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Hopf, C.

Publications and source records attributed to Hopf, C..

At least 19 recordsLinked to original sources

O-mannosylation of fibrocystin and fibrocystin-L expands TMEM260 sequon selectivity and provides a potential link to the renal and auditory phenotypes of SHDRA

Protein O-mannosylation in the endoplasmic reticulum (ER) regulates the maturation and function of extracellular proteins, yet the substrate spectrum and biological functions of individual O-mannosyltransferases remain incompletely understood. TMEM260 is an ER-resident O-mannosyltransferase that modifies immunoglobulin-like, plexins, transcription factors (IPT) domains. Here, we identify fibrocystin and fibrocystin-L, encoded by PKHD1 and PKHD1L1, respectively, as novel TMEM260-mediated O-mannosylated proteins. By combining screening of human proteomic datasets with mass spectrometry-based analysis of IPT domains expressed in TMEM260-deficient HEK293 cells, we demonstrate that multiple IPT domains of fibrocystin and fibrocystin-L are modified by TMEM260. Our findings expand the known substrate requirements of TMEM260 by revealing tolerance of substantial sequon variation and demonstrating serine as an alternative acceptor residue within IPT domains. In humans, loss-of-function variants in TMEM260 cause structural heart defects and renal anomalies (SHDRA) syndrome, whereas pathogenic variants in fibrocystin cause autosomal recessive polycystic kidney disease (ARPKD). Notably, patients with SHDRA and ARPKD share overlapping renal phenotypes, suggesting that impaired TMEM260 function may phenocopy aspects of fibrocystin-associated diseases. Given that fibrocystin is a substrate protein for TMEM260-mediated O-mannosylation, these findings raise the possibility that functional impairment of TMEM260 causes aberrant O-mannosylation of fibrocystin. Thereby fibrocystin function might be compromised leading to the renal phenotype observed in patients with TMEM260 mutations. To directly assess the functional relevance of this modification, we expressed recombinant fibrocystin fragments in TMEM260-deficient cells complemented with either wild-type TMEM260 or a catalytically inactive TMEM260 mutant. Further, we investigate the O-mannosylation of the threonine residue directly C-terminal to the ARPKD-associated patient mutation L1407R. Strikingly, substitution of leucine L1407 by the patient-associated arginine residue, completely abolished O-mannosylation of the adjacent threonine, demonstrating that this disease-associated mutation directly disrupts a TMEM260-dependent O-mannosylation site. Together, our findings establish fibrocystin and fibrocystin-L as TMEM260-dependent O-mannosylated proteins and reveal a potential molecular mechanism linking defective TMEM260-mediated O-mannosylation to the renal phenotype of SHDRA, which overlaps with PKHD1-associated ARPKD.

biochemistry↗

Decoding acute neuroinflammatory states from the 3D architecture of in vitro microglia

Microglia, core brain immune defenders, rapidly polarize into pro- or anti-inflammatory states that shape neuronal survival during acute brain inflammation. Yet, how these inflammatory states are encoded at the native cellular level remains unclear. While microglial states associate with specific molecular and organelle markers, it is unknown whether their cellular architecture integrates robust metabolic and structural features. Here, we quantitatively decode inflammatory states from the 3D architecture of individual in vitro mouse microglia (BV-2). Using soft X-ray tomography on established BV-2 polarization, we identify coordinated intracellular organization distinguishing homeostatic, pro-inflammatory, and anti-inflammatory cells, including characteristic lipid droplet-endosome architectures. We further link lipid-endosome reorganization with mTORC1 pathway, by functionally implicating sestrin-2 in promoting anti-inflammation. Finally, we resolve the time-dependent remodeling of lipid droplet 3D profiles by their distinct lipidomic composition across inflammatory states. Overall, our work enables deciphering microglia states in disease-relevant models, with potential to ultimately understand brain immunity.

cell biology↗

PEG-free, Triphosphate-Stabilized LNPs Enable Potent RNA Delivery

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/695515v2_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@d919d8org.highwire.dtl.DTLVardef@12fe9aforg.highwire.dtl.DTLVardef@96e2d2org.highwire.dtl.DTLVardef@54f73_HPS_FORMAT_FIGEXP M_FIG C_FIG Polyethylene glycol (PEG)-lipids have long enabled lipid nanoparticle (LNP) formulations by providing steric stabilization and prolonged circulation. However, anti-PEG immune responses may impede repeated systemic dosing in mRNA therapeutics due to the phenomenon known as accelerated blood clearance (ABC). Here, we introduce a PEG-free, polyanionic alternative in which sodium triphosphate (3P) electrostatically associates with ionizable surface lipids, conferring long-term colloidal stability through charge repulsion rather than steric shielding. 3P-LNPs maintained size uniformity, morphology, and mRNA integrity for over nine months at 4 {degrees}C. In a proof-of-concept study involving a single intravenous injection of LNPs in mice carrying a luciferase and a GFP transgene, early expression was approximately two-fold higher compared to PEG-LNPs, while expression levels at 24 hours and hepatic tolerability remained comparable. Serum enzyme and cytokine profiles indicated no necrosis or inflammation. These findings establish 3P-LNPs as a stable, biocompatible platform free of PEG, with potential for repeat systemic mRNA administration while avoiding PEG-related effects.

biochemistry↗

A sulfatide-centered ultra-high resolution magnetic resonance MALDI imaging benchmark dataset for MS1-based lipid annotation tools

Spatial omics techniques are indispensable for studying complex biological systems and for the discovery of spatial biomarkers. While several current matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) instruments are capable of localizing numerous metabolites at high spatial and spectral resolution, the majority of MSI data is acquired at the MS1 level only. Assigning molecular identities based on MS1 data presents significant analytical and computational challenges, as the inherent limitations of MS1 data preclude confident annotations beyond the sum formula level. To enable future advancements of computational lipid annotation tools, well-characterized benchmark - or ground truth - datasets are crucial, which exceed the scope of synthetic data or data derived from mimetic tissue models. To this end, we provide two sulfatide-centered, biology-driven magnetic resonance MSI (MR-MSI) datasets at different mass resolving powers that characterize lipids in a mouse model of human metachromatic dystrophy. This data includes an ultra-high-resolution (R [~]1,230,000) quantum cascade laser mid-infrared imaging-guided MR-MSI dataset that enables isotopic fine structure analysis and therefore enhances the level of confidence substantially. To highlight the usefulness of the data, we compared 118 manual sulfatide annotations with the number of decoy database-controlled sulfatide annotations performed in Metaspace (67 at FDR < 10%). Overall, our datasets can be used to benchmark annotation algorithms, validate spatial biomarker discovery pipelines, and serve as a reference for future studies that explore sulfatide metabolism and its spatial regulation.

biochemistry↗

Improving MALDI Mass Spectrometry Imaging Performance: Low-Temperature Thermal Evaporation for Controlled Matrix Deposition and Improved Image Quality

The deposition of matrix compounds significantly influences the effectiveness of matrix-assisted laser desorption/ionization (MALDI) Mass Spectrometry Imaging (MSI) experiments, impacting sensitivity, spatial resolution, and reproducibility. Dry deposition methods offer advantages by producing homogeneous matrix layers and minimizing analyte delocalization without the use of solvents. However, refining these techniques to precisely control matrix thickness, minimize heating temperatures, and ensure high-purity matrix layers is crucial for optimizing MALDI-MSI performance. Here, we present a novel approach utilizing low-temperature thermal evaporation (LTE) for organic matrix deposition under reduced vacuum pressure. Our method allows for reproducible control of matrix layer thickness, as demonstrated by linear calibration for two organic matrices, 2,5-dihydroxybenzoic acid (DHB), and 1,5-Diaminonaphthalene (DAN). The environmental scanning electron microscopy images reveal a uniform distribution of small-sized matrix crystals, consistently on the submicrometer scale, across tissue slides following LTE deposition. Remarkably, LTE serves as an additional purification step for organic matrices, producing very pure layers irrespective of initial matrix purity. Furthermore, stability assessment of MALDI-MSI data from mouse brain sections coated with LTE-deposited DHB or DAN matrix indicates minimal impact on ionization efficiency, signal intensity, and image quality even after storage at - 80{degrees}C for two weeks, underscoring the robustness of LTE-deposited matrices for MSI applications. Comparative analysis with the spray-coating method highlights several advantages of LTE deposition, including enhanced ionization, reduced analyte diffusion, and improved MSI image quality.

bioengineering↗

Exploring the Abeta Plaque Microenvironment in Alzheimer's Disease Mice by Multimodal Lipid-Protein-Histology Imaging on a Benchtop Mass Spectrometer

Amyloid-{beta} (A{beta}) plaque deposits in the brain are a hallmark of Alzheimers disease (AD) neuropathology. Plaques consist of complex mixtures of peptides like A{beta}1-42, characteristic lipids such as gangliosides, and they are targeted by reactive microglia and astrocytes. In pharmaceutical research and development it is therefore a formidable challenge to contextualize different biomolecular classes and cell types of the A{beta} plaque microenvironment in a coherent experimental workflow on a single tissue section and on a benchtop imaging reader. Here, we developed such a workflow that combines lipid MALDI mass spectrometry imaging using a vacuum-stable matrix with histopathology stains and with MALDI HiPLEX-immunohistochemistry of plaques and multiple protein markers on a bench-top imaging mass spectrometer. The three data layers consisting of lipid, protein markers, and histology can be co-registered and evaluated together. Multimodal data analysis suggests extensive co-localization of A{beta} plaques with the peptide precursor protein, with a defined subset of lipids and with reactive glia cells on a single brain section of APP/PS1 AD model mice. Plaque-associated lipids like ganglioside GM2 and phosphatidylinositol PI38:4 isoforms were readily identified using the tandem MS-capabilities of the mass spectrometer. Taken together, our data suggests that complex pathology involving multiple lipids, proteins and cell types can be interrogated by this spatial multiomics workflow on an easy-to-use benchtop mass spectrometer.

neuroscience↗

Fast Single-Cell MALDI Imaging of Low-Mass Metabolites Reveals Cellular Activation Markers

Single-cell MALDI mass spectrometry imaging (MSI) of lipids and metabolites >200 Da has recently come to the forefront of biomedical research and chemical biology, but fast metabolome-preserving methods without paraformaldehyde fixation for analysis of low mass, hydrophilic metabolites (<200 Da) in large cell populations are lacking. Introducing giant unilamellar vesicles (GUVs) as MSI ground truth for cell-sized objects and Monte Carlo reference-based consensus clustering for data-dependent identification of cell subpopulations. The PRISM-MS (PRescan Imaging for Small Molecule - Mass Spectrometry) dual-scan MSI workflow is presented, enabling space-efficient and therefore faster lipid analysis in single GUVs and cells. Beyond lipids, PRISM-MS enables MSI and on-cell MS2-based identification of low-mass metabolites like amino acids or Krebs cycle intermediates involved in stimulus-dependent cell activation. The utility of PRISM-MS is demonstrated through the characterization of complex metabolome changes in lipopolysaccharide (LPS)-stimulated microglial cells and human-induced pluripotent stem cell-derived microglia. Translation of single cell results to endogenous microglia in organotypic hippocampal slice cultures indicates that LPS-activation involves changes of the itaconate-to-taurine ratio and alterations in neuron-to-glia glutamine-glutamate shuttling. The data suggests that PRISM-MS could serve as a standard method in single cell metabolomics, given its capability to characterize larger cell populations and low-mass metabolites.

bioinformatics↗

Label-free Assessment of Complement-Dependent Cytotoxicity of Therapeutic Antibodies via a Whole-Cell MALDI Mass Spectrometry Bioassay

Potency assessment of monoclonal antibodies or corresponding biosimilars in cell-based assays is an essential prerequisite in biopharmaceutical research and development. However, cellular bioassays are still subject to limitations in sample throughput, speed, and often need costly reagents or labels as they are based on an indirect readout by luminescence or fluorescence. In contrast, whole-cell Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) Mass Spectrometry (MS) has emerged as a direct, fast and label-free technology for functional drug screening being able to unravel the molecular complexity of cellular response to pharmaceutical reagents. However, this approach has not yet been used for cellular testing of biologicals. In this study, we have conceived, developed and bench-marked a label-free MALDI-MS based cell bioassay workflow for the functional assessment of complement-dependent cytotoxicity (CDC) of Rituximab antibody. By computational evaluation of response profiles followed by subsequent m/z feature annotation via fragmentation analysis and trapped ion mobility MS, we identified adenosine triphosphate and glutathione as readily MS-assessable metabolite markers for CDC and demonstrate that robust concentration-response characteristics can be obtained by MALDI-TOF MS. Statistical assay performance indicators suggest that whole-cell MALDI-TOF MS could complement the toolbox for functional cellular testing of biopharmaceuticals.

biochemistry↗

Large-Scale Evaluation of Spatial Metabolomics Protocols and Technologies

Spatial metabolomics using imaging mass spectrometry (MS) enables untargeted and label-free metabolite mapping in biological samples. Despite the range of available imaging MS protocols and technologies, our understanding of metabolite detection under specific conditions is limited due to sparse empirical data and predictive theories. Consequently, challenges persist in designing new experiments, and accurately annotating and interpreting data. In this study, we systematically measured the detectability of 172 biologically-relevant metabolites across common imaging MS protocols using custom reference samples. We evaluated 24 MALDI-imaging MS protocols for untargeted metabolomics, and demonstrated the applicability of our findings to complex biological samples through comparison with animal tissue data. We showcased the potential for extending our results to further analytes by predicting metabolite detectability based on molecular properties. Additionally, our interlaboratory comparison of 10 imaging MS technologies, including MALDI, DESI, and IR-MALDESI, showed extensive metabolite coverage and comparable results, underscoring the broad applicability of our findings within the imaging MS community. We share our results and data through a new interactive web application integrated with METASPACE. This resource offers an extensive catalogue of detectable metabolite ions, facilitating protocol selection, supporting data annotation, and benefiting future untargeted spatial metabolomics studies.

systems biology↗

Deep MALDI-MS Spatial Omics guided by Quantum Cascade Laser Mid-infrared Imaging Microscopy

In spatial omics, highly confident molecular identifications are indispensable for the investigation of complex biology and for spatial biomarker discovery. However, current mass spectrometry (MS)-based spatial omics must compromise between data acquisition speed and biochemical profiling depth, thus often leading to only "putative" molecular identifications. Here, we introduce fast quantum cascade laser mid-infrared imaging microscopy to guide MS imaging to confined tissue areas of high interest, e.g., multicellular spheroid cores or kidney glomeruli, for spatial lipidomics profiling at maximized analytical depth utilizing magnetic resonance-MS imaging at >106 resolution or prm-PASEF-MS2 fragmentation imaging. Instigating selective sulfatide accumulation in arylsulfatase A-deficient mice as ground truth concept, we demonstrate that deep QCL-infrared-guided on-tissue spatial omics unequivocally identifies 120 sulfatides. This approach enables identifications of odd-chain sulfatides and studies of structure-ion mobility-relationships that provide chemical rationales for improvements to current ion mobility prediction algorithms. Workflows and data processing tools are provided as community resources.

biochemistry↗

APP substrate ectodomain defines A beta length by restraining gamma-secretase processivity and facilitating product release

Sequential proteolysis of the amyloid precursor protein (APP) by {gamma}-secretases (GSECs) generates amyloid-{beta} (A{beta}) and defines the proportion of short-to-long A{beta} peptides, which is tightly connected to Alzheimers disease (AD) pathogenesis. Here, we study the mechanism controlling substrate processing by GSECs and defining product 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 GSEC processive cleavage by destabilizing enzyme-substrate (E-S) interactions. We show that increasing hydrophobicity at APPC99-ECD - due to mutation or ligand binding - attenuates this substrate-driven product release mechanism, and rescues the effects that AD pathogenic variants exert on A{beta} profiles. In addition, our study reveals that APPC99-ECD facilitates the paradoxical production of longer A{beta}s caused by some GSEC inhibitors that act as high-affinity competitors to the substrate. These findings assign a pivotal role to the substrate ECD in the sequential proteolysis by GSEC and suggest it as a sweet spot for the potential design of APP targeting compounds selectively promoting its processing by GSEC.

biochemistry↗

Alzheimer's disease linked Aβ42 exerts product feedback inhibition on γsecretase impairing downstream cell signaling

Amyloid {beta} (A{beta}) peptides accumulating in the brain are proposed to trigger Alzheimers disease (AD). However, molecular cascades underlying their toxicity are poorly defined. Here, we explored a novel hypothesis for A{beta}42 toxicity that arises from its proven affinity for {gamma}-secretases. We hypothesized that the reported increases in A{beta}42, particularly in the endolysosomal compartment, promote the establishment of a product feedback inhibitory mechanism on {gamma}-secretases, and thereby impair downstream signaling events. We show that human A{beta}42 peptides, but neither murine A{beta}42 nor human A{beta}17-42 (p3), inhibit {gamma}-secretases and trigger accumulation of unprocessed substrates in neurons, including C-terminal fragments (CTFs) of APP, p75 and pan-cadherin. Moreover, A{beta}42 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 A{beta}42 contribute to cellular toxicity via the {gamma}-secretase inhibition, and provide a novel conceptual framework to address A{beta} toxicity in the context of {gamma}-secretase-dependent homeostatic signaling.

biochemistry↗

Spatial omics imaging of fresh-frozen tissue and routine FFPE histopathology on a single cancer needle core biopsy: freezing device and multimodal workflow

Complex molecular alterations underlying cancer pathophysiology are intensely studied with omics methods using bulk tissue extracts. For spatially resolved tissue diagnostics using needle biopsy cores, however, histopathological analysis using stained FFPE tissue and immuno-histochemistry (IHC) of few marker proteins is currently the main clinical focus. Today, spatial omics imaging using MSI or IRI are emerging diagnostic technologies for identification and classification of various cancer types. However, to conserve tissue-specific metabolomic states, fast, reliable and precise methods for preparation of fresh-frozen (FF) tissue sections are crucial. Such methods are often incompatible with clinical practice, since spatial metabolomics and routine histopathology of needle biopsies currently require two biopsies for FF and FFPE sampling, respectively. Therefore, we developed a device and corresponding laboratory and computational workflows for multimodal spatial omics analysis of fresh-frozen, longitudinally sectioned needle biopsies to accompany standard FFPE histopathology on the same biopsy core. As proof-of-concept, we analyzed surgical human liver cancer specimen by IRI and MSI with precise co-registration and, following FFPE processing, by sequential clinical pathology analysis on the same biopsy core. This workflow allowed spatial comparison between different spectral profiles and alterations in tissue histology, as well as direct comparison to histological diagnosis without the need of an extra biopsy. SIMPLE SUMMARYRoutine clinical approaches for cancer diagnosis demand fast, cost-efficient, and reliable methods, and their implementation within clinical settings. Currently, histopathology is the golden standard for tissue-based clinical diagnosis. Recently, spatially resolved molecular profiling techniques like mass spectrometry imaging (MSI) or infrared spectroscopy imaging (IRI) have increasingly contributed to clinical research, e.g., by differentiation of cancer subtypes using molecular fingerprints. However, adoption of the corresponding workflows in clinical routine remains challenging, especially for fresh-frozen tissue specimen. Here, we present a novel device based on 3D-printing technology, which facilitates sample preparation of needle biopsies for correlated clinical tissue analysis. It enables combination of MSI and IRI on fresh-frozen clinical samples with histopathological examination of the same needle core after formalin-fixation and paraffin-embedding (FFPE). This device and workflow can pave the way for a more profound understanding of biomolecular processes in cancer and, thus, aid more accurate diagnosis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=180 SRC="FIGDIR/small/528125v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@1da99aborg.highwire.dtl.DTLVardef@9ee706org.highwire.dtl.DTLVardef@5153daorg.highwire.dtl.DTLVardef@1581594_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Tryptophan stress activates EGFR-RAS-signaling to MTORC1 and p38/MAPK to sustain translation and AHR-dependent autophagy

Tumours face tryptophan (Trp) depletion, but the mechanisms sustaining protein biosynthesis under Trp stress remain unclear. We report that Trp stress increases the levels of the translation repressor EIF4EBP1. Yet, at the same time, EIF4EBP1 is selectively phosphorylated by the metabolic master regulator MTORC1 kinase, preventing EIF4EBP1 from inhibiting translation. MTORC1 activity under Trp stress is unexpected because the absence of amino acids is typically linked with MTORC1 inhibition. EIF4EBP1-sensitive translation in Trp starved cells is sustained by EGFR and RAS signalling to MTORC1. Via this mechanism, Trp stress enhances the synthesis and activity of the aryl hydrocarbon receptor (AHR). This is noteworthy as Trp catabolites are known to activate AHR, and therefore Trp stress was previously considered to inhibit AHR. Trp stress-induced AHR enhances the expression of key regulators of autophagy, which sustains intracellular Trp levels and Trp-charged tRNAs for translation. Hence, Trp stress switches MTORC1 from its established inhibitory function into an enhancer of autophagy, acting through AHR. The clinical potential of this fundamental mechanism is highlighted by the activity of the mTORC1-AHR pathway and an autophagy signature in 20% of glioblastoma patients, opening up new avenues for cancer therapy.

biochemistry↗

3D-Mass Spectrometry Imaging of Micro-scale 3D Cell Culture Models in Cancer Research

Three-dimensional (3D) human cell culture models have emerged as a key technology for personalized medicine and for phenotypic compound screening in more disease-like in-vitro systems. Mass spectrometry imaging (MSI) is one of the most versatile label-free techniques that enables simultaneous generation of spatial maps for multiple relevant molecules in these 3D-models. Here, we present an integrated platform for 3D-MSI of 3D-cell cultures comprising 3D-printed metal casting molds for freezing and embedding, MS imaging of 100 serial cryosections and their computational elastic 3D-reconstruction. With this platform, we monitored multiple lipids that were selectively associated with different cell-types or cell-cell interactions within 300 m-scale fibroblast and colon cancer biculture spheroids. Our findings suggest that 3D-printing-aided precise preparation of serial sections from small spheroids and visualization of marker molecules in 3D can provide a detailed overview of the cellular metabolic interplay in 3D cell culture models in cancer research and drug discovery.

cancer biology↗

Pre-analytical processing of plasma and serum samples for combined proteome and metabolome analysis

Metabolomic and proteomic analyses of human plasma and serum samples harbour the power to advance our understanding of disease biology. Pre-analytical factors may contribute to variability and bias in the detection of analytes, especially when multiple labs are involved, caused by sample handling, processing time, and differing operating procedures. To better understand the impact of pre-analytical factors that are relevant to implement a unified proteomic and metabolomic approach in a clinical setting, we assessed the influence of temperature, sitting times, and centrifugation speed on the plasma and serum metabolomes and proteomes from six healthy volunteers. We used targeted metabolic profiling (497 metabolites) and data-independent acquisition (DIA) proteomics (572 proteins) on the same samples generated with well-defined pre-analytical conditions to evaluate criteria for pre-analytical SOPs for plasma and serum samples. Time and temperature showed the strongest influence on the integrity of plasma and serum proteome and metabolome. While rapid handling and low temperatures (4{degrees}C) are imperative for metabolic profiling, the analysed proteome showed variability when exposed to temperatures of 4{degrees}C for more than 2 hours, highlighting the need for compromises in a combined analysis. We formalised a quality control scoring system to objectively rate sample stability and tested this score using external data sets from other pre-analytical studies. Stringent and harmonised standard operating procedures (SOPs) are required for pre-analytical sample handling when combining proteomics and metabolomics of clinical samples to yield robust and interpretable data on a longitudinal scale and across different clinics. To ensure an adequate level of practicability in a clinical routine for metabolomics and proteomics studies we suggest to keep blood samples up to 2 hours on ice (4{degrees}C) prior to snap-freezing as a compromise between stability and operability. Finally, we provide the methodology as an open source R package allowing the systematic scoring of proteomics and metabolomics datasets to assess the stability of plasma and serum samples.

biochemistry↗

Spatial Probabilistic Mapping of Metabolite Ensembles in Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) vows to enable simultaneous spatially-resolved investigation of hundreds of metabolites in tissue sections, but it still relies on poorly defined ion images for data interpretation. Here, we outline moleculaR, a computational framework (https://github.com/CeMOS-Mannheim/moleculaR) that introduces probabilistic mapping and point-for-point statistical testing of metabolites in tissue. It enables collective molecular projections and consequently spatially-resolved investigation of ion milieus, lipid pathways or user-defined biomolecular ensembles within the same image.

bioinformatics↗

Imaging stable isotope labelling kinetics (iSILK) for following spatial Aβ plaque aggregation dynamics in evolving Alzheimers disease pathology

For our understanding of Alzheimers disease (AD) pathophysiology, it is of critical importance to determine how key pathological factors, specifically amyloid {beta} (A{beta}) plaque formation, are interconnected and implicated in neurodegeneration, disease progression and the development of clinical symptoms. Exactly how A{beta} plaque formation is initiated and how the ongoing plaque deposition proceeds is not well understood. This is partly because we can only examine details of the molecular pathology after death in humans, and in mice, we can only examine a particular point in time without any longitudinal information on the fate of individually formed deposits. Herein, we used metabolic labelling of proteins with stable isotopes, together with multimodal imaging mass spectrometry (IMS) for imaging stable isotope labelling kinetics (iSILK) in the APPNL-G-F knock-in mouse model of AD. The aim was to monitor the earliest seeds of A{beta} deposition through ongoing plaque development and track the deposition of A{beta} that is produced later in relation to already deposited plaques. This allowed us to visualize A{beta} peptide aggregation dynamics within individual deposits across different brain regions. We identified the cortex as a primary site of deposition in precipitating plaque pathology. Further, our data show that structural plaque heterogeneity is associated with differential peptide deposition. Specifically, A{beta}1-42 is forming an initial core seed followed by radial outgrowth and late secretion and deposition of A{beta}1-38. Together these data prove the potential of iSILK for probing amyloid protein secretion, processing and aggregation dynamics in AD pathology.

neuroscience↗