Whooping cough, the infectious respiratory disease caused by Bordetella pertussis, is diagnosed in tens of millions of people and results in almost 300,000 deaths globally each year. Low-income and unvaccinated individuals as well as infants are especially susceptible. Current diagnostic procedures are complicated, costly, and can take up to a week, by which time the disease may have progressed or spread. The enormous impact of this disease urgently motivates the development of a faster, cheaper, and more reliable diagnostic. Our epidemiology models suggest that earlier diagnosis could drastically reduce the incidence and impact of the disease. We propose an engineered bacteriophage diagnostic system for rapid clinical detection of pertussis.
As a proof of principle, we worked on engineering the T7 bacteriophage to express a version of the beta subunit of human chorionic gonadotropin (hCG) which we codon-optimized for expression in E. coli. Due to host-pathogen specificity, bacteriophages will only replicate and produce intracellular hCG if the target bacteria is present in the sample. The bacteriophage lyses the cell, releasing the hCG, which can then be detected using a pregnancy test. Pregnancy tests are commonly available in all clinics and can detect very low concentrations of hCG, which is an advantage over currently-available methods for detecting phage amplification. The bacteriophage system also requires minimal training to be used in lab and does not require any high-tech machinery. This will make the diagnostic readily usable in developing countries, where whooping cough is a particular concern. Besides pertussis, this method can be used to detect the presence of any bacteria for which there exists a bacteriophage using a common pregnancy test.
See Virginia 2012's project wiki for more details.
From left to right: Jackie Grimm (Biology 2014), Josh Fass (BME 2014), Shaun Moshasha (Biochemistry and Physics 2013), Alex Zorychta (BME 2013), Joseph Muldoon (Biology and Biochemistry 2013), John Hubczak (ChE 2013), Syed Hassan (Computer Science and Chemistry 2014) Not pictured: Omar Raza (Biology 2014)