Identification of mutants with increased variation in cell size at onset of mitosis in fission yeast

A novel cell biological tool to explain mechanics and dynamics in fission yeast

The Rho guanosine triphosphatase hydrolase enzyme (GTPase) is required for the control of the actin cytoskeleton, but its activation in vivo condition is unknown. The study's goal was to find a new synthetic nanobody VHH (P-36 tagged with mNeonGreen) that interacts strongly with the Rho GTPase. We present the first novel synthetic nanobody, VHH (P-36 tagged with mNeonGreen), tested in fission yeast cells and found to have a particular interaction with Rho1GTPase. Plasmids were constructed by using of certain enzymes to digest the pDUAL-pef1a vector plasmid to produce a protein that was encoded by cloned genes. A varied VHH library was created synthetically, then transformed into yeast cells, and positive clones were chosen using chemical agents. To investigate protein interactions and cellular reactions, several studies were carried out, such as live cell imaging, growth curve analysis, coimmunoprecipitation, structural analysis, and cell therapies. Prism and RStudio were used for the statistical analysis. The presence of VHH (P-36) has no effect on the growth pattern making it an appropriate model for studying cytokinesis in vivo. According to a computational biological study, its affinity to interact with Rho1GTPase with all the complementarity-determining region (CDR) regions found on VHH (P-36) is extremely strong. We were able to track its subcellular target by localization using a fluorescent confocal microscope, ensuring the maintenance of cell polarity and morphology. Spheroplast analysis revealed a circular-shaped cell with an even distribution of Rho1 tagged VHH (P-36), indicating that the interaction occurs near the plasma membrane. The introduction of latrunculin-A (Lat-A) disrupted Rho GTPase localization, demonstrating the control over actin production, and the cell did not show evidence of mitotic phase commencement while Lat-A was present. Finally, this important biological tool can aid in our understanding of the mechanics and dynamics of cytokinesis in relation to Rho1GTPase.

The fission yeast cell size control system integrates pathways measuring cell surface area, volume, and time

Eukaryotic cells tightly control their size, but the relevant aspect of size is unknown in most cases. Fission yeast divide at a threshold cell surface area (SA) due, in part, to the protein kinase Cdr2. We find that fission yeast cells only divide by SA under a size threshold. Mutants that divide at a larger size shift to volume-based divisions. Diploid cells divide at a larger size than haploid cells do, but they maintain SA-based divisions, and this indicates that the size threshold for changing from surface-area-based to volume-based control is set by ploidy. Within this size control system, we found that the mitotic activator Cdc25 accumulates like a volume-based sizer molecule, whereas the mitotic cyclin Cdc13 accumulates in the nucleus as a timer. We propose an integrated model for cell size control based on multiple signaling pathways that report on distinct aspects of cell size and growth, including cell SA (Cdr2), cell volume (Cdc25), and time (Cdc13). Combined modeling and experiments show how this system can generate both sizer- and adder-like properties.

Characterization of proteome-size scaling by integrative omics reveals mechanisms of proliferation control in cancer

Almost all living cells maintain size uniformity through successive divisions. Proteins that over and underscale with size can act as rheostats, which regulate cell cycle progression. Using a multiomic strategy, we leveraged the heterogeneity of melanoma cell lines to identify peptides, transcripts, and phosphorylation events that differentially scale with cell size. Subscaling proteins are enriched in regulators of the DNA damage response and cell cycle progression, whereas super-scaling proteins included regulators of the cytoskeleton, extracellular matrix, and inflammatory response. Mathematical modeling suggested that decoupling growth and proliferative signaling may facilitate cell cycle entry over senescence in large cells when mitogenic signaling is decreased. Regression analysis reveals that up-regulation of TP53 or CDKN1A/p21CIP1 is characteristic of proliferative cancer cells with senescent-like sizes/proteomes. This study provides one of the first demonstrations of size-scaling phenomena in cancer and how morphology influences the chemistry of the cell.

Eukaryotic Cell Size Control and Its Relation to Biosynthesis and Senescence

The most fundamental feature of cellular form is size, which sets the scale of all cell biological processes. Growth, form, and function are all necessarily linked in cell biology, but we often do not understand the underlying molecular mechanisms nor their specific functions. Here, we review progress toward determining the molecular mechanisms that regulate cell size in yeast, animals, and plants, as well as progress toward understanding the function of cell size regulation. It has become increasingly clear that the mechanism of cell size regulation is deeply intertwined with basic mechanisms of biosynthesis, and how biosynthesis can be scaled (or not) in proportion to cell size. Finally, we highlight recent findings causally linking aberrant cell size regulation to cellular senescence and their implications for cancer therapies.

Photo Phenosizer, a rapid machine learning-based method to measure cell dimensions in fission yeast

Cell metrics such as area, length, and width provide informative data about cell cycle dynamics. Factors that affect these dimensions include environmental conditions and genotypic differences. Fission yeast ( Schizosaccharomyces pombe ) is a rod-shaped ascomycete fungus in which cell cycle progression is linked to changes in cell length. Microscopy work to obtain these metrics places considerable burdens on time and effort. We now report on Photo Phenosizer (PP), a machine learning-based methodology that measures cell dimensions in fission yeast. It does this in an unbiased, automated manner and streamlines workflow from image acquisition to statistical analysis. Using this new approach, we constructed an efficient and flexible pipeline for experiments involving different growth media (YES and EMM) and treatments (Untreated and MMS) as well as different genotypes ( cut6-621 versus wildtype). This methodology allows for the analysis of larger sample sizes and faster image processing relative to manual segmentation. Our findings suggest that researchers using PP can quickly and efficiently determine cell size differences under various conditions that highlight genetic or environmental disruptions.

Characterizing non-exponential growth and bimodal cell size distributions in fission yeast: An analytical approach

Unlike many single-celled organisms, the growth of fission yeast cells within a cell cycle is not exponential. It is rather characterized by three distinct phases (elongation, septation, and reshaping), each with a different growth rate. Experiments also showed that the distribution of cell size in a lineage can be bimodal, unlike the unimodal distributions measured for the bacterium Escherichia coli. Here we construct a detailed stochastic model of cell size dynamics in fission yeast. The theory leads to analytic expressions for the cell size and the birth size distributions, and explains the origin of bimodality seen in experiments. In particular, our theory shows that the left peak in the bimodal distribution is associated with cells in the elongation phase, while the right peak is due to cells in the septation and reshaping phases. We show that the size control strategy, the variability in the added size during a cell cycle, and the fraction of time spent in each of the three cell growth phases have a strong bearing on the shape of the cell size distribution. Furthermore, we infer all the parameters of our model by matching the theoretical cell size and birth size distributions to those from experimental single-cell time-course data for seven different growth conditions. Our method provides a much more accurate means of determining the size control strategy (timer, adder or sizer) than the standard method based on the slope of the best linear fit between the birth and division sizes. We also show that the variability in added size and the strength of size control in fission yeast depend weakly on the temperature but strongly on the culture medium. More importantly, we find that stronger size homeostasis and larger added size variability are required for fission yeast to adapt to unfavorable environmental conditions.

Advances in microscopy enable us to follow single cells over long timescales from which we can understand how their size varies with time and the nature of innate strategies developed to control cell size. These data show that in many cell types, growth is exponential and the distribution of cell size has one peak, namely there is a single characteristic cell size. However data for fission yeast show remarkable differences: growth is non-exponential and the distribution of cell sizes has two peaks, corresponding to different growth phases. Here we construct a detailed stochastic mathematical model of this organism; by solving the model analytically, we show that it is able to predict the two peaked distributions of cell size seen in data and provide an explanation for each peak in terms of various growth phases of the single-celled organism. Furthermore, by fitting the model to the data, we infer values for the rates of all microscopic processes in our model. This method is shown to provide a much more reliable inference than current methods and shed light on how the strategy used by fission yeast cells to control their size varies with external conditions.

Phosphoinositide-Dependent Protein Kinases Regulate Cell Cycle Progression Through the SAD Kinase Cdr2 in Fission Yeast

Aberration in the control of cell cycle contributes to the development and progression of many diseases including cancers. Ksg1 is a Schizosaccharomyces pombe fission yeast homolog of mammalian phosphoinositide-dependent protein kinase 1 (PDK1) which is regarded as a signaling hub for human tumorigenesis. A previous study reported that Ksg1 plays an important role in cell cycle progression, however, the underlying mechanism remains elusive. Our genomic library screen for novel elements involved in Ksg1 function identified two serine/threonine kinases, namely SAD family kinase Cdr2 and another PDK1 homolog Ppk21, as multicopy suppressors of the thermosensitive phenotype of ksg1-208 mutant. We found that overexpression of Ppk21 or Cdr2 recovered the defective cell cycle transition of ksg1-208 mutant. In addition, ksg1-208 Δppk21 cells showed more marked defects in cell cycle transition than each single mutant. Moreover, overexpression of Ppk21 failed to recover the thermosensitive phenotype of the ksg1-208 mutant when Cdr2 was lacking. Notably, the ksg1-208 mutation resulted in abnormal subcellular localization and decreased abundance of Cdr2, and Ppk21 deletion exacerbated the decreased abundance of Cdr2 in the ksg1-208 mutant. Intriguingly, expression of a mitotic inducer Cdc25 was significantly decreased in ksg1-208, Δppk21, or Δcdr2 cells, and overexpression of Ppk21 or Cdr2 partially recovered the decreased protein level of Cdc25 in the ksg1-208 mutant. Altogether, our findings indicated that Cdr2 is a novel downstream effector of PDK1 homologs Ksg1 and Ppk21, both of which cooperatively participate in regulating cell cycle progression, and Cdc25 is involved in this process in fission yeast.

Interactions, structural aspects, and evolutionary perspectives of the yeast 'START'-regulatory network

Molecular signal transduction networks which conduct transcription at the G1 to S phase transition of the eukaryotic cell division cycle have been identified in diverse taxa from mammals to baker´s yeast with analogous functional organization. However, regarding some network components, such as the transcriptional regulators STB1 and WHI5, only few orthologs exist which are confined to individual Saccharomycotina species. While Whi5 has been characterized as yeast analog of human Rb protein, in the particular case of Stb1 (Sin three binding protein 1) identification of functional analogs emerges as difficult because to date its exact functionality still remains obscured. By aiming to resolve Stb1´s enigmatic role this Perspectives article especially surveys works covering relations between Cyclin/CDKs, the heteromeric transcription factor complexes SBF (Swi4/Swi6) and MBF (Mbp1/Swi6), as well as additional coregulators (Whi5, Sin3, Rpd3, Nrm1) which are collectively associated with the orderly transcription at 'Start' of the Saccharomyces cerevisiae cell cycle. In this context, interaction capacities of the Sin3-scaffold protein are widely surveyed because its four PAH domains (Paired Amphiphatic Helix) represent a 'recruitment-code' for gene-specific targeting of repressive histone deacetylase activity (Rpd3) via different transcription factors. Here Stb1 plays a role in Sin3´s action on transcription at the G1/S-boundary. Through bioinformatic analyses a potential Sin3-interaction domain (SID) was detected in Stb1, and beyond that, connections within the G1/S-regulatory network are discussed in structural and evolutionary context thereby providing conceptual perspectives.

Cell Length Growth in the Fission Yeast Cell Cycle: Is It (Bi)linear or (Bi)exponential?

Fission yeast is commonly used as a model organism in eukaryotic cell growth studies. To describe the cells’ length growth patterns during the mitotic cycle, different models have been proposed previously as linear, exponential, bilinear and biexponential ones. The task of discriminating among these patterns is still challenging. Here, we have analyzed 298 individual cells altogether, namely from three different steady-state cultures (wild-type, wee1-50 mutant and pom1Δ mutant). We have concluded that in 190 cases (63.8%) the bilinear model was more adequate than either the linear or the exponential ones. These 190 cells were further examined by separately analyzing the linear segments of the best fitted bilinear models. Linear and exponential functions have been fitted to these growth segments to determine whether the previously fitted bilinear functions were really correct. The majority of these growth segments were found to be linear; nonetheless, a significant number of exponential ones were also detected. However, exponential ones occurred mainly in cases of rather short segments (<40 min), where there were not enough data for an accurate model fitting. By contrast, in long enough growth segments (≥40 min), linear patterns highly dominated over exponential ones, verifying that overall growth is probably bilinear.

The biosynthesis of phospholipids is linked to the cell cycle in a model eukaryote

The structural challenges faced by eukaryotic cells through the cell cycle are key for understanding cell viability and proliferation. We tested the hypothesis that the biosynthesis of structural lipids is linked to the cell cycle. If true, this would suggest that the cell's structure is important for progress through and perhaps even control of the cell cycle. Lipidomics (31P NMR and MS), proteomics (Western immunoblotting) and transcriptomics (RT-qPCR) techniques were used to profile the lipid fraction and characterise aspects of its metabolism at seven stages of the cell cycle of the model eukaryote, Desmodesmus quadricauda. We found considerable, transient increases in the abundance of phosphatidylethanolamine during the G1 phase (+35%, ethanolamine phosphate cytidylyltransferase increased 2·5×) and phosphatidylglycerol (+100%, phosphatidylglycerol synthase increased 22×) over the G1/pre-replication phase boundary. The relative abundance of phosphatidylcholine fell by ~35% during the G1. N-Methyl transferases for the conversion of phosphatidylethanolamine into phosphatidylcholine were not found in the de novo transcriptome profile, though a choline phosphate transferase was found, suggesting that the Kennedy pathway is the principal route for the synthesis of PC. The fatty acid profiles of the four most abundant lipids suggested that these lipids were not generally converted between one another. This study shows for the first time that there are considerable changes in the biosynthesis of the three most abundant phospholipid classes in the normal cell cycle of D. quadricauda, by margins large enough to elicit changes to the physical properties of membranes.