Determination of the cytosolic free NAD/NADH ratio in Saccharomyces cerevisiae under steady-state and highly dynamic conditions

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.

An industrial perspective on metabolic responses of Penicillium chrysogenum to periodic dissolved oxygen feast-famine cycles in a scale-down system

While traveling through different zones in large-scale bioreactors, microbes are most likely subjected to fluctuating dissolved oxygen (DO) conditions at the timescales of global circulation time. In this study, to mimic industrial-scale spatial DO gradients, we present a scale-down setup based on dynamic feast/famine regime (150 s) that leads to repetitive cycles with rapid changes in DO availability in glucose-limited chemostat cultures of Penicillium chrysogenum. Such DO feast/famine regime induced a stable and repetitive pattern with a reproducible metabolic response in time, and the dynamic response of intracellular metabolites featured specific differences in terms of both coverage and magnitude in comparison to other dynamic conditions, for example, substrate feast/famine cycles. Remarkably, intracellular sugar polyols were considerably increased as the hallmark metabolites along with a dynamic and higher redox state (NADH/NAD+) of the cytosol. Despite the increased availability of NADPH for penicillin production under the oscillatory DO conditions, this positive effect may be counteracted by the decreased ATP supply. Moreover, it is interesting to note that not only the penicillin productivity was reduced under such oscillating DO conditions, but also that of the unrecyclable byproduct ortho-hydroxyphenyl acetic acid and degeneration of penicillin productivity. Furthermore, dynamic flux profiles showed the most pronounced variations in central carbon metabolism, amino acid (AA) metabolism, energy metabolism and fatty acid metabolism upon the DO oscillation. Taken together, the metabolic responses of P. chrysogenum to DO gradients reported here are important for elucidating metabolic regulation mechanisms, improving bioreactor design and scale-up procedures as well as for constructing robust cell strains to cope with heterogenous industrial culture conditions.

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.

An NADH/NAD+-favored aldo-keto reductase facilitates avilamycin A biosynthesis by primarily catalyzing oxidation of avilamycin C

Avilamycins, which possess potent inhibitory activity against Gram-positive bacteria, are a group of oligosaccharide antibiotics produced by Streptomyces viridochromogenes. Among these structurally related oligosaccharide antibiotics, avilamycin A serves as the main bioactive component in veterinary drugs and animal feed additives, which differs from avilamycin C only in the redox state of the two-carbon branched-chain of the terminal octose moiety. However, the mechanisms underlying assembly and modification of the oligosaccharide chain to diversify individual avilamycins remain poorly understood. Here, we report that AviZ1, an aldo-keto reductase in the avilamycin pathway, can catalyze the redox conversion between avilamycins A and C. Remarkably, the ratio of these two components produced by AviZ1 depends on the utilization of specific redox cofactors, namely NADH/NAD+ or NADPH/NADP+. These findings are inspired by gene disruption and complementation experiments and are further supported by in vitro enzymatic activity assays, kinetic analyses, and cofactor affinity studies on AviZ1-catalyzed redox reactions. Additionally, the results from sequence analysis, structure prediction, and site-directed mutagenesis of AviZ1 validate it as an NADH/NAD+-favored aldo-keto reductase that primarily oxidizes avilamycin C to form avilamycin A by utilizing abundant NAD+ in vivo. Building upon the biological function and catalytic activity of AviZ1, overexpressing AviZ1 in S. viridochromogenes is thus effective to improve the yield and proportion of avilamycin A in the fermentation profile of avilamycins. This study represents, to our knowledge, the first characterization of biochemical reactions involved in avilamycin biosynthesis and contributes to the construction of high-performance strains with industrial value.IMPORTANCEAvilamycins are a group of oligosaccharide antibiotics produced by Streptomyces viridochromogenes, which can be used as veterinary drugs and animal feed additives. Avilamycin A is the most bioactive component, differing from avilamycin C only in the redox state of the two-carbon branched-chain of the terminal octose moiety. Currently, the biosynthetic pathway of avilamycins is not clear. Here, we report that AviZ1, an aldo-keto reductase in the avilamycin pathway, can catalyze the redox conversion between avilamycins A and C. More importantly, AviZ1 exhibits a unique NADH/NAD+ preference, allowing it to efficiently catalyze the oxidation of avilamycin C to form avilamycin A using abundant NAD+ in cells. Thus, overexpressing AviZ1 in S. viridochromogenes is effective to improve the yield and proportion of avilamycin A in the fermentation profile of avilamycins. This study serves as an enzymological guide for rational strain design, and the resulting high-performance strains have significant industrial value.

Characterization of conidial autofluorescence in powdery mildew

Autofluorescence is produced by endogenous fluorophores, such as NAD(P)H, lipofuscin, melanin, and riboflavin, indicating the accumulation of substances and the state of energy metabolism in organisms. As an obligate parasite, powdery mildew is wildly spread by air and parasitic crops. However, most identification studies have been based on morphology and molecular biology which were far too time- and labor-consuming, thus lacking characteristic, simple, and effective means. Using microscopy under the blue and cyan channels, we elaborated visible conidial autofluorescence in three powdery mildew species, Erysiphe quercicola, E. cichoracearum, and Podosphaera hibiscicola, with a sharp increase during the conidia senescence in E. quercicola. Additionally, the main spectral excitation detected by fluorescence spectrometery was 375 nm for these species, with a common emission peak at approximately 458-463 nm, and an additional trend at 487 nm for P. hibiscicola. Because NAD(P)H has a similar spectral feature, we further investigated the relation between NAD(P)H and conidial autofluorescence by fluorescence spectra. We observed that the reduced coenzymes prominently contributed to conidial autofluorescence; however, the conidial autofluorescence in P. hibiscicola displayed a different trend that may be affected by the oxidized coenzyme -NAD. Finally, the normalized average spectra of these three powdery mildew species and standard samples showed that the spectral trend of each species was similar but that the features in detail were specific and distinct based on principal component analysis. In conclusion, we showed and characterized conidial autofluorescence in three powdery mildew species for the first time. The specific conidial autofluorescence in these species provides a new idea for the development of field spore capture and identification devices for the discrimination of powdery mildew at the species level.

Top-Down, Knowledge-Based Genetic Reduction of Yeast Central Carbon Metabolism

Saccharomyces cerevisiae, whose evolutionary past includes a whole-genome duplication event, is characterized by a mosaic genome configuration with substantial apparent genetic redundancy. This apparent redundancy raises questions about the evolutionary driving force for genomic fixation of “minor” paralogs and complicates modular and combinatorial metabolic engineering strategies. While isoenzymes might be important in specific environments, they could be dispensable in controlled laboratory or industrial contexts. The present study explores the extent to which the genetic complexity of the central carbon metabolism (CCM) in S. cerevisiae, here defined as the combination of glycolysis, the pentose phosphate pathway, the tricarboxylic acid cycle, and a limited number of related pathways and reactions, can be reduced by elimination of (iso)enzymes without major negative impacts on strain physiology. Cas9-mediated, groupwise deletion of 35 of the 111 genes yielded a “minimal CCM” strain which, despite the elimination of 32% of CCM-related proteins, showed only a minimal change in phenotype on glucose-containing synthetic medium in controlled bioreactor cultures relative to a congenic reference strain. Analysis under a wide range of other growth and stress conditions revealed remarkably few phenotypic changes from the reduction of genetic complexity. Still, a well-documented context-dependent role of GPD1 in osmotolerance was confirmed. The minimal CCM strain provides a model system for further research into genetic redundancy of yeast genes and a platform for strategies aimed at large-scale, combinatorial remodeling of yeast CCM.

Sirtuins in Epigenetic Silencing and Control of Gene Expression in Model and Pathogenic Fungi

Fungi, including yeasts, molds, and mushrooms, proliferate on decaying matter and then adopt quiescent forms once nutrients are depleted. This review explores how fungi use sirtuin deacetylases to sense and respond appropriately to changing nutrients. Because sirtuins are NAD⁺-dependent deacetylases, their activity is sensitive to intracellular NAD⁺ availability. This allows them to transmit information about a cell's metabolic state on to the biological processes they influence. Fungal sirtuins are primarily known to deacetylate histones, repressing transcription and modulating genome stability. Their target genes include those involved in NAD⁺ homeostasis, metabolism, sporulation, secondary metabolite production, and virulence traits of pathogenic fungi. By targeting different genes over evolutionary time, sirtuins serve as rewiring points that allow organisms to evolve novel responses to low NAD⁺ stress by bringing relevant biological processes under the control of sirtuins. Expected final online publication date for the Annual Review of Microbiology, Volume 76 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Protein cost minimization promotes the emergence of coenzyme redundancy

Metabolism relies on a small class of molecules (coenzymes) that serve as universal donors and acceptors of key chemical groups and electrons. Although metabolic networks crucially depend on structurally redundant coenzymes [e.g., NAD(H) and NADP(H)] associated with different enzymes, the criteria that led to the emergence of this redundancy remain poorly understood. Our combination of modeling and structural and sequence analysis indicates that coenzyme redundancy may not be essential for metabolism but could rather constitute an evolved strategy promoting efficient usage of enzymes when biochemical reactions are near equilibrium. Our work suggests that early metabolism may have operated with fewer coenzymes and that adaptation for metabolic efficiency may have driven the rise of coenzyme diversity in living systems.

Coenzymes distribute a variety of chemical moieties throughout cellular metabolism, participating in group (e.g., phosphate and acyl) and electron transfer. For a variety of reactions requiring acceptors or donors of specific resources, there often exist degenerate sets of molecules [e.g., NAD(H) and NADP(H)] that carry out similar functions. Although the physiological roles of various coenzyme systems are well established, it is unclear what selective pressures may have driven the emergence of coenzyme redundancy. Here, we use genome-wide metabolic modeling approaches to decompose the selective pressures driving enzymatic specificity for either NAD(H) or NADP(H) in the metabolic network of Escherichia coli. We found that few enzymes are thermodynamically constrained to using a single coenzyme, and in principle a metabolic network relying on only NAD(H) is feasible. However, structural and sequence analyses revealed widespread conservation of residues that retain selectivity for either NAD(H) or NADP(H), suggesting that additional forces may shape specificity. Using a model accounting for the cost of oxidoreductase enzyme expression, we found that coenzyme redundancy universally reduces the minimal amount of protein required to catalyze coenzyme-coupled reactions, inducing individual reactions to strongly prefer one coenzyme over another when reactions are near thermodynamic equilibrium. We propose that protein minimization generically promotes coenzyme redundancy and that coenzymes typically thought to exist in a single pool (e.g., coenzyme A [CoA]) may exist in more than one form (e.g., dephospho-CoA).

Kinetic Modeling of Saccharomyces cerevisiae Central Carbon Metabolism: Achievements, Limitations, and Opportunities

Central carbon metabolism comprises the metabolic pathways in the cell that process nutrients into energy, building blocks and byproducts. To unravel the regulation of this network upon glucose perturbation, several metabolic models have been developed for the microorganism Saccharomyces cerevisiae. These dynamic representations have focused on glycolysis and answered multiple research questions, but no commonly applicable model has been presented. This review systematically evaluates the literature to describe the current advances, limitations, and opportunities. Different kinetic models have unraveled key kinetic glycolytic mechanisms. Nevertheless, some uncertainties regarding model topology and parameter values still limit the application to specific cases. Progressive improvements in experimental measurement technologies as well as advances in computational tools create new opportunities to further extend the model scale. Notably, models need to be made more complex to consider the multiple layers of glycolytic regulation and external physiological variables regulating the bioprocess, opening new possibilities for extrapolation and validation. Finally, the onset of new data representative of individual cells will cause these models to evolve from depicting an average cell in an industrial fermenter, to characterizing the heterogeneity of the population, opening new and unseen possibilities for industrial fermentation improvement.

Can thiol-based redox systems be utilized as parts for synthetic biology applications?

OBJECTIVES

Synthetic biology has emerged from molecular biology and engineering approaches and aims to develop novel, biologically-inspired systems for industrial and basic research applications ranging from biocomputing to drug production. Surprisingly, redoxin (thioredoxin, glutaredoxin, peroxiredoxin) and other thiol-based redox systems have not been widely utilized in many of these synthetic biology applications.

METHODS

We reviewed thiol-based redox systems and the development of synthetic biology applications that have used thiol-dependent parts.

RESULTS

The development of circuits to facilitate cytoplasmic disulfide bonding, biocomputing and the treatment of intestinal bowel disease are amongst the applications that have used thiol-based parts. We propose that genetically encoded redox sensors, thiol-based biomaterials and intracellular hydrogen peroxide generators may also be valuable components for synthetic biology applications.

DISCUSSION

Thiol-based systems play multiple roles in cellular redox metabolism, antioxidant defense and signaling and could therefore offer a vast and diverse portfolio of components, parts and devices for synthetic biology applications. However, factors limiting the adoption of redoxin systems for synthetic biology applications include the orthogonality of thiol-based components, limitations in the methods to characterize thiol-based systems and an incomplete understanding of the design principles of these systems.

Metabolic control analysis of L-tryptophan producing Escherichia coli applying targeted perturbation with shikimate

L-tryptophan production from glycerol with Escherichia coli was analysed by perturbation studies and metabolic control analysis. The insertion of a non-natural shikimate transporter into the genome of an Escherichia coli L-tryptophan production strain enabled targeted perturbation within the product pathway with shikimate during parallelised short-term perturbation experiments with cells withdrawn from a 15 L fed-batch production process. Expression of the shikimate/H⁺-symporter gene (shiA) from Corynebacterium glutamicum did not alter process performance within the estimation error. Metabolic analyses and subsequent extensive data evaluation were performed based on the data of the parallel analysis reactors and the production process. Extracellular rates and intracellular metabolite concentrations displayed evident deflections in cell metabolism and particularly in chorismate biosynthesis due to the perturbations with shikimate. Intracellular flux distributions were estimated using a thermodynamics-based flux analysis method, which integrates thermodynamic constraints and intracellular metabolite concentrations to restrain the solution space. Feasible flux distributions, Gibbs reaction energies and concentration ranges were computed simultaneously for the genome-wide metabolic model, with minimum bias in relation to the direction of metabolic reactions. Metabolic control analysis was applied to estimate elasticities and flux control coefficients, predicting controlling sites for L-tryptophan biosynthesis. The addition of shikimate led to enhanced deviations in chorismate biosynthesis, revealing a so far not observed control of 3-dehydroquinate synthase on L-tryptophan formation. The relative expression of the identified target genes was analysed with RT-qPCR. Transcriptome analysis revealed disparities in gene expression and the localisation of target genes to further improve the microbial L-tryptophan producer by metabolic engineering.

A review and assessment of the Shared-Pathway Hypothesis for the maintenance of signal honesty in red ketocarotenoid-based coloration

For decades, scientists have noted connections between individual condition and carotenoid-based coloration in terrestrial and aquatic animals. Organisms that produce more vibrant carotenoid-based coloration tend to have better physiological performance and behavioral displays compared to less colorful members of the same species. Traditional explanations for this association between ornamental coloration and performance invoked the need for color displays to be costly, but evidence for such hypothesized costs is equivocal. An alternative explanation for the condition-dependence of carotenoid-based coloration, the Shared-Pathway Hypothesis, was developed in response. This hypothesis proposes that red ketocarotenoid-based coloration is tied to core cellular processes involving a shared pathway with mitochondrial energy metabolism, making the concentration of carotenoids an index of mitochondrial function. Since the presentation of this hypothesis, empirical tests of the mechanisms proposed therein have been conducted in many species. In this manuscript, we review the Shared-Pathway Hypothesis and the growing number of studies that have investigated a connection between carotenoid-based coloration and mitochondrial function. We also discuss future strategies for assessing the Shared-Pathway Hypothesis to more effectively disentangle evidence that may simultaneously support evidence of carotenoid-resource tradeoffs.

Dynamic response of Aspergillus niger to periodical glucose pulse stimuli in chemostat cultures

In industrial large-scale bioreactors, microorganisms encounter heterogeneous substrate concentration conditions, which can impact growth or product formation. Here we carried out an extended (12 h) experiment of repeated glucose pulsing with a 10-min period to simulate fluctuating glucose concentrations with Aspergillus niger producing glucoamylase, and investigated its dynamic response by rapid sampling and quantitative metabolomics. The 10-min period represents worst-case conditions, as in industrial bioreactors the average cycling duration is usually in the order of 1 min. We found that cell growth and the glucoamylase productivity were not significantly affected, despite striking metabolomic dynamics. Periodical dynamic responses were found across all central carbon metabolism pathways, with different time scales, and the frequently reported ATP paradox was confirmed for this A. niger strain under the dynamic conditions. A thermodynamics analysis revealed that several reactions of the central carbon metabolism remained in equilibrium even under periodical dynamic conditions. The dynamic response profiles of the intracellular metabolites did not change during the pulse exposure, showing no significant adaptation of the strain to the more than 60 perturbation cycles applied. The apparent high tolerance of the glucoamylase producing A. niger strain for extreme variations in the glucose availability presents valuable information for the design of robust industrial microbial hosts.

Complex yeast-bacteria interactions affect the yield of industrial ethanol fermentation

Sugarcane ethanol fermentation represents a simple microbial community dominated by S. cerevisiae and co-occurring bacteria with a clearly defined functionality. In this study, we dissect the microbial interactions in sugarcane ethanol fermentation by combinatorically reconstituting every possible combination of species, comprising approximately 80% of the biodiversity in terms of relative abundance. Functional landscape analysis shows that higher-order interactions counterbalance the negative effect of pairwise interactions on ethanol yield. In addition, we find that Lactobacillus amylovorus improves the yeast growth rate and ethanol yield by cross-feeding acetaldehyde, as shown by flux balance analysis and laboratory experiments. Our results suggest that Lactobacillus amylovorus could be considered a beneficial bacterium with the potential to improve sugarcane ethanol fermentation yields by almost 3%. These data highlight the biotechnological importance of comprehensively studying microbial communities and could be extended to other microbial systems with relevance to human health and the environment.

An NADH preferring acetoacetyl-CoA reductase is engaged in poly-3-hydroxybutyrate accumulation in Escherichia coli

Oxygen supply implies higher production cost and reduction of maximum theoretical yields. Thus, generation of fermentation products is more cost-effective. Aiming to find a key piece for the production of (poly)-3-hydroxybutyrate (PHB) as a fermentation product, here we characterize an acetoacetyl-CoA reductase, isolated from a Candidatus Accumulibacter phosphatis-enriched mixed culture, showing a (k_cat^NADH/K_M^NADH)/(k_cat^NADPH/K_M^NADPH)>500. Further kinetic analyses indicate that, at physiological concentrations, this enzyme clearly prefers NADH, presenting the strongest NADH preference so far observed among the acetoacetyl-CoA reductases. Structural and kinetic analyses indicate that residues between E37 and P41 have an important role for the observed NADH preference. Moreover, an operon was assembled combining the phaCA genes from Cupriavidus necator and the gene encoding for this NADH-preferring acetoacetyl-CoA reductase. Escherichia coli cells expressing that assembled operon showed continuous accumulation of PHB under oxygen limiting conditions and PHB titer increased when decreasing the specific oxygen consumption rate. Taken together, these results show that it is possible to generate PHB as a fermentation product in E. coli, opening opportunities for further protein/metabolic engineering strategies envisioning a more efficient anaerobic production of PHB.

Biosynthesis of adipic acid in metabolically engineered Saccharomyces cerevisiae

Adipic Acid (AA) is a valued platform chemical compound, which can be used as a precursor of nylon-6,6. Due to the generation of an enormous amount of nitric oxide metabolites and the growing depletion of oil resources as a result of AA production from a mixture of cyclohexanol and cyclohexanone, the microbial methods for synthesizing AA have attracted significant attention. Of the several AA-producing pathways, the reverse adipate degradation pathway in Thermobifida fusca (Tfu RADP) is reported to be the most efficient, which has been confirmed in Escherichia coli. In this study, the heterologous Tfu RADP was constructed for producing AA in S. cerevisiae by co-expressing genes of Tfu_0875, Tfu_2399, Tfu_0067, Tfu_1647, Tfu_2576, and Tfu_2576. The AA titer combined with biomass, cofactors and other by-products was all determined after fermentation. During batch fermentation in a shake flask, the maximum AA titer was 3.83 mg/L, while the titer increased to 10.09 mg/L during fed-batch fermentation in a 5-L bioreactor after fermentation modification.

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.

Quantifying the RNA cap epitranscriptome reveals novel caps in cellular and viral RNA

Chemical modification of transcripts with 5' caps occurs in all organisms. Here, we report a systems-level mass spectrometry-based technique, CapQuant, for quantitative analysis of an organism's cap epitranscriptome. The method was piloted with 21 canonical caps-m7GpppN, m7GpppNm, GpppN, GpppNm, and m2,2,7GpppG-and 5 'metabolite' caps-NAD, FAD, UDP-Glc, UDP-GlcNAc, and dpCoA. Applying CapQuant to RNA from purified dengue virus, Escherichia coli, yeast, mouse tissues, and human cells, we discovered new cap structures in humans and mice (FAD, UDP-Glc, UDP-GlcNAc, and m7Gpppm6A), cell- and tissue-specific variations in cap methylation, and high proportions of caps lacking 2'-O-methylation (m7Gpppm6A in mammals, m7GpppA in dengue virus). While substantial Dimroth-induced loss of m1A and m1Am arose with specific RNA processing conditions, human lymphoblast cells showed no detectable m1A or m1Am in caps. CapQuant accurately captured the preference for purine nucleotides at eukaryotic transcription start sites and the correlation between metabolite levels and metabolite caps.

Combined In-Cell NMR and Simulation Approach to Probe Redox-Dependent Pathway Control

Dynamic response of intracellular reaction cascades to changing environments is a hallmark of living systems. As metabolism is complex, mechanistic models have gained popularity for describing the dynamic response of cellular metabolism and for identifying target genes for engineering. At the same time, the detailed tracking of transient metabolism in living cells on the subminute time scale has become amenable using dynamic nuclear polarization-enhanced ¹³C NMR. Here, we suggest an approach combining in-cell NMR spectroscopy with perturbation experiments and modeling to obtain evidence that the bottlenecks of yeast glycolysis depend on intracellular redox state. In pre-steady-state glycolysis, pathway bottlenecks shift from downstream to upstream reactions within a few seconds, consistent with a rapid decline in the NAD⁺/NADH ratio. Simulations using mechanistic models reproduce the experimentally observed response and help identify unforeseen biochemical events. Remaining inaccuracies in the computational models can be identified experimentally. The combined use of rapid injection NMR spectroscopy and in silico simulations provides a promising method for characterizing cellular reactions with increasing mechanistic detail.

Quantification of the Metabolic Heterogeneity in Mycobacterial Cells Through the Measurement of the NADH/NAD+ Ratio Using a Genetically Encoded Sensor

NADH/NAD⁺ levels are an indicator of the bacterial metabolic state. NAD(H) levels are maintained through coordination of pathways involved in NAD(H) synthesis and its catabolic utilization. Conventional methods of estimating NADH/NAD⁺ require cell disruption and suffer from low specificity and sensitivity and are inadequate in providing spatiotemporal resolution. Recently, genetically encoded biosensors of the NADH/NAD⁺ ratio have been developed. One of these sensors, Peredox-mCherry, was adapted for the measurement of cellular levels of NADH/NAD⁺ in the slow-growing Mycobacterium tuberculosis (Mtb) and the fast-growing Mycobacterium smegmatis. Importantly, the use of the engineered reporter strains of Mtb demonstrated a significantly higher heterogeneity among the bacteria residing in macrophages compared to the bacteria grown in synthetic media. Previous estimations of NADH/NAD⁺ levels have missed this important aspect of the biology of Mtb, which may contribute to the variable response of intracellular Mtb to different antimycobacterial agents. In this chapter, we describe the details of a method used in the generation of reporter strains for the measurement of the NADH/NAD⁺ ratio in mycobacteria. Importantly, once the reporter strains are created, they can be exploited with fluorescence spectroscopy, FACS, and confocal microscopy to access the dynamic changes in the NADH/NAD⁺ levels in intact individual bacterial cells. Although we have only described the method for the creation of reporter strains capable of measuring NADH/NAD⁺ in mycobacteria in this chapter, a similar method can be used for generating reporter strains for other bacterial species, as well. We believe that such reporter stains can be used in novel screens for small molecules that could alter the metabolism of bacterial cells and thus aid in the development of new class of therapeutic agents.

Highly efficient 5' capping of mitochondrial RNA with NAD+ and NADH by yeast and human mitochondrial RNA polymerase

Bacterial and eukaryotic nuclear RNA polymerases (RNAPs) cap RNA with the oxidized and reduced forms of the metabolic effector nicotinamide adenine dinucleotide, NAD⁺ and NADH, using NAD⁺ and NADH as non-canonical initiating nucleotides for transcription initiation. Here, we show that mitochondrial RNAPs (mtRNAPs) cap RNA with NAD⁺ and NADH, and do so more efficiently than nuclear RNAPs. Direct quantitation of NAD⁺- and NADH-capped RNA demonstrates remarkably high levels of capping in vivo: up to ~60% NAD⁺ and NADH capping of yeast mitochondrial transcripts, and up to ~15% NAD⁺ capping of human mitochondrial transcripts. The capping efficiency is determined by promoter sequence at, and upstream of, the transcription start site and, in yeast and human cells, by intracellular NAD⁺ and NADH levels. Our findings indicate mtRNAPs serve as both sensors and actuators in coupling cellular metabolism to mitochondrial transcriptional outputs, sensing NAD⁺ and NADH levels and adjusting transcriptional outputs accordingly.

The Crabtree Effect Shapes the Saccharomyces cerevisiae Lag Phase during the Switch between Different Carbon Sources

When faced with environmental changes, microbes often enter a temporary growth arrest during which they reprogram the expression of specific genes to adapt to the new conditions. A prime example of such a lag phase occurs when microbes need to switch from glucose to other, less-preferred carbon sources. Despite its industrial relevance, the genetic network that determines the duration of the lag phase has not been studied in much detail. Here, we performed a genome-wide Bar-Seq screen to identify genetic determinants of the Saccharomyces cerevisiae glucose-to-galactose lag phase. The results show that genes involved in respiration, and specifically those encoding complexes III and IV of the electron transport chain, are needed for efficient growth resumption after the lag phase. Anaerobic growth experiments confirmed the importance of respiratory energy conversion in determining the lag phase duration. Moreover, overexpression of the central regulator of respiration, HAP4, leads to significantly shorter lag phases. Together, these results suggest that the glucose-induced repression of respiration, known as the Crabtree effect, is a major determinant of microbial fitness in fluctuating carbon environments.IMPORTANCE The lag phase is arguably one of the prime characteristics of microbial growth. Longer lag phases result in lower competitive fitness in variable environments, and the duration of the lag phase is also important in many industrial processes where long lag phases lead to sluggish, less efficient fermentations. Despite the immense importance of the lag phase, surprisingly little is known about the exact molecular processes that determine its duration. Our study uses the molecular toolbox of S. cerevisiae combined with detailed growth experiments to reveal how the transition from fermentative to respirative metabolism is a key bottleneck for cells to overcome the lag phase. Together, our findings not only yield insight into the key molecular processes and genes that influence lag duration but also open routes to increase the efficiency of industrial fermentations and offer an experimental framework to study other types of lag behavior.

Dynamic elementary mode modelling of non-steady state flux data

BACKGROUND

A novel framework is proposed to analyse metabolic fluxes in non-steady state conditions, based on the new concept of dynamic elementary mode (dynEM): an elementary mode activated partially depending on the time point of the experiment.

RESULTS

Two methods are introduced here: dynamic elementary mode analysis (dynEMA) and dynamic elementary mode regression discriminant analysis (dynEMR-DA). The former is an extension of the recently proposed principal elementary mode analysis (PEMA) method from steady state to non-steady state scenarios. The latter is a discriminant model that permits to identify which dynEMs behave strongly different depending on the experimental conditions. Two case studies of Saccharomyces cerevisiae, with fluxes derived from simulated and real concentration data sets, are presented to highlight the benefits of this dynamic modelling.

CONCLUSIONS

This methodology permits to analyse metabolic fluxes at early stages with the aim of i) creating reduced dynamic models of flux data, ii) combining many experiments in a single biologically meaningful model, and iii) identifying the metabolic pathways that drive the organism from one state to another when changing the environmental conditions.

Molecular tools for pathway engineering in Saccharomyces cerevisiae

Molecular tools for the regulation of protein expression in Saccharomyces cerevisiae have contributed to rapid advances in pathway engineering for this yeast. This review considers new and enhanced additions to this toolbox, focusing on experimental approaches to modulate enzyme synthesis and enzyme fate. Methods for genome engineering, regulation of transcription, post-translational protein localization, and combinatorial screening and sensing in S. cerevisiae are highlighted, and promising new approaches are introduced.

Targeted redox and energy cofactor metabolomics in Clostridium thermocellum and Thermoanaerobacterium saccharolyticum

BACKGROUND

Clostridium thermocellum and Thermoanaerobacterium saccharolyticum are prominent candidate biocatalysts that, together, can enable the direct biotic conversion of lignocellulosic biomass to ethanol. The imbalance and suboptimal turnover rates of redox cofactors are currently hindering engineering efforts to achieve higher bioproductivity in both organisms. Measuring relevant intracellular cofactor concentrations will help understand redox state of these cofactors and help identify a strategy to overcome these limitations; however, metabolomic determinations of these labile metabolites have historically proved challenging.

RESULTS

Through our validations, we verified the handling and storage stability of these metabolites, and verified extraction matrices and extraction solvent were not suppressing mass spectrometry signals. We recovered adenylate energy charge ratios (a main quality indicator) above 0.82 for all extractions. NADH/NAD+ values of 0.26 and 0.04 for an adhE-deficient strain of C. thermocellum and its parent, respectively, reflect the expected shift to a more reduced redox potential when a species lacks the ability to re-oxidize NADH by synthesizing ethanol. This method failed to yield reliable results with C. bescii and poor-growing strains of T. saccharolyticum.

CONCLUSIONS

Our validated protocols demonstrate and validate the extraction and analysis of selected redox and energy-related metabolites from two candidate consolidated bioprocessing biocatalysts, C. thermocellum and T. saccharolyticum. This development and validation highlights the important, but often neglected, need to optimize and validate metabolomic protocols when adapting them to new cell or tissue types.

Metabolic adjustment upon repetitive substrate perturbations using dynamic 13C-tracing in yeast

BACKGROUND

Natural and industrial environments are dynamic with respect to substrate availability and other conditions like temperature and pH. Especially, metabolism is strongly affected by changes in the extracellular space. Here we study the dynamic flux of central carbon metabolism and storage carbohydrate metabolism under dynamic feast/famine conditions in Saccharomyces cerevisiae.

RESULTS

The metabolic flux reacts fast and sensitive to cyclic perturbations in substrate availability. Compared to well-documented stimulus-response experiments using substrate pulses, different metabolic responses are observed. Especially, cells experiencing cyclic perturbations do not show a drop in ATP with the addition of glucose, but an immediate increase in energy charge. Although a high glycolytic flux of up to 5.4 mmol g DW-1  h-1 is observed, no overflow metabolites are detected. From famine to feast the glucose uptake rate increased from 170 to 4788 μmol g DW-1  h-1 in 24 s. Intracellularly, even more drastic changes were observed. Especially, the T6P synthesis rate increased more than 100-fold upon glucose addition. This response indicates that the storage metabolism is very sensitive to changes in glycolytic flux and counterbalances these rapid changes by diverting flux into large pools to prevent substrate accelerated death and potentially refill the central metabolism when substrates become scarce. Using 13C-tracer we found a dilution in the labeling of extracellular glucose, G6P, T6P and other metabolites, indicating an influx of unlabeled carbon. It is shown that glycogen and trehalose degradation via different routes could explain these observations. Based on the 13C labeling in average 15% of the carbon inflow is recycled via trehalose and glycogen. This average fraction is comparable to the steady-state turnover, but changes significantly during the cycle, indicating the relevance for dynamic regulation of the metabolic flux.

CONCLUSIONS

Comparable to electric energy grids, metabolism seems to use storage units to buffer peaks and keep reserves to maintain a robust function. During the applied fast feast/famine conditions about 15% of the metabolized carbon were recycled in storage metabolism. Additionally, the resources were distributed different to steady-state conditions. Most remarkably is a fivefold increased flux towards PPP that generated a reversed flux of transaldolase and the F6P-producing transketolase reactions. Combined with slight changes in the biomass composition, the yield decrease of 5% can be explained.

Intracellular product recycling in high succinic acid producing yeast at low pH

BACKGROUND

The metabolic engineering of Saccharomyces cerevisiae for the production of succinic acid has progressed dramatically, and a series of high-producing hosts are available. At low cultivation pH and high titers, the product transport can become bidirectional, i.e. the acid is reentering the cell and is again exported or even catabolized. Here, a quantitative approach for the identification of product recycling fluxes is developed.

RESULTS

The metabolic flux distributions at two time-points of the fermentation process were analyzed. ¹³C labeled succinic acid was added to the extracellular space and intracellular enrichments were measured and subsequently used for the estimation of metabolic fluxes. The labeling was introduced by a labeling switch experiment, leading to an immediate labeling of about 85% of the acid while keeping the total acid concentration constant. Within 100 s significant labeling enrichment of the TCA cycle intermediates fumarate, iso-citrate and α-ketoglutarate was observed, while no labeling was detected for malate and citrate. These findings suggest that succinic acid is rapidly exchanged over the cellular membrane and enters the oxidative TCA cycle. Remarkably, in the oxidative direction malate ¹³C enrichment was not detected, indicating that there is no flux going through this metabolite pool. Using flux modeling and thermodynamic assumptions on compartmentation it was concluded that malate must be predominantly cytosolic while fumarate and iso-citrate were more dominant in the mitochondria.

CONCLUSIONS

Adding labeled product without changing the extracellular environment allowed to quantify intracellular metabolic fluxes under high producing conditions and identify product degradation cycles. In the specific case of succinic acid production, compartmentation was found to play a major role, i.e. the presence of metabolic activity in two different cellular compartments lead to intracellular product degradation reducing the yield. We also observed that the flux from glucose to succinic acid branches at two points in metabolism: (1) At the level of pyruvate, and (2) at cytosolic malate which was not expected.

Engineering an NADPH/NADP+ Redox Biosensor in Yeast

Genetically encoded biosensors have emerged as powerful tools for timely and precise in vivo evaluation of cellular metabolism. In particular, biosensors that can couple intercellular cues with downstream signaling responses are currently attracting major attention within health science and biotechnology. Still, there is a need for bioprospecting and engineering of more biosensors to enable real-time monitoring of specific cellular states and controlling downstream actuation. In this study, we report the engineering and application of a transcription factor-based NADPH/NADP⁺ redox biosensor in the budding yeast Saccharomyces cerevisiae. Using the biosensor, we are able to monitor the cause of oxidative stress by chemical induction, and changes in NADPH/NADP⁺ ratios caused by genetic manipulations. Because of the regulatory potential of the biosensor, we also show that the biosensor can actuate upon NADPH deficiency by activation of NADPH regeneration. Finally, we couple the biosensor with an expression of dosage-sensitive genes (DSGs) and thereby create a novel tunable sensor-selector useful for synthetic selection of cells with higher NADPH/NADP⁺ ratios from mixed cell populations. We show that the combination of exploitation and rational engineering of native signaling components is applicable for diagnosis, regulation, and selection of cellular redox states.

Quantification of Microbial Phenotypes

Metabolite profiling technologies have improved to generate close to quantitative metabolomics data, which can be employed to quantitatively describe the metabolic phenotype of an organism. Here, we review the current technologies available for quantitative metabolomics, present their advantages and drawbacks, and the current challenges to generate fully quantitative metabolomics data. Metabolomics data can be integrated into metabolic networks using thermodynamic principles to constrain the directionality of reactions. Here we explain how to estimate Gibbs energy under physiological conditions, including examples of the estimations, and the different methods for thermodynamics-based network analysis. The fundamentals of the methods and how to perform the analyses are described. Finally, an example applying quantitative metabolomics to a yeast model by 13C fluxomics and thermodynamics-based network analysis is presented. The example shows that (1) these two methods are complementary to each other; and (2) there is a need to take into account Gibbs energy errors. Better estimations of metabolic phenotypes will be obtained when further constraints are included in the analysis.

In Vivo Analysis of NH4+ Transport and Central Nitrogen Metabolism in Saccharomyces cerevisiae during Aerobic Nitrogen-Limited Growth

Ammonium is the most common N source for yeast fermentations. Although its transport and assimilation mechanisms are well documented, there have been only a few attempts to measure the in vivo intracellular concentration of ammonium and assess its impact on gene expression. Using an isotope dilution mass spectrometry (IDMS)-based method, we were able to measure the intracellular ammonium concentration in N-limited aerobic chemostat cultivations using three different N sources (ammonium, urea, and glutamate) at the same growth rate (0.05 h^-1). The experimental results suggest that, at this growth rate, a similar concentration of intracellular (IC) ammonium, about 3.6 mmol NH₄⁺/liter_IC, is required to supply the reactions in the central N metabolism, independent of the N source. Based on the experimental results and different assumptions, the vacuolar and cytosolic ammonium concentrations were estimated. Furthermore, we identified a futile cycle caused by NH₃ leakage into the extracellular space, which can cost up to 30% of the ATP production of the cell under N-limited conditions, and a futile redox cycle between Gdh1 and Gdh2 reactions. Finally, using shotgun proteomics with protein expression determined relative to a labeled reference, differences between the various environmental conditions were identified and correlated with previously identified N compound-sensing mechanisms.IMPORTANCE In our work, we studied central N metabolism using quantitative approaches. First, intracellular ammonium was measured under different N sources. The results suggest that Saccharomyces cerevisiae cells maintain a constant NH₄⁺ concentration (around 3 mmol NH₄⁺/liter_IC), independent of the applied nitrogen source. We hypothesize that this amount of intracellular ammonium is required to obtain sufficient thermodynamic driving force. Furthermore, our calculations based on thermodynamic analysis of the transport mechanisms of ammonium suggest that ammonium is not equally distributed, indicating a high degree of compartmentalization in the vacuole. Additionally, metabolomic analysis results were used to calculate the thermodynamic driving forces in the central N metabolism reactions, revealing that the main reactions in the central N metabolism are far from equilibrium. Using proteomics approaches, we were able to identify major changes, not only in N metabolism, but also in C metabolism and regulation.

The steady-state assumption in oscillating and growing systems

The steady-state assumption, which states that the production and consumption of metabolites inside the cell are balanced, is one of the key aspects that makes an efficient analysis of genome-scale metabolic networks possible. It can be motivated from two different perspectives. In the time-scales perspective, we use the fact that metabolism is much faster than other cellular processes such as gene expression. Hence, the steady-state assumption is derived as a quasi-steady-state approximation of the metabolism that adapts to the changing cellular conditions. In this article we focus on the second perspective, stating that on the long run no metabolite can accumulate or deplete. In contrast to the first perspective it is not immediately clear how this perspective can be captured mathematically and what assumptions are required to obtain the steady-state condition. By presenting a mathematical framework based on the second perspective we demonstrate that the assumption of steady-state also applies to oscillating and growing systems without requiring quasi-steady-state at any time point. However, we also show that the average concentrations may not be compatible with the average fluxes. In summary, we establish a mathematical foundation for the steady-state assumption for long time periods that justifies its successful use in many applications. Furthermore, this mathematical foundation also pinpoints unintuitive effects in the integration of metabolite concentrations using nonlinear constraints into steady-state models for long time periods.

Adenosine diphosphate restricts the protein remodeling activity of the Hsp104 chaperone to Hsp70 assisted disaggregation

Hsp104 disaggregase provides thermotolerance in yeast by recovering proteins from aggregates in cooperation with the Hsp70 chaperone. Protein disaggregation involves polypeptide extraction from aggregates and its translocation through the central channel of the Hsp104 hexamer. This process relies on adenosine triphosphate (ATP) hydrolysis. Considering that Hsp104 is characterized by low affinity towards ATP and is strongly inhibited by adenosine diphosphate (ADP), we asked how Hsp104 functions at the physiological levels of adenine nucleotides. We demonstrate that physiological levels of ADP highly limit Hsp104 activity. This inhibition, however, is moderated by the Hsp70 chaperone, which allows efficient disaggregation by supporting Hsp104 binding to aggregates but not to non-aggregated, disordered protein substrates. Our results point to an additional level of Hsp104 regulation by Hsp70, which restricts the potentially toxic protein unfolding activity of Hsp104 to the disaggregation process, providing the yeast protein-recovery system with substrate specificity and efficiency in ATP consumption.

DOI:http://dx.doi.org/10.7554/eLife.15159.001

Under stressful conditions, such as high temperatures, many proteins lose their proper structure and clump together to form large irregular aggregates. To combat this effect, living organisms exposed to stress produce specialized proteins called chaperones, which can rescue the damaged proteins from aggregates.

Studies into this “disaggregation” process often use budding yeast as a model organism. The protein-recovery machinery in this yeast is composed of a ring-shaped enzyme called Hsp104, together with a chaperone called Hsp70 and its partner Hsp40. The Hsp104 enzyme converts molecules of ATP into ADP and uses the energy released from the reaction to move, or “translocate”, damaged proteins through its central channel and release them from the aggregates.

Previous studies had reported that ADP negatively affects Hsp104. Now, Kłosowska et al show that Hsp104 is almost inactive in a test-tube if the concentration of ADP is as high as that found inside a cell. This raises a question: how can Hsp104 efficiently remove proteins from aggregates in cells if the conditions are so unfavorable?

Using purified proteins, Kłosowska et al. go on to show that Hsp104 is able to tolerate the level of ADP found inside cells thanks to the Hsp70 chaperone. The experiments show that ADP weakens Hsp104’s ability to bind proteins while Hsp70 supports this ability and counteracts the negative effect of ADP. Further experiments demonstrate that Hsp104 is less affected by ADP, and binds more readily to ATP, when it is translocating proteins. These findings explain how the yeast disaggregating machinery can work even at relatively high concentrations of ADP, and reveal a new control mechanism in the disaggregation process.

Many important proteins have poorly organized fragments that can be recognized by Hsp104, and if Hsp104 was to bind to and translocate these proteins it could harm the cell. The findings of Kłosowska et al. suggest that Hsp70 helps Hsp104 to specifically bind to and act upon proteins in aggregates, while binding to partly unstructured proteins is limited by the high ADP concentration. Further studies are now needed to understand how the protein-recovery machinery can discriminate between aggregated and non-aggregated proteins.

DOI:http://dx.doi.org/10.7554/eLife.15159.002

Improving the flux distributions simulated with genome-scale metabolic models of Saccharomyces cerevisiae

Genome-scale metabolic models (GEMs) can be used to evaluate genotype-phenotype relationships and their application to microbial strain engineering is increasing in popularity. Some of the algorithms used to simulate the phenotypes of mutant strains require the determination of a wild-type flux distribution. However, the accuracy of this reference, when calculated with flux balance analysis, has not been studied in detail before.

Here, the wild-type simulations of selected GEMs for Saccharomyces cerevisiae have been analysed and most of the models tested predicted erroneous fluxes in central pathways, especially in the pentose phosphate pathway. Since the problematic fluxes were mostly related to areas of the metabolism consuming or producing NADPH/NADH, we have manually curated all reactions including these cofactors by forcing the use of NADPH/NADP⁺ in anabolic reactions and NADH/NAD⁺ for catabolic reactions. The curated models predicted more accurate flux distributions and performed better in the simulation of mutant phenotypes.

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The flux distributions of the genome-scale models of Saccharomyces cerevisiae were evaluated

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Most of the tested models showed fluxes inconsistent with experimental data

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A manual curation process was performed on all reactions including NADH or NADPH

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The curated models showed flux distributions more consistent with experimental data

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Phenotype simulations improved when the curated flux distributions were used

Engineering cytosolic acetyl-coenzyme A supply in Saccharomyces cerevisiae: Pathway stoichiometry, free-energy conservation and redox-cofactor balancing

Saccharomyces cerevisiae is an important industrial cell factory and an attractive experimental model for evaluating novel metabolic engineering strategies. Many current and potential products of this yeast require acetyl coenzyme A (acetyl-CoA) as a precursor and pathways towards these products are generally expressed in its cytosol. The native S. cerevisiae pathway for production of cytosolic acetyl-CoA consumes 2 ATP equivalents in the acetyl-CoA synthetase reaction. Catabolism of additional sugar substrate, which may be required to generate this ATP, negatively affects product yields. Here, we review alternative pathways that can be engineered into yeast to optimize supply of cytosolic acetyl-CoA as a precursor for product formation. Particular attention is paid to reaction stoichiometry, free-energy conservation and redox-cofactor balancing of alternative pathways for acetyl-CoA synthesis from glucose. A theoretical analysis of maximally attainable yields on glucose of four compounds (n-butanol, citric acid, palmitic acid and farnesene) showed a strong product dependency of the optimal pathway configuration for acetyl-CoA synthesis. Moreover, this analysis showed that combination of different acetyl-CoA production pathways may be required to achieve optimal product yields. This review underlines that an integral analysis of energy coupling and redox-cofactor balancing in precursor-supply and product-formation pathways is crucial for the design of efficient cell factories.

Identifying Metabolic Subpopulations from Population Level Mass Spectrometry

Metabolism underlies many important cellular decisions, such as the decisions to proliferate and differentiate, and defects in metabolic signaling can lead to disease and aging. In addition, metabolic heterogeneity can have biological consequences, such as differences in outcomes and drug susceptibilities in cancer and antibiotic treatments. Many approaches exist for characterizing the metabolic state of a population of cells, but technologies for measuring metabolism at the single cell level are in the preliminary stages and are limited. Here, we describe novel analysis methodologies that can be applied to established experimental methods to measure metabolic variability within a population. We use mass spectrometry to analyze amino acid composition in cells grown in a mixture of (12)C- and (13)C-labeled sugars; these measurements allow us to quantify the variability in sugar usage and thereby infer information about the behavior of cells within the population. The methodologies described here can be applied to a large range of metabolites and macromolecules and therefore have the potential for broad applications.

Quantifying NAD(P)H production in the upper Entner-Doudoroff pathway from Pseudomonas putida KT2440

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The first kinetic characterization of PputG6PDH-1 is presented.

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The relative production of NADH and NADPH by PputG6PDH-1 is quantified.

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The stoichiometric matrix of in silico metabolic models for Pseudomonas putida must be modified.

Despite the lack of biochemical information, all available in silico metabolic models of Pseudomonas putida KT2440 consider NADP as the only cofactor accepted by the glucose-6-phosphate dehydrogenases. Because the Entner–Doudoroff pathway is the main glycolytic route in this bacterium, determining how much NADH and NADPH are produced in the reaction catalyzed by these enzymes is very important for the correct interpretation of metabolic flux distributions. To determine the actual cofactor preference of the glucose-6-phosphate dehydrogenase encoded by the zwf-1 gene (PputG6PDH-1), the major isoform during growth on glucose, we purified this protein and studied its kinetic properties. Based on simple kinetic principles, we estimated the in vivo relative production of NADH and NADPH during the oxidation of glucose-6-phosphate (G6P). Contrary to the general assumption, our calculations showed that the reaction catalyzed by PputG6PDH-1 yields around 1/3 mol of NADPH and 2/3 mol of NADH per mol of oxidized G6P. Additionally, we obtained data suggesting that the reaction catalyzed by the 6-phosphogluconate dehydrogenase is active during growth on glucose, and it also produces NADH. These results indicate that the stoichiometric matrix of in silico models of P. putida KT2440 must be corrected and highlight the importance of considering the physiological concentrations of the involved metabolites to estimate the actual proportion of NADH and NADPH produced by a dehydrogenase.

Determination of the Cytosolic NADPH/NADP Ratio in Saccharomyces cerevisiae using Shikimate Dehydrogenase as Sensor Reaction

Eukaryotic metabolism is organised in complex networks of enzyme catalysed reactions which are distributed over different organelles. To quantify the compartmentalised reactions, quantitative measurements of relevant physiological variables in different compartments are needed, especially of cofactors. NADP(H) are critical components in cellular redox metabolism. Currently, available metabolite measurement methods allow whole cell measurements. Here a metabolite sensor based on a fast equilibrium reaction is introduced to monitor the cytosolic NADPH/NADP ratio in Saccharomyces cerevisiae: NADP + shikimate ⇄ NADPH + H(+) + dehydroshikimate. The cytosolic NADPH/NADP ratio was determined by measuring the shikimate and dehydroshikimate concentrations (by GC-MS/MS). The cytosolic NADPH/NADP ratio was determined under batch and chemostat (aerobic, glucose-limited, D = 0.1 h(-1)) conditions, to be 22.0 ± 2.6 and 15.6 ± 0.6, respectively. These ratios were much higher than the whole cell NADPH/NADP ratio (1.05 ± 0.08). In response to a glucose pulse, the cytosolic NADPH/NADP ratio first increased very rapidly and restored the steady state ratio after 3 minutes. In contrast to this dynamic observation, the whole cell NADPH/NADP ratio remained nearly constant. The novel cytosol NADPH/NADP measurements provide new insights into the thermodynamic driving forces for NADP(H)-dependent reactions, like amino acid synthesis, product pathways like fatty acid production or the mevalonate pathway.

Determination of the in vivo NAD:NADH ratio in Saccharomyces cerevisiae under anaerobic conditions, using alcohol dehydrogenase as sensor reaction

With the current quantitative metabolomics techniques, only whole-cell concentrations of NAD and NADH can be quantified. These measurements cannot provide information on the in vivo redox state of the cells, which is determined by the ratio of the free forms only. In this work we quantified free NAD:NADH ratios in yeast under anaerobic conditions, using alcohol dehydrogenase (ADH) and the lumped reaction of glyceraldehyde-3-phosphate dehydrogenase and 3-phosphoglycerate kinase as sensor reactions. We showed that, with an alternative accurate acetaldehyde determination method, based on rapid sampling, instantaneous derivatization with 2,4 diaminophenol hydrazine (DNPH) and quantification with HPLC, the ADH-catalysed oxidation of ethanol to acetaldehyde can be applied as a relatively fast and simple sensor reaction to quantify the free NAD:NADH ratio under anaerobic conditions. We evaluated the applicability of ADH as a sensor reaction in the yeast Saccharomyces cerevisiae, grown in anaerobic glucose-limited chemostats under steady-state and dynamic conditions. The results found in this study showed that the cytosolic redox status (NAD:NADH ratio) of yeast is at least one order of magnitude lower, and is thus much more reduced, under anaerobic conditions compared to aerobic glucose-limited steady-state conditions. The more reduced state of the cytosol under anaerobic conditions has major implications for (central) metabolism. Accurate determination of the free NAD:NADH ratio is therefore of importance for the unravelling of in vivo enzyme kinetics and to judge accurately the thermodynamic reversibility of each redox reaction.

Alleviating Redox Imbalance Enhances 7-Dehydrocholesterol Production in Engineered Saccharomyces cerevisiae

Maintaining redox balance is critical for the production of heterologous secondary metabolites, whereas on various occasions the native cofactor balance does not match the needs in engineered microorganisms. In this study, 7-dehydrocholesterol (7-DHC, a crucial precursor of vitamin D₃) biosynthesis pathway was constructed in Saccharomyces cerevisiae BY4742 with endogenous ergosterol synthesis pathway blocked by knocking out the erg5 gene (encoding C-22 desaturase). The deletion of erg5 led to redox imbalance with higher ratio of cytosolic free NADH/NAD⁺ and more glycerol and ethanol accumulation. To alleviate the redox imbalance, a water-forming NADH oxidase (NOX) and an alternative oxidase (AOX1) were employed in our system based on cofactor regeneration strategy. Consequently, the production of 7-dehydrocholesterol was increased by 74.4% in shake flask culture. In the meanwhile, the ratio of free NADH/NAD⁺ and the concentration of glycerol and ethanol were reduced by 78.0%, 50.7% and 7.9% respectively. In a 5-L bioreactor, the optimal production of 7-DHC reached 44.49(±9.63) mg/L. This study provides a reference to increase the production of some desired compounds that are restricted by redox imbalance.

Metabolic energy-based modelling explains product yielding in anaerobic mixed culture fermentations

The fermentation of glucose using microbial mixed cultures is of great interest given its potential to convert wastes into valuable products at low cost, however, the difficulties associated with the control of the process still pose important challenges for its industrial implementation. A deeper understanding of the fermentation process involving metabolic and biochemical principles is very necessary to overcome these difficulties. In this work a novel metabolic energy based model is presented that accurately predicts for the first time the experimentally observed changes in product spectrum with pH. The model predicts the observed shift towards formate production at high pH, accompanied with ethanol and acetate production. Acetate (accompanied with a more reduced product) and butyrate are predicted main products at low pH. The production of propionate between pH 6 and 8 is also predicted. These results are mechanistically explained for the first time considering the impact that variable proton motive potential and active transport energy costs have in terms of energy harvest over different products yielding. The model results, in line with numerous reported experiments, validate the mechanistic and bioenergetics hypotheses that fermentative mixed cultures products yielding appears to be controlled by the principle of maximum energy harvest and the necessity of balancing the redox equivalents in absence of external electron acceptors.

A fast sensor for in vivo quantification of cytosolic phosphate in Saccharomyces cerevisiae

Eukaryotic metabolism consists of a complex network of enzymatic reactions and transport processes which are distributed over different subcellular compartments. Currently, available metabolite measurement protocols allow to measure metabolite whole cell amounts which hinder progress to describe the in vivo dynamics in different compartments, which are driven by compartment specific concentrations. Phosphate (Pi) is an essential component for: (1) the metabolic balance of upper and lower glycolytic flux; (2) Together with ATP and ADP determines the phosphorylation energy. Especially, the cytosolic Pi has a critical role in disregulation of glycolysis in tps1 knockout. Here we developed a method that enables us to monitor the cytosolic Pi concentration in S. cerevisiae using an equilibrium sensor reaction: maltose + Pi < = > glucose + glucose-1-phosphate. The required enzyme, maltose phosphorylase from L. sanfranciscensis was overexpressed in S. cerevisiae. With this reaction in place, the cytosolic Pi concentration was obtained from intracellular glucose, G1P and maltose concentrations. The cytosolic Pi concentration was determined in batch and chemostat (D = 0.1 h(-1) ) conditions, which was 17.88 µmol/gDW and 25.02 µmol/gDW, respectively under Pi-excess conditions. Under Pi-limited steady state (D = 0.1 h(-1) ) conditions, the cytosolic Pi concentration dropped to only 17.7% of the cytosolic Pi in Pi-excess condition (4.42 µmol/gDW vs. 25.02 µmol/gDW). In response to a Pi pulse, the cytosolic Pi increased very rapidly, together with the concentration of sugar phosphates. Main sources of the rapid Pi increase are vacuolar Pi (and not the polyPi), as well as Pi uptake from the extracellular space. The temporal increase of cytosolic Pi increases the driving force of GAPDH reaction of the lower glycolytic reactions. The novel cytosol specific Pi concentration measurements provide new insight into the thermodynamic driving force for ATP hydrolysis, GAPDH reaction, and Pi transport over the plasma and vacuolar membranes.