually inspected for evidence of correct site assignment. Where S or T residues are adjacent, the location of the phosphosite is ambiguous see . All phoA supplemental search of the cross-linked peak lists was made for cross-links that also contained a phosphorylation site. This search was identical to the previous cross-linking searches except that Phospho (ST) was included as a variable modification, and the search was limited to the N protein sequence. Search results containing a phosphorylation site were manually assessed. Only phosphorylation sites that had been discovered in the phospho search of the linear peptides were considered.2 ratios of heavy to light peptides were calculated and mean normalized to 0 for each of the 2 biological replicates and then transformed into log2  ratios. Weighted t tests were performed in R.For quantitating the isotopically labeled cross-links, peak areas were measured from the extracted precursor ion chromatograms (XICs) using the small molecule interface of Skyline (v20.1.0.155). A Skyline transition list was generated containing the elemental composition of each distinct peptide pair with both light and heavy BS3 modification and in each charge state detected in the Prospector search. Retention times were present in the transition list to help with peak detection. Peptide level measurements were imported into R and summarized at the level of unique residue pairs (“cross-links”). For each precursor ion, the log2, 1 mM EGTA, 1 mM DTT, 1% pluronic) was aliquoted into 384-well, glass-bottomed plates  and incubated for 5 minutes. Buffer was removed, and 0.5 μL of 2 mM compounds were stamped into 384-well plates with an Analytik-Jena Cybio Well Vario liquid handler. The final concentration of 7.8 μM N protein and 50 ng/μL polyC RNA were added to each plate. Each well contained a 25 μL mixture and 40 μM compound in the primary screen.For the FDA-approved drug screen, 75 mL of N protein at 16 μM was purified from HEK293S GNTI- cells. polyC RNA was obtained from Sigma. The FDA-approved drug library (TargetMol) has 1,200 compounds of well-characterized biological activity. A total of 10 mM compounds were stored in 100% dimethyl sulfoxide (DMSO) in 384-well plates. For screening plates, 20 μL imaging buffer  were taken at 40× with ImageXpress Micro High Content Imaging System . Images were analyzed with Metamorph Imaging software calculating condensate count and area. The volume of the condensates was calculated as described above. Data were then uploaded to CCD Vault for normalization to DMSO vehicle control wells. Wells that exhibit 3 SDs from the untreated sample and as well as others that produced qualitative morphological changes in N condensates were selected for dose–response screening. The same N protein and RNA were tested against candidate drugs using a 10-point serial dilution starting at 40 μM using the same procedure. Dose–response curves were generated by fitting to the equation2. For screening selected drugs against infected cells, 2,500 Vero-E6 (12 μL/well) or 10,000 Calu-3 (12 μL/well) were seeded in 384-well white optical bottom tissue culture plates (Nunc) with the Multidrop Combi liquid handling instrument (Thermo Fisher Scientific). Cells were allowed to recover for 24 hours for Vero-E6 and 48 hours for Calu-3 at 37°C and 5% CO2. Dose responses were generated by diluting the compounds using a Cybio Well Vario liquid handler , leading to a final concentration of DMSO at 0.4% in the assay plate (v/v). Cells were incubated at 37°C and 5% CO2 for 1 hour before infection. The viral inoculum was prepared such that the final multiplicity of infection (MOI) was 0.05 upon addition of 6 μL/well viral inoculum. After complete CPE was observed in DMSO-treated, infected wells (72 hours postinfection (hpi) for Vero-E6 and 96 hpi for Calu-3), the plates were developed with the CellTiter-Glo 2.0 reagent  according to the manufacturer’s instructions. For Vero-E6, the reagent was diluted 1:1 (v/v) in PBS. Luminescence of developed plates was read on a Spectramax L (Molecular Devices). Each plate contained 24 wells uninfected/DMSO treated cells (100% CPE inhibition) and 24 wells infected/DMSO treated cells (0% CPE inhibition). Average values from those wells were used to normalize data and determine % CPE inhibition for each compound well. To determine the cytotoxicity of the compounds, the same protocol was used but with 6-μL growth media added instead of viral inoculum. The data were plotted and analyzed in Origin and fit to the dose–response function above.Vero-E6  and Calu-3 cells (ATCC HTB-55) were cultured in high glucose DMEM (Gibco) supplemented with 10% FBS (R&D Systems), 1X GlutaMAX (Gibco), and 1X PenStrep (Gibco) at 37°C and 5% CO50 assay in Vero-E6 cells. At 24 hours post infection, 100 μL of supernatant from drug-treated infected cells was removed from each well and used to prepare a 10-fold dilution series in Vero growth medium. Moreover, 50 μL of the dilution series was added to Vero cells in 96-well plates, prepared as above, in 100 μL medium. Cells were observed for CPE for 3 days. TCID50/mL results were calculated using the Spearman and Kärber method [Vero-E6 cells were plated at 10,000 cells per well in Vero growth medium as above in 96-well plates and allowed to recover for 24 hours. Drug treatments were prepared in the same medium at 1.33× of final concentration and 0.53% v/v DMSO. Growth medium was removed from cells and replaced with 150-μL medium with drug treatment and incubated for 1 hour. Virus in 50-μL medium was added to each well to produce a final MOI of 0.05, final drug concentrations as indicated, and 0.4% v/v DMSO per well. Vehicle-only treatment was used as a positive control for productive viral infection and CPE, and remdesivir at 50 μM was used as a positive control for viral restriction by drug treatment. Each condition was plated in triplicate. Virus titer following drug treatment was determined by TCIDr method .2. Prior to imaging, cells were transferred to glass-bottomed plates  at approximately 25% confluence and allowed to recover for 24 hours. Media was exchanged into phenol-negative DMEM media supplemented with 10% FBS, and cells were transfected with N-GFP, NΔR2-GFP, or GFP only constructs. For each well, 400 ng of DNA was added to 20 μL DMEM media. A total of 1.2 μL FuGENE HD transfection reagent (Promega) was added, and the mixture was incubated at room temperature for 15 minutes before being added to the cell culture. Cells were allowed to express the constructs for 4 days. One hour prior to imaging, DRAQ5 stain at 1:1,000 was added to the media.HEK293T (RRID: CVCL_0063) cells were cultured in phenol-negative DMEM media supplemented with 10% FBS and 1% PS at 37°C with 5% COIn vivo imaging and FRAP measurements were performed with a Zeiss 880 Confocal Laser Scanning Microscope equipped with a 63×, 1.4 NA oil immersion objective. Samples were prepared as described above. All in vivo FRAP experiments used the 488 nm laser at 100% for bleaching conditions. Cells expressing N-GFP, ΔR2-GFP, or GFP only were bleached with 30 iterations, and images were collected continuously at 6.7 Hz for 30 seconds. All data were acquired using Zeiss Zen 2.3 SP1 FP3. Data were converted to the normalized intensity and fit to an exponential decay function in Origin.2. Prior to imaging, cells were transferred to glass-bottomed plates  at approximately 25% confluence. Cells were transfected with a construct expressing N-MS2 RNA  as described above. Cells were induced with doxycycline at a final concentration of 1,000 ng/mL and allowed to express for 14 hours. FISH was performed following the Stellaris RNA FISH protocol for adherent cells. Cells were fixed with 3.7% formaldehyde, permeabilized with 70% ethanol, and incubated in the dark at 37°C overnight with hybridization buffer  supplemented with 10% deionized formamide and either 125 nM Cy3-(d)T20 oligonucleotides  or 1 μM Cy3-MS2 probe , sequence AGGCAATTAGGTACCTTAGG) [U2OS cells stably expressing SARS-CoV-2 N protein with a carboxyl-terminal Clover tag were a gift from the Cleveland lab at the University of California San Diego (UCSD). Cells were cultured in phenol-negative DMEM media supplemented with 10% FBS and 1% PS at 37°C with 5% COCCTTAGG) . Cells wS1 Fig(A) The coomassie-stained denaturing gel of the N protein purified from affinity chromatography. (B) UV absorbance of the N protein purified from affinity chromatography shows no evidence for the presence of contaminating nucleic acids. (C) UV absorbance of protein standards eluting from a gel filtration column. (D) UV absorbance of the N protein eluting from a gel filtration column. Arrows mark the void volume and expected elution volume for an N monomer. (E) The coomassie-stained denaturing gel of the eluents from the gel filtration column. The yellow arrowhead shows the expected molecular weight of full-length N protein. (F) EMSA using no RNA, 10 nM 0–5 kb viral RNA, and 50 ng/μL polyC RNA and decreasing concentration of N protein. The protein was labeled with LD655. RNA was labeled with Cy3. Arrowheads indicate the minimum protein concentration for each condition with a noticeable signal in the protein gel. EMSA, electrophoresis mobility shift assay; N, nucleocapsid; WT, wild-type.(TIF)Click here for additional data file.S2 Fig(A) An agarose gel picture of 0–5 kb viral RNA and polyC RNA substrates. The gel was stained with GelRed (left), and the RNA substrates were labeled with Cy3 (right). The ladder corresponds to the length of double-stranded DNA. Estimated lengths of 0–5 kb viral RNA and polyC RNA are 5 kb and 2 kb, respectively. (B) Representative pictures show that 18 nM 0–5 kb viral RNA and 50 ng/μL polyC RNA do not form condensates in the absence of N protein. The assay was performed in 150 mM NaCl. (C) Two-color imaging shows colocalization of LD655-labeled N protein and Cy3-labeled polyC RNA in condensates. N, nucleocapsid.(TIF)Click here for additional data file.S3 Fig(A) Control experiments show changes in the fluorescent signal of N and polyC without photobleaching. (B) The changes in the integrated fluorescent intensities of regions highlighted with yellow and red rectangles in (A). (C) The maximum fractional recovery of N and polyC in condensates after photobleaching . The center and edges of the box represent the median with the first and third quartiles. The p-value was calculated from a 2-tailed t test. Data underlying this figure can be found in (TIF)Click here for additional data file.S4 Fig(A) Structure prediction of each section of SARS-CoV-2 genomic RNA. (B) The formation of asymmetric N condensates under different viral RNA concentrations. The N protein concentration was set to 18.5 μM. (C) Structure prediction of viral RNA (left) and the formation of asymmetric N condensates under different RNA concentrations (right). The N RNA is the 1.3 kb long genomic RNA fragment that encodes the SARS-CoV-2 N protein. The 5′ UTR RNA is the first 1,000 bases of the SARS-CoV-2 genome. The N protein concentration was set to 18.5 μM. (D) The distribution of aspect ratios of individual condensates formed with different RNA substrates. The N protein concentration was set to 18.5 μM, and RNA concentration was set to 50 ng/μL for RNA homopolymers and 18 nM for 0–5 kb viral RNA. The center and edges of the box represent the median with the first and third quartiles. p-Values are calculated from 2-tailed t tests. Data underlying this figure can be found in (TIF)Click here for additional data file.S5 Fig(A) Condensates formed by the N protein with in vitro transcribed N RNA or the 5′ UTR of the viral RNA are not sensitive to an increase of temperature to 37°C. (B) Condensates formed by the N protein with 5′ UTR of viral RNA do not change shape over 24 hours. (C) Condensates formed by 11.5 μM N protein and 36 nM 5′ UTR RNA are dissolved in the presence of 260 mM NaCl. (D) Condensates formed by 18.5 μM N protein and 18 nM 0–5 kb viral RNA do not fuse after contact (yellow arrow). N, nucleocapsid; UTR, untranslated region.(TIF)Click here for additional data file.S6 Fig(A) Control experiments show snapshots of LD655-labeled N and Cy3-labeled 0–5 kb viral RNA without photobleaching. (B) The changes in the integrated fluorescent intensities of the regions that are highlighted with yellow and red rectangles in (A). Data underlying this figure can be found in (TIF)Click here for additional data file.S7 Fig(A) In an initial qualitative experiment, pairwise interactions were detected by CLMS at 300 mM salt. Blue dots depict the positions of lysine residues. Lines depict a unique cross-link detected. The regions of N protein interactions flank the CTD. (B) Volcano plot of the quantitative CLMS data comparing the condensate and no condensate condition. Opaque data points have a p-value below 0.05, and transparent data points have a p-value greater than 0.05. Green represents unique cross-links that are enriched in the condensate condition. The yellow markers represent the K169-K65 and K169 (phosS176)-K65 cross-links. (C) The structure of the CTD of the SARS-CoV-2 N protein was plotted with BioRender (PDB 6WJI [(D) MS identified that the RNA binding domain of the stress granule protein G3BP1 interacts with the R2 region of N. Data underlying this figure can be found in PDB 6WJI ). Becaus(TIF)Click here for additional data file.S8 Fig(A) Denaturing gel pictures of purified WT and deletion mutants of N protein in the presence and absence of kinase and phosphatase treatment (see (B) UV absorbance of the ΔR2 mutant eluting from a gel filtration column. UV absorbance of WT N under the same experimental conditions is shown in a dashed red curve for comparison. (C) EMSA gels using no RNA, 10 nM 0–5 kb viral RNA, or 50 ng/μL polyC RNA and decreasing concentration of the ΔR2 mutant. The protein was labeled with LD655. RNA was labeled with Cy3. Arrows indicate the minimum protein concentration for each condition with a noticeable signal in the protein gel. EMSA, electrophoresis mobility shift assay; MS, mass spectrometry; N, nucleocapsid; WT, wild-type.ment see . The gel(TIF)Click here for additional data file.S9 Fig(A) Example pictures show that the N deletion mutants, except ΔR2, form spherical condensates with polyC RNA under different RNA concentrations. The N protein concentration was set to 18.5 μM. (B) The total volume of N-RNA condensates settled per micron squared area on the coverslip  exhibits a reentrant behavior under an increasing RNA concentration. (C) Example pictures show that the N deletion mutants, except ΔR2, form spherical condensates with polyC RNA under different protein concentrations. The polyC RNA concentration was set to 50 ng/μL. (D) The total volume of N-RNA condensates settled per micron squared area on the coverslip  under an increasing protein concentration. (E) Phase separation of truncated N protein constructs with 0.74 μM in vitro transcribed N RNA or 18 nM 0–5 kb viral RNA. The protein concentration was set to 18.5 μM. Data underlying this figure can be found in (TIF)Click here for additional data file.S10 Fig(A) Images of condensates formed by untreated and dephosphorylated ΔSR in the presence of 50 ng/μL polyC RNA. (B) The total volume of the condensates settled per micron squared area on the coverslip as a function of ΔSR concentration . (C) Images of condensates formed by untreated and dephosphorylated ΔR1 in the presence of 50 ng/μL polyC RNA. (D) The total volume of the condensates settled per micron squared area on the coverslip as a function of ΔR1 concentration . (E) Full-length N protein forms asymmetric condensates with 0.74 μM in vitro transcribed N RNA before and after phosphorylation and dephosphorylation. The protein concentration was set to 35 μM. Data underlying this figure can be found in (TIF)Click here for additional data file.S11 Fig(A) Example pictures show phase separation of 7.8 μM N protein and 50 ng/μL polyC RNA at different drug concentrations. (B) The percent change on the number (blue) and total volume (black) of N-polyC condensates settled per micron squared area on the coverslip under different drug concentrations . (C) Example pictures show phase separation of 57.6 μM LD655-labeled N protein and 1.5 μM Cy3-labeled in vitro transcribed N RNA in the presence of different drug treatments. The concentration of drugs was set to 40 μM. (D) Condensates formed in the presence of 57.6 μM N protein and 1.5 μM N RNA form thread-like filaments at high nilotinib concentrations. Data underlying this figure can be found in (TIF)Click here for additional data file.S12 Fig(A) Percent CPE inhibition  and cell viability (blue) of SARS-CoV-2–infected Calu-3 cells treated with serial dilutions of drugs. Solid curves represent a fit to a dose–response equation to determine EC50. (B) Viral titer in uninfected and SARS-CoV-2–infected Vero-E6 cells as measured by a TCID50 assay. Infected cells were treated with DMSO (negative control) and 50 μM remdesivir (positive control). Data underlying this figure can be found in (TIF)Click here for additional data file.S13 Fig(A) Representative FRAP imaging of HEK293T cells with high expression of N-GFP or ΔR2-GFP. Circles show the photobleached and control (not bleached) regions. (B) Fluorescence recovery signals of the N protein in the bleached versus the control regions. The solid curve represents a single exponential fit to reveal the recovery lifetime . (C) The distribution of fluorescence recovery lifetimes of cells expressing N-GFP or ΔR2-GFP and exhibiting either puncta or high expression . The center and edges of the box represent the median with the first and third quartiles. The p-values were calculated from a 2-tailed t test. (D) The maximum fractional recovery after photobleaching of cells expressing N-GFP or ΔR2-GFP and exhibiting either puncta or high expression . The center and edges of the box represent the median with the first and third quartiles. The p-values were calculated from a 2-tailed t test. (E) U2OS cells stably expressing N-Clover form condensates in the cytoplasm. Cy3-d(T)20 FISH probe targeting the polyA tails of RNA transcripts is uniformly distributed in cells exhibiting N condensates with (left) or without (right) expression of N-MS2 . Inset scale bar is 2 μm. Data underlying this figure can be found in (TIF)Click here for additional data file.S14 Fig(A) Representative FRAP imaging of N protein only, or in the presence of polyC or 0–5 kb viral RNA. The concentrations of N, polyC, and 0–5 kb viral RNA were kept at 24 μM, 50 ng/μL, and 18 nM, respectively. Rectangles highlight the photobleached area. (B) Fluorescence recovery signals of the N protein and RNA in the bleached versus the control regions. Solid curves represent a single exponential fit to reveal the recovery lifetime . (C) The distribution of fluorescence recovery lifetimes of the condensates . The center and edges of the box represent the median with the first and third quartiles. The p-values were calculated from a 2-tailed t test. (D) The maximum fractional recovery after photobleaching . The center and edges of the box represent the median with the first and third quartiles. The p-values were calculated from a 2-tailed t test. Data underlying this figure can be found in (TIF)Click here for additional data file.S15 Fig(A) (Left) Images of the LD655-labeled N protein in the presence of 10% PEG and 150 mM NaCl. The assays were performed in the absence of RNA. (Right) The total volume of N condensates settled per micron squared area on the coverslip . A linear fit (solid line) reveals csat (± SE). (B) Images of the condensates formed in the presence of LD655-labeled WT N protein before or after phosphatase and kinase treatments in the presence of 10% PEG and 150 mM NaCl. (C) Images of the LD655-labeled truncated N protein mutants in the presence of 10% PEG and 150 mM NaCl. The protein concentration was set at 3 μM. Assays were performed in the absence of RNA. Data underlying this figure can be found in (TIF)Click here for additional data file.S1 TableThe cross-link (xlink) position indicates the amino acid number of the N protein sequence. The K169-K65 peptide is phosphorylated at S176. N, nucleocapsid.(DOCX)Click here for additional data file.S2 Table(A) The coverage map and phosphorylation sites for the N protein detected in proteomics experiments. Text in red indicates peptide regions that were not detected; green highlight indicates an unambiguous phosphorylation site; and yellow highlight indicates an ambiguous phosphorylation site. (B) Each site identified by our study is characterized as being unambiguously or ambiguously localized based on manual inspection of the product ion series. See (DOCX)Click here for additional data file.S3 Table(A) The proteins were ranked by SAF. These protein sequences were included in the CLMS search. Asterisks indicate exogenous proteins. (B) Cross-links between N and the G3BP1 and G3BP2 stress granule proteins identified in the qualitative CLMS experiment ranked by an SVM score. Values are frequency of detection (2 conditions with 2 replicates each). Xlink position indicates the amino acid number of the given protein sequence. SVM indicates the confidence that the cross-link is correctly identified. CLMS, cross-linking mass spectrometry; MS, mass spectrometry; N, nucleocapsid; SAF, spectral abundance factor; SVM, support vector machine.(DOCX)Click here for additional data file.S4 TableThe parameters of fitting to a dose–response equation in the presence and absence of polyC RNA in response to increasing concentrations of salt or nelfinavir mesylate. N, nucleocapsid.(DOCX)Click here for additional data file.S1 DataFigs (XLSX)Click here for additional data file.S1 Raw Images(PDF)Click here for additional data file.


CACNA1C gene, which encodes a voltage-gated calcium channel, as an example. We highlight three areas that pose potential barriers to effective information transfer and offer suggestions as to how these may be addressed: firstly, a lack of clarity about the strength of the evidence for individual transcripts in current annotations; secondly, limitations to the transfer of information between nucleotide and protein databases; thirdly, challenges relating to the nomenclature used for transcriptional events and RNA modifications, both for genomic researchers and the wider scientific community.The advent of cost-effective high-throughput nucleotide sequencing means that information about the transcriptome is accruing at an exponential rate, rapidly refining our understanding of the diversity of gene products. It is important that these findings are readily accessible to the wider scientific community to maximise their impact. However, there are multiple barriers to their efficient dissemination and their translation into functional insights. Here, we outline how the status quo can result in information becoming siloed and/or ambiguous, using the Many projects have produced, or are aiming to produce, a reference transcriptome to synthesise the wealth of (highly redundant) sequencing information, although the resulting annotations vary due to differences in algorithms applied and the extent to which annotations are manually curated . HoweverCACNA1C transcripts from just one start exon identified 38 novel exons and 241 novel transcript isoforms, as well as abundant splice site variations [CACNA1C transcripts sequenced in human brain are predicted to encode functional voltage-gated calcium channels  [CACNA1C isoforms, there was strong support for only 10 of the 31 previously annotated in GENCODE (v27) and only one of these was amongst the ten most abundant isoforms. It is likely that some of the annotated isoforms that were not found in adult brain are expressed in other tissues and/or at other stages of development and ageing, but some may be false positives.Novel long-read RNA sequencing technologies, such as Oxford Nanopore Technologies and PacBio, allow full length transcript isoforms to be sequenced, thereby providing the potential to eliminate false positive isoforms arising from reconstruction errors. In addition, sequencing at depth and/or combining this technology with enrichment approaches also provides a means to identify novel, full-length transcripts. For example, targeted long-read sequencing of riations . As the unction) . This isThus, current annotations, even those generated using RNA-seq data, remain far from complete. The impact of inaccuracies in reference annotations is far-reaching since they are frequently used for mapping RNA-Seq and, in some instances, proteomic data. Against this backdrop, long-read sequencing has significant potential to improve annotations, particularly in combination with targeted approaches. As annotations begin to incorporate long-read sequencing data it would be extremely valuable if individual transcripts and splicing events could be flagged as being either predicted, based on reconstruction from short-read data, or validated, by long read sequencing, mass-spectrometry peptide identification, or other approaches, to help researchers to determine the strength of the underlying evidence for specific isoforms and to select a reference that suits their needs. For example, in ‘omics’ level proteomics, peptide identification is generally performed by matching peptide fragment products to a reference, meaning this process is a fine balance between the complexity of the reference and the number of multiple tests performed. There are therefore significant advantages to having a choice between a streamlined, high confidence transcript reference, and a more experimental comprehensive reference, depending on experimental goals.CACNA1C, splicing events across the gene have been shown to influence multiple aspects of channel function [in vivo but is also of medical relevance, given that splicing modulates the clinical presentation of Timothy Syndrome, a severe developmental condition caused by CACNA1C mutations [A primary reason for generating high-quality transcriptomic annotations is to inform functional studies of gene products. For example, in the case of function , resultifunction . Howeverutations  and becautations .CACNA1C transcripts annotated in Ensembl lack corresponding protein entries in Uniprot  that is not encoded by any of the current full-length Ensembl isoforms  changes in peptide sequence [CACNA1C [New exons and isoforms will continue to be discovered as sequencing breadth and depth increase. Furthermore, future annotations will also need to capture details of the RNA (and protein) modifications that are being identified by novel technological approaches, such as direct RNA sequencing . Incorpootations , 10. Thu8 and 8A , 17, whi8 and 8A ; as a resequence . Despite[CACNA1C , and so Using genomic co-ordinates to disambiguate RNA and protein isoforms, RNA modifications, exons and genomic loci is one possible solution. However, current genomic co-ordinates will likely have to change as long-read DNA sequencing increasingly uncovers the ‘dark’ areas of the genome, such as tandem repeat elements . AlongsiOur experiences highlight the challenges in ensuring that improvements in transcriptomic annotations are translated into novel biological insights. Central to this problem is the relative lack of information flow between existing databases. This problem will only be exacerbated by emerging improvements in our understanding of the nuances of the transcriptome. As others have highlighted, in coming years as more individual genomes are sequenced it will be necessary to reappraise our understanding of what we mean by the ‘reference genome’ . We woul