Dia-PASEF analysis of human amygdala in Parkinson’s disease
Ontology highlight
ABSTRACT:
INSTRUMENT(S): timsTOF Pro
ORGANISM(S): Homo Sapiens (human)
TISSUE(S): Brain
DISEASE(S): Parkinson's Disease
SUBMITTER: 
Alicia Flores
LAB HEAD: Dr Alino Martinez-Marcos
PROVIDER: PXD043503 | Pride | 2024-01-26
REPOSITORIES: Pride
Publications
Synaptic Involvement of the Human Amygdala in Parkinson's Disease.
Villar-Conde Sandra S Astillero-Lopez Veronica V Gonzalez-Rodriguez Melania M Saiz-Sanchez Daniel D Martinez-Marcos Alino A Ubeda-Banon Isabel I Flores-Cuadrado Alicia A
Molecular & cellular proteomics : MCP 20231029 12
α-Synuclein, a protein mostly present in presynaptic terminals, accumulates neuropathologically in Parkinson's disease in a 6-stage sequence and propagates in the nervous system in a prion-like manner through neurons and glia. In stage 3, the substantia nigra are affected, provoking motor symptoms and the amygdaloid complex, leading to different nonmotor symptoms; from here, synucleinopathy spreads to the temporal cortex and beyond. The expected increase in Parkinson's disease incidence accelera ...[more]
Similar Datasets
Project description:dia-PASEF analysis of human amygdala in Alzheimer’s disease
2023-06-28 | PXD038322 | Pride
Project description:Activity-based protein profiling (ABPP) uses a combination of activity-based chemical probes with mass spectrometry (MS) to selectively characterise a particular enzyme or enzyme class. ABPP has proven invaluable for profiling enzymatic inhibitors in drug discovery. When applied to cell extracts and cells, challenging the ABP-enzyme complex formation with a small molecule can simultaneously inform on potency, selectivity, reversibility/binding affinity, permeability, and stability. ABPP can also be applied to pharmacodynamic studies to inform on cellular target engagement within specific organs when applied to in vivo models. Recently, we established separate high depth and high throughput ABPP (ABPP-HT) protocols for the profiling of deubiquitylating enzymes (DUBs). However, the combination of the two, deep and fast, in one method has been elusive. To further increase the sensitivity of the current ABPP-HT workflow we implemented state-of-the-art data-independent acquisition (DIA) and data-dependent acquisition (DDA) MS analysis tools. Hereby, we describe an improved methodology, ABPP-HT* (enhanced high-throughput-compatible activity-based protein profiling), that in combination with DIA MS methods allowed for the consistent profiling of 35-40 DUBs and provided a reduced number of missing values, whilst maintaining a throughput of 100 samples per day.
2022-04-04 | PXD031848 | Pride
Project description:Data-independent acquisition (DIA) methods have become increasingly attractive in mass spectrometry (MS)-based proteomics, because they enable high data completeness and a wide dynamic range. Recently, we combined DIA with parallel accumulation – serial fragmentation (dia-PASEF) on a Bruker trapped ion mobility separated (TIMS) quadrupole time-of-flight (TOF) mass spectrometer. This requires alignment of the ion mobility separation with the downstream mass selective quadrupole, leading to a more complex scheme for dia-PASEF window placement compared to DIA. To achieve high data completeness and deep proteome coverage, here we employ variable isolation windows that are placed optimally depending on precursor density in the m/z and ion mobility plane. This Automatic Isolation Design procedure is implemented in the freely available py_diAID package. In combination with in-depth project-specific proteomics libraries and the Evosep LC system, we reproducibly identified over 7,700 proteins in a human cancer cell line in 44 minutes with quadruplicate single-shot injections at high sensitivity. Even at a throughput of 100 samples per day (11 minutes LC gradients), we consistently quantified more than 6,000 proteins in mammalian cell lysates by injecting four replicates. We found that optimal dia-PASEF window placement facilitates in-depth phosphoproteomics with very high sensitivity, quantifying more than 35,000 phosphosites in a human cancer cell line stimulated with an epidermal growth factor (EGF) in triplicate 21 minutes runs. This covers a substantial part of the regulated phosphoproteome with high sensitivity, opening up for extensive systems-biological studies.
2022-08-11 | PXD034128 | Pride
Project description:Spatial tissue proteomics combining microscopy-based cell phenotyping with ultrasensitive mass spectrometry (MS)-based proteomics is an emerging and powerful concept for the study of cell function and heterogeneity in health and disease. However, optimized workflows that preserve morphological information for image-based phenotype discovery and maximize proteome coverage of few or even single cells from laser microdissected archival tissue, are currently lacking. Here, we report a robust and scalable workflow for the proteomic analysis of ultra-low input formalin-fixed, paraffin-embedded (FFPE) material. Benchmarking in the murine liver resulted in up to 2,000 quantified proteins from single hepatocyte contours and nearly 5,000 proteins from 50-cell regions with high quantitative reproducibility. Applied to human tonsil, we profiled 146 microregions including spatially defined T and B lymphocyte niches and quantified cell-type specific markers, cytokines, immune cell regulators and transcription factors. These rich data also highlighted proteome dynamics in spatially defined zones of activated germinal centers, illuminating sites undergoing active B-cell proliferation and somatic hypermutation. Our results demonstrate the power of spatially-resolved proteomics for tissue phenotyping by integrating high-content imaging, laser microdissection, and ultrasensitive mass spectrometry. This approach has broad implications for a wide range of biomedical applications, including early disease profiling, drug target discovery and biomarker research.
2023-11-08 | PXD042367 | Pride
Project description:Several studies have reported diverse and prolonged symptoms after COVID-19; however, how long-term pulmonary dysfunction (L-TPD) post-COVID-19 is manifested, which variables support it, and which are the concomitant consequences remain unknown. In this study patients with L-TPD were identified according to their computer-tomography and diffusing capacity-for-carbon-monoxide evaluations at 4-month post-infection. Regarding the acute phase, L-TPD was favored in elderly patients with comorbidities, supported by pathways such as cardiac dysfunction and chemotaxis of phagocytes. At 4-months post-infection, L-TPD patients exhibited a restrictive lung condition favored by CXCL9, platelets and an inhibited FCgamma-receptor-mediated-phagocytosis due to reduced CD16 expression in their monocytes, suggesting that phagocytosis of virus-antibody immune complexes was compromised in this group. Finally, one-year post infection, patients with L-TPD worsened metabolic syndrome and augmented body mass index in comparison with other patient groups. Overall, our data suggest that COVID-19 survivors required a personalized follow-up and adequate intervention to reduce long-term sequelae and the appearance of further metabolic diseases.
2023-11-22 | PXD040175 | Pride
Project description:Single-cell proteomics by mass spectrometry (MS) is emerging as a powerful and unbiased method for the characterization of biological heterogeneity. So far, it has been limited to cultured cells, whereas an expansion of the method to complex tissues would greatly enhance biological insights. Here we describe single-cell Deep Visual Proteomics (scDVP), a technology that integrates high-content imaging, laser microdissection and multiplexed MS. scDVP resolves the context-dependent, spatial proteome of murine hepatocytes at a current depth of 1,700 proteins from a slice of a cell. Half of the proteome was differentially regulated in a spatial manner, with protein levels changing dramatically in proximity to the central vein. We applied machine learning to proteome classes and images, which subsequently inferred the spatial proteome from imaging data alone. scDVP is applicable to healthy and diseased tissues and complements other spatial proteomics or spatial omics technologies.
2023-10-02 | PXD038699 | Pride
Project description:Spatial tissue proteomics integrating whole-slide imaging, laser microdissection and ultrasensitive mass spectrometry is a powerful approach to link cellular phenotypes to functional proteome states in (patho)physiology. To be applicable to large patient cohorts and low sample input amounts, including single-cell applications, loss-minimized and streamlined end-to-end workflows are key. We here introduce an automated sample preparation protocol for laser microdissected samples utilizing the cellenONE® robotic system, which has the capacity to process 192 samples in three hours. Following laser microdissection collection directly into the proteoCHIP LF 48 or EVO 96 chip, our optimized protocol facilitates lysis, formalin de-crosslinking and tryptic digest of low-input archival tissue samples. The seamless integration with the Evosep ONE LC system by centrifugation allows ‘on-the-fly’ sample clean-up, particularly pertinent for laser microdissected workflows. We validate our method in human tonsil archival tissue, where we profile proteomes of spatially-defined B-cell, T-cell and epithelial microregions of 4,000 µm2 to a depth of ~2,000 proteins and with high cell type specificity. We finally provide detailed equipment templates and experimental guidelines for broad accessibility.
2024-03-22 | PXD047762 | Pride
Project description:The N-methyl-D-aspartate (NMDA) receptor is a glutamate-activated cation channel critical to many processes in the brain. Genome-wide association studies (GWAS) suggest that glutamatergic neurotransmission and NMDA receptor-mediated synaptic plasticity is important for body weight homeostasis1. Here, we report the engineering and preclinical development of a first-in-class bimodal molecule that integrates NMDA receptor antagonism with glucagon-like peptide-1 (GLP-1) receptor agonism to effectively reverse obesity, hyperglycemia, and dyslipidemia in rodent models of metabolic disease. We demonstrate that GLP-1-directed delivery of the NMDA receptor antagonist MK-801 affects NMDA receptor-mediated synaptic plasticity in the hypothalamus. Importantly, peptide-targeting of MK-801 specifically to GLP-1 receptor-expressing brain regions circumvent adverse physiological and behavioral effects associated with MK-801 monotherapy. In sum, our approach demonstrates the feasibility of cell specific ionotropic receptor-modulation via peptide targeting and highlights the therapeutic potential of unimolecular mixed GLP-1 receptor agonism and NMDA receptor antagonism for obesity treatment.
2024-04-26 | PXD045816 | Pride
Project description:Defining the molecular phenotype of single cells in-situ is essential for understanding tissue heterogeneity in health and disease. Powerful imaging technologies have recently been joined by spatial omics technologies, promising unparalleled insights into the molecular landscape of biological samples. One approach involves laser microdissection in combination with membrane glass slides for the isolation of single cells from specific anatomical regions for further analysis by spatial omics. However, so far this is not fully compatible with automated staining platforms and routine histology procedures such as heat-induced epitope retrieval, limiting reproducibility, throughput and integration of advanced staining procedures. This study describes a robust workflow for routine use of glass membrane slides, allowing precise extraction of tissue in combination with automated and multicolor immunofluorescence staining. The key advance is the addition of glycerol to standard heat-induced epitope retrieval protocol, preventing membrane distortion while preserving antigen retrieval properties. Importantly, we show that glycerol is fully compatible with mass-spectrometry based proteomics and does not affect proteome depth or quality. Further, we enable single focal plane imaging by removing remaining trapped air pockets with an incision. We demonstrate our workflow using the recently introduced Deep Visual Proteomics technology on the single-cell type analysis of adjacent suprabasal and basal keratinocytes of human skin. Our protocol extends the utility of membrane glass slides and enables much more robust integration with routine histology procedures, high-throughput multiplexed imaging and sophisticated downstream spatial omics technologies.
2023-10-24 | PXD040281 | Pride
Project description:Although current mass spectrometry (MS)-based proteomics identifies and quantifies thousands of proteins and (modified) peptides, only a minority of them are subjected to in-depth downstream analysis. With the advent of automated processing workflows, biologically or clinically important results within a study are rarely validated by visualization of the underlying raw information. Although several tools for this are in principle available, they are often not integrated into the overall analysis nor readily extendable with new approaches. To remedy this, we developed AlphaViz, an open-source Python package to superimpose output from common analysis workflows on the raw data for quick and easy visualization and validation of protein and peptide identifications. AlphaViz takes advantage of recent breakthroughs in the deep learning-assisted prediction of experimental peptide properties to allow manual assessment of the expected and measured peptide result deviation. We focused on the visualization of the 4-dimensional data cuboid provided by Bruker TimsTOF instruments, where the ion mobility dimension, besides intensity and retention time, can be predicted and used for verification. We illustrate how AlphaViz can quickly validate or invalidate peptide identifications regardless of the score given to them by automated workflows. Furthermore, we provide a ‘predict mode’ that can locate peptides present in the raw data but not reported by the search engine. This is illustrated with dilution series and the recovery of missing values from experimental replicates. Applied to phosphoproteomics of the EGF-signaling pathway, we show how key signaling nodes can be validated to enhance confidence for downstream interpretation or follow-up experiments. AlphaViz follows accepted standards for open-source software development, including extensive documentation, testing and continuous integration. It features an easy-to-install graphical user interface for end-users and a modular Python package for bioinformaticians. We hope that AlphaViz can help to make validation of critical proteomics results a standard feature in MS-based proteomics.
2022-07-11 | PXD034223 | Pride