UltraSEQ: a universal bioinformatic platform for information-based clinical metagenomics and beyond

Abstract

Applied metagenomics is a powerful emerging capability enabling untargeted detection of pathogens, and its application in clinical diagnostics promises to alleviate the limitations of current targeted assays. While metagenomics offers a hypothesis-free approach to identify any pathogen, including unculturable and potentially novel pathogens, its application in clinical diagnostics has so far been limited by workflow-specific requirements, computational constraints, and lengthy expert review requirements. To address these challenges, we developed UltraSEQ, a first-of its kind metagenomics-based clinical diagnostics and biosurveillance tool that is accurate and scalable. Here we present results for evaluation of our novel UltraSEQ pipeline using an in silico synthesized metagenome, mock microbial community datasets, and publicly available clinical datasets from samples of different infection types, and both short-read and long-read sequencing data. Our results show that UltraSEQ successfully detected all expected species across the tree of life in the in silico sample and detected all 10 bacterial and fungal species in the mock microbial community dataset. For clinical datasets, even without requiring dataset-specific configuration settings changes, background sample subtraction, or prior sample information, UltraSEQ achieved an overall accuracy of 91%. Further, we demonstrated UltraSEQs ability to provide accurate antibiotic resistance and virulence factor genotypes that are consistent with phenotypic results. Taken together, the above results demonstrates that the UltraSEQ platform offers a transformative approach to microbial and metagenomic sample characterization, employing a biologically informed detection logic, deep metadata, and a flexible system architecture for classification and characterization of taxonomic origin, gene function, and user-defined functions, including disease-causing infection.