Bottom-Up Analysis of Proteins by Peptide Mass Fingerprinting with tCITP-CZE-ESI-TOF MS After Tryptic Digest.

The identification of proteins in samples of moderate to complex composition is primarily done by bottom-up approaches. Therefore, proteins are enzymatically digested, mostly by trypsin, and the resulting peptides are then separated prior to their transfer to a mass spectrometer. The following protocol portrays a bottom-up method, which was optimized for the application of CZE-ESI-TOF MS. Protein denaturation is achieved by addition of 2,2,2-trifluoroethanol (TFE) and heat treatment. Afterwards, disulfide bonds are reduced with tris-(2-carboxyethyl)phosphine (TCEP) and subsequently alkylated with iodoacetamide (IAA). The tryptic digest is performed in an ammonium bicarbonate buffer at pH 8.0. The digested protein sample is then concentrated in-capillary by transient capillary isotachophoresis (tCITP) with subsequent CZE separation of tryptic peptides in an acidic background electrolyte. Hyphenation to a time-of-flight (TOF) mass spectrometer is carried out by a triple-tube coaxial sheath flow interface, which uses electrospray ionization (ESI). Peptide identification is done by peptide mass fingerprinting (PMF). The protocol is outlined exemplarily for a model protein, i.e., bovine ß-lactoglobulin A.

At-line quantitative profiling of monoclonal antibody products during bioprocessing using HPLC-MS.

(1) Background: The N-glycosylation profile as well as the subunit assembly of monoclonal antibodies (mAbs) are strongly dependent on manufacturing conditions and thus need to be monitored during the bioprocess. Commonly, mAbs are characterized downstream of the fermentation process applying different analytical techniques like released glycan analysis, peptide mapping, or subunit profiling. However, these procedures are time-consuming and difficult to perform in real-time. (2) Methods: We applied a simple HPLC-MS workflow with minimal sample preparation to characterize mAb product quality at the intact protein level at different time points during fermentation. After harvest, the cell culture medium was centrifuged briefly. The supernatant containing the fermentation product was diluted and immediately subjected to HPLC-MS analysis. (3) Results: Besides the product of interest (mAb), the fermentation broth contained misassembled variants, mostly light chain and light chain dimer. The mAb's glycosylation profile changed over time showing an increase in galactosylated variants with G0F/G1F being the most abundant glycoform at all time points of fermentation. Furthermore, expressed protein species were relatively and absolutely quantified. The workflow was very robust despite analyzing a highly complex matrix. Relative standard deviations for retention times were below 0.5% for both intra and inter-day comparison, whereas relative procedural standard deviations for quantification of the different protein species ranged between 7 and 13%. (4) Conclusions: This approach allows for reliable analysis of product profiles of monoclonal antibody species including misassembled subunits and glycosylation variants directly from fermentation broth using a fast and robust HPLC-MS workflow.

Exploring sample preparation and data evaluation strategies for enhanced identification of host cell proteins in drug products of therapeutic antibodies and Fc-fusion proteins.

Manufacturing of biopharmaceuticals involves recombinant protein expression in host cells followed by extensive purification of the target protein. Yet, host cell proteins (HCPs) may persist in the final drug product, potentially reducing its quality with respect to safety and efficacy. Consequently, residual HCPs are closely monitored during downstream processing by techniques such as enzyme-linked immunosorbent assay (ELISA) or high-performance liquid chromatography combined with tandem mass spectrometry (HPLC-MS/MS). The latter is especially attractive as it provides information with respect to protein identities. Although the applied HPLC-MS/MS methodologies are frequently optimized with respect to HCP identification, acquired data is typically analyzed using standard settings. Here, we describe an improved strategy for evaluating HPLC-MS/MS data of HCP-derived peptides, involving probabilistic protein inference and peptide detection in the absence of fragment ion spectra. This data analysis workflow was applied to data obtained for drug products of various biotherapeutics upon protein A affinity depletion. The presented data evaluation strategy enabled in-depth comparative analysis of the HCP repertoires identified in drug products of the monoclonal antibodies rituximab and bevacizumab, as well as the fusion protein etanercept. In contrast to commonly applied ELISA strategies, the here presented workflow is process-independent and may be implemented into existing HPLC-MS/MS setups for drug product characterization and process development. Graphical abstract.