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美国麻省大学医学院的James Munro团队应用单分子荧光共振能量转移(smFRET)和荧光相关光谱(FCS)技术揭示了新冠病毒(SARS-CoV-2)入侵呼吸道上皮细胞的分子机制。

美国麻省大学医学院的James Munro团队应用单分子荧光共振能量转移(smFRET)和荧光相关光谱(FCS)技术揭示了新冠病毒(SARS-CoV-2)入侵呼吸道上皮细胞的分子机制。

  • 分类:应用案例
  • 发布时间:2022-08-01 16:01
  • 访问量:

【概要描述】美国麻省大学医学院的James Munro团队应用单分子荧光共振能量转移(smFRET)和荧光相关光谱(FCS)技术揭示了新冠病毒(SARS-CoV-2)入侵呼吸道上皮细胞的分子机制。smFRET实验表明,SARS-CoV-2突刺蛋白(S蛋白)的受体结合域(RBD)存在两种构象:“up”和“down”;RBD处于up构象时,更有利于结合细胞膜表面的血管紧张素转换酶2(ACE2)受体,从而入侵细胞。通过smFRET实验,发现RBD与ACE2结合降低了前者的up构象到down构象的转换速率,从而稳定了RBD的up构象,更有利于病毒入侵。作者还对比了变异毒株D614G和原始毒株D614的smFRET实验结果,发现D614G的RBD处于up构象的占比更高,这解释了变异毒株更容易入侵人体的一个原因。此外,作者研究了多种单克隆抗体和D614、D614G病毒株S蛋白结合前后的RBD构象变化,发现与S蛋白颈部(stalk region)结合的抗体可稳定RBD的up构象,并暴露与ACE2受体的结合位点。应用广东中科奥辉科技有限公司开发的桌面式荧光相关光谱仪(CorTector SX系列),该研究团队测量了D614、D614G病毒株的S蛋白与ACE2受体结合反应的亲和力(KD值),以及多种单克隆抗体对这一亲和力的调控作用。这些FCS数据支持了RBD的up构象更有利于ACE2受体结合的假说,并对“鸡尾酒”抗体疗法提供了新思路:即应用与S蛋白颈部结合的抗体去促进RBD的up构象,从而更有利于RBD特异性抗体去阻断ACE2受体结合。

美国麻省大学医学院的James Munro团队应用单分子荧光共振能量转移(smFRET)和荧光相关光谱(FCS)技术揭示了新冠病毒(SARS-CoV-2)入侵呼吸道上皮细胞的分子机制。

【概要描述】美国麻省大学医学院的James Munro团队应用单分子荧光共振能量转移(smFRET)和荧光相关光谱(FCS)技术揭示了新冠病毒(SARS-CoV-2)入侵呼吸道上皮细胞的分子机制。smFRET实验表明,SARS-CoV-2突刺蛋白(S蛋白)的受体结合域(RBD)存在两种构象:“up”和“down”;RBD处于up构象时,更有利于结合细胞膜表面的血管紧张素转换酶2(ACE2)受体,从而入侵细胞。通过smFRET实验,发现RBD与ACE2结合降低了前者的up构象到down构象的转换速率,从而稳定了RBD的up构象,更有利于病毒入侵。作者还对比了变异毒株D614G和原始毒株D614的smFRET实验结果,发现D614G的RBD处于up构象的占比更高,这解释了变异毒株更容易入侵人体的一个原因。此外,作者研究了多种单克隆抗体和D614、D614G病毒株S蛋白结合前后的RBD构象变化,发现与S蛋白颈部(stalk region)结合的抗体可稳定RBD的up构象,并暴露与ACE2受体的结合位点。应用广东中科奥辉科技有限公司开发的桌面式荧光相关光谱仪(CorTector SX系列),该研究团队测量了D614、D614G病毒株的S蛋白与ACE2受体结合反应的亲和力(KD值),以及多种单克隆抗体对这一亲和力的调控作用。这些FCS数据支持了RBD的up构象更有利于ACE2受体结合的假说,并对“鸡尾酒”抗体疗法提供了新思路:即应用与S蛋白颈部结合的抗体去促进RBD的up构象,从而更有利于RBD特异性抗体去阻断ACE2受体结合。

  • 分类:应用案例
  • 发布时间:2022-08-01 16:01
  • 访问量:
详情

应用广东中科奥辉科技有限公司的荧光相关光谱单分子分析仪研究新冠病毒入侵人体细胞的分子机制

美国麻省大学医学院的James Munro团队应用单分子荧光共振能量转移(smFRET)和荧光相关光谱(FCS)技术揭示了新冠病毒(SARS-CoV-2)入侵呼吸道上皮细胞的分子机制。smFRET实验表明,SARS-CoV-2突刺蛋白(S蛋白)的受体结合域(RBD)存在两种构象:“up”和“down”;RBD处于up构象时,更有利于结合细胞膜表面的血管紧张素转换酶2(ACE2)受体,从而入侵细胞。通过smFRET实验,发现RBD与ACE2结合降低了前者的up构象到down构象的转换速率,从而稳定了RBD的up构象,更有利于病毒入侵。作者还对比了变异毒株D614G和原始毒株D614的smFRET实验结果,发现D614G的RBD处于up构象的占比更高,这解释了变异毒株更容易入侵人体的一个原因。此外,作者研究了多种单克隆抗体和D614、D614G病毒株S蛋白结合前后的RBD构象变化,发现与S蛋白颈部(stalk region)结合的抗体可稳定RBD的up构象,并暴露与ACE2受体的结合位点。应用广东中科奥辉科技有限公司开发的桌面式荧光相关光谱仪(CorTector SX系列),该研究团队测量了D614、D614G病毒株的S蛋白与ACE2受体结合反应的亲和力(KD值),以及多种单克隆抗体对这一亲和力的调控作用。这些FCS数据支持了RBD的up构象更有利于ACE2受体结合的假说,并对“鸡尾酒”抗体疗法提供了新思路:即应用与S蛋白颈部结合的抗体去促进RBD的up构象,从而更有利于RBD特异性抗体去阻断ACE2受体结合。

Abstract

  Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects cells through binding to angiotensin-converting enzyme 2 (ACE2). This interaction is mediated by the receptor-binding domain (RBD) of the viral spike (S) glycoprotein. Structural and dynamic data have shown that S can adopt multiple conformations, which controls the exposure of the ACE2-binding site in the RBD. Here, using single-molecule Förster resonance energy transfer (smFRET) imaging, we report the effects of ACE2 and antibody binding on the conformational dynamics of S from the Wuhan-1 strain and in the presence of the D614G mutation. We find that D614G modulates the energetics of the RBD position in a manner similar to ACE2 binding. We also find that antibodies that target diverse epitopes, including those distal to the RBD, stabilize the RBD in a position competent for ACE2 binding. Parallel solution-based binding experiments using fluorescence correlation spectroscopy (FCS) indicate antibody-mediated enhancement of ACE2 binding. These findings inform on novel strategies for therapeutic antibody cocktails.

Figure 1. Single-molecule Förster resonance energy transfer (smFRET) imaging of the conformational dynamics of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) S ectodomain. (A) (Left) SARS-CoV-2 SΔTM containing a single fluorescently labeled A4-tagged protomer within an otherwise untagged trimer was immobilized on a streptavidin‐coated quartz microscope slide by way of a C-terminal 8x-His-tag and biotin‐NiNTA. For clarity, only a monomer is depicted. Individual SΔTM trimers were visualized with prism-based TIRF microscopy using a 532 nm laser. Overlay of two S protomers with receptor-binding domains (RBD) in the ‘up’ (blue) and ‘down’ (green) conformations are shown with approximate positions of fluorophores indicated by green (LD550) and red (LD650) stars. (Right) Top view of the same S protomer overlay. The approximate distances between the sites of labeling are shown. Structures adapted from PDB 6VSB. (B) Domain organization of the SARS-CoV-2 SΔTM construct used for smFRET experiments, indicating the sites of A4 tag insertion. The S1 and S2 subunits are in blue and orange, respectively. Additional domains and features are as follows, ordered from N- to C-terminus: signal peptide, dark green; NTD, N-terminal domain; RBD and RBM, receptor-binding domain and motif (purple), respectively; SD1, subunit domain 1; SD2, subunit domain 2; SGAG, furin cleavage site mutation; FP, fusion peptide; HR1 and HR2, heptad repeat 1 and 2, respectively; PP, diproline mutations; T4 fibritin trimerization motif (foldon), magenta; TEV protease cleavage site, brown; 8x-His-tag, green. (Bottom) Amino acid sequence alignments indicating sites of A4 tag insertions in SΔTM. A4 peptide sequences (DSLDMLEW) are underlined. Fluorophores get attached to the serine amino acid within the A4 peptide.

  Figure 2. Verification of angiotensin-converting enzyme 2 (ACE2)-binding to A4-tagged SΔTM trimers using fluorescence correlation spectroscopy (FCS).(A) Cy5-labeled ACE2 was incubated in the absence or presence of untagged or A4-tagged SΔTM spikes. The diffusion of Cy5-ACE2 was evaluated by FCS using a 647 nm laser as indicated in Materials and methods. (B) Representative normalized autocorrelation curves for Cy5-ACE2 in the absence (circles) or presence (squares) of SΔTM, and the corresponding fits are shown in blue or magenta, respectively. The shift in the autocorrelation to longer timescales seen in the presence of SΔTM reflects the slower diffusion resulting from the larger size of the complex. (C) Cy5-ACE2 (100 nM) was incubated with different concentrations of the indicated SΔTM spikes and the resulting mixture was evaluated by FCS as described in Materials and methods. Dissociation constants (KD) determined from fitting the titration are indicated for the different SΔTM constructs. Data are presented as the mean ± standard deviation from three independent measurements. Raw data is provided in Figure 2—source data 1.

  Figure 3. Angiotensin-converting enzyme 2 (ACE2)-binding modulates the receptor-binding domain (RBD) conformation of SΔTM D614 and D614G. (A) Representative single-molecule Förster resonance energy transfer(smFRET) trajectory acquired from an individual SΔTM trimer (blue). Idealization resulting from Hidden Markov modeling (HMM) analysis is overlaid (red). The high-FRET(0.65) and low-FRET(0.35) states correspond to the RBD-down and RBD-up conformations, respectively, as indicated. Bulk fluorescence lifetime and anisotropy measurements supported the interpretation of changes in FRET as arising due to conformational transitions that reposition the fluorophores and are presented in Table 1. (B) (Left) FRET histogram for unbound SΔTM D614 overlaid with the sum of two Gaussian distributions centered at 0.65 and 0.35 FRET (sum, red; single distributions, gray) generated from the results of HMM analysis. FRET histograms are presented as the mean ± standard error determined from three technical replicates. The total number of smFRET traces used in the HMM analysis is shown(N). (Right) The same data for the ACE2-bound SΔTM D614 spike. (C) Violin plots indicating the distribution of occupancies in the 0.65-FRET (RBD-down) and 0.35-FRET(RBD-up) states seen for the smFRET traces analyzed. For each plot the gray circles and horizontal lines indicate the median and mean occupancy, respectively. The vertical gray lines extend to the 25th and 75th quantiles. The statistical significance of the differences in occupancies seen for the unbound and ACE2-bound SΔTM D614 trimers was evaluated with a one-way ANOVA (p-value is indicated). (D) Transition density plots (TDPs) for (left) unbound and (right) ACE2-bound SΔTM D614 indicating the frequency of observed FRET transitions determined through HMM analysis. The assignment of the two transitions is indicated on the left-hand TDP. (E) (Top) Kinetic scheme defining the rates of transition between FRET states. (Bottom) Rates of transition for unbound and ACE2-bound SΔTM D614 determined from HMM analysis of the individual smFRET traces. Rate constants are presented as the mean ± standard error determined from the same populations of smFRET traces used to construct the FRET histograms. (F) FRET histograms for the unbound and ACE2-bound SΔTM D614G spike, displayed as in (B). (G) Violin plots indicating FRET state occupancies for the SΔTM D614G spike, displayed as in (C). (H) TDPs for the SΔTM D614G spike, displayed as in (D). (I) Rate constants for the unbound and ACE2-bound SΔTM D614G spike, displayed as in (E). Numeric data are provided in Figure 3—source data 1.

  Figure 4. Antibodies directly and allosterically modulate SΔTM receptor-binding domain (RBD) conformation. (A) The RBD-up conformation occupancy (low-Förster resonance energy transfer [FRET] state) determined through Hidden Markov modeling (HMM) analysis for SΔTM D614 in the absence or presence of the indicated monoclonal antibodies (mAbs). Occupancy data are presented as violin plots as in Figure 3. The indicated p-values were determined by comparing mAb-bound to unbound SΔTM through one-way ANOVA. (B) (Top) Kinetic scheme defining the rates of transition between RBD-up and -down conformations. (Bottom) Rates of transition for SΔTM D614 in the presence of mAbs determined through HMM analysis of the single-molecule FRET (smFRET) traces. Rate constants are presented as mean ± standard error determined from three technical replicates. (C) RBD-up conformation occupancy data for SΔTM D614G displayed as in (A). (D) Kinetic data for SΔTM D614G displayed as in (B). Corresponding FRET histograms for each mAb-bound SΔTM trimer is shown in Figure 4—figure supplement 1. Data are shown numerically in Tables 2 and 3 and provided in Figure 4—source data 1.

 

原文链接:https://elifesciences.org/articles/75433

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