NEW YORK – Having listed this month on Nasdaq via a $1 billion-plus special purpose acquisition company, proteomics firm Quantum-Si has begun commercialization efforts for its protein sequencing platform.
The Guilford, Connecticut-based firm has placed two instruments in the field with a pair of early-access users, said CEO John Stark. The company also announced this week that it is establishing a 25,000-square-foot product development and operations facility in San Diego that it plans to begin operating in Q3 2021.
Founded by Jonathan Rothberg, inventor of the Ion Torrent next-generation sequencing technology, Quantum-Si aims to similarly apply semiconductor chip technology to protein sequencing, allowing for single-molecule analysis of proteins, including post-translational modifications. Ultimately, the company plans to apply its technology to molecules beyond proteins, including metabolites and nucleic acids, said Rothberg, noting that Quantum-Si researchers have done long-read DNA sequencing on the system.
The platform consists of two modules, a sample preparation component called Carbon and a semiconductor chip-based analyzer called Platinum. The Carbon module is a microfluidic system that uses a variety of sample prep techniques including target enrichment and sample depletion to reduce the dynamic range of proteomic samples prior to analysis by the Platinum system.
Rothberg said Carbon is relying on existing enrichment and depletion approaches to address proteomics' dynamic range challenges but that the system provides automated, easier-to-use versions of those methods.
"We've known how to deplete, we've known how to enrich, we've known how to do this [dynamic range] compression, but now we are moving it to a microfluidics platform," he said.
He added that the company was potentially interested in incorporating new proteomics sample prep technologies like Seer's nanobead-based Proteograph platform to its workflow.
"We would love to collaborate with [Seer] and move their protocols onto the Carbon platform," he said.
When it comes to proteins, the Platinum system runs in two modes — a protein sequencing mode, in which the instrument analyzes individual proteins by sequencing their individual amino acids, and what Rothberg called a "digital analyte" mode, an affinity agent-based approach in which the wells of the assay chip are functionalized with different affinity agents like antibodies, and analytes are identified by observing the kinetics of their binding to those agents.
Quantum-Si tackles protein sequencing by using probes to different amino acids, including modified amino acids, and observing the binding of those probes across proteins of interest. Key to the company's technology is that the semiconductor-based sensing device does not rely on observing the color of the probes for detection, but rather measures the timing of light emissions following excitation of the target molecules with a laser, which Rothberg said made it feasible to distinguish between the large number of amino acids and modified amino acids required for protein sequencing.
The device similarly relies on the timing of light emissions when operating in the digital analyte mode, measuring them to collect data on target binding to enable identification of the targets.
"We changed [detection of] colors to time, because there is a basic physics to colors and how fast they relax or come back to a ground state," Rothberg said. "The beautiful thing about that is while [semiconductor] chips are terrible at seeing colors — hence you have machines that cost half a million dollars if you want sequence DNA by color — but they are great on time."
This, he said, will allow Quantum-Si to sell instruments capable of single-molecule protein sequencing and protein detection for around $50,000.
That price point is key to the company's commercial strategy, said Stark. The high-end mass spectrometers used for most proteomics work typically run in the $500,000 to $1 million range, while one of Quantum-Si's competitors in terms of emerging proteomic technology, Nautilus Biotechnology, has priced its proteomic system at around $1 million. On the lower end, Olink's recently launched Signature Q100, which allows researchers to measure up to 92 proteins across 90 samples, lists for around $75,000.
"Any lab, at least in the US and Europe, a lab director can sign off on $50,000," Stark said. "It doesn't require a grant. So our sales cycles are tremendously fast."
The Platinum system's assay chips are disposable, making for a recurring revenue stream, he added. "So really the key is to get users using your technology frequently so then you have this amazing run rate."
Quantum-Si listed on Nasdaq this month after closing a business combination transaction with SPAC HighCape Capital Acquisition, in which it received roughly $109 million of cash held in HighCape's trust account and $425 million via a private investment in public equity transaction.
Stark said the company aims to place instruments at 10 sites by the end of the year and to place instruments at a total of around 50 sites throughout the entirety of its early-access launch, with a broad commercial launch planned for some time in 2022.
Rothberg said he anticipated that around 90 percent of the platform's early users would be focused on targeted protein work looking at "panels of tens to hundreds of proteins of interest," though he added that the current assay chips would enable measurement of hundreds to thousands of proteins using the system's digital analyte approach.
Stark said that while the company ultimately aims to be able to detect and distinguish between all 20 amino acids including modified forms, it is not at that level yet. He said, though, that it had calculated that if it were able to detect between 10 and 12 different amino acids, it would be able to measure roughly 80 percent of the proteome.
Quantum-Si is one of several companies looking to tackle proteomics via protein sequencing. One is San Diego-based startup Encodia, whose cofounder Michael Weiner, like Rothberg, is an inventor of 454 sequencing. Also, that firm's president, Mark Chee, and its VP and chief technology officer, Kevin Gunderson, are cofounders of Illumina, and Gunderson is the former senior director of advanced research at Illumina.
Encodia is using a labeling and degradation-based approach to protein sequencing, developing DNA tags to label amino acids on peptides and then degrading these peptides one amino acid at a time. Upon removal, the DNA tags can be sequenced using conventional NGS, allowing for readout of the tagged peptide sequences.
NGS firm Oxford Nanopore is also pursuing protein sequencing and has detailed methods using the protein ClpXP to unfold target proteins and translocate them through nanopores. The translocation of proteins through the pores generates signals that might, in theory, be used to identify the proteins and perhaps even determine their amino acid sequences, including the presence of post-translational modifications.
Rothberg said he believed the increased attention paid to proteomics stemmed in significant part from the sense in the genomics community that it has reached the point of diminishing returns with regard to using RNA as a surrogate for protein measurements.
"People have really pushed sequencing, sequencing cDNAs to find out levels of gene expression as a surrogate for gene expression," he said. "And so you have people getting diminishing returns."
That, he said, led people like himself, who had formerly focused on the development of genomic technologies, to shift their efforts to protein analysis.
"The ability to measure proteins is not only attractive to mass spec groups who want to quantify proteins, but it's also very attractive to the overall sequencing community," Stark said, noting that the company was not so much aiming to displace mass spec as to open up proteomics to a broader customer base.
"Mass spec is not going to go away over the next decade. It still offers tremendous value," he said. "But with mass spec, you are requiring [groups] to buy a system that is $500,000 to $1 million. You are requiring them to have an operator who is fairly sophisticated, and the operational cost of that is just not feasible for individual labs. We've built a device that is."