Characterizing Peptide-Antibody Interactions for Disease Detection

Authors:

Serra Elliott, Chia-In Lin

Mentor:

Patrick Daugherty, Professor and Vice Chair of Chemical Engineering, University of California, Santa Barbara

Pre-eclampsia (PE) is a pregnancy-related disease that affects 5-8 % of all pregnancies and is the cause of 18% of all maternal deaths in the US. Clinical diagnosis centers on the presentation of hypertension and excess protein in the urine after the 20th week of gestation. PE can lead to Hemolysis, Elevated Liver enzymes, and Low Platelet count (HELLP) syndrome or eclampsia, where the mother begins seizing. Currently, PE pathogenesis is poorly understood. Recent evidence suggests that an antibody against human (auto) protein angiotensin II AT1 receptor (AT1-AA) contributes to PE. However, AT1-AAs cannot be used as a diagnostic tool for PE because no high-throughput clinical assay exists and they are present in normal-outcome pregnancies and other diseases such as systemic sclerosis or kidney transplant rejection. Therefore, we hypothesized that other PE specific antibodies exist that may be used as a PE diagnostic tool with cell-surface expressed antibody detecting peptides. First, using a model peptide-antibody interaction, we demonstrated that there is a direct correlation between the peptide density and the observed maximum fluorescence, and the peptide density affects the cell-surface based binding affinity. This demonstrates that optimizing the peptide density can enhance diagnostic performance by improving the signal to noise ratio. Secondly, we tested the accuracy of a PE specific antibody detecting peptide to differentiate between PE and normal-outcome pregnancies. With this particular peptide, we were able to detect 65% of PE patients with 15% false positives. These results demonstrate the utility of antibody detecting peptide reagents for PE diagnosis.


Presented by:

Chia-In Lin

Date:

Saturday, November 23, 2013

Time:

1:40 PM — 1:55 PM

Room:

Science 208

Presentation Type:

Oral Presentation

Discipline:

Biology