Issue 20, 2022

Polymer-based chemical-nose systems for optical-pattern recognition of gut microbiota

Abstract

Gut-microbiota analysis has been recognized as crucial in health management and disease treatment. Metagenomics, a current standard examination method for the gut microbiome, is effective but requires both expertise and significant amounts of general resources. Here, we show highly accessible sensing systems based on the so-called chemical-nose strategy to transduce the characteristics of microbiota into fluorescence patterns. The fluorescence patterns, generated by twelve block copolymers with aggregation-induced emission (AIE) units, were analyzed using pattern-recognition algorithms, which identified 16 intestinal bacterial strains in a way that correlates with their genome-based taxonomic classification. Importantly, the chemical noses classified artificial models of obesity-associated gut microbiota, and further succeeded in detecting sleep disorder in mice through comparative analysis of normal and abnormal mouse gut microbiota. Our techniques thus allow analyzing complex bacterial samples far more quickly, simply, and inexpensively than common metagenome-based methods, which offers a powerful and complementary tool for the practical analysis of the gut microbiome.

Graphical abstract: Polymer-based chemical-nose systems for optical-pattern recognition of gut microbiota

Supplementary files

Article information

Article type
Edge Article
Submitted
26 Jan 2022
Accepted
06 Apr 2022
First published
26 Apr 2022
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY license

Chem. Sci., 2022,13, 5830-5837

Polymer-based chemical-nose systems for optical-pattern recognition of gut microbiota

S. Tomita, H. Kusada, N. Kojima, S. Ishihara, K. Miyazaki, H. Tamaki and R. Kurita, Chem. Sci., 2022, 13, 5830 DOI: 10.1039/D2SC00510G

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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