Dataset Information

Brain region mapping using global metabolomics.

ABSTRACT: Historically, studies of brain metabolism have been based on targeted analyses of a limited number of metabolites. Here we present an untargeted mass spectrometry-based metabolomic strategy that has successfully uncovered differences in a broad array of metabolites across anatomical regions of the mouse brain. The NSG immunodeficient mouse model was chosen because of its ability to undergo humanization leading to numerous applications in oncology and infectious disease research. Metabolic phenotyping by hydrophilic interaction liquid chromatography and nanostructure imaging mass spectrometry revealed both water-soluble and lipid metabolite patterns across brain regions. Neurochemical differences in metabolic phenotypes were mainly defined by various phospholipids and several intriguing metabolites including carnosine, cholesterol sulfate, lipoamino acids, uric acid, and sialic acid, whose physiological roles in brain metabolism are poorly understood. This study helps define regional homeostasis for the normal mouse brain to give context to the reaction to pathological events.

SUBMITTER: Ivanisevic J

PROVIDER: S-EPMC4304924 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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Brain region mapping using global metabolomics.

Ivanisevic Julijana J Epstein Adrian A AA Kurczy Michael E ME Benton Paul H PH Uritboonthai Winnie W Fox Howard S HS Boska Michael D MD Gendelman Howard E HE Siuzdak Gary G

Chemistry & biology 20141101 11

Historically, studies of brain metabolism have been based on targeted analyses of a limited number of metabolites. Here we present an untargeted mass spectrometry-based metabolomic strategy that has successfully uncovered differences in a broad array of metabolites across anatomical regions of the mouse brain. The NSG immunodeficient mouse model was chosen because of its ability to undergo humanization leading to numerous applications in oncology and infectious disease research. Metabolic phenot ...[more]

PMID: 25457182

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Project description:BackgroundPhysical maps employing libraries of bacterial artificial chromosome (BAC) clones are essential for comparative genomics and sequencing of large and repetitive genomes such as those of the hexaploid bread wheat. The diploid ancestor of the D-genome of hexaploid wheat (Triticum aestivum), Aegilops tauschii, is used as a resource for wheat genomics. The barley diploid genome also provides a good model for the Triticeae and T. aestivum since it is only slightly larger than the ancestor wheat D genome. Gene co-linearity between the grasses can be exploited by extrapolating from rice and Brachypodium distachyon to Ae. tauschii or barley, and then to wheat.ResultsWe report the use of Ae. tauschii for the construction of the physical map of a large distal region of chromosome arm 3DS. A physical map of 25.4 Mb was constructed by anchoring BAC clones of Ae. tauschii with 85 EST on the Ae. tauschii and barley genetic maps. The 24 contigs were aligned to the rice and B. distachyon genomic sequences and a high density SNP genetic map of barley. As expected, the mapped region is highly collinear to the orthologous chromosome 1 in rice, chromosome 2 in B. distachyon and chromosome 3H in barley. However, the chromosome scale of the comparative maps presented provides new insights into grass genome organization. The disruptions of the Ae. tauschii-rice and Ae. tauschii-Brachypodium syntenies were identical. We observed chromosomal rearrangements between Ae. tauschii and barley. The comparison of Ae. tauschii physical and genetic maps showed that the recombination rate across the region dropped from 2.19 cM/Mb in the distal region to 0.09 cM/Mb in the proximal region. The size of the gaps between contigs was evaluated by comparing the recombination rate along the map with the local recombination rates calculated on single contigs.ConclusionsThe physical map reported here is the first physical map using fingerprinting of a complete Triticeae genome. This study demonstrates that global fingerprinting of the large plant genomes is a viable strategy for generating physical maps. Physical maps allow the description of the co-linearity between wheat and grass genomes and provide a powerful tool for positional cloning of new genes.

Dataset Information

Brain region mapping using global metabolomics.

Publications

Brain region mapping using global metabolomics.

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