Spatial omics reveals molecular changes in focal cortical dysplasia type II.

Focal cortical dysplasia (FCD) represents a group of diverse localized cortical lesions that are highly epileptogenic and occur due to abnormal brain development caused by genetic mutations, involving the mammalian target of rapamycin (mTOR). These somatic mutations lead to mosaicism in the affected brain, posing challenges to unravel the direct and indirect functional consequences of these mutations. To comprehensively characterize the impact of mTOR mutations on the brain, we employed here a multimodal approach in a preclinical mouse model of FCD type II (Rheb), focusing on spatial omics techniques to define the proteomic and lipidomic changes. Mass Spectrometry Imaging (MSI) combined with fluorescence imaging and label free proteomics, revealed insight into the brain's lipidome and proteome within the FCD type II affected region in the mouse model. MSI visualized disrupted neuronal migration and differential lipid distribution including a reduction in sulfatides in the FCD type II-affected region, which play a role in brain myelination. MSI-guided laser capture microdissection (LMD) was conducted on FCD type II and control regions, followed by label free proteomics, revealing changes in myelination pathways by oligodendrocytes. Surgical resections of FCD type IIb and postmortem human cortex were analyzed by bulk transcriptomics to unravel the interplay between genetic mutations and molecular changes in FCD type II. Our comparative analysis of protein pathways and enriched Gene Ontology pathways related to myelination in the FCD type II-affected mouse model and human FCD type IIb transcriptomics highlights the animal model's translational value. This dual approach, including mouse model proteomics and human transcriptomics strengthens our understanding of the functional consequences arising from somatic mutations in FCD type II, as well as the identification of pathways that may be used as therapeutic strategies in the future.

MALDI-MSI-LC-MS/MS Workflow for Single-Section Single Step Combined Proteomics and Quantitative Lipidomics.

We introduce a novel approach for comprehensive molecular profiling in biological samples. Our single-section methodology combines quantitative mass spectrometry imaging (Q-MSI) and a single step extraction protocol enabling lipidomic and proteomic liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis on the same tissue area. The integration of spatially correlated lipidomic and proteomic data on a single tissue section allows for a comprehensive interpretation of the molecular landscape. Comparing Q-MSI and Q-LC-MS/MS quantification results sheds new light on the effect of MSI and related sample preparation. Performing MSI before Q-LC-MS on the same tissue section led to fewer protein identifications and a lower correlation between lipid quantification results. Also, the critical role and influence of internal standards in Q-MSI for accurate quantification is highlighted. Testing various slide types and the evaluation of different workflows for single-section spatial multiomics analysis emphasized the need for critical evaluation of Q-MSI data. These findings highlight the necessity for robust quantification methods comparable to current gold-standard LC-MS/MS techniques. The spatial information from MSI allowed region-specific insights within heterogeneous tissues, as demonstrated for glioblastoma multiforme. Additionally, our workflow demonstrated the efficiency of a single step extraction for lipidomic and proteomic analyses on the same tissue area, enabling the examination of significantly altered proteins and lipids within distinct regions of a single section. The integration of these insights into a lipid-protein interaction network expands the biological information attainable from a tissue section, highlighting the potential of this comprehensive approach for advancing spatial multiomics research.

Mass spectrometry imaging reveals flavor distribution in edible mushrooms.

The spatial distribution of molecules and compounds responsible for the flavor profile of edible button mushrooms (Agaricus bisporous) has never been determined. The food industry is interested in knowing the localization of these compounds. Such knowledge would enable extraction of flavor compounds from a particular regions of the mushroom, which is safer for consumption compared to alternatives such as synthetic flavoring agents. The present study utilizes matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI), to determine the spatial distribution of flavor compounds in a mushroom. As MALDI-MSI requires very thin sections, a sample preparation protocol was optimized and sectioning fresh frozen mushrooms at 35 µm thickness was considered the best method to evaluate the distribution of flavor compounds. Further, the effect of heat on the spatial distribution of flavor compounds was investigated by heating whole mushrooms to 140 ℃ prior to sectioning. Heating reduced the water content of the mushroom and thus enabled the generation of even-thinner 17 µm thick sections. MALDI-MSI measurements performed on underivatized and on-tissue derivatized fresh frozen and heat-treated mushroom sections elucidated the spatial distribution of several flavor-related compounds. Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-023-05883-0.

Untargeted metabolomics for lifestyle biomarker discovery in human hair.

There is a risk of crimes remaining unsolved when no matching DNA profiles or fingermarks are found. If this is the case, forensic investigations are faced with a significant shortage of evidence and information regarding the unknown perpetrator and/or victim as well as any missing persons. However, a rather commonly found biological trace encountered at crime scenes is human hair. As hair acts as a biochemical reservoir, it may contain valuable information regarding one's characteristics and habits. This study aimed to build an analytical method capable of determining a marker set of relevant metabolites in hair, eventually building up a profile of its donor. To find potential markers, an untargeted metabolomics approach was developed to select and identify statistically significant features. For that purpose, a total of 68 hair samples were collected at several hairdresser shops in varying neighbourhoods. Compound extraction was achieved via methanolic incubation overnight and analysis performed using a high-resolution mass spectrometry (HRMS) Orbitrap Q Exactive Focus. The acquired data was uploaded and statistically evaluated using two free online software/libraries, where a total of eight compounds have given a match on both tools. Their presumptive identity was confirmed using reference standards and consequently added to a dynamic target donor profiling list. These results show the potential of using untargeted metabolomics for the search for lifestyle biomarkers capable of differentiating individuals. Such tools are of paramount importance in a forensic setting with little or no evidence available and no clear tactical leads.

Spatial Neurolipidomics at the Single Amyloid-ß Plaque Level in Postmortem Human Alzheimer's Disease Brain.

Lipid dysregulations have been critically implicated in Alzheimer's disease (AD) pathology. Chemical analysis of amyloid-ß (Aß) plaque pathology in transgenic AD mouse models has demonstrated alterations in the microenvironment in the direct proximity of Aß plaque pathology. In mouse studies, differences in lipid patterns linked to structural polymorphism among Aß pathology, such as diffuse, immature, and mature fibrillary aggregates, have also been reported. To date, no comprehensive analysis of neuronal lipid microenvironment changes in human AD tissue has been performed. Here, for the first time, we leverage matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) through a high-speed and spatial resolution commercial time-of-light instrument, as well as a high-mass-resolution in-house-developed orbitrap system to characterize the lipid microenvironment in postmortem human brain tissue from AD patients carrying Presenilin 1 mutations (PSEN1) that lead to familial forms of AD (fAD). Interrogation of the spatially resolved MSI data on a single Aß plaque allowed us to verify nearly 40 sphingolipid and phospholipid species from diverse subclasses being enriched and depleted, in relation to the Aß deposits. This included monosialo-gangliosides (GM), ceramide monohexosides (HexCer), ceramide-1-phosphates (CerP), ceramide phosphoethanolamine conjugates (PE-Cer), sulfatides (ST), as well as phosphatidylinositols (PI), phosphatidylethanolamines (PE), and phosphatidic acid (PA) species (including Lyso-forms). Indeed, many of the sphingolipid species overlap with the species previously seen in transgenic AD mouse models. Interestingly, in comparison to the animal studies, we observed an increased level of localization of PE and PI species containing arachidonic acid (AA). These findings are highly relevant, demonstrating for the first time Aß plaque pathology-related alteration in the lipid microenvironment in humans. They provide a basis for the development of potential lipid biomarkers for AD characterization and insight into human-specific molecular pathway alterations.

Spatial Metabolomics Identifies LPC(18:0) and LPA(18:1) in Advanced Atheroma With Translation to Plasma for Cardiovascular Risk Estimation.

BACKGROUND: The metabolic alterations occurring within the arterial architecture during atherosclerosis development remain poorly understood, let alone those particular to each arterial tunica. We aimed first to identify, in a spatially resolved manner, the specific metabolic changes in plaque, media, adventitia, and cardiac tissue between control and atherosclerotic murine aortas. Second, we assessed their translatability to human tissue and plasma for cardiovascular risk estimation. METHODS: In this observational study, mass spectrometry imaging (MSI) was applied to identify region-specific metabolic differences between atherosclerotic (n=11) and control (n=11) aortas from low-density lipoprotein receptor-deficient mice, via histology-guided virtual microdissection. Early and advanced plaques were compared within the same atherosclerotic animals. Progression metabolites were further analyzed by MSI in 9 human atherosclerotic carotids and by targeted mass spectrometry in human plasma from subjects with elective coronary artery bypass grafting (cardiovascular risk group, n=27) and a control group (n=27). RESULTS: MSI identified 362 local metabolic alterations in atherosclerotic mice (log2 fold-change ≥1.5; P≤0.05). The lipid composition of cardiac tissue is altered during atherosclerosis development and presents a generalized accumulation of glycerophospholipids, except for lysolipids. Lysolipids (among other glycerophospholipids) were found at elevated levels in all 3 arterial layers of atherosclerotic aortas. LPC(18:0) (lysophosphatidylcholine; P=0.024) and LPA(18:1) (lysophosphatidic acid; P=0.025) were found to be significantly elevated in advanced plaques as compared with mouse-matched early plaques. Higher levels of both lipid species were also observed in fibrosis-rich areas of advanced- versus early-stage human samples. They were found to be significantly reduced in human plasma from subjects with elective coronary artery bypass grafting (P<0.001 and P=0.031, respectively), with LPC(18:0) showing significant association with cardiovascular risk (odds ratio, 0.479 [95% CI, 0.225-0.883]; P=0.032) and diagnostic potential (area under the curve, 0.778 [95% CI, 0.638-0.917]). CONCLUSIONS: An altered phospholipid metabolism occurs in atherosclerosis, affecting both the aorta and the adjacent heart tissue. Plaque-progression lipids LPC(18:0) and LPA(18:1), as identified by MSI on tissue, reflect cardiovascular risk in human plasma.

Improved on-tissue detection of the anti-cancer agent doxorubicin by quantitative matrix-assisted laser desorption/ionization mass spectrometry imaging.

Doxorubicin (dox) is an affordable, and highly effective chemotherapeutic agent used in cancer treatment, yet its application is known to cause cumulative cardiac and renal toxicity. In this study, we employed matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) to evaluate the distribution of dox in mouse heart and kidney after in vivo treatment. To this end, we performed absolute quantification using an isotopically labeled form (13C d3-dox) as an internal standard. Unfortunately, ion suppression often leads to loss of sensitivity in compound detection and can result in hampered drug quantification. To overcome this issue, we developed an on-tissue chemical derivatization (OTCD) method using Girard's reagent T (GirT). With the developed method, dox signal was increased by two orders of magnitude. This optimized sample preparation enabled a sensible gain in dox detection, making it possible to study its distribution and abundance (up to 0.11 pmol/mm2 in the heart and 0.33 pmol/mm2 in the kidney medulla). The optimized approach for on-tissue derivatization and subsequent quantification creates a powerful tool to better understand the relationship between dox exposure (at clinically relevant concentrations) and its biological detrimental effects in various tissues. Overall, this work is a showcase of the added value of MALDI-MSI for pharmaceutical studies to better understand heterogeneity in drug exposure between and within organs.

Lipid profiling of electrosurgical vapors for real-time assistance of soft tissue sarcoma resection.

BACKGROUND: Soft tissue sarcomas (STS) constitute a heterogeneous group of rare tumor entities. Treatment relies on challenging patient-tailored surgical resection. Real-time intraoperative lipid profiling of electrosurgical vapors by rapid evaporative ionization mass spectrometry (REIMS) may aid in achieving successful surgical R0 resection (i.e., microscopically negative-tumor margin resection). Here, we evaluate the ex vivo accuracy of REIMS to discriminate and identify various STS from normal surrounding tissue. METHODS: Twenty-seven patients undergoing surgery for STS at Maastricht University Medical Center+ were included in the study. Samples of resected STS specimens were collected and analyzed ex vivo using REIMS. Electrosurgical cauterization of tumor and surrounding was generated successively in both cut and coagulation modes. Resected specimens were subsequently processed for gold standard histopathological review. Multivariate statistical analysis (principal component analysis-linear discriminant analysis) and leave-one patient-out cross-validation were employed to compare the classifications predicted by REIMS lipid profiles to the pathology classifications. Electrosurgical vapors produced during sarcoma resection were analyzed in vivo using REIMS. RESULTS: In total, 1200 histopathologically-validated ex vivo REIMS lipid profiles were generated from 27 patients. Ex vivo REIMS lipid profiles classified STS and normal tissues with 95.5% accuracy. STS, adipose and muscle tissues were classified with 98.3% accuracy. Well-differentiated liposarcomas and adipose tissues could not be discriminated based on their respective lipid profiles. Distinction of leiomyosarcomas from other STS could be achieved with 96.6% accuracy. In vivo REIMS analyses generated intense mass spectrometric signals. CONCLUSION: Lipid profiling by REIMS is able to discriminate and identify STS with high accuracy and therefore constitutes a potential asset to improve surgical resection of STS in the future.

Ultrahigh-Mass Resolution Mass Spectrometry Imaging with an Orbitrap Externally Coupled to a High-Performance Data Acquisition System.

Matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging (MSI) is a powerful analytical tool that enables molecular sample analysis while simultaneously providing the spatial context of hundreds or even thousands of analytes. However, because of the lack of a separation step prior to ionization and the immense diversity of biomolecules, such as lipids, including numerous isobaric species, the coupling of ultrahigh mass resolution (UHR) with MSI presents one way in which this complexity can be resolved at the spectrum level. Until now, UHR MSI platforms have been restricted to Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometers. Here, we demonstrate the capabilities of an Orbitrap-based UHR MSI platform to reach over 1,000,000 mass resolution in a lipid mass range (600-950 Da). Externally coupling the Orbitrap Q Exactive HF with the high-performance data acquisition system FTMS Booster X2 provided access to the unreduced data in the form of full-profile absorption-mode FT mass spectra. In addition, it allowed us to increase the time-domain transient length from 0.5 to 10 s, providing improvement in the mass resolution, signal-to-noise ratio, and mass accuracy. The resulting UHR performance generates high-quality MALDI MSI images and simplifies the identification of lipids. Collectively, these improvements resulted in a 1.5-fold increase in annotations, demonstrating the advantages of this UHR imaging platform for spatial lipidomics using MALDI-MSI.

Lipidomic Phenotyping Of Human Small Intestinal Organoids Using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging.

In the past decade, interest in organoids for biomedical research has surged, resulting in a higher demand for advanced imaging techniques. Traditional specimen embedding methods pose challenges, such as analyte delocalization and histological assessment. Here, we present an optimized sample preparation approach utilizing an Epredia M-1 cellulose-based embedding matrix, which preserves the structural integrity of fragile small intestinal organoids (SIOs). Additionally, background interference (delocalization of analytes, nonspecific (histological) staining, matrix ion clusters) was minimized, and we demonstrate the compatibility with matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). With our approach, we can conduct label-free lipid imaging at the single-cell level, thereby yielding insights into the spatial distribution of lipids in both positive and negative ion modes. Moreover, M-1 embedding allows for an improved coregistration with histological and immunohistochemical (IHC) stainings, including MALDI-IHC, facilitating combined untargeted and targeted spatial information. Applying this approach, we successfully phenotyped crypt-like (CL) and villus-like (VL) SIOs, revealing that PE 36:2 [M - H]- (m/z 742.5) and PI 38:4 [M - H]- (m/z 885.5) display higher abundance in CL organoids, whereas PI 36:1 [M - H]- (m/z 863.6) was more prevalent in VL organoids. Our findings demonstrate the utility of M-1 embedding for advancing organoid research and unraveling intricate biological processes within these in vitro models.

Toward Omics-Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue Using a Multiclass Internal Standard Mixture.

Mass spectrometry imaging (MSI) has accelerated our understanding of lipid metabolism and spatial distribution in tissues and cells. However, few MSI studies have approached lipid imaging quantitatively and those that have focused on a single lipid class. We overcome this limitation by using a multiclass internal standard (IS) mixture sprayed homogeneously over the tissue surface with concentrations that reflect those of endogenous lipids. This enabled quantitative MSI (Q-MSI) of 13 lipid classes and subclasses representing almost 200 sum-composition lipid species using both MALDI (negative ion mode) and MALDI-2 (positive ion mode) and pixel-wise normalization of each lipid species in a manner analogous to that widely used in shotgun lipidomics. The Q-MSI approach covered 3 orders of magnitude in dynamic range (lipid concentrations reported in pmol/mm2) and revealed subtle changes in distribution compared to data without normalization. The robustness of the method was evaluated by repeating experiments in two laboratories using both timsTOF and Orbitrap mass spectrometers with an ∼4-fold difference in mass resolution power. There was a strong overall correlation in the Q-MSI results obtained by using the two approaches. Outliers were mostly rationalized by isobaric interferences or the higher sensitivity of one instrument for a particular lipid species. These data provide insight into how the mass resolving power can affect Q-MSI data. This approach opens up the possibility of performing large-scale Q-MSI studies across numerous lipid classes and subclasses and revealing how absolute lipid concentrations vary throughout and between biological tissues.

State-of-the-art mass spectrometry imaging applications in biomedical research.

Mass spectrometry imaging has advanced from a niche technique to a widely applied spatial biology tool operating at the forefront of numerous fields, most notably making a significant impact in biomedical pharmacological research. The growth of the field has gone hand in hand with an increase in publications and usage of the technique by new laboratories, and consequently this has led to a shift from general MSI reviews to topic-specific reviews. Given this development, we see the need to recapitulate the strengths of MSI by providing a more holistic overview of state-of-the-art MSI studies to provide the new generation of researchers with an up-to-date reference framework. Here we review scientific advances for the six largest biomedical fields of MSI application (oncology, pharmacology, neurology, cardiovascular diseases, endocrinology, and rheumatology). These publications thereby give examples for at least one of the following categories: they provide novel mechanistic insights, use an exceptionally large cohort size, establish a workflow that has the potential to become a high-impact methodology, or are highly cited in their field. We finally have a look into new emerging fields and trends in MSI (immunology, microbiology, infectious diseases, and aging), as applied MSI is continuously broadening as a result of technological breakthroughs.

Key regulator PNPLA8 drives phospholipid reprogramming induced proliferation and migration in triple-negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype and leads to the poorest patient outcomes despite surgery and chemotherapy treatment. Exploring new molecular mechanisms of TNBC that could lead to the development of novel molecular targets are critically important for improving therapeutic options for treating TNBC. METHODS: We sought to identify novel therapeutic targets in TNBC by combining genomic and functional studies with lipidomic analysis, which included mechanistic studies to elucidate the pathways that tie lipid profile to critical cancer cell properties. Our studies were performed in a large panel of human breast cancer cell lines and patient samples. RESULTS: Comprehensive lipid profiling revealed that phospholipid metabolism is reprogrammed in TNBC cells. We discovered that patatin-like phospholipase domain-containing lipase 8 (PNPLA8) is overexpressed in TNBC cell lines and tissues from breast cancer patients. Silencing of PNPLA8 disrupted phospholipid metabolic reprogramming in TNBC, particularly affecting the levels of phosphatidylglycerol (PG), phosphatidylcholine (PC), lysophosphatidylcholine (LPC) and glycerophosphocholine (GPC). We showed that PNPLA8 is essential in regulating cell viability, migration and antioxidation in TNBC cells and promoted arachidonic acid and eicosanoid production, which in turn activated PI3K/Akt/Gsk3ß and MAPK signaling. CONCLUSIONS: Our study highlights PNPLA8 as key regulator of phospholipid metabolic reprogramming and malignant phenotypes in TNBC, which could be further developed as a novel molecular treatment target.

Characterization of spatial lipidomic signatures in tick-bitten guinea pig skin as a model for host-vector-pathogen interaction profiling.

IMPORTANCE: Here, we demonstrate the adaptability of spatial "omics" methods to identify interphylum processes regulated at the vector-host interface of ticks during a mammalian blood meal. This approach enables a better understanding of complex bipartite or tripartite molecular interactions between hosts, arthropod vectors and transmitted pathogens, and contributes toward the development of spatially aware therapeutic target discovery and description.

MALDI-2 Mass Spectrometry for Synthetic Polymer Analysis.

Synthetic polymers are ubiquitous in daily life, and their properties offer diverse benefits in numerous applications. However, synthetic polymers also present an increasing environmental burden through their improper disposal and subsequent degradation into secondary micro- and nanoparticles (MNPs). These MNPs accumulate in soil and water environments and can ultimately end up in the food chain, resulting in potential health risks. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) has the potential to study localized biological or toxicological changes in organisms exposed to MNPs. Here, we investigate whether MALDI-2 postionization can provide a sensitivity enhancement in polymer analysis that could contribute to the study of MNPs. We evaluated the effect of MALDI-2 by comparing MALDI and MALDI-2 ion yields from polyethyleneglycol (PEG), polypropylene glycol (PPG), polytetrahydrofuran (PTHF), nylon-6, and polystyrene (PS). MALDI-2 caused a signal enhancement of the protonated species for PEG, PPG, PTHF, and nylon-6. PS, by contrast, preferentially formed radical ions, which we attribute to direct resonance-enhanced multiphoton ionization (REMPI). REMPI of PS led to an improvement in sensitivity by several orders of magnitude, even without cationizing salts. The improved sensitivity demonstrated by MALDI-2 for all polymers tested highlights its potential for studying the distribution of certain classes of polymers in biological systems.

Spatial lipidomics reveals biased phospholipid remodeling in acute Pseudomonas lung infection.

Pseudomonas aeruginosa (Pa) is a pathogen causing chronic pulmonary infections in patients with cystic fibrosis (CF). Manipulation of lipids is an important feature of Pa infection and on a tissue-level scale is poorly understood. Using a mouse model of acute Pa pulmonary infection, we explored the whole-lung phospholipid response using mass spectrometry imaging (MSI) and spatial lipidomics. Using a histology-driven analysis, we isolated airways and parenchyma from both mock- and Pa-infected lungs and used systems biology tools to identify enriched metabolic pathways from the differential phospholipid identities. Infection was associated with a set of 26 ions, with 11 unique to parenchyma and 6 unique to airways. Acyl remodeling was differentially enriched in infected parenchyma as the predominant biological function. These functions correlated with markers of polymorphonuclear (PMN) cell influx, a defining feature of the lung response to Pa infection, implicating enzymes active in phospholipid remodeling.

Isomer-Resolved Mass Spectrometry Imaging of Acidic Phospholipids.

The biological functions of lipids are entirely dependent on their molecular structures with even small changes in structure─such as different sites of unsaturation─providing critical markers for changes in the underlying metabolism. Conventional mass spectrometry imaging (MSI) approaches, however, face the twin challenges of mixture and structural complexity and are typically unable to differentiate lipid isomers that differ only in the position(s) of carbon-carbon double bonds. Recent coupling of ozone-induced dissociation (OzID) with matrix-assisted laser desorption/ionization (MALDI)-MSI has demonstrated the potential to map changes in individual double-bond isomers, thus enabling visualization of the modulation in lipid desaturation in adjacent tissue types. This has, to date, only been performed in positive-ion mode due to a generally higher abundance of phosphatidylcholines (PC) in mammalian tissues and the efficient desorption/ionization of this lipid subclass. Many other glycerophospholipids (GPLs), however, are better detected in negative-ion mode as deprotonated anions. Recently, OzID has been implemented on a traveling-wave ion-mobility mass spectrometer (Waters, SYNAPT G2-Si) that provides a 50-fold increase in the rate of the gas-phase reaction between ionized lipids and ozone and a commensurate increase in sensitivity for isomer-resolved mass spectrometry. These gains are exploited here to interrogate the distributions of anionic GPL isomers in biological tissues, covering the subclasses phosphatidylserine (PS), phosphatidylethanolamine (PE), phosphatidylinositol (PI), phosphatidylglycerol (PG), and phosphatidic acid (PA). Exploiting both ozone- and collision-induced dissociation in a single acquisition simultaneously identifies sites of unsaturation and acyl chain composition from the same mass spectrum.

Random forest and live single-cell metabolomics reveal metabolic profiles of human macrophages upon polarization.

Human macrophages are innate immune cells with diverse, functionally distinct phenotypes, namely, pro-inflammatory M1 and anti-inflammatory M2 macrophages. Both are involved in multiple physiological and pathological processes, including would healing, infection, and cancer. However, the metabolic differences between these phenotypes are largely unexplored at single-cell resolution. To address this knowledge gap, an untargeted live single-cell mass spectrometry-based metabolomic profiling coupled with a machine-learning data analysis approach was developed to investigate the metabolic profile of each phenotype at the single-cell level. Results show that M1 and M2 macrophages have distinct metabolic profiles, with differential levels of fatty acyls, glycerophospholipids, and sterol lipids, which are important components of plasma membrane and involved in multiple biological processes. Furthermore, we could discern several putatively annotated molecules that contribute to inflammatory response of macrophages. The combination of random forest and live single-cell metabolomics provided an in-depth profile of the metabolome of primary human M1 and M2 macrophages at the single-cell level for the first time, which will pave the way for future studies targeting the differentiation of other immune cells.

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) reveals potential lipid markers between infrapatellar fat pad biopsies of osteoarthritis and cartilage defect patients.

The incidence of osteoarthritis (OA) has been expected to increase due to an aging population, as well as an increased incidence of intra-articular (osteo-) chondral damage. Lipids have already been shown to be involved in the inflammatory process of OA. This study aims at revealing region-specific lipid profiles of the infrapatellar fat pad (IPFP) of OA or cartilage defect patients by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which could be used as biomarkers for early OA detection. A higher presence of phospholipids was found in OA patients compared with cartilage defect patients. In addition, a higher abundance of ether-linked phosphatidylethanolamines (PE O-s) containing arachidonic acid was specifically found in OA patients compared with cartilage defect patients. These lipids were mainly found in the connective tissue of the IPFP. Specific lipid species were associated to OA patients compared with cartilage defect patients. PE O-s have been suggested as possible biomarkers for OA. As these were found more abundantly in the connective tissue, the IPFP's intra-tissue heterogeneity might play an important role in biomarker discovery, implying that the amount of fibrous tissue is associated with OA.