An Improved ATP FRET Sensor For Yeast Shows Heterogeneity During Nutrient Transitions

Energy Aware Technology Mapping of Genetic Logic Circuits

Energy and its dissipation are fundamental to all living systems, including cells. Insufficient abundance of energy carriers─as caused by the additional burden of artificial genetic circuits─shifts a cell's priority to survival, also impairing the functionality of the genetic circuit. Moreover, recent works have shown the importance of energy expenditure in information transmission. Despite living organisms being non-equilibrium systems, non-equilibrium models capable of accounting for energy dissipation and non-equilibrium response curves are not yet employed in genetic design automation (GDA) software. To this end, we introduce Energy Aware Technology Mapping, the automated design of genetic logic circuits with respect to energy efficiency and functionality. The basis for this is an energy aware non-equilibrium steady state model of gene expression, capturing characteristics like energy dissipation─which we link to the entropy production rate─and transcriptional bursting, relevant to eukaryotes as well as prokaryotes. Our evaluation shows that a genetic logic circuit's functional performance and energy efficiency are disjoint optimization goals. For our benchmark, energy efficiency improves by 37.2% on average when comparing to functionally optimized variants. We discover a linear increase in energy expenditure and overall protein expression with the circuit size, where Energy Aware Technology Mapping allows for designing genetic logic circuits with the energetic costs of circuits that are one to two gates smaller. Structural variants improve this further, while results show the Pareto dominance among structures of a single Boolean function. By incorporating energy demand into the design, Energy Aware Technology Mapping enables energy efficiency by design. This extends current GDA tools and complements approaches coping with burden in vivo.

Energy Aware Technology Mapping of Genetic Logic Circuits

Energy and its dissipation are fundamental to all living systems, including cells. Insufficient abundance of energy carriers -as caused by the additional burden of artificial genetic circuits- shifts a cell's priority to survival, also impairing the functionality of the genetic circuit. Moreover, recent works have shown the importance of energy expenditure in information transmission. Despite living organisms being non-equilibrium systems, non-equilibrium models capable of accounting for energy dissipation and non-equilibrium response curves are not yet employed in genetic design automation (GDA) software. To this end, we introduce Energy Aware Technology Mapping, the automated design of genetic logic circuits with respect to energy efficiency and functionality. The basis for this is an energy aware non-equilibrium steady state (NESS) model of gene expression, capturing characteristics like energy dissipation -which we link to the entropy production rate- and transcriptional bursting, relevant to eukaryotes as well as prokaryotes. Our evaluation shows that a genetic logic circuit's functional performance and energy efficiency are disjoint optimization goals. For our benchmark, energy efficiency improves by 37.2% on average when comparing to functionally optimized variants. We discover a linear increase in energy expenditure and overall protein expression with the circuit size, where Energy Aware Technology Mapping allows for designing genetic logic circuits with the energy efficiency of circuits that are one to two gates smaller. Structural variants improve this further, while results show the Pareto dominance among structures of a single Boolean function. By incorporating energy demand into the design, Energy Aware Technology Mapping enables energy efficiency by design. This extends current GDA tools and complements approaches coping with burden in vivo.

Phenotypic heterogeneity follows a growth-viability tradeoff in response to amino acid identity

In their natural environments, microorganisms mainly operate at suboptimal growth conditions with fluctuations in nutrient abundance. The resulting cellular adaptation is subject to conflicting tasks: growth or survival maximisation. Here, we study this adaptation by systematically measuring the impact of a nitrogen downshift to 24 nitrogen sources on cellular metabolism at the single-cell level. Saccharomyces lineages grown in rich media and exposed to a nitrogen downshift gradually differentiate to form two subpopulations of different cell sizes where one favours growth while the other favours viability with an extended chronological lifespan. This differentiation is asymmetrical with daughter cells representing the new differentiated state with increased viability. We characterise the metabolic response of the subpopulations using RNA sequencing, metabolic biosensors and a transcription factor-tagged GFP library coupled to high-throughput microscopy, imaging more than 800,000 cells. We find that the subpopulation with increased viability is associated with a dormant quiescent state displaying differences in MAPK signalling. Depending on the identity of the nitrogen source present, differentiation into the quiescent state can be actively maintained, attenuated, or aborted. These results establish amino acids as important signalling molecules for the formation of genetically identical subpopulations, involved in chronological lifespan and growth rate determination.

Robustness of mitochondrial biogenesis and respiration explain aerobic glycolysis

A long-standing observation is that in fast-growing cells, respiration rate declines with increasing growth rate and is compensated by an increase in fermentation, despite respiration being more efficient than fermentation. This apparent preference for fermentation even in the presence of oxygen is known as aerobic glycolysis, and occurs in bacteria, yeast, and cancer cells. Considerable work has focused on understanding the potential benefits that might justify this seemingly wasteful metabolic strategy, but its mechanistic basis remains unclear. Here we show that aerobic glycolysis results from the saturation of mitochondrial respiration and the decoupling of mitochondrial biogenesis from the production of other cellular components. Respiration rate is insensitive to acute perturbations of cellular energetic demands or nutrient supplies, and is explained simply by the amount of mitochondria per cell. Mitochondria accumulate at a nearly constant rate across different growth conditions, resulting in mitochondrial amount being largely determined by cell division time. In contrast, glucose uptake rate is not saturated, and is accurately predicted by the abundances and affinities of glucose transporters. Combining these models of glucose uptake and respiration provides a quantitative, mechanistic explanation for aerobic glycolysis. The robustness of specific respiration rate and mitochondrial biogenesis, paired with the flexibility of other bioenergetic and biosynthetic fluxes, may play a broad role in shaping eukaryotic cell metabolism.

Lighting up Pyruvate Metabolism in Saccharomyces cerevisiae by a Genetically Encoded Fluorescent Biosensor

Monitoring intracellular pyruvate is useful for the exploration of fundamental metabolism and for guiding the construction of yeast cell factories for chemical production. Here, we employed a genetically encoded fluorescent Pyronic biosensor to light up the pyruvate metabolic state in the cytoplasm, nucleus, and mitochondria of Saccharomyces cerevisiae BY4741. A strong correlation was observed between the pyruvate fluctuation in mitochondria and cytoplasm when exposed to different metabolites. Further metabolic analysis of pyruvate uptake and glycolytic dynamics showed that glucose and fructose dose-dependently activated cytoplasmic pyruvate levels more effectively than direct exposure to pyruvate. Meanwhile, the Pyronic biosensor could visually distinguish phenotypes of the wild-type S. cerevisiae BY4741 and the pyruvate-hyperproducing S. cerevisiae TAM at a single-cell resolution, having the potential for high-throughput screening. Overall, Pyronic biosensors targeting different suborganelles contribute to mapping and studying the central carbon metabolism in-depth and guide the design and construction of yeast cell factories.

A fast method to distinguish between fermentative and respiratory metabolisms in single yeast cells

Saccharomyces cerevisiae adjusts its metabolism based on nutrient availability, typically transitioning from glucose fermentation to ethanol respiration as glucose becomes limiting. However, our understanding of the regulation of metabolism is largely based on population averages, whereas nutrient transitions may cause heterogeneous responses. Here we introduce iCRAFT, a method that couples the ATP Förster resonance energy transfer (FRET)-based biosensor yAT1.03 with Antimycin A to differentiate fermentative and respiratory metabolisms in individual yeast cells. Upon Antimycin A addition, respiratory cells experienced a sharp decrease of the normalized FRET ratio, while respiro-fermentative cells showed no response. Next, we tracked changes in metabolism during the diauxic shift of a glucose pre-grown culture. Following glucose exhaustion, the entire cell population experienced a progressive rise in cytosolic ATP produced via respiration, suggesting a gradual increase in respiratory capacity. Overall, iCRAFT is a robust tool to distinguish fermentation from respiration, offering a new single-cell opportunity to study yeast metabolism.

Genetically encoded ATP and NAD(P)H biosensors: potential tools in metabolic engineering

To date, many metabolic engineering tools and strategies have been developed, including tools for cofactor engineering, which is a common strategy for bioproduct synthesis. Cofactor engineering is used for the regulation of pyridine nucleotides, including NADH/NAD+ and NADPH/NADP+, and adenosine triphosphate/adenosine diphosphate (ATP/ADP), which is crucial for maintaining redox and energy balance. However, the intracellular levels of NADH/NAD+, NADPH/NADP+, and ATP/ADP cannot be monitored in real time using traditional methods. Recently, many biosensors for detecting, monitoring, and regulating the intracellular levels of NADH/NAD+, NADPH/NADP+, and ATP/ADP have been developed. Although cofactor biosensors have been mainly developed for use in mammalian cells, the potential application of cofactor biosensors in metabolic engineering in bacterial and yeast cells has received recent attention. Coupling cofactor biosensors with genetic circuits is a promising strategy in metabolic engineering for optimizing the production of biochemicals. In this review, we focus on the development of biosensors for NADH/NAD+, NADPH/NADP+, and ATP/ADP and the potential application of these biosensors in metabolic engineering. We also provide critical perspectives, identify current research challenges, and provide guidance for future research in this promising field.

Creatine Kinase Equilibration and ΔGATP over an Extended Range of Physiological Conditions: Implications for Cellular Energetics, Signaling, and Muscle Performance

In this report, we establish a straightforward method for estimating the equilibrium constant for the creatine kinase reaction (CK Keq″) over wide but physiologically and experimentally relevant ranges of pH, Mg2+ and temperature. Our empirical formula for CK Keq″ is based on experimental measurements. It can be used to estimate [ADP] when [ADP] is below the resolution of experimental measurements, a typical situation because [ADP] is on the order of micromolar concentrations in living cells and may be much lower in many in vitro experiments. Accurate prediction of [ADP] is essential for in vivo studies of cellular energetics and metabolism and for in vitro studies of ATP-dependent enzyme function under near-physiological conditions. With [ADP], we were able to obtain improved estimates of ΔGATP, necessitating the reinvestigation of previously reported ADP- and ΔGATP-dependent processes. Application to actomyosin force generation in muscle provides support for the hypothesis that, when [Pi] varies and pH is not altered, the maximum Ca2+-activated isometric force depends on ΔGATP in both living and permeabilized muscle preparations. Further analysis of the pH studies introduces a novel hypothesis around the role of submicromolar ADP in force generation.

Fluorescence microscopy imaging of mitochondrial metabolism in cancer cells

Mitochondrial metabolism is an important contributor to cancer cell survival and proliferation that coexists with enhanced glycolytic activity. Measuring mitochondrial activity is useful to characterize cancer metabolism patterns, to identify metabolic vulnerabilities and to identify new drug targets. Optical imaging, especially fluorescent microscopy, is one of the most valuable tools for studying mitochondrial bioenergetics because it provides semiquantitative and quantitative readouts as well as spatiotemporal resolution of mitochondrial metabolism. This review aims to acquaint the reader with microscopy imaging techniques currently used to determine mitochondrial membrane potential (ΔΨm), nicotinamide adenine dinucleotide (NADH), ATP and reactive oxygen species (ROS) that are major readouts of mitochondrial metabolism. We describe features, advantages, and limitations of the most used fluorescence imaging modalities: widefield, confocal and multiphoton microscopy, and fluorescent lifetime imaging (FLIM). We also discus relevant aspects of image processing. We briefly describe the role and production of NADH, NADHP, flavins and various ROS including superoxide and hydrogen peroxide and discuss how these parameters can be analyzed by fluorescent microscopy. We also explain the importance, value, and limitations of label-free autofluorescence imaging of NAD(P)H and FAD. Practical hints for the use of fluorescent probes and newly developed sensors for imaging ΔΨm, ATP and ROS are described. Overall, we provide updated information about the use of microscopy to study cancer metabolism that will be of interest to all investigators regardless of their level of expertise in the field.

Mitochondrial Irc3 helicase of the thermotolerant yeast Ogataea polymorpha displays dual DNA- and RNA-stimulated ATPase activity

Irc3 is one of the six mitochondrial helicases described in Saccharomyces cerevisiae. Physiological functions of Irc3 are not completely understood as both DNA metabolic processes and mRNA translation have been suggested to be direct targets of the helicase. In vitro analysis of Irc3 has been hampered by the modest thermostability of the S. cerevisiae protein. Here, we purified a homologous helicase (Irc3_op) of the thermotolerant yeast Ogataea polymorpha that retains structural integrity and catalytic activity at temperatures above 40 °C. Irc3_op can complement the respiratory deficiency phenotype of a S. cerevisiae irc3Δ mutant, indicating conservation of biochemical functions. The ATPase activity of Irc3_op is best stimulated by branched and double- stranded DNA cofactors. Single-stranded DNA binds Irc3_op tightly but is a weak activator of the ATPase activity. We could also detect a lower level stimulation with RNA, especially with molecules possessing a compact three-dimensional structure. These results support the idea that that Irc3 might have dual specificity and remodel both DNA and RNA molecules in vivo. Furthermore, our analysis of kinetic parameters predicts that Irc3 could have a regulatory function via sensing changes of the mitochondrial ATP pool or respond to the accumulation of single-stranded DNA.

Confocal imaging of biomarkers at a single-cell resolution: quantifying 'living' in 3D-printable engineered living material based on Pluronic F-127 and yeast Saccharomyces cerevisiae

BACKGROUND

Engineered living materials (ELMs) combine living cells with non-living scaffolds to obtain life-like characteristics, such as biosensing, growth, and self-repair. Some ELMs can be 3D-printed and are called bioinks, and their scaffolds are mostly hydrogel-based. One such scaffold is polymer Pluronic F127, a liquid at 4 °C but a biocompatible hydrogel at room temperature. In such thermally-reversible hydrogel, the microorganism-hydrogel interactions remain uncharacterized, making truly durable 3D-bioprinted ELMs elusive.

METHODS

We demonstrate the methodology to assess cell-scaffold interactions by characterizing intact alive yeast cells in cross-linked F127-based hydrogels, using genetically encoded ratiometric biosensors to measure intracellular ATP and cytosolic pH at a single-cell level through confocal imaging.

RESULTS

When embedded in hydrogel, cells were ATP-rich, in exponential or stationary phase, and assembled into microcolonies, which sometimes merged into larger superstructures. The hydrogels supported (micro)aerobic conditions and induced a nutrient gradient that limited microcolony size. External compounds could diffuse at least 2.7 mm into the hydrogels, although for optimal yeast growth bioprinted structures should be thinner than 0.6 mm. Moreover, the hydrogels could carry whole-cell copper biosensors, shielding them from contaminations and providing them with nutrients.

CONCLUSIONS

F127-based hydrogels are promising scaffolds for 3D-bioprinted ELMs, supporting a heterogeneous cell population primarily shaped by nutrient availability.

2-deoxyglucose transiently inhibits yeast AMPK signaling and triggers glucose transporter endocytosis, potentiating the drug toxicity

2-deoxyglucose is a glucose analog that impacts many aspects of cellular physiology. After its uptake and its phosphorylation into 2-deoxyglucose-6-phosphate (2DG6P), it interferes with several metabolic pathways including glycolysis and protein N-glycosylation. Despite this systemic effect, resistance can arise through strategies that are only partially understood. In yeast, 2DG resistance is often associated with mutations causing increased activity of the yeast 5’-AMP activated protein kinase (AMPK), Snf1. Here we focus on the contribution of a Snf1 substrate in 2DG resistance, namely the alpha-arrestin Rod1 involved in nutrient transporter endocytosis. We report that 2DG triggers the endocytosis of many plasma membrane proteins, mostly in a Rod1-dependent manner. Rod1 participates in 2DG-induced endocytosis because 2DG, following its phosphorylation by hexokinase Hxk2, triggers changes in Rod1 post-translational modifications and promotes its function in endocytosis. Mechanistically, this is explained by a transient, 2DG-induced inactivation of Snf1/AMPK by protein phosphatase 1 (PP1). We show that 2DG-induced endocytosis is detrimental to cells, and the lack of Rod1 counteracts this process by stabilizing glucose transporters at the plasma membrane. This facilitates glucose uptake, which may help override the metabolic blockade caused by 2DG, and 2DG export—thus terminating the process of 2DG detoxification. Altogether, these results shed a new light on the regulation of AMPK signaling in yeast and highlight a remarkable strategy to bypass 2DG toxicity involving glucose transporter regulation.

Visualizing the pH in Escherichia coli Colonies via the Sensor Protein mCherryEA Allows High-Throughput Screening of Mutant Libraries

Cytoplasmic pH in bacteria is tightly regulated by diverse active mechanisms and interconnected regulatory processes. Many processes and regulators underlying pH homeostasis have been identified via phenotypic screening of strain libraries for nongrowth at low or high pH values. Direct screens with respect to changes of the internal pH in mutant strain collections are limited by laborious methods, which include fluorescent dyes and radioactive probes. Genetically encoded biosensors equip single organisms or strain libraries with an internal sensor molecule during the generation of the strain. Here, we used the pH-sensitive mCherry variant mCherryEA as a ratiometric pH biosensor. We visualized the internal pH of Escherichia coli colonies on agar plates by the use of a GelDoc imaging system. Combining this imaging technology with robot-assisted colony picking and spotting allowed us to screen and select mutants with altered internal pH values from a small transposon mutagenesis-derived E. coli library. Identification of the transposon (Tn) insertion sites in strains with altered internal pH levels revealed that the transposon was inserted into trkH (encoding a transmembrane protein of the potassium uptake system) or rssB (encoding the adaptor protein RssB, which mediates the proteolytic degradation of the general stress response regulator RpoS), two genes known to be associated with pH homeostasis and pH stress adaptation. This successful screening approach demonstrates that the pH sensor-based analysis of arrayed colonies on agar plates is a sensitive approach for the rapid identification of genes involved in pH homeostasis or pH stress adaptation in E. coli.

IMPORTANCE Phenotypic screening of strain libraries on agar plates has become a versatile tool to understand gene functions and to optimize biotechnological platform organisms. Screening is supported by genetically encoded biosensors that allow to easily measure intracellular processes. For this purpose, transcription factor-based biosensors have emerged as the sensor type of choice. Here, the target stimulus initiates the activation of a response gene (e.g., a fluorescent protein), followed by transcription, translation, and maturation. Due to this mechanistic principle, biosensor readouts are delayed and cannot report the actual intracellular state of the cell in real time. To capture rapid intracellular processes adequately, fluorescent reporter proteins are extensively applied. However, these sensor types have not previously been used for phenotypic screenings. To take advantage of their properties, we established here an imaging method that allows application of a rapid ratiometric sensor protein for assessing the internal pH of colonies in a high-throughput manner.

Robustness: linking strain design to viable bioprocesses

Microbial cell factories are becoming increasingly popular for the sustainable production of various chemicals. Metabolic engineering has led to the design of advanced cell factories; however, their long-term yield, titer, and productivity falter when scaled up and subjected to industrial conditions. This limitation arises from a lack of robustness - the ability to maintain a constant phenotype despite the perturbations of such processes. This review describes predictable and stochastic industrial perturbations as well as state-of-the-art technologies to counter process variability. Moreover, we distinguish robustness from tolerance and discuss the potential of single-cell studies for improving system robustness. Finally, we highlight ways of achieving consistent and comparable quantification of robustness that can guide the selection of strains for industrial bioprocesses.

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.

Fluorescence-based sensing of the bioenergetic and physicochemical status of the cell

Fluorescence-based sensors play a fundamental role in biological research. These sensors can be based on fluorescent proteins, fluorescent probes or they can be hybrid systems. The availability of a very large dataset of fluorescent molecules, both genetically encoded and synthetically produced, together with the structural insights on many sensing domains, allowed to rationally design a high variety of sensors, capable of monitoring both molecular and global changes in living cells or in in vitro systems. The advancements in the fluorescence-imaging field helped researchers to obtain a deeper understanding of how and where specific changes occur in a cell or in vitro by combining the readout of the fluorescent sensors with the spatial information provided by fluorescent microscopy techniques. In this review we give an overview of the state of the art in the field of fluorescent biosensors and fluorescence imaging techniques, and eventually guide the reader through the choice of the best combination of fluorescent tools and techniques to answer specific biological questions. We particularly focus on sensors for probing the bioenergetics and physicochemical status of the cell.

Fluorescent toys 'n' tools lighting the way in fungal research

Although largely overlooked compared to bacterial infections, fungal infections pose a significant threat to the health of humans and other organisms. Many pathogenic fungi, especially Candida species, are extremely versatile and flexible in adapting to various host niches and stressful situations. This leads to high pathogenicity and increasing resistance to existing drugs. Due to the high level of conservation between fungi and mammalian cells, it is hard to find fungus-specific drug targets for novel therapy development. In this respect, it is vital to understand how these fungi function on a molecular, cellular as well as organismal level. Fluorescence imaging allows for detailed analysis of molecular mechanisms, cellular structures and interactions on different levels. In this manuscript, we provide researchers with an elaborate and contemporary overview of fluorescence techniques that can be used to study fungal pathogens. We focus on the available fluorescent labelling techniques and guide our readers through the different relevant applications of fluorescent imaging, from subcellular events to multispecies interactions and diagnostics. As well as cautioning researchers for potential challenges and obstacles, we offer hands-on tips and tricks for efficient experimentation and share our expert-view on future developments and possible improvements.

A yeast FRET biosensor enlightens cAMP signaling

The cAMP-PKA signaling cascade in budding yeast regulates adaptation to changing environments. We developed yEPAC, a FRET-based biosensor for cAMP measurements in yeast. We used this sensor with flow cytometry for high-throughput single cell-level quantification during dynamic changes in response to sudden nutrient transitions. We found that the characteristic cAMP peak differentiates between different carbon source transitions and is rather homogenous among single cells, especially for transitions to glucose. The peaks are mediated by a combination of extracellular sensing and intracellular metabolism. Moreover, the cAMP peak follows the Weber-Fechner law; its height scales with the relative, and not the absolute, change in glucose. Last, our results suggest that the cAMP peak height conveys information about prospective growth rates. In conclusion, our yEPAC-sensor makes possible new avenues for understanding yeast physiology, signaling, and metabolic adaptation.

Engineering crowding sensitivity into protein linkers

The intracellular environment contains a high concentration of biomacromolecules that present steric barriers and ample surface area for weak chemical interactions. Consequently, these forces influence protein conformations and protein self-assembly, with an outcome that depends on the sum of the effects resulting from crowding. Linkers are disordered domains that lack tertiary structure, and this flexible nature would render them susceptible to compression or extension under crowded conditions, compared to the equilibrium conformation in a dilute buffer. The change in distance between the linked proteins can become essential where it attenuates protein activity. In this chapter, we first discuss the experimental findings in vitro and in the cell on how linkers and other relevant macromolecules are affected by crowding. We focus on the dependence on the linker's size, flexibility, and the intra- and intermolecular interactions. Although the experimental data on the systematic variation of proteins in a buffer and cells is limited, extrapolating the available insights allows us to propose a protocol on how to engineer the directionality of crowding effects in the linker. Finally, we describe a straightforward experimental protocol on the determination of crowding sensitivity in a buffer and cell.