Stable isotope-labeling studies in metabolomics: new insights into structure and dynamics of metabolic networks

Analytical methods for stable isotope labeling to elucidate rapid auxin kinetics in Arabidopsis thaliana

The phytohormone auxin plays a critical role in plant growth and development. Despite significant progress in elucidating metabolic pathways of the primary bioactive auxin, indole-3-acetic acid (IAA), over the past few decades, key components such as intermediates and enzymes have not been fully characterized, and the dynamic regulation of IAA metabolism in response to environmental signals has not been completely revealed. In this study, we established a protocol employing a highly sensitive liquid chromatography-mass spectrometry (LC-MS) instrumentation and a rapid stable isotope labeling approach. We treated Arabidopsis seedlings with two stable isotope labeled precursors ([13C6]anthranilate and [13C8, 15N1]indole) and monitored the label incorporation into proposed indolic compounds involved in IAA biosynthetic pathways. This Stable Isotope Labeled Kinetics (SILK) method allowed us to trace the turnover rates of IAA pathway precursors and product concurrently with a time scale of seconds to minutes. By measuring the entire pathways over time and using different isotopic tracer techniques, we demonstrated that these methods offer more detailed information about this complex interacting network of IAA biosynthesis, and should prove to be useful for studying auxin metabolic network in vivo in a variety of plant tissues and under different environmental conditions.

Flying toward a plastic-free world: Can Drosophila serve as a model organism to develop new strategies of plastic waste management?

The last century was dominated by the widespread use of plastics, both in terms of invention and increased usage. The environmental challenge we currently face is not just about reducing plastic usage but finding new ways to manage plastic waste. Recycling is growing but remains a small part of the solution. There is increasing focus on studying organisms and processes that can break down plastics, offering a modern approach to addressing the environmental crisis. Here, we provide an overview of the organisms associated with plastics biodegradation, and we explore the potential of harnessing and integrating their genetic and biochemical features into a single organism, such as Drosophila melanogaster. The remarkable genetic engineering and microbiota manipulation tools available for this organism suggest that multiple features could be amalgamated and modeled in the fruit fly. We outline feasible genetic engineering and gut microbiome engraftment strategies to develop a new class of plastic-degrading organisms and discuss of both the potential benefits and the limitations of developing such engineered Drosophila melanogaster strains.

Give and Take: The Reciprocal Control of Metabolism and Cell Cycle

Cell cycle is an ordered sequence of events that occur in a cell preparing for cell division . The cell cycle is a four-stage process in which the cell increases in size, copies its DNA , prepares to divide, and divides. All these stages require a coordination of signaling pathways as well as adequate levels of energy and building blocks. These specific signaling and metabolic switches are tightly orchestrated in order for the cell cycle to occur properly. In this book chapter, we will provide information on the basis of metabolism and cell cycle interplay, and we will finish by an unexhaustive list of metabolomics approaches available to study the reciprocal control of metabolism and cell cycle.

Indoor metabolites and chemicals outperform microbiome in classifying childhood asthma and allergic rhinitis

Indoor microorganisms impact asthma and allergic rhinitis (AR), but the associated microbial taxa often vary extensively due to climate and geographical variations. To provide more consistent environmental assessments, new perspectives on microbial exposure for asthma and AR are needed. Home dust from 97 cases (32 asthma alone, 37 AR alone, 28 comorbidity) and 52 age- and gender-matched controls in Shanghai, China, were analyzed using high-throughput shotgun metagenomic sequencing and liquid chromatography-mass spectrometry. Homes of healthy children were enriched with environmental microbes, including Paracoccus, Pseudomonas, and Psychrobacter, and metabolites like keto acids, indoles, pyridines, and flavonoids (astragalin, hesperidin) (False Discovery Rate < 0.05). A neural network co-occurrence probability analysis revealed that environmental microorganisms were involved in producing these keto acids, indoles, and pyridines. Conversely, homes of diseased children were enriched with mycotoxins and synthetic chemicals, including herbicides, insecticides, and food/cosmetic additives. Using a random forest model, characteristic metabolites and microorganisms in Shanghai homes were used to classify high and low prevalence of asthma/AR in an independent dataset in Malaysian schools (N = 1290). Indoor metabolites achieved an average accuracy of 74.9% and 77.1% in differentiating schools with high and low prevalence of asthma and AR, respectively, whereas indoor microorganisms only achieved 51.0% and 59.5%, respectively. These results suggest that indoor metabolites and chemicals rather than indoor microbiome are potentially superior environmental indicators for childhood asthma and AR. This study extends the traditional risk assessment focusing on allergens or air pollutants in childhood asthma and AR, thereby revealing potential novel intervention strategies for these diseases.

Nitrogen isotopic composition as a gauge of tumor cell anabolism-to-catabolism ratio

Studies have suggested that cancerous tissue has a lower 15N/14N ratio than benign tissue. However, human data have been inconclusive, possibly due to constraints on experimental design. Here, we used high-sensitivity nitrogen isotope methods to assess the 15N/14N ratio of human breast, lung, and kidney cancer tissue at unprecedented spatial resolution. In lung, breast, and urothelial carcinoma, 15N/14N was negatively correlated with tumor cell density. The magnitude of 15N depletion for a given tumor cell density was consistent across different types of lung cancer, ductal in situ and invasive breast carcinoma, and urothelial carcinoma, suggesting similar elevations in the anabolism-to-catabolism ratio. However, tumor 15N depletion was higher in a more aggressive metaplastic breast carcinoma. These findings may indicate the ability of certain cancers to more effectively channel N towards growth. Our results support 15N/14N analysis as a potential tool for screening biopsies and assessing N metabolism in tumor cells.

Characterisation of Aberrant Metabolic Pathways in Hepatoblastoma Using Liquid Chromatography and Tandem Mass Spectrometry (LC-MS/MS)

Hepatoblastoma (HB) is a rare childhood tumour with an evolving molecular landscape. We present the first comprehensive metabolomic analysis using untargeted and targeted liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-MS/MS) of paired tumour and non-tumour surgical samples in HB patients (n = 8 pairs). This study demonstrates that the metabolomic landscape of HB is distinct from that of non-tumour (NT) liver tissue, with 35 differentially abundant metabolites mapping onto pathways such as fatty acid transport, glycolysis, the tricarboxylic acid (TCA) cycle, branched-chain amino acid degradation and glutathione synthesis. Targeted metabolomics demonstrated reduced short-chain acylcarnitines and a relative accumulation of branched-chain amino acids. Medium- and long-chain acylcarnitines in HB were similar to those in NT. The metabolomic changes reported are consistent with previously reported transcriptomic data from tumour and non-tumour samples (49 out of 54 targets) as well as metabolomic data obtained using other techniques. Gene set enrichment analysis (GSEA) from RNAseq data (n = 32 paired HB and NT samples) demonstrated a downregulation of the carnitine metabolome and immunohistochemistry showed a reduction in CPT1a (n = 15 pairs), which transports fatty acids into the mitochondria, suggesting a lack of utilisation of long-chain fatty acids in HB. Thus, our findings suggest a reduced metabolic flux in HB which is corroborated at the gene expression and protein levels. Further work could yield novel insights and new therapeutic targets.

Recent Review on Selected Xenobiotics and Their Impacts on Gut Microbiome and Metabolome

As it is well known, the gut is one of the primary sites in any host for xenobiotics, and the many microbial metabolites responsible for the interactions between the gut microbiome and the host. However, there is a growing concern about the negative impacts on human health induced by toxic xenobiotics. Metabolomics, broadly including lipidomics, is an emerging approach to studying thousands of metabolites in parallel. In this review, we summarized recent advancements in mass spectrometry (MS) technologies in metabolomics. In addition, we reviewed recent applications of MS-based metabolomics for the investigation of toxic effects of xenobiotics on microbial and host metabolism. It was demonstrated that metabolomics, gut microbiome profiling, and their combination have a high potential to identify metabolic and microbial markers of xenobiotic exposure and determine its mechanism. Further, there is increasing evidence supporting that reprogramming the gut microbiome could be a promising approach to the intervention of xenobiotic toxicity.

Mathematical reconstruction of the metabolic network in an in-vitro multiple myeloma model

It is increasingly apparent that cancer cells, in addition to remodelling their metabolism to survive and proliferate, adapt and manipulate the metabolism of other cells. This property may be a telling sign that pre-clinical tumour metabolism studies exclusively utilising in-vitro mono-culture models could prove to be limited for uncovering novel metabolic targets able to translate into clinical therapies. Although this is increasingly recognised, and work towards addressing the issue is becoming routinary much remains poorly understood. For instance, knowledge regarding the biochemical mechanisms through which cancer cells manipulate non-cancerous cell metabolism, and the subsequent impact on their survival and proliferation remains limited. Additionally, the variations in these processes across different cancer types and progression stages, and their implications for therapy, also remain largely unexplored. This study employs an interdisciplinary approach that leverages the predictive power of mathematical modelling to enrich experimental findings. We develop a functional multicellular in-silico model that facilitates the qualitative and quantitative analysis of the metabolic network spawned by an in-vitro co-culture model of bone marrow mesenchymal stem- and myeloma cell lines. To procure this model, we devised a bespoke human genome constraint-based reconstruction workflow that combines aspects from the legacy mCADRE & Metabotools algorithms, the novel redHuman algorithm, along with 13C-metabolic flux analysis. Our workflow transforms the latest human metabolic network matrix (Recon3D) into two cell-specific models coupled with a metabolic network spanning a shared growth medium. When cross-validating our in-silico model against the in-vitro model, we found that the in-silico model successfully reproduces vital metabolic behaviours of its in-vitro counterpart; results include cell growth predictions, respiration rates, as well as support for observations which suggest cross-shuttling of redox-active metabolites between cells.

Metabolism and Chemical Degradation of New Antidiabetic Drugs: A Review of Analytical Approaches for Analysis of Glutides and Gliflozins

The drug metabolism and drug degradation pathways may overlap, resulting in the formation of similar constituents. Therefore, the metabolism data can be helpful for deriving safe levels of degradation impurities and improving the quality of respective pharmaceutical products. The present article contains considerations on possible links between metabolic and degradation pathways for new antidiabetic drugs such as glutides, gliflozins, and gliptins. Special attention was paid to their reported metabolites and identified degradation products. At the same time, many interesting analytical approaches to conducting metabolism as well as degradation experiments were mentioned, including chromatographic methods and radioactive labeling of the drugs. The review addresses the analytical approaches elaborated for examining the metabolism and degradation pathways of glutides, i.e., glucagon like peptide 1 (GLP-1) receptor agonists, and gliflozins, i.e., sodium glucose co-transporter 2 (SGLT2) inhibitors. The problems associated with the chromatographic analysis of the peptide compounds (glutides) and the polar drugs (gliflozins) were addressed. Furthermore, issues related to in vitro experiments and the use of stable isotopes were discussed.

Advances of stable isotope technology in food safety analysis and nutrient metabolism research

Food quality, safety, and the regulatory metabolism of food nutrients in cells are primary factors in determining human health. However, residues of undesirable or hazardous compounds in food products and dysregulation in the nutrient metabolism inevitably occur occasionally. For years, chromatography-mass spectrometry technology has been recognized as an essential research tool in food analysis and nutrient metabolism research, and it is more accurate and robust when coupled with stable isotopes. In this study, we summarize the applications of stable isotope technology in the quantification of contaminant residues (pesticides, veterinary drugs, mycotoxins, polycyclic aromatic hydrocarbons, and other hazardous compounds) in foods and in the nutrients (glucose, lipids, amino acids and proteins) metabolism research. The aim of this review was to serve as a reference for providing effective analysis techniques for protecting food quality and human health, and to pave the way for the broader application of stable isotope technology.

The use of nitrogen-15 in microbial natural product discovery and biosynthetic characterization

This mini-review covers the use of nitrogen-15 in bacterial and fungal natural product discovery and biosynthetic characterization from 1970 to 2022. Nitrogen is an important element in a number of bioactive and structurally intriguing natural products including alkaloids, non-ribosomal peptides, and hybrid natural products. Nitrogen-15 can be detected at natural abundance utilizing two-dimensional nuclear magnetic resonance and mass spectrometry. Additionally, it is a stable isotope that can be added to growth media for both filamentous fungi and bacteria. With stable isotope feeding, additional two-dimensional nuclear magnetic resonance and mass spectrometry strategies have become available, and there is a growing trend to use nitrogen-15 stable isotope feeding for the biosynthetic characterization of natural products. This mini-review will catalog the use of these strategies, analyze the strengths and weaknesses of the different approaches, and suggest future directions for the use of nitrogen-15 in natural product discovery and biosynthetic characterization.

A strategy for evaluation of isotopic enrichment and structural integrity of deuterium labelled compounds by using HR-MS and NMR

Determining the purity of deuterium labelled compounds is important due to the increasing use of these compounds in mass spectrometry (MS) based quantitative analyses for targeting metabolic flux, reducing toxicity, confirming reaction mechanisms during synthesis, predicting enzyme mechanisms, and enhancing the efficacy of drugs, in quantitative proteomics, and also as internal standards. In the present study, a strategy using liquid chromatography electrospray ionization high resolution mass spectrometry (LC-ESI-HR-MS) and nuclear magnetic resonance (NMR) spectroscopy was proposed to determine the isotopic enrichment and structural integrity of deuterium labelled compounds. The proposed strategy involves recording full scan MS, extracting and integrating isotopic ions, and calculating the isotopic enrichment of the desired labelled compounds. NMR analysis confirms structural integrity or positions of labelled atoms and can provide insights into the relative percent isotopic purity. This strategy was used to evaluate the isotopic enrichment and structural integrity of in-house synthesized compounds as well as a series of commercially available deuterium labelled compounds. The % isotopic purity for labelled compounds of a benzofuranone derivative (BEN-d₂), tamsulosin-d₄ (TAM-d₄), oxybutynin-d₅ (OXY-d₅), eplerenone-d₃ (EPL-d₃), and propafenone-d₇ (PRO-d₇) was calculated and found to be 94.7, 99.5, 98.8, 99.9, and 96.5, respectively. All the samples were run in triplicate and the results were observed to be reproducible.

11C, 12C and 13C-Cyanation of Electron-Rich Arenes via Organic Photoredox Catalysis

As a non-invasive imaging technology, positron emission tomography (PET) plays a crucial role in personalized medicine, including early diagnosis, patient screening, and treatment monitoring. The advancement of PET research depends on the discovery of new PET agents, which requires the development of simple and efficient radiolabeling methods in many cases. As bioisosteres for halogen and carbonyl moieties, nitriles are important functional groups in pharmaceutical and agrochemical compounds. Here, we disclose a mild organophotoredox-catalyzed method for efficient cyanation of a broad spectrum of electron-rich arenes, including abundant and readily available veratroles and pyrogallol trimethyl ethers. Notably, the transformations not only are compatible with various affordable 12C and 13C-cyanide sources, but also could be applied to carbon-11 synthons to incorporate [11C]nitriles into arenes. The aryl [11C]nitriles can be further derivatized to [11C]carboxylic acids, [11C]amides, and [11C]alkyl amines. The newly developed reaction can serve as a powerful tool for generating new PET agents.

Mass Spectroscopy as an Analytical Tool to Harness the Production of Secondary Plant Metabolites: The Way Forward for Drug Discovery

The molecular map of diverse biological molecules linked with structure, function, signaling, and regulation within a cell can be elucidated using an analytically demanding omic approach. The latest trend of using "metabolomics" technologies has explained the natural phenomenon of opening a new avenue to understand and enhance bioactive compounds' production. Examination of sequenced plant genomes has revealed that a considerable portion of these encodes genes of secondary metabolism. In addition to genetic and molecular tools developed in the current era, the ever-increasing knowledge about plant metabolism's biochemistry has initiated an approach for wisely designed, more productive genetic engineering of plant secondary metabolism for improved defense systems and enhanced biosynthesis of beneficial metabolites. Secondary plant metabolites are natural products synthesized by plants that are not directly involved with their average growth and development but play a vital role in plant defense mechanisms. Plant secondary metabolites are classified into four major classes: terpenoids, phenolic compounds, alkaloids, and sulfur-containing compounds. More than 200,000 secondary metabolites are synthesized by plants having a unique and complex structure. Secondary plant metabolites are well characterized and quantified by omics approaches and therefore used by humans in different sectors such as agriculture, pharmaceuticals, chemical industries, and biofuel. The aim is to establish metabolomics as a comprehensive and dynamic model of diverse biological molecules for biomarkers and drug discovery. In this chapter, we aim to illustrate the role of metabolomic technology, precisely liquid chromatography-mass spectrometry, capillary electrophoresis mass spectrometry, gas chromatography-mass spectrometry, and nuclear magnetic resonance spectroscopy, specifically as a research tool in the production and identification of novel bioactive compounds for drug discovery and to obtain a unified insight of secondary metabolism in plants.

From protein biomarkers to proteomics in dementia with Lewy Bodies

Dementia with Lewy Bodies (DLB) is the second most common neurodegenerative dementia. Despite considerable research progress, there remain gaps in our understanding of the pathophysiology and there is no disease-modifying treatment. Proteomics is a powerful tool to elucidate complex biological pathways across heterogenous conditions. This review summarizes the widely used proteomic methods and presents evidence for protein dysregulation in the brain and peripheral tissues in DLB. Proteomics of post-mortem brain tissue shows that DLB shares common features with other dementias, such as synaptic dysfunction, but retains a unique protein signature. Promising diagnostic biomarkers are being identified in cerebrospinal fluid (CSF), blood, and peripheral tissues, such as serum Heart-type fatty acid binding protein. Research is needed to track these changes from the prodromal stage to established dementia, with standardized workflows to ensure replicability. Identifying novel protein targets in causative biological pathways could lead to the development of new targeted therapeutics or the stratification of participants for clinical trials.

Isotopic Tracer for Absolute Quantification of Metabolites of the Pentose Phosphate Pathway in Bacteria

The pentose phosphate pathway (PPP) plays a key role in many metabolic functions, including the generation of NADPH, biosynthesis of nucleotides, and carbon homeostasis. In particular, the intermediates of PPP have been found to be significantly perturbed in bacterial metabolomic studies. Nonetheless, detailed analysis to gain mechanistic information of PPP metabolism remains limited as most studies are unable to report on the absolute levels of the metabolites. Absolute quantification of metabolites is a prerequisite to study the details of fluxes and its regulations. Isotope tracer or labeling studies are conducted in vivo and in vitro and have significantly improved the analysis and understanding of PPP. Due to the laborious procedure and limitations in the in vivo method, an in vitro approach known as Group Specific Internal Standard Technology (GSIST) has been successfully developed to measure the absolute levels of central carbon metabolism, including PPP. The technique adopts derivatization of an experimental sample and a corresponding internal standard with isotope-coded reagents to provide better precision for accurate identification and absolute quantification. In this review, we highlight bacterial studies that employed isotopic tracers as the tagging agents used for the absolute quantification analysis of PPP metabolites.

FunHoP analysis reveals upregulation of mitochondrial genes in prostate cancer

Mitochondrial activity in cancer cells has been central to cancer research since Otto Warburg first published his thesis on the topic in 1956. Although Warburg proposed that oxidative phosphorylation in the tricarboxylic acid (TCA) cycle was perturbed in cancer, later research has shown that oxidative phosphorylation is activated in most cancers, including prostate cancer (PCa). However, more detailed knowledge on mitochondrial metabolism and metabolic pathways in cancers is still lacking. In this study we expand our previously developed method for analyzing functional homologous proteins (FunHoP), which can provide a more detailed view of metabolic pathways. FunHoP uses results from differential expression analysis of RNA-Seq data to improve pathway analysis. By adding information on subcellular localization based on experimental data and computational predictions we can use FunHoP to differentiate between mitochondrial and non-mitochondrial processes in cancerous and normal prostate cell lines. Our results show that mitochondrial pathways are upregulated in PCa and that splitting metabolic pathways into mitochondrial and non-mitochondrial counterparts using FunHoP adds to the interpretation of the metabolic properties of PCa cells.

The Promises, Challenges, and Opportunities of Omics for Studying the Plant Holobiont

Microorganisms are critical drivers of biological processes that contribute significantly to plant sustainability and productivity. In recent years, emerging research on plant holobiont theory and microbial invasion ecology has radically transformed how we study plant–microbe interactions. Over the last few years, we have witnessed an accelerating pace of advancements and breadth of questions answered using omic technologies. Herein, we discuss how current state-of-the-art genomics, transcriptomics, proteomics, and metabolomics techniques reliably transcend the task of studying plant–microbe interactions while acknowledging existing limitations impeding our understanding of plant holobionts.

Estradiol, Estrone and Ethinyl Estradiol Metabolism Studied by High Resolution LC-MS/MS Using Stable Isotope Labeling and Trapping of Reactive Metabolites

Biotransformation reactions that xenobiotics undergo during their metabolism are crucial for their proper excretion from the body, but can also be a source of toxicity, especially in the case of reactive metabolite formation. Unstable, reactive metabolites are capable of covalent binding to proteins, and have often been linked to liver damage and other undesired side effects. A common technique to assess the formation of reactive metabolites employs trapping them in vitro with glutathione and characterizing the resulting adducts by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Some endogenous compounds, however, can interfere with xenobiotic metabolites of interest, making the analysis more difficult. This study demonstrates the usefulness of isotope-labeled compounds to detect and elucidate the structures of both stable metabolites and trapped adducts of three estrogen analogs using an untargeted LC-MS/MS workflow. The metabolism of estradiol, estrone and ethinyl estradiol was investigated. Unlabeled and deuterated versions of these three compounds were incubated with human or rat liver microsomes in the presence of two different trapping agents, namely glutathione and N-acetylcysteine. The detection of closely eluting deuterated peaks allowed us to confirm the formation of several known metabolites, as well as many previously uncharacterized ones. The structure of each adduct was elucidated by the detailed analysis of high-resolution MS/MS spectra for elucidating fragmentation pathways with accurate mass measurements. The use of isotopic labeling was crucial in helping confirm many metabolites and adduct structures, as well as removing endogenous interferences.

Stable isotope approaches and opportunities for improving plant conservation

Successful conservation of threatened species and ecosystems in a rapidly changing world requires scientifically sound decision-making tools that are readily accessible to conservation practitioners. Physiological applications that examine how plants and animals interact with their environment are now widely used when planning, implementing and monitoring conservation. Among these tools, stable-isotope physiology is a potentially powerful, yet under-utilized cornerstone of current and future conservation efforts of threatened and endangered plants. We review the underlying concepts and theory of stable-isotope physiology and describe how stable-isotope applications can support plant conservation. We focus on stable isotopes of carbon, hydrogen, oxygen and nitrogen to address plant ecophysiological responses to changing environmental conditions across temporal scales from hours to centuries. We review examples from a broad range of plant taxa, life forms and habitats and provide specific examples where stable-isotope analysis can directly improve conservation, in part by helping identify resilient, locally adapted genotypes or populations. Our review aims to provide a guide for practitioners to easily access and evaluate the information that can be derived from stable-isotope signatures, their limitations and how stable isotopes can improve conservation efforts.

One-Pot Sequential Hydrogen Isotope Exchange/Reductive Deuteration for the Preparation of α,β-Deuterated Alcohols using Deuterium Oxide

An efficient one-pot sequential hydrogen isotope exchange (HIE)/reductive deuteration approach was developed for the preparation of α,β-deuterated alcohols using ketones as the precursors. The HIE step can also be used for the synthesis of α-deuterated ketones. This method has been applied in the synthesis of four deuterated drug and MS internal standards.

Single-cell stable isotope probing in microbial ecology

Environmental and host-associated microbiomes are typically diverse assemblages of organisms performing myriad activities and engaging in a network of interactions that play out in spatially structured contexts. As the sum of these activities and interactions give rise to overall microbiome function, with important consequences for environmental processes and human health, elucidating specific microbial activities within complex communities is a pressing challenge. Single-cell stable isotope probing (SC-SIP) encompasses multiple techniques that typically utilize Raman microspectroscopy or nanoscale secondary ion mass spectrometry (NanoSIMS) to enable spatially resolved tracking of isotope tracers in cells, cellular components, and metabolites. SC-SIP techniques are uniquely suited for illuminating single-cell activities in microbial communities and for testing hypotheses about cellular functions generated for example from meta-omics datasets. Here, we illustrate the insights enabled by SC-SIP techniques by reviewing selected applications in microbiology and offer a perspective on their potential for future research.

A rapid and robust method for amino acid quantification using a simple N-hydroxysuccinimide ester derivatization and liquid chromatography-ion mobility-mass spectrometry

The vast majority of mass spectrometry (MS)-based metabolomics studies employ reversed-phase liquid chromatography (RPLC) to separate analytes prior to MS detection. Highly polar metabolites, such as amino acids (AAs), are poorly retained by RPLC, making quantitation of these key species challenging across the broad concentration ranges typically observed in biological specimens, such as cell extracts. To improve the detection and quantitation of AAs in microglial cell extracts, the implementation of a 4-dimethylaminobenzoylamido acetic acid N-hydroxysuccinimide ester (DBAA-NHS) derivatization agent was explored for its ability to improve both analyte retention and detection limits in RPLC-MS. In addition to the introduction of the DBAA-NHS labeling reagent, a uniformly (U) ¹³C-labeled yeast extract was also introduced during the sample preparation workflow as an internal standard (IS) to eliminate artifacts and to enable targeted quantitation of AAs, as well as untargeted amine submetabolome profiling. To improve method sensitivity and selectivity, multiplexed drift-tube ion mobility (IM) was integrated into the LC-MS workflow, facilitating the separation of isomeric metabolites, and improving the structural identification of unknown metabolites. Implementation of the U-¹³C-labeled yeast extract during the multiplexed LC-IM-MS analysis enabled the quantitation of 19 of the 20 common AAs, supporting a linear dynamic range spanning up to three orders of magnitude in concentration for microglial cell extracts, in addition to reducing the required cell count for reliable quantitation from 10 to 5 million cells per sample.

TraVis Pies: A Guide for Stable Isotope Metabolomics Interpretation Using an Intuitive Visualization

Tracer metabolomics is a powerful technology for the biomedical community to study and understand disease-inflicted metabolic mechanisms. However, the interpretation of tracer metabolomics results is highly technical, as the metabolites’ abundances, tracer incorporation and positions on the metabolic map all must be jointly interpreted. The field is currently lacking a structured approach to help less experienced researchers start the interpretation of tracer metabolomics datasets. We propose an approach using an intuitive visualization concept aided by a novel open-source tool, and provide guidelines on how researchers can apply the approach and the visualization tool to their own datasets. Using a showcase experiment, we demonstrate that the visualization approach leads to an intuitive interpretation that can ease researchers into understanding their tracer metabolomics data.

An optimization method for untargeted MS-based isotopic tracing investigations of metabolism

INTRODUCTION

Stable isotope tracer studies are increasingly applied to explore metabolism from the detailed analysis of tracer incorporation into metabolites. Untargeted LC/MS approaches have recently emerged and provide potent methods for expanding the dimension and complexity of the metabolic networks that can be investigated. A number of software tools have been developed to process the highly complex MS data collected in such studies; however, a method to optimize the extraction of valuable isotopic data is lacking.

OBJECTIVES

To develop and validate a method to optimize automated data processing for untargeted MS-based isotopic tracing investigations of metabolism.

METHODS

The method is based on the application of a suitable reference material to rationally perform parameter optimization throughout the complete data processing workflow. It was applied in the context of ¹³C-labelling experiments and with two different software, namely geoRge and X13CMS. It was illustrated with the study of a E. coli mutant impaired for central metabolism.

RESULTS

The optimization methodology provided significant gain in the number and quality of extracted isotopic data, independently of the software considered. Pascal triangle samples are well suited for such purpose since they allow both the identification of analytical issues and optimization of data processing at the same time.

CONCLUSION

The proposed method maximizes the biological value of untargeted MS-based isotopic tracing investigations by revealing the full metabolic information that is encoded in the labelling patterns of metabolites.

Low and high resolution gas chromatography-mass spectrometry for untargeted metabolomics: A tutorial

GC-MS for untargeted metabolomics is a well-established technique. Small molecules and molecules made volatile by derivatization can be measured and those compounds are key players in main biological pathways. This tutorial provides ready-to-use protocols for GC-MS-based metabolomics, using either the well-known low-resolution approach (GC-Q-MS) with nominal mass or the more recent high-resolution approach (GC-QTOF-MS) with accurate mass, discussing their corresponding strengths and limitations. Analytical procedures are covered for different types of biofluids (plasma/serum, bronchoalveolar lavage, urine, amniotic fluid) tissue samples (brain/hippocampus, optic nerve, lung, kidney, liver, pancreas) and samples obtained from cell cultures (adipocytes, macrophages, Leishmania promastigotes, mitochondria, culture media). Together with the sample preparation and data acquisition, data processing strategies are described specially focused on Agilent equipments, including deconvolution software and database annotation using spectral libraries. Manual curation strategies and quality control are also deemed. Finally, considerations to obtain a semiquantitative value for the metabolites are also described. As a case study, an illustrative example from one of our experiments at CEMBIO Research Centre, is described and findings discussed.

Lessons From Insect Fungiculture: From Microbial Ecology to Plastics Degradation

Anthropogenic activities have extensively transformed the biosphere by extracting and disposing of resources, crossing boundaries of planetary threat while causing a global crisis of waste overload. Despite fundamental differences regarding structure and recalcitrance, lignocellulose and plastic polymers share physical-chemical properties to some extent, that include carbon skeletons with similar chemical bonds, hydrophobic properties, amorphous and crystalline regions. Microbial strategies for metabolizing recalcitrant polymers have been selected and optimized through evolution, thus understanding natural processes for lignocellulose modification could aid the challenge of dealing with the recalcitrant human-made polymers spread worldwide. We propose to look for inspiration in the charismatic fungal-growing insects to understand multipartite degradation of plant polymers. Independently evolved in diverse insect lineages, fungiculture embraces passive or active fungal cultivation for food, protection, and structural purposes. We consider there is much to learn from these symbioses, in special from the community-level degradation of recalcitrant biomass and defensive metabolites. Microbial plant-degrading systems at the core of insect fungicultures could be promising candidates for degrading synthetic plastics. Here, we first compare the degradation of lignocellulose and plastic polymers, with emphasis in the overlapping microbial players and enzymatic activities between these processes. Second, we review the literature on diverse insect fungiculture systems, focusing on features that, while supporting insects' ecology and evolution, could also be applied in biotechnological processes. Third, taking lessons from these microbial communities, we suggest multidisciplinary strategies to identify microbial degraders, degrading enzymes and pathways, as well as microbial interactions and interdependencies. Spanning from multiomics to spectroscopy, microscopy, stable isotopes probing, enrichment microcosmos, and synthetic communities, these strategies would allow for a systemic understanding of the fungiculture ecology, driving to application possibilities. Detailing how the metabolic landscape is entangled to achieve ecological success could inspire sustainable efforts for mitigating the current environmental crisis.

An isotopic labeling approach linking natural products with biosynthetic gene clusters

Major advances in genome sequencing and large-scale biosynthetic gene cluster (BGC) analysis have prompted an age of natural product discovery driven by genome mining. Still, connecting molecules to their cognate BGCs is a substantial bottleneck for this approach. We have developed a mass-spectrometry-based parallel stable isotope labeling platform, termed IsoAnalyst, which assists in associating metabolite stable isotope labeling patterns with BGC structure prediction to connect natural products to their corresponding BGCs. Here we show that IsoAnalyst can quickly associate both known metabolites and unknown analytes with BGCs to elucidate the complex chemical phenotypes of these biosynthetic systems. We validate this approach for a range of compound classes, using both the type strain Saccharopolyspora erythraea and an environmentally isolated Micromonospora sp. We further demonstrate the utility of this tool with the discovery of lobosamide D, a new and structurally unique member of the family of lobosamide macrolactams.

Metabolomics as an emerging tool to study plant–microbe interactions

In natural environments, interaction between plant roots and microorganisms are common. These interactions between microbial species and plants inhabited by them are being studied using various techniques. Metabolomics research based on mass spectrometric techniques is one of the crucial approaches that underpins system biology and relies on precision instrument analysis. In the last decade, this emerging field has received extensive attention. It provides a qualitative and quantitative approach for determining the mechanisms of symbiosis of bacteria and fungi with plants and also helps to elucidate the tolerance mechanisms of host plants against various abiotic stresses. However, this -omics application and its tools in plant–microbe interaction studies is still underutilized compared with genomic and transcriptomic methods. Therefore, it is crucial to bring this field forward to bear on the study of plant resistance and susceptibility. This review describes the current status of methods and progress in metabolomics applications for plant–microbe interaction studies discussing current challenges and future prospects.

CPExtract, a Software Tool for the Automated Tracer-Based Pathway Specific Screening of Secondary Metabolites in LC-HRMS Data

The use of stable isotopically labeled tracers is a long-proven way of specifically detecting and tracking derived metabolites through a metabolic network of interest. While the recently developed stable isotope-assisted methods and associated, supporting data analysis tools have greatly improved untargeted metabolomics approaches, no software tool is currently available that allows us to automatically and flexibly search liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) chromatograms for user-definable isotopolog patterns expected for the metabolism of labeled tracer substances. Here, we present Custom Pattern Extract (CPExtract), a versatile software tool that allows for the first time the high-throughput search for user-defined isotopolog patterns in LC-HRMS data. The patterns can be specified via a set of rules including the presence or absence of certain isotopologs, their relative intensity ratios as well as chromatographic coelution. Each isotopolog pattern satisfying the respective rules is verified on an MS scan level and also in the chromatographic domain. The CPExtract algorithm allows the use of both labeled tracer compounds in nonlabeled biological samples as well as a reversed tracer approach, employing nonlabeled tracer compounds along with globally labeled biological samples. In a proof-of-concept study, we searched for metabolites specifically arising from the malonate pathway of the filamentous fungi Fusarium graminearum and Trichoderma reesei. 1,2,3-¹³C₃-malonic acid diethyl ester and native malonic acid monomethyl ester were used as tracers. We were able to reliably detect expected fatty acids and known polyketides. In addition, up to 46 and 270 further, unknown metabolites presumably including novel polyketides were detected in the F. graminearum and T. reesei culture samples, respectively, all of which exhibited the user-predicted isotopolog patterns originating from the malonate tracer incorporation. The software can be used for every conceivable tracer approach. Furthermore, the rule sets can be easily adapted or extended if necessary. CPExtract is available free of charge for noncommercial use at https://metabolomics-ifa.boku.ac.at/CPExtract.

Combining Isotopologue Workflows and Simultaneous Multidimensional Separations to Detect, Identify, and Validate Metabolites in Untargeted Analyses

While the combination of liquid chromatography and tandem mass spectrometry (LC-MS/MS) is commonly used for feature annotation in untargeted omics experiments, ensuring these prioritized features originate from endogenous metabolism remains challenging. Isotopologue workflows, such as isotopic ratio outlier analysis (IROA), mass isotopomer ratio analysis of U-¹³C labeled extracts (MIRACLE), and credentialing incorporate isotopic labels directly into metabolic precursors, guaranteeing that all features of interest are unequivocal byproducts of cellular metabolism. Furthermore, comprehensive separation and annotation of small molecules continue to challenge the metabolomics field, particularly for isomeric systems. In this paper, we evaluate the analytical utility of incorporating ion mobility spectrometry (IMS) as an additional separation mechanism into standard LC-MS/MS isotopologue workflows. Since isotopically labeled molecules codrift in the IMS dimension with their ¹²C versions, LC-IMS-CID-MS provides four dimensions (LC, IMS, MS, and MS/MS) to directly investigate the metabolic activity of prioritized untargeted features. Here, we demonstrate this additional selectivity by showcasing how a preliminary data set of 30 endogeneous metabolites are putatively annotated from isotopically labeled Escherichia coli cultures when analyzed by LC-IMS-CID-MS. Metabolite annotations were based on several molecular descriptors, including accurate mass measurement, carbon number, annotated fragmentation spectra, and collision cross section (CCS), collectively illustrating the importance of incorporating IMS into isotopologue workflows. Overall, our results highlight the enhanced separation space and increased annotation confidence afforded by IMS for metabolic characterization and provide a unique perspective for future developments in isotopically labeled MS experiments.

Elucidation of xenoestrogen metabolism by non-targeted, stable isotope-assisted mass spectrometry in breast cancer cells

Environmental exposure to xenoestrogens, i.e., chemicals that imitate the hormone 17β-estradiol, has the potential to influence hormone homeostasis and action. Detailed knowledge of xenobiotic biotransformation processes in cell models is key when transferring knowledge learned from in vitro models to in vivo relevance. This study elucidated the metabolism of two naturally-occurring phyto- and mycoestrogens; namely genistein and zearalenone, in an estrogen receptor positive breast cancer cell line (MCF-7) with the aid of stable isotope-assisted metabolomics and the bioinformatic tool MetExtract II. Metabolism was studied in a time course experiment after 2 h, 6 h and 24 h incubation. Twelve and six biotransformation products of zearalenone and genistein were detected, respectively, clearly demonstrating the abundant xenobiotic biotransformation capability of the cells. Zearalenone underwent extensive phase-I metabolism resulting in α-zearalenol (α-ZEL), a molecule known to possess a significantly higher estrogenicity, and several phase-II metabolites (sulfo- and glycoconjugates) of the native compound and the major phase I metabolite α-ZEL. Moreover, potential adducts of zearalenone with a vitamin and several hydroxylated metabolites were annotated. Genistein metabolism resulted in sulfation, combined sulfation and hydroxylation, acetylation, glucuronidation and unexpectedly adduct formation with pentose- and hexose sugars. Kinetics of metabolite formation and subsequent excretion into the extracellular medium revealed a time-dependent increase in most biotransformation products. The untargeted elucidation of biotransformation products formed during cell culture experiments enables an improved and more meaningful interpretation of toxicological assays and has the potential to identify unexpected or unknown metabolites.

RTP: One Effective Platform to Probe Reactive Compound Transformation Products and Its Applications for a Reactive Plasticizer BADGE

Reactive compounds, such as covalent toxicants/drugs, have their ubiquitous occurrences and are known to react with protein or DNA in human beings, but their reactions with endogenous metabolites are rarely understood. Currently, a viable platform is demanded for discovering their reaction products since their efficacy/toxicity may be altered after the reaction. We aim to develop a platform for identifying unknown abiotic or biotransformation products for these reactive compounds. Based on stable isotope-labeling (SIL) metabolomics, we have developed a novel and robust analytical platform, reactive compound transformation profiler (RTP), which can automatically analyze preannotated high-resolution mass spectrometry (LC-HRMS) data sets and uncover probable transformation products. Generally, RTP consists of four complementary steps: (1) selecting peak pairs of light and heavy-labeled products, (2) defining the "core structure mass" for possible reaction search, (3) constructing an endogenous metabolite reaction database, and (4) developing algorithms to propose the potential transformation products by searching against the database with a single-/multiple-site reaction. Its performance was validated using the reactive plasticizer bisphenol A diglycidyl ether (BADGE) in several sample matrices. This platform enabled the identification of novel transformation products while also demonstrating its capacity to filter out the false-positive signals and provide product annotation. The RTP is freely accessible at https://github.com/FangLabNTU/Reactive-Compound-Transformation-Profiler-RTP-.

Combination of high specific activity carbon-14 labeling and high resolution mass spectrometry to study pesticide metabolism in crops: Metabolism of cycloxaprid in rice

The study of pesticide metabolism in crops is critical for assessing the mode of action and environmental risks of pesticides. However, the study of pesticide metabolism in crops is usually complicated and it is often a daunting challenge to accurately screen the metabolites of novel pesticides in complex matrices. This study demonstrated a combined use of high-specific activity carbon-14 labeling and high-resolution mass spectrometry (HSA-¹⁴C-HRMS) for metabolism profiling of a novel neonicotinoid cycloxaprid in rice. By generating the characteristic radioactive peaks on the liquid chromatogram, the use of ¹⁴C can eliminate the severe interference of complex matrices and quickly probe target compounds; by producing ion pairs with unique abundance ratios on HRMS, high-specific activity labeling can effectively exclude false matrix positives and promote the elucidation of metabolite structure. The structures of 15 metabolites were identified, three of which were further confirmed by authentic standards. Based on these metabolites, a metabolic profile of cycloxaprid was established, which includes denitrification, demethylation, imidazolidine hydroxylation and ring cleavage olefin formation, oxidation and carboxylation reactions. The strategy of combining high-specific activity ¹⁴C labeling and HRMS offers unique advantages and provides a powerful solution for profiling unknown metabolites of novel pesticides in complex matrices, especially when traditional non-labeling methods are not feasible.

Novel Stable Isotope-Resolved Metabolomics Method for a Small Number of Cells Using Chip-Based Nanoelectrospray Mass Spectrometry

Stable isotope-resolved metabolomics (SIRM) can provide metabolic conversion information of specific targets; it is a powerful tool for cell metabolism studies. The common analytical platform for SIRM is chromatography-mass spectrometry, which requires a large number of cells and is not suitable for precious rare cell analysis. To study a small number of cells, we established a novel SIRM method using chip-based nanoelectrospray mass spectrometry (MS). ¹³C-glutamine was taken as an example; the unlabeled and ¹³C-labeled cells were cultured and extracted in a 96-well plate and then directly injected into MS and analyzed in full scan mode and parallel reaction monitoring (PRM) mode targeting 44 glutamine-derived metabolites and their isotopologues. To define focused metabolite-related MS2 fragments produced in the PRM, a new strategy was proposed including MS2 exact m/z matching, MS2 false positive filtering, and MS2 fragment grouping to remove the interfering MS2 ions. In total, 292 and 349 pairs of paired MS2 ions were obtained in positive and negative ionization modes, respectively. By searching spectra databases, 31 targeted metabolites with their isotopologues were identified and their characteristic product ions were confirmed for MS2 quantification. The relative quantification was achieved by MS2 quantification, which showed better sensitivity and accuracy than common MS1-based quantification. Finally, this method was applied to isocitrate dehydrogenase I-mutated glioma cells for revealing the effects of triptolide on glioma cell metabolism using U-¹³C-glutamine as a labeling substrate.

A comparative study at bioprocess and metabolite levels of superhost strain Streptomyces coelicolor M1152 and its derivative M1581 heterologously expressing chloramphenicol biosynthetic gene cluster

Microbial superhost strains should provide an ideal platform for the efficient homologous or heterologous phenotypic expression of biosynthetic gene clusters (BGCs) of new and novel bioactive molecules. Our aim in the current study was to perform a comparative study at the bioprocess and metabolite levels of the previously designed superhost strain Streptomyces coelicolor M1152 and its derivative strain S. coelicolor M1581 heterologously expressing chloramphenicol BGC. Parent strain M1152 was characterized by a higher specific growth rate, specific CO₂ evolution rate, and a higher specific l-glutamate consumption rate as compared with M1581. Intracellular primary central metabolites (nucleoside/sugar phosphates, amino acids, organic acids, and CoAs) were quantified using four targeted LC-MS/MS-based methods. The metabolite pathways in the nonantibiotic producing S. coelicolor host strain were flooded with carbon from both carbon sources, whereas in antibiotic-producing strain, the carbon of l-glutamate seems to be draining out through excreting synthesized antibiotic. The ¹³ C-isotope-labeling experiments revealed the bidirectionality in the glycolytic pathway and reversibility in the non-oxidative part of PPP even with continuous uptake of d-glucose. The change in the primary metabolites due to the insertion of BGC disclosed a clear linkage between the primary and secondary metabolites.

Chemoselective and highly sensitive quantification of gut microbiome and human metabolites

The microbiome has a fundamental impact on the human host's physiology through the production of highly reactive compounds that can lead to disease development. One class of such compounds are carbonyl‐containing metabolites, which are involved in diverse biochemical processes. Mass spectrometry is the method of choice for analysis of metabolites but carbonyls are analytically challenging. Herein, we have developed a new chemical biology tool using chemoselective modification to overcome analytical limitations. Two isotopic probes allow for the simultaneous and semi‐quantitative analysis at the femtomole level as well as qualitative analysis at attomole quantities that allows for detection of more than 200 metabolites in human fecal, urine and plasma samples. This comprehensive mass spectrometric analysis enhances the scope of metabolomics‐driven biomarker discovery. We anticipate that our chemical biology tool will be of general use in metabolomics analysis to obtain a better understanding of microbial interactions with the human host and disease development.

Distinct nitrogen isotopic compositions of healthy and cancerous tissue in mice brain and head&neck micro-biopsies

BACKGROUND

Cancerous cells can recycle metabolic ammonium for their growth. As this ammonium has a low nitrogen isotope ratio (15N/14N), its recycling may cause cancer tissue to have lower 15N/14N than surrounding healthy tissue. We investigated whether, within a given tissue type in individual mice, tumoral and healthy tissues could be distinguished based on their 15N/14N.

METHODS

Micro-biopsies of murine tumors and adjacent tissues were analyzed for 15N/14N using novel high-sensitivity methods. Isotopic analysis was pursued in Nude and C57BL/6 mice models with mature orthotopic brain and head&neck tumors generated by implantation of H454 and MEERL95 murine cells, respectively.

RESULTS

In the 7 mice analyzed, the brain tumors had distinctly lower 15N/14N than healthy neural tissue. In the 5 mice with head&neck tumors, the difference was smaller and more variable. This was at least partly due to infiltration of healthy head&neck tissue by tumor cells. However, it may also indicate that the 15N/14N difference between tumoral and healthy tissue depends on the nitrogen metabolism of the healthy organ in question.

CONCLUSIONS

The findings, coupled with the high sensitivity of the 15N/14N measurement method used here, suggest a new approach for micro-biopsy-based diagnosis of malignancy as well as an avenue for investigation of cancer metabolism.

Possible role of corticosterone in proteolysis, glycolytic, and amino acid metabolism in primary cultured avian myotubes incubated at high-temperature conditions

Excess glucocorticoid secretion induces oxidative damage and muscle proteolysis and modulates glucose and lipid metabolism. It is known that the high-temperature (HT) treatment enhances corticosterone (CORT) secretion, muscle proteolysis, and mitochondrial reactive oxygen species (mtROS) generation in chickens. The present study investigated the co-effects of CORT on proteolysis and mtROS production, together with glucose, fatty acid, and amino acid metabolism in HT-treated cells. Myoblast cells were isolated from the major pectoralis muscle of five 0- or 1-day-old neonatal chicks and were precultured at 37°C/CO₂ conditions for 48 h to reach subconfluent (80%-90%) conditions. Cells were then reseeded onto a 6- or 24-well microplate for the subsequent measurement, followed by the culture under a control temperature (37°C, control) or HT (41°C) conditions for 1 or 6 h. The HT-treated cells were cocultured with physiologically relevant concentrations of CORT (20 ng/mL in dimethyl sulfoxide). The HT treatment decreased cellular protein content (P < 0.05) and increased atrogin-1 mRNA levels and mtROS generation levels compared to the control group (P < 0.05), whereas HT/CORT co-treatment did not induce changes in either parameter. The mRNA level of glucose transporter-1 was decreased in HT-treated cells compared to that in normal cells (P < 0.05), and the decrease was increased in the CORT co-treatment (P < 0.05). While HT treatment did not alter pyruvate dehydrogenase kinase-4 mRNA level, the level was increased in the CORT co-treatment compared to the control and HT-treated cells (P < 0.05). Neither HT nor HT/CORT treatments altered the mRNA levels of fatty acid oxidation-related factors, carnitine palmitoyl transferase-1, and cluster of differentiation 36. The study conducted a metabolic analysis using gas chromatography-mass spectrometry. The results showed that HT/CORT-treated cells had decreased intracellular citrate and α-ketoglutarate levels (P < 0.05) and increased extracellular alanine and amino acid that have gluconeogenic properties, as well as increased aspartate, isoleucine, serine, methionine, and threonine levels (P < 0.05) compared to HT-treated cells. These results suggest that CORT may not affect proteolysis and mtROS production but can suppress pyruvate oxidation and promote alanine production in HT-treated chickens.

Excess exogenous pyruvate inhibits lactate dehydrogenase activity in live cells in an MCT1-dependent manner

Cellular pyruvate is an essential metabolite at the crossroads of glycolysis and oxidative phosphorylation, capable of supporting fermentative glycolysis by reduction to lactate mediated by lactate dehydrogenase (LDH) among other functions. Several inherited diseases of mitochondrial metabolism impact extracellular (plasma) pyruvate concentrations, and [1-13C]pyruvate infusion is used in isotope-labeled metabolic tracing studies, including hyperpolarized magnetic resonance spectroscopic imaging. However, how these extracellular pyruvate sources impact intracellular metabolism is not clear. Herein, we examined the effects of excess exogenous pyruvate on intracellular LDH activity, extracellular acidification rates (ECARs) as a measure of lactate production, and hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion rates across a panel of tumor and normal cells. Combined LDH activity and LDHB/LDHA expression analysis intimated various heterotetrameric isoforms comprising LDHA and LDHB in tumor cells, not only canonical LDHA. Millimolar concentrations of exogenous pyruvate induced substrate inhibition of LDH activity in both enzymatic assays ex vivo and in live cells, abrogated glycolytic ECAR, and inhibited hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion rates in cellulo. Of importance, the extent of exogenous pyruvate-induced inhibition of LDH and glycolytic ECAR in live cells was highly dependent on pyruvate influx, functionally mediated by monocarboxylate transporter-1 localized to the plasma membrane. These data provided evidence that highly concentrated bolus injections of pyruvate in vivo may transiently inhibit LDH activity in a tissue type- and monocarboxylate transporter-1-dependent manner. Maintaining plasma pyruvate at submillimolar concentrations could potentially minimize transient metabolic perturbations, improve pyruvate therapy, and enhance quantification of metabolic studies, including hyperpolarized [1-13C]pyruvate magnetic resonance spectroscopic imaging and stable isotope tracer experiments.

Hierarchical Harmonization of Atom-Resolved Metabolic Reactions across Metabolic Databases

Metabolic models have been proven to be useful tools in system biology and have been successfully applied to various research fields in a wide range of organisms. A relatively complete metabolic network is a prerequisite for deriving reliable metabolic models. The first step in constructing metabolic network is to harmonize compounds and reactions across different metabolic databases. However, effectively integrating data from various sources still remains a big challenge. Incomplete and inconsistent atomistic details in compound representations across databases is a very important limiting factor. Here, we optimized a subgraph isomorphism detection algorithm to validate generic compound pairs. Moreover, we defined a set of harmonization relationship types between compounds to deal with inconsistent chemical details while successfully capturing atom-level characteristics, enabling a more complete enabling compound harmonization across metabolic databases. In total, 15,704 compound pairs across KEGG (Kyoto Encyclopedia of Genes and Genomes) and MetaCyc databases were detected. Furthermore, utilizing the classification of compound pairs and EC (Enzyme Commission) numbers of reactions, we established hierarchical relationships between metabolic reactions, enabling the harmonization of 3856 reaction pairs. In addition, we created and used atom-specific identifiers to evaluate the consistency of atom mappings within and between harmonized reactions, detecting some consistency issues between the reaction and compound descriptions in these metabolic databases.

Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data

Mining interspecies interactions remain a challenge due to the complex nature of microbial communities and the need for computational power to handle big data. Our meta-analysis indicates that genetic potential alone does not resolve all issues involving mining of microbial interactions. Nevertheless, it can be used as the starting point to infer synergistic interspecies interactions and to limit the search space (i.e., number of species and metabolic reactions) to a manageable size. A reduced search space decreases the number of additional experiments necessary to validate the inferred putative interactions. As validation experiments, we examine how multi-omics and state of the art imaging techniques may further improve our understanding of species interactions’ role in ecosystem processes. Finally, we analyze pros and cons from the current methods to infer microbial interactions from genetic potential and propose a new theoretical framework based on: (i) genomic information of key members of a community; (ii) information of ecosystem processes involved with a specific hypothesis or research question; (iii) the ability to identify putative species’ contributions to ecosystem processes of interest; and, (iv) validation of putative microbial interactions through integration of other data sources.

Metabolomics bridging proteomics along metabolites/oncometabolites and protein modifications: Paving the way toward integrative multiomics

Systems biology adopted functional and integrative multiomics approaches enable to discover the whole set of interacting regulatory components such as genes, transcripts, proteins, metabolites, and metabolite dependent protein modifications. This interactome build up the midpoint of protein-protein/PTM, protein-DNA/RNA, and protein-metabolite network in a cell. As the key drivers in cellular metabolism, metabolites are precursors and regulators of protein post-translational modifications [PTMs] that affect protein diversity and functionality. The precisely orchestrated core pattern of metabolic networks refer to paradigm 'metabolites regulate PTMs, PTMs regulate enzymes, and enzymes modulate metabolites' through a multitude of feedback and feed-forward pathway loops. The concept represents a flawless PTM-metabolite-enzyme(protein) regulomics underlined in reprogramming cancer metabolism. Immense interconnectivity of those biomolecules in their spectacular network of intertwined metabolic pathways makes integrated proteomics and metabolomics an excellent opportunity, and the central component of integrative multiomics framework. It will therefore be of significant interest to integrate global proteome and PTM-based proteomics with metabolomics to achieve disease related altered levels of those molecules. Thereby, present update aims to highlight role and analysis of interacting metabolites/oncometabolites, and metabolite-regulated PTMs loop which may function as translational monitoring biomarkers along the reprogramming continuum of oncometabolism.

Encoding Multiple Virtual Signals in DNA Barcodes with Single-Molecule FRET

DNA barcoding provides a way to label a myriad of different biological molecules using the extreme programmability in DNA sequence synthesis. Fluorescence imaging is presumably the most easy-to-access method for DNA barcoding, yet large spectral overlaps between fluorescence dyes severely limit the numbers of barcodes that can be detected simultaneously. We here demonstrate the use of single-molecule fluorescence resonance energy transfer (FRET) to encode virtual signals in DNA barcodes using conventional two-color fluorescence microscopy. By optimizing imaging and biochemistry conditions for weak DNA hybridization events, we markedly enhanced accuracy in our determination of the single-molecule FRET efficiency exhibited by each binding event between DNA barcode sequences. This allowed us to unambiguously differentiate six DNA barcodes encoding different FRET values without involving any probe sequence exchanges. Our method can be directly incorporated with previous DNA barcode techniques, and may thus be widely adopted to expand the signal space of DNA barcoding.

Tracing Nitrogen Metabolism in Mouse Tissues with Gas Chromatography-Mass Spectrometry

Nitrogen-containing metabolites including ammonia, amino acids, and nucleotides, are essential for cell metabolism, growth, and neural transmission. Nitrogen metabolism is tightly coordinated with carbon metabolism in the breakdown and biosynthesis of amino acids and nucleotides. Both nuclear magnetic resonance spectroscopy and mass spectrometry including gas chromatography-mass spectrometry (GC MS) and liquid chromatography (LC MS) have been used to measure nitrogen metabolism. Here we describe a protocol to trace nitrogen metabolism in multiple mouse tissues using ¹⁵N-ammonia coupled with GC MS. This protocol includes detailed procedures in tracer injection, tissue preparation, metabolite extraction, GC MS analysis and natural abundance corrections. This protocol will provide a useful tool to study tissue-specific nitrogen in metabolically active tissues such as the retina, brain, liver, and tumor.