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Acoustic Ejection Mass Spec Enables Targeted Protein Quant at Rate of 2K Samples Per Hour


NEW YORK – A team led by researchers at Cedars-Sinai Medical Center has developed a protein quantitation workflow capable of analyzing tens of thousands of samples per day.

Detailed in a paper published this month in Nature Communications, the workflow uses immunoenrichment of target peptides combined with acoustic ejection mass spectrometry to enable extremely high-throughput protein measurements.

In the study, the researchers measured 10 protein markers linked to acute phase response to SARS-CoV-2 infection in 267 plasma samples and the SARS-CoV-2 nucleocapsid (NCAP) protein in 145 nasopharyngeal swabs, reaching a measurement speed of 1.5 seconds per peptide per sample. In a separate analysis using the system to measure the SARS-CoV-2 NCAP protein, the researchers analyzed 11,490 samples in roughly five hours.

That level of throughput could open up new applications for targeted mass spectrometry, suggested Jennifer Van Eyk, professor of medicine and biomedical sciences at Cedars-Sinai and senior author on the study, citing as an example the approach's potential for large-scale epidemiological studies.

The workflow uses Sciex's Echo MS platform, which uses acoustical liquid handling to inject as many as three samples per second into a mass spectrometer. The researchers coupled the system to a Sciex QTRAP 6500+ mass spec instrument. They used the stable isotope standards and capture by anti-peptide antibodies (SISCAPA) immunoenrichment technology from SISCAPA Assay Technologies to purify the target peptides prior to their introduction into the mass spec.

Sciex launched the Echo MS in 2020. While the system has primarily been marketed for small molecule work, the company has been working both internally and in collaboration with Van Eyk's lab to develop workflows using it for targeted peptide and protein quantitation. At the US HUPO meeting, the company presented proof-of-principle data showing that the system could analyze peptides with extremely high throughput when combined with upfront SISCAPA enrichment. The Nature Communications study is the first peer-reviewed work demonstrating the feasibility of such an approach.

Van Eyk said adapting the system to protein measurements required a substantial amount of development work to determine the optimal conditions both for sample preparation and operation of the Echo system. While she and her colleagues were able to build somewhat on previous work using the system for measuring metabolites, "metabolites and peptides are truly two different worlds."

A key question, said Leigh Anderson, CEO of SISCAPA Assay Technologies and a coauthor on the Nature Communications paper, was whether the sample droplets generated by the Echo MS would be large and uniform enough to allow for highly reproducible quantitative assays.

"You're injecting these little droplets … and so you're getting these little bumps of signal, not a sort of smooth peak like you would get out of an LC system," he said. "The question was, can you make enough measurements in those little pulses to get good precise measurements."

The assays to the 10 acute phase response proteins had coefficients of variation (CVs) of between 4.2 percent and 10.5 percent, indicating good reproducibility. CVs for the run of 10,000 NCAP samples were under 10 percent.

Van Eyk noted that one advantage of the workflow's speed is that it mitigates concerns about system stability and batch effects.

"You're not spending days, weeks, months running these samples," she said. "That's another lovely aspect of it. All those post-analytic concerns go away."

Anderson added that the throughput of the system might also allow users to improve CVs simply by running many replicates of the same sample. "You can get a purely statistical improvement in precision just by doing the same measurement over and over and over again," he said.

Morteza Razavi, CEO of SISCAPA's Canadian subsidiary and a coauthor on the study, said the ability to reliably quantify proteins using SISCAPA and the Echo MS in place of traditional separation techniques helps move the company closer to its goal of streamlining protein mass spec for clinical use.

Key to this streamlining, he said, are approaches that eliminate upfront liquid chromatography, which is one of the most complex and time-consuming portions of traditional protein mass spec workflows. The goal "is that we can have an automated workflow upfront of mass spectrometry that would simplify the sample to an extent that you don't need big, complicated LC systems in the clinic," he said.

Use of the system for clinical applications is likely a longer-term prospect and one that could potentially be complicated by the US Food and Drug Administration's recently issued rule on laboratory-developed tests.

Nearer term, Anderson and Razavi said they hope to use the approach to read out longitudinal sampling studies that SISCAPA has been conducting internally for years.

"We are sitting on a really large collection of dried blood spot samples from the longitudinal samples that we have been doing," Anderson said. "It would be nice to be able to run those all in a short period of time."

He said that from SISCAPA's perspective, the Nature Communications study was in part an evaluation of whether it would be feasible to use the platform and workflow for such a purpose.

Van Eyk cited population-scale analyses as a potential application of the workflow, particularly for proteins that are difficult to target using the immunoassays and immunoassay platforms currently employed for such work.

"Say you want to run the UK Biobank [cohort]," she said. "You need to run 500,000 samples. We did 10,000 samples in under five hours. We have a targeted ability when you want to run large epidemiological studies to get at biology that can't be done necessarily with traditional technologies like immunoassay platforms."

Van Eyk said that Sciex is planning to couple the Echo MS to its flagship ZenoTOF 7600 mass spec, which could further improve the power and performance of the approach.