Detection of Glutamate Encapsulated in Liposomes by Optical Trapping Raman Spectroscopy.

The transmission of neuronal information is propagated through synapses by neurotransmitters released from presynapses to postsynapses. Neurotransmitters released from the presynaptic vesicles activate receptors on the postsynaptic membrane. Glutamate acts as a major excitatory neurotransmitter for synaptic vesicles in the central nervous system. Determining the concentration of glutamate in single synaptic vesicles is essential for understanding the mechanisms of neuronal activation by glutamate in normal brain functions as well as in neurological diseases. However, it is difficult to detect and quantitatively measure the concentration of glutamate in single synaptic vesicles owing to their small size, i.e., ∼40 nm. In this study, to quantitatively evaluate the concentrations of the contents in small membrane-bound vesicles, we developed an optical trapping Raman spectroscopic system that analyzes the Raman spectra of small objects captured using optical trapping. Using artificial liposomes encapsulating glutamate that mimic synaptic vesicles, we investigated whether spontaneous Raman scattered light of glutamate can be detected from vesicles trapped at the focus using optical forces. A 575 nm laser beam was used to simultaneously perform the optical trapping of liposomes and the detection of the spontaneous Raman scattered light. The intensity of Raman scattered light that corresponds to lipid bilayers increased with time. This observation suggested that the number of liposomes increased at the focal point. The number of glutamate molecules in the trapped liposomes was estimated from the calibration curve of the Raman spectra of glutamate solutions with known concentration. This method can be used to measure the number of glutamate molecules encapsulated in synaptic vesicles in situ.

Deuterated Glutamate-Mediated Neuronal Activity on Micro-Electrode Arrays.

The excitatory synaptic transmission is mediated by glutamate in neuronal networks of the mammalian brain. In addition to the synaptic glutamate, extra-synaptic glutamate is known to modulate the neuronal activity. In neuronal networks, glutamate uptake is an important role of neurons and glial cells for lowering the concentration of extracellular glutamate and to avoid the excitotoxicity by glutamate. Monitoring the spatial distribution of intracellular glutamate is important to study the uptake of glutamate, but the approach has been hampered by the absence of appropriate glutamate analogs that report the localization of glutamate. Deuterium-labeled glutamate (GLU-D) is a promising tracer for monitoring the intracellular concentration of glutamate, but physiological properties of GLU-D have not been studied. Here we study the effects of extracellular GLU-D for the neuronal activity by using primary cultured rat hippocampal neurons that form neuronal networks on microelectrodes array. The frequency of firing in the spontaneous activity of neurons increased with the increasing concentration of extracellular GLU-D. The frequency of synchronized burst activity in neurons increased similarly as we observed in the spontaneous activity. These changes of the neuronal activity with extracellular GLU-D were suppressed by antagonists of glutamate receptors. These results suggest that GLU-D can be used as an analog of glutamate with equivalent effects for facilitating the neuronal activity. We anticipate GLU-D developing as a promising analog of glutamate for studying the dynamics of glutamate during neuronal activity.

Real-time fluorescence measurement of spontaneous activity in a high-density hippocampal network cultivated on a plasmonic dish.

High-density cultured neuronal networks have been used to evaluate synchronized features of neuronal populations. Voltage-sensitive dye (VSD) imaging of a dissociated cultured neuronal network is a critical method for studying synchronized neuronal activity in single cells. However, the signals of VSD are generally too faint-that is, the signal-to-noise ratio (S/N) is too low-to detect neuronal activity. In our previous research, a silver (Ag) plasmonic chip enhanced the fluorescence intensity of VSD to detect spontaneous neural spikes on VSD imaging. However, no high-density network was cultivated on the Ag plasmonic chip, perhaps because of the chemical instability of the Ag surface. In this study, to overcome the instability of the chip, we used a chemically stable gold (Au) plasmonic dish, which was a plastic dish with a plasmonic chip pasted to the bottom, to observe neuronal activity in a high-density neuronal network. We expected that the S/N in real-time VSD imaging of the Au plasmonic chip would be improved compared to that of a conventional glass-bottomed dish, and we also expected to detect frequent neural spikes. The increase in the number of spikes when inhibitory neurotransmitter receptors were inhibited suggests that the spikes corresponded to neural activity. Therefore, real-time VSD imaging of an Au plasmonic dish was effective for measuring spontaneous network activity in a high-density neuronal network at the spatial resolution of a single cell.

Learning process for identifying different types of communication via repetitive stimulation: feasibility study in a cultured neuronal network.

It is well known that various types of information can be learned and memorized via repetitive training. In brain information science, it is very important to determine how neuronal networks comprising neurons with fluctuating characteristics reliably learn and memorize information. The aim of this study is to investigate the learning process in cultured neuronal networks and to address the question described above. Previously, we reported that the spikes resulting from stimulation at a specific neuron propagate as a cluster of excitation waves called spike wave propagation in cultured neuronal networks. We also reported that these waves have an individual spatiotemporal pattern that varies according to the type of neuron that is stimulated. Therefore, different spike wave propagations can be identified via pattern analysis of spike trains at particular neurons. Here, we assessed repetitive stimulation using intervals of 0.5 and 1.5 ms. Subsequently, we analyzed the relationship between the repetition of the stimulation and the identification of the different spike wave propagations. We showed that the various spike wave propagations were identified more precisely after stimulation was repeated several times using an interval of 1.5 ms. These results suggest the existence of a learning process in neuronal networks that occurs via repetitive training using a suitable interval.

Asynchronous Multiplex Communication Channels in 2-D Neural Network With Fluctuating Characteristics.

Neurons behave like transistors, but have fluctuating characteristics. In this paper, we show that several asynchronous multiplex communication channels can be established in a 2-D mesh neural network with randomly generated weights between eight neighbors. Neurons were simulated by integrate-and-fire neuron models without leakage and with fluctuating refractory period and output delay. If one of the transmitting neuron groups is stimulated, the signal is propagated in the form of spike waves. The corresponding receiving neuron group is able to identify the signal after having learned to form an asynchronous multiplex communication channel. The channel is composed of many intermediate/interstitial neurons working as relays. Each neuron can work as an I/O and as a relay element, i.e., as a multiuse unit. Grouping and synchronic firing is often seen in natural neuronal networks and seems to be effective for stable/robust communication in conjunction with spatial multiplex communication. This communication pattern corresponds to our wet lab experiments on cultured neuronal networks and is similar to sound identification by the ear and mobile adaptive communication systems.

Effect of correlating adjacent neurons for identifying communications: Feasibility experiment in a cultured neuronal network.

Neuronal networks have fluctuating characteristics, unlike the stable characteristics seen in computers. The underlying mechanisms that drive reliable communication among neuronal networks and their ability to perform intelligible tasks remain unknown. Recently, in an attempt to resolve this issue, we showed that stimulated neurons communicate via spikes that propagate temporally, in the form of spike trains. We named this phenomenon "spike wave propagation". In these previous studies, using neural networks cultured from rat hippocampal neurons, we found that multiple neurons, e.g., 3 neurons, correlate to identify various spike wave propagations in a cultured neuronal network. Specifically, the number of classifiable neurons in the neuronal network increased through correlation of spike trains between current and adjacent neurons. Although we previously obtained similar findings through stimulation, here we report these observations on a physiological level. Considering that individual spike wave propagation corresponds to individual communication, a correlation between some adjacent neurons to improve the quality of communication classification in a neuronal network, similar to a diversity antenna, which is used to improve the quality of communication in artificial data communication systems, is suggested.

Enhanced fluorescence microscopy with the Bull's eye-plasmonic chip.

A Bull's eye-plasmonic chip composed of concentric circles was applied to enhanced fluorescence microscopy. Among one dimensional (1-D), 2-D, and Bull's eye periodic structures, the Bull's eye-plasmonic chip provided the most enhanced fluorescence intensity under the epi-fluorescence microscope, because incident light through the objective lens with all azimuthal angles can be effectively applied to the surface plasmon resonance- field (excitation field) and the plasmon-enhanced emission was also effectively collected. In the fluorescence observation of a single nanoparticle, the enhanced fluorescence images for a microsphere with ϕ 2 µm and a nanosphere with ϕ 200 nm were observed. For the nanospheres with ϕ 40 and 20 nm, the fluorescence image, which was undetectable on a glass slide, was observed in a spatial resolution of roughly diffraction limit on the Bull's eye-plasmonic chip. Furthermore, the use of an appropriate pinhole at the aperture stop in the incident optical system improved the fluorescence enhancement. The applicability of a Bull's eye-plasmonic chip to fluorescence imaging was demonstrated.

Spike Code Flow in Cultured Neuronal Networks.

We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of "1101" and "1011," which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the "maximum cross-correlations" among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.

Simulation of Code Spectrum and Code Flow of Cultured Neuronal Networks.

It has been shown that, in cultured neuronal networks on a multielectrode, pseudorandom-like sequences (codes) are detected, and they flow with some spatial decay constant. Each cultured neuronal network is characterized by a specific spectrum curve. That is, we may consider the spectrum curve as a "signature" of its associated neuronal network that is dependent on the characteristics of neurons and network configuration, including the weight distribution. In the present study, we used an integrate-and-fire model of neurons with intrinsic and instantaneous fluctuations of characteristics for performing a simulation of a code spectrum from multielectrodes on a 2D mesh neural network. We showed that it is possible to estimate the characteristics of neurons such as the distribution of number of neurons around each electrode and their refractory periods. Although this process is a reverse problem and theoretically the solutions are not sufficiently guaranteed, the parameters seem to be consistent with those of neurons. That is, the proposed neural network model may adequately reflect the behavior of a cultured neuronal network. Furthermore, such prospect is discussed that code analysis will provide a base of communication within a neural network that will also create a base of natural intelligence.

In situ sensitive fluorescence imaging of neurons cultured on a plasmonic dish using fluorescence microscopy.

A plasmonic dish was fabricated as a novel cell-culture dish for in situ sensitive imaging applications, in which the cover glass of a glass-bottomed dish was replaced by a grating substrate coated with a film of silver. Neuronal cells were successfully cultured over a period of more than 2 weeks in the plasmonic dish. The fluorescence images of their cells including dendrites were simply observed in situ using a conventional fluorescence microscope. The fluorescence from neuronal cells growing along the dish surface was enhanced using the surface plasmon resonance field. Under an epi-fluorescence microscope and employing a donut-type pinhole, the fluorescence intensity of the neuron dendrites was found to be enhanced efficiently by an order of magnitude compared with that using a conventional glass-bottomed dish. In a transmitted-light fluorescence microscope, the surface-selective fluorescence image of a fine dendrite growing along the dish surface was observed; therefore, the spatial resolution was improved compared with the epi-fluorescence image of the identical dendrite.

Carbon nanotube-liposome supramolecular nanotrains for intelligent molecular-transport systems.

Biological network systems, such as inter- and intra-cellular signalling systems, are handled in a sophisticated manner by the transport of molecular information. Over the past few decades, there has been a growing interest in the development of synthetic molecular-transport systems. However, several key technologies have not been sufficiently realized to achieve optimum performance of transportation methods. Here we show that a new type of supramolecular system comprising of carbon nanotubes and liposomes enables the directional transport and controlled release of carrier molecules, and allows an enzymatic reaction at a desired area. The study highlights important progress that has been made towards the development of biomimetic molecular-transport systems and various lab-on-a-chip applications, such as medical diagnosis, sensors, bionic computers and artificial biological networks.

Detection of M-sequences from spike sequence in neuronal networks.

In circuit theory, it is well known that a linear feedback shift register (LFSR) circuit generates pseudorandom bit sequences (PRBS), including an M-sequence with the maximum period of length. In this study, we tried to detect M-sequences known as a pseudorandom sequence generated by the LFSR circuit from time series patterns of stimulated action potentials. Stimulated action potentials were recorded from dissociated cultures of hippocampal neurons grown on a multielectrode array. We could find several M-sequences from a 3-stage LFSR circuit (M3). These results show the possibility of assembling LFSR circuits or its equivalent ones in a neuronal network. However, since the M3 pattern was composed of only four spike intervals, the possibility of an accidental detection was not zero. Then, we detected M-sequences from random spike sequences which were not generated from an LFSR circuit and compare the result with the number of M-sequences from the originally observed raster data. As a result, a significant difference was confirmed: a greater number of "0-1" reversed the 3-stage M-sequences occurred than would have accidentally be detected. This result suggests that some LFSR equivalent circuits are assembled in neuronal networks.

Bright, non-blinking, and less-cytotoxic SiO2 beads with multiple CdSe/ZnS nanocrystals.

A method including surface silanization, phase transfer and self-assembly, and SiO2 shell growth has been developed to incorporate multiple hydrophobic CdSe/ZnS nanocrystals into SiO2 beads where they are well suited for bio-application due to their high brightness, less-cytotoxic, and non-blinking nature.

Resynchronization in neuronal network divided by femtosecond laser processing.

We demonstrated scission of a living neuronal network on multielectrode arrays (MEAs) using a focused femtosecond laser and evaluated the resynchronization of spontaneous electrical activity within the network. By an irradiation of femtosecond laser into hippocampal neurons cultured on a multielectrode array dish, neurites were cut at the focal point. After the irradiation, synchronization of neuronal activity within the network drastically decreased over the divided area, indicating diminished functional connections between neurons. Cross-correlation analysis revealed that spontaneous activity between the divided areas gradually resynchronized within 10 days. These findings indicate that hippocampal neurons have the potential to regenerate functional connections and to reconstruct a network by self-assembly.

Cluster formation of nanoparticles in an optical trap studied by fluorescence correlation spectroscopy.

We report in situ observation of cluster growth of nanoparticles confined in an optical trapping potential by means of fluorescence correlation spectroscopy. When an optical trapping force caused by a highly focused laser beam acts on nanoparticle suspensions, the number of nanoparticles increases and an assembly can be formed at the focal spot. The decay times of fluorescence autocorrelation curves were investigated as a function of the irradiation time of the laser beam and the laser power. In the initial stage of the optical assembling, the decay time increases with the irradiation time of the laser beam. On the other hand, in the later stage, a decrease of the decay time was observed. This behavior is explained successfully by using two models of Brownian motion under weak and strong optical trapping. It was revealed that trapping and clustering of nanoparticles proceed simultaneously and clusters confined in the focal spot make larger aggregates spontaneously.

Secondary structure and secondary structure dynamics of DNA hairpins complexed with HIV-1 NC protein.

Reverse transcription of the HIV-1 RNA genome involves several complex nucleic acid rearrangement steps that are catalyzed by the HIV-1 nucleocapsid protein (NC), including for example, the annealing of the transactivation response (TAR) region of the viral RNA to the complementary region (TAR DNA) in minus-strand strong-stop DNA. We report herein single-molecule fluorescence resonance energy transfer measurements on single immobilized TAR DNA hairpins and hairpin mutants complexed with NC (i.e., TAR DNA/NC). Using this approach we have explored the conformational distribution and dynamics of the hairpins in the presence and absence of NC protein. The data demonstrate that NC shifts the equilibrium secondary structure of TAR DNA hairpins from a fully "closed" conformation to essentially one specific "partially open" conformation. In this specific conformation, the two terminal stems are "open" or unwound and the other stems are closed. This partially open conformation is arguably a key TAR DNA intermediate in the NC-induced annealing mechanism of TAR DNA.

Optical assembling dynamics of individual polymer nanospheres investigated by single-particle fluorescence detection.

When a laser beam is focused into colloidal nanoparticle suspensions, a number of nanoparticles can be confined in the focal spot due to an optical gradient force. To reveal the assembling dynamics of polymer nanoparticles, the assembling process was investigated by analyzing the time evolution of the fluorescence intensity of the nanoparticles. In a dilute suspension of 100-nm-sized particles, a stepwise increase of the fluorescence intensity corresponding to a trapped single nanoparticle was observed. Statistical analysis revealed that the initial assembling rate of nanoparticles was proportional to the laser power and concentration of particle suspensions as expected from the diffusion equation. In 40-nm-sized particle suspensions, blinking profiles of fluorescence intensity were obtained, in which 2-3 particles were simultaneously trapped and then escaped from the focal point. It is considered from statistical analyses and two-dimensional Monte Carlo simulations that this assembling phenomenon is attributable to cluster formation assisted by optical trapping.