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Domon Lab Exploring Enrichment of His-peptides to Improve Targeted Protein Quantitation


NEW YORK (GenomeWeb) – A team led by Luxembourg Clinical Proteomics Center head Bruno Domon has developed a targeted proteomics workflow using upfront enrichment of histidine-containing peptides.

Detailed in a study last month in the Journal of Proteome Research, the method offers a simple, inexpensive approach for decreasing proteome complexity and reducing interferences and could serve as an alternative to techniques like HSA/IgG depletion, Domon told ProteoMonitor.

Reducing proteome complexity is a common goal in proteomic work as it allows for researchers to delve more deeply into low abundance analytes and, in the case of targeted experiments, reduce interferences that can hinder peptide quantitation.

The approach presented by the Luxembourg researchers takes advantage of the fact that histidine is a relatively rare amino acid. Given this, a strategy in which only histidine-containing peptides are selected for mass spec analysis can reduce the complexity of a sample's proteome by roughly four-fold.

Domon and his team enriched their samples for histidine-containing peptides using immobilized metal-ion affinity chromatography (IMAC) loaded with copper ions, finding that this approach provided high specificity and good recovery. The technique, Domon said, has been described in previous studies, but, he said, it has not been broadly used to date.

"People tend to just use what is described," he said "There are a few methods that are routinely used and people tend to stick to those."

But, he added, "We all know in the community there is a lot of need for improvement. So, what we have done in this study is take it and work out the details so that it can be used in a standardized, routine setup."

In the JPR study, the researchers tested the technique via selected-reaction monitoring analysis off a set of 108 stable isotope-labeled peptides, 76 of which contained histidine and 32 of which did not. None of the 32 without histidine were recovered, demonstrating the good selectivity of the method, while 72 of the 76 with histidine were detected.

They also tested the method's reproducibility by adding a 61 histidine peptide mixture into four human plasma samples, finding that for 56 of the 61 peptides, CVs were below 20 percent.

To test the approach's usefulness for improving targeted mass spec analysis, the researchers measured a set of 238 endogenous histidine-containing peptides in plasma digests and compared them to measurements of corresponding SIL peptides not spiked into plasma, which served as proxies for background noise.

Comparing measurements of the peptides in samples that had and had not undergone the IMAC-cu enrichment, Domon and his team found that of the 952 transitions they measured, 74 percent showed an improvement in signal-to-noise after enrichment, and 321 showed a more than five-fold improvement.

The method does not work well with peptides containing a single histidine near the N-terminus, Domon said, noting that such peptides tended to form very strong bonds with the IMAC-Cu material and were therefore difficult to recover.

"That is a general feature that we can predict to a large extent," he said.

Another potential issue is the extent to which using only histidine-containing peptides limits the proteotypic peptides available for identification or quantitation of a protein.

"Anytime you start to segment [a proteome] you are going to compromise," Domon said. "You get fewer peptides per protein, so there is a tradeoff, but it still gives you a reasonably good representation of your proteome."

In the JPR paper, the researchers found using in silico trypsin digestion of yeast and human proteomes, that more than 90 percent of these proteomes remained accessible. And, Domon noted, while in discovery workflows it could be difficult to assess exactly what proteins the method might miss, in the case of targeted experiments researchers can in advance determine in silico whether their targets are amenable to such an analysis.

He suggested the approach could serve as a simple, less expensive alternative to plasma depletion columns, which use antibodies to strip samples of the highest abundance proteins prior to mass spec analysis. Estimating a per-sample cost of "a couple of dollars," Domon said the IMAC-Cu method was at least an order of magnitude less expensive than depletion columns.

Another benefit, he said, particularly for targeted clinical work, is that unlike depletion columns, which are typically used many times for many samples, the IMAC-Cu method uses a new column for each sample.

While the approach could be used for discovery proteomics, Domon said that his focus is primarily on targeted assays where the method helps both by reducing interferences and by eliminating ion suppression.

"Low abundance [analytes] are always challenging not only because of interferences but also because of competitive ionization, so this is one of the main drivers," he said.

The workflow's simplicity also makes it well suited to targeted work, Domon said, noting that high-throughput is typically desirable in such experiments because researchers are often running dozens or hundreds of samples.

"Especially if you want to do it in the context of clinical studies," he said. "Anything that is simple, reproducible, and high recovery fits the criteria [required] of a clinical assay."

The technique does not provide sensitivity comparable to antibody-based enrichment methods like SISCAPA, Domon said, but he noted, it could be complementary to such approaches.

With SISCAPA, "unless it is one of the assays that is commercially available, you cannot access it very quickly – you have to design your experiment," he said. The IMAC-Cu method "is more for the front end of the biomarker pipeline. If it is the final assay where you want to just measure one or two proteins, I would not claim this approach is the best way to go."