CN114246080B - Method for regulating and controlling influence of heavy metal absorption and transportation by plants through mineral elements - Google Patents

Method for regulating and controlling influence of heavy metal absorption and transportation by plants through mineral elements Download PDF

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CN114246080B
CN114246080B CN202111541663.0A CN202111541663A CN114246080B CN 114246080 B CN114246080 B CN 114246080B CN 202111541663 A CN202111541663 A CN 202111541663A CN 114246080 B CN114246080 B CN 114246080B
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于晓章
田鹏
冯宇希
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Guilin University of Technology
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Abstract

The invention discloses a method for regulating and controlling the influence of heavy metal absorption and transportation by a plant by mineral elements, which is used for carrying out short-term heavy metal stress on the plant growing in ultrapure water and nutrient solution; taking the content of each mineral element of each treatment group as an independent variable, changing the differential expression of each HMA gene into a dependent variable, obtaining a standardized weight matrix of each mineral element of each treatment group and a prediction expression of each HMA gene through a partial least square method, screening out the mineral element with the largest influence in the expression of each HMA gene of each treatment group, and screening out the mineral elements with large influence on all HMAs genes of each treatment group; the addition amount of mineral elements in the soil is regulated and controlled by adding the mineral elements which have great influence to the polluted soil. The method for regulating and controlling the influence of heavy metal absorption and transportation by plants by mineral elements not only simplifies the test method, but also provides an effective scientific means for the field of plant restoration.

Description

Method for regulating and controlling influence of heavy metal absorption and transportation by plants through mineral elements
Technical Field
The invention belongs to the technical field of phytoremediation, and relates to a method for regulating and controlling the influence of heavy metal absorption and transportation by plants by mineral elements.
Background
Heavy metal pollution in farmlands has become a worldwide environmental problem due to the influence of artificial activities such as electroplating, metallurgy, mining, wastewater discharge and the like. Heavy metals are non-essential elements for plant growth and development, have high toxicity, high solubility, high mobility and high biological enrichment, and are easily absorbed by plants, so that photosynthesis and organ development of the plants are inhibited, water and nutrient absorption is disturbed, and plant growth is inhibited. In addition, heavy metals can also cause harm to the health of people and animals through the food chain, and effective measures must be taken to control heavy metal pollution.
Heavy metal transporters (HMAs) play a very critical role in the process of Heavy metal absorption and transport by plants. The HMAs in plants are of various kinds, and the HMAs protein families can be divided into the Cu/Ag subfamily and the Zn/Co/Cd/Pb subfamily according to the specificity of metal substrates. Furthermore, HMAs in plants differ in subcellular localization, metal specificity and regulation, which suggests that different HMAs have different functions. Therefore, the regulation and control of the expression of related genes of HMAs has important significance for determining the transport of metal ions in plants.
The growth and development of plants depend not only on the macroelements such as C, N, S and P, but also on the supply of mineral elements such as K, na, ca, mg, cu, fe, mn and Zn. By applying different mineral elements, the aim of reducing the absorption of heavy metals can be achieved through the interaction of the mineral elements and the heavy metals.
Disclosure of Invention
In order to achieve the purpose, the invention provides a method for regulating and controlling the influence of heavy metal absorbed and transported by plants by mineral elements, which adopts a treatment mode of 'heavy metal + nutrient solution' and 'heavy metal + ultrapure water' to analyze the correlation between heavy metal and major/trace mineral elements, and selects a preferable mineral element regulation and control scheme for stress resistance of plants under the condition of heavy metal stress by taking the expression of genes related to plant heavy metal transporters as a basis, explains some fuzzy links in the absorption and distribution processes of heavy metal and mineral elements related to heavy metal transporters in the prior cognition, and provides reference and theoretical support for the plants to resist heavy metal pollution.
The technical scheme adopted by the invention is that the method for regulating and controlling the influence of heavy metal absorption and transportation by plants by mineral elements comprises the following steps:
step 1: heavy metals are taken as pollutants, and plant seedlings growing in ultrapure water and nutrient solution are stressed for a short period of time respectively to form a heavy metal + ultrapure water treatment group and a heavy metal + nutrient solution treatment group;
step 2: calculating the relative growth rate of the plant seedlings of each treatment group through the change of biomass of the plant seedlings before and after short-term stress; respectively measuring the content of heavy metals in the roots and the leaves of the plants of each treatment group, and calculating the transport coefficients of the heavy metals in the roots and the leaves of the plants of each treatment group; respectively measuring the content of each mineral element in the roots and the leaves of the plants of each treatment group, and calculating the transport coefficient of each mineral element; respectively measuring the differential expression change of each heavy metal transport protein gene in the root tissue and the leaf tissue of each treatment group of plants;
and step 3: taking the content of each mineral element of each treatment group as an independent variable, changing the differential expression of each heavy metal transport protein gene into a dependent variable, and obtaining a standardized weight matrix of each mineral element of each treatment group and a prediction expression of each heavy metal transport protein gene by a partial least square method;
and 4, step 4: according to the standardized weight matrix of each mineral element of each treatment group, screening out the mineral element with the largest influence in the expression of each heavy metal transport protein gene in the root and the leaf of each treatment group plant, and screening out the mineral element with the large influence on all heavy metal transport protein genes in the root and the leaf of each treatment group plant;
and 5: the mineral elements which are screened out by the heavy metal and ultrapure water treatment group and have large influence on all heavy metal transport protein genes are added into the lean mineral element soil containing the heavy metal pollutants, or the mineral elements which are screened out by the heavy metal and nutrient solution treatment group and have large influence on all heavy metal transport protein genes are added into the normal soil containing the heavy metal pollutants, so that the addition amount of the mineral elements in the lean mineral element soil or the normal soil is regulated and controlled.
Further, in step 2, the relative growth rate of the young plants is calculated as shown in the following formula:
Figure BDA0003414436170000021
wherein RGR represents the relative growth rate of plant seedlings, M (F) Denotes biomass after stress, M (I) Representing biomass before stress.
Further, in step 2, the transport coefficient is calculated as follows:
Figure BDA0003414436170000022
in the formula, TF represents transport coefficient, C (s) Indicates the content of a mineral element in the leaf part, C (r) Indicating the content of a mineral element in the root.
Further, in the step 2, the differential expression change of the heavy metal transport protein gene is obtained by real-time fluorescent quantitative PCR analysis.
Further, in step 2, the mineral elements include: K. na, ca, mg, cu, fe, mn and Zn.
Further, in step 4, the most influential mineral elements in each heavy metal transporter gene expression are: the mineral elements with the largest positive weight and the mineral elements with the largest negative weight in the expression of each heavy metal transport protein gene in the roots and the leaves of the plants of each treatment group.
Further, in step 4, the mineral elements which have great influence on all heavy metal transport protein genes in the roots and leaves of the plants in each treatment group are as follows: and (3) mineral elements with the maximum weight value times or times in the expression of all heavy metal transport protein genes in roots or leaves of each treatment group.
Further, in the step 5, the step of adding the mineral elements in the lean soil or the normal soil specifically comprises the following steps:
s1, setting the gene expression amount of heavy metal transport proteins to be increased in poor mineral element soil or normal soil, taking the initial addition value of mineral elements with large influence as input, and substituting the initial addition value into the prediction expression of the gene expression of each heavy metal transport protein in a corresponding treatment group; the mineral element-poor soil corresponds to a heavy metal + ultrapure water treatment group, and the normal soil corresponds to a heavy metal + nutrient solution treatment group;
s2, in the prediction expression of each heavy metal transport protein gene expression, the addition amount of mineral elements with large influence is gradually increased by a set step length until the total value calculated on the right side of the prediction expression of the heavy metal transport protein gene expression is equal to the gene expression amount of the heavy metal transport protein which is increased in advance;
and S3, extracting the maximum addition amount of the mineral elements with large influence from the prediction expression of the gene expression of each heavy metal transport protein in the treatment group, and converting the maximum addition amount into original data to be used for regulating and controlling the application amount of the mineral elements in the lean mineral element soil or the normal soil.
The invention has the beneficial effects that:
(1) According to the embodiment of the invention, the mutual relation between the heavy metal and the major/trace mineral elements is analyzed by adopting a treatment mode of 'heavy metal + nutrient solution' and 'heavy metal + ultrapure water', and the optimal mineral element regulation scheme for stress resistance of plants under the heavy metal stress condition is screened by taking the expression of the plant heavy metal transport protein related genes as a basis, so that reference is provided for the plants to resist heavy metal pollution.
(2) The embodiment of the invention only needs eight tests, namely the partial least square method PLS can be used for analyzing the influence of heavy metal pollutants and exogenous mineral elements on the expression of the genes related to the plant heavy metal transport protein, so as to optimize the addition of the mineral elements in the lean soil or normal soil.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a method for regulating and controlling the effects of heavy metals absorbed and transported by plants by mineral elements in an embodiment of the invention.
FIG. 2 shows different processing of Cd in embodiments of the present invention 2+ Relative growth rate of rice seedlings varied under stress.
FIG. 3a is a diagram of different Cd processing embodiments of the present invention 2+ And (5) the Cd content of the roots of the rice seedlings is increased under stress.
FIG. 3b is a diagram of different Cd processing embodiments of the present invention 2+ And (4) stressing the Cd content in the rice seedling leaves.
FIG. 4 shows interaction mechanism of mineral elements and Cd drawn based on PLS in the embodiment of the present invention, where a in FIG. 4 is "Cd 2+ Treating with ultrapure water; b is "Cd 2+ + nutrient solution treatment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
A method for regulating and controlling the influence of heavy metal absorption and transportation by plants by mineral elements is shown in figure 1 and specifically comprises the following steps:
1 preparation of Rice seedlings
Soaking rice seeds (Xiang early indica No. 45) in deionized water for 12h, placing the seeds in disposable paper cups, carrying out sandy soil culture in an artificial climate box, and irrigating an appropriate amount of improved ISO8629 nutrient solution at constant temperature (25 +/-0.5 ℃) and constant humidity (60 +/-2%) (Table 1). And after the rice seedlings are cultured for 16 days, cleaning sandy soil at the roots of the rice seedlings, selecting the seedlings with uniform growth vigor, and temporarily culturing the seedlings in a nutrient solution for 12 hours to enable the rice seedlings to adapt to a water culture environment.
TABLE 1 modified ISO8692 nutritional liquids
Serial number Reagent Concentration of Serial number Reagent Concentration of
1 KNO 3 2823.9μmol/L 8 H 3 BO 3 2992.1nmol/L
2 MgCl 2 ·6H 2 O 59.0μmol/L 9 MnCl 2 ·4H 2 O 2097.0nmol/L
3 CaCl 2 ·2H 2 O 122.4μmol/L 10 Na 2 MoO 4 ·2H 2 O 28.9nmol/L
4 MgSO 4 ·7H 2 O 60.9μmol/L 11 CuSO 4 ·2H 2 O 0.1nmol/L
5 KH 2 PO 4 246.0μmol/L 12 ZnSO 4 22.0nmol/L
6 NaHCO 3 1785.5μmol/L 13 CoCl 2 ·6H 2 O 6.3nmol/L
7 Fe-EDTA 10.0μmol/L
2 design of the experiment
2.1 Cd (NO) was selected for this experiment 3 ) 2 ·4H 2 O as Cd 2+ Contaminants, screened rice seedlings were cultured in the following treatment solutions:
(1)Cd 2+ + ultrapure water treatment group: placing rice seedlings in a conical flask with 50mL of ultrapure water, and adding Cd into the ultrapure water 2+ The concentration of (a): 0. 0.2, 1.8, and 5.4mg Cd/L.
(2)Cd 2+ + nutrient solution treatment group: placing the rice seedlings in 50mL conical flasks of nutrient solution (modified ISO8692 nutrient solution) containing Cd 2+ The concentration of (c): 0. 0.2, 1.8 and 5.4mg Cd/L.
And each conical flask is wrapped by tinfoil paper to be protected from light, so that the water loss is reduced to the maximum extent and the growth of algae is inhibited. There were 4 biological replicates per treatment group with an exposure time of 2 days. "Cd 2+ The purpose of the + ultrapure Water "treatment setup was to analyze Cd 2+ Influence on mineral element distribution in plants. "Cd 2+ The purpose of the + nutrient solution "treatment setup was to analyze Cd 2+ The effect on plant uptake and distribution of mineral elements. "Cd 2+ + ultrapure water "and" Cd 2+ + nutrient solution "comparison was made to analyze the intervention of mineral elements on Cd 2+ Absorption and toxicity effects.
2.2 determination of relative growth rate of rice seedlings, cd content and transport coefficient in tissue, and content of mineral elements
Accurately weighing biomass M of each treatment group before rice seedling stress (I) And biomass M after stress (F) And calculating the Relative Growth Rate (RGR) of the rice seedlings according to the biomass difference before and after the stress. As shown in formula (1):
Figure BDA0003414436170000051
transport coefficient (TF) for evaluating the migration ability of rice seedlings to various mineral elements, C (s) Indicates the content of a mineral element in the leaf part, C (r) Indicating the content of a mineral element in the root. As shown in equation 2.2:
Figure BDA0003414436170000052
after the rice seedlings are stressed for 2 days, the roots of the rice seedlings are cleaned by deionized water, then the rice seedlings are divided into two parts, namely roots and leaves, the two parts are placed in a drying oven at the temperature of 90 ℃ for drying for 48 hours, and the dry weights of the roots and the leaves are respectively weighed. With mixed acids (HNO) 3 :HClO 4 =4:1, V/V) and determining the total content of Cd, K, na, ca, mg, cu, fe, mn and Zn in roots and leaves of the rice seedlings by an inductively coupled plasma emission spectrometry (ICP-AES).
2.3 real-time fluorescent quantitative PCR (qRT-PCR) analysis
There were 8 and 9 HMAs in arabidopsis and rice, respectively. In Arabidopsis and rice AtHMA1-AtHMA4 and OsHMA1-OsHMA3 belong to the Cu/Ag subfamily of the HMAs protein family, and AtHMA5-AtHMA8 and OsHMA4-OsHMA9 belong to the Zn/Co/Cd/Pb subfamily of the HMAs protein family. OsHMA1 and OsHMA9 in rice are thought to play a role in Zn transport, osHMA2 and OsHMA3 participate in Cd transport, and OsHMA4 and OsHMA5 participate in Cu transport.
In order to explore the differential expression change of HMAs related genes in rice seedlings, qRT-PCR detection is carried out on the differential expression of 9 HMAs (OsHMA 1-OsHMA 9) genes of the rice seedlings, and the method specifically comprises the following steps: after 2 days of exposure treatment, 0.2g of rice seedling tissue is weighed and immediately ground in liquid nitrogen, total RNA of a sample is extracted by using an RNA extraction kit, A260/A280 of the extracted RNA is detected to be between 1.8 and 2.0 by using an ultramicro spectrophotometer, pollution of gDNA is removed by using DNase I, first strand synthesis of cDNA is carried out by using a reverse transcription kit, and real-time fluorescent quantitative PCR (qRT-PCR) is carried out by using a SYBR green I dye method. Primers were designed using Primer Premier 5.0, the sequences of which are shown in Table 2, and differential expression of the genes was analyzed using AB-7500 type quantitative PCR instrument, and the fold of differential expression was 2 -ΔΔCT By calculation, osGAPDH (LOC _ Os08g03290.1) was used as an internal reference gene, with 4 repeats per gene.
TABLE 2 Rice HMAs Gene primer sequences
Figure BDA0003414436170000061
3 results of the experiment
3.1 Cd under two treatment modes 2+ Influence of stress on relative growth rate of rice seedlings
FIG. 2 shows that Cd 2+ The stress can inhibit the growth of rice seedlings. "Cd 2+ + nutrient solution "treatment group (in particular Cd) 2+ 1.8 and 5.4mg Cd/L) is obviously higher than that of Cd 2+ + ultrapure water "treatment group. Illustrating the intervention of exogenous mineral elements on Cd 2+ The growth of the stressed rice seedlings plays a role in relieving.
3.2 Cd under two treatment modes 2+ Influence of stress on Cd accumulation and distribution in rice seedlings
Cd under two treatment modes 2+ The accumulation amount of Cd in different tissues of the stressed rice seedling is increased along with the increase of the stress concentration, the roots and the leaves of the rice seedling show a linear accumulation mode for Cd, and the content of Cd accumulated at the roots is obviously higher than that of Cd accumulated at the leaves.
“Cd 2+ The Cd accumulation amounts of the roots and the leaves of the rice seedlings are higher than those of the Cd during the ultrapure water treatment 2+ + nutrient solution treatment (P)<0.05 As shown in fig. 3a and 3 b.
In addition, it was found by calculating the migration coefficient of Cd that "Cd" is shown in Table 3 2+ The migration coefficient of Cd in the rice seedling body is higher than that of Cd during the ultrapure water treatment 2+ + nutrient solution treatment, and "Cd 2+ The migration coefficient of Cd in the rice seedlings in the ultrapure water treatment group is increased along with the increase of the stress concentration, and the' Cd 2+ The migration coefficient of Cd is obviously reduced when + nutrient solution "is treated.
The results show that the roots of rice seedlings are the main part for Cd accumulation, and the Cd 2+ The migration capability of Cd in rice seedlings is stronger than that of Cd in ultrapure water treatment 2+ The results of the nutrient solution treatment show that the addition of exogenous mineral elements can reduce Cd pairs of rice seedlings 2+ The absorption of the Cd can inhibit the migration capacity of Cd in the rice seedlings and relieve the Cd 2+ Damage to rice seedlings by stress.
TABLE 3 migration coefficients of Cd and mineral elements in Rice seedlings
Figure BDA0003414436170000071
3.3 Cd under two treatment modes 2+ Influence of stress on accumulation and distribution of mineral elements in rice seedlings
Mineral element accumulation and distribution in the tissues of rice seedlings and relative expression levels of HMAs for both treatments are shown in table 4.
TABLE 4 Cd 2+ + ultrapure water "and" Cd 2+ + nutrient solution treatment of mineral element accumulation and distribution in various tissues of rice seedling and relative expression level of various HMAs
Figure BDA0003414436170000081
As shown in Table 4, "Cd 2+ When the ultrapure water is treated, the Zn, mn and Ca contents of the roots of the rice seedlings are increased, the Fe, na and Mg contents are reduced, and the Cu and K contents are low in Cd 2+ The stress concentration content is increased, and the medium-high concentration content is reduced. The Zn and Fe contents in the leaf part are increased, and Mn and Cu are in Cd 2+ Low concentration increase, medium and high concentration decrease, ca, mg and K contents decrease, na is only in Cd 2+ The stress concentration is reduced.
As shown in Table 3, the migration coefficients of mineral elements in the rice seedlings showed that "Cd 2+ The rice seedlings are low in Cd during the treatment of the ultrapure water 2+ The migration capacity of Zn, fe, cu and K is lower than that of medium-high Cd in stress concentration 2+ Stress concentration, while Ca, mg, na are in Cd 2+ The migration capability is strongest when the stress concentration is applied, and the migration coefficient of Mn in rice seedlings is along with Cd 2+ The stress concentration is reduced, and the migration coefficients of K and Fe in rice seedlings are along with Cd 2+ The stress concentration increases.
The results show that Cd 2+ Can interfere the distribution and transportation of mineral elements in rice seedlingsAnd (6) inputting.
As shown in Table 4, "Cd 2+ When the nutrient solution is used for treatment, the Zn and Mn contents of the roots of the rice seedlings are increased, the Fe, cu, ca and K contents are reduced, and the Mg and Na contents are only increased when the Cd content is high 2+ The stress concentration content is reduced. The Zn, fe, ca, mg and Na contents in the leaf part are increased, the Mn and Cu contents are reduced, and the K is high in Cd 2+ The stress concentration content is reduced.
As shown in Table 3, the migration coefficients of mineral elements in rice seedlings showed that the migration ability of Zn, ca, na and Mg was increased and the migration ability of Fe, mn, cu and K was decreased.
The results show that Cd 2+ The stress can affect the absorption and transportation of mineral elements by rice seedlings, thereby affecting the growth of the rice seedlings.
3.4 Cd under two treatment modes 2+ Influence of stress on expression of HMAs related genes of rice seedlings
As can be seen from Table 4, "Cd 2+ Cd in + ultrapure Water treatment 2+ When the nutrient solution is treated, the HMAs genes in the rice seedlings have different expression modes, which indicates that exogenous mineral elements can mediate HMAs related genes in the rice seedlings to regulate Cd 2+ Absorption and transport.
3.5 screening Cd based on Partial Least Squares (PLS) 2+ Optimal mineral element regulation and control scheme for stress resistance of paddy rice
PLS regression (Partial least squares regression) is a multivariate statistical method that can solve the problem of co-linearity, analyze multiple dependent variables Y simultaneously, and study influence relationships when processing small samples.
The present application proposes for the first time the use of PLS regression analysis "Cd 2+ + nutrient solution "and" Cd 2+ Relationship between independent variable X (different mineral elements) and dependent variable Y (HMAs gene expression) in the + ultrapure water "treatment group. The PLS analysis is carried out by adopting a micro-thought sheet machine learning online visualization tool set.
3.5.1“Cd 2+ PLS analysis of + ultra pure Water "treatment group blades
(1) "Cd" in Table 4 2+ Total number of blades of + ultrapure water "treatment groupInputting the data (Zn-OsHMA 9 is a row, and C1-C4 are columns) into an online table of the micro-thought sheet machine learning online visualization tool set;
(2) selecting a PLS regression function of a micro-thought sheet machine learning online visualization tool set, selecting all mineral element standardized data as independent variable sample data, selecting all HMAs relative expression level data as dependent variable sample data, selecting the number of components as 2, and starting training;
(3) a normalized weight matrix for each mineral element in the training results is obtained, as shown in table 5.
TABLE 5 Cd 2+ Normalized weight matrix for each mineral element of the + ultrapure water "treatment group blade
Figure BDA0003414436170000101
The influence of different mineral elements on the expression of each HMA gene was analyzed according to table 5, and the two mineral elements having the greatest influence on the expression of the HMA gene were analyzed by the maximum positive weight and the maximum negative weight of the mineral elements under each HMA. For example, fe and Zn most affect OsHMA1 gene expression, and Fe and Mg most affect OsHMA2 gene expression. From the statistical analysis of the major influence of the expression of all HMAs genes on the mineral elements in Table 5, it was concluded that: K. na, fe, zn and Cu play an extremely important role in explaining nine regression equations.
Statistical analysis is carried out on all mineral elements which have the greatest influence on HMA expression, and K (the influence on the expression of four HMA genes is the greatest) is obtained as the mineral element which has the greatest influence on the gene expression of all HMAs.
(4) And obtaining the prediction expression of each HMA gene expression in the training result, wherein the prediction expression is shown as formulas (1) to (9).
OsHMA1＝-0.718×Zn+0.963×Fe-0.04829×Mn+1.895×Cu-1.407×Ca-2.410×Mg-3.775×K+2.87×Na+3.472 (1)
OsHMA2＝-0.369×Zn-0.305×Fe+0.211×Mn+1.190×Cu+0.766×Ca+0.884×Mg+0.610×K-0.050×Na-1.897 (2)
OsHMA3＝-0.503×Zn-0.251×Fe+0.239×Mn+1.576×Cu+0.737×Ca+0.766×Mg+0.305×K+0.247×Na-2.090 (3)
OsHMA4＝1.785×Zn+0.361×Fe-0.692×Mn-5.45×Cu-1.63×Ca-1.315×Mg+0.603×K-1.885×Na+9.169 (4)
OsHMA5＝2.355×Zn+0.353×Fe-0.877×Mn-7.155×Cu-1.920×Ca-1.408×Mg+1.188×K-2.720×Na+11.149 (5)
OsHMA6＝-0.885×Zn+0.499×Fe+0.143×Mn+2.520×Cu-0.453×Ca-1.144×Mg-2.459×K+2.225×Na+0.514 (6)
OsHMA7＝-0.906×Zn-0.105×Fe+0.328×Mn+2.745×Cu+0.682×Ca+0.461×Mg-0.555×K+1.105×Na-2.730 (7)
OsHMA8＝-1.503×Zn+0.202×Fe+0.434×Mn+4.452×Cu+0.429×Ca-0.235×Mg-2.122×K+2.551×Na-3.189 (8)
OsHMA9＝-0.702×Zn+0.409×Fe+0.110×Mn+1.996×Cu-0.385×Ca-0.944×Mg-1.994×K+1.791×Na+0.717 (9)
And (3) drawing a prediction graph of the HMA gene expression according to the prediction expressions of the expressions (1) to (9), wherein the difference between each predicted value and each actual value in the prediction graph is small, and the fitting effect of the expressions (1) to (9) is good.
3.5.2“Cd 2+ PLS analysis of the root of the + ultrapure Water "treatment line
And "Cd 2+ The normalized weight matrix for this treatment group was obtained as shown in table 6, as was the PLS analysis procedure for the + ultrapure water "treatment group blades.
TABLE 6 Cd 2+ Normalized weight matrix for each mineral element at the root of the + ultrapure water "treatment group
Figure BDA0003414436170000111
From the analysis in Table 6, the mineral element that most affects the gene expression of all HMAs is Ca followed by Na.
And obtaining the prediction expression of each HMA gene expression in the training result, wherein the expression is shown in the formulas (10) to (18).
OsHMA1＝0.030×Zn+0.304×Fe+0.1524×Mn+0.6384×Cu-1.0494×Ca-0.371×Mg+0.486×K+2.173×Na-1.298 (10)
OsHMA2＝2.946×Zn+1.297×Fe+3.506×Mn+3.979×Cu-2.679×Ca-31.383×Mg+2.025×K+6.809×Na+14.915 (11)
OsHMA3＝-0.259×Zn+0.306×Fe-0.140×Mn+0.514×Cu-1.241×Ca+2.679×Mg+0.494×K+2.440×Na-3.791 (12)
OsHMA4＝1.807×Zn-0.517×Fe+1.623×Mn-0.259×Cu+2.972×Ca-19.003×Mg-0.860×K-5.325×Na+20.249 (13)
OsHMA5＝4.292×Zn-4.301×Fe+2.621×Mn-6.941×Cu+17.870×Ca-44.558×Mg-6.965×K-34.902×Na+73.425 (14)
OsHMA6＝1.759×Zn-1.595×Fe+1.142×Mn-2.499×Cu+6.733×Ca-18.298×Mg-2.585×K-13.087×Na+29.333 (15)
OsHMA7＝0.236×Zn+0.154×Fe+0.301×Mn+0.421×Cu-0.389×Ca-2.524×Mg+0.242×K+0.905×Na+1.577 (16)
OsHMA8＝-0.138×Zn+0.267×Fe-0.033×Mn+0.487×Cu-1.027×Ca+1.412×Mg+0.430×K+2.053×Na-2.480 (17)
OsHMA9＝4.002×Zn-4.848×Fe+2.107×Mn-8.196×Cu+19.609×Ca-41.388×Mg-7.836×K-38.609×Na+76.524 (18)
The prediction graphs of the HMA gene expression were plotted based on the prediction expressions of expressions (10) to (18), and the prediction graphs showed a small difference between the predicted values and the actual values, indicating that the fitting effects of expressions (10) to (18) were good.
3.5.3“Cd 2+ + nutrient solution "PLS analysis of treated groups of leaves
And "Cd 2+ The normalized weight matrix for this treatment group was obtained as shown in table 7, as was the PLS analysis procedure for the + ultrapure water "treatment group blades.
TABLE 7 Cd 2+ Normalized weight matrix for each mineral element of leaf of + nutrient solution treatment group
Figure BDA0003414436170000121
From the analysis in Table 7, the mineral elements that most affect the gene expression of all HMAs are Zn, cu and K.
And obtaining the prediction expression of each HMA gene expression in the training result, wherein the expression is shown in formulas (19) to (27).
OsHMA1＝1.690×Zn-5.113×Fe-3.593×Mn-4.694×Cu+1.575×Ca-0.176×Mg-4.609×K+1.857×Na+14.092 (19)
OsHMA2＝-0.318×Zn+0.991×Fe+0.678×Mn+0.883×Cu-0.293×Ca+0.051×Mg+0.873×K-0.343×Na-1.498 (20)
OsHMA3＝-0.340×Zn-0.172×Fe+0.604×Mn+0.924×Cu-0.452×Ca-0.678×Mg+0.668×K-0.599×Na+1.064 (21)
OsHMA4＝2.070×Zn-5.428×Fe-4.317×Mn-5.733×Cu+2.022×Ca+0.279×Mg-5.464×K+2.430×Na+15.170 (22)
OsHMA5＝0.182×Zn+1.676×Fe-0.167×Mn-0.469×Cu+0.422×Ca+1.307×Mg-0.016×K+0.619×Na-2.530 (23)
OsHMA6＝0.069×Zn+1.119×Fe-0.016×Mn-0.170×Cu+0.215×Ca+0.784×Mg+0.098×K+0.326×Na-1.418 (24)
OsHMA7＝-0.173×Zn+0.575×Fe+0.374×Mn+0.482×Cu-0.156×Ca+0.048×Mg+0.484×K-0.181×Na-0.457 (25)
OsHMA8＝0.200×Zn+1.903×Fe-0.176×Mn-0.512×Cu+0.470×Ca+1.471×Mg-0.003×K+0.690×Na-3.031 (26)
OsHMA9＝0.595×Zn+1.634×Fe-0.925×Mn-1.595×Cu+0.943×Ca+1.982×Mg-0.881×K+1.299×Na-2.036 (27)
And (3) drawing a prediction graph of the HMA gene expression according to the prediction expressions of the expressions (19) to (27), wherein the difference between each predicted value and each actual value in the prediction graph is small, and the fitting effect of the expressions (19) to (27) is good.
3.5.4“Cd 2+ + nutrient solution "treatment group root PLS analysis
And "Cd 2+ The normalized weight matrix for this treatment group was obtained as shown in table 8, as was the PLS analysis procedure for the + ultrapure water "treatment group blades.
TABLE 8 Cd 2+ Normalized weight matrix of each mineral element of the roots of the + nutrient solution "treatment group
Figure BDA0003414436170000141
From the analysis in table 8, K, zn and Cu play an extremely important role in the explanation of the nine regression equations, and the mineral element that most affects the gene expression of all HMAs is Zn.
And obtaining the prediction expression of each HMA gene expression in the training result, wherein the expression is shown as a formula (28) to a formula (36).
OsHMA1＝0.587×Zn+2.529×Fe+2.196×Mn-0.336×Cu+2.223×Ca+3.344×Mg+1.157×K+1.459×Na-12.151 (28)
OsHMA2＝0.512×Zn+0.428×Fe+0.707×Mn-0.951×Cu+0.295×Ca+0.249×Mg-0.669×K+0.073×Na+0.586 (29)
OsHMA3＝-0.310×Zn+1.418×Fe+0.711×Mn+1.193×Cu+1.371×Ca+2.364×Mg+1.984×K+1.087×Na-8.844 (30)
OsHMA4＝7.986×Zn-2.741×Fe+4.635×Mn-18.296×Cu-4.096×Ca-10.228×Mg-19.286×K-5.209×Na+48.319 (31)
OsHMA5＝2.890×Zn-0.302×Fe+2.145×Mn-6.365×Cu-0.844×Ca-2.667×Mg-6.328×K-1.420×Na+13.819 (32)
OsHMA6＝3.956×Zn-1.165×Fe+2.427×Mn-8.992×Cu-1.850×Ca-4.777×Mg-9.372×K-2.450×Na+23.363 (33)
OsHMA7＝-0.658×Zn+0.007×Fe-0.531×Mn+1.428×Cu+0.136×Ca+0.5153×Mg+1.384×K+0.282×Na-1.586 (34)
OsHMA8＝-0.704×Zn-0.031×Fe-0.594×Mn+1.513×Cu+0.109×Ca+0.493×Mg+1.444×K+0.275×Na-1.541 (35)
OsHMA9＝11.937×Zn-5.936×Fe+5.678×Mn-28.025×Cu-7.821×Ca-18.045×Mg-30.559×K-9.026×Na+82.781 (36)
And (3) drawing a prediction graph of the HMA gene expression according to the prediction expressions of the expressions (28) to (36), wherein the difference between each predicted value and each actual value in the prediction graph is small, and the fitting effect of the expressions (28) to (36) is good.
4 specific applications
For "Cd 2+ + ultrapure water "treatment, statistical analysis was performed on the normalized weight matrices for each mineral element in table 5 and table 6, yielding the results: the influence of K, na, fe, zn and Cu on Cd transport and distribution is large, the influence of K is the largest, and the influence of Na and Ca on Cd transport and distribution is large on roots (a in FIG. 4).
Thus, based on the normalized weight matrix for each mineral element of tables 5 and 6, the Cd content is 2+ Method for regulating Cd pair by adding K, na and Ca into poor mineral element soil 2+ Absorption of (2).
Meanwhile, the influence of different mineral elements on HMAs gene expression is predicted through formulas (1) to (18), so that the application amount of the mineral elements in the poor mineral element soil is adjusted, and the adjusting method specifically comprises the following steps:
s1, setting the expression quantity of each HMA pre-increased gene, and adding the initial addition values of the three preset mineral elements of K, na and Ca (refer to Table 4, and use' Cd 2+ + ultrapure water "treatment group blades are exemplified, e.g., when Cd 2+ K, na and Ca at a concentration of C2 of 0.83,0.93 and 1.04, these three values being the initial addition values of K, na and Ca) into the predicted expression for each HMA gene expression;
s2, in each prediction expression of HMA gene expression, the numerical values of other mineral elements are not changed, and the addition amounts of the three mineral elements of K, na and Ca are gradually increased by a certain step length (which can be set as 0.05) until the total value calculated on the right side of the prediction expression of the HMA gene expression is equal to the gene expression amount of the HMA;
s3, in Cd 2+ In the prediction expression of each HMA gene expression in the + ultrapure water "treatment group, the maximum addition amount of three mineral elements of K, na and Ca is extracted, and at the moment, standardized data is also extracted and converted into original data to be used for regulating and controlling the application amounts of the three mineral elements of K, na and Ca in the poor mineral element soil.
One specific embodiment is: and selecting Cd transport related genes OsHMA2, osHMA3, osHMA7 and OsHMA9 as heavy metal transport genes of the gene expression quantity to be increased, and performing the operation to obtain the application quantity of the K, na and Ca mineral elements in the lean mineral element soil.
For "Cd 2+ + nutrient solution "treatment, statistical analysis is performed on the normalized weight matrix of each mineral element in table 7 and table 8, and the results are obtained: the influence of the Zn, cu and K of the blades on the Cd transportation and distribution is large, the influence of the Zn and Cu is the largest, and the influence of the Zn and Cu on the Cd transportation and distribution of the roots is large (b in fig. 4).
Thus, based on the normalized weight matrix for each mineral element of tables 7 and 8, the Cd content 2+ Adding Zn, cu and K into normal soil to regulate and control Cd in plant pair 2+ Absorption of (2).
Meanwhile, the influence of different mineral elements on HMAs gene expression is predicted through formulas (19) to (36), so that the application amount of the mineral elements in normal soil is adjusted, and the adjustment method specifically comprises the following steps:
s1, setting the pre-increased gene expression amount of each HMA, and substituting the initial addition values of three preset mineral elements of Zn, cu and K into prediction expressions of each HMA gene expression;
s2, in each prediction expression of HMA gene expression, the numerical values of other mineral elements are not changed, and the addition amounts of Zn, cu and K mineral elements are gradually increased by a certain step length (which can be set as 0.05) until the total value calculated on the right side of the prediction expression of the HMA gene expression is equal to the gene expression amount of the HMA;
s3, in Cd 2+ In the prediction expression of each HMA gene expression in the + ultrapure water "treatment group, the maximum addition amount of three mineral elements of Zn, cu and K is extracted, and at the moment, standardized data is also extracted and converted into original data to be used for regulating and controlling the application amount of the three mineral elements of Zn, cu and K in the poor mineral element soil.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on differences from other embodiments.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.

Claims (5)

1. The method for regulating and controlling the influence of heavy metal absorption and transportation by the plants through the mineral elements is characterized by comprising the following steps:
step 1: heavy metals are taken as pollutants, and plant seedlings growing in ultrapure water and nutrient solution are stressed for a short period of time respectively to form a heavy metal + ultrapure water treatment group and a heavy metal + nutrient solution treatment group;
step 2: calculating the relative growth rate of the plant seedlings of each treatment group through the biomass change of the plant seedlings before and after short-term stress; respectively measuring the content of heavy metals in the roots and the leaves of the plants of each treatment group, and calculating the transport coefficients of the heavy metals in the roots and the leaves of the plants of each treatment group; respectively measuring the content of each mineral element in the root and the leaf of each treatment group plant, and calculating the transport coefficient of each mineral element; respectively measuring the differential expression change of each heavy metal transport protein gene in the root tissue and the leaf tissue of each treatment group of plants;
and step 3: taking the content of each mineral element of each treatment group as an independent variable, changing the differential expression of each heavy metal transport protein gene into a dependent variable, and obtaining a standardized weight matrix of each mineral element of each treatment group and a prediction expression of each heavy metal transport protein gene by a partial least square method;
and 4, step 4: screening out mineral elements with the largest influence in the expression of each heavy metal transport protein gene in the root and the leaf of each treatment group plant according to the standardized weight matrix of each mineral element of each treatment group, and screening out the mineral elements which have the large influence on all the heavy metal transport protein genes in the root and the leaf of each treatment group plant;
in step 4, the mineral elements with the largest influence in each heavy metal transporter gene expression are as follows: the mineral element with the largest positive weight and the mineral element with the largest negative weight in the expression of each heavy metal transport protein gene in the roots and the leaves of the plants in each treatment group;
in the step 4, the mineral elements which have great influence on all heavy metal transport protein genes in the roots and the leaves of the plants of each treatment group are as follows: mineral elements with the maximum weight value times or times in the expression of all heavy metal transport protein genes in roots or leaves of each treatment group are the most;
and 5: mineral elements which are screened out by adding a heavy metal and ultrapure water treatment group to the lean mineral element soil containing the heavy metal pollutants and have large influence on all heavy metal transport protein genes, or mineral elements which are screened out by adding a heavy metal and nutrient solution treatment group to the normal soil containing the heavy metal pollutants and have large influence on all heavy metal transport protein genes, and the addition amount of the mineral elements in the lean mineral element soil or the normal soil is regulated;
in the step 5, the step of adding the mineral elements in the lean mineral element soil or the normal soil specifically comprises the following steps:
s1, setting the gene expression amount of heavy metal transport protein to be increased for poor mineral element soil or normal soil, taking the initial addition value of mineral elements which have large influence on all heavy metal transport protein genes as input, and substituting the input value into the prediction expression of each heavy metal transport protein gene expression of a corresponding treatment group; the mineral element-poor soil corresponds to a heavy metal + ultrapure water treatment group, and the normal soil corresponds to a heavy metal + nutrient solution treatment group;
s2, in the prediction expression of each heavy metal transport protein gene expression, the addition amount of mineral elements which have large influence on all heavy metal transport protein genes is gradually increased by a set step length until the total value calculated on the right side of the prediction expression of the heavy metal transport protein gene expression is equal to the gene expression amount of the heavy metal transport protein which is increased in advance;
and S3, extracting the maximum addition amount of the mineral elements which have large influence on all heavy metal transport protein genes from the prediction expression of the heavy metal transport protein gene expression of the treatment group, and converting the maximum addition amount into original data to be used for regulating and controlling the application amount of the mineral elements in the lean mineral element soil or the normal soil.
2. The method for regulating and controlling the effect of heavy metal absorption and transportation by plants through mineral elements according to claim 1, wherein in the step 2, the relative growth rate of the young plants is calculated as shown in the following formula:
Figure 732586DEST_PATH_IMAGE001
；
in the formula (I), the compound is shown in the specification,RGRindicates the relative growth rate of the young plant seedlings,M （F） which means the biomass after stress and the biomass,M （I） representing biomass before stress.
3. The method for regulating and controlling the effect of heavy metal absorption and transport by plants through mineral elements according to claim 1, wherein in the step 2, the transport coefficient is calculated according to the following formula:
Figure 321830DEST_PATH_IMAGE002
；
in the formula (I), the compound is shown in the specification,TFthe transport coefficient is expressed in terms of the transport coefficient,C (s) indicates the content of certain mineral elements in the leaf part,C (r) indicating the content of a mineral element in the root.
4. The method for regulating and controlling the influence of heavy metal absorption and transportation by a plant according to claim 1, wherein in the step 2, the differential expression change of the heavy metal transporter gene is obtained by real-time fluorescent quantitative PCR analysis.
5. The method for regulating and controlling the effect of heavy metal absorption and transport by plants through the mineral elements according to claim 1, wherein in the step 2, the mineral elements comprise: K. na, ca, mg, cu, fe, mn and Zn.
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