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.     

Logic Gate Operation by DNA Translocation through Biological Nanopores

Logical operations using biological molecules, such as DNA computing or programmable diagnosis using DNA, have recently received attention. Challenges remain with respect to the development of such systems, including label-free output detection and the rapidity of operation. Here, we propose integration of biological nanopores with DNA molecules for development of a logical operating system. We configured outputs “1” and “0” as single-stranded DNA (ssDNA) that is or is not translocated through a nanopore; unlabeled DNA was detected electrically. A negative-AND (NAND) operation was successfully conducted within approximately 10 min, which is rapid compared with previous studies using unlabeled DNA. In addition, this operation was executed in a four-droplet network. DNA molecules and associated information were transferred among droplets via biological nanopores. This system would facilitate linking of molecules and electronic interfaces. Thus, it could be applied to molecular robotics, genetic engineering, and even medical diagnosis and treatment.     

DNA implementation of addition in which the input strands are separate from the operator strands

A DNA representation of Boolean logic for which the input strands are separate from the operator strands is described and used to construct a two-bit DNA adder. The successful operation of the adder for several test inputs demonstrates that digital molecular computation with a complexity of order 30 gates is feasible.     

A Single Pair of Neurons Modulates Egg-Laying Decisions in Drosophila

Animals have to judge environmental cues and choose the most suitable option for them from many different options. Female fruit flies selecting an optimum site to deposit their eggs is a biologically important reproductive behavior. When given the direct choice between ovipositing their eggs in a sucrose-containing medium or a caffeine-containing medium, female flies prefer the latter. However, the neural circuits and molecules that regulate this decision-making processes during egg-laying site selection remain poorly understood. In the present study, we found that amnesiac (amn) mutant flies show significant defects in egg-laying decisions, and such defects can be reversed by expressing the wild-type amn transgene in two dorsal paired medial (DPM) neurons in the brain. Silencing neuronal activity with an inward rectifier potassium channel (Kir2.1) in DPM neurons also impairs egg-laying decisions. Finally, the activity in mushroom body αβ neurons is required for the egg-laying behavior, suggesting a possible “DPM-αβ neurons” brain circuit modulating egg-laying decisions. Our results highlight the brain circuits and molecular mechanisms of egg-laying decisions in Drosophila.     

Transcription of Simian Virus 40 II. Hybridization of RNA Extracted from Different Lines of Transformed Cells to the Separated Strands of Simian Virus 40 DNA

The amount of simian virus 40 (SV40) DNA present in various SV40-transformed mouse cell lines and “revertants” isolated from them was determined. The number of viral DNA copies in the different cell lines ranged from 1.35 to 8.75 copies per diploid quantity of mouse cell DNA and from 2.2 to 14 copies per cell. The revertants had the same number of viral DNA copies per diploid quantity of mouse cell DNA as their parental cell lines. (However, they showed an increased number of viral DNA copies per cell due to their increased amount of DNA.) By using separated strands of SV40 DNA, the extent of each DNA strand transcribed into stable RNA species was determined for the transformed and “revertant” cell lines. From 30 to 80% of the “early” strand and from 0 to 20% of the “late” strand was present as stable RNA species in the cell lines tested. There was no alteration in the pattern of the stable viral RNA species present in three concanavalin A-selected revertants, whereas in a fluorodeoxyuridine-selected revertant there appeared to be less viral-specific RNA present in the cells.     

Chemically induced senescence in human stem cell‐derived neurons promotes phenotypic presentation of neurodegeneration

Modeling age‐related neurodegenerative disorders with human stem cells are difficult due to the embryonic nature of stem cell‐derived neurons. We developed a chemical cocktail to induce senescence of iPSC‐derived neurons to address this challenge. We first screened small molecules that induce embryonic fibroblasts to exhibit features characteristic of aged fibroblasts. We then optimized a cocktail of small molecules that induced senescence in fibroblasts and cortical neurons without causing DNA damage. The utility of the “senescence cocktail” was validated in motor neurons derived from ALS patient iPSCs which exhibited protein aggregation and axonal degeneration substantially earlier than those without cocktail treatment. Our “senescence cocktail” will likely enhance the manifestation of disease‐related phenotypes in neurons derived from iPSCs, enabling the generation of reliable drug discovery platforms.     

From the Phenomenology to the Mechanisms of Consciousness: Integrated Information Theory 3.0

This paper presents Integrated Information Theory (IIT) of consciousness 3.0, which incorporates several advances over previous formulations. IIT starts from phenomenological axioms: information says that each experience is specific – it is what it is by how it differs from alternative experiences; integration says that it is unified – irreducible to non-interdependent components; exclusion says that it has unique borders and a particular spatio-temporal grain. These axioms are formalized into postulates that prescribe how physical mechanisms, such as neurons or logic gates, must be configured to generate experience (phenomenology). The postulates are used to define intrinsic information as “differences that make a difference” within a system, and integrated information as information specified by a whole that cannot be reduced to that specified by its parts. By applying the postulates both at the level of individual mechanisms and at the level of systems of mechanisms, IIT arrives at an identity: an experience is a maximally irreducible conceptual structure (MICS, a constellation of concepts in qualia space), and the set of elements that generates it constitutes a complex. According to IIT, a MICS specifies the quality of an experience and integrated information Φ^Max its quantity. From the theory follow several results, including: a system of mechanisms may condense into a major complex and non-overlapping minor complexes; the concepts that specify the quality of an experience are always about the complex itself and relate only indirectly to the external environment; anatomical connectivity influences complexes and associated MICS; a complex can generate a MICS even if its elements are inactive; simple systems can be minimally conscious; complicated systems can be unconscious; there can be true “zombies” – unconscious feed-forward systems that are functionally equivalent to conscious complexes.     

A Formalized Design Process for Bacterial Consortia That Perform Logic Computing

The concept of microbial consortia is of great attractiveness in synthetic biology. Despite of all its benefits, however, there are still problems remaining for large-scaled multicellular gene circuits, for example, how to reliably design and distribute the circuits in microbial consortia with limited number of well-behaved genetic modules and wiring quorum-sensing molecules. To manage such problem, here we propose a formalized design process: (i) determine the basic logic units (AND, OR and NOT gates) based on mathematical and biological considerations; (ii) establish rules to search and distribute simplest logic design; (iii) assemble assigned basic logic units in each logic operating cell; and (iv) fine-tune the circuiting interface between logic operators. We in silico analyzed gene circuits with inputs ranging from two to four, comparing our method with the pre-existing ones. Results showed that this formalized design process is more feasible concerning numbers of cells required. Furthermore, as a proof of principle, an Escherichia coli consortium that performs XOR function, a typical complex computing operation, was designed. The construction and characterization of logic operators is independent of “wiring” and provides predictive information for fine-tuning. This formalized design process provides guidance for the design of microbial consortia that perform distributed biological computation.     

Ultrasensitive DNA detection by cycle isothermal amplification based on nicking endonuclease and its application to logic gates

In recent years, an intense interest has grown in the DNA logic gates having high potential for computation at literally the “nano-size” level. A limitation of traditional DNA logic gates is that each target strand hybridizes with only a single copy of the probe. This 1:1 hybridization radio limits the gain of the approach and thus its sensitivity. The exponential amplification of nucleic acids has become a core technology in medical diagnostics and has been widely used for the construction of DNA sensor, DNA nanomachine and DNA sequencing. It would be of great interest to develop DNA-based logic systems with exponential amplification for the output signal. In the present study, a series of three-input DNA logic gates with the cycle isothermal amplification based on nicking endonuclease (NEase) are designed. Very low concentrations of the analytes were sufficient to initiate an autocatalytic cascade, achieving a significant improvement of the detection limit, 100-fold improvement compared to the non-autocatalytic system. This was achieved by engineering a simple and flexible biological circuit designed to initiate a cascade of events to detect and amplify a specific DNA sequence. This procedure has the potential to greatly simplify the logic operation because amplification can be performed in “one-pot”.     

Unpaired bases in superhelical DNA: kinetic evidence

Kinetic analysis of the early, fast reaction of superhelical DNA with formaldehyde reveals that this region or regions is 56% “single strand like” in character. Hydrogen-tritium exchange studies coupled with other considerations show that this reaction is not due to a difference in conformational motility between form I and form II molecules, but is due to unpaired or weakly hydrogen bonded, localized region(s) of the form I allomorph of circular DNA.     

Injection of Fully-Defined Signal Mixtures: A Novel High-Throughput Tool to Study Neuronal Encoding and Computations

Understanding of how neurons transform fluctuations of membrane potential, reflecting input activity, into spike responses, which communicate the ultimate results of single-neuron computation, is one of the central challenges for cellular and computational neuroscience. To study this transformation under controlled conditions, previous work has used a signal immersed in noise paradigm where neurons are injected with a current consisting of fluctuating noise that mimics on-going synaptic activity and a systematic signal whose transmission is studied. One limitation of this established paradigm is that it is designed to examine the encoding of only one signal under a specific, repeated condition. As a result, characterizing how encoding depends on neuronal properties, signal parameters, and the interaction of multiple inputs is cumbersome. Here we introduce a novel fully-defined signal mixture paradigm, which allows us to overcome these problems. In this paradigm, current for injection is synthetized as a sum of artificial postsynaptic currents (PSCs) resulting from the activity of a large population of model presynaptic neurons. PSCs from any presynaptic neuron(s) can be now considered as “signal”, while the sum of all other inputs is considered as “noise”. This allows us to study the encoding of a large number of different signals in a single experiment, thus dramatically increasing the throughput of data acquisition. Using this novel paradigm, we characterize the detection of excitatory and inhibitory PSCs from neuronal spike responses over a wide range of amplitudes and firing-rates. We show, that for moderately-sized neuronal populations the detectability of individual inputs is higher for excitatory than for inhibitory inputs during the 2–5 ms following PSC onset, but becomes comparable after 7–8 ms. This transient imbalance of sensitivity in favor of excitation may enhance propagation of balanced signals through neuronal networks. Finally, we discuss several open questions that this novel high-throughput paradigm may address.     

Challenges and dreams: physics of weak interactions essential to life

Biological systems display stunning capacities to self-organize. Moreover, their subcellular architectures are dynamic and responsive to changing needs and conditions. Key to these properties are manifold weak “quinary” interactions that have evolved to create specific spatial networks of macromolecules. These specific arrangements of molecules enable signals to be propagated over distances much greater than molecular dimensions, create phase separations that define functional regions in cells, and amplify cellular responses to changes in their environments. A major challenge is to develop biochemical tools and physical models to describe the panoply of weak interactions operating in cells. We also need better approaches to measure the biases in the spatial distributions of cellular macromolecules that result from the integrated action of multiple weak interactions. Partnerships between cell biologists, biochemists, and physicists are required to deploy these methods. Together these approaches will help us realize the dream of understanding the biological “glue” that sustains life at a molecular and cellular level.     

Isolation and Characterization of Chloroplast DNA from the Marine Chromophyte, Olisthodiscus luteus: Electron Microscopic Visualization of Isomeric Molecular Forms

Chloroplast DNA (ctDNA) from the marine chromophytic alga, Olisthodiscus luteus, has been isolated using a whole cell lysis method followed by CsCl-Hoechst 33258 dye gradient centrifugation. This DNA, which has a buoyant density of 1.691 grams per cubic centimeter was identified as plastidic in origin by enrichment experiments. Inclusion of the nuclease inhibitor aurintricarboxylic acid in all lysis buffers was mandatory for isolation of high molecular weight DNA. Long linear molecules (40 to 48 micrometers) with considerable internal organization comprised the majority of the ctDNA isolated, whereas supertwisted ctDNA and open circular molecules averaging 46 micrometers were occasionally present. Also observed in this study were folded ctDNA molecules with electron dense centers (“rosettes”) and plastid DNA molecules which have a tightly wound “key-ring” center. The ctDNA of Olisthodiscus has a contour length that is median to the size range reported for chlorophytic plants.     

Statistical Analysis of Molecular Signal Recording

A molecular device that records time-varying signals would enable new approaches in neuroscience. We have recently proposed such a device, termed a “molecular ticker tape”, in which an engineered DNA polymerase (DNAP) writes time-varying signals into DNA in the form of nucleotide misincorporation patterns. Here, we define a theoretical framework quantifying the expected capabilities of molecular ticker tapes as a function of experimental parameters. We present a decoding algorithm for estimating time-dependent input signals, and DNAP kinetic parameters, directly from misincorporation rates as determined by sequencing. We explore the requirements for accurate signal decoding, particularly the constraints on (1) the polymerase biochemical parameters, and (2) the amplitude, temporal resolution, and duration of the time-varying input signals. Our results suggest that molecular recording devices with kinetic properties similar to natural polymerases could be used to perform experiments in which neural activity is compared across several experimental conditions, and that devices engineered by combining favorable biochemical properties from multiple known polymerases could potentially measure faster phenomena such as slow synchronization of neuronal oscillations. Sophisticated engineering of DNAPs is likely required to achieve molecular recording of neuronal activity with single-spike temporal resolution over experimentally relevant timescales.     

Double Strand Break Unwinding and Resection by the Mycobacterial Helicase-Nuclease AdnAB in the Presence of Single Strand DNA-binding Protein (SSB)

Mycobacterial AdnAB is a heterodimeric DNA helicase-nuclease and 3′ to 5′ DNA translocase implicated in the repair of double strand breaks (DSBs). The AdnA and AdnB subunits are each composed of an N-terminal motor domain and a C-terminal nuclease domain. Inclusion of mycobacterial single strand DNA-binding protein (SSB) in reactions containing linear plasmid dsDNA allowed us to study the AdnAB helicase under conditions in which the unwound single strands are coated by SSB and thereby prevented from reannealing or promoting ongoing ATP hydrolysis. We found that the AdnAB motor catalyzed processive unwinding of 2.7–11.2-kbp linear duplex DNAs at a rate of ∼250 bp s⁻¹, while hydrolyzing ∼5 ATPs per bp unwound. Crippling the AdnA phosphohydrolase active site did not affect the rate of unwinding but lowered energy consumption slightly, to ∼4.2 ATPs bp⁻¹. Mutation of the AdnB phosphohydrolase abolished duplex unwinding, consistent with a model in which the “leading” AdnB motor propagates a Y-fork by translocation along the 3′ DNA strand, ahead of the “lagging” AdnA motor domain. By tracking the resection of the 5′ and 3′ strands at the DSB ends, we illuminated a division of labor among the AdnA and AdnB nuclease modules during dsDNA unwinding, whereby the AdnA nuclease processes the unwound 5′ strand to liberate a short oligonucleotide product, and the AdnB nuclease incises the 3′ strand on which the motor translocates. These results extend our understanding of presynaptic DSB processing by AdnAB and engender instructive comparisons with the RecBCD and AddAB clades of bacterial helicase-nuclease machines.     

Thematic Minireview Series: Molecular Mechanisms of Synaptic Plasticity

The human brain contains ∼86 billion neurons, which are precisely organized in specific brain regions and nuclei. High fidelity synaptic communication between subsets of neurons in specific circuits is required for most human behaviors, and is often disrupted in neuropsychiatric disorders. The presynaptic axon terminals of one neuron release neurotransmitters that activate receptors on multiple postsynaptic neuron targets to induce electrical and chemical responses. Typically, postsynaptic neurons integrate signals from multiple presynaptic neurons at thousands of synaptic inputs to control downstream communication to the next neuron in the circuit. Importantly, the strength (or efficiency) of signal transmission at each synapse can be modulated on time scales ranging up to the lifetime of the organism. This “synaptic plasticity” leads to changes in overall neuronal circuit activity, resulting in behavioral modifications. This series of minireviews will focus on recent advances in our understanding of the molecular and cellular mechanisms that control synaptic plasticity.     

Manipulation of single polymerase-DNA complexes: A mechanical view of DNA unwinding during replication

Comment on: Morin JA, et al. Proc Natl Acad Sci USA 2012; 109:8115-20.DNA replication requires overcoming the energetic barrier associated with the base pair melting of its double helix and a fine-tuned coordination between the processes of DNA unwinding and DNA replication. One intriguing question that remains poorly understood is the exact mechanism of the coupling of these two reactions. In some organisms, these activities are coupled within the same protein, like in the case of the phage Phi29 DNA polymerase. This polymerase works as a hybrid polymerase-helicase, because it presents an amino acid insertion that together with other protein domains forms a narrow tunnel around the template strand. This topological restriction is similar to the one imposed by hexameric helicases at the fork junction and promotes the separation of the fork ahead.¹ The Phi29 DNA polymerase, therefore, constitutes a simple, good model system to understand the basic mechanistic principles of the coupling between DNA replication and unwinding activities: the polymerase may behave as a “passive” unwinding motor, if translocation of the protein traps transient unwinding fluctuations of the fork, or as an “active” motor, if the polymerase actively destabilizes the duplex DNA at the junction. Therefore, factors that affect the stability of the fork junction, as DNA sequence or mechanical destabilization of the fork, will have a stronger effect on the unwinding kinetics of a “passive” motor than on an “active” one.To determine the DNA unwinding mechanism of the Phi29 DNA polymerase, we used optical tweezers to measure at single molecule level the effect of DNA sequence and destabilizing forces on the fork on the rates of strand displacement (replication and unwinding are tightly coupled, Δx₁, Fig. 1A) and primer extension (replication of the displaced complementary strand without unwinding, Δx₂, Fig. 1A) of two polymerases: the wild-type Phi29 DNA polymerase and a strand displacement deficient variant, which bears a couple of mutations that may affect the stability of the tunnel required for unwinding.² We quantified the free energy of interaction between the polymerase and the DNA fork, ΔG_int, and the range of this interaction, M, through a theoretical analysis of the dependence of the replication, unwinding and pause kinetics on the DNA sequence and force.^3,4Open in a separate windowFigure 1. (A) Schematic representation of the experimental design (not to scale). A single DNA hairpin was attached to functionalized beads inside a fluidics chamber. One strand of the hairpin is attached through a dsDNA handle to a bead held in the optical trap (top), while the complementary strand is attached to a bead on top of a mobile micropipette (bottom). At a constant force, after flowing the nucleotides into the reaction chamber, the strand displacement and primer extension rates of the polymerase are detected as a change in distance between the beads, Δx₁ and Δx₂, respectively. (B) Representative replication activity of a single mutant polymerase molecule. Long pauses are observed only during the strand displacement reaction. (C) Mechanistic distinction between passive and active unwinding. The cartoon illustrates the degree of activeness in DNA unwinding of different replicative helicases⁶ and the Phi29 DNA polymerase.Our results show that while the primer extension rates of both polymerases are force- and sequence-independent their average unwinding rates are sensitive to these two variables, although with different intensity. As expected, the dsDNA fork presents a much stronger physical barrier to the mutant polymerase unwinding. Qualitative reasoning might suggest that the observed differences imply different “activeness” of the unwinding mechanism of each polymerase. However, the inclusion of the pause kinetics of each polymerase in our model revealed that they use the same active mechanism; they both destabilize the two nearest base pairs of the fork (M = 2) with an interaction energy ΔG_int = 2 k_BT per base pair. These results suggest that mutations affecting the stability of the tunnel required for unwinding do not decrease the “activeness” of the motor but instead increase the probability of the unwinding mechanism to fail upon encountering a closed fork junction, inducing the entrance of the mutant polymerase into a long-lived inactive pause state (Fig. 1B). These results bring out the importance to consider pause kinetics to accurately quantify the actual unwinding mechanism of the Phi29 DNA polymerase or any other nucleic acid unwinding motor in which pauses are relevant during its operation. The presence of pauses obscures the actual pause-free rates of the motor and can lead to misleading results when they are not properly accounted.Our data are consistent with a model in which the closed template tunnel that wraps around the template strand allows the Phi29 DNA polymerase to maintain a sharp bending of this strand (essential for template reading in all replicative polymerases) and a bending of the complementary strand, due to its steric exclusion, at a closed fork junction. Bending of the two strands would generate mechanical stress at the junction promoting its active destabilization. A less stable tunnel, as in the mutant polymerase, will not be able to keep the mechanical stress at a closed fork junction, in this case the fork pressure would induce loosening of the correct protein-DNA interactions favoring the entrance to a polymerization inactive state.Similar mechanisms for mechanical destabilization of the fork junction can be envisioned for other DNA replication systems in which a DNA polymerase and a helicase work in coordination. In these systems, the leading strand can be sharply bent by the steric exclusion induced by the helicase and by the functional binding of the polymerase generating effective mechanical stress at the fork junction to account for efficient unwinding during replication. These implications are further supported by recent single molecule studies using magnetic tweezers that describe a collaborative coupling of this nature between the activities of the bacteriophage T4 DNA polymerase and DNA helicase.⁵     

Slowness: An Objective for Spike-Timing–Dependent Plasticity?

Our nervous system can efficiently recognize objects in spite of changes in contextual variables such as perspective or lighting conditions. Several lines of research have proposed that this ability for invariant recognition is learned by exploiting the fact that object identities typically vary more slowly in time than contextual variables or noise. Here, we study the question of how this “temporal stability” or “slowness” approach can be implemented within the limits of biologically realistic spike-based learning rules. We first show that slow feature analysis, an algorithm that is based on slowness, can be implemented in linear continuous model neurons by means of a modified Hebbian learning rule. This approach provides a link to the trace rule, which is another implementation of slowness learning. Then, we show analytically that for linear Poisson neurons, slowness learning can be implemented by spike-timing–dependent plasticity (STDP) with a specific learning window. By studying the learning dynamics of STDP, we show that for functional interpretations of STDP, it is not the learning window alone that is relevant but rather the convolution of the learning window with the postsynaptic potential. We then derive STDP learning windows that implement slow feature analysis and the “trace rule.” The resulting learning windows are compatible with physiological data both in shape and timescale. Moreover, our analysis shows that the learning window can be split into two functionally different components that are sensitive to reversible and irreversible aspects of the input statistics, respectively. The theory indicates that irreversible input statistics are not in favor of stable weight distributions but may generate oscillatory weight dynamics. Our analysis offers a novel interpretation for the functional role of STDP in physiological neurons.