Large-Scale Survey of Intraspecific Fitness and Cell Morphology Variation in a Protoploid Yeast Species

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.

The cell morphological diversity of Saccharomycotina yeasts

The ∼1 200 known species in subphylum Saccharomycotina are a highly diverse clade of unicellular fungi. During its lifecycle, a typical yeast exhibits multiple cell types with various morphologies; these morphologies vary across Saccharomycotina species. Here, we synthesize the evolutionary dimensions of variation in cellular morphology of yeasts across the subphylum, focusing on variation in cell shape, cell size, type of budding, and filament production. Examination of 332 representative species across the subphylum revealed that the most common budding cell shapes are ovoid, spherical, and ellipsoidal, and that their average length and width is 5.6 µm and 3.6 µm, respectively. 58.4% of yeast species examined can produce filamentous cells, and 87.3% of species reproduce asexually by multilateral budding, which does not require utilization of cell polarity for mitosis. Interestingly, ∼1.8% of species examined have not been observed to produce budding cells, but rather only produce filaments of septate hyphae and/or pseudohyphae. 76.9% of yeast species examined have sexual cycle descriptions, with most producing one to four ascospores that are most commonly hat-shaped (37.4%). Systematic description of yeast cellular morphological diversity and reconstruction of its evolution promises to enrich our understanding of the evolutionary cell biology of this major fungal lineage.

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.

Phenotypic Diagnosis of Lineage and Differentiation During Sake Yeast Breeding

Sake yeast was developed exclusively in Japan. Its diversification during breeding remains largely uncharacterized. To evaluate the breeding processes of the sake lineage, we thoroughly investigated the phenotypes and differentiation of 27 sake yeast strains using high-dimensional, single-cell, morphological phenotyping. Although the genetic diversity of the sake yeast lineage is relatively low, its morphological diversity has expanded substantially compared to that of the Saccharomycescerevisiae species as a whole. Evaluation of the different types of breeding processes showed that the generation of hybrids (crossbreeding) has more profound effects on cell morphology than the isolation of mutants (mutation breeding). Analysis of phenotypic robustness revealed that some sake yeast strains are more morphologically heterogeneous, possibly due to impairment of cellular network hubs. This study provides a new perspective for studying yeast breeding genetics and micro-organism breeding strategies.

Dissection of quantitative traits by bulk segregant mapping in a protoploid yeast species

Since more than a decade ago, Saccharomyces cerevisiae has been used as a model to dissect complex traits, revealing the genetic basis of a large number of traits in fine detail. However, to have a more global view of the genetic architecture of traits across species, the examination of the molecular basis of phenotypes within non-conventional species would undoubtedly be valuable. In this respect, the Saccharomycotina yeasts represent ideal and potential non-model organisms. Here we sought to assess the feasibility of genetic mapping by bulk segregant analysis in the protoploid Lachancea kluyveri (formerly S. kluyveri) yeast species, a distantly related species to S. cerevisiae For this purpose, we designed a fluorescent mating-type marker, compatible with any mating-competent strains representative of this species, to rapidly create a large population of haploid segregants (>10(5) cells). Quantitative trait loci can be mapped by selecting and sequencing an enriched pool of progeny with extreme phenotypic values. As a test bed, we applied this strategy and mapped the causal loci underlying halotolerance phenotypes in L. kluyveri Overall, this study demonstrates that bulk segregant mapping is a powerful way for investigating the genetic basis of natural variations in non-model yeast organisms and more precisely in L. kluyveri.

Differences in environmental stress response among yeasts is consistent with species-specific lifestyles

Defining how organisms respond to environmental change has always been an important step toward understanding their adaptive capacity and physiology. Variation in transcription during stress has been widely described in model species, especially in the yeast Saccharomyces cerevisiae, which helped to shape general rules regarding how cells cope with environmental constraints, as well as to decipher the functions of many genes. Comparison of the environmental stress response (ESR) across species is essential to obtaining better insight into the common and species-specific features of stress defense. In this context, we explored the transcriptional landscape of the yeast Lachancea kluyveri (formerly Saccharomyces kluyveri) in response to diverse stresses, using RNA sequencing. We investigated variation in gene expression and observed a link between genetic plasticity and environmental sensitivity. We identified the ESR genes in this species and compared them to those already found in S. cerevisiae We observed common features between the two species, as well as divergence in the regulatory networks involved. Of interest, some changes were related to differences in species lifestyle. Thus we were able to decipher how adaptation to stress has evolved among different yeast species. Finally, by analyzing patterns of coexpression, we were able to propose potential biological functions for 42% of genes and also annotate 301 genes for which no function could be assigned by homology. This large data set allowed for the characterization of the evolution of gene regulation and provides an efficient tool for assessing gene function.