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

Metabolic reprogramming: a new option for the treatment of spinal cord injury

Spinal cord injuries impose a notably economic burden on society, mainly because of the severe after-effects they cause. Despite the ongoing development of various therapies for spinal cord injuries, their effectiveness remains unsatisfactory. However, a deeper understanding of metabolism has opened up a new therapeutic opportunity in the form of metabolic reprogramming. In this review, we explore the metabolic changes that occur during spinal cord injuries, their consequences, and the therapeutic tools available for metabolic reprogramming. Normal spinal cord metabolism is characterized by independent cellular metabolism and intercellular metabolic coupling. However, spinal cord injury results in metabolic disorders that include disturbances in glucose metabolism, lipid metabolism, and mitochondrial dysfunction. These metabolic disturbances lead to corresponding pathological changes, including the failure of axonal regeneration, the accumulation of scarring, and the activation of microglia. To rescue spinal cord injury at the metabolic level, potential metabolic reprogramming approaches have emerged, including replenishing metabolic substrates, reconstituting metabolic couplings, and targeting mitochondrial therapies to alter cell fate. The available evidence suggests that metabolic reprogramming holds great promise as a next-generation approach for the treatment of spinal cord injury. To further advance the metabolic treatment of the spinal cord injury, future efforts should focus on a deeper understanding of neurometabolism, the development of more advanced metabolomics technologies, and the design of highly effective metabolic interventions.

In Situ Isotope Tracing at Single-Cell Resolution Using Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) allows for label-free spatial molecular interrogation of tissues. With advances in the field over recent years, the spatial resolution at which MSI data can be recorded has reached the single-cell level. This makes MSI complementary to other single-cell omics technologies. As metabolism is a highly dynamic process, capturing the metabolic turnover adds a valuable layer of information. Here, we describe how to set up in situ stable isotope tracing followed by MSI-enabled spatial metabolomics to perform dynamic metabolomics at the single-cell level.

(Pre)Clinical Metabolomics Analysis

Metabolomics is the scientific field with the eager goal to comprehensively analyze the entirety of all small molecules of a biological system, i.e., the metabolome. Over the last few years, metabolomics has matured to become an analytical cornerstone of life science research across diverse fields, from fundamental biochemical applications to preclinical studies, including biomarker discovery and drug development. In this chapter, we provide an introduction to (pre)clinical metabolomics. We define key metabolomics aspects and provide the basis to thoroughly understand the relevance of this field in a biological and clinical context. We present and explain state-of-the-art analytical technologies devoted to metabolomic analysis as well as emerging technologies, discussing both strengths and weaknesses. Given the ever-increasing demand for handling complex datasets, the role of bioinformatics approaches in the context of metabolomic analysis is also illustrated.

Biofluorescence imaging-guided spatial metabolic tracing: In vivo tracking of metabolic activity in circulating tumor cell-mediated multi-organ metastases

Circulating tumor cells (CTC) are considered metastatic precursors that are shed from the primary or metastatic deposits and navigate the bloodstream before undergoing extravasation to establish distant metastases. Metabolic reprogramming appears to be a hallmark of metastatic progression, yet current methods for evaluating metabolic heterogeneity within organ-specific metastases in vivo are limited. To overcome this challenge, we present Biofluorescence Imaging-Guided Spatial Metabolic Tracing (BIGSMT), a novel approach integrating in vivo biofluorescence imaging, stable isotope tracing, stain-free laser capture microdissection, and liquid chromatography-mass spectrometry. This innovative technology obviates the need for staining or intricate sample preparation, mitigating metabolite loss, and substantially enhances detection sensitivity and accuracy through chemical derivatization of polar metabolites in central carbon pathways. Application of BIGSMT to a preclinical CTC-mediated metastasis mouse model revealed significant heterogeneity in the in vivo carbon flux from glucose into glycolysis and the tricarboxylic acid (TCA) cycle across distinct metastatic sites. Our analysis indicates that carbon predominantly enters the TCA cycle through the enzymatic reaction catalyzed by pyruvate dehydrogenase. Thus, our spatially resolved BIGSMT technology provides fresh insights into the metabolic heterogeneity and evolution during melanoma CTC-mediated metastatic progression and points to novel therapeutic opportunities.

Identifying metabolic limitations in the tumor microenvironment

Solid tumors are characterized by dysfunctional vasculature that limits perfusion and delivery of nutrients to the tumor microenvironment. Limited perfusion coupled with the high metabolic demand of growing tumors has led to the hypothesis that many tumors experience metabolic stress driven by limited availability of nutrients such as glucose, oxygen, and amino acids in the tumor. Such metabolic stress has important implications for the biology of cells in the microenvironment, affecting both disease progression and response to therapies. Recently, techniques have been developed to identify limiting nutrients and resulting metabolic stresses in solid tumors. These techniques have greatly expanded our understanding of the metabolic limitations in tumors. This review will discuss these experimental tools and the emerging picture of metabolic limitations in tumors arising from recent studies using these approaches.

Single-cell and spatial omics unravel the spatiotemporal biology of tumour border invasion and haematogenous metastasis

Solid tumours exhibit a well-defined architecture, comprising a differentiated core and a dynamic border that interfaces with the surrounding tissue. This border, characterised by distinct cellular morphology and molecular composition, serves as a critical determinant of the tumour's invasive behaviour. Notably, the invasive border of the primary tumour represents the principal site for intravasation of metastatic cells. These cells, known as circulating tumour cells (CTCs), function as 'seeds' for distant dissemination and display remarkable heterogeneity. Advancements in spatial sequencing technology are progressively unveiling the spatial biological features of tumours. However, systematic investigations specifically targeting the characteristics of the tumour border remain scarce. In this comprehensive review, we illuminate key biological insights along the tumour body-border-haematogenous metastasis axis over the past five years. We delineate the distinctive landscape of tumour invasion boundaries and delve into the intricate heterogeneity and phenotype of CTCs, which orchestrate haematogenous metastasis. These insights have the potential to explain the basis of tumour invasion and distant metastasis, offering new perspectives for the development of more complex and precise clinical interventions and treatments.

Deciphering breast cancer dynamics: insights from single-cell and spatial profiling in the multi-omics era

As one of the most common tumors in women, the pathogenesis and tumor heterogeneity of breast cancer have long been the focal point of research, with the emergence of tumor metastasis and drug resistance posing persistent clinical challenges. The emergence of single-cell sequencing (SCS) technology has introduced novel approaches for gaining comprehensive insights into the biological behavior of malignant tumors. SCS is a high-throughput technology that has rapidly developed in the past decade, providing high-throughput molecular insights at the individual cell level. Furthermore, the advent of multitemporal point sampling and spatial omics also greatly enhances our understanding of cellular dynamics at both temporal and spatial levels. The paper provides a comprehensive overview of the historical development of SCS, and highlights the most recent advancements in utilizing SCS and spatial omics for breast cancer research. The findings from these studies will serve as valuable references for future advancements in basic research, clinical diagnosis, and treatment of breast cancer.

The burgeoning spatial multi-omics in human gastrointestinal cancers

The development and progression of diseases in multicellular organisms unfold within the intricate three-dimensional body environment. Thus, to comprehensively understand the molecular mechanisms governing individual development and disease progression, precise acquisition of biological data, including genome, transcriptome, proteome, metabolome, and epigenome, with single-cell resolution and spatial information within the body's three-dimensional context, is essential. This foundational information serves as the basis for deciphering cellular and molecular mechanisms. Although single-cell multi-omics technology can provide biological information such as genome, transcriptome, proteome, metabolome, and epigenome with single-cell resolution, the sample preparation process leads to the loss of spatial information. Spatial multi-omics technology, however, facilitates the characterization of biological data, such as genome, transcriptome, proteome, metabolome, and epigenome in tissue samples, while retaining their spatial context. Consequently, these techniques significantly enhance our understanding of individual development and disease pathology. Currently, spatial multi-omics technology has played a vital role in elucidating various processes in tumor biology, including tumor occurrence, development, and metastasis, particularly in the realms of tumor immunity and the heterogeneity of the tumor microenvironment. Therefore, this article provides a comprehensive overview of spatial transcriptomics, spatial proteomics, and spatial metabolomics-related technologies and their application in research concerning esophageal cancer, gastric cancer, and colorectal cancer. The objective is to foster the research and implementation of spatial multi-omics technology in digestive tumor diseases. This review will provide new technical insights for molecular biology researchers.

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.

Metabolic ripple effects - deciphering how lipid metabolism in cancer interfaces with the tumor microenvironment

Cancer cells require a constant supply of lipids. Lipids are a diverse class of hydrophobic molecules that are essential for cellular homeostasis, growth and survival, and energy production. How tumors acquire lipids is under intensive investigation, as these mechanisms could provide attractive therapeutic targets for cancer. Cellular lipid metabolism is tightly regulated and responsive to environmental stimuli. Thus, lipid metabolism in cancer is heavily influenced by the tumor microenvironment. In this Review, we outline the mechanisms by which the tumor microenvironment determines the metabolic pathways used by tumors to acquire lipids. We also discuss emerging literature that reveals that lipid availability in the tumor microenvironment influences many metabolic pathways in cancers, including those not traditionally associated with lipid biology. Thus, metabolic changes instigated by the tumor microenvironment have 'ripple' effects throughout the densely interconnected metabolic network of cancer cells. Given the interconnectedness of tumor metabolism, we also discuss new tools and approaches to identify the lipid metabolic requirements of cancer cells in the tumor microenvironment and characterize how these requirements influence other aspects of tumor metabolism.

Premalignant Progression in the Lung: Knowledge Gaps and Novel Opportunities for Interception of Non-Small Cell Lung Cancer. An Official American Thoracic Society Research Statement

Rationale: Despite significant advances in precision treatments and immunotherapy, lung cancer is the most common cause of cancer death worldwide. To reduce incidence and improve survival rates, a deeper understanding of lung premalignancy and the multistep process of tumorigenesis is essential, allowing timely and effective intervention before cancer development. Objectives: To summarize existing information, identify knowledge gaps, formulate research questions, prioritize potential research topics, and propose strategies for future investigations into the premalignant progression in the lung. Methods: An international multidisciplinary team of basic, translational, and clinical scientists reviewed available data to develop and refine research questions pertaining to the transformation of premalignant lung lesions to advanced lung cancer. Results: This research statement identifies significant gaps in knowledge and proposes potential research questions aimed at expanding our understanding of the mechanisms underlying the progression of premalignant lung lesions to lung cancer in an effort to explore potential innovative modalities to intercept lung cancer at its nascent stages. Conclusions: The identified gaps in knowledge about the biological mechanisms of premalignant progression in the lung, together with ongoing challenges in screening, detection, and early intervention, highlight the critical need to prioritize research in this domain. Such focused investigations are essential to devise effective preventive strategies that may ultimately decrease lung cancer incidence and improve patient outcomes.

Applying Spatial Metabolomics To Investigate Age- and Drug-Induced Neurochemical Changes

In an era when population aging is increasing the burden of neurodegenerative conditions, deciphering the mechanisms underlying brain senescence is more important than ever. Here, we present a spatial metabolomics analysis of age-induced neurochemical alterations in the mouse brain using negative ionization mode mass spectrometry imaging. The age-dependent effects of the acetylcholinesterase inhibitor tacrine were simultaneously examined. For ultrahigh mass resolution analysis, we utilized a Fourier-transform ion cyclotron resonance spectrometer. To complement this, a trapped ion mobility spectrometry time-of-flight analyzer provided high speed and lateral resolution. The chosen approach facilitated the detection and identification of a wide range of metabolites, from amino acids to sphingolipids. We reported significant, age-dependent alterations in brain lipids which were most evident for sulfatides and lysophosphatidic acids. Sulfatide species, which are mainly localized to white matter, either increased or decreased with age, depending on the carbon chain length and hydroxylation stage. Lysophosphatidic acids were found to decrease with age in the detailed cortical and hippocampal subregions. An age-dependent increase in the glutamine/glutamate ratio, an indicator of glia-neuron interconnection and neurotoxicity, was detected after tacrine administration. The presented metabolic mapping approach was able to provide visualizations of the lipid signaling and neurotransmission alterations induced by early aging and can thus be beneficial to further elucidating age-related neurochemical pathways.

Mass spectrometry imaging as a promising analytical technique for herbal medicines: an updated review

Herbal medicines (HMs) have long played a pivotal role in preventing and treating various human diseases and have been studied widely. However, the complexities present in HM metabolites and their unclear mechanisms of action have posed significant challenges in the modernization of traditional Chinese medicine (TCM). Over the past two decades, mass spectrometry imaging (MSI) has garnered increasing attention as a robust analytical technique that enables the simultaneous execution of qualitative, quantitative, and localization analyses without complex sample pretreatment. With advances in technical solutions, MSI has been extensively applied in the field of HMs. MSI, a label-free ion imaging technique can comprehensively map the spatial distribution of HM metabolites in plant native tissues, thereby facilitating the effective quality control of HMs. Furthermore, the spatial dimension information of small molecule endogenous metabolites within animal tissues provided by MSI can also serve as a supplement to uncover pharmacological and toxicological mechanisms of HMs. In the review, we provide an overview of the three most common MSI techniques. In addition, representative applications in HM are highlighted. Finally, we discuss the current challenges and propose several potential solutions. We hope that the summary of recent findings will contribute to the application of MSI in exploring metabolites and mechanisms of action of HMs.

Application of Metabolomics across the Spectrum of Pulmonary and Critical Care Medicine

In recent years, metabolomics, the systematic study of small-molecule metabolites in biological samples, has yielded fresh insights into the molecular determinants of pulmonary diseases and critical illness. The purpose of this article is to orient the reader to this emerging field by discussing the fundamental tenets underlying metabolomics research, the tools and techniques that serve as foundational methodologies, and the various statistical approaches to analysis of metabolomics datasets. We present several examples of metabolomics applied to pulmonary and critical care medicine to illustrate the potential of this avenue of research to deepen our understanding of pathophysiology. We conclude by reviewing recent advances in the field and future research directions that stand to further the goal of personalizing medicine to improve patient care.

Imaging immunometabolism in situ in live animals

Immunometabolism is a rapidly developing field that holds great promise for diagnostic and therapeutic benefits to human diseases. The field has emerged based on seminal findings from in vitro and ex vivo studies that established the fundamental role of metabolism in immune cell effector functions. Currently, the field is acknowledging the necessity of investigating cellular metabolism within the natural context of biological processes. Examining cells in their native microenvironment is essential not only to reveal cell-intrinsic mechanisms but also to understand how cross-talk between neighboring cells regulates metabolism at the tissue level in a local niche. This necessity is driving innovation and advancement in multiple imaging-based technologies to enable analysis of dynamic intracellular metabolism at the single-cell level, with spatial and temporal resolution. In this review, we tally the currently available imaging-based technologies and explore the emerging methods of Raman and autofluorescence lifetime imaging microscopy, which hold significant potential and offer broad applications in the field of immunometabolism.

Historic obstacles and emerging opportunities in the field of developmental metabolism - lessons from Heidelberg

The field of developmental metabolism is experiencing a technological revolution that is opening entirely new fields of inquiry. Advances in metabolomics, small-molecule sensors, single-cell RNA sequencing and computational modeling present new opportunities for exploring cell-specific and tissue-specific metabolic networks, interorgan metabolic communication, and gene-by-metabolite interactions in time and space. Together, these advances not only present a means by which developmental biologists can tackle questions that have challenged the field for centuries, but also present young scientists with opportunities to define new areas of inquiry. These emerging frontiers of developmental metabolism were at the center of a highly interactive 2023 EMBO workshop 'Developmental metabolism: flows of energy, matter, and information'. Here, we summarize key discussions from this forum, emphasizing modern developmental biology's challenges and opportunities.

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.

A practical guide to spatial transcriptomics

Spatial transcriptomics is revolutionizing modern biology, offering researchers an unprecedented ability to unravel intricate gene expression patterns within tissues. From pioneering techniques to newly commercialized platforms, the field of spatial transcriptomics has evolved rapidly, ushering in a new era of understanding across various disciplines, from developmental biology to disease research. This dynamic expansion is reflected in the rapidly growing number of technologies and data analysis techniques developed and introduced. However, the expanding landscape presents a considerable challenge for researchers, especially newcomers to the field, as staying informed about these advancements becomes increasingly complex. To address this challenge, we have prepared an updated review with a particular focus on technologies that have reached commercialization and are, therefore, accessible to a broad spectrum of potential new users. In this review, we present the fundamental principles of spatial transcriptomic methods, discuss the challenges in data analysis, provide insights into experimental considerations, offer information about available resources for spatial transcriptomics, and conclude with a guide for method selection and a forward-looking perspective. Our aim is to serve as a guiding resource for both experienced users and newcomers navigating the complex realm of spatial transcriptomics in this era of rapid development. We intend to equip researchers with the necessary knowledge to make informed decisions and contribute to the cutting-edge research that spatial transcriptomics offers.

Metabolic rewiring and communication in cancer immunity

The immune system shapes tumor development and progression. Although immunotherapy has transformed cancer treatment, its overall efficacy remains limited, underscoring the need to uncover mechanisms to improve therapeutic effects. Metabolism-associated processes, including intracellular metabolic reprogramming and intercellular metabolic crosstalk, are emerging as instructive signals for anti-tumor immunity. Here, we first summarize the roles of intracellular metabolic pathways in controlling immune cell function in the tumor microenvironment. How intercellular metabolic communication regulates anti-tumor immunity, and the impact of metabolites or nutrients on signaling events, are also discussed. We then describe how targeting metabolic pathways in tumor cells or intratumoral immune cells or via nutrient-based interventions may boost cancer immunotherapies. Finally, we conclude with discussions on profiling and functional perturbation methods of metabolic activity in intratumoral immune cells, and perspectives on future directions. Uncovering the mechanisms for metabolic rewiring and communication in the tumor microenvironment may enable development of novel cancer immunotherapies.

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.

Metabolic regulation of the hallmarks of stem cell biology

Stem cells perform many different functions, each of which requires specific metabolic adaptations. Over the past decades, studies of pluripotent and tissue stem cells have uncovered a range of metabolic preferences and strategies that correlate with or exert control over specific cell states. This review aims to describe the common themes that emerge from the study of stem cell metabolism: (1) metabolic pathways supporting stem cell proliferation, (2) metabolic pathways maintaining stem cell quiescence, (3) metabolic control of cellular stress responses and cell death, (4) metabolic regulation of stem cell identity, and (5) metabolic requirements of the stem cell niche.

Complexity of fungal polyketide biosynthesis and function

Where does one draw the line between primary and secondary metabolism? The answer depends on the perspective. Microbial secondary metabolites (SMs) were at first believed not to be very important for the producers because they are dispensable for growth under laboratory conditions. However, such compounds become important in natural niches of the organisms, and some are of prime importance for humanity. Polyketides are an important group of SMs with aflatoxin as a well-known and well-characterized example. In Aspergillus spp., all 34 afl genes encoding the enzymes for aflatoxin biosynthesis are located in close vicinity on chromosome III in a so-called gene cluster. This led to the assumption that most genes required for polyketide biosynthesis are organized in gene clusters. Recent research, however, revealed an enormous complexity of the biosynthesis of different polyketides, ranging from individual polyketide synthases to a gene cluster producing several compounds, or to several clusters with additional genes scattered in the genome for the production of one compound. Research of the last decade furthermore revealed a huge potential for SM biosynthesis hidden in fungal genomes, and methods were developed to wake up such sleeping genes. The analysis of organismic interactions starts to reveal some of the ecological functions of polyketides for the producing fungi.

MSIpixel: a fully automated pipeline for compound annotation and quantitation in mass spectrometry imaging experiments

Mass spectrometry imaging (MSI) is commonly used to map the spatial distribution of small molecules within complex biological matrices. One of the major challenges in imaging MS-based spatial metabolomics is molecular identification and metabolite annotation, to address this limitation, annotation is often complemented with parallel bulk LC-MS2-based metabolomics to confirm and validate identifications. Here we applied MSI method, utilizing data-dependent acquisition, to visualize and identify unknown molecules in a single instrument run. To reach this aim we developed MSIpixel, a fully automated pipeline for compound annotation and quantitation in MSI experiments. It overcomes challenges in molecular identification, and improving reliability and comprehensiveness in MSI-based spatial metabolomics.

Matrix Selection for the Visualization of Small Molecules and Lipids in Brain Tumors Using Untargeted MALDI-TOF Mass Spectrometry Imaging

Matrix-assisted laser desorption/ionization mass spectrometry imaging allows for the study of metabolic activity in the tumor microenvironment of brain cancers. The detectable metabolites within these tumors are contingent upon the choice of matrix, deposition technique, and polarity setting. In this study, we compared the performance of three different matrices, two deposition techniques, and the use of positive and negative polarity in two different brain cancer types and across two species. Optimal combinations were confirmed by a comparative analysis of lipid and small-molecule abundance by using liquid chromatography-mass spectrometry and RNA sequencing to assess differential metabolites and enzymes between normal and tumor regions. Our findings indicate that in the tumor-bearing brain, the recrystallized α-cyano-4-hydroxycinnamic acid matrix with positive polarity offered superior performance for both detected metabolites and consistency with other techniques. Beyond these implications for brain cancer, our work establishes a workflow to identify optimal matrices for spatial metabolomics studies.