Browsing by Author "Sahari, Ali"

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    Data-driven statistical modeling of the emergent behavior of biohybrid microrobots
    Leaman, Eric J.; Sahari, Ali; Traore, Mahama Aziz; Geuther, Brian Q.; Morrow, Carmen M.; Behkam, Bahareh (2020-03-01)
    Multi-agent biohybrid microrobotic systems, owing to their small size and distributed nature, offer powerful solutions to challenges in biomedicine, bioremediation, and biosensing. Synthetic biology enables programmed emergent behaviors in the biotic component of biohybrid machines, expounding vast potential benefits for building biohybrid swarms with sophisticated control schemes. The design of synthetic genetic circuits tailored toward specific performance characteristics is an iterative process that relies on experimental characterization of spatially homogeneous engineered cell suspensions. However, biohybrid systems often distribute heterogeneously in complex environments, which will alter circuit performance. Thus, there is a critically unmet need for simple predictive models that describe emergent behaviors of biohybrid systems to inform synthetic gene circuit design. Here, we report a data-driven statistical model for computationally efficient recapitulation of the motility dynamics of two types of Escherichia coli bacteria-based biohybrid swarms-NanoBEADS and BacteriaBots. The statistical model was coupled with a computational model of cooperative gene expression, known as quorum sensing (QS). We determined differences in timescales for programmed emergent behavior in BacteriaBots and NanoBEADS swarms, using bacteria as a comparative baseline. We show that agent localization and genetic circuit sensitivity strongly influence the timeframe and the robustness of the emergent behavior in both systems. Finally, we use our model to design a QS-based decentralized control scheme wherein agents make independent decisions based on their interaction with other agents and the local environment. We show that synergistic integration of synthetic biology and predictive modeling is requisite for the efficient development of biohybrid systems with robust emergent behaviors.
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    Off-chip passivated-electrode, insulator-based dielectrophoresis (O pi DEP)
    Zellner, Phillip; Shake, Tyler; Sahari, Ali; Behkam, Bahareh; Agah, Masoud (Springer, 2013-08-01)
    In this study, we report the first off-chip passivated-electrode, insulator-based dielectrophoresis microchip (OπDEP). This technique combines the sensitivity of electrode-based dielectrophoresis (eDEP) with the high throughput and inexpensive device characteristics of insulator-based dielectrophoresis (iDEP). The device is composed of a permanent, reusable set of electrodes and a disposable, polymer microfluidic chip with microposts embedded in the microchannel. The device operates by capacitively coupling the electric fields into the microchannel; thus, no physical connections are made between the electrodes and the microfluidic device. During operation, the polydimethylsiloxan (PDMS) microfluidic chip fits onto the electrode substrate as a disposable cartridge. OπDEP uses insulting structures within the channel as well as parallel electrodes to create DEP forces by the same working principle that iDEP devices use. The resulting devices create DEP forces which are larger by two orders of magnitude for the same applied voltage when compared to off-chip eDEP designs from literature, which rely on parallel electrodes alone to produce the DEP forces. The larger DEP forces allow the OπDEP device to operate at high flow rates exceeding 1 mL/h. In order to demonstrate this technology, Escherichia coli (E. coli), a known waterborne pathogen, was trapped from water samples. Trapping efficiencies of 100 % were obtained at flow rates as high as 400 μL/h and 60 % at flow rates as high as 1200 μL/h. Additionally, bacteria were selectively concentrated from a suspension of polystyrene beads.