Growth during the cell cycle

Quantitative phase imaging based on holography: trends and new perspectives

In 1948, Dennis Gabor proposed the concept of holography, providing a pioneering solution to a quantitative description of the optical wavefront. After 75 years of development, holographic imaging has become a powerful tool for optical wavefront measurement and quantitative phase imaging. The emergence of this technology has given fresh energy to physics, biology, and materials science. Digital holography (DH) possesses the quantitative advantages of wide-field, non-contact, precise, and dynamic measurement capability for complex-waves. DH has unique capabilities for the propagation of optical fields by measuring light scattering with phase information. It offers quantitative visualization of the refractive index and thickness distribution of weak absorption samples, which plays a vital role in the pathophysiology of various diseases and the characterization of various materials. It provides a possibility to bridge the gap between the imaging and scattering disciplines. The propagation of wavefront is described by the complex amplitude. The complex-value in the complex-domain is reconstructed from the intensity-value measurement by camera in the real-domain. Here, we regard the process of holographic recording and reconstruction as a transformation between complex-domain and real-domain, and discuss the mathematics and physical principles of reconstruction. We review the DH in underlying principles, technical approaches, and the breadth of applications. We conclude with emerging challenges and opportunities based on combining holographic imaging with other methodologies that expand the scope and utility of holographic imaging even further. The multidisciplinary nature brings technology and application experts together in label-free cell biology, analytical chemistry, clinical sciences, wavefront sensing, and semiconductor production.

A cell-based model for size control in the multiple fission alga Chlamydomonas reinhardtii

Understanding how population-size homeostasis emerges from stochastic individual cell behaviors remains a challenge in biology.1,2,3,4,5,6,7 The unicellular green alga Chlamydomonas reinhardtii (Chlamydomonas) proliferates using a multiple fission cell cycle, where a prolonged G1 phase is followed by n rounds of alternating division cycles (S/M) to produce 2n daughters. A "Commitment" sizer in mid-G1 phase ensures sufficient cell growth before completing the cell cycle. A mitotic sizer couples mother-cell size to division number (n) such that daughter size distributions are uniform regardless of mother size distributions. Although daughter size distributions were highly robust to altered growth conditions, ∼40% of daughter cells fell outside of the 2-fold range expected from a "perfect" multiple fission sizer.7,8 A simple intuitive power law model with stochastic noise failed to reproduce individual division behaviors of tracked single cells. Through additional iterative modeling, we identified an alternative modified threshold (MT) model, where cells need to cross a threshold greater than 2-fold their median starting size to become division-competent (i.e., Committed), after which their behaviors followed a power law model. The Commitment versus mitotic size threshold uncoupling in the MT model was likely a key pre-adaptation in the evolution of volvocine algal multicellularity. A similar experimental approach was used in size mutants mat3/rbr and dp1 that are, respectively, missing repressor or activator subunits of the retinoblastoma tumor suppressor complex (RBC). Both mutants showed altered relationships between Commitment and mitotic sizer, suggesting that RBC functions to decouple the two sizers.

Scaling of nuclear numbers and their spatial arrangement in skeletal muscle cell size regulation

Many cells display considerable functional plasticity and depend on the regulation of numerous organelles and macromolecules for their maintenance. In large cells, organelles also need to be carefully distributed to supply the cell with essential resources and regulate intracellular activities. Having multiple copies of the largest eukaryotic organelle, the nucleus, epitomizes the importance of scaling gene products to large cytoplasmic volumes in skeletal muscle fibers. Scaling of intracellular constituents within mammalian muscle fibers is, however, poorly understood, but according to the myonuclear domain hypothesis, a single nucleus supports a finite amount of cytoplasm and is thus postulated to act autonomously, causing the nuclear number to be commensurate with fiber volume. In addition, the orderly peripheral distribution of myonuclei is a hallmark of normal cell physiology, as nuclear mispositioning is associated with impaired muscle function. Because underlying structures of complex cell behaviors are commonly formalized by scaling laws and thus emphasize emerging principles of size regulation, the work presented herein offers more of a unified conceptual platform based on principles from physics, chemistry, geometry, and biology to explore cell size-dependent correlations of the largest mammalian cell by means of scaling.

Coupling gene expression dynamics to cell size dynamics and cell cycle events: Exact and approximate solutions of the extended telegraph model

The standard model describing the fluctuations of mRNA numbers in single cells is the telegraph model which includes synthesis and degradation of mRNA, and switching of the gene between active and inactive states. While commonly used, this model does not describe how fluctuations are influenced by the cell cycle phase, cellular growth and division, and other crucial aspects of cellular biology. Here, we derive the analytical time-dependent solution of an extended telegraph model that explicitly considers the doubling of gene copy numbers upon DNA replication, dependence of the mRNA synthesis rate on cellular volume, gene dosage compensation, partitioning of molecules during cell division, cell-cycle duration variability, and cell-size control strategies. Based on the time-dependent solution, we obtain the analytical distributions of transcript numbers for lineage and population measurements in steady-state growth and also find a linear relation between the Fano factor of mRNA fluctuations and cell volume fluctuations. We show that generally the lineage and population distributions in steady-state growth cannot be accurately approximated by the steady-state solution of extrinsic noise models, i.e. a telegraph model with parameters drawn from probability distributions. This is because the mRNA lifetime is often not small enough compared to the cell cycle duration to erase the memory of division and replication. Accurate approximations are possible when this memory is weak, e.g. for genes with bursty expression and for which there is sufficient gene dosage compensation when replication occurs.

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.

A quantitative and spatial analysis of cell cycle regulators during the fission yeast cycle

Across eukaryotes, the increasing level of cyclin-dependent kinase (CDK) activity drives progression through the cell cycle. As most cells divide at specific sizes, information responding to the size of the cell must feed into the regulation of CDK activity. In this study, we use fission yeast to precisely measure how proteins that have been previously identified in genome-wide screens as cell cycle regulators change in their levels with cell cycle progression. We identify the mitotic B-type cyclin Cdc13 and the mitotic inhibitory phosphatase Cdc25 as the only two proteins that change in both whole-cell and nuclear concentration through the cell cycle, making them potential candidates for universal cell size sensors at the onset of mitosis and cell division.

We have carried out a systems-level analysis of the spatial and temporal dynamics of cell cycle regulators in the fission yeast Schizosaccharomyces pombe. In a comprehensive single-cell analysis, we have precisely quantified the levels of 38 proteins previously identified as regulators of the G2 to mitosis transition and of 7 proteins acting at the G1- to S-phase transition. Only 2 of the 38 mitotic regulators exhibit changes in concentration at the whole-cell level: the mitotic B-type cyclin Cdc13, which accumulates continually throughout the cell cycle, and the regulatory phosphatase Cdc25, which exhibits a complex cell cycle pattern. Both proteins show similar patterns of change within the nucleus as in the whole cell but at higher concentrations. In addition, the concentrations of the major fission yeast cyclin-dependent kinase (CDK) Cdc2, the CDK regulator Suc1, and the inhibitory kinase Wee1 also increase in the nucleus, peaking at mitotic onset, but are constant in the whole cell. The significant increase in concentration with size for Cdc13 supports the view that mitotic B-type cyclin accumulation could act as a cell size sensor. We propose a two-step process for the control of mitosis. First, Cdc13 accumulates in a size-dependent manner, which drives increasing CDK activity. Second, from mid-G2, the increasing nuclear accumulation of Cdc25 and the counteracting Wee1 introduce a bistability switch that results in a rapid rise of CDK activity at the end of G2 and thus, brings about an orderly progression into mitosis.

Quantitative Phase Imaging: Recent Advances and Expanding Potential in Biomedicine

Quantitative phase imaging (QPI) is a label-free, wide-field microscopy approach with significant opportunities for biomedical applications. QPI uses the natural phase shift of light as it passes through a transparent object, such as a mammalian cell, to quantify biomass distribution and spatial and temporal changes in biomass. Reported in cell studies more than 60 years ago, ongoing advances in QPI hardware and software are leading to numerous applications in biology, with a dramatic expansion in utility over the past two decades. Today, investigations of cell size, morphology, behavior, cellular viscoelasticity, drug efficacy, biomass accumulation and turnover, and transport mechanics are supporting studies of development, physiology, neural activity, cancer, and additional physiological processes and diseases. Here, we review the field of QPI in biology starting with underlying principles, followed by a discussion of technical approaches currently available or being developed, and end with an examination of the breadth of applications in use or under development. We comment on strengths and shortcomings for the deployment of QPI in key biomedical contexts and conclude with emerging challenges and opportunities based on combining QPI with other methodologies that expand the scope and utility of QPI even further.

Mechanisms of cellular mRNA transcript homeostasis

For most genes, mRNA transcript abundance scales with cell size to ensure a constant concentration. Scaling of mRNA synthesis rates with cell size plays an important role, with regulation of the activity and abundance of RNA polymerase II (Pol II) now emerging as a key point of control. However, there is also considerable evidence for feedback mechanisms that kinetically couple the rates of mRNA synthesis, nuclear export, and degradation to allow cells to compensate for changes in one by adjusting the others. Researchers are beginning to integrate results from these different fields to reveal the mechanisms underlying transcript homeostasis. This will be crucial for moving beyond our current understanding of relative gene expression towards an appreciation of how absolute transcript levels are linked to other aspects of the cellular phenotype.

An updated view on the centrosome as a cell cycle regulator

The centrosome is a multifunctional organelle that is known primarily for its microtubule organising function. Centrosomal defects caused by changes in centrosomal structure or number have been associated with human diseases ranging from congenital defects to cancer. We are only beginning to appreciate how the non-microtubule organising roles of the centrosome are related to these clinical conditions. In this review, we will discuss the historical evidence that led to the proposal that the centrosome participates in cell cycle regulation. We then summarize the body of work that describes the involvement of the mammalian centrosome in triggering cell cycle progression and checkpoint signalling. Then we will highlight work from the fission yeast model organism, revealing the molecular details that explain how the spindle pole body (SPB, the yeast functional equivalent of the centrosome), participates in these cell cycle transitions. Importantly, we will discuss some of the emerging questions from recent discoveries related to the role of the centrosome as a cell cycle regulator.

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.

Variations of intracellular density during the cell cycle arise from tip-growth regulation in fission yeast

Intracellular density impacts the physical nature of the cytoplasm and can globally affect cellular processes, yet density regulation remains poorly understood. Here, using a new quantitative phase imaging method, we determined that dry-mass density in fission yeast is maintained in a narrow distribution and exhibits homeostatic behavior. However, density varied during the cell cycle, decreasing during G2, increasing in mitosis and cytokinesis, and dropping rapidly at cell birth. These density variations were explained by a constant rate of biomass synthesis, coupled to slowdown of volume growth during cell division and rapid expansion post-cytokinesis. Arrest at specific cell-cycle stages exacerbated density changes. Spatially heterogeneous patterns of density suggested links between density regulation, tip growth, and intracellular osmotic pressure. Our results demonstrate that systematic density variations during the cell cycle are predominantly due to modulation of volume expansion, and reveal functional consequences of density gradients and cell-cycle arrests.

Exponential trajectories, cell size fluctuations, and the adder property in bacteria follow from simple chemical dynamics and division control

Experiments on steady-state bacterial cultures have uncovered several quantitative regularities at the system level. These include, first, the exponential growth of cell size with time and the balanced growth of intracellular chemicals between cell birth and division, which are puzzling given the nonlinear and decentralized chemical dynamics in the cell. We model a cell as a set of chemical populations undergoing nonlinear mass action kinetics in a container whose volume is a linear function of the chemical populations. This turns out to be a special class of dynamical systems that generically has attractors in which all populations grow exponentially with time at the same rate. This explains exponential balanced growth of bacterial cells without invoking any regulatory mechanisms and suggests that this could be a robust property of protocells as well. Second, we consider the hypothesis that cells commit themselves to division when a certain internal chemical population reaches a threshold of N molecules. We show that this hypothesis leads to a simple explanation of some of the variability observed across cells in a bacterial culture. In particular, it reproduces the adder property of cell size fluctuations observed recently in E. coli; the observed correlations among interdivision time, birth volume, and added volume in a generation; and the observed scale of the fluctuations (CV ≈ 10-30%) when N is between 10 and 100. Third, upon including a suitable regulatory mechanism that optimizes the growth rate of the cell, the model reproduces the observed bacterial growth laws including the dependence of the growth rate and ribosomal protein fraction on the medium. Thus, the models provide a framework for unifying diverse aspects of bacterial growth physiology under one roof. They also suggest new questions for experimental and theoretical enquiry.

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

Fission yeast cells divide at a similar cell length with little variation about the mean. This is thought to be the result of a control mechanism that senses size and corrects for any deviations by advancing or delaying onset of mitosis. Gene deletions that advance cells into mitosis at a smaller size or delay cells entering mitosis have led to the identification of genes potentially involved in this mechanism. However, the molecular basis of this control is still not understood. In this work, we have screened for genes that when deleted increase the variability in size of dividing cells. The strongest candidate identified in this screen was mga2 The mga2 deletion strain shows a greater variation in cell length at division, with a coefficient of variation (CV) of 15-24%, while the wild-type strain has a CV of 5-8%. Furthermore, unlike wild-type cells, the mga2 deletion cells are unable to correct cell size deviations within one cell cycle. We show that the mga2 gene genetically interacts with nem1 and influences the nuclear membrane and the nuclear-cytoplasmic transport of CDK regulators.

Strongly oversized fission yeast cells lack any size control and tend to grow linearly rather than bilinearly

During the mitotic cycle, the rod-shaped fission yeast cells grow only at their tips. The newly born cells grow first unipolarly at their old end, but later in the cycle, the 'new end take-off' event occurs, resulting in bipolar growth. Photographs were taken of several steady-state and induction synchronous cultures of different cell cycle mutants of fission yeast, generally larger than wild type. Length measurements of many individual cells were performed from birth to division. For all the measured growth patterns, three different functions (linear, bilinear and exponential) were fitted, and the most adequate one was chosen by using specific statistical criteria, considering the altering parameter numbers. Although the growth patterns were heterogeneous in all the cultures studied, we could find some tendencies. In cultures with sufficiently wide size distribution, cells large enough at birth tend to grow linearly, whereas the other cells generally tend to grow bilinearly. We have found that among bilinearly growing cells, the larger they are at birth, the rate change point during their bilinear pattern occurs earlier in the cycle. This shifting near to the beginning of the cycle might finally cause a linear pattern, if the cells are even larger. In all of the steady-state cultures studied, a size control mechanism operates to maintain homeostasis. By contrast, strongly oversized cells of induction synchronous cultures lack any sizer, and their cycle rather behaves like an adder. We could determine the critical cell size for both the G1 and G2 size controls, where these mechanisms become cryptic. TAKE AWAY: Most individual fission yeast cells in steady-state cultures grow bilinearly. In strongly oversized fission yeast cells, linear growth dominates over bilinear. Above birth length thresholds, both the G1 and G2 size controls become cryptic.

Computationally enhanced quantitative phase microscopy reveals autonomous oscillations in mammalian cell growth

The fine balance of growth and division is a fundamental property of the physiology of cells, and one of the least understood. Its study has been thwarted by difficulties in the accurate measurement of cell size and the even greater challenges of measuring growth of a single cell over time. We address these limitations by demonstrating a computationally enhanced methodology for quantitative phase microscopy for adherent cells, using improved image processing algorithms and automated cell-tracking software. Accuracy has been improved more than twofold and this improvement is sufficient to establish the dynamics of cell growth and adherence to simple growth laws. It is also sufficient to reveal unknown features of cell growth, previously unmeasurable. With these methodological and analytical improvements, in several cell lines we document a remarkable oscillation in growth rate, occurring throughout the cell cycle, coupled to cell division or birth yet independent of cell cycle progression. We expect that further exploration with this advanced tool will provide a better understanding of growth rate regulation in mammalian cells.

Mapping metabolic oscillations during cell cycle progression

Proliferating cells must synthesize a wide variety of macromolecules while progressing through the cell cycle, but the coordination between cell cycle progression and cellular metabolism is still poorly understood. To identify metabolic processes that oscillate over the cell cycle, we performed comprehensive, non-targeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) based metabolomics of HeLa cells isolated in the G₁ and SG₂M cell cycle phases, capturing thousands of diverse metabolite ions. When accounting for increased total metabolite abundance due to cell growth throughout the cell cycle, 18% of the observed LC-HRMS peaks were at least twofold different between the stages, consistent with broad metabolic remodeling throughout the cell cycle. While most amino acids, phospholipids, and total ribonucleotides were constant across cell cycle phases, consistent with the view that total macromolecule synthesis does not vary across the cell cycle, certain metabolites were oscillating. For example, ribonucleotides were highly phosphorylated in SG₂M, indicating an increase in energy charge, and several phosphatidylinositols were more abundant in G₁, possibly indicating altered membrane lipid signaling. Within carbohydrate metabolism, pentose phosphates and methylglyoxal metabolites were associated with the cycle. Interestingly, hundreds of yet uncharacterized metabolites similarly oscillated between cell cycle phases, suggesting previously unknown metabolic activities that may be synchronized with cell cycle progression, providing an important resource for future studies.

Gene Transcription as a Limiting Factor in Protein Production and Cell Growth

Cell growth is driven by the synthesis of proteins, genes, and other cellular components. Defining processes that limit biosynthesis rates is fundamental for understanding the determinants of cell physiology. Here, we analyze the consequences of engineering cells to express extremely high levels of mCherry proteins, as a tool to define limiting processes that fail to adapt upon increasing biosynthetic demands. Protein-burdened cells were transcriptionally and phenotypically similar to mutants of the Mediator, a transcription coactivator complex. However, our binding data suggest that the Mediator was not depleted from endogenous promoters. Burdened cells showed an overall increase in the abundance of the majority of endogenous transcripts, except for highly expressed genes. Our results, supported by mathematical modeling, suggest that wild-type cells transcribe highly expressed genes at the maximal possible rate, as defined by the transcription machinery’s physical properties. We discuss the possible cellular benefit of maximal transcription rates to allow a coordinated optimization of cell size and cell growth.

Dissecting Particle Uptake Heterogeneity in a Cell Population Using Bayesian Analysis

Individual cells in a solution display variable uptake of nanomaterials, peptides, and nutrients. Such variability reflects their heterogeneity in endocytic capacity. In a recent work, we have shown that the endocytic capacity of a cell depends on its size and surface density of endocytic components (transporters). We also demonstrated that in MDA-MB-231 breast cancer cells, the cell-surface transporter density (n) may decay with cell radius (r) following the power rule n ∼ r^α, where α ≈ -1. In this work, we investigate how n and r may independently contribute to the endocytic heterogeneity of a cell population. Our analysis indicates that the smaller cells display more heterogeneity because of the higher stochastic variations in n. By contrast, the larger cells display a more uniform uptake, reflecting less-stochastic variations in n. We provide analyses of these dependencies by establishing a stochastic model. Our analysis reveals that the exponent α in the above relationship is not a constant; rather, it is a random variable whose distribution depends on cell size r. Using Bayesian analysis, we characterize the cell-size-dependent distributions of α that accurately capture the particle uptake heterogeneity of MDA-MB-231 cells.

Total mRNA Quantification in Single Cells: Sarcoma Cell Heterogeneity

Single-cell analysis enables detailed molecular characterization of cells in relation to cell type, genotype, cell state, temporal variations, and microenvironment. These studies often include the analysis of individual genes and networks of genes. The total amount of RNA also varies between cells due to important factors, such as cell type, cell size, and cell cycle state. However, there is a lack of simple and sensitive methods to quantify the total amount of RNA, especially mRNA. Here, we developed a method to quantify total mRNA levels in single cells based on global reverse transcription followed by quantitative PCR. Standard curve analyses of diluted RNA and sorted cells showed a wide dynamic range, high reproducibility, and excellent sensitivity. Single-cell analysis of three sarcoma cell lines and human fibroblasts revealed cell type variations, a lognormal distribution of total mRNA levels, and up to an eight-fold difference in total mRNA levels among the cells. The approach can easily be combined with targeted or global gene expression profiling, providing new means to study cell heterogeneity at an individual gene level and at a global level. This method can be used to investigate the biological importance of variations in the total amount of mRNA in healthy as well as pathological conditions.

Cell Size Control in Plants

The genetic control of the characteristic cell sizes of different species and tissues is a long-standing enigma. Plants are convenient for studying this question in a multicellular context, as their cells do not move and are easily tracked and measured from organ initiation in the meristems to subsequent morphogenesis and differentiation. In this article, we discuss cell size control in plants compared with other organisms. As seen from yeast cells to mammalian cells, size homeostasis is maintained cell autonomously in the shoot meristem. In developing organs, vacuolization contributes to cell size heterogeneity and may resolve conflicts between growth control at the cellular and organ levels. Molecular mechanisms for cell size control have implications for how cell size responds to changes in ploidy, which are particularly important in plant development and evolution. We also discuss comparatively the functional consequences of cell size and their potential repercussions at higher scales, including genome evolution.

Synchronized replication of genes encoding the same protein complex in fast-proliferating cells

DNA replication perturbs the dosage balance among genes; at mid-S phase, early-replicating genes have doubled their copies while late-replicating ones have not. Dosage imbalance among genes, especially within members of a protein complex, is toxic to cells. However, the molecular mechanisms that cells use to deal with such imbalance remain not fully understood. Here, we validate at the genomic scale that the dosage between early- and late-replicating genes is imbalanced in HeLa cells. We propose the synchronized replication hypothesis that genes sensitive to stoichiometric relationships will be replicated simultaneously to maintain stoichiometry. In support of this hypothesis, we observe that genes encoding the same protein complex have similar replication timing but mainly in fast-proliferating cells such as embryonic stem cells and cancer cells. We find that the synchronized replication observed in cancer cells, but not in slow-proliferating differentiated cells, is due to convergent evolution during tumorigenesis that restores synchronized replication timing within protein complexes. Taken together, our study reveals that the demand for dosage balance during S phase plays an important role in the optimization of the replication-timing program; this selection is relaxed during differentiation as the cell cycle prolongs and is restored during tumorigenesis as the cell cycle shortens.

Cyclin-dependent kinase-mediated phosphorylation of the exocyst subunit Exo84 in late G1 phase suppresses exocytic secretion and cell growth in yeast

In eukaryotic cells, the growth rate is strictly regulated for proper progression of the cell cycle. In the budding yeast Saccharomyces cerevisiae, it was previously shown that cell growth dramatically slows down when the cells start budding at the G₁/S transition. However, the molecular mechanism for this G₁/S-associated growth arrest is unclear. In this study, using exocytic secretion, cyclin-dependent kinase (CDK) assay, immunoprecipitation, and microscopy, we demonstrate that the exocyst subunit Exo84, which is known to be phosphorylated in mitosis, can also be phosphorylated directly by Cdk1 in the late G₁ phase. Of note, we found that the Cdk1-mediated Exo84 phosphorylation impairs exocytic secretion in the late G₁ phase. Using conditional cdc mutants and phosphodeficient and phosphomimetic exo84 mutants, we further observed that Cdk1-phosphoryated Exo84 inhibits the exocyst complex assembly, exocytic secretion, and cell growth, which may be important for proper execution of the G₁/S-phase transition before commitment to a complete cell cycle. Our results suggest that the direct Cdk1-mediated regulation of the exocyst complex critically contributes to the coordination of cell growth and cell cycle progression.

Measuring Single-Cell Phenotypic Growth Heterogeneity Using a Microfluidic Cell Volume Sensor

An imaging-integrated microfluidic cell volume sensor was used to evaluate the volumetric growth rate of single cells from a Saccharomyces cerevisiae population exhibiting two phenotypic expression states of the PDR5 gene. This gene grants multidrug resistance by transcribing a membrane transporter capable of pumping out cytotoxic compounds from the cell. Utilizing fluorescent markers, single cells were isolated and trapped, then their growth rates were measured in two on-chip environments: rich media and media dosed with the antibiotic cycloheximide. Approximating growth rates to first-order, we assessed the fitness of individual cells and found that those with low PDR5 expression had higher fitness in rich media whereas cells with high PDR5 expression had higher fitness in the presence of the drug. Moreover, the drug dramatically reduced the fitness of cells with low PDR5 expression but had comparatively minimal impact on the fitness of cells with high PDR5 expression. Our experiments show the utility of this imaging-integrated microfluidic cell volume sensor for high-resolution, single-cell analysis, as well as its potential application for studies that characterize and compare the fitness and morphology of individual cells from heterogeneous populations under different growth conditions.

Cell size sensing in animal cells coordinates anabolic growth rates and cell cycle progression to maintain cell size uniformity

Cell size uniformity in healthy tissues suggests that control mechanisms might coordinate cell growth and division. We derived a method to assay whether cellular growth rates depend on cell size, by monitoring how variance in size changes as cells grow. Our data revealed that, twice during the cell cycle, growth rates are selectively increased in small cells and reduced in large cells, ensuring cell size uniformity. This regulation was also observed directly by monitoring nuclear growth in live cells. We also detected cell-size-dependent adjustments of G1 length, which further reduce variability. Combining our assays with chemical/genetic perturbations confirmed that cells employ two strategies, adjusting both cell cycle length and growth rate, to maintain the appropriate size. Additionally, although Rb signaling is not required for these regulatory behaviors, perturbing Cdk4 activity still influences cell size, suggesting that the Cdk4 pathway may play a role in designating the cell’s target size.

Animal cells come in many different sizes. In humans, for example, egg cells are thousands of times larger than sperm cells. Yet cells of any given type are often strikingly similar in size. The cells that line the surface of organs including the skin and kidneys are especially uniform; in fact a loss of size uniformity in certain tumors is a sign of malignancy. What kind of regulation could enable separate cells within a tissue to have the same size?

One possibility is that each type of cell is programmed with a specific target size, and that a cell can sense if it strays from its target and take steps to compensate. Animal cells sensing their own size was first reported in the 1960s, and now Ginzberg et al. confirm that human cells grown in the laboratory do indeed monitor their size and correct deviations from their target. It turns out that two separate and independent processes help to keep all the cells in the population roughly uniform in size. Firstly, proliferating human cells that are smaller than their target size spend longer growing before they divide. Secondly, at two time points between cell divisions, large cells adjust their growth rate such that they grow slower than small cells.

To show these processes in action, Ginzberg et al. introduced mutations or chemicals that perturbed the length of time between cell divisions or the rate of a cell’s growth. As expected, most of these perturbations had only a modest influence on cell size, due to the cell’s compensatory strategies. Cells that had less time to grow compensated by more quickly making new protein molecules, meaning that they still had enough material to build two new cells by the time they had to divide. In contrast, if a cell’s division was artificially delayed, it reduced its growth rate to stop it from becoming too large. Similarly, cells grown in conditions that slow the production of proteins extended the time between their cell divisions to give them enough time to accumulate the material required for two new cells.

In a recent related study, Liu, Ginzberg et al. identified some of the molecules that a human cell uses to sense its own size. Together these two studies now pave the road to answering a fundamental question in cell biology: what is the elusive cell size sensor? Understanding how cells sense their size will open a window onto how quantitative information is programmed, sensed and communicated within living cells. These findings will shed also new light onto how cells specialize into cell types of different sizes, and what happens when cells lose the ability to sense or regulate their size in diseases like cancers.

Whole lesion histogram analysis of meningiomas derived from ADC values. Correlation with several cellularity parameters, proliferation index KI 67, nucleic content, and membrane permeability

PURPOSE

To analyze several histopathological features and their possible correlations with whole lesion histogram analysis derived from ADC maps in meningioma.

MATERIALS AND METHODS

The retrospective study involved 36 patients with primary meningiomas. For every tumor, the following histogram analysis parameters of apparent diffusion coefficient (ADC) were calculated: ADC_mean, ADC_max, ADC_min, ADC_median, ADC_mode, ADC percentiles: P10, P25, P75, P90, as well kurtosis, skewness, and entropy. All measures were performed by two radiologists. Proliferation index KI 67, minimal, maximal and mean cell count, total nucleic area, and expression of water channel aquaporin 4 (AQP4) were estimated. Spearman's correlation coefficient was used to analyze associations between investigated parameters.

RESULTS

A perfect interobserver agreement for all ADC values (0.84-0.97) was identified. All ADC values correlated inversely with tumor cellularity with the strongest correlation between P10, P25 and mean cell count (-0.558). KI 67 correlated inversely with all ADC values except ADC_min. ADC parameters did not correlate with total nucleic area. All ADC values correlated statistically significant with expression of AQP4.

CONCLUSIONS

ADC histogram analysis is a valid method with an excellent interobserver agreement. Cellularity parameters and proliferation potential are associated with different ADC values. Membrane permeability may play a greater role for water diffusion than cell count and proliferation activity.

The Role for Myc in Coordinating Glycolysis, Oxidative Phosphorylation, Glutaminolysis, and Fatty Acid Metabolism in Normal and Neoplastic Tissues

That cancer cells show patterns of metabolism different from normal cells has been known for over 50 years. Yet, it is only in the past decade or so that an appreciation of the benefits of these changes has begun to emerge. Altered cancer cell metabolism was initially attributed to defective mitochondria. However, we now realize that most cancers do not have mitochondrial mutations and that normal cells can transiently adopt cancer-like metabolism during periods of rapid proliferation. Indeed, an encompassing, albeit somewhat simplified, conceptual framework to explain both normal and cancer cell metabolism rests on several simple premises. First, the metabolic pathways used by cancer cells and their normal counterparts are the same. Second, normal quiescent cells use their metabolic pathways and the energy they generate largely to maintain cellular health and organelle turnover and, in some cases, to provide secreted products necessary for the survival of the intact organism. By contrast, undifferentiated cancer cells minimize the latter functions and devote their energy to producing the anabolic substrates necessary to maintain high rates of unremitting cellular proliferation. Third, as a result of the uncontrolled proliferation of cancer cells, a larger fraction of the metabolic intermediates normally used by quiescent cells purely as a source of energy are instead channeled into competing proliferation-focused and energy-consuming anabolic pathways. Fourth, cancer cell clones with the most plastic and rapidly adaptable metabolism will eventually outcompete their less well-adapted brethren during tumor progression and evolution. This attribute becomes increasingly important as tumors grow and as their individual cells compete in a constantly changing and inimical environment marked by nutrient, oxygen, and growth factor deficits. Here, we review some of the metabolic pathways whose importance has gained center stage for tumor growth, particularly those under the control of the c-Myc (Myc) oncoprotein. We discuss how these pathways differ functionally between quiescent and proliferating normal cells, how they are kidnapped and corrupted during the course of transformation, and consider potential therapeutic strategies that take advantage of common features of neoplastic and metabolic disorders.

Cell Size Control via an Unstable Accumulating Activator and the Phenomenon of Excess Mitotic Delay

Unstable Accumulating Activator models for cellular size control propose an activator that accumulates in a size-dependent manner and triggers cell cycle progression once it has reached a certain threshold. Having a short half life makes such an activator responsive to changes in cell size and makes specific predictions for how cells respond to perturbation. In particular, it explains the curious phenomenon of excess mitotic delay. Excess mitotic delay, first observed in Tetrahymena in the '50s, is a phenomenon in which a pulse of protein synthesis inhibition causes a delay in mitotic entry that is longer than the pulse and that gets longer the later in the cell cycle the pulse is delivered. The interpretation of this phenomenon championed by Zeuthen and Mitchison in the '60s and '70s is that an unstable activator of mitosis is degraded during the pulse and has to be resynthesized to a threshold level to trigger mitosis; small cells have more time to resynthesize the activator before mitosis and so suffer less excess delay, whereas, large cells have less time thus suffer greater excess delay. Fifty years later, with our detailed understanding of cell cycle biochemistry, we can identify and test candidate Unstable Accumulating Activators. Here I review the field and further develop this concept.

Drug-Free Approach To Study the Unusual Cell Cycle of Giardia intestinalis

Giardia intestinalis is a protozoan parasite that causes giardiasis, a form of severe and infectious diarrhea. Despite the importance of the cell cycle in the control of proliferation and differentiation during a giardia infection, it has been difficult to study this process due to the absence of a synchronization procedure that would not induce cellular damage resulting in artifacts. We utilized counterflow centrifugal elutriation (CCE), a size-based separation technique, to successfully obtain fractions of giardia cultures enriched in G₁, S, and G₂. Unlike drug-induced synchronization of giardia cultures, CCE did not induce double-stranded DNA damage or endoreplication. We observed increases in the appearance and size of the median body in the cells from elutriation fractions corresponding to the progression of the cell cycle from early G₁ to late G₂. Consequently, CCE could be used to examine the dynamics of the median body and other structures and organelles in the giardia cell cycle. For the cell cycle gene expression studies, the actin-related gene was identified by the program geNorm as the most suitable normalizer for reverse transcription-quantitative PCR (RT-qPCR) analysis of the CCE samples. Ten of 11 suspected cell cycle-regulated genes in the CCE fractions have expression profiles in giardia that resemble those of higher eukaryotes. However, the RNA levels of these genes during the cell cycle differ less than 4-fold to 5-fold, which might indicate that large changes in gene expression are not required by giardia to regulate the cell cycle. IMPORTANCE Giardias are among the most commonly reported intestinal protozoa in the world, with infections seen in humans and over 40 species of animals. The life cycle of giardia alternates between the motile trophozoite and the infectious cyst. The regulation of the cell cycle controls the proliferation of giardia trophozoites during an active infection and contains the restriction point for the differentiation of trophozoite to cyst. Here, we developed counterflow centrifugal elutriation as a drug-free method to obtain fractions of giardia cultures enriched in cells from the G₁, S, and G₂ stages of the cell cycle. Analysis of these fractions showed that the cells do not show side effects associated with the drugs used for synchronization of giardia cultures. Therefore, counterflow centrifugal elutriation would advance studies on key regulatory events during the giardia cell cycle and identify potential drug targets to block giardia proliferation and transmission.

Associations between apparent diffusion coefficient (ADC) and KI 67 in different tumors: a meta-analysis. Part 1: ADCmean

Diffusion weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion in tissues. This diffusion can be quantified by apparent diffusion coefficient (ADC). Some reports indicated that ADC can reflect tumor proliferation potential. The purpose of this meta-analysis was to provide evident data regarding associations between ADC and KI 67 in different tumors. Studies investigating the relationship between ADC and KI 67 in different tumors were identified. MEDLINE library was screened for associations between ADC and KI 67 in different tumors up to April 2017. Overall, 42 studies with 2026 patients were identified. The following data were extracted from the literature: authors, year of publication, number of patients, tumor type, and correlation coefficients. Associations between ADC and KI 67 were analyzed by Spearman's correlation coefficient. The reported Pearson correlation coefficients in some studies were converted into Spearman correlation coefficients. The pooled correlation coefficient between ADC_mean and KI 67 for all included tumors was ρ = -0.44. Furthermore, correlation coefficient for every tumor entity was calculated. The calculated correlation coefficients were as follows: ovarian cancer: ρ = -0.62, urothelial carcinomas: ρ = -0.56, cerebral lymphoma: ρ = -0.55, neuroendocrine tumors: ρ = -0.52, glioma: ρ = -0.51, lung cancer: ρ = -0.50, prostatic cancer: ρ = -0.43, rectal cancer: ρ = -0.42, pituitary adenoma:ρ = -0.44, meningioma, ρ = -0.43, hepatocellular carcinoma: ρ = -0.37, breast cancer: ρ = -0.22.

cgCorrect: a method to correct for confounding cell-cell variation due to cell growth in single-cell transcriptomics

Accessing gene expression at a single-cell level has unraveled often large heterogeneity among seemingly homogeneous cells, which remains obscured when using traditional population-based approaches. The computational analysis of single-cell transcriptomics data, however, still imposes unresolved challenges with respect to normalization, visualization and modeling the data. One such issue is differences in cell size, which introduce additional variability into the data and for which appropriate normalization techniques are needed. Otherwise, these differences in cell size may obscure genuine heterogeneities among cell populations and lead to overdispersed steady-state distributions of mRNA transcript numbers. We present cgCorrect, a statistical framework to correct for differences in cell size that are due to cell growth in single-cell transcriptomics data. We derive the probability for the cell-growth-corrected mRNA transcript number given the measured, cell size-dependent mRNA transcript number, based on the assumption that the average number of transcripts in a cell increases proportionally to the cell's volume during the cell cycle. cgCorrect can be used for both data normalization and to analyze the steady-state distributions used to infer the gene expression mechanism. We demonstrate its applicability on both simulated data and single-cell quantitative real-time polymerase chain reaction (PCR) data from mouse blood stem and progenitor cells (and to quantitative single-cell RNA-sequencing data obtained from mouse embryonic stem cells). We show that correcting for differences in cell size affects the interpretation of the data obtained by typically performed computational analysis.

Genome-wide screen for cell growth regulators in fission yeast

Cellular growth control is important for all living organisms, but experimental investigation into this problem is difficult because of the complex range of growth regulatory mechanisms. Here, we have used the fission yeast Schizosaccharomyces pombe to identify potential master regulators of growth. At the restrictive temperature, the S. pombe pat1^ts mei4Δ strain enters the meiotic developmental program, but arrests in meiotic G2 phase as mei4⁺ is essential for meiotic progression. These cells do not grow, even in an abundance of nutrients. To identify regulators of growth that can reverse this growth arrest, we introduced an ORFeome plasmid library into the pat1^tsmei4Δ strain. Overexpression of eight genes promoted cell growth; two of these were core RNA polymerase subunits, and one was sck2⁺ , an S6 kinase thought to contribute to TORC1 signalling. Sck2 had the greatest effect on cell growth, and we also show that it significantly increases the cellular transcription rate. These findings indicate, for the first time, that global transcriptional control mediated through S6 kinase signalling is central to cellular growth control.

Flagellar Synchronization Is a Simple Alternative to Cell Cycle Synchronization for Ciliary and Flagellar Studies

Cilia and flagella are highly conserved antenna-like organelles that found in nearly all mammalian cell types. They perform sensory and motile functions contributing to numerous physiological and developmental processes. Defects in their assembly and function are implicated in a wide range of human diseases ranging from retinal degeneration to cancer. Chlamydomonas reinhardtii is an algal model system for studying mammalian cilium formation and function. Here, we report a simple synchronization method that allows detection of small changes in ciliary length by minimizing variability in the population. We find that this method alters the key relationship between cell size and the amount of protein accumulated for flagellar growth. This provides a rapid alternative to traditional methods of cell synchronization for uncovering novel regulators of cilia.

The unicellular green alga Chlamydomonas reinhardtii is an ideal model organism for studies of ciliary function and assembly. In assays for biological and biochemical effects of various factors on flagellar structure and function, synchronous culture is advantageous for minimizing variability. Here, we have characterized a method in which 100% synchronization is achieved with respect to flagellar length but not with respect to the cell cycle. The method requires inducing flagellar regeneration by amputation of the entire cell population and limiting regeneration time. This results in a maximally homogeneous distribution of flagellar lengths at 3 h postamputation. We found that time-limiting new protein synthesis during flagellar synchronization limits variability in the unassembled pool of limiting flagellar protein and variability in flagellar length without affecting the range of cell volumes. We also found that long- and short-flagella mutants that regenerate normally require longer and shorter synchronization times, respectively. By minimizing flagellar length variability using a simple method requiring only hours and no changes in media, flagellar synchronization facilitates the detection of small changes in flagellar length resulting from both chemical and genetic perturbations in Chlamydomonas. This method increases our ability to probe the basic biology of ciliary size regulation and related disease etiologies.

IMPORTANCE Cilia and flagella are highly conserved antenna-like organelles that found in nearly all mammalian cell types. They perform sensory and motile functions contributing to numerous physiological and developmental processes. Defects in their assembly and function are implicated in a wide range of human diseases ranging from retinal degeneration to cancer. Chlamydomonas reinhardtii is an algal model system for studying mammalian cilium formation and function. Here, we report a simple synchronization method that allows detection of small changes in ciliary length by minimizing variability in the population. We find that this method alters the key relationship between cell size and the amount of protein accumulated for flagellar growth. This provides a rapid alternative to traditional methods of cell synchronization for uncovering novel regulators of cilia.

The prescriptions from Shenghui soup enhanced neurite growth and GAP-43 expression level in PC12 cells

Background

Shenghui soup is a traditional Chinese herbal medicine used in clinic for the treatment of forgetfulness. In order to understanding the prescription principle, the effects of “tonifying qi and strengthening spleen” group (TQSS) including Poria cocos (Schw.) Wolf. and Panax ginseng C.A.Mey and “eliminating phlegm and strengthening intelligence” group (EPSI) composed of Polygala tenuifolia Willd., Acorus calamus L. and Sinapis alba L from the herb complex on neurite growth in PC12 cells, two disassembled prescriptions derived from Shenghui soup and their molecular mechanisms were investigated.

Methods

Firstly, CCK-8 kit was used to detect the impact of the two prescriptions on PC12 cell viability; and Flow cytometry was performed to measure the cell apoptosis when PC12 cells were treated with these drugs. Secondly, the effect of the two prescriptions on the differentiation of PC12 cells was observed. Finally, the mRNA and protein expression levels of GAP-43 were analyzed by RT-PCR and western blot, respectively.

Results

“Tonifying qi and strengthening spleen” prescription decreased cell viability in a dose-dependent manner, but had no significant effect on cell apoptosis. Meanwhile, it could improve neurite growth and elevate the mRNA and protein expression level of GAP-43. “Eliminating phlegm and strengthening intelligence” prescription also exerted the similar effects on cell viability and apoptosis. Furthermore, it could also enhance cell neurite growth, with a higher expression level of GAP-43 mRNA and protein.

Conclusion

“Tonifying qi and strengthening spleen” and “eliminating phlegm and strengthening intelligence” prescriptions from Shenghui soup have a positive effect on neurite growth. Their effects are related to the up-regulating expression of GAP-43.

Electronic supplementary material

The online version of this article (doi:10.1186/s12906-016-1339-y) contains supplementary material, which is available to authorized users.

Sizing up to divide: mitotic cell-size control in fission yeast

Schizosaccharomyces pombe is a good model to study cell-size control. These cells integrate size information into cell cycle controls at both the G1/S and G2/M transitions, although the primary control operates at the entry into mitosis. At G2/M there is both a size threshold, demonstrated by the fact that cells divide when they reach 14 μm in length, and also correction around this threshold, evident from the narrow distribution of sizes within a population. This latter property is referred to as size homeostasis. It has been argued that a population of cells accumulating mass in a linear fashion will have size homeostasis in the absence of size control, if cycle time is controlled by a fixed timer. Because fission yeast cells do not grow in a simple linear fashion, they require a size-sensing mechanism. However, current models do not fully describe all aspects of this control, especially the coordination of cell size with ploidy.

Elutriation for Cell Cycle Synchronization in Fission Yeast

Cell synchronization is a powerful technique for studying the eukaryotic cell cycle events precisely. The fission yeast is a rod-shaped cell whose growth is coordinated with the cell cycle. Monitoring the cellular growth of fission yeast is a relatively simple way to measure the cell cycle stage of a cell. Here, we describe a detailed method of unperturbed cell synchronization, named centrifugal elutriation, for fission yeast.

Cell-Size Control

Cells of a given type maintain a characteristic cell size to function efficiently in their ecological or organismal context. They achieve this through the regulation of growth rates or by actively sensing size and coupling this signal to cell division. We focus this review on potential size-sensing mechanisms, including geometric, external cue, and titration mechanisms. Mechanisms that titrate proteins against DNA are of particular interest because they are consistent with the robust correlation of DNA content and cell size. We review the literature, which suggests that titration mechanisms may underlie cell-size sensing in Xenopus embryos, budding yeast, and Escherichia coli, whereas alternative mechanisms may function in fission yeast.

Resonant microchannel volume and mass measurements show that suspended cells swell during mitosis

Suspended cells transiently increase their volume during mitosis because of ion exchange through the plasma membrane.

Osmotic regulation of intracellular water during mitosis is poorly understood because methods for monitoring relevant cellular physical properties with sufficient precision have been limited. Here we use a suspended microchannel resonator to monitor the volume and density of single cells in suspension with a precision of 1% and 0.03%, respectively. We find that for transformed murine lymphocytic leukemia and mouse pro–B cell lymphoid cell lines, mitotic cells reversibly increase their volume by more than 10% and decrease their density by 0.4% over a 20-min period. This response is correlated with the mitotic cell cycle but is not coupled to nuclear osmolytes released by nuclear envelope breakdown, chromatin condensation, or cytokinesis and does not result from endocytosis of the surrounding fluid. Inhibiting Na-H exchange eliminates the response. Although mitotic rounding of adherent cells is necessary for proper cell division, our observations that suspended cells undergo reversible swelling during mitosis suggest that regulation of intracellular water may be a more general component of mitosis than previously appreciated.

Cell Proliferation and Apoptosis in ADPKD

Increased tubular epithelial cell proliferation with fluid secretion is a key hallmark of autosomal dominant polycystic kidney disease (ADPKD). With disruption of either PKD1 or PKD2, the main causative genes of ADPKD, intracellular calcium homeostasis and cAMP accumulation are disrupted, which in turn leads to altered signaling in the pathways that regulate cell proliferation. These dysregulations finally stimulate the development of fluid-filled cysts originating from abnormally proliferating renal tubular cells. In addition, dysregulated apoptosis is observed in dilated cystic tubules. An imbalance between cell proliferation and apoptosis seems to contribute to cyst growth and renal tissue remodeling in ADPKD. In this section, the mechanisms through which cell proliferation and apoptosis are involved in disease progression, and further, how those signaling pathways impinge on each other in ADPKD will be discussed.

The Biosynthetic Basis of Cell Size Control

Cell size is an important physiological trait that sets the scale of all biosynthetic processes. Although physiological studies have revealed that cells actively regulate their size, the molecular mechanisms underlying this regulation have remained unclear. Here we review recent progress in identifying the molecular mechanisms of cell size control. We focus on budding yeast, where cell growth dilutes a cell cycle inhibitor to couple growth and division. We discuss a new model for size control based on the titration of activator and inhibitor molecules whose synthesis rates are differentially dependent on cell size.

Active Control of Cell Size Generates Spatial Detail during Plant Organogenesis

How cells regulate their dimensions is a long-standing question [1, 2]. In fission and budding yeast, cell-cycle progression depends on cell size, although it is still unclear how size is assessed [3, 4, 5]. In animals, it has been suggested that cell size is modulated primarily by the balance of external signals controlling growth and the cell cycle [1], although there is evidence of cell-autonomous control in cell cultures [6, 7, 8, 9]. Regardless of whether regulation is external or cell autonomous, the role of cell-size control in the development of multicellular organisms remains unclear. Plants are a convenient system to study this question: the shoot meristem, which continuously provides new cells to form new organs, maintains a population of actively dividing and characteristically small cells for extended periods [10]. Here, we used live imaging and quantitative, 4D image analysis to measure the sources of cell-size variability in the meristem and then used these measurements in computer simulations to show that the uniform cell sizes seen in the meristem likely require coordinated control of cell growth and cell cycle in individual cells. A genetically induced transient increase in cell size was quickly corrected by more frequent cell division, showing that the cell cycle was adjusted to maintain cell-size homeostasis. Genetically altered cell sizes had little effect on tissue growth but perturbed the establishment of organ boundaries and the emergence of organ primordia. We conclude that meristem cells actively control their sizes to achieve the resolution required to pattern small-scale structures.

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Cell divisions are unequal and cell growth is heterogeneous in the meristem

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Simulations indicate that growth and cell cycle are coordinated in individual cells

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Meristem cell sizes are rapidly corrected after perturbation

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Abnormal cell sizes do not affect growth but perturb organ boundaries and emergence

Molecular control of the Wee1 regulatory pathway by the SAD kinase Cdr2

Cell growth and division are tightly coordinated to maintain cell size constant during successive cell cycles. In Schizosaccharomyces pombe, the SAD kinase Cdr2 regulates the cell size at division and the positioning of the division plane. Cdr2 forms nodes on the medial cortex containing factors that constitute an inhibitory pathway for Wee1. This pathway is regulated by polar gradients of the DYRK kinase Pom1, and involves a direct inhibitor of Wee1, the SAD kinase Cdr1. Cdr2 also interacts with the anillin Mid1, which defines the division plane, and with additional components of the medial cortical nodes, including Blt1, which participate in the mitotic-promoting and cytokinetic functions of nodes. Here, we show that the interaction of Cdr2 with Wee1 and Mid1 requires the UBA domain of Cdr2, which is necessary for its kinase activity. In contrast, Cdr1 associates with the C-terminus of Cdr2, which is composed of basic and KA-1 lipid-binding domains. Mid1 also interacts with the C-terminus of Cdr2 and might bridge the N- and C-terminal domains, whereas Blt1 associates with the central spacer region. We propose that the association of Cdr2 effectors with different domains might constrain Cdr1 and Wee1 spatially to promote Wee1 inhibition upon Cdr2 kinase activation.

Bistability, oscillations, and traveling waves in frog egg extracts

Mathematical modeling is a powerful tool for unraveling the complexities of the molecular regulatory networks underlying all aspects of cell physiology. To support this claim, we review our experiences modeling the cyclin-dependent kinase (CDK) network that controls events of the eukaryotic cell cycle. The model was derived from classic experiments on the biochemistry and molecular genetics of CDKs and their partner proteins. Because the dynamical properties of CDK activity depend in large part on positive and negative feedback loops in the regulatory network, it is difficult to predict its behavior by intuitive reasoning alone. Mathematical modeling is the correct tool for reliably determining the properties of the network in comparison with observed properties of dividing cells and for predicting the behavior of the control system under novel conditions. In this review, we describe six unexpected predictions of our 1993 model of the CDK control system in frog egg extracts and the remarkable experiments, performed much later, that verified all six predictions. The dynamical properties of the CDK network are consequences of feedback signals and ultrasensitive responses of regulatory proteins to CDK activity, and we describe the experimental evidence for the predicted ultrasensitivity. This case study illustrates the novel insights that mathematical modeling, analysis, and simulation can provide cell physiologists, and it points the way to a new "dynamical perspective" on molecular cell biology.

A phyletic perspective on cell growth

Commonalities, as well as lineage-specific differences among bacteria, fungi, plants, and animals, are reviewed in the context of (1) the coordination of cell growth, (2) the flow of mass and energy affecting the physiological status of cells, (3) cytoskeletal dynamics during cell division, and (4) the coordination of cell size in multicellular organs and organisms. A comparative approach reveals that similar mechanisms are used to gauge and regulate cell size and proliferation, and shows that these mechanisms share similar modules to measure cell size, cycle status, competence, and number, as well as ploidy levels, nutrient availability, and other variables affecting cell growth. However, this approach also reveals that these modules often use nonhomologous subsystems when viewed at modular or genomic levels; that is, different lineages have evolved functionally analogous, but not genomically homologous, ways of either sensing or regulating cell size and growth, in much the same way that multicellularity has evolved in different lineages using analogous developmental modules.

A genomic Multiprocess survey of machineries that control and link cell shape, microtubule organization, and cell-cycle progression

Understanding cells as integrated systems requires that we systematically decipher how single genes affect multiple biological processes and how processes are functionally linked. Here, we used multiprocess phenotypic profiling, combining high-resolution 3D confocal microscopy and multiparametric image analysis, to simultaneously survey the fission yeast genome with respect to three key cellular processes: cell shape, microtubule organization, and cell-cycle progression. We identify, validate, and functionally annotate 262 genes controlling specific aspects of those processes. Of these, 62% had not been linked to these processes before and 35% are implicated in multiple processes. Importantly, we identify a conserved role for DNA-damage responses in controlling microtubule stability. In addition, we investigate how the processes are functionally linked. We show unexpectedly that disruption of cell-cycle progression does not necessarily affect cell size control and that distinct aspects of cell shape regulate microtubules and vice versa, identifying important systems-level links across these processes.

Lazy Updating of hubs can enable more realistic models by speeding up stochastic simulations

To respect the nature of discrete parts in a system, stochastic simulation algorithms (SSAs) must update for each action (i) all part counts and (ii) each action's probability of occurring next and its timing. This makes it expensive to simulate biological networks with well-connected "hubs" such as ATP that affect many actions. Temperature and volume also affect many actions and may be changed significantly in small steps by the network itself during fever and cell growth, respectively. Such trends matter for evolutionary questions, as cell volume determines doubling times and fever may affect survival, both key traits for biological evolution. Yet simulations often ignore such trends and assume constant environments to avoid many costly probability updates. Such computational convenience precludes analyses of important aspects of evolution. Here we present "Lazy Updating," an add-on for SSAs designed to reduce the cost of simulating hubs. When a hub changes, Lazy Updating postpones all probability updates for reactions depending on this hub, until a threshold is crossed. Speedup is substantial if most computing time is spent on such updates. We implemented Lazy Updating for the Sorting Direct Method and it is easily integrated into other SSAs such as Gillespie's Direct Method or the Next Reaction Method. Testing on several toy models and a cellular metabolism model showed >10× faster simulations for its use-cases-with a small loss of accuracy. Thus we see Lazy Updating as a valuable tool for some special but important simulation problems that are difficult to address efficiently otherwise.