Single Yeast Cells Research Articles

Single-cell heterogeneity in ribosome content and the consequences for the growth laws.

Across species and environments, the ribosome content of cell populations correlates with population growth rate. The robustness and universality of this correlation have led to its classification as a "growth law." This law has fueled theories about how evolution selects for microbial organisms that maximize their growth rate based on nutrient availability, and it has informed models about how individual cells regulate their growth rates and ribosomal content. However, due to methodological limitations, this growth law has rarely been studied at the level of individual cells. While populations of fast-growing cells tend to have more ribosomes than populations of slow-growing cells, it is unclear whether individual cells tightly regulate their ribosome content to match their environment. Here, we employ recent groundbreaking single-cell RNA sequencing techniques to study this growth law at the single-cell level in two different microbes, S. cerevisiae (a single-celled yeast and eukaryote) and B. subtilis (a bacterium and prokaryote). In both species, we observe significant variation in the ribosomal content of single cells that is not predictive of growth rate. Fast-growing populations include cells exhibiting transcriptional signatures of slow growth and stress, as do cells with the highest ribosome content we survey. Broadening our focus to non-ribosomal transcripts reveals subpopulations of cells in unique transcriptional states suggestive that they have evolved to do things other than maximize their rate of growth. Overall, these results indicate that single-cell ribosome levels are not finely tuned to match population growth rates or nutrient availability and cannot be predicted by a Gaussian process model that assumes measurements are sampled from a normal distribution centered on the population average. This work encourages the expansion of growth law and other models that predict how growth rates are regulated or how they evolve to consider single-cell heterogeneity. To this end, we provide extensive data and analysis of ribosomal and transcriptomic variation across thousands of single cells from multiple conditions, replicates, and species.

Two-layer elastic models for single-yeast compressibility with flat microlevers.

Unicellular organisms such as yeast can survive in very different environments, thanks to a polysaccharide wall that reinforces their extracellular membrane. This wall is not a static structure, as it is expected to be dynamically remodeled according to growth stage, division cycle, environmental osmotic pressure and ageing. It is therefore of great interest to study the mechanics of these organisms, but they are more difficult to study than other mammalian cells, in particular because of their small size (radius of a few microns) and their lack of an adhesion machinery. Using flat cantilevers, we perform compression experiments on single yeast cells (S. cerevisiae) on poly-L-lysine-coated grooved glass plates, in the limit of small deformation using an atomic force microscope (AFM). Thanks to a careful decomposition of force-displacement curves, we extract local scaling exponents that highlight the non-stationary characteristic of the yeast behavior upon compression. Our multi-scale nonlinear analysis of the AFM force-displacement curves provides evidence for non-stationary scaling laws. We propose to model these phenomena based on a two-component elastic system, where each layer follows a different scaling law..

Droplet-based microfluidic platform for detecting agonistic peptides that are self-secreted by yeast expressing a G-protein-coupled receptor

BackgroundSingle-cell droplet microfluidics is an important platform for high-throughput analyses and screening because it provides an independent and compartmentalized microenvironment for reaction or cultivation by coencapsulating individual cells with various molecules in monodisperse microdroplets. In combination with microbial biosensors, this technology becomes a potent tool for the screening of mutant strains. In this study, we demonstrated that a genetically engineered yeast strain that can fluorescently sense agonist ligands via the heterologous expression of a human G-protein-coupled receptor (GPCR) and concurrently secrete candidate peptides is highly compatible with single-cell droplet microfluidic technology for the high-throughput screening of new agonistically active peptides.ResultsThe water-in-oil microdroplets were generated using a flow-focusing microfluidic chip to encapsulate engineered yeast cells coexpressing a human GPCR [i.e., angiotensin II receptor type 1 (AGTR1)] and a secretory agonistic peptide [i.e., angiotensin II (Ang II)]. The single yeast cells cultured in the droplets were then observed under a microscope and analyzed using image processing incorporating machine learning techniques. The AGTR1-mediated signal transduction elicited by the self-secreted Ang II peptide was successfully detected via the expression of a fluorescent reporter in single-cell yeast droplet cultures. The system could also distinguish Ang II analog peptides with different agonistic activities. Notably, we further demonstrated that the microenvironment of the single-cell droplet culture enabled the detection of rarely existing positive (Ang II-secreting) yeast cells in the model mixed cell library, whereas the conventional batch-culture environment using a shake flask failed to do so. Thus, our approach provided compartmentalized microculture environments, which can prevent the diffusion, dilution, and cross-contamination of peptides secreted from individual single yeast cells for the easy identification of GPCR agonists.ConclusionsWe established a droplet-based microfluidic platform that integrated an engineered yeast biosensor strain that concurrently expressed GPCR and self-secreted the agonistic peptides. This offers individually isolated microenvironments that allow the culture of single yeast cells secreting these peptides and gaging their signaling activities, for the high-throughput screening of agonistic peptides. Our platform base on yeast GPCR biosensors and droplet microfluidics will be widely applicable to metabolic engineering, environmental engineering, and drug discovery.

The hyphal-specific toxin candidalysin promotes fungal gut commensalism.

The fungus Candida albicans frequently colonizes the human gastrointestinal tract, from which it can disseminate to cause systemic disease. This polymorphic species can transition between growing as single-celled yeast and as multicellular hyphae to adapt to its environment. The current dogma of C. albicans commensalism is that the yeast form is optimal for gut colonization, whereas hyphal cells are detrimental to colonization but critical for virulence1-3. Here, we reveal that this paradigm does not apply to multi-kingdom communities in which a complex interplay between fungal morphology and bacteria dictates C. albicans fitness. Thus, whereas yeast-locked cells outcompete wild-type cells when gut bacteria are absent or depleted by antibiotics, hyphae-competent wild-type cells outcompete yeast-locked cells in hosts with replete bacterial populations. This increased fitness of wild-type cells involves the production of hyphal-specific factors including the toxin candidalysin4,5, which promotes the establishment of colonization. At later time points, adaptive immunity is engaged, and intestinal immunoglobulin A preferentially selects against hyphal cells1,6. Hyphal morphotypes are thus under both positive and negative selective pressures in the gut. Our study further shows that candidalysin has a direct inhibitory effect on bacterial species, including limiting their metabolic output. We therefore propose that C. albicans has evolved hyphal-specific factors, including candidalysin, to better compete with bacterial species in the intestinal niche.

A multilayer microfluidic system for studies of the dynamic responses of cellular proteins to oxygen switches at the single-cell level.

Oxygen levels vary in the environment. Oxygen availability has a major effect on almost all organisms, and oxygen is far more than a substrate for energy production. However, less is known about related biological processes under hypoxic conditions and about the adaptations to changing oxygen concentrations. The yeast Saccharomyces cerevisiae can adapt its metabolism for growth under different oxygen concentrations and can grow even under anaerobic conditions. Therefore, we developed a microfluidic device that can generate serial, accurately controlled oxygen concentrations for single-cell studies of multiple yeast strains. This device can construct a broad range of oxygen concentrations, [O2] through on-chip gas-mixing channels from two gases fed to the inlets. Gas diffusion through thin polydimethylsiloxane (PDMS) can lead to the equilibration of [O2] in the medium in the cell culture layer under gas cover regions within 2min. Here, we established six different and stable [O2] varying between ~0.1 and 20.9% in the corresponding layers of the device designed for multiple parallel single-cell culture of four different yeast strains. Using this device, the dynamic responses of different yeast transcription factors and metabolism-related proteins were studied when the [O2] decreased from 20.9% to serial hypoxic concentrations. We showed that different hypoxic conditions induced varying degrees of transcription factor responses and changes in respiratory metabolism levels. This device can also be used in studies of the aging and physiology of yeast under different oxygen conditions and can provide new insights into the relationship between oxygen and organisms. Integration, innovation and insight: Most living cells are sensitive to the oxygen concentration because they depend on oxygen for survival and proper cellular functions. Here, a composite microfluidic device was designed for yeast single-cell studies at a series of accurately controlled oxygen concentrations. Using this device, we studied the dynamic responses of various transcription factors and proteins to changes in the oxygen concentration. This study is the first to examine protein dynamics and temporal behaviors under different hypoxic conditions at the single yeast cell level, which may provide insights into the processes involved in yeast and even mammalian cells. This device also provides a base model that can be extended to oxygen-related biology and can acquire more information about the complex networks of organisms.

Average collision velocity of single yeast cells during electrochemically induced impacts.

We recorded current-time (i-t) profiles for oxidizing ferrocyanide (FCN) while spherical yeast cells of radius (rc ≈ 2 μm) collided with disk ultramicroelectrodes (UMEs) of increasing radius (re ≈ 12-45 μm). Collision signals appear as minority steps and majority blips of decreased current overlayed on the i-t baseline when cells block ferrocyanide flux (JFCN). We assigned steps to adsorption events and blips to bouncing collisions or contactless passages. Yeast cells exhibit impact signals of long duration (Δt ≈ 15-40 s) likely due to sedimentation. We assume cells travel a threshold distance (T) to generate collision signals of duration Δt. Thus, T represents a distance from the UME surface, at which cell perturbations on JFCN blend in with the UME noise level. To determine T, we simulated the UME current, while placing the cell at increasing distal points from the UME surface until matching the bare UME current. T-Values at 90°, 45°, and 0° from the UME edge and normal to the center were determined to map out T-regions in different experimental conditions. We estimated average collision velocities using the formula T/Δt, and mimicked cells entering and leaving T-regions at the same angle. Despite such oversimplification, our analysis yields average velocities compatible with rigorous transport models and matches experimental current steps and blips. We propose that single-cells encode collision dynamics into i-t signals only when cells move inside the sensitive T-region, because outside, perturbations of JFCN fall within the noise level set by JFCN and rc/re (experimentally established). If true, this notion will enable selecting conditions to maximize sensitivity in stochastic blocking electrochemistry. We also exploited the long Δt recorded here for yeast cells, which was undetectable for the fast microbeads used in early pioneering work. Because Δt depends on transport, it provides another analytical parameter besides current for characterizing slow-moving cells like yeast.

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.

The versatility of the putative transient receptor potential ion channels in regulating the calcium signaling in Aspergillus nidulans.

Transient receptor potential (TRP) ion channels are evolutionarily conserved integral membrane proteins with non-selective ion permeability, and they are widely distributed in mammals and single-cell yeast and serve as crucial mediators of sensory signals. However, the relevant information concerning TRP channels in Aspergillus nidulans remains inadequately understood. In this study, by gene deletion, green fluorescent protein tagging, and cytosolic Ca2+ transient monitoring techniques, the biological functions of three potential TRP channels (TrpA, TrpB, and TrpC) have been explored for which they play distinct and multiple roles in hyphal growth, conidiation, responsiveness to external stress, and regulation of intracellular Ca2+ homeostasis. The findings of this study on the functions of potential TRP channels in A. nidulans may serve as a valuable reference for understanding the roles of TRP homologs in industrial or medical strains of Aspergillus, as well as in other filamentous fungi.

Use of probiotic preparations to increase productive qualities in goats: a review

An analytical review of scientific publications on probiotics in goat breeding was carried out. It has been established that the most popular probiotic microorganisms in goat farming are bacteria of the species Bacillus subtilis, Bifidobacterium bifidum, Enterococcus faecium, Lactobacillus acidophilus, Lactobacillus plantarum and single-celled yeast of the species Saccharomyces cerevisiae. Including probiotic microflora in the diet increases the number of bacteria in the rumen contents of goats. Reducing the number of Clostridia and Escherichia coli in animal faeces is achieved by replacing the native faecal microflora with streptococci and lactic acid bacteria. It has been shown that feeding probiotic preparations is accompanied by an improvement in the metabolic status in the body of goats and is expressed by an increase in the concentration of total protein and its fractions, haemoglobin, erythrocytes, macro- and microelements in the blood of animals, and optimisation of lipid metabolism. Probiotics help preserve villi and inhibit inflammation of the intestinal epithelium of animals, exhibit antimutagenic and anticarcinogenic properties, and help reduce putrescine concentration in faeces. Feeding probiotics ensures an increase in daily milk yield, fat and protein content by increasing the digestibility of diet solids, primarily crude fibre. The probiotic potential of some microorganisms is expressed in increased concentrations of unsaturated fatty acids in goat milk and meat with a decrease in the atherogenic index of raw materials. The use of drugs helps to increase the absolute increase in live weight of goat kids against the background of the harmonious development of the physique of young animals due to the production of microbial phytase, a decrease in the redox potential of chyme and an increase in the number of microorganisms that consume lactic acid. Some authors report the absence of a significant effect when using probiotics in feeding lactating animals and raising goat kids.

Evidence of Noisy Oscillations of cAMP under Nutritional Stress Condition in Budding Yeast

The Ras/cAMP/PKA pathway regulates responses to nutrients’ availability and stress in budding yeast. The cAMP levels are subjected to negative feedback, and we have previously simulated a dynamic model of this pathway suggesting the existence of stable oscillatory states depending on the symmetrical and opposed activity of the RasGEF (Cdc25) and RasGAPs (Ira proteins). Noisy oscillations related to the activity of this pathway were reported by looking at the nuclear localization of the transcription factor Msn2, and sustained oscillations of the nuclear accumulation of Msn2 under the condition of limiting glucose were observed. We were able to reproduce the periodic accumulation of Msn2-GFP protein in a yeast cell under the condition of limiting glucose, and we also detected oscillations of cAMP. We used a sensor based on a fusion protein between YFP-Epac2-CFP expressed in yeast cells. The FRET between CFP and YFP is controlled by the cAMP concentration. This sensor allows us to monitor changes in cAMP concentrations in a single yeast cell over a long time. Using this method, we were able to detect noisy oscillations of cAMP levels in single yeast cells under conditions of nutritional stress caused by limiting glucose availability.

Replaying the evolution of multicellularity

The first organisms on Earth were presumably unicellular. At one point, evolution shaped these individual cells into multicellular organisms, which was a significant transition in the history of life on Earth. To investigate how this change happened, Bozdag et al. re-ran evolution in the lab and observed how single-celled yeast forms large multicellular aggregates.

Temperature influence on the compression and breakage behaviour of yeast cells.

Industrial biotechnology uses microbial cells to produce a wide range of products. While the genetic and molecular properties of these organisms are well understood, less is known about their mechanical properties. Previous work has established a test procedure for single yeast cells using a nanoindentation instrument equipped with a flat-punch probe, which allows single cells (Saccharomyces cerevisiae) to be compressed between two parallel surfaces. The resulting force-displacement curves clearly showed the bursting of the cells and were used to determine characteristics such as burst force and burst energy. Other studies have investigated the influence of growth conditions and measurement conditions on the mechanical characteristics. The recent study examined the mechanical characteristics according to the temperature during compression. Temperature from 0°C to 25°C has no significant effect on the micromechanical properties. Increasing the temperature up to 35°C causes a reduction in the strength of the cells. At even higher temperatures, up to 50°C, the burst force and burst energy increase significantly. A deformation geometry model was used to calculate the cell wall tensile strength as a function of temperature. The results of these studies may facilitate the identification of efficient conditions for cell disruption and product recovery in downstream biotechnological processes.

Repeatability and reproducibility of apparent exchange rate measurements in yeast cell phantoms using filter-exchange imaging

ObjectivesDevelopment of a protocol for validation and quality assurance of filter-exchange imaging (FEXI) pulse sequences with well-defined and reproducible phantoms.Materials and methodsA FEXI pulse sequence was implemented on a 7 T preclinical MRI scanner. Six experiments in three different test categories were established for sequence validation, demonstration of the reproducibility of phantoms and the measurement of induced changes in the apparent exchange rate (AXR). First, an ice–water phantom was used to investigate the consistency of apparent diffusion coefficient (ADC) measurements with different diffusion filters. Second, yeast cell phantoms were utilized to validate the determination of the AXR in terms of repeatability (same phantom and session), reproducibility (separate but comparable phantoms in different sessions) and directionality of diffusion encodings. Third, the yeast cell phantoms were, furthermore, used to assess potential AXR bias because of altered cell density and temperature. In addition, a treatment experiment with aquaporin inhibitors was performed to evaluate the influence of these compounds on the cell membrane permeability in yeast cells.ResultsFEXI-based ADC measurements of an ice–water phantom were performed for three different filter strengths, showed good agreement with the literature value of 1.099 × 10–3 mm2/s and had a maximum coefficient of variation (CV) of 0.55% within the individual filter strengths. AXR estimation in a single yeast cell phantom and imaging session with five repetitions resulted in an overall mean value of (1.49 ± 0.05) s−1 and a CV of 3.4% between the chosen regions of interest. For three separately prepared phantoms, AXR measurements resulted in a mean value of (1.50 ± 0.04) s−1 and a CV of 2.7% across the three phantoms, demonstrating high reproducibility. Across three orthogonal diffusion directions, a mean value of (1.57 ± 0.03) s−1 with a CV of 1.9% was detected, consistent with isotropy of AXR in yeast cells. Temperature and AXR were linearly correlated (R2 = 0.99) and an activation energy EA of 37.7 kJ/mol was determined by Arrhenius plot. Furthermore, a negative correlation was found between cell density (as determined by the reference ADC/fe) and AXR (R2 = 0.95). The treatment experiment resulted in significantly decreased AXR values at different temperatures in the treated sample compared to the untreated control indicating an inhibiting effect.ConclusionsUsing ice–water and yeast cell-based phantoms, a protocol for the validation of FEXI pulse sequences was established for the assessment of stability, repeatability, reproducibility and directionality. In addition, a strong dependence of AXR on cell density and temperature was shown. As AXR is an emerging novel imaging biomarker, the suggested protocol will be useful for quality assurance of AXR measurements within a study and potentially across multiple sites.

Direct Visualization of Structurally Similar Polysaccharides in Single Yeast Cells in Vivo by Multivariate Analysis Assisted Raman Microspectroscopy.

The demand for functional food ingredients like β-glucan has risen enormously in recent times owing to its use in many fields including the food and beverage, cosmetics, pharmaceuticals, and biotechnology industries. Among the many natural sources of glucans such as oats, barley, mushrooms, and seaweeds, yeast has a special advantage in the industrial production of glucans. However, characterizing glucans is not straightforward as there are many different structural variations such as α- or β-glucans with various configurations which vary in their physical and chemical properties. Currently, microscopy, chemical or genetic approaches are followed to study glucan synthesis and accumulation in single yeast cells. However, they are time-consuming, lack molecular specificity, or are practically not feasible for real applications. Therefore, we developed a Raman microspectroscopy based method to identify, distinguish, and visualize structurally similar glucan polysaccharides. By employing multivariate curve resolution analysis, we successfully separated Raman spectra of α- and β-glucans from mixtures with high specificity and visualized heterogeneous molecular distributions during the sporulation of yeasts at the single-cell level in a label-free manner. We believe such an approach when combined with a flow cell can achieve the sorting of yeast cells based on the accumulation of glucans for various applications. Further, such an approach can also be extended to various other biological systems to investigate structurally similar carbohydrate polymers in a fast and reliable manner.

Alzheimer's Disease: Significant Benefit from the Yeast-Based Models.

Alzheimer's disease (AD) is an age-related, multifaceted neurological disorder associated with accumulation of aggregated proteins (amyloid Aβ and hyperphosphorylated tau), loss of synapses and neurons, and alterations in microglia. AD was recognized by the World Health Organization as a global public health priority. The pursuit of a better understanding of AD forced researchers to pay attention to well-defined single-celled yeasts. Yeasts, despite obvious limitations in application to neuroscience, show high preservation of basic biological processes with all eukaryotic organisms and offer great advantages over other disease models due to the simplicity, high growth rates on low-cost substrates, relatively simple genetic manipulations, the large knowledge base and data collections, and availability of an unprecedented amount of genomic and proteomic toolboxes and high-throughput screening techniques, inaccessible to higher organisms. Research reviewed above clearly indicates that yeast models, together with other, more simple eukaryotic models including animal models, C. elegans and Drosophila, significantly contributed to understanding Aβ and tau biology. These models allowed high throughput screening of factors and drugs that interfere with Aβ oligomerization, aggregation and toxicity, and tau hyperphosphorylation. In the future, yeast models will remain relevant, with a focus on creating novel high throughput systems to facilitate the identification of the earliest AD biomarkers among different cellular networks in order to achieve the main goal-to develop new promising therapeutic strategies to treat or prevent the disease.

Transcriptomic changes in single yeast cells under various stress conditions

BackgroundThe stress response of Saccharomyces cerevisiae has been extensively studied in the past decade. However, with the advent of recent technology in single-cell transcriptome profiling, there is a new opportunity to expand and further understanding of the yeast stress response with greater resolution on a system level. To understand transcriptomic changes in baker’s yeast S. cerevisiae cells under stress conditions, we sequenced 117 yeast cells under three stress treatments (hypotonic condition, glucose starvation and amino acid starvation) using a full-length single-cell RNA-Seq method.ResultsWe found that though single cells from the same treatment showed varying degrees of uniformity, technical noise and batch effects can confound results significantly. However, upon careful selection of samples to reduce technical artifacts and account for batch-effects, we were able to capture distinct transcriptomic signatures for different stress conditions as well as putative regulatory relationships between transcription factors and target genes.ConclusionOur results show that a full-length single-cell based transcriptomic analysis of the yeast may help paint a clearer picture of how the model organism responds to stress than do bulk cell population-based methods.

Microflow cytometer chip with multiple electro-rotation units for measuring electrical properties of single yeast cells

At present, many single-cell electrical parameter measurement techniques have exhibit broad application prospects, but there are still some limitations such as complex single-cell operation and time-consuming measurement. This paper proposed a microflow cytometer chip with multiple electro-rotation units for measuring the electrical properties of single cells. The microdevice leverages three serial electro-rotation units to rapidly obtain rotation speeds under different signal frequencies. According to the rotation results, the electrical parameters (membrane permittivity and cytoplasmic conductivity) are estimated by using Maxwell's mixture equation fitting and neural network fitting methods respectively. We demonstrated the measurement advantages of combining microflow and electro-rotation techniques. Experimental results show that the cytometer measurement method greatly improves the throughput of single-cell characterization with a guaranteed error of less than 0.8%. The microdevice provides a microfluidic platform capable of characterizing the electrical properties of cells and the possibility of combining with neural networks.

Tuneable Cell-Laden Double-Emulsion Droplets for Enhanced Signal Detection.

Water-in-oil-in-water (w/o/w) or double-emulsion (DE) droplets have been widely used for cellular assays at a single-cell level because of their stability and biocompatibility. The oil shell of w/o/w droplets plays the role of a semipermeable membrane that allows substances with low molecular weight (e.g., water) to travel through but restricts those with high molecular weight (e.g., fluorescent biomarkers). Therefore, the core of DEs can be manipulated using osmosis, resulting in the shrinking or swelling of the core. Water leaves the inner aqueous phase to the outer phase via the oil shell when the osmotic pressure of the outer phase is higher than that in the inner phase, causing the shrinkage of DEs and vice versa. These processes can be achieved by transferring the DEs to hypertonic or hypotonic solutions. Manipulation of the core size of DEs can be beneficial to cellular assays. First, due to the selectivity of the oil shell of DEs, the concentration of biomarkers in the core increases when the inner aqueous phase is shrunk, resulting in the enhancement of biosignals. We demonstrate this by encapsulating the Bgl3 enzyme-secreting yeast with a substrate that displays fluorescence after hydrolyzation. In a second application, a single GFP-tagged yeast cell was encapsulated in DEs. After swelling the core of DEs, we observe that the larger core of DEs promotes cell growth compared to those with the smaller cores, leading to more intracellular proteins (green-fluorescent protein) for screening. These osmotic manipulations provide new tools for droplet-based biochemistry.

Using the AKAR3-EV biosensor to assess Sch9p- and PKA-signalling in budding yeast.

Budding yeast uses the TORC1-Sch9p and cAMP-PKA signalling pathways to regulate adaptations to changing nutrient environments. Dynamic and single-cell measurements of the activity of these cascades will improve our understanding of the cellular adaptation of yeast. Here, we employed the AKAR3-EV biosensor developed for mammalian cells to measure the cellular phosphorylation status determined by Sch9p and PKA activity in budding yeast. Using various mutant strains and inhibitors, we show that AKAR3-EV measures the Sch9p- and PKA-dependent phosphorylation status in intact yeast cells. At the single-cell level, we found that the phosphorylation responses are homogenous for glucose, sucrose, and fructose, but heterogeneous for mannose. Cells that start to grow after a transition to mannose correspond to higher normalized Förster resonance energy transfer (FRET) levels, in line with the involvement of Sch9p and PKA pathways to stimulate growth-related processes. The Sch9p and PKA pathways have a relatively high affinity for glucose (K0.5 of 0.24 mM) under glucose-derepressed conditions. Lastly, steady-state FRET levels of AKAR3-EV seem to be independent of growth rates, suggesting that Sch9p- and PKA-dependent phosphorylation activities are transient responses to nutrient transitions. We believe that the AKAR3-EV sensor is an excellent addition to the biosensor arsenal for illuminating cellular adaptation in single yeast cells.

Directed evolution of Rhodotorula gracilisd-amino acid oxidase using single-cell hydrogel encapsulation and ultrahigh-throughput screening.

Engineering catalytic and biophysical properties of enzymes is an essential step en route to advanced biomedical and industrial applications. Here, we developed a high-throughput screening and directed evolution strategy relying on single-cell hydrogel encapsulation to enhance the performance of d-Amino acid oxidase from Rhodotorula gracilis (RgDAAOx), a candidate enzyme for cancer therapy. We used a cascade reaction between RgDAAOx variants surface displayed on yeast and horseradish peroxidase (HRP) in the bulk media to trigger enzyme-mediated crosslinking of phenol-bearing fluorescent alginate macromonomers, resulting in hydrogel formation around single yeast cells. The fluorescent hydrogel capsules served as an artificial phenotype and basis for pooled library screening by fluorescence activated cell sorting (FACS). We screened a RgDAAOx variant library containing ∼106 clones while lowering the d-Ala substrate concentration over three sorting rounds in order to isolate variants with low Km. After three rounds of FACS sorting and regrowth, we isolated and fully characterized four variants displayed on the yeast surface. We identified variants with a more than 5-fold lower Km than the parent sequence, with an apparent increase in substrate binding affinity. The mutations we identified were scattered across the RgDAAOx structure, demonstrating the difficulty in rationally predicting allosteric sites and highlighting the advantages of scalable library screening technologies for evolving catalytic enzymes.