Abstract

Abstract Background Despite extensive laboratory testing, infectious agents were not detected in approximately 50% of patients hospitalized for acute undifferentiated febrile illnesses (AUFI) at Siriraj Hospital, Bangkok, Thailand. Unbiased Metagenomic Next Generation Sequencing (mNGS) enables detection of any microbe present in patient samples. Target enrichment for viruses represents a highly sensitive and cost-effective approach for overcoming host background in clinical specimens. Plasma collected from 800 patients with undiagnosed AUFI between 2013-2020 were analyzed by mNGS coupled to target enrichment to identify known and novel viruses. Methods Plasma was pre-treated with benzonase before extraction on an Abbott m2000 instrument. mNGS libraries were prepared from double-stranded cDNA with Illumina Nextera XT reagents on an epMotion then combined in pools of 24 and hybridized to Comprehensive Viral Research Panel (CVRP; Twist Biosciences) probes covering >15,000 strains of vertebrate viruses. Captured viral sequences were amplified, quantified, and sequenced together on a MiSeq. Reads were taxonomically classified by the SURPI pipeline and aligned in CLC Bio Genomics Workbench software. Results CVRP method optimization enabled sequencing of 24-48 libraries per MiSeq run, for which >50% genome coverage was obtained with model viruses spiked into clinical specimens at 1000 cp/ml. This approach revealed an array of >24 different viruses found in 26% of samples. Dengue was the most prevalent at 7.4%, with all four genotypes detected. Other common causes of AUFI such as Chikungunya, HIV-1, HAV, HBV, HCV, and CMV were present in 1.5-2.5% of cases. Less prevalent (< 1%) infections included HEV, HSV-2, EBV, HHV-6, Enterovirus B&D and Parvovirus B19. We also encountered sporadic cases of Measles, Cardiovirus, West Nile, Rotavirus, Picobirnavirus, Polyomavirus 4&5, Kubovirus, and Rabies lyssavirus. Conclusion Target capture successfully demonstrated that viruses were important etiologies for unresolved cases of AUFI in Thailand. This data has led to a better understanding of the epidemiology of this clinical syndrome and has implications for proper management of AUFI, including lower rates of unnecessary testing and antimicrobial use. Disclosures Julie Yamaguchi, BS, Abbott Labs: Employee Michael G. Berg, PhD, Abbott Labs: Employee Pakpoom Phoompoung, MD, Abbott Labs: Grant/Research Support|Abbott Labs: Employee Jenna Malinauskas, MS, Abbott Labs: Employee Gavin Cloherty, PhD, Abbott: Employee|Abbott: Stocks/Bonds|Abbott Labs: Employee Yupin Suputtamongkol, MD, Abbott Labs: Grant/Research Support.

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