5-HT1A regulates axon outgrowth in a subpopulation of Drosophila serotonergic neurons.

Serotonergic neurons produce extensively branched axons that fill most of the central nervous system, where they modulate a wide variety of behaviors. Many behavioral disorders have been correlated with defective serotonergic axon morphologies. Proper behavioral output therefore depends on the precise outgrowth and targeting of serotonergic axons during development. To direct outgrowth, serotonergic neurons utilize serotonin as a signaling molecule prior to it assuming its neurotransmitter role. This process, termed serotonin autoregulation, regulates axon outgrowth, branching, and varicosity development of serotonergic neurons. However, the receptor that mediates serotonin autoregulation is unknown. Here we asked if serotonin receptor 5-HT1A plays a role in serotonergic axon outgrowth and branching. Using cultured Drosophila serotonergic neurons, we found that exogenous serotonin reduced axon length and branching only in those expressing 5-HT1A. Pharmacological activation of 5-HT1A led to reduced axon length and branching, whereas the disruption of 5-HT1A rescued outgrowth in the presence of exogenous serotonin. Altogether this suggests that 5-HT1A is a serotonin autoreceptor in a subpopulation of serotonergic neurons and initiates signaling pathways that regulate axon outgrowth and branching during Drosophila development.

nGauge: Integrated and Extensible Neuron Morphology Analysis in Python.

The study of neuron morphology requires robust and comprehensive methods to quantify the differences between neurons of different subtypes and animal species. Several software packages have been developed for the analysis of neuron tracing results stored in the standard SWC format. The packages, however, provide relatively simple quantifications and their non-extendable architecture prohibit their use for advanced data analysis and visualization. We developed nGauge, a Python toolkit to support the parsing and analysis of neuron morphology data. As an application programming interface (API), nGauge can be referenced by other popular open-source software to create custom informatics analysis pipelines and advanced visualizations. nGauge defines an extendable data structure that handles volumetric constructions (e.g. soma), in addition to the SWC linear reconstructions, while remaining lightweight. This greatly extends nGauge's data compatibility.

Bitbow Enables Highly Efficient Neuronal Lineage Tracing and Morphology Reconstruction in Single Drosophila Brains.

Identifying the cellular origins and mapping the dendritic and axonal arbors of neurons have been century old quests to understand the heterogeneity among these brain cells. Current Brainbow based transgenic animals take the advantage of multispectral labeling to differentiate neighboring cells or lineages, however, their applications are limited by the color capacity. To improve the analysis throughput, we designed Bitbow, a digital format of Brainbow which exponentially expands the color palette to provide tens of thousands of spectrally resolved unique labels. We generated transgenic Bitbow Drosophila lines, established statistical tools, and streamlined sample preparation, image processing, and data analysis pipelines to conveniently mapping neural lineages, studying neuronal morphology and revealing neural network patterns with unprecedented speed, scale, and resolution.

High density carbon fiber arrays for chronic electrophysiology, fast scan cyclic voltammetry, and correlative anatomy.

OBJECTIVE: Multimodal measurements at the neuronal level allow for detailed insight into local circuit function. However, most behavioral studies focus on one or two modalities and are generally limited by the available technology. APPROACH: Here, we show a combined approach of electrophysiology recordings, chemical sensing, and histological localization of the electrode tips within tissue. The key enabling technology is the underlying use of carbon fiber electrodes, which are small, electrically conductive, and sensitive to dopamine. The carbon fibers were functionalized by coating with Parylene C, a thin insulator with a high dielectric constant, coupled with selective re-exposure of the carbon surface using laser ablation. MAIN RESULTS: We demonstrate the use of this technology by implanting 16 channel arrays in the rat nucleus accumbens. Chronic electrophysiology and dopamine signals were detected 1 month post implant. Additionally, electrodes were left in the tissue, sliced in place during histology, and showed minimal tissue damage. SIGNIFICANCE: Our results validate our new technology and methods, which will enable a more comprehensive circuit level understanding of the brain.

Multispectral tracing in densely labeled mouse brain with nTracer.

SUMMARY: This note describes nTracer, an ImageJ plug-in for user-guided, semi-automated tracing of multispectral fluorescent tissue samples. This approach allows for rapid and accurate reconstruction of whole cell morphology of large neuronal populations in densely labeled brains. AVAILABILITY AND IMPLEMENTATION: nTracer was written as a plug-in for the open source image processing software ImageJ. The software, instructional documentation, tutorial videos, sample image and sample tracing results are available at https://www.cai-lab.org/ntracer-tutorial. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Quantitative simulation of extracellular single unit recording from the surface of cortex.

OBJECTIVE: Neural recording is important for a wide variety of clinical applications. Until recently, recording from the surface of the brain, even when using micro-electrocorticography (µECoG) arrays, was not thought to enable recording from individual neurons. Recent results suggest that when the surface electrode contact size is sufficiently small, it may be possible to record single neurons from the brain's surface. In this study, we use computational techniques to investigate the ability of surface electrodes to record the activity of single neurons. APPROACH: The computational model included the rat head, µECoG electrode, two existing multi-compartmental neuron models, and a novel multi-compartmental neuron model derived from patch clamp experiments in layer 1 of the cortex. MAIN RESULTS: Using these models, we reproduced single neuron recordings from µECoG arrays, and elucidated their possible source. The model resembles the experimental data when spikes originate from layer 1 neurons that are less than 60 µm from the cortical surface. We further used the model to explore the design space for surface electrodes. Although this model does not include biological or thermal noise, the results indicate the electrode contact area should be 100 µm2 or smaller to maintain a detectable waveform amplitude. Furthermore, the model shows the width of lateral insulation could be reduced, which may reduce scar formation, while retaining 95% of signal amplitude. SIGNIFICANCE: Overall, the model suggests single-unit surface recording is limited to neurons in layer 1 and further improvement in electrode design is needed.

Imaging Neural Architecture in Brainbow Samples.

The fluorescent protein revolution has made the light microscope the most widely used tool for studying biological structure from the single-molecule to whole organism scales. However, traditional approaches are limited in their ability to resolve components in highly complex structures, such as the brain. In recent years, this limitation has been circumvented by the development of multicolor labeling methods, termed Brainbow. Brainbow tools rely on site-specific recombinases to make stochastic "choices" between different combinations of fluorescent proteins so that structures in close proximity to one another can be resolved based on their color profile. These new approaches, however, call for more refined methods of sample preparation and imaging optimized for multispectral imaging, which are presented here. The most robust approach for generating useful Brainbow data combines immunohistology with multispectral laser scanning confocal microscopy. This chapter, therefore, focuses on this particular technique, though the imaging principle discussed here is applicable to other Brainbow approaches as well.

Protein-retention expansion microscopy of cells and tissues labeled using standard fluorescent proteins and antibodies.

Expansion microscopy (ExM) enables imaging of preserved specimens with nanoscale precision on diffraction-limited instead of specialized super-resolution microscopes. ExM works by physically separating fluorescent probes after anchoring them to a swellable gel. The first ExM method did not result in the retention of native proteins in the gel and relied on custom-made reagents that are not widely available. Here we describe protein retention ExM (proExM), a variant of ExM in which proteins are anchored to the swellable gel, allowing the use of conventional fluorescently labeled antibodies and streptavidin, and fluorescent proteins. We validated and demonstrated the utility of proExM for multicolor super-resolution (∼70 nm) imaging of cells and mammalian tissues on conventional microscopes.

Ciliobrevins as tools for studying dynein motor function.

Dyneins are a small class of molecular motors that bind to microtubules and walk toward their minus ends. They are essential for the transport and distribution of organelles, signaling complexes and cytoskeletal elements. In addition dyneins generate forces on microtubule arrays that power the beating of cilia and flagella, cell division, migration and growth cone motility. Classical approaches to the study of dynein function in axons involve the depletion of dynein, expression of mutant/truncated forms of the motor, or interference with accessory subunits. By necessity, these approaches require prolonged time periods for the expression or manipulation of cellular dynein levels. With the discovery of the ciliobrevins, a class of cell permeable small molecule inhibitors of dynein, it is now possible to acutely disrupt dynein both globally and locally. In this review, we briefly summarize recent work using ciliobrevins to inhibit dynein and discuss the insights ciliobrevins have provided about dynein function in various cell types with a focus on neurons. We temper this with a discussion of the need for studies that will elucidate the mechanism of action of ciliobrevin and as well as the need for experiments to further analyze the specificity of ciliobreviens for dynein. Although much remains to be learned about ciliobrevins, these small molecules are proving themselves to be valuable novel tools to assess the cellular functions of dynein.

Cytoplasmic dynein pushes the cytoskeletal meshwork forward during axonal elongation.

During development, neurons send out axonal processes that can reach lengths hundreds of times longer than the diameter of their cell bodies. Recent studies indicate that en masse microtubule translocation is a significant mechanism underlying axonal elongation, but how cellular forces drive this process is unknown. Cytoplasmic dynein generates forces on microtubules in axons to power their movement through 'stop-and-go' transport, but whether these forces influence the bulk translocation of long microtubules embedded in the cytoskeletal meshwork has not been tested. Here, we use both function-blocking antibodies targeted to the dynein intermediate chain and the pharmacological dynein inhibitor ciliobrevin D to ask whether dynein forces contribute to en bloc cytoskeleton translocation. By tracking docked mitochondria as fiducial markers for bulk cytoskeleton movements, we find that translocation is reduced after dynein disruption. We then directly measure net force generation after dynein disruption and find a dramatic increase in axonal tension. Taken together, these data indicate that dynein generates forces that push the cytoskeletal meshwork forward en masse during axonal elongation.

Drosophila growth cones advance by forward translocation of the neuronal cytoskeletal meshwork in vivo.

In vitro studies conducted in Aplysia and chick sensory neurons indicate that in addition to microtubule assembly, long microtubules in the C-domain of the growth cone move forward as a coherent bundle during axonal elongation. Nonetheless, whether this mode of microtubule translocation contributes to growth cone motility in vivo is unknown. To address this question, we turned to the model system Drosophila. Using docked mitochondria as fiduciary markers for the translocation of long microtubules, we first examined motion along the axon to test if the pattern of axonal elongation is conserved between Drosophila and other species in vitro. When Drosophila neurons were cultured on Drosophila extracellular matrix proteins collected from the Drosophila Kc167 cell line, docked mitochondria moved in a pattern indicative of bulk microtubule translocation, similar to that observed in chick sensory neurons grown on laminin. To investigate whether the C-domain is stationary or advances in vivo, we tracked the movement of mitochondria during elongation of the aCC motor neuron in stage 16 Drosophila embryos. We found docked mitochondria moved forward along the axon shaft and in the growth cone C-domain. This work confirms that the physical mechanism of growth cone advance is similar between Drosophila and vertebrate neurons and suggests forward translocation of the microtubule meshwork in the axon underlies the advance of the growth cone C-domain in vivo. These results highlight the need for incorporating en masse microtubule translocation, in addition to assembly, into models of axonal elongation.