Metastatic lesions compromise the mechanical integrity of vertebrae, increasing the fracture risk. Screw fixation is usually performed to guarantee spinal stability and prevent dramatic fracture events. Accordingly, predicting the overall mechanical response in such conditions is critical to planning and optimizing surgical treatment. This work proposes an image-based finite element computational approach describing the mechanical behavior of a patient-specific instrumented metastatic vertebra by assessing the effect of lesion size, location, type, and shape on the fracture load and fracture patterns under physiological loading conditions. A specific constitutive model for metastasis is integrated to account for the effect of the diseased tissue on the bone material properties. Computational results demonstrate that size, location, and type of metastasis significantly affect the overall vertebral mechanical response and suggest a better way to account for these parameters in estimating the fracture risk. Combining multiple osteolytic lesions to account for the irregular shape of the overall metastatic tissue does not significantly affect the vertebra fracture load. In addition, the combination of loading mode and metastasis type is shown for the first time as a critical modeling parameter in determining fracture risk. The proposed computational approach moves toward defining a clinically integrated tool to improve the management of metastatic vertebrae and quantitatively evaluate fracture risk. The vertebra is one of the most common sites that can be affected by metastasis ,2, and nCosta et al.  developeStadelmann et al.  investigFE-based computational approaches have also been used to evaluate the impact of size and location of simulated lytic metastasis on the vertebra structural response, concluding that the effect of the size of the metastasis is more significant than that caused by the site of the lesion ,12,13,14The image-based FE modeling approaches developed so far have demonstrated the potential of computational modeling in furnishing a better understanding of the impact of metastatic disease on vertebra mechanical behavior. However, in most studies reported in the literature, metastasis was modeled as voids or by considering the same CT-based density–elasticity relationship used for healthy bone. Furthermore, any investigation concerning the presence of screw fixation was advanced in such a context. As such, the lack of specific constitutive modeling of metastasis and, more importantly, the inattention to possible effects that the metastatic lesion may have on the bone surrounding the lesion in the presence of fixation screws represent significant limitations of the modeling studies . DevelopBone cement augmentation procedures such as vertebroplasty or kyphoplasty are often used to treat patients with metastasis-related vertebral compression fractures or to restore vertebral body stability when mechanical integrity is significantly compromised by metastasis. However, it was reported that these procedures are not always effective ,19. In sThe present work aims to evaluate in silico the mechanical behavior of instrumented metastatic vertebra through the development of an image-based FE computational tool. To this aim, we virtually insert the screws in the vertebra using the insertion trajectory that our previous analyses ,26 showeA CT spinal scan of a 49-year-old female patient was used in the present work. The following imaging parameters were set: 120 kVp, 489 mA, 0.8418 × 8418 mm pixel size, and 1 mm slice thickness. The images were acquired without a calibration phantom and were anonymized for their use, fulfilling the ethical protocols at the University Hospital Campus Bio-Medico of Rome.In The vertebral geometry was reconstructed starting from the CT images by segmenting the CT images . Then the CAD model of two screws, whose characteristics are reported in ,26, was  implant ,26. In F implant ,26, for Once the screws–vertebra computational domain was reconstructed, it was imported into the Comsol Multiphysics environment  for mesh generation. In detail, 10-node tetrahedral elements were used for computational discretization. For the vertebra, the maximum and minimum elements sizes of the mesh were set to 2 mm and 1 mm, respectively, resulting in 212,089 tetrahedral elements and 882,505 nodes, according to a preliminary convergence analysis ,26. For R represent the center coordinates and the radius of the j-th metastatic lesion, respectively. The metastasis was simulated within the vertebral domain considering different locations, as will be clarified in In the Cartesian coordinates system, the mathematical description of the j-th metastasis is expressed by the following relation: The present work’s primary novelty incorporates a specific constitutive description of diseased bone tissue accounting for bone–metastasis interaction in the presence of fixation screws. Following a similar approach previously developed ,28, we in is the total number of metastases, Under these assumptions, the stress can be expressed via the second-order Cauchy stress tensor orted in . As a reE and Poisson’s ratio E obtained from the CT images. In detail, Young’s modulus for the vertebra was derived by following a procedure that consists of two steps: (1) correction of Hounsfield Unit :ET=4730·ρρapp1.56EC=−892.5In terms of Poisson’s ratio vertebra . AccordiAssuming an elastic and isotropic behavior of the metastasis, the elasticity tensor e et al. . For theorted in ,38 in whorted in  for the Equation . PoissonTo model the bone–metastasis interaction in terms of degradation of material properties in the bone region close to the metastasis, for the j-th metastasis the Heaviside function Equation  and defiR of the metastatic lesion. This choice was made to induce a local change of Young’s modulus in the bone region close to the metastasis with a smooth transition at the interface between bone and metastasis avoiding sharp constitutive change. As reported in The function out 37%) ,28 for bterature  regardinTwo different loading conditions were simulated in the present work: extension (EXT) and left lateral bending (LLB). To replicate such loading cases, both vertebra and screws were loaded . In detaWe tested two failure criteria to detect the fracture load and the failure patterns of the vertebra: a maximum principal stress criterion and a maximum principal strain criterion.The maximum principal stress criterion (labeled as ed when:σ+>σ¯+(7a)σ+>σ¯+σ−>σ¯−wh follows ,42:(9a)relation : (10)ρasThe maximum principal strain criterion (labeled as ng when:ϵ+>ϵ¯+(1a)ϵ+>ϵ¯+ϵ−>ϵ¯−wiThe terms ectively .For both failure criteria tested, the local failure of the vertebra is assumed to occur when the failure criterion is verified for at least one element. In such occurrence, Young’s modulus of failed elements is set equal to https://doi.org/10.5281/zenodo.6534415, accessed on 10 May 2022). In detail, a quasi-static force-based incremental approach was adopted to model the progressive damage process. By denoting with k-th step, the force at the step k+1 , loading condition , and type of metastasis , numerical analyses were performed investigating different positions and extensions of a metastatic lesion. In detail, three different locations of the metastasis were considered in agreement with ,45,46,47Moreover, for each position, the influence of the extension of the metastasis was analyzed. In detail, lesions with a radius of 5 mm . The overall computational time was 7 days on an HP Z640 workstation with E5-2630 v3 (8 × 2.40 GHz) and 32 GB of RAM.A synthetic view of the fracture load values for the complete set of FE analyses is reported in In the following, the influence of the size, position, shape, and type of metastasis on the mechanical response of the metastatic vertebra is presented and critically discussed.In In bending, for each type of metastasis and position, an increase in lesion radius reduces the fracture load a,c, exceIn bending, for both radii values of osteoblastic metastasis, the fracture load decreases, moving the metastasis from P1 to the P3 position, with the highest fracture load value in the P1 position (closer to the screw) and the lowest value in the P2 position a. In extIn bending for the osteoblastic lesion a, an incFinally, comparing the presence of multiple osteolytic lesions, we obtain, as expected, a reduced maximum load see . In partIn most of the analyzed cases, the vertebra with osteoblastic metastasis demonstrated higher fracture loads compared to vertebrae with osteolytic metastasis .In bending, considering the load-displacement curves shown in In extension, the load-displacement curves reported in In the following, significant examples of the progression of fracture patterns up to the complete rupture of the vertebra are shown.The present study aimed to investigate the mechanical behavior of instrumented metastatic vertebra by developing an image-based FE computational approach that accounts for the bone–metastasis interaction in terms of local change of material properties within the metastatic lesion. The study was designed through an extended FE parametric analysis to assess the influence of type, size, location, and shape of metastasis on the mechanical response of the vertebra, comparing fracture load and fracture patterns.Numerical results demonstrate that the size of metastasis affects the prediction of fracture load of the vertebra with a different impact based on the type of metastasis. The increasing size of osteolytic lesions reduces the fracture load in almost all investigated cases. This result is in agreement with  in whichThe numerical results obtained in the present study demonstrated that the location of the metastasis could influence the overall mechanical response of a diseased vertebra, in agreement with previous studies emphasizing a non-negligible role of the metastasis location in predicting the vertebral strength ,48. HoweIn this contribution, a metastasis located closer to the screw leads to a higher fracture load than a metastasis situated far from the screw in the majority of the cases. This result can be justified by the higher stiffness of the screw that induces stress concentration in the surrounding tissue. In addition, the loading mode is crucial in determining the fracture pattern in combination with the position effect. In some extension-loading conditions, it was found that the fracture load is higher far from the screw. This result highlights the importance of patient-specific models necessary for a definite and personalized clinical assessment. The type of metastasis has an impact on fracture load prediction, with higher fracture loads predicted for osteoblastic lesions . This reAn additional result of our computational approach comes from the visual inspection of the fracture pattern distribution within the vertebra body. Such a feature is of crucial importance from a clinical point of view, indicating and quantifying the location and distribution of the damaged volumes in view of an optimized surgery procedure.The adopted constitutive modeling strategy moves toward defining a refined representation of metastatic lesions. In some studies, the metastatic tissue is modeled as void. However, such an approach neglects specific material properties of diseased tissues as well as the biomechanical interaction between the lesion and the surrounding environment. On the other hand, another widely adopted approach consists of modeling metastasis as healthy bone. Again, the tumor environment features altered constitutive parameters and requires advanced modeling strategies . TherefoWe point out limitations and future perspectives of our study. Starting from the constitutive description, bone and metastasis were considered isotropic linear elastic materials. As already mentioned, the tumor mechanical microenvironment is characterized by a porous solid matrix filled with interstitial fluids. Accordingly, a poroelastic constitutive description may be considered as a generalized modeling approach to improve our understanding of the overall mechanical behavior of metastatic vertebrae ,28. FurtConsidering modeling parameters, the shape of the function  methods ,33,34, aFrom a numerical and statistical viewpoint, the parametric analysis was conducted on a single patient. Thus, the study should be extended to a broader clinical cohort to corroborate and generalize our results. Moreover, the presence of mixed metastasis  should be investigated as in . FinallyIt is worth noting that the use of clinical datasets is intrinsically affected by the lack of experimental data to validate numerical findings. Considering the primary purpose of the present study, i.e., to provide a rigorous and reliable computational method to predict in silico the complex fracture patterns occurring in metastatic vertebrae, we hope that extensive experimental validation is made available in the near future to corroborate and augment our results.We presented a new image-based computational FE approach accounting for the effect of metastasis on bone material properties. A numerical tool was developed and used to evaluate the impact of size, location, and type of metastasis on the mechanical response of an instrumented human vertebra. Our analysis highlighted that these parameters significantly affect fracture load predictions and patterns. Moreover, improved modeling of the bone–metastasis interaction plays a crucial role in assessing the mechanical behavior of metastatic vertebra. Our study moves toward the definition of robust and reliable computational tools expected to be used by clinicians to improve the management of metastatic vertebrae. In particular, integrating numerical tools to predict complex fracture mechanisms would certainly help an optimal surgical treatment plan. The final objective is to minimize the risk of fracture and, thus, implant failure to improve the management of patients with metastatic disease.


The associated TPR-CHAT adopted a distinct conformation upon self versus non-self RNA target binding, with nucleotides at positions −1 and −2 of the CRISPR-derived RNA (crRNA) serving as a sensor. Only binding of the non-self RNA target activated the TPR-CHAT protease, leading to cleavage of Csx30 protein. Furthermore, TPR-CHAT structurally resembled eukaryotic separase, but with a distinct mechanism for protease regulation. Our findings should facilitate the development of gRAMP-based RNA manipulation tools, and advance our understanding of the virus-host discrimination process governed by a nuclease-protease Craspase during type III-E CRISPR-Cas immunity.The RNA-targeting type III-E CRISPR-gRAMP effector interacts with a caspase-like protease TPR-CHAT to form the CRISPR-guided caspase complex (Craspase), but their functional mechanism is unknown. Here, we report cryo-EM structures of the type III-E gRAMP The authors report several high-resolution functional snapshots of type III-E nuclease-protease Craspase complexes, revealing the mechanisms underlying target RNA cleavage and non-self RNA activated protease activities; and highlighting the potentials for the development of RNA-guided nuclease-protease Craspase-based tools for biotechnological applications. The immunity is acquired by integrating the invading nucleic acids between repeat sequences of the host CRISPR locus. The CRISPR loci are then transcribed into precursor RNAs (pre-crRNAs) that are processed into mature CRISPR-derived RNAs (crRNAs), which assemble with single- and multi-subunit Cas proteins. The resulting crRNA-effector complexes detect and degrade the invading nucleic acids.Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) systems provide prokaryotes with adaptive immunity against invading viruses and plasmids3. Class 1 systems  comprise multi-subunit effector complexes, whereas class 2 systems  are composed of single-subunit protein effectors. Of all known CRISPR-Cas systems, RNA-targeting effector complexes have been identified in type III, V, and VI systems6, of which the single-subunit effector type VI Cas13 is widely used for RNA detection, editing, and knockdown7. However, upon recognition of the RNA targets, Cas13 exhibits nonspecific RNA cleavage activity resulting in degradation of viral and host RNA9. The nonspecific, collateral RNA cleavage activity of Cas13 is toxic to multiple mammalian cell types11.Depending on their Cas gene composition, CRISPR-Cas systems are classified into two major classes (1 and 2) and six types (I−VI)13, representing a promising new tool for manipulating RNA. Kato et al. provided the first glimpse into the architecture of a type III-E CRISPR effector complex, Desulfonema ishimotonii Cas7-11, bound to a target RNA, elucidating the mechanism for target RNA cleavage14. However, given that the type III-E effector complex equally cleaves the invasive non-self and the host self RNA targets derived from the host CRISPR array12, it is unknown if the type III-E effector complex discriminates self and non-self RNA targets during antiviral defense.A recently characterized type III-E CRISPR-Cas subtype contains a single-protein effector that exhibits specific target RNA cleavage activity with no collateral activity or cell toxicity3. In previously reported canonical type III-A/B systems, the mature crRNA consists of a single spacer that is flanked by an 8-nt 5′-repeat tag derived from the repeat sequence of the host CRISPR array. The non-complementarity between 3′-flanking sequences of the target RNA and the 5′-repeat tag of crRNA designates an invasive non-self RNA target and triggers the immune response, whereas complementarity between these two sequence elements designates the RNA target derived from the host CRISPR array and prevents self-targeting15. Only binding of the invasive non-self RNA target, but not the host self RNA, allosterically activates the ssDNase and cyclic oligoadenylate (cOA) synthetase activities of the type III signature protein Cas10 to degrade the invading nucleic acids20. Meanwhile, cleavage of the invasive RNA target by the Csm3/Cmr4 subunit switches off Cas10 enzymic activities, thereby preventing potential damage to the host due to persistent enzyme activities21.Type III CRISPR-Cas systems are divided into six subtypes (type III-A to F), of which type III-A, -D, -E, and -F contain Csm proteins, whereas type III-B and -C consist of Cmr proteins22  to form the CRISPR-guided caspase complex (Craspase) in type III-E CRISPR-Cas systems12, suggesting a functional relationship between CRISPR-Cas systems and caspase-like proteases during type III-E CRISPR-Cas antiviral immunity. The TPR-CHAT protease is implicated in regulating bacteria death by site-specific cleavage and subsequent activation of a bacterial gasdermin, which executes cell death for antiphage defense23, suggesting an antiviral role of the TPR-CHAT protease in type III-E CRISPR-Cas immunity. However, we do not have a mechanistic understanding of the functional relationship between the type III-E CRISPR-Cas effector complex and the caspase-like protease TPR-CHAT, nor for the mechanism of the self versus non-self discrimination in type III-E systems.Lacking the type III signature protein Cas10, the III-E CRISPR loci often contain a gene encoding a caspase-like protease called TPR-CHAT that contains a caspase HetF associated with TPRs (CHAT) domain, which is a caspase family protease typically involved in programmed cell death, fused with a tetratricopeptide repeat (TPR) domain22 Fig. . The TPRcrRNA and gRAMPcrRNA-TPR-CHAT complexes, with or without their self or non-self RNA targets bound and revealed the mechanisms underlying RNA-targeting and virus-host discrimination governed by the non-self RNA-activated TPR-CHAT protease in type III-E CRISPR nuclease-protease Craspase-mediated antiviral immunity.Here, we combined structural biology and biochemistry analyses to generate high-resolution snapshots of the type III-E gRAMPCandidatus “Scalindua brodae” gRAMP complex specifically recognizes and cleaves self and non-self RNA targets12. To investigate whether the gRAMPcrRNA complex can distinguish self from invasive non-self RNA targets, we first co-expressed the gRAMP gene with a single CRISPR array in Escherichia coli cells  to prevent target cleavage , backbone (two Cas7-like Csm3 domains and one Cas11-like Csm2 domain) and tail (the Csm4 domain) fused by four linker domains (L1–L4), but lacking the type III signature protein Cas1027  of 0.463 Å  is responsible for pre-crRNA processing to generate the mature crRNA with a 15-nt 5′-repeat tag14. However, we observed an 18-nt 5′-repeat tag in our type III-E gRAMP complexes, numbered −18 to −1 according to the convention  and between nucleotides 9′ and 10′ (site 2) with a 6-nt interval in a metal-dependent manner12 Fig. . The pot12 Fig. . Consist12 Fig. . Notably12 Fig. , indicatcrRNA-target RNA ternary complex and the gRAMPcrRNA binary, whose structure we determined at 2.7 Å  and 5′-hydroxyl termini33. Thus, we speculate a similar catalytic pathway for target RNA cleavage by type III-E gRAMP complexes. We observed that the 2′-hydroxyl group of A4′ and A10′ are close to the basic residues K371 and K320  via electrostatic contacts, making the catalytic residues inaccessible to incoming substrates. In addition, the distance between H585 and C627 in bacterial TPR-CHAT was ~7 Å  Fig. , suggest7 Å Fig. , inset, 7 Å Fig. , inset, crRNA-TPR-CHAT complex. Then, we determined a 2.9 Å cryo-EM structure of an invasive non-self RNA target-bound gRAMPcrRNA-TPR-CHAT quaternary complex  to ~3 Å (in marine) upon non-self RNA target binding, a distance at which both of the catalytic residues were positioned for attack on the peptide bond of the substrate 35 35 Fig. , suggestcrRNA-TPR-CHAT bound to a self-RNA target with an anti-tag sequence complementary to the 5′-repeat tag . This complex binds to the invasive non-self RNA target, which activates the ssDNase and cOA synthetase of the signature protein Cas1020 Fig. . The sec13, representing a promising new RNA manipulation tool. While the type III-E CRISPR-Cas system lacks the signature Cas10 protein crucial for canonical type III CRISPR immunity20, type III-E CRISPR loci encode a caspase-like protease, TPR-CHAT, which directly interacts with the type III-E effector complex gRAMP to form Craspase12, and TPR-CHAT protease resides in a similar position as Cas10 in the type III-A effector complex27  peptide motif35. However, the critical separase residue D2151 responsible for the conserved R215 recognition at the P1 position is replaced by K670 in bacterial TPR-CHAT, and the residues around E212 at P4 position is also different between eukaryotic separase and bacterial TPR-CHAT . The csx30 gene was cloned into the pCDFDuet-1  vector with an N-terminal hexahistidine tag and a C-terminal Strep II tag. The csx31 gene was cloned into a modified pET28a vector with a SUMO tag following a ubiquitin-like protease (ULP1) cleavable site and an MBP tag to increase the soluble protein yield, fused with an N-terminal hexahistidine tag. For the expression of Csx30 -RpoE complex, the csx30 gene with an N-terminal hexahistidine tag and the rpoE gene with a C-terminal Strep II tag were subcloned into the two multiple cloning sites of pCDFDuet-1 vector, respectively. The gRAMP gene and the synthetic CRISPR gene were cloned into the pRSFDuet-1 vector , in which an N- terminal hexahistidine tag was fused with gRAMP. The TPR-CHAT gene was subcloned into the pETDuet-1 vector  with a C-terminal Strep II tag. Individual vector or two vectors were transformed into Escherichia coli BL21-CodonPlus (DE3). Streptomycin-resistant colonies for expression of Csx30 and Csx30-RpoE complex, kanamycin-resistant colonies for expression of Csx31, double-resistant colonies for expression of gRAMPcrRNA-TPR-CHAT complex or kanamycin-resistant colonies for expression of gRAMPcrRNA complex were picked and grown to OD600 of ~0.8 in LB medium at 37 °C. The expression was induced by adding isopropyl-β-D-1-thiogalactopyranoside to 0.5 mM and shifted to at 16 °C for 20 h. Cells were harvested by centrifugation and resuspended in lysis buffer . The harvested cells were then lysed by the EmulsiFlex-C3 homogenizer (Avestin) and centrifuged at 20,000 rpm for 30 min.The full-length crRNA complex or Csx31, the supernatant was applied to 5 mL HisTrap Fast flow column (Cytiva). The protein was eluted with lysis buffer supplemented with 500 mM imidazole after washing the column with 10 column volumes of lysis buffer and 2 column volumes of lysis buffer supplemented with 40 mM imidazole.For the purification of gRAMPcrRNA-TPR-CHAT complex, Csx30 or Csx30-RpoE complex, the elution from HisTrap Fast flow column was subjected to further purification by loading into 5 mL StrepTrap HP column (Cytiva). Proteins were eluted in buffer A  supplemented with 5 mM desthiobiotin and then loaded into 5 mL HiTrap Q Fast Flow column (Cytiva). Proteins were eluted in a linear gradient from 100 mM to 1 M NaCl in 20 column volumes, and then concentrated using 100 kDa molecular mass cut-off concentrators (Amicon) before final purification on a Superdex 200 increase 10/300 GL column (Cytiva) pre-equilibrated in buffer B . Pooled fractions were concentrated, flash-frozen in liquid nitrogen, and stored at −80 °C for further use.For the purification of the gRAMPAll mutants were generated by site-directed mutagenesis and purified by the same method as above.crRNA-target RNA or gRAMPcrRNA-TPR-CHAT-target RNA ternary complex, the purified gRAMPcrRNA binary or gRAMPcrRNA-TPR-CHAT ternary complex were mixed with either self RNA (5′ CUCUAGUAACAGCCGUGGAGUCCGGGGCAGAAAAUUGGGUACCGUGACAUUAAGUC 3′) or non-self RNA (5′ CUCUAGUAACAGCCGUGGAGUCCGGGGCAGAAAAUUGGCAUGGCACUGUAAUUCAG 3′) at a molar ration of 1:1.2 and then incubated on ice for 30 min. We have added 5 mM EDTA to chelate divalent cations and thus prevent target cleavage. The mixture was loaded on a Superdex 200 Increase 10/300 GL(Cytiva) column equilibrated with buffer B. Pooled fractions were concentrated, flash-frozen in liquid nitrogen, and stored at −80 °C.To assemble gRAMPcrRNA, gRAMPcrRNA-target RNAself, gRAMPcrRNA-target RNAnon-self, gRAMPcrRNA-TPR-CHAT, gRAMPcrRNA-TPR-CHAT-target RNAself, and gRAMPcrRNA-TPR-CHAT-target RNAnon-self complexes were applied onto glow-discharged UltrAuFoil 300 mesh R1.2/1.3 grids (Quantifoil), respectively. Grids were blotted for 2 s at 100% humidity, 4 °C, and flash frozen into liquid ethane using Vitrobot Mark IV (FEI). Images were collected with SerialEM v3.8.2 on the FEI Titan Krios electron microscope at acceleration voltage of 300 kV with a Gatan K3 Summit detector with a physical pixel size of 1.1 Å at a defocus range from −1.5 μm to −2.5 μm. Each movie comprises 32 subframes with a total dose of 50 e−/Å2.3.5 μL of 2 mg/mL purified gRAMP48 and cryoSPARC v3.149. The motion correction was performed with MotionCor250. Contrast transfer function (CTF) parameters were estimated by Ctffind451. Auto-picked particles using Laplacian-of-Gaussian were extracted and subjected to two rounds of 2D classification and two rounds of 3D classification in cryoSPARC v3.1, using the initial model generated in cryoSPARC v3.1 as a reference. Particles corresponding to the best class with the highest-resolution features were selected and subjected to non-uniform refinement in cryoSPARC v3.1. The final particles were subjected to the CTF refinement and then subjected to non-uniform refinement, generating the final reconstitutions. To further improve the density of the Csm5 insertion domain in the gRAMPcrRNA-target RNAself complex, a soft mask for the insertion domain was generated and applied for the subsequent local refinement in cryoSPARC v3.1. The final map of gRAMPcrRNA-target RNAself complex was obtained by combining the maps from non-uniform refinement and local refinement in Chimera v2.4.252. All resolutions were estimated by applying a soft mask around the protein density and the Fourier shell correlation (FSC) = 0.143 criterion in cryoSPARC v3.1. Local resolution estimates were calculated from two-half data maps in cryoSPARC v3.1. Further details related to data processing and refinement are summarized in Supplementary Table Image processing was performed by RELION 3.153. All models were refined against the cryo-EM maps using phenix.real_space_refine v1.19.254 by applying geometric and secondary structure restraints. All figures were prepared in PyMol v2.4.2 (http://www.pymol.org) and Chimera v1.1552. The statistics for data collection and model refinement are shown in Supplementary Table Atomic models were built de novo, then interactively refined in COOT v0.9.5crRNA complex or its mutants in different concentrations as indicated with 50 nM 5′ 6-FAM labeled RNA in 10 μL reaction buffer composed of 20 mM HEPES, 75 mM NaCl, 5 mM MgCl2, 100 μM CoCl2, pH 7.5 at 37 °C for 60 min. The reactions were quenched by the addition of protease K and 5× stop buffer  followed by incubation for 10 mins at 95 °C. The samples were separated on 15% 8 M urea-PAGE and the FAM fluorescence signal was quantified with Canon 6100 Multi imaging system . The cleavage assays were repeated at least three times, and representative results are shown. For the presentation of full scan blots, please see the Source Data files and In vitro RNA cleavage assays were performed by incubating gRAMPcrRNA-TPR-CHAT complex or its mutants  were added to reactions with 5 μM proposed substrates , followed by the addition of self RNA or non-self RNA target. Reactions were incubated at 37 °C for 60 min, then separated on 4–20% FuturePAGETM protein gel (ACE). Gels were stained with Coomassie G-250, and imaged using ChampGel7000 (Sage).The cleavage reactions were assembled in 10 μL reaction volume with buffer containing 20 mM Tris-HCl, 100 mM NaCl, pH 8.0. 1 μM gRAMPcrRNA-TPR-CHAT in presence of non-self RNA target in buffer containing 20 mM Tris-HCl, 100 mM NaCl, pH 8.0. Reaction was incubated at room temperature overnight. Then enzyme-digested products were purified by 1 mL HisTrap HP column (Cytiva), and the proteins were eluted in the lysis buffer supplemented with 300 mM imidazole, and the elutions were further purified by applying on Superdex 200 increase 10/300 GL column (Cytiva) equilibrated with buffer B. For the presentation of full scan blots, please see the Source Data files and The cleavage reaction of Csx30-RpoE complex was performed by gRAMP_D547A _D698AFurther information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Drosophila and human cells, we found that the off-target effects of RxCas13d, a commonly used Cas13 effector, can be as strong as the level of on-target RNA knockdown. The extent of off-target effects is positively correlated with target RNA expression levels, and collateral damage can be observed even after reducing RxCas13d/guide RNA levels. The PspCas13b effector showed improved specificity and, unlike RxCas13d, can be used to deplete a Drosophila circular RNA without affecting the expression of the associated linear RNA. PspCas13b nonetheless still can have off-target effects and we notably found that the extent of off-target effects for Cas13 effectors differs depending on the cell type and target RNA examined. In total, these results highlight the need for caution when designing and interpreting Cas13-based knockdown experiments.CRISPR/Cas13 effectors have garnered increasing attention as easily customizable tools for detecting and depleting RNAs of interest. Near perfect complementarity between a target RNA and the Cas13-associated guide RNA is required for activation of Cas13 ribonuclease activity. Nonetheless, the specificity of Cas13 effectors in eukaryotic cells has been debated as the Cas13 nuclease domains can be exposed on the enzyme surface, providing the potential for promiscuous cleavage of nearby RNAs . Here, using co-transfection assays in  The ability to edit eukaryotic genomes and alter gene expression patterns has revolutionized biology in recent years, opening up many new opportunities for defining gene functions and developing new therapeutic approaches. In particular, CRISPR -Cas systems, which function as defense mechanisms in prokaryotic cells against invading viruses and plasmids ,2, have trans-cleavage events) have been observed in bacteria (in vitro (trans-cleavage events) when expressed in eukaryotic cells. This debate has made it unclear how phenotypes observed with Cas13 should be interpreted and whether Cas13 effectors indeed have biotechnological potential for use as specific RNA knockdown tools in eukaryotic cells.Cas13 effectors associate with a guide RNA that base pairs to a target RNA via a spacer sequence that is often 22–30 nucleotides (or even longer) in length . Notablybacteria  and in vin vitro ,26, wherin vitro ,28. Therin vitro  or do noin vitro ,32–36 haDrosophila and human cells. We find that the off-target (trans-cleavage) effects of RxCas13d can be as strong as the level of on-target (cis-cleavage) knockdown observed in cells. The extent of off-target effects is positively correlated with the target RNA expression levels, and collateral damage can be observed even after reducing RxCas13d/guide RNA levels. In contrast, we find that PspCas13b shows improved specificity and, unlike RxCas13d, can be used to deplete a Drosophila circular RNA without affecting the expression of the associated linear RNA. Notably, we find that the extent of Cas13 off-target effects can differ between RNA targets and between human cell lines, which helps explain why there have been conflicting reports regarding Cas13 specificity. In total, our results underscore the need for caution when designing and interpreting Cas13 experiments, while also suggesting that certain Cas13 effectors, such as PspCas13b, may be more appropriate for use in eukaryotic cells.We thus aimed to determine the efficiency and specificity of several prominent Cas13 effectors, including RxCas13d   and PspCDrosophila DL1 and S2 cells were cultured at 25°C in Schneider's Drosophila medium (Thermo Fisher Scientific 21720024), supplemented with 10% (v/v) fetal bovine serum (HyClone SH30396.03), 1% (v/v) penicillin-streptomycin (Thermo Fisher Scientific 15140122), and 1% (v/v) l-glutamine (Thermo Fisher Scientific 35050061).2 in Dulbecco's modified Eagle's medium (DMEM) containing high glucose (Thermo Fisher Scientific 11995065) supplemented with 10% (v/v) fetal bovine serum (HyClone SH30396.03) and 1% (v/v) penicillin-streptomycin (Thermo Fisher Scientific 15140122).HeLa and HEK293T cells were cultured at 37°C and 5% CODrosophila plasmids that co-express a Cas13 effector along with its associated guide RNA, site directed mutagenesis was first used to remove the existing BsmBI site from the previously described pUb 3xFLAG MCS plasmid backbone , Laccase2 Exons 1–3 , and nLuc  under the control of the inducible Metallothionein A promoter were described previously  under the control of the Ubi-p63e promoter was described previously (eviously . Reporte5 cells per well) in complete Schneider's Drosophila medium and cultured overnight. On the following day, 500 ng of plasmid DNA was transfected (using a master mix) into each well using Effectene . Unless otherwise noted, 50 ng of Cas13 expression plasmid was transfected along with 225 ng of each of the on-/off-target expression plasmids. pUb-3xFLAG-MCS (No BsmBI) was used as the empty vector plasmid. Total RNA was isolated ∼40 h later using TRIzol (Thermo Fisher Scientific 15596018) according to the manufacturer's instructions. When examining reporters driven by the Metallothionein A promoter, a final concentration of 500 μM copper sulfate (Fisher BioReagents BP346-500) was added to cells for the last 14 h prior to RNA isolation.DL1 cells were seeded in 12-well plates (5 × 106 cells per well) in complete Schneider's Drosophila medium and cultured overnight. On the following day, 2000 ng of plasmid DNA was transfected into each well using Effectene . As above, total RNA was isolated ∼40 h later using TRIzol (Thermo Fisher Scientific 15596018) according to the manufacturer's instructions.S2 cells were seeded in six-well plates  and the corresponding guide RNA expression vector  were described previously . The PsppcDNA3.1(+)/AUG-nLuc-3XFLAG reporter (Addgene #127299) was previously described  and the 5 cells per well) or HEK293T cells (5.5 × 105 cells per well) were seeded in 6-well plates in complete DMEM medium and cultured overnight. On the following day, 1000 ng of plasmid DNA was transfected (using a master mix) into each well using Lipofectamine 2000 (Thermo Fisher Scientific 11668019) according to the manufacturer's instructions. Unless otherwise noted, 300 ng of Cas13 expression plasmid and 200 ng of guide RNA expression plasmid were transfected along with 250 ng of each of the on-/off-target expression plasmids. pBEVY-L was used as the empty vector plasmid , and oligonucleotide probes were performed as previously described . Oligonug for 15 min and the supernatants were moved to new tubes. Samples were resolved on NuPAGE 4–12% Bis–Tris gels (Thermo Fisher Scientific NP0323) and transferred to PVDF membranes (Bio-Rad 1620177). Membranes were blocked with 5% nonfat milk for 1 h before incubation in primary antibody (diluted in 1× TBST) overnight at 4°C. Membranes were then washed with 1× TBST (3 × 5 min) followed by incubation in secondary antibody at room temperature for 1 h. The following antibodies were used: rabbit anti-HA , mouse anti-α-tubulin , rabbit anti-GAPDH , sheep anti-mouse IgG/HRP , and donkey anti-rabbit IgG/HRP . Membranes were processed using SuperSignal West Pico PLUS Chemiluminescent Substrate (Thermo Fisher Scientific 34580) according to the manufacturer's protocol.Cells were lysed 40 h after transfection using RIPA buffer  for 20 min on ice. Lysates were then spun at 12 000 × 9 μg of total RNA (quantified by Nanodrop) was digested with TURBO DNase (Thermo Fisher Scientific AM2238) in a 50 μl reaction following the manufacturer's protocol. 1 μg of the digested RNA was then reverse transcribed to cDNA in a 20 μl reaction using SuperScript III (Thermo Fisher Scientific 18080051) with random hexamers following the manufacturer's protocol. cDNA was diluted 10-fold with DEPC-treated water and RT-qPCR was performed using Power SYBR Green PCR Master Mix (Thermo Fisher Scientific 4368708). RT-qPCR reactions were performed in 15 μl reactions that contained 1.5 μl of diluted cDNA, 7.5 μl 2× Power SYBR Green PCR Master Mix, and 6 μl 1.5 μM gene-specific primer pairs. Primer sequences were tested by serial dilution and melt curve analysis, and their sequences are provided in Drosophila Act42a or human GAPDH) were calculated using the 2−ΔΔCT method. RT-qPCR reactions were performed using three independent biological replicates, with each replicate having two technical replicates.Using the LightCycler 96 Real-Time PCR System (Roche) and white plates (VWR 10755–256), the following cycling conditions were used: 95°C for 10 min, 40 amplification cycles of 95°C for 15 s followed by 60°C for 1 min, and a final melting cycle of 95°C for 10 s, 65°C for 1 min, and 97°C for 1 s. Subsequently, a melt curve was performed to verify that amplified products were a single discrete species. Threshold cycle (CT) values were automatically calculated by the LightCycler system and relative transcript levels  because it is among the smallest and most commonly used Cas13 effectors (Drosophila DL1 cells were transiently transfected with the RxCas13d/guide RNA (24-nucleotide spacer length) expression plasmid along with reporter gene plasmids that express eGFP and mCherry from the copper-inducible Metallothionein A (MtnA) promoter. 24 h after transfection, copper sulfate was added to induce transcription of eGFP and mCherry. Total RNA was subsequently isolated after an additional 14 h. Northern blots revealed, as expected, that expression of RxCas13d and a random guide RNA sequence (with no predicted targets in the Drosophila genome) had no effect on expression of the fluorescent reporter genes  by RxCas13d. However, for all of the eGFP and mCherry guide RNAs tested, we notably detected equally strong depletion (60–75%) of the non-target reporter mRNA as well as the mRNA encoding RxCas13d itself  effects were observed with the random guide RNA  has been observed with a number of Cas13 effectors in vitro (Drosophila DL1 cells have low transfection efficiency (∼10%), it is difficult to see degradation of endogenous transcripts  effects of RxCas13d can be as strong as on-target knockdown (cis-cleavage) in cells.Given that (i) no off-target A Figure , we reasin vitro ,26–28, bin vitro ) have suin vitro ,32–36. Btrans-cleavage) is minimized. First, the co-transfection assays were repeated using catalytic dead RxCas13d (denoted dRxCas13d) that harbors quadruple mutations (R239A/H244A/R858A/H863A) in the HEPN (Higher Eukaryotic and Prokaryotic Nucleotide-binding) nuclease domains  effects of RxCas13d in cells.We aimed to explore the underlying cause of the RxCas13d off-target effects and determine if cellular conditions could be identified in which bystander RNA degradation  of mCherry by RxCas13d was only observed when expression of the eGFP target mRNA had been induced (We next examined whether the off-target effects are dependent on the presence of the target RNA . Similar induced . Collect induced .trans-cleavage) effects in Drosophila cells, we systematically altered each of the components of the co-transfection assay. Neither extending the RxCas13d guide RNA spacer length from 24 to 30 nucleotides (trans-cleavage) effects observed with RxCas13d. In all cases, the extent of off-target effects remained as strong as the level of on-target knockdown observed  effects and diminish off-target RNA degradation (trans-cleavage events). To first test the effect of reducing RxCas13d/guide RNA levels, the amount of RxCas13d/eGFP guide RNA plasmid transfected was reduced by 10-fold  activity.Although the nuclease activity of activated RxCas13d may lack strong specificity, we reasoned that limiting the amounts of RxCas13d/guide RNA and/or the activating target mRNA in cells may maximize on-target (trans-cleavage) RxCas13d nuclease activity. In contrast, as the eGFP mRNA levels were progressively decreased, the amounts of off-target effects also decreased and ultimately went away. For example, when 2 ng of eGFP plasmid was transfected, eGFP guide-2 resulted in >75% depletion of eGFP mRNA  effects may be minimal as the RxCas13d/guide RNA complex is rarely in an activated state (bound to the target RNA). Furthermore, this observation regarding target RNA abundance likely helps explain in part why some groups have suggested RxCas13d has good specificity in cells  effects of different Cas13 effectors could be highly divergent in Drosophila cells.The potential for significant off-target effects with RxCas13d severely limits its ability to catalyze specific depletion of RNAs of interest in subtypes . Cas13 esubtypes . In factLeptotrichia wadei) was originally shown in 2017 to be able to elicit knockdown of target RNAs in Escherichia coli and human HEK293FT cells, with an efficiency similar to that of short hairpin RNAs (shRNAs) in human cells (Drosophila DL1 cells (LwaCas13a (isolated from an cells . We founL1 cells . HoweverL1 cells . This neL1 cells .Prevotella sp. P5-125) (cis-cleavage) by PspCas13b. As expected, these on-target effects were lost when the guide RNAs alone (without the PspCas13b effector) were transfected (Drosophila cells.We instead obtained much more promising results when PspCas13b (from  P5-125)  was used P5-125) . Guide R P5-125) , left or P5-125) , right rnsfected  or when nsfected   gene, which can be backspliced to generate a 490-nt circular RNA from exon 2 that accumulates to high levels in vivo (cis-acting sequences required for laccase2 backsplicing and generated a copper-inducible three-exon minigene plasmid (Hy_pMT Laccase2 Exons 1–3) that efficiently produces a three-exon linear RNA as well as a circular RNA from exon 2  HA-tagged RxCas13d  followed by a 2A peptide and eGFP  a and eGFP , (iii) 3and eGFP . Guide Rand eGFP , left orand eGFP  enabled s Figure , activats Figure . Northers Figure  or nLuc s Figure  guide RNES cells ,31. We ps Figure . Consists Figure  and nLucs Figure –C.trans-cleavage) effects of RxCas13d in HeLa cells are diminished when the target mRNA level is reduced, we performed a titration assay analogous to that performed previously in Drosophila cells  observed  effects.To determine if the off-target  effects. Here, if one only focuses on the effects on RxCas13d-2A-eGFP mRNA levels, then it might be concluded that RxCas13d has the same degree of off-target effects between HeLa and HEK293T cells  effects  beyond the intended target RNA . Indeed, in the initial report characterizing the activity of a Cas13a effector (C2c2), prominent collateral damage effects were noted in bacteria  effects concomitantly increased  effects, perhaps due to their transcript lengths, subcellular localization, or accessibility  may have better specificity, especially in  Figures . Consist Figures  and to i Figures .In total, our data lead to the obvious question of whether Cas13 effectors can or should be used in eukaryotic cells to knock down a specific RNA of interest. We conclude that caution is needed and there is unfortunately not yet a straightforward answer. We observed prominent roles for target RNA expression and cell type in dictating the degree of Cas13-mediated off-target effects. When trying to deplete a lowly abundant RNA, it seems like it may be possible to achieve specific knockdown (e.g. with PspCas13b), but it is critical that care is taken to ensure that a minimal number of activated Cas13 proteins are present in cells. This task becomes increasingly more difficult as target RNA abundance increases. There are nonetheless situations when Cas13 collateral damage activity in eukaryotic cells may be useful, e.g. to kill cancer cells that are expressing a tumor-specific antigen or a mutated oncogene  or to imgkac159_Supplemental_FileClick here for additional data file.


Clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein (Cas) systems, especially type II (Cas9) systems, have been widely developed for DNA targeting and formed a set of mature precision gene-editing systems. However, the basic research and application of the CRISPR-Cas system in RNA is still in its early stages. Recently, the discovery of the CRISPR-Cas13 type VI system has provided the possibility for the expansion of RNA targeting technology, which has broad application prospects. Most type VI Cas13 effectors have dinuclease activity that catalyzes pre-crRNA into mature crRNA and produces strong RNA cleavage activity. Cas13 can specifically recognize targeted RNA fragments to activate the Cas13/crRNA complex for collateral cleavage activity. To date, the Cas13X protein is the smallest effector of the Cas13 family, with 775 amino acids, which is a promising platform for RNA targeting due to its lack of protospacer flanking sequence (PFS) restrictions, ease of packaging, and absence of permanent damage. This study highlighted the latest progress in RNA editing targeted by the CRISPR-Cas13 family, and discussed the application of Cas13 in basic research, nucleic acid diagnosis, nucleic acid tracking, and genetic disease treatment. Furthermore, we clarified the structure of the Cas13 protein family and their molecular mechanism, and proposed a future vision of RNA editing targeted by the CRISPR-Cas13 family. Escherichia coli. Unfortunately, there is not enough DNA sequence data available, and Ishino et al. could not explain the function of these unique sequences . In. In21]. This study mainly reviews the systematic classification, defense mechanism, and the application prospect of RNA editing targeted by the CRISPR-Cas13 family, and especially highlights the latest research progress of the CRISPR-Cas13 family, including Cas13d and Cas13X. The existing problems of RNA editing systems based on the Cas13 family are also analyzed.The CRISPR system is classified mainly according to its evolutionary development of the CRISPR system, Cas protein sequence, and genomic locus architecture . The adaRecently, researchers identified a CRISPR-Cas13 system in type VI CRISPR systems that can target RNA with high specificity when screening Cas proteins in microbial genome and metagenomics data. To date, the CRISPR-Cas13 system is the only known RNA editing in prokaryotes ,35,36. TCRISPR-Cas13 members can be divided into four subtypes  according to their phylogeny. A homology analysis indicated that those four subtypes shared low homology except for the HEPN domain . InteresEubacterium and Ruminococcus. Cryo-electron microscopy analysis of Cas13d indicated that it was a ~930 aa endoribonuclease and shared less similarity except for two conserved R-X4–6 H HEPN motifs (HEPN1 and HEPN2), compared to previous type VI CRISPR systems ..47].Gootenberg et al. designed a fast, cheap, and sensitive portable nucleic acid diagnosis platform, called SHERLOCK, based on the RNA trans-cleavage activity of Cas13 type VI CRISPR systems and strict crRNA complementary base pairing, and successfully applied it for nucleic acid detection and diagnosis . Later, The visualization of RNA localization and dynamics in living cells is an important technique for the in-depth study of RNA subcellular localization and function. Currently, single-molecule fluorescence in situ hybridization (smFISH) of RNA is the most commonly used method to observe the dynamics of intracellular RNA. However, CRISPR-Cas13 tagging fluorescent markers accelerate the development of RNA tracking and imaging in living cells b 56,102102. In 2Immunotherapy and precision medicine based on RNA editing become effective alternatives for antiviral therapies in animals and plants due to their specific target delivery and non-permanent genetic effect . PreviouFor antiviral therapy in mammals and plants, Freije et al. showed that the Cas13 effector can be programmed to target and destroy the genomes of multiple mammalian single-stranded RNA viruses, including lymphocytic choriomeningitis virus (LCMV), influenza A virus (IAV), and vesicular stomatitis virus (VSV) . MoreoveMyo6) transcripts that cause hearing loss in a mouse model [CRISPR/Cas13-based gene therapy strategies can treat many diseases, such as dominant and recessive genetic diseases, cancer, cardiovascular diseases, and neurodegenerative diseases . The CRIse model .In previous studies, oncogenes and toxic RNAs were knocked down by Cas13a under the control of a minimal promoter regulated by NF-κB transcription factor binding . In addi6A in PTH1R mRNA by the photoactivatable RNA m6A editing system using CRISPR-dCas13 (PAMEC) in bone marrow mesenchymal stem cells could hinder osteogenic differentiation and reduce translation efficiency without changing RNA stability [Cas13 family proteins are also widely used for the mRNA process because they are currently found to be CRISPR effectors that specifically cleave RNA . The firtability .As we know, because RNA is one of the most important messengers in cellular processes, characterization of its function and dynamic metabolism is crucial for understanding life processes. The use of the RNA-targeted CRISPR-Cas13 system will contribute to the understanding of the RNA’s function. Cas13 protein is an effector with dual ribonuclease activities (including pre-crRNA processing and crRNA-mediated RNA cleavage), and has unique advantages in RNA-specific recognition, RNA cleavage, and trans-activating activity). It has a wide application prospect in biomedical basic research, animal disease models, genetic disease diagnosis, nucleic acid subcellular localization, and disease treatment. Presently, although the CRISPR-Cas13 family can avoid permanent damage to the genome of organisms because of RNA targeting, it should be considered for the toxic effects of RNA-targeted cleavage. Cas13X in type VI CRISPR systems possesses a small size (~775 aa) without a PFS limit, enabling it to be conveniently fused with multiple RNA arrays and improving its high-throughput application. Taken together, RNA editing targeted by the CRISPR-Cas13 family further expands the CRISPR toolkit for RNA manipulation and greatly enhances diagnostic capabilities.


COOLAIR, are generated at the Arabidopsis floral-repressor locus FLOWERING LOCUS C (FLC)1. Different isoforms of COOLAIR influence FLC transcriptional output in warm and cold conditions7. Here, to further investigate the function of COOLAIR, we developed an RNA structure-profiling method to determine the in vivo structure of single RNA molecules rather than the RNA population average. This revealed that individual isoforms of the COOLAIR transcript adopt multiple structures with different conformational dynamics. The major distally polyadenylated COOLAIR isoform in warm conditions adopts three predominant structural conformations, the proportions and conformations of which change after cold exposure. An alternatively spliced, strongly cold-upregulated distal COOLAIR isoform6 shows high structural diversity, in contrast to proximally polyadenylated COOLAIR. A hyper-variable COOLAIR structural element was identified that was complementary to the FLC transcription start site. Mutations altering the structure of this region changed FLC expression and flowering time, consistent with an important regulatory role of the COOLAIR structure in FLC transcription. Our work demonstrates that isoforms of non-coding RNA transcripts adopt multiple distinct and functionally relevant structural conformations, which change in abundance and shape in response to external conditions.Cellular RNAs are heterogeneous with respect to their alternative processing and secondary structures, but the functional importance of this complexity is still poorly understood. A set of alternatively processed antisense non-coding transcripts, which are collectively called  COOLAIR RNA isoforms change in abundance and shape in response to external conditions; structural mutation of these isoforms altered FLC expression and flowering time, consistent with a regulatory role of the COOLAIR structure in FLC transcription.The structures of single  COOLAIR transcripts are alternatively polyadenylated at proximal sites to give around 400-nucleotide (nt) class I transcripts, or at distal sites to give around 600–750-nt class II transcripts1  grown in warm conditions and after two weeks of cold exposure when FLC is transcriptionally downregulated12. RNA structure determination was carried out using in vivo selective 2′-hydroxyl acylation analysed by primer extension (SHAPE) chemical probing in Arabidopsis thaliana seedlings. The SHAPE reagent, 2-methylnicotinic acid imidazolide (NAI), modifies single-stranded sites of all four RNA nucleotides13. The extracted RNAs were reverse transcribed, and the modified sites led to mutations in the complementary DNA (cDNA) . By comparing our SHAPE reactivities with the 18S rRNA phylogenetic secondary structure15, we found that our smStructure-seq analysis can accurately investigate the full-length RNA structure in vivo  Fig. . We thenles Fig. . To bencCOOLAIR isoforms in warm and cold conditions , such as COOLAIR, are dynamically involved in co-transcriptional regulation and, therefore, thermodynamics may have an incomplete role in determining the RNA structure in vivo17. We therefore developed an analysis method for our smStructure-seq that adopted stochastic context-free grammar (SCFG) constrained by individual SHAPE reactivity profiles, enabling the determination of the RNA structure of single-RNA molecules independent of thermodynamics. We named this structural analysis method DaVinci (Determination of the Variation of the RNA structure conformation through stochastic context-free grammar). DaVinci can construct a wide RNA structure landscape by generating the conformation of individual RNA structures from each in vivo SHAPE mutational profile , which enhances the production of class II.iv  , which showed increased chromatin association of the class II COOLAIR across the FLC TSS region in the mut line 3  and higher than those of the mut lines 3 Fig. . FLC tranes Fig. , supportFLC TSS region, we reasoned that the conformation-dependent COOLAIR–FLC chromatin association might involve the direct binding of COOLAIR to FLC DNA. Potentially, COOLAIR could complement the FLC Watson strand to form a DNA–RNA duplex, although we have not found COOLAIR to form a significant R-loop at the 5′ end of FLC19. Alternatively, COOLAIR could bind to the double-stranded DNA (dsDNA) to form a DNA–RNA triplex21  in both active FRI and null fri genotypes  and Var2–6 near-isogenic line have been described previously7. FLCWT, FLCWT-TEX, FLCmut, FLCmut-r, FLCmut-TEX and FLCmut-r-TEX were transgenic lines carrying an approximately 12 kb wild-type or mutated FLC genomic fragment. FLCmut was generated by introducing four-nucleotide mutations using site-directed mutagenesis. FLCWT-TEX and FLCmut-TEX were generated by inserting a NOS terminator fragment in the first exon of COOLAIR in the wild-type or mutated FLC genomic fragment, respectively3. FLCmut-r was generated by inserting a fragment (GAAATAAAGCGAGAACAAATGAAAACCCAGGT) complementary to the big bulge in the H4–H6 region using site-directed mutagenesis. Primers used for the construction are listed in Supplementary Table 26) and transformed into the Arabidopsis flc-2 FRI genotype3 with a floral-dipping method. Transgenic lines with a single insertion that segregated 3:1 for Basta resistance were identified in the T2 generation to generate homozygous T3 lines. T3 homozygous lines with FLCmut in flc-2 FRI background were crossed with Col FRI (WT) for F1 generation  for 10 days. For the cold treatment, the plants were subjected to a two-week treatment at 5 °C (8 h light and 16 h dark conditions) after a 10-day pre-growth period in warm conditions.13. In brief, A. thaliana seedlings were completely covered in 20 ml 1× SHAPE reaction buffer  and 0.5 mM MgCl2) in a 50-ml Falcon tube. NAI was added to a final concentration of 1 M and the tube swirled on a shaker . This high NAI concentration allows NAI to penetrate plant cells and modify the RNA in vivo. After quenching the reaction with freshly prepared dithiothreitol (DTT), the seedlings were washed with deionized water and immediately frozen with liquid nitrogen and ground into powder. Total RNA was extracted using the hot phenol method4, followed by DNase I treatment in accordance with the manufacturer’s protocol. The control group was prepared using DMSO (labelled as (−)SHAPE), following the same procedure as described above. Then, 2 µg (+)SHAPE or (−)SHAPE RNA samples was added to a 19-µl buffer system containing 2 µl 0.5 µM RNA–DNA hybrid adaptors ), 4 µl 5× reaction buffer , 2 µl 10× DTT  and 1 µl TGIRT-III enzyme . The reaction system was pre-incubated at room temperature for 30 min, then 1 µl of 25 mM dNTPs  was added. The whole reaction system in the tube was incubated at 60 °C for 120 min. To remove the TGIRT-III enzyme from the template, 1 µl of 5 M NaOH was added and the sample incubated at 95 °C for 3 min. The sample was cooled down to room temperature and neutralized with 1 µl of 5 M HCl before the clean-up of the cDNAs with a MinElute Reaction Cleanup Kit . To capture class I and class II COOLAIR isoforms along with 18S rRNA, PCR reactions with 10 cycles were done with specific primers  with parameters ‘--minPasses=3’ in order to achieve around 99.8% predicted accuracy (Q30)14. The HiFi reads were demultiplexed using the demultiplex barcoding algorithm Lima v.1.11.0 (https://github.com/pacificbiosciences/barcoding). The derived HiFi reads were mapped to both COOLAIR references and 18S rRNA  and ones 11. To generate the overall SHAPE reactivity profiles, the mutation rate (MR) at a given nucleotide is simply the total number of ones divided by the total number of zeroes and ones at that location. Raw SHAPE reactivities of class II COOLAIR were then generated for each nucleotide using the following equation:(−)SHAPE, represents the specificity at a specific location. The raw SHAPE reactivity (R) mathematically estimates the positive likelihood ratio of SHAPE modification. The raw SHAPE reactivity was normalized to a standard scale that spanned from 0 (no reactivity) to around 1 (high SHAPE reactivity)28 for showing the mutational profiles.The raw reads from (+)SHAPE and (−)SHAPE libraries were converted into HiFi reads (circular consensus sequences) using ‘ccs’ . The generated RNA structures with constraints derived from individual bitvectors were collected. Because the different structures can have the same mutational profile during probing, we used the sampling function with constraint of a bitvector to capture multiple structures of class II.ii COOLAIR isoforms. All of the collected RNA structures were transformed into dot-bracket strings followed by transformation into RNA structure elements using rnaConvert in the Forgi package31. The digitalized RNA secondary structure elements were extracted to create a numeric matrix and subjected to dimensionality reduction, such as PCA or multidimensional scaling. The dimensionality reduction results were clustered using k-means clustering with the k-means function from the scikit-learn Python package32. The value of k was set as determined visually. The representative structure for each cluster was identified by calculating the most common RNA structure type at each position  and was determined by the RNA structure that is at the centre of the cluster and most similar to the most common RNA structure. The base-pair probability was calculated by counting the frequency of all present base pairs in the conformation space. The positional base-pair probability was derived by Pij is the probability of base i of being base-paired with base j, over all its potential J pairing partners. The likelihood of single strandedness was calculated by the expression of 1 − Pi. In addition, the Shannon entropy was calculated as The whole pipeline of DaVinci is illustrated in Extended Data Fig. 11 were obtained from RRE-invitroDMS_NL43rna.bam (https://codeocean.com/capsule/6175523/tree/v1). Probing data for the cspA 5′ untranslated region33 at 37 °C and 10 °C were obtained from Sequence Read Archive (accessions numbers SRR6123773 and SRR6123774). We performed the RNA structure probing experiments of in vitro folded HIV-1 RRE61 RNAs (3 pmol) containing the stem loops III, IV and V18 as described previously11. The TenA RNAs (3 pmol) were subjected to NAI chemical treatment34 in the presence or absence of 1 µM thiamine pyrophosphate (TPP). The NAI-modified RNA samples (TPP-treated and non TPP-treated RNAs) were mixed with a ratio of 20:80 (vol/vol) or 50:50 (vol/vol) for the library construction. All of the sequencing data were mapped to the respective references as described above. The subsequent bitvectors were generated and subjected to the DaVinci analysis described above, including the creation of the numeric matrix for the digitalized RNA structure elements, dimensionality reduction, k-mean determination and representative structure construction. In silico structural ensemble analysis of RRE wild-type and mutant RRE61 were performed by Boltzmann sampling  using RNAfold35. The subsequent analysis for the in silico structure ensemble is the same as for the DaVinci analysis but includes only the steps of creating the numeric matrix for the digitalized RNA structure elements, dimensionality reduction, k-mean determination and representative structure construction.Probing data for HIV-1 RRE36. Genomic DNA was digested with TURBO DNA-free  according to the manufacturer’s guidelines before reverse transcription was performed. Reverse transcription was performed with the SuperScript III Reverse Transcriptase  following the manufacturer’s protocol using gene-specific primers. The standard reference gene UBC (At5g25760) for gene expression was used for normalization. All primers are listed in Supplementary Table Total RNA was extracted as previously described37. In brief, 2 g of warm-grown or cold-grown seedlings were ground into fine powder using mortar in liquid nitrogen. Then, 1% of the materials (about 200 mg fine powder) was used for total RNA extraction as described above. The nuclei from the remaining material were prepared with Honda buffer in the presence of 50 ng μl−1 tRNA, 20 U ml−1 RNase inhibitor , and 1× cOmplete protease inhibitor (Roche). The nuclei pellet was resuspended in an equal volume of resuspension buffer (50% (vol/vol) glycerol, 0.5 mM EDTA, 1 mM DTT, 100 mM NaCl and 25 mM Tris-HCl pH 7.5) and washed twice with urea wash buffer . Two volumes of wash buffer were added to the resuspended nuclei and vortexed for 1 s. The chromatin was spun down and protein was removed using phenol–chloroform. RNAs from the supernatant were precipitated with isopropanol, dissolved and DNase-treated. The chromatin-bound RNAs were reverse-transcribed with the SuperScript III Reverse Transcriptase  following the manufacturer’s protocol. A mixture of gene-specific primers 38, to estimate how many RNAs were bound to genome DNA (expressed as (chromatin-bound RNA)/EF1alpha), were included in the reverse-transcription reaction. The total RNAs were also reverse transcribed with the SuperScript III Reverse Transcriptase  following the manufacturer’s protocol. A mixture of gene-specific primers (Supplementary Table PP2A (At1g13320) as a control were added to the reverse-transcription reaction, which estimates the total expression level of class II /PP2A). The chromatin-binding ratio was calculated using the equation:Chromatin-bound RNAs were extracted as previously outlined40. Antisense DNA probes were designed against the distal exon sequence of COOLAIR class II and biotinylated at the 3′ end; probes are listed in Supplementary Table 2, 0.1% NP-40 and 5 mM DTT). The lysate was filtered through two layers of Miracloth  and pelleted by centrifugation. The pellets were washed twice with 10 ml of nuclear wash buffer . The nuclear pellet was then resuspended in nuclear lysis buffer  and sonicated using a Bioruptor ultrasonicator (Diagenode). All of the buffers were supplemented with 0.1 U μl−1 RNaseOUT (Life Technologies), 1 mM PMSF and Roche cOmplete tablets to keep the integrity of any RNA–protein and protein–protein complexes. The following steps were performed as previously described40. For each reaction, 30 μl pre-blocked Streptavidin C1 magnetic beads  were used. Then, 20 μl of RNase A/T1 Mix  instead of RNaseOUT was added into the RNase+ reactions  or FAM (RNA). Oligonucleotide sequences are shown in Supplementary Table 2 at 15 volt cm−1. Gel images were taken with a Typhoon FLA 9500 fluorescence reader . Sequences for the positive control rDNA enhancer En3-PAPAS were obtained from a previous study21.Electrophoretic mobility shift assays (EMSAs) were performed as described previouslyFurther information on research design is available in the Any methods, additional references, Nature Research reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41586-022-05135-9.Supplementary InformationCOOLAIR isoforms as well as the EMSA for triplex formation.The Supplementary Discussion includes details about the advantage of smStructure-seq and the validation of DaVinci methods. Supplementary Figure 1 contains original source images for RT–qPCR of the spliced class I and class II Reporting SummarySupplementary Table 1Primers, adaptor and reference sequences.Peer Review File


The Omicron transmission has infected nearly 600,000 people in Shanghai from March 26 to May 31, 2022. Combined with different control measures taken by the government in different periods, a dynamic model was constructed to investigate the impact of medical resources, shelter hospitals and aerosol transmission generated by clustered nucleic acid testing on the spread of Omicron. The parameters of the model were estimated by least square method and MCMC method, and the accuracy of the model was verified by the cumulative number of asymptomatic infected persons and confirmed cases in Shanghai from March 26 to May 31, 2022. The result of numerical simulation demonstrated that the aerosol transmission figured prominently in the transmission of Omicron in Shanghai from March 28 to April 30. Without aerosol transmission, the number of asymptomatic subjects and symptomatic cases would be reduced to 130,000 and 11,730 by May 31, respectively. Without the expansion of shelter hospitals in the second phase, the final size of asymptomatic subjects and symptomatic cases might reach 23.2 million and 4.88 million by May 31, respectively. Our results also revealed that expanded vaccination played a vital role in controlling the spread of Omicron. However, even if the vaccination rate were 100%, the transmission of Omicron should not be completely blocked. Therefore, other control measures should be taken to curb the spread of Omicron, such as widespread antiviral therapies, enhanced testing and strict tracking quarantine measures. This perspective could be utilized as a reference for the transmission and prevention of Omicron in other large cities with a population of 10 million like Shanghai. Ever since the outbreak of COVID-19 pandemic in December 2019, it has infected more than 500 million people and killed 6 million people worldwide by 02 June, 2022 . The OmiSince 2022, Omicron has caused several small outbreaks in many cities in China, such as Tianjin, Anyang and Shenzhen , 14. In As is well known, the main transmission pathways of COVID-19 in humans is through the inhalation of virus-laden droplets and close contact with infected people . Further alveoli . Nonethe alveoli , 23. Som alveoli , and a r alveoli . Case cl alveoli . Particu alveoli –29. As sEpidemiological models have been a prominent approach to uncover the characteristics of SARS-CoV-2 transmission, and provide information and guidance for policy-makers to deal with the emerging epidemics –42. MeanThe content of the article is arranged as follows: The research methods and data are presented in the second part. Firstly, according to the transmission characteristics of Omicron in Shanghai, a generalized compartment SEIR model was established. Secondly, the parameters of the model were estimated by least square method and MCMC method, and the accuracy of the model was verified by the cumulative number of asymptomatic infected persons and confirmed cases published by Shanghai Municipal Center for Disease Control and Prevention and Shanghai Municipal Health Commission , 17. Thet: the unvaccinated susceptible population S(t), vaccinated susceptible population V(t), latent unvaccinated population D(t), and recovered population R(t), respectively. Before constructing the dynamic model, we first make some assumptions as follows: f is the transmission rate by aerosol, We suppose that susceptible individuals can be infected through contacting with asymptomatic and symptomatic cases, as well as aerosols accumulated during nucleic acid testing. The force of infection for a susceptible individual is approximated as d(t), the average transfer rate a(t) from asymptomatic onset to shelter hospital, and average transfer rate b(t) from symptom onset to designated hospitals are ruled by the time, policy and medical resources.The transmission rate It is assumed that asymptomatic infected people will be quarantined in shelter hospitals, and symptomatic infected people are treated in designated hospitals. When infected people enter the shelter hospitals and designated hospitals, they no longer pose transmission risk to people in society.Vaccination does not provide 100% protection against Omicron variant, but it can reduce the risk of infection, hospitalization and death .Based on the hypotheses above, the transmission diagram is shown in Fig. In this part, we will construct a compartmental susceptible-exposed-infectious-removed (SEIR) model see Fig.  to simulentclass1pt{minimaThe modeling research and simulation just depend upon the publicly available aggregated data. Shanghai Municipal Center for Disease Control and Prevention (SCDC) and Shanghai Municipal Health Commission are authoritative organizations for the prevention and control of epidemic in Shanghai, China , 17. ThrX(t) and Y(t) represent the cumulative number of asymptomatic persons and symptomatic cases, respectively.We collected the daily number of asymptomatic infected persons and confirmed cases in Shanghai from February 26 to May 31, 2022 from Shanghai Municipal Health Commission . More thferences , 41. Stuferences . Since pferences , namely pandemic . Since Opandemic , 48. Stupandemic . In addiThe total population size in Shanghai is 24,871,100 and the average vaccination rate for COVID-19 vaccine is 72.6% . We taked(t),  a(t). Due to small number of infectious cases, we supposed that the detection rate of nucleic acid testing d(t) and the average transfer rate from asymptomatic to shelter hospital a(t) were all constants. We could calculate that d and a, other parameters are calculated and given in Table d, a based on the adaptive combination Delayed Rejection and Adaptive Metropolis (DRAM) algorithm [In the first stage, we considered the spread of Omicron in Shanghai as normal free transmission without aerosol transmission and non-pharmaceutical interventions, δ=0.0009 , 17, 54.entclass1pt{minimalgorithm , 56. MCMlgorithm  which isT is the transition time. Due to the large number of people waiting to be tested and the shortage of medical resources, the rate of nucleic acid testing presented a decreasing form. The nucleic acid detection rate d(t) was presumed to be a decreasing Logistic function, a(t) and b(t) were quadratic functions which decreased first and then increased. According to the news reports on April 13 [b(t) reached a minimum value a(t) reached a minimum of In the second stage from March 28 to April 30, 2022, Shanghai was basically in lockdown and medical resources were relatively tight. Under this situation, as the number of infectives increased, the government started to call for people to stay at home and nucleic acid test was carried out for all people. Faced with the huge number of asymptomatic persons, medical resources began to become strained, and the number of beds in shelter hospitals was seriously insufficient. The government set about transforming and expanding shelter hospitals and designated hospitals. Through the unremitting efforts of the country and government, the shortage of medical resources has gradually eased. On April 30, the number of beds in makeshift hospitals and designated hospitals reached a tight balance . During eference , 38, we the data , 17. As April 13 , a sectiIn the third stage from May 01 to May 31, 2022, Shanghai was in a phase of gradual deregulation, and people in low-risk areas could move freely in regulated area. Online shopping, community group buying, take-aways and supplies of daily life gradually returned to normal. As people’s contact gradually increased, and the risk of contact transmission might magnify. With the sufficient amount of social volunteer workers and the improvement of work efficiency, door-to-door nucleic acid services were carried out for the risk groups. The personnel at the nucleic acid testing points queued up in an orderly manner, and the phenomenon of clustering rarely occurred, and the probability of aerosol transmission started to decrease. Following the availability of medical personnel and an increase in the number of nucleic acid sampling sites, nucleic acid testing rates began to increase relative to the second phase. Due to the number of infected people decreased, the number of beds in designated and makeshift hospitals were sufficient. As a consequence, we could presume that the transfer rates of hospitalization and isolation rate of infected people were the same as those in the first stage. We could calculate that ata from , 17. DurIn the first stage from February 26 to March 28, 2022, the mean value, standard deviation, MC error and Geweke values of estimated parameters were showed in Table In the second stage from March 28 to April 30, 2022, if the lockdown was not adopt in Shanghai and the government did not take strict control measures, the virus would continue to spread as in the first stage. The simulation results of cumulative asymptomatic and symptomatic infected persons were shown in Fig. If aerosol transmission from aggregative nucleic acid detection was not taken into account during this epidemic, accumulated asymptomatic infected individuals and symptomatic cases predicted by the model are demonstrated in Fig. As the number of infectives increased, medical resources have been stretched and there were not enough shelter hospital beds to quarantine the asymptomatic infected people. If the government took measures to lie down and did not expand the number of shelter hospitals in the second stage, and did not take isolation measures for asymptomatic infected persons in the second and third stages, the cumulative number of infected asymptomatic and symptomatic persons predicted by the model are shown in Fig. In this part, we will discuss the impact of adequate medical resources on the spread of Omicron in Shanghai. Here, in case, medical resources are relatively sufficient in the second stage, and there is no run on medical resources. For instance, the rate of nucleic acid testing is consistent with that of the first stage, and the number of beds in shelter hospitals can satisfy the isolation of asymptomatic persons, and the number of beds in designated hospitals can meet the normal hospitalization of symptomatic cases, the cumulative number of asymptomatic and symptomatic cases predicted by the model is shown in Fig.     Here, we will investigate the influence of different vaccination coverage rates on the spread of Omicron in Shanghai. According to the literature , the vacBased on the specific characteristics of Omicron epidemic in Shanghai in the spring of 2022, we established a dynamic model to investigate the role of aerosol transmission caused by aggregative nucleic acid detection and the shelter hospitals in the spread of Omicron epidemic.Firstly, we collected the daily Omicron data of asymptomatic and symptomatic infected cases in Shanghai reported by Shanghai Health Supervision Commission from February 26 to May 31, 2022 and divided the whole transmission process into three stages according to a series of control intervention measures taken by the government. We utilized the nonlinear least square method and Markov chain Monte Carlo method to estimate the parameters of the model, and the cumulative number of asymptomatic and symptomatic infected persons were used to verify the model. The numerical simulation results are shown in Figs. Secondly, sensitivity analysis was applied to investigate the final size of asymptomatic and symptomatic infected persons in Shanghai under different control measures. According to Fig. This article also admits many limitations. First, we considered that the transmission rate was the same for all people. However, researches have indicated that the effect of different age structures on the risk of infection and the influence of heterogeneity in patterns of human social contact was different –62. Sinc


HTLV-1 bZIP factor (HBZ) gene in the antisense strand of the provirus. The HBZ protein is constantly expressed in HTLV-1 carriers and patients with adult T-cell leukemia-lymphoma, and it plays critical roles in pathogenesis. However, HBZ not only encodes this protein, but also functions as mRNA. Thus, HBZ gene mRNA is bifunctional. HIV-1 and BLV also encode long non-coding RNAs as antisense transcripts. In this review, we reshape our current understanding of how these antisense transcripts function and how they influence disease pathogenesis.Exogenous retroviruses such as human immunodeficiency virus type 1 (HIV-1), human T-cell leukemia virus type 1 (HTLV-1) and bovine leukemia virus (BLV) can cause various diseases including immunodeficiency, inflammatory diseases and hematologic malignancies. These retroviruses persistently infect their hosts. Therefore, they need to evade host immune surveillance. One way in which these viruses might avoid immune detection is to utilize functional RNAs, rather than proteins, for certain activities, because RNAs are not recognized by the host immune system. HTLV-1 encodes the  Viruses that cause persistent infection have strategies to evade host immune responses , 2. ThesRNA falls into the general classification of messenger RNA (mRNA) and non-coding RNA (ncRNA). NcRNAs include 1) classical ncRNAs such as transfer RNA (tRNA), ribosomal RNA (rRNA), small nuclear RNA (snRNA), and small nucleolar RNA (snoRNA); 2) functional microRNA (miRNA) and 3) long ncRNA (lncRNA) which is generally defined as ncRNA with a length > 200nt , 7. The In this review, we summarize recent findings on how functional antisense transcripts influence the pathogenicity of retroviruses, focusing on HTLV-1, HIV-1, and bovine leukemia virus (BLV).in vivo. EBV encodes a variety of RNAs that do not encode protein products. Two of these RNAs are EBER1 (167nt) and EBER2 (173nt), which are expressed in all latency types I to III and contain stem-loop RNA hairpins , contains a virally encoded miRNA, called miR-UL112-1. This miRNA maintains hCMV latency  of IE27 . Kaposi- of IE27 . The lnc of IE27 .gag , pro (protease), pol (reverse transcriptase) and env (envelope protein) which are flanked by the 5’ and 3’ long terminal repeats (LTRs). The LTR has promoter activity in both directions, sense and antisense  develop systemic inflammation and T-cell lymphoid malignancies  induces T-cell proliferation  and RNA polymerase II from the 5’ LTR, thereby contributing to the latency of the virus  family that interferes with caspases, the proteolytic components of the apoptotic pathway  activate expression of survivin. In addition, these two HBZ gene products also target host genes associated with the Treg-like phenotype  gene was identified as another gene upregulated by both the mRNA and protein of HBZ  suggests that it plays some important role. Thus, we speculate that, like the HBZ gene in HTLV-1, the ASP gene in HIV-1 may encode a bifunctional mRNA.Recently, it has become clear that natural antisense transcripts can repress sense gene expression . Indeed,1 5’ LTR . A subseith PRC2 . EctopicHBZ carries out many of its functions in “stealth” forms and locations. We have recently discovered that the antisense mRNAs of both HTLV-1 and HIV-1 are normally localized primarily in the nucleus  and in the latency of the virus (for HIV-1) (Both r HIV-1) Figure 2Retroviruses cleverly evade host immunosurveillance and expand their own numbers by intricate mechanisms that include the persistent expression of viral antisense transcripts. These transcripts are disproportionally retained in the nucleus and have lncRNA-like functions. These functions contribute to the persistence of the virus, and to its pathological effects. Moreover, the antisense transcripts of HTLV-1, and possibly HIV-1, can function in both molecular forms, mRNA and protein, suggesting that they are bifunctional.KT and MM wrote this review article. All authors contributed to the article and approved the submitted version.This research is supported by a grant from the Project for Cancer Research And Therapeutic Evolution (P-CREATE) (20cm0106306h0005 to MM), the Research Program on Emerging and Re-emerging Infectious Diseases (20fk0108088h0002 to MM) from the Japan Agency for Medical Research and Development (AMED), and JSPS KAKENHI (19H03689 to MM). This study was also supported in part by the JSPS Core-to-Core Program A, Advanced Research Networks.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.