Host cell protein detection gap risk mitigation: quantitative IAC-MS for ELISA antibody reagent coverage determination.

Host cell proteins (HCPs) must be sufficiently cleared from recombinant biopharmaceuticals during the downstream process (DSP) to ensure product quality, purity, and patient safety. For monitoring of HCP clearance, the typical method chosen is an enzyme-linked immunosorbent assay (ELISA) using polyclonal anti-HCP antibodies obtained from an immunization campaign. This polyclonal reagent is a critical factor for functionality and confidence of the ELISA. Therefore, it is important to ensure that the pool of ELISA antibodies covers a broad spectrum of the HCPs that potentially could persist in the final drug substance. Typically, coverage is determined by gel-based approaches. Here, we present a quantitative proteomics approach combined with purification of HCPs by immunoaffinity chromatography (qIAC-MS) for assessment of ELISA coverage. The cell culture fluid (CCF) of a mock fermentation and a recombinant monoclonal antibody product were characterized in detail to investigate whether the HCPs used for immunization of animals accurately represent HCPs that are relevant to the process. Using the qIAC-MS approach, the ELISA antibody coverage was determined for mock fermentation and product CCF, as well as several different DSP intermediates. Here, the use of different controls facilitated the identification and quantification of HCPs present in the polyclonal reagent and those that nonspecifically bound to IAC material. This study successfully demonstrates that the described qIAC-MS approach is not only a suitable orthogonal method to commonly used 2D SDS-PAGE-based analysis for evaluating ELISA antibody coverage, but that it further identifies HCPs covered as well as missed by the ELISA, enabling an improved risk assessment of HCP ELISA.

An evaluation of genetically encoded FRET-based biosensors for quantitative metabolite analyses in vivo.

A broad range of genetically-encoded fluorescence biosensors has been developed, allowing the detection of signaling intermediates and metabolites in real time. Many of these biosensors are based on Foerster Resonance Energy Transfer (FRET). The two biosensors of the well-known "Venus-flytrap" type exemplarily studied in this work are composed of a central sugar binding protein flanked by two green fluorescent protein derivatives, namely ECFP as well as Citrine and EYFP, respectively. In order to evaluate FRET-based biosensors as an in vivo tool for quantitative metabolite analyses, we have thoroughly studied the effects of pH, buffer salts, ionic strength, temperature and several intracellular metabolites on the signal intensity of both biosensors and both fluorescence proteins. Almost all micro-environmental variations led to considerably different FRET signals, because either the fluorescent proteins or the metabolite binding domains were affected by the tested parameters. This resulted not only in altered FRET ratios between the apo state and the saturated state but also in significant shifts of the apparent binding constant. This underlines the necessity of careful controls in order to allow reliable quantitative measurements in vivo.