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.

SmartGate is a spatial metabolomics tool for resolving tissue structures.

Imaging mass spectrometry (IMS) is one of the powerful tools in spatial metabolomics for obtaining metabolite data and probing the internal microenvironment of organisms. It has dramatically advanced the understanding of the structure of biological tissues and the drug treatment of diseases. However, the complexity of IMS data hinders the further acquisition of biomarkers and the study of certain specific activities of organisms. To this end, we introduce an artificial intelligence tool, SmartGate, to enable automatic peak selection and spatial structure identification in an iterative manner. SmartGate selects discriminative m/z features from the previous iteration by differential analysis and employs a graph attention autoencoder model to perform spatial clustering for tissue segmentation using the selected features. We applied SmartGate to diverse IMS data at multicellular or subcellular spatial resolutions and compared it with four competing methods to demonstrate its effectiveness. SmartGate can significantly improve the accuracy of spatial segmentation and identify biomarker metabolites based on tissue structure-guided differential analysis. For multiple consecutive IMS data, SmartGate can effectively identify structures with spatial heterogeneity by introducing three-dimensional spatial neighbor information.

Strigolactones repress nodule development and senescence in pea.

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

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

BACKGROUND: Chronic kidney disease (CKD) presents a persistent global health challenge, characterized by complex pathophysiology and diverse progression patterns. Metabolomics has emerged as a valuable tool in unraveling the intricate molecular mechanisms driving CKD progression. SUMMARY: This comprehensive review provides a summary of recent progress in the field of metabolomics in kidney disease with a focus on spatial metabolomics to shed important insights to enhancing our understanding of CKD progression, emphasizing its transformative potential in early disease detection, refined risk assessment, and the development of targeted interventions to improve patient outcomes. KEY MESSAGE: Through an extensive analysis of metabolic pathways and small-molecule fluctuations, bulk and spatial metabolomics offers unique insights spanning the entire spectrum of CKD, from early stages to advanced disease states. Recent advances in metabolomics technology have enabled spatial identification of biomarkers to provide breakthrough discoveries in predicting CKD trajectory and enabling personalized risk assessment. Furthermore, metabolomics can help decipher the complex molecular intricacies associated with kidney diseases for exciting novel therapeutic approaches. A recent example is the identification of adenine as a key marker of kidney fibrosis for diabetic kidney disease using both untargeted and targeted bulk and spatial metabolomics. The metabolomics studies were critical to identify a new biomarker for kidney failure and to guide new therapeutics for diabetic kidney disease. Similar approaches are being pursued for acute kidney injury and other kidney diseases to enhance precision medicine decision-making.

Impact of spatial metabolomics on immune-microenvironment in oral cancer prognosis: a clinical report.

MALDI imaging for metabolites and immunohistochemistry for 38 immune markers was used to characterize the spatial biology of 2 primary oral tumours, one from a patient with an early recurrence (Tumour R), and the other from a patient with no recurrence 2 years after treatment completion (Tumour NR). Tumour R had an increased purine nucleotide metabolism in different regions of tumour and adenosine-mediated suppression of immune cells compared to Tumour NR. The differentially expressed markers in the different spatial locations in tumour R were CD33, CD163, TGF-ß, COX2, PD-L1, CD8 and CD20. These results suggest that altered tumour metabolomics concomitant with a modified immune microenvironment could be a potential marker of recurrence.

Spatial metabolomics method to reveal the differences in chemical composition of raw and honey-fried Stemona tuberosa Lour. by using UPLC-Orbitrap Fusion MS and desorption electrospray ionization mass spectrometry imaging.

INTRODUCTION: Stemona tuberosa Lour. (ST) is a significant traditional Chinese medicine (TCM) renowned for its antitussive and insecticidal properties. ST is commonly subjected to processing in clinical practice before being utilized as a medicinal substance. Currently, the customary technique for processing ST is honey-fried. Nevertheless, the specific variations in chemical constituents of ST before and after honey-fried remain unclear. OBJECTIVE: This work aimed to analyze the variations in chemical constituents of ST before and after honey-fried and to study the distribution of differential markers in the roots. METHODS: UPLC-Orbitrap Fusion MS combined with molecular network analysis was used to analyze the metabolome of ST and honey-fried ST (HST) and to screen the differential metabolites by multivariate statistical analysis. Spatial metabolomics was applied to study the distribution of differential metabolites by desorption electrospray ionization mass spectrometry imaging (DESI-MSI). RESULTS: The ST and HST exhibited notable disparities, with 56 and 61 chemical constituents found from each, respectively. After processing, the types of alkaloids decreased, and 12 differential metabolites were screened from the common compounds. The notable component variations were epibisdehydro-tuberostemonine J, neostenine, tuberostemonine, croomine, neotuberostemonine, and so forth. MSI visualized the spatial distribution of differential metabolites. CONCLUSIONS: Our research provided a rapid and effective visualization method for the identification and spatial distribution of metabolites in ST. Compared with the traditional method, this method offered more convincing data supporting the processing mechanism investigations of Stemona tuberosa from a macroscopic perspective.

Advances in mass spectrometry imaging for spatial cancer metabolomics.

Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.

Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics.

Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main technical advantages over traditional LC-MS workflows. Firstly, in addition to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochemical identifier related to the chemical shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biological and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and molecular annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.

Heat-evolved algal symbionts enhance bleaching tolerance of adult corals without trade-off against growth.

Ocean warming has caused coral mass bleaching and mortality worldwide and the persistence of symbiotic reef-building corals requires rapid acclimation or adaptation. Experimental evolution of the coral's microalgal symbionts followed by their introduction into coral is one potential method to enhance coral thermotolerance. Heat-evolved microalgal symbionts of the generalist species, Cladocopium proliferum (strain SS8), were exposed to elevated temperature (31°C) for ~10 years, and were introduced into four genotypes of chemically bleached adult fragments of the scleractinian coral, Galaxea fascicularis. Two of the four coral genotypes acquired SS8. The new symbionts persisted for the 5 months of the experiment and enhanced adult coral thermotolerance, compared with corals that were inoculated with the wild-type C. proliferum strain. Thermotolerance of SS8-corals was similar to that of coral fragments from the same colony hosting the homologous symbiont, Durusdinium sp., which is naturally heat tolerant. However, SS8-coral fragments exhibited faster growth and recovered cell density and photochemical efficiency more quickly following chemical bleaching and inoculation under ambient temperature relative to Durusdinium-corals. Mass spectrometry imaging suggests that algal pigments involved in photobiology and oxidative stress were the greatest contributors to the thermotolerance differences between coral hosting heat-evolved versus wild-type C. proliferum. These pigments may have increased photoprotection in the heat-evolved symbionts. This is the first laboratory study to show that thermotolerance of adult corals (G. fascicularis) can be enhanced via the uptake of exogenously supplied, heat-evolved symbionts, without a trade-off against growth under ambient temperature. Importantly, heat-evolved C. proliferum remained in the corals in moderate abundance 2 years after first inoculation, suggesting long-term stability of this novel symbiosis and potential long-term benefits to coral thermotolerance.

Metabolic tumor constitution is superior to tumor regression grading for evaluating response to neoadjuvant therapy of esophageal adenocarcinoma patients.

The response to neoadjuvant therapy can vary widely between individual patients. Histopathological tumor regression grading (TRG) is a strong factor for treatment response and survival prognosis of esophageal adenocarcinoma (EAC) patients following neoadjuvant treatment and surgery. However, TRG systems are usually based on the estimation of residual tumor but do not consider stromal or metabolic changes after treatment. Spatial metabolomics analysis is a powerful tool for molecular tissue phenotyping but has not been used so far in the context of neoadjuvant treatment of esophageal cancer. We used imaging mass spectrometry to assess the potential of spatial metabolomics on tumor and stroma tissue for evaluating therapy response of neoadjuvant-treated EAC patients. With an accuracy of 89.7%, the binary classifier trained on spatial tumor metabolite data proved to be superior for stratifying patients when compared with histopathological response assessment, which had an accuracy of 70.5%. Sensitivities and specificities for the poor and favorable survival patient groups ranged from 84.9% to 93.3% using the metabolic classifier and from 62.2% to 78.1% using TRG. The tumor classifier was the only significant prognostic factor (HR 3.38, 95% CI 1.40-8.12, p = 0.007) when adjusted for clinicopathological parameters such as TRG (HR 1.01, 95% CI 0.67-1.53, p = 0.968) or stromal classifier (HR 1.86, 95% CI 0.81-4.25, p = 0.143). The classifier even allowed us to further stratify patients within the TRG1-3 categories. The underlying mechanisms of response to treatment have been figured out through network analysis. In summary, metabolic response evaluation outperformed histopathological response evaluation in our study with regard to prognostic stratification. This finding indicates that the metabolic constitution of the tumor may have a greater impact on patient survival than the quantity of residual tumor cells or the stroma. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Spatially Resolved Co-Imaging of Polyhalogenated Xenobiotics and Endogenous Metabolites Reveals Xenobiotic-Induced Metabolic Alterations.

A large group of polyhalogenated compounds has been added to the list of persistent organic pollutants in a global convention endorsed by over 100 nations. Once entering the biotas, these pollutants are transported to focal sites of toxicological action and affected endogenous metabolites, which exhibited distinct tissue or organ distribution patterns. However, no study is available to achieve simultaneous mapping of the spatial distributions of xenobiotics and endogenous metabolites for clarifying the molecular mechanism of toxicities. Herein, we present a sensitive mass spectrometry imaging method─tetraphenyl phosphonium chloride-enhanced ionization coupled with air flow-assisted ionization-Orbitrap mass spectrometry─which simultaneously determined the spatial distributions of polyhalogenated xenobiotics and endogenous metabolites. The spatially resolved toxicokinetics and toxicodynamics of typical polyhalogenated compounds (chlorinated paraffins (CPs) and hexabromocyclododecane (HBCD)) were assessed in zebrafish. Co-imaging of polyhalogenated compounds and metabolites visualized the major accumulation organs and maternal transfer of HBCD and CPs, and it clarified the reproductive toxicity of HBCD. CPs were accumulated in the liver, heart, and brain and decreased the concentrations of polyamine/inosine-related metabolites and lipid molecules in these organs. HBCD accumulated in the ovary and was effectively transferred to eggs, and it also disrupted normal follicular development and impaired the production of mature eggs from the ovary by inhibiting expressions of the luteinizing hormone/choriogonadotropin receptor gene. The toxic effects of metabolic disruptions were validated by organ-specific histopathological examinations. These results highlight the necessity to assess the distributions and bioeffects of pollutants in a spatial perspective.

Single cell metabolism: current and future trends.

Single cell metabolomics is an emerging and rapidly developing field that complements developments in single cell analysis by genomics and proteomics. Major goals include mapping and quantifying the metabolome in sufficient detail to provide useful information about cellular function in highly heterogeneous systems such as tissue, ultimately with spatial resolution at the individual cell level. The chemical diversity and dynamic range of metabolites poses particular challenges for detection, identification and quantification. In this review we discuss both significant technical issues of measurement and interpretation, and progress toward addressing them, with recent examples from diverse biological systems. We provide a framework for further directions aimed at improving workflow and robustness so that such analyses may become commonly applied, especially in combination with metabolic imaging and single cell transcriptomics and proteomics.

Spatial metabolomics on liver cirrhosis to hepatocellular carcinoma progression.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the deadliest cancers and is mainly developed from chronic liver diseases such as hepatitis-B infection-associated liver cirrhosis (LC). The progression from LC to HCC makes the detection of diagnostic biomarkers to be challenging. Hence, there have been constant efforts to improve on identifying the critical and predictive changes accompanying the disease progression. METHODS: In this study, we looked to using the mass spectrometry mediated spatial metabolomics technique to simultaneous examine hundreds of metabolites in an untargeted fashion. Additionally, metabolic profiles were compared between six subregions within the HCC tissue to collect spatial information. RESULTS: Through those metabolites, altered metabolic pathways in LC and HCC were identified. Specifically, the amino acid metabolisms and the glycerophospholipid metabolisms experienced the most changes. Many of the altered metabolites and metabolic pathways were able to be connected through the urea cycle. CONCLUSIONS: The identification of the key metabolites and pathways can expand our knowledge on HCC metabolic reprogramming and help us exam potential biomarkers for earlier detection of the malignant disease progression.

Advances in Plant Metabolomics and Its Applications in Stress and Single-Cell Biology.

In the past two decades, the post-genomic era envisaged high-throughput technologies, resulting in more species with available genome sequences. In-depth multi-omics approaches have evolved to integrate cellular processes at various levels into a systems biology knowledge base. Metabolomics plays a crucial role in molecular networking to bridge the gaps between genotypes and phenotypes. However, the greater complexity of metabolites with diverse chemical and physical properties has limited the advances in plant metabolomics. For several years, applications of liquid/gas chromatography (LC/GC)-mass spectrometry (MS) and nuclear magnetic resonance (NMR) have been constantly developed. Recently, ion mobility spectrometry (IMS)-MS has shown utility in resolving isomeric and isobaric metabolites. Both MS and NMR combined metabolomics significantly increased the identification and quantification of metabolites in an untargeted and targeted manner. Thus, hyphenated metabolomics tools will narrow the gap between the number of metabolite features and the identified metabolites. Metabolites change in response to environmental conditions, including biotic and abiotic stress factors. The spatial distribution of metabolites across different organs, tissues, cells and cellular compartments is a trending research area in metabolomics. Herein, we review recent technological advancements in metabolomics and their applications in understanding plant stress biology and different levels of spatial organization. In addition, we discuss the opportunities and challenges in multiple stress interactions, multi-omics, and single-cell metabolomics.

Comparative spatial lipidomics analysis reveals cellular lipid remodelling in different developmental zones of barley roots in response to salinity.

Salinity-induced metabolic, ionic, and transcript modifications in plants have routinely been studied using whole plant tissues, which do not provide information on spatial tissue responses. The aim of this study was to assess the changes in the lipid profiles in a spatial manner and to quantify the changes in the elemental composition in roots of seedlings of four barley cultivars before and after a short-term salt stress. We used a combination of liquid chromatography-tandem mass spectrometry, inductively coupled plasma mass spectrometry, matrix-assisted laser desorption/ionization mass spectrometry imaging, and reverse transcription - quantitative real time polymerase chain reaction platforms to examine the molecular signatures of lipids, ions, and transcripts in three anatomically different seminal root tissues before and after salt stress. We found significant changes to the levels of major lipid classes including a decrease in the levels of lysoglycerophospholipids, ceramides, and hexosylceramides and an increase in the levels of glycerophospholipids, hydroxylated ceramides, and hexosylceramides. Our results revealed that modifications to lipid and transcript profiles in plant roots in response to a short-term salt stress may involve recycling of major lipid species, such as phosphatidylcholine, via resynthesis from glycerophosphocholine.

Unique and highly specific cyanogenic glycoside localization in stigmatic cells and pollen in the genus Lomatia (Proteaceae).

BACKGROUND AND AIMS: Floral chemical defence strategies remain understudied despite the significance of flowers to plant fitness, and the fact that many flowers contain secondary metabolites that confer resistance to herbivores. Optimal defence and apparency theories predict that the most apparent plant parts and/or those most important to fitness should be most defended. To test whether within-flower distributions of chemical defence are consistent with these theories we used cyanogenic glycosides (CNglycs), which are constitutive defence metabolites that deter herbivores by releasing hydrogen cyanide upon hydrolysis. METHODS: We used cyanogenic florets of the genus Lomatia to investigate at what scale there may be strategic allocation of CNglycs in flowers, what their localization reveals about function, and whether levels of floral CNglycs differ between eight congeneric species across a climatic gradient. Within-flower distributions of CNglycs during development were quantified, CNglycs were identified and their localization was visualized in cryosectioned florets using matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI). KEY RESULTS: Florets of all congeneric species studied were cyanogenic, and concentrations differed between species. Within florets there was substantial variation in CNglyc concentrations, with extremely high concentrations (up to 14.6 mg CN g-1 d. wt) in pollen and loose, specialized surface cells on the pollen presenter, among the highest concentrations reported in plant tissues. Two tyrosine-derived CNglycs, the monoglycoside dhurrin and diglycoside proteacin, were identified. MALDI-MSI revealed their varying ratios in different floral tissues; proteacin was primarily localized to anthers and ovules, and dhurrin to specialized cells on the pollen presenter. The mix of transient specialized cells and pollen of L. fraxinifolia was ~11 % dhurrin and ~1.1 % proteacin by mass. CONCLUSIONS: Tissue-specific distributions of two CNglycs and substantial variation in their concentrations within florets suggests their allocation is under strong selection. Localized, high CNglyc concentrations in transient cells challenge the predictions of defence theories, and highlight the importance of fine-scale metabolite visualization, and the need for further investigation into the ecological and metabolic roles of CNglycs in floral tissues.

Mass spectrometry imaging: An emerging technology for the analysis of metabolites in insects.

Mass spectrometry imaging (MSI) can visualize the composition, abundance, and spatial distribution of molecules in tissues or cells, which has been widely used in the research of life science. Insects, especially the agricultural pests, have received a great deal of interests from the scientists in biodiversity and food security. This review introduces the major characteristics of MSI, summarizes its application to the investigation of insect endogenous metabolites, exogenous metabolites, and the spatiotemporal changes of metabolites between insects and plants, and discusses its shortfalls and perspectives. The significance of these concerns is beneficial for future insect research such as physiology and metabolism.

Spatial Metabolite Profiling by Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging.

Mass spectrometry imaging (MSI) is rapidly maturing as an advanced method for spatial metabolite profiling. Herein, we provide an introduction to MSI including types of instrumentation, detailed sample preparation, data collection, overview of data analysis steps, software, common standards, and new developments. Further, we provide an overview of MSI in the clinical space over the past 3 years where MSI has been deployed in diverse research areas including cancer, neurobiology, lipidomics, and metabolite profiling and mapping to name only a few. We provide several examples demonstrating the applicability of MSI to spatially profile metabolites in unique systems requiring special considerations outside of the norm.

Mass spectrometry imaging for plant biology: a review.

Mass spectrometry imaging (MSI) is a developing technique to measure the spatio-temporal distribution of many biomolecules in tissues. Over the preceding decade, MSI has been adopted by plant biologists and applied in a broad range of areas, including primary metabolism, natural products, plant defense, plant responses to abiotic and biotic stress, plant lipids and the developing field of spatial metabolomics. This review covers recent advances in plant-based MSI, general aspects of instrumentation, analytical approaches, sample preparation and the current trends in respective plant research.

Biomarker Identification in Liver Cancers Using Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) Imaging: An Approach for Spatially Resolved Metabolomics.

Liver cancers are characterized by interindividual and intratumoral heterogeneity, which makes early diagnosis and the development of therapies challenging. Desorption electrospray ionization mass spectrometry (DESI-MS) imaging is a potent and sensitive MS ionization technique for direct, unaltered 2D and 3D imaging of metabolites in complex biological samples. Indeed, DESI gently desorbs and ionizes analyte molecules from the sample surface using an electrospray source of highly charged aqueous spray droplets in ambient conditions. DESI-MS imaging of biological samples allows untargeted analysis and characterization of metabolites in liver cancers to identify new biomarkers of malignancy. In this chapter, we described a detailed protocol using liver cancer samples collected and stored for histopathology examination, either as frozen or as formalin-fixed, paraffin-embedded specimens. Such hepatocellular carcinoma samples can be subjected to DESI-MS analyses, illustrating the capacity of spatially resolved metabolomics to distinguish malignant lesions from adjacent normal liver tissue.