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.
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
