RNA Dynamics in Alzheimer’s Disease

Alzheimer's disease (AD) is the most common age-related neurodegenerative disorder that heavily burdens healthcare systems worldwide. There is a significant requirement to understand the still unknown molecular mechanisms underlying AD. Current evidence shows that two of the major features of AD are transcriptome dysregulation and altered function of RNA binding proteins (RBPs), both of which lead to changes in the expression of different RNA species, including microRNAs (miRNAs), circular RNAs (circRNAs), long non-coding RNAs (lncRNAs), and messenger RNAs (mRNAs). In this review, we will conduct a comprehensive overview of how RNA dynamics are altered in AD and how this leads to the differential expression of both short and long RNA species. We will describe how RBP expression and function are altered in AD and how this impacts the expression of different RNA species. Furthermore, we will also show how changes in the abundance of specific RNA species are linked to the pathology of AD

A Variety of Dicer Substrates in Human and C. elegans

SummaryThe endoribonuclease Dicer is known for its central role in the biogenesis of eukaryotic small RNAs/microRNAs. Despite its importance, Dicer target transcripts have not been directly mapped. Here, we apply biochemical methods to human cells and C. elegans and identify thousands of Dicer-binding sites. We find known and hundreds of additional miRNAs with high sensitivity and specificity. We also report structural RNAs, promoter RNAs, and mitochondrial transcripts as Dicer targets. Interestingly, most Dicer-binding sites reside on mRNAs/lncRNAs and are not significantly processed into small RNAs. These passive sites typically harbor small, Dicer-bound hairpins within intact transcripts and generally stabilize target expression. We show that passive sites can sequester Dicer and reduce microRNA expression. mRNAs with passive sites were in human and worm significantly associated with processing-body/granule function. Together, we provide the first transcriptome-wide map of Dicer targets and suggest conserved binding modes and functions outside of the miRNA pathway

A proteomics analysis of 5xFAD mouse brain regions reveals the lysosome-associated protein Arl8b as a candidate biomarker for Alzheimer's disease

BACKGROUND: Alzheimer's disease (AD) is characterized by the intra- and extracellular accumulation of amyloid-β (Aβ) peptides. How Aβ aggregates perturb the proteome in brains of patients and AD transgenic mouse models, remains largely unclear. State-of-the-art mass spectrometry (MS) methods can comprehensively detect proteomic alterations, providing relevant insights unobtainable with transcriptomics investigations. Analyses of the relationship between progressive Aβ aggregation and protein abundance changes in brains of 5xFAD transgenic mice have not been reported previously. METHODS: We quantified progressive Aβ aggregation in hippocampus and cortex of 5xFAD mice and controls with immunohistochemistry and membrane filter assays. Protein changes in different mouse tissues were analyzed by MS-based proteomics using label-free quantification; resulting MS data were processed using an established pipeline. Results were contrasted with existing proteomic data sets from postmortem AD patient brains. Finally, abundance changes in the candidate marker Arl8b were validated in cerebrospinal fluid (CSF) from AD patients and controls using ELISAs. RESULTS: Experiments revealed faster accumulation of Aβ42 peptides in hippocampus than in cortex of 5xFAD mice, with more protein abundance changes in hippocampus, indicating that Aβ42 aggregate deposition is associated with brain region-specific proteome perturbations. Generating time-resolved data sets, we defined Aβ aggregate-correlated and anticorrelated proteome changes, a fraction of which was conserved in postmortem AD patient brain tissue, suggesting that proteome changes in 5xFAD mice mimic disease-relevant changes in human AD. We detected a positive correlation between Aβ42 aggregate deposition in the hippocampus of 5xFAD mice and the abundance of the lysosome-associated small GTPase Arl8b, which accumulated together with axonal lysosomal membranes in close proximity of extracellular Aβ plaques in 5xFAD brains. Abnormal aggregation of Arl8b was observed in human AD brain tissue. Arl8b protein levels were significantly increased in CSF of AD patients. CONCLUSIONS: We report a comprehensive biochemical and proteomic investigation of hippocampal and cortical brain tissue derived from 5xFAD transgenic mice, providing a valuable resource to the neuroscientific community. We identified Arl8b, with significant abundance changes in 5xFAD and AD patient brains. Arl8b might enable the measurement of progressive lysosome accumulation in AD patients and have clinical utility as a candidate biomarker

Circular RNAs in the Mammalian Brain Are Highly Abundant, Conserved, and Dynamically Expressed

Circular RNAs (circRNAs) are an endogenous class of animal RNAs. Despite their abundance, their function and expression in the nervous system are unknown. Therefore, we sequenced RNA from different brain regions, primary neurons, isolated synapses, as well as during neuronal differentiation. Using these and other available data, we discovered and analyzed thousands of neuronal human and mouse circRNAs. circRNAs were extraordinarily enriched in the mammalian brain, well conserved in sequence, often expressed as circRNAs in both human and mouse, and sometimes even detected in Drosophila brains. circRNAs were overall upregulated during neuronal differentiation, highly enriched in synapses, and often differentially expressed compared to their mRNA isoforms. circRNA expression correlated negatively with expression of the RNA-editing enzyme ADAR1. Knockdown of ADAR1 induced elevated circRNA expression. Together, we provide a circRNA brain expression atlas and evidence for important circRNA functions and values as biomarkers.Fil: Rybak Wolf, Agnieszka. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Stottmeister, Christin. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Glažar, Petar. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Jens, Marvin. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Pino, Natalia. Max Planck Institute of Psychiatry; AlemaniaFil: Giusti, Sebastian. Max Planck Institute of Psychiatry; AlemaniaFil: Hanan, Mor. The Hebrew University of Jerusalem; IsraelFil: Behm, Mikaela. Stockholms Universitet; SueciaFil: Bartok, Osnat. The Hebrew University of Jerusalem; IsraelFil: Ashwal Fluss, Reut. The Hebrew University of Jerusalem; IsraelFil: Herzog, Margareta. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Schreyer, Luisa. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Papavasileiou, Panagiotis. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Ivanov, Andranik. Max-Delbrück Center for Molecular Medicine; AlemaniaFil: Öhman, Marie. Stockholms Universitet; SueciaFil: Refojo, Damian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires - Instituto Partner de la Sociedad Max Planck; Argentina. Max Planck Institute of Psychiatry; AlemaniaFil: Kadener, Sebastian. The Hebrew University of Jerusalem; IsraelFil: Rajewsky, Nikolaus. Max-Delbrück Center for Molecular Medicine; Alemani

Additional file 1 of A proteomics analysis of 5xFAD mouse brain regions reveals the lysosome-associated protein Arl8b as a candidate biomarker for Alzheimer’s disease

Additional file 1: Table S1. Commercial antibodies used in this study. Table S2. Characteristics of AD and HD patients and corresponding controls. Table S3. Spearman correlation analysis of Arl8b protein level measurements and AD biomarker levels

Additional file 2 of A proteomics analysis of 5xFAD mouse brain regions reveals the lysosome-associated protein Arl8b as a candidate biomarker for Alzheimer’s disease

Additional file 2: Fig. S1. Aβ peptide levels and APP and PSEN1 expression in hippocampus and cortex of 5xFAD mice. Fig. S2. Analysis of Aβ aggregate formation using membrane filter assays and sucrose gradient centrifugations. Fig. S3. Analysis of wild-type expression profiles to assess whether the protein abundance changes detected in 5xFAD brains are more frequent among highly expressed mouse proteins. Fig. S4. Functional analysis of dysregulated proteins defined with a pairwise model in brains of 5xFAD mice. Fig. S5. Enrichment analysis of cell-type-specific marker proteins among dysregulated proteins in brains of 5xFAD mice. Fig. S6. IPA and gene ontology enrichment analysis of differentially expressed proteins defined with the full model in cortical and hippocampal tissues of 5xFAD mice. Fig. S7. Ingenuity pathway analysis of Aβ-correlated and anticorrelated DEPs defined by the pairwise model in brains of 5xFAD mice. Fig. S8. Numbers of pairwise common DEPs in the mouse datasets and datasets from human studies. Fig. S9. Strategy to define mouse protein signatures that are concordantly altered also in AD patient brains. Fig. S10. Investigation of the overlap of DEPs in brains of 5xFAD mice with DEPs in asymptomatic AD brains. Fig. S11. Analysis of the correlation in protein effect sizes between 5xFAD mouse and AD patient brains for proteins present in all studies. Fig. S12. Selection of the neuronal lysosome-associated protein Arl8b by step-by-step data filtering. Fig. S13. Immunofluorescence analysis of 5xFAD brain slices. Fig. S14. Analysis of Arl8b protein aggregates using human brain homogenates derived from AD patients and control individuals

Additional file 3 of A proteomics analysis of 5xFAD mouse brain regions reveals the lysosome-associated protein Arl8b as a candidate biomarker for Alzheimer’s disease

Additional file 3: Supplementary Excel File 1a. DEPs from 5xFAD versus wild-type tissue comparisons in hippocampus and cortex; DEPs were defined using the “pairwise model”; Supplementary Excel File 1b. Summary of the statistical calculations from Supplementary Excel File 1a; Supplementary Excel File 1c. DEPs in both hippocampal and cortical tissues defined through the “full model”; Supplementary Excel File 2. DEPs that correlate or anticorrelate to Aβ aggregate load in both hippocampal and cortical tissues defined through the “pairwise model”; Supplementary Excel File 3. Identified genes differentially down- or upregulatedin cortex or hippocampus of 5xFAD mice; Supplementary Excel File 4. Results of the Ingenuity Pathway Analyses performed in Figures 3g and 4e; Supplementary Excel File 5a. Proteins with significant abundance changes from Johnson et al. 2020; Supplementary Excel File 5b. Proteins with significant abundance changes from Johnson et al. 2022; Supplementary Excel File 5c. Proteins with significant abundance changes from Johnson et al. 2022; Supplementary Excel File 5d. Proteins with significant abundance changes from Drummond et al. 2022; Supplementary Excel File 6. Numbers of common DEPs in mouse and human datasets; Supplementary Excel File 7. DEPs defined using a “pairwise model” and concomitantly altered both in mouse and human brain tissues from J20, J22 and D22. Supplementary Excel File 8a. The step-by-step selection process to identify the potential AD biomarker Arl8b. Supplementary Excel File 8b. The top 25 Aβ-correlated proteins in mouse hippocampal tissues

Defective metabolic programming impairs early neuronal morphogenesis in neural cultures and an organoid model of Leigh syndrome

Leigh syndrome (LS) is a severe manifestation of mitochondrial disease in children and is currently incurable. The lack of effective models hampers our understanding of the mechanisms underlying the neuronal pathology of LS. Using patient-derived induced pluripotent stem cells and CRISPR/Cas9 engineering, we developed a human model of LS caused by mutations in the complex IV assembly gene SURF1. Single-cell RNA-sequencing and multi-omics analysis revealed compromised neuronal morphogenesis in mutant neural cultures and brain organoids. The defects emerged at the level of neural progenitor cells (NPCs), which retained a glycolytic proliferative state that failed to instruct neuronal morphogenesis. LS NPCs carrying mutations in the complex I gene NDUFS4 recapitulated morphogenesis defects. SURF1 gene augmentation and PGC1A induction via bezafibrate treatment supported the metabolic programming of LSNPCs, leading to restored neuronal morphogenesis. Our findings provide mechanistic insights and suggest potential interventional strategies for a rare mitochondrial disease