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Microbial Interactions: Competition

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Related Experiment Video

Updated: Apr 20, 2026

Deferred Growth Inhibition Assay to Quantify the Effect of Bacteria-derived Antimicrobials on Competition

Deferred Growth Inhibition Assay to Quantify the Effect of Bacteria-derived Antimicrobials on Competition

Published on: September 3, 2016

Predicting competition and substrate preferences for targeted microbiome alteration.

Oriane Moyne¹, Grant J Norton¹, Mahmoud Al-Bassam¹

¹Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA.

|April 18, 2026

Summary

This summary is machine-generated.

Microbiome science can now predict microbial competition and substrate use with MIND. This functional approach guides targeted prebiotic and probiotic interventions for precise microbiome modulation.

Keywords:

SynCom functional profiling metaRibo-seq microbial competition microbiome microbiome engineering niche differentiation prebiotic probiotic synthetic community translation efficiency

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Last Updated: Apr 20, 2026

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An In Vitro Batch-culture Model to Estimate the Effects of Interventional Regimens on Human Fecal Microbiota

Published on: July 31, 2019

Area of Science:

Microbiome science
Metabolic interactions
Computational biology

Background:

Microbiome research often uses descriptive methods, limiting causal insights and intervention strategies.
Functional characterization of microbial interactions and metabolic preferences is crucial for predictive understanding.
Current approaches lack the ability to guide targeted microbiome interventions.

Purpose of the Study:

To introduce Microbial Interaction and Niche Determination (MIND) for quantifying mRNA translation prioritization.
To infer substrate preferences and competitive interactions within complex microbial communities.
To enable predictive and mechanistic understanding of microbiome dynamics.

Main Methods:

MIND quantifies mRNA translation prioritization.
Analysis of complex communities including synthetic communities, soil, human fecal samples, and a mouse model.
Application of MIND to predict microbial competition and substrate preferences.

Main Results:

MIND successfully predicted microbial competition and substrate preferences across diverse sample types.
The method guided precision prebiotic and probiotic interventions.
Selective modulation of microbial community composition was achieved based on MIND predictions.

Conclusions:

MIND provides a framework for functional characterization of microbial communities.
It enables targeted microbiome manipulation and rational intervention design.
The approach links functional measurements to ecological outcomes for enhanced microbiome research.