Spatiotemporally resolved metabolomics and isotope tracing reveal CNS drug targets

Illustrating the distribution and metabolic regulatory effects of nuciferine by mass spectrometry imaging and spatial metabolomics

Nuciferine has been widely used in traditional Chinese medicine compound preparations and natural edible resources. Most current studies have concentrated on its lipid-lowering and weight-loss effects, while relatively few have explored its impact on central nervous system disorders. To investigate the effects of nuciferine on the nervous system and its potential pharmacological mechanisms, we mapped the distribution of nuciferine and its key metabolites in brain microregions and major organs of mice using air-flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI). Nuciferine was found to be distributed throughout the brain, particularly in the prefrontal cortex and hippocampus. Additionally, nuciferine was detected in several peripheral organs, including the heart, liver, kidneys, and spleen. We also identified the distribution of a major demethylated metabolite (M1), which correlated with the localization of the CYP1A2 enzyme. Metabolomic analysis revealed that nuciferine significantly alters purine metabolism, specifically increasing adenosine levels while decreasing xanthine and hypoxanthine. This metabolic shift suggests a potential enhancement of neuroinhibitory effects, contributing to nuciferine's sedative, hypnotic, and analgesic properties. These findings provide novel insights into the neuropharmacological mechanisms of nuciferine.

BBB proteomic analysis reveals that complex febrile seizures in infancy enhance susceptibility to epilepsy in adulthood through dysregulation of ECM-receptor interaction signaling pathway

BACKGROUND

Complex febrile seizures (CFS) have been associated with an increased risk of epilepsy in adulthood. However, the specific link between blood-brain barrier (BBB) and the predisposition to epilepsy in adults who experienced CFS during infancy remains unclear. The objective of this study was to investigate the alteration of BBB in adult mice who had experienced CFS during infancy, and to explore the mechanisms of increased susceptibility to epilepsy after CFS.

METHODS

The CFS pup model was induced using hot air, and the seizure susceptibility was examined using low-dose pentylenetetrazole (PTZ) after 8 W. The brain microvessels representing BBB function were isolated and their protein expression changes were analyzed using data-independent acquisition (DIA) proteomic techniques. Subsequently, the bioinformatic analyses were performed using ClusterProfiler, STRING, Gene Set Enrichment Analysis (GSEA), etc. The enriched pathways, changes in the expression of BBB-related proteins, and alterations in metabolites including certain neurotransmitters were subsequently validated by Western Blotting, quantitative real-time polymerase chain reaction (qRT-PCR), and mass spectrometric imaging (MSI). In addition, we selected the MMP inhibitor Incyclinide to verify that dysregulation of the ECM-receptor interaction signaling pathway increases epilepsy susceptibility in adult mice.

RESULTS

Mice that experienced CFS in infancy show increased susceptibility to epilepsy in adulthood, and BBB proteomic profile was significantly altered in the CFS mice. The network analysis suggests that dysregulation of the extracellular matrix (ECM)-receptor interaction pathway is a key mechanism. Moreover, MSI analysis uncovered notable changes in differential metabolites, including amino acids and nucleotide-derived neurotransmitters associated with the function of BBB maintaining neuronal homeostasis. Subsequent validation experiments showed that dysregulation of the ECM-receptor interaction signaling pathway exacerbated epilepsy susceptibility in adult mice.

CONCLUSION

Our research represents the pioneering demonstration of the modified BBB proteomics associated with epilepsy susceptibility in adult mice previously exposed to CFS in infancy. Notably, the increased susceptibility is attributed to the dysregulation of the ECM-receptor interaction pathway. These findings may help to elucidate the role of BBB alterations in the progression of epilepsy susceptibility, and provide new orientations for subsequent prevention and treatment of epilepsy.

Spatial metabolomics and feature-based molecular networking to unveiling in-situ quality markers landscape and reflecting geographic origins of pomegranate seeds

Pomegranate seeds, a by-product of pomegranate processing, are gaining attention in food industries due to their high antioxidant activity. However, the lack of quality markers reflecting activity and spatial characteristics limits their utilization and product stability. In this research, a selective and sensitive method integrating ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry with feature-based molecular networking, and desorption electrospray ionization-mass spectrometry imaging developed to identify components and locate in-situ images of quality markers via spatial metabolomics analysis. Additionally, molecular docking analyses and 2,2-Diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assays validated the antioxidant quality markers and elucidated correlations between these markers, regions, and activity. A total of 227 components were identified, and six were selected as quality markers for pomegranate seeds, reflecting their antioxidant activity and spatial characteristics. Consequently, this research provides an efficient method for screening food quality markers based on activity and spatial characteristics, providing insights into food quality evaluation.

Spatial metabolic modulation in vascular dementia by Erigeron breviscapus injection using ambient mass spectrometry imaging

BACKGROUND

Vascular dementia (VaD), a significant cognitive disorder, is caused by reduced cerebral blood flow. Unraveling the metabolic heterogeneity and reprogramming in VaD is essential for understanding its molecular pathology and developing targeted therapies. However, the in situ metabolic regulation within the specific brain regions affected by VaD has not been thoroughly investigated, and the therapeutic mechanisms of Erigeron breviscapus injection (EBI), a traditional Chinese medicine, require further elucidation.

PURPOSE

To investigate the region-specific metabolic alterations in a VaD rat model, explore the therapeutic effects of EBI at a microregional level, identify the key metabolic pathways and metabolites involved in VaD, and elucidate how EBI modulates these pathways to exert its therapeutic effects.

METHODS

Air-flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI), a novel technique, was employed to investigate the metabolic changes in the brain microregions. We used a bilateral common carotid artery occlusion model to induce VaD in rats. Network analysis and network pharmacology were used to assess the local metabolic effects of the EBI treatment (3.6 mL/kg/day for 2 weeks).

RESULTS

The EBI treatment significantly ameliorated the neurological deficits in VaD rats. AFADESI-MSI revealed 31 key metabolites with significant alterations in the VaD model, particularly within the pathways related to neurotransmitter metabolism, redox homeostasis, and osmoregulation. The metabolic disturbances were primarily observed in the striatum (ST), pyriform cortex (PCT), hippocampus (HP), and other critical brain regions. The EBI treatment effectively reversed these metabolic imbalances, especially in neurotransmitter metabolism, suggesting its potential in mitigating VaD-related cognitive decline.

CONCLUSION

Our findings not only shed light on the molecular underpinnings of VaD but also highlight the potential of EBI as a therapeutic agent in neurodegenerative disorders. Moreover, this study demonstrates the power of advanced mass spectrometry imaging techniques in phytomedicine, offering new insights into the spatial metabolic changes induced by botanical treatments.

Integration of deep neural network modeling and LC-MS-based pseudo-targeted metabolomics to discriminate easily confused ginseng species

Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus (PJ) and Panax japonicus var. major (PJvm), containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM (sMRM), and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic (ROC)) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

Mass Spectrometry Imaging for Spatial Toxicology Research

The spatial information of xenobiotics distribution, metabolism, and toxicity mechanisms in situ has drawn increasing attention in both pharmaceutical and environmental toxicology research to aid drug development and environmental risk assessments. Mass spectrometry imaging (MSI) provides a label-free, multiplexed, and high-throughput tool to characterize xenobiotics, their metabolites, and endogenous molecules in situ with spatial resolution, providing knowledge on spatially resolved absorption, distribution, metabolism, excretion, and toxicity on the molecular level. In this perspective, we briefly summarize applications of MSI in toxicology on xenobiotic distribution and metabolism, quantification, toxicity mechanisms, and biomarker discovery. We identified several challenges regarding how we can fully harness the power of MSI in both fundamental toxicology research and regulatory practices. First, how can we increase the coverage, sensitivity, and specificity in detecting xenobiotics and their metabolites in complex biological matrices? Second, how can we link the spatial molecular information of xenobiotics to toxicity consequences to understand toxicity mechanisms, predict exposure outcomes, and aid biomarker discovery? Finally, how can we standardize the MSI experiment and data analysis workflow to provide robust conclusions for regulation and drug development? With these questions in mind, we provide our perspectives on the future directions of MSI as a promising tool in spatial toxicology research.

Spatially resolved metabolomics: From metabolite mapping to function visualising

Mass spectrometry imaging (MSI)-based spatially resolved metabolomics addresses the limitations inherent in traditional liquid chromatography-tandem mass spectrometry (LC-MS)-based metabolomics, particularly the loss of spatial context within heterogeneous tissues. MSI not only enhances our understanding of disease aetiology but also aids in the identification of biomarkers and the assessment of drug toxicity and therapeutic efficacy by converting invisible metabolites and biological networks into visually rendered image data. In this comprehensive review, we illuminate the key advancements in MSI-driven spatially resolved metabolomics over the past few years. We first outline recent innovations in preprocessing methodologies and MSI instrumentation that improve the sensitivity and comprehensiveness of metabolite detection. We then delve into the progress made in functional visualization techniques, which enhance the precision of metabolite identification and annotation. Ultimately, we discuss the significant potential applications of spatially resolved metabolomics technology in translational medicine and drug development, offering new perspectives for future research and clinical translation. HIGHLIGHTS: MSI-driven spatial metabolomics preserves metabolite spatial information, enhancing disease analysis and biomarker discovery. Advances in MSI technology improve detection sensitivity and accuracy, expanding bioanalytical applications. Enhanced visualization techniques refine metabolite identification and spatial distribution analysis. Integration of MSI with AI promises to advance precision medicine and accelerate drug development.

Metabolomics-driven approaches for identifying therapeutic targets in drug discovery

Identification of therapeutic targets can directly elucidate the mechanism and effect of drug therapy, which is a central step in drug development. The disconnect between protein targets and phenotypes under complex mechanisms hampers comprehensive target understanding. Metabolomics, as a systems biology tool that captures phenotypic changes induced by exogenous compounds, has emerged as a valuable approach for target identification. A comprehensive overview was provided in this review to illustrate the principles and advantages of metabolomics, delving into the application of metabolomics in target identification. This review outlines various metabolomics-based methods, such as dose-response metabolomics, stable isotope-resolved metabolomics, and multiomics, which identify key enzymes and metabolic pathways affected by exogenous substances through dose-dependent metabolite-drug interactions. Emerging techniques, including single-cell metabolomics, artificial intelligence, and mass spectrometry imaging, are also explored for their potential to enhance target discovery. The review emphasizes metabolomics' critical role in advancing our understanding of disease mechanisms and accelerating targeted drug development, while acknowledging current challenges in the field.

Spatial metabolomics highlights metabolic reprogramming in acute myeloid leukemia mice through creatine pathway

Acute myeloid leukemia (AML) is recognized as an aggressive cancer that is characterized by significant metabolic reprogramming. Here, we applied spatial metabolomics to achieve high-throughput, in situ identification of metabolites within the liver metastases of AML mice. Alterations at metabolite and protein levels were further mapped out and validated by integrating untargeted metabolomics and proteomics. This study showed a downregulation in arginine's contribution to polyamine biosynthesis and urea cycle, coupled with an upregulation of the creatine metabolism. The upregulation of creatine synthetases Gatm and Gamt, as well as the creatine transporter Slc6a8, resulted in a marked accumulation of creatine within tumor foci. This process further enhances oxidative phosphorylation and glycolysis of leukemia cells, thereby boosting ATP production to foster proliferation and infiltration. Importantly, we discovered that inhibiting Slc6a8 can counter these detrimental effects, offering a new strategy for treating AML by targeting metabolic pathways.

Whole-body mass spectrometry imaging reveals the systemic metabolic disorder and catecholamines biosynthesis alteration on heart-gut axis in heart failure rat

INTRODUCTION

Heart failure (HF) is a systemic metabolic disorder disease, across multiorgan investigations advancing knowledge of progression and treatment of HF. Whole-body MSI provides spatiotemporal information of metabolites in multiorgan and is expected to be a potent tool to dig out the complex mechanism of HF.

OBJECTIVES

This study aimed at exploring the systemic metabolic disorder in multiorgan and catecholamines biosynthesis alteration on heart-gut axis after HF.

METHODS

Whole-body MSI was used to characterize metabolic disorder of the whole rat body after HF. An integrated method by MSI, LC-MS/MS and ELISA was utilized to analyze key metabolites and enzymes on heart, small intestine, cecum and colon tissues of rat. Gut microbiota dysbiosis was investigated by 16S rDNA sequencing and metagenomic sequencing. Validation experiments and in vitro experiments were performed to verify the effect of catecholamines biosynthesis alteration on heart-gut axis after HF.

RESULTS

Whole-body MSI exhibited varieties of metabolites alteration in multiple organs. Remarkably, catecholamine biosynthesis was significantly altered in the serum, heart and intestines of rats. Furthermore, catecholamines and tyrosine hydroxylase were obviously upregulated in heart and colon tissue. Turicibacter_sanguinis was relevant to catecholamines of heart and colon. Validation experiments demonstrated excessive norepinephrine induced cardio-intestinal injury, including significantly elevating the levels of BNP, pro-BNP, LPS, DAO, and increased the abundance of Turicibacter_sanguinis. These alterations could be reversed by metoprolol treatment blocking the effect of norepinephrine. Additionally, in vitro studies demonstrated that norepinephrine promoted the growth of Turicibacter_sanguinis and Turicibacter_sanguinis could import and metabolize norepinephrine. Collectively, excessive norepinephrine exerted bidirectional effects on cardio-intestinal function to participate in the progression of HF.

CONCLUSION

Our study provides a new approach to elucidate multiorgan metabolic disorder and proposes new insights into heart-gut axis in HF development.

An isotopically-labelled temporal mass spectrometry imaging data analysis workflow to reveal glucose spatial metabolism patterns in bovine lens tissue

Application of stable isotopically labelled (SIL) molecules in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) over a series of time points allows the temporal and spatial dynamics of biochemical reactions to be tracked in a biological system. However, these large kinetic MSI datasets and the inherent variability of biological replicates presents significant challenges to the rapid analysis of the data. In addition, manual annotation of downstream SIL metabolites involves human input to carefully analyse the data based on prior knowledge and personal expertise. To overcome these challenges to the analysis of spatiotemporal MALDI-MSI data and improve the efficiency of SIL metabolite identification, a bioinformatics pipeline has been developed and demonstrated by analysing normal bovine lens glucose metabolism as a model system. The pipeline consists of spatial alignment to mitigate the impact of sample variability and ensure spatial comparability of the temporal data, dimensionality reduction to rapidly map regional metabolic distinctions within the tissue, and metabolite annotation coupled with pathway enrichment modules to summarise and display the metabolic pathways induced by the treatment. This pipeline will be valuable for the spatial metabolomics community to analyse kinetic MALDI-MSI datasets, enabling rapid characterisation of spatio-temporal metabolic patterns from tissues of interest.

Dual mass spectrometry imaging and spatial metabolomics to investigate the metabolism and nephrotoxicity of nitidine chloride

Evaluating toxicity and decoding the underlying mechanisms of active compounds are crucial for drug development. In this study, we present an innovative, integrated approach that combines air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI), time-of-flight secondary ion mass spectrometry (ToF-SIMS), and spatial metabolomics to comprehensively investigate the nephrotoxicity and underlying mechanisms of nitidine chloride (NC), a promising anti-tumor drug candidate. Our quantitive AFADESI-MSI analysis unveiled the region specific of accumulation of NC in the kidney, particularly within the inner cortex (IC) region, following single and repeated dose of NC. High spatial resolution ToF-SIMS analysis further allowed us to precisely map the localization of NC within the renal tubule. Employing spatial metabolomics based on AFADESI-MSI, we identified over 70 discriminating endogenous metabolites associated with chronic NC exposure. These findings suggest the renal tubule as the primary target of NC toxicity and implicate renal transporters (organic cation transporters, multidrug and toxin extrusion, and organic cation transporter 2 (OCT2)), metabolic enzymes (protein arginine N-methyltransferase (PRMT) and nitric oxide synthase), mitochondria, oxidative stress, and inflammation in NC-induced nephrotoxicity. This study offers novel insights into NC-induced renal damage, representing a crucial step towards devising strategies to mitigate renal damage caused by this compound.

Pharmacometabolomics and mass spectrometry imaging approach to reveal the neurochemical mechanisms of Polygala tenuifolia

Polygala tenuifolia, commonly known as Yuanzhi (YZ) in Chinese, has been shown to possess anti-insomnia properties. However, the material basis and the mechanism underlying its sedative-hypnotic effects remain unclear. Herein, we investigated the active components and neurochemical mechanism of YZ extracts using liquid chromatography tandem mass spectrometry (LC-MS/MS)-based pharmacometabolomics and mass spectrometry imaging (MSI)-based spatial resolved metabolomics. According to the results, 17 prototypes out of 101 ingredients in the YZ extract were detected in both the plasma and brain, which might be the major components contributing to the sedative-hypnotic effects. Network pharmacology analysis revealed that these prototypes may exert their effects through neuroactive ligand-receptor interaction, serotonergic synapse, dopaminergic synapse, and dopaminergic synapse, among other pathways. LC-MS/MS-based targeted metabolomics and Western blot (WB) revealed that tryptophan-serotonin-melatonin (Trp-5-HT-Mel) and tyrosine-norepinephrine-adrenaline (Tyr-Ne-Ad) are the key regulated pathways. Dopa decarboxylase (DDC) upregulation and phenylethanolamine N-methyltransferase (PNMT) downregulation further confirmed these pathways. Furthermore, MSI-based spatially resolved metabolomics revealed notable alterations in 5-HT in the pineal gland (PG), and Ad in the brainstem, including the middle brain (MB), pons (PN), and hypothalamus (HY). In summary, this study illustrates the efficacy of an integrated multidimensional metabolomics approach in unraveling the sedative-hypnotic effects and neurochemical mechanisms of a Chinese herbal medicine, YZ.

Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine

Aging and regeneration represent complex biological phenomena that have long captivated the scientific community. To fully comprehend these processes, it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions. Conventional omics methodologies, such as genomics and transcriptomics, have been instrumental in identifying critical molecular facets of aging and regeneration. However, these methods are somewhat limited, constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations. The advent of emerging spatiotemporal multi-omics approaches, encompassing transcriptomics, proteomics, metabolomics, and epigenomics, furnishes comprehensive insights into these intricate molecular dynamics. These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells, tissues, and organs, thereby offering an in-depth understanding of the fundamental mechanisms at play. This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research. It underscores how these methodologies augment our comprehension of molecular dynamics, cellular interactions, and signaling pathways. Initially, the review delineates the foundational principles underpinning these methods, followed by an evaluation of their recent applications within the field. The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field. Indubitably, spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration, thus charting a course toward potential therapeutic innovations.

Integrated spatial metabolomics and transcriptomics decipher the hepatoprotection mechanisms of wedelolactone and demethylwedelolactone on non-alcoholic fatty liver disease

Eclipta prostrata L. has been used in traditional medicine and known for its liver-protective properties for centuries. Wedelolactone (WEL) and demethylwedelolactone (DWEL) are the major coumarins found in E. prostrata L. However, the comprehensive characterization of these two compounds on non-alcoholic fatty liver disease (NAFLD) still remains to be explored. Utilizing a well-established zebrafish model of thioacetamide (TAA)-induced liver injury, the present study sought to investigate the impacts and mechanisms of WEL and DWEL on NAFLD through integrative spatial metabolomics with liver-specific transcriptomics analysis. Our results showed that WEL and DWEL significantly improved liver function and reduced the accumulation of fat in the liver. The biodistributions and metabolism of these two compounds in whole-body zebrafish were successfully mapped, and the discriminatory endogenous metabolites reversely regulated by WEL and DWEL treatments were also characterized. Based on spatial metabolomics and transcriptomics, we identified that steroid biosynthesis and fatty acid metabolism are mainly involved in the hepatoprotective effects of WEL instead of DWEL. Our study unveils the distinct mechanism of WEL and DWEL in ameliorating NAFLD, and presents a "multi-omics" platform of spatial metabolomics and liver-specific transcriptomics to develop highly effective compounds for further improved therapy.

Tracing the path of disruption: 13C isotope applications in traumatic brain injury-induced metabolic dysfunction

Cerebral metabolic dysfunction is a critical pathological hallmark observed in the aftermath of traumatic brain injury (TBI), as extensively documented in clinical investigations and experimental models. An in-depth understanding of the bioenergetic disturbances that occur following TBI promises to reveal novel therapeutic targets, paving the way for the timely development of interventions to improve patient outcomes. The 13C isotope tracing technique represents a robust methodological advance, harnessing biochemical quantification to delineate the metabolic trajectories of isotopically labeled substrates. This nuanced approach enables real-time mapping of metabolic fluxes, providing a window into the cellular energetic state and elucidating the perturbations in key metabolic circuits. By applying this sophisticated tool, researchers can dissect the complexities of bioenergetic networks within the central nervous system, offering insights into the metabolic derangements specific to TBI pathology. Embraced by both animal studies and clinical research, 13C isotope tracing has bolstered our understanding of TBI-induced metabolic dysregulation. This review synthesizes current applications of isotope tracing and its transformative potential in evaluating and addressing the metabolic sequelae of TBI.

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

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

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.