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Related Experiment Video

Updated: Oct 6, 2025

Assembly and Tracking of Microbial Community Development within a Microwell Array Platform

Assembly and Tracking of Microbial Community Development within a Microwell Array Platform

Published on: June 6, 2017

M&Ms: a versatile software for building microbial mock communities.

Natalia García-García¹, Javier Tamames¹, Fernando Puente-Sánchez¹

¹Department of Systems Biology, Address Centro Nacional de Biotecnología (CNB-CSIC), 28049 Madrid, Spain.

Bioinformatics (Oxford, England)

|January 13, 2022

Summary

This summary is machine-generated.

M&Ms is a new bioinformatic tool that generates simulated 16S rDNA sequencing datasets. This open-source software aids in developing and testing bioinformatic tools for microbial community analysis.

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Area of Science:

Bioinformatics
Microbial Ecology
Computational Biology

Background:

Next-generation sequencing technologies have advanced rapidly, necessitating robust bioinformatic tools for analyzing 16S ribosomal DNA (rDNA) sequence data.
Accurate testing and benchmarking of these bioinformatic tools require simulated datasets that realistically represent microbial communities from diverse environments.

Purpose of the Study:

To introduce M&Ms, a user-friendly, open-source bioinformatic tool designed for generating simulated 16S rDNA sequence datasets.
To enable the creation of 'in silico' microbial communities with user-defined ecological parameters such as richness, evenness, and microdiversity.

Main Methods:

M&Ms utilizes reference sequences to construct sequence libraries for simulated microbial communities.
The tool allows for user control over key ecological parameters, including richness, evenness, microdiversity, and the source environment.
It generates datasets ranging from simple to complex, based on realistic parameters.

Main Results:

M&Ms provides a flexible platform for generating diverse 16S rDNA datasets.
The generated datasets can be tailored to specific research needs, facilitating the development and validation of bioinformatic software.
The tool supports the creation of 'in silico' experiments for benchmarking existing bioinformatic pipelines.

Conclusions:

M&Ms offers a valuable resource for the bioinformatic and microbial ecology communities.
Its user-friendly interface and customizable parameter settings streamline the generation of realistic simulated 16S rDNA data.
This tool will aid in the advancement of bioinformatic software development and the reliable analysis of microbial community structures.