Cellular concentrations of enzymes and their substrates

A single microfluidic device for multi-omics analysis sample preparation

Combining different "omics" approaches, such as genomics and proteomics, is necessary to generate a detailed and complete insight into microbiome comprehension. Proper sample collection and processing and accurate analytical methods are crucial in generating reliable data. We previously developed the ChipFilter device for proteomic analysis of microbial samples. We have shown that this device coupled to LC-MS/MS can successfully be used to identify microbial proteins. In the present work, we have developed our workflow to analyze concomitantly proteins and nucleic acids from the same sample. We performed lysis and proteolysis in the device using cultures of E. coli, B. subtilis, and S. cerevisiae. After peptide recovery for LC-MS/MS analysis, DNA from the same samples was recovered and successfully amplified by PCR for the 3 species. This workflow was further extended to a complex microbial mixture of known compositions. Protein analysis was carried out, enabling the identification of more than 5000 proteins. The recovered DNA was sequenced, performing comparable to DNA extracted with a commercial kit without proteolysis. Our results show that the ChipFilter device is suited to prepare samples for parallel proteomic and genomic analyses, which is particularly relevant in the case of low-abundant samples and drastically reduces sampling bias.

A possible origin of life in nonpolar environments

Explaining the emergence of life is perhaps the central and most challenging question in modern science. We are proposing a new hypothesis concerning the origins of life. The new hypothesis is based on the assumption that during the emergence of life, evolution had to first involve autocatalytic systems which only subsequently acquired the capacity of genetic heredity. Additionally, the key abiotic and early biotic molecules required in the formation of early life, like cofactors, coenzymes, nucleic bases, prosthetic groups, polycyclic aromatic hydrocarbons (PAHs), some pigments, etc. are poorly soluble in aqueous media. To avoid the latter concentration problem, the new hypothesis assumes that life could have emerged in the nonpolar environments or low water systems, or at the interphase of the nonpolar and polar water phase, from where it was subsequently transferred to the aqueous environment. To support our hypothesis, we assume that hydrocarbons and oil on the Earth have abiotic origins.

Tracking fructose 1,6-bisphosphate dynamics in liver cancer cells using a fluorescent biosensor

HYlight is a genetically encoded fluorescent biosensor that ratiometrically monitors fructose 1,6-bisphosphate (FBP), a key glycolytic metabolite. Given the role of glucose in liver cancer metabolism, we expressed HYlight in human liver cancer cells and primary mouse hepatocytes. Through in vitro, in silico, and in cellulo experiments, we showed HYlight's ability to monitor FBP changes linked to glycolysis, not gluconeogenesis. HYlight's affinity for FBP was ∼1 μM and stable within physiological pH range. HYlight demonstrated weak binding to dihydroxyacetone phosphate, and its ratiometric response was influenced by both ionic strength and phosphate. Therefore, simulating cytosolic conditions in vitro was necessary to establish a reliable correlation between HYlight's cellular responses and FBP concentrations. FBP concentrations were found to be in the lower micromolar range, far lower than previous millimolar estimates. Altogether, this biosensor approach offers real-time monitoring of FBP concentrations at single-cell resolution, making it an invaluable tool for the understanding of cancer metabolism.

Structures, mechanisms, and kinetic advantages of the SgrAI filament forming mechanism

This review documents investigations leading to the unprecedented discovery of filamentation as a mode of enzyme regulation in the type II restriction endonuclease SgrAI. Filamentation is defined here as linear or helical polymerization of a single enzyme as occurs for SgrAI, and has now been shown to occur in many other enzyme systems, including conserved metabolic enzymes. In the case of SgrAI, filamentation activates the DNA cleavage rate by up to 1000-fold and also alters the enzyme's DNA sequence specificity. The investigations began with the observation that SgrAI cleaves two types of recognition sequences, primary and secondary, but cleaves the secondary sequences only when present on the same DNA as at least one primary. DNA cleavage rate measurements showed how the primary sequence is both a substrate and an allosteric effector of SgrAI. Biophysical measurements indicated that the activated form of SgrAI, stimulated by binding to the primary sequence, consisted of varied numbers of the SgrAI bound to DNA. Structural studies revealed the activated state of SgrAI as a left-handed helical filament which stabilizes an altered enzyme conformation, which binds a second divalent cation in the active site. Efforts to determine the mechanism of DNA sequence specificity alteration are ongoing and current models are discussed. Finally, global kinetic modeling of the filament mediated DNA cleavage reaction and simulations of in vivo activity suggest that the filament mechanism evolved to rapidly cleave invading DNA while protecting the Streptomyces host genome.

Speed-Energy-Efficiency Trade-off in Hsp70 Chaperone System

Proteins must fold into their native structure to carry out cellular functions. However, they can sometimes misfold into non-native structures, leading to reduced efficiency or malfunction. Chaperones help prevent misfolding by guiding proteins to their active state using energy from ATP hydrolysis. Experiments have revealed numerous kinetic and structural aspects of how various chaperones facilitate the folding of proteins into their native structure. However, what remains missing is a fundamental theoretical understanding of their operational mechanisms, especially the limits and constraints imposed on their efficiency by energy flow and dissipation. To address this, we built a kinetic model of the Hsp70 chaperone system by incorporating all key structural and kinetic details. Then, using the chemical kinetic equations, we investigate how energy expenditure shapes the efficiency of Hsp70 chaperones in the proper folding of misfolded proteins. We show that ATP consumption by chaperones significantly enhances the folding of proteins into their native states. Our investigations reveal that a chaperone achieves optimal efficiency when its binding to misfolded proteins is much faster than the misfolding kinetics of that protein. We also demonstrate the presence of an upper bound on a chaperone's efficiency of protein folding and its overall rescue rate. This upper bound increases with energy dissipation until it reaches a saturation point. Furthermore, we show a speed-energy-efficiency trade-off in chaperone action, demonstrating that it is impossible to simultaneously optimize the efficiency of chaperone-assisted protein folding and the energy efficiency of the process.

Reconstruction and analyses of genome-scale halomonas metabolic network yield a highly efficient PHA production

In pursuit of reliable and efficient industrial microbes, this study integrates cutting-edge systems biology tools with Halomonas bluephagenesis TD01, a robust halophilic bacterium. We generated the complete and annotated circular genome sequence for this model organism, constructed and meticulously curated a genome-scale metabolic network, achieving striking 86.32% agreement with Biolog Phenotype Microarray data and visualize the network via an interactive Electron/Thrift server architecture. We then analyzed the genome-scale network using vertex sampling analysis (VSA) and found that productions of biomass, polyhydroxyalkanoates (PHA), citrate, acetate, and pyruvate are mutually competing. Recognizing the dynamic nature of H. bluephagenesis TD01, we further developed and implemented the hyper-cube-shrink-analysis (HCSA) framework to predict effects of nutrient availabilities and metabolic reactions in the model on biomass and PHA accumulation. We then, based on the analysis results, proposed and validate multi-step feeding strategies tailored to different fermentation stages. This integrated approach yielded remarkable results, with fermentation culminating in a cell dry weight of 100.4 g/L and 70% PHA content, surpassing previous benchmarks. Our findings exemplify the powerful potential of system-level tools in the design and optimization of industrial microorganisms, paving the way for more efficient and sustainable bio-based processes.

A comparative analysis of NADPH supply strategies in Saccharomyces cerevisiae: Production of d-xylitol from d-xylose as a case study

Enhancing the supply of the redox cofactor NADPH in metabolically engineered cells is a critical target for optimizing the synthesis of many product classes, such as fatty acids or terpenoids. In S. cerevisiae, several successful approaches have been developed in different experimental contexts. However, their systematic comparison has not been reported. Here, we established the reduction of xylose to xylitol by an NADPH-dependent xylose reductase as a model reaction to compare the efficacy of different NADPH supply strategies in the course of a batch fermentation, in which glucose and ethanol are sequentially used as carbon sources and redox donors. We show that strains overexpressing the glucose-6-phosphate dehydrogenase Zwf1 perform best, producing up to 16.9 g L-1 xylitol from 20 g L-1 xylose in stirred tank bioreactors. The beneficial effect of increased Zwf1 activity is especially pronounced during the ethanol consumption phase. The same notion applies to the deletion of the aldehyde dehydrogenase ALD6 gene, albeit at a quantitatively lower level. Reduced expression of the phosphoglucose isomerase Pgi1 and heterologous expression of the NADP+-dependent glyceraldehyde-3-phosphate dehydrogenase Gdp1 from Kluyveromyces lactis acted synergistically with ZWF1 overexpression in the presence of glucose, but had a detrimental effect after the diauxic shift. Expression of the mitochondrial NADH kinase Pos5 in the cytosol likewise improved the production of xylitol only on glucose, but not in combination with enhanced Zwf1 activity. To demonstrate the generalizability of our observations, we show that the most promising strategies - ZWF1 overexpression and deletion of ALD6 - also improve the production of l-galactonate from d-galacturonic acid. Therefore, we expect that these findings will provide valuable guidelines for engineering not only the production of xylitol but also of diverse other pathways that require NADPH.

Beyond IC50-A computational dynamic model of drug resistance in enzyme inhibition treatment

Resistance to therapy is a major clinical obstacle to treatment of cancer and communicable diseases. Drug selection in treatment of patients where the disease is showing resistance to therapy is often guided by IC50 or fold-IC50 values. In this work, through a model of the treatment of chronic myeloid leukaemia (CML), we contest using fold-IC50 values as a guide for treatment selection. CML is a blood cancer that is treated with Abl1 inhibitors, and is often seen as a model for targeted therapy and drug resistance. Resistance to the first-line treatment occurs in approximately one in four patients. The most common cause of resistance is mutations in the Abl1 enzyme. Different mutant Abl1 enzymes show resistance to different Abl1 inhibitors and the mechanisms that lead to resistance for various mutation and inhibitor combinations are not fully known, making the selection of Abl1 inhibitors for treatment a difficult task. We developed a model based on information of catalysis, inhibition and pharmacokinetics, and applied it to study the effect of three Abl1 inhibitors on mutants of the Abl1 enzyme. From this model, we show that the relative decrease of product formation rate (defined in this work as "inhibitory reduction prowess") is a better indicator of resistance than an examination of the size of the product formation rate or fold-IC50 values for the mutant. We also examine current ideas and practices that guide treatment choice and suggest a new parameter for selecting treatments that could increase the efficacy and thus have a positive impact on patient outcomes.

Development of Malate Biosensor-Containing Hydrogels and Living Cell-Based Sensors

Malate is a key intermediate in the citric acid cycle, an enzymatic cascade that is central to cellular energy metabolism and that has been applied to make biofuel cells. To enable real-time sensing of malate levels, we have engineered a genetically encoded, protein-based fluorescent biosensor called Malon specifically responsive to malate by performing structure-based mutagenesis of the Cache-binding domain of the Citron GFP-based biosensor. Malon demonstrates high specificity and fluorescence activation in response to malate, and has been applied to monitor enzymatic reactions in vitro. Furthermore, we successfully incorporated Malon into redox polymer hydrogels and bacterial cells, enabling analysis of malate levels in these materials and living systems. These results show the potential for fluorescent biosensors in enzymatic cascade monitoring within biomaterials and present Malon as a novel tool for bioelectronic devices.

RidA proteins contribute to fitness of S. enterica and E. coli by reducing 2AA stress and moderating flux to isoleucine biosynthesis

Defining the physiological role of a gene product relies on interpreting phenotypes caused by the lack, or alteration, of the respective gene product. Mutations in critical genes often lead to easily recognized phenotypes that can include changes in cellular growth, metabolism, structure etc. However, mutations in many important genes may fail to generate an obvious defect unless additional perturbations are caused by medium or genetic background. The latter scenario is exemplified by RidA proteins. In vitro RidA proteins deaminate numerous imine/enamines, including those generated by serine/threonine dehydratase IlvA (EC:4.3.1.19) from serine or threonine - 2-aminoacrylate (2AA) and 2-aminocrotonate (2AC), respectively. Despite this demonstrable biochemical activity, a lack of RidA has little to no effect on growth of E. coli or S. enterica without the application of additional metabolic perturbation. A cellular role of RidA is to prevent accumulation of 2AA which, if allowed to persist, can irreversibly damage pyridoxal 5'-phosphate (PLP)-dependent enzymes, causing global metabolic stress. Because the phenotypes caused by a lack of RidA are dependent on the unique structure of each metabolic network, the link between RidA function and 2AA stress is difficult to demonstrate in some organisms. The current study used coculture experiments to exacerbate differences in growth caused by the lack of RidA in S. enterica and E. coli. Results described here solidify the established role of RidA in removing 2AA, while also presenting evidence for a role of RidA in enhancing flux towards isoleucine biosynthesis in E. coli. Overall, these data emphasize that metabolic networks can generate distinct responses to perturbation, even when the individual components are conserved.

Strangers in a foreign land: 'Yeastizing' plant enzymes

Expressing plant metabolic pathways in microbial platforms is an efficient, cost-effective solution for producing many desired plant compounds. As eukaryotic organisms, yeasts are often the preferred platform. However, expression of plant enzymes in a yeast frequently leads to failure because the enzymes are poorly adapted to the foreign yeast cellular environment. Here, we first summarize the current engineering approaches for optimizing performance of plant enzymes in yeast. A critical limitation of these approaches is that they are labour-intensive and must be customized for each individual enzyme, which significantly hinders the establishment of plant pathways in cellular factories. In response to this challenge, we propose the development of a cost-effective computational pipeline to redesign plant enzymes for better adaptation to the yeast cellular milieu. This proposition is underpinned by compelling evidence that plant and yeast enzymes exhibit distinct sequence features that are generalizable across enzyme families. Consequently, we introduce a data-driven machine learning framework designed to extract 'yeastizing' rules from natural protein sequence variations, which can be broadly applied to all enzymes. Additionally, we discuss the potential to integrate the machine learning model into a full design-build-test cycle.

Aging of the eye: Lessons from cataracts and age-related macular degeneration

Aging is the greatest risk factor for chronic human diseases, including many eye diseases. Geroscience aims to understand the effects of the aging process on these diseases, including the genetic, molecular, and cellular mechanisms that underlie the increased risk of disease over the lifetime. Understanding of the aging eye increases general knowledge of the cellular physiology impacted by aging processes at various biological extremes. Two major diseases, age-related cataract and age-related macular degeneration (AMD) are caused by dysfunction of the lens and retina, respectively. Lens transparency and light refraction are mediated by lens fiber cells lacking nuclei and other organelles, which provides a unique opportunity to study a single aging hallmark, i.e., loss of proteostasis, within an environment of limited metabolism. In AMD, local dysfunction of the photoreceptors/retinal pigmented epithelium/Bruch's membrane/choriocapillaris complex in the macula leads to the loss of photoreceptors and eventually loss of central vision, and is driven by nearly all the hallmarks of aging and shares features with Alzheimer's disease, Parkinson's disease, cardiovascular disease, and diabetes. The aging eye can function as a model for studying basic mechanisms of aging and, vice versa, well-defined hallmarks of aging can be used as tools to understand age-related eye disease.

Polyamines (PAs) but not small peptides with closely spaced positively charged groups interact with DNA and RNA, but they do not represent a relevant buffer system at physiological pH values

Polyamines (PAs) including putrescine (PUT), spermidine (SPD) and spermine (SPM) are small, versatile molecules with two or more positively charged amino groups. Despite their importance for almost all forms of life, their specific roles in molecular and cellular biology remain partly unknown. The molecular structures of PAs suggest two presumable biological functions: (i) as potential buffer systems and (ii) as interactants with poly-negatively charged molecules like nucleic acids. The present report focuses on the question, whether the molecular structures of PAs are essential for such functions, or whether other simple molecules like small peptides with closely spaced positively charged side chains might be suitable as well. Consequently, we created titration curves for PUT, SPD, and SPM, as well as for oligolysines like tri-, tetra-, and penta-lysine. None of the molecules provided substantial buffering capacity at physiological intracellular pH values. Apparently, the most important mechanism for intracellular pH homeostasis in neurons is not a buffer system but is provided by the actions of the sodium-hydrogen and the bicarbonate-chloride antiporters. In a similar approach we investigated the interaction with DNA by following the extinction at 260 nm when titrating DNA with the above molecules. Again, PUT and tri-lysine were not able to interact with herring sperm DNA, while SPD and SPM were. Obviously, the presence of several positively charged groups on its own is not sufficient for the interaction with nucleic acids. Instead, the precise spacing of these groups is necessary for biological activity.

Kinetic modeling of leucine-mediated signaling and protein metabolism in human skeletal muscle

Skeletal muscle protein levels are governed by the relative rates of muscle protein synthesis (MPS) and breakdown (MPB). The mechanisms controlling these rates are complex, and their integrated behaviors are challenging to study through experiments alone. The purpose of this study was to develop and analyze a kinetic model of leucine-mediated mTOR signaling and protein metabolism in the skeletal muscle of young adults. Our model amalgamates published cellular-level models of the IRS1-PI3K-Akt-mTORC1 signaling system and of skeletal-muscle leucine kinetics with physiological-level models of leucine digestion and transport and insulin dynamics. The model satisfactorily predicts experimental data from diverse leucine feeding protocols. Model analysis revealed that total levels of p70S6K are a primary determinant of MPS, insulin signaling substantially affects muscle net protein balance via its effects on MPB, and p70S6K-mediated feedback of mTORC1 signaling reduces MPS in a dose-dependent manner.

Future of the Search for Life: Workshop Report

The 2-week, virtual Future of the Search for Life science and engineering workshop brought together more than 100 scientists, engineers, and technologists in March and April 2022 to provide their expert opinion on the interconnections between life-detection science and technology. Participants identified the advances in measurement and sampling technologies they believed to be necessary to perform in situ searches for life elsewhere in our Solar System, 20 years or more in the future. Among suggested measurements for these searches, those pertaining to three potential indicators of life termed "dynamic disequilibrium," "catalysis," and "informational polymers" were identified as particularly promising avenues for further exploration. For these three indicators, small breakout groups of participants identified measurement needs and knowledge gaps, along with corresponding constraints on sample handling (acquisition and processing) approaches for a variety of environments on Enceladus, Europa, Mars, and Titan. Despite the diversity of these environments, sample processing approaches all tend to be more complex than those that have been implemented on missions or envisioned for mission concepts to date. The approaches considered by workshop breakout groups progress from nondestructive to destructive measurement techniques, and most involve the need for fluid (especially liquid) sample processing. Sample processing needs were identified as technology gaps. These gaps include technology and associated sampling strategies that allow the preservation of the thermal, mechanical, and chemical integrity of the samples upon acquisition; and to optimize the sample information obtained by operating suites of instruments on common samples. Crucially, the interplay between science-driven life-detection strategies and their technological implementation highlights the need for an unprecedented level of payload integration and extensive collaboration between scientists and engineers, starting from concept formulation through mission deployment of life-detection instruments and sample processing systems.

Structural and functional complexity of HSP90 in cellular homeostasis and disease

Heat shock protein 90 (HSP90) is a chaperone with vital roles in regulating proteostasis, long recognized for its function in protein folding and maturation. A view is emerging that identifies HSP90 not as one protein that is structurally and functionally homogeneous but, rather, as a protein that is shaped by its environment. In this Review, we discuss evidence of multiple structural forms of HSP90 in health and disease, including homo-oligomers and hetero-oligomers, also termed epichaperomes, and examine the impact of stress, post-translational modifications and co-chaperones on their formation. We describe how these variations influence context-dependent functions of HSP90 as well as its interaction with other chaperones, co-chaperones and proteins, and how this structural complexity of HSP90 impacts and is impacted by its interaction with small molecule modulators. We close by discussing recent developments regarding the use of HSP90 inhibitors in cancer and how our new appreciation of the structural and functional heterogeneity of HSP90 invites a re-evaluation of how we discover and implement HSP90 therapeutics for disease treatment.

Organic Catalytic Activity as a Method for Agnostic Life Detection

An ideal life detection instrument would have high sensitivity but be insensitive to abiotic processes and would be capable of detecting life with alternate molecular structures. In this study, we propose that catalytic activity can be the basis of a nearly ideal life detection instrument. There are several advantages to catalysis as an agnostic life detection method. Demonstrating catalysis does not necessarily require culturing/growing the alien life and in fact may persist even in dead biomass for some time, and the amplification by catalysis is large even by minute amounts of catalysts and, hence, can be readily detected against abiotic background rates. In specific, we propose a hydrolytic catalysis detection instrument that could detect activity in samples of extraterrestrial organic material from unknown life. The instrument uses chromogenic assay-based detection of various hydrolytic catalytic activities, which are matched to corresponding artificial substrates having the same, chromogenic (preferably fluorescent) upon release, group; D- and L-enantiomers of these substrates can be used to also answer the question whether unknown life is chiral. Since catalysis is a time-proportional product-concentration amplification process, hydrolytic catalytic activity can be measured on a sample of even a minute size, and with instruments based on, for example, optofluidic chip technology.

Modeling of glycosaminoglycan biosynthesis in intervertebral disc cells

Loss of proteoglycan (PG) is a potential factor responsible for degeneration of the intervertebral disc (IVD). PG consists of a core protein with covalently attached glycosaminoglycan (GAG) chains. The objective of this study was to develop a mathematical model of GAG biosynthesis to investigate the effects of glycolytic enzymes on GAG biosynthesis of IVD cells. A new mathematical model of GAG biosynthesis was developed for IVD cells by incorporating biosynthesis of uridine diphosphate-sugars into the glycolytic pathway. This new model showed good agreement between the model predictions of intracellular ATP content and GAG biosynthesis and experimental data measured at different external glucose levels. The quantitative analyses demonstrated that GAG biosynthesis may be sensitive to the activities of hexokinase (HK) and phosphofructokinase (PFK), especially at low glucose supply, with GAG biosynthesis being significantly enhanced by a slight increase in activities of HK and PFK. This suggests that metabolic reprogramming could be a potential strategy for promoting PG biosynthesis in IVD cells. Furthermore, it was shown that GAG biosynthesis may be promoted by increasing intracellular glutamine concentration or activity of glutamine:fructose-6-phosphate amidotransferase in the hexamine pathway. This study provides a better understanding of the relationship between glycolysis and PG biosynthesis in IVD cells. The theoretical framework developed in this study is useful for studying the role of glycolysis in disc degeneration and developing new preventive and treatment strategies for degeneration of the IVD.

Changing biosynthesis of terpenoid percursors in rice through synthetic biology

Many highly valued chemicals in the pharmaceutical, biotechnological, cosmetic, and biomedical industries belong to the terpenoid family. Biosynthesis of these chemicals relies on polymerization of Isopentenyl di-phosphate (IPP) and/or dimethylallyl diphosphate (DMAPP) monomers, which plants synthesize using two alternative pathways: a cytosolic mevalonic acid (MVA) pathway and a plastidic methyleritritol-4-phosphate (MEP) pathway. As such, developing plants for use as a platform to use IPP/DMAPP and produce high value terpenoids is an important biotechnological goal. Still, IPP/DMAPP are the precursors to many plant developmental hormones. This creates severe challenges in redirecting IPP/DMAPP towards production of non-cognate plant metabolites. A potential solution to this problem is increasing the IPP/DMAPP production flux in planta. Here, we aimed at discovering, understanding, and predicting the effects of increasing IPP/DMAPP production in plants through modelling. We used synthetic biology to create rice lines containing an additional ectopic MVA biosynthetic pathway for producing IPP/DMAPP. The rice lines express three alternative versions of the additional MVA pathway in the plastid, in addition to the normal endogenous pathways. We collected data for changes in macroscopic and molecular phenotypes, gene expression, isoprenoid content, and hormone abundance in those lines. To integrate the molecular and macroscopic data and develop a more in depth understanding of the effects of engineering the exogenous pathway in the mutant rice lines, we developed and analyzed data-centric, line-specific, multilevel mathematical models. These models connect the effects of variations in hormones and gene expression to changes in macroscopic plant phenotype and metabolite concentrations within the MVA and MEP pathways of WT and mutant rice lines. Our models allow us to predict how an exogenous IPP/DMAPP biosynthetic pathway affects the flux of terpenoid precursors. We also quantify the long-term effect of plant hormones on the dynamic behavior of IPP/DMAPP biosynthetic pathways in seeds, and predict plant characteristics, such as plant height, leaf size, and chlorophyll content from molecular data. In addition, our models are a tool that can be used in the future to help in prioritizing re-engineering strategies for the exogenous pathway in order to achieve specific metabolic goals.

How much (ATP) does it cost to build a trypanosome? A theoretical study on the quantity of ATP needed to maintain and duplicate a bloodstream-form Trypanosoma brucei cell

ATP hydrolysis is required for the synthesis, transport and polymerization of monomers for macromolecules as well as for the assembly of the latter into cellular structures. Other cellular processes not directly related to synthesis of biomass, such as maintenance of membrane potential and cellular shape, also require ATP. The unicellular flagellated parasite Trypanosoma brucei has a complex digenetic life cycle. The primary energy source for this parasite in its bloodstream form (BSF) is glucose, which is abundant in the host's bloodstream. Here, we made a detailed estimation of the energy budget during the BSF cell cycle. As glycolysis is the source of most produced ATP, we calculated that a single parasite produces 6.0 x 1011 molecules of ATP/cell cycle. Total biomass production (which involves biomass maintenance and duplication) accounts for ~63% of the total energy budget, while the total biomass duplication accounts for the remaining ~37% of the ATP consumption, with in both cases translation being the most expensive process. These values allowed us to estimate a theoretical YATP of 10.1 (g biomass)/mole ATP and a theoretical [Formula: see text] of 28.6 (g biomass)/mole ATP. Flagellar motility, variant surface glycoprotein recycling, transport and maintenance of transmembrane potential account for less than 30% of the consumed ATP. Finally, there is still ~5.5% available in the budget that is being used for other cellular processes of as yet unknown cost. These data put a new perspective on the assumptions about the relative energetic weight of the processes a BSF trypanosome undergoes during its cell cycle.

Diffusion NMR and Rheology of a Model Polymer in Bacterial Cell Lysate Crowders

The intracellular milieu is crowded and heterogeneous, and this can have profound consequences for biomolecule motions and biochemical kinetics. Macromolecular crowding has been traditionally studied in artificial crowders like Ficoll and dextran or globular proteins such as bovine serum albumin. It is, however, not clear if the effects of artificial crowders on such phenomena are the same as the crowding that is experienced in a heterogeneous biological environment. Bacterial cells, for example, are composed of heterogeneous biomolecules with different sizes, shapes, and charges. Using crowders composed of one of three different pretreatments of bacterial cell lysate (unmanipulated, ultracentrifuged, and anion exchanged), we examine the effects of crowding on the diffusivity of a model polymer. We measure the translational diffusivity, via diffusion NMR, of the test polymer polyethylene glycol (PEG) in these bacterial cell lysates. We show that the small (R_g ∼ 5 nm) test polymer shows a modest decrease in self-diffusivity with increasing crowder concentration for all lysate treatments. The corresponding self-diffusivity decrease in the artificial Ficoll crowder is much more pronounced. Moreover, a comparison of the rheological response of biological and artificial crowders shows that while the artificial crowder Ficoll exhibits a Newtonian response even at high concentrations, the bacterial cell lysate is markedly non-Newtonian; it behaves like a shear-thinning fluid with a yield stress. While at any concentration the rheological properties are sensitive to both lysate pretreatment and batch-to-batch variations, the PEG diffusivity is nearly unaffected by the type of lysate pretreatment.

Dosage balance acts as a time-dependent selective barrier to subfunctionalization

BACKGROUND

Gene duplication is an important process for genome expansion, sometimes allowing for new gene functions to develop. Duplicate genes can be retained through multiple processes, either for intermediate periods of time through processes such as dosage balance, or over extended periods of time through processes such as subfunctionalization and neofunctionalization.

RESULTS

Here, we built upon an existing subfunctionalization Markov model by incorporating dosage balance to describe the interplay between subfunctionalization and dosage balance to explore selective pressures on duplicate copies. Our model incorporates dosage balance using a biophysical framework that penalizes the fitness of genetic states with stoichiometrically imbalanced proteins. These imbalanced states cause increased concentrations of exposed hydrophobic surface areas, which cause deleterious mis-interactions. We draw comparison between our Subfunctionalization + Dosage-Balance Model (Sub + Dos) and the previous Subfunctionalization-Only (Sub-Only) Model. This comparison includes how the retention probabilities change over time, dependent upon the effective population size and the selective cost associated with spurious interaction of dosage-imbalanced partners. We show comparison between Sub-Only and Sub + Dos models for both whole-genome duplication and small-scale duplication events.

CONCLUSION

These comparisons show that following whole-genome duplication, dosage balance serves as a time-dependent selective barrier to the subfunctionalization process, by causing an overall delay but ultimately leading to a larger portion of the genome retained through subfunctionalization. This higher percentage of the genome that is ultimately retained is caused by the alternative competing process, nonfunctionalization, being selectively blocked to a greater extent. In small-scale duplication, the reverse pattern is seen, where dosage balance drives faster rates of subfunctionalization, but ultimately leads to a smaller portion of the genome retained as duplicates. This faster rate of subfunctionalization is because the dosage balance of interacting gene products is negatively affected immediately after duplication and the loss of a duplicate restores the stoichiometric balance. Our findings provide support that the subfunctionalization of genes that are susceptible to dosage balance effects, such as proteins involved in complexes, is not a purely neutral process. With stronger selection against stoichiometrically imbalanced gene partners, the rates of subfunctionalization and nonfunctionalization slow; however, this ultimately leads to a greater proportion of subfunctionalized gene pairs.

Quantitative chemometric phenotyping of three-dimensional liver organoids by Raman spectral imaging

Confocal Raman spectral imaging (RSI) enables high-content, label-free visualization of a wide range of molecules in biological specimens without sample preparation. However, reliable quantification of the deconvoluted spectra is needed. Here we develop an integrated bioanalytical methodology, qRamanomics, to qualify RSI as a tissue phantom calibrated tool for quantitative spatial chemotyping of major classes of biomolecules. Next, we apply qRamanomics to fixed 3D liver organoids generated from stem-cell-derived or primary hepatocytes to assess specimen variation and maturity. We then demonstrate the utility of qRamanomics for identifying biomolecular response signatures from a panel of liver-altering drugs, probing drug-induced compositional changes in 3D organoids followed by in situ monitoring of drug metabolism and accumulation. Quantitative chemometric phenotyping constitutes an important step in developing quantitative label-free interrogation of 3D biological specimens.

Impact of Negative Feedbacks on De Novo Pyrimidines Biosynthesis in Escherichia coli

Earlier studies aimed at investigating the metabolism of endogenous nucleoside triphosphates in synchronous cultures of E. coli cells revealed an auto-oscillatory mode of functioning of the pyrimidine and purine nucleotide biosynthesis system, which the authors associated with the dynamics of cell division. Theoretically, this system has an intrinsic oscillatory potential, since the dynamics of its functioning are controlled through feedback mechanisms. The question of whether the nucleotide biosynthesis system has its own oscillatory circuit is still open. To address this issue, an integral mathematical model of pyrimidine biosynthesis was developed, taking into account all experimentally verified negative feedback in the regulation of enzymatic reactions, the data of which were obtained under in vitro conditions. Analysis of the dynamic modes of the model functioning has shown that in the pyrimidine biosynthesis system, both the steady-state and oscillatory functioning modes can be realized under certain sets of kinetic parameters that fit in the physiological boundaries of the investigated metabolic system. It has been demonstrated that the occurrence of the oscillatory nature of metabolite synthesis depended on the ratio of two parameters: the Hill coefficient, h_UMP1-the nonlinearity of the UMP effect on the activity of carbamoyl-phosphate synthetase, and the parameter r characterizing the contribution of the noncompetitive mechanism of UTP inhibition to the regulation of the enzymatic reaction of UMP phosphorylation. Thus, it has been theoretically shown that the E. coli pyrimidine biosynthesis system possesses its own oscillatory circuit whose oscillatory potential depends to a significant degree on the mechanism of regulation of UMP kinase activity.

LOXL2-dependent deacetylation of aldolase A induces metabolic reprogramming and tumor progression

Lysyl-oxidase like-2 (LOXL2) regulates extracellular matrix remodeling and promotes tumor invasion and metastasis. Altered metabolism is a core hallmark of cancer, however, it remains unclear whether and how LOXL2 contributes to tumor metabolism. Here, we found that LOXL2 and its catalytically inactive L2Δ13 splice variant boost glucose metabolism of esophageal tumor cells, facilitate tumor cell proliferation and promote tumor development in vivo. Consistently, integrated transcriptomic and metabolomic analysis of a knock-in mouse model expressing L2Δ13 gene revealed that LOXL2/L2Δ13 overexpression perturbs glucose and lipid metabolism. Mechanistically, we identified aldolase A, glyceraldehyde-3-phosphate dehydrogenase and enolase as glycolytic proteins that interact physically with LOXL2 and L2Δ13. In the case of aldolase A, LOXL2/L2Δ13 stimulated its mobilization from the actin cytoskeleton to enhance aldolase activity during malignant transformation. Using stable isotope labeling of amino acids in cell culture (SILAC) followed by proteomic analysis, we identified LOXL2 and L2Δ13 as novel deacetylases that trigger metabolic reprogramming. Both LOXL2 and L2Δ13 directly catalyzed the deacetylation of aldolase A at K13, resulting in enhanced glycolysis which subsequently reprogramed tumor metabolism and promoted tumor progression. High level expression of LOXL2/L2Δ13 combined with decreased acetylation of aldolase-K13 predicted poor clinical outcome in patients with esophageal cancer. In summary, we have characterized a novel molecular mechanism that mediates the pro-tumorigenic activity of LOXL2 independently of its classical amine oxidase activity. These findings may enable the future development of therapeutic agents targeting the metabolic machinery via LOXL2 or L2Δ13. HIGHLIGHT OF THE STUDY: LOXL2 and its catalytically inactive isoform L2Δ13 function as new deacetylases to promote metabolic reprogramming and tumor progression in esophageal cancer by directly activating glycolytic enzymes such as aldolase A.

Global and gene-specific translational regulation in Escherichia coli across different conditions

How well mRNA transcript levels represent protein abundances has been a controversial issue. Particularly across different environments, correlations between mRNA and protein exhibit remarkable variability from gene to gene. Translational regulation is likely to be one of the key factors contributing to mismatches between mRNA level and protein abundance in bacteria. Here, we quantified genome-wide transcriptome and relative translation efficiency (RTE) under 12 different conditions in Escherichia coli. By quantifying the mRNA-RTE correlation both across genes and across conditions, we uncovered a diversity of gene-specific translational regulations, cooperating with transcriptional regulations, in response to carbon (C), nitrogen (N), and phosphate (P) limitations. Intriguingly, we found that many genes regulating translation are themselves subject to translational regulation, suggesting possible feedbacks. Furthermore, a random forest model suggests that codon usage partially predicts a gene's cross-condition variability in translation efficiency; such cross-condition variability tends to be an inherent quality of a gene, independent of the specific nutrient limitations. These findings broaden the understanding of translational regulation under different environments and provide novel strategies for the control of translation in synthetic biology. In addition, our data offers a resource for future multi-omics studies.

Reconstruction and Analysis of Thermodynamically Constrained Models Reveal Metabolic Responses of a Deep-Sea Bacterium to Temperature Perturbations

Microbial acclimation to different temperature conditions can involve broad changes in cell composition and metabolic efficiency. A systems-level view of these metabolic responses in nonmesophilic organisms, however, is currently missing. In this study, thermodynamically constrained genome-scale models were applied to simulate the metabolic responses of a deep-sea psychrophilic bacterium, Shewanella psychrophila WP2, under suboptimal (4°C), optimal (15°C), and supraoptimal (20°C) growth temperatures. The models were calibrated with experimentally determined growth rates of WP2. Gibbs free energy change of reactions (Δ_rG'), metabolic fluxes, and metabolite concentrations were predicted using random simulations to characterize temperature-dependent changes in the metabolism. The modeling revealed the highest metabolic efficiency at the optimal temperature, and it suggested distinct patterns of ATP production and consumption that could lead to lower metabolic efficiency under suboptimal or supraoptimal temperatures. The modeling also predicted rearrangement of fluxes through multiple metabolic pathways, including the glycolysis pathway, Entner-Doudoroff pathway, tricarboxylic acid (TCA) cycle, and electron transport system, and these predictions were corroborated through comparisons to WP2 transcriptomes. Furthermore, predictions of metabolite concentrations revealed the potential conservation of reducing equivalents and ATP in the suboptimal temperature, consistent with experimental observations from other psychrophiles. Taken together, the WP2 models provided mechanistic insights into the metabolism of a psychrophile in response to different temperatures. IMPORTANCE Metabolic flexibility is a central component of any organism's ability to survive and adapt to changes in environmental conditions. This study represents the first application of thermodynamically constrained genome-scale models in simulating the metabolic responses of a deep-sea psychrophilic bacterium to various temperatures. The models predicted differences in metabolic efficiency that were attributed to changes in metabolic pathway utilization and metabolite concentration during growth under optimal and nonoptimal temperatures. Experimental growth measurements were used for model calibration, and temperature-dependent transcriptomic changes corroborated the model-predicted rearrangement of metabolic fluxes. Overall, this study highlights the utility of modeling approaches in studying the temperature-driven metabolic responses of an extremophilic organism.

Loss of RPTPγ primes breast tissue for acid extrusion, promotes malignant transformation and results in early tumour recurrence and shortened survival

BACKGROUND

While cellular metabolism and acidic waste handling accelerate during breast carcinogenesis, temporal patterns of acid-base regulation and underlying molecular mechanisms responding to the tumour microenvironment remain unclear.

METHODS

We explore data from human cohorts and experimentally investigate transgenic mice to evaluate the putative extracellular HCO₃^--sensor Receptor Protein Tyrosine Phosphatase (RPTP)γ during breast carcinogenesis.

RESULTS

RPTPγ expression declines during human breast carcinogenesis and particularly in high-malignancy grade breast cancer. Low RPTPγ expression associates with poor prognosis in women with Luminal A or Basal-like breast cancer. RPTPγ knockout in mice favours premalignant changes in macroscopically normal breast tissue, accelerates primary breast cancer development, promotes malignant breast cancer histopathologies, and shortens recurrence-free survival. In RPTPγ knockout mice, expression of Na⁺,HCO₃^--cotransporter NBCn1-a breast cancer susceptibility protein-is upregulated in normal breast tissue but, contrary to wild-type mice, shows no further increase during breast carcinogenesis. Associated augmentation of Na⁺,HCO₃^--cotransport in normal breast tissue from RPTPγ knockout mice elevates steady-state intracellular pH, which has known pro-proliferative effects.

CONCLUSIONS

Loss of RPTPγ accelerates cellular net acid extrusion and elevates NBCn1 expression in breast tissue. As these effects precede neoplastic manifestations in histopathology, we propose that RPTPγ-dependent enhancement of Na⁺,HCO₃^--cotransport primes breast tissue for cancer development.

Dynamics and growth rate implications of ribosomes and mRNAs interaction in E. coli

Understanding how cells grow and adapt under various nutrient conditions is pivotal in the study of biological stoichiometry. Recent studies provide empirical evidence that cells use multiple strategies to maintain an optimal protein production rate under different nutrient conditions. Mathematical models can provide a solid theoretical foundation that can explain experimental observations and generate testable hypotheses to further our understanding of the growth process. In this study, we generalize a modeling framework that centers on the translation process and study its asymptotic behaviors to validate algebraic manipulations involving the steady states. Using experimental results on the growth of E. coli under C-, N-, and P-limited environments, we simulate the expected quantitative measurements to show the feasibility of using the model to explain empirical evidence. Our results support the findings that cells employ multiple strategies to maintain a similar protein production rate across different nutrient limitations. Moreover, we find that the previous study underestimates the significance of certain biological rates, such as the binding rate of ribosomes to mRNA and the transition rate between different ribosomal stages. Furthermore, our simulation shows that the strategies used by cells under C- and P-limitations result in a faster overall growth dynamics than under N-limitation. In conclusion, the general modeling framework provides a valuable platform to study cell growth under different nutrient supply conditions, which also allows straightforward extensions to the coupling of transcription, translation, and energetics to deepen our understanding of the growth process.

Full humanization of the glycolytic pathway in Saccharomyces cerevisiae

Although transplantation of single genes in yeast plays a key role in elucidating gene functionality in metazoans, technical challenges hamper humanization of full pathways and processes. Empowered by advances in synthetic biology, this study demonstrates the feasibility and implementation of full humanization of glycolysis in yeast. Single gene and full pathway transplantation revealed the remarkable conservation of glycolytic and moonlighting functions and, combined with evolutionary strategies, brought to light context-dependent responses. Human hexokinase 1 and 2, but not 4, required mutations in their catalytic or allosteric sites for functionality in yeast, whereas hexokinase 3 was unable to complement its yeast ortholog. Comparison with human tissues cultures showed preservation of turnover numbers of human glycolytic enzymes in yeast and human cell cultures. This demonstration of transplantation of an entire essential pathway paves the way for establishment of species-, tissue-, and disease-specific metazoan models.

Dynamics and Sensitivity of Signaling Pathways

Purpose of Review

Signaling pathways serve to communicate information about extracellular conditions into the cell, to both the nucleus and cytoplasmic processes to control cell responses. Genetic mutations in signaling network components are frequently associated with cancer and can result in cells acquiring an ability to divide and grow uncontrollably. Because signaling pathways play such a significant role in cancer initiation and advancement, their constituent proteins are attractive therapeutic targets. In this review, we discuss how signaling pathway modeling can assist with identifying effective drugs for treating diseases, such as cancer. An achievement that would facilitate the use of such models is their ability to identify controlling biochemical parameters in signaling pathways, such as molecular abundances and chemical reaction rates, because this would help determine effective points of attack by therapeutics.

Recent Findings

We summarize the current state of understanding the sensitivity of phosphorylation cycles with and without sequestration. We also describe some basic properties of regulatory motifs including feedback and feedforward regulation.

Summary

Although much recent work has focused on understanding the dynamics and particularly the sensitivity of signaling networks in eukaryotic systems, there is still an urgent need to build more scalable models of signaling networks that can appropriately represent their complexity across different cell types and tumors.

How many molecules of mitochondrial complex I are in a cell?

Mitochondrial complex I is the only enzyme responsible for oxidation of matrix NADH and regeneration of NAD+ for catabolism. Nuclear and mtDNA mutations, assembly impairments, and enzyme damage are implicated in inherited diseases, ischemia-reperfusion injury, neurodegeneration, and tumorogenesis. Here we introduce a novel method to measure the absolute content of complex I. The method is based on flavin fluorescence scanning of a polyacrylamide gel after separation of complexes by Clear Native electrophoresis. Using mouse primary astrocytes as an example, we calculated an average value of 2.2 × 105 complex I molecules/cell. Our method can be used for accurate quantification of complex I content.

Multisite Enzymes as a Mechanism for Bistability in Reaction Networks

Here, we focus on a common class of enzymes that have multiple substrate binding sites (multisite enzymes) and analyze their capacity to generate bistable dynamics in the reaction networks that they are embedded in. These networks include both substrate-product-substrate cycles and substrate-to-product conversion with subsequent product consumption. Using mathematical techniques, we show that the inherent binding and catalysis reactions arising from multiple substrate-enzyme complexes create a potential for bistable dynamics in such reaction networks. We construct a generic model of an enzyme with n-substrate binding sites and derive an analytical solution for the steady-state concentration of all enzyme-substrate complexes. By studying these expressions, we obtain a mechanistic understanding of bistability, derive parameter combinations that guarantee bistability, and show how changing specific enzyme kinetic parameters and enzyme levels can lead to bistability in reaction networks involving multisite enzymes. Thus, the presented findings provide a biochemical and mathematical basis for predicting and engineering bistability in multisite enzymes.

Beyond the Michaelis-Menten: Bayesian Inference for Enzyme Kinetic Analysis

Although the Michaelis-Menten (MM) rate law has been widely used to estimate enzyme kinetic parameters, it works only under the condition of extremely low enzyme concentration. Furthermore, even when this condition is satisfied, parameter estimation is often imprecise due to the parameter identifiability issue. To overcome these limitations of the canonical approach to enzyme kinetics, we developed a Bayesian approach based on a modified form of the MM rate law, which is derived with the total quasi-steady state approximation. Here, we illustrate how to perform the Bayesian inference for the progress curve assay with our user-friendly computational R package. We also describe an optimal experimental design for the progress curve assay, with which enzyme kinetic parameters can be accurately and precisely estimated from minimal measurements of the progress curves.

Roles of metal ions in the selective inhibition of oncogenic variants of isocitrate dehydrogenase 1

Cancer linked isocitrate dehydrogenase (IDH) 1 variants, notably R132H IDH1, manifest a 'gain-of-function' to reduce 2-oxoglutarate to 2-hydroxyglutarate. High-throughput screens have enabled clinically useful R132H IDH1 inhibitors, mostly allosteric binders at the dimer interface. We report investigations on roles of divalent metal ions in IDH substrate and inhibitor binding that rationalise this observation. Mg2+/Mn2+ ions enhance substrate binding to wt IDH1 and R132H IDH1, but with the former manifesting lower Mg2+/Mn2+ KMs. The isocitrate-Mg2+ complex is the preferred wt IDH1 substrate; with R132H IDH1, separate and weaker binding of 2-oxoglutarate and Mg2+ is preferred. Binding of R132H IDH1 inhibitors at the dimer interface weakens binding of active site Mg2+ complexes; their potency is affected by the Mg2+ concentration. Inhibitor selectivity for R132H IDH1 over wt IDH1 substantially arises from different stabilities of wt and R132H IDH1 substrate-Mg2+ complexes. The results reveal the importance of substrate-metal ion complexes in wt and R132H IDH1 catalysis and the basis for selective R132H IDH1 inhibition. Further studies on roles of metal ion complexes in TCA cycle and related metabolism, including from an evolutionary perspective, are of interest.

Energy metabolism design of the striated muscle cell

The design of the energy metabolism system in striated muscle remains a major area of investigation. Here, we review our current understanding and emerging hypotheses regarding the metabolic support of muscle contraction. Maintenance of ATP free energy, so called energy homeostasis, via mitochondrial oxidative phosphorylation is critical to sustained contractile activity, and this major design criterion is the focus of this review. Cell volume invested in mitochondria reduces the space available for generating contractile force, and this spatial balance between mitochondria acontractile elements to meet the varying sustained power demands across muscle types is another important design criterion. This is accomplished with remarkably similar mass-specific mitochondrial protein composition across muscle types, implying that it is the organization of mitochondria within the muscle cell that is critical to supporting sustained muscle function. Beyond the production of ATP, ubiquitous distribution of ATPases throughout the muscle requires rapid distribution of potential energy across these large cells. Distribution of potential energy has long been thought to occur primarily through facilitated metabolite diffusion, but recent analysis has questioned the importance of this process under normal physiological conditions. Recent structural and functional studies have supported the hypothesis that the mitochondrial reticulum provides a rapid energy distribution system via the conduction of the mitochondrial membrane potential to maintain metabolic homeostasis during contractile activity. We extensively review this aspect of the energy metabolism design contrasting it with metabolite diffusion models and how mitochondrial structure can play a role in the delivery of energy in the striated muscle.

Queueing theory model of Krebs cycle

MOTIVATION

Queueing theory can be effective in simulating biochemical reactions taking place in living cells, and the article paves a step toward development of a comprehensive model of cell metabolism. Such a model could help to accelerate and reduce costs for developing and testing investigational drugs reducing number of laboratory animals needed to evaluate drugs.

RESULTS

The article presents a Krebs cycle model based on queueing theory. The model allows for tracking of metabolites concentration changes in real time. To validate the model, a drug-induced inhibition affecting activity of enzymes involved in Krebs cycle was simulated and compared with available experimental data.

AVAILABILITYAND IMPLEMENTATION

The source code is freely available for download at https://github.com/UTP-WTIiE/KrebsCycleUsingQueueingTheory, implemented in C# supported in Linux or MS Windows.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Frequency-preference response in covalent modification cycles under substrate sequestration conditions

Covalent modification cycles (CMCs) are basic units of signaling systems and their properties are well understood. However, their behavior has been mostly characterized in situations where the substrate is in excess over the modifying enzymes. Experimental data on protein abundance suggest that the enzymes and their target proteins are present in comparable concentrations, leading to substrate sequestration by the enzymes. In this enzyme-in-excess regime, CMCs have been shown to exhibit signal termination, the ability of the product to return to a stationary value lower than its peak in response to constant stimulation, while this stimulation is still active, with possible implications for the ability of systems to adapt to environmental inputs. We characterize the conditions leading to signal termination in CMCs in the enzyme-in-excess regime. We also demonstrate that this behavior leads to a preferred frequency response (band-pass filters) when the cycle is subjected to periodic stimulation, whereas the literature reports that CMCs investigated so far behave as low-pass filters. We characterize the relationship between signal termination and the preferred frequency response to periodic inputs and we explore the dynamic mechanism underlying these phenomena. Finally, we describe how the behavior of CMCs is reflected in similar types of responses in the cascades of which they are part. Evidence of protein abundance in vivo shows that enzymes and substrates are present in comparable concentrations, thus suggesting that signal termination and frequency-preference response to periodic inputs are also important dynamic features of cell signaling systems, which have been overlooked.

Development of red genetically encoded biosensor for visualization of intracellular glucose dynamics

Glucose is the main source of energy for organisms, and it is important to understand the spatiotemporal dynamics of intracellular glucose. Single fluorescent protein-based glucose indicators, named "Red Glifons" have been developed that apply to live-cell and dual-color imaging. These indicators exhibited more than 3-fold increase in fluorescence intensity in the presence of 10 mM glucose. The two Red Glifons developed have different half-maximal effective concentration (EC₅₀) values for glucose (300 μM and 3,000 μM) and are able to monitor a wide range of glucose dynamics. Red Glifon combined with green indicators allowing visualization of the interplay between glucose and ATP, lactate, or pyruvate. Glucose influx in the pharyngeal muscle of Caenorhabditis elegans, enteroendocrine cells, and human iPS cell-derived cardiac myocytes was observed using the Red Glifons. Thus these red glucose indicators serve as a multi-color imaging toolkit for investigating complex interactions in energy metabolism.

Resource uptake and the evolution of moderately efficient enzymes

Enzymes speed up reactions that would otherwise be too slow to sustain the metabolism of selfreplicators. Yet, most enzymes seem only moderately efficient, exhibiting kinetic parameters orders of magnitude lower than their expected physically achievable maxima and spanning over surprisingly large ranges of values. Here, we question how these parameters evolve using a mechanistic model where enzyme efficiency is a key component of individual competition for resources. We show that kinetic parameters are under strong directional selection only up to a point, above which enzymes appear to evolve under near-neutrality, thereby confirming the qualitative observation of other modeling approaches. While the existence of a large fitness plateau could potentially explain the extensive variation in enzyme features reported, we show using a population genetics model that such a widespread distribution is an unlikely outcome of evolution on a common landscape, as mutation–selection–drift balance occupy a narrow area even when very moderate biases towards lower efficiency are considered. Instead, differences in the evolutionary context encountered by each enzyme should be involved, such that each evolves on an individual, unique landscape. Our results point to drift and effective population size playing an important role, along with the kinetics of nutrient transporters, the tolerance to high concentrations of intermediate metabolites, and the reversibility of reactions. Enzyme concentration also shapes selection on kinetic parameters, but we show that the joint evolution of concentration and efficiency does not yield extensive variance in evolutionary outcomes when documented costs to protein expression are applied.

Stable Transfection of the Singlet Oxygen Photosensitizing Protein SOPP3: Examining Aspects of Intracellular Behavior†

Protein-encased chromophores that photosensitize the production of reactive oxygen species, ROS, have been the center of recent activity in studies of oxidative stress. One potential attribute of such systems is that the local environment surrounding the chromophore, and that determines the chromophore's photophysics, ideally remains constant and independent of the global environment into which the system is placed. Therefore, a protein-encased sensitizer localized in the mitochondria would arguably have the same photophysics as that protein-encased sensitizer at the plasma membrane, for example. One thus obtains a useful tool to study processes modulated by spatially localized ROS. One ROS of interest is singlet oxygen, O₂ (a¹ Δ_g ). We recently developed a singlet oxygen photosensitizing protein, SOPP, in which flavin mononucleotide, FMN, is encased in a re-engineered light-oxygen-voltage protein. One goal was to ascertain how a version of this system, SOPP3, which selectively makes O₂ (a¹ Δ_g ), in vitro, behaves in a cell. We now demonstrate that SOPP3 undergoes exacerbated irradiation-mediated bleaching when expressed at either the plasma membrane or mitochondria in stable cell lines. We find that the environment around the SOPP3 system affects the bleaching rate, which argues against one of the key suppositions in support of a protein-encased chromophore.

Enzyme free energy profiles: Can substrate binding be nonspontaneous? Can ground state interactions enhance catalysis?

Two influential enzymological theories were proposed in the late 1970s - that catalytic power stems only from transition state stabilization, while ground state interactions are either irrelevant or inhibitory; and enzyme substrate binding is nonspontaneous at low substrate concentrations ([S]₀ << K_m). I show here that ground state destabilization can be a very effective source of catalytic power, especially at high substrate concentrations, and enzyme-substrate binding thermodynamics are independent of initial substrate concentration. Binding free energy ranges from negative (spontaneous) under pre-steady state conditions up to a maximum of zero at steady state. Nonspontaneous binding can only occur under standard state conditions when c° is defined to be less than K_m.

An acidic residue buried in the dimer interface of isocitrate dehydrogenase 1 (IDH1) helps regulate catalysis and pH sensitivity

Isocitrate dehydrogenase 1 (IDH1) catalyzes the reversible NADP+-dependent conversion of isocitrate to α-ketoglutarate (αKG) to provide critical cytosolic substrates and drive NADPH-dependent reactions like lipid biosynthesis and glutathione regeneration. In biochemical studies, the forward reaction is studied at neutral pH, while the reverse reaction is typically characterized in more acidic buffers. This led us to question whether IDH1 catalysis is pH-regulated, which would have functional implications under conditions that alter cellular pH, like apoptosis, hypoxia, cancer, and neurodegenerative diseases. Here, we show evidence of catalytic regulation of IDH1 by pH, identifying a trend of increasing kcat values for αKG production upon increasing pH in the buffers we tested. To understand the molecular determinants of IDH1 pH sensitivity, we used the pHinder algorithm to identify buried ionizable residues predicted to have shifted pKa values. Such residues can serve as pH sensors, with changes in protonation states leading to conformational changes that regulate catalysis. We identified an acidic residue buried at the IDH1 dimer interface, D273, with a predicted pKa value upshifted into the physiological range. D273 point mutations had decreased catalytic efficiency and, importantly, loss of pH-regulated catalysis. Based on these findings, we conclude that IDH1 activity is regulated, at least in part, by pH. We show this regulation is mediated by at least one buried acidic residue ∼12 Å from the IDH1 active site. By establishing mechanisms of regulation of this well-conserved enzyme, we highlight catalytic features that may be susceptible to pH changes caused by cell stress and disease.

Arabidopsis Carboxylesterase 20 Binds Strigolactone and Increases Branches and Tillers When Ectopically Expressed in Arabidopsis and Maize

Severe drought stress can delay maize silk emergence relative to the pollen shedding period, resulting in poor fertilization and reduced grain yield. Methods to minimize the delay in silking could thus improve yield stability. An Arabidopsis enhancer-tagged carboxylesterase 20 (AtCXE20) line was identified in a drought tolerance screen. Ectopic expression of AtCXE20 in Arabidopsis and maize resulted in phenotypes characteristic of strigolactone (SL)-deficient mutants, including increased branching and tillering, decreased plant height, delayed senescence, hyposensitivity to ethylene, and reduced flavonols. Maize silk growth was increased by AtCXE20 overexpression, and this phenotype was partially complemented by exogenous SL treatments. In drought conditions, the transgenic maize plants silked earlier than controls and had decreased anthesis-silking intervals. The purified recombinant AtCXE20 protein bound SL in vitro, as indicated by SL inhibiting AtCXE20 esterase activity and altering AtCXE20 intrinsic fluorescence. Homology modeling of the AtCXE20 three-dimensional (3D) protein structure revealed a large hydrophobic binding pocket capable of accommodating, but not hydrolyzing SLs. The AtCXE20 protein concentration in transgenic maize tissues was determined by mass spectrometry to be in the micromolar range, well-above known endogenous SL concentrations. These results best support a mechanism where ectopic expression of AtCXE20 with a strong promoter effectively lowers the concentration of free SL by sequestration. This study revealed an agriculturally important role for SL in maize silk growth and provided a new approach for altering SL levels in plants.

Structural distinctions between NAD+ riboswitch domains 1 and 2 determine differential folding and ligand binding

Riboswitches are important gene regulatory elements frequently encountered in bacterial mRNAs. The recently discovered nadA riboswitch contains two similar, tandemly arrayed aptamer domains, with the first domain possessing high affinity for nicotinamide adenine dinucleotide (NAD⁺). The second domain which comprises the ribosomal binding site in a putative regulatory helix, however, has withdrawn from detection of ligand-induced structural modulation thus far, and therefore, the identity of the cognate ligand and the regulation mechanism have remained unclear. Here, we report crystal structures of both riboswitch domains, each bound to NAD⁺. Furthermore, we demonstrate that ligand binding to domain 2 requires significantly higher concentrations of NAD⁺ (or ADP retaining analogs) compared to domain 1. Using a fluorescence spectroscopic approach, we further shed light on the structural features which are responsible for the different ligand affinities, and describe the Mg²⁺-dependent, distinct folding and pre-organization of their binding pockets. Finally, we speculate about possible scenarios for nadA RNA gene regulation as a putative two-concentration sensor module for a time-controlled signal that is primed and stalled by the gene regulation machinery at low ligand concentrations (domain 1), and finally triggers repression of translation as soon as high ligand concentrations are reached in the cell (domain 2).

ATP utilization by a DEAD-box protein during refolding of a misfolded group I intron ribozyme

DEAD-box helicase proteins perform ATP-dependent rearrangements of structured RNAs throughout RNA biology. Short RNA helices are unwound in a single ATPase cycle, but the ATP requirement for more complex RNA structural rearrangements is unknown. Here we measure the amount of ATP used for native refolding of a misfolded group I intron ribozyme by CYT-19, a Neurospora crassa DEAD-box protein that functions as a general chaperone for mitochondrial group I introns. By comparing the rates of ATP hydrolysis and ribozyme refolding, we find that several hundred ATP molecules are hydrolyzed during refolding of each ribozyme molecule. After subtracting nonproductive ATP hydrolysis that occurs in the absence of ribozyme refolding, we find that approximately 100 ATPs are hydrolyzed per refolded RNA as a consequence of interactions specific to the misfolded ribozyme. This value is insensitive to changes in ATP and CYT-19 concentration and decreases with decreasing ribozyme stability. Because of earlier findings that ∼90% of global ribozyme unfolding cycles lead back to the kinetically preferred misfolded conformation and are not observed, we estimate that each global unfolding cycle consumes ∼10 ATPs. Our results indicate that CYT-19 functions as a general RNA chaperone by using a stochastic, energy-intensive mechanism to promote RNA unfolding and refolding, suggesting an evolutionary convergence with protein chaperones.

Transomics analysis reveals allosteric and gene regulation axes for altered hepatic glucose-responsive metabolism in obesity

Impaired glucose tolerance associated with obesity causes postprandial hyperglycemia and can lead to type 2 diabetes. To study the differences in liver metabolism in healthy and obese states, we constructed and analyzed transomics glucose-responsive metabolic networks with layers for metabolites, expression data for metabolic enzyme genes, transcription factors, and insulin signaling proteins from the livers of healthy and obese mice. We integrated multiomics time course data from wild-type and leptin-deficient obese (ob/ob) mice after orally administered glucose. In wild-type mice, metabolic reactions were rapidly regulated within 10 min of oral glucose administration by glucose-responsive metabolites, which functioned as allosteric regulators and substrates of metabolic enzymes, and by Akt-induced changes in the expression of glucose-responsive genes encoding metabolic enzymes. In ob/ob mice, the majority of rapid regulation by glucose-responsive metabolites was absent. Instead, glucose administration produced slow changes in the expression of carbohydrate, lipid, and amino acid metabolic enzyme-encoding genes to alter metabolic reactions on a time scale of hours. Few regulatory events occurred in both healthy and obese mice. Thus, our transomics network analysis revealed that regulation of glucose-responsive liver metabolism is mediated through different mechanisms in healthy and obese states. Rapid changes in allosteric regulators and substrates and in gene expression dominate the healthy state, whereas slow changes in gene expression dominate the obese state.

Competitive effects in bacterial mRNA decay

In living organisms, the same enzyme catalyses the degradation of thousands of different mRNAs, but the possible influence of competing substrates has been largely ignored so far. We develop a simple mechanistic model of the coupled degradation of all cell mRNAs using the total quasi-steady-state approximation of the Michaelis-Menten framework. Numerical simulations of the model using carefully chosen parameters and analyses of rate sensitivity coefficients show how substrate competition alters mRNA decay. The model predictions reproduce and explain a number of experimental observations on mRNA decay following transcription arrest, such as delays before the onset of degradation, the occurrence of variable degradation profiles with increased non linearities and the negative correlation between mRNA half-life and concentration. The competition acts at different levels, through the initial concentration of cell mRNAs and by modifying the enzyme affinity for its targets. The consequence is a global slow down of mRNA decay due to enzyme titration and the amplification of its apparent affinity. Competition happens to stabilize weakly affine mRNAs and to destabilize the most affine ones. We believe that this mechanistic model is an interesting alternative to the exponential models commonly used for the determination of mRNA half-lives. It allows analysing regulatory mechanisms of mRNA degradation and its predictions are directly comparable to experimental data.