Mass Spectrometry Imaging Reveals Elevated Glomerular ATP/AMP in Diabetes/obesity and Identifies Sphingomyelin as a Possible Mediator

The Application of a Random Forest Classifier to ToF-SIMS Imaging Data

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging is a potent analytical tool that provides spatially resolved chemical information on surfaces at the microscale. However, the hyperspectral nature of ToF-SIMS datasets can be challenging to analyze and interpret. Both supervised and unsupervised machine learning (ML) approaches are increasingly useful to help analyze ToF-SIMS data. Random Forest (RF) has emerged as a robust and powerful algorithm for processing mass spectrometry data. This machine learning approach offers several advantages, including accommodating nonlinear relationships, robustness to outliers in the data, managing the high-dimensional feature space, and mitigating the risk of overfitting. The application of RF to ToF-SIMS imaging facilitates the classification of complex chemical compositions and the identification of features contributing to these classifications. This tutorial aims to assist nonexperts in either machine learning or ToF-SIMS to apply Random Forest to complex ToF-SIMS datasets.

Spatial metabolomics using mass-spectrometry imaging to decipher the impact of high red meat diet on the colon metabolome in rat

Colorectal cancer (CRC) is the third most common cancer in the world with a higher prevalence in the developed countries, mainly caused by environmental and lifestyle factors such as diet, particularly red meat consumption. The metabolic impact of high red meat consumption on the epithelial part of the colon was investigated using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MSI), to specifically analyze the epithelial substructure. Ten colons from rats fed for 100 days high red or white meat diet were subjected to untargeted MSI analyses using two spatial resolutions (100 μm and 10 μm) to evaluate metabolite changes in the epithelial part and to visualize the distribution of metabolites of interest within the epithelium crypts. Our results suggest a specific effect of red meat diet on the colonic epithelium metabolism, as evidenced by an increase of purine catabolism products or depletion in glutathione pool, reinforcing the hypothesis of increased oxidative stress with red meat diet. This study also highlighted cholesterol sulfate as another up-regulated metabolite, interestingly localized at the top of the crypts. Altogether, this study demonstrates the feasibility and the added value of using MSI to decipher the effect of high red meat diet on the colonic epithelium.

CAMKK2-AMPK axis endows dietary calcium and phosphorus levels with regulatory effects on lipid metabolism in weaned piglets

BACKGROUND

In the realm of swine production, optimizing body composition and reducing excessive fat accumulation is critical for enhancing both economic efficiency and meat quality. Despite the acknowledged impact of dietary calcium (Ca) and phosphorus (P) on lipid metabolism, the precise mechanisms behind their synergistic effects on fat metabolism remain elusive.

RESULTS

Research observations have shown a decreasing trend in the percentage of crude fat in carcasses with increased calcium and phosphorus content in feed. Concurrently, serum glucose concentrations significantly decreased, though differences in other lipid metabolism-related indicators were not significant across groups. Under conditions of low calcium and phosphorus, there is a significant suppression in the expression of FABPs, CD36 and PPARγ in the jejunum and ileum, leading to inhibited intestinal lipid absorption. Concurrently, this results in a marked increase in lipid accumulation in the liver. Conversely, higher levels of dietary calcium and phosphorus promoted intestinal lipid absorption and reduced liver lipid accumulation, with these changes being facilitated through the activation of the CAMKK2/AMPK signaling pathway by high-calcium-phosphorus diets. Additionally, the levels of calcium and phosphorus in the diet significantly altered the composition of liver lipids and the gut microbiota, increasing α-diversity and affecting the abundance of specific bacterial families related to lipid metabolism.

CONCLUSION

The evidence we provide indicates that the levels of calcium and phosphorus in the diet alter body fat content and lipid metabolism by modulating the response of the gut-liver axis to lipids. These effects are closely associated with the activation of the CAMKK2/AMPK signaling pathway.

Bacterial metabolomics: current applications for human welfare and future aspects

An imbalanced microbiome is linked to several diseases, such as cancer, inflammatory bowel disease, obesity, and even neurological disorders. Bacteria and their by-products are used for various industrial and clinical purposes. The metabolites under discussion were chosen based on their biological impacts on host and gut microbiota interactions as established by metabolome research. The separation of bacterial metabolites by using statistics and machine learning analysis creates new opportunities for applications of bacteria and their metabolites in the environmental and medical sciences. Thus, the metabolite production strategies, methodologies, and importance of bacterial metabolites for human well-being are discussed in this review.

Highly Sensitive Spatial Glycomics at Near-Cellular Resolution by On-Slide Derivatization and Mass Spectrometry Imaging

Glycans on proteins and lipids play important roles in maturation and cellular interactions, contributing to a variety of biological processes. Aberrant glycosylation has been associated with various human diseases including cancer; however, elucidating the distribution and heterogeneity of glycans in complex tissue samples remains a major challenge. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is routinely used to analyze the spatial distribution of a variety of molecules including N-glycans directly from tissue surfaces. Sialic acids are nine carbon acidic sugars that often exist as the terminal sugars of glycans and are inherently difficult to analyze using MALDI-MSI due to their instability prone to in- and postsource decay. Here, we report on a rapid and robust method for stabilizing sialic acid on N-glycans in FFPE tissue sections. The established method derivatizes and identifies the spatial distribution of α2,3- and α2,6-linked sialic acids through complete methylamidation using methylamine and PyAOP ((7-azabenzotriazol-1-yloxy)tripyrrolidinophosphonium hexafluorophosphate). Our in situ approach increases the glycans detected and enhances the coverage of sialylated species. Using this streamlined, sensitive, and robust workflow, we rapidly characterize and spatially localize N-glycans in human tumor tissue sections. Additionally, we demonstrate this method's applicability in imaging mammalian cell suspensions directly on slides, achieving cellular resolution with minimal sample processing and cell numbers. This workflow reveals the cellular locations of distinct N-glycan species, shedding light on the biological and clinical significance of these biomolecules in human diseases.

Imaging Mass Spectrometry and Genome Mining Reveal Antimicrobial Peptides of Novel Pediococcus acidilactici CCFM18

The mechanism of metabolites produced by lactic acid bacteria in mediating microbial interactions has been difficult to ascertain. This study comparatively evaluated the antimicrobial effect of the novel bacterium Pediococcus acidilactici CCFM18 and explored the global chemical view of its interactions with indicator bacteria. P. acidilactici CCFM18 had sufficiently strong antimicrobial activity to effectively inhibit the growth of the indicator bacteria and enhance their intracellular reactive oxygen species (ROS) level. The emerging technique of matrix-assisted laser desorption ionization-time-of-flight (MALDI-TOF) imaging mass spectrometry indicated that P. acidilactici CCFM18 increased the production of pediocin PA-1 and the penocin A profile during its interaction with the indicator bacteria, thus differing from P. acidilactici CCFM28 (a commonly used laboratory strain). Strikingly, the production of coagulin A was triggered only by signaling molecules made by the competing strain L. thermophilus, suggesting an idiosyncratic response from P. acidilactici CCFM18. Bioinformatic mining of the P. acidilactici CCFM18 draft genome sequence revealed gene loci that code for the complex secondary metabolites analyzed via MSI. Taken together, these results illustrate that chemical interactions between P. acidilactici CCFM18 and indicator bacteria exhibit high complexity and specificity and can drive P. acidilactici CCFM18 to produce different secondary metabolites.

Metabolic Analysis and Renal Protective Effects of Linagliptin and Empagliflozin in Alport Syndrome

Key Points

Linagliptin reduces kidney function decline and extends lifespan in Alport syndrome mice. Inhibiting the generation of glucose metabolites could serve as a potential therapeutic strategy for the treatment of Alport syndrome.

Background

We previously demonstrated that empagliflozin (Empa), a sodium-glucose cotransporter-2 inhibitor, reduces intrarenal lipid accumulation and slows kidney function decline in experimental Alport syndrome (AS). In this study, we aimed to evaluate the renal protective benefits of linagliptin (Lina), a dipeptidyl peptidase-4 inhibitor in AS, and compare it with Empa.

Methods

Metabolite distribution in kidney cortices was assessed using mass spectrometry imaging. We examined albuminuria and histological changes in kidneys from AS mice treated with Lina and/or Empa or vehicle.

Results

Several metabolites, including adrenic acid and glucose, were increased in renal cortices of AS mice compared with wild-type (WT) mice, whereas eicosapentaenoic acid levels were decreased. In addition, a redistribution of adrenic acid from the glomerular compartment in WT mice to the tubulointerstitial compartment in AS mice was observed. Both Lina and Empa treatments were found to reduce albuminuria to extend the survival of AS mice for about 10 days and to decrease glomerulosclerosis and tubulointerstitial fibrosis compared with WT mice. There were no significant differences with regard to the renal phenotype observed between Empa- and Lina-treated AS mice, and the combination of Lina and Empa was not superior to individual treatments. In vitro experiments revealed that dipeptidyl peptidase-4 is expressed in podocytes and tubular cells derived from both AS and WT mice. Differently from what we have reported for Empa, Lina treatment was found to reduce glucose-driven respiration in AS tubular cells but not in AS podocytes.

Conclusions

Renal expression patterns and spatial distribution of several metabolites differ in AS compared with WT mice. Although Lina and Empa treatments similarly partially slow the progression of kidney disease in AS, the metabolic mechanisms conferring the protective effect may be different.

Super-resolution techniques for biomedical applications and challenges

Super-resolution (SR) techniques have revolutionized the field of biomedical applications by detailing the structures at resolutions beyond the limits of imaging or measuring tools. These techniques have been applied in various biomedical applications, including microscopy, magnetic resonance imaging (MRI), computed tomography (CT), X-ray, electroencephalogram (EEG), ultrasound, etc. SR methods are categorized into two main types: traditional non-learning-based methods and modern learning-based approaches. In both applications, SR methodologies have been effectively utilized on biomedical images, enhancing the visualization of complex biological structures. Additionally, these methods have been employed on biomedical data, leading to improvements in computational precision and efficiency for biomedical simulations. The use of SR techniques has resulted in more detailed and accurate analyses in diagnostics and research, essential for early disease detection and treatment planning. However, challenges such as computational demands, data interpretation complexities, and the lack of unified high-quality data persist. The article emphasizes these issues, underscoring the need for ongoing development in SR technologies to further improve biomedical research and patient care outcomes.

Oxidized low-density lipoprotein changes the inflammatory status and metabolomics profiles in human and mouse macrophages and microglia

The conjunctiva of primary open angle glaucoma patients showed high level of oxidized low-density lipoprotein (ox-LDL), which is associated with the inflammatory response. Microglia and macrophages are the immune cells involved in retinal ganglion cell survival regulation; yet, their roles of the ox-LDL-induced inflammation in glaucoma remain elusive. Here we aimed to investigate the lipid uptake, inflammatory cytokine expression, and metabolomics profiles of human and murine-derived microglial and macrophage cell lines treated with ox-LDL. Under the same ox-LDL concentration, macrophages exhibited higher lipid uptake and expression of pro-inflammatory cytokines as compared to microglia. The ox-LDL increased the levels of fatty acid metabolites in macrophages and sphingomyelin metabolites in microglia. In summary, this study revealed the heterogeneity in the inflammatory capacity and metabolic profiles of macrophages and microglia under the stimulation of ox-LDL.

Deliverables from Metabolomics in Kidney Disease: Adenine, New Insights, and Implication for Clinical Decision-Making

BACKGROUND

Chronic kidney disease (CKD) presents a persistent global health challenge, characterized by complex pathophysiology and diverse progression patterns. Metabolomics has emerged as a valuable tool in unraveling the intricate molecular mechanisms driving CKD progression.

SUMMARY

This comprehensive review provides a summary of recent progress in the field of metabolomics in kidney disease with a focus on spatial metabolomics to shed important insights to enhancing our understanding of CKD progression, emphasizing its transformative potential in early disease detection, refined risk assessment, and the development of targeted interventions to improve patient outcomes.

KEY MESSAGE

Through an extensive analysis of metabolic pathways and small-molecule fluctuations, bulk and spatial metabolomics offers unique insights spanning the entire spectrum of CKD, from early stages to advanced disease states. Recent advances in metabolomics technology have enabled spatial identification of biomarkers to provide breakthrough discoveries in predicting CKD trajectory and enabling personalized risk assessment. Furthermore, metabolomics can help decipher the complex molecular intricacies associated with kidney diseases for exciting novel therapeutic approaches. A recent example is the identification of adenine as a key marker of kidney fibrosis for diabetic kidney disease using both untargeted and targeted bulk and spatial metabolomics. The metabolomics studies were critical to identify a new biomarker for kidney failure and to guide new therapeutics for diabetic kidney disease. Similar approaches are being pursued for acute kidney injury and other kidney diseases to enhance precision medicine decision-making.

Exploration of the hypoglycemic mechanism of Fuzhuan brick tea based on integrating global metabolomics and network pharmacology analysis

Introduction: Fuzhuan brick tea (FBT) is a worldwide popular beverage which has the appreciable potential in regulating glycometabolism. However, the reports on the hypoglycemic mechanism of FBT remain limited. Methods: In this study, the hypoglycemic effect of FBT was evaluated in a pharmacological experiment based on Kunming mice. Global metabolomics and network pharmacology were combined to discover the potential target metabolites and genes. In addition, the real-time quantitative polymerase chain reaction (RT-qPCR) analysis was performed for verification. Results: Seven potential target metabolites and six potential target genes were screened using the integrated approach. After RT-qPCR analysis, it was found that the mRNA expression of VEGFA, KDR, MAPK14, and PPARA showed significant differences between normal and diabetes mellitus mice, with a retracement after FBT treatment. Conclusion: These results indicated that the hypoglycemic effect of FBT was associated with its anti-inflammatory activities and regulation of lipid metabolism disorders. The exploration of the hypoglycemic mechanism of FBT would be meaningful for its further application and development.

Targeting metabolic reprogramming in hepatocellular carcinoma to overcome therapeutic resistance: A comprehensive review

Hepatocellular carcinoma (HCC) poses a heavy burden on human health with high morbidity and mortality rates. Systematic therapy is crucial for advanced and mid-term HCC, but faces a significant challenge from therapeutic resistance, weakening drug effectiveness. Metabolic reprogramming has gained attention as a key contributor to therapeutic resistance. Cells change their metabolism to meet energy demands, adapt to growth needs, or resist environmental pressures. Understanding key enzyme expression patterns and metabolic pathway interactions is vital to comprehend HCC occurrence, development, and treatment resistance. Exploring metabolic enzyme reprogramming and pathways is essential to identify breakthrough points for HCC treatment. Targeting metabolic enzymes with inhibitors is key to addressing these points. Inhibitors, combined with systemic therapeutic drugs, can alleviate resistance, prolong overall survival for advanced HCC, and offer mid-term HCC patients a chance for radical resection. Advances in metabolic research methods, from genomics to metabolomics and cells to organoids, help build the HCC metabolic reprogramming network. Recent progress in biomaterials and nanotechnology impacts drug targeting and effectiveness, providing new solutions for systemic therapeutic drug resistance. This review focuses on metabolic enzyme changes, pathway interactions, enzyme inhibitors, research methods, and drug delivery targeting metabolic reprogramming, offering valuable references for metabolic approaches to HCC treatment.

Cell and rat serum, urine and tissue metabolomics analysis elucidates the key pathway changes associated with chronic nephropathy and reveals the mechanism of action of rhein

BACKGROUND

Rhein can significantly delay the progression of chronic nephropathy. However, its mechanism of action has not been adequately elaborated, which hinders its extensive clinical application. In this work, the effects of rhein on models of TGF-β-induced NRK-49F cellular fibrosis and rat renal ischemia-reperfusion fibrosis were evaluated using metabolomics and western blotting.

METHODS

The metabolic profiles of NRK-49F cells and rat urine, serum, and kidney tissues in the control, model, and rhein groups were investigated using UPLC-QTOF-MS. The levels of p-P65, p-IKK, p-AKT, p-P38, p-JNK and AP-1 in NRK-49F cells were measured using western blotting and immunofluorescence methods. Molecular docking and network pharmacology methods were employed to explore the relationship between the potential targets of rhein and key proteins in the NF-κB and MAPK signaling pathways.

RESULTS

Various potential metabolites, including sphingolipids, ceramides, phosphatidylcholine, and lysophosphatidylcholine,14-hydroxy-E4-neuroprostane E, and 5-HPETE, were present in the cell, tissue, urine, and serum samples; however, few metabolites matches exactly among the four type of biological samples. These differential metabolites can effectively differentiated between the control, model, and rhein groups. Pathway enrichment analysis of differential metabolites unveiled that sphingolipid metabolism, arachidonic acid metabolism, and glycerophospholipid metabolism were closely related to nephropathy. Phosphorylation levels of AKT, IKK, P65 and AP-1 in NRK-49F cells was reduced by rhein treatment. Network pharmacology and molecular docking showed that the potential targets of rhein might regulated the expression of MAPK and AKT in the NF-κB and MAPK signaling pathways.

CONCLUSION

In brief, rhein might delays the progression of chronic nephropathy via the metabolic pathways, NF-κB and MAPKs signaling pathways, which provides the foundation for its development and clinical application.

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.

Multi-omics reveal mechanisms underlying chronic kidney disease of unknown etiology (CKDu) pathogenesis using zebrafish

Chronic kidney disease of unknown etiology (CKDu) is an endemic disease in the dry zone of farming communities, Sri Lanka. The drinking water in a CKDu prevalent area contains a high concentration of F-, hardness and other environmental pollutants, including heavy metals and microcystin, which are considered possible etiology of CKDu in these areas. Here, multi-omics data with host transcriptome, metabolome and gut microbiomes were obtained using simulated local drinking water of Sri Lanka after their exposure to adult zebrafish. Based on an integrated multi-omics analysis in the context of host physiology in the kidney injury samples with different pathologic grades, two common pathways necroptosis and purine metabolism were identified as potentially important pathways that affect kidney injury. The key metabolite acetyl adenylate in the purine metabolism pathway was significantly positively correlated with Comamonas (rho = 0.72) and significantly negatively correlated with Plesiomonas (rho = -0.58). This crucial metabolite and two key gut bacteria genera may not only be potential markers but also potential therapeutic targets in the uric acid metabolic pathway, which is an important factor in the pathogenesis of acute kidney injury (AKI) in general, as well as of chronic kidney disease (CKD). Based on this, we revealed the urea metabolism pathway of kidney injury in zebrafish and provided a new avenue for the treatment of CKDu in Sri Lanka.

rMSIfragment: improving MALDI-MSI lipidomics through automated in-source fragment annotation

Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) spatially resolves the chemical composition of tissues. Lipids are of particular interest, as they influence important biological processes in health and disease. However, the identification of lipids in MALDI-MSI remains a challenge due to the lack of chromatographic separation or untargeted tandem mass spectrometry. Recent studies have proposed the use of MALDI in-source fragmentation to infer structural information and aid identification. Here we present rMSIfragment, an open-source R package that exploits known adducts and fragmentation pathways to confidently annotate lipids in MALDI-MSI. The annotations are ranked using a novel score that demonstrates an area under the curve of 0.7 in ROC analyses using HPLC-MS and Target-Decoy validations. rMSIfragment applies to multiple MALDI-MSI sample types and experimental setups. Finally, we demonstrate that overlooking in-source fragments increases the number of incorrect annotations. Annotation workflows should consider in-source fragmentation tools such as rMSIfragment to increase annotation confidence and reduce the number of false positives.

Spatial lipidomics 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 and. 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-freeze 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 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, as well as adds to the collective efforts to achieve a holistic understanding of diseases via single-cell spatial multi-omics.

Rev1 deficiency induces a metabolic shift in MEFs that can be manipulated by the NAD+ precursor nicotinamide riboside

Replication stress, caused by Rev1 deficiency, is associated with mitochondrial dysfunction, and metabolic stress. However, the overall metabolic alterations and possible interventions to rescue the deficits due to Rev1 loss remain unclear. Here, we report that loss of Rev1 leads to intense changes in metabolites and that this can be manipulated by NAD ⁺ supplementation. Autophagy decreases in Rev1^-/- mouse embryonic fibroblasts (MEFs) and can be restored by supplementing the NAD⁺ precursor nicotinamide riboside (NR). The abnormal mitochondrial morphology in Rev1^-/- MEFs can be partially reversed by NR supplementation, which also protects the mitochondrial cristae from rotenone-induced degeneration. In nematodes rev-1 deficiency causes sensitivity to oxidative stress but this cannot be rescued by NR supplementation. In conclusion, Rev1 deficiency leads to metabolic dysregulation of especially lipid and nucleotide metabolism, impaired autophagy, and mitochondrial anomalies, and all of these phenotypes can be improved by NR replenishment in MEFs.

XAI-enabled neural network analysis of metabolite spatial distributions

We used deep neural networks to process the mass spectrometry imaging (MSI) data of mouse muscle (young vs aged) and human cancer (tumor vs normal adjacent) tissues, with the aim of using explainable artificial intelligence (XAI) methods to rapidly identify biomarkers that can distinguish different classes of tissues, from several thousands of metabolite features. We also modified classic neural network architectures to construct a deep convolutional neural network that is more suitable for processing high-dimensional MSI data directly, instead of using dimension reduction techniques, and compared it to seven other machine learning analysis methods' performance in classification accuracy. After ascertaining the superiority of Channel-ResNet10, we used a novel channel selection-based XAI method to identify the key metabolite features that were responsible for its learning accuracy. These key metabolite biomarkers were then processed using MetaboAnalyst for pathway enrichment mapping. We found that Channel-ResNet10 was superior to seven other machine learning methods for MSI analysis, reaching > 98% accuracy in muscle aging and colorectal cancer datasets. We also used a novel channel selection-based XAI method to find that in young and aged muscle tissues, the differentially distributed metabolite biomarkers were especially enriched in the propanoate metabolism pathway, suggesting it as a novel target pathway for anti-aging therapy.

Phosphatidylinositol metabolism of the renal proximal tubule S3 segment is disturbed in response to diabetes

Diabetes is a main risk factor for kidney disease, causing diabetic nephropathy in close to half of all patients with diabetes. Metabolism has recently been identified to be decisive in cell fate decisions and repair. Here we used mass spectrometry imaging (MSI) to identify tissue specific metabolic dysregulation, in order to better understand early diabetes-induced metabolic changes of renal cell types. In our experimental diabetes mouse model, early glomerular glycocalyx barrier loss and systemic metabolic changes were observed. In addition, MSI targeted at small molecule metabolites and glycero(phospho)lipids exposed distinct changes upon diabetes in downstream nephron segments. Interestingly, the outer stripe of the outer medullar proximal tubular segment (PT_S3) demonstrated the most distinct response compared to other segments. Furthermore, phosphatidylinositol lipid metabolism was altered specifically in PT_S3, with one of the phosphatidylinositol fatty acid tails being exchanged from longer unsaturated fatty acids to shorter, more saturated fatty acids. In acute kidney injury, the PT_S3 segment and its metabolism are already recognized as important factors in kidney repair processes. The current study exposes early diabetes-induced changes in membrane lipid composition in this PT_S3 segment as a hitherto unrecognized culprit in the early renal response to diabetes.

Comparison of Local Metabolic Changes in Diabetic Rodent Kidneys Using Mass Spectrometry Imaging

Understanding the renal region-specific metabolic alteration in different animal models of diabetic nephropathy (DN) is critical for uncovering the underlying mechanisms and for developing effective treatments. In the present study, spatially resolved metabolomics based on air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) was used to compare the local metabolic changes in the kidneys of HFD/STZ-induced diabetic rats and db/db mice. As a result, a total of 67 and 59 discriminating metabolites were identified and visualized in the kidneys of the HFD/STZ-induced diabetic rats and db/db mice, respectively. The result showed that there were significant region-specific changes in the glycolysis, TCA cycle, lipid metabolism, carnitine metabolism, choline metabolism, and purine metabolism in both DN models. However, the regional levels of the ten metabolites, including glucose, AMP, eicosenoic acid, eicosapentaenoic acid, Phosphatidylserine (36:1), Phosphatidylserine (36:4), Phosphatidylethanolamine (34:1), Phosphatidylethanolamine (36:4), Phosphatidylcholine (34:2), Phosphatidylinositol (38:5) were changed in reversed directions, indicating significant differences in the local metabolic phenotypes of these two commonly used DN animal models. This study provides comprehensive and in-depth analysis of the differences in the tissue and molecular pathological features in diabetic kidney injury in HFD/STZ-induced diabetic rats and db/db mice.

Treatment of tubular damage in high-fat-diet-fed obese mice using sodium-glucose co-transporter inhibitors

A long-term high-fat diet (HFD) causes obesity and changes in renal lipid metabolism and lysosomal dysfunction in mice, causing renal damage. Sodium-glucose co-transporter inhibitors, including phlorizin, exert nephroprotective effects in patients with chronic kidney disease, but the underlying mechanism remains unclear. A HFD or standard diet was fed to adult C57BL/6J male mice, and phlorizin was administered. Lamellar body components of the proximal tubular epithelial cells (PTECs) were investigated. After phlorizin administration in HFD-fed mice, sphingomyelin and ceramide in urine and tissues were assessed and label-free quantitative proteomics was performed using kidney tissue samples. Mitochondrial elongation by fusion was effective in the PTECs of HFD-fed obese mice under phlorizin administration, and many lamellar bodies were found in the apical portion of the S2 segment of the proximal tubule. Phlorizin functioned as a diuretic, releasing lamellar bodies from the apical membrane of PTECs and clearing the obstruction in nephrons. The main component of the lamellar bodies was sphingomyelin. On the first day of phlorizin administration in HFD-fed obese mice, the diuretic effect was increased, and more sphingomyelin was excreted through urine than in vehicle-treated mice. The expressions of three peroxisomal β-oxidation proteins involved in fatty acid metabolism were downregulated after phlorizin administration in the kidneys of HFD-fed mice. Fatty acid elongation protein levels increased with phlorizin administration, indicating an increase in long-chain fatty acids. Lamellar bodies accumulated in the proximal renal tubule of the S2 segment of the HFD-fed mice, indicating that the urinary excretion of lamellar bodies has nephroprotective effects.

Youth versus adult-onset type 2 diabetic kidney disease: Insights into currently known structural differences and the potential underlying mechanisms

Type 2 diabetes (T2D) is a global health pandemic with significant humanitarian, economic, and societal implications, particularly for youth and young adults who are experiencing an exponential rise in incident disease. Youth-onset T2D has a more aggressive phenotype than adult-onset T2D, and this translates to important differences in rates of progression of diabetic kidney disease (DKD). We hypothesize that youth-onset DKD due to T2D may exhibit morphometric, metabolic, and molecular characteristics that are distinct from adult-onset T2D and develop secondary to inherent differences in renal energy expenditure and substrate metabolism, resulting in a central metabolic imbalance. Kidney structural changes that are evident at the onset of puberty also serve to exacerbate the organ’s baseline high rates of energy expenditure. Additionally, the physiologic state of insulin resistance seen during puberty increases the risk for kidney disease and is exacerbated by both concurrent diabetes and obesity. A metabolic mismatch in renal energetics may represent a novel target for pharmacologic intervention, both for prevention and treatment of DKD. Further investigation into the underlying molecular mechanisms resulting in DKD in youth-onset T2D using metabolomics and RNA sequencing of kidney tissue obtained at biopsy is necessary to expand our understanding of early DKD and potential targets for therapeutic intervention. Furthermore, large-scale clinical trials evaluating the duration of kidney protective effects of pharmacologic interventions that target a metabolic mismatch in kidney energy expenditure are needed to help mitigate the risk of DKD in youth-onset T2D.

Suramin prevents the development of diabetic kidney disease by inhibiting NLRP3 inflammasome activation in KK-Ay mice

AIMS/INTRODUCTION

Nucleotide-binding oligomerization domain-like receptor family pyrin domain containing 3 (NLRP3) inflammasomes produce IL-18 upon being activated by various stimuli via the P2 receptors. Previously, we showed that serum and urine IL-18 levels are positively associated with albuminuria in patients with type 2 diabetes, indicating the involvement of inflammasome activation in the pathogenesis of diabetic kidney disease (DKD). In the present study, we investigated whether the administration of suramin, a nonselective antagonist of the P2 receptors, protects diabetic KK.Cg-A^y /TaJcl (KK-Ay) mice against DKD progression.

MATERIALS AND METHODS

Suramin or saline was administered i.p. to KK-Ay and C57BL/6J mice once every 2 weeks for a period of 8 weeks. Mouse mesangial cells (MMCs) were stimulated with ATP in the presence or absence of suramin.

RESULTS

Suramin treatment significantly suppressed the increase in the urinary albumin-to-creatinine ratio, glomerular hypertrophy, mesangial matrix expansion, and glomerular fibrosis in KK-Ay mice. Suramin also suppressed the upregulation of NLRP3 inflammasome-related genes and proteins in the renal cortex of KK-Ay mice. P2X4 and P2X7 receptors were significantly upregulated in the isolated glomeruli of KK-Ay mice and mainly distributed in the glomerular mesangial cells of KK-Ay mice. Although neither ATP nor suramin affected NLRP3 expression in MMCs, suramin inhibited ATP-induced NLRP3 complex formation and the downstream expression of caspase-1 and IL-18 in MMCs.

CONCLUSIONS

These results suggest that the NLRP3 inflammasome is activated in a diabetic kidney and that inhibition of the NLRP3 inflammasome with suramin protects against the progression of early stage DKD.

Potential progression biomarkers of diabetic kidney disease determined using comprehensive machine learning analysis of non-targeted metabolomics

Diabetic kidney disease is the main cause of end-stage renal disease worldwide. The prediction of the clinical course of patients with diabetic kidney disease remains difficult, despite the identification of potential biomarkers; therefore, novel biomarkers are needed to predict the progression of the disease. We conducted non-targeted metabolomics using plasma and urine of patients with diabetic kidney disease whose estimated glomerular filtration rate was between 30 and 60 mL/min/1.73 m². We analyzed how the estimated glomerular filtration rate changed over time (up to 30 months) to detect rapid decliners of kidney function. Conventional logistic analysis suggested that only one metabolite, urinary 1-methylpyridin-1-ium (NMP), was a promising biomarker. We then applied a deep learning method to identify potential biomarkers and physiological parameters to predict the progression of diabetic kidney disease in an explainable manner. We narrowed down 3388 variables to 50 using the deep learning method and conducted two regression models, piecewise linear and handcrafted linear regression, both of which examined the utility of biomarker combinations. Our analysis, based on the deep learning method, identified systolic blood pressure and urinary albumin-to-creatinine ratio, six identified metabolites, and three unidentified metabolites including urinary NMP, as potential biomarkers. This research suggests that the machine learning method can detect potential biomarkers that could otherwise escape identification using the conventional statistical method.

Mass Spectrometry-Based Nontargeted and Targeted Analytical Approaches in Fingerprinting and Metabolomics of Food and Agricultural Research

Mass spectrometry (MS)-based techniques have been extensively applied in food and agricultural research. This review aims to address the advances and applications of MS-based analytical strategies in nontargeted and targeted analysis and summarizes the recent publications of MS-based techniques, including flow injection MS fingerprinting, chromatography-tandem MS metabolomics, direct analysis using ambient mass spectrometry, as well as development in MS data deconvolution software packages and databases for metabolomic studies. Various nontargeted and targeted approaches are employed in marker compounds identification, material adulteration detection, and the analysis of specific classes of secondary metabolites. In the newly emerged applications, the recent advances in computer tools for the fast deconvolution of MS data in targeted secondary metabolite analysis are highlighted.

The Role of Mass Spectrometry Imaging in Pharmacokinetic Studies

Although liquid chromatography-tandem mass spectrometry is the gold standard analytical platform for the quantification of drugs, metabolites, and biomarkers in biological samples, it cannot localize them in target tissues.The localization and quantification of drugs and/or their associated metabolites in target tissues is a more direct measure of bioavailability, biodistribution, efficacy, and regional toxicity compared to the traditional substitute studies using plasma.Therefore, combining high spatial resolution imaging functionality with the superior selectivity and sensitivity of mass spectrometry into one analytical technique will be a valuable tool for targeted localization and quantification of drugs, metabolites, and biomarkers.Mass spectrometry imaging (MSI) is a tagless analytical technique that allows for the direct localization and quantification of drugs, metabolites, and biomarkers in biological tissues, and has been used extensively in pharmaceutical research.The overall goal of this current review is to provide a detailed description of the working principle of MSI and its application in pharmacokinetic studies encompassing absorption, distribution, metabolism, excretion, and toxicity processes, followed by a discussion of the strategies for addressing the challenges associated with the functional utility of MSI in pharmacokinetic studies that support drug development.

Mitochondrial Dysfunction in Individuals with Diabetic Kidney Disease: A Systematic Review

Mitochondrial dysfunction is implicated in the pathogenesis of diabetic kidney disease (DKD). Compared to the vast body of evidence from preclinical in vitro and in vivo studies, evidence from human studies is limited. In a comprehensive search of the published literature, findings from studies that reported evidence of mitochondrial dysfunction in individuals with DKD were examined. Three electronic databases (PubMed, Embase, and Scopus) were searched in March 2022. A total of 1339 articles were identified, and 22 articles met the inclusion criteria. Compared to non-diabetic controls (NDC) and/or individuals with diabetes but without kidney disease (DC), individuals with DKD (age ~55 years; diabetes duration ~15 years) had evidence of mitochondrial dysfunction. Individuals with DKD had evidence of disrupted mitochondrial dynamics (11 of 11 articles), uncoupling (2 of 2 articles), oxidative damage (8 of 8 articles), decreased mitochondrial respiratory capacity (1 of 1 article), decreased mtDNA content (5 of 6 articles), and decreased antioxidant capacity (3 of 4 articles) compared to ND and/or DC. Neither diabetes nor glycemic control explained these findings, but rather presence and severity of DKD may better reflect degree of mitochondrial dysfunction in this population. Future clinical studies should include individuals closer to diagnosis of diabetes to ascertain whether mitochondrial dysfunction is implicated in the development of, or is a consequence of, DKD.

Spatial localization of β-unsaturated aldehyde markers in murine diabetic kidney tissue by mass spectrometry imaging

Diabetic nephropathy (DN) is the leading cause of end-stage renal disease. Limitations in current diagnosis and screening methods have sparked a search for more specific and conclusive biomarkers. Hyperglycemic conditions generate a plethora of harmful molecules in circulation and within tissues. Oxidative stress generates reactive α-dicarbonyls and β-unsaturated hydroxyhexenals, which react with proteins to form advanced glycation end products. Mass spectrometry imaging (MSI) enables the detection and spatial localization of molecules in biological tissue sections. Here, for the first time, the localization and semiquantitative analysis of “reactive aldehydes” (RAs) 4-hydroxyhexenal (4-HHE), 4-hydroxynonenal (4-HNE), and 4-oxo-2-nonenal (4-ONE) in the kidney tissues of a diabetic mouse model is presented. Ionization efficiency was enhanced through on-tissue chemical derivatization (OTCD) using Girard’s reagent T (GT), forming positively charged hydrazone derivatives. MSI analysis was performed using matrix-assisted laser desorption ionization (MALDI) coupled with Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR). RA levels were elevated in diabetic kidney tissues compared to lean controls and localized throughout the kidney sections at a spatial resolution of 100 µm. This was confirmed by liquid extraction surface analysis–MSI (LESA-MSI) and liquid chromatography–mass spectrometry (LC–MS). This method identified β-unsaturated aldehydes as “potential” biomarkers of DN and demonstrated the capability of OTCD-MSI for detection and localization of poorly ionizable molecules by adapting existing chemical derivatization methods. Untargeted exploratory distribution analysis of some precursor lipids was also assessed using MALDI-FT-ICR-MSI.

Fatty kidney: A possible future for chronic kidney disease research

BACKGROUND

Metabolic syndrome is a growing twenty-first century pandemic associated with multiple clinical comorbidities ranging from cardiovascular diseases, non-alcoholic fatty liver disease and polycystic ovary syndrome to kidney dysfunction. A novel area of research investigates the concept of fatty kidney in the pathogenesis of chronic kidney disease, especially in patients with diabetes mellitus or metabolic syndrome.

AIM

To review the most updated literature on fatty kidney and provide future research, diagnostic and therapeutic perspectives on a disease increasingly affecting the contemporary world.

MATERIALS AND METHOD

We performed an extensive literature search through three databases including Embase (Elsevier) and the Cochrane Central Register of Controlled Trials (Wiley) and PubMed/Medline Web of Science in November 2021 by using the following terms and their combinations: 'fatty kidney', 'ectopic fat', 'chronic kidney disease', 'cardiovascular event', 'cardio-metabolic risk', 'albuminuria' and 'metabolic syndrome'. Each study has been individually assessed by the authors.

RESULTS

Oxidative stress and inflammation, Klotho deficiency, endoplasmic reticulum stress, mitochondrial dysfunction and disruption of cellular energy balance appear to be the main pathophysiological mechanisms leading to tissue damage following fat accumulation. Despite the lack of large-scale comprehensive studies in this novel field of research, current clinical trials demonstrate fatty kidney as an independent risk factor for the development of chronic kidney disease and cardiovascular events.

CONCLUSION

The requirement for future studies investigating the pathophysiology, clinical outcomes and therapeutics of fatty kidney is clear.

Referenced Kendrick Mass Defect Annotation and Class-Based Filtering of Imaging MS Lipidomics Experiments

Because of their diverse functionalities in cells, lipids are of primary importance when characterizing molecular profiles of physiological and disease states. Imaging mass spectrometry (IMS) provides the spatial distributions of lipid populations in tissues. Referenced Kendrick mass defect (RKMD) analysis is an effective mass spectrometry (MS) data analysis tool for classification and annotation of lipids. Herein, we extend the capabilities of RKMD analysis and demonstrate an integrated method for lipid annotation and chemical structure-based filtering for IMS datasets. Annotation of lipid features with lipid molecular class, radyl carbon chain length, and degree of unsaturation allows image reconstruction and visualization based on each structural characteristic. We show a proof-of-concept application of the method to a computationally generated IMS dataset and validate that the RKMD method is highly specific for lipid components in the presence of confounding background ions. Moreover, we demonstrate an application of the RKMD-based annotation and filtering to matrix-assisted laser desorption/ionization (MALDI) IMS lipidomic data from human kidney tissue analysis.

Glucose- and Non-Glucose-Induced Mitochondrial Dysfunction in Diabetic Kidney Disease

Mitochondrial dysfunction plays an important role in the pathogenesis and progression of diabetic kidney disease (DKD). In this review, we will discuss mitochondrial dysfunction observed in preclinical models of DKD as well as in clinical DKD with a focus on oxidative phosphorylation (OXPHOS), mitochondrial reactive oxygen species (mtROS), biogenesis, fission and fusion, mitophagy and urinary mitochondrial biomarkers. Both glucose- and non-glucose-induced mitochondrial dysfunction will be discussed. In terms of glucose-induced mitochondrial dysfunction, the energetic shift from OXPHOS to aerobic glycolysis, called the Warburg effect, occurs and the resulting toxic intermediates of glucose metabolism contribute to DKD-induced injury. In terms of non-glucose-induced mitochondrial dysfunction, we will review the roles of lipotoxicity, hypoxia and vasoactive pathways, including endothelin-1 (Edn1)/Edn1 receptor type A signaling pathways. Although the relative contribution of each of these pathways to DKD remains unclear, the goal of this review is to highlight the complexity of mitochondrial dysfunction in DKD and to discuss how markers of mitochondrial dysfunction could help us stratify patients at risk for DKD.

Extracellular ATP Limits Homeostatic T Cell Migration Within Lymph Nodes

Whereas adenosine 5'-triphosphate (ATP) is the major energy source in cells, extracellular ATP (eATP) released from activated/damaged cells is widely thought to represent a potent damage-associated molecular pattern that promotes inflammatory responses. Here, we provide suggestive evidence that eATP is constitutively produced in the uninflamed lymph node (LN) paracortex by naïve T cells responding to C-C chemokine receptor type 7 (CCR7) ligand chemokines. Consistently, eATP was markedly reduced in naïve T cell-depleted LNs, including those of nude mice, CCR7-deficient mice, and mice subjected to the interruption of the afferent lymphatics in local LNs. Stimulation with a CCR7 ligand chemokine, CCL19, induced ATP release from LN cells, which inhibited CCR7-dependent lymphocyte migration in vitro by a mechanism dependent on the purinoreceptor P2X7 (P2X7R), and P2X7R inhibition enhanced T cell retention in LNs in vivo. These results collectively indicate that paracortical eATP is produced by naïve T cells in response to constitutively expressed chemokines, and that eATP negatively regulates CCR7-mediated lymphocyte migration within LNs via a specific subtype of ATP receptor, demonstrating its fine-tuning role in homeostatic cell migration within LNs.

Uncovering Molecular Heterogeneity in the Kidney With Spatially Targeted Mass Spectrometry

The kidney functions through the coordination of approximately one million multifunctional nephrons in 3-dimensional space. Molecular understanding of the kidney has relied on transcriptomic, proteomic, and metabolomic analyses of kidney homogenate, but these approaches do not resolve cellular identity and spatial context. Mass spectrometry analysis of isolated cells retains cellular identity but not information regarding its cellular neighborhood and extracellular matrix. Spatially targeted mass spectrometry is uniquely suited to molecularly characterize kidney tissue while retaining in situ cellular context. This review summarizes advances in methodology and technology for spatially targeted mass spectrometry analysis of kidney tissue. Profiling technologies such as laser capture microdissection (LCM) coupled to liquid chromatography tandem mass spectrometry provide deep molecular coverage of specific tissue regions, while imaging technologies such as matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) molecularly profile regularly spaced tissue regions with greater spatial resolution. These technologies individually have furthered our understanding of heterogeneity in nephron regions such as glomeruli and proximal tubules, and their combination is expected to profoundly expand our knowledge of the kidney in health and disease.

Mitochondrial Pathophysiology on Chronic Kidney Disease

In healthy kidneys, interstitial fibroblasts are responsible for the maintenance of renal architecture. Progressive interstitial fibrosis is thought to be a common pathway for chronic kidney diseases (CKD). Diabetes is one of the boosters of CKD. There is no effective treatment to improve kidney function in CKD patients. The kidney is a highly demanding organ, rich in redox reactions occurring in mitochondria, making it particularly vulnerable to oxidative stress (OS). A dysregulation in OS leads to an impairment of the Electron transport chain (ETC). Gene deficiencies in the ETC are closely related to the development of kidney disease, providing evidence that mitochondria integrity is a key player in the early detection of CKD. The development of novel CKD therapies is needed since current methods of treatment are ineffective. Antioxidant targeted therapies and metabolic approaches revealed promising results to delay the progression of some markers associated with kidney disease. Herein, we discuss the role and possible origin of fibroblasts and the possible potentiators of CKD. We will focus on the important features of mitochondria in renal cell function and discuss their role in kidney disease progression. We also discuss the potential of antioxidants and pharmacologic agents to delay kidney disease progression.

In situ metabolic profile and spatial distribution of ocular tissues: New insights into dry eye disease

PURPOSE

Dry eye disease (DED) is a chronic multifactorial disorder affecting millions of people, yet the pathogenesis mechanisms still remain unclear. Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) is a novel in situ visualization approach combined high-throughput mass spectrometry and molecular imaging. We aimed to explore the in situ ocular metabolic changes via MALDI-MSI to accelerate the recognition of DED pathogenesis.

METHODS

Experimental dry eye was established in Wistar rats by subcutaneous injection of scopolamine. The induction of DED was assessed by tear film breakup time, sodium fluorescein, histopathological staining and cell apoptosis. MALDI-MSI was applied to explore in situ ocular metabolomic in DED rats, and histopathological staining from same sections were used for side-by-side comparison with MALDI to annotate different tissue structures in the eye.

RESULTS

Considering the complexity of ocular tissue, we visualized the metabolites in specific ocular regions (central cornea, peripheral cornea, fornix conjunctiva, eyelid conjunctiva and aqueous humor), and identified metabolites related to DED, with information of relative abundance and spatial signatures. In addition, integrative pathway analysis illustrated that, several metabolic pathways such as glycerophospholipid, sphingolipid phenylalanine, and metabolism of glycine, serine and threonine were significantly altered in certain regions in the dry eye tissue. Moreover, we discussed how the metabolic pathways with spatiotemporal signatures might be involved in the DED process.

CONCLUSIONS

Our data exploit the advantages of in situ analysis of MALDI-MSI to accurately analyze the region-specific metabolic behaviors in DED, and provide new clues to uncover DED pathogenesis.

Purinergic P2 receptors: Involvement and therapeutic implications in diabetes-related glomerular injury

The purinergic activation of P2 receptors initiates a powerful and rapid signaling cascade that contributes to the regulation of an array of physiological and pathophysiological processes in many organs, including the kidney. P2 receptors are broadly distributed in both epithelial and vascular renal cells. Disturbances of purinergic signaling can lead to impairments in renal function. A growing body of evidence indicates changes in P2 receptor expression and nucleotide metabolism in chronic renal injury and inflammatory diseases. Increasing attention has focused on purinergic P2X7 receptors, which are not normally expressed in healthy kidney tissue but are highly expressed at sites of tissue damage and inflammation. Under hyperglycemic conditions, several mechanisms that are linked to purinergic signaling and involve nucleotide release and degradation are disrupted, resulting in the accumulation of adenosine 5'-triphosphate in the bloodstream in diabetes. Dysfunction of the purinergic system might be associated with serious vascular complications in diabetes, including diabetic nephropathy. This review summarizes our current knowledge of the role of P2 receptors in diabetes-related glomerular injury and its implications for new therapeutics for diabetic nephropathy.

Factorial Design to Optimize Matrix Spraying Parameters for MALDI Mass Spectrometry Imaging

Matrix deposition is a critical step in obtaining reproducible and spatially representative matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging data. To date, few limited studies have examined the optimization of matrix spraying parameters for maximizing analyte extraction while minimizing analyte delocalization. Herein, we present a study using automated pneumatic spraying with a heated sample-holder tray to determine an optimized model for mouse whole kidney lipid imaging using a 2,5-dihydroxybenzoic acid matrix in which the solvent flow rate, nozzle velocity, and sample heating were optimized using a two-level factorial experimental design. Parameters examined to determine the optimum model include the number of analytes, the matrix crystal size, off tissue delocalization, the signal intensity, and spray time. Our results show that sample heating using a heated tray while spraying improves the MALDI imaging performance. This improvement is possible because higher solvent flow rates can be used in the pneumatic sprayer, allowing for better sample extraction, while sample delocalization is minimized due to sample heating.

Spatial-resolved metabolomics reveals tissue-specific metabolic reprogramming in diabetic nephropathy by using mass spectrometry imaging

Detailed knowledge on tissue-specific metabolic reprogramming in diabetic nephropathy (DN) is vital for more accurate understanding the molecular pathological signature and developing novel therapeutic strategies. In the present study, a spatial-resolved metabolomics approach based on air flow-assisted desorption electrospray ionization (AFADESI) and matrix-assisted laser desorption ionization (MALDI) integrated mass spectrometry imaging (MSI) was proposed to investigate tissue-specific metabolic alterations in the kidneys of high-fat diet-fed and streptozotocin (STZ)-treated DN rats and the therapeutic effect of astragaloside IV, a potential anti-diabetic drug, against DN. As a result, a wide range of functional metabolites including sugars, amino acids, nucleotides and their derivatives, fatty acids, phospholipids, sphingolipids, glycerides, carnitine and its derivatives, vitamins, peptides, and metal ions associated with DN were identified and their unique distribution patterns in the rat kidney were visualized with high chemical specificity and high spatial resolution. These region-specific metabolic disturbances were ameliorated by repeated oral administration of astragaloside IV (100 mg/kg) for 12 weeks. This study provided more comprehensive and detailed information about the tissue-specific metabolic reprogramming and molecular pathological signature in the kidney of diabetic rats. These findings highlighted the promising potential of AFADESI and MALDI integrated MSI based metabolomics approach for application in metabolic kidney diseases.

Changes in plasma and urine metabolites associated with empagliflozin in patients with type 1 diabetes

AIM

To examine the impact of the sodium-glucose co-transporter-2 inhibitor, empagliflozin, on plasma and urine metabolites in participants with type 1 diabetes.

MATERIAL AND METHODS

Participants (n = 40, 50% male, mean age 24.3 years) with type 1 diabetes and without overt evidence of diabetic kidney disease had baseline assessments performed under clamped euglycaemia and hyperglycaemia, on two consecutive days. Participants then proceeded to an 8-week, open-label treatment period with empagliflozin 25 mg/day, followed by repeat assessments under clamped euglycaemia and hyperglycaemia. Plasma and urine metabolites were first grouped into metabolic pathways using MetaboAnalyst software. Principal component analysis was performed to create a representative value for each sufficiently represented metabolic group (false discovery rate ≤ 0.1) for further analysis.

RESULTS

Of the plasma metabolite groups, tricarboxylic acid (TCA) cycle (P < .0001), biosynthesis of unsaturated fatty acids (P = .0045), butanoate (P < .0001), propanoate (P = .0053), and alanine, aspartate and glutamate (P < .0050) metabolites were increased after empagliflozin treatment under clamped euglycaemia. Of the urine metabolite groups, only butanoate metabolites (P = .0005) were significantly increased. Empagliflozin treatment also attenuated the increase in a number of urine metabolites observed with acute hyperglycaemia.

CONCLUSIONS

Empagliflozin was associated with increased lipid and TCA cycle metabolites in participants with type 1 diabetes, suggesting a shift in metabolic substrate use and improved mitochondrial function. These effects result in more efficient energy production and may contribute to end-organ protection by alleviating local hypoxia and oxidative stress.

The Loss of Mitochondrial Quality Control in Diabetic Kidney Disease

Diabetic kidney disease (DKD) is the predominant complication of diabetes mellitus (DM) and the leading cause of chronic kidney disease and end-stage renal disease worldwide, which are major risk factors for death. The pathogenesis of DKD is very complicated, including inflammation, autophagy impairment, oxidative stress, and so on. Recently, accumulating evidence suggests that the loss of mitochondrial quality control exerts critical roles in the progression of DKD. Mitochondria are essential for eukaryotic cell viability but are extremely vulnerable to damage. The mechanisms of mitochondrial quality control act at the molecular level and the organelle level, including mitochondrial dynamics (fusion and fission), mitophagy, mitochondrial biogenesis, and mitochondrial protein quality control. In this review, we summarize current knowledge of the role of disturbances in mitochondrial quality control in the pathogenesis of DKD and provide potential insights to explore how to delay the onset and development of DKD.

Cross-Normalization of MALDI Mass Spectrometry Imaging Data Improves Site-to-Site Reproducibility

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is an established tool for the investigation of formalin-fixed paraffin-embedded (FFPE) tissue samples and shows a high potential for applications in clinical research and histopathological tissue classification. However, the applicability of this method to serial clinical and pharmacological studies is often hampered by inevitable technical variation and limited reproducibility. We present a novel spectral cross-normalization algorithm that differs from the existing normalization methods in two aspects: (a) it is based on estimating the full statistical distribution of spectral intensities and (b) it involves applying a non-linear, mass-dependent intensity transformation to align this distribution with a reference distribution. This method is combined with a model-driven resampling step that is specifically designed for data from MALDI imaging of tryptic peptides. This method was performed on two sets of tissue samples: a single human teratoma sample and a collection of five tissue microarrays (TMAs) of breast and ovarian tumor tissue samples (N = 241 patients). The MALDI MSI data was acquired in two labs using multiple protocols, allowing us to investigate different inter-lab and cross-protocol scenarios, thus covering a wide range of technical variations. Our results suggest that the proposed cross-normalization significantly reduces such batch effects not only in inter-sample and inter-lab comparisons but also in cross-protocol scenarios. This demonstrates the feasibility of cross-normalization and joint data analysis even under conditions where preparation and acquisition protocols themselves are subject to variation.

Urinary 2-Hydroxyglutarate Enantiomers Are Markedly Elevated in a Murine Model of Type 2 Diabetic Kidney Disease

Metabolic reprogramming is a hallmark of diabetic kidney disease (DKD); nutrient overload leads to increased production of metabolic byproducts that may become toxic at high levels. One metabolic byproduct may be 2-hydroxyglutarate (2-HG), a metabolite with many regulatory functions that exists in both enantiomeric forms physiologically. We quantitatively determined the levels of L and D-2HG enantiomers in the urine, plasma, and kidney cortex of db/db mice, a pathophysiologically relevant murine model of type 2 diabetes and DKD. We found increased fractional excretion of both L and D-2HG enantiomers, suggesting increased tubular secretion and/or production of the two metabolites in DKD. Quantitation of TCA cycle metabolites in db/db cortex suggests that TCA cycle overload and an increase in 2-HG precursor substrate, α-ketoglutarate, drive the increased L and D-2HG production in DKD. In conclusion, we demonstrated increased 2-HG enantiomer production and urinary excretion in murine type 2 DKD, which may contribute to metabolic reprogramming and progression of diabetic kidney disease.

High-Resolution Human Kidney Molecular Histology by Imaging Mass Spectrometry of Lipids

For many years, traditional histology has been the gold standard for the diagnosis of many diseases. However, alternative and powerful techniques have appeared in recent years that complement the information extracted from a tissue section. One of the most promising techniques is imaging mass spectrometry applied to lipidomics. Here, we demonstrate the capabilities of this technique to highlight the architectural features of the human kidney at a spatial resolution of 10 μm. Our data demonstrate that up to seven different segments of the nephron and the interstitial tissue can be readily identified in the sections according to their characteristic lipid fingerprints and that such fingerprints are maintained among different individuals (n = 32). These results set the foundation for further studies on the metabolic bases of the diseases affecting the human kidney.

Spatially Resolved Metabolomics Based on Air-Flow-Assisted Desorption Electrospray Ionization-Mass Spectrometry Imaging Reveals Region-Specific Metabolic Alterations in Diabetic Encephalopathy

Spatially resolved metabolic profiling of brain is vital for elucidating tissue-specific molecular histology and pathology underlying diabetic encephalopathy (DE). In this study, a spatially resolved metabolomic method based on air-flow-assisted desorption electrospray ionization-mass spectrometry imaging (AFADESI-MSI) was developed for investigating the region-specific metabolic disturbances in the brain of DE model rats induced by a high-fat diet in combination with streptozotocin administration. A total of 19 discriminating metabolites associated with glycolysis and the pentose phosphate pathway (PPP); the glutamate/gamma aminobutyric acid-glutamine cycle and tricarboxylic acid cycle; nucleotide metabolism; lipid metabolism; carnitine homeostasis; and taurine, ascorbic acid, histidine, and choline metabolism were identified and located in the brains of the diabetic rats simultaneously for the first time. The results indicated that increased glycolytic and PPP activity; dysfunction of mitochondrial metabolism; dysregulation of adenosinergic, glutamatergic, dopaminergic, cholinergic, and histaminergic systems; disorder of osmotic regulation and antioxidant system; and disorder of lipid metabolism occur in a region-specific fashion in the brains of DE rats. Thus, this study provides valuable information regarding the molecular pathological signature of DE. These findings also underline the high potential of AFADESI-MSI for applications in various central nervous system diseases.

Effect of suramin on urinary excretion of diabetes-induced glomerular and tubular injury parameters in rats

Diabetes mellitus causes changes in metabolism of extracellular nucleotides acting through P2 receptors (P2Rs). This affects renal function and may lead to glomerular and tubular disturbances. We measured urinary excretion of nucleotides (ATP, ADP, AMP, UTP, UDP, UMP) in streptozotocin-induced diabetic rats (65 mg/kg, i.p., day 0) and the effects of P2Rs' blockade by suramin (10 mg/kg, i.p., days +7, +14) on glomerular P2×7R expression and urinary excretion of glomerular (albumin, nephrin) and tubular (KIM-1, NGAL) injury markers, electrolytes, and oxidative stress markers (TBARS, 8-OHdG). Concentrations of nucleotides, specific proteins, electrolytes, and oxidative stress markers in 24-h urine samples collected in metabolic cages at days -1, +6 and +20 were measured using ion-paired reversed-phase HPLC, immunoenzymatic and fluorometric methods, and flame photometry, respectively. Expression of KIM-1 and P2×7R was examined by immunohistochemistry or immunoblotting. Diabetes was associated with increased urinary excretion of ATP, ADP, UTP, UDP and glomerular P2×7R expression. Suramin attenuated P2×7R expression but did not affect urinary excretion of nucleotides. Urinary excretion of albumin, nephrin, NGAL, and 8-OHdG were increased in diabetic rats and were not affected by suramin. TBARS was higher in diabetic rats and suramin attenuated the excretion dynamics in this group. KIM-1 excretion was higher in diabetic rats and suramin further increased excretion of KIM-1 in both diabetic and non-diabetic rats. Furthermore, suramin attenuated the diabetes-induced natriuresis and kaliuresis. It is possible that suramin affects both glomerular and tubular functions in diabetic rats.

Cryptococcus neoformans-Infected Macrophages Release Proinflammatory Extracellular Vesicles: Insight into Their Components by Multi-omics

Cryptococcus neoformans causes cryptococcal meningitis, which is frequent in patients with HIV/AIDS, especially in less-developed countries. The incidence of cryptococcal meningitis is close to 1 million each year globally.

Cryptococcus neoformans causes deadly mycosis in immunocompromised individuals. Macrophages are key cells fighting against microbes. Extracellular vesicles (EVs) are cell-to-cell communication mediators. The roles of EVs from infected host cells in the interaction with Cryptococcus remain uninvestigated. Here, EVs from viable C. neoformans-infected macrophages reduced fungal burdens but led to shorter survival of infected mice. In vitro, EVs induced naive macrophages to an inflammatory phenotype. Transcriptome analysis showed that EVs from viable C. neoformans-infected macrophages activated immune-related pathways, including p53 in naive human and murine macrophages. Conserved analysis demonstrated that basic cell biological processes, including cell cycle and division, were activated by infection-derived EVs from both murine and human infected macrophages. Combined proteomics, lipidomics, and metabolomics of EVs from infected macrophages showed regulation of pathways such as extracellular matrix (ECM) receptors and phosphatidylcholine. This form of intermacrophage communication could serve to prepare cells at more distant sites of infection to resist C. neoformans infection.

Imaging the kidney: from light to super-resolution microscopy

The important achievements in kidney physiological and pathophysiological mechanisms can largely be ascribed to progress in the technology of microscopy. Much of what we know about the architecture of the kidney is based on the fundamental descriptions of anatomic microscopists using light microscopy and later by ultrastructural analysis provided by electron microscopy. These two techniques were used for the first classification systems of kidney diseases and for their constant updates. More recently, a series of novel imaging techniques added the analysis in further dimensions of time and space. Confocal microscopy allowed us to sequentially visualize optical sections along the z-axis and the availability of specific analysis software provided a three-dimensional rendering of thicker tissue specimens. Multiphoton microscopy permitted us to simultaneously investigate kidney function and structure in real time. Fluorescence-lifetime imaging microscopy allowed to study the spatial distribution of metabolites. Super-resolution microscopy increased sensitivity and resolution up to nanoscale levels. With cryo-electron microscopy, researchers could visualize the individual biomolecules at atomic levels directly in the tissues and understand their interaction at subcellular levels. Finally, matrix-assisted laser desorption/ionization imaging mass spectrometry permitted the measuring of hundreds of different molecules at the same time on tissue sections at high resolution. This review provides an overview of available kidney imaging strategies, with a focus on the possible impact of the most recent technical improvements.

Mitochondrion-driven nephroprotective mechanisms of novel glucose lowering medications

Therapy for diabetic kidney disease (DKD) is undergoing a revolution with the realization that some glucose-lowering drugs have nephroprotective actions that may be intrinsic to the drugs and not dependent on the impact on diabetes control, as demonstrated with the sodium glucose co-transporter-2 (SGLT-2) inhibitors. Mitochondria are a critical factor required for the maintenance of kidney function, given its high energy demanding profile, with extensive use of adenosine triphosphate (ATP). Consequently, deficiency of the master regulator of mitochondrial biogenesis peroxisome proliferator-activated receptor gamma coactivator 1α predisposes to kidney disease. Perhaps as a result of key role of mitochondria in fundamental cellular functions, mitochondrial dysfunction may play a role in the pathogenesis of common conditions such as DKD. Finding pharmacological agents to influence this pathway could therefore lead to early implementation of therapy. Importantly, glucose-lowering drugs such as glucagon-like peptide-1 receptor activators and SGLT2 inhibitors have kidney and/or cardioprotective actions in patients with diabetes. Accumulating evidence from preclinical studies has suggested a protective effect of these drugs that is in part mediated by normalizing mitochondrial function. We now critically review this evidence and discuss studies needed to confirm mitochondrial protective benefits across a range of clinical studies.

Validation of Candidate Phospholipid Biomarkers of Chronic Kidney Disease in Hyperglycemic Individuals and Their Organ-Specific Exploration in Leptin Receptor-Deficient db/db Mouse

Biological exploration of early biomarkers for chronic kidney disease (CKD) in (pre)diabetic individuals is crucial for personalized management of diabetes. Here, we evaluated two candidate biomarkers of incident CKD (sphingomyelin (SM) C18:1 and phosphatidylcholine diacyl (PC aa) C38:0) concerning kidney function in hyperglycemic participants of the Cooperative Health Research in the Region of Augsburg (KORA) cohort, and in two biofluids and six organs of leptin receptor-deficient (db/db) mice and wild type controls. Higher serum concentrations of SM C18:1 and PC aa C38:0 in hyperglycemic individuals were found to be associated with lower estimated glomerular filtration rate (eGFR) and higher odds of CKD. In db/db mice, both metabolites had a significantly lower concentration in urine and adipose tissue, but higher in the lungs. Additionally, db/db mice had significantly higher SM C18:1 levels in plasma and liver, and PC aa C38:0 in adrenal glands. This cross-sectional human study confirms that SM C18:1 and PC aa C38:0 associate with kidney dysfunction in pre(diabetic) individuals, and the animal study suggests a potential implication of liver, lungs, adrenal glands, and visceral fat in their systemic regulation. Our results support further validation of the two phospholipids as early biomarkers of renal disease in patients with (pre)diabetes.