A low-cost paper-based synthetic biology platform for analyzing gut microbiota and host biomarkers
| Autor: | Ashwin N. Ananthakrishnan, Nina M. Donghia, James J. Collins, Xiao Tan, Dana Braff, Reid T. K. Akana, Melissa K. Takahashi, Aaron J. Dy, Yoshikazu Furuta |
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| Přispěvatelé: | Institute for Medical Engineering and Science, Massachusetts Institute of Technology. Department of Biological Engineering, Takahashi, Melissa Kimie, Tan, Xiao, Dy, Aaron James, Braff, Dana, Akana, Reid T., Furuta, Yoshikazu, Collins, James J. |
| Rok vydání: | 2018 |
| Předmět: |
Paper
0301 basic medicine Science General Physics and Astronomy 02 engineering and technology Computational biology Biology Gut flora Article General Biochemistry Genetics and Molecular Biology Feces 03 medical and health sciences Synthetic biology Human health Species Specificity RNA Ribosomal 16S Humans RNA Messenger Microbiome lcsh:Science Inflammation Multidisciplinary Clostridioides difficile Gastrointestinal Microbiome Computational Biology General Chemistry Paper based 021001 nanoscience & nanotechnology biology.organism_classification Clostridium difficile infections Gut microbiome 3. Good health 030104 developmental biology lcsh:Q Synthetic Biology 0210 nano-technology Biomarkers |
| Zdroj: | Nature Communications Nature Nature Communications, Vol 9, Iss 1, Pp 1-12 (2018) |
| ISSN: | 2041-1723 |
| DOI: | 10.1038/s41467-018-05864-4 |
| Popis: | There is a need for large-scale, longitudinal studies to determine the mechanisms by which the gut microbiome and its interactions with the host affect human health and disease. Current methods for profiling the microbiome typically utilize next-generation sequencing applications that are expensive, slow, and complex. Here, we present a synthetic biology platform for affordable, on-demand, and simple analysis of microbiome samples using RNA toehold switch sensors in paper-based, cell-free reactions. We demonstrate species-specific detection of mRNAs from 10 different bacteria that affect human health and four clinically relevant host biomarkers. We develop a method to quantify mRNA using our toehold sensors and validate our platform on clinical stool samples by comparison to RT-qPCR. We further highlight the potential clinical utility of the platform by showing that it can be used to rapidly and inexpensively detect toxin mRNA in the diagnosis of Clostridium difficile infections. National Institutes of Health (U.S.) (Grant T32-DK007191) |
| Databáze: | OpenAIRE |
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