CN113390666A - Method for detecting performance index of chemical substance in cell - Google Patents

Method for detecting performance index of chemical substance in cell Download PDF

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CN113390666A
CN113390666A CN202110682860.8A CN202110682860A CN113390666A CN 113390666 A CN113390666 A CN 113390666A CN 202110682860 A CN202110682860 A CN 202110682860A CN 113390666 A CN113390666 A CN 113390666A
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熊伟
刘丹
张学和
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Anhui Kecheng Intelligent Health Technology Co ltd
Liu Dan
Xiong Wei
Zhang Xuehe
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Abstract

The invention discloses a method for detecting performance indexes of chemical substances in cells, which comprises the following steps: s1, preparing a sample slice; s2, sequentially carrying out MS detection, electrophysiology detection, Western blot detection and immunofluorescence detection on the sample slice to obtain a target detection data set corresponding to the target sample slice, wherein the target detection data set comprises: MS data, electrophysiology data, western blot data, and immunofluorescence data; s3, analyzing the target detection data to obtain the performance index of the compound in the sample slice; the invention can carry out multiple detections based on the same sample slice, on one hand, the influence of other external factors on the detection can be reduced, so that different experimental results can be provided for the same experimental object, on the other hand, the requirements of different detections can be met, and the preliminary research direction of chemical substances in cells can be provided.

Description

Method for detecting performance index of chemical substance in cell
Technical Field
The invention relates to the technical field of human biology, in particular to a method for detecting performance indexes of chemical substances in cells.
Background
With the development of science and technology, research on biological chemicals is more and more important, and especially refined chemicals can contribute to the development of human beings in different fields, for example, many diseases can be overcome in the medical field, the research on chemical substances in cells cannot leave the detection process of chemical substances in cells, and the properties and the purposes of the chemical substances can be better understood only through accurate detection.
At present, chemical substances in cells can be analyzed according to different experimental results to obtain different research results, and a set of system cannot be formed in the prior art for detecting the chemical substances in the cells so as to obtain a primary judgment direction for the chemical substances in cells with different components or contents and further research, so that misleading in the research on the chemical substances in the cells and waste of research and development resources and time are avoided.
Disclosure of Invention
In order to solve the problems in the prior art, multiple detections can be carried out based on the same sample slice, so that on one hand, the influence of other external factors on the detections can be reduced, different experimental results can be obtained for the same experimental object, on the other hand, different detection requirements can be met, and a preliminary research direction of chemical substances in cells can be provided; the embodiment of the invention provides a method for detecting performance indexes of chemical substances in cells, which comprises the following steps:
s1, preparing a sample slice;
s2, sequentially carrying out MS detection, electrophysiology detection, Western blot detection and immunofluorescence detection on the sample slice to obtain a target detection data set corresponding to the target sample slice, wherein the target detection data set comprises: MS data, electrophysiology data, western blot data, and immunofluorescence data;
and S3, analyzing the target detection data to obtain the performance index of the compound in the sample slice.
Further, S1 further includes the following steps:
taking a brain tissue sample of a target subject;
placing the brain tissue sample in a slicing solution for culture treatment, wherein the slicing solution comprises the following components: sucrose, NaCl, NaHCO3、MgCl2Glucose, KCl and NaH2PO4
And slicing the cultured brain tissue sample to obtain the sample slice.
Further, sucrose, NaCl, NaHCO3、MgCl2Glucose, KCl and NaH2PO4Comprises the following chemical components in percentage by weight: 200mM, 30mM, 26mM, 1mM, 10mM, 4.5mM and 1.2mM, the contents being in order of chemical composition.
Further, the slice thickness of the specimen is 300 μm.
Further, the method further comprises analyzing the MS data by: and extracting the ion intensity of the metabolite in the MS data to obtain a change value between the isotope-labeled metabolite and the non-isotope-labeled metabolite according to the ion intensity of the metabolite.
Further, the method further comprises analyzing the electrophysiological data by: the variation of the excitatory postsynaptic current is obtained from the average value of 60-90 light-excited excitatory postsynaptic currents in the electrophysiological data.
Further, the method further comprises analyzing the western blot data by: extracting protein bands in the western blot data, and calculating a target gray value according to the protein bands;
and adjusting the protein band according to the comparison between the target gray value and a preset gray threshold value.
Further, the method further comprises analyzing the immunofluorescence data by: and obtaining the quantity of the fluorescently-labeled NeuN protein according to the immunofluorescence data.
The method for detecting the performance index of the chemical substance in the cell has the following technical effects:
the method can prepare a sample slice, detect the sample slice to obtain the detection results of chemical substances and chemical substances in the sample slice, and analyze the detection results of the chemical substances to obtain the performance index value of the sample slice; wherein the detection result of the chemical substance comprises: MS data, electrophysiological data, western blot data and immunofluorescence data can realize multiple detections, do not need to change detection samples, guarantee the accuracy of detection, and adopt corresponding detection methods to detect according to different chemical substances, avoid the inaccuracy of detection results and then influence the judgment of the chemical substances in the cell, and enable researchers to predict the metabolic state of the cell according to the chemical substances in the cell.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flow chart of a method for detecting performance indicators of intracellular chemicals according to an embodiment of the present invention.
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 obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
As shown in fig. 1, the present embodiment provides a method for detecting performance indicators of chemical substances in cells, the method comprising the following steps:
s1, preparing a sample slice;
s2, sequentially carrying out MS detection, electrophysiology detection, Western blot detection and immunofluorescence detection on the sample slice to obtain a target detection data set corresponding to the target sample slice, wherein the target detection data set comprises: MS data, electrophysiology data, western blot data, and immunofluorescence data;
and S3, analyzing the target detection data to obtain the performance index of the compound in the sample slice.
Further, S1 further includes the following steps:
taking a brain tissue sample of a target subject;
placing the brain tissue sample in a slicing solution for culture treatment, wherein the slicing solution comprises the following components: sucrose, NaCl, NaHCO3、MgCl2Glucose, KCl and NaH2PO4
And slicing the cultured brain tissue sample to obtain the sample slice.
Further, sucrose, NaCl, NaHCO3、MgCl2Glucose, KCl and NaH2PO4Comprises the following chemical components in percentage by weight: 200mM, 30mM, 26mM, 1mM, 10mM, 4.5mM and 1.2mM, the contents being in order of chemical composition.
Further, the slice thickness of the specimen is 300 μm.
Further, the method further comprises preparing a target sample slice from the sample slice, preparing a pre-prepared solution as follows, wherein the pre-prepared solution refers to a diluted solution of the labeled isotope histidine;
under the condition of room temperature, the sample slice is incubated in the prepared solution for a preset time;
cleaning the incubated sample slice, and obtaining a single neuron sample on the cleaned sample slice;
and injecting a preset isotope solution into the single neuron sample to obtain the target sample slice.
Further, the isotope may be used13C。
Further, before analyzing the MS data in S21, the method further includes: carrying out calibration processing on a UCA numerical curve in MS data, wherein the calibration processing comprises the following steps:
preparing a plurality of calibration solutions with different concentrations according to a standard sample, wherein each calibration solution is an intracellular solution;
and sequentially calibrating the UCA numerical curve according to the concentration based on each calibration solution.
Further, the chemical composition of the intracellular solution is: potassium gluconate, NaCl, EGTA, HEPES, CaCl2、CsOH、MgCl2Na-ATP and Na-GTP.
Further, potassium gluconate, NaCl, EGTA, HEPES, CaCl2、CsOH、MgCl2The contents of Na-ATP and Na-GTP are respectively as follows: 130mM, 6mM, 10mM, 1mM, 4mM, 1mM, 2mM, and 0.2mM, wherein the order of contents is in order of chemical composition.
Further, the diluted solution of isotopic histidine was subjected to dilution and washing treatment by cerebrospinal fluid.
Further, in S22, obtaining a metabolic pathway of the chemical substance in the sample slice according to the analysis result of the MS data, further comprising the steps of:
comparing the increment corresponding to the metabolite ion strength of the labeled isotope with a preset threshold, wherein the increment is an increment value of the metabolite ion strength in percentage of the mass number of the substance;
and when the corresponding increment of the ion intensity of the metabolite of the labeled isotope is larger than the threshold value, tracking the metabolic path formed by the chemical substance of the labeled isotope.
Further, the method further comprises analyzing the MS data by: and extracting the ion intensity of the metabolite in the MS data to obtain a change value between the isotope-labeled metabolite and the non-isotope-labeled metabolite according to the ion intensity of the metabolite.
Preferably, the following formula is specifically adopted:
Figure BDA0003120401510000071
wherein the content of the first and second substances,
Figure BDA0003120401510000072
is marked by13The ratio of the metabolites of C is such that,
Figure BDA0003120401510000073
refers to the ratio of unlabeled 13C metabolites.
Therefore, the MS data are normalized by dividing the ion intensity of the metabolite by the total ion current (I/TIC) when being preprocessed by the method, so that the difference of the total ion current of mass spectrum detection signals of different samples in the original data can be avoided, the comparability among the samples is poor, and the comparability and the result of the signals among the samples are improved. Further, the method further comprises analyzing the electrophysiological data by: the variation of the excitatory postsynaptic current is obtained from the average value of 60-90 light-excited excitatory postsynaptic currents in the electrophysiological data.
Specifically, the following formula is adopted for processing:
ρ2=IQ(1-P),
wherein N is the number of synapses, i.e., the number of neurosynaptic areas presented to the electrical stimulation area on the brain tissue slice in the electrophysiological analysis;
q is quantum size, i.e. the postsynaptic response resulting from the release of a single neurotransmitter vesicle;
rho 2 is the degree of variation, and is a statistical index, namely the sample dispersion degree;
i is current, i.e., electrophysiological monitoring of post-synaptic excitatory current or post-synaptic inhibitory current, which results from the flow of charged ions resulting from the release of presynaptic transmitter acting on the post-synaptic ion channel;
p is the probability of release, i.e., the probability of an event that the presynaptic membrane releases a neurotransmitter.
Further, the method further comprises analyzing the western blot data by:
extracting protein bands in the western blot data, and calculating a target gray value according to the protein bands;
and adjusting the protein band according to the comparison between the target gray value and a preset gray threshold value.
Specifically, the following formula is adopted:
Figure BDA0003120401510000081
wherein F is the gray value of the normalized protein band, D is the target gray value,
Figure BDA0003120401510000082
the gray level is a preset gray level threshold value, namely the gray level of the ginseng-shoprotein band.
Furthermore, NAPDH or beta-actin can be selected from the ginseng S-protein band, but in some special tissue areas, more specific reference protein is selected, more accurate results can be obtained in corresponding tissues, and the experimental results have tissue specificity and targeting. For example, in the synaptic area sample analysis, PSD-95 is selected as a reference protein; and further, the situation that the absolute quantity of the sample is inevitably different, and the bandwidth of the protein strip of the sample with large absolute quantity is large, so that the analysis result is possibly inaccurate can be avoided.
Further, the method further comprises analyzing the immunofluorescence data by: and obtaining the quantity of the fluorescently-labeled NeuN protein according to the immunofluorescence data.
Specifically, the following formula is adopted:
Figure BDA0003120401510000091
wherein S is the average fluorescence, A is the integrated optical density in the visual field, and B is the area of the fluorescence pixel.
Further, both a and B are extracted through immunofluorescence data, and the in-view refers to a view observed through a microscopic instrument, and those skilled in the art can select the in-view according to actual needs, and details are not described herein.
Therefore, the method can improve the accuracy of experimental results and eliminate errors caused by differences of shooting, slicing and tissue sizes. The image analysis uses the average gray value to calculate the fluorescence intensity, and effectively eliminates the difference of the calculation result caused by the cell size and the cell number in each visual field.
In one specific example, data from blood and cerebrospinal fluid with and without isotope are compared as shown in Table 1.
TABLE 1
Figure BDA0003120401510000101
In a specific example, the results of the MS analysis data analysis corresponding to the target sample sections incubated with and without the isotope are compared, as shown in table 2.
TABLE 2
Figure BDA0003120401510000102
As can be seen from tables 1 and 2, metabolite and metabolic pathway tracing by tail vein injection of stable isotopes can be effectively demonstrated: the ability of metabolites to cross the blood brain barrier, the specificity and accuracy of the conversion between metabolites, and the accurate confirmation of metabolic pathways. In addition, the stable isotope has obvious advantages compared with the traditional radioactive isotope tracing, and the safety and the stability are obviously improved.
In summary, the table can be used for preparing serum and cerebrospinal fluid samples, preparing sample slices based on the serum and the cerebrospinal fluid, detecting the sample slices to obtain detection results of chemical substances and chemical substances in the sample slices, and analyzing the detection results of the chemical substances to obtain performance index values of the sample slices; wherein the detection result of the chemical substance comprises: the method has the advantages that one or more combinations of MS data, MR data, electrophysiological data, Western blot data and immunofluorescence data can be used for realizing multiple detections without replacing detection samples, detection accuracy is guaranteed, corresponding detection methods are adopted for detection according to different chemical substances, inaccuracy of detection results is avoided, judgment of the chemical substances in the cells is further prevented from being influenced, and researchers can predict biological health according to the chemical substances in the cells.

Claims (8)

1. A method for detecting a performance indicator of a chemical in a cell, the method comprising the steps of:
s1, preparing a sample slice;
s2, sequentially carrying out MS detection, electrophysiology detection, Western blot detection and immunofluorescence detection on the sample slice to obtain a target detection data set corresponding to the target sample slice, wherein the target detection data set comprises: MS data, electrophysiology data, western blot data, and immunofluorescence data;
and S3, analyzing the target detection data to obtain the performance index of the compound in the sample slice.
2. The method according to claim 1, wherein S1 further comprises the following steps:
taking a brain tissue sample of a target subject;
placing the brain tissue sample in a slicing solution for culture treatment, wherein the slicing solution comprises the following components: sucrose, NaCl, NaHCO3、MgCl2Glucose, KCl and NaH2PO4
And slicing the cultured brain tissue sample to obtain the sample slice.
3. The method of claim 2, wherein the performance indicators of the chemical substances in the cells are sucrose, NaCl, NaHCO3、MgCl2Glucose, KCl and NaH2PO4Comprises the following chemical components in percentage by weight: 200mM, 30mM, 26mM, 1mM, 10mM, 4.5mM and 1.2mM, the contents being in order of chemical composition.
4. The method of claim 2, wherein the section of the sample has a thickness of 300 μm.
5. The method of claim 1, further comprising analyzing the MS data by: and extracting the ion intensity of the metabolite in the MS data to obtain a change value between the isotope-labeled metabolite and the non-isotope-labeled metabolite according to the ion intensity of the metabolite.
6. The method of claim 1, further comprising analyzing the electrophysiological data by: the variation of the excitatory postsynaptic current is obtained from the average value of 60-90 light-excited excitatory postsynaptic currents in the electrophysiological data.
7. The method of claim 1, further comprising analyzing western blot data by: extracting protein bands in the western blot data, and calculating a target gray value according to the protein bands;
and adjusting the protein band according to the comparison between the target gray value and a preset gray threshold value.
8. The method of claim 1, further comprising analyzing immunofluorescence data according to the method comprising: and obtaining the quantity of the fluorescently-labeled NeuN protein according to the immunofluorescence data.
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Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1571848A (en) * 2001-09-05 2005-01-26 普赖德普罗特奥米克斯公司 Proteins in type 2 diabetes
US20060105322A1 (en) * 2003-06-30 2006-05-18 Ajinomoto Co., Inc. Intracellular metabolic flux analysis method using substrate labeled with isotope
CN101031793A (en) * 2005-06-07 2007-09-05 松下电器产业株式会社 Apparatus for measuring the electrical physiology of cells and a method for manufacturing the same
CN101484806A (en) * 2006-05-17 2009-07-15 协乐民公司 Method for automated tissue analysis
CN102911938A (en) * 2012-08-03 2013-02-06 华侨大学 siRNA (si Ribonucleic Acid) sequence for targeted restrain of POLD1 genetic expression
CN105784991A (en) * 2016-05-25 2016-07-20 南昌德漫多科技有限公司 Device and method for repeated immunostaining of same tissue section
CN105899953A (en) * 2013-11-05 2016-08-24 新加坡科技研究局 Bladder carcinoma biomarkers
US9759709B1 (en) * 2016-09-16 2017-09-12 The Florida International University Board Of Trustees Devices and methods to monitor HIV-infection in presence of substance of abuse and/or therapeutic agent
CN110850094A (en) * 2019-11-22 2020-02-28 西安交通大学 Immunohistochemical double-label single-staining kit and use method and application thereof
CN111317830A (en) * 2019-12-24 2020-06-23 吉林大学 Research method of pharmacological effect of mangiferin on diabetes of mice
CN111575336A (en) * 2020-05-14 2020-08-25 华东理工大学 Method for acquiring metabolic flux of intracellular central carbon metabolic pathway under metabolic steady isotope unsteady state
CN111721862A (en) * 2020-06-12 2020-09-29 山西大学 Method for identifying depression energy metabolism abnormal pathway based on stable isotope tracing metabonomics
CN112462058A (en) * 2020-11-20 2021-03-09 上海交通大学 Circulating nerve cell detection kit and detection method

Patent Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1571848A (en) * 2001-09-05 2005-01-26 普赖德普罗特奥米克斯公司 Proteins in type 2 diabetes
US20060105322A1 (en) * 2003-06-30 2006-05-18 Ajinomoto Co., Inc. Intracellular metabolic flux analysis method using substrate labeled with isotope
CN101031793A (en) * 2005-06-07 2007-09-05 松下电器产业株式会社 Apparatus for measuring the electrical physiology of cells and a method for manufacturing the same
CN101484806A (en) * 2006-05-17 2009-07-15 协乐民公司 Method for automated tissue analysis
CN102911938A (en) * 2012-08-03 2013-02-06 华侨大学 siRNA (si Ribonucleic Acid) sequence for targeted restrain of POLD1 genetic expression
CN105899953A (en) * 2013-11-05 2016-08-24 新加坡科技研究局 Bladder carcinoma biomarkers
CN105784991A (en) * 2016-05-25 2016-07-20 南昌德漫多科技有限公司 Device and method for repeated immunostaining of same tissue section
US9759709B1 (en) * 2016-09-16 2017-09-12 The Florida International University Board Of Trustees Devices and methods to monitor HIV-infection in presence of substance of abuse and/or therapeutic agent
CN110850094A (en) * 2019-11-22 2020-02-28 西安交通大学 Immunohistochemical double-label single-staining kit and use method and application thereof
CN111317830A (en) * 2019-12-24 2020-06-23 吉林大学 Research method of pharmacological effect of mangiferin on diabetes of mice
CN111575336A (en) * 2020-05-14 2020-08-25 华东理工大学 Method for acquiring metabolic flux of intracellular central carbon metabolic pathway under metabolic steady isotope unsteady state
CN111721862A (en) * 2020-06-12 2020-09-29 山西大学 Method for identifying depression energy metabolism abnormal pathway based on stable isotope tracing metabonomics
CN112462058A (en) * 2020-11-20 2021-03-09 上海交通大学 Circulating nerve cell detection kit and detection method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
刘池波等: "蛋白质组学技术在胃癌诊断中的应用及临床意义", 《中国热带医学》 *
王宁: "适量UV照射对脑内谷氨酸合成新通路的影响", 《中国博士学位论文全文数据库 基础科学辑》 *

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