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-2real-time RT-PCR assay, with 95% positive predictive agreement and 100% negative predictive agreement.

The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 has spread globally, with >52,000 cases in California as of May 4, 2020. Here we investigate the genomic epidemiology of SARS-CoV-2 in Northern California from late January to mid-March 2020, using samples from 36 patients spanning 9 counties and the Grand Princess cruise ship. Phylogenetic analyses revealed the cryptic introduction of at least 7 different SARS-CoV-2 lineages into California, including epidemic WA1 strains associated with Washington State, with lack of a predominant lineage and limited transmission between communities. Lineages associated with outbreak clusters in 2 counties were defined by a single base substitution in the viral genome. These findings support contact tracing, social distancing, and travel restrictions to contain SARS-CoV-2 spread in California and other states.

An unidentified agent was cultured in primary monkey cells at the Los Angeles County Public HealthDepartment from each of five stool specimens submitted from an outbreak of gastroenteritis. Electron microscopy and an adenovirus-specific monoclonal antibody confirmed this agent to be an adenovirus. Since viral titers were too low, complete serotyping was not possible. Using the DNase-sequence-independent viral nucleic acid amplification method, we identified several nucleotide sequences with a high homology to human adenovirus 41 (HAdV-41) and simian adenovirus 1 (SAdV-1). However, using anti-SAdV-1 sera, it was determined that this virus was serologically different than SAdV-1. Genomic sequencing and phylogenetic analysis confirmed that this new adenovirus was so divergent from the known human adenoviruses that it was not only a new type but also represented a new species (human adenovirus G). In a retrospective clinical study, this new virus was detected by PCR in one additional patient from a separate gastroenteritis outbreak. This study suggests that HAdV-52 may be one of many agents causing gastroenteritis of unknown etiology.

M. pneumoniae is the most common agent implicated in the California Encephalitis Project. Patients with M. pneumoniae-associated encephalitis are predominantly pediatric, and their presentations are clinically similar to enterovirus encephalitis, although they frequently require intensive care with prolonged hospitalizations. Given that M. pneumoniae infection is found more than any other pathogen, increased emphasis should be placed on elucidating the role and mechanism of M. pneumoniae in encephalitis.

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.