Catálogo de publicaciones - libros

Whiplash PCR-based methods of biomolecular computation (BMC), while highly-versatile in principle, are well-known to suffer from a simple but serious form of self-poisoning known as back-hybridization. In this work, an optimally re-engineered WPCR-based architecture, (DWPCR) is proposed and experimentally validated. DWPCR’s new biostep, which is based on the primer-targeted strand-displacement of back-hybridized hairpins, renders the most recently implemented rule-block of each strand unavailable, abolishing back-hybridization after each round of extension. In addition to attaining a near-ideal efficiency, DWPCR’s ability to support isothermal operation at physiological temperatures eliminates the need for thermal cycling, and opens the door for potential biological applications. DWPCR should also be capable of supporting programmable exon shuffling, allowing XWPCR, a proposed method for programmable protein evolution, to more closely imitate natural evolving systems. DWPCR is expected to realize a highly-efficient, versatile platform for routine and efficient massively parallel BMC.

The MethyLogic method performs flexible and reversible modification of DNA in order to establish the logical value of true or false for a set of clauses. It combines both the biological meaning and experimental procedure with the logical implementation of the basic Boolean operators: OR, AND, and NOT. The original feature of methylation logic, MethyLogic, is the use of the reversibility of DNA methylation of cytosine and adenine. Logic variables can be negated by reversing the DNA methylation status. We introduce four implementation scenarios: three of them use methyl-sensitive restriction enzymes and the fourth uses methyl-binding proteins. Encoding can use either single or double-stranded DNA. In addition, we show how to solve a three variable SAT problem and how to implement a logic circuit.

An enormous amount of data such as genomic data can be stored into DNA molecules as base sequences. DNA database is important for organizing and maintaining these data, because extracted data from DNA database can be directly manipulated by chemical reactions. In this paper, we develop a DNA relational database with a simple data model and realize a computational model (relational algebra) of data manipulation as a sequence of chemical experiments. By using the developed database, it is shown that we can execute query operations based on the contents of data (the values of attributes). Furthermore, we propose a conversion scheme of query input to a series of experiment operations.

Due to the multi-state nature of autonomous computing systems, it is important to develop a simulation model which accounts for process coupling, and allows the precise prediction of the behavior of a composite system formed by a series of competing reactions, in which each intermediate step is difficult to probe. In this work, the statistical thermodynamic apparatus for predicting the efficiency of DNA hairpin-based computers is validated experimentally. The model system employed is a simple competitive folding system, formed by two competing hairpin structures (sub-optimal vs. optimal), with the intent of testing the ability to predict the efficiency of target structure formation in the presence of a non-target structure. System behavior was characterized via a set of fluorescence measurement experiments, to directly determine the fractional occupancy of target structures versus temperature. Predicted and experimental behaviors are compared for both the melting of each of the two isolated hairpin structures (control), and the efficiency of the competitive composite system. Results indicate that the applied equilibrium model provides predictions which consistently agree with experimental results, supporting design for the control and programming of DNA-based systems.