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Scientists have repurposed the CRISPR genetic modification technology to identify antibodies in blood samples from patients. This, along with a host of other applications, could inspire a new class of medical diagnostics.
The technology involves customizable collections of proteins attached to a variant of Cas9, the protein in the heart of CRISPR, that binds to DNA but does not cut it, as would genetic modification. When these Cas9-fused proteins are placed on a microchip with thousands of unique DNA molecules, each protein in the mixture will assemble itself into position on the chip with the appropriate DNA sequence. The researchers named this technique “PICASSO”, short for “peptide immobilization by Cas9-mediated self-organization”. By subsequently applying a blood sample to the PICASSO microarray, the proteins on the microchip that are recognized by the patient’s antibodies can be identified.
The team around Dr. Stephen Elledge of Harvard Medical School and Brigham and Women’s Hospital in Boston published the research online in Molecular Cell today. The first author of the article, Dr. Karl Barber, is a 2018 Schmidt Science Fellow, with much of the work on developing the technology during his fellowship research internship in the laboratory of the corresponding author Dr. Elledge takes place.
About PICASSO, Dr. Barber: “Imagine you want to paint a picture on a canvas, but instead of painting in the normal way, you mix all your colors, splash them on the canvas and you get the perfect picture. With our new technique, you place DNA molecules at defined locations on a surface and each protein from a mixture will then assemble itself to its corresponding DNA sequence, like an automated paint-by-numbers kit to quickly identify antibodies in clinical samples that recognize all proteins, that you are interested in. “
The research team has shown that the technology assembles thousands of different proteins, suggesting that it could be easily adapted as a broad spectrum medical diagnostic tool. In the work, they used the technique to detect antibodies that bind to proteins derived from pathogens, including SARS-CoV-2, from the blood of recovering COVID-19 patients.
Dr. Barber said, “In this work we have demonstrated the application of PICASSO to protein studies and created a tool that we believe could be quickly adapted for medical diagnostics. Our protein self-assembly technology could also be used to develop new biomaterials “and biosensors by simply attaching DNA targets to a scaffold and enabling the binding of Cas9-bound proteins.”
Group leader Dr. Elledge commented: “One of the most exciting aspects of this work is the demonstration of how CRISPR can be applied in a completely new environment. So far, CRISPR has been mainly used for gene editing and the detection of DNA or RNA. PICASSO brings the power of CRISPR to a new area of protein studies, and the molecular self-assembly strategy we have shown can help in the development of new research and diagnostic tools. “
Dr. Megan Kenna, Executive Director of Schmidt Science Fellows, said, “This technology has the potential to be used as a medical diagnostic tool that could one day enable clinicians to quickly diagnose and determine the best course of treatment for each individual patient.”
“The way in which Karl and the research team brought basic biology together with molecular engineering to make this important discovery shows why the interdisciplinarity at the heart of our fellowship is so crucial to the advancement of science.”
Researchers improve the efficiency and accessibility of CRISPR
More information:
Barber et al., CRISPR-Based Peptide Library Display and Programmable Microarray Self-Assembly for Rapid Quantitative Protein Binding Assays, Molecular Cell (2021), doi.org/10.1016/j.molcel.2021.07.027
Courtesy of Schmidt Science Fellows
citation: New CRISPR-based technology could revolutionize antibody-based medical diagnostics (2021, August 13), accessed on August 13, 2021 from https://phys.org/news/2021-08-crispr-based-technology-revolutionize-antibody -based- medical.html
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