In the realms of genomics and systems biology, the intricate elucidation of gene function and its multifaceted interplay within cellular processes emerges as an unequivocally momentous pursuit. It is in this grand pursuit that the Kyoto Encyclopedia of Genes and Genomes (KEGG) assumes a pivotal role, offering an all-encompassing repository of knowledge and an array of sophisticated analytical tools that serve to bridge the chasm between genomic information and the revelation of higher-order functional insights. By ingeniously integrating genomic and molecular data, KEGG proffers a holistic database and a profound analytical platform, poised to illuminate the fundamental processes that underlie the intricate machinations of cells, organisms, and ecosystems alike. At the very heart of this expansive platform lies the KEGG Pathway Analysis, a prodigious component designed to unravel the labyrinthine interactions between genes, proteins, and compounds, thereby laying bare the hidden mechanisms that deftly govern cellular function.
The essence of KEGG Analysis lies in an intricate tapestry of computational techniques and resources, all intently aimed at unraveling the labyrinthine connections between genes, proteins, and chemicals that intricately weave the fabric of biological systems. Marrying genomic information with higher-order functional insights, KEGG emerges as a harbinger of profound revelations, bestowing upon researchers invaluable insights into gene function, disease knowledge, and drug information. Through a carefully orchestrated symphony of computational operations, KEGG Analysis affords researchers the ability to discern gene function, predict the cascading effects of diverse conditions upon biological pathways, and thereby navigate the vast seas of biological complexity.
The magnificence of the KEGG database resides in its rich interconnection of multiple interconnected databases, collectively constituting an expansive reservoir of information for pathway analysis. These constituent databases, artfully classified into four sprawling categories, engender a veritable cornucopia of biological knowledge: systems information, genomic information, chemical information, and health information. Each database, diligently updated on a daily basis, is bestowed freely upon the academic community, emblematic of KEGG's commitment to the dissemination of knowledge for the betterment of scientific inquiry (http://www.genome.ad.jp/kegg/).
The systems information databases in KEGG provide a broad understanding of biological processes and their interconnections. These include databases such as KEGG PATHWAY, which contains graphical representations of a variety of cellular processes, including metabolism, signal transduction, membrane transport, and the cell cycle. These pathway maps allow researchers to visualize and analyze the complex networks of molecular interactions within biological systems.
Genomic information databases in KEGG, such as the GENES database, store gene catalogs for fully sequenced genomes and partial genomes. These catalogs contain up-to-date annotations of gene function and can serve as portals for more detailed information about individual genes. Molecular-level functions are stored in the KO (KEGG Orthology) database, where each KO is defined as a functional ortholog of genes and proteins. By exploring the genomic information in KEGG, researchers can predict gene function, identify immediate homologous genes and gain insight into the genetic makeup of different organisms.
Fig. 1. Procedures used to organize and annotate the GENES database. (Kanehisa M, et al., 2000)
KEGG's chemical information databases, collectively known as KEGG LIGAND, focus on compounds, enzyme molecules, and enzymatic reactions. These databases provide researchers with a comprehensive understanding of the chemistry involved in biological processes. By exploring KEGG LIGAND, scientists can discover valuable information about the structure, function, and interactions of various molecules in cells.
The Health Information category in KEGG combines health-related data with drug labeling to form the KEGG MEDICUS database. The database is a valuable resource for researchers interested in exploring the links between diseases, genes, and drug treatments. By utilizing KEGG Medicus, researchers can gain insight into disease pathways, explore potential drug targets and identify therapeutic interventions.
Table 1. The KEGG databases. (Kanehisa M, et al., 2017)
KEGG Mapper: KEGG PATHWAY/BRITE/MODULE mapping tools.
BLASTKOALA: Blast-based KO annotation and KEGG mapping.
GHOSTKOALA: Ghostx-based KO annotation and KEGG mapping.
KOFAMKOALA: HMM profile-based KO annotation and KEGG mapping.
BLAST: Sequence similarity search.
SIMCOMP: Chemical structure similarity search.
Fig. 2. Examples of (a) the BlastKOALA result page and (b) the GhostKOALA result page. (Kanehisa M, et al., 2000)
Step 1: Data Retrieval
The journey into the intricacies of KEGG pathway analysis commences with the meticulous retrieval of the essential genomic and gene expression data. The pursuit of knowledge necessitates the acquisition of genome sequences and gene expression profiles sourced from high-throughput sequencing experiments or other pertinent datasets. Ensuring the accuracy and completeness of the data is critical to obtaining reliable results.
Step 2: Pathway Mapping
After collecting data, researchers can move on to pathway mapping, which involves linking genomic information to the KEGG PATHWAY database. By comparing the content of genes in the genome to pathways in the database, researchers can identify pathways and associated functions encoded within the genome. This step is facilitated by computational tools provided by KEGG that allow the automatic matching of genes and gene products to pathway maps.
Step 3: Enrichment Analysis
KEGG pathway analysis has achieved a triumphant milestone with the advent of enrichment analysis, which is key to elucidating pathways that are profoundly affected in support of specific experimental conditions. Comparisons between gene expression profiles or other relevant datasets and KEGG pathway maps can reveal the most relevant and enriched pathways in the experimental setting. This information provides an understanding of the underlying biological processes, allowing further scientific inquiry to be sensitively prioritized. Explore with our KEGG Enrichment Analysis Service for more information.
Step 4: Data Interpretation
The final step of KEGG pathway analysis involves interpreting the results and extracting meaningful conclusions. Researchers can identify key pathways that are significantly affected, explore the relationships between genes and gene products in these pathways, and reveal potential regulatory mechanisms or biological functions. The wealth of information provided by KEGG helps provide insight into the molecular mechanisms that control cellular processes and can guide further experiments and research.