SIRT6 knockout cells resist apoptosis initiation but not progression: a computational method to evaluate the progression of apoptosis
Apoptosis is essential for numerous processes, such as development, resistance to infections, and suppression of tumorigenesis. Here, we investigate the influence of the nutrient sensing and longevity-assuring enzyme SIRT6 on the dynamics of apoptosis triggered by serum starvation. Specifically, we characterize the progression of apoptosis in wild type and SIRT6 deficient mouse embryonic fibroblasts using time-lapse flow cytometry and computational modelling based on rate-equations and cell distribution analysis. We find that SIRT6 deficient cells resist apoptosis by delaying its initiation. Interestingly, once apoptosis is initiated, the rate of its progression is higher in SIRT6 null cells compared to identically cultured wild type cells. However, SIRT6 null cells succumb to apoptosis more slowly, not only in response to nutrient deprivation but also in response to other stresses. Our data suggest that SIRT6 plays a role in several distinct steps of apoptosis. Overall, we demonstrate the utility of our computational model to describe stages of apoptosis progression and the integrity of the cellular membrane. Such measurements will be useful in a broad range of biological applications.
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.
Promises and Challenges in Continuous Tracking Utilizing Amino Acids in Skin Secretions for Active Multi-Factor Biometric Authentication for Cybersecurity
We consider a new concept of biometric-based cybersecurity systems for active authentication by continuous tracking, which utilizes biochemical processing of metabolites present in skin secretions. Skin secretions contain a large number of metabolites and small molecules that can be targeted for analysis. Here we argue that amino acids found in sweat can be exploited for the establishment of an amino acid profile capable of identifying an individual user of a mobile or wearable device. Individual and combinations of amino acids processed by biocatalytic cascades yield physical (optical or electronic) signals, providing a time-series of several outputs that, in their entirety, should suffice to authenticate a specific user based on standard statistical criteria. Initial results, motivated by biometrics, indicate that single amino acid levels can provide analog signals that vary according to the individual donor, albeit with limited resolution versus noise. However, some such assays offer digital separation (into well-defined ranges of values) according to groups such as age, biological sex, race, and physiological state of the individual. Multi-input biocatalytic cascades that handle several amino acid signals to yield a single digital-type output, as well as continuous-tracking time-series data rather than a single-instance sample, should enable active authentication at the level of an individual.
Design of High Quality Chemical XOR Gates with Noise Reduction
We describe a chemical XOR gate design that realizes gate-response function with filtering properties. Such gate-response function is flat (has small gradients) at and in the vicinity of all the four binary-input logic points, resulting in analog noise suppression. The gate functioning involves cross-reaction of the inputs represented by pairs of chemicals to produce a practically zero output when both are present and nearly equal. This cross-reaction processing step is also designed to result in filtering at low output intensities by canceling out the inputs if one of the latter has low intensity compared with the other. The remaining inputs, which were not reacted away, are processed to produce the output XOR signal by chemical steps that result in filtering at large output signal intensities. We analyze the tradeoff resulting from filtering, which involves loss of signal intensity. We also discuss practical aspects of realizations of such XOR gates.
Glucose-Triggered Insulin Release from Fe3+ -Cross-linked Alginate Hydrogel: Experimental Study and Theoretical Modeling
We study the mechanisms involved in the release, triggered by the application of glucose, of insulin entrapped in Fe3+ -cross-linked alginate hydrogel particles further stabilized with a polyelectrolyte. Platelet-shaped alginate particles are synthesized containing enzyme glucose oxidase conjugated with silica nanoparticles, which are also entrapped in the hydrogel. Glucose diffuses in from solution, and production of hydrogen peroxide is catalyzed by the enzyme within the hydrogel. We argue that, specifically for the Fe3+ -cross-linked systems, the produced hydrogen peroxide is further converted to free radicals via a Fenton-type reaction catalyzed by the iron cations. The activity of free radicals, as well as the reduction of Fe3+ by the enzyme, and other mechanisms contribute to the decrease in density of the hydrogel. As a result, while the particles remain intact, void sizes increase and release of insulin ensues and is followed experimentally. A theoretical description of the involved processes is proposed and utilized to fit the data. It is then used to study the long-time properties of the release process that offers a model for designing new drug-release systems.
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.
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.
Random sequential adsorption on imprecise lattice
We report a surprising result, established by numerical simulations and analytical arguments for a one-dimensional lattice model of random sequential adsorption, that even an arbitrarily small imprecision in the lattice-site localization changes the convergence to jamming from fast, exponential, to slow, power-law, with, for some parameter values, a discontinuous jump in the jamming coverage value. This finding has implications for irreversible deposition on patterned substrates with pre-made landing sites for particle attachment. We also consider a general problem of the particle (depositing object) size not an exact multiple of the lattice spacing, and the lattice sites themselves imprecise, broadened into allowed-deposition intervals. Regions of exponential vs. power-law convergence to jamming are identified, and certain conclusions regarding the jamming coverage are argued for analytically and confirmed numerically.
Diffusion of Oligonucleotides from within Iron-Cross-Linked, Polyelectrolyte-Modified Alginate Beads: A Model System for Drug Release
An analytical model to describe diffusion of oligonucleotides from stable hydrogel beads is developed and experimentally verified. The synthesized alginate beads are Fe(3+) -cross-linked and polyelectrolyte-doped for uniformity and stability at physiological pH. Data on diffusion of oligonucleotides from inside the beads provide physical insights into the volume nature of the immobilization of a fraction of oligonucleotides due to polyelectrolyte cross-linking, that is, the absence of a surface-layer barrier in this case. Furthermore, the results suggest a new simple approach to measuring the diffusion coefficient of mobile oligonucleotide molecules inside hydrogels. The considered alginate beads provide a model for a well-defined component in drug-release systems and for the oligonucleotide-release transduction steps in drug-delivering and biocomputing applications. This is illustrated by destabilizing the beads with citrate, which induces full oligonucleotide release with nondiffusional kinetics.
Reaction-diffusion degradation model for delayed erosion of cross-linked polyanhydride biomaterials
We develop a theoretical model to explain the long induction interval of water intake that precedes the onset of erosion due to degradation caused by hydrolysis in the recently synthesized and studied cross-linked polyanhydrides. Various kinetic mechanisms are incorporated in the model in an attempt to explain the experimental data for the mass loss profile. Our key finding is that the observed long induction interval is attributable to the nonlinear dependence of the degradation rate constants on the local water concentration, which essentially amounts to the breakdown of the standard rate-equation approach, potential causes for which are then discussed. Our theoretical results offer physical insights into which microscopic studies will be required to supplement the presently available macroscopic mass-loss data in order to fully understand the origin of the observed behavior.