Unbiased next-generation sequencing (NGS) approaches enable comprehensive pathogen detection in the clinical microbiology laboratory and have numerous applications for public health surveillance, outbreak investigation, and the diagnosis of infectious diseases. However, practical deployment of the technology is hindered by the bioinformatics challenge of analyzing results accurately and in a clinically relevant timeframe. Here we describe SURPI (''sequence-based ultrarapid pathogen identification''), a computational pipeline for pathogen identification from complex metagenomic NGS data generated from clinical samples, and demonstrate use of the pipeline in the analysis of 237 clinical samples comprising more than 1.1 billion sequences. Deployable on both cloud-based and standalone servers, SURPI leverages two state-of-the-art aligners for accelerated analyses, SNAP and RAPSearch, which are as accurate as existing bioinformatics tools but orders of magnitude faster in performance. In fast mode, SURPI detects viruses and bacteria by scanning data sets of 7-500 million reads in 11 min to 5 h, while in comprehensive mode, all known microorganisms are identified, followed by de novo assembly and protein homology searches for divergent viruses in 50 min to 16 h. SURPI has also directly contributed to real-time microbial diagnosis in acutely ill patients, underscoring its potential key role in the development of unbiased NGS-based clinical assays in infectious diseases that demand rapid turnaround times.

f Next-generation sequencing was used for discovery and de novo assembly of a novel, highly divergent DNA virus at the interface between the Parvoviridae and Circoviridae. The virus, provisionally named parvovirus-like hybrid virus (PHV), is nearly identical by sequence to another DNA virus, NIH-CQV, previously detected in Chinese patients with seronegative (non-A-E) hepatitis. Although we initially detected PHV in a wide range of clinical samples, with all strains sharing ϳ99% nucleotide and amino acid identity with each other and with NIH-CQV, the exact origin of the virus was eventually traced to contaminated silica-binding spin columns used for nucleic acid extraction. Definitive confirmation of the origin of PHV, and presumably NIH-CQV, was obtained by in-depth analyses of water eluted through contaminated spin columns. Analysis of environmental metagenome libraries detected PHV sequences in coastal marine waters of North America, suggesting that a potential association between PHV and diatoms (algae) that generate the silica matrix used in the spin columns may have resulted in inadvertent viral contamination during manufacture. The confirmation of PHV/NIH-CQV as laboratory reagent contaminants and not bona fide infectious agents of humans underscores the rigorous approach needed to establish the validity of new viral genomes discovered by nextgeneration sequencing.

Interpretation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurveillance studies is limited by poorly defined performance of antibody assays over time in individuals with different clinical presentations. We measured antibody responses in plasma samples from 128 individuals over 160 days using 14 assays. We found a consistent and strong effect of disease severity on antibody magnitude, driven by fever, cough, hospitalization, and oxygen requirement. Responses to spike protein versus nucleocapsid had consistently higher correlation with neutralization. Assays varied substantially in sensitivity during early convalescence and time to seroreversion. Variability was dramatic for individuals with mild infection, who had consistently lower antibody titers, with sensitivities at 6 months ranging from 33 to 98% for commercial assays. Thus, the ability to detect previous infection by SARS-CoV-2 is highly dependent on infection severity, timing, and the assay used. These findings have important implications for the design and interpretation of SARS-CoV-2 serosurveillance studies.

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