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Related Experiment Video

Updated: Jun 10, 2026

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

Canine Fecal Microbiome Dataset: Ultra-deep Multi-platform Sequencing Across Extraction and Library Protocols.

Balázs Kakuk^1,2, Ákos Dörmő^1,2, Ahmed Taifi^1,2

¹MTA-SZTE Lendület GeMiNI Research Group, University of Szeged, Somogyi st. 4., 6720, Szeged, Hungary.

Scientific Data

|June 8, 2026

Summary

This summary is machine-generated.

This study presents a comprehensive canine gut microbiome dataset to standardize research methods. It evaluates DNA extraction, sequencing platforms, and primer sets for reliable cross-study comparisons in canine microbiome profiling.

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Last Updated: Jun 10, 2026

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Area of Science:

Microbiology
Genomics
Bioinformatics

Background:

The canine gut microbiome is a valuable model for human microbiome research.
Methodological inconsistencies in DNA isolation, library preparation, and sequencing hinder cross-study comparisons.

Purpose of the Study:

To create a multi-component dataset for evaluating methodological effects in canine fecal microbiome profiling.
To provide a resource for standardizing canine microbiome research.

Main Methods:

Generated an ultra-deep sequencing dataset from a single dog fecal sample using short-read (Illumina NovaSeq) and long-read (Oxford Nanopore MinION) platforms.
Collected longitudinal fecal samples from eight co-housed dogs over one year to compare two DNA extraction workflows.
Evaluated three full-length 16S rRNA primer sets using synthetic microbial communities and human/canine fecal samples on the MinION platform.

Main Results:

The dataset includes 75.2 GB of raw sequencing data, quality control, and taxonomic classification outputs.
Evaluated effects of different DNA extraction workflows and sequencing platforms.
Assessed the performance of various 16S rRNA primer sets for canine microbiome analysis.

Conclusions:

The presented dataset serves as a multi-platform resource for assessing methodological impacts on canine fecal microbiome profiling.
Standardizing methods is crucial for reliable and reproducible canine microbiome research.