Every year, thousands of Americans contract Lyme disease, which is caused by the bacterium Borrelia burgdorferi. Currently, clinical diagnosis of Lyme disease is limited by the low levels of B. burgdorferi cells in clinical samples. This presents a severe hardship on those who have the disease, since most individuals who go untreated develop Lyme arthritis. Lyme arthritis is a debilitating condition manifested by symptoms of acute joint pain and swelling. In this proposal, we outline a research project that will develop a highly sensitive, diagnostic assay for Lyme disease. This assay, unlike other assays that are currently available, will directly detect B. burgdorferi cells in the synovial fluid of individuals suffering from Lyme arthritis, thus filling a void that currently exists in the market. Notably, thousands of Americans who suffer with arthritic symptoms undergo a battery of tests to help pinpoint the source of their discomfort. This assay will provide valuable information to those patients, offering insight into treatment options. In this Phase I proposal, we initiate development of a sensitive diagnostic assay for Lyme arthritis. We will identify high affinity peptide ligands that directly detect B. burgdorferi cells through their interaction with the bacterial outer surface proteins ErpA and ErpP. Peptide sequences for this assay will be derived from the human complement regulator, factor H, which is a known ligand of ErpA and ErpP. We will identify and affinity mature peptide sequences of factor H that specifically bind ErpA and ErpP using high-density peptide chip selections. B. burgdorferi whole-cell binding assays will be performed to examine the utility of each of the peptides selected for our diagnostic assay. In addition, we will carry out whole-cell binding assays using human cells to demonstrate the specificity of our diagnostic probes. Once we have identified high affinity peptides that specifically detect B. burgdorferi cells in whole-cell binding assays through their interactions with outer surface proteins ErpA and ErpP, these ligands will progress to the second Phase of our Lyme Diagnostic program, which will include the development of a prototype instrument for the diagnosis of Lyme arthritis. It is worth noting that we have assembled a strong research team for this proposal. Dr. John Mueller, the Principal Investigator, is a molecular microbiologist who has extensive experience in peptide selections for drug discovery and the development of in vivo and in vitro biological assays. Dr. Sriram Shankar is experienced in the design and development of antibody and peptide-based assays. Dr Brian Stevenson is an internationally renowned B. burgdorferi microbiologist, whose research focuses on the biology of outer surface proteins ErpA and ErpP and their interaction with human factor H. In summary, we feel that given the strong interactions between factor H and the B. burgdorferi outer surface proteins ErpA and ErpP, we will successfully identify high-affinity peptides that can specifically detect B. burgdorferi cells in our whole-cell binding assay. These ligands will serve as high affinity probes in our novel diagnostic assay for Lyme disease.

Public Health Relevance

We propose to develop a novel diagnostic assay for Lyme arthritis that will directly detect B. burgdorferi cells in clinical samples. We will identify high affinity peptides derived from human complement regulator, factor H, that will collectively serve as our diagnostic probe to specifically bind B. burgdorferi outer surface proteins ErpA and ErpP. These peptide ligands will afford us a facile assay to detect B. burgdorferi cells in clinical samples.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
1R43AI091046-01
Application #
7999233
Study Section
Special Emphasis Panel (ZRG1-MOSS-D (12))
Program Officer
Breen, Joseph J
Project Start
2010-06-15
Project End
2011-11-30
Budget Start
2010-06-15
Budget End
2011-11-30
Support Year
1
Fiscal Year
2010
Total Cost
$150,328
Indirect Cost
Name
Lynntech, Inc.
Department
Type
DUNS #
184758308
City
College Station
State
TX
Country
United States
Zip Code
77845