Project description:Background: With its fully sequenced genome and simple, well-defined nervous system, the nematode C. elegans offers a unique opportunity to correlate gene expression with neuronal differentiation. The lineal origin, cellular morphology and synaptic connectivity of each of the 302 neurons are known. In many instances, specific behaviors can be attributed to particular neurons or circuits. Here we describe microarray-based methods that monitor gene expression in C. elegans neurons and thereby link comprehensive profiles of neuronal transcription to key developmental and functional attributes of the nervous system. Results: We employed complementary microarray-based strategies to profile gene expression in the embryonic and larval nervous systems. In the MAPCeL (Micro-Array Profiling C. elegans Cells) method, we used Fluorescence Activated Cell Sorting (FACS) to isolate GFP-tagged embryonic neurons for microarray analysis. To profile the larval nervous system, we used the mRNA-tagging technique in which an epitope-labeled mRNA binding protein (FLAG-PAB-1) was transgenically expressed in neurons for immunoprecipitation of cell-specific transcripts. These combined approaches identified approximately 2,500 mRNAs that are highly enriched in either the embryonic or larval C. elegans nervous system. These data are validated in part by the detection of gene classes (e.g. transcription factors, ion channels, synaptic vesicle components) with established roles in neuronal development or function. In addition to utilizing these profiling approaches to define stage specific gene expression, we also applied the mRNA-tagging method to fingerprint a specific neuron type, the A-class group of cholinergic motor neurons, during early larval development. A comparison of these data to a MAPCeL profile of embryonic A-class motor neurons identified genes with common functions in both types of A-class motor neurons as well as transcripts with roles specific to each motor neuron type. Conclusion: We describe microarray-based strategies for generating expression profiles of embryonic and larval C. elegans neurons. These methods can be applied to particular neurons at specific developmental stages and therefore provide an unprecedented opportunity to obtain spatially and temporally defined snapshots of gene expression in a simple model nervous system. Keywords: nervous system, development
Project description:Background: With its fully sequenced genome and simple, well-defined nervous system, the nematode C. elegans offers a unique opportunity to correlate gene expression with neuronal differentiation. The lineal origin, cellular morphology and synaptic connectivity of each of the 302 neurons are known. In many instances, specific behaviors can be attributed to particular neurons or circuits. Here we describe microarray-based methods that monitor gene expression in C. elegans neurons and thereby link comprehensive profiles of neuronal transcription to key developmental and functional attributes of the nervous system. Results: We employed complementary microarray-based strategies to profile gene expression in the embryonic and larval nervous systems. In the MAPCeL (Micro-Array Profiling C. elegans Cells) method, we used Fluorescence Activated Cell Sorting (FACS) to isolate GFP-tagged embryonic neurons for microarray analysis. To profile the larval nervous system, we used the mRNA-tagging technique in which an epitope-labeled mRNA binding protein (FLAG-PAB-1) was transgenically expressed in neurons for immunoprecipitation of cell-specific transcripts. These combined approaches identified approximately 2,500 mRNAs that are highly enriched in either the embryonic or larval C. elegans nervous system. These data are validated in part by the detection of gene classes (e.g. transcription factors, ion channels, synaptic vesicle components) with established roles in neuronal development or function. In addition to utilizing these profiling approaches to define stage specific gene expression, we also applied the mRNA-tagging method to fingerprint a specific neuron type, the A-class group of cholinergic motor neurons, during early larval development. A comparison of these data to a MAPCeL profile of embryonic A-class motor neurons identified genes with common functions in both types of A-class motor neurons as well as transcripts with roles specific to each motor neuron type. Conclusion: We describe microarray-based strategies for generating expression profiles of embryonic and larval C. elegans neurons. These methods can be applied to particular neurons at specific developmental stages and therefore provide an unprecedented opportunity to obtain spatially and temporally defined snapshots of gene expression in a simple model nervous system. Experiment Overall Design: Our goal is to profile gene expression throughout the nervous system of the model organism Caenorhabditis elegans. As a first goal, we profiled the entire nervous system at two developmental timepoints. To isolate transcripts from embryonic neurons we employed the MAPCeL (Microarray Profiling C. elegans Cells) technique in which pan-neuronal GFP+ cells are captured by FACS for RNA isolation. Since postembryonic cells are unattainable via this method, we used mRNA-tagging to isolated pan-neural RNAs from larval animals. In short, an epitope tagged poly-A binding protein (FLAG-PAB-1) was driven in all neurons using the F25B3.3 promoter. Following formaldehyde cross-linking, animals were passed through a French press and Dounce homogenized to isolate a cell-free extract. Anti-FLAG antibodies were incubated with the cell-free extract to capture FLAG-PAB bound RNAs. After elution and reversal of the crosslinks, RNAs are isolated by TriZOL extraction. We also identified transcripts enriched in a subset of C. elegans larval neurons, the A-class neurons (using unc-4::3xFLAG::PAB-1). Experiment Overall Design: 3 sets of experiments normalized separately by RMA Experiment Overall Design: larval references of sets 2 and 3 originate from the same hybridizations (accompanying CEL files are identical)
Project description:Background: Differential gene expression specifies the highly diverse cell types that constitute the nervous system. With its sequenced genome and simple, well-defined neuroanatomy, the nematode C. elegans is a useful model system in which to correlate gene expression with neuron identity. The UNC-4 transcription factor is expressed in thirteen embryonic motor neurons where it specifies axonal morphology and synaptic function. These cells can be marked with an unc-4::GFP reporter transgene. Here we describe a powerful strategy, Micro-Array Profiling of C. elegans cells (MAPCeL), and confirm that this approach provides a comprehensive gene expression profile of unc-4::GFP motor neurons in vivo. Results: Fluorescence Activated Cell Sorting (FACS) was used to isolate unc-4::GFP neurons from primary cultures of C. elegans embryonic cells. Microarray experiments detected 6,217 unique transcripts of which ~1,000 are enriched in unc-4::GFP neurons relative to the average nematode embryonic cell. The reliability of these data was validated by the detection of known cell-specific transcripts and by expression in UNC-4 motor neurons of GFP reporters derived from the enriched data set. In addition to genes involved in neurotransmitter packaging and release, the microarray data include transcripts for receptors to a remarkably wide variety of signaling molecules. The added presence of a robust array of G-protein pathway components is indicative of complex and highly integrated mechanisms for modulating motor neuron activity. Over half of the enriched genes (537) have human homologs, a finding that could reflect substantial overlap with the gene expression repertoire of mammalian motor neurons. Conclusion: We have described a microarray-based method, MAPCeL, for profiling gene expression in specific C. elegans motor neurons and provide evidence that this approach can reveal candidate genes for key roles in the differentiation and function of these cells. These methods can now be applied to generate a gene expression map of the C. elegans nervous system. Experiment Overall Design: Our goal is to profile gene expression throughout the nervous system of the model organism Caenorhabditis elegans. As a first goal, we profiled a single class of embryonic motor neurons. To isolate transcripts from thesec neurons we developed the MAPCeL (Microarray Profiling C. elegans Cells) technique in which unc-4::GFP+ cells are captured by FACS for RNA isolation. We verified these data by bioinformatic means and by in vivo validation by creating GFP reporters for a random set of genes in our enriched gene list.
Project description:Background: Differential gene expression specifies the highly diverse cell types that constitute the nervous system. With its sequenced genome and simple, well-defined neuroanatomy, the nematode C. elegans is a useful model system in which to correlate gene expression with neuron identity. The UNC-4 transcription factor is expressed in thirteen embryonic motor neurons where it specifies axonal morphology and synaptic function. These cells can be marked with an unc-4::GFP reporter transgene. Here we describe a powerful strategy, Micro-Array Profiling of C. elegans cells (MAPCeL), and confirm that this approach provides a comprehensive gene expression profile of unc-4::GFP motor neurons in vivo. Results: Fluorescence Activated Cell Sorting (FACS) was used to isolate unc-4::GFP neurons from primary cultures of C. elegans embryonic cells. Microarray experiments detected 6,217 unique transcripts of which ~1,000 are enriched in unc-4::GFP neurons relative to the average nematode embryonic cell. The reliability of these data was validated by the detection of known cell-specific transcripts and by expression in UNC-4 motor neurons of GFP reporters derived from the enriched data set. In addition to genes involved in neurotransmitter packaging and release, the microarray data include transcripts for receptors to a remarkably wide variety of signaling molecules. The added presence of a robust array of G-protein pathway components is indicative of complex and highly integrated mechanisms for modulating motor neuron activity. Over half of the enriched genes (537) have human homologs, a finding that could reflect substantial overlap with the gene expression repertoire of mammalian motor neurons. Conclusion: We have described a microarray-based method, MAPCeL, for profiling gene expression in specific C. elegans motor neurons and provide evidence that this approach can reveal candidate genes for key roles in the differentiation and function of these cells. These methods can now be applied to generate a gene expression map of the C. elegans nervous system. Keywords: expression profile
Project description:Yilmaz2016 - Genome scale metabolic model -
Caenorhabditis elegans (iCEL1273)
This model is described in the article:
A Caenorhabditis elegans
Genome-Scale Metabolic Network Model.
Yilmaz LS, Walhout AJ.
Cell Syst 2016 May; 2(5): 297-311
Abstract:
Caenorhabditis elegans is a powerful model to study
metabolism and how it relates to nutrition, gene expression,
and life history traits. However, while numerous experimental
techniques that enable perturbation of its diet and gene
function are available, a high-quality metabolic network model
has been lacking. Here, we reconstruct an initial version of
the C. elegans metabolic network. This network model
contains 1,273 genes, 623 enzymes, and 1,985 metabolic
reactions and is referred to as iCEL1273. Using flux balance
analysis, we show that iCEL1273 is capable of representing the
conversion of bacterial biomass into C. elegans biomass
during growth and enables the predictions of gene essentiality
and other phenotypes. In addition, we demonstrate that gene
expression data can be integrated with the model by comparing
metabolic rewiring in dauer animals versus growing larvae.
iCEL1273 is available at a dedicated website
(wormflux.umassmed.edu) and will enable the unraveling of the
mechanisms by which different macro- and micronutrients
contribute to the animal's physiology.
This model is hosted on
BioModels Database
and identified by:
MODEL1604210000.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.