Assessing dose-response of antibiotics and monitoring degradation of RNA aptamer biosensor on microfluidic devices

Abstract

In the last century, the technologies developed to miniaturize transistors and manufacture microprocessors have enabled the miniaturization and integration of tools in biology, chemistry, biotechnology and medical fields. These tools have low reagent consumption, display high levels of integration, parallelization and automation, can carry out fast reactions, and are portable. The miniaturized and integrated microfluidic platforms are capable of integrating multiple analysis steps: sample preparation, reaction, and detection onto a single chip, termed as “Lab-on-chip” or µTAS (micro total analysis system). This technology has altered and influenced the way various questions are addressed in biology, chemistry, and biotechnology. In this dissertation, we investigated the concentration- and time-dependent response of cell (bacteria) or molecule (RNA aptamer-based biosensor) to reagents (antibiotics or degrading agents) by using microfluidic systems. We obtained useful information for evaluating the attenuated inhibitory effect of antibiotics by bacteria’s resistance and differentiating degrading agents through monitoring the degrading profiles of RNA biosensor. Two microfluidic systems were used in this study. The first microfluidic system has multiplex reactors, and the second microfluidic system integrates a concentration gradient generator, reagent mixing and reaction sections. Both systems enable simultaneous, parallel and independent reactions, requiring nanoliter amount of reagents, unlike the conventional test tube or microtiter method. Our microfluidic tools are potential alternative to replace conventional batch culture methods. In addition, they have a great potential for screening drug molecules, determining drug’s potency as well as replacing conventional monitoring methods in transcriptomics. So, these devices are highly potential to benefit the process of lead identification and optimization during drug discovery as well as promote the transcriptomic researches.