An optimized approach to the rapid assessment and detection of sequence variants in recombinant protein products

Abstract

The development of sensitive techniques to detect sequence variants (SVs), which naturally arise due to DNA mutations and errors in transcription/translation (amino acid misincorporations), has resulted in increased attention to their potential presence in protein-based biologic drugs in recent years. Often, these SVs may be below 0.1%, adding challenges for consistent and accurate detection. Furthermore, the presence of false-positive (FP) signals, a hallmark of SV analysis, requires time-consuming analyst inspection of the data to sort true from erroneous signal. Consequently, gaps in information about the prevalence, type, and impact of SVs in marketed and in-development products are significant. Here, we report the results of a simple, straightforward, and sensitive approach to sequence variant analysis. This strategy employs mixing of two samples of an antibody or protein with the same amino acid sequence in a dilution series followed by subsequent sequence variant analysis. Using automated peptide map analysis software, a quantitative assessment of the levels of SVs in each sample can be made based on the signal derived from the mass spectrometric data. We used this strategy to rapidly detect differences in sequence variants in a monoclonal antibody after a change in process scale, and in a comparison of three mAbs as part of a biosimilar program. This approach is powerful, as true signals can be readily distinguished from FP signal, even at a level well below 0.1%, by using a simple linear regression analysis across the data set with none to minimal inspection of the MS/MS data. Additionally, the data produced from these studies can also be used to make a quantitative assessment of relative levels of product quality attributes. The information provided here extends the published knowledge about SVs and provides context for the discussion around the potential impact of these SVs on product heterogeneity and immunogenicity.

Identifying low‐level sequence variants via next generation sequencing to aid stable CHO cell line screening

“…Advanced data search packages such as Mascot‐ETS, SIEVE or MassAnalyzer may help to identify lower‐level sequence variants. However, these techniques could also miss a given amino acid substitution if ionization efficiency of the corresponding peptides is poor . One of the biggest advantages of a mass spectrometry‐based approach lies in its ability to detect non‐genetic mutation derived sequence variants resulting from either tRNA mischarging or codon misreading .…”

“…However, these techniques could also miss a given amino acid substitution if ionization efficiency of the corresponding peptides is poor. 9,10,13,14 One of the biggest advantages of a mass spectrometry-based approach lies in its ability to detect non-genetic mutation derived sequence variants resulting from either tRNA mischarging or codon misreading. 12,25,27,28,44 However, it is worth noting that the root cause of a given sequence variant cannot be determined only by mass spectrometry or any other amino acid based analytical approaches unless the corresponding nucleotide sequence is assessed simultaneously.…”

“…However, these conventional approaches have limitations and sometimes lack sensitivity . The need for highly sensitive tools to assess low‐level cell line specific heterogeneity in therapeutic products has recently stimulated method development in the field of mass spectrometry and data analysis . In contrast, there are few reports on applying advanced genomic tools to identify aberrant cell lines carrying low‐abundance mutations.…”

“…8 The need for highly sensitive tools to assess low-level cell line specific heterogeneity in therapeutic products has recently stimulated method development in the field of mass spectrometry and data analysis. 5,[9][10][11][12][13][14] In contrast, there are few reports on applying advanced genomic tools to identify aberrant cell lines carrying low-abundance mutations. This is despite the fact that characterization of genome and transcriptome by next generation sequencing (NGS) is now widely employed in clinical research to discover diverse mutational and splicing events and in cell culture to identify gene targets for cell line engineering and bioprocess optimization.…”

Utilization of sequence variants as biomarkers to analyze population dynamics in cloned cell lines

“…Detection of low level SVs has occurred more frequently due to improvements in sequencing (Pekin et al, 2011;Zhang et al, 2015b) and analytical instrumentation specifically in mass spectrometry and related software (Brady et al, 2015;Harris et al, 1993;Zeck et al, 2012;Zhang et al, 2013). In terms of protein analytics, there is much higher sensitivity and selectivity for product characterization and low level SV detection (Feeney et al, 2013;Wan et al, 1999).…”