Individual Yeast Cells Research Articles

Research on adjustable measuring range vibration sensors based on optical fiber tweezers

We presents a vibration sensor with an adjustable measuring range based on optical fiber tweezers. The sensor employs a tapered optical fiber to trap individual yeast cells in a liquid environment, forming a sensing structure. Vibration signals from the source are transmitted through the medium to the cells in the optical trap. By adjusting the input optical power, the maximum restoring force of the light trap is increased when the vibration amplitude exceeds the measuring range, thus achieving variable-range vibration sensing. Experimental results demonstrate that the measuring range of the vibration sensor increases linearly with trapping power, ranging from 0.5 to 12.5 mW. This method extends the measuring range while maintaining the original sensing structure, making the optical fiber tweezers vibration sensor more adaptable for multi-task measurements with varying measuring ranges.

Gaining insights into the responses of individual yeast cells to ethanol fermentation using Raman tweezers and chemometrics

Saccharomyces cerevisiae is the most common microbe used for the industrial production of bioethanol, and it encounters various stresses that inhibit cell growth and metabolism during fermentation. However, little is currently known about the physiological changes that occur in individual yeast cells during ethanol fermentation. Therefore, in this work, Raman spectroscopy and chemometric techniques were employed to monitor the metabolic changes of individual yeast cells at distinct stages during high gravity ethanol fermentation. Raman tweezers was used to acquire the Raman spectra of individual yeast cells. Multivariate curve resolution-alternating least squares (MCR-ALS) and principal component analysis were employed to analyze the Raman spectra dataset. MCR-ALS extracted the spectra of proteins, phospholipids, and triacylglycerols and their relative contents in individual cells. Changes in intracellular biomolecules showed that yeast cells undergo three distinct physiological stages during fermentation. In addition, heterogeneity among yeast cells significantly increased in the late fermentation period, and different yeast cells may respond to ethanol stress via different mechanisms. Our findings suggest that the combination of Raman tweezers and chemometrics approaches allows for characterizing the dynamics of molecular components within individual cells. This approach can serve as a valuable tool in investigating the resistance mechanism and metabolic heterogeneity of yeast cells during ethanol fermentation.

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.

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.

Ultrahigh-Throughput Directed Evolution of Polymer-Degrading Enzymes Using Yeast Display.

Enzymes that degrade synthetic polymers have attracted intense interest for eco-friendly plastic recycling. However, because enzymes did not evolve for the cleavage of abiotic polymers, directed evolution strategies are needed to enhance activity for plastic degradation. Previous directed evolution efforts relied on polymer degradation assays that were limited to screening ∼104 mutants. Here, we report a high-throughput yeast surface display platform to rapidly evaluate >107 enzyme mutants for increased activity in cleaving synthetic polymers. In this platform, individual yeast cells display distinct mutants, and enzyme activity is detected by a change in fluorescence upon the cleavage of a synthetic probe resembling a polymer of interest. Highly active mutants are isolated by fluorescence activated cell sorting and identified through DNA sequencing. To demonstrate this platform, we performed directed evolution of a polyethylene terephthalate (PET)-depolymerizing enzyme, leaf and branch compost cutinase (LCC). We identified activity-boosting mutations that substantially increased the kinetics of degradation of solid PET films. Biochemical assays and molecular dynamics (MD) simulations of the most active variants suggest that the H218Y mutation improves the binding of the enzyme to PET. Overall, this evolution platform increases the screening throughput of polymer-degrading enzymes by 3 orders of magnitude and identifies mutations that enhance kinetics for depolymerizing solid substrates.

Flow cytometry-based high-throughput screening of synthetic peptides for palladium adsorption

Conventionally, the measurement of metal ion adsorption capacity in biosorbent relies on expensive and time-consuming ICP-OES technique. Herein, a semi-quantitative method to measure Pd(II) adsorption capacity of single cells has been presented by analyzing side scatter (SSC) intensity in flow cytometry. Within the sensitive range and applicable conditions, excellent linearity correlation (R2 ranges from 0.89 to 0.96) between the amount of Pd(II) absorbed on yeast and the fold increase in SSC intensity has been observed. Using this method, six strains with high Pd adsorption capacities have sorted from a yeast library with metal-binding peptides displayed (up to 107 strains) based on SSC signal intensity. The optimal peptide (EF1) displayed on yeast and E. coli surface demonstrated Pd adsorption improvements of ∼32% and ∼200%, respectively. In summary, our study proposes an alternative high-throughput method for analyzing the Pd(II) adsorption capacity of individual yeast cells, enabling the screening of specific peptides/proteins with high Pd(II) affinity from extensive libraries.

Hybrid machine-learning framework for volumetric segmentation and quantification of vacuoles in individual yeast cells using holotomography.

The precise, quantitative evaluation of intracellular organelles in three-dimensional (3D) imaging data poses a significant challenge due to the inherent constraints of traditional microscopy techniques, the requirements of the use of exogenous labeling agents, and existing computational methods. To counter these challenges, we present a hybrid machine-learning framework exploiting correlative imaging of 3D quantitative phase imaging with 3D fluorescence imaging of labeled cells. The algorithm, which synergistically integrates a random-forest classifier with a deep neural network, is trained using the correlative imaging data set, and the trained network is then applied to 3D quantitative phase imaging of cell data. We applied this method to live budding yeast cells. The results revealed precise segmentation of vacuoles inside individual yeast cells, and also provided quantitative evaluations of biophysical parameters, including volumes, concentration, and dry masses of automatically segmented vacuoles.

Comparative biodeterioration at air interfaces of adipate-based polyester polyurethane coatings by fungal microcolonies of Aureobasidium sp. W12

Understanding conditions that enable environmentally common microbes to aggressively deteriorate polymer materials are important for predicting and controlling the environmental fates of these materials. For protective paints and coatings in terrestrial environments, processes at air interfaces are among important factors to understand. Here, we track fungal biodeterioration at air/solid polymer interfaces under nutrient limitation and high humidity, using polymer compositions common in commercial polyester polyurethanes. A fungal isolate, Aureobasidium sp. W12, was collected from an aircraft and identified as a polyester degrader through screening assays. Two polyadipate-based materials were then used for W12 coating deterioration analysis: a commercial polyester polyurethane, Irogran® PS455–203, and a model polyester urethane, PEA-HM. Single and micro-aggregated cell clusters distributed within ∼1.5 mm diameter regions were prepared on the polymer surfaces and incubated with no supplemental nutrients at >95% relative humidity for up to 13 days. Coating deterioration was semi-quantitatively monitored through ester carbonyl loss by transmission FTIR spectroscopy and both materials were rapidly deteriorated, although at different rates. With ∼0.5 monolayer cell surface coverage, PEA-HM showed about 6 × greater molar ester deterioration versus Irogran® over the first 24 h. By 13 days, the polyester fractions of Irogran coatings were deteriorated to an average depth of about 0.1 µm, while PEA-HM coatings about 1 µm thick were completely deteriorated in 5 days within and beyond cell covered regions. Localized analysis of non-uniform PEA-HM deterioration showed that quantities on the order of 10 individual Aureobasidium yeast cells could locally deteriorate through 1–2 µm of PEA-HM coating within 12 days (with deterioration rates up to about 2 × 10−6 µmol ester / (cell × day)). These results correlate conditions and polymer properties that promote high deterioration potentials of Aureobasidium W12 microcolonies at air / coating interfaces.

The Pathogenic Yeast Candida parapsilosis Forms Pseudohyphae through Different Signaling Pathways Depending on the Available Carbon Source.

ABSTRACTCandida parapsilosis is an emerging fungal pathogen that primarily affects immunocompromised patients in hospitals. A significant risk factor is the use of implanted medical devices, which support the growth of biofilms composed of a mixture of individual yeast cells and chains of elongated pseudohyphal cells. The morphological switch between these two forms is triggered by cues from the environment, including nutrient availability and temperature. We examined how different nutrient sources affect the balance between yeast and pseudohyphae and found that cells grown in the presence of five- or six-carbon sugars form more pseudohyphae at 30°C than at 37°C. Conversely, cells grown on glycerol, a three-carbon polyalcohol, form more pseudohyphae at 37°C. Furthermore, we found that different regulators influence pseudohyphal growth on glucose at 30°C compared with those on glycerol at 37°C. In particular, cAMP signaling and the sirtuin deacetylase Hst1 were required for pseudohyphal growth on glycerol at 37°C but not on glucose at 30°C. Finally, we found that the carbon source on which C. parapsilosis is grown can influence its ability to establish an infection in a wax moth model. Overall, this study reveals that environmental conditions affect not only the extent of pseudohyphal growth but also which pathways and regulators govern pseudohyphal formation.IMPORTANCE Candida parapsilosis is one of the leading causes of hospital-acquired yeast infections and poses a significant risk to immunocompromised people. Two of its properties that contribute to infection are metabolic flexibility, to use a range of nutrients available in the host, and cellular dimorphism, to switch between round yeast cells and chains of elongated pseudohyphal cells. Uncovering the molecular mechanisms that regulate these processes could reveal new targets for antifungal drugs. We found that for C. parapsilosis, the balance between yeast and pseudohyphal cells depends on the nutrients available and the growth temperature. Moreover, these environmental changes can affect its ability to cause infections. Finally, we found that a potential sensor of the cell’s metabolic state, the sirtuin Hst1, contributes to pseudohyphal growth for cells grown on glycerol. These findings indicate that the shape and virulence of C. parapsilosis likely vary depending on its location in the host.

Engineering cell-based microstructures to study the effect of structural complexity on in vitro bioaccessibility of a lipophilic bioactive compound.

A fundamental understanding of the influence of food microstructures on the bioaccessibility of micronutrients is vital for the design of functionally efficient foods. This study investigated the effect of microstructural features of model foods on the bioaccessibility of a bioactive compound - curcumin, using a unique bottom-up approach. In this approach, individual yeast cells with infused curcumin were coated with oppositely charged polyelectrolytes: first in poly(diallyl-dimethylammonium chloride), then in dextran sulfate or alginate, and assembled electrostatically to generate two types of cell clusters. These cell clusters were embedded in an alginate film to form a tissue-like structure. The influence of cell clustering and extracellular matrix on the release of encapsulated curcumin from cell-based microcarriers during simulated digestion was evaluated. Cell clusters that maintained their integrity during in vitro simulated digestion retained up to twice as much curcumin upon addition of the simulated intestinal fluid (SIF) compared to single cells during the first hour of intestinal digestion. Despite significant differences in the release profile, no spatial heterogeneity of curcumin release across a cell cluster was observed with the imaging measurements. Embedding single cells or cell clusters in calcium-crosslinked alginate films resulted in another 20-30% increase in curcumin retention and a prolonged barrier effect for more than 2 hours compared to microstructures without the films. This bottom-up approach of engineering cell-based tissue-like structures proves to be an effective method for investigating the contributions of microstructural properties of food matrices to influencing bioaccessibility of bioactives and guides future development of functional food materials.

Stressed-out yeast do not pass GO.

Using microfluidics and imaging, Argüello-Miranda et al. (2021. J. Cell Biol.https://doi.org/10.1083/jcb.202103171) monitor the response of individual yeast cells to nutrient withdrawal. They discover that cells arrest not only in the early G1 phase as expected, but also later in the cell cycle, and that an endoplasmic reticulum stress-induced transcription factor, Xbp1, is critical for arrest at other cell cycle phases.

Quantification of the Adhesion Strength of Candida albicans to Tooth Enamel.

Caries is one of the most prevalent diseases worldwide, which is caused by the degradation of the tooth enamel surface. In earlier research the opportunistic pathogen Candida albicans has been associated with the formation of caries in children. Colonization of teeth by C. albicans starts with the initial adhesion of individual yeast cells to the tooth enamel surface. In this study, we visualized the initial colonization of C. albicans yeast cells on pellicle-covered enamel by scanning electron microscopy. To quantitatively unravel the initial adhesion strength, we applied fluidic force microscopy-based single-cell force spectroscopy to examine the key adhesion parameters adhesion force, rupture length and de-adhesion work. We analyzed single saliva-treated or untreated yeast cells on tooth enamel specimens with or without salivary pellicle. Under all tested conditions, adhesion forces in the lower nanonewton range were determined. Furthermore, we have found that all adhesion parameters were enhanced on the pellicle-covered compared to the uncovered enamel. Our data suggest that initial adhesion occurs through a strong interaction between yeast cell wall-associated adhesins and the salivary pellicle. Future SCFS studies may show whether specific management of the salivary pellicle reduces the adhesion of C. albicans on teeth and thus contributes to caries prophylaxis.

Telomere shortening causes distinct cell division regimes during replicative senescence in Saccharomyces cerevisiae

BackgroundTelomerase-negative cells have limited proliferation potential. In these cells, telomeres shorten until they reach a critical length and induce a permanently arrested state. This process called replicative senescence is associated with genomic instability and participates in tissue and organismal ageing. Experimental data using single-cell approaches in the budding yeast model organism show that telomerase-negative cells often experience abnormally long cell cycles, which can be followed by cell cycles of normal duration, before reaching the terminal senescent state. These series of non-terminal cell cycle arrests contribute to the heterogeneity of senescence and likely magnify its genomic instability. Due to their apparent stochastic nature, investigating the dynamics and the molecular origins of these arrests has been difficult. In particular, whether the non-terminal arrests series stem from a mechanism similar to the one that triggers terminal senescence is not known.ResultsHere, we provide a mathematical description of sequences of non-terminal arrests to understand how they appear. We take advantage of an experimental data set of cell cycle duration measurements performed in individual telomerase-negative yeast cells that keep track of the number of generations since telomerase inactivation. Using numerical simulations, we show that the occurrence of non-terminal arrests is a generation-dependent process that can be explained by the shortest telomere reaching a probabilistic threshold length. While the onset of senescence is also triggered by telomere shortening, we highlight differences in the laws that describe the number of consecutive arrests in non-terminal arrests compared to senescence arrests, suggesting distinct underlying mechanisms and cellular states.ConclusionsReplicative senescence is a complex process that affects cell divisions earlier than anticipated, as exemplified by the frequent occurrence of non-terminal arrests early after telomerase inactivation. The present work unravels two kinetically and mechanistically distinct generation-dependent processes underlying non-terminal and terminal senescence arrests. We suggest that these two processes are responsible for two consequences of senescence at the population level, the increase of genome instability on the one hand, and the limitation of proliferation capacity on the other hand.

Yeast cell segmentation in microstructured environments with deep learning

Cell segmentation is a major bottleneck in extracting quantitative single-cell information from microscopy data. The challenge is exasperated in the setting of microstructured environments. While deep learning approaches have proven useful for general cell segmentation tasks, previously available segmentation tools for the yeast-microstructure setting rely on traditional machine learning approaches. Here we present convolutional neural networks trained for multiclass segmenting of individual yeast cells and discerning these from cell-similar microstructures. An U-Net based semantic segmentation approach, as well as a direct instance segmentation approach with a Mask R-CNN are demonstrated. We give an overview of the datasets recorded for training, validating and testing the networks, as well as a typical use-case. We showcase the methods’ contribution to segmenting yeast in microstructured environments with a typical systems or synthetic biology application. The models achieve robust segmentation results, outperforming the previous state-of-the-art in both accuracy and speed. The combination of fast and accurate segmentation is not only beneficial for a posteriori data processing, it also makes online monitoring of thousands of trapped cells or closed-loop optimal experimental design feasible from an image processing perspective.Code is and data samples are available at https://git.rwth-aachen.de/bcs/projects/tp/multiclass-yeast-seg.

A Versatile Strategy to Coat Individual Cell with Fully/Partially Covered Shell for Preparation of Self-Propelling Living Cells.

Coating living cells with a functional shell has been regarded as an effective way to protect them against environmental stress, regulate their biological behaviors, or extend their functionalities. Here, we reported a facile method to prepare fully or partially coated shells on an individual yeast cell surface by visible light-induced graft polymerization. In this strategy, yeast cells that were surface-absorbed with polyethylenimine (PEI) were deposited on the negatively charged glass slide to form a single layer by electrostatic interaction. Then, surface-initiated graft polymerization of poly(ethylene glycol) diacrylate (PEGDA) on yeast cells under visible light irradiation was carried out to generate cross-linked shells on the cells. The process of surface modification had negligible influence on the viability of yeast cells due to the mild reaction condition. Additionally, compared to the native yeast cells, a 17.5 h of delay in division was observed when the graft polymerization was performed under 15 mW/cm2 irradiation for 30 min. Introducing artificial shell endowed yeast cells with significant resistance against lyticase, and the protection can be enhanced by increasing the thickness of shell. Moreover, the partially coated yeast cells would be prepared by simply adjusting the reaction condition such as irradiation density and time. By immobilizing urease on the functional patch, the asymmetrically modified yeast cells exhibited self-propelling capability, and the speed of directional movement reached 4 μm/s in the presence of 200 mM urea. This tunable coating individual cell strategy with varying functionality has great potential applications in fields of cell-based drug delivery, cell therapy, biocatalysis, and tissue engineering.

A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels

Stochastic gene expression leads to inherent variability in expression outcomes even in isogenic single-celled organisms grown in the same environment. The Drop-Seq technology facilitates transcriptomic studies of individual mammalian cells, and it has had transformative effects on the characterization of cell identity and function based on single-cell transcript counts. However, application of this technology to organisms with different cell size and morphology characteristics has been challenging. Here we present yeastDrop-Seq, a yeast-optimized platform for quantifying the number of distinct mRNA molecules in a cell-specific manner in individual yeast cells. Using yeastDrop-Seq, we measured the transcriptomic impact of the lifespan-extending compound mycophenolic acid and its epistatic agent guanine. Each treatment condition had a distinct transcriptomic footprint on isogenic yeast cells as indicated by distinct clustering with clear separations among the different groups. The yeastDrop-Seq platform facilitates transcriptomic profiling of yeast cells for basic science and biotechnology applications.

Strongly oversized fission yeast cells lack any size control and tend to grow linearly rather than bilinearly.

During the mitotic cycle, the rod-shaped fission yeast cells grow only at their tips. The newly born cells grow first unipolarly at their old end, but later in the cycle, the 'new end take-off' event occurs, resulting in bipolar growth. Photographs were taken of several steady-state and induction synchronous cultures of different cell cycle mutants of fission yeast, generally larger than wild type. Length measurements of many individual cells were performed from birth to division. For all the measured growth patterns, three different functions (linear, bilinear and exponential) were fitted, and the most adequate one was chosen by using specific statistical criteria, considering the altering parameter numbers. Although the growth patterns were heterogeneous in all the cultures studied, we could find some tendencies. In cultures with sufficiently wide size distribution, cells large enough at birth tend to grow linearly, whereas the other cells generally tend to grow bilinearly. We have found that among bilinearly growing cells, the larger they are at birth, the rate change point during their bilinear pattern occurs earlier in the cycle. This shifting near to the beginning of the cycle might finally cause a linear pattern, if the cells are even larger. In all of the steady-state cultures studied, a size control mechanism operates to maintain homeostasis. By contrast, strongly oversized cells of induction synchronous cultures lack any sizer, and their cycle rather behaves like an adder. We could determine the critical cell size for both the G1 and G2 size controls, where these mechanisms become cryptic. TAKE AWAY: Most individual fission yeast cells in steady-state cultures grow bilinearly. In strongly oversized fission yeast cells, linear growth dominates over bilinear. Above birth length thresholds, both the G1 and G2 size controls become cryptic.

A programmable fate decision landscape underlies single-cell aging in yeast.

Chromatin instability and mitochondrial decline are conserved processes that contribute to cellular aging. Although both processes have been explored individually in the context of their distinct signaling pathways, the mechanism that determines which process dominates during aging of individual cells is unknown. We show that interactions between the chromatin silencing and mitochondrial pathways lead to an epigenetic landscape of yeast replicative aging with multiple equilibrium states that represent different types of terminal states of aging. The structure of the landscape drives single-cell differentiation toward one of these states during aging, whereby the fate is determined quite early and is insensitive to intracellular noise. Guided by a quantitative model of the aging landscape, we genetically engineered a long-lived equilibrium state characterized by an extended life span.

Programmed aging in yeast cells

Aging Following the fate of individual yeast cells has revealed aging to be more of a programmable decision process rather than a simple accumulation of deleterious events. Li et al. combined single-cell studies and mathematical modeling to show that yeast cells showed two different forms of aging: one with less ribosomal DNA silencing, in which nucleoli were degraded, and another with less heme accumulation and hemedependent transcription, in which mitochondria were more affected. Overexpression of the lysine deacetylase Sir2, which contributes to ribosomal DNA silencing, led to a third cell-aging fate in which the average life span was extended. If other cells age in similar ways, then this study may provide new ways to consider dynamics of aging and strategies to extend the health span. Science this issue p. [325][1] [1]: /lookup/doi/10.1126/science.aax9552

Electrospray patterning of yeast cells for applications in alcoholic fermentation

Yeast cells patterned by pulsed jet electrospray showed a high alcoholic fermentation rate. Multi-dimensional patterns of individual yeast cells were produced by varying the experimental parameters of the electrospray system. The electrospray process, which employed a vibrational electric field, could control patterns of viable yeast cells at a cellular resolution. This novel system for electrospraying viable cells can be applied to biological process engineering including whole cell biochip techniques and micro fermentation processes for biochemical studies.