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. 2016 Feb 18;11(2):e0149667.
doi: 10.1371/journal.pone.0149667. eCollection 2016.

Logic Gate Operation by DNA Translocation Through Biological Nanopores

Free PMC article

Logic Gate Operation by DNA Translocation Through Biological Nanopores

Hiroki Yasuga et al. PLoS One. .
Free PMC article


Logical operations using biological molecules, such as DNA computing or programmable diagnosis using DNA, have recently received attention. Challenges remain with respect to the development of such systems, including label-free output detection and the rapidity of operation. Here, we propose integration of biological nanopores with DNA molecules for development of a logical operating system. We configured outputs "1" and "0" as single-stranded DNA (ssDNA) that is or is not translocated through a nanopore; unlabeled DNA was detected electrically. A negative-AND (NAND) operation was successfully conducted within approximately 10 min, which is rapid compared with previous studies using unlabeled DNA. In addition, this operation was executed in a four-droplet network. DNA molecules and associated information were transferred among droplets via biological nanopores. This system would facilitate linking of molecules and electronic interfaces. Thus, it could be applied to molecular robotics, genetic engineering, and even medical diagnosis and treatment.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.


Fig 1
Fig 1. Droplet contact method (DCM) and the binary system based on DNA blocking and translocation.
(a) Definition of the binary system based on the presence of DNA in an aqueous droplet coated with a lipid monolayer. (b) A schematic view of the bilayer lipid membrane (BLM) formed via DCM. (c) The system for DNA transfer among droplets by DNA translocation through αHL nanopores. (d–f) Electrical detection of DNA translocation and determination of the presence of DNA constructs in the droplet. (d) Output 1 (translocation): A single-stranded DNA (ssDNA) is translocated through an αHL nanopore with a short current blockade. (e) Output 0 (blocking): A double-stranded DNA (dsDNA) is not translocated through the αHL nanopore owing to its larger diameter, inducing a long current blockade. (f) Output 0 (No DNA strand): No DNA strand is present for translocation, and thus no current blockade is generated.
Fig 2
Fig 2. Negative-AND (NAND) operation system based on DNA translocation.
(a) NAND logic gate concept based on αHL nanopores and three types of DNA strands, ADNA, BDNA, and complementary DNA (CDNA) in a droplet network. (b) A schematic table of NAND operations with the DNA structures and nanopore result for each input.
Fig 3
Fig 3. An overview of the experiment performed to confirm that the desired outputs were obtained.
(a) Schematic view of the experiment. DNA constructs, hybridized in advance, were injected into a droplet. (b) Typical method for channel current signal analysis. (c–f) A schematic view of translocation of the DNA strands present in each input and the current blockade signals produced.
Fig 4
Fig 4. A schematic view of the four-well chip, the device used for the four-droplet network.
(a) A four-droplet network for Negative-AND operation. Input (1, 0) was selected as an example. The input DNA strands were injected into the input droplets and the CDNA strands were prepared in the operation droplet. (b) An overall view of the 4WC. The electrodes in the wells were connected to a patch-clamp amplifier. (c) The wiring to the four wells. The electrodes were embedded on the bottom of the wells.
Fig 5
Fig 5. Outputs of the Negative-AND operation in a four-droplet network.
The operation was performed as follows: Collect 10 DNA translocation or blocking events for a single calculation. Measure duration of each blocking event. Differentiate the events into two groups, those greater than 1 s (number of events = a) and those not greater than 1 s (number of events = b). Calculate a–b, and determine the output as: Output 1: a–b < 0 or Output 0: a–b > 0. Standard errors were determined using the output from three operations. (a) input (0, 0): a–b = –8.0 ± 1.2, output = 1. (b) input (0, 1): a–b = –9.3 ± 0.7, output = 1. (c) input (1, 0): a–b = –2.7 ± 2.4, output = 1. (d) input (1, 1): a–b = 1.3 ± 0.7, output = 0.

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Grant support

This work was supported by a Grant-in-Aid for Scientific Research on Innovative Areas “Molecular Robotics” (No. 24104002) to RK and MT; a Grant-in-Aid for Challenging Exploratory Research (No. 26540160) to RK; a Grant-in-Aid for Young Scientists (A) (No. 25708024) to RK; the Regional Innovation Strategy Support Program to ST; a Grant-in-Aid for Scientific Research (A) (No. 25246017) to ST of The Ministry of Education, Culture, Sports, Science, and Technology, Japan. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.