Design of Digital Response in Enzyme-Based Bioanalytical Systems for Information Processing Applications

Recent Advances in Microfluidics-Based Electrochemical Sensors for Foodborne Pathogen Detection

Using pathogen-infected food that can be unhygienic can result in severe diseases and an increase in mortality rate among humans. This may arise as a serious emergency problem if not appropriately restricted at this point of time. Thus, food science researchers are concerned with precaution, prevention, perception, and immunity to pathogenic bacteria. Expensive, elongated assessment time and the need for skilled personnel are some of the shortcomings of the existing conventional methods. Developing and investigating a rapid, low-cost, handy, miniature, and effective detection technology for pathogens is indispensable. In recent times, there has been a significant scope of interest for microfluidics-based three-electrode potentiostat sensing platforms, which have been extensively used for sustainable food safety exploration because of their progressively high selectivity and sensitivity. Meticulously, scholars have made noteworthy revolutions in signal enrichment tactics, measurable devices, and portable tools, which can be used as an allusion to food safety investigation. Additionally, a device for this purpose must incorporate simplistic working conditions, automation, and miniaturization. In order to meet the critical needs of food safety for on-site detection of pathogens, point-of-care testing (POCT) has to be introduced and integrated with microfluidic technology and electrochemical biosensors. This review critically discusses the recent literature, classification, difficulties, applications, and future directions of microfluidics-based electrochemical sensors for screening and detecting foodborne pathogens.

Reversible Photoswitchable Inhibitors Generate Ultrasensitivity in Out-of-Equilibrium Enzymatic Reactions

Ultrasensitivity is a ubiquitous emergent property of biochemical reaction networks. The design and construction of synthetic reaction networks exhibiting ultrasensitivity has been challenging, but would greatly expand the potential properties of life-like materials. Herein, we exploit a general and modular strategy to reversibly regulate the activity of enzymes using light and show how ultrasensitivity arises in simple out-of-equilibrium enzymatic systems upon incorporation of reversible photoswitchable inhibitors (PIs). Utilizing a chromophore/warhead strategy, PIs of the protease α-chymotrypsin were synthesized, which led to the discovery of inhibitors with large differences in inhibition constants (K_i) for the different photoisomers. A microfluidic flow setup was used to study enzymatic reactions under out-of-equilibrium conditions by continuous addition and removal of reagents. Upon irradiation of the continuously stirred tank reactor with different light pulse sequences, i.e., varying the pulse duration or frequency of UV and blue light irradiation, reversible switching between photoisomers resulted in ultrasensitive responses in enzymatic activity as well as frequency filtering of input signals. This general and modular strategy enables reversible and tunable control over the kinetic rates of individual enzyme-catalyzed reactions and makes a programmable linkage of enzymes to a wide range of network topologies feasible.

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model we describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of "stiff" equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.

Enzyme-based logic gates and circuits-analytical applications and interfacing with electronics

The paper is an overview of enzyme-based logic gates and their short circuits, with specific examples of Boolean AND and OR gates, and concatenated logic gates composed of multi-step enzyme-biocatalyzed reactions. Noise formation in the biocatalytic reactions and its decrease by adding a "filter" system, converting convex to sigmoid response function, are discussed. Despite the fact that the enzyme-based logic gates are primarily considered as components of future biomolecular computing systems, their biosensing applications are promising for immediate practical use. Analytical use of the enzyme logic systems in biomedical and forensic applications is discussed and exemplified with the logic analysis of biomarkers of various injuries, e.g., liver injury, and with analysis of biomarkers characteristic of different ethnicity found in blood samples on a crime scene. Interfacing of enzyme logic systems with modified electrodes and semiconductor devices is discussed, giving particular attention to the interfaces functionalized with signal-responsive materials. Future perspectives in the design of the biomolecular logic systems and their applications are discussed in the conclusion. Graphical Abstract Various applications and signal-transduction methods are reviewed for enzyme-based logic systems.

How many enzyme molecules are needed for discrimination oriented applications?

Chemical reactions establish a molecular mechanism for information processing in living organisms. Here we consider a simple enzymatic reaction model that can be used to discriminate parameters characterizing periodic reagent inflow. Numerical simulations based on the kinetic equations show that there exist a range of inflow frequencies and amplitudes in which the time evolution of the system is very sensitive to small changes in the values of these parameters. However, the kinetic equations are derived for the thermodynamic limit, whereas in a real biological medium, like a cell, the number of enzyme molecules is an integer and finite. We use stochastic simulations to estimate discriminator reliability as a function of the number of enzyme molecules involved. For systems with 10 000 molecules the functionality predicted by kinetic equations is confirmed. If the number of molecules is decreased to 100, discrimination becomes unreliable.

Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications

We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s) as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed.

Molecular computing: paths to chemical Turing machines

In this perspective, we highlight some of the recent advances in the development of molecular and biomolecular systems for performing logic operations and computing. We also present a blueprint of a chemical Turing machine using a processive catalytic approach.

To comply with the rapidly increasing demand of information storage and processing, new strategies for computing are needed. The idea of molecular computing, where basic computations occur through molecular, supramolecular, or biomolecular approaches, rather than electronically, has long captivated researchers. The prospects of using molecules and (bio)macromolecules for computing is not without precedent. Nature is replete with examples where the handling and storing of data occurs with high efficiencies, low energy costs, and high-density information encoding. The design and assembly of computers that function according to the universal approaches of computing, such as those in a Turing machine, might be realized in a chemical way in the future; this is both fascinating and extremely challenging. In this perspective, we highlight molecular and (bio)macromolecular systems that have been designed and synthesized so far with the objective of using them for computing purposes. We also present a blueprint of a molecular Turing machine, which is based on a catalytic device that glides along a polymer tape and, while moving, prints binary information on this tape in the form of oxygen atoms.

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.