ArticleChemical science2020
An RGB-emitting molecular cocktail for the detection of bacterial fingerprints.
Article in Chemical science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Portable biosensor-based oral pathogenic bacteria detection for community and family applications.Analytical and bioanalytical chemistry · 2023Review
- Isolation and Cultivation of Human Gut Microorganisms: A Review.Microorganisms · 2023Review
- Fast label-free identification of bacteria by synchronous fluorescence of amino acids.Analytical and bioanalytical chemistry · 2021Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accumulating evidence indicates that colonized microbes play a crucial role in regulating health and disease in the human body. Detecting microbes should be essential for understanding the relationship between microbes and diseases, as well as increasing our ability to detect diseases. Here, a combined metabolic labeling strategy was developed to identify different bacterial species and microbiota by the use of three different fluorescent metabolite derivatives emitting red, green, and blue (RGB) fluorescence. Upon co-incubation with microbes, these fluorescent metabolite derivatives are incorporated into bacteria, generating unique true-color fingerprints for different bacterial species and different microbiota. A portable spectrometer was also fabricated to automate the colorimetric analysis in combination with a smartphone to conveniently identify different bacterial species and microbiota. Herein, the effectiveness of this system was demonstrated by the identification of certain bacterial species and microbiota in mice with different diseases, such as skin infections and bacteremia. By analyzing the microbiota fingerprints of saliva samples from clinical patients and healthy people, this system was proved to precisely distinguish oral squamous cell carcinoma (OSCC,
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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.