Plasmonic Imaging of Dynamic Interactions between Membrane Receptor Clusters beyond the Diffraction Limit in Live Cells

Single-particle rotational sensing for analyzing the neutralization activity of antiviral antibodies

Due to the pathogen-specific targeting, neutralization capabilities, and enduring efficacy, neutralizing antibodies (NAs) have received widespread attentions as a critical immunotherapeutic strategy against infectious viruses. However, because of the high variability and complexity of pathogens, rapid determination of neutralization activity of antiviral antibodies remains a challenge. Here, we report a new method, named as out-of-plane polarization imaging based single-particle rotational sensing, for rapid analysis of neutralization activity of antiviral antibody against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Using the spike protein functionalized gold nanorods (AuNRs) and angiotensin-converting enzyme 2 (ACE2) coated gold nanoparticles (AuNPs) as the rotational sensors and chaperone probes, we demonstrated the single-particle rotational sensing strategy for the measurement of rotational diffusion coefficient of the chaperone-bound rotational sensors caused by the specific spike protein-ACE2 interactions. This enables us to measure the neutralizing activity of neutralizing antibody from the analysis of dose-dependent changes in rotational diffusion coefficient (Dr) of the rotational sensors upon the treatment of SARS-CoV-2 antibody. With this technique, we achieved the quantitative determination of neutralization activity of a commercially available SARS-CoV-2 antibody (IC50, 294.1 ng/mL) with satisfying accuracy and anti-interference ability. This simple and robust method holds the potential for rapid and accurate evaluation of neutralization activity against different pathogenic viruses.

Plasmonic Imaging of Multivalent NTD-Nucleic Acid Interactions for Broad-Spectrum Antiviral Drug Analysis

The discovery and identification of broad-spectrum antiviral drugs are of great significance for blocking the spread of pathogenic viruses and corresponding variants of concern. Herein, we proposed a plasmonic imaging-based strategy for assessing the efficacy of potential broad-spectrum antiviral drugs targeting the N-terminal domain of a nucleocapsid protein (NTD) and nucleic acid (NA) interactions. With NTD and NA conjugated gold nanoparticles as core and satellite nanoprobes, respectively, we found that the multivalent binding interactions could drive the formation of core-satellite nanostructures with enhanced scattering brightness due to the plasmonic coupling effect. The core-satellite assembly can be suppressed in the presence of antiviral drugs targeting the NTD-NA interactions, allowing the drug efficacy analysis by detecting the dose-dependent changes in the scattering brightness by plasmonic imaging. By quantifying the changes in the scattering brightness of plasmonic nanoprobes, we uncovered that the constructed multivalent weak interactions displayed a 500-fold enhancement in affinity as compared with the monovalent NTD-NA interactions. We demonstrated the plasmonic imaging-based strategy for evaluating the efficacy of a potential broad-spectrum drug, PJ34, that can target the NTD-NA interactions, with the IC50 as 24.35 and 14.64 μM for SARS-CoV-2 and SARS-CoV, respectively. Moreover, we discovered that ceftazidime holds the potential as a candidate drug to inhibit the NTD-NA interactions with an IC50 of 22.08 μM from molecular docking and plasmonic imaging-based drug analysis. Finally, we validated that the potential antiviral drug, 5-benzyloxygramine, which can induce the abnormal dimerization of nucleocapsid proteins, is effective for SARS-CoV-2, but not effective against SARS-CoV. All these demonstrations indicated that the plasmonic imaging-based strategy is robust and can be used as a powerful strategy for the discovery and identification of broad-spectrum drugs targeting the evolutionarily conserved viral proteins.

High Confidence Single Particle Analysis with Machine Learning

Single particle analysis can effectively determine the heterogeneity between particles based on the local information on a single particle, which is utilized extensively for monitoring chemical reactions and biological activities. However, the study of obtaining ensemble reaction information at the single particle level, which can obtain both the structural and functional heterogeneity of particles as well as the ensemble reaction information, is challenging because the selection of a single particle mainly depends on experience, which will lead to a certain randomness when analyzing the ensemble reaction with single particles. Using machine learning, it is demonstrated that the proposed intelligent single particle analysis strategy can provide single particle and ensemble analyses with high confidence. Convolutional neural network and Gaussian mixture model were utilized to develop a machine learning model for resonance scattering imaging analysis of plasmonic nanoparticles. It can identify the scattered light of single particles and select representative or diverse particles. When single particle scattering imaging is used to obtain ensemble information on the reaction, the error caused by the selection of individual particles can be significantly reduced by selecting representative particles. In addition, the real situation of the reaction can be better revealed by selecting diverse particles. These results indicate that the intelligent single particle analysis strategy has great potential for imaging analysis and biological sensing.

In situ decrypting plasmonic nanoparticle size-controlled phosphorylation of epidermal growth factor receptor in living cells

Recently, interaction between epidermal growth factor receptor (EGFR) and EGFR-targeted nanoprobes is a hot topic. Here, we use dark field microscope (DFM) observe different aggregations of EGFR-targeted nanoprobes in diverticulum. Different aggregation states are related to phosphorylation of EGFR. EGFR phosphorylation can be adjusted by gold nanoparticles (GNPs) size.

Plasmonic scattering imaging of single Cu2-xSe nanoparticle for Hg2+ detection

The development of new efficient contrast nanoprobe has been greatly concerned in the field of scattering imaging for sensitive and accurate detection of trace analytes. In this work, the non-stoichiometric Cu_2-xSe nanoparticle with typical localized surface plasmon resonance (LSPR) properties originating from their copper deficiency as a plasmonic scattering imaging probe was developed for sensitive and selective detection of Hg²⁺ under dark-field microscopy. Hg²⁺ can compete with Cu(I)/Cu(II) which were sources of optically active holes coexisting in these Cu_2-xSe nanoparticles for its higher affinity with Se^2-. The plasmonic properties of Cu_2-xSe were adjusted effectively. Thus, the color scattering images of Cu_2-xSe nanoparticles was changed from blue to cyan, and the scattering intensity was obviously enhanced with the dark-field microscopy. There was a linear relationship between the scattering intensity enhancement and the Hg²⁺ concentration in the range of 10-300 nM with a low detection limit of 1.07 nM. The proposed method has good potential for Hg²⁺ detection in the actual water samples. This work provides a new perspective on applying new plasmonic imaging probe for the reliable determination of trace heavy metal substances in the environment at a single particle level.

Virus-like Plasmonic Nanoprobes for Quick Analysis of Antiviral Efficacy and Mutation-Induced Drug Resistance

As the pathogenic viruses and the variants of concern greatly threaten human health and global public safety, the development of convenient and robust strategies enabling rapid analysis of antiviral drug efficacy and mutation-induced resistance is quite important to prevent the spread of human epidemics. Herein, we introduce a simple single-particle detection strategy for quick analysis of anti-infective drugs against SARS-CoV-2 and mutation-induced drug resistance, by using the wild-type and mutant spike protein-functionalized AuNPs as virus-like plasmonic nanoprobes. Both the wild-type and mutant virus-like plasmonic nanoprobes can form core-satellite nanoassemblies with the ACE2@AuNPs, providing the opportunity to detect the drug efficacy and mutation-induced resistance by detecting the changes of nanoassemblies upon drug treatment with dark-field microscopy. As a demonstration, we applied the single-particle detection strategy for quantitative determination of antiviral efficacy and mutation-induced resistance of ceftazidime and rhein. The mutations in the receptor-binding domain of Omicron variant could lead to an increase of EC₅₀ values of ceftazidime and rhein, formerly from 49 and 57 μM against wild-type SARS-CoV-2, to 121 and 340 μM, respectively. The mutation-induced remarkable decline in the inhibitory efficacy of drugs was validated with molecule docking analysis and virus-like plasmonic nanoprobe-based cell-incubation assay. Due to the generality and feasibility of the strategy for the preparation of virus-like plasmonic nanoprobes and single-particle detection, we anticipated that this simple and robust method is promising for the discovery and efficacy evaluation of anti-infective drugs against different pathogenic viruses.