MakerFluidics: low cost microfluidics for synthetic biology

Recent advancements in multilayer, multicellular, genetic logic circuits often rely on manual intervention throughout the computation cycle and orthogonal signals for each chemical “wire”. These constraints can prevent genetic circuits from scaling. Microfluidic devices can be used to mitigate these constraints. However, continuous-flow microfluidics are largely designed through artisanal processes involving hand-drawing features and accomplishing design rule checks visually: processes that are also inextensible. Additionally, continuous-flow microfluidic routing is only a consideration during chip design and, once built, the routing structure becomes “frozen in silicon,” or for many microfluidic chips “frozen in polydimethylsiloxane (PDMS)”; any changes to fluid routing often require an entirely new device and control infrastructure. The cost of fabricating and controlling a new device is high in terms of time and money; attempts to reduce one cost measure are, generally, paid through increases in the other. This work has three main thrusts: to create a microfluidic fabrication framework, called MakerFluidics, that lowers the barrier to entry for designing and fabricating microfluidics in a manner amenable to automation; to prove this methodology can design, fabricate, and control complex and novel microfluidic devices; and to demonstrate the methodology can be used to solve biologically-relevant problems. Utilizing accessible technologies, rapid prototyping, and scalable design practices, the MakerFluidics framework has demonstrated its ability to design, fabricate and control novel, complex and scalable microfludic devices. This was proven through the development of a reconfigurable, continuous-flow routing fabric driven by a modular, scalable primitive called a transposer. In addition to creating complex microfluidic networks, MakerFluidics was deployed in support of cutting-edge, application-focused research at the Charles Stark Draper Laboratory. Informed by a design of experiments approach using the parametric rapid prototyping capabilities made possible by MakerFluidics, a plastic blood--bacteria separation device was optimized, demonstrating that the new device geometry can separate bacteria from blood while operating at 275% greater flow rate as well as reduce the power requirement by 82% for equivalent separation performance when compared to the state of the art. Ultimately, MakerFluidics demonstrated the ability to design, fabricate, and control complex and practical microfluidic devices while lowering the barrier to entry to continuous-flow microfluidics, thus democratizing cutting edge technology beyond a handful of well-resourced and specialized labs

Accelerating Exact Stochastic Simulation of Biochemical Systems

The ability to accurately and efficiently simulate computer models of biochemical systems is of growing importance to the molecular biology and pharmaceutical research communities. Exact stochastic simulation is a popular approach for simulating such systems because it properly represents genetic noise and it accurately represents systems with small populations of chemical species. Unfortunately, the computational demands of exact stochastic simulation often limit its applicability. To enable next-generation whole-cell and multi-cell stochastic modeling, advanced tools and techniques must be developed to increase simulation efficiency. This work assesses the applicability of a variety of hardware and software acceleration approaches for exact stochastic simulation including serial algorithm improvements, parallel computing, reconfigurable computing, and cluster computing. Through this analysis, improved simulation techniques for biological systems are explored and evaluated

Computation Using Patterning of Bacterial Colonies

The functional complexity that is possible to engineer in single cells is limited by different aspects, such as metabolic burden or protein cross talk. For these reasons, in recent years the field of synthetic biology is moving away from intracellular systems to intercellular systems. This allows to distribution of computation across different strains mimicking real biological systems, where complex behaviours emerge from population level interactions. One area of interest of the field is the development of biosensors. Different whole-cell biosensors have been developed where a system detecting an analyte is integrated in a living organism. The limitation of this approach is that they usually sense a single metabolite and a new strain needs to be engineered if a new function is required. There is therefore a need for a platform where different biosensors can be integrated to perform multiplexed computation with different inputs. The focus of this thesis was to explore new types of biocomputation. In particular, the main focus was to demonstrate how emergent computation can be performed using spatial patterning. In the first part I demonstrated that it is possible to perform spatial computation using the emergent behaviours of an existing bistable system. Here, I successfully computed an OR and XOR gate. In the second part, I developed a platform for the integration of biosensor signals using the patterning of bacterial colonies. The platform's architecture consists of two strains arranged in a grid structure: the ``sender'' strain integrates the biosensor system and produces diffusible molecules, and a ``receiver'' strain that expresses a reporter protein in response to the diffusible molecules. This is integrated with a dispensing robot and a custom imaging setup. Finally, this platform was successfully used to compute a spatial AND and OR logic gate, aided with simulations performed using a reaction-diffusion mathematical model. Overall, the work presented here contributes to the advancement of the field towards the construction of complex artificial biological systems and the engineering of emergent behaviours

Fluigi: an end-to-end software workflow for microfluidic design

One goal of synthetic biology is to design and build genetic circuits in living cells for a range of applications with implications in health, materials, and sensing. Computational design methodologies allow for increased performance and reliability of these circuits. Major challenges that remain include increasing the scalability and robustness of engineered biological systems and streamlining and automating the synthetic biology workflow of “specify-design-build-test.” I summarize the advances in microfluidic technology, particularly microfluidic large scale integration, that can be used to address the challenges facing each step of the synthetic biology workflow for genetic circuits. Microfluidic technologies allow precise control over the flow of biological content within microscale devices, and thus may provide more reliable and scalable construction of synthetic biological systems. However, adoption of microfluidics for synthetic biology has been slow due to the expert knowledge and equipment needed to fabricate and control devices. I present an end-to-end workflow for a computer-aided-design (CAD) tool, Fluigi, for designing microfluidic devices and for integrating biological Boolean genetic circuits with microfluidics. The workflow starts with a ``netlist" input describing the connectivity of microfluidic device to be designed, and proceeds through placement, routing, and design rule checking in a process analogous to electronic computer aided design (CAD). The output is an image of the device for printing as a mask for photolithography or for computer numerical control (CNC) machining. I also introduced a second workflow to allocate biological circuits to microfluidic devices and to generate the valve control scheme to enable biological computation on the device. I used the CAD workflow to generate 15 designs including gradient generators, rotary pumps, and devices for housing biological circuits. I fabricated two designs, a gradient generator with CNC machining and a device for computing a biological XOR function with multilayer soft lithography, and verified their functions with dye. My efforts here show a first end-to-end demonstration of an extensible and foundational microfluidic CAD tool from design concept to fabricated device. This work provides a platform that when completed will automatically synthesize high level functional and performance specifications into fully realized microfluidic hardware, control software, and synthetic biological wetware

Devobot: From Biological Morphogenesis to Morphogenetic Swarm Robotics

Complex systems are composed of a large number of relatively simple entities interacting with each other and their environment. From those entities and interactions emerge new and often unpredictable collective structures. Complex systems are widely present in nature, from cells and living organisms to human societies. A major biological process behind this emergence in natural complex systems is morphogenesis, which refers mainly, although not exclusively, to shape development in multicellular organisms. Inspired by morphogenesis, the field of Morphogenetic Engineering (ME) aims to design a system’s global architecture and behaviour in a bottom-up fashion from the self-organisation of a myriad of small components. In particular, Morphogenetic Robotics (MR) strives to apply ME to Swarm Robotics in order to create robot collectives exhibiting morphogenetic properties. While most MR works focus on small and cheap hardware, such as Kilobots, only few or them investigate swarms of mobile and more “intelligent” robot models. In this thesis, we present two original works involving higher-end MR swarms based on the PsiSwarm platform, a two-wheeled saucer-size robot running the Mbed operating system. First, we describe a novel distributed algorithm capable of growing a densely packed “multi-robot organism” out of a group of 40 PsiSwarms, based on ME principles. Then, in another study closer to Modular Robotics (MoR), and taking inspiration from “programmable network growth”, we demonstrate the self-organisation of (virtual) branched structures among a flock of robots. Both works use MORSE, a realistic simulation tool, while a path toward crossing the “reality gap” is shown by preliminary experiments conducted using real hardware

Ant-inspired Interaction Networks For Decentralized Vehicular Traffic Congestion Control

Mimicking the autonomous behaviors of animals and their adaptability to changing or foreign environments lead to the development of swarm intelligence techniques such as ant colony optimization (ACO) and particle swarm optimization (PSO) now widely used to tackle a variety of optimization problems. The aim of this dissertation is to develop an alternative swarm intelligence model geared toward decentralized congestion avoidance and to determine qualities of the model suitable for use in a transportation network. A microscopic multi-agent interaction network inspired by insect foraging behaviors, especially ants, was developed and consequently adapted to prioritize the avoidance of congestion, evaluated as perceived density of other agents in the immediate environment extrapolated from the occurrence of direct interactions between agents, while foraging for food outside the base/nest. The agents eschew pheromone trails or other forms of stigmergic communication in favor of these direct interactions whose rate is the primary motivator for the agents\u27 decision making process. The decision making process at the core of the multi-agent interaction network is consequently transferred to transportation networks utilizing vehicular ad-hoc networks (VANETs) for communication between vehicles. Direct interactions are replaced by dedicated short range communications for wireless access in vehicular environments (DSRC/WAVE) messages used for a variety of applications like left turn assist, intersection collision avoidance, or cooperative adaptive cruise control. Each vehicle correlates the traffic on the wireless network with congestion in the transportation network and consequently decides whether to reroute and, if so, what alternate route to take in a decentralized, non-deterministic manner. The algorithm has been shown to increase throughput and decrease mean travel times significantly while not requiring access to centralized infrastructure or up-to-date traffic information

A comprehensive survey on hybrid communication in context of molecular communication and terahertz communication for body-centric nanonetworks

With the huge advancement of nanotechnology over the past years, the devices are shrinking into micro-scale, even nano-scale. Additionally, the Internet of nano-things (IoNTs) are generally regarded as the ultimate formation of the current sensor networks and the development of nanonetworks would be of great help to its fulfilment, which would be ubiquitous with numerous applications in all domains of life. However, the communication between the devices in such nanonetworks is still an open problem. Body-centric nanonetworks are believed to play an essential role in the practical application of IoNTs. BCNNs are also considered as domain specific like wireless sensor networks and always deployed on purpose to support a particular application. In these networks, electromagnetic and molecular communications are widely considered as two main promising paradigms and both follow their own development process. In this survey, the recent developments of these two paradigms are first illustrated in the aspects of applications, network structures, modulation techniques, coding techniques and security to then investigate the potential of hybrid communication paradigms. Meanwhile, the enabling technologies have been presented to apprehend the state-of-art with the discussion on the possibility of the hybrid technologies. Additionally, the inter-connectivity of electromagnetic and molecular body-centric nanonetworks is discussed. Afterwards, the related security issues of the proposed networks are discussed. Finally, the challenges and open research directions are presented

An Approach Based on Particle Swarm Optimization for Inspection of Spacecraft Hulls by a Swarm of Miniaturized Robots

The remoteness and hazards that are inherent to the operating environments of space infrastructures promote their need for automated robotic inspection. In particular, micrometeoroid and orbital debris impact and structural fatigue are common sources of damage to spacecraft hulls. Vibration sensing has been used to detect structural damage in spacecraft hulls as well as in structural health monitoring practices in industry by deploying static sensors. In this paper, we propose using a swarm of miniaturized vibration-sensing mobile robots realizing a network of mobile sensors. We present a distributed inspection algorithm based on the bio-inspired particle swarm optimization and evolutionary algorithm niching techniques to deliver the task of enumeration and localization of an a priori unknown number of vibration sources on a simplified 2.5D spacecraft surface. Our algorithm is deployed on a swarm of simulated cm-scale wheeled robots. These are guided in their inspection task by sensing vibrations arising from failure points on the surface which are detected by on-board accelerometers. We study three performance metrics: (1) proximity of the localized sources to the ground truth locations, (2) time to localize each source, and (3) time to finish the inspection task given a 75% inspection coverage threshold. We find that our swarm is able to successfully localize the present so

Contract and Grant Awards Fiscal Year 2006

I invite you to read this report Contract & Grant Awards, fiscal year 2006, which lists contract and grant (C&G) awards received by the University of New Mexico (UNM) during the period from July 1, 2005 - June 30, 2006 (FY06). These awards represent new funds that were acquired during FY06 by the main campus, branch campuses and education centers, and the Health Sciences Center (HSC). The HSC includes the School of Medicine, College of Nursing, and College of Pharmacy. The awards received for FY06 total $298.6M, of which$165.4M is attributed to the main campus and $133.2M to HSC. These awards assist in providing resources that are necessary to support and enhance the quality of research and teaching at UNM, as well as the opportunities for students to be trained in state-of-the-art laboratories in a variety of disciplines