Spatial Metabolomics Research Articles

Investigation of the active ingredients of Shuangshen Ningxin Fomula and the mechanism underlying their protective effects against myocardial ischemia-reperfusion injury by mass spectrometric imaging

BackgroundTraditional Chinese medicine, particularly Shuangshen Ningxin Capsule (SSNX), has been studied intensely. SSNX includes total ginseng saponins (from Panax ginseng Meyer), total phenolic acids from Salvia miltiorrhiza Bunge, and total alkaloids from Corydalis yanhusuo W. T. Wang. It has been suggested to protect against myocardial ischemia by a mechanism that has not been fully elucidated. MethodsThe composition and content of SSNX were determined by UHPLC-Q-TOFQ-TOF / MS. Then, a rat model of myocardial ischemia-reperfusion injury was established, and the protective effect of SSNX was measured. The protective mechanism was investigated using spatial metabolomics. ResultsWe found that SSNX significantly improved left ventricular function and ameliorated pathological damages in rats with myocardial ischemia-reperfusion injury. Using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), the protective mechanism of SSNX was examined by comparing the monomer components of drugs targeted in myocardial tissue with the distribution of myocardial energy metabolism-related molecules and phospholipids. Interestingly, some lipids display inconsistent content distribution in the myocardial ischemia risk and non-risk zones. These discrepancies reflect the degree of myocardial injury in different regions. ConclusionThese findings suggest that SSNX protects against myocardial ischemia-reperfusion injury by correcting abnormal myocardial energy metabolism, changing the levels and distribution patterns of phospholipids, and stabilizing the structure of the myocardial cell membrane. MALDI-TOF MS can detect the spatial distribution of small molecule metabolites in the myocardium and can be used in pharmacological research.

Spatial metabolomics identifies distinct tumor-specific and stroma-specific subtypes in patients with lung squamous cell carcinoma

Molecular subtyping of lung squamous cell carcinoma (LUSC) has been performed at the genomic, transcriptomic, and proteomic level. However, LUSC stratification based on tissue metabolomics is still lacking. Combining high-mass-resolution imaging mass spectrometry with consensus clustering, four tumor- and four stroma-specific subtypes with distinct metabolite patterns were identified in 330 LUSC patients. The first tumor subtype T1 negatively correlated with DNA damage and immunological features including CD3, CD8, and PD-L1. The same features positively correlated with the tumor subtype T2. Tumor subtype T4 was associated with high PD-L1 expression. Compared with the status of subtypes T1 and T4, patients with subtype T3 had improved prognosis, and T3 was an independent prognostic factor with regard to UICC stage. Similarly, stroma subtypes were linked to distinct immunological features and metabolic pathways. Stroma subtype S4 had a better prognosis than S2. Subsequently, analyses based on an independent LUSC cohort treated by neoadjuvant therapy revealed that the S2 stroma subtype was associated with chemotherapy resistance. Clinically relevant patient subtypes as determined by tissue-based spatial metabolomics are a valuable addition to existing molecular classification systems. Metabolic differences among the subtypes and their associations with immunological features may contribute to the improvement of personalized therapy.

Untargeted and spatial-resolved metabolomics characterize serum and tissue-specific metabolic reprogramming in acute kidney injury

BackgroundAcute kidney injury (AKI) is one of the most common clinical emergencies characterized by rapid progression, difficulty in early diagnosis, and high mortality. Currently, there are no effective AKI early diagnostic methods and treatments. Therefore, identifying new mechanisms of AKI have become urgent for development new targets for early diagnosis and treatment of AKI in the current clinical setting. MethodsIn this study, systematic analysis and comparison of serum metabolic profiles of clinical AKI patients, chronic kidney disease (CKD) patients, and healthy subjects were performed using untargeted metabolomics. Moreover, the first spatial metabolomic analysis of kidney tissues in an AKI mouse model using MALDI-TOF MS technology was conducted. Differentially expressed metabolites were identified using a comprehensive, publicly available database. The metabolic data obtained were evaluated using principal component analysis, (orthogonal) partial least squares discriminant analysis, and metabolic pathway analysis to explore the unique serum metabolic profile of the patients, as well as to characterize the spatial distribution of differential metabolites in the kidneys of AKI mice. ResultsSignificant changes in the metabolite levels of amino acids, carnitine, and lipids were observed in the AKI and CKD groups versus the healthy population, suggesting that kidney injury may lead to abnormalities in various metabolic pathways, such as amino acids, fatty acids, and lipids. The significant difference between the AKI and CKD groups were found for the first time in these indexes including amino acid, carnitine, fatty acid, and lipid levels. Additionally, spatial metabolomics results revealed that amino acid, carnitine, organic acid, and fatty acid metabolites were more likely significantly altered in the renal cortex, while lipid metabolites were both differentially distributed in the cortex and medulla of the AKI group. ConclusionAbnormalities in the serum metabolism of amino acids, carnitine, and lipids in patients with kidney diseases, such as AKI and CKD, are closely associated with the physiological dysfunction of kidney injury. Metabolic differences between patients with AKI and CKD were compared for the first time, showing that fatty acid oxidative inhibition was more severe in patients with AKI. Furthermore, spatial metabolomics has revealed metabolic reprogramming with tissue heterogeneity in AKI mice model. Our study provides valuable information in the molecular pathological features of AKI in the kidney tissues.

Spatial Metabolomics Identifies Novel Glomerular Metabolite Signatures of Normal and Diabetic Kidneys

Spatial Metabolomics Identifies Novel Glomerular Metabolite Signatures of Normal and Diabetic Kidneys

Sample Preparation Method for MALDI Mass Spectrometry Imaging of Fresh-Frozen Spines.

Technologies assessing the lipidomics, genomics, epigenomics, transcriptomics, and proteomics of tissue samples at single-cell resolution have deepened our understanding of physiology and pathophysiology at an unprecedented level of detail. However, the study of single-cell spatial metabolomics in undecalcified bones faces several significant challenges, such as the fragility of bone, which often requires decalcification or fixation leading to the degradation or removal of lipids and other molecules. As such, we describe a method for performing mass spectrometry imaging on undecalcified spine that is compatible with other spatial omics measurements. In brief, we use fresh-frozen rat spines and a system of carboxyl methylcellulose embedding, cryofilm, and polytetrafluoroethylene rollers to maintain tissue integrity while avoiding signal loss from variations in laser focus and artifacts from traditional tissue processing. This reveals various tissue types and lipidomic profiles of spinal regions at 10 μm spatial resolutions using matrix-assisted laser desorption/ionization mass spectrometry imaging. We expect this method to be adapted and applied to the analysis of the spinal cord, shedding light on the mechanistic aspects of cellular heterogeneity, development, and disease pathogenesis underlying different bone-related conditions and diseases. This study furthers the methodology for high spatial metabolomics of spines and adds to the collective efforts to achieve a holistic understanding of diseases via single-cell spatial multiomics.

Adenine crosses the biomarker bridge: from 'omics to treatment in diabetic kidney disease.

Enabling the early detection and prevention of diabetic kidney damage has potential to substantially reduce the global burden of kidney failure. There is a critical need for identification of mechanistic biomarkers that can predict progression and serve as therapeutic targets. In this issue of the JCI, Sharma and colleagues used an integrated multiomics approach to identify the metabolite adenine as a noninvasive biomarker of progression in early diabetic kidney disease (DKD). The highest tertile of urine adenine/creatinine ratio (UAdCR) was associated with higher risk for end-stage kidney disease and mortality across independent cohorts, including participants with early DKD without macroalbuminuria. Spatial metabolomics, single-cell transcriptomics, and experimental studies localized adenine to regions of tubular pathology and implicated the mTOR pathway in adenine-mediated tissue fibrosis. Inhibition of endogenous adenine production was protective in a diabetic model. These findings exemplify the potential for multiomics to uncover mechanistic biomarkers and targeted therapies in DKD.

Endogenous adenine mediates kidney injury in diabetic models and predicts diabetic kidney disease in patients.

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality; however, few mechanistic biomarkers are available for high-risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from the Chronic Renal Insufficiency Cohort (CRIC) study, the Singapore Study of Macro-angiopathy and Micro-vascular Reactivity in Type 2 Diabetes (SMART2D), and the American Indian Study determined whether urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in the CRIC study and SMART2D. ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in the CRIC study, SMART2D, and the American Indian study. Empagliflozin lowered UAdCR in nonmacroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology, and single-cell transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mTOR. Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

Global and Spatial Metabolomics of Individual Cells Using a Tapered Pneumatically Assisted nano-DESI Probe.

Single-cell metabolomics has the potential to reveal unique insights into intracellular mechanisms and biological processes. However, the detection of metabolites from individual cells is challenging due to their versatile chemical properties and concentrations. Here, we demonstrate a tapered probe for pneumatically assisted nanospray desorption electrospray ionization (PA nano-DESI) mass spectrometry that enables both chemical imaging of larger cells and global metabolomics of smaller 15 μm cells. Additionally, by depositing cells in predefined arrays, we show successful metabolomics from three individual INS-1 cells per minute, which enabled the acquisition of data from 479 individual cells. Several cells were used to optimize analytical conditions, and 93 or 97 cells were used to monitor metabolome alterations in INS-1 cells after exposure to a low or high glucose concentration, respectively. Our analytical approach offers insights into cellular heterogeneity and provides valuable information about cellular processes and responses in individual cells.

Unveiling targeted spatial metabolome of rice seed at the dough stage using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry imaging

Rice (Oryza sativa) seeds contain a variety of metabolites, which not only provide energy for their own growth and development, but also are an important source of nutrition for humans. It is crucial to study the distribution of metabolites in rice seeds, but the spatial metabolome of rice seeds is rarely investigated. In this study, Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry (MALDI-MS) imaging was used to reveal the spatial distribution of free soluble sugars (glucose, fructose, sucrose, and maltose), amino acids (9 essential amino acids and 2 amino acids affecting rice eating quality: L-aspartic acid and L-glutamic acid), and 4 metabolites in the flavonoids synthesis pathway (cinnamic acid, naringenin chalcone, naringenin, and dihydrokaempferol) in rice seed at the dough stage. It was found that the 4 free soluble sugars present similar spatial distribution, mainly distributed in the seed cortex and embryo with high abundance. The majority of amino acids are also concentrated in the rice cortex and embryo, while the others are abundant in the whole seed. Besides cinnamic acid distributed in the seed cortex and embryo, the naringenin chalcone, naringenin, and dihydrokaempferol were also found in the endosperm and had lower content. Furthermore, a colocalization phylogenetic tree according to the spatial distribution imaging of each metabolite was constructed. This study revealed the distribution diversity of metabolites in different segmentations of rice seed at the dough stage, providing clues for the nutritional differences between brown rice and white rice, and serving as a reference for people to target a healthy diet.

Spatial metabolomics method to reveal differential metabolomes in microregions of Panax quinquefolius roots by using ultra-performance liquid chromatography quadrupole/time of flight-mass spectrometry and desorption electrospray ionization mass spectrometry imaging

Panax quinquefolius is a natural homology medicine and food that is rich in bioactive ingredients, such as ginsenosides and polysaccharides. The combination of ultra-performance liquid chromatography quadrupole/time of flight-mass spectrometry (UPLC-Q-TOF/MS) and desorption electrospray ionization mass spectrometry imaging (DESI-MSI) was used for the first time in a spatial metabolomics analysis to comprehensively evaluate the differential components in different microregions of P. quinquefolius. UPLC-Q-TOF/MS and DESI-MSI combined with principal component analysis and orthogonal partial least squares-discriminant analysis were used to screen differential metabolites. UPLC-Q-TOF/MS and DESI-MSI screened 27 and 23 differential metabolites, respectively, among which 15 differential metabolites were identified by both methods. It was found that some components, such as ginsenoside Rg1 and malonyl-ginsenoside Rc, were mainly distributed in P of the transverse slice of P. quinquefolius roots, while ginsenoside Ro and malonyl-ginsenoside Rd were mainly distributed in C. The methods and results of this study could be used to understand the precise localization, biosynthesis, and biological functions of special metabolites in P. quinquefolius.

Insights from multi-omics integration into seed germination of Taxus chinensis var mairei

The transition from deep dormancy to seed germination is essential for the life cycle of plants, but how this process occurs in the gymnosperm Chinese yew (Taxus chinensis var mairei), the natural source of the anticancer drug paclitaxel, remains unclear. Herein, we analyse the transcriptome, proteome, spatial metabolome, and spatial lipidome of the Chinese yew and present the multi-omics profiles of dormant and germinating seeds. Our results show that abscisic acid and gibberellic acid 12 homoeostasis is closely associated with gene transcription and protein translation, and the balance between these phytohormones thereby determines if seeds remain dormant or germinate. We find that an energy supply of carbohydrates from glycolysis and the TCA cycle feed into the pentose phosphate pathway during seed germination, and energy supplied from lipids are mainly derived from the lipolysis of triacylglycerols. Using mass spectrometry imaging, we demonstrate that the spatial distribution of plant hormones and phospholipids has a remarkable influence on embryo development. We also provide an atlas of the spatial distribution of paclitaxel C in Chinese yew seeds for the first time. The data from this study enable exploration of the germination mechanism of Chinese yew seeds across several omics levels.

Applications and advances of spatial metabolomics in oncology research

Applications and advances of spatial metabolomics in oncology research

Spatial metabolomics: from a niche field towards a driver of innovation.

Spatial metabolomics: from a niche field towards a driver of innovation.

Spatial Metabolomics Reveals the Multifaceted Nature of Lamprey Buccal Gland and Its Diverse Mechanisms for Blood-Feeding

Lampreys are blood-sucking vampires in marine environments. From a survival perspective, it is expected that the lamprey buccal gland exhibits a repository of pharmacologically active components to modulate the host’s homeostasis, inflammatory and immune responses. By analyzing the metabolic profiles of 14 different lamprey tissues, we show that two groups of metabolites in the buccal gland of lampreys, prostaglandins and the kynurenine pathway metabolites, can be injected into the host fish to assist lamprey blood feeding. Prostaglandins are well-known blood-sucking-associated metabolites that act as vasodilators and anticoagulants to maintain vascular homeostasis and are involved in inflammatory responses. The vasomotor reactivity test on catfish aortic ring showed that kynurenine can also relax the blood vessels of the host fish, thus improving the blood flow of the host fish at the bite site. Finally, a lamprey spatial metabolomics database (https://www.lampreydb.com) was constructed to assist studies using lampreys as animal model.

Metabolic heterogeneity in adrenocortical carcinoma impacts patient outcomes.

Spatially resolved metabolomics enables the investigation of tumoral metabolites in situ. Inter- and intratumor heterogeneity are key factors associated with patient outcomes. Adrenocortical carcinoma (ACC) is an exceedingly rare tumor associated with poor survival. Its clinical prognosis is highly variable, but the contributions of tumor metabolic heterogeneity have not been investigated thus far to our knowledge. An in-depth understanding of tumor heterogeneity requires molecular feature-based identification of tumor subpopulations associated with tumor aggressiveness. Here, using spatial metabolomics by high-mass resolution MALDI Fourier transform ion cyclotron resonance mass spectrometry imaging, we assessed metabolic heterogeneity by de novo discovery of metabolic subpopulations and Simpson's diversity index. After identification of tumor subpopulations in 72 patients with ACC, we additionally performed a comparison with 25 tissue sections of normal adrenal cortex to identify their common and unique metabolic subpopulations. We observed variability of ACC tumor heterogeneity and correlation of high metabolic heterogeneity with worse clinical outcome. Moreover, we identified tumor subpopulations that served as independent prognostic factors and, furthermore, discovered 4 associated anticancer drug action pathways. Our research may facilitate comprehensive understanding of the biological implications of tumor subpopulations in ACC and showed that metabolic heterogeneity might impact chemotherapy.

Strigolactones repress nodule development and senescence in pea.

Strigolactones are a class of phytohormones that are involved in many different plant developmental processes, including the rhizobium-legume nodule symbiosis. Although both positive and negative effects of strigolactones on the number of nodules have been reported, the influence of strigolactones on nodule development is still unknown. Here, by means of the ramosus (rms) mutants of Pisum sativum (pea) cv Terese, we investigated the impact of strigolactone biosynthesis (rms1 and rms5) and signaling (rms3 and rms4) mutants on nodule growth. The rms mutants had more red, that is, functional, and larger nodules than the wild-type plants. Additionally, the increased nitrogen fixation and senescence zones with consequently reduced meristematic and infection zones indicated that the rms nodules developed faster than the wild-type nodules. An enhanced expression of the nodule zone-specific molecular markers for meristem activity and senescence supported the enlarged, fast maturing nodules. Interestingly, the master nodulation regulator, NODULE INCEPTION, NIN, was strongly induced in nodules of all rms mutants but not prior to inoculation. Determination of sugar levels with both bulk and spatial metabolomics in roots and nodules, respectively, hints at slightly increased malic acid levels early during nodule primordia formation and reduced sugar levels at later stages, possibly the consequence of an increased carbon usage of the enlarged nodules, contributing to the enhanced senescence. Taken together, these results suggest that strigolactones regulate the development of nodules, which is probably mediated through NIN, and available plant sugars.

Expanded Coverage of Phytocompounds by Mass Spectrometry Imaging Using On-Tissue Chemical Derivatization by 4-APEBA.

Probing the entirety of any species metabolome is an analytical grand challenge, especially on a cellular scale. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a common spatial metabolomics assay, but this technique has limited molecular coverage for several reasons. To expand the application space of spatial metabolomics, we developed an on-tissue chemical derivatization (OTCD) workflow using 4-APEBA for the confident identification of several dozen elusive phytocompounds. Overall, this new OTCD method enabled the annotation of roughly 280 metabolites, with only a 10% overlap in metabolic coverage when compared to analog negative ion mode MALDI-MSI on serial sections. We demonstrate that 4-APEBA outperforms other derivatization agents by providing: (1) broad specificity toward carbonyls, (2) low background, and (3) introduction of bromine isotopes. Notably, the latter two attributes also facilitate more confidence in our bioinformatics for data processing. The workflow detailed here trailblazes a path toward spatial hormonomics within plant samples, enhancing the detection of carboxylates, aldehydes, and plausibly other carbonyls. As such, several phytohormones, which have various roles within stress responses and cellular communication, can now be spatially profiled, as demonstrated in poplar root and soybean root nodule.

Mapping the metabolic responses to oxaliplatin-based chemotherapy with in vivo spatiotemporal metabolomics

Adjuvant chemotherapy improves the survival outlook for patients undergoing operations for lung metastases caused by colorectal cancer (CRC). However, a multidisciplinary approach that evaluates several factors related to patient and tumor characteristics is necessary for managing chemotherapy treatment in metastatic CRC patients with lung disease, as such factors dictate the timing and drug regimen, which may affect treatment response and prognosis. In this study, we explore the potential of spatial metabolomics for evaluating metabolic phenotypes and therapy outcomes during the local delivery of the anticancer drug, oxaliplatin, to the lung. 12 male Yorkshire pigs underwent a 3 h left lung in vivo lung perfusion (IVLP) with various doses of oxaliplatin (7.5, 10, 20, 40, and 80 mg/L), which were administered to the perfusion circuit reservoir as a bolus. Biocompatible solid-phase microextraction (SPME) microprobes were combined with global metabolite profiling to obtain spatiotemporal information about the activity of the drug, determine toxic doses that exceed therapeutic efficacy, and conduct a mechanistic exploration of associated lung injury. Mild and subclinical lung injury was observed at 40 mg/L of oxaliplatin, and significant compromise of the hemodynamic lung function was found at 80 mg/L. This result was associated with massive alterations in metabolic patterns of lung tissue and perfusate, resulting in a total of 139 discriminant compounds. Uncontrolled inflammatory response, abnormalities in energy metabolism, and mitochondrial dysfunction next to accelerated kynurenine and aldosterone production were recognized as distinct features of dysregulated metabolipidome. Spatial pharmacometabolomics may be a promising tool for identifying pathological responses to chemotherapy.

Illustrate the distribution and metabolic regulatory effects of pterostilbene in cerebral ischemia-reperfusion rat brain by mass spectrometry imaging and spatial metabolomics

Pterostilbene is a promising molecule with superior pharmacological activities and pharmacokinetic characteristics compared to its structural analogue resveratrol, which could be used to treat ischemic stroke. However, its mechanism is still unclear. The cutting-edge air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) and spatial metabolomics analysis were applied to investigate the distribution of pterostilbene in ischemic rat brain and the changes of related small molecule metabolic pathways to further explore the potential mechanisms of pterostilbene against cerebral ischemia-reperfusion injury. This research found that pterostilbene could significantly restore cerebral microcirculation blood flow, reduce infarct volume, improve neurological function and ameliorate neuronal damage in ischemic rats. Moreover, pterostilbene was widely and abundantly distributed in ischemic brain tissue, laying a solid foundation for the rescue of ischemic penumbra. Further study revealed that pterostilbene played a therapeutic role in restoring energy supply, rebalancing neurotransmitters, reducing abnormal polyamine accumulation and phospholipid metabolism. These findings offer an opportunity to illustrate novel mechanisms of pterostilbene in the treatment of cerebral ischemia/reperfusion injury resulting from ischemic stroke.

SYST-25 MICROGLIA-SECRETED LIPID SPECIES DRIVE GLIOMA INVASION

Abstract The capacity of gliomas, including GBMs, to invade and infiltrate normal brain tissues makes their complete surgical removal impossible. The most crucial survival predictor is still the extent of surgical resection, urging the need to identify treatments that block the invasive growth of glioma to improve surgical resection and overall survival. Using a combination of single-cell transcriptomics, lipidomics, and high-resolution spatial metabolomics in genetically engineered GBM mouse models, reminiscent of human disease, and validation in human GBM samples, we found that 1) tumor cells infiltrating the normal brain parenchyma associate with and activate specific pathways in microglial cells (MGs), the residential brain macrophages. In turn, MGs undergo metabolic rewiring and secrete lipid species that promote glioma invasion of the different GBM subtypes by activating distinct signaling cues. Thus, blocking the MG-tumor cell axis or metabolic MG rewiring targets several GBM types and, in combination with standard therapy, results in small circumscribed tumors that should be easier excised and lead to a substantial increase in progression-free survival in glioma patients.