NEW YORK – Several proteomics firms have recently highlighted new mass spectrometry-based offerings that they say will significantly add to the number of proteins quantified in a typical plasma proteomic experiment.
The moves indicate that proteomic technologies are making substantial progress in plasma analysis, an area that has long been among the most challenging in the field.
This month, Swiss proteomics firm Biognosys said that it expects by the end of the year to begin offering a new discovery proteomics workflow that will allow it to quantify around 2,700 proteins in a typical plasma study, and that it expects to manage around 3,300 proteins in large-scale discovery studies by the end of 2022.
Also this month, Qing Wang, CEO of Baltimore, Maryland-based multi-omics company Complete Omics, said that the firm planned by the end of the year to launch a targeted mass spec assay that will quantify 4,550 proteins in plasma.
And at the US Human Proteome Organization's annual meeting this month, researchers from Bruker and proteomics firm Seer showed that a workflow combining Seer's Proteograph system with Bruker's timsTOF Pro mass spectrometer was able to quantify more than 1,700 proteins in plasma. That followed a study published by Seer last summer in Nature Communications in which the company used its Proteograph system to identify roughly 2,000 proteins in an analysis of 141 plasma samples.
Existing mass spec-based plasma protein assays typically measure somewhere in the range of 300 to 500 proteins in undepleted plasma and between 500 and 1,000 proteins in depleted plasma, meaning the Seer assay and the proposed Biognosys and Complete Omics workflows mark a significant jump in the depth of plasma proteomic analyses.
In the case of Complete Omics, the company will achieve this depth by using extensive sample fractionation, which will set it apart from most recent plasma proteomics efforts where throughput has become a major priority. According to Wang, running the complete assay will take around 10 hours per sample, which makes it poorly suited to the sort of large-scale experiments many researchers are interested in pursuing. Wang said he expected that for most projects the company would run a more targeted subset of the panel determined by the specific clinical questions they were trying to answer.
At Biognosys, the company's deep plasma proteomic workflow will be compatible with large-scale experiments as they will be capable of analyzing hundreds of samples in "a few weeks," said Lukas Reiter, Biognosys' chief technology officer.
Reiter said the improvements in depth were due to refinements across all portions of the mass spec sample prep and analysis process that had expanded the dynamic range covered by such experiments. This expansion of dynamic range has allowed the company to move into an abundance range where many more proteins are present.
"If you are in an abundance range were there are simply a lot of proteins, then any increase in your dynamic range will have a big effect on the amount of proteins you gain," he said.
Reiter noted that the field previously saw a similar phenomenon with experiments in cell lines.
"There was a time in the past when increasing dynamic range led to huge gains in the number of proteins [identified in cell lines]," he said, adding that the field was now on the cusp of a similar development in plasma.
Reiter said that when Biognosys started offering plasma proteomic assays it was quantifying proteins across a dynamic range of four to five orders of magnitude. Its new assay will measure across a dynamic range of six to seven orders of magnitude, he said.
He attributed the advance to a number of technological improvements, including advances in protein depletion workflows as well as liquid chromatography and the mass spec systems themselves.
"There have been big steps in chromatography over the last 10 years, and there are more coming," he said. "And then mass spectrometers have become much faster, which essentially means increasing your dynamic range."
The additional dimensions of separation provided by ion mobility systems like Bruker's trapped ion mobility (TIMS) and Thermo Fisher Scientific's FAIMS have also contributed to the improved depth of coverage, Reiter said.
"The major contributor here is the fact that all of these things can be combined and they all add up to an increase in dynamic range such that you are coming into a range where there are just more proteins around," he said.
Addressing the dynamic range challenges involved in analyzing the plasma proteome is also at the heart of Seer's Proteograph platform. The Redwood City, California-based company uses nanoparticle-based enrichment of proteins in samples like human plasma to enable deeper coverage in proteomic discovery experiments. The platform is based on the observation that when incubated in a biological sample, nanoparticles collect proteins, which form a "corona." This enables nanoparticles to serve as an enrichment tool, allowing researchers to pull proteins out of a sample, which they can then identify and quantify using technologies like mass spec or other detectors.
The company currently offers a panel of five nanoparticles with which it and its collaborators have quantified in the range of 1,500 to 2,000 proteins in plasma experiments.
The lab of Mark Flory, a researcher at the Oregon Health and Science University's Knight Cancer Institute, which is one of the first early-access sites working with Seer's technology, installed the Proteograph system at the end of 2020 and has been doing pilot experiments with the platform in order to determine its effectiveness before using it in large sample cohorts held by external collaborators.
Thus far, Flory, who was a co-author on the Bruker and Seer poster at US HUPO, said he has been impressed with the results.
"We did some initial comparison studies comparing it to traditional methods that have been used for discovery in plasma using fractionation and/or depletion, and Seer really outperformed those," he said. "It did better and with less labor, less time for preparation, and less time for data acquisition."
The system has also shown good reproducibility, Flory said, noting that this was a major concern of his initially and likely a major concern of others in the field.
"We were somewhat skeptical," he said. "We've seen a lot of platforms come through the proteomics field, but this one actually worked as advertised."
Flory said that based on his experience with the system so far, he anticipates using it for all the plasma samples his lab runs.
"There's just really no other alternative that allows you to do a scaled study for discovery or even validation of proteins in the mixtures easily," he said.
Like many researchers doing plasma proteomics work, Flory is keen to avoid protein depletion steps. While depletion improves depth of coverage by removing the most high-abundance proteins from a sample, it can be time-consuming, expensive, and cause issues with reproducibility.
"One thing we have always been concerned about is that as you deplete high-abundance proteins you may non-specifically deplete some of the [proteins] you are actually going after," he said. "There's not 100 percent specificity with those depletion methods, so that is something we have really shied away from, even though it does help" depth of coverage.
Reiter said, though, that Biognosys found depletion useful, noting that protocols and reproducibility and efficiency have improved.
Jochen Schwenk, director of translational plasma profiling at the Science for Life Laboratory at Sweden's Royal Institute of Technology, said that he believed announcements like that from Biognosys were not unexpected given the progress that has been made in plasma proteomics in recent years, though he noted that "the real benefit will come once we are able to routinely detect all of these [proteins] in all samples."
Philipp Geyer, chief scientific officer and co-founder of German plasma proteomics firm OmicEra Diagnostics, similarly noted that the numbers advertised by Biognosys reflected not the total number of proteins the company expected to quantify per sample but, rather, the number it expected to quantify over the course of an entire study.
"If you are going to do a complete study where you measure hundreds of samples or even thousands of samples, then of course you will find in one sample a protein that you haven't seen before in another sample," he said. "That is what we usually see, that if you go to larger and larger studies, you find more and more proteins."
He added that natural variation between samples could also add to the total number of proteins quantified in a study.
In the study published by Seer scientists this summer in Nature Communications, the researchers found in their analysis of 141 plasma samples that of the more than 2,000 proteins identified, 1,992 were quantified in at least 25 percent of all samples, suggesting that the per-sample number was somewhat lower than that.
Geyer said that in a typical plasma protein study, researchers might expect to quantify more than 1,000 proteins across all the samples measured in the study. Given that, the 2,700 proteins per study Biognosys aims to hit by the end of the year would still be a substantial advance.
Geyer who led several large-scale plasma proteomics experiments while a researcher in the lab of Max Planck Institute of Biochemistry researcher Matthias Mann, said that while he believed that "sooner or later" improved plasma proteomic coverage "will happen for sure," he was less optimistic that the field was currently on the cusp of seeing a significant increase in depth of coverage.
He said that his impression, based on his reading of the field, was that capabilities were still in the range of around 300 to 500 proteins per sample in undepleted plasma and somewhat more than that in depleted plasma.
That said, a jump in profiling depth "would be very nice to see," he said.