Abstract
CRISPR (clustered regularly interspaced short palindromic repeats), an ancient defense mechanism used by prokaryotes to cleave nucleic acids from invading viruses and plasmids, is currently being harnessed by researchers worldwide to develop new point-of-need diagnostics. In CRISPR diagnostics, a CRISPR RNA (crRNA) containing a "spacer" sequence that specifically complements with the target nucleic acid sequence guides the activation of a CRISPR effector protein (Cas13a, Cas12a or Cas12b), leading to collateral cleavage of RNA or DNA reporters and enormous signal amplification. CRISPR function can be disrupted by some types of sequence mismatches between the spacer and target, according to previous studies. This poses a potential challenge in the detection of variable targets such as RNA viruses with a high degree of sequence diversity, since mismatches can result from target variations. To cover viral diversity, we propose in this study that during crRNA synthesis mixed nucleotide types (degenerate sequences) can be introduced into the spacer sequence positions corresponding to viral sequence variations. We test this crRNA design strategy in the context of the Cas13a-based SHERLOCK (specific high-sensitivity enzymatic reporter unlocking) technology for detection of Crimean-Congo hemorrhagic fever virus (CCHFV), a biosafety level 4 pathogen with wide geographic distribution and broad sequence variability. The degenerate-sequence CRISPR diagnostic proves functional, sensitive, specific and rapid. It detects within 30-40 minutes 1 copy/μl of viral RNA from CCHFV strains representing all clades, and from more recently identified strains with new mutations in the CRISPR target region. Also importantly, it shows no cross-reactivity with a variety of CCHFV-related viruses. This proof-of-concept study demonstrates that the degenerate sequence-based CRISPR diagnostic is a promising tool of choice for effective detection of highly variable viral pathogens.
Highlights
Rapid reliable pathogen detection methods are critical for effective public health control measures, in order to prevent the further spread of infectious diseases and provide early diagnosis and treatment of patients [1]
Several types of CRISPR-based molecular diagnostics, currently under extensive development, hold great promise for field-deployable diagnosis of infectious diseases. These methods share a core mechanism of target recognition, where a CRISPR RNA contains a pathogen-specific “spacer” sequence that binds to the counterpart on the genetic material of the targeted pathogen
To address the viral sequence diversity, we have developed a “degenerate” sequence-based CRISPR strategy
Summary
Rapid reliable pathogen detection methods are critical for effective public health control measures, in order to prevent the further spread of infectious diseases and provide early diagnosis and treatment of patients [1]. PON diagnostics are anticipated to be broadly available, rapid, portable, easy to perform (by a non-professional with minimal or no training), and preferably sensitive and specific, at levels similar to or even higher than qPCR They can be deployed in extensive scenarios, for example, in medical laboratories to supplement testing at overwhelmingly high demand, or directly in the public and communities for mass testing (in airports, doctor’s offices, pharmacies, schools, or even homes, or by any individuals themselves). Among isothermal rapid molecular detection techniques, recombinase polymerase amplification (RPA) and loop mediated isothermal amplification (LAMP) platforms have so far been the best studied and most popularly used in the development of PON diagnostics [1,3,4] These can be optimized to reach high sensitivity, the sensitivity is typically lower than that of qPCR, and can sometimes suffer from nonspecific amplification leading to false positive results, especially when non-sequence-specific probes are used [3,5]. It is expected that improvement can be made through their coupling to an additional, sensitive and specific detection method [5]
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