Brain Cell Type-Specific Nuclear Proteomics Is Imperative to Resolve Neurodegenerative Disease Mechanisms

FrozONE: quick cell nucleus enrichment for comprehensive proteomics analysis of frozen tissues

Subcellular fractionation allows for the investigation of compartmentalized processes in individual cellular organelles. Nuclear enrichment methods commonly employ the use of density gradients combined with ultracentrifugation for freshly isolated tissues. Although it is broadly used in combination with proteomics, this approach poses several challenges when it comes to scalability and applicability for frozen material. To overcome these limitations, we developed FrozONE (Frozen Organ Nucleus Enrichment), a nucleus enrichment and proteomics workflow for frozen tissues. By extensively benchmarking our workflow against alternative methods, we showed that FrozONE is a faster, simpler, and more scalable alternative to conventional ultracentrifugation methods. FrozONE allowed for the study, profiling, and classification of nuclear proteomes in different tissues with complex cellular heterogeneity, ensuring optimal nucleus enrichment from different cell types and quantitative resolution for low abundant proteins. In addition to its performance in healthy mouse tissues, FrozONE proved to be very efficient for the characterization of liver nuclear proteome alterations in a pathological condition, diet-induced nonalcoholic steatohepatitis.

Neurotrophic Effects of Foeniculum vulgare Ethanol Extracts on Hippocampal Neurons: Role of Anethole in Neurite Outgrowth and Synaptic Development

Foeniculum vulgare Mill, commonly known as fennel, is an aromatic herb traditionally used for culinary and medicinal purposes, with potential therapeutic effects on neurological disorders. However, limited research has focused on its neurotrophic impact, particularly on neuronal maturation and synaptic development. This study investigates the neurotrophic effects of F. vulgare ethanol extracts (FVSE) on the maturation of rat primary hippocampal neurons. Results show that FVSE and its prominent component, anethole, significantly promote neurite outgrowth in a dose-dependent manner. Optimal axonal and dendritic growth occurred at concentrations of 40 µg/mL FVSE and 20 µM anethole, respectively, without causing cytotoxicity, underscoring the safety of FVSE for neuronal health. Additionally, FVSE enhances the formation of synapses, essential for neuronal communication. Network pharmacology analysis revealed that FVSE components influence critical neurotrophic pathways, including PI3K-AKT and Alzheimer's disease pathways. Specifically, FVSE modulates key proteins, including tropomyosin receptor kinase (Trk), glycogen synthase kinase 3 (GSK3βser9), phosphatidylinositol 3-kinase (PI3K), and extracellular signal-regulated protein kinase (Erk1/2). Anethole was found to play a key role in regulating these pathways, which was confirmed by immunocytochemistry experiments demonstrating its effect on promoting neuronal growth and synaptic development. In conclusion, this study highlights the neurotrophic properties of FVSE, with anethole emerging as a critical bioactive compound. These findings provide valuable insights into the therapeutic potential of fennel in treating neurological disorders, offering a basis for future research into interventions promoting neuronal growth and survival.

In vivo validation of late-onset Alzheimer's disease genetic risk factors

INTRODUCTION

Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action.

METHODS

Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE ε4/ε4 and Trem2*R47H. The potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts.

RESULTS

We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes.

DISCUSSION

These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.

HIGHLIGHTS

A novel approach to validate genetic risk factors for late-onset AD (LOAD) is presented. LOAD risk variants were knocked in to conserved mouse loci. Variant effects were assayed by transcriptional analysis. Risk variants in Abca7, Mthfr, Plcg2, and Sorl1 loci modeled molecular signatures of clinical disease. This approach should generate more translationally relevant animal models.

In vivo validation of late-onset Alzheimer's disease genetic risk factors

Introduction

Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action.

Methods

Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE4 and Trem2*R47H. Potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts.

Results

We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes.

Discussion

These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.

Cellular Proteomic Profiling Using Proximity Labeling by TurboID-NES in Microglial and Neuronal Cell Lines

Different brain cell types play distinct roles in brain development and disease. Molecular characterization of cell-specific mechanisms using cell type-specific approaches at the protein (proteomic) level can provide biological and therapeutic insights. To overcome the barriers of conventional isolation-based methods for cell type-specific proteomics, in vivo proteomic labeling with proximity-dependent biotinylation of cytosolic proteins using biotin ligase TurboID, coupled with mass spectrometry (MS) of labeled proteins, emerged as a powerful strategy for cell type-specific proteomics in the native state of cells without the need for cellular isolation. To complement in vivo proximity labeling approaches, in vitro studies are needed to ensure that cellular proteomes using the TurboID approach are representative of the whole-cell proteome and capture cellular responses to stimuli without disruption of cellular processes. To address this, we generated murine neuroblastoma (N2A) and microglial (BV2) lines stably expressing cytosolic TurboID to biotinylate the cellular proteome for downstream purification and analysis using MS. TurboID-mediated biotinylation captured 59% of BV2 and 65% of N2A proteomes under homeostatic conditions. TurboID labeled endolysosome, translation, vesicle, and signaling proteins in BV2 microglia and synaptic, neuron projection, and microtubule proteins in N2A neurons. TurboID expression and biotinylation minimally impacted homeostatic cellular proteomes of BV2 and N2A cells and did not affect lipopolysaccharide-mediated cytokine production or resting cellular respiration in BV2 cells. MS analysis of the microglial biotin-labeled proteins captured the impact of lipopolysaccharide treatment (>500 differentially abundant proteins) including increased canonical proinflammatory proteins (Il1a, Irg1, and Oasl1) and decreased anti-inflammatory proteins (Arg1 and Mgl2).

Somatic mosaicism in the diseased brain

It is hard to believe that all the cells of a human brain share identical genomes. Indeed, single cell genetic studies have demonstrated intercellular genomic variability in the normal and diseased brain. Moreover, there is a growing amount of evidence on the contribution of somatic mosaicism (the presence of genetically different cell populations in the same individual/tissue) to the etiology of brain diseases. However, brain-specific genomic variations are generally overlooked during the research of genetic defects associated with a brain disease. Accordingly, a review of brain-specific somatic mosaicism in disease context seems to be required. Here, we overview gene mutations, copy number variations and chromosome abnormalities (aneuploidy, deletions, duplications and supernumerary rearranged chromosomes) detected in the neural/neuronal cells of the diseased brain. Additionally, chromosome instability in non-cancerous brain diseases is addressed. Finally, theoretical analysis of possible mechanisms for neurodevelopmental and neurodegenerative disorders indicates that a genetic background for formation of somatic (chromosomal) mosaicism in the brain is likely to exist. In total, somatic mosaicism affecting the central nervous system seems to be a mechanism of brain diseases.