STANFORD, Calif.—"An app on a smart phone for allergytesting is realistic," says Stanford's Dr. Paul ("P.J.") Utz, as the eventual result of the collaboration between researchers at the StanfordUniversity School of Medicine and Intel Corp.
To date, the team has synthesized and studied a grid-likearray of short pieces of a disease-associated protein on silicon chips normallyused in computer microprocessors. They used this chip, which was createdthrough a process used to make semiconductors, to identify patients with aparticularly severe form of the autoimmune disease lupus linked to individualpeptide features.
"When I see patients in the clinic right now, I may knowthey have arthritis, but I don't know which of the 20 or 30 types of thedisease they have," notes Utz, an associate professor of medicine in Stanford'sdivision of immunology and rheumatology. He adds that existing methods can takedays or even weeks to answer such questions. "Now we can measure thousands ofprotein interactions at a time, integrate this information to diagnose thedisease and even determine how severe it may be. We may soon be able to do thisroutinely while the patient is still in the physician's office."
Using the new silicon chips, the Stanford team was able toidentify patients with lupus who expressed high levels of antibodies against aparticular histone called 2B. They then confirmed that these patients wereprecisely the ones struggling with a more severe form of the disease.
"Lupus is highly variable, and in some cases is quitesevere," says Utz. "Companies developing therapies are now accepting patientswith lupus for clinical trials without knowing which subset of disease they arein. This method could potentially be used to identify only those patientslikely to benefit, and aid in the identification of effective drugs."
To better understand these interactions, researchers atIntel synthesized short segments of peptides on silicon wafers using photolithography,the same process used to make semiconductors.
"With the Intel chip, the number of dots could be up to amillion," Utz says, "but right now, 50,000 peptides is our next goal. Then weneed to build a circuit that can integrate the array."
The researchers hope to eventually embed an integratedsemiconductor circuit within the microprocessor-ready silicon chip to create asort of minicomputer that could take the guesswork and decision-making out ofmany clinical processes (and perhaps lead to that smartphone app for allergytesting). It might also spell out patient-specific diagnoses or identify whichpotential treatments are most likely to be effective.
Initially, the Stanford/Intel team built a microarray usingthe last 21 amino acids of histone 2B. In making the array, they synthesizedevery possible overlapping sequence of every length from the short string ofamino acids: 1-21 (the full-length sequence) to 17-20 (four amino acids) to2-20 (19 amino acids) and all other possible variations creating 9,000 uniquepeptide dots on the array. They then washed the chip with solutions ofantibodies known to bind the sequence.
The pattern of binding showed that one antibody couldrecognize and bind to a sequence composed of only two amino acids of theoriginal 21. Another required at least four amino acids, one of them modified,for binding. Analyzing the binding of solutions of other antibodies in eachcase delineated specific binding regions, or epitopes, within the originalshort sequence.
When Intel approached Utz and his colleagues with the ideaof using silicon as a microarray platform to synthesize the peptides directlyon the chip the Stanford group, he was skeptical.
"Intel didn't know anything about biology and, honestly, wethought it wouldn't work," says Utz.
But it did. Silicon also allows the researchers to arrangethe individual peptides more closely together, using the space much moreefficiently. Finally, unlike glass, silicon alone does not fluoresce, makingsignal detection easier.
"If we couple these Intel arrays with an electronicdetection method, we could have real-time sensing over a period of minutes,"says Utz.
Utz notes that the four-year effort has cost "about $500,000."Silicon wound up being "one of the best surfaces we've ever worked with," hestates.
Although the new technology is focused on researchapplications, it has the potential to eventually improve diagnoses of amultitude of diseases, as well as to determine more quickly what drugs may bemost effective for a particular patient. It may also speed drug development byenabling researchers to better understand how proteins interact in the body.
The researchers are now exploring the use of the techniqueto help design influenza vaccines that elicit a strong immune response, as wellas ways to incorporate the three-dimensional folding involved in most proteininteractions.
