This is an Application Brief and does not contain a detailed Experimental section.
This application note demonstrates advanced multi-protease peptide mapping workflows, now enabled with the automated data analysis capabilities of the BiopharmaLynx Application Manager, version 1.3, for MassLynx Software.
Enabling advanced multi-protease peptide mapping workflows, with the automated data analysis capabilities of the BiopharmaLynx Application Manager, version 1.3, for MassLynx Software.
The recent availability of high-quality proteolytic digestion enzymes, in addition to trypsin, has facilitated a new generation of biotherapeutic peptide map analyses that can be performed with much greater flexibility.
In particular, multiple protease digestion workflows have enabled greater selectivity for peptide chromatographic retention, MS response, and peptide fragmentation pathways, while simplifying the task of achieving comprehensive sequence and fragmentation coverage for a given biotherapeutic. This technical brief will describe the employment of such workflows, and how they can yield greater biotherapeutic knowledge, often with less analytical development effort.
The most recent release of BiopharmaLynx, version 1.3, features additional flexibility for automating data analysis from higher complexity multi-enzyme peptide map experiments. BiopharmaLynx supports maps generated with the common proteolytic digest reagents (Table 1), and also provides scientists the flexibility to define additional custom digest reagents. BiopharmaLynx 1.3 now extends bioinformatic support for peptide mapping to analyses where multiple digestion enzymes are utilized.
Two multi-digest workflows are supported within the peptide mapping method editor (Figure 1): the combined workflow (or “one pot” digest), where multi-protease digestion is carried out in the same sample vial; and the separate workflow (or “or multi-pot” digest), where individual enzyme digests are prepared, quenched, and then mixed prior to LC-MS analysis.
Figure 2 illustrates the digest specificity on a theoretical protein from individual digestion with GluC and LysC. Individually, they each produce three digested peptides, including one very large peptide. T he products of the separate multi-enzymatic workflow represent the concatenated list from the individual digests, while the products of the combined multi-enzymatic workflow constitute a unique set of digested peptides, where the large peptides have been further digested by the additional protease.
The following sections will detail the practical utility of these new workflows for biotherapeutic peptide mapping analysis.
The combined workflow generates a set of peptides resulting from the combined specificities of all proteases used in the digestion process. Identified peptides are labeled using multi-letter peptide digest labels derived from the single enzyme digest designators (e.g., DT represents the combined product of AspN(D) and Trypsin (T)).
There are three common reasons to utilize the combined digest multi-enzyme workflow:
The separate workflow assumes that multiple independent digests were produced and that the enzymes were inactivated before the digests were mixed for analysis. BiopharmaLynx searches peptide mapping results for peptides predicted using the digest specificities of each enzyme. Identified peptides are labeled using the single-letter peptide digest nomenclature common to single enzyme digests (e.g., T for Trypsin; K for LysC; D for AspN)
There are three common reasons to utilize the separate digest multi-enzyme workflow:
The new separate digest workflow functionality can also be employed to compare maps prepared with two different enzymes. As this workflow generates concatenated lists of both enzyme digest products, searches against both data sets would return accurate identifications.
Human Serum Albumin (HSA) was individually digested with GluC and LysC, and high quality UPLC-MSE maps were generated for both digests. The annotated Total Ion Chromatogram (TIC) traces for both runs (Figure 3) show peptide identifications for fully digested products in both digests.
Without any optimization, it was shown (Figure 4) that 85% coverage was obtained with GluC, 92% coverage with LysC, and 100% sequence coverage from the combined results of both analyses. The absence of “common” coverage reflects the lack of identical peptide fragments generated from both enzyme digests, and the excellent specificity of accurate mass for biotherapeutic peptide mapping studies. From such studies, useful combinations of enzymes can be readily identified to assist in answering global or targeted questions about a biotherapeutic protein.
720004158, November 2011