Date Published: May 24, 2017
Publisher: John Wiley and Sons Inc.
Author(s): Jiang Zhuang, Byung‐Wook Park, Metin Sitti.
Despite the large body of experimental work recently on biohybrid microsystems, few studies have focused on theoretical modeling of such systems, which is essential to understand their underlying functioning mechanisms and hence design them optimally for a given application task. Therefore, this study focuses on developing a mathematical model to describe the 3D motion and chemotaxis of a type of widely studied biohybrid microswimmer, where spherical microbeads are driven by multiple attached bacteria. The model is developed based on the biophysical observations of the experimental system and is validated by comparing the model simulation with experimental 3D swimming trajectories and other motility characteristics, including mean squared displacement, speed, diffusivity, and turn angle. The chemotaxis modeling results of the microswimmers also agree well with the experiments, where a collective chemotactic behavior among multiple bacteria is observed. The simulation result implies that such collective chemotaxis behavior is due to a synchronized signaling pathway across the bacteria attached to the same microswimmer. Furthermore, the dependencies of the motility and chemotaxis of the microswimmers on certain system parameters, such as the chemoattractant concentration gradient, swimmer body size, and number of attached bacteria, toward an optimized design of such biohybrid system are studied. The optimized microswimmers would be used in targeted cargo, e.g., drug, imaging agent, gene, and RNA, transport and delivery inside the stagnant or low‐velocity fluids of the human body as one of their potential biomedical applications.
Onboard micrometer‐scale actuation and powering have been remained grand challenges for miniaturization of active devices down to a few micrometer scale. However, nature has its own solutions since billions of years ago: flagellated swimming bacteria can efficiently convert chemical energy into mechanical actuation with their nanoscale biomotors. Over the past decade, numerous studies have been conducted on harnessing the flagellated bacteria, such as E. coli and S. marcescens, as propellers for biohybrid microswimmers,1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 aiming to develop a new type of targeted drug delivery system for tumor therapy.14, 16, 18, 19 Recently, efforts have also been made to guide the motion of such bacteria‐driven microswimmers through taxis‐based14, 17, 20, 21, 22, 23, 24, 25 and magnetic steering16, 26 approaches. Among these studies, the most common way to integrate bacteria into biohybrid microswimmers is attaching intact bacterial cells onto the surfaces of synthetic microstructures, such as polystyrene microbeads, where the attachment could be enabled either by physical attraction2 or through chemical bonding.14 Current bacteria‐driven microswimmers vary vastly in materials, body shape and size, and bacterial attachment configurations; choices of these design parameters, however, have been mostly based on human intuition and empirical observation, lacking a systematic method to optimize the design of such biohybrid microsystems with respect to the their performance indicators, such as motility and guidability. To this end, it is essential to develop an analytical model that can describe the motion of bacteria‐driven microswimmers by incorporating critical design parameters, bacterial propulsion mechanics, and common guiding mechanisms such as chemotaxis.
We have developed a mathematical model to describe the propulsion mechanisms of a biohybrid microswimmer driven by a few attached flagellated bacteria. The simulations of the model produces 3D trajectories and motility characteristics that resemble those of experiments. The model, in combination with the signaling pathway models of bacterial chemotaxis, also traces out the chemotaxis behavior of bacteria‐driven microswimmers reported by recent studies.14, 17, 20, 21, 22, 23, 24, 25 The agreement between simulation and experiment implies that our model assumptions are reasonable and the model captures the fundamental biophysical mechanisms of the system. Furthermore, our simulation data suggests that the seemingly cooperative chemotaxis of multiple bacteria attached to a microswimmer could be explained by a synchronized signaling pathway response among these bacteria. However, proof of such prediction may need molecular level characterizations of the bacterial cells that are operated under a similar condition. In addition, the model reveals the potential dependencies of the microswimmers’ performances (motility and chemotactic guidability) on system parameters, including the chemoattractant gradient, microswimmer’s body size, and number of bacteria attached; such dependencies may offer useful clues for the optimized design of bacteria‐driven microswimmers.
Bacteria Culture: Escherichia coli (E. coli) MG1655 strain (Yale University, New Haven, USA) cultured on LB agar plates (Sigma‐Aldrich) was transferred to 5 mL LB broth (Sigma‐Aldrich, St. Louis, MO, USA) and allowed to grow at 30 °C for 4 h to its exponential growth phase. The resulted liquid culture was directly diluted with PBS (Thermo Fisher Scientific, Waltham, Massachusetts, USA) for the chemotaxis response tests of the free‐swimming bacteria. To prepare bacteria‐driven microswimmers, the resultant liquid culture was washed with phosphate‐buffered saline (PBS) before mixing with particles.
The authors declare no conflict of interest.