Programming chemistry in DNA-addressable bioreactors

We present a formal calculus, termed the chemtainer calculus, able to capture the complexity of compartmentalized reaction systems such as populations of possibly nested vesicular compartments. Compartments contain molecular cargo as well as surface markers in the form of DNA single strands. These markers serve as compartment addresses and allow for their targeted transport and fusion, thereby enabling reactions of previously separated chemicals. The overall system organization allows for the set-up of programmable chemistry in microfluidic or other automated environments. We introduce a simple sequential programming language whose instructions are motivated by state-of-the-art microfluidic technology. Our approach integrates electronic control, chemical computing and material production in a unified formal framework that is able to mimic the integrated computational and constructive capabilities of the subcellular matrix. We provide a non-deterministic semantics of our programming language that enables us to analytically derive the computational and constructive power of our machinery. This semantics is used to derive the sets of all constructable chemicals and supermolecular structures that emerge from different underlying instruction sets. Because our proofs are constructive, they can be used to automatically infer control programs for the construction of target structures from a limited set of resource molecules. Finally, we present an example of our framework from the area of oligosaccharide synthesis

Formalizing modularization and data hiding in synthetic biology

Biological systems employ compartmentalization and other co-localization strategies in order to orchestrate a multitude of biochemical processes by simultaneously enabling “data hiding” and modularization. This article presents recent research that embraces compartmentalization and co-location as an organizational programmatic principle in synthetic biological and biomimetic systems. In these systems, artificial vesicles and synthetic minimal cells are envisioned as nanoscale reactors for programmable biochemical synthesis and as chassis for molecular information processing. We present P systems, brane calculi, and the recently developed chemtainer calculus as formal frameworks providing data hiding and modularization and thus enabling the representation of highly complicated hierarchically organized compartmentalized reaction systems. We demonstrate how compartmentalization can greatly reduce the complexity required to implement computational functionality, and how addressable compartments permit the scaling-up of programmable chemical synthesis

Roadmap on Biological Pathways for Electronic Nanofabrication and Materials

Conventional microchip fabrication is energy and resource intensive. Thus, the discovery of new manufacturing approaches that reduce these expenditures would be highly beneficial to the semiconductor industry. In comparison, living systems construct complex nanometer-scale structures with high yields and low energy utilization. Combining the capabilities of living systems with synthetic DNA-/protein-based self-assembly may offer intriguing potential for revolutionizing the synthesis of complex sub-10 nm information processing architectures. The successful discovery of new biologically based paradigms would not only help extend the current semiconductor technology roadmap, but also offer additional potential growth areas in biology, medicine, agriculture and sustainability for the semiconductor industry. This article summarizes discussions surrounding key emerging technologies explored at the Workshop on Biological Pathways for Electronic Nanofabrication and Materials that was held on 16–17 November 2016 at the IBM Almaden Research Center in San Jose, CA

Neuronal mechanisms underlying innate and learned olfactory processing in Drosophila

Olfaction allows animals to adapt their behavior in response to different chemical cues in their environment. How does the brain efficiently discriminate different odors to drive appropriate behavior, and how does it flexibly assign value to odors to adjust behavior according to experience? This review traces neuronal mechanisms underlying these processes in adult Drosophila melanogaster from olfactory receptors to higher brain centers. We highlight neural circuit principles like lateral inhibition, segregation and integration of olfactory channels, temporal accumulation of sensory evidence, and compartmentalized synaptic plasticity underlying associative memory

Computation and programmability at the nano-bio interface

PhD ThesisThe manipulation of physical reality on the molecular level and construction of devices operating on the nanoscale has been the focal point of nanotechnology. In particular, nanotechnology based on DNA and RNA has a potential to nd applications in the eld of Synthetic Biology thanks to the inherent compatibility of nucleic acids with biological systems. Sca olded DNA origami, proposed by P. Rothemund, is one of the leading and most successful methods in which nanostructures are realised through rational programming of short 'staple' oligomers which fold a long single-stranded DNA called the 'sca old' strand into a variety of desired shapes. DNA origami already has many applications; including intelligent drug delivery, miniaturisation of logic circuits and computation in vivo. However, one of the factors that are limiting the complexity, applicability and scalability of this approach is the source of the sca old which commonly originates from viruses or phages. Furthermore, developing a robust and orthogonal interface between DNA nanotechnology and biological parts remains a signi cant challenge. The rst part of this thesis tackles these issues by challenging the fundamental as- sumption in the eld, namely that a viral sequence is to be used as the DNA origami sca old. A method is introduced for de novo generation of long synthetic sequences based on De Bruijn sequence, which has been previously proposed in combinatorics. The thesis presents a collection of algorithms which allow the construction of custom- made sequences that are uniquely addressable and biologically orthogonal (i.e. they do not code for any known biological function). Synthetic sca olds generated by these algorithms are computationally analysed and compared with their natural counter- parts with respect to: repetition in sequence, secondary structure and thermodynamic addressability. This also aids the design of wet lab experiments pursuing justi cation and veri cation of this novel approach by empirical evidence. The second part of this thesis discusses the possibility of applying evolutionary op- timisation to synthetic DNA sequences under constraints dictated by the biological interface. A multi-strand system is introduced based on an alternative approach to DNA self-assembly, which relies on strand-displacement cascades, for molecular data storage. The thesis demonstrates how a genetic algorithm can be used to generate viable solutions to this sequence optimisation problem which favours the target self- assembly con guration. Additionally, the kinetics of strand-displacement reactions are analysed with existing coarse-grained DNA models (oxDNA). This thesis is motivated by the application of scienti c computing to problems which lie on the boundary of Computer Science and the elds of DNA Nanotechnology, DNA Computing and Synthetic Biology, and thus I endeavour to the best of my ability to establish this work within the context of these disciplines

Field-Effect Sensors

This Special Issue focuses on fundamental and applied research on different types of field-effect chemical sensors and biosensors. The topics include device concepts for field-effect sensors, their modeling, and theory as well as fabrication strategies. Field-effect sensors for biomedical analysis, food control, environmental monitoring, and the recording of neuronal and cell-based signals are discussed, among other factors

On the Origin of the Living State

abstract: The origin of Life on Earth is the greatest unsolved mystery in the history of science. In spite of progress in almost every scientific endeavor, we still have no clear theory, model, or framework to understand the processes that led to the emergence of life on Earth. Understanding such a processes would provide key insights into astrobiology, planetary science, geochemistry, evolutionary biology, physics, and philosophy. To date, most research on the origin of life has focused on characterizing and synthesizing the molecular building blocks of living systems. This bottom-up approach assumes that living systems are characterized by their component parts, however many of the essential features of life are system level properties which only manifest in the collective behavior of many components. In order to make progress towards solving the origin of life new modeling techniques are needed. In this dissertation I review historical approaches to modeling the origin of life. I proceed to elaborate on new approaches to understanding biology that are derived from statistical physics and prioritize the collective properties of living systems rather than the component parts. In order to study these collective properties of living systems, I develop computational models of chemical systems. Using these computational models I characterize several system level processes which have important implications for understanding the origin of life on Earth. First, I investigate a model of molecular replicators and demonstrate the existence of a phase transition which occurs dynamically in replicating systems. I characterize the properties of the phase transition and argue that living systems can be understood as a non-equilibrium state of matter with unique dynamical properties. Then I develop a model of molecular assembly based on a ribonucleic acid (RNA) system, which has been characterized in laboratory experiments. Using this model I demonstrate how the energetic properties of hydrogen bonding dictate the population level dynamics of that RNA system. Finally I return to a model of replication in which replicators are strongly coupled to their environment. I demonstrate that this dynamic coupling results in qualitatively different evolutionary dynamics than those expected in static environments. A key difference is that when environmental coupling is included, evolutionary processes do not select a single replicating species but rather a dynamically stable community which consists of many species. Finally, I conclude with a discussion of how these computational models can inform future research on the origins of life.Dissertation/ThesisDoctoral Dissertation Physics 201

The Complexity–Stability Debate, Chemical Organization Theory, and the Identification of Non-classical Structures in Ecology

We present a novel approach to represent ecological systems using reaction networks, and show how a particular framework called chemical organization theory (COT) sheds new light on the longstanding complexity–stability debate. Namely, COT provides a novel conceptual landscape plenty of analytic tools to explore the interplay between structure and stability of ecological systems. Given a large set of species and their interactions, COT identifies, in a computationally feasible way, each and every sub-collection of species that is closed and self-maintaining. These sub-collections, called organizations, correspond to the groups of species that can survive together (co-exist) in the long-term. Thus, the set of organizations contains all the stable regimes that can possibly happen in the dynamics of the ecological system. From here, we propose to conceive the notion of stability from the properties of the organizations, and thus apply the vast knowledge on the stability of reaction networks to the complexity–stability debate. As an example of the potential of COT to introduce new mathematical tools, we show that the set of organizations can be equipped with suitable joint and meet operators, and that for certain ecological systems the organizational structure is a non-boolean lattice, providing in this way an unexpected connection between logico-algebraic structures, popular in the foundations of quantum theory, and ecology. © 2019, Springer Nature B.V.Indexación: Scopu

Synthetic DNA and RNA origami scaffolds, towards in vitro and in vivo applications

Ph. D. Thesis.Nucleic acid self-assembly is a branch of nanotechnology that consists in the use of DNA and RNA, not only as genetic material, but also as structural medium. In the last 30 years this technique developed from the simplest structures into more refined constructions that could require thousands of interacting sequences. DNA origami were presented by Rothemund as the evolution of DNA assemblies. Origami are nanostructures formed by a long single strand, the scaffold, held together by many shorter oligonucleotides, the staples. Later research showed how to functionalize the origami staples increasing the applicability. Bacteriophage genomes were used as convenient source of single stranded DNA scaffold. Today the potential biotechnological applications require to be bio-orthogonal and easily transferable from academic research to industrial ones. To solve these problems we can rely on the powerful tools of synthetic biology. I focused on the synthesis, analysis and application of synthetic scaffolds based on the combinatorial De Bruijn (DB) sequence. DB scaffolds are designed to be bio-orthogonal, uniquely addressable and thermodynamically optimized. I demonstrated their folding efficiency in DNA origami and RNA/DNA hybrid origami. DB scaffolds were analyzed in vivo in E: coli to asses their bio-orthogonality. Finally I designed a research tool to improve our knowledge on origami folding dynamics. The system includes functionalized origami encapsulated in giant unilamellar vesicles. The system allows the analysis of the origami using high throughput technologies, and can simulate a simple cell-like environment facilitating the intermediate steps towards the in vivo origami folding. With my interdisciplinary approach I contributed to the advancement of nucleic acid origami technology, taking advantage of tools and techniques from synthetic biology, origin of life, bioinformatics along with more classical scientific disciplines.Faculty of Science, Agriculture and Engineering, Newcastle University