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Hoppe2012 - Predicting changes in metabolic function using transcript profiles (HepatoNet1b_mouse)

ABSTRACT: Hoppe2012 - Predicting changes in metabolic function using transcript profiles Measuring metabolite concentrations, reaction fluxes, and enzyme activities on large scale are tricky tasks in the study of cellular metabolism. Here, a method that predicts activity changes of metabolic functions based on relative transcript profiles, has been presented. It provides a ranked list of most regulated functions. The method has been applied to TGF-beta treatment of hepatocyte cultures. This stoichiometric model of the mouse hepatocyte is based on a corrected and extended version of HepatoNet1. This model is described in the article: ModeScore: A Method to Infer Changed Activity of Metabolic Function from Transcript Profiles Andreas Hoppe and Hermann-Georg Holzhütter German Conference on Bioinformatics 2012; Publ.13.09.2012 Abstract: Genome-wide transcript profiles are often the only available quantitative data for a particular perturbation of a cellular system and their interpretation with respect to the metabolism is a major challenge in systems biology, especially beyond on/off distinction of genes. We present a method that predicts activity changes of metabolic functions by scoring reference flux distributions based on relative transcript profiles, providing a ranked list of most regulated functions. Then, for each metabolic function, the involved genes are ranked upon how much they represent a specific regulation pattern. Compared with the naïve pathway-based approach, the reference modes can be chosen freely, and they represent full metabolic functions, thus, directly provide testable hypotheses for the metabolic study. In conclusion, the novel method provides promising functions for subsequent experimental elucidation together with outstanding associated genes, solely based on transcript profiles. This model is hosted on BioModels Database and identified by: MODEL1208060000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. PMID: 20587024 . 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>http://creativecommons.org/publicdomain/zero/1.0/] for more information.

SUBMITTER: Andreas Hoppe

PROVIDER: MODEL1208060000 | BioModels | 2014-03-17

REPOSITORIES: BioModels

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			Action	DRS
	MODEL1208060000?filename=MODEL1208060000-biopax2.owl	Owl
	MODEL1208060000?filename=MODEL1208060000-biopax3.owl	Owl
	MODEL1208060000?filename=MODEL1208060000.m	Other
	MODEL1208060000?filename=MODEL1208060000.pdf	Pdf
	MODEL1208060000?filename=MODEL1208060000.png	Other

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Project description:To identify genes that are downstream of gonadal hormones and that control dimorphic behaviors, we used a MEEBO array platform to profile gene expression of adult male and female hypothalamus against a whole brain reference sample. The experimental design allowed us to identify genes that are upreguated in the hypothalamus compared to the whole brain and are dimorphically expressed between the two sexes. In situ hybridization of candiate genes were carried out to validate the dimorphic expression of these genes in the hypothalamus. Array results were used to create a list of genes to screen by in situ hybridization. For each normalization method, a list of genes that were upregulated in the male or the female was created, and a gene had to be on a set number of these individual normalization lists in order to be considered for screening. A similar method was used to create a list of hypothalamic upregulated genes. The final screening list was comprised of genes that were upregulated in the male or female as well as in the hypothalamus. If in situ hybridization proved that the gene was upregulated in the male or female brain, we concluded that that transcript was differentially expressed. No one normalization method was weighted over another, and the array results were used to create a screening list for in situ hybridizations. Hypothalami from 4 adult animals of each sex were microdissected and pooled for each experimental sample and the whole brain plus pituitary from one male and one female were pooled to provide the reference sample. Each set of samples (male and female) was hybridized to two arrays to provide two technical replicates for each set of samples taken. A total of three sets of samples were taken (three biological replicates). For the "_amp" Samples, source (hypothalamus and whole brain) mRNA was amplified using T7 based method. For this set, data were not normalized, rather the raw intensities were used to calculate ratios. Candidate genes from this study was also included in final list in situ screening.

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Hoppe2012 - Predicting changes in metabolic function using transcript profiles (HepatoNet1b_mouse)

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