Breaking free from references: a consensus-based approach for community profiling with long amplicon nanopore data

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• Third-generation sequencing (e.g., Oxford Nanopore Technology) enables long amplicon sequencing for enhanced taxonomic resolution.
• High error rates in long-read sequencing pose challenges for accurate microbial community profiling.
• Existing tools may struggle with closely related strains and require extensive reference databases.

Purpose of the Study:

• To introduce and validate CONCOMPRA, a novel bioinformatics tool for detecting closely related strains in microbial communities.
• To assess CONCOMPRA's performance against other tools for bacterial community profiling using full-length 16S rRNA gene sequencing.
• To highlight the importance of chimera detection in long amplicon sequencing data.

Main Methods:

• CONCOMPRA drafts and maps sequences to consensus sequences for strain-level detection.
• Utilizes full-length 16S rRNA gene sequencing data.
• Compares CONCOMPRA's performance with other community profiling tools.
• Includes validation tests for chimera detection in long PCR products.

Main Results:

• CONCOMPRA demonstrates superior performance in profiling bacterial communities compared to other tools.
• The tool effectively detects closely related strains, improving taxonomic resolution.
• Validation confirmed that CONCOMPRA is database-independent, broadening its applicability.
• Chimeric byproducts were identified as a significant issue inflating diversity and skewing community structure.

Conclusions:

• CONCOMPRA is a robust and versatile tool for microbial community analysis using long-read sequencing.
• The tool addresses the challenge of high error rates and strain-level resolution.
• Its database-independent nature makes it valuable for novel or under-characterized systems.
• Accurate chimera detection is crucial for reliable microbial community profiling with long amplicons.