Reliable cell cycle commitment in budding yeast is ensured by signal integration

Extending the G1 phase improves the production of lipophilic compounds in yeast by boosting enzyme expression and increasing cell size

Cell phase engineering can significantly impact protein synthesis and cell size, potentially enhancing the production of lipophilic products. This study investigated the impact of G1 phase extension on resource allocation, metabolic functions, and the unfolded protein response (UPR) in yeast, along with the potential for enhancing the production of lipophilic compounds. In brief, the regulation of the G1 phase was achieved by deleting CLN3 (G1 cyclin) in various yeast strains. This modification resulted in a 83% increase in cell volume, a 76.9% increase in dry cell weight, a 82% increase in total protein content, a 41% increase in carotenoid production, and a 159% increase in fatty alcohol production. Transcriptomic analysis revealed significant upregulation of multiple metabolic pathways involved in acetyl-CoA (acetyl coenzyme A) synthesis, ensuring an ample supply of precursors for the synthesis of lipophilic products. Furthermore, we observed improved protein synthesis, attributed to UPR activation during the prolonged G1 phase. These findings not only enhanced our understanding and application of yeast's capacity to synthesize lipophilic compounds in applied biotechnology but also offered unique insights into cellular behavior during the modified G1 phase, particularly regarding the UPR response, for basic research. This study demonstrates the potential of G1 phase intervention to increase the yield of hydrophobic compounds in yeast, providing a promising direction for further research.

A stochastic vs deterministic perspective on the timing of cellular events

Cells are the fundamental units of life, and like all life forms, they change over time. Changes in cell state are driven by molecular processes; of these many are initiated when molecule numbers reach and exceed specific thresholds, a characteristic that can be described as "digital cellular logic". Here we show how molecular and cellular noise profoundly influence the time to cross a critical threshold-the first-passage time-and map out scenarios in which stochastic dynamics result in shorter or longer average first-passage times compared to noise-less dynamics. We illustrate the dependence of the mean first-passage time on noise for a set of exemplar models of gene expression, auto-regulatory feedback control, and enzyme-mediated catalysis. Our theory provides intuitive insight into the origin of these effects and underscores two important insights: (i) deterministic predictions for cellular event timing can be highly inaccurate when molecule numbers are within the range known for many cells; (ii) molecular noise can significantly shift mean first-passage times, particularly within auto-regulatory genetic feedback circuits.

A multilayer microfluidic system for studies of the dynamic responses of cellular proteins to oxygen switches at the single-cell level

Oxygen levels vary in the environment. Oxygen availability has a major effect on almost all organisms, and oxygen is far more than a substrate for energy production. However, less is known about related biological processes under hypoxic conditions and about the adaptations to changing oxygen concentrations. The yeast Saccharomyces cerevisiae can adapt its metabolism for growth under different oxygen concentrations and can grow even under anaerobic conditions. Therefore, we developed a microfluidic device that can generate serial, accurately controlled oxygen concentrations for single-cell studies of multiple yeast strains. This device can construct a broad range of oxygen concentrations, [O2] through on-chip gas-mixing channels from two gases fed to the inlets. Gas diffusion through thin polydimethylsiloxane (PDMS) can lead to the equilibration of [O2] in the medium in the cell culture layer under gas cover regions within 2 min. Here, we established six different and stable [O2] varying between ~0.1 and 20.9% in the corresponding layers of the device designed for multiple parallel single-cell culture of four different yeast strains. Using this device, the dynamic responses of different yeast transcription factors and metabolism-related proteins were studied when the [O2] decreased from 20.9% to serial hypoxic concentrations. We showed that different hypoxic conditions induced varying degrees of transcription factor responses and changes in respiratory metabolism levels. This device can also be used in studies of the aging and physiology of yeast under different oxygen conditions and can provide new insights into the relationship between oxygen and organisms. Integration, innovation and insight: Most living cells are sensitive to the oxygen concentration because they depend on oxygen for survival and proper cellular functions. Here, a composite microfluidic device was designed for yeast single-cell studies at a series of accurately controlled oxygen concentrations. Using this device, we studied the dynamic responses of various transcription factors and proteins to changes in the oxygen concentration. This study is the first to examine protein dynamics and temporal behaviors under different hypoxic conditions at the single yeast cell level, which may provide insights into the processes involved in yeast and even mammalian cells. This device also provides a base model that can be extended to oxygen-related biology and can acquire more information about the complex networks of organisms.

Studying the Human Microbiota: Advances in Understanding the Fundamentals, Origin, and Evolution of Biological Timekeeping

The recently observed circadian oscillations of the intestinal microbiota underscore the profound nature of the human-microbiome relationship and its importance for health. Together with the discovery of circadian clocks in non-photosynthetic gut bacteria and circadian rhythms in anucleated cells, these findings have indicated the possibility that virtually all microorganisms may possess functional biological clocks. However, they have also raised many essential questions concerning the fundamentals of biological timekeeping, its evolution, and its origin. This narrative review provides a comprehensive overview of the recent literature in molecular chronobiology, aiming to bring together the latest evidence on the structure and mechanisms driving microbial biological clocks while pointing to potential applications of this knowledge in medicine. Moreover, it discusses the latest hypotheses regarding the evolution of timing mechanisms and describes the functions of peroxiredoxins in cells and their contribution to the cellular clockwork. The diversity of biological clocks among various human-associated microorganisms and the role of transcriptional and post-translational timekeeping mechanisms are also addressed. Finally, recent evidence on metabolic oscillators and host-microbiome communication is presented.

The linear framework II: using graph theory to analyse the transient regime of Markov processes

The linear framework uses finite, directed graphs with labelled edges to model biomolecular systems. Graph vertices represent chemical species or molecular states, edges represent reactions or transitions and edge labels represent rates that also describe how the system is interacting with its environment. The present paper is a sequel to a recent review of the framework that focussed on how graph-theoretic methods give insight into steady states as rational algebraic functions of the edge labels. Here, we focus on the transient regime for systems that correspond to continuous-time Markov processes. In this case, the graph specifies the infinitesimal generator of the process. We show how the moments of the first-passage time distribution, and related quantities, such as splitting probabilities and conditional first-passage times, can also be expressed as rational algebraic functions of the labels. This capability is timely, as new experimental methods are finally giving access to the transient dynamic regime and revealing the computations and information processing that occur before a steady state is reached. We illustrate the concepts, methods and formulas through examples and show how the results may be used to illuminate previous findings in the literature.

TOR Complex 1: Orchestrating Nutrient Signaling and Cell Cycle Progression

The highly conserved TOR signaling pathway is crucial for coordinating cellular growth with the cell cycle machinery in eukaryotes. One of the two TOR complexes in budding yeast, TORC1, integrates environmental cues and promotes cell growth. While cells grow, they need to copy their chromosomes, segregate them in mitosis, divide all their components during cytokinesis, and finally physically separate mother and daughter cells to start a new cell cycle apart from each other. To maintain cell size homeostasis and chromosome stability, it is crucial that mechanisms that control growth are connected and coordinated with the cell cycle. Successive periods of high and low TORC1 activity would participate in the adequate cell cycle progression. Here, we review the known molecular mechanisms through which TORC1 regulates the cell cycle in the budding yeast Saccharomyces cerevisiae that have been extensively used as a model organism to understand the role of its mammalian ortholog, mTORC1.

When yeast cells change their mind: cell cycle "Start" is reversible under starvation

Eukaryotic cells decide in late G1 phase of the cell cycle whether to commit to another round of division. This point of cell cycle commitment is termed "Restriction Point" in mammals and "Start" in the budding yeast Saccharomyces cerevisiae. At Start, yeast cells integrate multiple signals such as pheromones and nutrients, and will not pass Start if nutrients are lacking. However, how cells respond to nutrient depletion after the Start decision remains poorly understood. Here, we analyze how post-Start cells respond to nutrient depletion, by monitoring Whi5, the cell cycle inhibitor whose export from the nucleus determines Start. Surprisingly, we find that cells that have passed Start can re-import Whi5 into the nucleus. In these cells, the positive feedback loop activating G1/S transcription is interrupted, and the Whi5 repressor re-binds DNA. Cells which re-import Whi5 become again sensitive to mating pheromone, like pre-Start cells, and CDK activation can occur a second time upon replenishment of nutrients. These results demonstrate that upon starvation, the commitment decision at Start can be reversed. We therefore propose that cell cycle commitment in yeast is a multi-step process, similar to what has been suggested for mammalian cells.

What programs the size of animal cells?

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

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.

Cell region fingerprints enable highly precise single-cell tracking and lineage reconstruction

Experimental studies of cell growth, inheritance and their associated processes by microscopy require accurate single-cell observations of sufficient duration to reconstruct the genealogy. However, cell tracking-assigning identical cells on consecutive images to a track-is often challenging, resulting in laborious manual verification. Here, we propose fingerprints to identify problematic assignments rapidly. A fingerprint distance compares the structural information contained in the low frequencies of a Fourier transform to measure the similarity between cells in two consecutive images. We show that fingerprints are broadly applicable across cell types and image modalities, provided the image has sufficient structural information. Our tracker (Trac^X) uses fingerprints to reject unlikely assignments, thereby increasing tracking performance on published and newly generated long-term data sets. For Saccharomyces cerevisiae, we propose a comprehensive model for cell size control at the single-cell and population level centered on the Whi5 regulator, demonstrating how precise tracking can help uncover previously undescribed single-cell biology.

The G1/S repressor WHI5 is expressed at similar levels throughout the cell cycle

Objectives

While it is clear that cells need to grow before committing to division at the G1/S transition of the cell cycle, how cells sense their growth rate or size at the molecular level is unknown. It has been proposed that, in budding yeast, the dilution of the Whi5 G1/S transcriptional repressor as cells grow in G1 is the main driver of G1/S commitment. This model implies that Whi5 synthesis is substantially reduced in G1 phase. Recent work has reported that the concentration of Whi5 is size- and time-independent in G1 cells, challenging the dilution model. These results in turn imply that Whi5 must be synthesized in G1 phase, but the cell cycle dependence of WHI5 mRNA expression has not been examined in live cells.

Results description

To address this question, we monitored single WHI5 mRNA molecules in single live cells using confocal microscopy, and quantified WHI5 mRNA copy number in G1, G1/S, and S/G2/M phase cells. We observed that WHI5 mRNA is found in very similar amount irrespective of cell cycle stage. The constant WHI5 mRNA copy number throughout G1 phase rules out alterations in mRNA abundance as a contributing factor for any putative dilution of Whi5.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-022-06142-9.

Bilateral Feedback in Oscillator Model Is Required to Explain the Coupling Dynamics of Hes1 with the Cell Cycle

Biological processes are governed by the expression of proteins, and for some proteins, their level of expression can fluctuate periodically over time (i.e., they oscillate). Many oscillatory proteins (e.g., cell cycle proteins and those from the HES family of transcription factors) are connected in complex ways, often within large networks. This complexity can be elucidated by developing intuitive mathematical models that describe the underlying critical aspects of the relationships between these processes. Here, we provide a mathematical explanation of a recently discovered biological phenomenon: the phasic position of the gene Hes1’s oscillatory expression at the beginning of the cell cycle of an individual human breast cancer stem cell can have a predictive value on how long that cell will take to complete a cell cycle. We use a two-component model of coupled oscillators to represent Hes1 and the cell cycle in the same cell with minimal assumptions. Inputting only the initial phase angles, we show that this model is capable of predicting the dynamic mitosis to mitosis behaviour of Hes1 and predicting cell cycle length patterns as found in real-world experimental data. Moreover, we discover that bidirectional coupling between Hes1 and the cell cycle is critical within the system for the data to be reproduced and that nonfixed asymmetry in the interactions between the oscillators is required. The phase dynamics we present here capture the complex interplay between Hes1 and the cell cycle, helping to explain nongenetic cell cycle variability, which has critical implications in cancer treatment contexts.

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

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

OUP accepted manuscript

Many questions remain about the interplay between adaptive and neutral processes leading to genome expansion and the evolution of cellular complexity. Genome size appears to be tightly linked to the size of the regulatory repertoire of cells (van Nimwegen E. 2003. Scaling laws in the functional content of genomes. Trends Gen. 19(9):479–484). In the context of gene regulation, we here study the interplay between adaptive and nonadaptive forces on genome and regulatory network in a computational model of cell-cycle adaptation to different environments. Starting from the well-known Caulobacter crescentus network, we report on ten replicate in silico evolution experiments where cells evolve cell-cycle control by adapting to increasingly harsh spatial habitats.

We find adaptive expansion of the regulatory repertoire of cells. Having a large genome is inherently costly, but also allows for improved cell-cycle behavior. Replicates traverse different evolutionary trajectories leading to distinct eco-evolutionary strategies. In four replicates, cells evolve a generalist strategy to cope with a variety of nutrient levels; in two replicates, different specialist cells evolve for specific nutrient levels; in the remaining four replicates, an intermediate strategy evolves. These diverse evolutionary outcomes reveal the role of contingency in a system under strong selective forces.

This study shows that functionality of cells depends on the combination of regulatory network topology and genome organization. For example, the positions of dosage-sensitive genes are exploited to signal to the regulatory network when replication is completed, forming a de novo evolved cell cycle checkpoint. Our results underline the importance of the integration of multiple organizational levels to understand complex gene regulation and the evolution thereof.

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

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

A novel two-layer-integrated microfluidic device for high-throughput yeast proteomic dynamics analysis at the single-cell level

Current microfluidic methods for studying multicell strains (e.g., m-types) with multienvironments (e.g., n-types) require large numbers of inlets/outlets (m*n), a complicated procedure or expensive machinery. Here, we developed a novel two-layer-integrated method to combine different PDMS microchannel layers with different functions into one chip by a PDMS through-hole array, which improved the design of a PDMS-based microfluidic system. Using this method, we succeeded in converting 2 × m × n inlets/outlets into m + n inlets/outlets and reduced the time cost of loading processing (from m × n to m) of the device for studying multicell strains (e.g., m-types) in varied multitemporal environments (i.e., n-types). Using this device, the dynamic behavior of the cell-stress-response proteins was studied when the glucose concentration decreased from 2% to a series of lower concentrations. Our device could also be widely used in high-throughput studies of various stress responses, and the new concept of a multilayer-integrated fabrication method could greatly improve the design of PDMS-based microfluidic systems.

Random Parametric Perturbations of Gene Regulatory Circuit Uncover State Transitions in Cell Cycle

Many biological processes involve precise cellular state transitions controlled by complex gene regulation. Here, we use budding yeast cell cycle as a model system and explore how a gene regulatory circuit encodes essential information of state transitions. We present a generalized random circuit perturbation method for circuits containing heterogeneous regulation types and its usage to analyze both steady and oscillatory states from an ensemble of circuit models with random kinetic parameters. The stable steady states form robust clusters with a circular structure that are associated with cell cycle phases. This circular structure in the clusters is consistent with single-cell RNA sequencing data. The oscillatory states specify the irreversible state transitions along cell cycle progression. Furthermore, we identify possible mechanisms to understand the irreversible state transitions from the steady states. We expect this approach to be robust and generally applicable to unbiasedly predict dynamical transitions of a gene regulatory circuit.

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

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

Critical slowing down and attractive manifold: A mechanism for dynamic robustness in the yeast cell-cycle process

Biological processes that execute complex multiple functions, such as the cell cycle, must ensure the order of sequential events and maintain dynamic robustness against various fluctuations. Here, we examine the mechanisms and fundamental structure that achieve these properties in the cell cycle of the budding yeast Saccharomyces cerevisiae. We show that this process behaves like an excitable system containing three well-decoupled saddle-node bifurcations to execute DNA replication and mitosis events. The yeast cell-cycle regulatory network can be divided into three modules-the G1/S phase, early M phase, and late M phase-wherein both positive feedback loops in each module and interactions among modules play important roles. Specifically, when the cell-cycle process operates near the critical points of the saddle-node bifurcations, a critical slowing down effect takes place. Such interregnum then allows for an attractive manifold and sufficient duration for cell-cycle events, within which to assess the completion of DNA replication and mitosis, e.g., spindle assembly. Moreover, such arrangement ensures that any fluctuation in an early module or event will not transmit to a later module or event. Thus, our results suggest a possible dynamical mechanism of the cell-cycle process to ensure event order and dynamic robustness and give insight into the evolution of eukaryotic cell-cycle processes.

Overcome Competitive Exclusion in Ecosystems

Explaining biodiversity in nature is a fundamental problem in ecology. An outstanding challenge is embodied in the so-called Competitive Exclusion Principle: two species competing for one limiting resource cannot coexist at constant population densities, or more generally, the number of consumer species in steady coexistence cannot exceed that of resources. The fact that competitive exclusion is rarely observed in natural ecosystems has not been fully understood. Here we show that, by forming chasing pairs and chasing triplets among the consumers and resources in the consumption process, the Competitive Exclusion Principle can be naturally violated. The modeling framework developed here is broadly applicable and can be used to explain the biodiversity of many consumer-resource ecosystems and hence deepens our understanding of biodiversity in nature.

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Foraging with only chasing pairs cannot break the Competitive Exclusion Principle (CEP)

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A population dynamics model involving both chasing pairs and triplets can break CEP

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Redundant foraging within the chasing triplets facilitates species coexistence

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The theoretical framework is testable in ecosystems involving pack hunting

Control strategies for the timing of intracellular events

While the timing of intracellular events is essential for many cellular processes, gene expression inside a single cell can exhibit substantial cell-to-cell variability, raising the question of how cells ensure precision in event timing despite such stochasticity. We address this question by analyzing a biologically reasonable model of gene expression in the context of first passage time (FPT), focusing on two experimentally measurable statistics: mean FPT (MFPT) and timing variability (TV). We show that (1) transcriptional burst size (BS) and burst frequency (BF) can minimize the TV; (2) translational BS monotonically reduces the MFPT to a nonzero low bound; (3) the timescale of promoter kinetics can minimize both the MFPT and the TV, depending on the ratio of the on-switching rate over the off-switching rate; and (4) positive feedback regulation of any form can all minimize the TV, whereas negative feedback regulation of transcriptional BF or BS always enhances the TV. These control strategies can have broad implications for diverse cellular processes relying on precise temporal triggering of events.

Cell Cycle Inhibitor Whi5 Records Environmental Information to Coordinate Growth and Division in Yeast

Proliferating cells need to evaluate the environment to determine the optimal timing for cell cycle entry. However, how this is achieved is not well understood. Here, we show that, in budding yeast, the G1 inhibitor Whi5 is a key environmental indicator and plays a crucial role in coordinating cell growth and division. We found that, under a variety of nutrient and stress conditions, Whi5 amount in G1 is proportional to the cell's doubling time in the environment, which in turn influences the timing for the next cell cycle entry. In addition, the coordination between division and environment is further fine-tuned in G1 by environmentally dependent growth rate, G1 cyclin-Cdk1 contribution, and Whi5 threshold at the start. Our results show that the cell stores the past environmental information in Whi5, which works together with other mechanisms sensing the current environmental condition to achieve an adaptive cellular decision making process.

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

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

Competition in the chaperone-client network subordinates cell-cycle entry to growth and stress

The precise coordination of growth and proliferation has a universal prevalence in cell homeostasis. As a prominent property, cell size is modulated by the coordination between these processes in bacterial, yeast, and mammalian cells, but the underlying molecular mechanisms are largely unknown. Here, we show that multifunctional chaperone systems play a concerted and limiting role in cell-cycle entry, specifically driving nuclear accumulation of the G1 Cdk-cyclin complex. Based on these findings, we establish and test a molecular competition model that recapitulates cell-cycle-entry dependence on growth rate. As key predictions at a single-cell level, we show that availability of the Ydj1 chaperone and nuclear accumulation of the G1 cyclin Cln3 are inversely dependent on growth rate and readily respond to changes in protein synthesis and stress conditions that alter protein folding requirements. Thus, chaperone workload would subordinate Start to the biosynthetic machinery and dynamically adjust proliferation to the growth potential of the cell.

Growth strategy of microbes on mixed carbon sources

A classic problem in microbiology is that bacteria display two types of growth behavior when cultured on a mixture of two carbon sources: the two sources are sequentially consumed one after another (diauxie) or they are simultaneously consumed (co-utilization). The search for the molecular mechanism of diauxie led to the discovery of the lac operon. However, questions remain as why microbes would bother to have different strategies of taking up nutrients. Here we show that diauxie versus co-utilization can be understood from the topological features of the metabolic network. A model of optimal allocation of protein resources quantitatively explains why and how the cell makes the choice. In case of co-utilization, the model predicts the percentage of each carbon source in supplying the amino acid pools, which is quantitatively verified by experiments. Our work solves a long-standing puzzle and provides a quantitative framework for the carbon source utilization of microbes.

Bacteria grown on two carbon sources either consume both sources simultaneously or consume them sequentially. Here the authors use a metabolic network model of E. coli to show that optimal protein resource allocation and topological features of the network can explain the choice of carbon acquisition.

A role for Gic1 and Gic2 in Cdc42 polarization at elevated temperature

The conserved Rho-family GTPase Cdc42 is a master regulator of polarity establishment in many cell types. Cdc42 becomes activated and concentrated in a region of the cell cortex, and recruits a variety of effector proteins to that site. In turn, many effectors participate in regulation of cytoskeletal elements in order to remodel the cytoskeleton in a polarized manner. The budding yeast Saccharomyces cerevisiae has served as a tractable model system for studies of cell polarity. In yeast cells, Cdc42 polarization involves a positive feedback loop in which effectors called p21-activated kinases (PAKs) act to recruit a Cdc42-directed guanine nucleotide exchange factor (GEF), generating more GTP-Cdc42 in areas that already have GTP-Cdc42. The GTPase-interacting components (GICs) Gic1 and Gic2 are also Cdc42 effectors, and have been implicated in regulation of the actin and septin cytoskeleton. However, we report that cells lacking GICs are primarily defective in polarizing Cdc42 itself, suggesting that they act upstream as well as downstream of Cdc42 in yeast. Our findings suggest that feedback pathways involving GTPase effectors may be more prevalent than had been appreciated.

Scaling of G1 Duration with Population Doubling Time by a Cyclin in Saccharomyces cerevisiae

The longer cells stay in particular phases of the cell cycle, the longer it will take these cell populations to increase. However, the above qualitative description has very little predictive value, unless it can be codified mathematically. A quantitative relation that defines the population doubling time (Td) as a function of the time eukaryotic cells spend in specific cell cycle phases would be instrumental for estimating rates of cell proliferation and for evaluating introduced perturbations. Here, we show that in human cells, the length of the G1 phase (TG1) regressed on Td with a slope of ≈0.75, while in the yeast Saccharomyces cerevisiae, the slope was slightly smaller, at ≈0.60. On the other hand, cell size was not strongly associated with Td or TG1 in cell cultures that were proliferating at different rates. Furthermore, we show that levels of the yeast G1 cyclin Cln3p were positively associated with rates of cell proliferation over a broad range, at least in part through translational control mediated by a short upstream ORF (uORF) in the CLN3 transcript. Cln3p was also necessary for the proper scaling between TG1 and Td In contrast, yeast lacking the Whi5p transcriptional repressor maintained the scaling between TG1 and Td These data reveal fundamental scaling relationships between the duration of eukaryotic cell cycle phases and rates of cell proliferation, point to the necessary role of Cln3p in these relationships in yeast, and provide a mechanistic basis linking Cln3p levels to proliferation rates and the scaling of G1 with doubling time.

Daughter-cell-specific modulation of nuclear pore complexes controls cell cycle entry during asymmetric division

The acquisition of cellular identity is coupled to changes in the nuclear periphery and nuclear pore complexes (NPCs). Whether and how these changes determine cell fate remains unclear. We have uncovered a mechanism regulating NPC acetylation to direct cell fate after asymmetric division in budding yeast. The lysine deacetylase Hos3 associates specifically with daughter cell NPCs during mitosis to delay cell cycle entry (Start). Hos3-dependent deacetylation of nuclear basket and central channel nucleoporins establishes daughter cell-specific nuclear accumulation of the transcriptional repressor Whi5 during anaphase and perinuclear silencing of the CLN2 gene in the following G1 phase. Hos3-dependent coordination of both events restrains Start in daughter but not in mother cells. We propose that deacetylation modulates transport-dependent and -independent functions of NPCs, leading to differential cell cycle progression in mother and daughter cells. Similar mechanisms might regulate NPC functions in specific cell types and/or cell cycle stages in multicellular organisms.

Details Matter: Noise and Model Structure Set the Relationship between Cell Size and Cell Cycle Timing

Organisms across all domains of life regulate the size of their cells. However, the means by which this is done is poorly understood. We study two abstracted “molecular” models for size regulation: inhibitor dilution and initiator accumulation. We apply the models to two settings: bacteria like Escherichia coli, that grow fully before they set a division plane and divide into two equally sized cells, and cells that form a bud early in the cell division cycle, confine new growth to that bud, and divide at the connection between that bud and the mother cell, like the budding yeast Saccharomyces cerevisiae. In budding cells, delaying cell division until buds reach the same size as their mother leads to very weak size control, with average cell size and standard deviation of cell size increasing over time and saturating up to 100-fold higher than those values for cells that divide when the bud is still substantially smaller than its mother. In budding yeast, both inhibitor dilution or initiator accumulation models are consistent with the observation that the daughters of diploid cells add a constant volume before they divide. This “adder” behavior has also been observed in bacteria. We find that in bacteria an inhibitor dilution model produces adder correlations that are not robust to noise in the timing of DNA replication initiation or in the timing from initiation of DNA replication to cell division (the C+D period). In contrast, in bacteria an initiator accumulation model yields robust adder correlations in the regime where noise in the timing of DNA replication initiation is much greater than noise in the C + D period, as reported previously (Ho and Amir, 2015). In bacteria, division into two equally sized cells does not broaden the size distribution.

The Adder Phenomenon Emerges from Independent Control of Pre- and Post-Start Phases of the Budding Yeast Cell Cycle

Although it has long been clear that cells actively regulate their size, the molecular mechanisms underlying this regulation have remained poorly understood. In budding yeast, cell size primarily modulates the duration of the cell-division cycle by controlling the G1/S transition known as Start. We have recently shown that the rate of progression through Start increases with cell size, because cell growth dilutes the cell-cycle inhibitor Whi5 in G1. Recent phenomenological studies in yeast and bacteria have shown that these cells add an approximately constant volume during each complete cell cycle, independent of their size at birth. These results seem to be in conflict, as the phenomenological studies suggest that cells measure the amount they grow, rather than their size, and that size control acts over the whole cell cycle, rather than specifically in G1. Here, we propose an integrated model that unifies the adder phenomenology with the molecular mechanism of G1/S cell-size control. We use single-cell microscopy to parameterize a full cell-cycle model based on independent control of pre- and post-Start cell-cycle periods. We find that our model predicts the size-independent amount of cell growth during the full cell cycle. This suggests that the adder phenomenon is an emergent property of the independent regulation of pre- and post-Start cell-cycle periods rather than the consequence of an underlying molecular mechanism measuring a fixed amount of growth.

First-passage time approach to controlling noise in the timing of intracellular events

In the noisy cellular environment, gene products are subject to inherent random fluctuations in copy numbers over time. How cells ensure precision in the timing of key intracellular events despite such stochasticity is an intriguing fundamental problem. We formulate event timing as a first-passage time problem, where an event is triggered when the level of a protein crosses a critical threshold for the first time. Analytical calculations are performed for the first-passage time distribution in stochastic models of gene expression. Derivation of these formulas motivates an interesting question: Is there an optimal feedback strategy to regulate the synthesis of a protein to ensure that an event will occur at a precise time, while minimizing deviations or noise about the mean? Counterintuitively, results show that for a stable long-lived protein, the optimal strategy is to express the protein at a constant rate without any feedback regulation, and any form of feedback (positive, negative, or any combination of them) will always amplify noise in event timing. In contrast, a positive feedback mechanism provides the highest precision in timing for an unstable protein. These theoretical results explain recent experimental observations of single-cell lysis times in bacteriophage [Formula: see text] Here, lysis of an infected bacterial cell is orchestrated by the expression and accumulation of a stable [Formula: see text] protein up to a threshold, and precision in timing is achieved via feedforward rather than feedback control. Our results have broad implications for diverse cellular processes that rely on precise temporal triggering of events.

Noise Decomposition Principle in a Coherent Feed-Forward Transcriptional Regulatory Loop

Coherent feed-forward loops exist extensively in realistic biological regulatory systems, and are common signaling motifs. Here, we study the characteristics and the propagation mechanism of the output noise in a coherent feed-forward transcriptional regulatory loop that can be divided into a main road and branch. Using the linear noise approximation, we derive analytical formulae for the total noise of the full loop, the noise of the branch, and the noise of the main road, which are verified by the Gillespie algorithm. Importantly, we find that (i) compared with the branch motif or the main road motif, the full motif can effectively attenuate the output noise level; (ii) there is a transition point of system state such that the noise of the main road is dominated when the underlying system is below this point, whereas the noise of the branch is dominated when the system is beyond the point. The entire analysis reveals the mechanism of how the noise is generated and propagated in a simple yet representative signaling module.

Switch-like Transitions Insulate Network Motifs to Modularize Biological Networks

Cellular decisions are made by complex networks that are difficult to analyze. Although it is common to analyze smaller sub-networks known as network motifs, it is unclear whether this is valid, because these motifs are embedded in complex larger networks. Here, we address the general question of modularity by examining the S. cerevisiae pheromone response. We demonstrate that the feedforward motif controlling the cell-cycle inhibitor Far1 is insulated from cell-cycle dynamics by the positive feedback switch that drives reentry to the cell cycle. Before cells switch on positive feedback, the feedforward motif model predicts the behavior of the larger network. Conversely, after the switch, the feedforward motif is dismantled and has no discernable effect on the cell cycle. When insulation is broken, the feedforward motif no longer predicts network behavior. This work illustrates how, despite the interconnectivity of networks, the activity of motifs can be insulated by switches that generate well-defined cellular states.

Discovery of Covalent Ligands via Noncovalent Docking by Dissecting Covalent Docking Based on a "Steric-Clashes Alleviating Receptor (SCAR)" Strategy

Covalent ligands modulating protein activities/signals have attracted unprecedented attention in recent years, but the insufficient understanding of their advantages in the early days of drug discovery has hindered their rational discovery and development. This also left us inadequate knowledge on the rational design of covalent ligands, e.g., how to balance the contribution from the covalent group and the noncovalent group, respectively. In this work, we dissected the noncovalent docking from covalent docking by creating SCARs (steric-clashes alleviating receptors). We showed that the SCAR method outperformed those specifically developed but more complicated covalent docking protocols. We furthermore provided a "proof-of-principle" example by implementing this method in the first high-throughput screening and discovery of novel covalent inhibitors of S-adenosylmethionine decarboxylase. This work demonstrated that noncovalent groups play a predeterminate role in the design of covalent ligands, and would be of great value in accelerating the discovery and development of covalent ligands.

Whi5 phosphorylation embedded in the G1/S network dynamically controls critical cell size and cell fate

In budding yeast, overcoming of a critical size to enter S phase and the mitosis/mating switch--two central cell fate events--take place in the G1 phase of the cell cycle. Here we present a mathematical model of the basic molecular mechanism controlling the G1/S transition, whose major regulatory feature is multisite phosphorylation of nuclear Whi5. Cln3-Cdk1, whose nuclear amount is proportional to cell size, and then Cln1,2-Cdk1, randomly phosphorylate both decoy and functional Whi5 sites. Full phosphorylation of functional sites releases Whi5 inhibitory activity, activating G1/S transcription. Simulation analysis shows that this mechanism ensures coherent release of Whi5 inhibitory action and accounts for many experimentally observed properties of mitotically growing or conjugating G1 cells. Cell cycle progression and transcriptional analyses of a Whi5 phosphomimetic mutant verify the model prediction that coherent transcription of the G1/S regulon and ensuing G1/S transition requires full phosphorylation of Whi5 functional sites.

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.

A new class of cyclin dependent kinase in Chlamydomonas is required for coupling cell size to cell division

Proliferating cells actively control their size by mechanisms that are poorly understood. The unicellular green alga Chlamydomonas reinhardtii divides by multiple fission, wherein a ‘counting’ mechanism couples mother cell-size to cell division number allowing production of uniform-sized daughters. We identified a sizer protein, CDKG1, that acts through the retinoblastoma (RB) tumor suppressor pathway as a D-cyclin-dependent RB kinase to regulate mitotic counting. Loss of CDKG1 leads to fewer mitotic divisions and large daughters, while mis-expression of CDKG1 causes supernumerous mitotic divisions and small daughters. The concentration of nuclear-localized CDKG1 in pre-mitotic cells is set by mother cell size, and its progressive dilution and degradation with each round of cell division may provide a link between mother cell-size and mitotic division number. Cell-size-dependent accumulation of limiting cell cycle regulators such as CDKG1 is a potentially general mechanism for size control.

DOI:http://dx.doi.org/10.7554/eLife.10767.001

Most cells are programmed to maintain a certain size. This property, known as size control, is achieved by balancing growth and division, such that a cell will only divide after it reaches a certain size. However, and despite years of research, it is largely unknown how cells sense their size (or growth) to be able to divide accordingly. One theory proposes that there is a “sizer” protein inside cells, and that cells measure the abundance of this protein and use it to link cell size to the process of division. However, the existence of such a protein remained unproven.

Li, Liu et al. have now used the cells of the green alga Chlamydomonas to identify a candidate sizer protein. Chlamydomonas cells, like many other algae, can grow to become very large mother cells that then divide one or more times in succession to produce many daughter cells. Larger mother cells undergo more divisions than smaller mother cells in order to produce daughter cells of a correct size. Using a range of genetic and biochemical techniques, Li, Liu et al. identified a protein that is produced in Chlamydomonas cells just before they begin to divide. Larger mother cells contain more of this protein than smaller cells and the protein encourages cells to divide. For example, mutant cells that lack this protein divided too few times, while cells that produce too much of it divided too many times.

The protein, called CDKG1, belongs to a family of proteins that regulate cell division in many organisms. CDKG1 is a kinase – an enzyme that alters the activity of other proteins by adding a phosphate group on to them. In Chlamydomonas, CDKG1 couples cell size to cell division by altering the activity of an important protein called the retinoblastoma-related protein that controls cell division in numerous organisms. This protein is also frequently disrupted in cancers in humans.

These findings shed new light on a molecular pathway for size control. Future work will need to determine how the accumulation of CDKG1 links to the size of a mother cell and how it is inactivated once daughter cells reach the appropriate size.

DOI:http://dx.doi.org/10.7554/eLife.10767.002

Single-Cell Analysis of Growth in Budding Yeast and Bacteria Reveals a Common Size Regulation Strategy

To maintain a constant cell size, dividing cells have to coordinate cell-cycle events with cell growth. This coordination has long been supposed to rely on the existence of size thresholds determining cell-cycle progression [1]. In budding yeast, size is controlled at the G1/S transition [2]. In agreement with this hypothesis, the size at birth influences the time spent in G1: smaller cells have a longer G1 period [3]. Nevertheless, even though cells born smaller have a longer G1, the compensation is imperfect and they still bud at smaller cell sizes. In bacteria, several recent studies have shown that the incremental model of size control, in which size is controlled by addition of a constant volume (in contrast to a size threshold), is able to quantitatively explain the experimental data on four different bacterial species [4-7]. Here, we report on experimental results for the budding yeast Saccharomyces cerevisiae, finding, surprisingly, that cell size control in this organism is very well described by the incremental model, suggesting a common strategy for cell size control with bacteria. Additionally, we argue that for S. cerevisiae the "volume increment" is not added from birth to division, but rather between two budding events.

Dilution of the cell cycle inhibitor Whi5 controls budding-yeast cell size

Cell size fundamentally affects all biosynthetic processes by determining the scale of organelles and influencing surface transport^1,2. Although extensive studies have identified many mutations affecting cell size, the molecular mechanisms underlying size control have remained elusive³. In budding yeast, size control occurs in G1 phase prior to Start, the point of irreversible commitment to cell division^4,5. It was previously thought that activity of the G1 cyclin Cln3 increased with cell size to trigger Start by initiating the inhibition of the transcriptional inhibitor Whi5^6-8. However, while Cln3 concentration does modulate the rate at which cells pass Start, we found that its synthesis increases in proportion to cell size so that its total concentration is nearly constant during pre-Start G1. Rather than increasing Cln3 activity, we identify decreasing Whi5 activity — due to the dilution of Whi5 by cell growth — as a molecular mechanism through which cell size controls proliferation. Whi5 is synthesized in S/G2/M phases of the cell cycle in a largely size-independent manner. This results in smaller daughter cells being born with higher Whi5 concentrations that extend their pre-Start G1 phase. Thus, at its most fundamental level, budding yeast size control results from the differential scaling of Cln3 and Whi5 synthesis rates with cell size. More generally, our work shows that differential size-dependency of protein synthesis can provide an elegant mechanism to coordinate cellular functions with growth.