Ultrasensitive and Rapid Diagnosis of Influenza by Digital Nanobubbles on a Microwell Array Platform
Abstract
This proposed research addresses the Topic Area: Emerging Infectious Diseases; and the area of encouragement: Development of highly sensitive diagnostic system for use at the point of need to provide early diagnosis of infection prior to the onset of classical symptoms. The central critical problem that this proposed research tried to address is the lack of high-fidelity diagnostic platforms at the point of need. Taking the influenza (flu) as an example, it is one of the few infectious diseases that can quickly disrupt military operations and significantly affect Veterans and beneficiaries, in particular, adults over 65 years of age and children under 5 years of age. Despite a widely promoted vaccination effort, timely and accurate diagnosis of patients infected by influenza is of great importance for the doctors to prescribe correct treatments and stem the spread of this highly contagious disease. Current diagnostic methods for influenza can be classified into two categories: laboratory-based and rapid diagnostic tests. Laboratory-based tests include virus culture (i.e., growing the virus in a dish) and molecular test, the latter of which can be highly sensitive. One example of the molecular tests is called polymerase chain reaction, or PCR, which works by amplifying or creating copies of the gene of virus. While sensitive, PCR is time-consuming and costly to perform. On the other hand, rapid diagnostic tests, similar to a pregnancy dipstick, can be performed anywhere including in the doctor’s office or at home. However, the limitation of rapid diagnostic tests is the low sensitivity, for instance, only detecting 50%-70% of the actual influenza infections. The innovation of this proposed research is a new diagnostic method for emerging viral infections. Here we focus on influenza virus as it evolves rapidly and there are constantly new flu variants emerging. The working principle is taking advantage of the gold nanoparticles (AuNPs), in the range of 10 to 100 nanometers (one nanometer equals one billionth of one meter). An exciting aspect of this work is to prepare novel Janus AuNPs. These particles have one hemisphere that is attached with antibody molecules to specifically recognize the protein molecules on the virus surface and has another hemisphere that is protected against binding. This arrangement leads to much more stable assays than previous attempts. The employed antibodies can recognize many different strains of the influenza virus so that they are not limited to detect only one particular strain. Once the conjugated pair of AuNPs and antibodies recognizes and binds to the virus, it will appear as aggregates of AuNPs and absorb much more laser energy than individual AuNPs. Based on the difference of optical absorption, we then apply very short laser pulses to activate the aggregates of AuNPs to generate nanoscale vapor bubbles (i.e., nanobubbles), at which the energy level is not powerful to generate bubble from a single AuNP. By using optics to detect and count the nanobubbles, we can sensitively and quickly detect the presence of influenza virus. The unique advantage of this new approach is that it does not require extensive sample preparation, for instance, extracting the genes of virus as required by PCR. We will develop the new diagnostic assay as well as a prototype CD player-like device to realize the nanobubble measurement. The new diagnostic method can be broadly used in hospitals and point-of-need environments that do not have a laboratory. Success of the new diagnostic method will significantly change the current practice of infectious disease diagnosis and patient management. Instead of collecting nasal swabs and sending to laboratory for testing, the new diagnostic method can be performed in the doctor’s office within 30 minutes. This paradigm change will have several important implications. First, it will help the patient and doctor make the treatment decision and advis
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 10, 2021
- Source ID
- W81XWH2010106
Entities
People
- Zhenpeng Qin
Organizations
- United States Army
- University of Texas at Dallas