Pathological microglia activation can promote neuroinflammation in many neurodegenerative diseases, and it has therefore emerged as a potential therapeutic target. Increasing evidence suggests ...alterations in lipid metabolism as modulators and indicators in microglia activation and its effector functions. Yet, how lipid dynamics in activated microglia is affected by inflammatory stimuli demands additional investigation to allow development of more effective therapies. Here, we report an extensive matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) whole cell fingerprinting workflow to investigate inflammation-associated lipid patterns in SIM-A9 microglial cells. By combining a platform of three synergistic MALDI MS technologies we could detect substantial differences in lipid profiles of lipopolysaccharide (LPS)- stimulated and unstimulated microglia-like cells leading to the identification of 21 potential inflammation-associated lipid markers. LPS-induced lipids in SIM-A9 microglial cells include phosphatidylcholines, lysophosphatidylcholines (LysoPC), sphingolipids, diacylglycerols and triacylglycerols. Moreover, MALDI MS-based cell lipid fingerprinting of LPS-stimulated SIM-A9 microglial cells pre-treated with the non-selective histone deacetylase inhibitor suberoylanilide hydroxamic acid revealed specific modulation of LPS-induced-glycerolipids and LysoPC(18:0) with a significant reduction of microglial inflammation response. Our study introduces MALDI MS as a complementary technology for fast and label-free investigation of stimulus-dependent changes in lipid patterns and their modulation by pharmaceutical agents.
MALDI mass spectrometry imaging (MSI) enables label-free, spatially resolved analysis of a wide range of analytes in tissue sections. Quantitative analysis of MSI datasets is typically performed on ...single pixels or manually assigned regions of interest (ROIs). However, many sparse, small objects such as Alzheimer’s disease (AD) brain deposits of amyloid peptides called plaques are neither single pixels nor ROIs. Here, we propose a new approach to facilitate the comparative computational evaluation of amyloid plaque-like objects by MSI: a fast PLAQUE PICKER tool that enables a statistical evaluation of heterogeneous amyloid peptide composition. Comparing two AD mouse models, APP NL-G-F and APP PS1, we identified distinct heterogeneous plaque populations in the NL-G-F model but only one class of plaques in the PS1 model. We propose quantitative metrics for the comparison of technical and biological MSI replicates. Furthermore, we reconstructed a high-accuracy 3D-model of amyloid plaques in a fully automated fashion, employing rigid and elastic MSI image registration using structured and plaque-unrelated reference ion images. Statistical single-plaque analysis in reconstructed 3D-MSI objects revealed the Aβ1–42Arc peptide to be located either in the core of larger plaques or in small plaques without colocalization of other Aβ isoforms. In 3D, a substantially larger number of small plaques were observed than that indicated by the 2D-MSI data, suggesting that quantitative analysis of molecularly diverse sparsely-distributed features may benefit from 3D-reconstruction. Data are available via ProteomeXchange with identifier PXD020824.
Complementary treatment possibilities for the therapy of cancer are increasing in demand due to the severe side effects of the standard cytostatics used in the first-line therapy. A common approach ...as a complementary treatment is the use of aqueous extracts of Viscum album L. (Santalaceace). The therapeutic activity of these extracts is attributed to Mistletoe lectins which are Ribosome-inactivating proteins type II. Besides these main constituents the extract of Viscum album L. comprises also a mixture of lipophilic ingredients like triterpene acids of the oleanane, lupane and ursane type. However, these constituents are not contained in commercially available aqueous extracts due to their high lipophilicity and insolubility in aqueous extraction media. To understand the impact of the extract ingredients in cancer therapy, the intracellular uptake of the mistletoe lectin I (ML) by cultured tumor cells was investigated in relation to the mistletoe triterpene acids, mainly oleanolic acid. Firstly, these hydrophobic triterpene acids were solubilized using cyclodextrins ("TT" extract). Afterwards, the uptake of either single compounds (isolated ML and the aqueous "viscum" extract) or in combination with the TT extract (ML+TT, viscumTT), was analyzed. The uptake of ML was studied inTHP-1-, HL-60-, 143B- and Ewing TC-71-cells and determined after 30, 60 and 120 minutes by an enzyme linked immunosorbent assay which quantifies the A-chain of the hololectin. It could be shown that the intracellular uptake after 120 minutes amounted to 20% in all cell lines after incubation with viscumTT. The studies further revealed that the uptake in THP-1-, HL-60- and Ewing TC-71-cells was independent of the addition of TT extract. Interestingly, the uptake of ML by 143B-cells could only be measured after addition of triterpenes pointing to resistance to mistletoe lectin.
Abstract
Summary
Python is the most commonly used language for deep learning (DL). Existing Python packages for mass spectrometry imaging (MSI) data are not optimized for DL tasks. We, therefore, ...introduce pyM2aia, a Python package for MSI data analysis with a focus on memory-efficient handling, processing and convenient data-access for DL applications. pyM2aia provides interfaces to its parent application M2aia, which offers interactive capabilities for exploring and annotating MSI data in imzML format. pyM2aia utilizes the image input and output routines, data formats, and processing functions of M2aia, ensures data interchangeability, and enables the writing of readable and easy-to-maintain DL pipelines by providing batch generators for typical MSI data access strategies. We showcase the package in several examples, including imzML metadata parsing, signal processing, ion-image generation, and, in particular, DL model training and inference for spectrum-wise approaches, ion-image-based approaches, and approaches that use spectral and spatial information simultaneously.
Availability and implementation
Python package, code and examples are available at (https://m2aia.github.io/m2aia)
Cerebral accumulation of amyloid-β (Aβ) initiates molecular and cellular cascades that lead to Alzheimer’s disease (AD). However, amyloid deposition does not invariably lead to dementia. ...Amyloid-positive but cognitively unaffected (AP-CU) individuals present widespread amyloid pathology, suggesting that molecular signatures more complex than the total amyloid burden are required to better differentiate AD from AP-CU cases. Motivated by the essential role of Aβ and the key lipid involvement in AD pathogenesis, we applied multimodal mass spectrometry imaging (MSI) and machine learning (ML) to investigate amyloid plaque heterogeneity, regarding Aβ and lipid composition, in AP-CU versus AD brain samples at the single-plaque level. Instead of focusing on a population mean, our analytical approach allowed the investigation of large populations of plaques at the single-plaque level. We found that different (sub)populations of amyloid plaques, differing in Aβ and lipid composition, coexist in the brain samples studied. The integration of MSI data with ML-based feature extraction further revealed that plaque-associated gangliosides GM2 and GM1, as well as Aβ1–38, but not Aβ1–42, are relevant differentiators between the investigated pathologies. The pinpointed differences may guide further fundamental research investigating the role of amyloid plaque heterogeneity in AD pathogenesis/progression and may provide molecular clues for further development of emerging immunotherapies to effectively target toxic amyloid assemblies in AD therapy. Our study exemplifies how an integrative analytical strategy facilitates the unraveling of complex biochemical phenomena, advancing our understanding of AD from an analytical perspective and offering potential avenues for the refinement of diagnostic tools.
Cell-based assays for compound screening and profiling are fundamentally important in life sciences, chemical biology and pharmaceutical research. Most cell assays measure the amount of a single ...reporter molecule or cellular endpoint, and require the use of fluorescence or other labeled materials. Consequently, there is high demand for label-free technologies that enable multiple biomolecules or endpoints to be measured simultaneously. Here, we describe how to develop, optimize and validate MALDI-TOF mass spectrometry (MS) cell assays that can be used to measure cellular uptake of transporter substrates, to monitor cellular drug target engagement or to discover cellular drug-response markers. In uptake assays, intracellular accumulation of a transporter substrate and its inhibition by test compounds is measured. In drug response assays, changes to multiple cellular metabolites or to abundant posttranslational protein modifications are monitored as reporters of drug activity. We detail a ten-part optimization protocol with every part taking 1-2 d that leads to a final 2 d optimized procedure, which includes cell treatment, transfer, MALDI MS-specific sample preparation, quantification using stable-isotope-labeled standards, MALDI-TOF MS data acquisition, data processing and analysis. Key considerations for validation and automation of MALDI-TOF MS cell assays are outlined. Overall, label-free MS cell-based assays offer speed, sensitivity, accuracy and versatility in drug research.
Familial Alzheimer's disease (FAD), caused by mutations in Presenilin (PSEN1/2) and Amyloid Precursor Protein (APP) genes, is associated with an early age at onset (AAO) of symptoms. AAO is ...relatively consistent within families and between carriers of the same mutations, but differs markedly between individuals carrying different mutations. Gaining a mechanistic understanding of why certain mutations manifest several decades earlier than others is extremely important in elucidating the foundations of pathogenesis and AAO. Pathogenic mutations affect the protease (PSEN/γ-secretase) and the substrate (APP) that generate amyloid β (Aβ) peptides. Altered Aβ metabolism has long been associated with AD pathogenesis, with absolute or relative increases in Aβ42 levels most commonly implicated in the disease development. However, analyses addressing the relationships between these Aβ42 increments and AAO are inconsistent. Here, we investigated this central aspect of AD pathophysiology via comprehensive analysis of 25 FAD-linked Aβ profiles. Hypothesis- and data-driven approaches demonstrate linear correlations between mutation-driven alterations in Aβ profiles and AAO. In addition, our studies show that the Aβ (37 + 38 + 40) / (42 + 43) ratio offers predictive value in the assessment of 'unclear' PSEN1 variants. Of note, the analysis of PSEN1 variants presenting additionally with spastic paraparesis, indicates that a different mechanism underlies the aetiology of this distinct clinical phenotype. This study thus delivers valuable assays for fundamental, clinical and genetic research as well as supports therapeutic interventions aimed at shifting Aβ profiles towards shorter Aβ peptides.
Sequential proteolysis of the amyloid precursor protein (APP) by γ‐secretases generates amyloid‐β (Aβ) peptides and defines the proportion of short‐to‐long Aβ peptides, which is tightly connected to ...Alzheimer's disease (AD) pathogenesis. Here, we study the mechanism that controls substrate processing by γ‐secretases and Aβ peptide length. We found that polar interactions established by the APPC99 ectodomain (ECD), involving but not limited to its juxtamembrane region, restrain both the extent and degree of γ‐secretases processive cleavage by destabilizing enzyme–substrate interactions. We show that increasing hydrophobicity, via mutation or ligand binding, at APPC99‐ECD attenuates substrate‐driven product release and rescues the effects of Alzheimer's disease‐associated pathogenic γ‐secretase and APP variants on Aβ length. In addition, our study reveals that APPC99‐ECD facilitates the paradoxical production of longer Aβs caused by some γ‐secretase inhibitors, which act as high‐affinity competitors of the substrate. These findings assign a pivotal role to the substrate ECD in the sequential proteolysis by γ‐secretases and suggest it as a sweet spot for the potential design of APP‐targeting compounds selectively promoting its processing by these enzymes.
Synopsis
Sequential proteolysis of amyloid precursor protein (APP) by γ‐secretase generates various amyloid‐β (Aβ) peptides, whose length correlates with pathogenicity of Alzheimer's disease (AD)‐associated mutations. Here, the ectodomain of the APP substrate is found to define Aβ length by promoting product release and destabilizing enzyme–substrate interactions.
Polar residues in the APPC99 ectodomain (APPC99‐ECD) drive product release by destabilizing enzyme–substrate interactions.
Increased hydrophobicity in the substrate ECD increases both efficiency and extent of sequential γ‐secretase‐mediated proteolysis of APP and Notch.
γ‐Secretase inhibitors (GSIs) DAPT and semagacestat act as high‐affinity competitors of substrates.
GSI‐mediated displacement of partially digested Aβ peptides, facilitated by the APPC99‐ECD, explains paradoxical increases in longer Aβ peptides.
Mitigation of APPC99‐ECD‐driven product release rescues the increased production of longer Aβ peptides linked to pathogenic variants in γ‐secretase and APP.
How γ‐secretase cleaves and processes the amyloid precursor protein depends on the hydrophobicity of its ectodomain, with implications for disease mechanism and drug discovery.
Alzheimer's disease (AD) pathogenesis has been linked to the accumulation of longer, aggregation‐prone amyloid β (Aβ) peptides in the brain. Γ‐secretases generate Aβ peptides from the amyloid ...precursor protein (APP). Γ‐secretase modulators (GSMs) promote the generation of shorter, less‐amyloidogenic Aβs and have therapeutic potential. However, poorly defined drug–target interactions and mechanisms of action have hampered their therapeutic development. Here, we investigate the interactions between the imidazole‐based GSM and its target γ‐secretase—APP using experimental and in silico approaches. We map the GSM binding site to the enzyme–substrate interface, define a drug‐binding mode that is consistent with functional and structural data, and provide molecular insights into the underlying mechanisms of action. In this respect, our analyses show that occupancy of a γ‐secretase (sub)pocket, mediating binding of the modulator's imidazole moiety, is sufficient to trigger allosteric rearrangements in γ‐secretase as well as stabilize enzyme–substrate interactions. Together, these findings may facilitate the rational design of new modulators of γ‐secretase with improved pharmacological properties.
Synopsis
Modulators of γ‐secretase activity (GSMs) that shift amyloid‐β (Aβ) production towards the shorter non‐amyloidogenic peptides while sparing critical γ‐secretase‐mediated signalling cascades are promising agents in the fight against Alzheimer's disease. Here, insights into the underlying drug‐target interactions and GSM mode of action may help to overcome current limitations to their rational further therapeutic development.
The binding pocket of a potent imidazole‐based GSM (GSM III) maps towards the γ‐secretase‐amyloid precursor protein (APP) (enzyme‐substrate) interface.
The binding mode of GSM III at the γ‐secretase—APP interface reveals a dual mechanism of action, as activator and stabilizer of γ‐secretases.
Occupancy of a sub‐pocket in γ‐secretase is sufficient to allosterically activate γ‐secretase and to stabilize enzyme—substrate interactions.
This dual mode of action enhances the generation of short and non‐toxic Aβ peptides.
Insights into drug‐target interactions and mode of action of an imidazole‐based γ‐secretase modulator may facilitate rational design of next‐generation compounds for treatment of Alzheimer's disease.
Abstract
Background
Γ‐secretases are proteolytic switches at the membrane regulating multiple signaling cascades. Their dysfunction, resulting in enhanced generation of longer amyloid β (Aβ) peptides ...from the amyloid precursor protein (APP), leads to neurodegeneration in the context of Alzheimer’s disease (AD), while their inhibition causes neurodegenerative phenotypes in mice and cognitive worsening in AD patients treated with γ‐secretase inhibitors. The accumulation of Aβ in the brain is the earliest pathological hallmark of AD. Based on the proven affinity of Aβ peptides for γ‐secretases, we hypothesized that elevations in Aβ levels would promote an inhibitory‐feedback mechanism on γ‐secretases and impair downstream cell signaling events.
Method
We conducted rigorous kinetic analyses of γ‐secretase activity in the presence of a series of Aβ and p3 peptides, by quantifying the levels of intracellular domains generated from different γ‐secretase substrates in cell‐free assays. In addition, we determined the effects of these peptides on endogenous γ‐secretase activity in living neurons, using a ratiometric FRET‐based reporter and western blot analysis of the levels of immediate γ‐secretase substrates. Furthermore, we assessed the impact of Aβ and p3 peptides on γ‐secretase‐mediated, p75‐ and TrkA‐dependent downstream signaling via immunostaining for an apoptotic marker: cleaved caspase 3. Finally, we evaluated the impact of Aβ peptides on APP processing in synaptosome fractions derived from mouse brains.
Result
Our analyses showed that human Aβ42 inhibited γ‐secretase activity and accordingly caused accumulation of unprocessed γ‐secretase substrates in neuronal cells, i.e. CTFs of APP, p75 and pan‐cadherin. Remarkably, neither murine Aβ42 nor human p3 (17‐42) peptides exerted the inhibition. In TrkA signaling deficient PC12 cells and basal forebrain cholinergic neurons, Aβ1‐42‐mediated inhibition of γ‐secretase led to the accumulation of unprocessed p75‐CTFs and potentiated p75‐dependent cell death, mimicking the effects of γ‐secretase inhibitors.
Conclusion
We demonstrate that the pathologically relevant human Aβ1‐42 exerts product feedback inhibition on γ‐secretases, leading to dysregulation of downstream cellular signaling. These findings provide a novel conceptual framework for investigations of Aβ toxicity in the context of γ‐secretase‐dependent homeostatic signaling and raise the possibility that Aβ42‐mediated inactivation of these enzymes contributes to AD development.
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