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. 2018 Jul 26;57(31):9702-9706.
doi: 10.1002/anie.201804292. Epub 2018 Jul 9.

Biocomputing for Portable, Resettable, and Quantitative Point-of-Care Diagnostics: Making the Glucose Meter a Logic-Gate Responsive Device for Measuring Many Clinically Relevant Targets

Jingjing Zhang  1 , Yi Lu  1
Affiliations

Biocomputing for Portable, Resettable, and Quantitative Point-of-Care Diagnostics: Making the Glucose Meter a Logic-Gate Responsive Device for Measuring Many Clinically Relevant Targets

Jingjing Zhang et al. Angew Chem Int Ed Engl. .

Abstract

It is recognized that biocomputing can provide intelligent solutions to complex biosensing projects. However, it remains challenging to transform biomolecular logic gates into convenient, portable, resettable and quantitative sensing systems for point-of-care (POC) diagnostics in a low-resource setting. To overcome these limitations, the first design of biocomputing on personal glucose meters (PGMs) is reported, which utilizes glucose and the reduced form of nicotinamide adenine dinucleotide as signal outputs, DNAzymes and protein enzymes as building blocks, and demonstrates a general platform for installing logic-gate responses (YES, NOT, INHIBIT, NOR, NAND, and OR) to a variety of biological species, such as cations (Na+ ), anions (citrate), organic metabolites (adenosine diphosphate and adenosine triphosphate) and enzymes (pyruvate kinase, alkaline phosphatase, and alcohol dehydrogenases). A concatenated logical gate platform that is resettable is also demonstrated. The system is highly modular and can be generally applied to POC diagnostics of many diseases, such as hyponatremia, hypernatremia, and hemolytic anemia. In addition to broadening the clinical applications of the PGM, the method reported opens a new avenue in biomolecular logic gates for the development of intelligent POC devices for on-site applications.

Keywords: DNA; biosensing; enzyme cascades; glucose meter; point-of-care testing.

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Conflict of interest statement

Conflict of interest

The authors declare no conflict of interest.

Figures

Figure 1.
Figure 1.
A “YES” logic gate using glucose as the signal output. a) Na+ detection based on Na+-DNAzyme-invertase conjugate and a PGM. Schematic showing the release of the invertase in the presence of Na+ and detection using a PGM. b) Calibration curve of Na+ detection in human serum using a PGM. Inset of b is the truth table for the YES gate. A threshold value of 10 mg/dL was defined to separate the OFF and ON logic states of the output PGM signal. c) A clinical application of a PGM-based YES gate for diagnosis of hyponatremia and hypernatremia.
Figure 2.
Figure 2.
A “NOT” logic gate using NADH as the signal output. Schematic showing the biocatalytic cascade for the detection of pyruvate kinase (a) and citrate (b), and the calibration curves for PK (c) and citrate (d). Inset of c is the truth table for the NOT gate. A threshold value of 325 mg/dL was defined to separate the ON and OFF logic states of the output PGM signal.
Figure 3.
Figure 3.
An “OR” logic gate using both NADH and glucose as the signal output. a) Schematic showing the biocatalytic reaction for the detection of alkaline phosphatase (ALP) and alcohol dehydrogenases (ADH). b) PGM signal for the Boolean OR logic functions operating with ALP and ADH. c) The truth table for the OR gate.
Figure 4.
Figure 4.
“Concatenated” logic gate using both NADH and glucose as the output. a) Scheme of the biocatalytic cascade with multiple inputs and outputs. b) The PGM response of repeated switches between “off” and “on” states by adding appropriate inputs of enzyme substrates and coenzymes.
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