Cell size and morphological properties of yeast Saccharomyces cerevisiae in relation to growth temperature

Heat shock transcription factor-mediated thermal tolerance and cell size plasticity in marine diatoms

Diatoms are a crucial component of marine ecosystems, recognized for their broad environmental adaptability and wide temperature tolerance. However, the molecular mechanisms underlying their adaptability to diverse temperatures are unknown. In this study, we discover that heat shock transcription factors (HSFs) are potentially important for thermal tolerance in diatoms. Our study focuses on PtHSF2, annotated as HSF2 in Phaeodactylum tricornutum's genome, which is ubiquitous in diatoms. Overexpression of PtHSF2 markedly enhances thermal tolerance and increases cell size; causes significant differential expression of several genes, including cell division cycle protein 45-like (PtCdc45-like), ATM (ataxia telangiectasia mutated), ATR (ataxia telangiectasia and Rad3-related), light-harvesting complex protein 2 (Lhcx2), and fatty acid desaturase. Cleavage Under Targets and Tagmentation (CUT&Tag) and CUT&Tag-qPCR analyses demonstrate that PtHSF2 directly targets and upregulates PtCdc45-like and Lhcx2 while downregulating ATP-binding cassette transporter. Functional validation of PtCdc45-like shows that its overexpression results in larger cell size, enhances antioxidant capacity, and improves cell survival at elevated temperatures. Collectively, our findings elucidate the molecular mechanism by which PtHSF2 mediates high-temperature tolerance in diatoms and validate the functions of its target gene PtCdc45-like. These results highlight the importance of HSFs in diatom temperature adaptation and provide insights into temperature acclimation in microalgae.

Cellular variability as a driver for bioprocess innovation and optimization

Cellular heterogeneity plays a crucial role in biotechnological processes, significantly influencing metabolic activity, product yield, and process consistency. This review explores the different dimensions of cellular heterogeneity, focusing on its manifestation at both single-cell and population levels. The study examines how factors such as asymmetric cell division, age, and environmental conditions contribute to functional diversity within cell populations, with an emphasis on microorganisms like yeast. Age-related cellular heterogeneity, in particular, is highlighted for its impact on metabolic pathways, mitochondrial function, and secondary metabolite production, which directly affect bioprocess outcomes. Furthermore, the review discusses advanced techniques for detecting and managing heterogeneity, including surface marker-based approaches, which utilize proteins, polysaccharides, and lipids, and label-free methods that leverage cellular volume and physical properties for separation. Understanding and controlling cellular heterogeneity is essential for optimizing industrial bioprocesses, improving yield, and ensuring product quality. The review also underscores the potential of emerging biotechnological tools, such as real-time single-cell analysis and microfluidic devices, in enhancing separation techniques and managing cellular diversity for better process efficiency and robustness.

The rate of glucose metabolism sets the cell morphology across yeast strains and species

Yeasts are a diverse group of unicellular fungi that have developed a wide array of phenotypes and traits over 400 million years of evolution. However, we still lack an understanding of the biological principles governing the range of cell morphologies, metabolic modes, and reproductive strategies yeasts display. In this study, we explored the relationship between cell morphology and metabolism in sixteen yeast strains across eleven species. We performed a quantitative analysis of the physiology and morphology of these strains and discovered a strong correlation between the glucose uptake rate (GUR) and the surface-area-to-volume ratio. 14C-glucose uptake experiments demonstrated that the GUR for a given strain is governed either by glucose transport capacity or glycolytic rate, indicating that it is rather the rate of glucose metabolism in general that correlates with cell morphology. Furthermore, perturbations in glucose metabolism influenced cell sizes, whereas manipulating cell size did not affect GUR, suggesting that glucose metabolism determines cell size rather than the reverse. Across the strains tested, we also found that the rate of glucose metabolism influenced ethanol production rate, biomass yield, and carbon dioxide transfer rate. Overall, our findings demonstrate that the rate of glucose metabolism is a key factor shaping yeast cell morphology and physiology, offering new insights into the fundamental principles of yeast biology.

Deep learning enabled rapid classification of yeast species in food by imaging of yeast microcolonies

Diverse species of yeasts are commonly associated with food and food production environments. The contamination of food products by spoilage yeasts poses significant challenges, leading to quality degradation and food loss. Similarly, the introduction of undesirable strains during fermentation can cause considerable challenges with the quality and progress of the fermentation process. Conventional detection methods require the isolation of visible yeast colonies for genetic or biochemical characterization, which takes 5-7 days and demands significant labor. This study presents a deep learning-based yeast classification approach that combines conventional cultivation methods, white light optical microscopy of microcolony, and deep learning techniques for rapidly detecting and classifying yeasts. Utilizing deep convolutional neural networks, the model accurately discriminates 7 different yeasts within 6 h, achieving a mPrecision of 96.0 % and a mRecall of 96.3 %. Synthetic image dataset generated by generative adversarial networks (GAN) model further improved the model performance for Debaryomyces hansenii and Wickerhamomyces anomalus, yeast species with lower initial classification performance. With the addition of synthetic images in the training process, Precision for W. anomalus and Recall for D. hansenii increased by 7.7 % and 5.6 %, respectively. The yeast classification model was validated in the presence of microscopic food debris using tomato and tomato juice as representative examples of fresh produce and processed juice. The model maintained high classification accuracy in the presence of food debris (mPrecision and mRecall >93.9 %). Overall, this methodology significantly accelerates the detection and classification of yeast species using conventional cultivation and simple white light microscopy in combination with deep learning. The simplicity, including low cost of the experimental approaches and the robustness of the deep learning model make it a highly applicable approach for routine yeast monitoring and yeast spoilage control in the food industry.

An irreversible thermodynamic model of prebiological dissipative molecular structures inside vacuoles at the surface of the Archean Ocean

A prebiotic model, based in the framework of thermodynamic efficiency loss from small dissipative eukaryote organisms is developed to describe the maximum possible concentration of solar power to be dissipated on topological circular molecules structures encapsulated in lipid-walled vacuoles, which floated in the Archean oceans. By considering previously, the analysis of 71 species examined by covering 18 orders of mass magnitude from the Megapteranovaeangliae to Saccharomyces cerevisiae suggest that in molecular structures of smaller masses than any living being known nowadays, the power dissipation must be directly proportional to the power of the photons of solar origin that impinge them to give rise to the formation of more complex self-assembled molecular structures at the prebiotic stage by a quantum mechanics model of resonant photon wavelength excitation. The analysis of 12 circular molecules (encapsulated in lipid-walled vacuoles) relevant to the evolution of life on planet Earth such as the five nucleobases, and some aromatic molecules as pyrimidine, porphyrin, chlorin, coumarin, xanthine, etc., were carried out. Considering one vacuole of each type of molecule per square meter of the ocean's surface of planet Earth (1.8∗1015 vacuoles), their dissipative operation would require only 10-10 times the matter used by the biomass currently existing on Earth. Relevant numbers (1020-1021) for the annual dissipative cycles corresponding to high energy photo chemical events, which in principle allow the assembling of more complex polymers, were obtained. The previous figures are compatible with some results obtained by followers of the primordial soup theory where under certain suppositions about the Archean chemical kinetical changes on the precursors of RNA and DNA try to justify the formation rate of RNA and DNA components and the emergence of life within a 10-million-year window, 3.5 billion years ago. The physical foundation perspective and the simplicity of the proposed approach suggests that it can serve as a possible template for both, the development of new kind of experiments, and for prebiotic theories that address self-organization occurring inside such vacuoles. Our model provides a new way to conceptualize the self-production of simple cyclic dissipative molecular structures in the Archean period of planet Earth. © 2017 ElsevierInc.Allrightsreserved.

[PSI]-CIC: A Deep-Learning Pipeline for the Annotation of Sectored Saccharomyces cerevisiae Colonies

The [ P S I + ] prion phenotype in yeast manifests as a white, pink, or red color pigment. Experimental manipulations destabilize prion phenotypes, and allow colonies to exhibit [ p s i - ] (red) sectored phenotypes within otherwise completely white colonies. Further investigation of the size and frequency of sectors that emerge as a result of experimental manipulation is capable of providing critical information on mechanisms of prion curing, but we lack a way to reliably extract this information. Images of experimental colonies exhibiting sectored phenotypes offer an abundance of data to help uncover molecular mechanisms of sectoring, yet the structure of sectored colonies is ignored in traditional biological pipelines. In this study, we present [PSI]-CIC, the first computational pipeline designed to identify and characterize features of sectored yeast colonies. To overcome the barrier of a lack of manually annotated data of colonies, we develop a neural network architecture that we train on synthetic images of colonies and apply to real images of [ P S I + ] , [ p s i - ] , and sectored colonies. In hand-annotated experimental images, our pipeline correctly predicts the state of approximately 95% of colonies detected and frequency of sectors in approximately 89.5% of colonies detected. The scope of our pipeline could be extended to categorizing colonies grown under different experimental conditions, allowing for more meaningful and detailed comparisons between experiments. Our approach streamlines the analysis of sectored yeast colonies providing a rich set of quantitative metrics and provides insight into mechanisms driving the curing of prion phenotypes.

Optimal fermentation conditions for growth and recombinant protein production in Pichia pastoris: Strain selection, ploidy level and carbon source

High-cell-density fermentation is a critical aspect of industrial protein production, requiring the selection of an optimal growth medium and carbon source. Pichia pastoris, a methylotrophic yeast, has been established as a widespread recombinant protein expression system in the food and pharmaceutical industries. The primary objective of this work was to create a superior platform for producing alternative proteins thus contributing to future innovation in these sectors. This study compared three wild-type strains, with two of them also analyzed in their diploid versions, using shake flasks and bioreactors. It investigated glucose and glycerol as carbon sources using mCherry as a protein model. Glycerol emerged as the preferred carbon source, resulting in over 40% increase in biomass concentrations compared to glucose across all strains. Notably, wild-type strain Y-7556 reached an exceptional biomass concentration of 244 g DCW/L in just 48 h, the highest reported to date, highlighting the potential of high-cell-density fermentation in P. pastoris. Regarding protein expression, the diploid version of Y-11430 produced >43% of purified mCherry protein after 123 h of fermentation, compared to the haploid counterpart. Our findings underscore the advantages of diploid strains, optimized fermentation media, and carbon source selection, effectively addressing crucial gaps in the literature.

Statistical optimized production of Phytase from Hanseniaspora guilliermondii S1 and studies on purification, homology modelling and growth promotion effect

This investigation was performed to obtain a promising phytase enzyme producing yeast. In this regard, the PSM was used to isolate the phytase-producing Hanseniaspora guilliermondii S1 (MG663578) from sugarcane juice. The SSF optimum conditions for phytase generation were optimized using (OVAT) one-variable-at-a-time strategy using both Box-Behnken design and shake flask method (g/100 ml: 0.05 yeast extract, 0.15 Peptone, 0.05 malt extract 0.50 dextrose, pH 5.8 and 28ᵒC). The protein model developed was shown to be adequate for phytase production (91% accuracy), with the greatest phytase productivity in shake flask with substrate jack fruit seed powder being 395 ± 0.43 U/ml compared to 365U/ml for the BBD projected value. Crude Phytase was partially purified with a protein recovery of 43%, revealing a molecular weight of 120 kDa. It had an enzyme kinetic value of Km 3.3 mM and a Vmax of 19.1 mol/min. The 3D structure of PhyS1 amino acid sequences (PhyS1. B99990002) was simulated using Modeler 9.23, and the validated result revealed that 86.7% were in the favored region by Ramachandran plot. The SAVES server verified the 3D PDB file as satisfactory, and the model (in.pdb format) was uploaded in the PMDB database with the accession number ID: PM0082974. At the lab level, Hanseniaspora guilliermondii S1 (MG663578) producing phytase exhibited successful plant growth promotion activity in Ragi - CO 19 (Eleusine coracana L.) and Rice -Navarai - IR 64 (Oryza sativa L.). As a result, a phytase-based formulation for sustainable agriculture must be developed and tested on a large scale in diverse geographical areas of agricultural lands to determine its effect and potential on plant development.

The relationship between cell density and cell count differs among Saccharomyces yeast species

There is a recent push to develop wild and non-domesticated Saccharomyces yeast strains into useful model systems for research in ecology and evolution. Yet, the variation between species and strains in important population parameters remains largely undescribed. Here, we investigated the relationship between two commonly used measures in microbiology to estimate growth rate - cell density and cell count - in 23 strains across all eight Saccharomyces species . We found that the slope of this relationship significantly differs among species and a given optical density (OD) does not translate into the same number of cells across species. We provide a cell number calculator based on our OD measurements for each strain used in this study. Surprisingly, we found a slightly positive relationship between cell size and the slope of the cell density-cell count relationship. Our results show that the strain- and species-specificity of the cell density and cell count relationship should be taken into account, for instance when running competition experiments requiring equal starting population sizes or when estimating the fitness of strains with different genetic backgrounds in experimental evolution studies.

Sec18 binds the tethering/SM complex HOPS to engage the Qc-SNARE for membrane fusion

Membrane fusion is regulated by Rab GTPases, their tethering effectors such as HOPS, SNARE proteins on each fusion partner, SM proteins to catalyze SNARE assembly, Sec17 (SNAP), and Sec18 (NSF). Though concentrated HOPS can support fusion without Sec18, we now report that fusion falls off sharply at lower HOPS levels, where direct Sec18 binding to HOPS restores fusion. This Sec18-dependent fusion needs adenine nucleotide but neither ATP hydrolysis nor Sec17. Sec18 enhances HOPS recognition of the Qc-SNARE. With high levels of HOPS, Qc has a Km for fusion of a few nM. Either lower HOPS levels, or substitution of a synthetic tether for HOPS, strikingly increases the Km for Qc to several hundred nM. With dilute HOPS, Sec18 returns the Km for Qc to low nM. In contrast, HOPS concentration and Sec18 have no effect on Qb-SNARE recognition. Just as Qc is required for fusion but not for the initial assembly of SNAREs in trans, impaired Qc recognition by limiting HOPS without Sec18 still allows substantial trans-SNARE assembly. Thus, in addition to the known Sec18 functions of disassembling SNARE complexes, oligomerizing Sec17 for membrane association, and allowing Sec17 to drive fusion without complete SNARE zippering, we report a fourth Sec18 function, the Sec17-independent binding of Sec18 to HOPS to enhance functional Qc-SNARE engagement.

Automated quantification of lipid contents of Lipomyces starkeyi using deep-learning-based image segmentation

Intracellular lipid droplets (LDs), subcellular organelles playing a role in long-term carbon storage, have immense potential in biofuel and dietary lipid production. Monitoring the state of LDs in living cells is of utmost importance for quick biomass harvest and screening promising isolates. Here, a deep-learning-based segmentation model was developed for automatic detection and segmentation of LDs using the model yeast species Lipomyces starkeyi, leading to fast and accurate quantification of lipid contents in liquid cultures. The trained model detected the yeast's cell and LDs in light microscopic images with an accuracy of 98% and 92%, respectively. Lipid content prediction using pixel numbers counted in segmented LDs showed high similarity to lipid quantification results obtained with gas chromatography-mass spectrometry. This automated quantification can highly reduce cost and time in real-time monitoring of lipid production, thereby providing an efficient tool in bio-fermentation.

Studying the impact of cell age on the yeast growth behaviour of Saccharomyces pastorianus var. carlsbergensis by magnetic separation

Despite the fact that yeast is a widely used microorganism in the food, beverage, and pharmaceutical industries, the impact of viability and age distribution on cultivation performance has yet to be fully understood. For a detailed analysis of fermentation performance and physiological state, we introduced a method of magnetic batch separation to isolate daughter and mother cells from a heterogeneous culture. By binding functionalised iron oxide nanoparticles, it is possible to separate the chitin-enriched bud scars by way of a linker protein. This reveals that low viability cultures with a high daughter cell content perform similarly to a high viability culture with a low daughter cell content. Magnetic separation results in the daughter cell fraction (>95%) showing a 21% higher growth rate in aerobic conditions than mother cells and a 52% higher rate under anaerobic conditions. These findings emphasise the importance of viability and age during cultivation and are the first step towards improving the efficiency of yeast-based processes.

Investigation of osmotic shock effect on pulsed electric field treated S. cerevisiae yeast cells

Pulsed electric field (PEF) treatment is known to cause plasma membrane permeabilization of microorganisms, an effect known as electroporation. PEF treatment is very attractive since it can achieve permeabilization with or without lethal damage in accordance with desired results. This study aimed to expand the accomplishment of electroporation outcomes by applying sudden post-PEF osmotic composition change of the media. Changes in yeast cells' viability, size and plasma membrane regeneration rate were evaluated. However, we still have questions about the intracellular biochemical processes responsible for plasma membrane recovery after electroporation. Our suggested candidate is the high osmolarity glycerol (HOG) kinase pathway. The HOG pathway in Saccharomyces cerevisiae yeasts is responsible for volume recovery after dangerous shape modifications and intracellular water disbalance caused by environmental osmotic pressure changes. Thus, we evaluated the HOG pathway inactivation effect on S. cerevisiae's reaction to PEF treatment. Results showed that Hog1 deficient S. cerevisiae cells were considerably more sensitive to electric field treatment, confirming a link between the HOG pathway and S. cerevisiae recovery process after electroporation. By suddenly changing the osmolarity of the media after PEF we influenced the cells' plasma membrane recovery rate, severity of permeabilization and survivability of yeast cells. Studies of electroporation in combination with various treatments might improve electric field application range, efficiency, and optimization of the process.

The environmental stress response regulates ribosome content in cell cycle-arrested S. cerevisiae

Prolonged cell cycle arrests occur naturally in differentiated cells and in response to various stresses such as nutrient deprivation or treatment with chemotherapeutic agents. Whether and how cells survive prolonged cell cycle arrests is not clear. Here, we used S. cerevisiae to compare physiological cell cycle arrests and genetically induced arrests in G1-, meta- and anaphase. Prolonged cell cycle arrest led to growth attenuation in all studied conditions, coincided with activation of the Environmental Stress Response (ESR) and with a reduced ribosome content as determined by whole ribosome purification and TMT mass spectrometry. Suppression of the ESR through hyperactivation of the Ras/PKA pathway reduced cell viability during prolonged arrests, demonstrating a cytoprotective role of the ESR. Attenuation of cell growth and activation of stress induced signaling pathways also occur in arrested human cell lines, raising the possibility that the response to prolonged cell cycle arrest is conserved.

Evaluation of Physicochemical and Microbial Properties of Extracts from Wine Lees Waste of Matelica’s Verdicchio and Their Applications in Novel Cosmetic Products

Wine lees are sediments deposited on the walls and bottom of barrels resulting from wine fermentation and mainly consist of yeasts. Saccharomyces cerevisiae extracts, rich in beneficial components for the skin, have already been used in cosmesis, while wine lees have not been well exploited by the cosmetics industry yet. The aim of this work was the full characterization of the wine lees from Verdicchio’s wine, with the aim to exploit it as a beneficial ingredient in new cosmetic products. After mapping the microbial composition of the sample waste, the parameters for the sonication extraction process were optimized and the physicochemical properties of the extract were analyzed. The efficiency of the aqueous extraction—and in particular the yeast cell lysis necessary for the release of proteins from the cell—was assessed by evaluating cell shape and size, and protein release, under scanning electron microscopy (SEM), dynamic light scattering (DLS) and Bradford’s protein assays. Thus, the total phenol content and antioxidant capacity of the supernatant recovered from native and sonicated lees were determined by Folin–Ciocalteu’s and spectrophotometric assays, respectively. To quantify the heavy metals and highlight the presence of microelements beneficial for the skin, inductively coupled plasma-mass spectrometry (ICP-MS) was applied. In vitro metabolic activity and cytotoxicity were tested on both HaCat keratinocytes and human gingival fibroblasts, showing that wine lees are safe for skin’s cells. The results show that sonicated lees appear to be more interesting than native ones as a consequence of the release of the active ingredients from the cells. Due to the high antioxidant capacity, content of beneficial elements for skin and an appropriate microbiologic profile, wine lees were included in five new solid cosmetic products and tested for challenge test, compatibility with human skin, sensory analysis, trans epidermal water loss (TEWL) and sebometry.

Using oils and fats to replace sugars as feedstocks for biomanufacturing: Challenges and opportunities for the yeast Yarrowia lipolytica

More than 200 million tons of plant oils and animal fats are produced annually worldwide from oil, crops, and the rendered animal fat industry. Triacylglycerol, an abundant energy-dense compound, is the major form of lipid in oils and fats. While oils or fats are very important raw materials and functional ingredients for food or related products, a significant portion is currently diverted to or recovered as waste. To significantly increase the value of waste oils or fats and expand their applications with a minimal environmental footprint, microbial biomanufacturing is presented as an effective strategy for adding value. Though both bacteria and yeast can be engineered to use oils or fats as the biomanufacturing feedstocks, the yeast Yarrowia lipolytica is presented as one of the most attractive platforms. Y. lipolytica is oleaginous, generally regarded as safe, demonstrated as a promising industrial producer, and has unique capabilities for efficient catabolism and bioconversion of lipid substrates. This review summarizes the major challenges and opportunities for Y. lipolytica as a new biomanufacturing platform for the production of value-added products from oils and fats. This review also discusses relevant cellular and metabolic engineering strategies such as fatty acid transport, fatty acid catabolism and bioconversion, redox balances and energy yield, cell morphology and stress response, and bioreaction engineering. Finally, this review highlights specific product classes including long-chain diacids, wax esters, terpenes, and carotenoids with unique synthesis opportunities from oils and fats in Y. lipolytica.

Apparent diameter and cell density of yeast strains with different ploidy

Optical density at 600 nm (OD₆₀₀) measurements are routinely and quickly taken to estimate cell density in cultivation and to track cell growth. The yeast Saccharomyces cerevisiae is one of the microorganisms most used in industry, and the OD₆₀₀ values are frequently adopted as the indicator of yeast cell density, according to the Beer-Lambert law. Because the OD₆₀₀ value is based on turbidity measurement, the Beer-Lambert law can be applied only for microbial cultivation with low cell densities. The proportionality constants strongly depend on several parameters such as cell size. Typically, yeast strains are categorized into haploids and diploids. It is well known that cell size of diploid yeasts is larger than haploid cells. Additionally, polyploid (especially triploid and tetraploid) yeast cells are also employed in several human-activities such as bread-making and lager-brewing. As a matter of fact, there is almost no attention paid to the difference in the proportionality constants depending on the yeast ploidy. This study presents information for cell size of haploid, diploid, triploid, and tetraploid yeasts with isogenic background, and describes their proportionality constants (k) corresponding to the molar extinction coefficient (ε) in the Beer-Lambert law. Importantly, it was found that the constants are inversely proportional to apparent cell diameters estimated by flow cytometric analysis. Although each cell property highly depends on genetic and environmental factors, a set of results obtained from yeast strains with different ploidy in the current study would serve as a major reference source for researchers and technical experts.

Ultrastructure expansion microscopy reveals the cellular architecture of budding and fission yeast

The budding and fission yeasts Saccharomyces cerevisiae and Schizosaccharomyces pombe have served as invaluable model organisms to study conserved fundamental cellular processes. Although super-resolution microscopy has in recent years paved the way to a better understanding of the spatial organization of molecules in cells, its wide use in yeasts has remained limited due to the specific know-how and instrumentation required, contrasted with the relative ease of endogenous tagging and live-cell fluorescence microscopy. To facilitate super-resolution microscopy in yeasts, we have extended the ultrastructure expansion microscopy (U-ExM) method to both S. cerevisiae and S. pombe, enabling a 4-fold isotropic expansion. We demonstrate that U-ExM allows imaging of the microtubule cytoskeleton and its associated spindle pole body, notably unveiling the Sfi1p–Cdc31p spatial organization on the appendage bridge structure. In S. pombe, we validate the method by monitoring the homeostatic regulation of nuclear pore complex number through the cell cycle. Combined with NHS-ester pan-labelling, which provides a global cellular context, U-ExM reveals the subcellular organization of these two yeast models and provides a powerful new method to augment the already extensive yeast toolbox.

This article has an associated First Person interview with Kerstin Hinterndorfer and Felix Mikus, two of the joint first authors of the paper.

Highly-automated, high-throughput replication of yeast-based logic circuit design assessments

We describe an experimental campaign that replicated the performance assessment of logic gates engineered into cells of Saccharomyces cerevisiae by Gander et al. Our experimental campaign used a novel high-throughput experimentation framework developed under Defense Advanced Research Projects Agency's Synergistic Discovery and Design program: a remote robotic lab at Strateos executed a parameterized experimental protocol. Using this protocol and robotic execution, we generated two orders of magnitude more flow cytometry data than the original experiments. We discuss our results, which largely, but not completely, agree with the original report and make some remarks about lessons learned. Graphical Abstract.

Changes to the mtDNA copy number during yeast culture growth

We show that the mitochondrial DNA (mtDNA) copy number in growing cultures of the yeast Saccharomyces cerevisiae increases by a factor of up to 4, being lowest (approx. 10 per haploid genome) and stable during rapid fermentative growth, and highest at the end of the respiratory phase. When yeast are grown on glucose, the onset of the mtDNA copy number increase coincides with the early stages of the diauxic shift, and the increase continues through respiration. A lesser yet still substantial copy number increase occurs when yeast are grown on a nonfermentable carbon source, i.e. when there is no diauxic shift. The mtDNA copy number increase during and for some time after the diauxic shift is not driven by an increase in cell size. The copy number increase occurs in both haploid and diploid strains but is markedly attenuated in a diploid wild isolate that is a ready sporulator. Strain-to-strain differences in mtDNA copy number are least apparent in fermentation and most apparent in late respiration or stationary phase. While changes in mitochondrial morphology and function were previously known to accompany changes in physiological state, it had not been previously shown that the mtDNA copy number changes substantially over time in a clonal growing culture. The mtDNA copy number in yeast is therefore a highly dynamic phenotype.

Enhancing biofuels production by engineering the actin cytoskeleton in Saccharomyces cerevisiae

Saccharomyces cerevisiae is widely employed as a cell factory for the production of biofuels. However, product toxicity has hindered improvements in biofuel production. Here, we engineer the actin cytoskeleton in S. cerevisiae to increase both the cell growth and production of n-butanol and medium-chain fatty acids. Actin cable tortuosity is regulated using an n-butanol responsive promoter-based autonomous bidirectional signal conditioner in S. cerevisiae. The budding index is increased by 14.0%, resulting in the highest n-butanol titer of 1674.3 mg L-1. Moreover, actin patch density is fine-tuned using a medium-chain fatty acid responsive promoter-based autonomous bidirectional signal conditioner. The intracellular pH is stabilized at 6.4, yielding the highest medium-chain fatty acids titer of 692.3 mg L-1 in yeast extract peptone dextrose medium. Engineering the actin cytoskeleton in S. cerevisiae can efficiently alleviate biofuels toxicity and enhance biofuels production.

AI-based forecasting of ethanol fermentation using yeast morphological data

Several industries require getting information of products as soon as possible during fermentation. However, the trade-off between sensing speed and data quantity presents challenges for forecasting fermentation product yields. In this study, we tried to develop AI models to forecast ethanol yields in yeast fermentation cultures, using cell morphological data. Our platform involves the quick acquisition of yeast morphological images using a nonstaining protocol, extraction of high-dimensional morphological data using image processing software, and forecasting of ethanol yields via supervised machine learning. We found that the neural network algorithm produced the best performance, which had a coefficient of determination of >0.9 even at 30 and 60 min in the future. The model was validated using test data collected using the CalMorph-PC(10) system, which enables rapid image acquisition within 10 min. AI-based forecasting of product yields based on cell morphology will facilitate the management and stable production of desired biocommodities.

Oligomerization of yeast α-factor receptor detected by fluorescent energy transfer between ligands

G-protein-coupled receptors (GPCRs) comprise a large superfamily of transmembrane receptors responsible for transducing responses to the binding of a wide variety of hormones, neurotransmitters, ions, and other small molecules. There is extensive evidence that GPCRs exist as homo-and hetero-oligomeric complexes; however, in many cases, the role of oligomerization and the extent to which it occurs at low physiological levels of receptor expression in cells remain unclear. We report here the use of flow cytometry to detect receptor-receptor interactions based on fluorescence resonance energy transfer between fluorescently labeled cell-impermeant ligands bound to yeast α-mating pheromone receptors that are members of the GPCR superfamily. A novel, to our knowledge, procedure was used to analyze energy transfer as a function of receptor occupancy by donor and acceptor ligands. Measurements of loss of donor fluorescence due to energy transfer in cells expressing high levels of receptors were used to calibrate measurements of enhanced acceptor emission due to energy transfer in cells expressing low levels of receptors. The procedure allows determination of energy transfer efficiencies over a 50-fold range of expression of full-length receptors at the surface of living cells without the need to create fluorescent or bioluminescent fusion proteins. Energy transfer efficiencies for fluorescently labeled derivatives of the receptor agonist α-factor do not depend on receptor expression level and are unaffected by C-terminal truncation of receptors. Fluorescently labeled derivatives of α-factor that act as receptor antagonists exhibit higher transfer efficiencies than those for labeled agonists. Although the approach cannot determine the number of receptors per oligomer, these results demonstrate that ligand-bound, native α-factor receptors exist as stable oligomers in the cell membranes of intact yeast cells at normal physiological expression levels and that the extent of oligomer formation is not dependent on the concentration of receptors in the membrane.

Identifying carbohydrate-active enzymes of Cutaneotrichosporon oleaginosus using systems biology

Background

The oleaginous yeast Cutaneotrichosporon oleaginosus represents one of the most promising microbial platforms for resource-efficient and scalable lipid production, with the capacity to accept a wide range of carbohydrates encapsulated in complex biomass waste or lignocellulosic hydrolysates. Currently, data related to molecular aspects of the metabolic utilisation of oligomeric carbohydrates are sparse. In addition, comprehensive proteomic information for C. oleaginosus focusing on carbohydrate metabolism is not available.

Results

In this study, we conducted a systematic analysis of carbohydrate intake and utilisation by C. oleaginosus and investigated the influence of different di- and trisaccharide as carbon sources. Changes in the cellular growth and morphology could be observed, depending on the selected carbon source. The greatest changes in morphology were observed in media containing trehalose. A comprehensive proteomic analysis of secreted, cell wall-associated, and cytoplasmatic proteins was performed, which highlighted differences in the composition and quantity of secreted proteins, when grown on different disaccharides. Based on the proteomic data, we performed a relative quantitative analysis of the identified proteins (using glucose as the reference carbon source) and observed carbohydrate-specific protein distributions. When using cellobiose or lactose as the carbon source, we detected three- and five-fold higher diversity in terms of the respective hydrolases released. Furthermore, the analysis of the secreted enzymes enabled identification of the motif with the consensus sequence LALL[LA]L[LA][LA]AAAAAAA as a potential signal peptide.

Conclusions

Relative quantification of spectral intensities from crude proteomic datasets enabled the identification of new enzymes and provided new insights into protein secretion, as well as the molecular mechanisms of carbo-hydrolases involved in the cleavage of the selected carbon oligomers. These insights can help unlock new substrate sources for C. oleaginosus, such as low-cost by-products containing difficult to utilize carbohydrates. In addition, information regarding the carbo-hydrolytic potential of C. oleaginosus facilitates a more precise engineering approach when using targeted genetic approaches. This information could be used to find new and more cost-effective carbon sources for microbial lipid production by the oleaginous yeast C. oleaginosus.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-021-01692-2.

Influence of Ceramic Membrane Surface Characteristics on the Flux Behavior of a Complex Fermentation Broth

The valorization of agro-industrial residues using yeasts as biocatalysts requires efficient methods for biomass separation. Filtration with ceramic membranes is suitable for this task, however, the challenge of flux decline and the unavoidable cleaning must be taken into account. We investigated the filtration of fermentation broth and its components using tubular microfiltration and ultrafiltration membranes, and hollow-fiber ultrafiltration membranes, with cut-offs of 30 and 200 nm. The steady-state flux was limited by fouling under comparable wall shear stress conditions but increased when the wall shear stress was higher. Single-component filtration with two 30 nm tubular ultrafiltration membranes, whose average surface roughness ranged from 1.0 to 3.9 µm, showed that smoother surfaces experience less biomass fouling under more intense hydrodynamic conditions. Furthermore, we showed experimentally and by scanning electron microscopy in filtration with 30 nm tubular membranes that the thickness of the first separation layer is responsible for the degree of irreversible resistance caused by the deposition of organic material in the membrane pores. The thickness of this layer should therefore be minimized without compromising mechanical stability.

Biological autoluminescence for assessing oxidative processes in yeast cell cultures

Nowadays, modern medicine is looking for new, more gentle, and more efficient diagnostic methods. A pathological state of an organism is often closely connected with increased amount of reactive oxygen species. They can react with biomolecules and subsequent reactions can lead to very low endogenous light emission (biological autoluminescence—BAL). This phenomenon can be potentially used as a non-invasive and low-operational-cost tool for monitoring oxidative stress during diseases. To contribute to the understanding of the parameters affecting BAL, we analyzed the BAL from yeast Saccharomyces cerevisiae as a representative eukaryotic organism. The relationship between the BAL intensity and the amount of reactive oxygen species that originates as a result of the Fenton reaction as well as correlation between spontaneous BAL and selected physical and chemical parameters (pH, oxygen partial pressure, and cell concentration) during cell growth were established. Our results contribute to real-time non-invasive methodologies for monitoring oxidative processes in biomedicine and biotechnology.

Mechanism for food texture preference based on grittiness

An animal's decision to accept or reject a prospective food is based only, in part, on its chemical composition. Palatability is also greatly influenced by textural features including smoothness versus grittiness, which is influenced by particle sizes. Here, we demonstrate that Drosophila melanogaster is endowed with the ability to discriminate particle sizes in food and uses this information to decide whether a food is appealing. The decision depends on a mechanically activated channel, OSCA/TMEM63, which is conserved from plants to humans. We found that tmem63 is expressed in a multidendritic neuron (md-L) in the fly tongue. Loss of tmem63 impairs the activation of md-L by mechanical stimuli and the ability to choose food based on particle size. These findings reveal the first role for this evolutionarily conserved, mechanically activated TMEM63 channel in an animal and provide an explanation of how flies can sense and behaviorally respond to the texture of food provided by particles.

Yeast Morphology Assessment through Automated Image Analysis during Fermentation

The kinetics and success of an industrial fermentation are dependent upon the health of the microorganism(s) responsible. Saccharomyces sp. are the most commonly used organisms in food and beverage production; consequently, many metrics of yeast health and stress have been previously correlated with morphological changes to fermentations kinetics. Many researchers and industries use machine vision to count yeast and assess health through dyes and image analysis. This study assessed known physical differences through automated image analysis taken throughout ongoing high stress fermentations at various temperatures (30 °C and 35 °C). Measured parameters included sugar consumption rate, number of yeast cells in suspension, yeast cross-sectional area, and vacuole cross-sectional area. The cell morphological properties were analyzed automatically using ImageJ software and validated using manual assessment. It was found that there were significant changes in cell area and ratio of vacuole to cell area over the fermentation. These changes were temperature dependent. The changes in morphology have implications for rates of cellular reactions and efficiency within industrial fermentation processes. The use of automated image analysis to quantify these parameters is possible using currently available systems and will provide additional tools to enhance our understanding of the fermentation process.

A mechanistic explanation of the transition to simple multicellularity in fungi

Development of multicellularity was one of the major transitions in evolution and occurred independently multiple times in algae, plants, animals, and fungi. However recent comparative genome analyses suggest that fungi followed a different route to other eukaryotic lineages. To understand the driving forces behind the transition from unicellular fungi to hyphal forms of growth, we develop a comparative model of osmotrophic resource acquisition. This predicts that whenever the local resource is immobile, hard-to-digest, and nutrient poor, hyphal osmotrophs outcompete motile or autolytic unicellular osmotrophs. This hyphal advantage arises because transporting nutrients via a contiguous cytoplasm enables continued exploitation of remaining resources after local depletion of essential nutrients, and more efficient use of costly exoenzymes. The model provides a mechanistic explanation for the origins of multicellular hyphal organisms, and explains why fungi, rather than unicellular bacteria, evolved to dominate decay of recalcitrant, nutrient poor substrates such as leaf litter or wood.

Microfluidic Single-Cell Analytics

What is the impact of cellular heterogeneity on process performance? How do individual cells contribute to averaged process productivity? Single-cell analysis is a key technology for answering such key questions of biotechnology, beyond bulky measurements with populations. The analysis of cellular individuality, its origins, and the dependency of process performance on cellular heterogeneity has tremendous potential for optimizing biotechnological processes in terms of metabolic, reaction, and process engineering. Microfluidics offer unmatched environmental control of the cellular environment and allow massively parallelized cultivation of single cells. However, the analytical accessibility to a cell's physiology is of crucial importance for obtaining the desired information on the single-cell production phenotype. Highly sensitive analytics are required to detect and quantify the minute amounts of target analytes and small physiological changes in a single cell. For their application to biotechnological questions, single-cell analytics must evolve toward the measurement of kinetics and specific rates of the smallest catalytic unit, the single cell. In this chapter, we focus on an introduction to the latest single-cell analytics and their application for obtaining physiological parameters in a biotechnological context from single cells. We present and discuss recent advancements in single-cell analytics that enable the analysis of cell-specific growth, uptake, and production kinetics, as well as the gene expression and regulatory mechanisms at a single-cell level.

Copolymeric Hydrogel-Based Immobilization of Yeast Cells for Continuous Biotransformation of Fumaric Acid in a Microreactor

Although enzymatic microbioreactors have recently gained lots of attention, reports on the use of whole cells as biocatalysts in microreactors have been rather modest. In this work, an efficient microreactor with permeabilized Saccharomyces cerevisiae cells was developed and used for continuous biotransformation of fumaric into industrially relevant L-malic acid. The immobilization of yeast cells was achieved by entrapment in a porous structure of various hydrogels. Copolymers based on different ratios of sodium alginate (SA) and polyvinyl alcohol (PVA) were used for hydrogel formation, while calcium chloride and boric or phenylboronic acid were tested as crosslinking agents for SA and PVA, respectively. The influence of hydrogel composition on physico-chemical properties of hydrogels prepared in the form of thin films was evaluated. Immobilization of permeabilized S. cerevisiae cells in the selected copolymeric hydrogel resulted in up to 72% retained fumarase activity. The continuous biotransformation process using two layers of hydrogels integrated into a two-plate microreactor revealed high space time yield of 2.86 g/(L·h) while no activity loss was recorded during 7 days of continuous operation.

A New Pathway for Mannitol Metabolism in Yeasts Suggests a Link to the Evolution of Alcoholic Fermentation

The yeasts belonging to the Wickerhamiella and Starmerella genera (W/S clade) share a distinctive evolutionary history marked by loss and subsequent reinstatement of alcoholic fermentation mediated by horizontal gene transfer events. Species in this clade also share unusual features of metabolism, namely the preference for fructose over glucose as carbon source, a rare trait known as fructophily. Here we show that fructose may be the preferred sugar in W/S-clade species because, unlike glucose, it can be converted directly to mannitol in a reaction with impact on redox balance. According to our results, mannitol is excreted to the growth medium in appreciable amounts along with other fermentation products such as glycerol and ethanol but unlike the latter metabolites mannitol production increases with temperature. We used comparative genomics to find genes involved in mannitol metabolism and established the mannitol biosynthesis pathway in W/S-clade species Starmerella bombicola using molecular genetics tools. Surprisingly, mannitol production seems to be so important that St. bombicola (and other W/S-clade species) deploys a novel pathway to mediate the conversion of glucose to fructose, thereby allowing cells to produce mannitol even when glucose is the sole carbon source. Using targeted mutations and ¹³C-labeled glucose followed by NMR analysis of end-products, we showed that the novel mannitol biosynthesis pathway involves fructose-6-phosphate as an intermediate, implying a key role for a yet unknown fructose-6-P phosphatase. We hypothesize that mannitol production contributed to mitigate the negative effects on redox balance of the ancient loss of alcoholic fermentation in the W/S clade. Presently, mannitol also seems to play a role in stress protection.

INDIANA: An in-cell diffusion method to characterize the size, abundance and permeability of cells

NMR and MRI diffusion experiments contain information describing the shape, size, abundance, and membrane permeability of cells although extracting this information can be challenging. Here we present the INDIANA (IN-cell DIffusion ANAlysis) method to simultaneously and non-invasively measure cell abundance, effective radius, permeability and intrinsic relaxation rates and diffusion coefficients within the inter- and intra-cellular populations. The method couples an experimental dataset comprising stimulated-echo diffusion measurements, varying both the gradient strength and the diffusion delay, together with software to fit a model based on the Kärger equations to robustly extract the relevant parameters. A detailed error analysis is presented by comparing the results from fitting simulated data from Monte Carlo simulations, establishing its effectiveness. We note that for parameters typical of mammalian cells the approach is particularly effective, and the shape of the underlying cells does not unduly affect the results. Finally, we demonstrate the performance of the experiment on systems of suspended yeast and mammalian cells. The extracted parameters describing cell abundance, size, permeability and relaxation are independently validated.

Unite to divide - how models and biological experimentation have come together to reveal mechanisms of cytokinesis

Cytokinesis is the fundamental and ancient cellular process by which one cell physically divides into two. Cytokinesis in animal and fungal cells is achieved by contraction of an actomyosin cytoskeletal ring assembled in the cell cortex, typically at the cell equator. Cytokinesis is essential for the development of fertilized eggs into multicellular organisms and for homeostatic replenishment of cells. Correct execution of cytokinesis is also necessary for genome stability and the evasion of diseases including cancer. Cytokinesis has fascinated scientists for well over a century, but its speed and dynamics make experiments challenging to perform and interpret. The presence of redundant mechanisms is also a challenge to understand cytokinesis, leaving many fundamental questions unresolved. For example, how does a disordered cytoskeletal network transform into a coherent ring? What are the long-distance effects of localized contractility? Here, we provide a general introduction to 'modeling for biologists', and review how agent-based modeling and continuum mechanics modeling have helped to address these questions.