@article {51, title = {Metagenomic Next-Generation Sequencing for Identification and Quantitation of Transplant-Related DNA Viruses.}, journal = {J Clin Microbiol}, volume = {57}, year = {2019}, month = {2019 12}, abstract = {

Infections with DNA viruses are frequent causes of morbidity and mortality in transplant recipients. This study describes the analytical and clinical performance characteristics of the Arc Bio Galileo Pathogen Solution, an all-inclusive metagenomic next-generation sequencing (mNGS) reagent and bioinformatics pipeline that allows the simultaneous quantitation of 10 transplant-related double-stranded DNA (dsDNA) viruses (adenovirus [ADV], BK virus [BKV], cytomegalovirus [CMV], Epstein-Barr virus [EBV], human herpesvirus 6A [HHV-6A], HHV-6B, herpes simplex virus 1 [HSV-1], HSV-2, JC virus [JCV], and varicella-zoster virus [VZV]). The mNGS 95\% limit of detection ranged from 14 copies/ml (HHV-6) to 191 copies/ml (BKV), and the lower limit of quantitation ranged from 442 international units (IU)/ml (EBV) to 661 copies/ml (VZV). An evaluation of 50 residual plasma samples with at least one DNA virus detected in prior clinical testing showed a total percent agreement of mNGS and quantitative PCR (qPCR) of 89.2\% (306/343), with a κ statistic of 0.725. The positive percent agreement was 84.9\% (73/86), and the negative percent agreement was 90.7\% (233/257). Furthermore, mNGS detected seven subsequently confirmed coinfections that were not initially requested by qPCR. Passing-Bablok regression revealed a regression line of = 0.953 + 0.075 (95\% confidence interval [CI] of the slope, 0.883 to 1.011; intercept, -0.100 to 0.299), and Bland-Altman analysis (mNGS - qPCR) showed a slight positive bias (0.28 log concentration; 95\% limits of agreement, -0.62 to 1.18). In conclusion, the mNGS-based Galileo pipeline demonstrates analytical and clinical performance comparable to that of qPCR for transplant-related DNA viruses.

}, keywords = {Computational Biology, DNA Virus Infections, DNA Viruses, High-Throughput Nucleotide Sequencing, Humans, Metagenomics, Molecular Diagnostic Techniques, Sensitivity and Specificity, Transplantation}, issn = {1098-660X}, doi = {10.1128/JCM.01113-19}, author = {Carpenter, Meredith L and Tan, Susanna K and Watson, Thomas and Bacher, Rowena and Nagesh, Vaishnavi and Watts, Alain and Bentley, Gordon and Weber, Jenna and Huang, ChunHong and Sahoo, Malaya K and Hinterwirth, Armin and Doan, Thuy and Carter, Theodore and Dong, Queeny and Gourguechon, St{\'e}phane and Harness, Eric and Kermes, Sean and Radhakrishnan, Srihari and Wang, Gongbo and Quiroz-Z{\'a}rate, Alejandro and Ching, Jesus and Pinsky, Benjamin A} } @article {126, title = {Unbiased Pathogen Detection and Host Gene Profiling for Conjunctivitis.}, journal = {Ophthalmology}, volume = {126}, year = {2019}, month = {2019 08}, pages = {1090-1094}, abstract = {

PURPOSE: The etiology of conjunctivitis is often misdiagnosed. An ideal diagnostic test would identify all possible infectious causes. In this study, we apply unbiased metagenomic RNA deep sequencing (MDS) to identify pathogens causing conjunctivitis.

DESIGN: Molecular study of prospectively collected conjunctival swabs from patients with presumed infectious conjunctivitis.

PARTICIPANTS: Patients with presumed acute infectious conjunctivitis.

METHODS: Conjunctival swabs were collected from patients presenting with acute conjunctivitis. Swabs were processed for MDS. Pathogens were identified using a rapid computational pipeline to analyze the nonhost sequences obtained from MDS. Differential gene expression analysis was performed to evaluate for host transcriptome signatures for infectious types. Clinical samples were deidentified, and laboratory personnel handling the samples and interpreting the data were masked.

MAIN OUTCOME MEASURES: Pathogens and differential transcripts identified by MDS.

RESULTS: Metagenomic RNA deep sequencing detected pathogens in 86\% (12/14) of the patients tested. Swabs from 10 of 14 patients were positive for human adenovirus (HAdV) while swabs from 2 of 14 patients were positive for Vittaforma corneae (a parasitic fungal species of the microsporidia group). Samples positive for HAdV by RNA-seq were independently verified in a CLIA-certified laboratory. Pathogen-directed polymerase chain reaction confirmed the presence of V.\ corneae genome in the samples positive by RNA-seq. Local host transcriptome analysis identified 12 differentially expressed genes that provided distinct expression signatures for patients infected with HAdV compared with V.\ corneae.

CONCLUSIONS: Metagenomic RNA deep sequencing can reliably detect and quantify common and rare pathogens causing conjunctivitis, and identify strains. The unbiased nature of metagenomic RNA deep sequencing allowed an expanded scope of pathogen detection, including fungal species not commonly associated with acute conjunctivitis. In addition, the identification of infection type-specific local host transcriptome signatures may allow for pathogen detection even when the pathogen load is too low for direct identification.

}, keywords = {Adult, Aged, Conjunctivitis, DNA, Bacterial, DNA, Fungal, DNA, Viral, Female, High-Throughput Nucleotide Sequencing, Humans, Male, Metagenomics, Middle Aged, Young Adult}, issn = {1549-4713}, doi = {10.1016/j.ophtha.2019.03.039}, author = {Lalitha, Prajna and Seitzman, Gerami D and Kotecha, Ritesh and Hinterwirth, Armin and Chen, Cindi and Zhong, Lina and Cummings, Susie and Lebas, Elodie and Sahoo, Malaya K and Pinsky, Benjamin A and Lietman, Thomas M and Doan, Thuy} }