Protease sensor for rapid and sensitive detection of borrelia infections

The National Institute of Allergy and Infectious Diseases (NIAID) awarded The Leland Stanford Junior University a $436,236 Project Grant effective August 1, 2025, through July 31, 2027, under the Allergy and Infectious Diseases Research program (CFDA 93.855). The award supports development of a novel epitaxial graphene-based biosensor to enable rapid and sensitive detection of active Borrelia burgdorferi (Bb) infections, the causative agent of Lyme disease. The biosensor targets Bb High Temperature Requirement A (BbHtra) protease as a biomarker to accurately diagnose both early- and late-stage active infections, addressing critical limitations in current two-tier serology approaches that rely on antibody detection and cannot distinguish between active and prior infections. The proposed electrical transduction platform combined with selective biorecognition elements is designed to provide exceptionally high sensitivity, rapid detection capability, and the ability to function with minimal patient sample volumes.

The project includes a sub-award to the University of Maryland, College Park (awarded November 3, 2025), which will contribute specialized expertise to the research initiative. The research addresses a significant public health need, as an estimated 400,000 annual Lyme disease cases in North America are underdiagnosed due to limitations of existing diagnostic methodologies. Successful development of this protease-based biosensor would enable earlier detection and treatment, potentially preventing progression to serious complications including arthritis, carditis, and neuroborreliosis.

Abstract

Lyme disease (LD) is the most common tick-borne illness in north america caused by the bacterial species borrelia burgdorferi (BB). If diagnosed early, broad-spectrum antibiotics can effectively clear an infection. Unfortunately, delays in treatment lead to more serious symptoms including arthritis, carditis, and neuroborreliosis. The center for disease control and prevention reports 30,000 new cases of LD annually. However, experts estimate this number is closer to 400,000. This discrepancy is mainly due to the high frequency of misdiagnosis. Current diagnostic guidelines recommend a standard two-tier (STT) serology approach using an enzyme-linked immunosorbent assay (elisa) to measure antibody levels followed by a western blot to verify the presence of BB antigens. These tests have limited value because antibodies can take weeks to develop at which point the disease has progressed beyond the stage at which IT is effectively treated. In addition, BB antibodies continue circulating for years rendering them useless to distinguish between an active and a prior infection. In this proposal, we outline a plan to develop a sensitive solid-state biosensor that targets an active BB protease as a biomarker to accurately diagnose both early- and late-stage active BB infections. The proposed epitaxial graphene-based biosensor provides the potential for exceptionally high sensitivity, rapid detection, and ability to function with low volumes of patient samples by combining a novel electrical transduction platform with a selective biorecognition element. We have selected the BB protease, high temperature requirement a (bbhtra), as a biomarker because IT is constitutively expressed on the bacteria surface, is also secreted, remains active across all stages of BB infection, and contains an active site serine residue that is reactive towards small molecule electrophiles. This allows US to design and synthesize covalent probes consisting of short amino acid sequences attached to an electrophilic 'warhead' that irreversibly modifies the active protease with high selectivity and potency. The resulting covalent probes will be attached to the surface of a quasi-freestanding epitaxial graphene (QEG) biosensor and used to detect BB bacteria in patient blood and urine, as well as in test synovial fluid samples. Success of this project will address several of the most significant challenges associated with LD and potentially allow our overall approach to be applied to other diseases where proteases can serve as optimal biomarkers.