MALDI-imaging-guided transcriptomics
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PROVIDER: PRJEB69276 | ENA |
REPOSITORIES: ENA
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Project description:MALDI-imaging-guided transcriptomics
| PRJEB56461 | ENA
Project description:Autosomal recessive polycystic kidney disease is a severe, monogenetically inherited kidney and liver disease and PCK rats carrying the orthologous mutant gene serve as a model of human disease. We combined selective MALDI imaging of sulfated kidney lipids and Fisher discriminant analysis of imaging data sets for identification of candidate lipid markers of progressive disease in PCK rats. Our study highlights strong increases in lower mass lipids as main classifiers of cystic disease. Structure determination by high resolution mass spectrometry identifies these altered lipids as taurine-conjugated bile acids. Beside increased levels of serum-cholesterol these sulfated lipids are selectively elevated in the PCK rat model but not in models of related hepatorenal fibrocystic diseases suggesting that they be molecular markers of the disease. Genome-scale gene expression profiling of PCK and SD livers as control was performed to attempt elucidation of some of the underlying mechanisms leading to increases of cholesterol and taurine-conjugated bile acids in the PCK rat. Several pathways were found to be changed in cystic livers with up regulation or down regulation of important gene sets. Enhanced expression of steroid biosynthesis genes might result in the observed increased levels of cholesterol. In contrast, primary bile acid biosynthesis was found to be down regulated in diseased livers. These findings might be explained by compensatory mechanisms of liver metabolism to reduce toxic levels of accumulated bile acids. Snap-frozen liver tissue of 10 week old rats were subjected for RNA extraction and hybridization on Affymetrix microarrays to perform genome-scale gene expression profiling of n = 6 diseased PCK and n = 6 Sprague Dawley rat livers as control.
2013-12-01 | E-GEOD-48357 | biostudies-arrayexpress
Project description:The full complement of molecular pathways contributing to Parkinson’s disease (PD) pathogenesis remains unknown. Here, to address this issue, we began by using a high-resolution variant of functional magnetic resonance imaging (fMRI) to pinpoint brainstem regions differentially affected by, and resistant to, the disease. Then, relying on the imaging information as a guide, we profiled gene expression levels of postmortem brain samples and used a factorial statistical model to identify a disease related decrease in the expression of the polyamine enzyme spermidine/spermine N1-acetyltransferase 1 (SAT1). Next, a series of studies were performed to confirm the pathogenic relevance of this finding. First, to test for a causal link between polyamines and α-synuclein toxicity, we investigated a yeast model expressing α-synuclein. Polyamines were found to enhance the toxicity of α-synuclein, and an unbiased genome-wide screen for modifiers of α-synuclein toxicity identified Tpo4, a member of a family of proteins responsible for polyamine transport. Second, to test for a causal link between SAT1 activity and PD histopathology we investigated a mouse model expressing α-synuclein. DENSPM (N1, N11-diethylnorspermine), a polyamine analog that increases SAT1 activity, was found to reduce PD histopathology, while Berenil (diminazene aceturate), a pharmacological agent that reduces SAT1 activity, worsened the histopathology. Third, we genotyped PD patients and controls and isolated a rare but novel variant in the SAT1 gene, although the functional significance of this genetic variant was not identified. Taken together, the results suggest that the polyamine pathway contributes to PD pathogenesis. Imaging-guided microarray In principle, gene expression profiling techniques like microarray are well suited to identify molecular pathways contributing to the pathogenesis of complex diseases. In practice, however, microarray applied to diseases of the brain present a number of analytic challenges. By identifying regions within the same brain structure that are differentially targeted by and resistant to a disease, imaging-guided microarray is an approach designed to address these limitations. Specifically, guided by the spatial information generated from high resolution functional imaging, a 2x2 factorial analysis-of-variance can be designed, including both within and between group factors, and this “double subtraction” model is effective in improving signal-to-noise in a microarray experiment. Relying on imaging findings, we harvested the DMNV from 6 postmortem brains with evidence of PD and from 5 control brains. The postmortem PD cases were evaluated for pathological changes (Lewy body-containing neurons and Lewy neurites evidenced with antibodies directed against α-synuclein aggregates) that matched the pattern proposed by Braak. We relied on the imaging results to identify a neighboring medullary region relatively unaffected by the disease to be used as a within-brain control. We decided on the inferior olivary nucleus (ION), because it is histologically identifiable, and harvested the ION from each of the 6 PD cases and 5 controls. Microarray techniques were used to generate gene expression profiles for each of the 22 tissue samples. A repeated-measures 2x2 factorial ANOVA model constructed for the imaging study was applied to the expression dataset, in which expression levels from two regions of the medulla (DMNV vs. ION) were included as the first within group factor, diagnosis (PD vs. controls) was the between group factor, and age and sex were included as covariates. Based on current literature, one of the top hits (SAT1) was investigated further to determine if it played a role in PD pathogenesis.
2010-08-19 | E-GEOD-19587 | biostudies-arrayexpress
Project description:Highly specialized cells are fundamental for proper functioning of complex organs. Variations in cell-type specific gene expression and protein composition have been linked to a variety of diseases. Although single cell technologies have emerged as valuable tools to address this cellular heterogeneity, a majority of these workflows lack sufficient in situ resolution for functional classification of cells and are associated with extremely long analysis time, especially when it comes to in situ proteomics. In addition, lack of understanding of single cell dynamics within their native environment limits our ability to explore the altered physiology in disease development. This limitation is particularly relevant in the mammalian brain, where different cell types perform unique functions and exhibit varying sensitivities to insults. The hippocampus, a brain region crucial for learning and memory, is of particular interest due to its obvious involvement in various neurological disorders. Here, we present a combination of experimental and data integration approaches for investigation of cellular heterogeneity and functional disposition within the mouse brain hippocampus using MALDI Imaging mass spectrometry (MALDI-IMS) and shotgun proteomics (LC-MS/MS) coupled with laser-capture microdissection (LCM) along with spatial transcriptomics. Within the dentate gyrus granule cells we identified two proteomically distinct cellular subpopulations that are characterized by a substantial number of discriminative proteins. These cellular clusters contribute to the overall functionality of the dentate gyrus by regulating redox homeostasis, mitochondrial organization, RNA processing, and microtubule organization. Importantly, most of the identified proteins matched their transcripts, verifying the in situ protein identification and supporting their functional analyses. By combining high-throughput spatial proteomics with transcriptomics, our approach enables reliable near-single-cell scale identification of proteins and profiling of inter-cellular heterogeneity within similar cell-types in tissues. This methodology has the potential to be applied to different biological conditions and tissues, providing a deeper understanding of cellular subpopulations in situ.
2024-07-24 | GSE242688 | GEO
Project description:Autosomal recessive polycystic kidney disease is a severe, monogenetically inherited kidney and liver disease and PCK rats carrying the orthologous mutant gene serve as a model of human disease. We combined selective MALDI imaging of sulfated kidney lipids and Fisher discriminant analysis of imaging data sets for identification of candidate lipid markers of progressive disease in PCK rats. Our study highlights strong increases in lower mass lipids as main classifiers of cystic disease. Structure determination by high resolution mass spectrometry identifies these altered lipids as taurine-conjugated bile acids. Beside increased levels of serum-cholesterol these sulfated lipids are selectively elevated in the PCK rat model but not in models of related hepatorenal fibrocystic diseases suggesting that they be molecular markers of the disease. Genome-scale gene expression profiling of PCK and SD livers as control was performed to attempt elucidation of some of the underlying mechanisms leading to increases of cholesterol and taurine-conjugated bile acids in the PCK rat. Several pathways were found to be changed in cystic livers with up regulation or down regulation of important gene sets. Enhanced expression of steroid biosynthesis genes might result in the observed increased levels of cholesterol. In contrast, primary bile acid biosynthesis was found to be down regulated in diseased livers. These findings might be explained by compensatory mechanisms of liver metabolism to reduce toxic levels of accumulated bile acids.
2013-12-01 | GSE48357 | GEO
Project description:We developed and validated ‘HIT-MAP’ (High-resolution Informatics Toolbox in MALDI-MSI Proteomics), an open-source bioinformatics workflow using peptide mass fingerprint analysis and a dual scoring system to computationally assign peptide and protein annotations to high mass resolution MSI datasets, and generate customisable spatial distribution maps. The uploaded files are an example dataset for the HiTMaP proteomics search engine, designed for MALDI-imaging proteomics annotation. The example data files contain one bovine lens tissue section and one mouse brain tissue section. The ID folder contains the protein/peptide identification result for each tissue segment, and the summary folder contains the protein cluster images.
2021-05-17 | PXD025486 | Pride
Project description:MALDI imaging mass spectrometry (MALDI IMS) is a powerful tool for the visualization of proteins in tissues and has demonstrated considerable diagnostic and prognostic value. One main challenge is that the molecular identity of such potential biomarkers mostly remains unknown. We introduce a method that removes this issue by systematically identifying the proteins embedded in the MALDI matrix using a combination of bottom-up and top-down proteomics. The analyses of ten human tissues lead to the identification of 1,400 abundant and soluble proteins constituting the set of proteins detectable by MALDI IMS including >90% of all IMS biomarkers reported in the literature. Top-down analysis of the matrix proteome identified 124 mostly N- and C-terminally fragmented proteins indicating considerable protein processing activity in tissues. This work presents a generic method and near complete list of MALDI IMS biomarkers that will become a valuable resource for the IMS community. Detailed description of the bioinformatics pipeline can be found in pipeline.txt. Briefly, different Mascot Distiller, Mascot and Scaffold versions have been used for the bottom-up and top-down data.
2013-07-03 | PXD000125 | Pride
Project description:We present a spatial omics approach that merges and expands the capabilities of independently performedin situassays on a single tissue section. Our spatial multimodal analysis combines histology, mass spectrometry imaging, and spatial transcriptomics to facilitate precise measurements of mRNA transcripts and low-molecular weight metabolites across tissue regions. We demonstrate the potential of our method using murine and human brain samples in the context of dopamine and Parkinson’s disease.
2023-05-21 | GSE232910 | GEO
Project description:Maldi imaging with NEDC matrix of a rat brain tissue section. Image was acquired with 50 um resolution. Ion mobility seperation enabled. Negative ion mode.
2023-06-05 | MSV000092098 | MassIVE
Project description:Maldi imaging with NEDC matrix of a rat brain tissue section. Image was acquired with 50 um resolution. Ion mobility seperation enabled. Negative ion mode.
2023-06-05 | MSV000092098 | GNPS