Metabolomic strategies for the identification of new enzyme functions and metabolic pathways

Insight into the mechanism and toxicology of nitrofurantoin: a metabolomics approach

Safety and effectiveness are the two ends of the balance in drug development that needs to be evaluated. The biotransformation of drugs within a living organism could potentiate biochemical insults in the tissue and compromise the safety of drugs. Nitrofurantoin (NFT) is a cheap clinical antibiotic with a wide array of activities against gram-positive and gram-negative organisms. The NFT scaffold has been utilized to develop other derivates or analogues in the quest to repurpose drugs against other infectious diseases. Several techniques were developed over the years to study the mechanism of NFT metabolism and toxicity, such as voltammetry, chromatographic analysis, protein precipitation, liquid-liquid extraction, etc. Due to limitations in these methods, the mechanism of NFT biotransformation in the cell is poorly understood. Metabolomics has been adopted in drug metabolism to understand the mechanism of drug toxicity and could provide a solution to overcome the limitations of current techniques to determine mechanisms of toxicity. Unfortunately, little or no information regarding the metabolomics approach in NFT metabolism and toxicity is available. Hence, this review highlights the metabolomic techniques that can be adopted in NFT metabolism and toxicological studies to encourage the research community to widely adopt and utilize metabolomics in understanding NFT's metabolism and toxicity.

The Y-ome Conundrum: Insights into Uncharacterized Genes and Approaches for Functional Annotation

The ever-increasing availability of genome sequencing data has revealed a substantial number of uncharacterized genes without known functions across various organisms. The first comprehensive genome sequencing of E. coli K12 revealed that more than 50% of its open reading frames corresponded to transcripts with no known functions. The group of protein-coding genes without a functional description and/or a recognized pathway, beginning with the letter "Y", is classified as the "y-ome". Several efforts have been made to elucidate the functions of these genes and to recognize their role in biological processes. This review provides a brief update on various strategies employed when studying the y-ome, such as high-throughput experimental approaches, comparative omics, metabolic engineering, gene expression analysis, and data integration techniques. Additionally, we highlight recent advancements in functional annotation methods, including the use of machine learning, network analysis, and functional genomics approaches. Novel approaches are required to produce more precise functional annotations across the genome to reduce the number of genes with unknown functions.

Metabolic gene function discovery platform GeneMAP identifies SLC25A48 as necessary for mitochondrial choline import

Organisms maintain metabolic homeostasis through the combined functions of small-molecule transporters and enzymes. While many metabolic components have been well established, a substantial number remains without identified physiological substrates. To bridge this gap, we have leveraged large-scale plasma metabolome genome-wide association studies (GWAS) to develop a multiomic Gene-Metabolite Association Prediction (GeneMAP) discovery platform. GeneMAP can generate accurate predictions and even pinpoint genes that are distant from the variants implicated by GWAS. In particular, our analysis identified solute carrier family 25 member 48 (SLC25A48) as a genetic determinant of plasma choline levels. Mechanistically, SLC25A48 loss strongly impairs mitochondrial choline import and synthesis of its downstream metabolite betaine. Integrative rare variant and polygenic score analyses in UK Biobank provide strong evidence that the SLC25A48 causal effects on human disease may in part be mediated by the effects of choline. Altogether, our study provides a discovery platform for metabolic gene function and proposes SLC25A48 as a mitochondrial choline transporter.

Metabolomics and Microbial Metabolism: Toward a Systematic Understanding

Over the past decades, our understanding of microbial metabolism has increased dramatically. Metabolomics, a family of techniques that are used to measure the quantities of small molecules in biological samples, has been central to these efforts. Advances in analytical chemistry have made it possible to measure the relative and absolute concentrations of more and more compounds with increasing levels of certainty. In this review, we highlight how metabolomics has contributed to understanding microbial metabolism and in what ways it can still be deployed to expand our systematic understanding of metabolism. To that end, we explain how metabolomics was used to (a) characterize network topologies of metabolism and its regulation networks, (b) elucidate the control of metabolic function, and (c) understand the molecular basis of higher-order phenomena. We also discuss areas of inquiry where technological advances should continue to increase the impact of metabolomics, as well as areas where our understanding is bottlenecked by other factors such as the availability of statistical and modeling frameworks that can extract biological meaning from metabolomics data.

Subtractive Proteomics and Reverse-Vaccinology Approaches for Novel Drug Target Identification and Chimeric Vaccine Development against Bartonella henselae Strain Houston-1

Bartonella henselae is a Gram-negative bacterium causing a variety of clinical symptoms, ranging from cat-scratch disease to severe systemic infections, and it is primarily transmitted by infected fleas. Its status as an emerging zoonotic pathogen and its capacity to persist within host erythrocytes and endothelial cells emphasize its clinical significance. Despite progress in understanding its pathogenesis, limited knowledge exists about the virulence factors and regulatory mechanisms specific to the B. henselae strain Houston-1. Exploring these aspects is crucial for targeted therapeutic strategies against this versatile pathogen. Using reverse-vaccinology-based subtractive proteomics, this research aimed to identify the most antigenic proteins for formulating a multi-epitope vaccine against the B. henselae strain Houston-1. One crucial virulent and antigenic protein, the PAS domain-containing sensor histidine kinase protein, was identified. Subsequently, the identification of B-cell and T-cell epitopes for the specified protein was carried out and the evaluated epitopes were checked for their antigenicity, allergenicity, solubility, MHC binding capability, and toxicity. The filtered epitopes were merged using linkers and an adjuvant to create a multi-epitope vaccine construct. The structure was then refined, with 92.3% of amino acids falling within the allowed regions. Docking of the human receptor (TLR4) with the vaccine construct was performed and demonstrated a binding energy of -1047.2 Kcal/mol with more interactions. Molecular dynamic simulations confirmed the stability of this docked complex, emphasizing the conformation and interactions between the molecules. Further experimental validation is necessary to evaluate its effectiveness against B. henselae.

GeneMAP: A discovery platform for metabolic gene function

Organisms maintain metabolic homeostasis through the combined functions of small molecule transporters and enzymes. While many of the metabolic components have been well-established, a substantial number remains without identified physiological substrates. To bridge this gap, we have leveraged large-scale plasma metabolome genome-wide association studies (GWAS) to develop a multiomic Gene-Metabolite Associations Prediction (GeneMAP) discovery platform. GeneMAP can generate accurate predictions, even pinpointing genes that are distant from the variants implicated by GWAS. In particular, our work identified SLC25A48 as a genetic determinant of plasma choline levels. Mechanistically, SLC25A48 loss strongly impairs mitochondrial choline import and synthesis of its downstream metabolite, betaine. Rare variant testing and polygenic risk score analyses have elucidated choline-relevant phenomic consequences of SLC25A48 dysfunction. Altogether, our study proposes SLC25A48 as a mitochondrial choline transporter and provides a discovery platform for metabolic gene function.

Biotechnological and Biocontrol Approaches for Mitigating Postharvest Diseases Caused by Fungal Pathogens and Their Mycotoxins in Fruits: A Review

Postharvest diseases caused by fungal pathogens are significant contributors to the postharvest losses of fruits. Moreover, some fungal pathogens produce mycotoxins, which further compromise the safety and quality of fruits. In this review, the potential of biotechnological and biocontrol approaches for mitigating postharvest diseases and mycotoxins in fruits is explored. The review begins by discussing the impact of postharvest diseases on fruit quality and postharvest losses. Next, it provides an overview of major postharvest diseases caused by fungal pathogens. Subsequently, it delves into the role of biotechnological approaches in controlling these diseases. The review also explored the application of biocontrol agents, such as antagonistic yeasts, bacteria, and fungi, which can suppress pathogen growth. Furthermore, future trends and challenges in these two approaches are discussed in detail. Overall, this review can provide insights into promising biotechnological and biocontrol strategies for managing postharvest diseases and mycotoxins in fruits.

Amyloids of α-Synuclein Promote Chemical Transformations of Neuronal Cell Metabolites

The assembly of α-synuclein into cross-β structured amyloid fibers results in Lewy body deposits and neuronal degeneration in Parkinson's disease patients. As the cell environment is highly crowded, interactions between the formed amyloid fibers and a range of biomolecules can occur in cells. Although amyloid fibers are considered chemically inert species, recent in vitro work using model substrates has shown α-synuclein amyloids, but not monomers, to catalyze the hydrolysis of ester and phosphoester bonds. To search for putative catalytic activity of α-synuclein amyloids on biologically relevant metabolites, we here incubated α-synuclein amyloids with neuronal SH-SY5Y cell lysates devoid of proteins. LC-MS-based metabolomic (principal component and univariate) analysis unraveled distinct changes in several metabolite levels upon amyloid (but not monomer) incubation. Of 63 metabolites identified, the amounts of four increased (3-hydroxycapric acid, 2-pyrocatechuic acid, adenosine, and NAD), and the amounts of seventeen decreased (including aromatic and apolar amino acids, metabolites in the TCA cycle, keto acids) in the presence of α-synuclein amyloids. Many of these metabolite changes match what has been reported previously in Parkinson's disease patients and animal-model metabolomics studies. Chemical reactivity of α-synuclein amyloids may be a new gain-of-function that alters the metabolite composition in cells and, thereby, modulates disease progression.

Stable isotope-assisted metabolite profiling reveals new insights into L-tryptophan chemotrophic metabolism of Rubrivivax benzoatilyticus

Anoxygenic photosynthetic bacteria (APB) are metabolically versatile, capable of surviving with an extended range of carbon and nitrogen sources. This group of phototrophic bacteria have remarkable metabolic plasticity in utilizing an array of organic compounds as carbon source/electron donors and nitrogen sources with sophisticated growth modes. Rubrivivax benzoatilyticus JA2 is one such photosynthetic bacterium utilizes L-tryptophan as nitrogen source under phototrophic growth mode and produces an array of indolic compounds of biotechnological significance. However, chemotrophic L-tryptophan metabolism is largely unexplored and studying L-tryptophan metabolism under chemotrophic mode would provide new insights into metabolic potential of strain JA2. In the present study, we employed stable-isotopes assisted metabolite profiling to unravel the L-tryptophan catabolism in Rubrivivax benzoatilyticus strain JA2 under chemotrophic (dark aerobic) conditions. Utilization of L-tryptophan as a nitrogen source for growth and simultaneous production of indole derivatives was observed in strain JA2. Liquid chromatography mass spectrometry (LC-MS) analysis of exo-metabolite profiling of carbon labeled L-tryptophan (¹³C₁₁) fed cultures of strain JA2 revealed at least seventy labeled metabolites. Of these, only fourteen metabolites were confirmed using standards, while sixteen were putative and forty metabolites remained unidentified. L-tryptophan chemotrophic catabolism revealed multiple catabolic pathways and distinct differential catabolism of L-tryptophan under chemotropic state as compared to photo-catabolism of L-tryptophan in strain JA2.

Ex vivo metabolomics-A hypothesis-free approach to identify native substrate(s) and product(s) of orphan enzymes

Over the past decade, the number of fully sequenced genomes has increased at an awe-inspiring pace. Similarly, the quality and scope of tools for the prediction of both protein structure and function has seen vast improvements. However, to pinpoint the exact function of a protein, for instance the exact reaction catalyzed by an enzyme, experimental evidence is crucial. At the same time, this step is the main bottleneck when generating a conclusive model for the function of an enzyme and to interpret its function in a physiological context. Hence, a comprehensive experimental strategy for functional annotation of enzymes that is as efficient as possible is required. Ex vivo metabolomics is a powerful non-targeted approach that overcomes several of the challenges inherent to in vitro characterization of enzymes with unknown functions. By incubating the recombinant enzyme of interest in a quasi-native metabolite extract from its tissue of origin under specific environmental and developmental conditions, the complete native substrate range can be tested in a single assay. This unlocks compounds that are commercially unavailable or otherwise difficult to procure. Coupled with non-targeted metabolomics analysis, ex vivo has the capability to test for and identify even unexpected substrates and assign the respective products of the enzymatic reaction.

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.

The Aging Process: A Metabolomics Perspective

Aging process is characterized by a progressive decline of several organic, physiological, and metabolic functions whose precise mechanism remains unclear. Metabolomics allows the identification of several metabolites and may contribute to clarifying the aging-regulated metabolic pathways. We aimed to investigate aging-related serum metabolic changes using a metabolomics approach. Fasting blood serum samples from 138 apparently healthy individuals (20−70 years old, 56% men) were analyzed by Proton Nuclear Magnetic Resonance spectroscopy (1H NMR) and Liquid Chromatography-High-Resolution Mass Spectrometry (LC-HRMS), and for clinical markers. Associations of the metabolic profile with age were explored via Correlations (r); Metabolite Set Enrichment Analysis; Multiple Linear Regression; and Aging Metabolism Breakpoint. The age increase was positively correlated (0.212 ≤ r ≤ 0.370, p < 0.05) with the clinical markers (total cholesterol, HDL, LDL, VLDL, triacylglyceride, and glucose levels); negatively correlated (−0.285 ≤ r ≤ −0.214, p < 0.05) with tryptophan, 3-hydroxyisobutyrate, asparagine, isoleucine, leucine, and valine levels, but positively (0.237 ≤ r ≤ 0.269, p < 0.05) with aspartate and ornithine levels. These metabolites resulted in three enriched pathways: valine, leucine, and isoleucine degradation, urea cycle, and ammonia recycling. Additionally, serum metabolic levels of 3-hydroxyisobutyrate, isoleucine, aspartate, and ornithine explained 27.3% of the age variation, with the aging metabolism breakpoint occurring after the third decade of life. These results indicate that the aging process is potentially associated with reduced serum branched-chain amino acid levels (especially after the third decade of life) and progressively increased levels of serum metabolites indicative of the urea cycle.

Integrated miRNA, target mRNA, and metabolome profiling of Tinospora cordifolia with reference to berberine biosynthesis

MicroRNAs play a central role in gene regulation and emerge as novel targets for secondary metabolites improvement in plants. The crops thus can be improved through knowledge obtained by the study of miRNAs because of their conserved nature in gene regulation. The present study has been carried out on Tinospora cordifolia (T. cordifolia), because of its illimitable application for the treatment of various diseases. This plant has tremendous medicinal properties, yet unexplored at the molecular level, and has not received much recognition in the scientific field. Thus, here computational analysis was performed to identify T. cordifolia miRNAs using EST database. Using these miRNAs, we predicted their targets which were found to be associated with the regulation of diverse gene networks including 433 berberine biosynthesis genes in T. cordifolia. Further, selected miRNAs were validated and their expression was detected in different T. cordifolia tissues followed by expression analysis of their target mRNAs. These data were then compared with the metabolic profile of T. cordifolia with an emphasis on therapeutically important compound berberine. In this study, we did simultaneous miRNA/target gene expression and metabolome analysis which opens a new way for initiating new proposition and prioritization of miRNAs/genes/metabolites for targeted follow‑up metabolic engineering experimentations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03342-9.

Activity-based annotation: the emergence of systems biochemistry

Current tools to annotate protein function have failed to keep pace with the speed of DNA sequencing and exponentially growing number of proteins of unknown function (PUFs). A major contributing factor to this mismatch is the historical lack of high-throughput methods to experimentally determine biochemical activity. Activity-based methods, such as activity-based metabolite and protein profiling, are emerging as new approaches for unbiased, global, biochemical annotation of protein function. In this review, we highlight recent experimental, activity-based approaches that offer new opportunities to determine protein function in a biologically agnostic and systems-level manner.

Image to insight: exploring natural products through mass spectrometry imaging

Covering: 2017 to 2022Mass spectrometry imaging (MSI) has become a mature molecular imaging technique that is well-matched for natural product (NP) discovery. Here we present a brief overview of MSI, followed by a thorough discussion of different MSI applications in NP research. This review will mainly focus on the recent progress of MSI in plants and microorganisms as they are the main producers of NPs. Specifically, the opportunity and potential of combining MSI with other imaging modalities and stable isotope labeling are discussed. Throughout, we focus on both the strengths and weaknesses of MSI, with an eye on future improvements that are necessary for the progression of MSI toward routine NP studies. Finally, we discuss new areas of research, future perspectives, and the overall direction that the field may take in the years to come.

Bioprospecting of microbial enzymes: current trends in industry and healthcare

Microbial enzymes have an indispensable role in producing foods, pharmaceuticals, and other commercial goods. Many novel enzymes have been reported from all domains of life, such as plants, microbes, and animals. Nonetheless, industrially desirable enzymes of microbial origin are limited. This review article discusses the classifications, applications, sources, and challenges of most demanded industrial enzymes such as pectinases, cellulase, lipase, and protease. In addition, the production of novel enzymes through protein engineering technologies such as directed evolution, rational, and de novo design, for the improvement of existing industrial enzymes is also explored. We have also explored the role of metagenomics, nanotechnology, OMICs, and machine learning approaches in the bioprospecting of novel enzymes. Overall, this review covers the basics of biocatalysts in industrial and healthcare applications and provides an overview of existing microbial enzyme optimization tools. KEY POINTS: • Microbial bioactive molecules are vital for therapeutic and industrial applications. • High-throughput OMIC is the most proficient approach for novel enzyme discovery. • Comprehensive databases and efficient machine learning models are the need of the hour to fast forward de novo enzyme design and discovery.

Recent advances in metabolomics analysis for early drug development

The pharmaceutical industry adapted proteomics and other 'omics technologies for drug research early following their initial introduction. Although metabolomics lacked behind in this development, it has now become an accepted and widely applied approach in early drug development. Over the past few decades, metabolomics has evolved from a pure exploratory tool to a more mature and quantitative biochemical technology. Several metabolomics-based platforms are now applied during the early phases of drug discovery. Metabolomics analysis assists in the definition of the physiological response and target engagement (TE) markers as well as elucidation of the mode of action (MoA) of drug candidates under investigation. In this review, we highlight recent examples and novel developments of metabolomics analyses applied during early drug development.

Discovery of Two Novel Oxidases Using a High-Throughput Activity Screen

Discovery of novel enzymes is a challenging task, yet a crucial one, due to their increasing relevance as chemical catalysts and biotechnological tools. In our work we present a high-throughput screening approach to discovering novel activities. A screen of 96 putative oxidases with 23 substrates led to the discovery of two new enzymes. The first enzyme, N-acetyl-D-hexosamine oxidase (EC 1.1.3.29) from Ralstonia solanacearum, is a vanillyl alcohol oxidase-like flavoprotein displaying the highest activity with N-acetylglucosamine and N-acetylgalactosamine. Before our discovery of the enzyme, its activity was an orphan one - experimentally characterized but lacking the link to amino acid sequence. The second enzyme, from an uncultured marine euryarchaeota, is a long-chain alcohol oxidase (LCAO, EC 1.1.3.20) active with a range of fatty alcohols, with 1-dodecanol being the preferred substrate. The enzyme displays no sequence similarity to previously characterised LCAOs, and thus is a completely novel representative of a protein with such activity.

Metabolomics and genomics in natural products research: complementary tools for targeting new chemical entities

Covering: 2010 to 2021Organisms in nature have evolved into proficient synthetic chemists, utilizing specialized enzymatic machinery to biosynthesize an inspiring diversity of secondary metabolites. Often serving to boost competitive advantage for their producers, these secondary metabolites have widespread human impacts as antibiotics, anti-inflammatories, and antifungal drugs. The natural products discovery field has begun a shift away from traditional activity-guided approaches and is beginning to take advantage of increasingly available metabolomics and genomics datasets to explore undiscovered chemical space. Major strides have been made and now enable -omics-informed prioritization of chemical structures for discovery, including the prospect of confidently linking metabolites to their biosynthetic pathways. Over the last decade, more integrated strategies now provide researchers with pipelines for simultaneous identification of expressed secondary metabolites and their biosynthetic machinery. However, continuous collaboration by the natural products community will be required to optimize strategies for effective evaluation of natural product biosynthetic gene clusters to accelerate discovery efforts. Here, we provide an evaluative guide to scientific literature as it relates to studying natural product biosynthesis using genomics, metabolomics, and their integrated datasets. Particular emphasis is placed on the unique insights that can be gained from large-scale integrated strategies, and we provide source organism-specific considerations to evaluate the gaps in our current knowledge.

Unravelling the Anticancer Mechanisms of Traditional Herbal Medicines with Metabolomics

Metabolite profiling of cancer cells presents many opportunities for anticancer drug discovery. The Chinese, Indian, and African flora, in particular, offers a diverse source of anticancer therapeutics as documented in traditional folklores. In-depth scientific information relating to mechanisms of action, quality control, and safety profile will promote their extensive usage in cancer therapy. Metabolomics may be a more holistic strategy to gain valuable insights into the anticancer mechanisms of action of plants but this has remained largely unexplored. This review, therefore, presents the available metabolomics studies on the anticancer effects of herbal medicines commonly used in Africa and Asia. In addition, we present some scientifically understudied ‘candidate plants’ for cancer metabolomics studies and highlight the relevance of metabolomics in addressing other challenges facing the drug development of anticancer herbs. Finally, we discussed the challenges of using metabolomics to uncover the underlying mechanisms of potential anticancer herbs and the progress made in this regard.

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.

Understanding the Relationship between Intrinsic Cardiorespiratory Fitness and Serum and Skeletal Muscle Metabolomics Profile

Intrinsic cardiorespiratory fitness (iCRF) indicates the CRF level in the sedentary state. However, even among sedentary individuals, a wide interindividual variability is observed in the iCRF levels, whose associated molecular characteristics are little understood. This study aimed to investigate whether serum and skeletal muscle metabolomics profiles are associated with iCRF, measured by maximal power output (MPO). Seventy sedentary young adults were submitted to venous blood sampling, a biopsy of the vastus lateralis muscle and iCRF assessment. Blood serum and muscle tissue samples were analyzed by proton nuclear magnetic resonance (¹H NMR) spectroscopy. Metabolites related to iCRF were those supported by three levels of evidence: (1) correlation with iCRF, (2) significant difference between individuals with low and high iCRF, and (3) metabolite contribution to significant pathways associated with iCRF. From 43 serum and 70 skeletal muscle analyzed metabolites, iCRF was positively associated with levels of betaine, threonine, proline, ornithine, and glutamine in serum and lactate, fumarate, NADP+, and formate in skeletal muscle. Serum betaine and ornithine and skeletal muscle lactate metabolites explained 31.2 and 16.8%, respectively, of the iCRF variability in addition to body mass. The results suggest that iCRF in young adults is positively associated with serum and skeletal muscle metabolic levels, indicative of the amino acid and carbohydrate metabolism.

Identification of inhibitors of pinellic acid generation in whole wheat bread

Bitterness is a common aversive flavor attribute of foods associated with low consumer acceptance. Untargeted LC-MS flavoromic profiling was utilized to identify endogenous compounds that influence the generation of the bitter compound 9,12,13-trihydroxy-trans-10-octadecenoic acid (pinellic acid) during bread making. A diverse sample set of wheat germplasm was chemically profiled. The corresponding pinellic acid concentrations after dough formation were modeled by orthogonal partial least squares (OPLS) with good fit (R²Y = 0.8) and predictive ability (Q² = 0.6). The most predictive feature (negatively correlated), postulated to interfere with the biosynthetic pathway, was identified as schaftoside, an apigenin di-C-glycoside. Recombination experiments involving the addition of schaftoside to flour prior to breadmaking resulted in a 26% decrease in pinellic acid formation and significantly lower perceived bitterness intensity in whole wheat bread. This work provides novel understanding of bitter generation pathways in wheat products and new strategies to improve flavor profiles and consumer acceptability.

Comparative analysis of the chemical and biochemical synthesis of keto acids

Keto acids are essential organic acids that are widely applied in pharmaceuticals, cosmetics, food, beverages, and feed additives as well as chemical synthesis. Currently, most keto acids on the market are prepared via chemical synthesis. The biochemical synthesis of keto acids has been discovered with the development of metabolic engineering and applied toward the production of specific keto acids from renewable carbohydrates using different metabolic engineering strategies in microbes. In this review, we provide a systematic summary of the types and applications of keto acids, and then summarize and compare the chemical and biochemical synthesis routes used for the production of typical keto acids, including pyruvic acid, oxaloacetic acid, α-oxobutanoic acid, acetoacetic acid, ketoglutaric acid, levulinic acid, 5-aminolevulinic acid, α-ketoisovaleric acid, α-keto-γ-methylthiobutyric acid, α-ketoisocaproic acid, 2-keto-L-gulonic acid, 2-keto-D-gluconic acid, 5-keto-D-gluconic acid, and phenylpyruvic acid. We also describe the current challenges for the industrial-scale production of keto acids and further strategies used to accelerate the green production of keto acids via biochemical routes.

Advances and perspectives in the metabolomics of stomatal movement and the disease triangle

Crops are continuously exposed to microbial pathogens that cause tremendous yield losses worldwide. Stomatal pores formed by pairs of specialized guard cells in the leaf epidermis represent a major route of pathogen entry. Guard cells have an essential role as a first line of defense against pathogens. Metabolomics is an indispensable systems biology tool that has facilitated discovery and functional studies of metabolites that regulate stomatal movement in response to pathogens and other environmental factors. Guard cells, pathogens and environmental factors constitute the "stomatal disease triangle". The aim of this review is to highlight recent advances toward understanding the stomatal disease triangle in the context of newly discovered signaling molecules, hormone crosstalk, and consequent molecular changes that integrate pathogens and environmental sensing into stomatal immune responses. Future perspectives on emerging single-cell studies, multiomics and molecular imaging in the context of stomatal defense are discussed. Advances in this important area of plant biology will inform rational crop engineering and breeding for enhanced stomatal defense without disruption of other pathways that impact crop yield.

Seeing the forest for the trees: Retrieving plant secondary biochemical pathways from metabolome networks

Over the last decade, a giant leap forward has been made in resolving the main bottleneck in metabolomics, i.e., the structural characterization of the many unknowns. This has led to the next challenge in this research field: retrieving biochemical pathway information from the various types of networks that can be constructed from metabolome data. Searching putative biochemical pathways, referred to as biotransformation paths, is complicated because several flaws occur during the construction of metabolome networks. Multiple network analysis tools have been developed to deal with these flaws, while in silico retrosynthesis is appearing as an alternative approach. In this review, the different types of metabolome networks, their flaws, and the various tools to trace these biotransformation paths are discussed.

Regulation of Carbon Metabolism by Environmental Conditions: A Perspective From Diatoms and Other Chromalveolates

Diatoms belong to a major, diverse and species-rich eukaryotic clade, the Heterokonta, within the polyphyletic chromalveolates. They evolved as a result of secondary endosymbiosis with one or more Plantae ancestors, but their precise evolutionary history is enigmatic. Nevertheless, this has conferred them with unique structural and biochemical properties that have allowed them to flourish in a wide range of different environments and cope with highly variable conditions. We review the effect of pH, light and dark, and CO2 concentration on the regulation of carbon uptake and assimilation. We discuss the regulation of the Calvin-Benson-Bassham cycle, glycolysis, lipid synthesis, and carbohydrate synthesis at the level of gene transcripts (transcriptomics), proteins (proteomics) and enzyme activity. In contrast to Viridiplantae where redox regulation of metabolic enzymes is important, it appears to be less common in diatoms, based on the current evidence, but regulation at the transcriptional level seems to be widespread. The role of post-translational modifications such as phosphorylation, glutathionylation, etc., and of protein-protein interactions, has been overlooked and should be investigated further. Diatoms and other chromalveolates are understudied compared to the Viridiplantae, especially given their ecological importance, but we believe that the ever-growing number of sequenced genomes combined with proteomics, metabolomics, enzyme measurements, and the application of novel techniques will provide a better understanding of how this important group of algae maintain their productivity under changing conditions.

FAMIN Is a Multifunctional Purine Enzyme Enabling the Purine Nucleotide Cycle

Mutations in FAMIN cause arthritis and inflammatory bowel disease in early childhood, and a common genetic variant increases the risk for Crohn's disease and leprosy. We developed an unbiased liquid chromatography-mass spectrometry screen for enzymatic activity of this orphan protein. We report that FAMIN phosphorolytically cleaves adenosine into adenine and ribose-1-phosphate. Such activity was considered absent from eukaryotic metabolism. FAMIN and its prokaryotic orthologs additionally have adenosine deaminase, purine nucleoside phosphorylase, and S-methyl-5′-thioadenosine phosphorylase activity, hence, combine activities of the namesake enzymes of central purine metabolism. FAMIN enables in macrophages a purine nucleotide cycle (PNC) between adenosine and inosine monophosphate and adenylosuccinate, which consumes aspartate and releases fumarate in a manner involving fatty acid oxidation and ATP-citrate lyase activity. This macrophage PNC synchronizes mitochondrial activity with glycolysis by balancing electron transfer to mitochondria, thereby supporting glycolytic activity and promoting oxidative phosphorylation and mitochondrial H⁺ and phosphate recycling.

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An unbiased LC-MS screen reveals FAMIN as a purine nucleoside enzyme

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FAMIN combines adenosine phosphorylase with ADA-, PNP-, and MTAP-like activities

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FAMIN enables a purine nucleotide cycle (PNC) preventing cytoplasmic acidification

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The FAMIN-dependent PNC balances the glycolysis-mitochondrial redox interface

Chemical Discovery in the Era of Metabolomics

Untargeted metabolomics aims to quantify the complete set of metabolites within a biological system, most commonly by liquid chromatography/mass spectrometry (LC/MS). Since nearly the inception of the field, compound identification has been widely recognized as the rate-limiting step of the experimental workflow. In spite of exponential increases in the size of metabolomic databases, which now contain experimental MS/MS spectra for over a half a million reference compounds, chemical structures still cannot be confidently assigned to many signals in a typical LC/MS dataset. The purpose of this Perspective is to consider why identification rates continue to be low in untargeted metabolomics. One rationalization is that many naturally occurring metabolites detected by LC/MS are true "novel" compounds that have yet to be incorporated into metabolomic databases. An alternative possibility, however, is that research data do not provide database matches because of informatic artifacts, chemical contaminants, and signal redundancies. Increasing evidence suggests that, for at least some sample types, many unidentifiable signals in untargeted metabolomics result from the latter rather than new compounds originating from the specimen being measured. The implications of these observations on chemical discovery in untargeted metabolomics are discussed.

Function is what counts: how microbial community complexity affects species, proteome and pathway coverage in metaproteomics

Introduction: Metaproteomics is an established method to obtain a comprehensive taxonomic and functional view of microbial communities. After more than a decade, we are now able to describe the promise, reality, and perspectives of metaproteomics and provide useful information about the choice of method, applications, and potential improvement strategies.Areas covered: In this article, we will discuss current challenges of species and proteome coverage, and also highlight functional aspects of metaproteomics analysis of microbial communities with different levels of complexity. To do this, we re-analyzed data from microbial communities with low to high complexity (8, 72, 200 and >300 species). High species diversity leads to a reduced number of protein group identifications in a complex community, and thus the number of species resolved is underestimated. Ultimately, low abundance species remain undiscovered in complex communities. However, we observed that the main functional categories were better represented within complex microbiomes when compared to species coverage.Expert opinion: Our findings showed that even with low species coverage, metaproteomics has the potential to reveal habitat-specific functional features. Finally, we exploit this information to highlight future research avenues that are urgently needed to enhance our understanding of taxonomic composition and functions of complex microbiomes.

Exposure to recurrent hypoglycemia alters hippocampal metabolism in treated streptozotocin-induced diabetic rats

AIMS

Exposure to recurrent hypoglycemia (RH) is common in diabetic patients receiving glucose-lowering therapies and is implicated in causing cognitive impairments. Despite the significant effect of RH on hippocampal function, the underlying mechanisms are currently unknown. Our goal was to determine the effect of RH exposure on hippocampal metabolism in treated streptozotocin-diabetic rats.

METHODS

Hyperglycemia was corrected by insulin pellet implantation. Insulin-treated diabetic (ITD) rats were exposed to mild/moderate RH once a day for 5 consecutive days.

RESULTS

The effect of RH on hippocampal metabolism revealed 65 significantly altered metabolites in the RH group compared with controls. Several significant differences in metabolite levels belonging to major pathways (eg, Krebs cycle, gluconeogenesis, and amino acid metabolism) were discovered in RH-exposed ITD rats when compared to a control group. Key glycolytic enzymes including hexokinase, phosphofructokinase, and pyruvate kinase were affected by RH exposure.

CONCLUSION

Our results demonstrate that the exposure to RH leads to metabolomics alterations in the hippocampus of insulin-treated streptozotocin-diabetic rats. Understanding how RH affects hippocampal metabolism may help attenuate the adverse effects of RH on hippocampal functions.

Carboxylic Ester Hydrolases in Bacteria: Active Site, Structure, Function and Application

Carboxylic ester hydrolases (CEHs), which catalyze the hydrolysis of carboxylic esters to produce alcohol and acid, are identified in three domains of life. In the Protein Data Bank (PDB), 136 crystal structures of bacterial CEHs (424 PDB codes) from 52 genera and metagenome have been reported. In this review, we categorize these structures based on catalytic machinery, structure and substrate specificity to provide a comprehensive understanding of the bacterial CEHs. CEHs use Ser, Asp or water as a nucleophile to drive diverse catalytic machinery. The α/β/α sandwich architecture is most frequently found in CEHs, but 3-solenoid, β-barrel, up-down bundle, α/β/β/α 4-layer sandwich, 6 or 7 propeller and α/β barrel architectures are also found in these CEHs. Most are substrate-specific to various esters with types of head group and lengths of the acyl chain, but some CEHs exhibit peptidase or lactamase activities. CEHs are widely used in industrial applications, and are the objects of research in structure- or mutation-based protein engineering. Structural studies of CEHs are still necessary for understanding their biological roles, identifying their structure-based functions and structure-based engineering and their potential industrial applications.

The Molecular Basis of Human Anophthalmia and Microphthalmia

Human eye development is coordinated through an extensive network of genetic signalling pathways. Disruption of key regulatory genes in the early stages of eye development can result in aborted eye formation, resulting in an absent eye (anophthalmia) or a small underdeveloped eye (microphthalmia) phenotype. Anophthalmia and microphthalmia (AM) are part of the same clinical spectrum and have high genetic heterogeneity, with >90 identified associated genes. By understanding the roles of these genes in development, including their temporal expression, the phenotypic variation associated with AM can be better understood, improving diagnosis and management. This review describes the genetic and structural basis of eye development, focusing on the function of key genes known to be associated with AM. In addition, we highlight some promising avenues of research involving multiomic approaches and disease modelling with induced pluripotent stem cell (iPSC) technology, which will aid in developing novel therapies.

Precursor-feeding and altered-growth conditions reveal novel blue pigment production by Rubrivivax benzoatilyticus JA2

OBJECTIVE

To explore the secondary metabolite biosynthetic potential of Rubrivivax benzoatilyticus JA2 using a new metabolite mining strategy.

RESULTS

Combination of precursor-feeding and altered growth conditions were used to mine new biomolecules. Strain JA2 utilised L-phenylalanine as sole source of nitrogen and showed pigments production only under phenylalanine-amended aerobic cultures. Stable isotope based precursor feeding studies indicated the blue pigment consists of 4-phenyl rings derived from L-phenylalanine. The purified blue pigment displayed characteristic visible-absorption and pH-dependent color variations. Precursor-feeding under altered growth conditions activated the plausible novel aromatic pigment production in strain JA2.

CONCLUSION

Our approach unraveled the previously unknown pigment synthesis in strain JA2 and demonstrated the potential of mining strategy in discovering the hidden secondary metabolite repertoire in microorganisms.

"Salmonella, meet mycobacteria."

In this issue of JEM, Reinink et al. (https://doi.org/10.1084/jem.20181812) use comparative lipidomics to identify a new family of trehalose-containing cell wall lipids that are enriched in virulent Salmonella serovars. These lipids are structurally related to the important mycobacterial immunogen cord factor.

Synthetic Biology Tools to Engineer Microbial Communities for Biotechnology

Microbial consortia have been used in biotechnology processes, including fermentation, waste treatment, and agriculture, for millennia. Today, synthetic biologists are increasingly engineering microbial consortia for diverse applications, including the bioproduction of medicines, biofuels, and biomaterials from inexpensive carbon sources. An improved understanding of natural microbial ecosystems, and the development of new tools to construct synthetic consortia and program their behaviors, will vastly expand the functions that can be performed by communities of interacting microorganisms. Here, we review recent advancements in synthetic biology tools and approaches to engineer synthetic microbial consortia, discuss ongoing and emerging efforts to apply consortia for various biotechnological applications, and suggest future applications.

Interrogating metabolism as an electron flow system

Metabolism is generally considered as a neatly organised system of modular pathways, shaped by evolution under selection for optimal cellular growth. This view falls short of explaining and predicting a number of key observations about the structure and dynamics of metabolism. We highlight these limitations of a pathway-centric view on metabolism and summarise studies suggesting how these could be overcome by viewing metabolism as a thermodynamically and kinetically constrained, dynamical flow system. Such a systems-level, first-principles based view of metabolism can open up new avenues of metabolic engineering and cures for metabolic diseases and allow better insights to a myriad of physiological processes that are ultimately linked to metabolism. Towards further developing this view, we call for a closer interaction among physical and biological disciplines and an increased use of electrochemical and biophysical approaches to interrogate cellular metabolism together with the microenvironment in which it exists.

Fathoming Aspergillus oryzae metabolomes in formulated growth matrices

The stochasticity of Aspergillus oryzae (Trivially: the koji mold) pan-metabolomes commensurate with its ubiquitously distributed landscapes, i.e. growth matrices have been seemed uncharted since its food fermentative systems are mostly being investigated. In this review, we explicitly have discussed the likely tendencies of A. oryzae metabolomes pertaining to its growth milieu formulated with substrate matrices of varying nature, composition, texture, and associated physicochemical parameters. We envisaged typical food matrices, namely, meju, koji, and moromi as the semi-natural cultivation models toward delineating the metabolomic patterns of the koji mold, which synergistically influences the organoleptic and functional properties of the end products. Further, we highlighted how tailored conditions in sub-natural growth matrices, i.e. synthetic cultivation media blends, inducers, and growth surfaces, may influence A. oryzae metabolomes and targeted phenotypes. In general, the sequential or synchronous growth of A. oryzae on formulated matrices results in a number of metabolic tradeoffs with its immediate microenvironment influencing its adaptive and regulatory metabolomes. In broader context, evaluating the metabolic plasticity of A. oryzae relative to the tractable variables in formulated growth matrices might help approximate its growth and metabolism in the more complex natural matrices and environs. These approaches may considerably help in the design and manipulation of hybrid cultivation systems towards the efficient harnessing of commercial molds.

A Toolbox for Diverse Oxyfunctionalisation of Monoterpenes

The successful implementation of synthetic biology for chemicals biosynthesis relies on the availability of large libraries of well-characterized enzymatic building blocks. Here we present a scalable pipeline that applies the methodology of synthetic biology itself to bootstrap the creation of such a library. By designing and building a cytochrome P450 enzyme collection and testing it in a custom-made untargeted GC/MS-metabolomics-based approach, we were able to rapidly create and characterize a comprehensive enzyme library for the controlled oxyfunctionalisation of terpene scaffolds with a wide range of activities and selectivities towards several monoterpenes. This novel resource can now be used to access the extensive chemical diversity of terpenoids by pathway engineering and the assembly of biocatalytic cascades to subsequently produce libraries of oxygenated terpenoids and their derivatives for diverse applications, including drug discovery.

The growing role of precision and personalized medicine for cancer treatment

Cancer is a devastating disease that takes the lives of hundreds of thousands of people every year. Due to disease heterogeneity, standard treatments, such as chemotherapy or radiation, are effective in only a subset of the patient population. Tumors can have different underlying genetic causes and may express different proteins in one patient versus another. This inherent variability of cancer lends itself to the growing field of precision and personalized medicine (PPM). There are many ongoing efforts to acquire PPM data in order to characterize molecular differences between tumors. Some PPM products are already available to link these differences to an effective drug. It is clear that PPM cancer treatments can result in immense patient benefits, and companies and regulatory agencies have begun to recognize this. However, broader changes to the healthcare and insurance systems must be addressed if PPM is to become part of standard cancer care.

Biochemical control systems for small molecule damage in plants

As a system, plant metabolism is far from perfect: small molecules (metabolites, cofactors, coenzymes, and inorganic molecules) are frequently damaged by unwanted enzymatic or spontaneous reactions. Here, we discuss the emerging principles in small molecule damage biology. We propose that plants evolved at least three distinct systems to control small molecule damage: (i) repair, which returns a damaged molecule to its original state; (ii) scavenging, which converts reactive molecules to harmless products; and (iii) steering, in which the possible formation of a damaged molecule is suppressed. We illustrate the concept of small molecule damage control in plants by describing specific examples for each of these three categories. We highlight interesting insights that we expect future research will provide on those systems, and we discuss promising strategies to discover new small molecule damage-control systems in plants.

Global untargeted serum metabolomic analyses nominate metabolic pathways responsive to loss of expression of the orphan metallo β-lactamase, MBLAC1

The C. elegans gene swip-10 encodes an orphan metallo β-lactamase that genetic studies indicate is vital for limiting neuronal excitability and viability. Sequence analysis indicates that the mammalian gene Mblac1 is the likely ortholog of swip-10, with greatest sequence identity localized to the encoded protein's single metallo β-lactamase domain. The substrate for the SWIP-10 protein remains unknown and to date no functional roles have been ascribed to MBLAC1, though we have shown that the protein binds the neuroprotective β-lactam antibiotic, ceftriaxone. To gain insight into the functional role of MBLAC1 in vivo, we used CRISPR/Cas9 methods to disrupt N-terminal coding sequences of the mouse Mblac1 gene, resulting in a complete loss of protein expression in viable, homozygous knockout (KO) animals. Using serum from both WT and KO mice, we performed global, untargeted metabolomic analyses, resolving small molecules via hydrophilic interaction chromatography (HILIC) based ultra-performance liquid chromatography, coupled to mass spectrometry (UPLC-MS/MS). Unsupervised principal component analysis reliably segregated the metabolomes of MBLAC1 KO and WT mice, with 92 features subsequently nominated as significantly different by ANOVA, and for which we made tentative and putative metabolite assignments. Bioinformatic analyses of these molecules nominate validated pathways subserving bile acid biosynthesis and linoleate metabolism, networks known to be responsive to metabolic and oxidative stress. Our findings lead to hypotheses that can guide future targeted studies seeking to identify the substrate for MBLAC1 and how substrate hydrolysis supports the neuroprotective actions of ceftriaxone.