Neuroscience

Three-dimensional bioprinting utilizes additive manufacturing processes that combine cells and a bioink to create living tissue models that mimic tissues found in vivo. Stem cells can regenerate and differentiate into specialized cell types, making them valuable for research concerning degenerative diseases and their potential treatments. 3D bioprinting stem cell–derived tissues have an advantage over other cell types because they can be expanded in large quantities and then differentiated to multiple cell types. Using patient-derived stem cells also enables a personalized medicine approach to the study of disease progression. In particular, mesenchymal stem cells (MSC) are an attractive cell type for bioprinting because they are easier to obtain from patients in comparison to pluripotent stem cells, and their robust characteristics make them desirable for bioprinting. Currently, both MSC bioprinting protocols and cell culturing protocols exist separately, but there is a lack of literature that combines the culturing of the cells with the bioprinting process. This protocol aims to bridge that gap by describing the bioprinting process in detail, starting with how to culture cells pre-printing, to 3D bioprinting the cells, and finally to the culturing process post-printing. Here, we outline the process of culturing MSCs to produce cells for 3D bioprinting. We also describe the process of preparing Axolotl Biosciences TissuePrint - High Viscosity (HV) and Low Viscosity (LV) bioink, the incorporation of MSCs to the bioink, setting up the BIO X and the Aspect RX1 bioprinters, and necessary computer-aided design (CAD) files. We also detail the differentiation of 2D and 3D cell cultures of MSC to dopaminergic neurons, including media preparation. We have also included the protocols for viability, immunocytochemistry, electrophysiology, and performing a dopamine enzyme-linked immunosorbent assay (ELISA), along with the statistical analysis.

Graphical overview

The electroencephalogram (EEG) is a powerful tool for analyzing neural activity in various neurological disorders, both in animals and in humans. This technology has enabled researchers to record the brain’s abrupt changes in electrical activity with high resolution, thus facilitating efforts to understand the brain’s response to internal and external stimuli. The EEG signal acquired from implanted electrodes can be used to precisely study the spiking patterns that occur during abnormal neural discharges. These patterns can be analyzed in conjunction with behavioral observations and serve as an important means for accurate assessment and quantification of behavioral and electrographic seizures. Numerous algorithms have been developed for the automated quantification of EEG data; however, many of these algorithms were developed with outdated programming languages and require robust computational hardware to run effectively. Additionally, some of these programs require substantial computation time, reducing the relative benefits of automation. Thus, we sought to develop an automated EEG algorithm that was programmed using a familiar programming language (MATLAB), and that could run efficiently without extensive computational demands. This algorithm was developed to quantify interictal spikes and seizures in mice that were subjected to traumatic brain injury. Although the algorithm was designed to be fully automated, it can be operated manually, and all the parameters for EEG activity detection can be easily modified for broad data analysis. Additionally, the algorithm is capable of processing months of lengthy EEG datasets in the order of minutes to hours, reducing both analysis time and errors introduced through manual-based processing.

The zebrafish retina is a canonical vertebrate retina. Since the past few years, with the continually growing genetic toolbox and imaging techniques, zebrafish plays a crucial role in retinal research. This protocol describes a method to quantitatively evaluate the expression of Arrestin3a (Arr3a) and G-protein receptor kinase7a (Grk7a) in the adult zebrafish retina at protein levels by infrared fluorescence western blot. Our protocol can be easily adapted to measure protein levels in additional zebrafish tissues.

Molecular characterization of different cell types in rodent brains is a widely used and important approach in neuroscience. Fluorescent detection of transcripts using RNAscope (ACDBio) has quickly became a standard in situ hybridization (ISH) approach. Its sensitivity and specificity allow for the simultaneous detection of between three and forty-eight low abundance mRNAs in single cells (i.e., multiplexing or hiplexing), and, in contrast to other ISH techniques, it is performed in a shorter amount of time. Manual quantification of transcripts is a laborious and time-consuming task even for small portions of a larger tissue section. Herein, we present a protocol for creating high-quality images for quantification of RNAscope-labeled neurons in the rat brain. This protocol uses custom-made scripts within the open-source software QuPath to create an automated workflow for the careful optimization and validation of cell detection parameters. Moreover, we describe a method to derive mRNA signal thresholds using negative controls. This protocol and automated workflow may help scientists to reliably and reproducibly prepare and analyze rodent brain tissue for cell type characterization using RNAscope.

Graphical abstract

Targeting receptor-mediated transcytosis (RMT) is a successful strategy for drug delivery of biologic agents across the blood-brain barrier (BBB). The recent development of human BBB organoid models is a major advancement to help characterize the mechanisms of RMT and thus accelerate the design of brain delivery technologies. BBB organoids exhibit self-organization, which resembles the architecture of the neurovascular unit, and low paracellular permeability, due to the formation of tight junctions between endothelial cells. However, current methods of organoid generation have low throughput, exhibit substantial heterogeneity across experiments, and require extensive manual handling. These limitations prevent the use of BBB organoids as a screening tool for discovery and optimization of therapeutic molecules. In this protocol, we use hydrogel-based arrays to generate human BBB organoids, with a 35-fold increase in organoid yield as compared to previous protocols using 96-well plates. We incubate BBB organoid arrays with monoclonal antibody-based constructs and use a custom semi-automated imaging assay to assess RMT within the organoid core. The experimental and analytical tools described in this protocol provide a scalable platform that can be incorporated in the early stages of drug discovery to accelerate the development and optimization of brain delivery technologies to cross the BBB.

Thermotaxis behaviors in C. elegans exhibit experience-dependent plasticity of thermal preference memory. This behavior can be assayed either at population level, on linear temperature gradients, or at the individual animal level, by radial isothermal or microfluidic tracking of orientation. These behaviors are low-throughput as well as variable, due to the inherent sensitivity to environmental perturbations. To facilitate reproducible studies, we describe an updated apparatus design that enables simultaneous runs of three thermal preference assays, instead of single-run assays described previously. By enabling parallel runs of control and experimental conditions, this set-up enables more throughput and rigorous assessment of behavioral variability.

Optogenetics has the potential to transform the study of the peripheral nervous system (PNS), but the complex anatomy of the PNS poses unique challenges for the focused delivery of light to specific tissues. This protocol describes the fabrication of a wireless telemetry system for studying peripheral sensory pathways. Unlike existing wireless approaches, the low-power wireless telemetry offers organ specificity via a sandwiched pre-curved tether, and enables high-throughput analysis of behavioral experiments with a channel isolation strategy. We describe the technical procedures for the construction of these devices, the wireless power transmission (TX) system with antenna coils, and their implementation for in vivo experimental applications. In total, the timeline of the procedure, including device fabrication, implantation, and preparation to begin in vivo experimentation can be completed in ~2-4 weeks. Implementation of these devices allows for chronic (>1 month) wireless optogenetic manipulation of peripheral neural pathways in freely behaving animals navigating homecage environments (up to 8).

The blood-brain barrier (BBB), a crucial protection mechanism in the central nervous system (CNS), is a selective barrier comprised of endothelial cells. It hampers the development of therapeutic and diagnostic tools for neurological diseases due to the poor penetration of most of these agents. Rationally engineered nanoparticles (NP) can facilitate the transport of therapeutic and diagnostic agents across the BBB. However, evaluating BBB penetration by NP majorly relies on the use of expensive and time-consuming animal experiments with low throughput. In vitro BBB models composed of brain endothelial cells can be a useful tool to rapidly screen multiple NP formulations to compare their BBB penetration ability and identify optimal formulations for in vivo validation. In this protocol, we present an in vitro model of BBB developed using murine cerebral cortex endothelial cells (bEnd.3). bEnd.3 is a commercially available, easy to manipulate cell line that forms tight junctions with potent paracellular barrier property. The protocol includes culturing of bEnd.3 cells, establishment of the in vitro model, and assessing NP permeability. We believe that, due to its simplicity and consistency, this step-by-step protocol can be easily used by researchers to screen NP-based drug delivery systems for BBB penetration.

Graphic abstract:

Over the past decade, zebrafish have emerged as a powerful model for the study of vertebrate sleep and wake behaviors. Experimental evidence has demonstrated behavioral, anatomical, genetic, and pharmacological conservation of sleep between zebrafish and mammals, suggesting that discoveries in zebrafish can inform our understanding of mammalian sleep. Here, we describe a protocol for performing sleep behavioral experiments in larval zebrafish, using a high-throughput video tracking system. We explain how to set up a sleep behavioral experiment and provide guidelines on how to analyze the data. Using this protocol, a typical experiment can be completed in less than five days, and this method provides a scalable platform to perform genetic and pharmacological screens in a simple and cost-effective vertebrate model. By combining high-throughput behavioral assays with several advantageous features of zebrafish, this model system provides new opportunities to make discoveries that clarify the genetic and neurological mechanisms that regulate sleep.

In neurons, local translation in dendritic and axonal compartments allows for the fast and on-demand modification of the local proteome. As the last few years have witnessed dramatic advancements in our appreciation of the brain’s neuronal diversity, it is increasingly relevant to understand how local translation is regulated according to cell type. To this end, both sequencing-based and imaging-based techniques have recently been reported. Here, we present a subcellular single cell RNA sequencing protocol that allows molecular quantification from the soma and dendrites of single neurons, and which can be scaled up for the characterization of several hundreds to thousands of neurons. Somata and dendrites of cultured neurons are dissected using laser capture microdissection, followed by cell lysis to release mRNA content. Reverse transcription is then conducted using an indexed primer that allows the downstream pooling of samples. The pooled cDNA library is prepared for and sequenced in an Illumina platform. Finally, the data generated are processed and converted into a gene vs. cells digital expression table. This protocol provides detailed instructions for both wet lab and bioinformatic steps, as well as insights into controls, data analysis, interpretations, and ways to achieve robust and reproducible results.

Graphic abstract:

Subcellular Single Cell RNA-seq in Neurons.