Currently, there is a critical need to rapidly identify infectious organisms in clinical samples. Next-Generation Sequencing (NGS) could surmount the deficiencies of culture-based methods; however, there are no standardized, automated programs to process NGS data. To address this deficiency, we developed the Rapid Infectious Disease Identification (RIDI™) system. The system requires minimal guidance, which reduces operator errors. The system is compatible with the three major NGS platforms. It automatically interfaces with the sequencing system, detects their data format, configures the analysis type, applies appropriate quality control, and analyzes the results. Sequence information is characterized using both the NCBI database and RIDI™ specific databases. RIDI™ was designed to identify high probability sequence matches and more divergent matches that could represent different or novel species. We challenged the system using defined American Type Culture Collection (ATCC) reference standards of 27 species, both individually and in varying combinations. The system was able to rapidly detect known organisms in <12h with multi-sample throughput. the system accurately identifies 99.5% of dna sequence reads at genus-level and 75.3% species-level in reference standards. it has a limit detection 146cells/ml simulated clinical samples, is also able to identify components polymicrobial samples 16.9% discrepancy 31.2% species-level. thus, system's effectiveness may exceed current methods, especially situations where culture methods could produce false negatives or rapid results would influence patient outcomes. copyright © 2016 elsevier b.v. all rights reserved.
Journal: Journal of microbiological methods
DOI: 10.1016/j.mimet.2016.09.012
Year: 2017