How metabolites modulate metabolic flux

Peri active site catalysis of proline isomerisation is the molecular basis of allomorphy in β-phosphoglucomutase

Metabolic regulation occurs through precise control of enzyme activity. Allomorphy is a post-translational fine control mechanism where the catalytic rate is governed by a conformational switch that shifts the enzyme population between forms with different activities. β-Phosphoglucomutase (βPGM) uses allomorphy in the catalysis of isomerisation of β-glucose 1-phosphate to glucose 6-phosphate via β-glucose 1,6-bisphosphate. Herein, we describe structural and biophysical approaches to reveal its allomorphic regulatory mechanism. Binding of the full allomorphic activator β-glucose 1,6-bisphosphate stimulates enzyme closure, progressing through NAC I and NAC III conformers. Prior to phosphoryl transfer, loops positioned on the cap and core domains are brought into close proximity, modulating the environment of a key proline residue. Hence accelerated isomerisation, likely via a twisted anti/C4-endo transition state, leads to the rapid predominance of active cis-P βPGM. In contrast, binding of the partial allomorphic activator fructose 1,6-bisphosphate arrests βPGM at a NAC I conformation and phosphoryl transfer to both cis-P βPGM and trans-P βPGM occurs slowly. Thus, allomorphy allows a rapid response to changes in food supply while not otherwise impacting substantially on levels of important metabolites.

Bacterial protein acetylation: mechanisms, functions, and methods for study

Lysine acetylation is an evolutionarily conserved protein modification that changes protein functions and plays an essential role in many cellular processes, such as central metabolism, transcriptional regulation, chemotaxis, and pathogen virulence. It can alter DNA binding, enzymatic activity, protein-protein interactions, protein stability, or protein localization. In prokaryotes, lysine acetylation occurs non-enzymatically and by the action of lysine acetyltransferases (KAT). In enzymatic acetylation, KAT transfers the acetyl group from acetyl-CoA (AcCoA) to the lysine side chain. In contrast, acetyl phosphate (AcP) is the acetyl donor of chemical acetylation. Regardless of the acetylation type, the removal of acetyl groups from acetyl lysines occurs only enzymatically by lysine deacetylases (KDAC). KATs are grouped into three main superfamilies based on their catalytic domain sequences and biochemical characteristics of catalysis. Specifically, members of the GNAT are found in eukaryotes and prokaryotes and have a core structural domain architecture. These enzymes can acetylate small molecules, metabolites, peptides, and proteins. This review presents current knowledge of acetylation mechanisms and functional implications in bacterial metabolism, pathogenicity, stress response, translation, and the emerging topic of protein acetylation in the gut microbiome. Additionally, the methods used to elucidate the biological significance of acetylation in bacteria, such as relative quantification and stoichiometry quantification, and the genetic code expansion tool (CGE), are reviewed.

Oomycete Metabolism Is Highly Dynamic and Reflects Lifestyle Adaptations

The selective pressure of pathogen-host symbiosis drives adaptations. How these interactions shape the metabolism of pathogens is largely unknown. Here, we use comparative genomics to systematically analyze the metabolic networks of oomycetes, a diverse group of eukaryotes that includes saprotrophs as well as animal and plant pathogens, with the latter causing devastating diseases with significant economic and/or ecological impacts. In our analyses of 44 oomycete species, we uncover considerable variation in metabolism that can be linked to lifestyle differences. Comparisons of metabolic gene content reveal that plant pathogenic oomycetes have a bipartite metabolism consisting of a conserved core and an accessory set. The accessory set can be associated with the degradation of defense compounds produced by plants when challenged by pathogens. Obligate biotrophic oomycetes have smaller metabolic networks, and taxonomically distantly related biotrophic lineages display convergent evolution by repeated gene losses in both the conserved as well as the accessory set of metabolisms. When investigating to what extent the metabolic networks in obligate biotrophs differ from those in hemibiotrophic plant pathogens, we observe that the losses of metabolic enzymes in obligate biotrophs are not random and that gene losses predominantly influence the terminal branches of the metabolic networks. Our analyses represent the first metabolism-focused comparison of oomycetes at this scale and will contribute to a better understanding of the evolution of oomycete metabolism in relation to lifestyle adaptation. Numerous oomycete species are devastating plant pathogens that cause major damage in crops and natural ecosystems. Their interactions with hosts are shaped by strong selection, but how selection affects adaptation of the primary metabolism to a pathogenic lifestyle is not yet well established. By pan-genome and metabolic network analyses of distantly related oomycete pathogens and their nonpathogenic relatives, we reveal considerable lifestyle- and lineage-specific adaptations. This study contributes to a better understanding of metabolic adaptations in pathogenic oomycetes in relation to lifestyle, host, and environment, and the findings will help in pinpointing potential targets for disease control. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

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.

Electro-metabolic coupling in multi-chambered vascularized human cardiac organoids

The study of cardiac physiology is hindered by physiological differences between humans and small-animal models. Here we report the generation of multi-chambered self-paced vascularized human cardiac organoids formed under anisotropic stress and their applicability to the study of cardiac arrhythmia. Sensors embedded in the cardiac organoids enabled the simultaneous measurement of oxygen uptake, extracellular field potentials and cardiac contraction at resolutions higher than 10 Hz. This microphysiological system revealed 1 Hz cardiac respiratory cycles that are coupled to the electrical rather than the mechanical activity of cardiomyocytes. This electro-mitochondrial coupling was driven by mitochondrial calcium oscillations driving respiration cycles. Pharmaceutical or genetic inhibition of this coupling results in arrhythmogenic behaviour. We show that the chemotherapeutic mitoxantrone induces arrhythmia through disruption of this pathway, a process that can be partially reversed by the co-administration of metformin. Our microphysiological cardiac systems may further facilitate the study of the mitochondrial dynamics of cardiac rhythms and advance our understanding of human cardiac physiology.

Carbon Fluxes in Potato (Solanum tuberosum) Remain Stable in Cell Cultures Exposed to Nutritional Phosphate Deficiency

Nutritional phosphate deficiency is a major limitation to plant growth. Here, we monitored fluxes in pathways supporting respiratory metabolism in potato (Solanum tuberosum) cell cultures growing in control or limiting phosphate conditions. Sugar uptake was quantified using [U-14C]sucrose as precursor. Carbohydrate degradation through glycolysis and respiratory pathways was estimated using the catabolism of [U-14C]sucrose to 14CO2. Anaplerotic carbon flux was assessed by labeling with NaH14CO3. The data showed that these metabolic fluxes displayed distinct patterns over culture time. However, phosphate depletion had relatively little impact on the various fluxes. Sucrose uptake was higher during the first six days of culture, followed by a decline, which was steeper in Pi-sufficient cells. Anaplerotic pathway flux was more important at day three and decreased thereafter. In contrast, the flux between sucrose and CO2 was at a maximum in the mid-log phase of the culture, with a peak at Day 6. Metabolization of [U-14C]sucrose into neutral, basic and acidic fractions was also unaffected by phosphate nutrition. Hence, the well-documented changes in central metabolism enzymes activities in response to Pi deficiency do not drastically modify metabolic fluxes, but rather result in the maintenance of the carbon fluxes that support respiration.

ABHD17C, a metabolic and immune-related gene signature, predicts prognosis and anti-PD1 therapy response in pancreatic cancer

BACKGROUND

PDAC is a highly malignant and immune-suppressive tumor, posing great challenges to therapy.

METHODS

In this study, we utilized multi-center RNA sequencing and non-negative matrix factorization clustering (NMF) to identify a group of metabolism-related genes that could effectively predict the immune status and survival (both disease-free survival and overall survival) of pancreatic ductal adenocarcinoma (PDAC) patients. Subsequently, through the integration of single cell sequencing and our center's prospective and retrospective cohort studies, we identified ABHD17C, which possesses metabolic and immune-related characteristics, as a potential biomarker for predicting the prognosis and response to anti-PD1 therapy in PDAC. We then demonstrated how ABHD17C participates in the regulation of the immune microenvironment through in vitro glycolytic function experiments and in vivo animal experiments.

RESULTS

Through screening for pancreatic cancer metabolic markers and immune status, we identified a critical molecule that inhibits pancreatic cancer survival and prognosis. Further flow cytometry analysis confirmed that ABHD17C is involved in the inhibition of the formation of the immune environment in PDAC. Our research found that ABHD17C participates in the metabolic process of tumor cells in in vitro and in vivo experiments, reshaping the immunosuppressive microenvironment by downregulating the pH value. Furthermore, through LDHA inhibition experiments, we demonstrated that ABHD17C significantly enhances glycolysis and inhibits the formation of the immune suppressive environment. In in vivo experiments, we also validated that ABHD17C overexpression significantly mediates resistance to anti-PD1 therapy and promotes the progression of pancreatic cancer.

CONCLUSION

Therefore, ABHD17C may be a novel and effective biomarker for predicting the metabolic status and immune condition of PDAC patients, and provide a potential predictive strategy for anti-PD1 therapy in PDAC.

Microalgal Carotenoids: Therapeutic Application and Latest Approaches to Enhance the Production

Microalgae are microscopic photosynthetic organisms frequently found in fresh and marine water ecosystems. Various microalgal species have been considered a reservoir of diverse health-value products, including vitamins, proteins, lipids, and polysaccharides, and are broadly utilized as food and for the treatment of human ailments such as cancer, cardiovascular diseases, allergies, and immunodeficiency. Microalgae-derived carotenoids are the type of accessory pigment that possess light-absorbing potential and play a significant role in metabolic functions. To date, nearly a thousand carotenoids have been reported, but a very less number of microalgae have been used for the commercial production of carotenoids. This review article briefly discussed the carotenoids of microalgal origin and their therapeutic application. In addition, we have briefly compiled the optimization of culture parameters used to enhance microalgal carotenoid production. In addition, the latest biotechnological approaches used to improve the yields of carotenoid has also been discussed.

Tuning a high performing multiplexed-CRISPRi Pseudomonas putida strain to further enhance indigoidine production

In this study, a 14-gene edited Pseudomonas putida KT2440 strain for heterologous indigoidine production was examined using three distinct omic datasets. Transcriptomic data indicated that CRISPR/dCpf1-interference (CRISPRi) mediated multiplex repression caused global gene expression changes, implying potential undesirable changes in metabolic flux. ¹³C-metabolic flux analysis (¹³C-MFA) revealed that the core P. putida flux network after CRISPRi repression was conserved, with moderate reduction of TCA cycle and pyruvate shunt activity along with glyoxylate shunt activation during glucose catabolism. Metabolomic results identified a change in intracellular TCA metabolites and extracellular metabolite secretion profiles (sugars and succinate overflow) in the engineered strains. These omic analyses guided further strain engineering, with a random mutagenesis screen first identifying an optimal ribosome binding site (RBS) for Cpf1 that enabled stronger product-substrate pairing (1.6-fold increase). Then, deletion strains were constructed with excision of the PHA operon (ΔphaAZC-IID) resulting in a 2.2-fold increase in indigoidine titer over the optimized Cpf1-RBS construct at the end of the growth phase (∼6 h). The maximum indigoidine titer (at 72 h) in the ΔphaAZC-IID strain had a 1.5-fold and 1.8-fold increase compared to the optimized Cpf1-RBS construct and the original strain, respectively. Overall, this study demonstrated that integration of omic data types is essential for understanding responses to complex metabolic engineering designs and directly quantified the effect of such modifications on central metabolism.

The role of iron nanoparticles on morpho-physiological traits and genes expression (IRT1 and CAT) in rue (Ruta graveolens)

The iron nanoparticles with different physic-chemical properties induce inconsistent effects on various studied plant species. Thus, the effect of ferric oxide (Fe₂O₃) nanoparticles was compared with Fe₂O₃ microparticles and FeSO₄complexes of EDTA for major physiological and gene expression in Rue (Ruta graveolens). Iron root content increased as Fe-MPs + EDTA ˂˂ Fe-NPs + EDTA˂ FeSO₄ + EDTA. The shoot's iron remained unchanged or slightly increased under most of FeSO₄ and Fe-MPs + EDTA treatments. Under Fe-NPs + EDTA treatment, 50 and 250 µM concentration decreased on shoot iron by 23.2% and 19.4% compared to control, respectively. But the shoot iron at 500 µM NPs was 28.2% higher than that of the control. A 46-58 fold lower Fe translocation was observed under Fe-NPs + EDTA than Fe-MPs + EDTA. The effect of Fe-NPs + EDTA was more significant on plant fresh and dry mass than the control. All treatments showed an increase in anthocyanin by 19-84% in leaves compared to the control. The Fe-NPs + EDTA and MPs + EDTA induced similar effects on enhanced growth parameters, total chlorophyll, catalase enzyme activity, gene, and reduced chlorophyll a/b and oxidants. Catalase enzyme activity in FeSO₄ and MPs + EDTA was similar, and in Fe-NPs + EDTA treatments were influenced by coarse and fine regulation mechanisms, respectively. Iron MPs + EDTA had a more negative effect on IRT₁ relative gene expression in roots as compared to other iron forms. The IRT₁ relative gene expression in shoots was positively affected by 31-81% under all treatment types (except control and 250 µM Fe-NPs + EDTA, and 250 µM MPs + EDTA). These results could reveal the potential mechanism of plant response to nanoparticles.

Linear programming based gene expression model (LPM-GEM) predicts the carbon source for Bacillus subtilis

BACKGROUND

Elucidating cellular metabolism led to many breakthroughs in biotechnology, synthetic biology, and health sciences. To date, deriving metabolic fluxes by ¹³C tracer experiments is the most prominent approach for studying metabolic fluxes quantitatively, often with high accuracy and precision. However, the technique has a high demand for experimental resources. Alternatively, flux balance analysis (FBA) has been employed to estimate metabolic fluxes without labeling experiments. It is less informative but can benefit from the low costs and low experimental efforts and gain flux estimates in experimentally difficult conditions. Methods to integrate relevant experimental data have been emerged to improve FBA flux estimations. Data from transcription profiling is often selected since it is easy to generate at the genome scale, typically embedded by a discretization of differential and non-differential expressed genes coding for the respective enzymes.

RESULT

We established the novel method Linear Programming based Gene Expression Model (LPM-GEM). LPM-GEM linearly embeds gene expression into FBA constraints. We implemented three strategies to reduce thermodynamically infeasible loops, which is a necessary prerequisite for such an omics-based model building. As a case study, we built a model of B. subtilis grown in eight different carbon sources. We obtained good flux predictions based on the respective transcription profiles when validating with ¹³C tracer based metabolic flux data of the same conditions. We could well predict the specific carbon sources. When testing the model on another, unseen dataset that was not used during training, good prediction performance was also observed. Furthermore, LPM-GEM outperformed a well-established model building methods.

CONCLUSION

Employing LPM-GEM integrates gene expression data efficiently. The method supports gene expression-based FBA models and can be applied as an alternative to estimate metabolic fluxes when tracer experiments are inappropriate.

Substrate availability and toxicity shape the structure of microbial communities engaged in metabolic division of labor

Metabolic division of labor (MDOL) represents a widespread natural phenomenon, whereby a complex metabolic pathway is shared between different strains within a community in a mutually beneficial manner. However, little is known about how the composition of such a microbial community is regulated. We hypothesized that when degradation of an organic compound is carried out via MDOL, the concentration and toxicity of the substrate modulate the benefit allocation between the two microbial populations, thus affecting the structure of this community. We tested this hypothesis by combining modeling with experiments using a synthetic consortium. Our modeling analysis suggests that the proportion of the population executing the first metabolic step can be simply estimated by Monod-like formulas governed by substrate concentration and toxicity. Our model and the proposed formula were able to quantitatively predict the structure of our synthetic consortium. Further analysis demonstrates that our rule is also applicable in estimating community structures in spatially structured environments. Together, our work clearly demonstrates that the structure of MDOL communities can be quantitatively predicted using available information on environmental factors, thus providing novel insights into how to manage artificial microbial systems for the wide application of the bioindustry.

Predicting Metabolic Adaptation Under Dynamic Substrate Conditions Using a Resource-Dependent Kinetic Model: A Case Study Using Saccharomyces cerevisiae

Exposed to changes in their environment, microorganisms will adapt their phenotype, including metabolism, to ensure survival. To understand the adaptation principles, resource allocation-based approaches were successfully applied to predict an optimal proteome allocation under (quasi) steady-state conditions. Nevertheless, for a general, dynamic environment, enzyme kinetics will have to be taken into account which was not included in the linear resource allocation models. To this end, a resource-dependent kinetic model was developed and applied to the model organism Saccharomyces cerevisiae by combining published kinetic models and calibrating the model parameters to published proteomics and fluxomics datasets. Using this approach, we were able to predict specific proteomes at different dilution rates under chemostat conditions. Interestingly, the approach suggests that the occurrence of aerobic fermentation (Crabtree effect) in S. cerevisiae is not caused by space limitation in the total proteome but rather an effect of constraints on the mitochondria. When exposing the approach to repetitive, dynamic substrate conditions, the proteome space was allocated differently. Less space was predicted to be available for non-essential enzymes (reserve space). This could indicate that the perceived “overcapacity” present in experimentally measured proteomes may very likely serve a purpose in increasing the robustness of a cell to dynamic conditions, especially an increase of proteome space for the growth reaction as well as of the trehalose cycle that was shown to be essential in providing robustness upon stronger substrate perturbations. The model predictions of proteome adaptation to dynamic conditions were additionally evaluated against respective experimentally measured proteomes, which highlighted the model’s ability to accurately predict major proteome adaptation trends. This proof of principle for the approach can be extended to production organisms and applied for both understanding metabolic adaptation and improving industrial process design.

Intracellular and extracellular untargeted metabolomics reveal the effect of acute uranium exposure in HK-2 cells

Uranium exposure poses a serious threat to the health of occupational populations and the public. Although metabolomics is a promising research approach to study the toxicological mechanisms of uranium exposure, in vitro studies using human cells are scarce. Applying cultured cell metabolomics, we exhaustively analyzed the intracellular and extracellular differential metabolites upon uranium exposure and characterized the possible biological effects of uranium exposure on human kidney cells. Uranium exposure significantly induced disturbance in the amino acid biosynthesis and linoleic acid metabolism of the cells. Cells exposed to uranium produce excessive amounts of arachidonic acid, which has the potential to cause oxidative stress and damage cells. The results provide new evidence for an oxidative stress mechanism of uranium-induced renal cell injury. Cell metabolomics has proven to be a useful diagnostic tool to study the molecular mechanisms of uranium poisoning.

Limited Mechanistic Link Between the Monod Equation and Methanogen Growth: a Perspective from Metabolic Modeling

The Monod equation has been widely applied as the general rate law of microbial growth, but its applications are not always successful. By drawing on the frameworks of kinetic and stoichiometric metabolic models and metabolic control analysis, the modeling reported here simulated the growth kinetics of a methanogenic microorganism and illustrated that different enzymes and metabolites control growth rate to various extents and that their controls peak at either very low, intermediate, or very high substrate concentrations. In comparison, with a single term and two parameters, the Monod equation only approximately accounts for the controls of rate-determining enzymes and metabolites at very high and very low substrate concentrations, but neglects the enzymes and metabolites whose controls are most notable at intermediate concentrations. These findings support a limited link between the Monod equation and methanogen growth, and unify the competing views regarding enzyme roles in shaping growth kinetics. The results also preclude a mechanistic derivation of the Monod equation from methanogen metabolic networks and highlight a fundamental challenge in microbiology: single-term expressions may not be sufficient for accurate prediction of microbial growth. IMPORTANCE The Monod equation has been widely applied to predict the rate of microbial growth, but its application is not always successful. Using a novel metabolic modeling approach, we simulated the growth of a methanogen and uncovered a limited mechanistic link between the Monod equation and the methanogen's metabolic network. Specifically, the equation provides an approximation to the controls by rate-determining metabolites and enzymes at very low and very high substrate concentrations, but it is missing the remaining enzymes and metabolites whose controls are most notable at intermediate concentrations. These results support the Monod equation as a useful approximation of growth rates and highlight a fundamental challenge in microbial kinetics: single-term rate expressions may not be sufficient for accurate prediction of microbial growth.

Cadaverine Is a Switch in the Lysine Degradation Pathway in Pseudomonas aeruginosa Biofilm Identified by Untargeted Metabolomics

There is a critical need to accurately diagnose, prevent, and treat biofilms in humans. The biofilm forming P. aeruginosa bacteria can cause acute and chronic infections, which are difficult to treat due to their ability to evade host defenses along with an inherent antibiotic-tolerance. Using an untargeted NMR-based metabolomics approach, we identified statistically significant differences in 52 metabolites between P. aeruginosa grown in the planktonic and lawn biofilm states. Among them, the metabolites of the cadaverine branch of the lysine degradation pathway were systematically decreased in biofilm. Exogenous supplementation of cadaverine caused significantly increased planktonic growth, decreased biofilm accumulation by 49% and led to altered biofilm morphology, converting to a pellicle biofilm at the air-liquid interface. Our findings show how metabolic pathway differences directly affect the growth mode in P. aeruginosa and could support interventional strategies to control biofilm formation.

MetAMDB: Metabolic Atom Mapping Database

MetAMDB is an open-source metabolic atom mapping database, providing atom mappings for around 43,000 metabolic reactions. Each atom mapping can be inspected and downloaded either as an RXN file or as a graphic in SVG format. In addition, MetAMDB offers the possibility of automatically creating atom mapping models based on user-specified metabolic networks. These models can be of any size (small to genome-scale) and can subsequently be used in standard 13C metabolic flux analysis software.

Enzymatic cometabolic biotransformation of organic micropollutants in wastewater treatment plants: A review

Biotransformation of trace-level organic micropollutants (OMPs) by complex microbial communities in wastewater treatment facilities is a key process for their detoxification and environmental impact reduction. Therefore, understanding the metabolic activities and mechanisms that contribute to their biotransformation is essential when developing approaches aiming to minimize their discharge. This review addresses the relevance of cometabolic processes and discusses the main enzymatic activities currently known to take part in OMPs removal under different redox environments in the compartments of wastewater treatment plants. Furthermore, the most common methodologies to decipher such enzymes are discussed, including the use of in vitro enzyme assays, enzymatic inhibitors, the analysis of transformation products and the application of several -omic techniques. Finally, perspectives on major challenges and future research requirements to improve OMPs biotransformation are proposed.

Oxygen in Metabolic Dysfunction and Its Therapeutic Relevance

Significance: In recent years, a number of studies have shown altered oxygen partial pressure at a tissue level in metabolic disorders, and some researchers have considered oxygen to be a (macro) nutrient. Oxygen availability may be compromised in obesity and several other metabolism-related pathological conditions, including sleep apnea-hypopnea syndrome, the metabolic syndrome (which is a set of conditions), type 2 diabetes, cardiovascular disease, and cancer. Recent Advances: Strategies designed to reduce adiposity and its accompanying disorders have been mainly centered on nutritional interventions and physical activity programs. However, novel therapies are needed since these approaches have not been sufficient to counteract the worldwide increasing rates of metabolic disorders. In this regard, intermittent hypoxia training and hyperoxia could be potential treatments through oxygen-related adaptations. Moreover, living at a high altitude may have a protective effect against the development of abnormal metabolic conditions. In addition, oxygen delivery systems may be of therapeutic value for supplying the tissue-specific oxygen requirements. Critical Issues: Precise in vivo methods to measure oxygenation are vital to disentangle some of the controversies related to this research area. Further, it is evident that there is a growing need for novel in vitro models to study the potential pathways involved in metabolic dysfunction to find appropriate therapeutic targets. Future Directions: Based on the existing evidence, it is suggested that oxygen availability has a key role in obesity and its related comorbidities. Oxygen should be considered in relation to potential therapeutic strategies in the treatment and prevention of metabolic disorders. Antioxid. Redox Signal. 35, 642-687.

Design and Implementation of a Tool to Assess Students' Understanding of Metabolic Pathways Dynamics and Regulation

Metabolic systems form the very foundation of life and as such are broadly taught in the molecular life sciences. Here, we describe the biochemistry educator community-based development and use of an assessment instrument designed to evaluate students' ideas about metabolic pathway dynamics and regulation in undergraduate biochemistry courses. Analysis of student responses showed that most students were able to interpret visual representations in an unfamiliar metabolic pathway and that many could make basic predictions about how the system would be expected to respond to changes. However, fewer students generated nuanced responses that accounted for both microscopic changes at the protein level and macroscopic changes in pathway product outputs. These findings identify some of the challenges of meaningfully assessing students' understanding of metabolic pathways and could inform how instructors think about teaching and assessing metabolism in undergraduate biochemistry and beyond. The results also suggest future avenues for biochemistry education research.

Identifying sources of metabolomic diversity and reconfiguration in peach fruit: taking notes for quality fruit improvement

The metabolomic content determines many of the important features of a fruit, such as its taste, flavor, color, nutritional value, and abiotic or biotic resistance. Peach (Prunus persica (L.) Batsch) is one of the best genetically characterized species used as a model for Rosaceae, the drupes of which are a source of minerals, vitamins, fiber, and antioxidant compounds for healthy diets around the world. During the last few years, a great advance in the analysis of the metabolic diversity and reconfiguration in different peach varieties in response to developmental and environmental factors has occurred. These studies have shown that the great phenotypic diversity among different peach varieties is correlated with differential metabolomic content. Besides, the fruit metabolome of each peach variety is not static; on the contrary, it is drastically configured in response to both developmental and environmental signals, and moreover, it was found that these metabolic reconfigurations are also variety dependent. In the present review, the main sources of metabolic diversity and conditions that induce modifications in the peach fruit metabolome are summarized. It is postulated that comparison of the metabolic reconfigurations that take place among the fruits from different varieties may help us better understand peach fruit metabolism and their key drivers, which in turn may aid in the future design of high‐quality peach fruits.

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.

The remodel of the "central dogma": a metabolomics interaction perspective

BACKGROUND

In 1957, Francis Crick drew a linear diagram on a blackboard. This diagram is often called the "central dogma." Subsequently, the relationships between different steps of the "central dogma" have been shown to be considerably complex, mostly because of the emerging world of small molecules. It is noteworthy that metabolites can be generated from the diet through gut microbiome metabolism, serve as substrates for epigenetic modifications, destabilize DNA quadruplexes, and follow Lamarckian inheritance. Small molecules were once considered the missing link in the "central dogma"; however, recently they have acquired a central role, and their general perception as downstream products has become reductionist. Metabolomics is a large-scale analysis of metabolites, and this emerging field has been shown to be the closest omics associated with the phenotype and concomitantly, the basis for all omics.

AIM OF REVIEW

Herein, we propose a broad updated perspective for the flux of information diagram centered in metabolomics, including the influence of other factors, such as epigenomics, diet, nutrition, and the gut- microbiome.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Metabolites are the beginning and the end of the flux of information.

Control and regulation of acetate overflow in Escherichia coli

Overflow metabolism refers to the production of seemingly wasteful by-products by cells during growth on glucose even when oxygen is abundant. Two theories have been proposed to explain acetate overflow in Escherichia coli – global control of the central metabolism and local control of the acetate pathway – but neither accounts for all observations. Here, we develop a kinetic model of E. coli metabolism that quantitatively accounts for observed behaviours and successfully predicts the response of E. coli to new perturbations. We reconcile these theories and clarify the origin, control, and regulation of the acetate flux. We also find that, in turns, acetate regulates glucose metabolism by coordinating the expression of glycolytic and TCA genes. Acetate should not be considered a wasteful end-product since it is also a co-substrate and a global regulator of glucose metabolism in E. coli. This has broad implications for our understanding of overflow metabolism.

Seconds-Resolved, In Situ Measurements of Plasma Phenylalanine Disposition Kinetics in Living Rats

Current knowledge of the disposition kinetics of endogenous metabolites is founded almost entirely on poorly time-resolved experiments in which samples are removed from the body for later, benchtop analysis. Here, in contrast, we describe real-time, seconds-resolved measurements of plasma phenylalanine collected in situ in the body via electrochemical aptamer-based (EAB) sensors, a platform technology that is independent of the reactivity of its targets and thus is generalizable to many. Specifically, using indwelling EAB sensors, we have monitored plasma phenylalanine in live rats with a few micromolar precision and a 12 s temporal resolution, identifying a large-amplitude, few-seconds phase in the animals' metabolic response that had not previously been reported. Using the hundreds of individual measurements that the approach provides from each animal, we also identify inter-subject variability, including statistically significant differences associated with the feeding status. These results highlight the power of in vivo EAB measurements, an advancement that could dramatically impact our understanding of physiology and provide a valuable new tool for the monitoring and treatment of metabolic disorders.

Core Fermentation (CoFe) granules focus coordinated glycolytic mRNA localization and translation to fuel glucose fermentation

Glycolysis is a fundamental metabolic pathway for glucose catabolism across biology, and glycolytic enzymes are among the most abundant proteins in cells. Their expression at such levels provides a particular challenge. Here we demonstrate that the glycolytic mRNAs are localized to granules in yeast and human cells. Detailed live cell and smFISH studies in yeast show that the mRNAs are actively translated in granules, and this translation appears critical for the localization. Furthermore, this arrangement is likely to facilitate the higher level organization and control of the glycolytic pathway. Indeed, the degree of fermentation required by cells is intrinsically connected to the extent of mRNA localization to granules. On this basis, we term these granules, core fermentation (CoFe) granules; they appear to represent translation factories, allowing high-level coordinated enzyme synthesis for a critical metabolic pathway.

The organic loading rate affects organic micropollutants' cometabolic biotransformation kinetics under heterotrophic conditions in activated sludge

Several studies have shown that organic micropollutants (OMPs) are biotransformed cometabolically in activated sludge systems. However, the individual role of heterotrophs in the microbial consortium is still not clear, i.e., there is still a gap regarding the influence of the heterotrophic activity on the cometabolic biotransformation kinetics and yield of the OMPs. Aiming to answer these questions, experiments with increasing primary substrate concentrations were performed under aerobic heterotrophic conditions in a continuous stirred tank reactor operated at several organic loading rates (OLR) with fixed hydraulic retention time. Moreover, the individual kinetic parameters were determined in batch assays with different initial substrate concentrations using the sludges from the continuous reactor. A set of 15 OMPs displaying a variety of physicochemical properties were spiked to the feeding in the ng L^-1 - µg L^-1 range. Results reveal that the biodegradation of the primary carbon source and the biotransformation of the OMPs occur simultaneously, in clear evidence of cometabolic behavior. Moreover, we conclude that the OMPs biotransformation kinetic constant (k_biol) shows a linear dependence with the OLR of the primary substrate for most of the compounds studied, suggesting that the heterotrophic activity seriously affects the OMPs biotransformation kinetics. However, under typical activated sludge systems operating conditions (hydraulic retention times above 8 h), their biotransformation yield would not be significantly affected.

Human Islets Contain a Beta Cell Type That Expresses Proinsulin But Not the Enzyme That Converts the Precursor to Insulin

In pancreatic beta cells, proinsulin (ProIN) undergoes folding in endoplasmic reticulum/Golgi system and is translocated to secretory vesicles for processing into insulin and C-peptide by the proprotein convertases (PC)1/3 and PC2, and carboxypeptidase E. Human beta cells show significant variation in the level of expression of PC1/3, the critical proconvertase involved in proinsulin processing. To ascertain whether this heterogeneity is correlated with the level of expression of the prohormone and mature hormone, the expression of proinsulin, insulin, and PC1/3 in human beta cells was examined. This analysis identified a human beta cell type that expressed proinsulin but lacked PC1/3 (ProIN⁺PC1/3^-). This beta cell type is absent in rodent islets and is abundant in human islets of adults but scarce in islets from postnatal donors. Human islets also contained a beta cell type that expressed both proinsulin and variable levels of PC1/3 (ProIN⁺PC1/3⁺) and a less abundant cell type that lacked proinsulin but expressed the convertase (ProIN^-PC1/3⁺). These cell phenotypes were altered by type 2 diabetes. These data suggest that these three cell types represent different stages of a dynamic process with proinsulin folding in ProIN⁺PC1/3^- cells, proinsulin conversion into insulin in ProIN⁺PC1/3⁺cells, and replenishment of the proinsulin content in ProIN^-PC1/3⁺ cells.

Fructose Metabolism in Cancer

The interest in fructose metabolism is based on the observation that an increased dietary fructose consumption leads to an increased risk of obesity and metabolic syndrome. In particular, obesity is a known risk factor to develop many types of cancer and there is clinical and experimental evidence that an increased fructose intake promotes cancer growth. The precise mechanism, however, in which fructose induces tumor growth is still not fully understood. In this article, we present an overview of the metabolic pathways that utilize fructose and how fructose metabolism can sustain cancer cell proliferation. Although the degradation of fructose shares many of the enzymes and metabolic intermediates with glucose metabolism through glycolysis, glucose and fructose are metabolized differently. We describe the different metabolic fates of fructose carbons and how they are connected to lipogenesis and nucleotide synthesis. In addition, we discuss how the endogenous production of fructose from glucose via the polyol pathway can be beneficial for cancer cells.

Allomorphy as a mechanism of post-translational control of enzyme activity

Enzyme regulation is vital for metabolic adaptability in living systems. Fine control of enzyme activity is often delivered through post-translational mechanisms, such as allostery or allokairy. β-phosphoglucomutase (βPGM) from Lactococcus lactis is a phosphoryl transfer enzyme required for complete catabolism of trehalose and maltose, through the isomerisation of β-glucose 1-phosphate to glucose 6-phosphate via β-glucose 1,6-bisphosphate. Surprisingly for a gatekeeper of glycolysis, no fine control mechanism of βPGM has yet been reported. Herein, we describe allomorphy, a post-translational control mechanism of enzyme activity. In βPGM, isomerisation of the K145-P146 peptide bond results in the population of two conformers that have different activities owing to repositioning of the K145 sidechain. In vivo phosphorylating agents, such as fructose 1,6-bisphosphate, generate phosphorylated forms of both conformers, leading to a lag phase in activity until the more active phosphorylated conformer dominates. In contrast, the reaction intermediate β-glucose 1,6-bisphosphate, whose concentration depends on the β-glucose 1-phosphate concentration, couples the conformational switch and the phosphorylation step, resulting in the rapid generation of the more active phosphorylated conformer. In enabling different behaviours for different allomorphic activators, allomorphy allows an organism to maximise its responsiveness to environmental changes while minimising the diversion of valuable metabolites.

β-phosphoglucomutase (βPGM) from Lactococcus lactis is a phosphoryl transfer enzyme required for catabolism of trehalose and maltose. Coupled analyses of multiple βPGM structures and enzymatic activity lead to the proposal of allomorphy — a post-translational mechanism controlling enzyme activity.

Bioengineering of Microalgae: Recent Advances, Perspectives, and Regulatory Challenges for Industrial Application

Microalgae, due to their complex metabolic capacity, are being continuously explored for nutraceuticals, pharmaceuticals, and other industrially important bioactives. However, suboptimal yield and productivity of the bioactive of interest in local and robust wild-type strains are of perennial concerns for their industrial applications. To overcome such limitations, strain improvement through genetic engineering could play a decisive role. Though the advanced tools for genetic engineering have emerged at a greater pace, they still remain underused for microalgae as compared to other microorganisms. Pertaining to this, we reviewed the progress made so far in the development of molecular tools and techniques, and their deployment for microalgae strain improvement through genetic engineering. The recent availability of genome sequences and other omics datasets form diverse microalgae species have remarkable potential to guide strategic momentum in microalgae strain improvement program. This review focuses on the recent and significant improvements in the omics resources, mutant libraries, and high throughput screening methodologies helpful to augment research in the model and non-model microalgae. Authors have also summarized the case studies on genetically engineered microalgae and highlight the opportunities and challenges that are emerging from the current progress in the application of genome-editing to facilitate microalgal strain improvement. Toward the end, the regulatory and biosafety issues in the use of genetically engineered microalgae in commercial applications are described.

Metabolite sensing and signaling in cancer

Metabolites are not only substrates in metabolic reactions, but also signaling molecules controlling a wide range of cellular processes. Discovery of the oncometabolite 2-hydroxyglutarate provides an important link between metabolic dysfunction and cancer, unveiling the signaling function of metabolites in regulating epigenetic and epitranscriptomic modifications, genome integrity, and signal transduction. It is now known that cancer cells remodel their metabolic network to support biogenesis, caused by or resulting in the dysregulation of various metabolites. Cancer cells can sense alterations in metabolic intermediates to better coordinate multiple biological processes and enhance cell metabolism. Recent studies have demonstrated that metabolite signaling is involved in the regulation of malignant transformation, cell proliferation, epithelial-to-mesenchymal transition, differentiation blockade, and cancer stemness. Additionally, intercellular metabolite signaling modulates inflammatory response and immunosurveillance in the tumor microenvironment. Here, we review recent advances in cancer-associated metabolite signaling. An in depth understanding of metabolite signaling will provide new opportunities for the development of therapeutic interventions that target cancer.

Autocrine IFN-I inhibits isocitrate dehydrogenase in the TCA cycle of LPS-stimulated macrophages

Macrophage activation in response to LPS is coupled to profound metabolic changes, typified by accumulation of the TCA cycle intermediates citrate, itaconate, and succinate. We have identified that endogenous type I IFN controls the cellular citrate/α-ketoglutarate ratio and inhibits expression and activity of isocitrate dehydrogenase (IDH); and, via 13C-labeling studies, demonstrated that autocrine type I IFN controls carbon flow through IDH in LPS-activated macrophages. We also found that type I IFN-driven IL-10 contributes to inhibition of IDH activity and itaconate synthesis in LPS-stimulated macrophages. Our findings have identified the autocrine type I IFN pathway as being responsible for the inhibition of IDH in LPS-stimulated macrophages.

Differential Effects of Human Adenovirus E1A Protein Isoforms on Aerobic Glycolysis in A549 Human Lung Epithelial Cells

Viruses alter a multitude of host-cell processes to create a more optimal environment for viral replication. This includes altering metabolism to provide adequate substrates and energy required for replication. Typically, viral infections induce a metabolic phenotype resembling the Warburg effect, with an upregulation of glycolysis and a concurrent decrease in cellular respiration. Human adenovirus (HAdV) has been observed to induce the Warburg effect, which can be partially attributed to the adenovirus protein early region 4, open reading frame 1 (E4orf1). E4orf1 regulates a multitude of host-cell processes to benefit viral replication and can influence cellular metabolism through the transcription factor avian myelocytomatosis viral oncogene homolog (MYC). However, E4orf1 does not explain the full extent of Warburg-like HAdV metabolic reprogramming, especially the accompanying decrease in cellular respiration. The HAdV protein early region 1A (E1A) also modulates the function of the infected cell to promote viral replication. E1A can interact with a wide variety of host-cell proteins, some of which have been shown to interact with metabolic enzymes independently of an interaction with E1A. To determine if the HAdV E1A proteins are responsible for reprogramming cell metabolism, we measured the extracellular acidification rate and oxygen consumption rate of A549 human lung epithelial cells with constitutive endogenous expression of either of the two major E1A isoforms. This was followed by the characterization of transcript levels for genes involved in glycolysis and cellular respiration, and related metabolic pathways. Cells expressing the 13S encoded E1A isoform had drastically increased baseline glycolysis and lower maximal cellular respiration than cells expressing the 12S encoded E1A isoform. Cells expressing the 13S encoded E1A isoform exhibited upregulated expression of glycolysis genes and downregulated expression of cellular respiration genes. However, tricarboxylic acid cycle genes were upregulated, resembling anaplerotic metabolism employed by certain cancers. Upregulation of glycolysis and tricarboxylic acid cycle genes was also apparent in IMR-90 human primary lung fibroblast cells infected with a HAdV-5 mutant virus that expressed the 13S, but not the 12S encoded E1A isoform. In conclusion, it appears that the two major isoforms of E1A differentially influence cellular glycolysis and oxidative phosphorylation and this is at least partially due to the altered regulation of mRNA expression for the genes in these pathways.

Uncovering the Underlying Mechanisms of Cancer Metabolism through the Landscapes and Probability Flux Quantifications

Cancer metabolism is critical for understanding the mechanism of tumorigenesis, yet the understanding is still challenging. We studied gene-metabolism regulatory interactions and quantified the global driving forces for cancer-metabolism dynamics as the underlying landscape and probability flux. We uncovered four steady-state attractors: a normal state attractor, a cancer OXPHOS state attractor, a cancer glycolysis state attractor, and an intermediate cancer state attractor. We identified the key regulatory interactions through global sensitivity analysis based on the landscape topography. Different landscape topographies of glycolysis switch between normal cells and cancer cells were identified. We uncovered that the normal state to cancer state transformation is associated with the peaks of the probability flux and the thermodynamic dissipation, giving dynamical and thermodynamic origin of cancer formation. We found that cancer metabolism oscillations consume more energy to support cancer malignancy. This study provides a quantitative understanding of cancer metabolism and suggests a metabolic therapeutic strategy.

Dynamic 13C Flux Analysis Captures the Reorganization of Adipocyte Glucose Metabolism in Response to Insulin

Cellular metabolism is dynamic, but quantifying non-steady metabolic fluxes by stable isotope tracers presents unique computational challenges. Here, we developed an efficient 13C-tracer dynamic metabolic flux analysis (13C-DMFA) framework for modeling central carbon fluxes that vary over time. We used B-splines to generalize the flux parameterization system and to improve the stability of the optimization algorithm. As proof of concept, we investigated how 3T3-L1 cultured adipocytes acutely metabolize glucose in response to insulin. Insulin rapidly stimulates glucose uptake, but intracellular pathways responded with differing speeds and magnitudes. Fluxes in lower glycolysis increased faster than those in upper glycolysis. Glycolysis fluxes rose disproportionally larger and faster than the tricarboxylic acid cycle, with lactate a primary glucose end product. The uncovered array of flux dynamics suggests that glucose catabolism is additionally regulated beyond uptake to help shunt glucose into appropriate pathways. This work demonstrates the value of using dynamic intracellular fluxes to understand metabolic function and pathway regulation.

Glucose-6-Phosphate Upregulates Txnip Expression by Interacting With MondoA

The major metabolic fates of glucose in cells are glycolysis and the pentose phosphate pathway, and they share the first step: converting glucose to glucose-6-phosphate (G6P). Here, we show that G6P can be sensed by the transcription factor MondoA/Mlx to modulate Txnip expression. Endogenous knockdown and EMSA (gel migration assay) analyses both confirmed that G6P is the metabolic intermediate that activates the heterocomplex MondoA/Mlx to elicit the expression of Txnip. Additionally, the three-dimensional structure of MondoA is modeled, and the binding mode of G6P to MondoA is also predicted by in silico molecular docking and binding free energy calculation. Finally, free energy decomposition and mutational analyses suggest that certain residues in MondoA, GKL139-141 in particular, mediate its binding with G6P to activate MondoA, which signals the upregulation of the expression of Txnip.

Microbial energy management-A product of three broad tradeoffs

Wherever thermodynamics allows, microbial life has evolved to transform and harness energy. Microbial life thus abounds in the most unexpected places, enabled by profound metabolic diversity. Within this diversity, energy is transformed primarily through variations on a few core mechanisms. Energy is further managed by the physiological processes of cell growth and maintenance that use energy. Some aspects of microbial physiology are streamlined for energetic efficiency while other aspects seem suboptimal or even wasteful. We propose that the energy that a microbe harnesses and devotes to growth and maintenance is a product of three broad tradeoffs: (i) economic, trading enzyme synthesis or operational cost for functional benefit, (ii) environmental, trading optimization for a single environment for adaptability to multiple environments, and (iii) thermodynamic, trading energetic yield for forward metabolic flux. Consideration of these tradeoffs allows one to reconcile features of microbial physiology that seem to opposingly promote either energetic efficiency or waste.

Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses

Metabolomics aims to address what and how regulatory mechanisms are coordinated to achieve flux optimality, different metabolic objectives as well as appropriate adaptations to dynamic nutrient availability. Recent decades have witnessed that the integration of metabolomics and fluxomics within the goal of synthetic biology has arrived at generating the desired bioproducts with improved bioconversion efficiency. Absolute metabolite quantification by isotope dilution mass spectrometry represents a functional readout of cellular biochemistry and contributes to the establishment of metabolic (structured) models required in systems metabolic engineering. In industrial practices, population heterogeneity arising from fluctuating nutrient availability frequently leads to performance losses, that is reduced commercial metrics (titer, rate, and yield). Hence, the development of more stable producers and more predictable bioprocesses can benefit from a quantitative understanding of spatial and temporal cell-to-cell heterogeneity within industrial bioprocesses. Quantitative metabolomics analysis and metabolic modeling applied in computational fluid dynamics (CFD)-assisted scale-down simulators that mimic industrial heterogeneity such as fluctuations in nutrients, dissolved gases, and other stresses can procure informative clues for coping with issues during bioprocessing scale-up. In previous studies, only limited insights into the hydrodynamic conditions inside the industrial-scale bioreactor have been obtained, which makes case-by-case scale-up far from straightforward. Tracking the flow paths of cells circulating in large-scale bioreactors is a highly valuable tool for evaluating cellular performance in production tanks. The "lifelines" or "trajectories" of cells in industrial-scale bioreactors can be captured using Euler-Lagrange CFD simulation. This novel methodology can be further coupled with metabolic (structured) models to provide not only a statistical analysis of cell lifelines triggered by the environmental fluctuations but also a global assessment of the metabolic response to heterogeneity inside an industrial bioreactor. For the future, the industrial design should be dependent on the computational framework, and this integration work will allow bioprocess scale-up to the industrial scale with an end in mind.

Biomaterial-Based Metabolic Regulation in Regenerative Engineering

Recent advances in cell metabolism studies have deepened the appreciation of the role of metabolic regulation in influencing cell behavior during differentiation, angiogenesis, and immune response in the regenerative engineering scenarios. However, the understanding of whether the intracellular metabolic pathways could be influenced by material-derived cues remains limited, although it is now well appreciated that material cues modulate cell functions. Here, an overview of how the regulation of different aspect of cell metabolism, including energy homeostasis, oxygen homeostasis, and redox homeostasis could contribute to modulation of cell function is provided. Furthermore, recent evidence demonstrating how material cues, including the release of inherent metabolic factors (e.g., ions, regulatory metabolites, and oxygen), tuning of the biochemical cues (e.g., inherent antioxidant properties, cell adhesivity, and chemical composition of nanomaterials), and changing in biophysical cues (topography and surface stiffness), may impact cell metabolism toward modulated cell behavior are discussed. Based on the resurgence of interest in cell metabolism and metabolic regulation, further development of biomaterials enabling metabolic regulation toward dictating cell function is poised to have substantial implications for regenerative engineering.

Systematic mapping of protein-metabolite interactions in central metabolism of Escherichia coli

Metabolite binding to proteins regulates nearly all cellular processes, but our knowledge of these interactions originates primarily from empirical in vitro studies. Here, we report the first systematic study of interactions between water-soluble proteins and polar metabolites in an entire biological subnetwork. To test the depth of our current knowledge, we chose to investigate the well-characterized Escherichia coli central metabolism. Using ligand-detected NMR, we assayed 29 enzymes towards binding events with 55 intracellular metabolites. Focusing on high-confidence interactions at a false-positive rate of 5%, we detected 98 interactions, among which purine nucleotides accounted for one-third, while 50% of all metabolites did not interact with any enzyme. In contrast, only five enzymes did not exhibit any metabolite binding and some interacted with up to 11 metabolites. About 40% of the interacting metabolites were predicted to be allosteric effectors based on low chemical similarity to their target's reactants. For five of the eight tested interactions, in vitro assays confirmed novel regulatory functions, including ATP and GTP inhibition of the first pentose phosphate pathway enzyme. With 76 new candidate regulatory interactions that have not been reported previously, we essentially doubled the number of known interactions, indicating that the presently available information about protein-metabolite interactions may only be the tip of the iceberg.

Metabolomics Studies To Decipher Stress Responses in Mycobacterium smegmatis Point to a Putative Pathway of Methylated Amine Biosynthesis

Mycobacterium smegmatis, the saprophytic soil mycobacterium, is routinely used as a surrogate system to study the human pathogen Mycobacterium tuberculosis It has also been reported as an opportunistic pathogen in immunocompromised hosts. In addition, it can exist in several ecological setups, thereby suggesting its capacity to adapt to a variety of environmental cues. In this study, we employed untargeted proton nuclear magnetic resonance (¹H-NMR)-based metabolomics to identify metabolites and metabolic pathways critical for early adaptive responses to acidic stress, oxidative stress, and nutrient starvation in Mycobacterium smegmatis We identified 31, 20, and 46 metabolites that showed significant changes in levels in response to acidic, oxidative, and nutrient starvation stresses, respectively. Pathway analyses showed significant perturbations in purine-pyrimidine, amino-acid, nicotinate-nicotinamide, and energy metabolism pathways. Besides these, differential levels of intermediary metabolites involved in α-glucan biosynthesis pathway were observed. We also detected high levels of organic osmolytes, methylamine, and betaine during nutrient starvation and oxidative stress. Further, tracing the differential levels of these osmolytes through computational search tools, gene expression studies (using reverse transcription-PCR [RT-PCR]), and enzyme assays, we detected the presence of a putative pathway of biosynthesis of betaine, methylamine, and dimethylamine previously unreported in Mycobacterium smegmatis IMPORTANCE Alterations in metabolite levels provide fast and direct means to regulate enzymatic reactions and, therefore, metabolic pathways. This study documents, for the first time, the metabolic changes that occur in Mycobacterium smegmatis as a response to three stresses, namely, acidic stress, oxidative stress, and nutrient starvation. These stresses are also faced by intracellular mycobacteria during infection and therefore may be extended to frame therapeutic interventions for pathogenic mycobacteria. In addition to the purine-pyrimidine, amino acid, nicotinate-nicotinamide, and energy metabolism pathways that were found to be affected in response to different stresses, a novel putative methylamine biosynthesis pathway was identified to be present in Mycobacterium smegmatis.

Niche-specific metabolic adaptation in biotrophic and necrotrophic oomycetes is manifested in differential use of nutrients, variation in gene content, and enzyme evolution

The use of host nutrients to support pathogen growth is central to disease. We addressed the relationship between metabolism and trophic behavior by comparing metabolic gene expression during potato tuber colonization by two oomycetes, the hemibiotroph Phytophthora infestans and the necrotroph Pythium ultimum. Genes for several pathways including amino acid, nucleotide, and cofactor biosynthesis were expressed more by Ph. infestans during its biotrophic stage compared to Py. ultimum. In contrast, Py. ultimum had higher expression of genes for metabolizing compounds that are normally sequestered within plant cells but released to the pathogen upon plant cell lysis, such as starch and triacylglycerides. The transcription pattern of metabolic genes in Ph. infestans during late infection became more like that of Py. ultimum, consistent with the former's transition to necrotrophy. Interspecific variation in metabolic gene content was limited but included the presence of γ-amylase only in Py. ultimum. The pathogens were also found to employ strikingly distinct strategies for using nitrate. Measurements of mRNA, ¹⁵N labeling studies, enzyme assays, and immunoblotting indicated that the assimilation pathway in Ph. infestans was nitrate-insensitive but induced during amino acid and ammonium starvation. In contrast, the pathway was nitrate-induced but not amino acid-repressed in Py. ultimum. The lack of amino acid repression in Py. ultimum appears due to the absence of a transcription factor common to fungi and Phytophthora that acts as a nitrogen metabolite repressor. Evidence for functional diversification in nitrate reductase protein was also observed. Its temperature optimum was adapted to each organism's growth range, and its K_m was much lower in Py. ultimum. In summary, we observed divergence in patterns of gene expression, gene content, and enzyme function which contribute to the fitness of each species in its niche.

A key feature of disease is the pathogen's consumption of host metabolites to support its growth and multiplication. Understanding how host nutrients are used by pathogens may lead to strategies for limiting disease, for example by developing inhibitors of metabolic pathways needed for pathogen growth. Feeding strategies of plant pathogens range between two extremes: necrotrophs kill host cells and consume the released nutrients, while biotrophs do not injure host cells but instead acquire nutrients from extracellular spaces in the plant. In this study, a comparison was made between the metabolism of Phytophthora infestans (the infamous Irish Famine pathogen) and Pythium ultimum during potato tuber colonization. These microbes have close evolutionary histories, but while Py. ultimum is a necrotroph, Ph. infestans is a biotroph for most of the disease cycle. It was discovered that distinct patterns of metabolic gene expression, gene content, and enzyme behavior underlie these lifestyles. For example, genes for utilizing compounds that are normally stored within plant cells were expressed more by Py. ultimum, while Ph. infestans appeared to synthesize more biosubstances from precursors. Several differences in carbon and nitrogen metabolism were linked to variation in enzyme content and gene expression regulators in the two species.

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.

Regulatory Networks Governing Methionine Catabolism into Volatile Organic Sulfur-Containing Compounds in Clonostachys rosea

Adaptation to environmental perturbations requires living systems to coordinately regulate signaling pathways, gene expression, and metabolism. To better understand the mechanisms underlying adaptation, the regulatory nodes within networks must be elucidated. Here, ARO8-2 (which encodes an aminotransferase), PDC (which encodes a decarboxylase), and STR3 (which encodes a demethiolase) were identified as key genes involved in the catabolism of methionine in the mycoparasitic fungus Clonostachys rosea, isolated from Tuber melanosporum ascocarps. Exogenous Met induced the transcription of ARO8-2 and PDC but repressed the transcription of STR3, which is controlled by the putative MSN2 and GLN3 binding sites responding to nitrogen catabolite repression. Met and its structural derivatives function as glutamine synthetase inhibitors, resulting in the downregulation of STR3 expression. The putative GLN3 binding site was necessary for STR3 downregulation. In Saccharomyces cerevisiae, Met and its structural derivatives also triggered downregulation of demethiolase gene expression. Altogether, the results indicated that exogenous Met triggered nitrogen catabolite repression, which stimulated the Ehrlich pathway and negatively regulated the demethiolation pathway via the methionine sulfoximine-responsive regulatory pathway. This finding revealed the regulatory nodes within the networks controlling the catabolism of Met into volatile organic sulfur-containing compounds, thereby enhancing our understanding of adaptation.IMPORTANCE Methionine shuttles organic nitrogen and plays a central role in nitrogen metabolism. Exogenous Met strongly induces the expression of ARO8-2 and PDC, represses the expression of STR3, and generates volatile organic sulfur-containing compounds via the Ehrlich and demethiolation pathways. In this study, we used genetic, bioinformatic, and metabolite-based analyses to confirm that transcriptional control of the aminotransferase gene ARO8-2, the decarboxylase gene PDC, and the demethiolase gene STR3 modulates Met catabolism into volatile organic sulfur-containing compounds. Importantly, we found that, in addition to the Ehrlich pathway, the demethiolation pathway was regulated by a nitrogen catabolite repression-sensitive regulatory pathway that controlled the transcription of genes required to catabolize poor nitrogen sources. This work significantly advances our understanding of nitrogen catabolite repression-sensitive transcriptional regulation of sulfur-containing amino acid catabolism and provides a basis for engineering Met catabolism pathways for the production of fuel and valuable flavor alcohols.

Real Time Monitoring of NADPH Concentrations in Corynebacterium glutamicum and Escherichia coli via the Genetically Encoded Sensor mBFP

Analyses of intracellular NADPH concentrations are prerequisites for the design of microbial production strains and process optimization. mBFP was described as metagenomics derived, blue fluorescent protein showing NADPH-dependent fluorescence. Characterization of mBFP showed a high specificity for binding of NADPH (K_D 0.64 mM) and no binding of NADH, the protein exclusively amplified fluorescence of NADPH. mBFP catalyzed the NADPH-dependent reduction of benzaldehyde and further aldehydes, which fits to its classification as short chain dehydrogenase. For in vivo NADPH analyses a codon-optimized gene for mBFP was introduced into Corynebacterium glutamicum WT and the phosphoglucoisomerase-deficient strain C. glutamicum Δpgi, which accumulates high levels of NADPH. For determination of intracellular NADPH concentrations by mBFP a calibration method with permeabilized cells was developed. By this means an increase of intracellular NADPH concentrations within seconds after the addition of glucose to nutrient-starved cells of both C. glutamicum WT and C. glutamicum Δpgi was observed; as expected the internal NADPH concentration was significantly higher for C. glutamicum Δpgi (0.31 mM) when compared to C. glutamicum WT (0.19 mM). Addition of paraquat to E. coli cells carrying mBFP led as expected to an immediate decrease of intracellular NADPH concentrations, showing the versatile use of mBFP as intracellular sensor.