阅读说明：本技术 一种环境胁迫下植物中酶活性的原位可视化测定方法 (In-situ visual determination method for enzymatic activity in plant under environmental stress ) 是由 冯宇希 莫测辉 陈昕 冯乃宪 李彦文 蔡全英 于 2020-03-25 设计创作，主要内容包括：本发明公开了一种环境胁迫下植物中酶活性的原位可视化测定方法,包括植物预处理；酶谱成像；标曲制作；图像处理。本发明提供了一种污染物胁迫下植物中酶活性的原位可视化测定方法,弥补了现有技术中植物叶片酶谱的技术空白。同时,本发明通过提供一系列的图像处理手段,重建叶片酶谱高质量图像从而提高其定性准确性的有用信息,具有较大的应用前景。(The invention discloses an in-situ visual determination method of enzyme activity in plants under environmental stress, which comprises the steps of plant pretreatment; performing zymogram imaging; making a standard yeast; and (5) processing the image. The invention provides an in-situ visual determination method for enzyme activity in plants under the stress of pollutants, which fills up the technical blank of plant leaf zymogram in the prior art. Meanwhile, the invention reconstructs high-quality images of the leaf zymogram by providing a series of image processing means, thereby improving the useful information of qualitative accuracy and having wider application prospect.)

1. An in-situ visual determination method for enzyme activity in plants under environmental stress is characterized by comprising the following steps:

s1, preprocessing a plant under environmental stress;

s2, preparing enzyme activity fluorescence labeling substrate solution, soaking a polyamide membrane in the enzyme activity fluorescence labeling substrate solution, taking out the membrane after the membrane is uniformly saturated by the substrate solution, closely attaching the membrane to the surface of the plant leaf pretreated by S1 after air drying, fixing, applying pressure to two sides of the leaf, and reacting in a dark room; after the reaction is finished, stripping the polyamide membrane from the surface of the blade, and shooting the polyamide membrane under an ultraviolet lamp with the excitation wavelength of 355nm and the emission wavelength of 460nm to obtain a blade zymogram image;

s3, preparing standard fluorescent product solutions with series concentrations, taking a buffer solution without the fluorescent product as a blank control, and soaking the polyamide membrane in the buffer solution; dripping the standard fluorescent product solution with the series of concentrations onto an air-dried polyamide membrane, and shooting by using the same shooting conditions as the S2 zymogram imaging to obtain a standard curve image;

s4, converting the standard curve image obtained in the step S3 and the original image into an 8-bit gray scale image according to sigma_GDenoising by a Gaussian filter kernel of 0.5, carrying out image segmentation on all the denoised gradient concentration standard fluorescence grayscale images by taking a grayscale value of 98 as a global threshold and calculating a grayscale mean value,finally obtaining a gradient concentration standard fluorescence mean value with background subtracted, and then fitting a piecewise correction curve according to the standard fluorescence products with different concentrations and the change of the image gray level thereof:

whereinIs the concentration of fluorogenic substrate applied to the membrane; a is₁，a₂，b₁，b₂Is a parameter of a linear regression fit; g is the gray value at the breaking point;is the average gray value of the segmented image; the first part of the segmented correction curve is used for converting the pixel gray value in the enzyme spectrum into enzyme activity, endowing the gray value in the correction curve with RGB colors in proportional relation, and the obtained RGB color bars are used for creating a lookup table LUT (look-up table) and generating a pseudo-color leaf enzyme spectrogram; the zymogram image of the leaf obtained in S2 is converted into an 8-bit gray scale image according to sigma_GNoise reduction is carried out on the Gaussian filter kernel of 0.5, the gray level mean value in the range of 5 × 5 at the four corners of each image is recorded and is used as the background gray level of the image, the final gray level image is obtained by deducting the gray level mean value from the whole image, and then the LUT is applied to the blade image, so that the spatial distribution of the activity of the blade enzyme is visualized.

2. The method of claim 1, further comprising using the area of the blade zymogram where the gray scale value exceeds 75% of the first part of the calibration curve as a hot zone, and studying the change of the spatial distribution of the area with higher enzyme activity under the environmental stress by calculating the change of the area of the hot zone in the blade zymogram, wherein the change is used for representing the distribution trend of the enzyme activity from the base to the tip of the blade.

3. The method of claim 1, wherein the environmental stress is a pollutant stress.

4. The method of claim 3, wherein the contaminant is a phthalate.

5. The method of claim 3, wherein the contaminant is dibutyl phthalate.

6. The method of claim 1, wherein the enzyme is at least one of β -glucosidase, acid phosphatase, or xylanase.

7. The method of claim 1 or 6, wherein the enzymatically active fluorescently labeled substrate is at least one of 4-methylumbelliferone- β -D-glucoside, 4-methylumbelliferone- β -D-phosphate, or 4-methylumbelliferone- β -D-xyloside.

8. Use of the method of any one of claims 1 to 7 for phytotoxicity evaluation and physiological response detection under pollutant stress.

Technical Field

The invention relates to the technical field of visual phytotoxicity evaluation, in particular to a characterization technology for spatial distribution of enzyme activity related to metabolism of plant leaves C, P under the stress of in-situ visual pollutants, and more particularly relates to an in-situ visual characterization method for spatial distribution of glucosidase, xylanase and acid phosphatase activity in leaves under the stress of phthalate.

Background

Phthalic Acid Esters (PAEs) are important artificially synthesized organic compounds, are widely applied to plastic plasticizers (commonly called plasticizers) and industries of automobiles, clothing, cosmetics, lubricants, pesticides and the like, enter the environment in large quantities, have semi-volatility and long-distance migration, and become global environmental pollutants. PAEs have carcinogenic, teratogenic, mutagenic and other toxicities, are most concerned about the abnormal reproductive function of human body, are typical endocrine disruptors, and are called as "second global PCB pollutants". At present, a plurality of countries including China and environmental protection organizations list the PAEs into priority for controlling pollutants, and take corresponding measures to prevent the PAEs from harming human health.

To date, plant enzyme activity has been widely used as a biological index for evaluating environmental stresses such as heavy metals and organic pollutants. For example, several antioxidant enzymes, superoxide dismutase (SOD), Catalase (CAT), Peroxidase (POD), etc., are used to evaluate the generation of Reactive Oxygen Species (ROS) under stress conditions, including salinity, radiation, low temperature, organic pollutants, heavy metals, etc. Like Sucrose Phosphate Synthase (SPS), Invertase (INV) and Sucrose Synthase (SS), ROS are commonly used to assess the effect of environmental conditions on plant carbon metabolism. Enzyme activity responds unevenly to contaminants and enzyme selection varies from study to study. However, previous studies were only performed at the biochemical level; it is rarely involved in environmental samples, particularly in plants. In fact, the determination of enzymatic activity has been known for over 60 years, and the methods commonly used are spectrophotometry, fluorescence, titration and radioisotope methods, and most of the studies using fluorescence imaging methods are qualitative, and no visualization of the response of enzymatic activity in plants to stress conditions has been reported so far.

Zymograms are used to reveal enzymatic activity by substrate conversion (essentially enzyme imaging). The use of fluorescence imaging to measure enzyme activity is a powerful method because it has a large amount of fine-scale information on the sensitivity, relative ease of image acquisition, and spatial heterogeneity of enzyme activity in environmental samples obtained. Current research on zymograms has focused primarily on soil zymogram technology, which can be used for hydrolases or oxidases acting on any biological substrate, including proteins and polypeptides, oligosaccharides and polysaccharides, lipids and sugars. However, studies on leaf zymograms have not been reported so far.

Disclosure of Invention

The invention aims to overcome the defects in the prior art and provide an in-situ visual determination method for the enzyme activity in plants under the stress of pollutants.

The second purpose of the invention is to provide the application of the in-situ visual determination method.

The above object of the present invention is achieved by the following technical solutions:

an in-situ visual determination method for enzyme activity in plants under environmental stress comprises the following steps:

s1, preprocessing a plant under environmental stress;

s2, preparing enzyme activity fluorescence labeling substrate solution, soaking a polyamide membrane in the enzyme activity fluorescence labeling substrate solution, taking out the membrane after the membrane is uniformly saturated by the substrate solution, closely attaching the membrane to the surface of the plant leaf pretreated by S1 after air drying, fixing, applying pressure to two sides of the leaf, and reacting in a dark room; after the reaction is finished, stripping the polyamide membrane from the surface of the blade, and shooting the polyamide membrane under an ultraviolet lamp with the excitation wavelength of 355nm and the emission wavelength of 460nm to obtain a blade zymogram image;

s3, preparing standard fluorescent product solutions with series concentrations, taking a buffer solution without the fluorescent product as a blank control, and soaking the polyamide membrane in the buffer solution; dripping the standard fluorescent product solution with the series of concentrations onto an air-dried polyamide membrane, and shooting by using the same shooting conditions as the S2 zymogram imaging to obtain a standard curve image;

s4, converting the standard curve image obtained in the step S3 and the original image into an 8-bit gray scale image according to sigma_GDenoising by a Gaussian filter kernel of 0.5, performing image segmentation on all the denoised gradient concentration standard fluorescence gray-scale images by taking a gray value of 98 as a global threshold, calculating a gray average value, finally obtaining a gradient concentration standard fluorescence average value with a background subtracted, and fitting a piecewise correction curve according to the standard fluorescence products with different concentrations and the change of the image gray levels of the standard fluorescence products:

whereinIs the concentration of fluorogenic substrate applied to the membrane; a is₁，a₂，b₁，b₂Is a parameter of a linear regression fit; g is the gray value at the breaking point;is the average gray value of the segmented image; the first part of the segmented correction curve is used for converting the pixel gray value in the enzyme spectrum into enzyme activity, endowing the gray value in the correction curve with RGB colors in proportional relation, and the obtained RGB color bars are used for creating a lookup table LUT (look-up table) and generating a pseudo-color leaf enzyme spectrogram; the zymogram image of the leaf obtained in S2 is converted into an 8-bit gray scale image according to sigma_GNoise reduction is carried out by a Gaussian filter kernel of 0.5, the average value of the gray scales in the range of 5 × 5 corners of each image is recorded and is used as the background gray scale of the image, the final gray scale image is obtained by deducting the gray scale value from the whole image, and then the LUT is applied to the blade image to obtain the final gray scale imageAnd the spatial distribution of leaf enzyme activity is visualized.

The invention utilizes a high quenching fluorescent substrate method to carry out in-situ visualization of plant enzyme activity; one end of the substrate is connected with one molecule of fluorescent pigment for combination, the other end is combined with the fluorescence quenching agent, and the fluorescent signal can not be released under normal conditions. When the membrane saturated by the substrate is contacted with the pretreated plant, the substrate is degraded by enzyme in the plant leaves, the quencher is dropped, the action is disappeared, the fluorescence is emitted under the excitation light of ultraviolet, and the distribution condition of the plant enzyme activity on the leaves can be obtained by detecting the distribution of the fluorescence signal intensity on the membrane. In the above steps, among others, leaf image processing is an important issue, which has a profound effect on the results of all subsequent statistical analyses. However, previous studies lack useful information on how to reconstruct high quality images to improve their qualitative accuracy. The invention performs noise reduction enhancement processing by using a gaussian filter pair with σ G of 0.5. Meanwhile, in order to obtain the real fluorescence intensity of the fluorescence substrate, the invention carries out image segmentation before calculating the gray average value of the standard curve image, and uses a global threshold value method to segment the background and the foreground; and finally, processing the image through image denoising and segmentation to reconstruct a high-quality image so as to improve the qualitative accuracy of the image.

Preferably, the method also comprises the step of taking a region with the gray value exceeding 75% of the first part of the calibration curve in the blade zymogram as a hot region, and researching the change of the spatial distribution of the region with higher enzyme activity under the environmental stress by calculating the change of the area of the hot region in the blade zymogram, wherein the change is used for representing the distribution trend of the enzyme activity from the blade base to the blade tip. To better illustrate the spatial distribution of enzyme activity along the main vein

Specifically, the plant is cabbage heart.

In particular, the environmental stress is a pollutant stress.

In particular, the contaminant is a phthalate.

Specifically, the contaminant is dibutyl phthalate.

Specifically, the enzyme is at least one of beta-glucosidase, acid phosphatase or xylanase.

Preferably, the fluorescent label is 4-methylumbelliferone; namely, the enzyme activity fluorescence labeling substrate is at least one of 4-methylumbelliferone-beta-D-glucoside (MUF-G), 4-methylumbelliferone-beta-D-phosphate (MUF-P) or 4-methylumbelliferone-beta-D-xyloside (MUF-X), and the concentration of the enzyme activity fluorescence labeling substrate is 80-120 mu M.

Preferably, the polyamide membrane has a pore size of 0.45 μm and a size of 3 × 5cm²。

Specifically, the present invention quantifies the enzymatic activity under DBP stress in plant leaves by the above-described zymography. The method is used for researching the two-dimensional distribution of the glucosidase, xylanase and acid phosphatase in plant leaves, and provides a new idea for phytotoxicity evaluation and physiological reaction under the stress of pollutants.

As a preferred embodiment, the method for in situ visual determination of glucosidase, xylanase and acid phosphatase in plants under DBP stress comprises the following steps:

(1) plant planting and exposure: planting non-contaminated young plants, such as flowering cabbage; preparing a series of DBP solutions, exposing seedlings in a DBP environment, and carrying out pollutant stress pretreatment;

(2) zymogram imaging, after exposure of seedlings, preparing 4-methylumbelliferone- β -D-glucoside (MUF-G), 4-methylumbelliferone- β -D-phosphate (MUF-P) and 4-methylumbelliferone- β -D-xyloside (MUF-X) into enzyme substrate buffer solution with concentration of 100 μ M, and cutting polyamide membrane with pore diameter of 0.45 μ M into 3 × 5cm²Soaking the seedlings in the prepared enzyme substrate buffer solution for 8-12 min, air-drying for 2-4 min, and closely attaching the seedlings to the surfaces of the leaves of the seedlings exposed by DBP with different concentrations; fixing with an acrylic plate, applying 1.0kg pressure to each side, and reacting in a dark room for 30-40 min. After the reaction is finished, the polyamide membrane is carefully peeled off from the surface of the blade and placed under an ultraviolet lamp with the excitation wavelength of 355nm and the emission wavelength of 460nm, and the polyamide membrane is shot to obtain a blade zymogram image;

(3) making a standard yeast: preparing a series of 4-MUF solutions with the concentration of 0,4,8,10,15,20,40,80,100,200 and 400 mu M, taking a buffer solution without 4-MUF as a blank control, and soaking the polyamide membrane in the buffer solution for 8-12 min; dripping the 4-MUF solution with the series of concentrations on an air-dried polyamide membrane, and shooting by using the same shooting condition as that of S2 zymogram imaging to obtain a calibration image;

(4) image processing: converting the original image of the standard curve image obtained in S3 into 8-bit gray scale image with sigma_GDenoising by a Gaussian filter kernel of 0.5, performing image segmentation on all the denoised gradient concentration standard fluorescence gray-scale images by taking a gray value of 98 as a global threshold, calculating a gray average value, finally obtaining a gradient concentration standard fluorescence average value with a background subtracted, and fitting a piecewise correction curve according to the standard fluorescence products with different concentrations and the change of the image gray levels of the standard fluorescence products:

whereinIs the concentration of MUF applied to the membrane; a is₁，a₂，b₁，b₂Is a parameter of a linear regression fit; g is the gray value at the breaking point;is the average gray value of the segmented image; the first part of the segmented correction curve is used for converting the pixel gray value in the enzyme spectrum into enzyme activity, endowing the gray value in the correction curve with RGB colors in proportional relation, and the obtained RGB color bars are used for creating a lookup table LUT (look-up table) and generating a pseudo-color leaf enzyme spectrogram; the zymogram image of the leaf obtained in S2 is converted into an 8-bit gray scale image according to sigma_GNoise reduction is carried out on the Gaussian filter kernel of 0.5, the gray level mean value in the range of 5 × 5 at the four corners of each image is recorded and is used as the background gray level of the image, the final gray level image is obtained by deducting the gray level mean value from the whole image, and then the LUT is applied to the blade image, so that the spatial distribution of the activity of the blade enzyme is visualized.

The invention also protects the application of any one of the methods in phytotoxicity evaluation and physiological response detection under pollutant stress.

Compared with the prior art, the invention has the following beneficial effects:

the invention provides an in-situ visual determination method for enzyme activity in plants under the stress of pollutants, which fills up the technical blank of plant leaf zymogram in the prior art. Meanwhile, the method aims at the leaf zymogram, and reconstructs a high-quality image of the leaf zymogram by providing a series of image processing means, thereby improving the useful information of qualitative accuracy of the leaf zymogram and having wider application prospect.

Drawings

FIG. 1 is a schematic technical flow chart of the plant zymogram in-situ visualization method developed by the present invention.

FIG. 2 is a schematic diagram of incubation and reaction of a saturated substrate membrane in the plant zymogram in-situ visualization method of the invention.

FIG. 3 is a schematic diagram of an image processing flow in the plant zymogram in-situ visualization method of the present invention.

FIG. 4 is a standard curve drawing in the plant zymogram in-situ visualization method of the invention.

FIG. 5 is a noise reduction result of an image in the plant zymogram in-situ visualization method of the present invention; (a) a gray scale radial distribution map of the FFT image; (b) effect of pre-treatment at different concentrations of MUF on image analysis.

FIG. 6 is the analysis of the enzyme profile and hot zone of the leaves of the plants under DBP stress in example 1: (a) a xylanase; (b) a phosphatase enzyme; (c) beta-glucosidase.

FIG. 7 shows the activity of leaf enzymes along the main veins under DBP stress in example 1.

FIG. 8 is a quantitative analysis of total enzyme activity of leaves under DBP stress in example 1: (a) leaf zymography; (b) biochemical analysis.

Fig. 9 is a plot of different concentrations of MUF: (a) a spatial domain map; (b) and (4) a frequency domain graph.

Fig. 10 is a grayscale histogram of the labeled image after the noise reduction processing.

Detailed Description

The invention is further described with reference to the drawings and the following detailed description, which are not intended to limit the invention in any way. Reagents, methods and apparatus used in the present invention are conventional in the art unless otherwise indicated.

Unless otherwise indicated, reagents and materials used in the following examples are commercially available.

The present invention is illustrated by the following in situ visual assays of glucosidase, xylanase and acid phosphatase in plants under DBP stress. In actual research, test subjects such as environmental stress types, plant types, enzyme types, and the like are selected according to the research target.