Deep Single-Cell-Type Proteome Profiling of Mouse Brain by Nonsurgical AAV-Mediated Proximity Labeling.

Proteome profiling is a powerful tool in biological and biomedical studies, starting with samples at bulk, single-cell, or single-cell-type levels. Reliable methods for extracting specific cell-type proteomes are in need, especially for the cells (e.g., neurons) that cannot be readily isolated. Here, we present an innovative proximity labeling (PL) strategy for single-cell-type proteomics of mouse brain, in which TurboID (an engineered biotin ligase) is used to label almost all proteins in a specific cell type. This strategy bypasses the requirement of cell isolation and includes five major steps: (i) constructing recombinant adeno-associated viruses (AAVs) to express TurboID driven by cell-type-specific promoters, (ii) delivering the AAV to mouse brains by direct intravenous injection, (iii) enhancing PL labeling by biotin administration, (iv) purifying biotinylated proteins, followed by on-bead protein digestion, and (v) quantitative tandem-mass-tag (TMT) labeling. We first confirmed that TurboID can label a wide range of cellular proteins in human HEK293 cells and optimized the single-cell-type proteomic pipeline. To analyze specific brain cell types, we generated recombinant AAVs to coexpress TurboID and mCherry proteins, driven by neuron- or astrocyte-specific promoters and validated the expected cell expression by coimmunostaining of mCherry and cellular markers. Subsequent biotin purification and TMT analysis identified ∼10,000 unique proteins from a few micrograms of protein samples with excellent reproducibility. Comparative and statistical analyses indicated that these PL proteomes contain cell-type-specific cellular pathways. Although PL was originally developed for studying protein-protein interactions and subcellular proteomes, we extended it to efficiently tag the entire proteomes of specific cell types in the mouse brain using TurboID biotin ligase. This simple, effective in vivo approach should be broadly applicable to single-cell-type proteomics.

JUMPt: Comprehensive Protein Turnover Modeling of In Vivo Pulse SILAC Data by Ordinary Differential Equations.

Recent advances in mass spectrometry (MS)-based proteomics allow the measurement of turnover rates of thousands of proteins using dynamic labeling methods, such as pulse stable isotope labeling by amino acids in cell culture (pSILAC). However, when applying the pSILAC strategy to multicellular animals (e.g., mice), the labeling process is significantly delayed by native amino acids recycled from protein degradation in vivo, raising a challenge of defining accurate protein turnover rates. Here, we report JUMPt, a software package using a novel ordinary differential equation (ODE)-based mathematical model to determine reliable rates of protein degradation. The uniqueness of JUMPt is to consider amino acid recycling and fit the kinetics of the labeling amino acid (e.g., Lys) and whole proteome simultaneously to derive half-lives of individual proteins. Multiple settings in the software are designed to enable simple to comprehensive data inputs for precise analysis of half-lives with flexibility. We examined the software by studying the turnover of thousands of proteins in the pSILAC brain and liver tissues. The results were largely consistent with the proteome turnover measurements from previous studies. The long-lived proteins are enriched in the integral membrane, myelin sheath, and mitochondrion in the brain. In summary, the ODE-based JUMPt software is an effective proteomics tool for analyzing large-scale protein turnover, and the software is publicly available on GitHub (https://github.com/JUMPSuite/JUMPt) to the research community.

Tau modification by the norepinephrine metabolite DOPEGAL stimulates its pathology and propagation.

The noradrenergic locus ceruleus (LC) is the first site of detectable tau pathology in Alzheimer's disease (AD), but the mechanisms underlying the selective vulnerability of the LC in AD have not been completely identified. In the present study, we show that DOPEGAL, a monoamine oxidase A (MAO-A) metabolite of norepinephrine (NE), reacts directly with the primary amine on the Lys353 residue of tau to stimulate its aggregation and facilitate its propagation. Inhibition of MAO-A or mutation of the Lys353 residue to arginine (Lys353Arg) decreases tau Lys353-DOPEGAL levels and diminishes tau pathology spreading. Wild-type tau preformed fibrils (PFFs) trigger Lys353-DOPEGAL formation, tau pathology propagation and cognitive impairment in MAPT transgenic mice, all of which are attenuated with PFFs made from the Lys353Arg mutant. Thus, the selective vulnerability of LC neurons in AD may be explained, in part, by NE oxidation via MAO-A into DOPEGAL, which covalently modifies tau and accelerates its aggregation, toxicity and propagation.

Alzheimer's disease-associated U1 snRNP splicing dysfunction causes neuronal hyperexcitability and cognitive impairment.

Recent proteome and transcriptome profiling of Alzheimer's disease (AD) brains reveals RNA splicing dysfunction and U1 small nuclear ribonucleoprotein (snRNP) pathology containing U1-70K and its N-terminal 40-KDa fragment (N40K). Here we present a causative role of U1 snRNP dysfunction to neurodegeneration in primary neurons and transgenic mice (N40K-Tg), in which N40K expression exerts a dominant-negative effect to downregulate full-length U1-70K. N40K-Tg recapitulates N40K insolubility, erroneous splicing events, neuronal degeneration and cognitive impairment. Specifically, N40K-Tg shows the reduction of GABAergic synapse components (e.g., the GABA receptor subunit of GABRA2), and concomitant postsynaptic hyperexcitability that is rescued by a GABA receptor agonist. Crossing of N40K-Tg and the 5xFAD amyloidosis model indicates that the RNA splicing defect synergizes with the amyloid cascade to remodel the brain transcriptome and proteome, deregulate synaptic proteins, and accelerate cognitive decline. Thus, our results support the contribution of U1 snRNP-mediated splicing dysfunction to AD pathogenesis.

Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer's Disease Progression.

Alzheimer's disease (AD) displays a long asymptomatic stage before dementia. We characterize AD stage-associated molecular networks by profiling 14,513 proteins and 34,173 phosphosites in the human brain with mass spectrometry, highlighting 173 protein changes in 17 pathways. The altered proteins are validated in two independent cohorts, showing partial RNA dependency. Comparisons of brain tissue and cerebrospinal fluid proteomes reveal biomarker candidates. Combining with 5xFAD mouse analysis, we determine 15 Aß-correlated proteins (e.g., MDK, NTN1, SMOC1, SLIT2, and HTRA1). 5xFAD shows a proteomic signature similar to symptomatic AD but exhibits activation of autophagy and interferon response and lacks human-specific deleterious events, such as downregulation of neurotrophic factors and synaptic proteins. Multi-omics integration prioritizes AD-related molecules and pathways, including amyloid cascade, inflammation, complement, WNT signaling, TGF-ß and BMP signaling, lipid metabolism, iron homeostasis, and membrane transport. Some Aß-correlated proteins are colocalized with amyloid plaques. Thus, the multilayer omics approach identifies protein networks during AD progression.