Development of an automated amplicon-based next-generation sequencing pipeline for rapid detection of bacteria and fungi directly from clinical specimens.

The timely identification of microbial pathogens is essential to guide targeted antimicrobial therapy and ultimately, successful treatment of an infection. However, the yield of standard microbiology testing (SMT) is directly related to the duration of antecedent antimicrobial therapy as SMT culture methods are dependent on the recovery of viable organisms, the fastidious nature of certain pathogens, and other pre-analytic factors. In the last decade, metagenomic next-generation sequencing (mNGS) has been successfully utilized as a diagnostic tool for various applications within the clinical laboratory. However, mNGS is resource, time, and labor-intensive-requiring extensive laborious preliminary benchwork, followed by complex bioinformatic analysis. We aimed to address these shortcomings by developing a largely Automated targeted Metagenomic next-generation sequencing (tmNGS) PipeLine for rapId inFectIous disEase Diagnosis (AMPLIFIED) to detect bacteria and fungi directly from clinical specimens. Therefore, AMPLIFIED may serve as an adjunctive approach to complement SMT. This tmNGS pipeline requires less than 1 hour of hands-on time before sequencing and less than 2 hours of total processing time, including bioinformatic analysis. We performed tmNGS on 50 clinical specimens with concomitant cultures to assess feasibility and performance in the hospital laboratory. Of the 50 specimens, 34 (68%) were from true clinical infections. Specimens from cases of true infection were more often tmNGS positive compared to those from the non-infected group (82.4% vs 43.8%, respectively, IMPORTANCE: To our knowledge, this represents the first application of an automated sequencing and bioinformatics pipeline in an exclusively pediatric population. Next-generation sequencing is time-consuming, labor-intensive, and requires experienced personnel; perhaps contributing to hesitancy among clinical laboratories to adopt such a test. Here, we report a strong case for use by removing these barriers through near-total automation of our sequencing pipeline.