Metabolomics and mass spectrometry imaging reveal channeled de novo purine synthesis in cells

Organelle transporters and inter-organelle communication as drivers of metabolic regulation and cellular homeostasis

BACKGROUND

Spatial compartmentalization of metabolic pathways within membrane-separated organelles is key to the ability of eukaryotic cells to precisely regulate their biochemical functions. Membrane-bound organelles such as mitochondria, endoplasmic reticulum (ER) and lysosomes enable the concentration of metabolic precursors within optimized chemical environments, greatly accelerating the efficiency of both anabolic and catabolic reactions, enabling division of labor and optimal utilization of resources. However, metabolic compartmentalization also poses a challenge to cells because it creates spatial discontinuities that must be bridged for reaction cascades to be connected and completed. To do so, cells employ different methods to coordinate metabolic fluxes occurring in different organelles, such as membrane-localized transporters to facilitate regulated metabolite exchange between mitochondria and lysosomes, non-vesicular transport pathways via physical contact sites connecting the ER with both mitochondria and lysosomes, as well as localized regulatory signaling processes that coordinately regulate the activity of all these organelles.

SCOPE OF REVIEW

This review covers how cells use membrane transporters, membrane contact sites, and localized signaling pathways to mediate inter-organelle communication and coordinate metabolism. We also describe how disruption of inter-organelle communication is an emerging driver in a multitude of diseases, from cancer to neurodegeneration.

MAJOR CONCLUSIONS

Effective communication among organelles is essential to cellular health and function. Identifying the major molecular players involved in mediating metabolic coordination between organelles will further our understanding of cellular metabolism in health and lead us to design better therapeutics against dysregulated metabolism in disease.

Past accomplishments and future challenges of the multi-omics characterization of leaf growth

The advent of omics technologies has revolutionized biology and advanced our understanding of all biological processes, including major developmental transitions in plants and animals. Here, we review the vast knowledge accumulated concerning leaf growth in terms of transcriptional regulation before turning our attention to the historically less well-characterized alterations at the protein and metabolite level. We will then discuss how the advent of biochemical methods coupled with metabolomics and proteomics can provide insight into the protein-protein and protein-metabolite interactome of the growing leaves. We finally highlight the substantial challenges in detection, spatial resolution, integration, and functional validation of the omics results, focusing on metabolomics as a prerequisite for a comprehensive understanding of small-molecule regulation of plant growth.

Nanomaterials-assisted metabolic analysis toward in vitro diagnostics

In vitro diagnostics (IVD) has played an indispensable role in healthcare system by providing necessary information to indicate disease condition and guide therapeutic decision. Metabolic analysis can be the primary choice to facilitate the IVD since it characterizes the downstream metabolites and offers real-time feedback of the human body. Nanomaterials with well-designed composition and nanostructure have been developed for the construction of high-performance detection platforms toward metabolic analysis. Herein, we summarize the recent progress of nanomaterials-assisted metabolic analysis and the related applications in IVD. We first introduce the important role that nanomaterials play in metabolic analysis when coupled with different detection platforms, including electrochemical sensors, optical spectrometry, and mass spectrometry. We further highlight the nanomaterials-assisted metabolic analysis toward IVD applications, from the perspectives of both the targeted biomarker quantitation and untargeted fingerprint extraction. This review provides fundamental insights into the function of nanomaterials in metabolic analysis, thus facilitating the design of next-generation diagnostic devices in clinical practice.

Multi-Omics Strategies for Investigating the Microbiome in Toxicology Research

Microbial communities on and within the host contact environmental pollutants, toxic compounds, and other xenobiotic compounds. These communities of bacteria, fungi, viruses, and archaea possess diverse metabolic potential to catabolize compounds and produce new metabolites. Microbes alter chemical disposition thus making the microbiome a natural subject of interest for toxicology. Sequencing and metabolomics technologies permit the study of microbiomes altered by acute or long-term exposure to xenobiotics. These investigations have already contributed to and are helping to re-interpret traditional understandings of toxicology. The purpose of this review is to provide a survey of the current methods used to characterize microbes within the context of toxicology. This will include discussion of commonly used techniques for conducting omic-based experiments, their respective strengths and deficiencies, and how forward-looking techniques may address present shortcomings. Finally, a perspective will be provided regarding common assumptions that currently impede microbiome studies from producing causal explanations of toxicologic mechanisms.

Purine biosynthetic enzymes assemble into liquid-like condensates dependent on the activity of chaperone protein HSP90

Enzymes within the de novo purine biosynthetic pathway spatially organize into dynamic intracellular assemblies called purinosomes. The formation of purinosomes has been correlated with growth conditions resulting in high purine demand, and therefore, the cellular advantage of complexation has been hypothesized to enhance metabolite flux through the pathway. However, the properties of this cellular structure are unclear. Here, we define the purinosome in a transient expression system as a biomolecular condensate using fluorescence microscopy. We show that purinosomes, as denoted by formylglycinamidine ribonucleotide synthase granules in purine-depleted HeLa cells, are spherical and appear to coalesce when two come into contact, all liquid-like characteristics that are consistent with previously reported condensates. We further explored the biophysical and biochemical means that drive the liquid-liquid phase separation of these structures. We found that the process of enzyme condensation into purinosomes is likely driven by the oligomeric state of the pathway enzymes and not a result of intrinsic disorder, the presence of low-complexity domains, the assistance of RNA scaffolds, or changes in intracellular pH. Finally, we demonstrate that the heat shock protein 90 KDa helps to regulate the physical properties of the condensate and maintain their liquid-like state inside HeLa cells. We show that disruption of heat shock protein 90 KDa activity induced the transformation of formylglycinamidine ribonucleotide synthase clusters into more irregularly shaped condensates, suggesting that its chaperone activity is essential for purinosomes to retain their liquid-like properties. This refined view of the purinosome offers new insight into how metabolic enzymes spatially organize into dynamic condensates within human cells.

Enzyme Trafficking and Co-Clustering Precede and Accurately Predict Human Breast Cancer Recurrences: An Interdisciplinary Review

Although great effort has been expended to understand cancer's origins, less attention has been given to the primary cause of cancer deaths - cancer recurrences and their sequelae. This interdisciplinary review addresses mechanistic features of aggressive cancer by studying metabolic enzyme patterns within ductal carcinoma in situ (DCIS) of the breast lesions. DCIS lesions from patients who did or did not experience a breast cancer recurrence were compared. Several proteins, including phospho-Ser226-glucose transporter type 1, phosphofructokinase type L and phosphofructokinase/fructose 2,6-bisphosphatase type 4 are found in nucleoli of ductal epithelial cells in samples from patients who will not subsequently recur, but traffic to the cell periphery in samples from patients who will experience a cancer recurrence. Large co-clusters of enzymes near plasmalemmata will enhance product formation because enzyme concentrations in clusters are very high while solvent molecules and solutes diffuse through small channels. These structural changes will accelerate aerobic glycolysis. Agglomerations of pentose phosphate pathway and glutathione synthesis enzymes enhance GSH formation. As aggressive cancer lesions are incomplete at early stages, they may be unrecognizable. We have found that machine learning provides superior analyses of tissue images and may be used to identify biomarker patterns associated with recurrent and non-recurrent patients with high accuracy. This suggests a new prognostic test to predict DCIS patients who are likely to recur and those who are at low risk for recurrence. Mechanistic interpretations provide a deeper understanding of anti-cancer drug action and suggest that aggressive metastatic cancer cells are sensitive to reductive chemotherapy.

Liquid-liquid phase separation drives cellular function and dysfunction in cancer

Cancer is a disease of uncontrollably reproducing cells. It is governed by biochemical pathways that have escaped the regulatory bounds of normal homeostatic balance. This balance is maintained through precise spatiotemporal regulation of these pathways. The formation of biomolecular condensates via liquid-liquid phase separation (LLPS) has recently emerged as a widespread mechanism underlying the spatiotemporal coordination of biological activities in cells. Biomolecular condensates are widely observed to directly regulate key cellular processes involved in cancer cell pathology, and the dysregulation of LLPS is increasingly implicated as a previously hidden driver of oncogenic activity. In this Perspective, we discuss how LLPS shapes the biochemical landscape of cancer cells.

Multienzyme interactions of the de novo purine biosynthetic protein PAICS facilitate purinosome formation and metabolic channeling

There is growing evidence that mammalian cells deploy a mitochondria-associated metabolon called the purinosome to perform channeled de novo purine biosynthesis (DNPB). However, the molecular mechanisms of this substrate-channeling pathway are not well defined. Here, we present molecular evidence of protein-protein interactions (PPIs) between the human bifunctional phosphoribosylaminoimidazole carboxylase/succinocarboxamide synthetase (PAICS) and other known DNPB enzymes. We employed two orthogonal approaches: bimolecular fluorescence complementation, to probe PPIs inside live, intact cells, and co-immunoprecipitation using StrepTag-labeled PAICS that was reintegrated into the genome of PAICS-knockout HeLa cells (crPAICS). With the exception of amidophosphoribosyltransferase, the first enzyme of the DNPB pathway, we discovered PAICS interacts with all other known DNPB enzymes and with MTHFD1, an enzyme which supplies the 10-formyltetrahydrofolate cofactor essential for DNPB. We show these interactions are present in cells grown in both purine-depleted and purine-rich conditions, suggesting at least a partial assembly of these enzymes may be present regardless of the activity of the DNPB pathway. We also demonstrate that tagging of PAICS on its C terminus disrupts these interactions and that this disruption is correlated with disturbed DNPB activity. Finally, we show that crPAICS cells with reintegrated N-terminally tagged PAICS regained effective DNPB with metabolic signatures of channeled synthesis, whereas crPAICS cells that reintegrated C-terminally tagged PAICS exhibit reduced DNPB intermediate pools and a perturbed partitioning of inosine monophosphate into AMP and GMP. Our results provide molecular evidence in support of purinosomes and suggest perturbing PPIs between DNPB enzymes negatively impact metabolite flux through this important pathway.

Combined Targeted and Untargeted Profiling of HeLa Cells Deficient in Purine De Novo Synthesis

Three genetically determined enzyme defects of purine de novo synthesis (PDNS) have been identified so far in humans: adenylosuccinate lyase (ADSL) deficiency, 5-amino-4-imidazole carboxamide-ribosiduria (AICA-ribosiduria), and deficiency in bifunctional enzyme phosphoribosylaminoimidazole carboxylase and phosphoribosylaminoimidazolesuccinocarboxamide synthase (PAICS). Clinical signs of these defects are mainly neurological, such as seizures, psychomotor retardation, epilepsy, autistic features, etc. This work aims to describe the metabolic changes of CRISPR-Cas9 genome-edited HeLa cells deficient in the individual steps of PDNS to better understand known and potential defects of the pathway in humans. High-performance liquid chromatography coupled with mass spectrometry was used for both targeted and untargeted metabolomic analyses. The statistically significant features from the untargeted study were identified by fragmentation analysis. Data from the targeted analysis were processed in Cytoscape software to visualize the most affected metabolic pathways. Statistical significance of PDNS intermediates preceding deficient enzymes was the highest (p-values 10 × 10−7–10 × 10−15) in comparison with the metabolites from other pathways (p-values of up to 10 × 10−7). Disturbed PDNS resulted in an altered pool of adenine and guanine nucleotides. However, the adenylate energy charge was not different from controls. Different profiles of acylcarnitines observed among deficient cell lines might be associated with a specific enzyme deficiency rather than global changes related to the PDNS pathway. Changes detected in one-carbon metabolism might reduce the methylation activity of the deficient cells, thus affecting the modification state of DNA, RNA, and proteins.

Metabolism Characteristics of Th17 and Regulatory T Cells in Autoimmune Diseases

The abnormal number and functional deficiency of immune cells are the pathological basis of various diseases. Recent years, the imbalance of Th17/regulatory T (Treg) cell underlies the occurrence and development of inflammation in autoimmune diseases (AID). Currently, studies have shown that material and energy metabolism is essential for maintaining cell survival and normal functions and the altered metabolic state of immune cells exists in a variety of AID. This review summarizes the biology and functions of Th17 and Treg cells in AID, with emphasis on the advances of the roles and regulatory mechanisms of energy metabolism in activation, differentiation and physiological function of Th17 and Treg cells, which will facilitate to provide targets for the treatment of immune-mediated diseases.

The Purinosome: A Case Study for a Mammalian Metabolon

Over the past fifteen years, we have unveiled a new mechanism by which cells achieve greater efficiency in de novo purine biosynthesis. This mechanism relies on the compartmentalization of de novo purine biosynthetic enzymes into a dynamic complex called the purinosome. In this review, we highlight our current understanding of the purinosome with emphasis on its biophysical properties and function and on the cellular mechanisms that regulate its assembly. We propose a model for functional purinosomes in which they consist of at least ten enzymes that localize near mitochondria and carry out de novo purine biosynthesis by metabolic channeling. We conclude by discussing challenges and opportunities associated with studying the purinosome and analogous metabolons. Expected final online publication date for the Annual Review of Biochemistry, Volume 91 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Advances in MALDI Mass Spectrometry Imaging Single Cell and Tissues

Compared with conventional optical microscopy techniques, mass spectrometry imaging (MSI) or imaging mass spectrometry (IMS) is a powerful, label-free analytical technique, which can sensitively and simultaneously detect, quantify, and map hundreds of biomolecules, such as peptides, proteins, lipid, and other organic compounds in cells and tissues. So far, although several soft ionization techniques, such as desorption electrospray ionization (DESI) and secondary ion mass spectrometry (SIMS) have been used for imaging biomolecules, matrix-assisted laser desorption/ionization (MALDI) is still the most widespread MSI scanning method. Here, we aim to provide a comprehensive review of MALDI-MSI with an emphasis on its advances of the instrumentation, methods, application, and future directions in single cell and biological tissues.

Pharmacological inhibition of MERTK induces in vivo retinal degeneration: a multimodal imaging ocular safety assessment

The receptor tyrosine kinase, MERTK, plays an essential role in homeostasis of the retina via efferocytosis of shed outer nuclear segments of photoreceptors. The Royal College of Surgeons rat model of retinal degeneration has been linked to loss-of-function of MERTK, and together with the MERTK knock-out mouse, phenocopy retinitis pigmentosa in humans with MERTK mutations. Given recent efforts and interest in MERTK as a potential immuno-oncology target, development of a strategy to assess ocular safety at an early pre-clinical stage is critical. We have applied a state-of-the-art, multi-modal imaging platform to assess the in vivo effects of pharmacological inhibition of MERTK in mice. This involved the application of mass spectrometry imaging (MSI) to characterize the ocular spatial distribution of our highly selective MERTK inhibitor; AZ14145845, together with histopathology and transmission electron microscopy to characterize pathological and ultra-structural change in response to MERTK inhibition. In addition, we assessed the utility of a human retinal in vitro cell model to identify perturbation of phagocytosis post MERTK inhibition. We identified high localized total compound concentrations in the retinal pigment epithelium (RPE) and retinal lesions following 28 days of treatment with AZ14145845. These lesions were present in 4 of 8 treated animals, and were characterized by a thinning of the outer nuclear layer, loss of photoreceptors (PR) and accumulation of photoreceptor outer segments at the interface of the RPE and PRs. Furthermore, the lesions were very similar to that shown in the RCS rat and MERTK knock-out mouse, suggesting a MERTK-induced mechanism of PR cell death. This was further supported by the observation of reduced phagocytosis in the human retinal cell model following treatment with AZ14145845. Our study provides a viable, translational strategy to investigate the pre-clinical toxicity of MERTK inhibitors but is equally transferrable to novel chemotypes.

Optimization of metabolomic data processing using NOREVA

A typical output of a metabolomic experiment is a peak table corresponding to the intensity of measured signals. Peak table processing, an essential procedure in metabolomics, is characterized by its study dependency and combinatorial diversity. While various methods and tools have been developed to facilitate metabolomic data processing, it is challenging to determine which processing workflow will give good performance for a specific metabolomic study. NOREVA, an out-of-the-box protocol, was therefore developed to meet this challenge. First, the peak table is subjected to many processing workflows that consist of three to five defined calculations in combinatorially determined sequences. Second, the results of each workflow are judged against objective performance criteria. Third, various benchmarks are analyzed to highlight the uniqueness of this newly developed protocol in (1) evaluating the processing performance based on multiple criteria, (2) optimizing data processing by scanning thousands of workflows, and (3) allowing data processing for time-course and multiclass metabolomics. This protocol is implemented in an R package for convenient accessibility and to protect users' data privacy. Preliminary experience in R language would facilitate the usage of this protocol, and the execution time may vary from several minutes to a couple of hours depending on the size of the analyzed data.

Metabolic Fuel for Epigenetic: Nuclear Production Meets Local Consumption

Epigenetic modifications are responsible for finetuning gene expression profiles to the needs of cells, tissues, and organisms. To rapidly respond to environmental changes, the activity of chromatin modifiers critically depends on the concentration of a handful of metabolites that act as substrates and co-factors. In this way, these enzymes act as metabolic sensors that directly link gene expression to metabolic states. Although metabolites can easily diffuse through the nuclear pore, molecular mechanisms must be in place to regulate epigenetic marker deposition in specific nuclear subdomains or even on single loci. In this review, I explore the possible subcellular sites of metabolite production that influence the epigenome. From the relationship between cytoplasmic metabolism and nuclear metabolite deposition, I converse to the description of a compartmentalized nuclear metabolism. Last, I elaborate on the possibility of metabolic enzymes to operate in phase-separated nuclear microdomains formed by multienzyme and chromatin-bound protein complexes.

Comparative proteomics suggests the mode of action of a novel molluscicide against the invasive apple snail Pomacea canaliculata, intermediate host of Angiostrongylus cantonensis

Angiostrongylus cantonensis is a zoonotic parasitic nematode that is the most common cause of human eosinophilic meningitis. The invasive apple snail Pomacea canaliculata is an important intermediate host of A. cantonensis and contributes to its spread. P. canaliculata control will help prevent its invasion and transmission of A. cantonensis. The new molluscicide PBQ (1-(4-chlorophenyl)-3-(pyridin-3-yl)urea) exhibits great potency against P. canaliculata and has low toxicity against mammals and non-target aquatic organisms. We studied the mode of action of PBQ using TMT-based comparative quantitative proteomics analysis between PBQ-treated and control P. canaliculata snails. A total of 3151 proteins were identified, and 245 of these proteins were significantly differentially expressed with 135 downregulated and 110 upregulated. GO and KEGG enrichment analyses identified GO terms and KEGG pathways involved in de novo purine biosynthesis, ribosome components and translation process were significantly enriched and downregulated. The results indicated that PBQ treatment had substantial effects on the synthesis of genetic material, translation process, and protein synthesis of P. canaliculata and were likely the main cause of snail mortality.

Liquid Chromatograph-Mass Spectrometry-Based Non-targeted Metabolomics Discovery of Potential Endogenous Biomarkers Associated With Prostatitis Rats to Reveal the Effects of Magnoflorine

Magnoflorine (Mag) has multiple pharmacological activities for the prevention and treatment of prostatitis. However, its molecular mechanisms andpharmacological targets are not clear. In this study, the ultra-performance liquid tandem mass spectrometry-based metabolomics method was used to clarify the intervention of Mag against prostatitis and the biological mechanism. A total of 25 biomarkers associated with the prostatitis model were identified by metabolomics, and a number of metabolic pathways closely related to the model were obtained by MetPA analysis. After given Mag treatment, the results of each indicator were shown that Mag alkaloid could inhibit the development of prostatitis effectively. We found that Mag had regulative effects on potential biomarkers of prostatitis model, which can regulate them to the control group. Our results indicated that alkaloids have an effective intervention therapy for prostatitis, and five types of metabolic pathways closely related to prostatitis model were obtained, including phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, tyrosine metabolism, arginine and proline metabolism, glycine, serine and threonine metabolism, alanine, aspartate and glutamate metabolism. This study has provided the basic experimental data for the development of Mag in the prevention and treatment of prostatitis.

CD8+ T cell metabolism in infection and cancer

Cytotoxic CD8⁺ T cells play a key role in the elimination of intracellular infections and malignant cells and can provide long-term protective immunity. In the response to infection, CD8⁺ T cell metabolism is coupled to transcriptional, translational and epigenetic changes that are driven by extracellular metabolites and immunological signals. These programmes facilitate the adaptation of CD8⁺ T cells to the diverse and dynamic metabolic environments encountered in the circulation and in the tissues. In the setting of disease, both cell-intrinsic and cell-extrinsic metabolic cues contribute to CD8⁺ T cell dysfunction. In addition, changes in whole-body metabolism, whether through voluntary or disease-induced dietary alterations, can influence CD8⁺ T cell-mediated immunity. Defining the metabolic adaptations of CD8⁺ T cells in specific tissue environments informs our understanding of how these cells protect against pathogens and tumours and maintain tissue health at barrier sites. Here, we highlight recent findings revealing how metabolic networks enforce specific CD8⁺ T cell programmes and discuss how metabolism is integrated with CD8⁺ T cell differentiation and function and determined by environmental cues.

Mass Spectrometric Biosensing: A Powerful Approach for Multiplexed Analysis of Clinical Biomolecules

Rapid and sensitive detection of clinical biomolecules in a multiplexed fashion is of great importance for accurate diagnosis of diseases. Mass spectrometric (MS) approaches are exceptionally suitable for clinical analysis due to its high throughput, high sensitivity, and reliable qualitative and quantitative capabilities. To break through the bottleneck of MS technique for detecting high-molecular-weight substances with low ionization efficiency, the concept of mass spectrometric biosensing has been put forward by adopting mass spectrometric chips to recognize the targets and mass spectrometry to detect the signals switched by the recognition. In this review, the principle of mass spectrometric sensing, the construction of different mass tags used for biosensing, and the typical combination mode of mass spectrometric imaging (MSI) technique are summarized. Future perspectives including the design of portable matching platforms, exploitation of novel mass tags, development of effective signal amplification strategies, and standardization of MSI methodologies are proposed to promote the advancements and practical applications of mass spectrometric biosensing.

Metabolomics and complementary techniques to investigate the plant phytochemical cosmos

Covering: up to 2021Plants and their associated microbial communities are known to produce millions of metabolites, a majority of which are still not characterized and are speculated to possess novel bioactive properties. In addition to their role in plant physiology, these metabolites are also relevant as existing and next-generation medicine candidates. Elucidation of the plant metabolite diversity is thus valuable for the successful exploitation of natural resources for humankind. Herein, we present a comprehensive review on recent metabolomics approaches to illuminate molecular networks in plants, including chemical isolation and enzymatic production as well as the modern metabolomics approaches such as stable isotope labeling, ultrahigh-resolution mass spectrometry, metabolome imaging (spatial metabolomics), single-cell analysis, cheminformatics, and computational mass spectrometry. Mass spectrometry-based strategies to characterize plant metabolomes through metabolite identification and annotation are described in detail. We also highlight the use of phytochemical genomics to mine genes associated with specialized metabolites' biosynthesis. Understanding the metabolic diversity through biotechnological advances is fundamental to elucidate the functions of the plant-derived specialized metabolome.

Investigation on selenium and mercury interactions and the distribution patterns in mice organs with LA-ICP-MS imaging

It is the first time to investigate local distribution patterns of mercury (Hg) in mice organs after Hg and Se exposure with detection of laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Two batch of adult mice were employed to be exposed to inorganic mercury (iHg) and methylmercury (MeHg) with or without Se at the dose of 55 μmol kg^-1. Tissue sections of brain, kidney, liver, and spleen from one batch mice were prepared to get local imaging of Hg by LA-ICP-MS. Tissues from another batch mice were used to quantify Hg and Se in tissues with ICP-MS after acid digestion. The results indicated that, for mice exposed to iHg, Hg mainly distributed in kidney, a little in liver, and hardly in brain and spleen; for mice exposed to MeHg, lower amount of Hg was found in kidney, liver and spleen, and almost no Hg was found in brain. It was interesting that for Hg and Se co-administration groups, higher level of Hg was observed in kidney, liver, spleen and even in brain than single Hg administration groups. In addition, Se level in organ tissues increased obviously not only in Se exposure group but also in MeHg exposure group, while the phenomenon was not observed in iHg exposure group. HepG2 cells were employed to investigate Se and Hg interactions in single cell level, similar bioaccumulation behavior of Hg was found between cells and mice organs. Higher level of Hg was observed in cells cultured with Se and Hg medium than cells cultured with single Hg medium. The results are expected to provide new insight to investigate Hg and Se interactions in animal bodies and in-vitro cells.

Compartmentalization and metabolic regulation of glycolysis

Hypoxia inhibits the tricarboxylic acid (TCA) cycle and leaves glycolysis as the primary metabolic pathway responsible for converting glucose into usable energy. However, the mechanisms that compensate for this loss in energy production due to TCA cycle inactivation remain poorly understood. Glycolysis enzymes are typically diffuse and soluble in the cytoplasm under normoxic conditions. In contrast, recent studies have revealed dynamic compartmentalization of glycolysis enzymes in response to hypoxic stress in yeast, C. elegans and mammalian cells. These messenger ribonucleoprotein (mRNP) structures, termed glycolytic (G) bodies in yeast, lack membrane enclosure and display properties of phase-separated biomolecular condensates. Disruption of condensate formation correlates with defects such as impaired synaptic function in C. elegans neurons and decreased glucose flux in yeast. Concentrating glycolysis enzymes into condensates may lead to their functioning as 'metabolons' that enhance rates of glucose utilization for increased energy production. Besides condensates, glycolysis enzymes functionally associate in other organisms and specific tissues through protein-protein interactions and membrane association. However, as discussed in this Review, the functional consequences of coalescing glycolytic machinery are only just beginning to be revealed. Through ongoing studies, we anticipate the physiological importance of metabolic regulation mediated by the compartmentalization of glycolysis enzymes will continue to emerge.

SEAM is a spatial single nuclear metabolomics method for dissecting tissue microenvironment

Spatial metabolomics can reveal intercellular heterogeneity and tissue organization. Here we report on the spatial single nuclear metabolomics (SEAM) method, a flexible platform combining high-spatial-resolution imaging mass spectrometry and a set of computational algorithms that can display multiscale and multicolor tissue tomography together with identification and clustering of single nuclei by their in situ metabolic fingerprints. We first applied SEAM to a range of wild-type mouse tissues, then delineated a consistent pattern of metabolic zonation in mouse liver. We further studied the spatial metabolic profile in the human fibrotic liver. We discovered subpopulations of hepatocytes with special metabolic features associated with their proximity to the fibrotic niche, and validated this finding by spatial transcriptomics with Geo-seq. These demonstrations highlighted SEAM's ability to explore the spatial metabolic profile and tissue histology at the single-cell level, leading to a deeper understanding of tissue metabolic organization.

Metabolomics in Retinal Diseases: An Update

Retinal diseases are a leading cause of visual loss and blindness, affecting a significant proportion of the population worldwide and having a detrimental impact on quality of life, with consequent economic burden. The retina is highly metabolically active, and a number of retinal diseases are associated with metabolic dysfunction. To better understand the pathogenesis underlying such retinopathies, new technology has been developed to elucidate the mechanism behind retinal diseases. Metabolomics is a relatively new "omics" technology, which has developed subsequent to genomics, transcriptomics, and proteomics. This new technology can provide qualitative and quantitative information about low-molecular-weight metabolites (M.W. < 1500 Da) in a given biological system, which shed light on the physiological or pathological state of a cell or tissue sample at a particular time point. In this article we provide an extensive review of the application of metabolomics to retinal diseases, with focus on age-related macular degeneration (AMD), diabetic retinopathy (DR), retinopathy of prematurity (ROP), glaucoma, and retinitis pigmentosa (RP).

A Targeted Serum Metabolomics GC-MS Approach Identifies Predictive Blood Biomarkers for Retained Placenta in Holstein Dairy Cows

The retained placenta is a common pathology of dairy cows. It is associated with a significant drop in the dry matter intake, milk yield, and increased susceptibility of dairy cows to metritis, mastitis, and displaced abomasum. The objective of this study was to identify metabolic alterations that precede and are associated with the disease occurrence. Blood samples were collected from 100 dairy cows at −8 and −4 weeks prior to parturition and on the day of retained placenta, and only 16 healthy cows and 6 cows affected by retained placenta were selected to measure serum polar metabolites by a targeted gas chromatography–mass spectroscopy (GC-MS) metabolomics approach. A total of 27 metabolites were identified and quantified in the serum. There were 10, 18, and 17 metabolites identified as being significantly altered during the three time periods studied. However, only nine metabolites were identified as being shared among the three time periods including five amino acids (Asp, Glu, Ser, Thr, and Tyr), one sugar (myo-inositol), phosphoric acid, and urea. The identified metabolites can be used as predictive biomarkers for the risk of retained placenta in dairy cows and might help explain the metabolic processes that occur prior to the incidence of the disease and throw light on the pathomechanisms of the disease.

Metabolic channeling: predictions, deductions, and evidence

With the elucidation of myriad anabolic and catabolic enzyme-catalyzed cellular pathways crisscrossing each other, an obvious question arose: how could these networks operate with maximal catalytic efficiency and minimal interference? A logical answer was the postulate of metabolic channeling, which in its simplest embodiment assumes that the product generated by one enzyme passes directly to a second without diffusion into the surrounding medium. This tight coupling of activities might increase a pathway's metabolic flux and/or serve to sequester unstable/toxic/reactive intermediates as well as prevent their access to other networks. Here, we present evidence for this concept, commencing with enzymes that feature a physical molecular tunnel, to multi-enzyme complexes that retain pathway substrates through electrostatics or enclosures, and finally to metabolons that feature collections of enzymes assembled into clusters with variable stoichiometric composition. Lastly, we discuss the advantages of reversibly assembled metabolons in the context of the purinosome, the purine biosynthesis metabolon.

In vivo deep network tracing reveals phosphofructokinase-mediated coordination of biosynthetic pathway activity in the myocardium

Glucose metabolism comprises numerous amphibolic metabolites that provide precursors for not only the synthesis of cellular building blocks but also for ATP production. In this study, we tested how phosphofructokinase-1 (PFK1) activity controls the fate of glucose-derived carbon in murine hearts in vivo. PFK1 activity was regulated by cardiac-specific overexpression of kinase- or phosphatase-deficient 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase transgenes in mice (termed Glyco^Lo or Glyco^Hi mice, respectively). Dietary delivery of ¹³C₆-glucose to these mice, followed by deep network metabolic tracing, revealed that low rates of PFK1 activity promote selective routing of glucose-derived carbon to the purine synthesis pathway to form 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR). Consistent with a mechanism of physical channeling, we found multimeric protein complexes that contained phosphoribosylaminoimidazole carboxylase (PAICS)—an enzyme important for AICAR biosynthesis, as well as chaperone proteins such as Hsp90 and other metabolic enzymes. We also observed that PFK1 influenced glucose-derived carbon deposition in glycogen, but did not affect hexosamine biosynthetic pathway activity. These studies demonstrate the utility of deep network tracing to identify metabolic channeling and changes in biosynthetic pathway activity in the heart in vivo and present new potential mechanisms by which metabolic branchpoint reactions modulate biosynthetic pathways.

Advances and opportunities in image analysis of bacterial cells and communities

The cellular morphology and sub-cellular spatial structure critically influence the function of microbial cells. Similarly, the spatial arrangement of genotypes and phenotypes in microbial communities has important consequences for cooperation, competition, and community functions. Fluorescence microscopy techniques are widely used to measure spatial structure inside living cells and communities, which often results in large numbers of images that are difficult or impossible to analyze manually. The rapidly evolving progress in computational image analysis has recently enabled the quantification of a large number of properties of single cells and communities, based on traditional analysis techniques and convolutional neural networks. Here, we provide a brief introduction to core concepts of automated image processing, recent software tools and how to validate image analysis results. We also discuss recent advances in image analysis of microbial cells and communities, and how these advances open up opportunities for quantitative studies of spatiotemporal processes in microbiology, based on image cytometry and adaptive microscope control.

Liquid-liquid phase separation: a principal organizer of the cell's biochemical activity architecture

Numerous processes occur simultaneously in the cell both for normal function and in response to changes in the environment. The ability of cells to segregate biochemical reactions into separate compartments is essential to ensure specificity and efficiency in cellular processes. The discovery of liquid-liquid phase separation as a mechanism of compartmentalization has revised our thinking regarding the intracellular organization of molecular pathways such as signal transduction. Here, we highlight recent studies that advance our understanding of how phase separation impacts the organization of biochemical processes, with a particular focus on the tools used to study the functional impact of phase separation. In addition, we offer some of our perspectives on the pathological consequences of dysregulated phase separation in biochemical pathways.

SI-MOIRAI: A new method to identify and quantify the metabolic fate of nucleotides

Since the discovery of nucleotides over 100 years ago, extensive studies have revealed the importance of nucleotides for homeostasis, health, and disease. However, there remains no established method to investigate quantitively and accurately intact nucleotide incorporation into RNA and DNA. Herein, we report a new method, Stable-Isotope Measure Of Influxed Ribonucleic Acid Index (SI-MOIRAI), for the identification and quantification of the metabolic fate of ribonucleotides and their precursors. SI-MOIRAI, named after Greek goddesses of fate, combines a stable isotope-labeling flux assay with mass spectrometry to enable quantification of the newly synthesized ribonucleotides into r/m/tRNA under a metabolic stationary state. Using glioblastoma U87MG cells and a patient-derived xenograft (PDX) glioblastoma mouse model, SI-MOIRAI analyses showed that newly synthesized GTP was particularly and disproportionally highly utilized for rRNA and tRNA synthesis but not for mRNA synthesis in glioblastoma (GBM) in vitro and in vivo. Furthermore, newly synthesized pyrimidine nucleotides exhibited a significantly lower utilization rate for RNA synthesis than newly synthesized purine nucleotides. The results reveal the existence of discrete pathways and compartmentalization of purine and pyrimidine metabolism designated for RNA synthesis, demonstrating the capacity of SI-MOIRAI to reveal previously unknown aspects of nucleotide biology.

Mechanical Frustration of Phase Separation in the Cell Nucleus by Chromatin

Liquid-liquid phase separation is a fundamental mechanism underlying subcellular organization. Motivated by the striking observation that optogenetically generated droplets in the nucleus display suppressed coarsening dynamics, we study the impact of chromatin mechanics on droplet phase separation. We combine theory and simulation to show that cross-linked chromatin can mechanically suppress droplets' coalescence and ripening, as well as quantitatively control their number, size, and placement. Our results highlight the role of the subcellular mechanical environment on condensate regulation.

From Bioorganic Models to Cells

I endeavor to share how various choices-some deliberate, some unconscious-and the unmistakable influence of many others shaped my scientific pursuits. I am fascinated by how two long-term, major streams of my research, DNA replication and purine biosynthesis, have merged with unexpected interconnections. If I have imparted to many of the talented individuals who have passed through my lab a degree of my passion for uncloaking the mysteries hidden in scientific research and an understanding of the honesty and rigor it demands and its impact on the world community, then my mentorship has been successful.

Next-Generation Mass Spectrometry Metabolomics Revives the Functional Analysis of Plant Metabolic Diversity

The remarkable diversity of specialized metabolites produced by plants has inspired several decades of research and nucleated a long list of theories to guide empirical ecological studies. However, analytical constraints and the lack of untargeted processing workflows have long precluded comprehensive metabolite profiling and, consequently, the collection of the critical currencies to test theory predictions for the ecological functions of plant metabolic diversity. Developments in mass spectrometry (MS) metabolomics have revolutionized the large-scale inventory and annotation of chemicals from biospecimens. Hence, the next generation of MS metabolomics propelled by new bioinformatics developments provides a long-awaited framework to revisit metabolism-centered ecological questions, much like the advances in next-generation sequencing of the last two decades impacted all research horizons in genomics. Here, we review advances in plant (computational) metabolomics to foster hypothesis formulation from complex metabolome data. Additionally, we reflect on how next-generation metabolomics could reinvigorate the testing of long-standing theories on plant metabolic diversity.

Metabolomics in infectious diseases and drug discovery

Metabolomics has emerged as an invaluable tool that can be used along with genomics, transcriptomics and proteomics to understand host-pathogen interactions at small-molecule levels. Metabolomics has been used to study a variety of infectious diseases and applications. The most common application of metabolomics is for prognostic and diagnostic purposes, specifically the screening of disease-specific biomarkers by either NMR-based or mass spectrometry-based metabolomics. In addition, metabolomics is of great significance for the discovery of druggable metabolic enzymes and/or metabolic regulators through the use of state-of-the-art flux analysis, for example, via the elucidation of metabolic mechanisms. This review discusses the application of metabolomics technologies to biomarker screening, the discovery of drug targets in infectious diseases such as viral, bacterial and parasite infections and immunometabolomics, highlights the challenges associated with accessing metabolite compartmentalization and discusses the available tools for determining local metabolite concentrations.

Metabolic perturbations sensitize triple-negative breast cancers to apoptosis induced by BH3 mimetics

Cancer cells have differential metabolic dependencies compared to their nonmalignant counterparts. However, few metabolism-targeting compounds have been successful in clinical trials. Here, we investigated the metabolic vulnerabilities of triple-negative breast cancer (TNBC), particularly those metabolic perturbations that increased mitochondrial apoptotic priming and sensitivity to BH3 mimetics (drugs that antagonize antiapoptotic proteins). We used high-throughput dynamic BH3 profiling (HT-DBP) to screen a library of metabolism-perturbing small molecules, which revealed inhibitors of the enzyme nicotinamide phosphoribosyltransferase (NAMPT) as top candidates. In some TNBC cells but not in nonmalignant cells, NAMPT inhibitors increased overall apoptotic priming and induced dependencies on specific antiapoptotic BCL-2 family members. Treatment of TNBC cells with NAMPT inhibitors sensitized them to subsequent treatment with BH3 mimetics. The combination of a NAMPT inhibitor (FK866) and an MCL-1 antagonist (S63845) reduced tumor growth in a TNBC patient-derived xenograft model in vivo. We found that NAMPT inhibition reduced NAD⁺ concentrations below a critical threshold that resulted in depletion of adenine, which was the metabolic trigger that primed TNBC cells for apoptosis. These findings demonstrate a close interaction between metabolic and mitochondrial apoptotic signaling pathways and reveal that exploitation of a tumor-specific metabolic vulnerability can sensitize some TNBC to BH3 mimetics.

Challenges in Studying Stem Cell Metabolism

The expanding field of stem cell metabolism has been supported by technical advances in metabolite profiling and novel functional analyses. While use of these methodologies has been fruitful, many challenges are posed by the intricacies of culturing stem cells in vitro, along with the distinctive scarcity of adult tissue stem cells and the complexities of their niches in vivo. This review provides an examination of the methodologies used to characterize stem cell metabolism, highlighting their utility while placing a sharper focus on their limitations and hurdles the field needs to overcome for the optimal study of stem cell metabolic networks.

Direct Mapping of Phospholipid Ferroptotic Death Signals in Cells and Tissues by Gas Cluster Ion Beam Secondary Ion Mass Spectrometry (GCIB-SIMS)

Peroxidized phosphatidylethanolamine (PEox) species have been identified by liquid chromatography mass spectrometry (LC-MS) as predictive biomarkers of ferroptosis, a new program of regulated cell death. However, the presence and subcellular distribution of PEox in specific cell types and tissues have not been directly detected by imaging protocols. By applying gas cluster ion beam secondary ion mass spectrometry (GCIB-SIMS) imaging with a 70 keV (H2 O)n+ (n>28 000) cluster ion beam, we were able to map PEox with 1.2 μm spatial resolution at the single cell/subcellular level in ferroptotic H9c2 cardiomyocytes and cortical/hippocampal neurons after traumatic brain injury. Application of this protocol affords visualization of physiologically relevant levels of very low abundance (20 pmol μmol-1 lipid) peroxidized lipids in subcellular compartments and their accumulation in disease conditions.

Modeling the Th17 and Tregs Paradigm: Implications for Cancer Immunotherapy

CD4 + T cell differentiation is governed by gene regulatory and metabolic networks, with both networks being highly interconnected and able to adapt to external stimuli. Th17 and Tregs differentiation networks play a critical role in cancer, and their balance is affected by the tumor microenvironment (TME). Factors from the TME mediate recruitment and expansion of Th17 cells, but these cells can act with pro or anti-tumor immunity. Tregs cells are also involved in tumor development and progression by inhibiting antitumor immunity and promoting immunoevasion. Due to the complexity of the underlying molecular pathways, the modeling of biological systems has emerged as a promising solution for better understanding both CD4 + T cell differentiation and cancer cell behavior. In this review, we present a context-dependent vision of CD4 + T cell transcriptomic and metabolic network adaptability. We then discuss CD4 + T cell knowledge-based models to extract the regulatory elements of Th17 and Tregs differentiation in multiple CD4 + T cell levels. We highlight the importance of complementing these models with data from omics technologies such as transcriptomics and metabolomics, in order to better delineate existing Th17 and Tregs bifurcation mechanisms. We were able to recompilate promising regulatory components and mechanisms of Th17 and Tregs differentiation under normal conditions, which we then connected with biological evidence in the context of the TME to better understand CD4 + T cell behavior in cancer. From the integration of mechanistic models with omics data, the transcriptomic and metabolomic reprograming of Th17 and Tregs cells can be predicted in new models with potential clinical applications, with special relevance to cancer immunotherapy.

Metabolon: a novel cellular structure that regulates specific metabolic pathways

This manuscript of research highlight focused on one paper recently published in Nature Metabolism entitled "Mitochondrial Long Non-coding RNA GAS5 Tunes TCA Metabolism in Response to Nutrient Stress" from Lin Aifu's group in Zhejiang University. In this manuscript, we discussed the novel findings in Lin's paper and concluded that the metabolon is emerging as a novel cellular structure that regulates specific metabolic pathways.

Assessing the role of amino acids in systemic inflammation and organ failure in patients with ACLF

BACKGROUND & AIMS

Systemic inflammation and organ failure(s) are the hallmarks of acute-on-chronic liver failure (ACLF), yet their pathogenesis remains uncertain. Herein, we aimed to assess the role of amino acids in these processes in patients with ACLF.

METHODS

The blood metabolomic database of the CANONIC study (comprising 137 metabolites, with 43% related to amino acids) - obtained in 181 patients with ACLF and 650 with acute decompensation without ACLF (AD) - was reanalyzed with a focus on amino acids, in particular 9 modules of co-regulated metabolites. We also compared blood metabolite levels between ACLF and AD.

RESULTS

The main findings in ACLF were: i) Metabolite modules were increased in parallel with increased levels of markers of systemic inflammation and oxidative stress. ii) Seventy percent of proteinogenic amino acids were present and most were increased. iii) A metabolic network, comprising the amino acids aspartate, glutamate, the serine-glycine one-carbon metabolism (folate cycle), and methionine cycle, was activated, suggesting increased purine and pyrimidine nucleotide synthesis. iv) Cystathionine, L-cystine, glutamate and pyroglutamate, which are involved in the transsulfuration pathway (a methionine cycle branch) were increased, consistent with increased synthesis of the antioxidant glutathione. v) Intermediates of the catabolism of 5 out of the 6 ketogenic amino acids were increased. vi) The levels of spermidine (a polyamine inducer of autophagy with anti-inflammatory effects) were decreased.

CONCLUSIONS

In ACLF, blood amino acids fueled protein and nucleotide synthesis required for the intense systemic inflammatory response. Ketogenic amino acids were extensively catabolized to produce energy substrates in peripheral organs, an effect that was insufficient because organs failed. Finally, the decrease in spermidine levels may cause a defect in autophagy contributing to the proinflammatory phenotype in ACLF.

LAY SUMMARY

Systemic inflammation and organ failures are hallmarks of acute-on-chronic liver failure (ACLF). Herein, we aimed to characterize the role of amino acids in these processes. The blood metabolome of patients with acutely decompensated cirrhosis, and particularly those with ACLF, reveals evidence of intense skeletal muscle catabolism. Importantly, amino acids (along with glucose), are used for intense anabolic, energy-consuming metabolism in patients with ACLF, presumably to support de novo nucleotide and protein synthesis in the activated innate immune system.

Electron flow between the worlds of Marcus and Warburg

Living organisms are characterized by the ability to process energy (all release heat). Redox reactions play a central role in biology, from energy transduction (photosynthesis, respiratory chains) to highly selective catalyzed transformations of complex molecules. Distance and scale are important: electrons transfer on a 1 nm scale, hydrogen nuclei transfer between molecules on a 0.1 nm scale, and extended catalytic processes (cascades) operate most efficiently when the different enzymes are under nanoconfinement (10 nm-100 nm scale). Dynamic electrochemistry experiments (defined broadly within the term "protein film electrochemistry," PFE) reveal details that are usually hidden in conventional kinetic experiments. In PFE, the enzyme is attached to an electrode, often in an innovative way, and electron-transfer reactions, individual or within steady-state catalytic flow, can be analyzed in terms of precise potentials, proton coupling, cooperativity, driving-force dependence of rates, and reversibility (a mark of efficiency). The electrochemical experiments reveal subtle factors that would have played an essential role in molecular evolution. This article describes how PFE is used to visualize and analyze different aspects of biological redox chemistry, from long-range directional electron transfer to electron/hydride (NADPH) interconversion by a flavoenzyme and finally to NADPH recycling in a nanoconfined enzyme cascade.

Spatially Resolved Mass Spectrometry at the Single Cell: Recent Innovations in Proteomics and Metabolomics

Biological systems are composed of heterogeneous populations of cells that intercommunicate to form a functional living tissue. Biological function varies greatly across populations of cells, as each single cell has a unique transcriptome, proteome, and metabolome that translates to functional differences within single species and across kingdoms. Over the past decade, substantial advancements in our ability to characterize omic profiles on a single cell level have occurred, including in multiple spectroscopic and mass spectrometry (MS)-based techniques. Of these technologies, spatially resolved mass spectrometry approaches, including mass spectrometry imaging (MSI), have shown the most progress for single cell proteomics and metabolomics. For example, reporter-based methods using heavy metal tags have allowed for targeted MS investigation of the proteome at the subcellular level, and development of technologies such as laser ablation electrospray ionization mass spectrometry (LAESI-MS) now mean that dynamic metabolomics can be performed in situ. In this Perspective, we showcase advancements in single cell spatial metabolomics and proteomics over the past decade and highlight important aspects related to high-throughput screening, data analysis, and more which are vital to the success of achieving proteomic and metabolomic profiling at the single cell scale. Finally, using this broad literature summary, we provide a perspective on how the next decade may unfold in the area of single cell MS-based proteomics and metabolomics.

Novel technical developments in mass spectrometry imaging in 2020: A mini review

The applicability of mass spectrometry imaging (MSI) has exponentially increased with the improvement of sample preparation, instrumentation (spatial resolution) and data analysis. The number of MSI publications listed in PubMed continues to grow with 378 published articles in 2020-2021. Initially, MSI was just sensitive enough to identify molecular features correlating with distinct tissue regions, similar to the resolution achieved by visual inspection after standard immunohistochemical staining. Although the spatial resolution was limited compared with other imaging modalities, the molecular intensity mapping added a new exciting capability. Over the past decade, significant improvements in every step of the workflow and most importantly in instrumentation were made, which now enables the molecular analysis at a cellular and even subcellular level. Here, we summarize the latest developments in MSI, with a focus on the latest approaches for tissue-based imaging described in 2020.