NeuriteQuant: an open source toolkit for high content screens of neuronal morphogenesis

Tracing Cellular Senescence in Bone: Time-Dependent Changes in Osteocyte Cytoskeleton Mechanics and Morphology

Aging-related bone loss significantly impacts the growing elderly population globally, leading to debilitating conditions such as osteoporosis. Senescent osteocytes play a crucial role in the aging process of bone. This longitudinal study examines the impact of continuous local and paracrine exposure to senescence-associated secretory phenotype (SASP) factors on biophysical and biomolecular markers in osteocytes. Significant cytoskeletal stiffening in irradiated (IR) osteocytes are found, accompanied by expansion of F-actin areas and a decline in dendritic integrity. These changes, correlating with alterations in pro-inflammatory cytokine levels and osteocyte-specific gene expression, support the reliability of biophysical markers for identifying senescent osteocytes. Notably, local accumulation of SASP factors have a more pronounced impact on osteocyte biophysical properties than paracrine effects, suggesting that the interplay between local and paracrine exposure can substantially influence cellular aging. This study underscores the importance of osteocyte mechanical and morphological properties as biophysical markers of senescence, highlighting their time dependence and differential effects of local and paracrine SASP exposure. Collectively, the investigation into biophysical senescence markers offers unique and reliable functional hallmarks for the non-invasive identification of senescent osteocytes, providing insights that can inform therapeutic strategies to mitigate aging-related bone loss.

Tracing Cellular Senescence in Bone: Time-Dependent Changes in Osteocyte Cytoskeleton Mechanics and Morphology

Aging-related bone loss significantly impacts the growing elderly population globally, leading to debilitating conditions such as osteoporosis. Senescent osteocytes play a crucial role in the aging process of bone. This longitudinal study examines the impact of continuous local and paracrine exposure to senescence-associated secretory phenotype (SASP) factors on senescence-associated biophysical and biomolecular markers in osteocytes. We found significant cytoskeletal stiffening in irradiated osteocytes, accompanied by expansion of F-actin areas and a decline in dendritic integrity. These changes, correlating with alterations in pro-inflammatory cytokine levels and osteocyte-specific gene expression, support the reliability of biophysical markers for identifying senescent osteocytes. Notably, local accumulation of SASP factors had a more pronounced impact on osteocyte properties than paracrine effects, suggesting that the interplay between local and paracrine exposure could substantially influence cellular aging. This study underscores the importance of osteocyte mechanical and morphological properties as biophysical markers of senescence, highlighting their time-dependence and differential effects of local and paracrine SASP exposure. Collectively, our investigation into biophysical senescence markers offer unique and reliable functional hallmarks for non-invasive identification of senescent osteocytes, providing insights that could inform therapeutic strategies to mitigate aging-related bone loss.

Secretome of the Olfactory Ensheathing Cells Influences the Behavior of Neural Stem Cells

Olfactory ensheathing cell (OEC) transplantation demonstrates promising therapeutic results in neurological disorders, such as spinal cord injury. The emerging cell-free secretome therapy compensates for the limitations of cell transplantation, such as low cell survival rates. However, the therapeutic benefits of the human OEC secretome remain unclear. We harvested the secretome from human mucosal OECs and characterized its protein content, identifying 709 proteins in the human OEC secretome from three donors in two passages. Thirty-nine proteins, including neurological-related proteins, such as profilin-1, and antioxidants, such as peroxiredoxin-1 and glutathione S-transferase, were shared between the six samples. The secretome consistently demonstrated potential effects such as antioxidant activity, neuronal differentiation, and quiescence exit of neural stem cells (NSCs). The total secretome produced by OECs protects NSCs from H2O2-induced reactive oxygen species accumulation. During induction of neuronal differentiation, secretomes promoted neurite outgrowth, axon elongation, and expression of neuronal markers. The secretome ameliorated bone morphogenetic protein 4- and fibroblast growth factor 2-induced quiescence of NSCs. The human OEC secretome triggers NSCs to exit prime quiescence, which is related to increased phosphoribosomal protein S6 expression and RNA synthesis. The human OEC secretome has beneficial effects on NSCs and may be applied in neurological disease studies.

Synthetic biodegradable microporous hydrogels for in vitro 3D culture of functional human bone cell networks

Generating 3D bone cell networks in vitro that mimic the dynamic process during early bone formation remains challenging. Here, we report a synthetic biodegradable microporous hydrogel for efficient formation of 3D networks from human primary cells, analysis of cell-secreted extracellular matrix (ECM) and microfluidic integration. Using polymerization-induced phase separation, we demonstrate dynamic in situ formation of microporosity (5-20 µm) within matrix metalloproteinase-degradable polyethylene glycol hydrogels in the presence of living cells. Pore formation is triggered by thiol-Michael-addition crosslinking of a viscous precursor solution supplemented with hyaluronic acid and dextran. The resulting microporous architecture can be fine-tuned by adjusting the concentration and molecular weight of dextran. After encapsulation in microporous hydrogels, human mesenchymal stromal cells and osteoblasts spread rapidly and form 3D networks within 24 hours. We demonstrate that matrix degradability controls cell-matrix remodeling, osteogenic differentiation, and deposition of ECM proteins such as collagen. Finally, we report microfluidic integration and proof-of-concept osteogenic differentiation of 3D cell networks under perfusion on chip. Altogether, this work introduces a synthetic microporous hydrogel to efficiently differentiate 3D human bone cell networks, facilitating future in vitro studies on early bone development.

From pixels to connections: exploring in vitro neuron reconstruction software for network graph generation

Digital reconstruction has been instrumental in deciphering how in vitro neuron architecture shapes information flow. Emerging approaches reconstruct neural systems as networks with the aim of understanding their organization through graph theory. Computational tools dedicated to this objective build models of nodes and edges based on key cellular features such as somata, axons, and dendrites. Fully automatic implementations of these tools are readily available, but they may also be purpose-built from specialized algorithms in the form of multi-step pipelines. Here we review software tools informing the construction of network models, spanning from noise reduction and segmentation to full network reconstruction. The scope and core specifications of each tool are explicitly defined to assist bench scientists in selecting the most suitable option for their microscopy dataset. Existing tools provide a foundation for complete network reconstruction, however more progress is needed in establishing morphological bases for directed/weighted connectivity and in software validation.

ANDA: an open-source tool for automated image analysis of in vitro neuronal cells

BACKGROUND

Imaging of in vitro neuronal differentiation and measurements of cell morphologies have led to novel insights into neuronal development. Live-cell imaging techniques and large datasets of images have increased the demand for automated pipelines for quantitative analysis of neuronal morphological metrics.

RESULTS

ANDA is an analysis workflow that quantifies various aspects of neuronal morphology from high-throughput live-cell imaging screens of in vitro neuronal cell types. This tool automates the analysis of neuronal cell numbers, neurite lengths and neurite attachment points. We used chicken, rat, mouse, and human in vitro models for neuronal differentiation and have demonstrated the accuracy, versatility, and efficiency of the tool.

CONCLUSIONS

ANDA is an open-source tool that is easy to use and capable of automated processing from time-course measurements of neuronal cells. The strength of this pipeline is the capability to analyse high-throughput imaging screens.

Amyloid-β Impairs Dendritic Trafficking of Golgi-Like Organelles in the Early Phase Preceding Neurite Atrophy: Rescue by Mirtazapine

Neurite atrophy with loss of neuronal polarity is a pathological hallmark of Alzheimer's disease (AD) and other neurological disorders. While there is substantial agreement that disruption of intracellular vesicle trafficking is associated with axonal pathology in AD, comparatively less is known regarding its role in dendritic atrophy. This is a significant gap of knowledge because, unlike axons, dendrites are endowed with the complete endomembrane system comprising endoplasmic reticulum (ER), ER-Golgi intermediate compartment (ERGIC), Golgi apparatus, post-Golgi vesicles, and a recycling-degradative route. In this study, using live-imaging of pGOLT-expressing vesicles, indicative of Golgi outposts and satellites, we investigate how amyloid-β (Aβ) oligomers affect the trafficking of Golgi-like organelles in the different dendritic compartments of cultured rat hippocampal neurons. We found that short-term (4 h) treatment with Aβ led to a decrease in anterograde trafficking of Golgi vesicles in dendrites of both resting and stimulated (with 50 mM KCl) neurons. We also characterized the ability of mirtazapine, a noradrenergic and specific serotonergic tetracyclic antidepressant (NaSSA), to rescue Golgi dynamics in dendrites. Mirtazapine treatment (10 μM) increased the number and both anterograde and retrograde motility, reducing the percentage of static Golgi vesicles. Finally, mirtazapine reverted the neurite atrophy induced by 24 h treatment with Aβ oligomers, suggesting that this drug is able to counteract the effects of Aβ by improving the dendritic trafficking of Golgi-related vesicles.

Advancing Drug Discovery for Neurological Disorders Using iPSC-Derived Neural Organoids

In the last decade, different research groups in the academic setting have developed induced pluripotent stem cell-based protocols to generate three-dimensional, multicellular, neural organoids. Their use to model brain biology, early neural development, and human diseases has provided new insights into the pathophysiology of neuropsychiatric and neurological disorders, including microcephaly, autism, Parkinson’s disease, and Alzheimer’s disease. However, the adoption of organoid technology for large-scale drug screening in the industry has been hampered by challenges with reproducibility, scalability, and translatability to human disease. Potential technical solutions to expand their use in drug discovery pipelines include Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) to create isogenic models, single-cell RNA sequencing to characterize the model at a cellular level, and machine learning to analyze complex data sets. In addition, high-content imaging, automated liquid handling, and standardized assays represent other valuable tools toward this goal. Though several open issues still hamper the full implementation of the organoid technology outside academia, rapid progress in this field will help to prompt its translation toward large-scale drug screening for neurological disorders.

TDP-43 Regulates Coupled Dendritic mRNA Transport-Translation Processes in Co-operation with FMRP and Staufen1

Tightly regulated transport of messenger ribonucleoprotein (mRNP) granules to diverse locations of dendrites and axons is essential for appropriately timed protein synthesis within distinct sub-neuronal compartments. Perturbations of this regulation lead to various neurological disorders. Using imaging and molecular approaches, we demonstrate how TDP-43 co-operates with two other RNA-binding proteins, FMRP and Staufen1, to regulate the anterograde and retrograde transport, respectively, of Rac1 mRNPs in mouse neuronal dendrites. We also analyze the mechanisms by which TDP-43 mediates coupled mRNA transport-translation processes in dendritic sub-compartments by following in real-time the co-movement of RNA and endogenous fluorescence-tagged protein in neurons and by simultaneous examination of transport/translation dynamics by using an RNA biosensor. This study establishes the pivotal roles of TDP-43 in transporting mRNP granules in dendrites, inhibiting translation inside those granules, and reactivating it once the granules reach the dendritic spines.

A paralog-specific role of COPI vesicles in the neuronal differentiation of mouse pluripotent cells

The paralogous COPI coat subunit γ1-COP plays a unique role in promoting neurite outgrowth during the neuronal differentiation of mouse pluripotent cells.

Coat protein complex I (COPI)–coated vesicles mediate membrane trafficking between Golgi cisternae as well as retrieval of proteins from the Golgi to the endoplasmic reticulum. There are several flavors of the COPI coat defined by paralogous subunits of the protein complex coatomer. However, whether paralogous COPI proteins have specific functions is currently unknown. Here, we show that the paralogous coatomer subunits γ1-COP and γ2-COP are differentially expressed during the neuronal differentiation of mouse pluripotent cells. Moreover, through a combination of genome editing experiments, we demonstrate that whereas γ-COP paralogs are largely functionally redundant, γ1-COP specifically promotes neurite outgrowth. Our work stresses a role of the COPI pathway in neuronal polarization and provides evidence for distinct functions for coatomer paralogous subunits in this process.

The future of cerebral organoids in drug discovery

Until the discovery of human embryonic stem cells and human induced pluripotent stem cells, biotechnology companies were severely limited in the number of human tissues that they could model in large-scale in vitro studies. Until this point, companies have been limited to immortalized cancer lines or a small number of primary cell types that could be extracted and expanded. Nowadays, protocols continue to be developed in the stem cell field, enabling researchers to model an ever-growing library of cell types in controlled, large-scale screens. One differentiation method in particular- cerebral organoids- shows substantial potential in the field of neuroscience and developmental neurobiology. Cerebral organoid technology is still in an early phase of development, and there are several challenges that are currently being addressed by academic and industrial researchers alike. Here we briefly describe some of the early adopters of cerebral organoids, several of the challenges that they are likely facing, and various technologies that are currently being implemented to overcome them.

In vitro modeling of dendritic atrophy in Rett syndrome: determinants for phenotypic drug screening in neurodevelopmental disorders

Dendritic atrophy, defined as the reduction in complexity of the neuronal arborization, is a hallmark of several neurodevelopmental disorders, including Rett Syndrome (RTT). RTT, affecting 1:10,000 girls worldwide, is mainly caused by mutations in the MECP2 gene and has no cure. We describe here an in vitro model of dendritic atrophy in Mecp2^−/y mouse hippocampal primary cultures, suitable for phenotypic drug-screening. Using High-Content Imaging techniques, we systematically investigated the impact of culturing determinants on several parameters such as neuronal survival, total dendritic length, dendritic endpoints, soma size, cell clusterization, spontaneous activity. Determinants included cell-seeding density, glass or polystyrene substrates, coating with poly-Ornithine with/without Matrigel and miniaturization from 24 to 96-half surface multiwell plates. We show that in all plate-sizes at densities below 320 cells/mm², morphological parameters remained constant while spontaneous network activity decreased according to the cell-density. Mecp2^−/y neurons cultured at 160 cells/mm² density in 96 multiwell plates, displayed significant dendritic atrophy and showed a marked increase in dendritic length following treatment with Brain-derived neurotrophic factor (BDNF) or Mirtazapine. In conclusion, we have established a phenotypic assay suitable for fast screening of hundreds of compounds, which may be extended to other neurodevelopmental diseases with dendritic atrophy.

E2F1 Drives Breast Cancer Metastasis by Regulating the Target Gene FGF13 and Altering Cell Migration

In prior work we demonstrated that loss of E2F transcription factors inhibits metastasis. Here we address the mechanisms for this phenotype and identify the E2F regulated genes that coordinate tumor cell metastasis. Transcriptomic profiling of E2F1 knockout tumors identified a role for E2F1 as a master regulator of a suite of pro-metastatic genes, but also uncovered E2F1 target genes with an unknown role in pulmonary metastasis. High expression of one of these genes, Fgf13, is associated with early human breast cancer metastasis in a clinical dataset. Together these data led to the hypothesis that Fgf13 is critical for breast cancer metastasis, and that upregulation of Fgf13 may partially explain how E2F1 promotes breast cancer metastasis. To test this hypothesis we ablated Fgf13 via CRISPR. Deletion of Fgf13 in a MMTV-PyMT breast cancer cell line reduces colonization of the lungs in a tail vein injection. In addition, loss of Fgf13 reduced in vitro cell migration, suggesting that Fgf13 may be critical for tumor cells to escape the primary tumor and to colonize the distal sites. The significance of this work is twofold: we have both uncovered genomic features by which E2F1 regulates metastasis and we have identified new pro-metastatic functions for the E2F1 target gene Fgf13.

DEFiNE: A Method for Enhancement and Quantification of Fluorescently Labeled Axons

Visualization and quantification of fluorescently labeled axonal fibers are widely employed in studies of neuronal connectivity in the brain. However, accurate analysis of axon density is often confounded by autofluorescence and other fluorescent artifacts. By the time these problems are detected in labeled tissue sections, significant time and resources have been invested, and the tissue may not be easy to replace. In response to these difficulties, we have developed Digital Enhancement of Fibers with Noise Elimination (DEFiNE), a method for eliminating fluorescent artifacts from digital images based on their morphology and fluorescence spectrum, thus permitting enhanced visualization and quantification of axonal fibers. Application of this method is facilitated by a DEFiNE macro, written using ImageJ Macro Language (IJM), which includes an automated and customizable procedure for image processing and a semi-automated quantification method that accounts for any remaining local variation in background intensity. The DEFiNE macro is open-source and used with the widely available FIJI software for maximum accessibility.

Ginsenoside Rb1 improves leptin sensitivity in the prefrontal cortex in obese mice

AIM

Obesity impairs leptin-induced regulation of brain-derived neurotrophic factor (BDNF) expression and synaptogenesis, which has been considered to be associated with the incidence of neuronal degenerative diseases, cognitive decline, and depression. Ginsenoside Rb1 (Rb1), a major bioactive component of ginseng, is known to have an antiobesity effect and improve cognition. This study examined whether Rb1 can improve central leptin effects on BDNF expression and synaptogenesis in the prefrontal cortex during obesity using an in vivo and an in vitro model.

RESULT

Ginsenoside Rb1 (Rb1) chronic treatment improved central leptin sensitivity, leptin-JAK2-STAT3 signaling, and leptin-induced regulation of BDNF expression in the prefrontal cortex of high-fat diet-induced obese mice. In cultured prefrontal cortical neurons, palmitic acid, the saturated fat, impaired leptin-induced BDNF expression, reduced the immunoreactivity and mRNA expression of synaptic proteins, and impaired leptin-induced neurite outgrowth and synaptogenesis. Importantly, Rb1 significantly prevented these pernicious effects induced by palmitic acid.

CONCLUSION

These results indicate that Rb1 reverses central leptin resistance and improves leptin-BDNF-neurite outgrowth and synaptogenesis in the prefrontal cortical neurons. Thus, Rb1 supplementation may be a beneficial avenue to treat obesity-associated neurodegenerative disorders.

ReMAPping the microtubule landscape: How phosphorylation dictates the activities of microtubule-associated proteins

Classical microtubule-associated proteins (MAPs) were originally identified based on their co-purification with microtubules assembled from mammalian brain lysate. They have since been found to perform a range of functions involved in regulating the dynamics of the microtubule cytoskeleton. Most of these MAPs play integral roles in microtubule organization during neuronal development, microtubule remodeling during neuronal activity, and microtubule stabilization during neuronal maintenance. As a result, mutations in MAPs contribute to neurodevelopmental disorders, psychiatric conditions, and neurodegenerative diseases. MAPs are post-translationally regulated by phosphorylation depending on developmental time point and cellular context. Phosphorylation can affect the microtubule affinity, cellular localization, or overall function of a particular MAP and can thus have profound implications for neuronal health. Here we review MAP1, MAP2, MAP4, MAP6, MAP7, MAP9, tau, and DCX, and how each is regulated by phosphorylation in neuronal physiology and disease. Developmental Dynamics 247:138-155, 2018. © 2017 Wiley Periodicals, Inc.

NeuronRead, an open source semi-automated tool for morphometric analysis of phase contrast and fluorescence neuronal images

Neurons are specialized cells of the Central Nervous System whose function is intricately related to the neuritic network they develop to transmit information. Morphological evaluation of this network and other neuronal structures is required to establish relationships between neuronal morphology and function, and may allow monitoring physiological and pathophysiologic alterations. Fluorescence-based microphotographs are the most widely used in cellular bioimaging, but phase contrast (PhC) microphotographs are easier to obtain, more affordable, and do not require invasive, complicated and disruptive techniques. Despite the various freeware tools available for fluorescence-based images analysis, few exist that can tackle the more elusive and harder-to-analyze PhC images. To surpass this, an interactive semi-automated image processing workflow was developed to easily extract relevant information (e.g. total neuritic length, average cell body area) from both PhC and fluorescence neuronal images. This workflow, named 'NeuronRead', was developed in the form of an ImageJ macro. Its robustness and adaptability were tested and validated on rat cortical primary neurons under control and differentiation inhibitory conditions. Validation included a comparison to manual determinations and to a golden standard freeware tool for fluorescence image analysis. NeuronRead was subsequently applied to PhC images of neurons at distinct differentiation days and exposed or not to DAPT, a pharmacological inhibitor of the γ-secretase enzyme, which cleaves the well-known Alzheimer's amyloid precursor protein (APP) and the Notch receptor. Data obtained confirms a neuritogenic regulatory role for γ-secretase products and validates NeuronRead as a time- and cost-effective useful monitoring tool.

Fuzzy-Logic Based Detection and Characterization of Junctions and Terminations in Fluorescence Microscopy Images of Neurons

Digital reconstruction of neuronal cell morphology is an important step toward understanding the functionality of neuronal networks. Neurons are tree-like structures whose description depends critically on the junctions and terminations, collectively called critical points, making the correct localization and identification of these points a crucial task in the reconstruction process. Here we present a fully automatic method for the integrated detection and characterization of both types of critical points in fluorescence microscopy images of neurons. In view of the majority of our current studies, which are based on cultured neurons, we describe and evaluate the method for application to two-dimensional (2D) images. The method relies on directional filtering and angular profile analysis to extract essential features about the main streamlines at any location in an image, and employs fuzzy logic with carefully designed rules to reason about the feature values in order to make well-informed decisions about the presence of a critical point and its type. Experiments on simulated as well as real images of neurons demonstrate the detection performance of our method. A comparison with the output of two existing neuron reconstruction methods reveals that our method achieves substantially higher detection rates and could provide beneficial information to the reconstruction process.

Transfer of mitochondria from astrocytes to neurons after stroke

Recently, it was suggested that neurons can release and transfer damaged mitochondria to astrocytes for disposal and recycling ¹. This ability to exchange mitochondria may represent a potential mode of cell-cell signaling in the central nervous system (CNS). Here, we show that astrocytes can also release functional mitochondria that enter into neurons. Astrocytic release of extracellular mitochondria particles was mediated by a calcium-dependent mechanism involving CD38/cyclic ADP ribose signaling. Transient focal cerebral ischemia in mice induced astrocytic mitochondria entry to adjacent neurons that amplified cell survival signals. Suppression of CD38 signaling with siRNA reduced extracellular mitochondria transfer and worsened neurological outcomes. These findings suggest a new mitochondrial mechanism of neuroglial crosstalk that may contribute to endogenous neuroprotective and neurorecovery mechanisms after stroke.

NeuronCyto II: An automatic and quantitative solution for crossover neural cells in high throughput screening

Microscopy is a fundamental technology driving new biological discoveries. Today microscopy allows a large number of images to be acquired using, for example, High Throughput Screening (HTS) and 4D imaging. It is essential to be able to interrogate these images and extract quantitative information in an automated fashion. In the context of neurobiology, it is important to automatically quantify the morphology of neurons in terms of neurite number, length, branching and complexity, etc. One major issue in quantification of neuronal morphology is the “crossover” problem where neurites cross and it is difficult to assign which neurite belongs to which cell body. In the present study, we provide a solution to the “crossover” problem, the software package NeuronCyto II. NeuronCyto II is an interactive and user‐friendly software package for automatic neurite quantification. It has a well‐designed graphical user interface (GUI) with only a few free parameters allowing users to optimize the software by themselves and extract relevant quantitative information routinely. Users are able to interact with the images and the numerical features through the Result Inspector. The processing of neurites without crossover was presented in our previous work. Our solution for the “crossover” problem is developed based on our recently published work with directed graph theory. Both methods are implemented in NeuronCyto II. The results show that our solution is able to significantly improve the reliability and accuracy of the neurons displaying “crossover.” NeuronCyto II is freely available at the website: https://sites.google.com/site/neuroncyto/, which includes user support and where software upgrades will also be placed in the future. © 2016 The Authors. Cytometry Part A Published by Wiley Periodicals, Inc. on behalf of ISAC.

A label-free and high-throughput separation of neuron and glial cells using an inertial microfluidic platform

While neurons and glial cells both play significant roles in the development and therapy of schizophrenia, their specific contributions are difficult to differentiate because the methods used to separate neurons and glial cells are ineffective and inefficient. In this study, we reported a high-throughput microfluidic platform based on the inertial microfluidic technique to rapidly and continuously separate neurons and glial cells from dissected brain tissues. The optimal working condition for an inertial biochip was investigated and evaluated by measuring its separation under different flow rates. Purified and enriched neurons in a primary neuron culture were verified by confocal immunofluorescence imaging, and neurons performed neurite growth after separation, indicating the feasibility and biocompatibility of an inertial separation. Phencyclidine disturbed the neuroplasticity and neuron metabolism in the separated and the unseparated neurons, with no significant difference. Apart from isolating the neurons, purified and enriched viable glial cells were collected simultaneously. This work demonstrates that an inertial microchip can provide a label-free, high throughput, and harmless tool to separate neurological primary cells.

Establishment of Human Neural Progenitor Cells from Human Induced Pluripotent Stem Cells with Diverse Tissue Origins

Human neural progenitor cells (hNPCs) have previously been generated from limited numbers of human induced pluripotent stem cell (hiPSC) clones. Here, 21 hiPSC clones derived from human dermal fibroblasts, cord blood cells, and peripheral blood mononuclear cells were differentiated using two neural induction methods, an embryoid body (EB) formation-based method and an EB formation method using dual SMAD inhibitors (dSMADi). Our results showed that expandable hNPCs could be generated from hiPSC clones with diverse somatic tissue origins. The established hNPCs exhibited a mid/hindbrain-type neural identity and uniform expression of neural progenitor genes.

Scale of Carbon Nanomaterials Affects Neural Outgrowth and Adhesion

Carbon nanomaterials have become increasingly popular microelectrode materials for neuroscience applications. Here we study how the scale of carbon nanotubes and carbon nanofibers affect neural viability, outgrowth, and adhesion. Carbon nanotubes were deposited on glass coverslips via a layer-by-layer method with polyethylenimine (PEI). Carbonized nanofibers were fabricated by electrospinning SU-8 and pyrolyzing the nanofiber depositions. Additional substrates tested were carbonized and SU-8 thin films and SU-8 nanofibers. Surfaces were O2-plasma treated, coated with varying concentrations of PEI, seeded with E18 rat cortical cells, and examined at 3, 4, and 7 days in vitro (DIV). Neural adhesion was examined at 4 DIV utilizing a parallel plate flow chamber. At 3 DIV, neural viability was lower on the nanofiber and thin film depositions treated with higher PEI concentrations which corresponded with significantly higher zeta potentials (surface charge); this significance was drastically higher on the nanofibers suggesting that the nanostructure may collect more PEI molecules, causing increased toxicity. At 7 DIV, significantly higher neurite outgrowth was observed on SU-8 nanofiber substrates with nanofibers a significant fraction of a neuron's size. No differences were detected for carbonized nanofibers or carbon nanotubes. Both carbonized and SU-8 nanofibers had significantly higher cellular adhesion post-flow in comparison to controls whereas the carbon nanotubes were statistically similar to control substrates. These data suggest a neural cell preference for larger-scale nanomaterials with specific surface treatments. These characteristics could be taken advantage of in the future design and fabrication of neural microelectrodes.

Automatic neuron segmentation and neural network analysis method for phase contrast microscopy images

Phase Contrast Microscopy (PCM) is an important tool for the long term study of living cells. Unlike fluorescence methods which suffer from photobleaching of fluorophore or dye molecules, PCM image contrast is generated by the natural variations in optical index of refraction. Unfortunately, the same physical principles which allow for these studies give rise to complex artifacts in the raw PCM imagery. Of particular interest in this paper are neuron images where these image imperfections manifest in very different ways for the two structures of specific interest: cell bodies (somas) and dendrites. To address these challenges, we introduce a novel parametric image model using the level set framework and an associated variational approach which simultaneously restores and segments this class of images. Using this technique as the basis for an automated image analysis pipeline, results for both the synthetic and real images validate and demonstrate the advantages of our approach.

Morphometric assessment of toxicant induced neuronal degeneration in full and restricted contact co-cultures of embryonic cortical rat neurons and astrocytes: using m-Dinitrobezene as a model neurotoxicant

With m-Dinitrobenzene (m-DNB) as a selected model neurotoxicant, we demonstrate how to assess neurotoxicity, using morphology based measurement of neurite degeneration, in a conventional "full-contact" and a modern "restricted-contact" co-culture of rat cortical neurons and astrocytes. In the "full-contact" co-culture, neurons and astrocytes in complete physical contact are "globally" exposed to m-DNB. A newly emergent "restricted-contact" co-culture is attained with a microfluidic device that polarizes neuron somas and neurites into separate compartments, and the neurite compartment is "selectively" exposed to m-DNB. Morphometric analysis of the neuronal area revealed that m-DNB exposure produced no significant change in mean neuronal cell area in "full-contact" co-cultures, whereas a significant decrease was observed for neuron monocultures. Neurite elaboration into a neurite exclusive compartment in a compartmentalized microfluidic device, for both monocultures (no astrocytes) and "restricted" co-cultures (astrocytes touching neurites), decreased with exposure to increasing concentrations of m-DNB, but the average neurite area was higher in co-cultures. By using co-culture systems that more closely approach biological and architectural complexities, and the directionality of exposure found in the brain, this study provides a methodological foundation for unraveling the role of physical contact between astrocytes and neurons in mitigating the toxic effects of chemicals such as m-DNB.

SOAX: a software for quantification of 3D biopolymer networks

Filamentous biopolymer networks in cells and tissues are routinely imaged by confocal microscopy. Image analysis methods enable quantitative study of the properties of these curvilinear networks. However, software tools to quantify the geometry and topology of these often dense 3D networks and to localize network junctions are scarce. To fill this gap, we developed a new software tool called “SOAX”, which can accurately extract the centerlines of 3D biopolymer networks and identify network junctions using Stretching Open Active Contours (SOACs). It provides an open-source, user-friendly platform for network centerline extraction, 2D/3D visualization, manual editing and quantitative analysis. We propose a method to quantify the performance of SOAX, which helps determine the optimal extraction parameter values. We quantify several different types of biopolymer networks to demonstrate SOAX's potential to help answer key questions in cell biology and biophysics from a quantitative viewpoint.

Extracellular vesicles from a muscle cell line (C2C12) enhance cell survival and neurite outgrowth of a motor neuron cell line (NSC-34)

Introduction

There is renewed interest in extracellular vesicles over the past decade or 2 after initially being thought of as simple cellular garbage cans to rid cells of unwanted components. Although there has been intense research into the role of extracellular vesicles in the fields of tumour and stem cell biology, the possible role of extracellular vesicles in nerve regeneration is just in its infancy.

Background

When a peripheral nerve is damaged, the communication between spinal cord motor neurons and their target muscles is disrupted and the result can be the loss of coordinated muscle movement. Despite state-of-the-art surgical procedures only approximately 10% of adults will recover full function after peripheral nerve repair. To improve upon such results will require a better understanding of the basic mechanisms that influence axon outgrowth and the interplay between the parent motor neuron and the distal end organ of muscle. It has previously been shown that extracellular vesicles are immunologically tolerated, display targeting ligands on their surface, and can be delivered in vivo to selected cell populations. All of these characteristics suggest that extracellular vesicles could play a significant role in nerve regeneration.

Methods

We have carried out studies using 2 very well characterized cell lines, the C2C12 muscle cell line and the motor neuron cell line NSC-34 to ask the question: Do extracellular vesicles from muscle influence cell survival and/or neurite outgrowth of motor neurons?

Conclusion

Our results show striking effects of extracellular vesicles derived from the muscle cell line on the motor neuron cell line in terms of neurite outgrowth and survival.

Extraction of protein profiles from primary neurons using active contour models and wavelets

The function of complex networks in the nervous system relies on the proper formation of neuronal contacts and their remodeling. To decipher the molecular mechanisms underlying these processes, it is essential to establish unbiased automated tools allowing the correlation of neurite morphology and the subcellular distribution of molecules by quantitative means. We developed NeuronAnalyzer2D, a plugin for ImageJ, which allows the extraction of neuronal cell morphologies from two dimensional high resolution images, and in particular their correlation with protein profiles determined by indirect immunostaining of primary neurons. The prominent feature of our approach is the ability to extract subcellular distributions of distinct biomolecules along neurites. To extract the complete areas of neurons, required for this analysis, we employ active contours with a new distance based energy. For locating the structural parts of neurons and various morphological parameters we adopt a wavelet based approach. The presented approach is able to extract distinctive profiles of several proteins and reports detailed morphology measurements on neurites. We compare the detected neurons from NeuronAnalyzer2D with those obtained by NeuriteTracer and Vaa3D-Neuron, two popular tools for automatic neurite tracing. The distinctive profiles extracted for several proteins, for example, of the mRNA binding protein ZBP1, and a comparative evaluation of the neuron segmentation results proves the high quality of the quantitative data and proves its practical utility for biomedical analyses.

RGMa regulates cortical interneuron migration and differentiation

The etiology of neuropsychiatric disorders, including schizophrenia and autism, has been linked to a failure to establish the intricate neural network comprising excitatory pyramidal and inhibitory interneurons during neocortex development. A large proportion of cortical inhibitory interneurons originate in the medial ganglionic eminence (MGE) of the ventral telencephalon and then migrate through the ventral subventricular zone, across the corticostriatal junction, into the embryonic cortex. Successful navigation of newborn interneurons through the complex environment of the ventral telencephalon is governed by spatiotemporally restricted deployment of both chemorepulsive and chemoattractive guidance cues which work in concert to create a migratory corridor. Despite the expanding list of interneuron guidance cues, cues responsible for preventing interneurons from re-entering the ventricular zone of the ganglionic eminences have not been well characterized. Here we provide evidence that the chemorepulsive axon guidance cue, RGMa (Repulsive Guidance Molecule a), may fulfill this function. The ventricular zone restricted expression of RGMa in the ganglionic eminences and the presence of its receptor, Neogenin, in the ventricular zone and on newborn and maturing MGE-derived interneurons implicates RGMa-Neogenin interactions in interneuron differentiation and migration. Using an in vitro approach, we show that RGMa promotes interneuron differentiation by potentiating neurite outgrowth. In addition, using in vitro explant and migration assays, we provide evidence that RGMa is a repulsive guidance cue for newborn interneurons migrating out of the ganglionic eminence ventricular zone. Intriguingly, the alternative Neogenin ligand, Netrin-1, had no effect on migration. However, we observed complete abrogation of RGMa-induced chemorepulsion when newborn interneurons were simultaneously exposed to RGMa and Netrin-1 gradients, suggesting a novel mechanism for the tight regulation of RGMa-guided interneuron migration. We propose that during peak neurogenesis, repulsive RGMa-Neogenin interactions drive interneurons into the migratory corridor and prevent re-entry into the ventricular zone of the ganglionic eminences.

A morphometric screen identifies specific roles for microtubule-regulating genes in neuronal development of P19 stem cells

The first morphological change after neuronal differentiation is the microtubule-dependent initiation of thin cell protrusions called neurites. Here we performed a siRNA-based morphometric screen in P19 stem cells to evaluate the role of 408 microtubule-regulating genes during this early neuromorphogenesis step. This screen uncovered several novel regulatory factors, including specific complex subunits of the microtubule motor dynein involved in neurite initiation and a novel role for the microtubule end-binding protein EB2 in attenuation of neurite outgrowth. Epistasis analysis suggests that competition between EB1 and EB2 regulates neurite length, which links its expression to neurite outgrowth. We propose a model that explains how microtubule regulators can mediate cellular morphogenesis during the early steps of neuronal development by controlling microtubule stabilization and organizing dynein-generated forces.

HCS-Neurons: identifying phenotypic changes in multi-neuron images upon drug treatments of high-content screening

Background

High-content screening (HCS) has become a powerful tool for drug discovery. However, the discovery of drugs targeting neurons is still hampered by the inability to accurately identify and quantify the phenotypic changes of multiple neurons in a single image (named multi-neuron image) of a high-content screen. Therefore, it is desirable to develop an automated image analysis method for analyzing multi-neuron images.

Results

We propose an automated analysis method with novel descriptors of neuromorphology features for analyzing HCS-based multi-neuron images, called HCS-neurons. To observe multiple phenotypic changes of neurons, we propose two kinds of descriptors which are neuron feature descriptor (NFD) of 13 neuromorphology features, e.g., neurite length, and generic feature descriptors (GFDs), e.g., Haralick texture. HCS-neurons can 1) automatically extract all quantitative phenotype features in both NFD and GFDs, 2) identify statistically significant phenotypic changes upon drug treatments using ANOVA and regression analysis, and 3) generate an accurate classifier to group neurons treated by different drug concentrations using support vector machine and an intelligent feature selection method. To evaluate HCS-neurons, we treated P19 neurons with nocodazole (a microtubule depolymerizing drug which has been shown to impair neurite development) at six concentrations ranging from 0 to 1000 ng/mL. The experimental results show that all the 13 features of NFD have statistically significant difference with respect to changes in various levels of nocodazole drug concentrations (NDC) and the phenotypic changes of neurites were consistent to the known effect of nocodazole in promoting neurite retraction. Three identified features, total neurite length, average neurite length, and average neurite area were able to achieve an independent test accuracy of 90.28% for the six-dosage classification problem. This NFD module and neuron image datasets are provided as a freely downloadable MatLab project at http://iclab.life.nctu.edu.tw/HCS-Neurons.

Conclusions

Few automatic methods focus on analyzing multi-neuron images collected from HCS used in drug discovery. We provided an automatic HCS-based method for generating accurate classifiers to classify neurons based on their phenotypic changes upon drug treatments. The proposed HCS-neurons method is helpful in identifying and classifying chemical or biological molecules that alter the morphology of a group of neurons in HCS.

FiloDetect: automatic detection of filopodia from fluorescence microscopy images

Background

Filopodia are small cellular projections that help cells to move through and sense their environment. Filopodia play crucial roles in processes such as development and wound-healing. Also, increases in filopodia number or size are characteristic of many invasive cancers and are correlated with increased rates of metastasis in mouse experiments. Thus, one possible route to developing anti-metastatic therapies is to target factors that influence the filopodia system. Filopodia can be detected by eye using confocal fluorescence microscopy, and they can be manually annotated in images to quantify filopodia parameters. Although this approach is accurate, it is slow, tedious and not entirely objective. Manual detection is a significant barrier to the discovery and quantification of new factors that influence the filopodia system.

Results

Here, we present FiloDetect, an automated tool for detecting, counting and measuring the length of filopodia in fluorescence microscopy images. The method first segments the cell from the background, using a modified triangle threshold method, and then extracts the filopodia using a series of morphological operations. We verified the accuracy of FiloDetect on Rat2 and B16F1 cell images from three different labs, showing that per-cell filopodia counts and length estimates are highly correlated with the manual annotations. We then used FiloDetect to assess the role of a lipid kinase on filopodia production in breast cancer cells. Experimental results show that PI4KIII β expression leads to an increase in filopodia number and length, suggesting that PI4KIII β is involved in driving filopodia production.

Conclusion

FiloDetect provides accurate and objective quantification of filopodia in microscopy images, and will enable large scale comparative studies to assess the effects of different genetic and chemical perturbations on filopodia production in different cell types, including cancer cell lines.

Label-free detection of neuronal differentiation in cell populations using high-throughput live-cell imaging of PC12 cells

Detection of neuronal cell differentiation is essential to study cell fate decisions under various stimuli and/or environmental conditions. Many tools exist that quantify differentiation by neurite length measurements of single cells. However, quantification of differentiation in whole cell populations remains elusive so far. Because such populations can consist of both proliferating and differentiating cells, the task to assess the overall differentiation status is not trivial and requires a high-throughput, fully automated approach to analyze sufficient data for a statistically significant discrimination to determine cell differentiation. We address the problem of detecting differentiation in a mixed population of proliferating and differentiating cells over time by supervised classification. Using nerve growth factor induced differentiation of PC12 cells, we monitor the changes in cell morphology over days by phase-contrast live-cell imaging. For general applicability, the classification procedure starts out with many features to identify those that maximize discrimination of differentiated and undifferentiated cells and to eliminate features sensitive to systematic measurement artifacts. The resulting image analysis determines the optimal post treatment day for training and achieves a near perfect classification of differentiation, which we confirmed in technically and biologically independent as well as differently designed experiments. Our approach allows to monitor neuronal cell populations repeatedly over days without any interference. It requires only an initial calibration and training step and is thereafter capable to discriminate further experiments. In conclusion, this enables long-term, large-scale studies of cell populations with minimized costs and efforts for detecting effects of external manipulation of neuronal cell differentiation.