Multi-enzyme logic network architectures for assessing injuries: digital processing of biomarkers

A multi-enzyme biocatalytic cascade processing simultaneously five biomarkers characteristic of traumatic brain injury (TBI) and soft tissue injury (STI) was developed. The system operates as a digital biosensor based on concerted function of 8 Boolean AND logic gates, resulting in the decision about the physiological conditions based on the logic analysis of complex patterns of the biomarkers. The system represents the first example of a multi-step/multi-enzyme biosensor with the built-in logic for the analysis of complex combinations of biochemical inputs. The approach is based on recent advances in enzyme-based biocomputing systems and the present paper demonstrates the potential applicability of biocomputing for developing novel digital biosensor networks.     

'Non-destructive' biocomputing security system based on gas-controlled biofuel cell and potentially used for intelligent medical diagnostics

MOTIVATION: Biofuel cells (BFCs) based on enzymes and microbes are the promising future alternative sources of sustainable electrical energy under mild conditions (i.e. ambient temperature and neutral pH). By combining the adaptive behavior of BFCs self-regulating energy release with the versatility of biocomputing, we construct a novel gas-controlled biocomputing security system, which could be used as the potential implantable self-powered and 'smart' medical system with the logic diagnosis aim. RESULTS: We have demonstrated a biocomputing security system based on BFCs. Due to the unique 'RESET' reagent of N(2) applied in this work, the prepared biocomputing security system can be reset and cycled for a large number of times with no 'RESET' reagent-based 'waste'. This would be advantageous for the potential practical applications of such keypad lock as well as the development of biocomputing security devices. In order to validate the universality of the system and also to harvest energy directly from biofuels with enhanced power output, we replace the glucose with orange juice as the biofuel to operate BFCs-based biocomputing system, which also possesses the function of keypad lock. In addition, by introducing BFCs into the biocomputing security system, the adaptive behavior of the BFCs self-regulating the power release would be an immense advantage of such security keypad lock devices in potential self-powered implantable medical systems. The designed sequence gives the maximum power output and discriminate itself from the rest of the sequences. From this, we find that maximizing the dimensionless ratio of gap versus SD of the power output spectrum (a funnel in power outputs) gives the quantitative optimal design criterion. Therefore, our construction here may also provide a practical example and microscopic structural basis for mimicking the real biological network systems and bridge the gaps between the theoretical concepts and experiments important for biomolecular systems and synthetic biology.     

Computational functions in biochemical reaction networks.

In prior work we demonstrated the implementation of logic gates, sequential computers (universal Turing machines), and parallel computers by means of the kinetics of chemical reaction mechanisms. In the present article we develop this subject further by first investigating the computational properties of several enzymatic (single and multiple) reaction mechanisms: we show their steady states are analogous to either Boolean or fuzzy logic gates. Nearly perfect digital function is obtained only in the regime in which the enzymes are saturated with their substrates. With these enzymatic gates, we construct combinational chemical networks that execute a given truth-table. The dynamic range of a network's output is strongly affected by "input/output matching" conditions among the internal gate elements. We find a simple mechanism, similar to the interconversion of fructose-6-phosphate between its two bisphosphate forms (fructose-1,6-bisphosphate and fructose-2,6-bisphosphate), that functions analogously to an AND gate. When the simple model is supplanted with one in which the enzyme rate laws are derived from experimental data, the steady state of the mechanism functions as an asymmetric fuzzy aggregation operator with properties akin to a fuzzy AND gate. The qualitative behavior of the mechanism does not change when situated within a large model of glycolysis/gluconeogenesis and the TCA cycle. The mechanism, in this case, switches the pathway's mode from glycolysis to gluconeogenesis in response to chemical signals of low blood glucose (cAMP) and abundant fuel for the TCA cycle (acetyl coenzyme A).     

Development of a DNA sensor using a molecular logic gate

This communication reports the increase in fluorescence resonance energy transfer (FRET) efficiency between two laser dyes in the presence of deoxyribonucleic acid (DNA). Two types of molecular logic gates have been designed where DNA acts as input signal and fluorescence intensity of different bands are taken as output signal. Use of these logic gates as a DNA sensor has been demonstrated.     

Rapid and orthogonal logic gating with a gibberellin-induced dimerization system

Using a newly synthesized gibberellin analog containing an acetoxymethyl group (GA(3)-AM) and its binding proteins, we developed an efficient chemically inducible dimerization (CID) system that is completely orthogonal to existing rapamycin-mediated protein dimerization. Combining the two systems should allow applications that have been difficult or impossible with only one CID system. By using both chemical inputs (rapamycin and GA(3)-AM), we designed and synthesized Boolean logic gates in living mammalian cells. These gates produced output signals such as fluorescence and membrane ruffling on a timescale of seconds, substantially faster than earlier intracellular logic gates. The use of two orthogonal dimerization systems in the same cell also allows for finer modulation of protein perturbations than is possible with a single dimerizer.     

Multi/infinite dimensional neural networks, multi/infinite dimensional logic theory

A mathematical model of an arbitrary multi-dimensional neural network is developed and a convergence theorem for an arbitrary multi-dimensional neural network represented by a fully symmetric tensor is stated and proved. The input and output signal states of a multi-dimensional neural network/logic gate are related through an energy function, defined over the fully symmetric tensor (representing the connection structure of a multi-dimensional neural network). The inputs and outputs are related such that the minimum/maximum energy states correspond to the output states of the logic gate/neural network realizing a logic function. Similarly, a logic circuit consisting of the interconnection of logic gates, represented by a block symmetric tensor, is associated with a quadratic/higher degree energy function. Infinite dimensional logic theory is discussed through the utilization of infinite dimension/order tensors.     

Multiplexed sensing of mercury(II) and silver(I) ions: a new class of DNA electrochemiluminescent-molecular logic gates

Most of the DNA logic gates employ fluorescent or colorometric signals as their outputs, which were limited by the cumbersome handling procedures, lack of portability and lower sensitivity. To the best of our knowledge, the logic gates with electrochemiluminescent (ECL) signal as their outputs have not been reported. In response, we report here the construction of DNA molecular logic gates that produce ECL signals as their outputs, having the advantages of versatility, low background and simplified optical setup. The logic gates are based on the T-rich or C-rich oligonucleotides for the selective analysis of Hg(2+) and Ag(+) ions using energy or electron transfer-quenching path. Efficient and stable quenching of ECL of Ru bis(2,2'-bipyridine) (2,2'-bipyridine-4,4'-dicarboxylic acid) N-hydroxysuccinimide ester by oxidizing ferrocene at the Au electrode enabled us to use Hg(2+) and Ag(+) ions as inputs that activate logic gates, and to execute ECL of Ru(II) as readout signals for logic gate operations.     

Deoxyribozyme-based three-input logic gates and construction of a molecular full adder

We have developed an array of seven deoxyribozyme-based molecular logic gates that behaves as a full adder in a single solution, with three oligonucleotides as inputs and two independent fluorogenic cleavage reactions as carry and sum outputs. The sum output consisted of four new deoxyribozyme-based logic gates: an ANDAND gate and three ANDNOTANDNOT gates. These gates required the design of a generic three-input deoxyribozyme-based logic gate that can use any three-way combination of activating or inactivating inputs. This generic gate design utilizes an additional inverting element that hybridizes to convert YES logic into NOT logic and vice versa. The system represents the first solution-phase, single test tube, enzymatic full adder and shows the complexity of control over molecular scale events that can be achieved with deoxyribozyme-based logic gates. Similar systems could be applied to control autonomous therapeutic and diagnostic devices.     

A Novel Bio-Sensor Based on DNA Strand Displacement

DNA strand displacement technology performs well in sensing and programming DNA segments. In this work, we construct DNA molecular systems based on DNA strand displacement performing computation of logic gates. Specifically, a class of so-called “DNA neurons” are achieved, in which a “smart” way inspired by biological neurons encoding information is developed to encode and deliver information using DNA molecules. The “DNA neuron” is bistable, that is, it can sense DNA molecules as input signals, and release “negative” or “positive” signals DNA molecules. We design intelligent DNA molecular systems that are constructed by cascading some particularly organized “DNA neurons”, which could perform logic computation, including AND, OR, XOR logic gates, automatically. Both simulation results using visual DSD (DNA strand displacement) software and experimental results are obtained, which shows that the proposed systems can detect DNA signals with high sensitivity and accretion; moreover, the systems can process input signals automatically with complex nonlinear logic. The method proposed in this work may provide a new way to construct a sensitive molecular signal detection system with neurons spiking behavior in vitro, and can be used to develop intelligent molecular processing systems in vivo.     

Biochemical changes in the injured brain

Brain metabolism is an energy intensive phenomenon involving a wide spectrum of chemical intermediaries. Various injury states have a detrimental effect on the biochemical processes involved in the homeostatic and electrophysiological properties of the brain. The biochemical markers of brain injury are a recent addition in the armamentarium of neuro-clinicians and are being increasingly used in the routine management of neuropathological entities such as traumatic brain injury, stroke, subarachnoid haemorrhage and intracranial space occupying lesions. These markers are increasingly being used in assessing severity as well as in predicting the prognostic course of neuro-pathological lesions. S-100 protein, neuron specific enolase, creatinine phosphokinase isoenzyme BB and myelin basic protein are some of the biochemical markers which have been proven to have prognostic and clinical value in the brain injury. While S-100, glial fibrillary acidic protein and ubiquitin C terminal hydrolase are early biomarkers of neuronal injury and have the potential to aid in clinical decisionmaking in the initial management of patients presenting with an acute neuronal crisis, the other biomarkers are of value in predicting long-term complications and prognosis in such patients. In recent times cerebral microdialysis has established itself as a novel way of monitoring brain tissue biochemical metabolites such as glucose, lactate, pyruvate, glutamate and glycerol while small non-coding RNAs have presented themselves as potential markers of brain injury for future.     

Fluorescence for biological logic gates

Biological logic gates are smart probes able to respond to biological conditions in behaviors similar to computer logic gates, and they pose a promising challenge for modern medicine. Researchers are creating many kinds of smart nanostructures that can respond to various biological parameters such as pH, ion presence, and enzyme activity. Each of these conditions alone might be interesting in a biological sense, but their interactions are what define specific disease conditions. Researchers over the past few decades have developed a plethora of stimuli‐responsive nanodevices, from activatable fluorescent probes to DNA origami nanomachines, many explicitly defining logic operations. Whereas many smart configurations have been explored, in this review we focus on logic operations actuated through fluorescent signals. We discuss the applicability of fluorescence as a means of logic gate implementation, and consider the use of both fluorescence intensity as well as fluorescence lifetime.     

Customizing cell signaling using engineered genetic logic circuits

Cells live in an ever-changing environment and continuously sense, process and react to environmental signals using their inherent signaling and gene regulatory networks. Recently, there have been great advances on rewiring the native cell signaling and gene networks to program cells to sense multiple noncognate signals and integrate them in a logical manner before initiating a desired response. Here, we summarize the current state-of-the-art of engineering synthetic genetic logic circuits to customize cellular signaling behaviors, and discuss their promising applications in biocomputing, environmental, biotechnological and biomedical areas as well as the remaining challenges in this growing field.     

Nanobiohybrid Material‐Based Bioelectronic Devices

Biomolecules, especially proteins and nucleic acids, have been widely studied to develop biochips for various applications in scientific fields ranging from bioelectronics to stem cell research. However, restrictions exist due to the inherent characteristics of biomolecules, such as instability and the constraint of granting the functionality to the biochip. Introduction of functional nanomaterials, recently being researched and developed, to biomolecules have been widely researched to develop the nanobiohybrid materials because such materials have the potential to enhance and extend the function of biomolecules on a biochip. The potential for applying nanobiohybrid materials is especially high in the field of bioelectronics. Research in bioelectronics is aimed at realizing electronic functions using the inherent properties of biomolecules. To achieve this, various biomolecules possessing unique properties have been combined with novel nanomaterials to develop bioelectronic devices such as highly sensitive electrochemical‐based bioelectronic sensing platforms, logic gates, and biocomputing systems. In this review, recently reported bioelectronic devices based on nanobiohybrid materials are discussed. The authors believe that this review will suggest innovative and creative directions to develop the next generation of multifunctional bioelectronic devices.     

Biological Signal Processing with a Genetic Toggle Switch

Complex gene regulation requires responses that depend not only on the current levels of input signals but also on signals received in the past. In digital electronics, logic circuits with this property are referred to as sequential logic, in contrast to the simpler combinatorial logic without such internal memory. In molecular biology, memory is implemented in various forms such as biochemical modification of proteins or multistable gene circuits, but the design of the regulatory interface, which processes the input signals and the memory content, is often not well understood. Here, we explore design constraints for such regulatory interfaces using coarse-grained nonlinear models and stochastic simulations of detailed biochemical reaction networks. We test different designs for biological analogs of the most versatile memory element in digital electronics, the JK-latch. Our analysis shows that simple protein-protein interactions and protein-DNA binding are sufficient, in principle, to implement genetic circuits with the capabilities of a JK-latch. However, it also exposes fundamental limitations to its reliability, due to the fact that biological signal processing is asynchronous, in contrast to most digital electronics systems that feature a central clock to orchestrate the timing of all operations. We describe a seemingly natural way to improve the reliability by invoking the master-slave concept from digital electronics design. This concept could be useful to interpret the design of natural regulatory circuits, and for the design of synthetic biological systems.     

Adaptive rescaling maximizes information transmission

Adaptation is a widespread phenomenon in nervous systems, providing flexibility to function under varying external conditions. Here, we relate an adaptive property of a sensory system directly to its function as a carrier of information about input signals. We show that the input/output relation of a sensory system in a dynamic environment changes with the statistical properties of the environment. Specifically, when the dynamic range of inputs changes, the input/output relation rescales so as to match the dynamic range of responses to that of the inputs. We give direct evidence that the scaling of the input/output relation is set to maximize information transmission for each distribution of signals. This adaptive behavior should be particularly useful in dealing with the intermittent statistics of natural signals.     

Apoptosis,necrosis and autophagy are influenced by metabolic energy sources in cultured rat spermatocytes

Apoptosis, necrosis and autophagy are mechanistically related processes that control tissue homeostasis and cell survival. In the testis, germ cell death is important for controlling sperm output, but it is unknown whether or not germ cells can switch from apoptosis to necrosis, as has been reported in other tissues. Furthermore, autophagy has not been reported in spermatogenesis. Spermatocytes (meiotic cells) and spermatids (haploid cells) use lactate rather than glucose as their primary substrate for producing ATP. The metabolism of glucose, but not lactate, reduces ATP levels and increases intracellular [H⁺] and [Ca²⁺], both of which are associated with apoptosis and/or necrosis in somatic cells. In this work, we evaluated whether different energy sources, such as lactate or glucose, can influence spermatocyte death type and/or survival in primary cultures. Spermatocytes cultured for 12 h without an energy source died by necrosis, while spermatocytes cultured with 5 mM glucose showed a significant increase in apoptosis, as evidenced by caspase activity, TUNEL assay and phosphatidylserine exposure. Apoptosis was not observed in spermatocytes cultured with 5 mM lactate or deoxyglucose. Authophagy markers, such as LC3-II and autophagosomes, were detected after 12 h of culture, regardless the culture conditions. These results suggest that the availability of glucose and/or lactate affect the type of death or the survival of primary spermatocytes, where glucose can induce apoptosis, while lactate is a protective factor.     

Cultured trout liver cells: Utilization of substrates and response to hormones

Summary The characterization of a recently established system for the short-term culture of rainbow trout (Oncorhynchus mykiss) liver cells in chemically defined medium has been extended to studies on the metabolic competence of the cells and the characterization of their response to hormones. Three areas of metabolism have been addressed: a) the utilization of the exogenously added substrates fructose, lactate, glucose, dihydroxyacetone, and glycerol for glucose and lactate formation; b) the effects of the pancreatic hormones insulin and glucagon on cellular glucose formation, lactate formation, and fatty acid synthesis; and c) the effects of insulin and dexamethasone on the estradiol-dependent production of vitellogenin. Incubation of trout liver cells with fructose, lactate, glucose, dihydroxyacetone, or glycerol resulted in enhanced rates of cellular glucose and lactate production. Substrate-induced effects usually were more clearly expressed after extended (20 h) than after acute (5 h) culture periods. Addition of the hormones insulin or glucagon caused dose-dependent alterations in the flux of substrates to glucose and lactate. Rates of de novo synthesis of fatty acids from [¹⁴C]acetate were stimulated by insulin and inhibited by glucagon during acute and extended incubation periods. Treatment of liver cells isolated from male trout for 72 h with estradiol induced vitellogenin production and secretion into the medium. However, the addition of insulin or dexamethasone drastically reduced this estrogen-induced vitellogenesis. These results indicate that trout liver cells cultured in defined medium maintain central metabolic pathways, including glycolysis, gluconeogenesis, lipogenesis, and vitellogenesis as well as their responsiveness to various hormones, for at least 72 h. This cell culture system should provide an excellent model to further characterize metabolic processes in fish liver.     

A Visual Dual-Aptamer Logic Gate for Sensitive Discrimination of Prion Diseases-Associated Isoform with Reusable Magnetic Microparticles and Fluorescence Quantum Dots

Molecular logic gates, which have attracted increasing research interest and are crucial for the development of molecular-scale computers, simplify the results of measurements and detections, leaving the diagnosis of disease either “yes” or “no”. Prion diseases are a group of fatal neurodegenerative disorders that happen in human and animals. The main problem with a diagnosis of prion diseases is how to sensitively and selectively discriminate and detection of the minute amount of PrP^Res in biological samples. Our previous work had demonstrated that dual-aptamer strategy could achieve highly sensitive and selective discrimination and detection of prion protein (cellular prion protein, PrP^C, and the diseases associated isoform, PrP^Res) in serum and brain. Inspired by the advantages of molecular logic gate, we further conceived a new concept for dual-aptamer logic gate that responds to two chemical input signals (PrP^C or PrP^Res and Gdn-HCl) and generates a change in fluorescence intensity as the output signal. It was found that PrP^Res performs the “OR” logic operation while PrP^C performs “XOR” logic operation when they get through the gate consisted of aptamer modified reusable magnetic microparticles (MMPs-Apt1) and quantum dots (QDs-Apt2). The dual-aptamer logic gate simplifies the discrimination results of PrP^Res, leaving the detection of PrP^Res either “yes” or “no”. The development of OR logic gate based on dual-aptamer strategy and two chemical input signals (PrP^Res and Gdn-HCl) is an important step toward the design of prion diseases diagnosis and therapy systems.     

Monitoring liver alterations during hepatic tumorigenesis by NMR profiling and pattern recognition

Human hepatocellular carcinoma (HCC) is the most recurrent malignancy of the liver and represents one of the main causes of cancer death worldwide. Furthermore, the liver is the most frequent site of metastatic colonization, and hepatic metastases are far more common than primary cancers in Western countries. A possible way of investigating liver diseases is to study the tissue metabolic profiles. High-resolution nuclear magnetic resonance (NMR) spectroscopy of hepatic tissue extracts was combined with pattern-recognition and visualization techniques to uncover metabolic differences among analyzed tissue types. Extracts were from primary HCC, chronic hepatitis-C-virus related cirrhotic tissues, hepatic metastases from colorectal carcinomas, and non-cirrhotic normal liver tissues adjacent to metastases as controls. We identified all metabolites present in the NMR spectra, and after statistical evaluation of all spectral classes, we were able to define the metabolic changes underlying the different liver conditions and diseases. In particular, the lactate and the glucose tissue signals were found to primarily discriminate the different histological samples. We followed the biochemical changes of human hepatic lesions through primary (HCC) and secondary (metastases from colorectal carcinoma) liver tumors, cirrhotic tissues, and non-cirrhotic histologically-confirmed normal liver tissues adjacent to metastases, achieving a metabolic differentiation of the various pathological states based upon the variation of the intracellular lactate/glucose ratio. It is suggested that such a signal pattern may act as a potential marker for assessing pathological hepatic lesions.     

Controlling behavioral experiments with a new programming language (SORCA) for microcomputer systems

A new programming language SORCA has been defined and a compiler has been written for Z80-based microcomputer systems with CP/M operating system. The language was developed to control behavioral experiments by external stimuli and by time schedule in real-time. Eight binary hardware input lines are sampled cyclically by the computer and can be used to sense switches, level detectors and other binary information, while 8 binary hardware output lines, that are cyclically updated, can be used to control relays, lamps, generate tones or for other purposes. The typical reaction time (cycle time) of a SORCA-program is 500 microseconds to 1 ms. All functions can be programmed as often as necessary. Included are the basic logic functions, counters, timers, majority gates and other complex functions. Parameters can be given as constants or as a result of a step function or of a random process (with Gaussian or equal distribution). Several tasks can be performed simultaneously. In addition, results of an experiment (e.g., number of reactions or latencies) can be measured and printed out on request or automatically. The language is easy to learn and can also be used for many other control purposes.