NEW YORK (GenomeWeb) – Call it a multiplexed approach to rethinking PCR. Rice University Professor David Zhang is setting out to refine the application of polymerase chain reaction, all the way from hybridization dynamics to instrumentation.
It's an ambitious effort, but Zhang's got a new grant from the National Institutes of Health and a partnership with Thermo Fisher Scientific to help him along the way.
Earlier this month, he received a $3 million, five-year grant awarded by the National Cancer Institute to design and validate new reagents and instrumentation for efficient, point-of-care analysis of cancer mutations, capable of detection and quantification of thousands of single nucleotide variants.
"We've developed new methods for making PCR extremely specific," Zhang told GenomeWeb. "We can consistently detect alleles at frequencies down to 0.1 percent."
That specificity, combined with computational approaches to predict which primers will problematically dimerize, could usher in new multiplex possibilities for PCR.
Those technical advancements, along with work Zhang is doing on building a point-of-care PCR instrument, could help elevate PCR as a tool for cancer recurrence monitoring.
"A standard PCR assay consists of DNA reagents, enzymes, and the instrument," he said. "We're working on two of those, DNA and the instrument."
Zhang's lab at Rice has specialized in the study of DNA hybridization. He's come up with novel probes that have several applications, such as next-generation sequencing target enrichment. These probes have helped him spin out technologies to Searna Technologies, a company he co-founded.
Now, he's turning his attention to PCR to help amplify specific targets and block unwanted amplification using specially designed reagents, sensitive to single-base mutations at 0.1 percent allele frequency across a temperature change of 8˚ C in the PCR annealing stage.
One of the avenues Zhang is taking to improve multiplex PCR is to reduce primer-dimers. As multiplexing increases, the opportunity to generate nonsense primer-dimers follows. He's coming at primer-dimers from two angles: reagent design and computational prediction. The NCI grant will allow him to further develop them and validate them.
Special primers with modifications can make primer-dimers less of a problem in the first place, but Zhang is also pursuing a computational approach, which will allow researchers to predict before the reaction which primers might dimerize. This knowledge might allow them to select different primers that are less likely to dimerize.
"It's a machine learning-based method where we analyze a whole bunch of primer-dimers," Zhang explained. The computer program doesn't simulate every biophysical process (Zhang is also working on such a project), but is designed to correlate to which primers dimerize in reality.
"We design a whole bunch of primers and even kind of forget about whether they amplify correctly," he said. "Then we categorize how much they primer-dimerize and test different subsets at two-, four-, eight-plex, et cetera.
"What we hope to build in the end is a software package where you put in primers and it will tell you, 'oh, this combo will come up as a primer-dimer at 28 cycles,'" he said. It's a way of simulating the PCR process in a multiplex format.
Zhang acknowledged his computational model will have room for improvement, but said it would probably be better than current tools to analyze primer-dimers, especially in multiplex PCR.
Many current tools for predicting dimerization and designing primers in a multiplex setting just don't work very well, he said, and those that exist are proprietary. Thermo Fisher subsidiary Life Technologies offers Ampliseq, and there are enzymatic approaches to reducing primer-dimers, but there's little in the scientific literature about them.
"We don't know the details of design process," Zhang said. "We can't say for sure whether we're repeating some things, but we do think we have a unique angle. We think we understand DNA hybridization better than most groups out there do."
One aspect of his computational approach is to map out the possibilities of complex primer-dimers. His lab is building a large data set of primer-dimer reactions that they experimentally observe. These observations are then fed into the model to help predictions.
"Most people focus on the design aspect, saying, 'How do I design 100 different primers that will play nicely with each other.' We actually start from a later stage. We say, 'Let's not worry about design.' If given 100 primers, we want to predict at which point they will primer-dimerize, and see how severe that will be."
Researchers might be able to then swap out certain problematic primers and test if that will improve results, all before they actually run the reaction.
Part of Zhang's NCI grant is also going towards innovating PCR instruments. He's interested in developing a cheap and robust multiplex instrument and a chip to run on it.
Zhang's technology can help enrich and detect rare mutations that could be cancer drivers. A POC instrument could help with cancer recurrence monitoring, looking for rare mutations that would cause a patient to fall out of remission.
To this end, Zhang is building a microfluidic chip to analyze many different DNA mutations simultaneously. "It's a little bit like a microarray, but it's trying to combine microarray technology and PCR in a kind of fluidics device that has flow," Zhang said. "It's kind of a departure from our previous work, which is on well-mixed DNA settings," he said.
The chip will require having reagents bound to the chip surface — and with the grant money, he is planning to hire a new lab member with experience in this realm.
While the grants are at this point strictly for his lab at Rice, Zhang said he's always open to the idea of licensing new technologies to his startup, Searna.
"Down the road we may want to commercialize the results of the research that comes from [this grant], but at the moment these are for research only," he said.