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Biomedical subjects

Cameron Myhrvold

Publications and source records attributed to Cameron Myhrvold.

2 recordsLinked to original sources

Using CRISPR for viral nucleic acid detection.

Pathogenic microorganisms, such as viruses, have threatened human health and will continue to contribute to future epidemics and pandemics, highlighting the importance of developing effective diagnostics. To contain viral outbreaks within populations, fast and early diagnosis of infected individuals is essential. Although current standard methods are highly sensitive and specific, like RT-qPCR, some can have slow turnaround times, which can hinder the prevention of viral transmission. The discovery of CRISPR-Cas systems in bacteria and archaea initially revolutionized the world of genome editing. Intriguingly, CRISPR-Cas enzymes also have the ability to detect nucleic acids with high sensitivity and specificity, which sparked the interest of researchers to also explore their potential in diagnosis of viral pathogens. In particular, the CRISPR-Cas13 system has been used as a tool for detecting viral nucleic acids. Cas13's capability to detect both target RNA and non-specific RNAs has led to the development of detection methods that leverage these characteristics through designing specific detection read-outs. Optimization of viral sample collection, amplification steps and the detection process within the Cas13 detection workflow has resulted in assays with high sensitivity, rapid turnaround times and the capacity for large-scale implementation. This review focuses on the significant innovations of various CRISPR-Cas13-based viral nucleic acid detection methods, comparing their strengths and weaknesses while highlighting Cas13's great potential as a tool for viral diagnostics.

CRISPR-Cas Systems

Model-directed generation of artificial CRISPR-Cas13a guide RNA sequences improves nucleic acid detection.

CRISPR guide RNA sequences deriving exactly from natural sequences may not perform optimally in every application. Here we implement and evaluate algorithms for designing maximally fit, artificial CRISPR-Cas13a guides with multiple mismatches to natural sequences that are tailored for diagnostic applications. These guides offer more sensitive detection of diverse pathogens and discrimination of pathogen variants compared with guides derived directly from natural sequences and illuminate design principles that broaden Cas13a targeting.

CRISPR-Cas Systems