Desorption Electrospray Ionization Mass Spectrometry Imaging Research Articles

Distinguishing Non-Small Cell Lung Cancer Subtypes in Fine Needle Aspiration Biopsies by Desorption Electrospray Ionization Mass Spectrometry Imaging.

Distinguishing adenocarcinoma and squamous cell carcinoma subtypes of non-small cell lung cancers is critical to patient care. Preoperative minimally-invasive biopsy techniques, such as fine needle aspiration (FNA), are increasingly used for lung cancer diagnosis and subtyping. Yet, histologic distinction of lung cancer subtypes in FNA material can be challenging. Here, we evaluated the usefulness of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) to diagnose and differentiate lung cancer subtypes in tissues and FNA samples. DESI-MSI was used to analyze 22 normal, 26 adenocarcinoma, and 25 squamous cell carcinoma lung tissues. Mass spectra obtained from the tissue sections were used to generate and validate statistical classifiers for lung cancer diagnosis and subtyping. Classifiers were then tested on DESI-MSI data collected from 16 clinical FNA samples prospectively collected from 8 patients undergoing interventional radiology guided FNA. Various metabolites and lipid species were detected in the mass spectra obtained from lung tissues. The classifiers generated from tissue sections yielded 100% accuracy, 100% sensitivity, and 100% specificity for lung cancer diagnosis, and 73.5% accuracy for lung cancer subtyping for the training set of tissues, per-patient. On the validation set of tissues, 100% accuracy for lung cancer diagnosis and 94.1% accuracy for lung cancer subtyping were achieved. When tested on the FNA samples, 100% diagnostic accuracy and 87.5% accuracy on subtyping were achieved per-slide. DESI-MSI can be useful as an ancillary technique to conventional cytopathology for diagnosis and subtyping of non-small cell lung cancers.

Localization of constituents for determining the age and parts of ginseng through ultraperfomance liquid chromatography quadrupole/time of flight-mass spectrometry combined with desorption electrospray ionization mass spectrometry imaging

Ginseng has been used for prevention and treatment of disease for thousands of years in China and many other Asian countries. Phytochemical studies have indicated that ginsenosides, polysaccharides, alkaloids, and phenolic acids are the active constituents of ginseng. Main and branch roots of ginseng exhibit distinct bioactive behavior. Furthermore, the bioactive behavior of ginseng depends on its age. Traditional analysis is complex preparation and provides inadequate of chemical information of the original distribution of analytes. Therefore, in this study, ultraperformance liquid chromatography quadrupole/time of flight-mass spectrometry (UPLC-QTOF MS) and desorption electrospray ionization mass spectrometry imaging (DESI-MSI) combined with orthogonal partial least squares discriminant analysis were used to discriminate ginseng in different age and parts of ginseng, and profiled distribution of selected markers. The results indicated that UPLC-QTOF-MS and DESI-MSI could be used to determine the parts and age of ginseng. Fifteen variables including five of protopanaxatriol (PPT), four of protopanaxadiol (PPD), and six of other types were assumed as markers for different parts of ginseng. Moreover, four variables of PPT, four of PPD, and ten of other types were used to determine the age of ginseng samples. An analysis of localization of markers indicated that malonyl ginsenoside, including malonyl-ginsenoside Rb1, Rb2, Rc, and Rd was mainly distributed in the corks. Neutral ginsenoside Rg1, yesanchinoisde D, and chikusetsusaponin Iva were mainly distributed in the cork and phloem. Non-ginsenoside castanoside H, 20(S)-protopanaxatriol, unknown 2, saponin III and cistanoside C were distributed in all tissues. Ethyloleate, unknown 1 and monolinolein were distributed in the cork.

Preoperative metabolic classification of thyroid nodules using mass spectrometry imaging of fine-needle aspiration biopsies

Thyroid neoplasia is common and requires appropriate clinical workup with imaging and fine-needle aspiration (FNA) biopsy to evaluate for cancer. Yet, up to 20% of thyroid nodule FNA biopsies will be indeterminate in diagnosis based on cytological evaluation. Genomic approaches to characterize the malignant potential of nodules showed initial promise but have provided only modest improvement in diagnosis. Here, we describe a method using metabolic analysis by desorption electrospray ionization mass spectrometry (DESI-MS) imaging for direct analysis and diagnosis of follicular cell-derived neoplasia tissues and FNA biopsies. DESI-MS was used to analyze 178 tissue samples to determine the molecular signatures of normal, benign follicular adenoma (FTA), and malignant follicular carcinoma (FTC) and papillary carcinoma (PTC) thyroid tissues. Statistical classifiers, including benign thyroid versus PTC and benign thyroid versus FTC, were built and validated with 114,125 mass spectra, with accuracy assessed in correlation with clinical pathology. Clinical FNA smears were prospectively collected and analyzed using DESI-MS imaging, and the performance of the statistical classifiers was tested with 69 prospectively collected clinical FNA smears. High performance was achieved for both models when predicting on the FNA test set, which included 24 nodules with indeterminate preoperative cytology, with accuracies of 93% and 89%. Our results strongly suggest that DESI-MS imaging is a valuable technology for identification of malignant potential of thyroid nodules.

3D DESI-MS lipid imaging in a xenograft model of glioblastoma: a proof of principle

Desorption electrospray ionisation mass spectrometry (DESI-MS) can image hundreds of molecules in a 2D tissue section, making it an ideal tool for mapping tumour heterogeneity. Tumour lipid metabolism has gained increasing attention over the past decade; and here, lipid heterogeneity has been visualised in a glioblastoma xenograft tumour using 3D DESI-MS imaging. The use of an automatic slide loader automates 3D imaging for high sample-throughput. Glioblastomas are highly aggressive primary brain tumours, which display heterogeneous characteristics and are resistant to chemotherapy and radiotherapy. It is therefore important to understand biochemical contributions to their heterogeneity, which may be contributing to treatment resistance. Adjacent sections to those used for DESI-MS imaging were used for H&E staining and immunofluorescence to identify different histological regions, and areas of hypoxia. Comparing DESI-MS imaging with biological staining allowed association of different lipid species with hypoxic and viable tissue within the tumour, and hence mapping of molecularly different tumour regions in 3D space. This work highlights that lipids are playing an important role in the heterogeneity of this xenograft tumour model, and DESI-MS imaging can be used for lipid 3D imaging in an automated fashion to reveal heterogeneity, which is not apparent in H&E stains alone.

Use of whole-body cryosectioning and desorption electrospray ionization mass spectrometry imaging to visualize alkaloid distribution in poison frogs.

Ambient mass spectrometry is useful for analyzing compounds that would be affected by other chemical procedures. Poison frogs are known to sequester alkaloids from their diet, but the sequestration pathway is unknown. Here, we describe methods for whole-body cryosectioning of frogs and use desorption electrospray ionization mass spectrometry imaging (DESI-MSI) to map the orally administered alkaloid histrionicotoxin 235A in a whole-body section of the poison frog Dendrobates tinctorius. Our results show that whole-body cryosectioning coupled with histochemical staining and DESI-MSI is an effective technique to visualize alkaloid distribution and help elucidate the mechanisms involved in alkaloid sequestration in poison frogs.

Identification of lipid biomarkers of metastatic potential and gene expression (HER2/p53) in human breast cancer cell cultures using ambient mass spectrometry.

In breast cancer, overexpression of human epidermal growth factor receptor 2 (HER2) correlates with overactivation of lipogenesis, mutation of tumor suppressor p53, and increased metastatic potential. The mechanisms through which lipids mediate p53, HER2, and metastatic potential are largely unknown. We havedeveloped a desorption electrospray ionization mass spectrometry (DESI-MS) method to identify lipid biomarkers of HER2/p53 expression, metastatic potential, and disease state (viz. cancer vs. non-cancerous) in monolayer and suspension breast cancer cell cultures (metastatic potential: MCF-7, T-47D, MDA-MB-231; HER2/p53: HCC2218 (HER2+++/p53+), HCC1599 (HER2-/p53-), HCC202 (HER2++/p53-), HCC1419 (HER2+++/p53-) HCC70 (HER2-/p53+++); non-cancerous: MCF-10A). Unsupervised principal component analysis(PCA) of DESI-MS spectra enabled identification of twelve lipid biomarkers of metastatic potential and disease state, as well as ten lipids that distinguish cell lines based on HER2/p53 expression levels (> 200 lipids were identified per cell line). In addition, we developed a DESI-MS imaging (DESI-MSI) method for mapping the spatial distribution of lipids in metastatic spheroids (MDA-MB-231). Of the twelve lipids that correlate with changes in themetastatic potentialof monolayercell cultures, three were localized to the necrotic coreof spheroids, indicating a potential role in promoting cancer cell survival in nutrient-deficient environments. One lipid species, which was not detected in monolayer MDA-MB-231 cultures, was spatially localized to the periphery of the spheroid, suggesting a potential role in invasion and/or proliferation. These results demonstrate thatcombiningDESI-MS/PCA of monolayer and suspension cell cultures with DESI-MSI of spheroids isa promising approach for identifying lipid biomarkers of specific genotypes and phenotypes, as well as elucidating the potential functionof these biomarkers in breast cancer. Graphical Absract.

In Situ DESI-MSI Lipidomic Profiles of Breast Cancer Molecular Subtypes and Precursor Lesions.

Clinically meaningful molecular subtypes for classification of breast cancers have been established, however, initiation and progression of these subtypes remain poorly understood. The recent development of desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) facilitates the convergence of analytical chemistry and traditional pathology, allowing chemical profiling with minimal tissue pretreatment in frozen samples. Here, we characterized the chemical composition of molecular subtypes of breast cancer with DESI-MSI. Regions of interest were identified, including invasive breast cancer (IBC), ductal carcinoma in situ (DCIS), and adjacent benign tissue (ABT), and metabolomic profiles at 200 μm elaborated using Biomap software and the Lasso method. Top ions identified in IBC regions included polyunsaturated fatty acids, deprotonated glycerophospholipids, and sphingolipids. Highly saturated lipids, as well as antioxidant molecules [taurine (m/z 124.0068), uric acid (m/z 167.0210), ascorbic acid (m/z 175.0241), and glutathione (m/z 306.0765)], were able to distinguish IBC from ABT. Moreover, luminal B and triple-negative subtypes showed more complex lipid profiles compared with luminal A and HER2 subtypes. DCIS and IBC were distinguished on the basis of cell signaling and apoptosis-related ions [fatty acids (341.2100 and 382.3736 m/z) and glycerophospholipids (PE (P-16:0/22:6, m/z 746.5099, and PS (38:3), m/z 812.5440)]. In summary, DESI-MSI identified distinct lipid composition between DCIS and IBC and across molecular subtypes of breast cancer, with potential implications for breast cancer pathogenesis. SIGNIFICANCE: These findings present the first in situ metabolomic findings of the four molecular subtypes of breast cancer, DCIS, and normal tissue, and add to the understanding of their pathogenesis.

Metabolite therapy guided by liquid biopsy proteomics delays retinal neurodegeneration.

BackgroundNeurodegenerative diseases are incurable disorders caused by progressive neuronal cell death. Retinitis pigmentosa (RP) is a blinding neurodegenerative disease that results in photoreceptor death and progresses to the loss of the entire retinal network. We previously found that proteomic analysis of the adjacent vitreous served as way to indirectly biopsy the retina and identify changes in the retinal proteome.MethodsWe analyzed protein expression in liquid vitreous biopsies from autosomal recessive (ar)RP patients with PDE6A mutations and arRP mice with Pde6ɑ mutations. Proteomic analysis of retina and vitreous samples identified molecular pathways affected at the onset of photoreceptor death. Based on affected molecular pathways, arRP mice were treated with a ketogenic diet or metabolites involved in fatty-acid synthesis, oxidative phosphorylation, and the tricarboxylic acid (TCA) cycle.FindingsDietary supplementation of a single metabolite, ɑ-ketoglutarate, increased docosahexaeonic acid levels, provided neuroprotection, and enhanced visual function in arRP mice. A ketogenic diet delayed photoreceptor cell loss, while vitamin B supplementation had a limited effect. Finally, desorption electrospray ionization mass spectrometry imaging (DESI-MSI) on ɑ-ketoglutarate-treated mice revealed restoration of metabolites that correlated with our proteomic findings: uridine, dihydrouridine, and thymidine (pyrimidine and purine metabolism), glutamine and glutamate (glutamine/glutamate conversion), and succinic and aconitic acid (TCA cycle).InterpretationThis study demonstrates that replenishing TCA cycle metabolites via oral supplementation prolongs retinal function and provides a neuroprotective effect on the photoreceptor cells and inner retinal network.FundingNIH grants [R01EY026682, R01EY024665, R01EY025225, R01EY024698, R21AG050437, P30EY026877, 5P30EY019007, R01EY018213, F30EYE027986, T32GM007337, 5P30CA013696], NSF grant CHE-1734082.

Identification of diagnostic metabolic signatures in clear cell renal cell carcinoma using mass spectrometry imaging.

Clear cell renal cell carcinoma (ccRCC) is the most common and lethal subtype of kidney cancer. Intraoperative frozen section (IFS) analysis is used to confirm the diagnosis during partial nephrectomy. However, surgical margin evaluation using IFS analysis is time consuming and unreliable, leading to relatively low utilization. In our study, we demonstrated the use of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) as a molecular diagnostic and prognostic tool for ccRCC. DESI-MSI was conducted on fresh-frozen 23 normal tumor paired nephrectomy specimens of ccRCC. An independent validation cohort of 17 normal tumor pairs was analyzed. DESI-MSI provides two-dimensional molecular images of tissues with mass spectra representing small metabolites, fatty acids and lipids. These tissues were subjected to histopathologic evaluation. A set of metabolites that distinguish ccRCC from normal kidney were identified by performing least absolute shrinkage and selection operator (Lasso) and log-ratio Lasso analysis. Lasso analysis with leave-one-patient-out cross-validation selected 57 peaks from over 27,000 metabolic features across 37,608 pixels obtained using DESI-MSI of ccRCC and normal tissues. Baseline Lasso of metabolites predicted the class of each tissue to be normal or cancerous tissue with an accuracy of 94 and 76%, respectively. Combining the baseline Lasso with the ratio of glucose to arachidonic acid could potentially reduce scan time and improve accuracy to identify normal (82%) and ccRCC (88%) tissue. DESI-MSI allows rapid detection of metabolites associated with normal and ccRCC with high accuracy. As this technology advances, it could be used for rapid intraoperative assessment of surgical margin status.

DESI-MSI and METASPACE indicates lipid abnormalities and altered mitochondrial membrane components in diabetic renal proximal tubules.

Diabetic kidney disease (DKD) is the most prevalent complication in diabetic patients, which contributes to high morbidity and mortality. Urine and plasma metabolomics studies have been demonstrated to provide valuable insights for DKD. However, limited information on spatial distributions of metabolites in kidney tissues have been reported. In this work, we employed an ambient desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) coupled to a novel bioinformatics platform (METASPACE) to characterize the metabolome in a mouse model of DKD. DESI-MSI was performed for spatial untargeted metabolomics analysis in kidneys of mouse models (F1 C57BL/6J-Ins2Akita male mice at 17weeks of age) of type 1 diabetes (T1D, n = 5) and heathy controls (n = 6). Multivariate analyses (i.e., PCA and PLS-DA (a 2000 permutation test: P < 0.001)) showed clearly separated clusters for the two groups of mice on the basis of 878 measured m/z's in kidney cortical tissues. Specifically, mice with T1D had increased relative abundances of pseudouridine, accumulation of free polyunsaturated fatty acids (PUFAs), and decreased relative abundances of cardiolipins in cortical proximal tubules when compared with healthy controls. Results from the current study support potential key roles of pseudouridine and cardiolipins for maintaining normal RNA structure and normal mitochondrial function, respectively, in cortical proximal tubules with DKD. DESI-MSI technology coupled with METASPACE could serve as powerful new tools to provide insight on fundamental pathways in DKD.

Spatiochemically Profiling Microbial Interactions with Membrane Scaffolded Desorption Electrospray Ionization-Ion Mobility-Imaging Mass Spectrometry and Unsupervised Segmentation.

Imaging the inventory of microbial small molecule interactions provides important insights into microbial chemical ecology and human medicine. Herein we demonstrate a new method for enhanced detection and analysis of metabolites present in interspecies interactions of microorganisms on surfaces. We demonstrate that desorption electrospray ionization-imaging mass spectrometry (DESI-IMS) using microporous membrane scaffolds (MMS) enables enhanced spatiochemical analyses of interacting microbes among tested sample preparation techniques. Membrane scaffolded DESI-IMS has inherent advantages compared to matrix-assisted laser desorption ionization (MALDI) and other IMS methods through direct IMS analyses of microbial chemistry in situ. This rapid imaging method yields sensitive MS analyses with unique m/z measurements when compared to liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS) via unmediated sampling by MMS DESI-IMS. Unsupervised segmentation imaging analysis of acquired DESI-IMS data reveals distinct chemical regions corresponding to intermicrobial phenomenon such as predation and communication. We validate the method by linking Myxovirescin A and DKxanthene-560 to their known biological roles of predation and phase variation, respectively. In addition to providing the first topographic locations of known natural products, we prioritize 54 unknown features using segmentation within the region of predation. Thus, DESI-IMS and unsupervised segmentation spatially annotates the known biology of myxobacteria and provides functional exploration of newly uncharacterized small molecules.

Preoperative metabolic classification of thyroid nodules using mass spectrometry imaging of fine-needle aspiration biopsies

Thyroid neoplasia is common and requires appropriate clinical workup with imaging and fine-needle aspiration (FNA) biopsy to evaluate for cancer. Yet, up to 20% of thyroid nodule FNA biopsies will be indeterminate in diagnosis based on cytological evaluation. Genomic approaches to characterize the malignant potential of nodules showed initial promise but have provided only modest improvement in diagnosis. Here, we describe a method using metabolic analysis by desorption electrospray ionization mass spectrometry (DESI-MS) imaging for direct analysis and diagnosis of follicular cell-derived neoplasia tissues and FNA biopsies. DESI-MS was used to analyze 178 tissue samples to determine the molecular signatures of normal, benign follicular adenoma (FTA), and malignant follicular carcinoma (FTC) and papillary carcinoma (PTC) thyroid tissues. Statistical classifiers, including benign thyroid versus PTC and benign thyroid versus FTC, were built and validated with 114,125 mass spectra, with accuracy assessed in correlation with clinical pathology. Clinical FNA smears were prospectively collected and analyzed using DESI-MS imaging, and the performance of the statistical classifiers was tested with 69 prospectively collected clinical FNA smears. High performance was achieved for both models when predicting on the FNA test set, which included 24 nodules with indeterminate preoperative cytology, with accuracies of 93% and 89%. Our results strongly suggest that DESI-MS imaging is a valuable technology for identification of malignant potential of thyroid nodules.

Dietary Intake of Green Nut Oil or DHA Ameliorates DHA Distribution in the Brain of a Mouse Model of Dementia Accompanied by Memory Recovery.

Docosahexaenoic acid (DHA), an omega-3 polyunsaturated fatty acid, has significant health benefits. Previous studies reported decreased levels of DHA and DHA-containing phosphatidylcholines in the brain of animals suffering from Alzheimer’s disease, the most common type of dementia; furthermore, DHA supplementation has been found to improve brain DHA levels and memory efficiency in dementia. Oil extracted from the seeds of Plukenetia volubilis (green nut oil; GNO) is also expected to have DHA like effects as it contains approximately 50% α-linolenic acid, a precursor of DHA. Despite this, changes in the spatial distribution of DHA in the brain of animals with dementia following GNO or DHA supplementation remain unexplored. In this study, desorption electrospray ionization imaging mass spectrometry (DESI-IMS) was applied to observe the effects of GNO or DHA supplementation upon the distribution of DHA in the brain of male senescence-accelerated mouse-prone 8 (SAMP8) mice, a mouse model of dementia. DESI-IMS revealed that brain DHA distribution increased 1.85-fold and 3.67-fold in GNO-fed and DHA-fed SAMP8 mice, respectively, compared to corn oil-fed SAMP8 mice. Memory efficiency in SAMP8 mice was also improved by GNO or DHA supplementation. In summary, this study suggests the possibility of GNO or DHA supplementation for the prevention of dementia.

Spatial Mapping of Cellular Metabolites Using DESI Ion Mobility Mass Spectrometry.

Spatial mapping of cellular metabolites, such as neurotransmitters and lipids, on the tissue, can increase our understanding of the biological functions of those molecules. Mass spectrometry imaging (MSI) techniques, such as desorption electrospray ionization (DESI), have not demonstrated the ability to perform metabolite analysis at mammalian single cell level yet. However, they can be a valuable tool to provide insight into cellular metabolism in a very small population (tens) of cells. DESI MSI, coupled with ion mobility separation, improves the peak capacity and signal-to-noise ratio of detected analytes by separating a molecule of interest from interfering isobaric species found in a complex biological matrix. Here we present a protocol for mapping cellular metabolites neurotransmitters, such as serotonin, adenosine, and glutamine directly in brain tissue samples using DESI MSI.

The MYC Oncogene Cooperates with Sterol-Regulated Element-Binding Protein to Regulate Lipogenesis Essential for Neoplastic Growth

Lipid metabolism is frequently perturbed in cancers, but the underlying mechanism is unclear. We present comprehensive evidence that oncogene MYC, in collaboration with transcription factor sterol-regulated element-binding protein (SREBP1), regulates lipogenesis to promote tumorigenesis. We used human and mouse tumor-derived cell lines, tumor xenografts, and four conditional transgenic mouse models of MYC-induced tumors to show that MYC regulates lipogenesis genes, enzymes, and metabolites. We found that MYC induces SREBP1, and they collaborate to activate fatty acid (FA) synthesis and drive FA chain elongation from glucose and glutamine. Further, by employing desorption electrospray ionization mass spectrometry imaging (DESI-MSI), we observed invivo lipidomic changes upon MYC induction across different cancers, for example, aglobal increase in glycerophosphoglycerols. After inhibition of FA synthesis, tumorigenesis was blocked, and tumors regressed in both xenograft and primary transgenic mouse models, revealing the vulnerability of MYC-induced tumors to the inhibition of lipogenesis.

Discovery of lipid biomarkers correlated with disease progression in clear cell renal cell carcinoma using desorption electrospray ionization imaging mass spectrometry.

Clear cell renal cell carcinoma (ccRCC) often results in recurrence or metastasis, and there are only a few clinically effective biomarkers for early diagnosis and personalized therapy. Metabolic changes have been widely studied using mass spectrometry (MS) of tissue lysates to identify novel biomarkers. Our objective was to identify lipid biomarkers that can predict disease progression in ccRCC by a tissue-based approach. We retrospectively investigated lipid molecules in cancerous tissues and normal renal cortex tissues obtained from patients with ccRCC (n = 47) using desorption electrospray ionization imaging mass spectrometry (DESI-IMS). We selected eight candidate lipid biomarkers showing higher signal intensity in cancerous than in normal tissues, with a clear distinction of the tissue type based on the images. Of these candidates, low maximum intensity ratio (cancerous/normal) values of ions of oleic acid, m/z 389.2, and 391.3 significantly correlated with shorter progression-free survival compared with high maximum intensity ratio values (P = 0.011, P = 0.022, and P < 0.001, respectively). This study identified novel lipid molecules contributing to the prediction of disease progression in ccRCC using DESI-IMS. Our findings on lipid storage may provide a new diagnostic or therapeutic strategy for targeting cancer cell metabolism.

Surface chemical defence of the eelgrass Zostera marina against microbial foulers

Plants rely on both mechanical and chemical defence mechanisms to protect their surfaces against microorganisms. The recently completed genome of the eelgrass Zostera marina, a marine angiosperm with fundamental importance for coastal ecosystems, showed that its re-adaptation from land to the sea has led to the loss of essential genes (for chemical communication and defence) and structural features (stomata and thick cuticle) that are typical of terrestrial plants. This study was designed to understand the molecular nature of surface protection and fouling-control strategy of eelgrass against marine epiphytic yeasts. Different surface extraction methods and comparative metabolomics by tandem mass spectrometry (LC-MS/MS) were used for targeted and untargeted identification of the metabolite profiles of the leaf surface and the whole tissue extracts. Desorption electrospray ionization-imaging mass spectrometry (DESI-IMS) coupled with traditional bioassays revealed, for the first time, the unique spatial distribution of the eelgrass surface-associated phenolics and fatty acids, as well as their differential bioactivity against the growth and settlement of epiphytic yeasts. This study provides insights into the complex chemical defence system of the eelgrass leaf surface. It suggests that surface-associated metabolites modulate biotic interactions and provide chemical defence and structural protection to eelgrass in its marine environment.

Lipid dynamics in LPS-induced neuroinflammation by DESI-MS imaging

It is well-established that bacterial lipopolysaccharides (LPS) can promote neuroinflammation through receptor Toll-like 4 activation and induces sickness behavior in mice. This phenomenon triggers changes in membranes lipid dynamics to promote the intracellular cell signaling. Desorption electrospray ionization mass spectrometry (DESI-MS) is a powerful technique that can be used to image the distribution of lipids in the brain tissue directly. In this work, we characterize the LPS-induced neuroinflammation and the lipid dynamics in C57BL/6 mice at 3 and 24 h after LPS injection. We have observed that intraperitoneal administration of LPS (5 mg/kg body weight) induces sickness behavior and triggers a peripheral and cerebral increase of pro- and anti-inflammatory cytokine levels after 3 h, but only IL-10 was upregulated after 24 h. Morphological analysis of hypothalamus, cortex and hippocampus demonstrated that microglial activation was present after 24 h of LPS injection, but not at 3 h. DESI-MS revealed a total of 14 lipids significantly altered after 3 and 24 h and as well as their neuroanatomical distribution. Multivariate statistical analyzes have shown that ions associated with phosphatidylethanolamine [PE(38:4)] and docosatetraenoic acid [FA (22:4)] could be used as biomarkers to distinguish samples from the control or LPS treated groups. Finally, our data demonstrated that monitoring cerebral lipids dynamics and its neuroanatomical distribution can be helpful to understand sickness behavior and microglial activation after LPS administration.

Increased throughput and ultra-high mass resolution in DESI FT-ICR MS imaging through new-generation external data acquisition system and advanced data processing approaches

Desorption electrospray ionisation-mass spectrometry imaging (DESI-MSI) is a powerful imaging technique for the analysis of complex surfaces. However, the often highly complex nature of biological samples is particularly challenging for MSI approaches, as options to appropriately address molecular complexity are limited. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) offers superior mass accuracy and mass resolving power, but its moderate throughput inhibits broader application. Here we demonstrate the dramatic gains in mass resolution and/or throughput of DESI-MSI on an FT-ICR MS by developing and implementing a sophisticated data acquisition and data processing pipeline. The presented pipeline integrates, for the first time, parallel ion accumulation and detection, post-processing absorption mode Fourier transform and pixel-by-pixel internal re-calibration. To achieve that, first, we developed and coupled an external high-performance data acquisition system to an FT-ICR MS instrument to record the time-domain signals (transients) in parallel with the instrument’s built-in electronics. The recorded transients were then processed by the in-house developed computationally-efficient data processing and data analysis software. Importantly, the described pipeline is shown to be applicable even to extremely large, up to 1 TB, imaging datasets. Overall, this approach provides improved analytical figures of merits such as: (i) enhanced mass resolution at no cost in experimental time; and (ii) up to 4-fold higher throughput while maintaining a constant mass resolution. Using this approach, we not only demonstrate the record 1 million mass resolution for lipid imaging from brain tissue, but explicitly show such mass resolution is required to resolve the complexity of the lipidome.

Assessing the Spatial Distribution of Key Flavonoids in Mentha × piperita Leaves: An Application of Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI-MSI)

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) was used to assess the spatial distribution of some key flavonoids in peppermint (Mentha × piperita L.) leaves. The chemical images were generated by applying DESI-MSI on the peppermint leaves imprinting while acquiring the spectra in the negative ion mode. The following key flavonoids were detected and grouped within well-known biosynthetic routes in plants: naringenin route [naringenin, sakuranetin, hesperetin, hesperidin, luteolin, and apigenin]; luteolin route [luteolin, chrysoeriol, luteolin-7-O-D-glucuronide, luteolin-7-O-D-glucoside, luteolin-7-O-neohesperidoside]; apigenin route [apigenin, apigenin-7-O-gentiobioside, apigenin-7-O-neohesperidoside, thymusin/pilosin, pebrellin, acacetin/genkwanin, ladanein, xanthomicrol/pedunculin/nevadensin]. Maps of the spatial distribution of these flavonoids throughout the peppermint leaves within each route were then displayed. The results described herein comprise an important (although still underexplored) subject that certainly will experience a remarkable growth in the next years.