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Updated: Jun 9, 2026

Efficient Nucleic Acid Extraction and 16S rRNA Gene Sequencing for Bacterial Community Characterization

Efficient Nucleic Acid Extraction and 16S rRNA Gene Sequencing for Bacterial Community Characterization

Published on: April 14, 2016

Profiling lateral gene transfer events in the human microbiome using WAAFLE.

Tiffany Y Hsu¹, Etienne Nzabarushimana^1,2, Dennis Wong³

¹Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Nature Microbiology

|January 3, 2025

Summary

Lateral gene transfer (LGT) is crucial for microbial evolution. A new tool, WAAFLE, reveals widespread LGT in human microbiomes, uncovering over 100,000 new events and highlighting its significant role in genomic diversification.

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Efficient Nucleic Acid Extraction and 16S rRNA Gene Sequencing for Bacterial Community Characterization

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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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Published on: December 7, 2021

Area of Science:

Microbiology
Genomics
Bioinformatics

Background:

Lateral gene transfer (LGT) drives microbial genomic diversification.
Previous studies focused on isolate genomes, leaving the LGT landscape in complex human microbiomes poorly understood.
Lack of standardized methods hinders LGT characterization from metagenomic data.

Purpose of the Study:

To develop and validate a computational algorithm for profiling LGT from assembled metagenomes.
To characterize the prevalence and patterns of LGT in diverse human microbiomes.
To identify factors influencing LGT frequency and distribution.

Main Methods:

Development and benchmarking of the WAAFLE (Workflow to Annotate Assemblies and Find LGT Events) algorithm.
Application of WAAFLE to over 2,000 human metagenomes from various body sites.
Analysis of LGT events, associated mobile elements, and functional enrichment.

Main Results:

Identified over 100,000 high-confidence, previously uncharacterized LGT events.
Discovered LGT events enriched for mobile elements and restriction-modification systems.
Found LGT frequency influenced by biogeography, phylogenetic relatedness, and donor abundance.

Conclusions:

The WAAFLE algorithm provides a sensitive and specific method for detecting intergenus LGT in metagenomes.
Human microbiome LGT is more ubiquitous than previously recognized.
Biogeographical factors and microbial community structure shape LGT networks.