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New Proteomic Technologies Firms Leading With Targeted Analyses


NEW YORK – New proteomic technologies are coming to market, with several entrants launching their platforms this year or preparing for releases over the next year or so.

But while these firms have indicated their intentions to offer proteome-scale measurements, most are currently focused on targeted analyses measuring only a handful of proteins, suggesting that existing tools like mass spectrometry and affinity-based platforms from companies like Olink and SomaLogic will continue to dominate proteomics research, at least in the near term.

Over the last several years, a handful of startups have sought to commercialize new approaches to protein analysis and proteomic profiling. Broadly speaking, they can be divided into two sets, one including companies like Austin, Texas-based Erisyon; San Diego-based Encodia; and Guilford, Connecticut-based Quantum-Si that are employing protein sequencing-based approaches and another that includes Seattle-based Nautilus Biotechnology; Woburn, Massachusetts-based NanoMosaic; and Fremont, California-based Alamar Biosciences that are relying on affinity reagents.

Alamar, Erisyon, and Encodia have provided little detail on their operations or commercialization plans. Several of the companies in this space, however, have either released products or plan to do so soon.

NanoMosaic began sales of its Tessie platform at the beginning of the year and has since placed "close to 10 systems," said John Boyce, the company's cofounder, president, and CEO.

The company's system uses arrays of silicon "nanoneedles" functionalized with antibodies or other affinity reagents to detect and quantify proteins. Its measurements are based on changes in optical resonance that occur when target molecules bind to the functionalized needles.

The firm closed a $40.8 million Series A round at the end of 2021 that it is using to support commercialization of the platform.

Quantum-Si, meanwhile, is planning to launch its proteomics platform in the second half of the year. It consists of two modules, a sample preparation component called Carbon and a semiconductor chip-based analyzer called Platinum. The company's technology uses two approaches to analyzing proteins — a protein sequencing mode, in which the instrument determines the amino acid sequence, and what the company has 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.

The company has placed systems with more than 10 early-access users who are exploring applications ranging from analysis of SARS-CoV-2 spike protein variants to single-cell omics research.

Nautilus remains on track for a late 2023 launch of its proteomics platform. The system uses multiple sets of relatively nonspecific affinity reagents to iteratively probe proteins bound to chips and analyzes the different binding patterns produced to make protein identifications.

According to Parag Mallick, the company's cofounder and chief scientist, the firm has demonstrated the ability to affix up to 10 billion individual proteins to its chips using biological samples including cell lysates. In theory, the array would allow it to analyze proteomes across a dynamic range as large as 109 to 1011.

Mallick said that in terms of a commercial launch, Nautilus is now focused on scaling the production of the chips used in its platform while maintaining good quality and process control. The company is also working to secure and develop the library of affinity reagents it needs for the system. It has projected that it could analyze roughly 95 percent of the proteome with a set of 300 binders. Last year, it entered a strategic partnership with antibody firm Abcam for access to antibodies and antibody development expertise.

A targeted focus

For all the discussion at Nautilus and other firms of their technologies' potential for proteome-scale experiments, they currently appear primarily focused on applying their systems to targeted assays looking at just a handful of proteins.

Nautilus, for instance, has made two collaborations using its platform public to date, one with Genentech to detect specific forms of phosphorylated tau protein and the other with an investigator at the University of Texas MD Anderson Cancer Center using the platform to investigate specific proteins and proteoforms of interest.

The system's ability to iteratively probe proteins with multiple rounds of antibodies makes it useful for in-depth investigations of particular protein variants and proteoforms, allowing researchers to better assess the heterogeneity of particular proteins, which can be key to understanding how they are linked to biology or disease.

Quantum-Si likewise believes its platform will initially find a market among researchers looking to extensively profile a small number of proteins.

"Part of our launch objective is to look at between five and 50 proteins," said Patrick Schneider, the company's president and chief operating officer. "That, in our experience, is the sort of sweet spot."

Schneider said the company's ability to identify a protein's amino acid sequence as well as attached post-translational modifications make it well suited to in-depth targeted analysis of proteins and proteoforms.

The company recently released a white paper demonstrating the ability of its platform to distinguish between wild-type ß-amyloid protein and several forms containing different point mutations.

Unlike Nautilus, which analyzes whole proteins, Quantum-Si's workflow digests proteins into peptides prior to analysis, much like conventional shotgun mass spectrometry approaches. For mass spec, this digestion step has presented challenges to proteoform analysis that could prove a challenge for Quantum-Si, as well. Digesting proteins prior to analysis can make it difficult to determine what particular combinations of modifications or variations the original intact proteins featured, as multiple modifications may be spread across different peptides.

"It is an interesting challenge," Schneider said, noting that mass spectrometry faces this issue, as well.

NanoMosaic has likewise focused on more targeted measurements during the initial rollout of its Tessie platform. While the company has said the platform is, in theory, able to multiplex 94,000 analytes in a single experiment, this capability is limited by the availability of high-quality affinity reagents to targets of interest. NanoMosaic has been working to build its content library by securing antibodies and exploring the potential of aptamers as reagents, but thus far most of the interest in its platform has come from researchers looking to measure small panels of proteins, said Boyce.

NanoMosaic's platform uses what are essentially sandwich immunoassays and, unlike Nautilus or Quantum-Si's systems, it is not particularly focused on in-depth proteoform analyses. But Boyce said its customers and potential customers have been drawn in by the ability to run small panels of proteins of interest with high throughput and with wide dynamic range, which spans seven orders of magnitude, according to the company.

He said the platform's price — $49,500 for academics — and simplicity are also key selling points.

The workflow is fully automated and can be run on commonly used liquid handling platforms. Users operating in what Boyce described as "DIY" fashion can functionalize the company's chips to measure up to 20 proteins. For multiplexing beyond that, the chips must be functionalized using a spotter.

Boyce said that thus far, most customers have been maxing out at multiplexing around 12 proteins. The assay runs in a 96-well plate format, and the system can analyze a 96-well plate in 13 minutes, he said.

Erisyon, whose platform uses an approach that blends protein sequencing and mass spectrometry, also envisions targeted applications as its main focus in the near term, according to cofounder and CEO Talli Somekh. The company uses fluorescent labeling of specific amino acid residues on target peptides followed by Edman degradation of those peptides. By immobilizing the peptides on glass slides and using microscopy to measure decreases in fluorescence as the labeled amino acid residues are removed from these peptides via Edman degradation, the company researchers are able to obtain partial sequences of these molecules. They can then match these partial sequences to a reference database to make peptide and protein identifications.

Somekh cited the proteome's large dynamic range as a key challenge for any technology looking to address the space.

"When you are talking about blood having a dynamic range of something like 1012 and a single cell having something like 109, that requires a lot of technology development," he said. "So, for all us, I think we are talking about trying to enter the market with something that is looking at very specific targets, or at least being able to reduce the complexity of the sample from the perspective of dynamic range."

Somekh, who declined to give a timeline for a launch of Erisyon's platform, said the company believes its "particular differentiation comes in being able to look at things like post-translational modifications and being able to do very high-resolution, very high-fidelity identifications of things like phosphorylation."

This puts it in a similar space as Nautilus and Quantum-Si and, presumably, Encodia, whose sequencing-based approach would, in theory, likewise be well suited to looking at proteoforms and modifications — though the company has offered few public details on its efforts.

Like Quantum-Si, Erisyon's system analyzes peptides, not intact proteins.

Somekh cited neurology as an area where the kind of targeted, in-depth analysis Erisyon aims to provide could be particularly useful. The company has been active in research into Parkinson's disease. The early targets highlighted by Nautilus and Quantum-Si — tau and ß-amyloid, respectively — are also key proteins in neurology, both linked to Alzheimer's disease.

Potential for proteome scale

Nautilus, Quantum-Si, Encodia, and NanoMosaic presented at the VIB Next-Generation Protein Analysis and Detection conference in May, a forum for emerging proteomic and protein analysis technologies.

Lukas Reiter, chief technology officer at Swiss proteomics firm Biognosys, presented at the conference, as well. He said that he also took the opportunity to scout these emerging firms to assess what sort of competition they might present to his company, which offers mass spec-based proteomics services.

"I was mainly interested in the kind of applications we are doing, which is usually full-proteome, large dynamic range experiments," Reiter said. He noted that the companies did not appear focused on this kind of work, based on their VIB presentations, but added that, "of course, they have many other potentially very interesting applications like proteoforms or [analysis] of very low sample amounts."

He said that while mass spectrometry analysis of tissues and cell lines has progressed to the point where he thought it would be a difficult space for new proteomic technologies to compete in, mass spec continues to struggle with plasma and other bodily fluids, which could provide an opening for newer technologies if they are ultimately able to achieve proteome-scale analyses.

Based on publicly released data and statements, Nautilus is probably the furthest along that path. The company's ability, per Mallick, to deposit on the order of 10 billion single proteins for analysis suggests that it can reach the dynamic range required to measure proteins of samples like plasma.

Typically, the deposition of individual proteins in single wells follows the Poisson distribution, which places limits on how densely a chip can be populated while maintaining the one protein-per well distribution that enables single molecule analysis. Nautilus has developed an approach to deposit proteins that allows it to achieve super-Poisson distribution, with greater than 98 percent of its chips' wells occupied and just 1 percent of those wells containing more than one protein.

Quantum-Si's current chips feature 2 million wells, with the Poisson distribution dictating that roughly 30 percent of them would be occupied if you deposited target molecules such that there is only one per well, Schneider said. Quantum-Si also faces a somewhat greater dynamic range challenge than Nautilus due to the fact that it analyzes peptides as opposed to intact proteins.

Schneider said the company's aspiration at launch is to have the system, which will sell for around $50,000, capable of making 200,000 peptide reads per experiment, though he said the company expected that its semiconductor chip-based technology would allow it to scale rapidly.

Nautilus, meanwhile, has said it aims to measure 2,500 proteins per run in early 2022, a target that it missed. It also said it aims to up that to 10,000 proteins per run by late 2022, and to analyze the full proteome by the middle of 2023, though it is unclear whether it is on schedule to hit those milestones, and CEO Sujal Patel said in May that it would not be providing new timelines for meeting those goals. Development of the necessary affinity reagents is one of the major limitations Nautilus faces in terms of doing proteome-scale experiments. When it launches, its system is expected to sell for around $1 million.

Affinity reagents are also a major factor keeping NanoMosaic from proteome-scale experiments, Boyce said.

"Generally, with antibody capture you need paired antibodies that work together, and antibody companies only have so many pairs that work well together," he said. He added that the company hopes to expand its library by combining antibodies and aptamers.