Analysis of deamidation artifacts induced by microwave-assisted tryptic digestion of a monoclonal antibody

Mass Spectrometry-Based Methods for Immunoglobulin G N-Glycosylation Analysis

Mass spectrometry and its hyphenated techniques enabled by the improvements in liquid chromatography, capillary electrophoresis, novel ionization, and fragmentation modes are truly a cornerstone of robust and reliable protein glycosylation analysis. Boost in immunoglobulin G (IgG) glycan and glycopeptide profiling demands for both applied biomedical and research applications has brought many new advances in the field in terms of technical innovations, sample preparation, improved throughput, and confidence in glycan structural characterization. This chapter summarizes mass spectrometry basics, focusing on IgG and monoclonal antibody N-glycosylation analysis on several complexity levels. Different approaches, including antibody enrichment, glycan release, labeling, and glycopeptide preparation and purification, are covered and illustrated with recent breakthroughs and examples from the literature omitting excessive theoretical frameworks. Finally, selected highly popular methodologies in IgG glycoanalytics such as liquid chromatography-mass spectrometry and matrix-assisted laser desorption ionization are discussed more thoroughly yet in simple terms making this text a practical starting point either for the beginner in the field or an experienced clinician trying to make sense out of the IgG glycomic or glycoproteomic dataset.

Development of an LC-MS/MS peptide mapping protocol for the NISTmAb

Peptide mapping is a component of the analytical toolbox used within the biopharmaceutical industry to aid in the identity confirmation of a protein therapeutic and to monitor degradative events such as oxidation or deamidation. These methods offer the advantage of providing site-specific information regarding post-translational and chemical modifications that may arise during production, processing or storage. A number of such variations may also be induced by the sample preparation methods themselves which may confound the ability to accurately evaluate the true modification levels. One important focus when developing a peptide mapping method should therefore be the use of sample preparation conditions that will minimize the degree of artificial modifications induced. Unfortunately, the conditions that are amenable to effective reduction, alkylation and digestion are often the same conditions that promote unwanted modifications. Here we describe the optimization of a tryptic digestion protocol used for peptide mapping of the NISTmAb IgG1κ which addresses the challenge of balancing maximum digestion efficiency with minimum artificial modifications. The parameters on which we focused include buffer concentration, digestion time and temperature, as well as the source and type of trypsin (recombinant vs. pancreatic; bovine vs porcine) used. Using the optimized protocol we generated a peptide map of the NISTmAb which allowed us to confirm its identity at the level of primary structure. Graphical abstract Peptide map of the NISTmAb RM 8671 monoclonal antibody. Tryptic digestion was performed using an optimized protocol and followed by LC-UV-MS analysis. The trace represents the total ion chromatogram. Each peak was mapped to peptides identified using mass spectrometry data.

Automated Affinity Capture and On-Tip Digestion to Accurately Quantitate in Vivo Deamidation of Therapeutic Antibodies

Deamidation of therapeutic antibodies may result in decreased drug activity and undesirable changes in pharmacokinetics and immunogenicity. Therefore, it is necessary to monitor the deamidation levels [during storage] and after in vivo administration. Because of the complexity of in vivo samples, immuno-affinity capture is widely used for specific enrichment of the target antibody prior to LC-MS. However, the conventional use of bead-based methods requires large sample volumes and extensive processing steps. Furthermore, with automation difficulties and extended sample preparation time, bead-based approaches may increase artificial deamidation. To overcome these challenges, we developed an automated platform to perform tip-based affinity capture of antibodies from complex matrixes with rapid digestion and peptide elution into 96-well microtiter plates followed by LC-MS analysis. Detailed analyses showed that the new method presents high repeatability and reproducibility with both intra and inter assay CVs < 8%. Using the automated platform, we successfully quantified the levels of deamidation of a humanized monoclonal antibody in cynomolgus monkeys over a time period of 12 weeks after administration. Moreover, we found that deamidation kinetics between in vivo samples and samples stressed in vitro at neutral pH were consistent, suggesting that the in vitro stress test may be used as a method to predict the liability to deamidation of therapeutic antibodies in vivo.

Identification of Microorganisms by High Resolution Tandem Mass Spectrometry with Accurate Statistical Significance

Correct and rapid identification of microorganisms is the key to the success of many important applications in health and safety, including, but not limited to, infection treatment, food safety, and biodefense. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is challenging correct microbial identification because of the large number of choices present. To properly disentangle candidate microbes, one needs to go beyond apparent morphology or simple 'fingerprinting'; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptidome profiles of microbes to better separate them and by designing an analysis method that yields accurate statistical significance. Here, we present an analysis pipeline that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using MS/MS data of 81 samples, each composed of a single known microorganism, that the proposed pipeline can correctly identify microorganisms at least at the genus and species levels. We have also shown that the proposed pipeline computes accurate statistical significances, i.e., E-values for identified peptides and unified E-values for identified microorganisms. The proposed analysis pipeline has been implemented in MiCId, a freely available software for Microorganism Classification and Identification. MiCId is available for download at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html . Graphical Abstract ᅟ.