Longitudinal monitoring of DNA viral loads in transplant patients using quantitative metagenomic next-generation sequencing

Carbo, E.C.; Russcher, A.; Kraakman, M.E.M.; Brouwer, C.S. de; Sidorov, I.A.; Feltkamp, M.C.W.; ... ; Vries, J.J.C. de (2022)

Article / Letter to editor

Introduction: Immunocompromised patients are prone to reactivations and (re-)infections of multiple DNA viruses. Viral load monitoring by single-target quantitative PCRs (qPCR) is the current cornerstone for virus quantification. In this study, a metagenomic next-generation sequencing (mNGS) approach was used for the identification and load monitoring of transplantation-related DNA viruses. Methods: Longitudinal plasma samples from six patients that were qPCR-positive for cytomegalovirus (CMV), Epstein-Barr virus (EBV), BK polyomavirus (BKV), adenovirus (ADV), parvovirus B19 (B19V), and torque teno-virus (TTV) were sequenced using the quantitative metagenomic Galileo Viral Panel Solution (Arc Bio, LLC, Cambridge, MA, USA) reagents and bioinformatics pipeline combination. Qualitative and quantitative performance was analysed with a focus on viral load ranges relevant for clinical decision making. Results: All pathogens identified by qPCR were also identified by mNGS. BKV, CMV, and HHV6B were additionally detected by mNGS, and could be confirmed by qPCR or auxiliary bioinformatic analysis. Viral loads determined by mNGS correlated with the qPCR results, with inter-method differences in viral load per virus ranging from 0.19 log(10) IU/mL for EBV to 0.90 log(10) copies/mL for ADV. TTV, analysed by mNGS in a semiquantitative way, demonstrated a mean difference of 3.0 log(10) copies/mL. Trends over time in viral load determined by mNGS and qPCR were comparable, and clinical thresholds for initiation of treatment were equally identified by mNGS. Conclusions: The Galileo Viral Panel for quantitative mNGS performed comparably to qPCR concerning detection and viral load determination, within clinically relevant ranges of patient management algorithms.

• viral metagenomics
• pathogen detection
• quantification
• next-generation sequencing
• load monitoring

• All authors: Carbo, E.C.; Russcher, A.; Kraakman, M.E.M.; Brouwer, C.S. de; Sidorov, I.A.; Feltkamp, M.C.W.; Kroes, A.C.M.; Claas, E.C.J.; Vries, J.J.C. de
• Date: 2022-02-01
• Journal: Pathogens
• Volume: 11
• Issue: 2
• DOI: doi:10.3390/pathogens11020236