Ph.D. Candidate, Johns Hopkins University
Microfluidic platforms for rapid and sensitive detection of infectious pathogens in human samples
Conventional methods used in hospital labs for identifying, counting, and characterizing drug resistance of bacteria that exist in infected human samples are slow and cumbersome, and can take as long as 2 days for definitive diagnosis. This can inevitably delay treatment of the infection, which may result in grave clinical outcomes. As a solution to this critical problem, I am developing a medical diagnostic device that can be used to trap individual bacterial cells in microscopic compartments known as "droplets." Once trapped, these bacteria can be identified and counted, based on their specific nucleic acid signatures. Moreover, the bacterial cells can be characterized as sensitive or resistant, based on their response to antibiotics. By relying on measurements from single-cells, definitive diagnosis can be achieved in as little as 1 to 2 hours, much faster than conventional methods. A diagnostic device such as this has the potential to improve patient outcomes as well as curtail the emergence and spread of drug resistant pathogens.
Abstract: Personalized medicine - healthcare based on individual genetic variation - has the potential to transform the way healthcare is delivered to patients. The promise of personalized medicine has been predicated on the predictive and diagnostic power of genomic and proteomic biomarkers. Biomarker screening may help improve health outcomes, for example, by identifying individuals' susceptibility to diseases and predicting how patients will respond to drugs. Microfluidic droplet technology offers an exciting opportunity to revolutionize the accessibility of personalized medicine. A framework for the role of droplet microfluidics in biomarker detection can be based on two main themes. Emulsion-based microdroplet platforms can provide new ways to measure and detect biomolecules. In addition, microdroplet platforms facilitate high-throughput screening of biomarkers. Meanwhile, surface-based droplet platforms provide an opportunity to develop miniaturized diagnostic systems. These platforms may function as portable benchtop environments that dramatically shorten the transition of a benchtop assay into a point-of-care format.
Pub.: 12 Aug '14, Pinned: 19 Sep '17
Abstract: Droplet microfluidics has found use in many biological assay applications as a means of high-throughput sample processing. One of the challenges of the technology, however, is the ability to control and merge droplets on-demand as they flow through the microdevices. It is in the interest of developing lab-on-chip devices to be able to combinatorically program additive mixing steps for more complex multistep and multiplex assays. Existing technologies to merge droplets are either passive in nature or require highly predictable droplet movement for feedforward control, making them vulnerable to errors during high throughput operation. In this paper, we describe and demonstrate a microfluidic valve-based device for the purpose of combinatorial droplet injection at any stage in a multistep assay. Microfluidic valves are used to robustly control fluid flow, droplet generation, and droplet mixing in the device on-demand, while on-chip impedance measurements taken in real time are used as feedback to accurately time the droplet injections. The presented system is contrasted to attempts without feedback, and is shown to be 100% reliable over long durations. Additionally, content detection and discretionary injections are explored and successfully executed.
Pub.: 07 Jul '17, Pinned: 19 Sep '17
Abstract: Timely and accurate identification and determination of the antimicrobial susceptibility of uropathogens is central to the management of UTIs. Urine dipsticks are fast and amenable to point-of-care testing, but do not have adequate diagnostic accuracy or provide microbiological diagnosis. Urine culture with antimicrobial susceptibility testing takes 2-3 days and requires a clinical laboratory. The common use of empirical antibiotics has contributed to the rise of multidrug-resistant organisms, reducing treatment options and increasing costs. In addition to improved antimicrobial stewardship and the development of new antimicrobials, novel diagnostics are needed for timely microbial identification and determination of antimicrobial susceptibilities. New diagnostic platforms, including nucleic acid tests and mass spectrometry, have been approved for clinical use and have improved the speed and accuracy of pathogen identification from primary cultures. Optimization for direct urine testing would reduce the time to diagnosis, yet these technologies do not provide comprehensive information on antimicrobial susceptibility. Emerging technologies including biosensors, microfluidics, and other integrated platforms could improve UTI diagnosis via direct pathogen detection from urine samples, rapid antimicrobial susceptibility testing, and point-of-care testing. Successful development and implementation of these technologies has the potential to usher in an era of precision medicine to improve patient care and public health.
Pub.: 02 Mar '17, Pinned: 19 Sep '17
Abstract: There remains an urgent need for rapid diagnostic methods that can evaluate antibiotic resistance for pathogenic bacteria in order to deliver targeted antibiotic treatments. Toward this end, we present a rapid and integrated single-cell biosensing platform, termed dropFAST, for bacterial growth detection and antimicrobial susceptibility assessment. DropFAST utilizes a rapid resazurin-based fluorescent growth assay coupled with stochastic confinement of bacteria in 20 pL droplets to detect signal from growing bacteria after 1h incubation, equivalent to 2-3 bacterial replications. Full integration of droplet generation, incubation, and detection into a single, uninterrupted stream also renders this platform uniquely suitable for in-line bacterial phenotypic growth assessment. To illustrate the concept of rapid digital antimicrobial susceptibility assessment, we employ the dropFAST platform to evaluate the antibacterial effect of gentamicin on E. coli growth.
Pub.: 14 Jun '17, Pinned: 19 Sep '17
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