Temporal and spatially controlled APP transgene expression using Cre-dependent alleles

Need of orthogonal approaches in neurological disease modeling in mouse

Over the years, advancements in modeling neurological diseases have revealed innovative strategies aimed at gaining deeper insights and developing more effective treatments for these complex conditions. However, these progresses have recently been overshadowed by an increasing number of failures in clinical trials, raising doubts about the reliability and translatability of this type of disease modeling. This mini-review does not aim to provide a comprehensive overview of the current state-of-the-art in disease mouse modeling. Instead, it offers a brief excursus over some recent approaches in modeling neurological diseases to pinpoint a few intriguing strategies applied in the field that may serve as sources of inspiration for improving currently available animal models. In particular, we aim to guide the reader toward the potential success of adopting a more orthogonal approach in the study of human diseases.

Differential usage of DNA modifications in neurons, astrocytes, and microglia

BACKGROUND

Cellular identity is determined partly by cell type-specific epigenomic profiles that regulate gene expression. In neuroscience, there is a pressing need to isolate and characterize the epigenomes of specific CNS cell types in health and disease. In this study, we developed an in vivo tagging mouse model (Camk2a-NuTRAP) for paired isolation of neuronal DNA and RNA without cell sorting and then used this model to assess epigenomic regulation, DNA modifications in particular, of gene expression between neurons and glia.

RESULTS

After validating the cell-specificity of the Camk2a-NuTRAP model, we performed TRAP-RNA-Seq and INTACT-whole genome oxidative bisulfite sequencing (WGoxBS) to assess the neuronal translatome and epigenome in the hippocampus of young mice (4 months old). WGoxBS findings were validated with enzymatic methyl-Seq (EM-Seq) and nanopore sequencing. Comparing neuronal data to microglial and astrocytic data from NuTRAP models, microglia had the highest global mCG levels followed by astrocytes and then neurons, with the opposite pattern observed for hmCG and mCH. Differentially modified regions between cell types were predominantly found within gene bodies and distal intergenic regions, rather than proximal promoters. Across cell types there was a negative correlation between DNA modifications (mCG, mCH, hmCG) and gene expression at proximal promoters. In contrast, a negative correlation of gene body mCG and a positive relationship between distal promoter and gene body hmCG with gene expression was observed. Furthermore, we identified a neuron-specific inverse relationship between mCH and gene expression across promoter and gene body regions.

CONCLUSIONS

Neurons, astrocytes, and microglia demonstrate different genome-wide levels of mCG, hmCG, and mCH that are reproducible across analytical methods. However, modification-gene expression relationships are conserved across cell types. Enrichment of differential modifications across cell types in gene bodies and distal regulatory elements, but not proximal promoters, highlights epigenomic patterning in these regions as potentially greater determinants of cell identity. These findings also demonstrate the importance of differentiating between mC and hmC in neuroepigenomic analyses, as up to 30% of what is conventionally interpreted as mCG can be hmCG, which often has a different relationship to gene expression than mCG.

Differential usage of DNA modifications in neurons, astrocytes, and microglia

Background

Cellular identity is determined partly by cell type-specific epigenomic profiles that regulate gene expression. In neuroscience, there is a pressing need to isolate and characterize the epigenomes of specific CNS cell types in health and disease. This is especially true as for DNA modifications where most data are derived from bisulfite sequencing that cannot differentiate between DNA methylation and hydroxymethylation. In this study, we developed an in vivo tagging mouse model (Camk2a-NuTRAP) for paired isolation of neuronal DNA and RNA without cell sorting and then used this model to assess epigenomic regulation of gene expression between neurons and glia.

Results

After validating the cell-specificity of the Camk2a-NuTRAP model, we performed TRAP-RNA-Seq and INTACT whole genome oxidative bisulfite sequencing to assess the neuronal translatome and epigenome in the hippocampus of young mice (3 months old). These data were then compared to microglial and astrocytic data from NuTRAP models. When comparing the different cell types, microglia had the highest global mCG levels followed by astrocytes and then neurons, with the opposite pattern observed for hmCG and mCH. Differentially modified regions between cell types were predominantly found within gene bodies and distal intergenic regions, with limited differences occurring within proximal promoters. Across cell types there was a negative correlation between DNA modifications (mCG, mCH, hmCG) and gene expression at proximal promoters. In contrast, a negative correlation of mCG with gene expression within the gene body while a positive relationship between distal promoter and gene body hmCG and gene expression was observed. Furthermore, we identified a neuron-specific inverse relationship between mCH and gene expression across promoter and gene body regions.

Conclusions

In this study, we identified differential usage of DNA modifications across CNS cell types, and assessed the relationship between DNA modifications and gene expression in neurons and glia. Despite having different global levels, the general modification-gene expression relationship was conserved across cell types. The enrichment of differential modifications in gene bodies and distal regulatory elements, but not proximal promoters, across cell types highlights epigenomic patterning in these regions as potentially greater determinants of cell identity.

Sharing resources to advance translational research

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First person – Emily Koller

First Person is a series of interviews with the first authors of a selection of papers published in Disease Models & Mechanisms, helping early-career researchers promote themselves alongside their papers. Emily Koller is first author on ‘ Temporal and spatially controlled APP transgene expression using Cre-dependent alleles’, published in DMM. Emily is a postdoctoral associate in the lab of Joanna Jankowsky, PhD at Baylor College of Medicine, Houston, TX, USA, investigating the impact of ageing in Alzheimer's disease, and is also interested in developing therapeutic interventions for diseases of the brain.