Myelin subfractions isolated from mouse brain: Analysis of the lipid composition at three developmental stages

Lipids ◽  
1981 ◽  
Vol 16 (7) ◽  
pp. 502-507 ◽  
Author(s):  
Linda D. Rhein ◽  
Joseph Sampugna
Keyword(s):  
Mouse Brain ◽  
Lipid Composition ◽  
Developmental Stages ◽  
Myelin Subfractions

HUPO BPP pilot study: A proteomics analysis of the mouse brain of different developmental stages

PROTEOMICS ◽  
2007 ◽  
Vol 7 (21) ◽  
pp. 4008-4015 ◽  
Author(s):  
Jing Wang ◽  
Yong Gu ◽  
Lihong Wang ◽  
Xingyi Hang ◽  
Yan Gao ◽  
...  
Keyword(s):  
Pilot Study ◽  
Mouse Brain ◽  
Developmental Stages ◽  
Proteomics Analysis

scholarly journals Constructing and optimizing 3D atlases from 2D data with application to the developing mouse brain

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
David M Young ◽  
Siavash Fazel Darbandi ◽  
Grace Schwartz ◽  
Zachary Bonzell ◽  
Deniz Yuruk ◽  
...  
Keyword(s):  
Mouse Brain ◽  
3D Imaging ◽  
Developmental Stages ◽  
Brain Atlas ◽  
Imaging Data ◽  
Qualitative And Quantitative ◽  
Atlas Construction ◽  
Manual Curation ◽  
Developing Mouse Brain ◽  
2D Data

3D imaging data necessitate 3D reference atlases for accurate quantitative interpretation. Existing computational methods to generate 3D atlases from 2D-derived atlases result in extensive artifacts, while manual curation approaches are labor-intensive. We present a computational approach for 3D atlas construction that substantially reduces artifacts by identifying anatomical boundaries in the underlying imaging data and using these to guide 3D transformation. Anatomical boundaries also allow extension of atlases to complete edge regions. Applying these methods to the eight developmental stages in the Allen Developing Mouse Brain Atlas (ADMBA) led to more comprehensive and accurate atlases. We generated imaging data from 15 whole mouse brains to validate atlas performance and observed qualitative and quantitative improvement (37% greater alignment between atlas and anatomical boundaries). We provide the pipeline as the MagellanMapper software and the eight 3D reconstructed ADMBA atlases. These resources facilitate whole-organ quantitative analysis between samples and across development.

VARIATIONS IN THE LIPID COMPOSITION OF MOUSE BRAIN MYELIN AS A FUNCTION OF AGE

1966 ◽  
pp. 46 ◽  
Author(s):  
Lloyd A. Horrocks ◽  
Roy J. Meckler ◽  
Robert L. Collins
Keyword(s):  
Mouse Brain ◽  
Lipid Composition

Lipid Composition in Scrapie-Infected Mouse Brain: Prion Infection Increases the Levels of Dolichyl Phosphate and Ubiquinone

2002 ◽  
Vol 66 (1) ◽  
pp. 277-285 ◽  
Author(s):  
Zhizhong Guan ◽  
Magnus Söderberg ◽  
Pavel Sindelar ◽  
Stanley B. Prusiner ◽  
Krister Kristensson ◽  
...  
Keyword(s):  
Infected Mouse ◽  
Mouse Brain ◽  
Lipid Composition ◽  
Prion Infection ◽  
Dolichyl Phosphate

scholarly journals Parkinson’s disease-associated iPLA2-VIA/PLA2G6 regulates neuronal functions and α-synuclein stability through membrane remodeling

2019 ◽  
Vol 116 (41) ◽  
pp. 20689-20699 ◽  
Author(s):  
Akio Mori ◽  
Taku Hatano ◽  
Tsuyoshi Inoshita ◽  
Kahori Shiba-Fukushima ◽  
Takahiro Koinuma ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Er Stress ◽  
Lipid Composition ◽  
Developmental Stages ◽  
Lipid Analysis ◽  
Acyl Chain ◽  
Membrane Lipid ◽  
Membrane Remodeling ◽  
The Brain

Mutations in the iPLA2-VIA/PLA2G6 gene are responsible for PARK14-linked Parkinson’s disease (PD) with α-synucleinopathy. However, it is unclear how iPLA2-VIA mutations lead to α-synuclein (α-Syn) aggregation and dopaminergic (DA) neurodegeneration. Here, we report that iPLA2-VIA–deficient Drosophila exhibits defects in neurotransmission during early developmental stages and progressive cell loss throughout the brain, including degeneration of the DA neurons. Lipid analysis of brain tissues reveals that the acyl-chain length of phospholipids is shortened by iPLA2-VIA loss, which causes endoplasmic reticulum (ER) stress through membrane lipid disequilibrium. The introduction of wild-type human iPLA2-VIA or the mitochondria–ER contact site-resident protein C19orf12 in iPLA2-VIA–deficient flies rescues the phenotypes associated with altered lipid composition, ER stress, and DA neurodegeneration, whereas the introduction of a disease-associated missense mutant, iPLA2-VIA A80T, fails to suppress these phenotypes. The acceleration of α-Syn aggregation by iPLA2-VIA loss is suppressed by the administration of linoleic acid, correcting the brain lipid composition. Our findings suggest that membrane remodeling by iPLA2-VIA is required for the survival of DA neurons and α-Syn stability.

scholarly journals Constructing and Optimizing 3D Atlases From 2D Data With Application to the Developing Mouse Brain

2020 ◽  
Author(s):  
David M Young ◽  
Siavash Fazel Darbandi ◽  
Grace Schwartz ◽  
Zachary Bonzell ◽  
Deniz Yuruk ◽  
...  
Keyword(s):  
Mouse Brain ◽  
3D Imaging ◽  
Developmental Stages ◽  
Brain Atlas ◽  
Imaging Data ◽  
Qualitative And Quantitative ◽  
Atlas Construction ◽  
Manual Curation ◽  
Developing Mouse Brain ◽  
2D Data

Abstract3D imaging data necessitate 3D reference atlases for accurate quantitative interpretation. Existing computational methods to generate 3D atlases from 2D-derived atlases result in extensive artifacts, while manual curation approaches are labor-intensive. We present a computational approach for 3D atlas construction that substantially reduces artifacts by identifying anatomical boundaries in the underlying imaging data and using these to guide 3D transformation. Anatomical boundaries also allow extension of atlases to complete edge regions. Applying these methods to the eight developmental stages in the Allen Developing Mouse Brain Atlas (ADMBA) led to more comprehensive and accurate atlases. We generated imaging data from fifteen whole mouse brains to validate atlas performance and observed qualitative and quantitative improvement (37% greater alignment between atlas and anatomical boundaries). We provide the methods as the MagellanMapper software and the eight 3D reconstructed ADMBA atlases. These resources facilitate whole-organ quantitative analysis between samples and across development.

The lipid composition of light and heavy myelin subfractions isolated from rabbit sciatic nerve

1980 ◽  
Vol 20 (2) ◽  
pp. 211-215 ◽  
Author(s):  
C. Linington ◽  
T.V. Waehneldt ◽  
V. Neuhoff
Keyword(s):  
Sciatic Nerve ◽  
Lipid Composition ◽  
Myelin Subfractions ◽  
Rabbit Sciatic Nerve

scholarly journals Spatiotemporal mapping of RNA editing in the developing mouse brain using in situ sequencing reveals regional and cell-type-specific regulation

BMC Biology ◽  
2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Elin Lundin ◽  
Chenglin Wu ◽  
Albin Widmark ◽  
Mikaela Behm ◽  
Jens Hjerling-Leffler ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Editing ◽  
Mouse Brain ◽  
Developmental Stages ◽  
Cell Types ◽  
Specific Cell ◽  
Cell Type ◽  
Cell Type Specific ◽  
Specific Regulation

Abstract Background Adenosine-to-inosine (A-to-I) RNA editing is a process that contributes to the diversification of proteins that has been shown to be essential for neurotransmission and other neuronal functions. However, the spatiotemporal and diversification properties of RNA editing in the brain are largely unknown. Here, we applied in situ sequencing to distinguish between edited and unedited transcripts in distinct regions of the mouse brain at four developmental stages, and investigate the diversity of the RNA landscape. Results We analyzed RNA editing at codon-altering sites using in situ sequencing at single-cell resolution, in combination with the detection of individual ADAR enzymes and specific cell type marker transcripts. This approach revealed cell-type-specific regulation of RNA editing of a set of transcripts, and developmental and regional variation in editing levels for many of the targeted sites. We found increasing editing diversity throughout development, which arises through regional- and cell type-specific regulation of ADAR enzymes and target transcripts. Conclusions Our single-cell in situ sequencing method has proved useful to study the complex landscape of RNA editing and our results indicate that this complexity arises due to distinct mechanisms of regulating individual RNA editing sites, acting both regionally and in specific cell types.

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