Graphene Chip Detects DNA, RNA Mutations

Biosensor chip with a double stranded DNA probe embedded on a graphene transistor (University of California, San Diego)

15 June 2016. A biomedical engineering team developed a chip built on graphene that detects mutations in genetic material, for eventual use in mobile diagnostics equipment. Researchers from University of California in San Diego, led by engineering professor Ratnesh Lal, describe their device this week in Proceedings of the National Academy of Sciences.

Lal and colleagues from UC-San Diego’s Center for Excellence in Nanomedicine and Engineering are seeking a way of shrinking genetic analysis technologies into portable diagnostics equipment that can detect biomarkers for diseases resulting from mutations, variations in DNA sequences or RNA transcribed from the genetic code. Current equipment for detecting genetic variations called single nucleotide polymorphisms or SNPs are found in stationary lab equipment, which while accurate and effective, are expensive and time-consuming. The authors note that the growing use of precision medicine will likely mean increased demand for detection of genetic defects, thus the need for rapidly increasing the supply of these systems.

SNPs note differences in nucleotides, the DNA base building blocks identified by the letters A, C, G, and T. Most SNPs occur normally in the genetic code, but some of these variations are associated with inherited diseases, autoimmune conditions, and neurodegenerative disorders, as well as more common heart disease, cancer, and diabetes. Most of the current systems for detecting SNPs in specimen samples use enzymes, requiring expensive equipment in a lab setting. Efforts to develop alternatives to enzyme analysis, say the authors, so far encounter problems in specificity, returning too many false negative results.

The UC-San Diego team developed its device to search DNA or RNA strands and identify specific SNP sequences. The device analyzes individual strands of DNA or RNA looking for the SNP. When a targeted SNP sequence is encountered and binds to the chip, the device analyzes complementary strands replacing those with weak binding until a perfect match in the sequence is found. The matching strand then binds to the chip, which generates a signal indicting the device detected the targeted SNP.

The researchers built the device on graphene, a material closely related to graphite like that used in pencils. The material is very light, strong, chemically stable, and can conduct both heat and electricity, with applications in electronics, energy, and health care. With graphene, say the authors, they can replace measurement of chemical fluorescence used in standard lab systems, and algorithms in software for analysis, with electronic matching of complementary DNA or RNA strands. Thus graphene makes it possible to shrink the the device to a single chip, which in proof-of-concept tests returned results that correlated with standard lab systems using fluorescence measurement.

The authors say their electronic approach analyzing double DNA or RNA strands is also more reliable than other portable devices that sequence single strands. They report the graphene chip can sequence strands up to 47 nucleotides in length, which the authors say are the longest strands analyzed so far.

“We expected that with a longer probe, we can develop a reliable sequence-specific SNP detection chip,” says Lal in a university statement. “Indeed, we’ve achieved a high level of sensitivity and specificity with the technology we’ve developed.” For their next steps, the team plans to scale-up the technology and add wireless transmission. Later, the researchers hope to develop the chip into a clinical diagnostics tool for mobile and point-of-care devices.

Read more:

• More Genomic Tests Enhance Personalized Cancer Care
• Start-Up Licenses Genetics Technology for HIV Diagnostics
• Portable Genome Device to Combat Wildlife Trafficking
• Software Detects DNA Mutations in Single Cells
• 23andMe Creates Research Software for iPhone Apps

*     *     *