AI Article Synopsis
- Early identification of pathogens is crucial for preventing therapy-resistant strains and managing disease outbreaks.
- A new universal microbial diagnostics (UMD) platform uses random DNA probes, which are not specific to any one organism, to efficiently detect a wide range of pathogens.
- Validation showed that UMD can successfully identify various pathogenic bacteria both in lab tests and theoretically for common human pathogens, improving the efficiency of molecular diagnostics.
Article Abstract
Early identification of pathogens is essential for limiting development of therapy-resistant pathogens and mitigating infectious disease outbreaks. Most bacterial detection schemes use target-specific probes to differentiate pathogen species, creating time and cost inefficiencies in identifying newly discovered organisms. We present a novel universal microbial diagnostics (UMD) platform to screen for microbial organisms in an infectious sample, using a small number of random DNA probes that are agnostic to the target DNA sequences. Our platform leverages the theory of sparse signal recovery (compressive sensing) to identify the composition of a microbial sample that potentially contains novel or mutant species. We validated the UMD platform in vitro using five random probes to recover 11 pathogenic bacteria. We further demonstrated in silico that UMD can be generalized to screen for common human pathogens in different taxonomy levels. UMD's unorthodox sensing approach opens the door to more efficient and universal molecular diagnostics.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5040476 | PMC |
| http://dx.doi.org/10.1126/sciadv.1600025 | DOI Listing |
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