Integrative Single-Plaque Analysis Reveals Signature Aß and Lipid Profiles in the Alzheimer's Brain.

Cerebral accumulation of amyloid-ß (Aß) 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 Aß 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 Aß 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 Aß 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 Aß1-38, but not Aß1-42, 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.

pyM2aia: Python interface for mass spectrometry imaging with focus on deep learning.

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).

APP substrate ectodomain defines amyloid-ß peptide length by restraining γ-secretase processivity and facilitating product release.

Sequential proteolysis of the amyloid precursor protein (APP) by γ-secretases generates amyloid-ß (Aß) peptides and defines the proportion of short-to-long Aß peptides, which is tightly connected to Alzheimer's disease (AD) pathogenesis. Here, we study the mechanism that controls substrate processing by γ-secretases and Aß 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 Aß length. In addition, our study reveals that APPC99 -ECD facilitates the paradoxical production of longer Aßs 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.

Alzheimer's disease linked Aß42 exerts product feedback inhibition on γ-secretase impairing downstream cell signaling.

Amyloid ß (Aß) peptides accumulating in the brain are proposed to trigger Alzheimer's disease (AD). However, molecular cascades underlying their toxicity are poorly defined. Here, we explored a novel hypothesis for Aß42 toxicity that arises from its proven affinity for γ-secretases. We hypothesized that the reported increases in Aß42, particularly in the endolysosomal compartment, promote the establishment of a product feedback inhibitory mechanism on γ-secretases, and thereby impair downstream signaling events. We show that human Aß42 peptides, but neither murine Aß42 nor human Aß17-42 (p3), inhibit γ-secretases and trigger accumulation of unprocessed substrates in neurons, including C-terminal fragments (CTFs) of APP, p75 and pan-cadherin. Moreover, Aß42 treatment dysregulated cellular homeostasis, as shown by the induction of p75-dependent neuronal death in two distinct cellular systems. Our findings raise the possibility that pathological elevations in Aß42 contribute to cellular toxicity via the γ-secretase inhibition, and provide a novel conceptual framework to address Aß toxicity in the context of γ-secretase-dependent homeostatic signaling.

Enzyme-substrate interface targeting by imidazole-based γ-secretase modulators activates γ-secretase and stabilizes its interaction with APP.

Alzheimer's disease (AD) pathogenesis has been linked to the accumulation of longer, aggregation-prone amyloid ß (Aß) peptides in the brain. Γ-secretases generate Aß peptides from the amyloid precursor protein (APP). Γ-secretase modulators (GSMs) promote the generation of shorter, less-amyloidogenic Aßs 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.

Aß profiles generated by Alzheimer's disease causing PSEN1 variants determine the pathogenicity of the mutation and predict age at disease onset.

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 ß (Aß) peptides. Altered Aß metabolism has long been associated with AD pathogenesis, with absolute or relative increases in Aß42 levels most commonly implicated in the disease development. However, analyses addressing the relationships between these Aß42 increments and AAO are inconsistent. Here, we investigated this central aspect of AD pathophysiology via comprehensive analysis of 25 FAD-linked Aß profiles. Hypothesis- and data-driven approaches demonstrate linear correlations between mutation-driven alterations in Aß profiles and AAO. In addition, our studies show that the Aß (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 Aß profiles towards shorter Aß peptides.

LPS-induced lipid alterations in microglia revealed by MALDI mass spectrometry-based cell fingerprinting in neuroinflammation studies.

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.

Label-free cell assays to determine compound uptake or drug action using MALDI-TOF mass spectrometry.

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.

M2aia-Interactive, fast, and memory-efficient analysis of 2D and 3D multi-modal mass spectrometry imaging data.

BACKGROUND: Mass spectrometry imaging (MSI) is a label-free analysis method for resolving bio-molecules or pharmaceuticals in the spatial domain. It offers unique perspectives for the examination of entire organs or other tissue specimens. Owing to increasing capabilities of modern MSI devices, the use of 3D and multi-modal MSI becomes feasible in routine applications-resulting in hundreds of gigabytes of data. To fully leverage such MSI acquisitions, interactive tools for 3D image reconstruction, visualization, and analysis are required, which preferably should be open-source to allow scientists to develop custom extensions. FINDINGS: We introduce M2aia (MSI applications for interactive analysis in MITK), a software tool providing interactive and memory-efficient data access and signal processing of multiple large MSI datasets stored in imzML format. M2aia extends MITK, a popular open-source tool in medical image processing. Besides the steps of a typical signal processing workflow, M2aia offers fast visual interaction, image segmentation, deformable 3D image reconstruction, and multi-modal registration. A unique feature is that fused data with individual mass axes can be visualized in a shared coordinate system. We demonstrate features of M2aia by reanalyzing an N-glycan mouse kidney dataset and 3D reconstruction and multi-modal image registration of a lipid and peptide dataset of a mouse brain, which we make publicly available. CONCLUSIONS: To our knowledge, M2aia is the first extensible open-source application that enables a fast, user-friendly, and interactive exploration of large datasets. M2aia is applicable to a wide range of MSI analysis tasks.

Following spatial Aß aggregation dynamics in evolving Alzheimer's disease pathology by imaging stable isotope labeling kinetics.

ß-Amyloid (Aß) plaque formation is the major pathological hallmark of Alzheimer's disease (AD) and constitutes a potentially critical, early inducer driving AD pathogenesis as it precedes other pathological events and cognitive symptoms by decades. It is therefore critical to understand how Aß pathology is initiated and where and when distinct Aß species aggregate. Here, we used metabolic isotope labeling in APPNL-G-F knock-in mice together with mass spectrometry imaging to monitor the earliest seeds of Aß deposition through ongoing plaque development. This allowed visualizing Aß aggregation dynamics within single plaques across different brain regions. We show that formation of structurally distinct plaques is associated with differential Aß peptide deposition. Specifically, Aß1-42 is forming an initial core structure followed by radial outgrowth and late secretion and deposition of Aß1-38. These data describe a detailed picture of the earliest events of precipitating amyloid pathology at scales not previously possible.

Computational Analysis of Alzheimer Amyloid Plaque Composition in 2D- and Elastically Reconstructed 3D-MALDI MS Images.

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 Aß1-42Arc peptide to be located either in the core of larger plaques or in small plaques without colocalization of other Aß 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.

Direct Automated MALDI Mass Spectrometry Analysis of Cellular Transporter Function: Inhibition of OATP2B1 Uptake by 294 Drugs.

OATP2B1, a member of the solute carrier (SLC) transporter family, is an important mechanism of substrate drug uptake in the intestine and liver and therefore a determinant of clinical pharmacokinetics and site of drug-drug interactions. Other SLC transporters have emerged as pharmacology targets. Studies of SLC transporter uptake to-date relied on radioisotope- or fluorescence-labeled reagents or low-throughput quantification of unlabeled compounds in cell lysate. In this study, we developed a cell-based MALDI MS workflow for investigation of OATP2B1 cellular uptake by optimizing the substrate, matrix, matrix-analyte ratio, and matrix application and normalization method. This workflow was automated and applied to characterize substrate transport kinetics and to test 294 top-marketed drugs for OATP2B1 inhibition and quantify inhibitory potencies necessary for extrapolation of clinical drug-drug interaction potential. Intra-assay reproducibility of this MALDI MS method was high (CV < 10%), and results agreed well (83% overlap) with previously published radioisotope assay data. Our results indicate that fast and robust MALDI MS cellular assays could emerge as a high-throughput label-free alternative for direct assessment of drug transporter function in DDIs and toxicities as well as enable drug discovery for transporters as pharmacology targets.

Impact of Mistletoe Triterpene Acids on the Uptake of Mistletoe Lectin by Cultured Tumor Cells.

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.