CN108120679B - Kit for predicting susceptibility of children to caries - Google Patents

Abstract

The invention relates to a kit capable of predicting whether children are susceptible to caries or not, which comprises maltose, alpha-methyl-D-galactoside, alpha-amygdalin, D, L-alpha-glycerophosphate, D-trehalose, 3-methyl-D-glucose, turanose, glycyl-L-proline, L-glutamine and glycyl-L-glutamine, wherein 10 carbon sources are counted in total, and the kit is used for predicting the caries risk of the children. The kit can be used in medical institutions and even at home, and can predict the risk of the caries before the caries is suffered by children, so that the caries can be prevented in advance, and the resources of the society for caries are greatly reduced.

Description

Kit for predicting susceptibility of children to caries

Technical Field

The invention relates to the technical field of oral medicine, in particular to the prediction of children caries risks.

Background

Caries (ECC) in young children, formerly known as bottle caries or feeding caries, is considered a worldwide problem in pediatrics and public health. This is a chronic disease occurring in children, which is best seen at 2-5 years of age, but is often overlooked by people. Children's treatment of dental caries is often difficult and costly. Treatment under general anesthesia and hospitals eligible for general anesthesia treatment are needed for the treatment of ECC.

Previous studies have focused on taxonomic bacterial diversity. While these studies provide us with a number of important grounds for the relationship between oral microorganisms and plaque, this limits our depth of understanding of the ecological associations of microbial communities. These studies are also mostly limited to theoretical analysis and do not directly transform the results into practical applications.

For analysis of microbial phenotypes, such as metabolism, a more thorough understanding of microbial community structure is possible. First, metabolic processes are key points in determining virulence characteristics of pathogenic microorganisms in the oral cavity. In addition, the internal coordinated nutrient metabolism increases the diversity in the bacterial community and is of great importance in maintaining the stability of the microbial community.

Analysis of a sample for Single Carbon Source Utilization (SCSU) patterns by Biolog (Biolog inc., Hayward, CA, USA) is a method for identifying non-autotrophic microorganisms on a functional basis. One plate contains several wells, each well containing tetrazolium violet and a minimal amount of a different proprietary growth medium (a single carbon source), and the development of a reaction that reduces tetrazolium violet by respiration of microbial cells is indicative of the metabolic status of the bacteria. The analysis technology has the characteristics of high sensitivity, strong resolution, no need of separation culture and the like, the microorganisms have selectivity on the utilization of carbon sources, and each microorganism has different utilization capacities on different carbon sources, so that the measurement of multiple SCSUs can obtain the metabolic characteristic fingerprint of a single microorganism or a microorganism community to be measured so as to identify different microorganisms (communities), and therefore the technology is often used for the measurement of environmental microorganisms such as soil microorganism detection, ecological environment reconstruction evaluation and the like.

In 2014, Zhang et al published a paper on PLOS ONE journal for determining the bacterial plaque microflora of patients with periodontitis by applying Biolog technology, wherein bacterial plaques of the subjects are collected, and 95 single carbon source utilization patterns are analyzed to obtain 14 single carbon sources capable of distinguishing periodontitis groups from healthy control groups.

However, there are no relevant research reports on the metabolic characteristics of microorganisms in the mouth of ECC patients and healthy people, and no practical products or methods based on the research are available. Although both caries and periodontitis are plaque-dependent diseases, relying only on existing models for detection of periodontitis and the corresponding conclusions does not help to obtain information about caries for reasons that include: periodontitis is not the same as the causative bacteria of caries; periodontitis and caries are mutually antagonistic and difficult to coexist; the metabolic profile fingerprints for different carbon sources are different for both periodontitis and caries; the processing of the test sample will also be different for both; the times at which the carbon source exhibits significant differences compared to healthy subjects or other parameters of the relevant model in the experiment and their optimal values will also differ.

As caries is one of oral diseases with the highest prevalence rate in human beings, the fourth national oral health epidemiological survey shows that the current caries situation in China is very optimistic, so that the research on the pathogenesis and pathogenic factors is not needed for caries of low-age children, and a product capable of conveniently predicting the risk of caries is also needed to help the whole society to actively prevent the caries.

Disclosure of Invention

In view of the above problems, the present invention aims to provide a kit for predicting susceptibility of a child to caries. The early-stage caries prevention system can be used in medical institutions and even at home, and can predict the risk of caries before children suffer from the caries, so that early prevention can be realized, and the resources of the society for caries are greatly reduced.

Specifically, the kit for predicting whether children are susceptible to caries comprises maltose, alpha-methyl-D-galactoside, alpha-amygdalin, D, L-alpha-glycerophosphate, D-trehalose, 3-methyl-D-glucose, turanose, glycyl-L-proline, L-glutamine and glycyl-L-glutamine, wherein 10 carbon sources are counted, and the kit is used for predicting the risk of caries of infants.

The whole kit is of a plate-shaped structure, holes for placing the carbon source and the color developing agent are formed in the plate, different carbon sources are placed in different holes, and the color developing agent is filled in each hole. Wherein the color developer is preferably tetrazolium violet.

The kit may also comprise a well containing water and a color-developing agent and/or a well with an empty interior as a reference.

For further convenience of use, the kit may also include a phosphate saline buffer. The phosphate physiological saline buffer solution is preferably 0.01mol/L phosphate buffer solution with the pH value of 7.2-7.4.

The kit is convenient to use in the whole design, and can accurately predict the caries risk of children.

Drawings

FIG. 1: mean color change (AWCD) in disease (- ● -) and control (- □ -) when cultured on Biolog anaerobic plates for 24, 48, 72, 96 hours. P < 0.05

FIG. 2: the metabolic patterns of the carbon source are different between the disease group (- ● -) and the control group (- □ -). P < 0.05X P < 0.01

FIG. 3: schematic diagram of cluster analysis based on differential carbon source between disease group (P) and control group (C) at 24 hours.

FIG. 4: the main component analysis of the disease group (. tangle-solidup.) and the control group (■) was performed using 10 different carbon sources obtained after 24 hours of culture as variables.

FIG. 5 is a schematic diagram of the structure of the kit.

Detailed Description

The present invention is further described below.

(I) an experimental subject

Subjects were recruited in a computer generated random number from children examined or treated at the child dental clinic, the second clinic department of the medical college of Beijing university, during the period 1/1 to 8/31/2014. All pediatric subject parents signed written informed consent before the study began. The inclusion criteria were: the age is 48-71 months; noninfectious, congenital periodontal disease or dental abscess; no antibiotics, fluoride-coated treatments or tooth extractions were used within one month prior to plaque collection.

In diagnosing caries, one worker's diagnostic standard was calibrated against another experienced colleague, and then all dental examinations were performed. The dental caries can be diagnosed by visual examination and probing examination with mouth mirror and dental probe. Clean teeth with cotton ball, but do not take X-ray film. The deciduous tooth caries loss index (dmft), the sum of the number of teeth in one person's mouth that develop caries, the number of teeth lost due to caries and the number of teeth on filling treatment due to caries, was evaluated based on the caries diagnostic criteria of the world health organization (1997). There are 5 or more carious children classified in the SECC group, otherwise known as the disease group. Carieless (CF) children were assigned to the control group. The teeth which are filled and repaired before are counted as caries. All subjects received dental examination during months 8-10 of 2015, and the children of the control group remained carieless.

In summary, 20 children were included in the study, 10 of which had severe ecc (secc) and 10 of which served as control controls.

(II) sample collection and processing

Subjects were asked not to eat more food and not to brush their teeth after breakfast. Approximately 2 hours after breakfast, subjects were asked to rinse with fresh water. Plaque was sampled from the intact enamel of eight deciduous molars for each child. The specimens were collected with a sterile spatula and immediately placed in an Eppendorf tube containing 1ml of sodium thiosulfate solution. The samples were stored in ice bags at 0 ℃ and were sent to the laboratory within 2 hours after collection.

Biolog analysis

The samples were suspended in 0.01 mol/L11 ml of phosphate buffer pH 7.2-7.4, vortexed and mixed well for 60s, and the samples were plated on anaerobic Biolog plates (AN) with 100. mu.L of each well. Biolog plates contained 95 independent single carbon sources and one water blank. Each well contained tetrazolium violet, which changed color as a result of a reduction reaction to indicate bacterial metabolism. The initial Optical Density (ODS) of the bacterial suspension was measured prior to inoculation. The plates were incubated for 4 days at 37 ℃ in 5% carbon dioxide and Biolog plates were placed in anaerobic bags. OD values at 590nm (OD590nm) were determined and analyzed using a Biolog Micro Station and associated software.

(IV) data analysis

To correct for background, we introduce a modified OD value, i.e. experimental wells minus control well OD. If the difference is negative, the corrected OD value is zero. The overall metabolic activity of the microbial community was expressed as the mean color change (AWCD) on the Biolog plate, which is the average of the corrected OD values per well for a single carbon source. Our normalized corrected OD values were the corrected OD values for each well divided by the AWCD of each plate, thus avoiding initial OD variations caused by manual sampling differences of the microbial community in the plaque suspension.

Differences in AWCD of disease groups and control group plates after four days of culture were compared using independent sample t-tests. p < 0.05 or p < 0.01 are statistically significant. The carbon source utilization was determined for both groups and the independent sample t test was used to determine which carbon source had a difference in utilization between the two groups based on the normalized corrected OD values. The relationship between the disease group and the control group on the differentiated carbon source was determined by cluster analysis and Principal Component Analysis (PCA).

(V) results

The demographic and clinical characteristics of the samples are shown in table 1.

TABLE 1 demographic and clinical characteristics

The initial absorbance value of the disease group is higher than that of the control group, and the Biolog culture plate well reflects the change of plaque metabolism through chromogenic reaction along with the prolonging of the culture time, thereby indirectly prompting the change of the flora structure. Specifically, the difference in the average color change (AWCD) between the disease group and the control group was not statistically significant in the first 48 hours of culture. However, after 72 and 96 hours of culture, the AWCD value of the flora in the disease group is obviously higher than that of the control group (P < 0.05), and the detailed description is shown in the attached figure 1 of the specification. In which, we found two typical carbon source metabolism patterns, see the attached figure 2 of the specification, the upper two are the control groups using the carbon source stronger than that used by the disease group, and the lower is the disease group using the carbon source stronger than that used by the control group.

Specifically, in the present study, carbon sources with different utilization conditions between the disease group and the control group at four time points of 24, 48, 72, and 96 hours of culture were analyzed, and 10, 23, 9, and 7 carbon sources with statistical differences were found. Since the 24-hour in vitro culture time was the shortest, it was assumed that the metabolism of the flora at this time was closest to the real situation in the mouth, 10 different carbon sources found at this time point were selected for subsequent analysis in this study, as detailed in table 2. The differential carbon sources at the other time points are detailed in Table 3.

TABLE 2 differential carbon sources at 24 hours for disease groups versus control groups

TABLE 3 differential carbon sources at 48, 72 and 96 hours for disease groups versus control groups

For 10 different carbon sources obtained by 24-hour culture, clustering analysis (figure 3 in the specification) and principal component analysis (figure 4 in the specification) were performed on samples of the disease group and the control group in the present study to clarify the correlation between the carbon source metabolism pattern and the presence or absence of disease.

(VI) Cluster analysis

The cluster analysis is an exploratory analysis, and in the classification process, people do not give a classification standard in advance, and the cluster analysis can automatically classify from sample data. The principle is that samples with small distances are classified into one class according to the difference between individuals (namely the distance of data of sample characteristic indexes), so that the difference between the individuals in different classes is large, and the difference between the individuals in the same class is small. In this study, ward (sum of squared deviations) in the systematic clustering method was used, and R software was used as software. Description figure 3 is a heat map (heatmap) made after cluster analysis.

The upper left small graph is a legend, and the color blocks show gradual reduction of gray scale from left to right, which represents that the utilization degree of each carbon source of each sample is gradually increased. Since each use case corresponds to one of the corrected absorbance values described above, i.e., a total of 20 × 10 to 200 values, i.e., 200 color patches, the light gray count line in the small graph can be determined according to the number of color patches of each gray scale.

The horizontal axis of the large graph in FIG. 3 shows 10 different carbon sources, and in the vertical axis, P1-10 is a disease group sample, and C1-10 is a control group sample. The color blocks have the same meaning as the legend. It can be seen that the low-gray color blocks corresponding to the disease group samples are more than those of the control group, which indicates that the carbon source utilization degree of the disease group is stronger than that of the control group; in addition, it can be seen that there are more low-gray color patches in the disease group in the left 7 columns and more low-gray color patches in the control group in the right 3 columns.

In order to show the clustering effect more clearly, the clustering process is represented by a connecting line in fig. 3, samples with similar characteristics are firstly clustered into one class, the formed small class is further clustered into a large class with similar characteristics, and the clustering is performed upwards in sequence until all the samples are clustered into one class. The results of the bi-directional clustering are shown in fig. 3. The left line of the large graph is based on the results of sample clustering, and it can be seen that the samples can be divided into two categories, and this is just consistent with the disease group and the control group, which proves that there is a large difference between the carious children and healthy children in the ability to utilize these 10 carbon sources, and also shows that these 10 carbon sources are effective in distinguishing whether carious children are affected. The top line of the large graph is the result of clustering based on different carbon sources, wherein maltose is in one class and the other 9 carbon sources belong to another class. While in the other 9 classes, 6 carbohydrates were distinguished from 3 amino acids and peptides, indicating that 20 samples differ in the utilization of carbohydrates and amino acids and peptides.

(VII) Principal Components Analysis (PCA)

FIG. 4 is a schematic diagram of principal component analysis. In the principal component analysis, when the measurement dimension of the sample is large, for example, 10 different carbon sources in the present study, the dimension reduction is performed, and 20 samples in total, for example, 20 samples in the disease group and the control group in the present study, are evaluated by using several comprehensive indexes, for example, principal component 1(PC1), principal component 2(PC2), and the like. The study used R software to complete principal component analysis.

Specifically, FIG. 4 of the specification is a dual information plot (biplot) mainly analyzing the ability to distinguish disease groups from control groups between carbon sources. The horizontal axis is principal component 1, the vertical axis is principal component 2, and the percentage in parentheses represents the percentage of the principal component variance to the original variable variance, i.e., it can represent how much the entire data distribution changes, which are 23.24% and 17.21%, respectively. The study focused on PC 1. 10 arrows are sent from the center (0,0) of the graph to represent 10 carbon sources, and the direction and the length of the line segment have certain representative meanings:

● the carbon source represented by the left 7 arrows belongs to sugars, since they point in the negative direction of the horizontal axis, indicating that these variables are negatively related to PC 1;

● the carbon source represented by the 3 arrows to the right belongs to amino acids and peptides, and the variables are positively correlated with PC 1;

● the length of the arrow is understood to be the ability of the carbon source to distinguish the disease group from the control group, the longer the arrow, the stronger its ability to distinguish a certain sample to its pointing region.

The scatter on the graph represents the sample, the triangle is the disease group and the rectangle is the control group. It can be seen that two groups are located substantially on either side of the figure, the disease group is substantially on the left half, the control group is substantially on the right half, and the two groups can be better distinguished by PC 1; when arrows and samples are combined, the distinguishing ability of the saccharides to the disease group is strong, and the distinguishing ability of the amino acids and the peptides to the control group is strong. This is consistent with our analysis of table 2, i.e., the disease group utilizes 7 carbohydrates more than the control group, which utilizes 3 amino acids and peptides more than the disease group (all statistically significant).

As can be seen from the above analysis, the use of these 10 single carbon sources can effectively distinguish carious patients from non-carious ones. In children of low age, as a result, children suffering from caries, particularly, having a very large number of caries in the mouth, are certainly susceptible to caries, and subjects having plaque similar to those of the patients are also susceptible to caries. Therefore, the utilization of the 10 single carbon sources can also effectively distinguish caries-susceptible persons from caries-non-susceptible persons.

(VIII) products

Based on the experimental results, the invention provides a kit for predicting whether the infant is susceptible to caries, the kit comprises maltose, alpha-methyl-D-galactoside, alpha-amygdalin, D, L-alpha-glycerophosphate, D-trehalose, 3-methyl-D-glucose, turanose, glycyl-L-proline, L-glutamine and glycyl-L-glutamine, and 10 carbon sources in total are used for predicting the risk of the infant to suffer from caries.

In addition to the above 10 carbon sources, the kit also includes tetrazolium violet and water, and may also be provided with a phosphate buffered saline. The whole kit is in a plate-shaped structure, and 12 holes are formed in the plate, see the attached figure 5 of the specification. Wherein 10 wells, for example, wells 1-10, are filled with 10 carbon sources and tetrazole violet, 1 well is filled with water and tetrazole violet, and 1 well is empty.

The specific method for testing the testers by using the product comprises the following steps: the tester was unable to eat more food and brush their teeth after breakfast. Approximately 2 hours after breakfast, the test subjects were asked to rinse their mouth with clear water. Plaque was sampled from the intact enamel of eight deciduous molars. The specimen was collected with a sterile spoon, added to a centrifuge tube containing 1.5mL of 0.01mol/L phosphate buffer pH 7.2-7.4, the sample was suspended therein, vortexed, and mixed well for 60 s. Then, the mixed bacterial liquid is inoculated in the holes containing the carbon source of the kit under the anaerobic condition, and each hole is loaded with 100 mu L of the sample. Wells containing water served as blank controls. The inoculated kit is placed in an anaerobic bag and cultured for 1 day at 37 ℃. Determining 590nm OD value (OD590nm), clustering analysis, principal component analysis, and comparing with the corresponding data of patients and healthy persons in our database, and finally obtaining the susceptibility of the subject to caries.

The above description is only for illustrating the embodiment of the kit for predicting susceptibility of a patient to caries, and since it is easy for a person skilled in the art to make several modifications and changes on the basis, the present specification does not intend to limit the kit for predicting susceptibility of a patient to caries to the specific structure or composition shown and described, and therefore all the modifications and equivalents that may be utilized belong to the claims of the present invention.

Claims (5)

1. A kit for predicting whether children are susceptible to caries or not is characterized by comprising maltose, alpha-methyl-D-galactoside, alpha-amygdalin, D, L-alpha-phosphoglycerol, D-trehalose, 3-methyl-D-glucose, turanose, glycyl-L-proline, L-glutamine and glycyl-L-glutamine, wherein 10 carbon sources are counted, and the kit further comprises a color developing agent which is tetrazole violet.

2. The kit according to claim 1, which has a plate-like structure, and the plate has wells for placing the carbon source and the color-developing agent, wherein different wells have different carbon sources placed therein, and each of the wells has a color-developing agent.

3. The kit according to claim 2, further comprising a well containing water and a color developer and/or a well having an empty interior as a reference.

4. The kit of any one of claims 1 to 3, further comprising a phosphate buffered saline.

5. The kit according to claim 4, wherein the phosphate physiological saline buffer is 0.01mol/L phosphate buffer having a pH of 7.2 to 7.4.

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