Structural basis of double-stranded RNA recognition by the J2 monoclonal antibody

Domain: biology
Published: 2025-12-13
Editorial outcome: minor_revision

Abstract
Double-stranded (ds) RNAs are major structural components of the transcriptome, hallmarks of viral infection, and primary triggers of innate immune responses. The J2 monoclonal antibody is the gold-standard method to discover and map endogenous dsRNAs across subcellular locations and cell surfaces, detect exogenous RNAs in viral infection, and surveil mRNA prophylactics and therapeutics for inflammatory dsRNAs. To define its epitope, specificity, and mechanism, we determine a 2.85 Å co-crystal structure of J2 antigen-binding fragment (Fab) bound to dsRNA. J2 uses its heavy and light chains in tandem to track the dsRNA minor groove, recognizing a staggered 8-bp duplex. J2 is highly selective for dsRNAs, requires 14 bp for robust binding, and exhibits greatly diminished binding for GC-rich dsRNAs. J2 and the R-loop-specific S9.6 antibody share a common recognition strategy distinct from intracellular dsRNA-binding proteins. This study provides mechanistic insights into dsRNA recognition and establishes a framework for reliable application and data interpretation of the J2 antibody in RNA discovery.

Introduction
Double-stranded RNA (dsRNA) is a major structural form of cellular coding and noncoding RNAs. Rigid, persistent dsRNA segments assemble into tRNAs, ribosomal RNAs, catalytic and regulatory RNAs including ribozymes and riboswitches, mRNAs (particularly those with long, structured UTRs), long noncoding RNAs (lncRNAs), transcripts from LINE and SINE retrotransposons including Alu elements, and more1–3. Nuclear export of mRNAs and lncRNAs was recently suggested to be facilitated by transient dsRNA formation with their antisense transcripts4, as dsRNAs are preferentially loaded onto RNA export receptors such as Mex67. Abundant dsRNAs are found in the nucleus, cytoplasm, and organelles such as mitochondria due to bidirectional transcription. Excitingly, dsRNAs are increasingly discovered to populate cellular surfaces (e.g., glycoRNAs), extracellular space, including biofilm, tissues and biological fluids5–8.

DsRNA is also a prominent pathogen-associated molecular pattern (PAMP) that frequently accumulates as a result of viral infection and replication1. DsRNAs constitute the genomes of dsRNA viruses such as the rotavirus—the leading cause of acute gastroenteritis in infants and children, the ruminant-infecting Bluetongue virus (BTV), plant-infecting Rice dwarf virus (RDV), and Pseudomonas-infecting Bacteriophage Φ6. DsRNAs are also major structural components of the RNA genomes of single-stranded (ss) RNA viruses and retroviruses such as HIV-1. Besides serving as viral genomes, dsRNAs are frequently produced as replication intermediates of dsDNA, ssDNA, and ssRNA viruses or from bidirectional transcription of viral genomes. As a result, dsRNA has emerged as the principal trigger of innate antiviral immune responses in metazoans and is subject to direct detection by a cohort of pattern recognition receptors (PRRs), including RIG-I, MDA5, LGP2, TLRs, OASs, and PKR1,9. Activation of such dsRNA receptors produces type I interferons and other proinflammatory cytokines, represses global translation and reprograms cellular metabolism towards stress response and apoptosis. Due to the immunogenic and inflammatory properties of dsRNAs, they are either prevented from significant accumulation by RNases, edited by adenosine deaminases acting on RNA (ADARs) to reduce their base-pairing and dsRNA characteristics, or sequestered away from the PRR through protein binding or subcellular compartmentalization in normal nucleic acid metabolism. Dysregulation of dsRNA metabolism is a significant contributor to inflammatory and autoimmune diseases including systemic lupus erythematosus (SLE), inflammatory bowel disease (IBD), type 1 diabetes, and psoriasis10–13.

The J2 monoclonal antibody is the principal tool to map and track endogenous dsRNAs, detect foreign dsRNAs in viral infection, discover and characterize new viruses and RNAs, and surveil mRNA prophylactics and therapeutics for dsRNA contamination14–18. Despite its widespread use, it remains unknown how the J2 antibody recognizes dsRNA and its selectivity towards different types, lengths, and sequences of nucleic acids. Based on an atomic force microscopy (AFM) analysis, it was estimated that J2 requires ~40 bp (base-pair) dsRNA for binding. J2 exhibits a possible preference for A-rich sequences and binds inefficiently to poly(rI)-poly(rC)15,18. The indeterminate J2 specificity, undefined epitope on the dsRNA, potential sequence bias, and unknown mechanism of action have presented significant challenges in its numerous applications. For instance, it has confounded the determination of whether negative-strand RNA viruses produce substantial quantities of dsRNAs in their lifecycle19.

In this work, to address these questions and enable, optimize, and delimit reliable application of and data interpretation for the J2 antibody, we conduct biophysical analyses to define its selectivity, specificity, and binding kinetics. We determined a 2.85 Å co-crystal structure of the J2 Fab bound to a 23-bp dsRNA, which reveals its epitope and unusual mechanism of recognition. We further probe the observed J2-dsRNA interface using mutational analyses and examine the effects of nucleic acid type, length, and sequence on J2 recognition. Finally, we compare the dsRNA recognition strategies employed by secreted antibodies versus those by intracellular proteins.

Results
J2 antibody exhibits high specificity and complex binding kinetics for dsRNAs
Using the antibody-expression platform we recently developed for the S9.6 antibody20,21, we produced both J2 IgG and Fab and performed initial dsRNA binding characterizations using size-exclusion chromatography with multi-angle light scattering (SEC-MALS) and sedimentation velocity-analytical ultracentrifugation (SV-AUC). SEC-MALS revealed that the J2 Fab bound a 27-bp dsRNA forming a 1:1 complex (Fig. 1a, b, Supplementary Fig. 1). AUC analysis further detected stable 1:1 complexes that formed between the J2 Fab and a 23-bp dsRNA, and between the J2 IgG and a 30-bp dsRNA (Supplementary Fig. 1). These analyses confirmed the functional competency of the J2 IgG and Fab we produced and their stoichiometric interactions with dsRNAs of varying lengths.

To define the nucleic acid selectivity of the J2 antibody, we employed biolayer interferometry (BLI) to evaluate its interaction with dsRNA, dsDNA, ssRNA, ssDNA, and RNA-DNA hybrid of the same length (40 nucleotides (nts) per strand) and sequence (Fig. 1a). J2 IgG was immobilized on Protein-A probes and served as the ligand, whereas different nucleic acids were used as analytes. While robust binding by dsRNA was detected, dsDNA, ssRNA, and ssDNA exhibited no appreciable binding to J2 under the same conditions (Fig. 1c, d). Remarkably, J2 robustly discriminates against RNA-DNA hybrids, which form A-form duplex structures similar to dsRNA. This ensures that J2 does not substantially recognize abundant R-loops, which cover 5–10% of bacterial, eukaryotic, and viral genomes22. By contrast, the R-loop-specific S9.6 antibody exhibits substantial cross-reactivity with dsRNAs20,23.

Kinetical analyses of dsRNA binding to J2 IgG consistently produced biphasic sensorgrams (Fig. 1c, Supplementary Figs. 2–4 and Table 1), despite their stoichiometric (1:1) binding observed by AUC (Supplementary Fig. 1). The BLI sensorgrams deviate substantially from a simple, homogeneous binding model and require a heterogeneous ligand model which produced excellent agreement (Supplementary Fig. 3). This suggests the presence of two types of J2 ligands on the surface, or two separable binding modes. To ensure that non-specific surface interactions did not produce the ligand heterogeneity, we first verified the complete absence of RNA binding without J2. We then examined dsRNA binding across a wide range of ionic strengths, orbital speeds, and dsRNA lengths (Fig. 1e–j, Supplementary Figs. 2–4). These additional analyses suggest that dsRNA association with J2 IgG is an inherently heterogeneous process across multiple solute conditions, dsRNA lengths and sequences. By contrast, an Adenovirus Virus-Associated RNA I (VA-I, Supplementary Fig. 2i) bound J2 IgG following a homogeneous binding model, under the same conditions and across several ionic strengths (Fig. 1c, Supplementary Figs. 2, 3). VA-I is a prominent viral mimic of dsRNA that inhibits antiviral Protein Kinase R (PKR) by entrapping PKR monomers using its coaxially stacked apical stem and tetrastem, thereby preventing PKR dimerization and activation9,24. Notably, VA-I dissociates from J2 much more slowly than dsRNA, a characteristic that befits its role in recruiting and sequestering the dsRNA-binding motifs (dsRBMs) of PKR (Supplementary Fig. 3b). In addition, VA-I binding to J2 exhibits higher sensitivity to ionic strength than dsRNAs, which could be due to additional, sequence-specific electrostatic contacts that VA–I was proposed to make (Supplementary Fig. 3b, c)9,24. The distinct behaviors of dsRNA and VA–I suggest that dsRNA elements of different sequences and structures can differentially interact with J2. The observed heterogeneous binding behavior of dsRNA to J2 IgG is likely due to the presence of multiple, non-identical epitopes along the dsRNA, or J2 sliding along the dsRNA, as reported for dsRBMs25. It could also stem from differences in the number of Fabs contacting the dsRNA, paratope conformations or accessibility between the two Fabs due to asymmetric surface immobilization, or the location, orientation, or conformation of the dsRNA epitope during the initial encounter.

The remarkable selectivity of the J2 antibody for dsRNA over hybrids, dsDNA, ssRNA, and ssDNA gives essential assurances that previous and future studies using the J2 antibody provide reliable detection of dsRNAs among numerous competing nucleic acids. Further, the drastic differences between perfectly paired dsRNAs and natural RNAs such as VA-I in J2 binding kinetics and stability suggest J2 does not uniformly detect all dsRNAs in cells, indicating a selectivity for dsRNA length, sequence, or structure.

J2 IgG binds dsRNA in a length-dependent manner
As a widely used tool to detect, image, and enrich dsRNAs of cellular and viral origins, it is important to accurately define the effective dsRNA length required for J2 recognition. A previous AFM analysis estimated a 40-bp length requirement for J2 binding15. However, we observed robust and stable binding of J2 to VA-I RNA, which has a maximal dsRNA length of ~27 bp (Fig. 1f, Supplementary Figs. 2, 3). To quantitatively assess the effect of dsRNA length on J2 binding, we employed a fluorescence polarization (FP) titration assay. First, we measured direct, bimolecular binding of J2 IgG to a 3′-FAM (fluorescein)-labeled VA-I RNA, which yielded an apparent Kd of ~32 nM (Fig. 1f, Supplementary Fig. 3d). Then, we evaluated the ability of dsRNAs of varying lengths to displace the VA-I RNA pre-bound to J2 IgG. While a 6-bp dsRNA could not compete with VA–I at all, the 10-bp and 14-bp dsRNAs exhibited weak but detectable binding to J2 (Fig. 1g). Further elongating the dsRNA progressively and substantially improved binding, attaining an IC50 of ~17 nM at 50 bp (Fig. 1g, h).

To corroborate and extend the FP findings using an orthogonal method, we employed additional BLI analyses. First, we observed that J2 binding to dsRNA is sensitive to the ionic strength, suggesting contributions from electrostatic interactions at the interface (Supplementary Fig. 3). At an near-physiological 100 mM KCl, the 6-bp dsRNA produced no response on the BLI sensor (Fig. 1i, j, Supplementary Fig. 4). The 10-bp dsRNA started to trigger a weak, dose-dependent binding signal. At 14-bp and 20-bp, the dsRNAs yielded robust association responses but also dissociated rapidly from the J2 IgG (Fig. 1i, j, Supplementary Fig. 4 and Table 1). The association signal approached a plateau at 30 and 40 bp dsRNA lengths, while the dissociation further slowed with increasing dsRNA lengths (Fig. 1h–j, Supplementary Fig. 4). At 50-bp length, the dissociation portion of the sensorgrams could not be reliably fit by the heterogeneous ligand model, likely due to local rebinding of longer dsRNAs, or dsRNA being sufficiently long to bridge adjacent IgGs. Overall, the congruent BLI and FP data suggest a minimal length threshold of ~14 bp dsRNA for practical detection by the J2 antibody, and near-optimal J2 binding and retention at dsRNA lengths longer than 30 bp. This length dependency rationalizes our observations that J2 does not substantially bind tRNAs but strongly associates with VA–I, which possess contiguous dsRNA segments of 10–12 bp and 27 bp, respectively (Supplementary Fig. 2h, i).

Co-crystal structure of a J2 Fab bound to 23-bp dsRNA
To visualize how the J2 antibody specifically recognizes dsRNA, discern its minimal epitope, and understand its observed binding preferences, we co-crystallized a J2 Fab bound to a 23-bp dsRNA (Fig. 2a, Table 1 and Supplementary Fig. 5). The structure captured two J2 Fabs bound to the opposite sides of a central, 17-bp portion of the same dsRNA in crystallo, via nearly identical interfaces (all-atom RMSD ~0.6 Å, Fig. 2a, b, d, Supplementary Figs. 5, 6). While the central 17-bp dsRNA segment exhibited well-defined electron density, both flanking 3-bp terminal regions had only weak or no density. This finding is consistent with the notion that terminal regions of dsRNAs, such as HIV-1 TAR, exhibit substantial conformational flexibility and engage in transient excursions26,27. Each J2 Fab footprint on the dsRNA spans approximately 8 bp (Fig. 2b, c, f), which rationalizes the complete lack of binding by the 6-bp dsRNA and emergence of weak binding at 10 bp (Fig. 1i). The structure reveals that J2 uses its heavy chain (HC) and light chain (LC) complementarity-determining regions (CDRs) in a tandem arrangement to continuously track a single minor groove of the dsRNA, similar to how the S9.6 antibody follows the minor groove of RNA-DNA hybrid duplexes20. J2 binding does not substantially deform the dsRNA, reducing the entropic cost of complex formation (Fig. 2e). Interestingly, the J2 Fab asymmetrically binds the two RNA strands that bookend the minor groove in a staggered configuration (Fig. 2c, f). While it makes contacts to seven consecutive nucleotides on one strand (C15-U21 of Chain E), it touches six consecutive nucleotides on the opposite strand (U6-A11 of Chain F), with a 2-bp stagger or offset. As a result, an 8-bp dsRNA constitutes the minimal physical epitope required for J2 binding. Recognition involves a combination of 2′-OH groups, nucleobase edges, and backbone phosphate oxygens (Figs. 2f, 3a, b). Like the S9.6 antibody, the J2 heavy chain CDRs primarily mediate duplex recognition, while the light chain CDRs play assistive roles by positioning and stabilizing the heavy chain CDRs (Fig. 3a, b). Among the three heavy chain CDRs, CDR-H1 (denoting the first CDR of the heavy chain variable region) makes a relatively minor contribution, while CDR-H2 and CDR-H3 play essential roles in binding dsRNA (Figs. 2c, f, 3a, b). CDR-H1 contains a short 310 helix, which positions the peptide backbone carbonyl between N31 and H32 to contact the 2′-OH of A17, near the center of the RNA epitope (Fig. 3a, b). Since the side chains of this 310 helix do not directly bind the RNA, we instead asked if disrupting its main chain helical geometry by an A30P substitution would impact dsRNA binding. Surprisingly, the A30P substitution in the 310 helix is well tolerated, suggesting that the helical conformation is not required to engage the RNA (Fig. 3c, d, Supplementary Fig. 7). It is possible that the increased hydrophobic character of proline helped stabilize the local structure without the 310 helix.

On one flank of the centrally located CDR-H1, the short CDR-H2 binds at the edge of the epitope across the minor groove. It presents a network of three closely spaced tyrosines, Y50, Y52, and Y54, which collectively recognize the U9-A16 base pair. Specifically, Y50 binds the 2′-OH and phosphate oxygen of U9 backbone while Y52 recognizes the N3 of A16 nucleobase (Fig. 3a, b). Both appear to also engage in van der Waals interactions using their aromatic rings. Removing the aromatic moieties by Y50A or Y52A substitution greatly diminished RNA binding, while Y50F and Y52F substitutions produced marginal defects (Fig. 3c, d, Supplementary Fig. 7). Y54 protrudes across the minor groove, packs against the A16 ribose, and appears to engage its O4 group (Fig. 3a, b). Unlike the mutational effects of Y50 and Y52, Y54A conferred little defect while Y54F reduced binding, suggesting a distinct role from Y50 and Y52. Immediately adjacent to Y54, N55 loops back to recognize the 2′-OH group of G10 (Fig. 3a, b). N55A substantially diminished dsRNA binding, indicating the importance of 2′-OH recognition (Fig. 3c, d).

Buttressed by both CDR-H1 and CDR-H2, CDR-H3 binds near the center of the 8-bp dsRNA epitope, placing its N101 residue equidistant to both RNA strands (Fig. 3a, b). This prime location and flat, groove-parallel orientation of N101 allows it to descend deeper into the minor groove, making five hydrogen bonds to both strands. While the N101 main chain contacts the 2′-OH of U18, its side chain carboxamide concurrently engages the O2 of U9, N3 and 2′-OH of A17. Consistent with these numerous contacts, N101A strongly diminished RNA binding (Fig. 3c). To ask if a basic residue at this location might confer higher levels of RNA binding than the wild type, we replaced N101 with an arginine, which is frequently found to mediate RNA interactions such as forming arginine forks with HIV TAR and 7SK RNAs26,27. Compared to N101A, N101R further compromised RNA binding, suggesting that a bulky basic residue does not make favorable interactions at this location. Immediately adjacent to N101 is P102, which redirects the CDR-H3 loop trajectory and further stacks with the functionally important Y50 (Fig. 3a, b). P102A drastically reduced RNA binding, suggesting its functional importance. W104 closely follows N101 and P102, protrudes into the light chain region, and stacks with W56 of CDR-L2, which in turn stacks with Y38 of CDR-L1 (Figs. 2f, 3a, b). W104 is also well positioned to stack with Y55 of CDR-L2, allowing W104 to stabilize an aromatic network among the LC CDRs. Consistent with this structural role at the HC-LC interface, a W104A substitution severely compromised dsRNA binding (Fig. 3c, d).

Contrasting the extensive contacts made by the heavy chain CDRs, the light chain CDRs L1 and L2 only loosely engage the dsRNA, bind in the periphery of the epitope, and make just a handful of direct contacts. CDR-L3 makes no dsRNA contacts. Specifically, Y31 of CDR-L1 binds the 2′-OH of A7 while W56 of CDR-L2 contacts the phosphate oxygen of U20 (Fig. 3b). Y31A but not Y31F substitution substantially reduced RNA binding, which suggests the importance of hydrophobic interactions with the minor groove over specific hydrogen bonds to the RNA polar groups (Fig. 3a, b, Supplementary Fig. 8). The W56A substitution led to a severe reduction in dsRNA binding, confirming its importance. Considering the relative underutilization of the light chain, we asked if installing a basic residue at the tip of the extended CDR-L2 loop, in the form of S33R adjacent to Y31, might boost RNA binding by J2 (Fig. 3b). However, the S33R substitution nearly abolished RNA binding, presumably due to steric clashes at this snug interface (Fig. 3c, d). The strong negative effects of both HC N101R and LC S33R of J2 contrast with the essential role of HC R104 of the S9.6 antibody in hybrid binding20. This suggests that modulating overall electrostatic characteristics of CDRs is not a generally effective strategy to tune antibody binding affinities to duplex grooves. Mirroring the excursion of CDR-H3 W104 to engage with LC CDRs, Y101 of CDR-L3 makes a reciprocal approach to the HC CDRs. It is positioned to make van der Waals interactions with H35 of CDR-H1, W47 of CDR-H2, and F105 of CDR-H3. Due to this putative structural role in stabilizing the HC CDRs, the LC Y101A substitution strongly reduced dsRNA binding, like HC W104A (Fig. 3c, d).

Altogether, each J2 Fab binds 8 bp of dsRNA and recognizes five 2′-OHs, including two consecutive 2′-OHs on each RNA strand across the minor groove (Fig. 2f). Similarly, the S9.6 antibody also recognizes tandem 2′-OHs on the RNA strand20. The concurrent recognition of tandem 2′-OHs on both strands by J2 explains its strong preference for dsRNA over RNA-DNA hybrids (Fig. 1c). Numerous aromatic residues form interaction networks both within and between the HC and LC CDRs to stabilize their conformations, which allows the two chains to work in tandem to track a single, extended dsRNA minor groove. Mutational analyses suggest that van der Waals interactions from the aromatic side chains play a larger role in conferring dsRNA binding than individual hydrogen-bonding moieties such as the phenolic hydroxyls. Finally, we evaluated how well AlphaFold3 can predict the J2-dsRNA interface. Interestingly, AlphaFold3 successfully predicts the conformation of the J2 Fab, including the CDRs, achieving an RMSD of 0.9–1.0 Å. However, it completely fails to predict the J2-dsRNA interface, placing dsRNA in various orientations and locations far from the CDRs (Supplementary Fig. 9). This finding attests to the remarkable ability of AlphaFold3 to predict protein structures and conformations, including antibody CDRs, but also highlights its lack of training in unconventional RNA-protein interfaces, such as antibody-nucleic acids interfaces, underrepresented in the PDB.

J2 exhibits substantial sensitivity to nucleotide composition and skew
Diverse host and viral genomes exhibit wide-ranging GC contents. While the human genome has ~41% GC content, the dsDNA genomes of herpes simplex virus (HSV) contain ~70% GC28. By contrast, the SARS-CoV-2 genome has a lower GC content of ~38%. To ask if GC content affects dsRNA recognition by the J2 antibody, we tested a panel of nine 30-bp dsRNAs with varying GC contents, by both FP and BLI (Fig. 4, Supplementary Fig. 10). Both assays reveal that J2 possesses a substantial preference for low- and mid-GC content dsRNAs. Specifically, BLI analyses reveal that while GC contents from 0% up to 63% retained robust J2 binding with Kd in the nanomolar range, dsRNAs that have 77% GC only marginally bound J2, exhibiting micromolar affinities (Fig. 4b, c). Strikingly, dsRNAs that contain 90% or 100% GC were completely unable to bind J2 IgG under the BLI conditions (Fig. 4c, d, Supplementary Fig. 10). This observation is consistent with a previous report that J2 preferred to bind natural, mixed-composition dsRNAs such as the L dsRNA from yeast killer viruses—its original immunogen—over both poly(rA)-poly(rU) and poly(rI)-poly(rC) duplexes15.

To understand the preference of J2 for nucleotide composition, we first asked whether J2 contacts with specific nucleobase chemical groups could have conferred sequence selectivity. About half of the J2 contacts are to the 2′-OH and phosphate oxygen atoms (Fig. 2f). These RNA backbone contacts are not expected to be sequence selective. The remaining contacts occur between the nucleobases of U9, A16, A17 and side chains of Y52 and N101 of the J2 heavy chain. These are mediated by N3 of purines or O2 of pyrimidines, which are generally indistinguishable between A and G, and between U and C. Therefore, these nucleobase contacts are also unlikely to have produced the observed strong preference in GC content. Next, we explored whether the indirect effects of GC content on the dsRNA helical geometry are responsible for the observed J2 sequence selectivity. GC-rich dsRNAs exhibit substantially stronger intra- and cross-strand stacking, reduced helical rise, and narrower and more rigid minor grooves29–31. To ask if the changing GC content had a meaningful impact on the helical geometry and structure of the dsRNAs used in BLI, we employed temperature-scanning Circular Dichroism (CD) analyses of the duplexes and their constituents sRNA and ssDNA (Figs. 4, 5). RNA CD spectra are complex and multi-component in nature. They include aggregated chiral effects of individual nucleotides such as their glycosidic dihedral angles (anti or syn), π-π stacking between neighboring nucleobases, and overall helicity of the polynucleotide chains32–34. We observed distinct structural features between the AU-rich dsRNAs that bound J2 robustly and their GC-rich counterparts that did not (Fig. 4d–f). Increasing GC content progressively raised the Tm and strengthened intra-strand stacking, as evidenced by the deepening valley at ~210 nm, which was also observed for RNA-DNA hybrids20. This is accompanied by the increasing negative ellipticity near ~235 nm. The rising GC content also red-shifted the ~260 nm peak to near ~270 nm, suggesting a change in the A-form helicity due to increased base stacking and exciton coupling35. These data suggest that structural changes in the dsRNA helix due to changed nucleotide composition, instead of sequence-specific J2 contacts to nucleobase edges, are likely responsible for their variable compatibilities with J2.

Our FP and BLI data detected robust J2 binding to AU-only duplexes (Fig. 4a–d). However, a previous report noted inefficiency of J2 to detect poly(rA)-poly(rU) duplexes similar to poly(rI)-poly(rC)15. To address this discrepancy, we examined J2 binding to five additional 0% GC duplexes (Fig. 5a, Supplementary Fig. 11). We found that J2 exhibited robust binding towards a dsRNA duplex featuring AU dinucleotide steps exclusively with no AU skew between the two strands (Fig. 5a, b). However, binding to the 100% skewed poly(rA)-poly(rU) was much diminished and required high concentrations of the dsRNA. As expected, J2 binding to the poly(rA)-poly(dT) hybrid duplex was even weaker, and there was no binding to the poly(dA)-poly(rU) hybrid or poly(dA)-poly(dT) dsDNA duplexes (Fig. 5b). CD analyses of these duplexes and their constituent ssRNAs exhibited expected spectral features and melting temperatures (Fig. 5b–e). For instance, poly(dA)-poly(dT) dsDNA had characteristic CD peaks at ~280 nm associated with B-form geometry, while the poly(rA)-poly(dT) hybrid exhibited mixed A/B character. Compared to the poly(rA)-poly(dT) hybrid, the poly(dA)-poly(rU) hybrid is the least stable duplex due to reduced pairing, stacking, and helical stabilities (Fig. 5e). Consequently, this hybrid facilitates RNA slippage and shearing during transcription termination36 and reiterative transcription37.

Together, these data suggest that J2 binding is sensitive to the helical geometry of the dsRNA, which is in turn substantially modulated by their sequence composition and skew. Interestingly, similar conclusions were reached for the S9.6 antibody, which preferably binds higher GC content hybrids20.

J2 effectively recognizes the heterogeneous structure of poly(rI)-poly(rC)
Next, we evaluated J2 recognition of poly(rI)-poly(rC), which is widely used as a synthetic dsRNA analog that robustly activates Toll-like receptor 3 (TLR3), PKR, and other dsRNA sensors38,39. Notably, commercial high-molecular-weight (HMW) poly(rI)-poly(rC) is of variable lengths ranging from 1.5–8 kb and consists of annealed poly(rI) and poly(rC) strands. Due to its homotypic sequences and imperfect annealing of such long strands, poly(rI)-poly(rC) is known to exhibit a highly heterogeneous structure containing a mixture of dsRNA and ssRNA segments40,41. We performed temperature-scanning CD analysis of poly(rI)-poly(rC), which reveals unique spectra distinct from both AU-rich and GC-rich dsRNAs but nearly identical to previous measurements (Supplementary Fig. 12). Specifically, poly(rI)-poly(rC) spectra are characterized by prominent 245 and 280 nm peaks, suggesting unusual exciton coupling from the stacked inosine-cytosine pairs and an altered helical structure. This unusual helical geometry is likely at least partially responsible for the previously reported diminished affinity with J215,18. We observed a relatively low Tm of ~55.7 °C, also comparable with previous reports. Considering its average length of ~4.8 kb, this low Tm is consistent with poly(rI)-poly(rC) duplexes being regularly interrupted by ssRNA bulges and loops that reduce the Tm. We then monitored poly(rI)-poly(rC) binding to J2 IgG using BLI. Robust signal was observed at even picomolar concentrations of poly(rI)-poly(rC) (Supplementary Fig. 12). However, the bound poly(rI)-poly(rC) exhibited no discernible dissociation from J2 IgG, presumably due to cross-bridging of multiple J2 IgGs contacting and retaining the same lengthy poly(rI)-poly(rC) molecule. We conclude that J2 is competent in detecting poly(rI)-poly(rC), but it is difficult to quantitatively compare its binding affinity with perfectly paired dsRNA due to its heterogeneous and presumably branched structure. Notably, in typical immunofluorescence experiments with cells, J2 IgG is not immobilized and thus not expected to exhibit extensive cross-bridging with poly(rI)-poly(rC) beyond possible IgG bivalency driven by both Fabs engaging at the same time.

Effects of dsRNA length and Mg2+ on RNA helical geometry
The crystallographically observed 8-bp footprint of J2 Fab on dsRNA and its preferred binding to dsRNA 30 bp or longer may seem at odds with each other. To understand why shorter dsRNAs exhibit diminished binding to J2 despite in theory containing a full epitope, we examined their helical geometry using temperature-scanning CD. Interestingly, we found that as dsRNAs increased in length, their CD spectra progressively changed, concomitant with an expected increase in Tm (Supplementary Fig. 13). The ~276 nm peak typically associated with B-form helix gradually blue-shifted to ~260 nm while the ~210 nm valley deepened, suggesting length-dependent strengthening of A-form helical conformation and intra-strand stacking, respectively. These data indicate that short dsRNA duplexes don’t exhibit the full A-form helical structure of long dsRNAs, presumably due to insufficient accumulative coaxial stacking that compresses the dsRNA and reduces the helical rise. In addition, base pairs near helical termini are prone to fraying and transient opening, further reducing the length of stable dsRNA segment26,27. Therefore, the altered minor groove geometry of short dsRNAs is not well recognized by J2, whose original immunogen was a ~4.6 kb long viral dsRNA. An alternative explanation is that longer dsRNA is more likely to engage bivalent IgG binding via its two Fab arms. However, there is substantial steric hindrance that prevents the two Fab arms of IgG from recognizing immediately juxtaposed or contiguous epitopes. Recent analyses using DNA origami and other synthetic antigen arrays revealed that bivalent IgG binding prefers a 100–150 Å spacing (36–58 bp dsRNA) between adjacent epitopes42–45. Further, the rigidity of dsRNA imposes additional orientation requirements on both J2 Fabs in order to achieve IgG bivalency. These considerations and our AUC and SEC-MALS data favor the notion that shorter dsRNA segments exhibit diminished J2 binding due to their altered helical geometry as opposed to a lack of bivalent IgG binding.

Finally, we examined how Mg2+ may modulate the dsRNA helical structure46–48 and indirectly affect J2 interactions. We collected temperature-scanning CD spectra of 30-bp dsRNAs of low (0%), mid (47%), and high (100%) GC contents, at 0, 1, and 2 mM Mg2+. As expected, Mg2+ stabilized the A-form helical geometry of low- and mid-GC dsRNAs and raised their Tms, while exerting minimal effects on the high-GC dsRNA that is already stable without Mg2+ (Supplementary Fig. 14). There was little difference in the CD spectra collected at 1 or 2 mM Mg2+. Together, these data suggest that RNA topology (e.g., poly(rI)-poly(rC)), dsRNA length, and solute conditions (including monovalent and divalent cations such as Mg2+) likely additionally impact J2 interactions.

Duplex-binding antibodies employ distinct global and local strategies from intracellular dsRNA-binding proteins
The shared strategy of helical, minor groove-tracking used by J2 and S9.6 as secreted antibodies contrasts starkly with known strategies employed by most intracellular dsRNA-binding proteins (Fig. 6a). For instance, dsRBMs bind across three consecutive grooves (minor, major, minor) on the same face, and linearly track the helical axis of dsRNA (Fig. 6b)49. Similarly, transmembrane dsRNA channel SID1 linearly engages four adjacent grooves to capture and import dsRNAs50. By contrast, both J2 and S9.6 limit their contacts to a single minor groove and use their heavy and light chain CDR clusters in tandem to make continuous contacts along the extended groove. The free S9.6 antibody structure was nearly identical to that of the hybrid-bound structure, suggesting conformational rigidification of the CDRs prior to binding20. Such relatively rigid paratopes, common for affinity-matured antibodies, are expected to be less adaptable towards significant variations in the minor groove geometry and chemical environment due to nucleotide composition, skew, and duplex bending. Therefore, the groove-tracking modality is likely intrinsically less tolerant towards divergent duplex sequences, geometries and local deformations. This notion explains the divergent sequence preferences observed for different dsRNA antibodies, where J2 and J5 preferred mixed composition while K1 exclusively bound poly(rI)-poly(rC)15,64. By contrast, axis-tracking, ridge-spanning intracellular domains such as dsRBMs may be more tolerant of groove width variations by focusing on the recognition of the phosphodiester backbone and 2′-OHs and deploying flexibly tethered repeat domains that jointly conform to long, deformable dsRNAs51.

Besides the differences in overall topology, antibodies and intracellular proteins also favor distinct types of chemical contacts mediated by dissimilar amino acid types. Both J2 and S9.6 employ extensive networks of aromatic residues (e.g., Tyr and Trp) to bind the minor groove hydrophobic features (portions of nucleobases and riboses) through van der Waals interactions. This is evidenced by the functional sufficiency of Phe side chains in place of Tyr at LC Y31, HC Y50 and Y52 positions (Fig. 3c), and the essential HC Y101 position of the S9.6 antibody20. For comparison, multiple synthetic antibodies against structured RNAs discovered through phage display also extensively leverage non-polar interactions in addition to polar contacts52–58. By contrast, dsRBMs primarily utilize strategically positioned polar residues (Lys, Arg, His, Gln, Asn, Glu) to bind backbone chemical groups, including 2′-OHs and phosphate oxygens49,59,60. These two distinct approaches to dsRNA recognition likely evolved independently to better suit the local chemical environments of the interfaces and the characteristics of the protein folds being employed.

Methods
Sequences and expression plasmids for J2 IgG and J2-Fab
The protein sequences for J2-IgG HC and LC were derived from a previous report68. The sequences of the J2 antibody from the hybridoma cells were confirmed using LC-MS/MS. The DNA sequences for J2-IgG HC, J2-Fab HC and J2-IgG LC were codon-optimized for expression in CHO cells and synthesized as gBlocks (Integrated DNA Technologies, Coralville, IA). The HC-IgG sequence was extended at the 3′ end to encode a GGG linker followed by an octa-histidine tag (His8). The HC-Fab sequence was extended at the 3′ end to encode a sortase signal (“SoSi”, LPETGG) and followed by a hexa-histidine tag (His6). The ends of the gBlocks included XbaI (5’) and HindIII (3’) restriction sites with which the individual gBlocks were cloned into XbaI/HindIII cleaved expression vector pcDNA3.4 to generate pcDNA3.4-J2-IgG HC-TEV-His8, pcDNA3.4-J2-Fab HC-SoSi-His6 and pcDNA3.4-J2-IgG LC. Amino acid substitutions were generated using the Q5 Site-Directed Mutagenesis Kit (NEB). Plasmid sequences and mutations were confirmed by Sanger sequencing and whole plasmid sequencing (Psomagen, Rockville, MD). Amino acid sequences of the resulting J2-IgG HC, J2-Fab HC and J2-IgG LC are given below, where signal sequences (removed during secretion) are underlined.

J2-IgG HC-TEV-His8. MGWSCIILFLVATATGVHSQVQLQQSGPELVKPGASVKMSCKASGYTFANHVMHWVKQKPGQGLEWIGYIYPYNDGTKYNEKFKGKATLTSDKSSSTAYMELSSLASEDSAVYYCARGGNPAWFAYWGQGTLVTVSAAKTTAPSVYPLAPVCGDTTGSSVTLGCLVKGYFPEPVTLTWNSGSLSSGVHTFPAVLQSDLYTLSSSVTVTSSTWPSQSITCNVAHPASSTKVDKKIEPRGPTIKPCPPCKCPAPNLLGGPSVFIFPPKIKDVLMISLSPIVTCVVVDVSEDDPDVQISWFVNNVEVHTAQTQTHREDYNSTLRVVSALPIQHQDWMSGKEFKCKVNNKALPAPIERTISKPKGPVRAPQVYVLPPPEEEMTKKQVTLTCMVTDFMPEDIYVEWTNNGKTELNYKNTEPVLDSDGSYFMYSKLRVEKKNWVERNSYSCSVVHEGLHNHHTTKSFSRTPGKGGGHHHHHHHH.

J2-Fab HC-SoSi-His6. MGWSCIILFLVATATGVHSEVQLQQSGPELVKPGASVKMSCKASGYTFANHVMHWVKQKPGQGLEWIGYIYPYNDGTKYNEKFKGKATLTSDKSSSTAYMELSSLASEDSAVYYCARGGNPAWFAYWGQGTLVTVSAAKTTAPSVYPLAPVCGDTTGSSVTLGCLVKGYFPEPVTLTWNSGSLSSGVHTFPAVLQSDLYTLSSSVTVTSSTWPSQSITCNVAHPASSTKVDKKISALPETGGGHHHHHH.

J2-IgG LC. MGWSCIILFLVATATGVHSNIMMTQSPSSLAVSAGEKVTMSCKSSQSVLYSSNQKNYLAWYQQKPGQSPKLLIYWASTRESGVPDRFTGSGSGTDFTLTISSVQAEDLAVYYCHQYLSSYTFGGGTKLEIKRADAAPTVSIFPPSSEQLTSGGASVVCFLNNFYPKDINVKWKIDGSERQNGVLNSWTDQDSKDSTYSMSSTLTLTKDEYERHNSYTCEATHKTSTSPIVKSFNRNEC.

Expression and purification of J2-IgG and J2-Fab in ExpiCHO-S cells
The ExpiCHO Expression System kit (ThermoFisher Scientific, Waltham, MA) was used according to manufacturer-recommended protocols with modifications. Briefly, ExpiCHO-S cells were grown in ExpiCHO expression medium in plain-bottom Erlenmeyer flasks with vented screw caps at 37°C and 8% CO2 with continuous shaking at 120 rpm. ExpiCHO cells having viability >95% were transfected at a cell density of 5×106 cells/mL. Each 100-ml portion of expiCHO cells was transfected with 50 μg of each of IgG HC and IgG LC or Fab HC and IgG LC plasmids mixed with 8 mL of OptiPRO SFM and 320 μL of ExpiFectamine CHO reagent. These were combined and incubated for 1–5 min before addition to the cells. Following the “MaxTiter” protocol, 600 μl ExpiCHO Enhancer and 16 ml of ExpiCHO Feed were added 24 h post-transfection. The cells were moved to an incubator shaker kept at 32°C and 5% CO2, 120 rpm. An additional 16 ml ExpiCHO Feed was added on day 5, and the culture was harvested on days 10-12.

J2-IgG and J2-Fab proteins were purified from culture supernatant using their C-terminal histidine tags. Following centrifugation to remove the expiCHO cells, the supernatant was incubated batchwise with gentle rolling at 5°C for at least 1 h with 5% (w/v) Ni-NTA agarose beads (Qiagen). This amount of Ni-NTA agarose exceeds that normally used because materials in the medium interfere, possibly by chelation of the nickel. The agarose beads were collected on a porous funnel or column, washed with 30 mM Imidazole, 200 mM NaCl, pH 7.0, and the Fab proteins were then eluted with 300 mM Imidazole, pH 7.0. The purified proteins were dialyzed in 10 mM Tris (pH 7.2) and 100 mM NaCl and further purified by size-exclusion chromatography on a Superdex 200 column (Cytiva). Protein purity was assessed by SDS-PAGE on 4–20% Tris-Glycine polyacrylamide gels (Invitrogen). For reduced samples, the J2-IgG and J2-Fab proteins were treated with 1 mM dithiothreitol (DTT). To verify the presence of intended mutations, all Fab proteins were reduced by DTT and analyzed by mass spectrometry.

RNA preparation
tRNA used in biophysical analyses was prepared by T7 RNA polymerase in vitro transcription using PCR-generated templates69–71. To reduce the N+1 extension activity of T7 RNAP, two consecutive 2′-O-methyl modifications were introduced on the 5′ ends of the template strands. RNAs were purified by denaturing gel electrophoresis in Tris-borate EDTA buffer on 10% polyacrylamide (29:1 acrylamide:bisacrylamide) gels containing 8 M urea. RNAs were eluted by overnight crush and soak in 300 mM NaOAc, pH 5.2, and 1 mM EDTA at 4°C, washed with 1 M KCl using Amicon centrifugation filters, followed by two washes with DEPC-treated water. The concentrated RNAs were filtered and stored at −20°C until use. Oligonucleotides used for BLI and fluorescence polarization assays were purchased from Integrated DNA Technologies or Horizon Discovery Dharmacon and used without further purification.

Bimolecular fluorescence polarization (FP) analysis
For bimolecular FP assays, 5 nM 3′ FAM-labeled Adenovirus VA-I RNA (Supplementary Fig. 2) was titrated with increasing amounts of J2 IgG in a buffer consisting of 25 mM Tris-HCl (pH 7.5), 100 mM KCl, and 2 mM MgCl2 in a 96-well plate at 21°C. FP values were measured in triplicate using a BMG CLARIOstar Plus microplate reader with excitation at 482 nm, emission at 530–540 nm, and LP (long pass) 504 dichroic filter setting. Changes in FP as a function of J2 IgG concentrations were fit with the following equation to determine the apparent dissociation constant Kd using GraphPad Prism 10.

Y=Bmax×X=(Kd+X): (1)

Competition fluorescence polarization (FP) analysis
For competition FP assays, 10 nM 3′ FAM-labeled Adenovirus VA-I RNA was first mixed with 160 nM J2 IgG and kept on ice for 10 min to form a complex. Competing dsRNAs were heated at 90°C for 3 min in 25 mM Tris-HCl (pH 7.5) and 100 mM KCl, and rapidly cooled over 2 min, followed by the addition of 2 mM MgCl2. The nucleic acids were then serially diluted, and 20 µL of each diluted solution was combined with 20 µL of complex solution in a buffer composed of 25 mM Tris-HCl (pH 7.5), 100 mM KCl, and 2 mM MgCl2 in a 96-well plate, and incubated at 21°C for 10 min. FP values were recorded using the same settings as for the bimolecular binding measurements above. Changes in FP as a function of competitor concentrations were fit to the following model to determine the half-maximal inhibitory concentration (IC50):

Y=Bottom+(Top−Bottom)=(1+10(X−LogIC50)) (2)

Biolayer Interferometry (BLI)
Gator Bio Protein A (ProA) probes were first hydrated for 10 min in a BLI assay buffer composed of 25 mM Tris-HCl (pH 7.5), 200 mM KCl, and 2 mM MgCl2. Assays were performed in triplicate using flat black-bottom 96-well plates, with each well consisting of 200 µL of buffer, ligand, or analyte solution arranged by column. Columns 1 and 3 contained BLI assay buffer for baseline measurements; column 2 contained the ligand solution (30 µg/mL of J2 IgG) for probe loading; column 4 contained the analyte solution (nucleic acids). The analytes were serially diluted by a factor of two into the wells of column 4 with a starting concentration of 1 µM. The sensors were systematically transferred through a 5-step protocol: column 1 for baseline, column 2 for ligand loading, column 3 for second baseline, column 4 for analyte association and dissociation back in column 3. Each step was performed at 25°C for 120 s with an orbital shaking speed of 1000 rpm. Data analyses and global fits were conducted using the Gator Bio software provided by the manufacturer. For each sensorgram set, fits to the homogeneous and heterogeneous ligand models were performed and compared. Essentially, all dsRNA data fit the heterogeneous ligand model only, while the VA-I RNA data fit the homogeneous ligand model. Reduced orbital speeds of 200, 400, and 800 rpm were tested with a 30-bp dsRNA, which produced similar sensorgrams as 1000 rpm and could only be fit with the heterogeneous ligand model. Due to the steep dependency of dsRNA binding strength to J2 IgG on ionic strength, KCl concentrations were adjusted (noted in figure legends where applicable) so that the sensorgrams capture sufficient association and dissociation signal. Kinetic parameters (kon, koff), kinetics-derived Kd (koff/kon), and steady-state Kd values are in Supplementary Table 1. Kd (steady state) was derived by curve-fitting sensor responses (nm) as functions of dsRNA concentrations. Global fits using the heterogeneous ligand model suggest an approximately equal split between the two observed binding components for dsRNA. Only the parameters of the stable, concentration-dependent component were reported, as implemented in the manufacturer’s provided software. The parameters for the other component were generally unstable, out of range, and could not be accurately determined. They may be associated with nonspecific surface phenomena not associated with the productive J2-dsRNA interaction under study. Kds derived from steady-state analyses generally match those derived from kinetic analyses, which indicate reliable measurements in both modalities (Supplementary Table 1).

Temperature-scanning circular dichroism (CD)
CD experiments were performed using 10 µM of nucleic acids in 25 mM Tris-HCl, pH 7.5, 25 mM NaCl, and 2 mM EDTA on an Applied Photophysics Chirascan Q100 spectropolarimeter. The CD spectra were recorded from 195 to 320 nm using a 1 mm path length cell. The temperature range was from 20 to 97°C with a step size of 1°C min−1. The CD data were analyzed using the Global3 software provided with the instrument by Applied Photophysics. Melting temperatures (Tms) were determined by global fits of all the spectra across the temperature range.

Crystallization and structure determination of the J2 Fab-dsRNA complex
The complex was reconstituted at 6 mg/mL by mixing the J2 Fab with a 24-bp dsRNA in 25 mM Tris-HCl, pH 7.5, 50 mM NaCl and 1 mM MgCl2. The dsRNA contains a terminal AxA mismatch. The sequences were 5´-GUUGUAAAGAAGGUCAAUAUUGUA-3´ (Chain E) and 5´-AACAAUAUUGACCUUCUUUACAAC-3´ (Chain F). Crystals were obtained by sitting drop vapor diffusion and grew over two weeks at 20°C, by mixing 1:1 the complex with a reservoir solution composed of 0.15 M malic acid, pH 7, 0.1 M imidazole and 22% w/v PEG MME 550. Crystals were cryoprotected in the same reservoir solution supplemented with 30% ethylene glycol and vitrified at 100 K. Diffraction data were collected at SER-CAT beamline 22-ID at the Advanced Photon Source (APS). X-ray diffraction data were indexed, integrated, and scaled using XDS72. Phase information was obtained by molecular replacement using Phaser73 and the S9.6 Fab structure (PDB: 7TQB) and an 18-bp dsRNA generated in Coot74 as search models. Iterative rounds of model building were performed in Coot74 and refined using Phenix.Refine75. X-ray crystallographic data collection and refinement statistics are summarized in Table 1.

Size-exclusion chromatography coupled to multi-angle light scattering (SEC-MALS)
To measure the stoichiometry of J2 antibody binding to dsRNA, 40 μM of J2 Fab was mixed with 40 μM of 27-bp dsRNA for 10 min at room temperature in a buffer consisting of 25 mM Tris-HCl, pH 7.5, 50 mM NaCl and 1 mM MgCl2, prior to injection onto a Superdex 200 Increase column (Cytiva). The column was equilibrated in 25 mM Tris-HCl, pH 7.5, 50 mM NaCl and 1 mM MgCl2 and connected to an Agilent HPLC system. The HPLC system was coupled to a DAWN HELEOS II detector equipped with a quasi-elastic light scattering module and an Optilab T-rEX refractometer (Wyatt Technology). Data were analyzed using the ASTRA 7.3 software (Wyatt Technology Europe).

Sedimentation velocity analytical ultracentrifugation (AUC). Sedimentation velocity experiments were carried out at 50,000 rpm (201,600 x g at 7.20 cm) and 20°C on a Beckman Coulter ProteomeLab XL-I analytical ultracentrifuge and An50-Ti rotor following standard protocols76. Samples of 5 µM J2 Fab, 5 µM 23 bp dsRNA and their mixtures were prepared for analytical ultracentrifugation in 50 mM NaCl, 25 mM Tris-HCl, pH 7.5, and 1 mM MgCl2. Samples of 1 µM and 2 µM J2 IgG, 1 µM 30 bp dsRNA (17% GC), and their mixtures were prepared for analytical ultracentrifugation in 100 mM KCl, 50 mM Tris-HCl, pH 8.0, and 2 mM MgCl2. Sedimentation data were analyzed in SEDFIT77 in terms of a continuous c(s) distribution of sedimenting species. The solution density, viscosity, and protein partial specific volumes were calculated based on their composition in SEDNTERP78. A partial specific volume of 0.50 cm3 g−1 was used for RNA. Additivity rules were used to determine the partial specific volumes for the complexes. Because of differences in the partial specific volumes, experimental sedimentation coefficients present the c(s) distributions.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript by C. Bou Nader et al. provides a comprehensive and thorough analysis of the J2 monoclonal antibody which is used to detect endogenous and exogenous dsRNA. The study established J2 as a double stranded RNA (dsRNA) specific antibody that discriminates against other single stranded nucleotides and nucleotides of mixed composition. The mechanism of epitope binding by J2 antibody was revealed through binding experiments with various lengths of dsRNA and the co-crystal structure of the J2 antibody fragment with a dsRNA. The study expands the utility of J2 antibody as a dsRNA detection tool by determining the minimum required length of dsRNA for antibody binding while also highlighting the limitations of the tool by showing its strong preference for low GC content dsRNA. The study increases the reliability of dsRNA detection by J2 antibody.\n\nThe co-reviewers do not have any major comments on the manuscript but believe that the manuscript will benefit from incorporating the following suggestions:\n1) Considering that the binding data for the Fab are more easily interpreted than the more complex data with the antibody, the authors might consider presenting the Fab characterization first. This would help to build confidence in the methods before the more complex data are considered.\n2) In the extended data table 1, the legend reads “Kd (kinetics) was calculated from kon/koff” this should be changed to “Kd (kinetics) was calculated from koff/kon.”\n3) In the result section, the co-crystal structure of a J2 Fab bound to 23-bp dsRNA (line 177) says, “The structure captures two J2 Fabs bound to the same 23-bp dsRNA in crystallo”. The electron density and the crystallographic model shows that the dsRNA bound to the Fabs is only 17/18 nt long. The result section should be modified to indicate that.\n4) The method section for RNA preparation mentioned that the oligonucleotides were obtained from IDT and Dharmacon and were used without further purification. Did the authors verify the purity of the material? How might the purity of the material impact the BLI and FP experiments?\n5) The BLI and CD experiments were performed at 2mM Mg++ but other experiments were performed at 1mM Mg++ concentration. Is there a significant impact on the helical nature of the nucleotides because of the difference in the amount of Mg++ ions in solution?\n6) In the extended data Table 1, please correct the number of significant figures for mutant HC Y50F.\n7) According to the extended data table the kon and koff for WT 30mer dsRNA have substantial errors associated with the measurements. If possible, a more reliable measurement of kinetic parameters would be suitable.\n8) Considering this paper is focused on recognition of RNA by Fab/antibody, the authors should be made aware of seven known RNA-Fab/antibody interfaces involving six different Fabs. Proc Natl Acad Sci U S A. 2008;105(1):82-7; Nat Struct Mol Biol. 2011;18(1):100-6; J Mol Biol. 2016;428(20):4100-14; Nat Commun. 2019;10(1):3629; ACS Chem Biol. 2020;15(1):205-16; Nat Chem Biol. 2022;18(4):376-84.", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "This manuscript presents biophysical and structural analyses of the J2 antibody, a widely used tool for detecting dsRNA. The structure offers insights into the molecular basis of dsRNA recognition—clarifying how J2 distinguishes dsRNA from dsDNA, DNA:RNA hybrids and ssRNA. Given concerns about J2’s specificity in complex samples, the structural data are valuable for interpreting potential cross-reactivity and guiding future antibody optimization.\n\nWhile the work fills a knowledge gap, its impact is modest. The authors could strengthen the study by using the structural information to propose or test improved J2 variants with enhanced affinity or specificity.\n\nBelow are several points to address:\n1. Potential for antibody optimization:\nThe authors report that J2 exhibits moderate affinity (~32nM for VA-I RNA and ~17nM for 50-bp dsRNA), which may limit its sensitivity in detecting endogenous dsRNA under pathological conditions. Researchers would benefit from insights into how J2 could be engineered for improved binding affinity.\n\nThe authors can analyze the dsRNA–J2-Fab interface more thoroughly and propose mutations that may stabilize the interaction. For example, in Fig. 4d, S33R nearly abolishes RNA binding, presumably due to steric clash. A substitution like S33K may retain a positive charge but with reduced bulk. Similarly, Y38 and Y101 likely participate in π–π or hydrophobic interactions. A Y101W and/or Y38W mutation could potentially strengthen stacking interactions and improve affinity.\n\nThe manuscript would be more compelling if it included rational mutagenesis strategies, guided by the structure, to create J2 variants with improved affinity to significantly enhance the impact of the work for tool and therapeutic development.\n2. Affinity for poly(I:C)\nFormer studies mentioned J2 binds polyIC with approximately 10-fold lower affinity than it binds other dsRNAs. Since polyIC is widely used as a dsRNA mimic in both experimental and clinical settings (e.g., adjuvants), this observation needs further discussion. Can the authors elaborate on the structural or sequence-based reasons for this lower affinity? Addressing this would help researchers interpret J2 binding data in the context of poly(I:C) stimulation experiments.\n3. A30P mutation and 3₁₀ Helix Integrity:\nThe A30P mutation disrupts the short 3₁₀ helix, but it also increases local hydrophobicity. The authors suggest this might compensate for the loss of secondary structure. To dissect these effects more clearly, they could test an A30G variant, which lacks the added hydrophobicity and destabilizes helical structures as well. This would better determine whether the helix is structurally required for RNA binding.\n4. Stoichiometry of J2 Fab vs. IgG-dsRNA complex:\nDepending on the assay, the reported binding stoichiometries vary between 2:1 and 1:1, which is confusing. Notably, the stoichiometry of IgG:dsRNA binding does not necessarily correspond to half that of Fab:dsRNA, even though each IgG has 2 arms of Fab. Based on the conformation of Fab:dsRNA interaction, can an IgG molecule simultaneously engage both of its Fab arms with the same dsRNA molecule? Alternatively, does it predominantly crossbridge two separate dsRNA molecules, effectively resulting in a 2:2 stoichiometry? Such crosslinking could lead to the formation of higher-order assemblies, and dsRNA length-dependent aggregate formation (as longer dsRNA would have higher propensity to form multi-dsRNA bridged structures), which would significantly complicate interpretation of the binding stoichiometry based on fluorescence polarization (FP) measurements.\n\nCan the authors clarify these issues? Specifically, do they believe crossbridging has contributed to the reported stoichiometries and the apparent length selectivity of J2 binding? A direct comparison of dsRNA length sensitivity between J2 IgG and Fab would help address this point.\n5. Comparison with other dsRNA antibodies\nOne additional aspect I would encourage the authors to consider is the utility of AlphaFold 3. Has the AlphaFold 3 -predicted structure of the J2-dsRNA complex been compared to the crystallographic structure? If so, how well do they agree? If AlphaFold 3 indeed reproduces the observed structure well, can the authors use structural prediction to model other dsRNA antibodies, such as J5, K1, or 9D5, which exhibit distinct sequence preferences (as noted in the manuscript, e.g., J2 and J5 prefer mixed base compositions, while K1 exclusively binds poly(I:C)).\n\nCould structural modeling provide a rationale for these observed differences in sequence preference? For example, do differences in paratope orientation, groove access, or charge distribution explain K1’s selective recognition of poly(I:C)?\nFurthermore, if AF3 or mutational modeling can reveal structure-function relationships across these antibodies, it may even be possible to rationally engineer a universal dsRNA antibody with improved tolerance to GC skew or secondary structure distortion and overcoming limitations such as those noted in the manuscript (e.g., “J2 exhibits substantial sensitivity to nucleotide composition and skew”). This could significantly enhance the manuscript’s impact beyond structural characterization.", "reviewer_4": "The J2 antibody, which is derived from a mouse (IgG2a isotype), is commonly used in biological research to map and quantify double-stranded RNA (dsRNA), including in studies of virology, innate immune responses, and RNA biology. It is used in various applications, including ELISA, immunofluorescence, immunoprecipitation, dot blotting, and immunohistochemistry, and it is effective in both cultured cells and fixed tissue samples. J2 detects endogenous dsRNA, as well as dsRNA from viral intermediates, such as the hepatitis C and dengue viruses. Due to its widespread use, a detailed characterization of what the antibody detects and how it does so is of general interest.\n\nThe authors begin with a detailed biochemical characterization using biolayer interferometry. The data are compatible with a simple Kd-based binding model. The data confirm the field's consensus that J2 is highly specific to dsRNA. They also show that IC50 values decrease (affinity increases) as dsRNA length increases. While this result is likely what most biologists working with the antibody would have expected, it is unclear how it is to be reconciled with the footprint of J2 on the dsRNA, which corresponds to a much shorter region (see Figures 2 and 5).\n\nThe authors then proceed to a structural characterization (Figures 2 and 3). Towards the end of the work, the authors explore the dependence of binding on GC-content of the dsRNA, and they compare antibody strategies with the strategies of other (mostly immune related) proteins for dsRNA recognition. The authors argue that these strategies are different, and provide a rationale for the adoption of different strategies in terms of the relevant ionic milieus.\n\nQuestions and comments on merit:\nHow can the data on the dependence of IC50 values on the length of dsRNA be reconciled with the J2 footprint on dsRNA?\nIs the length dependence merely a result of longer dsRNA being able to bind to more than one copy of J2? In BLI experiments, a 2:1 stoichiometry is used for all analyses, irrespective of dsRNA length. Assuming this, it appears that the IC₅₀ decreases, i.e., affinity increases, with increasing dsRNA length. However, the authors report counterexamples to the 2:1 model for the Adenovirus Associated RNA-I. I suspect the authors are on the wrong track altogether with the concept of dsRNA-length-independent stoichiometry to explain binding.\n\nInstead, they should consider whether apparent increased affinity is simply a result of more J2 molecules binding to longer dsRNA while the affinity of each J2 molecule remains constant (provided there is enough dsRNA for the footprint). As far as I can tell, this model could explain the plateauing of the IC50 above 40 bp dsRNA because constant increases in dsRNA length increase the number of available binding sites by smaller and smaller multiplicative factors. Would this model be sufficient to explain the apparent increase in affinity?\n\nIf the \"constant affinity per J2/length-dependent number of J2 binding sites on dsRNA\" model cannot explain the apparent changes in IC₅₀, could the apparent increase in affinity be a consequence of favorable interactions between two or more J2 molecules bound to one longer dsRNA target? This could be tested by comparing a target with alternating dsRNA/dsDNA regions (so that bound J2 molecules cannot interact) with a target with blocked regions (so that J2 molecules can interact).\n\ndsRNA cannot adopt a backbone conformation like \"wet\" (B-form) DNA, but conversely, DNA can adopt a dry (A-form) structure that has similar backbone parameters to dsRNA. What hinders it from doing so? I doubt that the free energy cost for the dsDNA B- to A-form conversion is high enough that it could be explain the affinity difference. This suggests that 2'-OH groups of the dsRNA are also directly recognized. Is this the case, and how much -based on an analysis of the structure- are 2'-OH group interactions expected to contribute to the affinity difference of J2 binding to dsRNA and dsDNA?\n\nI like the argument that different ionic milieus call for different strategies of dsRNA recognition, due to enhancing effect of salt on hydrophobic interaction, and the screening effect on charge-charge interactions. Unfortunately, the authors are vague about the exact conditions. Can it be reconstructed from the way J2 made in the first place what ionic conditions J2 was \"naturally\" optimized for? This would make the comparison with the intracellular conditions more concrete, and the conceptually nice idea more convincing.\n\nPresentation:\nIt has become customary to sweep the crystallographic details of work as in the present study completely under the table. I am not advocating for a full crystallographic table in the main text as in the past. But for manuscripts that are mainly about structure, a minimal crystallographic table with the key information (what space group, how many molecules in the asymmetric unit, what resolution, refined to what Rfree) should be present in the main text for readers to have a rough idea of the quality of the structure. Also, I was unable to find a full crystallographic table in the Suppl. and could only assess the quality of the structure based on the PDB validation report. A full crystallographic table should still be included in the Suppl. To the authors credit, the data in the table in the validation report are good (for the experimental resolution), there is no need for additional structure refinement."}, "author_response": "Point-by-point responses to reviewer comments:\nReviewer #1 (Remarks to the Author):\nThe manuscript by C. Bou Nader et al. provides a comprehensive and thorough analysis of the J2\nmonoclonal antibody which is used to detect endogenous and exogenous dsRNA. The study\nestablished J2 as a double stranded RNA (dsRNA) specific antibody that discriminates against\nother single stranded nucleotides and nucleotides of mixed composition. The mechanism of\nepitope binding by J2 antibody was revealed through binding experiments with various lengths\nof dsRNA and the co-crystal structure of the J2 antibody fragment with a dsRNA. The study\nexpands the utility of J2 antibody as a dsRNA detection tool by determining the minimum\nrequired length of dsRNA for antibody binding while also highlighting the limitations of the tool\nby showing its strong preference for low GC content dsRNA. The study increases the reliability\nof dsRNA detection by J2 antibody.\nThe co-reviewers do not have any major comments on the manuscript but believe that the\nmanuscript will benefit from incorporating the following suggestions:\nA: We thank the reviewer for their positive assessments and helpful suggestions.\n1) Considering that the binding data for the Fab are more easily interpreted than the more\ncomplex data with the antibody, the authors might consider presenting the Fab characterization\nfirst. This would help to build confidence in the methods before the more complex data are\nconsidered.\nA: We appreciate the suggestion. Indeed, the characterizations started with the Fab (Fig. 1b and\nS1). We then intended to focus more on the IgG over the Fab, as the IgG form is what the\nresearch community nearly exclusively use, instead of the Fab. To reduce the apparent\ncomplexity and improve the clarity of the IgG BLI data, we have reworked the descriptions in\nthe text, figures, and methods. The point of confusion stems from the misnomer of “2:1 model”\nused by Gator Bio to describe 1:1 binding to heterogeneous immobilized ligands (J2). However,\n“2:1 model” is almost always intuitively interpreted to mean stoichiometry, which is not the case\nhere. We have substantially clarified this point of confusion throughout the manuscript, and\neliminated the use of “2:1 model” and only refer to it as the “heterogeneous ligand” model. The\n“1:1” model is renamed “homogeneous ligand” model. Through direct consultations and a virtual\nmeeting with Gator Bio technical team we have communicated these software and renaming\nsuggestions to the manufacturer.\n2) In the extended data table 1, the legend reads “Kd (kinetics) was calculated from kon/koff”\nthis should be changed to “Kd (kinetics) was calculated from koff/kon.”\nA: We thank the reviewer for catching this error, which has been corrected.\n3) In the result section, the co-crystal structure of a J2 Fab bound to 23-bp dsRNA (line 177)\nsays, “The structure captures two J2 Fabs bound to the same 23-bp dsRNA in crystallo”. The\nelectron density and the crystallographic model shows that the dsRNA bound to the Fabs is only\n17/18 nt long. The result section should be modified to indicate that.\nA: We corrected and clarified this as suggested. Although the 23-bp dsRNA was used in the\nexperiment, the terminal regions only have weak densities suggesting conformational flexibility.\nWe now state:\n“The structure captured two J2 Fabs bound to the opposite sides of a central, 17-bp portion of\nthe same dsRNA in crystallo, via nearly identical interfaces (all-atom RMSD ~0.6 Å, Fig. 2a, b,\nd, Supplementary Fig. 5-6). While the central 17-bp dsRNA segment exhibited well-defined\nelectron density, both flanking 3-bp terminal regions had only weak or no density. This finding is\nconsistent with the notion that terminal regions of dsRNAs such as HIV-1 TAR exhibit substantial\nconformational flexibility and engage in transient excursions26,27.”\n4) The method section for RNA preparation mentioned that the oligonucleotides were obtained\nfrom IDT and Dharmacon and were used without further purification. Did the authors verify the\npurity of the material? How might the purity of the material impact the BLI and FP experiments?\nA: The reviewer raised a valid consideration for oligo purity and quality. We have inspected all\nthe HPLC mass spec analyses performed and provided by the manufacturers, which suggest a\nhigh degree of chemical purity and agreement with the expected molecular masses. Please see\nexamples below, including the longest 50-nt oligos.\n5) The BLI and CD experiments were performed at 2mM Mg++ but other experiments were\nperformed at 1mM Mg++ concentration. Is there a significant impact on the helical nature of the\nnucleotides because of the difference in the amount of Mg++ ions in solution?\nA: Previous NMR and MD analyses suggested that Mg2+ ions strengthen helical stacking by\nneutralizing the negative charges of the phosphate backbone, which could impact the helical\nstructure of various dsRNAs (e.g. PMIDs: 17325014, 12798678, 29718375). To address this\nquestion more explicitly, we performed additional temperature-scanning CD analyses of three\nrepresentative dsRNA of low (0%), mid (47%), and high (100%) GC contents, at 0, 1, and 2 mM\nMg2+. In all cases the CD spectra in 1 and 2 mM Mg2+ are nearly identical (Figure below),\nsuggesting that within this range of Mg2+ concentration, the helical structure of the dsRNA under\nstudy remains similar, thus permitting comparison and correlation of data collected at 1 mM or\n2mM Mg2+. By contrast, the CD spectra in the absence of Mg2+ show detectable, but relatively\nminor differences. This Mg2+ effect is more pronounced for low- and mid-GC% dsRNAs than\nthe high-GC% dsRNA. This is likely due to the high-GC dsRNA already exhibiting stable A-\nform duplex structures without Mg2+. We further confirmed that where measurable, increasing\nMg2+ concentration increased the T of the dsRNAs, consistent with known effects of Mg2+ on\nm\ndsRNA duplex stability. These new data have been incorporated into a new Supplementary Fig.\n14 that addresses Mg2+ effects on dsRNA geometry. We now state in a new main text section:\n“Finally, we examined how Mg2+ may modulate the dsRNA helical structure46-48 and indirectly\naffect J2 interactions. We collected temperature-scanning CD spectra of 30-bp dsRNAs of low\n(0%), mid (47%), and high (100%) GC contents, at 0, 1, and 2 mM Mg2+. As expected, Mg2+\nstabilized the A-form helical geometry of low- and mid-GC dsRNAs and raised their T s, while\nm\nexerting minimal effects on the high-GC dsRNA that is already stable without Mg2+\n(Supplementary Fig. 14). There was little difference in the CD spectra collected at 1 or 2 mM\nMg2+. Together, these data suggest that RNA topology (e.g. poly(rI)-poly(rC)), dsRNA length,\nand solute conditions (including monovalent and divalent cations such as Mg2+) likely\nadditionally impact J2 interactions.”\n[Supplementary Fig. 14]\n6) In the extended data Table 1, please correct the number of significant figures for mutant HC\nY50F.\nA: Corrected as suggested.\n7) According to the extended data table the kon and koff for WT 30mer dsRNA have substantial\nerrors associated with the measurements. If possible, a more reliable measurement of kinetic\nparameters would be suitable.\nA: As suggested, we have repeated these measurements, which have substantially reduced the\nmeasurement errors and uncertainties.\n8) Considering this paper is focused on recognition of RNA by Fab/antibody, the authors should\nbe made aware of seven known RNA-Fab/antibody interfaces involving six different Fabs. Proc\nNatl Acad Sci U S A. 2008;105(1):82-7; Nat Struct Mol Biol. 2011;18(1):100-6; J Mol Biol.\n2016;428(20):4100-14; Nat Commun. 2019;10(1):3629; ACS Chem Biol. 2020;15(1):205-16;\nNat Chem Biol. 2022;18(4):376-84.\nA: Added all these relevant references as suggested and new text near the end of the Results\nsection. We now state:\n“For comparison, multiple synthetic antibodies against structured RNAs discovered through\nphage display also extensively leverage non-polar interactions in addition to polar contacts39-45”\nReviewer #2 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is\npart of the Nature Communications initiative to facilitate training in peer review and to provide\nappropriate recognition for Early Career Researchers who co-review manuscripts.\nA: We thank the reviewer for supporting the early career researchers.\nReviewer #3 (Remarks to the Author):\nThis manuscript presents biophysical and structural analyses of the J2 antibody, a widely used\ntool for detecting dsRNA. The structure offers insights into the molecular basis of dsRNA\nrecognition—clarifying how J2 distinguishes dsRNA from dsDNA, DNA:RNA hybrids and\nssRNA. Given concerns about J2’s specificity in complex samples, the structural data are\nvaluable for interpreting potential cross-reactivity and guiding future antibody optimization.\nWhile the work fills a knowledge gap, its impact is modest. The authors could strengthen the\nstudy by using the structural information to propose or test improved J2 variants with enhanced\naffinity or specificity.\nA: We thank the reviewer for their overall favorable assessments and helpful suggestions.\nBelow are several points to address:\n1. Potential for antibody optimization:\nThe authors report that J2 exhibits moderate affinity (~32nM for VA-I RNA and ~17nM for 50-\nbp dsRNA), which may limit its sensitivity in detecting endogenous dsRNA under pathological\nconditions. Researchers would benefit from insights into how J2 could be engineered for\nimproved binding affinity.\nThe authors can analyze the dsRNA–J2-Fab interface more thoroughly and propose mutations\nthat may stabilize the interaction. For example, in Fig. 4d, S33R nearly abolishes RNA binding,\npresumably due to steric clash. A substitution like S33K may retain a positive charge but with\nreduced bulk. Similarly, Y38 and Y101 likely participate in π–π or hydrophobic interactions. A\nY101W and/or Y38W mutation could potentially strengthen stacking interactions and improve\naffinity.\nThe manuscript would be more compelling if it included rational mutagenesis strategies, guided\nby the structure, to create J2 variants with improved affinity to significantly enhance the impact\nof the work for tool and therapeutic development.\nA: We appreciate the insightful and specific suggestions from the reviewer. Indeed our structure\nand results have indicated potential pathways toward improving it. However, we believe that\nsystemic optimization and improvement of the J2 antibody warrants a dedicated future study, and\nis beyond the intent and scope of this first manuscript. Our limited scope has been focused on\nquantitatively defining J2’s nucleic acid-binding properties, revealing its biases and limitations,\nand elucidating its basic mechanisms of recognition, all of which will lay the groundwork for\neffective improvements in the future.\nSecond, regarding the proposed new mutants, given the presumed steric clash from the flexible\nside chain of Arg and considering its numerous rotamers, it is unclear to us that a Lys at S33\nwould necessarily fare much better. For the suggested Y101W and Y38W substitutions we were\nconcerned that the substantial bulk of their side chains may disrupt the intimate, form-fitting\ninterfaces with the minor groove and outweigh any potential gain in increased stacking strength.\nThird, in our previous S9.6 antibody study (Bou-Nader 2022 Nat Commun), we did attempt to\nimprove the antibody by more extensive rational design, which did not yield any improvements.\nIn that study we substituted Y54 which makes a key sugar-pi interaction responsible for\nselectivity of hybrids over dsRNA, individually with 11 other side chains. Unfortunately, none of\nthe variants exhibited improved hybrid/dsRNA selectivity, including Y54F, Y54W, Y54H,\nY54R, etc. Despite being imperfect, Tyr is already the best residue at this location, in its specific\nsequence context. Mirroring that study, our limited trials of structure-guided rational design here\nwith S33R and N101R in J2 also failed to improve the antibody. The lesson we have gathered\nfrom both studies is that simple, structure-guided engineering of single side chains in antibody\nCDRs seems to have a low probability of success, probably due to the extremely limited\nsampling of the vast sequence space. By comparison, the initial creation of these antibodies\nthrough V(D)J recombination and somatic hypermutation had already sampled ~5×10³–7×10⁴\nCDR variants. This might partially explain the challenges we have encountered in trying to\nimprove these antibodies through simple point mutations. To achieve meaningful improvements\nthat outperform the naturally selected antibodies, we believe that multiple residues and the length\nof the CDR loops need be systematically mutated and varied, screened, and selected towards the\ndesired traits. AI tools that can rapidly sample large sequence space such as AlphaFold 3, in\ncombination with our experimental complex structure, may assist in a future virtual screening\nstudy.\n2. Affinity for poly(I:C)\nFormer studies mentioned J2 binds polyIC with approximately 10-fold lower affinity than it\nbinds other dsRNAs. Since polyIC is widely used as a dsRNA mimic in both experimental and\nclinical settings (e.g., adjuvants), this observation needs further discussion. Can the authors\nelaborate on the structural or sequence-based reasons for this lower affinity? Addressing this\nwould help researchers interpret J2 binding data in the context of poly(I:C) stimulation\nexperiments.\nA: Indeed, we agree with the reviewer that given its widespread use, it would be informative to\ntest and understand J2 interactions with polyIC, despite it being an artificial dsRNA mimic. We\nhave now performed CD and BLI analyses of polyIC binding to J2. Our CD spectra of polyIC is\nnearly identical to previously published CD data (PMID: 25184857, 30079840), showing that\npolyIC only partially resembles natural dsRNA helices (please compare to the AU-only and GC-\nonly dsRNA spectra in the Figure below). In particular, polyIC exhibits prominent 245 and 280\nnm CD peaks, suggesting distinct exciton coupling from the stacked inosine-cytosine pairs. In\nparticular, the unique peak at ~280 nm (and the absence of the 260 nm peak) indicates that free\npolyIC exhibits an unusual helical geometry, as is reminiscent of B-form dsDNA helices. This\ndistinct geometry of polyIC is likely at least partially responsible for the reduced affinity in\nprevious reports. However, accurate measurements of binding affinities to PolyIC is difficult,\ndue to its variable length from 1.5 to 8 kb and structural heterogeneity. Due to difficulty in\nannealing long, repetitive sequences of polyI and polyC, polyIC is known to contain mixed\ndsRNA and ssRNA segments due to extensive pairing register shifts and loop extrusion. To\nconfirm this we measured polyIC’s melting temperature, which was 55.7 °C in our standard\ncondition (in 25 mM Tris-HCl pH 7.5, 25 mM NaCl, and 2 mM EDTA), consistent with previous\nreports (e.g., PMID: 15600340). For comparison, perfectly paired dsRNAs between 20-30 bp\ncan reach similar T s. The low T is consistent with the notion that polyIC does not contain very\nm m\nlong contiguous dsRNA segments (e.g. >100 bp). Nonetheless, we tested polyIC binding to J2\nusing BLI, and found that polyIC does not visibly dissociate from immobilized J2. Its K could\nd\nnot be accurately determined but appears to be in pM range, lower than regular dsRNAs. This is\nlikely due to crossbridging and avidity effects, where the multiple covalently tethered, relatively\nshort dsRNA segments present in the same polyIC molecule bound multiple J2 IgGs on the\nsensor surface. We conclude that J2 is quite competent in detecting polyIC, but its precise\nbinding affinity is uncertain and likely variable, due to polyIC’s variable lengths, heterogeneous\ntopological structure, unusual helical geometry, mixed dsRNA/ssRNA composition, and\ncrossbridging effects. Notably, in a practical immunofluorescence-type of imaging experiment,\nwhere non-immobilized J2 IgG is added to cells transfected with polyIC, there would not be\ncrossbridging. Under these conditions J2 IgG may exhibit reduced binding to polyIC due to its\nmixed dsRNA and ssRNA topology and geometric differences from natural dsRNAs evidenced\nby their unique CD spectra. However, it remains difficult to carry out a fair comparison with\nbona fide dsRNAs due to the numerous aforementioned differences. We have added a new text\nsection and new Supplementary Fig. 12 (below) describing these characterizations of PolyIC-J2\ninteractions.\n[Supplementary Fig. 12]\n3. A30P mutation and 3₁₀ Helix Integrity:\nThe A30P mutation disrupts the short 3₁₀ helix, but it also increases local hydrophobicity. The\nauthors suggest this might compensate for the loss of secondary structure. To dissect these\neffects more clearly, they could test an A30G variant, which lacks the added hydrophobicity and\ndestabilizes helical structures as well. This would better determine whether the helix is\nstructurally required for RNA binding.\nA: We appreciate this thoughtful suggestion. Prolines in short helices such as 3₁₀ Helix would\nhave almost certainly removed the helical structure. Given that A30P maintained dsRNA\nbinding, it seems clear that the 3₁₀ Helix is not structurally required for RNA binding. A30G\nwould not destabilize the 3₁₀ Helix as severely as A30P, nor add hydrophobicity due to its lack of\nside chain. We don’t anticipate A30G would exert a strong effect either given the lack of effect\nof A30P, a result that may not be very helpful in further characterizing the interface.\n4. Stoichiometry of J2 Fab vs. IgG-dsRNA complex:\nDepending on the assay, the reported binding stoichiometries vary between 2:1 and 1:1, which is\nconfusing. Notably, the stoichiometry of IgG:dsRNA binding does not necessarily correspond to\nhalf that of Fab:dsRNA, even though each IgG has 2 arms of Fab. Based on the conformation of\nFab:dsRNA interaction, can an IgG molecule simultaneously engage both of its Fab arms with\nthe same dsRNA molecule? Alternatively, does it predominantly crossbridge two separate\ndsRNA molecules, effectively resulting in a 2:2 stoichiometry? Such crosslinking could lead to\nthe formation of higher-order assemblies, and dsRNA length-dependent aggregate formation (as\nlonger dsRNA would have higher propensity to form multi-dsRNA bridged structures), which\nwould significantly complicate interpretation of the binding stoichiometry based on fluorescence\npolarization (FP) measurements. Can the authors clarify these issues? Specifically, do they\nbelieve crossbridging has contributed to the reported stoichiometries and the apparent length\nselectivity of J2 binding? A direct comparison of dsRNA length sensitivity between J2 IgG and\nFab would help address this point.\nA: Indeed, this was an anticipated major point of confusion, which we tried inadequately to\npreempt. There was no 2:1 stoichiometry in this manuscript. As mentioned in responses to\nReviewer #1 point 1, the 2:1 (referring to BLI binding model) is an unfortunate misnomer used\nby Gator Bio to describe two types of ligands (heterogeneous ligand) each binding 1:1 to an\nincoming analyte, or the presence of two distinct binding modes. We had tried to explain and\nclarify this unusual use of 2:1 in the Methods but confusion was inevitable, as 2:1 nearly always\nrefers to stoichiometry. We have thus removed all mentions of 2:1, and only describe this as\n“heterogenous ligand” model.\nAs to whether the two Fab arms of the same J2 IgG can bind to the same dsRNA (<= 50 bp) in\nour experiments, we believe the answer is no, except for perhaps the newly added polyIC\nexperiment. The two Fab arms of IgG are flexibly tethered to the central constant region via\nhinges. However, the substantial bulk and rigidity of each Fab arm creates substantial steric\nhinderance restricting the relative motion between the two Fab arms. It has been estimated using\nprogrammable DNA origami-tethered epitopes, synthetic antigen arrays or viral capsid surfaces,\nthat bivalent IgG binding avidity is highest when the two epitopes were separated by 10-15 nm,\nwhich covers 36-58 bp (PMIDs: 24997862, 32561744, 30643273, 34135438). This separation,\nplus two 8-bp footprints of two Fabs, would mean that 52 -74 bp dsRNA would be minimally\nneeded to engage both Fabs of the same IgG at the same time. In reality even longer dsRNA is\nprobably required when there is no flexible ssRNA linker present between the two Fab-bound\ndsRNA segments, as the high rigidity of the dsRNA (persistent length ~250 bp) imposes certain\norientations of the Fabs, further hindering IgG bivalency. In conclusion, in our experiments\nwhere relatively short dsRNAs are used (<=50 bp), bivalent J2 IgG binding to the same dsRNA\nis probably minimal. For polyIC, we observed no dissociation from J2 IgG, which is consistent\nwith crossbridging between different Fab arms or IgGs. In addition, our AUC and SEC-MALS\nanalyses, using dsRNAs 23-30bp in length, only observed 1:1 stoichiometry between dsRNA and\nJ2 Fab/IgG (Supplementary Fig. 1). We have added clarifications, discussions, and references on\nthis point to the text.\n5. Comparison with other dsRNA antibodies\nOne additional aspect I would encourage the authors to consider is the utility of AlphaFold 3.\nHas the AlphaFold 3 -predicted structure of the J2-dsRNA complex been compared to the\ncrystallographic structure? If so, how well do they agree? Could structural modeling provide a\nrationale for these observed differences in sequence preference? For example, do differences in\nparatope orientation, groove access, or charge distribution explain K1’s selective recognition of\npoly(I:C)? Furthermore, if AF3 or mutational modeling can reveal structure-function\nrelationships across these antibodies, it may even be possible to rationally engineer a universal\ndsRNA antibody with improved tolerance to GC skew or secondary structure distortion and\novercoming limitations such as those noted in the manuscript (e.g., “J2 exhibits substantial\nsensitivity to nucleotide composition and skew”). This could significantly enhance the\nmanuscript’s impact beyond structural characterization.\nA: We agree completely with the reviewer that AF3 modeling should now be routinely\nperformed to compare with experimental structures to evaluate prediction success, give feedback\nto the prediction community, and to receive inspiration and alternative ideas. As suggested, we\nhave now performed AF3 predictions for the J2 Fab-dsRNA interface. While AF3 did a\nremarkable job predicting the free J2 Fab structure (panel a below), including the CDRs (overall\nRMSDs ~ 0.9-1.0 Å), and formation of dsRNA duplex as expected, it is completely unable to\npredict the J2-dsRNA interface (panel b). This failure is probably attributable to insufficient\ntraining from the limited PDB data on antibody-nucleic acid structures. Notably AF3 is\napparently unaware of the fact that CDR regions would be expected to interact with the dsRNA\nepitope. The stark contrast between AF3’s impressive success to predict free J2 Fab structure\nincluding the CDRs and complete failure in protein-dsRNA interfaces highlight the continued\nneed for experimental determination of protein-nucleic acids structures, especially of the\nrelatively scarce antibody-nucleic acid structures. We included these data in a new\nSupplementary Fig. 9 (below), and descriptions in the text.\n[Supplementary Fig. 9]\nNow we state:\n“Finally, we evaluated how well AlphaFold 3 can predict the J2-dsRNA interface. Interestingly,\nAlphaFold3 successfully predicts the conformation of the J2 Fab including the CDRs, achieving\na RMSD of 0.9-1.0 Å. However, it completely fails to predict the J2-dsRNA interface, placing\ndsRNA in various orientations and locations far from the CDRs (Supplementary Fig. 9). This\nfinding attests to the remarkable ability of AlphaFold 3 to predict protein structures and\nconformations including antibody CDRs but also highlights its lack of training in unconventional\nRNA-protein interfaces such as antibody-nucleic acids interfaces underrepresented in the PDB.”\nIf AlphaFold 3 indeed reproduces the observed structure well, can the authors use structural\nprediction to model other dsRNA antibodies, such as J5, K1, or 9D5, which exhibit distinct\nsequence preferences (as noted in the manuscript, e.g., J2 and J5 prefer mixed base compositions, while K1 exclusively binds poly(I:C)).\nA: As shown above AF3 completely fails to pinpoint the interface, or even come up with some\nplausible models with J2-dsRNA proximity. As far as we know, there is no amino acid sequence\navailable for any other dsRNA antibodies such as J5, K1, or 9D5. We have already shared J2\nplasmids and sequences with several research groups. In future studies, we do aim to continue to\nsequence and investigate additional nucleic acid antibodies and make them freely available to the\nresearch community.\nReviewer #4 (Remarks to the Author):\nThe J2 antibody, which is derived from a mouse (IgG2a isotype), is commonly used in biological\nresearch to map and quantify double-stranded RNA (dsRNA), including in studies of virology,\ninnate immune responses, and RNA biology. It is used in various applications, including ELISA,\nimmunofluorescence, immunoprecipitation, dot blotting, and immunohistochemistry, and it is\neffective in both cultured cells and fixed tissue samples. J2 detects endogenous dsRNA, as well\nas dsRNA from viral intermediates, such as the hepatitis C and dengue viruses. Due to its\nwidespread use, a detailed characterization of what the antibody detects and how it does so is of\ngeneral interest.\nThe authors begin with a detailed biochemical characterization using biolayer interferometry.\nThe data are compatible with a simple Kd-based binding model. The data confirm the field's\nconsensus that J2 is highly specific to dsRNA. They also show that IC50 values decrease\n(affinity increases) as dsRNA length increases. While this result is likely what most biologists\nworking with the antibody would have expected, it is unclear how it is to be reconciled with\nthe footprint of J2 on the dsRNA, which corresponds to a much shorter region (see Figures 2 and 5).\nThe authors then proceed to a structural characterization (Figures 2 and 3). Towards the end of\nthe work, the authors explore the dependence of binding on GC-content of the dsRNA, and they\ncompare antibody strategies with the strategies of other (mostly immune related) proteins for\ndsRNA recognition. The authors argue that these strategies are different, and provide a rationale\nfor the adoption of different strategies in terms of the relevant ionic milieus.\nA: We thank the reviewer for their detailed analyses, insightful syntheses, favorable assessments\nand helpful suggestions.\nQuestions and comments on merit:\nHow can the data on the dependence of IC50 values on the length of dsRNA be reconciled with\nthe J2 footprint on dsRNA? Is the length dependence merely a result of longer dsRNA being able\nto bind to more than one copy of J2? In BLI experiments, a 2:1 stoichiometry is used for all\nanalyses, irrespective of dsRNA length. Assuming this, it appears that the IC₅₀ decreases, i.e.,\naffinity increases, with increasing dsRNA length. However, the authors report counterexamples\nto the 2:1 model for the Adenovirus Associated RNA-I. I suspect the authors are on the wrong\ntrack altogether with the concept of dsRNA-length-independent stoichiometry to explain\nbinding.\nA: We do apologize for the across-the-board confusion about the intended meaning of “2:1”. The\nbinding stoichiometry is always 1:1 in this manuscript except for possibly polyIC (new\nSupplementary Fig. 12). As discussed in the responses to Reviewer #1 point 1 and Reviewer #3\npoint 4, the “2:1” refers to a heterogeneous ligand model, not binding stoichiometry. We have\nnow removed any such use of “2:1”, which is an unfortunate misnomer used by the instrument\nmanufacturer’s software. Their intention was that there were two types of ligands (immobilized\nJ2) present on the surface, or two distinct modes of binding — thus heterogeneous ligands (J2)\nreceiving a homogeneous analyte (dsRNA). We completely agree that it should not be referred as\n“2:1”, and now only refer to it as “heterogeneous ligand” model.\nThe reviewer raised an important question about the observed dsRNA length dependency of J2\n(~30 bp for near optimal binding) significantly exceeding the structural footprint (8 bp). The\nfirst, simplest explanation to consider would be stoichiometry. However, our AUC and SEC-\nMALS analyses, using dsRNAs 23-30 bp in length, only observed 1:1 stoichiometry between\ndsRNA and J2 Fab/IgG (Supplementary Fig. 1).\nA second possible explanation would be dsRNA helical geometry. We reason that as dsRNA\nincreases in length, the accumulative increase in overall stacking strength would cause the\ndsRNA to axially compress and shorten, which would in turn alter the width and geometry of the\nminor groove and impact J2 binding. We know by comparing apo and hybrid-bound S9.6\nantibody structures that the CDRs are not very flexible and preconfigured for the epitope, which\nresults from the process of affinity maturation. If J2 CDRs are preconfigured to bind a fixed\nminor groove geometry corresponding to its original immunogen, which are natural, 4.6-kb long\ndsRNAs, they might not fit potentially different helical geometry of short dsRNAs.\nTo test this hypothesis experimentally, we performed CD analyses of the dsRNAs ranging from\n6 to 50 bp in length, normalizing their concentrations so that each sample contained the same\nnumber of total nucleotides. Consistent with the hypothesis, we found that short dsRNAs that\nbind J2 poorly exhibit distinct CD spectra from the long dsRNAs that bind J2 strongly. Short\ndsRNAs exhibited reduced A-form characteristics including the valley at 210 nm, peak near 260\nnm, and increased B-form characteristics such as peaks near 275 nm. The latter is further\nconsistent with reduced stacking strength and increased helical rise found in dsDNA (~3.4 Å\ncompared to 2.9 Å of A-form dsRNA). We propose a simple explanation that short dsRNAs are\ninefficiently self-stacked and thus lack the optimal minor groove geometry found on long\ndsRNAs required for robust J2 binding. Further, dsRNA overall geometry may be additionally\naffected by terminal regions that are transiently frayed or otherwise not stably paired, as seen in\nthe J2-dsRNA co-crystal structure and the HIV-1 TAR lower stem (Bou-Nader et al., 2025, Nat.\nCommun.). We have incorporated these new data to form a new Supplementary Fig. S13, shown\nbelow, and describe them in a new text section entitled “Effects of dsRNA length and Mg2+ on\nRNA helical geometry”.\n[Supplementary Fig. 13]\nInstead, they should consider whether apparent increased affinity is simply a result of more J2\nmolecules binding to longer dsRNA while the affinity of each J2 molecule remains constant\n(provided there is enough dsRNA for the footprint). As far as I can tell, this model could explain\nthe plateauing of the IC50 above 40 bp dsRNA because constant increases in dsRNA length\nincrease the number of available binding sites by smaller and smaller multiplicative factors.\nWould this model be sufficient to explain the apparent increase in affinity?\nA: Please refer to the response to the preceding question. Based on recent studies on IgG\nbivalency and Fab spacing (please see responses to Reviewer #3, point 4), we believe 40-50 bp\ndsRNA is still too short for bivalent IgG binding to the same dsRNA. As to whether two J2 Fabs\ncan bind to opposite sides of dsRNA as seen in the crystals, we believe that is feasible. However,\nour AUC and SEC-MALS analyses using dsRNAs of 23, 27, and 30 bp did not provide evidence\nfor multiple J2 Fab or IgG binding to the same dsRNA.\nIf the \"constant affinity per J2/length-dependent number of J2 binding sites on dsRNA\" model\ncannot explain the apparent changes in IC₅₀, could the apparent increase in affinity be a\nconsequence of favorable interactions between two or more J2 molecules bound to one longer\ndsRNA target? This could be tested by comparing a target with alternating dsRNA/dsDNA\nregions (so that bound J2 molecules cannot interact) with a target with blocked regions (so that\nJ2 molecules can interact).\nA: Please refer to the responses to the two preceding questions. We appreciate the innovative\nexperimental design. Based on CD analyses in our previous S9.6 antibody study (Bou-Nader\nform intermediate helical geometry which impacted S9.6 binding. Adjacent dsRNA and dsDNA\nsegments may affect each other’s helical geometry through coaxial stacking. Such an experiment\nmay produce complex results that are difficult to interpret, due to the contiguous grooves with\npossible gradual geometric transitions rather than sharp dsDNA/dsRNA boundaries. J2-J2\ninteractions on dsRNA is certainly a possibility. We observed what appeared to be dsRNA-\ntriggered J2 IgG aggregation in some early experiments. We speculate that dsRNA-binding may\nhave exposed certain hydrophobic residues driving unscheduled protein-protein interactions.\ndsRNA cannot adopt a backbone conformation like \"wet\" (B-form) DNA, but conversely, DNA\ncan adopt a dry (A-form) structure that has similar backbone parameters to dsRNA. What\nhinders it from doing so? I doubt that the free energy cost for the dsDNA B- to A-form\nconversion is high enough that it could be explain the affinity difference. This suggests that 2'-\nOH groups of the dsRNA are also directly recognized. Is this the case, and how much -based on\nan analysis of the structure- are 2'-OH group interactions expected to contribute to the affinity\ndifference of J2 binding to dsRNA and dsDNA?\nA: Indeed, 5 2'-OH group are directly recognized by each J2 Fab (Fig. 2f), with 2 and 3 on each\nstrand of dsRNA. Mutational analyses of the 2'-OH-binding J2 residues show variable\nimportance and contributions (Fig. 3d). HC N101 touches two 2'-OHs and is among the most\nimportant residue. HC N55 binds one 2'-OH and is functionally important. By contrast, the\nremaining two 2'-OHs, bound by LC Y31 and HC Y50, make minimal contributions, as their\nremoval by Phe substitutions (LC Y31F, HC Y50F) conferred no binding defects. We had\nthought about removing specific 2'-OH groups on the dsRNA side to evaluate their contributions,\nas we did in the S9.6-hybrid study (Bou-Nader 2022 Nat. Commun.) However, we realized that\nJ2 could simply bind elsewhere if we introduce a small number of deoxy modifications. If we\nthen remove larger number of 2'-OH groups then it is expected to drive the duplex towards B-\nform, based on our observations in the S9.6 study.\nI like the argument that different ionic milieus call for different strategies of dsRNA recognition,\ndue to enhancing effect of salt on hydrophobic interaction, and the screening effect on charge-\ncharge interactions. Unfortunately, the authors are vague about the exact conditions. Can it be\nreconstructed from the way J2 made in the first place what ionic conditions J2 was \"naturally\"\noptimized for? This would make the comparison with the intracellular conditions more concrete, and\nthe conceptually nice idea more convincing.\nA: We appreciate the reviewer’s insight and helpful suggestion on this idea. The typical ionic\nconditions under which antibodies such as J2 was naturally selected and optimized are those in\nextracellular/interstitial fluids bathing the lymph node follicles. They are characterized by ~150\nmM ionic strength (Na⁺ ~140 mM, K⁺ ~4 mM, Ca²⁺ ~1.3 mM, Mg²⁺ ~1 mM, Cl⁻ ~110 mM), pH\n7.4, 37 °C, and are mildly oxidizing and protein-rich. We have added more detailed and specific\ninformation to the discussion to support the ionic milieu idea. Now we state:\n“While intracellular RNA-binding proteins function in the nucleoplasm and cytoplasm,\nantibodies first undergo affinity maturation in germinal centers inside lymph node follicles, and\nthen function in blood plasma, lymph, and interstitial fluids. Both the germinal centers and\nextracellular fluids have higher ionic strengths than the cytoplasm (~150 mM versus ~100 mM),\ntypically contain Na⁺ ~140 mM, K⁺ ~4 mM, Ca²⁺ ~2 mM, Mg²⁺ ~1 mM, Cl⁻ ~110 mM, HCO₃⁻ ~25\nmM, and are mildly oxidizing59. Importantly, they primarily contain small, fully dissociated ions\n(Na⁺, Cl⁻, HCO₃⁻) that contribute strongly to ionic strength, which effectively suppress\nnonspecific electrostatic interactions. This makes antibodies that leverage hydrophobic\ninteractions more effective and specific for nucleic acid interactions. By contrast, intracellular\nfluids are K+-rich and Na+-poor, and contain mostly large organic anions (ATP, proteins,\nnucleic acids) that are not fully dissociated and less mobile. Such conditions favor dynamic\nelectrostatic interactions between proteins (e.g. basic residues) and nucleic acids due to the\nreduced shielding of their charges.”\nPresentation:\nIt has become customary to sweep the crystallographic details of work as in the present study\ncompletely under the table. I am not advocating for a full crystallographic table in the main text\nas in the past. But for manuscripts that are mainly about structure, a minimal crystallographic\ntable with the key information (what space group, how many molecules in the asymmetric unit,\nwhat resolution, refined to what Rfree) should be present in the main text for readers to have a\nrough idea of the quality of the structure. Also, I was unable to find a full crystallographic table\nin the Suppl. and could only assess the quality of the structure based on the PDB validation\nreport. A full crystallographic table should still be included in the Suppl. To the authors credit,\nthe data in the table in the validation report are good (for the experimental resolution), there is no\nneed for additional structure refinement.\nA: We agree with the reviewer. Assuming we have the permission of the editor, we have moved\nthe X-ray crystallographic table to the main text to become Table 1."}, {"round": 2, "reviewer_comments": {"reviewer_1": "the authors have done a thorough job addressing my and my co-reviewer's comments. I am satisfied with the quality of this manuscript.", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "The authors have adequately addressed all of my comments and suggestions.", "reviewer_4": "In the previous revision round, I was mainly concerned about\n-the claim of 2:1 binding stoichiometry\n-the apparent discrepancy between the antibody footprint and the length-dependence of the binding constant.\nThe first issue turned out to be a question of nomenclature, the 2:1 was meant to describe a non-homogeneous binding model. As the other referees were equally confused, it is good that the nomenclature has been changed. I have no objection to an non-homogeneous binding model.\nThe second issue has been very substantively addressed. The authors suggest a different explanation than the one that I had had in mind, and back it up with CD analysis of dsRNA of different lengths. While not entirely conclusive, their model is certainly reasonable.\nWith this, my reservations are fully addressed."}, "author_response": ""}]

Decision letter