NCRD: A non-redundant comprehensive database for detecting antibiotic resistance genes

Area of Science:

• Environmental Science
• Microbiology
• Bioinformatics

Background:

• Antibiotic resistance genes (ARGs) are increasingly recognized as environmental pollutants.
• Current ARG databases (ARDB, CARD, SARG) have limitations for comprehensive environmental profiling.
• Accurate identification of ARGs is crucial for environmental monitoring and risk assessment.

Purpose of the Study:

• To develop a non-redundant, comprehensive database for improved ARG detection.
• To address the limitations of existing ARG databases in environmental sample analysis.
• To enhance the identification of potential ARGs in diverse environmental matrices.

Main Methods:

• Consolidated sequences from ARDB, CARD, and SARG to create a non-redundant database (NRD).
• Identified homologous proteins from NR and PDB databases.
• Clustered proteins to establish non-redundant comprehensive antibiotic resistance genes databases (NCRD) at 100% (NCRD100) and 95% (NCRD95) similarity.
• Compared NCRD performance against other databases using metagenome datasets.

Main Results:

• The developed NCRD database demonstrated superior performance in detecting potential ARGs.
• Metagenome dataset analysis confirmed the enhanced ARG identification capabilities of NCRD.
• NCRD provides a more comprehensive profile of ARGs in environmental samples compared to existing databases.

Conclusions:

• The novel NCRD database significantly improves the comprehensive profiling of antibiotic resistance genes in environmental samples.
• NCRD offers a valuable tool for researchers studying the spread and impact of ARGs in various environments.
• This enhanced database facilitates more accurate risk assessments related to antibiotic resistance pollution.