Researchers at the Stanford University School of Medicine and Intel Corp. have collaborated to synthesize and study a grid-like array of short pieces of a disease-associated protein on silicon chips normally used in computer microprocessors. They used this chip, which was created through a process used to make semiconductors, to identify patients with a particularly severe form of the autoimmune disease lupus.
Although the new technology is focused on research applications, it has the potential to eventually improve diagnoses of a multitude of diseases, as well as to determine more quickly what drugs may be most effective for a particular patient. It may also speed drug development by enabling researchers to better understand how proteins interact in the body.
“When I see patients in the clinic right now, I may know they have arthritis, but I don’t know which of the 20 or 30 types of the disease they have,” said associate professor of medicine Paul (P.J.) Utz, MD, noting that existing methods can take days or even weeks to answer such questions. “Now we can measure thousands of protein interactions at a time, integrate this information to diagnose the disease and even determine how severe it may be. We may soon be able to do this routinely while the patient is still in the physician’s office.”
Utz is a co-senior author of the research, published online Aug. 19 in Nature Medicine. Postdoctoral scholar Chih Long Liu, PhD, and Madoo Varma, PhD, director and head of life science research operations and business strategy for Intel’s Integrated Biosystems Laboratory, are the other senior authors. Graduate student Jordan Price is the first author. The research was funded in part by Intel Corp., and Intel scientists created the protein array on the silicon chips for the Stanford researchers to study.
The technology described in the study echoes that of DNA microarrays, in which thousands of unique nucleotide sequences are dotted on a glass slide in a grid-like pattern to identify patterns of gene expression in cells and tissues. Prior to the collaboration with Intel, Utz and his colleagues were using a similar technique for peptides — affixing them in defined patterns to glass or other substrates and then washing them with solutions of cellular or blood-borne proteins. A binding event between a protein in the solution, such as an antibody, and its slide-bound partner is indicated by a fluorescent signal, which is developed through a meticulous and lengthy series of detection steps.
About four years ago, however, researchers at Intel approached Utz and his colleagues with the idea of using silicon as a microarray platform to synthesize the peptides directly on the chip, rather than making the peptides separately and spotting them on the array using a robot.
“Honestly, we thought it wouldn’t work,” said Utz. But it did, and it had several advantages. For one thing, silicon is much less sticky to proteins than glass. As a result, researchers can skip some experimental steps meant to block random binding of peptides to the substrate. Silicon also allows the researchers to arrange the individual peptides more closely together, using the space much more efficiently. Finally, unlike glass, silicon alone does not fluoresce, making signal detection easier.
There’s also the promise of devising new, faster detection methods on the more-versatile silicon chip.
“If we couple these Intel arrays with an electronic detection method, for example, we could have real-time sensing over a period of minutes,” said Utz.
Read the press release at Stanford School of Medicine.
Read the manuscript published at Nature Medicine: On silico peptide microarrays for high-resolution mapping of antibody epitopes and diverse protein-protein interactions