models c elegans  (Nikon)

Journal: Journal of Neurochemistry

Article Title: Aminoacyl‐tRNA synthetases in Charcot–Marie–Tooth disease: A gain or a loss?

doi: 10.1111/jnc.15249

Figure Lengend Snippet: Effect of CMT variants on aminoacylation activity and conformational change of aaRSs

Article Snippet: Of eight variants, seven result in a loss of function as determined by yeast complementation assays, and neurotoxicity has been successfully recapitulated in transgenic C. elegans models of HARS R137Q and HARS D364Y variants (Abbott et al., ; Safka Brozkova et al., ; Vester et al., ).

Techniques: Activity Assay, Animal Model, In Vitro

Journal: Molecular Systems Biology

Article Title: Modeling tissue‐relevant Caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels

doi: 10.15252/msb.20209649

Figure Lengend Snippet: Computational pipeline to predict tissue function using tissue‐level gene expression data. Cartoon outlining the update of the C. elegans metabolic network model. GPR, gene‐protein‐reaction association. Conceptual overview of integration of iCEL1314 with four categories of genes: highly, moderately, lowly, and rarely expressed. The predicted flux state in a tissue is a flux distribution that trails reactions associated with highly expressed genes in that tissue, while avoiding those associated with lowly expressed and rarely expressed genes. Circles and arrows indicate metabolites and reactions, respectively. Black arrows show flux, with thicker arrows indicating higher flux. Boxes depict enzymes encoded by genes that have expression levels indicated by color. Dashed arrows indicate reactions with no flux in the preliminary flux distribution stage according to Fig B but are then detected as latent reactions and are forced to carry flux when possible (see text for details). To derive tissue‐relevant metabolic network functions, a gene expression dataset obtained with single‐cell RNA‐seq of L2 animals was used (Cao et al , ). Single‐cell data were combined by the authors to provide high‐quality gene expression data for the seven tissues shown. Distribution of metabolic genes in iCEL1314 in different expression categories in each individual tissue and in all tissues combined, with colors as in (B). For the combination of data, the union set of highly expressed genes and the intersection set of rarely and lowly expressed genes are illustrated with corresponding colors. One gene which was lowly expressed in some tissues and rarely expressed in others is not shown in the combined data.

Article Snippet: iCEL1314 (genome‐scale metabolic network model of C. elegans ) , This study, Yilmaz & Walhout ( ) , BioModels (Chelliah et al , ): MODEL2007280001 .

Techniques: Gene Expression, Expressing, RNA Sequencing

Journal: Molecular Systems Biology

Article Title: Modeling tissue‐relevant Caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels

doi: 10.15252/msb.20209649

Figure Lengend Snippet: Histograms representing average gene expression in seven tissues combined (upper panel) and in the intestine alone as an example tissue (lower panel). The mean ( μ ) and standard deviation ( σ ) of high expression (HES) and low expression (LES) subpopulation of genes were determined by curve fitting and used to define the thresholds for gene categorization. Red ( μ LES ), yellow ( μ LES + σ LES ), and green ( μ HES ) lines are hard thresholds for rarely, lowly, and highly expressed genes, respectively (lower panel). Dashed green line ( μ HES + σ HES ) indicates the relative expression threshold for describing additional highly and lowly expressed genes based on enrichment/depletion analysis as described in Fig . Bars reflect frequency of genes in the corresponding category based on color. Metabolic genes that are part of iCEL1314 are indicated with hatched bars (see Appendix Fig S1 for the histograms of metabolic genes).

Article Snippet: iCEL1314 (genome‐scale metabolic network model of C. elegans ) , This study, Yilmaz & Walhout ( ) , BioModels (Chelliah et al , ): MODEL2007280001 .

Techniques: Gene Expression, Standard Deviation, Expressing

Journal: Molecular Systems Biology

Article Title: Modeling tissue‐relevant Caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels

doi: 10.15252/msb.20209649

Figure Lengend Snippet: Dual‐tissue model used for compartmentalization of iCEL1314 during data integration. The two major compartments used are the intestine, which is the point of entry for bacterial nutrients, and another tissue. The lower panel shows the two main steps of integration. First, gene expression data for each tissue except the intestine is integrated with the model individually. Second, integrated flux distributions from the first step are combined using tissue weights that represent the relative mass and activity of each tissue (Fig A, Appendix Supplementary Methods ) and the intestine gene expression data is integrated. Flow chart of the optimized integration algorithm. A maximized or minimized variable from a step is carried to the next step as a constraint as shown by equations by the arrows (a bold uppercase term indicates a maximized or minimized sum of variables from the previous step). The δ term stands for small numbers that indicate the tolerance of deviation from the corresponding minimized flux sums. A latent reaction is a reaction that is only associated with highly expressed genes and converts metabolites that are available in the present state of the flux distribution, but does not carry any flux. See text and Appendix Supplementary Methods for details. Example pathways that share genes (only a relevant subset of reactions is shown for each pathway). Dashed arrows indicate skipped parts of the pathway and the rest of the metabolic network. Upper right panel shows expression categories of relevant genes in tissues. Lower right panel shows predicted flux in the propionate shunt obtained with iMAT and iMAT++ algorithms. Epsilon indicates the minimum flux imposed on reactions associated with highly expressed genes during integration ( ε = 0 .01 for every reaction shown). Analysis of agreement between experimental data and integrated flux distribution. The left panel shows percentage ( y ‐axis) and number (bold numbers) of highly expressed genes that have no association with any flux‐carrying reactions. The middle panel shows the same for reactions that depend on rarely expressed genes, but carry flux in the integrated network. The right panel shows the depletion rate of flux in lowly expressed reactions, which is calculated as one minus the ratio of total flux in these reactions to what is expected for the same number of flux‐carrying reactions on average. In each panel, the results for exactly the same set of genes or reactions were extracted from the output of each algorithm and compared ( Appendix Supplementary Methods ).

Article Snippet: iCEL1314 (genome‐scale metabolic network model of C. elegans ) , This study, Yilmaz & Walhout ( ) , BioModels (Chelliah et al , ): MODEL2007280001 .

Techniques: Gene Expression, Activity Assay, Expressing

Journal: Molecular Systems Biology

Article Title: Modeling tissue‐relevant Caenorhabditis elegans metabolism at network, pathway, reaction, and metabolite levels

doi: 10.15252/msb.20209649

Figure Lengend Snippet:

Article Snippet: iCEL1314 (genome‐scale metabolic network model of C. elegans ) , This study, Yilmaz & Walhout ( ) , BioModels (Chelliah et al , ): MODEL2007280001 .

Techniques: Software