Despite being curable and preventable, Tuberculosis (TB) is one of the Top 10 causes of death worldwide and the leading cause of death from a single infectious agent according to the World Health Organization. Currently, the TB epidemic is fueled by lack of an efficient and affordable diagnostic test. In order to ensure proper treatment, it’s essential to know whether the TB is active or latent and the personal resistance of the patient to the most common antibiotics used to treat the disease. In order to address the TB epidemic and ensure effective treatment for patients, a small portable sensor with the ability to rapidly diagnose the infection and identify the relevant antibiotic resistance genes is necessary.
My research aims to address the issues associated with TB diagnosis by using solid-state nanopore sensing. In nanopore sensing, molecules and salt ions are driven through a nanosized opening in glass using forces induced by electric fields. The molecules cause changes from the baseline ionic current as they go through the nanopore. These ionic current changes provide information about the molecules passing through the nanopore, allowing them to be identified.
In infected patients, TB bacterial DNA and other useful TB biomarkers can be found in their fluids such as sputum, urine, and blood. By using proteins and DNA nanotechnology, we can create a unique panel of specific barcodes that can be read by a nanopore sensor, allowing us to identify both the presence of TB and the resistance of the patient to different antibiotic treatments.
Using machine learning, simulations and complex data analysis methods to analyze and understand the nanopore sensor data we are working to improve rapid identification of bacterial diseases from clinically complex samples.
NanoDTC Student, c2019