Biomedical subjects

Erik Winfree

Publications and source records attributed to Erik Winfree.

8 recordsLinked to original sources

PubMed2006

Construction of an in vitro bistable circuit from synthetic transcriptional switches.

Information processing using biochemical circuits is essential for survival and reproduction of natural organisms. As stripped-down analogs of genetic regulatory networks in cells, we engineered artificial transcriptional networks consisting of synthetic DNA switches, regulated by RNA signals acting as transcription repressors, and two enzymes, bacteriophage T7 RNA polymerase and Escherichia coli ribonuclease H. The synthetic switch design is modular with programmable connectivity and allows dynamic control of RNA signals through enzyme-mediated production and degradation. The switches support sharp and adjustable thresholds using a competitive hybridization mechanism, allowing arbitrary analog or digital circuits to be created in principle. As an example, we constructed an in vitro bistable memory by wiring together two synthetic switches and performed a systematic quantitative characterization. Good agreement between experimental data and a simple mathematical model was obtained for switch input/output functions, phase plane trajectories, and the bifurcation diagram for bistability. Construction of larger synthetic circuits provides a unique opportunity for evaluating model inference, prediction, and design of complex biochemical systems and could be used to control nanoscale devices and artificial cells.

Escherichia coli↗

PubMed2006

Enzyme-free nucleic acid logic circuits.

Biological organisms perform complex information processing and control tasks using sophisticated biochemical circuits, yet the engineering of such circuits remains ineffective compared with that of electronic circuits. To systematically create complex yet reliable circuits, electrical engineers use digital logic, wherein gates and subcircuits are composed modularly and signal restoration prevents signal degradation. We report the design and experimental implementation of DNA-based digital logic circuits. We demonstrate AND, OR, and NOT gates, signal restoration, amplification, feedback, and cascading. Gate design and circuit construction is modular. The gates use single-stranded nucleic acids as inputs and outputs, and the mechanism relies exclusively on sequence recognition and strand displacement. Biological nucleic acids such as microRNAs can serve as inputs, suggesting applications in biotechnology and bioengineering.

Animals↗

PubMed2006

Catalyzed relaxation of a metastable DNA fuel.

Practically all of life's molecular processes, from chemical synthesis to replication, involve enzymes that carry out their functions through the catalytic transformation of metastable fuels into waste products. Catalytic control of reaction rates will prove to be as useful and ubiquitous in nucleic-acid-based engineering as it is in biology. Here we report a metastable DNA "fuel" and a corresponding DNA "catalyst" that improve upon the original hybridization-based catalyst system (Turberfield et al. Phys. Rev. Lett. 90, 118102-1-118102-4) by more than 2 orders of magnitude. This is achieved by identifying and purifying a fuel with a kinetically trapped metastable configuration consisting of a "kissing loop" stabilized by flanking helical domains; the catalyst strand acts by opening a helical domain and allowing the complex to relax to its ground state by a multistep pathway. The improved fuel/catalyst system shows a roughly 5000-fold acceleration of the uncatalyzed reaction, with each catalyst molecule capable of turning over in excess of 40 substrates. With k(cat)/K(M) approximately 10(7)/M/min, comparable to many protein enzymes and ribozymes, this fuel system becomes a viable component enabling future DNA-based synthetic molecular machines and logic circuits. As an example, we designed and characterized a signal amplifier based on the fuel-catalyst system. The amplifier uses a single strand of DNA as input and releases a second strand with unrelated sequence as output. A single input strand can catalytically trigger the release of more than 10 output strands.

Catalysis↗

PubMed2005

Two computational primitives for algorithmic self-assembly: copying and counting.

Copying and counting are useful primitive operations for computation and construction. We have made DNA crystals that copy and crystals that count as they grow. For counting, 16 oligonucleotides assemble into four DNA Wang tiles that subsequently crystallize on a polymeric nucleating scaffold strand, arranging themselves in a binary counting pattern that could serve as a template for a molecular electronic demultiplexing circuit. Although the yield of counting crystals is low, and per-tile error rates in such crystals is roughly 10%, this work demonstrates the potential of algorithmic self-assembly to create complex nanoscale patterns of technological interest. A subset of the tiles for counting form information-bearing DNA tubes that copy bit strings from layer to layer along their length.

Algorithms↗

PubMed2004

Design and characterization of programmable DNA nanotubes.

DNA self-assembly provides a programmable bottom-up approach for the synthesis of complex structures from nanoscale components. Although nanotubes are a fundamental form encountered in tile-based DNA self-assembly, the factors governing tube structure remain poorly understood. Here we report and characterize a new type of nanotube made from DNA double-crossover molecules (DAE-E tiles). Unmodified tubes range from 7 to 20 nm in diameter (4 to 10 tiles in circumference), grow as long as 50 microm with a persistence length of approximately 4 microm, and can be programmed to display a variety of patterns. A survey of modifications (1) confirms the importance of sticky-end stacking, (2) confirms the identity of the inside and outside faces of the tubes, and (3) identifies features of the tiles that profoundly affect the size and morphology of the tubes. Supported by these results, nanotube structure is explained by a simple model based on the geometry and energetics of B-form DNA.

DNA↗

PubMed2004

Algorithmic self-assembly of DNA Sierpinski triangles.

Algorithms and information, fundamental to technological and biological organization, are also an essential aspect of many elementary physical phenomena, such as molecular self-assembly. Here we report the molecular realization, using two-dimensional self-assembly of DNA tiles, of a cellular automaton whose update rule computes the binary function XOR and thus fabricates a fractal pattern--a Sierpinski triangle--as it grows. To achieve this, abstract tiles were translated into DNA tiles based on double-crossover motifs. Serving as input for the computation, long single-stranded DNA molecules were used to nucleate growth of tiles into algorithmic crystals. For both of two independent molecular realizations, atomic force microscopy revealed recognizable Sierpinski triangles containing 100-200 correct tiles. Error rates during assembly appear to range from 1% to 10%. Although imperfect, the growth of Sierpinski triangles demonstrates all the necessary mechanisms for the molecular implementation of arbitrary cellular automata. This shows that engineered DNA self-assembly can be treated as a Turing-universal biomolecular system, capable of implementing any desired algorithm for computation or construction tasks.

Algorithms↗

PubMed2004

Paradigms for computational nucleic acid design.

The design of DNA and RNA sequences is critical for many endeavors, from DNA nanotechnology, to PCR-based applications, to DNA hybridization arrays. Results in the literature rely on a wide variety of design criteria adapted to the particular requirements of each application. Using an extensively studied thermodynamic model, we perform a detailed study of several criteria for designing sequences intended to adopt a target secondary structure. We conclude that superior design methods should explicitly implement both a positive design paradigm (optimize affinity for the target structure) and a negative design paradigm (optimize specificity for the target structure). The commonly used approaches of sequence symmetry minimization and minimum free-energy satisfaction primarily implement negative design and can be strengthened by introducing a positive design component. Surprisingly, our findings hold for a wide range of secondary structures and are robust to modest perturbation of the thermodynamic parameters used for evaluating sequence quality, suggesting the feasibility and ongoing utility of a unified approach to nucleic acid design as parameter sets are refined further. Finally, we observe that designing for thermodynamic stability does not determine folding kinetics, emphasizing the opportunity for extending design criteria to target kinetic features of the energy landscape.

Algorithms↗

PubMed2002

Protein design is NP-hard.

Biologists working in the area of computational protein design have never doubted the seriousness of the algorithmic challenges that face them in attempting in silico sequence selection. It turns out that in the language of the computer science community, this discrete optimization problem is NP-hard. The purpose of this paper is to explain the context of this observation, to provide a simple illustrative proof and to discuss the implications for future progress on algorithms for computational protein design.

Algorithms↗