Kimchi is a traditional Korean food prepared by fermenting vegetables, such as Chinese cabbage and radishes, which are seasoned with various ingredients, including red pepper powder, garlic, ginger, green onion, fermented seafood (
Kimchi is a salty, fermented preparation of cabbage that is widely consumed in the traditional Korean diet. Certain types of kimchi are prepared by mixing salted cabbage with spicy ingredients, such as red pepper powder, garlic, and ginger, while others are prepared without red chili pepper or are soaked in a savory liquid. Kimchi is prepared by mixing cabbage well with other vegetables, fish seasoning, and salt, and packing it into jars. The various unique microorganisms [
In particular, the red chili pepper, the component of kimchi that makes it spicy, is a potent antioxidant due to its high vitamin C levels and capsaicin content. Furthermore, red pepper inhibits the decay of microorganisms and prevents food from spoiling. The physiological effects of kimchi thus originate from bioactive compounds present in its ingredients, and the functions of these are amplified by the fermentation process. Therefore, the health-promoting, probiotic, and functional properties of kimchi can be optimized by manipulating the types and amounts of ingredients, and by using appropriate probiotic starters and kimchi preparation methods such as fermentation. Optimally produced kimchi can be a very healthy food [
However, the available genome, biological pathway, and related disease data are still insufficient to explain the health benefits of kimchi. An integrated database of these data is not available, because it is difficult to control for the heterogeneous data types. Furthermore, biological processes are interrelated on many levels and their regulation presents complexity. These interactions must be understood in detail to successfully manage risks in the development of biological products. Evidence-based information on kimchi should be provided by both public and proprietary information sources, including public databases, experimental results from individual studies, text-mining analyses, and knowledge management systems. The model integrating this data would represent the accumulated knowledge in this domain that could be browsed and mined interactively. In this study, we have constructed the proper semantic data model and extracted integrated information on kimchi's nutritional content, and its effects on physiology and disease, based on analyses of the functional and biological characteristics of kimchi in the scientific literature.
We used a semantic tool for knowledge base management, BioXM (Biomax Information AG, Munchen, Germany), which was developed for object-oriented semantic integration. In this approach, semantically identical objects and the associations between them are identified and mapped based on data and descriptive meta-information [
Pathway Studio software 9.0 (Elsevier, Atlanta, GA, USA) was used to collect information on biological processes and diseases related to kimchi, based on information in the Korean Food Standard Reference (KFSR). Pathway Studio software allows the automatic extraction of regulatory and physical interactions from MEDLINE abstracts using a natural-language-processing technology called MedScan [
Elements and relations were maintained and linked by relation and object. This semantic model enabled elements to be mapped to known elements. Relations between biological data are used to efficiently extract interactions of interest. The semantic modeling in this study was configured in the generic BioXM knowledge management environment to create a knowledge base for this translational systems biology approach. We constructed semantic networks for the discovery of a network biomarker using BioXM software (Biomax Information AG), which is a customizable knowledge base management tool for scientific data. The graphical data model is shown in
This semantic model enabled us to integrate existing public databases and experimental data derived from the literature. To populate the knowledge base with data from public databases, we manually generated mappings in import-templates. A graphical wizard for import-template generation provided a selection of possible import options and mappings.
The United States Department of Agriculture (USDA) food and nutrient databases provide the basic infrastructure for food and nutrition research, nutrition monitoring, policy, and dietary practice. The databases date back to 1892 and they are unique, as the only databases available in the public domain that perform these functions. The Nutrient Data Laboratory develops and maintains the USDA Standard Reference and related data products [
We found a total 4,351 genes strongly associated with kimchi's secondary metabolites using the KFSR, as shown in
Kimchi is effective in enhancing immune function [
For a long time, many nutritionists have believed, based on metabolomics data, that well-fermented kimchi has numerous anti-biotic activities [
This work was supported by a grant from the Korea Food Research Institute.
Semantic object | Description | Example |
---|---|---|
Element | Represents a basic unit of a knowledge model | The "Foods" element type can be used to create the "Kimchi element; the "Metabolites" element type can be used to create the "Capsaicin" metabolite term element. |
Relation | Describes a relation between semantic objects | "Foods-Metabolites" relation; "Foods” are associated with Metabolites" relation |
Annotation | Extends the properties of a semantic object by a set of attributes | Gene Ontology ID, KEGG ID, HMGD ID, Disease Name, Drug ID, Omin ID Pathway, Chemical ID |
Ontology | Classifies semantic objects according to a defined hierarchical nomenclature of concepts | Gene Ontology to classify biological functions |
Context | Represents sets of semantic objects | Metabolic pathways, protein complexes, or disease |
Entity | Record No. | Entity data source | Relation | Record No. |
---|---|---|---|---|
Foods | 5 | Korean foods | Food_Group-Foods | 5 |
Food_Name | 7,914 | USDA ( |
Foods-Food_Name | 31 |
Food_Group | 27 | USDA ( |
Food_Name-Food_Group | 7,909 |
Metabolites | 40,286 | HMDB ( |
Food_Name-Metabolites | 12,697 |
geneR | 23,252 | UCSC ( |
Metabolites-drugR | 1,575 |
CNVR | 20,052 | Cancer genome ( |
Metabolites-diseaseR | 1,019 |
diseaseR | 9,648 | CTD ( |
Metabolites-geneR | 327,973 |
chemicalR | 144,435 | CTD ( |
geneR-CNVR | 21,591 |
pathwayR | 362 | CTD ( |
geneR-chemicalR | 308,405 |
CTR (clinical trials) | 1,273 | CT ( |
geneR-pathwayR | 60,057 |
drugR | 6,712 | DB ( |
chemicalR-drugR | 1,702 |
GOR (Gene Ontology) | 38,092 | GO ( |
CTR-drugR | 1,419 |
SNPR | 14,901,097 | 1000 genomes ( |
CTR-diseaseR | 1,210 |
pathwayR-chemicalR | 43,139 | |||
diseaseR-chemicalR | 842,368 | |||
geneR-SNPR | 15,240,996 | |||
geneR-diseaseR | 97,806,909 | |||
Total | 15,193,155 | Total | 26,848,859 |
USDA, United States Department of Agriculture; HMDB, Human Metabolome Database; UCSC, University of California, Santa Cruz; CNVR, copy number variation region; CTD, comparative toxicogenomics database; SNPR, single nucleotide polymorphism relation.
KEGG pathway map | No. of genes | |
---|---|---|
1. Metabolism | ||
1.1 Carbohydrate metabolism | 283 | |
1.2 Energy metabolism | 109 | |
1.3 Lipid metabolism | 309 | |
1.4 Nucleotide metabolism | 154 | |
1.5 Amino acid metabolism | 229 | |
1.6 Metabolism of other amino acids | 99 | |
1.7 Glycan biosynthesis and metabolism | 104 | |
1.8 Metabolism of cofactors and vitamins | 170 | |
1.9 Metabolism of terpenoids and polyketides | 16 | |
1.10 Biosynthesis of other secondary metabolites | 11 | |
1.11 Xenobiotic biodegradation and metabolism | 102 | |
2. Genetic information processing | ||
2.1 Transcription | 23 | |
2.2 Translation | 95 | |
2.3 Folding, sorting, and degradation | 108 | |
2.4 Replication and repair | 34 | |
3. Environmental information processing | ||
3.1 Membrane transport | 16 | |
3.2 Signal transduction | 429 | |
3.3 Signaling molecules and interactions | 127 | |
4. Cellular Process | ||
4.1 Transport and catabolism | 221 | |
4.2 Cell motility | 89 | |
4.3 Cell growth and death | 93 | |
4.4 Cell communication | 168 | |
5. Organismal systems | ||
5.1 Immune system | 220 | |
5.2 Endocrine system | 210 | |
5.3 Circulatory system | 117 | |
5.4 Digestive system | 207 | |
5.5 Excretory system | 89 | |
5.6 Nervous system | 291 | |
5.7 Sensory system | 41 | |
5.8 Development | 95 | |
5.9 Environmental adaptation | 84 | |
6. Human disease | ||
6.1 Cancers | 225 | |
6.2 Immune diseases | 39 | |
6.3 Neurodegenerative diseases | 154 | |
6.4 Substance dependence | 136 | |
6.6 Cardiovascular diseases | 30 | |
6.7 Endocrine and metabolic diseases | 25 | |
6.8 Infectious diseases | 298 |