# Autoinducer 2 as a universal language in microbial consortia: decoding molecular mechanisms, ecological impacts, and application

## TL;DR

This review explores AI-2, a microbial signaling molecule, and its role in communication, community dynamics, and applications in health, agriculture, and environmental sustainability.

## Contribution

The paper systematically synthesizes AI-2's structural dynamics, receptor diversity, and ecological impacts, charting a roadmap for its application in microbial communication.

## Key findings

- AI-2 exhibits dual structural dynamics and mediates bacterial crosstalk through diverse receptors like LuxP and LsrB.
- AI-2 regulates metabolic flux and enables coordinated bacterial responses to environmental changes.
- Factors like strain specificity, nutrition, and environmental stress influence AI-2 production and signaling.

## Abstract

In natural and engineered ecosystems, diverse species interact in complex ways to form highly efficient microecologies. One key orchestrator of these interactions is autoinducer-2 (AI-2), a signaling molecule that plays a crucial role in microbial community assembly, metabolic flux, and resilience to environmental disturbances. This review provides the systematic synthesis of AI-2’s dual structural dynamics (S-THMF-borate/R-THMF interconversion) and its context-dependent roles in mediating bacterial crosstalk. It also reveals the receptor diversity (such as LuxP and LsrB) of AI-2 in bacterial kingdom and the signal transduction mechanism. Systematically elaborated on AI-2’s regulation of cellular metabolic flux and its ability to autonomously exhibit a series of coordinated behaviors in response to environmental changes. The review explores the ramifications of AI-2 on bacterial community interactions in synthetic biology and natural ecosystems. The wide application of AI-2-mediated interspecific communication in various fields including host health, agriculture, industry and environmental ecology has also been widely discussed. Factors influencing AI-2 production are thoroughly examined, including internal factors such as strain specificity, cell density, growth form and the phenotypic heterogeneity. Additionally, external biological factors (such as nutritional status and environmental stress) and abiotic factors (aggregation, diffusion, and flow) are discussed in detail. By examining knowledge gaps in AI-2-mediated spatial heterogeneity and multi-QS system coordination, this work charts a roadmap for harnessing microbial communication in chemical engineering and environmental sustainability.