Engineering CRISPR immune systems conferring GLRaV-3 resistance in grapevine

Grapevine leafroll-associated virus 3 (GLRaV-3) is one of the causal agents of grapevine leafroll disease (GLD), which severely impacts grapevine production in most viticultural regions of the world. The development of virus-resistant plants is a desirable strategy for the efficient control of viral diseases. However, natural resistant resources have not been reported in the genus Vitis, and anti-GLRaV-3 research has been quite limited in grapevine. In this study, by expressing FnCas9 and LshCas13a, we established a highly effective transgenic construct screening system via an optimized Agrobacterium-mediated transient delivery system in grapevine plantlets. Our study indicated that CRISPR/FnCas9 and LshCas13a caused GLRaV-3 inhibition. Moreover, three vectors-pCR01-CP, pCR11-Hsp70h and pCR11-CP-exhibited the most robust inhibition efficiency compared to those targeting other sites and could be further engineered to generate GLRaV-3-resistant grapevine. In addition, the viral interference efficiency of FnCas9 was dependent on its RNA binding activity. The efficiency of virus inhibition was positively correlated with the level of Cas gene expression. Importantly, we demonstrated that LshCas13a had better interference efficiency against viruses than FnCas9. In summary, this study confirmed that these two RNA-targeting CRISPR mechanisms can confer immunity against viruses in grapevine, providing new avenues to control GLRaV-3 or other RNA viruses in fruit crops.

FnCas9-based CRISPR diagnostic for rapid and accurate detection of major SARS-CoV-2 variants on a paper strip

The COVID-19 pandemic originating in the Wuhan province of China in late 2019 has impacted global health, causing increased mortality among elderly patients and individuals with comorbid conditions. During the passage of the virus through affected populations, it has undergone mutations, some of which have recently been linked with increased viral load and prognostic complexities. Several of these variants are point mutations that are difficult to diagnose using the gold standard quantitative real-time PCR (qRT-PCR) method and necessitates widespread sequencing which is expensive, has long turn-around times, and requires high viral load for calling mutations accurately. Here, we repurpose the high specificity of Francisella novicida Cas9 (FnCas9) to identify mismatches in the target for developing a lateral flow assay that can be successfully adapted for the simultaneous detection of SARS-CoV-2 infection as well as for detecting point mutations in the sequence of the virus obtained from patient samples. We report the detection of the S gene mutation N501Y (present across multiple variant lineages of SARS-CoV-2) within an hour using lateral flow paper strip chemistry. The results were corroborated using deep sequencing on multiple wild-type (n = 37) and mutant (n = 22) virus infected patient samples with a sensitivity of 87% and specificity of 97%. The design principle can be rapidly adapted for other mutations (as shown also for E484K and T716I) highlighting the advantages of quick optimization and roll-out of CRISPR diagnostics (CRISPRDx) for disease surveillance even beyond COVID-19. This study was funded by Council for Scientific and Industrial Research, India.

Rapid and accurate nucleobase detection using FnCas9 and its application in COVID-19 diagnosis

Rapid detection of DNA/RNA pathogenic sequences or variants through point-of-care diagnostics is valuable for accelerated clinical prognosis, as witnessed during the recent COVID-19 outbreak. Traditional methods relying on qPCR or sequencing are tough to implement with limited resources, necessitating the development of accurate and robust alternative strategies. Here, we report FnCas9 Editor Linked Uniform Detection Assay (FELUDA) that utilizes a direct Cas9 based enzymatic readout for detecting nucleobase and nucleotide sequences without trans-cleavage of reporter molecules. We also demonstrate that FELUDA is 100% accurate in detecting single nucleotide variants (SNVs), including heterozygous carriers, and present a simple web-tool JATAYU to aid end-users. FELUDA is semi-quantitative, can adapt to multiple signal detection platforms, and deploy for versatile applications such as molecular diagnosis during infectious disease outbreaks like COVID-19. Employing a lateral flow readout, FELUDA shows 100% sensitivity and 97% specificity across all ranges of viral loads in clinical samples within 1hr. In combination with RT-RPA and a smartphone application True Outcome Predicted via Strip Evaluation (TOPSE), we present a prototype for FELUDA for CoV-2 detection closer to home.