Lipid systems play a substantial role in the pathophysiological mechanisms underlying several brain disorders. However, the mechanisms underlying the lipid profile in stress-induced maladaptations and how these changes can impact distinct neuronal circuits and behavioral states remain to be fully elucidated. Here, we investigated the effects of p11 deficiency in combination with stress by using p11KO mice and chronic stress mouse models of depression to study spatial lipidomic and transcriptomic signatures in the mouse nucleus accumbens. Our results show that p11 deficiency and stress induce depression-related maladaptive phenotypes and provide novel evidence that these responses are associated with phospholipid dyshomeostasis in the nucleus accumbens. Phospholipid disturbances were predominantly related to phosphatidylethanolamine (PE) and ether PE metabolism, along with targets involved in the PE biosynthetic pathway. Moreover, chelerythrine administration, a compound reported to disrupt phospholipid balance, induces PE changes and depression-like behaviors. Altogether, the present study provides evidence that alterations in phospholipid-related pathways may alter reward/anti-reward circuits and how these changes might be implicated in stress-related disorders.

Free fatty acids (FFAs) are bioactive mediators of inflammation, energy metabolism, and membrane remodeling, yet their spatial organization within the Alzheimer's disease (AD) brain and at individual amyloid-β (Aβ) plaques has remained inaccessible. We developed a novel, chemically tailored MALDI workflow that enables simultaneous, spatially resolved detection of nearly 30 FFAs alongside over 100 complex lipid species within the same tissue section. Applying this approach to a transgenic AD mouse model across brain regions and disease stages, and combining it with single-plaque microenvironment analysis (SPMA) that treats each plaque as an individual analytical object, we uncover two previously inaccessible dimensions of plaque-associated lipid biology. FFA distributions form highly structured spatial compartments reflecting regional cytoarchitecture, with distinct enrichment of saturated, monounsaturated, and polyunsaturated species across cortical layers. Within Aβ plaques, nearly 75% of detected FFAs are significantly remodeled, with reciprocal enrichment of short saturated and highly unsaturated species alongside depletion of long-chain monounsaturated FFAs. This pattern is consistent with concurrent disruption of ELOVL-mediated elongation and FADS-mediated desaturation, including opposing enrichment of pro-inflammatory arachidonic acid and pro-resolving docosahexaenoic acid. Machine learning of single-plaque profiles reveals that FFA composition alone classifies plaque age with high accuracy, demonstrating that lipid remodeling continues after Aβ peptide composition has stabilized. Together, these findings establish spatial FFA profiling as a new analytical dimension in neurodegeneration research, revealing that Aβ plaques are dynamic lipid-metabolic microenvironments that continue to remodel long after Aβ deposition has stabilized.

In this study, we demonstrate the complementary strengths of FMP-10 (4-(Anthracen-9-yl)-2-fluoro-1-methylpyridin-1-ium iodide) on-tissue derivatization with UV-MALDI MSI and IR-MALDESI MSI without derivatization for small molecule analysis. These MSI approaches were applied to the striatum of rats administered 6-OHDA to induce dopaminergic neurodegeneration, modeling Parkinson's disease. UV-MALDI MSI with FMP-10 derivatization enhanced the detection of dopaminergic and serotonergic metabolites, revealing clear lesion-related effects. IR-MALDESI MSI, in turn, expanded the molecular coverage by detecting several hundred additional small molecules, including neurotransmitters, amino acids, and lipids. The complementary application of these ionization strategies broadened metabolomic coverage, highlighting their potential for broader disease-related studies.

Parkinson's disease (PD) is characterized by Lewy body pathology, mainly consisting of accumulation of aggregated α-synuclein and lipid contents. Lipid dyshomeostasis has frequently been observed in PD, and compelling evidences indicate that lipids play critical roles in modulating α-synuclein toxicity. However, how α-synuclein regulates brain lipid composition remains poorly understood. Here, we used dual polarity matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to spatially profile brain lipids in a unilateral adeno-associated virus (AAV)-α-synuclein mouse model of Parkinsonism. We identified region-specific alterations in sphingolipids and glycerophospholipids in the substantia nigra and striatum of these mice. In sphingolipids, α-synuclein overexpression altered certain monosialotetrahexosylgangliosides (GM1s), sphingomyelins (SMs), and sulfated hexosyl ceramides (SHexCers; a.k.a. sulfatides). Glycerophospholipid changes followed a desaturation pattern: polyunsaturated fatty acid (PUFA)-containing species were decreased, while saturated and mono-unsaturated species were increased. Additionally, oxidized phosphatidylcholine (PC) lipids, such as SAzPC (1-stearoyl-2-azelaoyl-sn-PC) and PAzPC(1-palmitoyl-2-azelaoyl-sn-PC), were elevated in the substantia nigra, and ether phosphatidylethanolamines (PEs) were reduced in the substantia nigra but increased in the striatum. Our study provides a comprehensive, spatially resolved lipidomic landscape of α-synuclein-induced pathology in the nigrostriatal pathway, offering new insights into lipid dysregulation in experimental PD and a framework for future therapeutic exploration.

Free fatty acids (FFAs) are bioactive mediators of inflammation, energy metabolism, and membrane remodeling, yet their spatial organization within the Alzheimer's disease (AD) brain and at individual amyloid-beta (A beta) plaques has remained inaccessible. We developed a novel, chemically tailored MALDI workflow that enables simultaneous, spatially resolved detection of nearly 30 FFAs alongside over 100 complex lipid species within the same tissue section. Applying this approach to a transgenic AD mouse model across brain regions and disease stages, and combining it with single-plaque microenvironment analysis (SPMA) that treats each plaque as an individual analytical object, we uncover two previously inaccessible dimensions of plaque-associated lipid biology. FFA distributions form highly structured spatial compartments reflecting regional cytoarchitecture, with distinct enrichment of saturated, monounsaturated, and polyunsaturated species across cortical layers. Within A beta plaques, nearly 75% of detected FFAs are significantly remodeled, with reciprocal enrichment of short saturated and highly unsaturated species alongside depletion of long-chain monounsaturated FFAs. This pattern is consistent with concurrent disruption of ELOVL-mediated elongation and FADS-mediated desaturation, including opposing enrichment of pro-inflammatory arachidonic acid and pro-resolving docosahexaenoic acid. Machine learning of single-plaque profiles reveals that FFA composition alone classifies plaque age with high accuracy, demonstrating that lipid remodeling continues after A beta peptide composition has stabilized. Together, these findings establish spatial FFA profiling as a new analytical dimension in neurodegeneration research, revealing that A beta plaques are dynamic lipid-metabolic microenvironments that continue to remodel long after A beta deposition has stabilized.

The illicit use of anabolic androgenic steroids (AAS) to enhance physical strength, performance, and appearance is associated with severe physical and psychological adverse effects. Long-term AAS use has been associated with altered behavior and cognitive impairments. Nevertheless, the neurobiological effects of AAS use remain underexplored, especially in terms of brain neurotransmitter and lipid profiles. This study applied advanced Fourier-transform ion cyclotron resonance matrix-assisted laser desorption/ionization mass spectrometry imaging (FTICR-MALDI-MSI) to investigate the effects of three AAS decanoate prodrugs, nandrolone, testosterone, and trenbolone, on brain monoamine neurotransmitter systems and lipid composition in male rats (n = 32). The AAS administration was found to alter dopamine and serotonin levels, as well as the metabolism of these molecules across multiple brain regions; significant effects on neurotransmitter levels, associated metabolites, and turnover ratios were observed. Additionally, AAS treatment affected brain lipid composition, with nandrolone and testosterone increasing the levels of phosphatidylethanolamines, ether-linked phosphatidylethanolamines, and phosphatidylserines; in contrast, trenbolone demonstrated an opposite trend. The presented findings revealed distinct, steroid-specific alterations in brain neurotransmitters and lipid profiles; these changes were particularly strong in the tail of the striatum, where lipid dysregulation was linked to neurotransmitter dynamics. The potential neurotoxic effects further highlight the importance of understanding how steroid-specific mechanisms are linked to behavioral and neurobiological changes. This study advances our knowledge of the neurobiological effects, including the potential risks, of extended AAS use.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a promising tool for the spatial quantitation of endogenous and exogenous compounds directly in biological tissue sections. However, precise quantitation may be hampered due to matrix effects and variations in ionization efficiency, especially in spatially heterogeneous samples such as brain tissue. In this study, we developed and implemented two advanced MALDI-MSI protocols to address these limitations by employing a standard addition approach. The protocols involved the homogeneous spraying of standard solutions onto tissue sections to minimize the matrix effects associated with heterogeneous samples. The first method utilized spraying of deuterated analogues of neurotransmitters across all tissue sections for normalization, while calibration standards were applied in a quantitative manner to consecutive tissue sections. The second method employed two stable isotope-labeled compounds: one for calibration and the other for normalization. Both methods were applied to quantify neurotransmitters and their metabolites, e.g., dopamine, norepinephrine, and 3-methoxytyramine, in rodent brain tissue. The results showed strong linearity between signal intensities and analyte concentrations across brain tissue sections with values comparable to those obtained using high-performance liquid chromatography-electrochemical detection. The standard addition approach significantly enhanced the quantitation accuracy by accounting for tissue-specific matrix effects, providing a robust method for the spatial quantification of neurotransmitters in complex brain tissue environments.

This proteomic study provides a nuanced mechanistic understanding of the signaling processes upon agonist binding to the melanocortin-3 receptor (MC3R). Utilizing thermal proteome profiling (TPP) combined with LC-MS, we uncovered the distinct influences of the endogenous agonists adrenocorticotropic hormone (ACTH), α-melanocyte-stimulating hormone (α-MSH), and γ-melanocyte-stimulating hormone (γ-MSH) on protein thermal stability and pathway activation. In our 2D-TPP study, transfected HEK293 cells for expression of MC3R were exposed to the three endogenous MC3R-ligands across several concentrations followed by incubation at several temperatures, centrifugation and LC-MS analysis of the resulting supernatants. This enabled us to assess the effects of type of ligand and concentration on the thermal stability of proteins in these cells. We employed a combination of multivariate analysis, differential expression, TPP and pathway analysis to deeply characterize the impact of MC3R activation on molecular mechanisms. All three ligands affected signaling pathways related to the immune system and energy homeostasis. While α-MSH significantly modulated the IL-6 pathway via STAT3, and γ-MSH prominently activated interferon signaling, ACTH uniquely affected NADPH-related proteins. All ligands shared involvement in the cAMP-PKA-CREB and varied impacts on PI3K and ERK pathways, crucial for energy metabolism. All proteomic data are available under DOI: https://doi.org/10.6019/PXD039945.

Fagopyrum esculentum (Moench) is a valuable pseudo-cereal valued for its highly nutritious, gluten-free seeds. Despite being recognized as a 21st -century superfood, buckwheat remains non-competitive in seed yield compared to common cereals. Low productivity is mainly caused by abnormalities in female gametophyte development and frequent flower and embryo abortion. Buckwheat flowers accumulate high levels of phototoxic fagopyrin (FAG), whose physiological role remains unclear. FAG and its precursor (PFAG) are light-sensitive compounds with absorbance spectra in the green-yellow range (549-593 nm, peak at 590 nm), which makes their accumulation potentially responsive to light conditions. To address this, plants were cultivated under different light spectra, and the content of FAG and PFAG was analyzed in distinct floral organs (stamen, pistil, petal, and receptacle) using LC-MS, with their spatial distribution assessed by the MALDI-MS imaging. Pistil showed statistically the highest FAG and PFAG contents, while petals contained the lowest levels. A high density of FAG surrounding the ovary indicates a potential role in the reproductive part. Moreover, negative correlations were detected between flower production and FAG levels in the receptacles and pistils under specific light treatments. These results suggest that FAG may influence flower production and female gametophyte development, linking light environment to reproductive success in buckwheat.

Chromogranin A (CgA), a neuroendocrine pro-hormone, is proteolytically cleaved into bioactive peptides, most notably catestatin (CST) and pancreastatin (PST), which exert opposing effects on metabolic and inflammatory processes. Using CgA- and CST knockout (KO) mice, we investigated the roles of these peptides in pancreatic endocrine function, morphology, neurotransmitter dynamics, and systemic glucose homeostasis. CST-KO mice displayed impaired insulin secretion in vivo (but not ex vivo), disrupted islet architecture, and elevated catecholamine levels. In contrast, CgA-KO mice, which lack both CST and PST, exhibited reduced beta-cell mass but improved insulin sensitivity due to absence of PST. Peptide supplementation experiments in CgA-KO mice revealed that CST suppressed gluconeogenesis and enhanced glucagon regulation, whereas PST promoted insulin resistance and glucose production. Spatial mass spectrometry further demonstrated altered neurotransmitter and polyamine profiles in KO islets, implicating disrupted nerve-immune-islet crosstalk as a contributor to the observed metabolic phenotypes. Collectively, these findings identify CgA-derived peptides as critical regulators of islet function and highlight CST as a promising therapeutic candidate for diabetes and metabolic-inflammatory disorders.

Mass spectrometry imaging (MSI) is a powerful tool for spatial metabolomics and biomarker discovery, but molecular identification remains challenging, particularly for low-abundance analytes with poor signal-to-noise ratios. Herein, a novel approach that utilizes a deuterated analog of the reactive matrix FMP-10 to enhance molecular identification is introduced. This isotopically labeled matrix enables precise determination of derivatization patterns, allowing the number and sequence of reactive functional groups in small molecules to be deduced. By observing specific mass shifts, the method provides additional structural information beyond high-resolution MS and MS/MS, addressing key limitations in MSI-based biomarker discovery. This innovative labeling strategy improves identification confidence for neurotransmitters and metabolites, making it a powerful addition to the MSI toolbox for complex tissue analysis. The findings represent a significant advance for spatial metabolomics, with particular advantages for neurochemical mapping in the study of neurodegenerative diseases.

L-DOPA-induced dyskinesia (LID) is a significant and treatment-limiting complication in Parkinson’s disease (PD) therapy, yet its mechanisms remain poorly understood. We used high-resolution mass spectrometry imaging to map brain-region-specific alterations of glycerophospholipids and sphingolipids in a female macaque model of PD with and without LID following chronic L-DOPA treatment. LID was associated with depletion of antioxidant plasmalogen phosphatidylcholines in the globus pallidus interna, claustrum, and precentral gyrus—regions critical for motor function—and elevations of polyunsaturated fatty acid-containing glycerophospholipids, indicative of increased membrane fluidity. This lipid profile differed from similarly treated non-dyskinetic animals, suggesting lipid composition mediates differential susceptibility to LID. Lipid alterations correlated strongly with dyskinesia severity, dopamine, and L-DOPA concentrations, supporting a mechanistic link between lipid metabolism, neurotransmitter dysregulation, and LID. This comprehensive spatial lipidomic analysis identifies region-specific lipid dysregulation as a novel aspect of LID pathology, highlighting lipid pathways as potential therapeutic targets for mitigating dyskinesia.

The highly conserved CHCHD2 and CHCHD10 are small mitochondrial proteins residing in the intermembrane space. Recently, mutations in the genes encoding these proteins have been linked to severe disorders, including Parkinson's disease and amyotrophic lateral sclerosis. In cultured cells, a small fraction of CHCHD2 and CHCHD10 oligomerize to form a high molecular weight complex of unknown function. Here, we generated a whole-body Chchd2 knockout mouse to investigate the in vivo role of CHCHD2 and its protein complex. We show that CHCHD2 is crucial for sustaining full motor capacity, normal striatal dopamine levels, and lipid homeostasis in the brain of adult male mice. We also demonstrate that in mouse tissues, CHCHD2 and CHCHD10 exist exclusively as a high molecular weight complex, whose levels are finely tuned under physiological conditions. In response to mitochondrial dysfunction, the abundance and size of the CHCHD2-CHCHD10 complex increase, a mechanism conserved across different tissues. Although the loss of CHCHD2 does not abolish CHCHD10 oligomerization, it enhances cell vulnerability to mitochondrial stress, suggesting that CHCHD2 is protective against mitochondrial damage. Our findings uncover the role of CHCHD2 in preserving tissue homeostasis and provide important insights into the involvement of the CHCHD2-CHCHD10 complex in human diseases.

Here, we introduce Met-ID, a graphical user interface software designed to efficiently identify metabolites from MALDI-MSI data sets. Met-ID enables annotation of m/z features from any type of MALDI-MSI experiment, involving either derivatizing or conventional matrices. It utilizes structural information for derivatizing matrices to generate a subset of targets that contain only functional groups specific to the derivatization agent. The software is able to identify multiple derivatization sites on the same molecule, facilitating identification of the derivatized compound. This ability is exemplified by FMP-10, a reactive matrix that assists the covalent charge-tagging of molecules containing phenolic hydroxyl and/or primary or secondary amine groups. Met-ID also permits users to recalibrate data with known m/z ratios, boosting confidence in mass match results. Furthermore, Met-ID includes a database featuring MS2 spectra of numerous chemical standards, consisting of neurotransmitters and metabolites derivatized with FMP-10, alongside peaks for FMP-10 itself, all accessible directly through the software. The MS2 spectral database supports user-uploaded spectra and enables comparison of these spectra with user-provided tissue MS2 spectra for similarity assessment. Although initially installed with basic data, Met-ID is designed to be customizable, encouraging users to tailor the software to their specific needs. While several MSI-oriented software solutions exist, Met-ID combines both MS1 and MS2 functionalities. Developed in alignment with the FAIR Guiding Principles for scientific software, Met-ID is freely available as an open-source tool on GitHub, ensuring wide accessibility and collaboration.

While obesity and type 2 diabetes (T2D) are associated with altered dopaminergic activity in the central nervous system and in adipose tissue (AT), the directions and underlying mechanisms remain inconclusive. Therefore, we characterized changes in the abundance of dopamine, its metabolites, and receptors DRD1 and DRD2 in the brain and AT upon dietary intervention or obesity. Male Wistar rats were fed either a standard pellet diet, a cafeteria diet inducing obesity and insulin resistance, or a calorie-restricted diet for 12 weeks. Abundance of dopamine and its receptors DRD1 and DRD2 were examined in brain regions relevant for feeding behavior and energy homeostasis. Furthermore, DRD1 and DRD2 protein levels were analyzed in rat inguinal and epidydimal AT and in human subcutaneous and omental AT from individuals with or without obesity. Rats with diet-induced obesity displayed higher dopamine levels, as well as DRD1 or DRD2 receptor levels in the caudate putamen and the nucleus accumbens core. Surprisingly, caloric restriction induced similar changes in DRD1 and DRD2, but not in dopamine levels, in the brain. Both diets reduced DRD1 abundance in inguinal and epidydimal AT, but upregulated DRD2 levels in inguinal AT. Furthermore, in human obesity, DRD1 protein levels were elevated only in omental AT, while DRD2 was upregulated in both omental and subcutaneous AT. These findings highlight dopaminergic responses to changes in energy balance, occurring both in the brain and AT. We propose that dopaminergic pathways are involved in tissue crosstalk during the development of obesity and T2D.

Multiomics analysis of single tissue sections using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) provides comprehensive molecular insights. However, optimizing tissue sample preparation for MALDI-MSI to achieve high sensitivity and reproducibility for various biomolecules, such as lipids, N-glycans, and tryptic peptides, presents a significant challenge. This study introduces a robust and reproducible protocol for the comprehensive sequential analysis of the latter molecules using MALDI-MSI in fresh-frozen rodent brain tissue samples. The optimization process involved testing multiple organic solvents, which identified serial washing in ice-cold methanol, followed by chloroform as optimal for N-glycan analysis. Integrating this optimized protocol into MALDI-MSI workflows enabled comprehensive sequential analysis of lipids (in dual polarity mode), N-glycans, and tryptic peptides within the same tissue sections, enhancing both the efficiency and reliability. Validation across diverse rodent brain tissue samples confirmed the protocol's robustness and versatility. The optimized methodology was subsequently applied to a transgenic Alzheimer's disease (AD) mouse model (tgArcSwe) as a proof of concept. In the AD model, significant molecular alterations were observed in various sphingolipid and glycerophospholipid species, as well as in biantennary and GlcNAc-bisecting N-glycans, particularly in the cerebral cortex. These region-specific alterations are potentially associated with amyloid-beta (Aβ) plaque accumulation, which may contribute to cognitive and memory impairments. The proposed standardized methodology represents a significant advancement in neurobiological research, providing valuable insights into disease mechanisms and laying the foundation for potential preclinical applications. It could aid the development of diagnostic biomarkers and targeted therapies for AD and other neurodegenerative diseases, such as Parkinson's disease.

One of the main challenges in analyzing chemical messengers in the brain is the optimization of tissue sampling and preparation protocols. Limiting postmortem time and terminating enzyme activity is critical to identify low-abundance neurotransmitters and neuropeptides. Here, we used a rapid and uniform conductive heat transfer stabilization method that was compared with a conventional fresh freezing protocol. Together with a selective chemical derivatization method and an optimized quantitation approach using deuterated internal standards, we spatially mapped neurotransmitters and their related metabolites by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) in rat brain tissue sections. Although the heat stabilization did not show differences in the levels of dopamine, norepinephrine, and serotonin, their related metabolites 3,4-dihydroxyphenylacetaldehyde, 3,4-dihydroxyphenylacetic acid, homovanillic acid, 3-methoxy-4-hydroxyphenylacetaldehyde, dihydroxyphenylethyleneglycol, and 5-hydroxyindoleacetic acid were all significantly lower, indicating reduced neurotransmitter postmortem turnover ratios. Heat stabilization enabled detection of an increased number and higher levels of prodynorphin, proenkephalin, and tachykinin-derived bioactive neuropeptides. The low-abundant C-terminal flanking peptide, neuropeptide-γ, and nociceptin remained intact and were exclusively imaged in heat-stabilized brains. Without heat stabilization, degradation fragments of full-length peptides occurred in the fresh frozen tissues. The sample preparation protocols were furthermore tested on rat brains affected by acute anesthesia induced by isoflurane and medetomidine, showing comparable results to non-anesthetized animals on the neurotransmitters level without significant changes. Our data provide evidence for the potential use of heat stabilization prior to MALDI-MSI analyses to improve the examination of the in vivo state of neuronal chemical messengers in brain tissues not impacted by prior acute anesthesia.

Inhibitors targeting amyloids formed by the human Islet Amyloid Polypeptide (hIAPP) are promising therapeutic candidates for type 2 diabetes. Peptide formulations derived from the nonamyloidogenic rat IAPP (rIAPP) sequence are currently used as hIAPP mimetics to support insulin therapy. rIAPP itself acts as a peptide inhibitor; yet, the structural-level consequences of such inhibition, particularly its impact on amyloid polymorphism, have not been studied in detail. Here, we conduct coaggregation experiments with varying rIAPP-to-hIAPP concentration ratios and employ high-resolution cryo-electron microscopy (Cryo-EM) to elucidate the polymorphism of the resulting fibril structures. Our results demonstrate that the polymorphism of hIAPP amyloids is highly sensitive to the electrostatic environment, which can be modulated by buffer composition, the concentration of the inhibitor, and cosolvents such as hexafluoroisopropanol (HFIP). Under native conditions, rIAPP associates with hIAPP but does not cross-aggregate, resulting in fibrils primarily composed of hIAPP. Significant inhibition is observed at relatively high concentrations of rIAPP. However, trace amounts of HFIP disrupt this inhibition, leading to increased fibril concentrations due to the formation of cross-seeded products composed of both hIAPP and rIAPP, as evidenced by mass spectrometry and two-dimensional infrared (2D IR) spectroscopy. These findings highlight the critical role of experimental conditions, particularly the electrostatic environment, in modulating amyloid polymorphism, cross-seeding, and inhibition. By providing structural insights into these processes, this study advances our understanding of peptide aggregation and offers valuable guidance for the rational design of more effective therapeutic inhibitors targeting hIAPP-related amyloidosis.

A one-step, on-tissue chemical derivatisation method for MALDI mass spectrometry imaging was found to improve the detectability of aldehydes and ketones by charge-tagging. The developed reactive matrices, containing a UV-chromophore, ionisable moiety and hydrazide group, showed an equal or higher detection efficiency than Girard's reagent P, enabling improved imaging of brain metabolites without the need for additional co-matrices.