Project description:Familial amyotrophic lateral sclerosis (ALS) represents about 10% of ALS cases. In about 20% of familial ALS patients, a mutation in superoxide dismutase-1 (SOD1) can be found. The ubiquitous SOD1 protein converts superoxide radical anions to oxygen and hydrogen peroxide. Patients with familial ALS caused by mutations in SOD1 can show comorbidity with frontotemporal dementia and develop cognitive impairment, including apathy, inattention, verbal deficits, and hypersexuality. At the cellular level, pathological signs of ALS may include tau immunoreactive astrocytic and neuronal inclusions, suggesting that cognitive dysfunction in ALS may also reflect abnormal protein metabolism of the microtubule associated protein (MAP), tau. To identify cell-specific expression changes, we performed laser capture microdissection (LCM) to isolate anterior horn motor neurons and surrounding cells. To determine common pathways for the development of ALS due to dysfunction of SOD1 or TAU, we performed whole transcriptome analysis in SOD1 and TAU mouse models. Because ALS is a neurodegenerative disease that specifically affects motor neurons, these cells were the main investigative target. Global transcriptomes of glial cells surrounding the motor neurons were also assessed, because these cells have been implicated as triggers of neurodegeneration. Mouse experiments were performed at the presymptomatic stage, prior to the onset of cell loss, in order to reduce false positive signals due to tissue reactive changes. Lumbar anterior horn anterior horn motor neurons and surrounding cells (glia) were isolated from presymptomatic TAU-P301L and SOD1-G93A transgenic mice using laser capture microdissection (LCM; PixCellÂ® IIe LCM System, Arcturus, Molecular Devices, CA). On average, 500 motor neuron bodies or surrounding glial cells from 20 tissue sections per animal were collected. RNA isolation from LCM collected cells was performed using the Qiagen RNeasy Micro Kit. Only RNA with RNA Integrity Numbers (RIN) above 7.5 were taken for further analysis (Agilent Bioanalyzer 2100). A two-round T7-based amplification and labeling protocol (Agilent Low RNA Input Linear Amplification Kit PLUS) was used to generate high quality labeled cRNA. Agilent Whole Mouse Genome Microarray comparisons of motor neurons and surrounding glia were performed between transgenic (SOD1G93A and TAUP301L) and corresponding nontransgenic (control) littermate animals, producing four independent comparison groups: SOD1G93A motor neurons versus control motor neurons (SOD1mn), SOD1G93A motor neuron surrounding glia versus control glia (SOD1gl), TAUP301L motor neurons versus control motor neurons (TAUmn) and TAUP301L glia versus control glia (TAUgl). Each comparison used four pairs of transgenic (SOD1G93A or TAUP301L) vs. corresponding control littermate animals, producing four biological replicates. Raw microarray data were acquired using the Agilent DNA Microarray scanner and processed with the accompanying Agilent Feature Extraction 10.5 Image Analysis software using default settings. Normalized signal intensities were used to identify gene expression changes in SOD1G93A and TAUP301L motor neurons and surrounding glial cells, generating four partially overlapping sets of data. For the identification of differential expression, the genes were required to pass two conservative criteria: a ratio beyond the 99.5% confidence interval observed in homotypic comparisons, which corresponded to an approximately 1.5-fold expression change, and a paired t-test (P<0.01) computed using 100 permutations of the data for each gene. Correction for multiple comparisons was performed using the adjusted Bonferroni test. The analysis was performed in the TM4: Microarray Software Suite. These techniques identified 251 transcripts representing 186 known genes for which expression was altered in at least one of the four comparisons. Four-condition experiment, SOD1G93A motor neurons versus control motor neurons (SODmn), SOD1G93A motor neuron surrounding glia versus control glia (SODgl), TAUP301L motor neurons versus control motor neurons (TAUmn) and TAUP301L glia versus control glia (TAUgl). Each comparison used four pairs of transgenic (SOD1G93A or TAUP301L) vs. corresponding control littermate animals, producing four biological replicates. Biological replicates: 4 SOD1G93A motor neurons (SODmn), 4 non SOD littermate motor neurons (nonSODmn), 4 SOD1G93A motor neuron surrounding glia (SODgl), 4 non SOD littermate motor neuron surrounding glia (nonSODgl), 4 TAUP301L motor neurons (TAUmn), 4 non TAU littermate motor neurons (nonTAUmn), 4 TAUP301L motor neuron surrounding glia (TAUgl), 4 non TAU littermate motor neuron surrounding glia (nonTAUgl). Four independent comparison groups were generated: SOD1G93A motor neurons versus control nonSOD motor neurons, SOD1G93A motor neuron surrounding glia versus control nonSOD glia, TAUP301L motor neurons versus control nonTAU motor neurons and TAUP301L glia versus control nonTAU glia. Each comparison used four pairs of transgenic (SOD1G93A or TAUP301L) vs. corresponding control littermate animals, producing four biological replicates. Each replicate was repeated twice with dye flip to correct for unequal dye incorporation rates. Therefore, eight microarray hybridizations were performed for each biological comparison, for a total of 32 microarray slides and generating four groups of differentially expressed genes in SOD1G93A motor neurons (SODmn), SOD1G93A motor neuron surrounding glial cells (SODgl), TAUP301L motor neurons (TAUmn), and TAUP301L surrounding glial cells (TAUgl).

Project description:Egr3 is a zinc-finger transcription factor involved in growth and development. Egr3-deficient mice have severe sensory ataxia due to failed development of muscle spindle stretch receptors. Sensory and motor neurons that normally innervate spindles are absent in Egr3-deficient mice, presumably as a secondary consequence to the loss of trophic signals produced by spindles during development that are required for innervation and neuron survival. The molecular mechanisms involving motor neuron fate specification, target derived growth factor dependencies, and specification of target innervation have been difficult to study since select markers for functionally specific motor neurons are very poorly characterized. A more thorough understanding of the molecular mediators of motor neuron biology will be important to evaluate the efficacy of new strategies devised to thwart neuron death that occurs in a variety of human motor neuronopathies and neuropathies. To identify genes specifically expressed by spinal cord fusimotor neurons: Many motor neuron specific genes have been described over the years. However, none have been described that distinguish fusimotor neurons from skeletomotor neurons despite the fact that they have distinct muscle targets (muscle spindle stretch receptors) and comprise 25-30% of the spinal motor neuron populations. Since these motor neurons have remarkably different target innervation and function, we hypothesize that they express genes that establish their specific phenotypes during development. We hypothesize that fusimotor neurons can be distinguished in the spinal cord by characterizing fusimotor neuron specific gene expression. Once fusimotor neuron specific genes are identified, they will be used as markers to identify fusimotor neurons in complex neuroglial cell populations in vivo and in vitro. We hypothesize that by characterizing fusimotor neuron specific genes, unique marker molecules will be identified for in vivo and in vitro study of this functionally distinct and important motor neuron subtype. Moreover, we hypothesize that many of the genes that are specifically expressed by fusimotor neurons will be involved in mechanisms related to their fate specification, target innervation and growth factor dependent biology. We will use the Affymetrix microarray platform to identify genes that are specifically expressed by fusimotor neurons in mouse spinal cord. The differential expression analysis will be performed on microdissected segments of spinal cord (L3-L5) from wild type and Egr3-deficient mice. Postnatal Egr3-deficient mice lack muscle spindles and fusimotor neurons in their spinal cords. By comparing gene expression from microdissected segments of spinal cord (L3-L5) between wild type and Egr3-deficient mice, we hypothesize that fusimotor neuron selective genes can be identified. We will microdissect L3-L5 segments of spinal cord using precise anatomical landmarks to ensure that comparable spinal cord regions are anlayzed from each animal. For each microarray experiment, total RNA will be extracted from L3-L5 cords (approximately 2 mm length of spinal cord). The integrity of each RNA sample will be verified by gel electrophoresis. The intact RNA samples from mice of similar genotype will be pooled from three (3) 27-day old animals. The intact cord dissection is easier in young animals (eg: 27-day old) and the phenotype is known to exist at this developmental stage. The RNA from each animal of a similar genotype will be pooled into a single sample to minimize false positive gene calls that may represent genes related to the specific state of vigilance of a particular animal at the time of sacrifice (eg: activity dependent genes). Thus, each of the two RNA samples to be analyzed for a particular microarray experiment will represent RNA from three (3) spinal cords of each genotype. RNA amplification for probe synthesis should not be necessary since we will provide 7 ug of intact pooled total RNA for each sample. For statistical analysis, the experiment will be performed twice. Since the RNA samples are precious, they will be provided to the Array Consortium in two shipments with each of the experiments performed independently.

Project description:Purpose: Choline acetyltransferase (ChAT)-expressing epithelial cells are found in the upper and lower airways. In the trachea, they are referred to as brush cells. In the mouse nose two distinct populations of ChAT-eGFP+ cells had been previously described: a population of rare solitary chemosensory cells (SCCs) in the respiratory mucosa and a more abundant population of microvillous cells (MVCs) in the olfactory epithelium. Besides ChAT expression, SCCs share the expression of bitter taste receptors and signaling machinery with tracheal brush cells as well as close association with CGPR+ nerve fibers and an elongated shape. MVCs do not express bitter taste receptors, are not clearly associated with nerves and are smaller in size than SCCs. We have previously reported the transcriptional profile of tracheal ChAT-expressing brush cells but the transcriptional profile of nasal chemosensory ChAT+ epithelial cells has not been reported. Methods: In this study, we isolated nasal ChAT-eGFP+ cells by FACS from naïve ChAT(BAC)-eGFP mice with knockin of eGFP within a BAC spanning the ChAT locus, marking brush cells in the epithelium and performed transcriptome profiling using low input RNA sequencing. We sorted two distinct subsets of ChAT-eGFP+ epithelial cells from the nasal mucosa based on FACS ice and granularity characteristic: ChAT-eGFP+ EpCAM+ FSC/SSChigh (representing 5% of all ChAT-eGFP+ cells) and FSC/SSClow (representing 95% of all ChAT-eGFP+ cells), respectively. We compared them to unfractionated ChAT-eGFP- EpCAM+ epithelial cells. Results: Both nasal ChAT-eGFP subsets shared the core transcriptional profile of chemosensory cells from the intestine, trachea, gallbladder and thymus including the expression of Il25, Pou2f3, Trpm5, Avil, Plcb2 and transcripts of eicosanoid biosynthetic enzymes suggesting that most ChAT-eGFP+ cells in the nose belong to the chemosensory/tuft/brush cel family. The two subsets of nasal ChAT-eGFP+ cells differed in expression of taste receptors and taste receptor signaling machinery. Conclusions: Our study represents the first detailed analysis of the transcriptome of nasal ChAT-eGFP+ cells (brush cells) and identifies two subsets of nasal brush cells that share a core transcriptional signature but differ in expression of bitter taste receptors.

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Cell type-specific HITS-CLIP reveals differential RNA processing in motor neurons

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