SHERLOCK: A Gene Tool To Detect Zika Virus, Cancer And Antibiotic Resistance Genes
Researchers have developed a new CRISPR-based genetic diagnostic tool that is designed to make fast and effective diagnosis of acute and chronic diseases like Zika, Ebola, cancer and other hereditary disorders. Application of CRISPR-based gene tools for the diagnosis of genetic disorders is not an entirely new concept. The CRISPR-Cas9 tools are already in use for the detection of diseases like retinitis pigmentosa and sickle cell disease. These tools use RNA sequences to target the specific DNA sequence, which are then cut with the help of the enzymes present in the tool.
The new SHERLOCK (Specific High-sensitivity Enzymatic Reporter unLOCKing) gene tool that was developed by a group of researchers from the Broad Institute in Cambridge in Massachusetts. It is highly sensitive and suitable for clinical applications.
According to Fierce Biotech, SHERLOCK targets the pathogenic/cancer RNA specific to the occurrence of diseases. It also employs the Cas13a enzymes for cutting the target as well as nearby RNA.
A similar Cas13a-based tool that was developed by CRISPR Therapeutics also focused on RNA detection. However, its low sensitivity, i.e., inability to detect low copy numbers of the targeted DNA, hindered its point of care applications in the diagnosis of diseases.
On the contrary, SHERLOCK can detect extremely low concentrations of Zika virus and cancer DNA in blood, urine and saliva samples. Feng Zhang and Jim Collins, the lead researchers of the study, described that their team used body heat to deliberately raise the levels of DNA/RNA and then subjected it to a second round of amplification.
This not only increased the RNA concentration but also multiplied the sensitivity of the test. In addition, the enzyme used in the test is designed to fluoresce upon detection of the target RNA, thereby facilitating easy diagnosis, Genetic Literacy Project reported.
SHERLOCK's high sensitivity makes it an appropriate tool for the tracking of outbreak of diseases such as Zika and Ebola in real-time conditions. Apart from this, the researchers also successfully checked the utility of the test in the identification of antibiotic resistance genes in micro-organisms such as Klebsiella pneumoniae bacteria.