A method for detecting lipid nanoparticle-protein interactions based on graphene-based sensors

Abstract

This invention discloses a method for detecting lipid nanoparticle-protein interactions based on a graphene-based sensor, belonging to the field of biomedical detection and analysis technology. The graphene-based sensor is a graphene field-effect transistor sensor or a laser-induced graphene sensor, comprising a graphene sensing region. Lipid nanoparticles are bound to the graphene sensing region, allowing the lipid nanoparticles to contact the protein. The interaction between the lipid nanoparticles and the protein is determined by the change in the electrical signal of the graphene-based sensor before and after contact. Lipid nanoparticles have different affinities for different types of proteins, thus determining their targeting specificity. This invention achieves rapid, immediate, and high-throughput analysis of lipid nanoparticle-protein interactions by measuring changes in electrical signals, maximizing the preservation of the natural activity of biological samples, and providing accurate detection.

Description

Technical Field

[0001] This invention belongs to the field of biomedical detection and analysis technology, specifically relating to a detection method for lipid nanoparticle-protein interactions based on a graphene-based sensor. Background Technology

[0002] Lipid nanoparticles, as highly efficient drug delivery systems, have been widely used in gene therapy and vaccine development. The in vivo targeting ability of lipid nanoparticles directly determines their organ distribution and therapeutic efficacy; therefore, establishing efficient and quantifiable targeting evaluation methods is fundamental to achieving precise delivery and optimizing formulation design. Currently, methods for detecting the targeting ability of lipid nanoparticles mainly include three technical pathways: molecular level, cellular level, and animal level.

[0003] At the molecular level, existing technologies mainly employ surface plasmon resonance (SPR) and fluorescence resonance energy transfer (FRET) methods for detecting the targeting of lipid nanoparticles. SPR typically involves immobilizing receptor proteins or simulating biological membranes on the surface of a gold microarray. By monitoring the changes in the SPR induced by incident light, the refractive index changes during the binding of lipid nanoparticles to proteins and the formation of protein crowns are recorded in real time, thereby calculating binding kinetic parameters, as illustrated in the literature Baimanov D, Wang J, Liu Y, et al. Identification of Cell Receptors Responsible for Recognition and Binding of Lipid Nanoparticles[J]. Journal of the American Chemical Society, 2025, 147(9). DOI:10.1021 / jacs.4c16987. FRET, on the other hand, involves labeling fluorescent donors and acceptors onto nanoparticles or proteins, respectively. Energy transfer occurs when the distance between them is less than 10 nm, and the degree of binding is analyzed by detecting changes in fluorescence intensity or lifetime. For example, patent document CN105928919A discloses a method for detecting parameters of the formation process of scleroprotein crowns on the surface of nanoparticles using fluorescence resonance energy transfer (FRET) technology. This invention quantitatively characterizes the interaction between nanoparticles and adsorbed proteins by changing the intensity of the FRET signal. However, both surface plasmon resonance (SPR) and FRET methods rely on sophisticated optical detection systems, which are large, costly, and have complex platform structures. They also require strict experimental environments, making on-site detection difficult. Furthermore, these methods primarily characterize the molecular binding process indirectly based on changes in optical signals, making it difficult to directly obtain key electrical parameters such as changes in the surface charge of lipid nanoparticles. Consequently, they cannot analyze the selective mechanism of lipid nanoparticle-protein binding from the perspective of interfacial charge regulation.

[0004] At the cellular level, current techniques typically involve co-incubating fluorescently labeled lipid nanoparticles with target and non-target cells, analyzing cellular uptake efficiency using flow cytometry or confocal microscopy, and evaluating delivery capability by combining reporter gene expression or gene silencing efficiency. At the animal level, current techniques generally involve intravenous or local administration followed by in vivo fluorescence imaging and tissue section analysis to determine the distribution and expression levels of lipid nanoparticles in various organs, thus analyzing their targeting specificity. While these cellular and animal experiments can reflect the biological effects of lipid nanoparticles, they generally suffer from long experimental cycles, high costs, low sample throughput, and low formulation iteration efficiency, making it difficult to meet the needs of rapid screening of large-scale lipid nanoparticle formulations in the early stages.

[0005] Therefore, there is a need to develop a low-cost, miniaturized, high-throughput method for rapid targeted detection of lipid nanoparticles that can simultaneously acquire charge-related parameters. Summary of the Invention

[0006] To address the shortcomings of the prior art, this invention provides a method for detecting lipid nanoparticle-protein interactions based on graphene-based sensors. Lipid nanoparticles have different affinities for different types of proteins, which determines their targeting. This invention achieves rapid, instantaneous, and high-throughput analysis of lipid nanoparticle-protein interactions by measuring changes in electrical signals.

[0007] The specific technical solution adopted is as follows: A method for detecting lipid nanoparticle-protein interaction based on a graphene-based sensor, wherein the graphene-based sensor is a graphene field-effect transistor sensor or a laser-induced graphene sensor, including a graphene sensing region, and lipid nanoparticles are bound to the graphene sensing region to bring the lipid nanoparticles into contact with the protein. The interaction between the lipid nanoparticles and the protein is determined by the change in the electrical signal of the graphene-based sensor before and after contact. The graphene sensing region of the graphene field-effect transistor sensor was modified with 1-pyrene butyric acid, and lipid nanoparticles were bound after the carboxyl group was activated. After depositing gold nanoparticles on the graphene sensing region of a laser-induced graphene sensor, a self-assembled monolayer of 11-mercaptoundecanoic acid / 6-mercapto-1-hexanol was modified, followed by activation of carboxyl groups to bind lipid nanoparticles. Alternatively, cysteine ​​can be grafted onto the aforementioned carboxyl-activated graphene field-effect transistor sensor or laser-induced graphene sensor, and lipid nanoparticles can be combined under the action of a catalyst.

[0008] Different formulations of lipid nanoparticles result in variations in their surface charge and structure, leading to different affinities for various proteins and thus affecting their targeting specificity. Graphene-based sensors can respond to changes in the electrical properties of charged molecules adsorbed on their surface. Based on this, this invention uses lipid nanoparticles as a biosensing layer to detect the properties of lipid nanoparticles and their interactions with proteins, thereby further analyzing the surface charge, protein affinity, and even in vivo targeting properties of different lipid nanoparticles.

[0009] The graphene field-effect transistor sensor comprises, from bottom to top, a substrate, a Cr / Au electrode array, an insulating layer, another Cr / Au electrode array, a graphene channel, and an encapsulation layer; the graphene channel is exposed and serves as the sensing area. Specifically, the source of the graphene field-effect transistor sensor is a Cr / Au electrode array connected to one end of the graphene channel, the drain is a Cr / Au electrode array connected to the other end of the graphene channel, and the gate is a Cr / Au electrode with a window on the top layer.

[0010] The laser-induced graphene sensor is connected to the printed circuit board via a flexible flat cable adapter. The structure of the laser-induced graphene sensor includes a substrate layer, a patterned gold circuit, a laser-induced graphene electrode, and an encapsulation layer. The laser-induced graphene electrode is exposed and serves as the sensing area. The exposed part of the patterned gold circuit serves as the counter electrode. The part covered by the encapsulation layer is used to connect the laser-induced graphene electrode and the printed circuit board.

[0011] When a graphene field-effect transistor sensor is selected, the interaction between lipid nanoparticles and proteins is determined by the change in the transfer characteristic curve after the addition of a protein solution, thus determining the targeting of the lipid nanoparticles. The transfer characteristic curve is obtained by keeping the source-drain voltage constant, continuously scanning the gate voltage, and synchronously recording the corresponding drain current. When using a laser-induced graphene sensor, the source-drain voltage remains constant during the detection of lipid nanoparticles in contact with proteins. The interaction between lipid nanoparticles and proteins is determined by the change in source-drain current after the addition of a protein solution.

[0012] Furthermore, the substrate layer is a polyimide layer, and a microfluidic structure is bonded to the polyimide layer. The microfluidic structure is used for the preparation of lipid nanoparticles, and the corresponding setup can integrate lipid nanoparticle preparation and targeted detection into one.

[0013] Preferably, the method for modifying 1-pyrenebutyric acid is as follows: an organic solution of 24-36 mM 1-pyrenebutyric acid is added to the graphene sensing region to modify 1-pyrenebutyric acid.

[0014] Preferably, the method for depositing gold nanoparticles is electroplating deposition, which involves preparing an electroplating solution of 0.5-2 mM chloroauric acid and 10-15 mM sulfuric acid to electroplat and deposit gold nanoparticles on the graphene sensing region (laser-induced graphene electrode); and using an organic solution containing 0.3-0.6 mM 11-mercaptoundecanoic acid and 0.8-1.2 mM 6-mercapto-1-hexanol to perform 11-mercaptoundecanoic acid / 6-mercapto-1-hexanol self-assembled monolayer modification.

[0015] Specifically, carboxyl activation can be performed using methods known to those skilled in the art, such as 1-(3-dimethylaminopropyl)-3-ethylcarboimide / hydroxysuccinimide activation.

[0016] Preferably, cysteamine grafting can be performed using an 8-12 mM aqueous solution of cysteamine, and the catalyst can be potassium iodide or hydrogen peroxide.

[0017] Specifically, the cysteine ​​grafting method can achieve the elution and recombination of lipid nanoparticles. Specifically, after grafting cysteine ​​onto the above-mentioned carboxyl-activated graphene field-effect transistor sensor or laser-induced graphene sensor, the first type of lipid nanoparticle is bound under the action of a catalyst, followed by elution, and then the second type of lipid nanoparticle is re-bound under the action of a catalyst (the eluted and re-bound lipid nanoparticles can be the same or different).

[0018] Furthermore, the elution method is as follows: using dithiothreitol to break the bonds connecting the lipid nanoparticles and the graphene sensing region, and then washing away the lipid nanoparticles.

[0019] Specifically, lipid nanoparticle raw materials that are activated with carboxyl groups include amino-terminated lipids, such as distearyl phosphatidylethanolamine, dipalmitoyl phosphatidylethanolamine, dimyristoyl phosphatidylcholine, dioleoyl phosphatidylethanolamine, dilauryl phosphatidylethanolamine, distearyl lecithin, dipalmitoyl phosphatidylcholine, and dimyristoyl lecithin, which are amino groups linked to amino groups via polyethylene glycol chains.

[0020] Specifically, the lipid nanoparticle raw materials grafted with cysteine ​​include thiol-terminated lipids, such as distearyl phosphatidylethanolamine, dipalmitoyl phosphatidylethanolamine, dimyristoyl phosphatidylcholine, dioleoyl phosphatidylethanolamine, dilauryl phosphatidylethanolamine, distearyl lecithin, dimyristate phosphatidylcholine, and dimyristoyl lecithin, which are linked to thiol groups via polyethylene glycol chains.

[0021] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) Unlike existing fluorescence or chemiluminescence methods that require labeling of lipid nanoparticles or proteins, the labeling process is not only cumbersome but may also change the natural conformation of the protein and the physicochemical properties of the lipid nanoparticle surface, resulting in distortion of binding affinity data. Based on the inherent sensitivity of graphene-based sensors to charge changes, this invention can directly detect the specific binding of lipid nanoparticles to target proteins without any external labeling, thus maximizing the preservation of the natural activity of biological samples. The obtained interaction kinetic parameters are closer to the original state of lipid nanoparticles, and the detection method is accurate.

[0022] (2) Compared to methods such as surface plasmon resonance and fluorescence resonance energy transfer, this invention is based on the biosensing principle of field-effect transistors (FETs). It modulates the carriers in the semiconductor channel by controlling the interface charge changes caused by biorecognition events, thereby achieving electrical signal conversion of the interaction process between lipid nanoparticles and proteins. Specifically, the graphene FET, with its atomic-level thickness and high carrier mobility, enhances the interface charge response capability. The laser-induced graphene extended gate structure separates the recognition region from the transistor channel, allowing the interface potential changes generated by the interaction between lipid nanoparticles and proteins to be conducted to the transistor gate, circumventing the limitations of Debye shielding on long-distance charge transport in solution. Furthermore, the laser-induced graphene porous structure provides a high surface area and efficient ion coupling interface, and the surface-modified gold nanoparticles further increase the number of lipid nanoparticle binding sites at the sensing interface. This enables the invention to achieve highly sensitive, low-cost, and miniaturized detection of lipid nanoparticles.

[0023] (3) Traditional cell-level and animal-level experiments to detect the targeting of lipid nanoparticles can only obtain static results at a certain time point, which cannot reflect the dynamic process of lipid nanoparticle-protein binding. This invention can record the complete dynamic process of lipid nanoparticle-protein interaction by continuously monitoring the real-time fluctuations of drain current or the drift of transfer characteristic curves, providing data support with high temporal resolution for a deeper understanding of the protein crown formation mechanism, the targeting specificity of lipid nanoparticles, and their in vivo fate.

[0024] (4) The present invention facilitates high-throughput and parallel screening of lipid nanoparticles. By using semiconductor micro-nano fabrication technology to prepare high-density graphene-based sensor array chips, dozens or even more detection units can work in parallel. A single experiment can complete the cross-matrix analysis of multiple lipid nanoparticle formulations and multiple target proteins, greatly shortening the screening cycle.

[0025] (5) The method for detecting lipid nanoparticle-protein interaction based on graphene-based sensors provided by the present invention not only realizes the transformation from optical signal and fluorescent labeling method to label-free, in-situ electrical signal detection in terms of technical principle by measuring real-time drain current or transfer characteristic curve, but also surpasses the existing technology in terms of detection efficiency and detection cost, providing a powerful tool support for the targeted evaluation of lipid nanoparticles and the rapid optimization of nanodrug delivery systems. Attached Figure Description

[0026] Figure 1 This is a schematic diagram illustrating the working principle of a graphene field-effect transistor sensor.

[0027] Figure 2 The structure diagram and electrical performance characterization of the graphene field-effect transistor sensor are shown.

[0028] Figure 3 Scanning electron microscope images of lipid nanoparticles before and after modifying the graphene channel of a graphene field-effect transistor.

[0029] Figure 4 Raman spectra and transfer characteristics of lipid nanoparticles before and after the graphene channel of a graphene field-effect transistor is modified.

[0030] Figure 5 Scanning electron microscopy characterization results of the surface morphology of laser-induced graphene electrodes modified with lipid nanoparticles at different stages.

[0031] Figure 6 The results of scanning electron microscopy characterization of the surface morphology of a graphene field-effect transistor sensor reversibly modified with lipid nanoparticles at different stages are presented.

[0032] Figure 7 This is a schematic diagram of a laser-induced graphene sensor device.

[0033] Figure 8 Test results of a lipid nanoparticle-modified laser-induced graphene sensor in solutions with different BSA concentrations.

[0034] Figure 9 Normalized transfer curves of graphene field-effect transistors before and after modification with different targeted lipid nanoparticles.

[0035] Figure 10 Normalized transfer curves of protein response for graphene field-effect transistors modified with different targeted lipid nanoparticles.

[0036] Figure 11 This is a schematic diagram of an integrated device. Detailed Implementation

[0037] To make the objectives, features, and advantages of this invention more apparent and understandable, a detailed description is provided below through specific embodiments. Many specific details are set forth in the following description to provide a thorough understanding of the invention. However, the invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below. Technical features in various embodiments of the invention can be combined appropriately without mutual conflict.

[0038] Unless otherwise specified, the operating methods in the following examples are generally performed under conventional conditions or as recommended by the manufacturer. Contents not described in detail in this specification are prior art known to those skilled in the art. Unless otherwise specified, the experimental materials used in the examples below can be purchased from conventional biochemical reagent companies.

[0039] Example 1: Graphene field-effect transistor sensor for detecting lipid nanoparticle-protein interactions The working principle diagram of the graphene field-effect transistor sensor is as follows: Figure 1 As shown, in the graphene field-effect transistor sensor, the pattern design of each layer was completed using AutoCAD. The patterns were customized as positive or negative masks according to the fabrication process. The graphene field-effect transistor sensor includes a silicon dioxide wafer, a first-layer Cr / Au electrode array, an insulating layer, a second-layer Cr / Au electrode array, patterned graphene channels, and an SU-8 encapsulation layer. A complete device integrates 16 channels, enabling high-throughput, multi-channel detection of targeted lipid nanoparticles. The specific fabrication method is as follows: (1) Specifically, patterned structures were obtained using AZ5214 photoresist. AZ5214 photoresist was spin-coated onto a silicon dioxide wafer. The spin-coating parameters were: 500 rpm for 10 seconds (acceleration 100 rpm / s), followed by 2000 rpm for 40 seconds (acceleration 300 rpm / s). Before exposure, the wafer was placed on a heating plate and pre-baked at 120 °C for 3 minutes. Exposure was performed using a contact lithography machine for 13 seconds. AZ developer was used for development for 45 seconds. Cr / Au (5 nm / 150 nm) metal was then deposited using vacuum thermal evaporation. The treated wafer was then immersed in acetone for more than 2 hours to completely dissolve the AZ photoresist.

[0040] (2) Further, a 60 nm thick Al2O3 layer is deposited on the first Cr / Au electrode as an intermediate insulating layer via atomic layer deposition. AZ photoresist is then spin-coated onto the insulating layer, and the locations where the upper and lower metal layer electrodes are to be connected are removed. The spin-coating, pre-baking, exposure, and development processes for the AZ photoresist are the same as described above. Phosphoric acid is used to etch the developed locations to form windows, thereby achieving connectivity between the upper and lower metal layers. Subsequently, a second Cr / Au metal layer (5 nm / 150 nm) is deposited again via vacuum thermal evaporation to complete the construction of the double-layer electrode, forming well-defined gate, source, drain, and circuit I / O regions.

[0041] (3) Cutting the devices obtained in the above steps: Specifically, each device with a complete circuit pattern is finely cut using a glass cutter and surface pretreatment (plasma cleaning) is performed in an oxygen plasma chamber to enhance the subsequent affinity with graphene.

[0042] (4) Monolayer graphene bonding: Copper-based graphene grown by chemical vapor deposition was spin-coated with polymethyl methacrylate (PMMA). The graphene was first cut into 4 mm × 4 mm pieces. Before transfer, the PMMA and graphene surfaces were identified using a microscope, and the back of the graphene was treated with an oxygen plasma etching instrument (power: 50 W, time: 60 seconds, O2 flow rate: 40 sccm, total pressure: 15 Pa) to remove excess contaminants and prevent subsequent stacking damage. The treated PMMA-graphene pieces were then floated in a freshly prepared 7% ammonium persulfate solution (PMMA side up) for approximately 2 hours to completely remove the copper substrate. Subsequently, a clean silicon wafer was used to assist in transferring the graphene pieces to deionized water for 30 minutes to clean the surface of any remaining ammonium persulfate residue. This process was repeated twice. The graphene pieces were then transferred to the device surface treated in step (3) to accurately cover the array area. After placing the device in a drying oven overnight, it was baked (baking program: 60 °C, 30 minutes; 140 °C, 2 hours) to promote polymethyl methacrylate reflow and enhance the adhesion between graphene and the substrate. Finally, the chip was immersed in acetone for several hours to remove residual polymethyl methacrylate.

[0043] (5) Graphene patterning: First, AZ photoresist is used as a mask to pattern and isolate the graphene in the channel region. The specific process is the same as described above. Then, oxygen plasma etching is performed three times (under the same conditions as in step (4)), with a 5-minute interval between each etching to prevent the device from overheating. After etching, the device is immersed in acetone to completely remove the AZ photoresist and achieve graphene patterning.

[0044] (6) Graphene field-effect transistor sensor packaging: A thin film of about 5 μm thickness is spin-coated onto the device surface in step (5) using SU-8 2002 photoresist. The spin-coating parameters are: rotation speed of 500 rpm for 10 seconds (acceleration of 100 rpm / s), followed by rotation speed of 3000 rpm for 40 seconds (acceleration of 300 rpm / s). Graphene channel regions, electrode lead-out ports, gate windows, and other openings (the remaining areas of the SU-8 package) are obtained through photolithography and lift-off processes to obtain a 16-channel graphene field-effect transistor sensor. Its source is a Cr / Au electrode array connected to one end of the graphene channel, its drain is a Cr / Au electrode array connected to the other end of the graphene channel, and its gate is a Cr / Au electrode with an opening on the top layer. The graphene field-effect transistor sensor is as follows: Figure 2 As shown.

[0045] A source-drain voltage was applied to the source and drain terminals of the graphene field-effect transistor sensor. A buffer solution was dropped onto the surface of the graphene field-effect transistor, and a gate voltage was applied through the gate in the solution. Output and transfer curves were then tested, and the results are as follows: Figure 2 As shown.

[0046] Further graphene functionalization of the graphene field-effect transistor sensor was performed: After rinsing the graphene field-effect transistor sensor with pure water and drying it with nitrogen, 20 μL of a 30 mM N,N-dimethylformamide solution of 1-pyrenebutyric acid was added dropwise to the graphene array region. Small molecules of 1-pyrenebutyric acid were then modified onto the surface of the graphene channel through π-π stacking, thereby introducing carboxyl groups onto the graphene. After incubation at room temperature for 1 hour, the surface of the graphene field-effect transistor was rinsed sequentially with N,N-dimethylformamide and pure water to remove excess 1-pyrenebutyric acid, and then dried with nitrogen. The 1-pyrene butyric acid carboxyl group was then activated using 1-(3-dimethylaminopropyl)-3-ethylcarboimide / hydroxysuccinimide: An activation solution of 1-(3-dimethylaminopropyl)-3-ethylcarboimide / hydroxysuccinimide was prepared. Taking 1 mL of the activation solution as an example, the specific formulation was: 0.0382 g of 1-(3-dimethylaminopropyl)-3-ethylcarboimide, 0.0116 g of hydroxysuccinimide, 2.5 mL of 0.1 M 2-morpholine ethanesulfonic acid buffer, and 7.5 mL of H₂O. The final concentrations of 1-(3-dimethylaminopropyl)-3-ethylcarboimide, hydroxysuccinimide, and 2-morpholine ethanesulfonic acid were 200 mM, 0.1 M, and 25 mM, respectively. A 1-(3-dimethylaminopropyl)-3-ethylcarboimide / hydroxysuccinimide activating solution was dropped onto the surface of a graphene field-effect transistor and incubated at room temperature for 0.5 hours to activate the carboxyl groups on the 1-pyrene butyric acid molecule. After rinsing with pure water, it was dried with nitrogen gas.

[0047] Lipid nanoparticles were modified onto graphene-functionalized graphene field-effect transistor sensors: A solution of lipid nanoparticles (containing amino-terminated lipids) was dropped onto the surface of the graphene-functionalized graphene field-effect transistor sensor and incubated overnight at 4 °C. The device was then gently rinsed with pure water and dried to obtain a graphene field-effect transistor device with lipid nanoparticles modified on the channel surface.

[0048] The graphene regions of graphene field-effect transistor sensors and graphene field-effect transistor devices before and after lipid nanoparticle modification were characterized, and the results are as follows: Figure 3 and Figure 4 As shown in the image, analysis of scanning electron microscopy reveals that the graphene surface before lipid nanoparticle modification is smooth and flat; after lipid nanoparticle modification, the surface of the graphene sensing area exhibits spherical protrusions of relatively uniform size. Figure 4 The left image shows the Raman spectra of the graphene sensing region at different modification stages. Before modification, the visible length is approximately 1350 cm⁻¹. -1 and 1580 cm -1 Typical Raman peaks for monolayer graphene at [location missing]; approximately 1230 cm⁻¹ visible after modification with 1-pyrenebutyric acid. -1 and 1620 cm -1 The presence of pyrene-based characteristic vibrational peaks indicates successful modification with 1-pyrenebutyric acid. After modification with lipid nanoparticles, the pyrene-based characteristic vibrational peaks were significantly weakened. After removing the lipid nanoparticles, the pyrene-based characteristic vibrational peaks were enhanced again. Figure 4 The right figure shows that the transfer characteristic curve shifts to the right after modification with 1-pyrene butyric acid; after modification with lipid nanoparticles, the transfer characteristic curve shifts to the right even further.

[0049] The transfer characteristic curve testing method is as follows: A Keysight B2902B precision source meter module was used to input and detect the output signal. The testing process was performed on a probe station. 20 μL of phosphate-buffered saline (1×PBS) solution was dropped onto the surface of the lipid nanoparticle-modified graphene field-effect transistor, and the transfer curves of 16 channels were measured sequentially. The measurement parameters were: drain-source voltage Vds = 0.1 V, gate-source voltage Vgs scanned from 1.2 V to -0.1 V, and a scan step size of -0.0162 V. Devices modified with liver-targeting, lung-targeting, and spleen-targeting lipid nanoparticles were tested respectively, and different changes in transfer characteristic curves were obtained. The transfer curves measured for each device were averaged and normalized, and the results are shown below. Figure 9 As shown, the transfer characteristic curves after modification with lipid nanoparticles show distinguishable changes compared to before modification. In addition, the Dirac point of the device shifts to the left after modification with liver-targeting lipid nanoparticles, shifts to the right after modification with lung-targeting lipid nanoparticles, and shifts to the left after modification with spleen-targeting lipid nanoparticles.

[0050] Analytes, including 1×PBS, 10 μg / mL immunoglobulin M solution, and 10 μg / mL immunoglobulin G solution, were added dropwise to the surface of a lipid nanoparticle-modified graphene field-effect transistor (FET), 20 μL at a time. Transfer curves for 16 channels were then measured. After each analyte test, the FET array surface was rinsed with pure water. Alternatively, 0.1×PBS could be added to the device and allowed to stand for 3 min to elute proteins bound to the lipid nanoparticles. The device was then dried with a gentle airflow before testing the next analyte. Measurement parameters were defined as V. ds = 0.1 V, V gs The scan range was -0.1 V to 1.2 V, and the Keysight B2902B precision source meter module was used for testing. The transfer curves measured for each device were averaged and normalized, and the results are as follows. Figure 10 As shown, compared to the addition of PBS (blank control group), the addition of immunoglobulin M and immunoglobulin G solutions altered the transfer characteristic curves of the graphene field-effect transistors; furthermore, the effect of immunoglobulins on the transfer curves was inconsistent for transistors modified with different targeted lipid nanoparticles. This indicates that by comparing the transfer characteristic curves of graphene field-effect transistors modified with lipid nanoparticles in PBS (blank solution) with those in solutions of immunoglobulin M, immunoglobulin G, etc., the targeting specificity of the modified lipid nanoparticles can be reflected.

[0051] Example 2: Detection of lipid nanoparticle-protein interactions using a laser-induced graphene sensor The laser-induced graphene sensor comprises a polyimide substrate, a patterned gold circuit, a laser-induced graphene electrode, and a polyimide tape encapsulation layer. The polyimide substrate serves as device support and also as the raw material for fabricating the laser-induced graphene electrode using laser etching. The patterned gold circuit is directly fabricated on the polyimide substrate via magnetron sputtering and laser etching, with the exposed portion serving as the counter electrode and the portion covered by the encapsulation layer connecting the graphene electrode, counter electrode, and printed circuit board. The laser-induced graphene electrode is used to fabricate a functionalized sensing interface, converting the interaction between lipid nanoparticles and proteins into current changes. The polyimide tape encapsulation layer encapsulates the laser-induced graphene sensor, exposing only the graphene electrode and counter electrode to ensure stable circuit operation.

[0052] The laser-induced graphene sensor is connected to the printed circuit board via a flexible flat cable adapter, as shown in the schematic diagram. Figure 7 As shown.

[0053] (1) The patterned Au circuit of the laser-induced graphene sensor was prepared by magnetron sputtering and laser etching. The laser-induced graphene electrode was obtained by scanning the polyimide film with a carbon dioxide infrared laser. The laser-induced graphene electrode and the Au circuit on the polyimide film were connected by silver paste, and the silver paste was fixed by baking at 120 °C for 30 min. The Au pattern area and Ag area were covered by polyimide tape, exposing only the laser-induced graphene electrode and the counter electrode.

[0054] (2) Laser-induced functionalization modification of graphene electrode surface: An electroplating solution containing 1 mM H[AuCl4] and 10 mM sulfuric acid was prepared using pure water. The first gold nanoparticle electrodeposition was performed on the laser-induced graphene electrode using a CHI604e electrochemical workstation. The electrodeposition parameters were: initial potential -0.2 V, high potential 0 V, low potential -0.2 V, pulse width 0.5 s, 40 cycles. After electrodeposition, the electrode was rinsed with distilled water and dried. Subsequently, the laser-induced graphene electrode with gold nanoparticles modified on the surface was immersed in an ethanol solution containing 0.5 mM 11-mercaptoundecanoic acid and 1 mM 6-mercapto-1-hexanol and incubated overnight at room temperature, thereby forming a 11-mercaptoundecanoic acid / 6-mercapto-1-hexanol self-assembled monolayer on the surface of the gold nanoparticles. The electrode was rinsed with ethanol and water in sequence, and then dried under a nitrogen flow to obtain a 11-mercaptoundecanoic acid / 6-mercapto-1-hexanol-gold nanoparticle-laser-induced graphene electrode (i.e., the working electrode).

[0055] (3) The 11-mercaptoundecanoic acid / 6-mercapto-1-hexanol-gold nanoparticle-laser-induced graphene electrode was then incubated for 30 minutes with a solution of 200 mM 1-(3-dimethylaminopropyl)-3-ethylcarboimide, 0.1 M hydroxysuccinimide, and 25 mM 2-morpholinoethanesulfonic acid (pH=5). Subsequently, a lipid nanoparticle solution (1 μM~10 μM, containing amino-terminated lipids) was added dropwise to the working electrode and incubated overnight at 4 °C. Finally, the working electrode was gently rinsed with water and dried under a nitrogen stream to obtain a lipid nanoparticle-modified patterned laser-induced graphene electrode.

[0056] like Figure 5 As shown, Raman spectroscopy, scanning electron microscopy images, and transfer curves tested with a laser-induced graphene working electrode as the gate demonstrate the successful modification of lipid nanoparticles and the successful construction of the lipid nanoparticle sensing layer.

[0057] Test condition is V ds = 0.3 V, acquisition time resolution of 30 ms, total test time of 15 min, and statistical analysis of current distribution were performed to extract the current change at adsorption saturation under different protein concentrations. Results are as follows: Figure 8As shown.

[0058] Example 3: Detection of lipid nanoparticle-protein interaction using a graphene field-effect transistor sensor To achieve repeated modification and elution of lipid nanoparticles on the graphene surface, the present invention performs the following treatment on the unfunctionalized graphene field-effect transistor sensor of Example 1: (1) First lipid nanoparticle modification: The graphene field-effect transistor sensor was treated with a 30 mM N,N-dimethylformamide solution of 1-pyrene butyric acid to introduce carboxyl groups into the graphene channel through π-π stacking. After rinsing with N,N-dimethylformamide and water, the carboxyl groups were activated by incubation at room temperature for 30 minutes with a 1-(3-dimethylaminopropyl)-3-ethylcarboimide / hydroxysuccinimide solution. After rinsing with water again and drying under airflow, the graphene channel was incubated in a 10 mM cysteine ​​aqueous solution at 37 °C for 6 hours. Subsequently, a 1 M potassium iodide aqueous solution was mixed with a lipid nanoparticle solution (the raw material included thiol-terminated lipids) at a volume ratio of 1:9, and the mixture was dropped onto the graphene surface and incubated at 37 °C for 1.5 hours to obtain lipid nanoparticle-modified graphene channels. Cysteine ​​forms an amide bond with the carboxyl group of 1-pyrenebutyric acid through its amino group, thus leaving a free thiol group. Under the catalysis of potassium iodide, this thiol group forms a disulfide bond with the free thiol group of the lipid nanoparticles, thereby achieving stable modification of the lipid nanoparticles.

[0059] (2) Lipid nanoparticle elution: A 10 mM dithiothreitol aqueous solution was dropped onto the surface of the above lipid nanoparticle-modified graphene field-effect transistor sensor and treated at 37 °C for 30 minutes to break the disulfide bonds, thereby eluting the lipid nanoparticles. Then, the sensor was rinsed with water and dried.

[0060] (3) Further modification of lipid nanoparticles: The further modification of lipid nanoparticles (the raw materials include thiol-terminated lipids) was also carried out by adding a mixture of lipid nanoparticles / potassium iodide and incubating under the same conditions (37 °C, incubation for 1.5 hours).

[0061] The surface morphology of the graphene channels in the lipid nanoparticles before, after, and after elution, and after re-modification was characterized by scanning electron microscopy. The results are as follows: Figure 6 As shown.

[0062] Example 4: Integrated device for detecting lipid nanoparticle-protein interactions This embodiment provides an integrated device for lipid nanoparticle preparation and targeted detection, enabling rapid and sequential execution of these two processes. Figure 11As shown, the integrated device comprises two parts: a lipid nanoparticle microfluidic preparation module and a lipid nanoparticle targeting detection module. It consists of a microfluidic layer, a polyimide film, and a patterned gold circuit and a laser-induced graphene electrode on the polyimide film.

[0063] The microfluidic layer is prepared using polydimethylsiloxane through soft photolithography. First, a template is prepared, and then the polydimethylsiloxane microfluidic layer is prepared using the template. After bonding the polydimethylsiloxane microfluidic layer to a polyimide film, an integrated device is obtained.

[0064] Template preparation method: SU-8 2050 photoresist was dropped onto the surface of a silicon wafer and spin-coated. Specifically, to obtain a 150 μm thick SU-8 template, the spin-coating procedure was as follows: spin-coating at 500 rpm / min for 10 seconds, followed by spin-coating at 1250 rpm / min for 30 seconds; then a pre-baking procedure was performed: baking at 65 °C for 5 minutes and baking at 95 °C for 30 minutes; after 60 seconds of UV exposure, a post-baking procedure was performed: baking at 65 °C for 5 minutes and baking at 95 °C for 12 minutes; after cooling, the silicon wafer was immersed in propylene glycol methyl ether acetate for development for 11 minutes; after development, the silicon wafer was placed on a hot plate for annealing: baking at 65 °C for 5 minutes, baking at 130 °C for 5 minutes, baking at 180 °C for 40 minutes, and then slowly cooled to room temperature.

[0065] Preparation method of polydimethylsiloxane microchannels: Polydimethylsiloxane prepolymer and curing agent are thoroughly mixed at a mass ratio of 10:1. The mixture is poured into an SU-8 mold and vacuum degassed for 30 minutes to remove trapped air bubbles. After curing at 65 °C for 4 hours, the polydimethylsiloxane is peeled off from the mold. Subsequently, the polydimethylsiloxane microchannel layer is cut and perforated.

[0066] An irreversible bonding method for polydimethylsiloxane microchannel layers and polyimide films: Polydimethylsiloxane microchannels were treated with oxygen plasma (120 sccm, 90 W, 60 s) and then immersed in a 2% (v / v) 3-aminopropyltriethoxysilane solution (ethanol containing 3% (v / v) water) for 1 hour to introduce amino groups onto the polydimethylsiloxane surface. The 3-aminopropyltriethoxysilane solution on the surface of the polydimethylsiloxane microchannels was drained, and the microchannels were heated on a 120 °C hot plate for 2 minutes to evaporate any residual solvent. Subsequently, the polydimethylsiloxane microchannels and laser-induced graphene electrodes were tightly bonded to form a 1-pyrene-butyric acid-modified cysteine-grafted polyimide film. The film was then gently pressed for 30 seconds and heated at 70 °C for over 1 hour to improve bonding strength.

[0067] The method of using the aforementioned integrated device is as follows: Before bonding polydimethylsiloxane to the integrated device, the laser-induced graphene electrode is incubated at room temperature for 1 hour in an N,N-dimethylformamide solution containing 30 mM 1-pyrenebutyric acid to introduce carboxyl groups through π-π stacking modification of 1-pyrenebutyric acid. After sequential rinsing with N,N-dimethylformamide and water, the graphene is activated by incubating at room temperature for 30 minutes in a 1-(3-dimethylaminopropyl)-3-ethylcarboimide / hydroxysuccinimide solution. After rinsing again with water and drying under an airflow, the graphene is incubated at 37 °C in a 10 mM cysteine ​​aqueous solution for 6 hours, followed by bonding of polydimethylsiloxane to the polyimide film. After completion, the device is first washed with ultrapure water at a flow rate of 50 μL / min for 5 min. Thiol-containing lipid nanoparticles were synthesized via a stainless steel needle connected to the fluid inlet of the synthesis section of the integrated device (flow rates of 200 μL / min for the aqueous phase and 50 μL / min for the oil phase). Cell membrane solution (1–5 μg / mL) was then introduced and flowed through the electrofusion module (2.5 kHz, 10 V) to generate cell membrane-functionalized lipid nanoparticles. After collecting the lipid nanoparticle samples required for the biological experiment, 1 M potassium iodide aqueous solution was introduced through the central inlet to mix the solution thoroughly. The flow rate was reduced to 0, and the inlet and outlet of the flow channel were sealed. The mixture was incubated at 37 °C for 1 hour. The flow channel was then rinsed with 1×PBS (flow rate controlled at 1–5 μL / min). Subsequently, 1×PBS, immunoglobulin M solution, and immunoglobulin G solution were sequentially introduced as analytes (flow rate controlled at 0.5–2 μL / min). A constant drain-source voltage V was applied to the detection module using a Keysight B2902B precision source-source module. ds = -1 V and constant gate-source voltage V gs = 1.5 V, drain current recorded in real time. After all tests of the previous analyte were completed, the laser-induced graphene surface was rinsed with 1×PBS (flow rate controlled at 1~5 μL / min) to elute the proteins bound to the lipid nanoparticles. After completing a lipid nanoparticle test, to elute the lipid nanoparticles, a 10 mM dithiothreitol aqueous solution was passed through at 37 °C for 30 minutes to break the disulfide bonds, followed by rinsing the flow channel with 1×PBS. The binding-elution step was then repeated for the detection of the next lipid nanoparticle formulation.

[0068] The embodiments described above provide a detailed explanation of the technical solutions of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, additions, or similar substitutions made within the scope of the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for detecting lipid nanoparticle-protein interactions based on a graphene-based sensor, characterized in that, The graphene-based sensor is a graphene field-effect transistor sensor or a laser-induced graphene sensor, which includes a graphene sensing region. After lipid nanoparticles are combined on the graphene sensing region, the lipid nanoparticles come into contact with the protein. The interaction between the lipid nanoparticles and the protein is determined by the change in the electrical signal of the graphene-based sensor before and after contact. The graphene sensing region of the graphene field-effect transistor sensor was modified with 1-pyrene butyric acid, and lipid nanoparticles were bound after the carboxyl group was activated. After depositing gold nanoparticles on the graphene sensing region of a laser-induced graphene sensor, a self-assembled monolayer of 11-mercaptoundecanoic acid / 6-mercapto-1-hexanol was modified, followed by activation of carboxyl groups to bind lipid nanoparticles. Alternatively, cysteine ​​can be grafted onto the aforementioned carboxyl-activated graphene field-effect transistor sensor or laser-induced graphene sensor, and lipid nanoparticles can be combined under the action of a catalyst.

2. The detection method according to claim 1, characterized in that, The graphene field-effect transistor sensor comprises, from bottom to top, a substrate, a Cr / Au electrode array, an insulating layer, a Cr / Au electrode array, a graphene channel, and an encapsulation layer; the graphene channel is exposed and serves as the sensing area.

3. The detection method according to claim 1, characterized in that, The structure of the laser-induced graphene sensor includes a substrate layer, a patterned gold circuit, a laser-induced graphene electrode, and an encapsulation layer. The laser-induced graphene electrode is exposed and serves as the sensing area.

4. The detection method according to claim 1, characterized in that, When a graphene field-effect transistor sensor is selected, the interaction between lipid nanoparticles and proteins is determined by the change in the transfer characteristic curve after the addition of a protein solution, thus determining the targeting of the lipid nanoparticles. The transfer characteristic curve is obtained by keeping the source-drain voltage constant, continuously scanning the gate voltage, and synchronously recording the corresponding drain current. When using a laser-induced graphene sensor, the source-drain voltage remains constant during the detection of lipid nanoparticles in contact with proteins. The interaction between lipid nanoparticles and proteins is determined by the change in source-drain current after the addition of a protein solution.

5. The detection method according to claim 3, characterized in that, The substrate layer is a polyimide layer, and a microfluidic structure is also bonded to the polyimide layer. The microfluidic structure is used for the preparation of lipid nanoparticles.

6. The detection method according to claim 1, characterized in that, The method for modifying 1-pyrenebutyric acid is as follows: an organic solution of 24-36 mM 1-pyrenebutyric acid is added to the graphene sensing region to modify it with 1-pyrenebutyric acid.

7. The detection method according to claim 1, characterized in that, The method for depositing gold nanoparticles is electroplating deposition. An electroplating solution containing 0.5-2 mM chloroauric acid and 10-15 mM sulfuric acid is prepared for electroplating deposition of gold nanoparticles on the graphene sensing region. An organic solution containing 0.3-0.6 mM 11-mercaptoundecanoic acid and 0.8-1.2 mM 6-mercapto-1-hexanol is used for 11-mercaptoundecanoic acid / 6-mercapto-1-hexanol self-assembled monolayer modification.

8. The detection method according to claim 1, characterized in that, Cysteine ​​grafting was performed using an 8-12 mM aqueous solution of cysteine, with potassium iodide or hydrogen peroxide as the catalyst.

9. The detection method according to claim 1, characterized in that, By grafting cysteine ​​and combining the first type of lipid nanoparticles with a catalyst, the nanoparticles are eluted with dithiothreitol and then recombine with the second type of lipid nanoparticles with a catalyst.

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