Combinations of markers for skin classification and their use

Abstract

The present invention provides use of Moraxella osloensis for skin classification, characterization of skin conditions, or as a reagent or kit for characterizing skin conditions. The present invention also provides a marker combination comprising Moraxella osloensis and Propionibacterium acnes. The present invention also provides use of the marker combination in skin classification and / or skin condition assessment.

Description

Technical Field

[0001] The present invention relates to the field of biopharmaceuticals, and specifically, to combinations of markers for skin classification and their use.

Background Art

[0002] With the start of the microbiome project, it has come to be recognized that, like in the intestine, a large number of microorganisms also exist on the surface of the human body. In intestinal research, it has been shown that the interaction between microorganisms and the host, and the strategies of fecal microbiota transplantation, probiotics, and prebiotics can change the intestinal microecology and improve the intestinal steady state. The research on skin microecology has been relatively slow to progress, and in particular, there is a lack of large-scale population metagenomic data. From the metagenomic data of North American populations, it was shown that skin microorganisms have large individual differences in composition but high stability, that is, although individuals change spatially over time, the composition of their microorganisms is relatively stable and has very strong personal characteristics. In this research, the existence of individual differences was again demonstrated from the data of the Han Chinese population, and the composition of microorganisms was significantly related to a series of skin phenotypes of the host, and it was found that skin microorganisms are useful as potential new means and new targets for skin phenotypes.

[0003] However, due to significant individual differences, the research, development, and design of universally applicable skincare products and pharmaceuticals presents a significant challenge. Further statistical analysis has revealed that while individual differences are large, there are still some major characteristics and laws at the group level. By classifying groups based on combinations of these characteristics, the problem of large individual differences can be solved. Skin classification can suitably satisfy low-resolution "accurate" / "individualized" care. For example, one commonly used skin classification currently is "dry," "neutral," and "oily" skin, which classifies based on the water-oil characteristics of the host's skin. Similar to this, this research classifies groups based on the characteristics of the skin microbiome, rather than water-oil characteristics. Therefore, it is advantageous for the development of skincare products and pharmaceuticals that are more suitable for specific groups of different skin types in the industry, enabling a certain degree of "accurate" / "individualized" care and effectively improving the stable state of the skin.

[0004] Therefore, in this field, there is a strong need for the development of new methods for skin classification and assessment of skin aging, as well as the provision of new diagnostic and classification methods. [Overview of the Initiative] [Problems that the invention aims to solve]

[0005] The objective of this invention is to contribute to the development of skincare products and pharmaceuticals more suitable for specific skin types in industry by classifying populations based on the characteristics of the skin microbiome. It provides novel methods, diagnostic and classification means for skin classification and assessment of skin aging.

[0006] In this invention, two types of bacteria that influence skin classification, Moraxella osloensis and Cutibacterium acnes, and Staphylococcus epidermidis, one of the colonizing bacteria that are abundant on the skin and play an important role in host health and disease, are targeted. First, metagenomics data from large samples of Han Chinese populations were used to determine the relationship between the distribution and abundance of the three target skin commensal bacteria on the face and the host skin phenotype. Further verification was performed using QPCR experiments to identify Moraxella osloensis (M. osloensis), a bacterium that promotes skin aging. [Means for solving the problem]

[0007] In a first aspect of the present invention, the use of Moraxella osloensis (M. osloensis) or a detection reagent thereof is provided for (a) skin classification and / or (b) determination or characterization of skin conditions, or for the manufacture of reagents or kits used for (a) skin classification and / or (b) determination or characterization of skin conditions.

[0008] In another preferred example, the skin condition includes skin age, skin water content, skin elasticity, skin color, and degree of skin aging. In another preferred example, the degree of skin aging is determined based on one or more phenotypes selected from the group consisting of porphyrins, oils, water content, glossiness, pore area, skin yellowness value, pore size, and blemishes.

[0009] In another preferred example, the reagent or kit further includes a reagent for detecting *Propionibacterium acnes* (C. acnes). In another preferred example, the reagent or kit further comprises a reagent for detecting Moraxella bovoculi and / or Psychrobacter sp.

[0010] In another preferred example, the reagent or kit further comprises reagents for detecting Propionibacterium avidum, Propionibacterium granulosum, Staphylococcus species, Propionibacterium acnes phage and / or Staphylococcus phage. In another preferred example, the reagent or kit further includes a reagent for detecting Staphylococcus epidermidis.

[0011] A second aspect of the present invention provides a combination of markers comprising Moraxella osloensis (M. osloensis) and Propionibacterium acnes (C. acnes). In another preferred example, the combination of markers further includes Moraxella bovoculi and / or the genus Psychrobacter sp.

[0012] In another preferred example, the combination of markers further includes Propionibacterium avidum, Propionibacterium granulosum, Staphylococcus species, Propionibacterium acnes phage and / or Staphylococcus acnes phage.

[0013] In another preferred example, the combination of markers further includes Staphylococcus epidermidis. In another preferred example, the combination of markers is for (a) skin classification and / or (b) determination of skin condition.

[0014] In another preferred example, the skin condition includes skin age, skin water content, skin elasticity, skin color, and degree of skin aging. In another preferred example, the degree of skin aging is determined based on one or more phenotypes selected from the group consisting of porphyrins, oils, water content, glossiness, pore area, skin yellowness value, pore size, and blemishes.

[0015] In another preferred example, the marker or combination of markers is derived from a skin sample, preferably from skin of the whole body or face, more preferably from the cheek, forehead, or nasal ala. In another preferred example, the marker or combination of markers is derived from an Asian skin sample.

[0016] In another preferred example, the marker or combination of markers originates from the cheek, forehead, or nasal ala. In another preferred example, the level of each marker in the marker combination is detected by one or more methods selected from the group consisting of sequencing, PCR, and protein quantification detection.

[0017] In another preferred example, the method for detecting the level of the marker further includes one or more methods selected from characteristic gene quantitative PCR, qPCR, real-time quantitative PCR, metagenomic analysis, 16s RNA sequencing, mass spectrometry, and Western blotting.

[0018] In another preferred example, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of Propionibacterium acnes in the combination of markers satisfies M / C ≤ 1.3, preferably M / C ≤ 0.8, and more preferably M / C ≤ 0.4, then the skin type is type C (or type I), and its phenotype includes high oil content, high water content, good skin elasticity, low degree of skin aging, and light skin color.

[0019] In another preferred example, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of Propionibacterium acnes in the combination of markers satisfies 0.3 ≤ M / C ≤ 2.5, preferably 0.3 ≤ M / C ≤ 2.3, and more preferably 0.8 ≤ M / C ≤ 1.8, then the skin type is mixed (or type II), and its phenotype includes moderate oil content, moderate water content, general skin elasticity, moderate skin aging, and moderate skin color.

[0020] In another preferred example, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of Propionibacterium acnes in the marker combination satisfies M / C ≥ 0.5, preferably M / C ≥ 1.8, and more preferably M / C ≥ 2.2, then the skin type is type M (type III), and its phenotype includes low oil content, low water content, poor skin elasticity, high degree of skin aging, and dark skin color.

[0021] In another preferred example, if a sample derived from the cheek satisfies the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of Propionibacterium acnes, then the skin type is type C (or type I), and its phenotype includes high oil content, high water content, good skin elasticity, low degree of skin aging, and a light skin tone.

[0022] In another preferred example, if a sample derived from the cheek satisfies the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of Propionibacterium acnes, then the skin type is mixed (or type II), and its phenotype includes moderate oil content, moderate water content, general skin elasticity, moderate skin aging, and moderate skin color.

[0023] In another preferred example, in a sample derived from the cheek, when the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of acne bacteria satisfies M / C ≧ 1.7, the skin type is M type (type III), and its phenotype includes a low oil content, a low water content, poor skin elasticity, a high degree of skin aging, and a dark skin color.

[0024] In another preferred example, in a sample derived from the forehead, when the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of acne bacteria satisfies M / C ≦ 1.5, preferably M / C ≦ 1.25, the skin type is C type (or type I), and its phenotype includes a high oil content, a high water content, good skin elasticity, a low degree of skin aging, and a bright skin color.

[0025] In another preferred example, in a sample derived from the forehead, when the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of acne bacteria satisfies 1.25 ≦ M / C ≦ 2.5, more preferably 1.3 ≦ M / C ≦ 2.2, the skin type is a mixed type (or type II), and its phenotype includes a medium oil content, a medium water content, general skin elasticity, a medium degree of skin aging, and a medium skin color.

[0026] In another preferred example, in a sample derived from the forehead, when the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of acne bacteria satisfies M / C ≧ 2, preferably M / C ≧ 2.2, the skin type is M type (type III), and its phenotype includes a low oil content, a low water content, poor skin elasticity, a high degree of skin aging, and a dark skin color.

[0027] In another preferred example, if a sample derived from the nasal ala satisfies the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of Propionibacterium acnes, then the skin type is type C (or type I), and its phenotype includes high oil content, high water content, good skin elasticity, low degree of skin aging, and light skin color.

[0028] In another preferred example, if a sample derived from the nasal ala satisfies the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of Propionibacterium acnes, then the skin type is mixed (or type II), and its phenotype includes moderate oil content, moderate water content, general skin elasticity, moderate skin aging, and moderate skin color.

[0029] In another preferred example, if a sample derived from the nasal ala satisfies the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of Propionibacterium acnes, then the skin type is type M (type III), and its phenotype includes low oil content, low water content, poor skin elasticity, high degree of skin aging, and dark skin color.

[0030] A third aspect of the present invention provides a method for determining skin classification or skin condition, comprising the following steps: (1) Provide a skin sample from the subject, detect the level (e.g., content) of each marker in a combination of markers including Moraxella osloensis and Propionibacterium acnes in the sample, and obtain the level (e.g., content) (M) of Moraxella osloensis and the level (e.g., content) (C) of Propionibacterium acnes, respectively; (2) The skin classification and / or skin condition of the subject is determined based on the level (e.g., content) (M) of Moraxella osloensis, or by comparing the level (e.g., content) (M) of Moraxella osloensis in the sample with the level (e.g., content) (C) of Propionibacterium acnes.

[0031] In another preferred example, the subjects are of Asian descent. In another preferred example, step (2) is performed to classify the skin or determine the skin condition of the sample based on the relative value (e.g., M / C) of the level (e.g., content) (M) of Moraxella osloensis and the level (e.g., content) (C) of Propionibacterium acnes.

[0032] In another preferred example, the skin condition includes skin age, skin water content, skin elasticity, skin color, and degree of skin aging. In another preferred example, the levels (e.g., content) (M) of Moraxella osloensis and the levels (e.g., content) (C) of Propionibacterium acnes in the sample under test are determined by one or more methods selected from the group consisting of sequencing, PCR, and protein quantification detection.

[0033] In another preferred example, a method for detecting the level (e.g., content) (M) of Moraxella osloensis and the level (e.g., content) (C) of Propionibacterium acnes in the sample further includes one or more methods selected from characteristic gene quantitative PCR, qPCR, real-time quantitative PCR, metagenomic analysis, 16s RNA sequencing, mass spectrometry, and Western blotting.

[0034] In another preferred example, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis in the sample to the level (e.g., content) (C) of Propionibacterium acnes satisfies M / C ≤ 1.3, preferably M / C ≤ 0.8, and more preferably M / C ≤ 0.4, then the skin type is type C (or type I), and its phenotype includes high oil content, high water content, good skin elasticity, low degree of skin aging, and light skin color.

[0035] In another preferred example, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis in the sample to the level (e.g., content) (C) of Propionibacterium acnes satisfies 0.3 ≤ M / C ≤ 2.5, preferably 0.3 ≤ M / C ≤ 2.3, and more preferably 0.8 ≤ M / C ≤ 1.8, then the skin type is mixed (or type II), and its phenotype includes moderate oil content, moderate water content, general skin elasticity, moderate skin aging, and moderate skin color.

[0036] In another preferred example, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis in the sample to the level (e.g., content) (C) of Propionibacterium acnes satisfies M / C ≥ 0.5, preferably M / C ≥ 1.8, and more preferably M / C ≥ 2.2, then the skin type is type M (type III), and its phenotype includes low oil content, low water content, poor skin elasticity, high degree of skin aging, and dark skin color.

[0037] In another preferred example, in a cheek sample, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis in the sample to the level (e.g., content) (C) of Propionibacterium acnes satisfies M / C ≤ 0.8, preferably M / C ≤ 0.75, then the skin type is type C (or type I), and its phenotype includes high oil content, high water content, good skin elasticity, low degree of skin aging, and fair skin color.

[0038] In another preferred example, in a cheek-derived sample, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis in the sample to the level (e.g., content) (C) of Propionibacterium acnes satisfies 0.75 ≤ M / C ≤ 2, more preferably 0.8 ≤ M / C ≤ 1.7, then the skin type is mixed (or type II), and its phenotype includes moderate oil content, moderate water content, general skin elasticity, moderate skin aging, and moderate skin color.

[0039] In another preferred example, in a cheek sample, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis in the sample to the level (e.g., content) (C) of Propionibacterium acnes satisfies M / C ≥ 1.7, then the skin type is type M (type III), and its phenotype includes low oil content, low water content, poor skin elasticity, high degree of skin aging, and dark skin color.

[0040] In another preferred example, in a sample derived from the forehead, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis in the sample to the level (e.g., content) (C) of Propionibacterium acnes satisfies M / C ≤ 1.5, preferably M / C ≤ 1.25, then the skin type is type C (or type I), and its phenotype includes high oil content, high water content, good skin elasticity, low degree of skin aging, and light skin color.

[0041] In another preferred example, in a sample derived from the forehead, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis in the sample to the level (e.g., content) (C) of Propionibacterium acnes satisfies 1.25 ≤ M / C ≤ 2.5, more preferably 1.3 ≤ M / C ≤ 2.2, then the skin type is mixed (or type II), and its phenotype includes moderate oil content, moderate water content, general skin elasticity, moderate skin aging, and moderate skin color.

[0042] In another preferred example, in a sample derived from the forehead, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis in the sample to the level (e.g., content) (C) of Propionibacterium acnes satisfies M / C ≥ 2, preferably M / C ≥ 2.2, then the skin type is type M (type III), and its phenotype includes low oil content, low water content, poor skin elasticity, high degree of skin aging, and dark skin color.

[0043] In another preferred example, in a sample derived from the nasal ala, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis in the sample to the level (e.g., content) (C) of Propionibacterium acnes satisfies M / C ≤ 0.5, preferably M / C ≤ 0.35, then the skin type is type C (or type I), and its phenotype includes high oil content, high water content, good skin elasticity, low degree of skin aging, and light skin color.

[0044] In another preferred example, in a sample derived from the nasal ala, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis in the sample to the level (e.g., content) (C) of Propionibacterium acnes satisfies 0.35 ≤ M / C ≤ 0.7, preferably 0.35 ≤ M / C ≤ 0.6, and more preferably 0.35 ≤ M / C ≤ 0.55, then the skin type is mixed (or type II), and its phenotype includes moderate oil content, moderate water content, general skin elasticity, moderate skin aging, and moderate skin color.

[0045] In another preferred example, in a sample derived from the nasal ala, if the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis in the sample to the level (e.g., content) (C) of Propionibacterium acnes satisfies M / C ≥ 0.5, preferably M / C ≥ 0.55, then the skin type is type M (type III), and its phenotype includes low oil content, low water content, poor skin elasticity, high degree of skin aging, and dark skin color.

[0046] In another preferred example, the relative values ​​satisfy the following conditions: if M / C ≤ 1.3, the skin is type C, and if M / C ≥ 0.5, the skin is type M. In another preferred example, the relative value satisfies the following condition: the skin is mixed type when 0.3 ≤ M / C ≤ 2.5.

[0047] In another preferred example, an increase in the level (e.g., content) (M) of Moraxella osloensis indicates that the skin condition is characterized by an increased skin age, darker and yellower skin color, decreased skin water content, and decreased sebum and porphyrin content.

[0048] A fourth aspect of the present invention provides a combination of reagents for detecting skin classification and / or skin condition, comprising a reagent for detecting each marker in the combination described in the second aspect of the present invention. In another preferred example, the reagent is for detecting the level (e.g., content) of each marker.

[0049] In another preferred example, the reagent comprises a substance that detects the level of each marker in the combination described in the second aspect of the present invention by one or more methods selected from the group consisting of sequencing, PCR, and protein quantification detection. In another preferred example, the method for detecting the level of the marker further includes characteristic gene quantitative PCR, qPCR, real-time quantitative PCR, metagenomic analysis, 16s RNA sequencing, mass spectrometry, and Western blotting.

[0050] In another preferred example, the reagent combination includes the following: A first detection reagent for detecting the level (M) of Moraxella osloensis, and / or A second detection reagent for detecting the level (C) of acne bacteria.

[0051] A fifth aspect of the present invention provides a kit comprising the reagent combination described in the second aspect of the present invention. In another preferred example, each marker in the combination described in the second aspect of the present invention is used as a standard.

[0052] In a sixth aspect of the present invention, a system for classifying the skin and / or determining the skin condition of a test subject is provided, which includes the following: (a) A feature receiving module for receiving skin sample feature data, the feature data containing information on the quantitative determination of Moraxella osloensis (M) and Propionibacterium acnes (C) in the skin sample; (b) A module for obtaining a determination result for skin classification and / or skin condition by calculating feature data from the feature receiving module in a calculation processing module to obtain the ratio of each feature or the ratio relationship between each feature, and comparing the obtained ratio or ratio relationship between each feature with a standard value for skin classification or characterization; (c) A result output module that receives and outputs the diagnostic results.

[0053] In another preferred example, the subject is a human being. In another suitable example, the subject is Asian. In another preferred example, the subjects include men and women. In another preferred example, the subject may include infants, adolescents, or adults.

[0054] In another preferred example, the quantitative information includes the respective levels (e.g., content) of Moraxella osloensis (M) and Propionibacterium acnes (C). In another preferred example, the ratio relationship includes the relative values ​​of the respective levels (e.g., content) of Moraxella osloensis (M) and Propionibacterium acnes (C) in a skin sample, e.g., M / C.

[0055] In another preferred example, the system classifies skin conditions into at least two types. In another preferred example, the method for obtaining the quantitative information includes sequencing, PCR, and protein quantification detection.

[0056] In another preferred example, the method for obtaining the quantitative information further includes characteristic gene quantitative PCR, qPCR, real-time quantitative PCR, metagenomic analysis, 16s RNA sequencing, mass spectrometry, and Western blotting. In another preferred example, the feature receiving module includes a sample acquisition device and a feature signal input terminal.

[0057] In another preferred example, the computing module includes a processor and a memory device, the memory device storing threshold information for skin type and / or skin condition. In another preferred example, the output module includes any terminal, preferably a display, printer, tablet PC (PAD), or smartphone. In another preferred example, the modules are connected by wire or wireless means.

[0058] A seventh aspect of the present invention provides a method for screening substances or components that improve skin condition, comprising the following steps: (a) Provide screening bacteria that are Moraxella osloensis (M), Propionibacterium acnes (C), or a mixture containing Moraxella osloensis and / or Propionibacterium acnes; (b) Co-culture the substance or component to be screened with the screening bacteria, and detect the respective levels (e.g., content) of Moraxella osloensis or Propionibacterium acnes, or the relative levels (e.g., relative content) (M / C) between Moraxella osloensis and Propionibacterium acnes; (c) From the respective levels (e.g., content) of Moraxella osloensis or Propionibacterium acnes after culturing in (b), or the relative levels (e.g., relative content) (M / C) between Moraxella osloensis and Propionibacterium acnes, it is determined whether the substance or component being screened is a substance or component that improves skin condition.

[0059] In another preferred example, an increase in the Moraxella osloensis content or the relative level (e.g., relative content) (M / C) between Moraxella osloensis and Propionibacterium acnes indicates that the substance or component being screened is a contusion treatment substance.

[0060] In another preferred example, a decrease in the level (e.g., content) of Moraxella osloensis or a decrease in the relative level (e.g., relative content) (M / C) between Moraxella osloensis and Propionibacterium acnes indicates that the substance or component being screened is a skin anti-aging substance.

[0061] In another preferred example, an increase in the level (e.g., content) of Propionibacterium acnes, or an increase in the relative level (e.g., relative content) (C / M) between Moraxella osloensis and Propionibacterium acnes, indicates that the substance or component being screened is a skin anti-aging substance.

[0062] In another preferred example, a decrease in the level (e.g., content) of Propionibacterium acnes, or a decrease in the relative level (e.g., relative content) (M / C) between Moraxella osloensis and Propionibacterium acnes, indicates that the substance or component being screened is a contusion treatment substance.

[0063] In the eighth aspect of the present invention, the use of a combination of markers described in the second aspect of the present invention or a combination of reagents described in the fourth aspect of the present invention is provided for use in (a) skin classification and / or (b) the production of a kit for determining or characterizing a skin condition.

[0064] In the ninth aspect of the present invention, the use of a combination of markers described in the second aspect of the present invention or a combination of reagents described in the fourth aspect of the present invention is provided for the screening of substances or components that improve skin conditions.

[0065] Of course, within the scope of the present invention, it is understood that the above-mentioned technical features of the present invention and the technical features specifically described below (for example, in the examples) can be combined to form new or preferred technical solutions. Due to space limitations, each will not be explained in detail here. [Brief explanation of the drawing]

[0066] [Figure 1] Figure 1 shows a schematic diagram of the skin area to be sampled. [Figure 2] Figure 2 shows the microbial composition of the facial skin of Han Chinese populations. [Figure 3] Figure 3 shows an analysis of the optimal number of clusters for different regions.

[0067] [Figure 4]Figures 4A and 4B show the clustering results for the forehead, where the box plots represent the mean distance between samples within two groups, and the red lines represent the mean distance between samples from different groups. 4A is the Jensen-Shannon divergence, and 4B is the Bray-Curtis dissimilarity. Figures 4C and 4D show the relative levels of Propionibacterium acnes or Moraxella osloensis on the forehead, with each point representing a single sample. Figures 4E and 4F show the clustering results for the cheeks, where the box plots represent the mean distance between samples within two groups, and the red lines represent the mean distance between samples from different groups. 4E is the Jensen-Shannon divergence, and 4F is the Bray-Curtis dissimilarity. Figures 4G and 4H show the relative levels of Propionibacterium acnes or Moraxella osloensis in the cheeks, with each point representing a single sample. Figures 4I and 4J show the clustering results for the nasal ala, where the box plots represent the mean distance between samples within two groups, and the red lines represent the mean distance between samples in different groups. 4I is the Jensen-Shannon divergence, and 4J is the Bray-Curtis dissimilarity. Figures 4K and 4L show the relative levels of Propionibacterium acnes or Moraxella osloensis in the nasal ala, with each point representing a single sample.

[0068] [Figure 5] Figure 5 shows different microorganisms among different skin types, where the colors represent the relative levels of microorganisms, with each column representing one sample and each row representing one microorganism. [Figure 6]Figure 6 shows the characteristics of microbial networks in different skin types. The left side shows the types of microorganisms concentrated in the M-cutotype, and the right side shows the types of microorganisms concentrated in the C-cutotype. Each dot represents one species, and each colored bouquet also represents one species. As can be seen from the figure, the microorganisms concentrated within one skin type are positively correlated with each other and negatively correlated with the species concentrated in another skin type. [Figure 7] Figure 7 shows the differences in the concentration of gene function among different skin types of skin microorganisms. [Figure 8] Figure 8 shows the phenotypic differences between different skin types. [Figure 9] Figure 9 shows an analysis of the association between Moraxella osloensis and age and skin phenotype, with a p-value of less than 0.05 after calibration.

[0069] [Figure 10] Figure 10 shows that the aceA / aceB genes are concentrated in the M-Cutotype. [Figure 11] Figure 11 shows that the β-carotene synthesis pathway is concentrated in the M-Cutotype. [Figure 12] Figure 12 shows a concentrated analysis of RNA-seq-expressed differential genes in human keratinocytes (HaCaT) treated with the supernatant of Moraxella osloensis and a blank control group. [Figure 13] Figure 13 shows the utilization of Moraxella osloensis for several water-soluble carbon source compounds. The left figure shows results obtained using the CCK-8 kit, and the right figure shows results obtained using Dye mix A. [Figure 14] Figure 14 shows the results of verifying skin types using skin metagenomics data from Chinese people in Singapore.

[0070] [Figure 15] Figure 15 shows the results of verifying skin types using skin metagenomics data from the Philippines and Italy. [Figure 16] Figure 16 shows a heatmap of the correlation between the host phenotype and the species level of three types of skin commensal bacteria. [Figure 17] Figure 17 shows the results of Moraxella osloensis-HaCaT-QPCR. [Figure 18] Figure 18 shows the results of the acne bacteria-HaCaT-QPCR. [Figure 19] Figure 19 shows the results of Staphylococcus epidermidis-HaCaT-QPCR. [Modes for carrying out the invention]

[0071] Through extensive and in-depth research, the inventors discovered for the first time that Moraxella osloensis is useful for characterizing or classifying skin conditions. Furthermore, in this invention, a novel combination of Moraxella osloensis and Propionibacterium acnes as markers has been discovered for the first time. The marker combination of this invention is useful for (a) skin classification and / or (b) assessment of skin conditions, and has the advantages of high sensitivity and high specificity, thus possessing significant application value. Based on this, the inventors completed the present invention.

[0072] term The terms used in this invention have meanings that are ordinarily understood by those skilled in the art. However, to better understand this invention, some definitions and interpretations of related terms are as follows. According to the present invention, the term "combination of markers" refers to a combination of two or more types of markers. According to the present invention, the marker level is determined by the ratio of the abundance and / or expression levels of two types of microorganisms.

[0073] According to the present invention, the term "individual" means an animal, in particular a mammal, such as a primate, most preferably a human. According to the present invention, the terms "one," "one," and "this" include not only a single individual but also a common type that can describe a particular mode of implementation. As used herein, when used with specific example numbers, the term “approximately” means that the value may vary by no more than 1% from the example number. For example, as used herein, the expression “approximately 100” includes 99, 101 and all values ​​in between (e.g., 99.1, 99.2, 99.3, 99.4, etc.).

[0074] As used herein, the terms “contain” or “include” may be open, semi-closed, or closed. In other words, the terms also include “basically composed of…” or “composed of…”. The definitions of terms provided herein are intended to enable those skilled in the art to better understand the present invention, and are not intended to limit it.

[0075] Moraxella osloensis, also known as M. osloensis, will be abbreviated as M fungus below. Moraxella osloensis is a rod-shaped fungus belonging to the genus Moraxella, which is Gram-negative and chemoorganotrophic. It cannot produce acid from carbohydrates.

[0076] Propionibacterium acnes, also known as C. acnes, is hereinafter abbreviated as C. Propionibacterium acnes is a Gram-positive, rod-shaped bacterium belonging to the genus Propionibacterium, family Propionibacteraceae, order Actinomycetes, phylum Actinomycetes. It is an important colonizing bacterium on human skin, involved in maintaining skin health, and is also a pathogen of contusions vulgaris.

[0077] Surface Staphylococcus, Staphylococcus epidermidis, S. epidermidis These Gram-positive cocci that live on the surface of living organisms are found on the skin, vagina, and other parts of the human body, and are usually clustered together in a grape-like shape, hence the name "surface staphylococcus."

[0078] skin classification In the present invention, skin can be further divided into M-Cutotype (abbreviated as M-type), mixed type, and C-Cutotype (abbreviated as C-type).

[0079] C-Cutotype As used herein, the terms "C-Cutotype" and "Type C" are interchangeable and refer to a type of acne bacteria (C. acnes) that is one of the microbial skin classifications and exhibits a high concentration of its characteristics.

[0080] M-Cutotype As used herein, the terms "M-Cutotype" and "M-type" are interchangeable and refer to a type of Moraxella osloensis, one of the microbial-based skin classifications, in which its characteristics are concentrated at a high level.

[0081] skin elasticity As used herein, skin elasticity is determined by, but is not limited to, sufficient skin water content, collagen, elastin, and natural fats.

[0082] skin color As used herein, skin color is determined by, but is not limited to, skin gloss, skin color, yellow value, etc.

[0083] skin aging degree As used herein, skin aging is determined by, but is not limited to, phenomena such as an increase in porphyrins in the skin, a decrease in skin water content and glossiness, enlargement and increase in pore area, an imbalance in skin oils, and darkening of the skin.

[0084] Detection method A microbial sample is obtained by dipping a sampling device, such as a sterile cotton swab, into the bacterial collection solution and repeatedly rubbing it at the collection site. The levels (e.g., content) of M or C bacteria can be characterized and examined by common molecular biological methods, and the M / C ratio can be obtained by, for example, the following methods: 1. 16s RNA sequencing; 2. Metagenomic sequencing; 3. Designing primers for characteristic sequences of the two species and then obtaining the M / C ratio by qPCR; 4. Detecting specific expressed proteins or metabolites of the two types of bacteria for quantification purposes, for example by mass spectrometry, Western blotting, etc.

[0085] kit In the present invention, the kit of the present invention comprises the combination described in the second aspect of the present invention and / or the combination of reagents described in the fourth aspect of the present invention. In another preferred example, each marker in the combination described in the first aspect of the present invention is used as a standard.

[0086] The main advantages of this invention are as follows: (1) In the present invention, Moraxella osloensis and Propionibacterium acnes are used as a combination of markers for (a) skin classification and / or (b) determination of skin condition, such as water content, skin elasticity, and / or degree of aging, and have the advantages of high sensitivity and high specificity, and have significant application value. (2) For the first time in the present invention, Moraxella osloensis and Propionibacterium acnes, which have been found in Asian populations, are used as a marker combination to (a) classify skin into M-Cutotype, mixed type and / or C-Cutotype type; and / or (b) determine skin condition.

[0087] (3) In this invention, for the first time, a new classification method has been discovered that differs from conventional classifications based on the physiological drive of the host (oily skin, dry skin, wet skin). This new classification method is based on skin microorganisms, and three different skin types with distinct characteristics have been identified. Furthermore, analysis of these three skin types suggests that differences in nutrition due to the host's physiology may be the driving factor for the different skin types. The microbiome colonies of different skin types exert specific functions that, in turn, act on the host's skin, influencing skin health and appearance to some extent. Therefore, further research on skin types will contribute to the development of personalized medicine, enabling better maintenance of skin health.

[0088] (4) For the first time in this invention, a correlation has been found between M bacteria and skin phenotype, which is positively correlated with age and with certain skin aging phenotypes, for example, as the level of M bacteria increases, skin oiliness decreases, water content decreases, glossiness decreases, and yellowness increases (skin darkens). It also correlates with certain typical characteristics of contusions, for example, as the amount of M bacteria increases, oiliness decreases, porphyrins (many of which are metabolites of C bacteria and may promote inflammation) decrease, and pore area decreases.

[0089] (5) For the first time in the present invention, it has been found that by improving the relative level (e.g., content) of acne bacteria, it is possible to adjust M-type skin to C-type skin, which is useful for anti-aging of the skin. (6) For the first time in the present invention, it has been found that by improving the relative level (e.g., content) of Moraxella osloensis, it is possible to convert type C skin to type M skin, which is useful for treating lacerations.

[0090] (7) For the first time, the present invention performs correlation analysis between a single bacterium and the skin phenotype, exploring the possibility that skin microorganisms may lead to changes in the host's skin phenotype, and providing new perspectives and angles for the study of interactions between microorganisms and hosts. (8) In this invention, in addition to studying correlations, the host surface cells are treated with bacterial supernatant to explore the relationship of interactions between bacteria and the host at the molecular level.

[0091] The present invention will be further described below with reference to specific examples. These examples are used solely to illustrate the present invention and are not intended to limit its scope. In the following examples, experimental methods where specific conditions are not described were typically carried out under normal conditions or conditions recommended by the manufacturer. Unless otherwise specified, percentages and parts were calculated by weight. Unless otherwise specified, all reagents and materials used in the examples of this invention are commercially available products.

[0092] Common method 1. Correlation analysis: 1) Skin microorganism sampling and metagenomic sequencing Volunteers for this study were recruited from the permanent resident population of Shanghai. All volunteers participating in this study were examined by physicians from the Department of Dermatology at Shanghai Dermatology Hospital to eliminate skin lesions such as dermatitis, eczema, contusions, psoriasis, and infections in the test area, and to ensure that there were no skin diseases in the past six months. At the same time, volunteers who had received systemic or topical antibiotic treatment in the past six months were excluded. Ultimately, 294 healthy subjects aged 20-65 years were recruited, of which 46 were male (M) and 248 were female (F) (Table 1). [Table 1]

[0093] On the day of sampling, the subjects washed their faces with water only and refrained from using any skincare products or cosmetics from the day before sampling. The sampling location was kept at a room temperature of 20°C and a humidity of 50%. The experimenter repeatedly swab approximately 4 cm in length from three areas of the subject's forehead (Fh), cheeks (Ch), and nasal wings (Ns) using a dedicated sterile swab soaked in 0.15M NaCl and 0.1% Tween20 solution. 2The area was wiped, and the process was repeated 20 times. The swab was then folded and placed in a 1.5 ml sterile EP tube, and stored frozen at -80°C in preparation for extraction of skin microbial genomic DNA. A schematic diagram of the collection site is shown in Figure 1.

[0094] Samples were amplified using whole-genome amplification, followed by metagenomic sequencing, ultimately yielding sequencing data for 822 facial skin microorganisms. The relative abundance of each gene was calculated using SOAP2 (version 2.21), and the sum of the relative abundances of genes from the same bacterial species was calculated from the comparison results of each gene. This sum was then used as the relative abundance of that bacterial species.

[0095] 2) Measurement of skin phenotype All phenotypic measurements of 294 Han Chinese subjects were performed in a room environment with a temperature of 20°C and a humidity of 50%. Before the test, subjects were allowed to rest for at least 30 minutes in a seated position to allow blood circulation to recover to normal levels after any possible physical activity. The area of ​​phenotypic measurement coincided with the microbial sampling site. Phenotypics such as skin sebum content, stratum corneum hydration, transepidermal water loss (TEWL), skin pH value, porphyrin, skin color (L*a*b), lentigines, pores, telangiectasia, and elasticity were measured using the following instruments (Table 2). [Table 2]

[0096] 3) Correlation analysis between bacterial abundance and skin phenotype The correlation between strain levels and phenotypes was evaluated by performing a correlation analysis (Spearman rank correlation) on the species levels distributed on the faces of 294 Chinese Han Chinese individuals for each bacterial colony, as well as on phenotypes such as sebum content, stratum corneum water content, transepidermal water loss, skin pH value, blemishes, porphyrins, skin color, and pores. The p-values ​​of the correlation analysis results were then validated using FDR, and since the calibrated p-value was <0.05, it was shown to be statistically significant. A correlation heatmap was created using the R software pheatmap package (version 1.0.12) and is shown as a result. Blue: negative correlation; Red: positive correlation; Spearman correlation significance levels: *, p<0.05; **, p<0.01; ***, p<0.001.

[0097] 2. Matrix metalloproteinase (MMP) expression experiment 1) Preparation of bacterial strain supernatant i. Frozen bacterial suspensions obtained from skin were taken and streaked onto corresponding petri dishes using the three-compartment streaking method, and then cultured. Single colonies formed on the plates. These single colonies were taken and inoculated into corresponding culture media for liquid culture. ii. After 24 hours of incubation, genomic DNA was extracted from the bacterial culture medium, and 16S rDNA detection was performed to confirm that the bacterial cultures of the three strains remained the target strains and were free from contamination by other bacteria.

[0098] iii. Liquid cultures were performed on the identified bacteria, and a simple culture medium without bacterial inoculation was provided as a control group. iv. The absorbance value at 600 nm detected by a microplate reader after culturing the bacterial suspension was approximately 0.8. v. The bacterial suspensions of three bacterial strains were filtered twice through a 0.22 μm filter to remove bacterial cells, leaving the bacterial supernatant. The same procedure was performed on the control group in a simple culture medium. vi. The supernatant obtained by filtering the bacteria and the supernatant of the simple culture medium were stored at -80°C for use.

[0099] 2) Incubation of HaCaT cells with bacterial supernatant i. Human keratinocytes (HaCaT cells) 1 × 10 6 Cell cultures were performed individually. A bacterial suspension supernatant treatment group (experimental group) and a culture medium-only control group were established, and three repeats were performed in each group. The culture plates were gently shaken to ensure uniform cell distribution, and the cells were cultured in an incubator at 37°C and 5% CO2. Table 3 shows the three types of bacteria used in this invention. ii. Next, the cells were incubated in an incubator for 24 hours, the cell culture medium was discarded, and the cells were lightly washed with PBS. Then, trypsin was added to each petri dish, and the dishes were digested in the incubator for 5 minutes. After that, the dishes were centrifuged at 800 x g for 5 minutes to collect the cells. [Table 3]

[0100] 3) Extraction of cellular RNA i. The collected HaCaT cells or primary fibroblasts were placed in Trizol reagent and left at room temperature for 10 minutes. ii. Trichloromethane was placed in a centrifuge tube, shaken to mix uniformly, and then allowed to stand for 5 minutes. iii. Centrifuge at 13200 rpm and 4°C for 10 minutes, and aspirate the upper aqueous phase (approximately 200 μL) into another centrifuge tube. iv. Add an equal volume of isopropanol, invert the mixture to mix uniformly, and let it stand at room temperature for 5 minutes. The sample was centrifuged at 13200 rpm and 4°C for 10 minutes. The supernatant was discarded, and a white precipitate was observed at the bottom of the tube.

[0101] vi. Add 75% ethanol (prepared with anhydrous ethanol and DEPC water, prepared immediately before use and cooled to -20°C before use), and gently shake the tube to allow the RNA precipitate at the bottom to float. vii. Centrifuge at 13200 rpm and 4°C for 10 minutes, discard the supernatant, and repeat the above two steps. viii. Centrifuge for 2 minutes, then use a pipette to remove as much of the remaining ethanol as possible, and leave the lid of the centrifuge tube open to air dry at room temperature for 5 minutes. ix. After dissolving the RNA in DEPC water, the purity and concentration of the RNA were measured using NanoDrop, and the RNA concentration of each sample was adjusted to a uniform 200 ng / μL.

[0102] 4) cDNA synthesis i. In this experiment, cDNA was synthesized by reverse transcription PCR using the Vazyme HiScript III RT SuperMix for qPCR (+gDNA wiper) kit. ii. A total of 1 μg of total RNA was taken and reverse transcribed, and the remaining RNA was stored at -80°C.

[0103] iii. Before reverse transcription, any contaminating genomic DNA in the RNA sample was first removed. A genomic DNA removal reaction mixture (RNA sample: 4 × gDNA wiper Mix: RNase-free ddH2O = 5:4:7) was prepared in an RNase-free 8-tube strip, and after being gently mixed with a pipette, 5 × HiScript qRT Super Mix at a volume ratio of 0.25 was added and mixed further. iv. The product was placed in a PCR instrument and reacted at 37 °C for 15 min and 85 °C for 5 s. After the reverse transcription process was complete, the product was either used immediately for qPCR or stored at -20 °C.

[0104] 5) Real-time quantitative PCR i. In this experiment, real-time quantitative PCR was performed using QIAGEN's QuantiFast SYBR Green PCR Kit to detect the relative expression levels of genes. ii. The primers listed in Table 4 below were prepared with DEPC water to a concentration of 2 μM, homogeneously mixed, and prepared for use. [Table 4]

[0105] iii. A real-time PCR reaction system was prepared in a 384-well plate with primer (2 μM):cDNA:SYBR Master Mix (2×) = 1:4:5. iv. The 384-well plate was placed in a centrifuge and centrifuged at 4°C and 3000 rpm for 3 minutes. The 384-well plate was then placed in the QuantStudio™ 7 Flex Real-Time PCR System and RT-PCR was performed. The reaction program is shown in Table 5 below. [Table 5]

[0106] v. Statistical processing of experimental results is performed using QuantStudio™ real-time PCR software, and further 2- △△T The relative expression levels of genes in each sample were calculated according to the method, and finally, the experimental results were analyzed using the T-test method in GraphPad Prism 5.0 software and graphs were created. Significance levels: *, p<0.05; **, p<0.01; ***, p<0.001.

[0107] Example 1: Microbiome composition of facial skin in a Han Chinese population Study Participants: This study was authorized by the Ethics Committee of the School of Life Sciences, Fudan University, and 294 healthy residents of Shanghai were recruited as volunteers. Of these, 46 were male (M) and 248 were female (F). Skin microorganisms were collected from three areas of the face: the forehead (Fh), cheeks (Ch), and nasal wings (Ns) (see Figure 1).

[0108] By combining metagenomic sequencing with bioinformatics analysis, we systematically characterized the composition and function of the healthy skin microbiome of the Han Chinese population. Comparing this data with that of American skin microbial samples from the Human Microbiome Project (HMP), we found that the Chinese population had significantly higher relative levels of the bacterium Moraxella osloensis (M. osloensis) than the American population. Moraxella osloensis was also present at relatively high levels in Singaporean Chinese, suggesting that this species may be one of the characteristic strains of the skin microbiota of East Asian populations (see Figure 2).

[0109] Example 2: Population classification analysis based on the skin microbiome The skin microbiome, like the gut microbiome, is influenced by many factors and exhibits significant individual differences. In this research, the present invention aims to uncover the underlying rules of the skin microbiome and provide new classification criteria for clinical diagnosis by classifying human populations of skin microorganisms based on enterotypes and exploring the driving factors that give rise to these classifications.

[0110] In this invention, we selected subjects for whom data on the skin microbiome of three different areas was available, totaling 247 participants. Based on skin microbiome data, skin type identification was performed for the 247 subjects. First, samples from three different sites were clustered using the PAM method, and then the optimal number of clusters was determined using the CH index. Referring to Figure 3, the CH index results showed that the highest CH index score occurred when there were two clusters, indicating that the optimal number of clusters for all three sites was two.

[0111] Based on these results, in this invention, a classification analysis was performed on the samples, dividing them into two types, and PCoA analysis was performed on the classification results of the samples from three different sites using JSD distance and Bray-Curtis distance. Referring to Figures 4A-L, the results show that the classification results of the samples from all three sites are effectively divided into two types, and the microorganisms that contribute most to this classification are Propionibacterium acnes and Moraxella osloensis, respectively. That is, one site is concentrated with Propionibacterium acnes, and the other site is concentrated with Moraxella osloensis. Based on these results, the two types of skin cutotypes were named C-Cutotype and M-Cutotype, respectively.

[0112] This invention differentiates C-Cutotype and M-Cutotype microbial colonies based on data from the skin microbiome of the forehead. Referring to Figure 5, the colors represent the relative level (e.g., relative abundance) of the microorganisms, with each column representing one sample and each row representing one microorganism. From the results of the differentiation analysis, it was found that some microorganisms prefer certain skin types, possibly due to the mutual influence between the microbial colonies. For example, in the C-Cutotype, Propionibacterium avidum, Propionibacterium granulosum, Staphylococcus species, Propionibacter acnes phage and / or Staphylococcus phage are concentrated. On the other hand, in the M-Cutotype, Moraxella bovoculi and Psychrobacter sp. are concentrated.

[0113] In this invention, correlation analysis was performed based on the level of differentiated microbial colonies and presented in the form of a network diagram. Referring to Figure 6, the results showed that there was a strong positive correlation among microorganisms concentrated in the same skin type, while there was a strong negative correlation among microorganisms in different skin types. From these analysis results, it can be seen that microorganisms concentrated in the same skin type each occupy different ecological positions, forming stable ecological networks, constructing powerful microbial colonies, and resisting the establishment of new microorganisms, including opportunistic and latent pathogenic microorganisms.

[0114] Based on these 247 individuals and a total of 741 samples, the M / C ratio (M / C), which is the criterion for classifying skin types by the level (e.g., content) of M bacteria and C bacteria, is shown in Table 6. [Table 6]

[0115] The specific reference values ​​for classification differ depending on the site of origin of the microorganism. The principle of sampling for skin classification in clinical applications is to classify the skin area on the face that requires improvement, and then refer to the above data. Furthermore, the full name of bacterium C is Cutibacterium acnes, and its level (e.g., abundance) is closely associated with skin contusions. There are very few reports on the association of bacterium M, and in this study, for the first time, a correlation between bacterium M and skin phenotypes has been found, positively correlated with age and correlated with certain skin aging phenotypes.

[0116] The inventors conducted experiments on the skin quality and M / C ratio changes in subjects and obtained the results shown in Table 2, which indicated that the M / C ratio is related to skin quality. As the level of M bacteria increased, skin oiliness decreased, water content decreased, glossiness decreased, and yellowness increased (skin darkened). This correlated with some typical characteristics of contusions; for example, as M bacteria increased, oiliness decreased, porphyrins (many of which are metabolites of C bacteria and may promote inflammation) decreased, and pore area decreased. Table 7 shows the correlation between related phenotypes and M / C values, and all of the listed phenotypes show a significant correlation (p<0.05). [Table 7]

[0117] Example 3: Biological significance of microbial skin type Based on the gene-level spectrum (e.g., abundance), PCoA analysis of samples revealed that the two skin types were effectively separated, and significant functional differences between them were observed. Specifically, the genes of the C-Cutotype were concentrated in the metabolism of carbohydrates and sterols and the synthesis of fatty acids, while in the M-Cutotype, many of the microbiome genes were associated with the synthesis of amino acids, aromatic compounds, and some lipids, such as inositol. Previous studies have reported that *Propionibacterium acnes* can utilize carbohydrates as a carbon source, and the concentration of gene function also indicates that 17 KEGG functional modules in the C-Cutotype are associated with the phosphate transferase system (PTS). In prokaryotes, this system is responsible for carbohydrate transport and phosphorylation and is known to be associated with the metabolic capacity of glucose, maltose, lactose, fructose, and cellobiose, suggesting that the C-Cutotype is dependent on carbohydrates as a nutrient source. In contrast, previous studies on Moraxella osloensis have shown that the microorganism cannot utilize any carbohydrates and relies on fatty acids and alcohols as carbon sources. This further indicates that the two cutaneous forms constitute colonies with two different nutritional requirements.

[0118] The skin microenvironment is the growth environment for skin microorganisms, and therefore determines the nutrients available to these microorganisms. To explore whether skin phenotypes are a driving factor for different skin types, we further analyzed the phenotypic differences between two skin types. Referring to Figure 7, the results show significant differences between the two skin types in stratum corneum moisture, oil content, and skin color. Compared to the C-Cutotype, the C-Cutotype has higher oil and water content, while the M-Cutotype has drier skin. Since oil is a major nutrient source for microorganisms, these results further suggest that differences in nutritional requirements are a driving factor leading to different skin types.

[0119] Furthermore, since the skin phenotype characteristics of M-Cutotype are similar to those of older individuals, we compared the two skin types to see if there were any differences. Referring to Figure 8, as expected, the age of the M-Cutotype group was significantly higher than that of the C-Cutotype group. However, further analysis revealed that both C-Cutotype and M-Cutotype existed in different age intervals, meaning that C-Cutotype exists in older individuals and M-Cutotype exists in younger individuals. Therefore, age is not the truly decisive factor; nutritional requirements are the direct decisive factor. Also, the age difference may be due to the influence of physiological changes in the host during the aging process on the skin phenotype, which could explain why M-Cutotype is associated with older ages.

[0120] Example 4: Correlation between Moraxella osloensis and skin aging phenotypes In this study, skin fungal colonies were collected from three areas—the forehead (Fh), cheeks (Ch), and nasal ala (Ns)—of 248 healthy female subjects residing in Shanghai. Correlation analysis was performed between Moraxella osloensis, age, and skin phenotype. Spearman coefficients were calculated, and p-values ​​were calibrated using the FDR method. A calibrated p-value of less than 0.05 was used as the screening criterion. Referring to Figure 9, the results showed that the levels of Moraxella osloensis in all three areas were significantly positively correlated with age and significantly negatively correlated with porphyrin. It was also positively correlated with age spots on the cheeks and negatively correlated with stratum corneum moisture and oil content on the cheeks and oil content on the forehead. Furthermore, Moraxella osloensis tended to have a weak positive correlation with other aging phenotypes.

[0121] Example 5: Potential targets of M bacteria in skin aging In M-Cutotype, a concentration of isocitrate lyase (aceA) and malate synthase (aceB) genes in the skin microbiome was observed. The function of these genes is related to the glyoxylate cycle, and studies have demonstrated that the glyoxylate cycle is involved in the degradation of ethoxy groups. These results provide a basis for the involvement of skin microorganisms in the degradation of polyoxyethylene octylphenyl ethers (OPEs). Furthermore, alkylphenols and short-chain polyoxy metabolites produced by OPE degradation have endocrine interfering activity. Among these, alkylphenol ethoxylates (APEs) have estrogen-like activity, and experiments have shown that such compounds can mimic the effects of estradiol both in vivo and ex vivo, and are called environmental estrogens. Therefore, skin microorganisms interfere with estradiol production, and estradiol is important for preventing skin aging (see Figure 10).

[0122] 1. Referring to Figure 11, the results of the gene function differentiation analysis showed that the M-Cutotype is concentrated in the β-carotene synthesis pathway, and this result indicates that the M-Cutotype synthesizes more β-carotene. β-carotene is associated with skin yellowing. 2. Keratinocytes were stimulated with a culture medium of M bacteria, and the potential senescence-inducing mechanism of M bacteria was explored using transcriptome techniques.

[0123] Intensive analysis of RNA-Seq-mediated signaling pathways of differentially expressed genes revealed that Moraxella osloensis can influence skin cells through signaling pathways, primarily involving the regulation of collagen synthesis and degradation. Referring to Figure 12, RNA-seq results showed that a large number of differential genes were concentrated in biological processes strongly associated with aging phenotypes, such as collagen metabolism and extracellular matrix degradation.

[0124] Example 6: Method for adjusting the level of Moraxella osloensis The aforementioned analysis revealed that Moraxella osloensis is associated to some extent with age and the phenotype of skin aging. In this study, we incubated Moraxella osloensis with a single skin surface compound and detected the number of viable cells to reflect the utilization of different skin surface compounds by the microorganism, as well as the toxicity of specific compounds to Moraxella osloensis. Ultimately, by adjusting the amount of compounds preferred or toxic to Moraxella osloensis, we can achieve the goal of delaying aging by regulating the growth of Moraxella osloensis.

[0125] Referring to Figure 13, this study investigated the effects of 32 different skin surface compounds on the growth of Moraxella osloensis using two methods: CCK-8 and Dye mix A. The compounds were L-lysine, L-glutamine, L-histidine, L-arginine, taurocholic acid, creatinine, D-glucose, L-lactic acid, glycerin, 2-carboxybenzaldehyde, urea, SDS, L-threonine, L-tryptophan, glycine, L-methionine, L-serine, L-glutamic acid, L-phenylalanine, L-cystine, L-tyrosine, L-leucine, L-isoleucine, L-ornithine hydrochloride, L-citrulline, L-proline, L-valine, L-alanine, D-aspartic acid, trans-4-hydroxy-L-proline, uric acid, and taurine. Of these, L-glutamine, L-histidine, L-serine, and L-proine have a significant promoting effect on the growth of Moraxella osloensis, while SDS has a significant inhibitory effect.

[0126] Example 7: Detection of human populations in other countries To verify whether the obtained skin type is widespread, we downloaded several publicly available datasets and examined the existence of the skin type based on skin microbiome data from different species, different body parts, and different health conditions.

[0127] First, metagenomic data from the inner elbow area (wet type) of Singaporean Chinese were used, including both patients with atopic dermatitis (AD) and healthy individuals. Referring to Figure 14, the samples from this data were effectively divided into two types, and, similar to the results mentioned above, one was concentrated with Propionibacterium acnes and the other with Moraxella osloensis. These results suggest that the presence of skin type is not influenced by skin health or location.

[0128] Furthermore, using publicly available metagenomic data from Filipino children (scalp and neck) and Italians with psoriasis, consistent results were obtained, as shown in Figure 15, indicating that the colonies are effectively divided into two types: one C-Cutotype and the other M-Cutotype. As described above, the present invention has demonstrated that a wide range of skin types exist and are not affected by skin location, race, health condition, etc.

[0129] Example 8: Skin condition classification system Based on the above embodiment, a skin condition classification system was researched and developed. The system includes a feature receiving module, a computation processing module, and a result output module, each module connected by wired or wireless means, and the classification process is as follows. (a) A sample of skin microorganisms is collected from the subject's face and detected, and skin sample characteristic data is generated. The skin sample characteristic data is at the levels of Moraxella osloensis and Propionibacterium acnes, respectively. Here, the collection site is the same as described in Example 1, and the detection method is as described in the same detection method. (b) Input the skin sample feature data into the system from the feature receiving module.

[0130] (c) The processing module receives skin sample feature data from the feature receiving module, calculates the respective ratios of Moraxella osloensis and Propionibacterium acnes or the relative ratio between them, and obtains a skin classification and / or skin condition determination result by comparing the obtained respective ratios or the relative ratio between them with standard values ​​for skin classification or characterization. (d) A result output module, which may be any terminal such as a display, printer, tablet PC (PAD), or smartphone, is used to receive and output the decision result. The system includes a single memory device, in which information about standard threshold values ​​is stored.

[0131] The corresponding standard values ​​for the aforementioned skin classification and / or skin condition are as follows: The skin type is type C (or type I): the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of Propionibacterium acnes satisfies the following conditions: M / C ≤ 1.3, preferably M / C ≤ 0.8, more preferably M / C ≤ 0.4. The skin condition of this phenotype is characterized by higher oil and water content and better skin elasticity.

[0132] The skin type is M (Type III): The ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis in the sample to the level (e.g., content) (C) of Propionibacterium acnes satisfies the following conditions: M / C ≥ 0.5, preferably M / C ≥ 1.8, more preferably M / C ≥ 2.2. The skin condition of this phenotype is characterized by poor oiliness, low water content, poor skin elasticity, and high skin aging.

[0133] The skin type is mixed (or type II): the ratio (M / C) of the level (e.g., content) (M) of Moraxella osloensis to the level (e.g., content) (C) of Propionibacterium acnes satisfies the following conditions: 0.3 ≤ M / C ≤ 2.5, preferably 0.3 ≤ M / C ≤ 2.3, more preferably 0.8 ≤ M / C ≤ 1.8. The skin condition of the phenotype is between type C and type M.

[0134] Example 9: Correlation analysis between bacteria and skin phenotypes The correlation between bacterial strains and phenotypes was evaluated by performing correlation analysis using R-software on the species level of Moraxella osloensis, Propionibacterium acnes, and Staphylococcus surfaceis, as well as on the host's skin phenotype, including sebum content, stratum corneum water content, transepidermal water loss, skin pH value, blemishes, porphyrins, skin color, and pores in three areas of the host's face (cheeks, forehead, and nasal wings).

[0135] As shown in Figure 16, the results of the correlation between the abundance of bacteria in the three sites and their phenotypes were consistent. Specifically, Moraxella osloensis was positively correlated with age and skin discoloration (blackening / yellowing) and negatively correlated with skin water content, sebum, and porphyrin content. Propionibacterium acnes showed the exact opposite trend to Moraxella osloensis. Staphylococcus surfaceis was negatively correlated with age spots and positively correlated with epidermal water content. Thus, it was suggested that the three types of bacteria are related to skin aging to some extent.

[0136] Example 10 Molecular-level verification of skin cell treatment with bacterial supernatant We treated keratinocytes (HaCaT cell line), the most abundant cells in the host epidermis, with bacterial supernatants of Moraxella osloensis, Propionibacterium acnes, and Staphylococcus surfaceis, respectively, and investigated the changes in cell expression profiles after incubation using QPCR. We focused on matrix metalloproteinases (MMPs), genes mainly involved in collagen degradation and extracellular matrix assembly. In particular, MMPs are responsible for the degradation of extracellular matrix (ECM) proteins and promote photoaging. Through molecular-level verification, we explored the relationship between bacterial and host skin phenotypes.

[0137] As shown in Figures 17-19, QPCR results showed that HaCaT cells treated with Moraxella osloensis supernatant significantly increased the expression levels of MMP1, MMP10, MMP12, and MMP13 compared to the control group. However, there was no significant difference in MMP expression levels after treating HaCaT cells with Propionibacterium acnes and Staphylococcus epidermidis supernatants. This demonstrates that Moraxella osloensis promotes skin aging in the host, and at the same time, that the promotion of skin aging by skin microorganisms is not a universal effect, but rather an effect possessed by specific bacterial species.

[0138] All documents relating to the present invention are cited herein by reference, so that each document may be cited independently. Furthermore, after reading the above, those skilled in the art will understand that various variations and modifications of the present invention may be made, and that equivalent forms thereof are included within the scope of the claims of the present invention.

Claims

1. The use of a combination of Moraxella osloensis and Propionibacterium acnes or a reagent for detecting them, wherein the relative value between the level of Moraxella osloensis and the level of Propionibacterium acnes is (a) For the manufacture of reagents or kits used for skin classification and / or (b) for the determination or characterization of skin conditions. The use described above is characterized by being such.

2. The use according to claim 1, characterized in that the skin condition includes skin age, skin water content, skin elasticity, skin color, and degree of skin aging.

3. (a) A method for skin classification and / or (b) characterization of skin conditions, comprising the following steps: (1) Provide a skin sample from the subject of the study, detect the levels of Moraxella osloensis and Propionibacterium acnes in the sample, and obtain the levels of Moraxella osloensis (M) and Propionibacterium acnes (C), respectively; (2) Characterizing the skin classification and / or skin condition of the subject by comparing the level (M) of Moraxella osloensis and the level (C) of Propionibacterium acnes in the sample, Here, the skin classification and / or characterization of the skin condition of the sample is performed based on the relative values ​​of the levels of Moraxella osloensis (M) and Propionibacterium acnes (C) (e.g., M / C); If the ratio of the level (M) of Moraxella osloensis to the level (C) of Propionibacterium acnes in the sample (e.g., M / C) is M / C ≤ 0.8, then the skin classification is type C (or type I), and the skin condition includes high oil content, high water content, good skin elasticity, low degree of skin aging, and light skin color. If the ratio of the level (M) of Moraxella osloensis to the level (C) of Propionibacterium acnes in the sample (e.g., M / C) is 0.8 ≤ M / C ≤ 1.8, then the skin classification is mixed (or type II), and the skin condition includes moderate oil content, moderate water content, normal skin elasticity, moderate skin aging, and moderate skin color. If the ratio of the level (M) of Moraxella osloensis to the level (C) of Propionibacterium acnes in the sample (e.g., M / C) is M / C ≥ 1.8, the skin classification is type M (type III), and the skin condition includes low oil content, low water content, poor skin elasticity, high degree of skin aging, and dark skin color. The method characterized by the above.

4. A reagent for detecting skin classification and / or skin condition, characterized by comprising a reagent for detecting Moraxella osloensis and Propionibacterium acnes.

5. A kit characterized by containing the reagent described in claim 4.

6. A system for classifying the skin of a test subject and / or determining the skin condition of a test subject, the following: (a) A feature receiving module for receiving skin sample feature data, the feature data including information on the quantitative determination of Moraxella osloensis (M) and Propionibacterium acnes (C) in the skin sample; (b) A module for obtaining a determination result for skin classification and / or skin condition by calculating feature data from the feature receiving module in a calculation processing module to obtain the ratio of each feature or the ratio relationship between each feature, and comparing the obtained ratio or ratio relationship between each feature with standard values ​​for skin classification or characterization; (c) A module for receiving and outputting the judgment result in the result output module. The system, characterized by including the above.

7. The system according to claim 6, characterized in that the method for obtaining the quantitative information includes sequencing, PCR, and protein quantitative detection.

8. A method for screening substances or ingredients that improve skin condition, comprising the following steps: (a) To provide a screening bacterium comprising Moraxella osloensis (M), Propionibacterium acnes (C), or Moraxella osloensis and / or Propionibacterium acnes; (b) Co-culturing the substance or component to be screened with the screening bacteria, and detecting the respective levels of Moraxella osloensis or Propionibacterium acnes, or the relative levels (M / C) between Moraxella osloensis and Propionibacterium acnes; (c) Determining whether the substance or component being screened is a substance or component that improves skin condition, based on the respective levels of Moraxella osloensis or Propionibacterium acnes after culturing in (b), or the relative levels (M / C) between Moraxella osloensis and Propionibacterium acnes. The method, wherein in step (c), if the level of Moraxella osloensis increases, or the relative level (M / C) between Moraxella osloensis and Propionibacterium acnes increases, or the level of Propionibacterium acnes decreases, or the relative level (C / M) between Propionibacterium acnes and Moraxella osloensis decreases, the substance or component being screened is a substance for treating contusions, and / or in step (c), if the level of Moraxella osloensis decreases, or the relative level (M / C) between Moraxella osloensis and Propionibacterium acnes decreases, or the level of Propionibacterium acnes increases, or the relative level (C / M) between Propionibacterium acnes and Moraxella osloensis increases, the substance or component being screened is a skin anti-aging substance.

9. Use of the reagent according to claim 4, (a) To manufacture kits for skin classification and / or for determining or characterizing skin conditions, and / or (b) For screening substances or ingredients that improve skin condition The use described above is characterized by being such.

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