Dataset Information

Analysis of Amyloid Plaque Composition in two mouse models of Alzheimer’s disease

ABSTRACT: MALDI mass spectrometry imaging (MSI) enables label-free, spatially resolved analysis of a wide range of analytes in tissue sections. Quantitative analysis of MSI datasets is typically performed on single pixels or manually assigned regions of interest (ROI). However, many sparse, small objects such as Alzheimer’s disease (AD) brain deposits of amyloid peptides called plaques are neither single pixels nor ROI. Here, we propose a new approach to facilitate comparative computational evaluation of amyloid plaque-like objects by MSI: a fast PLAQUE PICKER tool that enables statistical evaluation of heterogeneous amyloid peptide composition. Comparing two AD mouse models, APP NL-G-F and APP PS1, we identified distinct heterogeneous plaque populations in the NL-G-F model, but only one class of plaques in the PS1 model. We propose quantitative metrics for the comparison of technical and biological MSI replicates.

INSTRUMENT(S): Bruker Daltonics flex series

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Brain

DISEASE(S): Alzheimer's Disease

SUBMITTER: Thomas Enzlein

LAB HEAD: Carsten Hopf

PROVIDER: PXD020824 | Pride | 2020-10-15

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	APPNL-G-F_18weeks_LP2-10kDa_20um.ibd	Other
	APPNL-G-F_18weeks_LP2-10kDa_20um.imzML	Other
	APPNL-G-F_18weeks_opticalimage.png	Other
	APPNL-G-F_67weeks_LP2-10kDa_20um.ibd	Other
	APPNL-G-F_67weeks_LP2-10kDa_20um.imzML	Other

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Publications

Computational Analysis of Alzheimer Amyloid Plaque Composition in 2D- and Elastically Reconstructed 3D-MALDI MS Images.

Enzlein Thomas T Cordes Jonas J Munteanu Bogdan B Michno Wojciech W Serneels Lutgarde L De Strooper Bart B Hanrieder Jörg J Wolf Ivo I Chávez-Gutiérrez Lucía L Hopf Carsten C

Analytical chemistry 20201014 21

MALDI mass spectrometry imaging (MSI) enables label-free, spatially resolved analysis of a wide range of analytes in tissue sections. Quantitative analysis of MSI datasets is typically performed on single pixels or manually assigned regions of interest (ROIs). However, many sparse, small objects such as Alzheimer's disease (AD) brain deposits of amyloid peptides called plaques are neither single pixels nor ROIs. Here, we propose a new approach to facilitate the comparative computational evaluati ...[more]

PMID: 33138378

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Project description:Background: ABCA1 has recently been identified as a novel genetic risk factor for Alzheimer’s disease. The major known role of ABCA1 in the brain is to transfer lipids onto lipid poor APOE. Given that APOEε4 is the strongest genetic risk factor for developing late onset Alzheimer’s disease, this recent finding implicates the cholesterol homeostatic pathway in the onset/progression of Alzheimer’s disease. microRNAs (miRs) are small RNA species that negatively regulate expression of their target genes. ABCA1 is regulated by miR-33, and loss of this miR significantly increases protein levels of ABCA1 and increases the lipidation of APOE. However, it is unknown if loss of miR-33 and subsequent increase in ABCA1 protein levels ameliorates amyloid pathology. Methods: We generated miR-33+/+;APP/PS1 and miR-33-/-;APP/PS1 mice to determine changes in amyloid-beta (Aβ) peptides and amyloid plaque formation utilizing biochemical and histological analyses. In addition to amyloid pathology, we assessed if deletion of miR-33 altered the activation of glial cells in the brains of these mice. We utilized in vitro methods to determine if miR-33 alters the phagocytosis of Aβ aggregates. We utilized RNA-sequencing and mass spectrometry to identify the transcriptome and proteome regulation by miR-33 in the context of amyloid pathology. Results: Deletion of miR-33 dramatically reduces insoluble Aβ peptide levels and the deposition of amyloid plaques in APP/PS1 mice. In addition, we identified that astrocyte and microglial activation is markedly decreased in miR-33-/-;APP/PS1 mice through histological analyses. Intriguingly, we show that loss of miR-33 results in amyloid plaques that are more compact, potentially implicating enhanced microglial phagocytosis. We confirm in vitro that loss of miR-33 significantly increases microglial phagocytosis of Aβ aggregates. Our multi-omics analyses reveal that deletion of miR-33 regulates immune response in the context of amyloid pathology. Interestingly, we identified that WNT/Beta-catenin signaling is significantly upregulated in miR-33-/-;APP/PS1 mice. Conclusion: We confirm that the deletion of miR-33 increases APOE lipidation and significantly reduces amyloid pathology as well as glial activation in APP/PS1 mice. Our results agree with previous work identifying APOE lipidation as an important modulator of amyloid pathology. We show, for the first time, that loss of miR-33 increases the phagocytosis of Aβ by microglia. In total, we identify miR-33 as a promising target for the amelioration of amyloid pathology.