CRISPR-based COVID-19 surveillance using a genomically-comprehensive machine learning approach

The emergence and outbreak of SARS-CoV-2, the causative agent of COVID-19, has rapidly become a global concern and has highlighted the need for fast, sensitive, and specific tools to surveil circulating viruses. Here we provide assay designs and experimental resources, for use with CRISPR-based nucleic acid detection, that could be valuable for ongoing surveillance. We provide assay designs for detection of 67 viral species and subspecies, including: SARS-CoV-2, phylogenetically-related viruses, and viruses with similar clinical presentation. The designs are outputs of algorithms that we are developing for rapidly designing nucleic acid detection assays that are comprehensive across genomic diversity and predicted to be highly sensitive and specific. Of our design set, we experimentally screened 4 SARS-CoV-2 designs with a CRISPR-Cas13 detection system and then extensively tested the highest-performing SARS-CoV-2 assay. We demonstrate the sensitivity and speed of this assay using synthetic targets with fluorescent and lateral flow detection. Moreover, our provided protocol can be extended for testing the other 66 provided designs. Assay designs are available at https://adapt.sabetilab.org/.

Integrated sample inactivation, amplification, and Cas13-based detection of SARS-CoV-2

The COVID-19 pandemic has highlighted that new diagnostic technologies are essential for controlling disease transmission. Here, we develop SHINE (SHERLOCK and HUDSON Integration to Navigate Epidemics), a sensitive and specific integrated diagnostic tool that can detect SARS-CoV-2 RNA from unextracted samples. We combine the steps of SHERLOCK into a single-step reaction and optimize HUDSON to accelerate viral inactivation in nasopharyngeal swabs and saliva. SHINEs results can be visualized with an in-tube fluorescent readout -- reducing contamination risk as amplification reaction tubes remain sealed -- and interpreted by a companion smartphone application. We validate SHINE on 50 nasopharyngeal patient samples, demonstrating 90% sensitivity and 100% specificity compared to RT-PCR with a sample-to-answer time of 50 minutes. SHINE has the potential to be used outside of hospitals and clinical laboratories, greatly enhancing diagnostic capabilities.

Equipment-free detection of SARS-CoV-2 and Variants of Concern using Cas13

The COVID-19 pandemic, and the recent rise and widespread transmission of SARS-CoV-2 Variants of Concern (VOCs), have demonstrated the need for ubiquitous nucleic acid testing outside of centralized clinical laboratories. Here, we develop SHINEv2, a Cas13-based nucleic acid diagnostic that combines quick and ambient temperature sample processing and lyophilized reagents to greatly simplify the test procedure and assay distribution. We benchmarked a SHINEv2 assay for SARS-CoV-2 detection against state-of-the-art antigen-capture tests using 96 patient samples, demonstrating 50-fold greater sensitivity and 100% specificity. We designed SHINEv2 assays for discriminating the Alpha, Beta, Gamma and Delta VOCs, which can be read out visually using lateral flow technology. We further demonstrate that our assays can be performed without any equipment in less than 90 minutes. SHINEv2 represents an important advance towards rapid nucleic acid tests that can be performed in any location.

Multiplexed CRISPR-based microfluidic platform for clinical testing of respiratory viruses and SARS-CoV-2 variants

The COVID-19 pandemic has demonstrated a clear need for high-throughput, multiplexed, and sensitive assays for detecting SARS-CoV-2 and other respiratory viruses as well as their emerging variants. Here, we present microfluidic CARMEN (mCARMEN), a cost-effective virus and variant detection platform that combines CRISPR-based diagnostics and microfluidics with a streamlined workflow for clinical use. We developed the mCARMEN respiratory virus panel (RVP) and demonstrated its diagnostic-grade performance on 533 patient specimens in an academic setting and then 166 specimens in a clinical setting. We further developed a panel to distinguish 6 SARS-CoV-2 variant lineages, including Delta and Omicron, and evaluated it on 106 patient specimens, with near-perfect concordance to sequencing-based variant classification. Lastly, we implemented a combined Cas13 and Cas12 approach that enables quantitative measurement of viral copies in samples. mCARMEN enables high-throughput surveillance of multiple viruses and variants simultaneously.

Phylogenetic analysis of SARS-CoV-2 in the Boston area highlights the role of recurrent importation and superspreading events

SARS-CoV-2 has caused a severe, ongoing outbreak of COVID-19 in Massachusetts with 111,070 confirmed cases and 8,433 deaths as of August 1, 2020. To investigate the introduction, spread, and epidemiology of COVID-19 in the Boston area, we sequenced and analyzed 772 complete SARS-CoV-2 genomes from the region, including nearly all confirmed cases within the first week of the epidemic and hundreds of cases from major outbreaks at a conference, a nursing facility, and among homeless shelter guests and staff. The data reveal over 80 introductions into the Boston area, predominantly from elsewhere in the United States and Europe. We studied two superspreading events covered by the data, events that led to very different outcomes because of the timing and populations involved. One produced rapid spread in a vulnerable population but little onward transmission, while the other was a major contributor to sustained community transmission, including outbreaks in homeless populations, and was exported to several other domestic and international sites. The same two events differed significantly in the number of new mutations seen, raising the possibility that SARS-CoV-2 superspreading might encompass disparate transmission dynamics. Our results highlight the failure of measures to prevent importation into MA early in the outbreak, underscore the role of superspreading in amplifying an outbreak in a major urban area, and lay a foundation for contact tracing informed by genetic data.