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Updated: Oct 1, 2025

Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing

Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing

Published on: March 19, 2018

Quantifying and Cataloguing Unknown Sequences within Human Microbiomes.

Sejal Modha¹, David L Robertson¹, Joseph Hughes¹

¹MRC University of Glasgowgrid.8756.c Centre for Virus Research, Glasgow, United Kingdom.

|March 8, 2022

Summary

This summary is machine-generated.

Researchers developed a framework to analyze unknown sequences in human microbiomes. They found an average of 2% of sequences are undefined, with higher proportions in skin and oral microbiomes, leading to new microbe discoveries.

Keywords:

dark matter genome assembly human microbiome metagenomics microbial dark matter novel sequences unknown sequences virus

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Last Updated: Oct 1, 2025

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Published on: March 19, 2018

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Published on: October 15, 2019

Area of Science:

Microbiology
Genomics
Bioinformatics

Background:

Genome sequencing advances generate vast amounts of microbiome data.
A significant portion of this data, termed "dark matter," remains unclassified.
This unknown sequence proportion is often excluded from analyses.

Purpose of the Study:

To develop a systematic framework for analyzing unknown sequences in human microbiomes.
To quantify the proportion of unclassified sequences across various human microbiome types.
To identify novel microbial sequences and assess their prevalence.

Main Methods:

A computational framework was developed for assembling, identifying, and measuring unknown sequences.
The framework was applied to 963 samples from 40 studies across 10 human microbiomes.
Publicly available data and novel sequences were shared for future research.

Main Results:

An average of 2% of assembled sequences across human microbiomes were taxonomically undefined.
Skin and oral microbiomes showed higher proportions of unknown sequences (up to 25%).
A taxonomic characterization rate of 1.64% per month was calculated, and novel viral genomes were discovered.

Conclusions:

Systematic characterization of unknown sequences is crucial for discovering novel microbes.
The developed framework and novel sequences aid in classifying the "dark matter" of microbiomes.
Community-wide collation and sharing of unknown sequences can accelerate microbiome research.