DNA computing

Biocomputers can be an alternative for traditional "silicon-based" computers, which continuous development may be limited due to further miniaturization (imposed by the Heisenberg Uncertainty Principle) and increasing the amount of information between the central processing unit and the main memory (von Neuman bottleneck). The idea of DNA computing came true for the first time in 1994, when Adleman solved the Hamiltonian Path Problem using short DNA oligomers and DNA ligase. In the early 2000s a series of biocomputer models was presented with a seminal work of Shapiro and his colleguas who presented molecular 2 state finite automaton, in which the restriction enzyme, FokI, constituted hardware and short DNA oligomers were software as well as input/output signals. DNA molecules provided also energy for this machine. DNA computing can be exploited in many applications, from study on the gene expression pattern to diagnosis and therapy of cancer. The idea of DNA computing is still in progress in research both in vitro and in vivo and at least promising results of these research allow to have a hope for a breakthrough in the computer science.     

Introduction to cloud computing: platforms and solutions

This special issue of the cluster computing journal will feature articles that discuss tools and applications for cloud computing. Specifically, it aims at delivering the state-of-the-art research on current cloud computing tools topics, and at promoting the cloud applications discipline by bringing to the attention of the community novel problems that must be investigated.     

New computing paradigms suggested by DNA computing: computing by carving

Inspired by the experiments in the emerging area of DNA computing, a somewhat unusual type of computation strategy was recently proposed by one of us: to generate a (large) set of candidate solutions of a problem, then remove the non-solutions such that what remains is the set of solutions. This has been called a computation by carving. This idea leads both to a speculation with possible important consequences--computing non-recursively enumerable languages--and to interesting theoretical computer science (formal language) questions.     

Ligation errors in DNA computing

DNA computing is a novel method of computing proposed by Adleman (1994), in which the data is encoded in the sequences of oligonucleotides. Massively parallel reactions between oligonucleotides are expected to make it possible to solve huge problems. In this study, reliability of the ligation process employed in the DNA computing is tested by estimating the error rate at which wrong oligonucleotides are ligated. Ligation of wrong oligonucleotides would result in a wrong answer in the DNA computing. The dependence of the error rate on the number of mismatches between oligonucleotides and on the combination of bases is investigated.     

The bounded complexity of DNA computing

This paper proposes a new approach to analyzing DNA-based algorithms in molecular computation. Such protocols are characterized abstractly by: encoding, tube operations and extraction. Implementation of these approaches involves encoding in a multiset of molecules that are assembled in a tube having a number of physical attributes. The physico-chemical state of a tube can be changed by a prescribed number of elementary operations. Based on realistic definitions of these elementary operations, we define complexity of a DNA-based algorithm using the physico-chemical property of each operation. We show that new algorithms for Hamiltonian path are about twice as efficient as Adleman's original one and that a recent algorithm for Max-Clique provides a similar increase in efficiency. Consequences of this approach to tube complexity and DNA computing are discussed.     

Production of random DNA oligomers for scalable DNA computing

While remarkably complex networks of connected DNA molecules can form from a relatively small number of distinct oligomer strands, a large computational space created by DNA reactions would ultimately require the use of many distinct DNA strands. The automatic synthesis of this many distinct strands is economically prohibitive. We present here a new approach to producing distinct DNA oligomers based on the polymerase chain reaction (PCR) amplification of a few random template sequences. As an example, we designed a DNA template sequence consisting of a 50-mer random DNA segment flanked by two 20-mer invariant primer sequences. Amplification of a dilute sample containing about 30 different template molecules allows us to obtain around 10¹¹ copies of these molecules and their complements. We demonstrate the use of these amplicons to implement some of the vector operations that will be required in a DNA implementation of an analog neural network.     

DNA computing the Hamiltonian path problem

The directed Hamiltonian path (DHP) problem is one of the hard computational problems for which there is no practical algorithm on a conventional computer available. Many problems, including the traveling sales person problem and the longest path problem, can be translated into the DHP problem, which implies that an algorithm for DHP can also solve all the translated problems. To study the robustness of the laboratory protocol of the pioneering DNA computing for the DHP problem performed by Leonard Adleman (1994), we investigated how the graph size, multiplicity of the Hamiltonian paths, and the size of oligonucleotides that encode the vertices would affect the laboratory procedures. We applied Adleman's protocol with 18-mer oligonucleotide per node to a graph with 8 vertices and 14 edges containing two Hamiltonian paths (Adleman used 20-mer oligonucleotides for a graph with 7 nodes, 14 edges and one Hamiltonian path). We found that depending on the graph characteristics such as the number of short cycles, the oligonucleotide size, and the hybridization conditions that used to encode the graph, the protocol should be executed with different parameters from Adleman's.     

Three dimensional DNA structures in computing

We show that 3-dimensional graph structures can be used for solving computational problems with DNA molecules. Vertex building blocks consisting of k-armed (k = 3 or 4) branched junction molecules are used to form graphs. We present procedures for the 3-SAT and 3-vertex-colorability problems. Construction of one graph structure (in many copies) is sufficient to determine the solution to the problem. In our proposed procedure for 3-SAT, the number of steps required is equal to the number of variables in the formula. For the 3-vertex-colorability problem, the procedure requires a constant number of steps regardless of the size of the graph.     

DNA computing using single-molecule hybridization detection

DNA computing aims at using nucleic acids for computing. Since micromolar DNA solutions can act as billions of parallel nanoprocessors, DNA computers can in theory solve optimization problems that require vast search spaces. However, the actual parallelism currently being achieved is at least a hundred million-fold lower than the number of DNA molecules used. This is due to the quantity of DNA molecules of one species that is required to produce a detectable output to the computations. In order to miniaturize the computation and considerably reduce the amount of DNA needed, we have combined DNA computing with single-molecule detection. Reliable hybridization detection was achieved at the level of single DNA molecules with fluorescence cross-correlation spectroscopy. To illustrate the use of this approach, we implemented a DNA-based computation and solved a 4-variable 4-clause instance of the computationally hard Satisfiability (SAT) problem.     

Immunity in society: diverse solutions to common problems

Understanding how organisms fight infection has been a central focus of scientific research and medicine for the past couple of centuries, and a perennial object of trial and error by humans trying to mitigate the burden of disease. Vaccination success relies upon the exposure of susceptible individuals to pathogen constituents that do not cause (excessive) pathology and that elicit specific immune memory. Mass vaccination allows us to study how immunity operates at the group level; denser populations are more prone to transmitting disease between individuals, but once a critical proportion of the population becomes immune, "herd immunity" emerges. In social species, the combination of behavioural control of infection--e.g., segregation of sick individuals, disposal of the dead, quality assessment of food and water--and aggregation of immune individuals can protect non-immune members from disease. While immune specificity and memory are well understood to underpin immunisation in vertebrates, it has been somewhat surprising to find similar phenomena in invertebrates, which lack the vertebrate molecular mechanisms deemed necessary for immunisation. Indeed, reports showing alternative forms of immune memory are accumulating in invertebrates. In this issue of PLoS Biology, Konrad et al. present an example of fungus-specific immune responses in social ants that lead to the active immunisation of nestmates by infected individuals. These findings join others in showing how organisms evolved diverse mechanisms that fulfil common functions, namely the discrimination between pathogens, the transfer of immunity between related individuals, and the group-level benefits of immunisation.     

The anatomy of organogenesis: Novel solutions to old problems

Understanding anatomical aspects of mammalian organ development, in both normal and mutant animals, is important for basic biology and also for regenerative medicine and tissue engineering. The size and complexity of developing organs, together with variations in their detailed anatomy, has made the obtaining of high-resolution time-courses of anatomical change difficult to obtain. The fact that organ development tends to use the same genes as early embryogenesis also makes genetic manipulation difficult, as so many mutant embryos die before organogenesis begins. These problems have seriously hampered the study of organogenesis. Here, we describe three significant advances that promise solutions: (1) the production of GFP-reporter mice that can be used for high-resolution live-imaging of small tissues as they grow, (2) RNA interference, which allows the manipulation of specific genes at any stage of organ development, and (3) optical projection tomography, which allows medium-resolution three-dimensional images of complete embryos to be obtained easily. We finish by looking ahead to the prospects of uniting these three technologies to allow accurate, high-throughput screening of mutants and automated comparison of biological data with computer predictions.     

The anatomy of organogenesis: novel solutions to old problems

Understanding anatomical aspects of mammalian organ development, in both normal and mutant animals, is important for basic biology and also for regenerative medicine and tissue engineering. The size and complexity of developing organs, together with variations in their detailed anatomy, has made the obtaining of high-resolution time-courses of anatomical change difficult to obtain. The fact that organ development tends to use the same genes as early embryogenesis also makes genetic manipulation difficult, as so many mutant embryos die before organogenesis begins. These problems have seriously hampered the study of organogenesis. Here, we describe three significant advances that promise solutions: (1) the production of GFP-reporter mice that can be used for high-resolution live-imaging of small tissues as they grow, (2) RNA interference, which allows the manipulation of specific genes at any stage of organ development, and (3) optical projection tomography, which allows medium-resolution three-dimensional images of complete embryos to be obtained easily. We finish by looking ahead to the prospects of uniting these three technologies to allow accurate, high-throughput screening of mutants and automated comparison of biological data with computer predictions.     

Optically programming DNA computing in microflow reactors

The programmability and the integration of biochemical processing protocols are addressed for DNA computing using photochemical and microsystem techniques. A magnetically switchable selective transfer module (STM) is presented which implements the basic sequence-specific DNA filtering operation under constant flow. Secondly, a single steady flow system of STMs is presented which solves an arbitrary instance of the maximal clique problem of given maximum size N. Values of N up to about 100 should be achievable with current lithographic techniques. The specific problem is encoded in an initial labeling pattern of each module with one of 2N DNA oligonucleotides, identical for all instances of maximal clique. Thirdly, a method for optically programming the DNA labeling process via photochemical lithography is proposed, allowing different problem instances to be specified. No hydrodynamic switching of flows is required during operation -- the STMs are synchronously clocked by an external magnet. An experimental implementation of this architecture is under construction and will be reported elsewhere.     

Fidelity of enzymatic ligation for DNA computing.

We describe a convenient assay for rapid qualitative evaluation of hybridization/ligation fidelity. The approach uses randomized probe strands of DNA and restriction enzyme digestion after amplification of reaction products by the polymerase chain reaction (PCR). We report ligation efficiencies and fidelities of two DNA ligases, T4 DNA ligase and Thermus aquaticus (Taq) DNA ligase, over a range of temperatures.