Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Modern Molecular Taxonomy

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Clues to Long COVID Linked to Virulence and Infectivity Found in Shell Proteins.

Advances in respiratory medicine·2026

Same author

Genome mining identifies a diversity of natural product biosynthetic capacity in human respiratory <i>Corynebacterium</i> strains.

mSphere·2025

Same author

Human milk oligosaccharides are associated with maternal genetics and respiratory health of human milk-fed children.

Nature communications·2024

Same author

A Comparative Experimental and Computational Study on the Nature of the Pangolin-CoV and COVID-19 Omicron.

International journal of molecular sciences·2024

Same author

Human milk immune factors, maternal nutritional status, and infant sex: The INSPIRE study.

American journal of human biology : the official journal of the Human Biology Council·2023

Same author

Contributions of Women to Cardiovascular Science Over Two Decades: Authorship, Leadership, and Mentorship.

Journal of the American Heart Association·2023

Same journal

Cross-Domain Transfer Learning from Peptides to Metabolites Using a Multi-Property Fine-Tuned LLM.

Bioinformatics (Oxford, England)·2026

Same journal

Biomedical Concept Recognition with Error-aware Negative-enhanced Ranking Framework.

Bioinformatics (Oxford, England)·2026

Same journal

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026

Same journal

PLNFGL: Joint Estimation of Multi-Condition Gene Networks from Single-cell RNA-seq Data.

Bioinformatics (Oxford, England)·2026

Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026

Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 18, 2026

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

Published on: August 29, 2014

MetAmp: combining amplicon data from multiple markers for OTU analysis.

Ilya Y Zhbannikov¹, James A Foster²

¹Graduate Program in Bioinformatics and Computational Biology, University of Idaho and Institute of Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA.

Bioinformatics (Oxford, England)

|January 30, 2015

Summary

This summary is machine-generated.

MetAmp is a new method that combines multiple genetic markers to improve the accuracy of microbial community analysis using Operational Taxonomic Units (OTUs). This tool enhances bacterial composition and community structure characterization, outperforming existing methods.

More Related Videos

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing

Published on: August 25, 2018

Related Experiment Videos

Last Updated: Apr 18, 2026

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

Published on: August 29, 2014

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

Published on: July 11, 2025

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing

Published on: August 25, 2018

Area of Science:

Microbiology
Bioinformatics
Genomics

Background:

Microbial community analysis relies on accurate identification of Operational Taxonomic Units (OTUs).
Existing OTU-based methods can be limited by the accuracy of single genetic markers.
Combining multiple markers offers potential for improved resolution and accuracy.

Purpose of the Study:

To introduce MetAmp, a novel method and application for microbial community analysis.
To enhance the accuracy of OTU-based microbial community characterization by integrating data from multiple genomic markers.
To provide a tool applicable to various marker genes and non-bacterial analyses.

Main Methods:

Developed MetAmp, a computational method to combine amplicon data from multiple genomic markers.
Calibrated genomic markers using data from known microbial genomes.
Applied MetAmp to analyze microbial communities, focusing on 16S rRNA gene data.

Main Results:

MetAmp demonstrated improved accuracy in characterizing bacterial composition and community structure when using multiple markers.
Performance was evaluated using standard test sequences from the Human Microbiome Mock Community.
MetAmp favorably compared to established tools like QIIME, UPARSE, and Mothur in recovering OTUs.

Conclusions:

MetAmp offers a robust approach to enhance OTU-based microbial community analysis.
The method shows particular benefit when utilizing at least three genetic markers.
MetAmp provides a valuable tool for microbial ecology research, with potential applications beyond 16S rRNA gene analysis.