CN109612953B

CN109612953B - Nano-gold array sensor and detection method and application thereof

Info

Publication number: CN109612953B
Application number: CN201811523230.0A
Authority: CN
Inventors: 张卓勇; 黄丽娟
Original assignee: Beijing Yuanda Hengtong Technology Development Co ltd
Current assignee: Beijing Yuanda Hengtong Technology Development Co ltd
Priority date: 2018-12-12
Filing date: 2018-12-12
Publication date: 2022-02-18
Anticipated expiration: 2038-12-12
Also published as: CN109612953A

Abstract

The invention relates to the field of chemical sensors, in particular to a nanogold array sensor and a preparation method and application thereof. The sensor can be provided with a plurality of sensing units, so that the detection of a univalent or multivariate peptide mixed system is realized. Constructing a first sensing unit through a competitive reaction among the peptide to be detected, the nanogold and the amino acid based on a cross-linking reaction mechanism; based on a non-crosslinking reaction mechanism, metal ions can perform a complex reaction with the peptide to be detected, and negative charges on the surface of the nano-gold can be neutralized, so that a second sensing unit is constructed. The UV-Vis spectrum acquired by the sensor is used for processing spectrum data by a multidimensional partial least square method, so that the quantitative analysis of a multivariate system is realized, and the method has the advantages of high accuracy, good stability and low detection limit.

Description

Nano-gold array sensor and detection method and application thereof

Technical Field

The invention relates to the field of chemical sensors, in particular to a nanogold array sensor and a detection method and application thereof.

Background

In recent decades, with the rapid development of medical science, the detection of biomolecules in body fluids has received much attention. In biology and clinical medicine, there is an increasing need for high sensitivity, specificity, reproducibility and reproducibility of measurements of tens to hundreds of peptides and proteins in clinical and biological samples. Endogenous peptides play an important role in human homeostasis. Many endogenous peptides are in. mu. mol. L^-1The level of concentration circulating in the body fluid, the analysis of this concentration of peptides places high demands on the bioanalytical process. Currently, immunological methods and colorimetric methods are commonly used as detection methods. Chinese patent document CN105572382A discloses an indirect enzyme-linked immunoassay method for antihypertensive peptides, which utilizes the specific reaction of antigen and antibody to efficiently and rapidly detect TunaAI in the productAnd (4) content. Firstly, coupling the TunaAI polypeptide with protein to prepare immunogen, then injecting the immunogen into the rabbit body to generate antibody, purifying the antibody, establishing a standard curve of indirect enzyme-linked immunosorbent assay, and calculating the TunaAI content in the sample by using the curve. However, immunological analysis often has the defects of cross-reactivity, low sensitivity and poor selectivity.

The colorimetric sensor is one of chemical sensors, and can detect various targets by using a change in color. Compared with electrochemical sensors and surface-enhanced Raman technologies, colorimetric sensors have the advantages of simple detection method, low cost, no need of professional technicians and complicated operation procedures, high sensitivity and the like, so that the colorimetric sensors are very suitable for rapid trace detection. The most commonly used nanomaterial in colorimetric sensors is nanogold (AuNPs) which binds to the aptamer through surface adsorption and electronegative effects, thereby utilizing a single variable a₆₂₀/A₅₂₀The detection of the target object is realized. In the prior art, a colorimetric method for quickly detecting cysteine is disclosed in documents, and is successfully applied to the determination of the content of cysteine in rat brain dialysate, and the measured response value is (9.6 +/-2.1) mu mol/L. The principle is based on adjusting the pH of the system, so that the molecular carboxyl group of cysteine and aspartic acid carries negative charges and the molecular amino group carries positive charges, and the ionic electrostatic attraction effect is generated between the molecular carboxyl group negative charges and the molecular amino group positive charges to connect the nanogold into an aggregation state, thereby showing the color and the ultraviolet absorption spectrum change to achieve the purpose of detecting the cysteine. Although the method realizes the detection of cysteine in the rat brain by using a visual detection technology, the detection sensitivity of the system needs to be improved, and a multi-element system cannot be detected.

Disclosure of Invention

Therefore, the technical problem to be solved by the invention is to overcome the defects of low sensitivity, poor specificity and incapability of detecting a multi-element system in the prior art for detecting endogenous peptides, so that the nanogold array sensor which is high in sensitivity, simple to operate, low in price and capable of simultaneously detecting various peptides, and the detection method and application thereof are provided.

Therefore, the technical scheme of the invention is as follows:

a nanogold array sensor comprises a first sensing unit and/or a second sensing unit;

the first sensing unit includes, a1: nano gold solution; and B1: an amino acid solution;

the second sensing unit includes, a 2: a nucleotide-modified nanogold solution; and B2: a metal ion solution.

Further, in the first sensing unit, the amino acid solution is a series of amino acid solutions including at least 2 concentration levels, and preferably, the series of amino acid solutions includes 10 concentration levels; the molar ratio of the nano gold solution to the series of amino acid solutions is 1: 100-1000.

Further, the amino acid is at least one of arginine and cysteine; preferably, the amino acid is arginine.

Further, the particle size of the nano gold is 5-50 nm; preferably, the particle size of the nano gold is 13 nm.

Further, the nanogold is prepared by a citrate reduction method.

Further, the citrate reduction method comprises the following steps: heating the gold salt solution to boiling, adding the citrate solution while stirring, continuing to stir to change the color of the reaction solution from yellow to deep red, then continuing to stir, stopping heating, and cooling to room temperature to obtain the nano-gold solution.

Further, in the second sensing unit, the metal ion solution is a series of metal ion solutions including at least 2 concentration levels, and preferably, the series of metal ion solutions includes 10 concentration levels; the molar ratio of the nucleotide modified nano gold solution to the series of metal ion solutions is 1: 100-1000.

Further, the metal ion solution is a solution containing metal ions Cd²⁺、Co²⁺、Cr³⁺And Pb²⁺A solution of at least one of (a); preferably, the metal ion is Cr³⁺。

Further, the nucleotide sequence consists of n dNTPs, wherein n is 15-30, and the dNTPs are at least one of A, T, C or G; preferably, the nucleotide is one of a30, T30, C30, a21, T21, C21, T15 and C15, wherein a 30: 5'-AAA AAA AAA AAA AAA AAA AAA AAA AAA AAA-3', T30: 5'-TTT TTT TTT TTT TTT TTT TTT TTT TTT TTT-3', C30: 5'-CCC CCC CCC CCC CCC CCC CCC CCC CCC CCC-3', A21: 5'-AAA AAA AAA AAA AAA AAA AAA-3', T21: 5'-TTT TTT TTT TTT TTT TTT TTT-3', C21: 5'-CCC CCC CCC CCC CCC CCC CCC-3', T15: 5'-TTT TTT TTT TTT TTT-3', C15: 5'-CCC CCC CCC CCC CCC-3' are provided.

Further, the preparation method of the nucleotide modified nano-gold comprises the following steps: adding nucleotide into the nanogold solution for oscillation reaction to obtain an AuNPs-DNA compound; wherein the molar ratio of the nanogold to the nucleotide is 1: 10.

further, the detection limit of the sensor is mu mol.L^-1(ii) a Preferably, the detection limit is 1.8-1.9. mu. mol. L^-1.

The invention also provides a method for detecting peptides, which comprises the following steps:

first sensing unit data determination: adding a series of peptides to be detected with known concentration into the nanogold solution, adding an amino acid solution, performing constant volume, collecting the ultraviolet-visible absorption spectrum of a sample in the wavelength range of 230-1000nm as the original ultraviolet-visible absorption spectrum S of the peptides to be detected_samCollecting the ultraviolet and visible absorption spectrum of pure water in the wavelength range as a reference ultraviolet and visible absorption spectrum S under the same conditions by taking the pure water as a reference substance_ref；

And (3) data measurement of a second sensing unit: adding a series of volumes of peptides to be detected with known concentration into the nucleotide modified nano-gold solution, adding the metal ion solution, performing constant volume, collecting the ultraviolet visible absorption spectrum of the sample in the wavelength range of 230-1000nm as the original ultraviolet visible absorption spectrum S of the peptides to be detected_samCollecting the ultraviolet and visible absorption spectrum of pure water in the wavelength range as a reference ultraviolet and visible absorption spectrum S under the same conditions by taking the pure water as a reference substance_ref；

Establishing a multi-dimensional partial least square model: the calculation is performed according to the following formula: the method comprises the following steps that S is Ssam-Sref, two sensing units respectively obtain a spectrum matrix, the two spectrum matrices are fused into one spectrum matrix to obtain a final ultraviolet visible spectrum, the spectrum is divided into a correction set and a verification set, the correction set spectrum adopts a multi-dimensional partial least square method to establish a quantitative analysis model, and the verification set carries out external verification on the quantitative analysis model;

and (3) detection: and (3) obtaining spectral data of the peptide to be detected by adopting the sensor, and analyzing the spectral data by using the established multidimensional partial least square model to obtain a predicted value.

Further, the peptide to be detected is one or two of Gly-Gly and Ala-Gln.

The invention also provides application of the nanogold array sensor or the method for detecting the peptide in qualitative and quantitative analysis of endogenous peptide.

The technical scheme of the invention has the following advantages:

1. the invention provides a nanogold array sensor which comprises a first sensing unit and/or a second sensing unit; the first sensing unit includes, a1: nano gold solution; and B1: an amino acid solution; the second sensing unit includes, a 2: a nucleotide-modified nanogold solution; and B2: a metal ion solution; the nanogold array sensor realizes detection of a unitary or binary mixed system of endogenous peptides by arranging a plurality of sensing units. The dispersed nano-gold solution shows red, the solution gradually changes from red to blue in the coagulation process of the nano-gold, the change process from red to blue can be detected by an ultraviolet-visible spectrometer, the peptide to be detected in the first sensing unit of the invention plays a role of a stabilizer for the nano-gold solution, the amino acid can make the nano-gold coagulated by utilizing the cross-linking reaction principle, and the coagulation degree of the nano-gold is influenced by the competitive reaction among the peptide to be detected, the nano-gold and the amino acid, so that the first sensing unit is constructed. In the second sensing unit, due to electrostatic repulsion among nucleic acids, the nucleotide modified nano-gold is not aggregated in an aqueous medium, after metal ions are added, part of the metal ions and the peptide to be detected are subjected to a complex reaction, and the other part of the metal ions neutralize negative charges on the surface of the nano-gold, so that the nano-gold is induced to aggregate. When the concentration of the added metal ions is constant, the aggregation degree of the nanogold has a certain relation with the concentration of the endogenous peptide, so that the second sensing unit is constructed.

2. The method for detecting the peptide by the sensor has the advantages of high sensitivity, good selectivity, convenience and practicability. The traditional method uses a univariate analysis method, and the property and the concentration of the object to be detected can be aligned to the characteristic peak A of the nano-gold₆₂₀And A₅₂₀The influence is generated, the stability is poor, and the sensitivity is low. As is well known, the sensitivity and detection capability of the sensor are closely related to the number of sensing elements, and the more the number of sensing elements, the more data volume needs to be processed, and the invention utilizes UV-Vis spectrum to replace A₆₂₀/A₅₂₀The ratio of the values is processed by a multidimensional partial least square method, so that the quantitative analysis of a multivariate system is realized, and the accuracy and the sensitivity of the analysis are improved.

Drawings

FIG. 1 is a method for fusing spectral data of two sensing units;

FIG. 2 UV-Vis spectra after fusion of ten horizontal data of example 1;

FIG. 3 shows the regression results of N-PLS based on Gly-Gly of N-PLS in example 1;

FIG. 4 example 7 regression results of N-PLS of Gly-Gly in saliva based on N-PLS model;

FIG. 5 shows the regression of Gly-Gly N-PLS based on PLS model.

Detailed Description

The following examples refer to:

the principle of the multidimensional partial least square linear discriminant analysis method is as follows:

multidimensional partial least squares (N-PLS) is a three-dimensional matrix correction algorithm proposed by Bro et al based on trilinear decomposition and classical PLS. The principle of the N-PLS algorithm is to decompose a three-dimensional solid array X (I multiplied by J multiplied by K) into a trilinear model:

wherein t is a score vector of the spectrum matrix,

and

is two load vectors corresponding to the F-th main factor pair of the spectrum matrix X containing n spectra (samples), wherein F is the number of the main factors, and eijk is a residual error matrix. Like the conventional PLS, the N-PLS decomposes the spectral array and decomposes the concentration array y (I X1), and combines the two decomposition processes of X and y into one through iteration. The specific algorithm of the N-PLS consists of two parts, correction and prediction.

The correction part: x (I multiplied by J multiplied by K) is a calibration set spectrum array, I is the number of calibration set samples, J is the number of wavelength points, and K is the condition of spectrum measurement.

(1) Unfolding X into a two-dimensional matrix X0(I × JK), and determining the number of major factors F, F ═ 1, …, F;

(2) calculating the Z matrix

(3) Singular value decomposition of the Z matrix, [ w ]^K，s，w^J]＝svd(Z_f)

(4) Computing

Kronecker product (Kroneckerproduct) which is a matrix;

(5) calculating t_f＝X_f-1w_f；

(6) Computing

(7) Calculating u_f＝y_f-1q_i；

(8) Computing

Wherein T f ═ t1, …, tf]；

(9) Updating X and y, X_f＝X_f-1-t_fw_f，

(10) F +1, return to (3), and sequentially obtain X, y F scores and loads.

And a prediction part: for an unknown sample spectrum array X^un(1 × J × K), the prediction result is calculated by the following steps:

(1) expand Xun into a two-dimensional matrix Xun (1 XJK), call saved w_f，b_fAnd q is_f；

(2) Computing

(3) Computing

Wherein T is_f＝[t₁，…，t_f]

Self-help Latin partitioning (Bootstrap partitioning) principle:

the self-help Latin distribution is a model verification method established on the basis of cross verification and random sampling verification and is used for evaluating the prediction capability and stability of a classification model. In fact, it is a statistical analysis method used to verify the performance of the model. The self-help latin distribution steps are as follows:

(1) by selecting a proper distribution number n, the samples are randomly, evenly or approximately evenly divided into n groups, and the number ratio of various types of samples contained in each group is ensured to be consistent in the random distribution process.

(2) Performing internal cross validation on the model, selecting one group of samples as a prediction set each time, using the rest (n-1) groups of samples as a correction set, performing cross validation for n times of cycles, finally enabling each sample to be used for only one prediction, recording a predicted value and a corresponding real value of each prediction set sample, and calculating a corresponding prediction Root Mean Square Error (SERMCV) of 1-time Latin distribution according to the following formula according to the predicted value and the real value of the sample;

where N is the number of samples, y_i' is the model prediction value of sample i, y_iIs the actual value of sample i.

(3) In the nboot self-help process, all samples are randomly grouped and arranged once again every self-help.

(4) And after the self-help of the n boot times, evaluating the classification capability of the built model by adopting the average RMSEP of the prediction set samples after the n boot times. The calculation formula is as follows:

the method can obtain a generalized and average prediction error, and is characterized in that some changes are generated when the training set and the prediction set spectrum are selected in the modeling process. Therefore, the method has statistical significance in evaluating and comparing the influence of different data processing methods on the classification accuracy of the model.

IUPAC defined limit of detection (LOD) principle:

the limit of detection (LOD) according to the IUPAC regulations is calculated as follows:

LOD＝35

in the above two formulae, x_iAnd

are respectively biased to minimumThe concentration values predicted by the model and the average value of the samples were multiplied by two.

The preparation method of the nano gold comprises the following steps: 250mL of a 1mM chloroauric acid solution was added to a three-necked flask, heated to boiling in a magnetic stirrer, and refluxed for about 5 minutes. One of the stoppers was removed and 25 ml of 38.8mM sodium citrate solution was quickly added to the solution and the stopper was closed. At this point the color of the solution changed rapidly from initially pale yellow to colorless to black and finally to wine-red. And continuously heating and refluxing for about 15min, stopping heating, and stirring until the solution returns to the room temperature. The condensed solution was passed through a filter membrane of 0.45 μm in size. The concentration of the obtained nano gold solution is 10nM, and the particle size is 13 nM.

The preparation method of the nucleotide modified nano-gold comprises the following steps: and (3) taking 100 mu L of 10nM nano gold particles, adding 10 mu L of 1.0 mu M C15 (5'-CCC CCC CCC CCC CCC-3') into the nano gold particles, and carrying out shake reaction to obtain the AuNPs-DNA compound. The nucleotides used in the examples and comparative examples were synthesized by bioengineering GmbH.

Example 1

The embodiment provides a nanogold array sensor which comprises a first sensing unit and a second sensing unit;

the first sensing unit includes, a1: nano gold solution with concentration of 10 nM;

b1: arginine (Arg) solution comprising 10 concentration levels of a series of amino acid solutions having concentrations of 1/6 μ M, 2/6 μ M, 3/6 μ M, 4/6 μ M, 5/6 μ M, 6/6 μ M, 7/6 μ M, 8/6 μ M, 9/6 μ M, 10/6 μ M in this order;

the second sensing unit includes, a 2: the concentration of the nucleotide modified nanogold (AuNPs-DNA) solution is 10 nM;

B2：CrCl₃solution comprising a series of CrCl at 10 concentration levels₃The concentration of the solution is 1/6 μ M, 2/6 μ M, 3/6 μ M, 4/6 μ M, 5/6 μ M, 6/6 μ M, 7/6 μ M, 8/6 μ M, 9/6 μ M and 10/6 μ M in sequence.

The present embodiment also provides a method for detecting peptides using the above array sensor, comprising the steps of:

preparation of a first sensing unit and data measurement: the final concentrations of Gly-Gly and Ala-Gln in the binary mixed system (Gly-Gly/Ala-Gln) are shown in Table 1, wherein different volumes of solutions of dipeptides to be detected, namely 1mM Gly-Gly and 1mM Ala-Gln, are respectively added into 100 mu L and 10nM AuNPs solution, 10 mu L, 20 mu L, 30 mu L, 40 mu L, 50 mu L, 60 mu L, 70 mu L, 80 mu L, 90 mu L and 100 mu L of Arg solution with the concentration of 10 mu M are respectively added into the solution, and the total volume is 600 mu L by using ultrapure water.

Standing for 30min, collecting the ultraviolet visible absorption spectrum of the mixed solution in the wavelength range of 230-1000nm, wherein the step length is 1nm, and using the ultraviolet visible absorption spectrum as the original ultraviolet visible absorption spectrum Ssam of the dipeptides Gly-Gly and Ala-Gln to be detected; pure water is taken as a reference substance, and under the same condition, the ultraviolet visible absorption spectrum of the pure water in the wavelength range of 230-1000nm is collected, the step length is 1nm, and the ultraviolet visible absorption spectrum is taken as the reference ultraviolet visible absorption spectrum Sref.

Preparation and data measurement of a second sensing unit: adding solutions of dipeptides to be detected, 1mM Gly-Gly and 1mM Ala-Gln, in different volumes, into AuNPs-DNA (C15) solution of 100 μ L and 10nM, respectively, and adding CrCl of 10 μ M concentration, 10 μ L, 20 μ L, 30 μ L, 40 μ L, 50 μ L, 60 μ L, 70 μ L, 80 μ L, 90 μ L and 100 μ L into the solution₃The solution was made to a total volume of 600. mu.L with ultra pure water, and the final concentrations of Gly-Gly and Ala-Gln in the binary mixed system (Gly-Gly/Ala-Gln) are shown in Table 1.

Establishing a multi-dimensional partial least square model: the calculation is performed according to the following formula: the two sensing units respectively obtain a spectrum matrix, the two spectrum matrices are fused into one spectrum matrix, the data fusion mode is shown in figure 1, the obtained final ultraviolet and visible spectrum is shown in figure 2, the spectrum is divided into a correction set and a verification set through self-help latin distribution, the number of samples in the correction set is 600, and the number of samples in the verification set is 150; and 5-fold cross validation is carried out by utilizing the ultraviolet-visible spectrum of the correction set sample to determine that the latent variable numbers of Gly-Gly and Ala-Gln are respectively 9 and 8, the correction set spectrum adopts a multidimensional partial least square method to establish a quantitative analysis model, and the validation set carries out external validation on the quantitative analysis model.

The N-PLS regression results for Gly-Gly and Ala-Gln are shown in FIG. 3, and it can be seen that the predicted concentrations of Gly-Gly and Ala-Gln are highly correlated with the concentrations predicted by the N-PLS model, and all sample points are reasonably distributed on both sides of the diagonal. The N-PLS model provides good prediction results for two ions in a binary mixture system of Gly-Gly and Ala-Gln. When Arg and Cr are substituted³⁺Performing data fusion on a UV-Vis spectrum matrix obtained by taking ten levels of the two factors of concentration into consideration, and then establishing an N-PLS model for the fused data matrix to obtain a lower cross validation root mean square error and a higher correlation coefficient, wherein the evaluation cross validation root mean square error RMSECV of the N-PLS model for quantitatively analyzing Gly-Gly is 0.19 +/-0.14%, and R is 0.9969; quantitative analysis of Ala-Gln evaluation of the N-PLS model cross-validated root mean square error RMSECV 1.15 ± 0.07%, R0.9989.

To further evaluate the performance of the model, six spectra were obtained by measuring Gly-Gly and Ala-Gln under the same conditions in a binary mixed system at concentrations of 50.00. mu.M. These six spectra were predicted using the N-PLS model described above, and the detection limits were calculated using the results of the prediction according to the IUPAC defined detection Limit (LOD) principle. The detection limits of the established N-PLS model Gly-Gly/Ala-Gln are 1.89 mu M and 1.86 mu M respectively. The standard deviation (STD) of Gly-Gly and Ala-Gln was 0.96 and 0.83, respectively. These results further indicate that the method of this example has good prediction ability and reproducibility for detecting a Gly-Gly/Ala-Gln binary mixed system within a certain concentration range.

TABLE 1 concentration of the components in the binary Mixed System (Gly-Gly/Ala-Gln)

Example 2

The embodiment provides a nanogold array sensor, which comprises a first sensing unit and a second sensing unit,

b1: cysteine solution comprising 10 concentration levels of amino acid series solution, the concentration is 1/6 μ M, 2/6 μ M, 3/6 μ M, 4/6 μ M, 5/6 μ M, 6/6 μ M, 7/6 μ M, 8/6 μ M, 9/6 μ M, 10/6 μ M in sequence;

the second sensing unit includes, a 2: a nucleotide-modified nanogold (AuNPs-DNA (T15)) solution with the concentration of 10 nM;

B2：CdCl₂solution, comprising a series of CdCl at 10 concentration levels₂The concentration of the solution is 1/6 μ M, 2/6 μ M, 3/6 μ M, 4/6 μ M, 5/6 μ M, 6/6 μ M, 7/6 μ M, 8/6 μ M, 9/6 μ M and 10/6 μ M in sequence.

preparation of a first sensing unit and data measurement: the final concentrations of Gly-Gly and Ala-Gln in the binary mixed system (Gly-Gly/Ala-Gln) are shown in Table 1, wherein different volumes of solutions of dipeptides to be detected, namely 1mM Gly-Gly and 1mM Ala-Gln, are respectively added into 100 muL and 10nM AuNPs solution, 10 muL, 20 muL, 30 muL, 40 muL, 50 muL, 60 muL, 70 muL, 80 muL, 90 muL and 100 muL of cysteine solution with the concentration of 10 muM are respectively added into the solution, and the final concentrations of Gly-Gly and Ala-Gln in the binary mixed system (Gly-Gly/Ala-Gln) are determined to be 600 muL by using ultrapure water.

Preparation and data measurement of a second sensing unit: respectively taking the solution of dipeptide 1mM Gly-Gly and dipeptide 1mM ala-Gln to be detected with different volumesThe solution was added to 100. mu.L of 10nM AuNPs-DNA (T15), and 10. mu.L, 20. mu.L, 30. mu.L, 40. mu.L, 50. mu.L, 60. mu.L, 70. mu.L, 80. mu.L, 90. mu.L, 100. mu.L of CdCl with a concentration of 10. mu.M were added to the solution₂The solution was made to a total volume of 600. mu.L with ultra pure water, and the final concentrations of Gly-Gly and Ala-Gln in the binary mixed system (Gly-Gly/Ala-Gln) are shown in Table 1.

and collecting spectral data of the peptide to be detected in the sensor, and analyzing the spectral data through the established multidimensional partial least square model to obtain a predicted value.

Example 3

the first sensing unit includes, a1: a nanogold solution with the concentration of 10nM (nM is nmol/L);

b1: arg solution, comprising a series of amino acid solutions at 1 concentration level, at a concentration of 1. mu.M (. mu.M in mol/L);

the second sensing unit includes, a 2: a nucleotide-modified nanogold (AuNPs-DNA (C30)) solution with the concentration of 10 nM;

B2：CrCl₃solution, comprising a series of CrCl at 1 concentration level₃Solution, concentration 5/6. mu.M.

preparation and data detection of the first sensing unit: adding 1mM Gly-Gly solution of the peptide to be detected with different volumes into 100 μ L10 nM AuNPs solution, adding 60 μ L Arg solution with concentration of 10 μ M into the solution, and adding ultrapure water to the solution until the total volume is 600 μ L, wherein the final concentrations of Gly-Gly are 14, 30, 50, 64 and 80 μ M respectively.

Standing for 30min, collecting the ultraviolet visible absorption spectrum of the mixed solution in the wavelength range of 230-1000nm, wherein the step length is 1nm, and using the ultraviolet visible absorption spectrum as the original ultraviolet visible absorption spectrum Ssam of the peptide Gly-Gly to be detected; pure water is taken as a reference substance, and under the same condition, the ultraviolet visible absorption spectrum of the pure water in the wavelength range of 230-1000nm is collected, the step length is 1nm, and the ultraviolet visible absorption spectrum is taken as the reference ultraviolet visible absorption spectrum Sref.

Preparation and data detection of a second sensing unit: adding different volumes of 1mM Gly-Gly solution of the peptide to be detected into 100 μ L10 nM AuNPs-DNA (C30) solution, respectively, and adding 50 μ L CrCl with concentration of 10 μ M into the solution₃The solution was made up to a total volume of 600. mu.L with ultra pure water, and the final concentrations of Gly-Gly were 14, 30, 50, 64, and 80. mu.M, respectively.

Example 4

b1: arg solution, comprising a series of amino acid solutions at 1 concentration level, 4/6. mu.M (. mu.M in mol/L);

the second sensing unit includes, a 2: a nucleotide-modified nanogold (AuNPs-DNA (C15)) solution with the concentration of 10 nM;

preparation and data detection of the first sensing unit: taking 1mMAla-Gln solution of the peptide to be detected with different volumes, respectively adding the solution into 100 mu L of 10nM AuNPs solution, respectively adding 40 mu L of 10 mu M Arg solution into the solution, and using ultrapure water to fix the volume to 600 mu L of the total volume, wherein the final concentration of Ala-Gln is respectively 18, 40, 54, 66 and 92 mu M.

Standing for 30min, collecting the ultraviolet visible absorption spectrum of the mixed solution in the wavelength range of 230-1000nm, wherein the step length is 1nm, and using the ultraviolet visible absorption spectrum as the original ultraviolet visible absorption spectrum Ssam of the peptide Ala-Gln to be detected; pure water is taken as a reference substance, and under the same condition, the ultraviolet visible absorption spectrum of the pure water in the wavelength range of 230-1000nm is collected, the step length is 1nm, and the ultraviolet visible absorption spectrum is taken as the reference ultraviolet visible absorption spectrum Sref.

Preparation and data detection of a second sensing unit: respectively adding solutions of 1mMAla-Gln of the peptide to be detected with different volumes into 100 muL of 10nM AuNPs-DNA (C15) solution, and respectively adding 50 muL of CrCl with the concentration of 10 muM into the solution₃The solution was made to a total volume of 600. mu.L with ultra pure water to give Ala-Gln final concentrations of 18, 40,54、66、92μM。

Example 5

The embodiment provides a nanogold array sensor, which comprises a first sensing unit,

the first sensing unit includes: a1, nano-gold solution with the concentration of 10 nM;

b1, arginine solution, including 10 concentration levels of amino acid solution series, the concentration is 1/6 μ M, 2/6 μ M, 3/6 μ M, 4/6 μ M, 5/6 μ M, 6/6 μ M, 7/6 μ M, 8/6 μ M, 9/6 μ M, 10/6 μ M sequentially;

preparation of a first sensing unit and data measurement: adding 1mM Gly-Gly solution of the peptide to be detected into 100 μ L AuNPs solution with the concentration of 10nM, adding 10 μ L, 20 μ L, 30 μ L, 40 μ L, 50 μ L, 60 μ L, 70 μ L, 80 μ L, 90 μ L and 100 μ L arginine solution with the concentration of 10 μ M into the solution, and diluting with ultrapure water to the total volume of 600 μ L, wherein the final concentration of Gly-Gly is 14, 30, 50, 64 and 80 μ M. Each concentration of Gly-Gly includes ten arginine concentration gradients, for example, there are ten samples with Gly-Gly concentration of 80. mu.M, and the arginine concentrations in the ten samples are 1/6. mu.M, 2/6. mu.M, 3/6. mu.M, 4/6. mu.M, 5/6. mu.M, 6/6. mu.M, 7/6. mu.M, 8/6. mu.M, 9/6. mu.M, 10/6. mu.M, respectively.

Establishing a multi-dimensional partial least square model: the calculation is performed according to the following formula: the spectrum is divided into a correction set and a verification set according to the ultraviolet-visible spectrum obtained by the sensing unit, the correction set spectrum adopts a multidimensional partial least square method to establish a quantitative analysis model, and the verification set carries out external verification on the quantitative analysis model;

Example 6

The embodiment provides a nanogold array sensor, which comprises a second sensing unit,

the second sensing unit includes: a2, nucleotide modified nanogold (AuNPs-DNA (T15)) solution with the concentration of 10 nM;

B2、CrCl₃solution comprising a series of CrCl at 10 concentration levels₃The concentration of the solution is 1/6 μ M, 2/6 μ M, 3/6 μ M, 4/6 μ M, 5/6 μ M, 6/6 μ M, 7/6 μ M, 8/6 μ M, 9/6 μ M and 10/6 μ M in sequence.

preparation and data measurement of a second sensing unit: adding solutions of 1mM ALA-Gln of the peptide to be detected into 100 μ L of 10nM AuNPs-DNA (C15) solution, respectively, and adding 10 μ L, 20 μ L, 30 μ L, 40 μ L, 50 μ L, 60 μ L, 70 μ L into the solutionL, 80. mu.L, 90. mu.L, 100. mu.L CrCl at a concentration of 10. mu.M₃The solution was brought to a total volume of 600. mu.L with ultra pure water to final concentrations of Ala-Gln of 18, 40, 54, 66, 92. mu.M. Ala-Gln includes ten CrCl per concentration₃Samples with a concentration gradient, e.g., ten samples with 92. mu.M Ala-Gln concentration, CrCl in ten samples₃The concentrations of (A) were 1/6. mu.M, 2/6. mu.M, 3/6. mu.M, 4/6. mu.M, 5/6. mu.M, 6/6. mu.M, 7/6. mu.M, 8/6. mu.M, 9/6. mu.M, and 10/6. mu.M, respectively.

Example 7

Based on the nanogold array sensor in example 1, quantitative Gly-Gly and Ala-Gln are added into saliva to be used as samples to be tested, and a binary system (Gly-Gly/Ala-Gln) in the saliva sample is quantitatively analyzed. The results of the N-PLS regression of Gly-Gly in saliva samples and Ala-Gln in saliva samples are shown in FIG. 4. Although there are more interference factors in the saliva sample, the real concentration of Gly-Gly and Ala-Gln is highly consistent with the result predicted by N-PLS model based on nano-gold array sensor.

Comparative example 1

The preparation method of the nanogold and the nucleotide modified nanogold is the same as that of the embodiment 1;

the final concentrations of Gly-Gly and Ala-Gln in the binary mixed system (Gly-Gly/Ala-Gln) are shown in Table 1, wherein different volumes of solutions of dipeptides to be detected, namely 1mM Gly-Gly and 1mM Ala-Gln, are respectively added into 100 mu L and 10nM AuNPs solution, 10 mu L, 20 mu L, 30 mu L, 40 mu L, 50 mu L, 60 mu L, 70 mu L, 80 mu L, 90 mu L and 100 mu L of Arg solution with the concentration of 10 mu M are respectively added into the solution, and the total volume is 600 mu L by using ultrapure water.

Adding solutions of dipeptides to be detected, 1mM Gly-Gly and 1mM Ala-Gln, in different volumes, into AuNPs-DNA (C15) solution of 100 μ L and 10nM, respectively, and adding CrCl of 10 μ M concentration, 10 μ L, 20 μ L, 30 μ L, 40 μ L, 50 μ L, 60 μ L, 70 μ L, 80 μ L, 90 μ L and 100 μ L into the solution₃The solution was made to a total volume of 600. mu.L with ultra pure water, and the final concentrations of Gly-Gly and Ala-Gln in the binary mixed system (Gly-Gly/Ala-Gln) are shown in Table 1.

The calculation is performed according to the following formula: and (3) establishing a quantitative analysis model by using Partial Least Squares (PLS) on the spectral data of Arg and Cr3+ with different concentrations, wherein relevant parameters of the corresponding model are shown in a table 2.

As shown in Table 2, Gly-Gly and Ala-Gln, different Arg and Cr, were detected in a binary mixture (Gly-Gly/Ala-Gln)³⁺Concentration versus PLS model results. To pairIn the quantitative analysis of Gly-Gly when V_Arg＝60μL，V_Cr ³⁺R reaches a maximum and RMSECV reaches a minimum at 50 μ L. For quantitative analysis of Gly-Gly, when V_Arg＝40μL，V_Cr ³⁺R reaches a maximum and RMSECV reaches a minimum at 100 μ L. Thus, V will be_Arg＝60μL，V_Cr ³⁺Applied to quantitation of Gly-Gly (fig. 5a) 50 μ L, R for this model reached 0.8798 with RMSECV of 11.17 ± 0.16 μ M. Will V_Arg＝40μL，V_Cr ³⁺Applied to quantitation of Ala-Gln (fig. 5b) at 100 μ L, R for this model reached 0.9742 with an RMSECV of 5.60 ± 0.18 μ M. The PLS quantitative analysis model established under the most condition has low R and high RMSECV of the two components, and the method does not meet the requirement of accurate quantitative analysis. And a condition cannot be found such that the quantitative analysis models of both components are optimized at the same time.

Table 2 is based on different Arg and Cr³⁺Parameters of PLS model of concentration binary mixed system

It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.

Claims

1. A nanogold array sensor is characterized by comprising a first sensing unit and a second sensing unit;

the first sensing unit comprises A1 nano gold solution; and B1 amino acid solution;

the second sensing unit includes, a 2: a nucleotide-modified nanogold solution; and B2: a metal ion solution;

the amino acid is at least one of arginine and cysteine;

the nucleotide is one of A30, T30, C30, A21, T21, C21, T15 and C15, wherein A30: 5'-AAA AAA AAAAAAAAAAAAAAAAAAAAA AAA-3', T30: 5'-TTT TTT TTTTTTTTTTTTTTTTTTTTT TTT-3', C30: 5'-CCC CCC CCCCCCCCCCCCCCCCCCCCC CCC-3', A21: 5'-AAA AAA AAAAAAAAAAAAAAA-3', T21: 5'-TTT TTT TTTTTTTTTTTTTTT-3', C21: 5'-CCC CCC CCCCCCCCCCCCCCC-3', T15: 5'-TTT TTT TTTTTTTTT-3', C15: 5'-CCC CCC CCCCCCCCC-3', respectively;

the metal ion solution contains the following metal ions Cd²⁺、Co²⁺、Cr³⁺And Pb²⁺A solution of at least one of (a).

2. The array sensor of claim 1, wherein in the first sensing unit, the amino acid solution is a series of amino acid solutions comprising at least 2 concentration levels.

3. The array sensor of claim 2, wherein the amino acid solution is the series of amino acid solutions at 10 concentration levels; the molar ratio of the nano gold solution to the series of amino acid solutions is 1: 100-1000.

4. The array sensor of claim 1, wherein the amino acid is arginine.

5. The array sensor according to claim 1 or 2, wherein the nano gold has a particle size of 5-50 nm.

6. The array sensor as claimed in claim 5, wherein the nano gold has a particle size of 13 nm.

7. The array sensor of claim 1, wherein in the second sensing cell, the metal ion solution is a series of metal ion solutions comprising at least 2 concentration levels.

8. The array sensor of claim 1, wherein the metal ion solution is a series of metal ion solutions at 10 concentration levels; the molar ratio of the nucleotide modified nano-gold solution to the series of metal ion solutions is 1: 100-1000.

9. The array sensor of claim 1, wherein the metal ion is Cr³⁺。

10. The array sensor of claim 1, 2 or 4, wherein the sensor has a detection limit of μmol-L^-1。

11. The array sensor of claim 10, wherein the detection limit is 1.8-1.9 μmol-L^-1。

12. A method for detecting a peptide using the array sensor of any one of claims 1 to 11, comprising the steps of:

first sensing unit data determination: adding peptides to be detected with known concentration in series of volumes into a nanogold solution, adding an amino acid solution, fixing the volume, collecting an ultraviolet visible absorption spectrum of a sample in a wavelength range of 230-1000nm as an original ultraviolet visible absorption spectrum Ssam of the peptides to be detected, taking pure water as a reference substance, and collecting the ultraviolet visible absorption spectrum of the pure water in the wavelength range as a reference ultraviolet visible absorption spectrum Sref under the same condition;

and (3) data measurement of a second sensing unit: adding peptides to be detected with known concentration in series of volumes into a nucleotide modified nanogold solution, adding a metal ion solution, fixing the volume, collecting an ultraviolet visible absorption spectrum of a sample in a wavelength range of 230-1000nm as an original ultraviolet visible absorption spectrum Ssam of the peptides to be detected, and collecting an ultraviolet visible absorption spectrum of pure water in the wavelength range as a reference ultraviolet visible absorption spectrum Sref under the same condition by taking the pure water as a reference substance;

establishing a multi-dimensional partial least square model: the calculation is performed according to the following formula: s = S_sam-S_refThe two sensing units respectively obtain a spectrum matrix, the two spectrum matrices are fused into one spectrum matrix to obtain a final ultraviolet-visible spectrum, the spectrum is divided into a correction set and a verification set, the spectrum of the correction set adopts a multi-dimensional partial least square method to establish a quantitative analysis model, and the verification set carries out external verification on the quantitative analysis model;

and (3) detection: and collecting spectral data of the peptide to be detected in the sensor, and analyzing the spectral data through the established multidimensional partial least square model to obtain a predicted value.

13. The method of claim 12, wherein the test peptide is one or both of Gly-Gly and Ala-Gln.

14. Use of an array sensor according to any of claims 1-11 or a method of detecting a peptide according to any of claims 12-13 for qualitative and quantitative analysis of endogenous peptides.