Can we build synthetic, multicellular systems by controlling developmental signaling in space and time?

Using biological machinery to make new, functional molecules is an exciting area in chemical biology. Complex molecules containing both ‘natural’ and ‘unnatural’ components are made by processes ranging from enzymatic catalysis to the combination of molecular biology with chemical tools. Here, we discuss applying this approach to the next level of biological complexity — building synthetic, functional biotic systems by manipulating biological machinery responsible for development of multicellular organisms. We describe recent advances enabling this approach, including first, recent developmental biology progress unraveling the pathways and molecules involved in development and pattern formation; second, emergence of microfluidic tools for delivering stimuli to a developing organism with exceptional control in space and time; third, the development of molecular and synthetic biology toolsets for redesigning or de novo engineering of signaling networks; and fourth, biological systems that are especially amendable to this approach

Remote Radio Control of Insect Flight

We demonstrated the remote control of insects in free flight via an implantable radio-equipped miniature neural stimulating system. The pronotum mounted system consisted of neural stimulators, muscular stimulators, a radio transceiver-equipped microcontroller and a microbattery. Flight initiation, cessation and elevation control were accomplished through neural stimulus of the brain which elicited, suppressed or modulated wing oscillation. Turns were triggered through the direct muscular stimulus of either of the basalar muscles. We characterized the response times, success rates, and free-flight trajectories elicited by our neural control systems in remotely controlled beetles. We believe this type of technology will open the door to in-flight perturbation and recording of insect flight responses

Transpiration actuation: the design, fabrication and characterization of biomimetic microactuators driven by the surface tension of water

We have designed, fabricated and characterized large displacement distributed-force polymer actuators driven only by the surface tension of water. The devices were inspired by the hygroscopic spore dispersal mechanism in fern sporangia. Microdevices were fabricated through a single mask process using a commercial photo-patternable silicone polymer to mimic the mechanical characteristics of plant cellulose. An analytical model for predicting the microactuator behavior was developed using the principle of virtual work, and a variety of designs were simulated and compared to the empirical data. Fabricated devices experienced tip deflections of more than 3.5 mm and angular rotations of more than 330° due to the surface tension of water. The devices generated forces per unit length of 5.75 mN m−1 to 67.75 mN m−1. We show initial results indicating that the transient water-driven deflections can be manipulated to generate devices that self-assemble into stable configurations. Our model shows that devices should scale well into the submicron regime. Lastly, the actuation mechanism presented may provide a robust method for embedding geometry-programmable and environment-scavenged force generation into common materials.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/49048/2/jmm6_11_018.pd

Physical principles for scalable neural recording

Simultaneously measuring the activities of all neurons in a mammalian brain at millisecond resolution is a challenge beyond the limits of existing techniques in neuroscience. Entirely new approaches may be required, motivating an analysis of the fundamental physical constraints on the problem. We outline the physical principles governing brain activity mapping using optical, electrical, magnetic resonance, and molecular modalities of neural recording. Focusing on the mouse brain, we analyze the scalability of each method, concentrating on the limitations imposed by spatiotemporal resolution, energy dissipation, and volume displacement. Based on this analysis, all existing approaches require orders of magnitude improvement in key parameters. Electrical recording is limited by the low multiplexing capacity of electrodes and their lack of intrinsic spatial resolution, optical methods are constrained by the scattering of visible light in brain tissue, magnetic resonance is hindered by the diffusion and relaxation timescales of water protons, and the implementation of molecular recording is complicated by the stochastic kinetics of enzymes. Understanding the physical limits of brain activity mapping may provide insight into opportunities for novel solutions. For example, unconventional methods for delivering electrodes may enable unprecedented numbers of recording sites, embedded optical devices could allow optical detectors to be placed within a few scattering lengths of the measured neurons, and new classes of molecularly engineered sensors might obviate cumbersome hardware architectures. We also study the physics of powering and communicating with microscale devices embedded in brain tissue and find that, while radio-frequency electromagnetic data transmission suffers from a severe power–bandwidth tradeoff, communication via infrared light or ultrasound may allow high data rates due to the possibility of spatial multiplexing. The use of embedded local recording and wireless data transmission would only be viable, however, given major improvements to the power efficiency of microelectronic devices

A Feedback Quenched Oscillator Produces Turing Patterning with One Diffuser

Efforts to engineer synthetic gene networks that spontaneously produce patterning in multicellular ensembles have focused on Turing's original model and the “activator-inhibitor” models of Meinhardt and Gierer. Systems based on this model are notoriously difficult to engineer. We present the first demonstration that Turing pattern formation can arise in a new family of oscillator-driven gene network topologies, specifically when a second feedback loop is introduced which quenches oscillations and incorporates a diffusible molecule. We provide an analysis of the system that predicts the range of kinetic parameters over which patterning should emerge and demonstrate the system's viability using stochastic simulations of a field of cells using realistic parameters. The primary goal of this paper is to provide a circuit architecture which can be implemented with relative ease by practitioners and which could serve as a model system for pattern generation in synthetic multicellular systems. Given the wide range of oscillatory circuits in natural systems, our system supports the tantalizing possibility that Turing pattern formation in natural multicellular systems can arise from oscillator-driven mechanisms