The critical size is set at a single-cell level by growth rate to attain homeostasis and adaptation

Cell growth and nutrient availability control the mitotic exit signaling network in budding yeast

Cell growth is required for cell cycle progression. The amount of growth required for cell cycle progression is reduced in poor nutrients, which leads to a reduction in cell size. In budding yeast, nutrients can influence cell size by modulating the extent of bud growth, which occurs predominantly in mitosis. However, the mechanisms are unknown. Here, we used mass spectrometry to identify proteins that modulate bud growth in response to nutrient availability. This led to the discovery that nutrients regulate numerous components of the mitotic exit network (MEN), which controls exit from mitosis. A key component of the MEN undergoes gradual multisite phosphorylation during bud growth that is dependent upon bud growth and correlated with the extent of growth. Furthermore, activation of the MEN is sufficient to override a growth requirement for mitotic exit. The data suggest a model in which the MEN ensures that mitotic exit occurs only when an appropriate amount of bud growth has occurred.

Whi5 hypo- and hyper-phosphorylation dynamics control cell-cycle entry and progression

Progression through the cell cycle depends on the phosphorylation of key substrates by cyclin-dependent kinases. In budding yeast, these substrates include the transcriptional inhibitor Whi5 that regulates G1/S transition. In early G1 phase, Whi5 is hypo-phosphorylated and inhibits the Swi4/Swi6 (SBF) complex that promotes transcription of the cyclins CLN1 and CLN2. In late G1, Whi5 is rapidly hyper-phosphorylated by Cln1 and Cln2 in complex with the cyclin-dependent kinase Cdk1. This hyper-phosphorylation inactivates Whi5 and excludes it from the nucleus. Here, we set out to determine the molecular mechanisms responsible for Whi5's multi-site phosphorylation and how they regulate the cell cycle. To do this, we first identified the 19 Whi5 sites that are appreciably phosphorylated and then determined which of these sites are responsible for G1 hypo-phosphorylation. Mutation of 7 sites removed G1 hypo-phosphorylation, increased cell size, and delayed the G1/S transition. Moreover, the rapidity of Whi5 hyper-phosphorylation in late G1 depends on "priming" sites that dock the Cks1 subunit of Cln1,2-Cdk1 complexes. Hyper-phosphorylation is crucial for Whi5 nuclear export, normal cell size, full expression of SBF target genes, and timely progression through both the G1/S transition and S/G2/M phases. Thus, our work shows how Whi5 phosphorylation regulates the G1/S transition and how it is required for timely progression through S/G2/M phases and not only G1 as previously thought.

Millifluidic magnetophoresis-based chip for age-specific fractionation: evaluating the impact of age on metabolomics and gene expression in yeast

A novel millifluidic process introduces age-based fractionation of S. pastorianus var. carlsbergensis yeast culture through magnetophoresis. Saccharomyces yeast is a model organism for aging research used in various industries. Traditional age-based cell separation methods were labor-intensive, but techniques like magnetic labeling have eased the process by being non-invasive and scalable. Our approach introduces an age-specific fractionation using a 3D-printed millfluidic chip in a two-step process, ensuring efficient cell deflection in the magnetic field and counteracting magnetic induced convection. Among various channel designs, the pinch-shaped channel proved most effective for age differentiation based on magnetically labeled bud scar numbers. Metabolomic analyses revealed changes in certain amino acids and increased NAD+ levels, suggesting metabolic shifts in aging cells. Gene expression studies further underlined these age-related metabolic changes. This innovative platform offers a high-throughput, non-invasive method for age-specific yeast cell fractionation, with potential applications in industries ranging from food and beverages to pharmaceuticals.

Casein kinase 1 controls components of a TORC2 signaling network in budding yeast

Tor kinases play diverse and essential roles in control of nutrient signaling and cell growth. Tor kinases are assembled into two large multiprotein complexes referred to as Tor Complex 1 and Tor Complex 2 (TORC1 and TORC2). In budding yeast, TORC2 controls a signaling network that relays signals regarding carbon source that strongly influence growth rate and cell size. However, the mechanisms that control TORC2 signaling are poorly understood. Activation of TORC2 requires Mss4, a phosphoinositol kinase that initiates assembly of a multi-protein complex at the plasma membrane that recruits and activates downstream targets of TORC2. Localization of Mss4 to the plasma membrane is controlled by phosphorylation and previous work suggested that yeast homologs of casein kinase 1γ, referred to as Yck1 and Yck2, control phosphorylation of Mss4. Here, we generated a new analog-sensitive allele of YCK2 and used it to test whether Yck1/2 influence signaling in the TORC2 network. We found that multiple components of the TORC2 network are strongly influenced by Yck1/2 signaling.

Whi5 hypo- and hyper-phosphorylation dynamics control cell cycle entry and progression

Progression through the cell cycle depends on the phosphorylation of key substrates by cyclin-dependent kinases. In budding yeast, these substrates include the transcriptional inhibitor Whi5 that regulates the G1/S transition. In early G1 phase, Whi5 is hypo-phosphorylated and inhibits the SBF complex that promotes transcription of the cyclins CLN1 and CLN2 . In late-G1, Whi5 is rapidly hyper-phosphorylated by Cln1,2 in complex with the cyclin-dependent kinase Cdk1. This hyper-phosphorylation inactivates Whi5 and excludes it from the nucleus. Here, we set out to determine the molecular mechanisms responsible for Whi5's multi-site phosphorylation and how they regulate the cell cycle. To do this, we first identified the 19 Whi5 sites that are appreciably phosphorylated and then determined which of these sites are responsible for G1 hypo-phosphorylation. Mutation of 7 sites removed G1 hypo-phosphorylation, increased cell size, and delayed the G1/S transition. Moreover, the rapidity of Whi5 hyper-phosphorylation in late G1 depends on 'priming' sites that dock the Cks1 subunit of Cln1,2-Cdk1 complexes. Hyper-phosphorylation is crucial for Whi5 nuclear export, normal cell size, full expression of SBF target genes, and timely progression through both the G1/S transition and S/G2/M phases. Thus, our work shows how Whi5 phosphorylation regulates the G1/S transition and how it is required for timely progression through S/G2/M phases and not only G1 as previously thought.

Plasmonic Functional Assay Platform Determines the Therapeutic Profile of Cancer Cells

Functional assay platforms could identify the biophysical properties of cells and their therapeutic response to drug treatments. Despite their strong ability to assess cellular pathways, functional assays require large tissue samples, long-term cell culture, and bulk measurements. Even though such a drawback is still valid, these limitations did not hinder the interest in these platforms for their capacity to reveal drug susceptibility. Some of the limitations could be overcome with single-cell functional assays by identifying subpopulations using small sample volumes. Along this direction, in this article, we developed a high-throughput plasmonic functional assay platform to identify the growth profile of cells and their therapeutic profile under therapies using mass and growth rate statistics of individual cells. Our technology could determine populations' growth profiles using the growth rate data of multiple single cells of the same population. Evaluating spectral variations based on the plasmonic diffraction field intensity images in real time, we could simultaneously monitor the mass change for the cells within the field of view of a camera with the capacity of > ∼500 cells/h scanning rate. Our technology could determine the therapeutic profile of cells under cancer drugs within few hours, while the classical techniques require days to show reduction in viability due to antitumor effects. The platform could reveal the heterogeneity within the therapeutic profile of populations and determine subpopulations showing resistance to drug therapies. As a proof-of-principle demonstration, we studied the growth profile of MCF-7 cells and their therapeutic behavior to standard-of-care drugs that have antitumor effects as shown in the literature, including difluoromethylornithine (DFMO), 5-fluorouracil (5-FU), paclitaxel (PTX), and doxorubicin (Dox). We successfully demonstrated the resistant behavior of an MCF-7 variant that could survive in the presence of DFMO. More importantly, we could precisely identify synergic and antagonistic effects of drug combinations based on the order of use in cancer therapy. Rapidly assessing the therapeutic profile of cancer cells, our plasmonic functional assay platform could be used to reveal personalized drug therapies for cancer patients.

A tractable physical model for the yeast polarity predicts epistasis and fitness

Accurate phenotype prediction based on genetic information has numerous societal applications, such as crop design or cellular factories. Epistasis, when biological components interact, complicates modelling phenotypes from genotypes. Here we show an approach to mitigate this complication for polarity establishment in budding yeast, where mechanistic information is abundant. We coarse-grain molecular interactions into a so-called mesotype, which we combine with gene expression noise into a physical cell cycle model. First, we show with computer simulations that the mesotype allows validation of the most current biochemical polarity models by quantitatively matching doubling times. Second, the mesotype elucidates epistasis emergence as exemplified by evaluating the predicted mutational effect of key polarity protein Bem1p when combined with known interactors or under different growth conditions. This example also illustrates how unlikely evolutionary trajectories can become more accessible. The tractability of our biophysically justifiable approach inspires a road-map towards bottom-up modelling complementary to statistical inferences.

This article is part of the theme issue ‘Interdisciplinary approaches to predicting evolutionary biology’.

Meiotic cells escape prolonged spindle checkpoint activity through kinetochore silencing and slippage

To prevent chromosome mis-segregation, a surveillance mechanism known as the spindle checkpoint delays the cell cycle if kinetochores are not attached to spindle microtubules, allowing the cell additional time to correct improper attachments. During spindle checkpoint activation, checkpoint proteins bind the unattached kinetochore and send a diffusible signal to inhibit the anaphase promoting complex/cyclosome (APC/C). Previous work has shown that mitotic cells with depolymerized microtubules can escape prolonged spindle checkpoint activation in a process called mitotic slippage. During slippage, spindle checkpoint proteins bind unattached kinetochores, but the cells cannot maintain the checkpoint arrest. We asked if meiotic cells had as robust of a spindle checkpoint response as mitotic cells and whether they also undergo slippage after prolonged spindle checkpoint activity. We performed a direct comparison between mitotic and meiotic budding yeast cells that signal the spindle checkpoint through two different assays. We find that the spindle checkpoint delay is shorter in meiosis I or meiosis II compared to mitosis, overcoming a checkpoint arrest approximately 150 minutes earlier in meiosis than in mitosis. In addition, cells in meiosis I escape spindle checkpoint signaling using two mechanisms, silencing the checkpoint at the kinetochore and through slippage. We propose that meiotic cells undertake developmentally-regulated mechanisms to prevent persistent spindle checkpoint activity to ensure the production of gametes.

Kinetics of blood cell differentiation during hematopoiesis revealed by quantitative long-term live imaging

Stem cells typically reside in a specialized physical and biochemical environment that facilitates regulation of their behavior. For this reason, stem cells are ideally studied in contexts that maintain this precisely constructed microenvironment while still allowing for live imaging. Here, we describe a long-term organ culture and imaging strategy for hematopoiesis in flies that takes advantage of powerful genetic and transgenic tools available in this system. We find that fly blood progenitors undergo symmetric cell divisions and that their division is both linked to cell size and is spatially oriented. Using quantitative imaging to simultaneously track markers for stemness and differentiation in progenitors, we identify two types of differentiation that exhibit distinct kinetics. Moreover, we find that infection-induced activation of hematopoiesis occurs through modulation of the kinetics of cell differentiation. Overall, our results show that even subtle shifts in proliferation and differentiation kinetics can have large and aggregate effects to transform blood progenitors from a quiescent to an activated state.

Temporal segregation of biosynthetic processes is responsible for metabolic oscillations during the budding yeast cell cycle

Many cell biological and biochemical mechanisms controlling the fundamental process of eukaryotic cell division have been identified; however, the temporal dynamics of biosynthetic processes during the cell division cycle are still elusive. Here, we show that key biosynthetic processes are temporally segregated along the cell cycle. Using budding yeast as a model and single-cell methods to dynamically measure metabolic activity, we observe two peaks in protein synthesis, in the G1 and S/G2/M phase, whereas lipid and polysaccharide synthesis peaks only once, during the S/G2/M phase. Integrating the inferred biosynthetic rates into a thermodynamic-stoichiometric metabolic model, we find that this temporal segregation in biosynthetic processes causes flux changes in primary metabolism, with an acceleration of glucose-uptake flux in G1 and phase-shifted oscillations of oxygen and carbon dioxide exchanges. Through experimental validation of the model predictions, we demonstrate that primary metabolism oscillates with cell-cycle periodicity to satisfy the changing demands of biosynthetic processes exhibiting unexpected dynamics during the cell cycle.

Meiotic Cells Escape Prolonged Spindle Checkpoint Activity Through Premature Silencing and Slippage

To prevent chromosome mis-segregation, a surveillance mechanism known as the spindle checkpoint delays the cell cycle if kinetochores are not attached to spindle microtubules, allowing the cell additional time to correct improper attachments. During spindle checkpoint activation, checkpoint proteins bind the unattached kinetochore and send a diffusible signal to inhibit the anaphase promoting complex/cyclosome (APC/C). Previous work has shown that mitotic cells with depolymerized microtubules can escape prolonged spindle checkpoint activation in a process called mitotic slippage. During slippage, spindle checkpoint proteins bind unattached kinetochores, but the cells cannot maintain the checkpoint arrest. We asked if meiotic cells had as robust of a spindle checkpoint response as mitotic cells and whether they also undergo slippage after prolonged spindle checkpoint activity. We performed a direct comparison between mitotic and meiotic budding yeast cells that signal the spindle checkpoint due to a lack of either kinetochore-microtubule attachments or due to a loss of tension-bearing attachments. We find that the spindle checkpoint is not as robust in meiosis I or meiosis II compared to mitosis, overcoming a checkpoint arrest approximately 150 minutes earlier in meiosis. In addition, cells in meiosis I escape spindle checkpoint signaling using two mechanisms, silencing the checkpoint at the kinetochore and through slippage. We propose that meiotic cells undertake developmentally-regulated mechanisms to prevent persistent spindle checkpoint activity to ensure the production of gametes.

AUTHOR SUMMARY

Mitosis and meiosis are the two major types of cell divisions. Mitosis gives rise to genetically identical daughter cells, while meiosis is a reductional division that gives rise to gametes. Cell cycle checkpoints are highly regulated surveillance mechanisms that prevent cell cycle progression when circumstances are unfavorable. The spindle checkpoint promotes faithful chromosome segregation to safeguard against aneuploidy, in which cells have too many or too few chromosomes. The spindle checkpoint is activated at the kinetochore and then diffuses to inhibit cell cycle progression. Although the checkpoint is active in both mitosis and meiosis, most studies involving checkpoint regulation have been performed in mitosis. By activating the spindle checkpoint in both mitosis and meiosis in budding yeast, we show that cells in meiosis elicit a less persistent checkpoint signal compared to cells in mitosis. Further, we show that cells use distinct mechanisms to escape the checkpoint in mitosis and meiosis I. While cells in mitosis and meiosis II undergo anaphase onset while retaining checkpoint proteins at the kinetochore, cells in meiosis I prematurely lose checkpoint protein localization at the kinetochore. If the mechanism to remove the checkpoint components from the kinetochore is disrupted, meiosis I cells can still escape checkpoint activity. Together, these results highlight that cell cycle checkpoints are differentially regulated during meiosis to avoid long delays and to allow gametogenesis.

What programs the size of animal cells?

The human body is programmed with definite quantities, magnitudes, and proportions. At the microscopic level, such definite sizes manifest in individual cells - different cell types are characterized by distinct cell sizes whereas cells of the same type are highly uniform in size. How do cells in a population maintain uniformity in cell size, and how are changes in target size programmed? A convergence of recent and historical studies suggest - just as a thermostat maintains room temperature - the size of proliferating animal cells is similarly maintained by homeostatic mechanisms. In this review, we first summarize old and new literature on the existence of cell size checkpoints, then discuss additional advances in the study of size homeostasis that involve feedback regulation of cellular growth rate. We further discuss recent progress on the molecules that underlie cell size checkpoints and mechanisms that specify target size setpoints. Lastly, we discuss a less-well explored teleological question: why does cell size matter and what is the functional importance of cell size control?

Nutrient availability as an arbiter of cell size

Pioneering work carried out over 60 years ago discovered that bacterial cell size is proportional to the growth rate set by nutrient availability. This relationship is traditionally referred to as the 'growth law'. Subsequent studies revealed the growth law to hold across all orders of life, a remarkable degree of conservation. However, recent work suggests the relationship between growth rate, nutrients, and cell size is far more complicated and less deterministic than originally thought. Focusing on bacteria and yeast, here we review efforts to understand the molecular mechanisms underlying the relationship between growth rate and cell size.

Sublinear scaling of the cellular proteome with ploidy

Ploidy changes are frequent in nature and contribute to evolution, functional specialization and tumorigenesis. Analysis of model organisms of different ploidies revealed that increased ploidy leads to an increase in cell and nuclear volume, reduced proliferation, metabolic changes, lower fitness, and increased genomic instability, but the underlying mechanisms remain poorly understood. To investigate how gene expression changes with cellular ploidy, we analyzed isogenic series of budding yeasts from 1N to 4N. We show that mRNA and protein abundance scales allometrically with ploidy, with tetraploid cells showing only threefold increase in protein abundance compared to haploids. This ploidy-dependent sublinear scaling occurs via decreased rRNA and ribosomal protein abundance and reduced translation. We demonstrate that the activity of Tor1 is reduced with increasing ploidy, which leads to diminished rRNA gene repression via a Tor1-Sch9-Tup1 signaling pathway. mTORC1 and S6K activity are also reduced in human tetraploid cells and the concomitant increase of the Tup1 homolog Tle1 downregulates the rDNA transcription. Our results suggest that the mTORC1-Sch9/S6K-Tup1/TLE1 pathway ensures proteome remodeling in response to increased ploidy.

TORC1 and PKA activity towards ribosome biogenesis oscillates in synchrony with the budding yeast cell cycle

Recent studies have revealed that the growth rate of budding yeast and mammalian cells varies during the cell cycle. By linking a multitude of signals to cell growth, the highly conserved Target of Rapamycin Complex 1 (TORC1) and Protein Kinase A (PKA) pathways are prime candidates for mediating the dynamic coupling between growth and division. However, measurements of TORC1 and PKA activity during the cell cycle are still lacking. Following the localization dynamics of two TORC1 and PKA targets via time-lapse microscopy in hundreds of yeast cells, we found that the activity of these pathways towards ribosome biogenesis fluctuates in synchrony with the cell cycle even under constant external conditions. Mutations of upstream TORC1 and PKA regulators suggested that internal metabolic signals partially mediate these activity changes. Our study reveals a new aspect of TORC1 and PKA signaling, which will be important for understanding growth regulation during the cell cycle.

Scaling of biosynthesis and metabolism with cell size

Cells adopt a size that is optimal for their function, and pushing them beyond this limit can cause cell aging and death by senescence or reduce proliferative potential. However, by increasing their genome copy number (ploidy), cells can increase their size dramatically and homeostatically maintain physiological properties such as biosynthesis rate. Recent studies investigating the relationship between cell size and rates of biosynthesis and metabolism under normal, polyploid, and pathological conditions are revealing new insights into how cells attain the best function or fitness for their size by tuning processes including transcription, translation, and mitochondrial respiration. A new frontier is to connect single-cell scaling relationships with tissue and whole-organism physiology, which promises to reveal molecular and evolutionary principles underlying the astonishing diversity of size observed across the tree of life.

High-resolution mass measurements of single budding yeast reveal linear growth segments

The regulation of cell growth has fundamental physiological, biotechnological and medical implications. However, methods that can continuously monitor individual cells at sufficient mass and time resolution hardly exist. Particularly, detecting the mass of individual microbial cells, which are much smaller than mammalian cells, remains challenging. Here, we modify a previously described cell balance ('picobalance') to monitor the proliferation of single cells of the budding yeast, Saccharomyces cerevisiae, under culture conditions in real time. Combined with optical microscopy to monitor the yeast morphology and cell cycle phase, the picobalance approaches a total mass resolution of 0.45 pg. Our results show that single budding yeast cells (S/G2/M phase) increase total mass in multiple linear segments sequentially, switching their growth rates. The growth rates weakly correlate with the cell mass of the growth segments, and the duration of each growth segment correlates negatively with cell mass. We envision that our technology will be useful for direct, accurate monitoring of the growth of single cells throughout their cycle.

A yeast cell cycle model integrating stress, signaling, and physiology

The cell division cycle in eukaryotic cells is a series of highly coordinated molecular interactions that ensure that cell growth, duplication of genetic material, and actual cell division are precisely orchestrated to give rise to two viable progeny cells. Moreover, the cell cycle machinery is responsible for incorporating information about external cues or internal processes that the cell must keep track of to ensure a coordinated, timely progression of all related processes. This is most pronounced in multicellular organisms, but also a cardinal feature in model organisms such as baker's yeast. The complex and integrative behavior is difficult to grasp and requires mathematical modeling to fully understand the quantitative interplay of the single components within the entire system. Here, we present a self-oscillating mathematical model of the yeast cell cycle that comprises all major cyclins and their main regulators. Furthermore, it accounts for the regulation of the cell cycle machinery by a series of external stimuli such as mating pheromones and changes in osmotic pressure or nutrient quality. We demonstrate how the external perturbations modify the dynamics of cell cycle components and how the cell cycle resumes after adaptation to or relief from stress.

Determination of protoplast growth properties using quantitative single-cell tracking analysis

BACKGROUND

Although quantitative single-cell analysis is frequently applied in animal systems, e.g. to identify novel drugs, similar applications on plant single cells are largely missing. We have exploited the applicability of high-throughput microscopic image analysis on plant single cells using tobacco leaf protoplasts, cell-wall free single cells isolated by lytic digestion. Protoplasts regenerate their cell wall within several days after isolation and have the potential to expand and proliferate, generating microcalli and finally whole plants after the application of suitable regeneration conditions.

RESULTS

High-throughput automated microscopy coupled with the development of image processing pipelines allowed to quantify various developmental properties of thousands of protoplasts during the initial days following cultivation by immobilization in multi-well-plates. The focus on early protoplast responses allowed to study cell expansion prior to the initiation of proliferation and without the effects of shape-compromising cell walls. We compared growth parameters of wild-type tobacco cells with cells expressing the antiapoptotic protein Bcl2-associated athanogene 4 from Arabidopsis (AtBAG4).

CONCLUSIONS

AtBAG4-expressing protoplasts showed a higher proportion of cells responding with positive area increases than the wild type and showed increased growth rates as well as increased proliferation rates upon continued cultivation. These features are associated with reported observations on a BAG4-mediated increased resilience to various stress responses and improved cellular survival rates following transformation approaches. Moreover, our single-cell expansion results suggest a BAG4-mediated, cell-independent increase of potassium channel abundance which was hitherto reported for guard cells only. The possibility to explain plant phenotypes with single-cell properties, extracted with the single-cell processing and analysis pipeline developed, allows to envision novel biotechnological screening strategies able to determine improved plant properties via single-cell analysis.

Mad3 modulates the G1 Cdk and acts as a timer in the Start network

Cells maintain their size within limits over successive generations to maximize fitness and survival. Sizer, timer, and adder behaviors have been proposed as possible alternatives to coordinate growth and cell cycle progression. Regarding budding yeast cells, a sizer mechanism is thought to rule cell cycle entry at Start. However, while many proteins controlling the size of these cells have been identified, the mechanistic framework in which they participate to achieve cell size homeostasis is not understood. We show here that intertwined APC and SCF degradation machineries with specific adaptor proteins drive cyclic accumulation of the G₁ Cdk in the nucleus, reaching maximal levels at Start. The mechanism incorporates Mad3, a centromeric-signaling protein that subordinates G₁ progression to the previous mitosis as a memory factor. This alternating-degradation device displays the properties of a timer and, together with the sizer device, would constitute a key determinant of cell cycle entry.

A high-throughput microfluidic diploid yeast long-term culturing (DYLC) chip capable of bud reorientation and concerted daughter dissection for replicative lifespan determination

Background

Budding yeast, Saccharomyces cerevisiae, has been extensively favored as a model organism in aging and age-related studies, thanks to versatile microfluidic chips for cell dynamics assay and replicative lifespan (RLS) determination at single-cell resolution. However, previous microfluidic structures aiming to immobilize haploid yeast may impose excessive spatial constraint and mechanical stress on cells, especially for larger diploid cells that sprout in a bipolar pattern.

Results

We developed a high-throughput microfluidic chip for diploid yeast long-term culturing (DYLC), optical inspection and cell-aging analysis. The DYLC chip features 1100 “leaky bowl”-shaped traps formatted in an array to dock single cells under laminar-perfused medium and effectively remove daughter cells by hydraulic shear forces. The delicate microstructures of cell traps enable hydrodynamic rotation of newborn buds, so as to ensure bud reorientation towards downstream and concerted daughter dissection thereafter. The traps provide sufficient space for cell-volume enlargement during aging, and thus properly alleviate structural compression and external stress on budding yeast. Trapping efficiency and long-term maintenance of single cells were optimized according to computational fluid dynamics simulations and experimental characterization in terms of critical parameters of the trap and array geometries. Owing to the self-filling of daughter cells dissected from traps upstream, an initial trapping efficiency of about 70% can rapidly reach a high value of over 92% after 4-hour cell culturing. During yeast proliferation and aging, cellular processes of growth, budding and daughter dissection were continuously tracked for over 60 h by time-lapse imaging. Yeast RLS and budding time interval (BTI) were directly calculated by the sequential two-digit codes indicating the budding status in images. With the employed diploid yeast strain, we obtained an RLS of 24.29 ± 3.65 generations, and verified the extension of BTI in the first couple of generations after birth and the last several generations approaching death, as well as cell de-synchronization along diploid yeast aging.

Conclusions

The DYLC chip offers a promising platform for reliable capture and culturing of diploid yeast cells and for life-long tracking of cell dynamics and replicative aging processes so that grasping comprehensive insights of aging mechanism in complex eukaryotic cells.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-022-01379-9.

Systematic In Vivo Characterization of Fluorescent Protein Maturation in Budding Yeast

Fluorescent protein (FP) maturation can limit the accuracy with which dynamic intracellular processes are captured and reduce the in vivo brightness of a given FP in fast-dividing cells. The knowledge of maturation timescales can therefore help users determine the appropriate FP for each application. However, in vivo maturation rates can greatly deviate from in vitro estimates that are mostly available. In this work, we present the first systematic study of in vivo maturation for 12 FPs in budding yeast. To overcome the technical limitations of translation inhibitors commonly used to study FP maturation, we implemented a new approach based on the optogenetic stimulations of FP expression in cells grown under constant nutrient conditions. Combining the rapid and orthogonal induction of FP transcription with a mathematical model of expression and maturation allowed us to accurately estimate maturation rates from microscopy data in a minimally invasive manner. Besides providing a useful resource for the budding yeast community, we present a new joint experimental and computational approach for characterizing FP maturation, which is applicable to a wide range of organisms.

A convolutional neural network for segmentation of yeast cells without manual training annotations

MOTIVATION

Single-cell time-lapse microscopy is a ubiquitous tool for studying the dynamics of complex cellular processes. While imaging can be automated to generate very large volumes of data, the processing of the resulting movies to extract high-quality single-cell information remains a challenging task. The development of software tools that automatically identify and track cells is essential for realizing the full potential of time-lapse microscopy data. Convolutional neural networks (CNNs) are ideally suited for such applications, but require great amounts of manually annotated data for training, a time-consuming and tedious process.

RESULTS

We developed a new approach to CNN training for yeast cell segmentation based on synthetic data and present (i) a software tool for the generation of synthetic images mimicking brightfield images of budding yeast cells and (ii) a convolutional neural network (Mask R-CNN) for yeast segmentation that was trained on a fully synthetic dataset. The Mask R-CNN performed excellently on segmenting actual microscopy images of budding yeast cells, and a density-based spatial clustering algorithm (DBSCAN) was able to track the detected cells across the frames of microscopy movies. Our synthetic data creation tool completely bypassed the laborious generation of manually annotated training datasets, and can be easily adjusted to produce images with many different features. The incorporation of synthetic data creation into the development pipeline of CNN-based tools for budding yeast microscopy is a critical step toward the generation of more powerful, widely applicable and user-friendly image processing tools for this microorganism.

AVAILABILITY AND IMPLEMENTATION

The synthetic data generation code can be found at https://github.com/prhbrt/synthetic-yeast-cells. The Mask R-CNN as well as the tuning and benchmarking scripts can be found at https://github.com/ymzayek/yeastcells-detection-maskrcnn. We also provide Google Colab scripts that reproduce all the results of this work.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Vacuolar Localization via the N-terminal Domain of Sch9 is Required for TORC1-dependent Phosphorylation and Downstream Signal Transduction

The budding yeast Sch9 kinase (functional orthologue of the mammalian S6 kinase) is a major effector of the Target of Rapamycin Complex 1 (TORC1) complex in the regulation of cell growth in response to nutrient availability and stress. Sch9 is partially localized at the vacuolar surface, where it is phosphorylated by TORC1. The recruitment of Sch9 on the vacuole is mediated by direct interaction between phospholipids of the vacuolar membrane and the region of Sch9 encompassing amino acid residues 1-390, which contains a C2 domain. Since many C2 domains mediate phospholipid binding, it had been suggested that the C2 domain of Sch9 mediates its vacuolar recruitment. However, the in vivo requirement of the C2 domain for Sch9 localization had not been demonstrated, and the phenotypic consequences of Sch9 delocalization remained unknown. Here, by examining cellular localization, phosphorylation state and growth phenotypes of Sch9 truncation mutants, we show that deletion of the N-terminal domain of Sch9 (aa 1-182), but not the C2 domain (aa 183-399), impairs vacuolar localization and TORC1-dependent phosphorylation of Sch9, while causing growth defects similar to those observed in Sch9Δ cells. These defects can be reversed either via artificial tethering of the protein to the vacuole, or by introducing phosphomimetic mutations at the TORC1 target sites, suggesting that Sch9 localization on the vacuole is needed for the TORC1-dependent activation of the kinase. Our study uncovers a key role for the N-terminal domain of Sch9 and provides new mechanistic insight into the regulation of a major TORC1 signaling branch.

Modeling aging and its impact on cellular function and organismal behavior

Aging is a complex phenomenon of functional decay in a biological organism. Although the effects of aging are readily recognizable in a wide range of organisms, the cause(s) of aging are ill defined and poorly understood. Experimental methods on model organisms have driven significant insight into aging as a process, but have not provided a complete model of aging. Computational biology offers a unique opportunity to resolve this gap in our knowledge by generating extensive and testable models that can help us understand the fundamental nature of aging, identify the presence and characteristics of unaccounted aging factor(s), demonstrate the mechanics of particular factor(s) in driving aging, and understand the secondary effects of aging on biological function. In this review, we will address each of the above roles for computational biology in aging research. Concurrently, we will explore the different applications of computational biology to aging in single-celled versus multicellular organisms. Given the long history of computational biogerontological research on lower eukaryotes, we emphasize the key future goals of gradually integrating prior models into a holistic map of aging and translating successful models to higher-complexity organisms.

Growth-dependent signals drive an increase in early G1 cyclin concentration to link cell cycle entry with cell growth

Entry into the cell cycle occurs only when sufficient growth has occurred. In budding yeast, the cyclin Cln3 is thought to initiate cell cycle entry by inactivating a transcriptional repressor called Whi5. Growth-dependent changes in the concentrations of Cln3 or Whi5 have been proposed to link cell cycle entry to cell growth. However, there are conflicting reports regarding the behavior and roles of Cln3 and Whi5. Here, we found no evidence that changes in the concentration of Whi5 play a major role in controlling cell cycle entry. Rather, the data suggest that cell growth triggers cell cycle entry by driving an increase in the concentration of Cln3. We further found that accumulation of Cln3 is dependent upon homologs of mammalian SGK kinases that control cell growth and size. Together, the data are consistent with models in which Cln3 is a crucial link between cell growth and the cell cycle.

Stress granules display bistable dynamics modulated by Cdk

Stress granules (SGs) are conserved biomolecular condensates that originate in response to many stress conditions. These membraneless organelles contain nontranslating mRNAs and a diverse subproteome, but our knowledge of their regulation and functional relevance is still incipient. Here, we describe a mutual-inhibition interplay between SGs and Cdc28, the budding yeast Cdk. Among Cdc28 interactors acting as negative modulators of Start, we have identified Whi8, an RNA-binding protein that localizes to SGs and recruits the mRNA of CLN3, the most upstream G1 cyclin, for efficient translation inhibition and Cdk inactivation under stress. However, Whi8 also contributes to recruiting Cdc28 to SGs, where it acts to promote their dissolution. As predicted by a mutual-inhibition framework, the SG constitutes a bistable system that is modulated by Cdk. Since mammalian cells display a homologous mechanism, we propose that the opposing functions of specific mRNA-binding proteins and Cdk’s subjugate SG dynamics to a conserved hysteretic switch.

Profiling the physiological pitfalls of anti-hepatitis C direct-acting agents in budding yeast

Sofosbuvir and Daclatasvir are among the direct-acting antiviral (DAA) medications prescribed for the treatment of chronic hepatitis C (CHC) virus infection as combination therapy with other antiviral medications. DAA-based therapy achieves high cure rates, reaching up to 97% depending on the genotype of the causative hepatitis C virus (HCV). While DAAs have been approved as an efficient and well-tolerated therapy for CHC, emerging concerns about adverse cardiac side effects, higher risk of recurrence and occurrence of hepatocellular carcinoma (HCC) and doubts of genotoxicity have been reported. In our study, we investigated in detail physiological off-targets of DAAs and dissected the effects of these drugs on cellular organelles using budding yeast, a unicellular eukaryotic organism. DAAs were found to disturb the architecture of the endoplasmic reticulum (ER) and the mitochondria, while showing no apparent genotoxicity or DNA damaging effect. Our study provides evidence that DAAs are not associated with genotoxicity and highlights the necessity for adjunctive antioxidant therapy to mitigate the adverse effects of DAAs on ER and mitochondria.

Refractive Index Sensing for Measuring Single Cell Growth

Accessing cell growth on adhesive substrates is critical for identifying biophysical properties of cells and their therapeutic response to drug therapies. However, optical techniques have low sensitivity, and their reliability varies with cell type, whereas microfluidic technologies rely on cell suspension. In this paper, we introduced a plasmonic functional assay platform that can precisely measure cell weight and the dynamic change in real-time for adherent cells. Possessing this ability, our platform can determine growth rates of individual cells within only 10 min to map the growth profile of populations in short time intervals. The platform could successfully determine heterogeneity within the growth profile of populations and assess subpopulations exhibiting distinct growth profiles. As a proof of principle, we investigated the growth profile of MCF-7 cells and the effect of two intracellular metabolisms critical for their proliferation. We first investigated the negative effect of serum starvation on cell growth. We then studied ornithine decarboxylase (ODC) activity, a key enzyme which is involved in proliferation, and degraded under low osmolarity that inhibits cell growth. We successfully determined the significant distinction between growth profiles of MCF-7 cells and their ODC-overproducing variants that possess strong resistance to the negative effects of low osmolarity. We also demonstrated that an exogenous parameter, putrescine, could rescue cells from ODC inhibition under hypoosmotic conditions. In addition to the ability of accessing intracellular activities through ex vivo measurements, our platform could also determine therapeutic behaviors of cancer cells in response to drug treatments. Here, we investigated difluoromethylornithine (DFMO), which has antitumor effects on MCF-7 cells by inhibiting ODC activity. We successfully demonstrated the susceptibility of MCF-7 cells to such drug treatment, while its DFMO-resistant subpopulation could survive in the presence of this antigrowth agent. By rapidly determining cell growth kinetics in small samples, our plasmonic platform may be of broad use to basic research and clinical applications.

A cytofluorimetric analysis of a Saccharomyces cerevisiae population cultured in a fed-batch bioreactor

The yeast Saccharomyces cerevisiae is a reference model system and one of the widely used microorganisms in many biotechnological processes. In industrial yeast applications, combined strategies aim to maximize biomass/product yield, with the fed-batch culture being one of the most frequently used. Flow cytometry (FCM) is widely applied in biotechnological processes and represents a key methodology to monitor cell population dynamics. We propose here an application of FCM in the analysis of yeast cell cycle along the time course of a typical S. cerevisiae fed-batch culture. We used two different dyes, SYTOX Green and SYBR Green, with the aim to better define each stage of cell cycle during S. cerevisiae fed-batch culture. The results provide novel insights in the use of FCM cell cycle analysis for the real-time monitoring of S. cerevisiae bioprocesses.

Protocol for tracking the inheritance patterns of proteins in live Saccharomyces cerevisiae cells using a photo-convertible fluorescent protein

Tracking the inheritance patterns of proteins (TrIPP) is a live-cell imaging technique used for tracking maternal protein segregation patterns between mother and daughter cells during asymmetric divisions of budding yeast. We use the photo-convertible fluorescent protein Dendra2 fused to a protein of interest (POI). Irreversible conversion from green to red fluorescence allows for parallel monitoring of old and new proteins for several generations. Single-cell quantitative image analysis of time-lapse microscopy gives synthesis and decay rates, as well as segregation patterns of the POI.

For complete details on the use and execution of this protocol, please refer to Auboiron et al. (2021).

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TriPP is a live-cell imaging technique based on the photo-convertible protein Dendra2

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TriPP reveals segregation patterns of maternal proteins after mitosis

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TriPP produces protein decay and synthesis rates from single-cell observations

The mitotic exit network regulates the spatiotemporal activity of Cdc42 to maintain cell size

During G1 in budding yeast, the Cdc42 GTPase establishes a polar front, along which actin is recruited to direct secretion for bud formation. Cdc42 localizes at the bud cortex and then redistributes between mother and daughter in anaphase. The molecular mechanisms that terminate Cdc42 bud-localized activity during mitosis are poorly understood. We demonstrate that the activity of the Cdc14 phosphatase, released through the mitotic exit network, is required for Cdc42 redistribution between mother and bud. Induced Cdc14 nucleolar release results in premature Cdc42 redistribution between mother and bud. Inhibition of Cdc14 causes persistence of Cdc42 bud localization, which perturbs normal cell size and spindle positioning. Bem3, a Cdc42 GAP, binds Cdc14 and is dephosphorylated at late anaphase in a Cdc14-dependent manner. We propose that Cdc14 dephosphorylates and activates Bem3 to allow Cdc42 inactivation and redistribution. Our results uncover a mechanism through which Cdc14 regulates the spatiotemporal activity of Cdc42 to maintain normal cell size at cytokinesis.

A synthetic RNA-based biosensor for fructose-1,6-bisphosphate that reports glycolytic flux

RNA-based sensors for intracellular metabolites are a promising solution to the emerging issue of metabolic heterogeneity. However, their development, i.e., the conversion of an aptamer into an in vivo-functional intracellular metabolite sensor, still harbors challenges. Here, we accomplished this for the glycolytic flux-signaling metabolite, fructose-1,6-bisphosphate (FBP). Starting from in vitro selection of an aptamer, we constructed device libraries with a hammerhead ribozyme as actuator. Using high-throughput screening in yeast with fluorescence-activated cell sorting (FACS), next-generation sequencing, and genetic-environmental perturbations to modulate the intracellular FBP levels, we identified a sensor that generates ratiometric fluorescent readout. An abrogated response in sensor mutants and occurrence of two sensor conformations-revealed by RNA structural probing-indicated in vivo riboswitching activity. Microscopy showed that the sensor can differentiate cells with different glycolytic fluxes within yeast populations, opening research avenues into metabolic heterogeneity. We demonstrate the possibility to generate RNA-based sensors for intracellular metabolites for which no natural metabolite-binding RNA element exits.

Transcriptome Analysis in Yeast Reveals the Externality of Position Effects

The activity of a gene newly integrated into a chromosome depends on the genomic context of the integration site. This “position effect” has been widely reported, although the other side of the coin, that is, how integration affects the local chromosomal environment, has remained largely unexplored, as have the mechanism and phenotypic consequences of this “externality” of the position effect. Here, we examined the transcriptome profiles of approximately 250 Saccharomyces cerevisiae strains, each with GFP integrated into a different locus of the wild-type strain. We found that in genomic regions enriched in essential genes, GFP expression tended to be lower, and the genes near the integration site tended to show greater expression reduction. Further joint analysis with public genome-wide histone modification profiles indicated that this effect was associated with H3K4me2. More importantly, we found that changes in the expression of neighboring genes, but not GFP expression, significantly altered the cellular growth rate. As a result, genomic loci that showed high GFP expression immediately after integration were associated with growth disadvantages caused by elevated expression of neighboring genes, ultimately leading to a low total yield of GFP in the long run. Our results were consistent with competition for transcriptional resources among neighboring genes and revealed a previously unappreciated facet of position effects. This study highlights the impact of position effects on the fate of exogenous gene integration and has significant implications for biological engineering and the pathology of viral integration into the host genome.

Bacterial Growth Control Mechanisms Inferred from Multivariate Statistical Analysis of Single-Cell Measurements

Analysis of single-cell measurements of bacterial growth and division often relied on testing preconceived models of cell size control mechanisms. Such an approach could limit the scope of data analysis and prevent us from uncovering new information. Here, we take an "agnostic" approach by applying regression methods to multiple simultaneously measured cellular variables, which allow us to infer dependencies among those variables from their apparent correlations. Besides previously observed correlations attributed to particular cell size control mechanisms, we identify dependencies that point to potentially new mechanisms. In particular, cells born smaller than their sisters tend to grow faster and make up for the size difference acquired during division. We also find that sister cells are correlated beyond what single-cell, size-control models predict. These trends are consistently found in repeat experiments, although the dependencies vary quantitatively. Such variation highlights the sensitivity of cell growth to environmental variations and the limitation of currently used experimental setups.

Stress-induced growth rate reduction restricts metabolic resource utilization to modulate osmo-adaptation time

A near-constant feature of stress responses is a downregulation or arrest of the cell cycle, resulting in transient growth slowdown. To investigate the role of growth slowdown in the hyperosmotic shock response of S. cerevisiae, we perturbed the G1/S checkpoint protein Sic1 to enable osmo-stress response activation with diminished growth slowdown. We document that in this mutant, adaptation to stress is accelerated rather than delayed. This accelerated recovery of the mutant proceeds by liquidation of internal glycogen stores, which are then shunted into the osmo-shock response. Therefore, osmo-adaptation in wild-type cells is delayed because growth slowdown prevents full accessibility to cellular glycogen stores. However, faster adaptation comes at the cost of acute sensitivity to subsequent osmo-stresses. We suggest that stress-induced growth slowdown acts as an arbiter to regulate the resources devoted to osmo-shock, balancing short-term adaptation with long-term robustness.

Origin of exponential growth in nonlinear reaction networks

Exponentially growing systems are prevalent in nature, spanning all scales from biochemical reaction networks in single cells to food webs of ecosystems. How exponential growth emerges in nonlinear systems is mathematically unclear. Here, we describe a general theoretical framework that reveals underlying principles of long-term growth: scalability of flux functions and ergodicity of the rescaled systems. Our theory shows that nonlinear fluxes can generate not only balanced growth but also oscillatory or chaotic growth modalities, explaining nonequilibrium dynamics observed in cell cycles and ecosystems. Our mathematical framework is broadly useful in predicting long-term growth rates from natural and synthetic networks, analyzing the effects of system noise and perturbations, validating empirical and phenomenological laws on growth rate, and studying autocatalysis and network evolution.

Conserved Ark1-related kinases function in a TORC2 signaling network

In all orders of life, cell cycle progression in proliferating cells is dependent on cell growth, and the extent of growth required for cell cycle progression is proportional to growth rate. Thus, cells growing rapidly in rich nutrients are substantially larger than slow-growing cells. In budding yeast, a conserved signaling network surrounding Tor complex 2 (target of rapamycin complex 2; TORC2) controls growth rate and cell size in response to nutrient availability. Here, a search for new components of the TORC2 network identified a pair of redundant kinase paralogues called Ark1 and Prk1. Previous studies found that Ark/Prk play roles in endocytosis. Here, we show that Ark/Prk are embedded in the TORC2 network, where they appear to influence TORC2 signaling independently of their roles in endocytosis. We also show that reduced endocytosis leads to increased cell size, which suggests that cell size homeostasis requires coordinated control of plasma membrane growth and endocytosis. The discovery that Ark/Prk are embedded in the TORC2 network suggests a model in which TORC2-dependent signals control both plasma membrane growth and endocytosis, which would ensure that the rates of each process are matched to each other and to the availability of nutrients so that cells achieve and maintain an appropriate size.

Cell-size regulation in budding yeast does not depend on linear accumulation of Whi5

Cells must couple cell-cycle progress to their growth rate to restrict the spread of cell sizes present throughout a population. Linear, rather than exponential, accumulation of Whi5, was proposed to provide this coordination by causing a higher Whi5 concentration in cells born at a smaller size. We tested this model using the inducible GAL1 promoter to make the Whi5 concentration independent of cell size. At an expression level that equalizes the mean cell size with that of wild-type cells, the size distributions of cells with galactose-induced Whi5 expression and wild-type cells are indistinguishable. Fluorescence microscopy confirms that the endogenous and GAL1 promoters produce different relationships between Whi5 concentration and cell volume without diminishing size control in the G1 phase. We also expressed Cln3 from the GAL1 promoter, finding that the spread in cell sizes for an asynchronous population is unaffected by this perturbation. Our findings indicate that size control in budding yeast does not fundamentally originate from the linear accumulation of Whi5, contradicting a previous claim and demonstrating the need for further models of cell-cycle regulation to explain how cell size controls passage through Start.

Growth-Dependent Activation of Protein Kinases Suggests a Mechanism for Measuring Cell Growth

In all cells, progression through the cell cycle occurs only when sufficient growth has occurred. Thus, cells must translate growth into a proportional signal that can be used to measure and transmit information about growth. Previous genetic studies in budding yeast suggested that related kinases called Gin4 and Hsl1 could function in mechanisms that measure bud growth; however, interpretation of the data was complicated by the use of gene deletions that cause complex terminal phenotypes. Here, we used the first conditional alleles of Gin4 and Hsl1 to more precisely define their functions. We show that excessive bud growth during a prolonged mitotic delay is an immediate consequence of inactivating Gin4 and Hsl1 Thus, acute loss of Gin4 and Hsl1 causes cells to behave as though they cannot detect that bud growth has occurred. We further show that Gin4 and Hsl1 undergo gradual hyperphosphorylation during bud growth that is dependent upon growth and correlated with the extent of growth. Moreover, gradual hyperphosphorylation of Gin4 during bud growth requires binding to anionic phospholipids that are delivered to the growing bud. While alternative models are possible, the data suggest that signaling lipids delivered to the growing bud generate a growth-dependent signal that could be used to measure bud growth.

Measuring glycolytic flux in single yeast cells with an orthogonal synthetic biosensor

Metabolic heterogeneity between individual cells of a population harbors significant challenges for fundamental and applied research. Identifying metabolic heterogeneity and investigating its emergence require tools to zoom into metabolism of individual cells. While methods exist to measure metabolite levels in single cells, we lack capability to measure metabolic flux, i.e., the ultimate functional output of metabolic activity, on the single-cell level. Here, combining promoter engineering, computational protein design, biochemical methods, proteomics, and metabolomics, we developed a biosensor to measure glycolytic flux in single yeast cells. Therefore, drawing on the robust cell-intrinsic correlation between glycolytic flux and levels of fructose-1,6-bisphosphate (FBP), we transplanted the B. subtilis FBP-binding transcription factor CggR into yeast. With the developed biosensor, we robustly identified cell subpopulations with different FBP levels in mixed cultures, when subjected to flow cytometry and microscopy. Employing microfluidics, we were also able to assess the temporal FBP/glycolytic flux dynamics during the cell cycle. We anticipate that our biosensor will become a valuable tool to identify and study metabolic heterogeneity in cell populations.

Differential scaling between G1 protein production and cell size dynamics promotes commitment to the cell division cycle in budding yeast

In the unicellular eukaryote Saccharomyces cerevisiae, Cln3-cyclin-dependent kinase activity enables Start, the irreversible commitment to the cell division cycle. However, the concentration of Cln3 has been paradoxically considered to remain constant during G1, due to the presumed scaling of its production rate with cell size dynamics. Measuring metabolic and biosynthetic activity during cell cycle progression in single cells, we found that cells exhibit pulses in their protein production rate. Rather than scaling with cell size dynamics, these pulses follow the intrinsic metabolic dynamics, peaking around Start. Using a viral-based bicistronic construct and targeted proteomics to measure Cln3 at the single-cell and population levels, we show that the differential scaling between protein production and cell size leads to a temporal increase in Cln3 concentration, and passage through Start. This differential scaling causes Start in both daughter and mother cells across growth conditions. Thus, uncoupling between two fundamental physiological parameters drives cell cycle commitment.

Particle Self-Aligning, Focusing, and Electric Impedance Microcytometer Device for Label-Free Single Cell Morphology Discrimination and Yeast Budding Analysis

Microfluidic electric impedance flow cytometry (IFC) devices have been applied in single cell analysis, such as cell counting, volume discrimination, cell viability, etc. A cell's shape provides specific information about cellular physiological and pathological conditions, especially in microorganisms such as yeast. In this study, the particle orientation focusing was theoretically analyzed and realized by hydrodynamics. The pulse width (passing time for the particles) of the conductance signal was used to discriminate particle shapes. Spherical and rod-shaped particles with similar volumes/lengths were differentiated by the IFC device, using the impedance pulse parameters of the events. Then, typical late-budding, early budding, and unbudded yeast cells were distinguished by the width, amplitude, and ratio of width to amplitude (R) of the impedance pulse. The pulse amplitude and the R combination gate for identifying the late-budding yeast was estimated through the statistic results. Using the gate, the late-budding rates under different conditions were calculated. Late-budding rates obtained using our method showed a high correlation (R² = 0.83) with the manual cell counting result and represented the budding status of yeast cells under different conditions proficiently. Thus, the late-budding rate calculated using the above method can be used as a qualitative parameter to assess the reproductive performance of yeast and whether a yeast culturing environment is optimal. This IFC device and cell shape discrimination method is very simple and could be applied in the fermentation industry and other microorganisms' discrimination as a rapid analysis technique in the future.

A Conserved PP2A Regulatory Subunit Enforces Proportional Relationships Between Cell Size and Growth Rate

Cell size is proportional to growth rate. Thus, cells growing rapidly in rich nutrients can be nearly twice the size of cells growing slowly in poor nutrients. This proportional relationship appears to hold across all orders of life, yet the underlying mechanisms are unknown. In budding yeast, most growth occurs during mitosis, and the proportional relationship between cell size and growth rate is therefore enforced primarily by modulating growth in mitosis. When growth is slow, the duration of mitosis is increased to allow more time for growth, yet the amount of growth required to complete mitosis is reduced, which leads to the birth of small daughter cells. Previous studies have found that Rts1, a member of the conserved B56 family of protein phosphatase 2A regulatory subunits, works in a TORC2 signaling network that influences cell size and growth rate. However, it was unclear whether Rts1 influences cell growth and size in mitosis. Here, we show that Rts1 is required for the proportional relationship between cell size and growth rate during mitosis. Moreover, nutrients and Rts1 influence the duration and extent of growth in mitosis via Wee1 and Pds1/securin, two conserved regulators of mitotic progression. Together, the data are consistent with a model in which global signals that set growth rate also set the critical amount of growth required for cell cycle progression, which would provide a simple mechanistic explanation for the proportional relationship between cell size and growth rate.

Osmolyte homeostasis controls single-cell growth rate and maximum cell size of Saccharomyces cerevisiae

Cell growth is well described at the population level, but precisely how nutrient and water uptake and cell wall expansion drive the growth of single cells is poorly understood. Supported by measurements of single-cell growth trajectories and cell wall elasticity, we present a single-cell growth model for yeast. The model links the thermodynamic quantities, such as turgor pressure, osmolarity, cell wall elasto-plasticity, and cell size, applying concepts from rheology and thin shell theory. It reproduces cell size dynamics during single-cell growth, budding, and hyper-osmotic or hypo-osmotic stress. We find that single-cell growth rate and final size are primarily governed by osmolyte uptake and consumption, while bud expansion requires additionally different cell wall extensibilities between mother and bud. Based on first principles the model provides a more accurate description of size dynamics than previous attempts and its analytical simplification allows for easy combination with models for other cell processes.

Proteostasis collapse, a hallmark of aging, hinders the chaperone-Start network and arrests cells in G1

Loss of proteostasis and cellular senescence are key hallmarks of aging, but direct cause-effect relationships are not well understood. We show that most yeast cells arrest in G1 before death with low nuclear levels of Cln3, a key G1 cyclin extremely sensitive to chaperone status. Chaperone availability is seriously compromised in aged cells, and the G1 arrest coincides with massive aggregation of a metastable chaperone-activity reporter. Moreover, G1-cyclin overexpression increases lifespan in a chaperone-dependent manner. As a key prediction of a model integrating autocatalytic protein aggregation and a minimal Start network, enforced protein aggregation causes a severe reduction in lifespan, an effect that is greatly alleviated by increased expression of specific chaperones or cyclin Cln3. Overall, our data show that proteostasis breakdown, by compromising chaperone activity and G1-cyclin function, causes an irreversible arrest in G1, configuring a molecular pathway postulating proteostasis decay as a key contributing effector of cell senescence.

Advances in quantitative biology methods for studying replicative aging in Saccharomyces cerevisiae

Aging is a complex, yet pervasive phenomenon in biology. As human cells steadily succumb to the deteriorating effects of aging, so too comes a host of age-related ailments such as neurodegenerative disorders, cardiovascular disease and cancer. Therefore, elucidation of the molecular networks that drive aging is of paramount importance to human health. Progress toward this goal has been aided by studies from simple model organisms such as Saccharomyces cerevisiae. While work in budding yeast has already revealed much about the basic biology of aging as well as a number of evolutionarily conserved pathways involved in this process, recent technological advances are poised to greatly expand our knowledge of aging in this simple eukaryote. Here, we review the latest developments in microfluidics, single-cell analysis and high-throughput technologies for studying single-cell replicative aging in S. cerevisiae. We detail the challenges each of these methods addresses as well as the unique insights into aging that each has provided. We conclude with a discussion of potential future applications of these techniques as well as the importance of single-cell dynamics and quantitative biology approaches for understanding cell aging.