Parallel biomolecular computation on surfaces with advanced finite automata

DNA Computing: Concepts for Medical Applications

The branch of informatics that deals with construction and operation of computers built of DNA, is one of the research directions which investigates issues related to the use of DNA as hardware and software. This concept assumes the use of DNA computers due to their biological origin mainly for intelligent, personalized and targeted diagnostics frequently related to therapy. Important elements of this concept are (1) the retrieval of unique DNA sequences using machine learning methods and, based on the results of this process, (2) the construction/design of smart diagnostic biochip projects. The authors of this paper propose a new concept of designing diagnostic biochips, the key elements of which are machine-learning methods and the concept of biomolecular queue automata. This approach enables the scheduling of computational tasks at the molecular level by sequential events of cutting and ligating DNA molecules. We also summarize current challenges and perspectives of biomolecular computer application and machine-learning approaches using DNA sequence data mining.

DNA nanotechnology-empowered finite state machines

A finite state machine (FSM, or automaton) is an abstract machine that can switch among a finite number of states in response to temporally ordered inputs, which allows storage and processing of information in an order-sensitive manner. In recent decades, DNA molecules have been actively exploited to develop information storage and nanoengineering materials, which hold great promise for smart nanodevices and nanorobotics under the framework of FSM. In this review, we summarize recent progress in utilizing DNA self-assembly and DNA nanostructures to implement FSMs. We describe basic principles for representative DNA FSM prototypes and highlight their advantages and potential in diverse applications. The challenges in this field and future directions have also been discussed.

Biomolecular computers with multiple restriction enzymes

The development of conventional, silicon-based computers has several limitations, including some related to the Heisenberg uncertainty principle and the von Neumann “bottleneck”. Biomolecular computers based on DNA and proteins are largely free of these disadvantages and, along with quantum computers, are reasonable alternatives to their conventional counterparts in some applications. The idea of a DNA computer proposed by Ehud Shapiro’s group at the Weizmann Institute of Science was developed using one restriction enzyme as hardware and DNA fragments (the transition molecules) as software and input/output signals. This computer represented a two-state two-symbol finite automaton that was subsequently extended by using two restriction enzymes. In this paper, we propose the idea of a multistate biomolecular computer with multiple commercially available restriction enzymes as hardware. Additionally, an algorithmic method for the construction of transition molecules in the DNA computer based on the use of multiple restriction enzymes is presented. We use this method to construct multistate, biomolecular, nondeterministic finite automata with four commercially available restriction enzymes as hardware. We also describe an experimental applicaton of this theoretical model to a biomolecular finite automaton made of four endonucleases.

A detailed experimental study of a DNA computer with two endonucleases

Great advances in biotechnology have allowed the construction of a computer from DNA. One of the proposed solutions is a biomolecular finite automaton, a simple two-state DNA computer without memory, which was presented by Ehud Shapiro's group at the Weizmann Institute of Science. The main problem with this computer, in which biomolecules carry out logical operations, is its complexity - increasing the number of states of biomolecular automata. In this study, we constructed (in laboratory conditions) a six-state DNA computer that uses two endonucleases (e.g. AcuI and BbvI) and a ligase. We have presented a detailed experimental verification of its feasibility. We described the effect of the number of states, the length of input data, and the nondeterminism on the computing process. We also tested different automata (with three, four, and six states) running on various accepted input words of different lengths such as ab, aab, aaab, ababa, and of an unaccepted word ba. Moreover, this article presents the reaction optimization and the methods of eliminating certain biochemical problems occurring in the implementation of a biomolecular DNA automaton based on two endonucleases.

Assessing the potential of surface-immobilized molecular logic machines for integration with solid state technology

Molecular computation with DNA has great potential for low power, highly parallel information processing in a biological or biochemical context. However, significant challenges remain for the field of DNA computation. New technology is needed to allow multiplexed label-free readout and to enable regulation of molecular state without addition of new DNA strands. These capabilities could be provided by hybrid bioelectronic systems in which biomolecular computing is integrated with conventional electronics through immobilization of DNA machines on the surface of electronic circuitry. Here we present a quantitative experimental analysis of a surface-immobilized OR gate made from DNA and driven by strand displacement. The purpose of our work is to examine the performance of a simple representative surface-immobilized DNA logic machine, to provide valuable information for future work on hybrid bioelectronic systems involving DNA devices. We used a quartz crystal microbalance to examine a DNA monolayer containing approximately 5×10(11)gatescm(-2), with an inter-gate separation of approximately 14nm, and we found that the ensemble of gates took approximately 6min to switch. The gates could be switched repeatedly, but the switching efficiency was significantly degraded on the second and subsequent cycles when the binding site for the input was near to the surface. Otherwise, the switching efficiency could be 80% or better, and the power dissipated by the ensemble of gates during switching was approximately 0.1nWcm(-2), which is orders of magnitude less than the power dissipated during switching of an equivalent array of transistors. We propose an architecture for hybrid DNA-electronic systems in which information can be stored and processed, either in series or in parallel, by a combination of molecular machines and conventional electronics. In this architecture, information can flow freely and in both directions between the solution-phase and the underlying electronics via surface-immobilized DNA machines that provide the interface between the molecular and electronic domains.

The laws of natural deduction in inference by DNA computer

We present a DNA-based implementation of reaction system with molecules encoding elements of the propositional logic, that is, propositions and formulas. The protocol can perform inference steps using, for example, modus ponens and modus tollens rules and de Morgan's laws. The set of the implemented operations allows for inference of formulas using the laws of natural deduction. The system can also detect whether a certain proposition a can be deduced from the basic facts and given rules. The whole protocol is fully autonomous; that is, after introducing the initial set of molecules, no human assistance is needed. Only one restriction enzyme is used throughout the inference process. Unlike some other similar implementations, our improved design allows representing simultaneously a fact a and its negation ~a, including special reactions to detect the inconsistency, that is, a simultaneous occurrence of a fact and its negation. An analysis of correctness, completeness, and complexity is included.

The biological microprocessor, or how to build a computer with biological parts

Systemics, a revolutionary paradigm shift in scientific thinking, with applications in systems biology, and synthetic biology, have led to the idea of using silicon computers and their engineering principles as a blueprint for the engineering of a similar machine made from biological parts. Here we describe these building blocks and how they can be assembled to a general purpose computer system, a biological microprocessor. Such a system consists of biological parts building an input / output device, an arithmetic logic unit, a control unit, memory, and wires (busses) to interconnect these components. A biocomputer can be used to monitor and control a biological system.

Biologically relevant molecular transducer with increased computing power and iterative abilities

As computing devices, which process data and interconvert information, transducers can encode new information and use their output for subsequent computing, offering high computational power that may be equivalent to a universal Turing machine. We report on an experimental DNA-based molecular transducer that computes iteratively and produces biologically relevant outputs. As a proof of concept, the transducer accomplished division of numbers by 3. The iterative power was demonstrated by a recursive application on an obtained output. This device reads plasmids as input and processes the information according to a predetermined algorithm, which is represented by molecular software. The device writes new information on the plasmid using hardware that comprises DNA-manipulating enzymes. The computation produces dual output: a quotient, represented by newly encoded DNA, and a remainder, represented by E. coli phenotypes. This device algorithmically manipulates genetic codes.

Biomolecular computing systems: principles, progress and potential

The task of information processing, or computation, can be performed by natural and man-made 'devices'. Man-made computers are made from silicon chips, whereas natural 'computers', such as the brain, use cells and molecules. Computation also occurs on a much smaller scale in regulatory and signalling pathways in individual cells and even within single biomolecules. Indeed, much of what we recognize as life results from the remarkable capacity of biological building blocks to compute in highly sophisticated ways. Rational design and engineering of biological computing systems can greatly enhance our ability to study and to control biological systems. Potential applications include tissue engineering and regeneration and medical treatments. This Review introduces key concepts and discusses recent progress that has been made in biomolecular computing.

Engineering bacteria to solve the Burnt Pancake Problem

Background

We investigated the possibility of executing DNA-based computation in living cells by engineering Escherichia coli to address a classic mathematical puzzle called the Burnt Pancake Problem (BPP). The BPP is solved by sorting a stack of distinct objects (pancakes) into proper order and orientation using the minimum number of manipulations. Each manipulation reverses the order and orientation of one or more adjacent objects in the stack. We have designed a system that uses site-specific DNA recombination to mediate inversions of genetic elements that represent pancakes within plasmid DNA.

Results

Inversions (or "flips") of the DNA fragment pancakes are driven by the Salmonella typhimurium Hin/hix DNA recombinase system that we reconstituted as a collection of modular genetic elements for use in E. coli. Our system sorts DNA segments by inversions to produce different permutations of a promoter and a tetracycline resistance coding region; E. coli cells become antibiotic resistant when the segments are properly sorted. Hin recombinase can mediate all possible inversion operations on adjacent flippable DNA fragments. Mathematical modeling predicts that the system reaches equilibrium after very few flips, where equal numbers of permutations are randomly sorted and unsorted. Semiquantitative PCR analysis of in vivo flipping suggests that inversion products accumulate on a time scale of hours or days rather than minutes.

Conclusion

The Hin/hix system is a proof-of-concept demonstration of in vivo computation with the potential to be scaled up to accommodate larger and more challenging problems. Hin/hix may provide a flexible new tool for manipulating transgenic DNA in vivo.

Towards biomedical applications for nucleic acid nanodevices

DNA and RNA can be used to construct artificial nanodevices with strong potential for future biomedical applications. DNA nanodevices can function as biosensors, which detect and report the presence of proteins and naturally occurring nucleic acids, such as mRNA or microRNAs. Complex sensors can be realized by supporting DNA devices with DNA-based information processing. Artificial DNA-based reaction networks can be created that amplify molecular signals or evaluate logical functions to report the simultaneous presence of several disease-related molecules. Other applications for DNA nanodevices are found in controlled release and drug delivery. DNA can be used to build nanocontainers for drugs or switchable hydrogels, which can trap and release compounds. For in vivo applications of DNA nanodevices, techniques for efficient packaging and delivery have been developed and the first examples of intracellular RNA-based nanodevices have already been demonstrated.

A Programmable Biomolecular Computing Machine with Bacterial Phenotype Output

The main advantage of autonomous biomolecular computing devices over electronic computers is their ability to interact directly with biological systems. No interface is required since all components of molecular computers, including hardware, software, input, and output are molecules that interact in solution along a cascade of programmable chemical events. Here, we demonstrate for the first time that the output of a computation preduced by a molecular finite automaton can be a visible bacterial phenotype. Our 2-symbol-2-state finite automaton utilized linear double-stranded DNA inputs that were prepared by inserting a string of six base pair symbols into the lacZ gene on the pUC18 plasmid. The computation resulted in a circular plasmid that differed from the original pUC18 by either a 9 base pair (accepting state) or 11 base pair insert (unaccepting state) within the lacZ alpha region gene. Upon transformation and expression of the resultant plasmids in E. coli, the accepting state was represented by production of functional beta-galactosidase and formation of blue colonies on X-gal medium. In contrast, the unaccepting state was represented by white colonies due to a shift in the open reading frame of lacZ.

Fabricating RNA microarrays with RNA-DNA surface ligation chemistry

A novel surface attachment strategy that utilizes RNA-DNA surface ligation chemistry to create renewable RNA microarrays from single-stranded DNA (ssDNA) microarrays on gold surfaces is demonstrated. The enzyme T4 DNA ligase was used to catalyze the formation of a phosphodiester bond between 5'-phosphate-modified ssDNA attached to the surface and the 3'-hydroxyl group of unlabeled RNA molecules from solution in the presence of a complementary template DNA strand. Surface plasmon resonance imaging (SPRI) measurements were performed to characterize the ligation process as well as to verify the bioactivity of the ssRNA microarray in terms of (i) the hybridization adsorption of complementary DNA onto the RNA array to form a surface RNA-DNA heteroduplex and (ii) the hydrolysis of the RNA microarrays with either ribonuclease S or ribonuclease H (RNase H). The hydrolysis of the surface-bound RNA with RNase H required the presence of a surface heteroduplex and, upon completion, regenerated the original 5'-phosphate-terminated ssDNA array elements. These ssDNA array elements could be ligated again to create a new RNA microarray. These RNA microarrays can be used in the study of RNA-protein/RNA/aptamer bioaffinity interactions and for the enzymatically amplified SPRI detection of DNA in the presence of RNase H.

Differential dependence on DNA ligase of type II restriction enzymes: A practical way toward ligase-free DNA automaton

DNA computing study is a new paradigm in computer science and biological computing fields. As one of DNA computing approaches, DNA automaton is composed of the hardware, input DNA molecule and state transition molecules. By now restriction enzymes are key hardware for DNA computing automaton. It has been found that DNA computing efficiency may be independent on DNA ligases when type IIS restriction enzymes like FokI are used as hardware. In this study, we compared FokI with four other distinct enzymes HgaI, BsmFI, BbsI, and BseMII, and found their differential independence on T4 DNA ligase when performing automaton reactions. Since DNA automaton is a potential powerful tool to tackle gene relationship in genomic network scale, the feasible ligase-free DNA automaton may set an initial base to develop functional DNA automata for various DNA technology development and implications in genetics study in the near future.

A modular DNA signal translator for the controlled release of a protein by an aptamer

Owing to the intimate linkage of sequence and structure in nucleic acids, DNA is an extremely attractive molecule for the development of molecular devices, in particular when a combination of information processing and chemomechanical tasks is desired. Many of the previously demonstrated devices are driven by hybridization between DNA 'effector' strands and specific recognition sequences on the device. For applications it is of great interest to link several of such molecular devices together within artificial reaction cascades. Often it will not be possible to choose DNA sequences freely, e.g. when functional nucleic acids such as aptamers are used. In such cases translation of an arbitrary 'input' sequence into a desired effector sequence may be required. Here we demonstrate a molecular 'translator' for information encoded in DNA and show how it can be used to control the release of a protein by an aptamer using an arbitrarily chosen DNA input strand. The function of the translator is based on branch migration and the action of the endonuclease FokI. The modular design of the translator facilitates the adaptation of the device to various input or output sequences.

Survey of the year 2005 commercial optical biosensor literature

We identified 1113 articles (103 reviews, 1010 primary research articles) published in 2005 that describe experiments performed using commercially available optical biosensors. While this number of publications is impressive, we find that the quality of the biosensor work in these articles is often pretty poor. It is a little disappointing that there appears to be only a small set of researchers who know how to properly perform, analyze, and present biosensor data. To help focus the field, we spotlight work published by 10 research groups that exemplify the quality of data one should expect to see from a biosensor experiment. Also, in an effort to raise awareness of the common problems in the biosensor field, we provide side-by-side examples of good and bad data sets from the 2005 literature.