Analyzing cell-type-specific dynamics of metabolism in kidney repair

New tools to study renal fibrogenesis

PURPOSE OF REVIEW

Kidney fibrosis is a key pathological aspect and outcome of chronic kidney disease (CKD). The advent of multiomic analyses using human kidney tissue, enabled by technological advances, marks a new chapter of discovery in fibrosis research of the kidney. This review highlights the rapid advancements of single-cell and spatial multiomic techniques that offer new avenues for exploring research questions related to human kidney fibrosis development.

RECENT FINDINGS

We recently focused on understanding the origin and transition of myofibroblasts in kidney fibrosis using single-cell RNA sequencing (scRNA-seq) [1] . We analysed cells from healthy human kidneys and compared them to patient samples with CKD. We identified PDGFRα+/PDGFRβ+ mesenchymal cells as the primary cellular source of extracellular matrix (ECM) in human kidney fibrosis. We found several commonly shared cell states of fibroblasts and myofibroblasts and provided insights into molecular regulators. Novel single-cell and spatial multiomics tools are now available to shed light on cell lineages, the plasticity of kidney cells and cell-cell communication in fibrosis.

SUMMARY

As further single-cell and spatial multiomic approaches are being developed, opportunities to apply these methods to human kidney tissues expand similarly. Careful design and optimisation of the multiomic experiments are needed to answer questions related to cell lineages, plasticity and cell-cell communication in kidney fibrosis.

Metabolism and bioenergetics in the pathophysiology of organ fibrosis

Fibrosis is the tissue scarring characterized by excess deposition of extracellular matrix (ECM) proteins, mainly collagens. A fibrotic response can take place in any tissue of the body and is the result of an imbalanced reaction to inflammation and wound healing. Metabolism has emerged as a major driver of fibrotic diseases. While glycolytic shifts appear to be a key metabolic switch in activated stromal ECM-producing cells, several other cell types such as immune cells, whose functions are intricately connected to their metabolic characteristics, form a complex network of pro-fibrotic cellular crosstalk. This review purports to clarify shared and particular cellular responses and mechanisms across organs and etiologies. We discuss the impact of the cell-type specific metabolic reprogramming in fibrotic diseases in both experimental and human pathology settings, providing a rationale for new therapeutic interventions based on metabolism-targeted antifibrotic agents.

Spatially resolved metabolomic dataset of distinct human kidney anatomic regions

Cortex, medulla and papilla are three major human kidney anatomic structures and they harbour unique metabolic functions, but the underlying metabolomic profiles are largely unknown at spatial resolution. Here, we generated a spatially resolved metabolomics dataset on human kidney cortex, medulla and papilla tissues dissected from the same donor. Matrix-Assisted Laser Desorption/Ionization-Imaging Mass Spectrometry (MALDI-IMS) was used to detect metabolite species over mass-to-charge ratios of 50 -1500 for each section at a resolution of 10 × 10 µm2 pixel size. We present raw data matrix of each sample, feature annotations, raw AnnData merged from three samples and processed AnnData files after quality control, dimensional reduction and data integration, which contains a total of 170,459 spatially resolved metabolomes with 562 features detected. This dataset can be either visualized through an interactive browser or further analyzed to study metabolomic heterogeneity across regional human kidney anatomy.

Spatial omics techniques and data analysis for cancer immunotherapy applications

In-depth profiling of cancer cells/tissues is expanding our understanding of the genomic, epigenomic, transcriptomic, and proteomic landscape of cancer. However, the complexity of the cancer microenvironment, particularly its immune regulation, has made it difficult to exploit the potential of cancer immunotherapy. High-throughput spatial omics technologies and analysis pipelines have emerged as powerful tools for tackling this challenge. As a result, a potential revolution in cancer diagnosis, prognosis, and treatment is on the horizon. In this review, we discuss the technological advances in spatial profiling of cancer around and beyond the central dogma to harness the full benefits of immunotherapy. We also discuss the promise and challenges of spatial data analysis and interpretation and provide an outlook for the future.

Metabolite profiling of human renal cell carcinoma reveals tissue-origin dominance in nutrient availability

The tumor microenvironment is a determinant of cancer progression and therapeutic efficacy, with nutrient availability playing an important role. Although it is established that the local abundance of specific nutrients defines the metabolic parameters for tumor growth, the factors guiding nutrient availability in tumor compared to normal tissue and blood remain poorly understood. To define these factors in renal cell carcinoma (RCC), we performed quantitative metabolomic and comprehensive lipidomic analyses of tumor interstitial fluid (TIF), adjacent normal kidney interstitial fluid (KIF), and plasma samples collected from patients. TIF nutrient composition closely resembles KIF, suggesting that tissue-specific factors unrelated to the presence of cancer exert a stronger influence on nutrient levels than tumor-driven alterations. Notably, select metabolite changes consistent with known features of RCC metabolism are found in RCC TIF, while glucose levels in TIF are not depleted to levels that are lower than those found in KIF. These findings inform tissue nutrient dynamics in RCC, highlighting a dominant role of non-cancer-driven tissue factors in shaping nutrient availability in these tumors.

A cell-free nutrient-supplemented perfusate allows four-day ex vivo metabolic preservation of human kidneys

The growing disparity between the demand for transplants and the available donor supply, coupled with an aging donor population and increasing prevalence of chronic diseases, highlights the urgent need for the development of platforms enabling reconditioning, repair, and regeneration of deceased donor organs. This necessitates the ability to preserve metabolically active kidneys ex vivo for days. However, current kidney normothermic machine perfusion (NMP) approaches allow metabolic preservation only for hours. Here we show that human kidneys discarded for transplantation can be preserved in a metabolically active state up to 4 days when perfused with a cell-free perfusate supplemented with TCA cycle intermediates at subnormothermia (25 °C). Using spatially resolved isotope tracing we demonstrate preserved metabolic fluxes in the kidney microenvironment up to Day 4 of perfusion. Beyond Day 4, significant changes were observed in renal cell populations through spatial lipidomics, and increases in injury markers such as LDH, NGAL and oxidized lipids. Finally, we demonstrate that perfused kidneys maintain functional parameters up to Day 4. Collectively, these findings provide evidence that this approach enables metabolic and functional preservation of human kidneys over multiple days, establishing a solid foundation for future clinical investigations.

Transcriptomic, epigenomic, and spatial metabolomic cell profiling redefines regional human kidney anatomy

A large-scale multimodal atlas that includes major kidney regions is lacking. Here, we employed simultaneous high-throughput single-cell ATAC/RNA sequencing (SHARE-seq) and spatially resolved metabolomics to profile 54 human samples from distinct kidney anatomical regions. We generated transcriptomes of 446,267 cells and chromatin accessibility profiles of 401,875 cells and developed a package to analyze 408,218 spatially resolved metabolomes. We find that the same cell type, including thin limb, thick ascending limb loop of Henle and principal cells, display distinct transcriptomic, chromatin accessibility, and metabolomic signatures, depending on anatomic location. Surveying metabolism-associated gene profiles revealed non-overlapping metabolic signatures between nephron segments and dysregulated lipid metabolism in diseased proximal tubule (PT) cells. Integrating multimodal omics with clinical data identified PLEKHA1 as a disease marker, and its in vitro knockdown increased gene expression in PT differentiation, suggesting possible pathogenic roles. This study highlights previously underrepresented cellular heterogeneity underlying the human kidney anatomy.

Metabolomics at the tumor microenvironment interface: Decoding cellular conversations

Cancer heterogeneity remains a significant challenge for effective cancer treatments. Altered energetics is one of the hallmarks of cancer and influences tumor growth and drug resistance. Studies have shown that heterogeneity exists within the metabolic profile of tumors, and personalized-combination therapy with relevant metabolic interventions could improve patient response. Metabolomic studies are identifying novel biomarkers and therapeutic targets that have improved treatment response. The spatial location of elements in the tumor microenvironment are becoming increasingly important for understanding disease progression. The evolution of spatial metabolomics analysis now allows scientists to deeply understand how metabolite distribution contributes to cancer biology. Recently, these techniques have spatially resolved metabolite distribution to a subcellular level. It has been proposed that metabolite mapping could improve patient outcomes by improving precision medicine, enabling earlier diagnosis and intraoperatively identifying tumor margins. This review will discuss how altered metabolic pathways contribute to cancer progression and drug resistance and will explore the current capabilities of spatial metabolomics technologies and how these could be integrated into clinical practice to improve patient outcomes.

Seeing is Believing: Developing Multimodal Metabolic Insights at the Molecular Level

This outlook explores how two different molecular imaging approaches might be combined to gain insight into dynamic, subcellular metabolic processes. Specifically, we discuss how matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and stimulated Raman scattering (SRS) microscopy, which have significantly pushed the boundaries of imaging metabolic and metabolomic analyses in their own right, could be combined to create comprehensive molecular images. We first briefly summarize the recent advances for each technique. We then explore how one might overcome the inherent limitations of each individual method, by envisioning orthogonal and interchangeable workflows. Additionally, we delve into the potential benefits of adopting a complementary approach that combines both MSI and SRS spectro-microscopy for informing on specific chemical structures through functional-group-specific targets. Ultimately, by integrating the strengths of both imaging modalities, researchers can achieve a more comprehensive understanding of biological and chemical systems, enabling precise metabolic investigations. This synergistic approach holds substantial promise to expand our toolkit for studying metabolites in complex environments.

Spatiotemporal Landscape of Kidney Tubular Responses to Glomerular Proteinuria

Key Points

Background

Large increases in glomerular protein filtration induce major changes in body homeostasis and are associated with a higher risk of kidney functional decline and cardiovascular disease. We investigated how elevated protein exposure modifies the landscape of tubular function along the entire nephron, to understand the cellular changes that mediate these important clinical phenomena.

Methods

We conducted single-nucleus RNA sequencing, functional intravital imaging, and antibody staining to spatially map transport processes along the mouse kidney tubule. We then delineated how these were altered in a transgenic mouse model of inducible glomerular proteinuria (POD-ATTAC) at 7 and 28 days.

Results

Glomerular proteinuria activated large-scale and pleiotropic changes in gene expression in all major nephron sections. Extension of protein uptake from early (S1) to later (S2) parts of the proximal tubule initially triggered dramatic expansion of a hybrid S1/2 population, followed by injury and failed repair, with the cumulative effect of loss of canonical S2 functions. Proteinuria also induced acute injury in S3. Meanwhile, overflow of luminal proteins to the distal tubule caused transcriptional convergence between specialized regions and generalized dedifferentiation.

Conclusions

Proteinuria modulated cell signaling in tubular epithelia and caused distinct patterns of remodeling and injury in a segment-specific manner.

Spatiotemporal Study of Galactolipid Biosynthesis in Duckweedwith Mass Spectrometry Imaging and in vivo Isotope Labeling

Isotope labeling coupled with mass spectrometry imaging (MSI) presents a potent strategy for elucidating the dynamics of metabolism in cellular resolution, yet its application to plant systems is scarce. It has the potential to reveal the spatiotemporal dynamics in lipid biosynthesis during plant development. In this study, we explore its application to galactolipid biosynthesis of an aquatic plant, Lemna minor, with D2O labeling. Specifically, matrix-assisted laser desorption/ionization (MALDI) MSI data of two major galactolipids in L. minor, monogalactosyldiacylglycerol and digalactosyldiacylglycerol, were studied after growing in 50% D2O media over fifteen-day time period. When they were partially labeled after five days, three distinct binomial isotopologue distributions were observed corresponding to the labeling of partial structural moieties: galactose only, galactose and a fatty acyl chain, and the entire molecule. The temporal change of the relative abundance of these distributions follows the expected linear pathway of galactolipid biosynthesis. Notably, their MS images revealed the localization of each isotopologue group to the old parent frond, the intermediate tissues, and the newly grown daughter fronds. Besides, two additional labeling experiments, 1) 13CO2 labeling and 2) backward labeling of completely 50% D2O labeled L. minor in H2O media, confirm the observations in forward labeling. Further, these experiments unveiled hidden isotopologue distributions indicative of membrane lipid restructuring. This study suggests the potential of isotope labeling with MSI to provide spatiotemporal details in lipid biosynthesis in plant development.

Metabolite profiling of human renal cell carcinoma reveals tissue-origin dominance in nutrient availability

The tumor microenvironment is a determinant of cancer progression and therapeutic efficacy, with nutrient availability playing an important role. Although it is established that the local abundance of specific nutrients defines the metabolic parameters for tumor growth, the factors guiding nutrient availability in tumor compared to normal tissue and blood remain poorly understood. To define these factors in renal cell carcinoma (RCC), we performed quantitative metabolomic and comprehensive lipidomic analyses of tumor interstitial fluid (TIF), adjacent normal kidney interstitial fluid (KIF), and plasma samples collected from patients. TIF nutrient composition closely resembles KIF, suggesting that tissue-specific factors unrelated to the presence of cancer exert a stronger influence on nutrient levels than tumor-driven alterations. Notably, select metabolite changes consistent with known features of RCC metabolism are found in RCC TIF, while glucose levels in TIF are not depleted to levels that are lower than those found in KIF. These findings inform tissue nutrient dynamics in RCC, highlighting a dominant role of non-cancer driven tissue factors in shaping nutrient availability in these tumors.

Atlas of Cell Repertoire Within Neointimal Lesions Is Metabolically Altered in Hypertensive Rats

BACKGROUND

High blood pressure has been suggested to accelerate vascular injury-induced neointimal formation and progression. However, little is known about the intricate relationships between vascular injury and hypertension in the context of arterial remodeling.

METHODS

Single-cell RNA-sequencing analysis was used to depict the cell atlas of carotid arteries of Wistar Kyoto rats and spontaneously hypertensive rats with or without balloon injury.

RESULTS

We found that hypertension significantly aggravated balloon injury-induced arterial stenosis. A total of 36 202 cells from carotid arteries with or without balloon injury were included in single-cell RNA-sequencing analysis. Cell composition analysis showed that vascular injury and hypertension independently induced distinct aortic cell phenotypic alterations including immune cells, endothelial cells (ECs), and smooth muscle cells. Specifically, our data showed that injury and hypertension-induced specific EC phenotypic alterations, and revealed a transition from functional ECs to hypermetabolic, and eventually dysfunctional ECs in hypertensive rats upon balloon injury. Importantly, our data also showed that vascular injury and hypertension-induced different smooth muscle cell phenotypic alterations, characterized by deferential expression of synthetic signatures. Interestingly, pathway analysis showed that dysregulated metabolic pathways were a common feature in monocytes/macrophages, ECs, and smooth muscle cells in response to injury and hypertension. Functionally, we demonstrate that inhibition of mitochondrial respiration significantly ameliorated injury-induced neointimal formation in spontaneously hypertensive rats.

CONCLUSIONS

This study provides the cell landscape changes of the main aortic cell phenotypic alterations in response to injury and hypertension. Our findings suggest that targeting cellular mitochondrial respiration could be a novel therapeutic for patients with hypertension undergoing vascular angioplasty.

Multiplex protein imaging in tumour biology

Tissue imaging has become much more colourful in the past decade. Advances in both experimental and analytical methods now make it possible to image protein markers in tissue samples in high multiplex. The ability to routinely image 40-50 markers simultaneously, at single-cell or subcellular resolution, has opened up new vistas in the study of tumour biology. Cellular phenotypes, interaction, communication and spatial organization have become amenable to molecular-level analysis, and application to patient cohorts has identified clinically relevant cellular and tissue features in several cancer types. Here, we review the use of multiplex protein imaging methods to study tumour biology, discuss ongoing attempts to combine these approaches with other forms of spatial omics, and highlight challenges in the field.

Combining imaging mass spectrometry and immunohistochemistry to analyse the lipidome of spinal cord inflammation

Inflammation is a complex process that accompanies many pathologies. Actually, dysregulation of the inflammatory process is behind many autoimmune diseases. Thus, treatment of such pathologies may benefit from in-depth knowledge of the metabolic changes associated with inflammation. Here, we developed a strategy to characterize the lipid fingerprint of inflammation in a mouse model of spinal cord injury. Using lipid imaging mass spectrometry (LIMS), we scanned spinal cord sections from nine animals injected with lysophosphatidylcholine, a chemical model of demyelination. The lesions were demonstrated to be highly heterogeneous, and therefore, comparison with immunofluorescence experiments carried out in the same section scanned by LIMS was required to accurately identify the morphology of the lesion. Following this protocol, three main areas were defined: the lesion core, the peri-lesion, which is the front of the lesion and is rich in infiltrating cells, and the uninvolved tissue. Segmentation of the LIMS experiments allowed us to isolate the lipid fingerprint of each area in a precise way, as demonstrated by the analysis using classification models. A clear difference in lipid signature was observed between the lesion front and the epicentre, where the damage was maximized. This study is a first step to unravel the changes in the lipidome associated with inflammation in the context of diverse pathologies, such as multiple sclerosis.

Plasmonic Alloys Enhanced Metabolic Fingerprints for the Diagnosis of COPD and Exacerbations

Accurate diagnosis of chronic obstructive pulmonary disease (COPD) and exacerbations by metabolic biomarkers enables individualized treatment. Advanced metabolic detection platforms rely on designed materials. Here, we design mesoporous PdPt alloys to characterize metabolic fingerprints for diagnosing COPD and exacerbations. As a result, the optimized PdPt alloys enable the acquisition of metabolic fingerprints within seconds, requiring only 0.5 μL of native plasma by laser desorption/ionization mass spectrometry owing to the enhanced electric field, photothermal conversion, and photocurrent response. Machine learning decodes metabolic profiles acquired from 431 individuals, achieving a precise diagnosis of COPD with an area under the curve (AUC) of 0.904 and an accurate distinction between stable COPD and acute exacerbations of COPD (AECOPD) with an AUC of 0.951. Notably, eight metabolic biomarkers identified accurately discriminate AECOPD from stable COPD while providing valuable information on disease progress. Our platform will offer an advanced nanoplatform for the management of COPD, complementing standard clinical techniques.

Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications

Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.

Advances and potential of regenerative medicine in pediatric nephrology

The endogenous capacity of the kidney to repair is limited, and generation of new nephrons after injury for adequate function recovery remains a need. Discovery of factors that promote the endogenous regenerative capacity of the injured kidney or generation of transplantable kidney tissue represent promising therapeutic strategies. While several encouraging results are obtained after administration of stem or progenitor cells, stem cell secretome, or extracellular vesicles in experimental kidney injury models, very little data exist in the clinical setting to make conclusions about their efficacy. In this review, we provide an overview of the cutting-edge knowledge on kidney regeneration, including pre-clinical methodologies used to elucidate regenerative pathways and describe the perspectives of regenerative medicine for kidney patients.

NAT10 promotes renal ischemia-reperfusion injury via activating NCOA4-mediated ferroptosis

Ischemia-reperfusion injury (IRI) is a significant contributor to acute kidney injury (AKI) and is associated with substantial morbidity and mortality rates. In this study, we aimed to investigate the role of NAT10 and its ac4C RNA modification in IRI-induced renal injury. Our findings revealed that both the expression level of NAT10 and the RNA ac4C level in the kidneys were elevated in the IRI group compared to the sham group. Functionally, we observed that inhibition of NAT10 activity with Remodelin or the specific knockout of NAT10 in the kidney led to a significant attenuation of IRI-induced renal injury. Furthermore, in vitro experiments demonstrated that NAT10 inhibition and specific knockout of NAT10 in the kidney markedly suppressed global ac4C RNA modification, providing protection against hypoxia/reoxygenation-induced tubular epithelial cell injury and ferroptosis. Mechanistically, our study uncovered that NAT10 promoted ac4C RNA modification of NCOA4 mRNA, thereby enhancing its stability and contributing to IRI-induced ferroptosis in tubular epithelial cells (TECs). These findings underscore the potential of NAT10 and ac4C RNA modification as promising therapeutic targets for the treatment of AKI. Overall, our study sheds light on the critical involvement of NAT10 and ac4C RNA modification in the pathogenesis of IRI-induced renal injury, offering valuable insights for the development of novel AKI treatment strategies.

Deciphering metabolic crosstalk in context: lessons from inflammatory diseases

Metabolism plays a crucial role in regulating the function of immune cells in both health and disease, with altered metabolism contributing to the pathogenesis of cancer and many inflammatory diseases. The local microenvironment has a profound impact on the metabolism of immune cells. Therefore, immunological and metabolic heterogeneity as well as the spatial organization of cells in tissues should be taken into account when studying immunometabolism. Here, we highlight challenges of investigating metabolic communication. Additionally, we review the capabilities and limitations of current technologies for studying metabolism in inflamed microenvironments, including single-cell omics techniques, flow cytometry-based methods (Met-Flow, single-cell energetic metabolism by profiling translation inhibition (SCENITH)), cytometry by time of flight (CyTOF), cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq), and mass spectrometry imaging. Considering the importance of metabolism in regulating immune cells in diseased states, we also discuss the applications of metabolomics in clinical research, as well as some hurdles to overcome to implement these techniques in standard clinical practice. Finally, we provide a flowchart to assist scientists in designing effective strategies to unravel immunometabolism in disease-relevant contexts.

Spatial multi-omics: novel tools to study the complexity of cardiovascular diseases

Spatial multi-omic studies have emerged as a promising approach to comprehensively analyze cells in tissues, enabling the joint analysis of multiple data modalities like transcriptome, epigenome, proteome, and metabolome in parallel or even the same tissue section. This review focuses on the recent advancements in spatial multi-omics technologies, including novel data modalities and computational approaches. We discuss the advancements in low-resolution and high-resolution spatial multi-omics methods which can resolve up to 10,000 of individual molecules at subcellular level. By applying and integrating these techniques, researchers have recently gained valuable insights into the molecular circuits and mechanisms which govern cell biology along the cardiovascular disease spectrum. We provide an overview of current data analysis approaches, with a focus on data integration of multi-omic datasets, highlighting strengths and weaknesses of various computational pipelines. These tools play a crucial role in analyzing and interpreting spatial multi-omics datasets, facilitating the discovery of new findings, and enhancing translational cardiovascular research. Despite nontrivial challenges, such as the need for standardization of experimental setups, data analysis, and improved computational tools, the application of spatial multi-omics holds tremendous potential in revolutionizing our understanding of human disease processes and the identification of novel biomarkers and therapeutic targets. Exciting opportunities lie ahead for the spatial multi-omics field and will likely contribute to the advancement of personalized medicine for cardiovascular diseases.

The metabolic pathway regulation in kidney injury and repair

Kidney injury and repair are accompanied by significant disruptions in metabolic pathways, leading to renal cell dysfunction and further contributing to the progression of renal pathology. This review outlines the complex involvement of various energy production pathways in glucose, lipid, amino acid, and ketone body metabolism within the kidney. We provide a comprehensive summary of the aberrant regulation of these metabolic pathways in kidney injury and repair. After acute kidney injury (AKI), there is notable mitochondrial damage and oxygen/nutrient deprivation, leading to reduced activity in glycolysis and mitochondrial bioenergetics. Additionally, disruptions occur in the pentose phosphate pathway (PPP), amino acid metabolism, and the supply of ketone bodies. The subsequent kidney repair phase is characterized by a metabolic shift toward glycolysis, along with decreased fatty acid β-oxidation and continued disturbances in amino acid metabolism. Furthermore, the impact of metabolism dysfunction on renal cell injury, regeneration, and the development of renal fibrosis is analyzed. Finally, we discuss the potential therapeutic strategies by targeting renal metabolic regulation to ameliorate kidney injury and fibrosis and promote kidney repair.

Imaging and spatial omics of kidney injury: significance, challenges, advances and perspectives

The kidneys are susceptible to a range of insults that can cause damage to them. Early diagnosis, timely prevention, and proper treatment are crucial for improving the outcome of kidney injury. However, the complexity of renal structure and function makes it difficult to reach the demand of early detection and comprehensive evaluation of kidney injury. No successful drug therapy caused by the elaborate pathogenesis mechanism network of kidney injury calls for a systematical interpretation in mechanism researches. Recent advances in renal imaging and omics studies have provided novel views and deeper insights into kidney injury, but also raise challenges in reaching a comprehensive cellular and molecular atlas of kidney injury. Progresses in imaging and omics of kidney injury are being made in various directions, with the initiative of construction a high-resolution structural atlas of kidney, dynamic and non-invasive evaluation of renal function, and systematic establishment of spatially resolved molecular atlas by transcriptomics and metabolomics. With the limitations of a single modality, novel multimodal integration technologies of imaging and omics are being attempted to achieve a systematic description of nephropathy mechanisms. Further extensive efforts in renal multimodal imaging and omics studies are extremely required to deepen our understanding on kidney injury in the context of diagnostic, mechanistic and therapeutic perspectives.

O-GlcNAcylation at the center of antitumor immunity

The post-translational modification known as O-GlcNAcylation is a highly dysregulated process in tumors, and a key contributor to malignant transformation. In contrast, after three decades since its discovery, very little has been revealed about this process in the immune system. With the prospect of targeting O-GlcNAcylation as tumor therapy, greater understanding of how it regulates immune responses in the context of the tumor microenvironment will be needed. Here, we discuss recent discoveries from which a picture is emerging that O-GlcNAcylation, in either tumors or in immune cells, could negatively impact overall antitumor immune responses. We propose that interference with O-GlcNAcylation thus holds promise for cancer treatment from both perspectives.

Host-pathogen interactions from a metabolic perspective: methods of investigation

Metabolism shapes immune homeostasis in health and disease. This review presents the range of methods that are currently available to investigate the dialog between metabolism and immunity at the systemic, tissue and cellular levels, particularly during infection.

Enablers and challenges of spatial omics, a melting pot of technologies

Spatial omics has emerged as a rapidly growing and fruitful field with hundreds of publications presenting novel methods for obtaining spatially resolved information for any omics data type on spatial scales ranging from subcellular to organismal. From a technology development perspective, spatial omics is a highly interdisciplinary field that integrates imaging and omics, spatial and molecular analyses, sequencing and mass spectrometry, and image analysis and bioinformatics. The emergence of this field has not only opened a window into spatial biology, but also created multiple novel opportunities, questions, and challenges for method developers. Here, we provide the perspective of technology developers on what makes the spatial omics field unique. After providing a brief overview of the state of the art, we discuss technological enablers and challenges and present our vision about the future applications and impact of this melting pot.

Strategies for uncovering stable isotope tracing patterns between cell populations

Despite practical complexities, isotope tracing studies in humans are becoming increasingly feasible. However, several technological challenges need to be addressed in order to take full advantage of human tracing studies. First, absolute metabolic flux measurements in mice are not so easily applied to human models, given that tissue resection is restricted to a single surgical time point. Second, isotope tracing has yet to be employed to detect metabolic differences between cells types in vivo. Here, we discuss the current models and propose an alternative, liquid tumor environment, that could overcome these limitations. Furthermore, we highlight current strategies used to maintain isotopolog enrichment following cell isolation techniques to facilitate cell-type-specific analysis.

Spatial metabolomics principles and application to cancer research

Mass spectrometry imaging (MSI) is an emerging technology in cancer metabolomics. Desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI) MSI are complementary techniques to identify hundreds of metabolites in space with close to single-cell resolution. This technology leap enables research focusing on tumor heterogeneity, cancer cell plasticity, and the communication signals between cancer and stromal cells in the tumor microenvironment (TME). Currently, unprecedented knowledge is generated using spatial metabolomics in fundamental cancer research. Yet, also translational applications are emerging, including the assessment of spatial drug distribution in organs and tumors. Moreover, clinical research investigates the use of spatial metabolomics as a rapid pathology tool during cancer surgeries. Here, we summarize MSI applications, the knowledge gained by this technology in space, future directions, and developments needed.

Spatially resolved metabolomics and isotope tracing reveal dynamic metabolic responses of dentate granule neurons with acute stimulation

Neuronal activity creates an intense energy demand that must be met by rapid metabolic responses. To investigate metabolic adaptations in the neuron-enriched dentate granule cell (DGC) layer within its native tissue environment, we employed murine acute hippocampal brain slices, coupled with fast metabolite preservation and followed by mass spectrometry (MS) imaging, to generate spatially resolved metabolomics and isotope-tracing data. Here we show that membrane depolarization induces broad metabolic changes, including increased glycolytic activity in DGCs. Increased glucose metabolism in response to stimulation is accompanied by mobilization of endogenous inosine into pentose phosphates via the action of purine nucleotide phosphorylase (PNP). The PNP reaction is an integral part of the neuronal response to stimulation, because inhibition of PNP leaves DGCs energetically impaired during recovery from strong activation. Performing MS imaging on brain slices bridges the gap between live-cell physiology and the deep chemical analysis enabled by MS.

Visualization of metabolites and microbes at high spatial resolution using MALDI mass spectrometry imaging and in situ fluorescence labeling

Label-free molecular imaging techniques such as matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) enable the direct and simultaneous mapping of hundreds of different metabolites in thin sections of biological tissues. However, in host-microbe interactions it remains challenging to localize microbes and to assign metabolites to the host versus members of the microbiome. We therefore developed a correlative imaging approach combining MALDI-MSI with fluorescence in situ hybridization (FISH) on the same section to identify and localize microbial cells. Here, we detail metaFISH as a robust and easy method for assigning the spatial distribution of metabolites to microbiome members based on imaging of nucleic acid probes, down to single-cell resolution. We describe the steps required for tissue preparation, on-tissue hybridization, fluorescence microscopy, data integration into a correlative image dataset, matrix application and MSI data acquisition. Using metaFISH, we map hundreds of metabolites and several microbial species to the micrometer scale on a single tissue section. For example, intra- and extracellular bacteria, host cells and their associated metabolites can be localized in animal tissues, revealing their complex metabolic interactions. We explain how we identify low-abundance bacterial infection sites as regions of interest for high-resolution MSI analysis, guiding the user to a trade-off between metabolite signal intensities and fluorescence signals. MetaFISH is suitable for a broad range of users from environmental microbiologists to clinical scientists. The protocol requires ~2 work days.

omicsMIC: a Comprehensive Benchmarking Platform for Robust Comparison of Imputation Methods in Mass Spectrometry-based Omics Data

Mass spectrometry is a powerful and widely used tool for generating proteomics, lipidomics, and metabolomics profiles, which is pivotal for elucidating biological processes and identifying biomarkers. However, missing values in spectrometry-based omics data may pose a critical challenge for the comprehensive identification of biomarkers and elucidation of the biological processes underlying human complex disorders. To alleviate this issue, various imputation methods for mass spectrometry-based omics data have been developed. However, a comprehensive and systematic comparison of these imputation methods is still lacking, and researchers are frequently confronted with a multitude of options without a clear rationale for method selection. To address this pressing need, we developed omicsMIC (mass spectrometry-based omics with Missing values Imputation methods Comparison platform), an interactive platform that provides researchers with a versatile framework to simulate and evaluate the performance of 28 diverse imputation methods. omicsMIC offers a nuanced perspective, acknowledging the inherent heterogeneity in biological data and the unique attributes of each dataset. Our platform empowers researchers to make data-driven decisions in imputation method selection based on real-time visualizations of the outcomes associated with different imputation strategies. The comprehensive benchmarking and versatility of omicsMIC make it a valuable tool for the scientific community engaged in mass spectrometry-based omics research. OmicsMIC is freely available at https://github.com/WQLin8/omicsMIC.

Enhancing metabolite coverage in MALDI-MSI using laser post-ionisation (MALDI-2)

Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) of metabolites can reveal how metabolism is altered throughout heterogeneous tissues. Here negative ion mode MALDI-MSI has been coupled with laser post-ionisation (MALDI-2) and applied to the MSI of low molecular weight (LMW) metabolites ( Collapse

Key Words Collapse

MESH Headings

• Animals
• Mice
• Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
• Molecular Weight
• Drama
• Glutamic Acid
• Lasers
• Thinness

Collapse

Grants Collapse

Affiliation(s)

J C McKinnon Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia.
H H Milioli Garvan Institute of Medical Research, Darlinghurst, NSW, Australia St. Vincent's Clinical School, UNSW Medicine, UNSW Sydney, NSW, Australia The Kinghorn Cancer Centre, Darlinghurst, NSW, Australia
C A Purcell Garvan Institute of Medical Research, Darlinghurst, NSW, Australia St. Vincent's Clinical School, UNSW Medicine, UNSW Sydney, NSW, Australia The Kinghorn Cancer Centre, Darlinghurst, NSW, Australia
C L Chaffer Garvan Institute of Medical Research, Darlinghurst, NSW, Australia St. Vincent's Clinical School, UNSW Medicine, UNSW Sydney, NSW, Australia The Kinghorn Cancer Centre, Darlinghurst, NSW, Australia
B Wadie Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
T Alexandrov Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
T W Mitchell Molecular Horizons, School of Medical, Indigenous and Health Science, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia
S R Ellis Molecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Northfields Ave, Wollongong, NSW 2522, Australia.

Collapse

An updated overview of some factors that influence the biological effects of nanoparticles

Nanoparticles (NPs) can be extremely effective in the early diagnosis and treatment of cancer due to their properties. The nanotechnology industry is developing rapidly. The number of multifunctional NPs has increased in the market and hundreds of NPs are in various stages of preclinical and clinical development. Thus, the mechanism underlying the effects of NPs on biological systems has received much attention. After NPs enter the body, they interact with plasma proteins, tumour cell receptors, and small biological molecules. This interaction is closely related to the size, shape, chemical composition and surface modification properties of NPs. In this review, the effects of the size, shape, chemical composition and surface modification of NPs on the biological effects of NPs were summarised, including the mechanism through which NPs enter cells, the resulting oxidative stress response, and the interaction with proteins. This review of the biological effects of NPs can not only provide theoretical support for the preparation of safer and more efficient NPs but also lay the foundation for their clinical application.

Mfsd2a-mediated lysolipid transport is important for renal recovery after acute kidney injury

Acute kidney injury (AKI) is a global public health concern with high mortality and morbidity. In ischemic-reperfusion injury (IRI), a main cause of AKI, the brush border membrane of S3 proximal tubules (PT) is lost to the tubular lumen. How injured tubules reconstitute lost membrane lipids during renal recovery is not known. Here, we identified Mfsd2a, a sodium-dependent lysophosphatidylcholine (LPC) transporter, to be expressed specifically in the basolateral membrane of S3 PT. Using an in vivo activity probe for Mfsd2a, transport activity was found to be specific to the S3 PT. Mice with haploinsufficiency of Mfsd2a exhibited delayed recovery of renal function after acute IRI, with depressed urine osmolality and elevated levels of histological markers of damage, fibrosis, and inflammation, findings corroborated by transcriptomic analysis. Lipidomics revealed a deficiency in docosahexaenoic acid (DHA) containing phospholipids in Mfsd2a haploinsufficiency. Treatment of Mfsd2a haploinsufficient mice with LPC-DHA improved renal function and reduced markers of injury, fibrosis, and inflammation. Additionally, LPC-DHA treatment restored S3 brush border membrane architecture and normalized DHA-containing phospholipid content. These findings indicate that Mfsd2a-mediated transport of LPC-DHA is limiting for renal recovery after AKI and suggest that LPC-DHA could be a promising dietary supplement for improving recovery following AKI.

Spatially resolved metabolomics and isotope tracing reveal dynamic metabolic responses of dentate granule neurons with acute stimulation

Neuronal activity creates an intense energy demand that must be met by rapid metabolic responses. To investigate metabolic adaptations in the neuron-enriched dentate granule cell (DGC) layer within its native tissue environment, we employed murine acute hippocampal brain slices coupled with fast metabolite preservation, followed by mass spectrometry imaging (MALDI-MSI) to generate spatially resolved metabolomics and isotope tracing data. Here we show that membrane depolarization induces broad metabolic changes, including increased glycolytic activity in DGCs. Increased glucose metabolism in response to stimulation is accompanied by mobilization of endogenous inosine into pentose phosphates, via the action of purine nucleotide phosphorylase (PNP). The PNP reaction is an integral part of the neuronal response to stimulation, as inhibiting PNP leaves DGCs energetically impaired during recovery from strong activation. Performing MSI on brain slices bridges the gap between live cell physiology and the deep chemical analysis enabled by mass spectrometry.

Spatial Metabolome Lipidome and Glycome from a Single brain Section

Metabolites, lipids, and glycans are fundamental biomolecules involved in complex biological systems. They are metabolically channeled through a myriad of pathways and molecular processes that define the physiology and pathology of an organism. Here, we present a blueprint for the simultaneous analysis of spatial metabolome, lipidome, and glycome from a single tissue section using mass spectrometry imaging. Complimenting an original experimental protocol, our workflow includes a computational framework called Spatial Augmented Multiomics Interface (Sami) that offers multiomics integration, high dimensionality clustering, spatial anatomical mapping with matched multiomics features, and metabolic pathway enrichment to providing unprecedented insights into the spatial distribution and interaction of these biomolecules in mammalian tissue biology.

Metabolic changes and potential biomarkers in "Candidatus Liberibacter solanacearum"-infected potato psyllids: implications for psyllid-pathogen interactions

Psyllid yellows, vein-greening (VG), and zebra chip (ZC) diseases, which are primarily transmitted by potato psyllid (PoP) carrying Candidatus Liberibacter solanacearum (CLso), have caused significant losses in solanaceous crop production worldwide. Pathogens interact with their vectors at the organic and cellular levels, while the potential changes that may occur at the biochemical level are less well reported. In this study, the impact of CLso on the metabolism of PoP and the identification of biomarkers from infected psyllids were examined. Using ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) analysis, metabolomic changes in CLso-infected psyllids were compared to uninfected ones. A total of 34 metabolites were identified as potential biomarkers of CLso infection, which were primarily related to amino acid, carbohydrate, and lipid metabolism. The significant increase in glycerophospholipids is thought to be associated with CLso evading the insect vector's immune defense. Matrix-assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) was used to map the spatial distribution of these biomarkers, revealing that 15-keto-Prostaglandin E2 and alpha-D-Glucose were highly expressed in the abdomen of uninfected psyllids but down-regulated in infected psyllids. It is speculated that this down-regulation may be due to CLso evading surveillance by immune suppression in the PoP midgut. Overall, valuable biochemical information was provided, a theoretical basis for a better understanding of psyllid-pathogen interactions was offered, and the findings may aid in breaking the transmission cycle of these diseases.

Metabolic reprogramming heterogeneity in chronic kidney disease

Fibrosis driven by excessive accumulation of extracellular matrix (ECM) is the hallmark of chronic kidney disease (CKD). Myofibroblasts, which are the cells responsible for ECM production, are activated by cross talk with injured proximal tubule and immune cells. Emerging evidence suggests that alterations in metabolism are not only a feature of but also play an influential role in the pathogenesis of renal fibrosis. The application of omics technologies to cell-tracing animal models and follow-up functional data suggest that cell-type-specific metabolic shifts have particular roles in the fibrogenic response. In this review, we cover the main metabolic reprogramming outcomes in renal fibrosis and provide a future perspective on the field of renal fibrometabolism.

Proximal tubule responses to injury: interrogation by single-cell transcriptomics

PURPOSE OF REVIEW

Acute kidney injury (AKI) occurs in approximately 10-15% of patients admitted to hospital and is associated with adverse clinical outcomes. Despite recent advances, management of patients with AKI is still mainly supportive, including the avoidance of nephrotoxins, volume and haemodynamic management and renal replacement therapy. A better understanding of the renal response to injury is the prerequisite to overcome current limitations in AKI diagnostics and therapy.

RECENT FINDINGS

Single-cell technologies provided new opportunities to study the complexity of the kidney and have been instrumental for rapid advancements in the understanding of the cellular and molecular mechanisms of AKI.

SUMMARY

We provide an update on single-cell technologies and we summarize the recent discoveries on the cellular response to injury in proximal tubule cells from the early response in AKI, to the mechanisms of tubule repair and the relevance of maladaptive tubule repair in the transition to chronic kidney disease.

Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem

Tumors are comprised of a multitude of cell types spanning different microenvironments. Mass spectrometry imaging (MSI) has the potential to identify metabolic patterns within the tumor ecosystem and surrounding tissues, but conventional workflows have not yet fully integrated the breadth of experimental techniques in metabolomics. Here, we combine MSI, stable isotope labeling, and a spatial variant of Isotopologue Spectral Analysis to map distributions of metabolite abundances, nutrient contributions, and metabolic turnover fluxes across the brains of mice harboring GL261 glioma, a widely used model for glioblastoma. When integrated with MSI, the combination of ion mobility, desorption electrospray ionization, and matrix assisted laser desorption ionization reveals alterations in multiple anabolic pathways. De novo fatty acid synthesis flux is increased by approximately 3-fold in glioma relative to surrounding healthy tissue. Fatty acid elongation flux is elevated even higher at 8-fold relative to surrounding healthy tissue and highlights the importance of elongase activity in glioma.

Physiological and pathological roles of lipogenesis

Lipids are essential metabolites, which function as energy sources, structural components and signalling mediators. Most cells are able to convert carbohydrates into fatty acids, which are often converted into neutral lipids for storage in the form of lipid droplets. Accumulating evidence suggests that lipogenesis plays a crucial role not only in metabolic tissues for systemic energy homoeostasis but also in immune and nervous systems for their proliferation, differentiation and even pathophysiological roles. Thus, excessive or insufficient lipogenesis is closely associated with aberrations in lipid homoeostasis, potentially leading to pathological consequences, such as dyslipidaemia, diabetes, fatty liver, autoimmune diseases, neurodegenerative diseases and cancers. For systemic energy homoeostasis, multiple enzymes involved in lipogenesis are tightly controlled by transcriptional and post-translational modifications. In this Review, we discuss recent findings regarding the regulatory mechanisms, physiological roles and pathological importance of lipogenesis in multiple tissues such as adipose tissue and the liver, as well as the immune and nervous systems. Furthermore, we briefly introduce the therapeutic implications of lipogenesis modulation.

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.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

Revealing the In Situ Behavior of Aggregation-Induced Emission Nanoparticles and Their Biometabolic Effects via Mass Spectrometry Imaging

Simultaneous imaging of exogenous nanomaterials and endogenous metabolites in situ remains challenging and is beneficial for a systemic understanding of the biological behavior of nanomaterials at the molecular level. Here, combined with label-free mass spectrometry imaging, visualization and quantification of the aggregation-induced emission nanoparticles (NPs) in tissue were realized as well as related endogenous spatial metabolic changes simultaneously. Our approach enables us to identify the heterogeneous deposition and clearance behavior of nanoparticles in organs. The accumulation of nanoparticles in normal tissues results in distinct endogenous metabolic changes such as oxidative stress as indicated by glutathione depletion. The low passive delivery efficiency of nanoparticles to tumor foci suggested that the enrichment of NPs in tumors did not benefit from the abundant tumor vessels. Moreover, spatial-selective metabolic changes upon NPs mediated photodynamic therapy was identified, which enables understanding of the NPs induced apoptosis in the process of cancer therapy. This strategy allows us to simultaneously detect exogenous nanomaterials and endogenous metabolites in situ, hence to decipher spatial selective metabolic changes in drug delivery and cancer therapy processes.

Metabolomics meets systems immunology

Metabolic processes play a critical role in immune regulation. Metabolomics is the systematic analysis of small molecules (metabolites) in organisms or biological samples, providing an opportunity to comprehensively study interactions between metabolism and immunity in physiology and disease. Integrating metabolomics into systems immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. Here, we provide an overview on recent technological developments of metabolomic applications in immunological research. To begin, two widely used metabolomics approaches are compared: targeted and untargeted metabolomics. Then, we provide a comprehensive overview of the analysis workflow and the computational tools available, including sample preparation, raw spectra data preprocessing, data processing, statistical analysis, and interpretation. Third, we describe how to integrate metabolomics with other omics approaches in immunological studies using available tools. Finally, we discuss new developments in metabolomics and its prospects for immunology research. This review provides guidance to researchers using metabolomics and multiomics in immunity research, thus facilitating the application of systems immunology to disease research.

Analysis of Metabolite Distribution in Rat Liver of High-Fat Model by Mass Spectrometry Imaging

Hyperlipidemia is a medical condition characterized by elevated levels of blood lipids, especially triglycerides (TG). However, it remains unclear whether TG levels remain consistently elevated throughout the entire developmental stage of the high-lipid state. In our animal experiment, we found that TG levels were significantly higher in the early stage of the high-lipid model but significantly decreased at the 14th week of the late stage, reaching levels similar to those of the control group. This suggests that TG levels in the high-lipid model are not always higher than those of the control group. To determine the reason for this observation, we used in situ mass spectrometry imaging (MSI) to detect the distribution of metabolites in the liver of rats. The metabolite distribution of the control rats at different stages was significantly different from that of the model rats, and the high-lipid model differed significantly from the control rats. We identified nine functional metabolites that showed differences throughout the period, namely, PA(20:3-OH/i-21:0), PA(20:4-OH/22:6), PG(20:5-OH/i-16:0), PG(22:6-2OH/i-13:0), PG(O-18:0/20:4), PGP(18:3-OH/i-12:0), PGP(PGJ2/i-15:0), SM(d18:0/18:1-2OH), and TG(14:0/14:0/16:0), among which TG was most significantly correlated with hyperlipidemia and high lipid. This study is unique in that it used MSI to reveal the changes in metabolites in situ, showing the distribution of different metabolites or the same metabolite in liver tissue. The findings highlight the importance of considering the animal’s age when using TG as a biomarker for hyperlipidemia. Additionally, the MSI images of the liver in the high-lipid model clearly indicated the distribution and differences of more significant metabolites, providing valuable data for further research into new biomarkers and mechanisms of hyperlipidemia. This new pathway of in situ, visualized, and data-rich metabolomics research provides a more comprehensive understanding of the characteristics of high lipid and its implications for disease prevention and treatment.

Lipidomics analysis in drug discovery and development

Despite being a relatively new addition to the Omics' landscape, lipidomics is increasingly being recognized as an important tool for the identification of druggable targets and biochemical markers. In this review we present recent advances of lipid analysis in drug discovery and development. We cover current state of the art technologies which are constantly evolving to meet demands in terms of sensitivity and selectivity. A careful selection of important examples is then provided, illustrating the versatility of lipidomics analysis in the drug discovery and development process. Integration of lipidomics with other omics', stem-cell technologies, and metabolic flux analysis will open new avenues for deciphering pathophysiological mechanisms and the discovery of novel targets and biomarkers.