Diversity of Ca2+-induced morphology revealed by morphological phenotyping of Ca2+-sensitive mutants of Saccharomyces cerevisiae

Application of unimodal probability distribution models for morphological phenotyping of budding yeast

Morphological phenotyping of the budding yeast Saccharomyces cerevisiae has helped to greatly clarify the functions of genes and increase our understanding of cellular functional networks. It is necessary to understand cell morphology and perform quantitative morphological analysis (QMA) but assigning precise values to morphological phenotypes has been challenging. We recently developed the Unimodal Morphological Data image analysis pipeline for this purpose. All true values can be estimated theoretically by applying an appropriate probability distribution if the distribution of experimental values follows a unimodal pattern. This reliable pipeline allows several downstream analyses, including detection of subtle morphological differences, selection of mutant strains with similar morphology, clustering based on morphology, and study of morphological diversity. In addition to basic research, morphological analyses of yeast cells can also be used in applied research to monitor breeding and fermentation processes and control the fermentation activity of yeast cells.

Assignment of unimodal probability distribution models for quantitative morphological phenotyping

Background

Cell morphology is a complex and integrative readout, and therefore, an attractive measurement for assessing the effects of genetic and chemical perturbations to cells. Microscopic images provide rich information on cell morphology; therefore, subjective morphological features are frequently extracted from digital images. However, measured datasets are fundamentally noisy; thus, estimation of the true values is an ultimate goal in quantitative morphological phenotyping. Ideal image analyses require precision, such as proper probability distribution analyses to detect subtle morphological changes, recall to minimize artifacts due to experimental error, and reproducibility to confirm the results.

Results

Here, we present UNIMO (UNImodal MOrphological data), a reliable pipeline for precise detection of subtle morphological changes by assigning unimodal probability distributions to morphological features of the budding yeast cells. By defining the data type, followed by validation using the model selection method, examination of 33 probability distributions revealed nine best-fitting probability distributions. The modality of the distribution was then clarified for each morphological feature using a probabilistic mixture model. Using a reliable and detailed set of experimental log data of wild-type morphological replicates, we considered the effects of confounding factors. As a result, most of the yeast morphological parameters exhibited unimodal distributions that can be used as basic tools for powerful downstream parametric analyses. The power of the proposed pipeline was confirmed by reanalyzing morphological changes in non-essential yeast mutants and detecting 1284 more mutants with morphological defects compared with a conventional approach (Box–Cox transformation). Furthermore, the combined use of canonical correlation analysis permitted global views on the cellular network as well as new insights into possible gene functions.

Conclusions

Based on statistical principles, we showed that UNIMO offers better predictions of the true values of morphological measurements. We also demonstrated how these concepts can provide biologically important information. This study draws attention to the necessity of employing a proper approach to do more with less.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01283-6.

Global study of holistic morphological effectors in the budding yeast Saccharomyces cerevisiae

Background

The size of the phenotypic effect of a gene has been thoroughly investigated in terms of fitness and specific morphological traits in the budding yeast Saccharomyces cerevisiae, but little is known about gross morphological abnormalities.

Results

We identified 1126 holistic morphological effectors that cause severe gross morphological abnormality when deleted, and 2241 specific morphological effectors with weak holistic effects but distinctive effects on yeast morphology. Holistic effectors fell into many gene function categories and acted as network hubs, affecting a large number of morphological traits, interacting with a large number of genes, and facilitating high protein expression. Holistic morphological abnormality was useful for estimating the importance of a gene to morphology. The contribution of gene importance to fitness and morphology could be used to efficiently classify genes into functional groups.

Conclusion

Holistic morphological abnormality can be used as a reproducible and reliable gene feature for high-dimensional morphological phenotyping. It can be used in many functional genomic applications.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4526-z) contains supplementary material, which is available to authorized users.

Systematic analysis of Ca2+ homeostasis in Saccharomyces cerevisiae based on chemical-genetic interaction profiles

We investigated the global landscape of Ca2+ homeostasis in budding yeast based on high-dimensional chemical-genetic interaction profiles. The morphological responses of 62 Ca2+-sensitive (cls) mutants were quantitatively analyzed with the image processing program CalMorph after exposure to a high concentration of Ca2+ After a generalized linear model was applied, an analysis of covariance model was used to detect significant Ca2+-cls interactions. We found that high-dimensional, morphological Ca2+-cls interactions were mixed with positive (86%) and negative (14%) chemical-genetic interactions, whereas one-dimensional fitness Ca2+-cls interactions were all negative in principle. Clustering analysis with the interaction profiles revealed nine distinct gene groups, six of which were functionally associated. In addition, characterization of Ca2+-cls interactions revealed that morphology-based negative interactions are unique signatures of sensitized cellular processes and pathways. Principal component analysis was used to discriminate between suppression and enhancement of the Ca2+-sensitive phenotypes triggered by inactivation of calcineurin, a Ca2+-dependent phosphatase. Finally, similarity of the interaction profiles was used to reveal a connected network among the Ca2+ homeostasis units acting in different cellular compartments. Our analyses of high-dimensional chemical-genetic interaction profiles provide novel insights into the intracellular network of yeast Ca2+ homeostasis.

Single-cell phenomics in budding yeast

The demand for phenomics, a high-dimensional and high-throughput phenotyping method, has been increasing in many fields of biology. The budding yeast Saccharomyces cerevisiae, a unicellular model organism, provides an invaluable system for dissecting complex cellular processes using high-resolution phenotyping. Moreover, the addition of spatial and temporal attributes to subcellular structures based on microscopic images has rendered this cell phenotyping system more reliable and amenable to analysis. A well-designed experiment followed by appropriate multivariate analysis can yield a wealth of biological knowledge. Here we review recent advances in cell imaging and illustrate their broad applicability to eukaryotic cells by showing how these techniques have advanced our understanding of budding yeast.

Applications in image-based profiling of perturbations

A dramatic shift has occurred in how biologists use microscopy images. Whether experiments are small-scale or high-throughput, automatically quantifying biological properties in images is now widespread. We see yet another revolution under way: a transition towards using automated image analysis to not only identify phenotypes a biologist specifically seeks to measure ('screening') but also as an unbiased and sensitive tool to capture a wide variety of subtle features of cell (or organism) state ('profiling'). Mapping similarities among samples using image-based (morphological) profiling has tremendous potential to transform drug discovery, functional genomics, and basic biological research. Applications include target identification, lead hopping, library enrichment, functionally annotating genes/alleles, and identifying small molecule modulators of gene activity and disease-specific phenotypes.

Image-based prediction of drug target in yeast

Discovering the intracellular target of drugs is a fundamental challenge in biomedical research. We developed an image-based technique with which we were able to identify intracellular target of the compounds in the yeast Saccharomyces cerevisiae. Here, we describe the rationale of the technique, staining of yeast cells, image acquisition, data processing, and statistical analysis required for prediction of drug targets.

Distinct roles of cell wall biogenesis in yeast morphogenesis as revealed by multivariate analysis of high-dimensional morphometric data

To better define how cell wall structure affects morphogenesis, the morphology of yeast cells was analyzed quantitatively after treatment with the three drugs that inhibit different aspects of cell wall synthesis. These drugs induced both similar effects, including broader necks and increased morphological variation, and distinct effects.

The cell wall of budding yeast is a rigid structure composed of multiple components. To thoroughly understand its involvement in morphogenesis, we used the image analysis software CalMorph to quantitatively analyze cell morphology after treatment with drugs that inhibit different processes during cell wall synthesis. Cells treated with cell wall–affecting drugs exhibited broader necks and increased morphological variation. Tunicamycin, which inhibits the initial step of N-glycosylation of cell wall mannoproteins, induced morphologies similar to those of strains defective in α-mannosylation. The chitin synthase inhibitor nikkomycin Z induced morphological changes similar to those of mutants defective in chitin transglycosylase, possibly due to the critical role of chitin in anchoring the β-glucan network. To define the mode of action of echinocandin B, a 1,3-β-glucan synthase inhibitor, we compared the morphology it induced with mutants of Fks1 that contains the catalytic domain for 1,3-β-glucan synthesis. Echinocandin B exerted morphological effects similar to those observed in some fks1 mutants, with defects in cell polarity and reduced glucan synthesis activity, suggesting that echinocandin B affects not only 1,3-β-glucan synthesis, but also another functional domain. Thus our multivariate analyses reveal discrete functions of cell wall components and increase our understanding of the pharmacology of antifungal drugs.

Dynamic changes in brewing yeast cells in culture revealed by statistical analyses of yeast morphological data

The vitality of brewing yeasts has been used to monitor their physiological state during fermentation. To investigate the fermentation process, we used the image processing software, CalMorph, which generates morphological data on yeast mother cells and bud shape, nuclear shape and location, and actin distribution. We found that 248 parameters changed significantly during fermentation. Successive use of principal component analysis (PCA) revealed several important features of yeast, providing insight into the dynamic changes in the yeast population. First, PCA indicated that much of the observed variability in the experiment was summarized in just two components: a change with a peak and a change over time. Second, PCA indicated the independent and important morphological features responsible for dynamic changes: budding ratio, nucleus position, neck position, and actin organization. Thus, the large amount of data provided by imaging analysis can be used to monitor the fermentation processes involved in beer and bioethanol production.

Regulation of cation balance in Saccharomyces cerevisiae

All living organisms require nutrient minerals for growth and have developed mechanisms to acquire, utilize, and store nutrient minerals effectively. In the aqueous cellular environment, these elements exist as charged ions that, together with protons and hydroxide ions, facilitate biochemical reactions and establish the electrochemical gradients across membranes that drive cellular processes such as transport and ATP synthesis. Metal ions serve as essential enzyme cofactors and perform both structural and signaling roles within cells. However, because these ions can also be toxic, cells have developed sophisticated homeostatic mechanisms to regulate their levels and avoid toxicity. Studies in Saccharomyces cerevisiae have characterized many of the gene products and processes responsible for acquiring, utilizing, storing, and regulating levels of these ions. Findings in this model organism have often allowed the corresponding machinery in humans to be identified and have provided insights into diseases that result from defects in ion homeostasis. This review summarizes our current understanding of how cation balance is achieved and modulated in baker's yeast. Control of intracellular pH is discussed, as well as uptake, storage, and efflux mechanisms for the alkali metal cations, Na(+) and K(+), the divalent cations, Ca(2+) and Mg(2+), and the trace metal ions, Fe(2+), Zn(2+), Cu(2+), and Mn(2+). Signal transduction pathways that are regulated by pH and Ca(2+) are reviewed, as well as the mechanisms that allow cells to maintain appropriate intracellular cation concentrations when challenged by extreme conditions, i.e., either limited availability or toxic levels in the environment.

Single-cell phenomics reveals intra-species variation of phenotypic noise in yeast

Background

Most quantitative measures of phenotypic traits represent macroscopic contributions of large numbers of cells. Yet, cells of a tissue do not behave similarly, and molecular studies on several organisms have shown that regulations can be highly stochastic, sometimes generating diversified cellular phenotypes within tissues. Phenotypic noise, defined here as trait variability among isogenic cells of the same type and sharing a common environment, has therefore received a lot of attention. Given the potential fitness advantage provided by phenotypic noise in fluctuating environments, the possibility that it is directly subjected to evolutionary selection is being considered. For selection to act, phenotypic noise must differ between contemporary genotypes. Whether this is the case or not remains, however, unclear because phenotypic noise has very rarely been quantified in natural populations.

Results

Using automated image analysis, we describe here the phenotypic diversity of S. cerevisiae morphology at single-cell resolution. We profiled hundreds of quantitative traits in more than 1,000 cells of 37 natural strains, which represent various geographical and ecological origins of the species. We observed abundant trait variation between strains, with no correlation with their ecological origin or population history. Phenotypic noise strongly depended on the strain background. Noise variation was largely trait-specific (specific strains showing elevated noise for subset of traits) but also global (a few strains displaying elevated noise for many unrelated traits).

Conclusions

Our results demonstrate that phenotypic noise does differ quantitatively between natural populations. This supports the possibility that, if noise is adaptive, microevolution may tune it in the wild. This tuning may happen on specific traits or by varying the degree of global phenotypic buffering.

Profilin is required for Ca2+ homeostasis and Ca2+-modulated bud formation in yeast

A cls5-1 mutant of Saccharomyces cerevisiae is specifically sensitive to high concentrations of Ca2+, with elevated intracellular calcium content and altered cell morphology in the presence of 100 mM Ca2+. To reveal the mechanisms of the Ca2+-sensitive phenotype, we investigated the gene responsible and its interacting network. We demonstrated that CLS5 is identical to PFY1, encoding profilin. Involvement of profilin in the maintenance of intracellular Ca2+ homeostasis was supported by the fact that both exchangeable and non-exchangeable intracellular Ca2+ pools in the cls5-1 mutant are higher than those of the wild-type strain. Several mutations of the genes whose proteins physically interact with profilin resulted in the Ca2+-sensitive phenotype. Examination of the intracellular Ca2+ pools indicated that Bni1p, Bem1p, Rho1p, and Cla4p are also required for the maintenance of Ca2+ homeostasis. Quantitative morphological analysis revealed that the Ca2+-induced morphological changes in cls5-1 cells are similar to bem1 and cls4-1 cells. Common Ca2+-induced morphological changes were an increase in cell size and a decrease of the ratio of budded cells in the population. Since a mutation allele of cls4-1 is located in the CDC24 gene, we suggest that profilin, Bem1p, and Cdc24p are required for Ca2+-modulated bud formation. Thus, profilin is involved in Ca2+ regulation in two ways: the first is Ca2+ homeostasis by coordination with Bni1p, Bem1p, Rho1p, and Cla4p, and the second is the requirement of Ca2+ for bud formation by coordination with Bem1p and Cdc24p.

Ethanol fermentation driven by elevated expression of the G1 cyclin gene CLN3 in sake yeast

Cellular and subcellular morphology reflects the physiological state of a cell. To determine the physiological nature of sake yeast with superior fermentation properties, we quantitatively analyzed the morphology of sake yeast cells by using the CalMorph system. All the sake strains examined here exhibited common morphological traits that are typically observed in the well-characterized whiskey (whi) mutants that show accelerated G(1)/S transition. In agreement with this finding, the sake strain showed less efficient G(0)/G(1) arrest and elevated expression of the G(1) cyclin gene CLN3 throughout the fermentation period. Furthermore, deletion of CLN3 remarkably impaired the fermentation rate in both sake and laboratory strains. Disruption of the SWI6 gene, a transcriptional coactivator responsible for Cln3p-mediated G(1)/S transition, also resulted in a decreased fermentation rate, whereas whi mutants exhibited significant improvement in the fermentation rate, demonstrating positive roles of Cln3p and its downstream signalling pathway in facilitating ethanol fermentation. The combined results indicate that enhanced induction of CLN3 contributes to the high fermentation rate of sake yeast, which are natural whi mutants.

Zds2p regulates Swe1p-dependent polarized cell growth in Saccharomyces cerevisiae via a novel Cdc55p interaction domain

Deletion of the paralogs ZDS1 and ZDS2 in the budding yeast Saccharomyces cerevisiae causes a mis-regulation of polarized cell growth. Here we show a function for these genes as regulators of the Swe1p (Wee1p) kinase-dependent G2/M checkpoint. We identified a conserved domain in the C-terminus of Zds2p consisting of amino acids 813-912 (hereafter referred to as ZH4 for Zds homology 4) that is required for regulation of Swe1p-dependent polarized bud growth. ZH4 is shown by protein affinity assays to be necessary and sufficient for interaction with Cdc55p, a regulatory subunit of protein phosphatase 2A (PP2A). We hypothesized that the Zds proteins are in a pathway that negatively regulates the Swe1p-dependent G2/M checkpoint via Cdc55p. Supporting this model, deletion of CDC55 rescues the aberrant bud morphology of a zds1Δzds2Δ strain. We also show that expression of ZDS1 or ZDS2 from a strong galactose-inducible promoter can induce mitosis even when the Swe1p-dependent G2/M checkpoint is activated by mis-organization of the actin cytoskeleton. This negative regulation requires the CDC55 gene. Together these data indicate that the Cdc55p/Zds2p module has a function in the regulation of the Swe1p-dependent G2/M checkpoint.

High-content, image-based screening for drug targets in yeast

Background

Drug discovery and development are predicated on elucidation of the potential mechanisms of action and cellular targets of candidate chemical compounds. Recent advances in high-content imaging techniques allow simultaneous analysis of a range of cellular events. In this study, we propose a novel strategy to identify drug targets by combining genetic screening and high-content imaging in yeast.

Methodology

In this approach, we infer the cellular functions affected by candidate drugs by comparing morphologic changes induced by the compounds with the phenotypes of yeast mutants.

Conclusions

Using this method and four well-characterized reagents, we successfully identified previously known target genes of the compounds as well as other genes involved with functionally related cellular pathways. This is the first demonstration of a genetic high-content assay that can be used to identify drug targets based on morphologic phenotypes of a reference mutant panel.

Multiple functional domains of the yeast l,3-beta-glucan synthase subunit Fks1p revealed by quantitative phenotypic analysis of temperature-sensitive mutants

The main filamentous structural component of the cell wall of the yeast Saccharomyces cerevisiae is 1,3-beta-glucan, which is synthesized by a plasma membrane-localized enzyme called 1,3-beta-glucan synthase (GS). Here we analyzed the quantitative cell morphology and biochemical properties of 10 different temperature-sensitive mutants of FKS1, a putative catalytic subunit of GS. To untangle their pleiotropic phenotypes, the mutants were classified into three functional groups. In the first group, mutants fail to synthesize 1,3-beta-glucan at the proper subcellular location, although GS activity is normal in vitro. In the second group, mutants have normal 1,3-beta-glucan content but are defective in polarized growth and endocytosis. In the third group, mutations in the putative catalytic domain of Fks1p result in a loss of the catalytic activity of GS. The differences among the three groups suggest that Fks1p consists of multiple domains that are required for cell wall construction and cellular morphogenesis.

Comprehensive and quantitative analysis of yeast deletion mutants defective in apical and isotropic bud growth

To obtain a comprehensive understanding of the budding phase transition, 4,711 Saccharomyces cerevisiae haploid nonessential gene deletion mutants were screened with the image processing program CalMorph, and 35 mutants with a round bud and 173 mutants with an elongated bud were statistically identified. We classified round and elongated bud mutants based on factors thought to affect the duration of the apical bud growth phase. Two round bud mutants (arc18 and sac6) were found to be defective in apical actin patch localization. Several elongated bud mutants demonstrated a delay of cell cycle progression at the apical growth phase, suggesting that these mutants have a defect in the control of cell cycle progression.

A microfluidic device to acquire high-magnification microphotographs of yeast cells

BACKGROUND

Yeast cell morphology was investigated to reveal the molecular mechanisms of cell morphogenesis and to identify key factors of other processes such as cell cycle progression. We recently developed a semi-automatic image processing program called CalMorph, which allows us to quantitatively analyze yeast cell morphology with the 501 parameters as biological traits and uncover statistical relationships between cell morphological phenotypes and genotypes. However, the current semi-automatic method is not suitable for morphological analysis of large-scale yeast mutants for the reliable prediction of gene functions because of its low-throughput especially at the manual image-acquiring process.

RESULTS

In this study, we developed a microfluidic chip designed to acquire successive microscopic images of yeast cells suitable for CalMorph image analysis. With the microfluidic chip, the morphology of living cells and morphological changes that occur during the cell cycle were successfully characterized.

CONCLUSION

The microfluidic chip enabled us to acquire the images faster than the conventional method. We speculate that the use of microfluidic chip is effective in acquiring images of large-scale for automated analysis of yeast strains.