Analytical Validation of a Highly Accurate and Reliable Next-Generation Sequencing-Based Urine Assay

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Abstract

ABSTRACT Culture is currently the gold standard for diagnosis of urinary tract infections (UTIs); however, it has poor sensitivity detecting urogenital pathogens, especially if patients have already initiated antimicrobial therapy, or have an infection from an organism that is not commonly cultured. False negative urine culture results can lead to the inappropriate use of antimicrobial therapies or to the progression to urosepsis in high-risk patients. Though not commonly applied to urine in a clinical setting, Next-generation sequencing (NGS)-based metagenomics offer a solution as a precision diagnostic. We developed and validated BIOTIA-ID, a clinical-grade NGS-based diagnostic pipeline for the detection and identification of pathogens in urine specimens. Remnant clinical urine specimens, and contrived sterile urine spiked with common UTI pathogens, were processed with our end-to-end assay including extraction, metagenomic library preparation and Illumina NextSeq 550 sequencing. We trained and applied a bioinformatic pipeline that uses machine learning (ML) to identify pathogens. Internal controls and other quality control measures were incorporated into the process to provide rigorous and standardized results. The assay was tested on 1,470 urine specimens and achieved 99.92% sensitivity, 99.95% specificity and a limit of detection (LoD) of <25,000 CFU/mL and <5,000 CFU/mL in bacteria and fungi, respectively. Discordant results were reconciled with additional testing by target-specific qPCR or 16S Sanger sequencing; 87% of the NGS results were ultimately determined to be the correct result. Overall, these data demonstrate that BIOTIA-ID is a highly accurate clinical-grade diagnostic tool with notable advantages over current culture- based diagnostics. Conflict of Interest Statement MCR, DCD, HLW, SR, XJS, JP, PFC, GF, CEM, CO, NBO and DNS are employees at Biotia, Inc.
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ABSTRACT Culture is currently the gold standard for diagnosis of urinary tract infections (UTIs); however, it has poor sensitivity detecting urogenital pathogens, especially if patients have already initiated antimicrobial therapy, or have an infection from an organism that is not commonly cultured. False negative urine culture results can lead to the inappropriate use of antimicrobial therapies or to the progression to urosepsis in high-risk patients. Though not commonly applied to urine in a clinical setting, Next-generation sequencing (NGS)-based metagenomics offer a solution as a precision diagnostic. We developed and validated BIOTIA-ID, a clinical-grade NGS-based diagnostic pipeline for the detection and identification of pathogens in urine specimens. Remnant clinical urine specimens, and contrived sterile urine spiked with common UTI pathogens, were processed with our end-to-end assay including extraction, metagenomic library preparation and Illumina NextSeq 550 sequencing. We trained and applied a bioinformatic pipeline that uses machine learning (ML) to identify pathogens. Internal controls and other quality control measures were incorporated into the process to provide rigorous and standardized results. The assay was tested on 1,470 urine specimens and achieved 99.92% sensitivity, 99.95% specificity and a limit of detection (LoD) of <25,000 CFU/mL and <5,000 CFU/mL in bacteria and fungi, respectively. Discordant results were reconciled with additional testing by target-specific qPCR or 16S Sanger sequencing; 87% of the NGS results were ultimately determined to be the correct result. Overall, these data demonstrate that BIOTIA-ID is a highly accurate clinical-grade diagnostic tool with notable advantages over current culture- based diagnostics. Conflict of Interest Statement MCR, DCD, HLW, SR, XJS, JP, PFC, GF, CEM, CO, NBO and DNS are employees at Biotia, Inc. Competing Interest Statement MCR, DCD, HLW, SR, XJS, JP, PFC, GF, CEM, CO, NBO and DNS are employees at Biotia, Inc. Funding Statement The BIOTIA-DX software pipeline work used Cromwell On Azure; the Microsoft Genomics supported implementation of the Broad Institute's Cromwell workflow engine on Azure. The development and validation work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant (ACI-1548562). Specifically, it used the Bridges system, which is supported by NSF award (ACI-1445606), at the Pittsburgh Supercomputing Center (PSC). Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Samples were collected and processed under an institutional review board (Advarra Pro00038083) without demographic information (consent was not required due to the nature of study - de-identified leftover urine specimens with no metadata). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability All data produced in the present study are available upon reasonable request to the authors.

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