Detection and quantitation of biomolecules is of central importance in biomedical research and in clinical assays. Our goal is to develop and apply novel bioanalytical methodology that will utilize the power of Next Generation Sequencing (NGS) that is normally reserved for analysis of nucleic acids, for discovery of target-specific polypeptide ligands and for highly parallel analysis of their interactions. Our hypothesis is that y establishing a direct link between peptide sequences and their coding RNA through in vitro translation under ribosome display (RD) conditions, quantitative analysis of binding of millions of peptides in a single experiment will be enabled by NGS. Next Generation Sequencing (NGS) has revolutionized analysis of nucleic acids. NGS analysis in a single experiment can provide information on identity and relative abundance of millions of specific nucleic acid sequences in a sample. We propose that the extraordinary power of NGS analysis can be harnessed for analysis of polypeptide interactions by combining ribosome display (RD) with NGS analysis. In RD, RNA encoding peptide sequences is translated in vitro under conditions where peptide products and its corresponding RNA's remain associated with the ribosomes effectively labeling each peptide with a unique RNA sequence tag enabling application of NGS analysis. We envision two major applications for this NGS-enhanced RD (NGSERD) approach. The first will be to use it as a ligand discovery tool (aim 1). A particular strength and unique feature of this NGSERD application will be the possibility of applying computational tools to NGS data to enable discovery of ligands for complex targets where authentic ligands recognizing desired target have to be sorted out from excess of spurious or nonspecific ligands. The second application for NGSERD (aim 2) will be to use it as a novel highly parallel binding assay in which NGS analysis will provide a unique readout where the RNA sequence tag will identify the ligand and the read count for the sequence will provide supersensitive quantitative signal reporting ligand binding enabling analysis of a large number (up to millions) of peptide reagents in a single experiment. Once the NGSERD methodology is developed in aims 1&2, we will apply it for the analysis of disease-related antibodies in human serum. Identification, detection, profiling and blocking antibodies has tremendous research, clinical and therapeutic values in autoimmune and infectious diseases, in cancer and in vaccine development. To establish a paradigm for practical applications of NGSERD-based antibody analysis, we will apply it to systemic lupus erythematosus (SLE), an autoimmune disease in which the antibodies produced to self-antigens are responsible for the pathology of the disease. The impact of this project lies in multitudes of exciting applications of NGSERD approach in research, in disease diagnosis and prognosis, in early detection of the disease, in design of therapeutic agents, and in vaccine development.

Public Health Relevance

This project outlines a plan to develop novel bioanalytical tools that will allow simultaneous analysis of binding of a large number (up to millions) of polypeptide ligands. These tools will enable identification of new reagents for difficult targets o biomedical interest and development of new generation of assays for research and clinical use. They will find multitudes of exciting applications in research, in disease diagnosis and prognosis, in early detection of the disease, in design of therapeutic agents, and in vaccine development.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM109974-03
Application #
9198775
Study Section
Enabling Bioanalytical and Imaging Technologies Study Section (EBIT)
Program Officer
Wu, Mary Ann
Project Start
2015-01-01
Project End
2018-12-31
Budget Start
2017-01-01
Budget End
2017-12-31
Support Year
3
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Saint Louis University
Department
Biochemistry
Type
Schools of Medicine
DUNS #
050220722
City
Saint Louis
State
MO
Country
United States
Zip Code
63103
Heyduk, Ewa; Hickey, Rachel; Pozzi, Nicola et al. (2018) Peptide ligand-based ELISA reagents for antibody detection. Anal Biochem 559:55-61
Heyduk, Tomasz; Heyduk, Ewa (2015) Next Generation Sequencing-based analysis of RNA polymerase functions. Methods 86:37-44