We are currently developing several distinct types of artificial cells in the laboratory, based on lipid bilayer interfaces and droplet-based emulsions. Several life-like characteristics are explored including self-movement, self-division, biochemical transformation, group dynamics and self-identity. In parallel with developing new artificial cell technologies we are exploring the use of artificial cells in natural cell ecologies such as microbial fuel cells (see below) and in directed theranostics.
We will develop artificial, technological evolution and use it to design functional ecosystems consisting of up to three forms of living technology, namely, artificial chemical life, living microorganisms, and reconfigurable robotics for the purpose of improved treatment and cleanup of wastewater for energy generation.
The goals of this project are i) develop a general, robotic platform, which by using artificial evolution can optimize the performance of a physicochemical or microbial system and its environment and ii) use the robotic platform to evolve improved microbial fuel cells in terms of robustness, longevity, or adaptability. The robot evolutionary platform will take the form of an open-source 3D printer extended with functionality for handling liquids and reaction vessels, and for obtaining feedback from the reaction vessels either using computer vision or task-specific sensors in real-time. The robot platform will optimize parameters such as the environment, hydraulics or real-time interaction with experiments (for instance, timing of injection of nutrients, removal of metabolic products, stirring, etc.) to maximize a desired functionality. Initially, we investigate processes such as fluid-structure-interaction driving bio-aggregate structure and in turn metabolic activity as well as the interaction of nanoparticles and bacterial cells by analyzing the outcome of the evolutionary process using state-of-the-art imaging techniques. We then seek to exploit synergies between these technologies to significantly improve the ability of the living technology, in the form of optimized microbial fuel cells, to cleanup wastewater. Overall, this is a cross-disciplinary project involving state-of-the-art chemistry, imaging, robotics, artificial life, microbiology and bio-energy harvesting for the purpose of enhancing our understanding of living technologies and how to best design and exploit groundbreaking bio-hybrid systems.
Complex Chemistry ad Massive Chemical Flow
Polymers of hydrogen cyanide and their hydrolysis products constitute a plausible, but still poorly understood proposal for early prebiotic chemistry on Earth. HCN polymers are generated by the interplay of more than a dozen distinctive reaction mechanisms and form a highly complex mixture. Here we use a computational model based on graph grammars as a means of exploring the chemical spaces of HCN polymerization and hydrolysis. A fundamental issue is to understand the combinatorial explosion inherent in large, complex chemical systems. We demonstrate that experimental data, here obtained by mass spectrometry, and computationally predicted free energies together can be used to guide the exploration of the chemical space and makes it feasible to investigate likely pathways and chemical motifs even in potentially open-ended chemical systems.