A last-in first-out stack data structure implemented in DNA.

DNA-based memory systems are being reported with increasing frequency. However, dynamic DNA data structures able to store and recall information in an ordered way, and able to be interfaced with external nucleic acid computing circuits, have so far received little attention. Here we present an in vitro implementation of a stack data structure using DNA polymers.

Toward Full-Stack Synthetic Biology: Integrating Model Specification, Simulation, Verification, and Biological Compilation.

We present the Infobiotics Workbench (IBW), a user-friendly, scalable, and integrated computational environment for the computer-aided design of synthetic biological systems. It supports an iterative workflow that begins with specification of the desired synthetic system, followed by simulation and verification of the system in high-performance environments and ending with the eventual compilation of the system specification into suitable genetic constructs. IBW integrates , , , and features into a single software suite.

Toward Engineering Biosystems With Emergent Collective Functions.

Many complex behaviors in biological systems emerge from large populations of interacting molecules or cells, generating functions that go beyond the capabilities of the individual parts. Such collective phenomena are of great interest to bioengineers due to their robustness and scalability. However, engineering emergent collective functions is difficult because they arise as a consequence of complex multi-level feedback, which often spans many length-scales.

Pathways to cellular supremacy in biocomputing.

Synthetic biology uses living cells as the substrate for performing human-defined computations. Many current implementations of cellular computing are based on the "genetic circuit" metaphor, an approximation of the operation of silicon-based computers. Although this conceptual mapping has been relatively successful, we argue that it fundamentally limits the types of computation that may be engineered inside the cell, and fails to exploit the rich and diverse functionality available in natural living systems.

Easybiotics: a GUI for 3D physical modelling of multi-species bacterial populations.

Motivation: 3D physical modelling is a powerful computational technique that allows for the simulation of complex systems such as consortia of mixed bacterial species. The complexities in physical modelling reside in the knowledge intensive model building process and the computational expense in calculating their numerical solutions. These models can offer insights into microbiology, both in understanding natural systems and as design tools for developing novel synthetic bacterial systems.

Population Dynamics of Autocatalytic Sets in a Compartmentalized Spatial World.

Autocatalytic sets are self-sustaining and collectively catalytic chemical reaction networks which are believed to have played an important role in the origin of life. Simulation studies have shown that autocatalytic sets are, in principle, evolvable if multiple autocatalytic subsets can exist in different combinations within compartments, i.e.

Sequence selection by dynamical symmetry breaking in an autocatalytic binary polymer model.

Template-directed replication of nucleic acids is at the essence of all living beings and a major milestone for any origin of life scenario. We present an idealized model of prebiotic sequence replication, where binary polymers act as templates for their autocatalytic replication, thereby serving as each others reactants and products in an intertwined molecular ecology. Our model demonstrates how autocatalysis alters the qualitative and quantitative system dynamics in counterintuitive ways.

Simbiotics: A Multiscale Integrative Platform for 3D Modeling of Bacterial Populations.

Simbiotics is a spatially explicit multiscale modeling platform for the design, simulation and analysis of bacterial populations. Systems ranging from planktonic cells and colonies, to biofilm formation and development may be modeled. Representation of biological systems in Simbiotics is flexible, and user-defined processes may be in a variety of forms depending on desired model abstraction.

Designing Uniquely Addressable Bio-orthogonal Synthetic Scaffolds for DNA and RNA Origami.

Nanotechnology and synthetic biology are rapidly converging, with DNA origami being one of the leading bridging technologies. DNA origami was shown to work well in a wide array of biotic environments. However, the large majority of extant DNA origami scaffolds utilize bacteriophages or plasmid sequences thus severely limiting its future applicability as a bio-orthogonal nanotechnology platform.

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 MATCHIT automaton: exploiting compartmentalization for the synthesis of branched polymers.

We propose an automaton, a theoretical framework that demonstrates how to improve the yield of the synthesis of branched chemical polymer reactions. This is achieved by separating substeps of the path of synthesis into compartments. We use chemical containers (chemtainers) to carry the substances through a sequence of fixed successive compartments.

Specific and reversible DNA-directed self-assembly of oil-in-water emulsion droplets.

Higher-order structures that originate from the specific and reversible DNA-directed self-assembly of microscopic building blocks hold great promise for future technologies. Here, we functionalized biotinylated soft colloid oil-in-water emulsion droplets with biotinylated single-stranded DNA oligonucleotides using streptavidin as an intermediary linker. We show the components of this modular linking system to be stable and to induce sequence-specific aggregation of binary mixtures of emulsion droplets.

Coarse graining and scaling in dissipative particle dynamics.

Dissipative particle dynamics (DPD) is now a well-established method for simulating soft matter systems. However, its applicability was recently questioned because some investigations showed an upper coarse-graining limit that would prevent the applicability of the method to the whole mesoscopic range. This article aims to re-establish DPD as a truly mesoscopic method by analyzing the problems reported by other authors and by presenting a scaling scheme that allows one to apply DPD simulations directly to any desired length scale.

Life cycle of a minimal protocell--a dissipative particle dynamics study.

Cross-reactions and other systematic difficulties generated by the coupling of functional chemical subsystems pose the largest challenge for assembling a viable protocell in the laboratory. Our current work seeks to identify and clarify such key issues as we represent and analyze in simulation a full implementation of a minimal protocell. Using a 3D dissipative particle dynamics simulation method, we are able to address the coupled diffusion, self-assembly, and chemical reaction processes required to model a full life cycle of a protocell composed of coupled genetic, metabolic, and container subsystems.

Minimal model of self-replicating nanocells: a physically embodied information-free scenario.

The building of minimal self-reproducing systems with a physical embodiment (generically called protocells) is a great challenge, with implications for both theory and applied sciences. Although the classical view of a living protocell assumes that it includes information-carrying molecules as an essential ingredient, a dividing cell-like structure can be built from a metabolism-container coupled system only. An example of such a system, modelled with dissipative particle dynamics, is presented here.