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Single-Cell Proteomics Benefits From New Instrumentation, Workflows

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NEW YORK – Single-cell proteomics has seen significant developments in recent weeks, with two BioRxiv preprints from independent groups presenting new methods for such analyses.

In an effort led by researchers at the Max Planck Institute of Biochemistry, scientists used a modified Bruker timsTOF Pro instrument to perform label-free single-cell proteomics, analyzing 420 cells and quantifying up to 1,209 proteins per cell.

In separate work, a team led by researchers at Northeastern University developed a refined version of their Single-Cell Proteomics by Mass Spectrometry (SCOPE-MS) approach, which was one of the first methods to enable proteomic measurements at the single-cell level. The researchers used the method, called SCOPE2, to quantify more than 3,000 proteins in 1,490 single cells, with around 900 to 1,000 protein quantified per cell.

The Max Planck team's effort "is a really nice demonstration of a label-free [single-cell] approach," said Christopher Rose, a senior scientist at Genentech.

Rose, who was not involved with either study, noted that the greater simplicity of the label-free approach presented by the Max Planck researchers was likely to draw attention. To date, most single-cell proteomics work has employed methods like SCOPE-MS, which uses isobaric labeling to boost mass spec sensitivity enough to measure large number of proteins at the single-cell level.

In such experiments, researchers label peptides from both the single-cell sample of interest and another, larger sample source (such as dozens or hundreds of cells of equivalent type) termed the "carrier proteome." By including the carrier proteome sample, they are able to ensure that even analytes present only at low abundance in the single-cell samples are present in relatively high abundance in the overall sample, making them more likely to be fragmented and detected by the mass spec.

Isobaric labeling adds another layer of complexity to the workflow, however, and, as Rose and colleagues showed in a recent Nature Methods paper, researchers need to be careful not to use too much proteome carrier in their experiments or else quantitative accuracy will suffer.

A number of optimizations were required to enable the label-free workflow, said Andreas-David Brunner, first author on the preprint and a graduate student in the group of Max Planck researcher Matthias Mann, which developed the method.

Perhaps most notably, the researchers modified a timsTOF Pro by introducing a brighter ion source and different ion optics elements to produce an ion current that was 4.7-fold higher than that of an unmodified instrument.

They also implemented a nearly loss-less sample prep approach using 384-well plates commonly used for PCR to do cell lysis and protein digestion. This was followed by concentration of peptides in disposable Evosep Evotip stagetips that allowed them to eliminate several liquid handling steps and interface the tips directly with an Evosep LC system, which they ran at a flow rate of 100 nanoliters per minute using a 30-minute LC gradient.

For the mass spec analysis, the researchers used the diaPASEF approach that the Mann lab developed for use on the timsTOF Pro. The method takes advantage of the timsTOF Pro's trapping ion mobility spectrometry (TIMS) system, which allows the instrument to collect ions in parallel and then release them into the mass spec analyzer based on their collisional cross section. Combining this with the ability of the instrument's quadrupole to rapidly switch between different masses allows researchers to isolate a number of different precursor ions for fragmentation and analysis in a single scan.

The approach allowed the Max Planck team to boost sensitivity by making use of more of the ions being produced at any given time, Brunner said, noting that they were able to use more than 10 percent of the incoming ion beam.

"The exciting part about [the study] is that it demonstrated two different technologies that people hadn't really used before for single cell [analysis], the timTOF and the Evosep LC," Rose said.

In a company statement last week, Gary Kruppa, Bruker's VP of proteomics, said that the firm plans to provide early-access users with the modified, high-sensitivity platform used by the Mann lab in its single-cell work in the second half of 2021 and to launch it broadly in 2022.

Rose said that such an instrument is something his lab would be interested in, noting that "the sensitivity gains are really nice."

The Northeastern team used a Thermo Fisher Scientific Q Exactive in its work to optimize the original SCOPE-MS protocol. Among the keys to the effort was improving the sample prep process by using a free-heat process that relies on PCR thermocyclers and automated liquid handling to allow for a more streamlined, higher-throughput process than can be done in smaller sample volumes than the original SCOPE-MS sample prep.

Nikolai Slavov, director of the single-cell proteomics center at Northeastern and senior author on the preprint, said that he and his colleagues have developed the protocol for use on Cellink's Cellenone single-cell handling system, which he said will make it more widely accessible.

The Northeastern team also implemented new data analysis approaches: DART-ID, a tool for incorporating retention time information when making peptide IDs, and DO-MS, which Slavov said helped to ensure the mass spectrometer samples at the apex of peptide LC elution peaks, delivering more ions to the instrument for analysis and boosting sensitivity.

The Max Planck team used its workflow to compare changes in the proteome at different points in the cell cycle, finding that it could develop protein-based models for identifying which stage of the cycle a single cell was in. They also compared their single-cell proteomic data to single-cell RNA data, noting that it varied significantly more than bulk proteomic and RNA data did. This indicated, they wrote, "that single-cell protein and RNA levels are very different, re-emphasizing that protein measurements yield complementary information to RNA measurements and do not simply reiterate similar gene expression states."

Slavov and his colleagues used the SCOPE2 method to look at single monocyte and macrophage cells and the differentiation of monocytes into macrophages, observing that the former were enriched for proteins driving proliferative functions while the latter were enriched for protein involved in cell surface signaling and cell adhesion.

He said the technology is now well enough developed for experiments analyzing thousands of single cells. "I think we are ready to demonstrate the power of this technology for an increasing number of biological questions," he said, though further optimization would be helpful, especially in terms of making the methods more robust and easier to use so they can spread beyond the handful of expert labs already using them.

Brunner said he and his colleagues are working to improve the throughput of their label-free method. He also said it was realistic to think they could get their LC gradient down to the range of 11 minutes without compromising depth of coverage.

He added that his team is also developing a fully automated sample prep workflow that would further improve the process's reproducibility.

Rose said that both workflows have their pros and cons, noting that although the label-free approach benefits from its relative simplicity, it couldn't match the throughput of the carrier proteome-based approaches, which, because they use isobaric tagging, are able to multiplex 10 or more samples in a single experiment.

"For label-free, the biggest challenge is going to be throughput," he said, noting that for many of the sorts of analyses people are envisioning for single-cell proteomics, researchers will want to analyze thousands of cells. With the method the Max Planck team presented in its preprint, it could analyze 40 cells per day, though that number would increase if the researchers manage to lower their LC gradient time, as Brunner suggested.