Progenesis QI for proteomics speeds up biopharmaceutical purification!

 

Most recombinant protein biopharmaceuticals are produced in specially designed expression systems typically using CHO (Chinese Hamster Ovary) cells. Many CHO proteins are simultaneously expressed along with high amounts of the desired biopharmaceutical, but they need to be removed by multi-step purification processes. Residual host cell proteins (HCPs) are low-level (1-100 ppm) process-related impurities that might be present in protein biopharmaceuticals even after extensive purification. HCPs could produce unwanted immunogenic responses in patients, they can reduce the efficacy or the stability of the drug or they can be responsible for drug degradation. For these reasons, the regulatory agencies required that all HCPs are identified and quantified prior to drug approval. The Biopharmaceutical industry relies on ELISA (enzyme-linked immunosorbent assays) for measuring the total HCP concentration expressed in ppm (or ng HCPs/mg biopharmaceutical). Mass spectrometry-based HCP analysis has emerged in recent years as a powerful alternative to ELISA [1-4] because it provides more extensive (proteome-wide) HCP coverage and is able to measure individual HCP levels.

Any LC-MS workflow for HCP analysis has three major goals: 1) identification of unknown HCPs; 2) reporting of the individual HCP quantification results expressed in ng HCP/mg biopharmaceutical (ppm concentrations); 3) monitoring of the HCP levels across multiple biopharmaceutical preparations. To accomplish these goals, two different LC/MS assays are required as illustrated by the workflow displayed in figure 1.

Figure 1. Workflow of the HCP analysis.

Figure 1. Workflow of the HCP analysis.

 

 

 

 

 

 

 

 

 

 

 

The Discovery HCP assay is performed in SONARTM mode in order to identify the unknown HCPs present in the purified biopharmaceutical and Progenesis QI for proteomics (QIP) is used for a proteome-wide database search to reveal the identity of these HCPs. For example, in the case of the NIST mAb, four HCPs and three spiked proteins (ADH, PHO and BSA) were identified as illustrated by the screenshot displayed in figure 2:

Table showing identification of 4 HCPs

Figure 2. Four HCPs (highlighted by red arrows) were identified by Progenesis QIP in the highly-purified NIST mAb.

A different type of LC-MS assay is required when multiple samples, produced from the bioprocessing of the same protein biotherapeutic, need to be analyzed with increased sample throughput, for the purpose of investigating HCP clearance. In this situation, the information gained from the HCP Discovery assay can be used to speed up the HCP identification and quantification process.

Using Progenesis QIP, the MS/MS fragmentation spectra of HCP peptides identified by SONAR acquisition can be assembled into spectral libraries, containing peptide precursors, charge states, retention times and relevant fragment ions. A list of HCP peptides sequenced from the NIST mAb is presented in Figure 3.

Table showing HCP peptides identified with a combination of NIST and SONAR

Figure 3. HCP peptides identified in the NIST mAb using SONAR acquisition.

 

 

 

 

 

 

 

 

 

 

 

The MS/MS fragmentation spectra of these peptides were assembled in a spectral library using Progenesis QIP. Peptides are sorted in the increasing order of their precursors. Two MS/MS spectra were recorded for four highlighted peptides, following fragmentation of their doubly and triply charged precursors.

Higher–throughput HCP Monitoring assays relying on 30 min peptide separations and employing MSE data acquisition are used for screening biopharmaceutical samples taken at every step of the purification process. The entire LC/MSE dataset is searched with Progenesis QIP against a spectral library for HCP identification, quantification, and monitoring.

To simulate an HCP monitoring assay, three protein digests standards (ADH–yeast alcohol dehydrogenase, BSA-bovine serum albumin and PHO-rabbit phosphorylase b) were spiked at four different concentration levels in four NIST mAb digests, while one protein digest (CLP_B-Ecoli chaperone protein) was spiked at the same concentration in all 4 samples. The LC/MSE data was searched in Progenesis QIP against a spectral library of 113 SONARTM fragmentation spectra of MIX-4 peptides (ADH, BSA, CLB-B, and PHO). Spiked proteins were easily tracked down to the lowest spiked levels (~ 20 ppm) across all five samples (20 LC/MSE runs) as exemplified by the graphs shown in Figure 4.

Graph showing measurement of spiked samples

Figure 4. (A) Example of protein level results obtained for the HCP Monitoring assay: the levels of spiked ADH were accurately measured in five NIST mAb samples; (B) Peptide level results of the HCP monitoring assay.

Eleven ADH peptides showed identical trends plots across all 20 runs. Four spiked samples, identified by letters A-D in this figure, containing different levels of ADH, BSA, PHO and CLP-B protein digests were spiked in the NIST mAb digest. The sample labeled “Blk” corresponded to the non-spiked NIST mAb digest. Each sample was analyzed with four replicates.

Protein measurements were obtained from multiple peptides and excellent correlation was obtained between the spiked and measured fold changes with RSDs under 10% for all measurements.

Progenesis QIP greatly simplifies the user interaction with HCP datasets. Extracting mass chromatograms and calculating peak areas for a multitude of peptide precursors (like the 113 peptides from the MIX-4 spectral library) can be a tedious process. In addition, the data from each individual sample replicates need to be compared in order to obtain the peptide level HCP trends. Finally, the HCP peptide level results need to be translated into HCP protein levels. All these steps are automated and they are performed rapidly in Progenesis QIP without significant user intervention. This saves a significant amount of time spent on data analysis, allowing for rapid results.

The experiment with spiked protein digests described above can be easily performed as a QC test to demonstrate the capability of the entire LC/MS platform to provide reliable HCP clearance results in a timely fashion.

Our collaborators from EMD Millipore asked us to test this capability for “real” mAb samples: they wanted to know which one of their four SCX (strong cation exchange) purification protocols produced “cleaner” purifications, with lower HCP content. The results are shown in Figure 5 and one of their protocols indeed worked better than the other three.

Graph showing monitoring of HCP peptides

Figure 5. Peptide level monitoring of three HCP peptides across five mAb preparations (one Protein A eluate and 4 SCX (strong cation exchange) chromatographic purifications using four different protocols (A-D). As illustrated here, Protocol D provided the best results.

Progenesis QIP allows purification laboratories to develop and test novel purification procedures in a relatively short time.

References:

  1. Doneanu CE, Anderson M, Williams BJ, Lauber MA, Chakraborty A, Chen W. Enhanced Detection of Low-Abundance Host-Cell Protein Impurities in High-Purity Monoclonal Antibodies Down to 1 ppm Using Ion Mobility Mass Spectrometry Coupled with Multidimensional Liquid Chromatography, Anal Chem, 2015, 87, 10283-10291.
  2. Huang L, Wang N, Mitchell CE, Brownlee T, Maple SR, De Felippis MR. A Novel Sample Preparation for Shotgun Proteomics Characterization of HCPs in Antibodies, Anal Chem, 2017, 89, 5436-5444.
  3. Weibin C, Doneanu CE, Lauber MA, Koza S, Prakash K, Stapels M, Fountain KJ. Improved Identification and Quantification of Host Cell Proteins (HCPs) in Biotherapeutics Using Liquid Chromatography-Mass Spectrometry, book chapter in Technologies for Therapeutic Monoclonal antibody characterization, Vol 3, ACS Symposium Series, 2015, 357-393.
  4. Doneanu C, Lennon S, Anderson M, Reah I, Ross M, Anderson S, Morns I, Yu YQ, Chakraborty A, Denbigh L, Chen W. A Comprehensive Approach for HCP Identification, Quantification and Monitoring Based on a Single Dimension (1D) LC Separation, Waters application note 720006262en, 2018.

Acknowledgments

Catalin Doneanu, Waters Corporations, Milford, MA, USA

Post a Comment

Your email is never shared. Required fields are marked *

*
*