Network analysis of biochemical logic for noise reduction and stability: a system of three coupled enzymatic and gates

Catalyst-Based Biomolecular Logic Gates

Regulatory processes in biology can be re-conceptualized in terms of logic gates, analogous to those in computer science. Frequently, biological systems need to respond to multiple, sometimes conflicting, inputs to provide the correct output. The language of logic gates can then be used to model complex signal transduction and metabolic processes. Advances in synthetic biology in turn can be used to construct new logic gates, which find a variety of biotechnology applications including in the production of high value chemicals, biosensing, and drug delivery. In this review, we focus on advances in the construction of logic gates that take advantage of biological catalysts, including both protein-based and nucleic acid-based enzymes. These catalyst-based biomolecular logic gates can read a variety of molecular inputs and provide chemical, optical, and electrical outputs, allowing them to interface with other types of biomolecular logic gates or even extend to inorganic systems. Continued advances in molecular modeling and engineering will facilitate the construction of new logic gates, further expanding the utility of biomolecular computing.

Enhancement of Biosensors by Implementing Photoelectrochemical Processes

Research on biosensors is growing in relevance, taking benefit from groundbreaking knowledge that allows for new biosensing strategies. Electrochemical biosensors can benefit from research on semiconducting materials for energy applications. This research seeks the optimization of the semiconductor-electrode interfaces including light-harvesting materials, among other improvements. Once that knowledge is acquired, it can be implemented with biological recognition elements, which are able to transfer a chemical signal to the photoelectrochemical system, yielding photo-biosensors. This has been a matter of research as it allows both a superior suppression of background electrochemical signals and the switching ON and OFF upon illumination. Effective electrode-semiconductor interfaces and their coupling with biorecognition units are reviewed in this work.

Mathematical Models of Protease-Based Enzymatic Biosensors

An important goal of synthetic biology is to build biosensors and circuits with well-defined input-output relationships that operate at speeds found in natural biological systems. However, for molecular computation, most commonly used genetic circuit elements typically involve several steps from input detection to output signal production: transcription, translation, and post-translational modifications. These multiple steps together require up to several hours to respond to a single stimulus, and this limits the overall speed and complexity of genetic circuits. To address this gap, molecular frameworks that rely exclusively on post-translational steps to realize reaction networks that can process inputs at a time scale of seconds to minutes have been proposed. Here, we build mathematical models of fast biosensors capable of producing Boolean logic functionality. We employ protease-based chemical and light-induced switches, investigate their operation, and provide selection guidelines for their use as on-off switches. As a proof of concept, we implement a rapamycin-induced switch in vitro and demonstrate that its response qualitatively agrees with the predictions from our models. We then use these switches as elementary blocks, developing models for biosensors that can perform OR and XOR Boolean logic computation while using reaction conditions as tuning parameters. We use sensitivity analysis to determine the time-dependent sensitivity of the output to proteolytic and protein-protein binding reaction parameters. These fast protease-based biosensors can be used to implement complex molecular circuits with a capability of processing multiple inputs controllably and algorithmically. Our framework for evaluating and optimizing circuit performance can be applied to other molecular logic circuits.

Modeling somatic computation with non-neural bioelectric networks

The field of basal cognition seeks to understand how adaptive, context-specific behavior occurs in non-neural biological systems. Embryogenesis and regeneration require plasticity in many tissue types to achieve structural and functional goals in diverse circumstances. Thus, advances in both evolutionary cell biology and regenerative medicine require an understanding of how non-neural tissues could process information. Neurons evolved from ancient cell types that used bioelectric signaling to perform computation. However, it has not been shown whether or how non-neural bioelectric cell networks can support computation. We generalize connectionist methods to non-neural tissue architectures, showing that a minimal non-neural Bio-Electric Network (BEN) model that utilizes the general principles of bioelectricity (electrodiffusion and gating) can compute. We characterize BEN behaviors ranging from elementary logic gates to pattern detectors, using both fixed and transient inputs to recapitulate various biological scenarios. We characterize the mechanisms of such networks using dynamical-systems and information-theory tools, demonstrating that logic can manifest in bidirectional, continuous, and relatively slow bioelectrical systems, complementing conventional neural-centric architectures. Our results reveal a variety of non-neural decision-making processes as manifestations of general cellular biophysical mechanisms and suggest novel bioengineering approaches to construct functional tissues for regenerative medicine and synthetic biology as well as new machine learning architectures.

Experimental Realization of a High-Quality Biochemical XOR Gate

We report an experimental realization of a biochemical XOR gate function that avoids many of the pitfalls of earlier realizations based on biocatalytic cascades. Inputs-represented by pairs of chemicals-cross-react to largely cancel out when both are nearly equal. The cross-reaction can be designed to also optimize gate functioning for noise handling. When not equal, the residual inputs are further processed to result in the output of the XOR type, by biocatalytic steps that allow for further gate-function optimization. The quality of the realized XOR gate is theoretically analyzed.

Enzyme-based logic systems interfaced with signal-responsive materials and electrodes

Enzyme-based biocomputing systems were interfaced with signal-responsive membranes and electrodes resulting in bioelectronic devices switchable by logically processed biomolecular signals. "Smart" membranes, electrodes, biofuel cells, memristors and substance-releasing systems were activated by various combinations of biomolecular signals in the pre-programmed way implemented in biocatalytic cascades mimicking logic networks.

An enzyme-based reversible CNOT logic gate realized in a flow system

An enzyme system organized in a flow device was used to mimic a reversible Controlled NOT (CNOT) gate with two input and two output signals. Reversible conversion of NAD(+) and NADH cofactors was used to perform a XOR logic operation, while biocatalytic hydrolysis of p-nitrophenyl phosphate resulted in an Identity operation working in parallel. The first biomolecular realization of a CNOT gate is promising for integration into complex biomolecular networks and future biosensor/biomedical applications.

Bridging the Two Worlds: A Universal Interface between Enzymatic and DNA Computing Systems

Molecular computing based on enzymes or nucleic acids has attracted a great deal of attention due to the perspectives of controlling living systems in the way we control electronic computers. Enzyme-based computational systems can respond to a great variety of small molecule inputs. They have the advantage of signal amplification and highly specific recognition. DNA computing systems are most often controlled by oligonucleotide inputs/outputs and are capable of sophisticated computing as well as controlling gene expressions. Here, we developed an interface that enables communication of otherwise incompatible nucleic-acid and enzyme-computational systems. The enzymatic system processes small molecules as inputs and produces NADH as an output. The NADH output triggers electrochemical release of an oligonucleotide, which is accepted by a DNA computational system as an input. This interface is universal because the enzymatic and DNA computing systems are independent of each other in composition and complexity.

Majority and minority gates realized in enzyme-biocatalyzed systems integrated with logic networks and interfaced with bioelectronic systems

Biocatalytic reactions operating in parallel and resulting in reduction of NAD(+) or oxidation of NADH were used to mimic 3-input majority and minority logic gates, respectively. The substrates corresponding to the enzyme reactions were used as the input signals. When the input signals were applied at their high concentrations, defined as logic 1 input values, the corresponding biocatalytic reactions were activated, resulting in changes of the NADH concentration defined as the output signal. The NADH concentration changes were dependent on the number of parallel reactions activated by the input signals. The absence of the substrates, meaning their logic 0 input values, kept the reactions mute with no changes in the NADH concentration. In the system mimicking the majority function, the enzyme-biocatalyzed reactions resulted in a higher production of NADH when more than one input signal was applied at the logic 1 value. Another system mimicking the minority function consumed more NADH, thus leaving a smaller residual output signal, when more than one input signal was applied at the logic 1 value. The performance of the majority gate was improved by processing the output signal through a filter system in which another biocatalytic reaction consumed a fraction of the output signal, thus reducing its physical value to zero when the logic 0 value was obtained. The majority gate was integrated with a preceding AND logic gate to illustrate the possibility of complex networks. The output signal, NADH, was also used to activate a process mimicking drug release, thus illustrating the use of the majority gate in decision-making biomedical systems. The 3-input majority gate was also used as a switchable AND/OR gate when one of the input signals was reserved as a command signal, switching the logic operation for processing of the other two inputs. Overall, the designed majority and minority logic gates demonstrate novel functions of biomolecular information processing systems.

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.

Enzymatic AND logic gate with sigmoid response induced by photochemically controlled oxidation of the output

We report a study of a system which involves an enzymatic cascade realizing an AND logic gate, with an added photochemical processing of the output, allowing the gate's response to be made sigmoid in both inputs. New functional forms are developed for quantifying the kinetics of such systems, specifically designed to model their response in terms of signal and information processing. These theoretical expressions are tested for the studied system, which also allows us to consider aspects of biochemical information processing such as noise transmission properties and control of timing of the chemical and physical steps.

Synthesizing biomolecule-based Boolean logic gates

One fascinating recent avenue of study in the field of synthetic biology is the creation of biomolecule-based computers. The main components of a computing device consist of an arithmetic logic unit, the control unit, memory, and the input and output devices. Boolean logic gates are at the core of the operational machinery of these parts, and hence to make biocomputers a reality, biomolecular logic gates become a necessity. Indeed, with the advent of more sophisticated biological tools, both nucleic acid- and protein-based logic systems have been generated. These devices function in the context of either test tubes or living cells and yield highly specific outputs given a set of inputs. In this review, we discuss various types of biomolecular logic gates that have been synthesized, with particular emphasis on recent developments that promise increased complexity of logic gate circuitry, improved computational speed, and potential clinical applications.

Enzyme-based D-flip-flop memory system

The enzyme system was used to mimic the D-flip-flop memory unit. The reversible conversion of NAD(+) and NADH cofactors was used to encode the states of the memory unit, while a mixture of inhibitors was used as the Clock input and the substrates were used as the Data input.

Realization of Associative Memory in an Enzymatic Process: Toward Biomolecular Networks with Learning and Unlearning Functionalities

We report a realization of an associative memory signal/information processing system based on simple enzyme-catalyzed biochemical reactions. Optically detected chemical output is always obtained in response to the triggering input, but the system can also "learn" by association, to later respond to the second input if it is initially applied in combination with the triggering input as the "training" step. This second chemical input is not self-reinforcing in the present system, which therefore can later "unlearn" to react to the second input if it is applied several times on its own. Such processing steps realized with (bio)chemical kinetics promise applications of bioinspired/memory-involving components in "networked" (concatenated) biomolecular processes for multisignal sensing and complex information processing.

Multiplexing of injury codes for the parallel operation of enzyme logic gates

The development of a highly parallel enzyme logic sensing concept employing a novel encoding scheme for the determination of multiple pathophysiological conditions is reported. The new concept multiplexes a contingent of enzyme-based logic gates to yield a distinct 'injury code' corresponding to a unique pathophysiological state as prescribed by a truth table. The new concept is illustrated using an array of NAND and AND gates to assess the biomedical significance of numerous biomarker inputs including creatine kinase, lactate dehydrogenase, norepinephrine, glutamate, alanine transaminase, lactate, glucose, glutathione disulfide, and glutathione reductase to assess soft-tissue injury, traumatic brain injury, liver injury, abdominal trauma, hemorrhagic shock, and oxidative stress. Under the optimal conditions, physiological and pathological levels of these biomarkers were detected through either optical or electrochemical techniques by monitoring the level of the outputs generated by each of the six logic gates. By establishing a pathologically meaningful threshold for each logic gate, the absorbance and amperometric assays tendered the diagnosis in a digitally encoded 6-bit word, defined as an 'injury code'. This binary 'injury code' enabled the effective discrimination of 64 unique pathological conditions to offer a comprehensive high-fidelity diagnosis of multiple injury conditions. Such processing of relevant biomarker inputs and the subsequent multiplexing of the logic gate outputs to yield a comprehensive 'injury code' offer significant potential for the rapid and reliable assessment of varied and complex forms of injury in circumstances where access to a clinical laboratory is not viable. While the new concept of parallel and multiplexed enzyme logic gates is illustrated here in connection to multi-injury diagnosis, it could be readily extended to a wide range of practical medical, industrial, security and environmental applications.

Enzyme-based multiplexer and demultiplexer

A digital 2-to-1 multiplexer and a 1-to-2 demultiplexer were mimicked by biocatalytic reactions involving concerted operation of several enzymes. Using glucose oxidase (GOx) and laccase (Lac) as the data input signals and variable pH as the addressing signal, ferrocyanide oxidation in the output channel was selectively activated by one from two inputs, thus mimicking the multiplexer operation. A demultiplexer based on the enzyme system composed of GOx, glucose dehydrogenase (GDH) and horseradish peroxidase (HRP) allowed selective activation of different output channels (oxidation of ferrocyanide or reduction of NAD(+)) by the glucose input. The selection of the output channel was controlled by the addressing input of NAD(+). The designed systems represent important novel components of future branched enzyme networks processing biochemical signals for biosensing and bioactuating.

Assembly of Anionic Conjugated Polymer with 6-O-Modified PNP-β-Galactoside for Fluorescence Logic-signal-based Multiplex Detections of Enzymes

Anionic conjugated polymer (PFP-SO 3-) was assembled with a novel enzymatic substrate 6-O-modified PNP-β-galactoside (1) for sensitive multiplex enzyme detections. The PFP-SO 3-/1/lipase/β-galactosidase system has two chemical input signals which are Input 1 (lipase) and Input 2 (β-galactosidase), and output optical signals such as fluorescence emission at 416 nm or 450 nm. Four types of logic gates, including YES, INH, NAND and AND, were successfully constructed and utilized for multiplex detections of lipase and β-galactosidase in one tube.