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Journal of Molecular Cell Biology logoLink to Journal of Molecular Cell Biology
. 2025 Dec 23;18:mjaf055. doi: 10.1093/jmcb/mjaf055

CD46 regulates hepatitis B virus entry by modulating cell-surface NTCP levels through cis-interaction

Kei Miyakawa 1,2,3,4,✉, Yusuke Nakai 5, Taichi Kameya 6,7, Hironori Nishitsuji 8, Koichi Watashi 9, Makoto Takeda 10, Tsukasa Seya 11, Kunitada Shimotohno 12, Yayoi Kimura 13, Akihide Ryo 14,15,✉
Editor: Xuebiao Yao
PMCID: PMC13424813  PMID: 41432296

Abstract

Hepatitis B virus (HBV) infection remains a major global health challenge. While sodium taurocholate co-transporting polypeptide (NTCP) is the primary receptor for HBV entry, the molecular mechanisms regulating NTCP-mediated viral entry remain incompletely understood. Here, we identified CD46 as a crucial regulatory factor for NTCP membrane expression. We found that CD46 interacted with NTCP in cis at the plasma membrane through proximity-based labeling screening. The depletion of CD46 significantly reduced cell-surface NTCP levels and HBV infection in hepatocytes. Anti-CD46 monoclonal antibodies, particularly clone E4.3, inhibited HBV infection by triggering NTCP internalization from the plasma membrane to intracellular vesicles. The antiviral effect of CD46 antibodies was also confirmed in primary human hepatocytes. Our study reveals a previously unknown mechanism regulating NTCP-mediated HBV entry and suggests CD46 as a potential therapeutic target for HBV infection.

Keywords: hepatitis B virus (HBV), sodium taurocholate co-transporting polypeptide (NTCP), proximity-based labeling, viral entry

Introduction

Hepatitis B virus (HBV) infection remains a major global health challenge, with chronic infection leading to severe complications including cirrhosis and hepatocellular carcinoma (HCC) (Schweitzer et al., 2015; Revill et al., 2019). Recent World Health Organization data highlight the magnitude of this challenge: ∼296 million people were living with chronic HBV infection in 2019, with 1.5 million new cases reported annually. Despite the availability of effective vaccines, HBV continues to pose a significant burden, particularly in Asia and Africa, where infection rates remain high.

The process of HBV entry into hepatocytes begins with the virus binding to cell-surface heparan sulfate proteoglycans (Schulze et al., 2007; Leistner et al., 2008; Herrscher et al., 2020). This initial attachment is stabilized by additional host factors, including glypican-5 and α3β1 integrin, which form a complex with these proteoglycans. The viral envelope proteins, particularly hepatitis B surface antigen (HBsAg), then engage with cellular receptors on the hepatocyte membrane. The key receptor mediating HBV entry is sodium taurocholate co-transporting polypeptide (NTCP), which is specifically expressed on hepatocytes (Schulze et al., 2007; Leistner et al., 2008; Yan et al., 2012; Konig et al., 2014). The preS1 region of the HBV large envelope protein directly interacts with NTCP to initiate virus–host engagement (Watashi and Wakita, 2015; Lin et al., 2020). This interaction is finely regulated by post-translational modifications of NTCP, particularly its glycosylation and phosphorylation states (Zakrzewicz et al., 2022), which trigger conformational changes in the viral envelope necessary for entry.

Following NTCP binding, HBV enters hepatocytes through clathrin-mediated endocytosis (Macovei et al., 2010; Herrscher et al., 2020). The internalized virus travels through the endosomal network, where vesicle maturation and fusion events occur sequentially. Within the acidic endosomal environment, the viral envelope proteins undergo critical conformational changes that enable viral nucleocapsid release into the cytoplasm (Herrscher et al., 2020). This escape from endosomes involves a complex mechanism where pH-dependent changes in the S protein expose a fusion peptide, facilitating viral–endosomal membrane fusion. Upon reaching the nucleus, the viral genome establishes itself as a stable episome, forming covalently closed circular DNA (cccDNA). This cccDNA then serves as the template for viral RNA synthesis, generating both pregenomic RNA and various subgenomic RNAs (Gunther et al., 1997; Wang et al., 2016), which direct the production of viral proteins essential for replication.

Understanding the intricacies of HBV entry into hepatocytes, particularly the interaction with NTCP, has provided valuable insights into the development of potential antiviral therapies. However, direct targeting of NTCP presents significant challenges due to its essential physiological role in bile acid transport (Li et al., 2024), necessitating the identification of alternative therapeutic targets within the NTCP-associated protein complex. In this study, we performed comprehensive screening of NTCP-interacting partners and identified CD46 as a novel regulator of NTCP-mediated HBV entry. Our findings not only reveal a previously unknown mechanism of HBV entry regulation but also suggest potential therapeutic strategies targeting CD46–NTCP interactions.

Results

Identification of NTCP partners by proximity-based labeling

To identify cellular proteins interacting with NTCP in hepatocytes, we performed an antibody-based in situ biotinylation assay (Bar et al., 2018; Noguchi et al., 2024) using HepG2-iNTCP cells (Figure 1A; Miyakawa et al., 2018). The cells were treated with doxycycline (Dox) to express NTCP (Figure 1B) followed by fixation, and then both NTCP-specific antibodies and horseradish peroxidase (HRP)-conjugated secondary antibodies were added. Cellular proteins spatially proximal to the NTCP were labeled with biotin by adding biotin-phenol and H2O2. We detected multiple bands corresponding to protein biotinylation in Dox-treated cells but not in Dox-untreated cells (Figure 1C), suggesting that only the host proteins proximal to NTCP were biotin-labeled by anti-NTCP antibody. Subsequently, streptavidin purification and mass spectrometry (MS) were performed. By repeating this process three times, we identified a total of 101 proteins detected exclusively in Dox-treated cells as candidate interaction partners of NTCP. There were 23 proteins that were identified in at least two replicates (Figure 1D). Among these, we focused on CD46, a membrane-localized protein whose expression has been associated with HBV-positive HCC (Kinugasa et al., 1999; Liu et al., 2020).

Figure 1.

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Identification of NTCP-interacting factors through proximity-based labeling. (A) Schematic representation of the antibody-based in situ biotinylation assay used to identify NTCP-interacting proteins. HepG2-iNTCP cells were treated with Dox to induce NTCP expression, followed by incubation with anti-NTCP antibody and HRP-conjugated secondary antibody. Biotin-phenol and H2O2 were added to label proteins proximal to NTCP. (B) Western blot analysis confirming Dox-induced NTCP expression in HepG2-iNTCP cells. Cells were treated with or without Dox (1 μg/ml) for 48 h. (C) Detection of biotinylated proteins. Cells were treated as described in A, and biotinylated proteins were visualized using streptavidin-HRP. (D) Proteins identified in at least two experiments are listed with their gene names and frequency of detection. A total of 101 proteins were detected across all experiments, with 23 proteins identified in two or more independent experiments.

CD46 interacts with NTCP in cis

To confirm whether CD46 interacts with NTCP in hepatocytes, we performed immunoprecipitation (IP) analysis of HepG2 cells and found that CD46 can interact with NTCP (Figure 2A). Immunofluorescence analysis revealed that both proteins co-localized at the plasma membrane (Figure 2B). We performed a NanoLuc-based bioluminescence resonance energy transfer (NanoBRET) assay, a quantitative protein–protein interaction analysis in living cells (Machleidt et al., 2015; Stoddart et al., 2015). Our results showed that CD46 indeed interacts with NTCP in living cells (Figure 2C). We used a luminescence microscopy and found that the NanoBRET signals derived from the CD46–NTCP interaction were detected mainly at the plasma membrane (Figure 2C). Indeed, a CD46 mutant lacking the transmembrane domain, referred to as CD46(ΔTM), showed reduced binding activity to NTCP compared to wild-type CD46 (Figure 2D). We used AlphaFold2 to predict potential interaction interfaces between CD46 and NTCP. The predicted model indicated that CD46 interacts with NTCP in cis (i.e. both proteins on the same cell membrane) at their transmembrane domains (Figure 2E). Analysis of the affinity between CD46 and NTCP using PDBePISA revealed that the solvation free energy gain (ΔG) upon interface formation was −26.6 kcal/mol, suggesting a very strong interaction between these proteins. Based on the predicted interaction interface, we introduced alanine substitutions at key residues within the transmembrane regions of NTCP (I30A, F33A, F37A, I193A, I194A, I197A, and L205A) (Supplementary Figure S1A). NanoBRET analysis revealed that these mutations significantly reduced the CD46–NTCP interaction (Supplementary Figure S1B). These results indicate that CD46 and NTCP can associate in cis at the plasma membrane.

Figure 2.

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Physical interaction between CD46 and NTCP. (A) Co-IP analysis of CD46 and NTCP interaction. HepG2 cells expressing NTCP-Myc were immunoprecipitated with anti-Myc antibodies, followed by western blot analysis. (B) Immunofluorescence microscopy showing co-localization of NTCP (green) and CD46 (red) at the plasma membrane. Nuclei were stained with DAPI (blue). Arrowheads indicate co-localized signals. The co-localization coefficient (Pearson’s correlation) is shown. Scale bar, 10 μm. (C) NanoBRET analysis showing the CD46–NTCP interaction in living cells. Left: quantification of NanoBRET signals. ****P < 0.0001 compared to CD46-NL alone. Right: representative luminescence microscopy images showing the spatial distribution of the CD46–NTCP interaction. Scale bar, 10 μm. (D) Co-IP analysis of CD46(WT) and CD46(ΔTM) with NTCP-Myc. HepG2 cells were co-transfected with NTCP-Myc and either CD46(WT) or CD46(ΔTM), followed by IP with anti-Myc antibodies and western blot analysis. (E) AlphaFold2-predicted structure of the CD46–NTCP complex, highlighting the transmembrane region interaction. PDBePISA analysis revealed strong thermodynamic favorability for the interaction (ΔG = −26.6 kcal/mol).

CD46 regulates cell-surface NTCP expression

To determine whether CD46 regulates the expression of NTCP, we next examined NTCP mRNA and protein levels in CD46-depleted cells. When siRNAs targeting CD46 or NTCP genes were added to HepG2-NTCP-C4 cells (Iwamoto et al., 2014), each siRNA was found to be able to specifically knock down its target gene (Figure 3A). We then examined the protein levels of NTCP and CD46 by western blot analysis and found that knockdown of CD46 resulted in a slight decrease in the amount of NTCP (Figure 3B). Flow cytometric analysis showed that CD46 knockdown and NTCP knockdown reduced cell-surface NTCP expression to similar levels (Figure 3C). Consistent with these results, immunostaining of CD46-knockdown cells revealed that the predominant localization of NTCP shifted from the membrane to the cytoplasm (Supplementary Figure S2A). Meanwhile, we confirmed that the knockdown of NTCP had no effect on the total and cell-surface expression of CD46 (Figure 3B and D). Although epidermal growth factor receptor (EGFR) is known as a co-factor for NTCP (Iwamoto et al., 2019), the total amount and membrane expression of EGFR were not affected in CD46-depleted cells (Supplementary Figure S2B). These results suggest that CD46 plays a role in maintaining NTCP at the plasma membrane.

Figure 3.

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CD46 regulates cell-surface expression of NTCP. (A) RT-qPCR analysis showing specific knockdown of CD46 and NTCP by their respective siRNAs in HepG2-NTCP-C4 cells. Data are presented as mean ± SD (n = 3). ****P < 0.0001 compared to control siRNA (siCtrl). (B) Western blot analysis of total NTCP and CD46 protein levels in cells treated with control, CD46, or NTCP siRNAs. Left: representative immunoblots. Cell lysates were treated with PNGase F to remove N-glycans prior to analysis. Right: densitometric quantification of protein levels normalized to tubulin. Data are presented as mean ± SD (n = 3). **P < 0.01, ****P < 0.0001 compared to siCtrl. (C) Flow cytometry analysis of cell-surface NTCP expression in control, NTCP-knockdown, and CD46-knockdown cells. Left: representative histograms. Right: quantification of mean fluorescence intensity (n = 3). **P < 0.01, ****P < 0.0001 compared to siCtrl. (D) Flow cytometry analysis of cell-surface CD46 expression in control, NTCP-knockdown, and CD46-knockdown cells. Left: representative histograms. Right: quantification of mean fluorescence intensity (n = 3). ***P < 0.0001 compared to siCtrl.

CD46 contributes to efficient HBV infection

To determine whether CD46 affects HBV infection, we used the CRISPR/Cas9 system to generate HepG2-NTCP-C4 cells lacking CD46 (CD46-KO cells) and confirmed that these cells do not express CD46 (Figure 4A). Furthermore, CD46-KO cells showed reduced cell-surface NTCP expression as well as decreased total NTCP levels (Figure 4A; Supplementary Figure S3A). We next examined the binding activity of FITC-conjugated HBV PreS1 peptide to HepG2-NTCP cells and observed reduced accumulation of PreS1 peptide at the plasma membrane of CD46-KO cells compared to the parental HepG2-NTCP-C4 cells (Figure 4B). We infected these cells with the HBV that encodes a secreted luciferase reporter gene (HBV-secNL) (Nishitsuji et al., 2018) to assess HBV entry efficiency. The results indicated that HBV susceptibility of CD46-KO cells was significantly reduced compared to the parental cells (Figure 4C). Furthermore, when an HBV molecular clone was introduced into CD46-KO cells, the viral particle production capacity was nearly equivalent to that of the parental cells (Supplementary Figure S3B). Reintroduction of CD46 into CD46-KO cells restored NTCP surface levels and HBV entry, whereas CD46(ΔTM), which lacks the ability to bind to NTCP, showed no such effect (Supplementary Figure S3C). These results indicate that CD46 is critical for the early stages of infection, particularly for maintaining NTCP localization at the plasma membrane.

Figure 4.

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CD46 depletion reduces HBV infection. (A) Western blot analysis confirming CD46 knockout and reduced NTCP expression in HepG2-NTCP-C4 cells by using CRISPR/Cas9. Two independent CD46-KO clones (CD46-KO1 and CD46-KO2) are shown. Cell lysates were treated with PNGase F to remove N-glycans prior to analysis. (B) PreS1 peptide binding assay. Cells were incubated with FITC-conjugated PreS1 peptide and analyzed by fluorescence microscopy. Representative images showing PreS1-FITC (green) binding to parental HepG2-NTCP-C4 and CD46-KO cells. Nuclei were stained with DAPI (blue). Scale bar, 10 μm. (C) HBV infection assay using HBV-secNL reporter virus. Parental and CD46-KO cells were infected with HBV-secNL, and viral infection efficiency was monitored by measuring secreted NanoLuc activity. Data are presented as mean ± SD (n = 3). ****P < 0.0001 compared to parental cells.

CD46 antibody inhibits HBV infection by reducing cell-surface NTCP expression

Previous studies have demonstrated that CD46 plays a crucial role in the entry step of various viruses, including measles virus (Dorig et al., 1993; Naniche et al., 1993) and human cytomegalovirus (Stein et al., 2019), and CD46 antibodies can inhibit the replication of these viruses. Therefore, we next investigated whether CD46 antibodies could inhibit HBV entry. Among CD46 antibodies tested, clones M75 and M160 showed ∼20% inhibition of viral entry, while clone E4.3 demonstrated ∼50% inhibition compared to the control antibody (Figure 5A). When we infected primary human hepatocytes with HBV in the presence of CD46 antibodies, clones M75 and E4.3 exhibited ∼50% inhibition of viral replication (Figure 5B). In primary human hepatocytes treated with these antibodies, NTCP levels were slightly decreased (Supplementary Figure S4A). Among these CD46 antibodies, clone E4.3 most strongly inhibited the CD46–NTCP interaction (Figure 5C). The IC50 of clone E4.3 was 1.027 μg/ml (Supplementary Figure S4B). Immunofluorescence analysis of hepatocytes treated with fluorescently labeled clone E4.3 revealed that NTCP was redistributed from the plasma membrane to intracellular vesicles and co-localized with CD46 (Figure 5D). These results suggest that CD46 antibodies, particularly clone E4.3, possess antiviral activity against HBV infection by triggering NTCP internalization from the plasma membrane.

Figure 5.

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Anti-CD46 antibodies inhibit HBV infection by modulating NTCP localization. (A) Effects of different CD46 antibody clones on HBV infection in HepG2-NTCP-C4 cells. Cells were pretreated with control IgG or anti-CD46 antibodies (clone E4.3, M75, or M160) before infection with HBV-secNL. Data are presented as mean ± SD (n = 3). **P < 0.01, ***P < 0.001 compared to control IgG. (B) Inhibition of HBV infection by CD46 antibodies in primary human hepatocytes. Cells were treated with control IgG or anti-CD46 antibodies before infection with wild-type HBV. Viral replication was assessed by measuring HBV DNA and HBsAg levels. Data are presented as mean ± SD (n = 3). *P < 0.05, **P < 0.01, ***P < 0.001 compared to control IgG. (C) Effects of CD46 antibodies on the CD46–NTCP interaction assessed by NanoBRET assay. Top: schematic representation of the assay principle. Bottom: HepG2 cells expressing CD46-NanoLuc and NTCP-HaloTag were treated with 0.5 or 1 μg/ml of control IgG or anti-CD46 antibodies (clone E4.3, M75, or M160). Data are presented as mean ± SD (n = 3). **P < 0.01, ***P < 0.001 compared to no antibody control. (D) Immunofluorescence analysis showing the effect of CD46 antibody (clone E4.3) on NTCP localization. Cells were treated with fluorescently labeled clone E4.3 (green) and stained for NTCP (red). Nuclei were stained with DAPI (blue). Scale bar, 10 μm. Quantification showing the distribution of cells with NTCP at plasma membrane and intracellular compartment (PM + Int) versus predominantly intracellular compartment (Int). Arrowheads indicate intracellular accumulation of both CD46 and NTCP.

Discussion

NTCP is the primary receptor for HBV entry (Yan et al., 2012), and the constitutive expression of this receptor is closely related to HBV tropism (Watashi et al., 2025). The presence of NTCP on the plasma membrane is essential for de novo HBV infection. In this study, we identified CD46 as a critical host factor that regulates the membrane expression of NTCP via a cis-acting mechanism. Our findings demonstrate that HBV entry through NTCP is significantly reduced in CD46-deficient cells, and CD46-specific monoclonal antibodies can suppress cell-surface NTCP expression and inhibit HBV infection. While CD46 is expressed in HepG2 cells, these cells remain resistant to HBV infection, suggesting that CD46 functions as a regulatory factor for NTCP-mediated viral entry rather than as a primary receptor.

Several studies have identified host factors that interact with NTCP at the cell membrane (Iwamoto et al., 2019; Hu et al., 2020; Palatini et al., 2022). For instance, EGFR functions as an NTCP co-factor, facilitating HBV entry through phosphorylation-dependent endocytosis (Iwamoto et al., 2019). Additionally, IFITM3 and E-cadherin support NTCP function through distinct mechanisms (Hu et al., 2020; Palatini et al., 2022). While our proximity-based labeling approach did not detect these previously reported NTCP-interacting partners, this discrepancy may reflect the dynamic nature of these interactions or cell type-specific variations in complex formation. We identified CD46 as an NTCP-interacting partner, and this finding was further supported by AlphaFold2 structural prediction analysis, which revealed a thermodynamically favorable interaction (ΔG = −26.6 kcal/mol) at the transmembrane domains. Notably, CD46 depletion did not affect EGFR expression or its membrane localization, indicating that CD46 regulates NTCP independently of the EGFR–NTCP axis and functions as a specific regulatory factor for NTCP rather than as a general regulator of multiple entry co-factors.

The precise molecular mechanism by which CD46 regulates NTCP localization remains to be fully elucidated. CD46 may stabilize NTCP at the plasma membrane by anchoring it within specific membrane microdomains or preventing its constitutive internalization. Alternatively, CD46 may protect NTCP from post-translational modifications that lead to degradation. Further investigations will be necessary to fully characterize the molecular mechanisms underlying the CD46–NTCP interaction.

Interestingly, NTCP expression has been shown to be dynamically regulated under different physiological conditions. Previous studies have demonstrated that proliferating hepatocytes exhibit transcriptional down-regulation of NTCP through cell cycle regulatory genes such as p53 and cyclin D1, leading to resistance against HBV reinfection (Yan et al., 2019). In contrast to this transcriptional mechanism, our findings suggest that CD46 regulates NTCP through distinct mechanisms affecting membrane localization and stability. This distinction indicates that NTCP membrane expression is controlled by multiple complementary pathways that operate under different cellular conditions.

CD46 is widely distributed across various cell types (Purcell et al., 1990; Liszewski et al., 2005; Oliaro et al., 2006) and primarily functions as a complement regulatory protein by facilitating C3b and C4b inactivation (Seya and Atkinson, 1989; Marie et al., 2002). The extracellular region of CD46 contains four short consensus repeat (SCR) domains, also known as complement control protein modules, which are responsible for its complement regulatory activity and serve as binding sites for various ligands. Several viruses, including measles virus, have evolved to utilize CD46 as an entry receptor. The measles virus hemagglutinin protein directly binds to CD46’s SCR domains, enabling viral entry (Dorig et al., 1993; Naniche et al., 1993; Buchholz et al., 1997; Manchester et al., 1997). We found that CD46 indirectly affects HBV entry by regulating the membrane localization of NTCP, highlighting the diverse roles of CD46 in viral infection.

Our investigation revealed that specific anti-CD46 antibodies, particularly clone E4.3 recognizing the SCR1 domain, can suppress HBV infection. Mechanistically, these antibodies trigger NTCP redistribution from the plasma membrane to intracellular vesicles, coinciding with reduced HBV infection in primary human hepatocytes. The differential efficacy of CD46 antibody clones (E4.3 > M75 > M160) may be related to their epitope recognition patterns and ability to disrupt the CD46–NTCP interaction. Indeed, clone E4.3 most strongly inhibited the CD46–NTCP interaction among the tested antibodies. Different antibody clones may also trigger distinct endocytic pathways; CD46 undergoes clathrin-mediated endocytosis upon antibody binding, and clone E4.3 may more efficiently trigger this pathway, co-internalizing NTCP. Future studies using pharmacological inhibitors of specific endocytic pathways would help elucidate the precise mechanism. The observation that HBV entry persists partially despite CD46 blockade suggests the existence of additional entry mechanisms. This complexity aligns with previous findings showing that targeting other entry co-factors, such as EGFR (Iwamoto et al., 2019), can inhibit HBV infection. Targeting these co-factors may provide alternative therapeutic strategies, given the challenges of directly targeting NTCP due to its essential role in bile acid transport (Li et al., 2024).

Beyond its role in viral entry, CD46 presents an additional therapeutic opportunity in HBV-related liver disease. CD46 is frequently overexpressed in HBV-positive HCC (Kinugasa et al., 1999; Liu et al., 2020), where it protects cancer cells from complement-mediated destruction. The dual role of CD46 in viral entry and tumor cell survival suggests that CD46-targeted antibodies, particularly those targeting the SCR domains, might simultaneously inhibit viral infection and enhance complement-mediated tumor cell destruction. This approach could be especially relevant for early-stage HBV-positive HCC treatment. Moreover, unlike proliferation-associated NTCP regulation that represents a natural antiviral defense mechanism during liver regeneration, CD46-targeted interventions could potentially inhibit HBV infection without interfering with normal hepatocyte proliferation cycles.

Future studies should address several key aspects of CD46-targeted therapy, including potential immune evasion mechanisms and the impact on physiological complement regulation. Additionally, detailed structural analysis of the CD46–NTCP complex and identification of potential intermediate binding partners will be crucial for understanding the molecular basis of this interaction. These insights could guide the development of more specific therapeutic strategies for HBV infection and HBV-associated liver cancer.

Materials and methods

Cell culture

HepG2 (JCRB, #JCRB1054), HepG2-iNTCP (Miyakawa et al., 2018), and HepG2-hNTCP-C4 (Iwamoto et al., 2014) cells were maintained in collagen-coated dishes with DMEM/F-12 GlutaMAX (Thermo Fisher Scientific, #10565018) supplemented with 10% fetal bovine serum (FBS), 10 mM HEPES, and 5 μg/ml insulin. For HepG2-iNTCP cells, NTCP expression was induced by treatment with 1 μg/ml Dox (TaKaRa, #Z1311N) for 48 h prior to experiments. Primary human hepatocytes (PXB cells) were purchased from PhoenixBio and cultured according to the manufacturer’s instructions using hepatocyte maintenance medium.

Generation of CD46-KO cells

CD46-KO cells were generated using the CRISPR/Cas9-mediated genome editing. HepG2-hNTCP-C4 cells were transfected with a mixture of 2.5 μg TrueCut Cas9 Protein v2 (Thermo Fisher Scientific, #A36496) and 15 pmol CD46-targeting sgRNA (Thermo Fisher Scientific, #CRISPR734362_SGM) using Lipofectamine CRISPRMAX Cas9 reagent (Thermo Fisher Scientific, #CMAX00003) according to the manufacturer’s protocol. Single-cell clones were isolated by limited dilution and screened for CD46 expression by western blot analysis. Clones showing a >90% reduction in CD46 expression compared to parental cells were selected for further experiments.

In situ proximity-based biotinylation

We modified the methodology for in situ biotinylation based on previous studies (Bar et al., 2018; Noguchi et al., 2024). HepG2-iNTCP cells were seeded in collagen-coated plates and treated with 1 μg/ml Dox for 48 h to induce NTCP expression. Cells were incubated with anti-NTCP primary antibody (Miyakawa et al., 2018; 1:100 dilution) for 1 h at room temperature, followed by HRP-conjugated secondary antibody (Sigma–Aldrich, #12-349, 1:5000 dilution) for 45 min. Proximity-based biotinylation was performed by adding biotinylation buffer containing 200 μM biotin-phenol and 0.0015% H2O2 in phosphate-buffered saline (PBS) for 1 min. The cells were immediately washed with PBS and lysed in 1% sodium dodecyl sulfate (SDS) RIPA buffer (50 mM Tris–HCl, pH 8.0, 150 mM NaCl, 1% Triton X-100, 0.5% sodium deoxycholate, and 1% SDS). Biotinylated proteins were enriched using Streptavidin MagneSphere Paramagnetic Particles (Promega, #Z5481) and subsequently digested with trypsin for MS analysis.

MS analysis

Liquid chromatography (LC)–MS/MS analysis was conducted using a TripleTOF 5600 mass spectrometer (AB-SCIEX) coupled with an UltiMate 3000 high-performance LC (HPLC) system (Thermo Fisher Scientific). Peptides were first loaded onto a trap column (100 μm × 20 mm, C18, 5 μm, 100 Å; Thermo Fisher Scientific) and subsequently separated on a nano HPLC capillary column (75 μm × 120 mm, C18, 3 μm; Nikkyo Technos) at a flow rate of 300 nl/min. The mobile phases consisted of solvent A (0.1% formic acid in 2% acetonitrile) and solvent B (0.1% formic acid in 80% acetonitrile). Peptide elution was performed with a gradient as follows: 2% B for 0–5 min, a linear increase from 2% to 40% B over 5–120 min, 95% B for 10 min, and re-equilibration at 2% B for 20 min. The data were acquired in data-dependent acquisition mode with a survey scan over a mass range of 400–1250 m/z and a scan time of 250 ms. The top 20 precursor ions were selected for fragmentation, with an MS/MS accumulation time of 100 ms and product ion scanning over a range of 230–1800 m/z. The peak lists were searched against the human protein sequences in the UniProtKB/Swiss-Prot database (version January 2020) using Mascot software version 2.7.0 (Matrix Science). Search parameters included trypsin digestion allowing up to two missed cleavages, variable modifications for N-terminal acetylation, methionine oxidation, and cysteine carbamidomethylation, and peptide charge states of 2+, 3+, and 4+. The peptide mass tolerance was set at ±0.05 Da and MS/MS tolerance at ±0.1 Da. A 1% false discovery rate threshold was applied for peptide identification. The MS parameters were configured as previously described (Nakai et al., 2022).

IP and western blot analysis

Cells were lysed in RIPA buffer (Fujifilm–Wako, #182-02451) supplemented with protease inhibitor cocktail (Merck, #11836170001). For IP, cell lysates were incubated with EZview Red Anti-c-Myc Affinity Gel (Merck, #E6654) overnight at 4°C with gentle rotation. Immunoprecipitates were washed three times with ice-cold RIPA buffer and eluted by boiling in SDS sample buffer (Fujifilm–Wako, #198-13282).

For western blot analysis, proteins were separated by SDS–polyacrylamide gel electrophoresis on 10%–20% gradient gels (Fujifilm–Wako, #198-15041) and transferred to polyvinylidene fluoride membranes (Merck, #IPVH00010). Membranes were blocked with 5% non-fat milk in Tris-buffered saline containing 0.1% Tween-20 for 1 h at room temperature and probed with primary antibodies overnight at 4°C, followed by HRP-conjugated secondary antibodies for 1 h at room temperature. Protein bands were visualized using Immobilon Western Chemiluminescent HRP Substrate (Merck, #WBKLS0500) and detected with a LuminoGraph imaging system (ATTO, ImageSaver software version 6.0). Band intensities were quantified using ImageJ software version 1.4 (NIH). The antibodies used in this study are as follows: anti-CD46 (Abcam, #ab108307, 1:1000 dilution), anti-NTCP (Sigma–Aldrich, #HPA042727, 1:1000 dilution), anti-EGFR (Cell Signaling Technology, #4267, 1:1000 dilution), anti-α-tubulin (MBL, #PM054-7, 1:5000 dilution), and anti-Myc (Cell Signaling Technology, #2276, 1:1000 dilution).

NanoBRET protein–protein interaction assay

NanoBRET assays were performed as previously described (Miyakawa et al., 2022). Expression constructs were generated by cloning NTCP cDNA with a HaloTag sequence at the C-terminus, and CD46 cDNA with a NanoLuc luciferase sequence at the C-terminus into pCMV vectors. HepG2 cells were seeded in 96-well white-walled plates and co-transfected with both constructs using Lipofectamine 3000 (Thermo Fisher Scientific, #L3000015). Cells were treated with HT-618 ligand and Nano-Glo substrate at 36 h and 48 h after transfection, respectively. NanoBRET activity was measured using the NanoBRET Nano-Glo Detection System (Promega, #N1661) on a GloMax Discovery system (Promega).

Flow cytometry

Cell-surface NTCP detection was performed as previously described (Miyakawa et al., 2018). Cells were harvested using 5 mM EDTA in PBS and stained with PE-conjugated CD46 antibody (Biolegend, #352401, 1:500 dilution) or APC-conjugated EGFR antibody (Biolegend, #352905, 1:500 dilution) for 30 min at 4°C. All staining procedures were performed in staining buffer (PBS containing 2% FBS and 0.1% sodium azide). After washing, cells were resuspended in PBS and analyzed using a FACSCanto II instrument (BD Biosciences). Data analysis was performed using FlowJo software (Tree Star).

PreS1 peptide binding assay

FITC-conjugated HBV PreS1 peptide (amino acids 2–48) was synthesized by GenScript. Cells were seeded on collagen-coated coverslips and cultured until 70% confluent. Cells were then incubated with 40 nM PreS1-FITC for 30 min at 37°C, washed extensively with PBS, and fixed with 4% paraformaldehyde. The coverslips were mounted using mounting medium containing 4',6-diamidino-2-phenylindole (DAPI; Vector Laboratories, #H-1200) and analyzed using a BZ-X800 fluorescence microscope (Keyence).

HBV infection assays

HBV encoding secreted NanoLuc luciferase (HBV-secNL) was produced as previously described (Nishitsuji et al., 2018). Wild-type HBV particles were purchased from PhoenixBio. For infection assays, cells seeded in 24-well plates were infected with either HBV-secNL (50 μl/well) or wild-type HBV (100 genome equivalents/cell) in the presence of 4% PEG8000 and 2% dimethyl sulfoxide. After 16 h, cells were washed three times with PBS and cultured in fresh medium with medium changes every 48 h. For HBV-secNL infections, viral entry was monitored by measuring secreted luciferase activity in the culture supernatant using Nano-Glo Luciferase Assay System (Promega, #N1110) according to the manufacturer’s instructions. For wild-type HBV infections, viral replication was assessed by measuring HBV DNA and HBsAg levels in the culture supernatant using digital polymerase chain reaction (PCR) and AlphaLISA HBsAg Detection Kit (Revvity, #AL3083HV), respectively, as described below.

Gene expression analysis

mRNA extraction and subsequent cDNA synthesis were performed using RNeasy Mini Kit (Qiagen, #74104) and ReverTra Ace qPCR RT Master Mix (Toyobo, #TRT-101), respectively, according to the manufacturer’s instructions. Gene expression was then analyzed by real-time quantitative PCR (RT-qPCR) using TB Green Premix Ex Taq II (TaKaRa Bio, #RR820S) and a CFX96 Real-Time PCR Detection System (Bio-Rad). Relative gene expression levels were calculated using the ΔΔCt method with ACTB as the internal control. The primer sequences used were as follows: ACTB, forward 5′-ggacttcgagcaagagatgg-3′ and reverse 5′-agcactgtgttggcgtacag-3′; NTCP, forward 5′-atggaggcccacaacgcgtctgccc-3′ and reverse 5′-cagaaggtggagcaggtggtcatcac-3′; CD46, forward 5′-tggctacctgtctcagatgacg-3′ and reverse 5′-gcatctgataaccaaactcgtaag-3′.

For HBV DNA quantification, DNA was extracted from cell culture supernatants using QIAamp DNA Blood Mini Kit (Qiagen, #51104) according to the manufacturer’s instructions. HBV DNA levels were measured using the QIAcuity Digital PCR System (Qiagen) with the following primers and probe: forward primer 5′-gtgtctgcggcgttttatca-3′, reverse primer 5′-gacaaacgggcaacatacctt-3′, and TaqMan probe 5′-FAM-cctctkcatcctgctgctatgcctcatc-TAMRA-3′. Digital PCR reactions were performed in duplicate, and HBV DNA copy numbers were calculated using QIAcuity Software Suite.

HBsAg quantification

Secreted HBsAg in culture supernatants was quantified using the AlphaLISA HBsAg Detection Kit (Revvity, #AL3083HV) according to the manufacturer’s instructions. Briefly, 5 μl of culture supernatant was mixed with 20 μl of reaction mixture containing anti-HBsAg acceptor beads and biotinylated anti-HBsAg antibody in AlphaLISA immunoassay buffer in white 384-well OptiPlates (Revvity). After incubation at room temperature for 60 min, 25 μl of streptavidin-coated donor beads were added and incubated for an additional 30 min in the dark. AlphaLISA signals were measured using an Nivo multimode plate reader (Revvity) with standard AlphaLISA settings.

Antibody treatment

Anti-CD46 monoclonal antibody clones M75 and M160 were described previously (Seya et al., 1990; Iwata et al., 1995). Clone E4.3 was obtained from NeoBiotechnologies. FITC-conjugated CD46 antibody was purchased from Santa Cruz Biotechnology (#sc7634 AF488). NTCP antibody was labeled using the Alexa Fluor 594 Antibody Labeling Kit (Thermo Fisher Scientific, #A20185) according to the manufacturer’s instructions.

For HBV-secNL infection experiments, cells were treated with anti-CD46 antibodies (1 μg/ml) simultaneously with viral infection, and antibody treatment was maintained until medium change at 16 h post-infection. For wild-type HBV infection experiments, cells were pre-treated with antibodies (1 μg/ml) for 1 h at 37°C before viral infection, and antibody treatment was maintained throughout the entire assay period. For IC50 determination, antibodies were tested at concentrations ranging from 0.03 μg/ml to 9 μg/ml, and IC50 values were calculated using nonlinear regression analysis with GraphPad Prism software.

For immunofluorescence imaging experiments, cells seeded on collagen-coated coverslips were treated with FITC-conjugated CD46 antibody (1 μg/ml) for 2 h at 37°C, washed three times with PBS, and fixed with 4% paraformaldehyde for 15 min at room temperature. Cells were then incubated with Alexa Fluor 594-conjugated NTCP antibody (1:100 dilution) for 2 h at 4°C, washed extensively with PBS, and mounted using mounting medium containing DAPI. Fluorescence imaging was performed using a BZ-X800 fluorescence microscope.

Transfection-based HBV production assay

HepG2 cells in 12-well plates were co-transfected with pUC19-C_JPNAT (1 μg) (Sugiyama et al., 2006) by using Lipofectamine 3000 (Thermo Fisher Scientific, #L3000015). After 4 h, the cells were washed three times with fresh medium to remove extracellular DNA. Three days post-transfection, cell debris was cleared from the culture supernatants by centrifugation at 860× g for 3 min. HBV production was assessed by measuring HBsAg levels in the culture supernatant using AlphaLISA HBsAg Detection Kit (Revvity, #AL3083HV).

Structure prediction

Protein structures for human CD46 and NTCP were retrieved from the AlphaFold Protein Structure Database (https://alphafold.ebi.ac.uk/). Protein–protein docking was performed using ColabFold with default parameters. The resulting complex models were evaluated based on confidence scores, and interface analysis was conducted using PyMOL. Interaction confidence was assessed using the ΔiG P-value calculated by the prediction algorithm.

Statistical analysis

All experiments were performed at least three times independently. Data are presented as mean ± standard deviation (SD). Statistical significance was determined using two-tailed Student’s t-test for pairwise comparisons or one-way analysis of variance followed by Tukey’s post-hoc test for multiple comparisons. P-values are indicated as follows: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Statistical analyses were performed using GraphPad Prism 10 software.

Supplementary Material

mjaf055_Supplemental_File
mjaf055_supplemental_file.pdf (458.3KB, pdf)

Acknowledgements

We thank Kyohei Kurobe and Kenji Yoshihara for technical assistance.

Contributor Information

Kei Miyakawa, AIDS Research Center, National Institute of Infectious Diseases, Japan Institute for Health Security, Tokyo 208-0011, Japan; Influenza Research Center, National Institute of Infectious Diseases, Japan Institute for Health Security, Tokyo 208-0011, Japan; Institute for Vaccine Research and Development, Hokkaido University, Hokkaido 001-0021, Japan; Department of Microbiology, Yokohama City University School of Medicine, Kanagawa 236-0004, Japan.

Yusuke Nakai, Influenza Research Center, National Institute of Infectious Diseases, Japan Institute for Health Security, Tokyo 208-0011, Japan.

Taichi Kameya, Department of Bioinformatics and Integrative Omics, National Institute of Infectious Diseases, Japan Institute for Health Security, Tokyo 208-0011, Japan; Life Science Laboratory, Technology and Development Division, Kanto Chemical Co., Inc., Kanagawa 259-1146, Japan.

Hironori Nishitsuji, Department of Virology, Fujita Health University School of Medicine, Aichi 470-1192, Japan.

Koichi Watashi, Department of Drug Development, National Institute of Infectious Diseases, Japan Institute for Health Security, Tokyo 208-0011, Japan.

Makoto Takeda, Department of Microbiology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.

Tsukasa Seya, Nebuta Research Institute for Life Sciences, Aomori University, Aomori 030-0943, Japan.

Kunitada Shimotohno, Institute of Microbial Chemistry (BIKAKEN), Tokyo 141-0021, Japan.

Yayoi Kimura, Advanced Medical Research Center, Yokohama City University, Kanagawa 236-0004, Japan.

Akihide Ryo, Department of Microbiology, Yokohama City University School of Medicine, Kanagawa 236-0004, Japan; Department of Bioinformatics and Integrative Omics, National Institute of Infectious Diseases, Japan Institute for Health Security, Tokyo 208-0011, Japan.

Data availability

All proteomics data are deposited in the ProteomeXchange Consortium (http://www.proteomexchange.org) via the jPOST (https://jpostdb.org) partner repository with the dataset identifier PXD065037. All data are fully available without restriction.

Funding

This work was supported by grants from Japan Society for the Promotion of Science (JP23K27419 to K.M. and JP23K27641 to A.R.), Japan Agency for Medical Research and Development (JP23fk0310507 and JP223fa627005 to K.M.), and the Takeda Science Foundation.

Conflict of interest: T.K. is an employee of Kanto Chemical Co., Inc. The other authors declare no competing interests.

Author contributions: K.M. designed and performed the research, analyzed the data, and wrote the manuscript; Y.N. and T.K. performed the research, analyzed the data, and wrote the manuscript; H.N., K.W., M.T., T.S., and K.S. contributed reagents; Y.K. analyzed the data; A.R. directed the research, analyzed the data, and wrote the manuscript.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

mjaf055_Supplemental_File
mjaf055_supplemental_file.pdf (458.3KB, pdf)

Data Availability Statement

All proteomics data are deposited in the ProteomeXchange Consortium (http://www.proteomexchange.org) via the jPOST (https://jpostdb.org) partner repository with the dataset identifier PXD065037. All data are fully available without restriction.

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