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Related Experiment Video

Updated: Dec 29, 2025

DNA Stable-Isotope Probing DNA-SIP

DNA Stable-Isotope Probing DNA-SIP

Published on: August 2, 2010

Simulating metagenomic stable isotope probing datasets with MetaSIPSim.

Samuel E Barnett¹, Daniel H Buckley²

¹School of Integrative Plant Science, Cornell University, Bradfield Hall, room 705, 306 Tower Rd, Ithaca, NY, 14853, USA.

BMC Bioinformatics

|February 1, 2020

Summary

Metagenomic stable isotope probing (metagenomic-SIP) improves genome assembly and binning from complex microbial communities. A new simulation toolkit, MetaSIPSim, aids in optimizing this powerful technique for environmental research.

Keywords:

Metagenomics SIP Simulation Stable isotope probing

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Last Updated: Dec 29, 2025

DNA Stable-Isotope Probing DNA-SIP

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Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

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Published on: June 11, 2016

Area of Science:

Microbial Ecology
Genomics
Bioinformatics

Background:

DNA-stable isotope probing (DNA-SIP) links microbes to functions in environmental samples.
Metagenomic-SIP combines DNA-SIP with metagenomics for improved genome assembly and functional linkage.
Current metagenomic-SIP method development is costly and complex.

Purpose of the Study:

To develop a simulation toolkit, MetaSIPSim, for generating datasets for metagenomic-SIP experiments.
To demonstrate the advantages of metagenomic-SIP over conventional shotgun metagenomics using simulated data.

Main Methods:

Development of the MetaSIPSim toolkit for simulating metagenomic-SIP sequencing libraries.
Utilizing simulated data to compare metagenomic-SIP with conventional shotgun metagenomics.
Analyzing the impact of experimental parameters on metagenomic-SIP performance.

Main Results:

Metagenomic-SIP significantly improves the assembly and binning of isotopically labeled genomes compared to standard metagenomics.
Assembly and binning improvements are influenced by sequencing depth and community Guanine-Cytosine (G+C) content.
High community G+C content and a large proportion of labeled community members can reduce the benefits of metagenomic-SIP.

Conclusions:

Metagenomic-SIP is an effective method for recovering labeled genomes from complex microbial communities.
Optimization of experimental parameters is crucial for maximizing metagenomic-SIP performance.
MetaSIPSim facilitates the development and optimization of metagenomic-SIP experiments and associated analytical methods.