May 31, 2016
Discovering disease-causing DNA in a sea of genetic code is a bit like finding a very tiny needle in a universe-sized haystack. The human genome contains about 3 billion base pairs, and mutations of just a few of those pairs in the wrong place could be enough to cause a life-threatening disease such as cancer.
Hertz Fellow David Zhang, a bioengineer at Rice University, wants to increase the odds of locating those elusive genetic variants, and do so in a cost-effective manner. With two separate grants from the National Institutes of Health totaling $5.5 million, Zhang will devote the next five years to efficiently detect and profile those rare DNA mutations that lead to illness.
“Way before it actually becomes medically a problem, (cancer cells) start shedding some of their DNA into the bloodstream, which can be used as a biomarker for detection,” Zhang said. “Basically you need to be able to detect cancer DNA at less than one part in a thousand; that’s why it’s a little bit challenging because there’s a large signal-to-noise problem.”
With a $2.5 million grant awarded in March, Zhang, head of Rice’s Nucleic Acid Bioengineering Laboratory (NABLab), will research allele enrichment techniques for next generation sequencing (NGS), essentially pushing healthy DNA strands to the side and focusing on the mutations. A number of new NGS platforms are being introduced for more clinical work, and allele enrichment facilitates maximizing the clinical information obtained using these lower throughput instruments.
“NGS is a technology that has matured over the past 10 years, allowing you to analyze complex samples,” Zhang said. “By weeding out unwanted DNA sequences, we can enable comprehensive mutation profiling for a fraction of the current cost.”
Currently, researchers can analyze anywhere from 10 billion to 1 trillion bases of information from a single sequencing run. While that sounds like a lot, Zhang said, it’s really not that much considering a single milliliter of blood can contain up to 100 quadrillion nucleotides.
“There’s still many orders of magnitude to go before we can really do truly comprehensive sequencing,” Zhang said. “Because of that, it’s still necessary for us to zoom in on these important parts of the DNA.”
The other NIH grant of $3 million, awarded last month, will go toward developing a polymerase chain reaction (PCR) point-of-care devices for cancer early detection and recurrence monitoring. Whereas standard PCR machines can analyze only a few different gene sequences at a time, Zhang is proposing a combination of microarrays and PCR reactions to analyze hundreds or thousands of genes simultaneously.
“We’ve basically designed these microarray probes in a way that’s really specific to particular sequences and we’re introducing a conduction flow fluidic chip on which the PCR reaction works,” Zhang said. “It’s actually a really simple idea.”
The chip, Zhang explained, is split into hot and cold sides, creating a thermal conduction current that allows a fluid (such as blood) to circulate and cycle autonomously using cheap and readily available components. The intent, Zhang said, is to devise a diagnostic capable of detecting cancer in a typical blood draw or urine sample that patients could do in their doctor’s office or at home.
“The way to beat cancer is to detect it early and doing something about it surgically,” Zhang said. “The survival rate for cancer really depends more than anything else on what stage you catch it… If you catch it in Stage 1 or 2 it’s as simple as going under the knife and cutting out the tumor. That’s the most cost-effective and successful way of treating cancer.”
Born and raised in Kansas, Zhang started his higher education at the California Institute of Technology, pursuing a degree in electrical and computer engineering. When the university decided to cancel that degree in favor of separate majors, he pivoted to biology, and with his Hertz Foundation funding attended grad school at Caltech to work on synthetic biology.
As a postdoc at Harvard Medical School, Zhang was drawn to work on research that would apply directly to human health, and dedicated himself to DNA analysis and detection. When he moved to Rice, he decided DNA diagnostics would be main focus of his NABlab.
Besides further developing detection technology, Zhang wants to gain a better understanding of DNA and RNA and how they interact. His lab is collaborating with Microsoft Research to apply machine learning to large datasets of known DNA sequences and using the information to predict thermodynamics and kinetics of new DNA sequences.