KEGG Degradation Database Schema¶

Formal specification of the KEGG Degradation Database v1.0.0 schema

This document provides a comprehensive technical specification of the KEGG Degradation Database schema, containing genes involved in xenobiotic and pollutant degradation pathways extracted from KEGG.

Overview¶

The KEGG Degradation Database uses a flat, denormalized schema optimized for gene-pathway queries. The schema consists of a single table with 3 columns representing KO-pathway-genesymbol associations for degradation pathways.

Design rationale:

• Simplicity — Minimal 3-column structure for focused pathway analysis
• KEGG-sourced — All data extracted from official KEGG pathways
• Interoperability — Standard CSV format ensures compatibility with bioinformatics pipelines
• Cross-reference ready — KO identifiers enable integration with BioRemPP and HADEG databases

Schema Definition¶

Table: KEGG Degradation Database v1.0.0¶

Primary format: CSV (Comma-Separated Values)

Rows: 855 (as of v1.0.0)

Columns: 3

Character encoding: UTF-8

Field delimiter: Semicolon (;)

Text qualifier: Double quote (")

Header row: Yes (column names in first row)

Column Specifications¶

Data completeness: 100% — Zero missing values across all fields

Column 1: ko¶

Column name: ko

Data type: Character (string)

Format: KEGG Orthology identifier

Pattern: K##### (capital K followed by exactly 5 digits)

Example: K00001, K00002, K00022

Controlled vocabulary: Yes — Values must exist in KEGG Orthology database

Uniqueness: Not unique — 517 unique KO entries, some appear in multiple pathways

Purpose: Links genes to functional orthologs in KEGG for cross-database integration

Cross-references:

• KEGG Orthology database: https://www.kegg.jp/entry/K#####
• KEGG Pathway maps
• BioRemPP Database (via ko column)
• HADEG Database (via ko column)

Validation rules:

• ✅ Must match regex: ^K\d{5}$
• ✅ Must exist in KEGG Orthology database
• ✅ Case-sensitive (uppercase K required)

Cardinality: 517 unique KO entries in v1.0.0

Column 2: pathname¶

Column name: pathname

Data type: Character (string)

Format: Pathway name (human-readable)

Example: Naphthalene, Cytochrome P450, Aromatic, Chloroalkane

Controlled vocabulary: Partially — 20 standardized pathway names

Uniqueness: Not unique — Multiple genes belong to each pathway

Purpose: Categorizes genes by their KEGG degradation pathway

Valid pathway names:

Validation rules:

• ✅ Must be non-empty string
• ✅ Should match one of 20 documented pathways

Cardinality: 20 unique pathways in v1.0.0

Column 3: genesymbol¶

Column name: genesymbol

Data type: Character (string)

Format: Standard gene nomenclature (free text)

Example: E1.1.1.1, AKR1A1, HADH, nahAc

Controlled vocabulary: No — Free text, sourced from KEGG KO annotations

Uniqueness: Not unique — 513 unique symbols, some shared across pathways

Purpose: Provides short gene abbreviation for the associated KO group

Naming conventions:

• EC number format for enzymes (e.g., E1.1.1.1)
• HUGO nomenclature for human genes (e.g., AKR1A1)
• Organism-specific symbols for microbial genes (e.g., nahAc)

Validation rules:

• ✅ Must be non-empty string
• ✅ Should correspond to KEGG KO annotation

Cardinality: 513 unique gene symbols in v1.0.0

Schema Constraints and Relationships¶

Primary Key¶

None defined — Database uses a flat structure without explicit primary key

Conceptual primary key: Combination of (ko, pathname) approximates uniqueness

Foreign Key Relationships¶

Conceptual foreign keys (not enforced):

• ko → KEGG Orthology database
• ko → BioRemPP Database
• ko → HADEG Database

Cross-table joins:

Users can join KEGG Degradation Database with:

• BioRemPP Database — via ko column (compound-gene relationships)
• HADEG Database — via ko column (pathway details)
• KEGG Orthology — via ko column

Cardinality Relationships¶

KO-to-Pathway¶

Many-to-Many — One KO can participate in multiple pathways, and one pathway contains multiple KOs

Example:

• K00001 → 3 different pathways
• Naphthalene → 50+ KO entries

Data Quality Specifications¶

Completeness¶

100% field completeness — Zero missing values across all 3 columns

Verification:

db <- read.csv("data/databases/kegg_degradation_db.csv", sep=";")
colSums(is.na(db))  # Should return all zeros

Consistency¶

Identifier format consistency:

• All ko values match ^K\d{5}$

Verification:

# Verify KO ID format
all(grepl("^K\\\\d{5}$", db$ko))  # Should return TRUE

Accuracy¶

Data provenance:

• ko — Sourced from KEGG Orthology database
• pathname — Extracted from KEGG Pathway database
• genesymbol — Sourced from KEGG KO annotations

Source: KEGG Pathway Database — Metabolism → Xenobiotics biodegradation and metabolism

Usage Examples¶

Loading the Database¶

# Load database
library(readr)
db <- read_delim("data/databases/kegg_degradation_db.csv", delim=";")

# Inspect schema
str(db)
# tibble [855 × 3]
#  $ ko         : chr  "K00001" "K00002" "K00022" ...
#  $ pathname   : chr  "Naphthalene" "Cytochrome P450" ...
#  $ genesymbol : chr  "E1.1.1.1" "AKR1A1" ...

import pandas as pd

# Load database
db = pd.read_csv("data/databases/kegg_degradation_db.csv", sep=";")

# Inspect schema
db.info()
# <class 'pandas.core.frame.DataFrame'>
# RangeIndex: 855 entries, 0 to 854
# Data columns (total 3 columns):
#  #   Column      Non-Null Count  Dtype 
# ---  ------      --------------  ----- 
#  0   ko          855 non-null    object
#  1   pathname    855 non-null    object
#  2   genesymbol  855 non-null    object

Common Queries¶

# Find all genes in naphthalene degradation
naphthalene_genes <- db[db$pathname == "Naphthalene", ]

# Count genes per pathway
table(db$pathname)

# Find pathways for a specific KO
ko_pathways <- unique(db[db$ko == "K00001", "pathname"])

Questions?¶

GitHub Issues: https://github.com/BioRemPP/biorempp_db/issues
Email: biorempp@gmail.com