Pathogenicity, virological features, and immune evasion of SARS-CoV-2 JN.1-derived variants including JN.1.7, KP.2, KP.3, and KP.3.1.1

Domain: neuroscience
Published: 2025-12-11
Editorial outcome: major_revision

Abstract
KP.3.1.1 became a dominant successor to JN.1 by the second half of 2024 but the intrinsic pathogenicity and virological feature of KP.3.1.1 remain incompletely understood. Here, we comprehensively evaluated the pathogenesis and characteristics of KP.3.1.1 in comparison to JN.1 and other JN.1-derived variants including JN.1.7, KP.2, and KP.3. The unique S31del mutation on KP.3.1.1 spike confers further evasion to the clinically authorized mAb Pemivibart and reduces convalescent serum neutralization efficiency. Structural analysis indicates that S31del induces novel glycosylation sites that facilitates evasion of neutralizing antibodies. We further reveal that S31del significantly enhances pseudovirus entry efficiency in all evaluated cell types including the human primary nasal epithelial cells. Nevertheless, the intrinsic pathogenicity of KP.3.1.1 is similar to JN.1 and KP.3, and higher than that of JN.1.7 and KP.2 in a male hamster model. Interestingly, the increased virus infectivity conferred by S31del in KP.3.1.1 spike is counterbalanced by the NSP10 S33C mutation. Overall, our study indicates that a single spike mutation can confer both enhanced immune escape and increased viral infectivity. The opposing effects of spike and non-spike mutations highlight the complex interplay of viral genomic elements in shaping their overall fitness, and reveal the high plasticity of coronavirus evolution.

Introduction
SARS-CoV-2 Omicron first identified in late 2021 has demonstrated substantially elevated infectability, pronounced immune evasion, and attenuated pathogenicity when compared to ancestral SARS-CoV-2 and earlier SARS-CoV-2 variants of concern (VOCs) 1–8. Over the past three years, Omicron subvariants continue to adapt and circulate in the human population 9–14. Omicron JN.1 emerged in 2023 and subsequently became the predominant strain, in part due to its spike L455S mutation that confers further increased immune evasion, infectivity, and transmissibility 15–20. Among the JN.1 sublineages, KP.3.1.1 was classified by the World Health Organization as a variant under monitoring (VUMs), which became a dominant successor to JN.1 by the second half of 2024 21. Recent studies have characterized the immune escape and infectivity mediated by the KP.3.1.1 spike protein 22–24. Nevertheless, the intrinsic pathogenicity and virological characteristics of KP.3.1.1 remain incompletely understood. In this study, we investigated the in vitro and in vivo virological features of KP.3.1.1 and included JN.1.7, KP.2, and KP.3 in comparative studies. We found that the unique S31del change in KP.3.1.1 spike significantly enhanced both immune evasion and viral infection fitness in the human nasal epithelial cells (hNECs), thereby conferring KP.3.1.1 a distinct competitive advantage over other JN.1-derived subvariants. Using a reverse genetics approach, we further revealed that the unique NSP10 S33C mutation in KP.3.1.1 negatively regulates virus replication, which equilibrates the overall pathogenicity of KP.3.1.1. Together, our results indicate that emerging Omicron subvariants may evolve spike mutations with dual advantages on immune evasion and intrinsic infectivity, highlighting the importance of continuous surveillance and characterization of emerging subvariants.

Results
Following the global dominance of JN.1 in early 2024, multiple JN.1-derived subvariants have emerged, including JN.1.7, JN.1.11.1.2 (KP.2), JN.1.11.1.3 (KP.3), and JN.1.11.1.3.1.1 (KP.3.1.1) (Fig. 1a and Fig. S1a). All JN.1-derived subvariants maintain the L455S mutation in their spike proteins, a feature that has been demonstrated by us and others to contribute to immune evasion and enhanced infectivity 25,26. The JN.1.7 subvariant contains two additional spike mutations (T572I and E1150D) relative to its parental JN.1 strain (Fig. 1b). KP.2 spike differs from that of JN.1 by three amino acid substitutions (R346T, F456L, and V1104L), while the KP.3 spike contains a distinct set of mutations (F456L, Q493E, and V1104L) relative to JN.1. Notably, the KP.3.1.1 spike protein carries an additional deletion at residue 31 (S31del) compared to KP.3 (Fig. 1b). These variants demonstrate distinct fitness advantages relative to JN.1. Globally, JN.1.7 exhibits a 21% fitness advantage, KP.2 shows a 42% advantage, and KP.3 demonstrates a 52% advantage. The relative fitness advantage of KP.3.1.1 reaches 80% compared to JN.1 (Supplementary Fig. 1b, c). Due to this substantial competitive advantage, KP.3.1.1 has become one of the most globally prevalent SARS-CoV-2 variants worldwide (Fig. 1c).

To assess the recognition of the JN.1-derived variants by monoclonal antibodies (mAbs) either approved for COVID-19 therapy or currently in development, we performed pseudovirus neutralization assays evaluating both naturally circulating strains (JN.1, JN.1.7, KP.2, KP.3, and KP.3.1.1) and engineered pseudoviruses containing specific mutant combinations (JN.1+R346T, JN.1+F456L, JN.1+R346T/F456L, JN.1+T572I, and JN.1+Q493E) 24. These mAbs include clinically approved mAbs (Pemivibart 27, Sipavibart 28, and S309 29) and the pre-clinical mAb SA55 30, chosen for their demonstrated efficacy against the JN.1 variant (Fig. 2a). Consistent with recent studies 27,31, the clinically authorized mAb Pemivibart demonstrated activity against JN.1, JN.1.7, and KP.2. However, its potency was reduced against JN.1+R346T/F456L and KP.3, with an IC50 of 0.36 µg/mL and 0.633 µg/mL, respectively. Notably, Pemivibart exhibited further reduced neutralization potency against KP.3.1.1 (IC50 = 4.716 µg/mL). While Sipavibart maintained efficacy against JN.1 subvariants lacking the F456L mutation, its antiviral activity was dramatically diminished against JN.1+F456L, JN.1+R346T/F456L, KP.2, KP.3, and KP.3.1.1. These findings demonstrated that the F456L substitution in the spike protein is primarily responsible for the loss of neutralizing activity by Sipavibart. In contrast, mAb S309 displayed weak neutralization activity against all tested JN.1 subvariants. Interestingly, mAb SA55 remained highly effective against all evaluated JN.1 subvariants, likely because the mutated residues in these variants do not directly interact with SA55.

To systematically characterize humoral immune evasion profiles, we evaluated both circulating JN.1-derived subvariants and engineered JN.1 variants containing single or combined mutations using convalescent plasma from two distinct cohorts of inactivated vaccine recipients who experienced breakthrough infections. The first cohort (n=16) consisted of individuals who received inactivated vaccines, subsequently experienced BA.5 breakthrough infection, and later contracted XBB reinfection. The second cohort (n=16) comprised inactivated vaccine recipients who experienced BA.5 breakthrough infection followed by JN.1 reinfection (Fig. 2b). Consistent with recent studies 32,33, our neutralization analyses revealed that sera from XBB-reinfected individuals demonstrated weak neutralizing activity against all JN.1-derived subvariants, showing a maximum geometric mean titer (GMT) of 724 against JN.1. These sera exhibited significantly reduced neutralization titers against KP.2, KP.3, and KP.3.1.1 pseudoviruses, while maintaining relatively stable activity against JN.1.7. Importantly, we identified that both R346T and F456L mutations independently conferred immune escape capabilities, with their combination demonstrating further increased impact on evasion from neutralizing antibodies. The KP.2 pseudovirus, incorporating R346T, F456L, and V1104L spike mutations, exhibited significantly enhanced immune evasion relative to JN.1, demonstrating a 2.3-fold reduction in GMT using sera from XBB-reinfected individuals with prior BA.5 infection. Similarly, the KP.3 pseudovirus containing F456L, Q493E, and V1104L spike mutations showed a 2.4-fold GMT decrease. Most notably, the KP.3.1.1 pseudovirus displayed additional immune evasion capacity through its unique S31del mutation, evidenced by a further 1.8-fold GMT reduction compared to KP.3 (Fig. 2b and Supplementary Fig. 2a).

Antigenic cartography of serum neutralization data revealed distinct clustering patterns among the variants. While the JN.1.7 pseudovirus maintained close antigenic similarity to its parental JN.1 strain, the emerging subvariants KP.3 and KP.3.1.1 formed a separate cluster, with KP.2 occupying an intermediate antigenic position distinct from both groups (Fig. 2c). These findings demonstrate that KP.3, KP.3.1.1, and KP.2 have undergone antigenic evolution from their parental JN.1 strain, highlighting both their shared antigenic properties and enhanced resistance to neutralizing antibodies compared to earlier variants 34. In the JN.1 breakthrough infection cohort, we observed consistently higher neutralizing titers against all JN.1-derived subvariants relative to the XBB-reinfected group, with KP.3.1.1 showing the lowest GMT of 1124 (Fig. 2b and Supplementary Fig. 2b). Notably, neutralizing titers against KP.2, KP.3, and KP.3.1.1 pseudoviruses showed substantial reductions, displaying 2.4-fold, 2.4-fold, and 2.6-fold decreases in GMT, respectively, when compared to the parental JN.1 variant. These results demonstrated that the acquired mutations in these variants contribute to immune evasion. Specifically, our results indicated the F456L mutation as a major determinant of immune escape for KP.2, KP.3, and KP.3.1.1, establishing the foundation for their evasion capacity. Additionally, S31del conferred a modest but measurable enhancement of immune evasion, ultimately rendering KP.3.1.1 the overall most resistant variant. Antigenic cartography confirmed these observations, with JN.1 and JN.1.7 maintaining in close proximity while KP.3 and KP.3.1.1 formed a distinct antigenic cluster (Fig. 2c). Intriguingly, while KP.2 shares the F456L mutation with KP.3 and KP.3.1.1, its distinct antigenic positioning reveals substantial evolutionary divergence among these JN.1-derived variants, suggesting differential impacts of their respective spike mutations on immune recognition. Since the spike N-terminal domain (NTD) S31del in KP.3.1.1 conferred increased immune evasion, we additionally assessed the immune evasion capability of XEC, which similarly contains NTD mutations. While KP.3.1.1 spike differs from KP.3 spike at NTD S31del, XEC spike differs from KP.3 spike at NTD T22N and F59S. We found that when compared with the KP.3.1.1 pseudovirus, the XEC pseudovirus demonstrated a subtle 1.1-fold and 1.3-fold increase in evasion against BA.5+XBB and BA.5+JN.1 breakthrough infection sera, respectively (Supplementary Fig. 3a). Overall, these findings indicate that the NTD mutations on the spike of KP.3.1.1 and XEC confer increased immune evasion, which may facilitate the circulation of these variants.

To systematically compare immunogenicity across JN.1-derived variants, we established a hamster infection model using authentic viruses of JN.1, JN.1.7, KP.2, KP.3, and KP.3.1.1, with BA.2 included as an ancestral comparator. Serum samples were collected at 16 days post-infection (dpi) for subsequent immunological analyses (Fig. 2d, e). Neutralization assays revealed that convalescent sera from BA.2-infected hamsters demonstrated low neutralizing activity against all tested JN.1-derived subvariants (Fig. 2e). Strikingly, pseudoviruses bearing KP.3 and KP.3.1.1 spike proteins exhibited pronounced resistance to neutralization by convalescent sera from hamsters infected with BA.2, JN.1, JN.1.7, and KP.2, an effect primarily attributed to the Q493E mutation. Comparative analysis of neutralization profiles revealed that S31del conferred additional immune evasion properties to KP.3.1.1 relative to KP.3. Antigenic cartography through both distance mapping and principal component analysis (PCA) consistently grouped KP.3 and KP.3.1.1 into a shared cluster, while distinctly separating JN.1, JN.1.7, and KP.2 into independent antigenic groups 35 (Fig. 2d). Collectively, these findings demonstrate that neutralization cross-reactivity patterns among JN.1 subvariants directly reflect their phylogenetic relationships. Importantly, our data establish that KP.3 and KP.3.1.1 have evolved substantial antigenic divergence from other JN.1-derived variants, including KP.2, suggesting these emerging strains may possess enhanced capacity to evade population immunity established through prior infection with earlier JN.1 subvariants.

The binding affinity between SARS-CoV-2 spike protein and human angiotensin-converting enzyme 2 (hACE2) represents a critical determinant of viral fitness through modulating virus entry. To systematically evaluate these interactions, we quantified the binding kinetics of spike trimers from both naturally circulating JN.1 subvariants and engineered JN.1 mutants (JN.1+R346T, JN.1+F456L, JN.1+R346T/F456L, JN.1+Q493E, and JN.1+T572I) with hACE2 using surface plasmon resonance (SPR) (Supplementary Fig. 4). In keeping with previous findings 36,37, the R346T (KD = 6.97 nM), F456L (KD = 7.43 nM), R346T/F456L (KD = 5.62 nM), and T572I (KD = 5.89 nM) mutations did not substantially alter the hACE2-binding affinity of JN.1 (KD = 6.3 nM). Similarly, JN.1.7 (KD = 6.6 nM), which carries the T572I mutation, displayed a comparable hACE2 binding affinity to JN.1+T572I (KD = 5.89 nM). KP.2 (KD = 3.7 nM), which harbors both the R346T and F456L mutations, exhibited slightly enhanced receptor binding affinity compared to the JN.1 (KD = 6.3 nM). Interestingly, introduction of the Q493E mutation in the JN.1 background (KD = 47.8 nM) resulted in substantially reduced receptor binding capacity. Notably, while the Q493E mutation alone substantially impaired receptor binding (JN.1+Q493E, KD = 47.8 nM), its combination with F456L in KP.3 (KD = 4.76 nM) and KP.3.1.1 (KD = 5.76 nM) restored high-affinity hACE2 interaction. This observation suggests an epistatic interaction between L456 and E493 that counteracts the affinity loss induced by Q493E mutation.

To further elucidate the differences in spike-receptor binding caused by different amino acid mutations, we first determined the structure of ACE2 in complex with the stabilized prefusion ectodomains of KP.2 S(6P) trimers using cryo-electron microscopy (cryo-EM) (Fig. 3). The 3D reconstruction revealed a single conformational state of the KP.2 spike-ACE2 complexes with three up-RBDs bound to three ACE2 molecules (Fig. 3a), resolved at a resolution of 2.27 Å (Supplementary Fig. 5). To improve the density around the spike-ACE2 interface, the NTD_RBD_ACE2 regions of KP.2 were locally refined to 2.90 Å, enabling the unambiguous model building for the RBD domain and ACE2 (Fig. 3b and Supplementary Fig. 5). The interfaces of the JN.1 spike-ACE2 and KP.2 spike-ACE2 complexes display a high degree of structural similarity, with the notable exception of a local variation induced by the F456L mutation (Fig. 3c, d). In the KP.2 spike-ACE2 complex, the side chain of ACE2 K31 is positioned between L456 and Q493 of RBD, forming a salt bridge with Q493 and a hydrogen bond with the backbone of F490 (Fig. 3d). In contrast, in the JN.1 spike-ACE2 complex, the side chain of F456 is oriented towards the ACE2 K31, preventing its side chain from inserting into the RBD. This hindrance disrupts both the hydrogen bonds and the salt bridge between ACE2 K31 and RBD, resulting JN.1 with the weakest binding affinity for ACE2 when compared to its L456-containing descendants (KP.2, KP.3, KP.3.1.1) (Fig. 3c). Compared to the KP.2 spike, the KP.3 spike RBD incorporates a Q493E mutation, which introduces additional salt bridges between E493 and H34, further enhancing its binding affinity for ACE2 38 (Fig. 3e). KP.3.1.1 contains the same F456L and Q493E RBD mutations as KP.3 but possesses the S31del mutation at its NTD. We determined the structure of KP.3.1.1 spike at a global resolution of 3.06 Å. Local refinement improved the density map of NTD and RBD domains, resulting in a local resolution of 3.37 Å (Supplementary Fig. 6). Structural analysis uncovered an interesting consequence of the S31 deletion on KP.3.1.1 spike, which converted the adjacent N30 residue into a novel N-glycosylation site. The S31del change also induced significant conformational rearrangement of the F32 side chain compared to its orientation in both JN.1 and KP.2 spike structures (Fig. 3f, g). The conformational change of F32 resulted in the formation of a π−π interaction region among Y28-F32-Y91-F216-Y266, which might stabilize the local conformation of KP.3.1.1 (Fig. 3h). Interestingly, another glycosylation site was observed at N61 in KP.3.1.1 due to the S31 deletion (Fig. 3f).

We next investigated the structural basis of NTD-directed antibody recognition against KP.3.1.1 spike. The S31 deletion facilitates a novel glycosylation event at the N30 site and induces a conformational rearrangement of residue F32, both of which are situated within the previously characterized antigenic site vi 24,39. This region is known to be targeted by multiple antibodies, including C1717 40, DH1052 41, S2M24 39, and polyclonal Fabs COV57 42. Since high-resolution structural data are currently limited to C1717 and DH1052, we performed structural superposition of the KP.3.1.1 NTD onto these known antibody-complex structures to evaluate potential steric or electrostatic conflicts (Fig. 3i). A close-up structural analysis of the spike-Fab interface revealed that the newly acquired N30 glycan would sterically clash with residue I57 of the C1717 heavy chain, likely disrupting antibody binding. Similarly, for DH1052, key residues including S31 and Y32 in the light chain, as well as Y100H and H100I in the heavy chain, would experience steric hindrance from the N30 glycosylation (Fig. 3i). These structural observations suggest that the S31del change in KP.3.1.1 spike facilitates immune evasion by introducing glycosylation-mediated steric interference, thereby impairing the recognition and binding of NTD-targeting antibodies such as C1717 and DH1052.

To experimentally validate the impact of N30 glycosylation on antibody neutralization, we performed pseudovirus-based neutralization assays using KP.3 and KP.3.1.1 spike pseudoviruses against four spike-NTD-targeting antibodies, including 4–18, 4–19, C1717, and DH1052 40,41,43–45. Among these antibodies, C1717 and DH1052 recognize epitopes that encompass the N30 site, and therefore their binding is likely influenced by glycosylation at this position. Our results showed that antibodies 4-18 and 4-19 retained activity against KP.3, with IC50 values of 2.315 μg/mL and 4.050 μg/mL, respectively, and showed comparable neutralization against KP.3.1.1, although 4-19 exhibited a moderate reduction in potency. In contrast, DH1052 and C1717 showed markedly reduced neutralization against KP.3.1.1 (IC50 = 6.516 μg/mL and 3.876 μg/mL) compared with KP.3 (IC50 = 1.221 μg/mL and 0.035 μg/mL), indicating that the S31 deletion in the spike protein confers substantial immune evasion (Figs. 3j and 3k). Next, we introduce the N30A mutation in the background of KP.3.1.1 spike to abolish the N30 glycosylation. Similarly, N30A was introduced in the background of KP.3 spike as a control. We evaluated the neutralization activity of C1717 against KP.3-N30A and KP.3.1.1-N30A pseudoviruses. In the KP.3 background, C1717 maintained a robust activity against the KP.3-N30A pseudovirus (IC50 = 0.033 μg/mL), with IC50 value comparable to that against the wild-type KP.3 pseudovirus (IC50 = 0.035 μg/mL). Interestingly, in the KP.3.1.1 background, the N30A mutation renders the KP.3.1.1-N30A pseudovirus highly susceptible to C1717 neutralization (IC50 = 0.054 μg/mL), which is an over 70-fold difference when compared to the wild-type KP.3.1.1 pseudovirus (IC50 = 3.876 μg/mL) (Fig. 3j, k). Overall, these validation experiments confirm that the S31 deletion and the consequent N30 glycosylation significantly enhance immune evasion by interfering with antibody binding, thereby supporting the structural and functional role of this modification in facilitating immune escape.

To systematically compare fusogenic activity across variants, we first employed a GFP reporter-based cell-cell fusion assay in 293T cells expressing spike proteins from JN.1.7, KP.2, KP.3, and KP.3.1.1. Quantitative analysis revealed all tested subvariant spikes mediated significantly less membrane fusion than their parental JN.1 spike protein (Fig. 4a). Notably, we observed comparable membrane fusion activity between KP.3 and KP.3.1.1 spike-expressing cells, indicating that the S31del mutation did not substantially alter the fusogenic potential of spike protein (Fig. 4a). We next evaluated the plaque morphology of JN.1 subvariants. To this end, we infected VeroE6-TMPRSS2 cells with authentic viruses (JN.1.7, KP.2, KP.3, and KP.3.1.1) with BA.2 and JN.1 included as controls. Plaque size analysis at 96 and 120 hpi demonstrated that KP.2 produced the smallest plaque size among all tested sublineages, which hinted its less robust replication fitness when compared with JN.1, JN.1.7, KP.3, and KP.3.1.1 (Fig. 4b). Additionally, we monitored the replication of JN.1-derived subvariants in Calu-3 cells and found that KP.2, KP.3, and KP.3.1.1 all replicated less efficiently compared to JN.1 (Figs. 4c and 4d). Area under the curve (AUC) analysis of virus replication in infected Calu-3 cells from 2 to 72 hpi showed that the infectious titer of KP.2, KP.3, and KP.3.1.1 in Calu-3 supernatants were 0.1- (P=0.0002), 0.2- (P=0.0005), and 0.5-fold (P=0.0369) than that of JN.1, respectively (Fig. 4d).

To systematically evaluate spike-mediated viral entry efficiency, we constructed VSV-based pseudoviruses expressing spike proteins from JN.1.7, KP.2, KP.3, and KP.3.1.1 subvariants or engineered spike proteins, and quantified pseudovirus entry in 293T, Calu-3, Caco-2, and VeroE6-TMPRSS2 cells. We found that while KP.2 and KP.3 pseudoviruses demonstrated reduced entry efficiency, the KP.3.1.1 pseudovirus displayed markedly enhanced infectivity when compared to JN.1 or other JN.1-derived subvariants across all tested cell lines. Since KP.3.1.1 and KP.3 spike only differs at S31del, these results indicate that the S31del change in KP.3.1.1 spike confers increased infectivity 21 (Fig. 4e). To delineate the entry pathway of these JN.1-derived subvariants, we employed Camostat (serine protease inhibitor) and E64D (cathepsin inhibitor) to selectively block the cell surface and endosomal entry pathway, respectively. Our inhibitor profiling revealed that JN.1.7, KP.2, and KP.3 pseudoviruses utilized largely similar entry pathways when compared to the JN.1 pseudovirus (Supplementary Fig. 7). Interestingly, the KP.3.1.1 pseudovirus displayed reduced sensitivity to both Camostat and E64D when compared to KP.3, suggesting that the S31del change might modulate the entry pathway of KP.3.1.1 (Supplementary Fig. 7). We also evaluated the role of S31del in using other proteases including members of the matrix metalloproteinase (MMP) family and the a disintegrin and metalloproteinase (ADAM) family, as they were found to facilitate Omicron entry 46. Our results revealed no significant difference in KP.3.1.1 pseudovirus entry relative to the KP.3 pseudovirus across any of the tested MMPs and ADAMs (Supplementary Fig. 8). Since the NTD S31del change in KP.3.1.1 increased infectivity, we additionally evaluated the entry of XEC pseudovirus, which carries the NTD T22N and F59S mutations in spike when compared to KP.3. Our results demonstrated that the XEC pseudovirus is more robust than the JN.1 pseudovirus in virus entry in all evaluated cells. Nevertheless, the level of entry enhancement gained by T22N and F59S was in general less pronounced than that observed with S31del (Supplementary Fig. 3b).

Next, we evaluated the replication fitness of the JN.1-derived subvariants in differentiated primary hNECs. We found that while JN.1.7 and KP.2 replicated less efficiently than JN.1, KP.3 and KP.3.1.1 replicated to similar level when compared to JN.1 (Fig. 5a, b). Interestingly, the replication of KP.3.1.1 was 1.5-fold higher than that of KP.3 albeit not reaching statistical difference, hinting a potential role of S31del in infecting hNECs (Fig. 5b). In addition, we analyzed spike cleavage of JN.1-derived subvariants in infected hNECs. Western blot of spike processing in hNECs indicated comparable cleavage efficiency among JN.1-derived subvariants and JN.1 with the exception of KP.2, which demonstrated reduced S1/S2 cleavage (Fig. 5c). To further assess spike-mediated virus entry in hNECs, we transduced hNECs with BA.2, JN.1, JN.1.7, KP.2, KP.3, and KP.3.1.1 pseudoviruses. We found that while the JN.1 pseudovirus entered hNECs more efficiently when compared to the BA.2 pseudovirus, JN.1.7, KP.2, and KP.3 pseudovirus entry in hNEC were largely comparable to that of the JN.1 pseudovirus (Fig. 5d). Remarkably, the KP.3.1.1 pseudovirus demonstrated significantly higher infectivity in the hNECs, which was 7.3-fold (P<0.0001) and 8.1-fold (P<0.0001) higher when compared to the JN.1 pseudovirus and the KP.3 pseudovirus, respectively (Fig. 5d). Interestingly, this significantly elevated infectivity of KP.3.1.1 was not observed in immunofluorescence assays, which detected nucleocapsid protein expression at 24 hpi in hNECs (Fig. 5e).

Since pseudovirus experiments performed in cell lines (Fig. 4e) and hNECs (Fig. 5d) both suggested a role of S31del in enhancing pseudovirus entry, we further evaluated the impact of S31del on virus entry. To this end, we constructed pseudoviruses expressing BA.2-, XBB.1-, and JN.1-spike proteins with or without the S31del mutation and compared entry efficiency of these pseudoviruses. Our data demonstrated that the S31del-containing pseudoviruses entered hNECs and cell lines significantly more robustly when compared to their control counterparts, confirming that S31del is capable of independently enhancing spike-mediated infectivity (Fig. 5f). To investigate the mechanism of how S31del enhances KP.3.1.1 infectivity, we first examined whether the S31del-induced N30 glycosylation contributes to the increased infectivity. We introduced the N30A substitution in the background of KP.3.1.1 spike to abolish the N30 glycosylation and produced the corresponding pseudoviruses. Similarly, N30A was introduced in the background of KP.3 as a control. We compared the entry efficiency of KP.3, KP.3+N30A, KP.3.1.1, and KP.3.1.1+N30A pseudoviruses in 293T, Calu-3, and Caco-2 cells. Our result demonstrated that the entry efficiency of the KP.3+N30A pseudovirus was comparable to that of the KP.3 pseudovirus in 293T and Caco-2 cells. Importantly, KP.3.1.1+N30A pseudovirus entry was also similar to that of the KP.3.1.1 pseudovirus in 293T and Caco-2 cells, which remained significantly higher than that of the KP.3+N30A pseudovirus. This result indicates that the enhanced infectivity of KP.3.1.1 spike is not primarily mediated by N30 glycosylation (Supplementary Fig. 9). Interestingly, the N30A mutation in the background of both KP.3 and KP.3.1.1 substantially reduced virus infectivity in Calu-3 cells, suggesting that this mutation is not tolerated by the two viral spike proteins for Calu-3 cell entry. Next, we evaluated whether the spike-S31del change might enhance spike protein expression, thereby increasing the infectivity of both authentic KP.3.1.1 virus and corresponding pseudoviruses. To test this hypothesis, we transfected 293T cells with four pairs of spike plasmids, including the spike from BA.2, BA.2+S31del, XBB.1, XBB.1+S31del, JN.1, JN.1+S31del, KP.3, and KP.3+S31del (KP.3.1.1). We quantified the total and cell surface expression level of the spike proteins with flow cytometry at 24 h post transfection. Interestingly, we found that the S31del change increased both the total and cell surface expression level of spike when it is introduced in the background of all four spike proteins (Supplementary Fig. 10 and Supplementary Fig. 11). Together, these results suggest that the S31 deletion in KP.3.1.1 spike likely promoted infectivity through increasing the spike expression level.

We next assessed the intrinsic pathogenicity of JN.1.7, KP.2, KP.3, and KP.3.1.1 in golden hamsters with their ancestral JN.1 strain included as a control. At 2 days post-infection (dpi), lung tissues were collected for comprehensive analysis including quantification of subgenomic RNA copies, determination of infectious virus titers, viral antigen expression profiling, and histopathological evaluation (Fig. 6a). Quantitative analysis of virological parameters revealed that the JN.1-derived subvariants in general replicated less efficiently in hamster lungs when compared to their ancestral JN.1 strain, which is in keeping with findings obtained in Calu-3 cells (Fig. 6b–d). In hamster nasal turbinates, the viral burden of JN.1, JN.1.7, KP.3, and KP.3.1.1 were largely comparable with the exception of KP.2, which demonstrated markedly reduced virus replication (Supplementary Fig. 12). Immunofluorescence analysis of infected hamster lungs revealed reduced viral antigen expression for JN.1.7 (0.1-fold) and KP.2 (0.2-fold) relative to JN.1, while antigen expression of KP.3 and KP.3.1.1 was more comparable to that of JN.1 (Fig. 6d, f). In parallel, our findings from histology studies were largely in keeping with the virus replication results, which identified attenuated lung pathology in JN.1.7- and KP.2-infected hamsters, characterized by minimal alveolar exudates, inflammatory infiltration, and epithelial damage. In contrast, KP.3 and KP.3.1.1 induced similar histopathological changes in hamster lungs when compared with JN.1 (Fig. 6e, g). Omicron replication in the lung tissues is attenuated when compared to ancestral SARS-CoV-2 or earlier SARS-CoV-2 variants such as Delta 6. We additionally compared the replication of JN.1 and KP.3.1.1 with that of Delta and found that the infectious titer of both JN.1 and KP.3.1.1 in hamster lung was more than 100-fold lower than that of Delta, which is keeping with our recent reports on the continuous attenuation of emerging Omicron subvariants 10–12,20 (Supplementary Fig. 13).

Peculiarly, while our results clearly indicated a positive role of S31del in KP.3.1.1 spike in augmenting virus entry, we did not detect a significant increase in KP.3.1.1 replication in vitro or in vitro. With sequence alignment, we found that KP.3.1.1 contains an additional ORF1a S4286C (NSP10 S33C) mutation that is absent in previous VOCs and other Omicron-derived variants including KP.3 (Fig. 7a). We speculated that this mutation might play a role in offsetting the replication fitness gained by the spike S31del change in KP.3.1.1. To evaluate this hypothesis, we introduced the NSP10-S33C mutation into the recombinant BA.1 (rBA.1) backbone (Fig. 7b). The modified plasmid was sequence-verified and transfected into VeroE6-TMPRSS2 cells for virus rescue (Fig. 7c). Comparative analysis of viral replication in VeroE6, VeroE6-TMPRSS2, and Calu-3 cells revealed that rBA.1-NSP10-S33C replicated significantly less efficiently than wild-type rBA.1 across all three evaluated cell lines (Fig. 7d, e). We further introduced the spike-S31del change into rBA.1-NSP10-S33C. Our results demonstrated that S31del rescued the attenuated replication fitness caused by NSP10-S33C in all evaluated cell types. For example, the infectious titer of rBA.1-NSP10-S33C was 16-fold (P=0.0061) lower than that of rBA.1 in Calu-3 cells at 72 h post infection. Introducing the spike-S31del change substantially restored virus replication. The infectious titer of rBA.1-NSP10-S33C-spike-S31del was largely comparable with that of rBA.1 in Calu-3 cells at 72 h post infection of (P=ns) (Figs. 7d and 7e). Furthermore, we challenged hamsters with rBA.1 and rBA.1-NSP10-S33C, and detected virus replication in lungs and nasal turbinates (NT) at 2 dpi (Fig. 7f). Our results indicated that the NSP10-S33C mutation reduced the replication of rBA.1 in hamster lung and NT tissues (Fig. 7g, h). In keeping with these observations, immunofluorescence staining of infected hamster lungs similarly indicated a reduction of antigen expression contributed by the introduction of the NSP10-S33C mutation (Fig. 7i, j). Collectively, these findings demonstrate that the NSP10-S33C mutation attenuates SARS-CoV-2 replication both in vitro and in vivo. Coronavirus NSP10 is known to interact with NSP14 and the interaction is important for the exoribonuclease activity of NSP14 47,48. Structural modeling revealed that residue S33 in NSP10 forms a hydrogen bond with N67 in NSP14 (Fig. 7k, l). The S33C substitution introduces a cysteine residue that may disrupt native hydrogen bonding networks and induces conformational rearrangements in the α2’ helix of NSP10 within its N-terminal domain, likely impairing NSP10-NSP14 complex formation, which provides a mechanistic basis for the attenuated replication observed in KP.3.1.1.

Methods
All our animal experiments were approved by the Committee on the Use of Live Animals in Teaching and Research (CULATR) of The University of Hong Kong (HKU) under CULATR 22-139. Golden Syrian hamsters were sourced from the Center for Comparative Medicine Research (CCMR) at HKU and housed in individually ventilated cages under controlled conditions (65% humidity, 21–23°C, 12 h/12 h light/dark cycle). For hamster infection, 4- to 6-week-old male hamsters were randomly allocated to experimental groups and anesthetized with ketamine and xylazine, followed by intranasal inoculation of 50 µL pre-diluted 1ⅹ105 PFU Omicron JN.1, JN.1.7, KP.2, KP.3 and KP.3.1.1 virus in DMEM. At 2 days post-infection (dpi), hamsters were euthanized and sacrificed for lung tissue collection to perform virological and histopathological examinations as we previously described 60.

SARS-CoV-2 Omicron BA.2 (GISAID: EPI_ISL_9845731), JN.1 (GISAID: EPI_ISL_18841631), JN.1.7 (GISAID: EPI_ISL_19351034), KP.2 (GISAID: EPI_ISL_19351035), KP.3 (GISAID: EPI_ISL_19535068), and KP.3.1.1 (GISAID: EPI_ISL_19534723) were isolated from laboratory-confirmed COVID-19 patients in Hong Kong. Virus isolation was performed on archived clinical specimens obtained during routine clinical practice from laboratory-confirmed COVID-19 patients in Hong Kong. This study was approved by the Institutional Review Board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster (HKU/HA HKW IRB) (Reference No.: UW 21-313; Protocol No.: 202104). The requirement for informed consent was waived by the IRB as the research involved no additional interventions and utilized only anonymized archival specimens. All SARS-CoV-2 subvariants were propagated in VeroE6-TMPRSS2 cells and titrated using plaque assays. All in vivo and in vitro experiments involving authentic viruses were conducted in the Biosafety Level 3 (BSL-3) facility at the Department of Microbiology, The University of Hong Kong, following approved standard operating procedures 61.

Peripheral blood samples were collected from vaccinated individuals (2–3 doses of inactivated vaccines) with prior BA.5 infection followed by XBB or JN.1 reinfection at Nanjing Hospital of Chinese Medicine. Serum was isolated by centrifugation and stored at −80°C. All collections complied with Declaration of Helsinki guidelines under approved protocols (Ethics Committee of Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, KY2023073). All participants provided written informed consent. The background information of the convalescent donors is summarized in Supplementary Table 1.

A total of 3863 SARS-CoV-2 genome sequences and pair-wised phylogenetic tree were downloaded from nextstrain (https://nextstrain.org/) 62 with open data 63 from January 2022 to October 2024 (Supplementary Table 2). We accessed recent 6-month global data on November 05, 2024, which highlight the Omicron variants. We re-colored the phylogenetic tree by labeling all variants as “BA.2,“ “JN.1,” “JN.1.7,” “KP.2,” “KP.3,” and “KP.3.1.1”. We analyzed the mutation and epidemic by using tools from covSPECTRUM (https://cov-spectrum.org/) 64 based on the GISAID data (https://www.gisaid.org/) 63 on November 4, 2024. The mutation proportion of each variant was based on all genome sequences obtained on June 27, 2025. Here, only mutations with >10% frequency were included. The variants frequency of each variant was calculated based on genome sequences from November 1, 2023 to November 1, 2024 obtained on June 27, 2025.

Relative fitness advantage was analyzed based on covSPECTRUM (https://cov-spectrum.org/) 64. The analysis employed a logistic growth model to estimate the relative fitness advantage of SARS-CoV-2 variants compared to the reference variant JN.1 across different geographic regions 65. Input data consisted of daily variant counts stratified by date, variant designation, observed counts, and geographic region information from November 1, 2023 to November 1, 2024 obtained on June 27, 2025. Temporal dynamics of fitness advantage for major SARS-CoV-2 lineages was analyzed following previous publications 65,66. The analysis assumed a viral generation time of 3.5 days derived from past research 67. A sliding window of 90 days was used to ensure temporal resolution while maintaining statistical stability. For each variant, a logistic growth model was applied within each 90-day window advancing weekly. The model compared the variant’s frequency against JN.1, using a binomial generalized linear model with a logit link. The response variable was binary (1 for the variant, 0 for JN.1), and the predictor was time (in days). Only windows with ≥5 data points and non-zero total samples were included. The growth rate was derived from the slope coefficient, and was converted to relative fitness advantage, which is expressed as a percentage change per generation (3.5 days). Confidence intervals (95%) were calculated using standard errors from the model covariance matrix. All analyses were implemented in R version 4.3.0 utilizing glm for model fitting, purrr for iterative processing across variants, and ggplot2 for visualization.

We generated mammalian expression plasmids encoding stabilized prefusion spike trimers (S6P) for JN.1, JN.1.7, KP.2, KP.3, and KP.3.1.1 variants, along with JN.1 derivatives containing individual or combined mutations. Each construct was synthesized by cloning the full-length spike sequence into pCMV3, incorporating C-terminal 8×His and 2×Strep-tagII affinity tags. Soluble dimeric ACE2 expression plasmids were prepared using established protocols 68. The Expi293 cells were transiently transfected with the corresponding expression plasmids using 1 mg/mL polyethylenimine (PEI, Polysciences) for protein expression. Five days post-transfection, culture supernatants were collected and subjected to affinity purification using Ni-Smart resin (Smart Lifesciences, Changzhou, China; catalog# SA036100, Ni Smart Beads 6FF) according to the manufacturer’s protocol. Purified proteins were quality-controlled by SDS-PAGE to verify molecular weight and purity before experimental use.

For this study, the monoclonal antibody Sipavibart was commercially sourced (Antibody System, Catalog# DVV00353), whereas Pemivibart, S309, SA55, 4-18, 4-19, C1717, and DH152 monoclonal antibodies were obtained from established in-house collections as described in our previous publications 20,45. Briefly, the variable region genes were codon-optimized for human cell expression and synthesized by HuaGene™ (Shanghai, China) into gWiz plasmids encoding the constant regions of human IgG1 heavy and light chains. Antibodies were expressed in Expi293F cells (Thermo Fisher, A14527) by co-transfection of plasmids encoding the heavy and light chains using polyethylenimine (Polysciences). The cells were cultured at 37°C with shaking at 125 rpm under 8% CO₂. Five days post-transfection, the supernatants were harvested for antibody purification using MabSelect™ PrismA affinity chromatography (Cytiva, 17549801).

SPR experiments were conducted using the Biacore 8K system (Cytiva) following previously described protocols 69. Spike trimer proteins were immobilized on CM5 sensor chips (Cytiva, 29149603) via amine coupling (Cytiva, BR100050) to achieve a target density of 2000 response units (RU). Serial dilutions of purified human ACE2 (6.25, 12.5, 25, 50, 100, and 200 nM) were injected across the functionalized sensor surface. Binding interactions were monitored at room temperature using Biacore 8K Evaluation Software 3.0 (Cytiva), with sensorgrams analyzed by fitting the raw data to a 1:1 Langmuir binding model.

Four-week-old male Syrian hamsters were intranasally inoculated with 2×105 PFU of Omicron BA.2, JN.1, JN.1.7, KP.2, KP.3, or KP.3.1.1 under anesthesia. Sixteen days post-inoculation, serum samples were harvested, centrifuged, and heat-inactivated at 56°C for 30 min.

Pseudoviruses were prepared as we previously described 70,71. Plasmids encoding spike proteins from Omicron variants JN.1, JN.1.7, KP.2, KP.3, and KP.3.1.1, along with engineered JN.1 variants containing single or combined mutations, were synthesized. Expi293F cells were grown to 3×106 cells/mL before transfection with the indicated spike gene using polyethylenimine (PEI, Polysciences). Cell were cultured overnight at 37°C with 8% CO2 and VSV-G pseudo-typed ΔG-luciferase (G*ΔG-luciferase, Kerafast) was used to infect the cells in DMEM at a multiplicity of infection (MOI) of 5 for 4 h. Subsequently, cells were washed three times with PBS containing 2% FBS (PBS/2%). After 24 h, the transfection supernatant was collected and clarified by centrifugation at 300×g for 10 min. Each viral stock was then incubated with 20% I1 hybridoma (anti-VSV-G; CRL-2700, ATCC) supernatant for 1 h at 37°C to neutralize residual VSV-G pseudotyped ΔG-luciferase virus prior to titer determination and aliquot storage at −80°C.

Neutralization assays were performed by incubating pseudoviruses with serially diluted monoclonal antibodies or serum samples, with neutralizing activity quantified through luciferase reporter gene expression reduction as previously established 72,73. In brief, VeroE6 cells were seeded in a 96-well plate at a density of 2×104 cells per well. On the following day, pseudoviruses were incubated with serial dilutions of the test samples in triplicate for 30 min at 37°C. The mixture was then added to cultured cells and incubated for 24 h, after which luminescence was measured using the Luciferase Assay System (Beyotime). IC50 was defined as the dilution at which the relative light units (RLUs) were reduced by 50% compared to the virus control wells (virus+cells) after subtracting the background signal in the control groups with cells only. The IC50 values were calculated using nonlinear regression analysis in GraphPad Prism 10.0.

The antigenic maps were generated as we described previously 20. The antigenic map was constructed through antigenic cartography analysis of serum neutralization data using the Racmacs package (https://acorg.github.io/Racmacs/). The map was generated in R with 10,000 optimization steps and default two-dimensional parameters. Map distances between sublineages and serum positions were optimized to reflect fold-changes in neutralizing ID50 titers relative to each serum’s maximum titer, with one map unit representing a two-fold titer difference.

The stabilized prefusion ectodomains of the KP.3.1.1 S(6P) trimer, the KP.2 S(6P) trimer and ACE2 were expressed in Expi293F cells and purified following previously described protocols 20. The purified KP.2 spike trimer was concentrated to 0.6 mg/mL, mixed with ACE2 ectodomain at a 1:1.2 molar ratio, and incubated at 4°C for 12 min. The KP.3.1.1 spike trimer was concentrated to 0.5 mg/mL, and 3 μL of the protein was applied to a novel light-emitting porous Ni-Ti amorphous alloy film supported by 400-mesh gold grid. Samples were vitrified using a Vitrobot Mark IV (Thermo Fisher Scientific) with the following parameters: 2 s blot time, blot force of -3, and 10 s wait time. Cryo-EM data were acquired on a 300 kV Titan Krios G4 microscope (Thermo Fisher Scientific) equipped with a Falcon 4i direct electron detector and Selectris X energy filter (20 eV slit width), using EPU software for automated data collection in AFIS mode. EER movie stacks were collected in super-resolution mode, KP.2 S-ACE2 magnification of 130,000×, corresponding to a physical pixel size of 0.932 Å, dose fractioned to 1080 frames. For KP.3.1.1-spike trimer, the magnification was 165,000×, corresponding to a physical pixel size of 0.760 Å. The defocusing range is −1.0 to −3.0 μm, and the total dose is about 50 e−/Å2 74.

For the KP.2 spike-ACE2 complex dataset, all dose-fractionated images underwent motion correction and dose weighting in RELION, followed by contrast transfer function estimation using cryoSPARC patch CTF analysis 75. Particle selection was performed through automated blob picking and template matching, followed by extraction at 320-pixel box size with Fourier-space cropping to 160 pixels. All subsequent 2D/3D classification and refinement procedures were conducted in cryoSPARC 75 (Supplementary Fig. 5a). 958,918 particles were selected after 2D classification, and these particles were used to do ab initio reconstruction heterogeneous refinement. This process yielded 393,648 converged particles, corresponding to a “3-up” conformation with three ACE2 bound to each RBD. Next, these particle sets were re-extracted with a box size of 400 pixels and subjected to non-uniform refinement, achieving a final resolution of 2.27 Å. To analyze the receptor interaction interface, a focused mask covering the NTD, RBD, and ACE2 regions was applied for alignment-free 3D classification and local refinement after achieving global particle convergence and applying C3 symmetry expansion. The provided particles depict a local reconstruction of the NTD-RBD-ACE2 region, resulting in a 2.90 Å map generated using 393,648 particles (Supplementary Fig. 5b).

For the KP.3.1.1 spike dataset, motion correction, CTF estimation, particle picking, and 2D classification were performed in cryoSPARC as previously described. From this processing, 83,990 high-quality particles were selected for ab initio reconstruction and heterogeneous refinement (4 classes). The optimal class served as input for Topaz training. The trained particle set was then merged with particles from the best refinement class, followed by removal of duplicate particles. Upon non-uniform refinement for these 75,262 particles, we yielded a map of 3.06 Å resolution. For further improving the density of NTD and RBD regions, 3D classification and local refinement with mask were performed and resulted in a 3.37 Å map using 36,563 particles (Supplementary Fig. 6).

The sharpened maps were generated by EMReady 76. For model building, the initial model was generated by SWISS-MODEL 77 and fitted to the map using UCSF Chimera 78. The model was then manually adjusted in COOT and further refined using PHENIX 79. Figures were produced by UCSF Chimera and UCSF ChimeraX 80. Data collection and model refinement statistics are shown in Supplementary Table 3.

293T, Caco-2, and VeroE6 cell lines (ATCC) were cultured in DMEM (11965-092, Gibco) supplemented with 10% FBS, 100 U/mL penicillin, and 100 μg/mL streptomycin. VeroE6-TMPRSS2 cells (JCRB Cell Bank) were maintained in DMEM containing 10% FBS, 100 U/mL penicillin, 100 μg/mL streptomycin, and 2% G418 (ant-gn-5, InvivoGen), while Calu-3 cells were cultured in DMEM/F12 (10565042, Gibco) with 10% FBS and antibiotics. All cells were incubated at 37°C with 5% CO2 and routinely tested for mycoplasma contamination. For viral infection assays, Calu-3 cells were seeded in 96-well plates and infected with SARS-CoV-2 Omicron subvariants at MOI 2 for replication studies.

hNECs cultured at air-liquid interface (ALI) were obtained from Epithelix (EP02MP, Switzerland) and maintained in MucilAir medium (EP04MM) before infection. For viral challenges, hNECs were washed apically three times with medium to remove mucus and then infected with SARS-CoV-2 Omicron subvariants (MOI = 2) at the apical surface, followed by 2-h incubation at 37°C for viral entry before inoculum removal. Viral load was assessed at 2, 24, 48, 72, and 96 h post-infection through apical collection of supernatants/cell lysates for infectious titer detection and RT-qPCR quantification of viral RNA. For immunofluorescence, cells were fixed with neutral-buffered formalin, permeabilized with 0.1% Triton X-100 (Sigma-Aldrich, 11332481001), and stained with rabbit anti-SARS-CoV-2 nucleocapsid serum (in-house) and mouse anti-β-tubulin (Sigma-Aldrich, T7941) to detect viral protein and ciliated cells, respectively, followed by incubation with Alexa Fluor-conjugated secondary antibodies (goat anti-mouse 594 [Thermo Fisher, A-11005] and goat anti-rabbit 488 [A-11034]). Samples were mounted with ProLong Diamond Antifade Mountant with DAPI (Thermo Fisher, P36962) and imaged on an LSM980 confocal microscope (Zeiss) using Z-stack acquisition and maximum intensity projection processing in ZEN Blue software.

To compare the entry efficiency of Omicron-spike pseudoviruses (BA.2, JN.1, JN.1.7, KP.2, KP.3, KP.3.1.1, and engineered JN.1 variants with single/combined mutations), 293T, Calu-3, Caco-2, and VeroE6-TMPRSS2 cells were seeded in 96-well plates for transduction. Parallel experiments using differentiated hNECs assessed entry of BA.2, JN.1, JN.1.7, KP.2, KP.3, and KP.3.1.1 spike pseudoviruses. After 24-h incubation, cells were PBS-washed and lysed (RG129M) for luminescence detection (Luciferase Assay System, RG066M, Beyotime). For inhibitor studies, cells were pretreated with 10 μM Camostat (HY-13512) or E64D (HY-100229) (MedChemExpress) for 2 h prior to transduction with the pseudovirus panel, with luminescence measured post-24 h incubation.

For SARS-CoV-2 antigen detection and histopathological evaluation, infected hamster lungs were immersion-fixed in 4% paraformaldehyde (24 h), ethanol-washed, and paraffin-embedded using a Leica TP1020 processor. Tissue sections (5 μm) were microtome-cut (Thermo Fisher), slide-mounted, and oven-dried (37°C overnight). For immunofluorescence, dewaxed slides underwent antigen retrieval (Vector Labs H-3300, 90 s boiling), Sudan black B quenching, and 5% FBS blocking before incubation with primary (rabbit anti-SARS-CoV-2-N) and secondary antibodies (goat anti-rabbit IgG-FITC, Thermo 65-6111, 1:500 dilution), followed by DAPI mounting (Vector H-1200). For H&E staining, slides were processed with Gill’s hematoxylin/eosin. All imaging used an Olympus BX53 microscope, with nucleocapsid signal intensity quantified in ImageJ 1.53 and histopathology scored semi-quantitatively (n=5 hamsters/group, 3 slides/hamster) 46.

RNA from infected cell lysates or homogenized animal tissues was extracted using the RNeasy Mini Kit (74106, Qiagen), while RNA from infected cell supernatants was isolated with the Viral RNA Mini Kit (52906, Qiagen) or QIAsymphony RNA Kit (931636, Qiagen). To quantify gene expression levels in the extracted RNA samples, RT-qPCR was performed using the QuantiNova Probe RT-PCR Kit (208354, Qiagen) or QuantiNova SYBR Green RT-PCR Kit (208154, Qiagen) on a LightCycler 480 Real-Time PCR System (Roche, Basel, Switzerland). Primer and probe sequences are shown in Supplementary Table 4.

293T cells were transfected with spike expressing plasmids for 24 h before fixing. The transfected cells were detached with 10 mM EDTA in PBS, fixed in 4% paraformaldehyde, followed by immunolabelling with a rabbit anti-SARS-CoV-2-spike-S1 specific antibody (ab283942, abcam) (1:500). Flow cytometry was performed using a BD FACSCanto II flow cytometer (BD) and data was analyzed using FlowJo (version v10.7) (BD).

To engineer the recombinant BA.1 plasmid with targeted mutations, we employed the Lambda-Red recombination system using the Counter-Selection BAC Modification Kit (Gene Bridges K002). Following manufacturer protocols, we co-transformed the pSmartBac-BA.1 plasmid (previously constructed via homologous recombination) and pRed/ET plasmid into DH10b competent cells (Thermo Fisher EC0113) prior to modification. Two distinct DNA fragments were generated: one containing the rpsL counter-selection marker and another bearing the viral sequence with desired mutations. These fragments were sequentially introduced into cells for recombination. Positive clones were selected using appropriate antibiotics, and plasmid integrity was verified by sequencing after maxiprep purification.

To assess the infectious titer in infected hamster tissues, a 50% tissue culture infectious dose (TCID50) assay was conducted. Briefly, VeroE6-TMPRSS2 cells were seeded into 96-well plates and inoculated with 10-fold serial dilutions of lung homogenates. After a 2-h incubation, residual viral particles were removed, and cells were washed three times with serum-free DMEM. At four days post-infection, cytopathic effects (CPE) were evaluated to determine the median tissue culture infectious dose (TCID50).

A population of 293T cells was co-transfected with GFP1-10 (cat# 68715, Addgene) along with SARS-CoV-2 spike expression plasmids to generate effector cells. Similarly, a separate set of 293T cells was co-transfected with GFP11 (cat# 68716, Addgene) and human ACE2 expression plasmids to establish target cells. Twenty-four hours post-transfection, cells were harvested using EDTA-Trypsin (25200072, Gibco) and subsequently co-cultured at 1:1 ratio in 8-well chamber slides for an additional 24 h. After incubation, cells were fixed with 10% formalin and permeabilized with 0.1% Triton X-100 (11332481001, Sigma, USA) at room temperature. Finally, slides were mounted using antifade mounting medium containing DAPI (H-1200, Vector Laboratories) and visualized using an Olympus BX73 fluorescence microscope (Olympus Life Science, Tokyo, Japan). The images were processed using ImageJ 1.53 software by separating the RGB channels, after which the green channel was selected for integrated density measurements. A uniform threshold was applied to all cell-cell fusion images to reduce background interference and ensure consistent quantification.

To investigate spike cleavage of Omicron subvariants in hNECs, differentiated hNECs were infected with BA.2, JN.1, JN.1.7, KP.2, KP.3, and KP.3.1.1 at a MOI of 2 for 96 h prior to sample collection. Cells were lysed in RIPA buffer (89901, Thermo Fisher Scientific), and proteins were separated by 8% SDS-PAGE. For Western blot analysis, membranes were blocked with 5% non-fat milk for 2 h and incubated overnight at 4°C with either a rabbit anti-SARS-CoV-2 spike S2 antibody (40590-T62, Sino Biological, China) or a β-actin antibody (clone AC-74, A5316, Sigma-Aldrich). Subsequently, horseradish peroxidase (HRP)-conjugated secondary antibodies (31460, Thermo Fisher Scientific) were applied, and protein bands were visualized using SuperSignal West Pico PLUS Chemiluminescent Substrate (34580, Thermo Scientific) with an Alliance Imager apparatus (Uvitec, Cambridge, UK).

Data in the figures are presented as means ± standard error of the mean (SEM). Comparisons between two groups were performed using two-sided Student’s t tests, while comparisons among three or more experimental groups were conducted using one-way or two-way ANOVA. Differences were considered statistically significant at p<0.05. All data analyses were performed using GraphPad Prism 10.0.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Dear editor, I have reviewed the manuscript entitled ” Intrinsic pathogenicity, virological features, and immune evasion of\nSARS-CoV-2 JN.1-derived variants including JN.1.7, KP.2, KP.3 and KP.3.1.1 by Shi and co-authors. The manuscript\ndescribes a variety of different assays to understand the ongoing evolution of SARS-CoV-2 and describes that immune\nevasion is the main feature for the ongoing evolution. Due to the wide variety of assays used, the overall contribution of each\nassay and the representative figures are sometimes hard to follow. E.g. the quantitative fitness analyses could have done by\njust referring to published literature as the data does not add to the story, each representative VOC will typically have\nsuperior fitness over the previous generation. In addition, the analyses of different plaque size phenotypes, the actual\ncontribution of this in vitro phenotype to the overall assessment of the lineages and mutations is not exactly clear.\nOne the authors should look at is the representation of the results of growth curves and animal studies as they are not\ndisplayed or analyzed according to the standard of the field, rather they are plotted as copynumber over household gene?\nThis will make it impossible to compare results between other studies, and results should be plotted with endpoint\ncopynumbers of titers.\nMinor points:\nLine 142: this is not strictly immune evasion, but failure of commercial monoclonal antibodies to recognize a single epitope.\nPlease rephrase\nLine 189, “significant antigenic evolution”, based on the antigenic maps fig 2c and d, the actual antigenic distance is\nrelatively small ~ 2 fold. Compared to the emergence of omicron, ~ 12 fold, although there is clear antigenic evolution, the\ndistance in the map appears to be relatively small (wilk science 2023).\nHamster experiments: actual copynumbers per gram of tissue should be plotted rather than over actin (see previous\ncomment)\nLung titer should be plotted per gram tissue\nIt would have been good if copynumbers and infectious titers of nasal turbinates would have been taken along? It’s a bit\nunclear as the authors did do hNEC cells?\nAs a comparison some of the earlier variants like Delta should have been taken along to put it into perspective", "reviewer_2": "In this study, Jialu Shi et al. investigate the immunological and virological characteristics of JN.1-derived variants circulating\nin 2024. The focus is on the KP.3.1.1 variant, which harbors a single deletion in the N-terminal domain of the Spike protein\n(S31del).\nThe authors observed a reduced activity of the monoclonal antibody Pemivibart against KP.3.1.1. Consistent with findings\npreviously published by other groups, they confirm that the S31 deletion enhances immune evasion (Jingyi Liu et al., The\nLancet Infectious Diseases, 2025). In agreement with Yu Kakut et al. (The Lancet, 2024), they also report increased viral\nentry in several cell lines.\nThe S31 deletion introduces a glycosylation site that has already been associated with enhanced immune escape (Jingyi\nLiu et al., The Lancet Infectious Diseases, 2025). Interestingly, although viral entry is increased in KP.3.1.1, this variant does\nnot exhibit higher replication levels compared to KP.3. The authors identify an additional mutation in Orf1a (S4286C),\nlocated in the region encoding NSP10. This mutation induces a conformational change in NSP10 that weakens its\ninteraction with NSP14, resulting in reduced viral fitness.\nOverall, the study is well written and well conducted. While several publications have previously explored the impact of the\nS31 deletion in the N-terminal domain of the Spike protein, this paper effectively consolidates prior findings and goes further\nby characterizing the KP.3.1.1 variant in more depth—particularly highlighting the impact of the mutation in NSP10.\nSpecific Comments\n1. Figure 1b: There is no visible variation in the frequency of mutations. Please adjust the color scheme to improve clarity.\n2. Figure 1c: This figure does not add any additional information beyond what is shown in Figure 1b.\n3. Figure 2a: This figure is unclear. The top graphs are missing X-axes. Also, “Antibody concentration (µg/ml)” should be\nlabeled only once for the entire row of graphs.\n4. Figure 2b: The data presented are repetitive, with many graphs that are not necessary to convey the key message.\n5. Figure 2d: For the antigenic cartography based on hamster data, please clarify which group of hamsters (which infection)\nwas used to generate the data.\n6. Figure 4a: For the quantification of cell–cell fusion, it appears that GFP area is being measured. Please either update the\nY-axis label accordingly or explain the measurement more clearly in the figure legend.\n7. Figure 4c: A single graph showing the replication kinetics would be more informative than multiple separate panels.\n8. Figure 5a: The replication kinetics of the different variants (at minimum, KP.3 vs KP.3.1.1) should be assessed in human\nnasal epithelial cells (hNECs). The authors should quantify viral mRNA at the apical side over time to better evaluate viral\nfitness.\n9. Figure 7: It would be interesting to compare the pathogenicity of BA.1 variants with and without the S31del and/or S4286C\nmutations.\n10. General Comment: The study is overall very compelling, but it is unfortunate that the authors did not include the latest\nXEC variants, which also harbor N-terminal domain mutations that introduce glycosylation sites.", "reviewer_3": "In this manuscript entitled “Intrinsic pathogenicity, virological features, and immune evasion of SARS-CoV-2 JN.1-derived\nvariants including JN.1.7, KP.2, KP.3, and KP.3.1.1”. Chu et al. investigated the in vitro and in vivo virological features of\nKP.3.1.1, with comparative analyses including JN.1.7, KP.2, and KP.3. The authors employed a comprehensive set of\nexperimental approaches, including in vitro neutralization assays, structural biology, a human nasal epithelial cell (hNEC)\nmodel and a golden hamster infection model, to evaluate immune evasion, cell-entry efficiency, ACE2-binding affinity,\npathogenicity in animal, and the impact of the ORF1a-S4286C mutation on viral replication. However, I must advise editor to\nconsider the following points before making decisions.\nFirst, there are significant discrepancies among the experimental findings that the authors have not sufficiently addressed or\nreconciled. For instance, in the cell–cell fusion assay, KP.3.1.1 exhibits lower fusion efficiency than JN.1, yet the S31del\nmutation - unique to KP.3.1.1 compared with KP.3 - appears to have no notable effect on fusion. In contrast, the pseudovirus\nentry assays in 293T, Calu-3, Caco-2, and VeroE6-TMPRSS2 cells attribute KP.3.1.1’s increased infectivity to S31del.\nMoreover, the pseudovirus results conflict with authentic virus infection outcomes in hNECs. These inconsistencies are not\ndiscussed in the manuscript. Instead, the authors use pseudoviruses of BA.2, XBB.1, and JN.1—with or without S31del—to\nargue that S31del independently enhances spike-mediated infectivity, which is logically unconvincing without further\nvalidation.\nIn evaluating intrinsic pathogenicity, the authors report similar lung viral loads, antigen expression, and histopathological\nfeatures in hamsters infected with KP.3, KP.3.1.1, and JN.1. These in vivo results do not align with the in vitro findings. Yet,\nno discussion or proposed mechanisms are provided to reconcile these discrepancies. How should these divergent findings\nbe interpreted in a coherent framework?\nSecond, in the “Receptor interaction” section, although the authors resolved high-resolution structures of the KP.2 spike-\nACE2 complex and the KP.3.1.1 spike trimer, and identified a novel glycosylation site introduced by the S31del mutation,\nthey fail to clarify how this structural feature contributes to immune evasion or infectivity. The manuscript lacks a clear\nfunctional link between structural observation and virological consequences, and no mechanistic hypotheses or validation\nexperiments are proposed. Furthermore, the neutralization assays only assess antibodies targeting the RBD, yet the authors\nsuggest that S31del in the NTD alters neutralization sensitivity. How do the authors justify this claim without testing\nneutralizing antibodies against the NTD?\nThird, given the aforementioned inconsistencies, the conclusion that the ORF1a S4286C mutation impacts viral replication\nremains speculative and unsupported. The manuscript does not clearly explain how the observed phenotypic effects were\nattributed specifically to the ORF1a region, nor how alternative explanations or confounding variables were excluded. As it\nstands, this conclusion lacks a solid logical and experimental foundation."}, "author_response": "Dear editor, I have reviewed the manuscript entitled” Intrinsic pathogenicity, virological\nfeatures, and immune evasion of SARS-CoV-2 JN.1-derived variants including JN.1.7, KP.2,\nKP.3 and KP.3.1.1 by Shi and co-authors. The manuscript describes a variety of different assays\nto understand the ongoing evolution of SARS-CoV-2 and describes that immune evasion is the\nmain feature for the ongoing evolution.\nDue to the wide variety of assays used, the overall contribution of each assay and the\nrepresentative figures are sometimes hard to follow. E.g. the quantitative fitness analyses could\nhave done by just referring to published literature as the data does not add to the story, each\nrepresentative VOC will typically have superior fitness over the previous generation.\nResponse: Thank you for your suggestion. Following your suggestion, we have moved the\nquantitative fitness analyses in Figure 1d to Supplementary Figure 1b of the revised\nmanuscript. In addition, we have double checked and cited relevant literature on the fitness of\nthe subvariants.\nIn addition, the analyses of different plaque size phenotypes, the actual contribution of this in\nvitro phenotype to the overall assessment of the lineages and mutations is not exactly clear.\nResponse: Thank you for the valuable comment. In our characterization of the virological\nfeatures of SARS-CoV-2 lineages, we made use of a series of tools in order to achieve a\ncomprehensive and holistic assessment of the SARS-CoV-2 lineages. The plaque size analysis\nis a classic experiment that provide information on multiple features of the SARS-CoV-2\nlineages under investigation, including virus replication rate, cell-cell spread, and capacity of\ncausing cytopathic effect.\nAs shown in Figure 4b, KP.2 produced the smallest plaque size among all tested sublineages,\nwhich hinted its less robust replication fitness when compared with JN.1, JN.1.7, KP.3, and\nKP.3.1.1. This finding is in keeping with data from the virus replication assays in Calu-3 cells\nand hNECs (Figure 4c, Figure 4d, Figure 5a and 5b), furin cleavage assay in hNECs (Figure\n5c), pseudovirus entry assays in multiple cells lines and hNECs (Figure 4e and Figure 5d),\nand the virus replication assay in hamster lungs (Figure 6).\nInterestingly, as also shown in Figure 4b, KP.3.1.1 produced similar plaque size when\ncompared with KP.3. This is consistent with the similar replication fitness observed between\nKP.3.1.1 and KP.3 across multiple assessments in Calu-3 cells, hNECs, and in hamsters (Figure\n4c and 4d, Figure 5a and 5b, Figure 6). The similar virus replication between KP.3.1.1 and\npromotes virus entry (Figure 4e, Figure 5d, Figure 5f). However, this is later explained by the\nother mutation present in KP.3.1.1 when compared to KP.3, NSP10 S33C, which reduces the\nreplication efficiency of KP.3.1.1, eventually leading to comparable replication fitness between\nKP.3.1.1 and KP.3 (Figure 7).\nAs also pointed out by the Reviewer, one of the strengths of the current study is that a variety\nof different assays were employed to understand the ongoing evolution of SARS-CoV-2.\nComparing and contrasting information obtained from all the different assays will allow us to\nderive the most scientifically correct answer for the overall assessment of the lineages and\nmutations being studied.\nWe apologize that the message obtained from the plaque size result was not clearly elaborated.\nWe have now revised the text so that the information obtained from the plaque size analysis is\nmore easily appreciated. Line 327: “Plaque size analysis at 96 and 120 hpi demonstrated that\nKP.2 produced the smallest plaque size among all tested sublineages, which hinted its less\nrobust replication fitness when compared with JN.1, JN.1.7, KP.3, and KP.3.1.1 (Fig. 4b).”.\nOne the authors should look at is the representation of the results of growth curves and animal\nstudies as they are not displayed or analyzed according to the standard of the field, rather they\nare plotted as copynumber over household gene? This will make it impossible to compare\nresults between other studies, and results should be plotted with endpoint copynumbers of titers.\nResponse: Thank you for your comment. According to your suggestion, we have performed\nTCID assays to determine the infectious titer of all samples from our in vitro and in vivo virus\n50\nreplication assays. The added results are now included as Figure 4d (infectious titer from Calu-\n3 cells), Figure 5a (infectious titer from hNECs), and Figure 6c (infectious titer from hamster\nlung tissues).\nFigure 4d. The infectious titer of Omicron sublineages in Calu-3 cells.\nFigure 6c. The infectious titer of Omicron sublineages in hamster lungs.\nMinor points:\nLine 142: this is not strictly immune evasion, but failure of commercial monoclonal antibodies\nto recognize a single epitope. Please rephrase\nResponse: Thank you for pointing this out. We have revised the text accordingly. Line 140:\n“To assess the recognition of the JN.1-derived variants by monoclonal antibodies (mAbs) either\napproved for COVID-19 therapy or currently in development, we performed……”.\nLine 189, “significant antigenic evolution”, based on the antigenic maps fig 2c and d, the actual\nantigenic distance is relatively small ~ 2 fold. Compared to the emergence of omicron, ~ 12\nfold, although there is clear antigenic evolution, the distance in the map appears to be relatively\nsmall (wilk science 2023).\nResponse: Thank you for the insightful comment. In one of our earlier studies (PMID:\n39379369), we compared JN.1 and BA.2 and revealed an antigenic distance of approximately\n3\n2- to 6-fold, which was contributed by over 30 amino acid differences in the spike protein. In\nthe current scenario, we observed an ~2-fold antigenic distance between KP.3.1.1 and JN.1,\nwhich was contributed by only 4 amino acids differences in spike. Therefore, we consider this\ndifference biologically meaningful, albeit relatively small in magnitude.\nIn accordance with your suggestion, we have removed the term “significant” from the sentence\nto ensure precise and accurate communication of our findings. Line 186: “These findings\ndemonstrate that KP.3, KP.3.1.1, and KP.2 have undergone antigenic evolution from their\nparental JN.1 strain, highlighting both their shared antigenic properties and enhanced resistance\nto neutralizing antibodies compared to earlier variants…”.\nHamster experiments: actual copynumbers per gram of tissue should be plotted rather than over\nactin (see previous comment)\nLung titer should be plotted per gram tissue\nResponse: Thank you for your comment. For sgE gene copies, we applied the qRT-PCR\nmethod to detect the cycle threshold (Ct) values of the sgE gene. The relative expression was\ncalculated using the 2−ΔCt method: ΔCt=Ct −Ct . Therefore, under our current setting of\nsgE β-actin\nshowing the relative amount of sgE gene over the house-keeping actin gene, we are unable to\nshow the copynumber of sgE gene per gram of tissue in this experiment.\nFollowing your instruction, we have plotted the infectious titer of Omicron lineages in hamster\nlungs as infectious titer per gram tissue. The revised figure panel is now included as Figure 6c\nof the revised manuscript.\nFigure 6c. The infectious titer of Omicron sublineages in hamster lungs.\nIt would have been good if copynumbers and infectious titers of nasal turbinates would have\nbeen taken along? It’s a bit unclear as the authors did do hNEC cells?\nResponse: Thank you for your important comment. We have indeed harvested nasal turbinate\nsamples from the infected hamsters but did not include the results in the original submission.\nPMID: 36459536; PMID: 35062015), we noticed that while hamster and transgenic mice\nmodels remain as robust models in the assessment of virus replication of Omicron in the lower\nrespiratory tract, the virus replication and transmission of Omicron in the nasal turbinates of\nthese small animals do not completely simulate the gained replication fitness of Omicron\namong humans and the human nasal epithelial cells (PMID: 37579626; PMID: 36893986;\nPMID: 37068258). Because of this observation, we and others have started to focus on using\nhNECs as a model for the assessment of Omicron replication fitness in the human nasal\nturbinates.\nNevertheless, we agree with the Reviewer that virus replication in the nasal turbinates of\ninfected animals remain important, which may provide addition layers of information on the\nvirological features of these Omicron sublineages. To this end, we have now included data on\nthe sgE gene copies and infectious titers in hamster nasal turbinates in the revised manuscript\n(Figure S12).\nFigure S12. The sgE gene copy and infectious titer of Omicron sublineages in hamster nasal\nturbinates.\nAs a comparison some of the earlier variants like Delta should have been taken along to put it\ninto perspective\nResponse: Thank you for your comment. Following your suggestion, we challenged hamsters\nwith the Delta, JN.1, and KP.3.1.1 variants and harvested samples for virological assessments.\nOur results demonstrated that the Delta variant replicated significantly better in hamster lungs\nwhen compared to both JN.1 and KP.3.1.1 (Figure S13), which is in keeping with earlier\nreports from us and others (PMID: 35062016; PMID: 35579953). In contrast, Delta, JN.1, and\nKP.3.1.1 replicated to comparable levels in the nasal turbinates of infected hamsters. As we\nmentioned earlier, the robust transmission and replication efficiency of Omicron and Omicron\nsubvariants are less readily observed in mouse and hamster models, potentially due to\nphysiological differences in the nasal turbinate tissues between humans and rodents. The added\nresults are now included as Supplementary Figure S12 in the revised manuscript.\nReviewer #2 (Remarks to the Author):\nIn this study, Jialu Shi et al. investigate the immunological and virological characteristics of\nJN.1-derived variants circulating in 2024. The focus is on the KP.3.1.1 variant, which harbors\na single deletion in the N-terminal domain of the Spike protein (S31del).\nThe authors observed a reduced activity of the monoclonal antibody Pemivibart against\nKP.3.1.1. Consistent with findings previously published by other groups, they confirm that the\nS31 deletion enhances immune evasion (Jingyi Liu et al., The Lancet Infectious Diseases,\n2025). In agreement with Yu Kakut et al. (The Lancet, 2024), they also report increased viral\nentry in several cell lines.\nThe S31 deletion introduces a glycosylation site that has already been associated with enhanced\nimmune escape (Jingyi Liu et al., The Lancet Infectious Diseases, 2025). Interestingly,\nalthough viral entry is increased in KP.3.1.1, this variant does not exhibit higher replication\nlevels compared to KP.3. The authors identify an additional mutation in Orf1a (S4286C),\nlocated in the region encoding NSP10. This mutation induces a conformational change in\nNSP10 that weakens its interaction with NSP14, resulting in reduced viral fitness.\nOverall, the study is well written and well conducted. While several publications have\npreviously explored the impact of the S31 deletion in the N-terminal domain of the Spike\nprotein, this paper effectively consolidates prior findings and goes further by characterizing the\nKP.3.1.1 variant in more depth—particularly highlighting the impact of the mutation in NSP10.\nSpecific Comments\nFigure 1b: There is no visible variation in the frequency of mutations. Please adjust the color\nscheme to improve clarity.\nResponse: Thank you for your suggestion. We have adjusted the color scheme of Figure 1b to\nenhance the clarity and readability of the presented data.\nto the ancestral spike.\nFigure 1c: This figure does not add any additional information beyond what is shown in Figure\n1b.\nResponse: Thank you for the comment. Following your suggestion, we have moved Figure\n1b (of the original submission) to the supplementary figures to ensure a better logical flow of\nthe main figures.\nFigure 2a: This figure is unclear. The top graphs are missing X-axes. Also, “Antibody\nconcentration (µg/ml)” should be labeled only once for the entire row of graphs.\nResponse: Thank you for pointing this out. We have now added the X-axes label for the top\ngraphs and removed redundant annotations to improve the clarity of the graphs.\nFigure 2b: The data presented are repetitive, with many graphs that are not necessary to convey\nthe key message.\nResponse: Thank you for your suggestion. We have now moved the redundant graphs to\nsupplementary figures to improve the clarity of the main figures.\nFigure 2d: For the antigenic cartography based on hamster data, please clarify which group of\nhamsters (which infection) was used to generate the data.\nResponse: Thank you for the comment. All six hamster infection groups (Figure 2e), each\nexposed to a different viral variant, were included in generating the antigenic map (Figure 2d).\nData from all groups were combined because each virus elicits a distinct immune response in\nimmunologically naïve hamsters. Since the infected animals have clean immune backgrounds\nand were infected with only one variant, the elicited responses can be considered independent\nand antigen-specific. A similar approach was reported in a recent study published in Nature\nCommunications (Tamura et al, Nat Commun, 2023 PMID: 37193706). Thus, incorporating\nall six groups into a single antigenic map enables direct comparison of the viruses’ antigenic\nproperties, with observed neutralization differences reflecting true immunological distances\n7\nbetween variants.\nFigure 4a: For the quantification of cell–cell fusion, it appears that GFP area is being measured.\nPlease either update the Y-axis label accordingly or explain the measurement more clearly in\nthe figure legend.\nResponse: Thank you for your suggestion. You are correct that the GFP area is being measured.\nWe have now provided a detailed description of the quantification methodology in the\ncorresponding figure legend and method section to ensure clarity.\nLegend: Line 1182:” After 24 hours of incubation, images were acquired using microscopy,\nand signal intensity was quantified with ImageJ. For analysis, images were split into RGB\nchannels, and the green channel was…”.\nMethod: Line 797:” The images were processed using ImageJ software by separating the RGB\nchannels, after which the green channel was selected for integrated density measurements. A\nuniform threshold was applied to all cell-cell fusion images to...”.\nFigure 4c: A single graph showing the replication kinetics would be more informative than\nmultiple separate panels.\nResponse: Thank you for your comment. Following your suggestion, we replaced the multiple\nseparate panels with a single graph in Figure 4c. In addition, we added the area under the curve\n(AUC) analysis to demonstrate the total extent of virus replication between 2 to 72 hours post\ninfection. To complement the sgE gene copy, we further added the infectious titer analysis in\nFigure 4d. These results are now included as Figure 4c and 4d of the revised manuscript.\nFigure 4c and 4d. The sgE gene copy and infectious titer of Omicron sublineages from Calu-\n3 cells.\nFigure 5a: The replication kinetics of the different variants (at minimum, KP.3 vs KP.3.1.1)\nshould be assessed in human nasal epithelial cells (hNECs). The authors should quantify viral\nmRNA at the apical side over time to better evaluate viral fitness.\nResponse: Thank you for your comment. Following your suggestion, we quantified the level\n8\nof infectious virus particle production in the apical side of the hNECs from 2 to 96 hours post\ninfection by infectious titer analysis. These results provided added information in the context\nof viral fitness in the hNECs and are now provided as Figure 5a of the revised manuscript.\nFigure 5a. The infectious titer of Omicron sublineages in hNECs.\nFigure 7: It would be interesting to compare the pathogenicity of BA.1 variants with and\nwithout the S31del and/or S4286C mutations.\nResponse: Thank you for your important comment. In Figure 7 of the original submission, we\nintroduced the ORF1a-S4286C mutation into the background of rBA.1 and demonstrated that\nthe presence of ORF1a-S4286C significantly attenuated virus replication in both in vitro and\nin vivo settings.\nFollowing your suggestion, we additionally introduced the spike-S31del change in rBA.1-\nORF1a-S4286C. Our results demonstrated that the spike-S31del change largely rescued the\nattenuated replication fitness caused by rBA.1-ORF1a-S4286C in all evaluated cell types. For\nexample, the infectious titer of rBA.1-ORF1a-S4286C was 16-fold (P=0.0061) lower than that\nof rBA.1 in Calu-3 cells at 72 hours post infection. Introducing the spike-S31del change\nsubstantially rescued virus replication. The infectious titer of rBA.1-ORF1a-S4286C-spike-\nS31del was largely comparable with that of rBA.1 in Calu-3 cells at 72 hours post infection of\n(P=ns) (Figure 7d and 7e). We did not construct the rBA.1-spike-S31del mutant virus to avoid\nthe potential gain-of-function risks. Overall, these results further confirmed the role of spike-\nS31del in enhancing virus replication through promoting virus entry, which offsets the negative\nimpacts of ORF1a-S4286C on virus replication. The added results are now included as Figure\n7d and 7e of the revised manuscript.\nGeneral Comment: The study is overall very compelling, but it is unfortunate that the authors\ndid not include the latest XEC variants, which also harbor N-terminal domain mutations that\nintroduce glycosylation sites.\nResponse: Thank you for your comment. Following your suggestion, we evaluated the immune\nevasion properties of pseudoviruses carrying either KP.3.1.1-spike or XEC-spike against\nconvalescent patient serum. Our results indicated that the XEC-spike pseudovirus exhibited a\nmodest, though not statistically significant, increase in immune evasion when compared to the\nKP.3.1.1-spike pseudovirus (Fig. S3a).\nTo characterize the functional properties of the XEC-spike protein, we further performed\npseudovirus entry assays in Calu-3, Caco-2, 293T, and VeroE6-TMPRSS2 cells. Our results\ndemonstrated that pseudoviruses bearing the XEC-spike protein exhibited significantly\nenhanced entry efficiency when compared to those carrying the JN.1-spike in Caco-2, 293T,\nand VeroE6-TMPRSS2 cells. A similar trend was observed for Calu-3 cells but was not\nstatistically significant (Fig. S3b). However, the level of entry enhancement mediated by the\nXEC-spike was in general less pronounced than that observed with the KP.3.1.1-spike (Fig.\nS3b). We have now included these findings in Supplementary Figure 3 of the revised\nmanuscript.\nReviewer #3 (Remarks to the Author):\nIn this manuscript entitled “Intrinsic pathogenicity, virological features, and immune evasion\nof SARS-CoV-2 JN.1-derived variants including JN.1.7, KP.2, KP.3, and KP.3.1.1”. Chu et al.\ninvestigated the in vitro and in vivo virological features of KP.3.1.1, with comparative analyses\nincluding JN.1.7, KP.2, and KP.3. The authors employed a comprehensive set of experimental\napproaches, including in vitro neutralization assays, structural biology, a human nasal epithelial\ncell (hNEC) model and a golden hamster infection model, to evaluate immune evasion, cell-\nentry efficiency, ACE2-binding affinity, pathogenicity in animal, and the impact of the ORF1a-\nS4286C mutation on viral replication. However, I must advise editor to consider the following\npoints before making decisions.\nFirst, there are significant discrepancies among the experimental findings that the authors have\nnot sufficiently addressed or reconciled. For instance, in the cell–cell fusion assay, KP.3.1.1\nexhibits lower fusion efficiency than JN.1, yet the S31del mutation - unique to KP.3.1.1\ncompared with KP.3 - appears to have no notable effect on fusion. In contrast, the pseudovirus\nentry assays in 293T, Calu-3, Caco-2, and VeroE6-TMPRSS2 cells attribute KP.3.1.1’s\nincreased infectivity to S31del.\nResponse: Thank you for raising this important point. As also pointed out by the Reviewer,\none of the strengths of the current study is that a comprehensive set of experimental approaches\nwere employed to understand the ongoing evolution of SARS-CoV-2. Comparing and\ncontrasting information obtained from all the different assays will allow us to derive the most\nscientifically correct answer for a holistic assessment of the lineages and mutations being\n11\nstudied.\nThe cell-cell fusion assay is a classic experiment that measures the fusion capacity of viral\nspike proteins when expressed on the surface of cells. It provides focused information on the\nfusogenicity as well as the efficiency of mediating cell-cell spread by the spike proteins under\ninvestigation. However, since the spike proteins are overexpressed on the plasma membrane of\ncells, their densities are often higher than what are naturally present on the virus particles,\nwhich may confound the observed phenotypes.\nThe pseudovirus entry assay is another commonly used experiment that simulates the process\nof virus entry including attachment, receptor engagement, conformational change of spike,\nprotease cleavage, fusion, and delivery of the viral genome into the cytoplasm. It provides a\ncomplete and holistic view of the infectious entry process that mimics the natural cell-free\ninfection of coronaviruses.\nThe data from these two assays are highly complementary. In the present case, analysis of\nfindings from the two assays indicates that the observed phenotype on the gained infectivity of\nKP.3.1.1 is likely not due to changes in fusogenicity of the KP.3.1.1 spike protein but due to\nother properties of the KP.3.1.1 virus particle during virus entry.\nSince the two assays address different core questions, it is not uncommon that the phenotype\nobtained from the two assays are different. For example: (1) Introducing the spike NTD F59S\nchange in the background of KP.3 spike does not alter the fusion capacity of KP.3 spike but\nincreased the infectivity of KP.3 spike pseudovirus particles (Li et al, J Virol, 2025, PMID:\n40135879). (2) BA.2.12.1 spike-mediated cell-cell fusion is significantly less efficient when\ncompared to BA4/5 spike-mediated cell-cell fusion in A549-ACE2 cells. Nevertheless, in\npseudovirus entry assays, they entered A549-ACE2 at the same efficiency (Hoffman et al, Nat\nCommun, 2023, PMID: 37311762).\nBecause of the important and complementary nature of the two experiments, they are often\napplied consecutively to assess the entry properties of variants and mutations. Comparing and\ncontrasting results obtained from the two assays together will provide a better overall\nknowledge related to the entry process.\nMoreover, the pseudovirus results conflict with authentic virus infection outcomes in hNECs.\nThese inconsistencies are not discussed in the manuscript. Instead, the authors use\npseudoviruses of BA.2, XBB.1, and JN.1—with or without S31del—to argue that S31del\nindependently enhances spike-mediated infectivity, which is logically unconvincing without\nfurther validation. In evaluating intrinsic pathogenicity, the authors report similar lung viral\nloads, antigen expression, and histopathological features in hamsters infected with KP.3,\nKP.3.1.1, and JN.1. These in vivo results do not align with the in vitro findings. Yet, no\ndiscussion or proposed mechanisms are provided to reconcile these discrepancies. How should\nthese divergent findings be interpreted in a coherent framework?\nResponse: Thank you for your comment on this important message of the manuscript. In\nS31del change in KP.3.1.1 results in significantly increased infectivity of pseudoviruses when\ncompared to KP.3 in in vitro settings. Intriguingly, the elevated infectivity did not translate into\ngained replication fitness of KP.3.1.1 when compared with KP.3 in Calu-3 cells, hNECs, and\nhamsters in in vivo settings, which we reported in Figure 4, Figure 5, and Figure 6 of the\noriginal submission.\nBecause of this interesting observation, we conducted amino acid sequence alignment between\nKP.3 and KP.3.1.1. We found that other than the spike-S31del change, KP.3.1.1 only differs\nfrom KP.3 at one other site, which is the ORF1a-S4286C mutation. Therefore, we speculate\nthat the ORF1a-S4286C mutation may act to counterbalance the increased infectivity conferred\nby the spike-S31del change in the context of authentic viral replication.\nTo test this hypothesis, we introduced the ORF1a-S4286C mutation into the rBA.1 backbone\nwith reverse genetics and demonstrated that rBA.1-ORF1a-S4286C replicated less efficiently\nwhen compared to rBA.1 both in vitro and in vivo settings, confirming the role of ORF1a-\nS4286C as a mutation that reduces viral replication fitness. This finding supports the notion\nthat ORF1a-S4286C acts as a fitness-cost mutation that offsets the gained infectivity conferred\nby spike-S31del in KP.3.1.1 live virus, which explained the comparable replication of KP.3.1.1\nand KP.3 across different models. These results were reported in Figure 7 and discussed in\nLine 412-426 of the original submission.\nIn the revised manuscript, we further introduced the spike-S31del change in rBA.1-ORF1a-\nS4286C. Our results demonstrated that the spike-S31del change largely restored the attenuated\nreplication fitness caused by rBA.1-ORF1a-S4286C in all evaluated cell types. For example,\nthe infectious titer of rBA.1-ORF1a-S4286C was 16-fold (P=0.0061) lower than that of rBA.1\nin Calu-3 cells at 72 hours post infection. Introducing the spike-S31del change substantially\nrescued virus replication. The infectious titer of rBA.1-ORF1a-S4286C-spike-S31del was\nlargely comparable with that of rBA.1 in Calu-3 cells at 72 hours post infection of (P=ns)\n(Figure 7d and 7e). Overall, these results further confirmed the role of spike-S31del in\nenhancing virus replication through promoting virus entry, which offsets the negative impacts\nof ORF1a-S4286C on virus replication. The opposing effects of spike and non-spike mutations\nhighlight the complex interplay of viral genomic elements in shaping their overall fitness\noutcomes. The added results are now included as Figure 7d and 7e of the revised manuscript.\nSecond, in the “Receptor interaction” section, although the authors resolved high-resolution\nstructures of the KP.2 spike-ACE2 complex and the KP.3.1.1 spike trimer, and identified a\nnovel glycosylation site introduced by the S31del mutation, they fail to clarify how this\nstructural feature contributes to immune evasion or infectivity. The manuscript lacks a clear\nfunctional link between structural observation and virological consequences, and no\nmechanistic hypotheses or validation experiments are proposed.\nResponse: Thank you for these valuable comments.\n(i) Following your suggestion to clarify how S31del contributes to immune evasion, we further\ninvestigated the structural basis of NTD-directed antibody recognition against the KP.3.1.1\nspike protein. The S31 deletion facilitates a novel glycosylation event at the N30 site and\ninduces a conformational rearrangement of residue F32, both of which are situated within the\npreviously characterized antigenic site vi (PMID: 33761326). This region is known to be\ntargeted by multiple antibodies, including C1717 (PMID: 35447092), DH1052 (PMID:\n34242577), S2M24 (PMID: 33761326), and polyclonal Fabs COV57 (PMID: 32645326).\nSince high-resolution structural data are currently limited to C1717 and DH1052, we performed\nstructural superposition of the KP.3.1.1 NTD onto these known antibody-complex structures to\nevaluate potential steric or electrostatic conflicts (Figure 3i).\nA close-up structural analysis of the spike-Fab interface revealed that the newly acquired N30\nglycan would sterically clash with residue I57 of the C1717 heavy chain, likely disrupting\nantibody binding. Similarly, for DH1052, key residues including S31 and Y32 in the light chain,\nas well as Y100H and H100I in the heavy chain, would experience steric hindrance from the\nN30 glycosylation (Figure 3i). These structural observations suggest that the S31del change in\nKP.3.1.1 spike facilitates immune evasion by introducing glycosylation-mediated steric\ninterference, thereby impairing the recognition and binding of NTD-targeting antibodies such\nas C1717 and DH1052.\nDH1052 antibody.\nTo experimentally validate the impact of N30 glycosylation on antibody neutralization, we\nperformed pseudovirus-based neutralization assays using four spike-NTD-targeting antibodies,\nincluding 4-18, 4-19, C1717, and DH1052. The latter two can bind the N30 site and are likely\naffected by glycosylation at this position. We carried out neutralization assays using KP.3 and\nKP.3.1.1 spike pseudoviruses. Our results showed that antibodies 4-18 and 4-19 retained\nactivity against KP.3, with IC₅₀ values of 2.315 μg/mL and 4.050 μg/mL, respectively, and\nshowed comparable neutralization against KP.3.1.1, although 4-19 exhibited a moderate\nreduction in potency. In contrast, DH1052 and C1717 showed markedly reduced neutralization\nagainst KP.3.1.1 (IC₅₀ = 6.516 μg/mL and 3.876 μg/mL) compared with KP.3 (IC₅₀ = 1.221\nμg/mL and 0.035 μg/mL, respectively), confirming that the S31 deletion in the spike protein\nconfers substantial immune evasion (Figure 3j and 3k).\nNext, we introduce the N30A mutation in the background of KP.3.1.1 spike to abolish the N30\nglycosylation. Similarly, N30A was introduced in the background of KP.3 as a control. We\nevaluated the neutralization activity of C1717 against KP.3-N30A and KP.3.1.1-N30A\npseudoviruses. In the KP.3 background, C1717 maintained a robust activity against the KP.3-\nN30A pseudovirus (IC₅₀ = 0.033 μg/mL), with IC₅₀ value comparable to that against the wild-\ntype KP.3 pseudovirus (IC₅₀ = 0.035 μg/mL). Interestingly, in the KP.3.1.1 background, the\nN30A mutation renders the KP.3.1.1-N30A pseudovirus highly susceptible to C1717\nneutralization (IC₅₀ = 0.053 μg/mL), which is an over 70-fold difference when compared to the\nwild-type KP.3.1.1 pseudovirus (IC₅₀ = 3.876 μg/mL) (Figure 3j and 3k).\nOverall, these validation experiments confirm that the S31 deletion and the consequent N30\nglycosylation significantly enhance immune evasion by interfering with antibody binding,\nthereby supporting the structural and functional role of this modification in facilitating immune\nescape.\n(ii) Next, we further investigated how S31del contributes to increased infectivity.\nIn the original submission, we have tackled this question using a series of different approaches:\n(a) First, we compared cell-cell fusion between KP.3.1.1 spike and KP.3 spike. We showed that\nthe two spike proteins induced fusion at similar efficiency, suggesting that S31del does not\npromote infectivity through increasing the fusion capacity of spike proteins (Figure 4a).\n(b) Second, we determined the binding affinity of the KP.3.1.1 spike and KP.3 spike to human\nACE2 with SPR experiments. Our result revealed that the binding affinity of KP.3.1.1 spike to\nhACE2 was slightly reduced when compared to that of the KP.3 spike. This finding suggests\nthat the S31del mutation does not enhance infectivity through strengthening receptor binding\n(Supplementary Figure 4).\n(c) Third, we assessed the spike cleavage of KP.3.1.1 and KP.3. We found that the two viruses\nhave largely comparable spike cleavage at the S1/S2 furin cleavage site, suggesting that the\nincreased infectivity is not due to changes in spike cleavage efficiency (Figure 5c).\n(d) Forth, we analyzed the transmembrane serine protease and cathepsin usage of KP.3.1.1 and\nKP.3 spike pseudoviruses. We found that the S31del in KP.3.1.1 does not result in increased\ntransmembrane serine protease and cathepsin usage by KP.3.1.1, suggesting that the increased\ninfectivity is not due to changes in transmembrane serine protease and cathepsin usage\n(Supplementary Figure 7).\nDuring the revision of the manuscript, we further investigated this question with additional\nassays:\n(e) Fifth, in the revised manuscript, we further evaluated the potential role of additional\nproteases in mediating the entry of KP.3.1.1 spike. We reported earlier that in addition to\ntransmembrane serine proteases and cathepsins, members of the matrix metalloproteinase\n(MMP) family and the a disintegrin and metalloproteinase (ADAM) protease family can also\nfacilitate Omicron entry (PMID: 36662861). To evaluate if KP.3.1.1 and KP.3 differentially\nutilized MMPs and ADAMs for entry, we overexpressed multiple proteases from the MMP\nfamily (MMP14, MMP15, MMP16, MMP17, MMP24, MMP25) and the ADAM family\n16\n(ADAM8, ADAM10, ADAM12, ADAM15, ADAM17, ADAM19, ADAM33) in 293T-ACE2\ncells and measured pseudovirus entry efficiency for both KP.3 and KP.3.1.1 pseudoviruses. Our\nresults revealed no significant difference in KP.3.1.1 spike-mediated entry relative to the KP.3\nspike across any of the tested MMPs and ADAMs, indicating that the observed increase in\ninfectivity is not attributable to altered protease usage or processing (Supplementary Figure\n8).\nSupplementary Figure 8. KP.3 and KP.3.1.1 pseudovirus usage of MMP and ADAM family\nmembers.\n(f) Sixth, based on our structural experiment and analysis, we found that the N30 glycosylation\nis the most significant change induced by the S31 deletion in spike. To evaluate if the N30\nglycosylation contributes to enhanced pseudovirus entry, we introduced an N30A substitution\ninto both KP.3 and KP.3.1.1 spike plasmids to abolish glycosylation at this site and produced\ncorresponding pseudoviruses. We compared the entry efficiency of KP.3, KP.3+N30A, KP.3.1.1,\nand KP.3.1.1+N30A pseudoviruses in 293T, Calu-3, and Caco-2 cells. Our result demonstrated\nthat the entry efficiency of the KP.3+N30A pseudovirus was comparable to that of the KP.3\npseudovirus in 293T and Caco-2 cells. Importantly, KP.3.1.1+N30A pseudovirus entry was also\nsimilar to that of the KP.3.1.1 pseudovirus in 293T and Caco-2 cells, which remained\nsignificantly higher than that of the KP.3+N30A pseudovirus. This result indicates that the\nenhanced infectivity of KP.3.1.1 spike is not primarily mediated by N30 glycosylation\n(Supplementary Figure 9). Interestingly, the N30A mutation in the background of both KP.3\nand KP.3.1.1 substantially reduced virus infectivity in Calu-3 cells, suggesting that this\nmutation is not tolerated by the two viral spike proteins for Calu-3 cell entry.\nspike N30A substitution.\n(g) Seventh, we evaluated whether spike-S31del change might enhance spike protein\nexpression, thereby increasing the infectivity of both authentic KP.3.1.1 virus and\ncorresponding pseudoviruses. To test this hypothesis, we transfected 293T cells with four pairs\nof spike plasmids, including the spike from BA.2, BA.2+S31del, XBB.1, XBB.1+S31del, JN.1,\nJN.1+S31del, KP.3, and KP.3+S31del (KP.3.1.1). We quantified the total and cell surface\nexpression level of the spike proteins with flow cytometry at 24 hours post transfection.\nInterestingly, we found that the S31del change increased both the total and cell surface\nexpression level when it is introduced in the background of all four spike proteins\n(Supplementary Figure 10 and Supplementary Figure 11). A higher spike expression level\nis known to both increase the amount of virus particle production, as well as increase the\ninfectivity of the assembled virus particles. Together, these results suggest that the S31 deletion\nin KP.3.1.1 spike likely promoted infectivity through increasing the spike expression level.\nS31del.\nFurthermore, the neutralization assays only assess antibodies targeting the RBD, yet the authors\nsuggest that S31del in the NTD alters neutralization sensitivity. How do the authors justify this\nclaim without testing neutralizing antibodies against the NTD?\nResponse: Thank you for your comment. To directly assess whether the S31del change in the\nNTD of the spike protein alters neutralization sensitivity, we performed pseudovirus-based\n20\nneutralization assays using four spike-NTD-targeting antibodies, including 4-18, 4-19, C1717,\nand DH1052. The latter two can bind the N30 site and are likely affected by glycosylation at\nthis position. We carried out neutralization assays using KP.3 and KP.3.1.1 spike pseudoviruses.\nOur results showed that antibodies 4-18 and 4-19 retained activity against KP.3, with IC₅₀\nvalues of 2.315 μg/mL and 4.050 μg/mL, respectively, and showed comparable neutralization\nagainst KP.3.1.1, although 4-19 exhibited a moderate reduction in potency. In contrast, DH1052\nand C1717 showed markedly reduced neutralization against KP.3.1.1 (IC₅₀ = 6.516 μg/mL and\n3.876 μg/mL) compared with KP.3 (IC₅₀ = 1.221 μg/mL and 0.035 μg/mL, respectively),\nconfirming that the S31 deletion in the spike protein confers substantial immune evasion\n(Figure 3j and 3k).\nNext, we introduce the N30A mutation in the background of KP.3.1.1 spike to abolish the N30\nglycosylation. Similarly, N30A was introduced in the background of KP.3 as a control. We\nevaluated the neutralization activity of C1717 against KP.3-N30A and KP.3.1.1-N30A\npseudoviruses. In the KP.3 background, C1717 maintained a robust activity against the KP.3-\nN30A pseudovirus (IC₅₀ = 0.033 μg/mL), with IC₅₀ value comparable to that against the wild-\ntype KP.3 pseudovirus (IC₅₀ = 0.035 μg/mL). Interestingly, in the KP.3.1.1 background, the\nN30A mutation renders the KP.3.1.1-N30A pseudovirus highly susceptible to C1717\nneutralization (IC₅₀ = 0.053 μg/mL), which is an over 70-fold difference when compared to the\nwild-type KP.3.1.1 pseudovirus (IC₅₀ = 3.876 μg/mL) (Figure 3j and 3k).\nOverall, these validation experiments confirm that the S31 deletion and the consequent N30\nglycosylation significantly enhance immune evasion by interfering with antibody binding,\nthereby supporting the functional role of this spike NTD modification in facilitating immune\nescape.\nFigure 3j and 3k. S31del facilitates immune evasion of spike-NTD antibodies.\nThird, given the aforementioned inconsistencies, the conclusion that the ORF1a S4286C\nmutation impacts viral replication remains speculative and unsupported. The manuscript does\nnot clearly explain how the observed phenotypic effects were attributed specifically to the\nORF1a region, nor how alternative explanations or confounding variables were excluded. As\nit stands, this conclusion lacks a solid logical and experimental foundation.\nResponse: Thank you for your comment. The conclusion that the ORF1a S4286C mutation\nimpacts viral replication came from our reverse genetics experiment. In this experiment, we\n21\nintroduced the ORF1a-S4286C mutation into the rBA.1 backbone with reverse genetics and\ndemonstrated that rBA.1-ORF1a-S4286C replicated less efficiently when compared to rBA.1\nboth in vitro and in vivo settings, confirming the role of ORF1a-S4286C as a mutation that\nreduces viral replication fitness. This finding supports the notion that ORF1a-S4286C acts as\na fitness-cost mutation that offsets the gained infectivity conferred by spike-S31del in KP.3.1.1\nlive virus, which explained the comparable replication of KP.3.1.1 and KP.3 across different\nmodels. These results were reported in Figure 7 of the original submission.\nIn the revised manuscript, we further introduced the spike-S31del change in rBA.1-ORF1a-\nS4286C. Our results demonstrated that the spike-S31del change largely rescued the attenuated\nreplication fitness caused by rBA.1-ORF1a-S4286C in all evaluated cell types. For example,\nthe infectious titer of rBA.1-ORF1a-S4286C was 16-fold (P=0.0061) lower than that of rBA.1\nin Calu-3 cells at 72 hours post infection. Introducing the spike-S31del change substantially\nrescued virus replication. The infectious titer of rBA.1-ORF1a-S4286C-spike-S31del was\nlargely comparable with that of rBA.1 in Calu-3 cells at 72 hours post infection of (P=ns)\n(Figure 7d and 7e). Overall, these results further confirmed the role of spike-S31del in\nenhancing virus replication through promoting virus entry, which offsets the negative impacts\nof ORF1a-S4286C on virus replication. The opposing effects of spike and non-spike mutations\nhighlight the complex interplay of viral genomic elements in shaping their overall fitness\noutcomes.\nThese added results are now included as Figure 7d and 7e of the revised manuscript. We hope\nthat the explanations and added experiments can help to clarify the logical and experimental\nfoundation of our manuscript.\nFigure 7d and 7e. The impact of ORF1a-S4286C and spike-S31del on rBA.1 replication.\n22"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have adequately addressed my comments and concerns, and the manuscript is now suitable for publication.\nno further comments or concerns.", "reviewer_2": "I have taken note of the authors' revisions. They have addressed all my comments. The results are presented more clearly, and additional experiments have been included to answer the questions raised. I have no further questions or suggestions.", "reviewer_3": "Dear Editor,\nThe authors have addressed most of the concerns raised in the first round and provided supporting data for the majority of points. A few issues remain that should be resolved.\nIn response to Question 1, the authors attribute the increased infectivity of KP.3.1.1 to “other properties of the virus particle” but do not specify which properties or cite supporting evidence.\nIn addition, the manuscript contains inconsistent labeling of the same substitution: in some sections it is described as ORF1a-S4286C, while in others it appears as NSP10 S33C."}, "author_response": "Response: Thank you for the comment. To investigate the mechanism underlying the enhanced\ninfectivity of the KP.3.1.1 spike compared to the KP.3 spike, we compared several virological\nproperties, including fusogenicity (Fig. 4a), spike-receptor binding affinity (Supplementary\nFig. 4), spike cleavage efficiency (Fig. 5c), protease usage (Supplementary Fig. 7 and\nSupplementary Fig. 8), and the effect of N30 glycosylation on pseudovirus entry\n(Supplementary Fig. 9). However, none of these assays revealed significant differences\nbetween the KP.3.1.1 and KP.3 spikes.\nSubsequently, we employed flow cytometry to evaluate spike protein expression to determine\nwhether the S31del mutation influences protein expression levels (Supplementary Fig. 10 and\nall exhibited increased expression both on the cell surface and intracellularly following the\nintroduction of the S31del mutation. This finding indicates that the S31del mutation enhances\nthe infectivity of the KP.3.1.1 spike by upregulating spike protein expression. Thus, we\nconclude that the elevated infectivity of the KP.3.1.1 spike is attributable to the S31del mutation,\nwhich augments spike protein expression both on the cell surface and within the cell.\nIn the revised text, we have clarified these findings in the Result section (line 398-408) and the\nDiscussion section (lines 496–501). Overall, these findings reaffirm the pivotal role of the\nS31del mutation in concurrently augmenting both immune evasion and infectivity of the\nKP.3.1.1 spike.\nIn addition, the manuscript contains inconsistent labeling of the same substitution: in some\nsections it is described as ORF1a-S4286C, while in others it appears as NSP10 S33C.\nResponse: Thanks for the comment. To enhance the clarity of the manuscript, the designation\nORF1a-S4286C has been consistently replaced with NSP10-S33C throughout the text and\nfigures, except in instances where both terms are used together to indicate the genomic location\nof this mutation within the full viral genome.\n2"}]

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