Stages of neuronal morphological development in vitro—An automated assay

Leach, Michelle K.; Naim, Youssef; Feng, Zhongyuan; Gertz, Caitlyn C.; Corey, Joseph M.

doi:10.1016/j.jneumeth.2011.04.033

Cited by 11 publications

(17 citation statements)

References 30 publications

(40 reference statements)

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“…DN development, evaluated in 4 stages according to cell morphology (Fig. 2d; based on a report by Leach et al) [19], showed that DS-DN development was reduced compared to Ctrl-DN (Fig. 2e).…”

Section: Resultsmentioning

confidence: 99%

“…A morphological analysis of DN was performed as previously described [19]. Briefly, neurite length and number of branches were measured from 100 TH-positive cells in 20 non-overlapping TH-immunostained images selected randomly from three experiments using the Neurite Outgrowth and Multi-Wavelength Cell Scoring module of MetaMorph software (Molecular Devices).…”

Section: Methodsmentioning

confidence: 99%

“…Briefly, neurite length and number of branches were measured from 100 TH-positive cells in 20 non-overlapping TH-immunostained images selected randomly from three experiments using the Neurite Outgrowth and Multi-Wavelength Cell Scoring module of MetaMorph software (Molecular Devices). Next, the cells were classified into 4 stages based on neurite length and cell diameter as previously described [19]. …”

Section: Methodsmentioning

confidence: 99%

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Altered development of dopaminergic neurons differentiated from stem cells from human exfoliated deciduous teeth of a patient with Down syndrome

et al. 2018

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BackgroundDown syndrome (DS) is a common developmental disorder resulting from the presence of an additional copy of chromosome 21. Abnormalities in dopamine signaling are suggested to be involved in cognitive dysfunction, one of the symptoms of DS, but the pathophysiological mechanism has not been fully elucidated at the cellular level. Stem cells from human exfoliated deciduous teeth (SHED) can be prepared from the dental pulp of primary teeth. Importantly, SHED can be collected noninvasively, have multipotency, and differentiate into dopaminergic neurons (DN). Therefore, we examined dopamine signaling in DS at the cellular level by isolating SHED from a patient with DS, differentiating the cells into DN, and examining development and function of DN.MethodsHere, SHED were prepared from a normal participant (Ctrl-SHED) and a patient with DS (DS-SHED). Initial experiments were performed to confirm the morphological, chromosomal, and stem cell characteristics of both SHED populations. Next, Ctrl-SHED and DS-SHED were differentiated into DN and morphological analysis of DN was examined by immunostaining. Functional analysis of DN was performed by measuring extracellular dopamine levels under basal and glutamate-stimulated conditions. In addition, expression of molecules involved in dopamine homeostasis was examined by quantitative real-time polymerase chain reaction and immunostaining. Statistical analysis was performed using two-tailed Student’s t-tests.ResultsCompared with Ctrl-SHED, DS-SHED showed decreased expression of nestin, a neural stem-cell marker. Further, DS-SHED differentiated into DN (DS-DN) exhibiting decreased neurite outgrowth and branching compared with Ctrl-DN. In addition, DS-DN dopamine secretion was lower than Ctrl-DN dopamine secretion. Moreover, aberrant expression of molecules involved in dopaminergic homeostasis was observed in DS-DN.ConclusionsOur results suggest that there was developmental abnormality and DN malfunction in the DS-SHED donor in this study. In the future, to clarify the detailed mechanism of dopamine-signal abnormality due to DN developmental and functional abnormalities in DS, it is necessary to increase the number of patients for analysis. Non-invasively harvested SHED may be very useful in the analysis of DS pathology.Electronic supplementary materialThe online version of this article (10.1186/s12883-018-1140-2) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Altered development of dopaminergic neurons differentiated from stem cells from human exfoliated deciduous teeth of a patient with Down syndrome

et al. 2018

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“…Stem cells were plated on polystyrene nanofiber scaffolds or films and either Dox-induced to overexpress Neurog1 or left uninduced. Neuronal differentiation and neuritogenesis were quantified using an automated image analysis program 136 to analyze neurites. Dox-induction produces a similar percentage of neuronal cells with or without fiber topography (B), but combining induced Neurog1 with a fiber substrate increased neurite outgrowth in a synergistic manner (C and D).…”

Section: Figurementioning

confidence: 99%

Combining Topographical and Genetic Cues to Promote Neuronal Fate Specification in Stem Cells

et al. 2012

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There is little remedy for the devastating effects resulting from neuronal loss caused by neural injury or neurodegenerative disease. Reconstruction of damaged neural circuitry with stem cell-derived neurons is a promising approach to repair these defects, but controlling differentiation and guiding synaptic integration with existing neurons remain significant unmet challenges. Biomaterial surfaces can present nanoscale topographical cues which influence neuronal differentiation and process outgrowth. By combining these scaffolds with additional molecular biology strategies, synergistic control over cell fate can be achieved. Here, we review recent progress in promoting neuronal fate using techniques at the interface of biomaterial science and genetic engineering. New data demonstrates that combining nanofiber topography with an induced genetic program enhances neuritogenesis in a synergistic fashion. We propose combining patterned biomaterial surface cues with prescribed genetic programs to achieve neuronal cell fates with the desired sublineage specification, neurochemical profile, targeted integration and electrophysiological properties.

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“…In particular, our focus on obtaining orientation data from high-density images is unique within the literature. Many published neuron tracing algorithms seek to evaluate neuronal morphology, and therefore may track neurites emanating from a single cell, focusing on characterizing parameters such as neurite length and branching morphology (Ho et al, 2011; Helmstaedter et al, 2011; Leach et al, 2011). For high density, longer term cultures, this sort of morphological delineation is impossible for both human users and computer programs to implement.…”

Section: Discussionmentioning

confidence: 99%

Neurient: An algorithm for automatic tracing of confluent neuronal images to determine alignment

Mitchel

Martin²,

Hoffman–Kim

2013

Journal of Neuroscience Methods

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A goal of neural tissue engineering is the development and evaluation of materials that guide neuronal growth and alignment. However, the methods available to quantitatively evaluate the response of neurons to guidance materials are limited and/or expensive, and may require manual tracing to be performed by the researcher. We have developed an open source, automated Matlab-based algorithm, building on previously published methods, to trace and quantify alignment of fluorescent images of neurons in culture. The algorithm is divided into three phases, including computation of a lookup table which contains directional information for each image, location of a set of seed points which may lie along neurite centerlines, and tracing neurites starting with each seed point and indexing into the lookup table. This method was used to obtain quantitative alignment data for complex images of densely cultured neurons. Complete automation of tracing allows for unsupervised processing of large numbers of images. Following image processing with our algorithm, available metrics to quantify neurite alignment include angular histograms, percent of neurite segments in a given direction, and mean neurite angle. The alignment information obtained from traced images can be used to compare the response of neurons to a range of conditions. This tracing algorithm is freely available to the scientific community under the name Neurient, and its implementation in Matlab allows a wide range of researchers to use a standardized, open source method to quantitatively evaluate the alignment of dense neuronal cultures.

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Stages of neuronal morphological development in vitro—An automated assay

Cited by 11 publications

References 30 publications

Altered development of dopaminergic neurons differentiated from stem cells from human exfoliated deciduous teeth of a patient with Down syndrome

Altered development of dopaminergic neurons differentiated from stem cells from human exfoliated deciduous teeth of a patient with Down syndrome

Combining Topographical and Genetic Cues to Promote Neuronal Fate Specification in Stem Cells

Neurient: An algorithm for automatic tracing of confluent neuronal images to determine alignment

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