Real-time nanoplasmonic mapping

Abstract

Disclosed herein are sensor chips, imaging systems, and methods of preparing and using the same. The sensor chips disclosed herein include a substrate and a plurality of nanoplasmon rulers immobilized on the substrate. Each nanoplasmon ruler includes a first plasmonic element and a second plasmonic element connected by opposing ends of a single strand nucleic acid connector. Binding of an analyte to the single strand nucleic acid connector induces a conformational change in the single strand nucleic acid connector. The conformational change modulates an end-to-end distance between the first plasmonic element and the second plasmonic element, thereby modulating the nanoplasmonic coupling between the first plasmonic element and the second plasmonic element.

Description

[0001] REAL-TIME NANOPLASMONIC MAPPING

[0002] CROSS-REFERENCE TO RELATED APPLICATION

[0003] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 652,959, filed May 29, 2024, which is incorporated by reference herein in its entirety.

[0004] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

[0005] This invention was made with government support under R35 GM133795 awarded by the National Institutes of Health, 1943302 awarded by the National Science Foundation, and 2030828 awarded by the National Science Foundation. The government has certain rights in the invention.

[0006] REFERENCE TO AN ELECTRONIC SEQUENCE LISTING

[0007] The contents of the electronic sequence listing (16999600513. xml; Size: 6,460 bytes; and Date of Creation: May 22, 2025) is herein incorporated by reference in its entirety.

[0008] FIELD OF THE INVENTION

[0009] The disclosed technology is generally directed to plasmonic detection and imaging systems. More particularly the technology is directed to nanoplasmonic detection and mapping.

[0010] BACKGROUND OF THE INVENTION

[0011] Many fields of research, including medical diagnostic and investigative tools, stand to benefit from rapid and accurate detection of target analytes. For example, fast virus detection is integral to response and control of viral pandemics such as COVID-19. In some fields, such as the development of Chimeric antigen receptor (CAR) T-cell therapies, faces challenges from inherent cellular heterogeneity, potentially impacting therapeutic effectiveness and safety. The complexity of individual cell behaviors and secreted analyte profiles, along with current limitations of singlecell analytical technology, complicates understanding heterogeneity and secretomic signatures at the single-cell level. To date, while other methods for single-cell immunoassays enable multiparametric analyte detection from individual cells, the detection is static and often involves laborious labeling and washing steps, preventing real-time analyte monitoring. Existing technologies attempting real-time secretory imaging from target cells, have yet to establish a method for directly visualizing and tracing analyte production, diffusion, and transportation with high spatiotemporal resolution. Therefore, there is a need for methods, systems, and devices for rapid and accurate detection of target analytes. In some cases, there is a need for spatially resolved, real-time visualization of target analytes.

[0012] BRIEF SUMMARY OF THE INVENTION

[0013] Disclosed herein are methods, systems, and devices for rapid and accurate detection of target analytes.

[0014] In one aspect, disclosed herein is a sensor chip. The sensor chip includes a substrate and a plurality of nanoplasmon rulers immobilized on the substrate. Each nanoplasmon ruler includes a first plasmonic element and a second plasmonic element connected by opposing ends of a single strand nucleic acid connector. Binding of an analyte to the single strand nucleic acid connector induces a conformational change in the single strand nucleic acid connector. The conformational change modulates an end-to-end distance between the first plasmonic element and the second plasmonic element, thereby modulating the nanoplasmonic coupling between the first plasmonic element and the second plasmonic element.

[0015] In another aspect, also disclosed herein is a sensor device including a housing surrounding the sensor chip. The housing includes an inlet for introducing a cell or an analyte.

[0016] Another aspect disclosed herein is an imaging system including the sensor chip, an illumination source configured to illuminate the sensor chip, and a detector configured to detect a signal generated by illuminating the sensor chip.

[0017] Another aspect of the technology disclosed herein is an imaging method including illuminating the sensor chip, and detecting a signal generated by illuminating the sensor chip. Binding of an analyte to the single strand nucleic acid connector modulates the signal compared to the signal in the absence of the analyte binding to the single strand nucleic acid connector.

[0018] Also disclosed herein is a method for preparing a sensor chip, the method including: immobilizing a first plasmonic element on a substrate, connecting the first plasmonic element with a single strand nucleic acid connector at a first end, connecting a second plasmonic element with a single strand nucleic acid connector at a second end opposite the first end where binding of an analyte to the single strand nucleic acid connector induces a conformational change in the single strand nucleic acid connector. The conformational change modulates an end-to-end distance between the first plasmonic element and the second plasmonic element, thereby modulating a nanoplasmonic coupling between the first plasmonic element and the second plasmonic element. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Non-limiting embodiments of the present invention will be described by way of example with reference to the accompanying figures, which are schematic and are not intended to be drawn to scale. In the figures, each identical or nearly identical component illustrated is typically represented by a single numeral. For purposes of clarity, not every component is labeled in every figure, nor is every component of each embodiment of the invention shown where illustration is not necessary to allow those of ordinary skill in the art to understand the invention.

[0020] FIG. 1 shows the principle of the nanoplasmon ruler method for single-cell secretion mapping. Panel (a) shows the nanoplasmon ruler assembled on a glass slide using a one-step microfluidic patterning technique. Upon cytokine binding, the NP dimers are brought closer together. Panel (b) shows strong plasmonic coupling leads to a redshift and scattering intensity change in the spectrum, which can be detected by the optical spectrometer. The real-time intensity change can be imaged via EMCCD coupled dark-field microscopy. Panel (c) shows cytokine secretion from a single cell can be detected in real time and located via customized MATLAB code. The cytokine distribution, cytokine concentration distribution, and cytokine diffusion data can be further analyzed via real-time imaging data analysis.

[0021] FIG. 2 shows switchable aptamer sequence design for the IL-6 and IFN-y aptamer. Panel (a) shows estimated structure of the bound state of the redesigned IL-6 aptamer sequence. Added nucleotides are underlined; GQ-required guanines are marked with square boxes; possible secondary structures are marked with dotted lines. The unbound and bound sequences are the same and are given in SEQ ID NO: 2. Panel (b) shows the structure of the IL-6 and DNA aptamer (PDB ID: 4NI7). Panel (c) shows the end-to-end distance probability distribution at a simulation temperature of 0.3. Superposition of the DNA aptamer structure (all-atom model in gray) against the DMD prediction results for the bound and unbound structures (ribbon backbone indicated by solid line arrows) are shown near the distribution curves. The backbones of added nucleotides are marked with broken line arrows. Panel (d) shows SEM image of the nanoplasmon ruler assembly process. The zoomed-in picture shows the plasmon ruler structure. The scale bar is 1 pM. The distribution of the different structures on the sensor chip before and after assembly is shown in the histogram. Panel (e) shows scattering spectra of sensor surfaces before and after analyte binding. Dark-field images of the nanoplasmon ruler sensor chip under the lOx objective lens are shown near the spectrum curves. The cytokine concentration here is 5 ng / mL. Panel (f) shows real-time intensity changes on the sensor surface for IL-6 detection at different concentrations. IL-6 mapping at different concentrations after 30 min of detection. The sensor area is 400 pm x 400 pm. Panel (g) shows a calibration curve obtained from the relative intensity change (dl / I) at different concentrations of IL-6. The error bands are presented by shaded regions, n=3. The inserted figure presents the linear region of the calibration curves.

[0022] FIG. 3 shows single-cell secretion mapping. Panel (a) shows a schematic of single-cell secretion imaging. Single T cells were allowed to randomly settle on the nanoplasmon ruler on the chip surface. After stimulation with PMA and ionomycin, the T cells secreted cytokines that were captured by the nanoplasmon ruler. The resulting binding signal could be imaged in real time by the EMCCD. Panel (b) shows fluorescence and dark-field images of two different single cells. Panels (c) and (f) show real-time secretion heatmap and incremental analysis of the IL-6 secretion process from single cells. Panels (d) and (g) show isotropic analysis of concentration profiles at different time points (0 min, 5 min 10 min, 15 min, 20 min, 25 min, 30 min) in all directions (15 degrees in each direction). Panels (e) and (h) show real-time secretion curve and anisotropy ratio changes over time during the IL-6 secretion process. While bulk measurement methods such as ELISA can yield quantitative data on average cytokine secretion rates, they often overlook significant diversity among individual immune cells. For example, the three T cells with the highest IL-6 secretion amounts showed large variations in secretion rates over time, transitioning from relatively high to relatively low and reaching secretion saturation within 20 minutes. Additionally, the 10 s-resolved secretion profiles offer high temporal resolution, enabling the identification of secretion initiation and end points within a 30-min observation window, as demonstrated in the representative isotropic and anisotropic secretion patterns. Panel (i) shows changes in the total secretion amount with increasing time. Panel (j) shows concentration distribution in the analyzed area around the cell (150 pm x 150 pm) and fitted cytokine diffusion model. Panel (k) shows real-time IL-6 secretion curves for single activated T cells. Panel (1) shows the interrelation between IDI and ARSD values derived from all stimulated single T cells within the 5~30 minute time frame. Panel (m) shows correlation analysis of 11-6 secretion. Panel (n) shows a comparison of the secretion rate, D, and ARSD values for IL-6 and IFN-y secretion from Jurkat T cells.

[0023] FIG. 4 shows cell-cell communication mapping in Cytokine Release Syndrome (CRS). Panel (a) shows a schematic of cytokine release during interactions among CAR-T cells, macrophages, and tumor cells. Panels (b) and (c) show IFN-y and IL-6 secretion profdes during the interactions among CAR-T cells, B-ALL cells, and macrophages. The cell locations were determined by fluorescence microscopy. CAR-T cells are shown in red, macrophages are shown in blue, and NALM-6 cells are shown in green. Rose diagrams of the concentration profiles at different time points and in different directions are presented. Cytokine secretion amounts at different time points obtained from the concentration profiles are shown in line graphs, (c) and (d) Different combinations during the interactions of the three cell types, (e) Comparison of secretion rates among different cell clusters, (f) Comparison of ARSD values among different cell clusters.

[0024] FIG. 5 shows electromagnetic field simulation results. Panel (a) shows electromagnetic field simulation of the scattering response of the AuNP dimer upon interaction with polarized incident light parallel to the dimer axis. The highest intensity of the electric field (red, alternatively light grey) is localized to the central features of the simulation. Panel (b) shows a comparison of the influence of incident light polarization on the scattering response of the AuNP dimer. Panel (c) shows predicted changes in scattering spectrum at various gap distances.

[0025] FIG. 6 shows a switchable aptamer sequence design. Panel (a) shows estimated structure of the bound state of the redesigned IFN- y aptamer sequence, given in SEQ ID NO: 4. A 38-nt sequence involving a 21 -nt T spacer was added to the 5’ end and 28-nt sequence to the 3’ end. Added nucleotides are indicated in brackets. The unbound sequence is given in SEQ ID NO: 3. Panel (b) shows end-to-end distance probability distribution at a simulation temperature of 0.3. Superposition of the DNA aptamer structure from the DMD prediction results for the bound and unbound structures are shown near the distribution curves. The backbones of added nucleotides are marked at their beginnings and ends with solid line arrows. Also shown are switchable aptamer sequences for IL-6 and IFN- y aptamer. The beginning and ends of the added nucleotides are marked with broken line arrows; 10-nt T spacer (marked in brackets) was added on both sides to avoid steric hindrance effect.

[0026] FIG. 7 shows gap distance distribution for the AuNP dimer conjugated with IL-6 in panel (a) and the IFN-y aptamer in panel (c). COMSOL simulation of the scattering spectrum of the IL- 6 in panel (b) and IFN-y nanoplasmon ruler in panel (d) before and after target binding.

[0027] FIG. 8 shows dynamic light scattering analysis of gold nanoparticles. Panel (a) shows size distribution. Panel (b) shows zeta potential. FIG. 9 shows a schematic of the nanoplasmon ruler assembly process. FIG. 10 shows the effects of the stoichiometric ratio of aptamer to AuNP on the formation of the nanoplasmon ruler. The large panels show the synthesized nanostructures under dark-field microscopy, and the inserted panels are zoomed-in images obtained under SEM.FIG. 11 shows real-time intensity changes on the sensor surface and calibration curve for IFN-y detection.

[0028] FIG. 12 shows verification of sensor selectivity. A nanoplasmon ruler assembled with a human IL-6 / IFN-y aptamer was used to measure human IL-6, IFN-y, IL-10, TNF-a, IL-2, and IL- 1 at 1 ng / mL.FIG. 13 shows real-time curves of IFN-y secretion from activated T cells.

[0029] FIG. 14 shows rose diagrams of the concentration profiles of IL-6 secretion at different time points in different directions from 20 individual cells. This figure further shows anisotropy ratio changes during IL-6 and IFN-y secretion over 30 min.

[0030] FIG. 15 shows IFN-gamma secretion analysis of single T cells.

[0031] FIG. 16 shows DBSCAN clustering analysis of IL-6 secretion from single activated T cells. Straight bracket indicates cells with more isotropic secretion. Curved bracket indicates cells with more anisotropic secretion.

[0032] FIG. 17 shows ARSD changes during IFN-gamma / IL-6 secretion by single T cells.

[0033] FIG. 18 shows correlation analysis of IFN-y secretion.

[0034] FIG. 19 shows imaging of IL-6 and IFN-y secretion during two-cell interactions. All secretion images and concentration profiles are shown at 30 min.FIG. 20 shows images of secretion by individual CAR-T cells, B-ALL cells, and macrophages without stimulation.

[0035] FIG. 21 shows secretion heatmap, incremental analysis, and isotropic analysis of IL-6 secretion during interaction between macrophages and NALM-6 cells.

[0036] FIG. 22 shows secretion heatmap, incremental analysis, and isotropic analysis of IFN-y secretion during interaction between macrophages and NALM-6 cells.

[0037] FIG. 23 shows secretion heatmap, incremental analysis, and isotropic analysis of IL-6 secretion during interaction between CAR-T cells and NALM-6 cells.

[0038] FIG. 24 shows secretion heatmap, incremental analysis, and isotropic analysis of IFN-y secretion during interaction between CAR-T cells and NALM-6 cells.

[0039] FIG. 25 shows secretion heatmap, incremental analysis, and isotropic analysis of IL-6 secretion during interaction between CAR-T cells and macrophages.

[0040] FIG. 26 shows secretion heatmap, incremental analysis, and isotropic analysis of IFN-y secretion during interaction between CAR-T cells and macrophages. FIG. 27 shows secretion heatmap, incremental analysis, and isotropic analysis of IL-6 secretion during interaction among CAR-T cells, NALM-6 cells and macrophages.

[0041] FIG. 28 shows secretion heatmap, incremental analysis, and isotropic analysis of IFN-y secretion during interaction among CAR-T cells, NALM-6 cells and macrophages.

[0042] FIG. 29 shows imaging of IFN-y secretion from individual CAR-T cells when they were isolated and when they were near B-ALL cells and macrophages. (a) and (b) show the secretion heatmap and isotropic analysis of CAR-T cells, respectively, and panel (c) shows the real-time intensity changes for all cells. T indicates CAR-T cells, M indicates macrophages, and N indicates NALM-6 cells.

[0043] FIG. 30 shows, in panel (a), the electric field plain distribution and scattering cross-section of 30nm AuNP dimer at X=600nm, in which the incident electric filed is parallel to the dimer axis. As the interparticle gap decreases, strong plasmonic coupling by two neighboring nanoparticles causes redshift of resonance peak and increase of SCS’s magnitude as well as electric field norm. Panel (b) shows the optical setup and schematics for SARs-CoV-2 RBD detection under a darkfield microscope. The plasmon rulers were patterned on a glass substrate mounted above an oil condenser (NA=1.45, Nikon). While light from a halogen lamp passes through condenser can illuminate the chip. Only scattering light can be received by objective lens (lOx, NA=0.6). After binding with the target antigen, the conformational change of aptamer causes AuNP dimer approach to each other, leading to strong plasmon coupling and increase of scattering intensity which can be real-time captured by the EMCCD camera.

[0044] FIG. 31 shows, in panel (a), and estimated secondary structure of SARS-CoV-2 aptamer at bound (SEQ ID NO: 6) and unbound state (SEQ ID NO: 5). Original aptamer bases are marked in dark grey. 10T base as the linkers on both 3’ and 5’ end are marked mid-tone grey and designed terminals are marked in light grey. Panel (b) shows the coarse-gained discrete molecular dynamics (DMD) prediction results of secondary structure of aptamer at bound and unbound state. Panel (c) shows end-to-end probability distribution at simulation Temperature of 0.3. Panel (d) shows schematic structure of plasmon ruler. The aptamers were functionalized with a thiol at 5’ end and a bio group at 3 ’end.

[0045] FIG. 32 shows, in panel (a), SPR detection of SARs-CoV-2 RBD at different concentrations in PBS buffer. The system was washed by PBS buffer after 400s to remove unbinding antigens. Panel (b) shows dark-field and electric scanning microscope (SEM) images of nanoplasmon ruler sensor chip. The sensor was imaged on a glass substrate which was sputtered by 3nm gold film to avoid electron accumulations on the glass surface under the SEM. Panel (c) shows COMSOL simulation result for scattering spectrum change of nanoplasmon ruler upon antigen binding under systemic consideration of gap distributions. a), intensity mapping of SARs-CoV-2 RBD binding at different concentrations. The imaging area was 45x45 pixels with one pixel of 8x8 pm. Panel (b) shows real-time binding curve of SARs-CoV-2 RBD on nanoplasmon ruler in PBS buffer in 30min. Panel (c) shows calibration curve for SARs-CoV-2 RBD detection in both PBS and virus transport medium. Panel (d) Correlation between results obtained from the nanoplasmon ruler biosensor and the ELISA for the SARs-CoV-2 RBD sample. Panel (e) shows selective response of nanoplasmon ruler biosensor toward SARs-CoV-2 antigen protein (RBD, SI, S2, nucleocapsid) and MERS-CoV protein.

[0046] FIG. 34 shows optical setup of LSPR immunoassay process. Prepared LSPR chip was mounted on the sample stage of a dark-field microscope. The sample was loaded into microfluidic channel through syringe pump at the speed of luL / min. Scattering light collected by a lOx objective lens was real-time captured by a EMCCD camera and analysed by a customized MATLAB code.

[0047] FIG. 35 shows gap distance distributions of nanoplasmon ruler before and after binding the target.

[0048] FIG. 36 shows a schematic of an exemplary imaging system disclosed herein. Dotted lines refer to optional actions.

[0049] FIG. 37 shows a schematic of an exemplary imaging method disclosed herein. Dotted lines refer to optional actions.

[0050] FIG. 38 shows a schematic of an exemplary method for preparing a sensor chip. Dotted lines refer to optional actions.

[0051] FIG. 39 shows a schematic of an exemplary method for preparing a sensor chip. Dotted lines refer to optional actions.

[0052] DETAILED DESCRIPTION OF THE INVENTION

[0053] Disclosed herein are methods, systems, and devices for rapid and accurate detection of analytes. In some embodiments, the systems, methods, and devices produce spatially resolved, real-time visualization of analytes. In some cases, the analyte may include biomolecules or components of biomolecules, such as proteins, nucleic acids, metabolites, lipids, or combinations thereof. In other cases, the analyte may include a collections of molecules such as exosome. In some cases, the analyte is secreted from one or more cells. As described in Examples, the analyte can be a protein such as a cytokine or a binding domain.

[0054] In one aspect, disclosed herein is a sensor chip. The sensor chip includes a substrate and at least one nanoplasmon ruler immobilized on the substrate. Each nanoplasmon ruler includes a first plasmonic element and a second plasmonic element. In some cases, each nanoplasmon ruler includes a first plasmonic element and a second plasmonic element connected by opposing ends of a single strand nucleic acid connector. The binding of an analyte to the single strand nucleic acid connector induces a conformational change in the single strand nucleic acid connector. The conformational change modulates an end-to-end distance between the first plasmonic element and the second plasmonic element, thereby modulating the nanoplasmonic coupling between the first plasmonic element and the second plasmonic element.

[0055] In some cases, the sensor chip includes a plurality of nanoplasmon rulers. The plurality of nanoplasmon rulers may be immobilized on the substrate so that the plurality of nanoplasmon rulers may be spatially resolved by microscopy or spectroscopy methods, such as by optical microscopy or spectroscopy or electron microscopy or spectroscopy. The plurality of nanoplasmon rulers may be immobilized randomly. In some cases, the nanoplasmon rulers may be immobilized in a pattern, such as a grid, line, spot, or channel.

[0056] Each nanoplasmon ruler includes a first plasmonic element and a second plasmonic element. In some cases, the first plasmonic element is a metal nanoparticle and the second plasmonic element is a metal nanoparticle. The first plasmonic element and the second plasmonic element may include gold, silver, copper, titanium, aluminum, chromium, or other metals which support surface plasmons. The plasmonic elements may comprise spherical, rod, sheet, wire, star, shell, hollow shell, cage, cluster, or combinations thereof. In some cases, the first plasmonic element and the second plasmonic element are plasmonic nanohole arrays, photonic crystals, or any combinations thereof.

[0057] The first plasmonic element and the second plasmonic element are connected by opposing ends of a nucleic acid connector. The nucleic acid connector may be a single stranded nucleic acid. For example, nucleic acid connector may include single-stranded deoxyribonucleic acid (ssDNA), ribonucleic acid (RNA), non-naturally occurring nucleotides, or any combination thereof. In some cases, the single strand nucleic acid connector comprises an aptamer motif having binding affinity for the analyte. In some cases, the single strand nucleic acid connector further comprises a competitive 5’ terminal sequence and / or competitive 3’ terminal sequence. In some embodiments, the single strand nucleic acid connector has less conformational stability in an unbound state than a bound state when bound to the analyte and greater conformational stability in the unbound state than the bound state in the absence of binding to the analyte.

[0058] The substrate may be composed of any material that allows for immobilization of a nanoplasmon ruler and detection of a single. Suitably, the substrate may include glass, PDMS, or a combination thereof. The nanoplasmon ruler may be covalently or noncovalently immobilized on the substrate. For example, as described in Examples 1 and 2, a first, citrate-capped gold nanoparticles electrostatically (i.e., noncovalently) interact with a glass substrate. The nucleic acid connector interacts with the first plasmonic element covalently or noncovalently. For example, the nucleic acid connector may be functionalized with a terminal thiol group which, when using a gold nanoparticle as the first plasmonic element, will form an Au-S bond.

[0059] Connecting the second plasmonic element with a single strand nucleic acid connector may comprise contacting the second plasmonic element having a functionalized surface with the single strand nucleic acid connector, the single strand nucleic acid comprising a conjugated functional group at the second end capable of binding the functionalized surface of the second plasmonic element. In some cases, the single strand nucleic acid connector is conjugated to a thiol group at the first end and conjugated to a biotin group at the second end, the first plasmonic element is a gold nanoparticle, and the second plasmonic element is a streptavidin functionalized gold nanoparticle.

[0060] The Examples disclose preparation of the nanoplasmon rulers on the substrate. Additionally or alternatively, the nanoplasmon rulers may be prepared prior to immobilization.

[0061] In another aspect, referring to FIG. 36, disclosed herein is an imaging system 3600 including a sensor chip 3610 as described above, an illumination source configured to illuminate the sensor chip 3620, and a detector 3630 configured to detect a signal generated by illuminating the sensor chip. Suitably the detected signal is spatially resolvable. The imaging system may further include a processor 3640 configured to process the signal (e.g., spatially resolvable signal), control the illumination source, and / or position the sensor chip. The sensor chip may be surrounded by a housing 3650. The housing 3650 may comprise an inlet for introducing a cell or analyte. In some cases, the detector is configured to detect a modulated signal induced by a conformational change in the single strand nucleic acid connector when the analyte binds the single strand nucleic acid connector. In some cases, the detector is configured to detect scattered light when the sensor chip is illuminated by the illumination source. In some cases, the modulated signal results from surface plasmon resonance (SPR) or localized surface plasmon resonance (LSPR). Skilled artisans can appreciate that there are many commercially available illumination sources, detectors, and processors capable of performing the detection and imaging measurements as disclosed herein, including those described in Examples 1 and 2.

[0062] Also disclosed herein are sensor devices including a housing surrounding a sensor chip, as described above. In some cases, the housing has an inlet for introducing a sample of interest, such as cell or an analyte. In some cases, the housing may include a microfluidics device. In some cases, the microfluidics device includes PDMS.

[0063] In another aspect, an imaging method is disclosed herein. Referring to FIG. 37, the imaging method 3700 includes illuminating a sensor chip 3710, detecting a signal (e.g., spatially resolvable signal) generated as a result of illuminating the sensor chip 3720. The binding of an analyte to the single strand nucleic acid connector modulates the signal (e.g., spatially resolvable signal) compared to the signal in the absence of the analyte binding to the single strand nucleic acid connector.

[0064] Still referring to FIG. 37, the imaging method may further include exposing the sensor to a sample including an analyte of interest 3730. In some cases, exposing the sensor to a sample including an analyte of interest may include introducing a first cell and detecting a signal (e.g., spatially resolvable signal) indicative of an analyte secreted by the first cell binding the single strand nucleic acid connector. In some cases, exposing the sensor to a sample including an analyte of interest may further include introducing a first cell and a second cell and detecting a signal indicative (e.g., spatially resolvable signal) of an analyte secreted by the first cell or the second cell binding the single strand nucleic acid connector.

[0065] In some cases, referring to FIG. 37, the imaging method may further include detecting a multiplicity of signals (e.g., spatially resolvable signals) at different timepoints 3740. The imaging method may further include generating a spatiotemporal map 3750. The imaging method may further include determining an anisotropy relative standard deviation (ARSD), inequality derivative index (IDI), extracellular diffusion coefficient (D), secretion rate, or any combination thereof in action 3760. Referring now to FIG. 38, also disclosed herein is a method for preparing a sensor chip 3800. The method includes immobilizing a first plasmonic element on a substrate 3810, connecting the first plasmonic element with a single strand nucleic acid connector at a first end 3820, connecting a second plasmonic element with a single strand nucleic acid connector at a second end opposite the first end 3830. The binding of an analyte to the single strand nucleic acid connector induces a conformational change in the single strand nucleic acid connector. The conformational change modulates an end-to-end distance between the first plasmonic element and the second plasmonic element, thereby modulating the nanoplasmonic coupling between the first plasmonic element and the second plasmonic element. The method for preparing a sensor chip may further include introducing a cell to the substrate 3840.

[0066] Referring to the methods for preparing a sensor chip of FIG. 38, connecting the first plasmonic element with the single strand nucleic acid connector may include contacting the first plasmonic element and the single strand nucleic acid connector, the single strand nucleic acid connector comprising a conjugated functional group at a first end capable of binding the first plasmonic element. Connecting the second plasmonic element with a single strand nucleic acid connector comprises contacting the second plasmonic element having a functionalized surface with the single strand nucleic acid connector, the single strand nucleic acid comprising a conjugated functional group at the second end capable of binding the functionalized surface of the second plasmonic element. In some cases, the single strand nucleic acid connector is conjugated to a thiol group at the first end and conjugated to a biotin group at the second end, the first plasmonic element is a gold nanoparticle, and the second plasmonic element is a streptavidin functionalized gold nanoparticle.

[0067] In some cases, the single strand nucleic acid and first plasmonic element (e.g., citrate- capped AuNPs) is introduced to the substrate at a ratio between 1 : 1 and 50: 1, between 1 :1 and 100: 1, between 1 : 1 and 10: 1, between 1 : 1 and 5: 1, between 1 : 1 and 2: 1, or between 1 : 1 and 0.5: 1.

[0068] In other embodiments, referring to FIG. 39, a method for preparing a sensor chip 3900 is disclosed herein. The method includes connecting a first plasmonic element with a single strand nucleic acid connector at a first end 3910, connecting a second plasmonic element with a single strand nucleic acid connector at a second end opposite the first end 3920 to form a nanoplasmon ruler (e g., a nanoparticle-aptamer-nanoparticle construct). The nanoruler is immobilized on a substrate 3930. The binding of an analyte to the single strand nucleic acid connector induces a conformational change in the single strand nucleic acid connector. The conformational change modulates an end-to-end distance between the first plasmonic element and the second plasmonic element, thereby modulating the nanoplasmonic coupling between the first plasmonic element and the second plasmonic element. The method for preparing a sensor chip may further include introducing a cell to the substrate 3940.

[0069] The sensor chips, imaging systems, and methods disclosed herein may also perform multiplexed detection of two or more analytes simultaneously. In some cases, multiplexed detection may be accomplished by assembling at least a first nanoplasmon ruler using a first aptamer sequence and a second nanoplasmon ruler using a second aptamer sequence, where the first aptamer sequence and second aptamer sequence are distinct aptamer sequences which undergo conformational changes upon interacting with at least two distinct analytes. Additionally or alternatively, separately identifiable detection channels may be created by using spectroscopically distinguishable nanoplasmon rulers. For example, the size and geometry of the first plasmonic element and second plasmonic element influences the properties, including intensity and wavelength, of the emitted light from the nanoplasmon ruler upon illumination. Leveraging this, separately identifiable detection channels may be created by assembling nanoplasmon rulers having plasmonic elements with spectroscopically distinguishable emission properties.

[0070] Miscellaneous

[0071] Unless otherwise specified or indicated by context, the terms “a”, “an”, and “the” mean “one or more.” For example, “a molecule” should be interpreted to mean “one or more molecules.” As used herein, “about”, “approximately,” “substantially,” and “significantly” will be understood by persons of ordinary skill in the art and will vary to some extent on the context in which they are used. If there are uses of the term which are not clear to persons of ordinary skill in the art given the context in which it is used, “about” and “approximately” will mean plus or minus <10% of the particular term and “substantially” and “significantly” will mean plus or minus >10% of the particular term.

[0072] As used herein, the terms “include” and “including” have the same meaning as the terms “comprise” and “comprising.” The terms “comprise” and “comprising” should be interpreted as being “open” transitional terms that permit the inclusion of additional components further to those components recited in the claims. The terms “consist” and “consisting of’ should be interpreted as being “closed” transitional terms that do not permit the inclusion additional components other than the components recited in the claims. The term “consisting essentially of’ should be interpreted to be partially closed and allowing the inclusion only of additional components that do not fundamentally alter the nature of the claimed subject matter.

[0073] All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.

[0074] All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein.

[0075] Preferred aspects of this invention are described herein, including the best mode known to the inventors for carrying out the invention. Variations of those preferred aspects may become apparent to those of ordinary skill in the art upon reading the foregoing description. The inventors expect a person having ordinary skill in the art to employ such variations as appropriate, and the inventors intend for the invention to be practiced otherwise than as specifically described herein. Accordingly, this invention includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above-described elements in all possible variations thereof is encompassed by the invention unless otherwise indicated herein or otherwise clearly contradicted by context.

[0076] EXAMPLES

[0077] Example 1: Real-Time Visualization of Single-Cell Cytokine Secretomic Signatures During CAR T-Cell Cancer Therapy by Nanoplasmonic Mapping

[0078] B-cell acute lymphoblastic leukemia (B-ALL), characterized by uncontrolled immature lymphocyte growth, presents management challenges due to its genetic complexity and resistance to standard treatments. While FDA-approved CD19-targeted CAR T-cell therapy offers hope, especially for recurrent pediatric B-ALL cases, its success in clinical trials has been unpredictable and inconsistent, largely influenced by the quality of CAR T cells and varying leukemic immunophenotypes. Moreover, CAR tumor antigen recognition triggers cytokine release, leading to cytokine release syndrome (CRS), and diverse cytokine responses among patients complicate disease control and treatment standardization. Hence, an in-depth understanding of CAR T-cell activation, cytokine release dynamics, and longitudinal evolution is vital for improving single-cell cytokine response analysis, comprehending leukemia-induced CRS, and augmenting the safety and efficacy of CAR T-cell therapy. A nuanced analysis with high spatiotemporal resolution is paramount to navigate clinical challenges and refine CAR T-cell therapeutic strategies.

[0079] Traditional methods such as enzyme-linked immunoassay (ELISA), polymerase chain reaction (PCR), and intracytoplasmic cytokine staining (flow cytometry) provide valuable bulk immune response measurements but fall short in dissecting cellular heterogeneity and individual CAR T-cell functions at the single-cell level. Although recent advancements in single-cell immunoassays, such as barcode and microengraving immunoassay, enable multiparametric cytokine detection from individual cells, the detection is static and often involves laborious labeling and washing steps, preventing real-time cytokine monitoring. Existing technologies attempting real-time secretory protein imaging from target cells, including interferometric detection of scattered light (iSCAT), photonic crystal resonances (PhC), and total internal reflection fluorescence microscopy (TIRFM), have yet to establish a method for directly visualizing and tracing cytokine production, diffusion, and transportation with high spatiotemporal resolution.

[0080] Disclosed herein is the 'nanoplasmon ruler', a label-free nanoplasmonic single-molecule sensing technique designed for in situ single-cell cytokine secretomics mapping and cellular crosstalk exploration. Leveraging potent plasmonic coupling via aptamer-cytokine binding, nanoplasmon ruler imaging (NRI) allows wash-free, real-time molecular binding visualization with unparalleled spatial resolution. Employing computationally designed, cytokine-specific aptamer-based nanoplasmon rulers, Inventors achieved highly sensitive, in situ spatiotemporal mapping of single-cell cytokine secretion for interleukin 6 (IL-6) and interferon-gamma (IFN-y). The analysis also delineated the cytokine secretomic signatures of activated single T cells, identifying two distinct secretion patterns based on cytokine secretion direction uniformity. Further exploration of cellular communication among single CAR T cells, macrophages, and leukemia cells revealed macrophages and CAR T cells to be primary sources of IL-6 and IFN-y, respectively, during interactions. The NRI system provides invaluable insights into cellular secretion behaviors and interactions, offering a novel perspective on immune and CAR T-cell crosstalk and offering a pathway to refine CAR T-cell immunotherapy for optimized efficacy and safety in cancer treatment.

[0081] Results and Discussion

[0082] Nanoplasmon ruler design and experimental principle

[0083] Each nanoplasmon ruler includes a metal nanoparticle (NP) dimer connected by a singlestrand DNA aptamer featuring a conformational switch that generates a light scattering spectrum upon optical excitation (Fig. 1). The peak frequency and intensity of this spectrum, reflective of the NP interparticle distance, shift upon cytokine binding due to the consequent aptamer conformation change that draws the NPs closer together (Fig. la). Utilizing an electronmultiplying CCD (EMCCD) detector and a dark-field microscope, Inventors captured scattering light intensity changes triggered by aptamer-cytokine binding events and, through monitoring intensity alterations across a microfluidic chip array of nanoplasmon rulers, achieved the in situ, real-time mapping of secretory cytokine binding (Fig. lb). Analyzing the mapped cytokine secretion patterns yielded insights into secretion signatures, facilitating the investigation of secretion anisotropy, rates, and extracellular diffusion coefficients (Fig. 1c), which are crucial for understanding the spatiotemporal dynamics of cytokine secretion and its implications for cellular communication and immunotherapy development.

[0084] Optimizing the nanoplasmon ruler's design and sensing performance involved numerical modeling via COMSOL Multiphysics, affirming that scattering intensities were primarily impacted by strong plasmon resonance (Fig. 5a-5b) and inversely related to the distance between two AuNPs (Fig. 5c). Subsequent aptamer sequence redesign introduced a competing short sequence to disrupt the original, target-binding-compatible structure, introducing new base pairs in an alternative conformational state. Taking an anti-IL-6 aptamer as an example, a 10-nt sequence was engineered into the 3' end to competitively interact with the G-quadruplex structure in the aptamer's binding sequence (Fig. 2a and 2b). A coarse-grained discrete molecular dynamics (DMD) simulation predicted that aptamer-target complex formation significantly reduced the anti- IL-6 aptamer's average end-to-end distance (Fig. 2c, 7a). A similar restructuring of the anti-IFN- y aptamer was predicted to result in a decrease the aptamer’s end-to-end distance and AuNP dimer gap distance upon IFN-y binding (Fig. 6a-6b, 7b), with substantial increases in scattering intensity and resonance peak redshift. In summary, these results demonstrate the optimized design of aptamers for nanoplasmon rulers targeting IL-6 and IFN-y.

[0085] Nanoplasmon ruler assembly and sensing performance

[0086] Initially, Inventors aimed to fabricate monodisperse, self-assembled nanoplasmon rulers on a glass substrate within a microfluidic chamber utilizing a straightforward nanomaterial patterning approach (Fig. 9). The on-chip assembly of AuNP dimers onto engineered aptamers was accomplished through streptavidin-biotin interactions and Au-S bonds. By optimizing the stoichiometric ratio of aptamers to AuNPs (Fig. 10), Inventors attained over a 70% yield of AuNP dimer structures with a 2:1 aptamer / AuNP ratio (Fig. 2d), ensuring a robust sensing surface for accurately recording single-cell cytokine secretion events. The scattering spectrum of the assembled nanoplasmon rulers revealed a 9.9% intensity increase and an 8 nm redshift in the scattering peak upon the introduction of a 5 ng / mL standard IL-6 solution (Fig. 2e). The NRI displayed dynamic responses to varying IL-6 concentrations within a 0~5 ng / mL range over 30 minutes (Fig. 2f), and the limits of detection for IL-6 and IFN-y were 61 pg / mL (Fig. 2g) and 79 pg / mL (Fig. 11), respectively. The specificity of NRI, validated against several other cytokines, produced negligible scattering intensity changes after incubation (Fig. 12). Compared to conventional cytokine immunoassays, Inenvtors’ NRI's digital image processing and analysis approach delivers superior spatial resolution, enabling the precise localization of cytokine binding events with heightened sensitivity and selectivity. This advanced capability facilitates a more thorough assessment of single-cell secretion patterns, which will enable deeper investigations into immune cell function and heterogeneity.

[0087] Measurement of the single-cell cytokine secretomic signatures of activated T cells

[0088] To showcase the feasibility of NRI for single-cell cytokine secretomic analysis, Inventors employed Jurkat T cells activated by 12-myristate 13-acetate (PMA) and ionomycin as a model, leveraging the pivotal role of the secretion of key cytokines (i.e., IL-6 and IFN-y) by T cells in adaptive immunity. After seeding activated T cells (10?cells / mL) into microchannels with immobilized nanoplasmon rulers (Fig. 3a), Inventors captured real-time cytokine secretion profiles of individual cells by taking dark-field microscopy images of the sensing chamber at 10- second intervals for 30 minutes (Fig. 3b). These spatiotemporally resolved scattering intensitybased images were converted into concentration-based secretion patterns using the established calibration curve (Fig. 3c, f). The acquired concentration profiles of secretory cytokines were then analyzed to discern distinct single-cell cytokine secretomic signatures, including the secretion rate, extracellular diffusion coefficient (D), and secretion anisotropy of cytokines.

[0089] Intriguingly, Inventors identified two distinct secretion signatures marked by consistent cytokine secretion directions and the amounts secreted along these directions. A subset of activated T cells (Fig. 3g) exhibited less uniform secretion patterns than others (Fig. 3d). To quantitatively characterize these patterns, Inventors introduced a scalar parameter, the anisotropy relative standard deviation (ARSD), defined as ARSD = a d rection! Ccytokine, where ^direction is the standard deviation of 24 sets of mean concentration within a defined direction’s area (with each image divided into 24 directions, each covering an angle range of 15°), and Ccytokme represents the average cytokine concentration across all directions. High ARSD values indicate substantial secretion variation, signifying a highly anisotropic cytokine secretion pattern from a single immune cell. A representative anisotropic secretion example is shown in Fig. 3f-h for cell 2, where IL-6 was predominantly secreted and diffused polarly along the diagonal targeting angles (Fig. 3g), with ARSD values between 0.73 and 0.79 in the 20th~30th minutes (Fig. 3h). In contrast, a typical isotropic secretion example (cell 1, Fig. 3c-e) exhibited more uniform cytokine production at each angle (Fig. 3d), with lower ARSD values of 0.34 to 0.39 under identical stimulation conditions (Fig. 3e). By amalgamating the density-based spatial clustering of applications with noise (DBSCAN) algorithm and artificial recognition, an ARSD value of 0.5 was set as the threshold to distinguish secretion isotropy (Fig. 13-15). Interestingly, the significant majority (85%) of cells with an ARSD value greater than 0.5 exhibited markedly more anisotropic secretion behavior than the remaining 15% with ARSD values below 0.5 (see Fig. 16), indicating that anisotropic IL-6 secretion is prevalent among individual activated T cells. A similar trend was observed for IFN-y release from activated T cells (Fig. 16). This secretomic anisotropy could be linked to the asymmetrical presentation of ligands on cell surfaces and the membrane's stimulation location directly influencing secretion direction.

[0090] To further explore real-time variations in cell secretion, an incremental analysis was performed, as illustrated in Fig. 3c and 3f, based on the concentration differences observed at 5- minute intervals. Hotspots and contour lines highlight areas of predominant secretion increases. The x- and y-axis profde analysis yielded cumulative differences across columns and rows within the image. Leveraging these axis profiles, a novel inequality derivative index (IDI) was devised to assess secretion symmetry. In the concentration-incremental images (Fig. 3c and 3f, bottom), both cell 1 and cell 2 show expanding hotspot ranges over time, suggesting a diffusion effect induced by central source secretion. At each observed time point, the more isotropic cell 1 consistently exhibited a lower IDI compared to the notably anisotropic cell 2.

[0091] Following Inventor’s secretomic anisotropy observations, Inventors estimated the cytokine secretion rates of individual activated T cells by determining the slope of the linear curve fitted based on the total cytokine secretion amount versus elapsed time (Fig. 3i). Subsequently, Inventors calculated the extracellular diffusion coefficient (D) of cytokines within the extracellular environment to understand the mobility and dispersion of cytokines by fitting the obtained cytokine secretion profiles to a well-established solitary cell secretion model (Fig. 3j, model details provided below). Through 30-minute continuous monitoring of a single activated T cell, Inventors simultaneously obtained three cellular characteristics (ARSD, D, and secretion rate), offering a multifaceted view of T-cell functional dynamics. Fig. 3k shows real-time IL-6 secretion curves from 20 individual T cells, with the averaged curve (orange dots / area) indicating a consistent secretion rate of ~11 cytokine molecules / s on average (see IFN-y secretion curves in Fig. 17).

[0092] In this analysis, both IDI and ARSD values were used to characterize cell secretion isotropy, where IDI assesses secretion signal symmetry along the x- and y-axis, while ARSD evaluates secretion signal homogeneity in all directions. To probe potential interrelations, Inventors juxtaposed the IDI and ARSD values derived from all stimulated single T cells within the 5~30 minute timeframe (Fig. 3i), aiming to discern correlations or discrepancies. Inventors’ observations indicated that ARSD values can more precisely determine cell secretion isotropy (discussion in ‘IDI Vs ARSD’ below). The IDI can complement ARSD values as a supplementary parameter, enhancing the reliability of isotropic and anisotropic determinations.

[0093] Utilizing the three cytokine secretomic signatures acquired from activated single T cells, Inventors evaluated the independence of these signatures through correlation analysis. A Pearson correlation coefficient test explored the correlations among ARSD, D, and secretion rate, revealing a strong negative correlation between ARSD and secretion rate for IL-6 (Pearson correlation coefficient = -0.63, Fig. 3m, left), with a p value less than 0.01, suggesting that this negative correlation likely persists in a larger T-cell population. The plot of ARSD against secretion rate (Fig. 3m, right) clearly showed that ARSD decreased as the secretion rate increased. Similar findings were observed for IFN-y secretion (Fig. 18). The correlation between ARSD values and secretion rate might be elucidated by varying the expression of cytokine receptors on the plasma membrane, such as SNAP -23 and syntaxin-4, which are implicated in SNARE-mediated exocytosis. With increased cytokine release, cytokine receptor expression also increases, rendering receptor distribution on the plasma membrane more uniform and less random and thereby leading to less anisotropic cytokine secretion.

[0094] Exploring the diffusion process associated with IL-6 and IFN-y secretion by activated T cells, Inventors found the mean diffusion coefficient (D) values to be 421.7 pm2 / min for IL-6 and 754.8 pm2 / min for IFN-y (Fig. 3n, left), which was consistent with previous findings. The higher D value for IFN-y is due to its lower molecular weight compared to IL-6, which facilitates faster diffusion. Comparing the average secretion rates and ARSD values of IL-6 and IFN-y in activated T cells revealed similar average secretion rates (11 molecules / s for IL-6 and 10 molecules / s for IFN-y), which was corroborated by the literature. However, individual cell secretion rates for IL- 6 and IFN-y varied significantly, spanning over two orders of magnitude (0.2-66.3 molecules / s for IL-6; 0.3-48.2 molecules / s for IFN-y). Additionally, the ARSD values for IL-6 secretion ranged from 0.2 to 1.8 (average 1.0), and those for IFN-y secretion ranged from 0.3 to 2.2 (average 0.8, Fig. 3n, right). The lower average ARSD value for IFN-y secretion could be due to fewer cells (30%, ARSD>1.36, Fig. 13) exhibiting a pronounced anisotropic secretion pattern. This analysis underscores the high heterogeneity among individual T cells, reflecting the intricacy of immune cell functionality. It also exemplifies the capability of NRI to yield high-resolution, real-time data on individual cytokine secretion patterns, paving the way for an enriched analysis to decipher the complex dynamics and heterogeneity in immune cell interactions, as seen in CAR T-cell immunotherapy scenarios.

[0095] Analysis of intercellular communication among CAR T cells, macrophages and B-ALL cells at the single-cell level

[0096] In pursuing a nuanced understanding of single-cell communication during CAR T-cell immunotherapy (Fig. 4a), Inventors cocultured CD19 CAR-T cells, B-ALL cells (NALM-6 cells), and monocyte lineage-derived macrophages (THP-1 cells) in various combinations and performed NRI to chart spatiotemporal cytokine secretion profiles for these cells (Fig. 4a). 4b~4d, Fig. 19, Fig. 21-29) Fig. 4b showcases a representative image of the three cell types cocultured together, which triggered sustained secretion of IL-6 and IFN-y at rates of 6 molecules / s and 0.5 molecules / s, respectively (‘Cell-cell communication’ discussed below). During a 30-minute observation, individual CAR T cells and macrophages did not secrete IFN-y, but their interaction induced secretion at 23 molecules / s (Fig. 4c). Interactions between a macrophage and a CAR T cell, a B- ALL cell, or both produced IL-6 at rates of 5 (MT1), 5, and 7 molecules / s, respectively. Conversely, isolated macrophages, CAR T cells, and B-ALL cells did not produce IFN-y or IL-6 (Fig. 20).

[0097] The combination of a CAR T-cell with either a B-ALL cell or a macrophage stimulated IFN-y secretion at average rates of 19 molecules / s and 7 molecules / s, respectively (Fig. 4e), whereas the copresence of a B-ALL cell with a macrophage yielded negligible amounts of IFN-y (0.1 molecules / s). CAR T-cell / B-ALL cell / macrophage clusters also produced IFN-y at an average rate of 11 molecules / s (Fig. 28). These results suggest that CAR T cells can be activated by either B-ALL cells or macrophages to produce IFN-y. Interestingly, direct contact between a CAR T-cell and a B-ALL cell or a macrophage does not appear to be necessary for the activation of CAR T- cell IFN-y secretion, as isolated CAR T cells secreted IFN-y when near a B-ALL cell and a macrophage, although cell contact prior to observation could have occurred (Fig. 29). In addition, the combination of CAR T cells and B-ALL cells did not result in notable IL-6 secretion (0.1 molecules / s). However, when a macrophage was present with a B-ALL cell or a CAR-T cell, IL- 6 production was stimulated at average rates of 8 molecules / s or 14 molecules / s, respectively. CAR T-cell / B-ALL cell / macrophage clusters produced IL-6 at an average rate of 11 molecules / s (Fig. 27).

[0098] After investigating more cell interactions, Inventors discovered that coculturing a CAR T- cell with a B-ALL cell or macrophage induced IFN-y secretion at average rates of 19 and 7 molecules / s, respectively (Fig. 4e), while pairing a B-ALL cell with a macrophage yielded a negligible IFN-y rate of 0.1 molecules / s. CAR T-cell / B-ALL cell / macrophage clusters also secreted IFN-y at an average of 11 molecules / s (Fig. 28). These findings imply that CAR T-cell activation for IFN-y production can be initiated by either B-ALL cells or macrophages, even without direct contact, as isolated CAR T cells secrete IFN-y when proximate to these cells (Fig. 29). Conversely, CAR T and B-ALL cell coculture marginally impacted IL-6 secretion (0.1 molecules / s), whereas adding a macrophage stimulated IL-6 production at 8 molecules / s with a B- ALL cell and 14 molecules / s with a CAR-T cell. CAR T-cell / B-ALL cell / macrophage coculture averaged an IL-6 output of 11 molecules / s (Fig. 27). Considering macrophages as a principal IL- 6 source during CRS, Inventors’ observations imply that ligand interactions with either CAR T cells or B-ALL cells activate macrophages, initiating IL-6 secretion. Intriguingly, the ARSD values for all cell combinations were inversely correlated with their secretion rates: B-ALL cell / macrophage interaction exhibited the highest ARSD value of 3.6 and the lowest IFN-y secretion rate (0.1 molecules / s) (Fig. 4f), while CAR T-cell / B-ALL cell interaction displayed an opposing trend with a minimal ARSD of 0.9 and maximal IFN-y rate (19 molecules / s). Likewise, for IL-6, the CAR T-cell / B-ALL cell interaction and CAR T-cell / macrophage interaction presented opposing extremes in secretion rates and ARSD values of 0.1 and 14 molecules / s and 2.9 and 0.9 molecules, respectively. These findings underscore the consistent negative correlation between ARSD values and secretion rates in both single-cell and cell interaction analysis, accentuating the nanoplasmon ruler’s utility in unraveling complex cytokine secretion dynamics and immune cell interactions during CAR T-cell immunotherapy. Such detailed analyses may refine therapeutic strategies and address challenges in CAR T-cell-induced CRS.

[0099] Conclusions

[0100] Inventors have pioneered a nanoplatform biosensing technology that enables the high spatiotemporal resolution mapping of single-cell cytokine secretomic signatures during CAR T- cell immunotherapy. The self-assembled nanoplasmon ruler sensor, with high sensitivity and high spatiotemporal resolution, permits real-time imaging of cytokine secretion via a wash-free homogeneous detection method. This advanced tool revealed previously unobserved heterogeneity in activated T cells, validating the feasibility of its use for single-cell analysis, and identified a negative secretion rate-anisotropy correlation in single-cell and cell cluster analyses, helping to elucidate biological mechanisms. Insights from three secretomic signatures facilitated exploration of the roles and functions of three cell types in cellular communication during CAR T-cell immunotherapy, providing the inaugural visualization of single-cell IFN-y and IL-6 cytokine crosstalk during therapy. This approach holds substantial promise for advancing the understanding of single-cell secretion and intercellular communication in CAR T-cell therapy and broader immunology research. Future research could adapt Inventors’ approach to investigate cellular interactions in other pathologies, such as inflammatory diseases and various cancers, potentially catalyzing opportunities in clinical settings for developing tailored therapeutic strategies rooted in a nuanced understanding of cellular behaviors and interactions.

[0101] Methods

[0102] Reagents and materials

[0103] Poly-L-lysine hydrobromide, tri s(2-carboxy ethyl) phosphine hydrochloride (TCEP-HC1), magnesium chloride (MgCh), phorbol 12-myristate 13-acetate (PMA), and ionomycin were purchased from Sigma-Aldrich. Hydrogen peroxide (H2O2, 30 wt.% in H2O), sulfuric acid (H2SO4, 95~98 wt.% in H2O), ethyl alcohol (70 wt.% in H2O), and streptavidin were obtained from VWR. Tween 20 (10% w / v in H2O) was obtained from Axela Biosensors. Glass substrates were obtained from Corning. SYLGARD 184 silicone elastomer kit was purchased from the Dow Chemical Company, l x phosphate buffered saline (PBS) buffer (pH 7.4) was obtained from Gibco. 30 nm gold nanoparticles (AuNPs) (0.05 mg / mL in aqueous sodium citrate buffer) were purchased from NanoComposix. Hoechst 33342 Solution, red fluorescent protein (RFP), green fluorescent protein (GFP), recombinant human IL-6, recombinant human IFN-y, recombinant human IL-2 , recombinant human IL-10, and recombinant human IL-1 were obtained from Thermo Fisher Scientific. Customized IL-6 and IFN-y DNA aptamer, IDTE (pH 8.0, IX TE Solution), and nuclease-free duplex buffer (30 mM HEPES, pH 7.5; 100 mM potassium acetate) were purchased from Integrated DNA Technologies (IDT); Dimethylsulfoxide (DMSO, 4-X™) was purchased from ATCC.

[0104] Electromagnetic field simulation with the AuNP dimer

[0105] To theoretically estimate the relationship between the scattering spectrum and interparticle gap of the nanoplasmon ruler, Inventors evaluated the electric field distribution near the surface of the AuNP dimer upon interaction with the external electric field using the commercial multiphysics simulation software COMSOL. The AuNP size was set to 30 nm. Inventors defined a far-field domain surrounding the AuNP dimer with a radius of half the wavelength of the incident light. A perfectly matched layer of the same thickness was set on top of the far-field domain, in which the scattering light decayed exponentially. The incident light was set parallel (Figure 5a) or perpendicular (Figure 5b) to the dimer axis. The mesh size was 1 nm. The scattering intensity of the scattering wave from the nanoplasmon ruler was evaluated through the scattering cross section Cscs, which can be calculated by integrating the intensity of the scattering wave over the surface of the far-field plane :

[0106] Cscs = f - - - dQ. [si]

[0107] ‘background where I is the scattering intensity from the nanoplasmon ruler, and Ibackground is the background intensity in the absence of the nanoplasmon ruler.

[0108] Coarse-grained discrete molecular dynamics (DMD) simulations

[0109] In DMD simulations, temperatures were presented as the reduced unit of kcal / (mol*fe), and Inventors used eight replica simulations with the following temperatures: 0.200, 0.225, 0.250, 0.270, 0.300, 0.333, 0.367, and 0.400. Inventors employed the weighted histogram analysis method to compute the distribution of end-to-end distances at T=0.300.

[0110] Aptamer sequence redesign

[0111] Inventors first optimized the design and sensing performance of the nanoplasmon ruler. Numerical modeling via COMSOL Multiphysics confirmed that scattering intensities were chiefly impacted by strong plasmon resonance parallel to the dimer axis (Fig. 5a-5b) and inversely related to the distance between two AuNPs within the structure (Fig. 5c). Subsequently, Inventors employed an aptamer sequence redesign, mirroring riboswitches in gene regulation, to maximize the changes in dimer distance upon cytokine binding (details given below). Specifically, a competing short sequence was introduced into either the 5' or 3' region to disrupt the original structure compatible with target binding (the "on" state), creating newly engineered base pairs in an alternative conformational state (the "off state). As the stability of this redesigned state (AGoff) lies between that of the "on" state of the aptamer alone (AGon) and that of the aptamer-target complex (AGon+AGbinding), the redesigned aptamer adopts the "off state without the target and switches to the "on" state with the target present.

[0112] Taking the anti-IL-6 aptamer as an example, inspired by a screened 32-nt anti-IL-6 aptamer with a binding constant Ka ~ 0.16 nM (AGbinding ~ -12.4 kcal / mol), Inventors engineered a 10-nt sequence attached to the 3' end to competitively interact with the G-quadruplex structure in the aptamer's binding sequence (Fig. 2a and 2b). Inventors employed coarse-grained discrete molecular dynamics (DMD) for predicting aptamer end-to-end distance alterations and the replica exchange method for enhanced conformational sampling. DMD simulations indicated that aptamer-target complex formation reduced the anti-IL-6 aptamer's average end-to-end distance from 7.0 nm to 3.9 nm (Fig. 2c) and the AuNP dimer gap distance from 5.8 nm to 4.9 nm upon IL-6 binding, considering steric hindrance (Fig. 7a). COMSOL simulation predicted a 4.8% scattering intensity increase and a 10 nm redshift in the resonance peak after IL-6 binding (Fig. 7a). Similarly, Inventors restructured the anti-IFN-'y aptamer (Fig. 6a) to theoretically decrease the aptamer’s end-to-end distance from 12.3 nm to 6.3 nm (Fig. 6b) and the AuNP dimer gap distance from 7 nm to 2.65 nm upon IFN-y binding (7b), with a predicted 23.2% increase in scattering intensity and a 20 nm redshift in the resonance peak (Fig. 7b). Collectively, these outcomes illustrate the optimized design of two aptamers for crafting nanoplasmon rulers targeting IL-6 and IFN-y.

[0113] LSPR immunoassay

[0114] Nanoplasmon rulers were self-assembled in the microfluidic device on a glass chip (Figure 9). A high-precision syringe pump (Masterfl ex, 100 to 240 VAC) was used to control the flow rate. Glass slides were first washed using DI water and dried in an oven. They were placed in piranha solution (FLSO^FLCL = 3: 1 v / v) for 10 min, followed by a thorough wash with DI water. Finally, the glass slide was rinsed in DI water and placed in an ultrasonic bath for 15 min. To pattern the AuNPs, the prepared PDMS mask was bonded onto the glass substrate. Then, Inventors loaded poly-L-lysine hydrobromide solution (PLL, Sigma) (0.1 mg / mL) into each channel at a flow rate of 1.5 pL / min for 6 min followed by 0.2 pL / min for 2 min. Then, Inventors sealed the inlets and outlets with a cover glass to prevent liquid evaporation from the channel and incubated the chip for at least 4 hr. Afterward, each channel was washed with DI water at a flow rate of 1.5 pL / min for 4 min, and then AuNP stock solution (0.05 mg / mL) was loaded into each channel at a flow rate of 1.5 pL / min for 6 min followed by 0.2 pL / min for 2 min. The chip was incubated overnight.

[0115] A DNA aptamer targeting human IL-6 was conjugated with a biotin group on one end and a thiol group on the other end. To prepare the stock solution, the lyophilized aptamer was suspended in IDTE buffer at a stock concentration of 100 pM and stored at -20 °C. Prior to use, the aptamer was reduced because thiol-modified oligos are in the oxidized form. 10 uL of 10 rnM TCEP solution was added to the same volume of aptamer stock solution and allowed to sit for approximately two hours at room temperature. Then, folding buffer (30 mM HEPES, pH 7.5; 100 mM potassium acetate) was used to dilute the aptamer to a 10-100x working concentration. To fold the aptamer, the solution was heated to 90-95 °C for 5 min and then cooled to room temperature (~15 min). Then, the folded aptamer was diluted to the working concentration using working buffer (1 mM MgCh in IDTE buffer).

[0116] After constructing the AuNP microarray patterns on the glass substrate, Inventors functionalized them with the aptamer within the microfluidic flow-patterning channels constructed above. To remove the unbound AuNPs, 20 pL of IDTE buffer was used to thoroughly wash the channel at 2 pL / min. Then, the reduced aptamer at a working concentration of 1 nM was loaded into each channel at a flow rate of 1.5 pL / min for 6 min, followed by 0.2 pL / min for 2 min and incubation overnight.

[0117] Adsorption of streptavidin (SA) on AuNPs was achieved by adding 100 pL of SA solution (100 nM in lx PBS buffer) to 100 pL of AuNP solution (0.05g / mL, pH=l 1), and the mixture was kept on ice for 1 h. The solution was centrifuged for 5 min at 12000 rpm. The unreacted excess SA was removed by discarding the supernatants and redispersing the particles in 100 pL of DI water.

[0118] After washing the channel with 20 pL of IDTE buffer to remove the excess unbound aptamer at a flow rate of 2 pL / min for 4 min, streptavidin-functionalized AuNP solution was loaded into each channel at a flow rate of 1.5 pL / min for 6 min, followed by 0.2 pL / min for 2 min and incubation overnight, for binding with aptamer-functionalized AuNPs to form the nanoplasmon rulers.

[0119] Real-time dynamic cytokine binding curve

[0120] The dark-field microscopy measurements were performed on a Nikon Eclipse Ni-U system. After the fabrication of the nanoplasmon ruler, the prepared immunoassay chip was mounted on a motorized X-Y stage (ProScanlll, Prior Scientific, Rockland, MA), which allowed automated image scanning. The back of the chip was attached to a dark-field condenser (NA=1.45, Nikon) with lens oil. A lOx objective lens (Nikon) was used in the system. Before performing the measurement, the PDMS layer used for the nanoplasmon ruler function was removed immediately and replaced with another sample-loading PDMS microfluidic channel placed perpendicularly. Before performing optical measurements, 30 pL of cell medium was loaded into the on-chip flow channel at a speed of 1.5 pL / min to stabilize the initial light intensity of the sensing spots. After signal stabilization, the cytokine sample was loaded into the channel using a syringe pump at 0.5 pL / min for 30 min. Automated imaging was performed with an ultrasensitive electron -multiplying CCD (EMCCD, Photometries) and recorded for NIS-Element BR analysis. Scattering intensities within the entire fixed sensor area of 250 x 250 pixels (400 x 400 pm2) were monitored at 10- second intervals. To ensure accurate positioning and minimize random errors caused by vibrations or other factors, each 5 x 5 pixel (8 x 8 pm2) region was treated as an individual sensing spot (equivalent to the size of a single cell), with intensity changes (I-Io) / Io) of each spot processed separately.

[0121] The real-time intensity change in the sensing area was obtained via MATLAB code, which computed the intensity difference between the analyzed image and the first image and obtained the relative intensity change: where Ii is the average intensity in the analyzed area for the first dark-field image. To characterize the uncertainty and limit of detection of Inventors’ LSPR microarray system, Inventors performed a control experiment measuring the variance of the background signal with nanoplasmon ruler microarrays loaded with cell medium solution. The average system uncertainty determined by the minimum distinguishable signal is equivalent to a confidence factor set to 3 times the standard deviation of the background noise (o). The detection limits of the target cytokines were thus calculated as 3o / ksiOpe, where ksioPe is the slope of calibration curves using linear fitting. Figure 11 shows real-time intensity changes on the sensor surface and the calibration curve for IFN-y detection. To investigate NRI selectivity, the sensors were challenged with interfering proteins, including 1 ng / mL human IL- 10, TNF-a, IL -2, and IL-1 (Figure 12), and no significant responses were observed.

[0122] Jurkat human T cell culture

[0123] Jurkat human T cells (CRL-2901TM, ATCC) were cultured in RPMI-1640 containing 10% fetal bovine serum (ATCC® 30-2020™) and 200 pg / mL G428. Cells were incubated at 37 °C with 5% CO2 in a Cell Culture Incubator (Thermo Scientific). To maintain a suitable cell culture concentration between 1 xlO3and IxlO6cells / mL, the culture medium was replaced two to three times per week. Cells at the needed concentration were collected via centrifugation at 125 g for 5 min, with subsequent resuspension in fresh culture medium.

[0124] Cell staining

[0125] To prepare stock solutions of GFP and RFP antibodies at a concentration of luM, lyophilized antibodies were reconstituted in Dimethylsulfoxide (DMSO, 4-XTM, ATCC). Subsequently, a 1 : 10000 dilution of the stock solution was made using lx PBS (pH=7.4), resulting in a final working concentration of 0.1 pg / mL. Cells were washed twice with PBS to eliminate excess culture medium, then suspended in the GFP / RFP working solution at a concentration of IxlO6cells / mL. The cells were incubated for 1 hour at room temperature with gentle agitation. Following incubation, the solution was removed, and the cells were washed twice with lx PBS before being resuspended in cell culture medium with concentration of 1x106cells / mL. For Hoechst 33342 Solution, the working solution should be 5ug / mL and incubation time was 20 minutes.

[0126] T cell stimulation and single-cell secretion patterning image

[0127] One milliliter of Jurkat T cells was suspended in the cell culture medium at a concentration of IxlO6cells / mL. A mixture of PMA (100 ng / mL, Sigma-Aldrich) and ionomycin (1000 ng / mL, Sigma-Aldrich) was added to the T-cell solution to stimulate cytokine secretion. The stimulated T cells were diluted to IxlO5cells / mL, loaded into PDMS channels and allowed to settle randomly on the prepared nanoplasmon ruler surface. The dark-field images were captured with an exposure time of 10 s for 30 mins.

[0128] Anisotropic analysis of cytokine secretion

[0129] Isotropy leads to uniform cytokine secretion from the cell in all directions, which means that the concentration distributions tend to be consistent surrounding the cell. In contrast, anisotropy occurs when cytokine secretion is restricted to specific regions. The anisotropic nature of cytokine secretion in different directions (every 30°) was determined by the anisotropy ratio - the ratio of the standard deviation of the concentration in different directions (every 15°) to the average concentration of the whole analyzed area (120 pm x 120 pm around the cell). Standard deviation

[0130] Anisotropy ratio = [S3]

[0131] Average concentration

[0132] Figures 14-15 show the secretion heatmap, incremental analysis, and isotropic analysis of IL-6 and IFN-y secretion from single activated T cells. Combining the density-based spatial clustering of applications with noise (DBSCAN) algorithm and artificial recognition, an ARSD value of 0.5 is preset as the boundary to determine the isotropy of secretion (see Figure 16). Figure 17 shows the ARSD values in the 15thto 30thmin, which suggest that 15% (3 out of 20) of T cells exhibited isotropic secretion of IL-6 and 26% (6 out of 23) of T cells exhibited isotropic secretion of IFN-y.

[0133] Cytokine mapping during CAR T-cell therapy using a nanoplasmon ruler

[0134] Human acute lymphoblastic leukemia cells (NALM-6, CRL-3273™) were cultured in RPML1640 medium (Invitrogen) supplemented with 10% FBS and 1% penicillin / streptomycin at 37 °C in a 5% CO2 incubator. NALM-6 cells were collected, suspended at IxlO5cells / ml and labeled with green fluorescent protein (GFP) for cell tracing. Human THP-1 cells (TIB202™, ATCC) were grown in RPML1640 medium supplemented with 10% FBS and 1% penicillin / streptomycin at 37 °C in a 5% CO2 incubator. Macrophages were differentiated from THP-1 cells by subjecting the THP-1 cells to a 24-hour incubation with 100 nM PMA, followed by an additional 24-hour incubation after replacing the medium with culture medium. Macrophages were fluorescently labeled with Hoechst solution (Thermo Scientific, 62249) according to the manufacturer’s instructions. Briefly, macrophages were incubated with serum - free RPML1640 containing 1 U / mL Hoechst solution for 25 min at 37 °C, followed by rinsing with RPML1640 medium three times. The labeled macrophages were then collected and resuspended at IxlO5cells / ml for further use. Human CD19 CAR-T cells (PM-CAR- 1003-1 M, ProMab) were expanded with 1 ml of T-cell medium supplemented with 200 U of IL-2 and 25 pl of anti-CD3 and CD8 activator in ImmunoCult™-XF T-Cell Expansion Medium (Stemcell Technologies, catalog # 10981), and red fluorescent protein (RFP) was added for fluorescencebased cell tracing. After expansion, CAR-T cells were collected and resuspended at IxlO5cells / ml for further use.

[0135] Fig. 4b showcases a representative image of the cocultured CAR T cells (red fluorescent protein (RFP)-labeled), macrophages (Hoechst-labeled), and B-ALL cells (green fluorescent protein (GFP)-labeled) at a ratio of 10:2:1 over 5 hours. This cellular interaction fostered cell cluster formation, triggering sustained secretion of IL-6 and IFN-y at rates of 6 molecules / s and 0.5 molecules / s, respectively. The computed ARSD values for IL-6 and IFN-y secretion were 1.1 and 2.1, respectively, underscoring the efficacy of NRI in analyzing cell clusters containing multiple interacting cells.

[0136] CD 19 CAR-T cells, B-ALL cells (NALM-6), and macrophages differentiated from a monocyte lineage (THP-1) were cocultured in various combinations for 5 hours. The resultant mixtures were used for NRI of both IL-6 and IFN-y secretion immediately after the cells interacted. The typical responses for all the combinations are shown in Figure 19. When macrophages, CAR- T cells, or B-ALL cells were situated individually, no significant IFN-y or IL-6 signals were produced in the local environment (see Fig. 20). The secretion heatmap, incremental analysis, and isotropic analysis of IL-6 and IFN-y secretion from various cell combinations are shown in Figures 21-29

[0137] Supporting Information

[0138] Characterization of gold nanoparticles

[0139] The gold nanoparticles (AuNPs) used in this study were purchased from NanoComposix in aqueous sodium citrate (2 mM) buffer and had an average diameter of 30 nm (0.05 mg / mL). The citrate coating on the AuNRs resulted in a negatively charged surface with a zeta potential of -48±0.5 mV (Zetasizer Nano ZS90, Malvern). The scattering spectrum of the AuNPs in solution was obtained using a spectrophotometer. The resonance peak wavelength of the AuNPs is approximately 520 nm (Figure 8). Morphological studies of the nanoplasmon ruler were performed using scanning electron microscopy (SEM, Hitachi TM 3000). An HR4000 high- resolution user-configured spectrometer (Ocean Optics) was used to analyze the sensing spots on the chip (Figure 2d) .

[0140] PDMS microfluidic channel fabrication

[0141] A microfluidic flow-patterning mask layer mold was fabricated on a silicon substrate by deep reactive-ion etching (DRZE). The mold contains five parallel microfluidic channels (400 pm (W) x 2.5 cm (L) x 50 pm) for AuNP patterning and function. To make the microfluidic mask layer, a liquid PDMS (Sylgard-184, Dow Coming) prepolymer fully mixed with a cross-linker at a weight ratio of 10: 1 was exposed to vacuum to completely remove air bubbles. After degassing, the mixture was poured onto the silicon mask mold wafer and degassed using a vacuum pump, and then Inventors placed the Petri dish containing the wafer in an oven for 6 h at 70 °C. The cured PDMS mask layer could be easily peeled off the mold wafer and cut into several pieces. Then, a hole puncher with a 1 mm diameter was used to create the inlets and outlets of the channel.

[0142] Biosensor optimization

[0143] To optimize the sensor behavior, Inventors demonstrated the correlation between the aptamer-to-AuNP ratio during the assembly process and the final nanoplasmon ruler density in the sensing area. A constant AuNP concentration was used as 0.05 mg / mL. Five different ratios of aptamer to AuNPs (1: 1, 2:1, 5: 1, 10:1, and 50:1) were evaluated, and the nanoplasmon ruler densities were determined from SEM images (Figure 10).

[0144] IDI vs. ARSD

[0145] To probe potential interrelations, Inventors juxtaposed IDI and ARSD values derived from all stimulated single T cells within the 5~30 minute timeframe (Fig. 3i), aiming to discern correlations or discrepancies. The more isotropic T cells predominantly exhibited values of ARSDO.5 and IDI<0.5. Conversely, all anisotropic T cells had ARSD>0.5 or IDI>0.5. Interestingly, some anisotropic cells had IDI<0.5 and ARSD>0.5, but none had IDI>0.5 and ARSD<0.5, highlighting ARSD's superiority for estimating cell secretion isotropy. This finding suggests the potential pitfalls of relying solely on symmetry as an indicator since symmetry might not always reflect secretomic direction preference. For instance, cell 2 (Fig. 3f~h) exhibits relatively high signal distribution symmetry with an IDI between 0.39 and 0.42, differing from most other anisotropic cells with IDI>0.5. However, cell 2 displays polarized secretion in the diagonal direction (as depicted in Fig. 3g), a hallmark of anisotropic behavior. This observation further bolsters the conclusion that ARSD values can serve as a more precise indicator for determining cell secretion isotropy. In addition, the IDI can complement ARSD values by serving as a supplementary parameter, enhancing the reliability of isotropic and anisotropic determinations.

[0146] Mathematical model for diffusion coefficient analysis To analyze the kinetics of cytokine secretion during imaging, a mathematical model was built based on a previously reported model of cyto / chemokine diffusion during the intercellular signaling process.

[0147] Single suspended solitary cells can be regarded as a source of cytokine secretion with a spherical surface. The time-dependent mass transport from a single cell can be described by the following equation: where C is the cytokine concentration, r is the distance, and D is the diffusion coefficient. There are three boundary conditions: (1) the secretion rate (Fo) is constant at the cell surface; (2) there are no cytokines far away from the cell; and (3) the cytokine concentration surrounding the cell is 0. These conditions can be stated as follows: dC

[0148] At r = p, Fo= —D — dr

[0149] At r -> oo, C -> 0

[0150] At t = 0, C = 0 where p is the cell radius. Notably, cell secretion can be asymmetric and show a “plume” shape around the cell. Then, the diffusion analysis will be restricted in that specific direction using the same model. The final diffusion equation can be expressed as:

[0151] The diffusion coefficient was obtained by the numerical approximation method performed in MATLAB.

[0152] Correlation analysis of cell secretion

[0153] A Pearson correlation coefficient test was conducted for the ARSD, D, and secretion rate. The ARSD values for IFN-y secretion were negatively correlated with the secretion rates, with a Pearson and Kendall correlation coefficient of -0.53 (Fig. 18).

[0154] Example 2: Nanoplasmon ruler for SARs-CoV-2 Receptor-Binding Domain detection

[0155] COVID- 19 pandemic caused by novel coronavirus (SARS-CoV-2) has resulted in around 2 million human deaths and nearly 100 million people have been infected. At the meantime, the continuous mutation of SARs-CoV-2 virus still present the ongoing threat of future pandemic. Most countries are now in the throes of a second wave at the onset of winter, leading to overwhelmed testing laboratories and medical institutions. There are several experimental effective vaccines have approved by FDA. However, before mass vaccination to transform the fight against COVID- 19, fast and accurate virus test and trace is still crucial in order to reopen the society safely.

[0156] Real-time reverse transcription-polymerase chain reaction (RT-PCR), as the primary method of nucleic acid detections, provides a relatively accurate test result. However, several hours’ detection time and laboursome operation procedures make PCR laboratories overwhelmed in such massive daily detections. Rapid viral antigens’ tests mainly for virus spike (S) protein, envelope (E) protein, membrane (M) protein, nucleocapsid protein (N) are, then, likely to play a big part in COVID- 19 testing strategies. Among them, S protein is mainly responsible for receptor binding and viral attached, serving as a key target for vaccines and antibodies. Previous studies have proved that the receptor-binding domain (RED) in the SARS-CoV-2 SI subunit plays the key role in viral attachment and entry by selectively bind with the ACE2 receptor which is expressed on host cells membrane, making RBD of the SARS-CoV-2 spike protein a key target for COVID- 19 diagnosis.

[0157] Nanoplasmon ruler consists of a metallic nanoparticle dimer linked by a biomolecule such as DNA or RNA. The resonating free electrons on both particle surfaces can generate a light scattering spectrum that can be tuned by the interparticle separation. These distance-dependent plasmon resonance behavior and large scattering cross-section during the strong plasmon coupling process make nanoplasmon ruler have significant potentials in sensor area. A decreasing interparticle separation results in a red-shift of the resonance spectrum and electric field enhancement which can be real-time monitored by a dark-field microscope. As shown in Figure 30a, the maximum electric field between two 30nm AuNPs with lOnm interparticle distance is around 30 v / m for incident wavelength is 600nm. When the interparticle distance is reduced to 5nm, electric filed reaches to around 70 v / m. This distance relevant plasmon coupling is even more sensitive in smaller gap distance as electric filed dramatically reaches to 110 v / m with 2nm interparticle distance. Aptamers are usually short single-strangled DNA or RNA molecules that bind to a specific target molecule. Compared to antibodies, aptamers have relative smaller size and can be easily chemical synthesized and precisely modified. After binding the analyte, the aptamer goes through conformational change leading to end-to-end distance change.

[0158] Inventors developed a self-assembled nanoplasmon ruler biosensor integrated with a dark -field image system to detection SARS-COV-2 spike protein RBD. Specifically, the optic setup based on a dark-field scattering scheme will include a dark-field condenser (NAM.4), a lOx objective (NA=0.6), an ultra-sensitive EMCCD camera (Photometries). The hybrid plasmonic ruler patterned on the glass substrate will be illuminated by guiding white light into the dark-field condenser from a halogen lamp. The binding of the target molecule brought the paired AuNPs into close proximate, yielding a significantly enhanced plasmonic coupling. Then, the scattering light intensity change from the arrays upon molecule binding will be captured by an EMCCD camera and analyzed using a customized MATLAB code (Figure 34). The unique optical response from plasmonic coupling is highly specific, allowing the wash-free homogeneous detection, which is the key to achieving the detection with high sensitivity and selectivity.

[0159] Results and discussions

[0160] Design an DNA aptamer with a robust conformational switch.

[0161] Effective target detection by the plasmon ruler requires a controllable and large conformation change before and after target molecule binding. Since a given DNA / RNA aptamer does not necessarily undergo end-to-end distance change upon antigen binding, Inventors propose a ribosome switch to force the aptamer to have “off’ state and “on” state by adding a competing short complementary sequence to a part of reported aptamer in either the 5’ or 3’ regions. The stability of redesigned structure sequence (AGoff) is stronger than the stability of the "on" state of the aptamer alone (AGon) but weaker than that of the aptamer-target complex (AGon+AGbinding). The redesigned aptamer prefers the "off" state before binding but switches to the "on" state in the presence of the target molecule. Inventors introduce a 14-nt sequence to the 5’ end and 13-nt sequence to the 3’ end (Figure 31a). The coarse-gained discrete molecular dynamics (DMD) was performed to estimate the conformational change of designed aptamer in “on” and “off” state showing by the simplified three-bead nucleotide model, where different colors of bead corresponding to groups of linkers, designed terminal, and original terminal (Figure 31b). The “On” state had the average end-to-end distance of ~8nm, while the “off” state had the average end- to-end distance of ~12nm (Figure 31c). Inventors also predicted the gap distance distribution between AuNP dimer conjugated with designed aptamer after considering the steric hindrance (Figure 35). Inventors predicted that the average gap distance change upon SARs-CoV-2 RBD binding is ~ 3nm. In order to assemble the nanoplasmon ruler, Inventors modified the aptamer with a thiol group on the one end and a biotin group on the other end. 10-T base was also functioned on both sides to serve as a spacer to avoid space steric hindrance. Aptamers can be directly functionalized to AuNPs through Au-S bond on the thiol group, while biotin group on the other end of aptamer has high binding affinity with streptavidin. Then, one aptamer can conjugate a bare AuNP and a streptavidin functionalized AuNP to form the final plasmon ruler structure (Figure 31d)

[0162] To verify the designed aptamer, Inventors use SPR technology first to characterize the binding kinetic between aptamer and SARs-Cov-2 RBD. The aptamer was immobilized on an Au film chip through Au-S bond. Uncovered chip surface was blocked with bovine serum albumin (BSA) and 6-Mercapto -1-hexanol. lOmM NaOH served as the regeneration buffer. SARs-CoV-2 RBD solutions ranging from 9.375nM to 500nM were injected into the SPR chamber for about 400s followed by washing SPR cell with PBS buffer to remove the unspecific binding antigens. The RBD specifically bound to aptamer leads to a change of resonance angle. The signals, showed in Figure 32a, were proportional to the analyte concentration. The Kd value of the aptamers is ~70nM. It proved the designed aptamer has good affinity to SARs-Cov-2 RBD.

[0163] The performance of nanoplasmon ruler was identified using LSPR device. The plasmon ruler sensors were first uniformly patterned on the APTES -functioned glass substrate through step- by-step injection of every component into PDMS microfluidic device covered on the glass substrate. Optimized aptamer-to- AuNPs ratio was required to ensure only one aptamer conjugated with a Au dimer. High aptamer concentration promoted the formation of trimer, pentamer, and AuNPs aggregations which would lead to a broad scattering spectrum and compromise the sensitivity of sensor, while monomer AuNP made small contributions to final signal due to the week scattering light. Dark-filed image and scanning electron microscope (SEM) image presented well distributed plasmonic sensors and high plasmon ruler ratio (-70%) (Figure 32b). Optical scattering simulation of nanoplasmon ruler based on the gap distance distribution upon SARs-Cov- 2 RBD binding showed a red-shift of resonance spectrum and large scattering intensity increase, proving theoretical feasibility of current system (Figure 32c). To quantify the SARs-Cov-2 concentration, scattering intensity change was recorded at a sensing spot with 250 x 250 pixels (400 x 400 pm2) under the dark-field microscope by an ultrasensitive electron multiplying CCD (EMCCD, Photometries) with a frame acquisition rate at every 10s for 30 min. To minimize system error, 5x5 pixels (8 x 8 pm2) were set as a detection unit due to the tiny image vibration. The relative intensity changes ((I-Io) / I) of every detection after introduction of the target antigen for 30 minute into the LSPR nanoplasmon ruler sensor device were subtracted using a customized MATLAB code and showed in a form of heatmap (Figure 33a). The real-time response of nanoplasmon rulers towards SARs-CoV-2 RBD at concentration of 10, 100, 500, 1000, 5000 pg / mL can also be recorded (Figure 32b). Inventors performed a control experiment to measure the background signal of nanoplasmon ruler biosensor with no antigen loaded. The average background change is -0.4% with standard deviation of 0.08%. The Limited of detection (LOD) of the sensor was thus obtained from 3a / k, where k is defined as the slope of the calibration curves using sigmoidal curve-fitting. The LOD is down to 18 pg / mL of SARs-CoV-2 in PBS, showing high sensitivity in antigen detection. Inventors also performed the antigen detection in virus transport medium (VTM) which is a commonly used buffer to suspend COVID-19 on the nasopharyngeal swabs for PCR testing. The results were similar comparted to the detection in PBS with LOD of 23 pg / mL, revealing the great potential of nanoplasmon ruler sensor in clinical sample detection (Figure 32c). Inventors then used the existing “gold-standard” assay-ELISA to validate immunoassay results obtained from nanoplasmon ruler biosensor. The prepared SARs-COV-2 RBD unknown samples were measured on both two detection systems. The LSPR detection results were well fitted with the ELISA results, proving the accuracy and reliability of the system (Figure 32d). Inventors then evaluated the biding specificity of nanoplamon ruler. The sensor showed no affinity toward S2 subunit, N protein, and MERS. Approximately 90% of binding were maintained in several antigens’ mixture environment. Besides, the sensor showed good binding affinity to SARs-CoV-2 SI protein. These results demonstrated that the nanoplasmon ruler could recognize RBD in SI protein and discriminated RBD in relative complex environment.

[0164] Conclusion

[0165] Rapid and accurate testing devices play a critical role in controlling the COVID-19 pandemic. Inventors developed a LSPR sensor based on nanoplasmon ruler structure in which a well controllable conformational change aptamer conjugated with a AuNP dimmer. The sensor was able to detect SAR-CoV-2 RBD with high sensitivity and selectivity, providing a new choice for COVID-19 as well as other antigen detections.

[0166] Methods

[0167] COMSOL simulation.

[0168] Electric filed plain distribution and scattering cross-section simulation of AuNP dimer with different interparticle separations were simulated using COMSOL. The size of AuNP was set as 30nm in diameter. The incident wavelength is 600nm, in which the incident electric filed is parallel to the dimer axis.

[0169] Coarse-grained discrete molecular dynamics (DMD) simulations.

[0170] In DMD simulations, temperatures were in the reduced unit of kcal / (molDkB) and Inventors used eight replica simulations with following temperatures: 0.200, 0.225, 0.250, 0.270, 0.300, 0.333, 0.367, and 0.400. Inventors employed the weighted histogram analysis method to compute the distribution of end-to-end distances at T=0.300.

[0171] Surface plasmon resonance analysis

[0172] Surface plasmon resonance (SPR) experiments were performed using a BIAcore 2000 biosensor system to measure the binding affinity of selected aptamers. The chip surface was functioned with SARs-CoV-2 RBD aptamer. 6-Mercapto -1 -hexanol solution were used to block the chip surface. After stabilizing the baseline, at least five different concentrations of the SARS- COV-2 spike protein solution were injected into the flow cells. The protein surface was regenerated with 10 mM NaOH after injection of each sample and re-equilibrated with the running buffer. The SPR sensograms were analyzed to calculate the association rate constant ka and the dissociation rate constant kd using BIA evaluation software (Version 3.2, BIAcore).

[0173] LSPR detection

[0174] The prepared nanoplasmon ruler functioned chip was mounted on sample stage of a darkfield microscope (Nikon N-elips) which was able to perform the automated time-lapse image record. The back of the chip was attached with a dark-field microscope condenser (NA=0.6, Nikon) via lens oil. Before doing the measurement, PDMS layer used for plasmon ruler function was removed immediately and replaced with another sample-loading PDMS microfluidic channels perpendicularly. The sample was loaded into the channel with O. luL / min during the 30min measurement.

[0175] Supporting Information

[0176] Reagents

[0177] 30nm citrate AuNPs were purchased from nanoComposix. SARs-CoV-2 RBD, SARs- CoV-2 Spike SI subunit, SARs-CoV-2 Spike S2 subunit, SARs-CoV-2 nucleocapsid were purchased from RayBiotech. Redesigned SARs-CoV-2 RBD aptamer were synthesized by Integrated DNA Technologies (IDT) with HPLC purification. Phosphate-buffered saline (PBS, pH=7.4, including 136.8 mM NaCl, 10.1 mM Na2HPO4, 2.7 mM KC1, 1.8 mM KH2PO4, 0.55 mM MgC12) and viral transport medium (VTM, 2% FBS,100pg / mb Gentamicin, and 0.5 pg / mL Amphotericin in a Hanks Balanced salt solution base ), were used as detection buffer.

[0178] APTES functioned glass.

[0179] The glass slide was first washed by Piranha solution (H2SO4:H2O2 = 3: 1 v / v) for 10 minute and dried in the oven. Then, the slide was further cleaned with plasma for 3 min under lOOw power and immersed in l%(v / v) APTES solution overnight under room temperature. After that, the glass slides were wash by ethanol and DI water.

[0180] Plasmon ruler assembling.

[0181] Nanoplasmon rulers were assembled step by step on the APTES-functioned glass slide through PDMS microfluidic channels (400 pm (W) x 2.5 cm (L) x 50 pm). First, citrate AuNPs were self-assembled on the glass surface through electrostatic interactions. AuNPs stock solution (0.5 nM, 30nm) was loaded into each sensor chamber and incubated overnight.

[0182] Aptamer functioned AuNP was achieved by forming Au-S bond during the interaction between AuNP and the thiol group on the one end of the aptamer. DNA aptamer targeting human SARS-CoV-2 RBD were first reduced by lOmM TCEP solution to fully reduce to oxidized thiol - modified oligos for Ih. Then, the aptamer solution was diluted to 10-100x working concentration by Nuclease-free Duplex Buffer (30 mM Hepes, pH 7.5, 100 mM KAc) and heated to 90-95 °C for 5 min. After cooling to the room temperature, the folded aptamer was diluted to InM in TE buffer. Prepared aptamer solution was loaded into microfluidic channels and incubated overnight. After that, streptavidin-functioned AuNP (lOOnm SA solution mixture with 0.5nm AuNPs for Ih at pH 11) was loaded into sensor chamber and incubated overnight to bind with biotin group on the other side of the aptamer to form the nanoplasma ruler.

[0183] Table 1. Sequences of the redesigned aptamer (Sequence in bold and Italic are original terminals; sequence in bold are linker).

Claims

CLAIMS1. A sensor chip comprising a substrate and a plurality of nanoplasmon rulers immobilized on the substrate, wherein each nanoplasmon ruler comprises a first plasmonic element and a second plasmonic element connected by opposing ends of a single strand nucleic acid connector, wherein binding of an analyte to the single strand nucleic acid connector induces a conformational change in the single strand nucleic acid connector, and wherein the conformational change modulates an end-to-end distance between the first plasmonic element and the second plasmonic element, thereby modulating the nanoplasmonic coupling between the first plasmonic element and the second plasmonic element.

2. The sensor chip of claim 1, wherein the plurality of nanoplasmon rulers are spatially resolvable.

3. The sensor chip of any one of claims 1-2, wherein the single strand nucleic acid connector comprises an aptamer motif having binding affinity for the analyte.

4. The sensor chip of claim 3, wherein the single strand nucleic acid connector further comprises a competitive 5’ terminal sequence and / or competitive 3’ terminal sequence, wherein the single strand nucleic acid connector has less conformational stability in an unbound state than a bound state when bound to the analyte and greater conformational stability in the unbound state than the bound state in the absence of binding to the analyte.

5. The sensor chip of any one of claims 1-2 having a cell capable of secreting the analyte on the substrate, optionally wherein the single strand nucleic acid connector comprises an aptamer motif having binding affinity for the analyte and further optionally wherein the single strand nucleic acid connector further comprises a competitive 5’ terminal sequence and / or competitive 3’ terminal sequence, wherein the single strand nucleic acid connector has less conformational stability in an unbound state than a bound state when bound to the analyte and greater conformational stability in the unbound state than the bound state in the absence of binding to the analyte.

6. The sensor chip of claim 5 having a first cell and a second cell on the substrate, wherein at least one of the first cell or the second cell is capable of secreting the analyte.

7. The sensor chip of any one of claims 1-6, wherein the single strand nucleic acid is conjugated to a functional group capable of binding the first plasmonic element and / or the single strand nucleic acid is conjugated to a functional group capable of binding a functionalized surface of the second plasmonic element.

8. The sensor chip of claim 7, wherein the single strand nucleic acid is conjugated to a thiol group at a first end bound to a gold nanoparticle and a biotin group at a second end bound to a streptavidin functionalized gold nanoparticle.

9. The sensor chip of any one of claims 1-8, wherein the first nanoplasmonic element is a first metal nanoparticle and the second nanoplasmonic element is a second metal nanoparticle.

10. The sensor chip of any one of claims 1-9, wherein the plurality of nanoplasmon rulers are configured for multiplexed detection.

12. A sensor device comprising a housing surrounding the sensor chip of claim 1, wherein the housing comprises an inlet for introducing a cell or an analyte.

13. The sensor device of claim 12, wherein the sensor chip is the sensor chip according to any one of claims 2-11.

14. An imaging system comprising the sensor chip of claim 1, an illumination source configured to illuminate the sensor chip, and a detector configured to detect a signal generated by illuminating the sensor chip.

15. The imaging system of claim 14, wherein the detector is configured to detect a spatially resolvable signal.

16. The imaging system of any one of claims 14-15, wherein the detector is configured to detect a modulated signal induced by a conformational change in the single strand nucleic acid connector when the analyte binds the single strand nucleic acid connector.

17. The imaging system of any one of claims 14-16, wherein the detector is configured to detect scattered light when the sensor chip is illuminated by the illumination source.

18. The imaging system of any one of claims 14-17, wherein the sensor chip is surrounded by a housing comprising an inlet for introducing a cell or an analyte.

19. The imaging system of any one of claims 14-18, wherein the imaging system comprises a processor configured to process a spatially resolvable signal, control the illumination source, and / or position the sensor chip.

20. The imaging system of any one of claims 14-19, wherein the sensor chip is the sensor chip according to any one of claims 2-14.

21. An imaging method comprising illuminating the sensor chip of claim 1 and detecting a signal generated by illuminating the sensor chip, wherein binding of an analyte to the single strand nucleic acid connector modulates the signal compared to the signal in the absence of the analyte binding to the single strand nucleic acid connector.

22. The imaging method of claim 21, wherein the method comprises detecting a spatially resolvable signal.

23. The imaging method of any one of claims 21-22 further comprising introducing a first cell and detecting a signal indicative of an analyte secreted by the first cell binding the single strand nucleic acid connector.

24. The imaging method of any one of claims 21-22 further comprising introducing a first cell and a second cell and detecting a signal indicative of an analyte secreted by the first cell or the second cell binding the single strand nucleic acid connector.

25. The imaging method of any one of claims 21-22 further comprising introducing the analyte and detecting a signal indicative of the analyte binding the single strand nucleic acid connector.

26. The imaging method of any one of claims 21-25, wherein the analyte is a biomolecule.

27. The imaging method of claim 26, wherein the biomolecule is a protein.

28. The imaging method of any one of claims 21-22 further comprising detecting a multiplicity of spatially resolvable signals at different timepoints.

29. The imaging method of claim 28 further comprising generating a spatiotemporal map.

30. The imaging method of claim 29 further comprising determining an anisotropy relative standard deviation (ARSD), inequality derivative index (ID I), extracellular diffusion coefficient (D), secretion rate, or any combination thereof.

31. The imaging method of any one of claim 28-30, further comprising introducing a first cell or a second cell and detecting a signal indicative of the analyte secreted by the first cell or the second cell binding the single strand nucleic acid connector or introducing theanalyte and detecting a signal indicative of the analyte binding the single strand nucleic acid connector.

32. The imaging method of any one of claims 21-31, wherein the sensor chip is the sensor chip according to any one of claims 2-14.

33. A method for preparing a sensor chip, the method comprising: immobilizing a first plasmonic element on a substrate; connecting the first plasmonic element with a single strand nucleic acid connector at a first end; connecting a second plasmonic element with a single strand nucleic acid connector at a second end opposite the first end; wherein binding of an analyte to the single strand nucleic acid connector induces a conformational change in the single strand nucleic acid connector; and wherein the conformational change modulates an end-to-end distance between the first plasmonic element and the second plasmonic element, thereby modulating a nanoplasmonic coupling between the first plasmonic element and the second plasmonic element.

34. The method of claim 33, wherein connecting the first plasmonic element with the single strand nucleic acid connector comprises contacting the first plasmonic element and the single strand nucleic acid connector, the single strand nucleic acid connector comprising a conjugated functional group at a first end capable of binding the first plasmonic element, and wherein connecting the second plasmonic element with a single strand nucleic acid connector comprises contacting the second plasmonic element having a functionalized surface with the single strand nucleic acid connector, the single strand nucleic acid comprising a conjugated functional group at the second end capable of binding the functionalized surface of the second plasmonic element.

35. The method of claim 34, wherein the single strand nucleic acid connector is conjugated to a thiol group at the first end and conjugated to a biotin group at the second end, the first plasmonic element is a gold nanoparticle, and the second plasmonic element is a streptavidin functionalized gold nanoparticle.

36. The method of any one of claims 33-35, wherein the single strand nucleic acid and first plasmonic element is introduced to the substrate at a ratio between 1 : 1 and 50: 1.

37. The method of any one of claims 33-36 further comprising introducing a cell to the substrate.

38. The method of any one of claims 33-37, wherein the method prepares the sensor chip according to any one of claims 1-14 or the sensor device according to any one of claims 15-16.

Images