Bypassing Genetic Bottlenecks With the CRISPR-SNP-Chip
Bypassing Genetic Bottlenecks With the CRISPR-SNP-Chip
Since its invention in 1983, genomics laboratories across the globe have been utilizing the polymerase chain reaction (PCR) to amplify DNA. Since then, few fundamentally new technologies have been invented in this area. In order to “democratize” the field of genomics, Cardea Bio has developed the CRISPR-SNP-Chip, a system that enables the detection of many biomolecules directly, using a minimally processed sample.
We spoke to Cardea Bio's CEO, Michael Heltzen, and Dr. Kiana Aran, chief scientific officer, to find out more about the development of the SNP-Chip and how it has been used in a recent study to detect sickle cell disease and amyotrophic lateral sclerosis (ALS).
Molly Campbell (MC): For our readers that may be unfamiliar, can you explain how the SNP-Chip works and how the technology was developed?
Michael Heltzen (MH): The CRISPR-SNP-Chip – SNP-Chip for short – is a CRISPR-powered system that runs on Cardean transistors and infrastructure. Cardean transistors are graphene-based field effect transistors (gFET) that use molecular biology bits as the transistor gate to form a direct link between live molecular signals and computer circuits. The nano material graphene was chosen as it has high biocompatibility and it is a near perfect conductor that gives the system a time resolution (detection speed) never seen before in life science. When a target molecule is present in the sample, it binds to the capture mechanism (the molecular gate) immobilized at the surface, changing the electrical base line profile of the transistor. This electrical signal is then digitized by a high-speed reader and fed into computer software that interprets the signal in near real time. The Cardean infrastructure and chips can be used for near real-time direct detection of many classes of biomolecules, such as DNA, RNA and protein interactions, including RNA binding proteins and other interactions that otherwise can’t be detected. In the case of SNP-chip, the capture molecule is a CRISPR-Cas complex immobilized to the surface with a guide RNA (gRNA) that is highly specific to the SNP target of interest. When this Cas-complex finds its target in the sample genome, it binds to it, creating an electrical signal across the graphene surface that can be read on the linked up computer. If the target SNP is not present in the sample genome, there will be no perfect binding event, and that can be seen in the signal profile.
In contrast with other genetic testing technologies like PCR and sequencing, which require much more time and well-equipped labs with highly trained technical staff to execute complex sample prep and measuring processes, the SNP-Chip needs only a minimally processed sample (e.g., from blood, saliva or plant material) to work. As such, SNP-Chip is the first genetic detection method that does not suffer from the problems and bottlenecks caused by DNA amplification, nor does it require expensive optical detection instruments.
MC: Can you talk about the rationale behind the latest study that used the SNP-Chip to detect sickle cell and ALS diseases?
MH: Sickle cell disease and ALS are both human genetic diseases resulting from the same phenomenon: single-nucleotide polymorphisms (SNPs), in which individual base pairs in various regions of the human genome differ between individuals. While many SNPs have no significant phenotypic effect, others have the potential to give rise to disease. Sickle cell and ALS represent two of the most widespread, severe and well-studied of these SNP-induced diseases. Studying the SNP-Chip on sickle cell and ALS allowed our research to have a greater impact and gave us the opportunity to test our technology’s ability to discriminate between homozygous and heterozygous samples without DNA amplification. Both diseases are furthermore early targets for CRISPR gene editing efforts by more pharma companies, and therefore relevant examples of use cases of the technology being used for quality assurance for genome engineering efforts.
MC: In the Nature Biomedical Engineering study, the SNP-Chip was able to discriminate between homozygous samples containing two copies of the healthy SNP vs the disease-associated SNP, without DNA amplification. Why is this a significant development?
MH: Having a single DNA base-pair resolution without the need of a fully equipped and expensive DNA lab is almost unbelievable for most geneticists, as it could lead to a future where DNA insight is as normal as any other data insight.
Through PCR and other DNA sample prep, the genomic sample is a proxy signal of itself before a signal is generated and then recorded, for example, sequencing a genome or a PCR test process can also take days. The SNP-Chip will in the future be able to be handheld and can provide answers to the presence or absence of important SNP mutations within an hour. This will allow doctors and gene-therapy developers to get the answers and actionable insights they need to provide and develop solutions to many diseases and save lives that we are not able to do today.
As SNPs make up 50 percent of mutations known to cause genetic disease the ability of the SNP-Chip to be reprogrammed via gRNAs to identify different disease markers is a relatively straightforward process that requires simply designing specific gRNAs to bind to SNPs specific to each disease. Most molecular biologists can therefore do it. Virtually any genetic disease can therefore be detected via SNP-Chip, as long as a gRNA can be designed to seek the target. In addition, SNP-chip is not just limited to human diagnostics but can also be used for SNP detection in any genetic material of interest for a wide range of applications, such as genotyping for agricultural and environmental monitoring. Eliminating the need for amplification means that detection can be done rapidly and at the point of need with minimal equipment and processing – bringing solutions to where they are most needed.
MC: SNP-Chip “opens up a new range of possibilities for diagnostic and research applications”. Can you expand on what some of these possibilities are, both in medical genetics and beyond?
Kiana Aran (KA): The ability to detect SNPs on a chip does not just get to the core of human health genetics, it also gives us valuable and actionable insight into areas like agriculture, industrial bioprocesses and even evolutionary change, such as mutations conferring resistance to antibiotics or mutating viruses. By eliminating the need for amplification and large optical instruments, SNP-Chip will make SNP genotyping for these purposes readily accessible. Our hope is that this paper will inspire scientists worldwide to explore SNP-Chip’s capacity for detecting genetic variation.
MC: Are there any challenges associated with developing a CRISPR-based device for use in a medical context?
MH: CRISPR and gFETs are novel technologies. Anytime that we are relying on a methodology or technology to bring insight to someone’s health, safety is critical. Maturing a new technology to the levels of consistency needed to meet the standards for human safety requires significant efforts in optimization and scaling. SNP-Chip is built on the Cardea infrastructure, which can meet the needed scale. Further optimization, safety testing and meeting all requirements set forth by the FDA is needed before ever considering using SNP-Chip and related technologies in a medical context. CRISPR-Chip and SNP-Chip is for research-use only, like www.CRISPRqc.com, as an early example.
MC: You have said “I believe this is the biggest tech breakthrough in the genetics industry since the invention of PCR in 1983”. What has made this breakthrough possible?
MH: First of all, there has been very few fundamentally new DNA detection technologies invented since PCR amplification (as that is what most technology is built with), and that is in itself a thought-provoking point, that the best and newest tech we have available in a pandemic is from the 80’s.
The inception of SNP-Chip can be viewed as the convergence of multiple distinct technological waves; it is the parallel advancements in the fields of semiconductors, digital networks, genomics and gene-editing that have made such a ground-breaking invention possible. When these technologies were invented, no one imagined it was possible to bring them together in such an impactful way that we would be able to get around using DNA amplification. By combining CRISPR with graphene semiconductors, we have enabled direct access and interaction – allowing us to pair biology directly with hypersensitive measuring technology to tap into the 3B year of R&D that we call evolution.
MC: How will SNP-Chip “democratize” genetics?
MH: Previous detection of genetic mutations and variation relied on largely inefficient optical technologies only found in DNA labs (e.g., PCR test, sequencing) as they required lengthy amplification steps, complex bio reagent use and processes done by technical trained experts. Our technology, the SNP-Chip, bypasses all of these bottlenecks and allows for the digital, direct and accurate detection of SNPs with minimal sample processing and no amplification step needed. In doing so, the SNP-Chip opens the door for a far more rapid, simple and accessible means of detecting genetic variation. With time it means everybody can do it everywhere.
MC: What is next for CRISPR-SNP-Chip?
MH: SNP-Chip and CRISPR-Chip open the door for thousands of use cases and possibilities and Cardea cannot possibly develop all of them alone. Through the Innovation Partnership Program, Cardea has created a vehicle for organizations to access these technologies to build novel, market disrupting products across agriculture, life science research, defense, environmental monitoring, human health and more. In the not too far future the Cardea partners will be able to start combining DNA, RNA and protein measurements on the same chips and the same samples, and that way open the door into understanding systems biology.
Michael Heltzen and Kiana Aran were speaking to Molly Campbell, Science Writer for Technology Networks