LuNER: Multiplexed SARS-CoV-2 detection in clinical swab and wastewater samples.

Clinical and surveillance testing for the SARS-CoV-2 virus relies overwhelmingly on RT-qPCR-based diagnostics, yet several popular assays require 2-3 separate reactions or rely on detection of a single viral target, which adds significant time, cost, and risk of false-negative results. Furthermore, multiplexed RT-qPCR tests that detect at least two SARS-CoV-2 genes in a single reaction are typically not affordable for large scale clinical surveillance or adaptable to multiple PCR machines and plate layouts. We developed a RT-qPCR assay using the Luna Probe Universal One-Step RT-qPCR master mix with publicly available primers and probes to detect SARS-CoV-2 N gene, E gene, and human RNase P (LuNER) to address these shortcomings and meet the testing demands of a university campus and the local community. This cost-effective test is compatible with BioRad or Applied Biosystems qPCR machines, in 96 and 384-well formats, with or without sample pooling, and has a detection sensitivity suitable for both clinical reporting and wastewater surveillance efforts.

Detection of Neoplasms by Metagenomic Next-Generation Sequencing of Cerebrospinal Fluid.

Importance: Cerebrospinal fluid (CSF) cytologic testing and flow cytometry are insensitive for diagnosing neoplasms of the central nervous system (CNS). Such clinical phenotypes can mimic infectious and autoimmune causes of meningoencephalitis. Objective: To ascertain whether CSF metagenomic next-generation sequencing (mNGS) can identify aneuploidy, a hallmark of malignant neoplasms, in difficult-to-diagnose cases of CNS malignant neoplasm. Design, Setting, and Participants: Two case-control studies were performed at the University of California, San Francisco (UCSF). The first study used CSF specimens collected at the UCSF Clinical Laboratories between July 1, 2017, and December 31, 2019, and evaluated test performance in specimens from patients with a CNS malignant neoplasm (positive controls) or without (negative controls). The results were compared with those from CSF cytologic testing and/or flow cytometry. The second study evaluated patients who were enrolled in an ongoing prospective study between April 1, 2014, and July 31, 2019, with presentations that were suggestive of neuroinflammatory disease but who were ultimately diagnosed with a CNS malignant neoplasm. Cases of individuals whose tumors could have been detected earlier without additional invasive testing are discussed. Main Outcomes and Measures: The primary outcome measures were the sensitivity and specificity of aneuploidy detection by CSF mNGS. Secondary subset analyses included a comparison of CSF and tumor tissue chromosomal abnormalities and the identification of neuroimaging characteristics that were associated with test performance. Results: Across both studies, 130 participants were included (median [interquartile range] age, 57.5 [43.3-68.0] years; 72 men [55.4%]). The test performance study used 125 residual laboratory CSF specimens from 47 patients with a CNS malignant neoplasm and 56 patients with other neurological diseases. The neuroinflammatory disease study enrolled 12 patients and 17 matched control participants. The sensitivity of the CSF mNGS assay was 75% (95% CI, 63%-85%), and the specificity was 100% (95% CI, 96%-100%). Aneuploidy was detected in 64% (95% CI, 41%-83%) of the patients in the test performance study with nondiagnostic cytologic testing and/or flow cytometry, and in 55% (95% CI, 23%-83%) of patients in the neuroinflammatory disease study who were ultimately diagnosed with a CNS malignant neoplasm. Of the patients in whom aneuploidy was detected, 38 (90.5%) had multiple copy number variations with tumor fractions ranging from 31% to 49%. Conclusions and Relevance: This case-control study showed that CSF mNGS, which has low specimen volume requirements, does not require the preservation of cell integrity, and was orginally developed to diagnose neurologic infections, can also detect genetic evidence of a CNS malignant neoplasm in patients in whom CSF cytologic testing and/or flow cytometry yielded negative results with a low risk of false-positive results.

Detection of cryptogenic malignancies from metagenomic whole genome sequencing of body fluids.

BACKGROUND: Metagenomic next-generation sequencing (mNGS) of body fluids is an emerging approach to identify occult pathogens in undiagnosed patients. We hypothesized that metagenomic testing can be simultaneously used to detect malignant neoplasms in addition to infectious pathogens. METHODS: From two independent studies (n = 205), we used human data generated from a metagenomic sequencing pipeline to simultaneously screen for malignancies by copy number variation (CNV) detection. In the first case-control study, we analyzed body fluid samples (n = 124) from patients with a clinical diagnosis of either malignancy (positive cases, n = 65) or infection (negative controls, n = 59). In a second verification cohort, we analyzed a series of consecutive cases (n = 81) sent to cytology for malignancy workup that included malignant positives (n = 32), negatives (n = 18), or cases with an unclear gold standard (n = 31). RESULTS: The overall CNV test sensitivity across all studies was 87% (55 of 63) in patients with malignancies confirmed by conventional cytology and/or flow cytometry testing and 68% (23 of 34) in patients who were ultimately diagnosed with cancer but negative by conventional testing. Specificity was 100% (95% CI 95-100%) with no false positives detected in 77 negative controls. In one example, a patient hospitalized with an unknown pulmonary illness had non-diagnostic lung biopsies, while CNVs implicating a malignancy were detectable from bronchoalveolar fluid. CONCLUSIONS: Metagenomic sequencing of body fluids can be used to identify undetected malignant neoplasms through copy number variation detection. This study illustrates the potential clinical utility of a single metagenomic test to uncover the cause of undiagnosed acute illnesses due to cancer or infection using the same specimen.

A diagnostic host response biosignature for COVID-19 from RNA profiling of nasal swabs and blood.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease-19 (COVID-19), has emerged as the cause of a global pandemic. We used RNA sequencing to analyze 286 nasopharyngeal (NP) swab and 53 whole-blood (WB) samples from 333 patients with COVID-19 and controls. Overall, a muted immune response was observed in COVID-19 relative to other infections (influenza, other seasonal coronaviruses, and bacterial sepsis), with paradoxical down-regulation of several key differentially expressed genes. Hospitalized patients and outpatients exhibited up-regulation of interferon-associated pathways, although heightened and more robust inflammatory responses were observed in hospitalized patients with more clinically severe illness. Two-layer machine learning-based host classifiers consisting of complete (>1000 genes), medium (<100), and small (<20) gene biomarker panels identified COVID-19 disease with 85.1-86.5% accuracy when benchmarked using an independent test set. SARS-CoV-2 infection has a distinct biosignature that differs between NP swabs and WB and can be leveraged for COVID-19 diagnosis.

Digital droplet PCR accurately quantifies SARS-CoV-2 viral load from crude lysate without nucleic acid purification.

The COVID-19 pandemic caused by the SARS-CoV-2 virus motivates diverse diagnostic approaches due to the novel causative pathogen, incompletely understood clinical sequelae, and limited availability of testing resources. Given the variability in viral load across and within patients, absolute viral load quantification directly from crude lysate is important for diagnosis and surveillance. Here, we investigate the use of digital droplet PCR (ddPCR) for SARS-CoV-2 viral load measurement directly from crude lysate without nucleic acid purification. We demonstrate ddPCR accurately quantifies SARS-CoV-2 standards from purified RNA and multiple sample matrices, including commonly utilized universal transport medium (UTM). In addition, we find ddPCR functions robustly at low input viral copy numbers on nasopharyngeal swab specimens stored in UTM without upfront RNA extraction. We also show ddPCR, but not qPCR, from crude lysate shows high concordance with viral load measurements from purified RNA. Our data suggest ddPCR offers advantages to qPCR for SARS-CoV-2 detection with higher sensitivity and robustness when using crude lysate rather than purified RNA as input. More broadly, digital droplet assays provide a potential method for nucleic acid measurement and infectious disease diagnosis with limited sample processing, underscoring the utility of such techniques in laboratory medicine.

Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids.

We developed a metagenomic next-generation sequencing (mNGS) test using cell-free DNA from body fluids to identify pathogens. The performance of mNGS testing of 182 body fluids from 160 patients with acute illness was evaluated using two sequencing platforms in comparison to microbiological testing using culture, 16S bacterial PCR and/or 28S-internal transcribed ribosomal gene spacer (28S-ITS) fungal PCR. Test sensitivity and specificity of detection were 79 and 91% for bacteria and 91 and 89% for fungi, respectively, by Illumina sequencing; and 75 and 81% for bacteria and 91 and 100% for fungi, respectively, by nanopore sequencing. In a case series of 12 patients with culture/PCR-negative body fluids but for whom an infectious diagnosis was ultimately established, seven (58%) were mNGS positive. Real-time computational analysis enabled pathogen identification by nanopore sequencing in a median 50-min sequencing and 6-h sample-to-answer time. Rapid mNGS testing is a promising tool for diagnosis of unknown infections from body fluids.

Digital droplet PCR accurately quantifies SARS-CoV-2 viral load from crude lysate without nucleic acid purification.

The COVID-19 pandemic caused by the SARS-CoV-2 virus motivates diverse diagnostic approaches due to the novel causative pathogen, incompletely understood clinical sequelae, and limited availability of testing resources. Given the variability in viral load across and within patients, absolute viral load quantification directly from crude lysate is important for diagnosis and surveillance. Here, we investigate the use of digital droplet PCR (ddPCR) for SARS-CoV-2 viral load measurement directly from crude lysate without nucleic acid purification. We demonstrate ddPCR accurately quantifies SARS-CoV-2 standards from purified RNA and multiple sample matrices, including commonly utilized universal transport medium (UTM). In addition, we find ddPCR functions robustly at low input viral copy numbers on nasopharyngeal swab specimens stored in UTM without upfront RNA extraction. We also show ddPCR, but not qPCR, from crude lysate shows high concordance with viral load measurements from purified RNA. Our data suggest ddPCR offers advantages to qPCR for SARS-CoV-2 detection with higher sensitivity and robustness when using crude lysate rather than purified RNA as input. More broadly, digital droplet assays provide a potential method for nucleic acid measurement and infectious disease diagnosis with limited sample processing, underscoring the utility of such techniques in laboratory medicine.

Direct Comparison of SARS-CoV-2 Analytical Limits of Detection across Seven Molecular Assays.

Analytical sensitivity for SARS-CoV-2 detection is a key performance metric for the evaluation of viral detection assays. We determined analytical limits of detection for seven SARS-CoV-2 assays using serial dilutions of pooled patient material quantified with droplet digital PCR. Limits of detection ranged from ≤10 to 74 copies/ml for commercial high-throughput laboratory analyzers (Roche Cobas, Abbott m2000, and Hologic Panther Fusion) and 167 to 511 copies/ml for sample-to-answer (DiaSorin Simplexa, GenMark ePlex) and point-of-care instruments (Abbott ID NOW). The CDC assay yielded limits of detection ranging from 85 to 499 copies/ml, depending on the extraction method and thermocycler used. These results can help to inform the assay choice for testing approaches to manage the current COVID-19 outbreak.

Genomic surveillance reveals multiple introductions of SARS-CoV-2 into Northern California.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread globally, with >365,000 cases in California as of 17 July 2020. We investigated the genomic epidemiology of SARS-CoV-2 in Northern California from late January to mid-March 2020, using samples from 36 patients spanning nine counties and the Grand Princess cruise ship. Phylogenetic analyses revealed the cryptic introduction of at least seven different SARS-CoV-2 lineages into California, including epidemic WA1 strains associated with Washington state, with lack of a predominant lineage and limited transmission among communities. Lineages associated with outbreak clusters in two counties were defined by a single base substitution in the viral genome. These findings support contact tracing, social distancing, and travel restrictions to contain the spread of SARS-CoV-2 in California and other states.

Rapid Detection of 2019 Novel Coronavirus SARS-CoV-2 Using a CRISPR-based DETECTR Lateral Flow Assay.

An outbreak of novel betacoronavirus, SARS-CoV-2 (formerly named 2019-nCoV), began in Wuhan, China in December 2019 and the COVID-19 disease associated with infection has since spread rapidly to multiple countries. Here we report the development of SARS-CoV-2 DETECTR, a rapid (~30 min), low-cost, and accurate CRISPR-Cas12 based lateral flow assay for detection of SARS-CoV-2 from respiratory swab RNA extracts. We validated this method using contrived reference samples and clinical samples from infected US patients and demonstrated comparable performance to the US CDC SARS-CoV-2 real-time RT-PCR assay.

A Genomic Survey of SARS-CoV-2 Reveals Multiple Introductions into Northern California without a Predominant Lineage.

The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 has spread globally, resulting in >300,000 reported cases worldwide as of March 21st, 2020. Here we investigate the genetic diversity and genomic epidemiology of SARS-CoV-2 in Northern California using samples from returning travelers, cruise ship passengers, and cases of community transmission with unclear infection sources. Virus genomes were sampled from 29 patients diagnosed with COVID-19 infection from Feb 3rd through Mar 15th. Phylogenetic analyses revealed at least 8 different SARS-CoV-2 lineages, suggesting multiple independent introductions of the virus into the state. Virus genomes from passengers on two consecutive excursions of the Grand Princess cruise ship clustered with those from an established epidemic in Washington State, including the WA1 genome representing the first reported case in the United States on January 19th. We also detected evidence for presumptive transmission of SARS-CoV-2 lineages from one community to another. These findings suggest that cryptic transmission of SARS-CoV-2 in Northern California to date is characterized by multiple transmission chains that originate via distinct introductions from international and interstate travel, rather than widespread community transmission of a single predominant lineage. Rapid testing and contact tracing, social distancing, and travel restrictions are measures that will help to slow SARS-CoV-2 spread in California and other regions of the USA.

CRISPR-Cas12-based detection of SARS-CoV-2.

An outbreak of betacoronavirus severe acute respiratory syndrome (SARS)-CoV-2 began in Wuhan, China in December 2019. COVID-19, the disease associated with SARS-CoV-2 infection, rapidly spread to produce a global pandemic. We report development of a rapid (<40 min), easy-to-implement and accurate CRISPR-Cas12-based lateral flow assay for detection of SARS-CoV-2 from respiratory swab RNA extracts. We validated our method using contrived reference samples and clinical samples from patients in the United States, including 36 patients with COVID-19 infection and 42 patients with other viral respiratory infections. Our CRISPR-based DETECTR assay provides a visual and faster alternative to the US Centers for Disease Control and Prevention SARS-CoV-2 real-time RT-PCR assay, with 95% positive predictive agreement and 100% negative predictive agreement.