Alexandria Digital Research Library

Discovery of disease-associated antibody biomarkers and their binding targets using bacterial displayed peptide libraries

Author:
Elliott, Serra
Degree Grantor:
University of California, Santa Barbara. Chemical Engineering
Degree Supervisor:
Patrick S. Daugherty
Place of Publication:
[Santa Barbara, Calif.]
Publisher:
University of California, Santa Barbara
Creation Date:
2014
Issued Date:
2014
Topics:
Engineering, Biomedical, Engineering, Chemical, Health Sciences, Obstetrics and Gynecology, and Health Sciences, Immunology
Keywords:
Antibody biomarker
Epitope
Bacterial display peptide library
Pre-eclampsia
Diagnostic
Genres:
Dissertations, Academic and Online resources
Dissertation:
Ph.D.--University of California, Santa Barbara, 2014
Description:

Discovery of biologic molecules specific to a diseased state, or biomarkers, can lead to diagnostic development, therapeutic target identification, and improved understanding of disease pathogenesis. Antibodies remain an attractive class of biomarkers given their amplification by the immune system, stability, and current clinical use. While the antibody repertoire represents a rich source for biomarker discovery, it has been difficult to impartially identify which molecules from this repertoire are associated with disease. This work demonstrates three molecular discovery processes centered on the utility of bacterial displayed peptide libraries and fluorescence activated cell sorting (FACS) for identifying novel antibody biomarkers and their targets. We applied these methods to discover and characterize disease-associated antibodies for pre-eclampsia (PE), a condition with unknown etiology that affects 5-8% of pregnancies, using an unbiased approach.

Applying three quantitative screening strategies against a set of PE and healthy-outcome pregnancies (HOP) identified unique disease-associated antibody binding peptides from a fully random 15 amino acid peptide library. With a two-color screening method, we used antibody fractions enriched from plasma to isolate significantly PE cross-reactive and specific peptides distinct from a previously identified PE-associated antibody specificity. We used a panel of these antibody-detecting peptides to train and validate an Adaptive Boosting classification algorithm that achieved high specificity (95%) and a validated overall 80% diagnostic accuracy. To more closely replicate the native antibody binding environment, a second screening method used unprocessed, diluted plasma. This approach sequentially enriched peptides binding to PE antibodies and removed HOP antibody binders, resulting in a strong consensus motif that we further expanded through directed evolution. Importantly, we linked this motif to a region of a common viral antigen, Epstein-Barr virus nuclear antigen 1, and a human G protein-coupled receptor, GPR50, presenting a novel case for molecular mimicry. Thus, this method enabled unbiased identification of a disease-associated antibody and characterization of its targets. Finally, we developed and applied a unique methodology that combines bacterial displayed library screening with next-generation sequencing to profile the antibody repertoire of individual PE patients and HOP samples. This analysis re-identified the viral antigen-linked motif among several distinct PE- and HOP-associated antibody specificities, providing broader insights into alterations to the immune repertoire in PE.

This work demonstrates the utility of screening bacterial displayed peptide libraries to profile the antibody repertoire and identify new markers of disease. These disease-associated antibody-detecting peptide reagents enable development of molecular diagnostics and discovery of antibody binding target(s) to improve understanding of disease etiology and potentially elucidate therapeutic targets.

Physical Description:
1 online resource (168 pages)
Format:
Text
Collection(s):
UCSB electronic theses and dissertations
ARK:
ark:/48907/f3m61hdd
ISBN:
9781321567717
Catalog System Number:
990045118190203776
Rights:
Inc.icon only.dark In Copyright
Copyright Holder:
Serra Elliott
File Description
Access: Public access
Elliott_ucsb_0035D_12388.pdf pdf (Portable Document Format)