Gold Nanoparticles Speed Gene Detection Techniques

Armen Hareyan's picture

Gold Nanoparticles and Cancer Treatment

Cancer is a disease caused by genetic mutations, so it should be no surprise that cancer researchers and clinical oncologists alike are eager for new, inexpensive methods that would enable them to rapidly and accurately identify mutations associated with cancer. Using gold nanoparticles, two groups of investigators have each developed gene-identification methods that may fill this need.


Research teams headed by Lloyd Smith, Ph.D., at the University of Wisconsin-Madison, and Robert Corn, of the University of California-Irvine, each published papers in the journal Analytical Chemistry that detail the two new approaches to rapid, quantitative gene identification. Both of the new techniques identify single-nucleotide polymorphisms (SNPs), the most frequent type of human genetic variation, with the help of DNA microarrays. In each case, sample DNA is added to a gene chip containing known sequences of DNA. Each of these known sequences corresponds to a known SNP associated with a disease. After any DNA in the sample binds to its chip-immobilized complement, the chip is washed to remove any unbound DNA.

In the Wisconsin team's method, the DNA chip is then treated with an enzyme that degrades the ends of the bound DNA, leaving a free, reactive phosphate group that over the course of two subsequent biochemical reactions is labeled with a gold nanoparticle. Because of the techniques the researchers used, only those places on the DNA chip where a piece of sample DNA had been bound to a SNP-identifying DNA probe become labeled with gold nanoparticles. When the chip is then viewed under an electron microscope, the gold nanoparticles appear as white pinpoints on a black background. Commercial software can readily analyze the electron micrograph, providing an accurate tally of any SNPs that were present in the original sample.

The investigators note that their methodology improves labeling efficiency by as much as 15-fold over conventional analytical methods. In addition, the signal-to-noise ratio