The self-inhibitory nature of metabolic networks and its alleviation through compartmentalization

Cell type-specific control and post-translational regulation of specialized metabolism: opening new avenues for plant metabolic engineering

Although plant metabolic engineering enables the sustainable production of valuable metabolites with many applications, we still lack a good understanding of many multi-layered regulatory networks that govern metabolic pathways at the metabolite, protein, transcriptional and cellular level. As transcriptional regulation is better understood and often reviewed, here we highlight recent advances in the cell type-specific and post-translational regulation of plant specialized metabolism. With the advent of single-cell technologies, we are now able to characterize metabolites and their transcriptional regulators at the cellular level, which can refine our searches for missing biosynthetic enzymes and cell type-specific regulators. Post-translational regulation through enzyme inhibition, protein phosphorylation and ubiquitination are clearly evident in specialized metabolism regulation, but not frequently studied or considered in metabolic engineering efforts. Finally, we contemplate how advances in cell type-specific and post-translational regulation can be applied in metabolic engineering efforts in planta, leading to optimization of plants as metabolite production vehicles.

Dual-Regulation in Peroxisome and Cytoplasm toward Efficient Limonene Biosynthesis with Rhodotorula toruloides

Rhodotorula toruloides is a potential workhorse for production of various value-added chemicals including terpenoids, oleo-chemicals, and enzymes from low-cost feedstocks. However, the limited genetic toolbox is hindering its metabolic engineering. In the present study, four type I and one novel type II peroxisomal targeting signal (PTS1/PTS2) were characterized and employed for limonene production for the first time in R. toruloides. The implant of the biosynthesis pathway into the peroxisome led to 111.5 mg/L limonene in a shake flask culture. The limonene titer was further boosted to 1.05 g/L upon dual-metabolic regulation in the cytoplasm and peroxisome, which included employing the acetoacetyl-CoA synthase NphT7, adding an additional copy of native ATP-dependent citrate lyase, etc. The final yield was 0.053 g/g glucose, which was the highest ever reported. The newly characterized PTSs should contribute to the expansion of genetic toolboxes forR. toruloides. The results demonstrated that R. toruloides could be explored for efficient production of terpenoids.

Homeostatic coordination of cellular phosphate uptake and efflux requires an organelle-based receptor for the inositol pyrophosphate IP8

Phosphate (Pi) serves countless metabolic pathways and is involved in macromolecule synthesis, energy storage, cellular signaling, and bone maintenance. Herein, we describe the coordination of Pi uptake and efflux pathways to maintain mammalian cell Pi homeostasis. We discover that XPR1, the presumed Pi efflux transporter, separately supervises rates of Pi uptake. This direct, regulatory interplay arises from XPR1 being a binding partner for the Pi uptake transporter PiT1, involving a predicted transmembrane helix/extramembrane loop in XPR1, and its hitherto unknown localization in a subset of intracellular LAMP1-positive puncta (named "XLPVs"). A pharmacological mimic of Pi homeostatic challenge is sensed by the inositol pyrophosphate IP8, which functionalizes XPR1 to respond in a temporally hierarchal manner, initially adjusting the rate of Pi efflux, followed subsequently by independent modulation of PiT1 turnover to reset the rate of Pi uptake. These observations generate a unifying model of mammalian cellular Pi homeostasis, expanding opportunities for therapeutic intervention.

DNA-empowered synthetic cells as minimalistic life forms

Cells, the fundamental units of life, orchestrate intricate functions - motility, adaptation, replication, communication, and self-organization within tissues. Originating from spatiotemporally organized structures and machinery, coupled with information processing in signalling networks, cells embody the 'sensor-processor-actuator' paradigm. Can we glean insights from these processes to construct primitive artificial systems with life-like properties? Using de novo design approaches, what can we uncover about the evolutionary path of life? This Review discusses the strides made in crafting synthetic cells, utilizing the powerful toolbox of structural and dynamic DNA nanoscience. We describe how DNA can serve as a versatile tool for engineering entire synthetic cells or subcellular entities, and how DNA enables complex behaviour, including motility and information processing for adaptive and interactive processes. We chart future directions for DNA-empowered synthetic cells, envisioning interactive systems wherein synthetic cells communicate within communities and with living cells.

The Calvin Benson cycle in bacteria: New insights from systems biology

The Calvin Benson cycle in phototrophic and chemolithoautotrophic bacteria has ecological and biotechnological importance, which has motivated study of its regulation. I review recent advances in our understanding of how the Calvin Benson cycle is regulated in bacteria and the technologies used to elucidate regulation and modify it, and highlight differences between and photoautotrophic and chemolithoautotrophic models. Systems biology studies have shown that in oxygenic phototrophic bacteria, Calvin Benson cycle enzymes are extensively regulated at post-transcriptional and post-translational levels, with multiple enzyme activities connected to cellular redox status through thioredoxin. In chemolithoautotrophic bacteria, regulation is primarily at the transcriptional level, with effector metabolites transducing cell status, though new methods should now allow facile, proteome-wide exploration of biochemical regulation in these models. A biotechnological objective is to enhance CO2 fixation in the cycle and partition that carbon to a product of interest. Flux control of CO2 fixation is distributed over multiple enzymes, and attempts to modulate gene Calvin cycle gene expression show a robust homeostatic regulation of growth rate, though the synthesis rates of products can be significantly increased. Therefore, de-regulation of cycle enzymes through protein engineering may be necessary to increase fluxes. Non-canonical Calvin Benson cycles, if implemented with synthetic biology, could have reduced energy demand and enzyme loading, thus increasing the attractiveness of these bacteria for industrial applications.

Prediction and integration of metabolite-protein interactions with genome-scale metabolic models

Metabolites, as small molecules, can act not only as substrates to enzymes, but also as effectors of activity of proteins with different functions, thereby affecting various cellular processes. While several experimental techniques have started to catalogue the metabolite-protein interactions (MPIs) present in different cellular contexts, characterizing the functional relevance of MPIs remains a challenging problem. Computational approaches from the constrained-based modeling framework allow for predicting MPIs and integrating their effects in the in silico analysis of metabolic and physiological phenotypes, like cell growth. Here, we provide a classification of all existing constraint-based approaches that predict and integrate MPIs using genome-scale metabolic networks as input. In addition, we benchmark the performance of the approaches to predict MPIs in a comparative study using different features extracted from the model structure and predicted metabolic phenotypes with the state-of-the-art metabolic networks of Escherichia coli and Saccharomyces cerevisiae. Lastly, we provide an outlook for future, feasible directions to expand the consideration of MPIs in constraint-based modeling approaches with wide biotechnological applications.

The four subunits of rabbit skeletal muscle lactate dehydrogenase do not exert their catalytic action additively

Oligomeric enzymes containing multiple active sites are usually considered to perform their catalytic action at higher rates when compared with their monomeric counterparts. This implies, in turn, that the activity performed by different holoenzyme subunits features additivity. Nevertheless, the extent of this additivity occurring in holoenzymes is far from being adequately understood. To tackle this point, we used tetrameric rabbit lactate dehydrogenase (rbLDH) as a model system to assay the reduction of pyruvate catalysed by this enzyme at the expense of β-NADH under pre-steady-state conditions. In particular, we observed the kinetics of reactions triggered by concentrations of β-NADH equimolar to 1, 2, 3, or all 4 subunits of the rbLDH holoenzyme, in the presence of an excess of pyruvate. Surprisingly, when the concentration of the limiting reactant exceeded that of a single holoenzyme subunit, we observed a sharp slowdown of the enzyme conformational rearrangements associated to the generation and the release of l-lactate. Furthermore, using a model to interpret the complex kinetics observed under the highest concentration of the limiting reactant, we estimated the diversity of the rates describing the action of the different rbLDH subunits.

Metabolic exchanges are ubiquitous in natural microbial communities

Microbial communities drive global biogeochemical cycles and shape the health of plants and animals-including humans. Their structure and function are determined by ecological and environmental interactions that govern the assembly, stability and evolution of microbial communities. A widely held view is that antagonistic interactions such as competition predominate in microbial communities and are ecologically more important than synergistic interactions-for example, mutualism or commensalism. Over the past decade, however, a more nuanced picture has emerged, wherein bacteria, archaea and fungi exist within interactive networks in which they exchange essential and non-essential metabolites. These metabolic interactions profoundly impact not only the physiology, ecology and evolution of the strains involved, but are also central to the functioning of many, if not all, microbiomes. Therefore, we advocate for a balanced view of microbiome ecology that encompasses both synergistic and antagonistic interactions as key forces driving the structure and dynamics within microbial communities.

Mixed and non-competitive enzyme inhibition: underlying mechanisms and mechanistic irrelevance of the formal two-site model

The formal mechanism of linear mixed and non-competitive enzyme inhibition implies the binding of inhibitors to both the active site of the free enzyme in competition with the substrate, and to an allosteric site on the enzyme-substrate complex. However, it is evident from a review of the scientific literature that the two-site mechanism is frequently mistaken as the actual underlying mechanism of mixed inhibition. In this study, we conducted a comprehensive assessment of the mechanistic relevance of this type of inhibition using a statistical approach. By combining a statistical analysis of the inhibition cases documented in the BRENDA database with a theoretical investigation of inhibition models, we conclude that mixed inhibitors exclusively bind to the active site of enzymes. Hence ruling out any implication of allosteric sites and depriving the two-site model of any mechanistic relevance.

Membrane transporters in cell physiology, cancer metabolism and drug response

By controlling the passage of small molecules across lipid bilayers, membrane transporters influence not only the uptake and efflux of nutrients, but also the metabolic state of the cell. With more than 450 members, the Solute Carriers (SLCs) are the largest transporter super-family, clustering into families with different substrate specificities and regulatory properties. Cells of different types are, therefore, able to tailor their transporter expression signatures depending on their metabolic requirements, and the physiological importance of these proteins is illustrated by their mis-regulation in a number of disease states. In cancer, transporter expression is heterogeneous, and the SLC family has been shown to facilitate the accumulation of biomass, influence redox homeostasis, and also mediate metabolic crosstalk with other cell types within the tumour microenvironment. This Review explores the roles of membrane transporters in physiological and malignant settings, and how these roles can affect drug response, through either indirect modulation of sensitivity or the direct transport of small-molecule therapeutic compounds into cells.

Peroxisomal compartmentalization of amino acid biosynthesis reactions imposes an upper limit on compartment size

Cellular metabolism relies on just a few redox cofactors. Selective compartmentalization may prevent competition between metabolic reactions requiring the same cofactor. Is such compartmentalization necessary for optimal cell function? Is there an optimal compartment size? Here we probe these fundamental questions using peroxisomal compartmentalization of the last steps of lysine and histidine biosynthesis in the fission yeast Schizosaccharomyces japonicus. We show that compartmentalization of these NAD+ dependent reactions together with a dedicated NADH/NAD+ recycling enzyme supports optimal growth when an increased demand for anabolic reactions taxes cellular redox balance. In turn, compartmentalization constrains the size of individual organelles, with larger peroxisomes accumulating all the required enzymes but unable to support both biosynthetic reactions at the same time. Our reengineering and physiological experiments indicate that compartmentalized biosynthetic reactions are sensitive to the size of the compartment, likely due to scaling-dependent changes within the system, such as enzyme packing density.

Functional Organization of Glycolytic Metabolon on Mitochondria

Glucose, the primary cellular energy source, is metabolized through glycolysis initiated by the rate-limiting enzyme Hexokinase (HK). In energy-demanding tissues like the brain, HK1 is the dominant isoform, primarily localized on mitochondria, crucial for efficient glycolysis-oxidative phosphorylation coupling and optimal energy generation. This study unveils a unique mechanism regulating HK1 activity, glycolysis, and the dynamics of mitochondrial coupling, mediated by the metabolic sensor enzyme O-GlcNAc transferase (OGT). OGT catalyzes reversible O-GlcNAcylation, a post-translational modification, influenced by glucose flux. Elevated OGT activity induces dynamic O-GlcNAcylation of HK1's regulatory domain, subsequently promoting the assembly of the glycolytic metabolon on the outer mitochondrial membrane. This modification enhances HK1's mitochondrial association, orchestrating glycolytic and mitochondrial ATP production. Mutations in HK1's O-GlcNAcylation site reduce ATP generation, affecting synaptic functions in neurons. The study uncovers a novel pathway that bridges neuronal metabolism and mitochondrial function via OGT and the formation of the glycolytic metabolon, offering new prospects for tackling metabolic and neurological disorders.

Prediction of metabolite-protein interactions based on integration of machine learning and constraint-based modeling

Motivation

Metabolite-protein interactions play an important role in regulating protein functions and metabolism. Yet, predictions of metabolite-protein interactions using genome-scale metabolic networks are lacking. Here, we fill this gap by presenting a computational framework, termed SARTRE, that employs features corresponding to shadow prices determined in the context of flux variability analysis to predict metabolite-protein interactions using supervised machine learning.

Results

By using gold standards for metabolite-protein interactomes and well-curated genome-scale metabolic models of Escherichia coli and Saccharomyces cerevisiae, we found that the implementation of SARTRE with random forest classifiers accurately predicts metabolite-protein interactions, supported by an average area under the receiver operating curve of 0.86 and 0.85, respectively. Ranking of features based on their importance for classification demonstrated the key role of shadow prices in predicting metabolite-protein interactions. The quality of predictions is further supported by the excellent agreement of the organism-specific classifiers on unseen interactions shared between the two model organisms. Further, predictions from SARTRE are highly competitive against those obtained from a recent deep-learning approach relying on a variety of protein and metabolite features. Together, these findings show that features extracted from constraint-based analyses of metabolic networks pave the way for understanding the functional roles of the interactions between proteins and small molecules.

Availability and implementation

https://github.com/fayazsoleymani/SARTRE.

Designing Intracellular Compartments for Efficient Engineered Microbial Cell Factories

With the rapid development of synthetic biology, various kinds of microbial cell factories (MCFs) have been successfully constructed to produce high-value-added compounds. However, the complexity of metabolic regulation and pathway crosstalk always cause issues such as intermediate metabolite accumulation, byproduct generation, and metabolic burden in MCFs, resulting in low efficiencies and low yields of industrial biomanufacturing. Such issues could be solved by spatially rearranging the pathways using intracellular compartments. In this review, design strategies are summarized and discussed based on the types and characteristics of natural and artificial subcellular compartments. This review systematically presents information for the construction of efficient MCFs with intracellular compartments in terms of four aspects of design strategy goals: (1) improving local reactant concentration; (2) intercepting and isolating competing pathways; (3) providing specific reaction substances and environments; and (4) storing and accumulating products.

Protein-metabolite interactomics of carbohydrate metabolism reveal regulation of lactate dehydrogenase

Metabolic networks are interconnected and influence diverse cellular processes. The protein-metabolite interactions that mediate these networks are frequently low affinity and challenging to systematically discover. We developed mass spectrometry integrated with equilibrium dialysis for the discovery of allostery systematically (MIDAS) to identify such interactions. Analysis of 33 enzymes from human carbohydrate metabolism identified 830 protein-metabolite interactions, including known regulators, substrates, and products as well as previously unreported interactions. We functionally validated a subset of interactions, including the isoform-specific inhibition of lactate dehydrogenase by long-chain acyl-coenzyme A. Cell treatment with fatty acids caused a loss of pyruvate-lactate interconversion dependent on lactate dehydrogenase isoform expression. These protein-metabolite interactions may contribute to the dynamic, tissue-specific metabolic flexibility that enables growth and survival in an ever-changing nutrient environment.

Nucleolar Architecture Is Modulated by a Small Molecule, the Inositol Pyrophosphate 5-InsP7

Inositol pyrophosphates (PP-InsPs); are a functionally diverse family of eukaryotic molecules that deploy a highly-specialized array of phosphate groups as a combinatorial cell-signaling code. One reductive strategy to derive a molecular-level understanding of the many actions of PP-InsPs is to individually characterize the proteins that bind them. Here, we describe an alternate approach that seeks a single, collective rationalization for PP-InsP binding to an entire group of proteins, i.e., the multiple nucleolar proteins previously reported to bind 5-InsP₇ (5-diphospho-inositol-1,2,3,4,6-pentakisphosphate). Quantitative confocal imaging of the outer nucleolar granular region revealed its expansion when cellular 5-InsP₇ levels were elevated by either (a) reducing the 5-InsP₇ metabolism by a CRISPR-based knockout (KO) of either NUDT3 or PPIP5Ks; or (b), the heterologous expression of wild-type inositol hexakisphosphate kinase, i.e., IP6K2; separate expression of a kinase-dead IP6K2 mutant did not affect granular volume. Conversely, the nucleolar granular region in PPIP5K KO cells shrank back to the wild-type volume upon attenuating 5-InsP₇ synthesis using either a pan-IP6K inhibitor or the siRNA-induced knockdown of IP6K1+IP6K2. Significantly, the inner fibrillar volume of the nucleolus was unaffected by 5-InsP₇. We posit that 5-InsP₇ acts as an 'electrostatic glue' that binds together positively charged surfaces on separate proteins, overcoming mutual protein-protein electrostatic repulsion the latter phenomenon is a known requirement for the assembly of a non-membranous biomolecular condensate.

Catalysis-Induced Phase Separation and Autoregulation of Enzymatic Activity

We present a thermodynamically consistent model describing the dynamics of a multicomponent mixture where one enzyme component catalyzes a reaction between other components. We find that the catalytic activity alone can induce phase separation for sufficiently active systems and large enzymes, without any equilibrium interactions between components. In the limit of fast reaction rates, binodal lines can be calculated using a mapping to an effective free energy. We also explain how this catalysis-induced phase separation can act to autoregulate the enzymatic activity, which points at the biological relevance of this phenomenon.

Homeostasis of the biosynthetic E. coli metabolome

Metabolite concentrations vary across conditions and such metabolome changes are relevant for metabolic and gene regulation. Here, we used LC-MS/MS to explore metabolite concentration changes in Escherichia coli. We measured 101 primary metabolites in 19 experimental conditions that include various nutrients and stresses. Many metabolites showed little variation across conditions and only few metabolites correlated with the growth rate. The least varying metabolites were nucleotides (e.g. UTP had 10% variation) and amino acids (e.g. methionine had 13% variation). These results show that E. coli maintains protein and RNA building blocks within narrow concentration ranges, thus indicating that many feedback mechanisms in biosynthetic pathways contribute to end-product homeostasis.

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101 E coli metabolites were measured in 19 conditions

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Biosynthetic end-products vary little between conditions

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Few metabolites correlate with the growth rate

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Metabolome data identify active regulatory metabolites

Human cytosolic transaminases: side activities and patterns of discrimination towards physiologically available alternative substrates

Transaminases play key roles in central metabolism, transferring the amino group from a donor substrate to an acceptor. These enzymes can often act, with low efficiency, on compounds different from the preferred substrates. To understand what might have shaped the substrate specificity of this class of enzymes, we examined the reactivity of six human cytosolic transaminases towards amino acids whose main degradative pathways do not include any transamination. We also tested whether sugars and sugar phosphates could serve as alternative amino group acceptors for these cytosolic enzymes. Each of the six aminotransferases reacted appreciably with at least three of the alternative amino acid substrates in vitro, albeit at usually feeble rates. Reactions with L-Thr, L-Arg, L-Lys and L-Asn were consistently very slow-a bias explained in part by the structural differences between these amino acids and the preferred substrates of the transaminases. On the other hand, L-His and L-Trp reacted more efficiently, particularly with GTK (glutamine transaminase K; also known as KYAT1). This points towards a role of GTK in the salvage of L-Trp (in cooperation with ω-amidase and possibly with the cytosolic malate dehydrogenase, MDH1, which efficiently reduced the product of L-Trp transamination). Finally, the transaminases were extremely ineffective at utilizing sugars and sugar derivatives, with the exception of the glycolytic intermediate dihydroxyacetone phosphate, which was slowly but appreciably transaminated by some of the enzymes to yield serinol phosphate. Evidence for the formation of this compound in a human cell line was also obtained. We discuss the biological and evolutionary implications of our results.

Structural, mechanistic and physiological insights into phospholipase A-mediated membrane phospholipid degradation in Pseudomonas aeruginosa

Cells steadily adapt their membrane glycerophospholipid (GPL) composition to changing environmental and developmental conditions. While the regulation of membrane homeostasis via GPL synthesis in bacteria has been studied in detail, the mechanisms underlying the controlled degradation of endogenous GPLs remain unknown. Thus far, the function of intracellular phospholipases A (PLAs) in GPL remodeling (Lands cycle) in bacteria is not clearly established. Here, we identified the first cytoplasmic membrane-bound phospholipase A₁ (PlaF) from Pseudomonas aeruginosa, which might be involved in the Lands cycle. PlaF is an important virulence factor, as the P. aeruginosa ΔplaF mutant showed strongly attenuated virulence in Galleria mellonella and macrophages. We present a 2.0-Å-resolution crystal structure of PlaF, the first structure that reveals homodimerization of a single-pass transmembrane (TM) full-length protein. PlaF dimerization, mediated solely through the intermolecular interactions of TM and juxtamembrane regions, inhibits its activity. The dimerization site and the catalytic sites are linked by an intricate ligand-mediated interaction network, which might explain the product (fatty acid) feedback inhibition observed with the purified PlaF protein. We used molecular dynamics simulations and configurational free energy computations to suggest a model of PlaF activation through a coupled monomerization and tilting of the monomer in the membrane, which constrains the active site cavity into contact with the GPL substrates. Thus, these data show the importance of the PlaF-mediated GPL remodeling pathway for virulence and could pave the way for the development of novel therapeutics targeting PlaF.

1D Colloidal chains: recent progress from formation to emergent properties and applications

Integrating nanoscale building blocks of low dimensionality (0D; i.e., spheres) into higher dimensional structures endows them and their corresponding materials with emergent properties non-existent or only weakly existent in the individual building blocks. Constructing 1D chains, 2D arrays and 3D superlattices using nanoparticles and colloids therefore continues to be one of the grand goals in colloid and nanomaterial science. Amongst these higher order structures, 1D colloidal chains are of particular interest, as they possess unique anisotropic properties. In recent years, the most relevant advances in 1D colloidal chain research have been made in novel synthetic methodologies and applications. In this review, we first address a comprehensive description of the research progress concerning various synthetic strategies developed to construct 1D colloidal chains. Following this, we highlight the amplified and emergent properties of the resulting materials, originating from the assembly of the individual building blocks and their collective behavior, and discuss relevant applications in advanced materials. In the discussion of synthetic strategies, properties, and applications, particular attention will be paid to overarching concepts, fresh trends, and potential areas of future research. We believe that this comprehensive review will be a driver to guide the interdisciplinary field of 1D colloidal chains, where nanomaterial synthesis, self-assembly, physical property studies, and material applications meet, to a higher level, and open up new research opportunities at the interface of classical disciplines.

Kinetic Modeling of Time-Dependent Enzyme Inhibition by Pre-Steady-State Analysis of Progress Curves: The Case Study of the Anti-Alzheimer's Drug Galantamine

The Michaelis–Menten model of enzyme kinetic assumes the free ligand approximation, the steady-state approximation and the rapid equilibrium approximation. Analytical methods to model slow-binding inhibitors by the analysis of initial velocities have been developed but, due to their inherent complexity, they are seldom employed. In order to circumvent the complications that arise from the violation of the rapid equilibrium assumption, inhibition is commonly evaluated by pre-incubating the enzyme and the inhibitors so that, even for slow inhibitors, the binding equilibrium is established before the reaction is started. Here, we show that for long drug-target residence time inhibitors, the conventional analysis of initial velocities by the linear regression of double-reciprocal plots fails to provide a correct description of the inhibition mechanism. As a case study, the inhibition of acetylcholinesterase by galantamine, a drug approved for the symptomatic treatment of Alzheimer’s disease, is reported. For over 50 years, analysis based on the conventional steady-state model has overlooked the time-dependent nature of galantamine inhibition, leading to an erroneous assessment of the drug potency and, hence, to discrepancies between biochemical data and the pharmacological evidence. Re-examination of acetylcholinesterase inhibition by pre-steady state analysis of the reaction progress curves showed that the potency of galantamine has indeed been underestimated by a factor of ~100.

Compartmentalization at the interface of primary and alkaloid metabolism

Plants produce many compounds used by humans as medicines, including alkaloids of the benzylisoquinoline (BIA), monoterpene indole (MIA) and tropane classes. The biosynthetic pathways of these pharmaceutical alkaloids are complex and spatially segregated across several tissues, cell-types and organelles. This review discusses the origin of primary metabolic inputs required by these specialized biosynthetic pathways and considers aspects relevant to their spatial organization. These factors are important for alkaloid production both in the native plants and for synthetic biology pathway reconstruction in microorganisms.

A generalized kinetic model for compartmentalization of organometallic catalysis

Compartmentalization is an attractive approach to enhance catalytic activity by retaining reactive intermediates and mitigating deactivating pathways. Such a concept has been well explored in biochemical and more recently, organometallic catalysis to ensure high reaction turnovers with minimal side reactions. However, the scarcity of theoretical frameworks towards confined organometallic chemistry impedes broader utility for the implementation of compartmentalization. Herein, we report a general kinetic model and offer design guidance for a compartmentalized organometallic catalytic cycle. In comparison to a non-compartmentalized catalysis, compartmentalization is quantitatively shown to prevent the unwanted intermediate deactivation, boost the corresponding reaction efficiency (γ), and subsequently increase catalytic turnover frequency (TOF). The key parameter in the model is the volumetric diffusive conductance (F_V) that describes catalysts' diffusion propensity across a compartment's boundary. Optimal values of F_V for a specific organometallic chemistry are needed to achieve maximal values of γ and TOF. As illustrated in specific reaction examples, our model suggests that a tailored compartment design, including the use of nanomaterials, is needed to suit a specific organometallic catalytic cycle. This work provides justification and design principles for further exploration into compartmentalizing organometallics to enhance catalytic performance. The conclusions from this work are generally applicable to other catalytic systems that need proper design guidance in confinement and compartmentalization.

Compartmentalization is an attractive approach to enhance catalytic activity by retaining reactive intermediates and mitigating deactivating pathways.

Cysteine and iron accelerate the formation of ribose-5-phosphate, providing insights into the evolutionary origins of the metabolic network structure

The structure of the metabolic network is highly conserved, but we know little about its evolutionary origins. Key for explaining the early evolution of metabolism is solving a chicken–egg dilemma, which describes that enzymes are made from the very same molecules they produce. The recent discovery of several nonenzymatic reaction sequences that topologically resemble central metabolism has provided experimental support for a “metabolism first” theory, in which at least part of the extant metabolic network emerged on the basis of nonenzymatic reactions. But how could evolution kick-start on the basis of a metal catalyzed reaction sequence, and how could the structure of nonenzymatic reaction sequences be imprinted on the metabolic network to remain conserved for billions of years? We performed an in vitro screening where we add the simplest components of metabolic enzymes, proteinogenic amino acids, to a nonenzymatic, iron-driven reaction network that resembles glycolysis and the pentose phosphate pathway (PPP). We observe that the presence of the amino acids enhanced several of the nonenzymatic reactions. Particular attention was triggered by a reaction that resembles a rate-limiting step in the oxidative PPP. A prebiotically available, proteinogenic amino acid cysteine accelerated the formation of RNA nucleoside precursor ribose-5-phosphate from 6-phosphogluconate. We report that iron and cysteine interact and have additive effects on the reaction rate so that ribose-5-phosphate forms at high specificity under mild, metabolism typical temperature and environmental conditions. We speculate that accelerating effects of amino acids on rate-limiting nonenzymatic reactions could have facilitated a stepwise enzymatization of nonenzymatic reaction sequences, imprinting their structure on the evolving metabolic network.

The evolutionary origins of metabolism are largely unknown. This study shows that the prebiotically available proteinogenic amino acid cysteine can promote the metabolism-like rate-limiting formation of ribose-5-phosphate, suggesting that early metabolic pathways could have emerged thought the stepwise enzymatization of non-enzymatic reaction sequences.

A Standardized Brain Molecular Atlas: A Resource for Systems Modeling and Simulation

Accurate molecular concentrations are essential for reliable analyses of biochemical networks and the creation of predictive models for molecular and systems biology, yet protein and metabolite concentrations used in such models are often poorly constrained or irreproducible. Challenges of using data from different sources include conflicts in nomenclature and units, as well as discrepancies in experimental procedures, data processing and implementation of the model. To obtain a consistent estimate of protein and metabolite levels, we integrated and normalized data from a large variety of sources to calculate Adjusted Molecular Concentrations. We found a high degree of reproducibility and consistency of many molecular species across brain regions and cell types, consistent with tight homeostatic regulation. We demonstrated the value of this normalization with differential protein expression analyses related to neurodegenerative diseases, brain regions and cell types. We also used the results in proof-of-concept simulations of brain energy metabolism. The standardized Brain Molecular Atlas overcomes the obstacles of missing or inconsistent data to support systems biology research and is provided as a resource for biomolecular modeling.

Recent advancements in enzyme engineering via site-specific incorporation of unnatural amino acids

With increased attention to excellent biocatalysts, evolving methods based on nature or unnatural amino acid (UAAs) mutagenesis have become an important part of enzyme engineering. The emergence of powerful method through expanding the genetic code allows to incorporate UAAs with unique chemical functionalities into proteins, endowing proteins with more structural and functional features. To date, over 200 diverse UAAs have been incorporated site-specifically into proteins via this methodology and many of them have been widely exploited in the field of enzyme engineering, making this genetic code expansion approach possible to be a promising tool for modulating the properties of enzymes. In this context, we focus on how this robust method to specifically incorporate UAAs into proteins and summarize their applications in enzyme engineering for tuning and expanding the functional properties of enzymes. Meanwhile, we aim to discuss how the benefits can be achieved by using the genetically encoded UAAs. We hope that this method will become an integral part of the field of enzyme engineering in the future.

The metabolic growth limitations of petite cells lacking the mitochondrial genome

Eukaryotic cells can survive the loss of their mitochondrial genome, but consequently suffer from severe growth defects. 'Petite yeasts', characterized by mitochondrial genome loss, are instrumental for studying mitochondrial function and physiology. However, the molecular cause of their reduced growth rate remains an open question. Here we show that petite cells suffer from an insufficient capacity to synthesize glutamate, glutamine, leucine and arginine, negatively impacting their growth. Using a combination of molecular genetics and omics approaches, we demonstrate the evolution of fast growth overcomes these amino acid deficiencies, by alleviating a perturbation in mitochondrial iron metabolism and by restoring a defect in the mitochondrial tricarboxylic acid cycle, caused by aconitase inhibition. Our results hence explain the slow growth of mitochondrial genome-deficient cells with a partial auxotrophy in four amino acids that results from distorted iron metabolism and an inhibited tricarboxylic acid cycle.

Adaptive mechanisms of plant specialized metabolism connecting chemistry to function

As sessile organisms, plants evolved elaborate metabolic systems that produce a plethora of specialized metabolites as a means to survive challenging terrestrial environments. Decades of research have revealed the genetic and biochemical basis for a multitude of plant specialized metabolic pathways. Nevertheless, knowledge is still limited concerning the selective advantages provided by individual and collective specialized metabolites to the reproductive success of diverse host plants. Here we review the biological functions conferred by various classes of plant specialized metabolites in the context of the interaction of plants with their surrounding environment. To achieve optimal multifunctionality of diverse specialized metabolic processes, plants use various adaptive mechanisms at subcellular, cellular, tissue, organ and interspecies levels. Understanding these mechanisms and the evolutionary trajectories underlying their occurrence in nature will ultimately enable efficient bioengineering of desirable metabolic traits in chassis organisms.

Enzymatic activation of pyruvate kinase increases cytosolic oxaloacetate to inhibit the Warburg effect

Pharmacological activation of the glycolytic enzyme PKM2 or expression of the constitutively active PKM1 isoform in cancer cells results in decreased lactate production, a phenomenon known as the PKM2 paradox in the Warburg effect. Here we show that oxaloacetate (OAA) is a competitive inhibitor of human lactate dehydrogenase A (LDHA) and that elevated PKM2 activity increases de novo synthesis of OAA through glutaminolysis, thereby inhibiting LDHA in cancer cells. We also show that replacement of human LDHA with rabbit LDHA, which is relatively resistant to OAA inhibition, eliminated the paradoxical correlation between the elevated PKM2 activity and the decreased lactate concentration in cancer cells treated with a PKM2 activator. Furthermore, rabbit LDHA-expressing tumours, compared to human LDHA-expressing tumours in mice, displayed resistance to the PKM2 activator. These findings describe a mechanistic explanation for the PKM2 paradox by showing that OAA accumulates and inhibits LDHA following PKM2 activation.

Modular optimization in metabolic engineering

There is an increasing demand for bioproducts produced by metabolically engineered microbes, such as pharmaceuticals, biofuels, biochemicals and other high value compounds. In order to meet this demand, modular optimization, the optimizing of subsections instead of the whole system, has been adopted to engineer cells to overproduce products. Research into modularity has focused on traditional approaches such as DNA, RNA, and protein-level modularity of intercellular machinery, by optimizing metabolic pathways for enhanced production. While research into these traditional approaches continues, limitations such as scale-up and time cost hold them back from wider use, while at the same time there is a shift to more novel methods, such as moving from episomal expression to chromosomal integration. Recently, nontraditional approaches such as co-culture systems and cell-free metabolic engineering (CFME) are being investigated for modular optimization. Co-culture modularity looks to optimally divide the metabolic burden between different hosts. CFME seeks to modularly optimize metabolic pathways in vitro, both speeding up the design of such systems and eliminating the issues associated with live hosts. In this review we will examine both traditional and nontraditional approaches for modular optimization, examining recent developments and discussing issues and emerging solutions for future research in metabolic engineering.

Evolutionary History of Plant Metabolism

Tremendous chemical diversity is the hallmark of plants and is supported by highly complex biochemical machinery. Plant metabolic enzymes originated and were transferred from eukaryotic and prokaryotic ancestors and further diversified by the unprecedented rates of gene duplication and functionalization experienced in land plants. Unlike microbes, which have frequent horizontal gene transfer events and multiple inputs of energy and organic carbon, land plants predominantly rely on organic carbon generated from CO₂ and have experienced very few, if any, gene transfers during their recent evolutionary history. As such, plant metabolic networks have evolved in a stepwise manner and on existing networks under various evolutionary constraints. This review aims to take a broader view of plant metabolic evolution and lay a framework to further explore evolutionary mechanisms of the complex metabolic network. Understanding the underlying metabolic and genetic constraints is also an empirical prerequisite for rational engineering and redesigning of plant metabolic pathways.

Conservation of metabolic regulation by phosphorylation and non-covalent small-molecule interactions

Here, we review extant observations of protein phosphorylation and small-molecule interactions in metabolism and ask which of their specific regulatory functions are conserved in Escherichia coli and Homo sapiens. While the number of phosphosites is dramatically higher in humans, the number of metabolite-protein interactions remains largely constant. Moreover, we found the regulatory logic of metabolite-protein interactions, and in many cases also the effector molecules, to be conserved. Post-translational regulation through phosphorylation does not appear to replace this regulation in human but rather seems to add additional opportunities for fine-tuning and more complex responses. The abundance of metabolite-protein interactions in metabolism, their conserved cross-species abundance, and the apparent conservation of regulatory logic across enormous phylogenetic distance demonstrate their relevance for maintaining cellular homeostasis in these ancient biological processes.

pH Feedback Lifecycles Programmed by Enzymatic Logic Gates Using Common Foods as Fuels

Artificial temporal signaling systems, which mimic living out-of-equilibrium conditions, have made large progress. However, systems programmed by enzymatic reaction networks in multicomponent and unknown environments, and using biocompatible components remain a challenge. Herein, we demonstrate an approach to program temporal pH signals by enzymatic logic gates. They are realized by an enzymatic disaccharide-to-monosaccharide-to-sugar acid reaction cascade catalyzed by two metabolic chains: invertase-glucose oxidase and β-galactosidase-glucose oxidase, respectively. Lifetimes of the transient pH signal can be programmed from less than 15 min to more than 1 day. We study enzymatic kinetics of the reaction cascades and reveal the underlying regulatory mechanisms. Operating with all-food grade chemicals and coupling to self-regulating hydrogel, our system is quite robust to work in a complicated medium with unknown components and in a biocompatible fashion.

Combination of network and molecule structure accurately predicts competitive inhibitory interactions

Mining of metabolite-protein interaction networks facilitates the identification of design principles underlying the regulation of different cellular processes. However, identification and characterization of the regulatory role that metabolites play in interactions with proteins on a genome-scale level remains a pressing task. Based on availability of high-quality metabolite-protein interaction networks and genome-scale metabolic networks, here we propose a supervised machine learning approach, called CIRI that determines whether or not a metabolite is involved in a competitive inhibitory regulatory interaction with an enzyme. First, we show that CIRI outperforms the naive approach based on a structural similarity threshold for a putative competitive inhibitor and the substrates of a metabolic reaction. We also validate the performance of CIRI on several unseen data sets and databases of metabolite-protein interactions not used in the training, and demonstrate that the classifier can be effectively used to predict competitive inhibitory interactions. Finally, we show that CIRI can be employed to refine predictions about metabolite-protein interactions from a recently proposed PROMIS approach that employs metabolomics and proteomics profiles from size exclusion chromatography in E. coli to predict metabolite-protein interactions. Altogether, CIRI fills a gap in cataloguing metabolite-protein interactions and can be used in directing future machine learning efforts to categorize the regulatory type of these interactions.

Molecular Dynamics Simulation to Uncover the Mechanisms of Protein Instability During Freezing

Freezing is a common process applied in the pharmaceutical industry to store and transport biotherapeutics. Herewith, multi-scale molecular dynamics simulations of Lactate dehydrogenase (LDH) protein in phosphate buffer with/without ice formation performed to uncover the still poorly understood mechanisms and molecular details of protein destabilization upon freezing. Both fast and slow ice growing conditions were simulated at 243 K from one or two-side of the simulation box, respectively. The rate of ice formation at all-atom simulations was crucial to LDH stability, as faster freezing rates resulted in enhanced structural stability maintained by a higher number of intramolecular hydrogen bonds, less flexible protein's residues, lower solvent accessibility and greater structural compactness. Further, protein aggregation investigated by coarse-grained simulations was verified to be initiated by extended protein structures and retained by electrostatic interactions of the salt bridges between charged residues and hydrogen bonds between polar residues of the protein. Lastly, the study of free energy of dissociation through steered molecular dynamics simulation revealed LDH was destabilized by the solvation of the hydrophobic core and the loss of hydrophobic interactions. For the first time, experimentally validated molecular simulations revealed the detailed mechanisms of LDH destabilization upon ice formation and cryoconcentration of solutes.

Transforming yeast peroxisomes into microfactories for the efficient production of high-value isoprenoids

Current approaches for the production of high-value compounds in microorganisms mostly use the cytosol as a general reaction vessel. However, competing pathways and metabolic cross-talk frequently prevent efficient synthesis of target compounds in the cytosol. Eukaryotic cells control the complexity of their metabolism by harnessing organelles to insulate biochemical pathways. Inspired by this concept, herein we transform yeast peroxisomes into microfactories for geranyl diphosphate-derived compounds, focusing on monoterpenoids, monoterpene indole alkaloids, and cannabinoids. We introduce a complete mevalonate pathway in the peroxisome to convert acetyl-CoA to several commercially important monoterpenes and achieve up to 125-fold increase over cytosolic production. Furthermore, peroxisomal production improves subsequent decoration by cytochrome P450s, supporting efficient conversion of (S)-(-)-limonene to the menthol precursor trans-isopiperitenol. We also establish synthesis of 8-hydroxygeraniol, the precursor of monoterpene indole alkaloids, and cannabigerolic acid, the cannabinoid precursor. Our findings establish peroxisomal engineering as an efficient strategy for the production of isoprenoids.

Metabolic Compartmentalization at the Leading Edge of Metastatic Cancer Cells

Despite advances in targeted therapeutics and understanding in molecular mechanisms, metastasis remains a substantial obstacle for cancer treatment. Acquired genetic mutations and transcriptional changes can promote the spread of primary tumor cells to distant tissues. Additionally, recent studies have uncovered that metabolic reprogramming of cancer cells is tightly associated with cancer metastasis. However, whether intracellular metabolism is spatially and temporally regulated for cancer cell migration and invasion is understudied. In this review, we highlight the emergence of a concept, termed “membraneless metabolic compartmentalization,” as one of the critical mechanisms that determines the metastatic capacity of cancer cells. In particular, we focus on the compartmentalization of purine nucleotide metabolism (e.g., ATP and GTP) at the leading edge of migrating cancer cells through the uniquely phase-separated microdomains where dynamic exchange of nucleotide metabolic enzymes takes place. We will discuss how future insights may usher in a novel class of therapeutics specifically targeting the metabolic compartmentalization that drives tumor metastasis.

Role of Glutathione in Cancer: From Mechanisms to Therapies

Glutathione (GSH) is the most abundant non-protein thiol present at millimolar concentrations in mammalian tissues. As an important intracellular antioxidant, it acts as a regulator of cellular redox state protecting cells from damage caused by lipid peroxides, reactive oxygen and nitrogen species, and xenobiotics. Recent studies have highlighted the importance of GSH in key signal transduction reactions as a controller of cell differentiation, proliferation, apoptosis, ferroptosis and immune function. Molecular changes in the GSH antioxidant system and disturbances in GSH homeostasis have been implicated in tumor initiation, progression, and treatment response. Hence, GSH has both protective and pathogenic roles. Although in healthy cells it is crucial for the removal and detoxification of carcinogens, elevated GSH levels in tumor cells are associated with tumor progression and increased resistance to chemotherapeutic drugs. Recently, several novel therapies have been developed to target the GSH antioxidant system in tumors as a means for increased response and decreased drug resistance. In this comprehensive review we explore mechanisms of GSH functionalities and different therapeutic approaches that either target GSH directly, indirectly or use GSH-based prodrugs. Consideration is also given to the computational methods used to describe GSH related processes for in silico testing of treatment effects.

Rapid stimulation of cellular Pi uptake by the inositol pyrophosphate InsP8 induced by its photothermal release from lipid nanocarriers using a near infra-red light-emitting diode

Inositol pyrophosphates (PP-InsPs), including diphospho-myo-inositol pentakisphosphate (5-InsP7) and bis-diphospho-myo-inositol tetrakisphosphate (1,5-InsP8), are highly polar, membrane-impermeant signaling molecules that control many homeostatic responses to metabolic and bioenergetic imbalance. To delineate their molecular activities, there is an increasing need for a toolbox of methodologies for real-time modulation of PP-InsP levels inside large populations of cultured cells. Here, we describe procedures to package PP-InsPs into thermosensitive phospholipid nanocapsules that are impregnated with a near infra-red photothermal dye; these liposomes are readily accumulated into cultured cells. The PP-InsPs remain trapped inside the liposomes until the cultures are illuminated with a near infra-red light-emitting diode (LED) which permeabilizes the liposomes to promote PP-InsP release. Additionally, so as to optimize these procedures, a novel stably fluorescent 5-InsP7 analogue (i.e., 5-FAM-InsP7) was synthesized with the assistance of click-chemistry; the delivery and deposition of the analogue inside cells was monitored by flow cytometry and by confocal microscopy. We describe quantitatively-controlled PP-InsP release inside cells within 5 min of LED irradiation, without measurable effect upon cell integrity, using a collimated 22 mm beam that can irradiate up to 106 cultured cells. Finally, to interrogate the biological value of these procedures, we delivered 1,5-InsP8 into HCT116 cells and showed it to dose-dependently stimulate the rate of [33P]-Pi uptake; these observations reveal a rheostatic range of concentrations over which 1,5-InsP8 is biologically functional in Pi homeostasis.

Towards a functional understanding of the plant metabolome

Plants are true organic chemists-the chemical diversity of plant metabolomes goes hand in hand with functional diversity. New, often unexpected roles are being reported for both evolutionarily conserved and well-characterised central metabolites such as amino acids, nucleotides, and sugars, and for specialized/secondary metabolites such as carotenoids, glucosinolates, and terpenoids. Our review aims to highlight recent studies reporting novel roles of metabolites and to emphasize the importance of cell-wide identification of metabolite-protein complexes for the comprehensive, functional understanding of the plant metabolome.

Nitrogen limitation reveals large reserves in metabolic and translational capacities of yeast

Cells maintain reserves in their metabolic and translational capacities as a strategy to quickly respond to changing environments. Here we quantify these reserves by stepwise reducing nitrogen availability in yeast steady-state chemostat cultures, imposing severe restrictions on total cellular protein and transcript content. Combining multi-omics analysis with metabolic modeling, we find that seven metabolic superpathways maintain >50% metabolic capacity in reserve, with glucose metabolism maintaining >80% reserve capacity. Cells maintain >50% reserve in translational capacity for 2490 out of 3361 expressed genes (74%), with a disproportionately large reserve dedicated to translating metabolic proteins. Finally, ribosome reserves contain up to 30% sub-stoichiometric ribosomal proteins, with activation of reserve translational capacity associated with selective upregulation of 17 ribosomal proteins. Together, our dataset provides a quantitative link between yeast physiology and cellular economics, which could be leveraged in future cell engineering through targeted proteome streamlining.

Cells maintain reserves in their metabolic and translational capacities enabling fast response to changing environments. Here, the authors quantify reserves in yeast by stepwise reduction in nitrogen availability and a combination of multi-omic analysis and metabolic modelling.

The evolution of metabolism: How to test evolutionary hypotheses at the genomic level

The origin of primordial metabolism and its expansion to form the metabolic networks extant today represent excellent systems to study the impact of natural selection and the potential adaptive role of novel compounds. Here we present the current hypotheses made on the origin of life and ancestral metabolism and present the theories and mechanisms by which the large chemical diversity of plants might have emerged along evolution. In particular, we provide a survey of statistical methods that can be used to detect signatures of selection at the gene and population level, and discuss potential and limits of these methods for investigating patterns of molecular adaptation in plant metabolism.

Control of XPR1-dependent cellular phosphate efflux by InsP8 is an exemplar for functionally-exclusive inositol pyrophosphate signaling

Homeostasis of cellular fluxes of inorganic phosphate (Pi) supervises its structural roles in bones and teeth, its pervasive regulation of cellular metabolism, and its functionalization of numerous organic compounds. Cellular Pi efflux is heavily reliant on Xenotropic and Polytropic Retrovirus Receptor 1 (XPR1), regulation of which is largely unknown. We demonstrate specificity of XPR1 regulation by a comparatively uncharacterized member of the inositol pyrophosphate (PP-InsP) signaling family: 1,5-bis-diphosphoinositol 2,3,4,6-tetrakisphosphate (InsP₈). XPR1-mediated Pi efflux was inhibited by reducing cellular InsP₈ synthesis, either genetically (knockout [KO] of diphosphoinositol pentakisphosphate kinases [PPIP5Ks] that synthesize InsP₈) or pharmacologically [cell treatment with 2.5 µM dietary flavonoid or 10 µM N2-(m-trifluorobenzyl), N6-(p-nitrobenzyl) purine], to inhibit inositol hexakisphosphate kinases upstream of PPIP5Ks. Attenuated Pi efflux from PPIP5K KO cells was quantitatively phenocopied by KO of XPR1 itself. Moreover, Pi efflux from PPIP5K KO cells was rescued by restoration of InsP₈ levels through transfection of wild-type PPIP5K1; transfection of kinase-dead PPIP5K1 was ineffective. Pi efflux was also rescued in a dose-dependent manner by liposomal delivery of a metabolically resistant methylene bisphosphonate (PCP) analog of InsP₈; PCP analogs of other PP-InsP signaling molecules were ineffective. High-affinity binding of InsP₈ to the XPR1 N-terminus (K _d = 180 nM) was demonstrated by isothermal titration calorimetry. To derive a cellular biology perspective, we studied biomineralization in the Soas-2 osteosarcoma cell line. KO of PPIP5Ks or XPR1 strongly reduced Pi efflux and accelerated differentiation to the mineralization end point. We propose that catalytically compromising PPIP5K mutations might extend an epistatic repertoire for XPR1 dysregulation, with pathological consequences for bone maintenance and ectopic calcification.

Untargeted metabolomics links glutathione to bacterial cell cycle progression

Cell cycle progression requires the coordination of cell growth, chromosome replication, and division. Consequently, a functional cell cycle must be coupled with metabolism. However, direct measurements of metabolome dynamics remained scarce, in particular in bacteria. Here, we describe an untargeted metabolomics approach with synchronized Caulobacter crescentus cells to monitor the relative abundance changes of ~400 putative metabolites as a function of the cell cycle. While the majority of metabolite pools remains homeostatic, ~14% respond to cell cycle progression. In particular, sulfur metabolism is redirected during the G1-S transition, and glutathione levels periodically change over the cell cycle with a peak in late S phase. A lack of glutathione perturbs cell size by uncoupling cell growth and division through dysregulation of KefB, a K+/H+ antiporter. Overall, we here describe the impact of the C. crescentus cell cycle progression on metabolism, and in turn relate glutathione and potassium homeostasis to timely cell division.