Strategies for Mitigating Commercial Sensor Chip Variability with Experimental Design Controls.

Surface plasmon resonance (SPR) is a popular real-time technique for the measurement of binding affinity and kinetics, and bench-top instruments combine affordability and ease of use with other benefits of the technique. Biomolecular ligands labeled with the 6xHis tag can be immobilized onto sensing surfaces presenting the Ni2+-nitrilotriacetic acid (NTA) functional group. While Ni-NTA immobilization offers many advantages, including the ability to regenerate and reuse the sensors, its use can lead to signal variability between experimental replicates. We report here a study of factors contributing to this variability using the Nicoya OpenSPR as a model system and suggest ways to control for those factors, increasing the reproducibility and rigor of the data. Our model ligand/analyte pairs were two ovarian cancer biomarker proteins (MUC16 and HE4) and their corresponding monoclonal antibodies. We observed a broad range of non-specific binding across multiple NTA chips. Experiments run on the same chips had more consistent results in ligand immobilization and analyte binding than experiments run on different chips. Further assessment showed that different chips demonstrated different maximum immobilizations for the same concentration of injected protein. We also show a variety of relationships between ligand immobilization level and analyte response, which we attribute to steric crowding at high ligand concentrations. Using this calibration to inform experimental design, researchers can choose protein concentrations for immobilization corresponding to the linear range of analyte response. We are the first to demonstrate calibration and normalization as a strategy to increase reproducibility and data quality of these chips. Our study assesses a variety of factors affecting chip variability, addressing a gap in knowledge about commercially available sensor chips. Controlling for these factors in the process of experimental design will minimize variability in analyte signal when using these important sensing platforms.

Individual recombinant repeats of MUC16 display variable binding to CA125 antibodies.

BACKGROUND: Despite its importance in the clinical management of ovarian cancer, the CA125 biomarker - located on the mucin protein MUC16 - is still not completely understood. Questions remain about MUC16's function and structure, specifically the identity and location of the CA125 epitopes. OBJECTIVE: The goal of this study was to characterize the interaction of individual recombinant repeats from the tandem repeat domain of MUC16 with antibodies used in the clinical CA125 II test. METHODS: Using E. coli expression, we isolated nine repeats from the putative antigenic domain of CA125. Amino acid composition of recombinant repeats was confirmed by high-resolution mass spectrometry. We characterized the binding of four antibodies - OC125, M11, "OC125-like," and "M11-like" - to nine recombinant repeats using Western blotting, indirect enzyme-linked immunosorbent assay (ELISA), and localized surface plasmon resonance (SPR) spectroscopy. RESULTS: Each recombinant repeat was recognized by a different combination of CA125 antibodies. OC125 and "OC125-like" antibodies did not bind the same set of recombinant repeats, nor did M11 and "M11-like" antibodies. CONCLUSIONS: Characterization of the interactions between MUC16 recombinant repeats and CA125 antibodies will contribute to ongoing efforts to identify the CA125 epitopes and improve our understanding of this important biomarker.

Individual recombinant repeats of MUC16 display variable binding to CA125 antibodies.

BACKGROUND: Despite its importance in the clinical management of ovarian cancer, the CA125 biomarker-located on the mucin protein MUC16-is still not completely understood. Questions remain about MUC16's function and structure, specifically the identity and location of the CA125 epitopes. OBJECTIVE: The goal of this study was to characterize the interaction of individual recombinant repeats from the tandem repeat domain of MUC16 with antibodies used in the clinical CA125 II test. METHODS: Using E. coli expression, we isolated nine repeats from the putative antigenic domain of CA125. Amino acid composition of recombinant repeats was confirmed by high-resolution mass spectrometry. We characterized the binding of four antibodies-OC125, M11, "OC125-like," and "M11-like"-to nine recombinant repeats using Western blotting, indirect enzyme-linked immunosorbent assay (ELISA), and localized surface plasmon resonance (SPR) spectroscopy. RESULTS: Each recombinant repeat was recognized by a different combination of CA125 antibodies. OC125 and "OC125-like" antibodies did not bind the same set of recombinant repeats, nor did M11 and "M11-like" antibodies. CONCLUSIONS: Characterization of the interactions between MUC16 recombinant repeats and CA125 antibodies will contribute to ongoing efforts to identify the CA125 epitopes and improve our understanding of this important biomarker.

Selection of DNA aptamers for ovarian cancer biomarker HE4 using CE-SELEX and high-throughput sequencing.

The development of novel affinity probes for cancer biomarkers may enable powerful improvements in analytical methods for detecting and treating cancer. In this report, we describe our use of capillary electrophoresis (CE) as the separation mechanism in the process of selecting DNA aptamers with affinity for the ovarian cancer biomarker HE4. Rather than the conventional use of cloning and sequencing as the last step in the aptamer selection process, we used high-throughput sequencing on an Illumina platform. This data-rich approach, combined with a bioinformatics pipeline based on freely available computational tools, enabled the entirety of the selection process-and not only its endpoint-to be characterized. Affinity probe CE and fluorescence anisotropy assays demonstrate the binding affinity of a set of aptamer candidates identified through this bioinformatics approach. Graphical Abstract A population of candidate aptamers is sequenced on an Illumina platform, enabling the process by which aptamers are selected over multiple SELEX rounds to be characterized. Bioinformatics tools are used to identify enrichment of selected aptamers and groupings into clusters based on sequence and structural similarity. A subset of sequenced aptamers may be intelligently chosen for in vitro testing.