Sunghoon Joo

Effects of ECM protein micropatterns on the migration and differentiation of adult neural stem cells.

The migration and differentiation of adult neural stem cells (aNSCs) are believed to be strongly influenced by the spatial distribution of extracellular matrix (ECM) proteins in the stem cell niche. In vitro culture platform, which involves the specific spatial distribution of ECM protein, could offer novel tools for better understanding of aNSC behavior in the spatial pattern of ECM proteins. In this work, we applied soft-lithographic technique to design simple and reproducible laminin (LN)-polylysine cell culture substrates and investigated how aNSCs respond to the various spatial distribution of laminin, one of ECM proteins enriched in the aNSC niche. We found that aNSC preferred to migrate and attach to LN stripes, and aNSC-derived neurons and astrocytes showed significant difference in motility towards LN stripes. By changing the spacing of LN stripes, we were able to control the alignment of neurons and astrocytes. To the best of our knowledge, this is the first time to investigate the differential cellular responses of aNSCs on ECM protein (LN) and cell adhesive synthetic polymer (PDL) using surface micropatterns. Our findings would provide a deeper understanding in astrocyte-neuron interactions as well as ECM-stem cell interactions.

Characterization of Axonal Spikes in Cultured Neuronal Networks Using Microelectrode Arrays and Microchannel Devices

Objective: Axonal propagation has a pivotal role in information processing in the brain. However, there has been little experimental study due to the difficulty of isolation of axons and recording their signals. Here, we developed dual chamber neuronal network interconnected with axons by integrating microchannel devices with microelectrode arrays (MEAs) to investigate axonal signals in developmental stage. Methods: The device was composed of two chambers and microchannels between them, and hippocampal neurons were cultured in both chambers. Neuronal activity was recorded for four weeks. Results: Large axonal signal was detected in microchannels, which were 137.0 ± 8.5 μV at 14 days in vitro (DIV). It was significantly larger than those in chambers with a similar range of signal-to-noise ratio. Detection efficiency of axonal spikes was analyzed by calculating the number of active electrodes over time. We found that active electrodes were detected earlier and their number increased faster in microchannels than those in chambers. Finally, we estimated the axonal conduction velocity and 73% of axons had the velocity in range of 0.2–0.5 m/s at 14 DIV. By estimating the velocity over the cultivation period, we observed that axonal conduction velocity increased linearly over time. Conclusion: Using MEAs and microchannel devices, we successfully detected large axonal signals and analyzed their detection efficiency and conduction velocity. We first showed the gradual increase in conduction velocity depending on cultivation days. Significance: The developed microchannel device integrated MEA may be applicable for the studies of axonal conduction in cultured neuronal networks.

Tissue-based metabolic labeling of polysialic acids in living primary hippocampal neurons

Significance The roles of cell-surface glycans remain elusive compared with those of proteins or lipids because of their diverse and dynamic nature. Metabolic incorporation of unnatural monosaccharides in the biochemical synthesis of glycans as a chemical reporter has been a successful method to investigate the functions of cell-surface glycans but has also left an issue of cytotoxicity for certain cells. In this work, we developed a tissue-based strategy for metabolic incorporation of a chemical reporter to primary neurons. We let an unnatural monosaccharide be metabolized by hippocampal tissues before dissociation into individual cells, and thereby, we could eliminate cytotoxicity. We used this method to describe, for the first time to our knowledge, the real-time distribution of polysialic acids on the membranes of neurons. The posttranslational modification of neural cell-adhesion molecule (NCAM) with polysialic acid (PSA) and the spatiotemporal distribution of PSA-NCAM play an important role in the neuronal development. In this work, we developed a tissue-based strategy for metabolically incorporating an unnatural monosaccharide, peracetylated N-azidoacetyl-d-mannosamine, in the sialic acid biochemical pathway to present N-azidoacetyl sialic acid to PSA-NCAM. Although significant neurotoxicity was observed in the conventional metabolic labeling that used the dissociated neuron cells, neurotoxicity disappeared in this modified strategy, allowing for investigation of the temporal and spatial distributions of PSA in the primary hippocampal neurons. PSA-NCAM was synthesized and recycled continuously during neuronal development, and the two-color labeling showed that newly synthesized PSA-NCAMs were transported and inserted mainly to the growing neurites and not significantly to the cell body. This report suggests a reliable and cytocompatible method for in vitro analysis of glycans complementary to the conventional cell-based metabolic labeling for chemical glycobiology.

Identification of feedback loops in neural networks based on multi-step Granger causality

MOTIVATION Feedback circuits are crucial network motifs, ubiquitously found in many intra- and inter-cellular regulatory networks, and also act as basic building blocks for inducing synchronized bursting behaviors in neural network dynamics. Therefore, the system-level identification of feedback circuits using time-series measurements is critical to understand the underlying regulatory mechanism of synchronized bursting behaviors. RESULTS Multi-Step Granger Causality Method (MSGCM) was developed to identify feedback loops embedded in biological networks using time-series experimental measurements. Based on multivariate time-series analysis, MSGCM used a modified Wald test to infer the existence of multi-step Granger causality between a pair of network nodes. A significant bi-directional multi-step Granger causality between two nodes indicated the existence of a feedback loop. This new identification method resolved the drawback of the previous non-causal impulse response component method which was only applicable to networks containing no co-regulatory forward path. MSGCM also significantly improved the ratio of correct identification of feedback loops. In this study, the MSGCM was testified using synthetic pulsed neural network models and also in vitro cultured rat neural networks using multi-electrode array. As a result, we found a large number of feedback loops in the in vitro cultured neural networks with apparent synchronized oscillation, indicating a close relationship between synchronized oscillatory bursting behavior and underlying feedback loops. The MSGCM is an efficient method to investigate feedback loops embedded in in vitro cultured neural networks. The identified feedback loop motifs are considered as an important design principle responsible for the synchronized bursting behavior in neural networks.

Stimuli-Responsive Neuronal Networking via Removable Alginate Masks

The neuron patterning method has been applied to cultured neuronal networks to achieve better reproducibility and various experimental conditions in brain research. However, as models of dynamic environments, conventional patterned neural networks having an unalterable structure formed by a preprogrammed substrate have limitations, such as replicating the changes in the physical structure of networks in vivo. This study presents a novel culture technique that can control the location of the neuronal cell bodies constituting the network and the connection of the isolated neuronal networks at a desired time point. Alginate hydrogel, which has a cell‐repellent property and is dissolvable by weak chemical treatment, is used as a background masking material for patterning. Axon growth from neural clusters to the background area formed by a microwell‐patterned alginate layer is possible due to removal of the alginate layer, triggering synchronized spontaneous firing of the neuronal clusters. This technique was combined with a microelectrode array system to observe dynamic changes in neuronal activity according to the transformed morphology of the network. Finally, the clustered network structure formed by this technique showed greatly improved spontaneous firing rates and spike amplitudes compared to the network model prepared using an existing uniform structure.

Power Laws in Neuronal Culture Activity from Limited Availability of a Shared Resource

We record spontaneous activity from a developing culture of dissociated rat hippocampal neurons in vitro using a multi electrode array. To statistically characterize activity, we look at the time intervals between recorded spikes, which, unlike neuronal avalanche sizes, do not require the selection of a time bin. The distribution of inter event intervals in our data approximate power laws at all recorded stages of development, with exponents that can be used to characterize the development of the culture. Synchronized bursting emerges as the culture matures, and these bursts show activity that decays approximately exponentially. From this, we propose a model for neuronal activity within bursts based on the consumption of a shared resource. Our model produces power law distributed avalanches in simulations, and is analytically demonstrated to produce power law distributed inter event intervals with an exponent close to that observed in our data. This indicates that power law distributions in neuronal avalanche size and other observables, can be also an artefact of exponentially decaying activity within synchronized bursts.

Cell-Type Dependent Effect of Surface-Patterned Microdot Arrays on Neuronal Growth

Surface micropatterns have been widely used as chemical cues to control the microenvironment of cultured neurons, particularly for neurobiological assays and neurochip designs. However, the cell-type dependency on the interactions between neurons and underlying micropatterns has been rarely investigated despite the inherent differences in the morphology of neuronal types. In this study, we used surface-printed microdot arrays to investigate the effect of the same micropatterns on the growth of mouse spinal interneuron, mouse hippocampal neurons, and rat hippocampal neurons. While mouse hippocampal neurons showed no significantly different growth on control and patterned substrates, we found the microdot arrays had different effects on early neuronal growth depending on the cell type; spinal interneurons tended to grow faster in length, whereas hippocampal neurons tended to form more axon collateral branches in response to the microdot arrays. Although there was a similar trend in the neurite length and branch number of both neurons changed across the microdot arrays with the expanded range of size and spacing, the dominant responses of each neuron, neurite elongation of mouse spinal interneurons and branching augmentation of rat hippocampal neurons were still preserved. Therefore, our results demonstrate that the same design of micropatterns could cause different neuronal growth results, raising an intriguing issue of considering cell types in neural interface designs.

Nanotopography-Promoted Formation of Axon Collateral Branches of Hippocampal Neurons

Axon collateral branches, as a key structural motif of neurons, allow neurons to integrate information from highly interconnected, divergent networks by establishing terminal boutons. Although physical cues are generally known to have a comprehensive range of effects on neuronal development, their involvement in axonal branching remains elusive. Herein, it is demonstrated that the nanopillar arrays significantly increase the number of axon collateral branches and also promote their growth. Immunostaining and biochemical analyses indicate that the physical interactions between the nanopillars and the neurons give rise to lateral filopodia at the axon shaft via cytoskeletal changes, leading to the formation of axonal branches. This report, demonstrates that nanotopography regulates axonal branching, and provides a guideline for the design of sophisticated neuron-based devices and scaffolds for neuro-engineering.

Accelerated Development of Hippocampal Neurons and Limited Adhesion of Astrocytes on Negatively Charged Surfaces

This work examines the development of primary neurons and astrocytes on thoroughly controlled functional groups. Negatively charged surfaces presenting carboxylate (COO-) or sulfonate (SO3-) groups prove beneficial to neuronal behavior, in spite of their supposed repulsive electrostatic interactions with cellular membranes. The adhesion and survival of primary hippocampal neurons on negatively charged surfaces are comparable to or slightly better than those on positively charged (poly-d-lysine-coated) surfaces, and neuritogenesis and neurite outgrowth are accelerated on COO- and SO3- surfaces. Moreover, such favorable influences of the negatively charged surfaces are only seen in neurons but not for astrocytes. Our results indicate that the in vitro developmental behavior of primary hippocampal neurons is sophisticatedly modulated by angstrom-sized differences in chemical structure or the charge density of the surface. We believe that this work provides new implications for understanding neuron-material interfaces as well as for establishing new ways to fabricate neuro-active surfaces.

Design and Fabrication of Miniaturized Neuronal Circuits on Microelectrode Arrays Using Agarose Hydrogel Micro-molding Technique

Dissociated neuronal cultures combined with planar-type microelectrode arrays (MEAs) have been used as a promising read-out platform for the application of cell-based biosensors. There are increasing interests in engineering neuronal cultures to form the desired network topology by surface micropatterning technology. Here, we report a long-term cultivation of primary hippocampal neurons on microelectrode arrays using soft-lithography. Ordered hippocampal neuronal networks were formed by seeding neurons in agarose-microwells and inducing neurite outgrowth through microgrooves. Unlike previous approaches, our technique allowed us to design networks with various microwells on microelectrode arrays with high repeatability. These hippocampal network chips were cultivated for 30 days with excellent pattern fidelity, and neural spikes were successfully measured. We also found that spontaneous activity of the networks could be enhanced by acute disinhibition of inhibitory synapses. The proposed patterning method for neuronal network chips will be a potentially powerful tool for cell-based drug-screening applications.