NEW YORK (GenomeWeb) – A team led by Northwestern University researcher Neil Kelleher has developed a workflow for label-free quantitation in top-down proteomics.
Detailed in a May paper in Analytical Chemistry, the method enables reliable quantitation of thousands of proteoforms, allowing researchers to use top-down proteomics to compare changes in protein expression across different conditions.
The approach marks a key development in applying top-down proteomics to biomarker discovery. Kelleher's lab, in fact, is currently using the method in collaboration with surgeons at Northwestern University Medical Center to investigate protein biomarkers related to transplant patients, Ioanna Ntai, a researcher in Kelleher's lab and first author on the study, told ProteoMonitor.
She declined to go into detail, but said that the paper had "laid out some groundwork [around top-down proteomics] to use in clinical biomarker discovery" and that the lab was currently pursuing such efforts.
Bottom-up, peptide-based proteomics has traditionally dominated the field, especially for large-scale quantitation of proteomes and protein biomarker discovery. Interest in top-down methods has grown, though, as improvements in methods and instrumentation have made analysis of intact proteins easier and researchers have become increasingly aware of the potential importance of protein isoforms and post-translational modifications.
Kelleher's lab has been one of the primary leaders of this charge. The lab was the first to demonstrate truly high-throughput, top-down proteomics, identifying more than 1,000 unique proteins and 3,000 proteoforms in a 2011 Nature paper. In a 2013 paper in Molecular & Cellular Proteomics, the lab published the largest top-down proteomics study of a human cell line to date, identifying 1,220 proteins and more than 5,000 proteoforms in H1299 cells.
As the authors noted in their current paper, groups including theirs have done top-down quantitation using metabolic labeling, but, because human clinical samples aren't amenable to such labeling, label-free approaches are desirable for biomarker discovery.
Some researchers have done limited label-free experiments, Ntai said, but these were "in smaller, less complex proteomes where there were only a few proteoforms present and there wasn't as much technical variation."
In the Analytical Chemistry study, she and her colleagues investigated two strains of the yeast Saccharomyces cerevisiae, one wildtype and the other the mutant rpd3Δ::KANMX which has a deletion of the rpd3 gene. Using their workflow, they were able to measure 838 proteoforms, and they were able to detect statistically significant differences between the two strains for 120 of them.
Ntai noted that since the yeast research, the team has turned the approach to more complicated proteomes, including those of human peripheral blood mononuclear cells.
The researchers used GELFREE separation upfront of nanoLC linked to a Thermo Fisher Scientific Orbitrap Elite instrument. Using data gathered from the instrument's MS1 scan, they were able to distinguish individual masses, which they termed Quantitation Mass Targets, or QMTs, and determine whether these masses were changing between the two samples being compared. They then used the MS2 scan to identify and characterize the individual proteoforms, which can then be linked to the quantitative QMT data obtained in MS1.
In terms of reproducibility, the technique achieves coefficients of variation equivalent to those in bottom-up, label-free quantitation experiments, Kelleher told ProteoMonitor.
One key to achieving this level of reproducibility has been improving chromatography, Ntai said.
"Chromatography was one of the big issues with top-down mass spectrometry, and especially as you get to larger proteins the chromatographic peaks were really wide," she said. "But now we have vastly improved the chromatography. It's getting very reproducible, even with biological replicates."
She noted that she and her colleagues expect to see increased variability when they move to actual clinical samples from different patients, but that "when it comes to cell lines in the lab, it is very reproducible."
One limitation of the Analytical Chemistry study, Ntai said, is that it focused only on proteins 30 kD and smaller. "There are more challenges with [higher] molecular weights with the chromatography and detection of the proteins," she said.
However, Ntai said, in more recent work the researchers have expanded the range they can analyze effectively and can now "easily go up to 60 kD." The researchers have upped the mass range, Kelleher noted, using the mass spec's "short transient mode," a method that uses an abbreviated scan to avoid signal decay associated with the increased collisional cross-section of higher mass ions.
Another area where the researchers are looking to improve the workflow is reducing the amount of sample required for their analyses. Currently, they need around 50 micrograms of protein per biological replicate, which limits the sort of clinical samples they are able to work with.
Indeed, as Pacific Northwest National Laboratory scientist Ljiljana Pasa-Tolic, a leading top-down researcher, told ProteoMonitor in a 2013 interview, sample size is an issue for top-down proteomics more generally.
"I think the main issue is that if you look at the amount of material that is needed to go through this particular pipeline to pull out this many [proteoform] IDs, it is not nearly as sensitive as bottom-up is at this point," she said, referring to the Kelleher lab's 2013 MCP paper.
The Northwestern researchers are also looking into using newer mass spec instrumentation for their top-down approach. They currently use the Orbitrap Elite, but, Ntai said, they are also looking into implementing the workflow on Thermo Fisher's Q Exactive and Orbitrap Fusion instruments.
Kelleher said that he was particularly interested in the Fusion as that instrument's ion trap provided good quantitative data while its Orbitrap would allow researchers to capture even more high-resolution MS2 data.