Field deployable handheld sequencing technology and bioinformatics system for rapid detection of pathogens, AMR, and virulence for clinical decision-making in a battlefield environment

Diagnosis of bacterial resistance in military deployment settings is challenging, representing a current health gap. Culture-based resistance testing is laborious, time consuming, and difficult to provide in severely resource-limited settings. We propose development of a precision metagenomics-based diagnostic tool by taking advantage of the rapid sequencing speed and portability of the Oxford Nanopore MinION platform and the powerful genome database/algorithms constructed by CosmosID. These curated databases and best-in-class bioinformatics can detect, identify, and characterize presence (or absence) of all microorganisms (bacteria, viruses, fungi, and protists), as well as resistome and virulome gene sequences, in individual isolate or complex (metagenomic) biological sample, directly on clinical samples without culture. The remaining gap is computational methods to identify the pathogens etc. rapidly, accurately and actionably with a field device to allow improved and reliable patient decisions. The first objective is to optimize the interface between MinION sequence reads and CosmosID database/algorithms for quantitative and qualitative detection of specific pathogens as well as AMR and virulence markers, so that the device can be deployed in a field setting and not require internet connection. This will be accomplished by employing computer engineering and optimizing CosmosID bioinformatics algorithms. Second, the platform will be tested in-silico and in-vitro to prove feasibility of the offline assay to rapidly detect pathogens of interest as well as virulence and antibiotic susceptibility. This will involve the production of relevant samples/conditions both in-silico and in-vitro to replicate the various challenges that a wound infection from an injured warfighter would present. In doing so, the assay’s accuracy, sensitivity, level of detection, reproducibility, as well as other metrics of wound analysis will be assessed. The in-silico testing will be done in parallel with the first aim, with a feedback cycle for continued algorithm optimization. The in-vitro testing and offline sequencing will show proof of concept and feasibility of this diagnostic platform, by confirming its ability to detect pathogens of interest, specifically including but not necessarily limited to the ESKAPE group of pathogens: Enterococcus spp., Staphylococcus aureus, Klebsiella pneumonia, Acientobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp, and Escherichia coli), virulence, and AMR. The Milestone for this Phase 1 project will be the development of a prototype field-capable diagnostic assay that passes all above testing and validation, showing proof of concept for its use in rapidly identifying the most common bacterial pathogens causing wound infections, as well as the ability to determine respective antibiotic susceptibility of the detected pathogen(s) to guide treatment decisions for wound infections in injured war-fighters. Anticipated