KR102661415B1 - Biomarker composition for diagnosis of ferumoxytol magnetic nanoparticles toxicity in endocrine system - Google Patents

Abstract

The present invention relates to one or more genes and proteins selected from the group consisting of insulin receptor substrate (IRS), glucose transporter (GLUT; Solute carrier family), and glycogen synthetase kinase (GSK). Peruvian order, including one or more amino acids selected from the group consisting of valine (Val), methionine (Met), phenylalanine (Phe), leucine (Leu) and lysine (Lys). The present invention relates to a biomarker composition for diagnosing the endocrine toxicity of ferumoxitol magnetic nanoparticles, which causes changes in expression upon exposure to sitol magnetic nanoparticles, and an analysis method for analyzing the same.
Biomarkers according to the present invention are gene, protein, and amino acid markers that are highly correlated with the toxicity of nanoparticles. Using these, endocrine toxicity caused by magnetic nanoparticles can be diagnosed with excellent detection sensitivity and accuracy, through which magnetic nanoparticles can be diagnosed with endocrine toxicity. It is useful in monitoring or evaluating the endocrine hazards of nanoparticles and can be useful as a tool to identify endocrine diseases or health effects caused by exposure to magnetic nanoparticles.

Description

Biomarker composition for diagnosis of ferumoxytol magnetic nanoparticles toxicity in endocrine system}

The present invention relates to a biomarker composition for diagnosing endocrine toxicity of ferumoxitol magnetic nanoparticles and its use in a diagnostic method using the same. More specifically, it relates to insulin receptor substrate (IRS), glucose transporter ( Expression of genes and proteins of the glucose transporter, GLUT; Solute carrier family) and glycogen synthetase kinase (GSK) families, as well as valine (Val), methionine (Meth), and phenylalanine (Phe). , Biomarker composition for diagnosing endocrine toxicity caused by magnetic nanomaterials with high accuracy without false negatives by combining changes in metabolites including Leucine (Leu) and Lysine (Lys), and diagnosis using the same It is about its use in the method.

As nanotechnology develops, nanomaterials are being used in a variety of ways, not only in industrial fields but also in everyday life, including medical and research purposes. In particular, as magnetic nanomaterials are used in a variety of ways in daily life, including in the pharmaceutical field, such as magnetic resonance imaging (MRI), contact with nanomaterials is a common occurrence in modern society, not only for workers in related fields but also for the general public. It can be seen that this happens frequently.

While the many useful uses of nanomaterials in industrial fields and daily life are attracting attention, it is also well known that nanomaterials have potential risks due to their properties. The smaller the particle size, the higher the specific surface area ratio, which results in strong chemical reaction activity within biological tissues. Existing literature data and academic experiments show that some nanoparticles, such as titanium dioxide and carbon nanomaterials, become smaller in size. Accordingly, it has been proven that the reaction activity increases and the toxicity to the living body, such as the increase in oxygen radicals and the induction of inflammatory reactions, becomes stronger. In addition, some fine nanomaterials can pass through the primary biological defenses such as airway mucosa and skin as well as the blood-brain barrier (BBB) and be transported to the brain, including the lungs and other biological organs. Claims that this accumulation in the body can cause various diseases and adverse effects on the central nervous system are being raised in academia based on theoretical interpretations and experimental results.

Despite the trend in academia suggesting the potential risks of nanomaterials, biological indicators and experimental methods to evaluate them depend on some biological tissues or fragmented experimental methods, so they do not have special effects depending on each biological tissue. There were limitations that could not be reflected, so the present inventors and others developed a method to present biological indicators for functional changes in metabolites and cells using an approach using the Systems biological analysis method in evaluating the safety of nanomaterials, Korean Patent Registration No. The invention of No. 10-1470692 (Patent Document 1) has been applied for and registered, and in Patent Document 1, "Gene Bank (Genebank) NM_001161504.1 (ALDH4H1, aldehyde dehydrogenase 4 family member A1), Gene Registration Number ( Genebank) NM_133443.2 (GPT2, glutamic-pyruvate transaminase 2), gene registration number (Genebank) NM_005271.3 (GLUD1, glutamate dehydrogenase 1), gene registration number (Genebank) NM_002080.2 (GOT2, glutamic oxaloacetic transaminase 2), Containing a nucleic acid sequence coating a polynucleotide capable of detecting gene registration number (Genebank) NM_013445.3 (GAD1, glutamic acid decarboxylase 1) and gene registration number (Genebank) NM_002065.5 (GLUL, glutamate ammonia ligase). , discloses a “biomarker composition for diagnosing the toxicity of nanoparticles, which is characterized by causing expression changes due to exposure to nanoparticles.” However, the most advanced known conventional technology as described above is only about a biomarker composition for diagnosing the toxicity of nanoparticles containing a nucleic acid sequence capable of detecting a specific gene, especially as a contrast agent for diagnosing diseases and for the purpose of treatment. Established biological biomarkers for the effects on the biological endocrine system by magnetic nanomaterials, which are suggested to have high utility in drug delivery systems, have not been standardized.

Patent Document 1: Republic of Korea Patent Registration No. 10-1470692

Therefore, the present invention was made in consideration of the technical problems in the prior art, and the main purpose of the present invention is to approach the safety evaluation of magnetic nanoparticles on the biological endocrine system, including the systems biological analysis method and the results derived therefrom. We aim to present genes, proteins, and metabolites as biological indicators to determine functional changes in endocrine cells.

Another object of the present invention is to provide its use in a diagnostic method using a biomarker composition for determining functional changes in endocrine cells that achieves the above-mentioned specific purpose.

The biomarker composition for diagnosing endocrine toxicity of ferumoxitol magnetic nanoparticles of the present invention to achieve the above object is:

Gene registration number (GeneBank) NM_005544.3 (IRS1, Homo sapiens Insulin receptor substrate 1), Gene registration number (GeneBank) NM_003749.3 (IRS2, Homo sapiens Insulin receptor substrate 2), Gene registration number (GeneBank) NM_003604.2 ( Homo sapiens Insulin receptor substrate 4), gene registration number (GeneBank) NM_010570.4 (Irs1, Mus musculus Insulin receptor substrate 1), gene registration number (GeneBank) NM_001081212.2 (Irs2, Mus musculus Insulin receptor substrate 2), gene registration Number (GeneBank) NM_010571.3 (Irs3, Mus musculus Insulin receptor substrate 3), Gene registration number (GeneBank) NM_010572.2 (Irs4, Mus musculus Insulin receptor substrate 4), Gene registration number (GeneBank) NM_006516.4 (SLC2A1, Homo sapiens solute carrier family 2 member 1), gene registration number (GeneBank) NM_006931.3 (SLC2A3, Homo sapiens solute carrier family 2 member 3), gene registration number (GeneBank) NM_001042.3 (SLC2A4, Homo sapiens solute carrier family 2 member 4), gene registration number (GeneBank) NM_030777.4 (SLC2A10, Homo sapiens solute carrier family 2 member 10), gene registration number (GeneBank) NM_145176.3 (SLC2A12, Homo sapiens solute carrier family 2 member 12), gene registration Number (GeneBank) NM_011400.3(Slc2a1, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 1), Gene registration number (GeneBank) NM_031197.2(Slc2a2, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 2 ), gene registration number (GeneBank) NM_011401.4 (Slc2a3, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 3), gene registration number (GeneBank) NM_009204.2 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose) transporter) member 4, transcript variant 1), gene registration number (GeneBank) NM_001359114.1 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 4, transcript variant 2), gene registration number (GeneBank) NM_019741.3 (Slc2a5, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 5), gene registration number (GeneBank) NM_130451.3 (Slc2a10, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 10), gene registration number (GeneBank) ) NM_178934.4 (Slc2a12, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 12), gene registration number (GeneBank) NM_001033633.3 (Slc2a13, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 13), gene Registration number (GeneBank) NM_019884.3 (GSK3A, Homo sapiens glycogen synthase kinase 3 alpha), Gene registration number (GeneBank) NM_002093.4 (GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 1), Gene registration number (GeneBank) NM_001146156.2(GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 2), Gene registration number (GeneBank) NM_001354596.2(GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 3) , Gene registration number (GeneBank) NM_001031667.1 (Gsk3a, Mus musculus glycogen synthase kinase 3 alpha), Gene registration number (GeneBank) NM_019827.7 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 1), Gene registration number (GeneBank) NM_001347232.1 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 2), which contains one or more genes selected from the group consisting of feumoxitol magnetic nanoparticles, causing expression changes. Do this.

The microarray chip for diagnosing the endocrine toxicity of ferumoxitol magnetic nanoparticles of the present invention to achieve the above other objectives includes one or more genes selected from the biomarkers to diagnose endocrine toxicity caused by the magnetic nanoparticles. the entire nucleic acid sequence; Fragment oligonucleotides of the gene nucleic acid sequence of the biomarker; Alternatively, it is characterized in that all or part of the complementary gene sequence of the biomarker is integrated.

In addition, the present invention for achieving the above other object is characterized by providing a kit for diagnosing endocrine toxicity of ferumoxitol magnetic nanoparticles including the microarray chip.

According to another configuration of the present invention, the method for evaluating whether the endocrine toxicity of the ferumoxitol magnetic nanoparticles of the present invention is:

Obtaining tissue and cell samples from non-human mammals exposed to ferumoxitol magnetic nanoparticles; Gene registration number (GeneBank) NM_005544.3 (IRS1, Homo sapiens Insulin receptor substrate 1), Gene registration number (GeneBank) NM_003749.3 (IRS2, Homo sapiens Insulin receptor substrate 2), Gene registration number (GeneBank) NM_003604.2 ( Homo sapiens Insulin receptor substrate 4), gene registration number (GeneBank) NM_010570.4 (Irs1, Mus musculus Insulin receptor substrate 1), gene registration number (GeneBank) NM_001081212.2 (Irs2, Mus musculus Insulin receptor substrate 2), gene registration Number (GeneBank) NM_010571.3 (Irs3, Mus musculus Insulin receptor substrate 3), Gene registration number (GeneBank) NM_010572.2 (Irs4, Mus musculus Insulin receptor substrate 4), Gene registration number (GeneBank) NM_006516.4 (SLC2A1, Homo sapiens solute carrier family 2 member 1), gene registration number (GeneBank) NM_006931.3 (SLC2A3, Homo sapiens solute carrier family 2 member 3), gene registration number (GeneBank) NM_001042.3 (SLC2A4, Homo sapiens solute carrier family 2 member 4), gene registration number (GeneBank) NM_030777.4 (SLC2A10, Homo sapiens solute carrier family 2 member 10), gene registration number (GeneBank) NM_145176.3 (SLC2A12, Homo sapiens solute carrier family 2 member 12), gene registration Number (GeneBank) NM_011400.3(Slc2a1, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 1), Gene registration number (GeneBank) NM_031197.2(Slc2a2, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 2 ), gene registration number (GeneBank) NM_011401.4 (Slc2a3, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 3), gene registration number (GeneBank) NM_009204.2 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose) transporter) member 4, transcript variant 1), gene registration number (GeneBank) NM_001359114.1 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 4, transcript variant 2), gene registration number (GeneBank) NM_019741.3 (Slc2a5, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 5), gene registration number (GeneBank) NM_130451.3 (Slc2a10, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 10), gene registration number (GeneBank) ) NM_178934.4 (Slc2a12, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 12), gene registration number (GeneBank) NM_001033633.3 (Slc2a13, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 13), gene Registration number (GeneBank) NM_019884.3 (GSK3A, Homo sapiens glycogen synthase kinase 3 alpha), Gene registration number (GeneBank) NM_002093.4 (GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 1), Gene registration number (GeneBank) NM_001146156.2(GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 2), Gene registration number (GeneBank) NM_001354596.2(GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 3) , Gene registration number (GeneBank) NM_001031667.1 (Gsk3a, Mus musculus glycogen synthase kinase 3 alpha), Gene registration number (GeneBank) NM_019827.7 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 1), Gene registration number (GeneBank) NM_001347232.1 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 2): examining the expression of one or more genes in the group; and comparing the expression level of the gene with the control group.

In addition, according to another configuration of the present invention, the method for evaluating whether the endocrine toxicity of the ferumoxitol magnetic nanoparticles of the present invention is:

Obtaining tissue and cell samples from non-human mammals exposed to ferumoxitol magnetic nanoparticles; Gene registration number (GeneBank) NM_005544.3 (IRS1, Homo sapiens Insulin receptor substrate 1), Gene registration number (GeneBank) NM_003749.3 (IRS2, Homo sapiens Insulin receptor substrate 2), Gene registration number (GeneBank) NM_003604.2 ( Homo sapiens Insulin receptor substrate 4), gene registration number (GeneBank) NM_010570.4 (Irs1, Mus musculus Insulin receptor substrate 1), gene registration number (GeneBank) NM_001081212.2 (Irs2, Mus musculus Insulin receptor substrate 2), gene registration Number (GeneBank) NM_010571.3 (Irs3, Mus musculus Insulin receptor substrate 3), Gene registration number (GeneBank) NM_010572.2 (Irs4, Mus musculus Insulin receptor substrate 4), Gene registration number (GeneBank) NM_006516.4 (SLC2A1, Homo sapiens solute carrier family 2 member 1), gene registration number (GeneBank) NM_006931.3 (SLC2A3, Homo sapiens solute carrier family 2 member 3), gene registration number (GeneBank) NM_001042.3 (SLC2A4, Homo sapiens solute carrier family 2 member 4), gene registration number (GeneBank) NM_030777.4 (SLC2A10, Homo sapiens solute carrier family 2 member 10), gene registration number (GeneBank) NM_145176.3 (SLC2A12, Homo sapiens solute carrier family 2 member 12), gene registration Number (GeneBank) NM_011400.3(Slc2a1, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 1), Gene registration number (GeneBank) NM_031197.2(Slc2a2, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 2 ), gene registration number (GeneBank) NM_011401.4 (Slc2a3, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 3), gene registration number (GeneBank) NM_009204.2 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose) transporter) member 4, transcript variant 1), gene registration number (GeneBank) NM_001359114.1 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 4, transcript variant 2), gene registration number (GeneBank) NM_019741.3 (Slc2a5, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 5), gene registration number (GeneBank) NM_130451.3 (Slc2a10, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 10), gene registration number (GeneBank) ) NM_178934.4 (Slc2a12, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 12), gene registration number (GeneBank) NM_001033633.3 (Slc2a13, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 13), gene Registration number (GeneBank) NM_019884.3 (GSK3A, Homo sapiens glycogen synthase kinase 3 alpha), Gene registration number (GeneBank) NM_002093.4 (GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 1), Gene registration number (GeneBank) NM_001146156.2(GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 2), Gene registration number (GeneBank) NM_001354596.2(GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 3) , Gene registration number (GeneBank) NM_001031667.1 (Gsk3a, Mus musculus glycogen synthase kinase 3 alpha), Gene registration number (GeneBank) NM_019827.7 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 1), Gene registration number (GeneBank) Investigating the expression of one or more proteins encoded in the gene group consisting of NM_001347232.1 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 2); and comparing the expression level of the protein with a control group.

According to another configuration of the present invention, the toxicity evaluation method includes; (a) analyzing the content of one or more of the metabolites of valine (Val), methionine (Methionine, Met), phenylalanine (Phe), leucine (Leu), and lysine (Lysine); (b) analyzing changes in insulin secretion due to glucose stimulation; and (c) analyzing intracellular insulin vesicles by selecting one or more from the group; and (d) comparing to a control group.

The biological indicators of the present invention comprised as described above are biomarkers that have a high correlation with endocrine toxicity caused by magnetic nanoparticles. Using them, endocrine toxicity caused by magnetic nanoparticles can be accurately confirmed with excellent detection sensitivity and low false negatives. Through this, it can be usefully used as a tool to monitor and evaluate the harmfulness of magnetic nanoparticles and to identify biological and environmental effects caused by exposure to magnetic nanoparticles, thereby eliminating all the problems required in the above-mentioned conventional technology. It also provides useful effects that solve the problem.

Figure 1 shows the results of examining cell feeding efficiency and cytotoxicity of magnetic nanoparticles. Figure 1a: Observation of feeding efficiency in endocrine cell lines according to magnetic nanoparticle concentration; Figure 1b: Observation of proliferation rate of endocrine cell lines according to treatment time and concentration of magnetic nanoparticles; and Figure 1c: Observation of survival rate of endocrine cell lines according to treatment time and concentration of magnetic nanoparticles.
Figure 2 shows the results of gene expression analysis of an endocrine cell line treated with magnetic nanoparticles. Figure 2a: Results of analysis of gene expression changes through microarray experiment; and Figure 2b: Schematic illustration of gene expression distribution according to magnetic nanoparticle treatment concentration.
Figure 3 shows the results of verifying the results derived from the microarray experiment using molecular biological techniques. Figure 3a: Qualitative evaluation results of insulin, IRS, GSK, and GLUT gene expression using PCR and electrophoresis experiments; and Figure 3b: Quantitative evaluation results of insulin, IRS, GSK, and GLUT gene expression using Realtime-PCR experimental technique.
Figure 4 shows the results of protein expression analysis of endocrine cell lines treated with magnetic nanoparticles. Figure 4a: Results of analysis of protein expression changes using a protein chip; and Figure 4b: Schematic illustration of protein expression distribution according to magnetic nanoparticle treatment concentration.
Figure 5 shows the results of verifying the results derived from an experiment using a protein chip using molecular biological techniques. Figure 5a: Qualitative evaluation results of insulin, IRS, GSK, and GLUT protein expression using protein inhalation method; and Figure 5b: Quantitative evaluation results of insulin, IRS, GSK and GLUT protein expression.
Figure 6 shows the results of analyzing commonly changed genes and proteins by applying microarray and protein chip analysis data to the KEGG (Kyoto Encyclopedia of Genes and Genomes) database.
Figure 7 shows the results of analyzing changes in amino acid content of endocrine cell lines treated with magnetic nanoparticles using GC-MS (Gas Chromatography and Mass Spectrometry).
Figure 8 shows the results of analyzing changes in insulin secretion due to glucose stimulation in an endocrine cell line treated with magnetic nanoparticles using the glucose-stimulated insulin secretion (GSIS) analysis method.
Figure 9 shows the results of electron microscopy analysis of insulin vesicles from an endocrine cell line treated with magnetic nanoparticles.
Figure 10 is a schematic diagram showing the overall mechanism of change due to treatment of magnetic nanoparticles in an endocrine cell line according to the present invention.

Hereinafter, the present invention will be described in more detail through preferred embodiments. However, it goes without saying that the scope of the present invention is not limited thereto.

In this specification, the embodiments are provided to ensure that the disclosure of the present invention is complete and to fully convey the scope of the invention to those skilled in the art to which the present invention pertains, and that the scope of the present invention is defined only by the claims. It is only defined by . Accordingly, in some embodiments, well-known components, well-known operations and well-known techniques are not specifically described in order to avoid ambiguous interpretation of the present invention.

The terms used herein are for describing embodiments and are in no way intended to limit the invention. As used herein, singular forms also include plural forms unless specifically stated otherwise in the context. Additionally, components and operations referred to as 'including (or, including)' do not exclude the presence or addition of one or more other components and operations.

Terms used in the claims and specification are defined as set forth below, unless otherwise specified. Additionally, if any term or symbol used in this specification is not defined as set forth below, it will have its ordinary meaning in the art.

The practice of the invention involves the use of routine techniques in organic chemistry, molecular biology (including recombinant techniques), microbiology, cell biology, biochemistry and immunology that are within the skill of the art.

As used in this specification and the appended claims, in the context of describing elements, and especially in the context of the claims, the singular and the like refer to the singular and the singular unless otherwise indicated herein or the context clearly contradicts. It should be interpreted as including plural protons. References to ranges of values herein are merely intended to serve as shorthand for individually referring to each individual value falling within the range, including the upper and lower limits of the range, unless otherwise indicated herein. Individual values of are incorporated into this specification as if individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context.

The present invention includes one or more genes selected from the group consisting of insulin receptor substrate (IRS), glucose transporter (GLUT; Solute carrier family), and glycogen synthetase kinase (GSK). Provides a biomarker composition for diagnosing the toxicity of nanoparticles, which is characterized in that it causes expression changes due to exposure to nanoparticles.

The magnetic nanoparticles of the present invention may be any nanoparticle that can respond to magnetism or has its own magnetic force. Depending on the purpose of use, it may be used as nanoparticles included in pharmaceutical compositions, nanoparticles included as a material for chemical products, or biological experiments. This may include nanoparticles, etc. included in the composition for the purpose, but is not limited thereto, and of course, there are no restrictions on the composition form, components, or materials.

The insulin receptor material includes Gene Bank (GeneBank) NM_005544.3 (IRS1, Homo sapiens Insulin receptor substrate 1), Gene Bank (GeneBank) NM_003749.3 (IRS2, Homo sapiens Insulin receptor substrate 2), Gene Registration Number ( GeneBank) NM_003604.2 (Homo sapiens Insulin receptor substrate 4), gene registration number (GeneBank) NM_010570.4 (Irs1, Mus musculus Insulin receptor substrate 1), gene registration number (GeneBank) NM_001081212.2 (Irs2, Mus musculus Insulin receptor substrate 2), gene registration number (GeneBank) NM_010571.3 (Irs3, Mus musculus Insulin receptor substrate 3), gene registration number (GeneBank) NM_010572.2 (Irs4, Mus musculus Insulin receptor substrate 4), glucose transporter, GLUT) include gene registration number (GeneBank) NM_006516.4 (SLC2A1, Homo sapiens solute carrier family 2 member 1), gene registration number (GeneBank) NM_006931.3 (SLC2A3, Homo sapiens solute carrier family 2 member 3), gene registration number (GeneBank) NM_001042.3 (SLC2A4, Homo sapiens solute carrier family 2 member 4), Gene registration number (GeneBank) NM_030777.4 (SLC2A10, Homo sapiens solute carrier family 2 member 10), Gene registration number (GeneBank) NM_145176.3 (SLC2A12, Homo sapiens solute carrier family 2 member 12), Gene registration number (GeneBank) NM_011400.3 (Slc2a1, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 1), Gene registration number (GeneBank) NM_031197.2 ( Slc2a2, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 2), gene registration number (GeneBank) NM_011401.4 (Slc2a3, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 3), gene registration number (GeneBank) NM_009204.2 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 4, transcript variant 1), gene registration number (GeneBank) NM_001359114.1 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 4 , transcript variant 2), gene registration number (GeneBank) NM_019741.3 (Slc2a5, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 5), gene registration number (GeneBank) NM_130451.3 (Slc2a10, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 10), gene registration number (GeneBank) NM_178934.4 (Slc2a12, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 12), gene registration number (GeneBank) NM_001033633.3 (Slc2a13, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 13), glycogen synthetase kinase (GSK), gene registration number (GeneBank) NM_019884.3 (GSK3A, Homo sapiens glycogen synthase kinase 3 alpha), gene registration Number (GeneBank) NM_002093.4 (GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 1), Gene registration number (GeneBank) NM_001146156.2 (GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 2 ), gene registration number (GeneBank) NM_001354596.2 (GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 3), gene registration number (GeneBank) NM_001031667.1 (Gsk3a, Mus musculus glycogen synthase kinase 3 alpha), With gene registration number (GeneBank) NM_019827.7 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 1) and gene registration number (GeneBank) NM_001347232.1 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 2). Any one selected from the group consisting of is preferred, but is not limited thereto.

In one embodiment of the present invention, the gene registration number (GeneBank) NM_010570.4 (Irs1, Mus musculus Insulin receptor substrate 1) and the gene registration number (GeneBank) NM_009204.2 (Slc2a4, Mus musculus solute carrier) shown in the biomarker composition by magnetic nanoparticles in a gene group that essentially includes at least one family 2 (facilitated glucose transporter) member 4, transcript variant 1) and gene registration number (GeneBank) NM_001031667.1 (Gsk3a, Mus musculus glycogen synthase kinase 3 alpha). Genetic changes in endocrine cell lines were confirmed, but are not limited to the presented biomarker composition.

In one embodiment of the present invention, a total of 276 genes, including 124 genes with increased expression and 152 genes with decreased expression, were classified in the experimental group treated with high concentration of magnetic nanoparticles, and the changed gene group was applied to the database. Thus, changes in the expression of insulin receptor substrate (IRS), glucose transporter (GLUT; Solute carrier family), and glycogen synthetase kinase (GSK), which are related to the biological mechanism of the endocrine system, were derived. The expression change usually refers to an expression change state of 1.5 times or more or 0.5 times or less of the expression amount, and when expression changes of the genes are observed compared to the control group, it is evaluated that magnetic nanoparticles may cause toxicity to the endocrine system. do.

More specifically, the insulin receptor substrate (IRS) gene whose expression is reduced due to magnetic nanoparticles is gene registration number (GeneBank) NM_005544.3 (IRS1, Homo sapiens insulin receptor substrate 1), gene registration number (GeneBank) ) NM_003749.3 (IRS2, Homo sapiens Insulin receptor substrate 2), gene registration number (GeneBank) NM_003604.2 (Homo sapiens Insulin receptor substrate 4), gene registration number (GeneBank) NM_010570.4 (Irs1, Mus musculus Insulin receptor substrate 1), gene registration number (GeneBank) NM_001081212.2 (Irs2, Mus musculus Insulin receptor substrate 2), gene registration number (GeneBank) NM_010571.3 (Irs3, Mus musculus Insulin receptor substrate 3) and gene registration number (GeneBank) NM_010572 This may include the .2 (Irs4, Mus musculus Insulin receptor substrate 4) gene, and the glucose transporter (GLUT) and glycogen synthetase kinase (GSK) whose expression increases due to magnetic nanoparticles. Genes include gene registration number (GeneBank) NM_006516.4 (SLC2A1, Homo sapiens solute carrier family 2 member 1), gene registration number (GeneBank) NM_006931.3 (SLC2A3, Homo sapiens solute carrier family 2 member 3), gene registration number (GeneBank) NM_001042.3 (SLC2A4, Homo sapiens solute carrier family 2 member 4), Gene registration number (GeneBank) NM_030777.4 (SLC2A10, Homo sapiens solute carrier family 2 member 10), Gene registration number (GeneBank) NM_145176.3 (SLC2A12, Homo sapiens solute carrier family 2 member 12), Gene registration number (GeneBank) NM_011400.3 (Slc2a1, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 1), Gene registration number (GeneBank) NM_031197.2 ( Slc2a2, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 2), gene registration number (GeneBank) NM_011401.4 (Slc2a3, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 3), gene registration number (GeneBank) NM_009204.2 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 4, transcript variant 1), gene registration number (GeneBank) NM_001359114.1 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 4 , transcript variant 2), gene registration number (GeneBank) NM_019741.3 (Slc2a5, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 5), gene registration number (GeneBank) NM_130451.3 (Slc2a10, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 10), gene registration number (GeneBank) NM_178934.4 (Slc2a12, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 12), gene registration number (GeneBank) NM_001033633.3 (Slc2a13, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 13), gene registration number (GeneBank) NM_019884.3 (GSK3A, Homo sapiens glycogen synthase kinase 3 alpha), gene registration number (GeneBank) NM_002093.4 (GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 1), gene registration number (GeneBank) NM_001146156.2(GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 2), gene registration number (GeneBank) NM_001354596.2(GSK3B , Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 3), gene registration number (GeneBank) NM_001031667.1 (Gsk3a, Mus musculus glycogen synthase kinase 3 alpha), gene registration number (GeneBank) NM_019827.7 (Gsk3b, Mus This may include the musculus glycogen synthase kinase 3 beta, transcript variant 1) and gene registration number (GeneBank) NM_001347232.1 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 2) genes.

In addition, the present invention relates to the entire nucleic acid sequence of one or more genes selected from the group consisting of the above biomarkers; Fragment oligonucleotides of the gene nucleic acid sequence of the biomarker; Provided is a diagnostic microarray chip in which all or part of the complementary gene sequence of the biomarker is integrated.

The oligonucleotide; Or its complementary strand molecule is 15 to 50 of the biomarker genes; preferably 15 to 30; More preferably, it contains 18 to 25 nucleic acids.

The microarray chip for diagnosing endocrine toxicity of magnetic nanoparticles according to the present invention can be manufactured by methods known to those skilled in the art. For example, in order to immobilize the searched genetic marker on the substrate of a DNA chip using a probe DNA molecule, a micropipetting method using a piezoelectric method or a pin-type spotter ( It is desirable to use a method using a spotter, but it is not limited to this. The substrate of the microarray chip is preferably coated with one active group selected from the group consisting of amino-silane, poly-L-lysine, and aldehyde, but is limited thereto. It doesn't work. Additionally, the substrate may be selected from the group consisting of slide glass, plastic, metal, silicon, nylon film, and nitrocellulose film, but is not limited thereto.

Additionally, the present invention provides a kit for diagnosing endocrine toxicity of magnetic nanoparticles including the microarray chip.

In addition, the kit may contain additional fluorescent substances, such as a group consisting of strepavidin-alkaline dephosphatase conjugate, chemifluorescence, and chemiluminescent. It is preferable to be selected from, but is not limited to.

In addition, the kit may include additional reaction reagents, which include a buffer solution used for hybridization, reverse transcriptase for synthesizing cDNA from RNA, cNTPs and rNTPs (premixed or separately supplied), and chemical fluorescent dye. It may consist of a labeling reagent such as an inducer, a washing buffer solution, etc., but is not limited thereto, and may include all reaction reagents required for the hybridization reaction of a microarray chip known to those skilled in the art.

The present invention provides a kit for diagnosing endocrine toxicity of magnetic nanoparticles containing a complementary primer pair capable of amplifying the biomarker gene. Here, ‘complementary’ means more than 80% homology in the primer base sequence; Preferably, it is a concept that means there is 100% homology. The primer pair has a biomarker gene amplification product of 100 to 300 bp; Preferably, it refers to a pair of forward and reverse primers with a length of 15 to 50 mer designed to be 100 to 200 bp.

In addition, the kit may contain additional reaction reagents, which include reverse transcriptase for synthesizing cDNA from RNA, cNTPs and rNTPs (premixed or separately supplied), labeling reagents such as chemical inducers of fluorescent dyes, and washing. It may consist of a buffer solution, etc., but is not limited thereto, and may include all reaction reagents necessary for RT-PCR reaction known to those skilled in the art.

In one embodiment of the present invention, the gene registration number (GeneBank) NM_010570.4 (Irs1, Mus musculus Insulin receptor substrate 1) and the gene registration number (GeneBank) NM_009204.2 (Slc2a4, Mus musculus solute carrier) shown in the biomarker composition Magnetic nanoparticles from a group of gene expression proteins that essentially contain at least one family 2 (facilitated glucose transporter) member 4, transcript variant 1) and gene registration number (GeneBank) NM_001031667.1 (Gsk3a, Mus musculus glycogen synthase kinase 3 alpha) Changes in the expression of proteins in endocrine cell lines were confirmed, but are not limited to the presented biomarker composition.

In one embodiment of the present invention, a total of 125 proteins, including 79 proteins with increased expression and 46 proteins with decreased expression, were classified in the experimental group treated with high concentration of magnetic nanoparticles, and the changed protein group was applied to the database. Thus, changes in the expression of insulin receptor substrate (IRS), glucose transporter (GLUT), and glycogen synthetase kinase (GSK), which are related to the biological mechanisms of the endocrine system, were derived. The expression change usually refers to an expression change of 1.5 times or more or 0.5 times or less than the expression amount, and if a change in the expression of the entire protein or polypeptide is observed compared to the control group, the magnetic nanoparticles may cause toxicity to the endocrine system. Evaluate that you can.

More specifically, the insulin receptor substrate (IRS) protein whose expression is reduced due to magnetic nanoparticles is gene registration number (GeneBank) NM_005544.3 (IRS1, Homo sapiens insulin receptor substrate 1), gene registration number (GeneBank) ) NM_003749.3 (IRS2, Homo sapiens Insulin receptor substrate 2), gene registration number (GeneBank) NM_003604.2 (Homo sapiens Insulin receptor substrate 4), gene registration number (GeneBank) NM_010570.4 (Irs1, Mus musculus Insulin receptor substrate 1), gene registration number (GeneBank) NM_001081212.2 (Irs2, Mus musculus Insulin receptor substrate 2), gene registration number (GeneBank) NM_010571.3 (Irs3, Mus musculus Insulin receptor substrate 3) and gene registration number (GeneBank) NM_010572 This may include proteins or polypeptides derived from and expressed in .2 (Irs4, Mus musculus Insulin receptor substrate 4), and glucose transporter (GLUT) and glycogen synthase phosphatase whose expression increases due to magnetic nanoparticles. (glycogen synthetase kinase, GSK) proteins include gene registration number (GeneBank) NM_006516.4 (SLC2A1, Homo sapiens solute carrier family 2 member 1), gene registration number (GeneBank) NM_006931.3 (SLC2A3, Homo sapiens solute carrier family 2) member 3), gene registration number (GeneBank) NM_001042.3 (SLC2A4, Homo sapiens solute carrier family 2 member 4), gene registration number (GeneBank) NM_030777.4 (SLC2A10, Homo sapiens solute carrier family 2 member 10), gene registration Number (GeneBank) NM_145176.3 (SLC2A12, Homo sapiens solute carrier family 2 member 12), Gene registration number (GeneBank) NM_011400.3 (Slc2a1, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 1), Gene registration number (GeneBank) NM_031197.2(Slc2a2, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 2), Gene registration number (GeneBank) NM_011401.4(Slc2a3, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 3) , Gene registration number (GeneBank) NM_009204.2 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 4, transcript variant 1), Gene registration number (GeneBank) NM_001359114.1 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 4, transcript variant 2), gene registration number (GeneBank) NM_019741.3(Slc2a5, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 5), gene registration number (GeneBank) NM_130451.3( Slc2a10, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 10), gene registration number (GeneBank) NM_178934.4 (Slc2a12, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 12), gene registration number (GeneBank) NM_001033633.3 (Slc2a13, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 13), gene registration number (GeneBank) NM_019884.3 (GSK3A, Homo sapiens glycogen synthase kinase 3 alpha), gene registration number (GeneBank) NM_002093. 4 (GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 1), gene registration number (GeneBank) NM_001146156.2 (GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 2), gene registration number ( GeneBank) NM_001354596.2 (GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 3), gene registration number (GeneBank) NM_001031667.1 (Gsk3a, Mus musculus glycogen synthase kinase 3 alpha), gene registration number (GeneBank) All proteins derived from and expressed in NM_019827.7 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 1) and gene registration number (GeneBank) NM_001347232.1 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 2) Or, polypeptides may fall into this category.

In addition, the present invention provides an entire antibody structure capable of specifically reacting with one or more proteins or polypeptides selected from the group consisting of the above biomarkers; Alternatively, a diagnostic protein chip on which part of the antibody structure is integrated is provided. The specific reactive antibody may be a monoclonal antibody; polyclonal antibodies; and special antibodies such as humanized antibodies are included in the present invention, and can be manufactured through a conventional production method by those skilled in the art, or commercially available off-the-shelf products can be used. For example, conventional antiserum production methods; And it can be produced by a conventional method of producing an antibody using a protein obtained by cloning all or part of the coating of the gene into an expression vector, but is not limited to this.

The protein chip for diagnosing endocrine toxicity of magnetic nanoparticles according to the present invention can be manufactured by methods known to those skilled in the art or can be manufactured in-house using the user's own technology.

In addition, the present invention provides the protein chip; The specific reactive antibody; and a kit for diagnosing the toxicity of magnetic nanoparticles containing a secondary antibody.

In addition, the specific reactive antibody and secondary antibody provided in the kit may contain a direct reactive group, for example, alkaline phosphatase (AP) or horseradish peroxidase (HRP). It is preferable to be selected from the group consisting of, but is not limited thereto.

Additionally, the kit may include additional reaction reagents, which may include a hybridization solution to induce an antigen-antibody reaction, a shielding solution to inhibit non-specific reactions, a labeling reagent such as a chemical inducer of a fluorescent dye, and a washing buffer solution. It may consist of, but is not limited to, all reagents required for reaction in protein chips and protein blotting (Western-blotting) known to those skilled in the art.

Additionally, the present invention includes obtaining tissue and cell samples from mammals exposed to magnetic nanoparticles; Examining the expression of one or more genes in the group consisting of insulin receptor substrate (IRS), glucose transporter (GLUT; Solute carrier family), and glycogen synthetase kinase (GSK); and comparing the expression level of the gene with a control group.

According to one embodiment of the present invention, 1) isolating RNA from biological tissues and cells exposed to magnetic nanoparticles as an experimental group; 2) synthesizing cDNA using RNA isolated from the experimental and control groups in step 1) while labeling them with different fluorescent substances; 3) hybridizing the labeled cDNA of step 2) with the microarray chip of the present invention; and 4) endocrine toxicity of magnetic nanoparticles can be evaluated by analyzing the microarray chip reacted in step 3) and comparing the level of gene expression with the control group.

According to another embodiment of the present invention, 1) isolating RNA from biological tissues and cells exposed to magnetic nanoparticles as an experimental group; 2) Performing real-time RT-PCR (Reverse transcript polymerase chain reaction) on the RNA isolated from the experimental and control groups in step 1) using a primer pair complementary to the biomarker gene of the present invention; and 3) the endocrine toxicity of magnetic nanoparticles can be evaluated by quantitatively comparing and analyzing the gene products of step 2) in the experimental and control groups.

More specifically, the expression of the insulin receptor substrate (IRS) gene decreases, and the expression of the glucose transporter (GLUT; Solute carrier family) or glycogen synthetase kinase (GSK) gene increases. In this case, magnetic nanoparticles can be evaluated as toxic to the endocrine system.

According to another embodiment of the present invention, 1) isolating proteins or polypeptides from biological tissues and cells exposed to magnetic nanoparticles as an experimental group; 2) biotinylating the protein or polypeptide isolated from the experimental group and control group in step 1); 3) hybridizing the proteins and polypeptides of step 2 with the protein chip of the present invention; 4) treating the protein chip hybridized in step 3) with a probe material to cause a luminescence reaction; and 5) endocrine toxicity of magnetic nanoparticles can be evaluated by analyzing the protein chip reacted in step 4) and comparing the experimental group and the control group.

According to another embodiment of the present invention, 1) isolating proteins or polypeptides from biological tissues and cells exposed to magnetic nanoparticles as an experimental group; 2) performing a protein absorption method on the protein or polypeptide isolated from the experimental group and control group in step 1) using an antibody that specifically reacts with the biomarker of the present invention; and 3) the endocrine toxicity of magnetic nanoparticles can be evaluated by quantitatively comparing and analyzing the results of step 2) in the experimental and control groups.

More specifically, the expression of insulin receptor substrate (IRS) protein or polypeptide is decreased, and the expression of glucose transporter (GLUT; Solute carrier family) or glycogen synthetase kinase (GSK) protein or polypeptide is decreased. If the expression of is increased, the magnetic nanoparticles can be assessed as having endocrine toxicity.

In another embodiment of the present invention, when evaluating the endocrine toxicity of the magnetic nanoparticles, the content of one or more of the metabolites of valine, methionine, phenylalanine, leucine, and lysine is analyzed; Analysis of changes in insulin secretion due to glucose stimulation; and analyzing intracellular insulin vesicles by selecting one or more from the group to investigate; And it may further include a step of comparing with a control group.

More specifically, the content analysis of one or more of the metabolites of valine (Val), methionine (Methionine, Met), phenylalanine (Phe), leucine (Leu), and lysine (Lysine) was performed using GC-MS analysis. It can be measured through, and if one or more metabolites selected from valine, methionine, and phenylalanine decrease, or one or more metabolites selected from leucine and lysine increase, it can be assessed that endocrine toxicity of magnetic nanoparticles exists.

In addition, more specifically, the change in insulin secretion due to glucose stimulation can be analyzed by measuring the change in insulin secretion in cell samples sequentially treated with low and high concentrations of glucose using ELISA (Enzyme linked) using an antibody that specifically reacts to insulin. It can be measured through immunoassay analysis, and if the change in insulin secretion due to the difference in glucose concentration decreases compared to the control group, the magnetic nanoparticles can be assessed as having endocrine toxicity.

In addition, more specifically, intracellular insulin vesicles can be analyzed through an electron microscope, and as shown in Figure 9 of the present invention, if insulin is not stored in the insulin vesicles, it can be assessed that the endocrine toxicity of the magnetic nanoparticles exists. .

Experiment example

The following experimental examples are intended to provide experimental examples commonly applied to each embodiment according to the present invention.

[Experimental Example 1] Cell culture and treatment of magnetic nanoparticles

MIN-6, a mouse-derived cell line, is a representative insulin-secreting cell line and can precisely reflect the characteristics of endocrine cells depending on the culture environment, including sugar concentration. Therefore, the endocrine toxicity of magnetic nanoparticles was evaluated for this cell line. Cells contained 10% fetal bovine serum (FBS, Gibco, USA), 100 units/ml penicillin, 100 μg/mL streptomycin (Gibco, USA), and 100 μM β-mercaptoethanol (Sigma-Aldrich, USA). The cells were cultured using RPMI1640 (Gibco, USA) medium at 37°C under 90% humidity and 5% CO ₂ atmospheric conditions. MIN-6 cells were distributed at a concentration of 1×10 ⁶ cells/100mm and treated with magnetic nanoparticles at concentrations of 0.01, 0.1, and 1.0μg/mL under culture conditions that excluded serum and antibiotics. The cells of the control group, which were not treated with magnetic nanoparticles, and the cells of the experimental group, which were treated with magnetic nanoparticles for 24 hours, were each washed twice with PBS (phosphate buffered saline) and washed with 0.25% trypsin/0.1% EDTA (GIBCO, USA). collected after use.

[Experimental Example 2] Isolation and purification of RNA

RNA from control cells and cells treated with magnetic nanoparticles was isolated and purified using TRIzol (Sigma-Aldrich, USA) and RNeasy kit (Qiagen, USA) in parallel. More specifically, the cells collected in [Experimental Example 1] were treated with 1 mL of TRIzol, then chloroform was added and left at 4°C for 5 minutes. Total RNA was precipitated using 600 μL isopropanol, and the precipitated RNA pellet was washed once each with 80% and 70% ethanol, and then RNA was eluted using RNase-free water treated with DEPC (Diethyl Pyrocarbonate). Quantitative-qualitative evaluation was performed using NanoDrop (Thermo Science, USA) and electrophoresis. For microarray and PCR experiments, RNA with an optical density (O.D.) of 260/230 and 260/280 of 1.9 to 2.0 was used, and low-purity RNA was purified using an RNeasy kit according to the manufacturer's manual.

[Experimental Example 3] Semi-q and real-time RT-PCR

The RNA sample was reverse-transcribed into cDNA using a reverse-transcription kit and then amplified with a primer pair that could specifically bind to each gene. The amplified PCR product was separated according to size by electrophoresis using a 1.0% agarose gel, stained with a nucleic acid staining reagent, and then quantified using image analysis software. For more accurate quantification of gene expression levels, gene amplification was performed using primer pairs capable of gene-specific binding, SYBR Green Real-time PCR kit, and DNA Engine (Bio-Rad, USA), and MJ Opticon Monitor Version 3.1 ( It was analyzed using Bio-Rad, USA).

[Experimental Example 4] Microarray and data analysis

In order to construct a gene expression profile according to magnetic nanoparticle treatment, RNA isolated was hybridized to a microarray chip in the manner of [Experimental Example 2]. More specifically, 20 μg of labeled RNA was hybridized to a Mouse Gene 2.0 ST Array (Affymetrix, USA) microarray chip containing 698,000 gene-specific probes, and washed multiple times using a washing solution. After washing, the hybridized microarray chip was scanned through a scanner, and analyzed through Transcriptome Analysis Console (TAC) Software (Thermo Fisher Scientific, USA) to examine changes in gene expression.

Hereinafter, the present invention will be described in detail by examples. However, the following examples illustrate the present invention, but the content of the present invention is not limited to the following examples.

In the following examples, ferumoxytol (Feraheme, AMAG Pharmaceuticals, USA), which is used as an MR imaging nano contrast agent for clinical application in the diagnosis of various diseases including diabetes, was used as the magnetic nanoparticle.

[Example 1]

Ferumoxitol was used to evaluate its effect on pancreatic β cells. Various concentrations of ferumoxitol were added directly to the serum-free culture medium, and MIN-6 cells were cultured in medium containing ferumoxitol for 12 hours. The cells were then washed with phosphate-buffered saline (PBS, GIBCO, USA) and 3,3'-diaminobenzidine (DAB)-enhanced Prussian blue staining was performed on MIN-6 cells in ferumoxitol. Labeling efficiency was evaluated. The cells were treated with a reagent prepared by mixing equal volumes of hydrochloric acid and potassium ferrocyanide solution, and then treated with a DAB solution of an appropriate concentration to produce strong Prussian blue staining. Cell images were taken using a contrast microscope and an image capture system.

[Example 2]

To assess cell viability, MTS assay was performed using a chromogenic assay kit according to the manufacturer's protocol. Briefly, MIN-6 cells were cultured in 96-well plates and treated with various concentrations of ferumoxitol for 12, 24, and 48 hours. After each hour of incubation, 20 μL of MTS solution was added to each well of the plate containing 100 μL of culture medium, and the assay plate was left at 37°C for 4 hours. Absorbance was then measured using a GloMax-Multi Plus detection system at 490 nm and signal values were normalized to background. The proliferation rate of cells was assessed using Alamar Blue staining according to the manufacturer's protocol. Cells were cultured in 48-well plates and treated with ferumoxitol at various concentrations. After 24, 48, and 72 hours, the concentrated Alamar Blue solution was added directly to each well and then allowed to react at 37°C for 4 hours while shielded from light. Fluorescence intensity was measured at 570/585 nm (excitation/emission) and signal values were normalized to background.

[Example 3]

Transmission electron microscopy (TEM) and magnetic resonance (MR) image observation

To observe intracellular organelles by TEM, cells were collected using 0.25% trypsin/0.1% EDTA and washed twice with PBS. Cells were then fixed with Karnofsky fixation solution (1% paraformaldehyde, 2% glutaraldehyde, 2mM calcium chloride) for 24 h and washed with cacodylate buffer. After fixation, the cells were reacted for 90 minutes in a 1% osmium tetroxide (OsO ₄ ) solution containing 0.05% potassium ferrocyanide (K ₄ Fe(CN) ₆ ). Afterwards, cells were sectioned using Reichert Jung Ultracul S. Cells were stained with uranyl acetate and lead citrate, observed using TEM (JEM-1400, JEOL Ltd., Japan), and photographs were taken. Permoxitol-labeled MIN-6 cells were observed with a 7-T Magnetic Resonance (MR) imaging system (Bruker-Biospin, Swiss) and ParaVision software (Ver. 5.0, Bruker-Biospin, Swiss). To observe the relationship between MR and optical images, cells were set at 1Х ⁵ cells/group in 3.0% agarose gel and photographed using a digital camera.

[Example 4]

RNA extraction and microarray analysis

RNA was isolated from ferumoxitol-treated and untreated MIN-6 cells and purified for microarray and PCR experiments. The isolated RNA was quantified by spectrophotometry (Eppendorf, Germany) and BioAnalyzer (Agilent, USA). RNA purities ranging from 1.9 to 2.0 depending on the ratio of optical density (O.D.) at 260/230 and 260/280 were used for microarray and PCR experiments. Microarrays were performed using a gene chip (Mouse Gene 2.0 ST Array) to construct transcriptional profiling. After hybridizing the dye-labeled RNA product overnight, the reaction chip was washed several times and images were scanned with a microarray chip scanner (Affymetrix, USA). Differentiated expressed gene (DEG) data sets were generated with a cutoff of 2.0-fold expression change.

[Example 5]

Semi-qRT and Real-time PCR experiment analysis

To quantify the transcription level of genes, the isolated RNA was reverse transcribed using a reverse transcription system (GenDEPOT, USA). These cDNA products were amplified using gene-specific primer pairs for semi-qRT and real-time PCR analysis. The amplified semi-qRT PCR products were separated on a 1% agarose gel, and the intensity of the electrophoretic bands was calculated using Multi Gauge 3.0 software (Fujifilm, Japan). Real-time PCR was performed using a commercial kit (iNtRON Biotechnology, Republic of Korea) and ABI Prism 7000 (Applied Biosystems, USA). The threshold cycle (Ct) was determined as the point at which the fluorescence value was significantly higher than the background level, and the data were analyzed by generating a melting curve using 7000 System SDS software (Applied Biosystems, USA). Relative quantification of transcription was assessed using the 2 ^-ddCt method.

[Example 6]

Antibody-based protein chip and protein absorption method analysis

To establish protein expression profiling, antibody-based protein arrays were performed using a commercial service following the manufacturer's guide. Briefly, harvested cells were washed with PBS and homogenized in lysis buffer for 10 min. After measuring the protein concentration by BCA analysis, these samples were incubated with biotin labeling reagent for protein biotinylation and hybridized to the array previously treated with the reagent for 12 hours. The array was then reacted with streptavadin-conjugated peroxidase and the substrate was added to the array membrane for development into film. After data scanning and analysis, spot signals were normalized using positive and negative control spots from each array. For protein adsorption, proteins were separated using a poly-acrylamide gel and transferred to a poly-vinylidene difluoride (PVDF, Thermo Fisher Scientific, USA) membrane. After blocking with 2% bovine serum albumin (BSA) solution, the membranes were treated with the respective primary antibodies overnight at 4°C. Afterwards, the membrane was washed with PBS containing Tween-20 and incubated with secondary goat anti-rabbit antibody (Santa Cruz Biotechnology, USA). Enhanced chemiluminescent (ECL) solution was added to the membrane and exposed to film for visualization of the bands. Intensity data were calculated and analyzed with image analysis software.

[Example 7]

Gas chromatography-mass spectrometry (GC-MS) for amino acid profiling

Samples were derivatized with N-methyl-trimethylsilyltrifluoroacetamide (MSTFA) to establish amino acid profiling using GC-MS. After the derivatization procedure, the samples were analyzed using an Agilent GC-MS system (Agilent, USA) interfaced with a gas chromatograph and mass selective detector. Helium as a carrier gas flowed in constant flow mode with the sample through the stationary stage of the capillary column, and the oven temperature was set at an increment rate of 5°C min from 150°C to 300°C. The mass of the amino acid was confirmed by comparison with the retention time and coefficient of the internal standard. Selected amino acids (e.g. valine, methionine, phenylalanine, leucine, and lysine) in cells treated with ferumoxitol were normalized to the average value of the control and depicted in the diagram.

[Example 8]

Glucose-Stimulated Insulin Secretion (GSIS) Analysis

To evaluate the insulin secretory function of MIN-6 cells, GSIS was performed using glucose concentrations of 60 and 300 mg/dL. Briefly, MIN-6 cells were cultured in insert well plates (Merck Millipore, USA) at 1Х10 ⁴ cells per well and incubated in Krebs-Ringer buffer (KRB) for 90 min at 37°C with 60 mg/dL glucose. ; 129mM NaCl, 4.8mM KCl, 2.5mM CaCl ₂ , 1.2mM KH ₂ PO ₄ , 5mM NaHCO ₃ , 10mM HEPES and 0.2% BSA). After pre-incubation and washing with PBS, cells were further incubated with 60 mg/dL glucose-KRB for 1 h, and cells were incubated with 300 mg/dL glucose-KRB for 1 h. Insulin secretion into the supernatant was measured using a commercial ELISA kit, and the stimulation index was expressed as the ratio of stimulated insulin release with 300 mg/dL glucose-KRB and basal insulin release with 60 mg/dL glucose-KRB.

statistical analysis

Statistical differences between experimental groups were post hoc tested with Tukey Honestly Significant Difference (HSD) along with one-way analysis of variance (ANOVA) using GraphPad Prism 5 (GraphPad Software, USA). These data were obtained from an independent set of experiments and are expressed as mean ± standard deviation (SD). Statistical differences between groups were determined at p -value ≤ 0.05.

Results and Discussion

Labeling efficiency and MR imaging detection of ferumoxitol-treated MIN-6 cells

In this study, ferumoxitol is a representative magnetic nanoparticle that has previously been approved for clinical application by the FDA as an iron supplement for anemia, so it was used as a representative nanoparticle to evaluate the effect of magnetic nanoparticles on pancreatic β cells. MIN-6, a mouse pancreatic β-cell line, was treated with 0.01, 0.1, and 1.0 mg/mL of ferumoxitol for 12 hours, and cell labeling efficiency was evaluated using DAB-enhanced Prussian blue staining. As shown in Figure 1a, the absorption of ferumoxitol increased significantly in a dose-dependent manner. Additionally, cytoplasmic accumulation of ferumoxitol was detected in MIN-6 cells treated with 1.0 mg/mL feumoxitol, but no accumulation was detected in the nucleus. To evaluate MRI sensitivity, MIN-6 cells were labeled with increasing doses of ferumoxitol, cell pellets were captured in agarose plates, and images were acquired using a 7-T MR imaging system under T2 ^* weighting conditions. At 1.0 mg/mL, cells were maximally labeled by ferumoxitol, providing sharp contrast according to T2 ^* weighted MR images, whereas no contrast was visible in the control group. Taken together, these data suggest that high-dose ferumoxitol induces increased labeling efficiency for MR detection in MIN-6 cells, but also shows cytoplasmic accumulation, which is likely to affect cellular activity.

Evaluation of proliferation and survival rates of ferumoxitol-treated MIN-6 cells

To evaluate the cell proliferation and survival rates of the β-cell line, MTS and Alamar Blue staining analyzes were performed with MIN-6 cells treated with various doses of ferumoxitol. Analysis of the cell proliferation rate showed a significant decrease in the experimental groups treated with 1.0 and 0.1 mg/mL ferumoxitol for long periods of 48 and 72 hours (Figure 1b). In contrast, cells treated with 0.01 mg/mL ferumoxitol showed no detectable change in cell proliferation rate at any time period examined and were similar to the control group. In the evaluation of cell viability excluding cell proliferation, no significant cell death was detected in the experimental group treated with 0.01 mg/mL ferumoxitol until 48 hours of culture, and the survival rate was similar to that of the control and DMSO-treated groups (Figure 1c) ). However, MIN-6 cells exposed to 0.1 and 1.0 mg/mL ferumoxitol showed a significant decrease in cell viability after 48 hours of culture. Therefore, MIN-6 cells treated with ferumoxitol showed a direct correlation between cell viability and treatment dose and time. These data show that high doses of ferumoxitol can be used for β-cell labeling within 24 hours without affecting cell proliferation and survival rates. However, β cells are stored for long periods of time (e.g. When treated with ferumoxitol (more than 48 hours), it shows that ferumoxitol can affect cell proliferation and survival rates not only at high doses but also at medium doses.

Transcriptome profiling of ferumoxitol-treated MIN-6 cells.

Cellular evaluation data suggest that high doses of ferumoxitol can be administered for appropriate incubation times, e.g. It has been shown that it can be applied for labeling and MR imaging detection of β cells without negative effects on cell survival and proliferation when used in combination with up to 12 hours). However, because these cellular assessments were insufficient to identify nanotoxicity at the gene transcription level, we used an oligonucleotide microarray system to construct a transcriptome profile induced by ferumoxitol treatment in MIN-6 cells. We investigated the transcriptional changes that occur. Low-dose, medium-dose, and high-dose ferumoxitol treatment groups represent MIN-6 cells treated with 0.01, 0.1, and 1.0 mg/mL ferumoxitol for 12 hours, respectively. After normalizing the signal intensity, DEG analysis was performed using the Expression Console™Software v1.4 (Thermo Fisher Scientific, USA) program. Of the total 35,240 functional probes, 277 probed for transcriptional changes in ferumoxitol-treated MIN-6 cells (Figure 2A). 124 and 152 functional probes were up- and down-expressed in the 1.0 mg/mL ferumoxitol group compared to the control group, respectively. By comparing the expression profiles of the feumoxitol-treated group and the control group, genes showing significant changes in response to feumoxitol treatment were identified. A comparative correlation plot to distinguish between up- and down-expression showed a higher differential expression rate in the experimental group treated with 1.0 mg/mL ferumoxitol compared to both the 0.1 mg/mL ferumoxitol group and control cells (Figure 2b). . The correlation of differential expression rates showed a correlation coefficient of 0.85 in the 1.0 mg/mL ferumoxitol administration group, and 0.94 and 0.93 in the 0.01 and 0.1 mg/mL ferumoxitol administration groups, respectively. As can be seen from these data, even when ferumoxitol is used at an appropriate culture time that does not have a significant adverse effect on cell survival and proliferation, treatment with 1.0 mg/mL ferumoxitol can cause transcriptome perturbation in β-cell lines. I was able to confirm that it was there.

Based on the microarray analysis results, semi qRT-PCR was performed using specific primer pairs for the genes that showed significant changes in the 1.0 mg/mL ferumoxitol experimental group to evaluate the transcription levels of these insulin signaling pathway-related genes ( Figure 3a). In the experimental group treated with 1.0 mg/mL ferumoxitol, the transcript levels of insulin and IRS1 decreased compared to the control group, while the transcript levels of GSK3 and GLUT4 increased. However, no significant changes were observed in these genes in the ferumoxitol 0.01 mg/mL treatment group compared to the control group. Real-time PCR analysis performed for accurate calculation of transcriptional changes showed similar transcriptional trends as semi-qRT PCR and transcriptome profiling. The transcription levels of insulin and IRS1 in the group administered 1.0 mg/mL ferumoxitol were lower than 50% of those in the control group (Figure 3b). Conversely, GSK3 and GLUT4 increased statistically significantly in the experimental group treated with ferumoxitol 1.0 mg/mL, while the group treated with ferumoxitol 0.01 mg/mL showed no significant change compared to the control group.

As a result of multifaceted transcriptome analysis, it was found that high-dose ferumoxitol induced transcriptome disruption of genes related to the insulin signaling pathway in β cells. IRS1 is known as a signaling protein involved in intracellular signaling in insulin. Additionally, GSK3 plays an important role in negative feedback regulation of insulin signaling through the phosphorylation pathway of serine 332 in IRS1. GLUT4 is a member of the insulin-regulated glucose transporter and contributes to glucose flow and glycolysis for cellular homeostasis. Additionally, because these genes are closely related to insulin action and glucose metabolism, insulin stimulation and impaired glucose homeostasis by high-dose ferumoxitol may be caused through transcriptome disruption of the insulin signaling pathway in β cells.

Proteomic profiling of ferumoxitol-treated MIN-6 cells.

To correlate the transcriptome profiling results with the translation step of the protein, proteomic profiling was performed by antibody-based protein chip analysis on MIN-6 cells treated with various doses of ferumoxitol (Figure 4a). Normalizing the spot signal intensity to the internal control spot showed that 125 out of 864 custom probes significantly changed the translation of peptides in the 1.0 mg/mL ferumoxitol-treated group compared to the control group, with 79 and 46 probe spots, respectively. Up- and down-regulation was confirmed in this 1.0 mg/mL ferumoxitol-treated group. Correlation analysis of differential protein expression between the ferumoxitol-treated group and the control group showed that the expression of a significant number of proteins was altered in the 1.0 mg/mL ferumoxitol-treated group compared to the other experimental groups and the control group (Figure 4b). . Compared to the control group, the experimental group treated with 1.0 mg/mL ferumoxitol showed a correlation coefficient of 0.68, while the correlation coefficients of the experimental groups treated with 0.01 and 0.1 mg/mL ferumoxitol remained at 0.89 and 0.86, respectively.

To verify the proteomic profiling results, cell lysates from the experimental and control groups were subjected to protein uptake analysis and protein expression levels were quantified and calculated using Multi Gauge 3.0 software. As a result, insulin and IRS1 proteins were significantly decreased depending on the dose. It was found that Translation of insulin protein showed a dramatic decrease of 68.5 and 73.7% in the ferumoxitol 0.1 mg/mL and 1.0 mg/mL groups, respectively, compared to the control group. Additionally, even at the lowest dose of 0.01 mg/mL, insulin decreased by 49.4%. In the groups administered ferumoxitol 0.1 and 1.0 mg/mL, the translation level of IRS1 decreased by 62.9% and 80.3%, respectively, compared to the control group, whereas no change in expression was observed in the group administered feumoxitol 0.01 mg/mL. On the contrary, in the group administered 1.0 mg/mL ferumoxitol, the translation of GSK3 and GLUT4 significantly increased to 509.9 and 51.1% compared to the control group. However, at low doses (e.g. 0.01 and 0.1 mg/mL), no significant changes were observed. Comparing changes in the insulin signaling pathway based on the above profiling results, it was confirmed that high concentrations of ferumoxitol can disturb the expression of related transcripts and proteomes in a similar manner (Table 1).

Comparison of transcriptional and translational expression of microarrays and protein arrays. item Transcriptome profiling ^a Proteomic profiling
low concentration ^b medium concentration high concentration low concentration ^b medium concentration high concentration insulin 0.981 0.897 0.429 0.717 0.305 0.143 IRS1 ^b 1.237 1.059 0.315 1.069 0.536 0.124 GSK3 1.036 0.989 3.156 1.203 1.192 2.157 GLUT4 1.282 1.234 2.058 0.891 1.182 3.159

a Relative values compared to ^the control group. ^b low concentration, 0.01 mg/mL; Medium concentration, 0.1 mg/mL; High concentration, 1.0 mg/mL. ^c IRS1, insulin receptor substrate 1; GSK3, glycogen synthase phosphorylase 3; GLUT4, glucose transporter type 4.

When the results derived from the transcriptome and proteome profiles were entered into the KEGG database, it was confirmed that the identified biomarkers were placed at important steps related to the overall insulin signaling pathway (Figure 6).

These results confirmed the findings that microarray and protein chip analyzes showed similar trends, and additionally, the combined results of transcriptomic and proteomic profiles showed that the cellular effects of high-dose ferumoxitol were related to insulin signaling pathway-related genes in β-cell lines. This shows that it can not only disrupt transcription but also limit the translation of these proteins.

Amino acid profiling of ferumoxitol-treated MIN-6 cells.

Amino acids are well known to be key components of nutrition and biocatalysis in cellular activities, and additionally, transcriptomic and proteomic profiling results show that several genes and proteins are associated with amino acid metabolic pathways, such as transamination, in high-dose ferumoxitol-treated cell lines. This appears to have changed.

To confirm changes in amino acid levels in treated cells, MIN-6 cells were treated with 0.1 and 1.0 mg/mL ferumoxitol and GC-MS analysis was performed on 17 amino acids. The amounts of amino acids changed in the control group and ferumoxitol-treated experimental group are listed in Table 2 below. Amino acid profiling results showed that lysine (1.76-fold) and leucine (2.28-fold) increased in cells treated with 1.0 mg/mL ferumoxitol, while arginine increased by 0.1 and 1.0 mg compared to the control group (1.32-fold and 1.44-fold, respectively). There was a gradual increase in all /mL doses. Additionally, methionine, phenylalanine, and valine decreased by 83.1, 55.3, and 91.4% in cells treated with 1.0 mg/mL ferumoxitol, whereas there was no significant change between the 0.1 mg/mL ferumoxitol treatment group and the control group. . Five amino acids (e.g. Selected GC-MS spectra of valine, methionine, phenylalanine, leucine, and lysine) also showed that these amino acids were significantly changed in cells treated with 0.1 mg/mL ferumoxitol ( Figure 7 ).

amino acid Detection capacity (ng/5Х10 ⁷ cell lysate) ratio ^a control group medium concentration ^b high concentration medium concentration high concentration leucine
212.59 ± 4.25
284.32 ± 4.87
486.71 ± 5.61
1.337
2.289 Lysine 1008.18 ± 135.64 1021.83 ± 77.70 1777.87 ± 61.28 1.014 1.763 methionine 116.83 ± 3.98 117.45 ± 5.09 19.79 ± 2.18 1.005 0.169 Phenylalanine 26.27 ± 1.07 23.95 ± 0.81 11.74 ± 2.29 0.912 0.447
Valine
130.75 ± 2.73
126.86 ± 5.86
11.19 ± 2.39
0.970
0.086

^a Detected values were normalized to the control group. ^b medium concentration, 0.01 mg/mL; High concentration, 1.0 mg/mL.

Amino acids play an important role in generating glucogenic or ketogenic precursors in the tricarboxylic acid (TCA) cycle reaction through the catabolism of the amino acid pathway. Leucine and lysine, which were increased in this amino acid profiling, are precursors of acetoacetic acid in the ketogenic cascade. Additionally, the amino acids reduced in this profiling, methionine and valine, are precursors of acetoacetic acid in the gluconeogenic cascade. Phenylalanine is the precursor of acetoacetate and fumarate in these two cascades. Therefore, since these amino acids are the main precursors of the TCA cycle reaction, we speculate that perturbation of amino acids may be a potential cause of ferumoxitol-induced TCA cycle reaction impairment in β-cell lines. However, further studies are needed to clearly elucidate the effects of ferumoxitol on TCA cycle response function and bioenergetic metabolism. In recent studies, several reports have demonstrated that impaired amino acid metabolism can lead to insulin resistance and type 2 diabetes mellitus (T2DM). Additionally, Lynch et al. It has been suggested that impaired branched-chain amino acid (BCAA) metabolism, such as leucine, isoleucine, and valine, is associated with insulin-resistant obesity and T2DM through activation of mTORC1 and phosphorylation of the IRS family. In this study, isoleucine and other BCAAs (e.g. leucine and valine) levels were varied, respectively. As presented in the transcriptomic and proteomic profiles, amino acid profiling results show that high-dose ferumoxitol can induce impairment of cellular processes related to glucose homeostasis, such as insulin activation and TCA cycle response, in β-cell lines.

Evaluation of insulin secretion activity and observation of small organelles in ferumoxitol-treated MIN-6 cells

As described above, through metabolic profiling evaluation, disturbances in genes and proteins related to the insulin signaling pathway and amino acids in β-cell lines treated with high-dose ferumoxitol were observed through transcriptome and proteome profiling (Figure 2, 3, 4, 5 and 7). Based on these profiling results, we hypothesized that treatment with ferumoxitol would affect insulin secretion when β cells were stimulated by glucose. To determine whether feumoxitol affects the insulin secretion of β cells, the insulin index of β cells was measured through glucose-stimulated insulin secretory (GSIS) assay analysis after ferumoxitol treatment. Compared to the control group, the insulin index was found to be significantly decreased in a dose-dependent manner at all doses, with a 58.9% decrease at 1.0 mg/mL ferumoxitol (Figure 8). Interestingly, although we assumed that the insulin index would decrease rapidly in cells treated with high-dose ferumoxitol, we observed a decrease in the insulin index of 31.3 and 50.8% at low and medium doses, respectively, despite no significant changes in the profiling results. It has been done. To explain this phenomenon, the entire cell body and insulin vesicles in MIN-6 cells treated with 1.0 mg/mL ferumoxitol were observed using a transmission electron microscope (TEM) (FIG. 9). As can be seen in the lower left panel of Figure 9, the cell membrane was collapsed in MIN-6 cells treated with 1.0 mg/mL ferumoxitol, whereas the control cells maintained the complex cell membrane structure. In addition to the cell membrane observations, insulin vesicles were emptied in MIN-6 cells treated with 1.0 mg/mL ferumoxitol, whereas vesicles in control cells were saturated with insulin (Figure 9, right panel). As a result of measuring the distribution of ferumoxitol in MIN-6 cells, feumoxitol aggregates of various sizes were located in the cytoplasm and small organs such as insulin vesicles.

The phenomenon of decreased insulin index in ferumoxitol-treated β-cell lines can be explained by two possibilities due to ferumoxitol intake: i) an indirect effect through disturbance of the composition of molecules and amino acids related to the insulin signaling pathway in β-cells; ii) This could be explained by the intercellular distribution of ferumoxitol and its direct effects through internalization into β-cell organelles (e.g. insulin vesicles). The schematic course of cellular events is illustrated in Figure 10. Previous reports have demonstrated that insulin response can be regulated by various biological factors, such as transcription of genes, translation of proteins, and metabolites. Disruption of transcription and translation of genes and proteins related to the insulin signaling pathway induced by high-dose ferumoxitol in β cells may affect insulin responses such as insulin biosynthesis and insulin feedback response. In addition to these molecular biological changes, changes in amino acid composition following high-dose ferumoxitol treatment may also be a factor that disrupts insulin secretion from β cells. Our profiling results demonstrate that high-dose ferumoxitol induces these comprehensive changes and leads to impairment of insulin response, including biosynthesis, feedback response, and secretion. Additionally, the experimental results presented in the present invention suggest that intercellular distribution and internalization of ferumoxitol may be a major factor in impaired insulin response. As a result of observing the internalization of ferumoxitol in β cells treated with high dose ferumoxitol by TEM, insulin was replaced by several feumoxitol aggregates in the insulin vesicles.

In the above example, a combination of transcriptomic, proteomic, and metabolic profiling analyzes was used to investigate the comprehensive effect of ferumoxitol on pancreatic β-cell lines. The results showed that ferumoxitol was effective in reducing insulin resistance in pancreatic β-cell lines at high doses. It was found that it statistically significantly altered secretory function and caused significant disturbances in insulin pathway genes, proteins, and metabolites. It was confirmed that genes and proteins related to the insulin signaling pathway, such as insulin, IRS1, GSK3, and GLUT4, were differentially expressed in pancreatic β-cell lines treated with high-dose ferumoxitol. Similar significant perturbations were observed in amino acid composition at high doses. As a result of treating pancreatic β-cell lines with a high dose of ferumoxitol, it was confirmed that the insulin secretion index was significantly reduced and the insulin in the insulin vesicles was also replaced with ferumoxitol. The intracellular processes of high-dose ferumoxitol include i) uptake of feumoxitol into β cells, ii) transcriptional and translational changes in insulin signaling-related pathways, iii) changes in amino acid metabolism, and iv) ferrumoxitol in insulin vesicles. Internalization of sitol, v) disturbance of insulin secretion and impaired glucose homeostasis have been suggested. The results of these examples suggest that determining biologically active doses is important for the therapeutic use of nanoparticles, and combined with the comprehensive evaluation methods of the above examples, the toxic effects of ferumoxitol and nanoparticles, particularly on pancreatic β-cells, are important. It can greatly contribute to the understanding of overall toxicity assessment.

As the specific parts of the present invention have been described in detail above, it is clear to those skilled in the art that these specific techniques are merely preferred embodiments and do not limit the scope of the present invention. will be. Accordingly, the substantial scope of the present invention will be defined by the appended claims and their equivalents.

Claims (7)

Gene registration number (GeneBank) NM_005544.3 (IRS1, Homo sapiens Insulin receptor substrate 1), Gene registration number (GeneBank) NM_003749.3 (IRS2, Homo sapiens Insulin receptor substrate 2), Gene registration number (GeneBank) NM_003604.2 ( Homo sapiens Insulin receptor substrate 4), gene registration number (GeneBank) NM_010570.4 (Irs1, Mus musculus Insulin receptor substrate 1), gene registration number (GeneBank) NM_001081212.2 (Irs2, Mus musculus Insulin receptor substrate 2), gene registration Number (GeneBank) NM_010571.3 (Irs3, Mus musculus Insulin receptor substrate 3), Gene registration number (GeneBank) NM_010572.2 (Irs4, Mus musculus Insulin receptor substrate 4), Gene registration number (GeneBank) NM_006516.4 (SLC2A1, Homo sapiens solute carrier family 2 member 1), gene registration number (GeneBank) NM_006931.3 (SLC2A3, Homo sapiens solute carrier family 2 member 3), gene registration number (GeneBank) NM_001042.3 (SLC2A4, Homo sapiens solute carrier family 2 member 4), gene registration number (GeneBank) NM_030777.4 (SLC2A10, Homo sapiens solute carrier family 2 member 10), gene registration number (GeneBank) NM_145176.3 (SLC2A12, Homo sapiens solute carrier family 2 member 12), gene registration Number (GeneBank) NM_011400.3(Slc2a1, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 1), Gene registration number (GeneBank) NM_031197.2(Slc2a2, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 2 ), gene registration number (GeneBank) NM_011401.4 (Slc2a3, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 3), gene registration number (GeneBank) NM_009204.2 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose) transporter) member 4, transcript variant 1), gene registration number (GeneBank) NM_001359114.1 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 4, transcript variant 2), gene registration number (GeneBank) NM_019741.3 (Slc2a5, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 5), gene registration number (GeneBank) NM_130451.3 (Slc2a10, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 10), gene registration number (GeneBank) ) NM_178934.4 (Slc2a12, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 12), gene registration number (GeneBank) NM_001033633.3 (Slc2a13, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 13), gene Registration number (GeneBank) NM_019884.3 (GSK3A, Homo sapiens glycogen synthase kinase 3 alpha), Gene registration number (GeneBank) NM_002093.4 (GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 1), Gene registration number (GeneBank) NM_001146156.2(GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 2), Gene registration number (GeneBank) NM_001354596.2(GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 3) , Gene registration number (GeneBank) NM_001031667.1 (Gsk3a, Mus musculus glycogen synthase kinase 3 alpha), Gene registration number (GeneBank) NM_019827.7 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 1), Gene registration number (GeneBank) NM_001347232.1 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 2), which contains one or more genes selected from the group consisting of feumoxitol magnetic nanoparticles and is characterized by causing expression changes by exposure to ferumoxitol magnetic nanoparticles. A biomarker composition for diagnosing endocrine toxicity of ferumoxitol magnetic nanoparticles. All of the nucleic acid sequences of one or more genes selected from the biomarkers of claim 1 for diagnosing endocrine toxicity caused by ferumoxitol magnetic nanoparticles; Fragment oligonucleotides of the gene nucleic acid sequence of the biomarker; Or, a microarray chip for diagnosing endocrine toxicity of ferumoxitol magnetic nanoparticles, characterized in that it integrates all or part of the complementary gene sequence of the biomarker. A kit for diagnosing endocrine toxicity of ferumoxitol magnetic nanoparticles, comprising the microarray chip of claim 2. Obtaining tissue and cell samples from non-human mammals exposed to ferumoxitol magnetic nanoparticles; Gene registration number (GeneBank) NM_005544.3 (IRS1, Homo sapiens Insulin receptor substrate 1), Gene registration number (GeneBank) NM_003749.3 (IRS2, Homo sapiens Insulin receptor substrate 2), Gene registration number (GeneBank) NM_003604.2 ( Homo sapiens Insulin receptor substrate 4), gene registration number (GeneBank) NM_010570.4 (Irs1, Mus musculus Insulin receptor substrate 1), gene registration number (GeneBank) NM_001081212.2 (Irs2, Mus musculus Insulin receptor substrate 2), gene registration Number (GeneBank) NM_010571.3 (Irs3, Mus musculus Insulin receptor substrate 3), Gene registration number (GeneBank) NM_010572.2 (Irs4, Mus musculus Insulin receptor substrate 4), Gene registration number (GeneBank) NM_006516.4 (SLC2A1, Homo sapiens solute carrier family 2 member 1), gene registration number (GeneBank) NM_006931.3 (SLC2A3, Homo sapiens solute carrier family 2 member 3), gene registration number (GeneBank) NM_001042.3 (SLC2A4, Homo sapiens solute carrier family 2 member 4), gene registration number (GeneBank) NM_030777.4 (SLC2A10, Homo sapiens solute carrier family 2 member 10), gene registration number (GeneBank) NM_145176.3 (SLC2A12, Homo sapiens solute carrier family 2 member 12), gene registration Number (GeneBank) NM_011400.3(Slc2a1, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 1), Gene registration number (GeneBank) NM_031197.2(Slc2a2, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 2 ), gene registration number (GeneBank) NM_011401.4 (Slc2a3, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 3), gene registration number (GeneBank) NM_009204.2 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose) transporter) member 4, transcript variant 1), gene registration number (GeneBank) NM_001359114.1 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 4, transcript variant 2), gene registration number (GeneBank) NM_019741.3 (Slc2a5, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 5), gene registration number (GeneBank) NM_130451.3 (Slc2a10, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 10), gene registration number (GeneBank) ) NM_178934.4 (Slc2a12, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 12), gene registration number (GeneBank) NM_001033633.3 (Slc2a13, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 13), gene Registration number (GeneBank) NM_019884.3 (GSK3A, Homo sapiens glycogen synthase kinase 3 alpha), Gene registration number (GeneBank) NM_002093.4 (GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 1), Gene registration number (GeneBank) NM_001146156.2(GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 2), Gene registration number (GeneBank) NM_001354596.2(GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 3) , Gene registration number (GeneBank) NM_001031667.1 (Gsk3a, Mus musculus glycogen synthase kinase 3 alpha), Gene registration number (GeneBank) NM_019827.7 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 1), Gene registration number (GeneBank) NM_001347232.1 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 2): examining the expression of one or more genes in the group; And a method for evaluating the endocrine toxicity of ferumoxitol magnetic nanoparticles, comprising the step of comparing the expression level of the gene with a control group. Obtaining tissue and cell samples from non-human mammals exposed to ferumoxitol magnetic nanoparticles; Gene registration number (GeneBank) NM_005544.3 (IRS1, Homo sapiens Insulin receptor substrate 1), Gene registration number (GeneBank) NM_003749.3 (IRS2, Homo sapiens Insulin receptor substrate 2), Gene registration number (GeneBank) NM_003604.2 ( Homo sapiens Insulin receptor substrate 4), gene registration number (GeneBank) NM_010570.4 (Irs1, Mus musculus Insulin receptor substrate 1), gene registration number (GeneBank) NM_001081212.2 (Irs2, Mus musculus Insulin receptor substrate 2), gene registration Number (GeneBank) NM_010571.3 (Irs3, Mus musculus Insulin receptor substrate 3), Gene registration number (GeneBank) NM_010572.2 (Irs4, Mus musculus Insulin receptor substrate 4), Gene registration number (GeneBank) NM_006516.4 (SLC2A1, Homo sapiens solute carrier family 2 member 1), gene registration number (GeneBank) NM_006931.3 (SLC2A3, Homo sapiens solute carrier family 2 member 3), gene registration number (GeneBank) NM_001042.3 (SLC2A4, Homo sapiens solute carrier family 2 member 4), gene registration number (GeneBank) NM_030777.4 (SLC2A10, Homo sapiens solute carrier family 2 member 10), gene registration number (GeneBank) NM_145176.3 (SLC2A12, Homo sapiens solute carrier family 2 member 12), gene registration Number (GeneBank) NM_011400.3(Slc2a1, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 1), Gene registration number (GeneBank) NM_031197.2(Slc2a2, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 2 ), gene registration number (GeneBank) NM_011401.4 (Slc2a3, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 3), gene registration number (GeneBank) NM_009204.2 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose) transporter) member 4, transcript variant 1), gene registration number (GeneBank) NM_001359114.1 (Slc2a4, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 4, transcript variant 2), gene registration number (GeneBank) NM_019741.3 (Slc2a5, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 5), gene registration number (GeneBank) NM_130451.3 (Slc2a10, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 10), gene registration number (GeneBank) ) NM_178934.4 (Slc2a12, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 12), gene registration number (GeneBank) NM_001033633.3 (Slc2a13, Mus musculus solute carrier family 2 (facilitated glucose transporter) member 13), gene Registration number (GeneBank) NM_019884.3 (GSK3A, Homo sapiens glycogen synthase kinase 3 alpha), Gene registration number (GeneBank) NM_002093.4 (GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 1), Gene registration number (GeneBank) NM_001146156.2(GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 2), Gene registration number (GeneBank) NM_001354596.2(GSK3B, Homo sapiens glycogen synthase kinase 3 beta (GSK3B) transcript variant 3) , Gene registration number (GeneBank) NM_001031667.1 (Gsk3a, Mus musculus glycogen synthase kinase 3 alpha), Gene registration number (GeneBank) NM_019827.7 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 1), Gene registration number (GeneBank) Investigating the expression of one or more proteins encoded in the gene group consisting of NM_001347232.1 (Gsk3b, Mus musculus glycogen synthase kinase 3 beta, transcript variant 2); And a method for evaluating endocrine toxicity of ferumoxitol magnetic nanoparticles, comprising the step of comparing the expression level of the protein with a control group. The method of claim 5, wherein the method for evaluating toxicity is; (a) analyzing the content of one or more of the metabolites of valine (Val), methionine (Methionine, Met), phenylalanine (Phe), leucine (Leu), and lysine (Lysine); (b) analyzing changes in insulin secretion due to glucose stimulation; and (c) analyzing intracellular insulin vesicles. The method of claim 6, wherein the method further includes the step of (d) comparing with a control group.