ArticleChemical science2022
Polymer-based chemical-nose systems for optical-pattern recognition of gut microbiota.
Article in Chemical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 31 citations in OpenAlex.
- A fingerprint-based polymeric sensing platform for comprehensive quality assessment of complex culture media in cell manufacturing.Chemical science · 2026Article
- Fingerprint profiling human gut microbiota through boronic acid-based sensor array and its application on colorectal cancer classification.Nature communications · 2026Article
- Identification of Polymeric Nanoparticles Using Strategic Peptide Sensor Configurations and Machine Learning.ACS sensors · 2025Article
- Expanding the recognition of monosaccharides and glycans: A comprehensive analytical approach using chemical-nose/tongue technology and a comparison to lectin microarrays.BBA advances · 2025Article
- Chemical tongues as multipurpose bioanalytical tools for the characterization of complex biological samples.Biophysics and physicobiology · 2024Review
- Identification of Water-Soluble Polymers through Machine Learning of Fluorescence Signals from Multiple Peptide Sensors.ACS applied bio materials · 2023Article
- A review on machine learning-powered fluorescent and colorimetric sensor arrays for bacteria identification.Mikrochimica acta · 2023Review
- Recent Advances in Colorimetric Sensors Based on Gold Nanoparticles for Pathogen Detection.Biosensors · 2022Review
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.