WO2022228319A1

WO2022228319A1 - Method for detecting target molecule

Info

Publication number: WO2022228319A1
Application number: PCT/CN2022/088659
Authority: WO
Inventors: 叶坚; 毕心缘
Original assignee: 上海交通大学
Priority date: 2021-04-26
Filing date: 2022-04-24
Publication date: 2022-11-03
Also published as: CN114486852A; CN114486852B

Abstract

A method for detecting a target molecule, comprising mixing a medium particle with a sample containing the target molecule, wherein the medium particle is used to perform two-component surface-enhanced Raman spectroscopy detection on an auxiliary molecule, and the ratio of the spectral number of a single molecule spectrum of the auxiliary molecule to number of spectra that generate a spectral signal is at least 50%; and carrying out surface-enhanced Raman spectroscopy detection on the auxiliary molecule by using the medium particle, the absolute value of a correlation coefficient of signal intensity generated by the auxiliary molecule at any time interval being below 0.3. The method above may achieve liquid-phase digital surface-enhanced Raman spectroscopy detection. The detection method is easy to operate, and the single-molecule level detection sensitivity may be achieved.

Description

Methods of Detecting Target Molecules

technical field

The present application relates to the field of biomedicine, in particular to a method for detecting target molecules.

Background technique

Raman spectroscopy is a fingerprint-type inelastic scattering spectrum, which can reflect the vibrational information of molecular structure and internal chemical bonds. It is a non-destructive and specific detection and analysis method. Although the Raman scattering signal itself is weak, surface-enhanced Raman spectroscopy can enhance the Raman scattering intensity of adsorbed molecules by up to ten orders of magnitude. The high sensitivity and high specificity of surface-enhanced Raman spectroscopy make it extremely advantageous and valuable in application scenarios such as qualitative identification and precise quantification in many fields such as the environment, food, biology, and medical treatment.

The strong signal-enhancing ability of adsorbed molecules in surface-enhanced Raman spectroscopy technology comes from the hot spot area on the surface of the surface-enhanced Raman substrate. The hot spot area has a high-plasmonic electromagnetic field, which can be used to amplify the Raman of the molecules located in it. Signal. However, the enhancement ability is highly related to various factors such as substrate size, surface topography, molecular adsorption orientation, and molecular-substrate distance, so small differences at the nanoscale can cause huge changes in signal intensity. For low-concentration molecular detection, the detected signal is often derived from the surface-enhanced Raman signal generated by a single molecule, and the signal fluctuation is particularly significant. Since the surface-enhanced Raman substrate, molecular adsorption and other conditions in the test system cannot be controlled to be completely consistent within this microscopic scale, the current technology based on signal intensity cannot achieve accurate quantification of target molecules.

Alexandre G.Brolo et al. first proposed the concept of digital surface-enhanced Raman spectroscopy, which is based on the frequency of the surface-enhanced Raman scattering signal of the molecule, rather than the signal intensity, to overcome quantitative inaccuracies caused by signal fluctuations. However, the implementation of the above technology uses solid-phase surface-enhanced Raman chips. Due to the poor repeatability of the manufacturing process and the limited number of hot spots, there is no way to promote the technology and the detection limit of molecular quantification cannot be fundamentally broken. Although the current method such as electron beam etching can improve the uniformity of hot spot distribution on the chip to a certain extent, the instrument is complex and expensive, and it still cannot completely solve many other problems including uniform molecular distribution.

It can be seen that surface-enhanced Raman spectroscopy still greatly limits its application scenarios such as qualitative identification and accurate quantification due to the uniformity, repeatability, detection limit of the detection system, and the high complexity and high cost of the detection process. application value in . Therefore, it is urgent to obtain a new surface-enhanced Raman spectroscopy detection method that can solve the above-mentioned defects.

SUMMARY OF THE INVENTION

The present application provides a method for detecting target molecules, specifically a method for liquid-phase digital surface-enhanced Raman spectroscopy detection. The method for detecting target molecules described in the present application may have at least one of the following properties: (1) the diversity of surface-enhanced Raman particles is high, which can be selected according to the properties of the target molecules. There are various preparation methods and/or modification methods; (2) in the detection process of the method, the surface-enhanced Raman particles have good dispersibility in the detection system; (3) in the detection process of the method, The target molecule has good dispersibility in the detection system; (4) the method is easy to operate, low in cost, and suitable for mass detection; (5) the target molecule can be accurately quantified at the single-molecule level; (6) High-throughput quantification of the target molecule can be achieved; (7) the target molecule can be destroyed and/or labeled without the need for it; (7) the method has good repeatability, high reliability of the detection result, and controllable quantitative error (ie digitalization). Quantification can increase the total amount of detected spectra to reduce counting errors); (8) the method can be basically not affected by single molecule fluctuations (such as the adsorption orientation of single molecules, the difference of enhancement factors and other uncertain factors) . The present application selects suitable medium particles to realize the method for detecting target molecules, and the suitable medium particles not only have the detection sensitivity at the single-molecule level of the target molecules, but also can ensure stability during the detection process of the method. sex. The present application also provides the application of the medium particles described in the present application in liquid-phase digital surface-enhanced Raman spectroscopy detection.

In one aspect, the present application provides a method of detecting a target molecule, comprising the steps of: a) mixing particles of a medium with a sample comprising the molecule of interest, wherein the particles of the medium exhibit the following properties: 1) utilizing the performing two-component surface-enhanced Raman spectroscopy (BiASERS) detection of auxiliary molecules on the mediator particles, wherein the ratio of the number of spectra of a single molecule spectrum of the auxiliary molecule to the number of spectra that produce a spectral signal is at least about 50%; and, 2) Surface-enhanced Raman spectroscopy is used to detect auxiliary molecules by using the medium particles, wherein the absolute value of the correlation coefficient between the signal intensities generated by the auxiliary molecules at any time interval is about 0.3 or less.

In certain embodiments, the detection includes qualitative detection and/or quantitative detection.

In certain embodiments, the detection comprises single-molecule level quantitative detection.

In certain embodiments, the sample is in the form of a solution.

In certain embodiments, the media particles are dispersed in a solution.

In certain embodiments, the medium particles are mixed with the sample in a liquid phase system.

In certain embodiments, mixing includes incubating the medium particles with the sample in a liquid phase system.

In certain embodiments, the target molecules include small molecules and/or macromolecules.

In certain embodiments, the macromolecules include peptides and/or proteins.

In certain embodiments, the media particles comprise metal nanoparticle sols, metal nanoparticles and/or nanostructured substrates.

In certain embodiments, the media particles comprise surface-enhanced Raman particles.

In certain embodiments, the media particles comprise hydroxylamine-silver colloidal particles, citric acid-silver colloidal particles, and/or citric acid-gold colloidal particles.

In certain embodiments, the accessory molecules comprise small molecules and/or macromolecules.

In certain embodiments, the helper molecule is of the same species as the target molecule.

In certain embodiments, the two-component surface-enhanced Raman spectroscopy detection comprises detecting a first sample comprising the mediator particles and at least two of the auxiliary molecules.

In certain embodiments, the two-component surface-enhanced Raman spectroscopy detection comprises the step of reducing the concentration of the at least two accessory molecules in the first sample at least once.

In certain embodiments, the reduction is a reduction in the concentration of each of the helper molecules by at least 0.1 orders of magnitude each time compared to the original concentration of the helper molecule in the first sample.

In certain embodiments, the reduction is from about 0.1 to about 1 order of magnitude at a time in the concentration of each of the helper molecules compared to the original concentration of the helper molecule in the first sample.

In certain embodiments, the two-component surface-enhanced Raman spectroscopy detection comprises the step of detecting the spectral signal generated by each of the auxiliary molecules in the first sample after the reduction.

In certain embodiments, in a single spectrum, when the spectral signal generated by the auxiliary molecule accounts for at least 85% of the spectral signal of the single spectrum, the single spectrum is the auxiliary molecule single molecule spectrum .

In certain embodiments, the mediator particles have single-molecule-level detection sensitivity for the helper molecule when the ratio of the spectral number of the helper molecule's single-molecule spectrum to the spectral number of the generated spectral signal is at least 50%.

In certain embodiments, the surface-enhanced Raman spectroscopy detection includes detecting a second sample, the second sample comprising the mediator particles and at least one of the helper molecules.

In certain embodiments, the surface-enhanced Raman spectroscopy detection comprises detecting the intensity of the signal generated by the helper molecule.

In some embodiments, the surface-enhanced Raman spectroscopy detection includes calculating a correlation coefficient between the signal intensities generated at any time interval based on the signal intensities.

In certain embodiments, the media particles are stable for detection by the surface-enhanced Raman spectroscopy when the absolute value of the correlation coefficient is about 0.3 or less.

In certain embodiments, the media particles have the stability for at least 60 minutes when the absolute value of the correlation coefficient is about 0.3 or less.

In certain embodiments, the method includes the step of: b) performing Raman detection on the mixed medium particles and the sample containing the target molecule, and obtaining a Raman spectrum of the target molecule.

In certain embodiments, the Raman detection comprises surface-enhanced Raman spectroscopy detection.

In certain embodiments, the Raman detection comprises digitized surface-enhanced Raman spectroscopy detection.

In certain embodiments, the method includes the following steps: c) obtaining the corresponding abundance value of the target molecule in each Raman spectrum according to the Raman spectrum of the target molecule.

In certain embodiments, the method for detecting a target molecule comprises the following steps: determining a threshold for judging the presence of the target molecule according to the abundance value of a blank sample that does not contain the target molecule.

In some embodiments, the method for detecting a target molecule comprises the step of: obtaining the concentration of the target molecule in the sample according to the number and/or frequency of the target molecule being judged to be present in the sample.

In some embodiments, the method for detecting a target molecule comprises the following steps: obtaining the target molecule in the sample according to a mathematical mapping relationship of the number and/or frequency of the target molecule being judged to exist in the sample in the concentration.

In certain embodiments, the method of detecting a target molecule comprises the step of adjusting the concentration of the target molecule in a sample comprising the target molecule.

In certain embodiments, the method for detecting a target molecule comprises the step of: adjusting the binding ability of the medium particle to the target molecule.

In certain embodiments, the method of detecting a target molecule comprises the step of adjusting the physicochemical properties of a sample comprising the target molecule.

In certain embodiments, the method of detecting a target molecule comprises the step of adjusting parameters of the equipment required for the Raman detection.

In certain embodiments, the method of detecting a target molecule comprises the steps of: adjusting the total number of the Raman spectra in each Raman detection; and/or the Raman spectra detected as positive for the target molecule total.

In certain embodiments, the method of detecting a target molecule comprises the step of adjusting the number of Raman detections.

In certain embodiments, the Raman detection comprises liquid surface enhanced Raman spectroscopy detection.

In another aspect, the present application provides the application of the medium particles described in the present application in the detection of target molecules by liquid-phase digital surface-enhanced Raman spectroscopy.

In certain embodiments, the medium particles and the target molecules are mixed in a liquid phase system.

In certain embodiments, the liquid phase digital surface-enhanced Raman spectroscopy detection quantifies the concentration of the target molecule.

Other aspects and advantages of the present application can be readily appreciated by those skilled in the art from the following detailed description. Only exemplary embodiments of the present application are shown and described in the following detailed description. As those skilled in the art will recognize, the content of this application enables those skilled in the art to make changes to the specific embodiments disclosed without departing from the spirit and scope of the invention to which this application relates. Accordingly, the drawings and descriptions in the specification of the present application are only exemplary and not restrictive.

Description of drawings

The invention to which this application relates is set forth with particularity characteristic of the appended claims. The features and advantages of the inventions involved in this application can be better understood by reference to the exemplary embodiments described in detail hereinafter and the accompanying drawings. A brief description of the drawings is as follows:

Figure 1 shows the extinction spectrum of the hydroxylamine-silver colloidal particle solution described in this application.

Figure 2 shows the results of transmission electron microscopy of the hydroxylamine-silver colloidal particle solution described in the present application.

FIG. 3 shows the threshold value for judging the presence or absence of crystal violet in the liquid-phase digital surface-enhanced Raman spectroscopy detection of the present application using the hydroxylamine-silver colloidal particle solution.

FIG. 4 shows the digital processing result of detecting crystal violet by liquid-phase digital surface-enhanced Raman spectroscopy described in the present application using hydroxylamine-silver colloidal particle solution.

Figure 5 shows a quantitative standard curve for the detection of ultra-low concentration crystal violet by liquid-phase digital surface-enhanced Raman spectroscopy described in the present application using a hydroxylamine-silver colloidal particle solution.

Figure 6 shows the extinction spectrum of the citric acid-gold colloidal particle solution described in the present application.

Figure 7 shows the transmission electron microscope results of the citric acid-gold colloidal particle solution described in the present application.

FIG. 8 shows the threshold value for judging the presence or absence of nitrothiophenol in the liquid-phase digital surface-enhanced Raman spectroscopy detection of the present application using the citric acid-gold colloidal particle solution.

Figure 9 shows the results of digital processing for the detection of nitrothiophenol by liquid-phase digital surface-enhanced Raman spectroscopy described in the present application using a citric acid-gold colloidal particle solution.

Figure 10 shows a quantitative standard curve for the detection of ultra-low concentrations of nitrothiophenol using liquid-phase digital surface-enhanced Raman spectroscopy described in the present application using a citric acid-gold colloidal particle solution.

FIG. 11 shows the threshold value for judging the presence or absence of hemoglobin in the liquid-phase digital surface-enhanced Raman spectroscopy detection of the present application using the hydroxylamine-silver colloidal particle solution.

Figure 12 shows the results of digital processing for the detection of hemoglobin by liquid-phase digital surface-enhanced Raman spectroscopy described herein using a hydroxylamine-silver colloidal particle solution.

Figure 13 shows a quantitative standard curve for the detection of ultra-low concentration hemoglobin by liquid-phase digital surface-enhanced Raman spectroscopy described in this application using a hydroxylamine-silver colloidal particle solution.

Figure 14 shows the threshold value for determining the presence or absence of A12 in the liquid phase digital surface-enhanced Raman spectroscopy detection described in the present application using the hydroxylamine-silver colloidal particle solution.

Figure 15 shows the results of digital processing of A12 detected by liquid-phase digital surface-enhanced Raman spectroscopy described in this application using a hydroxylamine-silver colloidal particle solution.

Figure 16 shows a quantitative standard curve for the detection of ultra-low concentration A12 by liquid-phase digital surface-enhanced Raman spectroscopy described in the present application using a hydroxylamine-silver colloidal particle solution.

Figures 17a-17c show the results of judging whether hydroxylamine-silver colloidal particles are suitable for use as surface-enhanced Raman particles in the liquid-phase digital surface-enhanced Raman spectroscopy detection described herein.

Figures 18a-18c show the results of judging whether the citric acid-silver colloidal particles are suitable for use as the surface-enhanced Raman particles in the liquid-phase digital surface-enhanced Raman spectroscopy detection described herein.

Figures 19a-19c show the results of judging whether the citric acid-gold colloidal particles are suitable for use as the surface-enhanced Raman particles in the liquid-phase digital surface-enhanced Raman spectroscopy detection described herein.

Figure 20 shows the results of judging whether hydroxylamine-silver nanoparticles are suitable for use as surface-enhanced Raman particles in liquid-phase digital surface-enhanced Raman spectroscopy detection described herein.

Figure 21 shows the results of judging whether the citric acid-silver nanostar particles are suitable for use as the surface-enhanced Raman particles in the liquid-phase digital surface-enhanced Raman spectroscopy detection described in the present application.

Figure 22 shows the results of judging whether hydroxylamine-silver nanoparticles are suitable for use as surface-enhanced Raman particles in the liquid-phase digital surface-enhanced Raman spectroscopy detection described herein.

Figure 23 shows the results of judging whether the citric acid-silver nanostar particles are suitable for use as the surface-enhanced Raman particles in the liquid-phase digital surface-enhanced Raman spectroscopy detection described in the present application.

Figure 24 shows the results of judging whether hydroxylamine-silver nanoparticles are suitable for use as surface-enhanced Raman particles in liquid-phase digital surface-enhanced Raman spectroscopy detection described herein.

FIG. 25 shows the threshold value for judging the presence or absence of oxytocin in the liquid phase digital surface-enhanced Raman spectroscopy detection of the present application using the hydroxylamine-silver colloidal particle solution.

Figure 26 shows the results of digital processing for the detection of oxytocin using liquid-phase digital surface-enhanced Raman spectroscopy described herein using a hydroxylamine-silver colloidal particle solution.

Figure 27 shows a quantitative standard curve for the detection of ultra-low concentrations of oxytocin using liquid-phase digital surface-enhanced Raman spectroscopy described herein using hydroxylamine-silver colloidal particle solutions.

FIG. 28 shows the threshold value for judging the presence or absence of fometidine using the liquid-phase digital surface-enhanced Raman spectroscopy detection of the present application using the hydroxylamine-silver colloidal particle solution.

Figure 29 shows the digitized results of the liquid phase digital surface-enhanced Raman spectroscopy described in the present application using hydroxylamine-silver colloidal particle solutions for detection of Famex.

Figure 30 shows a quantitative standard curve for the detection of ultra-low concentrations of fumetidine using the liquid-phase digital surface-enhanced Raman spectroscopy described in the present application using a hydroxylamine-silver colloidal particle solution.

Figure 31 shows the threshold for determining the presence or absence of paraquat using the liquid-phase digital surface-enhanced Raman spectroscopy detection of the present application using the hydroxylamine-silver colloidal particle solution.

Figure 32 shows the results of digital processing for the detection of paraquat using liquid-phase digital surface-enhanced Raman spectroscopy described herein using hydroxylamine-silver colloidal particle solutions.

Figure 33 shows a quantitative standard curve for the detection of ultra-low concentration paraquat using the liquid-phase digital surface-enhanced Raman spectroscopy described in this application using hydroxylamine-silver colloidal particle solution.

Figure 34 shows that increasing the total number of spectra included in the digital surface-enhanced Raman spectroscopy detection can improve the accuracy of the liquid-phase digital surface-enhanced Raman spectroscopy described in the present application to detect the molecules to be detected at ultra-low concentrations.

Figure 35 shows that increasing the detection volume can improve the accuracy of the liquid-phase digital surface-enhanced Raman spectroscopy described in the present application to detect molecules to be detected at ultra-low concentrations.

Detailed ways

The embodiments of the invention of the present application are described below by specific specific examples, and those skilled in the art can easily understand other advantages and effects of the invention of the present application from the contents disclosed in this specification.

Definition of Terms

In this application, the term "target molecule" generally refers to a substance whose presence, absence or concentration needs to be determined according to the methods described in this application. The target molecule can be a single molecule or a complex of molecules. The target molecule can be a macromolecule, such as a protein (such as an antibody, such as a monoclonal antibody), can be DNA and/or RNA expressed by bacteria, yeast, mammalian, plant or insect cells, can be a peptide and/or proteins; the target molecules can be small molecules, such as nucleosides, nucleotides and/or amino acids; such as minerals; can be chemical substances (such as pesticides, drugs, pollutants, drugs ), such as compounds (eg, may be organic, may be inorganic), peptides and polypeptides, oligosaccharides, sugar-modified proteins, polymers, metal chelates, ions.

In this application, the term "media particle" generally refers to a substance that assists in determining the presence or absence of the target molecule, or determining the concentration of the target molecule. The mediator particles can be contacted with the target molecule and assist the target molecule in generating a signal in detection after contact. The detection method can detect the presence and/or concentration of the target molecule by means of the signal. In this application, the detection method can be Raman spectroscopy detection (for example, it can be surface-enhanced Raman spectroscopy detection, it can be digital surface-enhanced Raman spectroscopy detection, it can be liquid-phase digital surface-enhanced Raman spectroscopy detection ). In the present application, the signal may be the Raman spectrum of the target molecule. In this application, the medium particles can be the substrate required for Raman spectroscopy detection. For example, the medium particles may be surface-enhanced Raman particles. In the present application, the medium particles may be metal nanoparticle sols, metal nanoparticles and/or nanostructured substrates. For example, the medium particles may be hydroxylamine-silver colloidal particles, citric acid-silver colloidal particles, and/or citric acid-gold colloidal particles.

In this application, the term "auxiliary molecule" generally refers to a substance required to determine whether the medium particles can be used in the methods described herein. In the present application, the mediator particles can be contacted with the helper molecule and help the helper molecule to generate a signal in detection after contact. It is determined whether the helper molecule-generated signal meets a certain threshold, thereby determining whether the mediator particles can be used in the methods described herein. In the present application, the detection method may be Raman spectroscopy detection, for example, two-component surface-enhanced Raman spectroscopy detection (BiASERS), for example, digital surface-enhanced Raman spectroscopy detection. In the present application, the signal may be the Raman spectrum of the target molecule, and/or may be the result obtained from data settlement based on the Raman spectrum. In the present application, the kind of the auxiliary molecule can be adjusted according to the kind of the target molecule. For example, the species of the helper molecule may be the same as the species of the target molecule. The species of the helper molecule may also be different from the species of the target molecule. In the present application, the auxiliary molecules may include small molecules and/or macromolecules.

In this application, the term "Raman spectroscopic detection" generally refers to a method of identifying and/or characterizing molecules by irradiating a sample with light to obtain Raman spectroscopic data obtained from a sample. In the Raman spectroscopic detection, the sample may be illuminated, eg, with light from a laser and having a known wavelength (which may be visible, or near-infrared, or ultraviolet, for example). The light can interact with the electron cloud in the molecules of the sample, and as a result of this interaction produces a scattered light signal with a wavelength shift from the incident laser light. This wavelength shift can represent the difference between the vibrational and/or rotational energy levels of the molecules. The exact nature of this wavelength shift may depend on the molecules in the sample and may also include Stokes shift (where the emitted photons have a longer wavelength than the incident or illuminating photons) and/or anti-Stokes shift ( where the emitted photons have a shorter wavelength than the incident photons). Each molecule can produce a unique spectral signature, which can be referred to as a Raman label or Raman spectrum. The Raman label can then be used to identify and characterize the molecule. For example, the Raman label (Raman spectrum) can be compared to a library of known Raman labels (eg, by a processor) to facilitate identification of molecules in the sample. Raman spectroscopic detection can be implemented with reference to Richard L. McCreery, Raman Spectroscopy for Chemical Analysis and U.S. patents US8107069, US8081305, etc.

In this application, the term "two-component surface-enhanced Raman spectroscopy detection (BiASERS)" generally refers to a method for surface-enhanced Raman spectroscopy detection with a sample containing two or more target molecules, which may also be referred to as Bi-analyte SERS. The method for the detection of the two-component surface-enhanced Raman spectroscopy can be found in Le Ru, E.C.; Meyer, M.; Etchegoin, P.G., Proof of single-molecule sensitivity in surface enhanced Raman scattering (SERS) by means of a two-analyte technique. J. Phys. Chem. B 2006, 110(4), 1944-1948. In the present application, the two-component surface-enhanced Raman spectroscopy detection can be used to determine whether the medium particles have single-molecule detection capabilities. For example, in the two-component surface-enhanced Raman spectroscopy detection, under the condition of high concentration of two or more of the auxiliary molecules, most of the obtained spectra that generate spectral signals are the signals of the two or more auxiliary molecules at the same time. When the concentration of the auxiliary molecule was gradually reduced, most of the obtained spectra producing spectral signals were spectra of signals with only one auxiliary molecule. The spectra thus obtained for signals originating from only one accessory molecule can be used to determine whether the medium particles have single-molecule detection capabilities.

In this application, the term "surface-enhanced Raman spectroscopy detection" generally refers to Surface-enhanced Raman Scattering, SERS, which is a surface-sensitive technique that enhances Raman scattering, thereby increasing the sensitivity of Raman spectroscopy detection. The surface-enhanced Raman spectroscopy detection may also be referred to as surface-enhanced Raman scattering detection. The surface-enhanced Raman spectroscopy detection can enhance Raman scattering by adsorption on metal surfaces (eg, rough metal surfaces) and/or sols with nanostructures. For example, the surface-enhanced Raman spectroscopy detection can enhance the Raman spectroscopy signal by at least 10 orders of magnitude. For another example, the surface-enhanced Raman spectroscopic detection may refer to Raman scattering of adsorbed molecules due to the enhancement of the electromagnetic field on or near the surface of the sample in the excitation region on a specially prepared surface or sol of some metal good conductors. A detection method that improves the sensitivity of Raman spectroscopy detection by the phenomenon that the signal is greatly enhanced than the ordinary Raman scattering (NRS) signal. The surface-enhanced Raman spectroscopy detection can provide non-destructive, ultra-sensitive characterization.

In this application, the term "digital surface-enhanced Raman spectroscopy detection" generally refers to a method by which the surface-enhanced Raman spectroscopy detection can be performed digitally and quantitatively. In the present application, when performing the surface-enhanced Raman spectroscopy detection, "the presence of the target molecule" can be defined as "1"; "the absence of the target molecule" can be defined as "0", by calculating "1" ” to the ratio of the number of spectra producing spectral signals to quantify the target molecule. In this application, according to the results of the digital surface-enhanced Raman spectroscopy detection, it can be used to judge whether the medium particles meet the stability requirements required for the Raman spectroscopy detection (for example, particle sedimentation, agglomeration, increase or decrease the number of particles in the detection volume, the target molecule).

In this application, the term "surface-enhanced Raman particle" generally refers to the substrate used to perform the surface-enhanced Raman spectroscopic detection. The surface-enhanced Raman particles can be noble metal sols (for example, can be gold or silver nanoparticle sols). The nanoparticles with different shapes, sizes and surface functions can be selected according to different detection samples detected by surface-enhanced Raman spectroscopy. The surface-enhanced Raman particles may be in solid phase, for example, may be rough metal electrodes, nanoparticles assembled on the surface of filter paper, and/or metal island films with microscopic topography. For example, the surface-enhanced Raman particles may be hydroxylamine-silver colloidal particles, citric acid-silver colloidal particles, and/or citric acid-gold colloidal particles.

In this application, the term "quantitative detection at the single molecule level" generally refers to the detection and/or quantification of single molecules of an analyte in a sample to be detected that can be detected and/or quantified at very low levels (eg, pg).

In this application, the term "solution" generally refers to a dispersion system obtained by homogeneous and stable distribution of a pure substance in the state of molecules or ions in another pure substance. In the present application, the solution may be liquid. The solution may be a colloid. The solution may have fluidity.

In this application, the term "liquid system" generally refers to a liquid system of homogeneous composition of matter, possessing homogeneous physical and chemical properties. For example, the liquid phase system can be a liquid-containing system.

In this application, the term "first sample" generally refers to a sample comprising said mediator particles and at least two of said auxiliary molecules. In this application, the first sample can be used for the two-component surface-enhanced Raman spectroscopy detection. In the present application, the first sample can be used to determine whether the medium particle has the ability to detect single molecules.

In this application, the term "second sample" generally refers to a sample comprising the mediator particles and at least one of the auxiliary molecules. In the present application, the second sample can be used for the digital surface-enhanced Raman spectroscopy detection. In the present application, the second sample can determine whether the medium particles meet the stability requirements required for the Raman spectroscopy detection. In this application, the "first" and the "second" only refer to the samples containing the medium particles that need to be used to judge whether the medium particles meet the requirements of the Raman spectroscopy detection, There is no meaning of priority or order. In some cases, the first sample can be the same as the second sample.

In this application, the term "spectral signal" generally refers to the Raman spectroscopy detection involved in this application (for example, it can be surface-enhanced Raman spectroscopy detection, it can be digital surface-enhanced Raman spectroscopy detection, it can be liquid-phase digitized surface Enhanced Raman Spectral Detection) The spectral signal in the Raman spectrum generated.

In this application, the term "signal strength" generally refers to an indicator reflecting the strength of a signal. For example, the signal strength may be the signal strength generated by the spectral signal.

In this application, the term "about", when used generally in connection with a numerical value, can refer to a set or range that includes the value. For example, "about X" includes a range of values that is X ±20%, ±10%, ±5%, ±2%, ±1%, ±0.5%, ±0.2%, or ±0.1%, where X is a numerical value .

Detailed description of the invention

In the present application, the detection may include qualitative detection and/or quantitative detection. For example, the detection includes quantitative detection at the single molecule level. For example, the detection can determine the presence or absence of a single molecule of the target molecule in the sample. The methods described in this application can therefore be used for precise quantification of target molecules.

In the present application, the step a) can provide suitable said medium particles and said sample for subsequent detection steps. In the present application, the step a) may provide the mixture comprising the medium particles and the sample to be detected for subsequent detection. Wherein, the step a) can be carried out in a liquid phase. The step a) can facilitate the binding of the target molecule and the mediator particles by adjusting the liquid phase system (eg, adjusting pH, ion concentration, etc.).

In the present application, suitable media particles can be selected by means of the auxiliary molecules by means of some experimental methods (eg two-component surface-enhanced Raman spectroscopy detection and/or digital surface-enhanced Raman spectroscopy detection). Specifically, two-component surface-enhanced Raman spectroscopy can be used to detect auxiliary molecules by using the medium particles, and it is determined whether the medium particles are Has a single-molecule level detection sensitivity for the accessory molecule. If so, it can be considered that the medium particle can also have a single-molecule level detection sensitivity for the target molecule. Specifically, surface-enhanced Raman spectroscopy can be used to detect auxiliary molecules by using the medium particles, and whether the medium particles can Stability (eg, suspension stability, eg, in a liquid-phase system) is maintained in the method for detecting a target molecule described in the application. Therefore, in step a), by selecting suitable medium particles (that is, the medium particles have single-molecule level detection sensitivity to the target molecule, and maintain stability in the method for detecting target molecules), so as to achieve a solution in the liquid phase system. The target molecule is detected with the aid of the medium particles.

In the present application, the sample may be in the form of a solution. For example, the target molecule can be dissolved in a solvent (eg, water, eg, ethanol). For example, the sample may be a solution containing target molecules.

In the present application, the medium particles may be dispersed in a solution. For example, the media particles can be dispersed in a liquid in which the media particles can be dispersed (eg, can be dispersed in a suitable liquid first, and can be further diluted, eg, diluted with water). In the present application, in the solution containing the medium particles, the properties and/or morphology of the medium particles can be detected by extinction spectroscopy and/or transmission electron microscopy.

In the present application, the medium particles may be mixed with the sample in a liquid phase system. For example, the sample may be mixed with a solution containing the medium particles in a volume ratio (eg, the sample and the solution containing the medium particles may be mixed at a ratio of about 1:20, about 1:15, about 1:10, about 1:9, about 1:8, about 1:7, about 1:6, about 1:5, about 1:4, about 1:3, about 1:2, about 1:1 ratio mixed). In the present application, the mixing may use means such as ultrasound to promote thorough and uniform mixing of the medium particles with the solution of the sample containing the target molecule.

In the present application, mixing includes that the medium particles can be incubated with the sample in a liquid phase system. For example, the incubation can be performed in the dark. For example, the incubation time can be at least about 0.5 hours, at least about 1 hour, at least about 1.5 hours, at least about 2 hours, or more.

In the present application, the target molecules may include small molecules and/or macromolecules. For example, the macromolecule can be a biological macromolecule. For example, the macromolecules can include peptides and/or proteins. The macromolecule can be a macromolecule of natural origin or a macromolecule obtained by artificial modification. In the present application, the macromolecule may be a molecule with a relative molecular mass of at least 5000. The macromolecules may also include polymers. In the present application, the small molecule can be an element, a compound (eg, organic or inorganic). For example, the small molecule can include nucleosides, nucleotides and/or amino acids.

In the present application, the medium particles may include metal nanoparticle sols, metal nanoparticles and/or nanostructured substrates. In the present application, the media particles may comprise surface-enhanced Raman particles. For example, the media particles may include hydroxylamine-silver colloidal particles, citric acid-silver colloidal particles, and/or citric acid-gold colloidal particles.

In the present application, the auxiliary molecules may include small molecules and/or macromolecules. In the present application, the kind of the auxiliary molecule may be the same as the kind of the target molecule. In the present application, the corresponding type of the auxiliary molecule can be selected according to the type of the target molecule (for example, the same type of molecule can be selected as the auxiliary molecule according to the type of the target molecule).

In the present application, the two-component surface-enhanced Raman spectroscopy detection may include detecting a first sample, the first sample comprising the medium particles and at least two (for example, at least two, at least three) , at least 4 or more) of the auxiliary molecules.

In the two-component surface-enhanced Raman spectroscopic detection of the present application, under the condition of high concentration of two or more of the auxiliary molecules, most of the obtained spectra that generate spectral signals may be two or more auxiliary molecules present at the same time. The spectrum of the signal of the molecule; when the concentration of the helper molecule is gradually reduced, most of the spectra obtained that produce the spectral signal may be the spectrum of the signal of only one kind of helper molecule. The spectra thus obtained for signals originating from only one accessory molecule can be used to determine whether the medium particles have single-molecule detection capabilities.

In the present application, the two-component surface-enhanced Raman spectroscopy detection may include the following steps: at least once (for example, at least 1 time, at least 2 times, at least 3 times, at least 4 times, at least 5 times, at least 6 times) , at least 7 times, at least 8 times, at least 9 times, at least 10 times or more) to reduce said at least two (eg can be at least 2, at least 3, at least 4 or more) concentrations of accessory molecules.

In the present application, the reduction is that the concentration of each of the helper molecules may be decreased by at least 0.1 orders of magnitude each time (eg, may be decreased by at least about 0.1 orders of magnitude, at least about 0.2 orders of magnitude, at least about 0.3 orders of magnitude, at least about 0.4 orders of magnitude, at least about 0.5 orders of magnitude, at least about 0.6 orders of magnitude, at least about 0.7 orders of magnitude, at least about 0.8 orders of magnitude, at least about 0.9 orders of magnitude order of magnitude, at least about 1.0 orders of magnitude, at least about 1.5 orders of magnitude, at least about 2.0 orders of magnitude or more).

In the present application, the reduction is that the concentration of each of the helper molecules can be decreased by about 0.1 to about 1 order of magnitude at a time compared to the original concentration of the helper molecule in the first sample (eg, it can be about 0.1 to about 1 order of magnitude, about 0.2 to about 1 order of magnitude, about 0.3 to about 1 order of magnitude, about 0.4 to about 1 order of magnitude, about 0.5 to about 1 order of magnitude, about 0.1 to about 0.9 order of magnitude, about 0.2 to about 0.9 orders of magnitude, about 0.3 to about 0.9 orders of magnitude, about 0.4 to about 0.9 orders of magnitude, about 0.5 to about 0.9 orders of magnitude, about 0.1 to about 0.8 orders of magnitude, about 0.2 to about 0.8 orders of magnitude, or about 0.3- about 0.8 orders of magnitude).

In the present application, the two-component surface-enhanced Raman spectroscopy detection may include the following steps: detecting the spectral signal generated by each of the auxiliary molecules in the first sample after the reduction.

In the present application, the two-component surface-enhanced Raman spectroscopic detection may further include the following step of counting the spectral numbers of all the spectra that generate spectral signals.

In the present application, in a single spectrum, when the spectral signal generated by the auxiliary molecule accounts for at least 85% of the spectral signal of the single spectrum (eg, can be at least about 85%, at least about 86%, at least about 87%, at least about 88%, at least about 89%, at least about 90%, at least about 91%, at least about 92%, at least about 93%, at least about 94%, at least about 95%, at least about 96%, at least about about 97%, at least about 98%, at least about 99% or more), the single spectrum can be considered to be the auxiliary molecule single molecule spectrum.

In the present application, when the ratio of the spectral number of the single molecule spectrum of the auxiliary molecule to the spectral number of the generated spectral signal is at least 50% (for example, it may be at least about 50%, at least about 55%, at least about 60%, at least about about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95% or more), the media particles may have specificity to the accessory molecule Detection sensitivity at the single molecule level. In the present application, when the ratio of the spectral number of the single molecule spectrum of the auxiliary molecule to the spectral number of the generated spectral signal is at least 50% (for example, it may be at least about 50%, at least about 55%, at least about 60%, at least about about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95% or more), the mediator particles may have specificity for the target molecule Detection sensitivity at the single molecule level.

In the present application, the surface-enhanced Raman spectroscopy detection may include detecting a second sample, the second sample comprising the medium particles and at least one (for example, may be at least 1, at least 2, at least 3, at least 4 or more) of the auxiliary molecules.

In the present application, the surface-enhanced Raman spectroscopy detection may include detecting the signal intensity generated by the helper molecule. The surface-enhanced Raman spectroscopy detection can be counted by the above counting. In the process of the digital surface-enhanced Raman spectroscopy detection, the signal intensity generated by the auxiliary molecules varies with the scanning process (for example, the size of the scanned area and the size of the scanned area can be used. / or the total duration of the scan to characterize) changes.

In the present application, the digitized surface-enhanced Raman spectroscopy detection may include calculating the time interval of the auxiliary molecule at any time interval (for example, an interval of about at least 1 second, an interval of about at least 2 seconds, an interval of about at least 3 seconds, at least about 4 seconds apart, at least about 5 seconds apart, at least about 6 seconds apart, at least about 7 seconds apart, at least about 8 seconds apart, at least about 9 seconds apart or longer) correlation coefficient between. For example, a correlation coefficient between the signal intensities of the helper molecule at two time points at any time interval can be calculated. For example, by using the signal strengths at multiple different time points at any time interval, the signal strengths at two adjacent time points can be selected respectively, so as to calculate the signal at these two optional adjacent time points. Intensity correlation coefficient. The average value of such a series of correlation coefficients can be used to determine whether the medium particles can maintain stability in the method for detecting target molecules described herein.

In the present application, if the absolute value of the correlation coefficient is about 0.3 or less (eg, the absolute value of the correlation coefficient |r| may be about 0.3 or less, about 0.25 or less, about 0.2 or less, about 0.15 or less) , about 0.1 or less, about 0.05 or less), it can be considered that the medium particles can maintain stability in the method for detecting target molecules described in the present application. For example, if the signal intensity gradually increases, decreases, or changes significantly with scanning, the slope of the fitted curve increases significantly (eg, the media particles settle, agglomerate, etc.), then the Mediator particles do not remain stable in the methods described herein for detecting target molecules.

In the present application, when the absolute value of the correlation coefficient is about 0.3 or less (for example, the absolute value of the correlation coefficient |r| may be about 0.3 or less, about 0.25 or less, about 0.2 or less, about 0.15 or less , about 0.1 or less, about 0.05 or less), the media particles may have stability for the digital surface-enhanced Raman spectroscopy detection, or the media particles may have stability for the detection target molecules described in the present application method stability.

In the present application, if the absolute value of the correlation coefficient is about 0.3 or less (eg, the absolute value of the correlation coefficient |r| may be about 0.3 or less, about 0.25 or less, about 0.2 or less, about 0.15 or less) , about 0.1 or less, about 0.05 or less), the media particles can be at least 60 minutes (eg, can be at least about 60 minutes, at least about 65 minutes, at least about 70 minutes, at least about 75 minutes, at least about 80 minutes minutes, at least about 85 minutes, at least about 90 minutes, at least about 95 minutes, at least about 100 minutes, at least about 105 minutes, at least about 110 minutes, at least about 115 minutes, at least about 120 minutes or more) sex.

In some cases, suitable media particles can be selected by some experimental methods (eg, two-component surface-enhanced Raman spectroscopy detection and/or extinction spectroscopy detection). Specifically, the extinction spectrum of the medium particles can be used to determine whether the medium particles can maintain stability (for example, suspension stability, such as suspension in a liquid phase system) in the method for detecting target molecules described in the present application. stability). Therefore, in step a), by selecting suitable medium particles (that is, the medium particles have single-molecule level detection sensitivity to the target molecule, and maintain stability in the method for detecting target molecules), so as to achieve a solution in the liquid phase system. The target molecule is detected with the aid of the medium particles.

In the present application, if the medium particles (for example, may be in a state of being dispersed in a solution) remain unchanged during the detection process of extinction spectroscopy, it can be considered that the medium particles do not settle in the solution, so they can be Stability is maintained in the methods of detecting target molecules described herein. The detection of the extinction spectrum can be measured by the extinction peak of the medium particles. If during the detection of the extinction spectrum (for example, it can be at least 180 minutes), the difference between the initial value and the final value of the intensity of the extinction peak of the medium particles is about 5% or less (for example, the initial value and the final value are less than 5%). The difference value of the final value can be calculated by the following formula: difference value=(last value-initial value)/initial value×100%) (for example, it can be about 5% or less, about 4.5% or less, about 4% or less, about 3.5% or less, about 3% or less, about 2.5% or less, about 2% or less, about 1.5% or less, about 1% or less, about 0.5% or less); and/or, the extinction peak of the medium particles The relative standard deviation of the intensity is about 2% or less (for example, it may be about 1.9% or less, about 1.8% or less, about 1.7% or less, about 1.6% or less, about 1.5% or less, about 1.4% or less, about 1.3% or less, about 1.2% or less, about 1.1% or less, about 1.0% or less, or less), it can be considered that the medium particles can maintain stability in the method for detecting target molecules described herein. On the contrary, if the relative standard deviation of the intensity of the extinction peak of the medium particle is too large, or the difference between the initial value and the final value of the intensity of the extinction peak of the medium particle is too large, the medium particle may be in the solution. Sedimentation occurs, and it is therefore believed that at this time the media particles cannot remain stable in the method for detecting target molecules described herein.

In some cases, suitable media particles can be selected by means of the helper molecule by some experimental methods (eg, two-component surface-enhanced Raman spectroscopy detection and/or digital surface-enhanced Raman spectroscopy detection). Specifically, surface-enhanced Raman spectroscopy can be used to detect auxiliary molecules by using the media particles, and it can be determined whether the media particles can be detected in the present application through the uniformity of the Raman spectra generated by the auxiliary molecules. The stability of the target molecule is maintained in the process (eg, suspension stability, eg, in a liquid phase system). Therefore, in step a), by selecting suitable medium particles (that is, the medium particles have single-molecule level detection sensitivity to the target molecule, and maintain stability in the method for detecting target molecules), so as to achieve a solution in the liquid phase system. The target molecule is detected with the aid of the medium particles.

In the present application, if the peak area of the characteristic peak of the auxiliary molecule does not change much with time during the surface-enhanced Raman spectroscopy detection process of the auxiliary molecule, and the generated signal intensity remains stable, it can be considered that the auxiliary molecule The mediator particles can remain stable in the methods of detecting target molecules described herein. For example, when the concentration of the accessory molecule is 10 ^-7 M, if the relative standard deviation of the characteristic signal intensity of the accessory molecule can be about 50% or less (for example, it can be about 50% or less, about 45% or less, about 40% or less, about 35% or less, about 30% or less, about 25% or less, about 20% or less, about 15% or less, about 10% or less, about 5% or less), it can be considered that the The mediator particles can remain stable in the methods of detecting target molecules described herein.

In the present application, the method may include the following steps: b) performing Raman detection on the mixed medium particles and the sample containing the target molecule to obtain a Raman spectrum of the target molecule.

In the present application, the laser wavelength, laser power, scanning step size and/or irradiation time can be selected in accordance with the target molecules and/or the medium particles. When performing the Raman detection, the mixed medium particles and the sample containing the target molecule can be carried in the form of a carrier (for example, it can be a capillary, a glass slide, a well plate or a dish), in a liquid system. The laser scanning of the Raman detection is performed internally.

In the present application, the Raman detection may include surface-enhanced Raman spectroscopy detection. For example, the Raman detection may include digitized surface-enhanced Raman spectroscopy detection. In the present application, "the presence of the target molecule" may be defined as "1", and the "absence of the target molecule" may be defined as "0". The concentration of the target molecule in the sample can be converted by counting the number of "1"s and dividing it by the ratio of the total number of points scanned.

In the present application, the method may include the following steps: c) obtaining the corresponding abundance value of the target molecule in each Raman spectrum according to the Raman spectrum of the target molecule. For example, the abundance value can be calculated from the following parameters: the characteristic peak intensity of the target molecule, the characteristic peak area of the target molecule, and the relative coefficient obtained by spectral fitting of the target molecule.

In the present application, for different target molecules, the sample where the target molecule may be located may be adjusted accordingly, and the method for detecting target molecules described in the present application (for example, the Raman detection, for example, the liquid phase digitization method) can be adjusted accordingly. Detection reagents and/or detection instruments required for surface-enhanced Raman spectroscopy detection), and/or adjusting the method for detecting target molecules described in this application (eg, the Raman detection, such as liquid-phase digital surface-enhanced Raman spectroscopy detection) The calculation methods and/or parameters in the involved calculation steps, so as to further improve the reliability of the method for detecting target molecules described in this application (such as the Raman detection, such as liquid phase digital surface-enhanced Raman spectroscopy detection) (such as , further reduce the detection error, and/or, further improve the reliability of the detection).

In the present application, the method for detecting target molecules may include the steps of diluting, concentrating and/or extracting the sample containing target molecules. In some cases, the concentration of the target molecule in the sample can be adjusted by means of dilution, concentration and/or extraction, thereby making the method of the present application more reliable (eg, further reducing detection errors, and/or, to further improve the reliability of detection) to detect the target molecule.

In the present application, the method for detecting target molecules may include the step of adjusting (eg, modifying the surface-enhanced Raman particles) the medium particles (eg, the surface-enhanced Raman particles) described in the present application. For example, in some cases, the surface-enhanced Raman particle can be modified to alter (eg, increase) the binding ability of the surface-enhanced Raman particle to the target molecule, thereby enabling the method of the present application The target molecule is detected more reliably (eg, by further improving the detection rate, by further reducing the detection error, and/or by further improving the reliability of the detection). For example, when the concentration of the target molecule is constant, the surface-enhanced Raman particles can be modified to increase or decrease the number of times and/or the number of times the target molecule is judged to exist in all the measured Raman spectra. frequency.

In the present application, the method for detecting a target molecule may include adjusting the sample comprising the target molecule described in the present application (eg, physicochemical properties of the sample (eg, temperature, salinity, pH and/or viscosity) adjustment) steps. For example, in some cases, the motility of the target molecule in the sample can be altered (eg, increased ), so that the method of the present application can detect the target molecule more reliably (eg, further improve the detection rate, further reduce the detection error, and/or further improve the reliability of the detection). For example, adjusting the sample (eg, heating, stirring, appropriately increasing salinity and/or appropriately reducing viscosity; or, cooling, standing, appropriately reducing salinity, and/or Appropriately increase the viscosity), increase or decrease the number and/or frequency of the target molecule judged to be present in all Raman spectra measured.

In the present application, the method of detecting target molecules may include parameters (eg laser wavelength, detection area/volume, power density, quantum of efficiency, etc.) to make adjustments. For example, in some cases, the method of the present application may be made more reliable (eg, further improved) by adjusting the parameters to change (eg, increase) the probability that the method will detect the target molecule. The detection rate, further reducing the detection error, and/or, further improving the reliability of the detection) detects the target molecule. For example, when the concentration of the target molecule is constant, the parameters are adjusted (for example, the detection volume is appropriately increased; the wavelength and/or power density of the detection instrument are adapted to the target molecule; and/or the quantum efficiency is appropriately increased) The number and/or frequency of the target molecule being judged to be present in all Raman spectra measured can be increased.

In the present application, the method for detecting a target molecule may include determining whether the target molecule is present in the sample based on the number of times the target molecule is judged to exist, the frequency, and/or the mathematical mapping relationship based on the number and/or frequency of the presence of the target molecule. Describe the steps for the presence or absence and/or concentration of target molecules. For example, the method may not completely depend on the number and frequency of the specific target molecule being judged to exist, but may also be based on the mapping relationship corresponding to the number and/or frequency.

In the present application, the method of detecting a target molecule may include the step of adjusting (eg increasing/decreasing) the total number of spectra tested/number of positive spectra detected in each assay. In some cases, the above adjustments may control (eg, reduce) the theoretical counting error of the method of detecting target molecules, thereby making the method of the present application more reliable (eg, further reducing the detection error, and/or , to further improve the reliability of detection) to detect the target molecule. In some cases, through the above adjustment, the detection sensitivity of the method described in the present application can be controlled (for example, improved), so that the method described in the present application can achieve uniform detection of samples containing the target molecules in different concentration ranges. Perform reliable qualitative and/or quantitative assays.

In the present application, the method of detecting a target molecule may include adjusting (eg, increasing) the number of digital surface-enhanced Raman spectroscopy detections (eg, liquid-phase digital surface-enhanced Raman spectroscopy detections). In some cases, through the above adjustments (for example, more than 2 (eg, 2, 3, 4, 5 or more) liquid-phase digital surface-enhanced Raman spectroscopy detection can be performed), the present application can be made The method detects the target molecule more reliably (eg, further reduces detection error, and/or further increases the reliability of detection).

In the present application, the method for detecting a target molecule can quantitatively analyze the target molecule (eg, the accuracy of the quantitative analysis can be controlled; and/or reproducibility).

In the present application, the method for detecting a target molecule includes the following steps: determining a threshold for judging the existence of the target molecule according to the abundance value of a blank sample that does not contain the target molecule. In the present application, the threshold value can be calculated by comparing with the corresponding value of a blank control (which can be a solvent that does not contain the target molecule). For example, the threshold may be set as the mean of the abundance values of the blank control + 3 times the standard deviation; alternatively, the threshold may be set as the mean of the abundance values of the blank + 5 times the standard deviation.

In the present application, the method for detecting a target molecule includes the following steps: obtaining the concentration of the target molecule in the sample according to the number and/or frequency of the target molecule being judged to exist in the sample. In the present application, the sample containing a high concentration of the target molecule can be diluted to further increase the accuracy of quantitative detection.

In this application, the method described in this application may be liquid-phase digital surface-enhanced Raman spectroscopy detection. For example, the methods described herein can mix the target molecules and the medium particles in a liquid phase system to perform digital surface-enhanced Raman spectroscopy detection.

In the present application, the medium particles can be mixed with the target molecules in a liquid phase system. For example, the mediator particles can be mixed with the target molecule in solution.

In the present application, the liquid-phase digital surface-enhanced Raman spectroscopy detection can quantitatively detect the concentration of the target molecule.

Without intending to be limited by any theory, the following examples are only used to illustrate the various technical solutions of the invention of the present application, but are not used to limit the scope of the invention of the present application.

Example

Example 1 Using hydroxylamine-silver colloidal particles (Hya-Ag NPs) as surface-enhanced Raman particles to detect crystal violet (Crystal Violet, CV) by liquid-phase digital surface-enhanced Raman spectroscopy

1. Preparation of hydroxylamine-silver colloidal particles

To synthesize 100ml Hya-Ag NPs system, 21mg of hydroxylamine hydrochloride (Aladdin, 99%), 18mg of sodium hydroxide (RHAWN, ≥98%) were dissolved in 90mL of water, and 10mL of an aqueous solution containing 17mg of silver nitrate (Aladdin, 99.8%) was added quickly, With rapid shaking, the color of the solution finally stabilized to yellow. The extinction spectrum of the hydroxylamine-silver colloidal particle solution is shown in FIG. 1 , and the transmission electron microscope result of the hydroxylamine-silver colloidal particle solution is shown in FIG. 2 .

2. Preparation of samples to be tested

Prepare CV (Absin, 95%)-ethanol (Sinopharm, ≥99.7%) solutions with different concentrations, mix the solution with hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9, and perform ultrasonic vibration after adding to make the mixing uniform , incubate in the dark for 1 hour, and briefly sonicate and shake to prevent particle precipitation.

3. Raman test

Take 10 μL of the solution into the capillary, place it in a Raman confocal spectrometer, use 638 nm as the laser wavelength, the laser power is 12.67 mW, 10 times the objective lens, with 10 μm as the scanning step, and perform the scanning mode of the platform moving area to obtain the surface-enhanced Raman spectrum .

4. Quantitative calculation

After the Raman spectrum is measured, the baseline is removed, 800 cm ^-1 is selected as the CV characteristic Raman peak, and the peak area of 780-820 cm ^-1 is calculated for calculation. Obtain the average value of the corresponding peak area values plus three times the standard deviation of the blank control (wherein the blank control is a solution obtained by mixing an ethanol solution that does not contain CV and a hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9) 200 (counts·cm ⁻¹ ) was used as a threshold for judging whether there was a CV contribution in each field spectrum (see FIG. 3 ).

In FIG. 3 , the peak area of 780-820 cm ⁻¹ is used as a quantitative index, and the numerical result of the peak area at the Raman shift of the blank control is shown in FIG. 3 . The threshold value is ≥ average + 3 times standard deviation, so this embodiment uses 200 (counts·cm ⁻¹ ) as the threshold (TH) for judging whether there is a CV.

For the surface-enhanced Raman spectra of all samples to be tested, the existence of CV is judged one by one, and the spectrum judged to be "with CV" is defined as "1", and the spectrum of "without CV" is defined as "0" ( See Figure 4). In Fig. 4, the left column shows the peak area value at 800 cm ^-1 of 600 sequential scan points for different concentrations of CV under the condition of hydroxylamine-silver colloidal particle solution, where TH represents the presence or absence of the CV threshold. The right column shows the result of digitizing the data in the left column. The numbers defined as "1" are marked in the form of vertical lines.

Calculate the ratio of the number of occurrences of "1" to the total test spectrum, which can correspond to the concentration of CV in the test sample. Quantitation of CV at ultra-low concentrations can be achieved by establishing a standard curve for quantification of ultra-low concentrations of CV (see Figure 5). In Fig. 5, 4 points are the average frequency values of the three tests of CV with different concentrations under the condition of hydroxylamine-silver colloidal particle solution; the standard deviation is the standard deviation of the average frequency value under each concentration; the black line is the fitted straight line y= ax+b, where R ² =0.99.

Example 2 Using citric acid-gold colloids (Citrate-Au NPs) as surface-enhanced Raman particles to detect 4-Nitrobenzenethiol (4-NBT) by liquid-phase digital surface-enhanced Raman spectroscopy

1. Preparation of citric acid-gold colloidal particles

Synthesize 550mL Citate-Au NPs system, dissolve 240mg of chloroauric acid in 500mL of water, boil, add 50mL of 1% sodium citrate solution, continue to boil for about 40 minutes, the solution finally turns wine red and stabilizes, and the reaction is terminated by rapid cooling. The extinction spectrum of the citric acid-gold colloidal particle solution is shown in FIG. 6 , and the transmission electron microscope result of the citric acid-gold colloidal particle solution is shown in FIG. 7 .

2. Preparation of samples to be tested

Prepare 4-NBT-ethanol solutions of different concentrations, mix the solution with citric acid-gold colloidal particle solution in a volume ratio of 1:9, and then ultrasonicate to make the mixture uniform. Particle precipitation.

3. Raman test

4. Quantitative calculation

After the Raman spectrum was measured, the baseline was removed, 1335 cm -1 was selected as the characteristic Raman peak of ⁴ -NBT, and the peak area of ^1305-1355 cm ^-1 was calculated for calculation. Calculate the average value of the peak area values corresponding to the blank control (wherein the blank control is a solution obtained by mixing an ethanol solution not containing 4-NBT and a citric acid-gold colloidal particle solution in a volume ratio of 1:9) and adding three The fold standard deviation was 200 (counts·cm ⁻¹ ) as the threshold for judging whether there was a contribution of 4-NBT in each field spectrum (see FIG. 8 ). In FIG. 8 , the peak area of 1305-1355 cm ⁻¹ is used as a quantitative index, and the numerical result of the peak area at the Raman shift of the blank control is shown in FIG. 8 . The threshold value is ≥ average value+3 times the standard deviation, so in this embodiment, 200 (counts·cm ⁻¹ ) is used as the threshold value (TH) for judging whether the -4-NBT exists.

For the surface-enhanced Raman spectra of all samples to be tested, the presence or absence of 4-NBT was judged one by one, the spectrum judged as "4-NBT present" was defined as "1", and the spectrum "without 4-NBT" was defined as "1" Defined as "0" (see Figure 9). In Fig. 9, the left column shows the peak area value at 1335 cm ^-1 of 600 sequential scan points of 4-NBT with different concentrations in the citric acid-gold colloidal particle solution condition, where TH represents the threshold for the presence or absence of 4-NBT. The right column shows the result of digitizing the data in the left column. The numbers defined as "1" are marked in the form of vertical lines.

Calculate the ratio of the number of occurrences of "1" to the total test spectrum, which can correspond to the concentration of 4-NBT in the test sample. Quantitation of ultra-low concentrations of 4-NBT can be achieved by establishing a standard curve for the quantification of ultra-low concentrations of 4-NBT (see Figure 10). In Figure 10, 4 points are the average frequency values of three tests of 4-NBT with different concentrations under the condition of citric acid-gold colloidal particle solution; the standard deviation is the standard deviation of the average frequency value at each concentration; the black line is the fitting Line y=ax ⁺ b, where R2=0.94.

Example 3 Using hydroxylamine-silver colloidal particles (Hya-Ag NPs) as surface-enhanced Raman particles to detect hemoglobin by liquid-phase digital surface-enhanced Raman spectroscopy

1. Preparation of hydroxylamine-silver colloidal particles

2. Preparation of samples to be tested

Prepare different concentrations of hemoglobin-water solution, mix the solution with hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9, and perform ultrasonic vibration after adding to make the mixing uniform.

3. Raman test

4. Quantitative calculation

After the Raman spectrum is measured, the baseline is removed, 1245 cm ^-1 is selected as the characteristic Raman peak of hemoglobin, and the peak area of 1220-1270 cm- ¹ is calculated for calculation. The average value of the corresponding peak area value plus three times the standard deviation is 562 (counts· cm ^- ¹ ) as the threshold for judging the presence or absence of the contribution of hemoglobin in each spectrum (see Figure 11).

In FIG. 11 , the peak area of 1220-1270 cm ⁻¹ is used as a quantitative indicator, wherein the numerical result of the peak area of the blank control at the Raman shift is shown in FIG. 11 . The threshold value is ≥ mean+3 times the standard deviation, so in this embodiment, 562 (counts·cm ⁻¹ ) is used as the threshold (TH) for judging whether hemoglobin exists.

For the surface-enhanced Raman spectra of all samples to be tested, the presence or absence of hemoglobin is judged one by one, and the spectrum judged to be "hemoglobin is present" is defined as "1", and the spectrum of "absence of hemoglobin" is defined as "0" ( See Figure 12). In Fig. 12, the left column shows the peak area value at 1245 cm ^-1 of 200 sequential scan points of hemoglobin with different concentrations under the condition of hydroxylamine-silver colloidal particle solution, where TH represents the threshold value of the presence or absence of hemoglobin. The right column shows the result of digitizing the data in the left column. The numbers defined as "1" are marked in the form of vertical lines.

The ratio of the number of occurrences of "1" to the total test spectrum can be calculated to correspond to the concentration of hemoglobin in the test sample. By establishing a low-concentration hemoglobin quantification standard curve (Figure 13), quantification of low-concentration hemoglobin can be achieved. In Figure 13, 3 points are the average frequency values of different concentrations of hemoglobin under the condition of hydroxylamine-silver colloidal particle solution for three tests; the standard deviation is the standard deviation of the average frequency value under each concentration; the black line is the fitted straight line y= ax+b, where R ² =0.99.

Example 4 Using hydroxylamine-silver colloidal particles (Hya-Ag NPs) as surface-enhanced Raman particles liquid-phase digital surface-enhanced Raman spectroscopy to detect nucleic acid sequences composed of adenine nucleotides (A12)

1. Preparation of hydroxylamine-silver colloidal particles

2. Preparation of samples to be tested

A12 aqueous solutions of different concentrations were prepared, and the solution was mixed with hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9. After adding, ultrasonic vibration was performed to make the mixing uniform, and short ultrasonic and vibration were used to prevent particle precipitation, and the test was carried out immediately.

3. Raman test

4. Quantitative calculation

After the Raman spectrum is measured, the baseline is removed, 728 cm ^-1 is selected as the A12 characteristic Raman peak, and the peak area of 705-755 cm- ¹ is calculated for calculation. The average value of the peak area value corresponding to the blank control (where the blank control is a solution obtained by mixing ultrapure water and hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9) plus three times the standard deviation is 500 (counts· cm ^-1 ) as the threshold for judging the presence or absence of the contribution of A12 in each spectrum (see Figure 11).

In FIG. 14 , the peak area of 705-755 cm ⁻¹ is used as a quantitative index, wherein the numerical result of the peak area of the blank control at the Raman shift is shown in FIG. 14 . The threshold value is ≥ average+3 times the standard deviation, so this embodiment uses 500 (counts·cm ⁻¹ ) as the threshold (TH) for judging whether A12 exists.

For the surface-enhanced Raman spectra of all samples to be tested, the existence of A12 is judged one by one, the spectrum judged as "existence of A12" is defined as "1", and the spectrum of "absence of A12" is defined as "0" ( See Figure 15). In Fig. 15, the left column shows the peak area value at 728 cm ^-1 of 200 sequential scan points of A12 with different concentrations under the condition of hydroxylamine-silver colloidal particle solution, where TH represents the threshold for the presence or absence of A12. The right column shows the result of digitizing the data in the left column. The numbers defined as "1" are marked in the form of vertical lines.

Calculate the ratio of the number of occurrences of "1" to the total test spectrum, which can correspond to the concentration of A12 in the test sample. The quantification of low concentrations of A12 can be achieved by establishing a low-concentration A12 quantification standard curve (Figure 16). In Figure 16, 3 points are the average frequency values of three tests of A12 with different concentrations under the condition of hydroxylamine-silver colloidal particle solution; the standard deviation is the standard deviation of the average frequency value under each concentration; the black line is the fitted straight line y= ax+b, where R ² =0.98.

Example 5 Selection of surface-enhanced Raman particles suitable for liquid-phase digital surface-enhanced Raman spectroscopy detection

The two-component surface-enhanced Raman technology was used to verify the single-molecule detection capability of surface-enhanced Raman particles. The steps are as follows:

(1) Prepare a test solution containing two target molecules, and mix it uniformly with the surface-enhanced Raman particle solution;

(2) carry out Raman mapping test to this mixed sample;

(3) analyzing the obtained spectrum, and finding out the spectrum containing the target molecule signal in the obtained spectrum;

(4) In all the spectra containing the target molecular signal, if the analysis spectrum contains the target molecular signal, the proportion of a certain target molecule in generating the signal can be used as an indicator for statistics;

(5) When the concentration of the two target molecules in the liquid to be tested gradually decreases, if a large number of spectra containing only the signals generated by a single target molecule can be obtained, the surface-enhanced Raman particles are considered to have single-molecule detection sensitivity.

1. Using hydroxylamine-silver colloidal particles (Hya-Ag NPs) as the candidate surface-enhanced Raman particles for detection

The results are shown in Table 1 and Figure 17:

Table 1

In Figure 17, Figure 17a shows the heat map of the distribution of crystal violet signal intensity in the mapping area, where the scale bar is 100 μm; Figure 17b shows the heat map of the distribution of the signal intensity of Nair blue in the mapping area, where the scale bar is 100 μm; Figure 17c shows The proportion of crystal violet signal intensity contribution in the spectrum with target molecule signal. Wherein, when p<0.1 or >0.9, the spectrum is judged to be a single molecule spectrum; when 0.1<p<0.9, the spectrum is judged to be a mixed spectrum containing two molecules.

2. Using citric acid-silver colloidal particles (Citrate-Ag NPs) as the candidate surface-enhanced Raman particles for detection

The results are shown in Table 2 and Figure 18:

Table 2

In Fig. 18, Fig. 18a shows the heat map of the distribution of crystal violet signal intensity in the mapping area, where the scale bar is 50 μm; Fig. 18b shows the heat map of the distribution of the signal intensity of Nair blue in the mapping area, where the scale bar is 50 μm; Fig. 18c shows The proportion of crystal violet signal intensity contribution in the spectrum with target molecule signal. Wherein, when p<0.1 or >0.9, the spectrum is judged to be a single molecule spectrum; when 0.1<p<0.9, the spectrum is judged to be a mixed spectrum containing two molecules.

3. Using citric acid-gold colloidal particles (Citrate-Au NPs) as the candidate surface-enhanced Raman particles for detection

The results are shown in Table 3 and Figure 19:

table 3

In Figure 19, Figure 19a shows the heat map of the distribution of crystal violet signal intensity in the mapping area, where the scale bar is 50 μm; Figure 19b shows the heat map of the distribution of the signal intensity of Nair blue in the mapping area, where the scale bar is 50 μm; Figure 19c shows The proportion of crystal violet signal intensity contribution in the spectrum with target molecule signal. Wherein, when p<0.1 or >0.9, the spectrum is judged to be a single molecule spectrum; when 0.1<p<0.9, the spectrum is judged to be a mixed spectrum containing two molecules.

Example 6 Selection of surface-enhanced Raman particles suitable for liquid-phase digital surface-enhanced Raman spectroscopy detection

6.1 Detection of crystal violet (CV) by surface-enhanced Raman spectroscopy using hydroxylamine-silver nanoparticles (Hya-Ag NPs) as surface-enhanced Raman particles

1. According to step 1 of Example 1, hydroxylamine-silver nanoparticles were synthesized.

2. Preparation of samples to be tested

Prepare CV (Absin, 95%)-ethanol (Sinopharm, ≥99.7%) solution, mix the solution with hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9, the final concentration of CV is 1nM, and ultrasonically vibrate after adding, Mix well, incubate in the dark for 1 hour, briefly sonicate and shake to prevent pellets from settling.

3. Raman test

4. Quantitative calculation

After the Raman spectrum is measured, the baseline is removed, 800 cm ^-1 is selected as the CV characteristic Raman peak, and the peak area of 780-820 cm ^-1 is calculated for calculation. The autocorrelation function of the CV characteristic Raman peak area values between the spectra is calculated according to the time series of the spectra.

The results are shown in Figure 20. Figure 20 reflects the autocorrelation coefficients of hydroxylamine-silver nanoparticle-enhanced CV time-series spectra. The calculation steps of the autocorrelation coefficient can be referred to (Brockwell, P.J., and R.A. Davis. 1987. Time Series: Theory and Methods. Springer-Verlag.). The correlation coefficients between spectra at any time interval in Fig. 20 show no correlation (|r|<0.3). It can be seen that the spectral sequence of hydroxylamine-silver colloidal particles scanned over time presents a "smooth" state, and hydroxylamine-silver colloidal particles can be used as the surface-enhanced Raman particles required for liquid-phase digital surface-enhanced Raman spectroscopy detection.

6.2 Detection of crystal violet (CV) by surface-enhanced Raman spectroscopy using Citrate-Ag NSs as surface-enhanced Raman particles

1. According to references (Adianez Garcia-Leis, Irene Rivera-Arreba, Santiago Sanchez-Cortes. Morphological tuning of plasmonic silver nanostars by controlling the nanoparticle growth mechanism: Application in the SERS detection of the amyloid marker Congo Red. Colloids and Surfaces A : Physicochemical and Engineering Aspects 2017, 535, 49-60.) Synthesis of citric acid-silver nanostar particles.

2. Preparation of samples to be tested

Prepare CV (Absin, 95%)-ethanol (Sinopharm, ≥99.7%) solution, mix the solution with hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9, the final concentration of CV is 10pM, and ultrasonically vibrate after adding, Mix well, incubate in the dark for 1 hour, briefly sonicate and shake to prevent pellets from settling.

3. Raman test

4. Quantitative calculation

The results are shown in Figure 21. Figure 21 reflects the autocorrelation coefficients of citric acid-silver nanostar particle-enhanced CV time-series spectra. The correlation coefficients between spectra at any time interval in Fig. 21 are all moderately/lowly correlated (|r|>0.3). It can be seen that the signal intensity of the spectral sequence of the citric acid-silver nanostar particles gradually increases with time and is unstable, so the citric acid-silver colloidal particles cannot be used as the surface-enhanced Raman required for liquid-phase digital surface-enhanced Raman spectroscopy detection. particles.

Example 7 Selection of surface-enhanced Raman particles suitable for liquid-phase digital surface-enhanced Raman spectroscopy detection

Extinction spectrum is used to judge whether it is suitable as the surface-enhanced Raman particles required for liquid-phase digital surface-enhanced Raman spectroscopy detection.

7.1 Preparation for the detection of crystal violet (CV) by surface-enhanced Raman spectroscopy using hydroxylamine-silver nanoparticles (Hya-Ag NPs) as surface-enhanced Raman particles

2. Take 3mL of the particle solution in a cuvette, and perform an extinction spectrum test in a violet-visible light spectrophotometer every 30min. During the period, the liquid is not taken out or shaken, and it is kept at rest.

The results are shown in Figure 22. Figure 22 is the extinction spectrum of hydroxylamine-silver nanoparticles as a function of time. The results show that the extinction peak spectrum does not change significantly within 3 hours, the relative standard deviation of the extinction peak (~406nm) intensity is 0.35%, and the value at the end of 3 hours is the same as The difference between the initial values is about 0.87% (the calculation method is: (last value-initial value)/initial value×100%), which is almost unchanged. It can be seen that the hydroxylamine-silver colloidal particles show a "stable" state with time, and the hydroxylamine-silver colloidal particles can be used as the surface-enhanced Raman particles required for liquid-phase digital surface-enhanced Raman spectroscopy detection.

7.2 Preparation of citric acid-silver nanostar particles (Citrate-Ag NSs) as surface-enhanced Raman particles to detect crystal violet (CV) by surface-enhanced Raman spectroscopy

The results are shown in Figure 23. Figure 23 is the extinction spectrum of citric acid-silver nanostar particles as a function of time, the results show that the extinction peak spectrum changes significantly within 3 hours, the relative standard deviation of the extinction peak (~420nm) intensity is 2.7%, and the value at the end of 3 hours The difference from the initial value is about -8.2% (the calculation method is: (last value-initial value)/initial value×100%). It can be seen that the citric acid-silver nanostar particles are in an "unstable" state with time, so the citric acid-silver nanostar particles cannot be used as the surface-enhanced Raman particles required for liquid-phase digital surface-enhanced Raman spectroscopy detection.

Example 8 Selection of surface-enhanced Raman particles suitable for liquid-phase digital surface-enhanced Raman spectroscopy detection

8.1 Detection of crystal violet (CV) by surface-enhanced Raman spectroscopy using hydroxylamine-silver nanoparticles (Hya-Ag NPs) as surface-enhanced Raman particles

(1) Hydroxylamine-silver nanoparticles and crystal violet-ethanol solution were uniformly mixed with a volume of 9:1, and the final concentration of crystal violet molecules in the mixed sample was 10 ^-7 M, and ultrasonically mixed uniformly, left to incubate for 30 minutes, and then Brief sonication and shaking to prevent particle precipitation

(2) Take 10 μL of the sample and inject it into the capillary, set the parameters (wavelength: 638 nm, power: 12.67 mW, integration time: 0.1 s, objective lens: 10 times, step size: 10 μm), and perform the scanning mode of the platform moving area to obtain surface enhancement Raman spectroscopy

(3) remove the baseline after recording the Raman spectrum, choose 800cm- ¹ as the CV characteristic Raman peak, calculate the peak area of 780-820cm ^- ¹ to calculate the relative standard of this CV-characteristic peak area corresponding to all obtained spectra Difference.

The results are shown in Figure 24. Figure 24 shows time-series spectral concentration CV-characteristic peak area intensities of hydroxylamine-silver nanoparticles enhanced ^10-7 M CV. The results show that the peak area of the CV-characteristic peak does not change much with time, and the signal intensity remains stable with a relative standard deviation of only 15%. It can be seen that hydroxylamine-silver colloidal particles can be used as the surface-enhanced Raman spectroscopic detection required for liquid-phase digital surface-enhanced Raman spectroscopy. Mann particles.

Example 9 Detection of oxytocin by liquid-phase digital surface-enhanced Raman spectroscopy using hydroxylamine-silver colloidal particles (Hya-Ag NPs) as surface-enhanced Raman particles

1. Preparation of hydroxylamine-silver colloidal particles

2. Preparation of samples to be tested

Different concentrations of oxytocin-water solution were prepared, and the solution was mixed with hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9. After adding, ultrasonic vibration was performed to make the mixing uniform, and short ultrasonic and vibration were used to prevent particle precipitation, and the test was carried out immediately.

3. Raman test

Take 10 μL of the solution into the capillary, place it in a Raman confocal spectrometer, use 532 nm as the laser wavelength, laser power 37.3 mW, 10x objective lens, and 10 μm as the scanning step size, perform the scanning mode of the platform moving area to obtain the surface-enhanced Raman spectrum .

4. Quantitative calculation

After the Raman spectrum is measured, the baseline is removed, 653 cm ^-1 is selected as the characteristic Raman peak of oxytocin, and the peak area of 625-675 cm ^-1 is calculated for calculation. The average value of the peak area value corresponding to the blank control (where the blank control is a solution obtained by mixing ultrapure water and hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9) plus three times the standard deviation is 1000 (counts· cm ^-1 ) as a threshold for judging the presence or absence of oxytocin contribution in each spectrum (see Figure 25).

In FIG. 25 , the peak area of 625-675 cm ⁻¹ is used as a quantitative indicator, wherein the numerical result of the peak area of the blank control at the Raman shift is shown in FIG. 25 . The threshold value is ≥ average + 3 times standard deviation, so in this embodiment, 1000 (counts·cm ⁻¹ ) is used as the threshold (TH) for judging whether oxytocin exists.

For the surface-enhanced Raman spectra of all the samples to be tested, the presence or absence of oxytocin was judged one by one, and the spectrum judged as "presence of oxytocin" was defined as "1", and the spectrum with "absence of oxytocin" was defined as " 0” (see Figure 26). In Figure 26, the left column shows the peak area value at 653 cm ^-1 of 200 sequential scan points of oxytocin at different concentrations under the condition of hydroxylamine-silver colloidal particle solution, where TH represents the threshold for the presence or absence of oxytocin. The right column shows the result of digitizing the data in the left column. The numbers defined as "1" are marked in the form of vertical lines.

The ratio of the number of occurrences of "1" to the total test spectrum can be calculated to correspond to the concentration of oxytocin in the test sample. Quantification of low concentrations of oxytocin can be achieved by establishing a standard curve for the quantification of low concentrations of oxytocin (Figure 27). In Figure 27, 3 points are the average frequency values of different concentrations of oxytocin under the condition of hydroxylamine-silver colloidal particle solution for three tests; the standard deviation is the standard deviation of the average frequency value under each concentration; the black line is the fitted straight line y =ax+b, where R ² =0.96.

Example 10 Using hydroxylamine-silver colloidal particles (Hya-Ag NPs) as surface-enhanced Raman particles liquid-phase digital surface-enhanced Raman spectroscopy to detect thiram in bean sprouts homogenate

1. Preparation of hydroxylamine-silver colloidal particles

2. Preparation of samples to be tested

Dispose different concentrations of Fumei Shuang-bean sprouts homogenate mixed solution, after 0.22 micron filter membrane filtration, the filtrate is mixed with hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9, and ultrasonic vibration is carried out after adding to make the mixing uniform, Briefly sonicate, shake to prevent particle precipitation, and test immediately.

3. Raman test

4. Quantitative calculation

After the Raman spectrum was measured, the baseline was removed, 1377 cm ^{-1 was selected as the double characteristic Raman peak of Fumei, and the peak area of 1355-1405 cm -1} ^was calculated for calculation. Obtain the blank control (wherein the blank control is the solution obtained by mixing the filtrate of bean sprouts homogenate and hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9) corresponding to the peak area value plus three times the standard The difference was 450 (counts·cm ⁻¹ ) as the threshold for judging whether there was a contribution of fumethicone in each spectrum (see FIG. 28 ).

In FIG. 28 , the peak area of 1355-1405 cm ⁻¹ is used as a quantitative indicator, wherein the numerical result of the peak area of the blank control at the Raman shift is shown in FIG. 28 . The threshold value is ≥ average + 3 times the standard deviation, so in this embodiment, 450 (counts·cm ⁻¹ ) is used as the threshold (TH) for judging whether or not there is fumedox.

For the surface-enhanced Raman spectra of all the samples to be tested, the presence or absence of fumethicone was judged one by one, and the spectrum judged as "presence of dextromethorphan" was defined as "1", and the spectrum of "absence of dextromethorphan" was defined as " 0” (see Figure 29). In Fig. 29, the left column shows the peak area value at 1377 cm ^-1 of 400 sequential scanning points in the filtrate of filtrates of different concentrations of tetracycline-bean sprouts homogenate, wherein TH represents the threshold value of the presence or absence of tetracycline. The right column shows the result of digitizing the data in the left column. The numbers defined as "1" are marked in the form of vertical lines.

The ratio of the number of occurrences of "1" to the total test spectrum can be calculated, which can correspond to the concentration of Famex in the test sample. By establishing a low-concentration fumetidine quantification standard curve (Figure 30), the quantification of low-concentration fumethicone can be achieved. In Figure 30, the 4 points are the average frequency values of the three tests of Fumei double solution with different concentrations; the standard deviation is the standard deviation of the average frequency value at each concentration; the black line is the fitted straight line y=ax+b, where R ² =0.99.

Example 11 Using hydroxylamine-silver colloidal particles (Hya-Ag NPs) as surface-enhanced Raman particles to detect paraquat in lake water by liquid-phase digital surface-enhanced Raman spectroscopy

1. Preparation of hydroxylamine-silver colloidal particles

2. Preparation of samples to be tested

The paraquat-lake water mixture of different concentrations was prepared, filtered through a 0.22-micron membrane, and the filtrate was mixed with the hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9. After adding, ultrasonic vibration was performed to make the mixture uniform, and ultrasonically for a short period of time. , shake to prevent particle precipitation, and test immediately.

3. Raman test

4. Quantitative calculation

After the Raman spectrum was measured, the baseline was removed, 1644 cm ^-1 was selected as the characteristic Raman peak of paraquat, and the peak area of 1620-1670 cm ^-1 was calculated for calculation. Obtain the blank control (wherein the blank control is the solution obtained by mixing the lake water filtrate without paraquat and the hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9) corresponding to the mean value of the peak area value plus three times the standard deviation as 450 (counts·cm ⁻¹ ) was used as the threshold for judging whether there was a contribution from paraquat in each spectrum (see FIG. 31 ).

In FIG. 31 , the peak area of 1620-1670 cm ⁻¹ is used as a quantitative index, and the numerical result of the peak area at the Raman shift of the blank control is shown in FIG. 31 . The threshold value is ≥ average + 3 times the standard deviation, so in this embodiment, 450 (counts·cm ⁻¹ ) is used as the threshold (TH) for judging the presence of paraquat.

For the surface-enhanced Raman spectra of all samples to be tested, the presence or absence of paraquat was judged one by one, and the spectrum judged to be "paraquat present" was defined as "1", and the spectrum of "paraquat absent" was defined as " 0” (see Figure 32). In Figure 32, the left column shows the peak area values at 1644 cm ^-1 of 400 sequential scan points in paraquat-lake water filtrate with different concentrations, where TH represents the threshold for the presence or absence of paraquat. The right column shows the result of digitizing the data in the left column. The numbers defined as "1" are marked in the form of vertical lines.

The ratio of the number of occurrences of "1" to the total test spectrum can be calculated to correspond to the concentration of paraquat in the test sample. Quantitation of low concentrations of paraquat can be achieved by establishing a standard curve for the quantification of paraquat at low concentrations (Figure 33). In Figure 33, the three points are the average frequency values of three tests of paraquat solutions with different concentrations; the standard deviation is the standard deviation of the average frequency value at each concentration; the black line is the fitted straight line y=ax+b, where R ² =0.99.

Example 12 Increase the total number of spectra included in the detection of digital surface-enhanced Raman spectroscopy/the number of spectra judged to be the presence of target molecules to improve detection accuracy

1. Preparation of samples to be tested

Prepare 1 pM crystal violet-ethanol mixture, mix it with hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9, and perform ultrasonic vibration after adding to make the mixture uniform.

2. Raman test

Take 10 μL of the solution into the capillary, place it in a Raman confocal spectrometer, use 638 nm as the laser wavelength, the laser power is 12.67 mW, 10 times the objective lens, with 10 μm as the scanning step, and perform the scanning mode of the platform moving area to obtain the surface-enhanced Raman spectrum , and set the total number of spectra obtained in each test scan to 100, 200, 300, 600, and 1000, respectively, and repeated three times.

3. Quantitative calculation

As described in Example 1, the positive rate of each test is calculated, and the relative standard deviation is calculated corresponding to the positive rate obtained from three tests with the same total number of spectra, and the relationship between the relative standard deviation of the positive rate and the total number of scanned spectra can be obtained, as shown in Figure 34 . The relative standard deviation of the positive rate can directly reflect the quantitative error, so it can be obtained that the quantitative error gradually decreases with the increase of the total number of scanned spectra. The above variation trend is consistent with the variation rule of the theoretical counting error corresponding to the total number of scanned spectra.

Example 13 Influence of different lens parameters on the detection rate of target molecules of the same concentration in the detection of digital surface-enhanced Raman spectroscopy

1. Preparation of samples to be tested

Prepare crystal violet-ethanol mixture of different concentrations, mix it with hydroxylamine-silver colloidal particle solution in a volume ratio of 1:9, and perform ultrasonic vibration after adding to make the mixture uniform.

2. Raman test

Take 10 μL of the solution into the capillary, place it in a Raman confocal spectrometer, use 638 nm as the laser wavelength and the laser power of 12.67 mW, and perform the scanning mode of the platform moving area to obtain the surface-enhanced Raman spectrum. The scanning step is 10 μm, and the objective lenses are respectively 10x, 40x and 60x lenses were selected to test each sample separately.

3. Quantitative calculation

As described in Example 1, the positive rate of each test was calculated, and corresponding to each objective lens, a crystal violet quantitative standard curve of liquid-phase digital surface-enhanced Raman spectroscopy could be obtained separately (as shown in Figure 35).

In this experiment, the detection volume of each spectrum is controlled by using objective lenses of different magnifications, that is, the detection volume corresponding to the 10x, 40x, and 60x objective lenses decreases in turn. As the detection volume decreases, the upper limit of the quantifiable concentration of the standard curve becomes higher and the slope of the curve increases.

The foregoing detailed description has been presented by way of explanation and example, and is not intended to limit the scope of the appended claims. Various modifications to the embodiments presently enumerated in this application will be apparent to those of ordinary skill in the art and remain within the scope of the appended claims and their equivalents.

Claims

A method for detecting a target molecule, comprising the following steps:

a) Particles of mediators are mixed with a sample comprising the target molecule, wherein the particles of mediators exhibit the following properties:

1) Bi-component surface-enhanced Raman spectroscopic detection (BiASERS) of auxiliary molecules using the medium particles, wherein the ratio of the spectral number of the single-molecule spectrum of the auxiliary molecule to the spectral number of the spectral signal is at least about 50%; and,

2) Using the medium particles to perform surface-enhanced Raman spectroscopy detection on auxiliary molecules, wherein the absolute value of the correlation coefficient between the signal intensities generated by the auxiliary molecules at any time interval is about 0.3 or less.
The method of claim 1, wherein the detection comprises qualitative detection and/or quantitative detection.
The method of any one of claims 1-2, wherein the detection comprises single-molecule level quantitative detection.
The method of any one of claims 1-3, wherein the sample is in the form of a solution.
The method of any of claims 1-4, wherein the medium particles are dispersed in a solution.
The method of any one of claims 1-5, wherein the medium particles and the sample are mixed in a liquid phase system.
6. The method of any one of claims 1-6, wherein mixing comprises incubating the medium particles and the sample in a liquid phase system.
The method of any one of claims 1-7, wherein the target molecules comprise small molecules and/or macromolecules.
The method of claim 8, wherein the macromolecules comprise peptides and/or proteins.
The method of any one of claims 1-9, wherein the medium particles comprise metal nanoparticle sols, metal nanoparticles and/or nanostructured substrates.
10. The method of any of claims 1-10, wherein the media particles comprise surface-enhanced Raman particles.
The method of any one of claims 1-11, wherein the media particles comprise hydroxylamine-silver colloidal particles, citric acid-silver colloidal particles, and/or citric acid-gold colloidal particles.
The method of any one of claims 1-12, wherein the accessory molecule comprises a small molecule and/or a macromolecule.
The method of any one of claims 1-13, wherein the species of the helper molecule is the same as the species of the target molecule.
15. The method of any one of claims 1-14, wherein the two-component surface-enhanced Raman spectroscopy detection comprises detecting a first sample comprising the medium particles and at least two of the the auxiliary molecule.
16. The method of claim 15, wherein the two-component surface-enhanced Raman spectroscopy detection comprises the step of reducing the concentration of the at least two accessory molecules in the first sample at least once.
17. The method of claim 16, wherein the reduction is a reduction in the concentration of each of the helper molecules by at least 0.1 orders of magnitude each time compared to the original concentration of the helper molecules in the first sample.
17. The method of any one of claims 16-17, wherein the reduction is a reduction in the concentration of each of the helper molecules each time about 0.1 to about 1 order of magnitude.
The method of any one of claims 1-18, wherein the two-component surface-enhanced Raman spectroscopy detection comprises the step of detecting the presence of each of the auxiliary molecules in the first sample after the reduction The resulting spectral signal.
19. The method of claim 19, wherein in a single spectrum, when the spectral signal generated by the auxiliary molecule accounts for at least 85% of the spectral signal of the single spectrum, the single spectrum is the auxiliary molecule Single Molecule Spectroscopy.
20. The method of any one of claims 19-20, wherein the medium particle has a characteristic for the auxiliary molecule when the ratio of the spectral number of the single-molecule spectrum of the auxiliary molecule to the spectral number of the resulting spectral signal is at least 50% Detection sensitivity at the single-molecule level of the molecule.
21. The method of any one of claims 1-21, wherein the surface-enhanced Raman spectroscopy detection comprises detecting a second sample, the second sample comprising the mediator particles and at least one of the helper molecules.
22. The method of any one of claims 1-22, wherein the surface-enhanced Raman spectroscopy detection comprises detecting the intensity of a signal generated by the helper molecule.
24. The method of claim 23, wherein the surface-enhanced Raman spectroscopy detection comprises calculating a correlation coefficient between the signal intensities generated at arbitrary time intervals based on the signal intensities.
25. The method of claim 24, wherein the dielectric particles are stable for detection by the surface-enhanced Raman spectroscopy when the absolute value of the correlation coefficient is about 0.3 or less.
25. The method of any of claims 24-25, wherein the media particles have the stability for at least 60 minutes when the absolute value of the correlation coefficient is about 0.3 or less.
The method of any one of claims 1-26, comprising the steps of:

b) Raman detection is performed on the mixed medium particles and the sample containing the target molecule to obtain a Raman spectrum of the target molecule.
28. The method of claim 27, wherein the Raman detection comprises surface-enhanced Raman spectroscopy detection.
28. The method of any of claims 27-28, wherein the Raman detection comprises digitized surface-enhanced Raman spectroscopy detection.
The method of claim 29, comprising the steps of:

c) According to the Raman spectrum of the target molecule, obtain the corresponding abundance value of the target molecule in each Raman spectrum.
The method according to claim 30, wherein the method for detecting a target molecule comprises the step of: determining a threshold for judging the existence of the target molecule according to the abundance value of a blank sample that does not contain the target molecule.
The method according to claim 31, wherein the method for detecting a target molecule comprises the step of: obtaining the target molecule in the sample according to the number and/or frequency of the target molecule being judged to be present in the sample concentration.
The method according to any one of claims 30-32, wherein the method for detecting a target molecule comprises the step of: a mathematical mapping relationship according to the number and/or frequency of the target molecule being judged to exist in the sample Obtain the concentration of the target molecule in the sample.
The method of any one of claims 30-33, wherein the method of detecting a target molecule comprises the step of adjusting the concentration of the target molecule in a sample containing the target molecule.
34. The method of any one of claims 30-34, wherein the method of detecting a target molecule comprises the step of adjusting the binding ability of the mediator particles to the target molecule.
The method of any one of claims 30-35, wherein the method of detecting a target molecule comprises the step of adjusting the physicochemical properties of a sample containing the target molecule.
The method of any one of claims 30-36, wherein the method of detecting a target molecule comprises the step of adjusting parameters of equipment required for the Raman detection.
The method of any one of claims 30-37, wherein the method of detecting a target molecule comprises the steps of: adjusting the total number of Raman spectra in each Raman detection; and/or being detected as the The total number of said Raman spectra positive for the target molecule.
38. The method of any one of claims 30-38, wherein the method of detecting a target molecule comprises the step of adjusting the number of Raman detections.
39. The method of any one of claims 28-39, wherein the Raman detection comprises liquid phase surface enhanced Raman spectroscopy detection.
Application of the medium particle according to any one of claims 1 to 40 in detecting target molecules by liquid-phase digital surface-enhanced Raman spectroscopy.
The use of claim 41, wherein the medium particles and the target molecules are mixed in a liquid phase system.
The use of any one of claims 1-42, wherein the liquid phase digital surface-enhanced Raman spectroscopy detection quantitatively detects the concentration of the target molecule.